Introduction Congenital heart defects (CHD) constitute a prevalent group of structural birth anomalies, characterised by substantial genetic heterogeneity and diverse clinical phenotypes. Methods To investigate the underlying genetic architecture, we performed whole-genome sequencing (WGS) in a cohort of 50 patients with echocardiographically confirmed CHD, followed by systematic variant identification and functional annotation. Results Our analysis reveals the limited discriminatory capacity of current genomic annotation databases and underscores the necessity of stratifying genetic risk assessments by specific CHD subtypes. By integrating clinical classifications, genomic data, and tissue-specific expression profiles, we identified novel coding and non-coding variants alongside putative regulatory signals that may contribute to CHD pathogenesis. Within cardiac-specific genes, we identified CHD subtype-specific genetic associations, including JARID2 with PDA, GOSR2/TBX18 with VSD, PCDHA9 with ASD, and a multi-gene signature (CREBBP, ZFPM2, SLC27A6, ADAM17, ETS1) with atrioventricular septal defects. Among coding variants in non-CHD-associated genes, we identified COL11A2 and PCOLCE2 as plausible collagen-related candidates for CHD pathogenesis. Discussion These findings reinforce the polygenic architecture of CHD and highlight the value of context-aware, phenotype-driven interpretation of genetic variants. Collectively, this study expands the understanding of the genetic landscape underlying congenital heart anomalies and emphasises the need for larger, deeply phenotyped cohorts to translate these preliminary insights into clinically applicable predictors.
A. Korobeinikova, E. Petriaikina, D. Tychinin et al.· Frontiers in Cardiovascular...· 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