Evidence map›Paper›PMID 40296127›Full record

SynthesisGenome biology2025

Multi-ancestry whole genome sequencing analysis of lean body mass.

Xiaoyu Zhang, Kuan-Jui Su, Bodhisattwa Banerjee, Ittai Eres, Yi-Hsiang Hsu, Carolyn J Crandall, Rajashekar Donaka, Zhe Han, Rebecca D Jackson, Hanhan Liu and 16 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

26 authors.

Xiaoyu Zhang *Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA. xyzhang6@bu.edu.
Kuan-Jui Su *Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA. ksu2@tulane.edu.
Bodhisattwa Banerjee *Department of Biochemistry, Larner College of Medicine, University of Vermont, Burlington, VT, 05405, USA.
Ittai Eres *Amgen Inc, South San Francisco, CA, 94080, USA.
Yi-Hsiang HsuHinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA.
Carolyn J CrandallDavid Geffen School of Medicine, University of California, Los Angeles, CA, 90024, USA.
Rajashekar DonakaAzrieli Faculty of Medicine, Bar-Ilan University, 130010, Safed, Israel.
Zhe HanDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Rebecca D JacksonDepartment of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
Hanhan LiuDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Zhe LuoCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Braxton D MitchellDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Chuan QiuCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Qing TianCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Hui ShenCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Ming-Ju TsaiHinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA.
Kerri L WigginsDepartment of Medicine, University of Washington, Seattle, WA, 98195, USA.
Hanfei XuDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.
Michelle YauHinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA.
Lan-Juan ZhaoCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Xiao ZhangCenter for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
May E MontasserDepartment of Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Douglas P Kiel *Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA.
Hong-Wen Deng *Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, 70112, USA.
Ching-Ti Liu *Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA. ctliu@bu.edu.
David Karasik *Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA. karasik@hsl.harvard.edu.ORCID http://orcid.org/0000-0002-8826-0530

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Katherine Teresa Mills · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI HONG-WEN DENG · 2017 to 2026
$24.3M
IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
Studies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD RiskR01HL113323 · NHLBI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI BLANGERO, JOHN, CURRAN, JOANNE E. · 2012 to 2016
$8.2M
Rare variants and NHLBI traits in deeply phenotyped cohortsU01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2017 to 2018
$5.6M
Identification and Functional characterization of a gene influencing LDL-C on 5qR01HL121007 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI MITCHELL, BRAXTON D · 2014 to 2017
$3.1M
Intensive Lifestyle Intervention, Metabolomics, and Risk of Frailty Fracture in Overweight or Obese Patients with Type 2 DiabetesR01AG068232 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI JOHNSON, KAREN C, ZHAO, QI · 2021 to 2025
$3.1M
Systemic contribution of age-associated epigenetic mechanisms to osteoarthritisR01AR075356 · NIAMS · HEBREW REHABILITATION CENTER FOR AGED · PI YAU, MICHELLE SZU-HUEI · 2019 to 2022
$1.7M
NHGRI NIH HHS U54 HG003067NHLBI NIH HHS HHSN268201500014CNHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL113323NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS R01 HL121007NHLBI NIH HHS U01 HL120393NIAMS NIH HHS R01 AR075356NIA NIH HHS R01 AG068232NIA NIH HHS U19 AG055373NIEHS NIH HHS HHSN268201600033CNIGMS NIH HHS P20 GM109036
6 · The paper itself

Abstract

backgroundLean body mass is a crucial physiological component of body composition. Although lean body mass has a high heritability, studies evaluating the genetic determinants of lean mass (LM) have to date been limited largely to genome-wide association studies (GWAS) and common variants. Using whole genome sequencing (WGS)-based studies, we aimed to discover novel genetic variants associated with LM in population-based cohorts with multiple ancestries.

resultsWe describe the largest WGS-based meta-analysis of lean body mass to date, encompassing 10,729 WGS samples from six TOPMed cohorts and the Louisiana Osteoporosis Study (LOS) cohort, measured with dual-energy X-ray absorptiometry. We identify seven genome-wide loci significantly associated with LM not reported by previous GWAS. We partially replicate these associations in UK Biobank samples. In rare variant analysis, we discover one novel protein-coding gene, DMAC1, associated with both whole-body LM and appendicular LM in females, and a long non-coding RNA gene linked to appendicular LM in males. Both genes exhibit notably high expression levels in skeletal muscle tissue. We investigate the functional roles of two novel lean-mass-related genes, EMP2 and SSUH2, in animal models. EMP2 deficiency in Drosophila leads to significantly reduced mobility without altering muscle tissue or body fat morphology, whereas an SSUH2 gene mutation in zebrafish stimulates muscle fiber growth.

conclusionsOur comprehensive analysis, encompassing a large-scale WGS meta-analysis and functional investigations, reveals novel genomic loci and genes associated with lean mass traits, shedding new insights into pathways influencing muscle metabolism and muscle mass regulation.

Indexed as

Body CompositionWhole Genome SequencingAnimalsDrosophila melanogasterFemaleGenome-Wide Association StudyHumansMaleMuscle, SkeletalRNA, Long NoncodingZebrafishRNA, Long Noncoding

Identifiers

PMID40296127
PMCPMC12036297

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.