A web application to perform linkage disequilibrium and linkage analyses on a computational grid

Motivation: Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits. Methods: Linkage disequilibrium and linkage analysis (LDLA) is a high-resolution gene mapping approach based on sophisticated mixed linear models, applicable to any population structure. LDLA can use population history information in addition to pedigree and molecular markers to decompose traits into genetic components. Analyses are distributed in parallel over a large public grid of computers in the UK. Results: We have proven the performance of LDLA with analyses of simulated data. There are real gains in statistical power to detect quantitative trait loci when using historical information compared with traditional linkage analysis. Moreover, the use of a grid of computers significantly increases computational speed, hence allowing analyses that would have been prohibitive on a single computer. © The Author 2009. Published by Oxford University Press. All rights reserved.

Inferring kangaroo phylogeny from incongruent nuclear and mitochondrial genes

The marsupial genus Macropus includes three subgenera, the familiar large grazing kangaroos and wallaroos of M. (Macropus) and M. (Osphranter), as well as the smaller mixed grazing/browsing wallabies of M. (Notamacropus). A recent study of five concatenated nuclear genes recommended subsuming the predominantly browsing Wallabia bicolor (swamp wallaby) into Macropus. To further examine this proposal we sequenced partial mitochondrial genomes for kangaroos and wallabies. These sequences strongly favour the morphological placement of W. bicolor as sister to Macropus, although place M. irma (black-gloved wallaby) within M. (Osphranter) rather than as expected, with M. (Notamacropus). Species tree estimation from separately analysed mitochondrial and nuclear genes favours retaining Macropus and Wallabia as separate genera. A simulation study finds that incomplete lineage sorting among nuclear genes is a plausible explanation for incongruence with the mitochondrial placement of W. bicolor, while mitochondrial introgression from a wallaroo into M. irma is the deepest such event identified in marsupials. Similar such coalescent simulations for interpreting gene tree conflicts will increase in both relevance and statistical power as species-level phylogenetics enters the genomic age. Ecological considerations in turn, hint at a role for selection in accelerating the fixation of introgressed or incompletely sorted loci. More generally the inclusion of the mitochondrial sequences substantially enhanced phylogenetic resolution. However, we caution that the evolutionary dynamics that enhance mitochondria as speciation indicators in the presence of incomplete lineage sorting may also render them especially susceptible to introgression.

Phenotypical characterisation of the isolated Norfolk Island population focusing on epidemiological indicators of cardiovascular disease

Objectives Only 193 people from Pitcairn Island, all descended from 9 ‘Bounty’ mutineers and 12 Tahitian women, moved to the uninhabited Norfolk Island in 1856. Our objective was to assess the population of Norfolk Island, several thousand km off the eastern coast of Australia, as a genetic isolate of potential use for cardiovascular disease (CVD) gene mapping. Methods A total of 602 participants, approximately two thirds of the island’s present adult population, were characterized for a panel of CVD risk factors. Statistical power and heritability were calculated. Results Norfolk Islander’s possess an increased prevalence of hypertension, obesity and multiple CVD risk factors when compared to outbred Caucasian populations. 64% of the study participants were descendents of the island’s original founder population. Triglycerides, cholesterol, and blood pressures all had heritabilities above 0.2. Conclusions The Norfolk land population is a potentially useful genetic isolate for gene mapping studies aimed at identifying CVD risk factor quantitative trait loci (QTL).

Estimating local stream fish assemblage attributes: Sampling effort and efficiency at two spatial scales

As part of a wider study to develop an ecosystem-health monitoring program for wadeable streams of south-eastern Queensland, Australia, comparisons were made regarding the accuracy, precision and relative efficiency of single-pass backpack electrofishing and multiple-pass electrofishing plus supplementary seine netting to quantify fish assemblage attributes at two spatial scales (within discrete mesohabitat units and within stream reaches consisting of multiple mesohabitat units). The results demonstrate that multiple-pass electrofishing plus seine netting provide more accurate and precise estimates of fish species richness, assemblage composition and species relative abundances in comparison to single-pass electrofishing alone, and that intensive sampling of three mesohabitat units (equivalent to a riffle-run-pool sequence) is a more efficient sampling strategy to estimate reach-scale assemblage attributes than less intensive sampling over larger spatial scales. This intensive sampling protocol was sufficiently sensitive that relatively small differences in assemblage attributes (<20%) could be detected with a high statistical power (1-β > 0.95) and that relatively few stream reaches (<4) need be sampled to accurately estimate assemblage attributes close to the true population means. The merits and potential drawbacks of the intensive sampling strategy are discussed, and it is deemed to be suitable for a range of monitoring and bioassessment objectives.

Progress towards understanding the genetics of posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a complex syndrome that occurs following exposure to a potentially life threatening traumatic event. This review summarises the literature on the genetics of PTSD including gene–environment interactions (GxE), epigenetics and genetics of treatment response. Numerous genes have been shown to be associated with PTSD using candidate gene approaches. Genome-wide association studies have been limited due to the large sample size required to reach statistical power. Studies have shown that GxE interactions are important for PTSD susceptibility. Epigenetics plays an important role in PTSD susceptibility and some of the most promising studies show stress and child abuse trigger epigenetic changes. Much of the molecular genetics of PTSD remains to be elucidated. However, it is clear that identifying genetic markers and environmental triggers has the potential to advance early PTSD diagnosis and therapeutic interventions and ultimately ease the personal and financial burden of this debilitating disorder.

Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study

Working memory-related brain activation has been widely studied, and impaired activation patterns have been reported for several psychiatric disorders. We investigated whether variation in N-back working memory brain activation is genetically influenced in 60 pairs of twins, (29 monozygotic (MZ), 31 dizygotic (DZ); mean age 24.4 ± 1.7S.D.). Task-related brain response (BOLD percent signal difference of 2 minus 0-back) was measured in three regions of interest. Although statistical power was low due to the small sample size, for middle frontal gyrus, angular gyrus, and supramarginal gyrus, the MZ correlations were, in general, approximately twice those of the DZ pairs, with non-significant heritability estimates (14-30%) in the low-moderate range. Task performance was strongly influenced by genes (57-73%) and highly correlated with cognitive ability (0.44-0.55). This study, which will be expanded over the next 3 years, provides the first support that individual variation in working memory-related brain activation is to some extent influenced by genes.

Heritability of working memory brain activation

Although key to understanding individual variation in task-related brain activation, the genetic contribution to these individual differences remains largely unknown. Here we report voxel-by-voxel genetic model fitting in a large sample of 319 healthy, young adult, human identical and fraternal twins (mean ± SD age, 23.6 ±1.8 years) who performed an n-back working memory task during functional magnetic resonance imaging (fMRI) at a high magnetic field (4 tesla). Patterns of task-related brain response (BOLD signal difference of 2-back minus 0-back) were significantly heritable, with the highest estimates (40 - 65%) in the inferior, middle, and superior frontal gyri, left supplementary motor area, precentral and postcentral gyri, middle cingulate cortex, superior medial gyrus, angular gyrus, superior parietal lobule, including precuneus, and superior occipital gyri. Furthermore, high test-retest reliability for a subsample of 40 twins indicates that nongenetic variance in the fMRI brain response is largely due to unique environmental influences rather than measurement error. Individual variations in activation of the working memory network are therefore significantly influenced by genetic factors. By establishing the heritability of cognitive brain function in a large sample that affords good statistical power, and using voxel-by-voxel analyses, this study provides the necessary evidence for task-related brain activation to be considered as an endophenotype for psychiatric or neurological disorders, and represents a substantial new contribution to the field of neuroimaging genetics. These genetic brain maps should facilitate discovery of gene variants influencing cognitive brain function through genome-wide association studies, potentially opening up new avenues in the treatment of brain disorders.

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.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.

Polymorphism in codon 17 of the CTLA-4 gene (+49 A/G) is not associated with susceptibility to rheumatoid arthritis in British Caucasians

The role of the CTLA-4 antigen in the development of autoimmune diseases is well documented, with several autoimmune disorders showing association or linkage with the CTLA-4 locus. Its role in the aetiology of rheumatoid arthritis (RA) however, remains unclear, as the functional studies of the B7-CTLA-4 pathway in mouse models of RA and genetic studies in humans have given contrasting results. We have studied the single nucleotide polymorphism at position +49 (A/G) of the CTLA-4 gene, in a cohort of 421 RA cases and 452 healthy controls from the UK. Despite the high statistical power to detect even a weak susceptibility effect, no significant association was found. We also analysed the distribution of the allele and genotype frequencies with respect to the presence of the shared epitope (a known RA susceptibility factor) and found no statistically significant differences. We conclude that, although the importance of the B7-CTLA-4 interaction in the development of RA can not be excluded, the CTLA-4 gene is unlikely to be a predisposing factor to this disease.

A mega-analysis of genome-wide association studies for major depressive disorder

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 x 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 x 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Association mapping

Association mapping seeks to identify marker alleles present at significantly different frequencies in cases carrying a particular disease or trait compared with controls. Genome-wide association studies are increasingly replacing candidate gene-based association studies for complex diseases, where a number of loci are likely to contribute to disease risk and the effect size of each particular risk allele is typically modest or low. Good study design is essential to the success of an association study, and factors such as the heritability of the disease under investigation, the choice of controls, statistical power, multiple testing and whether the association can be replicated need to be considered before beginning. Likewise, thorough quality control of the genotype data needs to be undertaken prior to running any association analyses. Finally, it should be kept in mind that a significant genetic association is not proof positive that a particular genetic locus causes a disease, but rather an important first step in discovering the genetic variants underlying a complex disease.

Search for genetic variants influencing human height

Human growth and attained height are determined by a combination of genetic and environmental effects and in modern Western societies > 80% of the observed variation in height is determined by genetic factors. Height is a fundamental human trait that is associated with many socioeconomic and psychosocial factors and health measures, however little is known of the identity of the specific genes that influence height variation in the general population. This thesis work aimed to identify the genetic variants that influence height in the general population by genome-wide linkage analysis utilizing large family samples. The study focused on analysis of three separate sets of families consisting of: 1) 1,417 individuals from 277 Finnish families (FinnHeight), 2) 8,450 individuals from 3,817 families from Australia and Europe (EUHeight) and 3) 9,306 individuals from 3,302 families from the United States (USHeight). The most significant finding in this study was found in the Finnish family sample where we a locus in the chromosomal region 1p21 was linked to adult height. Several regions showed evidence for linkage in the Australian, European and US families with 8q21 and 15q25 being the most significant. The region on 1p21 was followed up with further studies and we were able to show that the collagen 11-alpha-1 gene (COL11A1) residing at this location was associated with adult height. This association was also confirmed in an independent Finnish population cohort (Health 2000) consisting of 6,542 individuals. From this population sample, we estimated that homozygous males and females for this gene variant were 1.1 and 0.6 cm taller than the respective controls. In this thesis work we identified a gene variant in the COL11A1 gene that influences human height, although this variant alone explains only 0.1% of height variation in the Finnish population. We also demonstrated in this study that special stratification strategies such as performing sex-limited analyses, focusing on dizygous twin pairs, analyzing ethnic groups within a population separately and utilizing homogenous populations such as the Finns can improve the statistical power of finding QTL significantly. Also, we concluded from the results of this study that even though genetic effects explain a great proportion of height variance, it is likely that there are tens or even hundreds of genes with small individual effects underlying the genetic architecture of height.

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.