HLA-DRB1*15:01 and the MERTK Gene Interact to Selectively Influence the Profile of MERTK-Expressing Monocytes in Both Health and MS.

BACKGROUND AND OBJECTIVES: HLA-DRB1*15:01 (DR15) and MERTK are 2 risk genes for multiple sclerosis (MS). The variant rs7422195 is an expression quantitative trait locus for MERTK in CD14+ monocytes; cells with phagocytic and immunomodulatory potential. We aimed to understand how drivers of disease risk and pathogenesis vary with HLA and MERTK genotype and disease activity. METHODS: We investigated how proportions of monocytes vary with HLA and MERTK genotype and disease activity in MS. CD14+ monocytes were isolated from patients with MS at relapse (n = 40) and 3 months later (n = 23). Healthy controls (HCs) underwent 2 blood collections 3 months apart. Immunophenotypic profiling of monocytes was performed by flow cytometry. Methylation of 35 CpG sites within and near the MERTK gene was assessed in whole blood samples of individuals experiencing their first episode of clinical CNS demyelination (n = 204) and matched HCs (n = 345) using an Illumina EPIC array. RESULTS: DR15-positive patients had lower proportions of CD14+ MERTK+ monocytes than DR15-negative patients, independent of genotype at the MERTK SNP rs7422195. Proportions of CD14+ MERTK+ monocytes were further reduced during relapse in DR15-positive but not DR15-negative patients. Patients homozygous for the major G allele at rs7422195 exhibited higher proportions of CD14+ MERTK+ monocytes at both relapse and remission compared with controls. We observed that increased methylation of the MERTK gene was significantly associated with the presence of DR15. DISCUSSION: DR15 and MERTK genotype independently influence proportions of CD14+ MERTK+ monocytes in MS. We confirmed previous observations that the MERTK risk SNP rs7422195 is associated with altered MERTK expression in monocytes. We identified that expression of MERTK is stratified by disease in people homozygous for the major G allele of rs7422195. The finding that the proportion of CD14+ MERTK+ monocytes is reduced in DR15-positive individuals supports prior data identifying genetic links between these 2 loci in influencing MS risk. DR15 genotype-dependent alterations in methylation of the MERTK gene provides a molecular link between these loci and identifies a potential mechanism by which MERTK expression is influenced by DR15. This links DR15 haplotype to MS susceptibility beyond direct influence on antigen presentation and suggests the need for HLA-based stratification of approaches to MERTK as a therapeutic target.

Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events.

BACKGROUND: The recent COVID-19 pandemic highlighted the challenges for traditional forecasting. Prediction markets are a promising way to generate collective forecasts and could potentially be enhanced if high-quality crowdsourced inputs were identified and preferentially weighted for likely accuracy in real-time with machine learning. METHODS: We aim to leverage human prediction markets with real-time machine weighting of likely higher accuracy trades to improve performance. The crowd sourced Almanis prediction market longitudinal platform (n = 1822) and Next Generation Social Science (NGS2) platform (n = 103) were utilised. FINDINGS: A 43-feature model predicted accurate forecasters, those with top quintile relative Brier accuracy, with subsequent replication in two out-of-sample datasets (pboth <1 × 10-9). Trades graded by this model as having higher accuracy scores than others produced a greater AUC temporal gain in the overall market after vs before trade. Accuracy score-weighted forecasts had higher accuracy than market forecasts alone, particularly when the two systems disagreed by 5% or more for binary event prediction: the hybrid system demonstrating substantial % AUC gains of 13.2%, p = 1.35 × 10-14 and 13.8%, p = 0.003 in two out-of-sample datasets. When discordant, the hybrid model was correct for COVID-19 event occurrence 72.7% of the time vs 27.3% for market models, p = 0.007. This net classification benefit was replicated in the separate Almanis B dataset, p = 2.4 × 10-7. INTERPRETATION: Real-time machine classification followed by weighting human trades according to likely accuracy improves collective forecasting performance. This could provide improved anticipation of and thus response to emerging risks. FUNDING: This work was supported by an AusIndustry R and D tax incentive program from the Department of Industry, Science, Energy and Resources, Australia, to SlowVoice Pty Ltd. (IR 2101990) and Fellowship (GNT 1110200) and Investigator grant (GNT 1197234) to A-L Ponsonby by the National Health and Medical Research Council of Australia.

Household size, T regulatory cell development, and early allergic disease: a birth cohort study.

BACKGROUND: Children born to larger households have less allergic disease. T regulatory cell (Treg) development may be a relevant mechanism, but this has not been studied longitudinally. OBJECTIVE: We aim to (i) describe how prenatal and postnatal environmental factors are associated with Treg development and (ii) investigate whether serial Treg measures predict allergic outcomes at 1 year of age. METHODS: A birth cohort (n = 1074) with information on prenatal and postnatal early life factors. Both naïve Treg (nTreg) and activated Treg (aTreg) cell populations (as a proportion of CD4+ T cells) were available in 463 infants at birth (cord blood), 600 at 6 months, and 675 at 12 months. 191 infants had serial measures. Measures of allergic status at 12 months were polysensitization (sensitization to 2 or more allergens), clinically proven food allergy, atopic eczema, and atopic wheeze. RESULTS: Infants born to larger households (3 or more residents) had higher longitudinal nTreg proportions over the first postnatal year with a mean difference (MD) of 0.67 (95% CI 0.30-1.04)%. Higher nTreg proportions at birth were associated with a reduced risk of infant allergic outcomes. Childcare attendance and breastfeeding were associated with higher longitudinal nTreg proportions (MD 0.48 (95% CI 0.08-0.80)%. CONCLUSION: Multiple prenatal and postnatal microbial factors are associated with nTreg and aTreg development. Larger household size was associated with higher nTreg at birth which in turn was associated with reduced allergic sensitization and disease at 12 months of age.