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Comprehensive long-term data on atrial fibrillation trends in men and women are scant. We aimed to provide such data through analysis of the Framingham cohort over 50 years. We investigated trends in incidence, prevalence, and risk factors for atrial fibrillation and its association with stroke and mortality after onset in 9511 participants enrolled in the Framingham Heart Study between 1958 and 2007. We analysed trends within 10 year groups (1958–67, 1968–77, 1978–87, 1988–97, and 1998–2007), stratified by sex. During 50 years of observation (202 417 person-years), 1544 cases of new-onset atrial fibrillation occurred (of whom 723 [47%] were women). Between 1958–67 and 1998–2007, age-adjusted prevalence of atrial fibrillation quadrupled from 20·4 to 96·2 cases per 1000 person-years in men and from 13·7 to 49·4 cases per 1000 person-years in women; age-adjusted incidence increased from 3·7 to 13·4 new cases per 1000 person-years in men and from 2·5 to 8·6 new cases per 1000 person-years in women (ptrend<0·0001 for all comparisons). For atrial fibrillation diagnosed by electrocardiograph (ECG) during routine Framingham examinations, age-adjusted prevalence per 1000 person-years increased (12·6 in 1958–67 to 25·7 in 1998–2007 in men, ptrend=0·0007; 8·1 to 11·8 in women, ptrend=0·009). However, age-adjusted incidence of atrial fibrillation by Framingham Heart Study ECGs did not change significantly with time. Although the prevalence of most risk factors changed over time, their associated hazards for atrial fibrillation changed little. Multivariable-adjusted proportional hazards models revealed a 74% (95% CI 50–86%) decrease in stroke (hazards ratio [HR] 3·77, 95% CI 1·98–7·20 in 1958–1967 compared with 1998–2007; ptrend=0·0001) and a 25% (95% CI −3–46%) decrease in mortality (HR 1·34, 95% CI 0·97–1·86 in 1958–1967 compared with 1998–2007; ptrend=0·003) in 20 years following atrial fibrillation onset. Trends of increased incidence and prevalence of atrial fibrillation in the community were probably partly due to enhanced surveillance. Measures are needed to enhance early detection of atrial fibrillation, through increased awareness coupled with targeted screening programmes and risk factor-specific prevention. NIH, NHLBI, NINDS, Deutsche Forschungsgemeinschaft.

Objectives: To refine mild cognitive impairment (MCI) diagnostic criteria, we examined progression to dementia using two approaches to identifying MCI. Methods: A total of 1203 Framingham Heart Study participants were classified at baseline as cognitively normal or MCI (overall and four MCI subtypes) via conventional Petersen/Winblad criteria (single cognitive test impaired per domain, >1.5 SD below expectations) or Jak/Bondi criteria (two tests impaired per domain, >1 SD below norms). Cox proportional hazards models were constructed to examine the association between each MCI definition and incident dementia. Results: The Petersen/Winblad criteria classified 34% of participants as having MCI while the Jak/Bondi criteria classified 24% as MCI. Over a mean follow-up of 9.7 years, 58 participants (5%) developed incident dementia. Both MCI criteria were associated with incident dementia [Petersen/Winblad: hazards ratio (HR) = 2.64; p-value=.0002; Jak/Bondi: HR=3.30; p-value <.0001]. When both MCI definitions were included in the same model, only the Jak/Bondi definition remained statistically significantly associated with incident dementia (HR=2.47; p-value=.008). Multi-domain amnestic and single domain non-amnestic MCI subtypes were significantly associated with incident dementia for both diagnostic approaches (all p-values <.01). Conclusions: The Jak/Bondi MCI criteria had a similar association with dementia as the conventional Petersen/Winblad MCI criteria, despite classifying ~30% fewer participants as having MCI. Further exploration of alternative methods to conventional MCI diagnostic criteria is warranted. (JINS, 2016, 22, 937–943)

To determine whether classes of diabetes medications are associated with cognitive health and dementia risk, above and beyond their glycemic control properties. Findings were pooled from 5 population-based cohorts: the Framingham Heart Study, the Rotterdam Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Aging Gene-Environment Susceptibility-Reykjavik Study (AGES) and the Sacramento Area Latino Study on Aging (SALSA). Differences between users and non-users of insulin, metformin and sulfonylurea were assessed in each cohort for cognitive and brain MRI measures using linear regression models, and cognitive decline and dementia/AD risk using mixed effect models and Cox regression analyses, respectively. Findings were then pooled using meta-analytic techniques, including 3,590 individuals with diabetes for the prospective analysis. After adjusting for potential confounders including indices of glycemic control, insulin use was associated with increased risk of new-onset dementia (pooled HR (95% CI) = 1.58 (1.18, 2.12);p = 0.002) and with a greater decline in global cognitive function (β = -0.014±0.007;p = 0.045). The associations with incident dementia remained similar after further adjustment for renal function and excluding persons with diabetes whose treatment was life-style change only. Insulin use was not related to cognitive function nor to brain MRI measures. No significant associations were found between metformin or sulfonylurea use and outcomes of brain function and structure. There was no evidence of significant between-study heterogeneity. Despite its advantages in controlling glycemic dysregulation and preventing complications, insulin treatment may be associated with increased adverse cognitive outcomes possibly due to a greater risk of hypoglycemia.

Fibroblast growth factor 23 is an emerging vascular biomarker, recently associated with cerebral small vessel disease and poor cognition in patients on dialysis. It also interacts with klotho, an anti-aging and cognition enhancing protein. To determine if circulating Fibroblast growth factor 23 (FGF23) is associated with new-onset cognitive outcomes in a community-based cohort of cognitively healthy adults with long-term follow-up. We measured serum FGF23 levels in 1537 [53% women, mean age 68.7 (SD 5.7)] dementia-free Framingham Offspring participants at their 7th quadrennial examination (1998-2001), and followed these participants for the development of clinical all-cause dementia and Alzheimer's disease (AD). Secondary outcomes included MRI-based structural brain measures, and neurocognitive test performance at exam 7. During a median (Q1, Q3) 12-year (7.0, 13.3) follow up, 122 (7.9%) participants developed dementia, of whom 91 (5.9%) had AD. Proportional-hazards regression analysis, adjusted for age, sex, education, systolic blood pressure, antihypertensive medication, prevalent cardiovascular disease, diabetes mellitus, smoking status and apoE ε4 carrier status, revealed that higher serum FGF23 levels were associated with an increased risk of incident dementia and AD (Hazard ratio [HR] per 1 standard deviation increment in inverse transformed FGF23 level 1.25, 95% CI 1.02-1.53, and 1.32, 95% CI 1.04-1.69, respectively). There was no significant interaction according to presence/absence of significant renal impairment (eGFR <30 versus ≥30ml/min) and risk of dementia (based on 1537; p = 0.97). Higher circulating FGF23 is associated with an increased risk of dementia, suggesting that FGF23-related biological pathways may play a role in the development of dementia.

ABSTRACT Background and Aims Lower occupational cognitive complexity (OCC) and physical inactivity have been associated with advanced brain aging and cognitive decline in older adulthood. We examined whether the association of occupational sedentary time with cognitive function remains after adjustment for OCC and education. Methods In this cross‐sectional study, we included participants from the Framingham Heart Study who did not have dementia, were not retired or unemployed, and completed the neuropsychology and occupation assessments, and wore an accelerometer for at least 3 days (n = 1821, 47% men, mean age 48.5). Three cognitive function assessments were used: logical memory delayed recall (LMD), Weschler Adult Intelligence Scale (WAIS) similarities subtest (SIM), and Trail Making Test B minus A (Trails B‐A). Lastly, OCC was measured using data from the U.S. Department of Labor's Occupational Information Network (O*NET). Analysis of covariance (ANCOVA) models were used to evaluate the association of occupational sedentary time (independent variable) with cognitive function (dependent variable), including models adjusting for age, sex, leisure time physical activity (LTPA), education, and OCC. Results Higher self‐reported occupational sedentary time (“often/always” compared to “never/seldom”) was associated with higher cognitive function after adjusting for age, sex, and LTPA (beta = 0.72 [SE = 0.21], 0.76 [0.18], and 0.04 [0.01], for LMD, SIM, Trails B‐A, respectively, all with p < 0.001). OCC was also associated with higher cognitive function. When additionally adjusting for education and OCC, the association of occupational sedentary time with cognitive performance was attenuated and no longer statistically significant for LMD and SIM (beta= 0.18 [SE = 0.22], 0.11 [0.19], p > 0.05). Conclusion Our findings indicate that the association of higher occupational sedentary time with higher cognitive function was partially explained by a combination of higher OCC and education level. Occupations with higher OCC, may contribute to cognitive resilience despite these occupations being more sedentary. Summary Our results suggest that occupational cognitive complexity partially explains the positive association of occupational sitting time and cognitive function in middle‐aged adults. Individuals with more cognitively complex occupations spend more time sitting at work and performed better on cognitive function tests, even after adjusting for the higher educational status often required to obtain cognitively complex occupations. The context for sedentary behaviors (whether they are cognitively engaging or not) is an important consideration not typically studied when investigating the complex relationships among physical activity, sedentary time, and brain health.

Physical activity (PA) may play a role in maintenance of cognitive function in both middle and older ages and prevention of outcomes such as dementia and Alzheimer's disease. Cross-sectional regression analyses were performed in Framingham Heart Study Third Generation (n = 1861) and Offspring (n = 909) cohort participants assessing the association of accelerometry-measured PA with cognitive function, adjusting for age, sex, accelerometer wear time, education, occupational status/PA, and smoking status. In each cohort, achieving just 10–21.4 min/day moderate-to-vigorous PA related to better executive function (P < .02); and just 10 min/day moderate-to-vigorous PA was associated with better verbal memory in middle-aged adults in the Third Generation cohort (P = .02). In older adults of the Offspring cohort, total PA (measured in steps/day) was associated with better executive function (P < .02). PA at levels lower than the current PA Guidelines (just 10 min/day moderate-to-vigorous PA and total PA including lower intensity PA) were associated with better cognitive function. •Physical activity related to better cognition in middle-aged and older adults.•Just 10 minutes of moderate-to-vigorous activity related to better cognition.•Walking more total steps/day is related to better executive function in older adults.

Background Preclinical studies highlight the importance of endogenous cannabinoids (endocannabinoids; eCBs) in neurodegeneration. Yet, prior observational studies focused on limited outcome measures and assessed only few eCB compounds while largely ignoring the complexity of the eCB system. We examined the associations of multiple circulating eCBs and eCB-like molecules with early markers of neurodegeneration and neuro-injury and tested for effect modification by sex. Methods This exploratory cross-sectional study included a random sample of 237 dementia-free older participants from the Framingham Heart Study Offspring cohort who attended examination cycle 9 (2011–2014), were 65 years or older, and cognitively healthy. Forty-four eCB compounds were quantified in serum, via liquid chromatography high-resolution mass spectrometry. Linear regression models were used to examine the associations of eCB levels with brain MRI measures (i.e., total cerebral brain volume, gray matter volume, hippocampal volume, and white matter hyperintensities volume) and blood biomarkers of Alzheimer’s disease and neuro-injury (i.e., total tau, neurofilament light, glial fibrillary acidic protein and Ubiquitin C-terminal hydrolase L1). All models were adjusted for potential confounders and effect modification by sex was examined. Results Participants mean age was 73.3 ± 6.2 years, and 40% were men. After adjustment for potential confounders and correction for multiple comparisons, no statistically significant associations were observed between eCB levels and the study outcomes. However, we identified multiple sex-specific associations between eCB levels and the various study outcomes. For example, high linoleoyl ethanolamide (LEA) levels were related to decreased hippocampal volume among men and to increased hippocampal volume among women ( β  ± SE =  − 0.12 ± 0.06, p  = 0.034 and β  ± SE = 0.08 ± 0.04, p  = 0.026, respectively). Conclusions Circulating eCBs may play a role in neuro-injury and may explain sex differences in susceptibility to accelerated brain aging. Particularly, our results highlight the possible involvement of eCBs from the N-acyl amino acids and fatty acid ethanolamide classes and suggest specific novel fatty acid compounds that may be implicated in brain aging. Furthermore, investigation of the eCBs contribution to neurodegenerative disease such as Alzheimer’s disease in humans is warranted, especially with prospective study designs and among diverse populations, including premenopausal women.

In the Framingham Heart Study, the incidence of dementia among participants 60 years of age or older has declined over three decades; the 5-year cumulative hazard rate declined from 3.6 per 100 persons in the 1970s and 1980s to 2.0 per 100 persons in the 2000s and 2010s. Dementia is the leading cause of dependence and disability in the elderly population worldwide. 1 – 3 As the average life expectancy increases, the prevalence of dementia 4 and associated monetary costs are expected to increase exponentially. 5 A few studies have suggested that the age-specific incidence of dementia (i.e., the risk of dementia at any specific age) might be decreasing, but these studies either have shown a trend that failed to reach significance 6 , 7 or have relied on comparisons of prevalence data that were ascertained at multiple time points. 8 – 10 One study showed no decline in incidence. 11 Temporal trends are best derived through . . .

Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for dementia. We aimed to identify important candidate blood biomarkers for dementia using three machine learning models. We included 1642 (mean 69 ± 6 yr, 53% women) dementia-free Framingham Offspring Cohort participants attending examination, 7 who had available blood biomarker data. We developed three machine learning models, support vector machine (SVM), eXtreme gradient boosting of decision trees (XGB), and artificial neural network (ANN), to identify candidate biomarkers for incident dementia. Over a mean 12 ± 5 yr follow-up, 243 (14.8%) participants developed dementia. In multivariable models including all 38 available biomarkers, the XGB model demonstrated the strongest predictive accuracy for incident dementia (AUC 0.74 ± 0.01), followed by ANN (AUC 0.72 ± 0.01), and SVM (AUC 0.69 ± 0.01). Stepwise feature elimination by random sampling identified a subset of the nine most highly informative biomarkers. Machine learning models confined to these nine biomarkers showed improved model predictive accuracy for dementia (XGB, AUC 0.76 ± 0.01; ANN, AUC 0.75 ± 0.004; SVM, AUC 0.73 ± 0.01). A parsimonious panel of nine candidate biomarkers were identified which showed moderately good predictive accuracy for incident dementia, although our results require external validation.

Objective To determine the association between plasma insulin‐like growth factor binding protein 2 (IGFBP‐2) and cognitive outcomes. Methods We measured plasma IGFBP‐2 levels in 1596 (53% women, mean age 68.7 [SD 5.7] years) dementia‐free Framingham Offspring cohort participants between 1998 and 2001. Multivariable Cox proportional hazards models related plasma IGFBP‐2 to subsequent risk of incident dementia and Alzheimer’s disease. MRI brain measures and cognitive performance were included as secondary outcomes. Results During a median follow‐up of 11.8 (Q1, Q3: 7.1, 13.3) years, 131 participants developed incident dementia, of whom 98 were diagnosed with Alzheimer’s disease. The highest tertile of IGFBP‐2, compared to the lowest tertile, was associated with an increased risk of incident all‐cause dementia (hazard ratio [HR] 2.89, 95% CI 1.63–5.13) and Alzheimer’s disease (HR 3.63, 95% CI 1.76–7.50) in multivariable analysis. Higher circulating IGFBP2 levels were also cross‐sectionally associated with poorer performance on tests of reasoning but not with MRI‐based outcomes. After adding plasma IGFBP‐2 levels to a conventional dementia prediction model, 32% of individuals with dementia were correctly assigned a higher predicted risk, while 8% of individuals without dementia were correctly assigned a lower predicted risk (overall net reclassification improvement index, 0.40, 95% CI 0.22–0.59). Interpretation Elevated circulating IGFBP‐2 levels were associated with an increased risk of both all‐cause dementia and Alzheimer’s disease. Addition of IGFBP2 plasma levels to a model of traditional risk factors significantly improved dementia risk classification. Manipulation of insulin‐like growth factor signaling via IGFBP‐2 may be a promising therapeutic target for dementia.