From molecules to minds: Integrative multi-omics in psychiatry

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Psychiatric disorders stem from complex interactions across multiple biological layers.
• Single-omics studies capture only a fraction of the variance in these conditions, necessitating integrative frameworks.

Purpose of the Study:

• To review methodologies for multi-omics integration in psychiatric research.
• To highlight infrastructure needs and the importance of global inclusivity in psychiatric genomics.

Main Methods:

• Focus on systems-level integration of genomic risk scores, transcriptomic networks, and neuroimaging data.
• Discussion of infrastructural requirements: biobanking, Laboratory Information Management Systems (LIMS), FAIR data principles, and federated learning.
• Emphasis on addressing biases in current psychiatric genomics datasets.

Main Results:

• Integrative multi-omics approaches advance the biological understanding of depression, schizophrenia, and Alzheimer's disease.
• Standardized infrastructure and privacy-preserving methods like federated learning are crucial for effective multi-omics research.
• Locally led initiatives promote data sovereignty and equitable research practices, enhancing global inclusivity.

Conclusions:

• Coordinated investment in infrastructure, training, and international collaboration is essential for advancing multi-omics psychiatry.
• Future directions involve leveraging integrative approaches for a more complete biological understanding of psychiatric disorders.
• Addressing the lack of diversity in current datasets is critical for generalizability and equitable advancements in mental health research.