The first human lung cell atlas was born: 2.4 million+ cells were sequenced

• Facebook
• Twitter
• Reddit
• Tumblr
• LinkedIn
• Pinterest
• RSS Feed
• Link

The first human lung cell atlas was born: 2.4 million+ cells were sequenced, and a variety of new cell types were discovered, and the health/disease status of the lungs has been comprehensively referenced since then

• AstraZeneca Admits for the First Time that its COVID Vaccine Has Blood Clot Side Effects
• Was COVID virus leaked from the Chinese WIV lab?
• HIV Cure Research: New Study Links Viral DNA Levels to Spontaneous Control
• FDA has mandated a top-level black box warning for all marketed CAR-T therapies
• Can people with high blood pressure eat peanuts?
• What is the difference between dopamine and dobutamine?
• How long can the patient live after heart stent surgery?

“Nature Medicine”: The first human lung cell atlas was born: 2.4 million+ cells were sequenced, and a variety of new cell types were discovered, and the health/disease status of the lungs has been comprehensively referenced since then. 

Single-cell sequencing technology has changed our understanding of human tissue, but a single study usually has a limited number of samples and differences in the definition of cell types.

Integrating multiple single-cell data sets can eliminate the limitations of a single study and identify population-level differences. Variability, advancing the understanding of differences between healthy and diseased tissues.

In the recent “Nature Medicine” magazine, an international research team published the largest and most comprehensive Human Lung Cell Atlas (HLCA) to date, integrating data from 49 human respiratory system databases, including over 2.4 million data from 486 participants. cells.

The corresponding author of the study is from the Institute of Computational Biology and the Institute of Lung Health and Immunity, Helmholtz Center Munich, Germany [1].

 HLCA annotated different cell types based on matching marker genes , including some rare and previously undiscovered, and highlighted cellular differences among healthy individuals.

Using HLCA as a reference for disease studies, the research team also identified a shared cellular state in multiple lung diseases , such as SPP1 + pro-fibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis, and lung cancer , which contributes to the Our understanding of lung disease provides new insights while helping to identify new therapeutic targets.

To construct the HLCA, the researchers first collected single-cell RNA-sequencing data and detailed, unified technical, biological, and demographic metadata from 14 datasets, including 107 individuals with varying age, sex, race, BMI, and smoking status. 166 tissue samples from participants.

They projected the anatomical position of the sample onto a one-dimensional common coordinate frame (CCF), representing the origin of the respiratory system from the proximal end to the distal end, to standardize the origin of the anatomical position, and constructed a five-level hierarchical cell identity reference frame, each data The collected cell identity labels were mapped into a hierarchical reference frame, the cell type nomenclature was unified, and the proportion of different cell types was calculated for each sample.

After integration, the researchers built the HLCA core, on which they mapped 35 additional datasets containing disease samples to the HLCA core, expanding the total number of cells included in the atlas to 2.4 million.

HLCA overview

HLCA identified 6 cell types not previously found in human lung tissue or found only in individual studies , including migratory dendritic cells (312), hematopoietic stem cells (60), hyperproliferative mounded epithelial cells ( 4600), type 0 alveolar cells (1440), terminal prebronchiolar secretory cells (4393) and a subpopulation of smooth muscle cells (335), which are overwhelmingly present in the airways and express typical Smooth muscle cell markers CNN1 and MYH11 and a unique marker FAM83D .

Demographics and other factors influence cellular transcriptional phenotypes, e.g. sex was most correlated with transcriptome variation in lymphoid endothelial cells, BMI was most correlated with variation in B and T cells, smoking status was most correlated with innate lymphoid/natural killer The cellular variants had the highest correlations , helping researchers understand the impact of risk factors such as gender, BMI and smoking on the progression of lung tissue from a healthy state to a diseased state.

In single-cell studies of disease, sufficient numbers of matched control samples are required to correctly identify disease-specific changes.

Previous studies have suggested that ACKR1 is specifically highly expressed in tumor endothelial cells and is associated with poor prognosis, but based on multiple mapping data sets and HLCA controls in this study, ACKR1 is also highly expressed in healthy tissues, especially in vein endothelial cells , suggesting that ACKR1 is not a tumor-specific marker of endothelial cells.

Thus, HLCA can provide comprehensive healthy controls for disease studies, preventing limitations in sampling and experimental design from being misinterpreted as differences between healthy and diseased tissues.

In addition, HLCA can also provide a comprehensive and reliable background reference for large-scale disease genetics research such as genome-wide association studies (GWAS).

Association of HLCA cell types with four different lung states based on previous GWAS

Due to the inclusion of datasets containing disease samples, HLCA can also provide references to disease-specific cellular states.

Taking idiopathic pulmonary fibrosis (IPF) as an example, based on a single previous study, the researchers found that cells labeled as alveolar fibroblasts consistently exhibited high uncertainty in IPF samples compared with healthy controls, whereas Based on HLCA and the included IPF datasets, cluster analysis of alveolar fibroblasts showed that the vast majority of cells derived from IPF patients clustered in one cluster, characterized by high expression of IPF-related genes (CCL2, COL1A1, CTHRC1, and MMP19 ) , As well as fibrosis-related markers, including the extracellular matrix breakdown inhibitor SERPINE1 and the chronic hypoxia response gene HIF1A .

HLCA contains data from multiple lung diseases. Previous studies have found pro-fibrotic SPP1 + monocyte-derived macrophages (MDMs) in IPF, COVID-19, and lung cancer. Using HLCA, the researchers reproduced this discovery.

They performed a cluster analysis of all MDM in the HLCA and identified four major MDM subtypes with distinct patterns of gene expression and disease enrichment representing distinct stages of monocyte-to-MDM differentiation and adaptation to the disease microenvironment .

The first type is early and inflammatory MDM (cluster 2), with high expression of CCL2 , mainly from alveolar lavage fluid samples of patients with COVID-19 pneumonia in the early course of the disease, and the second type is MDM expressing genes related to inflammation and phagocytosis (cluster 2). category 4), enriched in COVID-19 pneumonia and lung cancer patients, the third category is more differentiated MDM (cluster 3), mainly from non-disease samples, and the fourth category MDM highly expresses SPP1, LPL and CHIT1 ( Cluster 0), mainly from IPF samples, was also enriched in samples from patients who died late in the course of COVID-19 and developed pulmonary fibrosis after COVID-19, and lung cancer.

Number and marker genes of different MDM disease states

SPP1, LPL , and CHIT1 have all been proven to play a causal role in the development of pulmonary fibrosis, and CHIT1 is currently a research target for IPF therapy.

This suggests that late-stage COVID-19 and lung cancer “share” part of the MDM fibrotic phenotype with IPF, potentially accelerating the discovery of effective disease therapies.

In general, this research, as part of the global human cell atlas project, established the first complete human lung single-cell atlas , with healthy lung cells as the core, and radiated more than ten lung disease data.

Researchers at Northwestern University Feinberg School of Medicine who participated in the study said that HLCA, as the first complete reference map of major organs, is a milestone in achieving a complete human cell map and will change our understanding of biology and disease.

references:

[1] Sikkema L, Ramírez-Suástegui C, Strobl DC, et al. An integrated cell atlas of the lung in health and disease[J]. Nature Medicine, 2023: 1-15.

The first human lung cell atlas was born: 2.4 million+ cells were sequenced, and a variety of new cell types were discovered, and the health/disease status of the lungs has been comprehensively referenced since then

(source:internet, reference only)

Disclaimer of medicaltrend.org

Important Note: The information provided is for informational purposes only and should not be considered as medical advice.