Generation Scotland: Donor DNA Databank; A control DNA resource

<p>Abstract</p> <p>Background</p> <p>Many medical disorders of public health importance are complex diseases caused by multiple genetic, environmental and lifestyle factors. Recent technological advances have made it possible to analyse the genetic variants that predispose to complex diseases. Reliable detection of these variants requires genome-wide association studies in sufficiently large numbers of cases and controls. This approach is often hampered by difficulties in collecting appropriate control samples. The Generation Scotland: Donor DNA Databank (GS:3D) aims to help solve this problem by providing a resource of control DNA and plasma samples accessible for research.</p> <p>Methods</p> <p>GS:3D participants were recruited from volunteer blood donors attending Scottish National Blood Transfusion Service (SNBTS) clinics across Scotland. All participants gave full written consent for GS:3D to take spare blood from their normal donation. Participants also supplied demographic data by completing a short questionnaire.</p> <p>Results</p> <p>Over five thousand complete sets of samples, data and consent forms were collected. DNA and plasma were extracted and stored. The data and samples were unlinked from their original SNBTS identifier number. The plasma, DNA and demographic data are available for research. New data obtained from analysis of the resource will be fed back to GS:3D and will be made available to other researchers as appropriate.</p> <p>Conclusions</p> <p>Recruitment of blood donors is an efficient and cost-effective way of collecting thousands of control samples. Because the collection is large, subsets of controls can be selected, based on age range, gender, and ethnic or geographic origin. The GS:3D resource should reduce time and expense for investigators who would otherwise have had to recruit their own controls.</p

Molecular genetic contributions to self-rated health

Poorer self-rated health (SRH) predicts worse health outcomes, even when adjusted for objective measures of disease at time of rating. Twin studies indicate SRH has a heritability of up to 60% and that its genetic architecture may overlap with that of personality and cognition.We carried out a genome-wide association study (GWAS) of SRH on 111 749 members of the UK Biobank sample. Univariate genome-wide complex trait analysis (GCTA)-GREML analyses were used to estimate the proportion of variance explained by all common autosomal single nucleotide polymorphisms (SNPs) for SRH. Linkage disequilibrium (LD) score regression and polygenic risk scoring, two complementary methods, were used to investigate pleiotropy between SRH in the UK Biobank and up to 21 health-related and personality and cognitive traits from published GWAS consortia.The GWAS identified 13 independent signals associated with SRH, including several in regions previously associated with diseases or disease-related traits. The strongest signal was on chromosome 2 (rs2360675, P = 1.77 x 10 -10 ) close to KLF7 . A second strong peak was identified on chromosome 6 in the major histocompatibility region (rs76380179, P = 6.15 x 10 -10 ). The proportion of variance in SRH that was explained by all common genetic variants was 13%. Polygenic scores for the following traits and disorders were associated with SRH: cognitive ability, education, neuroticism, body mass index (BMI), longevity, attention-deficit hyperactivity disorder (ADHD), major depressive disorder, schizophrenia, lung function, blood pressure, coronary artery disease, large vessel disease stroke and type 2 diabetes.Individual differences in how people respond to a single item on SRH are partly explained by their genetic propensity to many common psychiatric and physical disorders and psychological traits

Genetic contributions to stability and change in intelligence from childhood to old age

Understanding the determinants of healthy mental ageing is a priority for society today1,2. So far, we know that intelligence differences show high stability from childhood to old age3,4 and there are estimates of the genetic contribution to intelligence at different ages5,6. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative7–10. Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years)11,12. We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals13–17. We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change

Meta-analysis of genome-wide association studies for extraversion:Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

Inheritance of DNA methylation level in healthy human tissues

DNA methylation (DNAm) is the covalent modification of DNA by addition of a methyl group primarily at the cytosine directly upstream of a guanine. DNAm level plays a central role in transcriptional regulation and is linked to disease. Therefore, understanding genetic and environmental influences on DNAm level in healthy tissue is an important step in the elucidation of trait and disease etiology. However, at present only a minority of easy to access human tissues and ethnicities have been investigated. Therefore, we studied DNAm level measured in five human tissues: cerebellum, frontal cortex, pons, temporal cortex and colon in either North American or South American samples. We applied a novel statistical approach to estimate the heritability attributable to genomic regions (regional heritability, ĥ²/r,g ) for DNAm level at thousands of individual DNAm sites genome-wide. In all five tissues, DNAm level was significantly associated with the local genomic region for more DNAm sites than expected by chance. Moreover, DNAm level could be predicted from the local sequence variants with an accuracy that scaled with the estimated ĥ²/r,g . Our results inform on molecular mechanisms regulating DNAm level and trait etiology in several ways. Firstly, DNAm level at DNAm sites located in genomic risk regions and measured in a tissue relevant to the disease can be influenced by the local genetic variants. Specifically, we found that genetic variation within a region associated with Fluid Intelligence was also associated with local DNAm level at the proline-rich coiled-coil 1 (PRRC1) gene in healthy temporal cortex tissue. Additionally, we replicated the finding of a Colorectal Cancer risk variant (rs4925386) associated with two DNAm sites in healthy colon tissue. More generally, we showed that DNAm sites located within a susceptibility region and measured in a relevant tissue exhibit a similar overall pattern of estimated ĥ²/r,g to DNAm sites outwith a susceptibility region. Secondly, the propensity for DNAm level to be associated with the local sequence variation differs with respect to CpG dinucleotide density and genic location. Most notably, DNAm sites located in CpG dense regions of the genome are less likely to be heritable than DNAm sites located in CpG sparse regions of the genome. Additionally, within both CpG dense and CpG sparse regions of the genome intergenic DNAm sites are more likely to be heritable than intragenic DNAm sites. Overall, our study suggests that variation in DNAm level at some DNAm sites is at least partially controlled by nuclear genetic variation. Moreover, DNAm level in healthy tissue has the potential to act as an intermediary in trait variation and etiology

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

Evolutionary conserved longevity genes and human cognitive abilities in elderly cohorts

Genetic influences have an important role in the ageing process. The genetic factors that influence success in bodily ageing may also contribute to the successful ageing of cognitive abilities. A comparative genomics approach found longevity genes conserved between yeast Saccharomyces cerevisiae and nematode Caenorhabditis elegans. We hypothesised that these longevity genes influence variance in cognitive ability and age-related cognitive decline in humans. Here, we investigated six of these genes that have human orthologs and show expression in the brain. We tested AFG3L2 (MIM: 604581, AFG3 ATPase family gene 3-like 2 (yeast)), FRAP1 (MIM: 601231, a FK506 binding protein 12-rapamycin associated protein), MAT1A, MAT2A (MIM: 610550 and 601468, methionine adenosyltransferases I alpha and II alpha, respectively), SYNJ1 and SYNJ2 (MIM: 604297 and 609410, synaptojanin-1 and synaptojanin-2, respectively) in approximately 1000 healthy older Scots: the Lothian Birth Cohort 1936 (LBC1936). They were tested on general cognitive ability at age 11 years. At a mean age of 70 years, they re-sat the same general cognitive ability test and underwent an additional battery of diverse cognitive tests. In all, 70 tag and functional SNPs in the six longevity genes were genotyped and tested for association with cognition and cognitive ageing in LBC1936. Suggestive associations were detected between SNPs in SYNJ2, MAT1A, AFG3L2 and SYNJ1 and a general memory factor and general cognitive ability at age 11 and 70 years. Replication studies for cognitive ability associations were performed in 2506 samples from the Cognitive Ageing Genetics in England and Scotland consortium. A meta-analysis replicated the SYNJ2 association with cognitive abilities (lowest P=0.00077). SYNJ2 is a novel gene in which variation is potentially associated with cognitive abilities

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases