Effects of MTNR1B genetic variants on the risk of type 2 diabetes mellitus: A meta‐analysis

Abstract Background Whether melatonin receptor 1B (MTNR1B) variants are associated with type 2 diabetes mellitus (T2DM) remains unclear. Therefore, we performed this meta‐analysis to better explore correlations between MTNR1B variants and T2DM. Methods Literature research was performed in PubMed, Medline, and Embase. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results Totally 21 studies were enrolled to analyses. Pooled overall analyses showed that MTNR1B rs10830963 variant was significantly correlated with the susceptibility to T2DM (allele model: p = 0.02, OR = 0.97, 95% CI 0.95–1.00). Further subgroup analyses by ethnicity of participants revealed that rs10830963 variant was significantly correlated with the susceptibility to T2DM in South Asians, but not in Caucasians or East Asians. No any other positive results were found in overall and subgroup analyses. Conclusions Our findings indicated that MTNR1B rs10830963 variant might serve as a genetic biomarker of T2DM, especially in South Asians.


| INTRODUCTION
Type 2 diabetes mellitus (T2DM), characterized by chronic hyperglycemia resulted from resistance against insulin, is the most prevalent metabolic disorder worldwide, and it currently affects over 300 million people all over the world (American Diabetes Association, 2014;Zheng, Ley, & Hu, 2018). To date, the exact underlying pathogenic mechanism of T2DM is still unclear. Nevertheless, accumulating evidence support that genetic predisposition factors may play a crucial part in its pathogenesis. First, it was proved that positive family history is a strong independent risk factor of T2DM (Papazafiropoulou, Papanas, Melidonis, & Maltezos, 2017). Second, over one hundred genetic loci were found to be correlated with an increased risk of T2DM by past genome-wide association studies (Gaulton, 2017). Overall, these findings jointly supported that genetic factors are crucial for the occurrence and development of T2DM.
So far, several studies already investigated potential roles of MTNR1B in T2DM. But the results of these studies were inconsistent (Hu & Jia, 2016;She, Laudon, & Yin, 2014). Therefore, we performed the present meta-analysis to better evaluate potential associations between MTNR1B genetic variants and T2DM.

| Literature search and inclusion criteria
This meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline (Moher, Liberati, Tetzlaff, & Altman;PRISMA Group, 2009). Potentially relevant literatures that were published before November 2018 were retrieved from PubMed, Medline, and Embase using the following searching strategy: (melatonin receptor type 1B OR MTNR1B) AND (polymorphism OR variant OR mutation OR genotype OR allele) AND (type 2 diabetes mellitus OR T2DM). We also screened the references of retrieved articles to identify other potentially relevant studies.
To test the research hypothesis of this meta-analysis, included studies must meet all the following criteria: (a) case-control study on correlations between MTNR1B genetic variants and T2DM; (b) provide genotypic and/or allelic frequency of investigated variants in cases and controls; (c) full text in English available. Studies were excluded if one of the following criteria was fulfilled: (a) not relevant to MTNR1B genetic variants and T2DM; (b) case reports or case series; (c) abstracts, reviews, comments, letters, and conference presentations. For duplicate publications, we only included the study with the largest sample size for analyses.

| Data extraction and quality assessment
The following data were extracted from included studies: (a) name of the first author; (b) publication time; (c) country and ethnicity; (d) sample size; and (e) genotypic distributions of MTNR1B variants in cases and controls. The probability value (P-value) of Hardy-Weinberg equilibrium (HWE) was also calculated. When necessary, we wrote to the corresponding authors for raw data. We used the Newcastle-Ottawa scale (NOS) to assess the quality of eligible studies (Stang, 2010). This scale has a score range of 0 to 9, and studies with a score of more than seven were thought to be of high quality. Two experienced reviewers conducted data extraction and quality assessment independently. Any disagreement between two reviewers was solved by discussion until a consensus was reached.

| Statistical analyses
All statistical analyses were conducted with Review Manager Version 5.3.3 (The Cochrane Collaboration, Software Update, Oxford, United Kingdom). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate strength of associations between MTNR1B and T2DM in all possible genetic models, and P-values ≤0.05 were considered to be statistically significant. Between-study heterogeneities were evaluated by I 2 statistic. If I 2 was greater than 50%, random effect models (REMs) would be used to pool the data. Otherwise, fixed effect models (FEMs) would be employed for synthetic analyses. Subgroup analyses by ethnicity of participants were subsequently performed. Sensitivity analyses were conducted to examine the stability of synthetic results. Funnel plots were used to evaluate possible publication biases.

| Characteristics of included studies
We found 370 potential relevant articles. Among these articles, a total of 21 eligible studies were finally included for synthetic analyses (see Figure 1). The NOS score of eligible articles ranged from 7 to 8, which indicated that all included studies were of high quality. Baseline characteristics of included studies were shown in Table 1. HWE assumes that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences. Consider a population of monoecious diploids, where each organism produces male and female gametes at equal frequency, and has two alleles at each gene locus. The allele frequencies at each generation are obtained by pooling together the alleles from each genotype of the same generation according to the expected contribution from the homozygote and heterozygote genotypes.

T A B L E 1 (Continued)
| 5 of 6 SHEN aNd JIN association with the susceptibility to T2DM was detected for rs10830963 variant (allele model: p = 0.02, OR = 0.97, 95% CI 0.95-1.00) in overall analyses. Further subgroup analyses according to ethnicity of participants revealed that rs10830963 variant was significantly correlated with the susceptibility to T2DM in South Asians, but not in East Asians or Caucasians. No any other positive results were found in overall and subgroup analyses (see Table 2 and Supplementary Figure 1).

| Sensitivity analyses
We performed sensitivity analyses by excluding studies that deviated from HWE. No alterations of results were detected in sensitivity analyses, which suggested that our findings were statistically reliable.

| Publication biases
Publication biases were evaluated with funnel plots. We did not find obvious asymmetry of funnel plots in any comparisons, which indicated that our findings were unlikely to be impacted by severe publication biases.

| DISCUSSION
To the best of our knowledge, this is so far the most comprehensive meta-analysis on correlations between MTNR1B genetic variants and T2DM, and our pooled analyses demonstrated that rs10830963 variant may be correlated with susceptibility to T2DM, especially in South Asians.
There are several points that need to be addressed about this meta-analysis. Firstly, previous experimental studies showed that mutant allele of rs10830963 variants was correlated with altered glucose level and B-cell function, which may partially explain our positive finding (Li et al., 2018;Staiger et al., 2008). Secondly, the pathogenic mechanism of T2DM is highly complex, and hence it is unlikely that a single genetic variant could significantly contribute to its development. As a result, to better illustrate potential correlations of certain genetic variants with T2DM, we strongly recommend further studies to perform haplotype analyses and explore potential gene-gene interactions.
Like all meta-analyses, this study certainly has some limitations. First, our results were derived from unadjusted analyses due to lack of raw data, and lack of further adjusted analyses for potential confounding factors may impact the reliability of our findings (Xie, Shi, & Liu, 2017;Xie, Shi, Xun, & Rao, 2017). Second, obvious heterogeneities were found in several subgroups, which indicated that the controversial results of included studies could not be fully explained by differences in ethnic background, and other baseline characteristics of participants may also contribute to between-study The values in bold represent there is statistically significant differences between cases and controls.
heterogeneities (Shi, Xie, Jia, & Li, 2016). Third, associations between MTNR1B genetic variants and T2DM may also be modified by gene-gene and gene-environmental interactions. However, most eligible studies ignore these potential interactions, which impeded us to perform relevant analyses accordingly. To sum up, our findings should be cautiously interpreted on account of above mentioned limitations.
In conclusion, our meta-analysis suggested that MTNR1B rs10830963 variant might serve as a genetic biomarker of T2DM, especially in South Asians. However, further welldesigned studies are still warranted to confirm our findings.

ETHICAL APPROVAL
This article does not contain any studies with human participants or animals performed by any of the authors.