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Record W2765189091 · doi:10.1093/rheumatology/kex392

Autoantibodies to the survival of motor neuron complex in a patient with necrotizing autoimmune myopathy

2017· letter· en· W2765189091 on OpenAlexafffund
Adam Amlani, Glen Hazlewood, Leslie E. Hamilton, Minoru Satoh, Marvin J. Fritzler

Bibliographic record

VenueLara D. Veeken · 2017
Typeletter
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicineAutoantibodyMyopathyMotor neuronImmunologyPathologyAntibodyDisease

Abstract

fetched live from OpenAlex

Rheumatology key message Autoantibodies to the survival motor neuron complex may be a biomarker of necrotizing autoimmune myopathy. Sir, necrotizing autoimmune myopathies (NAMs) are a subset of autoimmune inflammatory myopathies characterized by proximal muscle weakness and distinctive pathology that is usually associated with autoantibodies to signal recognition particles (SRPs) and HMG-CoA reductase (HMGCR). [1–4]. We report the case of a previously healthy 27-year-old female with a 5 month history of arthritis and RP diagnosed by her general practitioner in an outpatient setting. At that time, her workup consisted of an RF that was slightly elevated at 22 kU/l (normal <20 kU/l), but anti-CCP and CRP were within normal limits. No therapeutic intervention was prescribed at that time and no further workup was completed until she presented to hospital 5 months later following gastroenteritis of undetermined aetiology accompanied by mild weakness. At that time her ANA was highly positive on HEp-2 substrate (titre 1:5120) with coarse nuclear speckled and nuclear dots staining patterns. Further testing revealed a high anti-U1-RNP titre and elevated creatine kinase (1729 U/l). A electromyogram in three separate muscle groups showed normal recruitment, no denervation and normal motor units with no myopathic units noted. One area of a single positive sharp wave was noted in the iliopsoas muscle. At presentation, her medications included birth control pills and occasional naproxen for joint pain. She had no known exposures to statins. Her only relevant family history included maternal Graves’ disease. She was treated with prednisone 15 mg orally twice daily and HCQ and completely recovered in 4 days. Pulmonary function testing during this admission showed a reduction in her diffusing capacity of carbon monoxide at 75% of the predicted value. She was admitted to hospital 30 days later with progressive proximal muscle weakness and respiratory distress. A CT scan of her chest was reported as unremarkable, with no evidence of pulmonary embolism or interstitial lung disease. A muscle biopsy showed diffusely scattered necrotizing and regenerating myofibres, histiocytic but minimal lymphocytic inflammation, upregulation of major histocompatibility complex class 1 and sarcolemmal deposition of complement (C5b-9), compelling evidence for the diagnosis of NAM. She received high-dose pulse corticosteroids and IVIG, but decompensated on her sixth day of admission and required intubation for respiratory failure. Her creatine kinase rose to >23 000 U/l. Plasmapheresis and CYC were initiated, but despite maximal intervention, she was diagnosed with disseminated intravascular coagulation, developed pulseless electrical activity cardiac arrest and died on day 14 after her admission. At autopsy, findings were again consistent with NAM and also showed myocardial necrosis without a particular vascular territory as well as a transmural acute ulcer in the terminal ileum consistent with ischaemia. Additional serology was negative for SRP, HMGCR, PM/Scl-100/PM/Scl-75, SSA/Ro60, Ro52/TRIM21, dsDNA, Jo-1 (histidyl tRNA synthetase) and other myositis-related autoantibodies (PL-7, PL-12, Mi2, Mi2‐α, Mi2-β, MDA5, NXP2, TIF1-γ, Ku, EJ, OJ). However, high-titre autoantibodies to the survival of motor neuron (anti-SMN) complex proteins and U1-RNP were identified by immunoprecipitation (IP) of metabolically labelled cell lysates (Fig. 1). Immunoprecipitation of patient sera revealed anti-SMN reactivity Radiolabeled human K652 cell lysates were prepared and then immunoprecipitated (IP) as previously described [5] with control human sera bearing antibodies to signal recognition particle (SRP), U1 and U2 RNP and SMN (SMN, gemin-2, -3 and -4). IP reactivity resolved on (a) 8% and (b) 12.5% gels. The 12.5% gels are used to provide better resolution of U1-RNP proteins. Sera collected from the patient before (lane 1) and after (lane 2) plasmapheresis demonstrated strong reactivity with U1-A, U1-70k, U1-C, D1/D2/D3, B/B′ and E, F and G proteins (U1RNP components) and remarkably high reactivity with SMN, gemin-2, -3 and -4, but not SRP72/69 or SRP54. This case was unique with respect to both the anti-SMN autoantibodies found as well as the severity of the myopathy and rapid time course of decompensation. To our knowledge, there have been no publications of autoantibodies directed towards the SMN complex in NAM. A single previous publication reported autoantibodies to the SMN complex in patients with PM and PM/SSc overlap [5], but features of NAM were not reported. Defects in the SMN gene are associated with a spinal muscular atrophy genetic disorder [6]. Our patient also had antibodies to U1-RNP components and clinical features of MCTD (RP, arthritis, myositis and high-titre U1-RNP). Previous studies have indicated that 20% of patients with anti-U1-RNP as detected by RNA IP techniques had histological evidence of NAM [7], but because RNA IP was used to detect autoantibodies, anti-SMN would not have been detected in that study. It remains unclear as to why autoantibodies to specific intracellular antigens SRP, HMGCR and tRNA synthetase are so closely linked to predictable clinical features and what role (if any) these autoantibodies play in the development of these features and in the pathogenesis of the associated disease processes [8]. The questions of whether these autoantibodies are produced following initial tissue damage or cell lysis and/or antedate the clinical presentation of NAM requires further study. Given the uniqueness of the clinical presentation of this patient and the IP results, we believe that, along with antibodies to SRP and HMGCR, autoantibodies to the SMN complex may serve as an additional biomarker for NAM. Since anti-SMNs are the subject of a single publication to date, where they were found in only ∼5% of the PM sera studied [6], further concerted research of a large multicentre cohort is needed to investigate a link between these autoantibodies and NAM and other diagnostic and prognostic features. The authors acknowledge the technical assistance and expertise of Haiyan Hou and Meifeng Zhang (University of Calgary) and Tomoko Hasegawa (University of Occupational and Environmental Health, Kitakyushu, Japan). M.S. was supported by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (KAKENHI) grant number 15K08790 to M.S. G.H. is supported by a Canadian Institutes of Health Research New Investigator Salary Award and an Arthritis Society Young Investigator Salary Award. Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article. Disclosure statement: M.F. is a consultant to Inova Diagnostics (San Diego, CA, USA) and Werfen International (Barcelona, Spain) and has received gifts in kind from Euroimmun (Lübeck, Germany) and Alexion Pharma Canada. All other authors have declared no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0110.006
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.253
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations15
Published2017
Admission routes2
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