A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline

OBJECTIVES: Grey matter network disruptions in Alzheimer's disease (AD) are associated with worse cognitive impairment cross-sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD). EXPERIMENTAL DESIGN: We included 231 individuals with SCD who had annually repeated neuropsychological assessment (3 ± 1 years; n = 646 neuropsychological investigations) available from the Amsterdam Dementia Cohort (54% male, age: 63 ± 9, MMSE: 28 ± 2). Single-subject grey matter networks were extracted from baseline 3D-T1 MRI scans and we computed basic network (size, degree, connectivity density) and higher-order (path length, clustering, betweenness centrality, normalized path length [lambda] and normalized clustering [gamma]) parameters at whole brain and/or regional levels. We tested associations of network parameters with baseline and annual cognition (memory, attention, executive functioning, language composite scores, and global cognition [all domains with MMSE]) using linear mixed models, adjusted for age, sex, education, scanner and total gray matter volume. PRINCIPAL OBSERVATIONS: Lower network size was associated with steeper decline in language (β ± SE = 0.12 ± 0.05, p < 0.05FDR). Higher-order network parameters showed no cross-sectional associations. Lower gamma and lambda values were associated with steeper decline in global cognition (gamma: β ± SE = 0.06 ± 0.02); lambda: β ± SE = 0.06 ± 0.02), language (gamma: β ± SE = 0.11 ± 0.04; lambda: β ± SE = 0.12 ± 0.05; all p < 0.05FDR). Lower path length values in precuneus and fronto-temporo-occipital cortices were associated with a steeper decline in global cognition. CONCLUSIONS: A more randomly organized grey matter network was associated with a steeper decline of cognitive functioning, possibly indicating the start of cognitive impairment

ATN classification and clinical progression in subjective cognitive decline

Objective: To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD). / Methods: We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD. / Results: Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition. / Conclusions: Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic

Subjective Cognitive Impairment Cohort (SCIENCe): study design and first results

BACKGROUND: We aimed to describe the Subjective Cognitive Impairment Cohort (SCIENCe) study design, to crosssectionally describe participant characteristics, and to evaluate the SCD-plus criteria. METHODS: The SCIENCe is a prospective cohort study of subjective cognitive decline (SCD) patients. Participants undergo extensive assessment, including cerebrospinal fluid collection and optional amyloid positron emission tomography scan, with annual follow-up. The primary outcome measure is clinical progression. RESULTS: Cross-sectional evaluation of the first 151 participants (age 64 ± 8, 44% female, Mini-Mental State Examination 29 ± 2) showed that 28 (25%) had preclinical Alzheimer’s disease (AD) (amyloid status available n = 114 (75%)), 58 (38%) had subthreshold psychiatry, and 65 (43%) had neither. More severe subjective complaints were associated with worse objective performance. The SCD-plus criteria age ≥ 60 (OR 7.7 (95% CI 1.7–38.9)) and apolipoprotein E (genotype) e4 (OR 4.8 (95% CI 1.6–15.0)) were associated with preclinical AD. CONCLUSIONS: The SCIENCe study confirms that SCD is a heterogeneous group, with preclinical AD and subthreshold psychiatric features. We found a number of SCD-plus criteria to be associated with preclinical AD. Further inclusion and follow-up will address important questions related to SCD

Personalized risk for clinical progression in cognitively normal subjects—the ABIDE project

Background: Biomarkers such as cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) have predictive value for progression to dementia in patients with mild cognitive impairment (MCI). The pre-dementia stage takes far longer, and the interpretation of biomarker findings is particular relevant for individuals who present at a memory clinic, but are deemed cognitively normal. The objective of the current study is to construct biomarker-based prognostic models for personalized risk of clinical progression in cognitively normal individuals presenting at a memory clinic. / Methods: We included 481 individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort. Prognostic models were developed by Cox regression with patient characteristics, MRI, and/or CSF biomarkers to predict clinical progression to MCI or dementia. We estimated 5- and 3-year individualized risks based on patient-specific values. External validation was performed on Alzheimer’s Disease Neuroimaging Initiative (ADNI) and an European dataset. / Results: Based on demographics only (Harrell’s C = 0.70), 5- and 3-year progression risks varied from 6% [3–11] and 4% [2–8] (age 55, MMSE 30) to 38% [29–49] and 28% [21–37] (age 70, MMSE 27). Normal CSF biomarkers strongly decreased progression probabilities (Harrell’s C = 0.82). By contrast, abnormal CSF markedly increased risk (5 years, 96% [56–100]; 3 years, 89% [44–99]). The CSF model could reclassify 58% of the individuals with an “intermediate” risk (35–65%) based on the demographic model. MRI measures were not retained in the models. / Conclusion: The current study takes the first steps in a personalized approach for cognitively normal individuals by providing biomarker-based prognostic models

Computer-assisted prediction of clinical progression in the earliest stages of AD

INTRODUCTION: Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression. METHODS: We included 674 patients with SCD (46% female, 64 ± 9 years, Mini–Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts. RESULTS: After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8). DISCUSSION: We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable

Prevalence of abnormal Alzheimer’s disease biomarkers in patients with subjective cognitive decline: cross-sectional comparison of three European memory clinic samples

INTRODUCTION: Subjective cognitive decline (SCD) in cognitively unimpaired older individuals has been recognized as an early clinical at-risk state for Alzheimer’s disease (AD) dementia and as a target population for future dementia prevention trials. Currently, however, SCD is heterogeneously defined across studies, potentially leading to variations in the prevalence of AD pathology. Here, we compared the prevalence and identified common determinants of abnormal AD biomarkers in SCD across three European memory clinics participating in the European initiative on harmonization of SCD in preclinical AD (Euro-SCD). METHODS: We included three memory clinic SCD samples with available cerebrospinal fluid (CSF) biomaterial (IDIBAPS, Barcelona, Spain, n = 44; Amsterdam Dementia Cohort (ADC), The Netherlands, n = 50; DELCODE multicenter study, Germany, n = 42). CSF biomarkers (amyloid beta (Aβ)42, tau, and phosphorylated tau (ptau181)) were centrally analyzed in Amsterdam using prespecified cutoffs to define prevalence of pathological biomarker concentrations. We used logistic regression analysis in the combined sample across the three centers to investigate center effects with regard to likelihood of biomarker abnormality while taking potential common predictors (e.g., age, sex, apolipoprotein E (APOE) status, subtle cognitive deficits, depressive symptoms) into account. RESULTS: The prevalence of abnormal Aβ42, but not tau or ptau181, levels was different across centers (64% DELCODE, 57% IDIBAPS, 22% ADC; p < 0.001). Logistic regression analysis revealed that the likelihood of abnormal Aβ42 (and also abnormal tau or ptau181) levels was predicted by age and APOE status. For Aβ42 abnormality, we additionally observed a center effect, indicating between-center heterogeneity not explained by age, APOE, or the other included covariates. CONCLUSIONS: While heterogeneous frequency of abnormal Aβ42 was partly explained by between-sample differences in age range and APOE status, the additional observation of center effects indicates between-center heterogeneity that may be attributed to different recruitment procedures. These findings highlight the need for the development of harmonized recruitment protocols for SCD case definition in multinational studies to achieve similar enrichment rates of preclinical AD

Differential associations of APOE-ε2 and APOE-ε4 alleles with PET-measured amyloid-β and tau deposition in older individuals without dementia

Data de publicació electrònica: 01-02-2021Purpose: To examine associations between the APOE-ε2 and APOE-ε4 alleles and core Alzheimer's disease (AD) pathological hallmarks as measured by amyloid-β (Aβ) and tau PET in older individuals without dementia. Methods: We analyzed data from 462 ADNI participants without dementia who underwent Aβ ([18F]florbetapir or [18F]florbetaben) and tau ([18F]flortaucipir) PET, structural MRI, and cognitive testing. Employing APOE-ε3 homozygotes as the reference group, associations between APOE-ε2 and APOE-ε4 carriership with global Aβ PET and regional tau PET measures (entorhinal cortex (ERC), inferior temporal cortex, and Braak-V/VI neocortical composite regions) were investigated using linear regression models. In a subset of 156 participants, we also investigated associations between APOE genotype and regional tau accumulation over time using linear mixed models. Finally, we assessed whether Aβ mediated the cross-sectional and longitudinal associations between APOE genotype and tau. Results: Compared to APOE-ε3 homozygotes, APOE-ε2 carriers had lower global Aβ burden (βstd [95% confidence interval (CI)]: - 0.31 [- 0.45, - 0.16], p = 0.034) but did not differ on regional tau burden or tau accumulation over time. APOE-ε4 participants showed higher Aβ (βstd [95%CI]: 0.64 [0.42, 0.82], p < 0.001) and tau burden (βstd range: 0.27-0.51, all p < 0.006). In mediation analyses, APOE-ε4 only retained an Aβ-independent effect on tau in the ERC. APOE-ε4 showed a trend towards increased tau accumulation over time in Braak-V/VI compared to APOE-ε3 homozygotes (βstd [95%CI]: 0.10 [- 0.02, 0.18], p = 0.11), and this association was fully mediated by baseline Aβ. Conclusion: Our data suggest that the established protective effect of the APOE-ε2 allele against developing clinical AD is primarily linked to resistance against Aβ deposition rather than tau pathology