CSF protein biomarkers predicting longitudinal reduction of CSF β-amyloid42 in cognitively healthy elders.

β-amyloid (Aβ) plaque accumulation is a hallmark of Alzheimer's disease (AD). It is believed to start many years prior to symptoms and is reflected by reduced cerebrospinal fluid (CSF) levels of the peptide Aβ1-42 (Aβ42). Here we tested the hypothesis that baseline levels of CSF proteins involved in microglia activity, synaptic function and Aβ metabolism predict the development of Aβ plaques, assessed by longitudinal CSF Aβ42 decrease in cognitively healthy people. Forty-six healthy people with three to four serial CSF samples were included (mean follow-up 3 years, range 2-4 years). There was an overall reduction in Aβ42 from a mean concentration of 211-195 pg ml(-1) after 4 years. Linear mixed-effects models using longitudinal Aβ42 as the response variable, and baseline proteins as explanatory variables (n=69 proteins potentially relevant for Aβ metabolism, microglia or synaptic/neuronal function), identified 10 proteins with significant effects on longitudinal Aβ42. The most significant proteins were angiotensin-converting enzyme (ACE, P=0.009), Chromogranin A (CgA, P=0.009) and Axl receptor tyrosine kinase (AXL, P=0.009). Receiver-operating characteristic analysis identified 11 proteins with significant effects on longitudinal Aβ42 (largely overlapping with the proteins identified by linear mixed-effects models). Several proteins (including ACE, CgA and AXL) were associated with Aβ42 reduction only in subjects with normal baseline Aβ42, and not in subjects with reduced baseline Aβ42. We conclude that baseline CSF proteins related to Aβ metabolism, microglia activity or synapses predict longitudinal Aβ42 reduction in cognitively healthy elders. The finding that some proteins only predict Aβ42 reduction in subjects with normal baseline Aβ42 suggest that they predict future development of the brain Aβ pathology at the earliest stages of AD, prior to widespread development of Aβ plaques

Cerebrospinal fluid markers including trefoil factor 3 are associated with neurodegeneration in amyloid-positive individuals.

We aimed to identify cerebrospinal fluid (CSF) biomarkers associated with neurodegeneration in individuals with and without CSF evidence of Alzheimer pathology. We investigated 287 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects (age=74.9±6.9; 22/48/30% with Alzheimer's disease/mild cognitive impairment/controls) with CSF multiplex analyte data and serial volumetric MRI. We calculated brain and hippocampal atrophy rates, ventricular expansion and Mini Mental State Examination decline. We used false discovery rate corrected regression analyses to assess associations between CSF variables and atrophy rates in individuals with and without amyloid pathology, adjusting in stages for tau, baseline volume, p-tau, age, sex, ApoE4 status and diagnosis. Analytes showing statistically significant independent relationships were entered into reverse stepwise analyses. Adjusting for tau, baseline volume, p-tau, age, sex and ApoE4, 4/83 analytes were significantly independently associated with brain atrophy rate, 1/83 with ventricular expansion and 2/83 with hippocampal atrophy. The strongest CSF predictor for the three atrophy measures was low trefoil factor 3 (TFF3). High cystatin C (CysC) was associated with higher whole brain atrophy and hippocampal atrophy rates. Lower levels of vascular endothelial growth factor and chromogranin A (CrA) were associated with higher whole brain atrophy. In exploratory reverse stepwise analyses, lower TFF3 was associated with higher rates of whole brain, hippocampal atrophy and ventricular expansion. Lower levels of CrA were associated with higher whole brain atrophy rate. The relationship between low TFF3 and increased hippocampal atrophy rate remained after adjustment for diagnosis. We identified a series of CSF markers that are independently associated with rate of neurodegeneration in amyloid-positive individuals. TFF3, a substrate for NOTCH processing may be an important biomarker of neurodegeneration across the Alzheimer spectrum

Analytical and Clinical Performance of Amyloid-Beta Peptides Measurements in CSF of ADNIGO/2 Participants by an LC–MS/MS Reference Method

BACKGROUND: Cerebrospinal fluid (CSF) amyloid-β1-42 (Aβ42) reliably detects brain amyloidosis based on its high concordance with plaque burden at autopsy and with amyloid positron emission tomography (PET) ligand retention observed in several studies. Low CSF Aβ42 concentrations in normal aging and dementia are associated with the presence of fibrillary Aβ across brain regions detected by amyloid PET imaging. METHODS: An LC-MS/MS reference method for Aβ42, modified by adding Aβ40 and Aβ38 peptides to calibrators, was used to analyze 1445 CSF samples from ADNIGO/2 participants. Seventy runs were completed using 2 different lots of calibrators. For preparation of Aβ42 calibrators and controls spiking solution, reference Aβ42 standard with certified concentration was obtained from EC-JRC-IRMM (Belgium). Aβ40 and Aβ38 standards were purchased from rPeptide. Aβ42 calibrators' accuracy was established using CSF-based Aβ42 Certified Reference Materials (CRM). RESULTS: CRM-adjusted Aβ42 calibrator concentrations were calculated using the regression equation Y (CRM-adjusted) = 0.89X (calibrators) + 32.6. Control samples and CSF pools yielded imprecision ranging from 6.5 to 10.2% (Aβ42) and 2.2 to 7.0% (Aβ40). None of the CSF pools showed statistically significant differences in Aβ42 concentrations across 2 different calibrator lots. Comparison of Aβ42 with Aβ42/Aβ40 showed that the ratio improved concordance with concurrent [18F]-florbetapir PET as a measure of fibrillar Aβ (n = 766) from 81 to 88%. CONCLUSIONS: Long-term performance assessment substantiates our modified LC-MS/MS reference method for 3 Aβ peptides. The improved diagnostic performance of the CSF ratio Aβ42/Aβ40 suggests that Aβ42 and Aβ40 should be measured together and supports the need for an Aβ40 CRM

Cerebrospinal fluid biomarker panel of synaptic dysfunction in Alzheimer's disease and other neurodegenerative disorders

Introduction: Synaptic degeneration is a key part of the pathophysiology of neurodegenerative diseases, and biomarkers reflecting the pathological alterations are greatly needed. Method: Seventeen synaptic proteins were quantified in a pathology-confirmed cerebrospinal fluid cohort of patients with Alzheimer's disease (AD; n = 63), frontotemporal lobar degeneration (FTLD; n = 53), and Lewy body spectrum of disorders (LBD; n = 21), as well as healthy controls (HC; n = 48). Results: Comparisons revealed four distinct patterns: markers decreased across all neurodegenerative conditions compared to HC (the neuronal pentraxins), markers increased across all neurodegenerative conditions (14-3-3 zeta/delta), markers selectively increased in AD compared to other neurodegenerative conditions (neurogranin and beta-synuclein), and markers selectively decreased in LBD and FTLD compared to HC and AD (AP2B1 and syntaxin-1B). Discussion: Several of the synaptic proteins may serve as biomarkers for synaptic dysfunction in AD, LBD, and FTLD. Additionally, differential patterns of synaptic protein alterations seem to be present across neurodegenerative diseases. Highlights: A panel of synaptic proteins were quantified in the cerebrospinal fluid using mass spectrometry. We compared Alzheimer's disease, frontotemporal degeneration, and Lewy body spectrum of disorders. Pathology was confirmed by autopsy or familial mutations. We discovered synaptic biomarkers for synaptic degeneration and cognitive decline. We found differential patterns of synaptic proteins across neurodegenerative diseases

Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction

There is a rising need for computational models that can complementarily leverage data of different modalities while investigating associations between subjects for population-based disease analysis. Despite the success of convolutional neural networks in representation learning for imaging data, it is still a very challenging task. In this paper, we propose a generalizable framework that can automatically integrate imaging data with non-imaging data in populations for uncertainty-aware disease prediction. At its core is a learnable adaptive population graph with variational edges, which we mathematically prove that it is optimizable in conjunction with graph convolutional neural networks. To estimate the predictive uncertainty related to the graph topology, we propose the novel concept of Monte-Carlo edge dropout. Experimental results on four databases show that our method can consistently and significantly improve the diagnostic accuracy for Autism spectrum disorder, Alzheimer's disease, and ocular diseases, indicating its generalizability in leveraging multimodal data for computer-aided diagnosis.Comment: Accepted to MICCAI 202

Higher CSF sTREM2 attenuates ApoE4-related risk for cognitive decline and neurodegeneration

BACKGROUND: The Apolipoprotein E ε4 allele (i.e. ApoE4) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). TREM2 (i.e. Triggering receptor expressed on myeloid cells 2) is a microglial transmembrane protein brain that plays a central role in microglia activation in response to AD brain pathologies. Whether higher TREM2-related microglia activity modulates the risk to develop clinical AD is an open question. Thus, the aim of the current study was to assess whether higher sTREM2 attenuates the effects of ApoE4-effects on future cognitive decline and neurodegeneration. METHODS: We included 708 subjects ranging from cognitively normal (CN, n = 221) to mild cognitive impairment (MCI, n = 414) and AD dementia (n = 73) from the Alzheimer's disease Neuroimaging Initiative. We used linear regression to test the interaction between ApoE4-carriage by CSF-assessed sTREM2 levels as a predictor of longitudinally assessed cognitive decline and MRI-assessed changes in hippocampal volume changes (mean follow-up of 4 years, range of 1.7-7 years). RESULTS: Across the entire sample, we found that higher CSF sTREM2 at baseline was associated with attenuated effects of ApoE4-carriage (i.e. sTREM2 x ApoE4 interaction) on longitudinal global cognitive (p = 0.001, Cohen's f2 = 0.137) and memory decline (p = 0.006, Cohen's f2 = 0.104) as well as longitudinally assessed hippocampal atrophy (p = 0.046, Cohen's f2 = 0.089), independent of CSF markers of primary AD pathology (i.e. Aβ1-42, p-tau181). While overall effects of sTREM2 were small, exploratory subanalyses stratified by diagnostic groups showed that beneficial effects of sTREM2 were pronounced in the MCI group. CONCLUSION: Our results suggest that a higher CSF sTREM2 levels are associated with attenuated ApoE4-related risk for future cognitive decline and AD-typical neurodegeneration. These findings provide further evidence that TREM2 may be protective against the development of AD

Neurofilament Light Chain Related to Longitudinal Decline in Frontotemporal Lobar Degeneration

OBJECTIVE: Accurate diagnosis and prognosis of frontotemporal lobar degeneration (FTLD) during life is an urgent concern in the context of emerging disease-modifying treatment trials. Few CSF markers have been validated longitudinally in patients with known pathology, and we hypothesized that CSF neurofilament light chain (NfL) would be associated with longitudinal cognitive decline in patients with known FTLD-TAR DNA binding protein ~43kD (TDP) pathology. METHODS: This case-control study evaluated CSF NfL, total tau, phosphorylated tau, and β-amyloid1-42 in patients with known FTLD-tau or FTLD-TDP pathology (n = 50) and healthy controls (n = 65) and an extended cohort of clinically diagnosed patients with likely FTLD-tau or FTLD-TDP (n = 148). Regression analyses related CSF analytes to longitudinal cognitive decline (follow-up ∼1 year), controlling for demographic variables and core AD CSF analytes. RESULTS: In FTLD-TDP with known pathology, CSF NfL is significantly elevated compared with controls and significantly associated with longitudinal decline on specific executive and language measures, after controlling for age, disease duration, and core AD CSF analytes. Similar findings are found in the extended cohort, also including clinically identified likely FTLD-TDP. Although CSF NfL is elevated in FTLD-tau compared with controls, the association between NfL and longitudinal cognitive decline is limited to executive measures. CONCLUSION: CSF NfL is associated with longitudinal clinical decline in relevant cognitive domains in patients with FTLD-TDP after controlling for demographic factors and core AD CSF analytes and may also be related to longitudinal decline in executive functioning in FTLD-tau

Expression of Toll-Like Receptors in the Developing Brain

Toll-like receptors (TLR) are key players of the innate and adaptive immune response in vertebrates. The original protein Toll in Drosophila melanogaster regulates both host defense and morphogenesis during development. Making use of real-time PCR, in situ hybridization, and immunohistochemistry we systematically examined the expression of TLR1–9 and the intracellular adaptor molecules MyD88 and TRIF during development of the mouse brain. Expression of TLR7 and TLR9 in the brain was strongly regulated during different embryonic, postnatal, and adult stages. In contrast, expression of TLR1–6, TLR8, MyD88, and TRIF mRNA displayed no significant changes in the different phases of brain development. Neurons of various brain regions including the neocortex and the hippocampus were identified as the main cell type expressing both TLR7 and TLR9 in the developing brain. Taken together, our data reveal specific expression patterns of distinct TLRs in the developing mouse brain and lay the foundation for further investigation of the pathophysiological significance of these receptors for developmental processes in the central nervous system of vertebrates