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Binder MD, Nwoke EC, Morwitch E, Dwyer C, Li V, Xavier A, Lea RA, Lechner-Scott J, Taylor BV, Ponsonby AL, Kilpatrick TJ. HLA-DRB1*15:01 and the MERTK Gene Interact to Selectively Influence the Profile of MERTK-Expressing Monocytes in Both Health and MS. Neurol Neuroimmunol Neuroinflamm 2024; 11:e200190. [PMID: 38150649 PMCID: PMC10752576 DOI: 10.1212/nxi.0000000000200190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 10/31/2023] [Indexed: 12/29/2023]
Abstract
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.
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Affiliation(s)
- Michele D Binder
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Eze C Nwoke
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Ellen Morwitch
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Chris Dwyer
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Vivien Li
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Alexandre Xavier
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Rodney A Lea
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Jeannette Lechner-Scott
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Bruce V Taylor
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Anne-Louise Ponsonby
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
| | - Trevor J Kilpatrick
- From the Florey Institute of Neuroscience and Mental Health (M.D.B., E.C.N., E.M., C.D., V.L., A.-L.P., T.J.K.); Department of Anatomy and Physiology (M.D.B.), University of Melbourne, Parkville; Crux Biolabs (E.C.N.), Bayswater; Department of Neurology (C.D.), Royal Melbourne Hospital, Parkville; Department of Neurology (A.X., J.L.-S.), John Hunter Hospital, Newcastle; Hunter Medical Research Institute (A.X., J.L.-S.), University of Newcastle, New South Wales Genomics Research Centre (R.A.L.), Centre of Genomics and Personalised Health, Queensland University of Technology; and Menzies Institute for Medical Research (B.V.T.), University of Tasmania, Hobart, Australia
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Gruen A, Mattingly KR, Morwitch E, Bossaerts F, Clifford M, Nash C, Ioannidis JPA, Ponsonby AL. Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events. EBioMedicine 2023; 96:104783. [PMID: 37708701 PMCID: PMC10502359 DOI: 10.1016/j.ebiom.2023.104783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/18/2023] [Accepted: 08/18/2023] [Indexed: 09/16/2023] Open
Abstract
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.
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Affiliation(s)
- Alexander Gruen
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | | | - Ellen Morwitch
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | | | | | - Chad Nash
- Dysrupt Labs by SlowVoice, Melbourne, Australia
| | - John P A Ioannidis
- Stanford Prevention Research Center, Department of Medicine, and Departments of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Meta-Research Innovation Center at Stanford, Stanford, CA, USA
| | - Anne-Louise Ponsonby
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Centre of Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Australia.
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Ponsonby AL, Collier F, O'Hely M, Tang MLK, Ranganathan S, Gray L, Morwitch E, Saffery R, Burgner D, Dwyer T, Sly PD, Harrison LC, Vuillermin P. Household size, T regulatory cell development, and early allergic disease: a birth cohort study. Pediatr Allergy Immunol 2022; 33:e13810. [PMID: 35754137 PMCID: PMC9545943 DOI: 10.1111/pai.13810] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/05/2022] [Accepted: 05/19/2022] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- Anne-Louise Ponsonby
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.,Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Fiona Collier
- School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - Martin O'Hely
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia.,School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - Mimi L K Tang
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Sarath Ranganathan
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Lawrence Gray
- School of Medicine, Deakin University, Geelong, Victoria, Australia.,Barwon Health, Geelong, Victoria, Australia
| | - Ellen Morwitch
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.,National Centre of Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - David Burgner
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Terence Dwyer
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia.,The George Institute for Global Health, Oxford University, Oxford, UK
| | - Peter D Sly
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia.,University of Queensland, South Brisbane, Queensland, Australia
| | | | - Peter Vuillermin
- Murdoch Children's Research Institute, Royal Children's Hospital, University of Melbourne, Parkville, Victoria, Australia.,School of Medicine, Deakin University, Geelong, Victoria, Australia.,Barwon Health, Geelong, Victoria, Australia
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