Biomarker Profiles Research Articles

Profile of immunological biomarkers in Behcet’s syndrome: a large-scale single-center real-world study

Behcet's syndrome (BS) is a vasculitis characterized by immune dysregulation. Biomarkers are valuable for assessing clinically atypical pathogenesis. We aimed to investigate the distribution of different biomarkers and their effects on the clinical features of patients with BS in a large-scale, real-world study. This is a retrospective, single-center study. In total, 502 patients diagnosed with BS were enrolled in this study. We analyzed the clinical features of this cohort and divided patients’ symptoms into six categories, including mucocutaneous, articular, neurological, gastrointestinal, vascular, and ocular involvements. HLA-B51 cells, autoantibodies, and subsets of immune cells from the patients were tested. Pearson’s correlation, Wilcoxon rank sum test and multivariate logistic regression were used for data analysis. Various autoantibodies were detected in the serum of 40.8% of patients with BS. The positivity rate of anti-endothelial cell antibodies (AECA) was the highest among autoantibodies and was found in 23.5% (118/502) of patients with BS. The positivity rate of HLA-B51 in patients with BS was 27.1%. Tumor necrosis factor (TNF)-α, IL-2, and IL-4 producing CD4+ T cells were positively correlated with the gastrointestinal BS. Increased IL-4+CD4+ T cell was a risk factor for gastrointestinal BS (P = 0.006, Overall rate [OR] = 2.491, 95% Confidence interval [CI]: [1.317, 5.100]). Various autoantibodies can be detected in patients with BS. HLA-B51 and AECA are the most common biomarkers. Increased IL-4+ CD4+ T cell was a risk factor for gastrointestinal involvement in BS.

Neck and shoulder pain and inflammatory biomarkers in plasma among forklift truck operators - A case-control study.

The aim of this study was to investigate a panel of inflammatory biomarkers in plasma from forklift truck operators (FLTOs) and healthy controls, and their relation to neck pain characteristics. From employees in a warehouse, 26 FLTOs were recruited and 24 healthy age- and sex-matched controls (CONs) were recruited via advertisement. The inclusion criterion for FLTOs was that they should operate reach decker and/or counterbalanced tilting mast forklift trucks. All participants were asked to answer a questionnaire covering demographic data, pain intensity numeric rating scale (NRS), anatomical spread, psychological distress, and health aspects. Pain sensitivity was measured using a pressure algometer. Blood samples were collected and analyzed for inflammatory proteins in plasma using a panel of 71 cytokines and chemokines. Multivariate data analysis including orthogonal partial least square-discriminant analysis (OPLS-DA) was performed to identify significant biomarkers. Thirty percent of FLTOs reported NRS > 3 in the neck. Shoulder pain was common in 26% of the FLTOs. Pain and discomfort that most often prevented completion of activities were in the neck (20%), lower back (32%), and hips (27%). The FLTOs reported significantly (p = 0.04) higher levels of anxiety than the CON group and they had significantly lower pressure pain thresholds in the trapezius muscle on both right (p < 0.001) and left sides (p = 0.003). A significant OPLS-DA model could discriminate FLTOs from CON based on nine inflammatory proteins where the expression levels of four proteins were upregulated and five proteins were downregulated in FLTOs compared to CONs. Twenty-nine proteins correlated multivariately with pain intensity. The profile of self-reported health, pain intensity, sensitivity, and plasma biomarkers can discriminate FLTOs with pain from healthy subjects. A combination of both self-reported and objective biomarker measurements can be useful for better understanding the pathophysiological mechanisms underlying work-related neck and shoulder pain.

First Biodistribution Study of [68Ga]Ga-NOTA-Insulin Following Intranasal Administration in Adult Vervet Monkeys.

Intranasal insulin (INI) is being explored as a treatment for Alzheimer's disease (AD). Improved memory, functional ability, and cerebrospinal fluid (CSF) AD biomarker profiles have been observed following INI administration. However, the method of intranasal delivery may significantly affect outcomes. To show reliable delivery of insulin to the brain using the Aptar Cartridge Pump System (CPS) intranasal delivery system. To visualize INI biodistribution, we developed a novel PET radiotracer, Gallium 68-radiolabeled (NOTA-conjugated) insulin, [68Ga]Ga-NOTA-insulin. We used the Aptar CPS to administer [68Ga]Ga-NOTA-insulin to anesthetized healthy adult vervet monkeys and measured brain regional activity and whole-body dosimetry following PET/CT scans. We observed brain penetration of [68Ga]Ga-NOTA-insulin following intranasal administration with the Aptar CPS. Radioactive uptake was seen in multiple regions, including the amygdala, putamen, hypothalamus, hippocampus, and choroid plexus. A safety profile and whole-body dosimetry were also established in a second cohort of vervets. Safety was confirmed: vitals remained stable, blood glucose levels were unchanged, and no organ was exposed to more than 2.5 mSv of radioactivity. Extrapolations from vervet organ distribution allowed for estimation of the [68Ga]Ga-NOTA-insulin absorbed dose in humans, and the maximum dose of [68Ga]Ga-NOTA-insulin that can be safely administered to humans was determined to be 185 MBq. The use of [68Ga]Ga-NOTA-insulin as a PET radiotracer is safe and effective for observing brain uptake in vervet monkeys. Further, the Aptar CPS successfully targets [68Ga]Ga-NOTA-insulin to the brain. The data will be essential in guiding future studies of intranasal [68Ga]Ga-NOTA-insulin administration in humans.

Tau PET positivity predicts clinically relevant cognitive decline driven by Alzheimer's disease compared to comorbid cases; proof of concept in the ADNI study.

β-amyloid (Aβ) pathology is not always coupled with Alzheimer's disease (AD) relevant cognitive decline. We assessed the accuracy of tau PET to identify Aβ(+) individuals who show prospective disease progression. 396 cognitively unimpaired and impaired individuals with baseline Aβ and tau PET and a follow-up of ≥ 2 years were selected from the Alzheimer's Disease Neuroimaging Initiative dataset. The participants were dichotomously grouped based on either clinical conversion (i.e., change of diagnosis) or cognitive deterioration (fast (FDs) vs. slow decliners (SDs)) using data-driven clustering of the individual annual rates of cognitive decline. To assess cognitive decline in individuals with isolated Aβ(+) or absence of both Aβ and tau (T) pathologies, we investigated the prevalence of non-AD comorbidities and FDG PET hypometabolism patterns suggestive of AD. Baseline tau PET uptake was higher in Aβ(+)FDs than in Aβ(-)FD/SDs and Aβ(+)SDs, independently of baseline cognitive status. Baseline tau PET uptake identified MCI Aβ(+) Converters and Aβ(+)FDs with an area under the curve of 0.85 and 0.87 (composite temporal region of interest) respectively, and was linearly related to the annual rate of cognitive decline in Aβ(+) individuals. The T(+) individuals constituted largely a subgroup of those being Aβ(+) and those clustered as FDs. The most common biomarker profiles in FDs (n = 70) were Aβ(+)T(+) (n = 34, 49%) and Aβ(+)T(-) (n = 19, 27%). Baseline Aβ load was higher in Aβ(+)T(+)FDs (M = 83.03 ± 31.42CL) than in Aβ(+)T(-)FDs (M = 63.67 ± 26.75CL) (p-value = 0.038). Depression diagnosis was more prevalent in Aβ(+)T(-)FDs compared to Aβ(+)T(+)FDs (47% vs. 15%, p-value = 0.021), as were FDG PET hypometabolism pattern not suggestive of AD (86% vs. 50%, p-value = 0.039). Our findings suggest that high tau PET uptake is coupled with both Aβ pathology and accelerated cognitive decline. In cases of isolated Aβ(+), cognitive decline may be associated with changes within the AD spectrum in a multi-morbidity context, i.e., mixed AD.

ASO Visual Abstract: Change in Biomarker Profile After Neoadjuvant Chemotherapy is Prognostic and is Common in Patients with HER2+ Breast Cancer.

ASO Visual Abstract: Change in Biomarker Profile After Neoadjuvant Chemotherapy is Prognostic and is Common in Patients with HER2+ Breast Cancer.

Vulnerable plaques on CCTA and biomarker profile in patients with acute coronary syndrome (preliminary results of the Combi-LLT ACS study (NCT05624658)

Vulnerable plaques on CCTA and biomarker profile in patients with acute coronary syndrome (preliminary results of the Combi-LLT ACS study (NCT05624658)

The role of puff volume in vaping emissions, inhalation risks, and metabolic perturbations: a pilot study

Secondhand vaping exposure is an emerging public health concern that remains understudied. In this study, saliva and exhaled emissions from ENDS users (secondhand) and non-ENDS users (baseline) were collected, firsthand emissions were generated using an automated ENDS aerosol generation system programmed to simulate puffing topography profiles collected from ENDS users. Particulate concentrations and sizes along with volatile organic compounds were characterized. We revealed puffing topography metrics as potential mediators of firsthand and secondhand particle and chemical exposures, as well as metabolic and respiratory health outcomes. Particle deposition modeling revealed that while secondhand emissions displayed smaller deposited mass, total and pulmonary particle deposition fractions were higher than firsthand deposition levels, possibly due to smaller secondhand emission particle diameters. Lastly, untargeted metabolomic profiling of salivary biomarkers of lung injury due to firsthand ENDS exposures revealed potential early indicators of respiratory distress that may also be relevant in bystanders exposed to secondhand vaping scenarios. By leveraging system toxicology, we identified 10 metabolites, including leukotriene D4, that could potentially serve as biomarkers for ENDS use, exposure estimation, and the prediction of vaping-related disease. This study highlights characterization of vaping behavior is an important exposure component in advancing our understanding of potential health effects in ENDS users and bystanders.

CSF markers of neurodegeneration Alzheimer’s and Lewy body pathology in isolated REM sleep behavior disorder

We investigated the biomarker profile of neurodegeneration, Alzheimer’s and Lewy body pathology in the CSF of 148 polysomnography-confirmed patients with isolated REM sleep behavior disorder (IRBD), a condition that precedes Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). We assessed misfolded α-synuclein (AS) by RT-QuIC assay, amyloid-beta peptides (Aβ42 and Aβ40), phosphorylated tau (p-tau), and total tau (t-tau) by CLEIA and neurofilament light chain (NfL) by ELISA. We detected AS in 75.3% of patients, pathologically decreased Aβ42/Aβ40 ratio in 22.5%, increased p-tau in 15.5%, increased t-tau in 14.9%, and elevated NfL in 14.7%. After a mean follow-up of 2.48 ± 2.75 years, 47 (38.1%) patients developed PD (n = 24) or DLB (n = 23). At CSF collection, AS positivity [HR 4.05 (1.26–12.99), p = 0.019], mild cognitive impairment [3.86 (1.96–7.61), p < 0.001], and abnormal DAT-SPECT [2.31 (1.09–4.91), p < 0.030] were independent predictors of conversion to PD and DLB. Among the other CSF markers, only elevated p-tau/Aβ42 was predictive of conversion, although only to DLB and not as an independent variable. In IRBD, CSF AS assessment by RT-QuIC provides an added value in defining the risk of short-term conversion to PD and DLB independent of clinical and instrumental investigations. Positive Alzheimer's disease (AD) pathology markers and elevated NfL occur in a subgroup of patients, but p-tau/Aβ42 is the only marker that predicts short-term conversion to DLB. Longer follow-up is needed to assess if AD biomarkers predict the later development of PD and DLB in IRBD.

Prognostic Role of Tissue Iron Deficiency Measured by sTfR Levels in Heart Failure Patients without Systemic Iron Deficiency or Anemia.

Background. Iron deficiency (ID) is a significant, high-prevalence comorbidity in chronic heart failure (HF) that represents an independent predictor of a worse prognosis. However, a clear-cut diagnosis of ID in HF patients is not assured. The soluble transferrin receptor (sTfR) is a marker that reflects tissue-level iron demand and may be an early marker of ID. However, the impact of sTfR levels on clinical outcomes in non-anemic HF patients with a normal systemic iron status has never been evaluated. Methods. This is a post hoc analysis of an observational, prospective cohort study of 1236 patients with chronic HF of which only those with normal hemoglobin levels and a normal systemic iron status were studied. The final cohort consisted of 215 patients. Tissue ID was defined as levels of sTfR > 75th percentile (1.65 mg/L). Our aim was to describe the association between sTfR and clinical outcomes (all-cause death and HF hospitalization) and to explore its association with a wide array of serum biomarkers. Results. The sTfR level (HR 1.48, 95% CI 1.13-1.96, p = 0.005) and tissue ID (HR 2.14, 95% CI 1.22-3.75, p = 0.008) was associated with all-cause death. However, we found no association between sTfR levels and the risk of HF hospitalization. Furthermore, high sTfR levels were associated with a worse biomarker profile indicating myocardial damage (troponin and NT-proBNP), systemic inflammation (CRP and albumin), and impaired erythropoiesis (erythropoietin). Conclusions. In this cohort, the presence of tissue ID defined by sTfR levels is an independent factor for all-cause death in patients with normal systemic iron parameters.

Biomarker Profiling with Targeted Metabolomic Analysis of Plasma and Urine Samples in Patients with Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease.

Background: Over the years, it was noticed that patients with diabetes have reached an alarming number worldwide. Diabetes presents many complications, including diabetic kidney disease (DKD), which can be considered the leading cause of end-stage renal disease. Current biomarkers such as serum creatinine and albuminuria have limitations for early detection of DKD. Methods: In our study, we used UHPLC-QTOF-ESI+-MS techniques to quantify previously analyzed metabolites. Based on one-way ANOVA and Fisher's LSD, untargeted analysis allowed the discrimination of six metabolites between subgroups P1 versus P2 and P3: tryptophan, kynurenic acid, taurine, l-acetylcarnitine, glycine, and tiglylglycine. Results: Our results showed several metabolites that exhibited significant differences among the patient groups and can be considered putative biomarkers in early DKD, including glycine and kynurenic acid in serum (p < 0.001) and tryptophan and tiglylglycine (p < 0.001) in urine. Conclusions: Although we identified metabolites as potential biomarkers in the present study, additional studies are needed to validate these results.

Change in Biomarker Profile After Neoadjuvant Chemotherapy is Prognostic and Common Among Patients with HER2+ Breast Cancer

BackgroundRates of pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer have improved, especially among human epidermal growth factor 2-positive (HER2+) and triple-negative subtypes. The frequency and significance of biomarker profile change in residual disease are unclear. This study aimed to determine the rate of biomarker profile changes after NAC and the impact on clinical outcomes in a contemporary cohort.MethodsUpon institutional review board approval, the study identified 634 consecutive patients treated with NAC between 2010 and 2022 at two academic institutions. The study cohort was focused on patients with residual disease who underwent biomarker profile retesting. Biomarker profile change for each subtype was compared across groups using Fisher-Irwin tests. Cox Proportional Hazards Model and Kaplan-Meier plots were performed to evaluate the association of changed versus unchanged biomarker profile with event-free survival.ResultsBiomarker retesting was performed for 259 (61.4 %) of 422 patients with residual disease. Biomarker profile change occurred in 18.1 % overall and was significantly higher among those with pre-NAC HER2+ disease (32.7 %, 17/52) than among those with HER2–disease (14.5 %, 30/207) (p = 0.004). Conversion of pre-NAC biomarker profiles of HR+HER2– and HR+HER2+ to triple-negative breast cancer (TNBC) post-NAC may be associated with worse event-free survival, hazard ratios of 2.23 (95 % confidence interval [CI], 0.90–5.53; p = 0.08), trending toward significance, and 36.7 (95 % CI, 2.2–610.8; p = 0.01), respectively.ConclusionsThe results from one of the largest contemporary cohorts demonstrated that biomarker profile change in patients with residual disease after NAC was common. Furthermore, specific biomarker profile change in residual disease may have prognostic value. These findings strengthen the rationale for routine re-testing of biomarkers in residual disease after NAC.

GC–MS analysis, molecular docking, and apoptotic-based cytotoxic effect of Caladium lindenii Madison extracts toward the HeLa cervical cancer cell line

Utilizing medicinal plants and other natural resources to prevent different types of human cancers is the prime focus of attention. Cervical cancer in women ranks as the fourth most common type of malignancy. The current study used gas chromatography-mass spectrometry (GC–MS) to identify the active phytochemical constituents from Caladium lindenii leaf extracts using ethanol (ECL) and n-hexane (HCL) solvents. Plant extracts were tested for potential cytotoxic effects on HeLa and HEK-293 T cells using the MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) and the crystal violet assays. SYBR Green-based real-time PCR was performed to assess the mRNA expression profile of the apoptosis biomarkers (BCL-2 and TP53). The molecular interaction of the compounds with the targeted proteins (TP53, BCL2, EGFR, and HER2) was determined using molecular docking. GC–MS analysis revealed a total of 93 compounds in both extracts. The ECL extract significantly reduced the proliferation of HeLa cervical cancer cells, with an IC50 value of 40 µg/mL, while HEK-293 T cells showed less effect (IC50 = 226 µg/mL). The quantitative RT-PCR gene expression analysis demonstrated the ethanol extract regulated TP53 and BCL2 mRNA expressions in treated cancer cell samples. Heptanediamide, N,Nʹ-di-benzoyloxy-(− 10.1) is the best-docked ligand with a TP53 target found in the molecular docking study, whereas EGFR/Clionasterol had the second highest binding affinity (− 9.7), followed by EGFR/Cycloeucalenol (− 9.6). It is concluded that ECL extract has promising anti-cervical cancer potential and might be valued for developing new plant-derived anticancer agents after further investigations.

Blood Biomarkers of Long COVID: A Systematic Review.

Long coronavirus disease (COVID; LC) affects millions of people worldwide. The exact mechanisms which result in a broad, undulating and detrimental symptom profile remain unknown. Blood biomarkers associated with LC have been described; however, consensus on these remains elusive, in part due to a lack of continuity between studies on a universally accepted definition of LC. This systematic review aimed to consolidate current knowledge of blood biomarkers associated with the prevalence of LC on the basis of the World Health Organisation (WHO) clinical definition of this condition. Observational, cross-sectional, and randomised control studies published in the English language that studied blood biomarkers associated with the WHO definition of LC. All studies included participants who were ≥ 18 years old and group sizes ≥ 10 participants, and were compared against a control group without any known co-morbidities. A systematic literature search was conducted according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and prospectively registered on Prospero (ID: CRD42022373121). The Cochrane, Embase, PubMed and Web of Science databases were searched from inception to January 2024. Search results were gathered using Rayyan software and data extracted using Microsoft Excel. The reporting recommendations for tumour markers prognostic studies (REMARK) questionnaire was used to assess the quality of the included studies. A total of 45 observational and one interventional study comprising 4415 participants were included in this review which identified 525 blood biomarkers thought to be associated with LC. Three blood biomarker subtypes were associated with the development of LC: (1) immunological and inflammatory dysfunction, (2) endothelial/vascular dysfunction and (3) metabolic and clotting abnormalities. Our data are consistent with previous findings; however, no single biomarker was sufficiently associated with LC prevalence and instead a profile of biomarkers across various physiological systems may be more clinically useful. In all, 196 studies were excluded due to a lack of an adequately healthy comparator group and/or failure to meet the WHO LC definition. This demonstrates a need for further research incorporating a universal LC definition across all disease severity groups and symptom profiles, and longitudinal data reflecting the relapsing and remitting nature of this condition. Further investigation into blood biomarkers of LC, including clear reporting of healthy comparator groups and the investigation of acute and chronic biomarker changes, within the context of medical practice, may support the development of curative/restorative approaches.

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We have also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease states. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.

Simultaneous onset of chronic nonbacterial osteomyelitis in siblings.

Chronic nonbacterial osteomyelitis (CNO) is an uncommon autoinflammatory disorder. Significant effort has recently been spent to better define and treat this disorder including development of consensus treatment protocols, validate disease activity tools, and refining classification criteria. However, the underlying immunopathogenesis of the disease remains elusive. In this report, we describe the simultaneous onset of CNO in siblings. A pathogenic gene mutation was not identified, and these sisters lacked a similar biomarker profile. This report highlights that if a genetic predisposition for CNO exists, it may be related to complex polygenic or multifactorial mechanisms of disease evolution.

Size-Exclusion Chromatography: A Path to Higher Yield and Reproducibility Compared to Sucrose Cushion Ultracentrifugation for Extracellular Vesicle Isolation in Multiple Myeloma.

Small extracellular vesicles (EVs) play a pivotal role in intercellular communication across various physiological and pathological contexts. Despite their growing significance as disease biomarkers and therapeutic targets in biomedical research, the lack of reliable isolation techniques remains challenging. This study characterizes vesicles that were isolated from conditioned culture media (CCM) sourced from three myeloma cell lines (MM.1S, ANBL-6, and ALMC-1), and from the plasma of healthy donors and multiple myeloma patients. We compared the efficacy, reproducibility, and specificity of isolating small EVs using sucrose cushion ultracentrifugation (sUC) vs. ultrafiltration combined with size-exclusion chromatography (UF-SEC). Our results demonstrate that UF-SEC emerges as a more practical, efficient, and consistent method for EV isolation, outperforming sUC in the yield of EV recovery and exhibiting lower variability. Additionally, the comparison of EV characteristics among the three myeloma cell lines revealed distinct biomarker profiles. Finally, our results suggest that HBS associated with Tween 20 improves EV recovery and preservation over PBS. Standardization of small EV isolation methods is imperative, and our comparative evaluation represents a significant step toward achieving this goal.

Elevated allostatic load is associated with poorer response to repetitive transcranial magnetic stimulation in treatment-resistant depression

This cohort study investigated whether allostatic load (AL) is associated with treatment response to repetitive transcranial magnetic stimulation (rTMS) in treatment-resistant depression (TRD). Pre-treatment blood samples measured AL across multiple systems. Pre- and post-treatment mood changes were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). Associations between AL and treatment outcomes were explored. Higher pre-treatment AL was significantly associated with poorer post-treatment response status but was not significantly associated with smaller reduction in MADRS score after 4 weeks of treatment. Identifying biomarker profiles informed by the AL model could enhance treatment decisions in TRD, reducing risks associated with prolonged, ineffective rTMS trials and emphasizing the need for reliable predictive biomarkers.

Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR

Background: Anterior cruciate ligament injury and anterior cruciate ligament reconstruction (ACLR) are risk factors for symptomatic posttraumatic osteoarthritis (PTOA). After ACLR, individuals demonstrate altered joint tissue metabolism indicative of increased inflammation and cartilage breakdown. Serum biomarker changes have been associated with tibiofemoral cartilage composition indicative of worse knee joint health but not with PTOA-related symptoms. Purpose/Hypothesis: The purpose of this study was to determine associations between changes in serum biomarker profiles from the preoperative sample collection to 6 months after ACLR and clinically relevant knee PTOA symptoms at 12 months after ACLR. It was hypothesized that increases in biomarkers of inflammation, cartilage metabolism, and cartilage degradation would be associated with clinically relevant PTOA symptoms after ACLR. Study Design: Case-control study; Level of evidence, 3. Methods: Individuals undergoing primary ACLR were included (N = 30). Serum samples collected preoperatively and 6 months after ACLR were processed to measure markers indicative of changes in inflammation (ie, monocyte chemoattract protein 1 [MCP-1]) and cartilage breakdown (ie, cartilage oligomeric matrix protein [COMP], matrix metalloproteinase 3, ratio of type II collagen breakdown to type II collagen synthesis). Knee injury and Osteoarthritis Outcome Score surveys were completed at 12 months after ACLR and used to identify participants with and without clinically relevant PTOA-related symptoms. K-means cluster analyses were used to determine serum biomarker profiles. One-way analyses of variance and logistic regressions were used to assess differences in Knee injury and Osteoarthritis Outcome Score subscale scores and clinically relevant PTOA-related symptoms between biomarker profiles. Results: Two profiles were identified and characterized based on decreases (profile 1: 67% female; age, 21.4 ± 5.1 years; body mass index, 24.4 ± 2.4) and increases (profile 2: 33% female; age, 21.3 ± 3.2 years; body mass index, 23.4 ± 2.6) in sMCP-1 and sCOMP preoperatively to 6 months after ACLR. Participants with profile 2 did not demonstrate differences in knee pain, symptoms, activities of daily living, sports function, or quality of life at 12 months after ACLR compared to those with profile 1 (P = .56-.81; η2 = 0.002-0.012). No statistically significant associations were noted between biomarker profiles and clinically relevant PTOA-related symptoms (odds ratio, 1.30; 95% CI, 0.23-6.33). Conclusion: Serum biomarker changes in MCP-1 and sCOMP within the first 6 months after ACLR were not associated with clinically relevant PTOA-related symptoms.

ANA-associated arthritis: clinical and biomarker characterization of a population for basket trials.

ANA-associated rheumatic and musculoskeletal (MSK) diseases (RMDs) [SLE, primary SS (pSS), scleroderma, inflammatory myositis, MCTD and UCTD] make up a disease spectrum with overlapping clinical and immunological features. MSK inflammation is common and impactful across ANA-associated RMDs. The objectives of this study were to evaluate MSK inflammation (ANA-associated arthritis) prevalence in a multidisease ANA-associated RMD study, assess its clinical impact across ANA-associated RMD diagnoses, propose new basket groupings of patients, and evaluate immunological profiles in legacy and new basket contexts. An observational study enrolled patients with ANA-associated RMDs. Demographic variables, comorbidities, therapies, disease activity instruments [BILAG, SLEDAI, the EULAR SS disease activity index (ESSDAI), physician visual analogue scale (VAS)], patient-reported outcomes [SF36, FACIT-Fatigue, EQ5D, ICECAP-A, Work Productivity and Activity impairment (WPAI), patient VAS] and the biomarker profile (six-gene expression scores, flow cytometry, autoantibody profile) were analysed. Reclustering utilized Gaussian mixture modelling (GMM). The clinical and immune features of new and legacy clusters were compared. Inflammatory MSK symptoms were prevalent across ANA-associated RMDs, in 213/294 patients. In ANA-associated arthritis patients, most variables did not differ between diagnoses, with the exception of the EQ5D-5L index and mobility domains (lower in MCTD/pSS, both P < 0.05). FM and OA prevalence were similar across diagnoses. Therapy use differed significantly, the use of biologics being greatest in SLE (P < 0.05). GMM yielded two multidisease clusters: High MSK disease activity (n = 89) and low MSK disease activity (n = 124). The high MSK disease activity cluster included all patients with active joint swelling, and they had significantly higher prednisolone usage, physician global assessment (PGA), Sm/RNP/SmRNP/chromatin positivity, Tetherin mean fluorescence intensity (MFI), and IFN Score-A activity, along with numerically lower FM and OA prevalence. We defined ANA-associated arthritis, a more clinically and immunologically homogeneous population than existing RMD populations for trials, and a more prevalent population for therapies in the clinic.

Biomarkers in Cutaneous Keratinocyte Carcinomas.

Skin cancer is the most common cancer type in the USA, with over fivemillion annually treated cases and one in five Americans predicted to develop the disease by the age of 70. Skin cancer can be classified as melanoma or non-melanoma (NMSC), the latter including basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC). Development of BCC and SCC is impacted by environmental, behavioral, and genetic risk factors and the incidence is on the rise, with the associated number of deaths surpassing those caused by melanoma, according to recent reports. Substantial morbidity is related to both BCC and SCC, including disfigurement, loss of function, and chronic pain, driving high treatment costs, and representing a heavy financial burden to patients and healthcare systems worldwide. Clinical presentations of BCC and SCC can be diverse, sometimes carrying considerable phenotypic similarities to benign lesions, and underscoring the need for the development of disease-specific biomarkers. Skin biomarker profiling plays an important role in deeper disease understanding, as well as in guiding clinical diagnosis and patient management, prompting the use of both invasive and non-invasive tools to evaluate specific biomarkers. In this work, we review the known and emerging biomarkers of BCC and SCC, with a focus on molecular and histologic biomarkers relevant for aspects of patient management, including prevention/risk assessments, tumor diagnosis, and therapy selection.