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Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease.

ABSTRACT: Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n?=?187) and serum (n?=?405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n?=?196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-? deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker.

SUBMITTER: Preische O

PROVIDER: S-EPMC6367005 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease.

Preische Oliver O Schultz Stephanie A SA Apel Anja A Kuhle Jens J Kaeser Stephan A SA Barro Christian C Gräber Susanne S Kuder-Buletta Elke E LaFougere Christian C Laske Christoph C Vöglein Jonathan J Levin Johannes J Masters Colin L CL Martins Ralph R Schofield Peter R PR Rossor Martin N MN Graff-Radford Neill R NR Salloway Stephen S Ghetti Bernardino B Ringman John M JM Noble James M JM Chhatwal Jasmeer J Goate Alison M AM Benzinger Tammie L S TLS Morris John C JC Bateman Randall J RJ Wang Guoqiao G Fagan Anne M AM McDade Eric M EM Gordon Brian A BA Jucker Mathias M

Nature medicine 20190121 2

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum N ...[more]

PMID: 30664784

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Project description:ImportanceUnrecognized demyelinating events often precede the clinical onset of multiple sclerosis (MS). Identification of these events at the time of occurrence would have implications for early diagnosis and the search of causal factors for the disease.ObjectiveTo assess whether serum neurofilament light chain (sNfL) levels are elevated before the clinical MS onset.Design, setting, and participantsNested case-control study among US military personnel who have serum samples stored in the US Department of Defense Serum Repository. Serum samples were collected from 2000 to 2011; sNfL assays and data analyses were performed from 2018 to 2019. We selected 60 case patients with MS who either had 2 samples collected before onset (mean follow-up, 6.3 years) or 1 sample collected before and 1 after onset (mean follow-up, 1.3 years), among 245 previously identified case patients. For each case, we randomly selected 1 of 2 previously identified control individuals matched by age, sex, race/ethnicity, and dates of sample collection. The sample size was chosen based on the available funding.ExposuresSerum NfL concentrations measured using an ultrasensitive single-molecule array assay (Simoa).Main outcomes and measurementsLog-transformed sNfL concentrations in case patients and control individuals compared using conditional logistic regression and linear mixed models.ResultsMean age at baseline was 27.5 years, and 92 of 120 participants (76.7%) were men. Serum NfL levels were higher in case patients with MS compared with their matched control individuals in samples drawn a median of 6 years (range, 4-10 years) before the clinical onset (median, 16.7 pg/mL; interquartile range [IQR], 12.6-23.1 pg/mL vs 15.2 pg/m; IQR, 10.3-19.9 pg/mL; P = .04). This difference increased with decreasing time to the case clinical onset (estimated coefficient for interaction with time = 0.063; P = .008). A within-person increase in presymptomatic sNfL levels was associated with higher MS risk (rate ratio for ≥5 pg/mL increase, 7.50; 95% CI, 1.72-32.80). The clinical onset was associated with a marked increase in sNfL levels (median, 25.0; IQR, 17.1-41.3 vs 45.1; IQR, 27.0-102.7 pg/mL for presymptomatic and postonset MS samples; P = .009).Conclusions and relevanceThe levels of sNfL were increased 6 years before the clinical MS onset, indicating that MS may have a prodromal phase lasting several years and that neuroaxonal damage occurs already during this phase.

Project description:Background: Plasma-based biomarkers would be potential biomarkers for early diagnosis of Alzheimer's disease (AD) because they are more available and cost-effective than cerebrospinal fluid (CSF) or neuroimaging. Therefore, we aimed to evaluate whether phosphorylated tau181 (p-tau181) in plasma could be an accurate AD predictor. Methods: Participants from the ADNI database included 185 cognitively unimpaired subjects with negative Aβ (CU-), 66 subjects with pre-clinical AD (CU with positive Aβ), 164 subjects with mild cognitive impairment with negative Aβ (MCI-), 254 subjects with prodromal AD (MCI with positive Aβ), and 98 subjects with dementia. Multiple linear regression models, linear mixed-effects models, and local regression were used to explore cross-sectional and longitudinal associations of plasma p-tau181 with cognition, neuroimaging, or CSF biomarkers adjusted for age, sex, education, and APOE genotype. Besides, Kaplan-Meier and adjusted Cox-regression model were performed to predict the risk of progression to dementia. Receiver operating characteristic analyses were performed to evaluate the predictive value of p-tau181. Results: Plasma p-tau181 level was highest in AD dementia, followed by prodromal AD and pre-clinical AD. In pre-clinical AD, plasma p-tau181 was negatively associated with hippocampal volume (β = -0.031, p-value = 0.017). In prodromal AD, plasma p-tau181 was associated with decreased global cognition, executive function, memory, language, and visuospatial functioning (β range -0.119 to -0.273, p-value < 0.05) and correlated with hippocampal volume (β = -0.028, p-value < 0.005) and white matter hyperintensity volume (WMH) volume (β = 0.02, p-value = 0.01). In AD dementia, increased plasma p-tau181 was associated with worse memory. In the whole group, baseline plasma p-tau181 was significantly associated with longitudinal increases in multiple neuropsychological test z-scores and correlated with AD-related CSF biomarkers and hippocampal volume (p-value < 0.05). Meanwhile, CU or MCI with high plasma p-tau181 carried a higher risk of progression to dementia. The area under the curve (AUC) of the adjusted model (age, sex, education, APOE genotype, and plasma p-tau181) was 0.78; that of additionally included CSF biomarkers was 0.84. Conclusions: Plasma p-tau181 level is related to multiple AD-associated cognitive domains and AD-related CSF biomarkers at the clinical stages of AD. Moreover, plasma p-tau181 level is related to the change rates of cognitive decline and hippocampal atrophy. Thus, this study confirms the utility of plasma p-tau181 as a non-invasive biomarker for early detection and prediction of AD.

Project description:Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of toxic misfolded proteins, which are believed to have propagated from disease-specific epicenters through their corresponding large-scale structural networks in the brain. Although previous cross-sectional studies have identified potential AD-associated epicenters and corresponding brain networks, it is unclear whether these networks are associated with disease progression. Hence, this study aims to identify the most vulnerable epicenters and corresponding large-scale structural networks involved in the early stages of AD and to evaluate its associations with multiple cognitive domains using longitudinal study design. Annual neuropsychological and MRI assessments were obtained from 23 patients with AD, 37 patients with amnestic mild cognitive impairment (MCI), and 33 healthy controls (HC) for 3 years. Candidate epicenters were identified as regions with faster decline rate in the gray matter volume (GMV) in patients with MCI who progressed to AD as compared to those regions in patients without progression. These epicenters were then further used as pre-defined regions of interest to map the synchronized degeneration network (SDN) in HCs. Spatial similarity, network preference and clinical association analyses were used to evaluate the specific roles of the identified SDNs. Our results demonstrated that the hippocampus and posterior cingulate cortex (PCC) were the most vulnerable AD-associated epicenters. The corresponding PCC-SDN showed significant spatial association with the patterns of GMV atrophy rate in each patient group and the overlap of these patterns was more evident in the advanced stages of the disease. Furthermore, individuals with a higher GMV atrophy rate of the PCC-SDN also showed faster decline in multiple cognitive domains. In conclusion, our findings suggest the PCC and hippocampus are two vulnerable regions involved early in AD pathophysiology. However, the PCC-SDN, but not hippocampus-SDN, was more closely associated with AD progression. These results may provide insight into the pathophysiology of AD from large-scale network perspective.

Dataset Information

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease.

Publications

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease.

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