Blood advances · 2026
Accurate identification of sickle cell disease cases in a large genotyped cohort using electronic health record data.
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Wuichet Kristin, Corty Robert, Bick Alexander, DeBaun Michael R
Аннотация
PURPOSE: The role of mitochondrial-related genes in the pathophysiology of hypertrophic scars (HS) is not well understood. This study aims to provide multi-omics insight into mitochondrial genes associated with HS through Mendelian randomization (MR) methods.
METHODS: Mitochondrial-related genes in this study were obtained from the MitoCarta3.0 database. Relevant single nucleotide polymorphisms (SNPs) were screened from methylation, expression and protein quantitative trait loci (mQTLs, eQTLs, and pQTLs) of mitochondrial genes. Five regression models including MR-Egger regression, Inverse variance weighted (IVW), Weighted Median, Weighted mode and Simple mode were employed to assess the potential causal relationship between mitochondrial genes and HS risk. Steiger filtering test was used to verify the direction of the causal relationship between genotype, intermediate variables, and final outcomes. Colocalization was employed to identify whether two phenotypes were driven by the same causal variant in a specific region. Multi-omics analysis integrated results from three different gene regulatory layers.
RESULTS: 376 CpG sites, 233 mitochondrial gene expressions and 34 proteins were found associated with HS via MR. Multi-omics results indicated that HTATIP2 and PDK1 were genes with tier 1 multi-omics evidence, along with 16 tier 2 genes and 3 tier 3 genes.
CONCLUSION: This study identified 21 mitochondrial genes with therapeutic potential, with HTATIP2 and PDK1 being the most promising genes for clinical application, which may strengthen the understanding of HS pathophysiology.
METHODS: Mitochondrial-related genes in this study were obtained from the MitoCarta3.0 database. Relevant single nucleotide polymorphisms (SNPs) were screened from methylation, expression and protein quantitative trait loci (mQTLs, eQTLs, and pQTLs) of mitochondrial genes. Five regression models including MR-Egger regression, Inverse variance weighted (IVW), Weighted Median, Weighted mode and Simple mode were employed to assess the potential causal relationship between mitochondrial genes and HS risk. Steiger filtering test was used to verify the direction of the causal relationship between genotype, intermediate variables, and final outcomes. Colocalization was employed to identify whether two phenotypes were driven by the same causal variant in a specific region. Multi-omics analysis integrated results from three different gene regulatory layers.
RESULTS: 376 CpG sites, 233 mitochondrial gene expressions and 34 proteins were found associated with HS via MR. Multi-omics results indicated that HTATIP2 and PDK1 were genes with tier 1 multi-omics evidence, along with 16 tier 2 genes and 3 tier 3 genes.
CONCLUSION: This study identified 21 mitochondrial genes with therapeutic potential, with HTATIP2 and PDK1 being the most promising genes for clinical application, which may strengthen the understanding of HS pathophysiology.