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Introduction: In this multicenter study on subjective cognitive decline (SCD) in community-based and memory clinic settings, we assessed the (1) incidence of Alzheimer’s disease (AD) and non-AD dementia and (2) determinants of progression to dementia. Methods: Eleven cohorts provided 2978 participants with SCD and 1391 controls. We estimated dementia incidence and identified risk factors using Cox proportional hazards models. Results: In SCD, incidence of dementia was 17.7 (95% Poisson confidence interval 15.2–20.3)/1000 person-years (AD: 11.5 [9.6–13.7], non-AD: 6.1 [4.7–7.7]), compared with 14.2 (11.3–17.6) in controls (AD: 10.1 [7.7–13.0], non-AD: 4.1 [2.6–6.0]). The risk of dementia was strongly increased in SCD in a memory clinic setting but less so in a community-based setting. In addition, higher age (hazard ratio 1.1 [95% confidence interval 1.1–1.1]), lower Mini-Mental State Examination (0.7 [0.66–0.8]), and apolipoprotein E ε4 (1.8 [1.3–2.5]) increased the risk of dementia. Discussion: SCD can precede both AD and non-AD dementia. Despite their younger age, individuals with SCD in a memory clinic setting have a higher risk of dementia than those in community-based cohorts.

ObjectiveWe investigated the association of plasma amyloid beta (Abeta)40, Abeta42, and total tau (tTau) with the presence of Alzheimer pathological changes in cognitively normal individuals with subjective cognitive decline (SCD).MethodsWe included 248 subjects with SCD (61 ± 9 years, 42% female, Mini‐Mental State Examination = 28 ± 2) from the SCIENCe project and Amsterdam Dementia Cohort. Subjects were dichotomized as amyloid abnormal by cerebrospinal fluid (CSF) and positron emission tomography (PET). Baseline plasma Abeta40, Abeta42, and tTau were measured using Simoa technology. Associations between plasma levels and amyloid status were assessed using logistic regression analyses and receiver operating characteristic analyses. Association of plasma levels with risk of clinical progression to mild cognitive impairment (MCI) or dementia was assessed using Cox proportional hazard models.ResultsFifty‐seven (23%) subjects were CSF‐amyloid abnormal. Plasma Abeta42/Abeta40 ratio and plasma Abeta42 alone, but not tTau, identified abnormal CSF‐amyloid status (plasma ratio: area under the curve [AUC] = 77%, 95% confidence interval [CI] = 69–84%; plasma Abeta42: AUC = 66%, 95% CI: 58–74%). Combining plasma ratio with age and apolipoprotein E resulted in AUC = 83% (95% CI = 77–89%). The Youden cutoff of the plasma ratio gave a sensitivity of 76% and specificity of 75%, and applying this as a prescreener would reduce the number of lumbar punctures by 51%. Using PET as outcome, a comparable reduction in number of PET scans would be achieved when applying the plasma ratio as prescreener. In addition, low plasma ratio was associated with clinical progression to MCI or dementia (hazard ratio = 2.0, 95% CI = 1.4–2.3).InterpretationPlasma Abeta42/Abeta40 ratio has potential as a prescreener to identify Alzheimer pathological changes in cognitively normal individuals with SCD. Ann Neurol 2018;84:656–666

Background Blood-based biomarkers for Alzheimer’s disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity. Methods We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET−), mild cognitive impairment (26 PET+, 24 PET−), or AD-dementia (132 PET+). Plasma Abeta(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald’s backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman’s correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA). Results Abeta(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83–93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = − 0.40 to − 0.26; NfL: range sβ = − 0.35 to − 0.18; all: p < 0.002), whereas Abeta(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 – 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman’s rho> 0.33, p < 0.001). Abeta(1-42/1-40) showed a moderate negative correlation with MTA (Spearman’s rho = − 0.24, p = 0.001). Discussion and conclusions Combination of plasma Abeta(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.