Modeling the Simultaneous Dynamics of Proteins in Blood Plasma and the Cerebrospinal Fluid in Human In Vivo.

The analysis of protein dynamics or turnover in patients has the potential to reveal altered protein recycling, such as in Alzheimer's disease, and to provide informative data regarding drug efficacy or certain biological processes. The observed protein dynamics in a solid tissue or a fluid is the net result of not only protein synthesis and degradation but also transport across biological compartments. We report an accurate 3-biological compartment model able to simultaneously account for the protein dynamics observed in blood plasma and the cerebrospinal fluid (CSF) including a hidden central nervous system (CNS) compartment. We successfully applied this model to 69 proteins of a single individual displaying similar or very different dynamics in plasma and CSF. This study puts a strong emphasis on the methods and tools needed to develop this type of model. We believe that it will be useful to any researcher dealing with protein dynamics data modeling.

Comparison of ultrasensitive and mass spectrometry quantification of blood-based amyloid biomarkers for Alzheimer's disease diagnosis in a memory clinic cohort.

BACKGROUND: Alzheimer's disease (AD) is a complex neurodegenerative disorder with ß-amyloid pathology as a key underlying process. The relevance of cerebrospinal fluid (CSF) and brain imaging biomarkers is validated in clinical practice for early diagnosis. Yet, their cost and perceived invasiveness are a limitation for large-scale implementation. Based on positive amyloid profiles, blood-based biomarkers should allow to detect people at risk for AD and to monitor patients under therapeutics strategies. Thanks to the recent development of innovative proteomic tools, the sensibility and specificity of blood biomarkers have been considerably improved. However, their diagnosis and prognosis relevance for daily clinical practice is still incomplete. METHODS: The Plasmaboost study included 184 participants from the Montpellier's hospital NeuroCognition Biobank with AD (n = 73), mild cognitive impairments (MCI) (n = 32), subjective cognitive impairments (SCI) (n = 12), other neurodegenerative diseases (NDD) (n = 31), and other neurological disorders (OND) (n = 36). Dosage of ß-amyloid biomarkers was performed on plasma samples using immunoprecipitation-mass spectrometry (IPMS) developed by Shimadzu (IPMS-Shim Aß42, Aß40, APP669-711) and Simoa Human Neurology 3-PLEX A assay (Aß42, Aß40, t-tau). Links between those biomarkers and demographical and clinical data and CSF AD biomarkers were investigated. Performances of the two technologies to discriminate clinically or biologically based (using the AT(N) framework) diagnosis of AD were compared using receiver operating characteristic (ROC) analyses. RESULTS: The amyloid IPMS-Shim composite biomarker (combining APP669-711/Aß42 and Aß40/Aß42 ratios) discriminated AD from SCI (AUC: 0.91), OND (0.89), and NDD (0.81). The IPMS-Shim Aß42/40 ratio also discriminated AD from MCI (0.78). IPMS-Shim biomarkers have similar relevance to discriminate between amyloid-positive and amyloid-negative individuals (0.73 and 0.76 respectively) and A-T-N-/A+T+N+ profiles (0.83 and 0.85). Performances of the Simoa 3-PLEX Aß42/40 ratio were more modest. Pilot longitudinal analysis on the progression of plasma biomarkers indicates that IPMS-Shim can detect the decrease in plasma Aß42 that is specific to AD patients. CONCLUSIONS: Our study confirms the potential usefulness of amyloid plasma biomarkers, especially the IPMS-Shim technology, as a screening tool for early AD patients.

Differential diagnostic performance of a panel of plasma biomarkers for different types of dementia.

Introduction: We explored what combination of blood-based biomarkers (amyloid beta [Aß]1-42/1-40, phosphorylated tau [p-tau]181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP]) differentiates Alzheimer's disease (AD) dementia, frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods: We measured the biomarkers with Simoa in two separate cohorts (n = 160 and n = 152). In one cohort, Aß1-42/1-40 was also measured with mass spectrometry (MS). We assessed the differential diagnostic value of the markers, by logistic regression with Wald's backward selection. Results: MS and Simoa Aß1-42/1-40 similarly differentiated AD from controls. The Simoa panel that optimally differentiated AD from FTD consisted of NfL and p-tau181 (area under the curve [AUC] = 0.94; cohort 1) or NfL, GFAP, and p-tau181 (AUC = 0.90; cohort 2). For AD from DLB, the panel consisted of NfL, p-tau181, and GFAP (AUC = 0.88; cohort 1), and only p-tau181 (AUC = 0.81; cohort 2). Discussion: A combination of plasma p-tau181, NfL, and GFAP, but not Aß1-42/1-40, might be useful to discriminate AD, FTD, and DLB.

Blood amyloid and tau biomarkers as predictors of cerebrospinal fluid profiles.

INTRODUCTION: Blood biomarkers represent a major advance for improving the management, diagnosis, and monitoring of Alzheimer's disease (AD). However, their context of use in relation to routine cerebrospinal fluid (CSF) analysis for the quantification of amyloid peptides and tau proteins remains to be determined. METHODS: We studied in two independent cohorts, the performance of blood biomarkers in detecting "nonpathological" (A-/T-/N-), amyloid (A+) or neurodegenerative (T+ /N+) CSF profiles. RESULTS: Plasma Aß1-42/Aß1-40 ratio and phosphorylated tau (p-tau(181)) were independent and complementary predictors of the different CSF profile and in particular of the nonpathological (A-/T-/N-) profile with a sensitivity and specificity close to 85%. These performances and the corresponding biomarker thresholds were significantly different from those related to AD detection. CONCLUSION: The use of blood biomarkers to identify patients who may benefit from secondary CSF testing represents an attractive stratification strategy in the clinical management of patients visiting memory clinics. This could reduce the need for lumbar puncture and foreshadow the use of blood testing on larger populations.

Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease-related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group.

INTRODUCTION: Pre-analytical sample handling might affect the results of Alzheimer's disease blood-based biomarkers. We empirically tested variations of common blood collection and handling procedures. METHODS: We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze-thawing. We measured amyloid beta (Aß)42 and 40 peptides with six assays, and Aß oligomerization-tendency (OAß), amyloid precursor protein (APP)699-711 , glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t-tau), and phosphorylated tau181. RESULTS: Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aß and t-tau; t-tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations. DISCUSSION: We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood-based biomarkers into the research and clinical settings.