Cognitive profile, neuroimaging and fluid biomarkers in post-acute COVID-19 syndrome.

We aimed to characterize the cognitive profile of post-acute COVID-19 syndrome (PACS) patients with cognitive complaints, exploring the influence of biological and psychological factors. Participants with confirmed SARS-CoV-2 infection and cognitive complaints ≥ 8 weeks post-acute phase were included. A comprehensive neuropsychological battery (NPS) and health questionnaires were administered at inclusion and at 1, 3 and 6 months. Blood samples were collected at each visit, MRI scan at baseline and at 6 months, and, optionally, cerebrospinal fluid. Cognitive features were analyzed in relation to clinical, neuroimaging, and biochemical markers at inclusion and follow-up. Forty-nine participants, with a mean time from symptom onset of 10.4 months, showed attention-executive function (69%) and verbal memory (39%) impairment. Apathy (64%), moderate-severe anxiety (57%), and severe fatigue (35%) were prevalent. Visual memory (8%) correlated with total gray matter (GM) and subcortical GM volume. Neuronal damage and inflammation markers were within normal limits. Over time, cognitive test scores, depression, apathy, anxiety scores, MRI indexes, and fluid biomarkers remained stable, although fewer participants (50% vs. 75.5%; p = 0.012) exhibited abnormal cognitive evaluations at follow-up. Altered attention/executive and verbal memory, common in PACS, persisted in most subjects without association with structural abnormalities, elevated cytokines, or neuronal damage markers.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches.

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

Evidence for a novel neuronal mechanism driving Alzheimer's disease, upstream of amyloid.

This perspective offers an alternative to the amyloid hypothesis in the etiology of Alzheimer's disease (AD). We review evidence for a novel signaling mechanism based on a little-known peptide, T14. T14 could drive neurodegeneration as an aberrantly activated process of plasticity selective to interconnecting subcortical nuclei, the isodendritic core, where cell loss starts at the pre-symptomatic stages of the disease. Each of these cell groups has the capacity to form T14, which can stimulate production of p-Tau and ß-amyloid, suggestive of an upstream driver of neurodegeneration. Moreover, results in an animal AD model show that antagonism of T14 with a cyclated variant, NBP14, prevents formation of ß-amyloid, and restores cognitive function to that of wild-type counterparts. Any diagnostic and/or therapeutic strategy based on T14-NBP14 awaits validation in clinical trials. However, an understanding of this novel signaling system could bring much-needed fresh insights into the progression of cell loss underlying AD. HIGHLIGHTS: The possible primary mechanism of neurodegeneration upstream of amyloid. Primary involvement of selectively vulnerable subcortical nuclei, isodendritic core. Bioactive peptide T14 trophic in development but toxic in context of mature brain. Potential for early-stage biomarker to detect Alzheimer's disease. Effective therapeutic halting neurodegeneration, validated already in 5XFAD mice.

Utility of visual rating scales in primary progressive aphasia.

INTRODUCTION: Differential diagnosis among subjects with Primary Progressive Aphasia (PPA) can be challenging. Structural MRI can support the clinical profile. Visual rating scales are a simple and reliable tool to assess brain atrophy in the clinical setting. The aims of the study were to establish to what extent the visual rating scales could be useful in the differential diagnosis of PPA, to compare the clinical diagnostic impressions derived from routine MRI interpretations with those obtained using the visual rating scale and to correlate results of the scales in a voxel-based morphometry (VBM) analysis. METHOD: Patients diagnosed with primary progressive aphasia (PPA) according to current criteria from two centers-Ospedale Maggiore Policlinico of Milan and Hospital Clínic de Barcelona-were included in the study. Two blinded clinicians evaluated the subjects MRIs for cortical atrophy and white matter hyperintensities using two protocols: routine readings and the visual rating scale. The diagnostic accuracy between patients and controls and within PPA subgroups were compared between the two protocols. RESULTS: One hundred fifty Subjects were studied. All the scales showed a good to excellent intra and inter-rater agreement. The left anterior temporal scale could differentiate between semantic PPA and all other variants. The rater impression after the protocol can increase the accuracy just for the logopenic PPA. In the VBM analysis, the scores of visual rating scales correlate with the corresponding area of brain atrophy. CONCLUSION: The Left anterior temporal rating scale can distinguish semantic PPA from other variants. The rater impression after structured view improved the diagnostic accuracy of logopenic PPA compared to normal readings. The unstructured view of the MRI was reliable for identifying semantic PPA and controls. Neither the structured nor the unstructured view could identify the nonfluent and undetermined variants.

Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC. METHODS: We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity. RESULTS: We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability. CONCLUSION: We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.

Impact of demographics and comorbid conditions on plasma biomarkers concentrations and their diagnostic accuracy in a memory clinic cohort.

Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aß) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aß status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aß positive) were included. Sex, age and Aß status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized ß -0.115 [-0.192 to -0.035], p = 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aß status (0.685 [0.607-0.763], p < 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aß status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aß status discrimination was minimal.

Thalamic nuclei changes in early and late onset Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Increasing evidence points to the thalamus as an important hub in the clinical symptomatology of the disease, with the 'limbic thalamus' been described as especially vulnerable. In this work, we examined thalamic atrophy in early-onset AD (EOAD) and late-onset AD (LOAD) compared to young and old healthy controls (YHC and OHC, respectively) using a recently developed cutting-edge thalamic nuclei segmentation method. A deep learning variant of Thalamus Optimized Multi Atlas Segmentation (THOMAS) was used to parcellate 11 thalamic nuclei per hemisphere from T1-weighted MRI in 88 biomarker-confirmed AD patients (49 EOAD and 39 LOAD) and 58 healthy controls (41 YHC and 17 OHC) with normal AD biomarkers. Nuclei volumes were compared among groups using MANCOVA. Further, Pearson's correlation coefficient was computed between thalamic nuclear volume and cortical-subcortical regions, CSF tau levels, and neuropsychological scores. The results showed widespread thalamic nuclei atrophy in EOAD and LOAD compared to their respective healthy control groups, with EOAD showing additional atrophy in the centromedian and ventral lateral posterior nuclei compared to YHC. In EOAD, increased thalamic nuclei atrophy was associated with posterior parietal atrophy and worse visuospatial abilities, while LOAD thalamic nuclei atrophy was preferentially associated with medial temporal atrophy and worse episodic memory and executive function. Our findings suggest that thalamic nuclei may be differentially affected in AD according to the age at symptoms onset, associated with specific cortical-subcortical regions, CSF total tau and cognition.

Alzheimer's disease phenotypes show different sleep architecture.

INTRODUCTION: Sleep-wake disturbances are a prominent feature of Alzheimer's disease (AD). Atypical (non-amnestic) AD syndromes have different patterns of cortical vulnerability to AD. We hypothesized that atypical AD also shows differential vulnerability in subcortical nuclei that will manifest as different patterns of sleep dysfunction. METHODS: Overnight electroencephalography monitoring was performed on 48 subjects, including 15 amnestic, 19 atypical AD, and 14 controls. AD was defined based on neuropathological or biomarker confirmation. We compared sleep architecture by visual scoring and spectral power analysis in each group. RESULTS: Overall, AD cases showed increased sleep fragmentation and N1 sleep compared to controls. Compared to atypical AD groups, typical AD showed worse N3 sleep dysfunction and relatively preserved rapid eye movement (REM) sleep. DISCUSSION: Results suggest differing effects of amnestic and atypical AD variants on slow wave versus REM sleep, respectively, corroborating the hypothesis of differential selective vulnerability patterns of the subcortical nuclei within variants. Optimal symptomatic treatment for sleep dysfunction in clinical phenotypes may differ. HIGHLIGHTS: Alzheimer's disease (AD) variants show distinct patterns of sleep impairment. Amnestic/typical AD has worse N3 slow wave sleep (SWS) impairment compared to atypical AD. Atypical AD shows more rapid eye movement deficits than typical AD. Selective vulnerability patterns in subcortical areas may underlie sleep differences. Relatively preserved SWS may explain better memory scores in atypical versus typical AD.

Priorities for research on neuromodulatory subcortical systems in Alzheimer's disease: Position paper from the NSS PIA of ISTAART.

The neuromodulatory subcortical system (NSS) nuclei are critical hubs for survival, hedonic tone, and homeostasis. Tau-associated NSS degeneration occurs early in Alzheimer's disease (AD) pathogenesis, long before the emergence of pathognomonic memory dysfunction and cortical lesions. Accumulating evidence supports the role of NSS dysfunction and degeneration in the behavioral and neuropsychiatric manifestations featured early in AD. Experimental studies even suggest that AD-associated NSS degeneration drives brain neuroinflammatory status and contributes to disease progression, including the exacerbation of cortical lesions. Given the important pathophysiologic and etiologic roles that involve the NSS in early AD stages, there is an urgent need to expand our understanding of the mechanisms underlying NSS vulnerability and more precisely detail the clinical progression of NSS changes in AD. Here, the NSS Professional Interest Area of the International Society to Advance Alzheimer's Research and Treatment highlights knowledge gaps about NSS within AD and provides recommendations for priorities specific to clinical research, biomarker development, modeling, and intervention. HIGHLIGHTS: Neuromodulatory nuclei degenerate in early Alzheimer's disease pathological stages. Alzheimer's pathophysiology is exacerbated by neuromodulatory nuclei degeneration. Neuromodulatory nuclei degeneration drives neuropsychiatric symptoms in dementia. Biomarkers of neuromodulatory integrity would be value-creating for dementia care. Neuromodulatory nuclei present strategic prospects for disease-modifying therapies.

Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data.

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.

The APOE4 effect: structural brain differences in Alzheimer's disease according to the age at symptom onset.

BACKGROUND AND PURPOSE: How the APOE genotype can differentially affect cortical and subcortical memory structures in biomarker-confirmed early-onset (EOAD) and late-onset (LOAD) Alzheimer's disease (AD) was assessed. METHOD: Eighty-seven cerebrospinal fluid (CSF) biomarker-confirmed AD patients were classified according to their APOE genotype and age at onset. 28 were EOAD APOE4 carriers (+EOAD), 21 EOAD APOE4 non-carriers (-EOAD), 23 LOAD APOE4 carriers (+LOAD) and 15 LOAD APOE4 non-carriers (-LOAD). Grey matter (GM) volume differences were analyzed using voxel-based morphometry in Papez circuit regions. Multiple regression analyses were performed to determine the relation between GM volume loss and cognition. RESULTS: Significantly more mammillary body atrophy in +EOAD compared to -EOAD is reported. The medial temporal and posterior cingulate cortex showed less GM in +LOAD compared to -LOAD. Medial temporal GM volume loss was also found in +EOAD compared to -LOAD. With an exception for +EOAD, medial temporal GM was strongly associated with episodic memory in the three groups, whilst posterior cingulate cortex GM volume was more related with visuospatial abilities. Visuospatial abilities and episodic memory were also associated with the anterior thalamic nucleus in -LOAD. CONCLUSIONS: Our results show that the APOE genotype has a significant effect on GM integrity as a function of age of disease onset. Specifically, whilst LOAD APOE4 genotype is mostly associated with increased medial temporal and parietal atrophy compared to -LOAD, for EOAD APOE4 might have a more specific effect on subcortical (mammillary body) structures. The findings suggest that APOE genotype needs to be taken into account when classifying patients by age at onset.

Diagnostic Performance and Clinical Applicability of Blood-Based Biomarkers in a Prospective Memory Clinic Cohort.

BACKGROUND AND OBJECTIVES: Blood-based biomarkers have emerged as minimally invasive options for evaluating cognitive impairment. Most studies to date have assessed them in research cohorts, limiting their generalization to everyday clinical practice. We evaluated their diagnostic performance and clinical applicability in a prospective, real-world, memory clinic cohort. METHODS: All patients referred with suspected cognitive impairment between July 2019 and June 2021 were prospectively invited to participate. Five plasma biomarkers (tau phosphorylated at threonine 181 [p-tau181], glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL], total tau [t-tau], and ubiquitin C-terminal hydrolase L1 [UCH-L1]) were determined with single-molecule array. Performance was assessed in comparison to clinical diagnosis (blinded to plasma results) and amyloid status (CSF/PET). A group of cognitively unimpaired (CU) controls was also included. RESULTS: Three hundred forty-nine participants (mean age 68, SD 8.3 years) and 36 CU controls (mean age 61.7, SD 8.2 years) were included. In the subcohort with available Alzheimer disease (AD) biomarkers (n = 268), plasma p-tau181 and GFAP had a high diagnostic accuracy to differentiate AD from non-neurodegenerative causes (area under the receiver operating characteristic curve 0.94 and 0.92, respectively), with p-tau181 systematically outperforming GFAP. Plasma p-tau181 levels predicted amyloid status (85% sensitivity and specificity) with accurate individual prediction in approximately 60% of the patients. Plasma NfL differentiated frontotemporal dementia (FTD) syndromes from CU (0.90) and non-neurodegenerative causes (0.93), whereas the discriminative capacity with AD and between all neurodegenerative and non-neurodegenerative causes was less accurate. A combination of p-tau181 and NfL identified FTD with 82% sensitivity and 85% specificity and had a negative predictive value for neurodegenerative diagnosis of 86%, ruling out half of the non-neurodegenerative diagnoses. In the subcohort without AD biomarkers, similar results were obtained. T-tau and UCH-L1 did not offer added diagnostic value. DISCUSSION: Plasma p-tau181 predicted amyloid status with high accuracy and could have potentially avoided CSF/amyloid PET testing in approximately 60% of subjects in a memory clinic setting. NfL was useful for identifying FTD from non-neurodegenerative causes but behaved worse than p-tau181 in all other comparisons. Combining p-tau181 and NfL improved diagnostic performance for FTD and non-neurodegenerative diagnoses. However, the 14% false-negative results suggest that further improvement is needed before implementation outside memory clinics. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that plasma p-tau181 correlates with the presence or absence of AD and a combination of plasma p-tau181 and NfL correlates moderately well with a diagnosis of FTD.

Early-onset Alzheimer's disease shows a distinct neuropsychological profile and more aggressive trajectories of cognitive decline than late-onset.

OBJECTIVES: Early- and late-onset Alzheimer's disease (EOAD and LOAD) share the same neuropathological traits but show distinct cognitive features. We aimed to explore baseline and longitudinal outcomes of global and domain-specific cognitive function in a well characterized cohort of patients with a biomarker-based diagnosis. METHODS: In this retrospective cohort study, 195 participants were included and classified according to their age, clinical status, and CSF AD biomarker profile: 89 EOAD, 37 LOAD, 46 young healthy controls (age ≤ 65 years), and 23 old healthy controls (>65 years). All subjects underwent clinical and neuropsychological assessment, neuroimaging, APOE genotyping and lumbar puncture. RESULTS: We found distinct neuropsychological profiles between EOAD and LOAD at the time of diagnosis. Both groups showed similar performances on memory and language domains, but the EOAD patients displayed worsened deficits in visual perception, praxis, and executive tasks (p < 0.05). Longitudinally, cognitive decline in EOAD was more pronounced than LOAD in the global outcomes at the expense of these non-amnestic domains. We found that years of education significantly influenced the decline in most of the neuropsychological tests. Besides, the APOE ε4 status showed a significant effect on the decline of memory-related tasks within the EOAD cohort (p < 0.05). INTERPRETATION: Age of onset is a main factor shaping the cognitive trajectories in AD patients, with younger age driving to a steeper decline of the non-memory domains. Years of education are related to a transversal decline in all cognitive domains and APOE ε4 status to a specific decline in memory performance in EOAD.

Sex differences in early-onset Alzheimer's disease.

BACKGROUND AND PURPOSE: Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (EOAD; <65 years) is scarce. METHODS: We included 62 EOAD patients and 44 healthy controls (HCs) with core AD cerebrospinal fluid (CSF) biomarkers, neurofilament light chain levels, neuropsychological assessment, and 3-T magnetic resonance imaging. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using FreeSurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition. RESULTS: Compared to same-sex HCs, female EOAD subjects showed greater cognitive impairment and broader atrophy burden than male EOAD subjects. In a direct female-EOAD versus male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female EOAD than in male EOAD subjects. Greater atrophy was associated with worse cognition in female EOAD subjects. CONCLUSIONS: At diagnosis, there are sex differences in the pattern of cognitive impairment, atrophy burden, and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.

Pittsburgh Sleep Quality Index (PSQI) responses are modulated by total sleep time and wake after sleep onset in healthy older adults.

OBJECTIVES: To investigate the objective sleep influencers behind older adult responses to subjective sleep measures, in this case, the Pittsburgh Sleep Quality Index (PSQI). Based on previous literature, we hypothesized that SE would be associated with PSQI reported sleep disruption. Furthermore, because SOL increases progressively with age and it tends to be easily remembered by the patients, we also expected it to be one of the main predictors of the perceived sleep quality in the elderly. METHODS: We studied 32 cognitively healthy community-dwelling older adults (age 74 ± 0.3 years) who completed an at-home sleep assessment (Zeo, Inc.) and the PSQI. Linear mixed models were used to analyze the association of the objective sleep parameters (measured by the Zeo) with the PSQI total score and sub-scores, adjusting for age, gender, years of education and likelihood of sleep apnea. RESULTS: Objective sleep parameters did not show any association with the PSQI total score. We found that objective measures of Wake after sleep onset (WASO, % and min) were positively associated with the PSQI sleep disturbance component, while SE and Total Sleep Time (TST) were negatively associated with PSQI sleep disturbance. Lastly, objective SE was positively associated with PSQI SE. CONCLUSIONS: Our findings showed that WASO, SE and TST, are associated with PSQI sleep disturbance, where the greater WASO, overall lower SE and less TST, were associated with increased subjective report of sleep disturbance. As expected, subjective (PSQI) and objective measures of SE were related. However, PSQI total score did not relate to any of the objective measures. These results suggest that by focusing on the PSQI total score we may miss the insight this easily administered self-report tool can provide. If interpreted in the right way, the PSQI can provide further insight into cognitively healthy older adults that have the likelihood of objective sleep disturbance.

Diagnostic Accuracy of Magnetic Resonance Imaging Measures of Brain Atrophy Across the Spectrum of Progressive Supranuclear Palsy and Corticobasal Degeneration.

Importance: The accurate diagnosis of progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) is hampered by imperfect clinical-pathological correlations. Objective: To assess and compare the diagnostic value of the magnetic resonance parkinsonism index (MRPI) and other magnetic resonance imaging-based measures of cerebral atrophy to differentiate between PSP, CBD, and other neurodegenerative diseases. Design, Setting, and Participants: This prospective diagnostic study included participants with 4-repeat tauopathies (4RT), PSP, CBD, other neurodegenerative diseases and available MRI who appeared in the University of California, San Francisco, Memory and Aging Center database. Data were collected from October 27, 1994, to September 29, 2019. Data were analyzed from March 1 to September 14, 2021. Main Outcomes and Measures: The main outcome of this study was the neuropathological diagnosis of PSP or CBD. The clinical diagnosis at the time of the MRI acquisition was noted. The imaging measures included the MRPI, cortical thickness, subcortical volumes, including the midbrain, pons, and superior cerebellar peduncle volumes. Multinomial logistic regression models (MLRM) combining different cortical and subcortical regions were defined to discriminate between PSP, CBD, and other pathologies. The areas under the receiver operating characteristic curves (AUROC) and cutoffs were calculated to differentiate between PSP, CBD, and other diseases. Results: Of the 326 included participants, 176 (54%) were male, and the mean (SD) age at MRI was 64.1 (8.0) years. The MRPI showed good diagnostic accuracy for the differentiation between PSP and all other pathologies (accuracy, 87%; AUROC, 0.90; 95% CI, 0.86-0.95) and between 4RT and other pathologies (accuracy, 80%; AUROC, 0.82; 95% CI, 0.76-0.87), but did not allow the discrimination of participants with CBD. Its diagnostic accuracy was lower in the subgroup of patients without the canonical PSP-Richardson syndrome (PSP-RS) or probable corticobasal syndrome (CBS) at MRI. MLRM combining cortical and subcortical measurements showed the highest accuracy for the differentiation between PSP and other pathologies (accuracy, 95%; AUROC, 0.98; 95% CI, 0.97-0.99), CBD and other pathologies (accuracy, 83%; AUROC, 0.86; 95% CI, 0.81-0.91), 4RT and other pathologies (accuracy, 89%; AUROC, 0.94; 95% CI, 0.92-0.97), and PSP and CBD (accuracy, 91%; AUROC, 0.95; 95% CI, 0.91-0.99), even in participants without PSP-RS or CBS at MRI. Conclusions and Relevance: In this study, the combination of widely available cortical and subcortical measures of atrophy on MRI discriminated between PSP, CBD, and other pathologies and could be used to support the diagnosis of 4RT in clinical practice.

Subcortical Neuronal Correlates of Sleep in Neurodegenerative Diseases.

Importance: Sleep disturbance is common among patients with neurodegenerative diseases. Examining the subcortical neuronal correlates of sleep disturbances is important to understanding the early-stage sleep neurodegenerative phenomena. Objectives: To examine the correlation between the number of important subcortical wake-promoting neurons and clinical sleep phenotypes in patients with Alzheimer disease (AD) or progressive supranuclear palsy (PSP). Design, Setting, and Participants: This longitudinal cohort study enrolled 33 patients with AD, 20 patients with PSP, and 32 healthy individuals from the Memory and Aging Center of the University of California, San Francisco, between August 22, 2008, and December 31, 2020. Participants received electroencephalographic and polysomnographic sleep assessments. Postmortem neuronal analyses of brainstem hypothalamic wake-promoting neurons were performed and were included in the clinicopathological correlation analysis. No eligible participants were excluded from the study. Exposures: Electroencephalographic and polysomnographic assessment of sleep and postmortem immunohistological stereological analysis of 3 wake-promoting nuclei (noradrenergic locus coeruleus [LC], orexinergic lateral hypothalamic area [LHA], and histaminergic tuberomammillary nucleus [TMN]). Main Outcomes and Measures: Nocturnal sleep variables, including total sleep time, sleep maintenance, rapid eye movement (REM) latency, and time spent in REM sleep and stages 1, 2, and 3 of non-REM (NREM1, NREM2, and NREM3, respectively) sleep, and wake after sleep onset. Neurotransmitter, tau, and total neuronal counts of LC, LHA, and TMN. Results: Among 19 patients included in the clinicopathological correlation analysis, the mean (SD) age at death was 70.53 (7.75) years; 10 patients (52.6%) were female; and all patients were White. After adjusting for primary diagnosis, age, sex, and time between sleep analyses and death, greater numbers of LHA and TMN neurons were correlated with decreased homeostatic sleep drive, as observed by less total sleep time (LHA: r = -0.63; P = .009; TMN: r = -0.62; P = .008), lower sleep maintenance (LHA: r = -0.85; P < .001; TMN: r = -0.78; P < .001), and greater percentage of wake after sleep onset (LHA: r = 0.85; P < .001; TMN: r = 0.78; P < .001). In addition, greater numbers of LHA and TMN neurons were correlated with less NREM2 sleep (LHA: r = -0.76; P < .001; TMN: r = -0.73; P < .001). A greater number of TMN neurons was also correlated with less REM sleep (r = -0.61; P = .01). A greater number of LC neurons was mainly correlated with less total sleep time (r = -0.68; P = .008) and greater REM latency (r = 0.71; P = .006). The AD-predominant group had significantly greater sleep drive, including higher total sleep time (mean [SD], 0.49 [1.18] vs -1.09 [1.37]; P = .03), higher sleep maintenance (mean [SD], 0.18 [1.22] vs -1.53 [1.78]; P = .02), and lower percentage of wake after sleep onset during sleep period time (mean [SD], -0.18 [1.20] vs 1.49 [1.72]; P = .02) than the PSP-predominant group based on unbiased k-means clustering and principal component analyses. Conclusions and Relevance: In this cohort study, subcortical wake-promoting neurons were significantly correlated with sleep phenotypes in patients with AD and PSP, suggesting that the loss of wake-promoting neurons among patients with neurodegenerative conditions may disturb the control of sleep-wake homeostasis. These findings suggest that the subcortical system is a primary mechanism associated with sleep disturbances in the early stages of neurodegenerative diseases.