Environmental Variance Components Research Articles

The genetic and environmental architecture of substance use development from early adolescence into young adulthood: a longitudinal twin study of comorbidity of alcohol, tobacco and illicit drug use

To investigate how use of alcohol, illicit drugs and tobacco come from substance-specific pathways and from pathways general to all three substances through adolescent development. Analysis of population-based survey. Adolescent twins reported alcohol use (AU), tobacco use (TU) and illicit drug use (IDU) in three waves (2006, 2008, 2010). Restructuring data by age allowed for variance decomposition into age- and substance-specific and common genetic and environmental variance components. Norway. Seven national twin birth cohorts from 1988 to 1994, totalling 1483 pairs (558 monozygotic; 925 dizygotic, same and opposite sex). Six-point Likert scores of AU, TU and IDU on items from the Monitoring the Future Study. Substance use was found to be highly heritable; a2 =0.73 [95% confidence interval (CI) =0.61-0.94] for AU, a2 =0.36 (CI=0.18-0.52); d2 =0.49 (95% CI=0.29-0.62) for IDU and a2 =0.46 (95% CI=0.23-0.54); d2 =0.05 (95% CI=0.00-0.07) for TU during the whole adolescence period. General substance use (GSU) was also highly heritable at each age and averaged a2 =0.57 (95% CI=0.48-0.66). There was a high genetic carry-over from earlier age to later age. Genetic effects on GSU at ages 12-14years were still detectable 4years later. New substance (general and specific)-genetic effects also appeared. IDU demonstrated significant non-additive genetic effects (ages 12-14years). Shared environment had a small impact on AU only. There was almost no non-shared environmental carry-over from age to age, the effect probably due partly to reliability deficiency. Common genetic effects among substance and substance-specific genetic effects were observed at each age-period. Among Norwegian adolescents, there appear to be strong genetic effects on both substance-specific and comorbid use of alcohol, illicit drugs and tobacco; individual differences in alcohol use can be explained partially by family background.

Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction.

Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2,110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES.

ACEt: An R Package for Estimating Dynamic Heritability and Comparing Twin Models.

Estimating dynamic effects of age on the genetic and environmental variance components in twin studies may contribute to the investigation of gene-environment interactions, and may provide more insights into more accurate and powerful estimation of heritability. Existing parametric models for estimating dynamic variance components suffer from various drawbacks such as limitation of predefined functions. We present ACEt, an R package for fast estimating dynamic variance components and heritability that may change with respect to age or other moderators. Building on the twin models using penalized splines, ACEt provides a unified framework to incorporate a class of ACE models, in which each component can be modeled independently and is not limited by a linear or quadratic function. We demonstrate that ACEt is robust against misspecification of the number of spline knots, and offers a refined resolution of dynamic behavior of the genetic and environmental components and thus a detailed estimation of age-specific heritability. Moreover, we develop resampling methods for testing twin models with different variance functions including splines, log-linearity and constancy, which can be easily employed to verify various model assumptions. We evaluated the type I error rate and statistical power of the proposed hypothesis testing procedures under various scenarios using simulated datasets. Potential numerical issues and computational cost were also assessed through simulations. We applied the ACEt package to a Finnish twin cohort to investigate age-specific heritability of body mass index and height. Our results show that the age-specific variance components of these two traits exhibited substantially different patterns despite of comparable estimates of heritability. In summary, the ACEt R package offers a useful tool for the exploration of age-dependent heritability and model comparison in twin studies.

SOCIOECONOMIC ADVERSITY AND ALLOSTATIC LOAD: A TWIN ANALYSIS

Childhood socioeconomic status (SES) is related to health concurrently and into adulthood, and is associated with adulthood SES. Given these far-reaching relationships, some question whether adulthood SES associates with health beyond childhood SES. Biometric twin (ACE) models partition the predictor variables into additive genetic (A), shared environmental (C), and nonshared (unique) environmental (E) variance components. Researchers can control for latent genetic and shared environmental factors that may confound conclusions about the causal effects of adulthood SES on health. We used family data from the second wave of the national Midlife in the United States (MIDUS) Study (128 MZ pairs, 99 DZ pairs, 119 Sibling pairs) to examine this question. Health was assessed with a measure of multi-system physiological dysregulation posited to confer risk for the development of physical health problems. Adult SES was calculated with education, family-adjusted poverty to income ratio, current financial situation, enough money to meet needs, and difficulty paying bills. Results of ACE models suggested that male twins with lower adult SES had higher allostatic load, indicating greater physiological risk, than their co-twins with higher SES (b = 0.19), adjusting for genetic and shared environmental correlations between allostatic load and SES, and observed childhood SES, health status, and perceived support from family and friends. This relationship was not observed among female twins. These results add to a growing literature indicating that lower adult SES is associated with poorer multi-system physiological health, even after accounting for shared genetic and early environmental influences.

Shared Genetics and Couple-Associated Environment Are Major Contributors to the Risk of Both Clinical and Self-Declared Depression

BackgroundBoth genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. MethodsUsing data from a large Scottish family-based cohort (GS:SFHS, N=19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM). FindingsBoth MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r=1.00, se=0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r=0.57, se=0.08) and the couple-shared environmental effect (r=0.53, se=0.22). InterpretationBoth genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression.

The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis.

Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.

Heritability of serum dehydroepiandrosterone sulphate levels and pubertal development in 6∼18-year-old girls: a twin study

Background: Dehydroepiandrosterone sulphate (DHEAS), the most plentiful circulating adrenal hormone, may be considered as a marker of the onset of adrenarche and is involved in pubertal development and metabolic disorders.Aim: The objective of this study is to determine the genetic and environmental influences on the variation of basal DHEAS levels and pubertal development in pubertal girls.Subjects and methods: Three hundred and sixty twin girls aged 6–18-years were enrolled, consisting of 132 monozygotic pairs and 48 dizygotic pairs. Anthropometric and sexual characteristics were examined. Serum DHEAS was measured by RIA. Estimates of genetic and environmental components of variance were based on the theory of normal maximum likelihood in Mx package.Results: Serum DHEAS concentrations of PH-II and PH-III were significantly higher than Tanner stage PH-I (p < .05) and maintained higher levels in PH-IV ∼ V. Heritability of serum DHEAS estimated by model-fitting on data from 180-pairs of twins is 0.61 (0.52–0.70), the rest of the variance in DHEAS levels could be explained by unique environmental influences and age. The heritabilities of DHEAS in two pubertal sub-groups (PH-I and PH-II-V) are 0.82 (0.71–0.90) and 0.63 (0.52–0.74), respectively. The heritability index of menarche, breast development and pube development are 0.71, 0.35 and 0.45, respectively.Conclusions: Serum DHEAS concentrations of pubertal girls are mainly influenced by genetic factors, especially during the period of adrenarche. The results stress the importance of research into the genetic regulation of the endocrine regulators involved in adrenarche and related metabolic disorders in girls.

Understanding the genetic bases of adaptation to soil water deficit in trees through the examination of water use efficiency and cavitation resistance: maritime pine as a case study

This article provides a comprehensive view on the existing knowledge related to adaptation to soil water deficit in maritime pine, a conifer species widely planted in the southwestern Europe. It synthesizes discoveries made in ecophysiology, quantitative and population genetics as well as in genomics, combining several layers of information at the genotypic, phenotypic and environmental levels. Particular focus is given to two major traits: water-use efficiency (WUE) and cavitation resistance (CR). The former is related the maintenance of productivity during periods of lower soil water availability, whereas the latter is tightly linked to survival during severe drought. The development of high throughput phenotypic technologies have made it possible to estimate genetic and environmental variance components of these key traits, providing clues about their suitability for breeding and the evolutionary forces that have shaped their variability. Both CR and WUE were screened in different ecotypes as well as in the Aquitaine breeding population, the main genetic resource of the most advanced maritime pine breeding program in Europe.While the unexpectedly low level of variation of CR within and between natural populations will most likely hamper its use in breeding application, for WUE the medium heritability, absence of unfavorable phenotypic and genetic correlations with diameter growth, as well as the high inter-site correlation and weak genotype-by-environment interaction indicates that artificial selection could be applied for this trait without unfavorable consequences for radial growth, at least within the Aquitaine provenance. On the other hand, recent advances in sequencing and genotyping technologies have contributed to reveal the genetic architecture (i.e. number, location and effect of quantitative trait loci) of these two traits. In combination with ultra-dense genetic linkage map and functional genomics approaches, these findings will contribute to identify positional and expressional candidate genes that should be validated by association genetics and eventually introduced in genomic prediction models to make such knowledge useful to improve tree breeding.This review also opens up new research avenues and raises key questions on how to promote adaptation to the challenge of soil water deficit through genetic approaches in this species. If the results obtained so far in maritime pine can only applied to the tested genetic material, we however believe that the overall strategy presented here can be considered and cited as an example of integrative research to better understand the genetic bases of adaptation to soil water deficit in any forest tree species.

Psychopathic personality traits in 5\xa0year old twins: the importance of genetic and shared environmental influences

There is limited research on the genetic and environmental bases of psychopathic personality traits in children. In this study, psychopathic personality traits were assessed in a total of 1189 5-year-old boys and girls drawn from the Preschool Twin Study in Sweden. Psychopathic personality traits were assessed with the Child Problematic Traits Inventory, a teacher-report measure of psychopathic personality traits in children ranging from 3 to 12 years old. Univariate results showed that genetic influences accounted for 57, 25, and 74 % of the variance in the grandiose–deceitful, callous–unemotional, and impulsive–need for stimulation dimensions, while the shared environment accounted for 17, 48 and 9 % (n.s.) in grandiose–deceitful and callous–unemotional, impulsive–need for stimulation dimensions, respectively. No sex differences were found in the genetic and environmental variance components. The non-shared environment accounted for the remaining 26, 27 and 17 % of the variance, respectively. The three dimensions of psychopathic personality were moderately correlated (0.54–0.66) and these correlations were primarily mediated by genetic and shared environmental factors. In contrast to research conducted with adolescent and adult twins, we found that both genetic and shared environmental factors influenced psychopathic personality traits in early childhood. These findings indicate that etiological models of psychopathic personality traits would benefit by taking developmental stages and processes into consideration.

Northern exposure: Mandibular torus in the Greenlandic Norse and the whole wide world.

In the first issue of the American Journal of Physical Anthropology, E.A. Hooton noted the expression of Eskimoid characteristics in the Icelandic skull, one of which was mandibular torus. Our goal is to evaluate this trait in another North Atlantic population, the Greenlandic Norse. An investigation of mandibular torus was carried out on all Greenlandic Norse skeletons disinterred up to 1986 (n = 109), along with comparative samples from Iceland (n = 82), Norway (n = 98), and Denmark (n = 64). Torus expression was scored on a six grade scale with absence and five degrees of trait presence. Greenlanders and Icelanders show extraordinarily high frequencies (65-97%) and pronounced expressions of mandibular torus. More surprising was the almost complete absence of this trait in a Danish Viking sample (9%) and a significantly lower frequency in medieval Norwegians (48%). The dramatic expression of mandibular torus in the Greenlandic Norse and their contrast to related Scandinavian populations in Europe stimulated the collection of data from the literature and the database of Christy G. Turner II for 49,970 individuals in 335 populations. When plotted on a global scale, mandibular torus shows a strong clinal distribution with the highest frequencies in northern latitudes and the lowest frequencies around the equator. Although mandibular torus has some hereditary component, as indicated by family studies, the trait has a strong environmental component of variance. How factors of a northern environment, including climatic stress and dietary behavior, influence torus expression remains enigmatic.

Detection of gene-environment interaction in pedigree data using genome-wide genotypes.

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

Environmental Variances of Fruit Traits in a Mandarin-related Population Used in Citrus Breeding in Japan

We estimated environmental variance components for fruit weight (FW), ease of peeling (EP), firmness of segment membrane (FSM), soluble solids content (SSC), and acidity of 20 mandarin and related cultivars used as cross-parents in citrus breeding in Japan. The variance by year was largest for FW (38% of the total) and SSC (23%), but negligible for EP, FSM, and acidity. Variance among trees and tree × year interaction were negligibly small except for FW, whereas the genotype × year interaction variance ranged from 9% to 22% of the total. Variance among fruits from the same tree was the largest environmental component for EP and FSM. Broad-sense heritability (hB2) was 0.29 for FW, 0.52 for EP, 0.11 for FSM, 0.34 for SSC, and 0.65 for acidity in evaluations performed using single-year measurements of one tree with one fruit. Yearly repetition was more efficient than tree replication for increasing hB2 of all traits investigated. Increasing fruit number from one to five in combination with yearly repetition also increased hB2, especially for EP and FSM.

Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.

Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene-environment (G×E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametricG×Einteraction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more insights into age-specific heritability of BMI and evidence ofG×Einteractions. These findings highlight the fundamental importance and implication of the proposed models in facilitating twin studies to investigate the heritability specific to age and other modifying factors.

Dynamic Association Mapping based on a Kalman Filter Model using GAW 18 Data Set

Background Linear mixed model with pedigree information commonly employed to detect and correct for genetic relationship in cross sectional genomics research. Main aim of this study was to dynamic association mapping by using a random walk-Kalman filter approach for analyzing GAW18 dataset. We also extended the model to incorporate stationary process by auto regressive structure for dynamic gene and environmental effects. Methods We used random walk model and it is given below 22 1 , (0, ); , (0, ) t t t t e t t t t n y N NA α e e σ α α η η α σ + = + ∞ = + In (1) the first equation is called the observation equation and the second equation is called the state equation. We assumed that observations, t y , depends on unobservable quantity, t α , and our aim was to do statistical inference on t α (states) Results Error, genetic and permanent environmental variance components were predicted as 17.3 (0.0006), 10.9 (0.0007) and 8.2 (0.0006) using genomic relation matrix for and 18.0 (0.0007), 9.2 (0.0008) and 8.4(0.0006) using pedigree relation matrix for diastolic blood pressure. Rs 11711953 from time point 1, 2 and 3 is found to be associated with MAP4 gene. Conclusions Probably due to small number of time points the model did not detect all true genomic signals. Genomic relationship matrix gave better inflation factors. Random walk is a non stationary process and in this paper we extended the model for stationary case by tuning ∆ parameter. In genomic studies failing to taken into account of longitudinal gene and environmental effects over time may lead to either undetection of true signals and/ or may also lead to false positives due to stochastic errors.

Romantic Relationship Satisfaction Moderates the Etiology of Adult Personality.

The heritability of major normative domains of personality is well-established, with approximately half the proportion of variance attributed to genetic differences. In the current study, we examine the possibility of gene×environment interaction (G×E) for adult personality using the environmental context of intimate romantic relationship functioning. Personality and relationship satisfaction are significantly correlated phenotypically, but to date no research has examined how the genetic and environmental components of variance for personality differ as a function of romantic relationship satisfaction. Given the importance of personality for myriad outcomes from work productivity to psychopathology, it is vital to identify variables present in adulthood that may affect the etiology of personality. In the current study, quantitative models of G×E were used to determine whether the genetic and environmental influences on personality differ as a function of relationship satisfaction. We drew from a sample of now-adult twins followed longitudinally from adolescence through age 29. All participants completed the Multidimensional Personality Questionnaire (MPQ) and an abbreviated version of the Dyadic Adjustment Scale. Biometric moderation was found for eight of the eleven MPQ scales examined: well-being, social potency, negative emotionality, alienation, aggression, constraint, traditionalism, and absorption. The pattern of findings differed, suggesting that the ways in which relationship quality moderates the etiology of personality may depend on the personality trait.

Genetic and Environmental Variation in a Commercial Breeding Program of Perennial Ryegrass

ABSTRACTImplementation of genomic selection (GS) for the genetic improvement of forage crops, such as perennial ryegrass, requires the establishment of sufficiently large training populations with high‐quality phenotype and genotype data. This paper presents estimates of genetic and environmental variance and covariance components, obtained in a training population of 1453 F2 families. These families were produced in 2001, 2003, 2005, and 2007, and they were tested at seven locations throughout Europe. Families were cultivated together with commercial varieties that were used as control. Analyses focused on forage yield (green and dry matter) and six traits scored by visual inspection (i.e., rust resistance, aftermath heading, spring growth, density, winter hardiness, and heading date). Data were analyzed with linear mixed models, including fixed effects (trial and control varieties, within year and location), and random effects (breeding values, pedigree or parents, repeated effects of family or parents within location, and within trial environmental effects, to recover interblock information). Results showed very significant genetic variances for all traits, which provide good opportunities for future GS‐based breeding programs. Forage yield showed family heritabilities of up to 0.30 across locations and up to 0.60 within a location. Similar or moderately lower values were found for the other traits. In particular, the heritabilities of rust resistance and aftermath heading were very promising. Genetic correlations between traits were generally low but positive, which increases the potential for multitrait selection.

Genetic variation in cassava for postharvest physiological deterioration

Cassava storage roots start deteriorating 1 to 3 days after harvest due to postharvest physiological deterioration (PPD) which reduces the potential of cassava as a commercial crop. The objective of this study was to examine the extent of genetic variability in cassava for PPD. Genetic variability is important in selecting suitable genotypes for crop improvement. Twelve cassava genotypes were evaluated in a randomized complete block design at three different locations in Uganda for five different harvest times, and PPD assessment was done 7 days after each harvest time. Genotype, location, harvest time, genotype × harvest time and harvest time × location were highly significantly different for PPD. Estimates of phenotypic, genotypic and environmental variance components revealed that a large portion of the phenotypic variance was accounted for by the genotypic component which is an indication of substantial genetic variability among the test genotypes for PPD. This genetic variability is important in a breeding programme because it indicates that significant genetic gain through phenotypic selection is possible for PPD. The results give guidance to breeding efforts for improved shelf life of cassava storage roots.

Maternal Age-Related Depletion of Offspring Genetic Variance in Immune Response to Phytohaemagglutinin in the Blue Tit (Cyanistes caeruleus).

Studies examining age-specific patterns in genetic variance have focussed primarily on changes in the genetic variance within cohorts. It remains unclear whether parental age may affect the genetic variance among offspring. To date, such an effect has been reported only in a single study performed in a wild bird population. Here, we provide experimental evidence that the additive genetic variance (VA) observed among offspring may be related to parental age in a wild passerine—the blue tit (Cyanistes caeruleus). To separate genetic and environmental components of phenotypic variance in nestling body size and immune function we cross-fostered nestlings between pairs of broods born to young and old mothers and used an animal model to estimate VA. We show that the genetic variance in immune response to phytohaemagglutinin (PHA) and body weight among offspring depends on maternal age. VA in response to PHA appeared to be lower among nestlings of older mothers. Such a tendency was not observed for tarsus length. We argue that the lower VA may result either from depletion of additive genetic variation due to selection acting on parents across age classes or from environmental effects confounded with parental age. Thus, our study suggests that parental age may significantly affect estimates of quantitative genetic parameters in the offspring.

Genetic and environmental variances of bone microarchitecture and bone remodeling markers: a twin study.

All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p < 0.001). For the corresponding distal radius traits, genetic factors accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ = 0.49) than DZ (rDZ = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling markers more because of differences in their genetic factors than differences in their environment.

Genetic and environmental influences on fitness-related traits in an endangered shorebird population

Abstract Adaptation depends on the additive genetic variance for fitness and its component traits. Yet estimating additive genetic variance and heritability for wild populations is challenging because determining relatedness of individuals is difficult. We used 20 years (1994–2013) of phenotypic records from mark-recapture data and a multi-generational pedigree to estimate quantitative genetic variation in three fitness-related traits in Great Lakes piping plovers (Charadrius melodus), an endangered wild shorebird. Genetic and environmental components of variance as well as heritabilities were estimated using Bayesian inference for animal models. Phenotypic variation in age-corrected chick mass was composed of a significant additive genetic component (h2 = 0.27; 95% credible interval: 0.16–0.38), and hatch year, common maternal environment, and hatch site effects. Conversely, natal dispersal distance and female breeding time were not significantly heritable (h2 = 0.03; 95% CI: 0.0–0.11; h2 = 0.08, 95% CI: 0.0–0.22, respectively). Rather, environmental factors (e.g., breeding site) are the main sources of variation in these two traits. Variation in female breeding time was minimally influenced by her mate and was moderately repeatable. The low potential for natal dispersal and breeding time to evolve may limit the ability of this population to adapt to climate change long-term. However, trait alteration could occur by a phenotypically plastic response, allowing rapid adjustment to novel environmental conditions and short-term persistence. Depending on the relative contribution of genetic and environmental influences on the trait(s) of interest, results from quantitative genetic studies can also help identify management priorities for endangered populations.