Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Comparison of fractional and geodesic anisotropy in diffusion tensor images of 90 monozygotic and dizygotic twins

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Genetic architecture of subcortical brain regions: Common and region-specific genetic contributions

Understanding the aetiology of patterns of variation within and covariation across brain regions is key to advancing our understanding of the functional, anatomical and developmental networks of the brain. Here we applied multivariate twin modelling and principal component analysis (PCA) to investigate the genetic architecture of the size of seven subcortical regions (caudate nucleus, thalamus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens) in a genetically informative sample of adolescents and young adults (N=1038; mean age=21.6±3.2years; including 148 monozygotic and 202 dizygotic twin pairs) from the Queensland Twin IMaging (QTIM) study. Our multivariate twin modelling identified a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In addition, we also found substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52). This provides further insight into the extent and organization of subcortical genetic architecture, which includes developmental and general growth pathways, as well as the functional specialization and maturation trajectories that influence each subcortical region. This multivariate twin study identifies a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In parallel, it also describes substantial region-specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52).

Cognitive functioning in older twins: The Older Australian Twins Study

Aim: To examine the concordance rates of common medical conditions and neurocognitive performance in monozygotic (MZ) and dizygotic (DZ) older twins. Methods: Twins aged ≥65 years and living in the three Eastern states of Australia were recruited through the Australian Twin Registry and underwent detailed neuropsychological and medical assessment. Results: Assessments were conducted on 113 MZ and 96 DZ twin pairs, with a mean age of 70.5 years. MZ twins were more concordant than DZ twins for hypertension and asthma. MZ twins had higher correlations than DZ twins on most neuropsychological tests, with the exception of some tests related to processing speed. The concordance rate for mild cognitive impairment or dementia was 76.2% in MZ twins and 42.9% in DZ twins, a non-significant difference. Conclusions: Except for some aspects of processing speed, most cognitive functions in older individuals show significant heritability. The heritability of neurocognitive disorders is, however, low.

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N1198) using genome-wide search

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis

Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10-6). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority. © 2013 Lin et al.

The interleukin 1 gene cluster contains a major susceptibility locus for ankylosing spondylitis

Ankylosing spondylitis (AS) is a common and highly heritable inflammatory arthropathy. Although the gene HLA-B27 is almost essential for the inheritance of the condition, it alone is not sufficient to explain the pattern of familial recurrence of the disease. We have previously demonstrated suggestive linkage of AS to chromosome 2q13, a region containing the interleukin 1 (IL-1) family gene cluster, which includes several strong candidates for involvement in the disease. In the current study, we describe strong association and transmission of IL-1 family gene cluster single-nucleotide polymorphisms and haplotypes with AS.

Identification of major loci controlling clinical manifestations of ankylosing spondylitis

Objective. To identify genomic regions linked with determinants of age at symptom onset, disease activity, and functional impairment in ankylosing spondylitis (AS). Methods. A whole genome linkage scan was performed in 188 affected sibling pair families with 454 affected individuals. Traits assessed were age at symptom onset, disease activity assessed by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and functional impairment assessed by the Bath Ankylosing Spondylitis Functional Index (BASFI). Parametric and nonparametric quantitative linkage analysis was performed using parameters defined in a previous segregation study. Results. Heritabilities of the traits studied in this data set were as follows: BASDAI 0.49 (P = 0.0001, 95% confidence interval [95% CI] 0.23-0.75), BASFI 0.76 (P = 10-7, 95% CI 0.49-1.0), and age at symptom onset 0.33 (P = 0.005, 95% CI 0.04-0.62). No linkage was observed between the major histocompatibility complex (MHC) and any of the traits studied (logarithm of odds [LOD] score <1.0). "Significant" linkage (LOD score 4.0) was observed between a region on chromosome 18p and the BASDAI. Age at symptom onset showed "suggestive" linkage to chromosome 11p (LOD score 3.3). Maximum linkage with the BASFI was seen at chromosome 2q (LOD score 2.9). Conclusion. In contrast to the genetic determinants of susceptibility to AS, clinical manifestations of the disease measured by the BASDAI, BASFI, and age at symptom onset are largely determined by a small number of genes not encoded within the MHC.

Is disease severity in ankylosing spondylitis genetically determined?

Objective. To assess the role of genes and the environment in determining the severity of ankylosing spondylitis. Methods: One hundred seventy-three families with >1 case of ankylosing spondylitis were recruited (120 affected sibling pairs, 26 affected parent-child pairs, 20 families with both first- and second-degree relatives affected, and 7 families with only second-degree relatives affected), comprising a total of 384 affected individuals. Disease severity was assessed by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and functional impairment was determined using the Bath Ankylosing Spondylitis Functional Index (BASFI). Disease duration and age at onset were also studied. Variance-components modeling was used to determine the genetic and environmental components Contributing to familiality of the traits examined, and complex segregation analysis was performed to assess different disease models. Results. Both the disease activity and functional capacity as assessed by the BASDAI and the BASFI, respectively, were found to be highly familial (BASDAI familiality 0.51 [P = 10-4], BASFI familiality 0,68 [P = 3 × 10-7]). No significant shared environmental component was demonstrated to be associated with either the BASDAI or the BASFI. Including age at disease onset and duration of disease as covariates made no difference in the heritability assessments. A strong correlation was noted between the BASDAI and the BASFI (genetic correlation 0.9), suggesting the presence of shared determinants of these 2 measures. However, there was significant residual heritability for each measure independent of the other (BASFI residual heritability 0.48, BASDAI 0,36), perhaps indicating that not all genes influencing disease activity influence chronicity. No significant heritability of age at disease onset was found (heritability 0.18; P = 0.2). Segregation studies suggested the presence of a single major gene influencing the BASDAI and the BASFI. Conclusion. This study demonstrates a major genetic contribution to disease severity in ankylosing spondylitis. As with susceptibility to ankylosing spondylitis, shared environmental factors play little role in determining the disease severity.

Promise and pitfalls of the Immunochip

Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Immunochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for immunogenetics gene mapping.

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.

Suggestive linkage of 2p22-25 and 11q12-13 with low bone mineral density at the lumbar spine in the Irish population

Osteoporosis is a disease characterized by low bone mineral density (BMD) and poor bone quality. Peak bone density is achieved by the third decade of life, after which bone is maintained by a balanced cycle of bone resorption and synthesis. Age-related bone loss occurs as the bone resorption phase outweighs the bone synthesis phase of bone metabolism. Heritability accounts for up to 90% of the variability in BMD. Chromosomal loci including 1p36, 2p22-25, 11q12-13, parathyroid hormone receptor type 1 (PTHR1), interleukin-6 (IL-6), interleukin 1 alpha (IL-1α) and type II collagen A1/vitamin D receptor (COL11A1/VDR) have been linked or shown suggestive linkage with BMD in other populations. To determine whether these loci predispose to low BMD in the Irish population, we investigated 24 microsatellite markers at 7 chromosomal loci by linkage studies in 175 Irish families of probands with primary low BMD (T-score ≤ -1.5). Nonparametric analysis was performed using the maximum likelihood variance estimation and traditional Haseman-Elston tests on the Mapmaker/Sibs program. Suggestive evidence of linkage was observed with lumbar spine BMD at 2p22-25 (maximum LOD score 2.76) and 11q12-13 (MLS 2.55). One region, 1p36, approached suggestive linkage with femoral neck BMD (MLS 2.17). In addition, seven markers achieved LOD scores > 1.0, D2S149, D11S1313, D11S987, D11S1314 including those encompassing the PTHR1 (D3S3559, D3S1289) for lumbar spine BMD and D2S149 for femoral neck BMD. Our data suggest that genes within a these chromosomal regions are contributing to a predisposition to low BMD in the Irish population.

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.

Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm

Background Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim To identify genetic variants associated with forearm BMD and forearm fractures. Methods BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (p<5×10-8) in meta-analysis (lead SNP, rs11951031[T] -0.20 SDs per allele, p=9.01×10-9). The gene-based association test suggested an association between MEF2C and forearm BMD ( p=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: OR=1.14 (95% CI 0.92 to 1.35), p=0.14). Meta-analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2. Conclusions These findings demonstrate that variants at MEF2C were associated with forearm BMD, implicating this gene in the determination of BMD at forearm.