Plasma amyloid beta X-42/X-40 ratio and cognitive decline in suspected early and preclinical Alzheimer's disease.

INTRODUCTION: Blood-based biomarkers are a cost-effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation-immunoassay (IP-IA) as a test for predicting cognitive decline. METHODS: We measured levels of amyloid beta (Aß)X-40 and AßX-42 in immunoprecipitated eluates from the DELCODE cohort. Receiver-operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aß42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia. RESULTS: We detected a significant correlation between AßX-42/X-40 in plasma and CSF (r = 0.473). Mixed-modeling analysis revealed a substantial prediction of AßX-42/X-40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AßX-42/X-40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline. DISCUSSION: Our results suggest that assessing the plasma AßX-42/X-40 ratio via our semiautomated IP-IA is a promising biomarker when examining patients with early or preclinical AD. HIGHLIGHTS: New plasma Aß42/Aß40 measurement using immunoprecipitation-immunoassay Plasma Aß42/Aß40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at-risk for brain amyloid positivity.

Aß oligomers peak in early stages of Alzheimer's disease preceding tau pathology.

INTRODUCTION: Soluble amyloid beta (Aß) oligomers have been suggested as initiating Aß related neuropathologic change in Alzheimer's disease (AD) but their quantitative distribution and chronological sequence within the AD continuum remain unclear. METHODS: A total of 526 participants in early clinical stages of AD and controls from a longitudinal cohort were neurobiologically classified for amyloid and tau pathology applying the AT(N) system. Aß and tau oligomers in the quantified cerebrospinal fluid (CSF) were measured using surface-based fluorescence intensity distribution analysis (sFIDA) technology. RESULTS: Across groups, highest Aß oligomer levels were found in A+ with subjective cognitive decline and mild cognitive impairment. Aß oligomers were significantly higher in A+T- compared to A-T- and A+T+. APOE Îµ4 allele carriers showed significantly higher Aß oligomer levels. No differences in tau oligomers were detected. DISCUSSION: The accumulation of Aß oligomers in the CSF peaks early within the AD continuum, preceding tau pathology. Disease-modifying treatments targeting Aß oligomers might have the highest therapeutic effect in these disease stages. Highlights: Using surface-based fluorescence intensity distribution analysis (sFIDA) technology, we quantified Aß oligomers in cerebrospinal fluid (CSF) samples of the DZNE-Longitudinal Cognitive Impairment and Dementia (DELCODE) cohortAß oligomers were significantly elevated in mild cognitive impairment (MCI)Amyloid-positive subjects in the subjective cognitive decline (SCD) group increased compared to the amyloid-negative control groupInterestingly, levels of Aß oligomers decrease at advanced stages of the disease (A+T+), which might be explained by altered clearing mechanisms.

Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.

OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. MATERIALS AND METHODS: A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network-based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer's Disease Assessment Scale. RESULTS: Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD (P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI (P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups (P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. CONCLUSIONS: The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.

A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings.

Memory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease (AD) patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± SD age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (CU; n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (SCD; n = 342), mild cognitive impairment (MCI; n = 118), or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid AD biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5), as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test if baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and MCI conversion rates of CU and SCD participants. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy first affected the medial temporal lobes, followed by further temporal and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological AD biomarker levels, APOE ε4 carriership, and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive AD biomarkers and was associated with more generalised cognitive impairment. Limbic-predominant atrophy, in all and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of MCI conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, both on the subject and group level, were excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for AD in applied settings. The implementation of atrophy subtype- and stage-specific end-points may increase the statistical power of pharmacological trials targeting early AD.

A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices.

Remote monitoring of cognition holds the promise to facilitate case-finding in clinical care and the individual detection of cognitive impairment in clinical and research settings. In the context of Alzheimer's disease, this is particularly relevant for patients who seek medical advice due to memory problems. Here, we develop a remote digital memory composite (RDMC) score from an unsupervised remote cognitive assessment battery focused on episodic memory and long-term recall and assess its construct validity, retest reliability, and diagnostic accuracy when predicting MCI-grade impairment in a memory clinic sample and healthy controls. A total of 199 participants were recruited from three cohorts and included as healthy controls (n = 97), individuals with subjective cognitive decline (n = 59), or patients with mild cognitive impairment (n = 43). Participants performed cognitive assessments in a fully remote and unsupervised setting via a smartphone app. The derived RDMC score is significantly correlated with the PACC5 score across participants and demonstrates good retest reliability. Diagnostic accuracy for discriminating memory impairment from no impairment is high (cross-validated AUC = 0.83, 95% CI [0.66, 0.99]) with a sensitivity of 0.82 and a specificity of 0.72. Thus, unsupervised remote cognitive assessments implemented in the neotiv digital platform show good discrimination between cognitively impaired and unimpaired individuals, further demonstrating that it is feasible to complement the neuropsychological assessment of episodic memory with unsupervised and remote assessments on mobile devices. This contributes to recent efforts to implement remote assessment of episodic memory for case-finding and monitoring in large research studies and clinical care.

Machine learning-based classification of Alzheimer's disease and its at-risk states using personality traits, anxiety, and depression.

BACKGROUND: Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages. METHODS: In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aß42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). RESULTS: Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets. CONCLUSION: Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages.

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline.

BACKGROUND AND OBJECTIVES: To determine the relevance of minor neuropsychological deficits (MNPD) in patients with subjective cognitive decline (SCD) with regard to CSF levels of Alzheimer disease (AD) biomarkers, cognitive decline, and clinical progression to mild cognitive impairment (MCI). METHODS: This study included patients with clinical SCD and SCD-free, healthy control (HC) participants with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia study. We defined MNPD as a performance of at least 0.5SD below the mean on a demographically adjusted total score derived from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery. We compared SCD patients with MNPD and those without MNPD with regard to CSF amyloid-ß (Aß)42/Aß40, phosphorylated tau (p-tau181), total tau and Aß42/p-tau181 levels, longitudinal cognitive composite trajectories, and risk of clinical progression to incident MCI (follow-up M ± SD: 40.6 ± 23.7 months). In addition, we explored group differences between SCD and HC in those without MNPD. RESULTS: In our sample (N = 672, mean age: 70.7 ± 5.9 years, 50% female), SCD patients with MNPD (n = 55, 12.5% of SCD group) showed significantly more abnormal CSF biomarker levels, increased cognitive decline, and a higher risk of progression to incident MCI (HR: 4.07, 95% CI 2.46-6.74) compared with SCD patients without MNPD (n = 384). MNPD had a positive predictive value of 57.0% (95% CI 38.5-75.4) and a negative predictive value of 86.0% (95% CI 81.9-90.1) for the progression of SCD to MCI within 3 years. SCD patients without MNPD showed increased cognitive decline and a higher risk of incident MCI compared with HC participants without MNPD (n = 215; HR: 4.09, 95% CI 2.07-8.09), while AD biomarker levels did not differ significantly between these groups. DISCUSSION: Our results suggest that MNPD are a risk factor for AD-related clinical progression in cognitively normal patients seeking medical counseling because of SCD. As such, the assessment of MNPD could be useful for individual clinical prediction and for AD risk stratification in clinical trials. However, SCD remains a risk factor for future cognitive decline even in the absence of MNPD.

Long-term environmental enrichment is associated with better fornix microstructure in older adults.

Background: Sustained environmental enrichment (EE) through a variety of leisure activities may decrease the risk of developing Alzheimer's disease. This cross-sectional cohort study investigated the association between long-term EE in young adulthood through middle life and microstructure of fiber tracts associated with the memory system in older adults. Methods: N = 201 cognitively unimpaired participants (≥ 60 years of age) from the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) baseline cohort were included. Two groups of participants with higher (n = 104) or lower (n = 97) long-term EE were identified, using the self-reported frequency of diverse physical, intellectual, and social leisure activities between the ages 13 to 65. White matter (WM) microstructure was measured by fractional anisotropy (FA) and mean diffusivity (MD) in the fornix, uncinate fasciculus, and parahippocampal cingulum using diffusion tensor imaging. Long-term EE groups (lower/higher) were compared with adjustment for potential confounders, such as education, crystallized intelligence, and socio-economic status. Results: Reported participation in higher long-term EE was associated with greater fornix microstructure, as indicated by higher FA (standardized ß = 0.117, p = 0.033) and lower MD (ß = -0.147, p = 0.015). Greater fornix microstructure was indirectly associated (FA: unstandardized B = 0.619, p = 0.038; MD: B = -0.035, p = 0.026) with better memory function through higher long-term EE. No significant effects were found for the other WM tracts. Conclusion: Our findings suggest that sustained participation in a greater variety of leisure activities relates to preserved WM microstructure in the memory system in older adults. This could be facilitated by the multimodal stimulation associated with the engagement in a physically, intellectually, and socially enriched lifestyle. Longitudinal studies will be needed to support this assumption.

Midlife occupational cognitive requirements protect cognitive function in old age by increasing cognitive reserve.

Introduction: Several lifestyle factors promote protection against Alzheimer's disease (AD) throughout a person's lifespan. Although such protective effects have been described for occupational cognitive requirements (OCR) in midlife, it is currently unknown whether they are conveyed by brain maintenance (BM), brain reserve (BR), or cognitive reserve (CR) or a combination of them. Methods: We systematically derived hypotheses for these resilience concepts and tested them in the population-based AgeCoDe cohort and memory clinic-based AD high-risk DELCODE study. The OCR score (OCRS) was measured using job activities based on the O*NET occupational classification system. Four sets of analyses were conducted: (1) the interaction of OCR and APOE-ε4 with regard to cognitive decline (N = 2,369, AgeCoDe), (2) association with differentially shaped retrospective trajectories before the onset of dementia of the Alzheimer's type (DAT; N = 474, AgeCoDe), (3) cross-sectional interaction of the OCR and cerebrospinal fluid (CSF) AD biomarkers and brain structural measures regarding memory function (N = 873, DELCODE), and (4) cross-sectional and longitudinal association of OCR with CSF AD biomarkers and brain structural measures (N = 873, DELCODE). Results: Regarding (1), higher OCRS was associated with a reduced association of APOE-ε4 with cognitive decline (mean follow-up = 6.03 years), consistent with CR and BR. Regarding (2), high OCRS was associated with a later onset but subsequently stronger cognitive decline in individuals converting to DAT, consistent with CR. Regarding (3), higher OCRS was associated with a weaker association of the CSF Aß42/40 ratio and hippocampal volume with memory function, consistent with CR. Regarding (4), OCR was not associated with the levels or changes in CSF AD biomarkers (mean follow-up = 2.61 years). We found a cross-sectional, age-independent association of OCRS with some MRI markers, but no association with 1-year-change. OCR was not associated with the intracranial volume. These results are not completely consistent with those of BR or BM. Discussion: Our results support the link between OCR and CR. Promoting and seeking complex and stimulating work conditions in midlife could therefore contribute to increased resistance to pathologies in old age and might complement prevention measures aimed at reducing pathology.

Heterozygous UCHL1 loss-of-function variants cause a neurodegenerative disorder with spasticity, ataxia, neuropathy, and optic atrophy.

PURPOSE: Biallelic variants in UCHL1 have been associated with a progressive early-onset neurodegenerative disorder, autosomal recessive spastic paraplegia type 79. In this study, we investigated heterozygous UCHL1 variants on the basis of results from cohort-based burden analyses. METHODS: Gene-burden analyses were performed on exome and genome data of independent cohorts of patients with hereditary ataxia and spastic paraplegia from Germany and the United Kingdom in a total of 3169 patients and 33,141 controls. Clinical data of affected individuals and additional independent families were collected and evaluated. Patients' fibroblasts were used to perform mass spectrometry-based proteomics. RESULTS: UCHL1 was prioritized in both independent cohorts as a candidate gene for an autosomal dominant disorder. We identified a total of 34 cases from 18 unrelated families, carrying 13 heterozygous loss-of-function variants (15 families) and an inframe insertion (3 families). Affected individuals mainly presented with spasticity (24/31), ataxia (28/31), neuropathy (11/21), and optic atrophy (9/17). The mass spectrometry-based proteomics showed approximately 50% reduction of UCHL1 expression in patients' fibroblasts. CONCLUSION: Our bioinformatic analysis, in-depth clinical and genetic workup, and functional studies established haploinsufficiency of UCHL1 as a novel disease mechanism in spastic ataxia.

Tocilizumab-associated posterior reversible encephalopathy syndrome in giant-cell arteritis - case report.

BACKROUND: We describe one of the first cases of a Posterior reversible encephalopathy syndrome (PRES) under tocilizumab as treatment of Giant cell arteritis (GCA). CASE PRESENTATION: A 65-year-old female with known GCA and treatment with Tocilizumab (TCZ) developed a convulsive epileptic seizure for the first time. MRI was suggestive of PRES and an associated left sided occipital hemorrhage. Extensive high blood pressure values were not detected. The patient recovered within a week and no further seizures occurred under anticonvulsive medication. CONCLUSION: PRES during the treatment with Tocilizumab hasn't been described in GCA so far. There are single reports of an association between TCZ and PRES in other entities. Thus, a link between interleukin-6 and the integrity of the vasculature could be considered. The clinical consequence should be a stringent blood pressure monitoring in the ambulant setting of patients receiving TCZ.

Clinical, Radiological, and Laboratory Features of Spinal Cord Involvement in Primary Sjögren's Syndrome.

OBJECTIVE: To identify radiological and laboratory hallmarks in patients with primary Sjögren's syndrome (pSS) presenting with spinal cord involvement. METHODS: Clinical and laboratory routine parameters were analyzed in a retrospective multicenter case series of four patients who developed myelitis associated with pSS. Serological and cerebrospinal fluid (CSF) measurements of pSS associated anti-SSA(Ro)-antibodies were initiated, and CSF neurofilament light chain (NFL) levels were assessed. NFL values were compared with results from 15 sex- and age-matched healthy controls. Radiological assessment was performed using multi-sequence spinal cord magnetic resonance imaging. RESULTS: Three of the four patients initially developed neurological signs suggestive of myelitis and were subsequently diagnosed with pSS. All patients presented a longitudinal spinal T2-hyperintense lesion in the cervical spinal cord, whereas only two patients showed pleocytosis and oligoclonal bands in the CSF. Median (range) CSF-NFL levels were significantly elevated in patients compared to controls (6672 pg/mL (621-50000) vs. 585 pg/mL (357-729), p = 0.009). One patient showed sustained, highly increased NFL levels (50000 pg/mL) in the initial assessment when radiological signs of axonal injury were still absent. Anti-SSA(Ro)-antibodies were found in the serum of three patients, while two patients additionally presented intrathecal anti-SSA(Ro)-antibody production. Elevated CSF-NFL levels and intrathecal synthesis of anti-SSA(Ro)-antibodies were associated with a relapsing and treatment-resistant disease course. CONCLUSION: Inflammatory spinal cord lesions associated with pSS are a rare but serious disease leading to severe disability. NFL and anti-SSA(Ro)-antibodies in CSF might serve as prognostic biomarkers and should be routinely assessed in patients with pSS.

CSF Neurofilament light chain level predicts axonal damage in cerebral vasculitis.

The rarity of primary angiitis of the central nervous system (PACNS) demands diagnostic and prognostic biomarkers. We retrospectively measured Neurofilament light chain (NFL) concentrations in cerebrospinal fluid in a severely relapsing PACNS patient at multiple time points during the course of the disease. A marked increase in NFL levels preceding the onset of neuro-axonal damage and arterial-vessel abnormalities was observed with magnetic resonance imaging as well as with MR- and conventional angiography. Thus, marked elevation of NFL in PACNS seems to occur ahead of definitive radiological abnormalities and might serve as a diagnostic biomarker.

The whole-brain pattern of magnetic susceptibility perturbations in Parkinson's disease.

Although iron-mediated oxidative stress has been proposed as a potential pathomechanism in Parkinson's disease, the global distribution of iron accumulation in Parkinson's disease has not yet been elucidated. This study used a new magnetic resonance imaging contrast, quantitative susceptibility mapping, and state-of-the-art methods to map for the first time the whole-brain landscape of magnetostatic alterations as a surrogate for iron level changes in n = 25 patients with idiopathic Parkinson's disease versus n = 50 matched controls. In addition to whole-brain analysis, a regional study including sub-segmentation of the substantia nigra into dorsal and ventral regions and qualitative assessment of susceptibility maps in single subjects were also performed. The most remarkable basal ganglia effect was an apparent magnetic susceptibility increase-consistent with iron deposition-in the dorsal substantia nigra, though an effect was also observed in ventral regions. Increased bulk susceptibility, additionally, was detected in rostral pontine areas and in a cortical pattern tightly concordant with known Parkinson's disease distributions of α-synuclein pathology. In contrast, the normally iron-rich cerebellar dentate nucleus returned a susceptibility reduction suggesting decreased iron content. These results are in agreement with previous post-mortem studies in which iron content was evaluated in specific regions of interest; however, extensive neocortical and cerebellar changes constitute a far more complex pattern of iron dysregulation than was anticipated. Such findings also stand in stark contrast to the lack of statistically significant group change using conventional magnetic resonance imaging methods namely voxel-based morphometry, cortical thickness analysis, subcortical volumetry and tract-based diffusion tensor analysis; confirming the potential of whole-brain quantitative susceptibility mapping as an in vivo biomarker in Parkinson's disease.