Evidence map›Paper›PMID 25110502›Full record

ArticlePsychiatry investigation2014

Effects of smoking cessation on gene expression in human leukocytes of chronic smoker.

Soo-Jeong Kim, Su Young Kim, Jae Hwa Kim, Dai-Jin Kim

Abstract read
In one paragraph

Article in Psychiatry investigation, 2014. 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
–field-weighted citation impact
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.

  1. Article
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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

4 authors.

Soo-Jeong KimDepartment of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
Su Young KimDepartment of Pathology, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
Jae Hwa KimDepartment of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
Dai-Jin KimDepartment of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe risks of cigarette smoking concerning higher systemic disease mortality are lessened by smoking cessation.

methodsMicroarray analysis compared the expression profiles of smokers who were successful and not successful at smoking cessation, with the goal of identifying genes that might serve as potential biomarkers or that might be valuable in elucidating distinct biological mechanisms. The mRNAs were isolated and compared from peripheral leukocytes of six smokers who were successful in cessation and six smokers who failed in smoking cessation.

resultsTwo hundred ninety nine genes displayed significantly different expression; 196 genes were up-regulated and 103 genes were down-regulated in the success group compared to the failure group. Twenty four of these genes were identified with biological processes including immunity, cytoskeleton and cell growth/cycle. Real-time PCR confirmed the differential gene expression. The mRNA levels of HEPACAM family member 2 (HEPACAM2) and tropomodulin 1 (TMOD1) were significantly more expressed in the success group, while the mRNA ubiquitin specific peptides 18 (USP18) were significantly less expressed in the success group compared to the failure group.

conclusionThe results suggest that smoking cessation can modulate cell adhesion and immune response by regulating expression levels of genes, especially HEPACAM2, TMOD1 and USP18, which have an important relationship with smoking cessation.

Indexed as

LeucocytesMicroarrayNicotine cessationReal time PCR

Identifiers

PMID25110502
PMCPMC4124188

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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.