Non-coding genetic variants underlying higher prostate cancer risk in men of African ancestry

Prostate cancer (PrCa) incidence and severity vary across ancestries; men of African ancestry (AA) are more likely to be diagnosed and die from PrCa than those of European ancestry (EA). Current polygenic risk scores, even from multi-ancestry GWAS, do not fully capture population-specific genetic mechanisms, especially those mediated by non-coding regulatory single nucleotide polymorphisms (SNPs). Using a deep learning model of prostate enhancers, we identify ~ 2000 SNPs, potentially affecting enhancer function, with higher alternate allele frequency in AA men, that may affect PrCa risk. These SNPs may promote cancer via two mechanisms: increased enhancer activity leading to immune suppression and telomere elongation or decreased activity causing de-differentiation and apoptosis inhibition. Identified SNPs predominantly modulate binding of key transcription factors such as FOX, HOX, and AR - the first was experimentally validated. Incorporating these SNPs into a polygenic risk score improves PrCa risk assessment beyond existing GWAS-identified variants.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-11-20
DOI
https://doi.org/10.1038/s41467-025-64631-4
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Non-coding genetic variants underlying higher prostate cancer risk in men of African ancestry

Sridhar Hannenhalli, Shan Li, Padma Sheila Rajagopal, David Y. Takeda et al.
Nature Communications
Prostate Cancer Diagnosis and Treatment
article

Non-coding genetic variants underlying higher prostate cancer risk in men of African ancestry

Sridhar Hannenhalli, Shan Li, Padma Sheila Rajagopal, David Y. Takeda, Dimple Notani, Nirmala SundarRaj, Arashdeep Singh, Kaniz Fatema
article en

Abstract

Prostate cancer (PrCa) incidence and severity vary across ancestries; men of African ancestry (AA) are more likely to be diagnosed and die from PrCa than those of European ancestry (EA). Current polygenic risk scores, even from multi-ancestry GWAS, do not fully capture population-specific genetic mechanisms, especially those mediated by non-coding regulatory single nucleotide polymorphisms (SNPs). Using a deep learning model of prostate enhancers, we identify ~ 2000 SNPs, potentially affecting enhancer function, with higher alternate allele frequency in AA men, that may affect PrCa risk. These SNPs may promote cancer via two mechanisms: increased enhancer activity leading to immune suppression and telomere elongation or decreased activity causing de-differentiation and apoptosis inhibition. Identified SNPs predominantly modulate binding of key transcription factors such as FOX, HOX, and AR - the first was experimentally validated. Incorporating these SNPs into a polygenic risk score improves PrCa risk assessment beyond existing GWAS-identified variants.

Nature CommunicationsVol. 16(1)
National Institutes of Health (US), National Centre for Biological Sciences (IN), National Cancer Institute (US), Center for Cancer Research (US)
National Institutes of Health, National Cancer Institute
Openalex Percentile: Top 49%
Prostate Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.