Evidence map›Paper›PMID 38948697›Full record

ArticlebioRxiv : the preprint server for biology2024

Conditional frequency spectra as a tool for studying selection on complex traits in biobanks.

Roshni A Patel, Clemens L Weiß, Huisheng Zhu, Hakhamanesh Mostafavi, Yuval B Simons, Jeffrey P Spence, Jonathan K Pritchard

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Roshni A PatelDepartment of Genetics, Stanford University School of Medicine, Stanford, CA.ORCID 0000-0002-8574-031X
Clemens L WeißStanford Cancer Institute Core, Stanford University School of Medicine, Stanford, CA.
Huisheng ZhuDepartment of Biology, Stanford University, Stanford, CA.
Hakhamanesh MostafaviCenter for Human Genetics and Genomics, New York University School of Medicine, New York, NY.ORCID 0000-0002-1060-2844
Yuval B SimonsDepartment of Medicine, University of Chicago, Chicago, IL.
Jeffrey P SpenceDepartment of Genetics, Stanford University School of Medicine, Stanford, CA.
Jonathan K PritchardDepartment of Genetics, Stanford University School of Medicine, Stanford, CA.

Funding

Integration of genetic association mapping and functional data to elucidate genetic mechanisms of diseaseR01HG008140 · NHGRI · STANFORD UNIVERSITY · PI JONATHAN K PRITCHARD · 2016 to 2026
$7.3M
New methods for constructing and evaluating polygenic scoresR01HG011432 · NHGRI · STANFORD UNIVERSITY · PI PRITCHARD, JONATHAN K · 2020 to 2023
$3.3M
NHGRI NIH HHS R01 HG008140NHGRI NIH HHS R01 HG011432
6 · The paper itself

Abstract

Natural selection on complex traits is difficult to study in part due to the ascertainment inherent to genome-wide association studies (GWAS). The power to detect a trait-associated variant in GWAS is a function of frequency and effect size - but for traits under selection, the effect size of a variant determines the strength of selection against it, constraining its frequency. To account for GWAS ascertainment, we propose studying the joint distribution of allele frequencies across populations, conditional on the frequencies in the GWAS cohort. Before considering these conditional frequency spectra, we first characterized the impact of selection and non-equilibrium demography on allele frequency dynamics forwards and backwards in time. We then used these results to understand conditional frequency spectra under realistic human demography. Finally, we investigated empirical conditional frequency spectra for GWAS variants associated with 106 complex traits, finding compelling evidence for either stabilizing or purifying selection. Our results provide insight into polygenic score portability and other properties of variants ascertained with GWAS, highlighting the utility of conditional frequency spectra.

Identifiers

PMID38948697
PMCPMC11212903

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.