Correction: Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation.

[This corrects the article DOI: 10.1371/journal.pgen.1005804.].

Genome-wide association study of copy number variation with lung function identifies a novel signal of association near BANP for forced vital capacity.

BACKGROUND: Genome-wide association studies of Single Nucleotide Polymorphisms (SNPs) have identified 55 SNPs associated with lung function. However, little is known about the effect of copy number variants (CNVs) on lung function, although CNVs represent a significant proportion of human genetic polymorphism. To assess the effect of CNVs on lung function quantitative traits, we measured copy number at 2788 previously characterised, common copy number variable regions in 6 independent cohorts (n = 24,237) using intensity data from SNP genotyping experiments. We developed a pipeline for genome-wide association analysis and meta-analysis of CNV genotypes measured across multiple studies using SNP genotype array intensity data from different platform technologies. We then undertook cohort-level genome-wide association studies of CNV with lung function in a subset of 4 cohorts (n < =12,403) with lung function measurements and meta-analysed the results. Follow-up was undertaken for CNVs which were well tagged by SNPs, in up to 146,871 individuals. RESULTS: We generated robust copy number calls for 1962 out of 2788 (70 %) known CNV regions genome-wide, with 1103 measured with compatible class frequencies in at least 2 cohorts. We report a novel CNV association (discovery P = 0.0007) with Forced Vital Capacity (FVC) downstream of BANP on chromosome 16 that shows evidence of replication by a tag SNP in two independent studies (replication P = 0.004). In addition, we provide suggestive evidence (discovery P = 0.0002) for a role of complex copy number variation at a previously reported lung function locus, containing the rootletin gene CROCC, that is not tagged by SNPs. CONCLUSIONS: We demonstrate how common CNV regions can be reliably and consistently called across cohorts, using an existing calling algorithm and rigorous quality control steps, using SNP genotyping array intensity data. Although many common biallelic CNV regions were well-tagged by common SNPs, we also identified associations with untagged mulitallelic CNV regions thereby illustrating the potential of our approach to identify some of the missing heritability of complex traits.

Exome sequencing to detect rare variants associated with general cognitive ability: a pilot study.

Variation in human cognitive ability is of consequence to a large number of health and social outcomes and is substantially heritable. Genetic linkage, genome-wide association, and copy number variant studies have investigated the contribution of genetic variation to individual differences in normal cognitive ability, but little research has considered the role of rare genetic variants. Exome sequencing studies have already met with success in discovering novel trait-gene associations for other complex traits. Here, we use exome sequencing to investigate the effects of rare variants on general cognitive ability. Unrelated Scottish individuals were selected for high scores on a general component of intelligence (g). The frequency of rare genetic variants (in n = 146) was compared with those from Scottish controls (total n = 486) who scored in the lower to middle range of the g distribution or on a proxy measure of g. Biological pathway analysis highlighted enrichment of the mitochondrial inner membrane component and apical part of cell gene ontology terms. Global burden analysis showed a greater total number of rare variants carried by high g cases versus controls, which is inconsistent with a mutation load hypothesis whereby mutations negatively affect g. The general finding of greater non-synonymous (vs. synonymous) variant effects is in line with evolutionary hypotheses for g. Given that this first sequencing study of high g was small, promising results were found, suggesting that the study of rare variants in larger samples would be worthwhile.

Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing: a population-based study.

BACKGROUND: Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia. METHODS: We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls. RESULTS: Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls. CONCLUSIONS: We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis.

Chronic pain in families: a cross-sectional study of shared social, behavioural, and environmental influences.

Chronic pain is common and creates a significant burden to the individual and society. Emerging research has shown the influence of the family environment on pain outcomes. However, it is not clear what shared factors between family members associate with chronic pain. This study aimed to investigate the family-level contribution to an individual's chronic pain status. This was a cross-sectional study using the Generation Scotland: Scottish Family Health Study data set. This study focused on a nested cohort of dyads (only 2 relatives per family, n = 2714). Multi-level modelling was first performed to estimate the extent of variance in chronic pain at the family level. Then each member of the dyad was randomly assigned as either the exposure or outcome family member, and logistic regression was used to identify shared factors associated with the outcome of chronic pain status. Multi-level modelling showed just under 10% of variation in chronic pain status was at a family level. There was an increase in odds of chronic pain if exposure family member had chronic pain (odds ratio [OR]: 1.30, 95% confidence interval [CI]: 1.02-1.65), if both were women (OR: 1.39, 95% CI: 0.99-1.94), if both were older in age (OR: 1.80, 95% CI: 1.31-2.48), and if both had low household income (OR: 3.27, 95% CI: 1.72-6.21). These findings show that most explanation for chronic pain is still at the individual level. However, some significant shared effects between family members associate with chronic pain, and this highlights the influence of the family context.

Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

Differential effects of the APOE e4 allele on different domains of cognitive ability across the life-course.

The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population; hence, meta-analyses have been based on many small, heterogeneous studies. Here, we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18 337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.