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Background: Women account for two thirds of the prevalence and incidence of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Evidence suggest that sex may differently influence the expression of proteins amyloid-beta (Aβ1–42) and tau, for which early detection is crucial in prevention of the disease. Objective: We investigated the effect of aging and cerebrospinal fluid (CSF) levels of Aβ1–42 and tau on frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) in a cohort of cognitively normal older women and women with MCI. Methods: 3T single-voxel MRS was performed on the medial frontal cortex, using Point Resolved Spectroscopy (PRESS) and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) in 120 women (age range 50–85). CSF samples of Aβ1–42 and tau and scores of general cognition were also obtained. Results: Levels of frontal gamma aminobutyric acid (GABA+) were predicted by age, independently of disease and CSF biomarkers. Importantly, levels of GABA+ were reduced in MCI patients. Additionally, we found that levels of N-acetylaspartate relative to myo-inositol (tNAA/mI) predicted cognition in MCI patients only and were not related to CSF biomarkers. Conclusion: This study is the first to demonstrate a strong association between frontal GABA+ levels and neurological aging in a sample consisting exclusively of healthy older women with various levels of CSF tau and Aβ1–42 and women with MCI. Importantly, our results show no correlation between CSF biomarkers and MRS metabolites in this sample.

Alzheimer’s disease (AD) progresses through a lengthy asymptomatic period during which pathological changes accumulate prior to development of clinical symptoms. As disease-modifying treatments are developed, tools to stratify risk of clinical disease will be required to guide their use. In this study, we examine the relationship of AD biomarkers in healthy middle-aged individuals to health history, family history, and neuropsychological measures and identify cerebrospinal fluid (CSF) biomarkers to stratify risk of progression from asymptomatic to symptomatic AD. CSF from cognitively normal (CN) individuals (N=1149) in the Emory Healthy Brain Study were assayed for Aβ42, total Tau (tTau), and phospho181-Tau (pTau), and a subset of 134 cognitively normal, but biomarker-positive, individuals were identified with asymptomatic AD (AsymAD) based on a locally-determined cutoff value for ratio of tTau to Aβ42. These AsymAD cases were matched for demographic features with 134 biomarker-negative controls (CN/BM-) and compared for differences in medical comorbidities and family history. Dyslipidemia emerged as a distinguishing feature between AsymAD and CN/BM- groups with significant association with personal and family history of dyslipidemia. A weaker relationship was seen with diabetes, but there was no association with hypertension. Examination of the full cohort by median regression revealed a significant relationship of CSF Aβ42 (but not tTau or pTau) with dyslipidemia and diabetes. On neuropsychological tests, CSF Aβ42 was not correlated with performance on any measures, but tTau and pTau were strongly correlated with visuospatial perception and visual episodic memory. In addition to traditional CSF AD biomarkers, a panel of AD biomarker peptides derived from integrating brain and CSF proteomes were evaluated using machine learning strategies to identify a set of 8 peptides that accurately classified CN/BM- and symptomatic AD CSF samples with AUC of 0.982. Using these 8 peptides in a low dimensional t-distributed Stochastic Neighbor Embedding analysis and k-Nearest Neighbor (k=5) algorithm, AsymAD cases were stratified into “Control-like” and “AD-like” subgroups based on their proximity to CN/BM- or AD CSF profiles. Independent analysis of these cases using a Joint Mutual Information algorithm selected a set of 5 peptides with 81% accuracy in stratifying cases into AD-like and Control-like subgroups. Performance of both sets of peptides was evaluated and validated in an independent data set from the Alzheimer’s Disease Neuroimaging Initiative. Based on our findings, we conclude that there is an important role of lipid metabolism in asymptomatic stages of AD. Visuospatial perception and visual episodic memory may be more sensitive than language-based abilities to earliest stages of cognitive decline in AD. Finally, candidate CSF peptides show promise as next generation biomarkers for predicting progression from asymptomatic to symptomatic stages of AD.

Introduction: As stroke survivors transition from acute to post-acute care, and finally to community settings, the Centers for Disease Control reports ~65% receive NO rehabilitation. Even more receive rehabilitation too late, after critical brain changes for recovery are complete. Stroke survivors with invisible disabilities of cognition and depression are especially vulnerable to experience poor recovery. We launched a dedicated process to identify invisible disabilities. Our long-term objective is to make acute and post-acute, evidence-based intervention accessible. Hypothesis: >50% of acute stroke patients have cognitive deficits, or depression. Methods: Our comprehensive stroke center completes bedside psychometric assessment with standardized instruments for aphasia (Language Screening Test, LAST), spatial neglect (Catherine Bergego Scale, CBS), memory/global cognition (Montreal Cognitive Assessment, MoCA), delirium (3-Minute Diagnostic Interview for the Confusion Assessment Method, 3D-CAM) and depression (Patient health questionnaire, PHQ-8). Patients unable to respond to questions are assessed for spatial neglect and delirium (standardized observations). Results: 105 ischemic stroke survivors were assessed in the first quarter of program launch (April-July, 2021). Of that group, patients met screening criteria for spatial neglect (47%), aphasia (40%), delirium (19%) and depression (31%). Over 90% had memory / global cognitive impairment (MoCA Conclusions: Our initiative, which includes systematic acute stroke unit spatial neglect screening, confirmed the previously reported high rate of cognitive disorders and depression (Champod, Eskes, Barrett, 2020). Our current step implements uniform recommendations for patients with deficits, and will examine post-acute outcomes, number receiving rehabilitation and medical follow-up, and treatment disparities (right/left stroke, under-represented groups).