Dataset Information

Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes.

ABSTRACT:

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.

SUBMITTER: Gannamani R

PROVIDER: S-EPMC8015914 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundProgress in genetics - particularly the advent of next-generation sequencing (NGS) - has enabled an unparalleled gene discovery and revealed unmatched complexity of genotype-phenotype correlations in movement disorders. Among other things, it has emerged that mutations in one and the same gene can cause multiple, often markedly different phenotypes. Consequently, movement disorder specialists have increasingly experienced challenges in clinicogenetic correlations.ObjectivesTo deconstruct biological phenomena and mechanistic bases of phenotypic heterogeneity in monogenic movement disorders and neurodegenerative diseases. To discuss the evolving role of movement disorder specialists in reshaping disease phenotypes in the NGS era.MethodsThis scoping review details phenomena contributing to phenotypic heterogeneity and their underlying mechanisms.ResultsThree phenomena contribute to phenotypic heterogeneity, namely incomplete penetrance, variable expressivity and pleiotropy. Their underlying mechanisms, which are often shared across phenomena and non-mutually exclusive, are not fully elucidated. They involve genetic factors (ie, different mutation types, dynamic mutations, somatic mosaicism, intragenic intra- and inter-allelic interactions, modifiers and epistatic genes, mitochondrial heteroplasmy), epigenetic factors (ie, genomic imprinting, X-chromosome inactivation, modulation of genetic and chromosomal defects), and environmental factors.ConclusionMovement disorders is unique in its reliance on clinical judgment to accurately define disease phenotypes. This has been reaffirmed by the NGS revolution, which provides ever-growing sequencing data and fuels challenges in variant pathogenicity assertions for such clinically heterogeneous disorders. Deep phenotyping, with characterization and continual updating of "core" phenotypes, and comprehension of determinants of genotype-phenotype complex relationships are crucial for clinicogenetic correlations and have implications for the diagnosis, treatment and counseling.

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