PAQR9

Progesterone and adipoQ receptor 9 (PAQR9) is an endoplasmic reticulum (ER)-localized membrane protein that is involved in protein quality control of ER by interacting with BAG6. One of the physiological functions of PAQR9 is regulation of fasting-induced ketogenesis and fatty acid oxidation in the liver via modulating protein degradation of PPARα. However, it is currently unknown whether or not PAQR9 impacts glucose homeostasis. We address this question using a Paqr9-deleted mouse model in which type 1 diabetes was induced by streptozotocin injection and type 2 diabetes was induced by high-fat diet (HFD) with streptozotocin injection. Paqr9 deletion improved hyperglycemia and glucose tolerance in both of the diabetic mouse models. In the pancreatic islets, Paqr9 deletion reduced apoptosis of β cells in type 2 diabetic mice. Paqr9 deletion also reduced HFD-induced hepatic steatosis and adiposity of white adipose tissue. In Min6 cells, overexpression of DUF3538 domain of BAG6 to block the interaction of PAQR9 with BAG6 was able to enhance glucose-stimulated insulin secretion upon treatment with inflammatory factors or thapsigargin, an ER stress inducer. Thapsigargin-induced ER stress markers were also reduced by overexpression of DUF3538 domain. Collectively, these results indicate that PAQR9 has a modulatory role in glucose homeostasis, associated with regulation on insulin secretion of β cells in vitro under stress conditions.

DNA methylation programming is sensitive to prenatal life environmental influences, but the impact of maternal exposure to green space on newborns DNA methylation has not been studied yet.

We conducted a meta-epigenome-wide association study (EWAS) of maternal exposure to green space during gestation with cord blood DNA methylation in two subsets of the ENVIRONAGE cohort (N = 538). Cord blood DNA methylation was measured by Illumina HumanMethylation 450 K in one subset (N = 189) and EPICarray in another (N = 349). High (vegetation height>3 m (m)), low (vegetation height<3 m) and total (including both) high-resolution green space exposures during pregnancy were estimated within 100 m and 1000 m distance around maternal residence. In each subset, we sought cytosine-phosphate-guanine (CpG) sites via linear mixed models adjusted on newborns' sex, ethnicity, gestational age, season at delivery, sampling day, maternal parity, age, smoking, education, and estimated blood cell proportions. EWASs results were meta-analysed via fixed-effects meta-analyses. Differentially methylated regions (DMRs) were identified via ENmix-combp and DMRcate algorithms. Sensitivity analyses were additionally adjusted on PM_2.5, distance to major roads, urbanicity and neighborhood income. In the 450 K subset, cord blood expression of differentially methylated genes was measured by Agilent microarrays and associated with green space.

147 DMRs were identified, 85 of which were still significant upon adjustment for PM_2.5, distance to major roads, urbanicity and neighborhood income, including HLA-DRB5, RPTOR, KCNQ1DN, A1BG-AS1, HTR2A, ZNF274, COL11A1 and PRSS36 DMRs. One CpG reached genome-wide significance, while 54 CpGs were suggestive significant (p-values<1e-05). Among them, a CpG, hypermethylated with 100 m buffer total green space, was annotated to PAQR9, whose expression decreased with 1000 m buffer low green space (p-value = 1.45e-05).

Our results demonstrate that maternal exposure to green space during pregnancy is associated with cord blood DNA methylation, mainly at loci organized in regions, in genes playing important roles in neurological development (e.g., HTR2A).

We aimed to explore the expression and clinical prognostic significance of PAQR4 in hepatocellular carcinoma (HCC).

We obtained the gene expression matrix and clinical data of HCC from the cancer genome atlas (TCGA) and international cancer genome consortium (ICGC) databases. The prognostic value of PAQR4 in HCC was evaluated using the Kaplan-Meier and Cox regression analyses. PAQR4-related pathways were explored by gene set enrichment analysis (GSEA). A clinical nomogram prognostic model based on the PAQR family was constructed using Cox proportional hazards models.

We found that PAQR4 is overexpressed in HCC from multiple databases; additionally, quantitative real-time polymerase chain reaction (qRT-PCR) validated the upregulation of PAQR4 in HCC. PAQR4 expression was related to age, grade, alpha fetoprotein (AFP), T classification and clinical stage of HCC patients. High PAQR4 expression was associated with poor overall survival and was an independent prognostic factor for HCC patients through Kaplan-Meier analysis and Cox regression analysis, respectively. In addition, GSEA identified that the high PAQR4 expression phenotype was involved in the cell cycle, Notch signaling pathway, mTOR signaling pathway, etc. Finally, three PAQR family genes (PAQR4, PAQR8 and PAQR9) were associated with the prognosis of patients with HCC. A clinical nomogram prediction model was verified in TCGA training and ICGC validation sets, and it exerted dramatic predictive efficiency in this study.

PAQR4 may be regarded as a promising prognostic biomarker and therapeutic target for HCC.