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Review

Association of N-acetyltransferases 1 and 2 Polymorphisms with Susceptibility to Head and Neck Cancers—A Meta-Analysis, Meta-Regression, and Trial Sequential Analysis

1
Department of Oral and Maxillofacial Surgery, Fellowship in Maxillofacial Trauma, Health Services, Kurdistan University of Medical Sciences, Sanandaj 6617713446, Iran
2
Department of Oral and Maxillofacial Surgery, Fellowship in Maxillofacial Trauma, School of Dentistry, Tehran University of Medical Sciences, Tehran 1439955991, Iran
3
Department of Biology, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
4
Department of Head and Neck Surgical Oncology and Reconstructive Surgery, The Cancer Institute, School of Medicine, Tehran University of Medical Sciences, Tehran 1439955991, Iran
5
Cancer and Immunology Research Center, Department of Internal Medicine, School of Medicine, Kurdistan University of Medical Sciences, Sanandaj 6617913446, Iran
6
School of Medicine and Dentistry, Griffith University, Brisbane, QLD 4222, Australia
7
Department of Oral and Maxillofacial Surgery, Dental School, Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran 1983963113, Iran
8
English Department, Baneh Branch, Islamic Azad University, Baneh 6691133845, Iran
9
Tehran Medical Branch, Islamic Azad University, Tehran 1419733171, Iran
10
Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah 6719851115, Iran
11
Center for Affective, Stress and Sleep Disorders, University of Basel, Psychiatric Clinics, 4001 Basel, Switzerland
12
Substance Abuse Prevention Research Center, Kermanshah University of Medical Sciences, Kermanshah 6715847141, Iran
13
Department of Psychology, Stanford University, Stanford, CA 94305, USA
14
Division of Sport Science and Psychosocial Health, Department of Sport, Exercise and Health, University of Basel, 4052 Basel, Switzerland
15
School of Medicine, Tehran University of Medical Sciences, Tehran 1416753955, Iran
*
Author to whom correspondence should be addressed.
Medicina 2021, 57(10), 1095; https://doi.org/10.3390/medicina57101095
Submission received: 23 August 2021 / Revised: 1 October 2021 / Accepted: 9 October 2021 / Published: 13 October 2021

Abstract

:
Background and objective:N-acetyltransferases 1 and 2 (NAT1 and NAT2) genes have polymorphisms in accordance with slow and rapid acetylator phenotypes with a role in the development of head and neck cancers (HNCs). Herein, we aimed to evaluate the association of NAT1 and NAT2 polymorphisms with susceptibility to HNCs in an updated meta-analysis. Materials and methods: A search was comprehensively performed in four databases (Web of Science, Scopus, PubMed/Medline, and Cochrane Library until 8 July 2021). The effect sizes, odds ratio (OR) along with 95% confidence interval (CI) were computed. Trial sequential analysis (TSA), publication bias and sensitivity analysis were conducted. Results: Twenty-eight articles including eight studies reporting NAT1 polymorphism and twenty-five studies reporting NAT2 polymorphism were involved in the meta-analysis. The results showed that individuals with slow acetylators of NAT2 polymorphism are at higher risk for HNC OR: 1.22 (95% CI: 1.02, 1.46; p = 0.03). On subgroup analysis, ethnicity, control source, and genotyping methods were found to be significant factors in the association of NAT2 polymorphism with the HNC risk. TSA identified that the amount of information was not large enough and that more studies are needed to establish associations. Conclusions: Slow acetylators in NAT2 polymorphism were related to a high risk of HNC. However, there was no relationship between NAT1 polymorphism and the risk of HNC.

1. Introduction

Cellular inflammation and immunity can play a significant role in various stages of carcinogenesis [1] such as head and neck cancers (HNCs). HNC mortality rates are elevating and disproportionately affect people in low- and middle-income countries and areas with restricted resources [2]. Global Burden of Disease Study (GBD) in 2016 estimated 512,492 deaths due to HNC (a minimum of 15,018 deaths in North Africa and the Middle East to a maximum of 199,280 in South Asia) and predicted the death count to reach 705,901 in 2030 [3,4]. HNC involves a series of tumors originating in the oropharynx, hypopharynx, oral cavity, lip, larynx, or nasopharynx [5]. Smoking, alcohol consumption, and high-risk human papillomaviruses have been related to HNC [5,6,7]. In connection with the role of genetics in HNC, several recent meta-analyses have reported the association of polymorphisms with the risk of HNCs [8,9,10,11].
A number of heterocyclic and aromatic amines are the main carcinogenic compounds of tobacco smoke [12,13] that their metabolism in humans is complex and includes acetylation as a main pathway for DNA mutation and the onset of carcinogenesis [14]. In particular, two N-acetyltransferases, NAT1 and NAT2 perform a role in catalyzing the deactivation and activation of several carcinogenic amines through N- and O-acetylation, respectively [14,15]. Both NAT genes (NAT1 and NAT2) have polymorphisms in humans and in accordance with slow and rapid acetylator phenotypes [16]. The NAT2 metabolized gene is located in region 10 of chromosome 8p21, which contains two exons with a long intron of about 8.6 kb [17]. Exon 1 is very short (100 bp) and the entire protein-coding region in Exon 2 is 870 bp [18]. Also, the NAT1 gene is located on the short arm of chromosome 8 (8p21) [19,20]. NAT1 accelerates acetylation specifically for arylamine receptor structures such as p-aminosalicylic and p-aminobenzoic acids [21] and NAT2 acetylates other arylamine-acceptor structures, such as isoniazid, sulfasalazine, procainamide, and caffeine [19].
Evidence from the published articles on the relationship between NAT1 and NAT2 polymorphisms and HNC susceptibility is conflicting [22,23]. The association between the polymorphisms (NAT1 and NAT2) and the HNC risk has been evaluated by one [24] and four [25,26,27,28] meta-analyses, respectively. However, these studies were published several years ago with the most recent one being published in 2015. Therefore, through this meta-analysis, we intend to update the evidence on the association between the polymorphisms and the HNC risk by including more studies. In addition, we aim to conduct trial sequential analysis (TSA) and meta-regression.

2. Materials and Methods

2.1. Study Design

The present meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols [29]. The PI/ECO (population, intervention/exposure, comparison, and outcome) question was: Are polymorphisms of NAT1 and NAT2 associated with the risk of HNC?

2.2. Identification of Articles

A search was comprehensively performed by one author (M.S.) in four databases of Web of Science, Scopus, PubMed/Medline, and Cochrane Library until 8 July 2021, without any restrictions in language, publication year, age, and sex to retrieve the relevant articles (Figure 1). The titles and abstracts of the relevant articles were assessed by the same author (M.S.); subsequently, the full-texts of the articles found to be relevant based on the eligibility criteria were downloaded. The search strategy included: (“N-acetyl transferases” or “N-acetyltransferase” or “NAT2” or “NAT1”) and (“mouth” or “OSCC” or “oral” or “tongue” or “head and neck” or “HNSCC“ or “nasopharyngeal” or “nasopharynx” or “oropharyngeal” or “salivary gland” or “laryngeal” or “larynx” or “hypopharyngeal” or “pharyngeal” or “pharynx” or “oral cavity” or “hypopharynx”) and (“tumor” or “carcinoma” or “cancer” or “neoplasm”) and (“allele” or “variant” or “polymorphism” or “genotype” or “gene”). The reference lists of the retrieved articles were reviewed to ensure that no important study was missed. Another author (H.M.) re-checked the process of searching and article selection. A lack of agreement between both authors was resolved by another author (J.T.).

2.3. Eligibility Criteria

The inclusion criteria were: (1) case-control studies reporting slow and rapid acetylators of NAT1 and NAT2 polymorphisms in HNC patients and controls, (2) HNC patients were diagnosed clinically and pathologically, and (3) HNC patients had no other systemic diseases and controls were healthy or free of tumors. On the contrary, meta-analyses, review studies, articles with incomplete data, studies without a control group, animal studies, conference papers, book chapters, and comment papers were excluded.

2.4. Data Summary

The data of the articles involved in the meta-analysis were separately retrieved by two authors (M.S. and S.B.). Extracted data included names of the authors, publication year, study country, ethnicity, number of cases, tumor type, source of controls, genotyping method, quality score, age, and gender distribution.

2.5. Quality Evaluation

The quality scoring was completed by one author (M.S.) based on the Newcastle-Ottawa Scale (NOS) scale [30] that a study is judged on three broad perspectives: the selection (4 scores); the comparability (2 scores); and the outcome (3 scores) for non-randomized studies, respectively. The maximum possible score was nine and high-quality studies were those with a score of ≥7.

2.6. Statistical Analysis

The effect sizes, odds ratios (OR) along with 95% confidence interval (CI), were calculated using the Review Manager 5.3 (RevMan 5.3; the Cochrane Collaboration, the Nordic Cochrane Centre, Copenhagen, Denmark) as well as subgroup analyses, quantifying the association between NAT1 and NAT2 polymorphisms and the HNC risk. A p-value (2-sided) < 0.05 was considered as a significant value. A random-effects model [31] was performed when I2 statistic represented a significant heterogeneity (Pheterogeneity < 0.1 or I2 > 50%) and if the heterogeneity was insignificant, a fixed-effect model [32] was applied.
Subgroup analyses were performed based on the ethnicity of study participants, control source in the study, tumor type, sample size, and genotyping method used in a study. To adjust for the effect of sample sizes, gender, and age distribution of the subjects included in the studies, a meta-regression analysis was conducted.
Publication bias was assessed applying funnel plots, Egger’s and/or Begg’s tests with a p-value (2-sided) < 0.05 demonstrating the existence of publication bias. Sensitivity analyses (“one-study-removed” and “cumulative” analyses) were conducted to evaluate the stability of pooled ORs. The meta-regression, publication bias, and sensitivity analysis were analyzed using the Comprehensive Meta-Analysis version 2.0 (CMA 2.0) software (CMA 2.0; Biostat Inc., Englewood, NJ, USA).
To illustrate false-positive or negative conclusions from meta-analyses [33], trial Sequential Analysis (TSA) software (version 0.9.5.10 beta) (Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen, Denmark) was used to evaluate TSA for analyses [34]. A futility threshold can be checked by the TSA to determine the effectiveness or ineffectiveness before information size is reached. The required information size (RIS) and a two-sided boundary type were computed with an alpha risk of 5% and beta risk of 20%. There were enough studies where the Z-curve reached the RIS line or the boundary line or entered the futility area. Otherwise, the amount of information was not enough and more evidence was needed.

2.7. Primer Sequences

The primer sequences of NAT1 and NAT2 are shown in the studies of Katoh et al. [35] and Chen et al. [36], respectively.

3. Results

3.1. Study Selection

From the four electronic databases and manual searching, 265 records were identified. After excluding the duplicates and irrelevant records, 48 full-text articles met the eligibility criteria (Figure 1). Then, 20 full-texts were removed (five were meta-analyses, one was an umbrella review, three were reviews, one was a book, one was an animal study, five articles had no control groups, one article had insufficient data, and three articles did not report genotypes of slow and rapid). Finally, 28 articles were used in the meta-analysis.

3.2. Characteristics of Studies

Twenty-eight studies included in the analysis were published between 1998 and 2014 (Table 1). Fourteen articles [22,23,36,37,38,39,40,41,42,43,44,45,46,47] reported the results in Caucasians, nine [35,48,49,50,51,52,53,54,55] in Asians, and five [56,57,58,59,60] among participants of mixed ethnicity. The control source in eighteen articles [22,23,35,37,39,40,43,44,45,46,48,49,51,52,53,57,58,60] was hospitals and ten [36,38,41,42,47,50,54,55,56,59] recruited the controls from a general population. In total, the articles included 5154 HNC cases and 6194 controls. Age, gender distribution, sample size, tumor type, genotyping method, and the quality score are shown in Table 1.
Table 2 shows the prevalence of slow and rapid acetylators of NAT1 and NAT2 polymorphisms. Eight studies [23,35,38,39,44,47,52,60] included NAT1 polymorphism with 1509 HNC cases and 1829 controls and twenty-five studies [22,23,35,36,37,38,40,41,42,43,44,45,46,47,48,49,50,51,53,54,55,56,57,58,59] included NAT2 polymorphism with 4393 HNC cases and 5321 controls.

3.3. Pooled Analyses

The pooled OR for the association between NAT1 polymorphism and the risk of HNC from eight studies was 0.89 (95% CI: 0.77, 1.02; p = 0.09; I2 = 48%), (Figure 2). The pooled effect estimate was not significant demonstrating no association between NAT1 polymorphism and the risk of HNC.
Forest plot in Figure 3 illustrates that the pooled OR was 1.22 (95% CI: 1.02, 1.46; p = 0.03; I2 = 74%) for the relationship between NAT2 polymorphism and the HNC risk. This indicates that slow acetylators are related to high risk of HNC.

3.4. Subgroup Analyses

When there was one study for a subgroup, we could delete it [61]. Subgroup analyses were performed based on ethnicity, sample size, control source, genotyping method, and tumor type (Table 3). With regards to NAT1 polymorphism, no subgroup differences were observed. For NAT2 polymorphism, significant subgroup effects were observed for ethnicity and the control source. Slow acetylators among Asians and also the population-based studies could be effective factors on the pooled result of the association between NAT2 polymorphism and the HNC risk.

3.5. Meta-Regression

The meta-regression analyses assessing the effect of publication year, the sample size, and the mean age and gender distribution of cases and controls on the risk of HNC in NAT1 and NAT2 polymorphisms are shown in Table 4. Sample size, the mean age of cases, and the percentage of males in the controls were confounding factors for the pooled result of the association between NAT2 polymorphism and the HNC susceptibility. With an increase in sample size, age of the cases, and percentage of males in the controls, the OR decreased.

3.6. Trial Sequential Analysis

TSA for both polymorphisms (NAT1 and NAT2) and the HNC risk is illustrated in Figure 4. The Z-curve (blue line) did not reach the RIS or the boundary lines or enter the futility area for either polymorphism and therefore, the amount of information was not large enough, suggesting the need for more studies.

3.7. Sensitivity Analysis

Both “one-study-removed” and “cumulative analysis” illustrated the pooled data stability for NAT1 and NAT2 polymorphisms (data not presented). After removing one study [46] with outlier data, in concordance with previous analysis, the new pooled result did not report any relationship between NAT2 polymorphism and the HNC susceptibility (OR = 1.17; 95% CI: 0.99, 1.39; p = 0.07, I2 = 70%). In addition, after removing the studies with a quality score of less than 7 for NAT2 polymorphism [43,49,53], the new result remained similar (OR = 1.27; 95% CI: 1.03, 1.57; p = 0.03; I2 = 76%). Removal of studies with a quality score of less than 7 for NAT1 polymorphism [39,52], did not change the pooled estimate (OR = 0.85; 95% CI: 0.75, 1.02; p = 0.08; I2 = 62%).

3.8. Publication Bias

The Egger’s (p = 0.240) and Begg’s (p = 0.322) tests did not reveal any publication bias for NAT1 polymorphism, but both tests revealed the presence of publication bias for NAT2 polymorphism (Egger’s: p = 0.012 and Begg’s: p = 0.028), (Figure 5).

4. Discussion

This meta-analysis showed a significant relationship between NAT2 polymorphisms and the HNC susceptibility with slow acetylators being at higher risk for HNC than rapid acetylators. For NAT2 polymorphism, the ethnicity, the control source, and genotyping methods could modify the association of this polymorphism and the HNC risk. In addition, TSA showed the amount of information for the association between the polymorphisms (NAT1 and NAT2) and the HNC risk was not large enough.
The findings from studies exploring the association of NAT1 polymorphism with other cancers and HNC are different. One meta-analysis [24] found NAT1 polymorphism to be related to the risk of lung, colorectal, head and neck, bladder, and gastric carcinomas, but not with prostate, breast, and pancreatic carcinomas and non-Hodgkin’s lymphoma. Varzim et al. [47] checked the association between NAT1 polymorphism and the laryngeal cancer risk and found that the association depends on tumor location. Among the eight studies included in our meta-analyses [23,35,38,39,44,47,52,60] which evaluated the association between NAT1 polymorphism and the HNC risk, just one study [35] reported a protective role of NAT1 slow acetylators in the HNC patients while the rest of the studies did not find any association.
Comparing the individual studies included in the meta-analysis, differences were observed between the studies. For example, five studies [41,46,48,55] found an elevated risk of HNC for NAT2 slow acetylators, one found a protective role of these acetylators in HNC patients, and three did not find any association between NAT2 polymorphism and the HNC risk [23,45,49].
Effective factors on the association between NAT polymorphisms and the risk of HNC were not included in our analysis due to low numbers of studies, including smoking, gene combination, and the linkage disequilibrium. One study [41] found an elevated frequency of the NAT2 slow acetylator genotypes among HNC patients who smoked less than those who smoked more frequently. Another study reported an association in cases with a smoking history ≤30 years in duration [35]. These contradictory results [35,41,46] suggest the need to evaluate the effect of NAT polymorphisms independent of the history of smoking. In addition, assessing the frequencies of gene-gene combination (NAT2 with GSTM1, XPD, and CYP1A1) between cases with laryngeal cancer and the controls, the frequency of combinations was superior to cases than in controls where the numbers of combinations had an increased risk of laryngeal cancer and the numbers of other combinations had a protective role [40]. The linkage disequilibrium between the genes of NAT1 and NAT2 has been observed in HNC [23,38,62] and other cancers [63,64,65]. Research [66] showed the highest level of carcinogen-DNA adducts formation in cases with acetylation activity of NAT1 rapid and NAT2 slow. Therefore, future studies should consider the linkage between these polymorphisms.
The limitations of the present meta-analysis were: (1) low sample size in some studies. (2) In a number of the involved studies, the controls were not well matched to the cases. (3) Low numbers of studies entered to the analysis as shown by TSA. (4) Existence of publication bias and high heterogeneity between the analyses.

5. Conclusions

There was no association between NAT1 polymorphism and susceptibility to HNC, whereas an association between and NAT2 polymorphism and the HNC risk was found. Slow acetylators of NAT2 polymorphism were at greater risk for HNC than the rapid acetylators. Despite the stability of the results, the presence of high heterogeneity, publication bias, and confounding factors warrant the need for more studies to confirm the results of the present meta-analysis as well as TSA.

Author Contributions

Conceptualization: H.M. and M.S. (Masoud Sadeghi); Methodology: M.M.R., A.G., H.H., M.S. (Masoud Sadeghi), B.G., J.T., A.A.M., M.D., S.M., M.M., M.S. (Mojtaba Salehi), D.S.-B. and S.B.; Formal analysis and investigation: M.S. (Masoud Sadeghi); Writing—original draft preparation: M.M.R., A.G., H.H., M.S. (Masoud Sadeghi), B.G., J.T., A.A.M., M.D., S.M., M.M., M.S. (Mojtaba Salehi), D.S.-B. and S.B.; Writing—review and editing: M.M.R., A.G., H.H., M.S. (Masoud Sadeghi), B.G., J.T., A.A.M., M.D., S.M., M.M., M.S. (Mojtaba Salehi), D.S.-B. and S.B.; Funding acquisition: H.M. and S.B.; Resources: H.M.; Supervision: M.M.R., A.G., H.H., M.S. (Masoud Sadeghi), B.G., J.T., A.A.M., M.D., S.M., M.M., M.S. (Mojtaba Salehi), D.S.-B. and S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We thank Undine Lang, medical director of the Psychiatric Clinics of the University of Basel (UPK; Basel, Switzerland) for financially support the open access publication.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Flowchart of the study selection.
Figure 1. Flowchart of the study selection.
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Figure 2. Forest plot for the association between N-acetyltransferases 1 (NAT1) polymorphism and the risk of head and neck cancer (slow vs. rapid acetylators). The diamond at the bottom of the forest plot illustrates the pooled result. The square in front of a individual study shows the result of the study and its horizontal line shows 95% confidence interval of the result.
Figure 2. Forest plot for the association between N-acetyltransferases 1 (NAT1) polymorphism and the risk of head and neck cancer (slow vs. rapid acetylators). The diamond at the bottom of the forest plot illustrates the pooled result. The square in front of a individual study shows the result of the study and its horizontal line shows 95% confidence interval of the result.
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Figure 3. Forest plot demonstrating association between N-acetyltransferases 2 (NAT2) polymorphism and the risk of head and neck cancer (slow vs. rapid). The diamond at the bottom of the forest plot illustrates the pooled result. The square in front of a individual study shows the result of the study and its horizontal line shows 95% confidence interval of the result.
Figure 3. Forest plot demonstrating association between N-acetyltransferases 2 (NAT2) polymorphism and the risk of head and neck cancer (slow vs. rapid). The diamond at the bottom of the forest plot illustrates the pooled result. The square in front of a individual study shows the result of the study and its horizontal line shows 95% confidence interval of the result.
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Figure 4. Trial sequential analysis of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators) [α = 5% and 1-β = 80%]. (A) NAT1 [diversity or D2 = 52%] and (B) NAT2 [D2 = 76%].
Figure 4. Trial sequential analysis of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators) [α = 5% and 1-β = 80%]. (A) NAT1 [diversity or D2 = 52%] and (B) NAT2 [D2 = 76%].
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Figure 5. Funnel plot analyses of the association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators). (A) NAT1 and (B) NAT2.
Figure 5. Funnel plot analyses of the association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators). (A) NAT1 and (B) NAT2.
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Table 1. Characteristics of the articles included in the meta-analysis.
Table 1. Characteristics of the articles included in the meta-analysis.
The First Author, Publication Year Country Ethnicity Control Source Number Mean Year Male Percentage Type of Tumor Genotyping Method Quality Score
CaseControlCaseControlCaseControl
Gonzalez, 1998 [41]SpainCaucasianPB7520058.74510075Oral, pharyngeal, laryngeal PCR-RFLP 7
Katoh, 1998 [35]JapanAsianHB6212261.762.464.561.5Oral PCR-RFLP 7
Henning, 1999 [23]GermanyCaucasianHB25551061.4NA90.6NALaryngeal PCR 7
Jourenkova-Mironova, 1999 [44]FranceCaucasianHB25017254.454.99694.8Oral, pharyngeal, laryngeal PCR-RFLP 7
Morita, 1999 [54]JapanAsianPB14516459.049.886.962.2Oral, pharyngeal, laryngeal PCR 7
Olshan, 2000 [60]USAMixedHB17119359.556.881.359.1Oral, pharyngeal, laryngeal PCR 7
Chen, 2001 [36]USACaucasianPB341552NANA70.471.6Oral PCR-RFLP 9
Fronhoffs, 2001 [39]GermanyCaucasianHB29130059.847.180.158Oral, pharyngeal, laryngealRT-PCR6
Hahn, 2002 [42]GermanyCaucasianPB949261.545.165.951.1Oral PCR-RFLP 7
Lei, 2002 [51] China AsianHB625660.258.2NANALaryngeal PCR-RFLP 7
Varzim, 2002 [47]PortugalCaucasianPB8817262.843.094.372.7Laryngeal PCR-RFLP 7
Cheng, 2003 [49]TaiwanAsianHB279325NANANANAPharyngeal PCR-RFLP 6
Gajecka, 2005 [40]PolandCaucasianHB28931157.945.9100100Laryngeal PCR-RFLP 8
Rydzanicz, 2005 [45]PolandCaucasianHB26614361.653.195.1100Oral, pharyngeal, laryngeal PCR-RFLP 8
Unal, 2005 [46] Turkey CaucasianHB4510453.550.093.365.4Laryngeal PCR-RFLP 7
Marques, 2006 [58]BrazilMixedHB23121256.655.383.579.2Oral PCR-RFLP 8
Gara, 2007 [57]TunisiaMixedHB6416050.753.665.645Oral, pharyngeal, laryngeal PCR-RFLP 7
Majumder, 2007 [53]IndiaAsianHB297342NANANANAOral PCR-RFLP 6
Boccia, 2008 [22]ItalyCaucasianHB21024563.663.371.472.2Oral, pharyngeal, laryngeal PCR-RFLP 8
Buch, 2008 [56]USAMixedPB18239958.758.787.475.7Oral PCR-RFLP 9
Harth, 2008 [43]GermanyCaucasianHB31230059.747.280.458.7Oral, pharyngeal, laryngeal PCR-RFLP 6
Chatzimichalis, 2010 [37]GreeceCaucasianHB8810266.562.587.574.5Laryngeal PCR-RFLP 8
Demokan, 2010 [38]TurkeyCaucasianPB959359.653.386.352.7Oral, pharyngeal, laryngeal PCR 8
Hou, 2011 [50] China AsianPB17217049.649.6100100Oral, pharyngealPCR-RFLP and Taqman9
Balaji, 2012 [48]IndiaAsianHB15713253.155.154.834.8OralTaqman7
Majumder, 2012 [52]IndiaAsianHB299381NANANANAOralPCR6
Tian, 2013 [55]ChinaAsianPB23310260.060.0NANALaryngealPCR8
Marques, 2014 [59]BrazilMixedPB101141NANANANAOral, pharyngeal, laryngealPCR-RFLP7
Abbreviations: HB, hospital-based; PB, Population-based; PCR, Polymerase Chain Reaction; RT, Real Time; RFLP, Restriction Fragment Length Polymorphism; NA, Not Available. Taqman: The 5′ Nuclease Assay.
Table 2. Prevalence of the polymorphisms of N-acetyltransferases 1 and 2 (NAT1 and NAT2), (slow vs. rapid acetylators).
Table 2. Prevalence of the polymorphisms of N-acetyltransferases 1 and 2 (NAT1 and NAT2), (slow vs. rapid acetylators).
Author, Year NAT1
CaseControl
SlowRapidSlowRapid
Katoh, 1998 [35]9534676
Henning, 1999 [23]144109232164
Jourenkova-Mironova, 1999 [44]1411099874
Olshan, 2000 [60]838810885
Fronhoffs, 2001 [39]1959620694
Varzim, 2002 [47]484010765
Demokan, 2010 [38]53424251
Majumder, 2012 [52]128171168213
Author, YearNAT2
CaseControl
SlowRapidSlowRapid
Gonzalez, 1998 [41]284737163
Katoh, 1998 [35]7557115
Henning, 1999 [23]138117286224
Jourenkova-Mironova, 1999 [44]1421089181
Morita, 1999 [54]1812717147
Chen, 2001 [36]198143302250
Hahn, 2002 [42]59355735
Lei, 2002 [51]50123422
Varzim, 2002 [47]47417696
Cheng, 2003 [49]3924054271
Gajecka, 2005 [40]127162165146
Rydzanicz, 2005 [45]1311357271
Unal, 2005 [46]1530797
Marques, 2006 [58]2920238174
Gara, 2007 [57]333159101
Majumder, 2007 [53]190107205137
Boccia, 2008 [22]109101128117
Buch, 2008 [56]8498224175
Harth, 2008 [43]189123181119
Chatzimichalis, 2010 [37]39496537
Demokan, 2010 [38]50454548
Hou, 2011 [50]4612633137
Balaji, 2012 [48]100576765
Tian, 2013 [55]189445646
Marques, 2014 [59]48535190
Table 3. Subgroup analyses of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
Table 3. Subgroup analyses of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
Polymorphism Variable (N) OR 95% CI p-Value I2 Pheterogeneity
NAT1Overall (8)0.890.77, 1.020.0948%0.06
Ethnicity
Caucasian (5)0.960.80, 1.150.640%0.45
Asian (2)0.550.17, 1.800.3287%0.005
Control source
Hospital-based (6)0.870.74, 1.010.0646%0.10
Population-based (2)1.050.51, 2.170.9072%0.06
Sample size
≥200 (6)0.900.77, 1.040.150%0.87
<200 (2)0.670.13, 3.560.6491%0.0007
Genotyping method
PCR (4)0.940.79, 1.140.5426%0.26
PCR-RFLP (3)0.640.34, 1.180.1574%0.02
Tumor type
Oral (2)0.550.17, 1.800.3287%0.005
Laryngeal (2)0.870.67, 1.150.330%0.43
NAT2Overall (25)1.221.02, 1.460.0374%<0.00001
Ethnicity
Caucasian (13)1.100.89, 1.370.3871%<0.0001
Asian (8)1.601.13, 2.260.00869%0.002
Mixed (4)1.040.61, 1.770.8979%0.003
Control source
Hospital-based (15)1.100.88, 1.370.3971%<0.0001
Population-based (10)1.411.04, 1.920.0375%<0.0001
Sample size
≥200 (20)1.191.00, 1.420.0570%<0.00001
<200 (5)1.490.68, 3.290.3285%<0.0001
Genotyping method
PCR (4)1.470.77, 2.780.2485%0.0002
PCR-RFLP (19)1.140.93, 1.390.2172%<0.00001
Tumor type
Oral (7)1.050.80,1.380.7262%0.01
Pharyngeal (2)0.820.54, 1.240.350%0.96
Laryngeal (8)1.480.88, 2.510.1488%<0.00001
Abbreviations: PCR, Polymerase Chain Reaction; RFLP, Restriction Fragment Length Polymorphism.
Table 4. Meta-regression analysis of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
Table 4. Meta-regression analysis of association between N-acetyltransferases 1 and 2 (NAT1 and NAT2) polymorphisms and the risk of head and neck cancer (slow vs. rapid acetylators).
Polymorphism Variable Point Estimate Standard Error Lower Limit Upper Limit Z-Value p-Value
NAT1Publication yearSlope0.018300.01361−0.008370.044971.344620.17875
Intercept−36.7709827.26207−90.2036516.66169−1.348800.17740
Sample sizeSlope0.000270.00045−0.000600.001150.612400.54027
Intercept−0.259930.24912−0.748190.22833−1.043400.29676
Mean age of casesSlope−0.011790.03248−0.075460.05186−0.363000.71660
Intercept0.570371.93376−3.219724.360470.294960.76803
Mean age of controlsSlope−0.022630.03624−0.093650.04839−0.624590.53224
Intercept1.179382.13386−3.002905.361670.552700.58047
Male percentage of casesSlope−0.011310.01256−0.035930.01331−0.900740.36773
Intercept0.867381.11137−1.310873.045620.780460.43512
Male percentage of controlsSlope−0.002680.00617−0.014780.00942−0.434740.066375
Intercept0.032300.43459−0.819480.884090.074330.94074
NAT2Publication yearSlope0.009440.01016−0.010470.029340.0929420.35267
Intercept−18.8228420.36308−58.7337321.08806−0.924360.35530
Sample sizeSlope−0.000800.00020−0.00120−0.00040−3.912390.00009
Intercept0.508820.113000.287330.730304.502650.00001
Mean age of casesSlope−0.040500.01356−0.06706−0.01393−2.0987760.00281
Intercept2.478880.800070.910774.046993.098320.00195
Mean age of controlsSlope−0.004380.00889−0.021800.01305−0.492030.62270
Intercept0.346910.47403−0.582171.276000.731840.46427
Male percentage of casesSlope−0.06290.00393−0.013990.00141−1.602010.10915
Intercept0.573660.33428−0.081521.228841.716100.08614
Male percentage of controlsSlope−0.007850.00289−0.01351−0.00219−2.719890.00653
Intercept0.643730.221520.209561.077902.905980.00366
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Mohammadi, H.; Roochi, M.M.; Sadeghi, M.; Garajei, A.; Heidar, H.; Ghaderi, B.; Tadakamadla, J.; Meybodi, A.A.; Dallband, M.; Mostafavi, S.; et al. Association of N-acetyltransferases 1 and 2 Polymorphisms with Susceptibility to Head and Neck Cancers—A Meta-Analysis, Meta-Regression, and Trial Sequential Analysis. Medicina 2021, 57, 1095. https://doi.org/10.3390/medicina57101095

AMA Style

Mohammadi H, Roochi MM, Sadeghi M, Garajei A, Heidar H, Ghaderi B, Tadakamadla J, Meybodi AA, Dallband M, Mostafavi S, et al. Association of N-acetyltransferases 1 and 2 Polymorphisms with Susceptibility to Head and Neck Cancers—A Meta-Analysis, Meta-Regression, and Trial Sequential Analysis. Medicina. 2021; 57(10):1095. https://doi.org/10.3390/medicina57101095

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Mohammadi, Hady, Mehrnoush Momeni Roochi, Masoud Sadeghi, Ata Garajei, Hosein Heidar, Bayazid Ghaderi, Jyothi Tadakamadla, Ali Aghaie Meybodi, Mohsen Dallband, Sarton Mostafavi, and et al. 2021. "Association of N-acetyltransferases 1 and 2 Polymorphisms with Susceptibility to Head and Neck Cancers—A Meta-Analysis, Meta-Regression, and Trial Sequential Analysis" Medicina 57, no. 10: 1095. https://doi.org/10.3390/medicina57101095

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