Mapping genes with longitudinal phenotypes via Bayesian posterior probabilities

Most association studies focus on disease risk, with less attention paid to disease progression or severity. These phenotypes require longitudinal data. This paper presents a new method for analyzing longitudinal data to map genes in both population-based and family-based studies. Using simulated systolic blood pressure measurements obtained from Genetic Analysis Workshop 18, we cluster the phenotype data into trajectory subgroups. We then use the Bayesian posterior probability of being in the high subgroup as a quantitative trait in an association analysis with genotype data. This method maintains high power (\u3e80%) in locating genes known to affect the simulated phenotype for most specified significance levels (a). We believe that this method can be useful to aid in the discovery of genes that affect severity or progression of disease

Enhanced genetic maps from family-based disease studies: population-specific comparisons

Abstract Background Accurate genetic maps are required for successful and efficient linkage mapping of disease genes. However, most available genome-wide genetic maps were built using only small collections of pedigrees, and therefore have large sampling errors. A large set of genetic studies genotyped by the NHLBI Mammalian Genotyping Service (MGS) provide appropriate data for generating more accurate maps. Results We collected a large sample of uncleaned genotype data for 461 markers generated by the MGS using the Weber screening sets 9 and 10. This collection includes genotypes for over 4,400 pedigrees containing over 17,000 genotyped individuals from different populations. We identified and cleaned numerous relationship and genotyping errors, as well as verified the marker orders. We used this dataset to test for population-specific genetic maps, and to re-estimate the genetic map distances with greater precision; standard errors for all intervals are provided. The map-interval sizes from the European (or European descent), Chinese, and Hispanic samples are in quite good agreement with each other. We found one map interval on chromosome 8p with a statistically significant size difference between the European and Chinese samples, and several map intervals with significant size differences between the African American and Chinese samples. When comparing Palauan with European samples, a statistically significant difference was detected at the telomeric region of chromosome 11p. Several significant differences were also identified between populations in chromosomal and genome lengths. Conclusions Our new population-specific screening set maps can be used to improve the accuracy of disease-mapping studies. As a result of the large sample size, the average length of the 95% confidence interval (CI) for a 10 cM map interval is only 2.4 cM, which is considerably smaller than on previously published maps.http://deepblue.lib.umich.edu/bitstream/2027.42/112826/1/12881_2010_Article_748.pd

A Systematic Mapping Approach of 16q12.2/FTO and BMI in More Than 20,000 African Americans Narrows in on the Underlying Functional Variation: Results from the Population Architecture using Genomics and Epidemiology (PAGE) Study

Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10-6) had not been highlighted in previous studies. While rs56137030was correlated at r2>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations

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

BACKGROUND: 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. METHODS AND RESULTS: 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. CONCLUSIONS: 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

Genetic Variation and Reproductive Timing: African American Women from the Population Architecture Using Genomics and Epidemiology (PAGE) Study

Age at menarche (AM) and age at natural menopause (ANM) define the boundaries of the reproductive lifespan in women. Their timing is associated with various diseases, including cancer and cardiovascular disease. Genome-wide association studies have identified several genetic variants associated with either AM or ANM in populations of largely European or Asian descent women. The extent to which these associations generalize to diverse populations remains unknown. Therefore, we sought to replicate previously reported AM and ANM findings and to identify novel AM and ANM variants using the Metabochip (n = 161,098 SNPs) in 4,159 and 1,860 African American women, respectively, in the Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) studies, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study. We replicated or generalized one previously identified variant for AM, rs1361108/CENPW, and two variants for ANM, rs897798/BRSK1 and rs769450/APOE, to our African American cohort. Overall, generalization of the majority of previously-identified variants for AM and ANM, including LIN28B and MCM8, was not observed in this African American sample. We identified three novel loci associated with ANM that reached significance after multiple testing correction (LDLR rs189596789, p = 5×10-08; KCNQ1 rs79972789, p = 1.9×10-07; COL4A3BP rs181686584, p = 2.9×10-07). Our most significant AM association was upstream of RSF1, a gene implicated in ovarian and breast cancers (rs11604207, p = 1.6×10-06). While most associations were identified in either AM or ANM, we did identify genes suggestively associated with both: PHACTR1 and ARHGAP42. The lack of generalization coupled with the potentially novel associations identified here emphasize the need for additional genetic discovery efforts for AM and ANM in diverse populations. © 2013 Spencer et al

The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course: The PAGE Study

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data

Genotype Imputation of MetabochipSNPs Using a Study-Specific Reference Panel of ∼4,000 Haplotypes in African Americans From the Women's Health Initiative: Imputation of Metabochip SNPs in African Americans

Genetic imputation has become standard practice in modern genetic studies. However, several important issues have not been adequately addressed including the utility of study-specific reference, performance in admixed populations, and quality for less common (minor allele frequency [MAF] 0.005–0.05) and rare (MAF 0.05 (0.03–0.05, 0.01–0.03, 0.005–0.01, and 0.001–0.005) passed the post-imputation filter. The average dosage r2 for these SNPs is 94.7%, 92.1%, 89.0%, 83.1%, and 79.7%, respectively. These results suggest that for African Americans imputation of Metabochip SNPs from GWAS data, including low frequency SNPs with MAF 0.005–0.05, is feasible and worthwhile for power increase in downstream association analysis provided a sizable reference panel is available

Genetic variation and reproductive timing: African American women from the Population Architecture Using Genomics and Epidemiology

Abstract Age at menarche (AM) and age at natural menopause (ANM) define the boundaries of the reproductive lifespan in women. Their timing is associated with various diseases, including cancer and cardiovascular disease. Genome-wide association studies have identified several genetic variants associated with either AM or ANM in populations of largely European or Asian descent women. The extent to which these associations generalize to diverse populations remains unknown. Therefore, we sought to replicate previously reported AM and ANM findings and to identify novel AM and ANM variants using the Metabochip (n = 161,098 SNPs) in 4,159 and 1,860 African American women, respectively, in the Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) studies, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study. We replicated or generalized one previously identified variant for AM, rs1361108/CENPW, and two variants for ANM, rs897798/BRSK1 and rs769450/APOE, to our African American cohort. Overall, generalization of the majority of previously-identified variants for AM and ANM, including LIN28B and MCM8, was not observed in this African American sample. We identified three novel loci associated with ANM that reached significance after multiple testing correction (LDLR rs189596789, p = 5610 208 ; KCNQ1 rs79972789, p = 1.9610 207 ; COL4A3BP rs181686584, p = 2.9610 207 ). Our most significant AM association was upstream of RSF1, a gene implicated in ovarian and breast cancers (rs11604207, p = 1.6610 206 ). While most associations were identified in either AM or ANM, we did identify genes suggestively associated with both: PHACTR1 and ARHGAP42. The lack of generalization coupled with the potentially novel associations identified here emphasize the need for additional genetic discovery efforts for AM and ANM in diverse populations

Centers For Mendelian Genomics: a Decade of Facilitating Gene Discovery

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients