Evidence map›Paper›PMID 32652930›Full record

SynthesisBMC genomics2020

Detecting fitness epistasis in recently admixed populations with genome-wide data.

Xumin Ni, Mengshi Zhou, Heming Wang, Karen Y He, Uli Broeckel, Craig Hanis, Sharon Kardia, Susan Redline, Richard S Cooper, Hua Tang and 1 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Human genetic admixture.PLoS genetics · 2021
    Review
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

11 authors at 8 institutions in 2 countries.

Xumin NiDepartment of Mathematics, School of Science, Beijing Jiaotong University, Beijing, 100044, China.
Mengshi ZhouDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
Heming WangDivision of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Karen Y HeDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
Uli BroeckelHuman and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI, USA.
Craig HanisDepartment of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA.
Sharon KardiaDepartment of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
Susan RedlineDivision of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Richard S CooperDepartment of Public Health Science, Loyola University Medical Center, Maywood, IL, USA.
Hua TangDepartment of Genetics, Stanford University, Stanford, CA, 94305, USA.
Xiaofeng ZhuDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA. xxz10@case.edu.ORCID http://orcid.org/0000-0003-0037-411X
Case Western Reserve University · USBrigham and Women's Hospital · USBeijing Jiaotong University · CNLoyola University Medical Center · USMedical College of Wisconsin · USStanford University · USThe University of Texas Health Science Center at Houston · USUniversity of Michigan · US

Funding

GENETICS OF HYPERTENSION IN BLACKSR01HL053353 · NHLBI · LOYOLA UNIVERSITY CHICAGO · PI COOPER, RICHARD STANLEY · 1995 to 2013
$8.3M
Phenotypic and Molecular Signatures for Sleep Apnea and Related MorbiditiesR35HL135818 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S. · 2017 to 2023
$7.2M
Leveraging Family Data to Identify Genetic Variants for Sleep ApneaR01HL113338 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LIN, XIHONG, REDLINE, SUSAN S. · 2012 to 2016
$4.4M
Statistical methods for analyzing high-throughput genotype dataR01HG003054 · NHGRI · LOYOLA UNIVERSITY CHICAGO · PI ZHU, XIAOFENG · 2005 to 2017
$3.6M
Statistical Analysis of Large Genomic Data SetsR01HG011052 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI XIAOFENG ZHU · 2020 to 2026
$3.3M
Fine Mapping of Hypertension Genes Detected by Admixture Mapping in the FBPPR01HL086718 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI ZHU, XIAOFENG · 2007 to 2011
$3.3M
Genetic Mechanisms of Arteriosclerosis in Hypertensive SibshipsR01HL119443 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KARDIA, SHARON L · 2014 to 2017
$2.1M
NHGRI NIH HHS HG011052NHGRI NIH HHS HL003054NHGRI NIH HHS R01 HG003054NHGRI NIH HHS R01 HG011052NHLBI NIH HHS HL053353NHLBI NIH HHS HL086718NHLBI NIH HHS R01 HL053353NHLBI NIH HHS R01 HL086718NHLBI NIH HHS R01 HL113338NHLBI NIH HHS R01 HL119443NHLBI NIH HHS R35 HL135818
6 · The paper itself

Abstract

backgroundFitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population.

resultsWe developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10

conclusionsOur analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Indexed as

Epistasis, GeneticGenetic FitnessBlack or African AmericanChromosomes, Human, Pair 1Chromosomes, Human, Pair 10Computer SimulationGenome-Wide Association StudyHumansLinkage DisequilibriumPolymorphism, Single NucleotideReceptors, G-Protein-CoupledADGRL4 protein, humanReceptors, G-Protein-CoupledAdmixed populationAdmixture linkage disequilibriumCo-evolutionDiseases/traitsFitness epistasis

Identifiers

PMID32652930
PMCPMC7353720
OpenAlexW3041164586

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.