Differences In Genetic Effects Research Articles

Genome-wide association study of obstructive sleep apnoea in the Million Veteran Program uncovers genetic heterogeneity by sex.

Genome-wide association studies (GWAS) for obstructive sleep apnoea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence. We performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analysed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totalling 916,696 individuals. MVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value < 0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, previously unreported, genome-wide significant regions. Sex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared aetiology and causal pathways. Described in acknowledgements.

GENETIC RISK FOR ADHD ON LATER LIFE EMOTIONAL AND COGNITIVE HEALTH: TESTING MECHANISMS OF EFFECT

Abstract Attention Deficit Hyperactivity Disorder (ADHD) is associated with emotional regulation and cognitive processing challenges throughout life. Not well-understood is how ADHD genetic risk (ADHD-GR) affects depressive symptoms (DepSx) and cognitive functioning in older age. Furthermore, less is known about the mechanisms through which some individuals show better outcomes despite higher ADHD-GR. We evaluated potential mechanisms using the Health and Retirement Study with data from 7,871 European Americans (EAs) and 1,226 African Americans (AAs), ages 50-93, and ADHD-GR calculated from a mixed ancestry genomewide scan. Mediators included closeness of parental relationships during childhood, sense of purpose in life in adulthood, and educational attainment. Outcomes included validated scales for DepSx and cognitive functioning. Structural equation models were stratified by race/ethnicity due to potential differences in genetic effects, adjusted for age, gender, ancestry, and health conditions with DepSx and genetic risk for dementia with cognitive functioning. Among EAs, ADHD-GR significantly predicted lower sense of purpose (p&amp;lt;.05) and worse parental relationships (p&amp;lt;.001), with higher levels of both, in turn, predicting less DepSx (p's&amp;lt; 0.01). ADHD-GR also showed significant direct effects on DepSx (p&amp;lt;.01), controlling for mediators. Additionally, ADHD-GR predicted less education (p&amp;lt;.001), but more education predicted better cognitive functioning (p&amp;lt; 0.001). No relationships with ADHD-GR were significant among AAs. Findings imply that among EAs, mediators could be targets to mitigate negative effects on psychological and cognitive health, two hallmark challenges for individuals with ADHD. More work is needed to characterize ADHD-GR on outcomes among older AAs.

Sex-specific genetic factors affect the risk of early-onset periodontitis in Europeans.

Various studies have reported that young European women are more likely to develop early-onset periodontitis compared to men. A potential explanation for the observed variations in sex and age of disease onset is the natural genetic variation within the autosomal genomes. We hypothesized that genotype-by-sex (G × S) interactions contribute to the increased prevalence and severity. Using the case-only design, we tested for differences in genetic effects between men and women in 896 North-West European early-onset cases, using imputed genotypes from the OmniExpress genotyping array. Population-representative 6823 controls were used to verify that the interacting variables G and S were uncorrelated in the general population. In total, 20 loci indicated G × S associations (P < 0.0005), 3 of which were previously suggested as risk genes for periodontitis (ABLIM2, CDH13, and NELL1). We also found independent G × S interactions of the related gene paralogs MACROD1/FLRT1 (chr11) and MACROD2/FLRT3 (chr20). G × S-associated SNPs at CPEB4, CDH13, MACROD1, and MECOM were genome-wide-associated with heel bone mineral density (CPEB4, MECOM), waist-to-hip ratio (CPEB4, MACROD1), and blood pressure (CPEB4, CDH13). Our results indicate that natural genetic variation affects the different heritability of periodontitis among sexes and suggest genes that contribute to inter-sex phenotypic variation in early-onset periodontitis.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

SummaryOsteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

Sex Differences in Genetic Effects Using Two Gene Aggregation Techniques: Depression and Cognition

The state of science has increasingly valued interdisciplinary training and research. As an early-stage investigator, interdisciplinary research, such as that supported by the Research Centers Collaborative Network through the National Institute on Aging, provides valuable opportunities to connect researchers across disciplinary boundaries. This program encourages researchers use their diverse training experiences to tackle difficult questions in aging research and forge scholarly relationship that advance the state of science through creative problem-solving and a spectrum of interdisciplinary perspectives. This presentation describes a recently funded project to examine sex differences in aging outcomes using genetics, depression, and impaired cognition with polygenic and gene-region aggregation techniques. We will highlight the benefits and opportunities of the Research Centers Collaborative Network pilot grant to this highly interdisciplinary work, co-lead by early-stage investigators.

Fostering Multidisciplinary Solutions in Aging: The Research Centers Collaborative Network

The important problems facing older adults will not be solved through the methods of a single discipline. In recognition of this, the NIA funded the Research Centers Collaborative Network (RCCN) to build collaborations between scientists from the 6 NIA-sponsored center programs: Alzheimer’s Disease Research Centers, Centers on the Demography and Economics of Aging, Claude D. Pepper Older Americans Independence Centers, Nathan Shock Centers of Excellence in the Basic Biology of Aging, Resource Centers for Minority Aging Research, and Roybal Centers for Translational Research on Aging. RCCN’s central premise is that researchers from different disciplines are most likely to collaborate when they are addressing similar problems. To foster collaboration the RCCN has convened 5 workshops on: 1. achieving and sustaining behavior change in older adults; 2. sex and gender in aging research; 3. reserve and resilience; 4. life course perspectives on aging; and 5. promoting the inclusion of older adults in clinical research. After each Workshop the RCCN awards pilot funds related to the theme. This symposium will review key learnings from the workshops and present work of four RCCN pilot teams from the first two workshops which focused on changing and sustaining behavior change in older adults, and sex and gender differences in aging. Dr. Hughes will discuss the value of interdisciplinary research to maintain behavior change while Dr. Lee will discuss social incentives to improve mobility postoperatively. Dr. Stites will discuss cognition and gender trends, while Dr. Ware will discuss sex differences in genetic effects.

The genetic architecture of appendicular lean mass characterized by association analysis in the UK Biobank study

Appendicular lean mass (ALM) is a heritable trait associated with loss of lean muscle mass and strength, or sarcopenia, but its genetic determinants are largely unknown. Here we conducted a genome-wide association study (GWAS) with 450,243 UK Biobank participants to uncover its genetic architecture. A total of 1059 conditionally independent variants from 799 loci were identified at the genome-wide significance level (p < 5 × 10−9), all of which were also significant at p < 5 × 10–5 in both sexes. These variants explained ~15.5% of the phenotypic variance, accounting for more than one quarter of the total ~50% GWAS-attributable heritability. There was no difference in genetic effect between sexes or among different age strata. Heritability was enriched in certain functional categories, such as conserved and coding regions, and in tissues related to the musculoskeletal system. Polygenic risk score prediction well distinguished participants with high and low ALM. The findings are important not only for lean mass but also for other complex diseases, such as type 2 diabetes, as ALM is shown to be a protective factor for type 2 diabetes.

Influence of OATP1B1 and BCRP polymorphisms on the pharmacokinetics and pharmacodynamics of rosuvastatin in elderly and young Korean subjects

A lack of information regarding whether genetic polymorphisms of SLCO1B1 and ABCG2 affect the pharmacokinetics (PKs)/pharmacodynamics (PDs) of rosuvastatin in elderly subjects prevents optimal individualized pharmacotherapy of rosuvastatin in clinical settings. This study aimed to investigate the effect of age and genetic polymorphisms and possible differences in genetic effects on the PKs/PDs of rosuvastatin between elderly and young subjects. Two separate clinical studies designed as open-label, one-sequence studies with multiple-dose administration for elderly (n = 20) and young (n = 32) subjects were conducted. All subjects received 20 mg of rosuvastatin once daily for 21 days. The exposure to rosuvastatin, characterized by the area under the time curve (AUC), increased by 23% in the elderly subjects compared with that of young subjects, which was not significant. When compared to the subjects with breast cancer resistance protein (BCRP) normal function, the exposure to rosuvastatin increased by 44% in young subjects (p = 0.0021) with BCRP intermediate function (IF) and by 35% and 59% (p > 0.05 for both) in elderly subjects with BCRP IF and low function, respectively. SLCO1B1 521T > C was also partially associated with a higher AUC of rosuvastatin in young subjects and a less pronounced increasing trend in elderly subjects (p > 0.05 for both). The lipid-lowering effect of rosuvastatin was less pronounced in the elderly subjects than in the young subjects, and genetic polymorphisms of neither SLCO1B1 nor ABCG2 significantly affected the PDs of rosuvastatin. The ABCG2 421C > A polymorphism was associated with the PKs of rosuvastatin and was identified as a more important determinant than the SLCO1B1 521T > C polymorphism in both elderly and young subjects.

Genetics of Chronic Kidney Disease Stages Across Ancestries: The PAGE Study

BackgroundChronic kidney disease (CKD) is common and disproportionally burdens United States ethnic minorities. Its genetic determinants may differ by disease severity and clinical stages. To uncover genetic factors associated CKD severity among high-risk ethnic groups, we performed genome-wide association studies (GWAS) in diverse populations within the Population Architecture using Genomics and Epidemiology (PAGE) study.MethodsWe assembled multi-ethnic genome-wide imputed data on CKD non-overlapping cases [4,150 mild to moderate CKD, 1,105 end-stage kidney disease (ESKD)] and non-CKD controls for up to 41,041 PAGE participants (African Americans, Hispanics/Latinos, East Asian, Native Hawaiian, and American Indians). We implemented a generalized estimating equation approach for GWAS using ancestry combined data while adjusting for age, sex, principal components, study, and ethnicity.ResultsThe GWAS identified a novel genome-wide associated locus for mild to moderate CKD nearby NMT2 (rs10906850, p = 3.7 × 10-8) that replicated in the United Kingdom Biobank white British (p = 0.008). Several variants at the APOL1 locus were associated with ESKD including the APOL1 G1 rs73885319 (p = 1.2 × 10-9). There was no overlap among associated loci for CKD and ESKD traits, even at the previously reported APOL1 locus (p = 0.76 for CKD). Several additional loci were associated with CKD or ESKD at p-values below the genome-wide threshold. These loci were often driven by variants more common in non-European ancestry.ConclusionOur genetic study identified a novel association at NMT2 for CKD and showed for the first time strong associations of the APOL1 variants with ESKD across multi-ethnic populations. Our findings suggest differences in genetic effects across CKD severity and provide information for study design of genetic studies of CKD in diverse populations.

Comparative analysis of genetic effects of wheat‐Dasypyrum villosum translocations T6V#2S·6AL and T6V#4S·6DL

AbstractWheat‐Dasypyrum villosum translocations T6V#2S·6AL and T6V#4S·6DL, carriers of Pm21 and PmV, respectively, confer high resistance to wheat powdery mildew. For better understanding of the difference in genetic effect between them, a RIL population was constructed based on the cross between “Yangmai 18” carrying T6V#2S·6AL and “Yangmai 22” carrying T6V#4S·6DL. Analysis of distribution of the translocations showed that T6V#2S·6AL is much more transmittable than T6V#4S·6DL. By comparing their effects on main agronomic traits, we firstly found that T6V#2S·6AL contributes greatly to top spikelet fecundity, but causes a decrease of 6.7%–10.5% of spike number. No stable effects of T6V#4S·6DL on agronomic traits were found, except for positive effect on plant height. Excitingly, a new recombinant, T6V#4S‐6V#2S·6AL carrying PmV, was screened and proved to have a higher transmission rate than the original translocation T6V#4S·6DL, which will greatly promote the utilization of PmV. The above conclusions of this research will provide important guidance for utilization of Pm21 and PmV more effectively, in wheat powdery mildew resistance breeding.

Genome-wide association study of homocysteine in African Americans from the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Coronary Artery Risk in Young Adults study.

Homocysteine (Hcy) is a heritable biomarker for CVD, peripheral artery disease, stroke, and dementia. Little is known about genetic associations with Hcy in individuals of African ancestry. We performed a genome-wide association study for Hcy in 4,927 AAs from the Jackson Heart Study (JHS), the Multi-Ethnic Study of Atherosclerosis (MESA), and the Coronary Artery Risk in Young Adults (CARDIA) study. Analyses were stratified by sex and results were meta-analyzed within and across sex. In the sex-combined meta-analysis, we observed genome-wide significant evidence (p<5.0×10−8) for the NOX4 locus (lead variant rs2289125, β= −0.15, p= 5.3 × 10−11). While the NOX4 locus was previously reported as associated with Hcy in European American populations, rs2289125 remained genome-wide significant when conditioned on the previously reported lead variants. Previously reported genome-wide significant associations at NOX4, MTR, CBS, and MMACHC were also nominally (p<0.050) replicated in AAs. Associations at the CPS1 locus, previously reported in females only, also was replicated specifically in females in this analysis, supporting sex-specific effects for this locus. These results suggest that there may be a combination of cross-population and population-specific genetic effects, as well as differences in genetic effects between males and females, in the regulation of Hcy levels.

Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation.

Genome-wide association meta-analyses (GWAMAs) conducted separately by two strata have identified differences in genetic effects between strata, such as sex-differences for body fat distribution. However, there are several approaches to identify such differences and an uncertainty which approach to use. Assuming the availability of stratified GWAMA results, we compare various approaches to identify between-strata differences in genetic effects. We evaluate type I error and power via simulations and analytical comparisons for different scenarios of strata designs and for different types of between-strata differences. For strata of equal size, we find that the genome-wide test for difference without any filtering is the best approach to detect stratum-specific genetic effects with opposite directions, while filtering for overall association followed by the difference test is best to identify effects that are predominant in one stratum. When there is no a priori hypothesis on the type of difference, a combination of both approaches can be recommended. Some approaches violate type I error control when conducted in the same data set. For strata of unequal size, the best approach depends on whether the genetic effect is predominant in the larger or in the smaller stratum. Based on real data from GIANT (>175 000 individuals), we exemplify the impact of the approaches on the detection of sex-differences for body fat distribution (identifying up to 10 loci). Our recommendations provide tangible guidelines for future GWAMAs that aim at identifying between-strata differences. A better understanding of such effects will help pinpoint the underlying mechanisms.

Sex-specific genetic effects associated with pigmentation, sensitivity to sunlight, and melanoma in a population of Spanish origin.

BackgroundHuman pigmentation is a polygenic quantitative trait with high heritability. In addition to genetic factors, it has been shown that pigmentation can be modulated by oestrogens and androgens via up- or down-regulation of melanin synthesis. Our aim was to identify possible sex differences in pigmentation phenotype as well as in melanoma association in a melanoma case-control population of Spanish origin.MethodsFive hundred and ninety-nine females (316 melanoma cases and 283 controls) and 458 males (234 melanoma cases and 224 controls) were analysed. We genotyped 363 polymorphisms (single nucleotide polymorphisms (SNPs)) from 65 pigmentation gene regions.ResultsWhen samples were stratified by sex, we observed more SNPs associated with dark pigmentation and good sun tolerance in females than in males (107 versus 75; P = 2.32 × 10−6), who were instead associated with light pigmentation and poor sun tolerance. Furthermore, six SNPs in TYR, SILV/CDK2, GPR143, and F2RL1 showed strong differences in melanoma risk by sex (P < 0.01).ConclusionsWe demonstrate that these genetic variants are important for pigmentation as well as for melanoma risk, and also provide suggestive evidence for potential differences in genetic effects by sex.Electronic supplementary materialThe online version of this article (doi:10.1186/s13293-016-0070-1) contains supplementary material, which is available to authorized users.

Using Bayesian Multilevel Whole Genome Regression Models for Partial Pooling of Training Sets in Genomic Prediction.

Training set size is an important determinant of genomic prediction accuracy. Plant breeding programs are characterized by a high degree of structuring, particularly into populations. This hampers the establishment of large training sets for each population. Pooling populations increases training set size but ignores unique genetic characteristics of each. A possible solution is partial pooling with multilevel models, which allows estimating population-specific marker effects while still leveraging information across populations. We developed a Bayesian multilevel whole-genome regression model and compared its performance with that of the popular BayesA model applied to each population separately (no pooling) and to the joined data set (complete pooling). As an example, we analyzed a wide array of traits from the nested association mapping maize population. There we show that for small population sizes (e.g., <50), partial pooling increased prediction accuracy over no or complete pooling for populations represented in the training set. No pooling was superior; however, when populations were large. In another example data set of interconnected biparental maize populations either partial or complete pooling was superior, depending on the trait. A simulation showed that no pooling is superior when differences in genetic effects among populations are large and partial pooling when they are intermediate. With small differences, partial and complete pooling achieved equally high accuracy. For prediction of new populations, partial and complete pooling had very similar accuracy in all cases. We conclude that partial pooling with multilevel models can maximize the potential of pooling by making optimal use of information in pooled training sets.

Genetic Influences on Trajectories of Systolic Blood Pressure Across Childhood and Adolescence

Blood pressure (BP) tends to increase across childhood and adolescence, but the genetic influences on rates of BP change are not known. Potentially important genetic influences could include genetic variants identified in genome-wide association studies of adults as being associated with BP, height, and body mass index. Understanding the contribution of these genetic variants to changes in BP across childhood and adolescence could yield understanding into the life course development of cardiovascular risk. Pooling data from 2 cohorts (the Avon Longitudinal Study of Parents and Children [n=7013] and the Western Australian Pregnancy Cohort [n=1459]), we examined the associations of allelic scores of 29 single-nucleotide polymorphisms (SNPs) for adult BP, 180 height SNPs, and 32 body mass index SNPs, with trajectories of systolic BP (SBP) from 6 to 17 years of age, using linear spline multilevel models. The allelic scores of BP and body mass index SNPs were associated with SBP at 6 years of age (per-allele effect sizes, 0.097 mm Hg [SE, 0.039 mm Hg] and 0.107 mm Hg [SE, 0.037 mm Hg]); associations with age-related changes in SBP between 6 and 17 years of age were of small magnitude and imprecisely estimated. The allelic score of height SNPs was only weakly associated with SBP changes. No sex or cohort differences in genetic effects were observed. Allelic scores of BP and body mass index SNPs demonstrated associations with SBP at 6 years of age with a similar magnitude but were not strongly associated with changes in SBP with age between 6 and 17 years. Further work is required to identify variants associated with changes with age in BP.

Genetic Susceptibility to Sickness Absence is Similar Among Women and Men: Findings From a Swedish Twin Cohort

Previous studies of risk factors for sickness absence (SA) focus primarily on psychosocial and work environmental exposures. The aim of this study was to investigate the relative contribution of genetic influences on SA among women and men. The population-based study sample of Swedish twins (34,547) included 13,743 twin pairs of known zygosity, 3,495 monozygotic, 5,073 same-sexed dizygotic, and 5,175 opposite sexed. The point prevalence of long-term SA (≥15 days) in each zygosity and sex group was calculated. The risk of SA was estimated as an odds ratio (OR) with 95% confidence intervals (CI) where the odds for twins on SA to have a co-twin on SA was compared to the OR for SA in twins whose co-twin were not sickness absent. Intrapair correlations and probandwise concordance rates were calculated and standard biometrical genetic model-fitting methods were used to estimate the heritability of SA. The prevalence of SA was 8.8% (women 10.7%; men 6.5%). Intrapair similarity was higher among monozygotic than dizygotic twin pairs. The best-fitting model showed no sex differences in genetic effects or variance components contributing to SA. The heritability estimate was 36% (95% CI: 35-40%). Results suggest genetic contribution to the variation of SA and that environmental factors have an important role, for women and men. As SA seem to be influenced by genetic factors, future studies of associations between risk factors and SA should consider this potentially confounding effect.

Sex-specific differences in effect size estimates at established complex trait loci

Background Genetic differences between men and women may contribute to sex differences in prevalence and progression of many common complex diseases.Using the WTCCC GWAS, we analysed whether there are sex-specific differences in effect size estimates at 142 established loci for seven complex diseases: rheumatoid arthritis, type 1 diabetes (T1D), Crohn’s disease, type 2 diabetes (T2D), hypertension, coronary artery disease and bipolar disorder.Methods For each Single nucleotide polymorphism (SNP), we calculated the per-allele odds ratio for each sex and the relative odds ratios (RORs; the effect size is higher in men with ROR greater than one). RORs were then meta-analysed across loci within each disease and across diseases.Results For each disease, summary RORs were not different from one, but there was between-SNP heterogeneity in the RORs for T1D and T2D. Four loci in T1D, three in Crohn’s disease and three in T2D showed differences in the genetic effect between men and women (P < 0.05). We probed these differences in additional independent replication samples for T1D and T2D. The differences remained for the T1D loci CTSH, 17q21 and 20p13 and the T2D locus BCL11A, when WTCCC data and replication data were meta-analysed. Only CTSH showed different genetic effect between men and women in the replication data alone.Conclusion Our results exclude the presence of large and frequent differences in the effect size estimates between men and women for the established loci in the seven common diseases explored. Documenting small differences in genetic effects between men and women requires large studies and systematic evaluation.

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

The effects of puberty on genetic risk for disordered eating: evidence for a sex difference.

Differences in genetic influences on disordered eating are present across puberty in girls. Heritability is 0% before puberty, but over 50% during and after puberty. Emerging data suggest that these developmental differences may be due to pubertal increases in ovarian hormones. However, a critical piece of evidence is lacking, namely, knowledge of genetic influences on disordered eating across puberty in boys. Boys do not experience increases in ovarian hormones during puberty. Thus, if pubertal increases in genetic effects are present in boys, then factors in addition to ovarian hormones may drive increases in heritability in girls. The current study was the first to examine this possibility in a sample of 1006 male and female twins from the Michigan State University Twin Registry. Disordered eating was assessed with the Minnesota Eating Behavior Survey. Pubertal development was assessed with the Pubertal Development Scale. No significant differences in genetic influences on disordered eating were observed in males across any developmental stage. Heritability was 51% in boys during pre-puberty, puberty and young adulthood. By contrast, in girls, genetic factors accounted for 0% of the variance in pre-puberty, but 51% of the variance during puberty and beyond. Sex differences in genetic effects were only significant during pre-puberty, as the best-fitting models constrained heritability to be equal across all males, pubertal females and young adult females. The results highlight sex-specific effects of puberty on genetic risk for disordered eating and provide indirect evidence of a role for ovarian hormones and/or other female-specific factors.