Integration of genomic and pharmacokinetic data to predict clinical outcomes in HIV-associated cryptococcal meningitis - 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; et al. (International Journal of Infectious Diseases)
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.