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The amount of data collected and managed in (bio)medicine is ever-increasing. Thus, there is a need to rapidly and efficiently collect, analyze, and characterize all this information. Artificial intelligence (AI), with an emphasis on deep learning, holds great promise in this area and is already being successfully applied to basic research, diagnosis, drug discovery, and clinical trials.

Congenital disorders of glycosylation (CDG) are a rapidly growing family of genetic diseases that currently includes some 130 different types. CDG diagnosis is a challenge, not only because of this large number but also because of the huge clinical heterogeneity even within a number of CDG.

Glycosylation is an essential biological process that adds structural and functional diversity to cells and molecules, participating in physiological processes such as immunity. The immune response is driven and modulated by protein-attached gly- cans that mediate cell-cell interactions, pathogen recognition and cell activation. Therefore, abnormal glycosylation can be associated with deranged immune responses.

Phosphomannomutase 2 (PMM2-CDG) is the most common congenital disorder of N-glycosylation and is caused by a deficient PMM2 activity. The clinical presentation and the onset of PMM2-CDG vary among affected individuals ranging from a severe antenatal presentation with multisystem involvement to mild adulthood presentation limited to minor neurological involvement. Management of affected patients requires a multidisciplinary approach.

Congenital disorders of glycosylation (CDG) are ultra-rare diseases showing a great phenotypic diversity ranging from mono- to multi-organ/multisystem involvement. Liver involvement, mostly nonprogressive, is often reported in CDG patients.

Congenital disorders of glycosylation (CDG) are a rapidly growing family comprising >100 genetic diseases. Some 25 CDG are pure O-glycosylation defects. Even among this CDG subgroup, phenotypic diversity is broad, ranging from mild to severe poly-organ/system dysfunction. Ophthalmic manifestations are present in 60% of these CDG. The ophthalmic manifestations in N-glycosylation-deficient patients have been described elsewhere.

Background: Health-related Quality of Life (HrQoL) is a multidimensional measure, which has gained clinical and social relevance. Implementation of a patient centred approach to both clinical research and care settings, has increased the recognition of patient and/or observer reported outcome measures (PROMs or ObsROMs) as informative and reliable tools for HrQoL assessment.

Congenital disorders of glycosylation (CDG) are a group of genetic disorders that affect protein and lipid glycosylation and glycosylphosphatidylinositol synthesis. More than 100 different disorders have been reported and the number is rapidly increasing. Since glycosylation is an essential post-translational process, patients present a large range of symptoms and variable phenotypes, from very mild to extremely severe.

Background: Public and patient involvement in the design of people-centred care and research is vital for communities whose needs are underserved, as are people with rare diseases. Innovations devised collectively by patients, caregivers, professionals and other members of the public can foster transformative change toward more responsive services and research.

Congenital disorders of glycosylation (CDG) are inborn errors of metabolism due to protein and lipid hypoglycosylation. This rapidly growing family of genetic diseases comprises 103 CDG types, with a broad phenotypic diversity ranging from mild to severe poly-organ -system dysfunction. This literature review summarizes cardiac involvement, reported in 20% of CDG.