Nasa Sinnott-Armstrong

This study conducts a GWAS of Lyme disease, identifying five genetic loci and linking it to post-infectious diseases like Bell palsy and joint pain.

This study evaluates adherence to NASEM recommendations on population descriptors in GWAS papers using a large language model-based toolkit, finding improvements over time but limited impact post-report publication.

The paper identifies estrogen-modulated SNVs associated with breast cancer risk and shows their interaction with reproductive factors using polygenic risk scores.

This study identifies 26 risk loci for fibromyalgia through a genome-wide association analysis of 2.5 million individuals, revealing genetic links to neural functions and chronic pain disorders.

The paper identifies genetic variants associated with diurnal glucose levels and their role in type 2 diabetes risk.

This study identifies 39 genetic loci shared between cannabis use and sleep traits through a meta-analysis of 152,807 cases and 220,272 controls.

The paper identifies a disease-associated motor neuron state in a mouse ALS model that precedes cell death and links it to human ALS genetic risk factors.

This study conducts a genome-wide association study (GWAS) of ME/CFS, identifying eight genetic loci associated with the disease, suggesting involvement of immune and neurological processes.

The paper shows that social factors of health reduce heritability estimates for anthropometric traits when included as covariates in genetic analyses.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

This study identifies and characterizes rRNA variants in human tissues and cancer, revealing tissue-specific ribosome subtypes and cancer-specific ribosome variations.

This study identifies ADRA2A as a major risk locus for Raynaud's syndrome through genome-wide association analysis and functional validation in vascular smooth muscle cells.

The paper introduces LipocyteProfiler, a high-throughput microscopy assay to profile lipid-storing cells and identifies cellular programs linked to metabolic traits like insulin resistance and lipodystrophy.

The paper performs metabolite GWAS on UK Biobank data to investigate pleiotropy and genetic correlation, finding pathway-relevant genes and contrasting variant effects.

The paper identifies upstream regulators of immune genes in human T cells and maps their regulatory network, revealing its enrichment for immune disease variants.

The paper tests for genetic interactions affecting causal variant effect sizes in gene expression and LDL-C across European and African American populations, finding significant evidence in gene expression but not LDL-C.

The paper identifies a genetic variant in SCGB1D2 that increases Lyme disease susceptibility and shows that the wild-type protein inhibits Borrelia burgdorferi growth more effectively than the variant.

This paper introduces a framework for estimating variant effect sizes from GWAS summary statistics, improving polygenic score accuracy by jointly inferring individual variant effects and distributional properties.

This paper develops a statistical method to identify gene co-essentiality, creating a genome-wide functional module almanac that predicts functions for 102 uncharacterized genes and validates key findings.

This study performs GWAS on three molecular traits, identifying core genes and pathways while highlighting a polygenic background contributing to trait variance.

This study identifies sex-specific genetic variants and causal links for testosterone using UK Biobank data and Bayesian modeling.

This paper introduces SMAC-seq, a method for long-range chromatin accessibility mapping in eukaryotes, and demonstrates its application in yeast.

This study identifies genetic variants associated with nightmares and finds strong genetic links between nightmares and psychiatric and sleep traits.

UK Biobank genetics of 38 blood and urine lab tests yields 1,857 independent loci; combining biomarker and disease polygenic scores improves FinnGen prediction of incident renal failure and alcoholic cirrhosis.

This paper evaluates transcriptome-wide association studies (TWAS) for causal gene prioritization, showing its strengths and limitations in identifying causal genes at GWAS loci.

The paper introduces HiDRA, a method for high-resolution functional analysis of regulatory regions, identifying 13,000 driver elements and linking them to disease-associated variants.

This study identifies genetic risk loci for narcolepsy, showing enrichment in immune cells and suggesting autoimmune modulation via T cell receptor chains and influenza-A infection.

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.

Omni-ATAC improves ATAC-seq by reducing background noise and enabling analysis of frozen tissues, revealing disease-associated DNA element activities in human brain structures.

The paper identifies driver genes in prostate cancer by analyzing convergence of non-coding mutations in regulatory regions using 3D chromatin interactions and genomic data.