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Wang M, Huang S. The collective effects of genetic variants and complex traits. J Hum Genet 2022; 68:255-262. [PMID: 36513763 DOI: 10.1038/s10038-022-01105-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022]
Abstract
Traditional approaches in studying the genetics of complex traits have focused on identifying specific genetic variants. However, the collective effects of variants have remained largely unexplored. Here, we evaluated whether traits could be influenced by the collective effects of variants across the entire protein coding-region of the genome or the entire genome. We studied the UK Biobank exome sequencing data of 167,246 individuals as well as the genome-wide SNP array data of 408,868 individuals. We calculated for each individual four different measures of genetic variation such as heterozygosity and number of variants and two different measures of the overall deleteriousness of all variants, and performed correlations with 17 representative traits that have been studied previously. Linear regression analysis was performed with adjustment for age, sex, and genetic principal components. The results showed a high correlation among the six different measures and an inverse association of two well-correlated traits (educational attainment and height) with the total number of all variants as well as the overall deleteriousness of all variants. We have also categorized the genes based on whether they are expressed in the brain and found that the association with educational attainment only held for the brain-expressed genes. No other traits examined showed a significant correlation with the brain-expressed genes. The study demonstrates that common traits could be studied by analyzing the overall genetic variation and suggests that educational attainment is inversely related to genetic variation.
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Affiliation(s)
- Mingrui Wang
- Center for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, 110 Xiangya Road, Changsha, Hunan, 410078, PR China
| | - Shi Huang
- Center for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, 110 Xiangya Road, Changsha, Hunan, 410078, PR China.
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Variation Screening of Zygote Arrest 1(ZAR1) in Women with Recurrent Zygote Arrest During IVF/ICSI Programs. Reprod Sci 2020; 27:2265-2270. [PMID: 32700283 DOI: 10.1007/s43032-020-00246-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 02/12/2020] [Accepted: 06/30/2020] [Indexed: 01/26/2023]
Abstract
Human zygote arrest during in vitro culture is rare and the etiology is unclear. The oocyte-specific gene Zar1 plays an essential role in oocyte-embryo transition, and most embryos from Zar1 knockout female mice arrest at the one-cell stage. This study investigates whether maternal ZAR1 gene variations play a role in human zygote arrest. Sequence analysis of ZAR1 was conducted for 47 women with recurrent uncleaved zygotes in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycles (≥ 70% zygotes uncleaved in at least 2 cycles), 93 women from IVF/ICSI cycles with normal uncleaved rate and live birth (control subset I) and 188 women with spontaneous pregnancy and live birth (control subset II). One novel synonymous variation (c.516C>T) and one novel intron variation (c.964-55A>T) of ZAR1 were identified in the zygote arrest group but not in any of the 188 controls. However, the bioinformatics analysis revealed that neither of the mutations in ZAR1 has effect on ZAR1 protein function. Compared with control subset I, the allele frequencies of rare SNPs rs117545505 and rs17609740 were significantly different in patients with zygote arrest (P = 0.047, OR = 3.66). Allele frequencies of these two SNPs were also significantly different between the case group and control subset II (P = 0.024, OR = 3.28). In conclusion, two SNPs in ZAR1 are associated with human zygote arrest, although additional proof is needed for validation.
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Hill WD, Arslan RC, Xia C, Luciano M, Amador C, Navarro P, Hayward C, Nagy R, Porteous DJ, McIntosh AM, Deary IJ, Haley CS, Penke L. Genomic analysis of family data reveals additional genetic effects on intelligence and personality. Mol Psychiatry 2018; 23:2347-2362. [PMID: 29321673 PMCID: PMC6294741 DOI: 10.1038/s41380-017-0005-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 11/08/2017] [Accepted: 11/21/2017] [Indexed: 12/17/2022]
Abstract
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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Affiliation(s)
- W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
| | - Ruben C Arslan
- Georg Elias Müller Institute of Psychology, Georg August University Göttingen, Göttingen, Germany
- Leibniz Science Campus, Primate Cognition, Göttingen, Germany
- Center for Adaptive Rationality Max Planck Institute for Human Development Lentzeallee, 94, 14195, Berlin, Germany
| | - Charley Xia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Reka Nagy
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, UK
| | - Lars Penke
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Georg Elias Müller Institute of Psychology, Georg August University Göttingen, Göttingen, Germany
- Leibniz Science Campus, Primate Cognition, Göttingen, Germany
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Teng S, Thomson PA, McCarthy S, Kramer M, Muller S, Lihm J, Morris S, Soares DC, Hennah W, Harris S, Camargo LM, Malkov V, McIntosh AM, Millar JK, Blackwood DH, Evans KL, Deary IJ, Porteous DJ, McCombie WR. Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia. Mol Psychiatry 2018; 23:1270-1277. [PMID: 28630456 PMCID: PMC5984079 DOI: 10.1038/mp.2017.115] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 03/20/2017] [Accepted: 03/27/2017] [Indexed: 12/20/2022]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacross P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacross P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.
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Affiliation(s)
- S Teng
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Biology, Howard University, Washington DC, USA
| | - P A Thomson
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - S McCarthy
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - M Kramer
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S Muller
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - J Lihm
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - S Morris
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - D C Soares
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - W Hennah
- Institute for Molecular Medicine, Finland FIMM, University of Helsinki, Helsinki, Finland
| | - S Harris
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - L M Camargo
- UCB New Medicines, One Broadway, Cambridge, MA, USA
| | - V Malkov
- Genetics and Pharmacogenomics, MRL, Merck & Co, Boston, MA, USA
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - J K Millar
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - D H Blackwood
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - K L Evans
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Genomic and Experimental Medicine, MRC/University of Edinburgh Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - W R McCombie
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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Abstract
In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.
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Affiliation(s)
- J Corley
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - S R Cox
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - I J Deary
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
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Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions. Transl Psychiatry 2016; 6:e980. [PMID: 27959336 PMCID: PMC5290340 DOI: 10.1038/tp.2016.246] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2016] [Revised: 10/04/2016] [Accepted: 10/17/2016] [Indexed: 12/25/2022] Open
Abstract
Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.
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A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence. Mol Psychiatry 2016; 21:1145-51. [PMID: 26239293 PMCID: PMC4650257 DOI: 10.1038/mp.2015.108] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Revised: 05/21/2015] [Accepted: 06/16/2015] [Indexed: 02/07/2023]
Abstract
Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case-control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence.
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Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences. INTELLIGENCE 2016; 54:80-89. [PMID: 26912939 PMCID: PMC4725222 DOI: 10.1016/j.intell.2015.11.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences. Only three loci have been associated with intelligence. In traits such as height common variants are found in the same genes as rare variants. We hypothesise that intelligence may also follow this trend. We examine genes where rare variants can produce large deleterious effects on IQ. No enrichment was found for the non-syndromic intellectual disability gene set.
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Abstract
Background The link between intelligence in youth and all-cause mortality in later-life is well established. To better understand this relationship, the current study examines the links between pre-morbid intelligence and a number of specific health outcomes at age 50 using the NLSY-1979 cohort. Methods Participants were the 5793 participants in the NLSY-79 who responded to questions about health outcomes at age 50. Sixteen health outcomes were examined: two were summary measures (physical health and functional limitation), 9 were diagnosed illness conditions, 4 were self-reported conditions, and one was a measure of general health status. Linear and logistic regressions were used, as appropriate, to examine the relationship between intelligence in youth and the health outcomes. Age, sex and both childhood and adult SES, and its sub-components – income, education, & occupational prestige – are all adjusted for separately. Results & conclusion Higher pre-morbid intelligence is linked with better physical health at age 50, and a lower risk for a number of chronic health conditions. For example, a 1 SD higher score in IQ was significantly associated with increased odds of having good, very good, or excellent health, with an odds ratio of 1.70 (C.I. 1.55–1.86). Thirteen of the illness outcomes were significantly and negatively associated with IQ in youth; the odds ratios ranged from 0.85 for diabetes/high blood sugar to 0.65 for stroke, per one standard deviation higher score in IQ. Adjustment for childhood SES led to little attenuation but adult SES partially mediated the relationship for a number of conditions. Mediation by adult SES was not consistently explained by any one of its components—income, education, and occupation status. The current findings contribute to our understanding of lower intelligence as a risk factor for poor health and how this may contribute to health inequalities. We examined links between intelligence in youth and health at age 50 in NLSY-1979. Higher intelligence in youth is linked with better physical health at age 50. Higher intelligence in youth is linked with lower risk for chronic illnesses. Adult but not childhood SES partially mediated the intelligence–health relationship.
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Affiliation(s)
- Christina Wraw
- Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, Scotland EH8 9JZ, United Kingdom
- Corresponding author.
| | - Ian J. Deary
- Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, Scotland EH8 9JZ, United Kingdom
| | - Catharine R. Gale
- Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, Scotland EH8 9JZ, United Kingdom
- MRC Life Course Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, SO16 6YD, United Kingdom
| | - Geoff Der
- MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, 200 Renfield Street, Glasgow, G2 3QB, United Kingdom
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Exome sequencing to detect rare variants associated with general cognitive ability: a pilot study. Twin Res Hum Genet 2015; 18:117-25. [PMID: 25744449 DOI: 10.1017/thg.2015.10] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
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.
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Mendelian and polygenic inheritance of intelligence: A common set of causal genes? Using next-generation sequencing to examine the effects of 168 intellectual disability genes on normal-range intelligence. INTELLIGENCE 2015. [DOI: 10.1016/j.intell.2014.12.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Plomin R, Deary IJ. Genetics and intelligence differences: five special findings. Mol Psychiatry 2015; 20:98-108. [PMID: 25224258 PMCID: PMC4270739 DOI: 10.1038/mp.2014.105] [Citation(s) in RCA: 350] [Impact Index Per Article: 38.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Revised: 07/18/2014] [Accepted: 07/22/2014] [Indexed: 01/27/2023]
Abstract
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.
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Affiliation(s)
- R Plomin
- King's College London, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, DeCrespigny Park, London, UK
| | - I J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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