Laura M. Raffield

The paper examines how social determinants of health modify polygenic risk scores for cardiometabolic diseases and shows that integrating social and genetic factors improves disease prediction.

The paper identifies 16 genetic loci interacting with sleep duration to influence glycemic traits in over 480,000 individuals, revealing distinct biological mechanisms for short and long sleep.

TorchGWAS2 improves genome-wide association testing in related samples by using a deterministic variance-correction algorithm, achieving faster and more powerful results across large-scale omics data.

The paper examines short-term, long-term, and genetic factors influencing human plasma proteome variability using longitudinal cohort data.

The paper integrates social risk factors with genetic risk scores to improve bipolar disorder prediction in the All of Us Research Program, finding social factors have larger effect sizes than genetic risk.

This study integrates polygenic risk scores and proteomic risk scores to improve prediction of complex traits across diverse populations.

The paper identifies genetic drivers of protein change over time using longitudinal proteomics data from MESA, UK Biobank, and CARDIA, finding that baseline adjustment improves replication but may introduce biases.

The paper analyzes expression and splicing quantitative trait loci (e/sQTL) across multiple tissues in the TOPMed dataset and finds that secondary e/sQTL signals are still discoverable, with many GWAS signals colocalizing with these e/sQTL.

HAUDI improves polygenic score construction for admixed populations by efficiently extending the GAUDI method to multi-way admixture with faster computation and better performance.

This paper develops a machine learning framework to impute cross-platform proteomic data, improving replication of epidemiological findings and protein quality scoring.

The paper introduces the expected polygenic risk score (ePRS) framework to address population stratification in polygenic risk score analysis by modeling ancestral makeup, showing it provides equitable risk quantification across diverse populations.

LANTERN improves rare-variant association testing in admixed populations by incorporating local ancestry information, identifying ancestry-specific associations in a cohort of African Americans.

The paper identifies African-specific genetic loci associated with iron status and risk of severe malaria and bacteremia in children, highlighting limited transferability of European polygenic risk scores.

This study investigates the association between mosaic loss of Y chromosome (mLOY) and lung function, emphysema, and epigenetic aging in men across multiple cohorts.

This study identifies a PTER inhibitor that reduces food intake and body weight in mice, linking PTER function to obesity treatment.

The paper maps cis- and trans-eQTLs in blood samples to infer gene regulatory networks and prioritize trait-relevant pathways.

cellSTAAR integrates single-cell ATAC-seq with whole-genome sequencing to enhance power and interpretation of rare variant association tests in non-coding regions.

The paper identifies USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

The paper analyzes circulating metabolites using genome-wide association data from the TOPMed program, identifying 1,778 loci and highlighting sex-specific genetic contributions.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

This study introduces VAE-PRS, a deep learning model that improves polygenic prediction for blood cell traits by capturing interaction effects and outperforming traditional methods in 14 out of 16 traits.

The paper identifies a novel genetic locus OSBPL11 associated with vitamin D levels and cardiometabolic health in African populations through genome-wide analysis.

This study identifies 22 novel gene-sleep duration interaction loci for blood pressure traits across 811,405 individuals, highlighting distinct genetic influences of short and long sleep on cardiovascular health.

This study conducts an epigenome-wide association study (EWAS) meta-analysis of BMI in African American adults, identifying 208 significant CpGs and 54 DMRs associated with BMI, including novel and replicated findings.

The paper identifies genetic and phenotypic correlates of mosaic loss of chromosome Y in blood using whole genome sequencing data from the TOPMed program.

This study identifies gene-environment interactions between excessive daytime sleepiness and genetic variants linked to obstructive sleep apnea severity, revealing novel therapeutic targets.

This study uses whole genome sequencing to identify 18 novel genetic loci associated with plasma fibrinogen levels, including variants more common in African populations and linked to liver-related traits and disease.

This study identifies 17 genetic loci associated with sleep duration and lipid levels, offering potential druggable targets for dyslipidemia in individuals with sleep disturbances.

The paper develops a method to quantify somatic mutation burden in whole-genome sequencing data without paired-tissue samples and identifies genetic and phenotypic correlates of clonal hematopoiesis without known driver mutations.