Honghuang Lin

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.

This study identifies 44 genetic loci associated with pulmonary artery diameter across COPD and population-based cohorts, highlighting shared causal variation between pulmonary and systemic vascular biology.

The paper identifies genes associated with obesity risk loci by integrating genetic and transcriptomic data from blood and brain tissues.

The paper introduces MultiSTAAR, a statistical framework for multi-trait rare variant analysis in WGS studies, identifying new lipid trait associations in diverse populations.

The paper conducts GWAS on brain volumes, identifies genetic loci, and develops polygenic scores with cross-ancestry predictive ability and causal links to neuropsychiatric disorders.

The paper investigates the association of common and rare variants with Alzheimer's Disease in 13,371 diverse individuals using whole-genome sequencing, identifying significant genetic loci and population-specific associations.

This study uses whole genome sequence data from the ADSP to identify 17 significant variants in five genomic regions associated with Alzheimer's disease.

The paper determines the cryo-EM structure of activated S1PR4, revealing mechanisms of ligand recognition and Gi coupling to aid in developing safer S1PR4 agonists.

The paper analyzes inflammation biomarkers using whole-genome sequencing from the TOPMed consortium, identifying both single-variant and rare variant associations with inflammatory traits.

This paper presents a strategy to jointly analyze 20,504 whole-exome sequencing samples from nine studies, generating high-quality variant calls and addressing batch effects from different capture kits.

The paper uses deep learning and genome-wide association studies to identify genetic loci associated with right heart structure and function in 40,000 individuals.

This study uses deep learning to analyze aortic dimensions from MRI and identifies genetic loci associated with aortic diameter, highlighting SVIL as a key gene and developing a polygenic score for aneurysm risk.

The paper examines gene expression in blood cells linked to sleep apnea traits, identifying CD1D and RAB20 expression changes reversed by CPAP treatment.

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 identifies 161 genome-wide significant genetic associations for cortical structure traits across 34 brain regions, highlighting key biological pathways and gene functions.

The paper identifies a missense variant in EDEM3 associated with lower blood triglyceride levels and shows EDEM3 deficiency increases LRP1 expression, reducing plasma TG through enhanced lipoprotein uptake.

The paper assesses if genetic risk for atrial fibrillation explains cardioembolic stroke risk using genome-wide data from the Stroke Genetics Network.

The paper describes the quality control and integration of genotype calls from two pipelines for whole genome sequencing data in the Alzheimer’s Disease Sequencing Project, resulting in a high-quality consensus dataset.

This study performs a large GWAS of Alzheimer's disease, identifies four new risk loci, and highlights pathways involving immunity, lipid metabolism, and APP/Aβ processing.

This paper introduces SAPPHO methods to detect pleiotropy in GWAS by modeling shared patterns of genetic associations, finding 16 additional and 124 novel loci in meta-analysis.

This study identifies 47 novel genetic loci associated with PR interval through genome-wide association meta-analysis across multiple populations.