The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA–miRNA–mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA–miRNA–mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA–miRNA–mRNA axis and validating experimentally. Our study is the first one to propose a new pipeline predicting the interactions between lncRNA and miRNA and mRNA by combining WGCNA and XGBoost. Compared with the methods reported previously, we developed an Optimized XGBoost model to reduce the degree of overfitting in multiomics data, thereby improving the generalization ability of the overall model for the integrated analysis of multiomics data. With applications to gestational diabetes mellitus (GDM), we predicted nine risk protein-coding biomarkers and some potential lncRNA–miRNA–mRNA regulatory axes, which all correlated with GDM. In those regulatory axes, the MALAT1/hsa-miR-144-3p/IRS1 axis was predicted to be the key axis and was identified as being associated with GDM for the first time. In short, as a flexible pipeline, DLRAPom can contribute to molecular pathogenesis research of diseases, effectively predicting potential disease-related noncoding RNA regulatory networks and providing promising candidates for functional research on disease pathogenesis.

Background Myopia has been shown to be associated with many pathological complications including cataracts, and previous evidence supported that high myopia facilitates the formation of cataracts. However, no studies have identified a link between the genetic susceptibility of high myopia-induced cataracts (HMC) and the underlying genetic mechanisms. Our study aimed to determine how the TRIB2 and CAPRIN2 genes correlate to the risk of HMC. Material/Methods In total, we successfully recruited 3162 participants, including 1026 participants with high myopia and cataracts and 2136 controls with high myopia only. For genotyping, 22 tag single nucleotide polymorphisms (SNPs) in TRIB2 and CAPRIN2 genes were chosen. Single marker association analysis and functional effects of significant SNPs were carried out. Results Strong correlation signals were captured for SNP rs890069 (χ 2 =22.13, P =2.55×10 −6 ) in TRIB2 and SNP rs17739338 (χ 2 =16.07, P =6.10×10 −5 ) in CAPRIN2 . In patients with high myopia, the C allele at SNP rs890069 was strongly linked to cataract risk (OR [95% CI]=1.36 [1.20–1.55]). In patients with high myopia, the T allele at SNP rs17739338 was significantly related to a lower risk of cataract (OR [95% CI]=0.54 [0.40–0.74]). In different types of human tissues, SNPs rs890069 and rs17739338 were found to be significantly correlated to the levels of TRIB2 and CAPRIN2 gene expression. Conclusions Our study indicated that both TRIB2 and CAPRIN2 genes conferred the susceptibility to cataract in patients with high myopia and Chinese Han ancestry. Future research remains necessary for fully understanding the pathogenic mechanisms and genetic characteristics of cataract.

ObjectivesMethamphetamine (METH) is a central nervous psychostimulant and one of the most frequently used illicit drugs. Numerous genetic loci that influence complex traits, including alcohol abuse, have been discovered; however, genetic analyses for METH dependence remain limited. An increased histone deacetylase 3 (HDAC3) expression has been detected in Fos-positive neurons in the dorsomedial striatum following withdrawal after METH self-administration. Herein, we aimed to systematically investigate the contribution of HDAC3 to the vulnerability to METH dependence in a Han Chinese population.MethodsIn total, we recruited 1,221 patients with METH dependence and 2,328 age- and gender-matched controls. For genotyping, we selected 14 single nucleotide polymorphisms (SNPs) located within ± 3 kb regions of HDAC3. The associations between genotyped genetic polymorphisms and the vulnerability to METH dependence were examined by single marker- and haplotype-based methods using PLINK. The effects of expression quantitative trait loci (eQTLs) on targeted gene expressions were investigated using the Genotype-Tissue Expression (GTEx) database.ResultsThe SNP rs14251 was identified as a significant association signal (χ2 = 9.84, P = 0.0017). An increased risk of METH dependence was associated with the A allele (minor allele) of rs14251 [odds ratio (95% CI) = 1.25 (1.09–1.43)]. The results of in silico analyses suggested that SNP rs14251 could be a potential eQTL signal for FCHSD1, PCDHGB6, and RELL2, but not for HDAC3, in various human tissues.ConclusionWe demonstrated that genetic polymorphism rs14251 located at 5q31.3 was significantly associated with the vulnerability to METH dependence in Han Chinese population.