Gene polymorphisms in ULK1 and PIK3CA are associated with the risk of microscopic polyangiitis in the Guangxi Zhuang Autonomous Region in China

Introduction

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of autoimmune diseases characterized by the inflammation of small- and medium-sized blood vessels. AAV is divided into granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic GPA (EGPA). Each clinical phenotype is associated with the presence of circulating ANCAs, mainly proteinase-3 (PR3) and myeloperoxidase (MPO) (Ramponi et al., 2021). AAV is more common in males than females, and its incidence rate increases with age, especially in the range of 60–70 years (Geetha & Jefferson, 2020). Additionally, a notable geographic preponderance of MPA rather than GPA and EGPA is observed in China (Chang et al., 2019).

The precise mechanism of AAV remains unestablished, but a genome-wide association study (GWAS) identified the genetic component in the development of this autoimmune disease. A GWAS conducted in a North American cohort demonstrated that GPA is significantly associated with single-nucleotide polymorphisms (SNPs) in the HLA region encoding major histocompatibility complex (MHC) Class II (Xie et al., 2013). A European study showed that the genetic association with AAV is antigen specificity. PR3-ANCA is associated with HLA-DP, which encodes SERPINA1 and PRTN3, while MPO-ANCA is associated with HLA-DQ (Lyons et al., 2012). Consistent with previous studies, a new large GWAS revealed that MHC and non-MHC gene variates are related to GPA/MPA susceptibility, and changing the expression of genes and proteins is associated with the immune response (Merkel et al., 2017).

Autophagy is an essential metabolic process in eukaryotic cells, and autophagy-related proteins are involved in various pathologies, including disorders of immune regulation, inflammation, and cancer (Wu & Adamopoulos, 2017). The PI3K/AKT/mTOR/ULK1 signaling pathway is one of the main regulators of autophagy. Uncoordinated 51-like kinase 1 (ULK1) is a serine/threonine kinase that plays a key role in the formation of the ULK1 complex. The human ULK1 complex can induce the initiation of the autophagy pathway and maturation of autophagosomes (Lin & Hurley, 2016). PIK3CA encodes the p110 α catalytic subunit of phosphatidylinositol 3-kinase (PI3K), which can inactivate mTOR through the PIK3CA/AKT signaling pathway and lead to autophagy (Qu et al., 2016). PIK3CA and ULK1 are the core components of this signaling pathway, and their mutations may alter the autophagy response and cause a change in the incidence of disease risk (Morgan et al., 2012; Qu et al., 2016; Zhang & Zhou, 2019; Zhang et al., 2017).

Numerous studies have revealed that autoimmune diseases may share susceptibility genes. ULK1 has been shown to be associated with ankylosing spondylitis (Zhang et al., 2017) and Crohn’s disease (Morgan et al., 2012). The cooccurrence of systemic lupus erythematosus (SLE) and AAV reported in cases suggests that these two diseases may have shared genetic factors, especially in MPO-ANCA-positive AAV (Hervier et al., 2012). Emerging evidence shows that autophagy-related gene polymorphisms, such as mTOR (Saravani et al., 2020) and ATG5 (López et al., 2013), participate in SLE. However, as an autoimmune disease, the role of autophagy-related gene mutations in AAV has not yet been reported. Considering that MPA is the most common clinical subtype of AAV in China, we focused on whether gene polymorphisms of ULK1 and PIK3CA play a role in susceptibility to MPA. In the present study, SNP loci with a minor allele frequency (MAF) ≥5% in the functional region of the ULK1 and PIK3CA genes were selected, and the association between these two gene polymorphisms and susceptibility to MPA was explored in a group of patients with MPA and a healthy control group from the Guangxi Zhuang Autonomous Region in China.

Materials & Methods

Results

Linkage disequilibrium analysis

Figure 1 shows the pattern of pairwise LD with respect to the analyzed SNPs of two genes in the current study. The LD plot indicated that the ULK1 rs10902469, rs12303764, rs4964879, rs7300908, rs7138581, and rs9481 loci formed six haplotypes (Table 4). Haplotype G-T-A-C-G-A was the most commonly observed haplotype in the cases (49.2%) and in the healthy controls (56.1%) and was associated with a reduced risk of MPA (OR = 0.749, 95% CI [0.563–0.997], p = 0.047). Other haplotypes did not exhibit an association with MPA. The SNP loci of the PIK3CA genes rs1607237 and rs9838117 also formed three haplotypes (Table 4). The results showed that the C-G haplotype was the most commonly observed haplotype in the cases (73.3%) and in the healthy controls (66.7%) and was associated with an increased risk of MPA (OR = 1.427, 95% CI [1.050–1.939], and p = 0.023). The T-G haplotype was significantly associated with a reduced risk of MPA (OR = 0.520, 95% CI [0.339–0.799], and p = 0.0025).

Table 2:

Basic information about SNPs in ULK1 and PIK3CA and their association with the risk of MPA.

Gene	SNP ID	Location	Alleles	MAF		p for allele frequencies	p for genotypes
				Case	Control
ULK1	rs10902469	12:132378133	G>C	0.079	0.069	0.571	0.832
	rs12303764	12:132399065	T>G	0.200	0.185	0.566	0.678
	rs4964879	12:132400309	A>G	0.406	0.356	0.143	0.019
	rs7300908	12:132405421	C>T	0.099	0.090	0.673	0.897
	rs7138581	12:132406666	G>C	0.174	0.167	0.781	0.853
	rs9481	12:132407089	A>G	0.442	0.378	0.060	0.070
PIK3CA	rs1607237	3:178950297	C>T	0.240	0.325	0.011	0.002
	rs9838117	3:178952507	G>T	0.168	0.165	0.901	0.765

DOI: 10.7717/peerj.12377/table-2

Table 3:

The genotype frequencies of the studied ULK1 and PIK3CA gene SNPs in the cases and the healthy controls.

SNP ID	Model	Genotype	Control n (%)	Case n (%)	OR (95% CI)	p
ULK1 rs4964879	Codominant	AA GA GG	92 (44) 85 (40.7) 32 (15.3)	67 (32.4) 112 (54.1) 28 (13.5)	1.00 1.76 (1.15–2.70) 1.19 (0.65–2.16)	0.03
	Dominant	AA GA+GG	92 (44) 117 (56)	68 (31.9) 145 (68.1)	1.00 1.60 (1.07–2.40)	0.022
	Recessive	AA+GA GG	177 (84.7) 32 (15.3)	184 (86.4) 29 (13.6)	1.00 0.87 (0.50–1.51)	0.61
	Overdominant	AA+GG GA	124 (59.3) 85 (40.7)	97 (45.5) 116 (54.5)	1.00 1.68 (1.13–2.49)	0.0096
ULK1 rs9481	Codominant	AA AG GG	81 (38.8) 98 (46.9) 30 (14.3)	73 (34.3) 90 (42.2) 50 (23.5)	1.00 1.00 (0.65–1.54) 1.76 (1.01–3.09)	0.086
	Dominant	AA AG/GG	81 (38.8) 128 (61.2)	73 (34.3) 140 (65.7)	1.00 1.18 (0.79–1.76)	0.36
	Recessive	AA/AG GG	179 (85.7) 30 (14.3)	163 (76.5) 50 (23.5)	1.00 1.77 (1.06–2.94)	0.027
	Overdominant	AA/GG AG	111 (53.1) 98 (46.9)	123 (57.8) 90 (42.2)	1.00 0.83 (0.56–1.22)	0.34
PIK3CArs1607237	Codominant	CC CT TT	101 (48.6) 79 (38) 28 (13.5)	138 (64.3) 45 (22.6) 26 (13.1)	1.00 0.47 (0.30–0.73) 0.78 (0.43–1.42)	0.0039
	Dominant	CC CT/TT	101 (48.6) 107 (51.4)	128 (64.3) 71(35.7)	1.00 0.55 (0.37–0.82)	0.0031
	Recessive	CC/CT TT	180 (86.5) 28 (13.5)	173 (86.9) 26 (13.1)	1.00 1.01 (0.57–1.81)	0.97
	Overdominant	CC/TT CT	129 (62) 79 (38)	154 (77.4) 45 (22.6)	1.00 0.49 (0.32–0.76)	0.0013

DOI: 10.7717/peerj.12377/table-3

Table 4:

The correlation between the haplotypes of ULK1 and PIK3CA gene SNPs and the MPA susceptibility.

Gene	Haplotype	Case (n = 208)	Control (n = 211)	OR (95% CI)	p
ULK1	C-T-A-C-C-G	27.6 (6.7%)	27.1(6.5%)	1.039 (0.599∼1.799)	0.893
	G-G-G-G-G	80.8 (19.5%)	67.0(16%)	1.285 (0.897∼1.841)	0.171
	G-T-A-C-G-A	203.7 (49.2%)	234.5(56.1%)	0.749 (0.563∼0.997)	0.047
	G-T-G-C-G-A	13.9 (3.4%)	10.6 (2.5%)	1.343 (0.596∼3.024)	0.475
	G-T-G-C-G-G	26.8 (6.5%)	20.7 (4.9%)	1.340 (0.741∼2.422)	0.331
	G-T-G-T-C-G	30.8 (7.4%)	29.9 (7.1%)	1.054 (0.624∼1.780)	0.844
PIK3CA	C-G	291.5 (73.3%)	278.7(66.7%)	1.427 (1.050∼1.939)	0.023
	T-G	36.5 (8.8%)	68.3 (16.3%)	0.520 (0.339∼0.799)	0.0025
	T-T	62.5 (15.7%)	66.7 (16.0%)	0.993 (0.681∼1.446]	0.9688

DOI: 10.7717/peerj.12377/table-4

Interaction of gene alleles with clinical characteristics

Generalized multifactor dimensionality reduction (GMDR) was used to analyze the interaction between the alleles of the ULK1 gene (rs10902469, rs12303764, rs4964879, rs7300908, rs7138581, and rs9481) and PIK3CA gene (rs1607237 and rs9838117). The interaction showed that rs4964879 and rs1607237 were the best models for MPA prediction (cross-validation consistency: 10/10). The risk of MPA in the “high-risk” combination was 2.27 times that in the “low-risk combination” (Fig. 2), but a margin testing p value was observed (p = 0.0547).

Discussion

In this study, polymorphisms in the autophagy-related genes ULK1 and PIK3CA and their association with MPA were examined. The results showed that the ULK1 SNPs rs4964879 and rs9481 were risk factors for MPA, and PIK3CA rs1607237 was a protective factor for MPA.

Autophagy is a fundamental intracellular biological process of eukaryotic cells that is essential for the activation of innate and adaptive immune responses, including self-antigen presentation, phagocytosis, maintenance of lymphocyte homeostasis, and regulation of cytokine production (Ye, Zhou & Zhang, 2019). It is well established that the mammalian target of rapamycin (mTOR)/ULK1 pathway is one of the main regulators of autophagy. Inhibition of mTOR results in dephosphorylation of ULK1 and upregulates autophagy, and it is positively modulated through the PI3K/AKT pathway and negatively modulated by adenosine monophosphate-activated protein kinase (Mohamed et al., 2021). Increasing studies have demonstrated that autophagy is involved in the biology of neutrophils, which play a critical role in the acute injury of AAV by releasing proteolytic enzymes via degranulation, producing reactive oxygen species and extruding neutrophil extracellular traps (NETs) (Al-Hussain et al., 2017; Skendros, Mitroulis & Ritis, 2018). Sha et al. (2016) proved that autophagy activity is elevated in neutrophils treated with ANCAs, and the NET formation rate increases or decreases in neutrophils pretreated with an autophagy inducer or inhibitor, respectively. Tang et al. (2015) also demonstrated that NET formation is associated with autophagy-related signaling in human neutrophils with AAV.

In this study, six SNPs (rs10902469, rs12303764, rs4964879, rs7300908, rs7138581, and rs9481) in ULK1 between healthy controls and MPA patients were evaluated. Our initial single SNP analysis detected a significant difference in the genotypic distribution (rs4964879, A >G) between the two groups. Subsequently, rs4964879 (codominant, dominant and overdominant model) and rs9481 (recessive model) of the ULK1 gene were significantly associated with the risk of MPA. In addition, the association between ULK1 gene polymorphisms and MPA risk was influenced by age, sex and ethnicity. Our findings indicated that rs4964879 and rs9481 variations (A>G) in the ULK1 gene may be able to increase susceptibility to MPA.

ULK1, which is a serine/threonine protein kinase, plays a central role in initiating autophagy. It has been reported that the knockdown of ULK1 in HEK293 cells is sufficient to inhibit the autophagy response (Chan, Kir & Tooze, 2007). Mouse embryonic fibroblasts derived from ULK1^−/− and ULK2^−/− mice blocked autophagy during amino acid starvation (Cheong et al., 2011). As expected by the role of ULK1 kinase in autophagy initiation, genetic variation in ULK1 could result in autophagy disorder. David J. Horne et al. found that ULK1-deficient cells present decreased cytokine secretion and autophagy activity. The study was also the first to report that the rs12297124 minor allele of the ULK1 gene contributes to an 80% reduction in latent tuberculosis infection risk in Asian participants (Horne et al., 2016). The ULK1 SNPs rs4964879 and rs9481 reported in this study are located in intron and 3′UTR regions, respectively. Although introns are untranslated regions in mRNAs, mutations in introns may affect the binding of transcription factors and change the splicing modes or transcription of the ULK1 gene, ultimately altering the sequence of amino acids (Kawasaki et al., 2018). The 3′UTR plays an important role in mRNA transport, stability and posttranscriptional regulation. Trans-acting factors or microRNAs bind to cis-acting elements in the 3′UTR of the target transcript and regulate protein synthesis by affecting transcription factors. Sequence variations in mRNA introns or 3′UTR regions in ULK1 may cause abnormal expression of the gene (Zhang et al., 2019). Considering the role of ULK1 in the autophagy pathway, we speculate that ULK1 (rs4964879 and rs9481) variations may lead to abnormal expression of ULK1 and then initiate the autophagy response, eventually increasing the susceptibility to MPA.

In the present study, another autophagy-related gene, PIK3CA (rs1607237, C>T), showed significant differences in the allele frequency and genotypic distribution between the patients with MPA and the healthy controls. A subject with at least one T allele has approximately half the risk for MPA compared with a subject with a CC genotype (TT+CT vs. CC: OR 0.56, 95% CI [0.37–0.83]). Increasing findings confirm that polymorphisms in the PI3K/AKT signaling pathway are related to the regulation of cell proliferation, survival and death. Similar to the results of our study, a case-control study conducted by Xing et al. found that the PIK3CA polymorphism is a defense factor against follicular thyroid cancer (Xing et al., 2012). PIK3CA rs1607237 is also significantly associated with a small decrease in breast cancer risk (Stevens et al., 2011). SNP rs1607237 is in the intron of PIK3CA gene. Although no published literature has reported the feature of PIK3CA rs1607237, given the location of this SNP, we speculate that SNPs may affect the transcription of the PIK3CA gene by interrupting the process of translation and splicing. The PIK3CA mutation increases the expression of the p110 α catalytic subunit of PI3K and then activates AKT through the PI3K/AKT signaling pathway. As mentioned above, the PI3K/AKT pathway positively regulates the mTOR/ULK1 pathway, and the activation of AKT may decrease the autophagy response. However, further research will be needed to provide strong evidence for this speculation.

This study has several limitations, which should be mentioned. First, the number of participants was relatively small because of the low incidence rate of MPA, especially for subpopulations after stratified analysis, which may provide insufficient evidence to provide definitive conclusions. Second, some follow-up information, such as the curative effect of glucocorticoids and immunosuppressants, renal survival rate, relapse rate, and mortality, was lacking. Third, we did not perform studies to explore the molecular mechanisms to verify the association between gene polymorphisms reported in this study and MPA.

Conclusions

The present study indicated that the polymorphisms observed in ULK1 (rs4964879 and rs9481) and PIK3CA (rs1607237) were significantly associated with MPA risk in the Guangxi population. However, the molecular mechanisms are still unclear, and studies designed with larger samples and basic research are needed to confirm our conclusions and explore the mechanisms.

Supplemental Information