
==== Front
BMC Infect Dis
BMC Infect Dis
BMC Infectious Diseases
1471-2334
BioMed Central London

36670363
7982
10.1186/s12879-023-07982-x
Research
Humoral immune response to inactivated COVID-19 vaccination at the 3rd month among people living with HIV
Wu Songjie 12
Zou Shi 23
Ming Fangzhao 4
Wu Mengmeng 23
Guo Wei 56
Xing Zhongyuan 7
Zhang Zhiyue 7
Liu Jinli 3
Tang Weiming Weiming_tang@med.unc.edu

89
Liang Ke keliang@whu.edu.cn

12310
1 https://ror.org/01v5mqw79 grid.413247.7 0000 0004 1808 0969 Department of Nosocomial Infection Management, Zhongnan Hospital of Wuhan University, Hubei, China
2 https://ror.org/02drdmm93 grid.506261.6 0000 0001 0706 7839 Wuhan Research Center for Infectious Diseases and Cancer, Chinese Academy of Medical Sciences, Wuhan, China
3 https://ror.org/01v5mqw79 grid.413247.7 0000 0004 1808 0969 Department of Infectious Diseases, Zhongnan Hospital of Wuhan University, Wuhan, 430071 Hubei China
4 https://ror.org/05t45gr77 grid.508004.9 0000 0004 1787 6607 Wuchang District Center for Disease Control and Prevention, Wuhan, Hubei China
5 https://ror.org/01v5mqw79 grid.413247.7 0000 0004 1808 0969 Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan, China
6 https://ror.org/033vjfk17 grid.49470.3e 0000 0001 2331 6153 Department of Pathology, School of Basic Medical Sciences, Wuhan University, Wuhan, China
7 https://ror.org/033vjfk17 grid.49470.3e 0000 0001 2331 6153 School of Basic Medical Sciences, Wuhan University, Wuhan, China
8 https://ror.org/045kpgw45 grid.413405.7 0000 0004 1808 0686 Guangdong No. 2 Provincial People’s Hospital, Guangzhou, China
9 The University of North Carolina at Chapel Hill Project-China, Guangzhou, 510095 China
10 Hubei Engineering Center for Infectious Disease Prevention, Control and Treatment, Wuhan, China
20 1 2023
20 1 2023
2023
23 3412 6 2022
3 1 2023
© The Author(s) 2023
2023
https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Background

Research on the immune response to inactivated COVID-19 vaccination among people living with HIV (PLWH) is limited, especially among those with low CD4+ T lymphocyte (CD4 cell) count. This prospective cohort study aimed to assess the humoral immune response to inactivated COVID-19 vaccination among PLWH compared to HIV negative controls (HNCs) and to determine the impact of CD4 cell count on vaccine response among PLWH.

Methods

The neutralizing antibodies (nAbs) and the specific IgM and IgG-binding antibody responses to the inactivated COVID-19 vaccine at the third month after the second dose of inactivated COVID-19 vaccination were measured among 138 PLWH and 35 HNCs. Multivariable logistic regression and multiple linear regression models were conducted to identify factors associated with the seroconversion rate of antibodies and the magnitude of anti-SARS-CoV-2 antibody titers, respectively.

Results

At the end of the third month after two doses of vaccination, the seroconversion rates of IgG were comparable between PLWH (44.9%; 95% CI 36.5–53.3%) and HNCs (60.0%; 95% CI 42.9–77.1%), respectively. The median titers and seroconversion rate of nAbs among PLWH were 0.57 (IQR: 0.30–1.11) log10 BAU/mL and 29.0% (95% CI 21.3–36.8%), respectively, both lower than those in HNCs (P < 0.05). After adjusting for age, sex, comorbidities, and CD4 cell count, the titers and seroconversion rate of nAbs were comparable between PLWH and HNCs (P > 0.05). Multivariable regression analyses showed that CD4 cell count < 200/μL was independently associated with lower titers and seroconversion rate of nAbs among PLWH (P < 0.05). A positive correlation was observed between the CD4 cell count and nAbs titers in PLWH (Spearman's ρ = 0.25, P = 0.0034).

Conclusion

Our study concluded that the immune response to inactivated COVID-19 vaccination among PLWH was independently associated with CD4 cell count, PLWH with lower CD4 cell count showed a weaker humoral immune response, especially those with CD4 cell count < 200/μL. This finding suggests that expanding COVID-19 vaccination coverage among PLWH is impendency. In addition, aggressive ART should be carried out for PLWH, especially for those with low CD4 cell count, to improve the immune response to vaccines.

Keywords

COVID-19
Inactivated vaccine
Humoral immunity
PLWH
CD4 cell count
National Nature Science Foundation of China81903371 Tang Weiming NIMHR34MH119963 Tang Weiming the National Science and Technology Major Project2018ZX10101-001-001-003 Tang Weiming Special Found on Prevention and Control of New Coronary Pneumonia in Guangdong Universities2020KZDZX1047 Tang Weiming Medical Science and Technology Innovation Platform Support Project of Zhongnan Hospital, Wuhan UniversityPTXM2020008 Liang Ke Science and Technology Innovation Cultivation Fund of Zhongnan Hospital, Wuhan Universitycxpy2017043 Liang Ke Medical Science Advancement Program (Basic Medical Sciences) of Wuhan UniversityTFJC2018004 Liang Ke the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences2020-PT320-004 Liang Ke issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2023
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pmcIntroduction

Recently, the ongoing pandemic of coronavirus disease 2019 (COVID-19) has posed a serious threat to global public health and economic development [1]. While it is noteworthy that SARS-CoV-2 infection has brought a big challenge to people living with HIV (PLWH). Studies have reported that PLWH had increased risks of more severe disease and deaths from COVID-19 [2, 3], possibly as a result of immunosuppression, higher rates of multimorbidity, unsuppressed HIV viral load (HIV-VL), and other determinants of health [4–7].

Nevertheless, limited information is available about the immune response to COVID-19 immunization in PLWH, especially in those with low CD4+ T lymphocyte (CD4 cell) count. Furthermore, the emerging immunogenicity data in PLWH were mostly focused on mRNA COVID-19 vaccines [8–11] or adenovirus vector-based vaccines [12–14], while very few studies focused on the immune response to inactivated COVID-19 vaccines. Two studies that reported the effect of inactivated COVID-19 vaccine on PLWH both had very small sample sizes [15, 16].

WIBP-CorV is an inactivated COVID-19 vaccine. An isolated SARS-CoV-2 strain (WIV‐04) was cultivated in Vero cells, chemically inactivated by β-propiolactone, then mixed with an aluminium-based adjuvant [17, 18]. Phase 1 and 2 trials revealed that WIBP-CorV had a low rate of side effects and good immunogenicity [17]. The interim analysis of phase 3 clinical trials showed that the vaccine is 72.8% effective against the symptomatic COVID-19 cases and 100% against severe disease [19]. WIBP-CorV vaccine was one of the most commonly used vaccine in China.

Previously, another published study of our team based on PLWH and HIV negative controls (HNCs) who finished 70 days’ follow-up showed that early humoral immune response to the inactivated COVID-19 vaccine was weaker and delayed among the PLWH than that among HNCs. But it has not discussed the risk factors associated with the humoral immune response in PLWH and HNCs because of limited sample size [20]. This study aimed to fill this gap by comparing the humoral immune response induced by the inactivated COVID-19 vaccine between PLWH and HNCs, and determining the impact of CD4 cell count on vaccine response in PLWH.

Materials and methods

Study participants and design

The study was conducted from March to October 2021. A total of 138 PLWH and 35 HNCs who received two doses of inactivated COVID-19 vaccine (Sinopharm, WIBP-CorV, 4 µg/0.5 mL, WIV04 strain, Wuhan Institute of Biological Products Co. Ltd) with an interval of 28 days were enrolled in our study. The inclusion criteria for PLWH included the following: (1) age ≥ 18 years old; (2) confirmed HIV infection by HIV-1/2 Western blot assay. Exclusion criteria included the following: (1) presence of severe hearing loss, impaired vision, or intellectual disability observed by the interviewers; or (2) a history of SARS-CoV-2 infection (via serological and nucleic acid test), major psychiatric illness (schizophrenia or bipolar disorder) or neurocognitive impairment; the HNCs shared the first inclusion criteria and both exclusion criteria with PLWH. HNCs were recruited from the physical examination center in Zhongnan Hospital of Wuhan University. Written informed consent was obtained from each participant before screening for eligibility. 138 PLWH and 35 HNCs completed immunizations with inactivated COVID-19 vaccine at respective community hospitals and scheduled visits within the prescribed time. Blood samples were collected at baseline (before the first dose vaccination) and the 3rd month after the second dose of COVID-19 vaccination. Data on demographic information, including age, sex, and comorbidities (i.e., hypertension, diabetes mellitus, hyperlipidemia, cancer, chronic cardiovascular and lung, liver, or kidney diseases) were collected from all participants through an electronic questionnaire before vaccination. Clinical and laboratory data regarding the HIV status of PLWH were obtained from the China National HIV/AIDS Comprehensive Response Information Management System (CRIMS). The CD4 cell count of the PLWH and HNCs were tested with the blood samples at baseline.

Immunogenicity assessments

The primary humoral immunogenicity outcomes included the neutralizing antibodies (nAbs) and the specific IgM and IgG-binding antibody response to the COVID-19 vaccine, measured at baseline and 3rd months after the participants were fully present vacillated with inactivated COVID-19 vaccination. An in-house SARS-CoV-2 nAbs assay kit by surrogate virus neutralization test (Livzon Diagnostics Inc., Zhuhai, China) was used to determine the serum titers of nAbs against the spike protein receptor-binding domain (RBD) according to the manufacturers' instructions. In brief, SARS-CoV-2 surrogate virus neutralization test detects total immunodominant neutralizing antibodies targeting the viral spike (S) protein receptor-binding domain in an isotype- and species-independent manner. This rapid test is based on antibody-mediated blockade of the interaction between the angiotensin-converting enzyme 2 (ACE2) receptor protein and the receptor-binding domain [21], a positive response is defined as ≥ 10BAU/mL. The semi-quantitative of total specific IgM and IgG antibodies were detected using an in-house-developed ELISA kits (Livzon Diagnostics Inc.,Zhuhai, China), which used the recombinant nucleocapsid (N) and RBD antigen of SARS-CoV-2 as coating antigen, following the instruction manual. Positive responses of IgM and IgG were defined as ≥ 0.15 EU/mL and 0.18 EU/mL, respectively. The qualitative of specific IgM or IgG antibodies was detected using an in-house-developed colloidal gold kit (Livzon Diagnostics Inc.,Zhuhai, China), following the instruction manual. We defined seroconversion of antibodies as a change from baseline seronegative to seropositive.

Statistical analysis

Categorical variables were presented as n (%) and compared using the Chi-square test or Fisher's exact test. Continuous variables with normal distribution were presented as mean (standard deviation [SD]) and compared using t-test or ANOVA analysis, while continuous variables with abnormal distribution were expressed as median (interquartile range [IQR]) and compared using Mann–Whitney U test. Multivariable logistic regression models with 2-sided 95% confidence intervals were conducted to identify factors associated with the seroconversion rate of antibodies. Multiple linear regression was employed to identify factors associated with the magnitude of anti-SARS-CoV-2 antibody titers. Analyses were conducted using SPSS software, version 26.0 (IBM SPSS Inc), and GraphPad Prism 8 for Mac OS X (GraphPad Software, San Diego, CA, USA). A two-sided p < 0.05 was considered statistically significant.

Results

Study participants

Characteristics of the 138 PLWH and 35 HNCs were shown in Table 1. PLWH and HNCs were similar in age and comorbidities but differed in proportion of male (P < 0.001). The median (IQR) age of PLWH was 38 (31–49) years old, and 88.4% were males. 91.3% of the PLWH were receiving ART and 107 (77.5%) had a HIV VL < 50 copies /mL. The CD4 cell count in PLWH was significantly lower than that in HNCs [495(IQR: 320–646) vs. 666 (IQR: 534–800)/μL, P < 0.001].Table 1 Characteristics of the PLWH (n = 138) and HNCs (n = 35) in Wuhan, China, 2021

Characteristics	PLWH (n = 138)	HNCs (n = 35)	Statistics	P	
Age in years, median (IQR)	38 (31–49)	33 (29–44)	2.56	0.08	
Men, No. (%)	16 (88.4)	17 (48.6)	28.06	< 0.001	
Comorbidities (%)	17 (12.3)	2 (5.7)	–	0.26	
CD4 cell count/μL, median (IQR)	495 (320–646)	666 (534–800)	4.12	< 0.001	
CD4 cell count (/μL)					
 < 200	18	0			
 200–500	52	4			
 ≥ 500	68	31	18.04	< 0.001	
Receiving ART, n (%)	126 (91.3)	–			
ART regimens					
No	12 (8.7)	–			
NNRTIs (NVP/EFV)	102 (73.9)	–			
INSTIs (EVG/DTG)	14 (10.1)	–			
PIs (LPV/r)	10 (7.3)	–			
HIV VL < 50 copies/mL	107 (77.5)				
IgM, n (%)	5 (3.6)	1 (2.9)	–*	1.00	
IgG,n (%)	62 (44.9)	21 (60.0)		0.11	
nAbs,n (%)	40 (29.0)	17 (48.6)	4.85	0.03	
IgM titers, GMT (95% CI)	0.016 (0.014–0.020)	0.018 (0.013–0.024)	1.18	0.24	
IgG titers, GMT (95% CI)	0.10 (0.074–0.13)	0.21 (0.14–0.32)	1.97	0.049	
Log10 nAbs titers, median (IQR)	0.57 (0.30–1.11)	0.91 (0.64–1.26)	2.46	0.01	
NNRTIs: nonnucleoside reverse transcriptase inhibitors; INSTIs: integrase inhibitors; PIs: protein inhibitors; NVP: nevirapine; EFV: efavirenz; EVG: elvitegravir; DTG: dolutegravir; LPV/r: lopinavir/ritonavir

*No statistics are computed because Fisher exact method was used

Binding-antibody responses to COVID-19 vaccination

At the end of third month after two doses of vaccination, the seroconversion rates of IgM in PLWH and HNCs were 3.6% (95% CI 0.5–6.8%) and 2.9% (95% CI 0–8.7%), respectively, while no significant difference between the two groups was observed. No significant difference was also found in seroconversion rates of IgG between PLWH (44.9%; 95% CI 36.5–53.3%) and HNCs (60.0%; 95% CI 42.9–77.1%). After adjusting for age, sex, comorbidities, and CD4 cell count, IgG seroconversion rates were comparable between PLWH and HNCs.

For the difference of IgG titers between PLWH and HNCs, univariate analysis showed that the IgG titers among PLWH was significantly lower than that among HNCs, but no significantly difference was found after adjusting for age, sex, comorbidities, and CD4 cell count.

Neutralizing antibody responses to COVID-19 vaccination among PLWH and HNCs

At the end of third month after two doses of vaccination, the seroconversion rate of nAbs among PLWH was 29.0% (95% CI 21.3–36.7%), which was significantly lower than that among HNCs (48.6%; 95% CI 31.2–66.0%)]. The nAbs titers among PLWH [0.57 (IQR: 0.30–1.11) log10 BAU/mL] was also significantly lower than that among HNCs [(median 0.91; IQR, 0.64–1.26) log10 BAU/mL] (Fig. 1).Fig. 1 nAbs titers in different groups (PLWH were divided into three groups: CD4 cell count < 200/μL, CD4 cell count between 200 and 500/μL and CD4 cell count ≥ 500/μL). P < 0.05, nAbs titers in PLWH were significantly different from HNCs; P < 0.01, nAbs titers in PLWH with CD4 cell count < 200/μL were differ from those in PLWH with CD4 cell count ≥ 500/μL; P > 0.05, there were no significantly difference between the groups; P-values were computed using the Mann–Whitney U-test

In multivariable logistic regression analysis, the people with CD4 cell count < 200/μL tended to have a lower seroconversion rate of nAbs (OR: 0.09; 95% CI 0.01–0.74; P = 0.03), as compared to those with CD4 cell count ≥ 500 /μL. Age, sex, comorbidities and HIV infection were not significantly associated with the seroconversion rate of nAbs (Table 2).Table 2 Factors associated with seroconversion rates of nAbs among PLWH and HNCs in Wuhan, China, 2021 (N = 173)

Variables	Adjusted OR (95% CI)	P	
Age	0.98 (0.96–1.01)	0.28	
Sex			
 Male	Ref		
 Female	2.19 (0.87–5.51)	0.10	
CD4 cell count (/μL)			
 ≥ 500	Ref		
 200–500	0.68 (0.32–1.45)	0.32	
 < 200	0.89 (0.01–0.74)	0.03	
Comorbidities			
 No	Ref		
 Yes	0.95 (0.26–3.46)	0.94	
HIV infection			
 No	Ref		
 Yes	0.86 (0.35–2.15)	0.75	

We further transformed the nAbs titers (log10) and performed multivariable linear regression analysis. The results determined that nAbs titers in participants with CD4 cell count < 200/μL were − 0.21 log10 lower than those with CD4 cell count ≥ 500/μL (P = 0.012). Age, sex, comorbidities, and HIV infection were not significantly associated with the nAbs titers (Table 3).Table 3 Factors associated with nAbs titers among PLWH and HNCs in Wuhan, China, 2021 (N = 173)

Variables	Estimate	95% CI	P	
CD4 cell count in 200–500 /μL(versus CD4 ≥ 500/μL)	− 0.07	− 0.27 to 0.12	0.43	
CD4 cell count < 200 /μL(versus CD4 ≥ 500/μL)	− 0.21	− 0.69 to − 0.09	0.01	
Age	− 0.14	− 0.01 to 0.001	0.07	
Comorbidities (Yes vs No)	0.03	− 0.23 to 0.34	0.71	
HIV infection (Yes vs No)	− 0.07	− 0.33 to 0.15	0.45	
Sex (Female vs Male)	0.09	− 0.11 to 0.36	0.29	

Then we analyzed the association between IgG and nAbs, the result showed that there were positive correlations between IgG and nABs titers in PLWH (ρ = 0.843, p < 0.001) and HNCs (ρ = 0.766, p < 0.001).

Neutralizing antibody responses to COVID-19 vaccination among PLWH

At the end of third month after two doses of vaccination, the seroconversion rates of nAbs were 5.6% (95% CI 0–17.3%) in the group with CD4 cell count < 200/μL, 25.0% (95% CI 12.8–37.2%) in the group with CD4 cell count between 200 and 500/μL, and 61.8% (95% CI 49.9–73.6%) in the group with CD4 cell count ≥ 500/μL, respectively. In the multivariable model, participants with CD4 cell count < 200/μL tend to have a lower nAbs seroconversion rate than those with CD4 cell count ≥ 500/μL (P = 0.03) (Table 4).Table 4 Factors associated with seroconversion rate of nAbs among PLWH in Wuhan, China, 2021 (N = 138)

Variables	Adjusted OR (95% CI)	P	
Age	0.99 (0.96–1.03)	0.62	
Sex			
 Male	Ref		
 Female	1.57 (0.41–6.01)	0.51	
CD4 cell count (/μL)			
 ≥ 500	Ref		
 200–500	0.51 (0.21–1.19)	0.12	
 < 200	0.07 (0.007–0.77)	0.03	
Comorbidities			
 No	Ref		
 Yes	0.73(0.14–3.62)	0.70	
HIV VL (copies/mL)			
 < 50	Ref		
 ≥ 50	2.51 (0.81–7.81)	0.11	
ART			
 No	Ref		
 Yes	2.40 (0.20–28.63)	0.49	

At the end of third month after two doses of vaccination, the median nAbs titers were 0.30 (IQR: 0.30–0.59) log10 BAU/mL in the group with CD4 cell count < 200/μL, 0.61 (IQR: 0.30–1.14) log10 BAU/mL in the group with CD4 cell count between 200 and 500/μL and 0.81 (IQR: 0.35–1.24) log10 BAU/mL in the group with CD4 cell count ≥ 500/μL, respectively. The nAbs titers were significantly different in three CD4 groups (P = 0.009), while participants with lower CD4 cell count < 200 /μL tend to have lower nAbs titers (Fig. 1). Multivariable linear regression analysis confirmed this finding (Table 5). There was no significant association between age, sex, comorbidities, HIV-VL, ART, and nAbs titers (P > 0.05).Table 5 Factors associated with nAbs titers among PLWH in Wuhan, China, 2021 (N = 138)

Variables	Estimate	95% CI	P	
CD4 cell count in 200–500/μL (versus CD4 ≥ 500/μL)	− 0.11	− 0.32 to 0.08	0.24	
CD4 cell count < 200/μL (versus CD4 ≥ 500/μL)	− 0.22	− 0.71 to − 0.02	0.04	
Sex (Female vs Male)	− 0.04	− 0.38 to 0.23	0.63	
Age	− 0.14	− 0.01 to 0.001	0.11	
Comorbidities (Yes vs No)	− 0.01	− 0.35 to 0.32	0.94	
ART (Yes vs No)	0.07	− 0.26 to 0.55	0.48	
HIV VL (≥ 50 vs < 50)	0.16	− 0.05 to 0.47	0.11	

The correlation analysis between CD4 cell count and nAbs titers showed a positive correlation in PLWH (Spearman's ρ = 0.25, P = 0.0034), while no significant correlation between CD4 count and nAbs titers was observed in HNCs (Spearman's ρ = 0.03, P = 0.86) (Fig. 2).Fig. 2 Correlation between CD4 cell count and nAbs titers at the 3rd months after two doses of inactivated COVID-19 vaccination among PLWH and HNCs

Discussion

Understanding the humoral immune response induced by the inactivated COVID-19 vaccine and the impact of CD4 cell count on vaccine response in PLWH were essential in decision-making regarding future disease control and revaccination strategies. It is important to ensure adequate protection against infection in the vulnerable population, especially to prevent the emerging new variants. This prospective cohort study extends the existing literatures [8–16] by providing more comprehensive evidence to assess the inactivated COVID-19 vaccine response among PLWH.

We found that PLWH and HNCs had a similar humoral immune response to the inactivated COVID-19 vaccine at the 3rd month after two doses of inactivated COVID-19 vaccination. Even though nAbs titers and seroconversion rate of nAbs in PLWH were both lower than that in HNCs, after adjusting for potential confounders, the differences disappeared. These findings are consistent with the results of other studies conducted in South Africa and UK, which suggested that the immune responses produced by the adenovirus vector-based COVID-19 vaccine among PLWH are similar to those among HNCs [12, 13]. Other studies about the immune response to mRNA COVID-19 vaccine among PLWH also reported similar humoral immune response to the healthy controls [8]. The results indicate that PLWH should complete both doses of inactivated COVID-19 vaccine to achieve good protection. Studies have shown that two doses of inactivated CoronaVac vaccines offer high levels of protection against severe disease and death among all age group [22].

Several studies have shown that PLWH have lower responses to some types of vaccine, including hepatitis A, hepatitis B, and influenza vaccine. These responses are dependent on the level of CD4 cell count [23–25]. CD4 cell is pivotal in orchestrating both the humoral and cellular immune responses to vaccination and has an essential impact on antibody production [26]. Some studies also suggested that PLWH with low CD4 cell count had a poor response to the COVID-19 vaccine while PLWH with CD4 cell count in a healthy range mounted equivalent vaccine responses to those in HIV-negative people [27, 28]. Our study found a statistically lower titer and seroconversion rate of nAbs among PLWH with the CD4 cell count < 200 μL (versus the group CD4 ≥ 500/μL). We also found a positive correlation between CD4 cell count and nAbs titers in PLWH and CD4 cell count < 200/μL independently predicted lower nAbs titers. The results indicate that PLWH, especially those with CD4 cell count < 200/μL were still relatively vulnerable even after two doses of inactivated COVID-19 vaccination. A study on the infection forms of SARS-CoV-2 infection among PLWH showed that PLWH were more likely to be an asymptomatic carrier [29]. Prolonged SARS-CoV-2 infection in advanced PLWH with profound immunosuppression or without ART would drive SARS-CoV-2 virus evolution [30], which may be the reason that 'omicron' emerged. We should expand COVID-19 vaccination coverage and promote the uptake among the lower- and middle-income countries where the COVID-19 vaccination rates are still low [31], and especially among PLWH. Furthermore, we should strengthen the appropriate ART for PLWH, especially for those with low CD4 cell count, to increase the CD4 cell count and strengthen their immune response level to vaccines and achieve longer duration of vaccines. This is not just to prevent PLWH from SARS-CoV-2 infection but to prevent the emergence of new variants.

This study has several limitations. First, the sample size of HNCs was relatively small. Studies with larger sample size will be more conductive to identify individuals who are particularly vulnerable to the impact of SARS-CoV-2 infection and develop targeted vaccination interventions. Second, imbalance existed in the sex distribution of PLWH, which may lead to some bias in our results. However, a previous study found the responses to inactivated COVID-19 vaccination had no significant differences between male and female, which may mitigate some of the sex imbalance in this study [19]. Third, the T-cell responses against the inactivated COVID-19 vaccines weren’t investigated in our study. Long-term follow-up for PLWH with inactivated COVID-19 vaccination will be performed in our further study, and the durability and quality of humoral and cellular responses of inactivated COVID-19 vaccines will be evaluated.

In conclusion, our study indicated that PLWH with lower CD4 cell count showed a weaker humoral immune response to inactivated COVID-19 vaccination, especially those with CD4 cell count < 200 /μL. Additional measures against COVID-19 are needed for PLWH who have low CD4 cell count.

Abbreviations

PLWH People living with HIV

SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2

COVID-19 Coronavirus disease 2019

HNCs HIV negative controls

nAbs The neutralizing antibodies

CRIMS China National HIV/AIDS Comprehensive Response Information Management System

RBD Spike protein receptor-binding domain

ACE2 Angiotensin-converting enzyme 2

SD Standard deviation

IQR Interquartile range

NNRTIs Nonnucleoside reverse transcriptase inhibitors

INSTIs Integrase inhibitors

PIs Protein inhibitors

NVP Nevirapine

EFV Efavirenz

EVG Elvitegravir

DTG Dolutegravir

LPV/r Lopinavir/ritonavir

Acknowledgements

Not applicable.

Author contributions

KL and WT participated in the inception of the idea of this manuscript with lead roles in conducting the study; SW, SZ and FM involved in the data analysis and drafting of the manuscript; SW, SZ and FM involved in data collection and interpretation; MW, WG, JL, ZX and ZZ participated in discussion section. All authors read and approved the final manuscript.

Funding

This work was supported by the National Nature Science Foundation of China (81903371), NIMH (R34MH119963), the National Science and Technology Major Project (2018ZX10101-001-001-003), Special Found on Prevention and Control of New Coronary Pneumonia in Guangdong Universities (2020KZDZX1047), Medical Science and Technology Innovation Platform Support Project of Zhongnan Hospital, Wuhan University (PTXM2020008), Science and Technology Innovation Cultivation Fund of Zhongnan Hospital, Wuhan University (cxpy2017043), Medical Science Advancement Program (Basic Medical Sciences) of Wuhan University (TFJC2018004) and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2020-PT320-004).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was reviewed and approved by the Research and Ethics Committee of Zhongnan Hospital (2020079K-1). All the procedures were performed in accordance with the Declaration of Helsinki, and the patient's confidentiality was maintained throughout the investigation. All individuals provided their written informed consent to participate in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no conflict of interest.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Songjie Wu, Shi Zou and Fangzhao Ming contributed equally to this work

Change history

9/16/2024

A Correction to this paper has been published: 10.1186/s12879-024-09913-w
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