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10.1101/2020.06.25.20139725
Genome-Wide Association Studies of retinal vessel tortuosity identify 173 novel loci, capturing genes and pathways associated with disease and vascular tissue pathomechanics
BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension. MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX. ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL. ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning. C_LIO_LIGWAS revealed 173 novel loci. C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins. C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending. C_LI What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues. C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension. C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome. C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation. C_LI
genetic and genomic medicine
10.1101/2020.06.25.20139725
GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Diseases
BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension. MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX. ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL. ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning. C_LIO_LIGWAS revealed 173 novel loci. C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins. C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending. C_LI What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues. C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension. C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome. C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation. C_LI
genetic and genomic medicine
10.1101/2020.06.25.20139725
GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Cardiometabolic Diseases
BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension. MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX. ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL. ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning. C_LIO_LIGWAS revealed 173 novel loci. C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins. C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending. C_LI What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues. C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension. C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome. C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation. C_LI
genetic and genomic medicine
10.1101/2020.06.25.20139725
GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Cardiometabolic Diseases
BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension. MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX. ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL. ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning. C_LIO_LIGWAS revealed 173 novel loci. C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins. C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending. C_LI What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues. C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension. C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome. C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation. C_LI
genetic and genomic medicine
10.1101/2020.06.26.20140590
A Metapopulation Network Model for the Spreading of SARS-CoV-2: Case Study for Ireland
We present preliminary results on an all-Ireland network modelling approach to simulate the spreading the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), commonly known as the coronavirus. In the model, nodes correspond to locations or communities that are connected by links indicating travel and commuting between different locations. While this proposed modelling framework can be applied on all levels of spatial granularity and different countries, we consider Ireland as a case study. The network comprises 3440 electoral divisions (EDs) of the Republic of Ireland and 890 superoutput areas (SOAs) for Northern Ireland, which corresponds to local administrative units below the NUTS 3 regions. The local dynamics within each node follows a phenomenological SIRX compartmental model including classes of Susceptibles, Infected, Recovered and Quarantined (X) inspired from Science 368, 742 (2020). For better comparison to empirical data, we extended that model by a class of Deaths. We consider various scenarios including the 5-phase roadmap for Ireland. In addition, as proof of concept, we investigate the effect of dynamic interventions that aim to keep the number of infected below a given threshold. This is achieved by dynamically adjusting containment measures on a national scale, which could also be implemented at a regional (county) or local (ED/SOA) level. We find that - in principle - dynamic interventions are capable to limit the impact of future waves of outbreaks, but on the downside, in the absence of a vaccine, such a strategy can last several years until herd immunity is reached.
epidemiology
10.1101/2020.06.25.20139980
Sex influences the effects of APOE genotype and Alzheimer's diagnosis on neuropathology and memory
Alzheimers disease (AD) is characterised by severe cognitive decline and pathological changes in the brain (brain atrophy, hyperphosphorylation of tau, and deposition of toxic amyloid-beta protein). Females have greater neuropathology (AD biomarkers and brain atrophy rates) and cognitive decline than males, however these effects can depend on diagnosis (amnestic mild cognitive impairment (aMCI) or AD) and APOE genotype (presence of {varepsilon}4 alleles). Using the ADNI database (N=630 females, N=830 males), we analysed the effect of sex, APOE genotype (non-carriers or carriers of APOE{varepsilon}4 alleles), and diagnosis (cognitively normal (CN), early aMCI (EMCI), late aMCI (LMCI), probable AD) on cognition (memory and executive function), hippocampal volume, and AD biomarkers (CSF levels of amyloid beta, tau and ptau). Regardless of APOE genotype, memory scores were higher in CN, EMCI, and LMCI females compared to males but this sex difference was absent in probable AD, which may suggest a delay in the onset of cognitive decline or diagnosis and/or a faster trajectory of cognitive decline in females. We found that, regardless of diagnosis, CSF tau-pathology was disproportionately elevated in female carriers of APOE{varepsilon}4 alleles compared to males. In contrast, male carriers of APOE{varepsilon}4 alleles had reduced levels of CSF amyloid beta compared to females, irrespective of diagnosis. We also detected sex differences in hippocampal volume but the direction was dependent on the method of correction. Altogether results suggest that across diagnosis females show greater memory decline compared to males and APOE genotype affects AD neuropathology differently in males and females which may influence sex differences in incidence and progression of aMCI and AD.
neurology
10.1101/2020.06.25.20139980
Sex influences the effects of APOE genotype and Alzheimer's diagnosis on neuropathology and memory
Alzheimers disease (AD) is characterised by severe cognitive decline and pathological changes in the brain (brain atrophy, hyperphosphorylation of tau, and deposition of toxic amyloid-beta protein). Females have greater neuropathology (AD biomarkers and brain atrophy rates) and cognitive decline than males, however these effects can depend on diagnosis (amnestic mild cognitive impairment (aMCI) or AD) and APOE genotype (presence of {varepsilon}4 alleles). Using the ADNI database (N=630 females, N=830 males), we analysed the effect of sex, APOE genotype (non-carriers or carriers of APOE{varepsilon}4 alleles), and diagnosis (cognitively normal (CN), early aMCI (EMCI), late aMCI (LMCI), probable AD) on cognition (memory and executive function), hippocampal volume, and AD biomarkers (CSF levels of amyloid beta, tau and ptau). Regardless of APOE genotype, memory scores were higher in CN, EMCI, and LMCI females compared to males but this sex difference was absent in probable AD, which may suggest a delay in the onset of cognitive decline or diagnosis and/or a faster trajectory of cognitive decline in females. We found that, regardless of diagnosis, CSF tau-pathology was disproportionately elevated in female carriers of APOE{varepsilon}4 alleles compared to males. In contrast, male carriers of APOE{varepsilon}4 alleles had reduced levels of CSF amyloid beta compared to females, irrespective of diagnosis. We also detected sex differences in hippocampal volume but the direction was dependent on the method of correction. Altogether results suggest that across diagnosis females show greater memory decline compared to males and APOE genotype affects AD neuropathology differently in males and females which may influence sex differences in incidence and progression of aMCI and AD.
neurology
10.1101/2020.06.25.20140186
Maternal obesity and metabolic disorders associate with congenital heart defects in the offspring: a systematic review
Congenital heart defects (CHDs) are the most common congenital malformations and affect neonatal mortality and morbidity. The aetiology of CHDs is complex. Large cohort studies have reported an association between higher risk of CHDs in the offspring and individual maternal metabolic disorders such as obesity, diabetes, hypertension, and preeclampsia, all conditions that can be related to insulin resistance or hyperglycaemia and possibly metabolic syndrome (MetS). The aim of this review is to evaluate the existing evidence on the association between maternal metabolic disorders, defined as obesity, diabetes, hypertension, preeclampsia, dyslipidaemia, and MetS, or combinations thereof and CHDs overall as well as by subtype in the offspring. A literature search of PubMed and Embase databases identified 2,076 studies, 30 qualified for inclusion. All but one study investigated the individual metabolic disorders and their association with CHDs. Some disorders (obesity, gestational diabetes, and hypertension) increased risk of CHDs marginally whereas pre-gestational diabetes and early-onset preeclampsia were strongly associated with CHDs, without consistent differences between CHD subtypes. Future studies of the role of aberrations of the glucose-insulin homeostasis in the common aetiology and mechanisms of metabolic disorders, present during pregnancy, and their association with CHDs as well as subtypes of CHDs are needed.
obstetrics and gynecology
10.1101/2020.06.26.20140780
Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil
COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or vaccines, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 published governmental interventions, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.
health policy
10.1101/2020.06.29.20142323
Group testing: revisiting the ideas
The task of identification of randomly scattered bad items in a fixed set of objects is a frequent one, and there are many ways to deal with it. Group testing (GT) refers to the testing strategy aiming to effectively replace the inspection of single objects by the inspection of groups spanning more than one object. First announced by Dorfman in 1943, the methodology has underwent vigorous development, and though many related research still takes place, the ground ideas remain the same. In the present paper, we revisit two classical GT algorithms: the Dorfmans algorithm and the halving algorithm. Our fresh treatment of the latter and expository comparison of the two is devoted to dissemination of GT ideas which are so important in the current COVID-19 induced pandemic situation.
infectious diseases
10.1101/2020.06.27.20141549
Health care seeking behaviour and financial protection of patients with hypertension: a cross-sectional study in rural West Bengal, India
BackgroundElevated blood pressure or hypertension is responsible for around 10 million annual deaths globally, and people residing in low and middle-income countries are disproportionately affected by it. India is no exception, where low rate of treatment seeking for hypertension coupled with widespread out-of-pocket payments (OOPs) have been a challenge. This study assessed the pattern of health care seeking and financial protection along with the associated factors among hypertensive individuals in a rural district of West Bengal, India. Method and findingsA cross-sectional study was conducted in Birbhum district of the state of West Bengal, India during 2017-2018, where 300 individuals with hypertension were recruited randomly from a pre-defined list of individuals with hypertension in the district. Healthcare seeking along with two instance of financial protection -OOPs and relative expense, were analysed. Findings indicated that, of all hypertensives, 47% were not on treatment, 80% preferred private healthcare, and 91% of them had wide-spread OOPs. Cost of medication being a major share of expenses followed by significant transport cost to access public health care facility. Multivariable logistic regression analysis indicated longer duration of disease and private health care seeking were associated with more incident of OOPs. Results from linear regression modelling (generalized linear model) demonstrated association of co-morbidities with higher relative expenditure. Individuals belonging to poor economic group suffered from a high relative expense, compared to the richest. ConclusionThis study suggested that individuals with hypertension had poor health care seeking, preferred private health care and had suboptimal financial protection. Hypertensives from economically poorer section had higher burden of health expenditure for treatment of hypertension, which indicated gaps in equitable health care for the control of hypertension.
health economics
10.1101/2020.06.28.20142158
A new estimation method for COVID-19 time-varying reproduction number using active cases
We propose a new method to estimate the time-varying effective (or instantaneous) reproduction number of the novel coronavirus disease (COVID-19). The method is based on a discrete-time stochastic augmented compartmental model that describes the virus transmission. A two-stage estimation method, which combines the Extended Kalman Filter (EKF) to estimate the reported state variables (active and removed cases) and a low pass filter based on a rational transfer function to remove short term fluctuations of the reported cases, is used with case uncertainties that are assumed to follow a Gaussian distribution. Our method does not require information regarding serial intervals, which makes the estimation procedure simpler without reducing the quality of the estimate. We show that the proposed method is comparable to common approaches, e.g., age-structured and new cases based sequential Bayesian models. We also apply it to COVID-19 cases in the Scandinavian countries: Denmark, Sweden, and Norway, where we see a delay of about four days in predicting the epidemic peak.
epidemiology
10.1101/2020.06.29.20141283
Inexpensive multi-patient respiratory monitoring system for helmet ventilation during COVID-19 pandemic
BackgroundHelmet continuous positive applied pressure is a form of non-invasive ventilation (NIV) that has been used to provide respiratory support to COVID-19 patients. Helmet NIV is low-cost, readily available, provides viral filters between the patient and clinician, and may reduce the need for invasive ventilation. Its widespread adoption has been limited, however, by the lack of a respiratory monitoring system needed to address known safety vulnerabilities and to monitor patients. To address these safety and clinical needs, we developed an inexpensive respiratory monitoring system based on readily available components suitable for local manufacture. Open-source design and manufacturing documents are provided. The monitoring system comprises flow, pressure and CO2 sensors on the expiratory path of the helmet circuit and a central remote station to monitor up to 20 patients. MethodsThe system is validated in bench tests, in human-subject tests on healthy volunteers, and in experiments that compare respiratory features obtained at the expiratory path to simultaneous ground-truth measurements from proximal sensors. FindingsMeasurements of flow and pressure at the expiratory path are shown to deviate at high flow rates, and the tidal volumes reported via the expiratory path are systematically underestimated. InterpretationHelmet monitoring systems exhibit high-flow rate, non-linear effects from flow and helmet dynamics. These deviations are found to be within a reasonable margin and should, in principle, allow for calibration, correction and deployment of clinically accurate derived quantities. FundingThis project is supported by Princeton University, and by National Science Foundation grants OAC-1836650, PHY-2031509 and IOS-1845137. The funding sources provided no role in the design or execution of the the work or in the preparation of the manuscript. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSRespiratory monitoring is standard when treating intubated patients undergoing invasive mechanical ventilation. In contrast, respiratory monitoring systems have not been developed for helmet non-invasive ventilation (NIV). Previous measurements of CO2 concentration in the helmet versus flow rate have been published and serve as the primary guide for setting the minimum flow rate for patient treatment of helmet NIV. Similar studies have explored optimal PEEP settings for clinical treatment. However, in practice, respiratory profiles are not measured during helmet treatment and more evidence is needed to evaluate whether clinically useful quantities, such as tidal volume, can be accurately measured during helmet NIV, to provide the same level of clincially relevant monitoring that is standard with invasive ventliation. Added value of this studyDue to the widespread need for inexpensive multi-patient respiratory monitoring systems to cope with the COVID-19 pandemic, a helmet NIV monitoring system was developed and validated with bench tests, human-subject tests on healthy volunteers, and in experiments that compare respiratory features obtained at the expiratory path to simultaneous ground-truth measurements from proximal sensors. At high flow rate, the non-linear effects from the flow and helmet dynamics are observed and have a measurable effect on the estimation of tidal volumes and derived quantities. Implications of all the available evidenceHelmet monitoring systems for NIV are in wide-spread use for the treatment of the coronavirus disease 2019. The introduction of respiratory monitoring systems for helmet NIV addresses important safety concerns and opens up the possibility of providing clinically relevant derived quantities to track disease progression. A systematic study of deviations between expiratory path measurements and ground-truth proximal sensors was conducted in bench tests and human-subject tests of health volunteers. The non-linear flow and helmet dynamics effects the accuracy of derived quantities at high flow rates. These deviations are found to be within a reasonable margin and should, in principle, allow for calibration, correction and deployment of clinically accurate derived quantities. An inexpensive implementation of the respiratory monitoring system was achieved to cope with the immense scale of the COVID-19 pandemic. Further steps to improve the quality of care for COVID-19 helmet NIV treatment can be achieved through the additional of respiratory monitoring systems that adjust for high flow-rate deviations in the estimation of tidal volumes and derived quantities.
intensive care and critical care medicine
10.1101/2020.06.29.20142760
Modeling impact and cost-effectiveness of gene drives for malaria elimination in the Democratic Republic of the Congo
BackgroundThe tremendous burden of malaria has led to renewed efforts focusing on malaria elimination in high burden countries and has spurred the development of novel tools such as the use of transgenic mosquitoes to modify or suppress vector populations to interrupt transmission. Gene drives offer a pathway to propagate transgenes and their associated phenotypes to future generations more efficiently than the natural 50% probability and could potentially be applied as a vector control method. This study evaluates the role of suppression gene drives within broader intervention strategies, using the sex-ratio distorting driving-Y gene drive as an example. MethodWe parameterize a spatially explicit, agent-based, mathematical model to capture malaria transmission in eight representative provinces of the Democratic Republic of the Congo, an operationally complex high-burden setting. We explore the potential impact of integrating driving-Y gene drive mosquitoes in malaria elimination strategies that include existing interventions such as insecticide-treated nets and treatment of clinical cases. An economic evaluation was performed to estimate the cost-effectiveness of gene drives, other interventions, and combinations. FindingsReleases of gene drive mosquitoes were capable of eliminating malaria and were the most cost-effective intervention overall, as long as the drive component was highly effective with at least 95% X-shredding, and associated cost of deployment was below 7.17 $int per person per year. InterpretationGenetically-based vector control via suppression gene drive could be a cost-effective supplement to traditional malaria interventions for malaria elimination, but tight constraints on drive effectiveness and cost ceilings may prove to limit its operational feasibility. FundingFederal Ministry for Economic Cooperation and Development via German Academic Exchange Service (DAAD) and the Wellcome Trust.
epidemiology
10.1101/2020.06.29.20142851
Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories
Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.
infectious diseases
10.1101/2020.06.29.20141564
A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine
BackgroundWe perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race. MethodsThe study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and September 2, 2020 at a large academic medical center. ResultsPre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with ICU admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. ConclusionsUnderstanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.
infectious diseases
10.1101/2020.07.01.20144196
Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype Definitions
Phenotyping is an effective way to identify cohorts of patients with particular characteristics within a population. In order to enhance the portability of a phenotype definition across institutions, it is often defined abstractly, with implementers expected to realise the phenotype computationally before executing it against a dataset. However, unclear definitions, with little information about how best to implement the definition in practice, hinder this process. To address this issue, we propose a new multi-layer, workflow-based model for defining phenotypes, and a novel authoring architecture, Phenoflow, that supports the development of these structured definitions and their realisation as computable phenotypes. To evaluate our model, we determine its impact on the portability of both code-based (COVID-19) and logic-based (diabetes) definitions, in the context of key datasets, including 26,406 patients at North-western University. Our approach is shown to ensure the portability of phenotype definitions and thus contributes to the transparency of resulting studies.
health informatics
10.1101/2020.06.30.20143669
Spatiotemporal Trends in Bed Bug Metrics, New York City
Bed bug outbreaks pose a major challenge in urban environments and cause significant strain on public resources. Few studies have systematically analyzed the epidemic or the potential effects of policies to combat bed bugs. Here we use three sources of administrative data to characterize the spatial-temporal trends of bed bug inquiries, complaints, and reports in New York City. From 2014-2020, Bed bug complaints have significantly decreased (p < 0.01), the absolute number of complaints per month dropping by half (875 average complaints per month to 440 average complaints per month); conversely cockroach-specific complaints increased over the same period. Despite the decrease of bed bug complaints, areas with reported high bed bug infestation tend to remain infested, highlighting the persistence of these pests. There are limitations to the datasets; still the evidence available suggests that interventions employed by New York City residents and lawmakers are stemming the bed bug epidemic and may serve as a model for other large cities.
epidemiology
10.1101/2020.07.03.20145847
Identifying target regions for enhanced control of gambiense human African trypanosomiasis in the Democratic Republic of Congo
Gambiense human African trypanosomiasis (sleeping sickness, gHAT) is a disease targeted for elimination of transmission (EOT) by 2030. Despite the number of new cases reported annually being at a historical minimum, the likelihood of achieving EOT is unknown. We utilised modelling to study the impact of four strategies comprised of currently-available intervention methods including active and passive screening and vector control (VC) on transmission across 168 health zones in the Democratic Republic of the Congo. By estimating the median year of EOT and the probability of EOT by 2030 under each strategy, the model predicts only 81 health zones are on track to achieve the EOT target using medical-only strategies and this number drops to 52 when uncertainty is considered (> 90% probability). Although all health zones are predicted to meet EOT by 2030 under strategies with VC, blanket coverage is impractical so this analysis provides a priority list of health zones for consideration for supplementary VC implementation in conjunction with medical interventions.
epidemiology
10.1101/2020.07.02.20143941
Convolutional neural networks on eye tracking trajectories classify patients with spatial neglect
Background and ObjectiveEye-movement trajectories are rich behavioral data, providing a window on how the brain processes information. We address the challenge of characterizing signs of visuo-spatial neglect from saccadic eye trajectories recorded in brain-damaged patients with spatial neglect as well as in healthy controls during a visual search task. MethodsWe establish a standardized preprocessing pipeline adaptable to other task-based eye-tracker measurements. We use a deep convolutional network, a very successful type of neural network architecture in many computer vision applications, including medical diagnosis systems, to automatically analyze eye trajectories. ResultsOur algorithm can classify brain-damaged patients vs. healthy individuals with an accuracy of 86{+/-}5%. Moreover, the algorithm scores correlate with the degree of severity of neglect signs estimated with standardized paper-and-pencil test and with white matter tracts impairment via Diffusion Tensor Imaging (DTI). Interestingly, the latter showed a clear correlation with the third branch of the superior longitudinal fasciculus (SLF), especially damaged in neglect. ConclusionsThe study introduces a new classification method to analyze eyes trajectories in patients with neglect syndrome. The method can likely be applied to other types of neurological diseases opening to the possibility of new computer-aided, precise, sensitive and non-invasive diagnosing tools. HighlightsO_LIWe identify signs of visuo-spatial neglect through an automated analysis of saccadic eye trajectories using deep convolutional neural networks (CNNs). C_LIO_LIWe provide a standardized pre-processing pipeline adaptable to other task-based eye-tracker measurements. C_LIO_LIPatient-wise, we benchmark the algorithm prediction with standardized paper-and-pencil test results. C_LIO_LIWe evaluate white matter tracts by using Diffusion Tensor Imaging (DTI) and find a clear correlation with the microstructure of the third branch of the superior longitudinal fasciculus. C_LIO_LIDeep CNNs can efficiently and non-invasively characterize left spatial neglect. C_LI
neurology
10.1101/2020.07.05.20146324
Impact of climate on COVID-19 transmission: A case study with Indian states
Coronavirus Disease 2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short time, it was declared as a worldwide pandemic by the World Health Organisation due to the very fast worldwide spread of the virus. There were a few studies that look for the correlation with infected individuals and different environmental parameters using early data of COVID-19 but there was no study that deal with the variation of effective reproduction number and environmental factors. Effective reproduction number is the driving parameter of the spread of a pandemic and it is important to study the effect of various environmental factors on effective reproduction numbers to understand the effect of those factors on the spread of the virus. We have used time-dependent models to investigate the variation of different time-dependent driving parameters of COVID-19 like effective reproduction number and contact rate using data from India as a test case. India is a large population country that was highly affected due to the COVID-19 pandemic and has a wide span of different temperature and humidity regions and is ideal for such study. We have studied the impact of temperature and humidity on the spread of the virus of different Indian states using time-dependent epidemiological models SIRD, and SEIRD for a long time scale. We used a linear regression method to look for any dependency between the effective reproduction number with the relative humidity, absolute humidity, and temperature. The effective reproduction number showed a negative correlation with both relative and absolute humidity for most of the Indian states, which are statistically significant. This implies that relative and absolute humidity may have an important role in the variation of effective reproduction numbers. There was no conclusive evidence of a correlation between effective reproduction numbers and average air temperature.
epidemiology
10.1101/2020.07.07.20148064
Developing a deep learning system to drive the work of the critical care outreach team
BackgroundCare of patients at risk of deterioration on acute medical and surgical wards requires timely identification, increased monitoring and robust escalation procedures. The critical care outreach role brings specialist-trained critical care nurses and physicians into acute wards to facilitate these processes. Performing this role is challenging, as the breadth of information synthesis required is both high and rapidly updating. We propose a novel automated watch-list to identify patients at high risk of deterioration, to help prioritise the work of the outreach team. ResultsThis system takes data from the electronic medical record in real-time and creates a discrete tokenized trajectory, which is fed into a recurrent neural network model. These models achieve an AUROC of 0.928 for inpatient death and 0.778 for unplanned ICU admission (within 24 hours), which compares favourably with existing early warning scores and is comparable with proof of concept deep learning systems requiring significantly more input data. ConclusionsBased on these results, we can conclude that it is technically feasible to build a set of predictive models that meet the needs of the critical care outreach role, based on a limited set of real-time clinical data.
health informatics
10.1101/2020.07.06.20144345
Community factors associated with local epidemic timing of respiratory syncytial virus: a spatiotemporal modeling study
BackgroundRespiratory syncytial virus (RSV) causes a large burden of morbidity in infants, young children, and the elderly. The timing of RSV seasonal epidemics exhibits strong spatial patterns within the United States. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving transmission of the virus. MethodsWe evaluated competing hypotheses about the associations between RSV epidemic timing at the ZIP-code level and household size, population density, school district boundaries, commuting patterns, and geographic proximity. We used hierarchical Bayesian models with monthly ZIP-code level hospitalization data from New York, New Jersey, and Connecticut between July 1997 and June 2014 to investigate these hypotheses. ResultsEarly epidemic timing across ZIP codes was associated with large household sizes and high population density, and nearby ZIP codes shared similar epidemic timing. Variations in epidemic timing attributed to commuting patterns or school district boundaries are negligible. ConclusionOur results suggest RSV epidemics take off faster in areas with more household crowding and higher population density, and that epidemic spread follows a spatial diffusion process based on geographic proximity. With several vaccines against RSV under development, it is important to understand the drivers of RSV transmission and disease in order to maximize population protection of a vaccine program. Our findings can inform more effective control measures against RSV, such as vaccine programs and household infection control, and guide future studies on the transmission dynamics of RSV.
epidemiology
10.1101/2020.07.06.20144345
Community factors associated with local RSV epidemic patterns: a spatiotemporal modeling study
BackgroundRespiratory syncytial virus (RSV) causes a large burden of morbidity in infants, young children, and the elderly. The timing of RSV seasonal epidemics exhibits strong spatial patterns within the United States. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving transmission of the virus. MethodsWe evaluated competing hypotheses about the associations between RSV epidemic timing at the ZIP-code level and household size, population density, school district boundaries, commuting patterns, and geographic proximity. We used hierarchical Bayesian models with monthly ZIP-code level hospitalization data from New York, New Jersey, and Connecticut between July 1997 and June 2014 to investigate these hypotheses. ResultsEarly epidemic timing across ZIP codes was associated with large household sizes and high population density, and nearby ZIP codes shared similar epidemic timing. Variations in epidemic timing attributed to commuting patterns or school district boundaries are negligible. ConclusionOur results suggest RSV epidemics take off faster in areas with more household crowding and higher population density, and that epidemic spread follows a spatial diffusion process based on geographic proximity. With several vaccines against RSV under development, it is important to understand the drivers of RSV transmission and disease in order to maximize population protection of a vaccine program. Our findings can inform more effective control measures against RSV, such as vaccine programs and household infection control, and guide future studies on the transmission dynamics of RSV.
epidemiology
10.1101/2020.07.06.20147231
Characterisation of alcohol polygenic risk scores in the context of mental health outcomes: Within-individual and intergenerational analyses in the Avon Longitudinal Study of Parents and Children
BackgroundHeavy alcohol consumption often co-occurs with mental health problems; this could be due to confounding, shared biological mechanisms, or causal effects. Polygenic risk scores (PRS) for alcohol use can be used to explore this association at critical life stages. DesignWe characterised a PRS reliably associated with patterns of adult alcohol consumption by 1) validating whether it predicts own alcohol use at different life-stages (pregnancy, adolescence) of interest for mental health impact. Additionally, we explored associations of alcohol PRS on mental health phenotypes 2) within-individuals (using own alcohol PRS on own phenotypes) and 3) intergenerationally (using maternal alcohol PRS on offspring phenotypes). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n=960 to 7841). Additional substance abuse behaviours and mental health/behavioural outcomes were investigated (alcohol phenotypes n=22; health phenotypes n=91). Findings: Maternal alcohol PRS was associated with consumption during pregnancy (strongest signal: alcohol frequency at 18 weeks gestation: {beta}=0.041, 95% CI=1.02 to 1.8), p=1.01x10-5, adjusted R2=1.16%), offspring alcohol PRS did not predict offspring alcohol consumption. We found evidence for an association of maternal alcohol PRS with own perinatal depression (OR=1.10, 95% CI=0.02 to 0.06, p=0.02) and decreased offspring intellectual ability ({beta}=-0.209, 95% CI -0.38 to 0.04, p=0.016). Conclusions: These alcohol PRS are a valid proxy for maternal alcohol use in pregnancy. Offspring alcohol PRS was not associated with drinking in adolescence. Consistently with results from different study designs, we found evidence that maternal alcohol PRS are associated with both prenatal depression and decreased offspring intellectual ability.
epidemiology
10.1101/2020.07.02.20145557
APOE-stratified genome-wide association study suggests potential novel genes for late-onset Alzheimers disease in East-Asian descent
In this study, we report two new possible susceptible genes for late-onset Alzheimers disease identified through an APOE-stratified genome-wide association analysis (GWAS) using East Asian samples. In the discovery phase, we performed a GWAS of Alzheimers disease in 2,291 Korean seniors from the Gwangju Alzheimers and Related Dementias (GARD) cohort study. A successive replication analysis with a Japanese sample of size 1,956 suggested three novel susceptible SNPs in two genes: LRIG1 and CACNA1A. This study demonstrates that the discovery of AD-associated variants can be accomplished in non-European ethnic groups with a more homogeneous genetic background using samples comprising fewer subjects.
genetic and genomic medicine
10.1101/2020.07.07.20148155
Ward-Level Factors Associated with Methicillin-Resistant Staphylococcus aureus Acquisition - an Electronic Medical Records study in Singapore
BackgroundMethicillin-Resistant Staphylococcus aureus (MRSA) is endemic in hospitals worldwide. When patients are transferred between wards within a hospital, their risk of acquiring MRSA may change. In this study, we investigated how ward characteristics and connectivity are associated with MRSA acquisition. MethodsWe analysed electronic medical records on patient transfers and MRSA screening of in-patients at an acute-care tertiary hospital in Singapore to investigate whether ward characteristics and connectivity within the hospital network were associated with MRSA acquisition rates over a period of four years. ResultsMost patient transfers concentrated in a stable core network of wards. Factors associated with increased rate of MRSA acquisition were ward MRSA admission prevalence (rate ratio (RR): 1.50, 95% CI: 1.28, 1.71, per one percentage point increase), admission to a critical care ward (RR: 1.86, 95% CI: 1.14, 3.06) and average number of patients in the ward on a typical day (RR: 1.31, 95% CI: 1.02, 1.68, for every 10 patients quarterly). Admission to an oncology ward (RR: 0.61, 95% CI: 0.40, 0.93) (compared to medical ward), and median length of stay (RR: 0.71, 95% CI: 0.54, 0.93) were associated with lower acquisition rates. We did not find evidence that network measures of ward connectivity, including in-degree, weighted in-degree, influenced MRSA acquisition rate after adjusting for other ward characteristics. ConclusionWard MRSA admission prevalence, critical care ward, ward patient capacity, ward specialty, and median length of stay, rather than relative connectivity of the ward in the hospital network were associated with MRSA acquisition.
infectious diseases
10.1101/2020.07.06.20147462
Two Separate, Large Cohorts Reveal Potential Modifiers of Age-Associated Variation in Visual Reaction Time Performance
To identify individual differences and potential factors influencing age-related cognitive decline and disease, we created MindCrowd. MindCrowd is a cross-sectional web-based assessment of simple visual (sv) reaction time (RT, index of processing speed) and paired-associate learning (PAL, index of verbal episodic memory). svRT and PAL results were combined with 22 survey questions. Analysis of MindCrowds svRT data revealed education and reported stroke as potential modifiers of changes in processing speed and memory from younger to older ages (ntotal = 75,666, nwomen = 47,700, nmen = 27,966; ages 18-85 years old, mean (M)Age = 46.54, standard deviation (SD)Age = 18.40). To complement this work, we evaluated complex recognition reaction time (cvrRT) in the UK Biobank cohort (ntotal = 158,249 nwomen = 89,333 nmen = 68,916; ages 40-70 years old, MAge = 55.81, SDAge = 7.72). Similarities between the UK Biobank and MindCrowd were assessed using a subset of the MindCrowd cohort. Labeled UKBb MindCrowd (ntotal = 39,795, nwomen = 29,640, nmen = 10,155; ages 40-70 years old, MAge = 56.59, SDAge = 8.16), this subset was carefully selected to mirror the UK Biobank. An identical linear model (LM) was used to assess both cohorts. The LM revealed similarities between MindCrowd and the UK Biobank across most results, despite obvious cohort differences (e.g., US vs. the UK). Notable divergent findings from the UK Biobank included (1) a first-degree family history of Alzheimers disease (FHAD) was associated with longer RTs in only. (2) Compared to being a man with more education, being a woman was associated with longer cvrRT length differences observed from younger to older ages. Divergent results from UKBb MindCrowd include more education and reported smoking. More education was associated with shorter and smoking longer cvrRTs differences observed from younger to older ages. Collected with our prior work, MindCrowd is beginning to reveal the intricate network connecting processing speed, memory, and cognition to healthy and pathological brain aging.
geriatric medicine
10.1101/2020.07.07.20148221
Growth Differentiation Factor-15 as a candidate biomarker in gynecologic malignancies: a meta-analysis
Growth Differentiation Factor-15 (GDF-15), though emerged as a novel marker in gynecological cancers, is yet to be recognized in clinical diagnostics. Eligible studies were sorted from multiple online databases, namely PubMed, Cochrane, ClinicalTrials.gov, Google Scholar, Web of Science, Embase, Scopus, LILACS, OpenGrey. From six studies, histopathologically diagnosed cases without prior treatment, and with diagnostic accuracy data for GDF-15 in gynecological cancers, were included. Our meta-analysis shows that GDF-15 has pooled diagnostic odds ratio of 12.74 at 80.5% sensitivity and 74.1% specificity, and an AUC of 0.84. Hence, GDF-15 is a potential marker to differentiate gynecological malignancy from non-malignant tumors.
obstetrics and gynecology
10.1101/2020.07.08.20113035
Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance
IntroductionConfounding bias threatens the reliability of observational studies and poses a significant scientific challenge. This paper introduces a framework for identifying confounding factors by exploiting literature-derived computable knowledge. In previous work, we have shown that semantic constraint search over computable knowledge extracted from the literature can be useful for reducing confounding bias in statistical models of EHR-derived observational clinical data. We hypothesize that adjustment sets of literature-derived confounders could also improve causal inference. MethodsWe introduce two methods (semantic vectors and string-based confounder search) that query the literature for potential confounders and use this information to build models from EHR-derived data to more accurately estimate causal effects. These methods search SemMedDB for indications TREATED BY the drug that is also known to CAUSE the adverse event. For evaluation, we attempt to rediscover associations in a publicly available reference dataset containing expected pairwise relationships between drugs and adverse events from empirical data derived from a corpus of 2.2M EHR-derived clinical notes. For our knowledge-base, we use SemMedDB, a database of computable knowledge mined from the biomedical literature. Using standard adjustment and causal inference procedures on dichotomous drug exposures, confounders, and adverse event outcomes, varying numbers of literature-derived confounders are combined with EHR data to predict and estimate causal effects in light of the literature-derived confounders. We then compare the performance of the new methods with naive ({chi}2, reporting odds ratio) measures of association. Results and ConclusionsLogistic regression with ten vector space-derived confounders achieved the most improvement with AUROC of 0.628 (95% CI: [0.556,0.720]), compared with baseline{chi} 20.507 (95% CI: [0.431,0.583]). Bias reduction was improved more often in modeling methods using more rather than less information, and using semantic vector rather than string-based search. We found computable knowledge useful for improving automated causal inference, and identified opportunities for further improvement, including a role for adjudicating literature-derived confounders by subject matter experts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/20113035v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@77d8a9org.highwire.dtl.DTLVardef@317d09org.highwire.dtl.DTLVardef@107dc05org.highwire.dtl.DTLVardef@fdf3c5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIAccess to causal background knowledge is required for causal learning to scale to large datasets. C_LIO_LIWe introduce a framework for identifying confounders to enhance causal inference from EHR. C_LIO_LIWe search computable knowledge for indications TREATED BY the drug that CAUSE the outcome. C_LIO_LILiterature-derived confounders reduce confounding bias in EHR data. C_LIO_LIStructured knowledge helps interpret and explain data captured in clinical narratives. C_LI
health informatics
10.1101/2020.07.08.20149120
Zika Virus Congenital Microcephaly Severity Classification and the Association of Severity with Neuropsychomotor Development
BackgroundZika virus infection during pregnancy is linked to birth defects, most notably, microcephaly, which in its turn, is associated with neurodevelopmental delays. ObjectiveThe goal of the study is to propose a method for severity classification of congenital microcephaly based on neuroradiological findings of MRI scans, and to investigate the association of severity with neuropsychomotor developmental scores. We also propose a semi-automated method for MRI-based severity classification of microcephaly. MethodsCross-sectional investigation of 42 infants born with congenital Zika infection. Bayley-III developmental evaluations and MRI scans were carried out at ages 13-39 months (mean: 24.8, SD: 5.8). The severity score was generated based on neuroradiologist evaluations of brain malformations. Next, we established a distribution of Zika virus-microcephaly severity score into mild, moderate, and severe and investigated the association of severity with neuropsychomotor developmental scores. Finally, we propose a simplified semi-automated procedure for estimating the severity score, based only on volumetric measures. ResultsResults showed a correlation of r = 0.89 (p < 0.001) between the Zika virus-microcephaly severity score and the semi-automated method. The trimester of infection did not correlate with the semi-automated method. Neuropsychomotor development correlated with the severity classification based on radiological readings and with the semi-automated method; the more severe the imaging scores, the lower neuropsychomotor developmental scores. ConclusionThe severity classification methods may be used to evaluate severity of microcephaly and possible association with developmental consequences. The semi-automated methods thus may be an alternative for prediction of severity of microcephaly using only one MRI sequence.
neurology
10.1101/2020.07.10.20150664
What effect might border screening have on preventing importation of COVID-19 compared with other infections? A modelling study
The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of COVID-19 to investigate the potential benefit of requiring all travellers to undergo thorough screening upon arrival. This is a purely theoretical study to investigate whether a single test at point of entry might ever prove to be a way of significantly decreasing risk of importation. We therefore assume ideal conditions such as 100% compliance among travellers and the use of a "perfect" test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of Influenza, SARS and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening may expect to detect 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results indicate that screening alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases. Data availabilityAll results described in the work, in addition to technical descriptions of methods used, are made available in the supplementary material. The Python package used to implement these methods and obtain our results has been made accessible online[1].
epidemiology
10.1101/2020.07.10.20150607
Wastewater SARS-CoV-2 Concentration and Loading Variability from Grab and 24-Hour Composite Samples
The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires a significant, coordinated public health response. Assessing case density and spread of infection is critical and relies largely on clinical testing data. However, clinical testing suffers from known limitations, including test availability and a bias towards enumerating only symptomatic individuals. Wastewater-based epidemiology (WBE) has gained widespread support as a potential complement to clinical testing for assessing COVID-19 infections at the community scale. The efficacy of WBE hinges on the ability to accurately characterize SARS-CoV-2 RNA concentrations in wastewater. To date, a variety of sampling schemes have been used without consensus around the appropriateness of grab or composite sampling. Here we address a key WBE knowledge gap by examining the variability of SARS-CoV-2 RNA concentrations in wastewater grab samples collected every 2 hours for 72 hours compared with three corresponding 24-hour flow-weighted composite samples collected over the same period. Results show relatively low variability (respective means for N1, N2, N3 assays = 608, 847.9, 768.4 copies 100 mL-1, standard deviations = 501.4, 500.3, 505.8 copies 100 mL-1) for grab sample concentrations, and good agreement between most grab samples and their respective composite (mean deviation from composite = 159 copies 100 mL-1). When SARS-CoV-2 RNA concentrations are used to calculate viral load (RNA concentration * total influent flow the sample day), the discrepancy between grabs (log10 range for all grabs = 11.9) or a grab and its associated 24-hour composite (log10 difference = 11.6) are amplified. A similar effect is seen when estimating carrier prevalence in a catchment population with median estimates based on grabs ranging 63-1885 carriers. Findings suggest that grab samples may be sufficient to characterize SARS-CoV-2 RNA concentrations, but additional calculations using these data may be sensitive to grab sample variability and warrant the use of flow-weighted composite sampling. These data inform future WBE work by helping determine the most appropriate sampling scheme and facilitate sharing of datasets between studies via consistent methodology.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan in August, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Few Excess Mortality probably due to COVID-19 in Tokyo, Japan in August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan in August and September, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan in August and September, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until March, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until April, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Significant Excess Mortality probably due to COVID-19 in Tokyo, Japan until May, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August and September, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August and September, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.09.20143164
Huge Excess Mortality due to the delta strain of COVID-19 in Japan in August and September, 2021
BackgroundNo remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan. ObjectWe sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model. MethodWe applied the NIID model to deaths of all causes from 1987 up through October, 2021 for the whole of Japan and up through August, 2021 for Tokyo. ResultsResults in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021. On the other hand, in Tokyo, 1323 excess mortality was detected Discussion and ConclusionWe detected substantial excess mortality in Japan in August and September, 2021 and in Tokyo in August, 2021. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.
epidemiology
10.1101/2020.07.10.20147488
Associations of Loneliness and Social Isolation with Healthspan and Lifespan in the US Health and Retirement Study
BackgroundLoneliness and social isolation are emerging public health challenges for aging populations. MethodsWe followed N=11,302 US Health and Retirement Study (HRS) participants aged 50-95 from 2006-2014 to measure persistence of experiences of loneliness and exposure to social isolation. We tested associations of longitudinal loneliness and social isolation phenotypes with disability, morbidity, mortality, and biological aging through 2018. ResultsDuring follow-up, 18% of older adults met criteria for loneliness, with 6% meeting criteria at two or more follow-up assessments. For social isolation, these fractions were 21% and 8%. HRS participants who experienced loneliness and were exposed to social isolation were at increased risk for disease, disability, and mortality. Those experiencing persistent loneliness were at a 57% increased hazard of mortality compared to those who never experienced loneliness. For social isolation, the increase was 28%. Effect-sizes were somewhat larger for counts of prevalent activity limitations and somewhat smaller for counts of prevalent chronic diseases. Covariate adjustment for socioeconomic and psychological risks attenuated but did not fully explain associations. Older adults who experienced loneliness and were exposed to social isolation also exhibited physiological indications of advanced biological aging (Cohens-d for persistent loneliness and social isolation=0.26 and 0.21, respectively). For loneliness, but not social isolation, persistence was associated with increased risk. ConclusionDeficits in social connectedness prevalent in a national sample of US older adults were associated with morbidity, disability, and mortality and with more advanced biological aging. Bolstering social connectedness to interrupt experiences of loneliness may promote healthy aging.
epidemiology
10.1101/2020.07.11.20142745
Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas
The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8+ T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and allelic imbalance burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas.
genetic and genomic medicine
10.1101/2020.07.12.20150367
Causal influence of dietary habits on the risk of major depressive disorder: A diet-wide Mendelian randomization analysis
Background & aimsSome evidence suggests that diet may potentially increase or decrease the risk of major depressive disorder (MDD). However, the association between dietary habits and MDD remains controversial. The aim of this study is to systemically investigate the causal influence of dietary habits on the risk of MDD by Mendelian randomization (MR) using diet- and genome-wide summary data. MethodsTo perform two-sample MR, we collected publicly available genome-wide association studies summary statistics for dietary habits from Benjamin Neales lab (n = 361,194) and MDD from the Psychiatric Genomics Consortium (n = 142,646). We used a weighted median approach to synthesize MR estimates across genetic instruments. For the robustness of our results, we compared weighted median results with results from the inverse-variance weighted method, the weighted mode method, and MR-PRESSO. ResultsBeef intake showed a significant protective effect against MDD ({beta} = -1.25; p-value = 0.002; Bonferroni-corrected p-value = 0.034; 9 single nucleotide polymorphisms [SNPs]); and cereal intake was nominally significantly protective ({beta} = -0.52; p-value = 0.011; 21 SNPs). In contrast, non-oily fish intake showed a nominally significantly effect on the risk of MDD ({beta} = 0.84; p-value = 0.030; 6 SNPs). We obtained similar results by using an inverse-variance weighted method and weighted mode approach, although some results were non-significant. On the other hand, we did not observe any significant causal effect of MDD on dietary habits. ConclusionsIn this two-sample MR analysis, we observed that higher beef and cereal intake may be protective factors for MDD, and that higher non-oily fish intake might increase the risk for MDD. However, MDD did not appear to affect dietary habits. Potential mechanisms need to be further investigated to support our novel findings.
psychiatry and clinical psychology
10.1101/2020.07.13.20152413
The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization
IntroductionGenome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example. MethodsWe simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 306,560 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome. ResultsThe simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios. ConclusionsGiven the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, careful consideration before using this approach is warranted. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.
epidemiology
10.1101/2020.07.13.20152272
Fluvastatin mitigates SARS-CoV-2 infection in human lung cells
The retrospective analysis of clinical data of patients suffering from COVID-19 has indicated that statin therapy, used to lower plasma cholesterol levels, is associated with a better clinical outcome. We therefore investigated the effect of statins on SARS-CoV-2 infection and found that selective statins reduced SARS-CoV-2 cell entry and inhibited high and low pathogenic coronavirus infection in human cells. A retrospective study on hospitalized patients with COVID-19 implies that reduced high density lipoprotein levels, which are typically counteracted by statin therapy, are associated with aggravated disease outcome. These results suggest that statin therapy poses no additional risk to individuals exposed to SARS-CoV-2 and that some statins may have a mild beneficial effect on COVID-19 outcome. Placebo controlled trials are required to clarify the role of statins in COVID-19 infected patients.
infectious diseases
10.1101/2020.07.12.20152140
Power law behaviour in the saturation regime of fatality curves of the COVID-19 pandemic
ABSTRACWe apply a versatile growth model, whose growth rate is given by a generalised beta distribution, to describe the complex behaviour of the fatality curves of the COVID-19 disease for several countries in Europe and North America. We show that the COVID-19 epidemic curves not only may present a subexponential early growth but can also exhibit a similar subexponential (power-law) behaviour in the saturation regime. We argue that the power-law exponent of the latter regime, which measures how quickly the curve approaches the plateau, is directly related to control measures, in the sense that the less strict the control, the smaller the exponent and hence the slower the diseases progresses to its end. The power-law saturation uncovered here is an important result, because it signals to policymakers and health authorities that it is important to keep control measures for as long as possible, so as to avoid a slow, power-law ending of the disease. The slower the approach to the plateau, the longer the virus lingers on in the population, and the greater not only the final death toll but also the risk of a resurgence of infections.
infectious diseases
10.1101/2020.07.13.20144808
Persistent intestinal abnormalities and symptoms in cystic fibrosis: The underpinning mechanisms impacting gut health and motility. Protocol for a systematic review.
BackgroundPatients with cystic fibrosis (CF) are characterised by abnormalities of the intestinal tract relating to gut motility and physiological issues, with daily symptoms of disease including abdominal pain, flatulence, bloating, and constipation. With improvements in respiratory outcomes, a shift in disease manifestations has highlighted the prevalence of the gastrointestinal-related problems associated with CF, yet most therapies currently in clinical use for the gut symptoms of CF have been repurposed from other disease indications and have not been developed with a knowledge of the mechanisms underpinning gastrointestinal disease in CF. Increased attention towards the role of intestinal inflammation and microbial dysbiosis in the CF population warrants a comprehensive knowledge of these aspects alongside the increased luminal fat content, dysmotility, and small intestinal bacterial overgrowth (SIBO) resultant of the primary consequences of CFTR dysfunction (disrupted fluid secretion and pancreatic insufficiency), and how they contribute towards the intestinal complications of CF disease. Methods and Study DesignWe will conduct a systematic review to comprehensively address our current understanding of the primary consequences of CFTR dysfunction, and their subsequent secondary effects that contribute towards the disruption of gut motility, health, and associated symptoms in the CF intestine. Databases searched will include PubMed, CINAHL, MEDLINE and the Cochrane library from 1939 until a specified date of last search, alongside clinical trial databases for ongoing studies. Search strategies will include various terminology that relates to the primary mechanistic defects of CF, postulated secondary effects of such defects, and symptoms experienced in patients. A full search strategy is outlined in appendix B. One reviewer will apply an inclusion criterion to obtained abstracts. Following agreement from a second reviewer, full-text articles will be sought, and data will be extracted from relevant articles. Disagreements will be resolved with a third reviewer. The quality of data will be assessed by the GRADE criteria. Data will be used to present a narrative, and where possible, quantitative synthesis. DiscussionThis systematic review will discuss our current understanding of the underpinning mechanisms of the persisting abnormalities in gut health and motility within CF, addressing potential intricate relationships that further contribute to disease progression within the intestinal tract. Furthermore, we will identify current gaps in the literature to propose directions for future research. A comprehensive understanding of these aspects in relation to intestinal abnormalities will aid future clinical directions.
gastroenterology
10.1101/2020.07.14.20152629
Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020)
BackgroundEpidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic. MethodsCohort study of 179 UK care homes with 9,339 residents and 11,604 staff.We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality, and estimate attributable mortality. Results2,075/9,339 residents developed COVID-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory-confirmed infections. The incidence of confirmed infection was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days in residents and staff respectively. 121/179 (67.6%) care homes had at least one COVID-19 infection or COVID-19-related death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection. 217/607 residents with confirmed infection died (case-fatality rate: 35.7% [31.9%; 39.7%]). Mortality in residents with no direct evidence of infection was two-fold higher in care homes with outbreaks versus those without (adjusted HR 2.2 [1.8; 2.6]). ConclusionsFindings suggest many deaths occurred in people who were infected with COVID-19, but not tested. Higher occupancy and lower staffing levels were independently associated with risks of infection. Protecting staff and residents from infection requires regular testing for COVID-19 and fundamental changes to staffing and care home occupancy.
infectious diseases
10.1101/2020.07.13.20153114
Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity
COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of SARS-CoV-2 specific monoclonal antibodies have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of bulk and plasma B-cells collected over multiple time points during infection to characterize signatures of B-cell response to SARS-CoV-2 in 19 patients. Using principled statistical approaches, we determined differential features of BCRs associated with different disease severity. We identified 38 significantly expanded clonal lineages shared among patients as candidates for specific responses to SARS-CoV-2. Using single-cell sequencing, we verified reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in a number of patients. Our results provide important insights for development of rational therapies and vaccines against COVID-19.
infectious diseases
10.1101/2020.07.13.20152884
Development and large-scale validation of a highly accurate SARS-COV-2 serological test using regular test strips for autonomous and affordable finger-prick sample collection, transportation, and storage
Accurate serological tests are essential tools to allow adequate monitoring and control of COVID-19 spread. Production of a low-cost and high-quality recombinant viral antigen can enable the development of reliable and affordable serological assays, which are urgently needed to facilitate epidemiological surveillance studies in low-income economies. Trimeric SARS-COV-2 spike (S) protein was produced in serum-free, suspension-adapted HEK293 cells. Highly purified S protein was used to develop an ELISA, named S-UFRJ test. It was standardized to work with different types of samples: (i) plasma or serum from venous blood samples; (ii) eluates from dried blood spots (DBS) obtained by collecting blood drops from a finger prick. We developed a cost-effective, scalable technology to produce S protein based on its stable expression in HEK293 cells. Using this recombinant antigen, we presented a workflow for test development in the setting of a pandemic, starting from limited amounts of samples up to reaching final validation with hundreds of samples. Test specificity was determined to be 98.6%, whereas sensitivity was 95% for samples collected 11 or more days after symptoms onset. A ROC analysis allowed optimizing the cut-off and confirming the high accuracy of the test. Endpoint titers were shown to correlate with virus neutralization assessed as PRNT90. There was excellent agreement between plasma and DBS samples, significantly simplifying sample collection, storing, and shipping. An overall cost estimate revealed that the final retail price could be in the range of one US dollar. The S-UFRJ assay developed herein meets the quality requirements of high sensitivity and specificity. The low cost and the use of mailable DBS samples allow for serological surveillance and follow-up of SARS-CoV-2 vaccination of populations regardless of geographical and socio-economic aspects. We hope the detailed guidelines for the development of an affordable and accurate anti-spike SARS-COV-2 ELISA, such as S-UFRJ described here, will stimulate governmental and non-governmental health agencies in other countries to engage in much-needed large-scale studies monitoring the spread and immunity to SARS-COV-2 infection.
infectious diseases
10.1101/2020.07.13.20153163
Comparison of seroprevalence of SARS-CoV-2 infections with cumulative and imputed COVID-19 cases: systematic review
BackgroundAccurate seroprevalence estimates of SARS-CoV-2 in different populations could clarify the extent to which current testing strategies are identifying all active infection, and hence the true magnitude and spread of the infection. Our primary objective was to identify valid seroprevalence studies of SARS-CoV-2 infection and compare their estimates with the reported, and imputed, COVID-19 case rates within the same population at the same time point. MethodsWe searched PubMed, Embase, the Cochrane COVID-19 trials, and Europe-PMC for published studies and pre-prints that reported anti-SARS-CoV-2 IgG, IgM and/or IgA antibodies for serosurveys of the general community from 1 Jan to 12 Aug 2020. ResultsOf the 2199 studies identified, 170 were assessed for full text and 17 studies representing 15 regions and 118,297 subjects were includable. The seroprevalence proportions in 8 studies ranged between 1%-10%, with 5 studies under 1%, and 4 over 10% - from the notably hard-hit regions of Gangelt, Germany; Northwest Iran; Buenos Aires, Argentina; and Stockholm, Sweden. For seropositive cases who were not previously identified as COVID-19 cases, the majority had prior COVID-like symptoms. The estimated seroprevalences ranged from 0.56-717 times greater than the number of reported cumulative cases - half of the studies reported greater than 10 times more SARS-CoV-2 infections than the cumulative number of cases. ConclusionsThe findings show SARS-CoV-2 seroprevalence is well below "herd immunity" in all countries studied. The estimated number of infections, however, were much greater than the number of reported cases and deaths in almost all locations. The majority of seropositive people reported prior COVID-like symptoms, suggesting that undertesting of symptomatic people may be causing a substantial under-ascertainment of SARS-CoV-2 infections. Key messagesO_LISystematic assessment of 17-country data show SARS-CoV-2 seroprevalence is mostly less than 10% - levels well below "herd immunity". C_LIO_LIHigh symptom rates in seropositive cases suggest undertesting of symptomatic people and could explain gaps between seroprevalence rates and reported cases. C_LIO_LIThe estimated number of infections for majority of the studies ranged from 2-717 times greater than the number of reported cases in that region and up to 13 times greater than the cases imputed from number of reported deaths. C_LI
epidemiology
10.1101/2020.07.13.20153247
Long Term Safety and Efficacy of Sub-Lingual Ketamine Troches / Lozenges in Chronic Non-Malignant Pain Management
IntroductionChronic non-malignant pain is a disabling condition that results in a reduction in function and quality of life when inadequately managed. Sub-lingual ketamine has been shown to be efficacious for use in chronic pain. Despite its use for decades in chronic non-malignant pain, there is no published long-term data on safety, side effects or adverse drug reactions. The aim of this case-series is to provide the initial evidence for safety and efficacy in this patient group. MethodsWe present a retrospective review of twenty-nine patients (n=29) from a metropolitan tertiary pain service who have been receiving sub-lingual ketamine troches / lozenges between the period of 2012-2019. Patients were identified from the outpatient pain clinic, who had been admitted for inpatient subcutaneous ketamine infusions as part of opiate detoxification or management of central sensitisation due to a chronic neuropathic pain syndrome. An initial review was performed to check the patient started taking the ketamine troches. Each of these medical records was reviewed manually to extract information to a datasheet. ResultsThere was a wide range of dosages used from 25-600mg in divided doses. The duration of treatment ranged from 2-89 months. There was no association with either the dosage or duration of treatment and frequency of side effects. There was an overall reduction in the use of opioids, gabapentinoids or benzodiazepines in 59% of patients with 39% having a complete cessation of an analgesic agent. Side effects were reported in 24%, but only 7% discontinued the treatment due to the side effect (drowsiness). There were no reports of renal impairment, cystitis, or hepatotoxicity. DiscussionThis retrospective case-series has demonstrated that sub-lingual ketamine is a safe and effective analgesic agent to use in chronic non-malignant pain management. It is indicated in a variety of chronic pain conditions and has an excellent safety profile, with no association between the frequency in side effects and duration of therapy or total daily dosages. The study has also shown that the "safe" dose may be higher than the previous consensus. Contribution StatementA.A and S.G. recruited the patients. A.A. & B.M. created the parameters for the data collection sheet. B.M Collected most of the data from the medical records, entered it into a datasheet, wrote the manuscript, ran the statistics, performed the data analysis, and generated the figures and tables. A.A. Edited the manuscript. S.G. and A.A were the research supervisors.
pain medicine
10.1101/2020.07.15.20154245
Organizational culture, quality of care and leadership style in government general hospitals in Kuwait: a multimethod study
PurposeTo investigate the organizational culture, assess the quality of care, and measure their association with a transformational/transactional leadership style in six hospitals. Materials and methodsWe used cross-sectional and retrospective quantitative approaches in government-sponsored secondary-care hospitals. A sample of 1,626 was drawn from a frame of 9,863 healthcare workers in six hospitals. Followers were surveyed using the Multifactor Leadership Questionnaire and the Organizational Description Questionnaire. We reviewed and analyzed one year (2012) of quarterly and annual quality indicators from the hospitals. Data were analyzed using suitable statistical analyses. ResultsWe collected 1,626 responses from six hospitals. 66.4% to 87.1% of participants in each hospital identified their hospitals organizational culture as transformational, whereas 41 out of 48 departments were identified as having a transformational culture. The percentage of participants at each hospital rating their leader and organizational culture as transformational ranged from 60.5% to 80.4%. The differences between leadership style and organizational culture were statistically significant for four of the hospitals. For most of the quality indicators, there was a positive, but nonsignificant, correlation with leadership style. ConclusionLeaders define and influence organizational culture. The prevailing transformational leadership style creates and maintains a transformational organizational culture. The effect of transformational leadership on the quality of care delivered by the organization was measured in this study, and showed a positive and nonsignificant relationship between generic quality indicators and the transformational style.
health systems and quality improvement
10.1101/2020.07.15.20154609
Protocol for a multicentre randomized controlled trial of normobaric versus hyperbaric oxygen therapy for hypoxemic COVID-19 patients
BackgroundAt least 1 in 6 COVID-19 patients admitted to hospital and receiving supplemental oxygen will die of complications. More than 50% of patients with COVID-19 that receive invasive treatment such as mechanical ventilation will die in hospital. Such impacts overwhelm the limited intensive care unit resources and may lead to further deaths given inadequate access to care. Hyperbaric oxygen therapy (HBOT) is defined as breathing 100% oxygen at a pressure higher than 1.4 atmosphere absolute (ATA). HBOT is safe, including for lungs, when administered by experienced teams and is routinely administrated for a number of approved indications. Preliminary clinical evidence suggests clinical improvement when hypoxemic COVID-19 patients are treated with HBOT. ObjectiveWe aim to determine the effectiveness of HBOT for improving oxygenation, morbidity, and mortality among hypoxemic COVID-19 patients. Methods and analysisThis trial is a sequential Bayesian Parallel-group, individually Randomized, Open, Blinded Endpoint controlled trial. Admitted hypoxemic COVID-19 patients who require supplemental oxygen (without mechanical ventilation) to maintain a satisfying tissue oxygenation will be eligible to participate. The anticipated sample size of 234 patients is informed by data from a treatment trial of COVID patients recently published. The intervention group will receive one HBOT per day at 2.0 ATA for 75 minutes. Daily HBOT will be administered until the patient does not require any oxygen supplementation, requires any type of mechanical ventilation, or until day 10 of treatment. Patients in the control group will receive the current standard of care treatment (no HBOT). The primary outcome of this trial will be the 7-level COVID ordinal outcomes scale assessed on Day 7 post-randomization. Secondary outcomes will include: (a) clinical outcomes (length of hospital stay, days with oxygen supplementation, oxygen flow values to obtain a saturation by pulse oximetry [&ge;]90%, intensive care admission and length of stay, days on invasive mechanical ventilation, sleep quality, fatigue, major thrombotic events, the 7-level COVID ordinal outcomes scale on Day 28; mortality, safety); (b) biological outcomes (plasma inflammatory markers); and (c) health system outcomes (cost of care and cost-effectiveness). Predetermined inclusion/exclusion criteria have been specified. The analytical approach for the primary outcome will use a Bayesian proportional odds ordinal logistic semiparametric model. The primary analysis will be by intention-to-treat. Bayesian posterior probabilities will be calculated every 20 patients to assess accumulating evidence for benefit or harm. A planned subgroup analysis will be performed for pre-specified variables known to impact COVID-19 prognosis and/or HBOT (biologic sex and age). DiscussionBased on the mortality rate and substantial burden of COVID-19 on the healthcare system, it is imperative that solutions be found. HBOT is a non-invasive and low-risk intervention when contraindications are respected. The established safety and relatively low cost of providing HBOT along with its potential to improve the prognosis of severe COVID-19 patients make this intervention worth studying, despite the current limited number of HBOT centres. If this trial finds that HBOT significantly improves outcome and prevents further deterioration leading to critical care for severe COVID-19 patients, practice will change internationally. If no benefit is found from the intervention, then the current standard of care (no HBOT) will be supported by level I evidence. Trials RegistrationNCT04500626
infectious diseases
10.1101/2020.07.15.20154765
Controlling COVID-19 via test-trace-quarantine
Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We performed this analysis using Covasim, an open-source agent-based model, which was calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we found that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.
epidemiology
10.1101/2020.07.15.20154765
Controlling COVID-19 via test-trace-quarantine
Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We performed this analysis using Covasim, an open-source agent-based model, which was calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we found that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.
epidemiology
10.1101/2020.07.15.20154849
New insight of adrenal responses in premature neonates versus full term neonates in critical care setting
BackgroundAdequate adrenocortical function is essential for survival of critically ill neonates. Although most of them display elevated plasma cortisol concentrations, which reflects activation of the hypothalamic pituitary adrenal axis (HPA), yet; adrenocortical insufficiency is seen in septic shock. Objectives: Evaluate the HPA response in critically ill neonates with shock. Methodsthis prospective observational Participant: a total of 60 neonates divided into 3 groups;(A) 30 critical ill neonates with septic shock on inotropic support, (B)15 patients with sepsis with no inotropic support and(C) control group(n=15). Intervention: a single diurnal ACTH reading and two readings for serum cortisol level (diurnal and nocturnal). ResultsGram negative organism was more prevalent among the patients; 53%, 63% in groups A and B respectively. Group A showed Significant statistical hypotension before vasopressor drug administration (p<0.001) as compared to both groups. Group A showed Significant statistical improvement of blood pressure after vasopressor drug administration (p<0.001) as compared to both groups B, C. Serum cortisol was significantly higher in group A(57.21{+/-}24.31) and B (48.01{+/-}18.27), while it was lower in group C(19.57{+/-}16.05). A highly statistically significant rise of serum cortisol level(p=0.000) and ACTH(p=0.000) in group A when was compared to the other two groups. ConclusionThis study introduced a new pattern of serum cortisol response in neonates ranging from very high cortisol level to a near normal values; highlighting a state of glucocorticoid resistance in neonates and relative adrenal insufficiency.
pediatrics
10.1101/2020.07.15.20154849
New insight of adrenal responses in premature neonates versus full term neonates in critical care setting
BackgroundAdequate adrenocortical function is essential for survival of critically ill neonates. Although most of them display elevated plasma cortisol concentrations, which reflects activation of the hypothalamic pituitary adrenal axis (HPA), yet; adrenocortical insufficiency is seen in septic shock. Objectives: Evaluate the HPA response in critically ill neonates with shock. Methodsthis prospective observational Participant: a total of 60 neonates divided into 3 groups;(A) 30 critical ill neonates with septic shock on inotropic support, (B)15 patients with sepsis with no inotropic support and(C) control group(n=15). Intervention: a single diurnal ACTH reading and two readings for serum cortisol level (diurnal and nocturnal). ResultsGram negative organism was more prevalent among the patients; 53%, 63% in groups A and B respectively. Group A showed Significant statistical hypotension before vasopressor drug administration (p<0.001) as compared to both groups. Group A showed Significant statistical improvement of blood pressure after vasopressor drug administration (p<0.001) as compared to both groups B, C. Serum cortisol was significantly higher in group A(57.21{+/-}24.31) and B (48.01{+/-}18.27), while it was lower in group C(19.57{+/-}16.05). A highly statistically significant rise of serum cortisol level(p=0.000) and ACTH(p=0.000) in group A when was compared to the other two groups. ConclusionThis study introduced a new pattern of serum cortisol response in neonates ranging from very high cortisol level to a near normal values; highlighting a state of glucocorticoid resistance in neonates and relative adrenal insufficiency.
pediatrics
10.1101/2020.07.15.20154864
Dense phenotyping from electronic health records enables machine-learning-based prediction of preterm birth
Identifying pregnancies at risk for preterm birth, one of the leading causes of worldwide infant mortality, has the potential to improve prenatal care. However, we lack broadly applicable methods to accurately predict preterm birth risk. The dense longitudinal information present in electronic health records (EHRs) is enabling scalable and cost-efficient risk modeling of many diseases, but EHR resources have been largely untapped in the study of pregnancy. Here, we apply machine learning to diverse data from EHRs to predict singleton preterm birth. Leveraging a large cohort of 35,282 deliveries, we find that machine learning models based on billing codes alone can predict preterm birth risk at various gestational ages (e.g., ROC-AUC=0.75, PR-AUC=0.40 at 28 weeks of gestation) and outperform comparable models trained using known risk factors (e.g., ROC-AUC=0.65, PR-AUC=0.25 at 28 weeks). Examining the patterns learned by the model reveals it stratifies deliveries into interpretable groups, including high-risk preterm birth sub-types enriched for distinct comorbidities. Our machine learning approach also predicts preterm birth sub-types (spontaneous vs. indicated), mode of delivery, and recurrent preterm birth. Finally, we demonstrate the portability of our approach by showing that the prediction models maintain their accuracy on a large, independent cohort (5,978 deliveries) from a different healthcare system. By leveraging rich phenotypic and genetic features derived from EHRs, we suggest that machine learning algorithms have great potential to improve medical care during pregnancy.
health informatics
10.1101/2020.07.14.20153825
Impact of body composition on COVID-19 susceptibility and severity: a two-sample multivariable Mendelian randomization study
ObjectivesRecent studies suggested obesity to be a possible risk factor for COVID-19 disease in the wake of the coronavirus (SARS-CoV-2) infection. However, the causality and especially the role of body fat distribution in this context is still unclear. Thus, using a univariable as well as multivariable two-sample Mendelian randomization (MR) approach, we investigated for the first time the causal impact of body composition on the susceptibility and severity of COVID-19. MethodsAs indicators of overall and abdominal obesity we considered the measures body mass index (BMI), waist circumference (WC), and trunk fat ratio (TFR). Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used. For the COVID-19 cohort neither age nor gender was available. Total and direct causal effect estimates were calculated using Single Nucleotide Polymorphisms (SNPs), sensitivity analyses were done applying several robust MR techniques and mediation effects of type 2 diabetes (T2D) and cardiovascular diseases (CVD) were investigated within multivariable MR analyses. ResultsGenetically predicted BMI was strongly associated with both, susceptibility (OR=1.31 per 1 SD increase; 95% CI: 1.15-1.50; P-value=7.3{middle dot}10-5) and hospitalization (OR=1.62 per 1 SD increase; 95% CI: 1.33-1.99; P-value=2.8{middle dot}10-6) even after adjustment for genetically predicted visceral obesity traits. These associations were neither mediated substantially by T2D nor by CVD. Finally, total but not direct effects of visceral body fat on outcomes could be detected. ConclusionsThis study provides strong evidence for a causal impact of overall obesity on the susceptibility and severity of COVID-19 disease. The impact of abdominal obesity was weaker and disappeared after adjustment for BMI. Therefore, obese people should be regarded as a high-risk group. Future research is necessary to investigate the underlying mechanisms linking obesity with COVID-19.
infectious diseases
10.1101/2020.07.14.20153742
Assessing the causal impact of adiposity variation on rates of hospital admission: Application of Mendelian randomization
We analyze how measures of adiposity - body mass index (BMI) and waist-hip ratio (WHR) - causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable modelsin a Mendelian Randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian Randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observe an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian Randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.
epidemiology
10.1101/2020.07.16.20150250
Saliva TwoStep for rapid detection of asymptomatic SARS-CoV-2 carriers
Here, we develop a simple molecular test for SARS-CoV-2 in saliva based on reverse transcription loop-mediated isothermal amplification (RT-LAMP). The test has two steps: 1) heat saliva with a stabilization solution, and 2) detect virus by incubating with a primer/enzyme mix. After incubation, saliva samples containing the SARS-CoV-2 genome turn bright yellow. Because this test is pH dependent, it can react falsely to some naturally acidic saliva samples. We report unique saliva stabilization protocols that rendered 295 healthy saliva samples compatible with the test, producing zero false positives. We also evaluated the test on 278 saliva samples from individuals who were infected with SARS-CoV-2 but had no symptoms at the time of saliva collection, and from 54 matched pairs of saliva and anterior nasal samples from infected individuals. The Saliva TwoStep test described herein identified infections with 94% sensitivity and >99% specificity in individuals with sub-clinical (asymptomatic or pre-symptomatic) infections.
infectious diseases
10.1101/2020.07.16.20155127
The heart of an endurance athlete: impact of and recovery after an ultra-endurance event.
AimsAcute bouts of ultra-endurance exercise may cause an acute reduction in cardiac function, causing a physiological cascade which releases cardiac biomarkers. This study set out to determine the cardiac stress and recovery of participation in a three-day ultra-endurance mountain biking event of athletes using heart rate variability (HRV) as an outcome measure. MethodsSixteen healthy participants (male and female) participating in a three-day ultra-endurance mountain biking event underwent a five-minute resting ECG recording in a supine position. Heart rate variability measurements were recorded two days before the race (baseline testing), after each race day, and at 24-hour post-event (recovery). ResultsTime-domain and frequency domain measures showed significant (p[&le;]0.05) changes from baseline in HRV parameters after each race day. The significant changes in HRV parameters reflected an increase in sympathetic activity after each day of the event. Our data revealed that the mean HR and RR variability variables did not return to baseline value after 24-hours of recovery, reflecting autonomic nervous system dysfunction, and that changes persisted for at least 24-hours post-event. ConclusionOur study shows that competing in an ultra-endurance mountain bike event led to diminished vagal activity and a decrease in HRV throughout the event and persisted for at least 24-hours post-event. The body was under continuous sympathetic dominance during rest as well as during each day of racing, implying each race day can be considered a physiological stress. This may, in turn, cause a disturbance in homeostasis and an increase in autonomic nervous system dysfunction. This has implications for further research, including dysrhythmia risk, and monitoring of athletes in advising a return to strenuous activity.
sports medicine
10.1101/2020.07.17.20156034
Assessing the effects of non-pharmaceutical interventions on SARS-CoV-2 spread in Belgium by means of a compartmental, age-stratified, extended SEIQRD model and public mobility data
We present a compartmental extended SEIQRD metapopulation model for SARS-CoV-2 spread in Belgium. We demonstrate the robustness of the calibration procedure by calibrating the model using incrementally larger datasets and dissect the model results by computing the effective reproduction number at home, in workplaces, in schools, and during leisure activities. We find that schools are an important transmission pathway for SARS-CoV-2, with the potential to increase the effective reproduction number from Re = 0.66 {+/-} 0.04 (95 % CI) to Re = 1.09 {+/-} 0.05 (95 % CI) under lockdown measures. The model accounts for the main characteristics of SARS-CoV-2 transmission and COVID-19 disease and features a detailed representation of hospitals with parameters derived from a dataset consisting of 22 136 hospitalized patients. Social contact during the pandemic is modeled by scaling pre-pandemic contact matrices with Google Community Mobility data and with effectivity-of-contact parameters inferred from hospitalization data. The calibrated social contact model with its publically available mobility data, although coarse-grained, is a readily available alternative to social-epidemiological contact studies under lockdown measures, which were not available at the start of the pandemic.
epidemiology
10.1101/2020.07.17.20156034
Assessing the effects of non-pharmaceutical interventions on SARS-CoV-2 spread in Belgium by means of a compartmental, age-stratified, extended SEIQRD model and public mobility data
We present a compartmental extended SEIQRD metapopulation model for SARS-CoV-2 spread in Belgium. We demonstrate the robustness of the calibration procedure by calibrating the model using incrementally larger datasets and dissect the model results by computing the effective reproduction number at home, in workplaces, in schools, and during leisure activities. We find that schools are an important transmission pathway for SARS-CoV-2, with the potential to increase the effective reproduction number from Re = 0.66 {+/-} 0.04 (95 % CI) to Re = 1.09 {+/-} 0.05 (95 % CI) under lockdown measures. The model accounts for the main characteristics of SARS-CoV-2 transmission and COVID-19 disease and features a detailed representation of hospitals with parameters derived from a dataset consisting of 22 136 hospitalized patients. Social contact during the pandemic is modeled by scaling pre-pandemic contact matrices with Google Community Mobility data and with effectivity-of-contact parameters inferred from hospitalization data. The calibrated social contact model with its publically available mobility data, although coarse-grained, is a readily available alternative to social-epidemiological contact studies under lockdown measures, which were not available at the start of the pandemic.
epidemiology
10.1101/2020.07.17.20155937
Probabilistic approaches for classifying highly variable anti-SARS-CoV-2 antibody responses
Serological studies are critical for understanding pathogen-specific immune responses and informing public health measures1,2. Here, we evaluate tandem IgM, IgG and IgA responses in a cohort of individuals PCR+ for SARS-CoV-2 RNA (n=105) representing different categories of disease severity, including mild and asymptomatic infections. All PCR+ individuals surveyed were IgG-positive against the virus spike (S) glycoprotein. Elevated Ab levels were associated with hospitalization, with IgA titers, increased circulating IL-6 and strong neutralizing responses indicative of intensive care status. Additional studies of healthy blood donors (n=1,000) and pregnant women (n=900), sampled weekly during the initial outbreak in Stockholm, Sweden (weeks 14-25, 2020), demonstrated that anti-viral IgG titers differed over 1,000-fold between seroconverters, highlighting the need for careful evaluation of assay cut-offs for individual measurements and accurate estimates of seroprevalence (SP). To provide a solution to this, we developed probabilistic machine learning approaches to assign likelihood of past infection without setting an assay cut-off, allowing for more quantitative individual and population-level Ab measures. Using these tools, that considered responses against both S and RBD, we report SARS-CoV-2 S-specific IgG in 6.8% of blood donors and pregnant women two months after the peak of spring COVID-19 deaths, with the SP curve and country death rate following similar trajectories.
allergy and immunology
10.1101/2020.07.18.20156653
Estimation of stroke outcomes based on time to thrombolysis and thrombectomy
Background & MotivationStroke outcomes following revascularization therapy (intravenous thrombolysis, IVT, and/or mechanical thrombectomy, MT) depend critically on time from stroke onset to treatment. Different service configurations may prioritise time to IVT or time to MT. In order to evaluate alternative acute stroke care configurations, it is necessary to estimate clinical outcomes given differing times to IVT and MT. MethodModel using an algorithm coded in Python. This is available at https://github.com/MichaelAllen1966/stroke_outcome_algorithm ResultsWe demonstrate how the code may be used to estimate clinical outcomes given varying times to IVT and MT. ConclusionPython code has been developed and shared to enable estimation of clinical outcome given times to IVT and MT. Here we share pseudocode and links to full Python code.
cardiovascular medicine
10.1101/2020.07.17.20156539
Quantifying SARS-CoV-2 infection risk within the Google/Apple exposure notification framework to inform quarantine recommendations
Most Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, [&ge;]15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long post-exposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes Theorem. We capture a 10-fold range of risk using 6 infectiousness values, 11-fold range using 3 Bluetooth attenuation bins, [~]6-fold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and [~]11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.
epidemiology
10.1101/2020.07.15.20154286
A privacy-preserving Bayesian network model for personalised COVID19 risk assessment and contact tracing
Concerns about the practicality and effectiveness of using Contact Tracing Apps (CTA) to reduce the spread of COVID19 have been well documented and, in the UK, led to the abandonment of the NHS CTA shortly after its release in May 2020. One of the key non-technical obstacles to widespread adoption of CTA has been concerns about privacy. We present a causal probabilistic model (a Bayesian network) that provides the basis for a practical CTA solution that does not compromise privacy. Users of the model can provide as much or little personal information as they wish about relevant risk factors, symptoms, and recent social interactions. The model then provides them feedback about the likelihood of the presence of asymptotic, mild or severe COVID19 (past, present and projected). When the model is embedded in a smartphone app, it can be used to detect new outbreaks in a monitored population and identify outbreak locations as early as possible. For this purpose, the only data needed to be centrally collected is the probability the user has COVID19 and the GPS location.
health informatics
10.1101/2020.07.17.20152702
Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes
To increase the throughput, lower the cost, and save scarce test reagents, laboratories can pool patient samples before SARS-CoV-2 RT-qPCR testing. While different sample pooling methods have been proposed and effectively implemented in some laboratories, no systematic and large-scale evaluations exist using real-life quantitative data gathered throughout the different epidemiological stages. Here, we use anonymous data from 9673 positive cases to simulate and compare 1D and 2D pooling strategies. We show that the optimal choice of pooling method and pool size is an intricate decision with a testing population-dependent efficiency-sensitivity trade-off and present an online tool to provide the reader with custom real-time pooling strategy recommendations.
epidemiology
10.1101/2020.07.17.20152702
Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes
To increase the throughput, lower the cost, and save scarce test reagents, laboratories can pool patient samples before SARS-CoV-2 RT-qPCR testing. While different sample pooling methods have been proposed and effectively implemented in some laboratories, no systematic and large-scale evaluations exist using real-life quantitative data gathered throughout the different epidemiological stages. Here, we use anonymous data from 9673 positive cases to simulate and compare 1D and 2D pooling strategies. We show that the optimal choice of pooling method and pool size is an intricate decision with a testing population-dependent efficiency-sensitivity trade-off and present an online tool to provide the reader with custom real-time pooling strategy recommendations.
epidemiology
10.1101/2020.07.13.20146118
Practical strategies for extreme missing data imputation in dementia diagnosis
Accurate computational models for clinical decision support systems require clean and reliable data but, in clinical practice, data are often incomplete. Hence, missing data could arise not only from training datasets but also test datasets which could consist of a single undiagnosed case, an individual. This work addresses the problem of extreme missingness in both training and test data by evaluating multiple imputation and classification workflows based on both diagnostic classification accuracy and computational cost. Extreme missingness is defined as having [~]50% of the total data missing in more than half the data features. In particular, we focus on dementia diagnosis due to long time delays, high variability, high attrition rates and lack of practical data imputation strategies in its diagnostic pathway. We identified and replicated the extreme missingness structure of data from a real-world memory clinic on a larger open dataset, with the original complete data acting as ground truth. Overall, we found that computational cost, but not accuracy, varies widely for various imputation and classification approaches. Particularly, we found that iterative imputation on the training dataset combined with a reduced-feature classification model provides the best approach, in terms of speed and accuracy. Taken together, this work has elucidated important factors to be considered when developing a predictive model for a dementia diagnostic support system.
health informatics
10.1101/2020.07.20.20157644
Depression stigma effects on help-seeking attitudes in college students: Baseline results of a randomized controlled trial
ObjectiveDepression stigma has been considered a significant barrier to treatment and rehabilitation. This study aimed to understand the effects of gender, previous health care use, and symptomatology on depression stigma and analyze the impact of depression stigma on help-seeking attitudes. MethodsA total of 969 students with a mean age of 18.87 (SD=1.49) were included in this study and completed the Depression Stigma Scale, the Attitude Toward Seeking Professional Psychological Help, the Patient Health Questionnaire-4 questionnaire, and a socio-demographic questionnaire. We analyzed data using SPSS 24.0, with a 95% confidence interval. We performed an analysis of variance using One-Way ANOVA and analyzed possible interactions between gender and previous mental healthcare groups on depression stigma and help-seeking attitudes using a Two-Way ANOVA. T-tests were used to study differences between the gender, symptomatology groups, and previous access to mental healthcare. We also executed a hierarchical linear regression to evaluate the effects of individual characteristics on Depression Stigma and Help-seeking attitudes scores. ResultsParticipants came from all University schools, and 64.6% were women. Stigma and help-seeking attitudes are positively affected by gender and previous access to mental healthcare services. Higher personal stigma weakened help-seeking attitudes. Depressive and anxiety symptoms influenced personal depression stigma and perceived stigma; however, we detected no direct symptomatology effect on help-seeking attitudes. ConclusionsPersonal depression stigma has an essential effect on help-seeking attitudes, and depressive and anxiety symptoms do not. The promotion of literacy may decrease personal depression stigma and increase professional help-seeking intentions.
psychiatry and clinical psychology
10.1101/2020.07.20.20157644
The association between stigmatizing attitudes towards depression and help-seeking attitudes in college students: Baseline results of a randomized controlled trial
ObjectiveDepression stigma has been considered a significant barrier to treatment and rehabilitation. This study aimed to understand the effects of gender, previous health care use, and symptomatology on depression stigma and analyze the impact of depression stigma on help-seeking attitudes. MethodsA total of 969 students with a mean age of 18.87 (SD=1.49) were included in this study and completed the Depression Stigma Scale, the Attitude Toward Seeking Professional Psychological Help, the Patient Health Questionnaire-4 questionnaire, and a socio-demographic questionnaire. We analyzed data using SPSS 24.0, with a 95% confidence interval. We performed an analysis of variance using One-Way ANOVA and analyzed possible interactions between gender and previous mental healthcare groups on depression stigma and help-seeking attitudes using a Two-Way ANOVA. T-tests were used to study differences between the gender, symptomatology groups, and previous access to mental healthcare. We also executed a hierarchical linear regression to evaluate the effects of individual characteristics on Depression Stigma and Help-seeking attitudes scores. ResultsParticipants came from all University schools, and 64.6% were women. Stigma and help-seeking attitudes are positively affected by gender and previous access to mental healthcare services. Higher personal stigma weakened help-seeking attitudes. Depressive and anxiety symptoms influenced personal depression stigma and perceived stigma; however, we detected no direct symptomatology effect on help-seeking attitudes. ConclusionsPersonal depression stigma has an essential effect on help-seeking attitudes, and depressive and anxiety symptoms do not. The promotion of literacy may decrease personal depression stigma and increase professional help-seeking intentions.
psychiatry and clinical psychology
10.1101/2020.07.20.20157644
The association between stigmatizing attitudes towards depression and help-seeking attitudes in college students
ObjectiveDepression stigma has been considered a significant barrier to treatment and rehabilitation. This study aimed to understand the effects of gender, previous health care use, and symptomatology on depression stigma and analyze the impact of depression stigma on help-seeking attitudes. MethodsA total of 969 students with a mean age of 18.87 (SD=1.49) were included in this study and completed the Depression Stigma Scale, the Attitude Toward Seeking Professional Psychological Help, the Patient Health Questionnaire-4 questionnaire, and a socio-demographic questionnaire. We analyzed data using SPSS 24.0, with a 95% confidence interval. We performed an analysis of variance using One-Way ANOVA and analyzed possible interactions between gender and previous mental healthcare groups on depression stigma and help-seeking attitudes using a Two-Way ANOVA. T-tests were used to study differences between the gender, symptomatology groups, and previous access to mental healthcare. We also executed a hierarchical linear regression to evaluate the effects of individual characteristics on Depression Stigma and Help-seeking attitudes scores. ResultsParticipants came from all University schools, and 64.6% were women. Stigma and help-seeking attitudes are positively affected by gender and previous access to mental healthcare services. Higher personal stigma weakened help-seeking attitudes. Depressive and anxiety symptoms influenced personal depression stigma and perceived stigma; however, we detected no direct symptomatology effect on help-seeking attitudes. ConclusionsPersonal depression stigma has an essential effect on help-seeking attitudes, and depressive and anxiety symptoms do not. The promotion of literacy may decrease personal depression stigma and increase professional help-seeking intentions.
psychiatry and clinical psychology
10.1101/2020.07.19.20157404
The genetic architecture of human infectious diseases and pathogen-induced cellular phenotypes
Here, we develop a genetics-anchored framework to decipher mechanisms of infectious disease (ID) risk and infer causal effect on potential complications. We perform transcriptome-wide association studies (TWAS) of 35 ID traits in 27,615 individuals in a broad collection of human tissues, identifying 70 gene-level associations with 26 ID traits, with replication in two large-scale biobanks. A phenome-scale scan and Mendelian Randomization of the 70 gene-level associations across 197 traits proposes a molecular basis for known complications of the ID traits. This rich resource of host genetic associations with pathogen cultures and 16S-rRNA-based microbiome variation provides a platform to investigate host-pathogen interactions. To identify relevant cellular processes, we develop a TWAS repository of 79 pathogen-exposure induced cellular phenotypes. Our study will facilitate mechanistic insights into the role of host genetic variation on ID risk and pathophysiology, with important implications for our molecular understanding of severe phenotypic outcomes.
genetic and genomic medicine
10.1101/2020.07.19.20157354
The Effect of GDP and Distance on Timing of COVID-19 Spread in Chinese Provinces in 2020
The geographical spread of COVID-19 across Chinas provinces provides the opportunity for retrospective analysis on contributors to the timing of the spread. Highly contagious diseases need to be seeded into populations and we hypothesized that greater distance from the epicenter in Wuhan, as well as higher province-level GDP per capita, would delay the time until a province detected COVID-19 cases. To test this hypothesis, we used province-level socioeconomic data such as GDP per capita and percentage of the population aged over 65, distance from the Wuhan epicenter, and health systems capacity in a Cox proportional hazards analysis of the determinants of each provinces time until epidemic start. The start was defined by the number of days it took for each province to reach thresholds of 3, 5, 10, or 100 cases. We controlled for the number of hospital beds and physicians as these could influence the speed of case detection. Surprisingly, none of the explanatory variables had a statistically significant effect on the time it took for each province to get its first cases; the timing of COVID-19 spread appears to have been random with respect to distance, GDP, demography, and the strength of the health system. Looking to other factors, such as travel, policy, and lockdown measures, could provide additional insights on realizing most critical factors in the timing of spread.
health economics
10.1101/2020.07.16.20155556
Recruitment of Older African Americans in Alzheimers Disease Clinical Trials Using A Community Based Research Approach
African Americans are disproportionately affected by Alzheimers disease and related dementias (ADRD) and are two times more likely to develop ADRD compared to their White counterparts. Despite the higher prevalence of ADRD among older African Americans, recent estimates suggest research enrollment by those who identify as African American remains limited. The purpose of the study is to 1) explore how a culturally tailored community education program impacts clinical trial interest and enrollment in ADRD research studies and to 2) identify how applicable the African American community perceived the culturally tailored curriculum. Using a community-engaged research approach, we collaborated with predominately African American serving community-based organizations to support content development and delivery of Aging with Grace (AWG), a culturally tailored ADRD educational curriculum. A total of five AWG presentations were given to 66 attendees. Most attendees (67%) expressed interest in participating in clinical trials after attending AWG. Enrollment increased within an observational study (84%) and lifestyle prevention clinical trials (52%) from 2018 to 2019. Attendees (32%) also perceived an increase in ADRD knowledge from attending AWG and 89.1% believed more African Americans should participate in research. Our work demonstrates the effectiveness of a culturally tailored community education program to enhance knowledge, clinical trial interest, and recruitment into observational studies and lifestyle ADRD clinical trials among older African Americans. Education programs developed in partnership with the community can serve as bridge to research participation for under-represented minorities in clinical research. Future studies should assess long-term retention of knowledge and research readiness.
public and global health
10.1101/2020.07.15.20154955
Managing the risk of a COVID-19 outbreak from border arrivals
In an attempt to maintain elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false negative test result. We show that the combination of 14-day quarantine with two tests reduces the risk of releasing an infectious case to around 0.1% per infected arrival. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases this risk. We calculate the fraction of cases detected in the second week of their two week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159707
Excess deaths in Spain during the first year of the COVID-19 pandemic outbreak from age/sex-adjusted death rates
OO_SCPLOWBJECTIVESC_SCPLOWAssess the impact of the illness designated COVID-19 during the first year of pandemic outbreak in Spain through age/sex-specific death rates. SO_SCPLOWTUDYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWDESIGNC_SCPLOWAge/sex-specific weeekly deaths in Spain were retrieved from Eurostat. Spanish resident population was obtained from the National Statistics Office. MO_SCPLOWETHODSC_SCPLOWGeneralized linear Poisson regressions were used to compute the contrafactual expected rates after one year (52 weeks or 364 days) of the pandemic onset. From this one-year age/sex-specific and age/sex-adjusted mortality excess rates were deduced. RO_SCPLOWESULTSC_SCPLOWFor the past continued 13 years one-year age/sex-adjusted death rates had not been as high as the rate observed on February 28th, 2021. The excess death rate was estimated as 1.790x10-3 (95 % confidence interval, 1.773x10-3 to 1.808x10-3; P-score = 20.2 % and z-score = 11.4) with an unbiased standard deviation of the residuals equal to 157x10-6. This made 84 849 excess deaths (84 008 to 85 690). Sex disaggregation resulted in 44 887 (44 470 to 45 303) male excess deaths and 39 947 (39 524 to 40 371) female excess deaths. CO_SCPLOWONCLUSIONC_SCPLOWWith 73 571 COVID-19 deaths and 9772 COVID-19 suspected deaths that occurred in nursing homes during the spring of 2020 it is only 1496 excess deaths (1.8 %, a z-score of 0.2) that remains unattributed. The infection rate during the first year of the pandemic is estimated in 16 % of population after comparing the ENE-COVID seroprevalence, the excess deaths at the end of the spring 2020 and the excess deaths at the end of the first year of the pandemic.
epidemiology
10.1101/2020.07.22.20159251
Exome sequencing identifies rare damaging variants in the ATP8B4 and ABCA1 genes as novel risk factors for Alzheimers Disease.
The genetic component of Alzheimers disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals --16,036 AD cases and 16,522 controls-- in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, A{beta}-aggregation, lipid metabolism and microglial function in AD.
genetic and genomic medicine
10.1101/2020.07.22.20159251
Exome sequencing identifies rare damaging variants in the ATP8B4 and ABCA1 genes as novel risk factors for Alzheimers Disease.
The genetic component of Alzheimers disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals --16,036 AD cases and 16,522 controls-- in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, A{beta}-aggregation, lipid metabolism and microglial function in AD.
genetic and genomic medicine
10.1101/2020.07.22.20159251
Exome sequencing identifies rare damaging variants in the ATP8B4 and ABCA1 genes as novel risk factors for Alzheimers Disease.
The genetic component of Alzheimers disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals --16,036 AD cases and 16,522 controls-- in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, A{beta}-aggregation, lipid metabolism and microglial function in AD.
genetic and genomic medicine
10.1101/2020.07.22.20159251
Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as novel risk factors for Alzheimers Disease
The genetic component of Alzheimers disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals --16,036 AD cases and 16,522 controls-- in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, A{beta}-aggregation, lipid metabolism and microglial function in AD.
genetic and genomic medicine
10.1101/2020.07.21.20159228
Genetic correlates of phenotypic heterogeneity in autism
The substantial phenotypic heterogeneity in autism limits our understanding of its genetic aetiology. To address this gap, we investigated genetic differences between autistic individuals (Nmax = 12,893) based on core (i.e., social communication difficulties, and restricted and repetitive behaviours) and associated features of autism, co-occurring developmental disabilities (e.g. language, motor, and intellectual developmental disabilities and delays), and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants including autism polygenic scores (PGS) were associated with the core factors but de novo variants were not, even though the latent factor structure was similar between carriers and non-carriers of de novo variants. We identify that increasing autism PGS decrease the likelihood of co- occurring developmental disabilities in autistic individuals, which reflects both a true protective effect and additivity between rare and common variants. Furthermore in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observe higher SNP heritability for males and autistic individuals without ID, but found no robust differences in SNP heritability by the level of core autism features. Deeper phenotypic characterisation will be critical to determining how the complex underlying genetics shapes cognition, behaviour, and co- occurring conditions in autism.
genetic and genomic medicine