Genetic polymorphisms in CYP17 , CYP3A4 , CYP19A1 , SRD5A2 , IGF-1 , and IGFBP-3 and prostate cancer risk in African-American men: The Flint Men's Health Study

BACKGROUND Association studies have examined the significance of several candidate genes based on biological pathways relevant to prostate carcinogenesis, including both the androgen and insulin-like growth factor pathways. Clinical and epidemiologic evidence suggest that androgens, specifically testosterone and dihydrotestosterone (DHT) are important not only in normal prostate growth but in the pathogenesis of prostate cancer. Similarly, the insulin-like growth factor-1 (IGF-1) signaling pathway regulates both cellular proliferation and apoptosis. Therefore, genes involved in the biosynthesis, activation, metabolism and degradation of androgens and the stimulation of mitogenic and antiapoptotic activities of prostate epithelial cells represent important candidates for affecting the development and progression of prostate cancer. METHODS Using resources from the Flint Men's Health Study, a population-based case control study of African-American men aged 40–79, we evaluated the associations between selected single-nucleotide polymorphisms (SNPs) in the CYP17 , CYP3A4 , CYP19A1 , SDR5A2 , IGF1 , and IGFBP3 genes and prostate cancer diagnosis in 473 men (131 prostate cancer cases and 342 disease-free controls). RESULTS We found a significant association between prostate cancer and selected CYP17 SNP genotypes, with the heterozygous genotype conferring decreased risk. Suggestive evidence for association between IGF1 SNPs and prostate cancer were also found. No significant associations were observed between SNPs in the other genes and prostate cancer. CONCLUSIONS These findings suggest that variation in or around CYP17 and/or IGF1 may be associated with prostate cancer development in the African-American population. Additional studies are needed to determine whether these polymorphisms are indeed associated with prostate cancer risk in African Americans. Prostate 68: 296–305, 2008. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57913/1/20696_ftp.pd

Exploring pleiotropy using principal components

A standard multivariate principal components (PCs) method was utilized to identify clusters of variables that may be controlled by a common gene or genes (pleiotropy). Heritability estimates were obtained and linkage analyses performed on six individual traits (total cholesterol (Chol), high and low density lipoproteins, triglycerides (TG), body mass index (BMI), and systolic blood pressure (SBP)) and on each PC to compare our ability to identify major gene effects. Using the simulated data from Genetic Analysis Workshop 13 (Cohort 1 and 2 data for year 11), the quantitative traits were first adjusted for age, sex, and smoking (cigarettes per day). Adjusted variables were standardized and PCs calculated followed by orthogonal transformation (varimax rotation). Rotated PCs were then subjected to heritability and quantitative multipoint linkage analysis. The first three PCs explained 73% of the total phenotypic variance. Heritability estimates were above 0.60 for all three PCs. We performed linkage analyses on the PCs as well as the individual traits. The majority of pleiotropic and trait-specific genes were not identified. Standard PCs analysis methods did not facilitate the identification of pleiotropic genes affecting the six traits examined in the simulated data set. In addition, genes contributing 20% of the variance in traits with over 0.60 heritability estimates could not be identified in this simulated data set using traditional quantitative trait linkage analyses. Lack of identification of pleiotropic and trait-specific genes in some cases may reflect their low contribution to the traits/PCs examined or more importantly, characteristics of the sample group analyzed, and not simply a failure of the PC approach itself

Genetic Contributors of Incident Stroke in 10,700 African Americans with Hypertension: A Meta-Analysis from the Genetics of Hypertension Associated Treatments and Reasons for Geographic and Racial Differences in Stroke Studies

Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals. Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs aiming to evaluate cross-ethnic performance. Results: We identified 10 statistically significant (p \u3c 5.00E-08) and 90 additional suggestive (p \u3c 1.00E-06) variants associated with incident stroke in the meta-analysis. Six of the top 10 variants were located in an intergenic region on chromosome 18 (LINC01443-LOC644669). Additional variants of interest were located in or near the COL12A1, SNTG1, PCDH7, TMTC1, and NTM genes. Replication was conducted in the Warfarin Pharmacogenomics Cohort (WPC), and while none of the variants were directly validated, seven intronic variants of NTM proximal to our target variants, had a p-value \u3c5.00E-04 in the WPC. The inclusion of the PRS did not improve the prediction accuracy compared to a reference model adjusting for age, sex, and genetic ancestry in either study and had lower predictive accuracy compared to models accounting for established stroke risk factors. These results demonstrate the necessity for PRS derivation in AAs, particularly for diseases that affect AAs disproportionately. Conclusion: This study highlights biologically plausible genetic determinants for incident stroke in hypertensive AAs. Ultimately, a better understanding of genetic risk factors for stroke in AAs may give new insight into stroke burden and potential clinical tools for those among the highest at risk

Gene-centric meta-analyses of 108,912 individuals confirm known body mass index loci and reveal three novel signals

Recent genetic association studies have made progress in uncovering components of the genetic architecture of body mass index (BMI). We used the ITMAT-Broad-CARe (IBC) array comprising up to 49,320 single nucleotide polymorphisms (SNPs) across ~2,100 metabolic and cardiovascular-related loci to genotype up to 108,912 individuals of European ancestry (EA), African Americans, Hispanics, and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P<2.40E-06), we identify novel BMI associations in loci TOMM40-APOE-APOC1 (rs2075650, P=2.95E-10), SREBF2 (a sterol regulatory element binding transcription factor gene, rs5996074, P=9.43E-07) and NTRK2 (a BDNF receptor, rs1211166, P=1.04E-06) in the Phase IV meta-analysis. Of ten loci with previous evidence for BMI association represented on IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI associated signals in BDNF and MC4R regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B1 notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics

Genetic Epidemiology of Body Mass Index and Body Mass Change From Adolescence to Young Adulthood

The complex interplay between genes and environment affecting body mass gain over lifecycle periods of risk is not well understood. We use longitudinal sibling cohort data to examine the role of shared household environment, additive genetic, and shared genetic effects on Body Mass Index (BMI) and BMI change. In the National Longitudinal Study of Adolescent Health, siblings and twin pairs sharing households for ≥10 years as adolescents (N=5524; mean=16.5±1.7 years) were followed into young adulthood (N = 4368; mean=22.4±1.8 years). Using a variance component approach, we quantified genetic and household effects on BMI in siblings and non-siblings sharing household environments over time. Adjusting for race, age, sex, and age by sex interaction, we detected a heritability of 0.43±0.05 for BMI change. Significant household effects were noted during the young adulthood time period only (0.11±0.06). We find evidence for shared genetic effects between BMI and BMI change during adolescence [Genetic Correlation (ρG)=0.61±0.03] and young adulthood (ρG=0.23±0.06). Our findings support a complex etiology of BMI and BMI change

Genome-Wide Association Study of Anthropometric Traits and Evidence of Interactions With Age and Study Year in Filipino Women

Increased values of multiple adiposity-related anthropometric traits are important risk factors for many common complex diseases. We performed a genome-wide association (GWA) study for four quantitative traits related to body size and adiposity (body mass index [BMI], weight, waist circumference, and height) in a cohort of 1,792 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey. This is the first GWA study of anthropometric traits in Filipinos, a population experiencing a rapid transition into a more obesogenic environment. In addition to identifying suggestive evidence of additional SNP association signals (P < 10−5), we replicated (P < 0.05, same direction of additive effect) associations previously reported in European populations of both BMI and weight with MC4R and FTO, of BMI with BDNF, and of height with EFEMP1, ZBTB38, and NPPC, but none with waist circumference. We also replicated loci reported in Japanese or Korean populations as associated with BMI (OTOL1) and height (HIST1H1PS2, C14orf145, GPC5). A difference in local linkage disequilibrium between European and Asian populations suggests a narrowed association region for BDNF, while still including a proposed functional non-synonymous amino acid substitution variant (rs6265, Val66Met). Finally, we observed significant evidence (P < 0.0042) for age-by-genotype interactions influencing BMI for rs17782313 (MC4R) and rs9939609 (FTO), and for a study year-by-genotype interaction for rs4923461 (BDNF). Our results show that several genetic risk factors are associated with anthropometric traits in Filipinos and provide further insight into the effects of BDNF, FTO, and MC4R on BMI

Association of RGS2 and RGS5 variants with schizophrenia symptom severity

Several lines of evidence indicate that Regulator of G Protein Signaling 4 (RGS4) contributes to schizophrenia vulnerability. RGS4 is one of a family of molecules that modulate signaling via G-protein coupled receptors. Five genes encoding members of this family (RGS2, RGS4, RGS5, RGS8 and RGS16) map to chromosome 1q23.3-1q31. Due to overlapping cellular functions and chromosomal proximity, we hypothesized that multiple RGS genes may contribute to schizophrenia severity and treatment responsiveness

Genome-wide linkage scan for prostate cancer susceptibility genes in men with aggressive disease: significant evidence for linkage at chromosome 15q12

Epidemiological and twin studies have consistently demonstrated a strong genetic component to prostate cancer (PCa) susceptibility. To date, numerous linkage studies have been performed to identify chromosomal regions containing PCa susceptibility genes. Unfortunately, results from these studies have failed to form any obvious consensus regarding which regions are most likely to contain genes that may contribute to PCa predisposition. One plausible explanation for the difficulty in mapping susceptibility loci is the existence of considerable heterogeneity in the phenotype of PCa, with significant variation in clinical stage and grade of disease even among family members. To address this issue, we performed a genome-wide linkage scan on 71 informative families with two or more men with aggressive PCa. When only men with aggressive PCa were coded as affected, statistically significant evidence for linkage at chromosome 15q12 was detected (LOD=3.49; genome-wide p =0.005). Furthermore, the evidence for linkage increased when analyses were restricted to Caucasian–American pedigrees ( n =65; LOD=4.05) and pedigrees with two confirmed aggressive cases ( n =42, LOD=4.76). Interestingly, a 1-LOD support interval about our peak at 15q12 overlaps a region of suggestive linkage, 15q11, identified by a recent linkage study on 1,233 PCa families by the International Consortium for Prostate Cancer Genetics. Using a more rigid definition of PCa in linkage studies will result in a severe reduction in sample sizes available for study, but may ultimately prove to increase statistical power to detect susceptibility genes for this multigenic trait.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47600/1/439_2006_Article_149.pd

Association of polymorphisms in CASP10 and CASP8 with FEV 1 /FVC and bronchial hyperresponsiveness in ethnically diverse asthmatics

Several chromosomal regions have been identified using family-based linkage analysis to contain genes contributing to the development of asthma and allergic disorders. One of these regions, chromosome 2q32-q33, contains a gene cluster containing CFLAR, CASP10 and CASP8. These genes regulate the extrinsic apoptosis pathway utilized by several types of immune and structural cells that have been implicated in the pathogenesis of asthma