Your browser doesn't support javascript.
loading
Strong Effect of Demographic Changes on Tuberculosis Susceptibility in South Africa.
Oyageshio, Oshiomah P; Myrick, Justin W; Saayman, Jamie; van der Westhuizen, Lena; Al-Hindi, Dana; Reynolds, Austin W; Zaitlen, Noah; Uren, Caitlin; Möller, Marlo; Henn, Brenna M.
Afiliação
  • Oyageshio OP; Center for Population Biology, University of California, Davis, Davis, CA 95616, USA.
  • Myrick JW; UC Davis Genome Center, University of California, Davis, Davis, CA 95616, USA.
  • Saayman J; 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.
  • van der Westhuizen L; 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.
  • Al-Hindi D; Department of Anthropology, University of California, Davis, Davis, CA 95616, USA.
  • Reynolds AW; Department of Anthropology, Baylor University, Waco, TX 76798, USA.
  • Zaitlen N; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
  • Uren C; 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.
  • Möller M; Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa.
  • Henn BM; 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.
medRxiv ; 2023 Nov 03.
Article em En | MEDLINE | ID: mdl-37961495
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article