Evidence map›Paper›PMID 25027082›Full record

ArticleThe Indian journal of medical research2014

Copy number polymorphism of glutathione-S-transferase genes (GSTM1 & GSTT1) in susceptibility to lung cancer in a high-risk population from north-east India.

Rakhshan Ihsan, Pradeep Singh Chauhan, Ashwani Kumar Mishra, L C Singh, Jagannath Dev Sharma, Eric Zomawia, Yogesh Verma, Sujala Kapur, Sunita Saxena

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In one paragraph

Article in The Indian journal of medical research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Rakhshan Ihsan
Pradeep Singh Chauhan
Ashwani Kumar Mishra
L C Singh
Jagannath Dev Sharma
Eric Zomawia
Yogesh Verma
Sujala Kapur
Sunita SaxenaNational Institute of Pathology (ICMR), New Delhi, India.
National Institute of Pathology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

objectivesGenetic polymorphisms in glutathione-S-transferase genes ( GSTM1 and GSTT1 ) have been studied intensively for their potential role in lung cancer susceptibility. However, most of the studies on association between the polymorphisms and lung cancer do not distinguish between genotypes with one or two copies of the genes. The present study investigates the gene dosage effects of GSTT1 and GSTM1 copy number and their environmental interactions to examine the association of lung cancer risk with trimodular genotypes of the GSTs in a high-risk population from north-east India.

methodsA total of 154 lung cancer cases and 154 age and sex matched controls from the high risk region of north-east India were analyzed by multiplex real-time PCR to determine the trimodal genotypes (+/+, +/- and -/-) in both the genes ( GSTM1 and GSTT1 ).

resultsNo significant association and gene dosage effect of GSTM1 gene copy number with lung cancer risk ( P trend =0.13) were found. However, absence of GSTT1 conferred 68 per cent (OR=0.32;95%CI=0.15-0.71;P=0.005) reduced risk compared to the two copy number of the gene. t0 here was evidence of gene dosage effect of GSTT1 gene ( P trend =0.006). Tobacco smoking was a major environmental risk factor to lung cancer (OR=3.03;95%CI=1.73-5.31;P<0.001). However, its interaction with null genotype of GSTT1 conferred significant reduced risk to lung cancer (OR=0.30;95%CI=0.10-0.91;P=0.03). Further in only tobacco smokers, null genotype was associated with increased reduced risk [0.03(0.001-0.78)0.03; P trend =0.006]. No effect modification of GSTM1 was observed with lung cancer risk by environmental risk factors. INTERPRETATION &

conclusionsThe results suggest that absence of GSTT1 null genotype may be associated with a reduced risk of lung cancer and the effect remains unchanged after interaction with smoking.

Indexed as

DNA Copy Number VariationsAdultAgedAged, 80 and overCase-Control StudiesFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGlutathioneGlutathione TransferaseHumansIndiaLung NeoplasmsMaleMiddle AgedRisk FactorsGlutathioneglutathione S-transferase T1Glutathione Transferase

Identifiers

PMID25027082
PMCPMC4140037
OpenAlexW2097134525

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LicenceCC BY-NC-SA
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Registered trials

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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.