Short Communication: The Association of WNT16 Polymorphisms with the CD4 + T Cell Count in the HIV-Infected Population

To date, HIV remains one of the major threats to world's public health. ¹ The duration of AIDS development among HIV-1–infected people varies greatly. It is well known that host genetic factors play a crucial role in regulating the rate of progression from HIV infection to AIDS. ²

Wnt proteins are a family of secretory glycoproteins that participate in many cellular processes, such as cell proliferation, differentiation, apoptosis, and cell fate determination. ^3,4 Wnt proteins interact with several frizzled receptors to activate β-catenin–dependent canonical or β-catenin–independent noncanonical signaling pathways. Wnt/β-catenin pathway plays an important role in controlling CD4⁺ T cell survival and T cell lineage fate determination. ^5,6 WNT16 protein is one of the 19 members of the Wnt family in human beings, with WNT16a and WNT16b two isoforms. A recent study has reported that inhibition of Wnt-16 expression may lead to a decrease in the proliferation of T cell lines (Jurkat) and promote apoptosis. ⁷ Therefore, it is reasonable to assume that WNT16 contributes to the proliferation of T lymphocytes.

Many studies have been conducted to assess the relationship between host genetic polymorphism and HIV infection or disease progression. In this study, we explored the possible association of WNT16 intron variant rs3801385 and missense variant rs2707466 (Thr > Ile) with the CD4⁺ T cell count in the context of HIV infection to identify new evidence of the relationship between host genetics and HIV infection.

A total of 93 HIV-1–infected patients were analyzed in this study. They were all diagnosed with HIV infections for the first time, with the HIV-1 confirmatory test positive, the hepatitis B or C virus negative, and the absence of other immune diseases concurrently. None of the patients underwent any antiretroviral treatment. The detection of the CD4⁺ T cell count and plasma HIV-1 RNA was carried out at the Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University. According to the test results of the CD4⁺ T cell count, the patients were separated into two groups: the CD4⁺ T cell count ≥200/mm³ group (range, 231–893 cells/mm³; median, 391 cells/mm³; n = 60) and the <200/mm³ group (range, 39–175 cells/mm³; median, 113 cells/mm³; n = 33). The median plasma HIV-1 RNA levels in the two groups were 2.76 × 10⁴ copies/mL and 9.36 × 10⁴ copies/mL, respectively. A total of 76 healthy individuals from the same hospital health examination center were randomly selected as the control group. The selection criteria for the control subjects were that the subjects be free of any evidence of HIV infection or other severe diseases. All participants were Han Chinese from Guangxi province, and other demographic characteristics are shown in Supplementary Table S1. The study protocol was approved by the ethics committee of the First Affiliated Hospital of Guangxi Medical University, and all of the subjects provided written informed consent.

DNA was extracted from EDTA anticoagulated whole blood using the Ezup Column Blood Genomic DNA Purification Kit (Sangon Biotech, Shanghai, China). The forward and reverse primers used in the polymerase chain reaction (PCR) were rs3801385-F 5′-AAATCGTCAGGGCTAGCTGT-3′ and R 5′-GCAAAAGGTGTCCTGCCCATT-3′, rs2707466-F 5′-ATTCTCTGCCTTGTGTCCCT-3′, and R 5′-CTGACATCAACTTG GCGACA-3′. Agarose gel electrophoresis was used to verify whether the PCR products were the desired target fragment (459 bp for rs3801385 and 293 bp for rs2707466) (Supplementary Fig. S1A, B). Then, the samples were directly sequenced by ABI-PRISM 3730 and analyzed by Chromas software (version 1.21). The genotypes of rs3801385 and rs2707466 are AA/GG/AG and GG/AA/GA, respectively (Supplementary Fig. S1C, D).

A goodness-of-fit χ ² test was used to assess the genotype distribution of the control group. The genotype frequencies of rs3801385 and rs2707466 for the control subjects both agreed with the Hardy–Weinberg equilibrium (both p > .05). As given in Table 1, the frequencies of the WNT16 rs2707466 GA genotype and A allele in CD4⁺ T cells ≥200/mm³ group were higher than those in the control group (p < .05). Binary logistic regression analysis, adjusted by age and gender, revealed that rs2707466 A allele and combined GA+AA genotypes were associated with a CD4⁺ T cell count maintained ≥200/mm³ in the context of an HIV infection (p = .026 and p = .044). Conversely, negative results were found in the CD4⁺ T cells <200/mm³ group (Table 1). In addition, no significant association between the WNT16 rs3801385 polymorphism and the CD4⁺ T cell count in HIV-infected patients was observed in any genetic model (Supplementary Table S2).

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Table 1.

Logistic Regression Analysis of the Relationship Between WNT16 rs2707466 Polymorphism and CD4⁺ T Cell Count in HIV-Infected Patients and Stratification Study Based on Viral Load

Model	Genotypes	Controls	CD4+ T cells <200/mm3			CD4+ T cells ≥200/mm3
		n = 76 (%)	n = 33 (%)	OR (95% CI) a,c	p a,c	n = 60 (%)	OR (95% CI) b,c	p b,c
Co-dominant	GG	61 (80.3)	24 (72.7)	1ref		37 (61.7)	1ref
	GA	14 (18.4)	8 (24.2)	1.85 (0.66–5.22)	.245	19 (31.7)	2.07 (0.87–4.90)	.098
	AA	1 (1.3)	1 (3.1)	2.08 (0.12–36.77)	.617	4 (6.6)	5.36 (0.56–51.42)	.145
Dominant	GA+AA	15 (19.7)	9 (27.3)	1.87 (0.69–5.08)	.220	23 (38.3)	2.33 (1.03–5.29)	.044
Allele	G	136 (89.4)	56 (84.9)	1ref		93 (77.5)	1ref
	A	16 (10.6)	10 (15.1)	1.60 (0.66–3.87)	.301	27 (22.5)	2.22 (1.10–4.48)	.026
<20 copies/mL
Allele	A vs. G			1.55 (0.31–7.81)	.559		4.02 (1.50–10.74)	.006
Dominant	GA+AA vs. GG			1.30 (0.23–7.43)	.770		3.79 (1.15–12.49)	.028
≥20 copies/mL
Allele	A vs. G			2.07 (0.70–6.11)	.190		1.46 (0.27–3.23)	.283
Dominant	GA+AA vs. GG			2.03 (0.68–6.08)	.205		1.86 (0.76–4.55)	.175

a

CD4⁺ cells <200/mm³ group versus control group.

b

CD4⁺ cells ≥200/mm³ group versus control group.

c

Adjusted by age and gender; dominant model: GA+AA versus GG.

CI, confidence interval; OR, odds ratio; SNP, single nucleotide polymorphism.

Next, we divided the patients into subgroups based on their viral load. In patients with a viral load of <20 copies/mL, there was still a strong positive relationship between the rs2707466 A allele and the CD4⁺ T cells ≥200/mm³ (p = .006), which also occurred in the combined GA+AA genotypes (p = .028) (Table 1).

As shown in the study, HIV-1 patients carrying the rs2707466 A allele were more inclined to maintain CD4⁺ T cells in excess of 200/mm³ compared with other genotypes. It suggests that the rs2707466 A allele may be a natural advantage for people in fighting AIDS. Niu et al. ⁸ predicted that WNT16 rs2707466 might cause a deleterious effect on WNT16 protein as a phosphorylation-related single nucleotide polymorphism (SNP). This indicated that rs2707466 may play a role by affecting the expression or activity of WNT16 protein. However, there was no significant association between the rs2707466 AA genotype and the CD4⁺ T cell count, and the main reason may be that there were too few people with AA genotypes in the study to compare. In addition, the different genotypes of rs3801385 site were not significantly associated with CD4⁺ T cell count in HIV patients, probably because rs3801385 as an intron variant of WNT16 did not participate in the regulation of the WNT16 transcription and translation.

Similar to other members of the Wnt family, WNT16 is involved in several processes of tumorigenesis and cell development. ^9,10 Furthermore, lymphocytes, especially T cells, in normal individuals have been verified to have higher WNT16 expression relative to other blood cells. ¹¹ WNT16b was initially recognized as an oncogene, upregulated in pre-B acute lymphoblastoid leukemia and promotes B lymphocyte survival by activating the Wnt/β-catenin signaling pathway. ¹² Qian et al. ⁷ found that MicroRNA-374b inhibits the proliferation of T-LBL cells by inhibiting AKT1 and WNT16b. Besides, Binet et al. ¹³ demonstrated that WNT16b activates the PI3K/Akt signaling, whereas PI3K/AKT signaling plays a positive role in T cell proliferation and apoptosis inhibition. ¹⁴ Based on our results, we are inclined to believe that mutation of WNT16 gene rs2707466 may suppress CD4⁺ T cells apoptosis by activating the canonical pathway or the PI3K/Akt pathway. Certainly, further research is needed to elucidate the mechanisms actually involved.

Taken together, our findings demonstrate that WNT16 rs2707466 A allele may have a protective effect on the CD4⁺ T cell count in HIV-1–infected patients, especially in individuals with low HIV-1 viral loads (<20 copies/mL). Furthermore, the mechanism of WNT16 gene polymorphisms in maintaining CD4⁺ T cell count in HIV-infected individuals deserves further study.