Genetic Associations and Epidemiology

This paper introduces DEEN, a deep learning method that improves polygenic risk score prediction by modeling both linear and non-linear SNP effects, showing better performance on UK Biobank and All of Us datasets.

The paper develops an age-informative polygenic score for kidney function and shows it improves prediction of eGFR and decline compared to an age-agnostic score.

This paper improves polygenic score prediction for underrepresented groups using transfer learning methods implemented in the GPTL R-package, showing better performance than traditional approaches.

This study identifies genetic relationships between substance use disorders and externalizing/internalizing psychopathology, finding that internalizing contributes uniquely to SUD risk.

This paper uses Mendelian randomization to investigate causal relationships between soluble ST2, heart failure, and sepsis, finding no evidence of direct causation.

The paper shows that phenotype scale choice affects GxE signals in biobank data, with log scaling revealing meaningful effects and explaining a significant portion of PGSxSex interactions.

This study evaluates how polygenic risk scores can optimize screening programs to reduce premature deaths by tailoring screening ages based on genetic risk.

This paper improves genetic discovery and polygenic risk prediction for respiratory diseases by analyzing multiple traits and ancestries, identifying novel loci and developing a new polygenic risk score method.

This study evaluates genetic disease prediction methods using simulations, finding random forests most accurate, followed by logistic regression and naive Bayes, while neural networks performed worse.

The paper shows that per-allele effect sizes of genetic variants in European populations are better predicted by African MAF than European MAF.

The paper identifies 508 CKD-associated genetic loci, prioritizes 651 kidney genes, and highlights novel CKD genes like CA12 with functional consequences.

The paper identifies a causal link between chronic pain genetics and late-onset asthma through the nervous system using genome-wide association and Mendelian randomization analyses.

The paper identifies risk loci for acute respiratory distress syndrome (ARDS) by analyzing protein quantitative trait loci (pQTLs) from GWAS of sepsis-related biomarkers.

This study identifies genetic loci regulating fatty acid levels in adipose tissue and links them to metabolic and cardiovascular traits.

This study investigates challenges in case-only analysis using polygenic risk scores for gene-environment interaction detection, showing false positives due to model misspecification and collider bias in large biobanks.

The paper introduces a polygenic risk score framework that improves type 2 diabetes risk prediction by accounting for clinical subtypes and pathway-specific contributions.

The paper integrates genomics and transcriptomics data from human heart samples to identify regulatory mechanisms linking genetic variation to dilated cardiomyopathy.

This paper introduces a new causal inference method, the transmission mean test (TMT), for identifying genetic loci associated with child phenotypes using parent-child trio data.

This study uses whole-genome sequencing to identify genetic variants associated with brain imaging phenotypes, finding significant associations at both variant and gene levels.

This study identifies bidirectional genetic links between glycemic traits and brain phenotypes using Mendelian randomization and validates findings in UK Biobank data.

This study examines genetic nurturing effects using polygenic scores in parent-offspring trios and identifies biases when parental phenotypes are included.

The paper introduces the Archipelago method to visualize variant set association test statistics by assigning genomic coordinates to P values, enabling combined visualization of set-level and individual variant associations.

The paper identifies rs3769823 as a functional variant near CASP8 influencing its expression in a cell-type specific manner and associated with multiple cancers.

The paper integrates perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits, finding 546 significant genes enriched for immune response and cellular signaling.

The paper evaluates EHR-based phenotyping accuracy in the All of Us Research Program to optimize statistical power for genetic association testing, finding disparities in accuracy across racial groups.

The paper investigates why the 9p21.3 CAD risk locus fails to replicate in African ancestry cohorts, finding ancestry-specific LD and haplotype diversity explain the lack of association.

This study identifies a shared genetic regulator linking metabolism and addiction-related behavior in mice and humans through a common enhancer regulating Eed/Me3 and EED/ME3.

This paper identifies multi-omic pleiotropy factors for peripheral artery disease by analyzing genetic, transcriptomic, and proteomic data across PAD, T2D, and CAD.

This paper introduces MR-CARV, a two-sample Mendelian randomization framework integrating common and rare variants to assess the causal effect of HDL-C on preeclampsia risk, showing improved statistical power and precision.