Joshua C. Denny

Shared trans-ancestry architecture of HLA-mediated disease risk in the All of Us Research Program

The paper analyzes HLA variation across six ancestry groups in the All of Us Research Program to identify HLA-phenotype associations and assess ancestry-specific genetic architecture.

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us

The paper performs large-scale GWAS and RVAS on 392,030 whole genomes from All of Us, identifying 49,863 associations and 193 novel pLoF gene-phenotype links through meta-analysis with UK Biobank.

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

A One-Shot Lossless Algorithm for Cross-Cohort Learning in Mixed-Outcomes Analysis

This paper introduces mixWAS, a one-shot, lossless algorithm for integrating distributed EHR datasets to identify cross-cohort genetic associations across multiple outcomes.

Phenome-Wide Association of APOE Alleles in the All of Us Research Program

This study performs a phenome-wide association analysis of APOE alleles in the All of Us Research Program, identifying significant associations with various health outcomes and highlighting sex and ancestry differences.

Frequency of pharmacogenomic variation and medication exposures among All of Us Participants

The paper assesses pharmacogenomic variation and medication exposures in a diverse cohort using whole genome sequencing and EHR data, finding high prevalence of actionable variants and previously unreported alleles.

A genome-wide mutational constraint map quantified from variation in 76,156 human genomes

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

Inferring compound heterozygosity from large-scale exome sequencing data

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

The Phenotype-Genotype Reference Map: Improving biobank data science through replication.

The paper introduces a phenotype-genotype reference map for replicating GWAS results in biobank data and demonstrates its utility in detecting data corruption and assessing reproducibility.

Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

This study compares meta-analysis and pooled analysis approaches in cross-cohort GWAS of lipid measures, finding method-specific variants and implications for TRE design and analysis.

Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

This study identifies 20 genome-wide significant loci associated with serum IgA levels and finds genetic correlations with various immune and metabolic traits.

A scalable EHR-based approach for phenotype discovery and variant interpretation for hereditary cancer genes

This study uses EHR data to identify gene-phenotype associations and develop phenotype risk scores for variant interpretation in hereditary cancer genes.

Arrhythmia variant associations and reclassifications in the eMERGE-III sequencing study

The paper identifies pathogenic variants in arrhythmia genes in eMERGE-III participants and reclassifies variants of uncertain significance using functional studies.

Trans-ancestry genome-wide association study identifies novel genetic mechanisms in rheumatoid arthritis

This study conducts a trans-ancestry GWAS of rheumatoid arthritis, identifying 124 loci, 34 novel, and shows improved polygenic risk score performance across populations.

Neptune: An environment for the delivery of genomic medicine

Neptune delivers structured genomic data to EHR systems through customizable reports and variant reanalysis, supporting over 15,000 clinical reports.

LabWAS: novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks

This study conducts a meta-analysis of EHR-based lab measurements across two biobanks, identifying novel genetic associations and validating EHR data as a source for GWAS.

Multi-ancestry Genome- and Phenome-wide Association Studies of Diverticular Disease in Electronic Health Records with Natural Language Processing enriched phenotype algorithm

This study uses NLP to identify diverticular disease from EHRs and performs GWAS and PheWAS across multiple ancestries to find genetic risk variants and clinical associations.

A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease

The paper identifies a missense variant in the MARC1 gene associated with protection against cirrhosis and lower liver enzyme and cholesterol levels.

A polygenic and phenotypic risk prediction for Polycystic Ovary Syndrome evaluated by Phenome-wide association studies

This study develops a polygenic and phenotypic risk score for PCOS using EHR data, showing improved detection and identifying shared metabolic and endocrine comorbidities.

Developing and Evaluating Mappings of ICD-10 and ICD-10-CM Codes to PheCodes

The paper develops and evaluates mappings from ICD-10 and ICD-10-CM codes to PheCodes, showing high coverage and reproducibility for chronic diseases.

Cox regression increases power to detect genotype-phenotype associations in genomic studies using the electronic health record

This study shows Cox regression improves power to detect genotype-phenotype associations in EHR-linked genomic studies compared to logistic regression.

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9

The paper analyzes genetic variants at the PCSK9 locus to assess their phenotypic effects on lipid levels and disease outcomes, finding concordance with PCSK9 inhibitor trials for myocardial infarction but discordance for type 2 diabetes.

WikiMedMap: Expanding the Phenotyping Mapping Toolbox Using Wikipedia

WikiMedMap maps phenotype strings to clinical vocabularies using Wikipedia, outperforming existing tools in matching accuracy.

Temporal changes in genetic admixture are linked to heterozygosity and health diagnoses in humans

The paper examines how changes in genetic admixture over time affect heterozygosity and health outcomes in a southeastern U.S. population.

Genetic variants related to antihypertensive targets inform drug efficacy and side effects

The paper uses genetic variants to investigate side effects and repurposing potential of antihypertensive drugs, finding a link between calcium channel blockers and increased diverticulosis risk.

PROTEIN-CODING VARIANTS IMPLICATE NOVEL GENES RELATED TO LIPID HOMEOSTASIS CONTRIBUTING TO BODY FAT DISTRIBUTION

This study identifies 15 common and 9 low-frequency protein-coding variants associated with body fat distribution, implicating novel genes related to lipid homeostasis and type 2 diabetes.

Using Topic Modeling via Non-negative Matrix Factorization to Identify Relationships between Genetic Variants and Disease Phenotypes: A Case Study of Lipoprotein(a) (LPA)

The paper uses non-negative matrix factorization to analyze electronic health records and identify associations between a genetic variant in LPA and disease topics, finding positive and negative correlations with cardiovascular diseases and lung cancer.

A rare variant on a common risk haplotype of HFE causes increased risk of hereditary hemochromatosis

The paper identifies HFE E168Q as a novel pathogenic variant associated with hereditary hemochromatosis using Phenotype Risk Scores and validates its mechanism through experimental assays.

Pulling the covers in electronic health records for an association study with self-reported sleep behaviors

This study uses EHR data to analyze sleep behaviors and their associations with health outcomes, finding links between weekend sleep patterns and mental health.

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies

This paper introduces SAIGE, a method that improves the accuracy of genetic association tests in unbalanced case-control studies by using saddlepoint approximation, and demonstrates its effectiveness on UK Biobank data.