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Current Pain and Headache Reports Apr 2024Fibromyalgia syndrome (FMS) is a disease of unknown pathophysiology, with the diagnosis being based on a set of clinical criteria. Proteomic analysis can provide... (Review)
Review
PURPOSE OF REVIEW
Fibromyalgia syndrome (FMS) is a disease of unknown pathophysiology, with the diagnosis being based on a set of clinical criteria. Proteomic analysis can provide significant biological information for the pathophysiology of the disease but may also reveal biomarkers for diagnosis or therapeutic targets. The present systematic review aims to synthesize the evidence regarding the proteome of adult patients with FMS using data from observational studies.
RECENT FINDINGS
An extensive literature search was conducted in MEDLINE/PubMed, CENTRAL, and clinicaltrials.gov from inception until November 2022. The study protocol was published in OSF. Two independent reviewers evaluated the studies and extracted data. The quality of studies was assessed using the modified Newcastle-Ottawa scale adjusted for proteomic research. Ten studies fulfilled the protocol criteria, identifying 3328 proteins, 145 of which were differentially expressed among patients with FMS against controls. The proteins were identified in plasma, serum, cerebrospinal fluid, and saliva samples. The control groups included healthy individuals and patients with pain (inflammatory and non-inflammatory). The most important proteins identified involved transferrin, α-, β-, and γ-fibrinogen chains, profilin-1, transaldolase, PGAM1, apolipoprotein-C3, complement C4A and C1QC, immunoglobin parts, and acute phase reactants. Weak correlations were observed between proteins and pain sensation, or quality of life scales, apart from the association of transferrin and a2-macroglobulin with moderate-to-severe pain sensation. The quality of included studies was moderate-to-good. FMS appears to be related to protein dysregulation in the complement and coagulation cascades and the metabolism of iron. Several proteins may be dysregulated due to the excessive oxidative stress response.
PubMed: 38652420
DOI: 10.1007/s11916-024-01244-4 -
Diabetes, Obesity & Metabolism Apr 2024To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM),... (Review)
Review
AIMS
To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low- and middle-income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training.
MATERIALS AND METHODS
Papers were sourced from six databases: the British Nursing Index, Google Scholar, PubMed, Sage, Science Direct and Scopus. Articles published between January 2002 and January 2023 were systematically reviewed by three reviewers and appropriate search terms and inclusion/exclusion criteria were applied.
RESULTS
A total of 18 studies were yielded, as well as 234 diagnostic biomarkers (74 for CVD and 160 for DM). Primary biomarkers for the diagnosis of CVDs included growth differentiation factor 15 and neurogenic locus notch homologue protein 1 (Notch1). For the diagnosis of DM, alpha-2-macroglobulin, C-peptides, isoleucine, glucose, tyrosine, linoleic acid and valine were frequently reported across the included studies. Advanced analytical techniques, such as liquid chromatography mass spectrometry, enzyme-linked immunosorbent assays and vibrational spectroscopy, were also repeatedly reported in the included studies and were utilized in combination with traditional and alternative matrices such as fingernails, hair and saliva.
CONCLUSIONS
While advanced analytical techniques are expensive, laboratories in LMICs should carry out a cost-benefit analysis of their use. Alternatively, laboratories may want to explore emerging techniques such as infrared, Fourier transform-infrared and near-infrared spectroscopy, which allow sensitive noninvasive analysis.
PubMed: 38637978
DOI: 10.1111/dom.15593 -
Journal of Alzheimer's Disease Reports 2023The relationship between alpha 2-macroglobulin (A2M) gene and Alzheimer's disease (AD) has been widely studied across populations; however, the results are inconsistent.
BACKGROUND
The relationship between alpha 2-macroglobulin (A2M) gene and Alzheimer's disease (AD) has been widely studied across populations; however, the results are inconsistent.
OBJECTIVE
This study aimed to evaluate the association of A2M gene with AD by the application of meta-analysis.
METHODS
Relevant studies were identified by comprehensive searches. The quality of each study was assessed using the Newcastle-Ottawa Scale. Allele and genotype frequencies were extracted from each of the included studies. Odds ratio (OR) with corresponding 95% confidence intervals (CI) was calculated using a random-effects or fixed-effects model. The Cochran Q statistic and I metric was used to evaluate heterogeneity, and Egger's test and Funnel plot were used to assess publication bias.
RESULTS
A total of 62 studies were identified and included in the current meta-analysis. The G allele of rs226380 reduced AD risk (OR: 0.64, 95% CI: 0.47-0.87, pFDR = 0.012), but carrier with the TT genotype was more likely to develop AD in Asian populations (OR: 1.56, 95% CI: 1.12-2.19, pFDR = 0.0135). The V allele of the A2M-I/V (rs669) increased susceptibility to AD in female population (OR, 95% CI: 2.15, 1.38-3.35, pFDR = 0.0024); however, the II genotype could be a protective factor in these populations (OR, 95% CI: 0.43, 0.26-0.73, pFDR = 0.003). Sensitivity analyses confirmed the reliability of the original results.
CONCLUSIONS
Existing evidence indicate that A2M single nucleotide polymorphisms (SNPs) may be associated with AD risk in sub-populations. Future studies with larger sample sizes will be necessary to confirm the results.
PubMed: 38143774
DOI: 10.3233/ADR-230131