Evidence map›Paper›PMID 26084345›Full record

SynthesisDiabetes care2015

Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.

Hassan S Dashti, Jack L Follis, Caren E Smith, Toshiko Tanaka, Marta Garaulet, Daniel J Gottlieb, Adela Hruby, Paul F Jacques, Jessica C Kiefte-de Jong, Stefania Lamon-Fava and 13 more

Erratum issuedAbstract readMeta-Analysis
In one paragraph

Synthesis in Diabetes care, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Trial
  2. Macronutrient-specific effect of theJournal of lipid research · 2018
    Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
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  10. Observational
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  12. Review
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  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. Off the Clock: From Circadian Disruption to Metabolic Disease.International journal of molecular sciences · 2019
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors.

Hassan S DashtiNutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA hassan.dashti@tufts.edu.
Jack L FollisDepartment of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas, Houston, TX.
Caren E SmithNutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Toshiko TanakaTranslational Gerontology Branch, National Institute on Aging, Baltimore, MD.
Marta GarauletDepartment of Physiology, University of Murcia, Murcia, Spain.
Daniel J GottliebDivision of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA Division of Sleep Medicine, Harvard Medical School, Boston, MA Sleep Disorders Center, VA Boston Healthcare System, Boston, MA.
Adela HrubyDepartment of Nutrition, Harvard School of Public Health, Boston, MA.
Paul F JacquesNutritional Epidemiology Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Jessica C Kiefte-de JongDepartment of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands Global Public Health, Leiden University College, The Hague, the Netherlands.
Stefania Lamon-FavaCardiovascular Nutrition Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Frank A J L ScheerDivision of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA Division of Sleep Medicine, Harvard Medical School, Boston, MA.
Traci M BartzCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA Department of Biostatistics, University of Washington, Seattle, WA.
Leena KovanenDepartment of Mental Health and Substance Abuse Services, National Institute for Health and Welfare (THL), Helsinki, Finland.
Mary K WojczynskiDepartment of Genetics, Washington University School of Medicine, St. Louis, MO.
Alexis C Frazier-WoodU.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX.
Tarunveer S AhluwaliaThe Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark Danish Pediatric Asthma Centre, Gentofte Hospital, The Capital Region, Copenhagen, Denmark.
Mia-Maria PeräläDepartment of Chronic Disease Prevention, National Institute for Health and Welfare (THL), Helsinki, Finland.
Anna JonssonThe Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Taulant MukaDepartment of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.
Ioanna P KalafatiDepartment of Nutrition and Dietetics, Harokopio University, Athens, Greece.
Vera MikkiläDepartment of Food and Environmental Sciences, Division of Nutrition, University of Helsinki, Helsinki, Finland Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
José M OrdovásNutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA Department of Epidemiology, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain Instituto Madrileño de Estudios Avanzados en Alimentación (IMDEA-FOOD), Madrid, Spain.
CHARGE Nutrition Study Group

Funding

UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR024156 · NCRR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2006 to 2011
$53.0M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PETER J TONTONOZ · 2003 to 2026
$40.4M
Genetic and Environmental Determinants of TriglyceridesU01HL072524 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ARNETT, DONNA K · 2002 to 2008
$11.9M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
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
CHS Events Follow-up StudyR01HL080295 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 2009 to 2014
$6.3M
Genomewide Association Study of Lipid Response to Fenofibrate and Dietary FatR01HL091357 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2008 to 2018
$5.8M
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
FHS-SCAN Genome Wide Association Scan for Atherosclerosis Pathway GenesR01HL087700 · NHLBI · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2006 to 2008
$5.4M
Prospective meta-analyses of drug-gene interactions: CHARGE GWAS consortiumR01HL103612 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 2011 to 2014
$5.4M
WGA Study to Identify Genetic Variants Associated with CV Events in CHSR01HL087652 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 2007 to 2009
$5.1M
NCATS NIH HHS UL1 TR000124NCATS NIH HHS UL1TR000124NCRR NIH HHS UL1 RR024156NHLBI NIH HHS HHSN268200800007CNHLBI NIH HHS HHSN268201200036CNHLBI NIH HHS K08 HL112845NHLBI NIH HHS K08-HL-112845-01NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01 HC055222NHLBI NIH HHS N01 HC085079NHLBI NIH HHS N01 HC085080NHLBI NIH HHS N01 HC085081NHLBI NIH HHS N01 HC085082NHLBI NIH HHS N01 HC085083NHLBI NIH HHS N01 HC085086NHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL080295NHLBI NIH HHS R01 HL087652NHLBI NIH HHS R01 HL087700NHLBI NIH HHS R01 HL088215NHLBI NIH HHS R01 HL091357NHLBI NIH HHS R01 HL094806NHLBI NIH HHS R01-HL-094806NHLBI NIH HHS R01 HL103612NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL117078NHLBI NIH HHS R01 HL120393NHLBI NIH HHS U01 HL053916NHLBI NIH HHS U01 HL072524NHLBI NIH HHS U01 HL080295NHLBI NIH HHS U01 HL120393NIDDK NIH HHS DK063491NIDDK NIH HHS P30 DK063491NIDDK NIH HHS R01 DK075681NIDDK NIH HHS R21 DK089378NIDDK NIH HHS R21-DK-089378NIMHD NIH HHS R01 MD009164
6 · The paper itself

Abstract

objectiveCommon circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations. RESEARCH DESIGN AND

methodsWe conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

resultsWe observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h).

conclusionsOur results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

Indexed as

Gene-Environment InteractionAdultAllelesBlood GlucoseCircadian Rhythm Signaling Peptides and ProteinsCohort StudiesDiabetes Mellitus, Type 2Diet, Fat-RestrictedFastingFemaleHumansInsulin ResistanceMaleMiddle AgedMulticenter Studies as TopicObservational Studies as TopicBlood GlucoseCircadian Rhythm Signaling Peptides and Proteins

Identifiers

PMID26084345
PMCPMC4512139

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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.