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Chronic pain leads to tau accumulation and hippocampal atrophy in mice. In this study, we provide one of the first assessments in humans, examining the associations of probable chronic pain with hippocampal volume, integrity of the locus coeruleus (LC)-an upstream site of tau deposition-and Alzheimer's Disease-related plasma biomarkers. Participants were mostly cognitively unimpaired men. Probable chronic pain was defined as moderate-to-severe pain in 2+ study waves at average ages 56, 62, and 68. At age 68, 424 participants underwent structural magnestic resonance imaging (MRI) of hippocampal volume and LC-sensitive MRI providing an index of LC integrity (LC contrast-to-noise ratio). Analyses adjusted for confounders including major health conditions, depressive symptoms, and opioid use. Models showed that men with probable chronic pain had smaller hippocampal volume and lower rostral-middle-but not caudal-LC contrast-to-noise ratio compared to men without probable chronic pain. Men with probable chronic pain also had higher levels of plasma total tau, beta-amyloid-42, and beta-amyloid-40 compared to men without probable chronic pain. These findings suggest that probable chronic pain is associated with tau accumulation and reduced structural brain integrity in regions affected early in the development of Alzheimer's Disease. PERSPECTIVE: Probable chronic pain was associated with plasma biomarkers and brain regions that are affected early in Alzheimer's disease (AD). Reducing pain in midlife and elucidating biological mechanisms may help to reduce the risk of AD in older adults., (Copyright © 2024 United States Association for the Study of Pain, Inc. Published by Elsevier Inc. All rights reserved.)

The delineation of biomarkers and neuropsychiatric symptoms across normal cognition, mild cognitive impairment (MCI), and dementia stages holds significant promise for early diagnosis and intervention strategies. This research investigates the association of neuropsychiatric symptoms, evaluated via the Neuropsychiatric Inventory (NPI), with cerebrospinal fluid (CSF) biomarkers (Amyloid-β42, P-tau, T-tau) across a spectrum of cognitive states to enhance diagnostic accuracy and treatment approaches. Drawing from the National Alzheimer's Coordinating Center's Uniform Data Set Version 3, comprising 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. To assess neuropsychiatric symptoms, we employed the NPI to understand the behavioral and psychological symptoms associated with each cognitive category. For the analysis of CSF biomarkers, we measured levels of Amyloid-β42, P-tau, and T-tau using the enzyme-linked immunosorbent assay (ELISA) and Luminex multiplex xMAP assay protocols. These biomarkers are critical in understanding the pathophysiological underpinnings of Alzheimer's disease and its progression, with specific patterns indicative of disease stage and severity. This study cohort consists of 1896 participants, which is composed of 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. Dementia is characterized by significantly higher NPI scores, which are largely reflective of mood-related symptoms ( p < 0.001). In terms of biomarkers, normal cognition shows median Amyloid-β at 656.0 pg/mL, MCI at 300.6 pg/mL, and dementia at 298.8 pg/mL ( p < 0.001). Median P-tau levels are 36.00 pg/mL in normal cognition, 49.12 pg/mL in MCI, and 58.29 pg/mL in dementia ( p < 0.001). Median T-tau levels are 241.0 pg/mL in normal cognition, 140.6 pg/mL in MCI, and 298.3 pg/mL in dementia ( p < 0.001). Furthermore, the T-tau/Aβ-42 ratio increases progressively from 0.058 in the normal cognition group to 0.144 in the MCI group, and to 0.209 in the dementia group ( p < 0.001). Similarly, the P-tau/Aβ-42 ratio also escalates from 0.305 in individuals with normal cognition to 0.560 in MCI, and to 0.941 in dementia ( p < 0.001). The notable disparities in NPI and CSF biomarkers among normal, MCI and Alzheimer's patients underscore their diagnostic potential. Their combined assessment could greatly improve early detection and precise diagnosis of MCI and dementia, facilitating more effective and timely treatment strategies.

Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such as amyloid beta 1-42, T-tau, and P-tau, in early diagnosis of Alzheimer's disease stages. The levels of these biomarkers in conjunction with the dementia rating scores are used to empirically differentiate the dementia patients from normal controls. In this work, we evaluated the performance of standard machine learning classifiers using cerebrospinal fluid biomarker levels as the features to differentiate dementia patients from normal controls. We employed various types of machine learning models, that includes Discriminant, Logistic Regression, Tree, K-Nearest Neighbor, Support Vector Machine, and Naïve Bayes classifiers. The results demonstrate that these models can distinguish cognitively impaired subjects from normal controls with an accuracy ranging from 64% to 69% and an area under the curve of the receiver operating characteristics between 0.64 and 0.73. In addition, we found that the levels of 2 biomarkers, amyloid beta 1-42 and T-tau, provide a modest improvement in accuracy when distinguishing dementia patients from healthy controls., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Alzheimer's disease cerebrospinal fluid (CSF) biomarkers amyloid-β 1-42 (Aβ42), total tau (T-tau), and phosphorylated tau 181 (P-tau181) are widely used. However, concentration gradient of these biomarkers between intraventricular (V-CSF) and lumbar CSF (L-CSF) has been demonstrated in idiopathic normal pressure hydrocephalus (iNPH), potentially affecting clinical utility., Objective: Here we aim to provide conversion factors for clinical and research use between V-CSF and L-CSF., Methods: Altogether 138 iNPH patients participated. L-CSF samples were obtained prior to shunt surgery. Intraoperative V-CSF samples were obtained from 97 patients. Post-operative follow-up L- and V-CSF (shunt reservoir) samples of 41 patients were obtained 1-73 months after surgery and then after 3, 6, and 18 months. CSF concentrations of Aβ42, T-tau, and P-tau181 were analyzed using commercial ELISA assays., Results: Preoperative L-CSF Aβ42, T-tau, and P-tau181 correlated to intraoperative V-CSF (ρ= 0.34-0.55, p < 0.001). Strong correlations were seen between postoperative L- and V-CSF for all biomarkers in every follow-up sampling point (ρs Aβ42: 0.77-0.88, T-tau: 0.91-0.94, P-tau181: 0.94-0.96, p < 0.0001). Regression equations were determined for intraoperative V- and preoperative L-CSF (Aβ42: V-CSF = 185+0.34*L-CSF, T-tau: Ln(V-CSF) = 3.11+0.49*Ln(L-CSF), P-tau181: V-CSF = 8.2+0.51*L-CSF), and for postoperative V- and L-CSF (Aβ42: V-CSF = 86.7+0.75*L-CSF, T-tau: V-CSF = 86.9+0.62*L-CSF, P-tau181: V-CSF = 2.6+0.74*L-CSF)., Conclusion: Aβ42, T-tau, and P-tau181 correlate linearly in-between V- and L-CSF, even stronger after CSF shunt surgery. Equations presented here, provide a novel tool to use V-CSF for diagnostic and prognostic entities relying on the L-CSF concentrations and can be applicable to clinical use when L-CSF samples are not available or less invasively obtained shunt reservoir samples should be interpreted.

Background: Toxic amyloid-β (Aβ) peptides aggregate into higher molecular weight assemblies and accumulate not only in the extracellular space, but also in the walls of blood vessels in the brain, increasing their permeability, and promoting immune cell migration and activation. Given the prominent role of the immune system, phagocytic blood cells may contact pathological brain materials., Objective: To develop a novel method for early Alzheimer's disease (AD) detection, we used blood leukocytes, that could act as "sentinels" after trafficking through the brain microvasculature, to detect pathological amyloid by labelling with a conformationally-sensitive fluorescent amyloid probe and imaging with confocal spectral microscopy., Methods: Formalin-fixed peripheral blood mononuclear cells (PBMCs) from cognitively healthy control (HC) subjects, mild cognitive impairment (MCI) and AD patients were stained with the fluorescent amyloid probe K114, and imaged. Results were validated against cerebrospinal fluid (CSF) biomarkers and clinical diagnosis., Results: K114-labeled leukocytes exhibited distinctive fluorescent spectral signatures in MCI/AD subjects. Comparing subjects with single CSF biomarker-positive AD/MCI to negative controls, our technique yielded modest AUCs, which improved to the 0.90 range when only MCI subjects were included in order to measure performance in an early disease state. Combining CSF Aβ42 and t-Tau metrics further improved the AUC to 0.93., Conclusion: Our method holds promise for sensitive detection of AD-related protein misfolding in circulating leukocytes, particularly in the early stages of disease.

Purpose: In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer's disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers-encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)-with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology., Methods: A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop., Results: By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability., Conclusions: Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Background: Longitudinal changes in cerebrospinal fluid (CSF) biomarkers are seldom studied. Furthermore, data on biomarker gradient between lumbar (L-) and ventricular (V-) compartments seems to be discordant., Objective: To examine alteration of CSF biomarkers reflecting Alzheimer's disease (AD)-related amyloid-β (Aβ) aggregation, tau pathology, neurodegeneration, and early synaptic degeneration by CSF shunt surgery in idiopathic normal pressure hydrocephalus (iNPH) in relation to AD-related changes in brain biopsy. In addition, biomarker levels in L- and V-CSF were compared., Methods: L-CSF was collected prior to shunt placement and, together with V-CSF, 3-73 months after surgery. Thereafter, additional CSF sampling took place at 3, 6, and 18 months after the baseline sample from 26 iNPH patients with confirmed Aβ plaques in frontal cortical brain biopsy and 13 iNPH patients without Aβ pathology. CSF Amyloid-β42 (Aβ42), total tau (T-tau), phosphorylated tau (P-tau181), neurofilament light (NFL), and neurogranin (NRGN) were analyzed with customized ELISAs., Results: All biomarkers but Aβ42 increased notably by 140-810% in L-CSF after CSF diversion and then stabilized. Aβ42 instead showed divergent longitudinal decrease between Aβ-positive and -negative patients in L-CSF, and thereafter increase in Aβ-negative iNPH patients in both L- and V-CSF. All five biomarkers correlated highly between V-CSF and L-CSF (Aβ42 R = 0.87, T-tau R = 0.83, P-tau R = 0.92, NFL R = 0.94, NRGN R = 0.9; all p < 0.0001) but were systematically lower in V-CSF (Aβ42 14 %, T-tau 22%, P-tau 20%, NFL 32%, NRGN 19%). With APOE genotype-grouping, only Aβ42 showed higher concentration in non-carriers of allele ɛ4., Conclusion: Longitudinal follow up shows that after an initial post-surgery increase, T-tau, P-tau, and NRGN are stable in iNPH patients regardless of brain biopsy Aβ pathology, while NFL normalized toward its pre-shunt levels. Aβ42 as biomarker seems to be the least affected by the surgical procedure or shunt and may be the best predictor of AD risk in iNPH patients. All biomarker concentrations were lower in V- than L-CSF yet showing strong correlations.

Study Objectives: To determine the effect of self-reported clinical diagnosis of obstructive sleep apnea (OSA) on longitudinal changes in brain amyloid PET and CSF biomarkers (Aβ42, T-tau, and P-tau) in cognitively normal (NL), mild cognitive impairment (MCI), and Alzheimer's disease (AD) elderly., Methods: Longitudinal study with mean follow-up time of 2.52 ± 0.51 years. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants included 516 NL, 798 MCI, and 325 AD elderly. Main outcomes were annual rate of change in brain amyloid burden (i.e. longitudinal increases in florbetapir PET uptake or decreases in CSF Aβ42 levels); and tau protein aggregation (i.e. longitudinal increases in CSF total tau [T-tau] and phosphorylated tau [P-tau]). Adjusted multilevel mixed effects linear regression models with randomly varying intercepts and slopes was used to test whether the rate of biomarker change differed between participants with and without OSA., Results: In NL and MCI groups, OSA+ subjects experienced faster annual increase in florbetapir uptake (B = .06, 95% CI = .02, .11 and B = .08, 95% CI = .05, .12, respectively) and decrease in CSF Aβ42 levels (B = -2.71, 95% CI = -3.11, -2.35 and B = -2.62, 95% CI = -3.23, -2.03, respectively); as well as increases in CSF T-tau (B = 3.68, 95% CI = 3.31, 4.07 and B = 2.21, 95% CI = 1.58, 2.86, respectively) and P-tau (B = 1.221, 95% CI = 1.02, 1.42 and B = 1.74, 95% CI = 1.22, 2.27, respectively); compared with OSA- participants. No significant variations in the biomarker changes over time were seen in the AD group., Conclusions: In both NL and MCI, elderly, clinical interventions aimed to treat OSA are needed to test if OSA treatment may affect the progression of cognitive impairment due to AD., (© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Background: To alleviate the interpretation of the core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers, amyloid β1-42 (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau), the Erlangen Score (ES) interpretation algorithm has been proposed., Objective: In this study, we aim to assess the predictive properties of the ES algorithm on cognitive and neuroimaging outcomes in mild cognitive impairment (MCI)., Methods: All MCI subjects with an available baseline CSF sample from ADNI-1 were included (n = 193), and assigned an ES between 0 and 4 based on their baseline CSF biomarker profile. Structural magnetic resonance imaging brain scans and MMSE and ADAS-Cog scores were collected at up to 7 times in follow-up examinations., Results: We observed strong and significant correlations between the ES at baseline and neuroimaging and cognitive results with patients with neurochemically probable AD (ES = 4) progressing significantly (p≤0.01) faster than those with a neurochemically improbable AD (ES = 0 or 1), and the subjects with neurochemically possible AD (ES = 2 or 3) in-between these two groups., Conclusion: This study further demonstrates the utility of the ES algorithm as a as a tool in predicting cognitive and imaging progression in MCI patients.

The role of PCSK9 in Alzheimer's disease (AD) is controversial. We compared cerebrospinal fluid (CSF) PCSK9 concentrations in 36 AD and 31 non-AD patients. CSF PCSK9 levels did not differ between AD and non-AD groups (2.80 versus 2.62 ng/mL). However, PCSK9 CSF levels were increased in AD and non-AD patients with other neurodegenerative process (non-AD ND, n = 20) compared to patients without neurodegenerative disorders (non-ND, n = 11): 2.80 versus 2.30 (p < 0.005) and 2.83 versus 2.30 ng/mL (p = NS), respectively. CSF PCSK9 were positively correlated with AD biomarkers (Aβ1-42, T-tau, and P-tau). PCSK9 concentrations in CSF are increased in neurodegenerative disorders rather than specifically in AD.

Latest research in the mental health field brings new hope to patients and promises to revolutionize the field of psychiatry. Personalized pharmacogenetic tests that aid in diagnosis and treatment choice are now becoming available for clinical practice. Amyloid beta peptide biomarkers in the cerebrospinal fluid of patients with Alzheimer's disease are now available. For the first time, radiologists are able to visualize amyloid plaques specific to Alzheimer's disease in live patients using Positron Emission Tomography-based tests approved by the FDA. A novel blood-based assay has been developed to aid in the diagnosis of depression based on activation of the HPA axis, metabolic, inflammatory and neurochemical pathways. Serotonin reuptake inhibitors have shown increased remission rates in specific ethnic subgroups and Cytochrome P450 gene polymorphisms can predict antidepressant tolerability. The latest research will help to eradicate "trial and error" prescription, ushering in the most personalized medicine to date. Like all major medical breakthroughs, integration of new algorithms and technologies requires sound science and time. But for many mentally ill patients, diagnosis and effective therapy cannot happen fast enough. This review will describe the newest diagnostic tests, treatments and clinical studies for the diagnosis and treatment of Alzheimer's disease and unipolar, major depressive disorder., (© 2013 Elsevier Inc. All rights reserved.)

Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity.