Two-Sample Mendelian Randomization detects bidirectional causality between gut microbiota and celiac disease in individuals with high genetic risk.

Background: Celiac Disease (CeD) is an autoimmune disorder triggered by gluten intake in genetically susceptible individuals. Highest risk individuals are homozygous for the Human Leucocyte Antigen (HLA) DQ2.5 haplotype or DQ2.5/DQ2.2 heterozygous. Both the HLA-DQ2-positive high genetic risk individuals and those that have developed the disease have altered intestinal microbiota, but it remains unclear whether these alterations are a cause or a consequence of CeD. Objective: To investigate a potential bidirectional causality between gut microbiota (GM) and CeD in HLA-DQ2 high genetic risk individuals. Materials and Methods: We performed a bidirectional Two-Sample Mendelian Randomization (2SMR) test using summary statistics from the largest publicly available Genome-Wide Association Study (GWAS) of GM and the summary statistics of the Immunochip CeD study of those individuals with the HLA-DQ2 high-risk haplotype. To test whether changes in GM composition were causally linked to CeD, GM data were used as exposure and CeD data as outcome; to test for reverse causation, the exposure and outcome datasets were inverted. Results: We identified several bacteria from Ruminococcaceae and Lachnospiraceae families of the Firmicutes phylum as potentially causal in both directions. In addition, our results suggest that changes in the abundance of Veillonellaceae family might be causal in the development of CeD, while alterations in Pasteurellaceae family might be a consequence of the disease itself. Conclusion: Our results suggest that the relationship between GM and HLA-DQ2 high risk individuals is highly complex and bidirectional.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders.

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

Genetic Contribution of Endometriosis to the Risk of Developing Hormone-Related Cancers.

Endometriosis is a common gynecological disorder that has been associated with endometrial, breast and epithelial ovarian cancers in epidemiological studies. Since complex diseases are a result of multiple environmental and genetic factors, we hypothesized that the biological mechanism underlying their comorbidity might be explained, at least in part, by shared genetics. To assess their potential genetic relationship, we performed a two-sample mendelian randomization (2SMR) analysis on results from public genome-wide association studies (GWAS). This analysis confirmed previously reported genetic pleiotropy between endometriosis and endometrial cancer. We present robust evidence supporting a causal genetic association between endometriosis and ovarian cancer, particularly with the clear cell and endometrioid subtypes. Our study also identified genetic variants that could explain those associations, opening the door to further functional experiments. Overall, this work demonstrates the value of genomic analyses to support epidemiological data, and to identify targets of relevance in multiple disorders.