title: A latent variable partial least squares path modeling approach to regional association and polygenic effect with applications to a human obesity study.
abstract: Genetic association studies are now routinely used to identify single nucleotide polymorphisms (SNPs) linked with human diseases or traits through single SNP-single trait tests. Here we introduced partial least squares path modeling (PLSPM) for association between single or multiple SNPs and a latent trait that can involve single or multiple correlated measurement(s). Furthermore, the framework naturally provides estimators of polygenic effect by appropriately weighting trait-attributing alleles. We conducted computer simulations to assess the performance via multiple SNPs and human obesity-related traits as measured by body mass index (BMI), waist and hip circumferences. Our results showed that the associate statistics had type I error rates close to nominal level and were powerful for a range of effect and sample sizes. When applied to 12 candidate regions in data (N = 2,417) from the European Prospective Investigation of Cancer (EPIC)-Norfolk study, a region in FTO was found to have stronger association (rs7204609∼rs9939881 at the first intron P = 4.29×10(-7)) than single SNP analysis (all with P>10(-4)) and a latent quantitative phenotype was obtained using a subset sample of EPIC-Norfolk (N = 12,559). We believe our method is appropriate for assessment of regional association and polygenic effect on a single or multiple traits.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan, China.
authors.forename: Fuzhong
authors.initials: F
authors.lastname: Xue
authors.forename: Shengxu
authors.initials: S
authors.lastname: Li
authors.forename: Jian'an
authors.initials: J
authors.lastname: Luan
authors.forename: Zhongshang
authors.initials: Z
authors.lastname: Yuan
authors.forename: Robert N
authors.initials: RN
authors.lastname: Luben
authors.forename: Kay-Tee
authors.initials: KT
authors.lastname: Khaw
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Wareham
authors.forename: Ruth J F
authors.initials: RJ
authors.lastname: Loos
authors.forename: Jing Hua
authors.initials: JH
authors.lastname: Zhao
mesh_terms: D000483:Alleles; D000886:Anthropometry; D015992:Body Mass Index; D015331:Cohort Studies; D003198:Computer Simulation; D005060:Europe; D005260:Female; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism; D009765:Obesity / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide