Evidence map›Paper›PMID 37098020›Full record

ArticlePloS one2023

Case-only exome variation analysis of severe alcohol dependence using a multivariate hierarchical gene clustering approach.

Amanda Elswick Gentry, Jeffry C Alexander, Mohammad Ahangari, Roseann E Peterson, Michael F Miles, Jill C Bettinger, Andrew G Davies, Mike Groteweil, Silviu A Bacanu, Kenneth S Kendler and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Human genetics and epigenetics of alcohol use disorder.The Journal of clinical investigation · 2024
    Review
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

13 authors at 3 institutions in 1 country.

Amanda Elswick GentryVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID 0000-0002-6425-9340
Jeffry C AlexanderVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Mohammad AhangariVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID 0000-0002-6585-5523
Roseann E PetersonVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID 0000-0001-6402-849X
Michael F MilesVCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Jill C BettingerVCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Andrew G DaviesVCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Mike GroteweilVCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Silviu A BacanuVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Kenneth S KendlerVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID 0000-0001-8689-6570
Brien P RileyVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.
Bradley T WebbVCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID 0000-0002-0576-5366
VCU Alcohol Research Center working group
Virginia Commonwealth University · USRTI International · USSUNY Downstate Health Sciences University · 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
Research Training: Psychiatric &Statistical GeneticsT32MH020030 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI HERMINE H MAES, MICHAEL CHURTON NEALE · 1999 to 2026
$6.7M
Whole Genome Sequencing in Irish Multiplex Schizophrenia FamiliesR01MH114593 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI RILEY, BRIEN P · 2017 to 2021
$2.1M
NIAAA NIH HHS P50 AA022537NIMH NIH HHS R01 MH114593NIMH NIH HHS T32 MH020030
6 · The paper itself

Abstract

backgroundVariation in genes involved in ethanol metabolism has been shown to influence risk for alcohol dependence (AD) including protective loss of function alleles in ethanol metabolizing genes. We therefore hypothesized that people with severe AD would exhibit different patterns of rare functional variation in genes with strong prior evidence for influencing ethanol metabolism and response when compared to genes not meeting these criteria.

objectiveLeverage a novel case only design and Whole Exome Sequencing (WES) of severe AD cases from the island of Ireland to quantify differences in functional variation between genes associated with ethanol metabolism and/or response and their matched control genes.

methodsFirst, three sets of ethanol related genes were identified including those a) involved in alcohol metabolism in humans b) showing altered expression in mouse brain after alcohol exposure, and altering ethanol behavioral responses in invertebrate models. These genes of interest (GOI) sets were matched to control gene sets using multivariate hierarchical clustering of gene-level summary features from gnomAD. Using WES data from 190 individuals with severe AD, GOI were compared to matched control genes using logistic regression to detect aggregate differences in abundance of loss of function, missense, and synonymous variants, respectively.

resultsThree non-independent sets of 10, 117, and 359 genes were queried against control gene sets of 139, 1522, and 3360 matched genes, respectively. Significant differences were not detected in the number of functional variants in the primary set of ethanol-metabolizing genes. In both the mouse expression and invertebrate sets, we observed an increased number of synonymous variants in GOI over matched control genes. Post-hoc simulations showed the estimated effects sizes observed are unlikely to be under-estimated.

conclusionThe proposed method demonstrates a computationally viable and statistically appropriate approach for genetic analysis of case-only data for hypothesized gene sets supported by empirical evidence.

Indexed as

AlcoholismAllelesAnimalsEthanolExomeGenetic VariationHumansMiceSilent MutationEthanol

Identifiers

PMID37098020
PMCPMC10128939
OpenAlexW4366981715

What OpenQuestion 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 OpenQuestion graph.