Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p < 0.05) in Plasma cells, T cells regulatory (Tregs), and Macrophages M2 were observed between diagnostic groups. Microglia cells were highly correlated with lipid metabolism functions.ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy

Global incidence trends of early-onset colorectal cancer and related exposures in early-life: an ecological analysis based on the GBD 2019

BackgroundThe incidence of early-onset colorectal cancer (EOCRC) is increasing globally. This study aims to describe the temporal trends of incidence and explore related risk exposures in early-life at the country level based on the GBD 2019.MethodsData on the incidence and attributable risk factors of EOCRC were obtained from the GBD 2019. Temporal trends of age-standardized incidence were evaluated by average annual percentage change (AAPC). Early-life exposures were indicated as summary exposure values (SEV) of selected factors, SDI and GDP per capita in previous decades and at ages 0–4, 5–9, 10–14 and 15–19 years. Weighted linear or non-linear regressions were applied to evaluate the ecological aggregate associations of the exposures with incidences of EOCRC.ResultsThe global age-standardized incidence of EOCRC increased from 3.05 (3.03, 3.07) to 3.85 (3.83, 3.86) per 100,000 during 1990 and 2019. The incidence was higher in countries with high socioeconomic levels, and increased drastically in countries in East Asia and Caribbean, particularly Jamaica, Saudi Arabia and Vietnam. The GDP per capita, SDI, and SEVs of iron deficiency, alcohol use, high body-mass index, and child growth failure in earlier years were more closely related with the incidences of EOCRC in 2019. Exposures at ages 0–4, 5–9, 10–14 and 15–19 years were also associated with the incidences, particularly for the exposures at ages 15–19 years.ConclusionThe global incidence of EOCRC increased during past three decades. The large variations at regional and national level may be related with the distribution of risk exposures in early life

Characterization of Conformation and Locations of C–F Bonds in Graphene Derivative by Polarized ATR-FTIR

It is still a challenge to explore the orientation and location of chemical groups in the two-dimensional derivative of graphene. In this study, polarized attenuated total reflectance Fourier transform infrared spectroscopy (polarized ATR-FTIR) was employed to investigate the orientation and location of C–F groups in the corresponding graphene derivative sheets, which facilitates building a relationship between the bonding nature and fine structure. There were two types of C–F bonding, (C–F)_I and (C–F)_II, in fluorinated graphene sheets. It was found that (C–F)_II bonds were linked at the coplanar carbon atoms in the weakly fluorinated region (C_<i>x</i>F, <i>x</i> ≥ 2), whereas the (C–F)_I bonds cluster at the strongly deformed carbon framework with a F/C ratio of about 1. The thermostability of (C–F)_II is lower than that of (C–F)_I bonds. This is because the coplanar structure of the weakly fluorinated region tends to transform to the planar aromatic ring with the breaking of the C–F bond as compared with the strong fluorinated nonplanar region

Data_Sheet_2_Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis.ZIP

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.</p

Data_Sheet_1_Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis.ZIP

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.</p

Data_Sheet_3_Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis.ZIP

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.</p

Table_1_Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis.XLSX

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy.</p