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Understanding Alzheimer Disease at the Interface between Genetics and Transcriptomics.

Jan Verheijen1, Kristel Sleegers1

  • 1Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, B-2610, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, B-2610, Belgium.

Trends in Genetics : TIG
|March 26, 2018
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Summary

Understanding Alzheimer disease (AD) risk requires integrating genetics and transcriptomics. This approach reveals how genetic variants influence gene expression, aiding in the interpretation of AD pathogenesis.

Keywords:
Alzheimerbraingeneticstranscriptomics

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Area of Science:

  • Neurogenetics
  • Molecular Biology
  • Genomics

Background:

  • Alzheimer disease (AD) is a common neurodegenerative dementia with over 25 known risk genes.
  • Limited mechanistic insight into AD pathogenesis hinders effective disease management.
  • Determining functional consequences of genetic associations in AD is challenging.

Purpose of the Study:

  • To explore the role of transcriptomics in interpreting genetic associations for Alzheimer disease risk.
  • To highlight the necessity of integrating genetics and transcriptomics for a comprehensive understanding of AD.

Main Methods:

  • Utilizing advanced sequencing technologies (second and third generation, single-cell).
  • Applying bioinformatics to analyze transcriptomic data.
  • Corroborating genetic discoveries with gene expression profiles.

Main Results:

  • Transcriptomics reveals allele-specific events linking AD risk genes to expression profiles.
  • Converging evidence points to specific pathophysiological pathways in AD.
  • Brain region- and cell-type-specific expression patterns and alternative splicing complicate direct genotype-phenotype correlations.

Conclusions:

  • An integrated approach combining genetics and transcriptomics is crucial for understanding Alzheimer disease.
  • Transcriptomic data enhances the interpretation of genetic associations in AD.
  • Identifying cell-type and region-specific effects is key to unraveling AD complexity.