Jade Howard, Amina Chaouch, Andrew G L Douglas, Rhona MacLeod, Jennifer Roggenbuck, Alisdair McNeill
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引用次数: 0
Abstract
Motor neuron disease (MND), also referred to as amyotrophic lateral sclerosis (ALS), is a monogenic disease in a minority of cases, with autosomal dominant inheritance. Increasing numbers of people with MND are requesting genetic testing, and indeed receiving a genetic diagnosis. Consequently, requests for genetic counselling and predictive testing (i.e. of unaffected family members) are similarly expected to rise, alongside pre-symptomatic clinical trials. Despite this, there is no evidence-based guideline for predictive genetic testing in MND. This paper provides an overview of the genomic basis of MND, focusing specifically on the most common monogenic causes of MND. It then lays out the complexities of MND predictive testing, including the genetic landscape characterised by incomplete penetrance, clinical and genetic heterogeneity, and an oligogenic mechanism of pathogenesis in some cases. Additionally, there is limited research on the psychosocial impact of predictive genetic testing for MND, with studies suggesting potential difficulty in adjusting to the news, in part due to a lack of support and follow-up. This underscores a case for evidence-based, disease-specific guidance for predictive testing in MND.
期刊介绍:
The European Journal of Human Genetics is the official journal of the European Society of Human Genetics, publishing high-quality, original research papers, short reports and reviews in the rapidly expanding field of human genetics and genomics. It covers molecular, clinical and cytogenetics, interfacing between advanced biomedical research and the clinician, and bridging the great diversity of facilities, resources and viewpoints in the genetics community.
Key areas include:
-Monogenic and multifactorial disorders
-Development and malformation
-Hereditary cancer
-Medical Genomics
-Gene mapping and functional studies
-Genotype-phenotype correlations
-Genetic variation and genome diversity
-Statistical and computational genetics
-Bioinformatics
-Advances in diagnostics
-Therapy and prevention
-Animal models
-Genetic services
-Community genetics