Metabolic status differentiates Trp53inp2 function in pressure-overload induced heart failure

Cardiometabolic disorders encompass a broad range of cardiovascular complications associated with metabolic dysfunction. These conditions have an increasing share in the health burden worldwide due to worsening endemic of hypertension, obesity, and diabetes. Previous studies have identified Tumor Protein p53-inducible Nuclear Protein 2 (Trp53inp2) as a molecular link between hyperglycemia and cardiac hypertrophy. However, its role in cardiac pathology has never been determined in vivo. In this study, we generated a cardiac specific knockout model of Trp53inp2 (Trp53inp2-cKO) and investigated the impact of Trp53inp2 inactivation on the pathogenesis of heart failure under mechanic or/and metabolic stresses. Based on echocardiography assessment, inactivation of Trp53inp2 in heart led to accelerated onset of HFrEF in response to pressure-overload, with significantly reduced ejection fraction and elevated heart failure marker genes comparing to the control mice. In contrast, inactivation of Trp53inp2 ameliorated cardiac dysfunction induced by combined stresses of high fat diet and moderate pressure overload (Cardiometabolic Disorder Model). Moreover, Trp53inp2 inactivation led to reduced expression of glucose metabolism genes in lean, pressure-overloaded hearts. However, the same set of genes were significantly induced in the Trp53inp2-cKO hearts under both mechanical and metabolic stresses. In summary, we have demonstrated for the first time that cardiomyocyte Trp53inp2 has diametrically differential roles in the pathogenesis of heart failure and glucose regulation under mechanical vs. mechanical plus metabolic stresses. This insight suggests that Trp53inp2 may exacerbate the cardiac dysfunction during pressure overload injury but have a protective effect in cardiac diastolic function in cardiometabolic disease

Metabolic status differentiates Trp53inp2 function in pressure-overload induced heart failure

Cardiometabolic disorders encompass a broad range of cardiovascular complications associated with metabolic dysfunction. These conditions have an increasing share in the health burden worldwide due to worsening endemic of hypertension, obesity, and diabetes. Previous studies have identified Tumor Protein p53-inducible Nuclear Protein 2 (Trp53inp2) as a molecular link between hyperglycemia and cardiac hypertrophy. However, its role in cardiac pathology has never been determined in vivo. In this study, we generated a cardiac specific knockout model of Trp53inp2 (Trp53inp2-cKO) and investigated the impact of Trp53inp2 inactivation on the pathogenesis of heart failure under mechanic or/and metabolic stresses. Based on echocardiography assessment, inactivation of Trp53inp2 in heart led to accelerated onset of HFrEF in response to pressure-overload, with significantly reduced ejection fraction and elevated heart failure marker genes comparing to the control mice. In contrast, inactivation of Trp53inp2 ameliorated cardiac dysfunction induced by combined stresses of high fat diet and moderate pressure overload (Cardiometabolic Disorder Model). Moreover, Trp53inp2 inactivation led to reduced expression of glucose metabolism genes in lean, pressure-overloaded hearts. However, the same set of genes were significantly induced in the Trp53inp2-cKO hearts under both mechanical and metabolic stresses. In summary, we have demonstrated for the first time that cardiomyocyte Trp53inp2 has diametrically differential roles in the pathogenesis of heart failure and glucose regulation under mechanical vs. mechanical plus metabolic stresses. This insight suggests that Trp53inp2 may exacerbate the cardiac dysfunction during pressure overload injury but have a protective effect in cardiac diastolic function in cardiometabolic disease

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p