Cited by 732Genetic Associations and EpidemiologyGenetics and Physical PerformanceNutrition, Genetics, and Disease

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

A common genetic variant is associated with adult and childhood obesity.

Herbert, Alan, Gerry, Norman P., McQueen, Matthew B., Heid, Iris M., Pfeufer, Arne, Illig, Thomas, Wichmann, H.-Erich, Meitinger, Thomas, Hunter, David, Hu, Frank B., Colditz, Graham, Hinney, Anke, Hebebrand, Johannes, Koberwitz, Kerstin, Zhu, Xiaofeng, Cooper, Richard, Ardlie, Kristin, Lyon, Helen, Hirschhorn, Joel N., Laird, Nan M., Lenburg, Marc E., Lange, Christoph, Christman, Michael F.·2006·Science

DOI 10.1126/science.1124779

Open this paper in CoChat — free account

Abstract

Obesity is a heritable trait and a risk factor for many common diseases such as type 2 diabetes, heart disease, and hypertension. We used a dense whole-genome scan of DNA samples from the Framingham Heart Study participants to identify a common genetic variant near the INSIG2 gene associated with obesity. We have replicated the finding in four separate samples composed of individuals of Western European ancestry, African Americans, and children. The obesity-predisposing genotype is present in 10% of individuals. Our study suggests that common genetic polymorphisms are important determinants of obesity.

Integrity signals

Registry

Crossref · 10.1126/science.1124779

Cites

32 of 32 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Haploview: analysis and visualization of LD and haplotype maps
Barrett, J. C., Fry, B., Maller, J., & Daly, M. J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth457 · Cited by 14,551
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002.
Hedley, A. A., Ogden, C., Johnson, C. L., Carroll, M., Curtin, L. R., & Flegal, K. (2004) · Journal of the American Medical Association (JAMA) · doi:10.1001/jama.291.23.2847 · Cited by 4,670
Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM).
Spielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679
Body Weight and Mortality among Women
Manson, J. E., Willett, W. C., Stampfer, M. J., Colditz, G. A., Hunter, D. J., Hankinson, S. E., Hennekens, C. H., & Speizer, F. E. (1995) · New England Journal of Medicine · doi:10.1056/nejm199509143331101 · Cited by 2,005
Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003) · Nature Genetics · doi:10.1038/ng1071 · Cited by 1,900
A comprehensive review of genetic association studies
Hirschhorn, J. N., Lohmueller, K., Byrne, E., & Hirschhorn, K. (2002) · Genetics in Medicine · doi:10.1097/00125817-200203000-00002 · Cited by 1,674
On the allelic spectrum of human disease
Reich, D. E., & Lander, E. S. (2001) · Trends in Genetics · doi:10.1016/s0168-9525(01)02410-6 · Cited by 1,185
The family based association test method: strategies for studying general genotype–phenotype associations
Horvath, S., Xu, X. P., & Laird, N. M. (2001) · European Journal of Human Genetics · doi:10.1038/sj.ejhg.5200625 · Cited by 739
The genetics of human obesity
Bell, C. G., Walley, A. J., & Froguel, P. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1556 · Cited by 677

Flagged first, then by citations

Show all 32 references

Research works printed but not linked: 3

C. G. Bell, A. J. Walley, P. Froguel, Nat. Rev. Genet.6, 221 (2005).
R. S. Spielman, R. E. McGinnis, W. J. Ewens, Am. J. Hum. Genet.52, 506 (1993).
H. E. Wichmann, C. Gieger, T. Illig, Das GesundheitwesenSpecial Issue 1, S26 (2005).

Sorted by citations

Items 301–400 of 732

High quality methylome-wide investigations through next-generation sequencing of DNA from a single archived dry blood spot
Åberg, K. A., Xie, L. Y., Nerella, S., Copeland, W., Costello, E. J., & van den Oord, E. J. C. G. (2013) · Epigenetics · doi:10.4161/epi.24508 · Cited by 27
“Such a genome-wide approach proved fruitful in the context of genome-wide association studies (GWAS) with SNPs where even the first generation of GWAS identified susceptible variants for common diseases.(20-23) When using blood as biomaterial for a MWAS, the DNA is typically extracted directly from fresh or frozen who…”
Background
From DNA to RNA to disease and back: The 'central dogma' of regulatory disease variation
Stranger, B. E., & Dermitzakis, E. T. (2006) · Human Genomics · doi:10.1186/1479-7364-2-6-383 · Cited by 27
Association of variants in the BAT1-NFKBIL1-LTA genomic region with protection against myocardial infarction in Europeans
Koch, W., Hoppmann, P., Michou, E., Jung, V., Pfeufer, A., Mueller, J. C., Gieger, C., Wichmann, H. ‐., Meitinger, T., Schömig, A., et al. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddm130 · Cited by 27
Common Obesity-Related Genetic Variants and Papillary Thyroid Cancer Risk
Kitahara, C. M., Neta, G. I., Pfeiffer, R. M., Kwon, D., Xu, L., Freedman, N. D., Hutchinson, A. A., Chanock, S. J., Sturgis, E. M., Sigurdson, A. J., et al. (2012) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-12-0790 · Cited by 27
Genetics of Obesity
Srivastava, A. N., Srivastava, N., & Mittal, B. (2015) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-015-0541-x · Cited by 32
Construct Validity of an Obesity Risk Screening Tool in Two Age Groups
Peyer, K. L., & Welk, G. J. (2017) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph14040419 · Cited by 27
“While a portion of the relationship between parent and child weight is likely genetic [49], a portion can also be attributed to shared environment and shared behaviors [50,51].”
Background
Childhood maltreatment and high dietary fat intake behaviors in adulthood: A birth cohort study
Abajobir, A. A., Kisely, S. R., Williams, G. M., Strathearn, L., & Najman, J. M. (2017) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2017.08.002 · Cited by 27
“Common modifiable risk factors are associated with an “obesogenic” environment (Hebebrand &Hinney, 2009; Herbert et al., 2006).”
Background
Evolution, developmental plasticity, and metabolic disease
Kuzawa, C. W., Gluckman, P. D., Hanson, M. A., & Beedle, A. S. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0019 · Cited by 27
The single nucleotide polymorphism upstream of insulin-induced gene 2 (INSIG2) is associated with the prevalence of hypercholesterolaemia, but not with obesity, in Japanese American women
Oki, K., Yamane, K., Kamei, N., Asao, T., Awaya, T., & Kohno, N. (2008) · British Journal Of Nutrition · doi:10.1017/s0007114508006557 · Cited by 27
INSIG2 SNPs Associated With Obesity and Glucose Homeostasis Traits in Hispanics: The IRAS Family Study
Talbert, M. E., Langefeld, C. D., Ziegler, J. T., Haffner, S. M., Norris, J. M., & Bowden, D. W. (2009) · Obesity · doi:10.1038/oby.2009.94 · Cited by 27
Combinatorial Search Methods for Multi-SNP Disease Association
Brinza, D., He, J., & Zelikovsky, A. (2006) · Conference proceedings · doi:10.1109/iembs.2006.260510 · Cited by 27
“In the reduced set of SNPs, we then propose to apply a novel combinatorial method for finding disease-associated multi-SNP combinations (MSCs).”
Method
INSIG2 variants, dietary patterns and metabolic risk in Samoa
Baylin, A., Deka, R., Tuitele, J., Viali, S., Weeks, D. E., & McGarvey, S. T. (2012) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2012.124 · Cited by 26
FASTCHI: AN EFFICIENT ALGORITHM FOR ANALYZING GENE-GENE INTERACTIONS
ZHANG, X., Zou, F., & Wang, W. W. (2008) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789812836939_0050 · Cited by 26
A common VLDLR polymorphism interacts with APOE genotype in the prediction of carotid artery disease risk
Crawford, D. C., Nord, A. S., Badzioch, M. D., Ranchalis, J., McKinstry, L. A., Ahearn, M., Bertucci, C., Shephard, C., Wong, M., Rieder, M. J., et al. (2007) · Journal of Lipid Research · doi:10.1194/jlr.m700409-jlr200 · Cited by 26
Lifestyle, diet, and disease: comparative perspectives on the determinants of chronic health risks
Leonard, W. R. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0020 · Cited by 26
A Common Haplotype in the G-Protein–Coupled Receptor Gene GPR74 Is Associated with Leanness and Increased Lipolysis
Dahlman, I. A., Dicker, A., Jiao, H., Kere, J., Blomqvist, L., van Harmelen, V., Hoffstedt, J., Borch‐Johnsen, K., Jørgensen, T., Hansen, T. F., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/518445 · Cited by 26
“We included both men and women in our analysis because genetic analyses of obesity indicate that the majority of susceptibility alleles are common in both sexes.(16,17) Our recruitment strategy for samples 1 and 2 resulted in a higher proportion of women than men in the study.”
Background
Epistemological issues in omics and high-dimensional biology: give the people what they want
Mehta, T. S., Zakharkin, S. O., Gadbury, G. L., & Allison, D. B. (2006) · Physiological Genomics · doi:10.1152/physiolgenomics.00095.2006 · Cited by 26
“For example, an exciting paper on obesity was published recently (30).”
Genetics of Adipose Tissue Biology
Dahlman, I. A., & Arner, P. (2010) · Progress in molecular biology and translational science · doi:10.1016/b978-0-12-375003-7.00003-0 · Cited by 25
Obesity Genes and Gene–Environment–Behavior Interactions: Recommendations for a Way Forward
Shuldiner, A. R. (2008) · Obesity · doi:10.1038/oby.2008.523 · Cited by 25
“To date, two genes that influence body mass, insulin induced gene 2 (INSIG2) and fat mass and obesity-associated (FTO) genes, have been identified by this approach (12,13).”
Background
Maternal Obesity Is Associated With Younger Age at Obesity Onset in U.S. Adolescent Offspring Followed Into Adulthood
Gordon‐Larsen, P., Adair, L. S., & Suchindran, C. (2007) · Obesity · doi:10.1038/oby.2007.331 · Cited by 25
Genetic Susceptibility, HIV Infection, and the Kidney
Kiryluk, K., Martino, J., & Gharavi, A. G. (2007) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.00320107 · Cited by 25
Appetite and Body Weight Regulation
Vasselli, J. R. (2012) · Wiley eBooks · doi:10.1002/9781394323142.ch8 · Cited by 25
Gene polymorphisms and increased DNA damage in morbidly obese women
Luperini, B. C. O., Almeida, D. C., Porto, M., Marcondes, J. P. D. C., Prado, R. P., Rasera, I., de Oliveira, M. R. M., & Salvadori, D. M. F. (2015) · Mutation research. Fundamental and molecular mechanisms of mutagenesis · doi:10.1016/j.mrfmmm.2015.01.004 · Cited by 24
Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy
Wang, Y.-C., Wu, Y., Choi, J. Y., Allington, G., Zhao, S., Khanfar, M., Yang, K., Fu, P.-Y., Wrubel, M., Yu, X., et al. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12020175 · Cited by 23
“Later, GWAS identified many risk loci associated with diseases and traits, including coronary heart disease [6], obesity [7,8], type 2 diabetes [9], schizophrenia [10], and so forth.”
Background
Non-replication of an association of CTNNBL1polymorphisms and obesity in a population of Central European ancestry
Vogel, C. I. G., Greene, B., Scherag, A., Müller, T. D., Friedel, S., Grallert, H., Heid, I. M., Illig, T., Wichmann, H. ‐., Schäfer, H., et al. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-14 · Cited by 25
“Interestingly, however, the study did find some evidence for an association of variants in INSIG2 with obesity [5,16-19].”
Background
An Integrative Review of Obesity Prevention in African American Children
Hudson, C. E. (2008) · Issues in Comprehensive Pediatric Nursing · doi:10.1080/01460860802475168 · Cited by 24
“Though metabolic and genetic factors impact obesity in all ethnic/racial groups, they are not thought to be a major factor in the current obesity epidemic (Herbert et al., 2006; Ogden et al., 2007).”
Background
Overexpression of Insig-2 inhibits atypical antipsychotic-induced adipogenic differentiation and lipid biosynthesis in adipose-derived stem cells
Chen, C.-C., Hsu, L., Huang, K., Goto, S., Chen, C., & Nakano, T. (2017) · Scientific Reports · doi:10.1038/s41598-017-11323-9 · Cited by 24
Pediatric Obesity
Stovitz, S. D., Schwimmer, J. B., Martínez, H., & Story, M. T. (2008) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.09.034 · Cited by 25
Arboreal adaptations of body fat in wild toque macaques (Macaca sinica) and the evolution of adiposity in primates
Dittus, W. P. J. (2013) · American Journal of Physical Anthropology · doi:10.1002/ajpa.22351 · Cited by 24
Application of DNA Microarrays in the Study of Human Obesity and Type 2 Diabetes
Sun, G. (2007) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2006.0003 · Cited by 25
“Another study by Herbert et al. (2006) used DNA microarrays to genotype hundreds of thousands of SNPs, identifying a common genetic variant near the INSIG2 gene that was associated with obesity.”
Evaluating the Association of FAAH Common Gene Variation with Childhood, Adult Severe Obesity and Type 2 Diabetes in the French Population
Durand, E., Lecœur, C., Delplanque, J., Benzinou, M., Degraeve, F., Boutin, P., Marre, M., Balkau, B., Charpentier, G., Froguel, P., et al. (2008) · Obesity Facts · doi:10.1159/000178157 · Cited by 24
Genome-Wide Association Studies of Cancer
Jorgenson, E., & Witte, J. S. (2007) · Future Oncology · doi:10.2217/14796694.3.4.419 · Cited by 24
“Future perspective Genome-wide association studies have already successfully identified genetic variants underlying myocardial infarction [41–43], age-related macular degeneration [44,45], Type 1 diabetes [46], Type 2 diabetes [28–30,46,47], Crohn’s disease [48–50] and obesity [51,52], prostate cancer [21–23] and brea…”
Background
Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass
Cummings, N., Shields, K., Curran, J. E., Bozaoglu, K., Trevaskis, J. L., Gluschenko, K., Cai, G., Comuzzie, A. G., Dyer, T. D., Walder, K. R., et al. (2011) · International Journal of Obesity · doi:10.1038/ijo.2011.67 · Cited by 26
“Genome-wide scans for obesity phenotypes have led to the identification of several chromosome regions that are likely to harbor obesity-susceptibility genes”
Background
No Association Between INSIG2 Gene rs7566605 Polymorphism and Being Overweight in Japanese Population
Tabara, Y., Kawamoto, R., Osawa, H., Nakura, J., Makino, H., Miki, T., & Kohara, K. (2008) · Obesity · doi:10.1038/oby.2007.25 · Cited by 24
“079) described in a previous report (2).”
BackgroundResultInfluential
Association Analysis Indicates That a Variant GATA-Binding Site in the PIK3CB Promoter Is a Cis-Acting Expression Quantitative Trait Locus for This Gene and Attenuates Insulin Resistance in Obese Children
Stunff, C. L., Dechartres, A., Mariot, V., Lotton, C., Trainor, C. D., del Giudice, E. M., Meyre, D., Bièche, I., Laurendeau, I., Froguel, P., et al. (2007) · Diabetes · doi:10.2337/db07-1273 · Cited by 25
Interspecies genetics of eating disorder traits
Kas, M. J., Kaye, W. H., Mathes, W. F., & Bulik, C. M. (2008) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30832 · Cited by 23
“For example, recent studies of memory function [Papassotiropoulos, 2006] and obesity [Herbert, 2006] each identified a single significantly associated SNP but with relatively small effect.”
Result
Characterization of the Human Insulin-induced Gene 2 (INSIG2) Promoter
Fernández-Álvarez, A. J., Álvarez, M. S., Cucarella, C., & Casado, M. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m109.067447 · Cited by 23
Predictive value of testing for multiple genetic variants in multifactorial diseases: implications for the discourse on ethical, legal and social issues
Janssens, A. C. J. W., & Khoury, M. J. (2006) · Italian Journal of Public Health · doi:10.2427/5915 · Cited by 23
Genetic factors contributing to obesity and body weight can act through mechanisms affecting muscle weight, fat weight, or both
Brockmann, G. A., Tsaih, S., Neuschl, C., Churchill, G. A., & Li, R. (2008) · Physiological Genomics · doi:10.1152/physiolgenomics.90277.2008 · Cited by 23
Decision tree learning to predict overweight/obesity based on body mass index and gene polymporphisms
Rodríguez-Pardo, C., Segura, A., Zamorano‐León, J. J., Martínez-Santos, C., Martı́nez, D., Collado-Yurrita, L., Giner, M., García‐García, J. M., Rodríguez-Pardo, J. M., & López-Farré, A. J. (2019) · Gene · doi:10.1016/j.gene.2019.03.011 · Cited by 23
Candidate genes and growth curves for adiposity in African- and European-American youth
Podolsky, R. H., Barbeau, P., Hs, K., Zhu, H., Treiber, F. A., & Snieder, H. (2007) · International Journal of Obesity · doi:10.1038/sj.ijo.0803673 · Cited by 23
Empirical null and false discovery rate inference for exponential families
Schwartzman, A. (2008) · The Annals of Applied Statistics · doi:10.1214/08-aoas184 · Cited by 23
A Bivariate Latent Class Correlated Generalized Ordered Probit Model with an Application to Modeling Observed Obesity Levels
Greene, W. H., Harris, M. N., Hollingworth, B., & Maitra, P. (2008) · Faculty Digital Archive (New York University Florence) · Cited by 23
Association of INSIG2 Polymorphism with Overweight and LDL in Children
Kaulfers, A.-M. D., Deka, R., Dolan, L. M., & Martin, L. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116340 · Cited by 22
“Herbert et al[4] published the first Table 2.”
BackgroundInfluential
Identification of shared genetic susceptibility locus for coronary artery disease, type 2 diabetes and obesity: a meta-analysis of genome-wide studies
Wu, C., Gong, Y., Yuan, J., Gong, H., Zou, Y., & Ge, J. (2012) · Cardiovascular Diabetology · doi:10.1186/1475-2840-11-68 · Cited by 21
“Characteristics of whole genome studies of obesity or BMI-defined obesity [76–111].”
Background
Effect of an Estrogen Receptor-α Intron 4 Polymorphism on Fat Mass in 11-Year-Old Children
Tobias, J. H., Steer, C. D., Vilariño‐Güell, C., & Brown, M. A. (2007) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2006-2447 · Cited by 22
Identification and Replication of a Novel Obesity Locus on Chromosome 1q24 in Isolated Populations of Cilento
Ciullo, M., Nutile, T., Dalmasso, C., Sorice, R., Bellenguez, C., Colonna, V., Persico, M. G., & Bourgain, C. (2007) · Diabetes · doi:10.2337/db07-0970 · Cited by 22
“that two of them have already been linked or associated with obesity or BMI in previous studies (9,30,40).”
BackgroundResultInfluential
Genome-wide selection of tag SNPs using multiple-marker correlation
Hao, K. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm496 · Cited by 22
“(Bender and Lange, 2001; Chen et al., 2006; Hao et al., 2004; Herbert et al., 2006; Pe’er et al., 2006; Rosenberg et al., 2006; Wen et al., 2006) There are two strategies in dealing with multiple testing.”
Background
Empirical Null and False Discovery Rate Inference for Exponential FamiliesPreprint
Schwartzman, A. (2008) · Cited by 22
Combined linkage and association analyses identify a novel locus for obesity near PROX1 in Asians
Kim, H.-J., Yoo, Y. J., Ju, Y. S., Lee, S., Cho, S., Sung, J., Kim, J., & Seo, J. (2013) · Obesity · doi:10.1002/oby.20153 · Cited by 21
“Many studies tried to validate this finding, but it has shown inconsistent replication results (16-18).”
BackgroundResult
Evaluation of 41 Candidate Gene Variants for Obesity in the EPIC-Potsdam Cohort by Multi-Locus Stepwise Regression
Knüppel, S., Rohde, K., Meidtner, K., Drogan, D., Holzhütter, H., Boeing, H., & Fisher, E. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068941 · Cited by 22
From fused toes in mice to human obesity
Groop, L. (2007) · Nature Genetics · doi:10.1038/ng0607-706 · Cited by 21
Genomics and genome-wide association studies: An integrative approach to expression QTL mapping
Degnan, J. H., Lasky-Su, J. A., Raby, B. A., Xu, M., Molony, C. M., Schadt, E. E., & Lange, C. (2008) · Genomics · doi:10.1016/j.ygeno.2008.05.012 · Cited by 21
Interpreting Results of Large-Scale Genetic Association Studies
Dupuis, J., & O’Donnell, C. J. (2007) · JAMA · doi:10.1001/jama.297.5.529 · Cited by 21
Discovery and Validation of a Recessively Inherited Major-Effect QTL Conferring Resistance to Maize Lethal Necrosis (MLN) Disease
Murithi, A., Olsen, M. S., Kwemoi, D. B., Ogugo, V., Ertiro, B. T., Suresh, L. M., Beyene, Y., Das, B., Prasanna, B. M., & Gowda, M. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.767883 · Cited by 20
Genome-wide linkage screen for stature and body mass index in 3.032 families: evidence for sex- and population-specific genetic effects
Sammalisto, S., Hiekkalinna, T., Schwander, K., Kardia, S. L. R., Weder, A. B., Rodríguez, B. L., Doria, A., Kelly, J. A., Bruner, G. R., Harley, J. B., et al. (2008) · European Journal of Human Genetics · doi:10.1038/ejhg.2008.152 · Cited by 21
Association study of childhood obesity with eight genetic variants recently identified by genome-wide association studies
Meng, X., Song, J., Ma, J., Liu, F., Shang, X., Guo, X., & Wang, H. (2014) · Pediatric Research · doi:10.1038/pr.2014.88 · Cited by 20
Replication of genetic variants from genome-wide association studies with metabolic traits in an island population of the Adriatic coast of Croatia
Karns, R. A., Zhang, G., Jeran, N., Auguštin, D. H., Missoni, S., Niu, W., Indugula, S. R., Sun, G., Duraković, Z., Narančić, N. S., et al. (2010) · European Journal of Human Genetics · doi:10.1038/ejhg.2010.178 · Cited by 19
Quantitative genomics of voluntary exercise in mice: transcriptional analysis and mapping of expression QTL in muscle
Kelly, S. A., Nehrenberg, D. L., Hua, K., Garland, T., & Pomp, D. (2014) · Physiological Genomics · doi:10.1152/physiolgenomics.00023.2014 · Cited by 20
The Gene-Gene Interaction of INSIG-SCAP-SREBP Pathway on the Risk of Obesity in Chinese Children
Liu, F., Song, J., Shang, X., Meng, X., Ma, J., & Wang, H. (2014) · BioMed Research International · doi:10.1155/2014/538564 · Cited by 20
“[11] discovered that a single Hindawi Publishing Corporation BioMed Research International Volume 2014, Article ID 538564, 8 pages http://dx.”
Background
Lack of association between rs7566605 and obesity in a Chinese population
Feng, Y., Dong, H., Xiang, Q., Hong, X., Wilker, E. H., Zhang, Y., Xu, X., & Xu, X. P. (2006) · Human Genetics · doi:10.1007/s00439-006-0258-2 · Cited by 20
“Herbert et al. (2006) recently reported a whole-genome association study on obesity using 100 K single nucleotide polymorphism (SNP) chips, and identiWed a common SNP (rs7566605) 10 kb upstream of the transcription start site of the insulin induced gene 2 (INSIG2) associated with obesity in…”
BackgroundResultInfluential
Power of selective genotyping in genome-wide association studies of quantitative traits
Xing, C., & Xing, G. (2009) · BMC Proceedings · doi:10.1186/1753-6561-3-s7-s23 · Cited by 20
“For example, it was applied in studying genetic association of intelligence scores [8], attention-deficit hyperactivity disorder [9], and body mass index [10].”
Reactivation of adiponectin expression in obese patients after bariatric surgery
Hindle, A. K., Edwards, C., McCaffrey, T., Fu, S. W., & Brody, F. J. (2009) · Surgical Endoscopy · doi:10.1007/s00464-009-0780-0 · Cited by 20
“Recent data show a clear association between SNPs and morbidly obese diabetic subjects [19].”
Background
Association analysis of positional obesity candidate genes based on integrated data from transcriptomics and linkage analysis
Jiao, H., Kaaman, M., Dungner, E., Kere, J., Arner, P., & Dahlman, I. A. (2008) · International Journal of Obesity · doi:10.1038/sj.ijo.0803789 · Cited by 22
No Association between rs7566605 Variant and Being Overweight in Japanese
Kuzuya, M., Ando, F., Iguchi, A., & Shimokata, H. (2007) · Obesity · doi:10.1038/oby.2007.301 · Cited by 20
“(1) demonstrated that a common genetic single-nucleotide polymorphism (rs7566605) upstream of the transcription start site for insulin-induced gene 2 was associated with obesity in 694 individuals of the National Heart, Lung, and Blood Institute-Framingham Heart Study.”
Background
MC4R Variant Is Associated With BMI but Not Response to Resistance Training in Young Females
Suer, F. E., Harmon, B. T., Gordish‐Dressman, H., Clarkson, P. M., Thompson, P. D., Angelopoulos, T. J., Gordon, P. M., Hubal, M. J., Moyna, N. M., Pescatello, L. S., et al. (2010) · Obesity · doi:10.1038/oby.2010.180 · Cited by 19
MetaGen: reference-free learning with multiple metagenomic samples
Xing, X., Liu, J. S., & Zhong, W. (2017) · Genome biology · doi:10.1186/s13059-017-1323-y · Cited by 19
“Recent studies have found that some bacteria in the human gut can disrupt the metabolic/energy homeostasis [2, 45], and the bacteria’s interactions with the host’s genes [46] are closely associated with the host’s obesity level.”
Background
The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts
Bressler, J., Fornage, M., Hanis, C. L., Kao, W. H. L., Lewis, C. E., McPherson, R., Dent, R., Mosley, T. H., Pennacchio, L. A., & Boerwinkle, E. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-56 · Cited by 20
“Herbert et al. identified a genetic variant (rs7566605) 10 kb upstream of INSIG2 that was associated with obesity as assessed by a BMI ≥ 30 kg/m2 in participants in the Framingham Heart Study.”
BackgroundMethodResultInfluential
Possible role for ENPP1 polymorphism in obesity but not for INSIG2 and PLIN variants
Peeters, A. V., Beckers, S., Verrijken, A., Mertens, I. L., Gaal, L. V., & Hul, W. V. (2009) · Endocrine · doi:10.1007/s12020-009-9194-y · Cited by 19
Emergence of new infectious diseases
Woolhouse, M. E. J., & Antia, R. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0016 · Cited by 19
P2BAT: a massive parallel implementation of PBAT for genome-wide association studies in R
Hoffmann, T. J., & Lange, C. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl507 · Cited by 19
A tagging SNP in INSIG2 is associated with obesity-related phenotypes among Samoans
Deka, R., Xu, L., Pal, P., Toelupe, P. T., Laumoli, T. S., Xi, H., Zhang, G., Weeks, D. E., & McGarvey, S. T. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-143 · Cited by 18
“Note that the initial study used the recessive model to fit the association signal [1].”
ResultInfluential
Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring
Jiang, X., Jao, J., & Neapolitan, R. E. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143247 · Cited by 19
Primary Prevention of Childhood Obesity: An Interdisciplinary Analysis
Hilbert, A., Ried, J., Schneider, D., Juttner, C., Sosna, M., Dabrock, P., Lingenfelder, M., Voit, W., Rief, W., & Hebebrand, J. (2008) · Obesity Facts · doi:10.1159/000113598 · Cited by 18
Studies of CTNNBL1 and FDFT1variants and measures of obesity: analyses of quantitative traits and case-control studies in 18,014 Danes
Andreasen, C. H., Mogensen, M. S., Borch‐Johnsen, K., Sandbæk, A., Lauritzen, T., Almind, K., Hansen, L., Jørgensen, T., Pedersen, O. B., & Hansen, T. F. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-17 · Cited by 19
“Other GWA studies have reported variants in the proximity of INSIG2 [15,16] and within PFKP [2,16] as novel obesity gene loci, however, attempts to replicate the association for the INSIG2 variant have been inconsistent [17-24], which also appears true for variation in PFKP [17].”
BackgroundInfluential
Gene by Sex Interaction for Measures of Obesity in the Framingham Heart Study
Benjamin, A. M., Suchindran, S., Pearce, K., Rowell, J. V., Lien, L. F., Guyton, J. R., & McCarthy, J. J. (2010) · Journal of Obesity · doi:10.1155/2011/329038 · Cited by 19
“No SNPs from prior genome-wide association studies of BMI showed up among our top 1000 consensus, including SNPs in the genes INSIG2 , FTO [13, 25], and MC4R [26] (Figure 4).”
Koch, I.*, Slotta-Huspenina, J.*, Hollweck, R.*, Anastasov, N., Hofler, H.*, Quintanilla-Martinez, L., Fend, F.*: Real-time quantitative RT-PCR shows variable, assay-dependent sensitivity to formalin fixation : Implications for direct comparison of transcript levels in paraffin-embedded tissues. Diagn. Mol. Pathol. 15, 149-156 (2006)
Horn, T., Kremer, M., Dechow, T. N., Pfeifer, W. M., Geist, B., Perker, M., & Duyster, J. (2007) · Cited by 18
Childhood obesity: causes, consequences, and prevention
Ali, A. T., Al-Ani, F., & Al-ani, O. (2023) · Česká a slovenská farmacie · doi:10.5817/csf2023-1-21 · Cited by 20
Genetic Association Study with Metabolic Syndrome and Metabolic-Related Traits in a Cross-Sectional Sample and a 10-Year Longitudinal Sample of Chinese Elderly Population
Yang, J., Liu, J., Liu, J., Li, W., Li, X., He, Y., & Ye, L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0100548 · Cited by 17
Variation in the MC4R Gene Is Associated with Bone Phenotypes in Elderly Swedish Women
Garg, G., Kumar, J., McGuigan, F. E., Ridderstråle, M., Gerdhem, P., Luthman, H., & Åkesson, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0088565 · Cited by 17
“Genotyping and Statistical Analysis Five obesity associated SNPs from three genes were genotyped in both cohorts (Table S1) [33,42].”
Background
Does child–parent resemblance in body weight status vary by sociodemographic factors in the USA?
Zhang, Q., Lamichhane, R., Chen, H., Xue, H., & Wang, Y. (2014) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2013-203476 · Cited by 17
Global spatial patterns of infectious diseases and human evolution
Guégan, J., Prugnolle, F., & Frédéric Thomas, A. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0002 · Cited by 16
Review: Genetics of the cardiometabolic syndrome: new insights and therapeutic implications
Sookoian, S. C., & Pirola, C. J. (2007) · Therapeutic Advances in Cardiovascular Disease · doi:10.1177/1753944707082702 · Cited by 16
Evolution of parasites
Koella, J. C., & Turner, P. E. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0017 · Cited by 17
The genetics of cardiovascular disease
Delles, C., McBride, M., Padmanabhan, S., & Dominiczak, A. F. (2008) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2008.07.010 · Cited by 16
Resources for Genetic Variation Studies
Serre, D., & Hudson, T. J. (2006) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.7.080505.115806 · Cited by 17
A common polymorphism is associated with body mass index in Uyghur population
Zhang, J., Lin, R., Wang, F., Lü, M., Lin, R., Wang, S., Wen, H., Li, J., & Wang, X. (2008) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2008.03.022 · Cited by 17
Intimate relations: Evolutionary conflicts of pregnancy and childhood
Haig, D. (2007) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199207466.003.0006 · Cited by 17
Absence of Association Between the INSIG2 Gene Polymorphism (rs7566605) and Obesity in the European Youth Heart Study (EYHS)
Vimaleswaran, K. S., Franks, P. W., Brage, S., Sardinha, L. B., Andersen, L. B., Wareham, N. J., Ekelund, U., & Loos, R. J. F. (2009) · Obesity · doi:10.1038/oby.2008.650 · Cited by 17
“(1) reported a difference of 1 BMI unit for the genotypes of the SNP rs7566605 in children under a recessive model and this difference tracked throughout life (11–60 years of age), suggesting that the SNP had an early onset effect on BMI.”
BackgroundResultInfluential
Three at One Swoop!
Hinney, A., & Hebebrand, J. (2009) · Obesity Facts · doi:10.1159/000200020 · Cited by 17
Uncloaking the Genetic Determinants of Metabolic Syndrome
Lahiry, P., Pollex, R. L., & Hegele, R. A. (2008) · Lifestyle Genomics · doi:10.1159/000112459 · Cited by 16
“These conclusions also suggest that replication is essential to increase confidence in the findings. Genome-Wide Association Studies Genome-wide association studies are the second approach used to uncover the genetic basis of a complex disease or trait. This analysis is performed without prior assumptions regarding th…”
Background
Four SNPs of insulin-induced gene 1 associated with growth and carcass traits in Qinchuan cattle in China
Liu, Y., Liu, X., He, H., & Gu, Y. L. (2012) · Genetics and Molecular Research · doi:10.4238/2012.may.8.3 · Cited by 16
Is rs7566605, a SNP near INSIG2, associated with body mass in a randomized clinical trial of antipsychotics in schizophrenia?
Skelly, T. J., Pinheiro, A. P., Lange, L. A., & Sullivan, P. F. (2007) · Molecular Psychiatry · doi:10.1038/sj.mp.4001956 · Cited by 16
Genetic modifiers of obesity and bariatric surgery outcomes
Sevilla, S., & Hubal, M. J. (2013) · Seminars in Pediatric Surgery · doi:10.1053/j.sempedsurg.2013.10.017 · Cited by 15
Mining Pure, Strict Epistatic Interactions from High-Dimensional Datasets: Ameliorating the Curse of Dimensionality
Jiang, X., & Neapolitan, R. E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046771 · Cited by 15
“By looking at single-locus associations, researchers have identified over 150 risk loci associated with 60 common diseases and traits [8], [9], [10], [11], [12], [13].”
Background
A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in N orth I ndian adults
Srivastava, A. N., Mittal, B., Prakash, J., Srivastava, P., Srivastava, N., & Srivastava, N. (2016) · American Journal of Human Biology · doi:10.1002/ajhb.22923 · Cited by 15
“Genome-wide association studies (GWAS) have identified a number of obesity associated loci (Herbert et al., 2006; Lindgren et al., 2009; Loos et al., 2008; Maes et al., 1997; Meyre et al., 2009; Rankinen et al., 2006; Thorleifsson et al., 2009; Willer et al., 2009).”
Background
Pathophysiology and genetics of obesity.
Srivastava, N., Lakhan, R., & Mittal, B. (2007) · PubMed · Cited by 15
Frequencies of obesity susceptibility alleles among ethnically and racially diverse bariatric patient populations
Parikh, M., Hetherington, J. A., Sheth, S., Seiler, J. L., D, H. O. M., Gerhard, G. S., Wood, C., & Still, C. D. (2012) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2012.04.004 · Cited by 15
Role of In Silico Tools in Gene Discovery
Yu, B. (2008) · Molecular Biotechnology · doi:10.1007/s12033-008-9134-8 · Cited by 17
“It is common to have repeated measurements in complex traits, such as body mass index in obesity [ 4 ].”
Background
Common INSIG2 polymorphisms are associated with age-related changes in body size and high-density lipoprotein cholesterol from young adulthood to middle age
Fornage, M., Papanicolaou, G., Lewis, C. E., Boerwinkle, E., & Siscovick, D. S. (2010) · Metabolism · doi:10.1016/j.metabol.2009.11.005 · Cited by 15

Authors: Herbert, A., Gerry, N. P., McQueen, M. B., Heid, I. M., Pfeufer, A., Illig, T., Wichmann, H.-E., Meitinger, T., Hunter, D., Hu, F. B., Colditz, G., Hinney, A., Hebebrand, J., Koberwitz, K., Zhu, X., Cooper, R., Ardlie, K., Lyon, H., Hirschhorn, J. N., Laird, N. M., Lenburg, M. E., Lange, C., & Christman, M. F.
Affiliations: Boston University (US)
Corresponding author: Herbert, Alan
Christman, Michael F.
ORCID: Herbert, Alan
McQueen, Matthew B.
Heid, Iris M.
Wichmann, H.-Erich
Meitinger, Thomas
Hu, Frank B.
Colditz, Graham
Hinney, Anke
Hebebrand, Johannes
Zhu, Xiaofeng
Cooper, Richard
Ardlie, Kristin
Hirschhorn, Joel N.
Laird, Nan M.
Lenburg, Marc E.
Lange, Christoph
Venue: Science
Publisher: American Association for the Advancement of Science (AAAS)
Published: 2006-04-14
Volume: 312
Issue: 5771
Pages: 279-283
ISSN: 0036-8075 (ISSN-L)
1095-9203
DOI: 10.1126/science.1124779
OpenAlex: W2149512324
Cited by: 732
References: 32
Citations by year: 2026: 2 · 2025: 5 · 2024: 2 · 2023: 10 · 2022: 8 · 2021: 10 · 2020: 8 · 2019: 11 · 2018: 2 · 2017: 17 · 2016: 19 · 2015: 28 · 2014: 30 · 2013: 37 · 2012: 39
FWCI: 75.55
Type: journal article
Language: en
Open access: closed
Locations: Science (publishedVersion)
PubMed (publishedVersion)
Civil War Book Review (submittedVersion)
mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
Site cant be reached (submittedVersion)
Funders: National Heart, Lung, and Blood Institute (R01 HL54485, U01HL065899, R01HL066289, R01HL66289, R01HL074166, U01 HL65899)
National Institute of Mental Health (R01MH59532, R01MH059532)
National Cancer Institute (CA-87969, P01CA087969)
National Institute of General Medical Sciences (R01GM046877)
National Institute of Diabetes and Digestive and Kidney Diseases (P30DK046200, K23DK067288, P30 DK-46200)
Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD060726)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
Keywords: obesity, genetic association, INSIG2, childhood obesity, adult obesity, type 2 diabetes risk, whole genome scan, Framingham Heart Study, African Americans
MeSH terms: Adult, Alleles, Black or African American, Child, Europe, Female, Gene Frequency, Genes, Recessive, Genotype, Haplotypes, Humans, Male, Membrane Proteins, Models, Genetic, Obesity, Genetic Variation, Cohort Studies, Linkage Disequilibrium, Body Mass Index, Case-Control Studies, Genetic Predisposition to Disease, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, White People, Intracellular Signaling Peptides and Proteins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

A common genetic variant is associated with adult and childhood obesity.

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks