Pathway analysis of body mass index genome-wide association study highlights risk pathways in cardiovascular disease

Identification of reversible and druggable pathways to improve beta-cell function and survival in Type 2 diabetes

Targeting β-cell failure could prevent, delay or even partially reverse Type 2 diabetes. However, development of such drugs is limited as the molecular pathogenesis is complex and incompletely understood. Further, while β-cell failure can be modeled experimentally, only some of the molecular changes will be pathogenic. Therefore, we used a novel approach to identify molecular pathways that are not only changed in a diabetes-like state but also are reversible and can be targeted by drugs. INS1E cells were cultured in high glucose (HG, 20 mM) for 72 h or HG for an initial 24 h followed by drug addition (exendin-4, metformin and sodium salicylate) for the remaining 48 h. RNAseq (Illumina TruSeq), gene set enrichment analysis (GSEA) and pathway analysis (using Broad Institute, Reactome, KEGG and Biocarta platforms) were used to identify changes in molecular pathways. HG decreased function and increased apoptosis in INS1E cells with drugs partially reversing these effects. HG resulted in upregulation of 109 pathways while drug treatment downregulated 44 pathways with 21 pathways in common. Interestingly, while hyperglycemia extensively upregulated metabolic pathways, they were not altered with drug treatment, rather pathways involved in the cell cycle featured more heavily. GSEA for hyperglycemia identified many known pathways validating the applicability of our cell model to human disease. However, only a fraction of these pathways were downregulated with drug treatment, highlighting the importance of considering druggable pathways. Overall, this provides a powerful approach and resource for identifying appropriate targets for the development of β-cell drugs.

Prediction for cardiovascular diseases based on laboratory data: An analysis of random forest model

Background

To establish a prediction model for cardiovascular diseases (CVD) in the general population based on random forests.

Methods

A retrospective study involving 498 subjects was conducted in Xi'an Medical University between 2011 and 2018. The random forest algorithm was used to screen out the variables that greatly affected the CVD prediction and to establish a prediction model. The important variables were included in the multifactorial logistic regression analysis. The area under the curve (AUC) was compared between logistic regression model and random forest model.

Results

The random forest model revealed the variables, including the age, body mass index (BMI), fasting blood glucose (FBG), diastolic blood pressure (DBP), triglyceride (TG), systolic blood pressure (SBP), total cholesterol (TC), waist circumference, and high‐density lipoprotein‐cholesterol (HDL‐C), were more significant for CVD prediction; the AUC was 0.802 in CVD prediction. Multifactorial logistic regression analysis indicated that the risk factors for CVD included the age [odds ratio (OR): 1.14, 95% confidence intervals (CI): 1.10‐1.17, P < .001], BMI (OR: 1.13, 95% CI: 1.06‐1.20, P < .001), TG (OR: 1.11, 95% CI: 1.02‐1.22, P = .023), and DBP (OR: 1.04, 95% CI: 1.02‐1.06, P = .001); the AUC was 0.843 in CVD prediction. The established logistic regression prediction model was Logit P = Log[P/(1 − P)] = −11.47 + 0.13 × age + 0.12 × BMI + 0.11 × TG + 0.04 × DBP; P = 1/[1 + exp(−Logit P)]. People were prone to develop CVD at the time of P > .51.

Conclusions

A prediction model for CVD is developed in the general population based on random forests, which provides a simple tool for the early prediction of CVD.

Integrating Genome-Wide Association Studies With Pathway Analysis and Gene Expression Analysis Highlights Novel Osteoarthritis Risk Pathways and Genes

Osteoarthritis (OA) is the most common degenerative joint disorder worldwide. To identify more genetic signals, genome-wide association study (GWAS) has been widely used and elucidated some OA susceptibility genes. However, these susceptibility genes could only explain only a small part of heritability of OA. It is suggested that the identification of disease-related pathways may contribute to understand the genomic etiology of OA. Here, we integrated the GWAS into pathway analysis to identify novel OA risk pathways. In this study, we first selected 187 independent genetic variants identified by GWAS (P < 1.00E−05) and found that most of these genetic variants are noncoding mutations. We then conducted an expression quantitative trait loci analysis and found that 165 of these 187 genetic variants could significantly regulate the expression of nearby genes. Third, we identified OA susceptibility genes corresponding to these genetic variants, conducted a pathway analysis, and identified novel OA-related KEGG pathways, GO biological processes, GO molecular functions, and GO cellular components. In KEGG database, transforming growth factor β signaling pathway is the most significant signal (P = 5.98E−05) and is the only pathway after the BH multiple-test adjustment with false discovery rate (FDR) = 0.02. In GO database, we identified 24 statistically significant GO biological processes, one statistically significant GO molecular function, and five statistically significant GO cellular components (FDR < 0.05). These signals are related with chondrocyte differentiation and development, which are all known biological pathways associated with OA. Finally, we conducted an OA case–control gene expression analysis to evaluate the differential expression of these OA risk genes. Using an OA case–control gene expression analysis, we showed that 44 risk genes were suggestively differentially expressed in OA cases compared with controls (P < 0.05). Three genes, WWP2, COG5, and MAPT, were statistically differentially expressed in OA cases compared with controls (P < 0.05/122 = 4.10E−04). Hence, our findings may contribute to understanding the genomic etiology of OA.

CDH1 rs9929218 variant at 16q22.1 contributes to colorectal cancer susceptibility

Colorectal cancer (CRC) is the third most common cancer. Large-scale genome-wide association studies (GWAS) have been performed and reported some novel CRC susceptibility variants in European ancestry including the CDH1 rs9929218. Following GWAS and candidate studies evaluated the association between the CDH1 rs9929218 polymorphism and CRC in European, Asian and American populations. However, these studies reported inconsistent associations. Evidence shows that rs9929218 may regulate different gene expressions in different human tissues. Here, we reevaluated this association using large-scale samples from 16 studies (n=131768) using a meta-analysis method. In heterogeneity test, we did not identify significant heterogeneity among these studies. Meta-analysis using fixed effect model showed significant association between rs9929218 and CRC (P=6.16E-21, odds ratio (OR) =0.92, 95% confidence interval (CI) 0.91-0.94). In order to validate the effect of rs9929218 variant on CDH1 expression, we further performed a functional analysis using two large-scale expression datasets. We identified significant regulation relation between rs9929218 variant and the expression of CDH1, ZFP90, RP11-354M1.2 and MCOLN2 by both cis-effect and trans-effect. In summary, our analysis highlights significant association between rs9929218 polymorphism and CRC susceptibility.

Multiple analyses of large-scale genome-wide association study highlight new risk pathways in lumbar spine bone mineral density

Osteoporosis is a common human complex disease. It is mainly characterized by low bone mineral density (BMD) and low-trauma osteoporotic fractures (OF). Until now, a large proportion of heritability has yet to be explained. The existing large-scale genome-wide association studies (GWAS) provide strong support for the investigation of osteoporosis mechanisms using pathway analysis. Recent findings showed that different risk pathways may be involved in BMD in different tissues. Here, we conducted multiple pathway analyses of a large-scale lumbar spine BMD GWAS dataset (2,468,080 SNPs and 31,800 samples) using two published gene-based analysis software including ProxyGeneLD and the PLINK. Using BMD genes from ProxyGeneLD, we identified 51 significant KEGG pathways with adjusted P<0.01. Using BMD genes from PLINK, we identified 38 significant KEGG pathways with adjusted P<0.01. Interestingly, 33 pathways are shared in both methods. In summary, we not only identified the known risk pathway such as Wnt signaling, in which the top GWAS variants are significantly enriched, but also highlight some new risk pathways. Interestingly, evidence from further supports the involvement of these pathways in MBD.

Genome-wide DNA methylome alterations in acute coronary syndrome

Acute coronary syndrome (ACS) is a common disease with high mortality and morbidity rates. The methylation status of blood DNA may serve as a potential early diagnosis and prevention biomarker for numerous diseases. The present study was designed to explore novel genome-wide aberrant DNA methylation patterns associated with ACS. The Infinium HumanMethylation450 assay was used to examine genome-wide DNA methylation profiles in 3 pairs of ACS and control group samples. Epigenome-wide DNA methylation, genomic distribution, Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The results were confirmed using methylation-specific polymerase chain reaction (MSP) and Sequenom MassARRAY analyses in ACS, stable coronary artery disease (SCAD) and control samples. A total of 11,342 differentially methylated (DM) 5′-C-phosphate-G-3′ (CpG) sites were identified, including 8,865 hypomethylated and 2,477 hypermethylated CpG sites in the ACS group compared with the control samples. They varied in frequency across genomic compartments, but were particularly notable in gene bodies and shores. The results of GO term and KEGG pathway enrichment analyses revealed that the methylated genes were associated with certain biological processes and pathways. Despite the considerable variability in methylation data, the candidate selected possessed significant methylation alteration in mothers against decapentaplegic homolog 3 (SMAD3) transcription start site 155 (Chr1:67356838-Chr1:67356942). MSP analysis from 81 ACS samples, 74 SCAD samples and 53 healthy samples, and Sequenom MassARRAY analysis, confirmed that differential CpG methylation of SMAD3 was significantly corrected with the reference results of the HumanMethylation450 array. The data identified an ACS-specific DNA methylation profile with a large number of novel DM CpG sites, some of which may serve as candidate markers for the early diagnosis of ACS.

A pathway analysis of genome-wide association study highlights novel type 2 diabetes risk pathways

Genome-wide association studies (GWAS) have been widely used to identify common type 2 diabetes (T2D) variants. However, the known variants just explain less than 20% of the overall estimated genetic contribution to T2D. Pathway-based methods have been applied into T2D GWAS datasets to investigate the biological mechanisms and reported some novel T2D risk pathways. However, few pathways were shared in these studies. Here, we performed a pathway analysis using the summary results from a large-scale meta-analysis of T2D GWAS to investigate more genetic signals in T2D. Here, we selected PLNK and VEGAS to perform the gene-based test and WebGestalt to perform the pathway-based test. We identified 8 shared KEGG pathways after correction for multiple tests in both methods. We confirm previous findings, and highlight some new T2D risk pathways. We believe that our results may be helpful to study the genetic mechanisms of T2D.

Tachykinin neurokinin 3 receptor antagonists: a new treatment for cardiovascular disease?

Great progress has been made in reducing cardiovascular mortality over the past 50 years. Nevertheless, prevalence is rising in some settings and remains higher in men than in women, even with the same level of established risk factors. To gain new insights, researchers are now considering cardiovascular disease in relation to the well known evolutionary biology model of growth and reproduction trading off against longevity, with trials of calorie restriction underway. However, calorie restriction has not been as successful as expected in primates and it is increasingly realised that effects on the reproductive axis might also be important. In this paper, the modulation of the reproductive axis using existing agents that have such properties-tachykinin neurokinin 3 receptor antagonists-is proposed as a way of reducing cardiovascular disease and combating a leading cause of global morbidity and mortality.

Genomic Contributors to Rhythm Outcome of Atrial Fibrillation Catheter Ablation - Pathway Enrichment Analysis of GWAS Data

BACKGROUND

Left atrial enlargement and persistent atrial fibrillation (AF) are well-known predictors for arrhythmia recurrence after AF catheter ablation (LRAF). In this study, by using pathway enrichment analysis of GWAS data, we tested the hypothesis that genetic pathways associated with these phenotypes are also associated with LRAF.

METHODS

Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing de-novo AF catheter ablation were genotyped for ~1,000,000 SNPs. SNPs found to be significantly associated with left atrial diameter (LAD) or AF type were used for gene-based association tests in a systematic biological Knowledge-based mining system for Genome-wide Genetic studies (KGG). Associated genes were tested for pathway enrichment using WEB-based Gene SeT AnaLysis Toolkit (WebGestalt), the Gene Annotation Tool to Help Explain Relationships (GATHER) and the databases provided by Kyoto Encyclopedia of Genes and Genomes (KEGG). In a second step, the association of consistently enriched pathways and LRAF was tested.

RESULTS

By using sequential 7-day Holter ECGs, LRAF between 3 and 12 months was observed in 48% and was associated with LAD (B = 1.801, 95% CI 0.760-2.841, p = 1.0E-3) and persistent AF (OR = 2.1; 95% CI 1.567-2.931, p = 2.0E-6). WebGestalt (adj. p = 2.7E-22) and GATHER (adj. p = 5.2E-3) identified the calcium signaling pathway (hsa04020) as the only consistently enriched pathway for LAD, while the extracellular matrix (ECM) -receptor interaction pathway (hsa04512) was the only consistently enriched pathway for AF type (adj. p = 2.1E-15 in WebGestalt; adj. p = 9.3E-4 in GATHER). Both calcium signaling (adj. p = 2.2E-17 in WebGestalt; adj. p = 2.9E-2 in GATHER) and ECM-receptor interaction (adj. p = 1.2E-10 in WebGestalt; adj. p = 2.9E-2 in GATHER) were significantly associated with LRAF.

CONCLUSIONS

Calcium signaling and ECM-receptor interaction pathways are associated with LAD and AF type and, in turn, with LRAF. Future and larger studies are necessary to replicate and apply these findings.

Genomic contributors to atrial electroanatomical remodeling and atrial fibrillation progression: Pathway enrichment analysis of GWAS data

In atrial fibrillation (AF), left atrial diameter (LAD) and low voltage area (LVA) are intermediate phenotypes that are associated with AF type and progression. In this study, we tested the hypothesis, that these phenotypes share common, genetically-determined pathways using pathway enrichment analysis of GWAS data. Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) were genotyped for ~1,000,000 SNPs. SNPs found significantly associated with LAD, LVA or AF type were used for gene-based association tests in a systematic biological Knowledge-based mining system for Genome-wide Genetic studies (KGG). Associated genes were tested for pathway enrichment using two enrichment tools (WebGestalt and GATHER) and the databases provided by Kyoto Encyclopedia of Genes and Genomes. The calcium signaling pathway (hsa04020) was the only pathway that reached statistical significance for LAD and LVA in both enrichment tools and was also significantly associated with AF type. Within this pathway, there were 39 genes (i.e. CACNA1C, RyR2) that were associated with LAD, LVA and AF type. In conclusion, there is a genomic contribution to electroanatomical remodeling (LAD, LVA) and AF type via the calcium signaling pathway. Future and larger studies are necessary to replicate and apply these findings.