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Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health.

ABSTRACT: The contribution of genetic variants to body mass index (BMI) during adolescence across multiethnic samples is largely unknown. We selected genetic loci associated with BMI or obesity in European-descent samples and examined them in a multiethnic adolescent sample.In 5103 European American (EA), 1748 African American (AfA), 1304 Hispanic American (HA) and 439 Asian American (AsA) participants of the National Longitudinal Study of Adolescent Health (Add Health; ages 12-21 years, 47.5% male), we assessed the association between 41 established obesity-related single-nucleotide polymorphisms (SNPs) with BMI using additive genetic models, stratified by race/ethnicity, and in a pooled meta-analysis sample. We also compared the magnitude of effect for BMI-SNP associations in EA and AfA adolescents to comparable effect estimates from 11?861 EA and AfA adults in the Atherosclerosis Risk in Communities study (ages 45-64 years, 43.2% male).Thirty-five of 41 BMI-SNP associations were directionally consistent with published studies in European populations, 18 achieved nominal significance (P<0.05; effect sizes from 0.19 to 0.71?kg?m(-2) increase in BMI per effect allele), while 4 (FTO, TMEM18, TFAP2B, MC4R) remained significant after Bonferroni correction (P<0.0015). Of 41 BMI-SNP associations in AfA, HA and AsA adolescents, nine, three and five, respectively, were directionally consistent and nominally significant. In the pooled meta-analysis, 36 of 41 effect estimates were directionally consistent and 21 of 36 were nominally significant. In EA adolescents, BMI effect estimates were larger (P<0.05) for variants near TMEM18, PTER and MC4R and smaller for variants near MTIF3 and NRXN3 compared with EA adults.Our findings suggest that obesity susceptibility loci may have a comparatively stronger role during adolescence than during adulthood, with variation across race/ethnic subpopulation.

SUBMITTER: Graff M

PROVIDER: S-EPMC3461356 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health.

Graff M M North K E KE Mohlke K L KL Lange L A LA Luo J J Harris K M KM Young K L KL Richardson A S AS Lange E M EM Gordon-Larsen P P

Nutrition & diabetes 20120924

<h4>Objective</h4>The contribution of genetic variants to body mass index (BMI) during adolescence across multiethnic samples is largely unknown. We selected genetic loci associated with BMI or obesity in European-descent samples and examined them in a multiethnic adolescent sample.<h4>Design and sample</h4>In 5103 European American (EA), 1748 African American (AfA), 1304 Hispanic American (HA) and 439 Asian American (AsA) participants of the National Longitudinal Study of Adolescent Health (Add ...[more]

PMID: 23168566

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Project description:BACKGROUND:To evaluate the association between weight misperception and psychological symptoms in the Determinants of young Adults Social well-being and Health (DASH) longitudinal study. METHODS:A longitudinal sample of 3227 adolescents, in 49 secondary schools in London, aged 11-16?years participated in 2002/2003 and were followed up in 2005/2006. A sub-sample (N =?595) was followed up again at ages 21-23?years in 2012/2013. An index of weight misperception was derived from weight perception and measured weight. Psychological well- being was measured using the Strengths and Difficulties Questionnaire at 11-16?years and the General Health Questionnaire at 21-23?years. Associations with weight misperception was assessed using regression models, adjusted for socio-economic and lifestyle factors. RESULTS:White British males and females were more likely than ethnic minority peers to report accurate perceptions of measured weight. At 11-13y, 46% females and 38% males did not have an accurate perception of their measured weight. The comparable figures at 14-16y were 42 and 40%. Compared with male adolescents, more females perceived themselves as overweight or were unsure of their weight but measured normal weight, and this was more pronounced among Indians, Pakistanis and Bangladeshis. At 14-16y, more males perceived themselves as underweight but measured normal weight, and this was more pronounced among Indians. Compared with those who had an accurate perception of their normal weight, a higher likelihood of probable clinically-relevant psychological symptoms was observed among those who measured normal weight but perceived themselves to be underweight (females Odds Ratio (OR)?=?1.87 95% CI 1.03-3.40; males OR?=?2.34 95% CI 1.47-3.71), overweight (females only OR?=?2.06 95% CI 1.10-3.87), or unsure of their weight (males only OR?=?1.61 95% CI 1.04-2.49). Among females, the association was driven by internalising rather than externalising symptoms. An accurate perception of overweight was associated with higher psychological symptoms in adolescence and early 20s. Ethnic specific effects were not evident. CONCLUSION:Weight misperception may be an important determinant of psychological symptoms in young people, with an accurate perception of normal weight status being protective. Culturally targeted interventions should be considered to promote healthy perceptions of body image.

Project description:Most genetic studies of nonalcoholic fatty liver disease (NAFLD) have been conducted in Whites. In this large and ethnically diverse cohort, we assessed the transportability of previously identified genetic variants for NAFLD, built a genetic risk score (GRS), and examined its association with NAFLD risk in multiple ethnic groups. Thirty previously identified genome-wide association studies (GWAS) variants (P < 5 × 10-8 ) and 17 other variants associated with NAFLD were examined in a nested case-control study of NAFLD (1,448 cases/8,444 controls) in this multi-ethnic cohort study. We then built a GRS using 11 independent single-nucleotide polymorphisms from these prior studies and examined its association with NAFLD by cirrhosis status across multiple ethnic groups. Of the 30 GWAS SNPs, 20 (67%) were replicated (P < 0.05) in the pooled multi-ethnic population. The highest percentage of replication was seen in Latinos (43%), followed by Japanese Americans (37%), Whites (17%), and Native Hawaiians and African Americans (≤10%). Several genetic variants, including those in PNPLA3 (patatin-like phospholipase domain containing 3), HSD17B13 (hydroxysteroid 17-beta dehydrogenase 13), TM6SF2 (transmembrane 6 superfamily member 2), GATAD2A (GATA zinc finger domain containing 2A), GCKR (glucokinase regulator), SUGP1 (SURP and G-patch domain containing 1), MBOAT7 (membrane bound O-acyltransferase domain containing 7), TRIB1 (tribbles pseudokinase 1), SAMM50 (sorting and assembly machinery component), and ERLIN1 (ER lipid raft associated 1)-CHUK (component of inhibitor of nuclear factor kappa B kinase complex)-CWF19L1 (CWF19 like cell cycle control factor 1) gene cluster, were replicated in at least two ethnic groups. An 11-SNP weighted GRS was associated with NAFLD risk in the multi-ethnic population (odds ratio [OR] per SD increase = 1.41; 95% confidence interval [CI] = 1.32-1.50), as well as in each ethnic group (OR ranged from 1.30 in African Americans to 1.52 in Latinos). The GRS-NAFLD association was stronger for NAFLD with cirrhosis (OR = 1.67; 95% CI = 1.46-1.92) compared to NAFLD without cirrhosis (OR = 1.37; 95% CI = 1.28-1.46) (P heterogeneity = 0.003). Conclusion: In this ethnically diverse cohort, we replicated several key genetic variants for NAFLD and showed the utility of GRS based on the risk alleles for NAFLD risk stratification in multiple ethnic groups.

Dataset Information

Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health.

Publications

Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health.

Similar Datasets

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