Preservation Analysis of Macrophage Gene Coexpression Between Human and Mouse Identifies PARK2 as a Genetically Controlled Master Regulator of Oxidative Phosphorylation in Humans

Genetic Association and Differential RNA Expression of Histone (De)Acetylation-Related Genes in Pemphigus Foliaceus-A Possible Epigenetic Effect in the Autoimmune Response

Pemphigus foliaceus (PF) is an autoimmune skin blistering disease characterized by antidesmoglein-1 IgG production, with an endemic form (EPF) in Brazil. Genetic and epigenetic factors have been associated with EPF, but its etiology is still not fully understood. To evaluate the genetic association of histone (de)acetylation-related genes with EPF susceptibility, we evaluated 785 polymorphisms from 144 genes, for 227 EPF patients and 194 controls. Carriers of HDAC4_rs4852054*A were more susceptible (OR = 1.79, p = 0.0038), whereas those with GSE1_rs13339618*A (OR = 0.57, p = 0.0011) and homozygotes for PHF21A_rs4756055*A (OR = 0.39, p = 0.0006) were less susceptible to EPF. These variants were not associated with sporadic PF (SPF) in German samples of 75 SPF patients and 150 controls, possibly reflecting differences in SPF and EPF pathophysiology. We further evaluated the expression of histone (de)acetylation-related genes in CD4+ T lymphocytes, using RNAseq. In these cells, we found a higher expression of KAT2B, PHF20, and ZEB2 and lower expression of KAT14 and JAD1 in patients with active EPF without treatment compared to controls from endemic regions. The encoded proteins cause epigenetic modifications related to immune cell differentiation and cell death, possibly affecting the immune response in patients with PF.

Network Preservation Analysis Reveals Dysregulated Metabolic Pathways in Human Vascular Smooth Muscle Cell Phenotypic Switching

BACKGROUND

Vascular smooth muscle cells are key players involved in atherosclerosis, the underlying cause of coronary artery disease. They can play either beneficial or detrimental roles in lesion pathogenesis, depending on the nature of their phenotypic changes. An in-depth characterization of their gene regulatory networks can help better understand how their dysfunction may impact disease progression.

METHODS

We conducted a gene expression network preservation analysis in aortic smooth muscle cells isolated from 151 multiethnic heart transplant donors cultured under quiescent or proliferative conditions.

RESULTS

We identified 86 groups of coexpressed genes (modules) across the 2 conditions and focused on the 18 modules that are least preserved between the phenotypic conditions. Three of these modules were significantly enriched for genes belonging to proliferation, migration, cell adhesion, and cell differentiation pathways, characteristic of phenotypically modulated proliferative vascular smooth muscle cells. The majority of the modules, however, were enriched for metabolic pathways consisting of both nitrogen-related and glycolysis-related processes. Therefore, we explored correlations between nitrogen metabolism-related genes and coronary artery disease-associated genes and found significant correlations, suggesting the involvement of the nitrogen metabolism pathway in coronary artery disease pathogenesis. We also created gene regulatory networks enriched for genes in glycolysis and predicted key regulatory genes driving glycolysis dysregulation.

CONCLUSIONS

Our work suggests that dysregulation of vascular smooth muscle cell metabolism participates in phenotypic transitioning, which may contribute to disease progression, and suggests that AMT (aminomethyltransferase) and MPI (mannose phosphate isomerase) may play an important role in regulating nitrogen and glycolysis-related metabolism in smooth muscle cells.

Distance correlation application to gene co-expression network analysis

BACKGROUND

To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear (such as Pearson's correlation) and monotonic (such as Spearman's correlation) dependence metrics, are not enough to observe the nature of real biological systems. Hence, introducing a more informative correlation metric when constructing gene co-expression networks is still an interesting topic.

RESULTS

In this paper, we test distance correlation, a correlation metric integrating both linear and non-linear dependence, with other three typical metrics (Pearson's correlation, Spearman's correlation, and maximal information coefficient) on four different arrays (macrophage and liver) and RNA-seq (cervical cancer and pancreatic cancer) datasets. Among all the metrics, distance correlation is distribution free and can provide better performance on complex relationships and anti-outlier. Furthermore, distance correlation is applied to Weighted Gene Co-expression Network Analysis (WGCNA) for constructing a gene co-expression network analysis method which we named Distance Correlation-based Weighted Gene Co-expression Network Analysis (DC-WGCNA). Compared with traditional WGCNA, DC-WGCNA can enhance the result of enrichment analysis and improve the module stability.

CONCLUSIONS

Distance correlation is better at revealing complex biological relationships between gene profiles compared with other correlation metrics, which contribute to more meaningful modules when analyzing gene co-expression networks. However, due to the high time complexity of distance correlation, the implementation requires more computer memory.

An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism

Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10^-7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.

CRIP1 expression in monocytes related to hypertension

Hypertension is a complex and multifactorial disorder caused by lifestyle and environmental factors, inflammation and disease-related genetic factors and is a risk factor for stroke, ischemic heart disease and renal failure. Although circulating monocytes and tissue macrophages contribute to the pathogenesis of hypertension, the underlying mechanisms are poorly understood. Cysteine rich protein 1 (CRIP1) is highly expressed in immune cells, and CRIP1 mRNA expression in monocytes associates with blood pressure (BP) and is up-regulated by proinflammatory modulation suggesting a link between CRIP1 and BP regulation through the immune system. To address this functional link, we studied CRIP1 expression in immune cells in relation to BP using a human cohort study and hypertensive mouse models. CRIP1 expression in splenic monocytes/macrophages and in circulating monocytes was significantly affected by angiotensin II (Ang II) in a BP-elevating dose (2 mg/kg/day). In the human cohort study, monocytic CRIP1 expression levels were associated with elevated BP, whereas upon differentiation of monocytes to macrophages this association along with the CRIP1 expression level was diminished. In conclusion, CRIP1-positive circulating and splenic monocytes seem to play an important role in hypertension related inflammatory processes through endogenous hormones such as Ang II. These findings suggest that CRIP1 may affect the interaction between the immune system, in particular monocytes, and the pathogenesis of hypertension.

K-Module Algorithm: An Additional Step to Improve the Clustering Results of WGCNA Co-Expression Networks

Among biological networks, co-expression networks have been widely studied. One of the most commonly used pipelines for the construction of co-expression networks is weighted gene co-expression network analysis (WGCNA), which can identify highly co-expressed clusters of genes (modules). WGCNA identifies gene modules using hierarchical clustering. The major drawback of hierarchical clustering is that once two objects are clustered together, it cannot be reversed; thus, re-adjustment of the unbefitting decision is impossible. In this paper, we calculate the similarity matrix with the distance correlation for WGCNA to construct a gene co-expression network, and present a new approach called the k-module algorithm to improve the WGCNA clustering results. This method can assign all genes to the module with the highest mean connectivity with these genes. This algorithm re-adjusts the results of hierarchical clustering while retaining the advantages of the dynamic tree cut method. The validity of the algorithm is verified using six datasets from microarray and RNA-seq data. The k-module algorithm has fewer iterations, which leads to lower complexity. We verify that the gene modules obtained by the k-module algorithm have high enrichment scores and strong stability. Our method improves upon hierarchical clustering, and can be applied to general clustering algorithms based on the similarity matrix, not limited to gene co-expression network analysis.

Qtlizer: comprehensive QTL annotation of GWAS results

Exploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10^–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r² > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

Metabolic determinants of leukocyte pathogenicity in neurological diseases

Neuroinflammatory and neurodegenerative diseases are characterized by the recruitment of circulating blood-borne innate and adaptive immune cells into the central nervous system (CNS). These leukocytes sustain the detrimental response in the CNS by releasing pro-inflammatory mediators that induce activation of local glial cells, blood-brain barrier (BBB) dysfunction, and neural cell death. However, infiltrating peripheral immune cells could also dampen CNS inflammation and support tissue repair. Recent advances in the field of immunometabolism demonstrate the importance of metabolic reprogramming for the activation and functionality of such innate and adaptive immune cell populations. In particular, an increasing body of evidence suggests that the activity of metabolites and metabolic enzymes could influence the pathogenic potential of immune cells during neuroinflammatory and neurodegenerative disorders. In this review, we discuss the role of intracellular metabolic cues in regulating leukocyte-mediated CNS damage in Alzheimer's and Parkinson's disease, multiple sclerosis and stroke, highlighting the therapeutic potential of drugs targeting metabolic pathways for the treatment of neurological diseases.

Pleiotropic loci underlying bone mineral density and bone size identified by a bivariate genome-wide association analysis

Aiming to identify pleiotropic genomic loci for bone mineral density and bone size, we performed a bivariate GWAS in five discovery samples and replicated in two large-scale samples. We identified 2 novel loci at 2q37.1 and 6q26. Our findings provide insight into common genetic architecture underlying both traits.

INTRODUCTION

Bone mineral density (BMD) and bone size (BS) are two important factors that contribute to the development of osteoporosis and osteoporotic fracture. Both BMD and BS are highly heritable and they are genetically correlated. In this study, we aim to identify pleiotropic loci associated with BMD and BS.

METHODS

We conducted a bivariate genome-wide association (GWA) analysis of hip BMD and hip BS in 6180 participants from 5 samples, followed by in silico replication in the UK Biobank study of BMD (N = 426,824) and the deCODE study of BS (N = 28,954), respectively.

RESULTS

SNPs from 2 genomic loci were significant at the genome-wide significance (GWS) level (p lt; 5 × 10-8) in the discovery samples and were successfully replicated in the replication samples (2q37.1, lead SNP rs7575512, discovery p = 1.49 × 10-10, replication p = 0.05; 6q26, lead SNP rs1040724, discovery p = 1.95 × 10-8, replication p = 0.03). Functional annotations suggested functional relevance of the identified variants to bone development.

CONCLUSION

Our findings provide insight into the common genetic architecture underlying BMD and BS, and enhance our understanding of the potential mechanism of osteoporosis fracture.

White Matter Abnormalities Linked to Interferon, Stress Response, and Energy Metabolism Gene Expression Changes in Older HIV-Positive Patients on Antiretroviral Therapy

Neurocognitive impairment (NCI) remains a significant cause of morbidity in human immunodeficiency virus (HIV)-positive individuals despite highly active antiretroviral therapy (HAART). White matter abnormalities have emerged as a key component of age-related neurodegeneration, and accumulating evidence suggests they play a role in HIV-associated neurocognitive disorders. Viral persistence in the brain induces chronic inflammation associated with lymphocytic infiltration, microglial proliferation, myelin loss, and cerebrovascular lesions. In this study, gene expression profiling was performed on frontal white matter from 34 older HIV+ individuals on HAART (18 with NCI) and 24 HIV-negative controls. We used the NanoString nCounter platform to evaluate 933 probes targeting inflammation, interferon and stress responses, energy metabolism, and central nervous system-related genes. Viral loads were measured using single-copy assays. Compared to HIV- controls, HIV+ individuals exhibited increased expression of genes related to interferon, MHC-1, and stress responses, myeloid cells, and T cells and decreased expression of genes associated with oligodendrocytes and energy metabolism in white matter. These findings correlated with increased white matter inflammation and myelin pallor, suggesting interferon (IRFs, IFITM1, ISG15, MX1, OAS3) and stress response (ATF4, XBP1, CHOP, CASP1, WARS) gene expression changes are associated with decreased energy metabolism (SREBF1, SREBF2, PARK2, TXNIP) and oligodendrocyte myelin production (MAG, MOG), leading to white matter dysfunction. Machine learning identified a 15-gene signature predictive of HIV status that was validated in an independent cohort. No specific gene expression patterns were associated with NCI. These findings suggest therapies that decrease chronic inflammation while protecting mitochondrial function may help to preserve white matter integrity in older HIV+ individuals.

A Genome Wide Association Study on plasma FV levels identified PLXDC2 as a new modifier of the coagulation process

BACKGROUND

Factor V (FV) is a circulating protein primarily synthesized in the liver, and mainly present in plasma. It is a major component of the coagulation process.

OBJECTIVE

To detect novel genetic loci participating to the regulation of FV plasma levels.

METHODS

We conducted the first Genome Wide Association Study on FV plasma levels in a sample of 510 individuals and replicated the main findings in an independent sample of 1156 individuals.

RESULTS

In addition to genetic variations at the F5 locus, we identified novel associations at the PLXDC2 locus, with the lead PLXDC2 rs927826 polymorphism explaining ~3.7% (P = 7.5 × 10-15 in the combined discovery and replication samples) of the variability of FV plasma levels. In silico transcriptomic analyses in various cell types confirmed that PLXDC2 expression is positively correlated to F5 expression. SiRNA experiments in human hepatocellular carcinoma cell line confirmed the role of PLXDC2 in modulating factor F5 gene expression, and revealed further influences on F2 and F10 expressions.

CONCLUSION

Our study identified PLXDC2 as a new molecular player of the coagulation process.

LncRNA and mRNA profiling during activation of tilapia macrophages by HSP70 and Streptococcus agalactiae antigen

Objectives

To investigate the lncRNA profiling during tilapia peritoneal macrophages (TPMs) activation and discuss the relationship between lncRNA and mRNA.

Materials and Methods

RNA sequencing was used to investigate the lncRNA and mRNA profiles of TPMs activation following stimulation with Streptococcus agalactiae (Sa) antigen, heat shock protein 70 (HSP70) and HSP70+Sa. The expressions of lncRNA and mRNA were confirmed by qPCR. 356 lncRNA, 10173 mRNA and 1782 transcripts of uncertain coding potential (TUCP) were differentially expressed by pairwise comparison. These lncRNAs were shorter in length, fewer in exon number and higher in expression levels as compared with mRNAs. 683 lncRNAs and 4320 mRNAs were co-located, while 316 lncRNAs and 9997 mRNAs were in co-expression networks. Seven mRNAs (ANKRD34A, FMODA, GJA3, CNTN5, BMP10, BAI2 and HS3ST6) were involved in both networks of LNC_00035 and LNC_000466. Differentially expressed genes were involved in signaling pathways, such as "phosphorylation", "cytokine-cytokine receptor interaction", "endocytosis" and "MHC protein complex". LNC_000792, LNC_000215, LNC_000035 and LNC_000310, with cis and/or trans relationships with mRNAs, were also involved in ceRNA network.

Conclusions

These results might represent the first identified expression profile of lncRNAs and mRNAs in tilapia macrophages activated by HSP70 and Sa.