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 ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Small Vessel ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis

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.

scholarly journals Body Shape and Alzheimer’s Disease: A Mendelian Randomization Analysis

2019 ◽  
Vol 13 ◽  
Author(s):  
Yuchang Zhou ◽  
Xiubin Sun ◽  
Maigeng Zhou
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Body Shape ◽  
Mendelian Randomization ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis

scholarly journals Evidence of a Causal Association Between Cancer and Alzheimer’s Disease: a Mendelian Randomization Analysis

2019 ◽  
Author(s):  
Sahba Seddighi ◽  
Alexander L Houck ◽  
James B Rowe ◽  
Paul DP Pharoah
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mendelian Randomization ◽  
Inverse Association ◽  
Lower Odds ◽  
Mendelian Randomization Analysis ◽  
Log Odds ◽  
Randomization Analysis

AbstractObjectivesTo determine whether cancer confers protection against Alzheimer’s disease and to evaluate the relationship in the context of smoking-related cancers versus non-smoking related cancersDesignMendelian randomization analysis using cancer-associated genetic variants as instrumental variablesSettingInternational Genomics of Alzheimer’s ProjectParticipants17,008 Alzheimer’s disease cases and 37,154 controlsMain outcome measuresOdds ratio of Alzheimer’s disease per 1-unit higher log odds of genetically predicted cancerResultsWe found that genetically predicted lung cancer (OR 0.91, 95% CI 0.84-0.99, p=0.019), leukemia (OR 0.98, 95% CI 0.96-0.995, p=0.012), and breast cancer (OR 0.94, 95% CI 0.89-0.99, p=0.028) were associated with 9.0%, 2.4%, and 5.9% lower odds of Alzheimer’s disease, respectively, per 1-unit higher log odds of cancer. When genetic predictors of all cancers were pooled, cancer was associated with 2.5% lower odds of Alzheimer’s disease (OR 0.98, 95% CI 0.96-0.988, p=0.00027) per 1-unit higher log odds of cancer. Finally, genetically predicted smoking-related cancers showed a more robust inverse association with Alzheimer’s disease than non-smoking related cancers (5.2% lower odds, OR 0.95, 95% CI 0.92-0.98, p=0.0026, vs. 1.9% lower odds, OR 0.98, 95% CI 0.97-0.995, p=0.0091).ConclusionsGenetically predicted lung cancer, leukemia, breast cancer, and all cancers in aggregate are associated with lower odds of incident Alzheimer’s disease. Furthermore, the risk of Alzheimer’s disease was lower in smoking-related versus non-smoking related cancers. These results add to the substantial epidemiological evidence of an inverse association between history of cancer and lower odds of Alzheimer’s disease, by suggesting a causal basis for this relationship.

scholarly journals Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

2019 ◽  
Author(s):  
Emma L Anderson ◽  
Rebecca C Richmond ◽  
Samuel E Jones ◽  
Gibran Hemani ◽  
Kaitlin. H Wade ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Factor ◽  
Daytime Sleepiness ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Sleep Parameters ◽  
Tentative Evidence ◽  
Patients Experience ◽  
Randomization Analysis

ABSTRACTINTRODUCTIONIt is established that Alzheimer’s disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.METHODSMendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.RESULTSOverall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.DISCUSSONOur findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.

scholarly journals Causal Association Between Heart Failure and Alzheimer’s Disease: A Two-Sample Bidirectional Mendelian Randomization Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Chenglin Duan ◽  
Jingjing Shi ◽  
Guozhen Yuan ◽  
Xintian Shou ◽  
Ting Chen ◽  
...  
Keyword(s):  
Heart Failure ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Sensitivity Analysis ◽  
Causal Relationship ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Relationships ◽  
Simple Mode

Background: Traditional observational studies have demonstrated an association between heart failure and Alzheimer’s disease. The strengths of observational studies lie in their speed of implementation, cost, and applicability to rare diseases. However, observational studies have several limitations, such as uncontrollable confounders. Therefore, we employed Mendelian randomization of genetic variants to evaluate the causal relationships existing between AD and HF, which can avoid these limitations.Materials and Methods: A two-sample bidirectional MR analysis was employed. All datasets were results from the UK’s Medical Research Council Integrative Epidemiology Unit genome-wide association study database, and we conducted a series of control steps to select the most suitable single-nucleotide polymorphisms for MR analysis, for which five primary methods are offered. We reversed the functions of exposure and outcomes to explore the causal direction of HF and AD. Sensitivity analysis was used to conduct several tests to avoid heterogeneity and pleiotropic bias in the MR results.Results: Our MR studies did not support a meaningful causal relationship between AD on HF (MR-Egger, p = 0.634 > 0.05; weighted median (WM), p = 0.337 > 0.05; inverse variance weighted (IVW), p = 0.471 > 0.05; simple mode, p = 0.454 > 0.05; weighted mode, p = 0.401 > 0.05). At the same time, we did not find a significant causal relationship between HF and AD with four of the methods (MR-Egger, p = 0.195 > 0.05; IVW, p = 0.0879 > 0.05; simple mode, p = 0.170 > 0.05; weighted mode, p = 0.110 > 0.05), but the WM method indicated a significant effect of HF on AD (p = 0.025 < 0.05). Because the statistical powers of IVW and MR-Egger are more than that of WM, we think that there is no causal effect of HF on AD. Sensitivity analysis and horizontal pleiotropy were not detected in the MR analysis.Conclusion: Our results did not provide significant evidence indicating any causal relationships between HF and AD in the European population. Therefore, more large-scale datasets or datasets related to similar factors are expected for further MR analysis.

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 Homocysteine and small vessel stroke: A mendelian randomization analysis

2019 ◽  
Vol 85 (4) ◽  
pp. 495-501 ◽  
Author(s):  
Susanna C. Larsson ◽  
Matthew Traylor ◽  
Hugh S. Markus
Keyword(s):  
Mendelian Randomization ◽  
Small Vessel ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis

scholarly journals Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

2020 ◽  
Vol 70 ◽  
pp. 102300
Author(s):  
Padraig Dixon ◽  
William Hollingworth ◽  
Sean Harrison ◽  
Neil M. Davies ◽  
George Davey Smith
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Hospital Costs ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis

scholarly journals Evidence of a Causal Association Between Cancer and Alzheimer’s Disease: a Mendelian Randomization Analysis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sahba Seddighi ◽  
Alexander L. Houck ◽  
James B. Rowe ◽  
Paul D. P. Pharoah
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mendelian Randomization ◽  
Observational Evidence ◽  
Inverse Association ◽  
Causal Association ◽  
Lower Odds ◽  
Genetic Predictors ◽  
Log Odds ◽  
Randomization Analysis

Abstract While limited observational evidence suggests that cancer survivors have a decreased risk of developing Alzheimer’s disease (AD), and vice versa, it is not clear whether this relationship is causal. Using a Mendelian randomization approach that provides evidence of causality, we found that genetically predicted lung cancer (OR 0.91, 95% CI 0.84–0.99, p = 0.019), leukemia (OR 0.98, 95% CI 0.96–0.995, p = 0.012), and breast cancer (OR 0.94, 95% CI 0.89–0.99, p = 0.028) were associated with 9.0%, 2.4%, and 5.9% lower odds of AD, respectively, per 1-unit higher log odds of cancer. When genetic predictors of all cancers were pooled, cancer was associated with 2.5% lower odds of AD (OR 0.98, 95% CI 0.96–0.988, p = 0.00027) per 1-unit higher log odds of cancer. Finally, genetically predicted smoking-related cancers showed a more robust inverse association with AD than non-smoking related cancers (OR 0.95, 95% CI 0.92–0.98, p = 0.0026, vs. OR 0.98, 95% CI 0.97–0.995, p = 0.0091).

Sign in / Sign up

Export Citation Format

Share Document