Palle Duun Rohde

This study evaluates polygenic risk scores (PRS) for colorectal cancer (CRC) screening, showing they stratify risk independently of ancestry and sex but offer limited additional predictive value when combined with FIT.

This paper uses a polygenic risk score to show that genetic liability for endometriosis is linked to pain, inflammatory, and metabolic traits in both sexes.

This study uses functionality-informed fine mapping to identify causal variants and pathways contributing to coronary artery disease risk using GWAS summary statistics from over a million individuals.

This study uses Mendelian randomization to explore causal relationships between psoriasis, type 2 diabetes, and inflammatory bowel disease, finding positive associations for psoriasis and inverse for type 2 diabetes with ulcerative colitis.

This study uses genetic correlations to prioritize drug groups for repurposing in type 2 diabetes, identifying several drug classes with significant genetic relevance.

The paper introduces gact, an R package that integrates GWAS summary statistics with genomic resources to identify causal genes and pathways, demonstrating its application in coronary artery disease and type 2 diabetes.

This study investigates how genetic variation affects phenotypic responses to diet and aging in Drosophila melanogaster, finding significant genotype-by-diet and genotype-by-age interactions.

This study identifies 21 infertility loci and over 400 reproductive hormone loci through GWAS across multiple cohorts, finding limited genetic correlation between reproductive hormones and infertility.

This study identifies genetic regulation of plasma proteins in children and adolescents, finding obesity- and age-dependent pQTLs and potential causal links to cardiometabolic traits.

This paper evaluates Bayesian Linear Regression derived gene set tests, showing they outperform MAGMA in detecting genetic associations with complex diseases.

This study evaluates Bayesian Linear Regression models for gene set prioritization in complex diseases, showing improved performance in identifying T2D-related pathways using multi-trait analysis.

The paper expands the R package qgg with Bayesian Linear Regression models for genomic analysis of complex traits using individual data or GWAS summary statistics.

This paper evaluates Bayesian Linear Regression models with BayesC and BayesR priors as fine mapping tools, comparing them to existing methods and showing improved F1 scores and credible set properties.

The paper identifies five genetic loci associated with postpartum hemorrhage through a meta-analysis and links them to progesterone receptor binding sites and related traits.

The paper introduces a deep learning framework for polygenic risk score prediction, showing improved performance over traditional methods for various diseases.

The paper uses Drosophila metabolomics to show metabolites predict organismal phenotypes better than genomic data in some traits.

This study performs a GWAS on medication-use data from 335,744 UK Biobank individuals, identifying 59 genetic loci and showing that medication-use is a highly polygenic trait with 18% heritability from common variants.

The paper introduces the qgg R package for large-scale quantitative genetic analyses, including genetic parameter estimation and predictive modeling of complex traits using human height data from the UK Biobank.