Circulating microRNA expression signatures accurately discriminate myalgic encephalomyelitis from fibromyalgia and comorbid conditions.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and fibromyalgia (FM) are two chronic complex diseases with overlapping symptoms affecting multiple systems and organs over time. Due to the absence of validated biomarkers and similarity in symptoms, both disorders are misdiagnosed, and the comorbidity of the two is often unrecognized. Our study aimed to investigate the expression profiles of 11 circulating miRNAs previously associated with ME/CFS pathogenesis in FM patients and individuals with a comorbid diagnosis of FM associated with ME/CFS (ME/CFS + FM), and matched sedentary healthy controls. Whether these 11 circulating miRNAs expression can differentiate between the two disorders was also examined. Our results highlight differential circulating miRNAs expression signatures between ME/CFS, FM and ME/CFS + FM, which also correlate to symptom severity between ME/CFS and ME/CFS + FM groups. We provided a prediction model, by using a machine-learning approach based on 11 circulating miRNAs levels, which can be used to discriminate between patients suffering from ME/CFS, FM and ME/CFS + FM. These 11 miRNAs are proposed as potential biomarkers for discriminating ME/CFS from FM. The results of this study demonstrate that ME/CFS and FM are two distinct illnesses, and we highlight the comorbidity between the two conditions. Proper diagnosis of patients suffering from ME/CFS, FM or ME/CFS + FM is crucial to elucidate the pathophysiology of both diseases, determine preventive measures, and establish more effective treatments.

Upregulation of microRNA-96-5p is associated with adolescent idiopathic scoliosis and low bone mass phenotype.

Bone densitometry revealed low bone mass in patients with adolescent idiopathic scoliosis (AIS) and its prognostic potential to predict curve progression. Recent studies showed differential circulating miRNAs in AIS but their diagnostic potential and links to low bone mass have not been well-documented. The present study aimed to compare miRNA profiles in bone tissues collected from AIS and non-scoliotic subjects, and to explore if the selected miRNA candidates could be useful diagnostic biomarkers for AIS. Microarray analysis identified miR-96-5p being the most upregulated among the candidates. miR-96-5p level was measured in plasma samples from 100 AIS and 52 healthy girls. Our results showed significantly higher plasma levels of miR-96-5p in AIS girls with an area under the curve (AUC) of 0.671 for diagnostic accuracy. A model that was composed of plasma miR-96-5p and patient-specific parameters (age, body weight and years since menarche) gave rise to an improved AUC of 0.752. Ingenuity Pathway Analysis (IPA) indicated functional links between bone metabolic pathways and miR-96-5p. In conclusion, differentially expressed miRNAs in AIS bone and plasma samples represented a new source of disease biomarkers and players in AIS etiopathogenesis, which required further validation study involving AIS patients of both genders with long-term follow-up.

Profile of circulating microRNAs in myalgic encephalomyelitis and their relation to symptom severity, and disease pathophysiology.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic disease, rooted in multi-system dysfunctions characterized by unexplained debilitating fatigue. Post-exertional malaise (PEM), defined as the exacerbation of the patient's symptoms following minimal physical or mental stress, is a hallmark of ME/CFS. While multiple case definitions exist, there is currently no well-established biomarkers or laboratory tests to diagnose ME/CFS. Our study aimed to investigate circulating microRNA expression in severely ill ME/CFS patients before and after an innovative stress challenge that stimulates PEM. Our findings highlight the differential expression of eleven microRNAs associated with a physiological response to PEM. The present study uncovers specific microRNA expression signatures associated with ME/CFS in response to PEM induction and reports microRNA expression patterns associated to specific symptom severities. The identification of distinctive microRNA expression signatures for ME/CFS through a provocation challenge is essential for the elucidation of the ME/CFS pathophysiology, and lead to accurate diagnoses, prevention measures, and effective treatment options.

A validated composite model to predict risk of curve progression in adolescent idiopathic scoliosis.

BACKGROUND: In adolescent idiopathic scoliosis (AIS), the continuous search for effective prognostication of significant curve progression at the initial clinical consultation to inform decision for timely treatment and to avoid unnecessary overtreatment remains a big challenge as evidence of the multifactorial etiopathogenic nature is increasingly reported. This study aimed to formulate a composite model composed of clinical parameters and circulating markers in the prediction of curve progression. METHOD: This is a two-phase study consisting of an exploration cohort (120 AIS, mean Cobb angle of 25°± 8.5 at their first clinical visit) and a validation cohort (51 AIS, mean Cobb angle of 23° ± 5.0° at the first visit). Patients with AIS were followed-up for a minimum of six years to formulate a composite model for prediction. At the first visit, clinical parameters were collected from routine clinical practice, and circulating markers were assayed from blood. FINDING: We constructed the composite predictive model for curve progression to severe Cobb angle > 40° with a high HR of 27.9 (95% CI of 6.55 to 119.16). The area under curve of the composite model is higher than that of individual parameters used in current clinical practice. The model was validated by an independent cohort and achieved a sensitivity of 72.7% and a specificity of 90%. INTERPRETATION: This is the first study proposing and validating a prognostic composite model consisting of clinical and circulating parameters which could quantitatively evaluate the probability of curve progression to a severe curvature in AIS at the initial consultation. Further validation in clinic will facilitate application of composite model in assisting objective clinical decision.