Objective

Previous studies linking telomere length (TL) and health have been largely associational. We apply genetic instrumental variables (IV) analysis, also known as Mendelian randomization, to test the hypothesis that shorter TL leads to poorer health. This method reduces bias from reverse causation or confounding.

Methods

We used two approaches in this study that rely on two separate data sources: (1) individual-level data from the Health and Retirement Study (HRS) (N=3734), and (2) coefficients from genome-wide association studies (GWAS). We employed two-sample genetic IV analyses, constructing a polygenic risk score (PRS) of TL-associated single nucleotide polymorphisms. The first approach examined the association of the PRS with nine individual health outcomes in HRS. The second approach took advantage of estimates available in GWAS databases to estimate the impact of TL on five health outcomes using an inverse variance-weighted meta-analytic technique.

Results

Using individual-level data, shorter TL was marginally statistically significantly associated with decreased risk of stroke and increased risk of heart disease. Using the meta-analytic approach, shorter TL was associated with increased risk of coronary artery disease (OR 1.02 per 100 base pairs, 95%CI: 1.00, 1.03).

Discussion

With the exception of a small contribution to heart disease, our findings suggest that TL may be a marker of disease rather than a cause. They also demonstrate the utility of the inverse variance-weighted meta-analytic approach when examining small effect sizes.

Bias due to unobserved confounding can seldom be ruled out with certainty when estimating the causal effect of a nonrandomized treatment. The instrumental variable (IV) design offers, under certain assumptions, the opportunity to tame confounding bias, without directly observing all confounders. The IV approach is very well developed in the context of linear regression and also for certain generalized linear models with a nonlinear link function. However, IV methods are not as well developed for regression analysis with a censored survival outcome. In this article, we develop the IV approach for regression analysis in a survival context, primarily under an additive hazards model, for which we describe 2 simple methods for estimating causal effects. The first method is a straightforward 2-stage regression approach analogous to 2-stage least squares commonly used for IV analysis in linear regression. In this approach, the fitted value from a first-stage regression of the exposure on the IV is entered in place of the exposure in the second-stage hazard model to recover a valid estimate of the treatment effect of interest. The second method is a so-called control function approach, which entails adding to the additive hazards outcome model, the residual from a first-stage regression of the exposure on the IV. Formal conditions are given justifying each strategy, and the methods are illustrated in a novel application to a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We also establish that analogous strategies can also be used under a proportional hazards model specification, provided the outcome is rare over the entire follow-up.

Background

Post-stroke memory impairment is more common among older adults, women and blacks. It is unclear whether post-stroke differences reflect differential effects of stroke per se or differences in prestroke functioning. We compare memory trajectories before and after stroke by age, sex and race.

Methods

Health and Retirement Study participants aged ≥50 years (n = 17,341), with no stroke history at baseline, were interviewed biennially up to 10 years for first self- or proxy-reported stroke (n = 1,574). Segmented linear regression models were used to compare annual rates of memory change before and after stroke among 1,169 stroke survivors, 405 stroke decedents and 15,767 stroke-free participants. Effect modification was evaluated with analyses stratified by baseline age (≤70 vs. >70), sex and race (white vs. nonwhite), and using interaction terms between age/sex/race indicators and annual memory change.

Results

Older (>70 years) adults experienced a faster memory decline before stroke (-0.19 vs. -0.10 points/year for survivors, -0.24 vs. -0.13 points/year for decedents, p < 0.001 for both interactions), and among stroke survivors, larger memory decrements (-0.64 vs. -0.26 points, p < 0.001) at stroke and faster memory decline (-0.15 vs. -0.07 points/year, p = 0.003) after stroke onset, compared to younger adults. Female stroke survivors experienced a faster prestroke memory decline than male stroke survivors (-0.14 vs. -0.10 points/year, p < 0.001). However, no sex differences were seen for other contrasts. Although whites had higher post-stroke memory scores than nonwhites, race was not associated with rate of memory decline during any period of time; i.e. race did not significantly modify the rate of decline before or after stroke or the immediate effect of stroke on memory.

Conclusions

Older age predicted worse memory change before, at and after stroke onset. Sex and race differences in post-stroke memory outcomes might be attributable to prestroke disparities, which may be unrelated to cerebrovascular disease.

There is a consistent association between education and depressive symptoms, but research on the mechanisms to explain this association remains limited. No study has formally evaluated the extent to which the association between education and depressive symptoms is mediated through a foundational skill such as literacy. Inverse odds ratio weighting (IORW) was used to estimate total, natural direct, and natural indirect effects in examining literacy as a mediator of the association between education and depressive symptoms. Health and Retirement Study participants born in the U.S. between 1900 and 1947 were interviewed biennially for up to 12 years (N = 16,718). Literacy was assessed with a brief vocabulary measure. Depressive symptoms were measured using the 8-item Centers for Epidemiologic Studies-Depression (CES-D) scale. Decomposition estimates were derived using regression analyses of repeated measures of depressive symptoms. Standard errors were obtained using a nonparametric bootstrap with the individual as the independent unit to account for dependence of observations within an individual. In a large cohort of older Americans, a one standard deviation difference in educational attainment (~ 3 years) was associated with a 0.35-point decrement in CES-D score (95% CI: -0.38, -0.32). This decrement represents a 0.22 standard deviation difference in depressive symptoms. Using IORW, the estimated effect of education on depressive symptoms mediated through literacy was -0.10 (95% CI: -0.18, -0.01), which represents 28% of the total effect. Education confers many benefits; as demonstrated by this study for depressive symptoms, one important benefit is literacy.

Objective

To test the hypothesis that incipient Alzheimer disease (AD) may adversely affect hearing and that hearing loss may adversely affect cognition, we evaluated whether genetic variants that increase AD risk also increase problem hearing and genetic variants that increase hearing impairment risk do not influence cognition.

Methods

UK Biobank participants without dementia ≥56 years of age with Caucasian genetic ancestry completed a Digit Triplets Test of speech-in-noise hearing (n = 80,074), self-reported problem hearing and hearing with background noise (n = 244,915), and completed brief cognitive assessments. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related polymorphisms. A genetic risk score for hearing (hearing-GRS) was calculated using 3 previously identified polymorphisms related to hearing impairment. Using age-, sex-, and genetic ancestry-adjusted logistic and linear regression models, we evaluated whether the AD-GRS predicted poor hearing and whether the hearing-GRS predicted worse cognition.

Results

Poor speech-in-noise hearing (>-5.5-dB speech reception threshold; prevalence 14%) was associated with lower cognitive scores (ß = -1.28; 95% confidence interval [CI] -1.54 to -1.03). Higher AD-GRS was significantly associated with poor speech-in-noise hearing (odds ratio [OR] 1.06; 95% CI 1.01-1.11) and self-reported problems hearing with background noise (OR 1.03; 95% CI 1.00-1.05). Hearing-GRS was not significantly associated with cognitive scores (ß = -0.05; 95% CI -0.17 to 0.07).

Conclusions

Genetic risk for AD also influences speech-in-noise hearing. We failed to find evidence that genetic risk for hearing impairment affects cognition. AD disease processes or a that shared etiology may cause speech-in-noise difficulty before dementia onset.

Objectives

Compression of morbidity postulates that as the populations age, the age of onset of disease is postponed. The objective of this study is to test for evidence of compression of morbidity in Spain.

Methods

We calculated the age and sex-specific incidence of myocardial infarction, heart failure, cerebrovascular disease, as well as bladder, prostate, breast, lung, and colon cancer among hospital discharges covering 99.5 % of the Spanish population, approximately 40 million inhabitants for two non-overlapping periods, 1997-2000 and 2007-2010, and estimated the length of life spent with disease using the Sullivan method.

Results

We found that expansion of morbidity due to an earlier age-specific onset of incident disease and increase in life expectancy was the norm in Spain. Notable exceptions were cardiovascular disease in women (-0.2 % time spent with disease) and lung cancer for men (-0.9 % time spent with disease) from 1997-2000 to 2007-2010.

Conclusions

Compression of morbidity is often cited by policy makers when discussing adjustments to the health-care system. If morbidity is measured by age at onset of disease, the burden of morbidity has increased in Spain.

Background

To use neuropsychological assessments for studying the underlying disease processes contributing to dementia, it is crucial that they correspond to magnetic resonance imaging (MRI)-based measures of dementia, regardless of educational level.

Methods

French 3-City Dijon MRI study cohort members (n=1782) with assessments of white matter lesion volume (WMLV), hippocampal volume (HCV), and cerebrospinal fluid volume (CSFV), and 6 waves of neuropsychological assessments over 11 years, including Mini-Mental State Examination (MMSE), plus 5 other tests combined using a Z-score or item-response theory (IRT-cognition) comprised the study cohort. We evaluated, testing interactions, whether education modified associations of MRI markers with intercept or rate of change of MMSE, Z-score composite, or IRT-cognition.

Results

In linear models, education modified the associations of WMLV and CSFV with MMSE and CSFV and Z-score composite. In mixed models, education modified the associations of WMLV and CSFV with level of MMSE and the association of HCV with slope of MMSE. Education also modified the association with CSFV and slope of Z-score composite decline. There was no evidence that education modified associations between MRI measures and level or slope of IRT-cognition.

Conclusions

Longitudinal analysis of correctly scaled neuropsychological assessments may provide unbiased proxies for MRI-based measures of dementia risk.

Mendelian Randomization studies, which use genetic instrumental variables (IVs) as quasi-experiments to estimate causal effects, report inconsistent findings regarding effects of body mass index (BMI) on mental health. We used genetic IV to estimate effects of BMI on depression and evaluated validity of a commonly used IV. Female Nurse's Health Study participants (n=6989, average age 56.4, [Standard Deviation 6.91] years at first depression assessment) self-reported BMI, which was averaged across eight reports prior to depression assessment (mean=24.96, SD 4.50). Genetic instruments included fat mass and obesity-associated protein (FTO) alleles, melanocortin receptor 4 (MC4R) alleles, and polygenic risk scores based on 32 established polymorphisms for BMI. Depression was assessed using multiple symptom measures, scaled to the Geriatric Depression Scale 15, averaged across up to 7 biennial waves. We used over-identification tests to assess the validity of genetic IVs. In conventional estimates, each additional BMI point predicted 0.024 (95% Confidence Interval (CI): 0.020-0.029) higher average depression scores. Genetic IV estimates were not significant when based on FTO (beta: 0.064, CI: -0.014, 0.142), MC4R (beta: 0.005, CI: -0.146, 0.156), polygenic score excluding FTO (beta=-0.003, 95%-CI -0.051, 0.045), or mechanism-specific scores. The over-identification test comparing IV estimates based on FTO to estimates based on the polygenic score excluding FTO rejected equality of estimated effects (P=0.014). Results provide no evidence against a null effect of BMI on depression and call into question validity of FTO as an instrument for BMI in Mendelian Randomization studies.

Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.

Introduction

We hypothesized that, like apolipoprotein E (APOE), other late-onset Alzheimer's disease (LOAD) genetic susceptibility loci predict mortality.

Methods

We used a weighted genetic risk score (GRS) from 21 non-APOE LOAD risk variants to predict survival in the Adult Changes in Thought and the Health and Retirement Studies. We meta-analyzed hazard ratios and examined models adjusted for cognitive performance or limited to participants with dementia. For replication, we assessed the GRS-longevity association in the Cohorts for Heart and Aging Research in Genomic Epidemiology, comparing cases surviving to age ≥90 years with controls who died between ages 55 and 80 years.

Results

Higher GRS predicted mortality (hazard ratio = 1.05; 95% confidence interval: 1.00-1.10, P = .04). After adjusting for cognitive performance or restricting to participants with dementia, the relationship was attenuated and no longer significant. In case-control analysis, the GRS was associated with reduced longevity (odds ratio = 0.64; 95% confidence interval: 0.41-1.00, P = .05).

Discussion

Non-APOE LOAD susceptibility loci confer risk for mortality, likely through effects on dementia incidence.