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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 -
Journal of Psychosomatic Research Aug 2021Delirium is a common neuropsychiatric disorder associated with prolonged hospital stays, and increased morbidity and mortality. Diagnosis is frequently missed due to... (Review)
Review
BACKGROUND
Delirium is a common neuropsychiatric disorder associated with prolonged hospital stays, and increased morbidity and mortality. Diagnosis is frequently missed due to varying disease presentation and lack of standardized testing. We examined biomarkers as diagnostic or prognostic indicators of delirium, and provide a rational basis for future studies.
METHOD
Systematic review of literature published between Jan 2000 and June 2019. Searches included: PubMed; Web of Science; CINAHL; EMBASE; COCHRANE and Medline. Additional studies were identified by searching bibliographies of eligible articles.
RESULTS
2082 relevant papers were identified from all sources. Seventy-three met the inclusion criteria, all of which were observational. These assessed a range of fourteen biomarkers. All papers included were in the English language. Assessment methods varied between studies, including: DSM criteria; Confusion Assessment Method (CAM) or CAM-Intensive Care Unit (ICU). Delirium severity was measured using the Delirium Rating Scale (DRS). Delirium was secondary to post-operative dysfunction or acute medical conditions.
CONCLUSION
Evidence does not currently support the use of any one biomarker. However, certain markers were associated with promising results and may warrant evaluation in future studies. Heterogeneity across study methods may have contributed to inconclusive results, and more clarity may arise from standardization of methods of clinical assessment. Adjusting for comorbidities may improve understanding of the pathophysiology of delirium, in particular the role of confounders such as inflammation, cognitive disorders and surgical trauma. Future research may also benefit from inclusion of other diagnostic modalities such as EEG as well as analysis of genetic or epigenetic factors.
Topics: Biomarkers; Cognition Disorders; Delirium; Humans; Intensive Care Units; Length of Stay
PubMed: 34098376
DOI: 10.1016/j.jpsychores.2021.110530 -
Cell Communication and Signaling : CCS Feb 2020Breast cancer has grown to be the second leading cause of cancer-related deaths in women. Only a few treatment options are available for breast cancer due to the... (Review)
Review
Breast cancer has grown to be the second leading cause of cancer-related deaths in women. Only a few treatment options are available for breast cancer due to the widespread occurrence of chemoresistance, which emphasizes the need to discover and develop new methods to treat this disease. Signal transducer and activator of transcription 3 (STAT3) is an early tumor diagnostic marker and is known to promote breast cancer malignancy. Recent clinical and preclinical data indicate the involvement of overexpressed and constitutively activated STAT3 in the progression, proliferation, metastasis and chemoresistance of breast cancer. Moreover, new pathways comprised of upstream regulators and downstream targets of STAT3 have been discovered. In addition, small molecule inhibitors targeting STAT3 activation have been found to be efficient for therapeutic treatment of breast cancer. This systematic review discusses the advances in the discovery of the STAT3 pathways and drugs targeting STAT3 in breast cancer. Video abstract.
Topics: Antineoplastic Agents; Biomarkers, Tumor; Breast Neoplasms; Cell Line, Tumor; Drug Resistance, Neoplasm; Female; Humans; STAT3 Transcription Factor; Signal Transduction
PubMed: 32111215
DOI: 10.1186/s12964-020-0527-z -
Journal of Obesity 2020. Globally, obesity is becoming a public health problem in the general population. Various determinants were reported by different scholars even though there are...
. Globally, obesity is becoming a public health problem in the general population. Various determinants were reported by different scholars even though there are inconsistencies. Different biomarkers of obesity were identified for the prediction of obesity. Even though researchers speculate the factors, biomarkers, consequences, and prevention mechanisms, there is a lack of aggregate and purified data in the area of obesity. . In this review, the epidemiology, predisposing factors, biomarkers, consequences, and prevention approaches of obesity were reviewed. . The epidemiology of obesity increased in low-, middle-, and high-income countries. Even if the factors vary across regions and socioeconomic levels, sociodemographic, behavioral, and genetic factors were prominent for the development of obesity. There are a lot of biomarkers for obesity, of which microRNA, adipocytes, oxidative stress, blood cell profile, nutrients, and microbiota were promising biomarkers for determination of occurrence of obesity. Since the consequences of obesity are vast and interrelated, multidimensional prevention strategy is mandatory in all nations.
Topics: Biomarkers; Humans; Obesity; Risk Factors
PubMed: 32566274
DOI: 10.1155/2020/6134362 -
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... 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... 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 -
Fertility and Sterility Aug 2022To identify the most robust molecular biomarkers in sperm and seminal plasma for the diagnosis of male infertility, and to evaluate their clinical use. (Review)
Review
OBJECTIVE
To identify the most robust molecular biomarkers in sperm and seminal plasma for the diagnosis of male infertility, and to evaluate their clinical use.
DESIGN
Systematic review.
SETTING
Not applicable.
PATIENT(S)
Accessible studies reporting well-defined (in)fertile populations and semen molecular biomarkers were included in this review.
INTERVENTION(S)
A systematic search of the literature published in MEDLINE-PubMed and EMBASE databases was performed, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
MAIN OUTCOME MEASURE(S)
The primary outcome was the content, expression, or activity of molecular biomarkers in human semen samples. Only studies reporting a receiver-operating characteristic (ROC) analysis values were included.
RESULT(S)
Eighty-nine studies were included. Direct evaluation of sperm DNA damage has high potential as a diagnostic biomarker of fertility and assisted reproductive technology outcomes (area under the curve [AUCs] median = 0.67). Regarding strand break-associated chromatin modifications, γH2AX levels show good predictive value for the diagnosis of male infertility (AUCs median = 0.93). Some noncoding ribonucleic acid (RNA) exhibit excellent predictive values; miR-34c-5p in semen is the most well-characterized and robust transcriptomic biomarker (AUCs median = 0.78). While many proteins in semen show fair diagnostic value for sperm quality and fertilizing capacity, the levels of some, such as TEX101, in seminal plasma have an excellent diagnostic potential (AUCs median = 0.69). Although individual metabolites and metabolomic profiles in seminal plasma present good predictive value, the latter seem to be better than the former when inferring sperm quality and fertilizing capacity.
CONCLUSION(S)
The current review supports that some Omics (e.g., DNA structure and integrity, genomics and epigenomics, transcriptomics, metabolomics, and proteomics) could be considered relevant molecular biomarkers that may help identify infertility etiologies and fertilization prognosis with cost-effective, simple, and accurate diagnosis.
Topics: Biomarkers; Fertility; Humans; Infertility, Male; Male; Semen; Semen Analysis; Spermatozoa
PubMed: 35718545
DOI: 10.1016/j.fertnstert.2022.04.028