Multiplexed immunoassay panel identifies novel CSF biomarkers for Alzheimer's disease diagnosis and prognosis

Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.

The Link Between Matrix Metalloproteinases and Alzheimer's Disease Pathophysiology

Alzheimer's disease (AD) is a major contributor to dementia and the most common neurodegenerative disorder. In AD pathophysiology, matrix metalloproteinases (MMPs)-proteolytic enzymes, best known to be responsible for remodeling and degradation of the extracellular matrix-were suggested to play an important role. Due to the diverse nature of the published data and frequent inconsistent results presented in available papers, it was considered essential to analyze all aspects of MMP literature with respect to AD pathophysiology and attempt to outline a unifying concept for understanding their role in AD. Thus, the main contribution of this review article is to summarize the most recent research on the participation of MMP in AD pathophysiology obtained using the cell cultures to understand the molecular principles of their action. Furthermore, an updated comprehensive view regarding this topic based exclusively on papers from human studies is provided as well. It can be concluded that determining the exact role of any particular MMPs in the AD pathophysiology holds promise for establishing their role as potential biomarkers reflecting the severity or progression of this disease or for developing new therapeutic agents targeting the processes that lead to AD.

Plasmodium knowlesi infection is associated with elevated circulating biomarkers of brain injury and endothelial activation

Introduction

Malaria remains a major public health concern with substantial morbidity and mortality worldwide. In Malaysia, the emergence of Plasmodium knowlesi has led to a surge in zoonotic malaria cases and deaths in recent years. Signs of cerebral involvement have been observed in a non-comatose, fatal case of severe knowlesi infection, but the potential impact of this malaria species on the brain remains underexplored. To address this gap, we investigated circulating levels of brain injury, inflammation, and vascular biomarkers in a cohort of knowlesi-infected patients and controls.

Methods

Archived plasma samples from 19 patients with confirmed symptomatic knowlesi infection and 19 healthy, age-matched controls from Peninsular Malaysia were analysed. A total of 52 plasma biomarkers of brain injury, inflammation, and vascular activation were measured using Luminex and SIMOA assays. Wilcoxon tests were used to examine group differences, and biomarker profiles were explored through hierarchical clustering heatmap analysis.

Results

Bonferroni-corrected analyses revealed significantly elevated brain injury biomarker levels in knowlesi-infected patients, including S100B (p<0.0001), Tau (p=0.0007), UCH-L1 (p<0.0001), αSyn (p<0.0001), Park7 (p=0.0006), NRGN (p=0.0022), and TDP-43 (p=0.005). Compared to controls, levels were lower in the infected group for BDNF (p<0.0001), CaBD (p<0.0001), CNTN1 (p<0.0001), NCAM-1 (p<0.0001), GFAP (p=0.0013), and KLK6 (p=0.0126). Hierarchical clustering revealed distinct group profiles for circulating levels of brain injury and vascular activation biomarkers.

Conclusions

Our findings highlight for the first time the impact of Plasmodium knowlesi infection on the brain, with distinct alterations in cerebral injury and endothelial activation biomarker profiles compared to healthy controls. Further studies are warranted to investigate the pathophysiology and clinical significance of these altered surrogate markers, through both neuroimaging and long-term neurocognitive assessments.

Blood-brain barrier biomarkers

The blood-brain barrier (BBB) is a dynamic interface that regulates the exchange of molecules and cells between the brain parenchyma and the peripheral blood. The BBB is mainly composed of endothelial cells, astrocytes and pericytes. The integrity of this structure is essential for maintaining brain and spinal cord homeostasis and protection from injury or disease. However, in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, and multiple sclerosis, the BBB can become compromised thus allowing passage of molecules and cells in and out of the central nervous system parenchyma. These agents, however, can serve as biomarkers of BBB permeability and neuronal damage, and provide valuable information for diagnosis, prognosis and treatment. Herein, we provide an overview of the BBB and changes due to aging, and summarize current knowledge on biomarkers of BBB disruption and neurodegeneration, including permeability, cellular, molecular and imaging biomarkers. We also discuss the challenges and opportunities for developing a biomarker toolkit that can reliably assess the BBB in physiologic and pathophysiologic states.

ChatGPT-Enhanced ROC Analysis (CERA): A shiny web tool for finding optimal cutoff points in biomarker analysis

Diagnostic tests play a crucial role in establishing the presence of a specific disease in an individual. Receiver Operating Characteristic (ROC) curve analyses are essential tools that provide performance metrics for diagnostic tests. Accurate determination of the cutoff point in ROC curve analyses is the most critical aspect of the process. A variety of methods have been developed to find the optimal cutoffs. Although the R programming language provides a variety of package programs for conducting ROC curve analysis and determining the appropriate cutoffs, it typically needs coding skills and a substantial investment of time. Specifically, the necessity for data preprocessing and analysis can present a significant challenge, especially for individuals without coding experience. We have developed the CERA (ChatGPT-Enhanced ROC Analysis) tool, a user-friendly ROC curve analysis web tool using the shiny interface for faster and more effective analyses to solve this problem. CERA is not only user-friendly, but it also interacts with ChatGPT, which interprets the outputs. This allows for an interpreted report generated by R-Markdown to be presented to the user, enhancing the accessibility and understanding of the analysis results.

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.

Cystatins: unravelling the biological implications for neuroprotection

Cystatins, a family of proteins known for their inhibitory role against cysteine proteases, have garnered significant attention in the field of neurodegeneration. Numerous genetic, experimental, and clinical studies concerning cystatin C suggest it plays an important role in the course of neurodegenerative diseases. Its beneficial effects are associated with cysteine protease inhibition, impact on β-amyloid aggregation, as well as regulation of cell proliferation, autophagy, and apoptosis. Cystatin isolated from chicken egg white, called ovocystatin, has been widely used in medical and pharmaceutical research due to its structural and biological similarities to human cystatin C. This article focuses on the potential use of cystatins, with special emphasis on easily obtained ovocystatin, in the treatment of neurodegenerative diseases, such as dementia. The current evidence on cystatin use has shed light on its mechanisms of action and therapeutic implications for neuroprotection and maintenance of cognitive functions.

Elevated GRO-α and IL-18 in serum and brain implicate the NLRP3 inflammasome in frontotemporal dementia

Neuroinflammation is a hallmark of frontotemporal dementia (FTD), a heterogeneous group of proteinopathies characterized by the progressive degeneration of the frontal and temporal lobes. It is marked by microglial activation and subsequent cytokine release. Although cytokine levels in FTD brain and CSF have been examined, the number of cytokines measured in each study is limited and knowledge on cytokine concentrations in FTD serum is scarce. Here, we assessed 48 cytokines in FTD serum and brain. The aim was to determine common cytokine dysregulation pathways in serum and brain in FTD. Blood samples and brain tissue samples from the superior frontal cortex (SFC) were collected from individuals diagnosed with behavioral variant FTD (bvFTD) and healthy controls, and 48 cytokines were measured using a multiplex immunological assay. The data were evaluated by principal component factor analysis to determine the contribution from different components of the variance in the cohort. Levels of a number of cytokines were altered in serum and SFC in bvFTD compared to controls, with increases in GRO-α and IL-18 in both serum and SFC. These changes could be associated with NLRP3 inflammasome activation or the NFκB pathway, which activates NLRP3. The results suggest the possible importance of the NLRP3 inflammasome in FTD. An improved understanding of the role of inflammasomes in FTD could provide valuable insights into the pathogenesis, diagnosis and treatment of FTD.

Circulating Bile Acids as Biomarkers for Disease Diagnosis and Prevention

CONTEXT

Bile acids (BAs) are pivotal signaling molecules that regulate energy metabolism and inflammation. Recent epidemiological studies have reported specific alterations in circulating BA profiles in certain disease states, including obesity, type 2 diabetes mellitus (T2DM), nonalcoholic fatty liver disease (NAFLD), and Alzheimer disease (AD). In the past decade, breakthroughs have been made regarding the translation of BA profiling into clinical use for disease prediction. In this review, we summarize and synthesize recent data on variation in circulating BA profiles in patients with various diseases to evaluate the value of these biomarkers in human plasma for early diagnosis.

EVIDENCE ACQUISITION

This review is based on a collection of primary and review literature gathered from a PubMed search for BAs, obesity, T2DM, insulin resistance (IR), NAFLD, hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), colon cancer, and AD, among other keywords.

EVIDENCE SYNTHESIS

Individuals with obesity, T2DM, HCC, CCA, or AD showed specific alterations in circulating BA profiles. These alterations may have existed long before the initial diagnosis of these diseases. The intricate relationship between obesity, IR, and NAFLD complicates the establishment of clear and independent associations between BA profiles and nonalcoholic steatohepatitis. Alterations in the levels of total BAs and several BA species were seen across the entire spectrum of NAFLD, demonstrating significant increases with the worsening of histological features.

CONCLUSIONS

Aberrant circulating BA profiles are an early event in the onset and progression of obesity, T2DM, HCC, and AD. The pleiotropic effects of BAs explain these broad connections. Circulating BA profiles could provide a basis for the development of biomarkers for the diagnosis and prevention of a wide range of diseases.

Fibrin-Targeting Immunotherapy for Dementia

Blood-brain barrier (BBB) disruption is an early event in the development of Alzheimer's disease. It precedes extracellular deposition of amyloid-β in senile plaques and blood vessel walls, the intracellular accumulation of neurofibrillary tangles containing phosphorylated tau protein, microglial activation, and neuronal cell death. BBB disruption allows the coagulation protein fibrinogen to leak from the blood into the brain, where it is converted by thrombin cleavage into fibrin and deposits in the parenchyma and CNS vessels. Fibrinogen cleavage by thrombin exposes a cryptic epitope termed P2 which can bind CD11b and CD11c on microglia, macrophages and dendritic cells and trigger an inflammatory response toxic to neurons. Indeed, genetic and pharmacological evidence demonstrates a causal role for fibrin in innate immune cell activation and the development of neurodegenerative diseases. The P2 inflammatory epitope is spatially and compositionally distinct from the coagulation epitope on fibrin. Mouse monoclonal antibody 5B8, which targets the P2 epitope without interfering with the clotting process, has been shown to reduce neurodegeneration and neuroinflammation in animal models of Alzheimer's disease and multiple sclerosis. The selectivity and efficacy of this anti-human fibrin-P2 antibody in animal models supports the development of a monoclonal antibody drug targeting fibrin P2 for the treatment of neurodegenerative diseases. THN391 is a humanized, affinity-matured antibody which has a 100-fold greater affinity for fibrin P2 and improved development properties compared to the parental 5B8 antibody. It is currently in a Phase 1 clinical trial.

Voice biomarkers as indicators of cognitive changes in middle and later adulthood

Voice prosody measures have been linked with Alzheimer's disease (AD), but it is unclear whether they are associated with normal cognitive aging. We assessed relationships between voice measures and 10-year cognitive changes in the MIDUS national sample of middle-aged and older adults ages 42-92, with a mean age of 64.09 (standard deviation = 11.23) at the second wave. Seven cognitive tests were assessed in 2003-2004 (Wave 2) and 2013-2014 (Wave 3). Voice measures were collected at Wave 3 (N = 2585) from audio recordings of the cognitive interviews. Analyses controlled for age, education, depressive symptoms, and health. As predicted, higher jitter was associated with greater declines in episodic memory, verbal fluency, and attention switching. Lower pulse was related to greater decline in episodic memory, and fewer voice breaks were related to greater declines in episodic memory and verbal fluency, although the direction of these effects was contrary to hypotheses. Findings suggest that voice biomarkers may offer a promising approach for early detection of risk factors for cognitive impairment or AD.

Neurovascular Dysfunction in Diverse Communities With Health Disparities-Contributions to Dementia and Alzheimer's Disease

Alzheimer's disease and related dementias (ADRD) are an expanding worldwide crisis. In the absence of scientific breakthroughs, the global prevalence of ADRD will continue to increase as more people are living longer. Racial or ethnic minority groups have an increased risk and incidence of ADRD and have often been neglected by the scientific research community. There is mounting evidence that vascular insults in the brain can initiate a series of biological events leading to neurodegeneration, cognitive impairment, and ADRD. We are a group of researchers interested in developing and expanding ADRD research, with an emphasis on vascular contributions to dementia, to serve our local diverse community. Toward this goal, the primary objective of this review was to investigate and better understand health disparities in Alabama and the contributions of the social determinants of health to those disparities, particularly in the context of vascular dysfunction in ADRD. Here, we explain the neurovascular dysfunction associated with Alzheimer's disease (AD) as well as the intrinsic and extrinsic risk factors contributing to dysfunction of the neurovascular unit (NVU). Next, we ascertain ethnoregional health disparities of individuals living in Alabama, as well as relevant vascular risk factors linked to AD. We also discuss current pharmaceutical and non-pharmaceutical treatment options for neurovascular dysfunction, mild cognitive impairment (MCI) and AD, including relevant studies and ongoing clinical trials. Overall, individuals in Alabama are adversely affected by social and structural determinants of health leading to health disparities, driven by rurality, ethnic minority status, and lower socioeconomic status (SES). In general, these communities have limited access to healthcare and healthy food and other amenities resulting in decreased opportunities for early diagnosis of and pharmaceutical treatments for ADRD. Although this review is focused on the current state of health disparities of ADRD patients in Alabama, future studies must include diversity of race, ethnicity, and region to best be able to treat all individuals affected by ADRD.

Endosomal-Lysosomal and Autophagy Pathway in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

The endosomal-lysosomal and autophagy (ELA) pathway may be implicated in the progression of Alzheimer's disease (AD); however, findings thus far have been inconsistent.

OBJECTIVE

To systematically summarize differences in endosomal-lysosomal and autophagy proteins in the cerebrospinal fluid (CSF) of people with AD and healthy controls (HC).

METHODS

Studies measuring CSF concentrations of relevant proteins in the ELA pathway in AD and healthy controls were included. Standardized mean differences (SMD) with 95% confidence intervals (CI) between AD and healthy controls in CSF concentrations of relevant proteins were meta-analyzed using random-effects models.

RESULTS

Of 2,471 unique studies, 43 studies were included in the systematic review and meta-analysis. Differences in ELA protein levels in the CSF between AD and healthy controls were observed, particularly in lysosomal membrane (LAMP-1: NAD/NHC = 348/381, SMD [95% CI] = 0.599 [0.268, 0.930], I2 = 72.8% ; LAMP-2: NAD/NHC = 401/510, SMD [95% CI] = 0.480 [0.134, 0.826], I2 = 78.7%) and intra-lysosomal proteins (GM2A: NAD/NHC = 390/420, SMD [95% CI] = 0.496 [0.039, 0.954], I2 = 87.7% ; CTSB: NAD/NHC = 485/443, SMD [95% CI] = 0.201 [0.029, 0.374], I2 = 28.5% ; CTSZ: NAD/NHC = 535/820, SMD [95% CI] = -0.160 [-0.305, -0.015], I2 = 24.0%) and in proteins involved in endocytosis (AP2B1:NAD/NHC = 171/205, SMD [95% CI] = 0.513 [0.259, 0.768], I2 = 27.4% ; FLOT1: NAD/NHC = 41/45, SMD [95% CI] = -0.489 [-0.919, -0.058], I2 <0.01). LC3B, an autophagy marker, also showed a difference (NAD/NHC = 70/59, SMD [95% CI] = 0.648 [0.180, 1.116], I2 = 38.3%)), but overall there was limited evidence suggesting differences in proteins involved in endosomal function and autophagy.

CONCLUSION

Dysregulation of proteins in the ELA pathway may play an important role in AD pathogenesis. Some proteins within this pathway may be potential biomarkers for AD.

Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

Background

Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches.

Methods

Plasma gas chromatography–liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women’s Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models.

Results

Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models’ specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways.

Conclusions

We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00445-8.

Prediction of Medical Conditions Using Machine Learning Approaches: Alzheimer’s Case Study

Alzheimer’s Disease (AD) is a highly prevalent condition and most of the people suffering from it receive the diagnosis late in the process. The diagnosis is currently established following an evaluation of the protein biomarkers in cerebrospinal fluid (CSF), brain imaging, cognitive tests, and the medical history of the individuals. While diagnostic tools based on CSF collections are invasive, the tools used for acquiring brain scans are expensive. Taking these into account, an early predictive system, based on Artificial Intelligence (AI) approaches, targeting the diagnosis of this condition, as well as the identification of lead biomarkers becomes an important research direction. In this survey, we review the state-of-the-art research on machine learning (ML) techniques used for the detection of AD and Mild Cognitive Impairment (MCI). We attempt to identify the most accurate and efficient diagnostic approaches, which employ ML techniques and therefore, the ones most suitable to be used in practice. Research is still ongoing to determine the best biomarkers for the task of AD classification. At the beginning of this survey, after an introductory part, we enumerate several available resources, which can be used to build ML models targeting the diagnosis and classification of AD, as well as their main characteristics. After that, we discuss the candidate markers which were used to build AI models with the best results in terms of diagnostic accuracy, as well as their limitations.

Scalable and accurate variational Bayes for high-dimensional binary regression models

Modern methods for Bayesian regression beyond the Gaussian response setting are often computationally impractical or inaccurate in high dimensions. In fact, as discussed in recent literature, bypassing such a trade-off is still an open problem even in routine binary regression models, and there is limited theory on the quality of variational approximations in high-dimensional settings. To address this gap, we study the approximation accuracy of routinely-used mean-field variational Bayes solutions in high-dimensional probit regression with Gaussian priors, obtaining novel and practically relevant results on the pathological behaviour of such strategies in uncertainty quantification, point estimation and prediction. Motivated by these results, we further develop a new partially-factorized variational approximation for the posterior distribution of the probit coefficients which leverages a representation with global and local variables but, unlike for classical mean-field assumptions, it avoids a fully factorized approximation, and instead assumes a factorization only for the local variables. We prove that the resulting approximation belongs to a tractable class of unified skew-normal densities that crucially incorporates skewness and, unlike for state-of-the-art mean-field solutions, converges to the exact posterior density as p →∞. To solve the variational optimization problem, we derive a tractable coordinate ascent variational inference algorithm that easily scales to p in the tens of thousands, and provably requires a number of iterations converging to 1 as p →∞. Such findings are also illustrated in extensive empirical studies where our novel solution is shown to improve the approximation accuracy of mean-field variational Bayes for any n and p, with the magnitude of these gains being remarkable in those high-dimensional p &gt; n settings where state-of-the-art methods are computationally impractical.

The Importance of CXCL1 in Physiology and Noncancerous Diseases of Bone, Bone Marrow, Muscle and the Nervous System

This review describes the role of CXCL1, a chemokine crucial in inflammation as a chemoattractant for neutrophils, in physiology and in selected major non-cancer diseases. Due to the vast amount of available information, we focus on the role CXCL1 plays in the physiology of bones, bone marrow, muscle and the nervous system. For this reason, we describe its effects on hematopoietic stem cells, myoblasts, oligodendrocyte progenitors and osteoclast precursors. We also present the involvement of CXCL1 in diseases of selected tissues and organs including Alzheimer’s disease, epilepsy, herpes simplex virus type 1 (HSV-1) encephalitis, ischemic stroke, major depression, multiple sclerosis, neuromyelitis optica, neuropathic pain, osteoporosis, prion diseases, rheumatoid arthritis, tick-borne encephalitis (TBE), traumatic spinal cord injury and West Nile fever.

Fully automated discrimination of Alzheimer's disease using resting-state electroencephalography signals

Background

The Alzheimer's disease (AD) population increases worldwide, placing a heavy burden on the economy and society. Presently, there is no cure for AD. Developing a convenient method of screening for AD and mild cognitive impairment (MCI) could enable early intervention, thus slowing down the progress of the disease and enabling better overall disease management.

Methods

In the current study, resting-state electroencephalography (EEG) data were acquired from 113 normal cognition (NC) subjects, 116 amnestic MCI patients, and 72 probable AD patients. After preprocessing by an automatic algorithm, features including spectral power, complexity, and functional connectivity were extracted, and machine-learning classifiers were built to differentiate among the 3 groups. The classification performance was evaluated from multiple perspectives, including accuracy, specificity, sensitivity, area under the curve (AUC) with 95% confidence intervals, and compared to the empirical chance level by permutation tests.

Results

The analysis of variance results (P<0.05 with false discovery rate correction) confirmed the tendency to slow brain activity, reduced complexity, and connectivity with AD progress. By combining the features, the ability of the machine-learning classifiers, especially the ensemble trees, to differentiate among the 3 groups, was significantly better than that of the empirical chance level of the permutation test. The AUC of the classifier with the best performance was 80.08% for AD vs. NC, 70.82% for AD vs. MCI, and 63.95% for MCI vs. NC.

Conclusions

The current study presented a fully automatic procedure that could significantly distinguish NC, MCI, and AD subjects via resting-state EEG signals. The study was based on a large data set with evidence-based medical diagnosis and provided further evidence that resting-state EEG data could assist in the discrimination of AD patients.

Matrix metalloproteinase 10 is linked to the risk of progression to dementia of the Alzheimer's type

Alzheimer's disease has a long asymptomatic phase that offers a substantial time window for intervention. Utilizing this window of opportunity will require early diagnostic and prognostic biomarkers to detect Alzheimer's disease pathology at pre-dementia stages, thus allowing identification of patients who will most probably progress to dementia of the Alzheimer's type and benefit from specific disease-modifying therapies. Consequently, we searched for CSF proteins associated with disease progression along with the clinical disease staging. We measured the levels of 184 proteins in CSF samples from 556 subjective cognitive decline and mild cognitive impairment patients from three independent memory clinic longitudinal studies (Spanish ACE, n = 410; German DCN, n = 93; German Mannheim, n = 53). We evaluated the association between protein levels and clinical stage, and the effect of protein levels on the progression from mild cognitive impairment to dementia of the Alzheimer's type. Mild cognitive impairment subjects with increased CSF level of matrix metalloproteinase 10 showed a higher probability of progressing to dementia of the Alzheimer's type and a faster cognitive decline. CSF matrix metalloproteinase 10 increased the prediction accuracy of CSF Aβ42, P-tau181, and T-tau for conversion to dementia of the Alzheimer's type. Including matrix metalloproteinase 10 to the [A/T/(N)] scheme improved considerably the prognostic value in mild cognitive impairment patients with abnormal Aβ42, but normal P-tau181 and T-tau, and in mild cognitive impairment patients with abnormal Aβ42, P-tau181, and T-tau. Matrix metalloproteinase 10 was correlated with age in subjects with normal Aβ42, P-tau181, and T-tau levels. Our findings support the use of CSF matrix metalloproteinase 10 as a prognostic marker for dementia of the Alzheimer's type and its inclusion to the [A/T/(N)] scheme to incorporate pathologic aspects beyond amyloid and tau. CSF level of matrix metalloproteinase 10 may reflect ageing and neuroinflammation.

Detection of multiplex exosomal miRNAs for clinically accurate diagnosis of Alzheimer's disease using label-free plasmonic biosensor based on DNA-Assembled advanced plasmonic architecture

Alzheimer's disease (AD), the most common neurologic disorder, is characterized by progressive cognitive impairment. However, the low clinical significance of the currently used core AD biomarkers amyloid-beta and tau proteins remains a challenge. Recently, exosomes, found in human biological fluids, are gaining increasing attention because of their clinical significance in diagnosing of various diseases. In particular, blood-derived exosomal miRNAs are not only stable but also provide information regarding the different characteristics according to AD progression. However, quantitative and qualitative detection is difficult due to their characteristics, such as small size, low abundance, and high homology. Here, we present a DNA-assembled advanced plasmonic architecture (DAPA)-based plasmonic biosensor to accurately detect exosomal miRNAs in human serum. The designed nanoarchitecture possesses two narrow nanogaps that induce plasmon coupling; this significantly enhances its optical energy density, resulting in a 1.66-fold higher refractive-index (RI) sensitivity than nanorods at localized surface plasmon resonance (LSPR). Thus, the proposed biosensor is ultrasensitive and capable of selective single-nucleotide detection of exosomal miRNAs at the attomolar level. Furthermore, it identified AD patients from healthy controls by measuring the levels of exosomal miRNA-125b, miRNA-15a, and miRNA-361 in clinical serum samples. In particular, the combination of exosomal miRNA-125b and miRNA-361 showed the best diagnostic performance with a sensitivity of 91.67%, selectivity of 95.00%, and accuracy of 99.52%. These results demonstrate that our sensor can be clinically applied for AD diagnosis and has great potential to revolutionize the field of dementia research and treatment in the future.

Differential chemokine alteration in the variants of primary progressive aphasia-a role for neuroinflammation

BACKGROUND

The primary progressive aphasias (PPA) represent a group of usually sporadic neurodegenerative disorders with three main variants: the nonfluent or agrammatic variant (nfvPPA), the semantic variant (svPPA), and the logopenic variant (lvPPA). They are usually associated with a specific underlying pathology: nfvPPA with a primary tauopathy, svPPA with a TDP-43 proteinopathy, and lvPPA with underlying Alzheimer's disease (AD). Little is known about their cause or pathophysiology, but prior studies in both AD and svPPA have suggested a role for neuroinflammation. In this study, we set out to investigate the role of chemokines across the PPA spectrum, with a primary focus on central changes in cerebrospinal fluid (CSF) METHODS: Thirty-six participants with sporadic PPA (11 svPPA, 13 nfvPPA, and 12 lvPPA) as well as 19 healthy controls were recruited to the study and donated CSF and plasma samples. All patients with lvPPA had a tau/Aβ42 biomarker profile consistent with AD, whilst this was normal in the other PPA groups and controls. We assessed twenty chemokines in CSF and plasma using Proximity Extension Assay technology: CCL2 (MCP-1), CCL3 (MIP-1a), CCL4 (MIP-1β), CCL7 (MCP-3), CCL8 (MCP-2), CCL11 (eotaxin), CCL13 (MCP-4), CCL19, CCL20, CCL23, CCL25, CCL28, CX3CL1 (fractalkine), CXCL1, CXCL5, CXCL6, CXCL8 (IL-8), CXCL9, CXCL10, and CXCL11.

RESULTS

In CSF, CCL19 and CXCL6 were decreased in both svPPA and nfvPPA compared with controls whilst CXCL5 was decreased in the nfvPPA group with a borderline significant decrease in the svPPA group. In contrast, CCL2, CCL3 and CX3CL1 were increased in lvPPA compared with controls and nfvPPA (and greater than svPPA for CX3CL1). CXCL1 was also increased in lvPPA compared with nfvPPA but not the other groups. CX3CL1 was significantly correlated with CSF total tau concentrations in the controls and each of the PPA groups. Fewer significant differences were seen between groups in plasma, although in general, results were in the opposite direction to CSF, i.e. decreased in lvPPA compared with controls (CCL3 and CCL19), and increased in svPPA (CCL8) and nfvPPA (CCL13).

CONCLUSION

Differential alteration of chemokines across the PPA variants is seen in both CSF and plasma. Importantly, these results suggest a role for neuroinflammation in these poorly understood sporadic disorders, and therefore also a potential future therapeutic target.

Inflammatory Biomarkers Aid in Diagnosis of Dementia

Dual pathology of Alzheimer's disease (AD) and vascular cognitive impairment and dementia (VCID) commonly are found together at autopsy, but mixed dementia (MX) is difficult to diagnose during life. Biological criteria to diagnose AD have been defined, but are not available for vascular disease. We used the biological criteria for AD and white matter injury based on MRI to diagnose MX. Then we measured multiple biomarkers in CSF and blood with multiplex biomarker kits for proteases, angiogenic factors, and cytokines to explore pathophysiology in each group. Finally, we used machine learning with the Random forest algorithm to select the biomarkers of maximal importance; that analysis identified three proteases, matrix metalloproteinase-10 (MMP-10), MMP-3 and MMP-1; three angiogenic factors, VEGF-C, Tie-2 and PLGF, and three cytokines interleukin-2 (IL-2), IL-6, IL-13. To confirm the clinical importance of the variables, we showed that they correlated with results of neuropsychological testing.

Extracellular protein components of amyloid plaques and their roles in Alzheimer's disease pathology

Alzheimer's disease (AD) is pathologically defined by the presence of fibrillar amyloid β (Aβ) peptide in extracellular senile plaques and tau filaments in intracellular neurofibrillary tangles. Extensive research has focused on understanding the assembly mechanisms and neurotoxic effects of Aβ during the last decades but still we only have a brief understanding of the disease associated biological processes. This review highlights the many other constituents that, beside Aβ, are accumulated in the plaques, with the focus on extracellular proteins. All living organisms rely on a delicate network of protein functionality. Deposition of significant amounts of certain proteins in insoluble inclusions will unquestionably lead to disturbances in the network, which may contribute to AD and copathology. This paper provide a comprehensive overview of extracellular proteins that have been shown to interact with Aβ and a discussion of their potential roles in AD pathology. Methods that can expand the knowledge about how the proteins are incorporated in plaques are described. Top-down methods to analyze post-mortem tissue and bottom-up approaches with the potential to provide molecular insights on the organization of plaque-like particles are compared. Finally, a network analysis of Aβ-interacting partners with enriched functional and structural key words is presented.

Cognitive and brain cytokine profile of non-demented individuals with cerebral amyloid-beta deposition

BACKGROUND

Brain inflammation has been increasingly associated with early amyloid accumulation in Alzheimer's disease models; however, evidence of its occurrence in humans remains scarce. To elucidate whether amyloid deposition is associated with neuroinflammation and cognitive deficits, we studied brain inflammatory cytokine expression and cognitive decline in non-demented elderly individuals with and without cerebral amyloid-beta deposition.

METHODS

Global cognition, episodic, working, and semantic memory, perceptual speed, visuospatial ability, and longitudinal decline (5.7 ± 3.6 years) in each cognitive domain were compared between elderly individuals (66-79 years) with and without cerebral amyloid-beta deposition. The expression of 20 inflammatory cytokines was analyzed in frozen temporal, parietal, and frontal cortices and compared between older individuals with and without amyloid-beta deposition in each brain region. Correlation analyses were performed to analyze associations between amyloid-beta load, cytokine expression, and cognitive decline.

RESULTS

Individuals with cortical amyloid-beta deposition displayed deficits and a faster rate of cognitive decline in perceptual speed as compared with those individuals without amyloid-beta. This decline was positively associated with cortical amyloid-beta levels. Elderly individuals with amyloid-beta deposition had higher levels of IL-1β, IL-6, and eotaxin-3 in the temporal cortex accompanied by an increase in MCP-1 and IL-1β in the parietal cortex and a trend towards higher levels of IL-1β and MCP-1 in the frontal cortex as compared with age-matched amyloid-free individuals. Brain IL-1β levels displayed a positive association with cortical amyloid burden in each brain region. Finally, differential cytokine expression in each cortical region was associated with cognitive decline.

CONCLUSIONS

Elderly individuals with amyloid-beta neuropathology but no symptomatic manifestation of dementia, exhibit cognitive decline and increased brain cytokine expression. Such observations suggest that increased cytokine expression might be an early event in the Alzheimer's continuum.

Hemostasis components in cerebral amyloid angiopathy and Alzheimer's disease

Increased cerebrovascular amyloid-β (Aβ) deposition represents the main pathogenic mechanisms characterizing Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). Whereas an increasing number of studies define the contribution of fibrin(ogen) to neurodegeneration, how other hemostasis factors might be pleiotropically involved in the AD and CAA remains overlooked. Although traditionally regarded as pertaining to hemostasis, these proteins are also modulators of inflammation and angiogenesis, and exert cytoprotective functions. This review discusses the contribution of hemostasis components to Aβ cerebrovascular deposition, which settle the way to endothelial and blood-brain barrier dysfunction, vessel fragility, cerebral bleeding, and the associated cognitive changes. From the primary hemostasis, the process that refers to platelet aggregation, we discuss evidence regarding the von Willebrand factor (vWF) and its regulator ADAMTS13. Then, from the secondary hemostasis, we focus on tissue factor, which triggers the extrinsic coagulation cascade, and on the main inhibitors of coagulation, i.e., tissue factor pathway inhibitor (TFPI), and the components of protein C pathway. Last, from the tertiary hemostasis, we discuss evidence on FXIII, involved in fibrin cross-linking, and on components of fibrinolysis, including tissue-type plasminogen activator (tPA), urokinase-type plasminogen activator (uPA) and its receptor uPA(R), and plasminogen activator inhibitor-1 (PAI-1). Increased knowledge on contributors of Aβ-related disease progression may favor new therapeutic approaches for early modifiable risk factors.

Longitudinal CSF proteomics identifies NPTX2 as a prognostic biomarker of Alzheimer's disease

Introduction: Biomarkers that reflect pathologic processes affecting neuronal function during preclinical and early stages of Alzheimer's disease (AD) are needed to aid drug development.

Methods: A targeted, stable isotope, quantitative mass spectrometry‐based investigation of longitudinal changes in concentrations of previously identified candidate biomarkers was performed in cerebrospinal fluid (CSF) of Alzheimer's Disease Neuroimaging Initiative participants who were classified as cognitively normal (CN; n = 76) or with mild cognitive impairment (MCI; n = 111) at baseline.

Results: Of the candidate biomarkers, the CSF concentration of neuronal pentraxin 2 (NPTX2), a protein involved in synaptic function, exhibited rates of change that were significantly different between three comparison groups (i.e., CN vs. MCI participants; AD pathology positive vs. negative defined by phosphorylated tau181/amyloid beta1‐42 ratio; and clinical progressors vs. non‐progressors). The rate of change of NPTX2 also significantly correlated with declining cognition.

Discussion: CSF NPTX2 concentration is a strong prognostic biomarker candidate of accelerated cognitive decline with potential use as a therapeutic target.

Estimating the AUC with a Graphical Lasso Method for High-dimensional Biomarkers with LOD

This manuscript estimates the area under the receiver operating characteristic curve (AUC) of combined biomarkers in a high-dimensional setting. We propose a penalization approach to the inference of precision matrices in the presence of the limit of detection. A new version of expectation-maximization algorithm is then proposed for the penalized likelihood, with the use of numerical integration and the graphical lasso method. The estimated precision matrix is then applied to the inference of AUCs. The proposed method outperforms the existing methods in numerical studies. We apply the proposed method to a data set of brain tumor study. The results show a higher accuracy on the estimation of AUC compared with the existing methods.

Neuroinflammation modulates the association of PGRN with cerebral amyloid-β burden

Progranulin (PGRN) and neuroinflammatory markers increased over the course of Alzheimer's disease (AD). We aimed to determine whether neuroinflammation could modulate the association of PGRN with amyloid pathologies. Baseline cerebrospinal fluid (CSF) PGRN and AD pathologies were measured for 965 participants, among whom 228 had measurements of CSF neuroinflammatory markers. Causal mediation analyses with 10,000 bootstrapped iterations were conducted to explore the mediation effects within the framework of A/T/N biomarker profile. Increased levels of CSF PGRN and inflammatory markers (sTNFR1, sTNFR2, TGF-β1, ICAM1, and VCAM1) were associated with T- or N-positive (TN+) profile, irrespective of the amyloid pathology. In TN+ group, CSF PGRN was associated with increased levels of these inflammatory markers and CSF amyloid-β_1-42 (p < 0.01). The neuroinflammatory markers significantly modulated (proportion: 20%~60%) the relationship of amyloid burden with CSF PGRN, which could predict slower cognitive decline and lower AD risk in the TN+ group. The abovementioned associations became non-significant in the TN- group. These findings revealed a close relationship between neuroinflammation and CSF PGRN in contributing to AD pathogenesis, and also highlighted the specific roles of PGRN in neurodegenerative conditions. Future experiments are warranted to verify the causal relationship.

Evolution of neuroinflammation across the lifespan of individuals with Down syndrome

Epidemiological and experimental studies suggest that a disease-aggravating neuroinflammatory process is present at preclinical stages of Alzheimer's disease. Given that individuals with Down syndrome are at increased genetic risk of Alzheimer's disease and therefore develop the spectrum of Alzheimer's neuropathology in a uniform manner, they constitute an important population to study the evolution of neuroinflammation across the Alzheimer's continuum. Therefore, in this cross-sectional study, we characterized the brain inflammatory profile across the lifespan of individuals with Down syndrome. Microglial morphology and inflammatory cytokine expression were analysed by immunohistochemistry and electrochemiluminescent-based immunoassays in the frontal cortex from foetuses to adults with Down syndrome and control subjects (16 gestational weeks to 64 years), totalling 127 cases. Cytokine expression in mixed foetal primary cultures and hippocampus of adults with Down syndrome, as well as the effects of sex on cytokine expression were also analysed. A higher microglial soma size-to-process length ratio was observed in the frontal cortex of children and young adults with Down syndrome before the development of full-blown Alzheimer's pathology. Moreover, young adults with Down syndrome also displayed increased numbers of rod-like microglia. Increased levels of interleukin-8 and interleukin-10 were observed in children with Down syndrome (1-10 years; Down syndrome n = 5, controls n = 10) and higher levels of interleukin-1β, interleukin-1α, interleukin-6, interleukin-8, interleukin-10, interleukin-15, eotaxin-3, interferon gamma-induced protein 10, macrophage-derived chemokine, and macrophage inflammatory protein-beta, were found in young adults with Down syndrome compared to euploid cases (13-25 years, Down syndrome n = 6, controls n = 24). Increased cytokine expression was also found in the conditioned media of mixed cortical primary cultures from second trimester foetuses with Down syndrome (Down syndrome n = 7, controls n = 7). Older adults with Down syndrome (39-68 years, Down syndrome n = 22, controls n = 16) displayed reduced levels of interleukin-10, interleukin-12p40, interferon-gamma and tumour necrosis factor-alpha. Microglia displayed larger somas and shorter processes. Moreover, an increase in dystrophic microglia and rod-like microglia aligning to neurons harbouring tau pathology were also observed. Sex stratification analyses revealed that females with Down syndrome had increased interleukin-6 and interleukin-8 levels compared to males with Down syndrome. Finally, multivariate projection methods identified specific cytokine patterns among individuals with Down syndrome. Our findings indicate the presence of an early and evolving neuroinflammatory phenotype across the lifespan in Down syndrome, a knowledge that is relevant for the discovery of stage-specific targets and for the design of possible anti-inflammatory trials against Alzheimer's disease in this population.

Common Peripheral Immunity Mechanisms in Multiple Sclerosis and Alzheimer's Disease

Neurodegenerative diseases are closely related to inflammatory and autoimmune events, suggesting that the dysregulation of the immune system is a key pathological factor. Both multiple sclerosis (MS) and Alzheimer's disease (AD) are characterized by infiltrating immune cells, activated microglia, astrocyte proliferation, and neuronal damage. Moreover, MS and AD share a common pro-inflammatory signature, characterized by peripheral leukocyte activation and transmigration to the central nervous system (CNS). MS and AD are both characterized by the accumulation of activated neutrophils in the blood, leading to progressive impairment of the blood–brain barrier. Having migrated to the CNS during the early phases of MS and AD, neutrophils promote local inflammation that contributes to pathogenesis and clinical progression. The role of circulating T cells in MS is well-established, whereas the contribution of adaptive immunity to AD pathogenesis and progression is a more recent discovery. Even so, blocking the transmigration of T cells to the CNS can benefit both MS and AD patients, suggesting that common adaptive immunity mechanisms play a detrimental role in each disease. There is also growing evidence that regulatory T cells are beneficial during the initial stages of MS and AD, supporting the link between the modulatory immune compartments and these neurodegenerative disorders. The number of resting regulatory T cells declines in both diseases, indicating a common pathogenic mechanism involving the dysregulation of these cells, although their precise role in the control of neuroinflammation remains unclear. The modulation of leukocyte functions can benefit MS patients, so more insight into the role of peripheral immune cells may reveal new targets for pharmacological intervention in other neuroinflammatory and neurodegenerative diseases, including AD.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease: Current Evidence and Future Perspectives

Alzheimer's disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer's disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer's disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer's disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer's disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

Exome-wide rare variant analysis in familial essential tremor

INTRODUCTION

Essential tremor (ET) is one of the most common movement disorders. Despite its high prevalence and heritability, its genetic etiology remains elusive with only a few susceptibility genes identified and poorly replicated. Our aim was to find novel candidate genes involved in ET predisposition through whole exome sequencing.

METHODS

We studied eight multigenerational families (N = 40 individuals) with an autosomal-dominant inheritance using a comprehensive strategy combining whole exome sequencing followed by case-control association testing of prioritized variants in a separate cohort comprising 521 ET cases and 596 controls. We further performed gene-based burden analyses in an additional dataset comprising 789 ET patients and 770 healthy individuals to investigate whether there was an enrichment of rare deleterious variants within our candidate genes.

RESULTS

Fifteen variants co-segregated with disease status in at least one of the families, among which rs749875462 in CCDC183, rs535864157 in MMP10 and rs114285050 in GPR151 showed a nominal association with ET. However, we found no significant enrichment of rare variants within these genes in cases compared with controls. Interestingly, MMP10 protein is involved in the inflammatory response to neuronal damage and has been previously associated with other neurological disorders.

CONCLUSIONS

We prioritized a set of promising genes, especially MMP10, for further genetic and functional studies in ET. Our study suggests that rare deleterious coding variants that markedly increase susceptibility to ET are likely to be found in many genes. Future studies are needed to replicate and further infer biological mechanisms and potential disease causality for our identified genes.

Inflammation in Alzheimer's Disease: Do Sex and APOE Matter?

BACKGROUND

Alzheimer's disease (AD) disproportionately affects females with steeper cognitive decline and more neuropathology compared to males, which is exacerbated in females carrying the APOEɛ4 allele. The risk of developing AD is also higher in female APOEɛ4 carriers in earlier age groups (aged 65-75), and the progression from cognitively normal to mild cognitive impairment (MCI) and to AD may be influenced by sex. Inflammation is observed in AD and is related to aging, stress, and neuroplasticity, and although studies are scarce, sex differences are noted in inflammation.

OBJECTIVE

The objective of this study was to investigate underlying physiological inflammatory mechanisms that may help explain why there are sex differences in AD and APOEɛ4 carriers.

METHODS

We investigated, using the ADNI database, the effect of sex and APOE genotype (non-carriers or carriers of 1 and 2 APOEɛ4 alleles) and sex and diagnosis (cognitively normal (CN), MCI, AD) on CSF (N = 279) and plasma (N = 527) markers of stress and inflammation.

RESULTS

We found CSF IL-16 and IL-8 levels differed by sex and APOE genotype, as IL-16 was higher in female APOEɛ4 carriers compared to non-carriers, while the opposite pattern was observed in males with IL-8. Furthermore, females had on average higher levels of plasma CRP and ICAM1 but lower levels of CSF ICAM1, IL-8, IL-16, and IgA than males. Carrying APOEɛ4 alleles and diagnosis (MCI and AD) decreased plasma CRP in both sexes.

CONCLUSION

Sex and APOE genotype differences in CSF and plasma inflammatory biomarkers support that the underlying physiological changes during aging differ by sex and tissue origin.

Neutrophil activation in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis of protein markers in blood and cerebrospinal fluid

Inflammation is involved in the pathophysiology of Alzheimer's disease (AD), with multiple inflammatory processes implicated in its risk and progression. This review included original peer-reviewed studies measuring the cerebrospinal fluid or peripheral blood concentrations of protein markers specifically related to neutrophil activity in healthy controls (HC) and in patients with AD or mild cognitive impairment (MCI). A total of 35 studies (N_HC = 3095, N_AD = 2596, N_MCI = 1203) were included. Random-effects meta-analyses were used to estimate between-groups standardized mean differences (SMD) and 95 % confidence intervals. In blood, concentrations of myeloperoxidase (MPO; N_AD/N_HC = 271/209, SMD = 0.41 [0.20, 0.62]; I² = 15.7 %) and neutrophil gelatinase associated lipocalin (NGAL; N_AD/N_HC = 273/185, SMD = 0.30 [0.11, 0.49]; I² < 0.005 %) were significantly higher in AD relative to HC. Peripheral blood concentrations of NGAL were also higher in MCI compared to HC (N_MCI/N_HC = 489/145, SMD = 0.39 [0.11, 0.67]; I² = 38.6 %). None of the protein markers exhibited a significant difference between HC, MCI, or AD groups in the cerebrospinal fluid. The evidence suggests that peripheral neutrophil activation, as indicated by blood concentrations of NGAL and MPO, may be a pathological feature of cognitive impairment due to AD, evident at stages of MCI and AD dementia.

Sexual dimorphism of physical activity on cognitive aging: Role of immune functioning

OBJECTIVE

Exercise is one of the most potent strategies available to support cognitive health with age, yet substantial variability exists. Sexual dimorphism is evident for brain and immune functioning, the latter being implicated as important pathway for exercise. We examined the moderating role of sex on the relationship between physical activity and systemic inflammatory and brain health outcomes in support of more personalized approaches to behavioral interventions.

METHODS

Our discovery cohort included 45 typically aging women matched on age (±5y) and education (±2y) to 45 men (mean age = 72.5; Clinical Dementia Rating = 0) who completed self-reported current physical activity (Physical Activity Scale for Elderly), blood draw, neuropsychological evaluation, and brain MRI. An independent sample of 45 typically aging women and 36 men who completed the same measures comprised a replication cohort. Plasma was analyzed for 11 proinflammatory cytokine and chemokine markers via MesoScale Discovery.

RESULTS

Discovery cohort: Reported physical activity did not differ between sexes (150 vs. 157, p = 0.72). There was a significant interaction between sex and physical activity on chemokine markers MDC, MIP-1b, MCP-4, and eotaxin-3 (ps < 0.03), with a similar trend for MCP-1 and INFγ (ps < 0.09). Men who reported greater activity demonstrated lower inflammatory markers, an effect attenuated-to-absent in women. An interaction between sex and physical activity was also observed for parahippocampal volumes (p = 0.02) and cognition (processing speed and visual memory; ps < 0.04). Again, the beneficial effect of physical activity on outcomes was present in men, but not women. Replication cohort analyses conferred a consistent effect of sex on the relationship between physical activity and immune markers; models examining neurobehavioral outcomes did not strongly replicate. Across cohorts, post-hoc models demonstrated an interaction between sex and activity-related inflammatory markers on total gray matter volume and visual memory. Men with higher inflammatory markers demonstrated poorer brain structure and function, whereas inflammatory markers did not strongly relate to neurobehavioral outcomes in women.

CONCLUSIONS

Greater physical activity was associated with lower markers of inflammation in clinically normal older men, but not women - an effect consistently replicated across cohorts. Additionally, men appeared disproportionately vulnerable to the adverse effects of peripheral inflammatory markers on brain structure and function compared to women. Immune activation may be a male-specific pathway through which exercise confers neurobehavioral benefit.

Identification of a Simple and Novel Cut-Point Based Cerebrospinal Fluid and MRI Signature for Predicting Alzheimer's Disease Progression that Reinforces the 2018 NIA-AA Research Framework

The 2018 NIA-AA research framework proposes a classification system with Amyloid-β deposition, pathologic Tau, and Neurodegeneration (ATN) for diagnosis and staging of Alzheimer's disease (AD). Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database can be utilized to identify diagnostic signatures for predicting AD progression, and to determine the utility of this NIA-AA research framework. Profiles of 320 peptides from baseline cerebrospinal fluid (CSF) samples of 287 normal, mild cognitive impairment (MCI), and AD subjects followed over a 3-10-year period were measured via multiple reaction monitoring mass spectrometry. CSF Aβ42, total-Tau (tTau), phosphorylated-Tau (pTau-181), and hippocampal volume were also measured. From these candidate markers, optimal signatures with decision thresholds to separate AD and normal subjects were first identified via unbiased regression and tree-based algorithms. The best performing signature determined via cross-validation was then tested in an independent group of MCI subjects to predict future progression. This multivariate analysis yielded a simple diagnostic signature comprising CSF pTau-181 to Aβ42 ratio, MRI hippocampal volume, and low CSF levels of a novel PTPRN peptide, with a decision threshold on each marker. When applied to a separate MCI group at baseline, subjects meeting these signature criteria experience 4.3-fold faster progression to AD compared to a 2.2-fold faster progression using only conventional markers. This novel 4-marker signature represents an advance over the current diagnostics based on widely used markers, and is easier to use in practice than recently published complex signatures. This signature also reinforces the ATN construct from the 2018 NIA-AA research framework.

A comprehensive systematic review of CSF proteins and peptides that define Alzheimer's disease

BACKGROUND

During the last two decades, over 100 proteomics studies have identified a variety of potential biomarkers in CSF of Alzheimer's (AD) patients. Although several reviews have proposed specific biomarkers, to date, the statistical relevance of these proteins has not been investigated and no peptidomic analyses have been generated on the basis of specific up- or down- regulation. Herein, we perform an analysis of all unbiased explorative proteomics studies of CSF biomarkers in AD to critically evaluate whether proteins and peptides identified in each study are consistent in distribution; direction change; and significance, which would strengthen their potential use in studies of AD pathology and progression.

METHODS

We generated a database containing all CSF proteins whose levels are known to be significantly altered in human AD from 47 independent, validated, proteomics studies. Using this database, which contains 2022 AD and 2562 control human samples, we examined whether each protein is consistently present on the basis of reliable statistical studies; and if so, whether it is over- or under-represented in AD. Additionally, we performed a direct analysis of available mass spectrometric data of these proteins to generate an AD CSF peptide database with 3221 peptides for further analysis.

RESULTS

Of the 162 proteins that were identified in 2 or more studies, we investigated their enrichment or depletion in AD CSF. This allowed us to identify 23 proteins which were increased and 50 proteins which were decreased in AD, some of which have never been revealed as consistent AD biomarkers (i.e. SPRC or MUC18). Regarding the analysis of the tryptic peptide database, we identified 87 peptides corresponding to 13 proteins as the most highly consistently altered peptides in AD. Analysis of tryptic peptide fingerprinting revealed specific peptides encoded by CH3L1, VGF, SCG2, PCSK1N, FBLN3 and APOC2 with the highest probability of detection in AD.

CONCLUSIONS

Our study reveals a panel of 27 proteins and 21 peptides highly altered in AD with consistent statistical significance; this panel constitutes a potent tool for the classification and diagnosis of AD.

Artificial intelligence and neuropsychological measures: The case of Alzheimer's disease

One of the current challenges in the field of Alzheimer's disease (AD) is to identify patients with mild cognitive impairment (MCI) that will convert to AD. Artificial intelligence, in particular machine learning (ML), has established as one of more powerful approach to extract reliable predictors and to automatically classify different AD phenotypes. It is time to accelerate the translation of this knowledge in clinical practice, mainly by using low-cost features originating from the neuropsychological assessment. We performed a meta-analysis to assess the contribution of ML and neuropsychological measures for the automated classification of MCI patients and the prediction of their conversion to AD. The pooled sensitivity and specificity of patients' classifications was obtained by means of a quantitative bivariate random-effect meta-analytic approach. Although a high heterogeneity was observed, the results of meta-analysis show that ML applied to neuropsychological measures can lead to a successful automatic classification, being more specific as screening rather than prognosis tool. Relevant categories of neuropsychological tests can be extracted by ML that maximize the classification accuracy.

Key role of MIF-related neuroinflammation in neurodegeneration and cognitive impairment in Alzheimer's disease

Background

Macrophage Migration Inhibitory Factor (MIF) is a potent proinflammatory cytokine that promotes the production of other immune mediators. MIF is produced by most cell types in the brain including microglia, astrocytes and neurons. Enhanced expression of MIF might contribute to the persistent activation of glial, chronic neuroinflammation and neurodegeneration. Here, we investigated the effect of MIF on inflammatory markers and spatial learning in a mouse model of sporadic AD and on tau pathology in AD patients.

Methods

We examined the effects of MIF deficiency and pharmacological MIF inhibition in vitro and in vivo. In vitro, quantitative PCR and ELISA were used to assess cytokine production of STZ-treated glial cells. In vivo, C57BL/6 mice were subjected to intracerebroventricular streptozotocin injection (3 mg/kg, ICV-STZ). Neuroinflammation and contextual learning performance were assessed using quantitative PCR and fear conditioning, respectively. Pharmacological MIF inhibition was achieved with intraperitoneal injections of ISO-1 (daily, IP, 20 mg/kg in 5% DMSO in 0.9% NaCl) for 4 weeks following ICV-STZ injection. The findings from ISO-1 treated mice were confirmed in MIF knockout C57BL/6. To assess the role of MIF in human AD, cerebrospinal fluid levels of MIF and hyperphosphorylated tau were measured using ELISA.

Results

Administration ICV-STZ resulted in hippocampal dependent cognitive impairment. MIF inhibition with ISO-1 significantly improved the STZ-induced impairment in contextual memory performance, indicating MIF-related inflammation as a major contributor to ICV-STZ-induced memory deficits. Furthermore, inhibition of the MIF resulted in reduced cytokine production in vitro and in vivo.

In human subjects with AD at early clinical stages, cerebrospinal fluid levels of MIF were increased in comparison with age-matched controls, and correlated with biomarkers of tau hyper-phosphorylation and neuronal injury hinting at MIF levels as a potential biomarker for early-stage AD.

Conclusions

The present study indicates the key role of MIF in controlling the chronic cytokine release in neuroinflammation related to tau hyperphosphorylation, neurodegeneration, and clinical manifestations of AD, suggesting the potential of MIF inhibition as therapeutic strategy to slow down neurodegeneration and clinical disease progression.

MicroRNA-429/Cxcl1 Axis Protective Against Oxygen Glucose Deprivation/Reoxygenation-Induced Injury in Brain Microvascular Endothelial Cells

Objective:

The objective of the present work was to study the role of Cxcl1 in cerebral ischemia–reperfusion (I/R) injury and to in-depth explore its pathogenesis.

Methods:

The expression of Cxcl1 based on the public data was analyzed. Then, we constructed an oxygen glucose deprivation/reoxygenation (OGD/R) model in vitro using mice brain microvascular endothelial cells (BMECs) to simulate cerebral I/R in vivo.

Results:

The results of quantitative real-time polymerase chain reaction assay uncovered that Cxcl1 showed higher expression while miR-429 showed lower expression in BMECs damaged by OGD/R, whereas overexpression of Cxcl1 or inhibition of miR-429 expression can strengthen this effect. Hereafter, through dual luciferase reporter assay, we verified that miR-429 directly targets Cxcl1 and negatively regulates Cxcl1 expression. Furthermore, the results also revealed that overexpression of Cxcl1 can reverse the miR-429-mediated effects.

Conclusion:

We concluded that miR-429 exerts protective effects against OGD/R-induce injury in vitro through modulation of Cxcl1 and nuclear factor kinase B pathway, hoping provide a new view on the pathogenesis of cerebral I/R injury and a feasible potential therapeutic target.

Apolipoprotein D: a potential biomarker for cerebral amyloid angiopathy

AIMS

We investigated the potential of apolipoprotein D (apoD) as cerebrospinal fluid (CSF) biomarker for cerebral amyloid angiopathy (CAA) after confirmation of its association with CAA pathology in human brain tissue.

METHODS

The association of apoD with CAA pathology was analysed in human occipital lobe tissue of CAA (n = 9), Alzheimer's disease (AD) (n = 11) and healthy control cases (n = 11). ApoD levels were quantified in an age- and sex-matched CSF cohort of CAA patients (n = 31), AD patients (n = 27) and non-neurological controls (n = 67). The effects of confounding factors (age, sex, serum levels) on apoD levels were studied using CSF of non-neurological controls (age range 16-85 years), and paired CSF and serum samples.

RESULTS

ApoD was strongly associated with amyloid deposits in vessels, but not with parenchymal plaques in human brain tissue. CSF apoD levels correlated with age and were higher in men than women in subjects >50 years. The apoD CSF/serum ratio correlated with the albumin ratio. When controlling for confounding factors, CSF apoD levels were significantly lower in CAA patients compared with controls and compared with AD patients (P = 0.0008).

CONCLUSIONS

Our data show that apoD is specifically associated with CAA pathology and may be a CSF biomarker for CAA, but clinical application is complicated due to dependency on age, sex and blood-CSF barrier integrity. Well-controlled follow-up studies are required to determine whether apoD can be used as reliable biomarker for CAA.

Clinically accurate diagnosis of Alzheimer's disease via multiplexed sensing of core biomarkers in human plasma

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder, affecting one in ten people aged over 65 years. Despite the severity of the disease, early diagnosis of AD is still challenging due to the low accuracy or high cost of neuropsychological tests and neuroimaging. Here we report clinically accurate and ultrasensitive detection of multiple AD core biomarkers (t-tau, p-tau₁₈₁, Aβ₄₂, and Aβ₄₀) in human plasma using densely aligned carbon nanotubes (CNTs). The closely packed and unidirectionally aligned CNT sensor array exhibits high precision, sensitivity, and accuracy, evidenced by a low coefficient of variation (<6%), a femtomolar-level limit of detection, and a high degree of recovery (>93.0%). By measuring the levels of t-tau/Aβ₄₂, p-tau₁₈₁/Aβ₄₂, and Aβ₄₂/Aβ₄₀ in clinical blood samples, the sensor array successfully discriminates the clinically diagnosed AD patients from healthy controls with an average sensitivity of 90.0%, a selectivity of 90.0%, and an average accuracy of 88.6%.

Detection of Alzheimer’s disease (AD) biomarkers from patients’ blood is challenging because these are present in very low concentrations in the plasma. Here the authors develop a sensor array of densely aligned single-walled carbon nanotubes for clinically accurate detection of femtomolar AD biomarkers in human plasma samples.

Macrophage Migration Inhibitory Factor Alters Functional Properties of CA1 Hippocampal Neurons in Mouse Brain Slices

Neuroinflammation is implicated in a host of neurological insults, such as traumatic brain injury (TBI), ischemic stroke, Alzheimer's disease, Parkinson's disease, and epilepsy. The immune response to central nervous system (CNS) injury involves sequelae including the release of numerous cytokines and chemokines. Macrophage migration inhibitory factor (MIF), is one such cytokine that is elevated following CNS injury, and is associated with the prognosis of TBI, and ischemic stroke. MIF has been identified in astrocytes and neurons, and some of the trophic actions of MIF have been related to its direct and indirect actions on astrocytes. However, the potential modulation of CNS neuronal function by MIF has not yet been explored. This study tests the hypothesis that MIF can directly influence hippocampal neuronal function. MIF was microinjected into the hippocampus and the genetically encoded calcium indicator, GCaMP6f, was used to measure Ca²⁺ events in acute adult mouse brain hippocampal slices. Results demonstrated that a single injection of 200 ng MIF into the hippocampus significantly increased baseline calcium signals in CA1 pyramidal neuron somata, and altered calcium responses to N-methyl-d-aspartate (NMDA) + D-serine in pyramidal cell apical dendrites located in the stratum radiatum. These data are the first to show direct effects of MIF on hippocampal neurons and on NMDA receptor function. Considering that MIF is elevated after brain insults such as TBI, the data suggest that, in addition to the previously described role of MIF in astrocyte reactivity, elevated MIF can have significant effects on neuronal function in the hippocampus.

Cerebrospinal fluid proteomics and biological heterogeneity in Alzheimer's disease: A literature review

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by aggregation of amyloid and tau proteins in the brain. Results from genetic studies suggest that the pathophysiology underlying AD is complex, but studying this complexity in patients remains difficult. The cerebrospinal fluid (CSF) proteome contains a large number of proteins that can reflect ongoing biological processes. Proteomics techniques can be used to measure many proteins simultaneously in individual patients and may therefore provide an opportunity to study AD disease mechanisms. Here, we review the CSF proteomics literature to identify proteins consistently associated with AD, and perform pathway analyses on these proteins to study which biological processes may be involved in the disease.We performed a literature search of studies that investigated CSF proteomic alterations related to AD. We included original research articles when they measured at least 10 proteins in (antemortem) CSF in at least 10 individuals with AD, mild cognitive impairment (MCI) or controls. We examined if proteins were consistently related to AD, defined as consistent increase or decrease in AD vs. controls across studies. Next, we used the proteins identified as input to pathway analyses using Reactome to investigate which biological processes were enriched.In total, 29 studies were included that investigated AD-related changes to the CSF proteome, including a total of 1434 individuals with AD (of whom 47.1% had a CSF biomarker profile and 9.6% a postmortem examination consistent with AD) and 1380 controls. The studies reported 1 to 138 proteins associated with AD, of which 97 proteins were reported by two or more studies. Among proteins that were measured in more than one study, 27 (27.8%) showed consistent increases, 15 (15.5%) consistent decreases and 55 (56.7%) had contrasting results. Pathway analyses showed that AD-related proteins were enriched for hemostasis, lipoprotein and extracellular matrix pathways.These results indicate that proteomic alterations in CSF associated with AD reflect involvement of various biological pathways. The frequent occurrence of inconsistent protein level changes reported by different studies suggests that additional biological and/or (pre)analytical factors may influence the CSF proteome in AD, which should be further investigated in order to improve understanding of the biological complexity underlying AD.

VGF in Cerebrospinal Fluid Combined With Conventional Biomarkers Enhances Prediction of Conversion From MCI to AD

BACKGROUND

Previous work has suggested that the brain and cerebrospinal fluid (CSF) levels of a neural protein involved in synaptic transmission, VGF (a noninitialism), may be altered in mild cognitive impairment (MCI) and Alzheimer Disease (AD). The objective of the current work is to examine the potential of CSF levels of a peptide derived from VGF to predict conversion from MCI to AD.

MATERIALS AND METHODS

Using multivariate analytical approaches, the performance of the conventional biomarkers (CSF Aβ1-42 and phosphorylated tau +/- hippocampal volume) was compared with the same biomarkers combined with CSF VGF peptide levels in a large publicly available data set from human subjects.

RESULTS

It was observed that VGF peptides are lowered in CSF of patients with AD compared with controls and that combinations of CSF Aβ1-42 and phosphorylated tau, hippocampal volume, and VGF peptide levels outperformed conventional biomarkers alone (hazard ratio=2.2 vs. 3.9), for predicting MCI to AD conversion.

CONCLUSIONS

CSF VGF enhances the ability of conventional biomarkers to predict MCI to AD conversion. Future work will be needed to determine the specificity of VGF for AD versus other neurodegenerative diseases.

Levels of islet amyloid polypeptide in cerebrospinal fluid and plasma from patients with Alzheimer's disease

The biologically active pancreatic hormone peptide islet amyloid polypeptide (IAPP) regulates brain functions such as appetite and cognition. It also plays a role in clearance of amyloid beta (Aβ), a peptide implicated in the dementia disorder Alzheimer’s disease (AD). If IAPP becomes modified, it loses its biological activity and starts to aggregate. Such aggregations have been found in the AD brain and decreased plasma levels of the unmodified IAPP (uIAPP) have been shown in the same patients. In the current study, we analyze levels of uIAPP and total IAPP (unmodified and modified) in cerebrospinal fluid (CSF) to investigate its potential as a biomarker for AD. We found no differences in neither CSF nor plasma levels of uIAPP or total IAPP in AD patients compared to cognitive healthy individuals (NC). The levels of uIAPP in CSF of NC were positively correlated with uIAPP in plasma, Q-albumin and albumin levels in CSF, but negatively correlated with CSF levels of t-tau and p-tau. These findings were not seen in AD patients. Levels of total CSF IAPP correlated positively with total Q-albumin and albumin levels in CSF in both AD and NC. In addition, total plasma IAPP correlated positively with CSF t-tau and p-tau in NC and negatively with CSF Aβ₄₂ in AD patients. To conclude, our studies did not find evidence supporting the use of CSF IAPP as an AD biomarker. However, our findings, indicating a compromised translocation of uIAPP in and out of the brain in AD patients as well as the correlations between total plasma IAPP and AD biomarkers, encourage further research on the role for IAPP in AD.

Upregulation of MIF as a defense mechanism and a biomarker of Alzheimer's disease

BACKGROUND

Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine. Chronic inflammation induced by amyloid β proteins (Aβ) is one prominent neuropathological feature in Alzheimer's disease (AD) brain.

METHODS

Elisa, Western blot, and immunohistochemical staining analysis were performed to examine the level of MIF protein in CSF and brain tissues. MTT and LDH assays were used to examine the neurotoxicity, and the Morris Water Maze test was performed to examine the cognitive function in the MIF^+/-/APP23 transgenic mice.

RESULTS

MIF expression was upregulated in the brain of AD patients and AD model mice. Elevated MIF concentration was detected in the cerebrospinal fluid of AD patients but not in that of the patients suffering from mild cognitive impairment and vascular dementia. Reduced MIF expression impaired learning and memory in the AD model mice. MIF expression largely associates with Aβ deposits and microglia. The binding assay revealed a direct association between MIF and Aβ oligomers. Neurons instead of glial cells were responsible for the secretion of MIF upon stimulation by Aβ oligomers. In addition, overexpression of MIF significantly protected neuronal cells from Aβ-induced cytotoxicity.

CONCLUSION

Our study suggests that neuronal secretion of MIF may serve as a defense mechanism to compensate for declined cognitive function in AD, and increased MIF level could be a potential AD biomarker.

A Random Forests Quantile Classifier for Class Imbalanced Data

Extending previous work on quantile classifiers (q-classifiers) we propose the q*-classifier for the class imbalance problem. The classifier assigns a sample to the minority class if the minority class conditional probability exceeds 0 < q* < 1, where q* equals the unconditional probability of observing a minority class sample. The motivation for q*-classification stems from a density-based approach and leads to the useful property that the q*-classifier maximizes the sum of the true positive and true negative rates. Moreover, because the procedure can be equivalently expressed as a cost-weighted Bayes classifier, it also minimizes weighted risk. Because of this dual optimization, the q*-classifier can achieve near zero risk in imbalance problems, while simultaneously optimizing true positive and true negative rates. We use random forests to apply q*-classification. This new method which we call RFQ is shown to outperform or is competitive with existing techniques with respect to tt-mean performance and variable selection. Extensions to the multiclass imbalanced setting are also considered.

CSF Cytokines in Aging, Multiple Sclerosis, and Dementia

Inflammation is a common process involved in aging, multiple sclerosis (MS), and age-related neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD), but there is limited evidence for the effects of aging on inflammation in the central nervous system. We collected cerebrospinal fluid (CSF) from 105 healthy control subjects representing a wide age range (23–86), and analyzed levels of cytokines associated innate immunity (TNF-α) and different T-helper subtypes: interferon–gamma induced protein 10 (IP-10) for Th1, interleukin-10 (IL-10) for Th2, and interleukin 8 (IL-8/CXCL8) for Th17. We show that CSF levels of TNF-α, IP-10, and IL-8 all increased linearly with age, but levels of IL-10 demonstrated a U-shaped relationship with age. We further found greater age-related increases in TNF-α, IL-10, and IL-8 relative to increases in IP-10 levels, consistent with a shift from Th1 to other inflammatory phenotypes. Finally, when we analyzed the same four cytokines in people with neurological disorders, we found that MS and AD, but not PD or dementia with Lewy bodies, further accentuated the age-related shift from Th1- to non-Th1-related cytokines. We propose that CSF cytokine levels represent powerful surrogates of brain inflammation and aging, and some, but not all, neurological disorders accelerate the shift away from Th1 phenotypes.