Evidence map›Paper›PMID 37995919›Full record

ArticleNeuroImage2023

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes.

Pritesh R Jain, Madison Yates, Carlos Rubin de Celis, Petros Drineas, Neda Jahanshad, Paul Thompson, Peristera Paschou

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Pritesh R JainDepartment of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States.
Madison YatesDepartment of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States.
Carlos Rubin de CelisDepartment of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States.
Petros DrineasDepartment of Computer Science, Purdue University, United States.
Neda JahanshadMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of South California, United States.
Paul ThompsonMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of South California, United States.
Peristera PaschouDepartment of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States. Electronic address: ppaschou@purdue.edu.
Purdue University West Lafayette · USCognitive Neuroimaging Lab · FR

Funding

Large-Scale Collaborative Genetic and Epigenetic Studies of Tourette SyndromeR01NS105746 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI MATHEWS, CAROL A, PASCHOU, PERISTERA · 2019 to 2023
$3.1M
High resolution mapping of the genetic risk for disease in the aging brainR01AG059874 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JAHANSHAD, NEDA · 2018 to 2022
$3.1M
Tourette Syndrome genetics and neuroimaging international collaborative studyR01MH126213 · NIMH · PURDUE UNIVERSITY · PI Peristera Paschou · 2022 to 2026
$2.5M
NIA NIH HHS R01 AG059874NIMH NIH HHS R01 MH126213NINDS NIH HHS R01 NS105746
6 · The paper itself

Abstract

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes, with nine proteins and five metabolites replicated using independent exposure data. We found causal associations between accumbens volume and plasma protease c1 inhibitor as well as strong association between putamen volume and Agouti signaling protein. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisBiomarkersBrainHumansMagnetic Resonance ImagingMultiomicsBiomarkersMendelian randomizationMetabolitesNeurological disordersProteomeSubcortical brain volume

Identifiers

PMID37995919
PMCPMC11647565
OpenAlexW4388914665

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.