@article {1261,
	title = {A genome-wide association study identifies novel loci associated with circulating IGF-I and IGFBP-3.},
	journal = {Hum Mol Genet},
	volume = {20},
	year = {2011},
	month = {2011 Mar 15},
	pages = {1241-51},
	abstract = {<p>Insulin-like growth factor-I (IGF-I) and insulin-like growth factor-binding protein-3 (IGFBP-3) are involved in cell replication, proliferation, differentiation, protein synthesis, carbohydrate homeostasis and bone metabolism. Circulating IGF-I and IGFBP-3 concentrations predict anthropometric traits and risk of cancer and cardiovascular disease. In a genome-wide association study of 10 280 middle-aged and older men and women from four community-based cohort studies, we confirmed a known association of single nucleotide polymorphisms in the IGFBP3 gene region on chromosome 7p12.3 with IGFBP-3 concentrations using a significance threshold of P < 5 {\texttimes} 10(-8) (P = 3.3 {\texttimes} 10(-101)). Furthermore, the same IGFBP3 gene locus (e.g. rs11977526) that was associated with IGFBP-3 concentrations was also associated with the opposite direction of effect, with IGF-I concentration after adjustment for IGFBP-3 concentration (P = 1.9 {\texttimes} 10(-26)). A novel and independent locus on chromosome 7p12.3 (rs700752) had genome-wide significant associations with higher IGFBP-3 (P = 4.4 {\texttimes} 10(-21)) and higher IGF-I (P = 4.9 {\texttimes} 10(-9)) concentrations; when the two measurements were adjusted for one another, the IGF-I association was attenuated but the IGFBP-3 association was not. Two additional loci demonstrated genome-wide significant associations with IGFBP-3 concentration (rs1065656, chromosome 16p13.3, P = 1.2 {\texttimes} 10(-11), IGFALS, a confirmatory finding; and rs4234798, chromosome 4p16.1, P = 4.5 {\texttimes} 10(-10), SORCS2, a novel finding). Together, the four genome-wide significant loci explained 6.5\% of the population variation in IGFBP-3 concentration. Furthermore, we observed a borderline statistically significant association between IGF-I concentration and FOXO3 (rs2153960, chromosome 6q21, P = 5.1 {\texttimes} 10(-7)), a locus associated with longevity. These genetic loci deserve further investigation to elucidate the biological basis for the observed associations and clarify their possible role in IGF-mediated regulation of cell growth and metabolism.</p>},
	keywords = {Aged, Chromosomes, Human, Pair 7, Cohort Studies, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Insulin-Like Growth Factor Binding Protein 3, Insulin-Like Growth Factor I, Male, Polymorphism, Single Nucleotide},
	issn = {1460-2083},
	doi = {10.1093/hmg/ddq560},
	author = {Kaplan, Robert C and Petersen, Ann-Kristin and Chen, Ming-Huei and Teumer, Alexander and Glazer, Nicole L and D{\"o}ring, Angela and Lam, Carolyn S P and Friedrich, Nele and Newman, Anne and M{\"u}ller, Martina and Yang, Qiong and Homuth, Georg and Cappola, Anne and Klopp, Norman and Smith, Holly and Ernst, Florian and Psaty, Bruce M and Wichmann, H-Erich and Sawyer, Douglas B and Biffar, Reiner and Rotter, Jerome I and Gieger, Christian and Sullivan, Lisa S and V{\"o}lzke, Henry and Rice, Kenneth and Spyroglou, Ariadni and Kroemer, Heyo K and Ida Chen, Y-D and Manolopoulou, Jenny and Nauck, Matthias and Strickler, Howard D and Goodarzi, Mark O and Reincke, Martin and Pollak, Michael N and Bidlingmaier, Martin and Vasan, Ramachandran S and Wallaschofski, Henri}
}
@article {6296,
	title = {A robust method for genome-wide association meta-analysis with the application to circulating insulin-like growth factor I concentrations.},
	journal = {Genet Epidemiol},
	volume = {38},
	year = {2014},
	month = {2014 Feb},
	pages = {162-71},
	abstract = {<p>Genome-wide association studies (GWAS) offer an excellent opportunity to identify the genetic variants underlying complex human diseases. Successful utilization of this approach requires a large sample size to identify single nucleotide polymorphisms (SNPs) with subtle effects. Meta-analysis is a cost-efficient means to achieve large sample size by combining data from multiple independent GWAS; however, results from studies performed on different populations can be variable due to various reasons, including varied linkage equilibrium structures as well as gene-gene and gene-environment interactions. Nevertheless, one should expect effects of the SNP are more similar between similar populations than those between populations with quite different genetic and environmental backgrounds. Prior information on populations of GWAS is often not considered in current meta-analysis methods, rendering such analyses less optimal for the detecting association. This article describes a test that improves meta-analysis to incorporate variable heterogeneity among populations. The proposed method is remarkably simple in computation and hence can be performed in a rapid fashion in the setting of GWAS. Simulation results demonstrate the validity and higher power of the proposed method over conventional methods in the presence of heterogeneity. As a demonstration, we applied the test to real GWAS data to identify SNPs associated with circulating insulin-like growth factor I concentrations. </p>},
	keywords = {Computer Simulation, Genetic Linkage, Genome, Genome-Wide Association Study, Humans, Insulin-Like Growth Factor I, Meta-Analysis as Topic, Models, Genetic, Polymorphism, Single Nucleotide, Sample Size},
	issn = {1098-2272},
	doi = {10.1002/gepi.21766},
	author = {Wang, Tao and Zhou, Baiyu and Guo, Tingwei and Bidlingmaier, Martin and Wallaschofski, Henri and Teumer, Alexander and Vasan, Ramachandran S and Kaplan, Robert C}
}
