Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis
Background: Cryptococcal meningitis causes an estimated 112,000 global deaths annually. Genomic and phenotypic features of the infecting strain of Cryptococcus spp. have been studied extensively. Population-level pharmacokinetic variability is well documented in these patient cohorts. The relative c...
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Elsevier
2025-03-01
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| Series: | International Journal of Infectious Diseases |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1201971224007148 |
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| author | Dr Katharine Stott Mr Jason Mohabir Miss Kate Bowers Assistant Professor Jennifer Tenor Associate Professor Dena Tofaletti Dr Jennifer Unsworth Ms Ana Jimenez-Valverde Mr Ajisa Ahmadu Dr Melanie Moyo Mrs Ebbie Gondwe Mrs Wezi Chimang'anga Mr Madalitso Chasweka Dr David Lawrence Professor Joseph Jarvis Professor Tom Harrison Professor William Hope Professor David Lalloo Professor Henry Mwandumba Professor John Perfect Professor Christina Cuomo |
| author_facet | Dr Katharine Stott Mr Jason Mohabir Miss Kate Bowers Assistant Professor Jennifer Tenor Associate Professor Dena Tofaletti Dr Jennifer Unsworth Ms Ana Jimenez-Valverde Mr Ajisa Ahmadu Dr Melanie Moyo Mrs Ebbie Gondwe Mrs Wezi Chimang'anga Mr Madalitso Chasweka Dr David Lawrence Professor Joseph Jarvis Professor Tom Harrison Professor William Hope Professor David Lalloo Professor Henry Mwandumba Professor John Perfect Professor Christina Cuomo |
| author_sort | Dr Katharine Stott |
| collection | DOAJ |
| description | Background: Cryptococcal meningitis causes an estimated 112,000 global deaths annually. Genomic and phenotypic features of the infecting strain of Cryptococcus spp. have been studied extensively. Population-level pharmacokinetic variability is well documented in these patient cohorts. The relative contribution of these factors to clinical outcomes is unknown. We integrated pathogen genomic and phenotypic data with pharmacokinetic data to assess the relative contribution of each to clinical outcomes from cryptococcal meningitis. Methods: Based in Malawi, we conducted a sub-study of the phase 3 Ambition-CM trial (ISRCTN72509687), collecting plasma and cerebrospinal fluid at serial time points during the first 14 days of antifungal therapy. We performed whole-genome sequencing on multiple isolates collected at each time point from each patient. Sequence data were examined for genotypic variants. Maximum likelihood phylogenies were constructed. Phenotypic antifungal susceptibility profiling was performed. An intensive pharmacokinetic study was undertaken, and population pharmacokinetic models were constructed for fluconazole, flucytosine, amphotericin B deoxycholate and liposomal amphotericin B. Using adjusted multiple regression analyses, we explored the relative contribution of pathogen genotype, drug resistance phenotype and pharmacokinetics on clinical outcomes including lumbar opening pressure, pharmacodynamic effect and mortality. Results: We report remarkable genomic homogeneity among 718 infecting strains of Cryptococcus spp.. Chromosome 1 aneuploidy was evident in 26% of isolates, while 52% of isolates had at least one non-synonymous mutation in a drug target gene. There was no evidence of acquired antifungal resistance in our isolates. Pharmacokinetic modelling revealed considerable population variability in drug exposure despite uniform weight-based dosing. Strain lineage VNIb was associated with increased aneuploidy of chromosome 1, but also with reduced odds of raised lumbar opening pressure and increased EFA. Baseline fungal burden and early fungicidal activity (EFA) were associated with mortality. The strongest predictor of EFA was the level of exposure to amphotericin B, with increased exposure being independently associated with increased EFA. Discussion: Our unique analysis provides novel insight into the relative contribution of pathogen genomic characteristics and individual-level estimates of drug exposure to clinical outcomes from HIV-associated cryptococcal meningitis. The lack of evolution of resistance in our isolates may reflect the fact that all patients received highly potent, amphotericin B-based combination antifungal therapy. Genotypic features of the infecting strain were not consistently associated with adverse or favourable clinical outcomes. The strongest predictors of mortality were baseline fungal burden and EFA, in keeping with previous studies. The strongest predictor of EFA was level of exposure to amphotericin B and future studies may consider increasing the dose of liposomal amphotericin B further. Conclusion: Relative to pathogen features, level of antifungal drug exposure strongly predicted clinical outcomes from cryptococcal meningitis. This study underscores the importance of optimal exposure to potent antifungal drugs to promote improved clinical outcomes. |
| format | Article |
| id | doaj-art-910abc6fbea440b69ec4a7ce040bbd92 |
| institution | OA Journals |
| issn | 1201-9712 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Infectious Diseases |
| spelling | doaj-art-910abc6fbea440b69ec4a7ce040bbd922025-08-20T02:17:08ZengElsevierInternational Journal of Infectious Diseases1201-97122025-03-0115210763910.1016/j.ijid.2024.107639Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitisDr Katharine Stott0Mr Jason Mohabir1Miss Kate Bowers2Assistant Professor Jennifer Tenor3Associate Professor Dena Tofaletti4Dr Jennifer Unsworth5Ms Ana Jimenez-Valverde6Mr Ajisa Ahmadu7Dr Melanie Moyo8Mrs Ebbie Gondwe9Mrs Wezi Chimang'anga10Mr Madalitso Chasweka11Dr David Lawrence12Professor Joseph Jarvis13Professor Tom Harrison14Professor William Hope15Professor David Lalloo16Professor Henry Mwandumba17Professor John Perfect18Professor Christina Cuomo19Antimicrobial Pharmacodynamics and Therapeutics group, Department of Pharmacology and Therapeutics, University of Liverpool; Malawi Liverpool Wellcome Clinical Research ProgrammeBroad Institute of MIT and Harvard, CambridgeBroad Institute of MIT and Harvard, CambridgeDivision of Infectious Diseases, Department of Medicine, Duke University School of Medicine, DurhamDivision of Infectious Diseases, Department of Medicine, Duke University School of Medicine, DurhamAntimicrobial Pharmacodynamics and Therapeutics group, Department of Pharmacology and Therapeutics, University of LiverpoolAntimicrobial Pharmacodynamics and Therapeutics group, Department of Pharmacology and Therapeutics, University of LiverpoolMalawi Liverpool Wellcome Clinical Research ProgrammeMalawi Liverpool Wellcome Clinical Research Programme; Department of Medicine, Kamuzu University of Health SciencesMalawi Liverpool Wellcome Clinical Research ProgrammeMalawi Liverpool Wellcome Clinical Research ProgrammeMalawi Liverpool Wellcome Clinical Research ProgrammeDepartment of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Tropical Medicine; Botswana Harvard Health Partnership; Clinical Microbiology and Infectious Diseases, School of Pathology, Faculty of Health Sciences, University of the WitwatersrandDepartment of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Tropical Medicine; Botswana Harvard Health PartnershipInstitute of Infection and Immunity, St George's University LondonAntimicrobial Pharmacodynamics and Therapeutics group, Department of Pharmacology and Therapeutics, University of LiverpoolLiverpool School of Tropical MedicineMalawi Liverpool Wellcome Clinical Research ProgrammeDivision of Infectious Diseases, Department of Medicine, Duke University School of Medicine, DurhamBroad Institute of MIT and Harvard, CambridgeBackground: Cryptococcal meningitis causes an estimated 112,000 global deaths annually. Genomic and phenotypic features of the infecting strain of Cryptococcus spp. have been studied extensively. Population-level pharmacokinetic variability is well documented in these patient cohorts. The relative contribution of these factors to clinical outcomes is unknown. We integrated pathogen genomic and phenotypic data with pharmacokinetic data to assess the relative contribution of each to clinical outcomes from cryptococcal meningitis. Methods: Based in Malawi, we conducted a sub-study of the phase 3 Ambition-CM trial (ISRCTN72509687), collecting plasma and cerebrospinal fluid at serial time points during the first 14 days of antifungal therapy. We performed whole-genome sequencing on multiple isolates collected at each time point from each patient. Sequence data were examined for genotypic variants. Maximum likelihood phylogenies were constructed. Phenotypic antifungal susceptibility profiling was performed. An intensive pharmacokinetic study was undertaken, and population pharmacokinetic models were constructed for fluconazole, flucytosine, amphotericin B deoxycholate and liposomal amphotericin B. Using adjusted multiple regression analyses, we explored the relative contribution of pathogen genotype, drug resistance phenotype and pharmacokinetics on clinical outcomes including lumbar opening pressure, pharmacodynamic effect and mortality. Results: We report remarkable genomic homogeneity among 718 infecting strains of Cryptococcus spp.. Chromosome 1 aneuploidy was evident in 26% of isolates, while 52% of isolates had at least one non-synonymous mutation in a drug target gene. There was no evidence of acquired antifungal resistance in our isolates. Pharmacokinetic modelling revealed considerable population variability in drug exposure despite uniform weight-based dosing. Strain lineage VNIb was associated with increased aneuploidy of chromosome 1, but also with reduced odds of raised lumbar opening pressure and increased EFA. Baseline fungal burden and early fungicidal activity (EFA) were associated with mortality. The strongest predictor of EFA was the level of exposure to amphotericin B, with increased exposure being independently associated with increased EFA. Discussion: Our unique analysis provides novel insight into the relative contribution of pathogen genomic characteristics and individual-level estimates of drug exposure to clinical outcomes from HIV-associated cryptococcal meningitis. The lack of evolution of resistance in our isolates may reflect the fact that all patients received highly potent, amphotericin B-based combination antifungal therapy. Genotypic features of the infecting strain were not consistently associated with adverse or favourable clinical outcomes. The strongest predictors of mortality were baseline fungal burden and EFA, in keeping with previous studies. The strongest predictor of EFA was level of exposure to amphotericin B and future studies may consider increasing the dose of liposomal amphotericin B further. Conclusion: Relative to pathogen features, level of antifungal drug exposure strongly predicted clinical outcomes from cryptococcal meningitis. This study underscores the importance of optimal exposure to potent antifungal drugs to promote improved clinical outcomes.http://www.sciencedirect.com/science/article/pii/S1201971224007148 |
| spellingShingle | Dr Katharine Stott Mr Jason Mohabir Miss Kate Bowers Assistant Professor Jennifer Tenor Associate Professor Dena Tofaletti Dr Jennifer Unsworth Ms Ana Jimenez-Valverde Mr Ajisa Ahmadu Dr Melanie Moyo Mrs Ebbie Gondwe Mrs Wezi Chimang'anga Mr Madalitso Chasweka Dr David Lawrence Professor Joseph Jarvis Professor Tom Harrison Professor William Hope Professor David Lalloo Professor Henry Mwandumba Professor John Perfect Professor Christina Cuomo Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis International Journal of Infectious Diseases |
| title | Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis |
| title_full | Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis |
| title_fullStr | Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis |
| title_full_unstemmed | Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis |
| title_short | Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis |
| title_sort | integration of genomic and pharmacokinetic data to predict clinical outcomes in hiv associated cryptococcal meningitis |
| url | http://www.sciencedirect.com/science/article/pii/S1201971224007148 |
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