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Baker CR, Barilar I, de Araujo LS, Rimoin AW, Parker DM, Boyd R, Tobias JL, Moonan PK, Click ES, Finlay A, Oeltmann JE, Minin VN, Modongo C, Zetola NM, Niemann S, Shin SS. Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana. Emerg Infect Dis 2023; 29:977-987. [PMID: 37081530 PMCID: PMC10124643 DOI: 10.3201/eid2905.220796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.
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Jonathan J, Barakabitze AA. ML technologies for diagnosing and treatment of tuberculosis: a survey. HEALTH AND TECHNOLOGY 2023. [DOI: 10.1007/s12553-023-00727-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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Zhang TP, Li R, Wang LJ, Li HM. Impact of m6A demethylase (ALKBH5, FTO) genetic polymorphism and expression levels on the development of pulmonary tuberculosis. Front Cell Infect Microbiol 2022; 12:1074380. [PMID: 36619747 PMCID: PMC9817133 DOI: 10.3389/fcimb.2022.1074380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
Objective The m6A methylation was involved in the pathogenesis of pulmonary tuberculosis (PTB), and our study aimed to reveal the potential association of m6A demethylase (ALKBH5, FTO) genes variation, expression levels and PTB. Methods Eight SNPs (ALKBH5 gene rs8400, rs9913266, rs12936694, rs4925144 and FTO gene rs6499640, rs8047395, rs1121980, rs9939609) were selected for genotyping by SNPscan technique in 449 PTB patients and 463 healthy controls. Results The mRNA expression levels of ALKBH5, FTO were detected by qRT-PCR. There were no significant differences in genotype, allele distributions of all SNPs between PTB patients and healthy controls. Haplotype analysis demonstrated that the frequency of FTO gene GAAA haplotype was significantly reduced in PTB patients when compared to controls. ALKBH5 rs8400 AA genotype, A allele frequencies were associated with the decreased risk of sputum smear-positive, while AA genotype frequency was related to the increased risk of hypoproteinemia in PTB patients. In addition, rs9913266 variant was linked to the occurrence of drug-induced liver injury, sputum smear-positive, and rs4925144 variant was associated with leukopenia among PTB patients. In FTO gene, rs8047395 GG genotype and G allele frequencies were significantly higher in the PTB patients with drug resistance than that in the PTB patients without drug resistance. The ALKBH5, FTO expression levels were significantly decreased in PTB patients in comparison to controls. Moreover, ALKBH5 level was increased in PTB patients with drug resistance, and FTO level was decreased in PTB patients with sputum smear-positive. Conclusion FTO gene polymorphisms might be associated with PTB susceptibility, and ALKBH5, FTO levels were decreased in PTB patients, suggesting that these m6A demethylase played important roles in PTB.
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Affiliation(s)
- Tian-Ping Zhang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Rui Li
- Department of Nosocomial Infection Management, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Li-Jun Wang
- Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Hong-Miao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China,*Correspondence: Hong-Miao Li,
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Sailo CV, Tonsing MV, Sanga Z, Chhakchhuak Z, Kharkongor F, Fela V, Chhakchhuak L, Ralte L, Nemi L, Senthil Kumar N. Risk factors of tuberculosis in Mizoram: First report of the possible role of water source. Indian J Tuberc 2022; 69:675-681. [PMID: 36460407 DOI: 10.1016/j.ijtb.2022.03.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 03/03/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Various risk factors of tuberculosis have been studied across the globe, but these may be altered over time and can be specific to geographical regions and there is not much information available from Northeastern region of India. This study aims to investigate the various risk factors of tuberculosis and analyze the presence of any less-established risk factors. METHODS A total of 400 TB cases and 840 healthy controls were interviewed from December 2017 - June 2020. Logistic regression model was used to analyze associated risk factors. Patients were categorized into pulmonary and extrapulmonary TB. RESULTS Clinical presentation such as fever, cough, weight loss, chest pain and night sweats were more prominent among pulmonary TB patients. The most common mode of diagnosis among pulmonary and extrapulmonary TB were GeneXpert and X-ray, respectively. Tuberculosis was found to be strongly prevalent among patients from lower socio-economic status, less educated, unemployed and improper housing condition. Other risk factors associated were alcohol consumption, neighbours with TB, travel history, no BCG vaccine, mass gathering, and non-ideal weight. An interesting less-established risk factor that demands attention is the source of water supply (p-0.017, OR-2.313, CI: 1.160-4.613), which was significant in this study. CONCLUSION Our data suggests that apart from all the well-established risk factors for TB, water supply might play a crucial role towards the transmission of TB, since proper hospital waste water treatment is yet to be adopted in Mizoram, Northeast India. From a public health standpoint, this highlights the need for further research in this area.
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Affiliation(s)
| | | | - Zothan Sanga
- Department of Health and Family Welfare, Directorate of Health Services, Aizawl, 796009, Mizoram, India
| | | | - Febiola Kharkongor
- Department of Health and Family Welfare, Directorate of Health Services, Aizawl, 796009, Mizoram, India
| | - Vanlal Fela
- Department of Health and Family Welfare, Directorate of Health Services, Aizawl, 796009, Mizoram, India
| | - Lily Chhakchhuak
- National Health Mission, Directorate of Health Services, Aizawl, 796009, Mizoram, India
| | - Lalremruata Ralte
- Department of Microbiology and Pathology, Synod Hospital, Durtlang, 796025, Mizoram, India
| | - Lalnun Nemi
- Department of Microbiology and Pathology, Synod Hospital, Durtlang, 796025, Mizoram, India
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Association between TAP gene polymorphisms and tuberculosis susceptibility in a Han Chinese population in Guangdong. Mol Genet Genomics 2022; 297:779-790. [PMID: 35325275 PMCID: PMC8943507 DOI: 10.1007/s00438-022-01885-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 03/08/2022] [Indexed: 12/02/2022]
Abstract
Tuberculosis (TB) is an important public health problem. Studies indicated that TAP plays a key role in the presentation and transport of antigenic peptides during anti-M.tb infection. Given the important biological role of the TAP gene involved in anti-M.tb infection, a family-based case–control study including 133 tuberculosis patients, 107 healthy household contacts, and 173 healthy controls was conducted to assess the association between TAP gene polymorphisms and TB susceptibility. The basic information of subjects and their blood samples were collected. Four SNPs including rs1135216, rs1057141, rs241447, and rs3819721 were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP). Our results suggested that BMI, residence, bedroom crowding, indoor humidity, fitness activities, history of smoking, and TB exposure history were associated with the occurrence of tuberculosis (P < 0.05). A significant association was observed between the TAP1 rs1135216 CT/CC genotype and increased TB risk, and the ORs were 2.56 (95% CI 1.31–4.99) and 6.73 (95% CI 1.33–34.02), respectively. TAP2 rs3819721 GG genotype carriers also showed an increased risk of TB when compared TB patients to healthy household contacts. Haplotype analysis revealed that the haplotype CT at rs1057141 and rs1135216 (OR = 11.34, 95% CI 1.49–86.56; OR = 7.45, 95% CI 1.43–38.76), as well as TA at rs241447 and rs3819721 (OR = 2.20, 95% CI 1.07–4.56) had a significantly increased risk of TB. The genetic risk scores (GRS) analysis of the four loci indicated that the risk of tuberculosis increased with increasing GRS scores in TB vs HHC (Ptrend = 0.010) and in TB vs HC (Ptrend = 0.001). In conclusion, our findings suggested that the SNPs of rs1135216 and rs3819721 were associated with TB susceptibility among the tuberculosis-prone families in the Chinese Han population and the risk of developing tuberculosis increases with the number of risk alleles, which could help identify high-risk groups in time and take scientific preventive measures. Further cohort studies with large samples are needed to validate the role of TAP gene variants on TB susceptibility.
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Lash RR, Moonan PK, Byers BL, Bonacci RA, Bonner KE, Donahue M, Donovan CV, Grome HN, Janssen JM, Magleby R, McLaughlin HP, Miller JS, Pratt CQ, Steinberg J, Varela K, Anschuetz GL, Cieslak PR, Fialkowski V, Fleischauer AT, Goddard C, Johnson SJ, Morris M, Moses J, Newman A, Prinzing L, Sulka AC, Va P, Willis M, Oeltmann JE. COVID-19 Case Investigation and Contact Tracing in the US, 2020. JAMA Netw Open 2021; 4:e2115850. [PMID: 34081135 PMCID: PMC8176334 DOI: 10.1001/jamanetworkopen.2021.15850] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 04/20/2021] [Indexed: 01/17/2023] Open
Abstract
Importance Contact tracing is a multistep process to limit SARS-CoV-2 transmission. Gaps in the process result in missed opportunities to prevent COVID-19. Objective To quantify proportions of cases and their contacts reached by public health authorities and the amount of time needed to reach them and to compare the risk of a positive COVID-19 test result between contacts and the general public during 4-week assessment periods. Design, Setting, and Participants This cross-sectional study took place at 13 health departments and 1 Indian Health Service Unit in 11 states and 1 tribal nation. Participants included all individuals with laboratory-confirmed COVID-19 and their named contacts. Local COVID-19 surveillance data were used to determine the numbers of persons reported to have laboratory-confirmed COVID-19 who were interviewed and named contacts between June and October 2020. Main Outcomes and Measures For contacts, the numbers who were identified, notified of their exposure, and agreed to monitoring were calculated. The median time from index case specimen collection to contact notification was calculated, as were numbers of named contacts subsequently notified of their exposure and monitored. The prevalence of a positive SARS-CoV-2 test among named and tested contacts was compared with that jurisdiction's general population during the same 4 weeks. Results The total number of cases reported was 74 185. Of these, 43 931 (59%) were interviewed, and 24 705 (33%) named any contacts. Among the 74 839 named contacts, 53 314 (71%) were notified of their exposure, and 34 345 (46%) agreed to monitoring. A mean of 0.7 contacts were reached by telephone by public health authorities, and only 0.5 contacts per case were monitored. In general, health departments reporting large case counts during the assessment (≥5000) conducted smaller proportions of case interviews and contact notifications. In 9 locations, the median time from specimen collection to contact notification was 6 days or less. In 6 of 8 locations with population comparison data, positive test prevalence was higher among named contacts than the general population. Conclusions and Relevance In this cross-sectional study of US local COVID-19 surveillance data, testing named contacts was a high-yield activity for case finding. However, this assessment suggests that contact tracing had suboptimal impact on SARS-CoV-2 transmission, largely because 2 of 3 cases were either not reached for interview or named no contacts when interviewed. These findings are relevant to decisions regarding the allocation of public health resources among the various prevention strategies and for the prioritization of case investigations and contact tracing efforts.
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Affiliation(s)
- R. Ryan Lash
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Patrick K. Moonan
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brittany L. Byers
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Robert A. Bonacci
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Kimberly E. Bonner
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- Public Health Division, Oregon Health Authority, Portland
| | - Matthew Donahue
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- Nebraska Department of Health and Human Services, Lincoln
| | - Catherine V. Donovan
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- North Carolina Department of Health and Human Services, Raleigh
| | - Heather N. Grome
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- Tennessee Department of Health, Nashville
| | - Julia M. Janssen
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Reed Magleby
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- New Jersey Department of Health, Trenton
| | - Heather P. McLaughlin
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - James S. Miller
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- Washington State Department of Health, Tumwater
| | - Caroline Q. Pratt
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jonathan Steinberg
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
- South Dakota State Health Department, Sioux Falls
| | - Kate Varela
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
| | | | | | | | - Aaron T. Fleischauer
- North Carolina Department of Health and Human Services, Raleigh
- Career Epidemiology Field Officer Program, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Clay Goddard
- Springfield-Greene County Health Department, Springfield, Missouri
| | | | | | - Jill Moses
- Chinle Indian Health Service Unit, Chinle, Arizona
| | - Allison Newman
- Nebraska Department of Health and Human Services, Lincoln
| | | | - Alana C. Sulka
- Gwinnett, Newton, Rockdale Counties Health Departments, Lawrenceville, Georgia
| | - Puthiery Va
- Chinle Indian Health Service Unit, Chinle, Arizona
| | | | - John E. Oeltmann
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
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