Clinicians are provided with a structured, evidence-based framework that identifies specific clinical scenarios where molecular diagnostics, host-response biomarkers, and three-dimensional imaging may meaningfully modify periodontal treatment decisions, supporting the operationalisation of precision approaches in daily practice.
Emerging biomarkers are fundamental for the transition to precision medicine in IBD, aiming to enhance pathogenesis understanding, personalize therapies, and improve patient quality of life, establishing pathways for more effective, individualized management approaches.
Matheus Querino da Silva, João Daniel de Souza Menezes, José Luis Esteves Francisco et al.· PLoS ONE· 0 citations
Objectives: To synthesize current evidence regarding advances in periodontal diagnosis and therapy, with emphasis on molecular biomarkers, omics technologies, microbiome profiling, digital imaging, and artificial intelligence-based analytical models that support the transition toward precision periodontology. Methods: This narrative review examines contemporary evidence on emerging molecular, microbiological, and digital technologies applied to periodontal diagnosis, prognostic assessment, and therapeutic planning. The review includes studies addressing salivary and gingival crevicular fluid biomarkers, microbiome characterization, omics approaches, cone-beam computed tomography, three-dimensional imaging, machine-learning algorithms, and personalized periodontal therapies. Relevant literature was identified through searches in major biomedical databases, including PubMed/MEDLINE, Scopus, and Web of Science, focusing on studies published on periodontal diagnostics, biomarkers, digital technologies, artificial intelligence, and precision medicine approaches in periodontology. Results: Peer-reviewed articles addressing innovative diagnostic and therapeutic approaches in periodontology were considered. Priority was given to studies evaluating clinical applicability, diagnostic performance, prognostic utility, and personalized treatment strategies integrating molecular and digital technologies. Conclusions: Emerging molecular and digital technologies are reshaping periodontal diagnosis and therapy by improving disease detection, risk prediction, and individualized treatment planning. Biomarkers, omics technologies, microbiome profiling, and artificial intelligence-assisted imaging may enhance diagnostic precision and clinical decision-making. These developments support the implementation of precision periodontology; however, challenges related to biomarker validation, algorithm standardization, cost, and accessibility remain barriers to routine clinical adoption. Further research is necessary to validate these approaches and facilitate their integration into periodontal practice. The integration of biomarkers, omics technologies, advanced imaging, and artificial intelligence may improve early periodontal diagnosis, prognostic assessment, and personalized treatment planning. These innovations support the transition toward precision periodontology and have the potential to enhance clinical decision-making, treatment outcomes, and long-term periodontal health in routine dental practice.
Tatiana Chacón, Ó. Zuluaga-López, Gloria María Sandoval-Llanos et al.· Biomedicines· 0 citations
Critical care has produced hundreds of neutral randomized trials, in part because therapies have been tested in biologically incoherent populations that dilute meaningful treatment effects. Syndromic diagnoses such as sepsis, acute respiratory distress syndrome, and traumatic brain injury group distinct pathobiological states under a single label, limiting the ability to detect treatment-responsive subgroups. While high-dimensional omics technologies have revealed this biologic heterogeneity, the field lacks a practical framework to translate these insights into clinical trial design and bedside decision-making. This Review addresses the translational gap in precision critical care through a pathway-level framework. We synthesize advances in genomics, transcriptomics, proteomics, and metabolomics, highlighting their roles in capturing susceptibility, host response, effector function, and real-time physiology. We propose pathway-focused biomarkers as clinically translatable signatures that preserve biological mechanisms while enabling practical measurement. We outline how pathway enrichment, network analysis, and multi-omic integration can identify these programs, and how feature selection can derive parsimonious biomarker panels for clinical use. This approach also supports pathway-guided drug repurposing by linking dysregulated molecular programs to existing therapies. Together, these signatures provide a framework for predictive enrichment, aligning patient selection with therapeutic mechanisms and facilitating implementation within adaptive platform trials. This Review serves as a practical primer that outlines the concepts and methods needed to translate omics into clinically actionable tools. By shifting from syndromic classification to pathway-defined biology, it provides a framework for biomarker development, trial design, and precision critical care.
L. V. Van Nynatten, Hira Raheel, J. Basmaji et al.· Critical Care· 2 citations
Genetic neuromuscular diseases are highly heterogeneous disorders characterized by diagnostic challenges and limited therapeutic options, underscoring an urgent need for precise biomarkers. The rapid advancement of multi‐omics technologies has broadened biomarker discovery from single genomics to multidimensional integrative analyses encompassing transcriptomics, proteomics, and metabolomics. This progression offers opportunities to improve disease diagnosis, subtyping, prognosis assessment, and treatment monitoring. However, translational gaps persist between multi‐omics discoveries and clinically applicable biomarkers. This review systematically examines the current application of multi‐omics biomarkers in genetic neuromuscular diseases. It provides an in‐depth analysis of the multifaceted barriers encountered during the translation process, including technical hurdles, clinical validation complexities, data interpretation challenges, and health system‐level obstacles. Furthermore, the review explores emerging solutions including artificial intelligence‐assisted decision‐making, ethical governance, and policy preparedness. The review aims to offer a framework for constructing a potentially responsible and efficient multi‐omics translation in genetic neuromuscular diseases.
Suming Zhang, Xiaoling Lang, Lunxin Liu· Human Mutation· 0 citations
AIM
To critically evaluate the emerging contribution of genomics, transcriptomics, proteomics, metabolomics and microbiomics to the development of precision endodontics, and to examine the opportunities and translational challenges associated with integrating omics technologies into clinical endodontic practice.
METHODOLOGY
This narrative review synthesises recent literature across the biomedical and dental sciences, encompassing endodontic research and the principles of translational precision medicine and dentistry to assess the potential applications of omics technologies in endodontics, focusing on how these innovative approaches can inform clinical practice.
RESULTS
Emerging evidence suggests that omics technologies may enhance understanding of the biological mechanisms underlying pulpal and periapical diseases and support the identification of candidate biomarkers relevant to diagnosis, prognosis, treatment selection and outcome monitoring. Genomic and transcriptomic studies have identified molecular signatures associated with host susceptibility, inflammatory responses and tissue repair processes. Proteomic and metabolomic investigations have revealed biomarkers and metabolic pathways that may improve disease characterisation and provide insight into pulpal vitality and periapical healing. Microbiomic analyses have expanded understanding of the complex microbial ecology of endodontic infections and may contribute to the development of more targeted disinfection strategies. Furthermore, integrating multi-omics platforms and data with artificial intelligence (AI) could yield sophisticated predictive models to support personalised decision-making, thereby advancing individualised patient care. However, despite these advances, the current evidence remains largely exploratory. Many reported biomarkers and molecular signatures have not undergone robust validation, and significant challenges persist regarding standardisation, reproducibility, data integration, cost-effectiveness and clinical implementation.
CONCLUSION
The concept of precision endodontics represents a potential evolution from conventional 'one-size-fits-all' approaches to more tailored interventions guided by extensive omics data. The synergistic integration of omics and AI may provide a roadmap for developing the next generation of biologically individualised endodontic therapies. However, translating omics-driven approaches into clinically applicable diagnostic and therapeutic tools remains at an early stage. Future progress will depend on rigorous validation studies, interdisciplinary collaboration and the development of practical translational frameworks. While the combined application of omics technologies and AI has considerable potential, substantial evidence gaps must be addressed before precision endodontics can be routinely implemented in clinical practice.
M. Turky, P. Cooper, Paul M. H. Dummer· International Endodontic Jou...· 0 citations
Rheumatoid arthritis (RA) is a biologically heterogeneous immune-mediated disease characterized by substantial variability in therapeutic response. Despite the availability of multiple conventional synthetic, biologic, and targeted synthetic disease-modifying antirheumatic drugs (DMARDs), many patients fail to achieve adequate disease control or experience secondary loss of efficacy, underscoring the need for predictive biomarkers that can guide treatment selection. This narrative review was based on a structured literature search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar, covering publications from January 2000 to June 2026, with earlier landmark studies included when relevant. Literature selection followed PRISMA-informed principles, although the review was not designed as a formal systematic review. Unlike previous reviews that mainly catalogue RA biomarkers by analytical platform, drug class, or clinical use, this review integrates conventional and emerging biomarkers within a tissue-immunophenotype-centered framework. We critically evaluate clinical, serological, pharmacological, molecular, imaging, and tissue-based biomarkers according to biological plausibility, reproducibility, level of validation, clinical actionability, and translational readiness. Established markers such as rheumatoid factor, anti-citrullinated protein antibodies, acute-phase reactants, drug concentrations, and anti-drug antibodies remain clinically useful but provide incomplete insight into mechanism-specific therapeutic response. In contrast, synovial pathotypes, fibroblast and macrophage subsets, B-cell niches, tertiary lymphoid structures, single-cell and spatial omics, and ligand–receptor interaction networks offer a mechanistically richer view of treatment response and resistance. We conclude that precision medicine in RA will require integrated biomarker panels combining clinical, pharmacological, molecular, and synovial tissue data. The key future direction is the development of scalable, externally validated, and clinically interpretable models capable of assigning synovial endotypes and supporting mechanism-based therapeutic selection.
N. A. Batashkov, E. Gerasimova, D. Gerasimova et al.· Frontiers in Immunology· 0 citations
