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Psychotherapy and Psychosomatics 2021Allostatic load refers to the cumulative burden of chronic stress and life events. It involves the interaction of different physiological systems at varying degrees of... (Review)
Review
INTRODUCTION
Allostatic load refers to the cumulative burden of chronic stress and life events. It involves the interaction of different physiological systems at varying degrees of activity. When environmental challenges exceed the individual ability to cope, then allostatic overload ensues. Allostatic load is identified by the use of biomarkers and clinical criteria.
OBJECTIVE
To summarize the current knowledge on allostatic load and overload and its clinical implications based on a systematic review of the literature.
METHODS
PubMed, PsycINFO, Web of Science, and the Cochrane Library were searched from inception to December 2019. A manual search of the literature was also performed, and reference lists of the retrieved articles were examined.We considered only studies in which allostatic load or overload were adequately described and assessed in either clinical or non-clinical adult populations.
RESULTS
A total of 267 original investigations were included. They encompassed general population studies, as well as clinical studies on consequences of allostatic load/overload on both physical and mental health across a variety of settings.
CONCLUSIONS
The findings indicate that allostatic load and overload are associated with poorer health outcomes. Assessment of allostatic load provides support to the understanding of psychosocial determinants of health and lifestyle medicine. An integrated approach that includes both biological markers and clinimetric criteria is recommended.
Topics: Adaptation, Psychological; Adult; Allostasis; Biomarkers; Humans; Life Style; Stress, Psychological
PubMed: 32799204
DOI: 10.1159/000510696 -
International Journal of Molecular... Feb 2023Around 40-50% of all triple-negative breast cancer (TNBC) patients achieve a pathological complete response (pCR) after treatment with neoadjuvant chemotherapy (NAC).... (Review)
Review
Around 40-50% of all triple-negative breast cancer (TNBC) patients achieve a pathological complete response (pCR) after treatment with neoadjuvant chemotherapy (NAC). The identification of biomarkers predicting the response to NAC could be helpful for personalized treatment. This systematic review provides an overview of putative biomarkers at baseline that are predictive for a pCR following NAC. Embase, Medline and Web of Science were searched for articles published between January 2010 and August 2022. The articles had to meet the following criteria: patients with primary invasive TNBC without distant metastases and patients must have received NAC. In total, 2045 articles were screened by two reviewers resulting in the inclusion of 92 articles. Overall, the most frequently reported biomarkers associated with a pCR were a high expression of Ki-67, an expression of PD-L1 and the abundance of tumor-infiltrating lymphocytes, particularly CD8+ T cells, and corresponding immune gene signatures. In addition, our review reveals proteomic, genomic and transcriptomic markers that relate to cancer cells, the tumor microenvironment and the peripheral blood, which also affect chemo-sensitivity. We conclude that a prediction model based on a combination of tumor and immune markers is likely to better stratify TNBC patients with respect to NAC response.
Topics: Humans; Neoadjuvant Therapy; Triple Negative Breast Neoplasms; Proteomics; Lymphocytes, Tumor-Infiltrating; Biomarkers; Tumor Microenvironment
PubMed: 36769287
DOI: 10.3390/ijms24032969 -
Diabetes Care May 2016To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes.
RESEARCH DESIGN AND METHODS
We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite.
RESULTS
We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%).
CONCLUSIONS
In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.
Topics: Biomarkers; Cross-Sectional Studies; Diabetes Mellitus, Type 2; Female; Humans; Incidence; Metabolomics; Middle Aged; Prediabetic State; Prospective Studies
PubMed: 27208380
DOI: 10.2337/dc15-2251 -
Schizophrenia Research May 2018Current diagnosis of schizophrenia relies exclusively on the potentially subjective interpretation of clinical symptoms and social functioning as more objective... (Review)
Review
Current diagnosis of schizophrenia relies exclusively on the potentially subjective interpretation of clinical symptoms and social functioning as more objective biological measurement and medical diagnostic tests are not presently available. The use of metabolomics in the discovery of disease biomarkers has grown in recent years. Metabolomic methods could aid in the discovery of diagnostic biomarkers of schizophrenia. This systematic review focuses on biofluid metabolites associated with schizophrenia. A systematic search of Web of Science and Ovid Medline databases was conducted and 63 studies investigating metabolite biomarkers of schizophrenia were included. A review of these studies revealed several potential metabolite signatures of schizophrenia including reduced levels of essential polyunsaturated fatty acids (EPUFAs), vitamin E and creatinine; and elevated levels of lipid peroxidation metabolites and glutamate. Further research is needed to validate these biomarkers and would benefit from large cohort studies and more homogeneous and well-defined subject groups.
Topics: Biomarkers; Databases, Bibliographic; Fatty Acids, Unsaturated; Humans; Lipid Peroxidation; Metabolomics; Schizophrenia; Vitamin E
PubMed: 28947341
DOI: 10.1016/j.schres.2017.09.021 -
International Journal of Molecular... Aug 2022Background: Glioblastoma (GBM) is a highly aggressive cancer with poor prognosis that needs better treatment modalities. Moreover, there is a lack of reliable biomarkers... (Meta-Analysis)
Meta-Analysis Review
Background: Glioblastoma (GBM) is a highly aggressive cancer with poor prognosis that needs better treatment modalities. Moreover, there is a lack of reliable biomarkers to predict the response and outcome of current or newly designed therapies. While several molecular markers have been proposed as potential biomarkers for GBM, their uptake into clinical settings is slow and impeded by marker heterogeneity. Detailed assessment of prognostic and predictive value for biomarkers in well-defined clinical trial settings, if available, is scattered throughout the literature. Here we conducted a systematic review and meta-analysis to evaluate the prognostic and predictive significance of clinically relevant molecular biomarkers in GBM patients. Material and methods: A comprehensive literature search was conducted to retrieve publications from 3 databases (Pubmed, Cochrane and Embase) from January 2010 to December 2021, using specific terms. The combined hazard ratios (HR) and confidence intervals (95% CI) were used to evaluate the association of biomarkers with overall survival (OS) in GBM patients. Results: Twenty-six out of 1831 screened articles were included in this review. Nineteen articles were included in the meta-analyses, and 7 articles were quantitatively summarised. Fourteen studies with 1231 GBM patients showed a significant association of MGMT methylation with better OS with the pooled HR of 1.66 (95% CI 1.32−2.09, p < 0.0001, random effect). Five studies including 541 GBM patients analysed for the prognostic significance of IDH1 mutation showed significantly better OS in patients with IDH1 mutation with a pooled HR of 2.37 (95% CI 1.81−3.12; p < 0.00001]. Meta-analysis performed on 5 studies including 575 GBM patients presenting with either amplification or high expression of EGFR gene did not reveal any prognostic significance with a pooled HR of 1.31 (95% CI 0.96−1.79; p = 0.08). Conclusions: MGMT promoter methylation and IDH1 mutation are significantly associated with better OS in GBM patients. No significant associations were found between EGFR amplification or overexpression with OS.
Topics: Biomarkers; Biomarkers, Tumor; Brain Neoplasms; DNA Methylation; DNA Modification Methylases; DNA Repair Enzymes; Glioblastoma; Humans; Tumor Suppressor Proteins
PubMed: 36012105
DOI: 10.3390/ijms23168835 -
Survey of Ophthalmology 2022The human tear film is at the interface between the ocular surface and the external environment. Although investigation has been hindered by its small volume,... (Review)
Review
The human tear film is at the interface between the ocular surface and the external environment. Although investigation has been hindered by its small volume, improvements in preanalytical and analytical methods have allowed the omics approach to represent an innovative biomarker search strategy. There is still a significant lack of standardization, representing a barrier for performing between-studies comparisons and transferring experimental findings into clinical use and trials. We summarize the preanalytical and analytical procedures, describe the biomarkers that can be found using the metabo-lipidomics approach, and provide our expert opinion for omics investigations in human tears. For this systematic review of 38 studies, we searched PubMed by combining Boolean operators with the following keywords: tear, metabolomic, lipidomic, -omics. The human tear metabo-lipidome has been well-characterized in normal individuals using high-resolution liquid chromatography coupled with mass spectrometry. Lipid and metabolite profiles were influenced by ocular (e.g., dry eye disorders; Meibomian gland dysfunction; contact lens wear; glaucoma; keratoconus; pterygium) and systemic conditions (e.g., multiple sclerosis). Investigating the tear metabo-lipidome could improve our understanding of the pathogenesis of both ocular and systemic diseases, but also provide diagnostic as well as prognostic biomarkers.
Topics: Biomarkers; Dry Eye Syndromes; Humans; Lipidomics; Meibomian Glands; Metabolomics; Tears
PubMed: 35093405
DOI: 10.1016/j.survophthal.2022.01.010 -
International Journal of Molecular... Jan 2022Stroke is a primary debilitating disease in adults, occurring in 15 million individuals each year and causing high mortality and disability rates. The latest estimate... (Meta-Analysis)
Meta-Analysis
Stroke is a primary debilitating disease in adults, occurring in 15 million individuals each year and causing high mortality and disability rates. The latest estimate revealed that stroke is currently the second leading cause of death worldwide. Post-stroke cognitive impairment (PSCI), one of the major complications after stroke, is frequently underdiagnosed. However, stroke has been reported to increase the risk of cognitive impairment by at least five to eight times. In recent decades, peripheral blood molecular biomarkers for stroke have emerged as diagnostic, prognostic, and therapeutic targets. In this study, we aimed to evaluate some blood-derived proteins for stroke, especially related to brain damage and cognitive impairments, by conducting a systematic review and meta-analysis and discussing the possibility of these proteins as biomarkers for PSCI. Articles published before 26 July 2021 were searched in PubMed, Embase, the Web of Science, and the Cochrane Library to identify all relevant studies reporting blood biomarkers in patients with stroke. Among 1820 articles, 40 were finally identified for this study. We meta-analyzed eight peripheral biomarker candidates: homocysteine (Hcy), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), uric acid, and glycated hemoglobin (HbA1c). The Hcy, CRP, TC, and LDL-C levels were significantly higher in patients with PSCI than in the non-PSCI group; however, the HDL-C, TG, uric acid, and HbA1c levels were not different between the two groups. Based on our findings, we suggest the Hcy, CRP, TC, and LDL-C as possible biomarkers in patients with post-stroke cognitive impairment. Thus, certain blood proteins could be suggested as effective biomarkers for PSCI.
Topics: Biomarkers; Cognitive Dysfunction; Humans; Stroke
PubMed: 35054785
DOI: 10.3390/ijms23020602 -
Annals of Oncology : Official Journal... Aug 2019Cancers with a defective DNA mismatch repair (dMMR) system contain thousands of mutations most frequently located in monomorphic microsatellites and are thereby defined...
ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: a systematic review-based approach.
BACKGROUND
Cancers with a defective DNA mismatch repair (dMMR) system contain thousands of mutations most frequently located in monomorphic microsatellites and are thereby defined as having microsatellite instability (MSI). Therefore, MSI is a marker of dMMR. MSI/dMMR can be identified using immunohistochemistry to detect loss of MMR proteins and/or molecular tests to show microsatellite alterations. Together with tumour mutational burden (TMB) and PD-1/PD-L1 expression, it plays a role as a predictive biomarker for immunotherapy.
METHODS
To define best practices to implement the detection of dMMR tumours in clinical practice, the ESMO Translational Research and Precision Medicine Working Group launched a collaborative project, based on a systematic review-approach, to generate consensus recommendations on the: (i) definitions related to the concept of MSI/dMMR; (ii) methods of MSI/dMMR testing and (iii) relationships between MSI, TMB and PD-1/PD-L1 expression.
RESULTS
The MSI-related definitions, for which a consensus frame-work was used to establish definitions, included: 'microsatellites', 'MSI', 'DNA mismatch repair' and 'features of MSI tumour'. This consensus also provides recommendations on MSI testing; immunohistochemistry for the mismatch repair proteins MLH1, MSH2, MSH6 and PMS2 represents the first action to assess MSI/dMMR (consensus with strong agreement); the second method of MSI/dMMR testing is represented by polymerase chain reaction (PCR)-based assessment of microsatellite alterations using five microsatellite markers including at least BAT-25 and BAT-26 (strong agreement). Next-generation sequencing, coupling MSI and TMB analysis, may represent a decisive tool for selecting patients for immunotherapy, for common or rare cancers not belonging to the spectrum of Lynch syndrome (very strong agreement). The relationships between MSI, TMB and PD-1/PD-L1 expression are complex, and differ according to tumour types.
CONCLUSIONS
This ESMO initiative is a response to the urgent questions raised by the growing success of immunotherapy and provides also important insights on the relationships between MSI, TMB and PD-1/PD-L1.
Topics: Antineoplastic Agents, Immunological; B7-H1 Antigen; Biomarkers, Tumor; DNA Mismatch Repair; DNA Mutational Analysis; European Union; Genetic Testing; High-Throughput Nucleotide Sequencing; Humans; Immunohistochemistry; Medical Oncology; Microsatellite Instability; Mutation; Neoplasms; Patient Selection; Practice Guidelines as Topic; Programmed Cell Death 1 Receptor; Societies, Medical
PubMed: 31056702
DOI: 10.1093/annonc/mdz116 -
International Journal of Molecular... Mar 2021Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on...
BACKGROUND
Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis.
METHODS
We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD.
METHODS
We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD.
RESULTS
In additional to Aβ and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls.
CONCLUSIONS
Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics.
Topics: Aged; Alzheimer Disease; Biomarkers; Chromatography, High Pressure Liquid; Diagnosis, Computer-Assisted; Female; Humans; Machine Learning; Middle Aged
PubMed: 33803217
DOI: 10.3390/ijms22052761 -
Apoptosis : An International Journal on... Aug 2022Programmed cell death is considered a key player in a variety of cellular processes that helps to regulate tissue growth, embryogenesis, cell turnover, immune response,... (Review)
Review
Programmed cell death is considered a key player in a variety of cellular processes that helps to regulate tissue growth, embryogenesis, cell turnover, immune response, and other biological processes. Among different types of cell death, apoptosis has been studied widely, especially in the field of cancer research to understand and analyse cellular mechanisms, and signaling pathways that control cell cycle arrest. Hallmarks of different types of cell death have been identified by following the patterns and events through microscopy. Identified biomarkers have also supported drug development to induce cell death in cancerous cells. There are various serological and microscopic techniques with advantages and limitations, that are available and are being utilized to detect and study the mechanism of cell death. The complexity of the mechanism and difficulties in distinguishing among different types of programmed cell death make it challenging to carry out the interventions and delay its progression. In this review, mechanisms of different forms of programmed cell death along with their conventional and unconventional methods of detection of have been critically reviewed systematically and categorized on the basis of morphological hallmarks and biomarkers to understand the principle, mechanism, application, advantages and disadvantages of each method. Furthermore, a very comprehensive comparative analysis has been drawn to highlight the most efficient and effective methods of detection of programmed cell death, helping researchers to make a reliable and prudent selection among the available methods of cell death assay. Conclusively, how programmed cell death detection methods can be improved and can provide information about distinctive stages of cell death detection have been discussed.
Topics: Apoptosis; Biomarkers; Cell Death; Signal Transduction
PubMed: 35713779
DOI: 10.1007/s10495-022-01735-y