A flexible modeling and inference framework for estimating variant effect sizes from GWAS summary statistics DOI Creative Commons
Jeffrey P. Spence, Nasa Sinnott-Armstrong, Themistocles L. Assimes

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: April 19, 2022

Abstract Genome-wide association studies (GWAS) have highlighted that almost any trait is affected by many variants of relatively small effect. On one hand this presents a challenge for inferring the effect single variant as signal-to-noise ratio high This compounded when combining information across in polygenic scores predicting values. other hand, large number contributing provides an opportunity to learn about average behavior encoded distribution sizes. Many approaches looked at aspects problem, but no method has unified inference effects individual with sizes while requiring only GWAS summary statistics and properly accounting linkage disequilibrium between variants. Here we present flexible, unifying framework combines infer uses improve estimation We also develop variational (VI) scheme perform efficient under framework. show useful constructing (PGSs) outperform state-of-the-art. Our modeling easily extends jointly multiple cohorts, where building PGSs using additional cohorts differing ancestries improves predictive accuracy portability. investigate inferred distributions traits find these ranging over orders magnitude, contrast assumptions implicit commonly-used statistical genetics methods.

Language: Английский

Methylation Clocks Do Not Predict Age or Alzheimer’s Disease Risk Across Genetically Admixed Individuals DOI Open Access
Sebastián Cruz-González,

Esther Gu,

Lissette Gomez

et al.

Published: Jan. 31, 2025

Epigenetic clocks that quantify rates of aging from DNA methylation patterns across the genome have emerged as a potential biomarker for risk age-related diseases, like Alzheimer’s disease (AD), and environmental social stressors. However, not been validated in genetically diverse cohorts. Here we evaluate set 621 AD patients matched controls African American, Hispanic, white co-horts. The are less accurate at predicting age admixed individuals, especially those with substantial ancestry, than cohort. also do consistently identify acceleration cases compared to controls. Methylation QTL (meQTL) commonly influence CpGs clocks, these meQTL significantly higher frequencies genetic ancestries. Our results demonstrate often fail predict beyond their training populations suggest avenues improving portability.

Language: Английский

Citations

1
Fine-scale population structure and widespread conservation of genetic effect sizes between human groups across traits DOI Creative Commons
Sile Hu, Lino A. F. Ferreira, Sinan Shi

et al.

Nature Genetics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Abstract Understanding genetic differences between populations is essential for avoiding confounding in genome-wide association studies and improving polygenic score (PGS) portability. We developed a statistical pipeline to infer fine-scale Ancestry Components applied it UK Biobank data. identify population structure not captured by widely used principal components, stratification correction geographically correlated traits. To estimate the similarity of effect sizes groups, we ANCHOR, which estimates changes predictive power an existing PGS distinct local ancestry segments. ANCHOR infers highly similar (estimated correlation 0.98 ± 0.07) participants African European 47 53 quantitative phenotypes, suggesting that gene–environment gene–gene interactions do play major roles poor cross-ancestry transferability these traits United Kingdom, providing optimism shared causal mutations operate similarly different populations.

Language: Английский

Citations

1
Lottery, luck, or legacy. A review of “The Genetic Lottery: Why DNA matters for social equality” DOI Creative Commons
Graham Coop, Molly Przeworski

Evolution, Journal Year: 2022, Volume and Issue: 76(4), P. 846 - 853

Published: Feb. 28, 2022

A book review of "The genetic lottery: why DNA matters for social equality." (Princeton University Press, 2021) by Kathryn Paige Harden.

Language: Английский

Citations

32
Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa DOI Creative Commons
Michelle S. Kim,

Daphne Naidoo,

Ujani Hazra

et al.

Genome biology, Journal Year: 2022, Volume and Issue: 23(1)

Published: Sept. 13, 2022

Abstract Background Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates prostate cancer in men African descent, much what is known about genetics comes from populations European descent. To understand how genetic predictions perform different we evaluated test characteristics PRS three previous using data UK Biobank a novel dataset 1298 cases 1333 controls Ghana, Nigeria, Senegal, South Africa. Results Allele frequency differences cause predicted risks to vary populations. However, natural selection primary driver these differences. Comparing continental datasets, find that case vs. control status are more effective for individuals (AUC 0.608–0.707, OR 2.37–5.71) than 0.502–0.585, 0.95–2.01). Furthermore, leverage information Americans yield modest AUC odds ratio improvements sub-Saharan individuals. These were larger West Africans Africans. Finally, existing largely unable predict whether develop aggressive forms cancer, as specified by tumor stages or Gleason scores. Conclusions Genetic poorly if study sample does match ancestry original GWAS. built GWAS may be inadequate application non-European perpetuate health disparities.

Language: Английский

Citations

32
A flexible modeling and inference framework for estimating variant effect sizes from GWAS summary statistics DOI Creative Commons
Jeffrey P. Spence, Nasa Sinnott-Armstrong, Themistocles L. Assimes

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: April 19, 2022

Abstract Genome-wide association studies (GWAS) have highlighted that almost any trait is affected by many variants of relatively small effect. On one hand this presents a challenge for inferring the effect single variant as signal-to-noise ratio high This compounded when combining information across in polygenic scores predicting values. other hand, large number contributing provides an opportunity to learn about average behavior encoded distribution sizes. Many approaches looked at aspects problem, but no method has unified inference effects individual with sizes while requiring only GWAS summary statistics and properly accounting linkage disequilibrium between variants. Here we present flexible, unifying framework combines infer uses improve estimation We also develop variational (VI) scheme perform efficient under framework. show useful constructing (PGSs) outperform state-of-the-art. Our modeling easily extends jointly multiple cohorts, where building PGSs using additional cohorts differing ancestries improves predictive accuracy portability. investigate inferred distributions traits find these ranging over orders magnitude, contrast assumptions implicit commonly-used statistical genetics methods.

Language: Английский

Citations

31