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Li P, Wang Q, He Y, Yang C, Zhang Z, Liu Z, Liu B, Yin L, Cui Y, Hu P, Liu Y, Zheng P, Wang W, Qu L, Sun C, Guan S, Feng L, Chen L. Booster vaccination is required to elicit and maintain COVID-19 vaccine-induced immunity in SIV-infected macaques. Emerg Microbes Infect 2023; 12:e2136538. [PMID: 36239345 PMCID: PMC9980405 DOI: 10.1080/22221751.2022.2136538] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
ABSTRACTProlonged infection and possible evolution of SARS-CoV-2 in patients living with uncontrolled HIV-1 infection highlight the importance of an effective vaccination regimen, yet the immunogenicity of COVID-19 vaccines and predictive immune biomarkers have not been well investigated. Herein, we report that the magnitude and persistence of antibody and cell-mediated immunity (CMI) elicited by an Ad5-vectored COVID-19 vaccine are impaired in SIV-infected macaques with high viral loads (> 105 genome copies per ml plasma, SIVhi) but not in macaques with low viral loads (< 105, SIVlow). After a second vaccination, the immune responses are robustly enhanced in all uninfected and SIVlow macaques. These responses also show a moderate increase in 70% SIVhi macaques but decline sharply soon after. Further analysis reveals that decreased antibody and CMI responses are associated with reduced circulating follicular helper T cell (TFH) counts and aberrant CD4/CD8 ratios, respectively, indicating that dysregulation of CD4+ T cells by SIV infection impairs the COVID-19 vaccine-induced immunity. Ad5-vectored COVID-19 vaccine shows no impact on SIV loads or SIV-specific CMI responses. Our study underscores the necessity of frequent booster vaccinations in HIV-infected patients and provides indicative biomarkers for predicting vaccination effectiveness in these patients.
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Affiliation(s)
- Pingchao Li
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China, Pingchao Li State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China; Liqiang Feng
| | - Qian Wang
- State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
| | - Yizi He
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Chenchen Yang
- Guangzhou nBiomed Ltd., Guangzhou, People’s Republic of China
| | - Zhengyuan Zhang
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Zijian Liu
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Bo Liu
- Guangzhou nBiomed Ltd., Guangzhou, People’s Republic of China
| | - Li Yin
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Yilan Cui
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Peiyu Hu
- Guangzhou Laboratory & Bioland Laboratory, Guangzhou, People’s Republic of China
| | - Yichu Liu
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China
| | - Pingqian Zheng
- Guangzhou Laboratory & Bioland Laboratory, Guangzhou, People’s Republic of China
| | - Wei Wang
- Guangzhou Laboratory & Bioland Laboratory, Guangzhou, People’s Republic of China
| | - Linbing Qu
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China
| | - Caijun Sun
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China
| | - Suhua Guan
- Guangzhou nBiomed Ltd., Guangzhou, People’s Republic of China
| | - Liqiang Feng
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,Guangzhou Laboratory & Bioland Laboratory, Guangzhou, People’s Republic of China
| | - Ling Chen
- State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China,State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China,Guangzhou Laboratory & Bioland Laboratory, Guangzhou, People’s Republic of China,Ling Chen State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou, People’s Republic of China
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Ndikabona G, Alege JB, Kirirabwa NS, Kimuli D. Unsuppressed viral load after intensive adherence counselling in rural eastern Uganda; a case of Kamuli district, Uganda. BMC Public Health 2021; 21:2294. [PMID: 34922502 PMCID: PMC8684255 DOI: 10.1186/s12889-021-12366-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 12/01/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The East Central (EC) region of Uganda has the least viral suppression rate despite having a relatively low prevalence of human immunodeficiency virus (HIV). Although the viral suppression rate in Kamuli district is higher than that observed in some of the districts in the region, the district has one of the largest populations of people living with HIV (PLHIV). We sought to examine the factors associated with viral suppression after the provision of intensive adherence counselling (IAC) among PLHIV in the district. METHODS We reviewed records of PLHIV and used them to construct a retrospective cohort of patients that started and completed IAC during January - December 2019 at three high volume HIV treatment facilities in Kamuli district. We also conducted key informant interviews of focal persons at the study sites. We summarized the data descriptively, tested differences in the outcome (viral suppression after IAC) using chi-square and t-tests, and established independently associated factors using log-binomial regression analysis with robust standard errors at 5% statistical significance level using STATA version 15. RESULTS We reviewed 283 records of PLHIV. The mean age of the participants was 35.06 (SD 18.36) years. The majority of the participants were female (56.89%, 161/283). The viral suppression rate after IAC was 74.20% (210/283). The most frequent barriers to ART adherence reported were forgetfulness 166 (58.66%) and changes in the daily routine 130 (45.94). At multivariable analysis, participants that had a pre-IAC viral load that was greater than 2000 copies/ml [adjusted Prevalence Risk Ratio (aPRR)= 0.81 (0.70 - 0.93), p=0.002] and those that had a previous history of viral load un-suppression [aPRR= 0.79 (0.66 - 0.94), p=0.007] were less likely to achieve a suppressed viral load after IAC. ART drug shortages were rare, ART clinic working hours were convenient for clients and ART clinic staff received training in IAC. CONCLUSION Despite the consistency in drug availability, counselling training, flexible and frequent ART clinic days, the viral suppression rate after IAC did not meet recommended targets. A high viral load before IAC and a viral rebound were independently associated with having an unsuppressed viral load after IAC. IAC alone may not be enough to achieve viral suppression among PLHIV. To improve viral suppression rates after IAC, other complementary services should be paired with IAC.
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Affiliation(s)
- Geoffrey Ndikabona
- Institute of Public Health, Clarke International University, P.O. Box 7782, Uganda, Kampala
| | - John Bosco Alege
- Institute of Public Health, Clarke International University, P.O. Box 7782, Uganda, Kampala
| | | | - Derrick Kimuli
- Directorate of Socio-Economic Surveys, Uganda Bureau of Statistics, Kampala, Uganda, P.O. Box 7186, Kampala, Uganda.
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Vasylyeva TI, Smyrnov P, Strathdee S, Friedman SR. Challenges posed by COVID-19 to people who inject drugs and lessons from other outbreaks. J Int AIDS Soc 2020; 23:e25583. [PMID: 32697423 PMCID: PMC7375066 DOI: 10.1002/jia2.25583] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 06/19/2020] [Accepted: 06/26/2020] [Indexed: 11/07/2022] Open
Abstract
INTRODUCTION In light of the COVID-19 pandemic, considerable effort is going into identifying and protecting those at risk. Criminalization, stigmatization and the psychological, physical, behavioural and economic consequences of substance use make people who inject drugs (PWID) extremely vulnerable to many infectious diseases. While relationships between drug use and blood-borne and sexually transmitted infections are well studied, less attention has been paid to other infectious disease outbreaks among PWID. DISCUSSION COVID-19 is likely to disproportionally affect PWID due to a high prevalence of comorbidities that make the disease more severe, unsanitary and overcrowded living conditions, stigmatization, common incarceration, homelessness and difficulties in adhering to quarantine, social distancing or self-isolation mandates. The COVID-19 pandemic also jeopardizes essential for PWID services, such as needle exchange or substitution therapy programmes, which can be affected both in a short- and a long-term perspective. Importantly, there is substantial evidence of other infectious disease outbreaks in PWID that were associated with factors that enable COVID-19 transmission, such as poor hygiene, overcrowded living conditions and communal ways of using drugs. CONCLUSIONS The COVID-19 crisis might increase risks of homelessnes, overdoses and unsafe injecting and sexual practices for PWID. In order to address existing inequalities, consultations with PWID advocacy groups are vital when designing inclusive health response to the COVID-19 pandemic.
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Vasylyeva TI, Zarebski A, Smyrnov P, Williams LD, Korobchuk A, Liulchuk M, Zadorozhna V, Nikolopoulos G, Paraskevis D, Schneider J, Skaathun B, Hatzakis A, Pybus OG, Friedman SR. Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention. Viruses 2020; 12:E469. [PMID: 32326127 PMCID: PMC7232463 DOI: 10.3390/v12040469] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 04/02/2020] [Accepted: 04/15/2020] [Indexed: 01/01/2023] Open
Abstract
Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.
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Affiliation(s)
- Tetyana I. Vasylyeva
- Department of Zoology, University of Oxford, OX1 3SY Oxford, UK
- New College, University of Oxford, OX1 3BN Oxford, UK
| | | | | | - Leslie D. Williams
- Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL 60612, USA
| | | | - Mariia Liulchuk
- State Institution “The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine”, Kyiv 03038, Ukraine
| | - Viktoriia Zadorozhna
- State Institution “The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine”, Kyiv 03038, Ukraine
| | | | - Dimitrios Paraskevis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece
| | - John Schneider
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Britt Skaathun
- Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
| | - Angelos Hatzakis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, OX1 3SY Oxford, UK
| | - Samuel R. Friedman
- Department of Population Health, New York University, New York, NY 10003, USA
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