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Mokrousov I, Badleeva M, Mudarisova R, Kozhevnikov V, Markhaev A, Guntupova A, Vyazovaya A. Increasing circulation of multi-drug resistant tuberculosis strains in Buryatia, high-burden and ethnically diverse region in the Russian Far East. Tuberculosis (Edinb) 2024; 149:102555. [PMID: 39241696 DOI: 10.1016/j.tube.2024.102555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 08/23/2024] [Accepted: 08/27/2024] [Indexed: 09/09/2024]
Abstract
Buryatia is a multidrug-resistant tuberculosis (MDR-TB) high-burden region in the Russian Far East with ethnically diverse population (30 % Mongoloid Buryats and 65 % Russians). Two hundred M. tuberculosis strains from newly-diagnosed patients were subjected to phenotypic testing and genotyping. The Beijing genotype was more prevalent among Russians than Buryats (68 % vs 53 %; P = 0.055). European non-Beijing genotypes (LAM, Ural, Haarlem) were double more prevalent in Buryats vs Russians (39.2 % vs 20.5 %; P = 0.01). Higher prevalence of Beijing among former prison inmates (79 % vs 61 % in other patients, P = 0.1) suggests its increased transmissibility. The Russian epidemic cluster B0/W148 was in 9.5 %, double smaller than elsewhere in Siberia. The hypervirulent Beijing 14717-15-cluster was endemic in Buryatia but paradoxically enough, it was more frequently isolated from Russians than Buryats (9.1 % vs 3.9 %; P = 0.2). Beijing subtypes B0/W148, CAO, and 14717-15 were associated with poly/multi-drug resistance (P = 0.01-0.0001). HIV coinfection was more frequent in Russians than in Buryats: 35/141 (24.8 %) vs 5/51 (9.8 %), P = 0.03. To conclude, M. tuberculosis population structure in Buryatia retained its singularities compared to other parts of Russia and remains strikingly different from the neighboring Mongolia. A circulation of strongly MDR-associated Beijing subtypes and drug-resistant non-Beijing strains highlights a risk of their broader dissemination.
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Affiliation(s)
- Igor Mokrousov
- Laboratory of Molecular Epidemiology and Evolutionary Genetics, St. Petersburg Pasteur Institute, St. Petersburg, Russia.
| | - Maria Badleeva
- Department of Infectious Diseases, Dorji Banzarov Buryat State University, Ulan-Ude, Buryatia, Russia
| | - Regina Mudarisova
- Laboratory of Molecular Epidemiology and Evolutionary Genetics, St. Petersburg Pasteur Institute, St. Petersburg, Russia
| | - Valery Kozhevnikov
- G.D. Dugarova Clinical Anti-tuberculosis Dispensary, Ulan-Ude, Buryatia, Russia
| | - Andrey Markhaev
- Department of Infectious Diseases, Dorji Banzarov Buryat State University, Ulan-Ude, Buryatia, Russia
| | | | - Anna Vyazovaya
- Laboratory of Molecular Epidemiology and Evolutionary Genetics, St. Petersburg Pasteur Institute, St. Petersburg, Russia.
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Aravindhan V, Yuvaraj S. Immune-endocrine network in diabetes-tuberculosis nexus: does latent tuberculosis infection confer protection against meta-inflammation and insulin resistance? Front Endocrinol (Lausanne) 2024; 15:1303338. [PMID: 38327565 PMCID: PMC10848915 DOI: 10.3389/fendo.2024.1303338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/02/2024] [Indexed: 02/09/2024] Open
Abstract
Tuberculosis patients with diabetes, have higher sputum bacillary load, delayed sputum conversion, higher rates of drug resistance, higher lung cavitary involvement and extra-pulmonary TB infection, which is called as "Diabetes-Tuberculosis Nexus". However, recently we have shown a reciprocal relationship between latent tuberculosis infection and insulin resistance, which has not been reported before. In this review, we would first discuss about the immune-endocrine network, which operates during pre-diabetes and incipient diabetes and how it confers protection against LTBI. The ability of IR to augment anti-TB immunity and the immunomodulatory effect of LTBI to quench IR were discussed, under IR-LTB antagonism. The ability of diabetes to impair anti-TB immunity and ability of active TB to worsen glycemic control, were discussed under "Diabetes-Tuberculosis Synergy". The concept of "Fighter Genes" and how they confer protection against TB but susceptibility to IR was elaborated. Finally, we conclude with an evolutionary perspective about how IR and LTBI co-evolved in endemic zones, and have explained the molecular basis of "IR-LTB" Antagonism" and "DM-TB Synergy", from an evolutionary perspective.
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Affiliation(s)
- Vivekanandhan Aravindhan
- Department of Genetics, Dr Arcot Lakshmanasamy Mudaliyar Post Graduate Institute of Basic Medical Sciences (Dr ALM PG IBMS), University of Madras, Chennai, India
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Oyageshio OP, Myrick JW, Saayman J, van der Westhuizen L, Al-Hindi D, Reynolds AW, Zaitlen N, Uren C, Möller M, Henn BM. Strong Effect of Demographic Changes on Tuberculosis Susceptibility in South Africa. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.02.23297990. [PMID: 37961495 PMCID: PMC10635255 DOI: 10.1101/2023.11.02.23297990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
South Africa is among the world's top eight TB burden countries, and despite a focus on HIV-TB co-infection, most of the population living with TB are not HIV co-infected. The disease is endemic across the country with 80-90% exposure by adulthood. We investigated epidemiological risk factors for tuberculosis (TB) in the Northern Cape Province, South Africa: an understudied TB endemic region with extreme TB incidence (645/100,000) and the lowest provincial population density. We leveraged the population's high TB incidence and community transmission to design a case-control study with population-based controls, reflecting similar mechanisms of exposure between the groups. We recruited 1,126 participants with suspected TB from 12 community health clinics, and generated a cohort of 878 individuals (cases =374, controls =504) after implementing our enrollment criteria. All participants were GeneXpert Ultra tested for active TB by a local clinic. We assessed important risk factors for active TB using logistic regression and random forest modeling. Additionally, a subset of individuals were genotyped to determine genome-wide ancestry components. Male gender had the strongest effect on TB risk (OR: 2.87 [95% CI: 2.1-3.8]); smoking and alcohol consumption did not significantly increase TB risk. We identified two interactions: age by socioeconomic status (SES) and birthplace by residence locality on TB risk (OR = 3.05, p = 0.016) - where rural birthplace but town residence was the highest risk category. Finally, participants had a majority Khoe-San ancestry, typically greater than 50%. Epidemiological risk factors for this cohort differ from other global populations. The significant interaction effects reflect rapid changes in SES and mobility over recent generations and strongly impact TB risk in the Northern Cape of South Africa. Our models show that such risk factors combined explain 16% of the variance (r2) in case/control status.
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Affiliation(s)
- Oshiomah P. Oyageshio
- Center for Population Biology, University of California, Davis, Davis, CA 95616, USA
| | - Justin W. Myrick
- UC Davis Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Jamie Saayman
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Lena van der Westhuizen
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Dana Al-Hindi
- Department of Anthropology, University of California, Davis, Davis, CA 95616, USA
| | | | - Noah Zaitlen
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Caitlin Uren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Marlo Möller
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Brenna M. Henn
- Center for Population Biology, University of California, Davis, Davis, CA 95616, USA
- UC Davis Genome Center, University of California, Davis, Davis, CA 95616, USA
- Department of Anthropology, University of California, Davis, Davis, CA 95616, USA
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Yu J, Liu M, Mijiti X, Liu H, Wang Q, Yin C, Anwaierjiang A, Xu M, Li M, Deng L, Xiao H, Zhao X, Wan K, Li G, Yuan X. Association of Single-Nucleotide Polymorphisms in the VDR Gene with Tuberculosis and Infection of Beijing Genotype Mycobacterium tuberculosis. Infect Drug Resist 2023; 16:3157-3169. [PMID: 37235072 PMCID: PMC10208660 DOI: 10.2147/idr.s407595] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 05/03/2023] [Indexed: 05/28/2023] Open
Abstract
Background The aim of the present study was to investigate the association between vitamin D receptor (VDR) gene polymorphism and tuberculosis susceptibility, as well as the potential interaction of host genetic factors with the heterogeneity of Mycobacterium tuberculosis in the population from Xinjiang, China. Methods From January 2019 to January 2020, we enrolled 221 tuberculosis patients as the case group and 363 staff with no clinical symptoms as the control group from four designated tuberculosis hospitals in southern Xinjiang, China. The polymorphisms of Fok I, Taq I, Apa I, Bsm I, rs3847987 and rs739837 in the VDR were detected by sequencing. M. tuberculosis isolates were collected from the case group and identified as Beijing or non-Beijing lineage by multiplex PCR. Propensity score (PS), univariate analysis and multivariable logistic regression models were used to perform the analysis. Results Our results showed that the allele and genotype frequencies of Fok I, Taq I, Apa I, Bsm I, rs3847987 and rs739837 in VDR were not correlated with tuberculosis susceptibility or lineages of M. tuberculosis. Two out of six loci of the VDR gene formed one haplotype block, and none of the haplotypes was found to correlate with tuberculosis susceptibility or lineages of M. tuberculosis infected. Conclusion Polymorphisms in the VDR gene may not indicate susceptibility to tuberculosis. There was also no evidence on the interaction between the VDR gene of host and the lineages of M. tuberculosis in the population from Xinjiang, China. Further studies are nonetheless required to prove our conclusions.
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Affiliation(s)
- Jinjie Yu
- School of Public Health, University of South China, Hengyang, 421001, People’s Republic of China
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Mengwen Liu
- School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, 830011, People’s Republic of China
| | - Xiaokaiti Mijiti
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830049, People’s Republic of China
| | - Haican Liu
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Quan Wang
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830049, People’s Republic of China
| | - Chunjie Yin
- School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, 830011, People’s Republic of China
| | | | - Miao Xu
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830049, People’s Republic of China
| | - Machao Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Lele Deng
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Hui Xiao
- School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, 830011, People’s Republic of China
| | - Xiuqin Zhao
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Kanglin Wan
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Guilian Li
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People’s Republic of China
| | - Xiuqin Yuan
- School of Public Health, University of South China, Hengyang, 421001, People’s Republic of China
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