Unknown

Dataset Information

Identifying therapeutic targets for breast cancer: insights from systematic Mendelian randomization analysis.


ABSTRACT:

Background

Breast cancer (BC) exhibits a high incidence rate, imposing a substantial burden on healthcare systems. Novel drug targets are urgently needed for BC. Mendelian randomization (MR) has gained widespread application for identifying fresh therapeutic targets. Our endeavor was to pinpoint circulatory proteins causally linked to BC risk and proffer potential treatment targets for BC.

Methods

Through amalgamating protein quantitative trait loci from 2,004 circulating proteins and comprehensive genome-wide association study data from the Breast Cancer Association Consortium, we conducted MR analyses. Employing Steiger filtering, bidirectional MR, Bayesian colocalization, phenotype scanning, and replication analyses, we further solidified MR study outcomes. Additionally,

SUBMITTER: Yao T 

PROVIDER: S-EPMC11180768 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature