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Journal of Clinical Laboratory Analysis Apr 2024Kidney disease is fairly unique due to the lack of symptoms associated with disease activity, and it is therefore dependent on biological monitoring. Dried biofluids,... (Review)
Review
BACKGROUND
Kidney disease is fairly unique due to the lack of symptoms associated with disease activity, and it is therefore dependent on biological monitoring. Dried biofluids, particularly dried capillary blood spots, are an accessible, easy-to-use technology that have seen increased utility in basic science research over the past decade. However, their use is yet to reach the kidney patient population clinically or in large-scale discovery science initiatives. The aim of this study was to systematically evaluate the existing literature surrounding the use of dried biofluids in kidney research.
METHODS
A systematic literature review was conducted using three search engines and a predefined search term strategy. Results were summarised according to the collection method, type of biofluid, application to kidney disease, cost, sample stability and patient acceptability.
RESULTS
In total, 404 studies were identified and 67 were eligible. In total, 34,739 patients were recruited to these studies with a skew towards male participants (> 73%). The majority of samples were blood, which was used either for monitoring anti-rejection immunosuppressive drug concentrations or for kidney function. Dried biofluids offered significant cost savings to the patient and healthcare service. The majority of patients preferred home microsampling when compared to conventional monitoring.
CONCLUSION
There is an unmet need in bringing dried microsampling technology to advance kidney disease despite its advantages. This technology provides an opportunity to upscale patient recruitment and longitudinal sampling, enhance vein preservation and overcome participation bias in research.
Topics: Humans; Dried Blood Spot Testing; Kidney Diseases
PubMed: 38525922
DOI: 10.1002/jcla.25032 -
BMC Oral Health Mar 2024Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species...
BACKGROUND
Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species translational research in dentistry and medicine. This study aimed to conduct a systematic review to investigate the similarities and differences between the oral biofluids' proteomics profile of dogs with and without oral diseases.
METHODS
PubMed, Web of Science, and Scopus were searched with no restrictions on publication language or year to address the following focused question: "What is the proteome signature of healthy versus diseased (oral) dogs' biofluids?" Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analyses of the most abundant proteins were performed. Moreover, protein-protein interaction analysis was conducted. The risk of bias (RoB) among the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data.
RESULTS
In healthy dogs, the proteomic analysis identified 5,451 proteins, with 137 being the most abundant, predominantly associated with 'innate immune response'. Dogs with oral diseases displayed 6,470 proteins, with distinct associations: 'defense response to bacterium' (periodontal diseases), 'negative regulation of transcription' (dental calculus), and 'positive regulation of transcription' (oral tumors). Clustering revealed significant protein clusters in each case, emphasizing the diverse molecular profiles in health and oral diseases. Only six studies were provided to the JBI tool, as they encompassed case-control evaluations that compared healthy dogs to dogs with oral disease(s). All included studies were found to have low RoB (high quality).
CONCLUSION
Significant differences in the proteomics profiles of oral biofluids between dogs with and without oral diseases were found. The synergy of animal proteomics and bioinformatics offers a promising avenue for cross-species research, despite persistent challenges in result validation.
Topics: Animals; Dogs; Proteomics; Mass Spectrometry; Periodontal Diseases; Bacteria; Mouth Neoplasms
PubMed: 38519930
DOI: 10.1186/s12903-024-04096-x -
EClinicalMedicine Apr 2024Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small...
BACKGROUND
Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small for GA at a population level. Currently, the gold standard for pregnancy dating is measurement of the fetal crown rump length at 11-14 weeks of gestation. However, this is not possible for women first presenting in later pregnancy, or in settings where routine ultrasound is not available. A reliable, cheap and easy to measure GA-dependent biomarker would provide an important breakthrough in estimating the age of pregnancy. Therefore, the aim of this study was to determine the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA).
METHODS
Systematic review prospectively registered with PROSPERO (CRD42020167727) and reported in accordance with the PRISMA-DTA. Medline, Embase, CINAHL, LILACS, and other databases were searched from inception until September 2023 for cohort or cross-sectional studies that reported on the accuracy of prenatal and postnatal biomarkers for estimating GA. In addition, we searched Google Scholar and screened proceedings of relevant conferences and reference lists of identified studies and relevant reviews. There were no language or date restrictions. Pooled coefficients of correlation and root mean square error (RMSE, average deviation in weeks between the GA estimated by the biomarker and that estimated by the gold standard method) were calculated. The risk of bias in each included study was also assessed.
FINDINGS
Thirty-nine studies fulfilled the inclusion criteria: 20 studies (2,050 women) assessed prenatal biomarkers (placental hormones, metabolomic profiles, proteomics, cell-free RNA transcripts, and exon-level gene expression), and 19 (1,738,652 newborns) assessed postnatal biomarkers (metabolomic profiles, DNA methylation profiles, and fetal haematological components). Among the prenatal biomarkers assessed, human chorionic gonadotrophin measured in maternal serum between 4 and 9 weeks of gestation showed the highest correlation with the reference standard GA, with a pooled coefficient of correlation of 0.88. Among the postnatal biomarkers assessed, metabolomic profiling from newborn blood spots provided the most accurate estimate of GA, with a pooled RMSE of 1.03 weeks across all GAs. It performed best for term infants with a slightly reduced accuracy for preterm or small for GA infants. The pooled RMSEs for metabolomic profiling and DNA methylation profile from cord blood samples were 1.57 and 1.60 weeks, respectively.
INTERPRETATION
We identified no antenatal biomarkers that accurately predict GA over a wide window of pregnancy. Postnatally, metabolomic profiling from newborn blood spot provides an accurate estimate of GA, however, as this is known only after birth it is not useful to guide antenatal care. Further prenatal studies are needed to identify biomarkers that can be used in isolation, as part of a biomarker panel, or in combination with other clinical methods to narrow prediction intervals of GA estimation.
FUNDING
The research was funded by the Bill and Melinda Gates Foundation (INV-000368). ATP is supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the NIHR Biomedical Research Centre funding scheme. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, the Department of Health, or the Department of Biotechnology. The funders of this study had no role in study design, data collection, analysis or interpretation of the data, in writing the paper or the decision to submit for publication.
PubMed: 38495518
DOI: 10.1016/j.eclinm.2024.102498 -
ESMO Open Mar 2024Identifying the association between body mass index (BMI) or weight change and cancer prognosis is essential for the development of effective cancer treatments. We aimed... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Identifying the association between body mass index (BMI) or weight change and cancer prognosis is essential for the development of effective cancer treatments. We aimed to assess the strength and validity of the evidence of the association between BMI or weight change and cancer prognosis by a systematic evaluation and meta-analysis of relevant cohort studies.
METHODS
We systematically searched the PubMed, Web of Science, EconLit, Embase, Food Sciences and Technology Abstracts, PsycINFO, and Cochrane databases for literature published up to July 2023. Inclusion criteria were cohort studies with BMI or weight change as an exposure factor, cancer as a diagnostic outcome, and data type as an unadjusted hazard ratio (HR) or headcount ratio. Random- or fixed-effects models were used to calculate the pooled HR along with the 95% confidence interval (CI).
RESULTS
Seventy-three cohort studies were included in the meta-analysis. Compared with normal weight, overweight or obesity was a risk factor for overall survival (OS) in patients with breast cancer (HR 1.37, 95% CI 1.22-1.53; P < 0.0001), while obesity was a protective factor for OS in patients with gastrointestinal tumors (HR 0.67, 95% CI 0.56-0.80; P < 0.0001) and lung cancer (HR 0.67, 95% CI 0.48-0.92; P = 0.01) compared with patients without obesity. Compared with normal weight, underweight was a risk factor for OS in patients with breast cancer (HR 1.15, 95% CI 0.98-1.35; P = 0.08), gastrointestinal tumors (HR 1.54, 95% CI 1.32-1.80; P < 0.0001), and lung cancer (HR 1.28, 95% CI 1.22-1.35; P < 0.0001). Compared with nonweight change, weight loss was a risk factor for OS in patients with gastrointestinal cancer.
CONCLUSIONS
Based on the results of the meta-analysis, we concluded that BMI, weight change, and tumor prognosis were significantly correlated. These findings may provide a more reliable argument for the development of more effective oncology treatment protocols.
Topics: Humans; Female; Body Mass Index; Obesity; Cohort Studies; Breast Neoplasms; Lung Neoplasms; Gastrointestinal Neoplasms
PubMed: 38442453
DOI: 10.1016/j.esmoop.2024.102241 -
Particle and Fibre Toxicology Mar 2024Crystalline silica (cSiO) is a mineral found in rocks; workers from the construction or denim industries are particularly exposed to cSiO through inhalation. cSiO...
BACKGROUND
Crystalline silica (cSiO) is a mineral found in rocks; workers from the construction or denim industries are particularly exposed to cSiO through inhalation. cSiO inhalation increases the risk of silicosis and systemic autoimmune diseases. Inhaled cSiO microparticles can reach the alveoli where they induce inflammation, cell death, auto-immunity and fibrosis but the specific molecular pathways involved in these cSiO effects remain unclear. This systematic review aims to provide a comprehensive state of the art on omic approaches and exposure models used to study the effects of inhaled cSiO in mice and rats and to highlight key results from omic data in rodents also validated in human.
METHODS
The protocol of systematic review follows PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Eligible articles were identified in PubMed, Embase and Web of Science. The search strategy included original articles published after 1990 and written in English which included mouse or rat models exposed to cSiO and utilized omic approaches to identify pathways modulated by cSiO. Data were extracted and quality assessment was based on the SYRCLE's Risk of Bias tool for animal studies.
RESULTS
Rats and male rodents were the more used models while female rodents and autoimmune prone models were less studied. Exposure of animals were both acute and chronic and the timing of outcome measurement through omics approaches were homogeneously distributed. Transcriptomic techniques were more commonly performed while proteomic, metabolomic and single-cell omic methods were less utilized. Immunity and inflammation were the main domains modified by cSiO exposure in lungs of mice and rats. Less than 20% of the results obtained in rodents were finally verified in humans.
CONCLUSION
Omic technics offer new insights on the effects of cSiO exposure in mice and rats although the majority of data still need to be validated in humans. Autoimmune prone model should be better characterised and systemic effects of cSiO need to be further studied to better understand cSiO-induced autoimmunity. Single-cell omics should be performed to inform on pathological processes induced by cSiO exposure.
Topics: Animals; Rats; Inflammation; Lung; Proteomics; Silicon Dioxide; Silicosis; Mice
PubMed: 38429797
DOI: 10.1186/s12989-024-00573-x -
Frontiers in Immunology 2024Anaphylaxis manifests as a severe immediate-type hypersensitivity reaction initiated through the immunological activation of target B-cells by allergens, leading to the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Anaphylaxis manifests as a severe immediate-type hypersensitivity reaction initiated through the immunological activation of target B-cells by allergens, leading to the release of mediators. However, the well-known underlying pathological mechanisms do not fully explain the whole variety of clinical and immunological presentations. We performed a systemic review of proteomic and metabolomic studies and analyzed the extracted data to improve our understanding and identify potential new biomarkers of anaphylaxis.
METHODS
Proteomic and metabolomic studies in both human subjects and experimental models were extracted and selected through a systematic search conducted on databases such as PubMed, Scopus, and Web of Science, up to May 2023.
RESULTS
Of 137 retrieved publications, we considered 12 for further analysis, including seven on proteome analysis and five on metabolome analysis. A meta-analysis of the four human studies identified 118 proteins with varying expression levels in at least two studies. Beside established pathways of mast cells and basophil activation, functional analysis of proteomic data revealed a significant enrichment of biological processes related to neutrophil activation and platelet degranulation and metabolic pathways of arachidonic acid and icosatetraenoic acid. The pathway analysis highlighted also the involvement of neutrophil degranulation, and platelet activation. Metabolome analysis across different models showed 13 common metabolites, including arachidonic acid, tryptophan and lysoPC(18:0) lysophosphatidylcholines.
CONCLUSION
Our review highlights the underestimated role of neutrophils and platelets in the pathological mechanisms of anaphylactic reactions. These findings, derived from a limited number of publications, necessitate confirmation through human studies with larger sample sizes and could contribute to the development of new biomarkers for anaphylaxis.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024506246.
Topics: Humans; Anaphylaxis; Arachidonic Acid; Proteomics; Allergens; Biomarkers
PubMed: 38384462
DOI: 10.3389/fimmu.2024.1328212 -
Heliyon Feb 2024Type 2 diabetes (T2D) is a complex metabolic ailment marked by a global high prevalence and significant attention in primary healthcare settings due to its elevated...
BACKGROUND
Type 2 diabetes (T2D) is a complex metabolic ailment marked by a global high prevalence and significant attention in primary healthcare settings due to its elevated morbidity and mortality rates. The pathophysiological mechanisms underlying the onset and progression of this disease remain subjects of ongoing investigation. Recent evidence underscores the pivotal role of the intricate intercellular communication network, wherein cell-derived vesicles, commonly referred to as extracellular vesicles (EVs), emerge as dynamic regulators of diabetes-related complications. Given that the protein cargo carried by EVs is contingent upon the metabolic conditions of the originating cells, particular proteins may serve as informative indicators for the risk of activating or inhibiting signaling pathways crucial to the progression of T2D complications.
METHODS
In this study, we conducted a systematic review to analyze the published evidence on the proteome of EVs from the plasma or serum of patients with T2D, both with and without complications (PROSPERO: CRD42023431464).
RESULTS
Nine eligible articles were systematically identified from the databases, and the proteins featured in these articles underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We identified changes in the level of 426 proteins, with CST6, CD55, HBA1, S100A8, and S100A9 reported to have high levels, while FGL1 exhibited low levels.
CONCLUSION
These proteins are implicated in pathophysiological mechanisms such as inflammation, complement, and platelet activation, suggesting their potential as risk markers for T2D development and progression. Further studies are required to explore this topic in greater detail.
PubMed: 38356516
DOI: 10.1016/j.heliyon.2024.e25537 -
Fluids and Barriers of the CNS Feb 2024The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS... (Meta-Analysis)
Meta-Analysis Review
Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data.
BACKGROUND
The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS cancer, the current study aims to (1) evaluate past mass spectrometry-based workflows and (2) synthesize previous CSF proteomic data, focusing on both qualitative summaries and quantitative re-analysis. MAIN: In our analysis of 11 studies investigating the CSF proteome in pediatric patients with acute lymphoblastic leukemia (ALL) or primary brain tumors, we observed significant methodological variability. This variability negatively affects comparative analysis of the included studies, as per GRADE criteria for quality of evidence. The qualitative summaries covered 161 patients and 134 non-tumor controls, while the application of validation cohort varied among the studies. The quantitative re-analysis comprised 15 B-ALL vs 6 "healthy" controls and 15 medulloblastoma patients vs 22 non-tumor controls. Certain CSF proteins were identified as potential indicators of specific malignancies or stages of neurotoxicity during chemotherapy, yet definitive conclusions were impeded by inconsistent data. There were no proteins with statistically significant differences when comparing cases versus controls that were corroborated across studies where quantitative reanalysis was feasible. From a gene ontology enrichment, we observed that age disparities between unmatched case and controls may mislead to protein correlations more indicative of age-related CNS developmental stages rather than neuro-oncological disease. Despite efforts to batch correct (HarmonizR) and impute missing values, merging of dataset proved unfeasible and thereby limited meaningful data integration across different studies.
CONCLUSION
Infrequent publications on rare pediatric cancer entities, which often involve small sample sizes, are inherently prone to result in heterogeneous studies-particularly when conducted within a rapidly evolving field like proteomics. As a result, obtaining clear evidence, such as CSF proteome biomarkers for CNS dissemination or early-stage neurotoxicity, is currently impractical. Our general recommendations comprise the need for standardized methodologies, collaborative efforts, and improved data sharing in pediatric CNS malignancy research. We specifically emphasize the possible importance of considering natural age-related variations in CSF due to different CNS development stages when matching cases and controls in future studies.
Topics: Child; Humans; Proteome; Proteomics; Central Nervous System Neoplasms; Mass Spectrometry; Biomarkers; Cerebrospinal Fluid
PubMed: 38350915
DOI: 10.1186/s12987-024-00515-x -
Pain Physician Feb 2024Chronic cancer-related pain remains underdiagnosed and undertreated, although it affects 40% of cancer survivors. Recent insights suggest that cytokine signaling between...
BACKGROUND
Chronic cancer-related pain remains underdiagnosed and undertreated, although it affects 40% of cancer survivors. Recent insights suggest that cytokine signaling between immune, neuro, and glial cells contributes to chronic pain.
OBJECTIVES
This study systematically reviewed cytokine levels and their relation to chronic cancer-related pain and, additionally, investigated differences in cytokine levels between cancer survivors with and without chronic pain.
STUDY DESIGN
Systematic review.
METHODS
This systematic review was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA). The study conducted a systematic literature search in the databases PubMed, Web of Science, and Embase for articles examining cytokine levels and pain experience at a time point of a minimum of 3 months post-cancer diagnosis. Pain experience was categorized into a total pain score, pain intensity, and pain interference. The risk of bias was assessed using the Newcastle Ottawa Scale.
RESULTS
Eight articles were included, investigating 6 cancer types and 30 cytokines. Moderate evidence was found for pro-inflammatory cytokine IL-6 to be correlated with pain intensity, of which higher levels are observed in cancer survivors experiencing chronic pain compared to pain-free survivors. Moderate evidence was found for TNF-alpha to be not correlated with any pain experience, which is similar for anti-inflammatory cytokines IL-8 and IL-10 with pain intensity. For the remaining 26 cytokines and pain outcomes, only limited evidence was found for an association or alteration.
LIMITATIONS
The number of included studies was small. Overall, studies showed a moderate risk of bias, except one indicated a high risk of bias.
CONCLUSION
More standardized post-cancer treatment studies are warranted to confirm these results and explore associations and alterations of other cytokines. Nonetheless, moderate evidence suggests that elevated levels of IL-6, in contrast with TNF-alpha levels, are correlated with pain intensity in cancer survivors experiencing chronic pain compared to pain-free survivors.
Topics: Humans; Cytokines; Tumor Necrosis Factor-alpha; Chronic Pain; Interleukin-6; Cancer Survivors; Cancer Pain; Neoplasms
PubMed: 38324786
DOI: No ID Found -
BMC Medicine Jan 2024Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk...
BACKGROUND
Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality.
METHODS
We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies-of Exposure tool.
RESULTS
Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies.
CONCLUSIONS
In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.
Topics: Humans; Heart Failure; Proteomics; Stroke Volume; Ventricular Dysfunction, Left
PubMed: 38273315
DOI: 10.1186/s12916-024-03249-7