<i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables
<b>Background</b>: <i>MECP2</i> duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagn...
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/2075-4418/15/1/10 |
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| author | Lourdes Vega-Hanna Dídac Casas-Alba Sol Balsells Mercè Bolasell Patricia Rubio Ana García-García Oscar García-García Mar O’Callaghan Ainhoa Pascual-Alonso Judith Armstrong MDS Group Antonio F. Martinez-Monseny |
| author_facet | Lourdes Vega-Hanna Dídac Casas-Alba Sol Balsells Mercè Bolasell Patricia Rubio Ana García-García Oscar García-García Mar O’Callaghan Ainhoa Pascual-Alonso Judith Armstrong MDS Group Antonio F. Martinez-Monseny |
| author_sort | Lourdes Vega-Hanna |
| collection | DOAJ |
| description | <b>Background</b>: <i>MECP2</i> duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. <b>Methods</b>: A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024. Epidemiological, clinical, and molecular data were collected. A standardized clinical questionnaire was collaboratively developed with input from physicians and parents. Patient photographs were used to train Face2Gene. <b>Results</b>: Thirty-five patients (0–24 years, 30 males) were included. Key features in males comprised intellectual disability (100%), hypotonia (93%), autism spectrum disorder (77%) and developmental regression (52%). Recurrent respiratory infections (79%), dysphagia (73%), constipation (73%) and gastroesophageal reflux (57%) were common. Seizures occurred in 53%, with 33% being treatment-refractory. The Face2Gene algorithm was successfully trained to identify MDS. A specific clinical severity scale (MECPDup) was developed and validated, correlating with the MBA (a scale developed for Rett syndrome). The MECPDup score was significantly higher in males (<i>p</i> < 0.001) and those with early death (<i>p</i> = 0.003). It showed significant positive correlations with age (<i>p</i> < 0.001) and duplication size (<i>p</i> = 0.044). <b>Conclusions</b>: This study expands the understanding of MDS through comprehensive clinical and molecular insights. The integration of AI-based facial recognition technology and the development of the MECPDup severity scale hold promise for enhancing diagnostic accuracy, monitoring disease progression, and evaluating treatment responses in individuals affected by MDS. |
| format | Article |
| id | doaj-art-daa5b5324306434089c4813476e47a61 |
| institution | Kabale University |
| issn | 2075-4418 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-daa5b5324306434089c4813476e47a612025-01-10T13:16:26ZengMDPI AGDiagnostics2075-44182024-12-011511010.3390/diagnostics15010010<i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular VariablesLourdes Vega-Hanna0Dídac Casas-Alba1Sol Balsells2Mercè Bolasell3Patricia Rubio4Ana García-García5Oscar García-García6Mar O’Callaghan7Ainhoa Pascual-Alonso8Judith Armstrong9MDS GroupAntonio F. Martinez-Monseny10Genetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, SpainGenetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, SpainStatistics Department, Fundació de Recerca Sant Joan de Déu, 08950 Esplugues de Llobregat, SpainGenetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, SpainGenetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, SpainClinical Immunology Unit, Hospital Sant Joan de Déu-Hospital Clínic, 08950 Barcelona, SpainServei d’Atenció Ambulatòria, Fundació Aspace Catalunya, 08038 Barcelona, SpainPediatric Neurology Department, Hospital Sant Joan de Déu, 08950 Esplugues de Llobregat, SpainFundació de Recerca Sant Joan de Déu, 08950 Barcelona, SpainGenetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, SpainGenetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, Spain<b>Background</b>: <i>MECP2</i> duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. <b>Methods</b>: A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024. Epidemiological, clinical, and molecular data were collected. A standardized clinical questionnaire was collaboratively developed with input from physicians and parents. Patient photographs were used to train Face2Gene. <b>Results</b>: Thirty-five patients (0–24 years, 30 males) were included. Key features in males comprised intellectual disability (100%), hypotonia (93%), autism spectrum disorder (77%) and developmental regression (52%). Recurrent respiratory infections (79%), dysphagia (73%), constipation (73%) and gastroesophageal reflux (57%) were common. Seizures occurred in 53%, with 33% being treatment-refractory. The Face2Gene algorithm was successfully trained to identify MDS. A specific clinical severity scale (MECPDup) was developed and validated, correlating with the MBA (a scale developed for Rett syndrome). The MECPDup score was significantly higher in males (<i>p</i> < 0.001) and those with early death (<i>p</i> = 0.003). It showed significant positive correlations with age (<i>p</i> < 0.001) and duplication size (<i>p</i> = 0.044). <b>Conclusions</b>: This study expands the understanding of MDS through comprehensive clinical and molecular insights. The integration of AI-based facial recognition technology and the development of the MECPDup severity scale hold promise for enhancing diagnostic accuracy, monitoring disease progression, and evaluating treatment responses in individuals affected by MDS.https://www.mdpi.com/2075-4418/15/1/10<i>MECP2</i><i>MECP2</i> duplication syndromeclinical severity scalefacial recognitionartificial intelligence |
| spellingShingle | Lourdes Vega-Hanna Dídac Casas-Alba Sol Balsells Mercè Bolasell Patricia Rubio Ana García-García Oscar García-García Mar O’Callaghan Ainhoa Pascual-Alonso Judith Armstrong MDS Group Antonio F. Martinez-Monseny <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables Diagnostics <i>MECP2</i> <i>MECP2</i> duplication syndrome clinical severity scale facial recognition artificial intelligence |
| title | <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables |
| title_full | <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables |
| title_fullStr | <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables |
| title_full_unstemmed | <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables |
| title_short | <i>MECP2</i> Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables |
| title_sort | i mecp2 i duplication syndrome ai based diagnosis severity scale development and correlation with clinical and molecular variables |
| topic | <i>MECP2</i> <i>MECP2</i> duplication syndrome clinical severity scale facial recognition artificial intelligence |
| url | https://www.mdpi.com/2075-4418/15/1/10 |
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