Shared genetic variance between the features of the metabolic syndrome: Heritability studies

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Abstract

Heritability estimates of MetS range from approximately 10%–30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation in common, by reviewing the literature regarding genetic correlation coefficients. Identification of features, that have much genetic variation in common, may eventually facilitate the search for pleitropic genetic variants that may explain the clustering of MetS features.

A PubMed search with the search terms “(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)” was performed. Studies published before 7th July 2011, which presented genetic correlation coefficients between the different MetS features and genetic correlation coefficients of MetS and its features with adipose tissue-, pro-inflammatory and pro-thrombotic biomarkers were included.

Nine twin and 19 family studies were included in the review. Genetic correlations varied, but were strongest between waist circumference and HOMA-IR (r2: 0.36 to 0.79, median: 0.50), HDL cholesterol and triglycerides (r2: − 0.05 to − 0.59, median − 0.45), adiponectin and MetS (r2: − 0.32 to − 0.43; median − 0.38), adiponectin and insulin (r2: − 0.10 to − 0.60; median − 0.30) and between adiponectin and HDL-cholesterol (r2: − 0.22 to − 0.51, median − 0.29).

In conclusion, heritability studies suggest that genetic pleiotropy exist especially between certain MetS features, as well as between MetS and adiponectin. Further research on actual genetic variants responsible for the genetic pleiotropy of these combinations will provide more insight into the etiology of MetS.

Highlights

► Strongly genetically correlated features share much genetic variation. ► We reviewed studies on genetic correlations of metabolic syndrome features. ► Waist circumference and HOMA-IR were strongly genetically correlated. ► HDL cholesterol and triglycerides were strongly genetically correlated. ► Adiponectin was clearly genetically correlated with metabolic syndrome.

Introduction

Metabolic syndrome (MetS) refers to the clustering of abdominal obesity, hypertriglyceridemia, low HDL-cholesterol levels, hypertension and hyperglycemia [1]. People with three or more of these features are defined to have MetS according to the consensus statement of IDF and NCEP ATP III [1]. People with MetS are at increased risk of coronary heart disease (CHD) and type 2 diabetes (T2D) [1]. Besides the conventional MetS features, adipose tissue-, pro-inflammatory- and pro-thrombotic biomarkers, such as adiponectin and CRP, are important MetS related factors that play a role in the onset of CVD and T2D [2]. If added to the definition of MetS, these biomarkers may improve the predictive power of MetS for these conditions [2].

Heritability estimates of MetS range from approximately 10 to 30% [3], [4], [5]. This indicates that MetS is influenced both by environmental and genetic factors. The amount of additive genetic variation which is shared between two MetS features can be estimated from family and twin studies and is expressed by a genetic correlation coefficient. A genetic correlation expresses the extent to which two measurement reflect the same genetic character [6]. Research on genetic correlations can facilitate the search for pleiotropic genetic variants. MetS features which are highly genetically correlated have much genetic variation in common. For those features it will be easier to identify common genetic variants [6]. Identification of, for example, common genetic variants for dyslipidemia and insulin resistance may help to understand why some diabetic patients will develop dyslipidaemia, while others will not. Eventually, this understanding may affect treatment strategies.

Genetic correlation coefficients of the MetS features with each other and with MetS related biomarkers have been calculated in multiple twin and family studies. However, results of these studies are inconsistent and no overview of the available evidence exists. Therefore, the objective of this paper is to summarize these genetic correlation coefficients in order to identify those MetS features that share much genetic variation with another MetS feature or with a MetS related biomarker.

Section snippets

Methods

An electronic literature search was conducted using PubMed. The search terms “(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)” were used. Furthermore, we reviewed the reference lists of retrieved articles to identify other relevant publications.

Studies included were: 1) published before 7th July 2011; 2) family or twin studies; and 3) studies which presented genetic correlation coefficients between the different MetS features or

Results

Our literature search through PubMed yielded 444 articles. In 21 of these articles genetic correlation coefficients with MetS features were described. Through review of references we identified 7 additional articles. Finally, we included 9 twin [7], [8], [9], [10], [11], [12], [13], [14], [15] and 19 family studies [3], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], describing 239 genetic correlations. The number of subjects

Discussion

In this paper we have summarized the results of 28 family and twin studies that presented genetic correlation coefficients between the different MetS features, as well as genetic correlations between MetS features and MetS-related biomarkers. Genetic correlations were strongest between waist circumference and insulin resistance, HDL cholesterol and triglycerides, and adiponectin and MetS. The MetS features most strongly genetically correlated with adiponectin were insulin and HDL cholesterol.

Disclosure

No conflict of interest.

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