Causal Inference between Rheumatoid Arthritis and Breast Cancer in East Asian and European Population: A Two-Sample Mendelian Randomization

Rheumatoid arthritis and risk of site-specific cancers: Mendelian randomization study in European and East Asian populations

BACKGROUND

The associations of rheumatoid arthritis (RA) with risk of site-specific cancers beyond lymphohematopoietic cancer have been scarcely explored. We conducted a Mendelian randomization investigation of the associations of RA with site-specific cancers in European and East Asian populations.

METHODS

Independent genetic variants strongly associated with RA in European and East Asian populations were selected as instrumental variables from genome-wide association studies of 58,284 European individuals (14,361 cases and 43,923 controls) and 22,515 East Asian individuals (4873 cases and 17,642 controls), respectively. The associations of genetic variants with overall and 22 site-specific cancers were extracted from the UK Biobank study (n = 367,561), the FinnGen study (n = 260,405), Biobank Japan (n = 212,453), and international consortia. The associations for one outcome from different data sources were combined by meta-analysis.

RESULTS

In the European population, the combined odds ratios per 1-unit increase in log odds of genetic liability to RA were 1.06 (95% confidence interval [CI] 1.03-1.10) for head and neck cancer, 1.06 (95% CI 1.02-1.10) for cervical cancer, 0.92 (95% CI 0.87-0.96) for testicular cancer, and 0.94 (95% CI 0.90-0.98) for multiple myeloma. In the East Asian population, the corresponding odds ratios were 1.17 (95% CI 1.06-1.29) for pancreatic cancer, 0.91 (95% CI 0.88-0.94) for breast cancer, and 0.90 (95% CI 0.84-0.96) for ovarian cancer. There were suggestive associations for breast and ovarian cancer and overall cancer in the European population. No other associations were observed.

CONCLUSION

This study suggests that RA may play a role in the development of several site-specific cancers.

Genetic causal inference between amblyopia and perinatal factors

Amblyopia is a common visual disorder that causes significant vision problems globally. Most non-ocular risk factors for amblyopia are closely related to the intrauterine environment, and are strongly influenced by parent-origin effects. Parent-origin perinatal factors may have a direct causal inference on amblyopia development; therefore, we investigated the causal association between perinatal factors and amblyopia risk using a one-sample Mendelian Randomization (MR) with data from the UK Biobank Cohort Data (UKBB). Four distinct MR methods were employed to analyze the association between three perinatal factors (birth weight [BW], maternal smoking, and breastfeeding) and amblyopia risk, based on the summary statistics of genome-wide association studies in the European population. The inverse variance weighting method showed an inverse causal association between BW and amblyopia risk (odds ratio, 0.48 [95% CI, 0.29-0.80]; p = 0.004). Maternal smoking and breastfeeding were not causally associated with amblyopia risk. Our findings provided a possible evidence of a significant genetic causal association between low BW and increased amblyopia risk. This evidence may highlight the potential of BW as a predictive factor for visual maldevelopment and the need for careful management of amblyopia risk in patients with low BW.

Bioinformatics Characterization of Candidate Genes Associated with Gene Network and miRNA Regulation in Esophageal Squamous Cell Carcinoma Patients

The present study aimed to identify potential therapeutic targets for esophageal squamous cell carcinoma (ESCC). The gene expression profile GSE161533 contained 84 samples, in that 28 tumor tissues and 28 normal tissues encoded as ESCC patients were retrieved from the Gene Expression Omnibus database. The obtained data were validated and screened for differentially expressed genes (DEGs) between normal and tumor tissues with the GEO2R tool. Next, the protein–protein network (PPI) was constructed using the (STRING 2.0) and reconstructed with Cytoscape 3.8.2, and the top ten hub genes (HGsT10) were predicted using the Maximal Clique Centrality (MCC) algorithm of the CytoHubba plugin. The identified hub genes were mapped in GSE161533, and their expression was determined and compared with The Cancer Genome Atlas (TCGA.) ESCC patient’s samples. The overall survival rate for HGsT10 wild and mutated types was analyzed with the Gene Expression Profiling Interactive Analysis2 (GEPIA2) server and UCSC Xena database. The functional and pathway enrichment analysis was performed using the WebGestalt database with the reference gene from lumina human ref 8.v3.0 version. The promoter methylation for the HGsT10 was identified using the UALCAN server. Additionally, the miRNA-HGsT10 regulatory network was constructed to identify the top ten hub miRNAs (miRT10). Finally, we identified the top ten novel driving genes from the DEGs of GSE161533 ESCC patient’s sample using a multi-omics approach. It may provide new insights into the diagnosis and treatment for the ESCC affected patients early in the future.

Causal risk and protective factors in rheumatoid arthritis: A genetic update

The characterization of risk and protective factors in complex diseases such as rheumatoid arthritis (RA) has evolved from epidemiological studies, which test association, to the use of Mendelian randomization approaches, which test direct relationships. Indeed, direct associations with the mucosal origin of RA are retrieved with periodontal disease (Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans predominantly), interstitial lung involvement, tobacco smoking and air pollutants. Next, factors directly associated with an acquired immune response include genetic factors (HLA DRB1, PTPN22), capacity to produce anti-modified protein antibodies (AMPA), and relatives with a history of autoimmune diseases. Finally, factors can be also classified according to their direct capacity to interfere with the IL-6/CRP/sIL-IL6R proinflammatory pathway as risk factor (body fat, cardiometabolic factors, type 2 diabetes, depressive syndrome) or either as protective factors by controlling of sIL-6R levels (higher education level, and intelligence). Although some co-founders have been characterized (e.g. vitamin D, physical activity, cancer) the direct association with sex-discrepancy, pregnancy, and infections among other factors remains to be better explored.