The genetics of coronary heart disease: The contribution of twin studies

Despite the decline in coronary heart disease in many European countries, the disease remains an enormous public health problem. Although we know a great deal about environmental risk factors for coronary heart disease, a heritable component was recognized a long time ago. The earliest and best known examples of how our genetic constitution may determine cardiovascular risk relate to lipoprotein(a), familial hypercholesterolaemia and apolipoprotein E. In the past 20 years a fair number of polymorphisms assessed singly have shown strong associations with the disease but most are subject to poor repeatability. Twins constitute a compelling natural experiment to establish the genetic contribution to coronary heart disease and its risk factors. GenomEUtwin, a recently funded Framework 5 Programme of the European Community, affords the opportunity of comparing the heritability of risk factors in different European Twin Registries. As an illustration we present the heritabilities of systolic and diastolic blood pressure, based on data from over 4000 twin pairs from six different European countries and Australia. Heritabilities for systolic blood pressure are between 52 and 66% and for diastolic blood pressure between 44 and 66%. There is no evidence of sex differences in heritability estimates and very little to no evidence for a significant contribution of shared family environment. A non-twin based prospective case/cohort study of coronary heart disease and stroke (MORGAM) will allow hypotheses relating to cardiovascular disease, generated in the twin cohorts, to be tested prospectively in adult populations. Twin studies have also contributed to our understanding of the life course hypothesis, and GenomEUtwin has the potential to add to this.

Effects of early-life environment and epigenetics on cardiovascular disease risk in children: highlighting the role of twin studies

Cardiovascular disease (CVD) is the leading cause of death worldwide and originates in early life. The exact mechanisms of this early-life origin are unclear, but a likely mediator at the molecular level is epigenetic dysregulation of gene expression. Epigenetic factors have thus been posited as the likely drivers of early-life programming of adult-onset diseases. This review summarizes recent advances in epidemiology and epigenetic research of CVD risk in children, with a particular focus on twin studies. Classic twin studies enable partitioning of phenotypic variance within a population into additive genetic, shared, and nonshared environmental variances, and are invaluable in research in this area. Longitudinal cohort twin studies, in particular, may provide important insights into the role of epigenetics in the pathogenesis of CVD. We describe candidate gene and epigenome-wide association studies (EWASs) and transgenerational epigenetic inheritance of CVD, and discuss the potential for evidence-based interventions. Identifying epigenetic changes associated with CVD-risk biomarkers in children will provide new opportunities to unravel the underlying biological mechanism of the origins of CVD and enable identification of those at risk for early-life interventions to alter the risk trajectory and potentially reduce CVD incidence later in life.

The relationship between obesity, low back pain, and lumbar disc degeneration when genetics and the environment are considered: a systematic review of twin studies

BACKGROUND CONTEXT: The relationships between obesity and low back pain (LBP) and lumbar disc degeneration (LDD) remain unclear. It is possible that familial factors, including genetics and early environment, affect these relationships.PURPOSE: To investigate the relationship between obesity-related measures (eg, weight, body mass index [BMI]) and LBP and LDD using twin studies, where the effect of genetics and early environment can be controlled.STUDY DESIGN: A systematic review with meta-analysis.METHODS: MEDLINE, CINAHL, Scopus, Web of Science, and EMBASE databases were searched from the earliest records to August 2014. All cross-sectional and longitudinal observational twin studies identified by the search strategy were considered for inclusion. Two investigators independently assessed the eligibility, conducted the quality assessment, and extracted the data. Metaanalyses (fixed or random effects, as appropriate) were used to pool studies'estimates of association.RESULTS: In total, 11 articles met the inclusion criteria. Five studies were included in the LBP analysis and seven in the LDD analysis. For the LBP analysis, pooling of the five studies showed that the risk of having LBP for individuals with the highest levels of BMI or weight was almost twice that of people with a lower BMI (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.6-2.0; I-2 = 0%). A dose-response relationship was also identified. When genetics and the effects of a shared early environment were adjusted for using a within-pair twin case-control analysis, pooling of three studies showed a reduced but statistically positive association between obesity and prevalence of LBP (OR 1.5; 95% CI 1.1-2.1; I-2 = 0%). However, the association was further diminished and not significant (OR 1.4; 95% CI 0.8-2.3; I-2 = 0%) when pooling included two studies on monozygotic twin pairs only. Seven studies met the inclusion criteria for LDD. When familial factors were not controlled for, body weight was positively associated with LDD in all five cross-sectional studies. Only two cross-sectional studies investigated the relationship between obesity-related measures and LDD accounting for familial factors, and the results were conflicting. One longitudinal study in LBP and three longitudinal studies in LDD found no increase in risk in obese individuals, whether or not familial factors were controlled for.CONCLUSIONS: Findings from this review suggest that genetics and early environment are possible mechanisms underlying the relationship between obesity and LBP; however, a direct causal link between these conditions appears to be weak. Further longitudinal studies using the twin design are needed to better understand the complex mechanisms underlying the associations between obesity, LBP, and LDD.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Reduced variance in monozygous twins for multiple MR parameters : implications for disease studies and the genetic basis of brain structure

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

Candidate gene studies on cardiovascular traits

Cardiovascular diseases (CVD) are a major cause of death and disability in Western countries and a growing health problem in the developing world. The genetic component of both coronary heart disease (CHD) and ischemic stroke events has been established in twin studies, and the traits predisposing to CVD, such as hypertension, dyslipidemias, obesity, diabetes, and smoking behavior, are all partly hereditary. Better understanding of the pathophysiology of CVD-related traits could help to target disease prevention and clinical treatment to individuals at an especially high disease risk and provide novel pharmaceutical interventions. This thesis aimed to clarify the genetic background of CVD at a population level using large Nordic population cohorts and a candidate gene approach. The first study concentrated on the allelic diversity of the thrombomodulin (THBD) gene in two Finnish cohorts, FINRISK-92 and FINRISK-97. The results from this study implied that THBD variants do not substantially contribute to CVD risk. In the second study, three other candidate genes were added to the analyses. The study investigated the epistatic effects of coagulation factor V (F5), intercellular adhesion molecule -1 (ICAM1), protein C (PROC), and THBD in the same FINRISK cohorts. The results were encouraging; we were able to identify several single SNPs and SNP combinations associating with CVD and mortality. Interestingly, THBD variants appeared in the associating SNP combinations despite the negative results from Study I, suggesting that THBD contributes to CVD through gene-gene interactions. In the third study, upstream transcription factor -1 (USF1) was analyzed in a cohort of Swedish men. USF1 was associated with metabolic syndrome, characterized by accumulation of different CVD risk factors. A putative protective and a putative risk variant were identified. A direct association with CVD was not observed. The longitudinal nature of the study also clarified the effect of USF1 variants on CVD risk factors followed in four examinations throughout adulthood. The three studies provided valuable information on the study of complex traits, highlighting the use of large study samples, the importance of replication, and the full coverage of the major allelic variants of the target genes to assure reliable findings. Although the genetic basis of coronary heart disease and ischemic stroke remains unknown, single genetic findings may facilitate the recognition of high-risk subgroups.

Genetic influences on handedness: data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

The effect of known cardiovascular risk factors on carotid-femoral pulse wave velocity in school-aged children: a population based twin study

Childhood cardiovascular risk factors affect vascular function long before overt cardiovascular disease. Twin studies provide a unique opportunity to examine the influence of shared genetic and environmental influences on childhood cardiovascular function. We examined the relationship between birth parameters, markers of adiposity, insulin resistance, lipid profile and blood pressure and carotid-femoral pulse wave velocity (PWV), a validated non-invasive measure of arterial stiffness in a healthy cohort of school-aged twin children. PWV was performed on a population-based birth cohort of 147 twin pairs aged 7-11 years. Fasting blood samples, blood pressure and adiposity measures were collected concurrently. Mixed linear regression models were used to account for twin clustering, within- and between-twin pair associations. There were positive associations between both markers of higher adiposity, insulin resistance, elevated triglycerides and PWV, which remained significant after accounting for twin birth-set clustering. There was a positive association between both diastolic and mean arterial blood pressure and PWV in within-pair analysis in dizygotic, but not monozygotic twins, indicating genetic differences evident in dizygotic not monozygotic twins may affect these associations. Increased blood pressure, triglycerides and other metabolic markers are associated with increased PWV in school-aged twins. These results support both the genetic and environmental contribution to higher PWV, as a marker of arterial stiffness, and reiterate the importance of preventing metabolic syndrome from childhood.

A possible smoking susceptibility locus on chromosome 11p12: Evidence from sex-limitation linkage analyses in a sample of Australian twin families

Many twin studies have identified sex differences in the influence of genetic and environmental factors on smoking behaviors. We explore the evidence for sex differences for smoking initiation and cigarette consumption in a sample of Australian twin families, and extend these models to incorporate sex differences in linkage analyses for these traits. We further examine the impact of including or excluding non-smokers in genetic analyses of tobacco consumption. Accounting for sex differences improved linkage results in some instances. We identified one region suggestive of linkage on chromosome 11p12. This locus, as well as another region identified on chromosome 6p12, replicates regions identified in previous studies.

Empirical Evaluation of the Genetic Similarity of Samples From Twin Registries in Australia and the Netherlands Using 359 STRP Markers

One way to achieve the large sample sizes required for genetic studies of complex traits is to combine samples collected by different groups. It is not often clear, however, whether this practice is reasonable from a genetic perspective. To assess the comparability of samples from the Australian and the Netherlands twin studies, we estimated F,, (the proportion of total genetic variability attributable to genetic differences between cohorts) based on 359 short tandem repeat polymorphisms in 1068 individuals. IF,, was estimated to be 0.30% between the Australian and the Netherlands cohorts, a smaller value than between many European groups. We conclude that it is reasonable to combine the Australian and the Netherlands samples for joint genetic analyses.

Linkage mapping of CVD risk traits in the isolated Norfolk Island population

To understand the underlying genetic architecture of cardiovascular disease (CVD) risk traits, we undertook a genome-wide linkage scan to identify CVD quantitative trait loci (QTLs) in 377 individuals from the Norfolk Island population. The central aim of this research focused on the utilization of a genetically and geographically isolated population of individuals from Norfolk Island for the purposes of variance component linkage analysis to identify QTLs involved in CVD risk traits. Substantial evidence supports the involvement of traits such as systolic and diastolic blood pressures, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, body mass index and triglycerides as important risk factors for CVD pathogenesis. In addition to the environmental inXuences of poor diet, reduced physical activity, increasing age, cigarette smoking and alcohol consumption, many studies have illustrated a strong involvement of genetic components in the CVD phenotype through family and twin studies. We undertook a genome scan using 400 markers spaced approximately 10 cM in 600 individuals from Norfolk Island. Genotype data was analyzed using the variance components methods of SOLAR. Our results gave a peak LOD score of 2.01 localizing to chromosome 1p36 for systolic blood pressure and replicated previously implicated loci for other CVD relevant QTLs.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Neuroimaging and genetics: Exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.