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  • Software engineering plays a key role in developing high-quality healthcare systems, particularly in Precision Medicine, where advanced systems are required to tailor clinical interventions based on individual genetic, environmental, and lifestyle factors. Therefore, it is necessary to rethink software engineering methods to address the significant challenges in healthcare systems, especially in system design, complex data analysis, traceability, and AI explainability. This paper presents the MATIIGEN project, which aims to address these challenges. MATIIGEN introduces an intelligent system for automated DNA variant interpretation. The project combines Model-Driven Software Engineering (MDSE) principles with Explainable Artificial Intelligence (XAI) to support the transition of genomic tools from laboratory validation environments (TRL4) to operational clinical settings (TRL6). MDSE provides the structural and methodological basis for building robust, traceable, and interoperable software systems, and XAI provides mechanisms to make the system’s outputs more transparent and understandable to clinicians. The applicability of MATIIGEN platform is demonstrated through a historically overlooked chronic disease: Lipedema. By focusing on a condition that is under-researched in clinical settings, we can demonstrate that the MATTIGEN platform can generate insights in areas of medicine where data is scarce and complex. Our work demonstrates that adopting MDSE principles provides a systematic methodology for transforming multifaceted clinical data into actionable medical insights and establishes a scalable architecture for high-quality, software-intensive systems in the healthcare domain.

  • Background/Objectives: Lipedema is a chronic disorder that affects almost exclusively women and is characterized by bilateral, symmetrical accumulation of subcutaneous fat, typically in the buttocks, hips, and lower limbs, and in some cases the arms. The primary objective of this study was to describe the clinical and anatomical manifestations of lipedema, together with the associated physical and psychological comorbidities, in a large Spanish cohort. Methods: Descriptive study of 1803 patients aged ≥ 17 years who attended two clinics in Spain between January 2022 and November 2024. Results: The mean age was 42.9 years (SD: 11.3), and 60.6% of patients were diagnosed during their reproductive years. The mean body mass index was 28.6 (SD: 6.2), and 87.6% presented a gynoid fat distribution. A total of 46.6% were classified as Schingale stage IV or V. The most frequent comorbidities were chronic low-grade inflammatory alterations and connective tissue damage. Particularly suspected high intestinal permeability (99%), bilateral trochanteric pain region (97.4%), iliotibial band involvement, and ligamentous hyperlaxity (95.8%). Thyroid disorders, inflammatory ovarian dysfunction, and psychological impairment were also common. Conclusions: Lipedema is a complex condition that extends beyond lower-limb adipose tissue and is associated with multiple comorbidities. This study also presents a novel approach to clinical assessment that may help physicians gain a deeper understanding of this pathology and formulate etiological hypotheses that will need to be tested.

Last update from database: 11/1/26, 8:25 AM (UTC)

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