单细胞RNA测序应用于肾小球疾病研究的进展

doi:10.3969/j.issn.1674-8115.2022.10.012

摘要/Abstract

摘要：

肾小球疾病是导致慢性肾脏病和终末期肾功能衰竭的主要原因。了解肾小球疾病发生和发展的分子机制对于早期识别疾病危险因素、挽救肾功能具有重要意义。肾脏中复杂且高度分化的细胞组成是肾小球疾病研究面临的一大挑战，传统测序方法无法确定特定细胞的转录变化以及不同类型细胞间的相互作用。近年来，单细胞RNA测序（single-cell RNA sequencing， scRNA-seq ）技术发展迅速，可用于研究肾脏、尿液以及血液等不同来源细胞群体中单个细胞的基因表达模式。将scRNA-seq应用于肾小球疾病有助于生成全面的肾脏细胞图谱，从细胞层面解析肾小球疾病的复杂机制，开发预警生物标志物和细胞特异性的治疗方法。该文就scRNA-seq技术在临床常见原发性和继发性肾小球疾病中的应用研究进展进行综述。

关键词: 单细胞RNA测序, 转录组, 肾小球肾炎, 糖尿病肾病, 狼疮性肾炎, IgA肾病, 局灶节段性肾小球硬化, 膜性肾病

Abstract:

Glomerular diseases are a leading cause of chronic kidney disease and end-stage renal failure. Understanding the molecular mechanism underlying the initiation and progression of glomerular diseases is important to early identify risk factors for disease development and rescue renal function. The kidney is composed of complex and highly differentiated cells, which is a major challenge in the study of glomerular diseases. Bulk RNA sequencing cannot assess differential transcription or the interactions between cell types. Single-cell RNA sequencing (scRNA-seq) technology has developed rapidly in recent years, making it possible to study a wide range of cell types in kidney, urine and blood. The application of scRNA-seq to glomerular diseases helps to construct a comprehensive cell atlas, elucidate complex cellular and molecular mechanisms, develop efficient and accurate prognostic biomarkers and cell-specific therapies. This review focuses on the latest research advances in scRNA-seq in primary and secondary glomerular diseases.

Key words: single-cell RNA sequencing (scRNA-seq), transcriptome, glomerulonephritis, diabetic nephropathies, lupus nephritis, glomerulonephritis, IGA, glomerulosclerosis, focal segmental, glomerulonephritis, membranous

中图分类号:

R692.6

邢海帆, 范瑛. 单细胞RNA测序应用于肾小球疾病研究的进展[J]. 上海交通大学学报（医学版）, 2022, 42(10): 1458-1465.

XING Haifan, FAN Ying. Advances in single-cell RNA sequencing in glomerular diseases[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2022, 42(10): 1458-1465.

图/表 2

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Disease	Publi-cation Year	Author	Sample source	Sample number	Technology	Platform	Reference
DN	2019	FU， et al.	Glomerulus （Mouse）	2 groups，n=3/group： eNOS^-/- + Vehicle， eNOS^-/- + STZ	scRNA-seq	Fluidigm C1	［28］
	2019	WILSON， et al.	Nephrectomy	3 diabetic nephropathy samples， 3 control samples	snRNA-seq	10×Genomics	［31］
	2021	ABEDINI， et al.	Urine	17 urine samples from 5 subjects， 1 pooled sample from 10 healthy individuals	scRNA-seq	10×Genomics	［33］
	2021	WU，et al.	Kidney （Mouse）	5 groups，n=2‒ 4/group： db/m+vehicle， db/db + vehicle， db/db + dapagliflflozin， db/db + irbesartan，db/db + dapagliflflozin+irbesartan	scRNA-seq	10×Genomics	［34］
	2022	WU，et al.	Kidney （Mouse）	7 groups， two early time points/group， 70 mice in total： ReninAAV Unx db/db treated with Vehicle， Lisinopril， Rosiglitazone， JNJ-39933673， Lisinopril + JNJ-39933673， Lisinopril + rosiglitazone； LacZ AAV db/m	snRNA-seq	10×Genomics	［35］
	2022	WU，et al.	Kidney （Mouse）		RNA-seq		［35］
LN	2019	ARAZI，et al.	Kidney biopsy	24 lupus nephritis， 10 controls	scRNA-seq	CEL-Seq2	［21］
			Urine	8 lupus nephritis	scRNA-seq	CEL-Seq2
			PBMC	10 lupus nephritis， 6 controls	scRNA-seq	10×Genomics
			PBMC	10 lupus nephritis， 6 controls	RNA-seq
	2019	DER， et al.	Kidney biopsy	21 lupus nephritis， 3 controls	scRNA-seq	Fluidigm C1	［22］
			Skin biopsy	17 lupus nephritis， 3 controls
			PBMC	8 lupus nephritis
IgAN	2020	ZHENG， et al.	Kidney	13 IgAN，6 nephropathy samples from controls	scRNA-seq	STRT-Seq	［37］
	2020	ZHENG， et al.	CD14+ PBMC	5 IgAN， 5 controls	scRNA-seq	STRT-Seq	［37］
	2021	TANG， et al.	Kidney biopsy	4 IgAN， 1 control	scRNA-seq	10×Genomics	［38］
	2021	ZENG， et al.	PBMC	10 IgAN， 6 controls	scRNA-seq	BD Rhapsody	［40］
	2022	ZAMBRANO， et al.	Glomerulus （Mouse）	5 gddY mice， 5 ddY mice	scRNA-seq	SMART-seq2	［39］
PMN	2021	XU，et al.	Kidney biopsy	6 PMN， 2 controls	scRNA-seq	10×Genomics	［43］
FSGS	2021	MENON， et al.	Kidney	24 healthy single-cell samples	scRNA-seq	10×Genomics	［41］
FSGS	2021	LATT， et al.	Urine	23 urine cell samples from 12 subjects	scRNA-seq	10×Genomics	［42］

Disease	Publi-cation Year	Author	Sample source	Sample number	Technology	Platform	Reference
DN	2019	FU， et al.	Glomerulus （Mouse）	2 groups，n=3/group： eNOS^-/- + Vehicle， eNOS^-/- + STZ	scRNA-seq	Fluidigm C1	［28］
	2019	WILSON， et al.	Nephrectomy	3 diabetic nephropathy samples， 3 control samples	snRNA-seq	10×Genomics	［31］
	2021	ABEDINI， et al.	Urine	17 urine samples from 5 subjects， 1 pooled sample from 10 healthy individuals	scRNA-seq	10×Genomics	［33］
	2021	WU，et al.	Kidney （Mouse）	5 groups，n=2‒ 4/group： db/m+vehicle， db/db + vehicle， db/db + dapagliflflozin， db/db + irbesartan，db/db + dapagliflflozin+irbesartan	scRNA-seq	10×Genomics	［34］
	2022	WU，et al.	Kidney （Mouse）	7 groups， two early time points/group， 70 mice in total： ReninAAV Unx db/db treated with Vehicle， Lisinopril， Rosiglitazone， JNJ-39933673， Lisinopril + JNJ-39933673， Lisinopril + rosiglitazone； LacZ AAV db/m	snRNA-seq	10×Genomics	［35］
	2022	WU，et al.	Kidney （Mouse）		RNA-seq		［35］
LN	2019	ARAZI，et al.	Kidney biopsy	24 lupus nephritis， 10 controls	scRNA-seq	CEL-Seq2	［21］
			Urine	8 lupus nephritis	scRNA-seq	CEL-Seq2
			PBMC	10 lupus nephritis， 6 controls	scRNA-seq	10×Genomics
			PBMC	10 lupus nephritis， 6 controls	RNA-seq
	2019	DER， et al.	Kidney biopsy	21 lupus nephritis， 3 controls	scRNA-seq	Fluidigm C1	［22］
			Skin biopsy	17 lupus nephritis， 3 controls
			PBMC	8 lupus nephritis
IgAN	2020	ZHENG， et al.	Kidney	13 IgAN，6 nephropathy samples from controls	scRNA-seq	STRT-Seq	［37］
	2020	ZHENG， et al.	CD14+ PBMC	5 IgAN， 5 controls	scRNA-seq	STRT-Seq	［37］
	2021	TANG， et al.	Kidney biopsy	4 IgAN， 1 control	scRNA-seq	10×Genomics	［38］
	2021	ZENG， et al.	PBMC	10 IgAN， 6 controls	scRNA-seq	BD Rhapsody	［40］
	2022	ZAMBRANO， et al.	Glomerulus （Mouse）	5 gddY mice， 5 ddY mice	scRNA-seq	SMART-seq2	［39］
PMN	2021	XU，et al.	Kidney biopsy	6 PMN， 2 controls	scRNA-seq	10×Genomics	［43］
FSGS	2021	MENON， et al.	Kidney	24 healthy single-cell samples	scRNA-seq	10×Genomics	［41］
FSGS	2021	LATT， et al.	Urine	23 urine cell samples from 12 subjects	scRNA-seq	10×Genomics	［42］

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