RESUMEN
Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of muscle disorders including adult and juvenile dermatomyositis, polymyositis, immune-mediated necrotising myopathy and sporadic inclusion body myositis, all of which present with variable symptoms and disease progression. The identification of effective biomarkers for IIMs has been challenging due to the heterogeneity between IIMs and within IIM subgroups, but recent advances in machine learning (ML) techniques have shown promises in identifying novel biomarkers. This paper reviews recent studies on potential biomarkers for IIM and evaluates their clinical utility. We also explore how data analytic tools and ML algorithms have been used to identify biomarkers, highlighting their potential to advance our understanding and diagnosis of IIM and improve patient outcomes. Overall, ML techniques have great potential to revolutionize biomarker discovery in IIMs and lead to more effective diagnosis and treatment.
Asunto(s)
Enfermedades Autoinmunes , Dermatomiositis , Miositis , Adulto , Humanos , Miositis/diagnóstico , Miositis/terapia , Dermatomiositis/diagnóstico , Biomarcadores , Progresión de la EnfermedadRESUMEN
OBJECTIVES: Inclusion body myositis (IBM) is a progressive inflammatory-degenerative muscle disease of older individuals, with some patients producing anti-cytosolic 5'-nucleotidase 1A (NT5C1A, aka cN1A) antibodies. Human Leukocyte Antigens (HLA) is the highest genetic risk factor for developing IBM. In this study, we aimed to further define the contribution of HLA alleles to IBM and the production of anti-cN1A antibodies. METHODS: We HLA haplotyped a Western Australian cohort of 113 Caucasian IBM patients and 112 ethnically matched controls using Illumina next-generation sequencing. Allele frequency analysis and amino acid alignments were performed using the Genentech/MiDAS bioinformatics package. Allele frequencies were compared using Fisher's exact test. Age at onset analysis was performed using the ggstatsplot package. All analysis was carried out in RStudio version 1.4.1717. RESULTS: Our findings validated the independent association of HLA-DRB1*03:01:01 with IBM and attributed the risk to an arginine residue in position 74 within the DRß1 protein. Conversely, DRB4*01:01:01 and DQA1*01:02:01 were found to have protective effects; the carriers of DRB1*03:01:01 that did not possess these alleles had a fourteenfold increased risk of developing IBM over the general Caucasian population. Furthermore, patients with the abovementioned genotype developed symptoms on average five years earlier than patients without. We did not find any HLA associations with anti-cN1A antibody production. CONCLUSIONS: High-resolution HLA sequencing more precisely characterised the alleles associated with IBM and defined a haplotype linked to earlier disease onset. Identification of the critical amino acid residue by advanced biostatistical analysis of immunogenetics data offers mechanistic insights and future directions into uncovering IBM aetiopathogenesis.
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Miositis por Cuerpos de Inclusión , Miositis , Humanos , Miositis por Cuerpos de Inclusión/genética , Genotipo , Haplotipos , Arginina , Australia , Antígenos HLA , Cadenas HLA-DRB1/genética , AlelosRESUMEN
Objective: Inclusion body myositis (IBM) is a progressive late-onset muscle disease characterised by preferential weakness of quadriceps femoris and finger flexors, with elusive causes involving immune, degenerative, genetic and age-related factors. Overlapping with normal muscle ageing makes diagnosis and prognosis problematic. Methods: We characterised peripheral blood leucocytes in 81 IBM patients and 45 healthy controls using flow cytometry. Using a random forest classifier, we identified immune changes in IBM compared to HC. K-means clustering and the random forest one-versus-rest model classified patients into three immunophenotypic clusters. Functional outcome measures including mTUG, 2MWT, IBM-FRS, EAT-10, knee extension and grip strength were assessed across clusters. Results: The random forest model achieved a 94% AUC ROC with 82.76% specificity and 100% sensitivity. Significant differences were found in IBM patients, including increased CD8+ T-bet+ cells, CD4+ T cells skewed towards a Th1 phenotype and altered γδ T cell repertoire with a reduced proportion of Vγ9+Vδ2+ cells. IBM patients formed three clusters: (i) activated and inflammatory CD8+ and CD4+ T-cell profile and the highest proportion of anti-cN1A-positive patients in cluster 1; (ii) limited inflammation in cluster 2; (iii) highly differentiated, pro-inflammatory T-cell profile in cluster 3. Additionally, no significant differences in patients' age and gender were detected between immunophenotype clusters; however, worsening trends were detected with several functional outcomes. Conclusion: These findings unveil distinct immune profiles in IBM, shedding light on underlying pathological mechanisms for potential immunoregulatory therapeutic development.
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Introduction: Inclusion body myositis (IBM) is a progressive inflammatory myopathy characterised by skeletal muscle infiltration and myofibre invasion by CD8+ T lymphocytes. In some cases, IBM has been reported to be associated with a systemic lymphoproliferative disorder of CD8+ T cells exhibiting a highly differentiated effector phenotype known as T cell Large Granular Lymphocytic Leukemia (T-LGLL). Methods: We investigated the incidence of a CD8+ T-LGL lymphoproliferative disorder in 85 IBM patients and an aged-matched group of 56 Healthy Controls (HC). Further, we analysed the phenotypical characteristics of the expanded T-LGLs and investigated whether their occurrence was associated with any particular HLA alleles or clinical characteristics. Results: Blood cell analysis by flow cytometry revealed expansion of T-LGLs in 34 of the 85 (40%) IBM patients. The T cell immunophenotype of T-LGLHIGH patients was characterised by increased expression of surface molecules including CD57 and KLRG1, and to a lesser extent of CD94 and CD56 predominantly in CD8+ T cells, although we also observed modest changes in CD4+ T cells and γδ T cells. Analysis of Ki67 in CD57+ KLRG1+ T cells revealed that only a small proportion of these cells was proliferating. Comparative analysis of CD8+ and CD4+ T cells isolated from matched blood and muscle samples donated by three patients indicated a consistent pattern of more pronounced alterations in muscles, although not significant due to small sample size. In the T-LGLHIGH patient group, we found increased frequencies of perforin-producing CD8+ and CD4+ T cells that were moderately correlated to combined CD57 and KLRG1 expression. Investigation of the HLA haplotypes of 75 IBM patients identified that carriage of the HLA-C*14:02:01 allele was significantly higher in T-LGLHIGH compared to T-LGLLOW individuals. Expansion of T-LGL was not significantly associated with seropositivity patient status for anti-cytosolic 5'-nucleotidase 1A autoantibodies. Clinically, the age at disease onset and disease duration were similar in the T-LGLHIGH and T-LGLLOW patient groups. However, metadata analysis of functional alterations indicated that patients with expanded T-LGL more frequently relied on mobility aids than T-LGLLOW patients indicating greater disease severity. Conclusion: Altogether, these results suggest that T-LGL expansion occurring in IBM patients is correlated with exacerbated immune dysregulation and increased disease burden.
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Leucemia Linfocítica Granular Grande , Miositis por Cuerpos de Inclusión , Humanos , Linfocitos T CD8-positivos , Miositis por Cuerpos de Inclusión/metabolismo , Músculo Esquelético/metabolismo , Fenotipo , Gravedad del PacienteRESUMEN
Objectives: Sporadic Inclusion Body Myositis (IBM) is an inflammatory muscle disease affecting individuals over the age of 45, leading to progressive muscle wasting, disability and loss of independence. Histologically, IBM is characterised by immune changes including myofibres expressing major histocompatibility complex molecules and invaded by CD8+ T cells and macrophages, and by degenerative changes including protein aggregates organised in inclusion bodies, rimmed vacuoles and mitochondrial abnormalities. There is currently no cure, and regular exercise is currently the only recognised treatment effective at limiting muscle weakening, atrophy and loss of function. Testosterone exerts anti-inflammatory effects, inhibiting effector T-cell differentiation and pro-inflammatory cytokine production. Methods: We conducted a double-blind, placebo-controlled, cross-over trial in men with IBM, to assess whether a personalised progressive exercise training combined with application of testosterone, reduced the inflammatory immune response associated with this disease over and above exercise alone. To assess intervention efficacy, we immunophenotyped blood immune cells by flow cytometry, and measured serum cytokines and chemokines by Luminex immunoassay. Results: Testosterone supplementation resulted in modest yet significant count reduction in the classical monocyte subset as well as eosinophils. Testosterone-independent immunoregulatory effects attributed to exercise included altered proportions of some monocyte, T- and B-cell subsets, and reduced IL-12, IL-17, TNF-α, MIP-1ß and sICAM-1 in spite of interindividual variability. Conclusion: Overall, our findings indicate anti-inflammatory effects of exercise training in IBM patients, whilst concomitant testosterone supplementation provides some additional changes. Further studies combining testosterone and exercise would be worthwhile in larger cohorts and longer testosterone administration periods.
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In inflammatory myopathies, the self-reactive immune cells involved in muscle aggression have been studied mostly using histological assessment of muscle biopsy sections; this methodology provides the advantage of visualizing and identifying cells within the tissue, but it does not allow further investigation. To gain access to live and isolated cells, many studies utilized blood samples; however, in the absence of biological tools to discriminate the leukocytes associated with the autoimmune process from those that emerged from responses against pathogens, the information observed on circulating immune cells often lacks in specificity, and thus result interpretation may prove difficult. In order to selectively retrieve self-reactive immune cells, we developed a protocol to isolate live leukocytes from human muscle biopsies, which allows for further analysis using a large range of methodologies. The protocol uses enzymatic digestion to release live leukocytes from freshly collected skeletal muscle samples, followed by filtration and separation of the leukocytes from the myocytes by density gradient centrifugation. The isolated cells can be submitted immediately to various analysis strategies to characterize ex vivo the specific cellular and molecular mechanisms responsible for self-directed immune muscle aggression or may be placed in culture for expansion.