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.

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.

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

INTRODUCTION

Soluble amyloid beta (Aβ) oligomers have been suggested as initiating Aβ 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. Aβ and tau oligomers in the quantified cerebrospinal fluid (CSF) were measured using surface-based fluorescence intensity distribution analysis (sFIDA) technology.

RESULTS

Across groups, highest Aβ oligomer levels were found in A+ with subjective cognitive decline and mild cognitive impairment. Aβ oligomers were significantly higher in A+T- compared to A-T- and A+T+. APOE ε4 allele carriers showed significantly higher Aβ oligomer levels. No differences in tau oligomers were detected.

DISCUSSION

The accumulation of Aβ oligomers in the CSF peaks early within the AD continuum, preceding tau pathology. Disease-modifying treatments targeting Aβ oligomers might have the highest therapeutic effect in these disease stages.

Highlights

Using surface-based fluorescence intensity distribution analysis (sFIDA) technology, we quantified Aβ oligomers in cerebrospinal fluid (CSF) samples of the DZNE-Longitudinal Cognitive Impairment and Dementia (DELCODE) cohortAβ 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 Aβ oligomers decrease at advanced stages of the disease (A+T+), which might be explained by altered clearing mechanisms.

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.

Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi-kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution; (B) incorporating demographics & clinical covariates; (C) the impact of the size of the training data set; (D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of-sample predictions. The highest performance for Aβ42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status.

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-β (Aβ)42/Aβ40, phosphorylated tau (p-tau181), total tau and Aβ42/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.

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, Aβ42/40 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.

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 β = 0.117, p = 0.033) and lower MD (β = -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 Aβ42/40 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 (621–50,000) vs. 585 pg/mL (357–729), p = 0.009). One patient showed sustained, highly increased NFL levels (50,000 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.

Evidence for prospective associations among depression and obesity in population-based studies

Obesity may lead to depression or be one of its consequences. We reviewed population-based studies in order to, first, identify the most commonly used research methods, and, second, to evaluate the strength of evidence for prospective associations among obesity and depression. We examined 25 studies, of which 10 tested 'obesity-to-depression' pathways, and 15 tested 'depression-to-obesity' pathways. Descriptive statistics summarized the frequency with which various measurements, designs and data analytic strategies were used. We tallied the number of studies that reported any vs. no statistically significant associations, and report on effect sizes, identified moderating variables within reports, and sought common findings across studies. Results indicated considerable methodological heterogeneity in the literature. Depression was assessed by clinical interview in 44% of studies, weight and height were directly measured in 32%, and only 12% used both. In total, 80% of the studies reported significant obesity-to-depression associations, with odds ratios generally in the range of 1.0 to 2.0, while only 53% of the studies reported significant depression-to-obesity associations. Sex was a common moderating variable. Thus, there was good evidence that obesity is prospectively associated with increased depression, with less consistent evidence that depression leads to obesity. Recommendations for future research regarding study samples, measurement and data analysis are provided.