Matthew Zawistowski

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.

This study investigates the clinical consequences of a genetic predisposition to lower white blood cell counts using a polygenic score and finds associations with bone marrow biopsy outcomes and treatment responses.

The Michigan Genomics Initiative links genotypes with electronic clinical records in Michigan Medicine patients, showing higher disease prevalence and validating GWAS findings.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

This study performs a genome-wide association analysis of hemorrhoidal disease in 944,133 individuals, identifying 102 risk loci and linking them to vascular and tissue development pathways.

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.

Meta-MultiSKAT improves power for region-based genetic association tests by meta-analyzing multiple correlated phenotypes using summary statistics and variance component tests.

This study constructs and evaluates polygenic risk scores for skin cancer subtypes using the Michigan Genomics Initiative and UK Biobank data, and develops a visual catalog to compare PRS methods.

This study identifies 147 genetic loci associated with eGFR, including 53 novel ones, and finds sex-specific effects on kidney function.

The paper identifies loss-of-function variants affecting liver-related blood traits that reduce CVD risk without increasing metabolic disease risk, highlighting potential therapeutic targets.

The paper analyzes rare variants to uncover mutation rate heterogeneity in the human genome, identifying genomic features that influence mutation rates.

This study uses polygenic risk scores (PRS) for cancers in a phenome-wide association study (PheWAS) to identify associations with multiple phenotypes, finding significant links to both cancer and non-cancer diagnoses.