Evidence map›Paper›PMID 37777674›Full record

ArticleInflammation2024

Single-Cell Sequencing Reveals the Expression of Immune-Related Genes in Macrophages of Diabetic Kidney Disease.

Xian Shao, Yueyue Shi, Yao Wang, Li Zhang, Pufei Bai, JunMei Wang, Ashanjiang Aniwan, Yao Lin, Saijun Zhou, Pei Yu

Abstract read
PubMed Publisher
In one paragraph

Article in Inflammation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Xian Shao *NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Yueyue Shi *Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300134, China.
Yao Wang *Clinical Medical College & Affiliated Hospital of Chengdu University, Chengdu University, Chengdu, Sichuan, 610081, People's Republic of China.
Li ZhangNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Pufei BaiNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
JunMei WangNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Ashanjiang AniwanNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Yao LinNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Saijun ZhouNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Pei YuNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China. peiyu@tmu.edu.cn.ORCID http://orcid.org/0000-0001-6137-5824
Tianjin Medical University · CNChengdu University · CNSecond Hospital of Tianjin Medical University · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is characterized by macrophage infiltration, which requires further investigation. This study aims to identify immune-related genes (IRGs) in macrophage and explore their potential as therapeutic targets. This study analyzed isolated glomerular cells from three diabetic mice and three control mice. A total of 59 glomeruli from normal kidney samples and 66 from DKD samples were acquired from four kidney transcriptomic profiling datasets. Bioinformatics analysis was conducted using both single-cell RNA (scRNA) and bulk RNA sequencing data to investigate inflammatory responses in DKD. Additionally, the "AUCell" function was used to investigate statistically different gene sets. The significance of each interaction pair was determined by assigning a probability using "CellChat." The study also analyzed the biological diagnostic importance of immune hub genes for DKD and validated the expression of these immune genes in mice models. The top 2000 highly variable genes (HVGs) were identified after data normalization. Subsequently, a total of eight clusters were identified. It is worth mentioning that macrophages showed the highest percentage increase among all cell types in the DKD group. Furthermore, the present study observed significant differences in gene sets related to inflammatory responses and complement pathways. The study also identified several receptor-ligand pairs and co-stimulatory interactions between endothelial cells and macrophages. Notably, SYK, ITGB2, FCER1G, and VAV1 were identified as immunological markers of DKD with promising predictive ability. This study identified distinct cell clusters and four marker genes. SYK, ITGB2, FCER1G, and VAV1 may be important roles. Consequently, the present study extends our understanding regarding IRGs in DKD and provides a foundation for future investigations into the underlying mechanisms.

Indexed as

Diabetes Mellitus, ExperimentalDiabetic NephropathiesAnimalsEndothelial CellsKidney GlomerulusMacrophagesMicediabetic kidney diseaseinflammationmacrophages.marker genessingle-cell RNA sequencing

Identifiers

PMID37777674
OpenAlexW4387215048

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.