Safety and efficacy of inhaled IBIO123 for mild-to-moderate COVID-19: a randomised, double-blind, dose-ascending, placebo-controlled, phase 1/2 trial.

BACKGROUND: COVID-19 severity is associated with its respiratory manifestations. Neutralising antibodies against SARS-CoV-2 administered systemically have shown clinical efficacy. However, immediate and direct delivery of neutralising antibodies via inhalation might provide additional respiratory clinical benefits. IBIO123 is a cocktail of three, fully human, neutralising monoclonal antibodies against SARS-CoV-2. We aimed to assess the safety and efficacy of inhaled IBIO123 in individuals with mild-to-moderate COVID-19. METHODS: This double-blind, dose-ascending, placebo-controlled, first-in-human, phase 1/2 trial recruited symptomatic and non-hospitalised participants with COVID-19 in South Africa and Brazil across 11 centres. Eligible participants were adult outpatients (aged ≥18 years; men and non-pregnant women) infected with COVID-19 (first PCR-confirmed within 72 h) and with mild-to-moderate symptoms, the onset of which had to be within 10 days of randomisation. Using permuted blocks of four, stratified by site, we randomly assigned participants (1:3) to receive single-dose placebo or IBIO123 (1 mg, 5 mg, or 10 mg) in phase 1, and single-dose placebo or IBIO123 (10 mg) in phase 2, in addition to local standard of care. Participants underwent serological testing to identify antibodies against SARS-CoV-2. Participants, investigators, and the study team were masked to treatment assignment. In phase 1, the primary outcome was the safety assessment in the safety population (ie, all participants who received an intervention). In phase 2, the primary outcome was the mean absolute change from baseline to day 5 in SARS-CoV-2 viral load measured by nasopharyngeal swabs analysed using a mixed model for repeated measures in the full analysis set (FAS; ie, participants with one analysable viral load value at baseline and at least one analysable viral load value at day 3 or day 5). Secondary clinical outcomes included safety from baseline to day 29, assessed by evaluating adverse events; the effect of IBIO123 on baseline COVID-19 symptoms resolution until day 6, with symptoms systemically evaluated by the investigators; and disease progression as measured by the COVID-19 WHO Clinical Progression Scale. For clinical endpoints in phase 2, we used a modified FAS (ie, participants who had at least one analysable viral load value over the course of the study, confirming that they were infected with SARS-CoV-2). This trial is now completed and is registered with ClinicalTrials.gov, NCT05298813. FINDINGS: Between Dec 4, 2021, and May 23, 2022, 24 participants were enrolled in phase 1. Between July 20, 2022, and Jan 4, 2023, 138 participants were enrolled in phase 2 and five were excluded because they did not meet the inclusion criteria. Participants were randomly assigned to receive IBIO123 (n=18) or placebo (n=6) in phase 1, and randomly assigned to receive IBIO123 (n=104) or placebo (n=34) in phase 2. In phase 2, the study was stopped before reaching the planned accrual because of a decline in COVID-19 incidence. In phase 1, no safety issues were observed. In phase 2, the difference in mean absolute change from baseline viral load to day 5 between participants in the IBIO123 group and participants in the placebo group was -0·29 log10 copies per mL (95% CI -1·32 to 0·75; p=0·45) in the FAS population and -0·49 log10 copies per mL (-1·56 to 0·58; p=0·20) in seropositive participants. In the modified FAS, 81 (69%) of 118 participants were at high risk of severe disease progression. The number of participants with resolution of respiratory symptoms at day 6 was 34 (42%) of 81 in the IBIO123 group versus five (17%) of 29 in the placebo group (p=0·017) in the modified FAS population and 19 (35%) of 55 versus three (14%) of 21 among participants at high risk (p=0·083). One participant died and one participant was hospitalised in the placebo group, whereas no deaths or hospitalisations were reported in the IBIO123 group. 39 (38%) of 104 participants in the IBIO123 group had adverse events, compared with 13 (38%) of 34 in the placebo group. INTERPRETATION: Inhalation of IBIO123 was safe. Despite the lack of significant reduction of viral load at day 5, treatment with IBIO123 resulted in a higher proportion of participants with complete resolution of respiratory symptoms at day 6. This study supports further clinical research on inhaled monoclonal antibodies in COVID-19 and respiratory diseases in general. FUNDING: Canadian Strategic Innovation Fund and Immune Biosolutions.

GWAS in the southern African context.

Researchers would generally adjust for the possible confounding effect of population structure by considering global ancestry proportions or top principle components. Alternatively, researchers would conduct admixture mapping to increase the power to detect variants with an ancestry effect. This is sufficient in simple admixture scenarios, however, populations from southern Africa can be complex multi-way admixed populations. Duan et al. (2018) first described local ancestry adjusted allelic (LAAA) analysis as a robust method for discovering association signals, while producing minimal false positive hits. Their simulation study, however, was limited to a two-way admixed population. Realizing that their findings might not translate to other admixture scenarios, we simulated a three- and five-way admixed population to compare the LAAA model to other models commonly used in genome-wide association studies (GWAS). We found that, given our admixture scenarios, the LAAA model identifies the most causal variants in most of the phenotypes we tested across both the three-way and five-way admixed populations. The LAAA model also produced a high number of false positive hits which was potentially caused by the ancestry effect size that we assumed. Considering the extent to which the various models tested differed in their results and considering that the source of a given association is unknown, we recommend that researchers use multiple GWAS models when analysing populations with complex ancestry.

Local Ancestry Adjusted Allelic Association Analysis Robustly Captures Tuberculosis Susceptibility Loci.

Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease. The risk of developing active TB is in part determined by host genetic factors. Most genetic studies investigating TB susceptibility fail to replicate association signals particularly across diverse populations. South African populations arose because of multi-wave genetic admixture from the indigenous KhoeSan, Bantu-speaking Africans, Europeans, Southeast Asian-and East Asian populations. This has led to complex genetic admixture with heterogenous patterns of linkage disequilibrium and associated traits. As a result, precise estimation of both global and local ancestry is required to prevent both false positive and false-negative associations. Here, 820 individuals from South Africa were genotyped on the SNP-dense Illumina Multi-Ethnic Genotyping Array (∼1.7M SNPs) followed by local and global ancestry inference using RFMix. Local ancestry adjusted allelic association (LAAA) models were utilized owing to the extensive genetic heterogeneity present in this population. Hence, an interaction term, comprising the identification of the minor allele that corresponds to the ancestry present at the specific locus under investigation, was included as a covariate. One SNP (rs28647531) located on chromosome 4q22 was significantly associated with TB susceptibility and displayed a SNP minor allelic effect (G allele, frequency = 0.204) whilst correcting for local ancestry for Bantu-speaking African ancestry (p-value = 5.518 × 10-7; OR = 3.065; SE = 0.224). Although no other variants passed the significant threshold, clear differences were observed between the lead variants identified for each ancestry. Furthermore, the LAAA model robustly captured the source of association signals in multi-way admixed individuals from South Africa and allowed the identification of ancestry-specific disease risk alleles associated with TB susceptibility that have previously been missed.

Prospective avenues for human population genomics and disease mapping in southern Africa.

Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development.