Evidence map›Paper›PMID 30297966›Full record

ArticleNature genetics2018

Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations.

Steven Gazal, Po-Ru Loh, Hilary K Finucane, Andrea Ganna, Armin Schoech, Shamil Sunyaev, Alkes L Price

Abstract read
In one paragraph

Article in Nature genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 8 pooled it
–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

124 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  11. Evolution of quantitative traits with background selection.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  20. Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article

64 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Steven GazalDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. sgazal@hsph.harvard.edu.ORCID http://orcid.org/0000-0003-4510-5730
Po-Ru LohProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Hilary K FinucaneProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Andrea GannaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Armin SchoechDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Shamil SunyaevProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Alkes L PriceDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. aprice@hsph.harvard.edu.ORCID http://orcid.org/0000-0002-2971-7975

Funding

Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
Powering whole genome sequence-based genetic discovery for common human diseases- Extended 2021-2022.U01HG009088 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIN, XIHONG, NEALE, BENJAMIN MICHAEL · 2016 to 2021
$5.1M
Statistical methods to localize disease heritability and identify biological mechanismsR01MH107649 · NIMH · BROAD INSTITUTE, INC. · PI NEALE, BENJAMIN MICHAEL · 2015 to 2018
$2.9M
Functionally specialized components of disease heritability in ENCODE dataU01HG009379 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L, RAYCHAUDHURI, SOUMYA · 2017 to 2021
$2.5M
Network-based prediction and validation of causal schizophrenia genes and variantsR01MH109978 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI EGGAN, KEVIN C, KELLIS, MANOLIS · 2016 to 2020
$2.1M
From common to rare variant functional architectures of human diseasesK99HG010160 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI GAZAL, STEVEN · 2018 to 2019
$164k
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NHGRI NIH HHS K99 HG010160NHGRI NIH HHS U01 HG009088NHGRI NIH HHS U01 HG009379NIMH NIH HHS R01 MH101244NIMH NIH HHS R01 MH107649NIMH NIH HHS R01 MH109978
6 · The paper itself

Abstract

Common variant heritability has been widely reported to be concentrated in variants within cell-type-specific non-coding functional annotations, but little is known about low-frequency variant functional architectures. We partitioned the heritability of both low-frequency (0.5%≤ minor allele frequency <5%) and common (minor allele frequency ≥5%) variants in 40 UK Biobank traits across a broad set of functional annotations. We determined that non-synonymous coding variants explain 17 ± 1% of low-frequency variant heritability ([Formula: see text]) versus 2.1 ± 0.2% of common variant heritability ([Formula: see text]). Cell-type-specific non-coding annotations that were significantly enriched for [Formula: see text] of corresponding traits were similarly enriched for [Formula: see text] for most traits, but more enriched for brain-related annotations and traits. For example, H3K4me3 marks in brain dorsolateral prefrontal cortex explain 57 ± 12% of [Formula: see text] versus 12 ± 2% of [Formula: see text] for neuroticism. Forward simulations confirmed that low-frequency variant enrichment depends on the mean selection coefficient of causal variants in the annotation, and can be used to predict effect size variance of causal rare variants (minor allele frequency <0.5%).

Indexed as

Gene FrequencyPolymorphism, Single NucleotideSelection, GeneticAllelesBiological Specimen BanksGenetics, PopulationGenetic VariationGenome-Wide Association StudyHumansLinkage DisequilibriumMolecular Sequence AnnotationOpen Reading FramesUnited KingdomWhite People

Identifiers

PMID30297966
PMCPMC6236676

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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.