Type 2 Diabetes and Cognitive Status in the Health and Retirement Study: A Mendelian Randomization Approach

Life course plasma metabolomic signatures of genetic liability to Alzheimer's disease

Mechanisms through which most known Alzheimer's disease (AD) loci operate to increase AD risk remain unclear. Although Apolipoprotein E (APOE) is known to regulate lipid homeostasis, the effects of broader AD genetic liability on non-lipid metabolites remain unknown, and the earliest ages at which metabolic perturbations occur and how these change over time are yet to be elucidated. We examined the effects of AD genetic liability on the plasma metabolome across the life course. Using a reverse Mendelian randomization framework in two population-based cohorts [Avon Longitudinal Study of Parents and Children (ALSPAC, n = 5648) and UK Biobank (n ≤ 118,466)], we estimated the effects of genetic liability to AD on 229 plasma metabolites, at seven different life stages, spanning 8 to 73 years. We also compared the specific effects of APOE ε4 and APOE ε2 carriage on metabolites. In ALSPAC, AD genetic liability demonstrated the strongest positive associations with cholesterol-related traits, with similar magnitudes of association observed across all age groups including in childhood. In UK Biobank, the effect of AD liability on several lipid traits decreased with age. Fatty acid metabolites demonstrated positive associations with AD liability in both cohorts, though with smaller magnitudes than lipid traits. Sensitivity analyses indicated that observed effects are largely driven by the strongest AD instrument, APOE, with many contrasting effects observed on lipids and fatty acids for both ε4 and ε2 carriage. Our findings indicate pronounced effects of the ε4 and ε2 genetic variants on both pro- and anti-atherogenic lipid traits and sphingomyelins, which begin in childhood and either persist into later life or appear to change dynamically.

Addressing unmeasured confounders in cohort studies: Instrumental variable method for a time-fixed exposure on an outcome trajectory

Instrumental variable methods, which handle unmeasured confounding by targeting the part of the exposure explained by an exogenous variable not subject to confounding, have gained much interest in observational studies. We consider the very frequent setting of estimating the unconfounded effect of an exposure measured at baseline on the subsequent trajectory of an outcome repeatedly measured over time. We didactically explain how to apply the instrumental variable method in such setting by adapting the two-stage classical methodology with (1) the prediction of the exposure according to the instrumental variable, (2) its inclusion into a mixed model to quantify the exposure association with the subsequent outcome trajectory, and (3) the computation of the estimated total variance. A simulation study illustrates the consequences of unmeasured confounding in classical analyses and the usefulness of the instrumental variable approach. The methodology is then applied to 6224 participants of the 3C cohort to estimate the association of type-2 diabetes with subsequent cognitive trajectory, using 42 genetic polymorphisms as instrumental variables. This contribution shows how to handle endogeneity when interested in repeated outcomes, along with a R implementation. However, it should still be used with caution as it relies on instrumental variable assumptions hardly testable in practice.

Prevalence and incidence of mild cognitive impairment in adults with diabetes in the United States

BACKGROUND

Limited evidence exists about the prevalence and incidence of mild cognitive impairment (MCI) in individuals with diabetes in the U.S. We aimed to address such knowledge gaps using a nationally representative study dataset.

METHOD

We conducted a secondary analysis from the Health and Retirement Study (HRS) (1996-2018). The sample for examining the prevalence of MCI was14,988, with 4192 (28.0%) having diabetes, while the sample for the incidence was 21,824, with 1534 (28.0%) having diabetes.

RESULTS

Participants with diabetes had a higher prevalence of MCI than those without diabetes (19.9 % vs. 14.8 %; odds ratio [95 % confidence interval] (OR[95 %CI]): 1.468 [1.337, 1.611], p <.001). The incidence of MCI in participants with/without newly diagnosed diabetes was 42.9 % vs. 31.6 % after a mean 10-year follow-up, with the incidence rate ratio (IRR) [95 %CI] (1.314 [1.213, 1.424], p <.001). Newly diagnosed diabetes was associated with elevated risks of MCI compared with non-diabetes, with the uncontrolled hazard ratio (HR) [95 %CI] (1.498 [1.405, 1.597], p <.001).

CONCLUSIONS

Using a nationally representative study data in the U.S., participants with diabetes had a higher prevalence and incidence of MCI than those without diabetes. Findings show the importance of developing interventions tailored to the needs of individuals with diabetes and cognitive impairment.

Mendelian randomization study of diabetes and dementia in the Million Veteran Program

INTRODUCTION

Diabetes and dementia are diseases of high health-care burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases.

METHODS

We conducted a one-sample Mendelian randomization (MR) analysis in the US Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data.

RESULTS

For each standard deviation increase in genetically predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: odds ratio [OR] = 1.07 [1.05-1.08], P = 3.40E-18; vascular: OR = 1.11 [1.07-1.15], P = 3.63E-09, Alzheimer's disease [AD]: OR = 1.06 [1.02-1.09], P = 6.84E-04) and non-Hispanic Black participants (all-cause: OR = 1.06 [1.02-1.10], P = 3.66E-03, vascular: OR = 1.11 [1.04-1.19], P = 2.20E-03, AD: OR = 1.12 [1.02-1.23], P = 1.60E-02) but not in Hispanic participants (all P > 0.05).

DISCUSSION

We found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies using two-sample MR techniques.

Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia

Dementia is a major global challenge for health and social care in the 21st century. A third of individuals >65 years of age die with dementia, and worldwide incidence numbers are projected to be higher than 150 million by 2050. Dementia is, however, not an inevitable consequence of old age; 40% of dementia may theoretically be preventable. Alzheimer's disease (AD) accounts for approximately two-thirds of dementia cases and the major pathological hallmark of AD is accumulation of amyloid-β. Nevertheless, the exact pathological mechanisms of AD remain unknown. Cardiovascular disease and dementia share several risk factors and dementia often coexists with cerebrovascular disease. In a public health perspective, prevention is crucial, and it is suggested that a 10% reduction in prevalence of cardiovascular risk factors could prevent more than nine million dementia cases worldwide by 2050. Yet this assumes causality between cardiovascular risk factors and dementia and adherence to the interventions over decades for a large number of individuals. Using genome-wide association studies, the entire genome can be scanned for disease/trait associated loci in a hypothesis-free manner, and the compiled genetic information is not only useful for pinpointing novel pathogenic pathways but also for risk assessments. This enables identification of individuals at high risk, who likely will benefit the most from a targeted intervention. Further optimization of the risk stratification can be done by adding cardiovascular risk factors. Additional studies are, however, highly needed to elucidate dementia pathogenesis and potential shared causal risk factors between cardiovascular disease and dementia.

Mendelian randomization study of diabetes and dementia in the Million Veteran Program

INTRODUCTION

Diabetes and dementia are diseases of high healthcare burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases.

METHODS

We conducted a one-sample Mendelian randomization (MR) analysis in the U.S. Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data.

RESULTS

For each standard deviation increase in genetically-predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: OR=1.07[1.05-1.08], P =3.40E-18; vascular: OR=1.11[1.07-1.15], P =3.63E-09, Alzheimer's: OR=1.06[1.02-1.09], P =6.84E-04) and non-Hispanic Black participants (all-cause: OR=1.06[1.02-1.10], P =3.66E-03, vascular: OR=1.11[1.04-1.19], P =2.20E-03, Alzheimer's: OR=1.12 [1.02-1.23], P =1.60E-02) but not in Hispanic participants (all P >.05).

DISCUSSION

We found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies utilizing two-sample MR techniques.

Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis

This study aims to explore the genetic causal association between type 2 diabetes (T2D) and glycemic traits (fasting glucose [FG], fasting insulin [FI], and glycated hemoglobin [HbA1c]) on delirium using Mendelian randomization (MR). Genome-wide association studies (GWAS) summary data for T2D and glycemic traits were obtained from the IEU OpenGWAS database. GWAS summary data for delirium were obtained from the FinnGen Consortium. All the participants were of European ancestry. In addition, we used T2D, FG, FI, and HbA1c as exposures and delirium as outcomes. A random-effects variance-weighted model (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform MR analysis. In addition, MR-IVW and MR-Egger analyses were used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using MR-Egger regression and MR pleiotropy residual sum and outliers (MR-PRESSO). MR-PRESSO was also used to assess outlier single nucleotide polymorphisms (SNPs). The "leave one out" analysis was used to investigate whether the MR analysis results were influenced by a single SNP and evaluate the robustness of the results. In this study, we conducted a two-sample MR analysis, and there was no evidence of a genetic causal association between T2D and glycemic traits (T2D, FG, FI, and HbA1c) on delirium (all p > 0.05). The MR-IVW and MR-Egger tests showed no heterogeneity in our MR results (all p values >0.05). In addition, The MR-Egger and MR-PRESSO tests showed no horizontal pleiotropy in our MR results (all p > 0.05). The MR-PRESSO results also showed that there were no outliers during the MR analysis. In addition, the "leave one out" test did not find that the SNPs included in the analysis could affect the stability of the MR results. Therefore, our study did not support the causal effects of T2D and glycemic traits (FG, FI, and HbA1c) on delirium risk.

Race, polygenic risk and their association with incident dementia among older US adults

Dementia incidence increases steadily with age at rates that may vary across racial groups. This racial disparity may be attributable to polygenic risk, as well as lifestyle and behavioural factors. We examined whether Alzheimer's disease polygenic score and race predict Alzheimer's disease and other related dementia incidence differentially by sex and mediation through polygenic scores for other health and behavioural conditions. We used longitudinal data from the nationally representative Health and Retirement Study. We restricted participants to those with complete data on 31 polygenic scores, including Alzheimer's disease polygenic score (2006-2012). Among participants aged 55 years and older in 2008, we excluded those with any memory problems between 2006 and 2008 and included those with complete follow-up on incident Alzheimer's disease and all-cause dementia, between 2010 and 2018 (N = 9683), based on self- or proxy-diagnosis every 2 years (2010, 2012, 2014, 2016 and 2018). Cox proportional hazards and 4-way decomposition models were conducted. Analyses were also stratified by sex and by race. There were racial differences in all-cause dementia incidence (age and sex-adjusted model, per standard deviation: hazard ratio, HR = 1.34, 95% confidence interval, CI: 1.09-1.65, P = 0.007), partially driven by educational attainment and income. We also found independent associations of race (age and sex-adjusted model, African American versus White adults: HR = 2.07, 95% CI: 1.52-2.83, P < 0.001) and Alzheimer's disease polygenic score (age and sex-adjusted model, per SD: HR = 1.37, 95% CI: 1.00-1.87, P < 0.001) with Alzheimer's disease incidence, including sex differences whereby women had a stronger effect of Alzheimer's disease polygenic score on Alzheimer's disease incidence compared with men (P < 0.05 for sex by Alzheimer's disease polygenic score interaction) adjusting for race and other covariates. The total impact of Alzheimer's disease polygenic scores on Alzheimer's disease incidence was mostly direct, while the effect of race on all-cause dementia incidence was mediated through socio-economic, lifestyle and health-related factors. Finally, among the 30 polygenic scores we examined, the total effects on the pathway Alzheimer's disease polygenic score --> Other polygenic score --> Incident Alzheimer's or all-cause dementia, were statistically significant for all, driven primarily by the controlled direct effect (P< 0. 001). In conclusion, both race and Alzheimer's disease polygenic scores were associated independently with Alzheimer's disease and all-cause dementia incidence. Alzheimer's disease polygenic score was more strongly linked to incident Alzheimer's disease among women, while racial difference in all-cause dementia was explained by other factors including socio-economic status.

Diabetes and dementia: Clinical perspective, innovation, knowledge gaps

The world faces a pandemic-level prevalence of type 2 diabetes. In parallel with this massive burden of metabolic disease is the growing prevalence of dementia as the population ages. The two health issues are intertwined. The Lancet Commission on dementia prevention, intervention, and care was convened to tackle the growing global concern of dementia by identifying risk factors. It concluded, along with other studies, that diabetes as well as obesity and the metabolic syndrome more broadly, which are frequently comorbid, raise the risk of developing dementia. Type 2 diabetes is a modifiable risk factor; however, it is uncertain whether anti-diabetic drugs mitigate risk of developing dementia. Reasons are manifold but constitute a critical knowledge gap in the field. This review outlines studies of type 2 diabetes on risk of dementia, illustrating key concepts. Moreover, it identifies knowledge gaps, reviews strategies to help fill these gaps, and concludes with a series of recommendations to mitigate risk and advance understanding of type 2 diabetes and dementia.

A Diabetes Genetic Risk Score Is Associated With All-Cause Dementia and Clinically Diagnosed Vascular Dementia in the Million Veteran Program

OBJECTIVE

Diabetes and dementia are diseases of high health care burden worldwide, and studies have shown that diabetes is associated with an increased relative risk of dementia. We set out to examine whether type 2 diabetes-associated genetic variants were associated with dementia and whether they differed by race/ethnicity or clinical dementia diagnosis.

RESEARCH DESIGN AND METHODS

We evaluated associations of two type 2 diabetes genetic risk scores (GRS and GRS-nonAPOE: a score without rs429358, a variant associated with Alzheimer disease [AD]) with three classifications of clinical dementia diagnoses in the Million Veteran Program (MVP): all-cause dementia, vascular dementia (VaD), and AD. We conducted our analysis stratified by European (EUR), African (AFR), and Hispanic (HIS) races/ethnicities.

RESULTS

In EUR, we found associations of the GRS with all-cause dementia (odds ratio [OR] 1.06, P = 1.60e-07) and clinically diagnosed VaD (OR 1.12, P = 5.2e-05) but not with clinically diagnosed AD (OR 1.02, P = 0.43). The GRS was not associated with any dementia outcome in AFR or HIS. When testing with GRS-nonAPOE, we found that effect size estimates in EUR increased and P values decreased for all-cause dementia (OR 1.08, P = 2.6e-12), for VaD (OR 1.14, P = 7.2e-07), and for AD (OR 1.06, P = 0.018). For AFR, the association of GRS-nonAPOE and clinically diagnosed VaD (OR 1.15, P = 0.016) was statistically significant. There were no significant findings for HIS.

CONCLUSIONS

We found evidence suggesting shared genetic pathogenesis of diabetes with all-cause dementia and clinically diagnosed VaD.

Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer's Disease in Electronic Health Records

Alzheimer's disease (AD) is the most common form of dementia and a growing public health burden in the United States. Significant progress has been made in identifying genetic risk for AD, but limited studies have investigated how AD genetic risk may be associated with other disease conditions in an unbiased fashion. In this study, we conducted a phenome-wide association study (PheWAS) by genetic ancestry groups within a large academic health system using the polygenic risk score (PRS) for AD. PRS was calculated using LDpred2 with genome-wide association study (GWAS) summary statistics. Phenotypes were extracted from electronic health record (EHR) diagnosis codes and mapped to more clinically meaningful phecodes. Logistic regression with Firth's bias correction was used for PRS phenotype analyses. Mendelian randomization was used to examine causality in significant PheWAS associations. Our results showed a strong association between AD PRS and AD phenotype in European ancestry (OR = 1.26, 95% CI: 1.13, 1.40). Among a total of 1,515 PheWAS tests within the European sample, we observed strong associations of AD PRS with AD and related phenotypes, which include mild cognitive impairment (MCI), memory loss, and dementias. We observed a phenome-wide significant association between AD PRS and gouty arthropathy (OR = 0.90, adjusted p = 0.05). Further causal inference tests with Mendelian randomization showed that gout was not causally associated with AD. We concluded that genetic predisposition of AD was negatively associated with gout, but gout was not a causal risk factor for AD. Our study evaluated AD PRS in a real-world EHR setting and provided evidence that AD PRS may help to identify individuals who are genetically at risk of AD and other related phenotypes. We identified non-neurodegenerative diseases associated with AD PRS, which is essential to understand the genetic architecture of AD and potential side effects of drugs targeting genetic risk factors of AD. Together, these findings expand our understanding of AD genetic and clinical risk factors, which provide a framework for continued research in aging with the growing number of real-world EHR linked with genetic data.

Cognitive impairment in racially/ethnically diverse older adults: Accounting for sources of diagnostic bias

INTRODUCTION

The Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study enrolled Asian, Black, Latino, and White adults ages 65+ without prior dementia diagnosis (N = 1709). We evaluated the prevalence of cognitive impairment (mild cognitive impairment or dementia) accounting for potential biases.

METHODS

A random subgroup (N = 541) received clinical evaluation and others were evaluated if they failed a cognitive screen. Diagnoses were made under two conditions: (1) demographics-blind, based on clinical exam and demographically adjusted neuropsychological test scores; and (2) all available information (clinical exam, demographics, and adjusted and unadjusted test scores).

RESULTS

Cognitive impairment prevalence was 28% for blinded-adjusted diagnosis and 25% using all available information. Black participants had higher impairment rates than White (both conditions) and Latino (blinded-adjusted diagnosis) participants. Incomplete assessments negatively biased prevalence estimates for White participants.

DISCUSSION

Racial/ethnic disparities in cognitive impairment were amplified by attrition bias in White participants but were unaffected by type of test norms and diagnosticians' knowledge of demographics.