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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 -
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 -
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 -
The American Journal of Psychiatry Jan 2023The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.
METHODS
A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.
RESULTS
A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."
CONCLUSIONS
There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.
Topics: Humans; Autism Spectrum Disorder; Biomarkers; Phenotype; Magnetic Resonance Imaging; Research Design
PubMed: 36475375
DOI: 10.1176/appi.ajp.21100992 -
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 -
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 -
JAMA Neurology Apr 2022Brain injury biomarkers released into circulation from the injured neurovascular unit are important prognostic tools in patients with cardiac arrest who develop hypoxic... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
Brain injury biomarkers released into circulation from the injured neurovascular unit are important prognostic tools in patients with cardiac arrest who develop hypoxic ischemic brain injury (HIBI) after return of spontaneous circulation (ROSC).
OBJECTIVE
To assess the neuroprognostic utility of bloodborne brain injury biomarkers in patients with cardiac arrest with HIBI.
DATA SOURCES
Studies in electronic databases from inception to September 15, 2021. These databases included MEDLINE, Embase, Evidence-Based Medicine Reviews, CINAHL, Cochrane Database of Systematic Reviews, and the World Health Organization Global Health Library.
STUDY SELECTION
Articles included in this systmatic review and meta-analysis were independently assessed by 2 reviewers. We included studies that investigated neuron-specific enolase, S100 calcium-binding protein β, glial fibrillary acidic protein, neurofilament light, tau, or ubiquitin carboxyl hydrolase L1 in patients with cardiac arrest aged 18 years and older for neurologic prognostication. We excluded studies that did not (1) dichotomize neurologic outcome as favorable vs unfavorable, (2) specify the timing of blood sampling or outcome determination, or (3) report diagnostic test accuracy or biomarker concentration.
DATA EXTRACTION AND SYNTHESIS
Data on the study design, inclusion and exclusion criteria, brain biomarkers levels, diagnostic test accuracy, and neurologic outcome were recorded. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.
MAIN OUTCOMES AND MEASURES
Summary receiver operating characteristic curve analysis was used to calculate the area under the curve, sensitivity, specificity, and optimal thresholds for each biomarker. Risk of bias and concerns of applicability were assessed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.
RESULTS
We identified 2953 studies, of which 86 studies with 10 567 patients (7777 men [73.6] and 2790 women [26.4]; pooled mean [SD] age, 62.8 [10.2] years) were included. Biomarker analysis at 48 hours after ROSC demonstrated that neurofilament light had the highest predictive value for unfavorable neurologic outcome, with an area under the curve of 0.92 (95% CI, 0.84-0.97). Subgroup analyses of patients treated with targeted temperature management and those who specifically had an out-of-hospital cardiac arrest showed similar results (targeted temperature management, 0.92 [95% CI, 0.86-0.95] and out-of-hospital cardiac arrest, 0.93 [95% CI, 0.86-0.97]).
CONCLUSIONS AND RELEVANCE
Neurofilament light, which reflects white matter damage and axonal injury, yielded the highest accuracy in predicting neurologic outcome in patients with HIBI at 48 hours after ROSC.
TRIAL REGISTRATION
PROSPERO Identifier: CRD42020157366.
Topics: Biomarkers; Brain; Brain Injuries; Female; Humans; Hypothermia, Induced; Hypoxia-Ischemia, Brain; Male; Middle Aged; Out-of-Hospital Cardiac Arrest; Prognosis
PubMed: 35226054
DOI: 10.1001/jamaneurol.2021.5598 -
NeuroImage Sep 2022Diagnosis and management of chronic neuropathic pain are challenging, leading to current efforts to characterize 'objective' biomarkers of pain using imaging or... (Review)
Review
Diagnosis and management of chronic neuropathic pain are challenging, leading to current efforts to characterize 'objective' biomarkers of pain using imaging or neurophysiological techniques, such as electroencephalography (EEG). A systematic literature review was conducted in PubMed-Medline and Web-of-Science until October 2021 to identify EEG biomarkers of chronic neuropathic pain in humans. The risk of bias was assessed by the Newcastle-Ottawa-Scale. Experimental, provoked, or chronic non-neuropathic pain studies were excluded. We identified 14 studies, in which resting-state EEG spectral analysis was compared between patients with pain related to a neurological disease and patients with the same disease but without pain or healthy controls. From these heterogeneous exploratory studies, some conclusions can be drawn, even if they must be weighted by the fact that confounding factors, such as medication and association with anxio-depressive disorders, are generally not taken into account. Overall, EEG signal power was increased in the θ band (4-7Hz) and possibly in the high-β band (20-30Hz), but decreased in the high-α-low-β band (10-20Hz) in the presence of ongoing neuropathic pain, while increased γ band oscillations were not evidenced, unlike in experimental pain. Consequently, the dominant peak frequency was decreased in the θ-α band and increased in the whole-β band in neuropathic pain patients. Disappointingly, pain intensity correlated with various EEG changes across studies, with no consistent trend. This review also discusses the location of regional pain-related EEG changes in the pain connectome, as the perspectives offered by advanced techniques of EEG signal analysis (source location, connectivity, or classification methods based on artificial intelligence). The biomarkers provided by resting-state EEG are of particular interest for optimizing the treatment of chronic neuropathic pain by neuromodulation techniques, such as transcranial alternating current stimulation or neurofeedback procedures.
Topics: Artificial Intelligence; Biomarkers; Electroencephalography; Humans; Neuralgia; Neurofeedback
PubMed: 35659993
DOI: 10.1016/j.neuroimage.2022.119351 -
International Journal of Molecular... Apr 2023Preterm premature rupture of membranes, leading to preterm birth, is associated with neonatal and maternal morbidity and mortality. The study aimed to review the... (Review)
Review
Preterm premature rupture of membranes, leading to preterm birth, is associated with neonatal and maternal morbidity and mortality. The study aimed to review the existing data on the best predictive value of pregnancy latency for known biomarkers in pregnancies after preterm premature rupture of membranes. The following databases were screened for the purposes of this systematic review: Pubmed/MEDLINE, Web of Science, EMBASE, Scopus, and the Cochrane Library. The study was conducted according to the PRISMA guidelines for systematic reviews. Only a few studies assessed biomarkers predicting pregnancy duration after PPROM. IL-6, IL-8, CRP, IL1RA, s-endoglin, βhCG, AFP, PCT, urea, creatinine, oxygen radical absorbance capacity, MDA, lipocalin-2, endotoxin activity, MMP-8, MMP-9 and S100 A8/A9 were found to have a positive predictive value for delivery timing prediction. Proinflammatory biomarkers, such as IL-6 or CRP, proved to be best correlated with delivery timing, independent of the occurrence of intrauterine infection.
Topics: Pregnancy; Female; Infant, Newborn; Humans; Premature Birth; Interleukin-6; Fetal Membranes, Premature Rupture; Biomarkers; Gestational Age
PubMed: 37175733
DOI: 10.3390/ijms24098027 -
JAMA Pediatrics Aug 2022Neonatal early-onset sepsis (EOS) is a severe disease, particularly in preterm infants. Timely diagnosis can be challenging owing to unspecific presentation and... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
Neonatal early-onset sepsis (EOS) is a severe disease, particularly in preterm infants. Timely diagnosis can be challenging owing to unspecific presentation and questionable performance of the common markers of infection. Presepsin was recently proven to be a promising biomarker for the diagnosis of EOS.
OBJECTIVE
To assess presepsin accuracy for the diagnosis of EOS.
DATA SOURCES
PubMed Medline, EMBASE, Web of Science, and Google Scholar. No publication date restrictions were applied. The literature search was limited to the English language. Articles were checked for duplication.
STUDY SELECTION
Inclusion criteria were studies that (1) included term or preterm newborns (defined as newborns with gestational age ≥37 weeks or <37 weeks, respectively); (2) included a diagnosis of EOS, defined as culture-proven sepsis for primary analysis and as either clinical or culture-proven sepsis for secondary analysis; and (3) assessed presepsin values during the initial workup for suspected EOS. Exclusion criteria were studies that (1) did not include EOS cases; (2) lacked data on presepsin sensitivity and/or specificity; and (3) were case reports, commentaries, or reviews. Two independent reviewers performed the study selection.
DATA EXTRACTION AND SYNTHESIS
Two independent reviewers performed data extraction and quality assessment. Quality assessment was performed using the Quality Assessment for Studies of Diagnostic Accuracy 2 tool, and data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data were pooled using a random-effects model.
MAIN OUTCOMES AND MEASURES
The outcomes of interest for both the primary and secondary analyses were presepsin sensitivity, specificity, and diagnostic odds ratio for the diagnosis of EOS.
RESULTS
A total of 12 studies of 245 (4.9%) met inclusion criteria for the primary analysis. Twenty-three studies of 245 (9.4%) met the inclusion criteria for the secondary analysis. In the primary analysis, among 12 studies and 828 newborns of any gestational age, pooled sensitivity and specificity were 0.93 (95% CI, 0.86-0.95) and 0.91 (95% CI, 0.85-0.95), respectively; pooled diagnostic odds ratio was 131.69 (95% CI, 54.93-310.94). Subgroup analysis showed that presepsin specificity was associated with the inclusion of only EOS or all neonatal sepsis. Presepsin accuracy was not associated with gestational age, measurement with chemiluminescence enzyme immunoassay or enzyme-linked immunosorbent assay testing, country where the study was performed, or risk of bias judgment. In the secondary analysis, among 23 studies and 1866 newborns, accuracy was significantly associated with only test type.
CONCLUSIONS AND RELEVANCE
Results of this systematic review and meta-analysis suggest that presepsin was an accurate biomarker of EOS. Clinical trials are warranted to assess its usefulness and safety to reduce early antibiotic exposure, particularly in preterm newborns.
Topics: Biomarkers; Humans; Infant; Infant, Newborn; Infant, Premature; Lipopolysaccharide Receptors; Neonatal Sepsis; Peptide Fragments; Sepsis
PubMed: 35639395
DOI: 10.1001/jamapediatrics.2022.1647