ASHG 2012 abstracts (3): miscellaneous

The Myth of Random Mating: Evidence of ancestry-related assortative mating across 3 generations in Framingham, MA. R. Sebro^1,2, G. Peloso^3,4, J. Dupuis^5,6, N. Risch^1,7,8 1) Institute for Human Genetics, University of California, San Francisco, San Francisco, CA; 2) Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA; 3) Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA; 4) Program in Medical and Population Genetics, Broad Institute, Cambridge, MA; 5) Department of Biostatistics, Boston University School of Public Health, Boston MA; 6) The National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, MA; 7) Department of Biostatistics and Epidemiology, University of California, San Francisco, San Francisco, CA; 8) Division of Research, Kaiser Permanente, Oakland, CA.

   The factors that influence spouse selection are important to geneticists because the mating pattern determines the genetic structure of a population. There has been evidence of positive assortative mating (PAM) related to several phenotypic traits like height. Ancestrally-related PAM is necessary for genetic population stratification, which means spouses are more likely to share genes of common ancestry. Prior studies have shown strong ancestry-related assortative mating among Latino populations. Here, Caucasian spouse pairs from the Framingham Heart Study (FHS) Original and Offspring cohorts (N=885) genotyped on Affymetrix 500K were analyzed using principal components (PC) analysis. Data from individuals genotyped in HapMap and the Human Genome Diversity Project (HGDP) were projected onto these PCs to facilitate interpretation. Based on these and other data, the first principal component delineates the prominent northwest-to-southeast European cline. In our data, there was clear clustering on this axis, probably separating individuals of English/Irish/German ancestry from those of Italian ancestry. The second principal component also reveals strong clustering, and likely reveals individuals of Ashkenazi Jewish ancestry. In the Original (older) cohort, there is a very strong correlation in PC1 between the spouses (r=0.73, P=2e-22) and also for PC2 (r=0.80, P=4e-29). In the Offspring cohort the spouse correlations were lower but still highly significant: r=0.38, P=3e-28 for PC1 and r=0.45, P =9e-40) for PC2. Examination of scatter plots for spouse pairs in the two generations reveals both a reduction in clustering and lower but still evident correlation in the Offspring cohort. Of genetic impact, we observed highly significant Hardy-Weinberg disequilibrium (homozygote excess) for SNPs loading heavily on PC1 and PC2 across 3 generations, and also highly significant linkage disequilibrium between the same set of SNPs located on different chromosomes. These results are consistent with demographic patterns of social homogamy which have existed in Framingham over several generations, and a general trend of reduced homogamy over time. While Framingham is not representative of the general US population, its historic mating patterns serve as a reminder that assumptions of Hardy Weinberg and Linkage Equilibrium need to be made with caution when applied to genetic loci that are related to ancestry in any population.




A web-based initiative to accelerate research on genetics and disease in African Americans. K. E. Barnholt¹, A. K. Kiefer¹, H. L. Gates, Jr.², M. Nelson¹, M. Mullins¹, E. Baker³, J. Frank¹, C. D. Bustamante⁴, T. W. Love⁵, R. A. Kittles⁶, N. Eriksson¹, J. L. Mountain¹ 1) 23andMe, Inc., Mountain View, CA; 2) W.E.B. Du Bois Institute for African and African American Studies, Harvard University, Cambridge, MA; 3) 23andYou.com; 4) Department of Genetics, Stanford University School of Medicine, Stanford, CA; 5) Onyx Pharmaceuticals, Inc., South San Francisco, CA; 6) College of Medicine, University of Illinois at Chicago, Chicago, IL.

   Little is known about the connections between DNA and disease in African Americans, in part because most genetics research has involved only those of European ancestry. Greater understanding of such connections could improve diagnoses and lead to opportunities for more personalized health care. In 2011 23andMe, Inc., a personal genomics and research company, launched the Roots into the Future initiative, which aims to enroll 10,000 African Americans in an innovative research project. The study seeks to determine whether genetic associations previously identified in Europeans are relevant to African Americans and to discover other genetic markers linked to conditions of particular relevance to the African American community. Currently the 23andMe cohort includes nearly 10,000 African Americans, over 5700 of whom were recruited through the Roots into the Future initiative. Each of these individuals (58% female, 42% male; mean age: 44) has submitted a saliva sample for genotyping via 23andMe’s custom genotyping array, which includes approximately 1 million single nucleotide polymorphisms. Participants are currently contributing information about their health and traits through online surveys. To date over 6200 participants have completed an average of 10.6 surveys. Using the genetic data we estimated the percent African and European ancestry of each participant. Median estimates were 73% and 23% respectively (with 4% uncertain). As expected, the higher a person’s proportion of European ancestry, the greater the chance that person carries variants that are more common among Europeans than among Africans, such as those linked to HIV-resistance and alpha-1 antitrypsin deficiency. Furthermore, the higher a person’s proportion of African ancestry, the more likely that person reported having curly hair, high blood pressure and type 2 diabetes, and the less likely that person reported having facial wrinkles, rosacea and Parkinson’s Disease. Based on data for over 8700 individuals likely to self-identify as African American, we replicated over 25 genetic associations reported previously for African Americans, including those for body-mass index, type 2 diabetes, lupus, height, and osteoporosis. For conditions for which we have already accrued at least 500 cases among this cohort, such as asthma, migraines, and uterine fibroids, we anticipate having power either to replicate associations identified through previous studies of Europeans or to find new associations.



Hidden heritability and risk prediction based on genome-wide association studies. N. Chatterjee¹, B. Wheeler², J. Sampson¹, P. Hartge¹, S. Chanock¹, J. Park¹ 1) National Institute of Health, Rockville, MD, USA; 2) Information management system, Rockville, MD.

   Known discoveries from genome-wide association studies have limited predictive ability for individual traits, but recent estimates of “hidden heritability” suggest that in the future performance of predictive models can be potentially enhanced by incorporation of a large number of SNPs each with individually small effects. We use a novel theoretical model, discoveries from the largest genome-wide association studies and recent estimates of hidden heritability to project the predictive performance of polygenic models for ten complex traits as a function of the number and distribution of effect sizes for the underlying susceptibility SNPs, the sample size of the training dataset and the balance of true and false positives associated with the SNP selection criterion. We project, for example, that while 45% of the total variance of adult height has been attributed to common variants, a predictive model built based on as many as one million people may only explain 33.4% of variance of the trait in an independent sample. For rare highly familial conditions, such as Type 1 diabetes and Crohn’s disease, risk models including family history and optimal polygenic scores built based on current GWAS can identify a large proportion (e.g 80-90%) of cases by targeting a small group of high-risk individuals (e.g subjects with top 20% risk). In contrast, for more common conditions with modest familial components, such as Type 2 diabetes (T2D), coronary heart disease (CAD) and prostate cancer (PrCA), risk models built based on GWAS with current or foreseeable sample sizes (e.g triple in size) can miss large proportion (>50%) of cases by targeting a small group of high-risk individuals. For these common disease, the proportion of the population that can be identified to have 2-fold or higher risk than an average person in the population ranged between 1.1% (CAD) and 7.0% (PrCA) for polygenic models built based on current GWAS. If the sample size for future studies could be tripled, these proportions could range between 6.1% (CAD) and 18.8% (T2D). Our analyses suggest that the predictive utility of polygenic models depends not only on heritability, but also on achievable sample sizes, effect-size distribution and information on other risk-factors, including family history.



GWAS Identifies Biologically Relevant SNP Associations with Sexual Partnering Behavior. J. Gelernter^{1, 2}, H. R. Kranzler³, R. Sherva⁴, R. Koesterer⁴, L. Almasy⁵, H. Zhao¹, L. A. Farrer⁴ 1) Yale University School of Medicine, New Haven, CT; 2) VA CT Healthcare Center, West Haven, CT; 3) University of Pennsylvania School of Medicine, Philadelphia, PA; 4) Boston University School of Medicine, Boston, MA; 5) Texas Biomedical Research Institute, San Antonio, TX.

   The specific factors influencing human sexual partnering are poorly understood. Arguably, in the pre-modern era, multiple mating may have been tied to selection for traits related to survival including resistance to infection and starvation, strength, and certain behaviors. Recently, we completed a GWAS using the Illumina Omni-Quad microarray in ~5800 African- and European-American (AA and EA) participants in genetic studies of alcohol, cocaine, and opioid dependence. Subjects were interviewed using the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) - an instrument that covers all major DSM-IV diagnoses as well as other numerous psychiatric and lifestyle traits. One of these is the response to: “How many sexual partners have you had in your life?” Association of age-adjusted residuals of this variable with more than 3 million SNPs reliably imputed using the 1K Genomes reference panel was tested in each sex*population subgroup using generalized estimating equations. Results from subgroup analyses were combined by meta analysis. SNPs with p-values <1E-06 were genotyped in a replication sample of ~2300 subjects. Genomewide-significant results were obtained for 13 SNPs including ones that map to genes coding proteins involved in reproductive-related functions (e.g., rs74738626 in KCNU1 which encodes a testes-specific K+ channel [p=1.2E-12], rs78227383 in NME5, a nucleoside diphosphate kinase which may have a specific function in the phosphotransfer network involved in spermatogenesis [p=4.0E-11 in EAs only], and rs76221611 in CCND2 which encodes cyclin D2, shown to be highly expressed in ovarian and testicular tumors [p=3.3E-11 in AAs only]), immune response (e.g., rs2709778 in GARS which encodes gylcyl-tRNA synthetase shown to be a target of autoantibodies in human autoimmune diseases [p=1.0E-10 in males only]), and other genes of biological interest (e.g., rs10849971 in ALDH2, an alcohol-metabolizing enzyme that is also an alcohol dependence risk locus [p=9.6E-09 in females only]). These findings have clear implications with respect to normal sexual function and potentially for risk of sexually transmitted disease.




Ubiquitous polygenicity of human complex traits: genome-wide analysis of 49 traits in Koreans. J. Yang¹, T. Lee², J. Kim³, S. Cho⁴, P. Visscher^1,5, H. Kim^2,3,4 1) University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia; 2) Department of Agricultural Biotechnology, Seoul National University, Seoul, Korea; 3) Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea; 4) C&K Genomics, Seoul, Korea; 5) The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia.

   Recent studies in population of European ancestry have shown that 30-50% of heritability for human complex traits such as height (Yang et al. 2010) and body mass index (Yang et al. 2011), and common diseases such as schizophrenia (Lee et al. 2012) and rheumatoid arthritis (Stahl et al. 2012) can be captured by common SNPs, and that genetic variation can be attributed to chromosomes, in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed 49 human quantitative traits, many of which are relevant to human diseases, in 7,170 unrelated Korean individuals genotyped on 326,591 SNPs. For 43 of the 49 traits, we estimated a significant (P < 0.05) proportion of variance explained by all SNPs (h2G). On average across 47 of the 49 traits for which the estimate of h2G is non-zero, 13.4% (range of 3.4% to 31.6%) of phenotypic variance can be explained by all the SNPs being analysed, or approximately one-third (range of 7.8% to 76.8%) of narrow sense heritability. In contrast, on average across 25 of the 49 traits, the top associated SNPs at genome-wide significance level (P < 5e-8) explain 1.5% (range of 0.5% to 3.8%) of phenotypic variance. The majority (~92%) of explained variation estimated from all SNPs is captured by the SNPs with p-values < 0.031 in single SNP association analyses. Longer genomic segments tend to explain more phenotypic variation, with a correlation of 0.78 between the estimate of variance explained by individual chromosomes and their physical length. This correlation was stronger (0.81) for intergenic regions. Despite the fact that there are a few SNPs with large effects for most traits, these results suggest that polygenicity is ubiquitous for most human complex traits, and that a substantial proportion of heritability is captured by common SNPs.


What is the total SNP-associated heritability for alcohol dependence? N. G. Martin¹, G. Zhu¹, P. A. Lind¹, A. C. Heath², P. A. F. Madden², M. L. Pergadia², G. W. Montgomery¹, J. B. Whitfield¹ 1) Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia; 2) Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.

   Background. Much has been written about the so-called “missing heritability” for complex traits. Nowhere is this more pertinent than for alcohol and nicotine dependence (AD, ND) for which there are estimates of heritability of up to 65% from twin studies, yet few causal variants have been replicated from GWAS studies, despite large sample sizes, suggesting that individual effect sizes of SNPs must be very small. Recently new statistical genetic techniques have been developed which allow estimation of the total variance associated with all SNPs on a GWAS chip, but this has yet to be applied to AD and ND. Methods. The current analysis is based on AD and ND symptom count data from over 8000 participants in our population-based twin-family studies who have used either alcohol or cigarettes at some stage of their lives. They were individually genotyped with Illumina 370K or 660K chips and 7.034M genotypes were imputed from HapMap 3 and 1000-Genomes data. The GCTA program of Yang, Visscher et al is used first to detect the degree of relatedness between apparently unrelated subjects, based on a set of about 300,000 SNPs pruned for LD. Phenotypic similarity is then regressed on IBS sharing for all possible relative pairs to estimate the total amount of variance due to SNPs on the chip. Results. Based on GCTA analysis for other complex traits we expect to find SNP associated variance accounting for about half the heritability estimated from conventional genetic epidemiology designs. However, these estimates are highly sensitive to population stratification so great care will be taken to remove all traces of population stratification during the analysis. Conclusions. The gap between the SNP-associated variance estimated by GCTA and twin and family estimates of heritability is most likely due to several factors. First, the tag SNPs on the chip are not in perfect LD with the causal SNPs; for other traits, simulation has shown that correcting for imperfect LD raises the SNP “heritability” by about 10%. Another major factor is that commercial chips only interrogate common SNPs so large effects of rare SNPs are simply not captured. Reasonable estimates from simulations suggest that this could account for another 20% of variance. Finally, we recognize that there are large sections of the genome containing highly repetitive DNA which are very poorly tagged by current chips, and where substantial proportions of genetic variance may be hidden.


What is the total SNP-associated heritability for alcohol dependence? N. G. Martin¹, G. Zhu¹, P. A. Lind¹, A. C. Heath², P. A. F. Madden², M. L. Pergadia², G. W. Montgomery¹, J. B. Whitfield¹ 1) Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia; 2) Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.

   Background. Much has been written about the so-called “missing heritability” for complex traits. Nowhere is this more pertinent than for alcohol and nicotine dependence (AD, ND) for which there are estimates of heritability of up to 65% from twin studies, yet few causal variants have been replicated from GWAS studies, despite large sample sizes, suggesting that individual effect sizes of SNPs must be very small. Recently new statistical genetic techniques have been developed which allow estimation of the total variance associated with all SNPs on a GWAS chip, but this has yet to be applied to AD and ND. Methods. The current analysis is based on AD and ND symptom count data from over 8000 participants in our population-based twin-family studies who have used either alcohol or cigarettes at some stage of their lives. They were individually genotyped with Illumina 370K or 660K chips and 7.034M genotypes were imputed from HapMap 3 and 1000-Genomes data. The GCTA program of Yang, Visscher et al is used first to detect the degree of relatedness between apparently unrelated subjects, based on a set of about 300,000 SNPs pruned for LD. Phenotypic similarity is then regressed on IBS sharing for all possible relative pairs to estimate the total amount of variance due to SNPs on the chip. Results. Based on GCTA analysis for other complex traits we expect to find SNP associated variance accounting for about half the heritability estimated from conventional genetic epidemiology designs. However, these estimates are highly sensitive to population stratification so great care will be taken to remove all traces of population stratification during the analysis. Conclusions. The gap between the SNP-associated variance estimated by GCTA and twin and family estimates of heritability is most likely due to several factors. First, the tag SNPs on the chip are not in perfect LD with the causal SNPs; for other traits, simulation has shown that correcting for imperfect LD raises the SNP “heritability” by about 10%. Another major factor is that commercial chips only interrogate common SNPs so large effects of rare SNPs are simply not captured. Reasonable estimates from simulations suggest that this could account for another 20% of variance. Finally, we recognize that there are large sections of the genome containing highly repetitive DNA which are very poorly tagged by current chips, and where substantial proportions of genetic variance may be hidden.


Vascular Stiffness in a Healthy High Risk African American Population is Modified by the Extent of European Admixture. D. Vaidya, R. A. Mathias, L. R. Yanek, L. C. Becker, D. M. Becker Medicine, Johns Hopkins University, Baltimore, MD.

   Background: Compared to European Americans (EA), African-Americans (AA) have stiffer peripheral vessels, reflected in reduced carotid distensibility coefficient (DC). To determine whether this racial difference may be genetically determined, we examined the extent to which the variance in carotid distensibility in AA could be explained by EA admixture either at a global or local at genomic level. Methods: We examined data from 344 AA, 62% women, aged 25-76 years, enrolled in a large study (GeneSTAR) of apparently healthy people with a family history of early-onset coronary artery disease. DC was assessed using 2D ultrasound, calculated as 2*(fractional change in diameter from diastole to systole)/(systolic -diastolic blood pressure). By its calculation DC is inherently corrected for blood pressure levels. EA admixture was determined using a panel of 50,000 ancestry informative markers (deCODE Genetics), and local ancestry was calculated on Illumina Human 1M genomewide SNP panel using LAMP. Associations of log-transformed DC were tested using mixed model regressions adjusted for age, sex, sex*age interaction and within-family correlations. LAMP models were adjusted for population stratification PCAs derived from the Illumina 1M SNPs (EIGENSTRAT). Results: The median [interquartile range] of the DC was 0.0017 [0.0012-0.0024] mmHg^-1. Every 10% incremental level of EA admixture was associated with 5% higher DC (95% CI: 1% to 9%, p=0.005), reflecting more distensibility, and less stiffness. In genomewide local ancestry analysis adjusted for sex, age, sex*age interaction, population stratification PCAs and within-family correlations, of 2756 genome segments in local ancestry LD, the highest association for local ancestry was found in Chromosome 8, positions 8.3M to 10M (Build 37.3), p=0.0012. On adjusting for local ancestry in this region, population stratification PCA1 representing global Caucasian ancestry was no longer significantly associated with DC (p=0.93). Conclusions: The racial difference in arterial distensibility between AA and EA is likely to have a basis in genetic admixture. We have identified a candidate region on chromosome 8 that may be responsible for this global admixture association.


A population isolate reveals enriched recessive deleterious variants underlying neurodevelopmental traits. O. Pietilainen^1,2,3, J. Suvisaari⁵, W. Hennah², V. Leppa², T. Paunio^2,3,4, M. Torniainen⁵, S. Ripatti^1,2, S. Ala-Mello⁶, K. Rehnstrom¹, A. Tuulio-Henriksson⁵, T. Varilo², J. Tallila¹, K. Kristiansson², M. Isohanni⁷, J. Kaprio², J. Eriksson⁸, M. Jarvelin⁹, R. Durbin¹, J. Lonnqvist^4,5, M. Hurles², H. Stefansson¹⁰, N. Freimer¹¹, M. Daly¹², A. Palotie^1,2,12 1) The Wellcome Trust Sanger Institute, Cambridge, Cambridge, United Kingdom; 2) Institute for Molecular Medicine Finland FIMM, Helsinki, Finland; 3) National Institute for Health and Welfare, Public Health Genomics Unit, Helsinki, Finland; 4) University of Helsinki and Helsinki University Central Hospital, Department of Psychiatry, Helsinki, Finland; 5) National Institute for Health and Welfare, Department of Mental Health and Substance Abuse Services, Helsinki, Finland; 6) Helsinki University Central Hospital, Department of Clinical Genetics, Helsinki, Finland; 7) Department of Psychiatry, Institute of Clinical Medicine, University of Oulu, Finland; 8) National Institute for Health and Welfare, Chronic Disease Epidemiology and Prevention, Helsinki, 90014, Finland; 9) Institute of Health Sciences, University of Oulu, Oulu, Finland; 10) deCODE genetics, 101 Reykjavik, Iceland; 11) Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, California, USA; 12) The Broad Institute of MIT and Harvard University, Cambridge, Ma, USA.

   Low frequency variants (MAF <5%) likely contribute to susceptibility for complex traits, but their study is challenging in admix populations. We hypothesize that population isolates that have experienced bottlenecks would have an enrichment of specific low frequency variants some of which could be predisposing to complex traits. This enrichment could benefit especially identification of variants with recessive effects. To test this hypothesis, we studied homozygous deletions in a prospective birth cohort from an isolated Northern Finnish population (N=4,931). The role of rare deletions being clearly establish in abnormal neuronal development led us to constrain our initial analysis to seven supposedly relevant phenotypes including diagnosis of schizophrenia, intellectual deficit, learning difficulties, epilepsy, neonatal convulsion, impaired hearing and cerebral palsy/perinatal brain damage. The analysis included 32,487 homozygous deletions in 205 loci of which 11% included exons of one or more genes. Among the seven traits studied, the strongest association was found with impaired hearing and a deletion on 15q15.3, overlapping STRC, previously associated with deafness (p = 10-4). The largest identified homozygous deletion was 240 kb on 22q11.22 and was associated with intellectual deficit (p<0.02). The deletion showed significant regional enrichment in an internal north-eastern isolate with 3-fold risk of schizophrenia compared to elsewhere in the country. Follow up of the deletion in 265 schizophrenia patients and 5140 controls revealed an allelic association with schizophrenia (p= 0.02, OR = 1.9) and was further replicated in 9,539 cases and 15,677 controls of European origin (p = 0.03, OR = 2.1). After screening over 13,106 Finns, we identified four individuals being homozygous for the deletion, all diagnosed with schizophrenia and/or intellectual disability. The deletion overlaps a gene encoding for TOP3B and was found to down regulate its expression to half among heterozygous carriers and zero in homozygous carriers (p < 10-10). Our results demonstrate the effect of multiple consecutive population bottlenecks in the enrichment of sizable deletions contributing to abnormal neuronal development. In addition the findings highlight the usefulness of population isolates in studying rare and low frequency variants in complex traits.

Identifying age- and sex- associated gene expression profiles in >7,000 whole-blood samples. M. J. Peters^1,2,17, R. Joehanes^3,17, T. Esko^4,17, K. Heim^5,17, H. Völzke^6,17, L. Pilling^7,17, J. Brody^8,17, Y. F. Ramos^9,17, B. E. Stranger^10,11, M. W. Christiansen⁸, S. Gharib⁸, R. Hanson¹², A. Hofman^2,13, J. Kettunen¹⁴, D. Levy³, P. Munson³, C. O’Donnell³, B. Psaty⁸, F. Rivadeneira^1,2,13, A. Suchy-Dicey⁸, A. G. Uitterlinden^1,2,13, H. Westra¹⁵, I. Meulenbelt^2,9,17, D. Enquobahrie^8,17, T. Frayling^7,17, A. Teumer^16,17, H. Prokisch^5,17, A. Metspalu^4,17, J. B. J. Van Meurs^1,2,17, A. D. Johnson^3,17 on behalf of the CHARGE Gene Expression Working Group. 1) Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands; 2) Netherlands Genomics Initiative-Sponsored by the Netherlands Consortium for Healthy Aging, Rotterdam and Leiden, the Netherlands; 3) Framingham Heart Study, National Heart, Lung and Blood Institute, Framingham, USA; 4) Estonian Genome Center and Institute of Molecular and Cell Biology of University of Tartu, Estonia; 5) Institute of Human Genetics, Technische Universität München, Munich, Germany; 6) Institute for Community Medicine, University Medicine Greifswald, Germany; 7) Epidemiology and Public Health, Peninsula College of Medicine and Dentistry, University of Exeter, UK; 8) Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, United States; 9) Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; 10) Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA; 11) Broad Institute of Harvard and MIT, Cambridge, USA; 12) Phoenix Epidemiology and Clinical Research Branch, NIDDK, National Institute of Health, Phoenix, AZ, USA; 13) Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands; 14) Institute for Molecular Medicine Finland FIMM, University of Helsinki, Finland; 15) Department of Genetics, University of Groningen, University Medical Center Groningen, the Netherlands; 16) Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt University Greifswald, Germany; 17) Contributed Equally.

   Genome-Wide Expression Profiles (GWEPs) have been assayed in a growing number of cohort studies, but few attempts have been made to meta-analyse and cross-validate expression datasets. Consequently, many expression studies have been under powered. Therefore, we established a large-scale multi-cohort GWEP meta-analysis. The aim of this study was to robustly identify novel gene expression signatures associated with age and sex, two major risk factors for many diseases. We analyzed 6,993 European-ancestry PAXgene (whole-blood) samples from 6 cohort studies (RS, FHS, EGCUT, KORA, SHIP, INCHIANTI). GWEPs were quantile-normalized, log2-transformed, probe-centered and sample-z-transformed prior to analysis. In the discovery stage we meta-analysed age- and sex-associated signals for samples hybridized to an Illumina or Affymetrix array separately. All analyses were adjusted for plate ID, RNA quality, fasting- and smoking status, and cell counts (when available). The age analysis was additionally adjusted for sex. All significant signals were cross-validated between the Illumina and Affymetrix platforms. We examined the top-associated GWEPs in 3 additional studies: HVH (n=348), GARP (n=134), and NIDDK/PIMA (n=1457). We identified 396 age-associated transcripts with p<1E-5 and same direction in both platforms. NELL2, a protein kinase C-binding protein, was the most significant result with gene expression levels decreasing with age (Illumina p=8.2E-81, Affymetrix p=3.2E-64). NELL2 is involved in cell growth regulation and differentiation, and there is evidence for developmental fluctuation in puberty. We identified 347 transcripts differentially expressed between males and females(p<1E-5, same direction both platforms), of which >200 show mapping to sex chromosomes. The top autosomal gender-differentiated transcript is DACT1, which has higher mRNA levels in females (Illumina p=2.4E-47, Affymetrix p=1.6E-75). DACT1 is an antagonist of beta-catenin and prior work indicates it to be differentially methylated in testes. It is a biomarker for semen and DACT1 knockout mice showed developmental defects. Both the NELL2 and the DACT1 signals were replicated in all 3 additional cohorts. With the GWEP meta-analysis, we gained power relative to individual cohort analyses, and were able to identify novel replicable significant age- and sex- associated loci. These loci may have implications for age-related disease biology, gender biology, and in sample forensics.


Genetic variants in pigmentation genes, skin color, and risk of skin cancer in Japanese. T. Suzuki¹, Y. Abe¹, J. Yoshizawa¹, Y. Hozumi¹, T. Nakamura², G. Tamiya² 1) Dept Dermatology, Yamagata Univ Sch Med, Yamagata, Japan; 2) Advanced Molecular Epidemiology Research Institute, Yamagata Univ Sch Med, Yamagata, Japan.

   Melanin pigmentation plays an important role in shielding the body from ultraviolet (UV) radiation and may serve as a scavenger for reactive oxygen species. More than 150 genes have been implicated in determining in mice, and include transcription factors, membrane and structural proteins, enzymes, and several kinds of receptors and their legands, most of which have human orthologues. Although many molecular mechanisms involved in melanin pigmentation are being determined, relatively little is understood about the genetic component responsible for variations in skin color within or between human populations. First, in order to reveal their genetic contribution to skin color, we examined the association of pigmentation-related genes variants and variations in the melanin index in members of the general Japanese population whose skin color was objectively measured by reflectometry. The multiple regression showed that OCA2 A481T rs74653330 (p = 6.18e-8) and, OCA2 H615R rs1800414 (p = 5.72e-6) were strongly associated with the mean of the melanin index in the female population. Three variants (SLC45A2 T500P rs11568737 p = 0.048, OCA2 T387M p = 0.015, TYR D125Y rs13312741 p = 0.022) were also significantly associated with melanin index. However, no significant associations were found between age and melanin index for variants of MC1R. Second, we evaluated the associations of the pigmentation-related genes variants and the risk of skin cancer. The statistical analysis revealed that only OCA2 H615R was associated with the risk of all skin cancers, especially malignant melanoma. We could not find any statistical significance in the associations of other variants, including OCA2 A481T, or melanin index with the risk of skin cancer. This is the first report on the association between the genetic variants in pigmentation genes and the risk of skin cancer in East Asian population.

You may contact the first author (during and after the meeting) at tamsuz@med.id.yamagata-u.ac.jp


Molecular phylogeny of an autosomal region under natural selection. V. A. Canfield¹, A. Berg¹, S. Peckins¹, S. Oppenheimer², K. C. Cheng¹ 1) Penn State College of Medicine, Hershey, PA; 2) Oxford University, Oxford, UK.

   The derived (A111T) variant of SLC24A5 is associated with lighter skin pigmentation compared to the ancestral allele. A111T is fixed or nearly fixed in most European, North African and Middle Eastern populations, extending east to Pakistan. In Europeans, a large genomic region of diminished variation on chromosome 15, nearly 150 kb in extent, includes SLC24A5. We analyzed the haplotypes in this region using existing genomic data. Eleven haplotypes, defined on the basis of 16 SNPs that span a 76 kb genomic region in which recombination was rare, account for 95% of the total. A single haplotype (here called C11) carries A111T, suggesting that its origin did not long predate the onset of selection. Haplotype C11 was the product of recombination between haplotypes C3 and C10, followed by the A111T mutation. C3 and C10 are both present in East Asia and the New World but virtually absent in Africa, suggesting that C11 originated outside of Africa, most likely in the Middle East. The current distribution of A111T is consistent with the view that it originated after the divergence between populations that settled Europe and those that settled East Asia.

You may contact the first author (during and after the meeting) at vac3@psu.edu

Sharing by descent, phasing, rare variants and population structure. A. Kong deCODE Genet., Reykjavik, Iceland. Session Descriptions: Identity by descent (IBD) is fundamental to genetics and has diverse applications. Recently developed statistical methods and genome-wide SNP data have made it possible to detect haplotypes shared identically by descent between individuals with common ancestry up to 25-50 generations ago. With sequence data, shared haplotypes from even more distant ancestry can be detected. Patterns of IBD segment sharing within and between populations reveal important population demographic features including recent effective population size and migration patterns. IBD segment sharing is directly relevant to disease gene mapping and estimation of heritability. Individuals who share a genetic basis for a trait are more likely to have IBD sharing compared to randomly chosen individuals, and this forms the basis for IBD mapping and heritability estimation. Analysis of data from extended pedigrees was extremely difficult with standard linkage approaches, but is now possible using approaches based on detected IBD segments. Detected IBD can be present across pedigrees, which enhances power to detect association with the trait. Further, in population samples there is potential to utilize detected IBD segments to improve power to detect association when multiple variants within a gene influence the trait. IBD segments can also be used to greatly improve haplotype phase estimates, which is critical to understanding the functional consequence of genetic variation. IBD-based long-range phasing has previously been shown to be effective in isolated populations such as Iceland, but recent advances have extended its application to large outbred populations. In this session, we explore these exciting new developments.