Pleiotropic genes for metabolic syndrome and inflammation
Introduction
Metabolic syndrome (MetS) is a constellation of medical conditions that include abdominal obesity with visceral fat deposition, atherogenic dyslipidemia (high triglyceride and low high density lipoprotein cholesterol levels), hyperglycemia and/or insulin resistance, and high blood pressure [1]. Due to the rise in obesity rates and poor dietary habits, MetS has become an increasing public health and financial burden [2], [3], [4], [5], [6], [7]. MetS is associated with at least five-fold increased risk in developing diabetes mellitus (T2D) and two-fold increased heart disease risk [5]. Recently, it was reported that individuals with acute ischemic stroke and metabolic syndrome have increased inflammation and arterial stiffness [8], [9]. Overall MetS captures a confluence of clinical disorders, assisting front-line practitioners in identifying cardiovascular and metabolic risk factors requiring simultaneous clinical attention [1], [10].
There are differing ideas regarding the genetic etiology and cardiovascular sequelae of MetS, including whether the MetS components are independent in origin or share common determinants. At the phenotypic level, the increased cardiovascular disease (CVD) risk associated with MetS appears to be no greater than the sum of its single traits' risk [11], [12].
Individuals with MetS, often exhibit a pro-inflammatory state, with increased levels of C-reactive protein, white blood cell count, coagulation factors VII, VIII and fibrinogen, von Willebrand factor, plasminogen activator inhibitor 1, soluble vascular adhesion molecules such as intercellular adhesion molecule 1 (ICAM-1), P-selectin as well as decreased levels of adiponectin [13], [14], [15], [16], [17]. It has been suggested that modified cytokine expression associating a greater volume of adipose tissue may be a mechanism for the low grade inflammation accompanying dysregulated lipid and glucose metabolism, as well as blood pressure [13], [18], [19]. Henneman et al. [12] recommended the genetic dissection of MetS be approached by studying individual components, because of their high heritability. Currently, it remains unclear whether genetic variants identified for individual metabolic traits [20], [21], [22], [23], [24] and inflammatory markers [25], [26], [27], [28], [29], have pleiotropic effects, thereby influencing the correlated architecture of these traits. Dallmeier et al. [30] suggested that the relationship between MetS and a number of inflammatory markers is largely accounted for by the individual MetS components, and MetS as a construct generally is no more than the sum of its parts with respect to inflammation. We propose that in addition to genes influencing individual MetS risk factors, there are genetic variants that influence MetS risk factors and inflammatory markers, forming a pleiotropic intertwined genetic network. As part of the “Pleiotropy among Metabolic traits and Inflammatory-prothrombotic markers” working group, a sub-group of the Cross Consortia Pleiotropy Group, we aimed to: (a) evaluate epidemiological associations between MetS and inflammatory markers; (b) assess correlations among metabolic traits and inflammatory markers for identifying combinations to explore for potentially genetic pleiotropic associations and pathways; (c) utilize these newly identified trait-combinations to perform correlated meta-analyses using previously published GWAS meta-results from large consortia for the individual traits, with the overall goal of detecting MetS candidates with potential pleiotropic effects across metabolic traits and inflammatory markers.
Section snippets
A brief summary of implemented methods
The international collaboration of Cross Consortia Pleiotropy Group (XC-Pleiotropy) was founded in the early 2011 for studying pleiotropy by using published GWAS results. The PMI-WG is a collaborative group within the XC-Pleiotropy (Supplement 1). For implementing the first two aims (see Introduction), 17 metabolic traits and inflammatory markers are studied (Section 2.1.1), from 14 large-scale cohort studies (dependent on cohort-specific assay availability, Table 1.a and Supplement 2).
Epidemiological associations between inflammatory markers and MetS
Using data from more than 85,500 participants across 14 cohorts (Table 1.a), we assessed at the phenotypic level the associations between 9 inflammatory markers CRP, FIB, PAI-1, IL-6, IL-10, ICAM-1, WBCC, TNFA and ADIP and MetS. Metabolic traits studied were BMI, WAIST, HDLC, TG, GLUC, INS, SBP and DBP (Supplemental Table 1). The mean age varied from 25 (SD = ± 3) years in the CARDIA study to 74 (SD = ± 8) years in the Rotterdam Study. These 14 studies capture a range of MetS (NCEP criteria)
Discussion
This is the first time that a large sample of more than 85,500 participants with 8 metabolic traits and 9 inflammatory markers is analyzed together with the purpose of understanding relationships of inflammatory markers and MetS. Mean levels of inflammatory markers FIB, CRP, PAI-1, ICAM-1, WBCC and TNFA were higher, while mean ADIP level was lower in individuals classified with MetS compared to those without. These differences reached statistical significance. We explored the pairwise average
Author contributions
A.T.K., J.B.M., I.B.B. conceived the study project; A.T.K., D.I.C., K.E.N., A.P.R., L.R.Y., T.O.K., J.A.S., A.D., J.D., M.G.L., B.Z.A., I.P., J.B.M., and I.B.B. researched data, contributed to discussion and wrote the manuscript; A.D.J., M.F.F., F.T.A., A.Y.C., I.M.N., Z.D., A.M., S.A.P., Y.V.S., M.D.R., A.V., H.L., S.L., L.M., R.R., Y.S., M.A.Z., H.K.I., R.B.S., T.J., M.E.J., T.H., O.P., R.P.S., H.S., A.H., A.G.U., O.H.F., M.A.I., J.B.R., C.R., J.G.W., L.L., S.K.G., M.N., L.J.R., J.S.P., J.C.,
Conflict of interest
All authors have no conflict of interest to declare.
Acknowledgments
The authors express their gratitude to large meta-GWAS Consortia and studies for contributing results in the XC-Pleiotropy. They are recognized as contributing studies in the coauthorship. In addition we acknowledge the followings studies for contributing correlation analyses:
ARIC:
The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C,
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