Genetically informed brain atlas (GIANT) for enhancing neuroimaging genetics studies

@@ IMPORTANT UPDATE @@
! We are currently working on addressing the comments received from the reviewers. 
! We will release the updated scripts and results shortly!

This repository includes the Genetically Informed brAiN Ttlas (GIANT) with its implementation, and all imaging-genetics subsequent analysis summary statistics for the GIANT.

ShenLab@Penn LongLab@Penn

GIANT - A genetically informed brain atlas

We introduce GIANT, a genetically informed brain atlas. Our 3D clustering algorithm was applied separately to gray matter and white matter, and the best-tuned brain parcellations were integrated to define GIANT. Our annotation results divided GIANT into 7 anatomical sub-structures: cerebellum (A), deep gray matter and white matter structure (B), frontal structure (C and D), occipital structure (F), parietal structure (G), temporal structure (H), and others (E).

The NIFTI file for GIANT and its specifications: https://github.com/JingxuanBao/GIANT/tree/main/GIANT

We developed a novel brain annotation method that can annotate the new generated brain atlas using the reference atlas: https://github.com/JingxuanBao/GIANT/tree/main/scripts/BrainRegionNaming.py.

3D heritability-aware brain parcellation model

We propose a 3D heritability-aware brain parcellation model that integrates voxel-wise heritability and spatial proximity to cluster brain voxels into genetically informed regions.

You may find the implementation and example: https://github.com/JingxuanBao/GIANT/blob/main/scripts/Her_Atlas.py

Voxel-level heritability estimates

The voxel-level heritability estiamtes for UK Biobank (UKBB): https://github.com/JingxuanBao/GIANT/tree/main/example_data/voxel_heritability_UKBB

The voxel-level heritability estimates for Alzheimer's disease neuroimaging initiative (ADNI): https://github.com/JingxuanBao/GIANT/tree/main/example_data/voxel_heritability_ADNI

Regional-level heritability estimates for GIANT

The regional-level heritability estimates for UKBB and ADNI using GIANT brian parcellation: https://github.com/JingxuanBao/GIANT/tree/main/GIANT/GIANT_regional_heritability

Genome-wide association study summary statistics

We conducted a regional-level GWAS on both GIANT and the conventional brain atlas using the UKBB imaging-genetics cohort and the ADNI imaging-genetics cohort.

We performed the linear regression on 59 heritability-aware brain atlas defined ROIs and 140 MUSE atlas defined ROIs. Each ROI defines a brain regional level quantitative trait measuring the brain variations. Specifically, we fit a linear regression model for each ROI-SNP pair by treating imaging volumetric quantitative trait as the response variable and common-variant autosomal individual SNP as the independent variable. Our model was adjusted for age, sex, first 10 principal components, and AD-by-proxy/AD as covariates. The genome-wide significant threshold was set as $5\times 10^{-8}$. All GWAS analyses were performed using PLINK v1.9. For each ROI volumetric imaging QT, we performed the post-GWAS analysis using FUMA. FUMA is a web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results. We use the FUMA analysis protocol from Wen et al. We constructed LD blocks by tagging all variants with minor allele frequency greater than or equal to 0.0005 and with at least one of the independent significant variants. Of note, the LD blocks are constructed from the 1000 Genomes as reference panels, which may not be overlapped with the variants in the current study. Finally, FUMA merges the LD blocks of independent significant variants into a single genomic locus if they are within 250 kilobases from the closest boundary variants of LD blocks. We used the default parameters settings on FUMA online platform for the other unmentioned parameters.

Genome builder: GRCh37

Link to GWAS summary statistics with FUMA post GWAS analyses (GIANT and Conventional brain atlas): https://upenn.box.com/v/GeneticallyInformedBrainAtlas

Polygenetic risk scores

We estimate the PRSs for regional-level brain variations defined by both GIANT and the conventional brain atlas on both the UKBB and the ADNI imaging-genetics cohorts. For the PRS analysis of the UKBB imaging-genetics cohort, we use the base GWAS summary statistics calculated from the ADNI study. Similarly, we use the base GWAS summary statistics calculated from the UKBB study to estimate the PRSs for regional-level brain variations in the ADNI cohort. All the analyses are performed using PRSice-2.

Link to polygenetic risk score (GIANT and Conventional brain atlas): https://upenn.box.com/v/GeneticallyInformedBrainAtlas

Acknowledgement

This work was supported in part by the National Institutes of Health grants R01 AG071470, U01 AG068057, U01 AG066833, RF1 AG063481, RF1 AG068191, and R01 AG071174.

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

Maintainers

jingxuan.bao@pennmedicine.upenn.edu