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.

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.

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.

Non-major-histocompatibility-complex genetics of ankylosing spondylitis

There is strong evidence from twin and family studies indicating that a substantial proportion of the heritability of susceptibility to ankylosing spondylitis (AS) and its clinical manifestations is encoded by non-major-histocompatibility-complex genes. Efforts to identify these genes have included genomewide linkage studies and candidate gene association studies. One region, the interleukin (IL)-1 gene complex on chromosome 2, has been repeatedly associated with AS in both Caucasians and Asians. It is likely that more than one gene in this complex is involved in AS, with the strongest evidence to date implicating IL-1A. Identifying the genes underlying other linkage regions has been difficult due to the lack of obvious candidates and the low power of most studies to date to identify genes of the small to moderate magnitude that are likely to be involved. The field is moving towards genomewide association analysis, involving much larger datasets of unrelated cases and controls. Early successes using this approach in other diseases indicates that it is likely to identify genes in common diseases like AS, but there remains the risk that the common-variant, common-disease hypothesis will not hold true in AS. Nonetheless, it is appropriate for the field to be cautiously optimistic that the next few years will bring great advances in our understanding of the genetics of this condition.

Genetic susceptibility to ankylosing spondylitis

Ankylosing spondylitis is a highly heritable, common rheumatic condition, primarily affecting the axial skeleton. The association with HLA-B27 has been demonstrated worldwide, and evidence for a role of HLA-B27 in disease comes from linkage and association studies in humans, and transgenic animal models. However, twin studies indicate that HLA-B27 contributes only 16% of the total genetic risk for disease. Furthermore, there is compelling evidence that non-B27 genes, both within and outwith the major histocompatability complex, are involved in disease aetiology. In this post-genomic era we have the tools to help elicit the genetic basis of disease. This review describes methods for genetic investigation of ankylosing spondylitis, and summarises the status of current research in this exciting area.

Genetic aspects of susceptibility, severity, and clinical expression in ankylosing spondylitis

While twin studies have previously demonstrated high heritability of susceptibility to ankylosing spondylitis (AS), it is only recently that the involvement of genetic factors in determining the severity of the disease has been demonstrated. The genes involved in determining the rate of ankylosis in AS are likely to be different from those involved in the underlying immunologic events, and represent important potential targets for treatment of AS. This article will describe the progress that has been made in the genetic epidemiology of AS, and in identifying the genes involved.

A genome-wide association study of sleep habits and insomnia

Several aspects of sleep behavior such as timing, duration and quality have been demonstrated to be heritable. To identify common variants that influence sleep traits in the population, we conducted a genome-wide association study of six sleep phenotypes assessed by questionnaire in a sample of 2,323 individuals from the Australian Twin Registry. Genotyping was performed on the Illumina 317, 370, and 610K arrays and the SNPs in common between platforms were used to impute non-genotyped SNPs. We tested for association with more than 2,000,000 common polymorphisms across the genome. While no SNPs reached the genome-wide significance threshold, we identified a number of associations in plausible candidate genes. Most notably, a group of SNPs in the third intron of the CACNA1C gene ranked as most significant in the analysis of sleep latency (P = 1.3 x 10(-)(6)). We attempted to replicate this association in an independent sample from the Chronogen Consortium (n = 2,034), but found no evidence of association (P = 0.73). We have identified several other suggestive associations that await replication in an independent sample. We did not replicate the results from previous genome-wide analyses of self-reported sleep phenotypes after correction for multiple testing.

Genome-wide linkage and association analyses implicate FASN in predisposition to Uterine Leiomyomata

Uterine leiomyomata (UL), the most prevalent pelvic tumors in women of reproductive age, pose a major public health problem given their high frequency, associated morbidities, and most common indication for hysterectomies. A genetic component to UL predisposition is supported by analyses of ethnic predisposition, twin studies, and familial aggregation. A genome-wide SNP linkage panel was genotyped and analyzed in 261 white UL-affected sister-pair families from the Finding Genes for Fibroids study. Two significant linkage regions were detected in 10p11 (LOD = 4.15) and 3p21 (LOD = 3.73), and five additional linkage regions were identified with LOD scores > 2.00 in 2q37, 5p13, 11p15, 12q14, and 17q25. Genome-wide association studies were performed in two independent cohorts of white women, and a meta-analysis was conducted. One SNP (rs4247357) was identified with a p value (p = 3.05 x 10(-8)) that reached genome-wide significance (odds ratio = 1.299). The candidate SNP is under a linkage peak and in a block of linkage disequilibrium in 17q25.3, which spans fatty acid synthase (FASN), coiled-coil-domain-containing 57 (CCDC57), and solute-carrier family 16, member 3 (SLC16A3). By tissue microarray immunohistochemistry, we found elevated (3-fold) FAS levels in UL-affected tissue compared to matched myometrial tissue. FAS transcripts and/or protein levels are upregulated in various neoplasms and implicated in tumor cell survival. FASN represents the initial UL risk allele identified in white women by a genome-wide, unbiased approach and opens a path to management and potential therapeutic intervention.

A variant in LIN28B is associated with 2D:4D finger-length ratio, a putative retrospective biomarker of prenatal testosterone exposure

The ratio of the lengths of an individual's second to fourth digit (2D:4D) is commonly used as a noninvasive retrospective biomarker for prenatal androgen exposure. In order to identify the genetic determinants of 2D:4D, we applied a genome-wide association approach to 1507 11-year-old children from the Avon Longitudinal Study of Parents and Children (ALSPAC) in whom 2D:4D ratio had been measured, as well as a sample of 1382 12- to 16-year-olds from the Brisbane Adolescent Twin Study. A meta-analysis of the two scans identified a single variant in the LIN28B gene that was strongly associated with 2D:4D (rs314277: p = 4.1 x 10(-8)) and was subsequently independently replicated in an additional 3659 children from the ALSPAC cohort (p = 1.53 x 10(-6)). The minor allele of the rs314277 variant has previously been linked to increased height and delayed age at menarche, but in our study it was associated with increased 2D:4D in the direction opposite to that of previous reports on the correlation between 2D:4D and age at menarche. Our findings call into question the validity of 2D:4D as a simplistic retrospective biomarker for prenatal testosterone exposure.

Variants in EMX2 and PTEN do not contribute to risk of endometriosis

Endometriosis has a genetic component, and significant linkage has been found to a region on chromosome 10q. Two candidate genes, EMX2 and PTEN, implicated in both endometriosis and endometrial cancer, lie on chromosome 10q. We hypothesized that variation in EMX2 and/or PTEN could contribute to the risk of endometriosis and may account for some of the linkage signal on 10q. We genotyped single nucleotide polymorphisms (SNPs) in a case-control design to evaluate association between endometriosis and common variations in these two genes. The genotyping and statistical analysis were based on samples collected from Australian volunteers. The cases were 768 unrelated women with surgically confirmed endometriosis selected from affected sister pair (ASP) families participating in the Australian Genes behind Endometriosis Study. The controls were 768 female participants in twin studies who, based on screening questions, did not have a diagnosis of endometriosis. Genotypes of 22 SNPs in the EMX2 gene and 15 SNPs in the PTEN gene were the main outcome measures. Statistical analysis provided measures of linkage disequilibrium and association. Permutation testing showed no globally significant association between any SNPs or haplotypes and endometriosis for either gene. It is unlikely that the EMX2 or PTEN gene variants investigated contribute to risk for initiation and/or development of endometriosis.

Genomewide significant linkage to migrainous headache on chromosome 5q21

Familial typical migraine is a common, complex disorder that shows strong familial aggregation. Using latent-class analysis (LCA), we identified subgroups of people with migraine/severe headache in a community sample of 12,245 Australian twins (60% female), drawn from two cohorts of individuals aged 23-90 years who completed an interview based on International Headache Society criteria. We report results from genomewide linkage analyses involving 756 twin families containing a total of 790 independent sib pairs (130 affected concordant, 324 discordant, and 336 unaffected concordant for LCA-derived migraine). Quantitative-trait linkage analysis produced evidence of significant linkage on chromosome 5q21 and suggestive linkage on chromosomes 8, 10, and 13. In addition, we replicated previously reported typical-migraine susceptibility loci on chromosomes 6p12.2-p21.1 and 1q21-q23, the latter being within 3 cM of the rare autosomal dominant familial hemiplegic migraine gene (ATP1A2), a finding which potentially implicates ATP1A2 in familial typical migraine for the first time. Linkage analyses of individual migraine symptoms for our six most interesting chromosomes provide tantalizing hints of the phenotypic and genetic complexity of migraine. Specifically, the chromosome 1 locus is most associated with phonophobia; the chromosome 5 peak is predominantly associated with pulsating headache; the chromosome 6 locus is associated with activity-prohibiting headache and photophobia; the chromosome 8 locus is associated with nausea/vomiting and moderate/severe headache; the chromosome 10 peak is most associated with phonophobia and photophobia; and the chromosome 13 peak is completely due to association with photophobia. These results will prove to be invaluable in the design and analysis of future linkage and linkage disequilibrium studies of migraine.