4.5 Review

Advances in the genetic classification of amyotrophic lateral sclerosis

期刊

CURRENT OPINION IN NEUROLOGY
卷 34, 期 5, 页码 756-764

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/WCO.0000000000000986

关键词

amyotrophic lateral sclerosis; genetics; personalized medicine

资金

  1. Wellcome Trust [216596/Z/19/Z]
  2. European Research Council (ERC) under the European Union [772376 -EScORIAL]
  3. PPP Allowance by Health~Holland, Top Sector Life Sciences Health
  4. Wellcome Trust [216596/Z/19/Z] Funding Source: Wellcome Trust

向作者/读者索取更多资源

Amyotrophic lateral sclerosis (ALS) is a complex disease influenced by multiple genetic and environmental factors. Recent advancements in large-scale genome-wide association studies (GWAS) have provided new insights, but challenges such as structural variation and somatic heterogeneity require a multidisciplinary approach for successful disease subclassification and personalized medicine.
Purpose of review Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease wherein disease risk and severity are, for the majority of patients, the product of interaction between multiple genetic and environmental factors. We are in a period of unprecedented discovery with new large-scale genome-wide association study (GWAS) and accelerating discovery of risk genes. However, much of the observed heritability of ALS is undiscovered and we are not yet approaching elucidation of the total genetic architecture, which will be necessary for comprehensive disease subclassification. Recent findings We summarize recent developments and discuss the future. New machine learning models will help to address nonlinear genetic interactions. Statistical power for genetic discovery may be boosted by reducing the search-space using cell-specific epigenetic profiles and expanding our scope to include genetically correlated phenotypes. Structural variation, somatic heterogeneity and consideration of environmental modifiers represent significant challenges which will require integration of multiple technologies and a multidisciplinary approach, including clinicians, geneticists and pathologists. The move away from fully penetrant Mendelian risk genes necessitates new experimental designs and new standards for validation. The challenges are significant, but the potential reward for successful disease subclassification is large-scale and effective personalized medicine.

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