Evidence map›Paper›PMID 41053791›Full record

ArticleGenome medicine2025

Genetic underpinnings of the heterogeneous impact of obesity on lipid levels and cardiovascular disease.

Daeeun Kim, Heather M Highland, Roelof A J Smit, Micah R Hysong, Victoria L Buchanan, Kristin L Young, Chi Zhao, Cassandra N Spracklen, Tuomas O Kilpeläinen, Boya Guo and 22 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

32 authors.

Daeeun KimDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. daeeun.kim@unc.edu.
Heather M HighlandDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Roelof A J SmitCharles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Micah R HysongDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Victoria L BuchananDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Kristin L YoungDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Chi ZhaoDepartment of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA.
Cassandra N SpracklenDepartment of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA.
Tuomas O KilpeläinenNovo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
Boya GuoDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Burcu F DarstDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Yanwei CaiDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Zhe WangCharles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jessica LundinDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Sonja I BerndtDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, USA.
JoAnn E MansonDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Eirini MarouliBarts and The London School of Medicine and Dentistry, William Harvey Research Institute, Queen Mary University of London, London, UK.
Leslie LangeDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Ethan LangeDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Myriam FornageBrown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
Christopher R GignouxDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Christopher A HaimanDepartment of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
Stephen S RichCenter for Public Health Genomics, University of Virginia Charlottesville, Charlottesville, VA, USA.
Steven BuyskeDepartment of Genetics, Rutgers University, Piscataway, NJ, USA.
Ruth J F LoosCharles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Charles KooperbergDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Ulrike PetersDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Christy L AveryDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Penny Gordon-LarsenDepartment of Nutrition, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Mariaelisa GraffDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Laura M RaffieldDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Kari E NorthDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Kari.E.North@uth.tmc.edu.

Funding

Leveraging multi-omics approaches to examine metabolic challenges of obesity in relation to cardiovascular diseasesR01HL143885 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AVERY, CHRISTY LEIGH, GORDON-LARSEN, PENNY · 2019 to 2022
$8.9M
PAGE III: Population Architecture using Genomics and EpidemiologyR01HG010297 · NHGRI · RUTGERS, THE STATE UNIV OF N.J. · PI GIGNOUX, CHRISTOPHER R, MATISE, TARA C. · 2019 to 2022
$6.5M
Gene-Environment Interactions and Weight GainR01HD057194 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY, NORTH, KARI E. · 2008 to 2019
$5.9M
Hispanic Latino Lipid ConsortiumR01HL142302 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Jennifer Below, JOSEPH MCCORMICK · 2018 to 2026
$5.8M
Integrative Approaches to Identifying Function and Clinical Significance of Adiposity Susceptibility GenesR01DK122503 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Anne Justice, Ching-Ti Liu · 2020 to 2026
$4.5M
Leveraging metabolic pathways and gene expression data to propel understanding of severe obesity in a vulnerable and understudied populationR01DK139598 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Jennifer Below, PENNY GORDON-LARSEN · 2024 to 2026
$2.1M
American Heart Association 903805Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD057194NCI NIH HHS Intramural Research ProgramNHGRI NIH HHS R01 HG010297NHGRI NIH HHS R01HG010297NHLBI NIH HHS R01 HL142302NHLBI NIH HHS R01HL142302NHLBI NIH HHS R01 HL143885NICHD NIH HHS R01 HD057194NIDDK NIH HHS R01 DK122503NIDDK NIH HHS R01DK122503NIDDK NIH HHS R01 DK139598Novo Nordisk Foundation Center for Basic Metabolic Research NNF22OC0074128
6 · The paper itself

Abstract

backgroundObesity is thought to increase cardiovascular disease (CVD) risk partly through dyslipidemia. Yet, obesity's effects on dyslipidemia are not uniform. Understanding the shared genetic basis between obesity and lipid traits can provide insight into this heterogeneity and its implications for CVD risk.

methodsWe examined local genetic correlations between three lipid measures [high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and triglycerides (TG)] and body mass index (BMI) using genome-wide association study summary statistics from European ancestry UK Biobank participants. We identified genomic loci with opposing genetic effects on obesity and dyslipidemia risk (protective BMI-lipid loci) and those with concordant directions for both obesity and dyslipidemia risk (adverse BMI-lipid loci). Gene-based association analyses were used to prioritize potential causal genes. We then constructed polygenic risk scores for BMI (PRS

resultsAmong 2495 regions, we identified 789 HDL, 26 LDL, and 494 TG loci with significant local genetic correlation with BMI (including overlapping loci). Of these, 3 HDL, 10 LDL, and 8 TG loci showed protective correlations. Gene-based analyses prioritized 18 candidate causal genes. The protective PRS

conclusionsIdentifying and validating genomic loci with shared genetic signals between BMI and lipid levels further supports the importance of genetics in defining the heterogeneous impact of obesity on dyslipidemia and CVD.

Indexed as

Cardiovascular DiseasesLipidsObesityBody Mass IndexFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMiddle AgedMultifactorial InheritancePolymorphism, Single NucleotideTriglyceridesLipidsTriglyceridesBMI-lipid pleiotropyHeterogeneities in obesityLocal genetic correlationMendelian randomizationPolygenic risk scores

Identifiers

PMID41053791
PMCPMC12502452

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