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本文引用的文献

1
Clinical Application of Polygenic Risk Score in IgA Nephropathy.多基因风险评分在IgA肾病中的临床应用
Phenomics. 2024 Mar 21;4(2):146-157. doi: 10.1007/s43657-023-00138-6. eCollection 2024 Apr.
2
The gut microbiota posttranslationally modifies IgA1 in autoimmune glomerulonephritis.肠道微生物群在自身免疫性肾小球肾炎中对 IgA1 进行翻译后修饰。
Sci Transl Med. 2024 Mar 27;16(740):eadl6149. doi: 10.1126/scitranslmed.adl6149.
3
Time-Varying Proteinuria and Progression of IgA Nephropathy: A Cohort Study.时变蛋白尿与 IgA 肾病进展：一项队列研究。
Am J Kidney Dis. 2024 Aug;84(2):170-178.e1. doi: 10.1053/j.ajkd.2023.12.016. Epub 2024 Feb 15.
4
An Update on the Genetics of IgA Nephropathy.IgA肾病遗传学研究进展
J Clin Med. 2023 Dec 25;13(1):123. doi: 10.3390/jcm13010123.
5
IgA nephropathy.IgA 肾病。
Nat Rev Dis Primers. 2023 Nov 30;9(1):67. doi: 10.1038/s41572-023-00476-9.
6
Genome-Wide Association Analysis of Protein-Coding Variants in IgA Nephropathy.IgA 肾病中蛋白编码变异的全基因组关联分析。
J Am Soc Nephrol. 2023 Nov 1;34(11):1900-1913. doi: 10.1681/ASN.0000000000000222. Epub 2023 Oct 2.
7
Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy.全基因组关联分析定义了致病性信号通路，并为 IgA 肾病确定了药物靶点。
Nat Genet. 2023 Jul;55(7):1091-1105. doi: 10.1038/s41588-023-01422-x. Epub 2023 Jun 19.
8
Genome-Wide Association Study of CKD Progression.全基因组关联研究与慢性肾脏病进展。
J Am Soc Nephrol. 2023 Sep 1;34(9):1547-1559. doi: 10.1681/ASN.0000000000000170. Epub 2023 Jun 1.
9
Omics are Getting Us Closer to Understanding IgA Nephropathy.组学研究让我们更深入地了解 IgA 肾病。
Arch Immunol Ther Exp (Warsz). 2023 Apr 15;71(1):12. doi: 10.1007/s00005-023-00677-w.
10
Long-Term Outcomes in IgA Nephropathy.IgA 肾病的长期预后。
Clin J Am Soc Nephrol. 2023 Jun 1;18(6):727-738. doi: 10.2215/CJN.0000000000000135. Epub 2023 Apr 13.

Towards Risk Stratification in Clinical Care for IgA Nephropathy: Genetic Risk Scores: Comments on the Study "Clinical Application of Polygenic Risk Score in IgA Nephropathy".

作者信息

Berthier Celine C, Ju Wenjun

机构信息

Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI USA.

Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI USA.

出版信息

Phenomics. 2024 Nov 12;4(5):527-530. doi: 10.1007/s43657-024-00184-8. eCollection 2024 Oct.

DOI:10.1007/s43657-024-00184-8
PMID:39723228
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11666848/
Abstract
摘要