The Lung Cancer Associated MicroRNAs and Single Nucleotides Polymorphisms: a Mendelian Randomization Analysis

Systematic genome-wide Mendelian randomization reveals the causal links between miRNAs and Parkinson's disease

Background

MicroRNAs (miRNAs) have pivotal roles in gene regulation. Circulating miRNAs have been developed as novel candidate non-invasive biomarkers for diagnosis, prognosis, and treatment response for diseases. However, miRNAs that have causal effects on Parkinson's Disease (PD) remain largely unknown. To investigate the causal relationships between miRNAs and PD, here we conduct a Mendelian randomization (MR) study.

Methods

This study utilized the summary-level data of respective genome-wide association studies (GWAS) for 2083 miRNAs and seven PD-related outcomes to comprehensively reveal the causal associations between the circulating miRNAs and PD. Two-sample MR design was deployed and the causal effects were estimated with inverse variance weighted, MR-Egger, and weighted median. Comprehensively sensitive analyses were followed, including Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis, to validate the robustness of our results. Finally, we investigated the potential role of the MR significant miRNAs by predicting their target genes and functional enrichment analysis.

Results

Inverse variance weighted estimates suggested that two miRNAs, miR-205-5p (β = -0.46, 95%CI: -0.690 to -0.229, p = 9.3 × 10-5) and miR-6800-5p (β = -0.389, 95%CI: -0.575 to -0.202, p = 4.32 × 10-5), significantly decreased the rate of cognitive decline among PD patients. In addition, eight miRNAs were nominally associated with more than three PD-related outcomes each. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. Gene Ontology (GO) analysis showed that the targets of these causal miRNAs were significantly enriched in cell cycle, apoptotic, and aging pathways.

Conclusion

This MR study identified two miRNAs whose genetically regulated expression might have a causal role in the development of PD dementia. Our findings provided potential miRNA biomarkers to make better and early diagnoses and risk assessments of PD.

Transcriptional expressions of hsa-mir-183 predicted target genes as independent indicators for prognosis in bladder urothelial carcinoma

OBJECTIVE

To uncover novel prognostic and therapeutic targets for BLCA, our study is the first to investigate the role of hsa-mir-183 and its up-regulated predicted target genes in bladder urothelial carcinoma.

METHODS

To address this issue, our study explored the roles of hsa-mir-183 predicted target genes in the prognosis of BLCA via UALCAN, Metascape, Kaplan-Meier plotter, Human Protein Atlas, TIMER2.0, cBioPortal and Genomics of Drug Sensitivity in Cancer databases.

RESULTS

High transcriptional expressions of PDCD6, GNG5, PHF6 and MAL2 were markedly relevant to favorable OS in BLCA patients, whereas SLC25A15 and PTDSS1 had opposite expression significance. Additionally, high transcriptional expression of PDCD6, GNG5, PHF6, MAL2, SLC25A15 and PTDSS1 were significantly correlated with BLCA individual cancer stages and molecular subtypes. Furthermore, high mutation rate of PDCD6, MAL2, SLC25A15 and PTDSS1 were observed. Finally, TP53 mutation of PDCD6, GNG5, PHF6, MAL2, SLC25A15 and PTDSS1 has guiding significance for drug selection in BLCA.

CONCLUSIONS

PDCD6, GNG5, PHF6, MAL2, SLC25A15 and PTDSS1 could be the advanced independent indicators for prognosis of BLCA patients, and TP53-mutation might be a biomarker for drug option in BLCA patients.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.