Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response

Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, diversity metric of the HLA profile of individuals within a population and consideration of sequence diversity in the context of an individual's CD8 T-cell immune repertoire to assess the HIV proteome for defined regions of immunogenicity. Using this approach, analysis of HLA adaptation and functional immunogenicity data enabled the identification of regions within the proteome that offer significant conservation, HLA recognition within a population, low prevalence of HLA adaptation and demonstrated immunogenicity. We believe this unique and novel approach to vaccine design as a supplement to vitro functional assays, offers a bespoke pipeline for expedited and rational CD8 T-cell vaccine design for HIV and potentially other pathogens with the potential for both global and local coverage.Fil: McGowan, Ed. Imperial College London; Reino UnidoFil: Rosenthal, Rachel. Francis Crick Institute; Reino UnidoFil: Fiore Gartland, Andrew. Fred Hutchinson Cancer Research Cente; Estados UnidosFil: Macharia, Gladys. Imperial College London; Reino UnidoFil: Balinda, Sheila. Uganda Virus Research Institute; UgandaFil: Kapaata, Anne. Uganda Virus Research Institute; UgandaFil: Umviligihozo, Gisele. Center for Family Health Research; RuandaFil: Muok, Erick. Center for Family Health Research; RuandaFil: Dalel, Jama. Imperial College London; Reino UnidoFil: Streatfield, Claire L.. Imperial College London; Reino UnidoFil: Coutinho, Helen. Imperial College London; Reino UnidoFil: Dilernia, Dario. University of Emory; Estados UnidosFil: Monaco, Daniela C.. University of Emory; Estados UnidosFil: Morrison, David. South Walsham; Reino UnidoFil: Yue, Ling. University of Emory; Estados UnidosFil: Hunter, Eric. University of Emory; Estados UnidosFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gilmour, Jill. Imperial College London; Reino UnidoFil: Hare, Jonathan. International Aids Vaccine Initiative; Estados Unido

End-point definition and trial design to advance tuberculosis vaccine development.

Tuberculosis (TB) remains a leading infectious cause of death worldwide and the coronavirus disease 2019 pandemic has negatively impacted the global TB burden of disease indicators. If the targets of TB mortality and incidence reduction set by the international community are to be met, new more effective adult and adolescent TB vaccines are urgently needed. There are several new vaccine candidates at different stages of clinical development. Given the limited funding for vaccine development, it is crucial that trial designs are as efficient as possible. Prevention of infection (POI) approaches offer an attractive opportunity to accelerate new candidate vaccines to advance into large and expensive prevention of disease (POD) efficacy trials. However, POI approaches are limited by imperfect current tools to measure Mycobacterium tuberculosis infection end-points. POD trials need to carefully consider the type and number of microbiological tests that define TB disease and, if efficacy against subclinical (asymptomatic) TB disease is to be tested, POD trials need to explore how best to define and measure this form of TB. Prevention of recurrence trials are an alternative approach to generate proof of concept for efficacy, but optimal timing of vaccination relative to treatment must still be explored. Novel and efficient approaches to efficacy trial design, in addition to an increasing number of candidates entering phase 2-3 trials, would accelerate the long-standing quest for a new TB vaccine

Evaluation of cell-based and surrogate SARS-CoV-2 neutralization assays

Determinants of protective immunity against SARS-CoV-2 infection require the development of well-standardized, reproducible antibody assays. This need has led to the emergence of a variety of neutralization assays. Head-to-head evaluation of different SARS-CoV-2 neutralization platforms could facilitate comparisons across studies and laboratories. Five neutralization assays were compared using forty plasma samples from convalescent individuals with mild-to-moderate COVID-19: four cell-based systems using either live recombinant SARS-CoV-2 or pseudotyped viral particles created with lentivirus (LV) or vesicular stomatitis virus (VSV) packaging and one surrogate ELISA-based test that measures inhibition of the spike protein receptor binding domain (RBD) binding its receptor, human angiotensin converting enzyme 2 (hACE2). Vero, Vero E6, HEK293T expressing hACE2, and TZM-bl cells expressing hACE2 and transmembrane serine protease 2 were tested. All cell-based assays showed 50% neutralizing dilution (ND50) geometric mean titers (GMTs) that were highly correlated (Pearson r = 0.81–0.89) and ranged within 3.4-fold. The live-virus assay and LV-pseudovirus assays with HEK293T/hACE2 cells showed very similar mean titers: 141 and 178, respectively. ND50 titers positively correlated with plasma IgG targeting SARS-CoV-2 spike and RBD (r = 0.63–0.89), but moderately correlated with nucleoprotein IgG (r = 0.46–0.73). ND80 GMTs mirrored ND50 data and showed similar correlation between assays and with IgG concentrations. The VSV-pseudovirus assay and LV-pseudovirus assay with HEK293T/hACE2 cells in low and high-throughput versions were calibrated against the WHO SARS-CoV-2 IgG standard. High concordance between the outcomes of cell-based assays with live and pseudotyped virions enables valid cross-study comparison using these platforms. 24

Validation of a host blood transcriptomic biomarker for pulmonary tuberculosis in people living with HIV: a prospective diagnostic and prognostic accuracy study.

BACKGROUND: A rapid, blood-based triage test that allows targeted investigation for tuberculosis at the point of care could shorten the time to tuberculosis treatment and reduce mortality. We aimed to test the performance of a host blood transcriptomic signature (RISK11) in diagnosing tuberculosis and predicting progression to active pulmonary disease (prognosis) in people with HIV in a community setting. METHODS: In this prospective diagnostic and prognostic accuracy study, adults (aged 18-59 years) with HIV were recruited from five communities in South Africa. Individuals with a history of tuberculosis or household exposure to multidrug-resistant tuberculosis within the past 3 years, comorbid risk factors for tuberculosis, or any condition that would interfere with the study were excluded. RISK11 status was assessed at baseline by real-time PCR; participants and study staff were masked to the result. Participants underwent active surveillance for microbiologically confirmed tuberculosis by providing spontaneously expectorated sputum samples at baseline, if symptomatic during 15 months of follow-up, and at 15 months (the end of the study). The coprimary outcomes were the prevalence and cumulative incidence of tuberculosis disease confirmed by a positive Xpert MTB/RIF, Xpert Ultra, or Mycobacteria Growth Indicator Tube culture, or a combination of such, on at least two separate sputum samples collected within any 30-day period. FINDINGS: Between March 22, 2017, and May 15, 2018, 963 participants were assessed for eligibility and 861 were enrolled. Among 820 participants with valid RISK11 results, eight (1%) had prevalent tuberculosis at baseline: seven (2·5%; 95% CI 1·2-5·0) of 285 RISK11-positive participants and one (0·2%; 0·0-1·1) of 535 RISK11-negative participants. The relative risk (RR) of prevalent tuberculosis was 13·1 times (95% CI 2·1-81·6) greater in RISK11-positive participants than in RISK11-negative participants. RISK11 had a diagnostic area under the receiver operating characteristic curve (AUC) of 88·2% (95% CI 77·6-96·7), and a sensitivity of 87·5% (58·3-100·0) and specificity of 65·8% (62·5-69·0) at a predefined score threshold (60%). Of those with RISK11 results, eight had primary endpoint incident tuberculosis during 15 months of follow-up. Tuberculosis incidence was 2·5 per 100 person-years (95% CI 0·7-4·4) in the RISK11-positive group and 0·2 per 100 person-years (0·0-0·5) in the RISK11-negative group. The probability of primary endpoint incident tuberculosis was greater in the RISK11-positive group than in the RISK11-negative group (cumulative incidence ratio 16·0 [95% CI 2·0-129·5]). RISK11 had a prognostic AUC of 80·0% (95% CI 70·6-86·9), and a sensitivity of 88·6% (43·5-98·7) and a specificity of 68·9% (65·3-72·3) for incident tuberculosis at the 60% threshold. INTERPRETATION: RISK11 identified prevalent tuberculosis and predicted risk of progression to incident tuberculosis within 15 months in ambulant people living with HIV. RISK11's performance approached, but did not meet, WHO's target product profile benchmarks for screening and prognostic tests for tuberculosis. FUNDING: Bill & Melinda Gates Foundation and the South African Medical Research Council

Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial.

BACKGROUND: Targeted preventive therapy for individuals at highest risk of incident tuberculosis might impact the epidemic by interrupting transmission. We tested performance of a transcriptomic signature of tuberculosis (RISK11) and efficacy of signature-guided preventive therapy in parallel, using a hybrid three-group study design. METHODS: Adult volunteers aged 18-59 years were recruited at five geographically distinct communities in South Africa. Whole blood was sampled for RISK11 by quantitative RT-PCR assay from eligible volunteers without HIV, recent previous tuberculosis (ie, <3 years before screening), or comorbidities at screening. RISK11-positive participants were block randomised (1:2; block size 15) to once-weekly, directly-observed, open-label isoniazid and rifapentine for 12 weeks (ie, RISK11 positive and 3HP positive), or no treatment (ie, RISK11 positive and 3HP negative). A subset of eligible RISK11-negative volunteers were randomly assigned to no treatment (ie, RISK11 negative and 3HP negative). Diagnostic discrimination of prevalent tuberculosis was tested in all participants at baseline. Thereafter, prognostic discrimination of incident tuberculosis was tested in the untreated RISK11-positive versus RISK11-negative groups, and treatment efficacy in the 3HP-treated versus untreated RISK11-positive groups, during active surveillance through 15 months. The primary endpoint was microbiologically confirmed pulmonary tuberculosis. The primary outcome measures were risk ratio [RR] for tuberculosis of RISK11-positive to RISK11-negative participants, and treatment efficacy. This trial is registered with ClinicalTrials.gov, NCT02735590. FINDINGS: 20 207 volunteers were screened, and 2923 participants were enrolled, including RISK11-positive participants randomly assigned to 3HP (n=375) or no 3HP (n=764), and 1784 RISK11-negative participants. Cumulative probability of prevalent or incident tuberculosis disease was 0·066 (95% CI 0·049 to 0·084) in RISK11-positive (3HP negative) participants and 0·018 (0·011 to 0·025) in RISK11-negative participants (RR 3·69, 95% CI 2·25-6·05) over 15 months. Tuberculosis prevalence was 47 (4·1%) of 1139 versus 14 (0·78%) of 1984 in RISK11-positive compared with RISK11-negative participants, respectively (diagnostic RR 5·13, 95% CI 2·93 to 9·43). Tuberculosis incidence over 15 months was 2·09 (95% CI 0·97 to 3·19) vs 0·80 (0·30 to 1·30) per 100 person years in RISK11-positive (3HP-negative) participants compared with RISK11-negative participants (cumulative incidence ratio 2·6, 95% CI 1·2 to 5·9). Serious adverse events related to 3HP included one hospitalisation for seizures (unintentional isoniazid overdose) and one death of unknown cause (possibly temporally related). Tuberculosis incidence over 15 months was 1·94 (95% CI 0·35 to 3·50) versus 2·09 (95% CI 0·97 to 3·19) per 100 person-years in 3HP-treated RISK11-positive participants compared with untreated RISK11-positive participants (efficacy 7·0%, 95% CI -145 to 65). INTERPRETATION: The RISK11 signature discriminated between individuals with prevalent tuberculosis, or progression to incident tuberculosis, and individuals who remained healthy, but provision of 3HP to signature-positive individuals after exclusion of baseline disease did not reduce progression to tuberculosis over 15 months. FUNDING: Bill and Melinda Gates Foundation, South African Medical Research Council

Considerations for biomarker-targeted intervention strategies for tuberculosis disease prevention.

CAPRISA, 2018.Abstract available in pdf

Parsimonious transcriptomic signatures: Statistical analysis plan

Statistical Analysis Plan: Evaluation of parsimonious host-blood tuberculosis transcriptomic signatures in HIV-infected and HIV-uninfected individuals: A sub-study of the CORTIS-01 and CORTIS-HR trials.Version: 1.0Date: 08 January 2020</div