Evidence map›Paper›PMID 37415601›Full record

ArticleFrontiers in genetics2023

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information.

Huseyin Gedik, Tan Hoang Nguyen, Roseann E Peterson, Christos Chatzinakos, Vladimir I Vladimirov, Brien P Riley, Silviu-Alin Bacanu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 5% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Huseyin GedikIntegrative Life Sciences, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States.
Tan Hoang NguyenDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States.
Roseann E PetersonInstitute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, United States.
Christos ChatzinakosStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States.
Vladimir I VladimirovDepartment of Psychiatry, College of Medicine, University of Arizona Phoenix, Phoenix, AZ, United States.
Brien P RileyDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States.
Silviu-Alin BacanuDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States.
Virginia Commonwealth University · USHarvard University · USSUNY Downstate Health Sciences University · USUniversity of Arizona · US

Funding

Project 5 - Genetic architecture of alcohol use disorder using cross-trait genetic correlations and public next-generation sequencing studiesP50AA022537 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI MICHAEL F MILES · 2014 to 2026
$19.6M
Cross-Population Working Group on Genes and Environment in Major Depression (POP-GEM): Advancing the Understating of Etiology through DiversityR01MH125938 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI Roseann Elizabeth Peterson · 2022 to 2026
$4.2M
Assessing miRNA expression in the Corticolimbic System of Major Depressive DisorderR01MH118239 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI VLADIMIROV, VLADIMIR IVANOV · 2019 to 2024
$2.8M
Using transmitted and untransmitted gene networks to identify molecular pathways to substance use & misuse in genetically controlled twinsR01DA052453 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI GILLESPIE, NATHAN ALEXANDER, VLADIMIROV, VLADIMIR IVANOV · 2021 to 2024
$2.2M
Translational Approach to Studying miRNA functions in sACC and amygdala in patients with BPDR01MH132806 · NIMH · UNIVERSITY OF ARIZONA · PI Vladimir Ivanov Vladimirov · 2023 to 2026
$2.2M
NIAAA NIH HHS P50 AA022537NIDA NIH HHS R01 DA052453NIMH NIH HHS R01 MH118239NIMH NIH HHS R01 MH125938NIMH NIH HHS R01 MH132806
6 · The paper itself

Abstract

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality)

Indexed as

alcohol use disorderbipolar disordereQTLMendelian randomizationmQTLpQTLschizophrenia

Identifiers

PMID37415601
PMCPMC10320396
OpenAlexW4379505716

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.