EGAGenomicsLongitudinal Cohort; Longitudinal; FamilydbGaPEGA study phs000580.v1.p1http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000580.v1.p1dbGaPEGArestrictedhttps://ega-archive.org/studies/phs000580.v1.p1Available data indicate that cardiovascular disease has become the leading cause of death in American Indians. However, limited information is available on cardiovascular disease incidence, prevalence, and risk factors in this population. Reported cardiovascular disease rates vary greatly among groups in different geographic areas. These rates have been obtained from studies of varying sizes and different methodologies. The Strong Heart Study, which uses standardized methodology, is designed to estimate cardiovascular disease mortality and morbidity rates and the prevalence of known and suspected cardiovascular disease risk factors in American Indians. The study population consists of 12 tribes in three geographic areas: an area near Phoenix, Arizona, the southwestern area of Oklahoma, and the Aberdeen area of North and South Dakota. The study includes three components. The first is a mortality survey to estimate cardiovascular disease mortality rates for 1984-1988 among tribal members aged 35-74 years, and the second is a morbidity survey to estimate incidence of both first and first or recurrent hospitalized myocardial infarction and stroke (cerebrovascular disease) among tribal members aged 45-74 years in 1984-1988, and the third is a clinical examination of 4,500 tribal members aged 45-74 years in order to estimate the prevalence of cardiovascular disease and its associations with risk factors. Family history, diet, alcohol and tobacco consumption, physical activity, degree of acculturation, and socioeconomic status are assessed in personal interviews. The physical examination includes measurements of body fat, body circumferences, and blood pressure, an examination of the heart and lungs, an evaluation of peripheral vascular disease, and a 12-lead electrocardiogram. Laboratory measurements include fasting and postload glucose, insulin, fasting lipids, apoproteins, fibrinogen, and glycated hemoglobin. Also measured are serum and urine creatinine and urinary albumin. DNA from lymphocytes is isolated and stored for future genetic studies.<h4>Background</h4>Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.<h4>Methods and results</h4>Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.<h4>Conclusions</h4>Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the "phenome-wide association study" approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information's Database of Genotypes and Phenotypes and made available via a custom browser.Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.<h4>Background</h4>Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.<h4>Methods</h4>As part of the 'Population Architecture using Genomics and Epidemiology (PAGE)' Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.<h4>Results</h4>We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, p(interaction) = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5 x 10(-5)), vs. former/never smokers (β = 0.006, p = 0.05, p(interaction) = 0.08).<h4>Conclusions</h4>These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.<h4>Clinical trial registration</h4>NCT00000611.<h4>Background</h4>High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.<h4>Results</h4>A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.<h4>Conclusions</h4>We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.<h4>Study question</h4>Do genetic associations identified in genome-wide association studies (GWAS) of age at menarche (AM) and age at natural menopause (ANM) replicate in women of diverse race/ancestry from the Population Architecture using Genomics and Epidemiology (PAGE) Study?<h4>Summary answer</h4>We replicated GWAS reproductive trait single nucleotide polymorphisms (SNPs) in our European descent population and found that many SNPs were also associated with AM and ANM in populations of diverse ancestry.<h4>What is known already</h4>Menarche and menopause mark the reproductive lifespan in women and are important risk factors for chronic diseases including obesity, cardiovascular disease and cancer. Both events are believed to be influenced by environmental and genetic factors, and vary in populations differing by genetic ancestry and geography. Most genetic variants associated with these traits have been identified in GWAS of European-descent populations.<h4>Study design, size, duration</h4>A total of 42 251 women of diverse ancestry from PAGE were included in cross-sectional analyses of AM and ANM.<h4>Materials, setting, methods</h4>SNPs previously associated with ANM (n = 5 SNPs) and AM (n = 3 SNPs) in GWAS were genotyped in American Indians, African Americans, Asians, European Americans, Hispanics and Native Hawaiians. To test SNP associations with ANM or AM, we used linear regression models stratified by race/ethnicity and PAGE sub-study. Results were then combined in race-specific fixed effect meta-analyses for each outcome. For replication and generalization analyses, significance was defined at P < 0.01 for ANM analyses and P < 0.017 for AM analyses.<h4>Main results and the role of chance</h4>We replicated findings for AM SNPs in the LIN28B locus and an intergenic region on 9q31 in European Americans. The LIN28B SNPs (rs314277 and rs314280) were also significantly associated with AM in Asians, but not in other race/ethnicity groups. Linkage disequilibrium (LD) patterns at this locus varied widely among the ancestral groups. With the exception of an intergenic SNP at 13q34, all ANM SNPs replicated in European Americans. Three were significantly associated with ANM in other race/ethnicity populations: rs2153157 (6p24.2/SYCP2L), rs365132 (5q35/UIMC1) and rs16991615 (20p12.3/MCM8). While rs1172822 (19q13/BRSK1) was not significant in the populations of non-European descent, effect sizes showed similar trends.<h4>Limitations, reasons for caution</h4>Lack of association for the GWAS SNPs in the non-European American groups may be due to differences in locus LD patterns between these groups and the European-descent populations included in the GWAS discovery studies; and in some cases, lower power may also contribute to non-significant findings.<h4>Wider implications of the findings</h4>The discovery of genetic variants associated with the reproductive traits provides an important opportunity to elucidate the biological mechanisms involved with normal variation and disorders of menarche and menopause. In this study we replicated most, but not all reported SNPs in European descent populations and examined the epidemiologic architecture of these early reported variants, describing their generalizability and effect size across differing ancestral populations. Such data will be increasingly important for prioritizing GWAS SNPs for follow-up in fine-mapping and resequencing studies, as well as in translational research.<h4>Background</h4>A number of genetic variants have been discovered by recent genome-wide association studies for their associations with clinical coronary heart disease (CHD). However, it is unclear whether these variants are also associated with the development of CHD as measured by subclinical atherosclerosis phenotypes, ankle brachial index (ABI), carotid artery intima-media thickness (cIMT) and carotid plaque.<h4>Methods</h4>Ten CHD risk single nucleotide polymorphisms (SNPs) were genotyped in individuals of European American (EA), African American (AA), American Indian (AI), and Mexican American (MA) ancestry in the Population Architecture using Genomics and Epidemiology (PAGE) study. In each individual study, we performed linear or logistic regression to examine population-specific associations between SNPs and ABI, common and internal cIMT, and plaque. The results from individual studies were meta-analyzed using a fixed effect inverse variance weighted model.<h4>Results</h4>None of the ten SNPs was significantly associated with ABI and common or internal cIMT, after Bonferroni correction. In the sample of 13,337 EA, 3809 AA, and 5353 AI individuals with carotid plaque measurement, the GCKR SNP rs780094 was significantly associated with the presence of plaque in AI only (OR = 1.32, 95% confidence interval: 1.17, 1.49, P = 1.08 × 10(-5)), but not in the other populations (P = 0.90 in EA and P = 0.99 in AA). A 9p21 region SNP, rs1333049, was nominally associated with plaque in EA (OR = 1.07, P = 0.02) and in AI (OR = 1.10, P = 0.05).<h4>Conclusions</h4>We identified a significant association between rs780094 and plaque in AI populations, which needs to be replicated in future studies. There was little evidence that the index CHD risk variants identified through genome-wide association studies in EA influence the development of CHD through subclinical atherosclerosis as assessed by cIMT and ABI across ancestries.Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network.Associations between incident ischemic stroke events and stroke and cardiovascular disease-related genome-wide association studies single nucleotide polymorphisms in the Population Architecture Using Genomics and Epidemiology study.Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study.Lack of associations of ten candidate coronary heart disease risk genetic variants and subclinical atherosclerosis in four US populations: the Population Architecture using Genomics and Epidemiology (PAGE) study.Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.The Strong Heart Study. A study of cardiovascular disease in American Indians: design and methods.Replication of genetic loci for ages at menarche and menopause in the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) study.The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.Zhang Lili L, Buzkova Petra P, Wassel Christina L CL, Roman Mary J MJ, North Kari E KE, Crawford Dana C DC, Boston Jonathan J, Brown-Gentry Kristin D KD, Cole Shelley A SA, Deelman Ewa E, Goodloe Robert R, Wilson Sarah S, Heiss Gerardo G, Jenny Nancy S NS, Jorgensen Neal W NW, Matise Tara C TC, McClellan Bob E BE, Nato Alejandro Q AQ, Ritchie Marylyn D MD, Franceschini Nora N, Kao W H Linda WHFesinmeyer Megan D MD, North Kari E KE, Lim Unhee U, Bůžková Petra P, Crawford Dana C DC, Haessler Jeffrey J, Gross Myron D MD, Fowke Jay H JH, Goodloe Robert R, Love Shelley-Ann SA, Graff Misa M, Carlson Christopher S CS, Kuller Lewis H LH, Matise Tara C TC, Hong Ching-Ping CP, Henderson Brian E BE, Allen Melissa M, Rohde Rebecca R RR, Mayo Ping P, Schnetz-Boutaud Nathalie N, Monroe Kristine R KR, Ritchie Marylyn D MD, Prentice Ross L RL, Kolonel Lawrence N LN, Manson JoAnn E JE, Pankow James J, Hindorff Lucia A LA, Franceschini Nora N, Wilkens Lynne R LR, Haiman Christopher A CA, Le Marchand Loic L, Peters Ulrike UPendergrass Sarah A SA, Brown-Gentry Kristin K, Dudek Scott S, Frase Alex A, Torstenson Eric S ES, Goodloe Robert R, Ambite Jose Luis JL, Avery Christy L CL, Buyske Steve S, Bůžková Petra P, Deelman Ewa E, Fesinmeyer Megan D MD, Haiman Christopher A CA, Heiss Gerardo G, Hindorff Lucia A LA, Hsu Chu-Nan CN, Jackson Rebecca D RD, Kooperberg Charles C, Le Marchand Loic L, Lin Yi Y, Matise Tara C TC, Monroe Kristine R KR, Moreland Larry L, Park Sungshim L SL, Reiner Alex A, Wallace Robert R, Wilkens Lynn R LR, Crawford Dana C DC, Ritchie Marylyn D MDLee E T ET, Welty T K TK, Fabsitz R R, Cowan L D LD, Le N A NA, Oopik A J AJ, Cucchiara A J AJ, Savage P J PJ, Howard B V BVTaylor Kira C KC, Carty Cara L CL, Dumitrescu Logan L, Bůžková Petra P, Cole Shelley A SA, Hindorff Lucia L, Schumacher Fred R FR, Wilkens Lynne R LR, Shohet Ralph V RV, Quibrera P Miguel PM, Johnson Karen C KC, Henderson Brian E BE, Haessler Jeff J, Franceschini Nora N, Eaton Charles B CB, Duggan David J DJ, Cochran Barbara B, Cheng Iona I, Carlson Chris S CS, Brown-Gentry Kristin K, Anderson Garnet G, Ambite Jose Luis JL, Haiman Christopher C, Le Marchand Loïc L, Kooperberg Charles C, Crawford Dana C DC, Buyske Steven S, North Kari E KE, Fornage Myriam MCarty Cara L CL, Buzková Petra P, Fornage Myriam M, Franceschini Nora N, Cole Shelley S, Heiss Gerardo G, Hindorff Lucia A LA, Howard Barbara V BV, Mann Sue S, Martin Lisa W LW, Zhang Ying Y, Matise Tara C TC, Prentice Ross R, Reiner Alexander P AP, Kooperberg Charles CMatise Tara C TC, Ambite Jose Luis JL, Buyske Steven S, Carlson Christopher S CS, Cole Shelley A SA, Crawford Dana C DC, Haiman Christopher A CA, Heiss Gerardo G, Kooperberg Charles C, Marchand Loic Le LL, Manolio Teri A TA, North Kari E KE, Peters Ulrike U, Ritchie Marylyn D MD, Hindorff Lucia A LA, Haines Jonathan L JLCarty C L CL, Spencer K L KL, Setiawan V W VW, Fernandez-Rhodes L L, Malinowski J J, Buyske S S, Young A A, Jorgensen N W NW, Cheng I I, Carlson C S CS, Brown-Gentry K K, Goodloe R R, Park A A, Parikh N I NI, Henderson B B, Le Marchand L L, Wactawski-Wende J J, Fornage M M, Matise T C TC, Hindorff L A LA, Arnold A M AM, Haiman C A CA, Franceschini N N, Peters U U, Crawford D C DCDumitrescu Logan L, Carty Cara L CL, Taylor Kira K, Schumacher Fredrick R FR, Hindorff Lucia A LA, Ambite José L JL, Anderson Garnet G, Best Lyle G LG, Brown-Gentry Kristin K, Bůžková Petra P, Carlson Christopher S CS, Cochran Barbara B, Cole Shelley A SA, Devereux Richard B RB, Duggan Dave D, Eaton Charles B CB, Fornage Myriam M, Franceschini Nora N, Haessler Jeff J, Howard Barbara V BV, Johnson Karen C KC, Laston Sandra S, Kolonel Laurence N LN, Lee Elisa T ET, MacCluer Jean W JW, Manolio Teri A TA, Pendergrass Sarah A SA, Quibrera Miguel M, Shohet Ralph V RV, Wilkens Lynne R LR, Haiman Christopher A CA, Le Marchand Loïc L, Buyske Steven S, Kooperberg Charles C, North Kari E KE, Crawford Dana C DCfalsePopulation Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Strong Heart Study (SHS) and Strong Heart Family Study (SHFS)<p>The SHS is a study of cardiovascular disease and its risk factors among American Indian men and women. Using standardized methodology, it was designed to estimate cardiovascular disease mortality and morbidity and the prevalence of known and suspected cardiovascular disease risk factors and to assess the significance of these risk factors in a longitudinal analysis. The study included 13 American Indian tribes and communities in three geographic areas: an area near Phoenix, Arizona, the southwestern area of Oklahoma, and western and central North and South Dakota. The SHS included three components: The first was a survey to determine cardiovascular disease mortality rates from 1984 to 1994 among tribal members aged 35-74 years of age residing in the 3 study areas (the community mortality study). The second was the clinical examination of 4,500 tribal members aged 45-74. The SHS has completed three clinical examinations of the original Cohort (Phase I: 1989-1991; Phase II: 1993-1995; Phase III: 1998- 1999, respectively). The third component is the morbidity and mortality (M&M) surveillance of these 4,500 participants. Yearly SHS surveillance has only 0.2% loss to follow-up. All deaths and all nonfatal CVD events are classified by standardized criteria, including details of stroke and HF. </p> <p>The Strong Heart Family Study (SHFS) is a genetic epidemiological study designed to investigate the heritability of CVD and its risk factors and to localize genes that contribute to CVD risk in American Indians. SHFS participants include 3,838 family members that were >/=15 years old, and ascertained through sibships of the original SHS, from 94 extended (large, multigenerational) families. Exams have occurred in a pilot Phase III (1998-1999, 900 SHFS participants), in Phase IV (2001-2003), and Phase V (2006-2009). SHFS morbidity and mortality surveillance has occurred throughout the study phases, with 0.3% lost to follow-up. Genetic data includes complete pedigree information, DNA samples from all family members, a 10cM-spaced microsatellite map used for IBD estimation and to perform linkage analysis, genotypes for more than 12,000 SNPs in candidate regions, and genotypes from commercially available SNP assays. </p>
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