Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis.
Lin WangJiaming SuZhongjie LiuShaowei DingYaotan LiBaoluo HouYuxin HuZhaoxi DongJingyi TangHongfang LiuWeijing LiuPublished in: BioData mining (2024)
Our study provides new insights into the role of immune-related biomarkers in DN tubulointerstitial injury and provides potential targets for early diagnosis and treatment of DN patients. Seven different genes ( AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1, FSTL1 ), as promising sensitive biomarkers, may affect the progression of DN by regulating immune inflammatory response. However, further comprehensive studies are needed to fully understand their exact molecular mechanisms and functional pathways in DN.
Keyphrases
- inflammatory response
- machine learning
- end stage renal disease
- ejection fraction
- type diabetes
- newly diagnosed
- chronic kidney disease
- cardiovascular disease
- dendritic cells
- high throughput
- genome wide
- peritoneal dialysis
- lipopolysaccharide induced
- artificial intelligence
- regulatory t cells
- dna methylation
- risk assessment
- immune response
- glycemic control
- patient reported outcomes
- lps induced
- transcription factor
- density functional theory
- human health
- patient reported
- genome wide identification
- insulin resistance