A genomewide study of body mass index and its genetic correlation with thromboembolic risk

SummaryThrombosis and obesity are complex epidemiologically associated diseases. The mechanism of this association is not yet understood. It was the objective of this study to identify genetic components of body mass index (BMI) and their possible role in the risk of thromboembolic disease. With the self-reported BMI of 397 individuals from 21 extended families enrolled in the GAIT (Genetic Analysis of Idiopathic Thrombophilia) Project, we estimated the heritability of BMI and the genetic correlation with the risk of thrombosis. Subjects were genotyped for an autosomal genome-wide scan with 363 highly-informative DNA markers. Univariate and bivariate multipoint linkage analyses were performed. The heritability for BMI was 0.31 (p= 2.9×10–5). Thromboembolic disease (including venous and arterial) and BMI had a significant genetic correlation (ρG= 0.54, p= 0.005). Two linkage signals for BMI were obtained, one at 13q34 (LOD= 3.36, p= 0.0004) and other at 2q34, highly suggestive of linkage (LOD= 1.95). Bivariate linkage analysis with BMI and thrombosis risk also showed a significant signal at 13q34 (LOD= 3), indicating that this locus influences at the same time normal variation in the BMI phenotype as well as susceptibility to thrombosis. In conclusion, BMI and thrombosis are genetically correlated. The locus 13q34, which showed pleiotropy with both phenotypes, contains two candidate genes, which may explain our linkage pleiotropic signal and deserve further investigation as possible risk factors for obesity and thrombosis.

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Genome-Wide Scan of Obesity in Finnish Sibpairs Reveals Linkage to Chromosome Xq24*

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jcem.85.9.6797 ◽

2000 ◽

Vol 85 (9) ◽

pp. 3183-3190 ◽

Cited By ~ 1

Author(s):

Miina Öhman ◽

Laura Oksanen ◽

Jaakko Kaprio ◽

Markku Koskenvuo ◽

Pertti Mustajoki ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Chromosomal Region ◽

Adult Population ◽

Average Density ◽

Model Free ◽

Melanocortin 4 Receptor ◽

Genome Wide ◽

Sample Set ◽

Genome Wide Scan

Abstract Obesity is a multifactorial trait with evidence of a genetic component. Obesity is very common in all westernized countries, including Finland, where 10% of the adult population has a body mass index of 32 kg/m2 or more. Here we report results from a three-stage genome-wide scan of obesity in 188 affected subjects (body mass index,≥ 32 kg/m2) from 87 Finnish families. Initially, 374 markers with an average density of 10 centimorgans were genotyped. The strongest evidence for linkage to obesity was detected on chromosome Xq24, with the marker DXS6804 providing a maximum likelihood score (MLS) 3.14 in a model-free 2-point sibpair analysis. Fine-mapping in an extended sample set of 367 affected subjects from 166 families yielded a multipoint MLS of 3.48 over this X-chromosomal region. The Xq24 region contains a plausible candidate gene, serotonin 2C receptor, variants of which have been shown to predispose to obesity and type II diabetes in mice. Another chromosomal region also provided suggestive evidence of linkage, an area on 18q21, flanking the melanocortin-4 receptor, where a 2-point MLS of 2.42 with marker D18S1155 was obtained with a set of 367 affected subjects. In conclusion, our results in this Finnish study sample suggest that a locus on chromosome Xq24 influences the risk of obesity.

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Genetic variants in vitamin D metabolism-related genes and body mass index: analysis of genome-wide scan data of approximately 7000 Chinese women

International Journal of Obesity ◽

10.1038/ijo.2011.246 ◽

2011 ◽

Vol 36 (9) ◽

pp. 1252-1255 ◽

Cited By ~ 28

Author(s):

T Dorjgochoo ◽

J Shi ◽

Y-T Gao ◽

J Long ◽

R Delahanty ◽

...

Keyword(s):

Body Mass Index ◽

Vitamin D ◽

Body Mass ◽

Genetic Variants ◽

Chinese Women ◽

Vitamin D Metabolism ◽

Index Analysis ◽

Genome Wide ◽

Scan Data ◽

Genome Wide Scan

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Further Evidence for a QTL Influencing Body Mass Index on Chromosome 7p from a Genome-wide Scan in Dutch Families

Twin Research ◽

10.1375/136905204323016177 ◽

2004 ◽

Vol 7 (2) ◽

pp. 192-196 ◽

Cited By ~ 13

Author(s):

Bastiaan T. Heijmans ◽

A. Leo Beem ◽

Gonneke Willemsen ◽

Daniëlle Posthuma ◽

P. Eline Slagboom ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Genome Wide ◽

A Genome ◽

Genome Wide Scan

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A Genome-Wide Scan for Body Mass Index among Nigerian Families

Obesity Research ◽

10.1038/oby.2003.40 ◽

2003 ◽

Vol 11 (2) ◽

pp. 266-273 ◽

Cited By ~ 45

Author(s):

Adebowale Adeyemo ◽

Amy Luke ◽

Richard Cooper ◽

Xiaodong Wu ◽

Bamidele Tayo ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Genome Wide ◽

A Genome ◽

Genome Wide Scan

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Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index

Demography ◽

10.1007/s13524-013-0259-4 ◽

2013 ◽

Vol 51 (1) ◽

pp. 119-139 ◽

Cited By ~ 32

Author(s):

Jason D. Boardman ◽

Benjamin W. Domingue ◽

Casey L. Blalock ◽

Brett C. Haberstick ◽

Kathleen Mullan Harris ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Environment Interaction ◽

Gene Environment Interaction ◽

Gene Environment ◽

Genome Wide

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Novel recessive locus for body mass index in childhood asthma

Thorax ◽

10.1136/thoraxjnl-2020-215742 ◽

2021 ◽

pp. thoraxjnl-2020-215742

Author(s):

Sanghun Lee ◽

Jessica Lasky-Su ◽

Sungho Won ◽

Cecelia Laurie ◽

Juan Carlos Celedón ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Association Studies ◽

Additive Model ◽

Recessive Model ◽

Genome Wide Association Studies ◽

Association Testing ◽

Genome Wide ◽

Children With Asthma ◽

Recessive Locus

Most genome-wide association studies of obesity and body mass index (BMI) have so far assumed an additive mode of inheritance in their analysis, although association testing supports a recessive effect for some of the established loci, for example, rs1421085 in FTO. In two whole-genome sequencing (WGS) studies of children with asthma and their parents (892 Costa Rican trios and 286 North American trios), we discovered an association between a locus (rs9292139) in LOC102724122 and BMI that reaches genome-wide significance under a recessive model in the combined analysis. As the association does not achieve significance under an additive model, our finding illustrates the benefits of the recessive model in WGS analyses.

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Genome-wide Genetic Contribution to Diet Response in an Epidemiological Dataset (P15-018-19)

Current Developments in Nutrition ◽

10.1093/cdn/nzz037.p15-018-19 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

Author(s):

Kenneth Westerman ◽

Jose M Ordovas

Keyword(s):

Body Mass Index ◽

Longitudinal Data ◽

Body Mass ◽

White Women ◽

Dietary Intervention ◽

Statistical Significance ◽

Cross Sectional ◽

Statistical Correlations ◽

Mathematical Correlation ◽

Genome Wide

Abstract Objectives Many gene-diet interactions have been uncovered for obesity and other cardiometabolic risk factors, but truly personalized nutritional recommendations will require the incorporation of an individual's full genome in predicting response to diet. Statistical genetics studies typically require thousands of individuals, limiting the ability of dietary intervention trials to answer these genome-wide nutrigenetic questions. We sought to explore a novel approach for identifying the genetic architecture of the diet-body mass index (BMI) relationship using an epidemiological dataset. Methods As a mathematical correlation is defined as the expected product of two standardized variables, it may be possible to estimate the genetic signal describing an underlying diet-BMI correlation by predicting their product. Statistical simulations were performed to assess the ability of this method to pick up pre-specified effects of genotype on diet response. In white women from the longitudinal Women's Health Initiative (WHI) dataset, the product of log-transformed fat-to-carbohydrate ratio (F: C) and body mass index (BMI) (both variables standardized) was calculated both cross-sectionally at baseline (n = 9357) and with respect to longitudinal changes in these variables before follow-up (n = 1333). Plink and GCTA tools were used to estimate the genotype-based heritability of these products, as well as that of the change in BMI in response to a separate intervention in WHI focused partially on fat reduction. Results Simulations demonstrated that the method is sensitive to changes in the underlying effect sizes, but is able to detect underlying statistical correlations as intended. Genetic heritability estimates using cross-sectional data were negligible, while those using longitudinal data approached statistical significance (variance explained = 14%, P = 0.07). BMI changes in the dietary modification trial showed non-significant heritability (v.e. = 4%), which was insufficient to validate any genetic correlation with the longitudinal results. Conclusions While cross-sectional data may contain too much noise, this method shows promise for the detection of genome-wide contributions to diet response in longitudinal data, and should be investigated further in larger datasets and with alternative phenotypes. Funding Sources This study was supported by the NHLBI T32 training grant.

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