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Multiple system atrophy: the application of genetics in understanding etiology

Abstract

Classically defined phenotypically by a triad of cerebellar ataxia, parkinsonism, and autonomic dysfunction in conjunction with pyramidal signs, multiple system atrophy (MSA) is a rare and progressive neurodegenerative disease affecting an estimated 3–4 per every 100,000 individuals among adults 50–99 years of age. With a pathological hallmark of alpha-synuclein-immunoreactive glial cytoplasmic inclusions (GCIs; Papp–Lantos inclusions), MSA patients exhibit marked neurodegenerative changes in the striatonigral and/or olivopontocerebellar structures of the brain. As a member of the alpha-synucleinopathy family, which is defined by its well-demarcated alpha-synuclein-immunoreactive inclusions and aggregation, MSA’s clinical presentation exhibits several overlapping features with other members including Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Given the extensive fund of knowledge regarding the genetic etiology of PD revealed within the past several years, a genetic investigation of MSA is warranted. While a current genome-wide association study is underway for MSA to further clarify the role of associated genetic loci and single-nucleotide polymorphisms, several cases have presented solid preliminary evidence of a genetic etiology. Naturally, genes and variants manifesting known associations with PD (and other phenotypically similar neurodegenerative disorders), including SNCA and MAPT, have been comprehensively investigated in MSA patient cohorts. More recently variants in COQ2 have been linked to MSA in the Japanese population although this finding awaits replication. Nonetheless, significant positive associations with subsequent independent replication studies have been scarce. With very limited information regarding genetic mutations or alterations in gene dosage as a cause of MSA, the search for novel risk genes, which may be in the form of common variants or rare variants, is the logical nexus for MSA research. We believe that the application of next generation genetic methods to MSA will provide valuable insight into the underlying causes of this disease, and will be central to the identification of etiologic-based therapies.

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Acknowledgments

The authors work is supported in part by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Department of Health and Human Services; project ZO1 AG000958.

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Appendix

Appendix

Panel 1: Key technological and analytical tools used in human genetics

GENOME-WIDE ASSOCIATION (GWA)
Definition: A GWA study uses extremely dense genome-wide genotyping to identify associations between genetic loci and the presence or absence of a trait. The goal is to identify genomic regions that contain risk alleles and this is done in a largely unbiased manner (i.e., without consideration of gene function or position). This is typically accomplished using millions of common genetic variants genotyped in large series of cases and controls.
Application: Used primarily in the identification of risk loci for diseases and traits, it is largely limited to the identification of common risk alleles and explicitly tests the common disease common variant hypothesis.
Limitations: In general GWA requires many thousands of cases and controls to reliably detect effects. Independent replication of identified loci is required. Does not reliably detect rare risk alleles. Identifies genetic regions that contain risk alleles, but does not identify either the causal risk allele or the affected gene.
Cost and Use: Current cost ~ $200 per sample. Since initial use in 2005 GWA has been widely adopted and is still used extensively today.
LINKAGE AND POSITIONAL CLONING
Definition: Linkage and positional cloning served as the critical methods in the identification of mutations that caused single-gene (monogenic) disorders. Traditionally linkage analysis was performed in families with an obviously inherited disease. Polymorphic (variable) markers were run throughout the genomes of member of the family to identify regions of the genome that segregated with disease. The inference from this result was that a disease-segregating region was likely to contain the disease-causing mutation. Linkage was performed using 200-800 polymorphic markers spaced throughout the genome, although more recently this has been replaced by the use of SNP panels of hundreds of thousands of variants. Following the identification of positive linkage gene candidates within that region were sequenced to identify the causal mutation (this portion of the experiment was termed positional cloning).
Application: Used in the identification of disease-causing mutations in highly informative (but usually rare) families
Limitations: These methods were quite slow, with successful linkage and positional cloning projects often taking years. In general, families that were informative enough for this method are extremely rare, and in particular for a late-onset disease, challenging to collect (because multiple generations are required).
Cost and Use: Relatively inexpensive, however, these methods have been largely supplanted by the use of exome sequencing, which combines elements of linkage and sequencing
SECOND GENERATION SEQUENCING
Definition: Second-generation sequencing (SGS) represents a major advance in molecular genetics. This method allows the generation of extremely large amounts of DNA sequence data, including the routine sequencing of human genomes. Most commonly thus far in human genetics, this method has been used in the context of exome sequencing. This involves sequencing of the protein-coding regions of the human genome.
Application: The principal application has been in the identification of disease-causing mutations; exome sequencing allows an investigator to identify rare disease-segregating mutations rapidly and quite efficiently. More recently there has been interest in applying this method to large groups rather than families in an attempt to identify risk alleles.
Limitations: The current methods are not able to easily detect certain types of variability (such as repeat expansions), and sequencing of certain parts of the genome (such as copy number variants) is unreliable.
Cost and Use: Within a research setting exome sequencing costs approximately $500 per sample and whole genome sequencing $1,500 per sample; however, the price continues to decrease. Exome sequencing is widely used in genetics laboratories, but will likely be replaced by whole genome sequencing in short order.
Use of exome/genome sequencing in a clinical setting: This is becoming a more cost-effective approach toward complex neurological diseases. However, there are mixed opinions on reporting of mutations in genes that were not intended to be the target. For example, finding a BRCA mutation in a patient being investigated because of a neurological disease. Guidelines have been developed [149, 150] to aid clinicians and laboratories, but this is a complicated matter and there is a large debate on clinical proceedings, ethical issues and consent.

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Federoff, M., Schottlaender, L.V., Houlden, H. et al. Multiple system atrophy: the application of genetics in understanding etiology. Clin Auton Res 25, 19–36 (2015). https://doi.org/10.1007/s10286-014-0267-5

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Keywords

  • Genome-wide association
  • Linkage analysis
  • Genetic risk
  • Mutation