scholarly journals The causal effect of educational attainment on Alzheimer’s disease: A two-sample Mendelian randomization study

2017 ◽  
Author(s):  
Emma L Anderson ◽  
Kaitlin H Wade ◽  
Gibran Hemani ◽  
Jack Bowden ◽  
Roxanna Korologou-Linden ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Genome Wide Association Study ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Inverse Variance ◽  
Higher Educational Attainment ◽  
Years Of Schooling

ABSTRACTBackgroundObservational evidence suggests that higher educational attainment is protective for Alzheimer’s disease (AD). It is unclear whether this association is causal or confounded by demographic and socioeconomic characteristics. We examined the causal effect of educational attainment on AD in a two-sample MR framework.MethodsWe extracted all available effect estimates of the 74 single nucleotide polymorphisms (SNPs) associated with years of schooling from the largest genome-wide association study (GWAS) of educational attainment (N=293,723) and the GWAS of AD conducted by the International Genomics of Alzheimer’s Project (n=17,008 AD cases and 37,154 controls). SNP-exposure and SNP-outcome coefficients were combined using an inverse variance weighted approach, providing an estimate of the causal effect of each SD increase in years of schooling on AD. We also performed appropriate sensitivity analyses examining the robustness of causal effect estimates to the various assumptions and conducted simulation analyses to examine potential survival bias of MR analyses.FindingsWith each SD increase in years of schooling (3.51 years), the odds of AD were, on average, reduced by approximately one third (odds ratio= 0.63, 95% confidence interval [CI]: 0.48 to 0.83, p<0.001). Causal effect estimates were consistent when using causal methods with varying MR assumptions or different sets of SNPs for educational attainment, lending confidence to the magnitude and direction of effect in our main findings. There was also no evidence of survival bias in our study.InterpretationOur findings support a causal role of educational attainment on AD, whereby an additional ∼3.5 years of schooling reduces the odds of AD by approximately one third.

scholarly journals Education, intelligence and Alzheimer’s disease: Evidence from a multivariable two-sample Mendelian randomization study

2018 ◽  
Author(s):  
Emma L Anderson ◽  
Laura D Howe ◽  
Kaitlin H Wade ◽  
Yoav Ben-Shlomo ◽  
W. David Hill ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Univariate Analysis ◽  
Causal Effects ◽  
Training Interventions ◽  
Bidirectional Relationship ◽  
Years Of Schooling

AbstractObjectivesTo examine whether educational attainment and intelligence have causal effects on risk of Alzheimer’s disease (AD), independently of each other.DesignTwo-sample univariable and multivariable Mendelian Randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on risk of AD.Participants17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP) consortiumMain outcome measureOdds ratio of AD per standardised deviation increase in years of schooling and intelligenceResultsThere was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23% to 49%) and 35% (95% CI: 25% to 43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account, but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis.ConclusionsThere is robust evidence for an independent, causal effect of intelligence in lowering AD risk, potentially supporting a role for cognitive training interventions to improve aspects of intelligence. However, given the observed causal effect of educational attainment on intelligence, there may also be support for policies aimed at increasing length of schooling to lower incidence of AD.

scholarly journals Education, intelligence and Alzheimer’s disease: evidence from a multivariable two-sample Mendelian randomization study

2020 ◽  
Vol 49 (4) ◽  
pp. 1163-1172 ◽  
Author(s):  
Emma L Anderson ◽  
Laura D Howe ◽  
Kaitlin H Wade ◽  
Yoav Ben-Shlomo ◽  
W David Hill ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Univariate Analysis ◽  
Causal Effects ◽  
Bidirectional Relationship ◽  
Robust Evidence ◽  
Years Of Schooling

Abstract Objectives To examine whether educational attainment and intelligence have causal effects on risk of Alzheimer’s disease (AD), independently of each other. Design Two-sample univariable and multivariable Mendelian randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on AD risk. Participants 17 008 AD cases and 37 154 controls from the International Genomics of Alzheimer’s Project (IGAP) consortium. Main outcome measure Odds ratio (OR) of AD per standardized deviation increase in years of schooling (SD = 3.6 years) and intelligence (SD = 15 points on intelligence test). Results There was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions [OR for intelligence on education = 0.51 SD units, 95% confidence interval (CI): 0.49, 0.54; OR for education on intelligence = 0.57 SD units, 95% CI: 0.48, 0.66]. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23–49%) and 35% (95% CI: 25–43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account (OR = 1.15, 95% CI: 0.68–1.93), but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis (OR = 0.69, 95% CI: 0.44–0.88). Conclusions There is robust evidence for an independent, causal effect of intelligence in lowering AD risk. The causal effect of educational attainment on AD risk is likely to be mediated by intelligence.

scholarly journals Genetically Predicted Higher Educational Attainment Decreases the Risk of COVID-19 Susceptibility and Severity: A Mendelian Randomization Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhongyu Jian ◽  
Menghua Wang ◽  
Xi Jin ◽  
Xin Wei
Keyword(s):  
Educational Attainment ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Vigorous Physical Activity ◽  
Health Resources ◽  
Primary Analysis ◽  
Genome Wide ◽  
Inverse Variance ◽  
Higher Educational Attainment

Background: Prior observational studies indicated that lower educational attainment (EA) is associated with higher COVID-19 risk, while these findings were vulnerable to bias from confounding factors. We aimed to clarify the causal effect of EA on COVID-19 susceptibility, hospitalization, and severity using Mendelian randomization (MR).Methods: We identified genetic instruments for EA from a large genome-wide association study (GWAS) (n = 1,131,881). Summary statistics for COVID-19 susceptibility (112,612 cases and 2,474,079 controls), hospitalization (24,274 cases and 2,061,529 controls), and severity (8,779 cases and 1,001,875 controls) were obtained from the COVID-19 Host Genetics Initiative. We used the single-variable MR (SVMR) and the multivariable MR (MVMR) controlling intelligence, income, body mass index, vigorous physical activity, sedentary behavior, smoking, and alcohol consumption to estimate the total and direct effects of EA on COVID-19 outcomes. Inverse variance weighted was the primary analysis method. All the statistical analyses were performed using R software.Results: Results from the SVMR showed that genetically predicted higher EA was correlated with a lower risk of COVID-19 susceptibility [odds ratio (OR) 0.86, 95% CI 0.84–0.89], hospitalization (OR 0.67, 95% CI 0.62–0.73), and severity (OR 0.67, 95% CI 0.58–0.79). EA still maintained its effects in most of the MVMR.Conclusion: Educational attainment is a predictor for susceptibility, hospitalization, and severity of COVID-19 disease. Population with lower EA should be provided with a higher prioritization to public health resources to decrease the morbidity and mortality of COVID-19.

scholarly journals Genetically Predicted Telomere Length and Its Relationship With Alzheimer’s Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Guangping Yu ◽  
Leihong Lu ◽  
Zaihong Ma ◽  
Shouhai Wu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Telomere Length ◽  
Genome Wide Association Study ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Inverse Variance ◽  
A Genome ◽  
Summary Effect ◽  
Weighted Median

Are shorter telomeres causal risk factors for Alzheimer’s disease (AD)? This study aimed to examine if shorter telomeres were causally associated with a higher risk of AD using Mendelian randomization (MR) analysis. Two-sample MR methods were applied to the summary effect sizes and standard errors from a genome-wide association study for AD. Twenty single nucleotide polymorphisms of genome-wide significance were selected as instrumental variables for leukocyte telomere length. The main analyses were performed primarily using the random-effects inverse-variance weighted method and complemented with the other three methods: weighted median approaches, MR-Egger regression, and weighted mode approach. The intercept of MR-Egger regression was used to assess horizontal pleiotropy. We found that longer telomeres were associated with lower risks of AD (odds ratio = 0.79, 95% confidence interval: 0.67, 0.93, P = 0.004). Comparable results were obtained using weighted median approaches, MR-Egger regression, and weighted mode approaches. The intercept of the MR-Egger regression was close to zero. This may show that there was not suggestive of horizontal pleiotropy. Our findings provided additional evidence regarding the putative causal association between shorter telomere length and the higher risk of AD.

scholarly journals Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

Brain ◽  
2020 ◽  
Author(s):  
Longfei Jia ◽  
Fangyu Li ◽  
Cuibai Wei ◽  
Min Zhu ◽  
Qiumin Qu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Predictive Models ◽  
Genome Wide Association Study ◽  
Disease Onset ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Risk Variants ◽  
Genome Wide

Abstract Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer’s disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer’s disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer’s disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; Pcombined = 3.07 × 10−19, 2.49 × 10−23, 1.35 × 10−67, and 4.81 × 10−9, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P &lt; 5.0 × 10−8). Literature mining suggested that these novel single nucleotide polymorphisms are related to amyloid precursor protein transport and metabolism, antioxidation, and neurogenesis. Based on their possible roles in the development of Alzheimer’s disease, we used different combinations of these variants and the apolipoprotein E status and successively built 11 predictive models. The predictive models include relatively few single nucleotide polymorphisms useful for clinical practice, in which the maximum number was 13 and the minimum was only four. These predictive models were all significant and their peak of area under the curve reached 0.73 both in the first and second stages. Finally, these models were validated using a separate longitudinal cohort of 5474 individuals. The results showed that individuals carrying risk variants included in the models had a shorter latency and higher incidence of Alzheimer’s disease, suggesting that our models can predict Alzheimer’s disease onset in a population with genetic susceptibility. The effectiveness of the models for predicting Alzheimer’s disease onset confirmed the contributions of these identified variants to disease pathogenesis. In conclusion, this is the first study to validate genome-wide association study-based predictive models for evaluating the risk of Alzheimer’s disease onset in a large Chinese population. The clinical application of these models will be beneficial for individuals harbouring these risk variants, and particularly for young individuals seeking genetic consultation.

scholarly journals Genetically Determined Levels of Serum Metabolites and Risk of Neuroticism: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Li Qian ◽  
Yajuan Fan ◽  
Fengjie Gao ◽  
Binbin Zhao ◽  
Bin Yan ◽  
...  
Keyword(s):  
Uric Acid ◽  
Lower Risk ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Strong Predictor ◽  
Causal Effects ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Inverse Variance

Abstract Background Neuroticism is a strong predictor for a variety of social and behavioral outcomes, but the etiology is still unknown. Our study aims to provide a comprehensive investigation of causal effects of serum metabolome phenotypes on risk of neuroticism using Mendelian randomization (MR) approaches. Methods Genetic associations with 486 metabolic traits were utilized as exposures, and data from a large genome-wide association study of neuroticism were selected as outcome. For MR analysis, we used the standard inverse-variance weighted (IVW) method for primary MR analysis and 3 additional MR methods (MR-Egger, weighted median, and MR pleiotropy residual sum and outlier) for sensitivity analyses. Results Our study identified 31 metabolites that might have causal effects on neuroticism. Of the 31 metabolites, uric acid and paraxanthine showed robustly significant association with neuroticism in all MR methods. Using single nucleotide polymorphisms as instrumental variables, a 1-SD increase in uric acid was associated with approximately 30% lower risk of neuroticism (OR: 0.77; 95% CI: 0.62–0.95; PIVW = 0.0145), whereas a 1-SD increase in paraxanthine was associated with a 7% higher risk of neuroticism (OR: 1.07; 95% CI: 1.01–1.12; PIVW = .0145). Discussion Our study suggested an increased level of uric acid was associated with lower risk of neuroticism, whereas paraxanthine showed the contrary effect. Our study provided novel insight by combining metabolomics with genomics to help understand the pathogenesis of neuroticism.

scholarly journals Exploring the causal effects of genetic liability to ADHD and Autism on Alzheimer’s disease

2020 ◽  
Author(s):  
Panagiota Pagoni ◽  
Christina Dardani ◽  
Beate Leppert ◽  
Roxanna Korologou-Linden ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Autism Spectrum ◽  
Causal Effects ◽  
Direct Effects ◽  
Limited Evidence ◽  
Genetic Liability

ABSTRACTBackgroundThere are very few studies investigating possible links between Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD) and Alzheimer’s disease and these have been limited by small sample sizes, diagnostic and recall bias. However, neurocognitive deficits affecting educational attainment in individuals with ADHD could be risk factors for Alzheimer’s later in life while hyper plasticity of the brain in ASD and strong positive genetic correlations of ASD with IQ and educational attainment could be protective against Alzheimer’s.MethodsWe estimated the bidirectional total causal effects of genetic liability to ADHD and ASD on Alzheimer’s disease through two-sample Mendelian randomization. We investigated their direct effects, independent of educational attainment and IQ, through Multivariable Mendelian randomization.ResultsThere was limited evidence to suggest that genetic liability to ADHD (OR=1.00, 95% CI: 0.98 to 1.02, p=0.39) or ASD (OR=0.99, 95% CI: 0.97 to 1.01, p=0.70) was associated with risk of Alzheimer’s disease. Similar causal effect estimates were identified when the direct effects, independent of educational attainment (ADHD: OR=1.00, 95% CI: 0.99 to 1.01, p=0.07; ASD: OR=0.99, 95% CI: 0.98 to 1.00, p=0.28) and IQ (ADHD: OR=1.00, 95% CI: 0.99 to 1.02. p=0.29; ASD: OR=0.99, 95% CI: 0.98 to 1.01, p=0.99), were assessed. Finally, genetic liability to Alzheimer’s disease was not found to have a causal effect on risk of ADHD or ASD (ADHD: OR=1.12, 95% CI: 0.86 to 1.44, p=0.37; ASD: OR=1.19, 95% CI: 0.94 to 1.51, p=0.14).ConclusionsIn the first study to date investigating the causal associations between genetic liability to ADHD, ASD and Alzheimer’s, within an MR framework, we found limited evidence to suggest a causal effect. It is important to encourage future research using ADHD and ASD specific subtype data, as well as longitudinal data in order to further elucidate any associations between these conditions.

scholarly journals Pleiotropy of Alzheimer’s Disease and Educational Attainment: Insights from the Summary Statistics

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 986-986
Author(s):  
Yury Loika ◽  
Elena Loiko ◽  
Irina Culminskaya ◽  
Alexander Kulminski
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Large Scale ◽  
Association Studies ◽  
Epidemiological Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Nucleotide Polymorphisms ◽  
Omnibus Test

Abstract Epidemiological studies report beneficial associations of higher educational attainment (EDU) with Alzheimer’s disease (AD). Prior genome-wide association studies (GWAS) also reported variants associated with AD and EDU separately. The analysis of pleiotropic predisposition to these phenotypes may shed light on EDU-related protection against AD. We examined pleiotropic predisposition to AD and EDU using Fisher’s method and omnibus test applied to summary statistics for single nucleotide polymorphisms (SNPs) associated with AD and EDU in large-scale univariate GWAS at suggestive-effect (5×10-8

scholarly journals Causal effect of Insulin Resistance on Small Vessel Stroke and Alzheimer's Disease: A Mendelian Randomization Analysis

2021 ◽  
Author(s):  
Mengyuan Zhou ◽  
Hao Li ◽  
Yongjun Wang ◽  
Yuesong Pan ◽  
Yilong Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Insulin Resistance ◽  
Alzheimer's Disease ◽  
Gold Standard ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Small Vessel ◽  
European Ancestry ◽  
Fasting Insulin ◽  
Inverse Variance

Abstract Background The causal effect of insulin resistance on small vessel stroke and Alzheimer Disease was controversial in previous studies. Methods We selected 12 single-nucleotide polymorphisms (SNPs) associated with body mass index (BMI)-adjusted fasting insulin levels and 5 SNPs associated with gold standard measures of insulin resistance as instrumental variables in Mendelian randomization (MR) analyses. Summary statistical data of SNP-small vessel stroke and of SNP-AD associations were derived from the Multi-ancestry Genome-Wide Association Study of Stroke Consortium and Psychiatric Genomics Consortium-Alzheimer’s Disease Workgroup data of individuals of European ancestry. Two-sample MR estimates were conducted with inverse-variance-weighted, robust inverse-variance-weighted, simple median, weighted median, weighted mode-based estimator, and MR pleiotropy residual sum and outlier methods. Results Genetically predicted higher insulin resistance had a higher odds ratio (OR) of small vessel stroke (OR 1.23; 95% confidence interval [CI] 1.05–1.44; P = 0.01 using BMI-adjusted fasting insulin; OR 1.25; 95% CI 1.07–1.46; P = 0.006 using gold standard measure of insulin resistance) and AD (OR 1.13; 95% CI 1.04–1.23; P = 0.004 using BMI-adjusted fasting insulin; OR 1.02; 95% CI 1.00-1.03; P = 0.03 using gold standard measures of insulin resistance) using the inverse-variance-weighted method. No evidence of pleiotropy was found using MR-Egger regression. Conclusion Our findings provide genetic support for a causal effect of insulin resistance on small vessel stroke and AD. Further investigation on the involved mechanisms is needed.

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