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PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗

PubMed2025

In vitro protocol demonstrating five functional steps of trained immunity in mice: Implications on biomarker discovery and translational research.

We developed an in vitro methodology to study trained immunity using murine bone-marrow-derived macrophages stimulated with β-glucan and lipopolysaccharide (LPS). Longitudinal analysis of interleukin (IL)-6 and tumor necrosis factor (TNF) production demonstrates that trained macrophages secrete higher cytokine levels following primary stimulation with β-glucan compared to unstimulated macrophages (step 1). After a resting period, trained macrophages return to basal levels of cytokine production (step 2) but rapidly produce enhanced levels of IL-6 and TNF after secondary stimulation with LPS, compared to macrophages individually stimulated with either β-glucan (step 3) or LPS (step 4) alone. The combined cytokine production of macrophages after single stimulation with β-glucan (stimulus 1) and LPS (stimulus 2) is significantly lower than the cytokine levels produced by trained macrophages sequentially stimulated with both β-glucan and LPS (stimulus 1 + 2) (step 5). These results experimentally reproduce the distinctive functional stages that macrophages undergo during the training process.

Animals↗

PubMed2025

Sustainability in translational genomics research with undiagnosed patients: What is it, why do we need it, and how do we do it?

PURPOSE: Genomics research enrolling undiagnosed patients can provide answers for one-third of participants, and more can be diagnosed through future reanalysis. The long-term value for participants has raised questions of the sustainability of these studies, but the meaning, goals, and best practices for sustainability remain unclear. METHODS: We conducted semistructured interviews with researchers leading studies enrolling undiagnosed patients in the United States and Canada and used thematic content analysis to summarize key themes. RESULTS: Researchers lacked consensus regarding what sustainability was actually intended to sustain, variably referencing study procedures, personnel, data access, and participant recontact. However, the primary driver of sustainability was widely shared as the perceived obligation to continue to search for answers for undiagnosed participants. Proposed sustainability strategies included diversifying funding sources, developing centralized data infrastructure, and building collaborations across disciplines and institutions. Researchers also emphasized the need to address ethical concerns, to integrate research with clinical care, and for leadership from research funders to guide these efforts. CONCLUSION: Although genomics researchers perceived continued obligations to undiagnosed participants, they also lacked a shared understanding of the goals of sustainability and called for coordinated efforts to develop centralized infrastructure that integrated research and clinical care.

Humans↗

PubMed2026

Research updates in cystic fibrosis related diabetes: Understanding pathophysiology, expanding animal and human islet models, and advancing clinical and translational research.

In 2024-2025, the Cystic Fibrosis Foundation (US) and Cystic Fibrosis Trust (UK) hosted an International CFRD Consortium round-table webinar series for basic science, translational, and clinical researchers with the goal of sharpening mechanistic understanding of CFRD pathogenesis and prioritizing therapeutic development. This review summarizes the research priorities identified in the International CFRD Consortium, including (i) further investigation into the role of pancreatic fibrosis, vascular abnormalities, and α-cell dysfunction in the development of CFRD; (ii) the creation and refinement of novel animal and human cell- and tissue-based models to understand the complex interplay of exocrine and endocrine cells in the CF pancreas; (iii) development and validation of circulating and imaging biomarkers, together with dynamic glucose testing to explore β-cell function and kinetics in people with CF across the dysglycemia spectrum; and (iv) prospective clinical studies to guide CFRD treatment options and investigate the changing landscape of aging, increasing prevalence of obesity and diabetes and their complications in the era of cystic fibrosis transmembrane conductance regulator (CFTR) modulators. Collectively, these priorities aim to accelerate transition from mechanism to intervention and expand evidence-based care for people with CF at risk of, or living with, CFRD.

Humans↗

PubMed2026

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

Humans↗

PubMed2026

Unlocking the Circulating Proteome: Toward Clinical Translation.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Humans↗

PubMed2025

Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.

Diabetes mellitus encompasses several disorders, each with differing clinical presentation, prognoses and pathophysiology. Distinct polygenic architectures underlie type 1 diabetes mellitus and type 2 diabetes mellitus, and govern numerous pathophysiological pathways that converge on dysglycaemia. Over the previous decade, polygenic risk scores (PRS) derived from large genome-wide association studies have become broadly recognized for their potential in precision medicine. PRS, and now partitioned polygenic scores generated by clustering of risk variants, can quantify individual genetic predisposition to diabetes mellitus and reveal molecular heterogeneity responsible for variation in clinical presentation and prognoses. In this Review, we examine and contrast progress in the development of type 1 diabetes mellitus PRS and type 2 diabetes mellitus PRS, and discuss paths to further methodological advances. We examine how studies in the past 10 years have harnessed PRS and novel partitioned polygenic scores to reveal insights into diabetes mellitus aetiology and characterize changes in cellular and tissue-specific disease-modifying molecular pathways. Additionally, we discuss advances and opportunities in areas of clinical translation, including improved classification of diabetes mellitus type, screening of those at risk and personalized interventions informed by PRS. Finally, we emphasize the urgent need to overcome ancestry-related challenges and highlight current progress and gaps in ensuring the equitable translation of PRS for diabetes mellitus precision medicine.

Humans↗

PubMed2026

Five tenets for advancing evidence-based precision medicine.

Precision medicine for complex diseases uses individual-level characteristics to improve prediction of risk, therapeutic response and prognosis. Many precision medicine studies leverage existing data types and analytic methods to reveal new insights; however, beyond oncology, there has been limited success in translating precision medicine research for complex diseases into clinical practice. Thus, there is a need to identify areas for improvement, particularly in translation-oriented analytical methods and study designs. In this perspective article, we outline five fundamental tenets to enhance the efficient clinical translation of precision medicine research. These tenets focus on addressing (1) heterogeneity in risk, response and prognosis; (2) signal robustness; (3) structured statistical benchmarking against key performance indicators; (4) precision trial designs; and (5) risks and benefits to individuals and society. Our intention is to promote clinically meaningful, reproducible, scalable and equitable health outcomes through precision medicine, beyond those possible through contemporary approaches.

Precision Medicine↗

PubMed2026

A translational framework for early-phase inner-ear gene therapy: clinical trial design, regulatory strategy, and ethical considerations.

PURPOSE OF REVIEW: Hereditary hearing loss has historically been approached as a diagnostic category rather than a therapeutically modifiable disease. Recent advances in molecular genetics, cochlear gene delivery, and first-in-human clinical trials are changing that. This review summarizes contemporary progress in the genetics of hearing loss, with emphasis on emerging gene-based therapies, clinical trial design, regulatory and ethical considerations, and practical implications for otolaryngologists as biologic treatment enters clinical practice. RECENT FINDINGS: Early clinical trials targeting OTOF -related DFNB9 deafness have demonstrated satisfactory safety profiles and meaningful auditory recovery, establishing the first proof-of-concept for cochlear gene therapy in humans, culminating in the April 2026 FDA approval of Otarmeni. Genetic diagnoses are increasingly informing prognosis, cochlear implant counseling, and therapeutic candidacy. Preclinical research continues to expand toward recessive, dominant, and syndromic hearing loss using gene replacement, antisense, RNA interference, and genome-editing strategies. Substantial challenges remain, including heterogeneous outcome measures, uncertain long-term efficacy, regulatory complexity, and inequitable global access. SUMMARY: The genetics of hearing loss is transitioning from a diagnostic modality to an interventional one. Widespread clinical impact will require advances in vector engineering, equitable implementation, multidisciplinary counseling, and integration with established rehabilitation pathways. For otolaryngologists, genetic literacy is becoming essential to contemporary hearing care.

Humans↗

PubMed2026

Multiomics approaches to cardiovascular disease: technological innovations and clinical translation.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, reflecting a persistent gap between clinical phenotyping and the molecular mechanisms that govern disease initiation, progression, and interindividual variability. Recent advances in emerging technologies have fundamentally reshaped cardiovascular physiology by enabling high-resolution, cross-layer profiling of the heart and vasculature across genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, and fluxomic layers, increasingly at single-cell and spatial resolution. These approaches reveal CVD as a coordinated, multilayered process driven by dynamic interactions among cell types, regulatory programs, and metabolic states, rather than isolated gene-level defects. In this review, we synthesize how emerging multiomic, computational, and functional genomic technologies are redefining the study of cardiovascular disease across molecular, cellular, and tissue levels. We highlight recent innovations in single-cell and spatial atlases, long-read sequencing, proteomics and metabolomics, integrative data modeling, and functional omics approaches, including genome-scale perturbation screens and single-cell perturbation frameworks. These platforms enable mechanistic dissection of regulatory circuits, distinguish primary disease drivers from secondary adaptations, and directly assess therapeutic reversibility, advancing the field beyond associative biomarker discovery toward mechanism-guided target prioritization. We further discuss key methodological and translational challenges accompanying high-dimensional cardiovascular data, including preanalytical variability, control selection, temporal misalignment across molecular layers, population diversity, and reference bias. By integrating technological innovation with computational rigor and functional validation, this review frames emerging omics-enabled strategies as a unified, physiologically grounded framework for translating molecular insight into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

Humans↗

PubMed2026

Application of a Translational Research Platform to Unveil Efficacy Signals and Mechanisms of Resistance of FGFR Inhibitors in Multiple FGFR-Altered Solid Tumors.

PURPOSE: The predictive value of fibroblast growth factor receptor (FGFR) amplifications (amp) and the role of FGFR mutations (mut) beyond known activating variants remain unclear. We aimed to establish a translational research platform to characterize FGFR alterations (alt) and explore their potential as predictive biomarkers for FGFR-targeted agents. EXPERIMENTAL DESIGN: This ambispective study included a retrospective analysis of patients with FGFR-alt tumors treated with selective FGFR inhibitors (FGFRi) and a prospective collection of longitudinal tumor samples. Patient-derived xenografts (PDX) were generated to investigate FGFRi mechanisms of action and resistance. Molecular characterization included genomic, transcriptomic, proteomic, and functional analyses using the Functional Annotation for Cancer Treatment (FACT) assay. RESULTS: Among 36 retrospectively analyzed patients, clinical benefit from FGFRis was observed in cases with FGFR mRNA overexpression or FGFR2/11q co-amp, but no association was found with the amplification levels. In archival tumor samples, exploratory proteomic analysis showed FGFR1-4 protein expression in 78% of FGFR1/2-amp tumors detected by fluorescence in situ hybridization. RNA sequencing identified a higher prevalence of FGFR mRNA overexpression than proteomic analysis. Among patients harboring FGFR-mut, only one bladder cancer with an FGFR3-mut S249C derived benefit. FACT assay supported the functional activity of selected variants, including FGFR3 T689M, and suggested potential resistance mechanisms involving PI3K/PTEN and MAPK pathway co-alterations. A prospective FGFR-alt PDX biorepository enabled exploratory biomarker analyses, supporting the hypothesis that FGFR1-4 mRNA expression may better reflect FGFR dependency than genomic alterations alone. CONCLUSIONS: These findings highlight the complexity of FGFR-driven oncogenesis and support integrative molecular approaches to refine patient selection for FGFR-targeted therapies.

Humans↗

PubMed2026

Adeno-Associated Virus Gene Therapy Translation: Lessons from Early Regulatory Meetings.

The Platform Vector-Gene Therapy (PaVe-GT) program is a National Institutes of Health (NIH) initiative that aims to develop adeno-associated virus (AAV) gene therapies for four monogenic rare diseases, two organic acidemias and two congenital myasthenic syndromes. PaVe-GT's platform-based approach identifies and diminishes redundancies and applies efficiencies in preclinical, clinical, and regulatory activities. The program's hypothesis is that implementing these efficiencies can accelerate clinical trial initiation. Based on its platform-centric experience and public-serving mission, the PaVe-GT program actively shares its scientific and regulatory learnings with the public to benefit the development of similar gene therapy products for rare diseases. PaVe-GT's first investigational AAV gene therapy candidate is AAV serotype 9 human propionyl-CoA carboxylase alpha subunit (AAV9-hPCCA) for propionic acidemia caused by PCCA deficiency, which received initial feedback from the Food and Drug Administration (FDA) in an INitial Targeted Engagement for Regulatory Advice on CBER/Center for Drug Evaluation and Research (CDER) ProducTs (INTERACT) meeting. Upon further product development that took into consideration the FDA's initial advice, the program obtained the Agency's feedback in pre-investigational new drug (IND) (Type B) and Type C meetings. Here, we share our experience from these meetings, including strategy, preparation, pre- and post-meeting feedback from the FDA, and lessons learned during the AAV9-hPCCA regulatory process, which the program plans to apply across the PaVe-GT platform. Topics discussed in the regulatory meetings included animal model and efficacy studies, toxicology study plans, manufacturing of the investigational AAV product, and clinical trial design. The main lessons learned from the pre-IND and Type C meetings for AAV9-hPCCA are: (1) Pharmacology/Toxicology studies in a single rodent species are sufficient for filing an initial IND; (2) FDA feedback guides product quality improvements and early development of a quantitative potency assay; (3) use of biomarkers as potential surrogate endpoints in a future efficacy trial benefits from collection of data in the natural history study and the first-in-human Phase 1/2 study; and (4) evidence from the Phase 1/2 clinical trial could be leveraged to support a license application. Lightly redacted regulatory documents and comprehensive templates developed by the PaVe-GT team are available on the PaVe-GT website.

Dependovirus↗

PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗

PubMed2025

Advancing translational exposomics: bridging genome, exposome and personalized medicine.

Understanding the interplay between genetic predisposition and environmental and lifestyle exposures is essential for advancing precision medicine and public health. The exposome, defined as the sum of all environmental exposures an individual encounters throughout their lifetime, complements genomic data by elucidating how external and internal exposure factors influence health outcomes. This treatise highlights the emerging discipline of translational exposomics that integrates exposomics and genomics, offering a comprehensive approach to decipher the complex relationships between environmental and lifestyle exposures, genetic variability, and disease phenotypes. We highlight cutting-edge methodologies, including multi-omics technologies, exposome-wide association studies (EWAS), physiology-based biokinetic modeling, and advanced bioinformatics approaches. These tools enable precise characterization of both the external and the internal exposome, facilitating the identification of biomarkers, exposure-response relationships, and disease prediction and mechanisms. We also consider the importance of addressing socio-economic, demographic, and gender disparities in environmental health research. We emphasize how exposome data can contextualize genomic variation and enhance causal inference, especially in studies of vulnerable populations and complex diseases. By showcasing concrete examples and proposing integrative platforms for translational exposomics, this work underscores the critical need to bridge genomics and exposomics to enable precision prevention, risk stratification, and public health decision-making. This integrative approach offers a new paradigm for understanding health and disease beyond genetics alone.

Humans↗

PubMed2026

Epigenetic Profiling for Early Detection and Treatment Response Monitoring in Non-Small Cell Lung Cancer: Protocol for a Prospective Translational Biomarker Study.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide and continues to have poor survival outcomes, with most patients diagnosed at advanced stages of disease. In New Zealand, NSCLC contributes substantially to cancer inequities, with Māori communities experiencing disproportionately high incidence and mortality rates. Although low-dose computed tomography screening can improve early detection, major limitations remain, including false-positive findings, overdiagnosis, high infrastructure costs, and limited accessibility for rural and underserved populations. Liquid biopsy approaches using circulating tumor DNA (ctDNA), particularly DNA methylation profiling, have emerged as promising, minimally invasive strategies for improving cancer detection, treatment monitoring, and precision oncology. OBJECTIVE: This study aims to establish integrated genomic and epigenomic predictive and prognostic biomarkers using ctDNA, tumor tissue, and transcriptomic profiling to improve early detection, risk stratification, treatment selection and response prediction, and longitudinal monitoring, with particular emphasis on identifying molecular mechanisms associated with treatment resistance and disease progression. METHODS: This prospective observational translational biomarker study is being conducted through the University of Otago and associated respiratory and oncology services in New Zealand. The study will recruit participants with NSCLC (including squamous and nonsquamous subtypes), individuals referred to fast-track lung nodule assessment clinics, and nonmalignant respiratory controls. Serial peripheral blood sampling will be performed in selected participants at predefined clinical follow-up time points to evaluate treatment response and disease progression. The availability of formalin-fixed paraffin-embedded archival tissues will be recorded, but will not be mandatory for enrollment. Genome-scale DNA methylation profiling will be performed using cell-free reduced representation bisulfite sequencing (cfRRBS), while targeted genomic profiling and transcriptomic analyses will be conducted using targeted sequencing panels and RNA sequencing. Integrative bioinformatic analyses will be used to identify molecular biomarkers associated with early-stage disease, advanced disease, treatment response, and therapeutic resistance. RESULTS: Ethics approval for the study has been obtained from the New Zealand Health and Disability Ethics Committee (2022 EXP 12566). This study commenced in 2022, and recruitment and biospecimen collection are ongoing. The study aims to recruit approximately 450 participants, including patients with NSCLC, individuals referred through respiratory diagnostic pathways, and nonmalignant controls. As of July 31, 2026, 205 participants have been recruited, with recruitment continuing until the target sample size is reached. Molecular and data analyses are ongoing, with additional publications expected as the cohort matures. CONCLUSIONS: This study will generate one of the first integrated genomic, epigenomic, and transcriptomic liquid biopsy datasets for NSCLC in New Zealand. The findings are expected to support the development of sensitive, accessible, and equitable blood-based biomarkers for NSCLC detection and treatment monitoring while also contributing to improved precision oncology approaches and reducing NSCLC inequities among Māori populations.

Humans↗

PubMed2026

Molecular Pathways, Target Landscape, and Translational Models in Heart Failure with Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) is a substantial global health burden and the greatest unmet medical need for cardiovascular diseases. It is marked by pronounced clinical heterogeneity and complex multi-system pathophysiology with limited therapeutic options. Progress in developing effective therapeutics is constrained by the inadequacy of experimental models to fully recapitulate the multifactorial nature of the disease. Recent evidence underscores the significant involvement of inflammatory, oxidative, and mitochondrial pathways in the pathogenesis of HFpEF, with non-coding RNAs and epigenetic regulation serving as crucial modulators and prospective therapeutic targets. This review maps the HFpEF target landscape, while critically assessing the mechanistic contributions, translational fidelity, and limitations of existing in vivo and in vitro models. Further, advances are noted among the in vitro technologies, including human cardiac organoids and engineered heart tissues integrated with high-throughput multi-omics and computational modeling, enabling in-depth examination of HFpEF mechanisms. Finally, we underscore the necessity of integrative, systems-level approaches and multi-marker strategies to enhance translational relevance, improve risk stratification, and accelerate development of mechanism-based therapies. Collectively, this review supports phenotypic-guided and mechanism-informed therapeutic development for HFpEF, and provides a roadmap for next generation model development and therapeutic innovation.

Humans↗

PubMed2026

Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays.

Humans↗

PubMed2026

Molecular and Genomic Mechanisms Linking Diabetes Mellitus and Periodontitis: From Pathogenesis to Translational Opportunities.

Diabetes mellitus and periodontitis are bidirectionally associated chronic disorders linked through metabolic dysregulation, host inflammation, microbial dysbiosis, and impaired tissue remodeling. This review summarizes clinical, molecular, cellular, genomic, epigenomic, transcriptomic, and microbial evidence concerning the mechanisms underlying this relationship and their potential translational relevance. Chronic hyperglycemia is associated with advanced glycation end product signaling through the receptor for advanced glycation end products, mitogen-activated protein kinase/nuclear factor-κB activation, reactive oxygen species production, oxidative stress, and NLR family pyrin domain-containing 3 inflammasome activation, which may contribute to enhanced cytokine responses and periodontal tissue injury. Diabetes is also associated with altered neutrophil and macrophage function, increased T helper 17/interleukin-17 signaling, and an elevated receptor activator of nuclear factor-κB ligand/osteoprotegerin ratio, thereby favoring osteoclastogenesis and alveolar bone loss. Conversely, periodontal inflammation and microbial products may contribute to systemic low-grade inflammation, insulin resistance, and metabolic dysregulation. Multi-omics studies have identified shared susceptibility loci, regulatory networks, and disease-associated cell states, although their causal and clinical significance remains incompletely defined. These findings suggest potential roles for integrated medical-dental care, glycemic screening in dental settings, periodontal inflammation control, host-modulatory therapies, and regenerative biomaterials. Further longitudinal and experimental studies are needed to determine their clinical applicability.

Humans↗