Background
Physical activity is associated with reduced risk for Alzheimer’s disease (AD). Aerobic exercise produced modest‐to‐moderate cognitive gains in older adults with mild cognitive impairment ...or AD dementia. In animal models, aerobic exercise modifies AD’s AT(N) biomarkers of Amyloid‐beta (Aβ), hyperphosphorylated Tau, and Neurodegeneration. However, most observational studies didn’t find significant associations between physical activity and AT(N) biomarkers. Few exercise trials included biomarkers, partially attributable to the prohibitive cost and invasiveness of cerebrospinal fluid or PET biomarkers and reported mixed effects on central AT(N) biomarkers. Plasma Aβ42/40 ratio, phosphorylated tau 181 (p‐tau181), and total tau (t‐tau) demonstrate robust correlations with central amyloid and tau levels and offer an opportunity for inclusion in exercise trials.
Method
This pilot study examined the preliminary effects of 6‐month aerobic exercise on plasma Aβ42/40 ratio, p‐tau181, and t‐tau in older adults with mild‐to‐moderate AD dementia. Twenty‐six participants were eligible, and all consented to enroll (8 in stretching, 18 in cycling). Plasma Aβ42/40 ratio, p‐tau181, and t‐tau were measured using Simoa™ assays at baseline, 3, and 6 months. Data were analyzed using Cohen’s d, multilevel model, and intention‐to‐treat.
Result
The sample averaged 77.58±6.99 years old, 15.44±3.00 years of education, 65% male, and 96.2% carrying an APOE e4 allele. The 6‐month within‐group trajectories of changes in outcomes trended differently but were not statistically significant. Aβ42/40 ratio (mean ± standard deviation) increased by 0.001±0.012, p‐tau181 increased by 0.609±1.417 pg/ml, and t‐tau decreased by 0.020±0.279 ng/ml in the stretching group, while Aβ42/40 ratio decreased by 0.001±0.010, p‐tau181 increased by 0.101±1.579 pg/ml, and t‐tau decreased by 0.075±0.215 pg/ml in the cycling group. Between‐group differences were not significant. Effect sizes for 6‐month within‐group changes were small except for p‐tau181 in stretching (d = 0.43 ‐.65, 1.45) and t‐tau in cycling (‐0.35 ‐0.87, 0.17). Most 6‐month between‐group effect sizes were also small except for p‐tau181 (d = .40 ‐.70, 1.51) and t‐tau (d = .53 ‐.40, 1.46), a trend favoring cycling.
Conclusion
Blood biomarkers are highly feasible and tolerable. Exercise modalities may affect AD plasma biomarkers differently. Aerobic exercise may reduce p‐tau181 levels and stretching exercise may improve Aβ42/40 ratio, which need to be validated in future trials.
Background
Alzheimer’s disease (AD) disproportionately affects Mexican Americans, however, reasons underlying this health disparity remain unknown. Type 2 diabetes (T2D) is a risk factor for AD and ...may contribute to AD pathogenesis. The purpose of this study was to examine the associations between T2D and AD blood biomarkers among Mexican Americans and non‐Hispanic Whites.
Methods
This study analyzed baseline data from the Health and Aging Brain Study: Health Disparities (HABS‐HD) that investigated AD differences among Mexican Americans and non‐Hispanic White. HABS‐AD participants were excluded from this study if they had missing data or were outliers (z‐scores >|4|) on a given AD biomarker (N = 1,552 for Aβ42/40 ratio, 1,570 for t‐tau, and 1,553 for NfL). AD biomarkers included plasma Aβ42/42 ratio, total tau (t‐tau), and neurofilament light (NfL) analyzed using Simoa. Predictors were blood glucose, HbA1c, and T2D diagnosis. Data were analyzed with regression analyses controlling for covariates (e.g., demographics, smoking, BMI, health status, diseases, cognition) and treating missing predictor data using Bayesian MCMC estimation.
Results
Mexican Americans differed significantly from non‐Hispanic Whites in age (66.6±8.7 vs. 69.5±8.6), sex (64.9% female vs. 55.1%), education (9.5±4.6 vs. 15.6±2.5), blood glucose (113.5±36.6 vs. 99.2±17.0), HbA1c (6.33±1.4 vs. 5.51±0.6), T2D diagnosis (35.3% vs. 11.1%), Aβ42/40 ratio (.051±.012 vs. .047±.011), t‐tau (2.56±.95 vs. 2.33±.90), and NfL (16.3±9.5 vs. 20.3±10.3). The models with the covariates and predictors accounted for 6% (p<.001), 15% (p<.001), and 36% (p<.001) of the variation in Aβ42/40 ratio, t‐tau, and NfL, respectively. Blood glucose, HbA1c, and T2D diagnosis were not related to Aβ42/40 ratio and t‐tau but explained 3.7% of the variation in NfL (p<.001). Among non‐Hispanic Whites, blood glucose, HbA1c, and T2D diagnosis were negatively (b = ‐0.09, p<.01, β = ‐0.26), not (b = 0.34, p = .71, β = 0.04), and positively (b = 3.32, p<.01, β = 0.33) associated with NfL, respectively. In contrast, blood glucose and T2D diagnosis were not, while HbA1c was positively (b = 2.31, p<.001, β = 0.26), associated with NfL among Mexican Americans.
Conclusion
Blood glucose, HbA1c, and T2D may contribute to differences in NfL levels, but not Aβ42/40 ratio and t‐tau, in an ethnicity‐specific manner. Future studies are needed to corroborate our findings in longitudinal cohorts.
Background
Epidemiological evidence has repeatedly demonstrated elevated systolic blood pressure (SBP) in midlife as a modifiable risk factor for Alzheimer’s Disease and Related Dementia (ADRD) later ...in life. Despite SBP being readily treatable with safe and inexpensive medications, no clinical intervention implementing a lower SBP goal (<120 mm Hg) in midlife to lower future ADRD risk has ever been attempted. Clinical outcomes are not practical in the age range of interest (45‐65 or 45‐70) during an initial trial period of 5 years however robust evidence demonstrates white matter hyperintensity volume (WMHV) as an MRI finding associated with and predictive of incident ADRD.
Method
We used four data sets (SPRINT, Wisconsin Registry for Alzheimer’s Prevention, Framingham, and UK Biobank) with longitudinal MRI data to examine the effect of age range on power for a clinical trial proposal investigating the effect of intensive SBP control on annualized rates of WMHV accumulation in persons starting in middle age. Analyses were conducted separately in each data set. We calculated mean, standard deviations, and annualized rates of WMHV accumulation (derived from T2 FLAIR MRI), using the linear rate of change for accumulation rate, first stratifying by SBP ( = 132 mm Hg vs <132mm Hg except in SPRINT where groups were stratified by goal SBP group) and then by various age ranges. Next, we examined the effect of age range on necessary sample size with 80% power and two‐tailed alpha of 0.05 for a prospective clinical trial.
Result
As expected, annualized WMHV accumulation rate is lower with younger age in all data sets. However, variability decreased (all four data sets) and the percent reduction achieved at lower SBPs is higher at younger ages (3/4 data sets), thus increasing power when excluding older individuals (e.g., >65 years old, Table 1).
Conclusion
Restricting age to individuals to = 65 years‐old may unexpectedly increase power in a clinical trial designed to investigate the effect of goal SBP<120 mm Hg on annualized WMHV accumulation rate. 45‐65 years‐old is a practical age range for the first ever clinical trial intended to investigate the effects of a lower SBP goal in middle age to reduce future ADRD risk.
Background
Epidemiological evidence has repeatedly demonstrated elevated systolic blood pressure (SBP) in midlife as a modifiable risk factor for Alzheimer’s Disease and Related Dementia (ADRD) later ...in life. Despite SBP being readily treatable with safe and inexpensive medications, no clinical intervention implementing a lower SBP goal (<120 mm Hg) in midlife to lower future ADRD risk has ever been attempted. Clinical outcomes are not practical in the age range of interest (45‐65 or 45‐70) during an initial trial period of 5 years however robust evidence demonstrates white matter hyperintensity volume (WMHV) as an MRI finding associated with and predictive of incident ADRD.
Method
We used four data sets (SPRINT, Wisconsin Registry for Alzheimer’s Prevention, Framingham, and UK Biobank) with longitudinal MRI data to examine the effect of age range on power for a clinical trial proposal investigating the effect of intensive SBP control on annualized rates of WMHV accumulation in persons starting in middle age. Analyses were conducted separately in each data set. We calculated mean, standard deviations, and annualized rates of WMHV accumulation (derived from T2 FLAIR MRI), using the linear rate of change for accumulation rate, first stratifying by SBP (≥132 mm Hg vs <132mm Hg except in SPRINT where groups were stratified by goal SBP group) and then by various age ranges. Next, we examined the effect of age range on necessary sample size with 80% power and two‐tailed alpha of 0.05 for a prospective clinical trial.
Result
As expected, annualized WMHV accumulation rate is lower with younger age in all data sets. However, variability decreased (all four data sets) and the percent reduction achieved at lower SBPs is higher at younger ages (3/4 data sets), thus increasing power when excluding older individuals (e.g., >65 years old, Table 1).
Conclusion
Restricting age to individuals to ≤65 years‐old may unexpectedly increase power in a clinical trial designed to investigate the effect of goal SBP<120 mm Hg on annualized WMHV accumulation rate. 45‐65 years‐old is a practical age range for the first ever clinical trial intended to investigate the effects of a lower SBP goal in middle age to reduce future ADRD risk.
Background
Vascular dysfunction is increasingly recognized as an important partner in the pathogenesis of Alzheimer’s disease (AD). Alterations in vascular endothelial‐derived growth factor (VEGF) ...pathways have been implicated as potential mechanisms. However, the specific impact of VEGF proteins in preclinical AD and their relationships with other AD and vascular pathologies during this critical early period remain to be elucidated.
Method
We examined 316 cognitively unimpaired at baseline older adults from the Harvard Aging Brain Study (Table 1). VEGF family proteins (VEGF‐A, VEGF‐C, VEGF‐D, PlGF, VEGFR‐1) were measured in baseline fasting plasma using MSD V‐PLEX Angiogenesis Panel. Using linear mixed effects models, we examined the interactive effects of baseline plasma VEGF proteins and amyloid PET burden (Pittsburgh Compound‐B) on longitudinal cognitive decline (Preclinical Alzheimer Cognitive Composite‐5). We further investigated if effects on cognition may be mediated by longitudinal inferior temporal tau PET burden (Flortaucipir; subset n = 186) or hippocampal atrophy (subset n = 206). Lastly, we examined the impact of adjusting for baseline cardiovascular risk score or white matter hyperintensity volume (WMH).
Result
High plasma VEGF‐A (β = 0.06, t = 3.23, p = 0.001) and low PlGF (β = ‐0.08, t = ‐3.88, p<0.001) each interacted with elevated baseline amyloid burden to slow prospective cognitive decline (Figure 1A). Concordantly, high VEGF‐A (β = ‐0.12, t = ‐4.56, p<0.001) and low PlGF (β = 0.09, t = 3.63, p<0.001) were associated with reduced longitudinal tau accumulation in those with elevated amyloid (Figure 1B). Moderated mediation analyses revealed that, under elevated amyloid, reduced tau accumulation fully mediated the effects of high VEGF‐A and partially mediated the effects of low PlGF (30%) on slower cognitive decline (Figure 2). There were no significant associations with hippocampal atrophy. The interactive effects of VEGF‐A and PlGF on tau and cognition remained significant after adjusting for cardiovascular risk score or WMH (p<0.003).
Conclusion
High plasma VEGF‐A and low PlGF were associated with slower prospective cognitive decline in preclinical AD, which was fully (VEGF‐A) and partially (PlGF) mediated by reduced tau accumulation. These effects were distinct from conventional vascular risk and injury measures, highlighting VEGF‐A and PlGF as potential molecular targets in preclinical AD to modify the vascular‐AD synergy in combination with anti‐amyloid and traditional vascular risk reduction therapies.
Type 2 diabetes (T2D) and Alzheimer disease (AD) are both highly prevalent diseases worldwide, and each is associated with high-morbidity and high-mortality. Numerous clinical studies have ...consistently shown that T2D confers a two-fold increased risk for a dementia, including dementia attributable to AD. Yet, the mechanisms underlying this relationship, especially non-vascular mechanisms, remain debated. Cerebral vascular disease (CVD) is likely to be playing a role. But increased AD neuropathologic changes (ADNC), specifically neuritic amyloid plaques (AP) and neurofibrillary tangles (NFT), are also posited mechanisms. The clinicopathologic studies to date demonstrate T2D to be consistently associated with infarcts, particularly subcortical lacunar infarcts, but not ADNC, suggesting the association of T2D with dementia may largely be mediated through CVD. Furthermore, growing interest exists in insulin resistance (IR), particularly IR within the brain itself, which may be an associated but distinct phenomenon from T2D, as possibly itself associated with ADNC. Other mechanisms largely related to protein processing and efflux in the central nervous system with altered function in T2D may also be involved. Such mechanisms include islet amyloid polypeptide (or amylin) deposition, co-localized with beta-amyloid and found in more abundance in the AD temporal cortex, blood-brain barrier breakdown and dysfunction, potentially related to pericyte degeneration, and disturbance of brain lymphatics, both in the glial lymphatic system and the newly discovered discrete central nervous system lymph vessels. Medical research is ongoing to further disentangle the relationship of T2D to dementia in the aging human brain.
Background
Amyloid‐beta (Aβ) and vascular risk factors are commonly observed together among cognitively unimpaired adults. Here, we examined the interactive associations of Aβ burden and systemic ...vascular risk with respect to longitudinal patterns of neurodegeneration. Secondarily, we assessed whether systemic vascular risk associations with brain atrophy were modified after adjusting for imaging based markers of white matter integrity (white matter hyperintensities (WMH) and diffusion‐derived fractional anisotropy).
Methods
Participants were 197 adults (age=73.5±6.1 years) from the Harvard Aging Brain Study with at least two MRI scans over a median of 4.5 years. Baseline Aβ burden was measured with Pittsburgh Compound‐B PET. Vascular risk was quantified with the Framingham Heart Study general cardiovascular disease risk score. Altered white matter microstructure was measured via diffusion‐derived fractional anisotropy and WMH burden was quantified using FLAIR images. Brain atrophy was assessed longitudinally with serial structural MRI. Aβ burden and vascular risk were examined as interactive and independent predictors of brain atrophy in separate linear mixed models, adjusting for age, sex, education, APOE ε4 status, and intracranial volume (where appropriate).
Result
We found a significant interaction between elevated Aβ burden and higher vascular risk in relation to faster atrophy within frontal (t=‐2.95, p=0.003) and anterior temporal lobes (t =‐2.32, p=0.021), thalamus (t=‐2.61, p=0.010) and striatum (t =‐2.17, p=0.031). Higher Aβ burden, but not vascular risk, was associated with faster atrophy in the parietal lobes (Aβ: t=‐4.14, p<0.001; vascular risk: t=‐1.54, p=0.124), occipital lobes (Aβ: t=‐2.95, p=0.003; vascular risk: t=‐0.63, p=0.526), and hippocampus (Aβ: t=‐2.72, p=0.007; vascular risk: t=0.207, p=0.836). These effects remained very similar after adjusting for WMH and fractional anisotropy measures.
Conclusion
Elevated vascular risk was associated with accelerated Aβ‐related atrophy in frontal and anterior temporal regions. However, higher Aβ burden alone was correlated with greater atrophy in regions often associated with a canonical AD pattern of neurodegeneration, including the hippocampus and parietal regions. These findings highlight interactions between vascular and Aβ‐related pathways with respect to brain atrophy, and the potential benefit of managing vascular risk factors as a possible intervention to slow regional neurodegeneration in preclinical Alzheimer’s disease.
Background
The Colombian kindred affected by the autosomal dominant AD causative mutation PSEN1 E280A are an invaluable population in determining the utility of blood biomarkers (BB) and how ...additional risk factors may affect BB years to decades prior to symptom onset. Neurofilament light (NfL) (Quiroz et al., 2020) and phospho‐tau 217 (p‐tau217) (Palmqvist et al., 2020) diverge about 20 years prior to onset of clinical symptoms in carriers compared to non‐carriers. How APOE4 carriage may influence NfL and p‐tau217 in the kindred is unknown. We assessed cross‐sectional effects of APOE4 carriage on plasma NfL and p‐tau217 in the PSEN1 E280A kindred.
Method
We used a single molecule array immunoassay to quantify plasma NfL and a Meso Scale Discovery based plasma immunoassay to quantify p‐tau217. 1428 persons (age 18 to 75, mean 35.8, 23% APOE4 carriers, 54% PSEN1 E280A carriers) had available data for NfL analyses. A total of 612 persons (age 18 to 60, mean 35.9, 25% APOE4 carriers, 62% PSEN1 E280A carriers) had available data for p‐tau217 analyses. Age related trajectories were derived from cross‐sectional log‐transformed p‐tau217 and NfL concentrations modelled using a restricted cubic spline model. Model parameters were estimated using a Hamiltonian Markov chain Monte Carlo method in E280A mutation and APOE4 carriage defined groups. The primary comparison was made between APOE4 carrier and noncarriers within E280A carriers and noncarriers separately.
Result
In PSEN1 E280A mutation carriers, plasma NfL concentrations begin to differentiate those who were APOE4 carriers from non‐carriers at age 47.4 (figure 1). Plasma NfL concentrations did not differentiate APOE4 carriers versus non‐carriers in those without the PSEN1 E280A mutation though concentration of NfL trended higher in APOE4 carriers in the higher age range of the sample. Plasma p‐tau217 concentrations did not differentiate APOE4 carriers from non‐carriers in PSEN1 E280A mutation carriers or non‐carriers.
Conclusion
APOE4 carriage results in accelerated NfL plasma increases in PSEN1 E280A mutation carriers starting at about the age of symptom onset. The inability to detect APOE4‐related ptau217 and NfL differences in the other groups may be related to the younger age of participants and limitations in statistical power.
Alzheimer's disease (AD) affects Latinos disproportionately. One of the reasons underlying this disparity may be type 2 diabetes (T2D) that is a risk factor for AD. The purpose of this study was to ...examine the associations of T2D and AD blood biomarkers and the differences in these associations between Mexican Americans and non-Hispanic Whites. This study was a secondary analysis of baseline data from the observational Health and Aging Brain Study: Health Disparities (HABS-HD) that investigated factors underlying health disparities in AD in Mexican Americans in comparison to non-Hispanic Whites. HABS-HD participants were excluded if they had missing data or were large outliers (z-scores >|4|) on a given AD biomarker. Fasting blood glucose and glycosylated hemoglobin (HbA1c) levels were measured from clinical labs. T2D was diagnosed by licensed clinicians. Plasma amyloid-beta 42 and 40 (Aβ42/42) ratio, total tau (t-tau), and neurofilament light (NfL) were measured via ultra-sensitive Simoa assays. The sample sizes were 1,552 for Aβ42/40 ratio, 1,570 for t-tau, and 1,553 for NfL. Mexican Americans were younger (66.6±8.7 vs. 69.5±8.6) and had more female (64.9% female vs. 55.1%) and fewer years of schooling (9.5±4.6 vs. 15.6±2.5) than non-Hispanic Whites. Mexican Americans differed significantly from non-Hispanic Whites in blood glucose (113.5±36.6 vs. 99.2±17.0) and HbA1c (6.33±1.4 vs. 5.51±0.6) levels, T2D diagnosis (35.3% vs. 11.1%), as well as blood Aβ42/40 ratio (.051±.012 vs. .047±.011), t-tau (2.56±.95 vs. 2.33±.90), and NfL levels (16.3±9.5 vs. 20.3±10.3). Blood glucose, blood HbA1c, and T2D diagnosis were not related to Aβ42/40 ratio and t-tau but explained 3.7% of the variation in NfL (p < .001). Blood glucose and T2D diagnosis were not, while HbA1c was positively (b = 2.31, p < .001, β = 0.26), associated with NfL among Mexican Americans. In contrast, blood glucose, HbA1c, and T2D diagnosis were negatively (b = -0.09, p < .01, β = -0.26), not (b = 0.34, p = .71, β = 0.04), and positively (b = 3.32, p < .01, β = 0.33) associated with NfL, respectively in non-Hispanic Whites. To conclude, blood glucose and HbA1c levels and T2D diagnosis are associated with plasma NfL levels, but not plasma Aβ and t-tau levels. These associations differ in an ethnicity-specific manner and need to be further studied as a potential mechanism underlying AD disparities.
Abstract
Background
Recruitment for preclinical Alzheimer’s disease clinical trials and observational studies in the Latino population continues to increase as researchers aim to diversify their ...samples. The Telephone Interview for Cognitive Status modified version (TICS‐m) is a pre‐screening tool that has shown to have high diagnostic validity for identification of dementia in mostly Caucasian samples. The TICS‐m cut‐off currently used for screening out cognitive impairment in older individuals is ≥26. We aimed to 1) determine whether currently used TICS‐m cut‐offs are appropriate for pre‐screening clinically normal older Latinos, and 2) assess the relationships among the TICS‐m score and outcome measures typically used in clinical trials, such as Mini Mental State Exam (MMSE), Logical Memory Delayed Recall, and Clinical Dementia Rating (CDR).
Methods
Twenty‐nine older Latino adults (mean age= 68.7, mean education=15.6, and mean TICS‐m= 33.4/40) from the Harvard Aging Brain Study (HABS) were included in this study. Participants completed the pre‐screening TICS‐m over the phone, followed by an in‐clinic screening neuropsychological battery, which included the MMSE, Logical Memory Delayed Recall, and CDR, administered in Spanish. Linear regression models controlling for age, sex, and education were used to assess the relationships between TICS‐m score and performance on the neuropsychological measures.
Results
TICS‐m scores were positively correlated with years of education (r=0.54, p=0.002). No significant associations were observed among TICS‐m scores and other cognitive measures, after adjusting by age, sex, and education (MMSE: r=0.04, p=0.82; Logical Memory Delayed: r=0.10, p=0.62; and CDR sum of boxes: r=‐0.03, p=0.86).
Conclusion
Preliminary results suggest that in this sample of largely cognitively normal Latino adults, TICS‐m score is not associated with performance in other cognitive outcome measures typically used in clinical and observational trials for preclinical Alzheimer’s disease. These findings also suggest that the TICS‐m may not accurately reflect actual cognitive function in older Latino participants. However, we do not know if we are inadvertently screen‐failing participants using TICS‐m as a pre‐screening tool. Further research is needed to assess whether this pre‐screening tool is adequate in the pre‐screening process for preclinical Alzheimer’s disease in older Latino adults.
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