David Westergaard

This study shows that menstrual phase length variation is linked to daily symptom intensity, highlighting the need for individualized baseline assessments rather than fixed phase assumptions.

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

The paper uses genetic data from Denmark and Britain to infer historical North Sea migrations from the Middle Ages to the Industrial Revolution, identifying distinct population patterns and migration trends.

This study identifies 40 genetic loci associated with placental weight using GWAS in 179,025 children and parents, revealing shared and distinct genetic influences with fetal growth.

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.

This study identifies genetic loci associated with gestational duration and preterm delivery, showing maternal and fetal genetic effects and antagonistic pleiotropy with birth weight.

This study uses Danish registries to estimate heritability and genetic correlations of disease phenotypes and trajectories, identifying novel genetic associations and sex-specific contributions.

This study identifies seven new genetic loci associated with febrile seizures, linking them to fever response and neuronal excitability genes, and suggests potential clinical applications of polygenic risk scores.

This study analyzes 15 million full-text scientific articles to assess text mining's potential, showing it outperforms abstract-only analysis in extracting biological associations.