A New Tool to Identify Pediatric Patients with Atypical Diabetes Associated with Gene Polymorphisms.

Diabetes mellitus Diabetes mellitus, type 1 Diabetes mellitus, type 2 Genetic testing Pediatrics

Journal

Diabetes & metabolism journal
ISSN: 2233-6087
Titre abrégé: Diabetes Metab J
Pays: Korea (South)
ID NLM: 101556588

Informations de publication

Date de publication:
22 Mar 2024
Historique:
received: 26 05 2023
accepted: 25 11 2023
medline: 25 3 2024
pubmed: 25 3 2024
entrez: 25 3 2024
Statut: aheadofprint

Résumé

Recent diabetes subclassifications have improved the differentiation between patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus despite several overlapping features, yet without considering genetic forms of diabetes. We sought to facilitate the identification of monogenic diabetes by creating a new tool that we validated in a pediatric maturity-onset diabetes of the young (MODY) cohort. We first created the DIAgnose MOnogenic DIAbetes (DIAMODIA) criteria based on the pre-existing, but incomplete, MODY calculator. This new score is composed of four strong and five weak criteria, with patients having to display at least one weak and one strong criterion. The effectiveness of the DIAMODIA criteria was evaluated in two patient cohorts, the first consisting of patients with confirmed MODY diabetes (n=34) and the second of patients with T1DM (n=390). These DIAMODIA criteria successfully detected 100% of MODY patients. Multiple correspondence analysis performed on the MODY and T1DM cohorts enabled us to differentiate MODY patients from T1DM. The three most relevant variables to distinguish a MODY from T1DM profile were: lower insulin-dose adjusted A1c score ≤9, glycemic target-adjusted A1c score ≤4.5, and absence of three anti-islet cell autoantibodies. We validated the DIAMODIA criteria, as it effectively identified all monogenic diabetes patients (MODY cohort) and succeeded to differentiate T1DM from MODY patients. The creation of this new and effective tool is likely to facilitate the characterization and therapeutic management of patients with atypical diabetes, and promptly referring them for genetic testing which would markedly improve clinical care and counseling, as well.

Sections du résumé

Background UNASSIGNED
Recent diabetes subclassifications have improved the differentiation between patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus despite several overlapping features, yet without considering genetic forms of diabetes. We sought to facilitate the identification of monogenic diabetes by creating a new tool that we validated in a pediatric maturity-onset diabetes of the young (MODY) cohort.
Methods UNASSIGNED
We first created the DIAgnose MOnogenic DIAbetes (DIAMODIA) criteria based on the pre-existing, but incomplete, MODY calculator. This new score is composed of four strong and five weak criteria, with patients having to display at least one weak and one strong criterion.
Results UNASSIGNED
The effectiveness of the DIAMODIA criteria was evaluated in two patient cohorts, the first consisting of patients with confirmed MODY diabetes (n=34) and the second of patients with T1DM (n=390). These DIAMODIA criteria successfully detected 100% of MODY patients. Multiple correspondence analysis performed on the MODY and T1DM cohorts enabled us to differentiate MODY patients from T1DM. The three most relevant variables to distinguish a MODY from T1DM profile were: lower insulin-dose adjusted A1c score ≤9, glycemic target-adjusted A1c score ≤4.5, and absence of three anti-islet cell autoantibodies.
Conclusion UNASSIGNED
We validated the DIAMODIA criteria, as it effectively identified all monogenic diabetes patients (MODY cohort) and succeeded to differentiate T1DM from MODY patients. The creation of this new and effective tool is likely to facilitate the characterization and therapeutic management of patients with atypical diabetes, and promptly referring them for genetic testing which would markedly improve clinical care and counseling, as well.

Identifiants

pubmed: 38523249
pii: dmj.2023.0166
doi: 10.4093/dmj.2023.0166
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Sophie Welsch (S)

Pediatrics Unit, Institute for Experimental and Clinical Research, UCLouvain, Brussels, Belgium.

Antoine Harvengta (A)

Pediatrics Unit, Institute for Experimental and Clinical Research, UCLouvain, Brussels, Belgium.

Paola Gallo (P)

Pediatric Endocrinology Unit, Saint-Luc University Clinics, Brussels, Belgium.

Manon Martin (M)

Louvain Institute of Biomolecular Science and Technology (IBST) Unit, UCLouvain, Brussels, Belgium.

Dominique Beckers (D)

Pediatric Endocrinology and Diabetology Unit, CHU-UCL Namur sites Saint-Elisabeth and Mont-Godinne, Namur, Belgium.

Thierry Mouraux (T)

Pediatric Endocrinology and Diabetology Unit, CHU-UCL Namur sites Saint-Elisabeth and Mont-Godinne, Namur, Belgium.

Nicole Seret (N)

Pediatric Endocrinology and Diabetology Unit, Clinique CHC MontLégia (CHC MontLégia Clinic), Liège, Belgium.

Marie-Christine Lebrethon (MC)

Pediatric Endocrinology Unit, CHU of Liège site ND-des Bruyères, Liège, Belgium.

Raphael Helear (R)

Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium.

Pascal Brouillard (P)

Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium.

Miikka Vikkula (M)

Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium.

Philippe A Lysy (PA)

Pediatrics Unit, Institute for Experimental and Clinical Research, UCLouvain, Brussels, Belgium.
Pediatric Endocrinology Unit, Saint-Luc University Clinics, Brussels, Belgium.

Classifications MeSH