Overcoming Data Gaps in Life Course Epidemiology by Matching Across Cohorts.

Life course epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages in the same individuals. We describe when the effect of an exposure ( A ) on an outcome ( Y ) in a target population is identifiable in a combined ("synthetic") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures of Y . We enumerate causal assumptions needed for unbiased effect estimation in the synthetic cohort and illustrate by simulating target populations under four causal models. From each target population, we randomly sampled early- and late-life cohorts and created a synthetic cohort by matching individuals from the two cohorts based on mediators and confounders. We estimated the effect of A on Y in the synthetic cohort, varying matching variables, the match ratio, and the strength of association between matching variables and A . Finally, we compared bias in the synthetic cohort estimates when matching variables did not d-separate A and Y to the bias expected in the original cohort. When the set of matching variables includes all variables d-connecting exposure and outcome (i.e., variables blocking all backdoor and front-door pathways), the synthetic cohort yields unbiased effect estimates. Even when matching variables did not fully account for confounders, the synthetic cohort estimate was sometimes less biased than comparable estimates in the original cohort. Methods based on merging cohorts may hasten the evaluation of early- and mid-life determinants of late-life health but rely on available measures of both confounders and mediators.

Representativeness of Participants in the ACCORD Trial Compared to Middle-aged and Older Adults Living with Diabetes in the United States.

BACKGROUND: We evaluated whether participants in the landmark Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial represent US adults aged ≥40 with diabetes. METHODS: Using the nationally representative 2017-2020 prepandemic National Health and Nutrition Examination Survey data, we made operational definitions of ACCORD eligibility criteria. We calculated the percentage of individuals aged ≥40 with diabetes and HbA1c ≥ 6.0% or ≥ 7.5% who met operational ACCORD eligibility criteria. RESULTS: Applying survey sampling weights to 715 National Health and Nutrition Examination Survey participants aged ≥40 with diabetes and HbA1c ≥ 6.0% (representing 29,717,406 individuals), 12% (95% confidence interval [CI] = 8%, 18%) met the operational ACCORD eligibility criteria. Restricting to HbA1c ≥ 7.5%, 39% (95% CI = 28%, 51%) of respondents met the operational ACCORD eligibility criteria. CONCLUSIONS: ACCORD represented a minority of US middle-aged and older adults with diabetes. Given the differential risk profile between ACCORD participants and the general population with diabetes, extrapolating the trial findings may not be appropriate.

A Critique and Examination of the Polysocial Risk Score Approach: Predicting Cognition in the Health and Retirement Study.

Polysocial risk scores were recently proposed as a strategy to improve clinical relevance of knowledge about social determinants of health. The objective of this paper was to assess if the polysocial risk score model improves prediction of cognition and all-cause mortality in middle-aged and older adults beyond simpler models including a smaller set of key social determinants of health. We used a sample of 13,773 individuals aged 50+ at baseline from the 2006 to 2018 waves of the Health and Retirement Study, a US population-based longitudinal cohort. Four linear mixed models were compared: two simple models including a priori selected covariates and two polysocial risk score models which used LASSO regularization to select covariates among 9 or 21 candidate social predictors. All models included age. Predictive accuracy was assessed via R-squared and root mean-squared prediction error (RMSPE) using training/test split and cross-validation. For predicting cognition, the simple model including age, race, gender, and education had an R-squared of 0.31 and an RMSPE of 0.880. Compared with this, the most complex polysocial risk score selected 12 predictors (R-squared=0.35 and RMSPE=0.858; 2.2% improvement). For all-cause mortality, the simple model including age, race, gender, and education had an AUROC of 0.747, while the most complex polysocial risk score did not demonstrate improved performance (AUROC = 0.745). Models built on a smaller set of key social determinants performed comparably to models built on a more complex set of social "risk factors".

Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

The Association Between Physical Activity and Cognition in a Racially/Ethnically Diverse Cohort of Older Adults: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

OBJECTIVE: Most prior research on physical activity (PA) and cognition is based on predominantly white cohorts and focused on associations of PA with mean (average) cognition versus the distribution of cognition. Quantile regression offers a novel way to quantify how PA affects cognition across the entire distribution. METHODS: The Kaiser Healthy Aging and Diverse Life Experiences study includes 30% white, 19% black, 25% Asian, and 26% Latinx adults age 65+ living in Northern California (n = 1600). The frequency of light or heavy PA was summarized as 2 continuous variables. Outcomes were z-scored executive function, semantic memory, and verbal episodic memory. We tested associations of PA with mean cognition using linear regression and used quantile regression to estimate the association of PA with the 10th-90th percentiles of cognitive scores. RESULTS: Higher levels of PA were associated with higher mean semantic memory (b = 0.10; 95% CI: 0.06, 0.14) and executive function (b = 0.05; 95% CI: 0.01, 0.09). Associations of PA across all 3 cognitive domains were stronger at low quantiles of cognition. CONCLUSION: PA is associated with cognition in this racially/ethnically diverse sample and may have larger benefits for individuals with low cognitive scores, who are most vulnerable to dementia.

Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants.

INTRODUCTION: We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults. METHODS: Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume. RESULTS: AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices. DISCUSSION: APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Association of cancer history with structural brain aging markers of Alzheimer's disease and related dementias risk.

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed-effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = -19 mm3 , 95% CI = -36, -1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = -0.004 mm, 95% CI = -0.007, -0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. HIGHLIGHTS: We found no evidence of an inverse association between cancer history and ADRD-related neurodegeneration. Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region. Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history.

Low- and High-Density Lipoprotein Cholesterol and Dementia Risk Over 17 Years of Follow-up Among Members of a Large Health Care Plan.

BACKGROUND AND OBJECTIVES: The associations of high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) with dementia risk in later life may be complex, and few studies have sufficient data to model nonlinearities or adequately adjust for statin use. We evaluated the observational associations of HDL-C and LDL-C with incident dementia in a large and well-characterized cohort with linked survey and electronic health record (EHR) data. METHODS: Kaiser Permanente Northern California health plan members aged 55 years and older who completed a health behavior survey between 2002 and 2007, had no history of dementia before the survey, and had laboratory measurements of cholesterol within 2 years after survey completion were followed up through December 2020 for incident dementia (Alzheimer disease-related dementia [ADRD]; Alzheimer disease, vascular dementia, and/or nonspecific dementia) based on ICD-9 or ICD-10 codes in EHRs. We used Cox models for incident dementia with follow-up time beginning 2 years postsurvey (after cholesterol measurement) and censoring at end of membership, death, or end of study period. We evaluated nonlinearities using B-splines, adjusted for demographic, clinical, and survey confounders, and tested for effect modification by baseline age or prior statin use. RESULTS: A total of 184,367 participants [mean age at survey = 69.5 years, mean HDL-C = 53.7 mg/dL (SD = 15.0), mean LDL-C = 108 mg/dL (SD = 30.6)] were included. Higher and lower HDL-C values were associated with elevated ADRD risk compared with the middle quantile: HDL-C in the lowest quintile was associated with an HR of 1.07 (95% CI 1.03-1.11), and HDL-C in the highest quintile was associated with an HR of 1.15 (95% CI 1.11-1.20). LDL-C was not associated with dementia risk overall, but statin use qualitatively modified the association. Higher LDL-C was associated with a slightly greater risk of ADRD for statin users (53% of the sample, HR per 10 mg/dL increase = 1.01, 95% CI 1.01-1.02) and a lower risk for nonusers (HR per 10 mg/dL increase = 0.98; 95% CI 0.97-0.99). There was evidence for effect modification by age with linear HDL-C (p = 0.003) but not LDL-C (p = 0.59). DISCUSSION: Both low and high levels of HDL-C were associated with elevated dementia risk. The association between LDL-C and dementia risk was modest.

Metformin Cessation and Dementia Incidence.

Importance: Prior studies suggested that metformin may be associated with reduced dementia incidence, but associations may be confounded by disease severity and prescribing trends. Cessation of metformin therapy in people with diabetes typically occurs due to signs of kidney dysfunction but sometimes is due to less serious adverse effects associated with metformin. Objective: To investigate the association of terminating metformin treatment for reasons unrelated to kidney dysfunction with dementia incidence. Design, Setting, and Participants: This cohort study was conducted at Kaiser Permanente Northern California, a large integrated health care delivery system, among a cohort of metformin users born prior to 1955 without history of diagnosed kidney disease at metformin initiation. Dementia follow-up began with the implementation of electronic health records in 1996 and continued to 2020. Data were analyzed from November 2021 through September 2023. Exposures: A total of 12 220 early terminators, individuals who stopped metformin with normal estimated glomerular filtration rate (eGFR), were compared with routine metformin users, who had not yet terminated metformin treatment or had terminated (with or without restarting) after their first abnormal eGFR measurement. Early terminators were matched with routine users of the same age and gender who had diabetes for the same duration. Main outcomes and measures: The outcome of interest was all-cause incident dementia. Follow-up for early terminators and their matched routine users was started at age of termination for the early terminator. Survival models adjusted for sociodemographic characteristics and comorbidities at the time of metformin termination (or matched age). Mediation models with HbA1c level and insulin usage 1 and 5 years after termination tested whether changes in blood glucose or insulin usage explained associations between early termination of metformin and dementia incidence. Results: The final analytic sample consisted of 12 220 early terminators (5640 women [46.2%]; mean [SD] age at start of first metformin prescription, 59.4 [9.0] years) and 29 126 routine users (13 582 women [46.6%]; mean [SD] age at start of first metformin prescription, 61.1 [8.9] years). Early terminators had 1.21 times the hazard of dementia diagnosis compared with routine users (hazard ratio, 1.21; 95% CI, 1.12 to 1.30). In mediation analysis, contributions to this association by changes in HbA1c level or insulin use ranged from no contribution (0.00 years; 95% CI, -0.02 to 0.02 years) for insulin use at 5 years after termination to 0.07 years (95% CI, 0.02 to 0.13 years) for HbA1c level at 1 year after termination, suggesting that the association was largely independent of changes in HbA1c level and insulin usage. Conclusions and Relevance: In this study, terminating metformin treatment was associated with increased dementia incidence. This finding may have important implications for clinical treatment of adults with diabetes and provides additional evidence that metformin is associated with reduced dementia risk.

Using an Online Panel to Crosswalk Alternative Measures of Alcohol Use As Fielded in Two National Samples.

Introduction: Accurate estimation of the health effects of drinking is hampered by inconsistent phrasing of questions about alcohol use in commonly-used health surveys (e.g., HRS, NYLS79), and measurement error in brief self-reports of drinking. We fielded an online survey to a diverse pool of respondents, assessing two versions of alcohol use questions. We used the measurement survey responses to evaluate correspondence across question versions and create a crosswalk between versions of alcohol questions from two different nationally representative studies of middle-aged adults. The measurement model can also be used to incorporate measurement error correction. Methods: Respondents to two measurement survey platforms (Centiment and Qualtrics) were asked drinking frequency and quantity questions as phrased in the Health and Retirement Study (HRS: average days per week drank in the last 3 months; quantity consumed on days drank in the last 3 months) and differently phrased questions from the National Longitudinal Survey of Youth 1979 (NLSY79: days drank in last 30 days, average quantity consumed on days drank). The order in which respondents encountered different versions of the questions was randomized. From these questions, we derived measures of average weekly alcohol consumption. In the online panel data, we regressed responses to the HRS question on responses to the NLSY question and vice versa to create imputation models. HRS (n=14,639) and NLSY79 (n=7,069) participants aged 50-59 self-rated their overall health (range 0-4, 0=excellent and 4=poor). NLSY79 or HRS participants' responses to the alcohol question from the other survey were multiply imputed (k=30) using the measurement model from the measurement survey participant data (k=30). We regressed self-rated health on each alcohol measure and estimated covariate-adjusted coefficients from observed and imputed versions of the questions. Results: The measurement survey (n=2,070) included respondents aged 50+; 64.8% female; 21.4% Hispanic, 23.95% Black, 27.1% White, and 27.6% another ("Other") self-reported racial/ethnic identity. Associations of observed alcohol question responses with self-reported health were slightly smaller than associations of imputed responses for frequency of alcohol use and consumption on days when alcohol was used. For example, using the HRS version of the frequency of alcohol use (days per week), the estimate for the observed question in HRS respondents was ꞵ =-0.045 [-0.055,-0.036]; and the estimate for the imputed version of the HRS question in NLSY79 respondents was ꞵ=-0.051 [-0.065,-0.037]. The estimated effect of average drinks per week was substantially larger for the imputed version of the measure (ꞵ for the observed question in HRS=-0.002 [-0.004,0.001], ꞵ for the imputed version of the HRS measure in NLSY79 respondents=-0.02 [-0.027,-0.012]). Patterns were similar when using the NLSY79 versions of questions as reported in NLSY79 and imputed for HRS respondents. For example, the estimated effect of average drinks per week was substantially larger for the imputed version of the NLSY79 question (ꞵ for the observed question in NLSY79=-0.006 [-0.01,-0.002], ꞵ for the imputed version of the HRS question in NLSY79 respondents=-0.019 [-0.027,-0.01]). Conclusions: Measurement inconsistencies and imperfect reliability are major challenges in estimating effects of alcohol use on health. Collecting additional data using online panels is a feasible and flexible approach to quantifying measurement differences. This approach may enable measurement error corrections, improve meta-analyses, and promote evidence triangulation.

Sex-specific effect of P2Y2 purinergic receptor on glucose metabolism during acute inflammation.

The sex of an animal impacts glucose sensitivity, but little information is available regarding the mechanisms causing that difference, especially during acute inflammation. We examined sex-specific differences in the role of the P2Y2 receptor (P2Y2R) in glucose flux with and without LPS challenge. Male and female wild-type and P2Y2R knockout mice (P2Y2R-/-) were injected with LPS or saline and glucose tolerance tests (GTT) were performed. P2Y2R, insulin receptor, and GLUT4 transporter gene expression was also evaluated. Female mice had reduced fasting plasma glucose and females had reduced glucose excursion times compared to male mice during GTT. P2Y2R-/- males had significantly decreased glucose flux throughout the GTT as compared to all female mice. Acute inflammation reduced fasting plasma glucose and the GTT area under the curve in both sexes. While both wild-type and P2Y2R-/- male animals displayed reduced fasting glucose in LPS treatment, female mice did not have significant difference in glucose tolerance, suggesting that the effects of P2Y2R are specific to male mice, even under inflammatory conditions. Overall, we conclude that the role for the purinergic receptor, P2Y2R, in regulating glucose metabolism is minimal in females but plays a large role in male mice, particularly in the acute inflammatory state.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias.

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Comparison of Imputation Strategies for Incomplete Longitudinal Data in Life-Course Epidemiology.

Incomplete longitudinal data are common in life-course epidemiology and may induce bias leading to incorrect inference. Multiple imputation (MI) is increasingly preferred for handling missing data, but few studies explore MI-method performance and feasibility in real-data settings. We compared 3 MI methods using real data under 9 missing-data scenarios, representing combinations of 10%, 20%, and 30% missingness and missing completely at random, at random, and not at random. Using data from Health and Retirement Study (HRS) participants, we introduced record-level missingness to a sample of participants with complete data on depressive symptoms (1998-2008), mortality (2008-2018), and relevant covariates. We then imputed missing data using 3 MI methods (normal linear regression, predictive mean matching, variable-tailored specification), and fitted Cox proportional hazards models to estimate effects of 4 operationalizations of longitudinal depressive symptoms on mortality. We compared bias in hazard ratios, root mean square error, and computation time for each method. Bias was similar across MI methods, and results were consistent across operationalizations of the longitudinal exposure variable. However, our results suggest that predictive mean matching may be an appealing strategy for imputing life-course exposure data, given consistently low root mean square error, competitive computation times, and few implementation challenges.

Discordance in chromosomal and self-reported sex in the UK Biobank: Implications for transgender- and intersex-inclusive data collection.

There is growing need to distinguish between sex and gender. While sex is assigned at birth, gender is socially constructed and may not correspond to one's assigned sex. However, in most research studies, sex or gender is assessed in isolation or the terms are used interchangeably, which has implications for research accuracy and inclusivity. We used data from the UK Biobank to quantify the prevalence of disagreement between chromosomal and self-reported sex and identify potential reasons for discordance. Among approximately 200 individuals with sex discordance, 71% of discordances were potentially explained by the presence of intersex traits or transgender identity. The findings indicate that when describing sex- and/or gender-specific differences in health, researchers may be limited in their ability to draw conclusions regarding specific sex and/or gender health information.

Propensity Scores in Health Disparities Research: The Example of Cognitive Aging and the Hispanic Paradox.

BACKGROUND: Individuals of Mexican ancestry in the United States experience substantial socioeconomic disadvantages compared with non-Hispanic white individuals; however, some studies show these groups have similar dementia risk. Evaluating whether migration selection factors (e.g., education) associated with risk of Alzheimer disease and related dementia (ADRD) explain this paradoxical finding presents statistical challenges. Intercorrelation of risk factors, common with social determinants, could make certain covariate patterns very likely or unlikely to occur for particular groups, which complicates their comparison. Propensity score (PS) methods could be leveraged here to diagnose nonoverlap and help balance exposure groups. METHODS: We compare conventional and PS-based methods to examine differences in cognitive trajectories between foreign-born Mexican American, US-born Mexican American, and US-born non-Hispanic white individuals in the Health and Retirement Study (1994-2018). We examined cognition using a global measure. We estimated trajectories of cognitive decline from linear mixed models adjusted for migration selection factors also associated with ADRD risk conventionally or with inverse probability weighting. We also employed PS trimming and match weighting. RESULTS: In the full sample, where PS overlap was poor, unadjusted analyses showed both Mexican ancestry groups had worse baseline cognitive scores but similar or slower rates of decline compared with non-Hispanic white adults; adjusted findings were similar, regardless of method. Focusing analyses on populations where PS overlap was improved (PS trimming and match weighting) did not alter conclusions. CONCLUSIONS: Attempting to equalize groups on migration selection and ADRD risk factors did not explain paradoxical findings for Mexican ancestry groups in our study.

Melatonin: Both a Messenger of Darkness and a Participant in the Cellular Actions of Non-Visible Solar Radiation of Near Infrared Light.

Throughout the history of melatonin research, almost exclusive focus has been on nocturnally-generated pineal melatonin production, which accounts for its circadian rhythm in the blood and cerebrospinal fluid; these light/dark melatonin cycles drive the daily and seasonal photoperiodic alterations in organismal physiology. Because pineal melatonin is produced and secreted primarily at night, it is referred to as the chemical expression of darkness. The importance of the other sources of melatonin has almost been ignored. Based on current evidence, there are at least four sources of melatonin in vertebrates that contribute to the whole-body melatonin pool. These include melatonin produced by (1) the pineal gland; (2) extrapineal cells, tissues, and organs; (3) the microbiota of the skin, mouth, nose, digestive tract, and vagina as well as (4) melatonin present in the diet. These multiple sources of melatonin exhibit differentially regulated mechanisms for its synthesis. Visible light striking the retina or an intense physical stimulus can suppress nocturnal pineal melatonin levels; in contrast, there are examples where extrapineal melatonin levels are increased during heavy exercise in daylight, which contains the whole range of NIR radiation. The cumulative impact of all cells producing augmented extrapineal melatonin is sufficient to elevate sweat concentrations, and potentially, if the exposure is sustained, to also increasing the circulating values. The transient increases in sweat and plasma melatonin support the premise that extrapineal melatonin has a production capacity that exceeds by far what can be produced by the pineal gland, and is used to maintain intercellular homeostasis and responds to rapid changes in ROS density. The potential regulatory mechanisms of near infrared light (NIR) on melatonin synthesis are discussed in detail herein. Combined with the discovery of high levels of melanopsin in most fat cells and their response to light further calls into question pineal centric theories. While the regulatory processes related to microbiota-derived melatonin are currently unknown, there does seem to be crosstalk between melatonin derived from the host and that originating from microbiota.

Associations Between Handgrip Strength and Dementia Risk, Cognition, and Neuroimaging Outcomes in the UK Biobank Cohort Study.

Importance: The associations between muscle strength and cognitive outcomes have sparked interest in interventions that increase muscle strength for prevention of dementia, but the associations between muscle strength and cognitive aging are unclear, particularly among middle-aged adults. Objective: To evaluate the association between handgrip strength (HGS) and dementia, reduced cognition, and poorer neuroimaging outcomes in a UK population of middle-aged adults. Design, Setting, and Participants: This cohort study evaluated UK Biobank participants aged 39 to 73 years enrolled from 2006 to 2010 with measured HGS and prospectively followed up for dementia diagnosis. Data were analyzed from October 2021 to April 2022. Exposures: HGS assessed in both hands via dynamometer. Main Outcomes and Measures: Outcomes included cognitive test scores (fluid intelligence and prospective memory), brain magnetic resonance imaging measures (total brain volume, white matter hyperintensity, and hippocampal volume), and incident dementia (all-cause, vascular, and Alzheimer disease [AD] from primary care, hospital, or death records) over a median (IQR) of 11.7 (11.0-12.4) years of follow-up. Mixed-effects linear and logistic regressions and Cox proportional-hazard models were used to estimate associations, stratified by gender and adjusted for covariates. Estimates are presented per 5-kg decrement in HGS. To evaluate reverse causation, we assessed whether a polygenic risk score for AD is associated with HGS. Results: A subsample of 190 406 adult participants in the UK Biobank (mean [SD] age, 56.5 [8.1] years; 102 735 women [54%]) were evaluated. A 5-kg decrement in HGS was associated with lower fluid intelligence scores in men (ß, -0.007; 95% CI, -0.010 to -0.003) and women (ß, -0.04; 95% CI, -0.05 to -0.04. A 5-kg decrement in HGS was associated with worse odds of correctly responding to a prospective memory task for men (odds ratio, 0.91; 95% CI, 0.90 to 0.92) and women (odds ratio, 0.88; 95% CI, 0.87 to 0.90). A 5-kg decrement in HGS was associated with greater white matter hyperintensity volume in men (ß, 92.22; 95% CI, 31.09 to 153.35) and women (ß, 83.56; 95% CI, 13.54 to 153.58). A 5-kg decrement in HGS was associated with incident dementia for men (hazard ratio, 1.20; 95% CI, 1.12 to 1.28) and women (hazard ratio, 1.12; 95% CI, 1.00 to 1.26). The AD genetic risk score was not significantly associated with HGS. Conclusions and Relevance: These findings suggest that HGS is associated with measures of neurocognitive brain health among men and women and they add to a growing body of research indicating that interventions designed to increase muscle strength, particularly among middle-aged adults, may hold promise for the maintenance of neurocognitive brain health.

Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife.

Importance: Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis. Objective: To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference. Design, Setting, and Participants: This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022. Exposure: The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations. Main Outcomes and Measures: Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change. Results: A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures. Conclusions and Relevance: In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.

Association of Social Integration with Cognitive Status in a Multi-Ethnic Cohort: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

We evaluated overall and race-specific relationships between social integration and cognition in older adults. Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) cohort participants included 1343 Asian, Black, Latino, or non-Latino White Kaiser Permanente Northern California members. We estimated the effect of social integration on verbal episodic memory, semantic memory, and executive function derived from the Spanish and English Neuropsychological Assessment (SENAS) Scales. Social integration scores included marital status; volunteer activity; and contact with children, relatives, friends, and confidants. We estimated covariate-adjusted linear mixed-effects models for baseline and 17-month follow-up cognition. Social integration was associated with higher baseline cognitive scores (average  ß = 0.066 (95% confidence interval: 0.040, 0.092)) overall and in each racial/ethnic group. The association did not vary by race/ethnicity. Social integration was not associated with the estimated rate of cognitive change. In this cohort, more social integration was similarly associated with better late-life cognition across racial/ethnic groups.

The Role of Dementia Diagnostic Delay in the Inverse Cancer-Dementia Association.

BACKGROUND: Cancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history. METHODS: We used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to U.S. population and cohort data. We varied the average lapse between dementia onset and diagnosis, including nondifferential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis. RESULTS: Nondifferential dementia diagnosis delay introduced minimal bias (IRRs = 0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR = 0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias. CONCLUSIONS: Delays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.