Sonia H Shah

This study identifies latent regulatory programs from disease-associated variants to reveal biological mechanisms and clinical subtypes in complex diseases.

This paper benchmarks parameters for TWAS signature-matching to prioritize drug candidates using GWAS data and CMap, showing sensitivity to cell line choice and proposing a best-practice framework.

This study shows glycaemic variability, not just hyperglycaemia, increases heart muscle dysfunction and myocardial injury risk in diabetes using genetic and experimental models.

The paper describes the AMBER program's cohort profile, collecting questionnaire data on antidepressant response from Generation Scotland participants to develop phenotypes and link with biological data.

This study evaluates polygenic risk scores (PRS) in dilated cardiomyopathy (DCM) patients, finding higher PRS in those without monogenic variants and TTN-related DCM, suggesting polygenic contributions.

GWASHub is a cloud-based platform for GWAS meta-analysis that automates data handling, QC, and analysis workflows to improve reproducibility and reduce researcher burden.

This study identifies key considerations for accrediting polygenic risk score testing through stakeholder consultations and proposes checklists for quality assessment.

This paper introduces an unsupervised framework to identify genetic subtypes of disease by clustering variant co-occurrence, applied to type 2 diabetes and asthma without using phenotype data.

This study explores South Asian Australians' health beliefs about cardiovascular disease and genomic testing, finding positive attitudes toward genomic testing but concerns about effectiveness and access.

This study finds that genetic risk for major depression is associated with higher cardiovascular disease risk in females but not males, even without a depression diagnosis.

The paper identifies regions of the human genome under cellular constraint by analyzing chromatin accessibility across cell types, showing their predictive power for functional loci and applications in variant identification and drug discovery.

This study identifies 667 genetic loci associated with lipid species and links 186 of them to coronary artery disease through integrative lipidomics and genomics.

This study compares gene expression responses to statins and antidepressants, finding shared immune pathway perturbations and associations with monocyte and platelet metrics.

This paper uses Mendelian randomisation to examine the causal effect of antihypertensive drugs on psychiatric disorders, finding an increased schizophrenia risk with lower ACE gene expression.

This study conducts a large GWAS on heart failure, identifying 12 genetic loci with associations to CAD, atrial fibrillation, and reduced left ventricular function, and provides causal evidence for several risk factors.

The paper replicates 55,000 DNA methylation QTLs using two cohorts and finds enrichment of trans mQTLs in specific genomic regions and complex traits.