Injury markers predict time to dementia in subjects with MCI and amyloid pathology

OBJECTIVES: Alzheimer disease (AD) can now be diagnosed in subjects with mild cognitive impairment (MCI) using biomarkers. However, little is known about the rate of decline in those subjects. In this cohort study, we aimed to assess the conversion rate to dementia and identify prognostic markers in subjects with MCI and evidence of amyloid pathology. METHODS: We pooled subjects from the VU University Medical Center Alzheimer Center and the Development of Screening Guidelines and Criteria for Predementia Alzheimer's Disease (DESCRIPA) study. We included subjects with MCI, an abnormal level of β-amyloid(1-42) (Aβ(1-42)) in the CSF, and at least one diagnostic follow-up visit. We assessed the effect of APOE genotype, CSF total tau (t-tau) and tau phosphorylated at threonine 181 (p-tau) and hippocampal volume on time to AD-type dementia using Cox proportional hazards models and on decline on the Mini-Mental State Examination (MMSE) using linear mixed models. RESULTS: We included 110 subjects with MCI with abnormal CSF Aβ(1-42) and a mean MMSE score of 26.3 ± 2.8. During a mean follow-up of 2.2 ± 1.0 (range 0.4-5.0) years, 63 subjects (57%) progressed to AD-type dementia. Abnormal CSF t-tau (hazard ratio [HR] 2.3, 95% confidence interval [CI] 1.1-4.6, p = 0.03) and CSF p-tau (HR 3.5, 95% CI 1.3-9.2, p = 0.01) concentration and hippocampal atrophy (HR 2.5, 95% CI 1.1-5.6, p = 0.02) predicted time to dementia. For subjects with both abnormal t-tau concentration and hippocampal atrophy, HR was 7.3 (95% CI 1.0-55.9, p = 0.06). Furthermore, abnormal CSF t-tau and p-tau concentrations and hippocampal atrophy predicted decline in MMSE score. CONCLUSIONS: In subjects with MCI and evidence of amyloid pathology, the injury markers CSF t-tau and p-tau and hippocampal atrophy can predict further cognitive decline

Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline (vol 9, 101, 2017)

Pathophysiology, epidemiology and therapy of agein

Validation of plasma proteomic biomarkers relating to brain amyloid burden in the EMIF-Alzheimer's disease multimodal biomarker discovery cohort

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ϵ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure

Characteristics of subjective cognitive decline associated with amyloid positivity

Introduction: The evidence for characteristics of persons with subjective cognitive decline (SCD) associated with amyloid positivity is limited. Methods: In 1640 persons with SCD from 20 Amyloid Biomarker Study cohort, we investigated the associations of SCD-specific characteristics (informant confirmation, domain-specific complaints, concerns, feelings of worse performance) demographics, setting, apolipoprotein E gene (APOE) ε4 carriership, and neuropsychiatric symptoms with amyloid positivity. Results: Between cohorts, amyloid positivity in 70-year-olds varied from 10% to 76%. Only older age, clinical setting, and APOE ε4 carriership showed univariate associations with increased amyloid positivity. After adjusting for these, lower education was also associated with increased amyloid positivity. Only within a research setting, informant-confirmed complaints, memory complaints, attention/concentration complaints, and no depressive symptoms were associated with increased amyloid positivity. Feelings of worse performance were associated with less amyloid positivity at younger ages and more at older ages. Discussion: Next to age, setting, and APOE ε4 carriership, SCD-specific characteristics may facilitate the identification of amyloid-positive individuals

Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

IMPORTANCE One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.OBJECTIVE To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.DESIGN, SETTING, AND PARTICIPANTS This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.EXPOSURES Alzheimer disease biomarkers detected on PET or in CSF.MAIN OUTCOMES AND MEASURES Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.RESULTS Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PETand CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for dinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).CONCLUSIONS AND RELEVANCE This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies

Duration of care trajectories in persons with dementia differs according to demographic and clinical characteristics.

Objectives To estimate: (1) the duration of no formal care, home care, and institutional care after dementia diagnosis, (2) the effect of age, sex, living situation, dementia medication, migration background, and income on this dementia care duration. Design Longitudinal retrospective study using routinely recorded general practice electronic health records linked with population-based healthcare and mortality data. Setting and participants In total, 11,012 community-dwelling persons who received an incident dementia diagnosis and were listed in a Dutch general practitioner database from 448 general practices in the Netherlands. Methods Using multistate modeling analyses, we estimated the mean duration of care types (no/home/institutional care) for different ages based on simulations of transition rates and examined the influence of demographic and clinical factors on these durations. Results From dementia diagnosis onward in 85-year-old men, the mean duration without formal care was 0.7 years, of home care 1.7, and institutional care 1.1 years. In 85-year-old women, the duration without formal care was 0.8 years, of home care 2.3, and institutional care 2.3 years. Total care duration was 3.5 years in 85-year-old men and 5.4 years in 85-year-old women. In men, the duration of home care was longer compared with no formal care and institutional care. The duration of no formal care was longer in persons not living alone, without prescribed dementia medication, with a non‒Western migration background, or with a higher income. The duration of home or institutional care was longer in women, persons without polypharmacy, in those living alone, or those with a Western background. Conclusions and implications Our findings help to increase understanding of long-term dementia care trajectories and show that demographic and clinical factors determine the duration of care types. Our results can contribute to the organization of healthcare resource planning and monitoring of the effects of healthcare policy and interventions

Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders

The prevalence of somatic insulinopathies, like metabolic syndrome (MetS), obesity, and type 2 diabetes mellitus (T2DM), is higher in Alzheimer's disease (AD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD). Dysregulation of insulin signalling has been implicated in these neuropsychiatric disorders, and shared genetic factors might partly underlie this observed multimorbidity. We investigated the genetic overlap between AD, ASD, and OCD with MetS, obesity, and T2DM by estimating pairwise global genetic correlations using the summary statistics of the largest available genome-wide association studies for these phenotypes. Having tested these hypotheses, other potential brain "insulinopathies" were also explored by estimating the genetic relationship of six additional neuropsychiatric disorders with nine insulin-related diseases/traits. Stratified covariance analyses were then performed to investigate the contribution of insulin-related gene sets. Significant negative genetic correlations were found between OCD and MetS (r(g) = -0.315, p = 3.9 x 10(-8)), OCD and obesity (r(g) = -0.379, p = 3.4 x 10(-5)), and OCD and T2DM (r(g) = -0.172, p = 3 x 10(-4)). Significant genetic correlations with insulin-related phenotypes were also found for anorexia nervosa (AN), attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, and schizophrenia (p < 6.17 x 10(-4)). Stratified analyses showed negative genetic covariances between AD, ASD, OCD, ADHD, AN, bipolar disorder, schizophrenia and somatic insulinopathies through gene sets related to insulin signalling and insulin receptor recycling, and positive genetic covariances between AN and T2DM, as well as ADHD and MetS through gene sets related to insulin processing/secretion (p < 2.06 x 10(-4)). Overall, our findings suggest the existence of two dusters of neuropsychiatric disorders, in which the genetics of insulin-related diseases/traits may exert divergent pleiotropic effects. These results represent a starting point for a new research line on "insulinopathies" of the brain