Anu Sooda

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.

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 DRβ1 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.