Evaluation of multiple displacement amplification in a 5 cM STR genome-wide scan

Multiple displacement amplification (MDA) has emerged as a promising new method of whole genome amplification (WGA) with the potential to generate virtually unlimited genome-equivalent DNA from only a small amount of seed DNA. To date, genome-wide high marker density assessments of MDA–DNA have focussed mainly upon suitability for single nucleotide polymorphism (SNP) genotyping applications. Suitability for short tandem repeat (STR) genotyping has not been investigated in great detail, despite their inherent instability during DNA replication, and the obvious challenge that this presents to WGA techniques. Here, we aimed to assess the applicability of MDA in STR genotyping by conducting a genome-wide scan of 768 STR markers for MDAs of 15 high quality genomic DNAs. We found that MDA genotyping call and accuracy rates were only marginally lower than for genomic DNA. Pooling of three replicate MDAs resulted in a small increase in both call rate and genotyping accuracy. We identified 34 STRs (4.4% of total markers) of which five essentially failed with MDA samples, and 29 of which showed elevated genotyping failures/discrepancies in the MDAs. We emphasise the importance of DNA and MDA quality checks, and the use of appropriate controls to identify problematic STR markers

ANKK1, TTC12, and NCAM1 polymorphisms and heroin dependence: importance of considering drug exposure

Context: The genetic contribution to liability for opioid dependence is well established; identification of the responsible genes has proved challenging. Objective: To examine association of 1430 candidate gene single-nucleotide polymorphisms (SNPs)with heroin dependence, reporting here only the 71 SNPs in the chromosome 11 gene cluster (NCAM1, TTC12, ANKK1, DRD2) that include the strongest observed associations. Design: Case-control genetic association study that included 2 control groups (lacking an established optimal control group). Setting: Semistructured psychiatric interviews. Participants: A total of 1459 Australian cases ascertained from opioid replacement therapy clinics, 531 neighborhood controls ascertained from economically disadvantaged areas near opioid replacement therapy clinics, and 1495 unrelated Australian Twin Registry controls not dependent on alcohol or illicit drugs selected from a twin and family sample. Main Outcome Measure: Lifetime heroin dependence. Results: Comparison of cases with Australian Twin Registry controls found minimal evidence of association for all chromosome 11 cluster SNPs (P≥.01); a similar comparison with neighborhood controls revealed greater differences (P≥1.8×10-4). Comparing cases (n=1459) with the subgroup of neighborhood controls not dependent on illicit drugs (n=340), 3 SNPs were significantly associated (correcting for multiple testing): ANKK1 SNP rs877138 (most strongly associated; odds ratio=1.59; 95% CI, 1.32-1.92; P=9.7×10-7), ANKK1 SNP rs4938013, and TTC12 SNP rs7130431. A similar pattern of association was observed when comparing illicit drug-dependent (n=191) and nondependent (n=340) neighborhood controls, suggesting that liability likely extends to nonopioid illicit drug dependence. Aggregate heroin dependence risk associated with 2 SNPs, rs877138 and rs4492854 (located in NCAM1), varied more than 4-fold (P=2.7×10-9 for the risk-associated linear trend). Conclusions: Our results provide further evidence of association for chromosome 11 gene cluster SNPs with substance dependence, including extension of liability to illicit drug dependence. Our findings highlight the necessity of considering drug exposure history when selecting control groups for genetic investigations of illicit drug dependence

Study protocol for the Australian autism biobank: an international resource to advance autism discovery research

BACKGROUND: The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) presents considerable challenges in understanding etiological pathways, selecting effective therapies, providing genetic counselling, and predicting clinical outcomes. With advances in genetic and biological research alongside rapid-pace technological innovations, there is an increasing imperative to access large, representative, and diverse cohorts to advance knowledge of ASD. To date, there has not been any single collective effort towards a similar resource in Australia, which has its own unique ethnic and cultural diversity. The Australian Autism Biobank was initiated by the Cooperative Research Centre for Living with Autism (Autism CRC) to establish a large-scale repository of biological samples and detailed clinical information about children diagnosed with ASD to facilitate future discovery research. METHODS: The primary group of participants were children with a confirmed diagnosis of ASD, aged between 2 and 17 years, recruited through four sites in Australia. No exclusion criteria regarding language level, cognitive ability, or comorbid conditions were applied to ensure a representative cohort was recruited. Both biological parents and siblings were invited to participate, along with children without a diagnosis of ASD, and children who had been queried for an ASD diagnosis but did not meet diagnostic criteria. All children completed cognitive assessments, with probands and parents completing additional assessments measuring ASD symptomatology. Parents completed questionnaires about their child's medical history and early development. Physical measurements and biological samples (blood, stool, urine, and hair) were collected from children, and physical measurements and blood samples were collected from parents. Samples were sent to a central processing site and placed into long-term storage. DISCUSSION: The establishment of this biobank is a valuable international resource incorporating detailed clinical and biological information that will help accelerate the pace of ASD discovery research. Recruitment into this study has also supported the feasibility of large-scale biological sample collection in children diagnosed with ASD with comprehensive phenotyping across a wide range of ages, intellectual abilities, and levels of adaptive functioning. This biological and clinical resource will be open to data access requests from national and international researchers to support future discovery research that will benefit the autistic community

The variance shared across forms of childhood trauma is strongly associated with liability for psychiatric and substance use disorders

Introduction: Forms of childhood trauma tend to co-occur and are associated with increased risk for psychiatric and substance use disorders. Commonly used binary measures of trauma exposure have substantial limitations. Methods: We performed multigroup confirmatory factor analysis (CFA), separately by sex, using data from the Childhood Trauma (CT) Study's sample of twins and siblings (N = 2594) to derive three first-order factors (childhood physical abuse, childhood sexual abuse, and parental partner abuse) and, as hypothesized, one higher order, childhood trauma factor (CTF) representing a measure of their common variance. Results: CFA produced a good-fitting model in the CT Study; we replicated the model in the Comorbidity and Trauma (CAT) Study's sample (N = 1981) of opioid-dependent cases and controls. In both samples, first-order factors are moderately correlated (indicating they measure largely unique, but related constructs) and their loadings on the CTF suggest it provides a reasonable measure of their common variance. We examined the association of CTF score with risk for psychiatric and substance use disorders in these samples and the OZ-ALC GWAS sample (N = 1538) in which CT Study factor loadings were applied. We found that CTF scores are strongly associated with liability for psychiatric and substance use disorders in all three samples; estimates of risk are extremely consistent across samples. Conclusions: The CTF is a continuous, robust measure that captures the common variance across forms of childhood trauma and provides a means to estimate shared liability while avoiding multicollinearity. Confirmatory factor analysis was used to derive a higher order, childhood trauma factor representing a measure of the common variance across three forms of trauma: childhood physical abuse, childhood sexual abuse, and parental partner abuse. We replicated the model in a second sample. We then examined the association of childhood trauma score with risk for psychiatric and substance use disorders in these samples and a third sample in which the primary sample's factor loadings were applied finding factor scores to be strongly and consistently associated with liability for psychiatric and substance use disorders in all three samples

Hypermethylation in the ZBTB20 gene is associated with major depressive disorder.

This is the final version of the article. Available from BioMed Central via the DOI in this record.BACKGROUND: Although genetic variation is believed to contribute to an individual's susceptibility to major depressive disorder, genome-wide association studies have not yet identified associations that could explain the full etiology of the disease. Epigenetics is increasingly believed to play a major role in the development of common clinical phenotypes, including major depressive disorder. RESULTS: Genome-wide MeDIP-Sequencing was carried out on a total of 50 monozygotic twin pairs from the UK and Australia that are discordant for depression. We show that major depressive disorder is associated with significant hypermethylation within the coding region of ZBTB20, and is replicated in an independent cohort of 356 unrelated case-control individuals. The twins with major depressive disorder also show increased global variation in methylation in comparison with their unaffected co-twins. ZBTB20 plays an essential role in the specification of the Cornu Ammonis-1 field identity in the developing hippocampus, a region previously implicated in the development of major depressive disorder. CONCLUSIONS: Our results suggest that aberrant methylation profiles affecting the hippocampus are associated with major depressive disorder and show the potential of the epigenetic twin model in neuro-psychiatric disease.The study was funded by the Wellcome Trust; European Community’s Seventh Framework Programme (FP7/2007-2013). The study also receives support from the National Institute for Health Research (NIHR) Clinical Research Facility at Guy’s & St Thomas’ Davies et al. Genome Biology 2014, 15:R56 Page 9 of 12 http://genomebiology.com/2014/15/4/R56 NHS Foundation Trust and NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. Matthew Davies is supported by the EU FP7 grant EuroBATS (No. 259749). Tim Spector is an NIHR senior Investigator and is holder of an ERC Advanced Principal Investigator award. Further funding support for this project was obtained from the European Research Council (project number 250157). The members of the UK Brain Expression Consortium (UKBEC) are: (1) Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK: John A Hardy, Mina Ryten, and Daniah Trabzuni; (2) Department of Medical and Molecular Genetics, King's College London, UK: Michael E Weale, Adaikalavan Ramasamy and Paola Forabosco; (3) Department of Pathology, The University of Edinburgh, Wilkie Building, Teviot Place, Edinburgh, UK: Colin Smith and Robert Walker. Australia: funding for phenotype and blood collection was from NHMRC grants to Nick Martin and NIH grants to Andrew Heath and Pamela Madden. We thank David Smyth for database management, Lisa Bowdler for sample preparation, and the twins for their cooperation

Genome-wide Meta-analysis Finds the ACSL5-ZDHHC6 Locus Is Associated with ALS and Links Weight Loss to the Disease Genetics

We meta-analyze amyotrophic lateral sclerosis (ALS) genome-wide association study (GWAS) data of European and Chinese populations (84,694 individuals). We find an additional significant association between rs58854276 spanning ACSL5-ZDHHC6 with ALS (p = 8.3 × 10−9), with replication in an independent Australian cohort (1,502 individuals; p = 0.037). Moreover, B4GALNT1, G2E3-SCFD1, and TRIP11-ATXN3 are identified using a gene-based analysis. ACSL5 has been associated with rapid weight loss, as has another ALS-associated gene, GPX3. Weight loss is frequent in ALS patients and is associated with shorter survival. We investigate the effect of the ACSL5 and GPX3 single-nucleotide polymorphisms (SNPs), using longitudinal body composition and weight data of 77 patients and 77 controls. In patients’ fat-free mass, although not significant, we observe an effect in the expected direction (rs58854276: −2.1 ± 1.3 kg/A allele, p = 0.053; rs3828599: −1.0 ± 1.3 kg/A allele, p = 0.22). No effect was observed in controls. Our findings support the increasing interest in lipid metabolism in ALS and link the disease genetics to weight loss in patients

Genome-Wide Association Reveals Pigmentation Genes Play a Role in Skin Aging

Loss of fine skin patterning is a sign of both aging and photoaging. Studies investigating the genetic contribution to skin patterning offer an opportunity to better understand a trait that influences both physical appearance and risk of keratinocyte skin cancer. We undertook a meta-analysis of genome-wide association studies (GWAS) of a measure of skin pattern (microtopography score) damage in 1,671 twin pairs and 1,745 singletons (N = 5,087) drawn from three independent cohorts. We identified that rs185146 near SLC45A2 is associated with a skin aging trait (p = 4.1 × 10-9); to our knowledge this is previously unreported. We also confirm previously identified loci, rs12203592 near IRF4 (p = 8.8 × 10-13), and rs4268748 near MC1R (p = 1.2 × 10-15). At all three loci we highlight putative functionally relevant SNPs. There are a number of red hair/low pigmentation alleles of MC1R; we found that together these MC1R alleles explained 4.1% of variance in skin pattern damage. We also show that skin aging and reported experience of sunburns was proportional to the degree of penetrance for red hair of alleles of MC1R. Our work has uncovered genetic contributions to skin aging and confirmed previous findings, showing that pigmentation is a critical determinate of skin aging

Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank.

BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism.MethodsGenome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain.ResultsThe ASD (p = 6.1e-13), sibling (p = 4.9e-3) and unrelated (p = 3.0e-3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height-a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e-3) and parents (r = 0.17, p = 8.0e-7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e-3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants.LimitationsThis dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered.ConclusionsWe report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair)