Large autosomal copy-number differences within unselected monozygotic twin pairs are rare

Monozygotic (MZ) twins form an important system for the study of biological plasticity in humans. While MZ twins are generally considered to be genetically identical, a number of studies have emerged that have demonstrated copy-number differences within a twin pair, particularly in those discordant for disease. The rate of autosomal copy-number variation (CNV) discordance within MZ twin pairs was investigated using a population sample of 376 twin pairs genotyped on Illumina Human610-Quad arrays. After CNV calling using both QuantiSNP and PennCNV followed by manual annotation, only a single CNV difference was observed within the MZ twin pairs, being a 130 KB duplication of chromosome 5. Five other potential discordant CNV were called by the software, but excluded based on manual annotation of the regions. It is concluded that large CNV discordance is rare within MZ twin pairs, indicating that any CNV difference found within phenotypically discordant MZ twin pairs has a high probability of containing the causal gene(s) involved

Effects of GABRA2 variation on physiological, psychomotor and subjective responses in the Alcohol Challenge Twin Study

Multiple reports have identified variation in the GABRA2 gene as contributing to the genetic susceptibility to alcohol dependence. However, both the mechanism behind this association, and the range of alcohol-related phenotypes affected by variation in this gene, are currently undefined. Other data suggest that the risk of alcohol dependence is increased by relative insensitivity to alcohol's intoxicating effects. We have therefore tested whether GABRA2 variation is associated with variation in the subjective and objective effects of a standard dose of alcohol in humans. Data on responses to alcohol from the Alcohol Challenge Twin Study (Martin et al., 1985) have been tested against allelic and haplotype information obtained by typing 41 single-nucleotide polymorphisms in or close to the GABRA2 gene. Nominally significant allelic associations (p < .05, without correction for multiple testing) were found for body sway, motor coordination, pursuit rotor and arithmetical computation tasks, and for the personality dimension of Neuroticism. Because of the large number of phenotypes tested, these possibly significant findings will need to be confirmed in further studies

Highly cost-efficient genome-wide association studies using DNA pools and dense SNP arrays

Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the same DNA pools and showed that the HumanHap300 arrays are substantially more efficient. In terms of effective sample size, HumanHap300-based pooling extracts >80% of the information available with individual genotyping (IG). In contrast, Genechip HindIII-based pooling only extracts ∼30% of the available information. With HumanHap300 arrays concordance with IG data is excellent. Guidance is given on best study design and it is shown that even after taking into account pooling error, one stage scans can be performed for >100-fold reduced cost compared with IG. With appropriately designed two stage studies, IG can provide confirmation of pooling results whilst still providing ∼20-fold reduction in total cost compared with IG-based alternatives. The large cost savings with Illumina HumanHap300-based pooling imply that future studies need only be limited by the availability of samples and not cost

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

The association of genetic predisposition to depressive symptoms with non-suicidal and suicidal self-Injuries

Non-suicidal and suicidal self-injury are very destructive, yet surprisingly common behaviours. Depressed mood is a major risk factor for non-suicidal self-injury (NSSI), suicidal ideation and suicide attempts. We conducted a genetic risk prediction study to examine the polygenic overlap of depressive symptoms with lifetime NSSI, suicidal ideation, and suicide attempts in a sample of 6237 Australian adult twins and their family members (3740 females, mean age\ua0=\ua042.4\ua0years). Polygenic risk scores for depressive symptoms significantly predicted suicidal ideation, and some predictive ability was found for suicide attempts; the polygenic risk scores explained a significant amount of variance in suicidal ideation (lowest p\ua0=\ua00.008, explained variance ranging from 0.10 to 0.16\ua0%) and, less consistently, in suicide attempts (lowest p\ua0=\ua00.04, explained variance ranging from 0.12 to 0.23\ua0%). Polygenic risk scores did not significantly predict NSSI. Results highlight that individuals genetically predisposed to depression are also more likely to experience suicidal ideation/behaviour, whereas we found no evidence that this is also the case for NSSI

Estimation of the Rate of SNP Genotyping Errors From DNA Extracted From Different Tissues

High density single nucleotide polymorphism (SNP) genotyping panels provide an alternative to microsatellite markers for genome scans. However, genotype errors have a major impact on power to detect linkage or association and are difficult to detect for SNPs. We estimated error rates with the Affymetrix GeneChip® SNP platform in samples from a family with a mixed set of monozygotic (MZ) and dizygotic (DZ) triplets using lymphocyte, buccal DNA and samples from whole genome amplification using the multiple displacement amplification (MDA) technique. The average call rate from 58,960 SNPs for five genomic samples was 99.48%. Comparison of results for the MZ twins showed only three discordant genotypes (concordance rate 99.995%). The mean concordance rate for comparisons of samples from lymphocyte and buccal DNA was 99.97%. Mendelian inconsistencies were identified in 46 SNPs with errors in one or more family members, a rate of 0.022%. Observed genotype concordance rates between parents, between parents and children, and among siblings were consistent with previously reported allele frequencies and Hardy-Weinberg equilibrium. Using the MDA technique, results for two samples had equivalent high accuracy to results with genomic samples. However, the SNP call rate for the remaining seven samples varied from 72.5% to 99.5%, with an average of 86.11%. Quality of the DNA sample following the MDA reaction appears to be the critical factor in SNP call rate for MDA samples. Our results demonstrate highly accurate and reproducible genotyping for the Affymetrix GeneChip® Human Mapping Set in lymphocyte and buccal DNA samples.</p

Testing the role of circadian genes in conferring risk for psychiatric disorders

Disturbed sleep and disrupted circadian rhythms are a common feature of psychiatric disorders, and many groups have postulated an association between genetic variants in circadian clock genes and psychiatric disorders. Using summary data from the association analyses of the Psychiatric Genomics Consortia (PGC) for schizophrenia, bipolar disorder and major depressive disorder, we evaluated the evidence that common SNPs in genes encoding components of the molecular clock influence risk to psychiatric disorders. Initially, gene-based and SNP P-values were analyzed for 21 core circadian genes. Subsequently, an expanded list of genes linked to control of circadian rhythms was analyzed. After correcting for multiple comparisons, none of the circadian genes were significantly associated with any of the three disorders. Several genes previously implicated in the etiology of psychiatric disorders harbored no SNPs significant at the nominal level of

A genome-wide association study of self-rated health

Self-rated health questions have been proven to be a highly reliable and valid measure of overall health as measured by other indicators in many population groups. It also has been shown to be a very good predictor of mortality, chronic or severe diseases, and the need for services, and is positively correlated with clinical assessments. Genetic factors have been estimated to account for 25-64% of the variance in the liability of self-rated health. The aim of the present study was to identify Single Nucleotide Polymorphisms (SNPs) underlying the heritability of self-rated health by conducting a genome-wide association analysis in a large sample of 6,706 Australian individuals aged 18-92. No genome wide significant SNPs associated with self-rated health could be identified, indicating that self-rated health may be influenced by a large number of SNPs with very small effect size. A very large sample will be needed to identify these SNPs