Search

Background: Diagnosis of dementia with Lewy bodies (DLB) remains challenging and biomarkers discriminating DLB from Alzheimer's disease (AD) are highly needed. We aimed to establish the specific cerebrospinal fluid (CSF) proteomic changes that underlie DLB and to identify translatable diagnostic biomarkers. Methods: Proximity extension‐based multiplex immunoassays were used to measure 665 proteins in 534 CSF samples from patients with Dementia with Lewy bodies (n=109), AD‐dementia (n=235) and cognitively‐unimpaired controls (CON, n=190) from the Amsterdam Dementia cohort (ADC) and Penn University. An additional multicenter cohort (n=307) from ADC and SPIN was used for validation of custom assays. A positive/negative AD CSF profile supported the diagnosis of AD and CON respectively. Results: Nested linear models identified 97 CSF proteins with altered abundance in DLB compared to controls (p<0.05). After comparison with the AD CSF proteome, we observed that 52 of these proteins (54%) were especially associated to DLB (e.g. DDC, GH, FCER2, MMP1), while 15 proteins (16%) showed opposite changes to those detected in AD patients (CRH, MMP3). The protein with the highest fold‐changed observed in DLB was L‐amino acid decarboxylase (DDC; >1.5 fold‐change vs.CN or AD; q<1E‐16), an enzyme involved in dopamine biosynthesis. DDC could optimally discriminate DLB from controls and AD patients (AUC: 0.91 and 0.81 respectively). Using penalized generalized linear modelling we identified a panel of 7‐CSF markers including DDC that could discriminate DLB from AD patients with high accuracy (AUC: 0.93, 95%CI: 0.86‐0.98), which have been successfully translated into customized multiplex assays (correlations > 0.84 with discovery measurements). Conclusions: We unveil CSF changes specifically related to DLB and identified a panel of 7‐CSF markers associated to several aspects of DLB pathophysiology that enables discrimination of these dementia types with high accuracy. Multiplex custom assays containing these markers are currently being clinically validated in independent cohorts for their potential use in diagnostic settings or clinical trials. [ABSTRACT FROM AUTHOR]

Background: The development of disease‐modifying therapies against Alzheimer's disease (AD) requires biomarker panels that reflect the diverse pathological pathways specifically involved in AD. Here we aimed to identify and validate panels of cerebrospinal fluid (CSF) proteins covering different molecular pathways for early and specific diagnosis of AD. Method: We measured 665 proteins in 797 CSF samples from patients with mild cognitive impairment with abnormal amyloid (MCI(Aβ+): n=50), AD‐dementia (n=230), non‐AD dementias (n=322; 123 DLB and 199 FTD) and cognitively‐unimpaired controls (n=195; classical AD CSF biomarkers negative) using proximity ligation‐based multiplex immunoassays. Nested and penalized linear modeling were used to identify protein differences (q<0,05) and translatable classification signatures. Result: We detected highly dysregulated CSF proteins in MCI(Aβ+) or AD compared to controls (112 and 288 proteins respectively, lowest q:1‐15 and 1‐23), as well as between AD and non‐AD dementias (469 proteins; lowest q:1‐29). We confirmed previous findings (e.g., DDAH1, ENO2, PARK7), but we also identified novel proteins especially associated to the prodromal and/or dementia AD stages (e.g., ABL1, SCD4, ENTPD5). Proteins dysregulated in MCI(Aβ+) were primarily related to oxidative stress and energy metabolism, while those specifically dysregulated in later stages of AD dementia were related to cell remodeling, vascular function and immune system. Using penalised generalised linear modeling we identified the minimal number of markers with maximal power to discriminate clinical groups: for MCI(Aβ+) vs. controls: 10‐CSF proteins, AUC:0.99 (95%CI:0.97‐1); for AD vs. controls: 8‐CSF proteins, AUC:0.95 (95%CI:0.92‐0.99) and for AD vs. non‐AD dementias: 9‐CSF proteins, AUC:0.87 (95%CI:0.81‐0.93). The CSF panel discriminating AD from cognitively unimpaired controls was validated in an independent external cohort (n=62, AUC:0.94). Only 3 proteins overlapped across panels, suggesting that the panels with the strongest discriminative power are specific for disease stage and clinical group. Conclusion: This unprecedented large and protein‐rich CSF study indicates that CSF proteome follows a highly dynamic trajectory with distinct CSF profiles associated to different biological processes along the AD continuum. We unveil optimal CSF biomarker panels reflecting the specific multifactorial nature of AD, which can be now translated into customised assays for widespread validation and potential use in heterogeneous diagnostic settings or clinical trials. [ABSTRACT FROM AUTHOR]