Electron microscopy in the diagnosis of Ehlers–Danlos syndromes: correlation with clinical and genetic investigations
Bibliographic record
Abstract
BACKGROUND: The Ehlers-Danlos syndromes (EDS) consist of 13 subtypes with overlapping features including joint hypermobility, skin and vascular fragility and generalized connective tissue friability. As DNA analysis has become the gold standard for investigation of EDS, transmission electron microscopy (TEM) in clinical practice is decreasing. However, owing to the use of next-generation sequencing, the frequency of variants of uncertain significance (VUS) identified using DNA analysis is increasing. We hypothesized that TEM can provide evidence for or against pathogenicity of VUS. OBJECTIVES: The aim of this study was to evaluate the role of TEM in the diagnosis of EDS subtypes. METHODS: Data were collected from patients who underwent a skin biopsy between October 2012 and March 2017 at the London EDS National Diagnostic Service. TEM biopsies were categorized as 'normal' or 'abnormal' according to the description and conclusion in the TEM reports. Definitive diagnoses were reached via a combination of clinical features, structural and functional studies and DNA investigations. RESULTS: The analysis included 177 patients, comprising 30 abnormal and 147 normal TEM reports. A definitive diagnosis of monogenic EDS subtypes was made in 24 patients. Overall, 17 of these 24 patients (71%) had an abnormal biopsy report and seven (29%) had a normal biopsy report. No TEM findings were specifically associated with any EDS subtype, although collagen flowers were present in most patients with a genetically confirmed diagnosis of classical EDS. CONCLUSIONS: TEM analysis of collagen structure may have the potential to provide evidence for or against the pathogenicity of a VUS, but more work is needed to establish a clear role for TEM in this process. What's already known about this topic? Collagen fibril abnormalities can be seen in several Ehlers-Danlos syndrome (EDS) subtypes. What does this study add? This study provides clinical data, transmission electron microscopy (TEM) data and molecular data of one of the largest groups of patients suspected to have a monogenetic EDS subtype. No TEM findings were specifically associated with an EDS subtype. There was a higher percentage (71%) of abnormal biopsy findings in patients with a definitive diagnosis of a monogenetic EDS subtype and where a class 4/5 genetic variant was present.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".