Project description:Impulsivity and compulsivity are traits relevant to a range of mental health problems and have traditionally been conceptualised as distinct constructs. Here, we reconceptualised impulsivity and compulsivity as partially overlapping phenotypes using a bifactor modelling approach and estimated heritability for their shared and unique phenotypic variance within a classical twin design. Adult twin pairs (N = 173) completed self-report questionnaires measuring psychological processes related to impulsivity and compulsivity. We fitted variance components models to three uncorrelated phenotypic dimensions: a general impulsive-compulsive dimension; and two narrower phenotypes related to impulsivity and obsessiveness.There was evidence of moderate heritability for impulsivity (A2 = 0.33), modest additive genetic or common environmental effects for obsessiveness (A2 = 0.25; C2 = 0.23), and moderate effects of common environment (C2 = 0.36) for the general dimension, This general impulsive-compulsive phenotype may reflect a quantitative liability to related mental health disorders that indexes exposure to potentially modifiable environmental risk factors.
Project description:IntroductionWhile whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes.MethodsWe applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV1), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort.ResultsWe found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts.ConclusionsLongitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.
Project description:Nonhuman primates and especially rhesus macaques (Macaca mulatta) have been indispensable animal models for studies of various aspects of neurobiology, developmental psychology, and other aspects of neuroscience. While remarkable progress has been made in our understanding of influences on atypical human social behavior, such as that observed in autism spectrum disorders (ASD), many significant questions remain. Improved understanding of the relationships among variation in specific genes and variation in expressed social behavior in a nonhuman primate would benefit efforts to investigate risk factors, developmental mechanisms, and potential therapies for behavioral disorders including ASD. To study genetic influences on key aspects of social behavior and interactions-individual competence and/or motivation for specific aspects of social behavior-we quantified individual variation in social interactions among juvenile rhesus macaques using both a standard macaque ethogram and a macaque-relevant modification of the human Social Responsiveness Scale. Our analyses demonstrate that various aspects of juvenile social behavior exhibit significant genetic heritability, with estimated quantitative genetic effects similar to that described for ASD in human children. We also performed exome sequencing and analyzed variants in 143 genes previously suggested to influence risk for human ASD. We find preliminary evidence for genetic association between specific variants and both individual behaviors and multi-behavioral factor scores. To our knowledge, this is the first demonstration that spontaneous social behaviors performed by free-ranging juvenile rhesus macaques display significant genetic heritability and then to use exome sequencing data to examine potential macaque genetic associations in genes associated with human ASD.
Project description:the goal of this experiment is to identify the molecular modules that underlie social phenotypes in A. burtoni Keywords: loop design comparison of dominant (T) subordinate (NT) and brooding female (F) phenotypes 6 individuals of each phenotype under normal mixed population conditions
Project description:Telomere length and telomere shortening predict survival in many organisms. This raises the question of the contribution of genetic and environmental effects to variation in these traits, which is still poorly known, particularly for telomere shortening. We used experimental (cross-fostering) and statistical (quantitative genetic "animal models") means to disentangle and estimate genetic and environmental contributions to telomere length variation in pedigreed free-living jackdaws (Corvus monedula). Telomere length was measured twice in nestlings, at ages 4 (n = 715) and 29 days (n = 474), using telomere restriction fragment (TRF) analysis, adapted to exclude interstitial telomeric sequences. Telomere length shortened significantly over the nestling period (10.4 ± 0.3 bp day-1 ) and was highly phenotypically (rP = 0.95 ± 0.01) and genetically (rG > 0.99 ± 0.01) correlated within individuals. Additive genetic effects explained a major part of telomere length variation among individuals, with its heritability estimated at h2 = 0.74 on average. We note that TRF-based studies reported higher heritabilities than qPCR-based studies, and we discuss possible explanations. Parent-offspring regressions yielded similar heritability estimates for mothers and fathers when accounting for changes in paternal telomere length over life. Year effects explained a small but significant part of telomere length variation. Heritable variation for telomere shortening was low (h2 = 0.09 ± 0.11). The difference in heritability between telomere length (high) and telomere shortening (low) agrees with evolutionary theory, in that telomere shortening has stronger fitness consequences in this population. Despite the high heritability of telomere length, its evolvability, which scales the additive genetic variance by mean telomere length, was on average 0.48%. Hence, evolutionary change of telomere length due to selection is likely to be slow.
Project description:Many correlated disease variables are analyzed jointly in genetic studies in the hope of increasing power to detect causal genetic variants. One approach involves assessing the relationship between each phenotype and each SNP individually and using a Bonferroni correction for the effective number of tests conducted. Alternatively, one can apply a multivariate regression or a dimension reduction technique, such as principal component analysis, and test for the association with the principal components of the phenotypes rather than the individual phenotypes. Inspired by the previous approaches of combining phenotypes to maximize heritability at individual SNPs, in this paper, we propose to construct a maximally heritable (MaxH) phenotype by taking advantage of the estimated total heritability and co-heritability. The heritability and co-heritability only need to be estimated once; therefore, our method is applicable to genome-wide scans. The MaxH phenotype is a linear combination of the individual phenotypes with increased heritability and power over the phenotypes being combined. Simulations show that the heritability and power achieved agree well with the theory for large samples and two phenotypes. We compare our approach with commonly used methods and assess both the heritability and the power of the MaxH phenotype. Moreover, we provide suggestions for how to choose the phenotypes for combination. An application of our approach to a GWAS on chronic obstructive pulmonary disease shows its practical relevance.
Project description:Changes in an individual's human metabolic phenotype (metabotype) over time can be indicative of disorder-related modifications. Studies covering several months to a few years have shown that metabolic profiles are often specific for an individual. This "metabolic individuality" and detected changes may contribute to personalized approaches in human health care. However, it is not clear whether such individual metabotypes persist over longer time periods. Here we investigate the conservation of metabotypes characterized by 212 different metabolites of 818 participants from the Cooperative Health Research in the Region of Augsburg; Germany population, taken within a 7-year time interval. For replication, we used paired samples from 83 non-related individuals from the TwinsUK study. Results indicated that over 40 % of all study participants could be uniquely identified after 7 years based on their metabolic profiles alone. Moreover, 95 % of the study participants showed a high degree of metabotype conservation (>70 %) whereas the remaining 5 % displayed major changes in their metabolic profiles over time. These latter individuals were likely to have undergone important biochemical changes between the two time points. We further show that metabolite conservation was positively associated with heritability (rank correlation 0.74), although there were some notable exceptions. Our results suggest that monitoring changes in metabotypes over several years can trace changes in health status and may provide indications for disease onset. Moreover, our study findings provide a general reference for metabotype conservation over longer time periods that can be used in biomarker discovery studies.
Project description:RationalePrevious studies of chronic obstructive pulmonary disease (COPD) have suggested that genetic factors play an important role in the development of disease. However, single-nucleotide polymorphisms that are associated with COPD in genome-wide association studies have been shown to account for only a small percentage of the genetic variance in phenotypes of COPD, such as spirometry and imaging variables. These phenotypes are highly predictive of disease, and family studies have shown that spirometric phenotypes are heritable.ObjectivesTo assess the heritability and coheritability of four major COPD-related phenotypes (measurements of FEV1, FEV1/FVC, percent emphysema, and percent gas trapping), and COPD affection status in smokers of non-Hispanic white and African American descent using a population design.MethodsSingle-nucleotide polymorphisms from genome-wide association studies chips were used to calculate the relatedness of pairs of individuals and a mixed model was adopted to estimate genetic variance and covariance.Measurements and main resultsIn the non-Hispanic whites, estimated heritabilities of FEV1 and FEV1/FVC were both about 37%, consistent with estimates in the literature from family-based studies. For chest computed tomography scan phenotypes, estimated heritabilities were both close to 25%. Heritability of COPD affection status was estimated as 37.7% in both populations.ConclusionsThis study suggests that a large portion of the genetic risk of COPD is yet to be discovered and gives rationale for additional genetic studies of COPD. The estimates of coheritability (genetic covariance) for pairs of the phenotypes suggest considerable overlap of causal genetic loci.
Project description:ImportanceMechanisms behind pigmentary glaucoma, a form of early-onset glaucoma that may potentially lead to severe visual impairment or blindness, are poorly understood.ObjectiveTo calculate the single-nucleotide polymorphism (SNP) heritability of pigmentary glaucoma and identify genetic associations with the disease.Design, setting and participantsThis genome-wide association study included affected individuals from Germany and control participants from the United Kingdom. Genome-wide information was obtained for patients with pigmentary glaucoma and control participants free of glaucoma by using the Illumina Human Omni Express Exome 8v1-2 chip and genomic imputation. The SNP heritability of pigmentary glaucoma was estimated through a restricted maximum likelihood analysis. Associations between the genetic variants and pigmentary glaucoma obtained from age, sex, and principal component-adjusted logistic regression models were compared with those of SNPs previously associated with other eye phenotypes using Pearson product-moment correlations. Data were collected from November 2008 to January 2018, and analysis was completed between April 2018 and August 2019.Main outcomes and measuresAn estimate of SNP-explained heritability for pigmentary glaucoma; correlations of effect sizes between pigmentary glaucoma and iris pigmentation and myopia; and correlations of effect sizes between pigmentary glaucoma and other eye phenotypes.ResultsA total of 227 affected individuals (mean [SD] age, 58.7 [13.3] years) and 291 control participants (mean [SD] age, 80.2 [4.9] years) were included; all were of European ancestry. The SNP heritability of pigmentary glaucoma was 0.45 (SE, 0.22; P = 6.15 × 10-10). Twelve SNPs previously reported with genome-wide significant associations with eye pigmentation were associated with pigmentary glaucoma's SNP heritability (4.9% SNP heritability; 0.022; P = 6.0 × 10-4). Pigmentary glaucoma SNP effect sizes were correlated moderately for myopia (r, 0.42 [95% CI, 0.14-0.63]; P = 4.3 × 10-3) and more strongly with those for iris pigmentation (r = -0.69 [95% CI, -0.91 to -0.20]; P = .01), although this was nonsignificant per a strict adjusted significance threshold (P < .01).Conclusions and relevanceThese findings support the conclusion that pigmentary glaucoma may have a genetic basis and be highly heritable. Variants associated with lighter eye color and myopia appear to be associated with increased risk of pigmentary glaucoma, but no shared genetic basis with primary open-angle glaucoma (or its quantitative endophenotype of cup-disc ratio) was observed.
Project description:Pharmacogenomic studies have successfully identified variants-typically with large effect sizes in drug target and metabolism enzymes-that predict drug outcome phenotypes. However, these variants may account for a limited proportion of phenotype variability attributable to the genome. Using genome-wide common variation, we measured the narrow-sense heritability ( hSNP2 ) of seven pharmacodynamic and five pharmacokinetic phenotypes across three cardiovascular drugs, two antibiotics, and three immunosuppressants. We used a Bayesian hierarchical mixed model, BayesR, to model the distribution of genome-wide variant effect sizes for each drug phenotype as a mixture of four normal distributions of fixed variance (0, 0.01%, 0.1%, and 1% of the total additive genetic variance). This model allowed us to parse hSNP2 into bins representing contributions of no-effect, small-effect, moderate-effect, and large-effect variants, respectively. For the 12 phenotypes, a median of 969 (range 235-6,304) unique individuals of European ancestry and a median of 1,201,626 (range 777,427-1,514,275) variants were included in our analyses. The number of variants contributing to hSNP2 ranged from 2,791 to 5,356 (median 3,347). Estimates for hSNP2 ranged from 0.05 (angiotensin-converting enzyme inhibitor-induced cough) to 0.59 (gentamicin concentration). Small-effect and moderate-effect variants contributed a majority to hSNP2 for every phenotype (range 61-95%). We conclude that drug outcome phenotypes are highly polygenic. Thus, larger genome-wide association studies of drug phenotypes are needed both to discover novel variants and to determine how genome-wide approaches may improve clinical prediction of drug outcomes.