Application of the regression of offspring on mid-parent method to detect associations between single-nucleotide polymorphisms and the beta 2 electroencephalogram phenotype in the COGA data

The beta 2 electroencephalogram (EEG) phenotype is used as a quantitative measure related to alcoholism, and evidence of linkage and association has previously been reported in the Collaborative Study on the Genetics of Alcoholism data. In this study, associations between the beta 2 EEG phenotype and single nucleotide polymorphisms from whole-genome Illumina and Affymetrix panels were investigated with the regression of offspring on mid-parent method to identify significant genetic effects and to estimate their heritability. Separate regressions on father and mother were performed to identify parent-specific effects. Estimates of the heritability of the beta 2 EEG phenotype were 0.68 ± 0.12 and 0.52 ± 0.07 based on father-offspring and mother-offspring pairs, respectively. Significant associations at the 0.0005 level, some of which were parent-specific, were found on chromosomes 1, 2, 5, 6, 7, 8, 11, 12, 15, 16, 17, 18, and 19 with heritability attributable to each SNP ranging from 0.01 to 8%

Ageing, menopause, and ischaemic heart disease mortality in England, Wales, and the United States: modelling study of national mortality data

Objectives To use changes in heart disease mortality rates with age to investigate the plausibility of attributing women’s lower heart disease mortality than men to the protective effects of premenopausal sex hormones

Comparison of year-of-exam- and age-matched estimates of heritability in the Framingham Heart Study data

Several different approaches can be used to examine generational and temporal trends in family studies. The measurement of offspring and parents can be made over a short period of time with parents and offspring having quite different ages, or measurements can be made at the same ages but with decades between parent and offspring measures. A third approach, used in the Framingham Heart Study, has repeated examinations across a broad range of age and time, and provides a unique opportunity to compare these approaches. Parents and offspring were matched both on (year of exam) and on age. Heritability estimates for systolic blood pressure, body mass index, height, weight, cholesterol, and glucose were obtained by regressing offspring on midparent values with and without adjustment for age. Higher estimates of heritability were obtained for age-matched than for year-of-exam-matched data for all traits considered. For most traits, estimates of the heritability of the change over time (slope) of the trait were near zero. These results suggest that the optimal design to identify genetic effects in traits with large age-related effects may be to measure parents and offspring at similar ages and not to rely on age-adjustment or longitudinal measures to account for these temporal effects

On the Analysis of Genome-Wide Association Studies in Family-Based Designs: A Universal, Robust Analysis Approach and an Application to Four Genome-Wide Association Studies

For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1) in 4 genome-wide association studies

Evaluation of random forests performance for genome-wide association studies in the presence of interaction effects

Random forests (RF) is one of a broad class of machine learning methods that are able to deal with large-scale data without model specification, which makes it an attractive method for genome-wide association studies (GWAS). The performance of RF and other association methods in the presence of interactions was evaluated using the simulated data from Genetic Analysis Workshop 16 Problem 3, with knowledge of the major causative markers, risk factors, and their interactions in the simulated traits. There was good power to detect the environmental risk factors using RF, trend tests, or regression analyses but the power to detect the effects of the causal markers was poor for all methods. The causal marker that had an interactive effect with smoking did show moderate evidence of association in the RF and regression analyses, suggesting that RF may perform well at detecting such interactions in larger, more highly powered datasets

Evolution of Hominin Polyunsaturated Fatty Acid Metabolism: From Africa to the New World

The metabolic conversion of dietary omega-3 and omega-6 18 carbon (18C) to long chain (>20 carbon) polyunsaturated fatty acids (LC-PUFAs) is vital for human life. The rate-limiting steps of this process are catalyzed by fatty acid desaturase (FADS) 1 and 2. Therefore, understanding the evolutionary history of the FADS genes is essential to our understanding of hominin evolution. The FADS genes have two haplogroups, ancestral and derived, with the derived haplogroup being associated with more efficient LC-PUFA biosynthesis than the ancestral haplogroup. In addition, there is a complex global distribution of these haplogroups that is suggestive of Neanderthal introgression. We confirm that Native American ancestry is nearly fixed for the ancestral haplogroup, and replicate a positive selection signal in Native Americans. This positive selection potentially continued after the founding of the Americas, although simulations suggest that the timing is dependent on the allele frequency of the ancestral Beringian population. We also find that the Neanderthal FADS haplotype is more closely related to the derived haplogroup and the Denisovan clusters closer to the ancestral haplogroup. Furthermore, the derived haplogroup has a time to the most recent common ancestor of 688,474years before present. These results support an ancient polymorphism, as opposed to Neanderthal introgression, forming in the FADS region during the Pleistocene with possibly differential selection pressures on both haplogroups. The near fixation of the ancestral haplogroup in Native American ancestry calls for future studies to explore the potential health risk of associated low LC-PUFA levels in these populations.Center for Health Related Informatics and Biomaging at the University of Maryland School of Medicine; National Institutes of Health/National Heart, Lung, and Blood Institute [U01 HL72518, HL087698, HL112064]; National Institutes of Health [R01-AT008621]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Resequencing Candidate Genes Implicates Rare Variants in Asthma Susceptibility

Common variation in over 100 genes has been implicated in the risk of developing asthma, but the contribution of rare variants to asthma susceptibility remains largely unexplored. We selected nine genes that showed the strongest signatures of weak purifying selection from among 53 candidate asthma-associated genes, and we sequenced the coding exons and flanking noncoding regions in 450 asthmatic cases and 515 nonasthmatic controls. We observed an overall excess of p values <0.05 (p = 0.02), and rare variants in four genes (AGT, DPP10, IKBKAP, and IL12RB1) contributed to asthma susceptibility among African Americans. Rare variants in IL12RB1 were also associated with asthma susceptibility among European Americans, despite the fact that the majority of rare variants in IL12RB1 were specific to either one of the populations. The combined evidence of association with rare noncoding variants in IL12RB1 remained significant (p = 3.7 × 10−4) after correcting for multiple testing. Overall, the contribution of rare variants to asthma susceptibility was predominantly due to noncoding variants in sequences flanking the exons, although nonsynonymous rare variants in DPP10 and in IL12RB1 were associated with asthma in African Americans and European Americans, respectively. This study provides evidence that rare variants contribute to asthma susceptibility. Additional studies are required for testing whether prioritizing genes for resequencing on the basis of signatures of purifying selection is an efficient means of identifying novel rare variants that contribute to complex disease

Identification of tag single-nucleotide polymorphisms in regions with varying linkage disequilibrium

We compared seven different tagging single-nucleotide polymorphism (SNP) programs in 10 regions with varied amounts of linkage disequilibrium (LD) and physical distance. We used the Collaborative Studies on the Genetics of Alcoholism dataset, part of the Genetic Analysis Workshop 14. We show that in regions with moderate to strong LD these programs are relatively consistent, despite different parameters and methods. In addition, we compared the selected SNPs in a multipoint linkage analysis for one region with strong LD. As the number of selected SNPs increased, the LOD score, mean information content, and type I error also increased

Investigation of altering single-nucleotide polymorphism density on the power to detect trait loci and frequency of false positive in nonparametric linkage analyses of qualitative traits

Genome-wide linkage analysis using microsatellite markers has been successful in the identification of numerous Mendelian and complex disease loci. The recent availability of high-density single-nucleotide polymorphism (SNP) maps provides a potentially more powerful option. Using the simulated and Collaborative Study on the Genetics of Alcoholism (COGA) datasets from the Genetics Analysis Workshop 14 (GAW14), we examined how altering the density of SNP marker sets impacted the overall information content, the power to detect trait loci, and the number of false positive results. For the simulated data we used SNP maps with density of 0.3 cM, 1 cM, 2 cM, and 3 cM. For the COGA data we combined the marker sets from Illumina and Affymetrix to create a map with average density of 0.25 cM and then, using a sub-sample of these markers, created maps with density of 0.3 cM, 0.6 cM, 1 cM, 2 cM, and 3 cM. For each marker set, multipoint linkage analysis using MERLIN was performed for both dominant and recessive traits derived from marker loci. Our results showed that information content increased with increased map density. For the homogeneous, completely penetrant traits we created, there was only a modest difference in ability to detect trait loci. Additionally, as map density increased there was only a slight increase in the number of false positive results when there was linkage disequilibrium (LD) between markers. The presence of LD between markers may have led to an increased number of false positive regions but no clear relationship between regions of high LD and locations of false positive linkage signals was observed

The impact of FADS genetic variants on ω6 polyunsaturated fatty acid metabolism in African Americans

<p>Abstract</p> <p>Background</p> <p>Arachidonic acid (AA) is a long-chain omega-6 polyunsaturated fatty acid (PUFA) synthesized from the precursor dihomo-gamma-linolenic acid (DGLA) that plays a vital role in immunity and inflammation. Variants in the Fatty Acid Desaturase (<it>FADS</it>) family of genes on chromosome 11q have been shown to play a role in PUFA metabolism in populations of European and Asian ancestry; no work has been done in populations of African ancestry to date.</p> <p>Results</p> <p>In this study, we report that African Americans have significantly higher circulating levels of plasma AA (p = 1.35 × 10^-48) and lower DGLA levels (p = 9.80 × 10^-11) than European Americans. Tests for association in N = 329 individuals across 80 nucleotide polymorphisms (SNPs) in the Fatty Acid Desaturase (<it>FADS</it>) locus revealed significant association with AA, DGLA and the AA/DGLA ratio, a measure of enzymatic efficiency, in both racial groups (peak signal p = 2.85 × 10^-16in African Americans, 2.68 × 10^-23in European Americans). Ancestry-related differences were observed at an upstream marker previously associated with AA levels (rs174537), wherein, 79-82% of African Americans carry two copies of the G allele compared to only 42-45% of European Americans. Importantly, the allelic effect of the G allele, which is associated with <it>enhanced </it>conversion of DGLA to AA, on enzymatic efficiency was similar in both groups.</p> <p>Conclusions</p> <p>We conclude that the impact of <it>FADS </it>genetic variants on PUFA metabolism, specifically AA levels, is likely more pronounced in African Americans due to the larger proportion of individuals carrying the genotype associated with increased FADS1 enzymatic conversion of DGLA to AA.</p