Associations between admission levels of multiple biomarkers and subsequent worse outcomes in acute ischemic stroke patients

The modified Rankin Scale change score (ΔmRS) is useful for evaluating acute poststroke functional improvement or deterioration. We investigated the relationship between multiple biomarkers and ΔmRS by analyzing data on 6931 patients with acute ischemic stroke (average age 62.3 ± 11.3 years, 2174 (31.4%) female) enrolled from the Third China National Stroke Registry (CNSR-III) and 15 available biomarkers. Worse outcomes at 3 months were defined as ΔmRS3m-discharge ≥1 (ΔmRS3m-discharge = mRS3m-mRSdischarge). Adjusted odds ratios (aORs) and their 95% confidence intervals (CIs) were calculated from logistic regression models. At 3-months poststroke, 1026 (14.8%) patients experienced worse outcomes. The highest quartiles of white blood cells (WBCs) (aOR [95%CI],1.37 [1.12-1.66]), high-sensitivity C-reactive protein (hs-CRP) (1.37 [1.12-1.67]), interleukin-6 (IL-6) (1.43 [1.16-1.76]), interleukin-1 receptor antagonist (IL-1Ra) (1.46 [1.20-1.78]) and YKL-40 (1.31 [1.06-1.63]) were associated with an increased risk of worse outcomes at 3 months. Results remained stable except for YKL-40 when simultaneously adding multiple biomarkers to the basic traditional-risk-factor model. Similar results were observed at 6 and 12 months after stroke. This study indicated that WBCs, hs-CRP, IL-6, IL-1Ra, and YKL-40 were significantly associated with worse outcomes in acute ischemic stroke patients, and all inflammatory biomarkers except YKL-40 were independent predictors of worse outcomes at 3 months.

Identification of Critical Genes Differentiating Stable and Unstable Atherosclerotic Plaques: A Bioinformatic and Computational Analysis

BACKGROUND

Identification of biomarkers to distinguish between stable and unstable plaque formation would be very useful to predict plaque vulnerability.

METHODS

We downloaded microarray profiles of gene set enrichment (GSE) accession numbers including GSE71226 and GSE20680 (group A: containing healthy vs stable plaque samples) and GSE62646 and GSE34822 (group B: containing stable vs unstable plaque samples) from Gene expression omnibus (GEO) database. Differentially expressed genes were compared in both data sets of each group.

RESULTS

Ten and 12 key genes were screened in groups A and B, respectively. Gene Ontology (GO) enrichment was applied by the plugin "BiNGO" (Biological networks gene ontology tool) of the Cytoscape. The key genes were mostly enriched in the biological process of positive regulation of the cellular process. The protein-protein interaction and co-expression network were analyzed by the STRING (search tool for the retrieval of interacting genes/proteins) and GeneMANIA (gene multiple association network integration algorithm) plugin of Cytoscape, respectively, which showed that Epidermal growth factor (EGF), Heparin-binding EGF like growth factor (HBEGF), and Matrix metalloproteinase 9 (MMP9) were at the core of the network. Further validation of key genes using two datasets showed that Phosphodiesterase 5A (PDE5A) and Protein S (PROS1) were decreased in unstable plaques, while Suppressor of cytokine signaling (SOCS3), HBEGF, and Leukocyte immunoglobulin-like receptor B4 (LILRB4) were increased.

CONCLUSION

The present study used several datasets to identify key genes associated with stable and unstable atherosclerotic plaque.

Impact of demographics and comorbid conditions on plasma biomarkers concentrations and their diagnostic accuracy in a memory clinic cohort

Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aβ) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aβ status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aβ positive) were included. Sex, age and Aβ status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized β -0.115 [-0.192 to -0.035], p = 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aβ status (0.685 [0.607-0.763], p < 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aβ status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aβ status discrimination was minimal.

Circulating biomarkers of inflammaging and Alzheimer's disease to track age-related trajectories of dementia: Can we develop a clinically relevant composite combination?

Alzheimer's disease (AD) is a rapidly growing global concern due to a consistent rise of the prevalence of dementia which is mainly caused by the aging population worldwide. An early diagnosis of AD remains important as interventions are plausibly more effective when started at the earliest stages. Recent developments in clinical research have focused on the use of blood-based biomarkers for improve diagnosis/prognosis of neurodegenerative diseases, particularly AD. Unlike invasive cerebrospinal fluid tests, circulating biomarkers are less invasive and will become increasingly cheaper and simple to use in larger number of patients with mild symptoms or at risk of dementia. In addition to AD-specific markers, there is growing interest in biomarkers of inflammaging/neuro-inflammaging, an age-related chronic low-grade inflammatory condition increasingly recognized as one of the main risk factor for almost all age-related diseases, including AD. Several inflammatory markers have been associated with cognitive performance and AD development and progression. The presence of senescent cells, a key driver of inflammaging, has also been linked to AD pathogenesis, and senolytic therapy is emerging as a potential treatment strategy. Here, we describe blood-based biomarkers clinically relevant for AD diagnosis/prognosis and biomarkers of inflammaging associated with AD. Through a systematic review approach, we propose that a combination of circulating neurodegeneration and inflammatory biomarkers may contribute to improving early diagnosis and prognosis, as well as providing valuable insights into the trajectory of cognitive decline and dementia in the aging population.

The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults

Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.

Predicting early Alzheimer's with blood biomarkers and clinical features

Alzheimer's disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer's Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

IgG glycosylation associates with risk of progression from latent to active tuberculosis

OBJECTIVES

Glycosylation motifs shape antibody structure, stability and antigen affinity and play an important role in antibody localization and function. Serum IgG glycosylation profiles are significantly altered in infectious diseases, including tuberculosis (TB), but have not been studied in the context of progression from latent to active TB.

METHODS

We performed a longitudinal study of paired bulk IgG glycosylation and transcriptomic profiling in blood from individuals with active TB (ATB) or latent TB infection (LTBI) before and after treatment.

RESULTS

We identified that a combination of two IgG1 glycosylation traits were sufficient to distinguish ATB from LTBI with high specificity and sensitivity, prior to, and after treatment. Importantly, these two features positively correlated with previously defined cellular and RNA signatures of ATB risk in LTBI, namely monocyte to lymphocyte ratio and the expression of interferon (IFN)-associated gene signature of progression (IFN-risk signature) in blood prior to treatment. Additional glycosylation features at higher prevalence in LTBI individuals with high expression of the IFN-risk signature prior to treatment included fucosylation on IgG1, IgG2 and IgG3.

CONCLUSIONS

Together, our results demonstrate that bulk IgG glycosylation features could be useful in stratifying the risk of LTBI reactivation and progression to ATB.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

BACKGROUND

Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation.

METHODS

Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations.

RESULTS

The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas.

CONCLUSIONS

The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

Association between nutritional status and biochemical markers among hematopoietic stem cell transplant candidates: a cross-sectional study

AIM

Candidates of Hematopoietic Stem Cell Transplantation (HSCT) may be at nutritional risk due to decreased oral intake, high nutritional requirements and nutrient malabsorption. The aim of this study was to evaluate the association between nutritional status and blood biomarkers in candidates of HSCT.

METHODS

A total of 278 patients aged 18-65 years old were recruited and their baseline demographic and clinical characteristics were recorded. All subjects underwent nutritional status analysis using Nutritional Risk Screening (NRS-2002). Blood biomarkers including C-reactive protein (CRP), Erythrocyte Sedimentation Rate (ESR), hemoglobin, albumin and total protein as well as CRP-albumin ratio (CAR) and Body Mass Index (BMI) were measured and compared between two groups based on Nutritional Risk Screening (NRS-2002) within 24 h of admission in Bone Marrow Transplant ward.

RESULTS

The results showed that undernourished patients (NRS ≥ 3) had significantly higher inflammatory markers including ESR, CRP and CAR as well as lower BMI and serum albumin and hemoglobin concentrations (P < 0.05); however, no significant association was observed in terms of total protein even after adjusting for confounders (P > 0.05).

CONCLUSIONS

This study revealed that BMI combined with biochemical markers are the appropriate parameters for assessment of nutritional status in HSCT candidates. Furthermore, the nutritional status was verified to be significantly associated with systematic inflammation.

Blood biomarkers for traumatic brain injury: A narrative review of current evidence

Introduction

A blood-based biomarker (BBBM) test could help to better stratify patients with traumatic brain injury (TBI), reduce unnecessary imaging, to detect and treat secondary insults, predict outcomes, and monitor treatment effects and quality of care.

Research question

What evidence is available for clinical applications of BBBMs in TBI and how to advance this field?

Material and methods

This narrative review discusses the potential clinical applications of core BBBMs in TBI. A literature search in PubMed, Scopus, and ISI Web of Knowledge focused on articles in English with the words "traumatic brain injury" together with the words "blood biomarkers", "diagnostics", "outcome prediction", "extracranial injury" and "assay method" alone-, or in combination.

Results

Glial fibrillary acidic protein (GFAP) combined with Ubiquitin C-terminal hydrolase-L1(UCH-L1) has received FDA clearance to aid computed tomography (CT)-detection of brain lesions in mild (m) TBI. Application of S100B led to reduction of head CT scans. GFAP may also predict magnetic resonance imaging (MRI) abnormalities in CT-negative cases of TBI. Further, UCH-L1, S100B, Neurofilament light (NF-L), and total tau showed value for predicting mortality or unfavourable outcome. Nevertheless, biomarkers have less role in outcome prediction in mTBI. S100B could serve as a tool in the multimodality monitoring of patients in the neurointensive care unit.

Discussion and conclusion

Largescale systematic studies are required to explore the kinetics of BBBMs and their use in multiple clinical groups. Assay development/cross validation should advance the generalizability of those results which implicated GFAP, S100B and NF-L as most promising biomarkers in the diagnostics of TBI.

Protein profiling in plasma for biomarkers of seizure

PURPOSE

A biochemical way to measure seizures would greatly benefit epilepsy research and clinical follow-up. Short-term biomarkers like lactate exist, and interest in biomarkers representative of longer-term seizure burden is growing. In this exploratory study, we aimed to identify markers in blood plasma that differentiate persons with recent seizures from persons with epilepsy and long-standing seizure freedom.

METHODS

A proteomic analysis was performed on plasma samples of 120 persons with seizures using the Olink Neuro-exploratory panel. Participants were selected from a regional biobank study in Västra Götaland (Sweden) and categorized into two groups: recent seizure and seizure-free. The panel contained 92 proteins linked to neurological diseases and processes, and levels of these proteins were compared between the patient groups to identify potential markers of seizure activity.

RESULTS

We identified significant differences in protein levels between the recent seizure and seizure-free patient groups for Cadherin-15 [(CDH15; p = 0.008)], Latent transforming growth factor beta-binding protein 3 [(LTBP3; p = 0.002)], Phosphoethanolamine/phosphocholine phosphatase 1 [(PHOSPHO1; p = 0.011)], and Progestagen associated endometrial protein [(PAEP; p = 0.0005)].

CONCLUSION

The findings in this study present CDH15, LTBP3, PHOSPHO1 and PAEP as candidate markers of seizure activity. Further confirmatory studies are needed.

Mitigation of Imidacloprid Toxicity in Poultry Chicken by Selenium Nanoparticles: Growth Performance, Lipid Peroxidation, and Blood Traits

Imidacloprid is an insecticide that protects against insects in the agriculture, animal, and poultry production sectors. Since the accumulation of imidacloprid induces adverse impacts on general health status and quality of the food chain, this study tested the impacts on broilers. Besides, selenium nanoparticles were fed to birds to relieve the negative impacts on growth performance and health status. Birds (1-day age, initial weight 46.05 ± 1.0 g) divided into four groups (triplicates) where 15 chicks of each replicate (45 for each group). The first group (control) was fed the basal diet without either selenium or imidacloprid toxicity. The second group was fed selenium nano form at 3 mg/kg. The third group was fed selenium and exposed to imidacloprid at 1/10 LT50 (3 mg/kg body weight). The fourth group was fed selenium nano form (3 mg/kg) and exposed to imidacloprid at 1/10 LT50 (3 mg/kg body weight). All groups were kept under the same conditions for 35 days. The final weight and weight gain of birds fed selenium nano form showed marked improvement compared to the imidacloprid-exposed group, while the feed intake and feed conversion ratio markedly reduced. The red blood cells showed higher values in birds fed selenium nano than the control and those exposed to imidacloprid. Interestingly, the hemoglobulin and hematocrit increased in birds fed selenium nano form with or without imidacloprid exposure. Furthermore, the white blood cells increased in birds fed selenium nano form with or without imidacloprid exposure. The total protein, albumin, and globulin were higher in birds fed selenium nanoparticles than those exposed to imidacloprid with or without selenium feeding. Birds in the control and imidacloprid groups had higher aspartate aminotransferase (AST), alanine aminotransferase (ALT), and malondialdehyde levels than the remaining groups. Accordingly, dietary selenium nanoparticles are suggested in broiler feed to cope with the adverse effects of imidacloprid toxicity.

PlateletSeq: A novel method for discovery of blood-based biomarkers

Platelets are small circulating fragments of cells that play important roles in thrombosis, haemostasis, immune response, inflammation and cancer growth. Although anucleate, they contain a rich RNA repertoire which offers an opportunity to characterise changes in platelet gene expression in health and disease. Whilst this can be achieved with conventional RNA sequencing, a large input of high-quality RNA, and hence blood volume, is required (unless a pre-amplification step is added), along with specialist bioinformatic skills for data analysis and interpretation. We have developed a transcriptomics next-generation sequencing-based approach that overcomes these limitations. Termed PlateletSeq, this method requires very low levels of RNA input and does not require specialist bioinformatic analytical skills. Here we describe the methodology, from sample collection to processing and data analysis. Specifically, blood samples can be stored for up to 8 days at 4 °C prior to analysis. Platelets are isolated using multi-step centrifugation and a purity of ≤ 1 leucocyte per 0.26x106 platelets is optimal for gene expression analysis. We have applied PlateletSeq to normal adult blood samples and show there are no age-associated variations and only minor gender-associated differences. In contrast, platelets from patients with myeloproliferative neoplasms show differences in platelet transcript profiles from normal and between disease subtypes. This illustrates the potential applicability of PlateletSeq for biomarker discovery and studying platelet biology in patient samples. It also opens avenues for assessing platelet quality in other fields such as transfusion research.

Pan-immune-inflammation and its dynamics: predictors of survival and immune-related adverse events in patients with advanced NSCLC receiving immunotherapy

OBJECTIVES

Pan-immune-inflammation value (PIV) is defined by the neutrophil, platelet, monocyte, and lymphocyte counts and is associated with immune-checkpoint inhibitor (ICI) therapy outcomes in advanced non-small cell lung cancer (aNSCLC). However, PIV is dynamic under therapy and its longitudinal assessment may help predict efficacy. This study investigated the impact of baseline PIV and its dynamics on ICI efficacy and its immune-related adverse events (irAEs). The study additionally attempted to understand the biological significance of PIV.

PATIENTS AND METHODS

This retrospective study analyzed the clinical data of 269 consecutive patients with aNSCLC. PIV was calculated at baseline and at weeks 3-4 to determine its association with overall survival (OS), progression-free survival (PFS), and irAEs.

RESULTS

Results revealed that low baseline PIV was positively correlated with the incidence of irAEs. Moreover, a low PIV at baseline was significantly associated with a prolonged PFS (median PFS: 10 vs. 7 months, p = 0.0005) and OS (median OS: 29 vs. 21 months, p < 0.0001). When the PIV at baseline and weeks 3-4 was considered together, its low dynamics correlated with a higher incidence of irAEs (p = 0.001), a longer PFS (median PFS, 9 vs. 6 months, p = 0.012), and a longer OS (median OS; 28 vs. 21 months, p = 0.002).

CONCLUSION

Thus, PIV at baseline and its dynamics are novel and potent predictors of irAEs, PFS, and OS in patients with aNSCLC receiving immunotherapy. Moreover, the PIV dynamics may be an effective, novel surrogate marker to dynamically observe the efficacy of immunotherapy.

The association of circulating endocannabinoids with neuroimaging and blood biomarkers of neuro-injury

BACKGROUND

Preclinical studies highlight the importance of endogenous cannabinoids (endocannabinoids; eCBs) in neurodegeneration. Yet, prior observational studies focused on limited outcome measures and assessed only few eCB compounds while largely ignoring the complexity of the eCB system. We examined the associations of multiple circulating eCBs and eCB-like molecules with early markers of neurodegeneration and neuro-injury and tested for effect modification by sex.

METHODS

This exploratory cross-sectional study included a random sample of 237 dementia-free older participants from the Framingham Heart Study Offspring cohort who attended examination cycle 9 (2011-2014), were 65 years or older, and cognitively healthy. Forty-four eCB compounds were quantified in serum, via liquid chromatography high-resolution mass spectrometry. Linear regression models were used to examine the associations of eCB levels with brain MRI measures (i.e., total cerebral brain volume, gray matter volume, hippocampal volume, and white matter hyperintensities volume) and blood biomarkers of Alzheimer's disease and neuro-injury (i.e., total tau, neurofilament light, glial fibrillary acidic protein and Ubiquitin C-terminal hydrolase L1). All models were adjusted for potential confounders and effect modification by sex was examined.

RESULTS

Participants mean age was 73.3 ± 6.2 years, and 40% were men. After adjustment for potential confounders and correction for multiple comparisons, no statistically significant associations were observed between eCB levels and the study outcomes. However, we identified multiple sex-specific associations between eCB levels and the various study outcomes. For example, high linoleoyl ethanolamide (LEA) levels were related to decreased hippocampal volume among men and to increased hippocampal volume among women (β ± SE =  - 0.12 ± 0.06, p = 0.034 and β ± SE = 0.08 ± 0.04, p = 0.026, respectively).

CONCLUSIONS

Circulating eCBs may play a role in neuro-injury and may explain sex differences in susceptibility to accelerated brain aging. Particularly, our results highlight the possible involvement of eCBs from the N-acyl amino acids and fatty acid ethanolamide classes and suggest specific novel fatty acid compounds that may be implicated in brain aging. Furthermore, investigation of the eCBs contribution to neurodegenerative disease such as Alzheimer's disease in humans is warranted, especially with prospective study designs and among diverse populations, including premenopausal women.

Neuropsychiatric Symptoms are Related to Blood-biomarkers in Major Neurocognitive Disorders

BACKGROUND

Neuropsychiatric symptoms (NPS) are highly prevalent among individuals with major neurocognitive disorders (MNCD).

OBJECTIVE

Here, we characterized blood biomarkers (metabolic, inflammatory, neurotrophic profiles and total antioxidant), body composition, physical fitness and quality of life (QoL) in individuals with MNCD according to NPS.

METHODS

The sample comprised 34 older adults (71.4% women; 74.06±6.03 yrs, with MNCD diagnosis) categorized according to 50th percentile [Low (≤12) or High (≥13)] for NPS (Neuropsychiatric Inventory Questionnaire). Sociodemographic, clinical data, body composition, anthropometric, cognitive assessment (ADAS-Cog), physical fitness (Senior Fitness Test), QoL (QoL-Alzheimer's Disease scale) were evaluated, and blood samples were collected for biochemical analysis.

RESULTS

Low compared to high NPS group showed higher levels of IL-6, IGF-1and neurotrophic zscore (composite of IGF-1, VEGF-1, BDNF). Additionally, low compared to high NPS group have higher QoL, aerobic fitness and upper body and lower body strength.

CONCLUSION

The severity of NPS seems to be related to modified neurotrophic and inflammatory outcomes, lower physical fitness, and poor QoL. Strategies to counteract NPS development may preserve the physical and mental health of individuals with MNCD.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers

BACKGROUND

A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling.

METHODS

We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined).

RESULTS

Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models.

CONCLUSION

This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

[Identification of Peripheral Blood GZMK + CD8 + T Cells As Biomarkers of Alzheimer's Disease Based on Single-Cell Transcriptome]

Objective

Based on single-cell RNA sequencing (scRNA-seq) to explore immune characteristics in the peripheral blood of patients with Alzheimer's disease (AD) as biomarkers.

Methods

GSE168522, the scRNA-seq dataset of AD peripheral blood immune cells, was downloaded from the Gene Expression Omnibus (GEO) database and was analyzed in the RAD-Blood web server (http://www.bioinform.cn/RAD-Blood/). The changes in blood cell composition in AD patients were analyzed. The abnormal communications between different types of cells in AD patients were investigated by the CellChat R package.

Results

There were two kinds of CD8 + T cells in the blood of AD patients and healthy individuals, one of which highly expressed granzyme K ( GZMK) (false discovery rate [FDR]<0.05), and the other highly expressed GZMA, GZMB, and GZMH (FDR<0.05). In the blood of AD patients, the content of GZMK + CD8 + T cells was increased by 32.9% ( P=5.15E-21), their interactions with other cell types were increased, and they might be associated with AD through the abnormal signal transduction of major histocompatibility complex class Ⅰ (MHC-Ⅰ). Erythrocyte provided the main ligands, that are, human leukocyte antigen (HLA) class Ⅰ molecules, including HLA- A, HLA- B, HLA- C, and HLA- E, for the abnormal MHC-Ⅰ signaling pathway of GZMK + CD8 + T cells. The RESISTIN signaling pathway was specifically enriched in the blood of AD patients.

Conclusion

The increased content of peripheral blood GZMK + CD8 + T cells, the increased interaction between GZMK + CD8 + T cells and erythrocytes, and the enhanced RESISTIN pathway are potential blood biomarkers of AD.

Hippocampal subfield abnormalities and biomarkers of pathologic brain changes: from SARS-CoV-2 acute infection to post-COVID syndrome

BACKGROUND

Cognitive deficits are among the main disabling symptoms in COVID-19 patients and post-COVID syndrome (PCS). Within brain regions, the hippocampus, a key region for cognition, has shown vulnerability to SARS-CoV-2 infection. Therefore, in vivo detailed evaluation of hippocampal changes in PCS patients, validated on post-mortem samples of COVID-19 patients at the acute phase, would shed light into the relationship between COVID-19 and cognition.

METHODS

Hippocampal subfields volume, microstructure, and perfusion were evaluated in 84 PCS patients and compared to 33 controls. Associations with blood biomarkers, including glial fibrillary acidic protein (GFAP), myelin oligodendrocyte glycoprotein (MOG), eotaxin-1 (CCL11) and neurofilament light chain (NfL) were evaluated. Besides, biomarker immunodetection in seven hippocampal necropsies of patients at the acute phase were contrasted against eight controls.

FINDINGS

In vivo analyses revealed that hippocampal grey matter atrophy is accompanied by altered microstructural integrity, hypoperfusion, and functional connectivity changes in PCS patients. Hippocampal structural and functional alterations were related to cognitive dysfunction, particularly attention and memory. GFAP, MOG, CCL11 and NfL biomarkers revealed alterations in PCS, and showed associations with hippocampal volume changes, in selective hippocampal subfields. Moreover, post mortem histology showed the presence of increased GFAP and CCL11 and reduced MOG concentrations in the hippocampus in post-mortem samples at the acute phase.

INTERPRETATION

The current results evidenced that PCS patients with cognitive sequalae present brain alterations related to cognitive dysfunction, accompanied by a cascade of pathological alterations in blood biomarkers, indicating axonal damage, astrocyte alterations, neuronal injury, and myelin changes that are already present from the acute phase.

FUNDING

Nominative Grant FIBHCSC 2020 COVID-19. Department of Health, Community of Madrid. Instituto de Salud Carlos III through the project INT20/00079, co-funded by European Regional Development Fund "A way to make Europe" (JAMG). Instituto de Salud Carlos III (ISCIII) through Sara Borrell postdoctoral fellowship Grant No. CD22/00043) and co-funded by the European Union (MDC). Instituto de Salud Carlos III through a predoctoral contract (FI20/000145) (co-funded by European Regional Development Fund "A way to make Europe") (MVS). Fundación para el Conocimiento Madri+d through the project G63-HEALTHSTARPLUS-HSP4 (JAMG, SOM).

Cognitive Activity Is Associated with Cognitive Function over Time in a Diverse Group of Older Adults, Independent of Baseline Biomarkers

BACKGROUND

More frequent engagement in cognitive activity is associated with better cognitive function in older adults, but the mechanism of action is not fully understood. Debate remains whether increased cognitive activity provides a meaningful benefit for cognitive health or if decreased cognitive activity represents a prodrome of cognitive impairment. Neurological biomarkers provide a novel way to examine this relationship in the context of cognitive aging.

METHODS

We examined the association of self-reported cognitive activity, cognitive function, and concentrations of three biomarkers in community-dwelling participants of a longitudinal, population-based study. Cognitive activity was measured at baseline by asking participants to rate the frequency of 7 activities: (1) viewing television, (2) listening to the radio, (3) visiting a museum, (4) playing games, such as cards, checkers, crosswords, or other puzzles or games, (5) reading books, (6) reading magazines, and (7) reading newspapers. Cognitive function was measured with a battery of four tests (Mini-Mental State Examination, Digit Symbol Test, and the immediate and delayed recall of the East Boston Test) averaged into a composite score. At baseline, we evaluated the concentration of total tau (tau), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP).

RESULTS

The study sample comprised 1,168 older participants, primarily non-Hispanic Blacks (60%) and women (63%). At baseline, they were an average of 77 years old with 12.6 years of education. Mixed-effects models showed that cognitive activity was associated with better cognitive functioning at baseline and over time. These relationships remained after each biomarker was added to the model. Over an average of 6.4 years of follow-up, cognitive activity was associated with cognitive decline in the model with tau (estimate = 0.0123; p value = 0.03) and was mildly attenuated in the models with NfL (estimate = 0.0110; p value = 0.06) and GFAP (estimate = 0.0111; p value = 0.06). Biomarkers did not modify the association between cognitive activity and cognitive function over time.

CONCLUSION

The benefits of cognitive activity on cognition appear to be independent of biomarkers: tau, NfL, and GFAP, measured at baseline. More frequent cognitive activity may benefit the cognitive health of older adults with a wide range of potential disease risk and presentations.

Head-to-head comparison of plasma p-tau181, p-tau231 and glial fibrillary acidic protein in clinically unimpaired elderly with three levels of APOE4-related risk for Alzheimer's disease

Plasma phosphorylated tau (p-tau) and glial fibrillary acidic protein (GFAP) both reflect early changes in Alzheimer's disease (AD) pathology. Here, we compared the biomarker levels and their association with regional β-amyloid (Aβ) pathology and cognitive performance head-to-head in clinically unimpaired elderly (n = 88) at three levels of APOE4-related genetic risk for sporadic AD (APOE4/4 n = 19, APOE3/4 n = 32 or non-carriers n = 37). Concentrations of plasma p-tau181, p-tau231 and GFAP were measured using Single molecule array (Simoa), regional Aβ deposition with ¹¹C-PiB positron emission tomography (PET), and cognitive performance with a preclinical composite. Significant differences in plasma p-tau181 and p-tau231, but not plasma GFAP concentrations were present between the APOE4 gene doses, explained solely by brain Aβ load. All plasma biomarkers correlated positively with Aβ PET in the total study population. This correlation was driven by APOE3/3 carriers for plasma p-tau markers and APOE4/4 carriers for plasma GFAP. Voxel-wise associations with amyloid-PET revealed different spatial patterns for plasma p-tau markers and plasma GFAP. Only higher plasma GFAP correlated with lower cognitive scores. Our observations suggest that plasma p-tau and plasma GFAP are both early AD markers reflecting different Aβ-related processes.

Blood Biomarkers in the Fetally Growth Restricted and Small for Gestational Age Neonate: Associations with Brain Injury

Fetal growth restriction (FGR) and small for gestational age (SGA) infants have increased risk of mortality and morbidity. Although both FGR and SGA infants have low birthweights for gestational age, a diagnosis of FGR also requires assessments of umbilical artery Doppler, physiological determinants, neonatal features of malnutrition, and in utero growth retardation. Both FGR and SGA are associated with adverse neurodevelopmental outcomes ranging from learning and behavioral difficulties to cerebral palsy. Up to 50% of FGR, newborns are not diagnosed until around the time of birth, yet this diagnosis lacks further indication of the risk of brain injury or adverse neurodevelopmental outcomes. Blood biomarkers may be a promising tool. Defining blood biomarkers indicating an infant's risk of brain injury would provide the opportunity for early detection and therefore earlier support. The aim of this review was to summarize the current literature to assist in guiding the future direction for the early detection of adverse brain outcomes in FGR and SGA neonates. The studies investigated potential diagnostic blood biomarkers from cord and neonatal blood or serum from FGR and SGA human neonates. Results were often conflicting with heterogeneity common in the biomarkers examined, timepoints, gestational age, and definitions of FGR and SGA used. Due to these variations, it was difficult to draw strong conclusions from the results. The search for blood biomarkers of brain injury in FGR and SGA neonates should continue as early detection and intervention is critical to improve outcomes for these neonates.

Blood Biomarkers for Healthy Aging

Measuring the abundance of biological molecules and their chemical modifications in blood and tissues has been the cornerstone of research and medical diagnoses for decades. Although the number and variety of molecules that can be measured have expanded exponentially, the blood biomarkers routinely assessed in medical practice remain limited to a few dozen, which have not substantially changed over the last 30-40 years. The discovery of novel biomarkers would allow, for example, risk stratification or monitoring of disease progression or the effectiveness of treatments and interventions, improving clinical practice in myriad ways. In this review, we combine the biomarker discovery concept with geroscience. Geroscience bridges aging research and translation to clinical applications by combining the framework of medical gerontology with high-technology medical research. With the development of geroscience and the rise of blood biomarkers, there has been a paradigm shift from disease prevention and cure to promoting health and healthy aging. New -omic technologies have played a role in the development of blood biomarkers, including epigenetic, proteomic, metabolomic, and lipidomic markers, which have emerged as correlates or predictors of health status, from disease to exceptional health.

Seasonal Biodistribution of Some Trace Elements (Cd, Pb, Cr, Hg) and "Blood Biomarkers" Response in Mugil cephalus (Linnaeus, 1758)

This study had a purpose to evaluate the seasonal biodistribution of some trace elements (cadmium, Cd; Lead, Pb; chrome, Cr; and mercury, Hg) in different tissues (muscle, gills, liver, stomach, and intestine) of striped mullet Mugil cephalus (Linnaeus, 1758) and the hematological and biochemical responses of this species to aquatic pollution by trace metals. For this purpose, 80 M. cephalus (20 for each season) were captured in three different stations of Faro Lake, Messina, Sicily. Biometric indices (weight, fork length, and total length) of each fish were registered. The physico-chemical parameters of the water of the study area were also measured, and the content of trace elements in water and sediment was determined. The hematological (white blood cell, WBC; red blood cell, RBC; hemoglobin concentration, Hb; hematocrit, Hct; mean corpuscular volume, MCV; mean corpuscular hemoglobin, MCH; mean corpuscular hemoglobin concentration, MCHC; thrombocytes count, TC), biochemical parameters (aspartate aminotransferase, AST; alanine aminotransferase, ALT; alkaline phosphatase, ALP; lactate dehydrogenase, LDH), and the seasonal concentration of the trace elements in the different tissues of M. cephalus were assessed. Our results showed a different biodistribution of the trace elements in M. cephalus and significant variations of the blood parameters in the different seasons. This research provides a valid contribute to environmental biomonitoring techniques useful in aquatic pollution control and water management. It also contributes to broadening the studies on the improvement of the health and sustainability of aquatic environments.

Whole blood transcript and protein abundance of the vascular endothelial growth factor family relate to cognitive performance

The vascular endothelial growth factor (VEGF) family of genes has been implicated in the clinical development of Alzheimer's Disease (AD). A previous study identified associations between gene expression of VEGF family members in the prefrontal cortex and cognitive performance and AD pathology. This study explored if those associations were also observed in the blood. Consistent with previous observations in brain tissue, higher blood gene expression of placental growth factor (PGF) was associated with a faster rate of memory decline (p=0.04). Higher protein abundance of FMS-related receptor tyrosine kinase 4 (FLT4) in blood was associated with biomarker levels indicative of lower amyloid and tau pathology, opposite the direction observed in brain. Also, higher gene expression of VEGFB in blood was associated with better baseline memory (p=0.008). Notably, we observed that higher gene expression of VEGFB in blood was associated with lower expression of VEGFB in the brain (r=-0.19, p=0.02). Together, these results suggest that the VEGFB, FLT4, and PGF alterations in the AD brain may be detectable in the blood compartment.

Neutrophil-to-leukocyte ratio and admission glycemia as predictors of short-term death in very old elderlies with lobar intracerebral hemorrhage

BACKGROUND

The incidence of spontaneous intracerebral hemorrhage (SICH) is highest in very old elderlies (≥75 years). The increasing use of antithrombotic drugs is shifting the epidemiology of SICH towards predominance of lobar subtype, suggesting an incremented propensity of bleeding associated with underlying cerebral amyloid angiopathy. With population aging and antithrombotic use, a parallel raise of proportion of lobar SICH is occurring. Improvement of prognostication in this specific age group and SICH type is needed. Routine blood biomarkers can contribute to prediction of short-term mortality after SICH.

OBJECTIVE

Our aim was to investigate the contribution of routine blood biomarkers for short-term mortality (30-days) in elderly patients with lobar SICH.

METHODS

Retrospective analysis of consecutive 130 patients with ≥ 75 years and lobar SICH. The outcome was 30-day mortality. Logistic regression analysis was used to investigate whether admission routine biomarkers can be used as predictors.

RESULTS

The case fatality was 40.8%. Admission glycaemia level, neutrophil to lymphocyte ratio and mean platelet volume were significantly different between groups (p = 0.001, p = 0.024, p = 0.038, respectively). There was no significant difference in all other routine biomarkers. On multivariate analysis, admission higher mean BG level (odds ratio [OR]: 1.010, 95% confidence interval [CI]: 1.001-1.019, p = 0.026) and neutrophil to lymphocyte ratio (OR: 1.070, 95% CI: 1.008-1.136, p = 0.027) emerged as predictors.

CONCLUSION

In very old patients with lobar SICH, higher BG level and neutrophil to lymphocyte ratio are associated with increased risk of short-term death.

Blood biomarkers predict outcomes in patients with hepatocellular carcinoma treated with immune checkpoint Inhibitors: A pooled analysis of 44 retrospective sudies

OBJECTIVE

We conducted the first meta-analysis to identify the predictive significance of baseline blood biomarkers (such as neutrophil to lymphocyte ratio (NLR), early alpha-fetoprotein (AFP) response, albumin-bilirubin (ALBI), AFP, platelet to lymphocyte ratio (PLR), C-reactive protein (CRP), protein induced by vitamin K absence II (PIVKA-II), and lymphocyte to monocyte ratio (LMR)) in hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitors (ICIs).

METHODS

Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by November 24, 2022. Clinical outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and hyperprogressive disease (HPD).

RESULTS

A total of 44 articles with 5322 patients were included in this meta-analysis. The pooled results demonstrated that patients with high NLR levels had significantly poorer OS (HR: 1.951, P < 0.001) and PFS (HR: 1.632, P < 0.001), lower ORR (OR: 0.484, P < 0.001) and DCR (OR: 0.494, P = 0.027), and higher HPD (OR: 8.190, P < 0.001). The patients with high AFP levels had shorter OS (HR: 1.689, P < 0.001) and PFS (HR: 1.380, P < 0.001), and lower DCR (OR: 0.440, P < 0.001) than those with low AFP levels, however, there was no difference in ORR (OR: 0.963, P = 0.933). We also found that early AFP response was correlated with better OS (HR: 0.422, P < 0.001) and PFS (HR: 0.385, P < 0.001), higher ORR (OR: 7.297, P < 0.001) and DCR (OR: 13.360, P < 0.001) compared to non-responders. Besides, a high ALBI grade was significantly related to shorter OS (HR: 2.440, P = 0.009) and PFS (HR: 1.373, P = 0.022), lower ORR (OR: 0.618, P = 0.032) and DCR (OR: 0.672, P = 0.049) than those with an ALBI grade 1.

CONCLUSION

The NLR, early AFP response, and ALBI were useful predictors of outcomes in HCC patients treated with ICIs.

Identifying blood biomarkers for type 2 diabetes subtyping: a report from the ORIGIN trial

AIMS/HYPOTHESIS

Individuals with diabetes can be clustered into five subtypes using up to six routinely measured clinical variables. We hypothesised that circulating protein levels might be used to distinguish between these subtypes. We recently used five of these six variables to categorise 7017 participants from the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial into these subtypes: severe autoimmune diabetes (SAID, n=241), severe insulin-deficient diabetes (SIDD, n=1594), severe insulin-resistant diabetes (SIRD, n=914), mild obesity-related diabetes (MOD, n=1595) and mild age-related diabetes (MARD, n=2673).

METHODS

Forward-selection logistic regression models were used to identify a subset of 233 cardiometabolic protein biomarkers that were independent determinants of one subtype vs the others. We then assessed the performance of adding identified biomarkers (one after one, from the most discriminant to the least) to predict each subtype vs the others using area under the receiver operating characteristic curve (AUC ROC). Models were adjusted for age, sex, ethnicity, C-peptide level, diabetes duration and glucose-lowering medication usage at blood collection.

RESULTS

A total of 25 biomarkers were independent determinants of subtypes, including 13 for SIDD, 2 for SIRD, 7 for MOD and 11 for MARD (all p<4.3 × 10^-5). The performance of the biomarker sets (comprising 1 to 25 biomarkers), assessed through the AUC ROC, ranged from 0.611 to 0.734, 0.723 to 0.861, 0.672 to 0.742, and 0.651 to 0.751, for SIDD, SIRD, MOD and MARD, respectively. No biomarkers other than GAD antibodies were determinants of SAID.

CONCLUSIONS/INTERPRETATION

We identified 25 serum biomarkers, as independent determinants of type 2 diabetes subtypes, that could be combined into a diagnostic test for subtyping.

TRIAL REGISTRATION

ORIGIN trial, ClinicalTrials.gov NCT00069784.

Modeling biological age using blood biomarkers and physical measurements in Chinese adults

BACKGROUND

This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum.

METHODS

The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004-08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI).

FINDINGS

The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (-0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019).

INTERPRETATION

In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade.

FUNDING

This work was supported by National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01).

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Circulating micro-RNAs Differentially Expressed in Korean Alzheimer's Patients With Brain Aβ Accumulation Activate Amyloidogenesis

BACKGROUND

Roles for extracellular vesicles (EVs) enriched with micro-RNAs (miRNAs) have been proposed in Alzheimer's disease (AD) pathogenesis, leading to the discovery of blood miRNAs as AD biomarkers. However, the diagnostic utility of specific miRNAs is not consistent. This study aimed to discover blood miRNAs that are differentially expressed in Korean AD patients, evaluate their clinical performance, and investigate their role in amyloidogenesis.

METHODS

We discovered miRNAs differentially expressed in AD (N = 8) from cognitively normal participants (CN, N = 7) or Parkinson's disease (PD) patients (N = 8). We evaluated the clinical performance of these miRNAs in plasma of subgroup (N = 99) and in plasma EVs isolated from the total cohort (N = 251). The effects of miRNAs on amyloidogenesis and on the regulation of their target genes were investigated in vitro.

RESULTS

Among 17 upregulated and one downregulated miRNAs in AD (>twofold), miR-122-5p, miR-210-3p, and miR-590-5p were differentially expressed compared with CN or PD. However, the diagnostic performance of the selected plasma or EV miRNAs in total participants were limited (area under the curve < 0.8). Nevertheless, levels of 3 miRNAs in plasma or plasma EVs of participants who were amyloid positron emission tomography (Aβ-PET) positive were significantly higher than those from the Aβ-PET negative participants (p < .05). The selected miRNAs induced Aβ production (p < .05) through activation of β-cleavage of amyloid precursor protein (CTF-β; p < .01), and downregulated their target genes (ADAM metallopeptidase domain 10, Brain-derived neurotrophic factor, and Jagged canonical notch ligand 1; p < .05), which was further supported by pathway enrichment analysis of target genes of the miRNAs.

CONCLUSION

In conclusion, despite of the limited diagnostic utility of selected miRNAs as plasma or plasma EV biomarkers, the discovered miRNAs may play a role in amyloidogenesis during AD onset and progression.

Improving the Prediction of Death from Cardiovascular Causes with Multiple Risk Markers

Background

Traditional risk factors including demographics, blood pressure, cholesterol, and diabetes status are successfully able to predict a proportion of cardiovascular disease (CVD) events. Whether including additional routinely measured factors improves CVD prediction is unclear. To determine whether a comprehensive risk factor list, including clinical blood measures, blood counts, anthropometric measures, and lifestyle factors, improves prediction of CVD deaths beyond traditional factors.

Methods

The analysis comprised of 21,982 participants aged 40 years and older (mean age=59.4 years at baseline) from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2016 survey cycles. Data were linked with the National Death Index mortality data through 2019 and split into 80:20 training and testing sets. Relative to the traditional risk factors (age, sex, race/ethnicity, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol, antihypertensive medications, and diabetes), we compared models with an additional 22 clinical blood biomarkers, 20 complete blood counts, 7 anthropometric measures, 51 dietary factors, 13 cardiovascular health-related questions, and all 113 predictors together. To build prediction models for CVD mortality, we performed Cox proportional hazards regression, elastic-net (ENET) penalized Cox regression, and random survival forest, and compared classification using C-index and net reclassification improvement.

Results

During follow-up (median, 9.3 years), 3,075 participants died; 30.9% (1,372/3,075) deaths were from cardiovascular causes. In Cox proportional hazards models with traditional risk factors (C-index=0.850), CVD mortality classification improved with incorporation of clinical blood biomarkers (C-index=0.867), blood counts (C-index=0.861), and all predictors (C-index=0.871). Net CVD mortality reclassification improved 13.2% by adding clinical blood biomarkers and 12.2% by adding all predictors. Results for ENET-penalized Cox regression and random survival forest were similar. No improvement was observed in separate models for anthropometric measures, dietary nutrient intake, or cardiovascular health-related questions.

Conclusions

The addition of clinical blood biomarkers and blood counts substantially improves CVD mortality prediction, beyond traditional risk factors. These biomarkers may serve as an important clinical and public health screening tool for the prevention of CVD deaths.

Clinical performance of an antibody-free assay for plasma Aβ42/Aβ40 to detect early alterations of Alzheimer's disease in individuals with subjective cognitive decline

BACKGROUND

Accessible and cost-effective diagnostic tools are urgently needed to accurately quantify blood biomarkers to support early diagnosis of Alzheimer's disease (AD). In this study, we investigated the ability of plasma amyloid-beta (Aβ)42/Aβ40 ratio measured by an antibody-free mass-spectrometric (MS) method, ABtest-MS, to detect early pathological changes of AD.

METHODS

This cohort study included data from the baseline and 2-year follow-up visits from the Fundació ACE Healthy Brain Initiative (FACEHBI) study. Plasma Aβ42/Aβ40 was measured with ABtest-MS and compared to ¹⁸F-Florbetaben PET as the reference standard (cutoff for early amyloid deposition of 13.5 centiloids). Cross-validation was performed in an independent DPUK-Korean cohort. Additionally, associations of plasma Aβ42/Aβ40 with episodic memory performance and brain atrophy were assessed.

RESULTS

The FACEHBI cohort at baseline included 200 healthy individuals with subjective cognitive decline (SCD), of which 36 (18%) were Aβ-PET positive. Plasma Aβ42/Aβ40 levels were significantly lower in Aβ-PET positive individuals (median [interquartile range, IQR], 0.215 [0.203-0.236]) versus Aβ-PET negative subjects (median [IQR], 0.261 [0.244-0.279]) (P < .001). Plasma Aβ42/Aβ40 was significantly correlated with Aβ-PET levels (rho = -0.390; P < .001) and identified Aβ-PET status with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI], 0.80-0.93). A cutoff for the Aβ42/Aβ40 ratio of 0.241 (maximum Youden index) yielded a sensitivity of 86.1% and a specificity of 80.5%. These findings were cross-validated in an independent DPUK-Korean cohort (AUC 0.86 [95% CI 0.77-0.95]). Lower plasma Aβ42/Aβ40 ratio was associated with worse episodic memory performance and increased brain atrophy. Plasma Aβ42/Aβ40 at baseline predicted clinical conversion to mild cognitive impairment and longitudinal changes in amyloid deposition and brain atrophy at 2-year follow-up.

CONCLUSIONS

This study suggests that plasma Aβ42/Aβ40, as determined by this MS-based assay, has potential value as an accurate and cost-effective tool to identify individuals in the earliest stages of AD, supporting its implementation in clinical trials, preventative strategies and clinical practice.

Cognitive assessment in patients treated by immunotherapy: the prospective Cog-Immuno trial

BACKGROUND

The discovery of the importance of the immune system and its role in oncogenesis led to the development of immunotherapy, a treatment that represents a major advance in oncology management. Due to the recent nature of immunotherapy, little is known about its side effects and their impact on quality of life. To date, there is no published study that accurately assesses the impact of immunotherapy on cognition, mood and/or fatigue in patients treated for cancer, despite potential neurological toxicities. The purpose of this study is to prospectively assess the incidence of cognitive impairment and cognitive complaints among cancer patients naïve for immunotherapy without concomitant anti-cancer treatment.

METHODS

The Cog-Immuno trial is a multicentre longitudinal study addressing patients with cancer candidate to receive immunotherapy alone (n = 100). Immunotherapy treatment will include either anti-PD1/PDL1 or anti-CTLA4 monotherapy or combination therapy. Cognitive and quality of life assessment, electrocardiogram (ECG) and biological tests will be performed at baseline, thereafter 3, and 6 months after immunotherapy initiation. The primary endpoint is the proportion of patients treated by immunotherapy who will experience a decline in cognitive performances or in Montreal Cognitive Assessment (MoCA) score within 3 months after inclusion. Secondary endpoints concern: anxiety, depression, fatigue, clinical characteristics, biological data and neurophysiological measures (heart rate variability and hemispheric lateralization). A pre-clinical study will be conducted in cancer bearing mice receiving checkpoint inhibitors (ICI) with the evaluation of cognitive functions and emotional reactivity, collection of blood samples and investigation of neurobiological mechanisms from brain slices.

DISCUSSION

Assessing and understanding the incidence and the severity of cognitive impairment and its impact on quality of life in cancer patients treated by immunotherapy is a major issue. The results of this study will provide information on the impact of these treatments on cognitive functions in order to help the physicians in the choice of the treatment.

TRIAL REGISTRATION

NCT03599830, registered July 26, 2018.

PROTOCOL VERSION

Version 5.1 dated from 2020/10/02.

The Preventing Alzheimer's with Cognitive Training (PACT) randomized clinical trial

BACKGROUND

To address the rising prevalence of Alzheimer's disease and related dementias, effective interventions that can be widely disseminated are warranted. The Preventing Alzheimer's with Cognitive Training study (PACT) investigates a commercially available computerized cognitive training program targeting improved Useful Field of View Training (UFOVT) performance. The primary goal is to test the effectiveness of UFOVT to reduce incidence of clinically defined mild cognitive impairment (MCI) or dementia with a secondary objective to examine if effects are moderated by plasma β-amyloid level or apolipoprotein E e4 (APOE e4) allele status.

METHODS/DESIGN

This multisite study utilizes a randomized, controlled experimental design with blinded assessors and investigators. Individuals who are 65 years of age and older are recruited from the community. Eligible participants who demonstrate intact cognitive status (Montreal Cognitive Assessment score > 25) are randomized and asked to complete 45 sessions of either a commercially available computerized-cognitive training program (UFOVT) or computerized games across 2.5 years. After three years, participants are screened for cognitive decline. For those demonstrating decline or who are part of a random subsample, a comprehensive neuropsychological assessment is completed. Those who perform below a pre-specified level are asked to complete a clinical evaluation, including an MRI, to ascertain clinical diagnosis of normal cognition, MCI, or dementia. Participants are asked to provide blood samples for analyses of Alzheimer's disease related biomarkers.

DISCUSSION

The PACT study addresses the rapidly increasing prevalence of dementia. Computerized cognitive training may provide a non-pharmaceutical option for reducing incidence of MCI or dementia to improve public health.

REGISTRATION

The PACT study is registered at http://Clinicaltrials.govNCT03848312.

Soluble TREM2 and Alzheimer-related biomarker trajectories in the blood of patients with diabetes based on their cognitive status

AIM

We aimed to elucidate the dynamics of blood biomarkers according to the severity of cognitive impairment in patients with type 2 diabetes mellitus (DM) and to identify useful biomarkers for diabetes-related dementia.

METHODS

This was a cross-sectional, nested case-control study of 121 Japanese DM and non-DM patients with different levels of cognitive functioning. We evaluated participants' cognitive functions, blood biomarkers related to Alzheimer's disease, and soluble triggering receptors expressed on myeloid cells 2 (sTREM2). We then compared these biomarkers between the DM and non-DM and across the different cognitive strata.

RESULTS

In all cognitive strata, significantly lower levels of serum sTREM2 were observed in the DM than in the non-DM. We also found that plasma levels of phosphorylated tau (p-tau) increased with increasing levels of cognitive decline in both the DM and non-DM. However, this was accompanied by a decrease in plasma amyloid-β(Aβ42/Aβ40 ratios in non-DM only.

CONCLUSION

This study revealed novel characteristic trajectories of dementia-related blood biomarkers in diabetes-related dementia, suggesting the pathological involvement of molecular cascades initiated by impaired microglial activation. This results in decreased serum sTREM2, followed by tauopathy without substantial amyloid plaques, reflected by plasma p-tau elevation with no decrease in the Aβ42/Aβ40 ratio. Clinical trials (the unique trial number and the name of the registry): UMIN000048032, https://www.umin.ac.jp.

Study in Parkinson's disease of exercise phase 3 (SPARX3): study protocol for a randomized controlled trial

BACKGROUND

To date, no medication has slowed the progression of Parkinson's disease (PD). Preclinical, epidemiological, and experimental data on humans all support many benefits of endurance exercise among persons with PD. The key question is whether there is a definitive additional benefit of exercising at high intensity, in terms of slowing disease progression, beyond the well-documented benefit of endurance training on a treadmill for fitness, gait, and functional mobility. This study will determine the efficacy of high-intensity endurance exercise as first-line therapy for persons diagnosed with PD within 3 years, and untreated with symptomatic therapy at baseline.

METHODS

This is a multicenter, randomized, evaluator-blinded study of endurance exercise training. The exercise intervention will be delivered by treadmill at 2 doses over 18 months: moderate intensity (4 days/week for 30 min per session at 60-65% maximum heart rate) and high intensity (4 days/week for 30 min per session at 80-85% maximum heart rate). We will randomize 370 participants and follow them at multiple time points for 24 months. The primary outcome is the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor score (Part III) with the primary analysis assessing the change in MDS-UPDRS motor score (Part III) over 12 months, or until initiation of symptomatic antiparkinsonian treatment if before 12 months. Secondary outcomes are striatal dopamine transporter binding, 6-min walk distance, number of daily steps, cognitive function, physical fitness, quality of life, time to initiate dopaminergic medication, circulating levels of C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF). Tertiary outcomes are walking stride length and turning velocity.

DISCUSSION

SPARX3 is a Phase 3 clinical trial designed to determine the efficacy of high-intensity, endurance treadmill exercise to slow the progression of PD as measured by the MDS-UPDRS motor score. Establishing whether high-intensity endurance treadmill exercise can slow the progression of PD would mark a significant breakthrough in treating PD. It would have a meaningful impact on the quality of life of people with PD, their caregivers and public health.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04284436 . Registered on February 25, 2020.

Biomarkers and the quadriceps femoris muscle architecture assessed by ultrasound in older adults with heart failure with preserved ejection fraction: a cross-sectional study

BACKGROUND

Sarcopenia is an important comorbidity in patients with heart failure with preserved ejection fraction (HFpEF). The ultrasound (US) assessment has all the advantages of being used in primary care to assess muscle quantity and quality. Some biomarkers could be indicative of muscle mass loss.

AIMS

To describe the quantitative and qualitative characteristics of the quadriceps femoris assessed by US in older adults with HFpEF and to assess the relationship of the blood and urinary biomarkers, the polypharmacy and comorbidities with US outcomes in older adults with HFpEF.

METHODS

A cross-sectional study was conducted. 76 older adults with HFpEF were included. The quadriceps femoris muscle thickness (MT, cm), the subcutaneous fat tissue thickness (FT, cm), the muscle echo intensity (MEI) and the subcutaneous fat tissue echo intensity (FEI) were assessed by US in a non-contraction (non-con) and contraction (con) situations. Polypharmacy, comorbidities, blood and urine biomarkers were also collected.

RESULTS

The carbohydrate antigen 125 (CA-125), the folic acid and the urine creatinine shared the 86.6% variance in the non-con MT, adjusted by age, sex and body mass index (BMI). The folic acid shared the 38.5% of the variance in the con MT, adjusted by age, sex and BMI. The glycosylated haemoglobin explained the 39.6% variance in the non-con MEI, adjusted by age, sex and BMI. The chlorine (Cl-) explained the 40.2% of the variance in the non-con FT, adjusted by age, sex and BMI. The polypharmacy and the folic acid explained the 37.9% of variance in the non-con FEI, while the polypharmacy and the thyrotropin (TSH) shared the 44.4% of variance in the con FEI, both adjusted by age, sex and BMI. No comorbidities, polypharmacy, or blood and urinary biomarkers could explain the con MEI and the con FT variance.

CONCLUSIONS

Blood and urinary biomarkers obtained in routine analyses could help clinicians detect US outcome changes in older adults with HFpEF and identify a worsening of sarcopenia.

TRIAL REGISTRATION

NCT03909919. April 10, 2019. Retrospectively registered.

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil

Background:

Despite an extensive network of primary care availability, Brazil has suffered profoundly during the COVID-19 pandemic, experiencing the greatest sanitary collapse in its history. Thus, it is important to understand phenotype risk factors for SARS-CoV-2 infection severity in the Brazilian population in order to provide novel insights into the pathogenesis of the disease.

Objective:

This study proposes to predict the risk of COVID-19 death through machine learning, using blood biomarkers data from patients admitted to two large hospitals in Brazil.

Methods:

We retrospectively collected blood biomarkers data in a 24-h time window from 6,979 patients with COVID-19 confirmed by positive RT-PCR admitted to two large hospitals in Brazil, of whom 291 (4.2%) died and 6,688 (95.8%) were discharged. We then developed a large-scale exploration of risk models to predict the probability of COVID-19 severity, finally choosing the best performing model regarding the average AUROC. To improve generalizability, for each model five different testing scenarios were conducted, including two external validations.

Results:

We developed a machine learning-based panel composed of parameters extracted from the complete blood count (lymphocytes, MCV, platelets and RDW), in addition to C-Reactive Protein, which yielded an average AUROC of 0.91 ± 0.01 to predict death by COVID-19 confirmed by positive RT-PCR within a 24-h window.

Conclusion:

Our study suggests that routine laboratory variables could be useful to identify COVID-19 patients under higher risk of death using machine learning. Further studies are needed for validating the model in other populations and contexts, since the natural history of SARS-CoV-2 infection and its consequences on the hematopoietic system and other organs is still quite recent.

Blood-based gene-expression biomarkers identification for the non-invasive diagnosis of Parkinson's disease using two-layer hybrid feature selection

Parkinson's disease (PD) is one of the most prevalent neurodegenerative diseases. Understanding the molecular mechanism and identifying potential biomarkers of PD promote effective treatments to the patients. Due to less invasiveness and easy accessibility, biomarkers from blood support early detection and diagnosis of PD. This study combined three independent PD microarray gene expression data from blood samples applying the early integration approach. Moderated t-statistics was employed to identify differentially expressed genes (DEGs). Relevant genes were selected using a two-layer embedded wrapper feature selection method with gradient boosting machine (GBM) in the first layer followed by an ensemble of wrappers including Recursive Feature Elimination (RFE), Genetic algorithm (GA) and Bi-directional elimination (Stepwise). All three wrappers were based on logistic regression classifier (LR). The PD-predictability of the generated signature was tested using nine supervised classification models, including eight shallow machine learning and one deep learning. On an independent dataset, GSE72267, Support Vector Machine-Radial (SVMR), and Deep Neural Network (DNN) showed the best performance with AUC 0.821 and 0.82, respectively. Comparison with existing blood-based PD signatures and the biological analysis verified the reliability of the proposed signature.

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer's disease

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer’s disease (LOAD) over a relatively short period of time (12–48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

The analysis of dynamic gene expression patterns in peripheral blood of multiple sclerosis patients indicates possible diagnostic and prognostic biomarkers

INTRODUCTION

Among numerous invasive procedures for the research of biomarkers, blood-based indicators are regarded as marginally non-invasive procedures in the diagnosis and prognosis of demyelinating disorders, including multiple sclerosis (MS). In this study, we looked into the blood-derived gene expression profiles of patients with multiple sclerosis to investigate their clinical traits and linked them with dysregulated gene expressions to establish diagnostic and prognostic indicators.

METHODS

We included 51 patients with relapsing-remitting MS (RRMS, n = 31), clinically isolated syndrome (CIS, n = 12), primary progressive MS (PPMS, n = 8) and a control group (n = 51). Using correlational analysis, the transcriptional patterns of chosen gene panels were examined and subsequently related with disease duration and the expanded disease disability score (EDSS). In addition, principal component analysis, univariate regression, and logistic regression analysis were employed to highlight distinct profiles of genes and prognosticate the excellent biomarkers of this illness.

RESULTS

Our findings demonstrated that neurofilament light (NEFL), tumor necrosis factor α (TNF-α), Tau, and clusterin (CLU) were revealed to be increased in recruited patients, whereas the presenilin-1 (PSEN1) and cell-surface glycoprotein-44 (CD44) were downregulated. Principal Component Analysis revealed distinct patterns between the MS and control groups. Correlation analysis indicated co-dependent dysregulated genes and their differential expression with clinical findings. Furthermore, logistic regression demonstrated that Clusterin (AUC=0.940), NEFL (AUC=0.775), TNF-α (AUC=0.817), Tau (AUC=0.749), PSEN1 (AUC=0.6913), and CD44 (AUC=0.832) had diagnostic relevance. Following the univariate linear regression, a significant regression equation was found between EDSS and IGF-1 (R² adj = 0.10844; p= 0.0060), APP (R² adj = 0.1107; p= 0.0098), and PSEN1 (R² adj = 0.1266; p=0.0102).

CONCLUSION

This study exhibits dynamic gene expression patterns that represent the significance of specified genes that are prospective diagnostic and prognostic biomarkers for multiple sclerosis.

Diagnostic value of serum versus plasma phospho-tau for Alzheimer's disease

BACKGROUND

Blood phosphorylated tau (p-tau) forms are promising Alzheimer's disease (AD) biomarkers, but validation in matrices other than ethylenediaminetetraacetic acid (EDTA) plasma is limited. Firstly, we assessed the diagnostic potential of p-tau231 and p-tau181 in paired plasma and serum samples. Secondly, we compared serum and cerebrospinal fluid (CSF) samples from biomarker-positive AD and biomarker-negative control participants.

METHODS

We studied three independent cohorts (n=115 total): cohorts 1 and 2 included individuals with paired plasma and serum, while cohort 3 included paired serum and CSF. Blood-based p-tau231 and p-tau181 were measured using in-house or commercial single molecule array (Simoa) methods.

RESULTS

Serum and plasma p-tau231 and p-tau181 were two- to three-fold increased in biomarker-positive AD versus biomarker-negative controls (P≤0.0008). Serum p-tau231 separated diagnostic groups with area under the curve (AUC) of 82.2% (cohort 3) to 88.2% (cohort 1) compared with 90.2% (cohort 1) for plasma. Similarly, p-tau181 showed AUC of 89.6% (cohort 1) to 89.8% (cohort 3) in serum versus 85.4% in plasma (cohort 1). P-tau231 and p-tau181 correlated slightly better in serum (rho=0.92 for cohort 1, 0.93 for cohort 3) than in plasma (rho=0.88, cohort 1). Within-individual p-tau181 (Quanterix) and p-tau231 concentrations were twice higher in plasma versus serum, but p-tau181 (in-house, Gothenburg) levels were not statistically different. Bland-Altman plots revealed that the relative difference between serum/plasma was larger in the lower range. P-tau levels in paired plasma and serum correlated strongly with each other (rho=0.75-0.93) as well as with CSF Aβ₄₂ (rho= -0.56 to -0.59), p-tau and total-tau (rho=0.53-0.73). Based on the results, it seems possible that serum p-tau reflects the same pool of brain-secreted p-tau as in CSF; we estimated that less than 2% of CSF p-tau is found in serum, being same for both controls and AD.

CONCLUSIONS

Comparable diagnostic performances and strong correlations between serum versus plasma pairs suggest that p-tau analyses can be expanded to research cohorts and hospital systems that prefer serum to other blood matrices. However, absolute biomarker concentrations may not be interchangeable, indicating that plasma and serum samples should be used independently. These results should be validated in independent cohorts.

Protective effects of cinnamon powder against hyperlipidemia and hepatotoxicity in butter fed female albino mice

A butter-enriched high-fat diet changes lipid metabolism, resulting in fat storage, hyperlipidemia and obesity. Effects of cinnamon powder were investigated in butter-fed mice. 40 Swiss Albino mice, aged 28 to 30 days, were randomly assigned into two groups. Group A was an untreated control group (n = 8) and another group (n = 32) was a butter-treated group fed 10% butter. In the fifth week, mice of the butter-fed group were further divided into four equal groups: B, C, D, and E (n = 8), fed 10% butter with cinnamon 200 mg, 400 mg, and 600 mg powder per liter drinking water, respectively for 10 weeks. The butter-fed group was gained the most weight. Cinnamon supplementation significantly normalized weight gain and had no harmful effects on hematological parameters. Butter supplementation significantly increased total cholesterol (TC), triglycerides, and LDL cholesterol (LDL-c) whereas, cinnamon powder significantly reduced TC, LDL-c and glucose levels. In butter-fed mice, a significant increase was observed in the liver enzymes, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels with subsequent fat deposition in the liver. Excitingly, these enzymes were decreased and no fat depositions were observed in the liver of cinnamon-treated mice. Applying different concentrations of cinnamon powder improved the lipid profile in butter-fed female albino mice.

Blood biomarkers of post-stroke depression after minor stroke at three months in males and females

BACKGROUND

Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. Studies on the underlying mechanisms and biological markers of sex differences in PSD are of great significance, but there are still few such studies. Therefore, the main objective of this study was to investigate the association of biomarkers with PSD at 3 months after minor stroke in men and women.

METHODS

This was a prospective multicenter cohort study that enrolled 530 patients with minor stroke (males, 415; females, 115). Demographic information and blood samples of patients were collected within 24 h of admission, and followed up at 3 months after stroke onset. PSD was defined as a depressive disorder due to another medical condition with depressive features, major depressive-like episode, or mixed-mood features according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V). Univariate analysis was performed using the chi-square test, Mann-Whitney U test, or t-test. Partial least-squares discriminant analysis (PLS-DA) was used to distinguish between patients with and without PSD. Factors with variable importance for projection (VIP) > 1.0 were classified as the most important factors in the model segregation.

RESULTS

The PLS-DA model mainly included component 1 and component 2 for males and females. For males, the model could explain 13% and 16.9% of the variables, respectively, and 29.9% of the variables in total; the most meaningful predictors were exercise habit and fibrinogen level. For females, the model could explain 15.7% and 10.5% of the variables, respectively, and 26.2% of the variables in total; the most meaningful predictors in the model were brain-derived neurotrophic factor (BDNF), magnesium and free T3. Fibrinogen was positively correlated with the Hamilton Depression Scale-17 items (HAMD-17) score. BDNF, magnesium, and free T3 levels were negatively correlated with the HAMD-17 score.

CONCLUSIONS

This was a prospective cohort study. The most important markers found to be affecting PSD at 3 months were fibrinogen in males, and free T3, magnesium, and BDNF in females.

TRIAL REGISTRATION

ChiCTR-ROC-17013993 .

The Alzheimer's disease drug candidate J147 decreases blood plasma fatty acid levels via modulation of AMPK/ACC1 signaling in the liver

J147 is a novel drug candidate developed to treat neurological dysfunction. Numerous studies have demonstrated the beneficial effects of J147 in cellular and animal models of disease which has led to the transitioning of the compound into human clinical trials. However, no biomarkers for its target engagement have been identified. Here, we determined if specific metabolites in the plasma could be indicative of J147's activity in vivo. Plasma lipidomics data from three independent rodent studies were assessed along with liver lipidomics data from one of the studies. J147 consistently reduced plasma free fatty acid (FFA) levels across the independent studies. Decreased FFA levels were also found in the livers of J147-treated mice that correlated well with those in the plasma. These changes in the liver were associated with activation of the AMP-activated protein kinase/acetyl-CoA carboxylase 1 signaling pathway. A reduction in FFA levels by J147 was confirmed in HepG2 cells, where activation of the AMPK/ACC1 pathway was seen along with increases in acetyl-CoA and ATP levels which correlated with enhanced cellular bioenergetics. Our data show that J147 targets liver cells to activate the AMPK/ACC1 signaling pathway and preserve energy at the expense of inhibiting FFA synthesis.

Use of Cognitive Testing, Questionnaires, and Plasma Biomarkers to Quantify Cognitive Impairment in an Aging Pet Dog Population

BACKGROUND

Aging dogs may suffer from canine cognitive dysfunction syndrome (CCDS), a condition in which cognitive decline is associated with amyloid pathology and cortical atrophy. Presumptive diagnosis is made through physical examination, exclusion of systemic/metabolic conditions, and completion of screening questionnaires by owners.

OBJECTIVE

This study aimed to determine whether cognitive function could be quantified in aging pet dogs, and to correlate cognitive testing with validated questionnaires and plasma neurofilament light chain (pNfL) concentration.

METHODS

Thirty-nine dogs from fifteen breeds were recruited (9.3 to 15.3 years). Owners completed the Canine Dementia Scale (CADES) and Canine Cognitive Dysfunction Rating scale (CCDR). Executive control and social cues were tested, and pNfL was measured with single molecule array assay. Comparisons were made between cognitive testing scores, CADES, CCDR scores, and pNfL.

RESULTS

CADES scoring classified five dogs as severe CCDS, six as moderate, ten as mild, and eighteen as normal. CCDR identified seven dogs at risk of CCDS and thirty-two as normal. Cognitive testing was possible in the majority of dogs, although severely affected dogs were unable to learn tasks. CADES score correlated with sustained attention duration (r = -0.47, p = 0.002), inhibitory control (r = -0.51, p = 0.002), detour (r = -0.43, p = 0.001), and pNfL (r = 0.41, p = 0.025). Concentration of pNfL correlated with inhibitory control (r = -0.7, p≤0.001). The CCDR scale correlated with performance on inhibitory control (r = -0.46, p = 0.005).

CONCLUSION

Our findings suggest that a multi-dimensional approach using a combination of questionnaires, specific cognitive tests, and pNfL concentration can be used to quantify cognitive decline in aging pet dogs.

Blood levels of adiponectin and IL-1Ra distinguish type 3c from type 2 diabetes: Implications for earlier pancreatic cancer detection in new-onset diabetes

BACKGROUND

Screening for pancreatic ductal adenocarcinoma (PDAC) in populations at high risk is recommended. Individuals with new-onset type 2 diabetes mellitus (NOD) are the largest high-risk group for PDAC. To facilitate screening, we sought biomarkers capable of stratifying NOD subjects into those with type 2 diabetes mellitus (T2DM) and those with the less prevalent PDAC-related diabetes (PDAC-DM), a form of type 3c DM commonly misdiagnosed as T2DM.

METHODS

Using mass spectrometry- and immunoassay-based methodologies in a multi-stage analysis of independent sample sets (n=443 samples), blood levels of 264 proteins were considered using Ingenuity Pathway Analysis, literature review and targeted training and validation.

FINDINGS

Of 30 candidate biomarkers evaluated in up to four independent patient sets, 12 showed statistically significant differences in levels between PDAC-DM and T2DM. The combination of adiponectin and interleukin-1 receptor antagonist (IL-1Ra) showed strong diagnostic potential, (AUC of 0.91; 95% CI: 0.84-0.99) for the distinction of T3cDM from T2DM.

INTERPRETATION

Adiponectin and IL-1Ra warrant further consideration for use in screening for PDAC in individuals newly-diagnosed with T2DM.

FUNDING

North West Cancer Research, UK, Cancer Research UK, Pancreatic Cancer Action, UK.

Clinical and analytical comparison of six Simoa assays for plasma P-tau isoforms P-tau181, P-tau217, and P-tau231

INTRODUCTION

Studies using different assays and technologies showed highly promising diagnostic value of plasma phosphorylated (P-)tau levels for Alzheimer's disease (AD). We aimed to compare six P-tau Simoa assays, including three P-tau181 (Eli Lilly, ADx, Quanterix), one P-tau217 (Eli Lilly), and two P-tau231 (ADx, Gothenburg).

METHODS

We studied the analytical (sensitivity, precision, parallelism, dilution linearity, and recovery) and clinical (40 AD dementia patients, age 66±8years, 50%F; 40 age- and sex-matched controls) performance of the assays.

RESULTS

All assays showed robust analytical performance, and particularly P-tau217 Eli Lilly; P-tau231 Gothenburg and all P-tau181 assays showed robust clinical performance to differentiate AD from controls, with AUCs 0.936-0.995 (P-tau231 ADx: AUC = 0.719). Results obtained with all P-tau181 assays, P-tau217 Eli Lilly assay, and P-tau231 Gothenburg assay strongly correlated (Spearman's rho > 0.86), while correlations with P-tau231 ADx results were moderate (rho < 0.65).

DISCUSSION

P-tau isoforms can be measured robustly by several novel high-sensitive Simoa assays.