Genetisches Risiko für Adipositas bei Kindern und Jugendlichen

ZUSAMMENFASSUNG

Adipositas ist eine komplexe Erkrankung, die sowohl genetischen wie auch nicht-genetischen Ursachen zugrunde liegt. Betrachtet man den BMI als einfaches Maß für die Fettleibigkeit, liegt die geschätzte Heritabilität sowohl bei Erwachsenen wie auch bei Kindern bei 0,7. Das Verständnis über die Rolle genetischer Faktoren bei polygener Adipositas bleibt eine der größten Herausforderungen. Obwohl kandidatengenbasierte sowie genomweite Kopplungsstudien mehrere Jahrzehnte dominierten, ermöglichen heute neue Technologien im Hochdurchsatz das Genotypisieren von Millionen genetischer Varianten, wodurch der Weg für genomweite Assoziationsstudien (GWAS) geebnet wurde. Diese stellen nach wie vor das effizienteste Werkzeug dar, um neue genetische Marker mit Assoziation zur Adipositas zu entdecken. Bis heute wurden so hunderte Polymorphismen im Zusammenhang mit der Fettleibigkeit identifiziert, darunter auch Varianten in Genen wie FTO, TMEM18 und MC4R. Obwohl viele dieser Gene auch mit der Fettleibigkeit im Kindesalter in Verbindung zu stehen scheinen, haben umgekehrt auch Studien in Kohorten von Kindern und Jugendlichen zur initialen Entdeckung weiterer mit Adipositas assoziierter Gene (z. B. OLFM4 und HOXB5) geführt. Auch wenn die komplette Entschlüsselung der Adipositas-Genetik nach wie vor eine große Herausforderung bleibt, könnte ein besseres Verständnis über das genetische Risiko in die klinische Praxis übertragen werden. So kann man basierend auf der Vielzahl bekannter genetischer Varianten sogenannte Polygenic Risk Scores nutzen, um Kinder und Jugendliche mit einem erhöhten Risiko für die Entwicklung einer Adipositas zu identifizieren, und so möglichst frühzeitig deren Manifestierung und damit verbunden Konsequenzen entgegenzuwirken.

ABSTRACT

Obesity is a complex disease resulting from an interplay of genetic and nongenetic factors. Although heritability estimates for body mass index (BMI) in childhood and adults account for up to 70 %, better understanding of the genetic factors in polygenic obesity remains a major challenge. Whereas genome-wide linkage analyses as well as candidate gene strategies have been the dominating research efforts over several decades, current advances in DNA technologies allowing genotyping of millions of genetic variants have paved new avenues for research approaches like genome-wide association studies (GWAS). This resulted in uncovering of hundreds of genetic variants associated with obesity, which map within genes such as FTO, TMEM18, MC4R. Majority of these genes found in cohorts of adults seem to play a role in childhood obesity as well. Nevertheless, also studies in children and adolescents contributed to initial identification of additional obesity susceptibility genes (e. g. OLFM4 and HOXB5). Explaining the heritability of obesity is immensely important since better knowledge of the genetics could have a large impact in the clinical world as well. In this context, polygenic risk scores based on contribution of numerous obesity susceptibility variants might help to identify children at high risk of obesity and so, allow early intervention against the disease as well as its metabolic consequences.

Schlüsselwörter

Adipositas - genetisches Risiko - Polygenic Risk Score

Keywords

Genetic risk - obesity - childhood - polygenic risk score - genome-wide association study

Publikationsverlauf

Artikel online veröffentlicht:
24. Februar 2023

• Literatur

• 1 Must A, Spadano J, Coakley EH. et al The disease burden associated with overweight and obesity. JAMA 1999; 282: 1523-1529
• 2 Kelly T, Yang W, Chen C-S. et al Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond) 2008; 32: 1431-1437
• 3 Wang Y, Beydoun MA, Liang L. et al Will all Americans become overweight or obese? estimating the progression and cost of the US obesity epidemic. Obesity (Silver Spring) 2008; 16: 2323-2330
• 4 French SA, Story M, Jeffery RW. Environmental influences on eating and physical activity. Annu Rev Public Health 2001; 22: 309-335
• 5 Bell CG, Walley AJ, Froguel P. The genetics of human obesity. Nat Rev Genet 2005; 06: 221-234
• 6 Stunkard AJ, Foch TT, Hrubec Z. A twin study of human obesity. JAMA 1986; 256: 51-54
• 7 Stunkard AJ, Sørensen TI, Hanis C. et al An adoption study of human obesity. N Engl J Med 1986; 314: 193-198
• 8 Hinney A, Vogel CIG, Hebebrand J. From monogenic to polygenic obesity: recent advances. Eur Child Adolesc Psychiatry 2010; 19: 297-310
• 9 Wu Y, Palmer JR, Rosenberg L. et al Admixture mapping of anthropometric traits in the Black Women’s Health Study: evidence of a shared African ancestry component with birth weight and type 2 diabetes. J Hum Genet 2022; 67: 331-338
• 10 Scliar MO, Sant’Anna HP, Santolalla ML. et al Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass and fat mass indexes. Int J Obes (Lond) 2021; 45: 1017-1029
• 11 Cheng C-Y, Kao WHL, Patterson N. et al Admixture mapping of 15,280 African Americans identifies obesity susceptibility loci on chromosomes 5 and X. PLoS Genet 2009; 05: e1000490
• 12 Froguel P, Blakemore AIF. The power of the extreme in elucidating obesity. N Engl J Med 2008; 359: 891-893
• 13 Rohde K, Keller M, La Cour Poulsen L. et al Genetics and epigenetics in obesity. Metabolism 2019; 92: 37-50
• 14 Harismendy O, Bansal V, Bhatia G. et al Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level. Genome Biol 2010; 11: R118
• 15 Semenkovich CF. Regulation of fatty acid synthase (FAS). Progress in Lipid Research 1997; 36: 43-53
• 16 Mobbs CV, Makimura H. Block the FAS, lose the fat. Nat Med 2002; 08: 335-336
• 17 Kovacs P, Harper I, Hanson RL. et al A novel missense substitution (Val1483Ile) in the fatty acid synthase gene (FAS) is associated with percentage of body fat and substrate oxidation rates in nondiabetic Pima Indians. Diabetes 2004; 53: 1915-1919
• 18 Körner A, Ma L, Franks PW. et al Sex-specific effect of the Val1483Ile polymorphism in the fatty acid synthase gene (FAS) on body mass index and lipid profile in Caucasian children. Int J Obes (Lond) 2007; 31: 353-358
• 19 Berndt J, Kovacs P, Ruschke K. et al Fatty acid synthase gene expression in human adipose tissue: association with obesity and type 2 diabetes. Diabetologia 2007; 50: 1472-1480
• 20 Schleinitz D, Klöting N, Körner A. et al Effect of genetic variation in the human fatty acid synthase gene (FASN) on obesity and fat depot-specific mRNA expression. Obesity (Silver Spring) 2010; 18: 1218-1225
• 21 Sievert H, Krause C, Geißler C. et al Epigenetic Downregulation of FASN in Visceral Adipose Tissue of Insulin Resistant Subjects. Exp Clin Endocrinol Diabetes 2021; 129: 674-682
• 22 Gao X, Lin S-H, Ren F. et al Acetate functions as an epigenetic metabolite to promote lipid synthesis under hypoxia. Nat Commun 2016; 07: 11960
• 23 Meyre D, Lecoeur C, Delplanque J. et al A genome-wide scan for childhood obesity-associated traits in French families shows significant linkage on chromosome 6q22.31-q23.2. Diabetes 2004; 53: 803-811
• 24 Maddux BA, Goldfine ID. Membrane glycoprotein PC-1 inhibition of insulin receptor function occurs via direct interaction with the receptor alpha-subunit. Diabetes 2000; 49: 13-19
• 25 Pizzuti A, Frittitta L, Argiolas A. et al A polymorphism (K121Q) of the human glycoprotein PC-1 gene coding region is strongly associated with insulin resistance. Diabetes 1999; 48: 1881-1884
• 26 Bochenski J, Placha G, Wanic K. et al New polymorphism of ENPP1 (PC-1) is associated with increased risk of type 2 diabetes among obese individuals. Diabetes 2006; 55: 2626-2630
• 27 Abate N, Chandalia M, Satija P. et al ENPP1/PC-1 K121Q polymorphism and genetic susceptibility to type 2 diabetes. Diabetes 2005; 54: 1207-1213
• 28 Meyre D, Bouatia-Naji N, Tounian A. et al Variants of ENPP1 are associated with childhood and adult obesity and increase the risk of glucose intolerance and type 2 diabetes. Nat Genet 2005; 37: 863-867
• 29 Böttcher Y, Körner A, Reinehr T. et al ENPP1 variants and haplotypes predispose to early onset obesity and impaired glucose and insulin metabolism in German obese children. J Clin Endocrinol Metab 2006; 91: 4948-4952
• 30 Wang R, Zhou D, Xi B. et al ENPP1/PC-1 gene K121Q polymorphism is associated with obesity in European adult populations: evidence from a meta-analysis involving 24,324 subjects. Biomed Environ Sci 2011; 24: 200-206
• 31 Yengo L, Sidorenko J, Kemper KE. 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: 3641-3649
• 32 Claussnitzer M, Dankel SN, Kim K-H. et al FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. N Engl J Med 2015; 373: 895-907
• 33 Frayling TM, Timpson NJ, Weedon MN. et al A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889-894
• 34 Dina C, Meyre D, Gallina S. et al Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 2007; 39: 724-726
• 35 Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nat Rev Genet 2022; 23: 120-133
• 36 Stratigopoulos G, Leibel RL. FTO gains function. Nat Genet 2010; 42: 1038-1039
• 37 Gerken T, Girard CA, Tung Y-CL. et al The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science 2007; 318: 1469-1472
• 38 Church C, Moir L, McMurray F. et al Overexpression of Fto leads to increased food intake and results in obesity. Nat Genet 2010; 42: 1086-1092
• 39 Speliotes EK, Willer CJ, Berndt SI. et al Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937-948
• 40 Manolio TA, Collins FS, Cox NJ. et al Finding the missing heritability of complex diseases. Nature 2009; 461: 747-753
• 41 Warner ET, Jiang L, Adjei DN. et al A Genome-Wide Association Study of Childhood Body Fatness. Obesity (Silver Spring) 2021; 29: 446-453
• 42 Hoed M den, Ekelund U, Brage S. et al Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies. Diabetes 2010; 59: 2980-2988
• 43 Liu G, Zhu H, Lagou V. et al FTO variant rs9939609 is associated with body mass index and waist circumference, but not with energy intake or physical activity in European- and African-American youth. BMC Med Genet 2010; 11: 57
• 44 Xi B, Shen Y, Zhang M. et al The common rs9939609 variant of the fat mass and obesity-associated gene is associated with obesity risk in children and adolescents of Beijing, China. BMC Med Genet 2010; 11: 107
• 45 Wheeler E, Huang N, Bochukova EG. et al Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat Genet 2013; 45: 513-517
• 46 Couto Alves A, Silva NMG de, Karhunen V. et al GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. Sci Adv 2019; 05: eaaw3095
• 47 Yao S, Wu H, Ding J-M. et al Transcriptome-wide association study identifies multiple genes associated with childhood body mass index. Int J Obes (Lond) 2021; 45: 1105-1113
• 48 Costa-Urrutia P, Colistro V, Jiménez-Osorio AS. et al Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children. Genes (Basel) 2019: 10
• 49 Liu HY, Alyass A, Abadi A. et al Fine-mapping of 98 obesity loci in Mexican children. Int J Obes (Lond) 2019; 43: 23-32
• 50 Zhao J, Bradfield JP, Li M. et al The role of obesity-associated loci identified in genome-wide association studies in the determination of pediatric BMI. Obesity (Silver Spring) 2009; 17: 2254-2257
• 51 Zhao J, Grant SFA. Genetics of childhood obesity. J Obes 2011: 845148
• 52 Bressler J, Fornage M, Hanis C. et al The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts. BMC Med Genet 2009; 10: 56
• 53 Campa D, Hüsing A, McKay JD. et al The INSIG2 rs7566605 polymorphism is not associated with body mass index and breast cancer risk. BMC Cancer 2010; 10: 563
• 54 Deka R, Xu L, Pal P. et al A tagging SNP in INSIG2 is associated with obesity-related phenotypes among Samoans. BMC Med Genet 2009; 10: 143
• 55 Heid IM, Huth C, Loos RJF. et al Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design?. PLoS Genet 2009; 05: e1000694
• 56 Herbert A, Gerry NP, McQueen MB. et al A common genetic variant is associated with adult and childhood obesity. Science 2006; 312: 279-283
• 57 Zhao J, Bradfield JP, Zhang H. et al Examination of all type 2 diabetes GWAS loci reveals HHEX-IDE as a locus influencing pediatric BMI. Diabetes 2010; 59: 751-755
• 58 Wu L, Xi B, Zhang M. et al Associations of six single nucleotide polymorphisms in obesity-related genes with BMI and risk of obesity in Chinese children. Diabetes 2010; 59: 3085-3089
• 59 Scherag A, Dina C, Hinney A. et al Two new Loci for body-weight regulation identified in a joint analysis of genome-wide association studies for early-onset extreme obesity in French and german study groups. PLoS Genet 2010; 06: e1000916
• 60 Bradfield JP, Taal HR, Timpson NJ. et al A genome-wide association meta-analysis identifies new childhood obesity loci. Nat Genet 2012; 44: 526-531
• 61 Maher BS. Polygenic Scores in Epidemiology: Risk Prediction, Etiology, and Clinical Utility. Curr Epidemiol Rep 2015; 02: 239-244
• 62 Khera AV, Chaffin M, Wade KH. et al Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell 2019; 177: 587-596.e9
• 63 Lange K, Kerr JA, Mansell T. et al Can adult polygenic scores improve prediction of body mass index in childhood?. Int J Obes (Lond) 2022; 46: 1375-1383
• 64 Hardy J, Singleton A. Genomewide association studies and human disease. N Engl J Med 2009; 360: 1759-1768
• 65 Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science 1996; 273: 1516-1517