Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes.
Yue Zhaonull AnsarullahParveen KumarJ Matthew MahoneyHao HeYoonjung Yoonie JooJoshy GeorgeSheng LiPublished in: bioRxiv : the preprint server for biology (2024)
The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic β-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting β-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to β-cell dysfunction, we investigated single-cell gene expression changes in β-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta- cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.
Keyphrases
- single cell
- type diabetes
- genome wide
- gene expression
- cell therapy
- cardiovascular disease
- rna seq
- glycemic control
- high throughput
- physical activity
- oxidative stress
- dna methylation
- stem cells
- adipose tissue
- copy number
- molecular docking
- mesenchymal stem cells
- bone marrow
- transcription factor
- smoking cessation
- genome wide identification
- adverse drug
- genome wide analysis