Meta-Analysis of the INSIG2 Association with Obesity Including 74,345 Individuals: Does Heterogeneity of Estimates Relate to Study Design?

Heid, Iris M.; Huth, Cornelia; Loos, Ruth J.F.; Kronenberg, Florian; Adámková, Věra; Anand, Sonia S.; Ardlie, Kristin; Biebermann, Heike; Bjerregaard, Peter; Boeing, Heiner; Bouchard, Claude; Ciullo, Marina; Cooper, Jackie A.; Corella, Dolores; Dina, Christian; Engert, James C.; Fisher, Eva; Francès, Francesc; Froguel, Philippe; Hebebrand, Johannes; Hegele, Robert A.; Hinney, Anke; Hoehe, Margret R.; Hu, Frank B.; Hubacek, Jaroslav A.; Humphries, Steve E.; Hunt, Steven C.; Illig, Thomas; Järvelin, Marjo‐Riitta; Kaakinen, Marika; Kollerits, Barbara; Krude, Heiko; Kumar, Jitender; Lange, Leslie A.; Langer, Birgit; Li, Shengxu; Luchner, Andreas; Lyon, Helen N.; Meyre, David; Mohlke, Karen L.; Mooser, Vincent; Nebel, Almut; Nguyen, Thuy Trang; Paulweber, Bernhard; Pérusse, Louis; Qi, Lü; Rankinen, Tuomo; Rosskopf, Dieter; Schreiber, Stefan; Sengupta, Shantanu; Sorice, Rossella; Suk, Anita; Þorleifsson, Guðmar; Þorsteinsdóttir, Unnur; Völzke, Henry; Vimaleswaran, Karani Santhanakrishnan; Wareham, Nicholas J.; Waterworth, Dawn; Yusuf, Salim; Lindgren, Cecilia M.; McCarthy, Mark I.; Lange, Christoph; Hirschhorn, Joel N.; Laird, Nan M.; Wichmann, H‐Erich

doi:10.1371/journal.pgen.1000694

Cited by 65 publications

(63 citation statements)

References 27 publications

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“…No heterogeneity in INSIG2 main effect estimates was found between studies with higher compared with lower mean subject age; however, contrasted studies overlapped considerably in age range, with mean ages lying between 41 and 58 years. 18 Nevertheless, this meta-analysis revealed an increased obesity risk for rs7566605 minor allele homozygotes in general population studies (odds ratio 1.092, P ¼ 0.035, 48 844 subjects from 16 studies), but a decreased obesity risk in population-based studies with subjects selected for better health status (odds ratio 0.796, P ¼ 0.028, 7640 subjects from 5 studies). Six other studies also indicated a tendency toward a protective effect of rs7566605 risk genotype CC on BMI or obesity status, 3,9,10,12,14 or on waist-to-hip ratio.…”

Section: Introductionmentioning

confidence: 73%

“…3,[8][9][10][11][12][13][14][15][16][17] Combining all study results on INSIG2 suggest age as the most probable interaction candidate. A large metaanalysis 18 (34 studies, 74 345 individuals) confirmed association of INSIG2 with obesity across study designs when comparing extremes (eg, BMI Z32.5 kg/m 2 versus BMI o25 kg/m 2 ). No heterogeneity in INSIG2 main effect estimates was found between studies with higher compared with lower mean subject age; however, contrasted studies overlapped considerably in age range, with mean ages lying between 41 and 58 years.…”

Section: Introductionmentioning

confidence: 89%

“…However, the two-way interaction test with baseline age is expected to have better power 42 in KORA3 and KORA4, because of short-term follow-up (10, 7 years) and lower autocorrelation (r ¼ 0.16, 0.27). The three-way interaction tested for differential effects in older compared with younger subjects (which were suspected previously 18 ). LNPT agreed with parametric results.…”

Section: Insig2 Rs7566605-age Interaction On Bmimentioning

confidence: 99%

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Controversial association results for INSIG2 on body mass index may be explained by interactions with age and with MC4R

et al. 2014

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Among the single-nucleotide polymorphisms (SNPs) previously reported to be associated with body mass index (BMI) and obesity, we focus on a common risk variant rs7566605 upstream of the insulin-induced gene 2 (INSIG2) gene and a rare protective variant rs2229616 on the melanocortin-4 receptor (MC4R) gene. INSIG2 is involved in adipogenesis and MC4R effects hormonal appetite control in response to the amount of adipose tissue. The influence of rs2229616 (MC4R) on BMI and obesity has been confirmed repeatedly and insight into the underlying mechanism provided. However, a main effect of rs7566605 (INSIG2) is under debate because of inconsistent replications of association. Interaction of rs7566605 with age may offer an explanation. SNP-age and SNP-SNP interaction models were tested on independent individuals from three population-based longitudinal cohorts, restricting the analysis to an observed age of 25-74 years. KORA S3/F3, KORA S4/F4 (Augsburg, Germany, 1994, 1999, and Framingham-Offspring data (Framingham, USA, 1971-2001 were analysed, with a total sample size of N ¼ 6926 in the joint analysis. The effect of interaction between rs7566605 and age on BMI and obesity status is significant and consistent across studies. This new evidence for rs7566605 (INSIG2) complements previous research. In addition, the interaction effect of rs7566605 with the MC4R variant rs2229616 on BMI was observed. This effect size was three times larger than that in a previously reported single-locus main effect of rs2229616. This leads to the conclusion that SNP-age or SNP-SNP interactions can mask genetic effects for complex diseases if left unaccounted for.

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Section: Introductionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 89%

Section: Insig2 Rs7566605-age Interaction On Bmimentioning

confidence: 99%

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Controversial association results for INSIG2 on body mass index may be explained by interactions with age and with MC4R

et al. 2014

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“…In fact, a meta-analysis involving a large sample size of more than 70 000 individuals has been carried out recently to examine the INSIG2 association with obesity, and it found no evidence to support the association of the landmark SNP (rs7566605) with obesity. 28 Similarly, the SNPs that were identified for PD were not replicated in a large scale international study. 29 The second study for PD was only in its first stage of analysis at that time and it did not find any significant result.…”

Section: Gwas After Hapmap-the Progress Over the Past 5 Years The Firmentioning

confidence: 98%

The pursuit of genome-wide association studies: where are we now?

et al. 2010

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It is now 5 years since the first genome-wide association studies (GWAS), published in 2005, identified a common risk allele with large effect size for age-related macular degeneration in a small sample set. Following this exciting finding, researchers have become optimistic about the prospect of the genome-wide association approach. However, most of the risk alleles identified in the subsequent GWAS for various complex diseases are common with small effect sizes (odds ratio o1.5). So far, more than 450 GWAS have been published and the associations of greater than 2000 single nucleotide polymorphisms (SNPs) or genetic loci were reported. The aim of this review paper is to give an overview of the evolving field of GWAS, discuss the progress that has been made by GWAS and some of the interesting findings, and summarize what we have learned over the past 5 years about the genetic basis of human complex diseases. This review will focus on GWAS of SNPs association for complex diseases but not studies of copy number variations.

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“…However, this association could be replicated in only 5 of 9 cohorts drawn from different populations [Lyon et al, 2007]. A recent meta-analysis of 27 studies on Caucasian adults suggested an association of the INSIG2 CC genotype with extreme obesity, but not with obesity in general [Heid et al, 2009]. …”

Section: Introductionmentioning

confidence: 99%

FTO and INSIG2 Genotyping Combined with Metabolic and Anthropometric Phenotyping of Morbidly Obese Patients

Burgdörfer

Korenkov²,

Jonas³

et al. 2013

Mol Syndromol

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termediate-risk AT genotype was found in patients and controls at similar frequencies (48.4 vs. 48.6%, OR = 0.99). The low-risk TT genotype for rs9939609 was found in 19.4% of patients (35.5% of controls; p = 0.0013) and was associated with a decreased risk for morbid obesity (OR = 0.43, CI = 0.26-0.73). In contrast, INSIG2 rs7566605 showed no association with obesity in our patients. Evaluation of metabolic data indicated associations between the high-risk FTO genotype (rs9939609_AA) and increased levels of serum glutamic oxaloacetic transaminase (GOT) and between the high-risk INSIG2 genotype (rs7566605_CC) and lower waist-to-hip ratio and lower hemoglobin A1c (HbA1c) levels. Our results confirm an association of the FTO SNP with extreme obesity. However, we found no association of the potential obesity risk allele of INSIG2 in our sample and thus cannot confirm an association of the INSIG2 CC genotype with obesity. We identified an association between the high-risk FTO genotype (rs9939609_AA) and higher GOT levels, which could possibly reflect the increased frequency of nonalcoholic steatohepatitis with obesity. We also detected associations of the high-risk INSIG2 genotype (rs7566605_CC) with lower waist-to-hip ratios and lower HbA1c levels, which may indicate amelioration of impaired glucose tolerance and type 2 diabetes for patients with this genotype after bariatric surgery. AbstractObesity is a major health problem worldwide. Associations of obesity with common variants of the fat mass-and obesityassociated gene (FTO) and insulin-induced gene 2 (INSIG2) have been reported in various studies. We aimed to further investigate the association of 2 single nucleotide polymorphisms (SNPs), rs9939609 in FTO and rs7566605 in INSIG2 , with body mass index (BMI) and other anthropometric and metabolic parameters in subjects with morbid obesity (BMI ≥ 40). SNPs rs9939609 and rs7566605 were genotyped in 124 unrelated morbidly obese patients (mean BMI = 50, range 40.1-77.1) from Mainz, Germany, and in 253 normal controls without a history of morbid obesity. Metabolic and anthropometric parameters were analyzed in 109 of the 124 patients, and associations with the genotype data were examined. The high-risk AA genotype for FTO rs9939609 was observed in 32.3% of patients versus 15.8% of controls (p = 0.0004) and was associated with an increased obesity risk [odds ratio (OR) = 2.54, 95% confidence interval (CI) = 1.53-4.21]. The in-

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Meta-Analysis of the INSIG2 Association with Obesity Including 74,345 Individuals: Does Heterogeneity of Estimates Relate to Study Design?

Cited by 65 publications

References 27 publications

Controversial association results for INSIG2 on body mass index may be explained by interactions with age and with MC4R

Controversial association results for INSIG2 on body mass index may be explained by interactions with age and with MC4R

The pursuit of genome-wide association studies: where are we now?

FTO and INSIG2 Genotyping Combined with Metabolic and Anthropometric Phenotyping of Morbidly Obese Patients

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