Population-specific genome-wide mapping of expression quantitative trait loci in the colon of Han Chinese

Genetic variant of cyclooxygenase-2 in gastric cancer: More inflammation and susceptibility

Gastric cancer accounts for the majority cancer-related deaths worldwide. Although various methods have considerably improved the screening, diagnosis, and treatment of gastric cancer, its incidence is still high in Asia, and the 5-year survival rate of advanced gastric cancer patients is only 10%-20%. Therefore, more effective drugs and better screening strategies are needed for reducing the incidence and mortality of gastric cancer. Cyclooxygenase-2 (COX-2) is considered to be the key inducible enzyme in prostaglandins (PGs) synthesis, which is involved in multiple pathways in the inflammatory response. For example, inflammatory cytokines stimulate innate immune responses via Toll-like receptors and nuclear factor-kappa B to induce COX-2/PGE2 pathway. In these processes, the production of an inflammatory microenvironment promotes the occurrence of gastric cancer. Epidemiological studies have also indicated that non-steroidal anti-inflammatory drugs can reduce the risk of malignant tumors of the digestive system by blocking the effect of COX-2. However, clinical use of COX-2 inhibitors to prevent or treat gastric cancer may be limited because of potential side effects, especially in the cardiovascular system. Given these side effects and low treatment efficacy, new therapeutic approaches and early screening strategies are urgently needed. Some studies have shown that genetic variation in COX-2 also play an important role in carcinogenesis. However, the genetic variation analysis in these studies is incomplete and isolated, pointing out only a few single nucleotide polymorphisms (SNPs) and the risk of gastric cancer, and no comprehensive study covering the whole gene region has been carried out. In addition, copy number variation (CNV) is not mentioned. In this review, we summarize the SNPs in the whole COX-2 gene sequence, including exons, introns, and both the 5' and 3' untranslated regions. Results suggest that COX-2 does not increase its expression through the CNV and the SNPs in COX-2 may serve as the potential marker to establish risk stratification in the general population. This review synthesizes emerging insights of COX-2 as a biomarker in multiple studies, summarizes the association between whole COX-2 sequence variation and susceptibility to gastric cancer, and discusses the future prospect of therapeutic intervention, which will be helpful for early screening and further research to find new approaches to gastric cancer treatment.

Integrating GWAS and eQTL to predict genes and pathways for non-syndromic cleft lip with or without palate

OBJECTIVE

To explore susceptibility genes and pathways for non-syndromic cleft lip with or without cleft palate (NSCL/P).

MATERIALS AND METHODS

Two genome-wide association studies (GWAS) datasets, including 858 NSCL/P cases and 1,248 controls, were integrated with expression quantitative trait loci (eQTL) dataset identified by Genotype-Tissue Expression (GTEx) project in whole-blood samples. The expression of the candidate genes in mouse orofacial development was inquired from FaceBase. Protein-protein interaction (PPI) network was visualized to identify protein functions. Go and KEGG pathway analyses were performed to explore the underlying risk pathways.

RESULTS

A total of 233 eQTL single-nucleotide polymorphisms (SNPs) in 432 candidate genes were identified to be associated with the risk of NSCL/P. One hundred and eighty-three susceptible genes were expressed in mouse orofacial development according to FaceBase. PPI network analysis highlighted that these genes involved in ubiquitin-mediated proteolysis (KCTD7, ASB1, UBOX5, ANAPC4) and DNA synthesis (XRCC3, RFC3, KAT5, RHNO1) were associated with the risk of NSCL/P. GO and KEGG pathway analyses revealed that the fatty acid metabolism pathway (ACADL, HSD17B12, ACSL5, PPT1, MCAT) played an important role in the development of NSCL/P.

CONCLUSIONS

Our results identified novel susceptibility genes and pathways associated with the development of NSCL/P.

Systems biology in inflammatory bowel diseases: on the way to precision medicine

Inflammatory bowel diseases (IBD) are chronic and recurrent inflammatory disorders of the gastrointestinal tract. The elucidation of their etiopathology requires complex and multiple approaches. Systems biology has come to fulfill this need in approaching the pathogenetic mechanisms of IBD and its etiopathology, in a comprehensive way, by combining data from different scientific sources. In combination with bioinformatics and network medicine, it uses principles from computer science, mathematics, physics, chemistry, biology, medicine and computational tools to achieve its purposes. Systems biology utilizes scientific sources that provide data from omics studies (e.g., genomics, transcriptomics, etc.) and clinical observations, whose combined analysis leads to network formation and ultimately to a more integrative image of disease etiopathogenesis. In this review, we analyze the current literature on the methods and the tools utilized by systems biology in order to cover an innovative and exciting field: IBD-omics.

Roles of Cyclooxygenase-2 gene -765G > C (rs20417) and -1195G > A (rs689466) polymorphisms in gastric cancer: A systematic review and meta-analysis

BACKGROUND

The roles of cyclooxygenase-2 (COX2) -765G > C (rs20417) and -1195G > A (rs689466) polymorphisms in gastric cancer were intensively analyzed, but the results of these studies were inconsistent. We conducted a meta-analysis and trial sequential analysis to elucidate the associations between these two COX2 polymorphisms and gastric cancer risk.

METHODS

Eligible studies were searched in PubMed, Embase, Cochrane library databases, China National Knowledge Infrastructure, Vip, and Wanfang databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the genetic correlation between COX2 polymorphisms and gastric cancer susceptibility in five genetic models. Trial sequential analysis (TSA) was conducted to estimate whether the evidence of the results is sufficient. Furthermore, their interactions with Helicobacter pylori (H. pylori) or smoking in gastric cancer were also assessed using a case-only method.

RESULTS

The COX2 gene -765G > C polymorphism showed no significant association with gastric cancer susceptibility under all the five genetic models (take the allelic model for example: OR = 1.41, 95% CI: 0.95-2.09) in total analysis, and the stratification analysis by ethnicity indicated a similar association in Caucasian group under four genetic models (allelic model, dominant model, homozygous model, and heterozygous model). But in the subgroup of the Asian population, the -765G > C polymorphism was significantly associated with gastric cancer risk under the same contrast. The COX2 -1195G > A polymorphism showed significant correlation with gastric cancer susceptibility in total analysis, and stratification analysis by ethnicity also revealed a similar association in both Asian and Caucasian groups under the same contrast. Moreover, TSA confirmed such associations. Both H. pylori infection and cigarette smoking interacted with -765 C allele in gastric cancer (OR = 3.79, 95% CI: 1.15-12.43 and OR = 2.48, 95% CI: 1.38-4.48, respectively), but not in -1195 A allele (OR = 1.96, 95% CI: 0.62-6.21, and OR = 1.24, 95% CI: 0.93-1.64, respectively).

CONCLUSIONS

COX2 -765G > C polymorphism may serve as a genetic biomarker of gastric cancer in Asians, but not in Caucasians. COX2 -1195G > A polymorphism may serve as a genetic biomarker of gastric cancer in both Asians and Caucasians. The -765G > C, rather than -1195G > A polymorphism interacted with H. pylori infection or cigarette smoking to increase gastric cancer risk.

Functional Genomics of Host-Microbiome Interactions in Humans

The human microbiome has been linked to various host phenotypes and has been implicated in many complex human diseases. Recent genome-wide association studies (GWASs) have used microbiome variation as a complex trait and have uncovered human genetic variants that are associated with the microbiome. Here we summarize results from these studies and illustrate potential regulatory mechanisms by which host genetic variation can interact with microbiome composition. We argue that, similar to human GWASs, it is important to use functional genomics techniques to gain a mechanistic understanding of causal host-microbiome interactions and their role in human disease. We highlight experimental, functional, and computational genomics methodologies for the study of the genomic basis of host-microbiome interactions and describe how these approaches can be utilized to explain how human genetic variation can modulate the effects of the microbiome on the host.