Novel Blood-Based RNA Profiles can Predict Human Degenerative Cervical Myelopathy
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE223227 | GEO | 2024/10/05
REPOSITORIES: GEO
Similar Datasets
Project description:Novel Blood-Based RNA Profiles can Predict Human Degenerative Cervical Myelopathy
| PRJNA925435 | ENA
Project description:Degenerative myelopathy (DM) is a canine disease very similar to amyotrophic lateral sclerosis (ALS) in humans. We previously showed that DM is a promising model for ALS, as genome-wide association identified a mutation in SOD1, a known ALS gene. In this study, we identify a modifier gene, SP110, which strongly affects overall disease risk and age-of-onset in Pembroke Welsh corgis at risk of DM. Dissecting the complex genetics of this disease in a model organism may lead to new insights about risk and progression in both canine and human patients. 15 DM-affected and 31 unaffected PWC homozygous for SOD1 mutation genotyped using the Illumina CanineHD array (~170,000 SNPs genomewide)
2016-06-01 | E-GEOD-80735 | biostudies-arrayexpress
Project description:Degenerative myelopathy (DM) is a canine disease very similar to amyotrophic lateral sclerosis (ALS) in humans. We previously showed that DM is a promising model for ALS, as genome-wide association identified a mutation in SOD1, a known ALS gene. In this study, we identify a modifier gene, SP110, which strongly affects overall disease risk and age-of-onset in Pembroke Welsh corgis at risk of DM. Dissecting the complex genetics of this disease in a model organism may lead to new insights about risk and progression in both canine and human patients. 15 DM-affected and 10 unaffected Boxers homozygous for SOD1 mutation genotyped using the Illumina CanineHD array (~170,000 SNPs genomewide)
2016-06-01 | E-GEOD-80315 | biostudies-arrayexpress
Project description:Degenerative myelopathy (DM) is a canine disease very similar to amyotrophic lateral sclerosis (ALS) in humans. We previously showed that DM is a promising model for ALS, as genome-wide association identified a mutation in SOD1, a known ALS gene. In this study, we identify a modifier gene, SP110, which strongly affects overall disease risk and age-of-onset in Pembroke Welsh corgis at risk of DM. Dissecting the complex genetics of this disease in a model organism may lead to new insights about risk and progression in both canine and human patients.
2016-06-01 | GSE80315 | GEO
Project description:Degenerative myelopathy (DM) is a canine disease very similar to amyotrophic lateral sclerosis (ALS) in humans. We previously showed that DM is a promising model for ALS, as genome-wide association identified a mutation in SOD1, a known ALS gene. In this study, we identify a modifier gene, SP110, which strongly affects overall disease risk and age-of-onset in Pembroke Welsh corgis at risk of DM. Dissecting the complex genetics of this disease in a model organism may lead to new insights about risk and progression in both canine and human patients.
2016-06-01 | GSE80735 | GEO
Project description:The degeneration of cartilage endplate in cervical disc is considered as a basis of cervical spondylosis. Owing to the important role of post-transcriptional gene regulation in phenotypes and functions of cells, non-coding ribonucleic acid (ncRNA) molecules contributed to the regulation.Degenerated cervical vertebral endplate cartilage specimens were collected from patients with cervical intervertebral disc degeneration (CIDD) that suffered from cervical spondylosis myelopathy, who had received anterior cervical discectomy and fusion (ACDF). CE specimens of healthy subjects were obtained from patients with a cervical fracture who received ACDF at The Second Affiliated Hospital of Nanchang University (Nanchang, China) and adopted SBC human ceRNA array V1.0（4×180K）. The results revealed that expressions of369 lncRNAs, 246 mRNAs, 578 circRNAs were different between degenerated cartilage endplate and healthy cartilage endplate. The functions of differentially expressed lncRNAs and co-expressed potential targeting genes were predicted by analyzing Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analysis. Furthermore, we analyzed and find the co-expression and interaction patterns of different RNAs and possible ceRNA mechanism. The present study provided a systematic perspective on the potential function of non-coding RNAs (ncRNAs) in the degeneration of cartilage endplate in CIDD.
2020-07-04 | GSE153761 | GEO
Project description:(1) Background: Cervical vertigo (CV) represents a controversial entity, with a prevalence ranging from reported high frequency to negation of CV existence. (2) Objectives: To assess the prevalence and cause of vertigo in patients with a manifest form of severe cervical spondylosis-degenerative cervical myelopathy (DCM) with special focus on CV. (3) Methods: The study included 38 DCM patients. The presence and character of vertigo were explored with a dedicated questionnaire. The cervical torsion test was used to verify the role of neck proprioceptors, and ultrasound examinations of vertebral arteries to assess the role of arteriosclerotic stenotic changes as hypothetical mechanisms of CV. All patients with vertigo underwent a detailed diagnostic work-up to investigate the cause of vertigo. (4) Results: Symptoms of vertigo were described by 18 patients (47%). Causes of vertigo included: orthostatic dizziness in eight (22%), hypertension in five (14%), benign paroxysmal positional vertigo in four (11%) and psychogenic dizziness in one patient (3%). No patient responded positively to the cervical torsion test or showed significant stenosis of vertebral arteries. (5) Conclusions: Despite the high prevalence of vertigo in patients with DCM, the aetiology in all cases could be attributed to causes outside cervical spine and related nerve structures, thus confirming the assumption that CV is over-diagnosed.
| S-EPMC8201049 | biostudies-literature
Project description:Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imaging features, and patient characteristics to determine if a patient will benefit from surgery for DCM. We applied a supervised machine learning approach to develop a classification model to predict individual patient outcome after surgery for DCM. Patients undergoing surgery for DCM as a part of the AOSpine CSM-NA or CSM-I prospective, multi-centre studies were included in the analysis. Out of 757 patients 605, 583, and 539 patients had complete follow-up information at 6, 12, and 24 months respectively and were included in the analysis. The primary outcome was improvement in the SF-6D quality of life indicator score by the minimum clinically important difference (MCID). The secondary outcome was improvement in the modified Japanese Orthopedic Association (mJOA) score by the MCID. Predictor variables reflected information about pre-operative disease severity, disease presentation, patient demographics, and comorbidities. A machine learning approach of feature engineering, data pre-processing, and model optimization was used to create the most accurate predictive model of outcome after surgery for DCM. Following data pre-processing 48, 108, and 101 features were chosen for model training at 6, 12, and 24 months respectively. The best performing predictive model used a random forest structure and had an average area under the curve (AUC) of 0.70, classification accuracy of 77%, and sensitivity of 78% when evaluated on a testing cohort that was not used for model training. Worse pre-operative disease severity, longer duration of DCM symptoms, older age, higher body weight, and current smoking status were associated with worse surgical outcomes. We developed a model that predicted positive surgical outcome for DCM with good accuracy at the individual patient level on an independent testing cohort. Our analysis demonstrates the applicability of machine-learning to predictive modeling in spine surgery.
| S-EPMC6448910 | biostudies-literature
Project description:BackgroundDegenerative cervical myelopathy (DCM) is a poorly recognised form of spinal cord injury which arises when degenerative changes in the cervical spine injure the spinal cord. Timely surgical intervention is critical to preventing disability. Despite this, DCM is frequently undiagnosed, and may be misconstrued as normal ageing. For a disease associated with age, we hypothesised that the elderly may represent an underdiagnosed population. This study aimed to evaluate this hypothesis by comparing age-stratified estimates of DCM prevalence based on spinal cord compression (SCC) data with hospital-diagnosed prevalence in the UK.MethodsWe queried the UK Hospital Episode Statistics database for admissions with a primary diagnosis of DCM. Age-stratified incidence rates were calculated and extrapolated to prevalence by adjusting population-level life expectancy to the standardised mortality ratio of DCM. We compared these figures to estimates of DCM prevalence based on the published conversion rate of asymptomatic SCC to DCM.ResultsThe mean prevalence of DCM across all age groups was 0.19% (0.17, 0.21), with a peak prevalence of 0.42% at age 50-54 years. This contrasts with estimates from SCC data which suggest a mean prevalence of 2.22% (0.436, 2.68) and a peak prevalence of 4.16% at age > 79 years.ConclusionsTo our knowledge, this is the first study to estimate the age-stratified prevalence of DCM and estimate underdiagnosis. There is a substantial difference between estimates of DCM prevalence derived from SCC data and UK hospital activity data. This is greatest amongst elderly populations, indicating a potential health inequality.
| S-EPMC9813047 | biostudies-literature