The role of public health in rare diseases: hemophilia as an example

Frontiers in Public Health, Journal Year: 2025, Volume and Issue: 13

Published: March 20, 2025

Introduction The role of public health has evolved from addressing infectious diseases to encompass non-communicable diseases. Individuals with genetic disorders and rare constitute a particularly vulnerable population, requiring tailored policies, practical implementation strategies, long-term vision ensure sustainable support. Given the prolonged duration significant costs often associated these conditions, comprehensive, patient-centered, cost-effective approaches are essential safeguard their physical mental well-being. Aims To summarize definitions concepts related health, diseases, highlight integrating interventions into routine care in improving patient outcomes. Hemophilia was selected as an exemplary disease due its lifetime treatment recent approval pricing gene therapy world’s most expensive drug, highlighting critical importance policies ensuring equitable access treatment. Methods A narrative literature review conducted between July 2023 December 2024, searching PubMed, Google Scholar, for various topics hemophilia. Results Public can play important outcomes people by implementing conceptual applied models accomplish set objectives. Over past two decades, legislative regulatory support high income countries (HICs) facilitated development diagnostics treatments several leading advancements. In contrast, many low- middle-income (LMICs) face obstacles enacting legislation, developing regulations, diagnosis More investment innovation drug discovery market pathways still needed both LMICs HICs. Ensuring translation measures, turn implementing, regularly evaluating measures assess effectiveness is crucial. case hemophilia, pivotal role. Conclusion Enhancing surveillance, hemophilia other bridge data gaps, treatment, promote evidence-based care, improve across socioeconomic spectrum.

Language: Английский

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Unravelling disease complexity: integrative analysis of multi-omic data in clinical research

Expert Review of Proteomics, Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

A holistic view on biological systems is today a reality with the application of multi-omic technologies. These technologies allow profiling genome, epigenome, transcriptome, proteome, metabolome as well newly emerging 'omes.' While multiple layers data accumulate, their integration and reconciliation in single system map cumbersome exercise that faces many challenges. Application to human health disease requires large sample size, robust methodologies high-quality standards. We review different methods used integrate multi-omics, recent ones including artificial intelligence. With proteomics an anchor technology, we then present selected applications its combination other omics' clinical research, mainly covering literature from last five years Scopus and/or PubMed databases. Multi-omics powerful comprehensively type molecular link them phenotype. Yet, are very diverse still strategies properly these modalities needed.

Language: Английский

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Epigenomic insights and computational advances in hematologic malignancies

Molecular Cytogenetics, Journal Year: 2025, Volume and Issue: 18(1)

Published: April 12, 2025

Hematologic malignancies (HMs) encompass a diverse spectrum of cancers originating from the blood, bone marrow, and lymphatic systems, with myeloid representing significant complex subset. This review provides focused analysis their classification, prevalence, incidence, highlighting persistent challenges posed by intricate genetic epigenetic landscapes in clinical diagnostics therapeutics. The basis malignancies, including chromosomal translocations, somatic mutations, copy number variations, is examined detail, alongside modifications specific emphasis on DNA methylation. We explore dynamic interplay between factors, demonstrating how these mechanisms collectively shape disease progression, therapeutic resistance, outcomes. Advances diagnostic modalities, particularly those integrating epigenomic insights, are revolutionizing precision diagnosis HMs. Key approaches such as nano-based contrast agents, optical imaging, flow cytometry, circulating tumor analysis, mutation testing discussed, particular attention to transformative role machine learning data analysis. methylation episignatures have emerged pivotal tool, enabling development highly sensitive prognostic assays that now being adopted practice. also impact computational advancements integration refining strategies. By combining genomic profiling techniques, innovations accelerating biomarker discovery translation, applications oncology becoming increasingly evident. Comprehensive datasets, coupled artificial intelligence, driving actionable insights into biology facilitating optimization patient management Finally, this emphasizes translational potential advancements, focusing tangible benefits for care synthesizing current knowledge recent innovations, we underscore critical medicine research transforming treatment setting stage ongoing broader implementation.

Language: Английский

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Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease

Orphanet Journal of Rare Diseases, Journal Year: 2025, Volume and Issue: 20(1)

Published: April 17, 2025

Abstract Background Use of artificial intelligence (AI) in rare diseases has grown rapidly recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify analyse large amounts data, such as standardized images or specific text electronic health records. To illustrate how these been adapted developed for use with diseases, focused on Fabry disease, an X-linked genetic disorder caused by lysosomal α-galactosidase. A deficiency that can result multiple organ damage. Methods We searched PubMed articles focusing AI, disease published anytime up 08 January 2025. Further searches, limited between 01 2021 31 December 2023, were also performed using double combinations keywords related AI each affected diseases. Results total, 20 included. field, may be applied prospectively populations identify patients, retrospectively data sets diagnose a previously overlooked disease. Different facilitate diagnosis, help monitor progression organs, potentially contribute personalized therapy development. The implementation general healthcare medical imaging centres raise awareness prompt practitioners consider conditions earlier diagnostic pathway, while chatbots telemedicine accelerate patient referral experts. technologies generate ethical risks, prompting new regulatory frameworks aimed at addressing issues established Europe United States. Conclusion AI-based will lead substantial improvements diagnosis management need human guarantee is key issue pursuing innovation ensuring involvement remains centre care during technological revolution.

Language: Английский

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