Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.

Journal of human genetics - 1 Sept 2023

Lin Bochao Danae, Pries Lotta-Katrin, van Os Jim, Luykx Jurjen J, Rutten Bart P F, Guloksuz Sinan

Abstract excerpt

The current study was conducted to provide a general guidance for model specifications in polygenic risk score (PRS) analyses of the UK Biobank, such as adjusting for covariates (i.e. age, sex, recruitment centers, and genetic batch) and the number of principal components (PCs) that need to be included. To cover behavioral, physical and mental health outcomes, we evaluated three continuous outcomes (BMI, smoking,...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biological Specimen Banks
Share to Depressive Disorder, Major

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome-Wide Association Study

Share to Multifactorial Inheritance

Share to Phenotype

Share to Risk Factors

Share to United Kingdom

Source

Identifiers

PMID: 37188914
DOI: 10.1038/s10038-023-01161-1

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.PMID 37188914Read ↗

A systematic framework for assessing the clinical impact of polygenic risk scoresSemantic proximity Read ↗

Identifying and characterizing disease subpopulations that most benefit from polygenic risk scores.Semantic proximity Read ↗

Calculating Polygenic Risk Scores (PRS) in UK Biobank: A Practical Guide for EpidemiologistsSemantic proximity Read ↗

Significant sparse polygenic risk scores across 813 traits in UK Biobank.Semantic proximity Read ↗

Selecting Covariates for Genome-Wide Association StudiesSemantic proximity Read ↗

Understanding polygenic models, their development and the potential application of polygenic scores in healthcare.Semantic proximity Read ↗

Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives.Semantic proximity Read ↗

Polygenic risk modeling with latent trait-related genetic components.Semantic proximity Read ↗

From Basic Science to Clinical Application of Polygenic Risk Scores: A Primer.Semantic proximity Read ↗

Benchmarking Polygenic Risk Score Model Assumptions: towards more accurate risk assessmentSemantic proximity Read ↗

Polygenic risk modeling with latent trait-related genetic componentsSemantic proximity Read ↗

Improving reporting standards for polygenic scores in risk prediction studies.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.