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Current Diabetes Reports
Erschienen in: Current Diabetes Reports 1/2020

01.01.2020 | Genetics (AP Morris, Section Editor)

Heterogeneity in Obesity: Genetic Basis and Metabolic Consequences

verfasst von: Jonathan Sulc, Thomas W. Winkler, Iris M. Heid, Zoltán Kutalik

Erschienen in: Current Diabetes Reports | Ausgabe 1/2020

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Abstract

Purpose of Review

Our review provides a brief summary of the most recent advances towards the identification of the genetic basis of specific aspects of obesity and the quantification of their consequences on health. We also highlight the most promising avenues to be explored in the future.

Recent Findings

While obesity has been demonstrated to lead to adverse cardio-metabolic consequences, the determinants of inter-individual variability remain largely unknown. The elucidation of the molecular underpinnings of this relationship is hampered by the extremely heterogeneous nature of obesity as a human trait. Recent technological advances have facilitated a more in-depth characterization of body composition at large-scale.

Summary

At the pace of current data acquisition and resolution, it is realistic to improve characterization of obesity and to advise individuals based on detailed body composition combined with tissue-specific molecular signatures. Individualized predictions of health implications would enable more personalized and effective public health interventions.
Literatur
1.
Boles A, Kandimalla R, Reddy PH. Dynamics of diabetes and obesity: epidemiological perspective. Biochim Biophys Acta Mol basis Dis. 1863;2017:1026–36.
2.
3.
Chiu M, Austin PC, Manuel DG, Shah BR, Tu JV. Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care. 2011;34:1741–8.PubMedPubMedCentral
4.
5.
Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med. 2008;359:2105–20.PubMed
6.
Kaess BM, Pedley A, Massaro JM, Murabito J, Hoffmann U, Fox CS. The ratio of visceral to subcutaneous fat, a metric of body fat distribution, is a unique correlate of cardiometabolic risk. Diabetologia. 2012;55:2622–30.PubMedPubMedCentral
7.
Rosenquist KJ, Pedley A, Massaro JM, Therkelsen KE, Murabito JM, Hoffmann U, et al. Visceral and subcutaneous fat quality and cardiometabolic risk. JACC Cardiovasc Imaging. 2013;6:762–71.PubMedPubMedCentral
8.
Abraham TM, Pedley A, Massaro JM, Hoffmann U, Fox CS. Association between visceral and subcutaneous adipose depots and incident cardiovascular disease risk factors. Circulation. 2015;132:1639–47.PubMedPubMedCentral
9.
Virtue S, Vidal-Puig A. Adipose tissue expandability, lipotoxicity and the metabolic syndrome--an allostatic perspective. Biochim Biophys Acta. 1801;2010:338–49.
10.
Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12:e1001779.PubMedPubMedCentral
11.
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum Mol Genet. 2018;27:3641–9.PubMedPubMedCentral
12.
Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28:166–74.PubMed
13.
Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Mägi R, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015;518:187–96.PubMedPubMedCentral
14.
Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206.PubMedPubMedCentral
15.
Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50:26–41.PubMed
16.
Justice AE, Karaderi T, Highland HM, Young KL, Graff M, Lu Y, et al. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution. Nat Genet. 2019;51:452–69.PubMedPubMedCentral
17.
•• Winkler TW, Günther F, Höllerer S, Zimmermann M, Loos RJ, Kutalik Z, et al. A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications. Nat Commun. 2018;9:1946 Variants clustered according to their effects on BMI and WHR suggested different mechanisms underlying these measures of body morphology and highlighted a genetic basis for the favorable deposition of fat on hips which appears protective against T2D and CVD.PubMedPubMedCentral
18.
Randall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, Monda KL, et al. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLoS Genet. 2013;9:e1003500.PubMedPubMedCentral
19.
Winkler TW, Justice AE, Graff M, Barata L, Feitosa MF, Chu S, et al. The influence of age and sex on genetic associations with adult body size and shape: a large-scale genome-wide interaction study. PLoS Genet. 2015;11:e1005378.PubMedPubMedCentral
20.
Wells JCK. Sexual dimorphism of body composition. Best Pract Res Clin Endocrinol Metab. 2007;21:415–30.PubMed
21.
22.
Brown LM, Clegg DJ. Central effects of estradiol in the regulation of food intake, body weight, and adiposity. J Steroid Biochem Mol Biol. 2010;122:65–73.PubMed
23.
24.
25.
Norheim F, Hasin-Brumshtein Y, Vergnes L, Chella Krishnan K, Pan C, Seldin MM, et al. Gene-by-sex interactions in mitochondrial functions and cardio-metabolic traits. Cell Metab. 2019;29:932–49.e4.PubMedPubMedCentral
26.
Kassam I, Wu Y, Yang J, Visscher PM, McRae AF. Tissue-specific sex differences in human gene expression. Hum Mol Genet. 2019;28:2976–86.PubMedPubMedCentral
27.
Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37:658–65.PubMedPubMedCentral
28.
Chu AY, Deng X, Fisher VA, Drong A, Zhang Y, Feitosa MF, et al. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation. Nat Genet. 2017;49:125–30.PubMed
29.
Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90.PubMedPubMedCentral
30.
Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–16.PubMedPubMedCentral
31.
Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–83.PubMedPubMedCentral
32.
Manolopoulos KN, Karpe F, Frayn KN. Gluteofemoral body fat as a determinant of metabolic health. Int J Obes. 2010;34:949–59.
33.
Rydén M, Andersson DP, Bergström IB, Arner P. Adipose tissue and metabolic alterations: regional differences in fat cell size and number matter, but differently: a cross-sectional study. J Clin Endocrinol Metab. 2014;99:E1870–6.PubMed
34.
Lotta LA, Wittemans LBL, Zuber V, Stewart ID, Sharp SJ, Luan J ‘a, et al. Association of genetic variants related to gluteofemoral vs abdominal fat distribution with type 2 diabetes, coronary disease, and cardiovascular risk factors. JAMA. 2018;320:2553–63.PubMedPubMedCentral
35.
• Yaghootkar H, Scott RA, White CC, Zhang W, Speliotes E, Munroe PB, et al. Genetic evidence for a normal-weight “metabolically obese” phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes. Diabetes. 2014;63:4369–77 The findings of this study substantiate the role of a shift from visceral to subcutaneous locations in favorable adiposity. Furthermore, they showed that this was associated with reduced WHR in women but increased WHR in men.PubMedPubMedCentral
36.
Yaghootkar H, Lotta LA, Tyrrell J, Smit RAJ, Jones SE, Donnelly L, et al. Genetic evidence for a link between favorable adiposity and lower risk of type 2 diabetes, Hypertension, and Heart Disease. Diabetes. 2016;65:2448–60.PubMed
37.
• Lotta LA, Gulati P, Day FR, Payne F, Ongen H, van de Bunt M, et al. Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance. Nat Genet. 2017;49:17–26 This study found that genetically increased risk for insulin resistance was associated with decreased peripheral adiposity, which also increased the risk of CVD. Furthermore, the involved genetic variants were shown to contribute to familial lipodystrophy, a severe form of insulin resistance.PubMed
38.
Ji Y, Yiorkas AM, Frau F, Mook-Kanamori D, Staiger H, Thomas EL, et al. Genome-wide and abdominal MRI data provide evidence that a genetically determined favorable adiposity phenotype is characterized by lower ectopic liver fat and lower risk of type 2 diabetes, heart disease, and hypertension. Diabetes. 2019;68:207–19.PubMed
39.
Sun G, French CR, Martin GR, Younghusband B, Green RC, Xie Y-G, et al. Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population. Am J Clin Nutr. 2005;81:74–8.PubMed
40.
Achamrah N, Colange G, Delay J, Rimbert A, Folope V, Petit A, et al. Comparison of body composition assessment by DXA and BIA according to the body mass index: A retrospective study on 3655 measures. PLoS One. 2018;13:e0200465.PubMedPubMedCentral
41.
42.
Mägi R, Suleimanov YV, Clarke GM, Kaakinen M, Fischer K, Prokopenko I, et al. SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes. BMC Bioinformatics. 2017;18:25.PubMedPubMedCentral
43.
Ried JS, Jeff MJ, Chu AY, Bragg-Gresham JL, van Dongen J, Huffman JE, et al. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nat Commun. 2016;7:13357.PubMedPubMedCentral
44.
Cichonska A, Rousu J, Marttinen P, Kangas AJ, Soininen P, Lehtimäki T, et al. metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinformatics. 2016;32:1981–9.PubMedPubMedCentral
45.
Bergmann S, Ihmels J, Barkai N. Iterative signature algorithm for the analysis of large-scale gene expression data. Phys Rev E Stat Nonlinear Soft Matter Phys. 2003;67:031902.
Metadaten
Titel
Heterogeneity in Obesity: Genetic Basis and Metabolic Consequences
verfasst von
Jonathan Sulc
Thomas W. Winkler
Iris M. Heid
Zoltán Kutalik
Publikationsdatum
01.01.2020
Verlag
Springer US
Erschienen in
Current Diabetes Reports / Ausgabe 1/2020
Print ISSN: 1534-4827
Elektronische ISSN: 1539-0829
DOI
https://doi.org/10.1007/s11892-020-1285-4

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