Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database
Abstract Background The Center for Personalized Precision Medicine of Tuberculosis (cPMTb) was constructed to develop personalized pharmacotherapeutic systems for tuberculosis (TB). This study aimed to introduce the cPMTb cohort and compare the distinct characteristics of patients with TB, non-tuber...
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| Format: | Article |
| Language: | English |
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BMC
2023-11-01
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| Series: | BMC Pulmonary Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12890-023-02646-7 |
| _version_ | 1797454091848253440 |
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| author | Woo Jung Seo Hyeon-Kyoung Koo Ji Yeon Kang Jieun Kang So Hee Park Hyung Koo Kang Hye Kyeong Park Sung-Soon Lee Sangbong Choi Tae Won Jang Kyeong-Cheol Shin Jee Youn Oh Joon Young Choi Jinsoo Min Young-Kyung Choi Jae-Gook Shin Yong-Soon Cho |
| author_facet | Woo Jung Seo Hyeon-Kyoung Koo Ji Yeon Kang Jieun Kang So Hee Park Hyung Koo Kang Hye Kyeong Park Sung-Soon Lee Sangbong Choi Tae Won Jang Kyeong-Cheol Shin Jee Youn Oh Joon Young Choi Jinsoo Min Young-Kyung Choi Jae-Gook Shin Yong-Soon Cho |
| author_sort | Woo Jung Seo |
| collection | DOAJ |
| description | Abstract Background The Center for Personalized Precision Medicine of Tuberculosis (cPMTb) was constructed to develop personalized pharmacotherapeutic systems for tuberculosis (TB). This study aimed to introduce the cPMTb cohort and compare the distinct characteristics of patients with TB, non-tuberculosis mycobacterium (NTM) infection, or latent TB infection (LTBI). We also determined the prevalence and specific traits of polymorphisms in N-acetyltransferase-2 (NAT2) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) phenotypes using this prospective multinational cohort. Methods Until August 2021, 964, 167, and 95 patients with TB, NTM infection, and LTBI, respectively, were included. Clinical, laboratory, and radiographic data were collected. NAT2 and SLCO1B1 phenotypes were classified by genomic DNA analysis. Results Patients with TB were older, had lower body mass index (BMI), higher diabetes rate, and higher male proportion than patients with LTBI. Patients with NTM infection were older, had lower BMI, lower diabetes rate, higher previous TB history, and higher female proportion than patients with TB. Patients with TB had the lowest albumin levels, and the prevalence of the rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 39.2%, 48.1%, and 12.7%, respectively. The prevalence of rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 42.0%, 44.6%, and 13.3% for NTM infection, and 42.5%, 48.3%, and 9.1% for LTBI, respectively, which did not differ significantly from TB. The prevalence of the normal, intermediate, and lower transporter SLCO1B1 phenotypes in TB, NTM, and LTBI did not differ significantly; 74.9%, 22.7%, and 2.4% in TB; 72.0%, 26.1%, and 1.9% in NTM; and 80.7%, 19.3%, and 0% in LTBI, respectively. Conclusions Understanding disease characteristics and identifying pharmacokinetic traits are fundamental steps in optimizing treatment. Further longitudinal data are required for personalized precision medicine. Trial registration This study registered ClinicalTrials.gov NO. NCT05280886. |
| first_indexed | 2024-03-09T15:31:17Z |
| format | Article |
| id | doaj.art-82790218805f4197af0a89a93df1938a |
| institution | Directory Open Access Journal |
| issn | 1471-2466 |
| language | English |
| last_indexed | 2024-03-09T15:31:17Z |
| publishDate | 2023-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pulmonary Medicine |
| spelling | doaj.art-82790218805f4197af0a89a93df1938a2023-11-26T12:12:46ZengBMCBMC Pulmonary Medicine1471-24662023-11-0123111010.1186/s12890-023-02646-7Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort databaseWoo Jung Seo0Hyeon-Kyoung Koo1Ji Yeon Kang2Jieun Kang3So Hee Park4Hyung Koo Kang5Hye Kyeong Park6Sung-Soon Lee7Sangbong Choi8Tae Won Jang9Kyeong-Cheol Shin10Jee Youn Oh11Joon Young Choi12Jinsoo Min13Young-Kyung Choi14Jae-Gook Shin15Yong-Soon Cho16Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of MedicineDivision of Pulmonary, Department of Internal Medicine, Kosin University College of Medicine, Kosin University Gospel HospitalDivision of Pulmonology, Allergy and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Yeungnam University, Yeungman University Medical CenterDivision of Pulmonology, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of MedicineDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Incheon St. Mary’s Hospital, The Catholic University of KoreaDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of KoreaCenter for Personalized Precision Medicine of Tuberculosis (cPMTb), Inje University College of MedicineCenter for Personalized Precision Medicine of Tuberculosis (cPMTb), Inje University College of MedicineCenter for Personalized Precision Medicine of Tuberculosis (cPMTb), Inje University College of MedicineAbstract Background The Center for Personalized Precision Medicine of Tuberculosis (cPMTb) was constructed to develop personalized pharmacotherapeutic systems for tuberculosis (TB). This study aimed to introduce the cPMTb cohort and compare the distinct characteristics of patients with TB, non-tuberculosis mycobacterium (NTM) infection, or latent TB infection (LTBI). We also determined the prevalence and specific traits of polymorphisms in N-acetyltransferase-2 (NAT2) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) phenotypes using this prospective multinational cohort. Methods Until August 2021, 964, 167, and 95 patients with TB, NTM infection, and LTBI, respectively, were included. Clinical, laboratory, and radiographic data were collected. NAT2 and SLCO1B1 phenotypes were classified by genomic DNA analysis. Results Patients with TB were older, had lower body mass index (BMI), higher diabetes rate, and higher male proportion than patients with LTBI. Patients with NTM infection were older, had lower BMI, lower diabetes rate, higher previous TB history, and higher female proportion than patients with TB. Patients with TB had the lowest albumin levels, and the prevalence of the rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 39.2%, 48.1%, and 12.7%, respectively. The prevalence of rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 42.0%, 44.6%, and 13.3% for NTM infection, and 42.5%, 48.3%, and 9.1% for LTBI, respectively, which did not differ significantly from TB. The prevalence of the normal, intermediate, and lower transporter SLCO1B1 phenotypes in TB, NTM, and LTBI did not differ significantly; 74.9%, 22.7%, and 2.4% in TB; 72.0%, 26.1%, and 1.9% in NTM; and 80.7%, 19.3%, and 0% in LTBI, respectively. Conclusions Understanding disease characteristics and identifying pharmacokinetic traits are fundamental steps in optimizing treatment. Further longitudinal data are required for personalized precision medicine. Trial registration This study registered ClinicalTrials.gov NO. NCT05280886.https://doi.org/10.1186/s12890-023-02646-7TuberculosisNon-tuberculosis mycobacteriumN-Acetyltransferase-2Solute carrier organic anion transporter family member 1B1The Center for Personalized Precision Medicine of Tuberculosis |
| spellingShingle | Woo Jung Seo Hyeon-Kyoung Koo Ji Yeon Kang Jieun Kang So Hee Park Hyung Koo Kang Hye Kyeong Park Sung-Soon Lee Sangbong Choi Tae Won Jang Kyeong-Cheol Shin Jee Youn Oh Joon Young Choi Jinsoo Min Young-Kyung Choi Jae-Gook Shin Yong-Soon Cho Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database BMC Pulmonary Medicine Tuberculosis Non-tuberculosis mycobacterium N-Acetyltransferase-2 Solute carrier organic anion transporter family member 1B1 The Center for Personalized Precision Medicine of Tuberculosis |
| title | Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database |
| title_full | Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database |
| title_fullStr | Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database |
| title_full_unstemmed | Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database |
| title_short | Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database |
| title_sort | risk adjustment model for tuberculosis compared to non tuberculosis mycobacterium or latent tuberculosis infection center for personalized precision medicine of tuberculosis cpmtb cohort database |
| topic | Tuberculosis Non-tuberculosis mycobacterium N-Acetyltransferase-2 Solute carrier organic anion transporter family member 1B1 The Center for Personalized Precision Medicine of Tuberculosis |
| url | https://doi.org/10.1186/s12890-023-02646-7 |
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