Automated remote speech-based testing of individuals with cognitive decline: Bayesian agreement of transcription accuracy.

Introduction: We investigated the agreement between automated and gold-standard manual transcriptions of telephone chatbot-based semantic verbal fluency testing. Methods: We examined 78 cases from the Screening over Speech in Unselected Populations for Clinical Trials in AD (PROSPECT-AD) study, including cognitively normal individuals and individuals with subjective cognitive decline, mild cognitive impairment, and dementia. We used Bayesian Bland-Altman analysis of word count and the qualitative features of semantic cluster size, cluster switches, and word frequencies. Results: We found high levels of agreement for word count, with a 93% probability of a newly observed difference being below the minimally important difference. The qualitative features had fair levels of agreement. Word count reached high levels of discrimination between cognitively impaired and unimpaired individuals, regardless of transcription mode. Discussion: Our results support the use of automated speech recognition particularly for the assessment of quantitative speech features, even when using data from telephone calls with cognitively impaired individuals in their homes. Highlights: High levels of agreement were found between automated and gold-standard manual transcriptions of telephone chatbot-based semantic verbal fluency testing, particularly for word count.The qualitative features had fair levels of agreement.Word count reached high levels of discrimination between cognitively impaired and unimpaired individuals, regardless of transcription mode.Automated speech recognition for the assessment of quantitative and qualitative speech features, even when using data from telephone calls with cognitively impaired individuals in their homes, seems feasible and reliable.

Association of Neurogranin and BACE1 With Clinical Cognitive Decline in Individuals With Subjective Cognitive Decline.

BACKGROUND AND OBJECTIVES: CSF biomarkers have immense diagnostic and prognostic potential for Alzheimer disease (AD). However, AD is still diagnosed relatively late in the disease process, sometimes even years after the initial manifestation of cognitive symptoms. Thus, further identification of biomarkers is required to detect related pathology in the preclinical stage and predict cognitive decline. Our study aimed to assess the association of neurogranin and ß-site amyloid precursor protein-cleaving enzyme 1 (BACE1) with cognitive decline in individuals with subjective cognitive decline (SCD). METHODS: We enrolled participants with available neurogranin and BACE1 measurements in CSF from the DELCODE (DZNE-Longitudinal Cognitive Impairment and Dementia, Germany) cohort. The longitudinal change of Preclinical Alzheimer's Cognitive Composite score was assessed as the primary outcome in participants with SCD and controls. The secondary outcome was defined as conversion of SCD to mild cognitive impairment (MCI) during follow-up. Levels of neurogranin, BACE1, and neurogranin/BACE1 ratio across groups were compared by analysis of covariance after adjustment for demographics. The linear mixed-effects model and Cox regression analysis were applied to evaluate their association with cognitive decline and progression of SCD to MCI, respectively. RESULTS: A total of 530 participants (mean age: 70.76 ± 6.01 years, 48.7% female) were analyzed in the study. The rate of cognitive decline was faster in individuals with SCD with higher neurogranin and neurogranin/BACE1 ratio (ß = -0.138, SE = 0.065, p = 0.037, and ß = -0.293, SE = 0.115, p = 0.013). Higher baseline neurogranin and neurogranin/BACE1 ratio were associated with an increased rate of conversion from SCD to MCI (hazard ratio [HR] 1.35 per SD, 95% CI 1.03-1.77, p = 0.028, and HR 1.53 per SD, 95% CI 1.13-2.07, p = 0.007). In addition, the impact of higher neurogranin levels on accelerating the rate of cognitive decline was more pronounced in the SCD group than in cognitively unimpaired controls (ß = -0.077, SE = 0.033, p = 0.020). DISCUSSION: Our findings suggest that CSF neurogranin and BACE1 begin to change in the preclinical stage of AD and they are associated with clinical progression in individuals with SCD.

Amyloid and SCD jointly predict cognitive decline across Chinese and German cohorts.

INTRODUCTION: Subjective cognitive decline (SCD) in amyloid-positive (Aß+) individuals was proposed as a clinical indicator of Stage 2 in the Alzheimer's disease (AD) continuum, but this requires further validation across cultures, measures, and recruitment strategies. METHODS: Eight hundred twenty-one participants from SILCODE and DELCODE cohorts, including normal controls (NC) and individuals with SCD recruited from the community or from memory clinics, underwent neuropsychological assessments over up to 6 years. Amyloid positivity was derived from positron emission tomography or plasma biomarkers. Global cognitive change was analyzed using linear mixed-effects models. RESULTS: In the combined and stratified cohorts, Aß+ participants with SCD showed steeper cognitive decline or diminished practice effects compared with NC or Aß- participants with SCD. These findings were confirmed using different operationalizations of SCD and amyloid positivity, and across different SCD recruitment settings. DISCUSSION: Aß+ individuals with SCD in German and Chinese populations showed greater global cognitive decline and could be targeted for interventional trials. HIGHLIGHTS: SCD in amyloid-positive (Aß+) participants predicts a steeper cognitive decline. This finding does not rely on specific SCD or amyloid operationalization. This finding is not specific to SCD patients recruited from memory clinics. This finding is valid in both German and Chinese populations. Aß+ older adults with SCD could be a target population for interventional trials.

Symptomatic Clusters Related to Amyloid Positivity in Cognitively Unimpaired Individuals.

Background: The NIA-AA Research Framework on Alzheimer's disease (AD) proposes a transitional stage (stage 2) characterized by subtle cognitive decline, subjective cognitive decline (SCD) and mild neurobehavioral symptoms (NPS). Objective: To identify participant clusters based on stage 2 features and assess their association with amyloid positivity in cognitively unimpaired individuals. Methods: We included baseline data of N = 338 cognitively unimpaired participants from the DELCODE cohort with data on cerebrospinal fluid biomarkers for AD. Classification into the AD continuum (i.e., amyloid positivity, A+) was based on Aß42/40 status. Neuropsychological test data were used to assess subtle objective cognitive dysfunction (OBJ), the subjective cognitive decline interview (SCD-I) was used to detect SCD, and the Neuropsychiatric Inventory Questionnaire (NPI-Q) was used to assess NPS. A two-step cluster analysis was carried out and differences in AD biomarkers between clusters were analyzed. Results: We identified three distinct participant clusters based on presented symptoms. The highest rate of A+ participants (47.6%) was found in a cluster characterized by both OBJ and SCD. A cluster of participants that presented with SCD and NPS (A+:26.6%) and a cluster of participants with overall few symptoms (A+:19.7%) showed amyloid positivity in a range that was not higher than the expected A+ rate for the age group. Across the full sample, participants with a combination of SCD and OBJ in the memory domain showed a lower Aß42/ptau181 ratio compared to those with neither SCD nor OBJ. Conclusions: The cluster characterized by participants with OBJ and concomitant SCD was enriched for amyloid pathology.

Neural Adaptation at Stimulus Onset and Speed of Neural Processing as Critical Contributors to Speech Comprehension Independent of Hearing Threshold or Age.

Background: It is assumed that speech comprehension deficits in background noise are caused by age-related or acquired hearing loss. Methods: We examined young, middle-aged, and older individuals with and without hearing threshold loss using pure-tone (PT) audiometry, short-pulsed distortion-product otoacoustic emissions (pDPOAEs), auditory brainstem responses (ABRs), auditory steady-state responses (ASSRs), speech comprehension (OLSA), and syllable discrimination in quiet and noise. Results: A noticeable decline of hearing sensitivity in extended high-frequency regions and its influence on low-frequency-induced ABRs was striking. When testing for differences in OLSA thresholds normalized for PT thresholds (PTTs), marked differences in speech comprehension ability exist not only in noise, but also in quiet, and they exist throughout the whole age range investigated. Listeners with poor speech comprehension in quiet exhibited a relatively lower pDPOAE and, thus, cochlear amplifier performance independent of PTT, smaller and delayed ABRs, and lower performance in vowel-phoneme discrimination below phase-locking limits (/o/-/u/). When OLSA was tested in noise, listeners with poor speech comprehension independent of PTT had larger pDPOAEs and, thus, cochlear amplifier performance, larger ASSR amplitudes, and higher uncomfortable loudness levels, all linked with lower performance of vowel-phoneme discrimination above the phase-locking limit (/i/-/y/). Conslusions: This study indicates that listening in noise in humans has a sizable disadvantage in envelope coding when basilar-membrane compression is compromised. Clearly, and in contrast to previous assumptions, both good and poor speech comprehension can exist independently of differences in PTTs and age, a phenomenon that urgently requires improved techniques to diagnose sound processing at stimulus onset in the clinical routine.

Inferior Frontal Sulcal Hyperintensities on Brain MRI Are Associated with Amyloid Positivity beyond Age-Results from the Multicentre Observational DELCODE Study.

Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer's disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aß42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05-3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57-2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00-1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26-0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid ß beyond age.

Single-value brain activity scores reflect both severity and risk across the Alzheimer's continuum.

Single-value scores reflecting the deviation from (FADE score) or similarity with (SAME score) prototypical novelty-related and memory-related functional magnetic resonance imaging (fMRI) activation patterns in young adults have been proposed as imaging biomarkers of healthy neurocognitive aging. Here, we tested the utility of these scores as potential diagnostic and prognostic markers in Alzheimer's disease (AD) and risk states like mild cognitive impairment (MCI) or subjective cognitive decline (SCD). To this end, we analyzed subsequent memory fMRI data from individuals with SCD, MCI, and AD dementia as well as healthy controls (HC) and first-degree relatives of AD dementia patients (AD-rel) who participated in the multi-center DELCODE study (N = 468). Based on the individual participants' whole-brain fMRI novelty and subsequent memory responses, we calculated the FADE and SAME scores and assessed their association with AD risk stage, neuropsychological test scores, CSF amyloid positivity, and ApoE genotype. Memory-based FADE and SAME scores showed a considerably larger deviation from a reference sample of young adults in the MCI and AD dementia groups compared to HC, SCD and AD-rel. In addition, novelty-based scores significantly differed between the MCI and AD dementia groups. Across the entire sample, single-value scores correlated with neuropsychological test performance. The novelty-based SAME score further differed between Aß-positive and Aß-negative individuals in SCD and AD-rel, and between ApoE ε4 carriers and non-carriers in AD-rel. Hence, FADE and SAME scores are associated with both cognitive performance and individual risk factors for AD. Their potential utility as diagnostic and prognostic biomarkers warrants further exploration, particularly in individuals with SCD and healthy relatives of AD dementia patients.

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 ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease 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 ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer's disease 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 whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer's disease 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 Alzheimer's disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants 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 mild cognitive impairment 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, at both the subject and the group level, was 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 Alzheimer's disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer's disease.

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.

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.

Whole-body metabolic modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease.

In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Fornix fractional anisotropy mediates the association between Mediterranean diet adherence and memory four years later in older adults without dementia.

Here, we investigated whether fractional anisotropy (FA) of hippocampus-relevant white-matter tracts mediates the association between baseline Mediterranean diet adherence (MeDiAd) and verbal episodic memory over four years. Participants were healthy older adults with and without subjective cognitive decline and patients with amnestic mild cognitive impairment from the DELCODE cohort study (n = 376; age: 71.47 ± 6.09 years; 48.7 % female). MeDiAd and diffusion data were obtained at baseline. Verbal episodic memory was assessed at baseline and four yearly follow-ups. The associations between baseline MeDiAd and white matter, and verbal episodic memory's mean and rate of change over four years were tested with latent growth curve modeling. Baseline MeDiAd was associated with verbal episodic memory four years later (95 % confidence interval, CI [0.01, 0.32]) but not with its rate of change over this period. Baseline Fornix FA mediated - and, thus, explained - that association (95 % CI [0.002, 0.09]). Fornix FA may be an appropriate response biomarker of Mediterranean diet interventions on verbal memory in older adults.

Prognostic Value of Gut Microbiome for Conversion from Mild Cognitive Impairment to Alzheimer's Disease Dementia within 4 Years: Results from the AlzBiom Study.

Alterations in the gut microbiome are associated with the pathogenesis of Alzheimer's disease (AD) and can be used as a diagnostic measure. However, longitudinal data of the gut microbiome and knowledge about its prognostic significance for the development and progression of AD are limited. The aim of the present study was to develop a reliable predictive model based on gut microbiome data for AD development. In this longitudinal study, we investigated the intestinal microbiome in 49 mild cognitive impairment (MCI) patients over a mean (SD) follow-up of 3.7 (0.6) years, using shotgun metagenomics. At the end of the 4-year follow-up (4yFU), 27 MCI patients converted to AD dementia and 22 MCI patients remained stable. The best taxonomic model for the discrimination of AD dementia converters from stable MCI patients included 24 genera, yielding an area under the receiver operating characteristic curve (AUROC) of 0.87 at BL, 0.92 at 1yFU and 0.95 at 4yFU. The best models with functional data were obtained via analyzing 25 GO (Gene Ontology) features with an AUROC of 0.87 at BL, 0.85 at 1yFU and 0.81 at 4yFU and 33 KO [Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog] features with an AUROC of 0.79 at BL, 0.88 at 1yFU and 0.82 at 4yFU. Using ensemble learning for these three models, including a clinical model with the four parameters of age, gender, body mass index (BMI) and Apolipoprotein E (ApoE) genotype, yielded an AUROC of 0.96 at BL, 0.96 at 1yFU and 0.97 at 4yFU. In conclusion, we identified novel and timely stable gut microbiome algorithms that accurately predict progression to AD dementia in individuals with MCI over a 4yFU period.

Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition.

Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aß42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aß when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.

Dysfunction of specific auditory fibers impacts cortical oscillations, driving an autism phenotype despite near-normal hearing.

Autism spectrum disorder is discussed in the context of altered neural oscillations and imbalanced cortical excitation-inhibition of cortical origin. We studied here whether developmental changes in peripheral auditory processing, while preserving basic hearing function, lead to altered cortical oscillations. Local field potentials (LFPs) were recorded from auditory, visual, and prefrontal cortices and the hippocampus of BdnfPax2 KO mice. These mice develop an autism-like behavioral phenotype through deletion of BDNF in Pax2+ interneuron precursors, affecting lower brainstem functions, but not frontal brain regions directly. Evoked LFP responses to behaviorally relevant auditory stimuli were weaker in the auditory cortex of BdnfPax2 KOs, connected to maturation deficits of high-spontaneous rate auditory nerve fibers. This was correlated with enhanced spontaneous and induced LFP power, excitation-inhibition imbalance, and dendritic spine immaturity, mirroring autistic phenotypes. Thus, impairments in peripheral high-spontaneous rate fibers alter spike synchrony and subsequently cortical processing relevant for normal communication and behavior.

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline.

INTRODUCTION: We investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum. METHODS: We studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid. RESULTS: We found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline. DISCUSSION: Latent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy: A Bayesian Approach.

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.

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.

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.

Whole-body modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease.

In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilized whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalized models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.