Mark O. Goodarzi

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.

This paper develops and validates multi-ancestry polygenic risk scores for type 2 diabetes prediction and complications across diverse populations.

This paper conducts a multi-ancestry time-to-event GWAS to identify genetic variants associated with incident cardiovascular disease in people with type 2 diabetes, finding three novel loci and confirming known CAD variants.

This study identifies 31 plasma proteins and expands genetic loci associated with PCOS, highlighting metabolic and hormonal influences and polygenic risk effects on cardio-metabolic outcomes.

The paper identifies a gene-diet interaction modifying the association between macronutrient intake and glycemic traits, highlighting challenges in detecting such interactions due to measurement error and sample size.

The paper performs whole genome sequence association analysis of fasting glucose and insulin levels in diverse cohorts, identifying 22 significant variants across 16 gene regions, including rare variants.

The paper identifies 15 SNPs associated with androgen production in theca cells and a haplotype on chromosome 12q13.2 linked to PCOS and AMH levels.

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.

This study identifies genetic variants associated with body fat distribution traits in Hispanics/Latinos and finds ancestry-specific associations.

The paper identifies rare non-coding variants from whole genome sequencing in the TOPMed program, showing they contribute significantly to type 2 diabetes heritability.

The paper identifies LOC157273 as a negative regulator of PPP1R3B and glycogen deposition in human hepatocytes, linking it to type 2 diabetes risk.

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

The paper identifies genetic variants affecting HbA1c levels in multi-ancestry cohorts, showing ancestry-specific impacts on diabetes diagnosis via HbA1c.

This study performs a large-scale genome-wide meta-analysis of PCOS cases and identifies genetic loci associated with PCOS and related traits, showing shared genetic architecture across different diagnostic criteria.