bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic association supports indexing size measures in echocardiography by body surface area
Authors: Fung Angus SY , Soundappan Dhnanjay , Loewenstein Daniel E , Playford David , Strange Geoffrey , Kozor Rebecca , Otton James , Ugander Martin 
Published: December 2021

AbstractBACKGROUNDBSA is the most commonly used metric for body size indexation of echocardiographic measures, but its use in patients who are underweight or obese is questioned (BMI<18.5 kg/m2or ≥30 kg/m2, respectively).AIMSWe aim to use survival analysis to identify an optimal body size indexation metric for echocardiographic measures that would be a better predictor of survival than body surface area (BSA) regardless of body mass index (BMI).METHODSAdult patients with no prior valve replacement were selected from the National Echocardiography Database Australia. Survival analysis was performed for echocardiographic measures both unindexed and indexed to different body size metrics, with 5-year cardiovascular mortality as the primary endpoint.RESULTSIndexation of echocardiographic measures (left ventricular end-diastolic diameter [n=230,109] and mass [n=224,244], left atrial area [n=90,596], aortic sinus diameter [n=90,805], right atrial area [n=59,516], right ventricular diameter [n=3,278], right ventricular outflow tract diameter [n=1,406]) by BSA had better prognostic performance vs unindexed measures (normal weight/overweight: average C-statistic 0.661 vs 0.620; underweight: C-statistic 0.650 vs 0.648; obese: C-statistic 0.627 vs 0.614). Indexation by other body size metrics (lean body mass, height, and/or weight raised to different powers) did not improve prognostic performance versus BSA by a clinically relevant magnitude (average C-statistic increase ≤0.02), with smaller differences in other BMI subgroups.CONCLUSIONSIndexing measures of cardiac and aortic size by BSA improves prognostic performance regardless of BMI, and no other body size metric has a clinically meaningful better performance.
MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19
Authors: Lazari Lucas C. , Zerbinati Rodrigo M. , Rosa-Fernandes Livia , Santiago Veronica Feijoli , Rosa Klaise F. , Angeli Claudia B. , Schwab Gabriela , Palmieri Michelle , Sarmento Dmity J. S. , Marinho Claudio R. F. , Almeida Janete Dias , To Kelvin , Giannecchini Simone , Wrenger Carsten , Sabino Ester C. , Martinho Herculano , Lindoso José A. L. , Durigon Edison L. , Braz-Silva Paulo H. , Palmisano Giuseppe 
Published: December 2021

AbstractThe SARS-CoV-2 infections are still imposing a great public health challenge despite the recent developments in vaccines and therapy. Searching for diagnostic and prognostic methods that are fast, low-cost and accurate is essential for disease control and patient recovery. The MALDI-TOF mass spectrometry technique is rapid, low cost and accurate when compared to other MS methods, thus its use is already reported in the literature for various applications, including microorganism identification, diagnosis and prognosis of diseases. Here we developed a prognostic method for COVID-19 using the proteomic profile of saliva samples submitted to MALDI-TOF and machine learning algorithms to train models for COVID-19 severity assessment. We achieved an accuracy of 88.5%, specificity of 85% and sensitivity of 91.5% for classification between mild/moderate and severe conditions. Then, we tested the model performance in an independent dataset, we achieved an accuracy, sensitivity and specificity of 67.18, 52.17 and 75.60% respectively. Saliva is already reported to have high inter-sample variation; however, our results demonstrates that this approach has the potential to be a prognostic method for COVID-19. Additionally, the technology used is already available in several clinics, facilitating the implementation of the method. Further investigation using a bigger dataset is necessary to consolidate the technique.
Weakening of the cognition and height association from 1957 to 2018: findings from four British birth cohort studies
Authors: Bann David , Wright Liam , Davies Neil M , Moulton Vanessa 
Published: December 2021

BackgroundOn average taller individuals have been repeatedly found to have higher scores on cognitive assessments, yet it is unclear whether the magnitude of this association has systematically changed across time. Recent studies have found that this association can be explained by genetic factors, yet this does not preclude the influence of environmental or social factors that affect the genome. We tested whether the association between cognition and height has weakened across time.MethodsWe used four British birth cohorts (born 1946c, 1958c, 1970c, and 2001) with comparable data available at 10/11 and 14/17 years (N = 41,418). Height was measured at each age, and cognition via verbal reasoning (10/11 years) and vocabulary/comprehension scales (14/16 years) and via mathematical tests at both ages. We constructed age-adjusted height and cognition measures and converted cognition measures to ridit scores to aid interpretation. We then used linear and quantile regression to investigate whether cross-sectional associations between cognition and height differed in each cohort, sequentially adjusting for sex, childhood socioeconomic position, and maternal and paternal height.ResultsTaller participants had higher mean cognitive assessment scores in childhood and adolescence, yet the associations were weaker in later (1970c and 2001c) cohorts – after adjustment for sex the mean difference in height comparing the highest with lowest verbal cognition scores at 10/11 years was 0.57 SD (95% CI = 0.44, 0.7) in the 1946c, 0.59 SD (0.52, 0.65) in the 1958c, 0.47 SD (0.41, 0.53) in the 1970c, 0.30 SD (0.23, 0.37) in the 2001c. This pattern of change in association was observed across all specifications (ages 10/11 and 14/16 years, and for each cognition measure used), and was robust to adjustment for social class and parental height, and modelling of plausible missing-not-at-random scenarios. Quantile regression suggested that these average differences were driven by differences in the lower centiles of height. This pattern was most evident in older cohorts – for example, in 1958c, the difference in height was 0.73 SD (0.64, 0.82) at the 10th centile, yet 0.46 SD (0.34, 0.57) at the 90th centile.ConclusionAssociations between height and cognitive assessment scores in childhood-adolescence weakened by at least half from 1957 to 2018. These results support the notion that environmental and social change can markedly weaken associations between cognition and other traits.
Software Application Profile: SUMnlmr, an R package that facilitates flexible and reproducible non-linear Mendelian randomisation analyses
Authors: Mason Amy M. , Burgess Stephen 
Published: December 2021

AbstractMotivationMendelian randomisation methods that estimate non-linear exposure—outcome relationships typically require individual-level data. This package implements non-linear Mendelian randomisation methods using stratified summarised data, facilitating analyses where individual-level data cannot easily be shared, and additionally increasing reproducibility as summarised data can be reported. Dependence on summarised data means the methods are independent of the form of the individual- level data, increasing flexibility to different outcome types (such as continuous, binary, or time-to- event outcomes).ImplementationSUMnlmr is available as an R package (version 3.1.0 or higher).General featuresThe package implements the previously proposed fractional polynomial and piecewise linear methods on stratified summarised data that can either be estimated from individual-level data using the package or supplied by a collaborator. It constructs plots to visualise the estimated exposure— outcome relationship, and provides statistics to assess preference for a non-linear model over a linear model.AvailabilityThe package is freely available from GitHub [https://github.com/amymariemason/SUMnlmr].
Genetic Subtypes of Smoldering Multiple Myeloma are associated with Distinct Pathogenic Phenotypes and Clinical Outcomes
Authors: Bustoros Mark , Anand Shankara , Sklavenitis-Pistofidis Romanos , Redd Robert , Boyle Eileen M. , Zhitomirsky Benny , Dunford Andrew J , Tai Yu-Tzu , Chavda Selina J , Boehner Cody , Neuse Carl Jannes , Rahmat Mahshid , Dutta Ankit , Casneuf Tineke , Verona Raluca , Kastritis Efstathis , Trippa Lorenzo , Stewart Chip , Walker Brian A. , Davies Faith E. , Dimopoulos Meletios-Athanasios , Bergsagel Leif , Yong Kwee , Morgan Gareth J. , Aguet François , Getz Gad , Ghobrial Irene M. 
Published: December 2021

AbstractSmoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrated 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identified six distinct genetic subtypes. These subtypes were differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three subtypes were associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification model.
Human pathogenic RNA viruses establish non-competing lineages by occupying independent niches
Authors: Mutz Pascal , Rochman Nash D. , Wolf Yuri I. , Faure Guilhem , Zhang Feng , Koonin Eugene V. 
Published: December 2021

AbstractMany pathogenic viruses are endemic among human populations and can cause a broad variety of diseases, some potentially leading to devastating pandemics. How virus populations maintain diversity and what selective pressures drive population turnover, is not thoroughly understood. We conducted a large-scale phylodynamic analysis of 27 human pathogenic RNA viruses spanning diverse life history traits in search of unifying trends that shape virus evolution. For most virus species, we identify multiple, co-circulating lineages with low turnover rates. These lineages appear to be largely noncompeting and likely occupy semi-independent epidemiological niches that are not regionally or seasonally defined. Typically, intra-lineage mutational signatures are similar to inter-lineage signatures. The principal exception are members of the familyPicornaviridae, for which mutations in capsid protein genes are primarily lineage-defining. The persistence of virus lineages appears to stem from limited outbreaks within small communities so that only a minor fraction of the global susceptible population is infected at any time. As disparate communities become increasingly connected through globalization, interaction and competition between lineages might increase as well, which could result in changing selective pressures and increased diversification and/or pathogenicity. Thus, in addition to zoonotic events, ongoing surveillance of familiar, endemic viruses appears to merit global attention with respect to the prevention or mitigation of future pandemics.SignificanceNumerous pathogenic viruses are endemic in humans and cause a broad variety of diseases, but what is their potential of causing new pandemics? We show that most human pathogenic RNA viruses form multiple, co-circulating lineages with low turnover rates. These lineages appear to be largely noncompeting and occupy distinct epidemiological niches that are not regionally or seasonally defined, and their persistence appears to stem from limited outbreaks in small communities so that a minor fraction of the global susceptible population is infected at any time. However, due to globalization, interaction and competition between lineages might increase, potentially leading to increased diversification and pathogenicity. Thus, endemic viruses appear to merit global attention with respect to the prevention of future pandemics.
Extend Mixed Models to Multi-layer Neural Networks for Genomic Prediction Including Intermediate Omics Data
Authors: Zhao Tianjing , Zeng Jian , Cheng Hao 
Published: December 2021

ABSTRACTWith the growing amount and diversity of intermediate omics data complementary to genomics (e.g., DNA methylation, gene expression, and protein abundance), there is a need to develop methods to incorporate intermediate omics data into conventional genomic evaluation. The omics data helps decode the multiple layers of regulation from genotypes to phenotypes, thus forms a connected multi-layer network naturally. We developed a new method named NN-LMM to model the multiple layers of regulation from genotypes to intermediate omics features, then to phenotypes, by extending conventional linear mixed models (“LMM”) to multi-layer artificial neural networks (“NN”). NN-LMM incorporates intermediate omics features by adding middle layers between genotypes and phenotypes. Linear mixed models (e.g., pedigree-based BLUP, GBLUP, Bayesian Alphabet, single-step GBLUP, or single-step Bayesian Alphabet) can be used to sample marker effects or genetic values on intermediate omics features, and activation functions in neural networks are used to capture the nonlinear relationships between intermediate omics features and phenotypes. NN-LMM had significantly better prediction performance than the recently proposed single-step approach for genomic prediction with intermediate omics data. Compared to the single-step approach, NN-LMM can handle various patterns of missing omics measures, and allows nonlinear relationships between intermediate omics features and phenotypes. NN-LMM has been implemented in an open-source package called “JWAS”.
Novel Multiple Sclerosis Agents-Induced Cardiotoxicity
Authors: Al-Yafeai Zaki , Abduljabbar Hamzah , Carvajal-González Alexander , Arvas Muhammed , Patel Shaun , Patel Neev 
Published: December 2021

AbstractBackgroundEmerging novel therapeutics have been developed to hamper the progression of multiple sclerosis. However, the adverse events related to these new agents remain largely unknown. Therefore, we sought to investigate the cardiovascular complications of these drugs.MethodsUtilizing data from the U.S. Food and Drug Administration Adverse Events Reporting System, we comprehensively evaluated the cardiovascular complications of the newly FDA approved anti-multiple sclerosis agents. Disproportionality signal analysis was conducted by measuring reporting odds ratio (ROR) with 95% confidence interval of all the cardiovascular adverse events adverse events since approval till 2021.ResultsAfter vetting the newly approved agents for multiple sclerosis, CD20 and CD25 inhibitors and sphingosine-1-phosphate receptors agonists were the latest approved medications for multiple sclerosis since 2015. Two CD20 (ocrelizumab, ofatumumab) and one CD25 inhibitors (daclizumab) were significantly associated with multiple cardiovascular adverse events. Among all the cardiotoxic events; coronary artery disease, cardiac failure and atrial fibrillation were the most predominant among CD20 or CD25 blockers. Interestingly, Sphingosine-1-phosphate receptors agonists showed much fewer reported cardiac adverse events. However, fingolimod and siponimod were associated with significant bradycardia.ConclusionsOur data revealed the new agents prescribed for multiple sclerosis have cardiotoxic effects, including not only the known adverse effects observed effects for S1P receptor modulators but also undefined cardiovascular complications associated with CD20 and CD25 inhibitors. These findings potentially instigate further studies to personalize prescribing these agents for multiple sclerosis based on patient’s cardiovascular profile.
A quantitative evaluation of aerosol generation from upper airway suctioning during tracheal intubation and extubation sequences
Authors: Shrimpton AJ , Brown JM , Cook TM , Penfold CM , Reid JP , Pickering AEP 
Published: December 2021

AbstractBackgroundOpen respiratory suctioning is considered to be an aerosol generating procedure (AGP) and laryngopharyngeal suction, used to clear secretions during anaesthesia, is widely managed as an AGP. It is uncertain whether such upper airway suctioning should be designated an aerosol generating procedure (AGP) because of a lack of both aerosol and epidemiological evidence of risk.AimTo assess the relative risk of aerosol generation by upper airway suction during tracheal intubation and extubation in anaesthetised patients.MethodsProspective environmental monitoring study in ultraclean operating theatres to assay aerosol concentration during intubation and extubation sequences including upper airway suctioning for patients undergoing surgery (n=19 patients). An Optical Particle Sizer (particle size 300nm-10μm) was used to sample aerosol from 20cm above the patient’s mouth. Baseline recordings (background, tidal breathing and volitional coughs) were followed by intravenous induction of anaesthesia with neuromuscular blockade. Four periods of oropharyngeal suction were performed with a Yankauer sucker: pre-laryngoscopy, post-intubation and pre- and post-extubation.FindingsAerosol from breathing was reliably detected (65[39-259] particles.L−1 (median[IQR])) above background (4.8[1-7] particles.L−1, p<0.0001 Friedman). The procedure of upper airway suction was associated with much lower average concentrations of aerosol than breathing (6.0[0-12] particles.L−1, P=0.0007) and was indistinguishable from background (P>0.99). The peak aerosol concentration recorded during suctioning (45[30-75] particles.L−1) was much lower than both volitional coughs (1520[600-4363] particles.L−1, p<0.0001, Friedman) and tidal breathing (540[300-1826] particles.L−1, p<0.0001, Friedman).ConclusionThe procedure of upper airway suction during airway management is associated with no higher concentration of aerosol than background and much lower than breathing and coughing. Upper airway suction should not be designated as a high risk AGP.
Diagnostic Strategies to Identify Patients with Genetic Salt-Losing Tubulopathies
Authors: Wan Elizabeth , Iancu Daniela , Ashton Emma , Siew Keith , Mohidin Barian , Sung Chih-Chien , Nagano China , Bockenhauer Detlef , Lin Shih-Hua , Nozu Kandai , Walsh Stephen B 
Published: December 2021

AbstractBackgroundDistinguishing patients with the inherited salt-losing tubulopathies (SLT), Gitelman or Bartter syndrome (GS or BS) from wildtype (WT) patients who purge is difficult. We decided to identify clinical/biochemical characteristics which correctly classify SLT.Methods66 patients with possible SLT were recruited to a prospective observational cohort study at the UCL Renal Tubular Clinic (London). 31 datapoints were recorded on each patient. All patients were genotyped for pathogenic mutations in genes which cause SLT; 39 patients had pathogenic variants in genes causing SLT. We obtained similar datasets from cohorts in Taipei and Kobe; the combined dataset comprised 419 patients, 291 had genetically confirmed SLT. London and Taipei datasets were combined to train machine learning (ML) algorithms. These were then tested on the Kobe dataset to determine the best biochemical predictors of genetic confirmation of SLT.ResultsSingle biochemical variables (e.g. plasma renin) were significantly, but inconsistently different between SLT and WT, in the London and combined cohorts.A decision table algorithm using serum bicarbonate and urinary sodium excretion (FENa) achieved a classification accuracy of 74%. A simpler algorithm based on the FECl achieved a classification accuracy of 61%. This was superior to all of the single biochemical variables identified previously.
SARS-CoV-2 T cell responses are expected to remain robust against Omicron
Authors: Ahmed Syed Faraz , Quadeer Ahmed Abdul , McKay Matthew R. 
Published: December 2021

ABSTRACTOmicron, the most recent SARS-CoV-2 variant of concern (VOC), harbours multiple mutations in the spike protein that were not observed in previous VOCs. Initial studies suggest Omicron to substantially reduce the neutralizing capability of antibodies induced from vaccines and previous infection. However, its effect on T cell responses remains to be determined. Here, we assess the effect of Omicron mutations on known T cell epitopes and report data suggesting T cell responses to remain broadly robust against this new variant.
Microarray-based detection of antibodies against SARS-CoV-2 proteins, common respiratory viruses and type I interferons
Authors: Savvateeva Elena , Filippova Marina , Valuev-Elliston Vladimir , Nuralieva Nurana , Yukina Marina , Troshina Ekaterina , Baklaushev Vladimir , Ivanov Alexander , Gryadunov Dmitry 
Published: December 2021

AbstractA microarray-based assay to detect IgG and IgM antibodies against betacoronaviruses (SARS-CoV-2, SARS, MERS, OC43, and HKU1), other respiratory viruses and type I interferons (IFN-Is) was developed. This multiplex assay was applied to track antibody cross-reactivity due to previous contact with similar viruses and to identify antibodies against IFN-Is as the markers for severe COVID-19. In total, 278 serum samples from convalescent plasma donors, COVID-19 patients in the intensive care unit (ICU) and patients who recovered from mild/moderate COVID-19, vaccine recipients, prepandemic and pandemic patients with autoimmune endocrine disorders, and a heterogeneous prepandemic cohort including healthy individuals and chronically ill patients were analyzed. The anti-SARS-CoV-2 microarray results agreed well with the ELISA results. Regarding ICU patients, autoantibodies against IFN-Is were detected in 10.5% of samples, and 10.5% of samples were found to simultaneously contain IgM antibodies against more than two different viruses. Cross-reactivity between IgG against the SARS-CoV-2 nucleocapsid and IgG against the OC43 and HKU1 spike proteins was observed, resulting in positive signals for the SARS-CoV-2 nucleocapsid in prepandemic samples from patients with autoimmune endocrine disorders. The presence of IgG against the SARS-CoV-2 nucleocapsid in the absence of IgG against the SARS-CoV-2 spike RBD should be interpreted with caution.
Identification of Genetic Loci Simultaneously Associated with Multiple Cardiometabolic Traits
Authors: Wood Alexis C. , Arora Amit , Newell Michelle , Bland Victoria L. , Zhou Jin , Pirastu Nicola , Ordovas Jose M. , Klimentidis Yann C. 
Published: December 2021

AbstractBackground and AimsCardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits.Methods and ResultsWe conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high-density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N=356,574–456,823). Multiple loci reached genome-wide levels of significance (N=145-333) for each trait, but only four loci (in/nearVEGFA, GRB14-COBLL1, KLF14, andRGS19-OPRL1)were associated with risk across all seven traits (P<5×10−8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses.GRB14-COBLL1showed the most consistent replication, revealing nominally significant associations (P<0.05) with all traits except DBP.ConclusionsOur analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.