Diagnosis of Kidney Diseases of Unknown Etiology Through Biopsy-Genetic Analysis

通过活检-基因分析诊断病因不明的肾脏疾病

阅读:2

Abstract

INTRODUCTION: Previous studies have suggested that genetic kidney diseases in adults are often overlooked, representing up to 10% of all cases of chronic kidney disease (CKD). We present data obtained from exome sequencing (ES) analysis of patients with biopsy-proven undetermined kidney disease (UKD). METHODS: ES was proposed during routine clinical care in patients with UKD from January 2020 to December 2021. We used in silico custom kidney genes panel analysis to detect pathological variations using American College of Medical Genetics guidelines in 52 patients with biopsy-proven UKD with histological finding reassessment. RESULTS: We detected 12 monogenic renal disorders in 21 (40.4%) patients. The most common diagnoses were collagenopathies (8/21,38.1%), COL4A3 and COL4A4 accounting for 80% of these diagnoses, and ciliopathies (5/21, 23.8%). The diagnostic yield of ES was higher in female patients and patients with a family history of kidney disease (57.1% and 71%, respectively). Clinical nephropathy categories matched with the final genetic diagnoses in 72.7% of cases, whereas histological renal lesions matched with the final diagnoses in 92.3% of cases. The genetics diagnoses and histopathological findings were in complete agreement for both glomerular and tubulointerstitial cases. Interstitial inflammation without tubulitis was only observed in tubulopathies or ciliopathies. Isolated CKD, CKD with proteinuria or hematuria, and isolated proteinuria or hematuria yielded the highest diagnostic yields (54.6%, 52.6%, and 42.9%, respectively). CONCLUSION: ES done in patients with biopsy-proven UKD should be considered as a first-line tool for CKD patients with a family history of kidney disease. Combination of ES and kidney biopsy may have major impacts on kidney disease ontology.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。