Dataset Information

The Identification of Novel Biomarkers Is Required to Improve Adult SMA Patient Stratification, Diagnosis and Treatment.

ABSTRACT: Spinal muscular atrophy (SMA) is currently classified into five different subtypes, from the most severe (type 0) to the mildest (type 4) depending on age at onset, best motor function achieved, and copy number of the SMN2 gene. The two recent approved treatments for SMA patients revolutionized their life quality and perspectives. However, upon treatment with Nusinersen, the most widely administered therapy up to date, a high degree of variability in therapeutic response was observed in adult SMA patients. These data, together with the lack of natural history information and the wide spectrum of disease phenotypes, suggest that further efforts are needed to develop precision medicine approaches for all SMA patients. Here, we compile the current methods for functional evaluation of adult SMA patients treated with Nusinersen. We also present an overview of the known molecular changes underpinning disease heterogeneity. We finally highlight the need for novel techniques, i.e., -omics approaches, to capture phenotypic differences and to understand the biological signature in order to revise the disease classification and device personalized treatments.

SUBMITTER: Smeriglio P

PROVIDER: S-EPMC7564782 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Identification of Novel Biomarkers Is Required to Improve Adult SMA Patient Stratification, Diagnosis and Treatment.

Smeriglio Piera P Langard Paul P Querin Giorgia G Biferi Maria Grazia MG

Journal of personalized medicine 20200729 3

Spinal muscular atrophy (SMA) is currently classified into five different subtypes, from the most severe (type 0) to the mildest (type 4) depending on age at onset, best motor function achieved, and copy number of the <i>SMN2</i> gene. The two recent approved treatments for SMA patients revolutionized their life quality and perspectives. However, upon treatment with Nusinersen, the most widely administered therapy up to date, a high degree of variability in therapeutic response was observed in a ...[more]

PMID: 32751151

Similar Datasets

Project description:ObjectivePostmenopausal osteoporosis (PMOP) is one of the most commonly occurring conditions worldwide and is characterized by estrogen deficiency as well as persistent calcium loss with age. The aim of our study was to identify significant ferroptosis-associated biomarkers for PMOP.Methods and materialsWe obtained our training dataset from the Gene Expression Omnibus (GEO) database using GSE56815 expression profiling data. Meanwhile, we extracted ferroptosis-associated genes for further analysis. Differentially expressed ferroptosis-associated genes (DEFAGs) between OP patients and normal controls were selected using the "limma" package. We established a ferroptosis-associated gene signature using training models, specifically, random forest (RF) and support vector machine (SVM) models. It was further validated in another dataset (GSE56814) which also showed a high AUC: 0.98, indicating high diagnostic value. Using consensus clustering, the OP patient subtypes were identified. A ferroptosis associated gene (FAG)-Scoring scheme was developed by PCA. The important candidate genes associated with OP were also compared between different ferrclusters and geneclusters.ResultsThere were significant DEFAGs acquired, of which five (HMOX1, HAMP, LPIN1, MAP3K5, FLT3) were selected for establishing a ferroptosis-associated gene signature. Analyzed from the ROC curve, our established RF model had a higher AUC value than the SVM model (RF model AUC:1.00). Considering these results, the established RF model was chosen to be the most appropriate training model. Later, based on the expression levels of the five DEFAGs, a clinical application nomogram was established. The OP patients were divided into two subtypes (ferrcluster A, B and genecluster A, B, respectively) according to the consensus clustering method based on DEFAGs and differentially expressed genes (DEGs). Ferrcluster B and genecluster B had higher ferroptosis score than ferrcluster A and genecluster A, respectively. The expression of COL1A1 gene was significantly higher in ferrcluster B and gencluster B compared with ferrcluster A and gencluster A, respectively, while there is no statistical difference in term of VDR gene, COL1A2 genes, and PTH gene expressions between ferrcluster A and B, together with gencluster A and B.ConclusionsOn the basis of five explanatory variables (HMOX1, HAMP, LPIN1, MAP3K5 and FLT3), we developed a diagnostic ferroptosis-associated gene signature and identified two differently categorized OP subtypes that may potentially be applied for the early diagnosis and individualized treatment of PMOP. The ER gene, VDR gene, IL-6 gene, COL1A1 and COL1A2 genes, and PTH gene are important candidate gene of OP, however, more studies are still anticipated to further elucidate the relationship between these genes and ferroptosis in OP.

Dataset Information

The Identification of Novel Biomarkers Is Required to Improve Adult SMA Patient Stratification, Diagnosis and Treatment.

Publications

The Identification of Novel Biomarkers Is Required to Improve Adult SMA Patient Stratification, Diagnosis and Treatment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets