Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG).

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

A Community-Led Approach as a Guide to Overcome Challenges for Therapy Research in Congenital Disorders of Glycosylation.

Congenital Disorders of Glycosylation (CDG) are a large family of rare genetic diseases for which effective therapies are almost nonexistent. To better understand the reasons behind this, to analyze ongoing therapy research and development (R&D) for CDG, and to provide future guidance, a community-led mixed methods approach was organized during the 4th World Conference on CDG for Families and Professionals. In the quantitative phase, electronic surveys pointed to the prioritization of six therapeutic R&D tools, namely biobanks, registries, biomarkers, disease models, natural history studies, and clinical trials. Subsequently, in the qualitative phase, the challenges and solutions associated with these research tools were explored through community-driven think tanks. The multiple challenges and solutions identified administrative/regulatory, communication, financial, technical, and biological issues, which are directly related to three fundamental aspects of therapy R&D, namely data, sample, and patient management. An interdependence was traced between the prioritized tools, with diagnosis and therapies acting as bidirectional triggers that fuel these interrelationships. In conclusion, this study's pioneering and adaptable community-led methodology identified several CDG therapy R&D gaps, many common to other rare diseases, without easy solutions. However, the strong proactive attitude towards research, based on inclusive and international partnerships and involving all members of the CDG community, sets the direction for better future therapy R&D.

Patient-reported outcomes and quality of life in PMM2-CDG.

Patient-reported outcomes (PROs) measure important aspects of disease burden, however they have received limited attention in the care of patients with Congenital Disorders of Glycosylation (CDG). We evaluated the PROs and correlation between clinical disease severity scoring and reported quality of life (QoL) in a PMM2-CDG patient cohort. Twenty-five patients with diagnosis of PMM2-CDG were enrolled as part of the Frontiers in Congenital Disorders of Glycosylation Consortium (FCDGC) natural history study. Patient- Reported Outcomes Measurement Information System (PROMIS) was completed by caregivers to assess health-related QoL. Clinical disease severity was scored by medical providers using the Nijmegen Progression CDG Rating Scale (NPCRS). The domains such as physical activity, strength impact, upper extremity, physical mobility, and a satisfaction in social roles (peer relationships) were found to be the most affected in the PMM2-CDG population compared to US general population. We found a strong correlation between NPCRS 1 (current functional ability) and three out of ten PROMIS subscales. NPCRS 2 (laboratory and organ function) and NPCRS 3 (neurological involvement) did not correlate with PROMIS. Mental health domains, such as anxiety, were positively correlated with depressive symptoms (r = 0.76, p = 0.004), fatigue (r = 0.67, p = 0.04). Surprisingly, patients with severely affected physical mobility showed low anxiety scores according to PROMIS (inverse correlation, r = -0.74, p = 0.005). Additionally, there was a positive correlation between upper extremity and physical mobility (r = 0.75, p = 002). Here, we found that PROMIS is an informative additional tool to measure CDG disease burden, which could be used as clinical trial outcome measures. The addition of PROMIS to clinical follow-up could help improve the quality of care for PMM2-CDG by facilitating a holistic approach for clinical decision-making. SYNOPSIS: We recommend PROMIS as an informative tool to measure disease burden in PMM2-CDG in addition to traditional CDG disease severity scores.