Genetic Polymorphisms of miR-149 Associated with Susceptibility to Both Pulmonary and Extrapulmonary Tuberculosis

Abstract

Background:

Single nucleotide polymorphisms (SNPs) within precursor microRNAs (miRNAs) can affect the expression of the miRNAs and may be involved in the pathogenesis of pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB).

Aims:

We investigated the potential associations among four precursor miRNA SNPs (miR-149 A>G, C>T; miR-196a2 C>T; miR-499 C>T) and both PTB and EPTB.

Methods:

The study included 380 PTB patients, 242 EPTB patients, and 606 healthy control (HC) subjects from a Chinese Han population. We determined the miRNA relative expression levels from 10 HCs and 10 tuberculosis (TB) patients by quantitative PCR.

Results:

We found that the PTB group had a significantly lower miR-149 level (p < 0.05) versus the HCs. The allele and genotype frequencies of the miR-149 SNPs were significantly different between the TB patients and the HC group. The C allele at the rs2292832 and the A allele at the rs71428439 locus were associated with susceptibility to EPTB. The C allele of rs2292832 was associated with an increased risk of EPTB compared with that of HCs (p < 0.01), and the A allele of rs71428439 was protective against EPTB (p < 0.01) and PTB (p < 0.01).

Conclusions:

We identified genetic polymorphisms in miR-149 that appear to be associated with susceptibility to both PTB and EPTB within a Chinese population.

Introduction

Tuberculosis (TB) caused by Mycobacterium tuberculosis remains a major global health problem. TB causes morbidity among millions of people each year and ranks as the second leading cause of death from an infectious disease worldwide (World Health Organization 2017). China has the second largest TB prevalence in the world, and the loss of life and property caused by TB is inestimable. Previous reports have shown that ∼90% of infected individuals will remain asymptomatic with latent M. tuberculosis infection (LTBI), and only 10% of the individuals infected with M. tuberculosis will develop active disease (Khalilullah et al., 2014). These findings suggest that host genetic factors play a crucial role in regulating the progression of TB infection. The innate susceptibility to TB has a genetic component, but the precise mechanism of this genetic component remains unknown. Describing the interplay of host genetics and M. tuberculosis may provide insight into the occurrence, progression, and control of the disease.

microRNAs (miRNAs) are a class of endogenous, small, and noncoding RNAs. These molecules have been identified as important regulators of gene expression at the post-transcriptional level, and miRNAs influence many biological systems including mammalian immune systems (Williams, 2008). Macrophages and natural killer (NK) cells are important in the immunity of TB. Several studies have revealed altered gene expression profiles in macrophages and NK cells from active and latent TB as well as from TB patients and healthy controls (HCs) (Maertzdorf et al., 2011; Matthew et al., 2012). Several studies have shown that miRNAs play an important role in human immunity against M. tuberculosis. For example, miR-29 downregulates interferon-γ and regulates the apoptotic pathway in immune cells to suppress immune responses to M. tuberculosis (Park et al., 2009; Ma et al., 2011). miR-99b regulates the expression of various cytokines and transcription factors by targeting the tumor necrosis factor (TNF) receptor superfamily and TNF-α mRNA (Singh et al., 2013). It is known that TNF-α plays a crucial role in controlling M. tuberculosis growth in macrophages through several mechanisms, and this protein plays a central role in the establishment and maintenance of LTBI (Algood et al., 2005; Jacobs et al., 2007; Algood et al., 2005). Studies have shown that miR-149 represents an important new regulator of endothelial function through the negative regulation of molecules associated with TNF-α-induced endothelial dysfunction. Therefore, we hypothesized that miR-149 might influence the antituberculosis response in humans. Four potentially functional single nucleotide polymorphisms (SNPs) in pre-miRNAs (miR-149A>G, C>T; miR-196a2 C>T; miR-499C>T) have been listed in the public miRNA database, and the expression of miRNAs has also been found to be correlated with TB. Therefore, we speculated that a correlation exists between the miRNA SNPs and the susceptibility to pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB).

Materials and Methods

Subjects

The control population included 606 individuals (262 females and 344 males) who were at least 18 years of age and attested to no history of TB; the purified protein derivative tests and QuantiFERON-TB tests were negative, and no evidence of prior TB presented in the chest radiographies. Individuals in the control group were matched with the case group according to age, gender, and ethnicity. A total of 622 patients (266 females and 356 males) were recruited from the Shanghai Pulmonary Hospital in China. The case subjects were further divided into two subgroups based on the location of the infection: (1) PTB patients (n = 380) and (2) EPTB patients (n = 242). PTB patients were smear and culture positive for M. tuberculosis and categorized as low (bacilli burden in sputum [BAAR]+ or BAAR++) or high (BAAR+++ or BAAR++++) smear burden according to Acid-Fast Bacilli in sputum smear. Severe form of PTB was identified according to the appearance of pulmonary cavities measured by chest radiography. EPTB diagnosis was based on the clinical evidence that the M. tuberculosis culture was positive in the sample (needle aspiration cytology, cerebrospinal fluid, ascites, etc.) as well as clinical and radiography features. Among the 242 patients with EPTB, the following groups were identified: (58) pleurisy TB, (42) meningitis TB, (46) lymph node TB, (46) bone TB, (12) urinary TB, (10) genital TB, (10) TB of pericardium, (8) laryngophthisis, and (10) intestinal TB. For the sample size, we merged the last five groups and defined these individuals as other extra TB (50 cases). The demographic characteristic data are indicated in Table 1.

Table 1.

Demographic Characteristics of Tuberculosis Patients and Healthy Controls

Subgroup	Number	Male	Female	Age, mean ± SD	BMI, mean ± SD
Control	606	344	262	34.78 ± 9.70	21.57 ± 3.06
PTB	380	220	136	36.43 ± 12.50	20.34 ± 3.29
EPTB	242	160	106	35.32 ± 12.55	21.64 ± 3.15
Pleurisy tuberculosis	58	36	22	33.67 ± 14.30	21.69 ± 2.68
Meningitis tuberculosis	42	26	16	43.04 ± 17.02	22.57 ± 3.44
Lymph node tuberculosis	46	34	12	40.5 ± 17.06	21.88 ± 2.12
Bone tuberculosis	46	28	18	36.20 ± 13.45	20.68 ± 3.32
Other extra tuberculosis	50	36	14	26.14 ± 18.68	21.46 ± 2.94

PTB, pulmonary tuberculosis; EPTB, extrapulmonary tuberculosis; BMI, body mass index; SD, standard deviation.

Ethics statement

All the controls and patients were Chinese, and all the subjects were HIV negative. Written consent was obtained from all the subjects, and the Ethics Committee of the Shanghai Pulmonary Hospital Affiliated to Tongji University School of Medicine, China, provided authorization for the present study.

Variants selected for genotyping

Four SNPs (miR-149 [rs2292832 and rs71428439], miR-499 [rs3746444], and miR-196a2 [rs11614913]) were picked out from the 1000 Genomes Project Phage3. The general rule for selecting tagged SNPs were R2 linkage disequilibrium of >0.8 and minor allele frequency of >0.1. The PCR primers were designed using Primer 3 software and are shown in Table 2.

Table 2.

Single Nucleotide Polymorphisms Identified by Sequencing

SNP ID	miRNA	chr	SNP property	PCR primer	Alleles
rs11614913	miR196a2	12	UTR	F: CGCTCAGCTGATCTGTGGCTTA	C/T
rs11614913	miR196a2	12	UTR	R: TTGTTCTGCAACCCCACTCACA	C/T
rs3746444	miR499	20	intron22	F: CTGGGAGACAGACCCTCCCTCT	C/T
rs3746444	miR499	20	intron22	R: GCCCTGCACTTTTGCTCTTTCA	C/T
rs2292832	miR149	2	intron1	F: TCTGGCTCCGTGTCTTCACTCC	C/T
rs2292832	miR149	2	intron1	R: GGCCCGAAACACCCGTAAGATA	C/T
rs71428439	miR149	2	intron1	F: TCTGGCTCCGTGTCTTCACTCC	A/G
rs71428439	miR149	2	intron1	R: GGCCCGAAACACCCGTAAGATA	A/G

F, forward primer; R, reverse primer; SNP, single nucleotide polymorphism.

DNA isolation and genotyping

DNA was extracted from 1 mL ethylenediaminetetraacetic acid anticoagulated blood samples using a commercial DNA extraction kit (QIAamp Genomic DNA Isolation Mid Kit; Qiagen) according to the manufacturer's recommendations. The DNA samples were stored at −80°C until further analysis. Genotyping of the SNPs was performed using an improved multiplex ligation detection reaction technique.

A 20 μL mixture was prepared to amplify the fragments covering each target SNP in a multiplex PCR (1 × PCR buffer [Takara], 3.0 mM Mg²⁺, 0.3 mM dNTPs, 1 U of Hot-Start Taq DNA polymerase [Takara], 1 μL of primer mixture, and 1 μL of genomic DNA). The following cycling program was used: 95°C for 2 min; 11 cycles of 94°C for 20 s, 65°C-0.5°C/cycle for 40 s, 72°C for 1.5 min; 24 cycles of 94°C for 20 s, 59°C for 30 s, 72°C for 1.5 min; and 72°C for 4 min, with a final hold at 4°C. After amplification, shrimp alkaline phosphatase (SAP) and exonuclease I (ExoI) were used to purify the PCR product. Then, 5 U of SAP enzyme and 2 U ExoI enzyme were added to 20 μL of PCR product, followed by incubating for 1 h at 37°C and subsequent inactivation at 75°C for 15 min. The ligation reaction was performed in a 10 μL volume, containing 1 × ligation buffer, 0.25 μL of Taq DNA ligase (NEB), 0.4 μL of 5′ ligation probe mixture, 0.4 μL of 3′ ligation probe mixture, 2 μL of purified multiple PCR product, and 6 μL of ddH₂O. To detect polymorphisms, we used the following ligation probes: rs11614913FP: CTGAGTTACATCAGTCGGTTTTCGTCTTTTTTTTTT; rs2292832FP: GGAACAACGCAGGTCG CCGTTTTTTTTT; rs3746444RP: GTTCACGTGGAGAGGAGTTAAACATCTTTTTTTT; rs71428439FP: GCYGGAACAACGCAGGTCGCCGTTTTTTTTT. The ligation cycling program was 38 cycles at 94°C for 1 min, and 56°C for 4 min, with a final hold at 4°C. A total of 0.5 μL of the ligation product was loaded onto an ABI 3730xl DNA analyzer and the raw data were analyzed by GeneMapper 4.1.

RNA isolation, reverse transcription, and quantitative PCR

The total RNA was extracted from the peripheral blood using TRIzol reagent according to the manufacturer's protocol. The RNA yield and A260/280 ratio were monitored with the ScanDrop100 spectrometer. The total RNA (100 ng) was reverse transcribed to cDNA, and quantitative PCR was performed to quantify mature miR-149 expression using the TaqMan miRNA assay (Applied Biosystems) according to the manufacturer's instructions. The samples were measured in triplicate in three different experiments. U6 was used as a reference for the data analysis of the human samples. Mean normalized gene expression ± standard error was calculated from independent experiments.

Statistical analysis

The genotype and allele distributions between the patient and the control groups were compared using the χ² test or Fisher's exact test. The data were analyzed using the SHEsis system and were then evaluated for fit in the Hardy-Weinberg equilibrium (HWE) to ensure that all the data were within-population equilibrium. Relative risk was estimated with an odds ratio and 95% confidence interval of p < 0.05, which was considered statistically significant. To illustrate the multiple comparisons, the Bonferroni correction was used in the present study, and the corrected p-value was five times the observed p-value.

Results

Analysis of the associations between the miRNAs alleles and the genotypes with PTB patients and controls

There were no significant differences in age and gender and body mass index between TB cases and controls, and the data are indicated in Table 1. To determine the relationship between miRNAs and PTB, we collected the blood samples to examine the polymorphisms of miRNAs. The allelic frequencies of the four miRNA SNPs in PTB patients and control subjects are shown in Tables 3 and 4. Both populations were consistent with the HWE for all the polymorphisms tested (p > 0.05). As shown in Tables 3 and 4, miR-149 (rs71428439) showed significant differences in PTB patients when compared with that in HCs (p < 0.001). However, miR-499 (rs3746444), miR-149 (rs2292832), and miR-196a2 (rs11614913) were not associated with PTB.

Table 3.

Allele Frequencies of microRNA Single Nucleotide Polymorphisms in the Pulmonary Tuberculosis Patients and Healthy Controls

SNP ID	Alleles (MAF/minor)	Group	N	Allele frequency (%)		p Value	OR (95% CI)
rs3746444	C/T	PTB	380	642 (0.845)	118 (0.155)	0.26	0.827480 (0.64-1.10)
rs3746444	C/T	Control	606	1052 (0.868)	160 (0.132)	0.26	0.827480 (0.64-1.10)
rs2292832	C/T	PTB	380	262 (0.345)	498 (0.665)	0.15	1.151892 (0.95-1.40)
rs2292832	C/T	Control	606	380 (0.314)	832 (0.686)	0.15	1.151892 (0.95-1.40)
rs71428439	A/G	PTB	380	614 (0.808)	146 (0.192)	0.0007^*	0.658109 (0.52-0.84)
rs71428439	A/G	Control	606	1048 (0.865)	164 (0.135)	0.0007^*	0.658109 (0.52-0.84)
rs11614913	C/T	PTB	380	336 (0.442)	424 (0.558)	0.132	0.869230 (0.72-1.04)
rs11614913	C/T	Control	606	578 (0.477)	634 (0.523)	0.132	0.869230 (0.72-1.04)

p Indicates the significant association after the Bonferroni correction for multiple testing at the significance level α = 0.05.

MAF, minor allele frequency; OR, odds ratio; CI, confidence interval.

Table 4.

Genotypic Frequencies of microRNA Single Nucleotide Polymorphisms in the Pulmonary Tuberculosis Patients and Healthy Controls

SNP ID	Genotype	Genotype frequency (%)		p Value
SNP ID	Genotype	PTB patients	Controls	p Value
rs3746444	A/A	274 (0.721)	454 (0.749)	0.12
	A/G	94 (0.247)	144 (0.238)
	G/G	12 (0.032)	8 (0.013)
rs2292832	C/C	60 (0.158)	66 (0.109)	0.07
	C/T	142 (0.374)	248 (0.409)
	T/T	178 (0.468)	292 (0.482)
rs71428439	A/A	248 (0.653)	454 (0.749)	0.004^*
	A/G	118 (0.311)	140 (0.231)
	G/G	14 (0.037)	12 (0.020)
rs11614913	C/C	70 (0.184)	122 (0.201)	0.192
	C/T	196 (0.516)	334 (0.551)
	T/T	114 (0.300)	150 (0.248)

p Indicates the significant association after the Bonferroni correction for multiple testing at the significance level α = 0.05.

Analysis of the associations between the miRNAs alleles and the genotypes of EPTB patients and controls

To deeply investigate the hypothesis relating to miRNA SNPs with TB, we next analyzed the relationship between EPTB and miRNAs. As shown in Tables 5 and 6, both miR-149 (rs71428439) and miR-149 (rs2292832) showed significant differences in EPTB (p < 0.001). Compared with the above results, miR-149 (rs2292832) was only meaningful in EPTB, suggesting that miR-149 (rs2292832) is the only location that acts on EPTB.

Table 5.

Allele Frequencies of microRNA Single Nucleotide Polymorphisms in the Extrapulmonary Tuberculosis Patients and Healthy Controls

SNP ID	Alleles (MAF/minor)	Group	N	Allele frequency (%)		p Value	OR (95% CI)
rs3746444	C/T	EPTB	242	410 (0.847)	74 (0.153)	0.26	0.842668 (0.63-1.14)
rs3746444	C/T	Control	606	1052 (0.868)	160 (0.132)	0.26	0.842668 (0.63-1.14)
rs2292832	C/T	EPTB	242	192 (0.397)	292 (0.603)	0.001^*	1.439654 (1.16-1.80)
rs2292832	C/T	Control	606	380 (0.314)	832 (0.686)	0.001^*	1.439654 (1.16-1.80)
rs71428439	A/G	EPTB	242	382 (0.789)	102 (0.211)	0.0001^*	0.586065 (0.45-0.77)
rs71428439	A/G	Control	606	1048 (0.865)	164 (0.135)	0.0001^*	0.586065 (0.45-0.77)
rs11614913	C/T	EPTB	242	220 (0.455)	264 (0.545)	0.405	0.914072 (0.74-1.13)
rs11614913	C/T	Control	606	578 (0.477)	634 (0.523)	0.405	0.914072 (0.74-1.13)

p Indicates the significant association after the Bonferroni correction for multiple testing at the significance level α = 0.05.

Table 6.

Genotypic Frequencies of microRNA Single Nucleotide Polymorphisms in the Extrapulmonary Tuberculosis Patients and Healthy Controls

SNP ID	Genotype	Genotype frequency (%)		p Value
SNP ID	Genotype	EPTB patients	Controls	p Value
rs3746444	A/A	170 (0.702)	454 (0.749)	0.26
	A/G	70 (0.289)	144 (0.238)
	G/G	2 (0.008)	8 (0.013)
rs2292832	C/C	38 (0.157)	66 (0.109)	0.005^*
	C/T	116 (0.479)	248 (0.409)
	T/T	88 (0.364)	292 (0.482)
rs71428439	A/A	152 (0.628)	454 (0.749)	0.0007^*
	A/G	78 (0.322)	140 (0.231)
	G/G	12 (0.050)	12 (0.020)
rs11614913	C/C	48 (0.198)	122 (0.201)	0.438
	C/T	124 (0.512)	334 (0.551)
	T/T	70 (0.289)	150 (0.248)

p Indicates the significant association after the Bonferroni correction for multiple testing at the significance level α = 0.05.

Association between clinical features and the rs71428439 SNP variants in PTB

To assess the relationship between polymorphism and disease severity, we also analyzed clinical features. In PTB patients, 68% of rs71428439 AA genotype displayed no cavitary PTB, whereas just 29% of rs71428439 GG genotype displayed no cavitary PTB (p < 0.01). Furthermore, bacilli burden in sputum between three genotypes has no significant difference (Table 7). These results indicated that rs71428439 AA genotype in PTB patients exhibited protective effection of lung tissue, indirectly affecting the severity of the disease and associated with clinical features.

Table 7.

Association Between Clinical Features and the rs71428439 Single Nucleotide Polymorphism Variants in Pulmonary Tuberculosis

Tuberculosis patient	rs71428439			p Value
Tuberculosis patient	GG	GA	AA	p Value
AFB in sputum smear (n = 380)
BAAR+ or BAAR++	8 (57%)	58 (50%)	154 (62%)	0.09
BAAR+++ or BAAR++++	6 (43)%	58(50%)	94 (38%)	0.09
Radiological lesions (n = 380)
Cavity	10 (71%)	60 (52%)	80 (32%)	<0.01
No cavity	4 (29%)	56 (48%)	170 (68%)	<0.01

Acid-fast bacilli (AFB) in sputum smear: BAAR+ (bacilli burden in sputum), 1-9 bacilli/100 fields; BAAR++, 1-9 bacilli/10 fields; BAAR+++, 1-9 bacilli/field; BAAR++++, >10 bacilli/field.

Reduced expression of miR-149 in TB patients

From the above results, we found that the miR-149 polymorphism shows a significant difference between TB patients and HCs. To investigate the relationship between TB and miR-149, we collected the peripheral blood to detect the miR-149 relative expression (Fig. 1). As shown in Figure 1, miR-149 is slightly expressed in TB patients compared with that in HC population (*p < 0.05).

FIG. 1.

Relative miR-149 expression between TB patients and HC populations. Quantitative PCR detection of miR-149 in the peripheral blood from TB (n = 10) and HC (n = 10) individuals. TB, tuberculosis; HC, healthy control.

Discussion

TB is a chronic inflammatory disease that occurs throughout the entire body and can cause multisystem complications, including pulmonary, osteoarticular, renal, and central nerve system complications. The initiation and progression of TB involve the dynamic interplay between numerous signaling pathways and cell types, whereas macrophages, dendritic cells (DCs), T cells, and other cellular elements present at infection sites contribute to M. tuberculosis pathogenesis. Several miRNAs have been found to regulate T cell differentiation and function (Ebert et al., 2009; Du et al., 2009; O'Connell et al., 2010a, 2010b). Moreover, miRNAs are important in regulating the innate function of macrophages, DCs, and NK cells (Taganov et al., 2006; Bezman et al., 2010). Increasing evidence has revealed that miRNAs play an important role in the molecular pathology of TB.

In the present study, we focus on miR-149, miR-196a2, and miR-499. According to the results, two miR-149 SNPs showed significant differences between HCs and TB patients. However, there were no significant differences in the frequencies of the alleles and genotypes of miR-196a2 and miR-499. Moreover, we also compared the differences between EPTB patients and HCs among the four SNPs. Consistent with the above results, miR-149 SNPs show a significant difference between HCs and EPTB patients, whereas miR-196a2 and miR-499 showed no significance. Particularly, miRNA149 (rs2292832) was only meaningful in EPTB, whereas miRNA149 (rs71428439) was meaningful in both PTB and EPTB. Thus, miRNA149 (rs2292832) may be used as an indicator of the PTB and EPTB.

The analysis of allele, genotype, and haplotype frequencies and genetic patterns revealed that the miR-149 rs2292832 and rs71428439 are associated with susceptibility to PTB, particularly EPTB, and may increase the risk of infection with PTB. Previous studies have shown that the miR-149 T > C SNP was not associated with pulmonary TB in the Chinese Uygur, Kazak, and Southern Han populations (Zhang et al., 2015). The difference between these results may reflect differences in race and location.

Several studies on miR-149 have previously been reported. The miR-149 rs2292832 polymorphism has been reported that it may not be associated with lung cancer risk in Chinese nonsmoking females (Li et al., 2016). Moreover, miRNA-149 can target specificity protein 1 to suppress human tongue squamous cell carcinoma cell proliferation and motility and may be a novel target for tongue squamous cell carcinoma therapy in the future (Chen et al., 2017). miR-149 expression and functional differences have been demonstrated in various tumor diseases, such as glioma and melanoma (Jin et al., 2011; Shen et al., 2016; Lei et al., 2011). The mechanism of how miR-149 variants regulate susceptibility to human M. tuberculosis infection is not clear. Macrophages are essential components of TB immunity; therefore, we speculated that human miR-149 variation can change the immunity of macrophages and can affect the susceptibility to TB. Further studies are needed to clarify the functional impact of the genetic variants in miR-149 in the respond of the human immunity system to infection.

In summary, the present study associated miR-149, miR-196a2, and miR-499 with the risk of PTB and EPTB, suggesting that the miR-149 polymorphism have significant difference between TB patients and healthy individuals. Further studies are warranted that examine the association between TB and polymorphisms in the genes involved in TB immunity pathways.

Footnotes

Acknowledgments

We are grateful to Mr. J.Y. and Mr. J.C. for their collaboration on this study. This work was supported by the National Great Research Program of China (2018zx10103001-004) and the National Natural Science Foundation of China (81371775).

Author Disclosure Statement

No competing financial interests exist.

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