Novel Metabolomic Approach for Identifying Pathology-Specific Biomarkers in Rare Diseases:A Case Study in Oculopharyngeal Muscular Dystrophy (OPMD)

The identification of metabolomic biomarkers relies on the analysis of large cohorts of patients compared to healthy controls followed by the validation of markers in an independent sample set. Indeed, circulating biomarkers should be causally linked to pathology to ensure that changes in the marker precede changes in the disease. However, this approach becomes unfeasible in rare diseases due to the paucity of samples, necessitating the development of new methods for biomarker identification. The present study describes a novel approach that combines samples from both mouse models and human patients to identify biomarkers of OPMD. We initially identified a pathology-specific metabolic fingerprint in murine dystrophic muscle. This metabolic fingerprint was then translated into (paired) murine serum samples and then to human plasma samples. This study identified a panel of nine candidate biomarkers that could predict muscle pathology with a sensitivity of 74.3% and specificity of 100% in a random forest model. These findings demonstrate that the proposed approach can identify biomarkers with good predictive performance and a higher degree of confidence in their relevance to pathology than markers identified in a small cohort of human samples alone. Therefore, this approach has a high potential utility for identifying circulating biomarkers in rare diseases.</p

Novel Metabolomic Approach for Identifying Pathology-Specific Biomarkers in Rare Diseases:A Case Study in Oculopharyngeal Muscular Dystrophy (OPMD)

The identification of metabolomic biomarkers relies on the analysis of large cohorts of patients compared to healthy controls followed by the validation of markers in an independent sample set. Indeed, circulating biomarkers should be causally linked to pathology to ensure that changes in the marker precede changes in the disease. However, this approach becomes unfeasible in rare diseases due to the paucity of samples, necessitating the development of new methods for biomarker identification. The present study describes a novel approach that combines samples from both mouse models and human patients to identify biomarkers of OPMD. We initially identified a pathology-specific metabolic fingerprint in murine dystrophic muscle. This metabolic fingerprint was then translated into (paired) murine serum samples and then to human plasma samples. This study identified a panel of nine candidate biomarkers that could predict muscle pathology with a sensitivity of 74.3% and specificity of 100% in a random forest model. These findings demonstrate that the proposed approach can identify biomarkers with good predictive performance and a higher degree of confidence in their relevance to pathology than markers identified in a small cohort of human samples alone. Therefore, this approach has a high potential utility for identifying circulating biomarkers in rare diseases.</p

Diagnostics of short tandem repeat expansion variants using massively parallel sequencing and componential tools

Short tandem repeats (STRs) are scattered throughout the human genome. Some STRs, like trinucleotide repeat expansion (TRE) variants, cause hereditable disorders. Unambiguous molecular diagnostics of TRE disorders is hampered by current technical limitations imposed by traditional PCR and DNA sequencing methods. Here we report a novel pipeline for TRE variant diagnosis employing the massively parallel sequencing (MPS) combined with an opensource software package (FDSTools), which together are designed to distinguish true STR sequences from STR sequencing artifacts. We show that this approach can improve TRE diagnosis, such as Oculopharyngeal muscular dystrophy (OPMD). OPMD is caused by a trinucleotide expansion in the PABPN1 gene. A short GCN expansion, (GCN[10]), coding for a 10 alanine repeat is not pathogenic, but an alanine expansion is pathogenic. Applying this novel procedure in a Dutch OPMD patient cohort, we found expansion variants from GCN[11] to GCN[16], with the GCN[16] as the most abundant variant. The repeat expansion length did not correlate with clinical features. However, symptom severity was found to correlate with age and with the initial affected muscles, suggesting that aging and muscle-specific factors can play a role in modulating OPMD.Molecular Technology and Informatics for Personalised Medicine and HealthFunctional Genomics of Muscle, Nerve and Brain Disorder

Muscle MRI in a large cohort of patients with oculopharyngeal muscular dystrophy

Background and objective: Oculopharyngeal muscular dystrophy (OPMD) is a genetic disorder caused by an abnormal expansion of GCN triplets within the PABPN1 gene. Previous descriptions have focused on lower limb muscles in small cohorts of patients with OPMD, but larger imaging studies have not been performed. Previous imaging studies have been too small to be able to correlate imaging findings to genetic and clinical data. Methods: We present cross-sectional, T1-weighted muscle MRI and CT-scan data from 168 patients with genetically confirmed OPMD. We have analysed the pattern of muscle involvement in the disease using hierarchical analysis and presented it as heatmaps. Results of the scans were correlated with genetic and clinical data. Results: Fatty replacement was identified in 96.7% of all symptomatic patients. The tongue, the adductor magnus and the soleus were the most commonly affected muscles. Muscle pathology on MRI correlated positively with disease duration and functional impairment. Conclusions: We have described a pattern that can be considered characteristic of OPMD. An early combination of fat replacement in the tongue, adductor magnus and soleus can be helpful for differential diagnosis. The findings suggest the natural history of the disease from a radiological point of view. The information generated by this study is of high diagnostic value and important for clinical trial development