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Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes.
Gannamani, Rahul; van der Veen, Sterre; van Egmond, Martje; de Koning, Tom J; Tijssen, Marina A J.
Afiliación
  • Gannamani R; Department of Neurology University of Groningen, University Medical Centre Groningen Groningen The Netherlands.
  • van der Veen S; Department of Genetics University of Groningen, University Medical Centre Groningen Groningen The Netherlands.
  • van Egmond M; Expertise Centre Movement Disorders Groningen University Medical Centre Groningen Groningen The Netherlands.
  • de Koning TJ; Department of Neurology University of Groningen, University Medical Centre Groningen Groningen The Netherlands.
  • Tijssen MAJ; Expertise Centre Movement Disorders Groningen University Medical Centre Groningen Groningen The Netherlands.
Mov Disord Clin Pract ; 8(3): 311-321, 2021 Apr.
Article en En | MEDLINE | ID: mdl-33816658
BACKGROUND: In the field of movement disorders, what you see (phenotype) is seldom what you get (genotype). Whereas 1 phenotype was previously associated to 1 gene, the advent of next-generation sequencing (NGS) has facilitated an exponential increase in disease-causing genes and genotype-phenotype correlations, and the "one-phenotype-many-genes" paradigm has become prominent. OBJECTIVES: To highlight the "one-phenotype-many-genes" paradigm by discussing the main challenges, perspectives on how to address them, and future directions. METHODS: We performed a scoping review of the various aspects involved in identifying the underlying molecular cause of a movement disorder phenotype. RESULTS: The notable challenges are (1) the lack of gold standards, overlap in clinical spectrum of different movement disorders, and variability in the interpretation of classification systems; (2) selecting which patients benefit from genetic tests and the choice of genetic testing; (3) problems in the variant interpretation guidelines; (4) the filtering of variants associated with disease; and (5) the lack of standardized, complete, and up-to-date gene lists. Perspectives to address these include (1) deep phenotyping and genotype-phenotype integration, (2) adherence to phenotype-specific diagnostic algorithms, (3) implementation of current and complementary bioinformatic tools, (4) a clinical-molecular diagnosis through close collaboration between clinicians and genetic laboratories, and (5) ongoing curation of gene lists and periodic reanalysis of genetic sequencing data. CONCLUSIONS: Despite the rapidly emerging possibilities of NGS, there are still many steps to take to improve the genetic diagnostic yield. Future directions, including post-NGS phenotyping and cohort analyses enriched by genotype-phenotype integration and gene networks, ought to be pursued to accelerate identification of disease-causing genes and further improve our understanding of disease biology.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Observational_studies Idioma: En Revista: Mov Disord Clin Pract Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Observational_studies Idioma: En Revista: Mov Disord Clin Pract Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos