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Background This study aimed to examine multi‐dimensional MRI features’ predictability on survival outcome and associations with differentially expressed Genes ( RNA Sequencing) in groups of glioblastoma multiforme ( GBM ) patients. Methods Radiomics features were extracted from segmented lesions of T2‐ FLAIR MRI data of 137 GBM patients. Radiomics features include intensity, shape and textural features in seven classes were included in the analysis. Patients were divided into two groups depending on their survival time (shorter or longer than 1‐year survival). Four different machine learning algorithms were implemented to construct the prediction models. Features with top importance (importance >0.04) were selected to construct the prediction model using the model with the best performance. The interactions between image features and genomics were then analysed with Pearson's correlation analysis. Results The GBDT model with 72 features with highest importance had the highest accuracy of 0.81 on both short and long survival time classes, and the area under the curve ( AUC ) of the receiver operative characteristic ( ROC ) of the short and long survival time class were 0.79 and 0.81. Six metagenes showed significant interactive effect ( P < 0.05), and Pearson's correlation analysis revealed that three of these metagenes ( TIMP 1 , ROS 1 EREG ) showed moderate (0.3 < | r | < 0.5) or high correlation (| r | > 0.5) with image features. Conclusion Radiogenomics analysis shows that MRI features are predictive of survival outcomes, and image features are highly associated with selective metagenes. Radiogenomics analysis is a useful method for optimizing clinical diagnosis and selecting effective treatments.

Hereditary spastic paraplegias (HSPs) encompass a clinically and genetically heterogeneous group of neurodegenerative disorders. Recently, mutations in fatty acid 2-hydroxylase gene (FA2H) have been identified responsible for HSPs type 35 (SPG35). This study aims to define the contribution of FA2H to Chinese autosomal recessive HSP (AR-HSP) patients and provide insights into the enzymatic functions of the novel mutations. Direct sequencing of FA2H was conducted in 31 AR-HSP families and 55 sporadic cases without SPG11, SPG15, SPG5 and SPG7 gene mutations. Enzymatic activity of the mutated proteins was further examined. Three novel mutations were found in two Chinese families, including two compound heterozygous mutations (c.388C>T/p.L130F and c.506+6C>G) and one homozygous mutation (c.230T>G/p.L77R). The c.506+6C>G splice-site mutation led to the deletion of exon 3. Measurement of enzymatic functions revealed a significant reduction in the enzymatic activity of FA2H associated with p.L130F and p.L77R. Overall, our data widens the spectrum of the mutations on FA2H, and functional analyses indicate that these mutations severely impair the enzymatic activity of FA2H. Furthermore, frequency analysis shows that SPG35 is the second most common subtype of AR-HSP in China.

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