Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants

Nagy, Réka; Boutin, Thibaud; Marten, Jonathan; Huffman, Jennifer E.; Kerr, Shona M.; Campbell, Archie; Evenden, Louise; Gibson, Jude; Amador, Carmen; Howard, David M.; Navarro, Pau; Morris, Andrew P.; Deary, Ian J.; Hocking, Lynne J.; Padmanabhan, Sandosh; Smith, Blair H.; Joshi, Peter K.; Wilson, James F.; Hastie, Nicholas D.; Wright, Alan F.; McIntosh, Andrew M.; Porteous, David J.; Haley, Chris; Vitart, Véronique; Hayward, Caroline

doi:10.1186/s13073-017-0414-4

Cited by 121 publications

(126 citation statements)

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“…Firstly, using a recently developed analytic design for combined pedigree and genome-wide molecular genetic data, we test whether rare genetic variants, CNVs, and structural variants make an additional contribution to the genetic variance in intelligence, neuroticism, and extraversion. Secondly, using unrelated individuals, and genotype data imputed using the Haplotype Reference Consortium [3,4] (HRC) data, we use minor allele frequency (MAF) stratified GREML (GREML-MS) to quantify the effect of SNPs with a MAF of ≥ 0.001 to determine if this additional variance can also be recovered based on SNPs alone using imputation.…”

Section: Introductionmentioning

confidence: 99%

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

et al. 2018

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Pedigree-based analyses of intelligence have reported that genetic differences account for 50-80% of the phenotypic variation. For personality traits these effects are smaller, with 34-48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using~20,000 individuals in the Generation Scotland family cohort genotyped for~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that 50% of differences in intelligence, and~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance.

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Section: Introductionmentioning

confidence: 99%

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

et al. 2018

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“…Association studies of affective disorder and related traits were performed in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS) [24][25][26] and UK Biobank (UKB) [27], fitting principal components and cohort/phenotypes appropriate covariates using subsets of unrelated individuals (see Supplementary methods: UK Population-based cohorts: GS:SFHS and UKB and region-wide association analyses).…”

Section: Methodsmentioning

confidence: 99%

DNA sequence-level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders

et al. 2018

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Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome-and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes.

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“…The individuals used in this study were a subset of Generation Scotland: the Scottish Family Health Study (GS), which has been described in detail elsewhere [25][26][27]29 . Briefly, GS comprises 23,690 individuals aged 18 years and over, recruited via general practitioners' throughout Scotland.…”

Section: Sample Descriptionmentioning

confidence: 99%

“…Genotyping is described in greater detail elsewhere 25 . Population outliers were identified and removed from the sample.…”

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confidence: 99%

“…In the present study, we aim to estimate the SNP and pedigree eritability of SLEs and also the contribution of couple, sibling and nuclear family effects on SLEs in a family-based cohort drawn from the population of Scotland, Generation Scotland: the Scottish Family Heath Study (GS) [25][26][27] . A subset of GS that were re-contacted as part of a mental health follow-up study, are used here for the current investigation 28 .…”

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Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

Clarke¹,

Zeng²,

Navrady³

et al. 2018

Wellcome Open Res

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Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is correlated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively correlated with lifetime MDD status (β=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=1.9%, p=1.04 x 10-37) at the phenotypic level. Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r2=0.3%, p=3 x 10-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (rG=0.33, S.E.=0.08 ) and neuroticism (rG=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

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Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants

Cited by 121 publications

References 50 publications

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

DNA sequence-level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders

Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

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