Evidence map›Paper›PMID 26857597›Full record

ArticleMolecular psychiatry2016

Assessing the genetic overlap between BMI and cognitive function.

R E Marioni, J Yang, D Dykiert, R Mõttus, A Campbell, CHARGE Cognitive Working Group, G Davies, C Hayward, D J Porteous, P M Visscher and 1 more

Abstract read
In one paragraph

Article in Molecular psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Neurobehavioral correlates of obesity are largely heritable.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Trial
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  14. Sexual dimorphism in the relationship betweenFrontiers in aging neuroscience · 2022
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  17. Body Mass Index and Polygenic Risk for Alzheimer's Disease Predict Conversion to Alzheimer's Disease.The journals of gerontology. Series A, Biological sciences and medical sciences · 2021
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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.

R E MarioniCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
J YangQueensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.ORCID 0000-0003-2001-2474
D DykiertCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
R MõttusCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
A CampbellGeneration Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.ORCID 0000-0003-0198-5078
CHARGE Cognitive Working Group
G DaviesCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
C HaywardGeneration Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
D J PorteousCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
P M VisscherCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
I J DearyCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.

Funding

SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
UC Davis Alzheimer's Disease Core CenterP30AG010129 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI DECARLI, CHARLES · 1991 to 2020
$28.3M
PRECURSORS OF STROKE INCIDENCE AND PROGNOSISR01NS017950 · NINDS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Hugo Javier Aparicio, Jose Rafael Romero · 1985 to 2026
$22.9M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
EPIDEMIOLOGY OF DEMENTIA IN THE FRAMINGHAM STUDYR01AG008122 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, SESHADRI, SUDHA · 1989 to 2015
$14.4M
Temporal Trends, Novel Imaging and Molecular Characterization of Preclinical and Clinical Alzheimer's Disease in the Framingham CohortsR01AG054076 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI DECARLI, CHARLES, SESHADRI, SUDHA · 2016 to 2020
$12.3M
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
Risk Factors, Pathology, and Clinical Expressions of ADRF1AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2014 to 2014
$6.0M
Collaborative GWAS of Dementia, AD and related MRI and Cognitive EndophenotypesR01AG033193 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI SESHADRI, SUDHA · 2009 to 2016
$4.4M
CHARGE: Identifying Risk & Protective SNV for AD in ADSP Case-control SampleU01AG049505 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI SESHADRI, SUDHA · 2014 to 2017
$3.0M
Biotechnology and Biological Sciences Research CouncilChief Scientist Office CZD/16/6Chief Scientist Office CZD/16/6/4Medical Research Council MR/K026992/1NHLBI NIH HHS R01 HL105756NIA NIH HHS P30 AG010129NIA NIH HHS P30 AG010161NIA NIH HHS R01 AG008122NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG033193NIA NIH HHS R01 AG054076NIA NIH HHS RF1 AG015819NIA NIH HHS U01 AG049505NINDS NIH HHS R01 NS017950Wellcome Trust
6 · The paper itself

Abstract

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=-0.11; high body mass index (BMI)-low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)-GREML; independent samples bivariate GCTA-GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of -0.51 (s.e. 0.15) was observed using the same-sample GCTA-GREML approach compared with -0.10 (s.e. 0.08) from the independent-samples GCTA-GREML approach and -0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10(-7)) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10(-5), which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function.

Indexed as

Body Mass IndexAgedCognitionFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenotypeHumansMaleMiddle AgedMultifactorial InheritanceObesityPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID26857597
PMCPMC4863955

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Registered trials

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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.