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Background: Frailty—feelings of weakness, fatigue, and lack of physiological resiliency—places older adults at increased risk for Alzheimer's Disease (AD) and related dementias. A possible mechanism underlying these associations may be the effects of frailty on brain aging prior to old age. Method: A prospective observational study of approximately 502 community‐based men of predominantly European ancestry without dementia at baseline, from the Vietnam Era Twin Study of Aging (VETSA). Frailty index and MRI imaging were collected at three waves at average ages 56, 62, and 68. We created frailty index (FI) scores using 37 items from previously validated cumulative deficit model indices. Imaging measures included brain‐age (BA; Cole et al. 2018), as well as a validated thickness/hippocampal volume AD‐signature (CTS), and a novel gray matter mean diffusivity AD‐signature (MDS), both weighted averages of MRI‐based morphometry or diffusivity in eight AD‐related brain regions. Different longitudinal models were tested using structural equation modeling in Mplus. Models were adjusted for age, race/ethnicity, education, and smoking. Result: FI was highly correlated over time (range rs = 0.69 to 0.77), as were the brain signatures (range rs = 0.52 to 0.85). The best fitting model was the simplex/auto‐regressive model with correlated random intercepts. Figures 1‐3 show significant associations in the covariate‐adjusted models. FI is significantly associated with brain‐age and the cortical thickness/hippocampal volume AD‐signature random intercepts but not the mean diffusivity signature. Associations attenuate when smoking is added to the model. Moreover, when the cortical thickness/hippocampal volume and mean diffusivity AD‐signatures are adjusted for brain‐age then the associations further attenuate and are no longer significant. No cross‐lag associations were significant. Conclusion: The results are striking given the relatively young age of the sample. Across middle age, frailty was associated with worse brain age and a smaller cortical thickness/hippocampal volume AD‐signature. These associations do not appear to be causal, rather biological aging processes running in parallel. Combined with recent evidence showing associations between frailty and AD‐related biomarkers, the results suggest frailty is not just a geriatric disease and support the need for early intervention in biological aging. [ABSTRACT FROM AUTHOR]

Background: Late‐life ambient air pollution exposures are associated with increased Alzheimer's disease (AD) risk1. Cortical thinning in temporal areas vulnerable to AD is associated with memory decline, neuropathological changes, and increased AD risk. However, most neuroimaging studies on air pollution neurotoxicity analyzed volumetric indices that are not sensitive to early cortical changes, and focused on discrete regions of interest (ROI) selected a priori rather than taking an ROI approach across the whole brain. Therefore, the mechanisms linking exposures to early neuropathological processes in older age are poorly understood. Method: We examined data from 1068 cognitively unimpaired women from the Women's Health Initiative Memory Study who underwent neuroimaging in 2005‐6 (Meanage = 77.8±3.7). Long‐term residential exposures to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were quantified as the 3‐year average of monthly estimates prior to MRI using spatiotemporal models with regionalized universal kriging. Brain scans were processed using FreeSurfer‐v.5.3.0 to estimate cortical thickness in 34 bilateral regions parcellated with the Desikan‐Killiany atlas. Exposure effects on AD‐vulnerable regions were assessed by calculating an AD signature (higher value representing thicker cortices) of surface‐area‐weighted thickness in the bilateral entorhinal, fusiform, inferior temporal, and middle temporal cortices2. We used linear mixed models to estimate exposure effects on standardized regional cortical thickness and the AD signature, adjusting for sociodemographic, lifestyle, and clinical characteristics, and a random effect for scanner manufacturer. Result: After adjusting for covariates and multiple comparisons using the False discovery rate (FDR) method, higher exposures to PM2.5 and NO2 were associated with thinner cortices in at least 31 brain regions (FDR‐adjusted p's<0.05). There were also significant adverse effects of PM2.5 (β = ‐0.055, 95%CI = [‐0.07,‐0.04] per 1µg/m3) and NO2 (β = ‐0.022, 95%CI = [‐0.03,‐0.01] per 1ppb) on the AD signature, equivalent to 1.1 and 0.5 years of aging, respectively. Across all analyses the strongest effects were observed in the frontal lobe, especially the motor cortex. Conclusion: In cognitively unimpaired older women, higher exposures to PM2.5 and NO2 were associated with widespread cortical thinning, including regions sensitive to AD. However, the strongest associations in the frontal lobe suggest a greater impact of air pollution neurotoxicity on brain aging rather than AD risk. [ABSTRACT FROM AUTHOR]

Background: Frailty refers to a person's physical and functional capabilities and increases during aging. Abnormal white matter (AWM; e.g., hyperintensities on T2‐weighted MRI) is a neuroimaging marker of small‐vessel vascular disease associated with increased risk of Alzheimer's Disease and related dementias. While some studies have found associations between frailty indices (FIs) and global AWM, their association with accumulation of regional AWM and any related cognitive correlates is understudied. Method: 342 men from the Vietnam Era Twin Study of Aging with frailty measured at study baseline (mean age = 56.4) and structural MRI scans at follow‐up (mean 5.5 years later) were included (Table 1). The FI measure was based on a cumulative deficit model[1] using an index of 37 health‐ and function‐related items. Global AWM was defined using morphological operators on multi‐channel, three‐class tissue segmentation[2]. A novel watershed routine, applied to our AWM frequency atlas, generated 5 distinct AWM parcellations: frontal, posterior, anterior periventricular, deep, and temporal stem (Figure 1A). Cognitive factor scores (memory, processing speed, executive function, fluency) were derived from normative neuropsychological test performance. Result: Mixed‐effects linear regression models controlling for age, years of education and twin‐pair demonstrated that higher baseline FI was associated with greater future AWM volume in temporal stem (p = 0.03) and anterior periventricular (p = 0.02) regions, but not for global or other parcellations (Figure 1B). Baseline FI was not cross‐sectionally associated with any cognitive factor score but was associated longitudinally with decreased processing speed (p = 0.002) (Table 2). Conclusion: Higher cumulative frailty in late‐middle aged men was associated with greater future AWM burden and greater decline in processing speed. These findings suggest that cumulative frailty during the 6th decade is a relevant indicator and possible predictor of future pathological structural and functional processes in the brain. Longitudinal studies may elucidate whether frailty affects AWM progression and cognitive decline along a common causal pathway. References: [1] Rockwood K. A global clinical measure of fitness and frailty in elderly people. Canadian Medical Association Journal 2005;173:489‐95. [2] Fennema‐Notestine C, et al. White matter disease in midlife is heritable, related to hypertension, and shares some genetic influence with systolic blood pressure. NeuroImage: Clinical 2016;12:737‐45. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging signatures based on cortical thickness or volume in regions vulnerable to Alzheimer's disease (AD) pathology are tools developed to identify brain changes specific to mild AD. Lower thickness/volume signatures (indicating comparatively thinner cortex) are commonly associated with risk of future decline. In contrast, some evidence suggests a biphasic pattern of changes wherein higher, rather than lower, cortical thickness is associated with very early AD pathology. Understanding the difference between high cortical thickness indicating a risk versus a protective factor carries important implications for early identification of AD. We examined whether integrating information from a novel AD brain signature based on gray matter mean diffusivity (MD)—previously shown by our group to be sensitive to early AD‐related changes and predictive of thickness/volume‐based signatures over a decade later—can aid in the interpretation of when high cortical thickness/volume is a risk versus a protective factor for future AD‐related changes. Method: Participants were 572 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively unimpaired (CU) at baseline (mean age = 56 years; range = 51‐60). A validated thickness/volume signature and novel gray matter MD signature, each a weighted average of MRI‐based morphometry in eight AD‐related brain regions, were used in longitudinal mixed models predicting brain and cognitive outcomes. Subgroup analyses included all CU participants with high baseline thickness/volume signatures, regardless of subsequent cognitive status (n = 147). Result: Among individuals with high thickness/volume signature scores at baseline, those that additionally had high values on MD signature scores showed significantly lower thickness/volume signatures and lower episodic memory performance 12 years later compared to the high thickness/volume‐low MD group. In contrast, group differences in global mean cortical thickness remained stable across waves. Groups did not differ in level of young adult cognitive reserve. Conclusion: Gray matter MD differences may capture heterogeneous subgroups among individuals with high cortical thickness/volume. Findings are in line with a biphasic model in which increased cortical thickness in AD‐related regions may precede future decline. An AD signature based on cortical MD can be used alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes. [ABSTRACT FROM AUTHOR]

Background: Before onset of Alzheimer's dementia, aggregation of amyloid‐beta (Aβ) is thought to drive accumulation of Tau, followed by neurodegeneration (indexed here by neurofilament light chain [NFL]). Why or how Aβ increases Tau accumulation remains unclear. Using genetically informative twins aged 61.4 to 73.3 years, we sought to: (1) identify genetic and environmental influences on plasma Aβ (Aβ40, Aβ42, Aβ42/40), total Tau (t‐Tau), and NFL; (2) determine if their genetic and environmental influences are correlated with one another; (3) determine if Aβ40 and Aβ42 causally impact Tau levels; (4) measure associations between biomarkers and APOE‐ε4 status; and (5) measure associations between these biomarkers and mild cognitive impairment (MCI). Method: Data were from 1,035 male twins in the Vietnam Era Twin Study of Aging. Average age was 67.1 years (SD = 2.6). Twin models were used to estimate heritability, genetic and environmental correlations, model the direction of causation between biomarkers, and associations with APOE‐ε4 status. Mixed effect linear regressions were applied to regress MCI on biomarkers. Result: Heritability for Aβ40, Aβ42, t‐Tau and NFL ranged from 43% to 51%, whereas Aβ42/40 heritability was not significantly different from zero. Phenotypic correlations between t‐Tau and Aβ40 (rP = 0.01) and Aβ42 (rP = 0.14) were small. Genetic correlations between t‐Tau and Aβ40 (rG = ‐0.05) and Aβ42 (rG = 0.05) were also very small. In contrast, genetic correlations between NFL and Aβ40 and Aβ42 were higher (rG ranging = 0.31‐0.37). We found no evidence to suggest that Aβ40 or Aβ42 causally impacts t‐Tau. APOE‐ε4 accounted for a significant, but very small amount of variance in Aβ40 and Aβ42. Finally, none of the biomarkers was significantly associated with MCI, which affected 15.1% of the sample. Conclusion: Both Aβ40 or Aβ42 appear heritable, but have very little phenotypic and genetic association with t‐Tau. The associations between the amyloid‐beta biomarkers and t‐Tau are mostly explained by non‐shared environmental factors, and the direction of causation is unclear. The small associations between APOE‐ε4 and the biomarkers, including their lack of association with MCI, may stem from the low sensitivity of plasma biomarkers, the relatively young age or the low proportion of MCI cases in this community‐dwelling sample. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) and vascular disease frequently co‐occur and may interact additively or synergistically on risk for cognitive decline, though the degree of shared overlap between these pathologies remains unclear. Our group has demonstrated the utility of AD signatures, or composite MRI metrics in brain regions associated with AD pathology, for prediction of AD‐related changes beginning in midlife. Our novel signature based on gray matter mean diffusivity (MD) aided 12‐year prediction of incident mild cognitive impairment among cognitively unimpaired adults in their 50s, captured unique phenotypic and genetic variance not otherwise explained by an AD signature based on cortical thickness/volume or general brain aging, and robustly predicted thickness/volume signatures over a decade later. Here, we leveraged twin data from the Vietnam Era Twin Study of Aging (VETSA) to delineate shared and unique genetic and environmental influences on two AD signatures and white matter hyperintensities (WMHs), which have been consistently linked to vascular origin. Method: Participants were 512 men from the VETSA (age = 67.52, SD = 2.60). Our validated thickness/volume signature, novel MD signature based on the same brain regions as the thickness/volume signature, and WMH volume were used in biometrical twin analyses to examine their phenotypic, genetic, and environmental relationships. We adjusted each AD signature for an MRI‐based measure of brain age to detect associations with WMH that were specific to AD‐related brain regions versus general brain aging. We also examined regional WMH parcellations. Result: Phenotypic and genetic correlations demonstrated significant associations between the MD signature and WMH (rp = 0.26 [95% CI: 0.15, 0.36]; rg = 0.34 [95% CI: 0.10, 0.57]). In contrast, phenotypic and genetic correlations between the thickness/volume signature and WMHs were nonsignificant. Environmental correlations between each AD signature and WMH were similarly nonsignificant. Results were similar for each WMH parcellation, suggesting global WMH effects. Conclusion: A gray matter MD signature and WMHs share significant genetic influences, whereas a thickness/volume signature was not associated with WMHs. AD signatures based on brain microstructure, such as the MD signature, may capture very early AD‐related and vascular‐related changes that are not captured by a macrostructural signature at the same timepoint. [ABSTRACT FROM AUTHOR]

Background: Predicted brain age difference (PBAD) scores are novel metrics which compare chronological age to age predicted from neuroimaging data. PBADs are highly relevant to Alzheimer's disease (AD) and cognitive aging. Individuals with AD have predicted brain ages about 10 years older than their chronological age (Franke et al. 2010). Less is known about PBADs in midlife, but recent work on the sample studied here has demonstrated that PBADs are highly heritable (59‐75%), highly stable between middle‐ and early‐old age, and moderated by modifiable lifestyle behaviors earlier in midlife (age 40). The current study examined how midlife PBAD (mean age 56) predicted executive functions concurrently and longitudinally into early old age (mean age 68). Method: We examined 779 non‐demented men in the Vietnam Era Twin Study of Aging (VETSA) who completed cognitive and neuroimaging assessments at up to three assessments (M = 56, 62, and 68 years). PBADs were based on two methods (Liem et al., 2017, Cole et al. 2019) which include information about grey matter or both gray and white matter. Executive function was based on six tasks spanning inhibition, shifting and working memory. Analyses controlled for age, diabetes, hypertension, and APOE‐ε4 dosage. Result: Latent growth models revealed that greater PBAD at age 56 (i.e., greater brain age than chronological age) was associated with worse executive functioning at baseline and greater decline in executive functioning over the following 12 years. The latter association was observed only for PBADs that included white matter (Cole et al., 2019) and persisted even when excluding N = 61 individuals with amnestic mild cognitive impairment (MCI). Subsequent analyses indicated that associations were not moderated by APOE allele status or cognitive reserve (general cognitive ability at mean age 20). Conclusion: Our findings indicate that PBAD is associated with executive functioning in midlife and predicts executive function changes into early old age. They also suggest that PBADs capturing more information about brain health are better predictors of executive function decline across midlife into early‐old age. Finally, the persistence of these effects within cognitively normal subjects suggests PBADs are important predictors of cognitive decline before the onset of MCI/AD. [ABSTRACT FROM AUTHOR]

Background: Inferences about cognitive reserve and related constructs may be subject to reverse causation, but too often the possibility of reverse causation is not addressed in research on reserve and resilience. A lifespan perspective can shed light on the relationships among education, IQ, and related constructs and what can be concluded about causality with respect to late‐life cognitive and dementia outcomes. Method: We use general cognitive ability (GCA) to refer to IQ or IQ‐like measures. We provide examples from the literature plus some new findings examining the effect of cognitive reserve on late‐life outcomes and how modifiable factors may impact reserve and resilience effects. Some of the data presented are from genetically‐informative studies that help to clarify issues related to causality. Result: There is a bidirectional relationship between education and GCA, but the directional influences change across the lifespan. The relationship is not unidirectional in childhood and adolescence, but during that period more education does increase GCA. The effect reaches an asymptote, and in late adolescence and early adulthood, the causal direction shifts toward GCA driving educational attainment. When both education and GCA are in the same model, both longitudinal phenotypic and Mendelian randomization studies show that GCA is a stronger driver of late‐life cognitive and dementia outcomes than education. Appropriately designed studies often support the idea that occupational complexity and engagement in enriching activities are not directly causal, but are downstream effects of GCA. Finally, earlier lifestyle factors can moderate associations between cognitive reserve and late‐life outcomes. For example, favorable early midlife social/health behaviors can offset advanced brain aging in individuals with lower cognitive reserve (i.e., lower young adult GCA). Conclusion: The results have implications regarding interventions to improve cognitive reserve and resilience, and what the balance should be when it comes to resources for early‐ versus late‐life interventions. The primary direction of causal effects raises questions about how and, importantly, when during the lifespan, increased education, cognitive enrichment/training programs (which may be thought of as a type of education), or other lifestyle factors are likely to increase reserve or resilience, thereby improving cognitive function and reducing dementia risk. [ABSTRACT FROM AUTHOR]

Background: Subjective memory concern is a risk factor for dementia in older adults, yet it also appears to be stable over time. Few studies examine memory concern starting in midlife in cognitively normal adults or the role of genetic influences on memory concern. We focused on the stability of subjective memory concern from early midlife into older adulthood and its association with objectively assessed episodic memory and depressive symptoms. Using a classical twin design, we assessed genetic and environmental influences on longitudinally‐assessed subjective concern and its overlap with episodic memory and depressive symptoms. Method: We examined 1,334 community‐dwelling men assessed in the Survey of Health and the Vietnam Era Twin Study of Aging, who were assessed for subjective memory concern at average ages 38, 56, 62, and 67. Objective episodic memory and depressive symptoms were assessed at 56, 62, and 67. Biometric twin models were used to estimate genetic and environmental influences over time, and correlated genetic and environmental influences between measures. Result: Subjective memory concern was highly stable after average age 38 and not significantly associated with age. Phenotypic models showed that subjective memory concern was more related to depressive symptoms (β =.46) than with episodic memory (β = ‐.12) within timepoint, as shown by non‐overlapping confidence intervals. There were no significant lagged associations of subjective memory concern with episodic memory or depressive symptoms. Heritability of subjective memory concern was 51% and remained stable over time; 49% of the variation was attributed to unshared environmental influences. There were also significant genetic correlations between subjective memory concern and both episodic memory and depressive symptoms. Conclusion: Subjective memory concern was stable from age 38 to age 67, and over half of the variance was explained by genetic influences. There was also significant genetic overlap with depressive symptoms and episodic memory. The stability and heritability results provide strong support for a trait‐like component of subjective memory concern. To be most useful as an indicator of imminent cognitive decline and increased risk for dementia, it will be important to differentiate dynamic aspects of subjective concern from its trait‐related dimension. [ABSTRACT FROM AUTHOR]

Background: Composite scores of MRI‐based brain regions associated with Alzheimer's disease (AD) pathology, commonly termed 'AD signatures,' are tools developed to identify brain changes specific to mild AD. In recent work from our group, we found that a novel diffusion‐based cortical mean diffusivity (MD) signature among cognitively normal adults in their 50s aided prediction of 12‐year progression to MCI beyond age and polygenic risk for AD. Results held up after accounting for general brain age. In contrast, a cortical thickness/hippocampal volume‐based signature did not improve prediction. Given the importance of genetic influences on brain structure and AD, here we examined the phenotypic and genetic relationships among diffusion and structural AD signatures and brain age, and how those relationships change across midlife and early old age. Method: Our validated thickness/volume signature, novel MD signature, and a validated brain age measure were used in biometrical twin analyses to examine phenotypic, genetic, and environmental relationships both cross‐sectionally and longitudinally across 12 years. Participants were 736 men from three waves of the Vietnam Era Twin Study of Aging (VETSA; baseline age=56.1, SD=2.6, range=51.1‐60.2). Subsequent waves were at approximately 5.7‐year intervals. Result: Both AD signatures and brain age are heritable (56%‐72%), but each signature captured unique phenotypic and genetic variance that is also not explained by general brain aging. Genetic correlations across time within each signature were high (0.77‐0.98). Baseline MD signatures (age=56 years) predicted thickness/volume signatures over a decade later (r= ‐0.53, 95% CI: ‐0.62, ‐0.42), but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures (r= ‐0.13, 95% CI: ‐0.24, ‐0.01). Interestingly, by wave 2 (average age=62 years), the thickness/volume signature appears to have caught up with the MD signature in terms of predictive ability. Conclusion: Findings lend further support to the idea that a signature based on brain microstructure captures very early AD‐related changes that are later reflected in the macrostructural signature. This MD signature explains substantial genetic variance that is consistent throughout midlife and into early old age, supporting the utility of the MD signature as a very early AD‐related neuroimaging biomarker and its potential role in clinical trials. [ABSTRACT FROM AUTHOR]

Background: Cortical surface area, cortical thickness, and hippocampal volume are well‐studied in relation to later life cognitive impairments and AD. Fewer studies have investigated how white mater microstructure relates to cognition in late life. Existing work has focused on fractional anisotropy (FA) and mean diffusivity (MD) measures that are thought to capture demyelination and axonal degradation and relate to cognitive decline in normal aging and AD. However, these measures are susceptible to partial volume effects. Here, we evaluated whether executive function and memory are associated with FA and MD after deploying a free‐water (FW) elimination post‐processing method that separates fluid (FW) from tissue (FW‐corrected FA and MD). Method: We examined 489 non‐demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Executive function was based on 6 tasks spanning inhibition, shifting, and working memory. Memory was based on 7 subtests from the Logical Memory, Visual Reproductions, and California Verbal Learning tests. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FW‐corrected FA, and FW‐corrected MD. Analyses controlled for age, scanner, diabetes, hypertension, race, and ethnicity. We used false discovery rate to account for multiple testing. Result: Better executive functioning was associated with lower FW across all 11 tracts. Better memory was associated with lower FW in 3 tracts: the superior longitudinal fasciculus (SLF) and two sections of the inferior frontal gyrus (opercularis and triangularis). Despite widespread differences with FW, there was only one significant association with intracellular metrics (executive function and FW‐corrected FA in the SLF). Finally, indicators of cognitive reserve (education or general cognitive ability assessed in early adulthood) did not moderate these associations between cognition and white matter microstructure. Conclusion: Our findings leveraged a post‐processing method that separates extracellular fluid (FW) from intracellular tissue (FA, MD). We found that cognitive abilities in early old age are associated primarily with extracellular white matter microstructure (FW), which demonstrated global associations with executive function. Finally, there was no evidence that indicators of cognitive reserve influenced the strength of the association between cognition and white matter, at least in this sample of non‐demented men. [ABSTRACT FROM AUTHOR]

Background: Air pollution, which includes exposure to tiny particulate matter (PM2.5) and Nitrogen Dioxide (NO2) is a notable public health hazard. Exposure has adverse effects on multiple health outcomes as well as with increased risk of developing cognitive impairment and Alzheimer's disease and related dementias. Although the primary cognitive focus in Alzheimer's disease is memory, there is growing recognition of the importance of early executive function (EF) deficits as a risk indicator. In addition, there is some evidence of genetic susceptibility to pollution‐related cognitive decline. Few studies have strong measures of air pollution, EF, as well as APOE genotyping. We recently showed that APOE genotype was associated with significant decline in EF from middle to early old age among individuals who were cognitively unimpaired at baseline (Gustavson et al, 2022). Here we tested the hypothesis that the impact of air pollution on executive functions would be greater in APOE‐ε4+ carriers compared with APOE‐ε4‐ individuals. Method: We examined associations between exposure in midlife and EF from midlife to early old age in ∼800 men from the Vietnam Era Twin Study of Aging. Measures included average PM2.5 and NO2 exposure in the three years prior to the time 1 (mean age 56; range 51‐61) assessment, and an executive function factor score at time 1 and time 2 (mean age 68; range 65‐72). GEE analyses adjusted for multiple health and lifestyle covariates, as well as the random effect of family. Result: Cognitive performance declined over time from age 56 to age 68 (F = 439.38, p<0.0001). There were no main effects of air pollution on EF. Overall APOE‐ε4+ carriers had higher EF performance than non‐carriers (F = 5.43, p = 0.02). In addition, we found a significant PM2.5‐by‐APOE genotype interaction (F = 8.80, p = 0.003). Increased exposure to PM2.5 in midlife was related to lower executive function in APOE‐ε4 carriers, but not non‐carriers. The interaction with NO2 did not reach significance (F = 2.83, p = 0.09). Conclusion: These results indicate that midlife PM2.5 exposure in men is associated with poorer frontal‐executive function, and APOEε4 carriers are more susceptible to the deleterious effects of PM2.5. [ABSTRACT FROM AUTHOR]

Background: Aging‐related episodic memory (EM) decline and Alzheimer's disease (AD)‐related brain changes begin in late middle age around age 60. However, rate and severity of cognitive decline do not consistently correspond to the extent of neuropathological changes, suggesting a high degree of heterogeneity in EM trajectories. We tested if brain maintenance (BM; relative absence of changes in neural resources as a determinant of preserved cognition) and/or cognitive reserve (CR; a property of the brain that allows for sustained cognitive performance in the face of age‐related changes and brain insult or disease) explain individual differences and heterogeneity in EM in late middle age. Method: Participants were 1604 men from the Vietnam Era Twin Study of Aging. A practice effect‐adjusted composite EM score based on six measures was calculated at three time points with mean ages of 56, 62, and 68. Young adult general cognitive ability (GCA) and lifetime years of education were used as proxy measures of CR. BM was assessed as relative change (from age 56 to 68) in cortical thickness and surface area in a bilateral cortical signature of AD regions‐of‐interest (N = 321). We used linear mixed effect modeling. Result: On average, there was a significant decline in EM from age 56 to 68 (p<0.001). Education (p = 0.042) and young adult GCA (p<0.001) were positively related to EM, but there were no significant effects of education or GCA on the rate of EM change (all p's≥0.316). Relative brain changes were not related to EM (all p's≥0.067) and there were no significant interactions of CR proxies and brain changes on EM (all p's≥0.379). Conclusion: Higher education and higher young adult GCA were related to better EM performance across late middle age – with a stronger contribution of GCA compared to education – but EM change did not differ as a function of these proxy CR measures. Our results did not support effects of BM or CR on EM change in late middle age but rather reflected baseline differences in memory in those with low versus high education/cognitive ability. Whether differential change occurs at later ages or with increased AD pathology remains to be determined. [ABSTRACT FROM AUTHOR]

Background: Executive functions encompass effortful top‐down cognitive processes crucial for daily functioning. They are particularly vulnerable to aging in older adults and are often affected early in the course of Alzheimer's disease. However, the neural mechanisms underlying aging‐related decline in executive functions are not well understood. Modal controllability is a structural metric quantifying the ease at which brain regions can move the brain into difficult‐to‐reach states with substantial effort to support diverse cognitive processes. The emphasis on effortful state transitions bears strong similarity to the definition of executive functions as effortful cognitive processes, rendering modal controllability as a putative neural substrate of executive function. Controllability has been associated with cognitive performance in younger populations, but no studies have examined controllability in older adults or its association with executive function over time. Method: We used diffusion MRI (dMRI) data from community‐dwelling men ages 56‐70 (N=264 Time 2, N=104 Both Time 1 & 2) in the Vietnam Era Twin Study of Aging (VETSA).We performed whole‐brain deterministic fiber tracking on dMRI data to reconstruct white matter streamlines, which were then used to build structural connectivity matrices. Network‐level modal controllability of two cognitive control networks (multiple demand system and control network) were computed from connectivity matrices. An executive function factor score was computed based on six well‐established neuropsychological tasks: Stroop, Trail Making Test, Category Switching, Letter‐Number Sequencing, Reading Span, and Digit Span. Results: In cross‐sectional analyses controlling for age, health status, ethnicity, and young adult general cognitive ability, modal controllability of cognitive control networks was positively associated with executive function at Time 2. Change in controllability from Time 1 to Time 2 (∼6 years) was positively associated with change in executive function over the same period. Conclusion: Findings suggest that a putative mechanism of cognitive aging may involve the controllability of structural networks in supporting brain functional dynamics necessary for cognition. In particular, the longitudinal association suggests that structural network changes in controllability may be a key mechanism underlying aging‐related decline in executive function. A next step will be to how such changes are related to risk for mild cognitive impairment and Alzheimer's dementia. [ABSTRACT FROM AUTHOR]

Background: About 7 million older American adults are affected by frailty (Bandeen‐Roche et al., 2015). Frailty places older adults at an increased risk of adverse physical and mental health outcomes, including Alzheimer's Disease (AD). However, prior to old age, frailty or its relationship to AD biomarkers such as beta‐amyloid 40 and 42 (Aβ40, Aβ42), tau, and neurofilament light (NfL) are understudied. Method: Participants in this prospective longitudinal observational study were community‐based men of predominantly European ancestry. Data were collected across 3 waves at average ages 56 (2002‐08), 62 (2009‐14), and 68 (2016‐19). We calculated frailty index (FI) scores using 37 out of 49 items from an index previously validated in the UK Biobank (Williams et al. 2019; Jiang et al. 2017) which assesses health deficits across multiple physiological systems. FI is calculated as a proportion of deficits out of the total, with scores ranging from 0 (no deficits) to 1 (all deficits present). AD‐related plasma biomarkers for Aβ40,and Aβ42, total tau, and NfL were assayed at average ages 56 and 68. Biomarker values were adjusted for study site and storage time. Result: Average FI score at age 56 was.2, equivalent to having about 7 health deficits. Frailty was significantly correlated (rs=.67‐.74) over time. Higher frailty at both age 56 and 62 doubled the risk for mortality across the 12 years of the study. Age 56 frailty was significantly associated with age 56 tau. Age 68 frailty was significantly associated with age 68 NfL, tau, Aβ40 and Aβ42. In models adjusted for age, education, and ethnicity, age 56 frailty predicted age 68 NfL (B=0.64, t=2.72, p=0.007); associations with age 68 Aβ40 (B=0.39, t=1.96, p=0.0513) and Aβ42 were attenuated (B=0.27, t=1.79, p=0.0743). Age 62 frailty mediated associations between age 56 tau and age 68 tau and NfL, but not other biomarkers. Conclusion: The results are striking given the relatively young age of the sample. Even as early as one's 50s, links between frailty and increased risk for AD emerged. Public health groups have recommended routine frailty screening in adults over 65, but it may be important to start screenings earlier. [ABSTRACT FROM AUTHOR]

Background: The amyloid‐tau‐neurodegeneration (ATN) framework has led to an increased focus on Alzheimer's disease (AD) biomarkers. The costs and invasiveness of methods relying on cerebrospinal fluid or positron emission tomography imaging have led to efforts to develop sensitive blood‐based biomarkers. Although AD is highly heritable, the biometric genetic and environmental etiology of blood‐based biomarkers has never been explored. Method: We therefore analyzed plasma beta amyloid (Ab40, Ab42, Ab42/40), total Tau (t‐tau), and neurofilament light (NFL) biomarkers based on a sample of 1,050 men aged 60 to 73 years (m=67.1, SD=2.57) from the Vietnam Era Twin Study of Aging (VETSA). Unlike AB and tau, NFL does not define AD; however, as a biomarker of neurodegeneration it serves as the N component in the ATN framework. Result: Univariate analyses revealed that familial aggregation in Ab42, Ab42/40, t‐tau and NFL could be entirely explained by additive genetic influences accounting for 50% to 56% of the total variance. All remaining variances were unshared or unique environmental influences. For Ab40, additive genetic (31%) and shared environmental (44%) influences both contributed to total variance. In multivariate analyses, genetic influences accounted for 73% to 75% of the variance in the Ab biomarkers and 55% to 57% of the variance in t‐tau and NFL. The same analyses also revealed that Ab40 and Ab42 were statistically genetically identical and moderately correlated in terms of their environmental influences. All other bivariate associations ranged from small to moderate. Conclusion: Our findings suggest that plasma biomarkers are heritable and that Ab40 and Ab42 share the same genetic influences. In contrast, genetic influences on plasma t‐tau and NFL are mostly unique and uncorrelated with plasma Ab in early old‐age men. [ABSTRACT FROM AUTHOR]

Background: Practice effects (PEs) mask true cognitive decline. Even with declines at follow‐up, PEs can still obscure even steeper declines. Accounting for PEs means that impairment cutoffs are reached earlier. Importantly, mild cognitive impairment (MCI) would be detected earlier. If these diagnoses are valid, there should be more biomarker‐positive MCI cases and fewer biomarker‐positive cognitively normal subjects (CNs). We tested this hypothesis using a replacement‐subjects method. Method: We examined 722 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects who were CN at baseline (mean age=74.9±6.8). MCI at follow‐up was diagnosed by Jak‐Bondi and Petersen criteria. We identified "pseudo‐replacements" whose baseline age was matched to the age of returnees at their 1‐year follow‐up. Education and estimated premorbid IQ were also matched. Difference scores were calculated at Time 2 between returnees on their second testing and the demographically‐matched pseudo‐replacements on their first testing. Attrition effects were estimated by comparing returnee baseline scores with the full baseline sample. PEs = difference scores – attrition effects. PEs are then subtracted from follow‐up scores, with the resultant scores used in diagnosing MCI. CSF Aβ42 and phosphorylated (p)‐tau were measured 6‐12 months prior to retesting. Result: There were significant PEs on 5 of 6 tests (average Cohen's d=.27). For Jak‐Bondi diagnoses, accounting for PEs at follow‐up resulted in a 24.8% increase in the proportion of MCI cases (p<.000001). There were increased proportions of Aβ42‐positive (18.8%) and p‐tau‐positive cases (29.8%), and reduced proportions of Aβ42‐positive (5.8%) and p‐tau‐positive (7.9%) CNs (McNemar χ2: Aβ42: p<.0014, p‐tau: p<.028; Figure 1). Results were similar for Petersen diagnoses. Of 26 false negatives (i.e., CNs whose diagnosis changed to MCI after accounting for PEs), 9 (35%) were MCI without PE adjustment at 2‐year follow‐up. Conclusion: Accounting for PEs led to earlier detection of MCI at 1‐year follow‐up. Biomarker data support these being more accurate diagnoses because more cases were biomarker‐positive and more CNs were biomarker‐negative. Longer‐term follow‐up indicated that MCI cases may be detected a year or more earlier if performance is adjusted for PEs. Accounting for PEs has meaningful, real‐world implications for early identification, which may, in turn, improve opportunities to slow disease progression. [ABSTRACT FROM AUTHOR]

Background: Recent studies have reported significant associations between modifiable lifestyle factors and dementia (Licher et al, 2019; Lourida et al, 2019). We sought to extend those findings by examining whether the effect of lifestyle on brain age, a possible risk factor for dementia, is moderated by one's level of general cognitive ability (GCA). Additionally, we examined associations between brain aging and mild cognitive impairment (MCI). Method: At mean age 68 (SD 2.6; range 61‐72), 356 participants from the Vietnam Era Twin Study of Aging (VETSA) underwent structural MRI which was used to create predicted brain age difference (PBAD) scores (Liem et al., 2017). MCI at age 68 was determined using Jak/Bondi criteria. At mean age 40 (SD 2.7; range 34‐44), a positive lifestyle index was created comprising three self‐reported behaviors: not smoking, ≤ moderate alcohol consumption, and high social engagement. GCA at mean age 20 was assessed with the Armed Forces Qualification Test. Linear mixed models included GCA, lifestyle and their interaction as IVs, and adjusted for age, ethnicity, APOE genotype, height, and family membership. Result: Age 20 GCA and age 40 lifestyle were significantly associated with PBAD [F=5.83; p=.02 and F=15.14; p<.001, respectively]. Having a higher GCA or more positive lifestyle behaviors predicted having less advanced brain age. The GCA‐lifestyle interaction was significant, indicating moderation. Having both lower GCA and few positive behaviors predicted having an older brain age relative to chronological age [F=5.00; p=. 03], but GCA made no difference when more positive behaviors were present (Figure 1). At age 68, non‐amnestic MCI participants had significantly more advanced brain aging compared with cognitively normal or amnestic MCI participants [F=3.10; p=.05]. Conclusion: Risk reduction remains a major component in the fight to prevent/delay dementia. Early positive lifestyle behaviors appeared to be protective against brain aging nearly three decades later for those with low or moderate GCA. High GCA appeared to be protective regardless of lifestyle behaviors. These results suggest that the negative effects of lifestyle start early, particularly for those who have lower cognitive reserve. Early intervention may help promote healthier brain aging and possibly delay dementia onset. [ABSTRACT FROM AUTHOR]

Background: The locus coeruleus (LC) is one of the earliest sites of Alzheimer's disease (AD) pathology, and it experiences extensive neurodegeneration through the disease course. The LC has long been associated with arousal and the sleep‐wake cycle, which are commonly disrupted in AD. Recent research implicates the LC in modulating cognitive function, suggesting an additional path by which LC dysfunction can contribute to cognitive decline in AD. Recent advances in MRI allow for in vivo measures of LC integrity, which may detect early effects of AD or other diseases. We examined whether an MRI measure of LC structural integrity was heritable and whether it was associated with cognitive performance, mild cognitive impairment (MCI), and sleep‐wake disruption. Method: Participants were 481 late‐middle‐aged men (mean age=67.5; range=62‐71.7) from the Vietnam Era Twin Study of Aging. Rostral LC structural integrity was indexed by contrast‐to‐noise ratio (LCCNR) in manually marked regions of an FSE T1‐weighted MRI scan. We determined heritability with the classical twin method comparing monozygotic and dizygotic twins. Cognitive performance was assessed using factor scores across multiple domains, and amnestic MCI (aMCI) was diagnosed according to Jak‐Bondi criteria. The Pittsburgh Sleep Quality Index was used to measure sleep‐wake disruption. Result: Genetic influences (heritability) accounted for 62% of variance in LCCNR. The remaining variance was accounted for by unique environmental variance. Participants with aMCI showed significantly greater daytime dysfunction on the Pittsburgh scale compared to cognitively normal participants. Lower LCCNR was associated with increased odds of aMCI and greater daytime dysfunction. Lower LCCNR was also associated with lower episodic memory, general fluency, semantic‐specific fluency, and processing speed factor scores. Conclusion: These results demonstrate that MRI‐assessed LC integrity is a meaningful biological index. They suggest that LC damage may contribute to sleep‐wake disturbances and cognitive impairment among those with aMCI. Further research is needed to determine whether and how these factors are causally linked. Associations with factor scores across multiple domains highlight the potentially widespread impact of reduced LC integrity on cognition. Furthermore, these findings in late‐middle‐aged adults highlight the potential utility of MRI‐based measures of LC integrity in early identification of AD risk. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) brain signatures based on cortical thickness, with or without hippocampal volume, predict progression from mild cognitive impairment (MCI) to AD. It would be advantageous if AD signatures could predict earlier progression to MCI. Toward that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: 1) AD signatures in cognitively normal middle‐aged adults can predict progression to MCI; and 2) Gray matter mean diffusivity (MD) may capture earlier microstructural changes associated with AD. Method: We investigated the ability of a published cortical thickness/volume signature and a novel MD signature to predict incident MCI in 261 cognitively normal middle‐aged men from the Vietnam Era Twin Study of Aging (VETSA) (baseline age=56.28±2.56; follow‐up age=67.50±2.61). The thickness/volume signature was a weighted average of 8 bilateral regions found to maximally discriminate AD from healthy controls. The same weights were applied to MD in these regions to create an MD signature in 206 subjects with diffusion‐weighted MRI data at baseline. Logistic regression and ROC curves were used to compare models with baseline thickness/volume signature, MD signature, age, and an AD polygenic risk score (ADPRS) predicting MCI at follow‐up. Result: Thickness/volume signature, MD signature, age, and ADPRS together predicted progression to MCI an average of 12 years later with 77.85% specificity, 80% sensitivity, and area‐under‐the‐curve (AUC) of 0.822 (95% CI=0.729‐0.914) (Figure 1). Age and ADPRS alone yielded a significantly lower AUC of 0.633 (95% CI=0.561‐0.705; n=601). Adding the MD signature significantly improved prediction over age and ADPRS (AUC=0.811 vs. 0.633; p=.002) but adding the thickness/volume signature did not (AUC=0.746; p=.069). Conclusion: AD brain signatures can predict 12‐year progression to MCI among cognitively normal adults who are only in their 50s, but our novel MD signature may be more sensitive to AD‐related changes than traditional thickness/volume signatures. Notably, the MD signature was limited by being yoked to the thickness/volume signature weightings. An independently derived MD signature may provide even stronger prediction. The results are thus promising with respect to early identification of AD and the potential value of MD‐ and/or multimodal AD brain signatures. [ABSTRACT FROM AUTHOR]

Background: Cigarette smoking and environmental exposure to other biohazardous chemicals and substances are associated with increased risk of developing cancer, cardiovascular disease, and other diseases that contribute to shorter life expectancy. Their associations with Alzheimer's Disease (AD)‐related brain indicators of structural integrity and plasma biomarkers are less often examined. Method: At average age 68 (range 61‐73), 1118 male participants in the Vietnam Era Twin Study of Aging (VETSA) self‐reported on cigarette smoking habits which we used to calculate pack years. Participants also self‐reported on prolonged or severe exposure to herbicides/pesticides, metal dust, Agent Orange, or other biochemical hazards. Using MRI data collected at average age 68 from approximately 470 participants, we examined a published an AD‐Brain signature based on thickness in 7 AD‐related cortical regions and hippocampal volume. We created a novel an AD‐Mean Diffusivity (AD‐MD) signature based on those same regions (higher AD‐MD scores being worse). We also examined a predicted brain age difference score (PBAD), an indicator of global accelerated brain aging. Plasma abeta42, abeta42/40 ratio, and total tau (t‐tau) were assayed using the Quanterix Simoa system. Multivariable analyses controlled for age, ethnicity, education, and the random effect of family (i.e., twin pairs). Results: Smoking pack years at age 68 were negatively associated with AD‐Brain Signature (p<0.0001) and PBAD (p=0.0013). Pack years (p=0.0001) and Agent Orange (p=0.047) were positively associated with AD‐MD Signature. T‐tau was positively significantly associated with smoking (p=0.0039) and Agent Orange (p=0.004). Conclusions: Heavier lifetime smokers had brains more similar to brains of adults with AD, showed accelerated brain aging, and had higher levels of t‐tau in early old age. All of these are indicators of higher risk for AD. Exposure to Agent Orange, a toxic herbicide, was also related to poorer structural brain integrity and t‐tau. Smoking had the strongest relationship with overall brain health in late midlife compared with other types of environmental exposures, reinforcing its role in pathological aging and its importance as a public health priority. The results suggest that more attention should be paid to potentially toxic environmental exposures that may increase risk for AD and other health conditions. [ABSTRACT FROM AUTHOR]

Background: Musical instrument playing provides intellectual stimulation, which is hypothesised to generate cognitive reserve that protects against cognitive impairment. Method: A systematic review and meta‐analysis of all studies with musical instrument playing as the exposure, and cognitive impairment and/or dementia as the outcome. This was followed by a primary analysis drawing on data from the EPIC‐Norfolk population cohort, attesting for a dose‐response relationship between mid‐life musical instrument playing and late‐life cognition, after adjusting for relevant health and social confounders. Result: Of 1211 articles identified from literature searching, three met inclusion criteria. All were of good methodological quality, and reported large protective effects of musical instrument playing. A twin study reported that musicians were 64% less likely to develop mild cognitive impairment or dementia, after additionally adjusting for sex, education and physical activity. A meta‐analysis of two cohort studies found a 59% reduction in the risk of developing dementia within the study follow up. In EPIC‐Norfolk, data were available from 5693 participants (745 musicians) on music playing, cognition, and all covariables. Classification of musicianship by frequency of playing demonstrated key differences in socio‐demographic factors. Musicians outperformed non‐musicians in cognition generally. Compared to non‐musicians, frequent musicians had 80% higher odds of being in the top cognitive decile (OR 1.80 [95%CI 1.19‐2.73]), whilst musicians playing at any frequency had 29% higher odds (95% CI 1.03‐1.62), compared to non‐musicians. There was evidence of a threshold effect, rather than a linear dose‐response relationship. Conclusion: The existing evidence base suggests a substantial protective effect of musical instrument playing on cognition, but is limited by size and the risk of reverse causality. Our primary EPIC‐Norfolk analysis also supports a positive association between mid‐life musical instrument playing and late‐life cognition. 'Musicians' are a heterogeneous group, and those playing frequently demonstrated the best cognition. Larger, more focused studies are required to further explore this association, with a particular need to consider the cumulative lifetime quantity of music playing. Studies investigating the association between lifestyle factors (e.g. music playing) and cognitive decline should consider the heterogeneous nature of participants, rather than simply adopting a binary classification. [ABSTRACT FROM AUTHOR]

Background: We previously showed that failure to account for practice effects (PEs) delays detection of conversion from unimpaired to mild cognitive impairment (MCI) and reduces diagnostic accuracy based on biomarker positivity data. Even among those who decline, PE can mask steeper declines by inflating cognitive scores. Within MCI samples, PEs may increase reversion rates and impede detection of new impairments. Here, within a baseline MCI sample, we evaluated how PEs affect prevalence, reversion rates, and progression from single‐domain to multi‐domain MCI at follow‐up. Method: We examined 347 baseline Alzheimer's Disease Neuroimaging Initiative MCI participants (mean age=73.2; SD=7.4). We used Jak/Bondi diagnostic criteria (6 tests). We also calculated PEs on a cognitive composite (ADAS‐cog 11) and a cognitive screener (MMSE). We identified participants who were demographically matched to returning subjects at their 1‐year follow‐up. The only difference was that one group was tested once and the other had completed prior testing. We subtracted PEs—based on comparing these groups—from follow‐up scores and recalculated MCI diagnoses. Result: PEs were absent or small for 5 tests (Cohen's d=.00‐.06) and medium for 1 (d=.50). There was a PE on the MMSE (Cohen's d =.16), but none was found on the ADAS‐cog 11. Accounting for PEs increased MCI prevalence at follow‐up by 6% (252 vs 268), and reduced reversion rate by 15% (95 vs 79). PEs also masked progression from single‐domain to multi‐domain MCI: 24 vs 36 (+50.0% after accounting for PEs). Conclusion: Although PEs were small, accounting for them in baseline MCI participants after 1‐year, increased MCI prevalence and progression from single‐domain to multi‐domain, and decreased reversion rates. PEs may be masked within a composite measures, but were present on a short cognitive screener. Failure to consider PEs reduces accuracy regarding conclusions about MCI stability/change and weakens our ability to determine when impairment spreads to new domains. [ABSTRACT FROM AUTHOR]

Background: The locus coeruleus (LC) serves as the primary source of norepinephrine for the brain. Findings that the LC is one of the earliest sites of tau pathology make it a key structure in the early stages of Alzheimer’s disease (AD) progression. An important question is whether measures of LC integrity are associated with indexes of brain structure that may suggest broader patterns of neurodegeneration, particularly if such patterns are detectable prior to substantial macrostructural change. We therefore examined whether LC structural integrity was associated with differences in cortical gray matter microstructure among adults in early old age. Method: Participants were 435 men (mean age=67.5; range=62‐71.7) from the Vietnam Era Twin Study of Aging (VETSA). Rostral LC structural integrity was indexed by contrast‐to‐noise ratio (LCCNR) from a neuromelanin‐sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi‐shell diffusion technique, was used to characterize cortical microstructure, modeling diffusion in restricted, hindered, and free water compartments. Associations between LCCNR and isotropic diffusion within each compartment were examined for bilateral averages of 34 cortical ROIs defined by the Desikan‐Killiany parcellation. As a sensitivity analysis, we also examined whether LCCNR was associated with mean diffusivity (MD), a conventional diffusion tensor imaging (DTI) metric, or cortical thickness in the same regions. Result: After correction for multiple comparisons, higher LCCNR (greater structural integrity) was significantly associated with higher hindered isotropic diffusion and lower free water diffusion across multiple brain regions. In contrast, LCCNR was only associated with lower MD in one brain region and there were no associations with cortical thickness after correction. Conclusion: These results provide evidence that lower MRI‐assessed LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cellular membranes due to broader neurodegenerative processes. Individual differences in LC integrity were only detected with more advanced measures of microstructure that may be more sensitive to early changes than conventional diffusion imaging or macrostructural measures. These results highlight the potential utility for MRI of the LC and cortical microstructure in early identification of AD risk. [ABSTRACT FROM AUTHOR]

Background: Composite scores of MRI‐based brain morphometry, commonly termed ‘Alzheimer’s disease (AD) signatures,’ have demonstrated associations with AD symptom severity and progression to AD. Our group recently showed that two AD signatures, a cortical thickness/volume and mean diffusivity (MD) signature, aid prediction of progression to mild cognitive impairment among cognitively normal adults in their 50s. Genetic and environmental influences on these signatures, and whether the signatures capture unique AD‐related variance, remains unclear. Method: Participants were from the Vietnam Era Twin Study of Aging (age=56.18, SD=2.61). Our previously published thickness/volume signature, a novel MD signature using the same regions and weights as the thickness/volume signature, and an MRI‐based measure of predicted brain age (ns=310‐502) were used in trivariate twin models to determine the relative influence of genetic and environmental factors on each phenotype. Correlations were examined to determine if the latent genetic and environmental influences overlap among the three phenotypes. Result: Heritability estimates were similar for the signatures and predicted brain age (0.68‐0.71). Phenotypic correlations ranged from ‐0.47 to 0.27. Genetic correlations were: 0.33 [95% CI: 0.19,0.47] (thickness/volume signature and predicted brain age); ‐0.55 [95% CI: ‐0.66,‐0.42] (MD signature and predicted brain age); and ‐0.36 [95% CI: ‐0.51,‐0.20] (thickness/volume and MD signatures). Conclusion: Both AD brain signatures are highly heritable. However, despite very similar heritability estimates among the three phenotypes, genetic correlations demonstrated that the two AD signatures are not redundant with each other or with a measure of predicted brain age. The results suggest that each AD signature captures some unique genetic variance, including genetic influences that are distinct from genetic influences on general brain aging. [ABSTRACT FROM AUTHOR]

Background: Persistent pain has been recently linked to increased Alzheimer's disease (AD) risk, calling for the identification of related AD biomarkers. One biomarker of interest is integrity of the locus coeruleus (LC), a brainstem region that is thought to be the earliest site of tau deposition in the brain. The LC is also the main projection site for norepinephrine (NE), a major neurotransmitter inhibiting pain via rostral and caudal LC projections. A recently proposed mechanism suggests that persistent pain alters LC‐NE function and advances AD pathology in this region, explaining increased AD risk. Here we examined the association between persistent pain and LC integrity in older adults. Method: Data were derived from the Vietnam Era Twin Study of Aging (VETSA) in which community‐dwelling men were assessed across up to 12 years in 3 waves. At the third wave, 426 community‐dwelling men (mean age = 67.55) underwent MRI‐assessment sensitive to neuromelanin, a byproduct of LC NE production. Using neuromelanin signal intensities, we calculated contrast‐to‐noise ratios between LC regions (i.e., rostral and caudal) and a pontine tegmentum reference region. Higher contrast‐to‐noise ratios indicate better LC integrity. Persistent pain was defined as reporting 2 or more waves of moderate‐to‐severe pain on the SF‐36 Bodily Pain Scale (n = 80, 16.5%). Generalized linear models examined associations between persistent pain and LC integrity after weighting for survival effects and adjusting for demographic (i.e., age, race, young adult general cognitive ability, income) and health confounders (i.e., comorbidities, depressive symptoms, opioid use), and nested twin observations. Result: Persistent pain was associated with.21 standard deviation lower rostral LC integrity (95% CI: ‐.40 to ‐.03) and.23 standard deviation lower caudal LC integrity at the third wave (95% CI: ‐.44 to ‐.04). Conclusion: Persistent pain was associated with worse LC integrity in older adults. Persistent pain related to worse integrity in both the rostral and caudal LC regions. These associations are consistent with the recent proposed mechanism emphasizing the role of pain on LC‐NE dysfunction, but this relationship may also be bidirectional. Longitudinal designs would be informative, as would studies looking at later dementia trajectories. [ABSTRACT FROM AUTHOR]

Background: Genome‐wide association studies are instrumental in quantifying genetic influences underlying Alzheimer's disease (AD), and applications of polygenic scores derived from association studies have already shed light on early disease pathology. For example, AD polygenic scores (AD‐PGS) are associated with amnestic mild cognitive impairment (MCI) diagnoses in midlife. What remains unclear is how AD‐PGS relate to objectively measured cognitive changes across midlife. Moreover, executive function abilities have been somewhat neglected despite prominent executive impairments in MCI and AD. Here we tested the hypothesis that an AD‐PGS would be associated with executive function and episodic memory changes across late midlife. Method: We examined 1412 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively normal at their first assessment and had up to 3 cognitive assessments across 10‐12 years (mean ages 56, 62, and 68). Latent growth models of executive function were based on 6 tasks spanning inhibition, shifting, and working memory subdomains and growth models of episodic memory were based on 7 subtests from the Logical Memory, Visual Reproductions, and California Verbal Learning tests. The AD‐PRS (Lambert et al. 2013) significantly differentiated MCI and cognitively normal participants in earlier VETSA investigations. Result: Latent growth models of executive function and memory indicated that, compared to baseline performance (i.e., intercept at mean age 56), 10‐year variability in cognitive change was comparatively larger for executive function (e.g., slope variance/intercept variance ratio=39% for executive function, 22% for memory). Importantly, individuals with higher AD‐PGS had sharper declines in executive functioning (r= ‐.24, 95% CI [‐.41, ‐.08]) but not episodic memory (r= ‐.11, 95% CI [‐.25,.04]). Baseline executive function (r=.00) and memory (r=‐.02) were not associated with PD‐PGS. Conclusion: AD genetic risk was associated with executive function changes, but not episodic memory changes, across midlife. These findings highlight the importance of considering executive function changes in midlife, especially for predicting disease progression and AD biology. Executive functions are one of the first cognitive abilities to decline in midlife in normal aging. This study is among the first to demonstrate that this decline also relates to AD genetic influences. [ABSTRACT FROM AUTHOR]

Background: Despite the relevance of semantic fluency measures to risk for dementia and psychiatric disorders, little is known about their genetic and environmental architecture in mid‐to‐late life. Existing studies in community samples of middle‐aged or older adults have yielded a wide range of heritability estimates for semantic fluency (20% to 77%). Some inconsistency may be due to measures available, but genetic variance on semantic fluency may also differ as a function of age, education, or other variables that varied across these studies. Method: Participants represent 21,684 middle‐aged and older adult twins (M = 60.84 years, SD = 11.21; Range 40‐89) from six studies from three countries participating in the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium, representing three countries (Australia, Denmark, and the United States). All subjects completed the same measure of semantic fluency (naming animals in 60 seconds). Education was based on the International standard classification of education (ISCED). Result: Results revealed small‐to‐moderate phenotypic associations with age (b = ‐.182, p <.001), age‐squared (b = ‐.005, p <.001) and education (b = 1.18, p <.001), with education more strongly positively associated with fluency performance in females than males. Heritability decreased with age, ranging from a2 =.58 to a2 =.40 in 40 versus 89‐year‐olds respectively. Genetic variance increased as education increased and nonshared environmental variance decreased with higher education, but the modification of heritability by education was only observed in males. Conclusion: Semantic fluency is interwoven with a network of other cognitive abilities and highly relevant to aging/dementia. However, there is much to learn about its genetic and environmental structure and the way these influences vary based on other biological and environmental factors. This is the largest study to examine the genetic and environmental architecture of semantic fluency, and the first to demonstrate that these influences vary based on age, sex, and education. These findings highlight the dynamic interplay of genetic and environmental influences on cognitive function, and highlight the need to examine the genetic underpinnings of cognition using very large samples that can capture these complex associations. [ABSTRACT FROM AUTHOR]