Skip to content

netneurolab/Farahani_Metabolic_Health

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 

Repository files navigation

Joint multi-omics profiling of brain and body health in aging

Authors: Asa Farahani, Zhen-Qi Liu, Filip Morys, Roqaie Moqadam, Yashar Zeighami, Mahsa Dadar, Alain Dagher, Bratislav Misic.

The paper is now available at bioRxiv.

Abstract

The human brain and peripheral systems undergo coordinated changes throughout the lifespan, yet studies of aging have traditionally examined these systems as separate entities. Here we ask how brain health relates to peripheral biomarkers of bodily health including body mass index, blood pressure, and blood biochemistry results. We use partial least squares analysis to identify generalizable patterns of covariance between multi-modal neuroimaging data (structural, functional, diffusion, and arterial spin labeling MRI), demographic, and peripheral physiological markers in two large-scale deeply phenotyped datasets: the Human Connectome Project-Aging and UK Biobank. This data-driven pattern learning approach identifies two principal axes of brain-body associations in both biological sex groups. The first prominent axis is driven by the dominant contribution of age. Across multiple brain measures, aging is associated with loss of brain structural integrity and cerebral vascular dysfunction. The second axis is driven by metabolic features, characterized by low high-density lipoprotein cholesterol, elevated body mass index, blood pressure, glycosylated hemoglobin, insulin, glucose, and alanine aminotransferase, and reduced cerebral blood perfusion. Finally, we show that deviations from a healthy metabolic profile are linked to cognitive deficits, particularly in females. Our study contributes to development of comprehensive translatable biomarkers for brain health assessment, and highlights the importance of metabolic health as a determinant of brain health.

Data Confidentiality Notice

Data in this study comes from Human Connectome Project Lifespan studies (HCP-Aging), and UK Biobank. For more details and to request access to the dataset, please visit the HCP Lifespan, and UK Biobank websites.

Repository Structure

Code

This folder contains all scripts used in the project.

Data

This folder includes some basic data such as the parcellations used in this project.

Utility Scripts

  • globals.py - Defines the paths to data directories and some constants used throughout the project.
  • functions.py - Contains functions utilized across various scripts in the project.

Contact Information

For questions, email: [email protected].

About

No description, website, or topics provided.

Resources

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages