Prognostic Characterization of Metabolism Gene-Related Risk Score Associated with Myelodysplastic Syndromes and Single-Cell Sequencing Analysis DOI

Changrui Tao,

Jie Liu, Xiaoqing Yu

et al.

Published: Jan. 1, 2024

Language: Английский

Causal relationship between drug target genes of LDL-cholesterol and coronary artery disease: Drug Target Mendelian Randomization Study DOI

Yongho Jee,

Jong Won Shin, Mikyung Ryu

et al.

Published: Oct. 30, 2024

Abstract Background High LDL-cholesterol (LDL-C) is a well-known risk factor for coronary artery disease (CAD). PCSK9, HMGCR, NPC1L1, ACLY, and LDLR gene have been reported as lipid lowering drug genes related to LDL-C lowering. However relevant Asian studies were rare. Methods We examined the causality between LDL-c target CAD using Korean Japanese data two sample Mendelian Randomization (MR) method. conducted two-sample MR analysis of (7 Single-nucleotide polymorphisms (SNP) in PCSK9, 6 SNPs HMGCR, 5 NPC1L1, 9 ACLY, 3 LDLR) CAD. used summary statistics from Genome Epidemiology Study (KOGES) data, Biobank Japan (BBJ) data. Results For every 10 mg/dl decrease determined by four significant PCSK9 gene, decreased approximately 20% (OR = 0.80, 95% CI: 0.75–0.86). The 10% due six HMGCR 0.90, 0.86–0.94). Due LDLR, 26% 0.74, 0.66–0.82). combined effect on showed largest size PCSK9 LDLR reduced induced these together was OR 0.78 (95%CI, 0.74–0.83). Finally, all three (PCSK9, LDLR) 0.85 0.79–0.91) (Fig. 3D). Conclusion reduction estimated significantly found potential proxy research design clinical trials drugs.

Language: Английский

Citations

0

Integrative multi-omic analyses identify candidate targets for celiac disease involving tissue-specific regulation DOI Creative Commons
Jiazheng Sun, Yulan Zeng

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Abstract Introduction: Celiac disease (CeD) is an autoimmune condition characterized by a reversible inflammatory reaction in the mucous membrane of small intestine. Nevertheless, there limited availability efficient control approaches. Prior research has demonstrated that pharmacological targets supported genetic evidence can greatly enhance efficacy drug development. Hence, study aims to integrate transcriptomic and proteomic information identify candidate for CeD. Methods The employed proteome-wide Mendelian randomization (MR) analysis circulating plasma proteins investigate their causal association with CeD were further assessed employing colocalization analysis, transcriptome-wide summary-data-based (SMR) multimarker genomic annotation (MAGMA) gene-based bulk RNAseq-based differential expression analysis. For identified, extended Phenome-wide studies (PheWAS) conducted assess side-effect profiles, while DGIdb database provided on approved or investigated drugs targets. Results Systematic MR identified 22 Among analyzed, BTN2A1 passed all subsequent verification analyses. Additionally, three proteins, including CatH, IL-18R1, PTPRC, majority other 18 also (Trehalase, CD226, SH2B3, ICOSLG, ULK3, Park7, ALDH2, RABEP1, TNFRSF9, COL11A2, GNPDA1, IL-1RL1, B3galt6, TNFSF11, CCL21, BTN3A3, OLFM2 Colipase). Conclusions combination human information, several analytical methods. As result, divided into four tiers, as prospective therapeutic

Language: Английский

Citations

0

Uncovering SPP1+ Macrophage, Neutrophils and Their Related Diagnostic Biomarkers in Intracranial Aneurysm and Subarachnoid Hemorrhage DOI Creative Commons

Haipeng Jie,

Boyang Wang, Jingjing Zhang

et al.

Journal of Inflammation Research, Journal Year: 2024, Volume and Issue: Volume 17, P. 8569 - 8587

Published: Nov. 1, 2024

Intracranial aneurysms (IA) frequently cause subarachnoid hemorrhage (SAH) and have poor prognosis. However, the molecular mechanisms diagnostic biomarkers associated with IA ruptured (rIA) remain poorly understood.

Language: Английский

Citations

0

Prognostic Characterization of Metabolism Gene-Related Risk Score Associated with Myelodysplastic Syndromes and Single-Cell Sequencing Analysis DOI

Changrui Tao,

Jie Liu, Xiaoqing Yu

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0