bluuebunny/crossref_metadata_2025_split huggingface dataset:
The genetic relationships between brain structure and schizophrenia
Authors: Stauffer Eva-Maria , Bethlehem Richard A.I. , Dorfschmidt Lena , Won Hyejung , Warrier Varun , Bullmore Edward T. 
Published: March 2023

ABSTRACTRecent studies suggest shared genetic effects on both schizophrenia and brain structure, but it has been challenging to specify which genes mediate this pleiotropic association. We accessed genome-wide association data on schizophrenia (N=69,369 cases; 236,642 controls), and on three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N=36,843). Using Hi-C-coupled MAGMA, we identified 61 genes that were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to covariance of their MRI metrics, and genetic covariation between schizophrenia and cortical regional phenotypes was greatest in the hubs of the corresponding structural covariance network. Three genomic regions, on chromosomes 3p21, 17q21 and 11p11, were enriched for neurodevelopmental processes and consistently implicated in these pleiotropic associations between schizophrenia and cortical network organization.
Rare Variants in Pharmacogenes Influence Clozapine Metabolism in Individuals with Schizophrenia
Authors: Kappel Djenifer B. , Rees Elliott , Fenner Eilidh , King Adrian , Jansen John , Helthuis Marinka , Owen Michael J. , O’Donovan Michael C. , Walters James T.R. , Pardiñas Antonio F. 
Published: March 2023

AbstractClozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and the occurrence of adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. Our main aim is to investigate whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤1%) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β= -0.054, SE= 0.019, P-value= 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. Gene-based analysis identified rare variants inCYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β= 0.324, SE= 0.124, P= 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations. These results also converge with common variant evidence, particularly in relation toCYP1A2, suggesting the need for further evaluations of the pharmacogenomic makeup of this gene. Overall, our results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.
Importation of Alpha and Delta variants during the SARS-CoV-2 epidemic in Switzerland: phylogenetic analysis and intervention scenarios
Authors: Reichmuth Martina L , Hodcroft Emma B , Althaus Christian L 
Published: March 2023

AbstractThe SARS-CoV-2 pandemic has led to the emergence of various variants of concern (VoCs) that are associated with increased transmissibility, immune evasion, or differences in disease severity. The emergence of VoCs fueled interest in understanding the potential impact of travel restrictions and surveillance strategies to prevent or delay the early spread of VoCs. We performed phylogenetic analyses and mathematical modeling to study the importation and spread of the VoCs Alpha and Delta in Switzerland in 2020 and 2021. Using a phylogenetic approach, we estimated 383-1,038 imports of Alpha and 455-1,347 imports of Delta into Switzerland. We then used the results from the phylogenetic analysis to parameterize a dynamic transmission that accurately described the subsequent spread of Alpha and Delta. We modeled different counterfactual intervention scenarios to quantify the potential impact of border closures and surveillance of travelers on the spread of Alpha and Delta. We found that implementing border closures after the announcement of VoCs would have been of limited impact to mitigate the spread of VoCs. In contrast, increased surveillance of travelers could prove to be an effective measure for delaying the spread of VoCs in situations where their severity remains unclear. Our study shows how phylogenetic analysis in combination with dynamic transmission models can be used to estimate the number of imported SARS-CoV-2 variants and the potential impact of different intervention scenarios to inform the public health response during the pandemic.
Genetic insights into the age-specific biological mechanisms governing human ovarian ageing
Authors: Ojavee Sven E. , Darrous Liza , Patxot Marion , Läll Kristi , Fischer Krista , Mägi Reedik , Kutalik Zoltan , Robinson Matthew R. 
Published: March 2023

AbstractThere is currently little evidence that the genetic basis of human phenotype varies significantly across the lifespan. However, time-to-event phenotypes are understudied and can be thought of as reflecting an underlying hazard, which is unlikely to be constant through life when values take a broad range. Here, we find that 74% of 245 genome-wide significant genetic associations with age at natural menopause (ANM) in the UK Biobank show a form of age-specific effect. Nineteen of these replicated discoveries are identified only by our modelling framework, which determines the time-dependency of DNA variant-age-at-onset associations, without a significant multiple-testing burden. Across the range of early to late menopause, we find evidence for significantly different underlying biological pathways, changes in the sign of genetic correlations of ANM to health indicators and outcomes, and differences in inferred causal relationships. We find that DNA damage response processes only act to shape ovarian reserve and depletion for women of early ANM. Genetically mediated delays in ANM were associated with increased relative risk of breast cancer and leiomyoma at all ages, and with high cholesterol and heart failure for late-ANM women. These findings suggest that a better understanding of the age-dependency of genetic risk factor relationships among health indicators and outcomes is achievable through appropriate statistical modelling of large-scale biobank data.
Targeted proteomic quantitation of NRF2 signaling and predictive biomarkers in HNSCC
Authors: Wamsley Nathan T. , Wilkerson Emily M. , Guan Li , LaPak Kyle M. , Schrank Travis P. , Holmes Brittany J. , Sprung Robert W. , Gilmore Petra Erdmann , Gerndt Sophie P. , Jackson Ryan S. , Paniello Randal , Pipkorn Patrik , Puram Sidarth V. , Rich Jason T. , Townsend Reid R. , Zevallos José P. , Zolkind Paul , Le Quynh-Thu , Goldfarb Dennis , Major M. Ben 
Published: March 2023

AbstractThe NFE2L2/NRF2 oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry (MS)-based targeted proteomics assay based on internal standard triggered parallel reaction monitoring (IS-PRM) to quantify 69 NRF2 pathway components and targets as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved the existing IS-PRM acquisition algorithm, called SureQuant™, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded (FFPE) HNSCCs, NRF2 signaling intensity positively correlated with NRF2 activating mutations and with SOX2 protein expression. PD-L2/CD273 and protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus (HPV) infection status. p16/CDKN2A protein expression positively correlated with the HPV oncogenic E7 protein, and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or FFPE archived tissues in under 90 minutes.
Inequities in hypertension management: an observational cross-sectional study in North-East London using electronic health records
Authors: Rison Stuart , Redfern Oliver , Dostal Isabel , Carvalho Chris , Mathur Rohini , Raisi-Estabragh Zahra , Robson John 
Published: March 2023

ABSTRACTBackgroundHypertension is a key potentially modifiable risk factor for cardiovascular disease-the leading cause of death in the UK. Good blood pressure (BP) control reduces mortality; however, health inequalities may lead to variability in hypertension management.AimTo investigate health inequities related to ethnicity, sex, age, and socio-economic status in the treatment and control of BP in a large cohort of adult patients with hypertension.Design and SettingA cross-sectional cohort study of adults with hypertension registered with general practices in North East London on 1stApril 2019.MethodMultivariable logistic regression was used to estimate associations of demographics and treatment intensity on the following hypertension management indicators: 1) BP recording in last 12 months, 2) BP on age-adjusted target, 3) BP on age-adjusted target and BP recorded in last 12 months.ResultsIn total, 156,296 adults were included. Black/Black British ethnic groups were less likely to have controlled BP than White ethnic groups (OR 0.89, 95% CI = 0.86-0.92). Asian/Asian British ethnic groups were more likely to have controlled blood pressure (OR 1.29, 95% CI = 1.25-1.34). Ethnic differences in control could not be explained by the likelihood of having a recent blood pressure recording, nor by treatment intensity differences. Older adults were more likely to have controlled hypertension than younger patients.ConclusionBlack/Black British and younger people are less likely to have controlled hypertension and may warrant targeted interventions. Possible explanations for these findings are presented and further research is needed on reasons for ethnic differences.HOW THIS FITS INHealth inequities in the management of long-term conditions are widely recognised. This study identifies ethnic, age, gender and deprivation inequities in the control of blood pressure in a large unselected cohort of adults with hypertension in an ethnically diverse and nationally disadvantaged area of London. It confirms previous findings that blood pressure control in Black ethnic groups with hypertension is worse than in White or Asian ethnic groups. These differences were not related to access to blood pressure recording or treatment intensity. Younger adults were less likely to have controlled hypertension than older adults.
Multisensory Flicker Modulates Widespread Brain Networks and Reduces Interictal Epileptiform Discharges in Humans
Authors: Blanpain Lou T. , Chen Emily. , Park James , Walelign Michael Y. , Gross Robert E. , Cabaniss Brian T. , Willie Jon T. , Singer Annabelle C. 
Published: March 2023

AbstractModulating brain oscillations has strong therapeutic potential. However, commonly used non-invasive interventions such as transcranial magnetic or direct current stimulation have limited effects on deeper cortical structures like the medial temporal lobe. Repetitive audio- visual stimulation, or sensory flicker, modulates such structures in mice but little is known about its effects in humans. Using high spatiotemporal resolution, we mapped and quantified the neurophysiological effects of sensory flicker in human subjects undergoing presurgical intracranial seizure monitoring. We found that flicker modulates both local field potential and single neurons in higher cognitive regions, including the medial temporal lobe and prefrontal cortex, and that local field potential modulation is likely mediated via resonance of involved circuits. We then assessed how flicker affects pathological neural activity, specifically interictal epileptiform discharges, a biomarker of epilepsy also implicated in Alzheimer’s and other diseases. In our patient population with focal seizure onsets, sensory flicker decreased the rate interictal epileptiform discharges. Our findings support the use of sensory flicker to modulate deeper cortical structures and mitigate pathological activity in humans.
Neonatal apnea and hypopnea prediction in infants with Robin sequence with neural additive models for time series
Authors: Vetter Julius , Lim Kathleen , Dijkstra Tjeerd M. H. , Dargaville Peter A. , Kohlbacher Oliver , Macke Jakob H. , Poets Christian F. 
Published: March 2023

AbstractNeonatal apneas and hypopneas present a serious risk for healthy infant development. Treating these adverse events requires frequent manual stimulation by skilled personnel, which can lead to alert fatigue. Automatically predicting these adverse events before they occur would enable the use of methods for automatic intervention. In this work, we propose a neural additive model to predict individual events of neonatal apnea and hypopnea and apply it to a physiological dataset from infants with Robin sequence at risk of upper airway obstruction. The dataset will be made publicly available together with this study. Our model achieved an average area under the receiver operating characteristic curve of 0.80 by additively combining information from different modalities of the respiratory polygraphy recording. This permits the prediction of individual apneas and hypopneas up to 15 seconds before they occur. Its additive nature makes the model inherently interpretable, which allowed insights into how important a given signal modality is for prediction and which patterns in the signal are discriminative. For our problem of predicting apneas and hyponeas in infants with Robin sequence, prior irregularities in breathing-related modalities as well as decreases in SpO2levels were especially discriminative.
The role of Late Presenters on HIV-1 transmission clusters in Europe
Authors: Miranda Mafalda N. S. , Pingarilho Marta , Pimentel Victor , Gomes Perpétua , O. Martins Maria do Rosário , Seabra Sofia G. , Kaiser Rolf , Böhm Michael , Seguin-Devaux Carole , Paredes Roger , Bobkova Marina , Zazzi Maurizio , Incardona Francesca , Abecasis Ana B. 
Published: March 2023

AbstractBackgroundInvestigating the role of late presenters (LP) on HIV-1 transmission is important, as they can contribute to the onward spread of HIV-1 virus in the long period before diagnosis, when they are not aware of their HIV statusObjectiveTo describe the clinical and socio-demographic characteristics of HIV-1 infected individuals followed in Europe, to characterize patients in clusters and to compare transmission clusters (TC) in LP vs non-late presenters (NLP) populations.MethodsClinical, socio-demographic and genotypic information from 38531 HIV-1 infected patients was collected from the EuResist Integrated Database (EIDB) between 1981 and 2019. Sequences were aligned using VIRULIGN. Maximum likelihood (ML) phylogenies were constructed using FastTree. Putative transmission clusters were identified using ClusterPicker v1.332. Statistical analyses were performed using R.Results32652 (84·7%) sequences were from subtype B, 3603 (9·4%) were from subtype G, and 2276 (5·9%) were from subtype A. The median age was 33 (IQR: 26·0-41·0) years old and 75·5% of patients were males. The main transmission route was through homosexual (MSM) contact (36·9%) and 86·4% were originated from Western Europe. Most patients were native (84·2%), 59·6% had a chronic infection, and 73·4% had acquired drug resistance (ADR). CD4 count and viral load at diagnosis (log10) presented a median of 341 cells/mm3, and of log10 4·3 copies/mL, respectively. 51·4% of patients were classified as LP and 21·6% patients were inside TCs. Most patients from subtype B (85·6%) were in clusters, compared to subtypes A (5·2%) and G (9·2%). Phylogenetic analyses showed consistent clustering of MSM individuals. In subtype A, patients in TCs were more frequently MSM patients and with a recent infection. For subtype B, patients in TCs were more frequently those with older age (≥ 56), MSM transmission route, originating from Western Europe, migrants, and with a recent infection. For subtype G, patients in TC were more frequently patients with recent infection and migrants. When analysing cluster size, we found that NLP more frequently belonged to large clusters (>8 patients) when compared to LP.ConclusionWhile late presentation is still a threat to HIV-1 transmission, LP individuals are more present either outside or in small clusters, indicating a limited role of late presentation to HIV-1 transmission.
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype
Authors: Shankar Vivek , Yang Xiaoli , Krishna Vrishab , Tan Brent T. , Silva Oscar , Rojansky Rebecca , Ng Andrew Y. , Valvert Fabiola , Briercheck Edward L. , Weinstock David M. , Natkunam Yasodha , Fernandez-Pol Sebastian , Rajpurkar Pranav 
Published: March 2023

AbstractLymphomas vary in terms of clinical behavior, morphology, and response to therapies and thus accurate classification is essential for appropriate management of patients. In this study, using a set of 670 cases of lymphoma obtained from a center in Guatemala City, we propose an interpretable machine learning method, LymphoML, for lymphoma subtyping into eight diagnostic categories. LymphoML sequentially applies steps of (1) object segmentation to extract nuclei, cells, and cytoplasm from hematoxylin and eosin (H&E)-stained tissue microarray (TMA) cores, (2) feature extraction of morphological, textural, and architectural features, and (3) aggregation of per-object features to create patch-level feature vectors for lymphoma classification. LymphoML achieves a diagnostic accuracy of 64.3% (AUROC: 85.9%, specificity: 88.7%, sensitivity: 66.9%) among 8 lymphoma subtypes using only H&E-stained TMA core sections, at a level similar to experienced hematopathologists. We find that the best model’s set of nuclear and cytoplasmic morphological, textural, and architectural features are most discriminative for diffuse large B-cell lymphoma (F1: 78.7%), classic Hodgkin lymphoma (F1 score: 74.5%), and mantle cell lymphoma (F1: 71.0%). Nuclear shape features provide the highest diagnostic yield, with nuclear texture, cytoplasmic, and architectural features providing smaller gains in accuracy. Finally, combining information from the H&E-based model together with the results of a limited set of immunohistochemical (IHC) stains resulted in a similar diagnostic accuracy (accuracy: 85.3%, AUROC: 95.7%, sensitivity: 84.5%, specificity: 93.5%) as with a much larger set of IHC stains (accuracy: 86.1%, AUROC: 96.7%, specificity: 93.2%, sensitivity: 86.0%). Our work suggests a potential way to incorporate machine learning tools into clinical practice to reduce the number of expensive IHC stains while achieving a similar level of diagnostic accuracy.
Detecting post-stroke aphasia using EEG-based neural envelope tracking of natural speech
Authors: De Clercq Pieter , Kries Jill , Mehraram Ramtin , Vanthornhout Jonas , Francart Tom , Vandermosten Maaike 
Published: March 2023

AbstractAfter a stroke, approximately one-third of patients suffer from aphasia, a language disorder that impairs communication ability. The standard behavioral tests used to diagnose aphasia are time-consuming, require subjective interpretation, and have low ecological validity. As a consequence, comorbid cognitive problems present in individuals with aphasia (IWA) can bias test results, generating a discrepancy between test outcomes and everyday-life language abilities. Neural tracking of the speech envelope is a promising tool for investigating brain responses to natural speech. The envelope of speech is crucial for speech understanding, encompassing cues for detecting and segmenting linguistic units, e.g., phrases, words and phonemes. In this study, we aimed to test the potential of the neural envelope tracking technique for detecting language impairments in IWA.We recorded EEG from 27 IWA in the chronic phase after stroke and 22 healthy controls while they listened to a 25-minute story. We quantified neural envelope tracking in a broadband frequency range as well as in the delta, theta, alpha, beta, and gamma frequency bands using mutual information analysis. Besides group differences in neural tracking measures, we also tested its suitability for detecting aphasia at the individual level using a Support Vector Machine (SVM) classifier. We further investigated the required recording length for the SVM to detect aphasia and to obtain reliable outcomes.IWA displayed decreased neural envelope tracking compared to healthy controls in the broad, delta, theta, and gamma band, which is in line with the assumed role of these bands in auditory and linguistic pro-cessing of speech. Neural tracking in these frequency bands effectively captured aphasia at the individual level, with an SVM accuracy of 84% and an area under the curve of 88%. Moreover, we demonstrated that high-accuracy detection of aphasia can be achieved in a time-efficient (5 minutes) and highly reliable manner (split-half reliability correlations between R=0.62 and R=0.96 across frequency bands).Our study shows that neural envelope tracking of natural speech is an effective biomarker for language impairments in post-stroke aphasia. We demonstrated its potential as a diagnostic tool with high reliability, individual-level detection of aphasia, and time-efficient assessment. This work represents a significant step towards more automatic, objective, and ecologically valid assessments of language impairments in aphasia.