Common genetic variants in ADCY5 and gestational glycemic traits

Identifying novel genetic loci associated with polycystic ovary syndrome based on its shared genetic architecture with type 2 diabetes

Genome-wide association studies (GWAS) have identified several common variants associated with polycystic ovary syndrome (PCOS). However, the etiology behind PCOS remains incomplete. Available evidence suggests a potential genetic correlation between PCOS and type 2 diabetes (T2D). The publicly available data may provide an opportunity to enhance the understanding of the PCOS etiology. Here, we quantified the polygenic overlap between PCOS and T2D using summary statistics of PCOS and T2D and then identified the novel genetic variants associated with PCOS behind this phenotypic association. A bivariate causal mixture model (MiXeR model) found a moderate genetic overlap between PCOS and T2D (Dice coefficient = 44.1% and after adjusting for body mass index, 32.1%). The conditional/conjunctional false discovery rate method identified 11 potential risk variants of PCOS conditional on associations with T2D, 9 of which were novel and 6 of which were jointly associated with two phenotypes. The functional annotation of these genetic variants supports a significant role for genes involved in lipid metabolism, immune response, and the insulin signaling pathway. An expression quantitative trait locus functionality analysis successfully repeated that 5 loci were significantly associated with the expression of candidate genes in many tissues, including the whole blood, subcutaneous adipose, adrenal gland, and cerebellum. We found that SCN2A gene is co-localized with PCOS in subcutaneous adipose using GWAS-eQTL co-localization analyses. A total of 11 candidate genes were differentially expressed in multiple tissues of the PCOS samples. These findings provide a new understanding of the shared genetic architecture between PCOS and T2D and the underlying molecular genetic mechanism of PCOS.

Circulating Placental Alkaline Phosphatase Expressing Exosomes in Maternal Blood Showed Temporal Regulation of Placental Genes

Background: Analysis of placental genes could unravel maternal-fetal complications. However, inaccessibility to placental tissue during early pregnancy has limited this effort. We tested if exosomes (Exo) released by human placenta in the maternal circulation harbor crucial placental genes. Methods: Placental alkaline phosphate positive exosomes (ExoPLAP) were enriched from maternal blood collected at the following gestational weeks; 6-8th (T1), 12-14th (T2), 20-24th (T3), and 28th-32nd (T4). Nanotracking analysis, electron microscopy, dynamic light scattering, and immunoblotting were used for characterization. We used microarray for transcriptome and quantitative PCR (qPCR) for gene analysis in ExoPLAP. Results: Physical characterization and presence of CD63 and CD9 proteins confirmed the successful ExoPLAP enrichment. Four of the selected 36 placental genes did not amplify in ExoPLAP, while 32 showed regulations (n = 3-8/time point). Most genes in ExoPLAP showed significantly lower expression at T2-T4, relative to T1 (p < 0.05), such as NOS3, TNFSF10, OR5H6, APOL3, and NEDD4L. In contrast, genes, such as ATF6, NEDD1, and IGF2, had significantly higher expression at T2-T4 relative to T1. Unbiased gene profiling by microarray also confirmed expression of above genes in ExoPLAP-transcriptome. In addition, repeated measure ANOVA showed a significant change in the ExoPLAP transcriptome from T2 to T4 (n = 5/time point). Conclusion: Placental alkaline phosphate positive exosomes transcriptome changed with gestational age advancement in healthy women. The transcriptome expressed crucial placental genes involved in early embryonic development, such as actin cytoskeleton organization, appropriate cell positioning, DNA replication, and B-cell regulation for protecting mammalian fetuses from rejection. Thus, ExoPLAP in maternal blood could be a promising source to study the placental genes regulation for non-invasive monitoring of placental health.

Identification of hub genes and functional modules in colon adenocarcinoma based on public databases by bioinformatics analysis

Background

Colon adenocarcinoma (COAD) is one of the most common cancers in the world. Although an extensive effort has been made to elucidate its pathogenesis, the underlying molecular mechanisms and genetic characteristics remain elusive.

Methods

In this study, protein-coding transcript expression profiles of COAD were downloaded from the Cancer RNA-Seq Nexus (CRN) database. They were then integrated to identify the overlapping transcripts expressed in every COAD RNA sequencing (RNA-seq) subset. The functional annotation of these overlapping genes (OLGs) involved noting their biological process (BP), cellular components (CC), molecular function (MF) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in the Database for Annotation, Visualization and Integrated Discovery (DAVID). Protein-protein interaction (PPI) networks were then constructed and analyzed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape 3.8.2.

Results

A total of 10 hub genes and 3 functional modules were screened by the plugin cytoHubba and MCODE, respectively. The plugin ClueGO and DAVID were used for the functional enrichment analyses of both hub genes and modules. The expression of hub genes was verified through the gene expression profiling interactive analysis (GEPIA) database. Survival analysis of the hub genes revealed that low expressions of ADCY5, GNG2, and PTPRC were significantly associated with an improved COAD prognosis. Furthermore, the expression level of ADCY5 in stages I/II was lower than that in stages III/IV, which seems to explain why the low expression of ADCY5 results in a better prognosis.

Conclusions

The identification of hub genes, functional modules, and pathways have the potential to improve our understanding of the causes and underlying molecular events of COAD. The hub gene ADCY5 could also be a prognostic monitoring indicator or therapeutic target in the treatment of COAD.

Effects of Whole-Body Adenylyl Cyclase 5 (Adcy5) Deficiency on Systemic Insulin Sensitivity and Adipose Tissue

Genome-wide association studies have identified adenylyl cyclase type 5 (ADCY5) as candidate gene for diabetes-related quantitative traits and an increased risk of type 2 diabetes. Mice with a whole-body deletion of Adcy5 (Adcy5-/-) do not develop obesity, glucose intolerance and insulin resistance, have improved cardiac function and increased longevity. Here, we investigated Adcy5 knockout mice (Adcy5-/-) to test the hypothesis that changes in adipose tissue (AT) may contribute to the reported healthier phenotype. In contrast to previous reports, we found that deletion of Adcy5 did not confer any physiological or biochemical benefits. However, this unexpected finding allowed us to investigate the effects of Adcy5 depletion on AT independently of lower body weight and a metabolically healthier phenotype. Adcy5-/- mice exhibited an increased number of smaller adipocytes, lower mean adipocyte size and a distinct AT gene expression pattern with midline 1 (Mid1) as the most significantly downregulated gene compared to control mice. Our Adcy5-/- model challenges previously described beneficial effects of Adcy5 deficiency and suggests that targeting Adcy5 does not improve insulin sensitivity and may therefore limit the relevance of ADCY5 as potential drug target.

In Vivo and In Vitro Models of Diabetes: A Focus on Pregnancy

Diabetes in pregnancy is associated with an increased risk of poor outcomes, both for the mother and her offspring. Although clinical and epidemiological studies are invaluable to assess these outcomes and the effectiveness of potential treatments, there are certain ethical and practical limitations to what can be assessed in human studies.Thus, both in vivo and in vitro models can aid us in the understanding of the mechanisms behind these complications and, in the long run, towards their prevention and treatment. This review summarizes the existing animal and cell models used to mimic diabetes, with a specific focus on the intrauterine environment. Summary of this review.