Evidence map›Paper›PMID 22832404›Full record

ArticleTranslational psychiatry2011

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms.

H Le-Niculescu, Y Balaraman, S D Patel, M Ayalew, J Gupta, R Kuczenski, A Shekhar, N Schork, M A Geyer, A B Niculescu

Open access · goldAbstract read
In one paragraph

Article in Translational psychiatry, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

48 citing papers in PubMed, 96 citations in OpenAlex.

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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

10 authors at 6 institutions in 1 country.

H Le-NiculescuDepartment of Psychiatry, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Y Balaraman
S D Patel
M Ayalew
J Gupta
R Kuczenski
A Shekhar
N Schork
M A Geyer
A B Niculescu
Indiana University – Purdue University Indianapolis · USIndiana University School of MedicineRichard L. Roudebush VA Medical Center · USUniversity of California, San Diego · USIndiana Clinical and Translational Sciences Institute · USScripps Research Institute · US

Funding

Developing Blood Tests for Mood DisordersDP2OD007363 · OD · INDIANA UNIVERSITY INDIANAPOLIS · PI NICULESCU, ALEXANDER B · 2010 to 2010
$2.3M
Mood State Blood Biomarkers: A Discovery-Based ApproachI01CX000139 · VA · RLR VA MEDICAL CENTER · PI NICULESCU, ALEXANDER B · 2009 to 2017
–
CSRD VA I01 CX000139NIH HHS 1DP2OD007363NIH HHS DP2 OD007363
6 · The paper itself

Abstract

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain.

Indexed as

GenesAnimalsAnxiety DisordersBiomarkersCyclic AMPDisease Models, AnimalGenomicsHumansMiceModels, AnimalSchizophreniaSignal TransductionTranslational Research, BiomedicalBiomarkersCyclic AMP

Identifiers

PMID22832404
PMCPMC3309477
OpenAlexW2082212379

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.