Geda, Yonas E.

The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.

AbstractINTRODUCTIONWe examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults.METHODSCross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment.RESULTSP‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p < 0.001), p‐tau217 (OR 1.70, 95% CI 1.10–2.61, p = 0.016), and t‐tau (OR 1.44, 95% CI 1.08–1.92, p = 0.012) were associated with appetite change. We also found that p‐tau181 and p‐tau217 were associated with increased symptoms of agitation (OR 1.93, 95% CI 1.20–3.11, p = 0.007 and OR 2.04, 95% CI 1.21–3.42, p = 0.007, respectively), and disinhibition (OR 2.39, 95% CI 1.45–3.93, p = 0.001 and OR 2.30, 95% CI 1.33–3.98, p = 0.003, respectively). Aβ42/Aβ40 and NfL were not associated with NPS.CONCLUSIONHigher plasma‐derived p‐tau181 and p‐tau217 levels are associated with increased symptoms of appetite change, agitation, and disinhibition. These findings may support the validity of plasma tau biomarkers for predicting behavioral symptoms that often accompany cognitive impairment.HIGHLIGHTS We studied 1005 community‐dwelling persons aged ≥ 50 years Higher plasma tau levels are associated with increased neuropsychiatric symptoms Aβ42/Aβ40 and NfL are not associated with neuropsychiatric symptoms Clinicians should treat neuropsychiatric symptoms in persons with high plasma‐derived tau

AbstractBackgroundPhysical 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.MethodThis 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.ResultThe 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.ConclusionBlood 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.

Abstract The observation that aging is regulated by microRNAs (miRNA) and at the same time represents the greatest risk factor for Alzheimer's disease (AD), prompted us to examine the circulating miRNA network in AD beyond aging. We here show that plasma miRNAs in aging are downregulated and predicted to be preferentially targeted to the extracellular vesicle (EV) content. In AD, miRNAs are further downregulated, display altered proportions of motifs relevant to their loading into EVs and secretion propensity, and are forecast to be found exclusively in EVs. The circulating miRNA network in AD, therefore, reflects pathological exacerbation of the aging process whereby physiological suppression of AD pathology by miRNAs becomes insufficient. image

There is a growing interest in the application of machine learning (ML) in Alzheimer’s disease (AD) research. However, neuropsychiatric symptoms (NPS), frequent in subjects with AD, mild cognitive impairment (MCI), and other related dementias have not been analyzed sufficiently using ML methods. To portray the landscape and potential of ML research in AD and NPS studies, we present a comprehensive literature review of existing ML approaches and commonly studied AD biomarkers. We conducted PubMed searches with keywords related to NPS, AD biomarkers, machine learning, and cognition. We included a total of 38 articles in this review after excluding some irrelevant studies from the search results and including 6 articles based on a snowball search from the bibliography of the relevant studies. We found a limited number of studies focused on NPS with or without AD biomarkers. In contrast, multiple statistical machine learning and deep learning methods have been used to build predictive diagnostic models using commonly known AD biomarkers. These mainly included multiple imaging biomarkers, cognitive scores, and various omics biomarkers. Deep learning approaches that combine these biomarkers or multi-modality datasets typically outperform single-modality datasets. We conclude ML may be leveraged to untangle the complex relationships of NPS and AD biomarkers with cognition. This may potentially help to predict the progression of MCI or dementia and develop more targeted early intervention approaches based on NPS.