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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

AbstractBackgroundHigher brain amyloid PET is associated with slower gait speed and has been hypothesized to play a role in age‐related mobility decline. With the development of blood‐based biomarkers of Alzheimer’s disease pathology, we examined whether plasma levels of amyloid‐beta (Aβ)40, Aβ42, the Aβ42/Aβ40 ratio, phosphorylated tau 181 (p‐tau181) and 217 (p‐tau217), total tau, and neurofilament light chain (NfL) were associated with gait speed.MethodThis study included 779 cognitively unimpaired participants (median age 75, 54.8% male, median follow‐up 6.8 years) in the Mayo Clinic Study of Aging with concurrent measurement of plasma biomarkers and gait speed. Individuals with chronic kidney disease or a history of stroke were excluded. The plasma markers (pg/mL) were measured on the Quanterix Simoa® HD‐1 analyzer (total tau, Aβ42, Aβ40, NfL) and the Meso Scale Discovery platform (p‐tau181, p‐tau217). Gait speed (m/s) was obtained by timing a self‐paced walk across 25 ft using a stopwatch. Linear mixed effects models, with subject‐specific intercepts and slopes for time since baseline, with z‐scored baseline plasma markers were used to predict cross‐sectional and longitudinal gait speed. All models adjusted for baseline age and sex.ResultAt baseline, higher Aβ42 [Beta = ‐0.019; 95%CI = (‐0.035, ‐0.004)], total‐tau [‐0.026; (‐0.041, ‐0.011)], and p‐tau181 [‐0.021; (‐0.036, ‐0.006)] were associated with slower gait speed. Gait speed decreased, on average, by about 0.015 m/s annually for those in this study. Each one standard deviation (SD) increase in baseline level of plasma Aβ40 [‐0.005; (‐0.007, ‐0.002)], NfL [‐0.006; (‐0.009, ‐0.004)], and p‐tau217 [‐0.004; (‐0.007, ‐0.001)] accelerated this decline over time. In contrast, each one SD increase in Aβ42/Aβ40 ratio [0.003; (0.001, 0.006)] mitigated decline. Additional analyses adjusting for Charlson comorbidity index, Beck Depression Inventory, body mass index, and APOE E4 allele status gave similar results.ConclusionBoth cross‐sectional and longitudinal associations of plasma markers of amyloid and tau pathology and neurodegeneration with gait speed among cognitively unimpaired individuals were present. Therefore, not only are these markers of cognitive changes, they are also related to motor changes such as those affecting gait speed.

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.

AbstractBackgroundNeurofilament light chain (NfL) is an emerging blood‐based biomarker useful for assessing neuro‐axonal injury in several neurological conditions. Plasma NfL concentrations reflect the extent of axonal damage, making it a general marker of neurodegenerative disease progression. This study evaluates the analytical performance characteristics of the Quanterix NfL Advantage method in EDTA‐plasma.MethodThe assay was performed per manufacturer’s instructions on the Quanterix Simoa HD‐X Analyzer. Analytical validation included analyte stability, imprecision, lower limit of quantification (LLOQ), analytical measurement range (AMR), accuracy, and interferences. One‐sided reference intervals were established using quantile regression methods among 1100 cognitive normal individuals, age 20 to 95 years without known chronic kidney disease, stroke, or myocardial infarction.ResultNfL was stable in plasma three days ambient, seven days refrigerate, 90 days frozen (‐20C), and over 3 freeze/thaw cycles. Intra and inter‐assay imprecision, expressed as % coefficient of variation (%CV), ranged from 3.4 – 6.0% and 5.9 – 11.6% respectively. The LLOQ was evaluated using patient plasma pools at concentrations of 1.7 and 3.6 pg/mL. %CVs were 16.8% and 9.7% respectively, and the LLOQ was set at 3.0 pg/mL. Accuracy was assessed by spiking 5 plasma samples with NfL calibratoran 87% average recovery (range 81‐94%) was observed. The AMR of 3.0 – 1500 pg/mL was verified with a regression slope of 0.93 and r2 > 0.99. Additionally, plasma admixtures covering the AMR showed acceptable linear response (slope of 1.02 and r² >0.99). The assay was not affected by icterus to 100 mg/dL, lipemia to 1000 mg/dL, hemolysis to 1000 mg/dL at NfL concentrations >30 pg/mL or to 200 mg/dL at NfL concentrations ≤30 pg/mL. NfL increased with age but did not differ by sex. The data supported age‐based reference intervals broken down into 10‐year intervals. The 97.5th percentile limits were: 20s: ≤8.4 pg/mL, 30s: ≤11.4 pg/mL, 40s: ≤15.4 pg/mL, 50s: ≤20.8 pg/mL, 60s: ≤28.0 pg/mL, 70s: ≤37.9 pg/mL, 80+: ≤51.2 pg/mL.ConclusionThe analytical performance characteristics of the plasma Quanterix NfL advantage assay were deemed acceptable for clinical laboratory implementation. The establishment of NfL reference intervals will aid in the clinical interpretation of patient plasma NfL concentrations.