Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression.
Amin AbediniJonathan LevinsohnKonstantin A KlötzerBernhard DumoulinZiyuan MaJulia FrederickPoonam DhillonMichael S BalzerRojesh ShresthaHongbo LiuSteven VitaleAndi M BergesonKishor Devalaraja-NarashimhaPaola GrandiTanmoy BhattacharyyaErding HuSteven S PullenCarine M Boustany-KariPaolo GuarnieriAnil KarihalooDaniel TraumHanying YanKyle ColemanMatthew PalmerLea Sarov-BlatLori MortonChristopher A HunterKlaus H KaestnerMingyao LiKatalin SusztákPublished in: Nature genetics (2024)
Kidneys are intricate three-dimensional structures in the body, yet the spatial and molecular principles of kidney health and disease remain inadequately understood. We generated high-quality datasets for 81 samples, including single-cell, single-nuclear, spot-level (Visium) and single-cell resolution (CosMx) spatial-RNA expression and single-nuclear open chromatin, capturing cells from healthy, diabetic and hypertensive diseased human kidneys. Combining these data, we identify cell types and map them to their locations within the tissue. Unbiased deconvolution of the spatial data identifies the following four distinct microenvironments: glomerular, immune, tubule and fibrotic. We describe the complex organization of microenvironments in health and disease and find that the fibrotic microenvironment is able to molecularly classify human kidneys and offers an improved prognosis compared to traditional histopathology. We provide a comprehensive spatially resolved molecular roadmap of the human kidney and the fibrotic process, demonstrating the clinical utility of spatial transcriptomics.
Keyphrases
- single cell
- endothelial cells
- rna seq
- healthcare
- induced pluripotent stem cells
- systemic sclerosis
- public health
- stem cells
- pluripotent stem cells
- high throughput
- idiopathic pulmonary fibrosis
- mental health
- type diabetes
- gene expression
- blood pressure
- dna damage
- risk assessment
- poor prognosis
- mesenchymal stem cells
- machine learning
- genome wide
- bone marrow
- cell therapy
- social media
- long non coding rna