Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization
Lin, Siying ; Zhang, Haoyang LU
; Qi, Mengling
; Cooper, David N
; Yang, Yuedong
; Yang, Yuanhao
and Zhao, Huiying
(2023)
In NeuroImage
279.
- Abstract
Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple... (More)
Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.
(Less)
- author
- Lin, Siying
; Zhang, Haoyang
LU
; Qi, Mengling
; Cooper, David N
; Yang, Yuedong
; Yang, Yuanhao
and Zhao, Huiying
- publishing date
- 2023-10-01
- type
- Contribution to journal
- publication status
- published
- keywords
- Humans, Depressive Disorder, Major/diagnostic imaging, Cardiovascular Diseases/diagnostic imaging, Genome-Wide Association Study/methods, Autism Spectrum Disorder/diagnostic imaging, Amyotrophic Lateral Sclerosis, Mendelian Randomization Analysis/methods, Phenotype, Brain Diseases/diagnostic imaging, Hypertension, Neuroimaging
- in
- NeuroImage
- volume
- 279
- article number
- 120325
- publisher
- Elsevier
- external identifiers
-
- pmid:37579999
- scopus:85168001202
- ISSN
- 1095-9572
- DOI
- 10.1016/j.neuroimage.2023.120325
- language
- English
- LU publication?
- no
- additional info
- Copyright © 2023. Published by Elsevier Inc.
- id
- 5e322ce4-bde5-4609-9081-d6cdb4a95be1
- date added to LUP
- 2024-02-05 14:51:35
- date last changed
- 2024-06-17 15:46:32
@article{5e322ce4-bde5-4609-9081-d6cdb4a95be1,
abstract = {{<p>Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.</p>}},
author = {{Lin, Siying and Zhang, Haoyang and Qi, Mengling and Cooper, David N and Yang, Yuedong and Yang, Yuanhao and Zhao, Huiying}},
issn = {{1095-9572}},
keywords = {{Humans; Depressive Disorder, Major/diagnostic imaging; Cardiovascular Diseases/diagnostic imaging; Genome-Wide Association Study/methods; Autism Spectrum Disorder/diagnostic imaging; Amyotrophic Lateral Sclerosis; Mendelian Randomization Analysis/methods; Phenotype; Brain Diseases/diagnostic imaging; Hypertension; Neuroimaging}},
language = {{eng}},
month = {{10}},
publisher = {{Elsevier}},
series = {{NeuroImage}},
title = {{Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization}},
url = {{http://dx.doi.org/10.1016/j.neuroimage.2023.120325}},
doi = {{10.1016/j.neuroimage.2023.120325}},
volume = {{279}},
year = {{2023}},
}