Many of genes mediating Known Drug-Disease Association (KDDA) are escaped from experimental detection. Identifying of these genes (hidden genes) is of great significance for understanding disease pathogenesis and guiding drug repurposing. Here, we presented a novel computational tool, called KDDANet, for systematic and accurate uncovering the hidden genes mediating KDDA from the perspective of genome-wide functional gene interaction network. KDDANet demonstrated the competitive performances in both sensitivity and specificity of identifying genes in mediating KDDA in comparison to the existing state-of-the-art methods. Case studies on Alzheimer’s disease (AD) and obesity uncovered the mechanistic relevance of KDDANet predictions. Furthermore, when applied with multiple types of cancer-omics datasets, KDDANet not only recapitulated known genes mediating KDDAs related to cancer, but also revealed novel candidates that offer new biological insights. Importantly, KDDANet can be used to discover the shared genes mediating multiple KDDAs. KDDANet can be accessed at http://www.kddanet.cn and the code can be freely downloaded at https://github.com/huayu1111/KDDANet.
Many of genes mediating Known Drug-Disease Association (KDDA) are escaped from experimental detection. Identifying of these genes (hidden genes) is of great significance for understanding disease pathogenesis and guiding drug repurposing. Here, we presented a novel computational tool, called KDDANet, for systematic and accurate uncovering the hidden genes mediating KDDA from the perspective of genome-wide functional gene interaction network. KDDANet demonstrated the competitive performances in both sensitivity and specificity of identifying genes in mediating KDDA in comparison to the existing state-of-the-art methods. Case studies on Alzheimer’s disease (AD) and obesity uncovered the mechanistic relevance of KDDANet predictions. Furthermore, when applied with multiple types of cancer-omics datasets, KDDANet not only recapitulated known genes mediating KDDAs related to cancer, but also revealed novel candidates that offer new biological insights. Importantly, KDDANet can be used to discover the shared genes mediating multiple KDDAs. KDDANet can be accessed at http://www.kddanet.cn and the code can be freely downloaded at https://github.com/huayu1111/KDDANet.
“…Hence, we used the GWAS datasets from the exposure (serum calcium) and the outcome (AD) to estimate the effect of exposure on outcome ( He et al, 2020 ). MR analysis has three assumptions, which have been widely described ( Liu et al, 2018 ; Anderson et al, 2020 ; He et al, 2020 ; Wang L. et al, 2020 ; Zhang et al, 2020 ; Ou et al, 2021 ; Sproviero et al, 2021 ). Ethical approvals were provided in the original articles ( Lambert et al, 2013 ; Young et al, 2021 ).…”
Section: Methodsmentioning
confidence: 99%
“…AD cases were autopsy-confirmed or clinically confirmed using the NINCDS-ADRDA criteria or DSM-IV guidelines ( Kunkle et al, 2019 ). The IGAP AD GWAS summary statistics have been widely used in recent MR analysis ( Liu et al, 2018 ; Anderson et al, 2020 ; He et al, 2020 ; Wang L. et al, 2020 ; Zhang et al, 2020 ; Ou et al, 2021 ; Sproviero et al, 2021 ).…”
It has been a long time that the relationship between serum calcium levels and Alzheimer’s disease (AD) remains unclear. Until recently, observational studies have evaluated the association between serum calcium levels and the risk of AD, however, reported inconsistent findings. Meanwhile, a Mendelian randomization (MR) study had been conducted to test the causal association between serum calcium levels and AD risk, however, only selected 6 serum calcium SNPs as the instrumental variables. Hence, these findings should be further verified using additional more genetic variants and large-scale genome-wide association study (GWAS) dataset to increase the statistical power. Here, we conduct an updated MR analysis of the causal association between serum calcium levels and the risk of AD using a two-stage design. In discovery stage, we conducted a MR analysis using 14 SNPs from serum calcium GWAS dataset (N = 61,079), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). All four MR methods including IVW, weighted median, MR-Egger, and MR-PRESSO showed a reduced trend of AD risk with the increased serum calcium levels. In the replication stage, we performed a MR analysis using 166 SNPs from serum calcium GWAS dataset (N = 305,349), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). Only the weighted median indicated that genetically increased serum calcium level was associated with the reduced risk of AD. Hence, additional studies are required to investigate these findings.
“…A [106]. A more recent MR study investigating the causal association between DBP levels and Alzheimer's disease showed that a standard deviation increase of the genetically DBP levels was significantly associated with reduced AD risk [odds ratio = 0.63 (0.45-0.89); p = 0.009 [107]. In this study, the DBP rs2282679 variant was selected as the instrumental variable, and the dataset was extracted from the multiple GWAS summary statistics data from International Genomics of Alzheimer's Project (IGAP).…”
Since the discovery of its role in vitamin D metabolism, significant progress has been made in the understanding of gene organisation, protein structure, catalytic function, and genetic polymorphism of cytochrome P450 2R1 (CYP2R1). Located on chromosome 11p15.2, CYP2R1 possesses five exons, unlike most other CYP isoforms that carry nine exons. CYP2R1 crystal structure displays a fold pattern typical of a CYP protein, with 12 a-helices as its structural core, and b-sheets mostly arranged on one side, and the heme buried in the interior part of the protein. Overall, CYP2R1 structure adopts a closed conformation with the B′ helix serving as a gate covering the substrate access channel, with the substrate vitamin D3 occupying a position with the side chain pointing toward the heme group. In liver, CYP2R1 25-hydroxylates vitamin D and serves as an important determinant of 25(OH)D level in the tissue and in circulation. While substrate profile has been well studied, inhibitor specificity for CYP2R1 requires further investigation. Both exonic and non-exonic single nucleotide polymorphisms (SNPs) have been reported in CYP2R1, including the CYP2R1*2 carrying Leu99Pro exchange, and a number of non-exonic SNPs with variable functional consequences in gene regulation. A non-exonic SNP, rs10741657, has its causal relationship with diseases established, including that of rickets, ovarian cancer, and multiple sclerosis. The role of other CYP2R1 SNPs in vitamin D deficiency and their causal link to other traits however remain uncertain currently and more studies are warranted to help identify possible physiological mechanisms underlying those complex traits.
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