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Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes

Background: Individuals with a phenotype of early-onset severe obesity associated with intellectual disability can have molecular diagnoses ranging from monogenic to complex genetic traits. Severe overweight is the major sign of a syndromic physical appearance and predicting the influence of a singl...

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Autores principales: Rodríguez-López, Raquel, Gimeno-Ferrer, Fátima, do Santos, David Albuquerque, Ferrer-Bolufer, Irene, Luján, Carola Guzmán, Alcalá, Otilia Zomeño, García-Banacloy, Amor, Cogollos, Virginia Ballesteros, Juan, Carlos Sánchez
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878830/
https://www.ncbi.nlm.nih.gov/pubmed/36777005
http://dx.doi.org/10.2174/1389202923666220426093436
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author Rodríguez-López, Raquel
Gimeno-Ferrer, Fátima
do Santos, David Albuquerque
Ferrer-Bolufer, Irene
Luján, Carola Guzmán
Alcalá, Otilia Zomeño
García-Banacloy, Amor
Cogollos, Virginia Ballesteros
Juan, Carlos Sánchez
author_facet Rodríguez-López, Raquel
Gimeno-Ferrer, Fátima
do Santos, David Albuquerque
Ferrer-Bolufer, Irene
Luján, Carola Guzmán
Alcalá, Otilia Zomeño
García-Banacloy, Amor
Cogollos, Virginia Ballesteros
Juan, Carlos Sánchez
author_sort Rodríguez-López, Raquel
collection PubMed
description Background: Individuals with a phenotype of early-onset severe obesity associated with intellectual disability can have molecular diagnoses ranging from monogenic to complex genetic traits. Severe overweight is the major sign of a syndromic physical appearance and predicting the influence of a single gene and/or polygenic risk profile is extremely complicated among the majority of the cases. At present, considering rare monogenic bases as the principal etiology for the majority of obesity cases associated with intellectual disability is scientifically poor. The diversity of the molecular bases responsible for the two entities makes the appliance of the current routinely powerful genomics diagnostic tools essential. Objective: Clinical investigation of these difficult-to-diagnose patients requires pediatricians and neurologists to use optimized descriptions of signs and symptoms to improve genotype correlations. Methods: The use of modern integrated bioinformatics strategies which are conducted by experienced multidisciplinary clinical teams. Evaluation of the phenotype of the patient’s family is also of importance. Results: The next step involves discarding the monogenic canonical obesity syndromes and considering infrequent unique molecular cases, and/or then polygenic bases. Adequate management of the application of the new technique and its diagnostic phases is essential for achieving good cost/efficiency balances. Conclusion: With the current clinical management, it is necessary to consider the potential coincidence of risk mutations for obesity in patients with genetic alterations that induce intellectual disability. In this review, we describe an updated algorithm for the molecular characterization and diagnosis of patients with a syndromic obesity phenotype.
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spelling pubmed-98788302023-02-09 Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes Rodríguez-López, Raquel Gimeno-Ferrer, Fátima do Santos, David Albuquerque Ferrer-Bolufer, Irene Luján, Carola Guzmán Alcalá, Otilia Zomeño García-Banacloy, Amor Cogollos, Virginia Ballesteros Juan, Carlos Sánchez Curr Genomics Genetics & Genomics Background: Individuals with a phenotype of early-onset severe obesity associated with intellectual disability can have molecular diagnoses ranging from monogenic to complex genetic traits. Severe overweight is the major sign of a syndromic physical appearance and predicting the influence of a single gene and/or polygenic risk profile is extremely complicated among the majority of the cases. At present, considering rare monogenic bases as the principal etiology for the majority of obesity cases associated with intellectual disability is scientifically poor. The diversity of the molecular bases responsible for the two entities makes the appliance of the current routinely powerful genomics diagnostic tools essential. Objective: Clinical investigation of these difficult-to-diagnose patients requires pediatricians and neurologists to use optimized descriptions of signs and symptoms to improve genotype correlations. Methods: The use of modern integrated bioinformatics strategies which are conducted by experienced multidisciplinary clinical teams. Evaluation of the phenotype of the patient’s family is also of importance. Results: The next step involves discarding the monogenic canonical obesity syndromes and considering infrequent unique molecular cases, and/or then polygenic bases. Adequate management of the application of the new technique and its diagnostic phases is essential for achieving good cost/efficiency balances. Conclusion: With the current clinical management, it is necessary to consider the potential coincidence of risk mutations for obesity in patients with genetic alterations that induce intellectual disability. In this review, we describe an updated algorithm for the molecular characterization and diagnosis of patients with a syndromic obesity phenotype. Bentham Science Publishers 2022-07-05 2022-07-05 /pmc/articles/PMC9878830/ /pubmed/36777005 http://dx.doi.org/10.2174/1389202923666220426093436 Text en © 2022 Bentham Science Publishers https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Genetics & Genomics
Rodríguez-López, Raquel
Gimeno-Ferrer, Fátima
do Santos, David Albuquerque
Ferrer-Bolufer, Irene
Luján, Carola Guzmán
Alcalá, Otilia Zomeño
García-Banacloy, Amor
Cogollos, Virginia Ballesteros
Juan, Carlos Sánchez
Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title_full Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title_fullStr Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title_full_unstemmed Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title_short Reviewed and updated Algorithm for Genetic Characterization of Syndromic Obesity Phenotypes
title_sort reviewed and updated algorithm for genetic characterization of syndromic obesity phenotypes
topic Genetics & Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878830/
https://www.ncbi.nlm.nih.gov/pubmed/36777005
http://dx.doi.org/10.2174/1389202923666220426093436
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