Disease Biomarkers Research Articles

Translational Strategy to Evaluate Urinary Plasminogen as a Targetable Biomarker of Glomerular Diseases

Translational Strategy to Evaluate Urinary Plasminogen as a Targetable Biomarker of Glomerular Diseases

Soluble Proteoglycans and Proteoglycan Fragments as Biomarkers of Pathological Extracellular Matrix Remodeling

ABSTRACTProteoglycans and their proteolytic fragments diffuse into biological fluids such as plasma, serum, urine, or synovial fluid, where they can be detected by antibodies or mass‐spectrometry. Neopeptides generated by the proteolysis of proteoglycans are recognized by specific neoepitope antibodies and can act as a proxy for the activity of certain proteases. Proteoglycan and proteoglycan fragments can be potentially used as prognostic, diagnostic, or theragnostic biomarkers for several diseases characterized by dysregulated extracellular matrix remodeling such as osteoarthritis, rheumatoid arthritis, atherosclerosis, thoracic aortic aneurysms, central nervous system disorders, viral infections, and cancer. Here, we review the main mechanisms accounting for the presence of soluble proteoglycans and their fragments in biological fluids, their potential application as diagnostic, prognostic, or theragnostic biomarkers, and highlight challenges and opportunities ahead of their clinical translation.

Effect of nuts on lipid profile and inflammatory biomarkers in atherosclerotic cardiovascular disease: a systematic review and meta-analysis of randomized controlled trials.

Nut-enriched diets are related to improve lipid and inflammatory biomarkers in meta-analyses in the context of primary cardiovascular prevention. However, primary studies on secondary cardiovascular prevention are scarce and controversial. This systematic review and meta-analysis aimed to evaluate the effect of nut supplementation on lipid and inflammatory profiles in individuals with atherosclerotic cardiovascular disease, and the frequency of adverse events. Six databases were used for research: PubMed, EMBASE, BVS, Cochrane Library, Web of Science, and ClinicalTrials.gov, until February 2023, with no language restrictions. We performed random-effects meta-analyses to compare nut-enriched diets vs. control diets for pre-post intervention changes. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system assessed the evidence's certainty. From the 5187 records identified, eight publications containing data referring to five randomized clinical trials involving 439 participants were included in the final analyses. The nuts evaluated were almonds, pecans, Brazil nuts, and mixed nuts, with doses ranging between 5g and 85g (median: 30g/day). The intervention time varied between 6 and 12 weeks. Compared to nut-free diets, nut intake did not have a statistically significant effect on lipid profile biomarkers, except on the atherogenic index (MD: -0.32 [95% CI -0.58 to -0.06], I2 = 0% - moderate certainty of the evidence). Similarly, there was no effect of nuts on inflammatory profile biomarkers. It was not possible to aggregate data on adverse events. Nut supplementation did not change lipid and inflammatory profiles in the secondary cardiovascular prevention setting.

Glomerular filtration rate determined by measuring serum clearance of iohexol in unanesthetized cheetahs (Acinonyx jubatus) with comparison to serum symmetric dimethylarginine.

One of the more common diseases affecting zoo-managed cheetahs (Acinonyx jubatus) is chronic renal disease, which can impact their welfare and ultimately shortens their lifespan. Early diagnosis, for which estimating Glomerular Filtration Rate (GFR) is one such tool, is imperative to help mitigate the negative impacts of this insidious disease. GFR was determined by measuring the serum clearance of iohexol in nine clinically normal, cheetahs managed under human care that presented for voluntary blood collection. A 2-sample iohexol clearance method was performed, along with serum symmetric dimethylarginine (SDMA) determination. SDMA has shown promise in humans, dogs, and cats, as an early biomarker of renal disease. Additionally, the relationship between GFR and SDMA, along with serum creatinine and BUN were analyzed. The mean values for the uncorrected GFR and corrected GFR were 2.08 ± 0.215 mL/min/kg body weight and 1.87 ± 0.173 mL/min/kg body weight, respectively. No significant correlations were observed between GFR, SDMA, serum creatinine, or BUN. Both the uncorrected and corrected iohexol-based GFR values were similar to an inulin-based GFR reference interval determined in zoo managed cheetahs and a reported domestic cat iohexol-based GFR reference interval. Serum SDMA values support previous research suggesting cheetahs have a separate reference interval from domestic cats (0-14 μg/dL). Measuring GFR by the serum clearance of iohexol shows promise as a readily available, cheap, and easily administered clearance marker that can be used in cheetahs trained for voluntary blood collection, thereby avoiding the need for anesthesia.

Methylation of Selected CpG-Sites of the Gene CSF1 as a Factor in Regulation of Its Expression and a Marker of Human Biological Aging

—Age-associated transformation of methylation patterns is considered to be an important predictor of human biological age. Changes in the level of CpG-dinucleotide methylation contribute to a shift in the function of a number of genes, including those associated with the functioning of the immune system. One such gene is CSF1. The protein product of this gene is associated with inflammatory aging, making it an important biomarker of age-related diseases. We studied the methylation profile of the promoter-associated CpG island of the CSF1 gene by MALDI-TOF mass spectrometry. Dependences between the character of CpG-site methylation within the investigated regions and the relative level of the gene mRNA and its protein product in people of different age groups were sought. For two CpG sites, a high level of correlation with the studied parameters is shown. A search for the landing sites of transcription factor binding sites associated with gene transcription showed that these CpG dinucleotides are part of motifs for the NFI family transcription factors and the EGR1 factor. We hypothesize that these CpG sites play an important role in the regulation of CSF1 gene expression.

Non-enzymatic cholesterol biosensor: Electrochemical sensing based on peptide-polylactic acid thin film

Cholesterol is a fundamental lipid prevalent in eukaryotic cell membranes and circulating in the bloodstream bound to lipoproteins. It serves as a precursor to steroid hormones and is regarded as a biomarker for cardiovascular disease and other metabolic disorders. Numerous cholesterol detection methods predominantly rely on enzymes, which suffer from instability, leading to non-cost-effective biosensors with low sensitivity and poor reusability. Therefore, monitoring cholesterol levels with a feasible, rapid, and stable biosensor is critical for diagnosing and treating various disorders. This study aimed to develop a non-enzymatic cholesterol biosensor based on a selected cholesterol recognition peptide as the detection element. Screen-printed carbon electrodes (SPEs) modified with biocompatible poly-L-lactic acid (PLLA) porous nanomembranes (NMs) were utilized as support for the covalent immobilization of the peptide. Data obtained from electrochemical impedance spectroscopy (EIS) demonstrated the peptide's effective binding affinity towards cholesterol, paving the way for its implementation. The determination of cholesterol with the proposed biosensor exhibited a low limit of detection of 6.31 μM with linear responses ranging from 2–15 μM and 20–40 μM. These findings present an alternative method for cholesterol sensing by integrating novel peptides as biorecognition motifs with biocompatible polymeric materials, potentially useful as biocompatible and future point-of-care sensors.

Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design

ObjectiveDespite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can...

MicroRNAs as diagnostic biomarkers in cardiovascular diseases that cause sudden cardiac death: comparison between methods used in discovery and validation phases in major research studies

MicroRNAs as diagnostic biomarkers in cardiovascular diseases that cause sudden cardiac death: comparison between methods used in discovery and validation phases in major research studies

A French multicenter analytical evaluation of the automated Lumipulse G sNfL blood assay (Fujirebio®) and its comparison to four other immunoassays for serum neurofilament light chain assessment in clinical settings

ObjectivesMeasurement of serum neurofilament light chain (sNfL) protein is becoming a key biomarker for many neurological diseases. Several immunoassays have been developed to meet these clinical needs, revealing significant differences in terms of variability and results. Here, we propose a French multicenter comparison of 5 sNfL assays. Methods6 replicates of 3 pools with low (10 pg/mL), medium (30 pg/mL) and high (100 pg/mL) sNfL values and one replicate of 12 samples with growing sNfL values were analyzed by six independent French clinical laboratories. The analytical performances of the sNfL blood assay (Fujirebio®) on Lumipulse G were first evaluated then compared to four other immunoassays: NF-light V2 (Quanterix®) on SiMOA HD-X, Human NF-L (Biotechne®) on Ella, R-Plex Human Neurofilament L (MSD®) on Sector 2400; manual ELISA test using Uman Diagnostic/Quanterix®. ResultsInter-center comparison of the Lumipulse blood assay revealed limited but significant differences in the mean sNfL values across low, medium, and high pools between each city (p < 0.001) and between the two different batches used. Coefficients of variation of pools ranged from 2.0 to 16.9 %. Z-score of sNfL results of the 12 samples ranged from −1.70 to +1.71. Inter-technique comparison showed a systematic difference of sNfL values, with a overestimation of MSD and Ella over other tests. Nonetheless, results were all significantly correlated (p < 0.001). ConclusionThe automated Lumipulse assay produced comparable sNfL values across laboratories; but further adjustments are needed to harmonize sNfL results. Biologists and physicians should be aware of the variability in results between different immunoassay suppliers.

Non-Alzheimer's amnestic mild cognitive impairment with medial temporal hypometabolism.

The increasing use of Alzheimer's disease (AD) biomarkers has led to the recognition of a subgroup of non-AD amnestic mild cognitive impairment (aMCI) patients who have medial temporal hypometabolism on fluorodeoxyglucose-positron emission tomography (FDG-PET). In this academic memory-clinic-based consecutive series, 16 non-AD aMCI patients and 28 AD controls matched for sex, age, and baseline Mini-Mental State Examination (MMSE) were followed for a median duration of 4.5 years. Our primary outcome was the MMSE decline rate over the subsequent years. We also determined the final diagnosis over time. FDG-PET showed more pronounced medial temporal hypometabolism in non-AD cases and more inferior parietal lobule hypometabolism in AD controls. MMSE decline was slower in non-AD (β=-0.51) than in AD (β=-2.00) patients. Five non-AD cases developed frontotemporal dementia years after symptom onset, and one developed dementia with Lewy bodies. Non-AD aMCI patients with medial temporal hypometabolism show slower cognitive decline. Non-AD aMCI with medial temporal hypometabolism shows slower cognitive decline than AD.FDG-PET revealed distinct metabolic patterns between non-AD aMCI and AD patients.Approximately one-third of non-AD aMCI cases developed frontotemporal dementia.Comprehensive diagnostic biomarkers are crucial for non-AD aMCI characterization.

Psychological outcomes of dementia risk estimation in MCI patients: Results from the PreDADQoL project.

Understanding the impact of biomarker-based dementia risk estimation in people with mild cognitive impairment (MCI) and their care partners is critical for patient care. MCI patients and study partners were counseled on Alzheimer's disease (AD) biomarker and dementia risk was disclosed. Data on mood, quality of life (QoL), and satisfaction with life (SwL) were obtained 1 week and 3 months after disclosure. Seventy-six dyads were enrolled, and two-thirds of the patients opted for biomarker testing. None of the participants experienced clinically relevant depression or anxiety after disclosure. All dyads reported moderate to high QoL and SwL throughout the study. Patients reported more subthreshold depressive symptoms 1 week and lower QoL and SwL 3 months after disclosure. In patients, depression (odds ratio [OR]: 0.76) and anxiety (OR: 0.81) were significant predictors for the decision against biomarker testing. No major psychological harm is to be expected in MCI patients and care partners after dementia risk disclosure. This study is registered in the German clinical trials register (Deutsches Register Klinischer Studien, DRKS): http://www.drks.de/DRKS00011155, DRKS registration number: DRKS00011155, date of registration: 18.08.2017. Patients with mild cognitive impairment (MCI) and study partners were counseled on Alzheimer's disease (AD) biomarker-based dementia risk estimation. About two-thirds of patients opted for biomarker testing and received their dementia risk based on their AD biomarker status. Patients who decided in favor or against CSF biomarker testing differed in psychological features. We did not observe major psychological harm after the dementia risk disclosure. Coping strategies were associated with better subsequent mood and well-being in all participants.

How fiber bundle alterations differ in presumed LATE and amnestic Alzheimer's disease.

Typical Alzheimer's disease (AD) and limbic-predominant age-related TAR DNA-binding protein 43 (TDP-43) encephalopathy (LATE) are two neurodegenerative diseases that present with a similar initial amnestic clinical phenotype but are associated with distinct proteinopathies. We investigated white matter (WM) fiber bundle alterations, using fixel-based analysis, a state-of-the-art diffusion magnetic resonance imaging model, in early AD, presumed LATE, and controls. We also investigated regional cortical atrophy. Both amnestic AD and presumed LATE patients exhibited WM alterations in tracts of the temporal and limbic lobes and in callosal fibers connecting superior frontal gyri. In addition, presumed LATE patients showed alterations in callosal fibers connecting the middle frontal gyri and in the cerebello-thalamo-cortical tract. Cortical thickness was reduced in regions connected by the most altered tracts. These findings, the first to describe WM fiber bundle alterations in presumed LATE, are consistent with results on cortical atrophy and with the staging system of tau or TDP-43 accumulation. Fixel-based analysis revealed white matter (WM) fiber bundle alterations in presumed limbic-predominant age-related TAR DNA-binding protein 43 encephalopathy (LATE) patients identified by isolated episodic/limbic amnesia, the absence of positive Alzheimer's disease (AD) biomarkers, and no other neurological diagnosis after 2 years of follow-up. Presumed LATE and amnestic AD shared similar patterns of WM alterations in fiber bundles of the limbic and temporal lobes, in congruence with their similar limbic cognitive phenotype. Presumed LATE differed from AD by the alteration of the callosal fibers connecting the middle frontal gyri and of the cerebello-thalamo-cortical tract. WM fiber bundle alterations were consistent with results on regional cortical atrophy. The different anatomical patterns of WM degeneration could provide information on the propagation pathways of distinct proteinopathies.

Multidisciplinary approach to redefining thyroid hormone reference intervals with big data analysis

ObjectivesThis study aimed to employ big data analysis to harmonize reference intervals (RI) for thyroid function tests, with refinement to the TSH upper reference limit, and to optimize the TSH reflex algorithm to improve clinical management and test utilization. Design & methodsTSH, free T4, and free T3 results tested in Alberta, Canada, on Roche Cobas and Siemens Atellica were extracted from the laboratory information system (N = 1,144,155 for TSH, N = 183,354 for free T4 and N = 92,632 for free T3). Results from specialists, inpatients, or repeat testing, as well as from positive thyroid disease, autoimmune disease, and pregnancy biomarkers were excluded. RIs were derived using statistical models (Bhattacharya, refineR, and simple non-parametric) followed by endocrinology and laboratory review. ResultsThe TSH RIs for 0 to 7 days, 8 days to 1 year, and ≥1 year were 1.23 to 25.0 mIU/L, 1.00 to 6.80 mIU/L and 0.20 to 6.50 mIU/L, respectively. The free T4 RIs for 0 to 14 days, 15 to 29 days, and ≥30 days were 13.5 to 50.0 pmol/L, 8.7 to 32.5 pmol/L, and 10.0 to 25.0 pmol/L, respectively. An updated TSH reflex algorithm was developed based on the optimized TSH and free T4 RIs, with free T4 reflexed only at a TSH of <0.1 mIU/L. ConclusionsThe collaboration of a multidisciplinary team and the utilization of big data analysis led to the enhancement of thyroid function RIs, specifically resulting in the widening of the upper TSH reference limit to 6.50. Application of these optimized RIs with the TSH reflex algorithm will serve as a guide for improvement in interpretation of thyroid function tests.

CISL-PD: A deep learning framework of clinical intervention strategies for Parkinson’s disease based on directional counterfactual Dual GANs

Parkinson’s disease (PD) is a prevalent chronic neurodegenerative disorder characterized by both motor and non-motor symptoms. The significant heterogeneity among PD patients poses a major challenge for treatment interventions. Current clinical interventions for PD primarily target motor symptoms, often neglecting non-motor symptoms, which can lead to unnecessary complications in non-motor symptoms while treating motor symptoms. Therefore, it is crucial to provide comprehensive and precise intervention strategies that encompass both symptom types. To address this issue, we develop a deep learning framework of clinical intervention strategies for PD (CISL-PD) based on counterfactual thinking. This framework introduces Directional Counterfactual Dual Generative Adversarial Networks (DCD-GANs), which apply various counterfactual constraints to longitudinal data to generate practical and plausible counterfactual instances aligned with clinical reality. By analyzing these counterfactual instances and their differences from the original instances, we explore PD intervention strategies with duration-specific fine regulation of multidimensional features. Experiments conducted on 374 PD patients from the Parkinson’s Progression Markers Initiative (PPMI) demonstrate that the counterfactual instances generated by DCD-GANs surpass other state-of-the-art models in terms of similarity (0.307 ± 0.246), sparsity (0.513 ± 0.161), smoothness (0.238 ± 0.135), and trend consistency (0.100 ± 0.089). From these generated counterfactual instances, we develop three clinically feasible intervention strategies that address both motor and non-motor symptoms and identify corresponding patterns of PD with distinct progression differences. Validation on an independent cohort of 351 patients from the National Institute of Neurological Disorders and Stroke Parkinson’s Disease Biomarkers Program (PDBP) confirmed the framework’s robustness and generalizability. By offering precise, multidimensional intervention strategies that can address both motor and non-motor symptoms, the CISL-PD framework has the potential to enhance patient outcomes, reduce complications, improve overall quality of life, and guide clinical decision-making.

Heat-shock protein 27 (HSP27) not just a biomarker of cardiac and renal diseases

Heat-shock protein 27 (HSP27) not just a biomarker of cardiac and renal diseases

Comparative accuracy of CA-153 and KL-6 as diagnostic and prognostic biomarkers for interstitial lung disease

BackgroundsTo discern the potential of KL-6 and CA-153 as diagnostic tools for interstitial lung disease (ILD), understand their relationship with GAP (Gender, Age, and Physiology) stage, and analyze their predictive capacities alongside CT features. This research aims to enhance ILD detection and management in autoimmune patients, emphasizing the diagnostic utility of these biomarkers. MethodsFrom Mar 2017 to Mar 2024, 398 patients from Taichung Veterans General Hospital’s Division of Allergy, Immunology, and Rheumatology with autoimmune diseases were prospectively enrolled. ILD diagnoses were confirmed using High-Resolution Computed Tomography (HRCT) or lung biopsy and characterized by radiologists. GAP scores were calculated for IPF prognosis. 583 serum samples were collected and tested for KL-6, CA-153, CA-199, and CA-125 using specific assays. Statistical analyses compared patients, assessed variables, determined missingness, and predicted ILD, with tools like ROC analysis and logistic regressions. Analyses were performed with IBM SPSS and MedCalc. ResultsILD patients were older, predominantly male, and had more smokers compared to non-ILD. Both KL-6 and CA-153 were higher in ILD and showed a significant, but non-interchangeable correlation. Age, BMI, smoking, and biomarker levels influenced ILD odds, with KL-6 and CA-153 being the strongest predictors. HRCT imaging highlighted these markers’ roles, especially in detecting specific features. Both markers also strongly associated with GAP stages. Stratified analyses emphasized KL-6′s significance in predicting ILD across both AD and non-AD groups. Complete data sensitivity analysis reinforced KL-6 and CA-153 as key ILD predictors. ConclusionsThis research emphasizes CA-153 as a feasible, cost-effective alternative to KL-6 in diagnosing and monitoring ILD. Both CA-153 and KL-6 levels were notably elevated in ILD patients, displaying a strong correlation, especially at CA-153 levels of ≤100 U/ml. They both also have significant associations with CT characteristics and GAP stages. The study reinforces the potential of CA-153, particularly in settings where KL-6 testing might be inaccessible or expensive.

Oral and Gingival Crevicular Fluid Biomarkers for Jawbone Turnover Diseases: A Scoping Review

Gingival crevicular fluid (GCF) and oral fluid have emerged as promising diagnostic tools for detecting biomarkers. This review aimed to evaluate the existing literature on using oral fluids as a source of biomarkers for bone turnover diseases affecting the jawbone. A comprehensive search strategy was executed between August 2014 and August 2024 across five major databases (Web of Science, EBSCOhost Dentistry &amp; Oral Sciences Source, Cochrane Library, Scopus, and PubMed) and grey literature sources. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was applied. The screening was facilitated using Rayyan at rayyan.ai and Endnote X20 software tools, culminating in the evaluation of 14,965 citations from databases and 34 from grey literature. Following rigorous scrutiny, 37 articles were selected for inclusion in this review, encompassing diseases such as periodontitis, medication-related osteonecrosis of the jaw (MRONJ), and osteoporosis. The quality of the included observational studies was assessed using the Revised Risk of Bias Assessment Tool for Non-Randomized Studies (RoBANS 2). Interleukin-1 beta (IL-1β), sclerostin, osteoprotegerin (OPG), and interleukin-34 (IL-34) emerged as significant biomarkers in GCF, and they were mainly from periodontitis and osteoporosis. Osteocalcin (OC), IL-1β, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), OPG, and matrix metalloproteinase-9 (MMP-9) were significant in oral fluid or saliva, and they were from periodontitis, MRONJ, and osteoporosis. These findings underscore the potential use of oral fluids, which are regarded as non-invasive tools for biomarker identification in bone turnover. Many biomarkers overlap, and it is important to identify other specific biomarkers to enable accurate diagnosis of these conditions.

N-terminal pro-B-type natriuretic peptide, eGFR, and progression of kidney disease in chronic kidney disease patients without heart failure.

Cardiorenal syndrome highlights the bidirectional relationship between kidney and heart dysfunction. N-terminal pro-B-type natriuretic peptide (NT-proBNP), which is the gold standard biomarker in heart failure (HF), may be an important biomarker for chronic kidney disease (CKD) progression. However, NT-proBNP is negatively related with estimated glomerular filtration rate (eGFR). In this study, we investigated the association of NT-proBNP, eGFR, and progression of kidney disease in CKD patients without HF. This multicentric retrospective cohort study recruited 23 860 CKD patients without HF, who had at least one NT-proBNP record from China Renal Data System database. Linear regression model evaluated the relationship between eGFR and NT-proBNP. Cox regression analysis assessed the association between NT-proBNP and CKD progression. Sensitivity analysis examined the robustness of the main findings. This study involved 23 860 CKD patients without HF, distributed across different CKD stages: 10 526 in stages G1-2, 4665 in G3a, 3702 in G3b, 2704 in G4, and 2263 in G5. NT-proBNP was negatively correlated with eGFR, particularly in stages 4-5 CKD. A 15-unit decrease in eGFR was associated with increases in log (NT-proBNP) levels by 1.04-fold, 1.27-fold, 1.29-fold, 1.80-fold, and 3.50-fold for stages 1-2, 3a, 3b, 4, and 5, respectively. After excluding patients who developed CKD progression within 1 year, the Cox regression analysis revealed that the relationship between NT-proBNP and CKD progression was not significant in stages 4 and 5. However, for stages 1-3, each standard deviation increase in log (NT-proBNP) was associated with a 26%, 36%, and 28% higher risk of CKD progression, with P interaction ≤.001. The hazard ratios were 1.26 (95% confidence intervals (CI), 1.18 to 1.35), 1.36 (95% CI, 1.22 to 1.51), and 1.28 (95% CI, 1.14 to 1.43) for stages 1-2, stage 3a, and stage 3b, respectively. Despite its strong inverse association with eGFR, NT-proBNP was positively associated with the risk of progression of kidney disease in CKD patients with stages 1-3 without HF. Future studies should investigate the effectiveness of NT-proBNP as a predictive biomarker for the progression of kidney disease across diverse racial groups and healthcare settings.

Development of an ultrasound-based metric of muscle functional capacity for use in patients with neuromuscular disease.

Spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD) are progressive neuromuscular disorders characterized by severe muscle weakness and functional decline (Pillen et al., Muscle Nerve 2008; 37(6):679-693). With new therapeutics, objective methods with increased sensitivity are needed to assess muscle function. Ultrasound imaging is a promising approach for assessing muscle fat and fibrosis in neuromuscular disorders. This study builds on prior work by combining ultrasound-based measurements of muscle size, shape, and quality, relating these measures to muscle strength, and proposing a multivariable image-based estimate of muscle function. Maximum voluntary elbow flexion torque of 36 participants (SMA, DMD, and healthy controls) was measured by hand-held dynamometry and elbow flexor muscles were imaged using ultrasound. Muscle size (cross-sectional area, maximum Feret diameter or width, and thickness), quality (echogenicity, texture anisotropy index), and cross-sectional shape (diameter ratio) were measured. Multivariable regression was used to select ultrasound measurements that predict elbow flexion torque. Significant differences were observed in muscle size (decreased), shape (thinned), and quality (decreased) with increased disease severity and compared to healthy participants. CSA (brachioradialis R2 = 0.51), maximum Feret diameter (biceps R2 = 0.49, brachioradialis R2 = 0.58) and echogenicity (brachioradialis R2 = 0.61) were most correlated with torque production. Multivariable regression models identified that muscle size (CSA, maximum Feret diameter) and quality (echogenicity) were both essential to predict elbow flexion torque (R2 = 0.65). A multivariable approach combining muscle size and quality improves strength predictions over single variable approaches. These methods present a promising avenue for the development of sensitive and functionally relevant biomarkers of neuromuscular disease.

Циркулирующие микроРНК тромбоцитарного происхождения как потенциальные биомаркеры STEMI у пациентов с гипертонической болезнью

Background: Circulating extracellular platelet-derived microRNAs have been actively studied over the last decade as promising biomarkers of cardiovascular disease (CVD), since platelet activation plays a key role in the pathogenesis of CVD. The aim of the study: To compare platelet-derived microRNA profiles in patients with uncomplicated hypertension (HT) and in patients with HT and acute myocardial infarction with ST-segment elevation (STEMI). Materials and methods: The study included 20 patients with uncomplicated HT and 15 patients with HT and STEMI. At least 90% of the participants in each group received antiplatelet therapy. A blood sample was collected from each patient in a CTAD anticoagulant tube and blood plasma was obtained by two-step centrifugation. The degree of hemolysis of the plasma samples was determined spectrophotometrically. MicroRNAs were isolated from plasma samples and used for reverse transcription and quantification of relative levels of eight main circulating extracellular platelet-derived microRNAs (miR-223-3p, miR-126-3p, miR21-5p, miR-24-3p, miR-320a-3p, miR-191-5p, miR-150-5p and miR-23a-3p) by quantitative PCR using the TaqMan Advanced technology (Thermo Fisher Scientific, USA). Normalized relative expression levels for each miRNA were calculated. Differences were considered statistically significant at p &lt; 0.05 (Mann-Whitney test). Results: Patient groups did not differ in age, BMI, platelet count, lipid profile and degree of hemolysis of plasma samples. No differences were found between the ratio of platelet-derived and erythrocyte-derived microRNA between patient groups. No statistically significant differences were found in the relative levels of circulating microRNA between the study groups. Principal component analysis and heatmap analysis of microRNA expression in the samples showed a division of the samples into groups based more on the degree of hemolysis than on the presence/absence of STEMI. Conclusion: In the studied sample of hypertensive patients, the effect of hemolysis of plasma samples on circulating platelet-derived microRNA profiles was more significant than the presence of STEMI.