Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Area of Science:

• Genetics
• Neuroscience
• Systems Biology

Background:

• Neurodegenerative diseases exhibit complex genetic architectures, ranging from monogenic to polygenic models.
• Recent advancements in multi-omics and systems genetics offer deeper insights into disease mechanisms.
• Understanding genetic influences is crucial for diagnosis, prognosis, and therapeutic development.

Purpose of the Study:

• To provide a comprehensive overview of genetic architecture concepts in neurodegenerative diseases.
• To explore the role of multi-omics data in elucidating disease mechanisms.
• To introduce a novel framework for understanding disease progression.

Main Methods:

• Review of genetic architecture models (Mendelian, oligogenic, omnigenic).
• Analysis of multi-omics data (genomic, transcriptomic, proteomic, epigenetic, metabolomic).
• Examination of advanced techniques like single-cell omics, TWAS, and EWAS.

Main Results:

• Common and rare variants, gene-gene/environment interactions, and epigenetics significantly influence disease phenotypes.
• Multi-omics data are essential for understanding molecular mechanisms and addressing missing heritability.
• The OmicPeak Disease Trajectory Model integrates multi-omics data across biological layers and time.

Conclusions:

• A systems genetics approach is vital for unraveling the complex genetic architecture of neurodegenerative diseases.
• A holistic understanding of multi-omics data enhances diagnostic precision and therapeutic strategies.
• This framework provides a foundation for refining genetic architectures and improving patient outcomes.