INTRODUCTION:Dementia prevalence is associated with modifiable factors. We quantified the contribution of dementia risk factors in midlife (45-64 years) and late life (≥ 65 years) in the United States. METHODS:Data from six community-based cohorts in the Dementia Risk Prediction Project (DRPP) were used. We estimated risk factor prevalence using nationally representative data. Cohort-specific Cox regression models were used to estimate the association between modifiable risk factors and incident dementia in midlife and late life. Hazard ratios were pooled using meta-analysis then used to calculate population attributable fractions (PAFs) and potential impact fractions. RESULTS:Midlife and late-life risk factors contributed to 22.7% and 16.5% of total dementia cases, respectively. Midlife obesity (PAF: 7.7%; 95% confidence interval [CI]: 4.9%-10.5%), lower education (PAF: 8.1%; 95% CI: 5.2%-11.1%), and late-life physical inactivity (PAF: 10.4%; 95% CI: 6.2%-14.5%) were the greatest contributors. DISCUSSION:Midlife and late-life modifiable risk factors contribute to dementia risk, highlighting a need for interventions across the life course. HIGHLIGHTS:Our sample included 37,931 participants across six pooled, longitudinal US cohorts. We observed midlife and late-life risk factors contributed to 22.7% and 16.5% of dementia cases, respectively. Midlife obesity, late-life physical inactivity, and lower education appear to be the greatest contributors to dementia risk.

Introduction: Cerebral small vessel disease (CSVD) is strongly related to increased risk of stroke and dementia. Long-term exposure to uncontrolled vascular risk factors (VRF), such as systolic and diastolic blood pressure, cigarette smoking, and elevated triglycerides are associated with higher CSVD burden. However, it is unclear whether life stage influences these relationships as the cumulative impact of exposure to VRF may differ depending on the age at which CSVD burden is assessed. Hypothesis: The association between longitudinal VRF trajectories and CSVD burden differs by life stage, with older life stages showing stronger relationships. Methods: Framingham Heart Study participants with six or more repeated VRF measurements during their lifetime and available subsequent brain MRI were included. A multi-marker score quantified CSVD burden by assigning one point to each of the following present MRI markers: cerebral microbleeds, covert infarcts, extensive white matter hyperintensities, cortical superficial siderosis and high burden of perivascular spaces. The score was categorized as 0, 1, 2+ for analysis. Functional principal components analysis was used to summarize VRF trajectories from baseline to MRI assessment. Participants were then grouped by age at MRI (<60, 60–75, >75 years). Within each group, multivariable ordinal logistic regression models were used to assess the association of VRF trajectories and total CSVD score. Results: In 1,614 participants (mean baseline age 33±9 years, 45% male), 134 were younger than 60 years, 840 were between 60-75, and 640 were 75 or older at MRI assessment. After adjusting for age, sex, and cohort, there were no significant associations between VRF trajectories and CSVD score in participants younger than 60. In participants between age 60-75, significant associations were observed with trajectories of systolic and diastolic blood pressure and pulse pressure (p < 0.05), while only trajectories for systolic blood pressure were associated with higher CSVD score in participants older than 75. Conclusions: These findings suggest that the relationship between VRF trajectories and CSVD burden is age-dependent and that the cumulative effects of blood pressure may play a more prominent role in CSVD burden during later life stages. Future research should evaluate whether continuous monitoring of blood pressure and its impact on CSVD burden from mid to late life improves stroke and dementia prevention.

Higher Mediterranean- DASH for Neurodegenerative Delay (MIND) diet scores have previously been associated with larger total brain volume (TBV) in the Framingham Offspring Study (FOS) community-based cohort. We investigated cross-sectional relationships between the MIND diet and structural brain imaging volumes and white matter hyperintensity volume (WMHV) across six community-based cohorts. We analyzed data from 3130 dementia-, stroke- and other neurological disease free adults (aged 65 to 74) who participated in the Atherosclerosis Risk in Communities (ARIC) cohort, Cardiovascular Health Study (CHS), Three City (3C) cohort, FOS cohort, Rotterdam Study (RS) or the Study of Health in Pomerania (SHIP) cohort. Individuals completed a brain magnetic resonance imaging (MRI) scan, and a validated food frequency questionnaire (FFQ) (ARIC, CHS, FOS, RS), 24h dietary recall (3C), or an extensive food list (SHIP). The MIND diet consists of ten healthy (e.g. green leafy vegetables, berries and fish) and five unhealthy (e.g. cheese, red meat and products and fast fried foods) components. Outcomes from brain MRI included TBV, total grey matter volume (TGMV), hippocampal volume (HPV), and WMHV. We used multivariable linear regression to relate MIND diet adherence to the outcomes. Results were combined in meta-analysis using fixed effects and random effects models. Higher MIND diet scores (score range: 0-15) were associated with larger HPV (beta = 0.015, 95% confidence interval = 0.004 to 0.026, cm³ per one unit MIND diet score increase) after adjustment for age, age squared, sex, time from clinical exam to brain MRI exam, total intracranial volume and energy intake, but not with TBV, TGMV and WMHV. Heterogeneity between studies was low (I 2 = 0% TBV, TGMV, HPV) to moderate (I 2 = 44% WMHV). In cross-sectional analyses, higher MIND diet scores were associated with larger HPV, but not with other brain volume measures. It might be that HPV was a more sensitive marker of brain health in the populations under study. Future studies are encouraged to examine the associations between the MIND diet and amyloid and tau positron emission tomography (PET) imaging to elucidate whether a relationship between the MIND diet and dementia pathologies exists.

Peak-width of skeletonized mean diffusivity (PSMD) is an emerging biomarker of cerebral small vessel disease (cSVD)-related vascular contributions to cognitive impairment and dementia (VCID). Higher PSMD values reflect greater white matter microstructural damage, and prior research has related PSMD to sporadic and monogenic forms of cSVD and worse cognitive function. Therefore, we proposed PSMD as a risk stratification biomarker for VCID. This study aimed to perform a rigorous instrumental and biological validation for PSMD in the MarkVCID-1 consortium. Methods to derive PSMD were packaged in a kit containing a protocol, scripts, and instructions. The instrumental validation included a pre-specified plan to assess inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility among MarkVCID-1 participants aged 53-78 years across the spectrum of cSVD. We used intra-class correlations for absolute agreement (ICC AA ) and consistency (ICC C ) to evaluate results, with ICC>0.07 as the pre-specified goal. The biological validation was performed on 7,289 participants of diverse ages and racial/ethnic backgrounds from MarkVCID-1 and population-based cohorts from CHARGE, RUSH, and UCD-ADRC. All sites derived a composite measure of general cognitive function using neuropsychological tests assessing distinct cognitive domains. Finally, we used linear regression models to assess the association between log-PSMD and general cognition adjusting for age, age 2 , sex, and education. Our instrumental validation results (Figure 1) showed excellent reliability between raters from seven sites (overall ICC AA =0.945, P<0.001), agreement between test and retest measurements obtained within two weeks (ICC AA =0.986, P<0.001), and reproducibility across Philips Achieva, Siemens Prisma, and Siemens Trio scanners (ICC C = 0.954, P<0.001). In the biological validation, higher PSMD values were associated with lower general cognitive function in MarkVCID-1 (Beta=-0.82, P<0.001), and these findings were replicated across the CHARGE, RUSH, and UCD-ADRC cohorts (Table 1). Our rigorous instrumental validation study showed excellent inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility for the PSMD kit. We further observed strong associations between higher PSMD values and poorer cognitive function across diverse samples in the biological validation. Taken together, our findings support using PSMD as a robust risk stratification biomarker in multi-site clinical trials of VCID. Additional longitudinal validation studies for PSMD are underway in MarkVCID-2.

PURPOSE OF REVIEW:Late-life depression (LLD) is a prevalent condition and frequently complicated by higher rates of medical comorbidities and cognitive decline. We review the current evidence implicating inflammation in the pathophysiology of LLD and the potential of related molecules and pathways to be used as biomarkers or pharmacological targets. RECENT FINDINGS:A growing body of evidence implicates chronic low-grade inflammation in the pathophysiology and progression of LLD. Inflammatory cytokines, stress-related neuroendocrine pathways, oxidative stress, mitochondrial dysfunction, and blood-brain barrier permeability all synergize with aging to worsen depressive symptoms. Moreover, LLD presents marked biological heterogeneity, with inflammation-related subtypes exhibiting worse clinical outcomes. Several biomarkers and novel therapeutic targets, including cytokines, gut microbiota, and mitochondrial DNA, are identified. SUMMARY:Inflammation is a key modifiable contributor to LLD and may serve as both a biomarker and therapeutic target. Although current clinical trials of anti-inflammatory treatments show promise, findings remain inconsistent. Future research should focus on identifying inflammatory subtypes of LLD and validating personalized, mechanism-based interventions to improve treatment outcomes in aging populations.

Plasma p-tau biomarkers are promising diagnostic tools for widespread clinical use. However, recent studies have raised concerns regarding the effect of common medical comorbidities, such as cardiovascular disease (CVD), on plasma p-tau specificity. These influences must be better understood to enable appropriate clinical use of p-tau181. We sought to evaluate the association between p-tau181 and CVD outcomes in the Framingham Heart Study (FHS), a population-based prospective cohort with deep-phenotyping of CVD. FHS Offspring and Omni 1 Cohort participants have been followed through quadrennial exams with detailed CVD assessment. Plasma p-tau181 was measured from samples of 2543 participants collected in 2011-2014 using Quanterix Simoa, and analyzed as a binary predictor (highest quintile vs remainder). CVD outcomes (binary:yes/no) included overall CVD, congestive heart failure(CHF), coronary heart disease(CHD), stroke/TIA, and peripheral arterial disease(PAD). Multivariate logistic regressions were performed to assess the association between p-tau181 and each prevalent CVD outcome adjusting for age, sex, cohort in base models, and additionally for eGFR, and BMI in adjusted models. Cox regression models were performed to assess the association between p-tau181 and incident CVD outcomes adjusting for similar covariates after a median survival time of 7.0 years [5.9-7.6]). Participant characteristics are displayed in Table 1. Elevated p-tau181 was associated with 74% higher odds of prevalent CHF (OR 1.74; 95%CI[1.02-2.98], p=0.04) in adjusted models (Table 2). Elevated p-tau181 was associated with 41% higher risk of incident overall CVD (HR 1.41[1.03-1.93], p=0.03) and 55% higher risk of incident CHF (1.55[1.03-2.34], p=0.04) in adjusted models (Table 3). There was no association between p-tau181 levels and other CVD outcomes in cross-sectional or longitudinal analyses. Elevated plasma p-tau181 is associated with prevalent and incident CHF and with overall CVD in a community-based population. This aligns with growing evidence of a possible bidirectional relationship between CHF and AD. P-tau levels should be interpreted with caution in patients with CHF until the link between p-tau181 and CHF can be further clarified. Studies to understand systemic diseases that influence plasma AD biomarkers are necessary prior to widespread clinical use, and can reveal new relationships between AD and systemic diseases.

Advancing therapeutic and prevention strategies for vascular contributions to cognitive impairment and dementia (VCID) warrants identifying novel biomarkers. However, due to the high heterogeneity underlying dementia pathology, a single marker may not fully risk-stratify for VCID. A blood-based biomarker of neuroaxonal injury, neurofilament light chain (NfL), and a neuroimaging-based biomarker of white matter microstructural damage on diffusion weighted imaging, peak width of skeletonized mean diffusivity (PSMD), have been related to worse general cognition and proposed as robust biomarkers for cerebral small vessel disease (cSVD). We investigated the joint contribution of NfL and PSMD for improved specificity/sensitivity to identify persons at risk for VCID. Dementia-free participants from the Framingham Offspring Study with cognitive, neuroimaging, and NfL data were included (N=969). NfL was measured in plasma, and PSMD was derived from MRI diffusion weighted imaging. Executive function and general cognitive function were assessed from a neuropsychological battery. NfL and PSMD were dichotomized by the top quartile and combined to indicate a high cSVD burden. The high NfL-PSMD risk category was related to cognitive function using linear regression adjusting for age, age-squared, sex, education, renal function (eGFR), and total intracranial volume. Additional analyses incorporating amyloid PET uptake in 64 participants were performed to discern Alzheimer’s disease pathology from VCID. Higher NfL-PSMD was significantly associated with worse executive (Beta±SE, -0.06±0.02, p=0.002) and general cognitive function (-0.15±0.07, p=0.02). Additionally, amyloid PET over-predicted NfL levels in those with PSMD below the median (observedpredicted, 0.06 (0.33)). Although results were not significant (p=0.15) due to the limited sample, they suggest that amyloid pathology does not explain cSVD burden measured with NfL and PSMD. Our findings suggest combining NfL and PSMD can better risk-stratify those with VCID and poorer cognitive function. This NfL-PSMD multi-biomarker has potential to discriminate vascular dysfunction from Alzheimer’s pathology, improving identification of persons better suited for VCID clinical trials. Utilizing a multi-biomarker approach may improve accuracy for risk stratification of persons bearing covert cerebral vascular injury. Further studies are underway to confirm these findings in larger, diverse samples.

Introduction: Dementia has a long preclinical phase, with pathological and brain changes emerging decades before clinical symptoms appear. Cardiovascular risk factors throughout life contribute to dementia risk, but their effects vary based on their timing and duration. Identifying critical periods of influence is key for developing targeted prevention strategies. Hypothesis: We hypothesize the association between cardiovascular risk factors and dementia varies across the lifespan. Methods: We pooled data for 39,524 individuals from seven cohort studies (Whitehall II, ARIC, CHS, HAAS, MESA, SALSA, and FHS) as part of the Dementia Risk Prediction Pooling Project. We imputed trajectories of body mass index (BMI), systolic blood pressure (SBP), fasting glucose, and cholesterol for each participant starting from age 40 years. Time-weighted average exposures during midlife (ages 40-64 years) and later life (ages 65+ years) were calculated, and hazard ratios for dementia incidence were estimated using Cox proportional hazards models. These models accounted for competing risks of death and were adjusted for sex, race, cohort, educational level, and depressive symptoms. Results: Over a median follow-up of 14 years, there were 5,654 dementia cases and 10,819 deaths. Joint modeling of midlife and late-life risk factors revealed higher BMI, fasting glucose, and cholesterol in midlife were each independently associated with elevated risk of dementia. In contrast, higher late-life values for these factors were associated with lower risk of dementia (Figure). For example, compared to BMI < 20, a BMI ≥ 30 in midlife was associated with a 70% higher risk of dementia, while in late life, it was associated with a 50% lower risk. No association was found between late-life SBP and dementia, but higher midlife SBP was linked to higher risk of dementia. Using rank-based cut offs for risk factors instead of clinical ones did not change the findings. Conclusion: Midlife, but not later-life, levels of cardiovascular risk factors have a stronger effect on dementia risk, highlighting a critical period for intervention.

BACKGROUND:The association between transient ischemic attack (TIA) and dementia is incompletely characterized. Determining the cognitive sequalae of TIA is important as it can function as an early warning sign or additional risk factor for dementia. We sought to determine the long-term incidence of post-TIA dementia and examined whether TIA prompts changes in vascular risk factors. METHODS:Nested matched longitudinal cohort study within the community-based Framingham Heart Study. A prospectively collected sample of participants without dementia or transient ischemic attack were matched on age and sex (5:1) to participants with first incident TIA >60 years. The primary outcome of interest was the 20-year incidence of all-cause dementia. RESULTS:The study matched 297 participants with TIA, 141 (47%) men, mean age 72.7±7.7 years, with 1485 controls without TIA. People with TIA were more likely to have hypertension, coronary heart disease, and atrial fibrillation. Over a median of 8.9 years of follow up, 57 (19%) participants with TIA and 353 (24%) controls without TIA developed dementia (hazard ratio [HR], 0.93 [95% CI, 0.71-1.24], P=0.63). Adjusting for stroke and accounting for the competing risk of death did not alter this association. Participants with TIA were more likely to have a reduction in the frequency of smoking (18% to 11%, P=0.025), an increase in anticoagulant use from 3% to 18%, (P=0.0005), and a marginal increase in aspirin use (46% to 61%, P=0.052). CONCLUSIONS:We found no significant difference in dementia incidence over a 20-year follow-up period compared with matched TIA-free controls. Our findings suggest that TIA prompts treatment changes and behavioral shifts that lower cardiovascular risk. Whether these are sufficient to mitigate subsequent dementia risk remains to be tested in prospective randomized studies.

Recent research has highlighted the importance of sleep on cognitive processes. However, conflicting evidence exists regarding optimal sleep duration and the impact of other co-occurring conditions, such as depression. A diagnosis of depression in mid-life may increase the risk of developing dementia. We examined the association between self-reported sleep duration and cognition and whether depression status modified this relationship. Dementia-and-stroke-free participants 45 years and older from the Framingham Heart Study Third-Generation, Omni 2, and New Off-spring Cohorts were included (n = 1,853; age 49.8[SD 9.2] years; 42.69% male; Table 1 ). Neuropsychological testing assessed verbal learning and memory abilities, abstract reasoning skills, processing speed and visuospatial memory. Depression was defined as having CES-D ≥16 or being under pharmacological treatment (n = 448; 32%). Multivariable linear regression models examined the association between sleep duration categories (≤6h; >6-<9h [reference]; ≥9h), individual cognitive tasks and global cognition, adjusting for age, sex, education and time between sleep and cognitive assessments. A second model included further adjustment for vascular risk factors and APOE4 status. Long sleep duration (≥9h) was associated with worse global cognition (β±SE: -0.24±0.07; p <0.001) compared to average sleep duration. In cognitive domain-specific tasks, long sleep was associated with worse verbal learning and memory abilities (-1.50±0.60, p = 0.013), visuospatial memory (-1.74±0.42, p <0.001), and processing speed (-0.08±0.03, p = 0.014), but not with abstract reasoning skills (-0.06±0.28, p = 0.838). Depression status significantly modified the association (global cognition int. p = 0.015; visual int. p = 0.006; and processing speed int. p = 0.038), where long sleep duration was associated with global cognition (-0.34±0.11; p = 0.003), visuospatial memory (-2.16±0.68; p = 0.002), and processing speed (-0.14±0.05; p = 0.011) in those with depression. Long sleep duration was also associated with visuospatial memory in those without depression (-1.27±0.55, p = 0.022) ( Table 3 ). Short sleep duration (≤6h) was not associated with cognition ( Table 2 ) and did not interact with depression status ( Table 3 ). Long sleep duration was associated with worse cognition particularly among adults with depression, underscoring the complex sleep-mood-cognition interplay. Further research should explore the longitudinal impacts and causal mechanisms of suboptimal sleep. These findings may inform public health promotion of optimal sleep to maintain cognitive health among persons with depression.

Disrupted sleep patterns have been shown to exacerbate Alzheimer's disease (AD) risk, potentially because of sleep's role in memory consolidation and synaptic plasticity. Recent evidence highlights that high brain-derived neurotrophic factor (BDNF) levels, a protein enabling neuroplasticity and memory functions, could play a protective role in age related cognitive impairment. We examined the association between total sleep time and cognition, and BDNF levels as a potential modifier. Third Generation, Omni 2, and New Offspring cohorts from the Framingham Heart Study Exam 2 (2008-2011) were included (n=2,344; age 48(9.1) y; 48%F; Table 1). Self-reported total sleep duration was categorized as: short sleep duration (≤6h), average sleep (7-8h, reference), and long sleep duration (≥9h). A composite measure of global cognition was calculated from neuropsychological tests, including Trails B, visual reproduction (VR), logical memory (LM), and similarities. A multivariable linear regression estimated the association between sleep duration and global cognition, and individual cognitive tasks. We further tested effect modification by BDNF level (median split). Long sleep duration was associated with worse global cognition (β±SE: -2.19 ±0.06; p<.001), compared to average sleep (Table 2). The association between sleep duration and individual cognitive tests are shown in Table 2. BDNF levels significantly modified the association of sleep duration with global cognition (p=0.03). Long sleep duration was associated with poorer global cognition (-0.17±0.08; p=0.04) in persons with lower BDNF, but not in those with higher BDNF levels (Table 3). Finally, short sleep duration was associated with poorer global cognition (-0.1±0.05; p=0.04) only among those with higher BDNF (Table 3). Long sleep duration was associated with poorer global cognition, an effect most notable in those with lower BDNF levels. Short sleep duration was also associated with worse global cognition, but in those with higher BDNF. An appropriate sleep duration may promote neuronal integrity and prevent age-related cognitive disorders. Further studies shall elucidate the role of BDNF in the interplay between sleep duration and cognition.

OBJECTIVE:Accidental falls are the leading cause of injury for older adults in the United States. Identifying risk factors for falls is a public health priority. Poor sleep is prevalent among aging adults and has been linked to falls risk. We examined late-life sleep medication use and falls risk in a cohort of older adults. METHODS:The Atherosclerosis Risk in Communities (ARIC) study is an ongoing community-based cohort study. ARIC participants taking any barbiturates, benzodiazepines, antidepressants, non-benzodiazepine receptor agonists, or other hypnotics in the past 4 weeks (2011-2013) were categorized as taking a medication that affects sleep, regardless of indication. Participant hospital discharge records were reviewed through 2019 for ICD codes indicating incident falls. Propensity score matching was used to match participants who used sleep medications with those who did not (1:2). Cox proportional hazards regression models were used to assess the association of sleep medication use with falls with adjustment for demographics, lifestyle, and health characteristics. RESULTS:In the matched sample (N = 4794; 70% female; mean age 75.5 ± 5 years), 1200 documented falls occurred over 6.5 years of follow-up. In fully adjusted models, sleep medication use was associated with a 33% greater risk of falls compared to nonuse (HR: 1.33; 95% CI: 1.18-1.51). Results did not differ by age, sex, depressive symptoms, baseline cognitive status, or physical functioning status (interaction p-values >.05). CONCLUSIONS:Late-life sleep medication use is associated with a higher risk of falls. Further research is needed to clarify the mechanisms linking sleep medications to falls risk.

STUDY OBJECTIVES:Poor sleep may play a role in the risk of dementia. However, few studies have investigated the association between polysomnography (PSG)-derived sleep architecture and dementia incidence. We examined the relationship between sleep architecture and dementia incidence across five US-based cohort studies from the Sleep and Dementia Consortium. METHODS:Percent of time spent in stages of sleep (N1, N2, N3, rapid eye movement sleep), wake after sleep onset, sleep maintenance efficiency, apnea-hypopnea index, and relative delta power were derived from a single night home-based PSG. Dementia was ascertained in each cohort using its cohort-specific criteria. Each cohort performed Cox proportional hazard regressions for each sleep exposure and incident dementia, adjusting for age, sex, body mass index, antidepressant use, sedative use, and APOE e4 status. Results were then pooled in a random effects model. RESULTS:The pooled sample comprised 4657 participants (30% women) aged ≥ 60 years (mean age was 74 years at sleep assessment). There were 998 (21.4%) dementia cases (median follow-up time of 5 to 19 years). Pooled effects of the five cohorts showed no association between sleep architecture and incident dementia. When pooled analysis was restricted to the three cohorts which had dementia case ascertainment based on DSM-IV/V criteria (n = 2374), higher N3% was marginally associated with an increased risk of dementia (hazard ratio (HR): 1.06; 95%CI: 1.00-1.12, per percent increase N3, p = .050). CONCLUSIONS:There were no consistent associations between sleep architecture measured and the risk of incident dementia. Implementing more nuanced sleep metrics and examination of associations with dementia subtypes remains an important next step for uncovering more about sleep-dementia associations.

INTRODUCTION:This study investigates whether midlife cortisol levels predict Alzheimer's disease (AD) biomarker burden 15 years later, with particular attention to sex differences and menopausal status. METHODS:We analyzed data from 305 cognitively unimpaired Framingham Heart Study participants (48.5% female; mean age: 39.6 ± 8.1 years). Serum cortisol was categorized into tertiles, with amyloid ([11C]PiB) and tau ([18F]Flortaucipir) positron emission tomography (PET) imaging conducted 15 years later. We performed multivariable regression analyses adjusted for confounders including, apolipoprotein E4 (APOE4) status. RESULTS:Elevated midlife cortisol correlated with increased amyloid deposition, specifically in post-menopausal women, predominantly in posterior cingulate, precuneus, and frontal-lateral regions (p < 0.05). No significant associations were observed with tau burden or in males. DISCUSSION:These findings reveal post-menopausal women with high midlife cortisol are at increased risk of AD. Results highlight the importance of identifying early risk factors when biomarkers are detectable but cognitive impairment is absent. HIGHLIGHTS:High midlife cortisol is linked to increased amyloid deposition in post-menopausal women. Cortisol showed no association with tau pathology. Post-menopausal hormone changes may amplify cortisol's effects on amyloid.

INTRODUCTION:We investigated whether depression modified the associations between sleep duration and cognitive performance. METHODS:We examined the associations between sleep duration and cognition in 1853 dementia-and-stroke-free participants (mean age 49.8 years, [range 27-85]; 42.7% male). Participants were categorized into four groups: no depressive symptoms, no antidepressants; depressive symptoms without antidepressant use; antidepressant use without depressive symptoms; and depressive symptoms and antidepressant use. RESULTS:Long sleep was associated with reduced overall cognitive function (β ± standard error = -0.25 ± 0.07, p < 0.001), with strongest effects in those with depressive symptoms using (-0.74 ± 0.30, p = 0.017) and not using antidepressants (-0.60 ± 0.26, p = 0.024). Weaker but significant effects were observed in those without depressive symptoms (-0.18 ± 0.09, p = 0.044). No significant associations were observed in participants using antidepressants without depressive symptoms. DISCUSSION:Associations between sleep duration and cognitive performance are strongest in individuals with depressive symptoms, regardless of antidepressant use. Future research should elucidate underlying mechanisms and temporal relationships. HIGHLIGHTS:Sleeping ≥ 9 hours/night was associated with worse cognitive performance. This association was stronger among those with depression. Long sleepers were more likely to report symptoms of depression. Sleep may be a modifiable risk for cognitive decline in people with depression.

CONTEXT:The influence of sleep and circadian-related factors on metabolic outcomes among Black Americans are under-studied, despite the disparities in both metabolic and sleep health in this population. OBJECTIVE:This work aimed to investigate the relationship between domains of sleep and metabolic dysfunction severity in Black individuals. METHODS:We conducted a cross-sectional analysis of the Jackson Heart Sleep Study (2012-2016), using logistic regression to assess the associations between actigraphy parameters (sleep timing, duration and regularity, continuity) and severe metabolic syndrome (MetS), defined as the highest tertile of a validated sex-, race-, and ethnicity-specific MetS severity Z score. Models were adjusted for age, socioeconomic factors, physical activity, smoking, alcohol use, and moderate to severe obstructive sleep apnea. RESULTS:Among 754 participants (mean age 63 ± 11 years, 66% women, mean body mass index 31.8 ± 6.8), mean sleep onset was 23:10 ± 1:24 (hh:mm), mean sleep duration was 6.7 ± 1.1 hour, median sleep maintenance efficiency was 88.9% (interquartile range [IQR], 85.7-91.5), and median sleep fragmentation index was 28.3% (IQR, 23.2-34). In adjusted models, each 1-hour later in mid-sleep time was associated with 14% (95% CI, 1.01-1.30) higher odds of severe MetS and each 1-hour increase in sleep duration variability was associated with 34% (95% CI, 1.01-1.77) higher odds. Each 1% decrease in sleep maintenance efficiency was associated with 5% (95% CI, 0.92-0.98) higher odds of having severe MetS, and each 1% increase in sleep fragmentation index was associated with 2% (95% CI, 1.01-1.04) higher odds. CONCLUSION:Later sleep timing, irregular sleep duration, and poor sleep continuity were associated with more severe metabolic dysfunction in Black individuals, highlighting the importance of sleep health, beyond sleep duration, on metabolic health.

Introduction: Perivascular Spaces (PVS) visible on brain magnetic resonance imaging (MRI) are markers of Cerebral Small Vessel Disease (CSVD). Recent evidence suggests a potential role of inflammatory biomarkers in the pathogenesis of PVS. This study aimed to examine the relation between inflammation markers and progression of PVS burden in community-dwelling individuals. Methods: Offspring Framingham Heart Study participants with available inflammatory biomarkers at exam 7 and MRI-PVS assessments at exams 7 and 8 were included. Sixteen components of the inflammatory cascade were analyzed at baseline. PVS were rated as low PVS burden (grade I-II) and high PVS burden (grade III-IV) separately in the Basal Ganglia (BG) and Centrum Semiovale (CSO), using a validated method. Progression in PVS burden between exams 7 and 8 were categorized as change (low to high burden) vs no change. Multivariable logistic regression models were used to assess the association between individual inflammatory biomarkers and changes in MRI-PVS burden. Model 1 was adjusted for age and sex, and Model 2 was additionally adjusted for smoking (SMK), diabetes (DM), hypertension (HTN), prevalent cardiovascular disease (CVD), body mass index and apoE4. Results: Among 561 participants (mean age 61.12 ± 8.85 years, 48% male) with an overall low prevalence of vascular risk factors (HTN 37 %, DM 11,15%, SMK 10,87%, CVD 10.34%) we observed that Osteoprotegerin (OPG) levels (mean 5.40 pmol/L ± 1.62) were associated with increase in PVS burden in BG (OR 1.43 [1.08, 1.88] p = 0.01) and CSO (OR 1.32 [1.07, 1.62] p = 0.008). Further adjustment for vascular risk factors did not change this association. No other significant associations were observed. Conclusion: In community dwelling individuals free of stroke and dementia with a low prevalence of vascular risk factors, the inflammatory marker OPG was associated with progression of PVS burden in BG and CSO. Further research is needed to elucidate the specific mechanism behind this association and the potential role of OPG as treatment target to mitigate the inflammatory processes contributing to PVS and its adverse consequences.