Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study

Gemma Cadby, Phillip E. Melton, Nina S. McCarthy, Marcio Almeida, Sarah Williams-Blangero, Joanne E. Curran, John L. VandeBerg, Jennie Hui, John Beilby, A. W. Musk, Alan L. James, Joseph Hung, John Blangero, Eric K. Moses

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Abstract

Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h2) and genetic correlations (rg) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h2 range 0.18–0.57). We identified 50 significant genetic correlations (rg range: − 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist–hip ratio; triglycerides and waist–hip ratio; triglycerides and waist–height ratio; non-HDL-C and waist–height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.

Original languageEnglish
Pages (from-to)45–53
Number of pages9
JournalHuman Genetics
Volume137
Issue number1
DOIs
Publication statusPublished - 2018

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Obesity
Health
Single Nucleotide Polymorphism
Triglycerides
Body Mass Index
Genetic Pleiotropy
Skinfold Thickness
HDL Cholesterol
Linear Models
Genome
Insulin

Cite this

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title = "Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study",
abstract = "Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h2) and genetic correlations (rg) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h2 range 0.18–0.57). We identified 50 significant genetic correlations (rg range: − 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist–hip ratio; triglycerides and waist–hip ratio; triglycerides and waist–height ratio; non-HDL-C and waist–height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.",
author = "Gemma Cadby and Melton, {Phillip E.} and McCarthy, {Nina S.} and Marcio Almeida and Sarah Williams-Blangero and Curran, {Joanne E.} and VandeBerg, {John L.} and Jennie Hui and John Beilby and Musk, {A. W.} and James, {Alan L.} and Joseph Hung and John Blangero and Moses, {Eric K.}",
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T1 - Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study

AU - Cadby, Gemma

AU - Melton, Phillip E.

AU - McCarthy, Nina S.

AU - Almeida, Marcio

AU - Williams-Blangero, Sarah

AU - Curran, Joanne E.

AU - VandeBerg, John L.

AU - Hui, Jennie

AU - Beilby, John

AU - Musk, A. W.

AU - James, Alan L.

AU - Hung, Joseph

AU - Blangero, John

AU - Moses, Eric K.

PY - 2018

Y1 - 2018

N2 - Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h2) and genetic correlations (rg) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h2 range 0.18–0.57). We identified 50 significant genetic correlations (rg range: − 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist–hip ratio; triglycerides and waist–hip ratio; triglycerides and waist–height ratio; non-HDL-C and waist–height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.

AB - Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h2) and genetic correlations (rg) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h2 range 0.18–0.57). We identified 50 significant genetic correlations (rg range: − 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist–hip ratio; triglycerides and waist–hip ratio; triglycerides and waist–height ratio; non-HDL-C and waist–height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.

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DO - 10.1007/s00439-017-1856-x

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