Cell-Specific PEAR1 Methylation Studies Reveal a Locus that Coordinates Expression of Multiple Genes

[Screening for Characteristic Genes of Different Traditional Chinese Medicine Syndromes of Psoriasis Vulgaris: A Study Based on Bioinformatics and Machine Learning]

Objective

To screen for the key characteristic genes of the psoriasis vulgaris (PV) patients with different Traditional Chinese Medicine (TCM) syndromes, including blood-heat syndrome (BHS), blood stasis syndrome (BSS), and blood-dryness syndrome (BDS), through bioinformatics and machine learning and to provide a scientific basis for the clinical diagnosis and treatment of PV of different TCM syndrome types.

Methods

The GSE192867 dataset was downloaded from Gene Expression Omnibus (GEO). The limma package was used to screen for the differentially expressed genes (DEGs) of PV, BHS, BSS, and BDS in PV patients and healthy populations. In addition, KEGG (Kyoto Encyclopedia of Genes and Genes) pathway enrichment analysis was performed. The DEGs associated with PV, BHS, BSS, and BDS were identified in the screening and were intersected separately to obtain differentially characterized genes. Out of two algorithms, the support vector machine (SVM) and random forest (RF), the one that produced the optimal performance was used to analyze the characteristic genes and the top 5 genes were identified as the key characteristic genes. The receiver operating characteristic (ROC) curves of the key characteristic genes were plotted by using the pROC package, the area under curve (AUC) was calculated, and the diagnostic performance was evaluated, accordingly.

Results

The numbers of DEGs associated with PV, BHS, BSS, and BDS were 7699, 7291, 7654, and 6578, respectively. KEGG enrichment analysis was focused on Janus kinase (JAK)/signal transducer and activator of transcription (STAT), cyclic adenosine monophosphate (cAMP), mitogen-activated protein kinase (MAPK), apoptosis, and other pathways. A total of 13 key characteristic genes were identified in the screening by machine learning. Among the 13 key characteristic genes, malectin (MLEC), TUB like protein 3 (TULP3), SET domain containing 9 (SETD9), nuclear envelope integral membrane protein 2 (NEMP2), and BTG anti-proliferation factor 3 (BTG3) were the key characteristic genes of BHS; phosphatase 15 (DUSP15), C1q and tumor necrosis factor related protein 7 (C1QTNF7), solute carrier family 12 member 5 (SLC12A5), tripartite motif containing 63 (TRIM63), and ubiquitin associated protein 1 like (UBAP1L) were the key characteristic genes of BSS; recombinant mouse protein (RRNAD1), GTPase-activating protein ASAP3 Protein (ASAP3), and human myomesin 2 (MYOM2) were the key characteristic genes of BDS. Moreover, all of them showed high diagnostic efficacy.

Conclusion

There are significant differences in the characteristic genes of different PV syndromes and they may be potential biomarkers for diagnosing TCM syndromes of PV.

Integrative analysis of drug response and clinical outcome in acute myeloid leukemia

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

Association of colorectal cancer with genetic and epigenetic variation in PEAR1—A population-based cohort study

Platelet Endothelial Aggregation Receptor 1 (PEAR1) modulates angiogenesis and platelet contact-induced activation, which play a role in the pathogenesis of colorectal cancer. We therefore tested the association of incident colorectal cancer and genetic and epigenetic variability in PEAR1 among 2532 randomly recruited participants enrolled in the family-based Flemish Study on Environment, Genes and Health Outcomes (51.2% women; mean age 44.8 years). All underwent genotyping of rs12566888 located in intron 1 of the PEAR1 gene; in 926 participants, methylation at 16 CpG sites in the PEAR1 promoter was also assessed. Over 18.1 years (median), 49 colorectal cancers occurred, all in different pedigrees. While accounting for clustering of risk factors within families and adjusting for sex, age, body mass index, the total-to-HDL cholesterol ratio, serum creatinine, plasma glucose, smoking and drinking, use of antiplatelet and nonsteroidal anti-inflammatory drug, the hazard ratio of colorectal cancer contrasting minor-allele (T) carriers vs. major-allele (GG) homozygotes was 2.17 (95% confidence interval, 1.18–3.99; P = 0.013). Bootstrapped analyses, from which we randomly excluded from two to nine cancer cases, provided confirmatory results. In participants with methylation data, we applied partial least square discriminant analysis (PLS-DA) and identified two methylation sites associated with higher colorectal cancer risk and two with lower risk. In-silico analysis suggested that methylation of the PEAR1 promoter at these four sites might affect binding of transcription factors p53, PAX5, and E2F-1, thereby modulating gene expression. In conclusion, our findings suggest that genetic and epigenetic variation in PEAR1 modulates the risk of colorectal cancer in white Flemish. To what extent, environmental factors as exemplified by our methylation data, interact with genetic predisposition and modulate penetrance of colorectal cancer risk is unknown.

Genome sequencing unveils a regulatory landscape of platelet reactivity

Platelet aggregation at the site of atherosclerotic vascular injury is the underlying pathophysiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes.

Impact of Platelet Endothelial Aggregation Receptor-1 Genotypes on Long-Term Cerebrovascular Outcomes in Patients With Minor Stroke or Transient Ischemic Attack

Background: Platelet endothelial aggregation receptor-1 (PEAR1) rs12041331 has been reported to affect agonist-stimulated platelet aggregation, but it remains unclear whether this variant plays a role in recurrent stroke. Here we assess the clinical relevance of PEAR1 rs12041331 in acute minor ischemic stroke (AMIS) and transient ischemic attack (TIA) Chinese patients treated with dual antiplatelet therapy (DAPT).

Methods: We recruited 273 consecutive minor stroke and TIA patients, and Cox proportional hazard regression was used to model the relationship between PEAR1 rs12041331 and thrombotic and bleeding events.

Results: Genotyping for PEAR1 rs12041331 showed 49 (18.0%) AA homozygotes, 129 (47.3%) GA heterozygotes, and 95 (34.7%) GG homozygotes. No association was observed between PEAR1 rs12041331 genotype and stroke or composite clinical vascular event rates (ischemic stroke, hemorrhagic stroke, TIA, myocardial infarction, or vascular death) or bleeding events regardless if individuals carried one or two copies of the A allele. Our results suggested that rs12041331 genetic polymorphism was not an important contributor to clinical events in AMIS and TIA patients in the setting of secondary prevention.

Conclusions: Our data do provide robust evidence that genetic variation in PEAR1 rs12041331 do not contribute to atherothrombotic or bleeding risk in minor stroke and TIA patients treated with DAPT.

NMU DNA methylation in blood is associated with metabolic and inflammatory indices: results from the Moli-sani study

Neuromedin U (NMU) is a neuropeptide involved in gut-brain axis, energy balance and immune response. We aimed at analysing the association between NMU epigenetic variability and metabolic indices and the potential mediating role of low-grade inflammation in a general population of Italian adults.NMU Blood DNA methylation levels at two CpG islands (NMU76 and NMU32) were analysed using pyrosequencing in a randomly selected sub-cohort of 1,160 subjects from the Moli-sani study (≥35years; 49.20% men). Multivariable regressions adjusted for age, sex, smoking, alcohol and vegetable consumption were performed to estimate the associations between methylation and metabolic phenotypes (BMI, waist-to-hip ratio, blood pressure, glucose, HOMA-IR, lipids, lipoprotein(a) and apolipoproteins). Mediation analysis was performed to identify the influence of low-grade inflammation in the association using a composite index based on C reactive protein, granulocyte-to-lymphocyte ratio (GLR), platelet and white blood cell counts (INFLA-score).Using principal component analysis four methylation factors were identified: NMU76-F1, NMU76-F2, NMU32-F1 and NMU32-F2. NMU76-F1 was FDR significantly associated with total cholesterol (for 1 SD increase: β = 4.5 ± 1.4 mg/dL of, R² = 10.8%, p = 0.001), ApoB (0.03 ± 0.01 g/L, 12.2%, p = 0.0004), with INFLA-score (1.05 ± 0.22, p = 2.7E-6) and GLR (-0.27 ± 0.03, 30.4%, p = 1.3E-20). GLR and lymphocyte numbers mediate the association of NMU76-F1 with cholesterol (24.0% of total effect, Sobel p = 0.013) and ApoB (42.6%, p = 9E-7), respectively.These findings suggest that NMU promoter methylation patterns could mark a pathway linking lipids with haematopoiesis and systemic inflammation.

PEAR1 polymorphisms as a prognostic factor in hemostasis and cardiovascular diseases

Platelet Endothelial Aggregation Receptor (PEAR1), as a platelet receptor, plays a vital role in hemostasis. This receptor, by its extracellular part, causes platelet adhesion and consequently initiates platelet aggregation. Dysfunction of PEAR1 can disrupt platelet aggregation in patients with cardiovascular diseases (CVDs). The content used in this paper has been taken from English language articles (2005-2020) retrieved from Pubmed database and Google scholar search engine using "Cardiovascular Disease", "PEAR1", "Polymorphism", and "Platelet Aggregation" keywords. Some PEAR1 polymorphisms can disrupt homeostasis and interfere with the function mechanism of cardiac drugs. Since polymorphisms in this gene affect platelet function and the platelet aggregation process, PEAR1 could be further studied in the future as an essential factor in controlling the treatment process of patients with cardiovascular diseases. PEAR1 polymorphisms through disruption of the platelet aggregation process can be a risk factor in patients with CVDs. Therefore, controlling patients through genetic testing and the evaluation of PEAR1 polymorphisms can help improve the treatment process of patients. According to the studies on the PEAR1 gene and the effect of different polymorphisms on some crucial issues in CVDs patients (changes in platelet activity), it is clear that if there is a significant relationship between polymorphisms and CVDs, they can be used as prognostic and diagnostic markers. This study aims to evaluate the prognosis and drug treatment of the PEAR1 gene in CVDs patients.

Impact of Platelet Endothelial Aggregation Receptor-1 Genotypes on Platelet Reactivity and Early Cardiovascular Outcomes in Patients Undergoing Percutaneous Coronary Intervention and Treated With Aspirin and Clopidogrel

BACKGROUND

The genetic determinants of response to clopidogrel and aspirin are incompletely characterized. Recently, PEAR1 (platelet endothelial aggregation receptor-1) rs12041331 polymorphism has been shown to influence the platelet reactivity, but its impact on cardiovascular outcomes remains unclear in patients treated with antiplatelet agents.

METHODS AND RESULTS

In this prospective cohort study, 2439 Chinese patients with acute coronary syndrome or stable coronary artery disease undergoing coronary stent implantation and receiving clopidogrel and aspirin were consecutively recruited. Their platelet reactivity was determined by light transmission aggregometry at 5 and 30 days after coronary intervention. Genotyping was performed using an improved multiplex ligation detection reaction technique. All patients completed a 30-day follow-up for clinical outcomes. Genotyping for PEAR1 showed 768 (38.3%) GG homozygotes, 941 (46.9%) GA heterozygotes, and 298 (14.8%) AA homozygotes. The 30-day incidence of major adverse cardiovascular events, the composite of cardiovascular death, nonfatal myocardial infarction, and ischemic stroke were significantly higher in AA homozygotes than in non-AA homozygotes (adjusted hazard ratio, 2.78; 95% CI, 1.13-6.82; P=0.026), irrespective of CYP2C19*2 loss-of-function polymorphism and known outcome predictors including age, sex, smoking, and diabetes mellitus. The ADP-induced platelet aggregation was significantly lower in AA homozygotes than that in GG homozygotes at both time points, although no significant difference was found for the arachidonic acid-induced platelet aggregation among the 3 groups.

CONCLUSIONS

About 15% of Chinese patients undergoing coronary stent implantation were AA homozygotes for PEAR1 rs12041331. These patients had ≈3-fold increase in short-term major adverse cardiovascular events risk compared with non-AA homozygotes, and the adverse clinical outcome is unlikely to be mediated by suboptimal pharmacological response to aspirin or clopidogrel.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov . Unique identifier: NCT01968499.

Variation of PEAR1 DNA methylation influences platelet and leukocyte function

BACKGROUND

Platelet-endothelial aggregation receptor 1 (PEAR-1) is a transmembrane receptor involved in platelet activation and megakaryopoiesis whose expression is driven by DNA methylation. PEAR1 variants were associated with differential platelet response to activation and cardiovascular outcomes. We aimed at investigating the link between PEAR1 methylation and platelet and leukocyte function markers in a family-based population.

RESULTS

We measured PEAR1 methylation in 605 Moli-family participants with available blood counts, plasma P-selectin and C-reactive protein, whole blood platelet P-selectin, and platelet-leukocyte mixed conjugate measurements. We performed principal component analysis (PCA) to identify groups of highly correlated CpG sites. We used linear mixed regression models (using age, gender, BMI, smoking, alcohol drinking, being a proband for family recruitment, being a member of myocardial infarction (MI) family as fixed effects, and family as a random effect) to evaluate associations between PEAR1 methylation and phenotypes. PEAR1 methylation Factor2, characterized by the previously identified megakaryocyte-specific CpG sites, was inversely associated with platelet-monocyte conjugates, P-selectin, and WBC counts, while positively associated with the platelet distribution width (PDW) and with leukocyte CD11b and L-selectin. Moreover, PEAR1 Factor2 methylation was negatively associated with INFLAscore, a low-grade inflammation score. The latter was partially mediated by the PEAR1 methylation effect on platelet variables. PEAR1 methylation association with WBC measurements and INFLAscore was confirmed in the independent cohort FLEMENGHO.

CONCLUSIONS

We report a significant link between epigenetic signatures in a platelet functional gene and inflammation-dependent platelet function variability measured in two independent cohorts.