Causal Effect of Plasminogen Activator Inhibitor Type 1 on Coronary Heart Disease

$\textit{Background—}$Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. $\textit{Methods and Results—}$To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. $\textit{Conclusions—}$Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction.This work was supported by NHLBI Intramural funds to Christopher O’Donnell and Andrew Johnson. Stephen Burgess is supported by a fellowship from the Wellcome Trust (100114)

Dairy Intake and Body Composition and Cardiometabolic Traits among Adults : Mendelian Randomization Analysis of 182041 Individuals from 18 Studies

BACKGROUND: Associations between dairy intake and body composition and cardiometabolic traits have been inconsistently observed in epidemiological studies, and the causal relationship remains ill-defined. METHODS: We performed Mendelian randomization analysis using an established genetic variant located upstream of the lactase gene (LCT- 13910 C/T, rs4988235) associated with dairy intake as an instrumental variable (IV). The causal effects of dairy intake on body composition and cardiometabolic traits (lipids, glycemic traits, and inflammatory factors) were quantified by IV estimators among 182041 participants from 18 studies. RESULTS: Each 1 serving/day higher dairy intake was associated with higher lean mass [beta (SE) = 0.117 kg (0.035); P = 0.001], higher hemoglobin A(1c) [0.009% (0.002); P <0.001], lower LDL [-0.014 mmol/L (0.006); P = 0.013], total cholesterol (TC) [-0.012 mmol/L (0.005); P = 0.023], and non-HDL [- 0.012 mmol/L (0.005); P = 0.028]. The LCT- 13910 C/T CT + TT genotype was associated with 0.214 more dairy servings/day (SE = 0.047; P = 0.001), 0.284 cm higher waist circumference (SE = 0.118; P = 0.017), 0.112 kg higher lean mass (SE = 0.027; P = 3.8 X 10(-5)), 0.032 mmol/L lower LDL (SE = 0.009; P = 0.001), and 0.032 mmol/L lower TC (SE = 0.010; P = 0.001). Genetically higher dairy intake was associated with increased lean mass [0.523 kg per serving/day (0.170); P = 0.002] after correction for multiple testing (0.05/18). However, we find that genetically higher dairy intake was not associated with lipids and glycemic traits. CONCLUSIONS: The present study provides evidence to support a potential causal effect of higher dairy intake on increased lean mass among adults. Our findings suggest that the observational associations of dairy intake with lipids and glycemic traits may be the result of confounding. (C) 2019 American Association for Clinical ChemistryPeer reviewe

Elucidating mechanisms of genetic cross-disease associations at the PROCR vascular disease locus

Many individual genetic risk loci have been associated with multiple common human diseases. However, the molecular basis of this pleiotropy often remains unclear. We present an integrative approach to reveal the molecular mechanism underlying the PROCR locus, associated with lower coronary artery disease (CAD) risk but higher venous thromboembolism (VTE) risk. We identify PROCR-p.Ser219Gly as the likely causal variant at the locus and protein C as a causal factor. Using genetic analyses, human recall-by-genotype and in vitro experimentation, we demonstrate that PROCR-219Gly increases plasma levels of (activated) protein C through endothelial protein C receptor (EPCR) ectodomain shedding in endothelial cells, attenuating leukocyte– endothelial cell adhesion and vascular inflammation. We also associate PROCR-219Gly with an increased pro- thrombotic state via coagulation factor VII, a ligand of EPCR. Our study, which links PROCR-219Gly to CAD through anti-inflammatory mechanisms and to VTE through pro-thrombotic mechanisms, provides a framework to reveal the mechanisms underlying similar cross-phenotype associations

Impact of protein supplementation during endurance training on changes in skeletal muscle transcriptome

Background: Protein supplementation improves physiological adaptations to endurance training, but the impact on adaptive changes in the skeletal muscle transcriptome remains elusive. The present analysis was executed to determine the impact of protein supplementation on changes in the skeletal muscle transcriptome following 5- weeks of endurance training. Results: Skeletal muscle tissue samples from the vastus lateralis were taken before and after 5-weeks of endurance training to assess changes in the skeletal muscle transcriptome. One hundred and 63 genes were differentially expressed after 5-weeks of endurance training in both groups (q-value 0.05). Endurance training primarily affected expression levels of genes related to extracellular matrix and these changes tended to be greater in PRO than in CON. Conclusions: Protein supplementation subtly impacts endurance training-induced changes in the skeletal muscle transcriptome. In addition, our transcriptomic analysis revealed that the extracellular matrix may be an important factor for skeletal muscle adaptation in response to endurance training. This trial was registered at clinicaltrials.gov as NCT03462381, March 12, 201

3D Bioprinted Human Skeletal Muscle Constructs for Muscle Function Restoration

A bioengineered skeletal muscle tissue as an alternative for autologous tissue flaps, which mimics the structural and functional characteristics of the native tissue, is needed for reconstructive surgery. Rapid progress in the cell-based tissue engineering principle has enabled in vitro creation of cellularized muscle-like constructs; however, the current fabrication methods are still limited to build a three-dimensional (3D) muscle construct with a highly viable, organized cellular structure with the potential for a future human trial. Here, we applied 3D bioprinting strategy to fabricate an implantable, bioengineered skeletal muscle tissue composed of human primary muscle progenitor cells (hMPCs). The bioprinted skeletal muscle tissue showed a highly organized multi-layered muscle bundle made by viable, densely packed, and aligned myofiber-like structures. Our in vivo study presented that the bioprinted muscle constructs reached 82% of functional recovery in a rodent model of tibialis anterior (TA) muscle defect at 8 weeks of post-implantation. In addition, histological and immunohistological examinations indicated that the bioprinted muscle constructs were well integrated with host vascular and neural networks. We demonstrated the potential of the use of the 3D bioprinted skeletal muscle with a spatially organized structure that can reconstruct the extensive muscle defects

A Widespread Distribution of Genomic CeMyoD Binding Sites Revealed and Cross Validated by ChIP-Chip and ChIP-Seq Techniques

Identifying transcription factor binding sites genome-wide using chromatin immunoprecipitation (ChIP)-based technology is becoming an increasingly important tool in addressing developmental questions. However, technical problems associated with factor abundance and suitable ChIP reagents are common obstacles to these studies in many biological systems. We have used two completely different, widely applicable methods to determine by ChIP the genome-wide binding sites of the master myogenic regulatory transcription factor HLH-1 (CeMyoD) in C. elegans embryos. The two approaches, ChIP-seq and ChIP-chip, yield strongly overlapping results revealing that HLH-1 preferentially binds to promoter regions of genes enriched for E-box sequences (CANNTG), known binding sites for this well-studied class of transcription factors. HLH-1 binding sites were enriched upstream of genes known to be expressed in muscle, consistent with its role as a direct transcriptional regulator. HLH-1 binding was also detected at numerous sites unassociated with muscle gene expression, as has been previously described for its mouse homolog MyoD. These binding sites may reflect several additional functions for HLH-1, including its interactions with one or more co-factors to activate (or repress) gene expression or a role in chromatin organization distinct from direct transcriptional regulation of target genes. Our results also provide a comparison of ChIP methodologies that can overcome limitations commonly encountered in these types of studies while highlighting the complications of assigning in vivo functions to identified target sites

Stroke genetics informs drug discovery and risk prediction across ancestries

Daniel Strbian työryhmän jäsenenä Correction; Early Access DOI: 10.1038/s41586-022-05492-5 Early Access: NOV 2022Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.Peer reviewe