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PubMed2006

Influence of sample type and storage conditions on soluble CD40 ligand assessment.

BACKGROUND: Several studies have consistently shown that soluble CD40 ligand (sCD40L) concentrations are increased in patients with acute coronary syndromes and can serve as a biomarker for risk stratification. However, few data are available on preanalytic conditions that impact sCD40L values. Thus, the aim of our prospective study was to evaluate the impact of sampling techniques and storage conditions on sCD40L concentrations. METHODS: We included a total of 30 patients with no, stable, or unstable coronary heart disease. Blood samples were collected in gel-filled tubes without additives, in EDTA-filled tubes, and in citrate-filled tubes and were kept at various storage conditions. RESULTS: Median (interquartile range) sCD40L values at baseline were higher in serum samples [5.29 (3.89-6.33) microg/L] than in either EDTA plasma [0.78 (0.39-1.12) microg/L; P <0.001] or citrate plasma [0.37 (0.22-0.51) microg/L; P <0.001]. Serum values increased with delayed processing [7.94 (5.97-9.62) microg/L after 1.5 h (P <0.001) vs baseline; 10.55 (7.58-11.55) microg/L after 3 h (P <0.001) vs baseline]. However, after centrifugation, sCD40L values remained stable for all 3 sample types. CONCLUSION: Plasma, but not serum, samples are appropriate for sCD40L measurements. In general, preanalytic conditions are critical in the assessment of sCD40L concentrations and thus should be carefully considered for future studies.

Biomarkers↗

PubMed2005

Biomarker-based risk assessment model in acute pulmonary embolism.

AIMS: Despite growing interest in biomarkers application for risk evaluation in acute pulmonary embolism (APE), no decision-making levels have been defined. METHODS AND RESULTS: We developed a biomarker-based risk stratification in 100 consecutive, normotensive on admission, APE patients (35 males, 65 females, 62+/-18 years). On admission serum NT-proBNP and cardiac troponin T (cTnT) levels were assessed and echocardiography was performed. All-cause 40-day mortality was 15% and APE mortality was 8%. In univariable analysis, cTnT>0.07 microg/L predicted all-cause mortality, hazard ratio (HR) 9.2 (95% CI: 3.3-26.1, P<0.0001), and APE mortality, HR 18.1 (95% CI: 3.6-90.2, P=0.0004); similarly, NT-proBNP>7600 ng/L predicted all-cause and APE mortalities [HR 6.7 (95% CI: 2.4-19.0, P=0.0003) and 7.3 (95% CI: 1.7-30.6, P=0.007)]. NT-proBNP<600 ng/L indicated uncomplicated outcome. Multivariable analysis revealed that cTnT>0.07 microg/L was the most significant independent predictor, whereas NT-proBNP and systemic systolic blood pressure measured on admission and echocardiographic parameters were non-significant. APE mortality in patients with NT-proBNP> or =600 ng/L and cTnT> or =0.07 microg/L reached 33%. NT-proBNP<600 ng/L indicated group without deaths. APE mortality for patients with NT-proBNP> or =600 ng/L and cTnT<0.07 microg/L was 3.7%. Incorporation of echocardiographic data did not improve group selection. CONCLUSION: Simultaneous measurement of serum cTnT and NT-proBNP allows for precise APE prognosis. Normotensive patients on admission with cTnT> or =0.07 microg/L and NT-proBNP> or =600 ng/L are at high risk of APE mortality, whereas NTproBNP<600 ng/L indicates excellent prognosis.

Acute Disease↗

PubMed2026

Metabolic convergence of diabetes and prostate cancer: from dysglycemia to tumor microenvironment reprogramming.

The relationship between diabetes mellitus and prostate cancer (PC) represents one of the most intriguing paradoxes in cancer epidemiology, with diabetic individuals exhibiting a reduced incidence of PC yet poorer prognosis following diagnosis. This apparent contradiction underscores the need for an integrated understanding of how systemic metabolic dysfunction influences prostate carcinogenesis and disease progression. The present review critically synthesizes contemporary epidemiological, mechanistic, and translational evidence to establish metabolic convergence as a unifying framework linking diabetes-associated metabolic abnormalities with PC biology. Current evidence indicates that chronic dysglycemia, hyperinsulinemia, insulin resistance, and endocrine perturbations orchestrate interconnected intracellular signaling networks involving PI3K-AKT-mTOR, AMPK, AGE-RAGE signaling, oxidative stress, mitochondrial dysfunction, and epigenetic reprogramming, collectively driving metabolic adaptation and tumor evolution. Beyond tumor-intrinsic mechanisms, diabetes profoundly remodels the prostate tumor microenvironment through alterations in stromal metabolism, cancer-associated fibroblast activation, adipocyte-tumor crosstalk, extracellular matrix (ECM) remodeling, hypoxic adaptation, and vascular dysfunction, while simultaneously promoting immunometabolic reprogramming characterized by macrophage polarization, T-cell dysfunction, immune checkpoint activation, and immune evasion. The review further examines the bidirectional interactions between antidiabetic therapies and PC treatment, critically evaluating the translational potential of metformin and emerging glucose-lowering agents within the context of precision metabolic therapeutics. Finally, future directions encompassing biomarker-guided patient stratification, longitudinal metabolic profiling, multi-omics integration, artificial intelligence, and clinically relevant mechanistic validation are discussed as essential components of next-generation precision oncology. Collectively, this review reframes diabetes as an active metabolic determinant of PC rather than a coincidental comorbidity and highlights metabolism-centered precision strategies as promising avenues for improving risk stratification, therapeutic decision-making, and clinical outcomes in diabetes-associated PC.

Humans↗

PubMed2026

A novel peptide encoded by circTLL1 drives osimertinib resistance in lung cancer by modulating the NT5C2/Ras/PI3K axis.

BACKGROUND: Acquired resistance to osimertinib, a third-generation EGFR tyrosine kinase inhibitor, remains a major clinical challenge in the treatment of non-small cell lung cancer (NSCLC). Although circular RNAs (circRNAs) have been increasingly implicated in drug resistance, most studies have focused on their canonical role as microRNA sponges, while their capacity to encode functional micropeptides remains largely unexplored. This study aimed to identify novel circRNAs involved in osimertinib resistance and to characterize their regulatory functions at the protein level. METHODS: Osimertinib-resistant (OR) NSCLC cell lines were established and validated. High-throughput RNA sequencing was performed to compare the circRNA expression profiles between parental and OR cells. The function of the candidate circRNA was assessed through a series of in vitro and in vivo experiments, including cell viability assays, apoptosis analysis, and xenograft mouse models. Mechanistic investigations involved mass spectrometry, co-immunoprecipitation and western blotting to explore its protein-coding potential and downstream signaling pathways. RESULTS: We identified a novel circRNA, termed circTLL1, that was stably and significantly upregulated in OR-NSCLC cells. Functionally, overexpression of circTLL1 promoted osimertinib resistance, whereas its knockdown restored drug sensitivity both in vitro and in vivo. Mechanistically, we discovered that circTLL1 harbors an open reading frame (ORF) that is translated into a novel 90-amino-acid protein, which we designated circTLL1-90aa. Further investigation revealed that circTLL1-90aa directly interacts with and promotes the degradation of 5'-nucleotidase, cytosolic II (NT5C2), thereby uncoupling nucleotide metabolism from its normal regulatory constraints. The consequent downregulation of NT5C2 leads to elevated GTP levels and leading to the sustained activation of the downstream Ras/PI3K/AKT signaling pathway. CONCLUSION: Our findings unveil a previously unrecognized circRNA/micropeptide/metabolism cascade underlying osimertinib resistance. The identification of the circTLL1-90aa/NT5C2/Ras/PI3K axis not only expands the functional repertoire of the non-coding genome but also provides new insights into the complexity of drug resistance. Given its selective upregulation in resistant cells, circTLL1-90aa holds promise both as a predictive biomarker for treatment stratification and as an actionable therapeutic target, offering a novel strategy to overcome osimertinib resistance in NSCLC patients.

Pyrimidines↗

PubMed2026

Extracellular Vesicles From Glioblastoma Cells Reflect 2D vs. 3D Culture Adaptation and Resistance to Temozolomide.

Glioblastoma (GBM) is an aggressive brain tumor marked by extensive heterogeneity, resistance to therapy, and dismal prognosis. Extracellular vesicles (EVs) have emerged as key players in GBM biology, mediating intercellular communication and therapy adaptation. However, the exact functions and molecular impact of EVs in GBM remain incompletely understood. In this study, we performed a comparative proteomic analysis of U87MG GBM cells grown in two-dimensional (2D) monolayers and three-dimensional (3D) spheroids following temozolomide (TMZ) treatment, alongside characterization of EVs derived from both culture systems. 3D-spheroids secreted more EVs of smaller size and exhibited a more TMZ-resistant, stem-like proteome under TMZ-induced genotoxic stress. In contrast, 2D cell cultures demonstrated greater proteome remodeling, with EVs enriched in protein families involved in DNA repair, oxidative stress adaptation, and methylation processes. Notably, several methyltransferases were decreased intracellularly but selectively retained in EVs, suggesting active sorting to influence the tumor microenvironment or modulate epigenetic states in recipient cells. EVs also carried adhesion molecules and signaling proteins linked to migration, invasion, and Wnt pathway activation, as well as metabolic enzymes connecting serine metabolism and redox control to TMZ resistance. Mapping EV and cellular proteomes onto The Cancer Genome Atlas (TCGA) dataset identified prognostic protein families associated with either poor or favorable patient outcomes. Our data demonstrate that EV cargo composition mirrors TMZ-induced phenotypic adaptation and reveals molecular mechanisms underlying therapeutic resistance. These EV-associated signatures may serve as clinically actionable biomarkers for patient stratification and offer potential targets to overcome chemoresistance in GBM.

Humans↗

PubMed2005

How many genomics targets can a portfolio afford?

The pharmaceutical industry can look back at a history of successful innovations. Although genomics technologies have provided drug discovery pipelines with a plethora of new potential drug targets, solid target validation is crucial to avoiding high attrition rates. Biomarkers for patient stratification and approaches for personalized medicine will further help to reduce the risk associated with new targets. To achieve an overall risk balance, portfolios have to be supplemented with precedented targets, me-too approaches and line extensions of existing drugs. However, capitalizing on genomics investments and working on unprecedented targets is essential for a continuous stream of innovative drugs.

Drug Industry↗

PubMed2026

Integrated signatures define mutational processes in prostate cancer.

Prostate cancer follows a long and heterogeneous disease course with incompletely understood aetiology1. Here we dissect the mutational processes shaping the genomes of 959 donors from the Pan Prostate Cancer Group and assess their clinical relevance. By integrating de novo extracted single-base substitution, insertion-deletion and copy-number signatures with six novel complex structural variant signatures, we identify eight integrated mutational footprints (IMFs) that collectively explain the mutational processes in 85% of primary prostate cancer genomes. IMFs were strongly influenced by regional biases in the genome, most prevalently androgen receptor-mediated mutagenesis and replication stress. Four IMFs, present in 37% of primary tumours, were significantly associated with shorter time to metastasis. These included reactive oxygen-species-driven mutagenesis and both canonical and non-canonical homologous recombination deficiency, the latter being enriched in patients of African ancestry. Extending to the metastatic setting, we found that IMFs predicted sensitivity to androgen receptor pathway inhibitors. Taken together, our study delineates the aetiologies and mutational processes that drive the genomic and clinical heterogeneity of prostate cancer, introduces IMFs as a unifying framework, and highlights their potential to improve both risk stratification and biomarker-guided treatment selection.

Journal Article↗

PubMed2025

Innovative strategies for mitochondrial dysfunction in myeloproliferative neoplasms a step toward precision medicine.

Myeloproliferative neoplasms (MPNs) are clonal disorders of hematopoietic stem cells characterized by aberrant proliferation of myeloid lineages, driven primarily by mutations in JAK2, CALR, and myeloproliferative leukemia, leading to constitutive activation of the JAK-STAT pathway. Emerging evidence highlights mitochondrial dysfunction as a key factor in MPN pathogenesis, contributing to increased reactive oxygen species production, mitochondrial DNA mutations, and dysregulated mitochondrial dynamics, which collectively promote clonal expansion and apoptosis resistance. Targeting mitochondrial pathways has gained attention as a therapeutic strategy, with approaches including mitochondria-targeted antioxidants, metabolic inhibitors, and modulation of mitophagy and mitochondrial fission/fusion dynamics. However, challenges such as drug delivery specificity, therapeutic resistance, and off-target effects remain significant. Recent advances in precision medicine, incorporating genomic, transcriptomic, and proteomic profiling, offer a more personalized approach to MPN treatment by tailoring interventions to individual mutation patterns. Additionally, novel therapeutic strategies, including gene editing technologies, RNA-based therapies, and nanoparticle-mediated drug delivery systems, hold promise for overcoming current treatment limitations. The integration of artificial intelligence in drug discovery and biomarker identification further enhances the potential for targeted therapies. Future research should focus on refining these strategies, developing reliable biomarkers for patient stratification, and exploring combination therapies that enhance treatment efficacy while minimizing adverse effects. By addressing mitochondrial dysfunction as an underlying driver of MPNs, these emerging approaches have the potential to improve disease management, extend patient survival, and enhance quality of life. Also, this new approach of precision medicine allows patient stratification and ensures that treatments are formed according to the individual disease biology of each patient, which results in overall better outcomes.

combination drug therapy↗

PubMed2006

Embracing the complexity of genomic data for personalized medicine.

Numerous recent studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in cancer and other complex diseases. Such studies herald the future of genomic medicine and the opportunity for personalized prognosis in a variety of clinical contexts that utilizes genome-scale molecular information. The scale, complexity, and information content of high-throughput gene expression data, as one example of complex genomic information, is often under-appreciated as many analyses continue to focus on defining individual rather than multiplex biomarkers for patient stratification. Indeed, this complexity of genomic data is often--rather paradoxically--viewed as a barrier to its utility. To the contrary, the complexity and scale of global genomic data, as representing the many dimensions of biology, must be embraced for the development of more precise clinical prognostics. The need is for integrated analyses--approaches that embrace the complexity of genomic data, including multiple forms of genomic data, and aim to explore and understand multiple, interacting, and potentially conflicting predictors of risk, rather than continuing on the current and traditional path that oversimplifies and ignores the information content in the complexity. All forms of potentially relevant data should be examined, with particular emphasis on understanding the interactions, complementarities, and possible conflicts among gene expression, genetic, and clinical markers of risk.

Breast Neoplasms↗

PubMed2026

Epigenetic alterations of AKT1 orchestrate a metabolic reprogramming in advanced lipedema: translational insights from an integrated multi-omics study.

BACKGROUND: lipedema is a chronic, progressive adipose disorder predominantly affecting women, characterized by painful, symmetrical subcutaneous fat accumulation, and typically resistant to lifestyle interventions. The pathophysiology of advanced-stage lipedema remains poorly defined, and no validated biomarkers or targeted therapies are currently available. METHODS: in this observational study, we applied a comprehensive multi-omics approach to dissect the molecular and metabolic alterations underlying late-stage lipedema. RESULTS: Genome-wide DNA methylation profiling identified over 5,000 differentially methylated CpG sites affecting genes involved in receptor tyrosine kinase signaling, phospho-metabolism, and immune pathways. Transcriptomic analysis revealed profound downregulation of mitochondrial functions, including oxidative phosphorylation, the TCA cycle, and fatty acid β-oxidation, alongside disruption of the sirtuin pathway and extracellular matrix remodeling. Integrative analysis pinpointed AKT1 as a central regulatory node: its promoter region was hypomethylated, correlating with increased gene expression and protein phosphorylation. Metabolomic profiling confirmed AKT1-linked metabolic dysregulation, including altered levels of L-arginine, NADP+, ATP, guanosine, glycerol, and glutamate, indicating impaired redox balance and energy metabolism. Trans-omic network analysis positioned AKT1 at the intersection of multiple dysregulated pathways, suggesting its key role in advanced-stage lipedema. CONCLUSIONS: the consistent enhancing of AKT pathway signaling across omic layers highlights its potential not only as a biomarker for disease stratification but also as a putative druggable target for therapeutic intervention. These findings offer new mechanistic insights into lipedema pathophysiology and provide a rationale for future personalized treatment strategies guided by AKT1-centric molecular profiling.

Proto-Oncogene Proteins c-akt↗

PubMed2026

Advanced and underlying therapeutic strategies in transformed small cell lung cancer.

Transformed small-cell lung cancer (T-SCLC) is a clinically important form of histologic transformation and a mechanism of acquired resistance in non-small-cell lung cancer (NSCLC). It is associated with poor prognosis, with a median overall survival of only about 9-13 months. This review summarizes recent advances in the mechanisms, diagnosis, monitoring, and treatment of T-SCLC. Repeat biopsy remains the gold standard for confirming histologic transformation, whereas molecular profiling and liquid biopsy may facilitate early detection and longitudinal disease monitoring. Platinum-etoposide remains the most commonly used clinical standard after transformation, but its benefit is typically transient and durable disease control remains uncommon. Continuation of EGFR tyrosine kinase inhibitors combined with chemotherapy may prolong progression-free survival in selected patients but has not consistently improved overall survival. Anti-angiogenic therapy, particularly anlotinib, and chemo-immunotherapy have shown encouraging activity in selected patients, while emerging strategies targeting DLL3, MYC, SOX2, and epigenetic regulators may broaden the therapeutic landscape. Prospective studies integrating repeat tissue sampling, comprehensive genomic profiling, biomarker-guided patient stratification, pharmacogenomics, functional drug-sensitivity testing where feasible, and integrated multi-omics approaches are needed to advance molecularly guided and individualized treatment for T-SCLC.

advanced therapy↗

PubMed2025

The X-Linked TLR7 rs179008 T Allele Is Associated with an Increased Risk of Severe Multisystem Inflammatory Syndrome in Children/Kawasaki-like Syndrome in SARS-CoV-2-Infected Boys.

The X-linked TLR7 rs179008 T allele has been associated with altered antiviral immunity. Given their shared inflammatory pathways and higher pediatric mortality rates in Brazil during the pandemic, we investigated their association with multisystem inflammatory syndrome in children (MIS-C) together with Kawasaki disease (KS) following SARS-CoV-2 infection. A cross-sectional study (2021-2022) analyzed 73 hospitalized children (<13 years) with confirmed COVID-19. Genotyping for TLR7 rs179008, TLR8 (rs3764879, rs2407992), and TLR3 rs3775291 was performed via PCR and Sanger sequencing. MIS-C/KS cases were identified using CDC criteria, with severity classified by the need for ICU care. Statistical analysis included Fisher's exact test and relative risk (RR) calculations. Hemizygous boys carrying the TLR7 T allele had a 1.87-fold higher risk of MIS-C/KS (p = 0.007) and a 1.75-fold increased risk of severe or critical outcomes. The T allele frequency was 2.6× higher in MIS-C/KS cases versus other COVID-19 presentations. All fatalities occurred in boys (3/8 MIS-C cases) with one T-allele carrier. No associations were found for TLR8 or TLR3 variants. The TLR7 rs179008 T allele is a potential genetic risk factor for severe post-COVID-19 inflammatory syndromes in boys, likely due to impaired immune signaling. These findings highlight its utility as a biomarker for risk stratification in pediatric populations.

Humans↗

PubMed2003

Combining natriuretic peptides and necrosis markers in the assessment of acute coronary syndromes.

Management of patients with acute coronary syndromes (ACS) is becoming more complex as the array of treatment options available to patients and physicians continues to expand. Cardiac biomarkers play an important role in risk stratification in ACS, and results of cardiac biomarker tests can be used to help guide choices between alternative therapies. In addition to biomarkers of myocyte necrosis, markers of neurohormonal activation, such as B-type natriuretic peptide (BNP), provide important prognostic information in ACS. In the future, multimarker strategies that incorporate panels of cardiac biomarkers are likely to be used for risk stratification and for pathophysiology-guided treatment in patients with ACS.

Acute Disease↗

PubMed2004

Biomarkers of cardiac disease.

The challenge of medical practice today is to identify individuals who are at risk of developing disease, determine the severity of the disease and distinguish the responders from the nonresponders to therapy (individualized medicine). Advances in molecular genetics and biology have shifted the paradigm for identification of markers from large-scale epidemiologic studies to studies on genomic- and proteomic-based techniques. Consequently, a large number of biologic markers, referred to as biomarkers, are being identified and validated to serve for risk stratification, prognostication and individualization of therapy. Identification of biomarkers for cardiovascular diseases could also provide insight into the pathogenesis of the phenotype, which is fundamental for the development of specific therapies. The list of biomarkers for cardiovascular disease is expanding rapidly. Nonetheless, the field is in the early stages of evolution and large-scale clinical studies are required to validate the utility of newly identified biomarkers in diagnosis, risk stratification and treatment of cardiovascular diseases. Selected biomarkers for coronary atherosclerosis, acute coronary syndromes and heart failure are discussed in this review.

Biomarkers↗

PubMed2006

Genetic and epigenetic biomarkers in cancer : improving diagnosis, risk assessment, and disease stratification.

Gene expression patterns change during the initiation, progression, and development of cancer, as a result of both genetic and epigenetic mechanisms. Genetic changes arise due to irreversible changes in the nucleotide sequence, whereas epigenetic changes occur due to changes in chromatin conformation, histone acetylation, and methylation of the CpG islands located primarily in the promoter region of a gene. Both genetic and epigenetic markers can potentially be utilized to identify different stages of tumor development. Several such markers exhibit high sensitivity and specificity for different tumor types and can be assayed in biofluids and other specimens collected by noninvasive technologies. In spite of the availability of large numbers of diagnostic markers, only a few have been clinically validated so far. The current status and the challenges in the field of genetic and epigenetic markers in cancer diagnosis, risk assessment, and disease stratification are discussed.

Biomarkers, Tumor↗

PubMed2026

A CFH- and SPINT2-based prognostic signature for cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant tumor with a poor prognosis, and reliable biomarkers for postoperative risk stratification remain limited. This study aimed to develop and validate a CFH- and SPINT2-based prognostic signature to support postoperative risk stratification and inform adjuvant therapy selection in CCA through integrative machine learning and single-cell transcriptomics. METHODS: Differentially expressed genes were screened from GSE26566. Integrative machine learning (least absolute shrinkage and selection operator-Cox, random forest, and univariate Cox regression) was performed in the training cohort (GSE89749; n=115) to construct a risk model, which was externally validated in two independent cohorts: cohort 1 (E-MTAB-6389; n=75) and cohort 2 [The Cancer Genome Atlas Cholangiocarcinoma (TCGA-CHOL) data set; n=36]. Systematic analysis was conducted and included examinations of immune infiltration [via single-sample gene set enrichment analysis (ssGSEA)], pathway enrichment (via hallmark GSEA), cellular localization (via single-cell RNA sequencing), and drug sensitivity (via the Genomics of Drug Sensitivity in Cancer 2 database). RESULTS: Two genes, CFH and SPINT2, were identified and incorporated into a prognostic risk score. High-risk patients in the training cohort had a significantly worse overall survival (log-rank P=0.02). External validation was performed in two independent cohorts. In validation cohort 1, the risk group was an independent prognostic factor [hazard ratio =2.27, 95% confidence interval (CI): 1.18-4.37; P=0.01]. In validation cohort 2, the model demonstrated acceptable discriminative ability (concordance index =0.721; 3-year area under the curve =0.692). The high-risk group exhibited an immunosuppressive microenvironment characterized by increased infiltration of macrophages and myeloid-derived suppressor cells, along with the activation of epithelial-mesenchymal transition, inflammatory response, and NF-κB signaling pathways. Single-cell analysis revealed a cell-type-specific expression pattern: CFH was predominantly expressed in fibroblasts, while SPINT2 was mainly expressed in malignant cells. Drug sensitivity analysis demonstrated that the high-risk group was more sensitive to gemcitabine, cisplatin, poly(ADP-ribose) polymerase (PARP) inhibitors, and mammalian target of rapamycin (mTOR) inhibitors, whereas the low-risk group was more sensitive to lapatinib. CONCLUSIONS: The CFH- and SPINT2-based prognostic signature may serve as an independent biomarker for postoperative risk stratification in CCA. High-risk patients, characterized by fibroblast-derived CFH enrichment and malignant-cell SPINT2 loss, exhibit an immunosuppressive microenvironment and may be more suitable for gemcitabine-based chemotherapy or PARP/mTOR inhibitors, whereas low-risk patients may benefit from less intensive adjuvant strategies or HER2/EGFR-targeted lapatinib. Prospective validation is warranted before clinical implementation.

Cholangiocarcinoma (CCA)↗

PubMedDate not supplied

[Therapeutic and prognostic significance of cardiac biomarkers in patients with the acute coronary syndrome].

Diagnostics in patients with the acute coronary syndromes (ACS) is becoming even more complex with the increase of number of available options. In addition, the number of treatment options accessible to patients with ACS keeps on growing rapidly. Physicians must now choose from a wide variety of antiplatelet and antithrombotic therapies and also determine what patients would benefit from an invasive management approach. These decisions have become more difficult with the introduction of recent drugs such as low molecular weight heparins, direct-acting antithrombins, thienopyridines, and glycoprotein IIb/IIIa inhibitors. Simple tools, which can often be applied at the patient's bedside, can help physicians to choose the intensity of antiplatelet and antithrombotic therapy, and decide whether to use invasive coronary procedures. Cardiac biomarkers have proven to be particularly effective for these purposes. Moreover, cardiac biomarkers play an important role in risk stratification in ACS, and the results of cardiac biomarker tests can be used to help us choose between alternative therapies. In addition to biomarkers of myocyte necrosis, markers of neurohormonal activation, such as B-type natriuretic peptide (BNP), provide important prognostic information in ACS. However, the increase of number of elevated biomarkers, although simple to implement in practice, does not allow for full employment of value of information provided by these biomarkers. In the future, multimarker strategies that incorporate panels of cardiac biomarkers are likely to be used for risk stratification and for pathophysiology guided treatment in patients with ACS.

Angina, Unstable↗

PubMed2025

Elevated triglyceride-glucose index and risk of thymoma-associated myasthenia gravis: a prospective analysis from the UK Biobank.

BACKGROUND: Thymoma-associated myasthenia gravis (MG) is a clinically significant but uncommon condition, affecting up to half of thymoma patients and associated with worse outcomes than either disease alone. Reliable biomarkers for early risk stratification remain scarce. The triglyceride-glucose (TyG) index and triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio are established biomarkers reflecting insulin resistance and dyslipidemia. However, their clinical associations with thymoma-associated MG remain incompletely characterized. METHODS: A total of 501,954 UK Biobank participants were included. After exclusions, 422,397 (313 cases) were analyzed for TyG index and 422,691 (314 cases) for TG/HDL-C ratio. Exposures were stratified into quartiles, and assessed continuously per unit increase. Cox proportional hazards models estimated hazard ratios (HRs), restricted cubic splines (RCS) assessed non-linear associations, and subgroup analyses were stratified by body mass index (BMI). Sensitivity analyses examined TyG index and MG alone. RESULTS: An elevated TyG index was associated with increased risk of thymoma-associated MG. Compared to Q1, Q4 had higher risk (HR = 1.66, 95% CI: 1.20-2.31, P = 0.003); the overall HR per unit increase was 1.42 (95% CI: 1.17-1.73, P = 0.0005). TG/HDL-C ratio showed similar patterns: Q4 vs Q1 HR = 1.54 (95% CI: 1.11-2.15, P = 0.01); overall HR per unit increase was 1.06 (95% CI: 1.02-1.10, P = 0.002). Non-linear relationships were observed, with suggested inflection points at TyG index 8.7 and TG/HDL-C ratio 2.8, rather than strict thresholds. Subgroup analyses revealed stronger associations in normal-weight and obese participants, although tests for interaction were not statistically significant. Sensitivity analyses confirmed consistent associations between TyG index and MG risk, including for isolated MG. CONCLUSION: Elevated TyG index and TG/HDL-C ratio were independently associated with higher thymoma-associated MG risk in this large prospective cohort, with evidence of non-linear relationships and BMI-related heterogeneity. These findings provide novel epidemiologic evidence linking metabolic markers of insulin resistance with thymoma-associated MG, but clinical translation requires further validation.

Humans↗