Cardiac metabolism is deranged in heart failure, but underlying mechanisms remain unclear. Here, we show that lysine demethylase 8 (Kdm8) maintains an active mitochondrial gene network by repressing Tbx15, thus preventing dilated cardiomyopathy leading to lethal heart failure. Deletion of Kdm8 in mouse cardiomyocytes increased H3K36me2 with activation of Tbx15 and repression of target genes in the NAD+ pathway before dilated cardiomyopathy initiated. NAD+ supplementation prevented dilated cardiomyopathy in Kdm8 mutant mice, and TBX15 overexpression blunted NAD+-activated cardiomyocyte respiration. Furthermore, KDM8 was downregulated in human hearts affected by dilated cardiomyopathy, and higher TBX15 expression defines a subgroup of affected hearts with the strongest downregulation of genes encoding mitochondrial proteins. Thus, KDM8 represses TBX15 to maintain cardiac metabolism. Our results suggest that epigenetic dysregulation of metabolic gene networks initiates myocardium deterioration toward heart failure and could underlie heterogeneity of dilated cardiomyopathy.
Background: Preeclampsia is an important clinical syndrome occurring during pregnancy. It shows genetic disposition, and the genetic risk has large ethnic heterogeneity. The study was designed to investigate the genetic risk of preeclampsia in Chinese pregnancies, and to apply it in early screening of the disease.
Methods: We performed a genome-wide association study to screen candidate risk loci associated with preeclampsia in Chinese people, and validated them with an independent cohort of enlarged size. We also trained prediction models using the genotypes of newly identified risk loci to screen the pregnancies with high preeclampsia risk.
Results: A segment in chromosome 6 covering HLA-DQB1, HLA-DRB5 and other immune-related genes shows the most significant association, and three loci in HLA-DRB5 were confirmed with an enlarged validation cohort. One of the validated loci, rs147440497, forms an amino acid change by the nucleotide polymorphism, which further causes a conformational change in the antigen-binding domain of HLA-DRB5 protein. With the genotypes of risk genetic loci and other demographic features, a machine-learning model was trained, which can predict Chinese preeclampsia pregnancies accurately, with a cross-validated recalling rate of 0.63 at a false positive rate of 8%.
Conclusion: We identified a novel gene from maternal genome, HLA-DRB5, the polymorphism in which is associated with preeclampsia. The genotypes of risk SNP loci can also be used for prediction of preeclampsia risk in Chinese population accurately.
Stably Expressed Genes (SEGs) are a set of genes with invariant expression. Identification of SEGs, especially among both healthy and diseased tissues, is of clinical relevance to enable more accurate data integration, gene expression comparison and biomarker detection. However, it remains unclear how many global SEGs there are, whether there are development-, tissue- or cell-specific SEGs, and whether diseases can influence their expression. In this research, we systematically investigate human SEGs at single-cell level and observe their development-, tissue- and cell-specificity, and expression stability under various diseased states. A hierarchical strategy is proposed to identify a list of 408 spatial-temporal SEGs. Development-specific SEGs are also identified, with adult tissue-specific SEGs enriched with the function of immune processes and fetal tissue-specific SEGs enriched in RNA splicing activities. Cells of the same type within different tissues tend to show similar SEG composition profiles. Diseases or stresses do not show influence on the expression stableness of SEGs in various tissues. In addition to serving as markers and internal references for data normalization and integration, we examine another possible application of SEGs, i.e., being applied for cell decomposition. The deconvolution model could accurately predict the fractions of major immune cells in multiple independent testing datasets of peripheral blood samples. The study provides a reliable list of human SEGs at the single-cell level, facilitates the understanding on the property of SEGs, and extends their possible applications.
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