scholarly journals Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

2019 ◽  
Author(s):  
Max Lam ◽  
W. David Hill ◽  
Joey W. Trampush ◽  
Jin Yu ◽  
Emma Knowles ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Genetic Correlation ◽  
Allelic Variation ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Biological Mechanisms ◽  
Genetic Level ◽  
Higher Educational Attainment ◽  
Synaptic Pruning

AbstractLiability to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published GWAS in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected (“Concordant”) direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants demonstrating the counterintuitive (“Discordant”) relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education and/or schizophrenia at p<5×10−8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs, and many of these have been validated by larger, more recent single-phenotype GWAS. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms: early neurodevelopmental pathways that characterize concordant allelic variation, and adulthood synaptic pruning pathways that were linked to the paradoxical positive genetic association between education and schizophrenia. Further, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia, but also to the broader biological dimensions that are implicated in both general health outcomes and psychiatric illness.

scholarly journals An Atlas of Genetic Correlations across Human Diseases and Traits

2015 ◽  
Author(s):  
Brendan Bulik-Sullivan ◽  
Hilary K Finucane ◽  
Verneri Anttila ◽  
Alexander Gusev ◽  
Felix R Day ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Educational Attainment ◽  
Genetic Correlation ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Significant Snps ◽  
Modeling Framework ◽  
Genome Wide ◽  
Meta Analyses

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use our method to estimate 300 genetic correlations among 25 traits, totaling more than 1.5 million unique phenotype measurements. Our results include genetic correlations between anorexia nervosa and schizophrenia/ body mass index and associations between educational attainment and several diseases. These results highlight the power of a polygenic modeling framework, since there currently are no genome-wide significant SNPs for anorexia nervosa and only three for educational attainment.

scholarly journals Shared genetic architecture and casual relationship between leptin levels and type 2 diabetes: large-scale cross-trait meta-analysis and Mendelian randomization analysis

2020 ◽  
Vol 8 (1) ◽  
pp. e001140
Author(s):  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Large Scale ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Shared Genetic

ObjectiveWe aimed to estimate genetic correlation, identify shared loci and test causality between leptin levels and type 2 diabetes (T2D).Research design and methodsOur study consists of three parts. First, we calculated the genetic correlation of leptin levels and T2D or glycemic traits by using linkage disequilibrium score regression analysis. Second, we conducted a large-scale genome-wide cross-trait meta-analysis using cross-phenotype association to identify shared loci between trait pairs that showed significant genetic correlations in the first part. In the end, we carried out a bidirectional MR analysis to find out whether there is a causal relationship between leptin levels and T2D or glycemic traits.ResultsWe found positive genetic correlations between leptin levels and T2D (Rg=0.3165, p=0.0227), fasting insulin (FI) (Rg=0.517, p=0.0076), homeostasis model assessment-insulin resistance (HOMA-IR) (Rg=0.4785, p=0.0196), as well as surrogate estimates of β-cell function (HOMA-β) (Rg=0.4456, p=0.0214). We identified 12 shared loci between leptin levels and T2D, 1 locus between leptin levels and FI, 1 locus between leptin levels and HOMA-IR, and 1 locus between leptin levels and HOMA-β. We newly identified eight loci that did not achieve genome-wide significance in trait-specific genome-wide association studies. These shared genes were enriched in pancreas, thyroid gland, skeletal muscle, placenta, liver and cerebral cortex. In addition, we found that 1-SD increase in HOMA-IR was causally associated with a 0.329 ng/mL increase in leptin levels (β=0.329, p=0.001).ConclusionsOur results have shown the shared genetic architecture between leptin levels and T2D and found causality of HOMA-IR on leptin levels, shedding light on the molecular mechanisms underlying the association between leptin levels and T2D.

scholarly journals Deciphering the Biological Mechanisms Underlying the Genome-Wide Associations between Computerized Device Use and Psychiatric Disorders

2019 ◽  
Vol 8 (12) ◽  
pp. 2040 ◽  
Author(s):  
Wendt ◽  
Carvalho ◽  
Pathak ◽  
Gelernter ◽  
Polimanti
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Computer Games ◽  
Molecular Mechanisms ◽  
Genetic Correlations ◽  
Nucleotide Polymorphisms ◽  
Biological Mechanisms ◽  
Device Use ◽  
Causal Variable

Computerized device use (CDU) is societally ubiquitous but its effects on mental health are unknown. We performed genetic correlation, Mendelian randomization, and latent causal variable analyses to identify shared genetic mechanisms between psychiatric disorders (Psychiatric Genomics Consortium; 14,477 < N < 150,064) and CDU (UK Biobank; N = 361,194 individuals). Using linkage disequilibrium score regression, we detected strong genetic correlations between “weekly usage of mobile phone in last 3 months” (PhoneUse) vs. attention deficit hyperactivity disorder (ADHD; rg = 0.425, p = 4.59 × 10−29) and “plays computer games” (CompGaming) vs. schizophrenia (SCZ; rg = −0.271, p = 7.16 × 10−26). Focusing on these correlations, we used two sample MRs to detect the causal relationships between trait pairs by treating single nucleotide polymorphisms as non-modifiable risk factors underlying both phenotypes. Significant bidirectional associations were detected (PhoneUse→ADHD β = 0.132, p = 1.89 × 10−4 and ADHD→PhoneUse β = 0.084, p = 2.86 × 10−10; CompGaming→SCZ β = −0.02, p = 6.46 × 10−25 and CompGaming→SCZ β = −0.194, p = 0.005) and the latent causal variable analyses did not support a causal relationship independent of the genetic correlations between these traits. This suggests that molecular pathways contribute to the genetic overlap between these traits. Dopamine transport enrichment (Gene Ontology:0015872, pSCZvsCompGaming = 2.74 × 10−10) and DRD2 association (pSCZ = 7.94 × 10−8; pCompGaming = 3.98 × 10−25) were detected in SCZ and CompGaming and support their negative correlative relationship. FOXP2 was significantly associated with ADHD (p = 9.32 × 10−7) and PhoneUse (p = 9.00 × 10−11) with effect directions concordant with their positive genetic correlation. Our study demonstrates that epidemiological associations between psychiatric disorders and CDUs are due, in part, to the molecular mechanisms shared between them rather than a causal relationship. Our findings imply that biological mechanisms underlying CDU contribute to the psychiatric phenotype manifestation.

scholarly journals The identification of established modifiable mid-life risk factors for cardiovascular disease which contribute to cognitive decline: Korean Longitudinal Study of Aging (KLoSA)

2021 ◽  
Author(s):  
Yebeen Ysabelle Boo ◽  
Otto-Emil Jutila ◽  
Meghan A. Cupp ◽  
Logan Manikam ◽  
Sung-Il Cho
Keyword(s):  
Risk Factors ◽  
Longitudinal Study ◽  
Educational Attainment ◽  
Protective Factors ◽  
Cognitive Decline ◽  
Cognitive Ability ◽  
Protective Factor ◽  
Regular Exercise ◽  
Higher Educational ◽  
Higher Educational Attainment

Abstract Introduction We explored how different chronic diseases, risk factors, and protective factors highly associated with cardiovascular diseases (CVD) are associated with dementia or Mild Cognitive Impairment (MCI) in Korean elders, with a focus on those that manifest in mid-life. Methods A CVD-free cohort (n = 4289) from the Korean Longitudinal Study of Aging was selected to perform Cox mixed-effects proportional hazard regressions. Eighteen control variables with strong associations to CVD were chosen as explanatory variables, and Mini-Mental State Examination (MMSE) score cut-off for dementia and MCI were used as outcome variables. Results The statistically significant (P < 0.05) adverse factors that contribute in developing dementia were age (aHR 1.07, 1.05–1.09), Centre for Epidemiological Studies Depression Scale (CESD-10) (aHR 1.17, 1.12–1.23), diagnosis with cerebrovascular disease (aHR 3.73, 1.81–7.66), living with diabetes (aHR 2.30, 1.22–4.35), and living with high blood pressure (HBP) (aHR 2.05, 1.09–3.87). In contrast, the statistically significant protective factors against developing dementia were current alcohol consumption (aHR 0.67, 0.46–0.99), higher educational attainment (aHR 0.36, 0.26–0.56), and regular exercise (aHR 0.37, 0.26–0.51). The factors with a statistically significant adverse association with progression to MCI were age (aHR 1.02, 1.01–1.03) and CESD-10 (aHR 1.17, 1.14–1.19). In contrast, the statistically significant protective factors against developing MCI were BMI (aHR 0.96, 0.94–0.98), higher educational attainment (aHR 0.33, 0.26–0.43), and regular exercise (aHR 0.83, 0.74–0.92). Conclusion In lieu of the protective factor of MCI and dementia, implementing regular exercise routine well before mid-life and cognitive decline is significant, with adjustments made for those suffering from health conditions, so they can continue exercising despite their morbidity. Further attention in diabetes care and management is needed for patients who already show decline in cognitive ability as it is likely that their MCI impacts their ability to manage their existing chronic conditions, which may adversely affect their cognitive ability furthermore.

scholarly journals Cleft lip/palate and educational attainment: cause, consequence or correlation? A Mendelian randomization study

2020 ◽  
Vol 49 (4) ◽  
pp. 1282-1293 ◽  
Author(s):  
Christina Dardani ◽  
Laurence J Howe ◽  
Nandita Mukhopadhyay ◽  
Evie Stergiakouli ◽  
Yvonne Wren ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Genetic Correlation ◽  
Cleft Lip ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Genetic Liability ◽  
Performance Factors ◽  
A Genome ◽  
Cleft Lip Palate

Abstract Background Previous studies have found that children born with a non-syndromic orofacial cleft have lower-than-average educational attainment. Differences could be due to a genetic predisposition to low intelligence and academic performance, factors arising due to the cleft phenotype (such as social stigmatization, impaired speech/language development) or confounding by the prenatal environment. A clearer understanding of this mechanism will inform interventions to improve educational attainment in individuals born with a cleft, which could substantially improve their quality of life. We assessed evidence for the hypothesis that common variant genetic liability to non-syndromic cleft lip with or without cleft palate (nsCL/P) influences educational attainment. Methods We performed a genome-wide association study (GWAS) meta-analysis of nsCL/P with 1692 nsCL/P cases and 4259 parental and unrelated controls. Using GWAS summary statistics, we performed Linkage Disequilibrium (LD)-score regression to estimate the genetic correlation between nsCL/P, educational attainment (GWAS n = 766 345) and intelligence (GWAS n = 257 828). We used two-sample Mendelian randomization to evaluate the causal effects of genetic liability to nsCL/P on educational attainment and intelligence. Results There was limited evidence for shared genetic aetiology or causal relationships between nsCL/P and educational attainment [genetic correlation (rg) −0.05, 95% confidence interval (CI) −0.12 to 0.01, P 0.13; MR estimate (βMR) −0.002, 95% CI −0.009 to 0.006, P 0.679) or intelligence (rg −0.04, 95% CI −0.13 to 0.04, P 0.34; βMR −0.009, 95% CI −0.02 to 0.002, P 0.11). Conclusions Common variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This is an important first step towards understanding the aetiology of low educational attainment in this group.

scholarly journals Evidence for Recent Polygenic Selection on Educational Attainment Inferred from GWAS Hits

2016 ◽  
Author(s):  
Davide Piffer
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Association Studies ◽  
Meta Analysis ◽  
Significant Snps ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Model Average ◽  
Polygenic Scores ◽  
Polygenic Selection

The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. The PS of 161 GWAS significant SNPs in a recent meta-analysis was highly correlated to population IQ (r=0.863) and to the polygenic score of four alleles independently associated with general cognitive ability. High&nbsp; correlations with PISA scores for a subsample were observed.SNP p value predicted correlation to population IQ and factors from the two previous GWAS (r= -.25). Factor analysis produced similar estimates of selection pressure for educational attainment across the three datasets. Polygenic and factor scores computed using the top 20 significant SNPs showed very high correlation to population IQ (r=0.88; 0.9). Similar findings were obtained using 52 populations from another database (ALFRED). The results together constitute a replication of preliminary findings and provide strong evidence for recent diversifying polygenic selection on educational attainment and underlying cognitive ability.

scholarly journals LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

2016 ◽  
Author(s):  
Jie Zheng ◽  
A. Mesut Erzurumluoglu ◽  
Benjamin L. Elsworth ◽  
Laurence Howe ◽  
Philip C. Haycock ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Web Interface ◽  
The Public ◽  
Genome Wide ◽  
Level Data ◽  
Centralized Database

AbstractMotivationLD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously.ResultsIn this manuscript, we describe LD Hub – a centralized database of summary-level GWAS results for 177 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies.Availability and implementationThe web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/

A Meta-Analysis of Interviews and Cognitive Ability

2013 ◽  
Vol 12 (4) ◽  
pp. 157-169 ◽  
Author(s):  
Philip L. Roth ◽  
Allen I. Huffcutt
Keyword(s):  
Cognitive Ability ◽  
Meta Analysis ◽  
Incremental Validity ◽  
Employment Interviews ◽  
Moderator Analysis ◽  
The Future ◽  
Research Questions ◽  
Meta Analyses ◽  
The Relationship

The topic of what interviews measure has received a great deal of attention over the years. One line of research has investigated the relationship between interviews and the construct of cognitive ability. A previous meta-analysis reported an overall corrected correlation of .40 ( Huffcutt, Roth, & McDaniel, 1996 ). A more recent meta-analysis reported a noticeably lower corrected correlation of .27 ( Berry, Sackett, & Landers, 2007 ). After reviewing both meta-analyses, it appears that the two studies posed different research questions. Further, there were a number of coding judgments in Berry et al. that merit review, and there was no moderator analysis for educational versus employment interviews. As a result, we reanalyzed the work by Berry et al. and found a corrected correlation of .42 for employment interviews (.15 higher than Berry et al., a 56% increase). Further, educational interviews were associated with a corrected correlation of .21, supporting their influence as a moderator. We suggest a better estimate of the correlation between employment interviews and cognitive ability is .42, and this takes us “back to the future” in that the better overall estimate of the employment interviews – cognitive ability relationship is roughly .40. This difference has implications for what is being measured by interviews and their incremental validity.

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