Thilo Dörk

PRANA: A Deep Learning Method for Adapting Polygenic Risk Scores to Diverse Ethnic Groups

PRANA adapts polygenic risk scores to non-European populations, improving predictive accuracy by 5%-20% in South Asian, East Asian, and Ashkenazi Jewish populations.

Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification

The paper uses case-control data from over 400,000 women to classify BRCA1 and BRCA2 variants, finding high consistency with ClinVar annotations for 785 previously unclassified variants.

Exome sequencing identifies HELB as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer

This study uses exome sequencing to identify HELB as a novel susceptibility gene for non-high grade serous epithelial ovarian cancer, with a strong association found in genetic analyses.

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

This study identifies genetic signals associated with age at menarche, highlights genes involved in pubertal development, and links reproductive timing to later life disease risk.

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

This study identifies seven novel genetic loci associated with high-grade serous ovarian cancer risk using a large-scale GWAS and develops polygenic scores for improved risk prediction.

Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction

This study examines differences in polygenic risk score distributions across European populations and shows how country-specific calibration can improve breast cancer risk prediction.

Exome sequencing identifies novel susceptibility genes and defines the contribution of coding variants to breast cancer risk.

The paper uses whole-exome sequencing data to identify novel breast cancer susceptibility genes and assess the contribution of coding variants to breast cancer risk.

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

The paper assesses breast cancer risks linked to rare missense variants in five susceptibility genes using logistic and mixture models, finding varying risk contributions across genes.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes

The paper identifies breast cancer risk variants associated with tumor subtypes and shows their differential effects on luminal and non-luminal subtypes.

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies new candidate susceptibility genes for breast and ovarian cancer

This study improves transcriptome-wide association studies by integrating pleiotropy-guided methods with GWAS data to identify new cancer susceptibility genes.

Rare copy number variants (CNVs) and breast cancer risk

The paper analyzes rare copy number variants (CNVs) in breast cancer cases and controls, identifying associations with known and novel susceptibility loci.

Population based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high grade serous ovarian cancer

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

This study identifies 32 new breast cancer susceptibility loci through GWAS, with associations varying by tumor subtype and genetic correlations among subtypes.

Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes

This study fine-maps 150 breast cancer risk regions to identify 178 high confidence target genes using genomic and functional annotations.

Shared heritability and functional enrichment across six solid cancers

This study quantifies genetic correlations between six solid cancers and other diseases using GWAS data, finding shared heritability and functional enrichment in regulatory regions.