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Updated: Nov 10, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes
Rahul Gannamani1,2,3, Sterre van der Veen1,3, Martje van Egmond1,3
1Department of Neurology University of Groningen, University Medical Centre Groningen Groningen The Netherlands.
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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