Mardiyyah/TAPT_data_V2_split · Datasets at Hugging Face

PMCID stringclasses 24 values	Title stringclasses 24 values	Sentences stringlengths 2 40.7k
PMC10287567	An integrated cell atlas of the lung in health and disease.	In contrast, in plasma cells, high BMI is associated with downregulation of gene sets associated with immune response and upregulation of gene sets associated with cellular respiration, the cell cycle and DNA repair.
PMC10287567	An integrated cell atlas of the lung in health and disease.	This is consistent with obesity being a known risk factor for multiple myeloma—a plasma cell malignancy.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Thus, the HLCA enables a detailed understanding of the effects of anatomical and demographic covariates on the cellular landscape of the lung and their relation to disease.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Biological and technical factors can also affect cell type proportions.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Indeed, all cell types show changes in abundance as a function of anatomical location (Fig. 4c and Extended Data Fig. 5).
PMC10287567	An integrated cell atlas of the lung in health and disease.	For example, ionocytes are present at comparable proportions in the airway epithelium, from the larger lower airways (CCF score = 0.36) down to the distal lobular airways (CCF score = 0.81), while being largely absent in the lung parenchyma (CCF score = 0.97).
PMC10287567	An integrated cell atlas of the lung in health and disease.	In contrast, neuroendocrine cells are predominantly observed in the larger lower airways but are absent from more distal parts of the bronchial tree (Fig. 4c).
PMC10287567	An integrated cell atlas of the lung in health and disease.	In some cases, these proportions are highly dependent on the tissue sampling method and the dissociation protocol used (for example, for smooth muscle FAM83D cells; Extended Data Fig. 5).
PMC10287567	An integrated cell atlas of the lung in health and disease.	These observations shed light on the effects of biological and technical factors on the abundance of cell types in different parts of the lung and can help guide important choices in study design.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The HLCA core contains an unprecedented diversity of donors, sampling protocols and cell identities, and can serve as a transcriptomic reference for lung research.
PMC10287567	An integrated cell atlas of the lung in health and disease.	New datasets can be mapped to this reference to substantially speed up data analysis by transferring consensus cell identity annotations to the new data.
PMC10287567	An integrated cell atlas of the lung in health and disease.	We tested this on a recently released multimodal lung dataset (Methods, Fig. 6a and Extended Data Fig. 6).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Overall, the transferred labels were correct in the majority of cases, with 68% of the cells correctly labeled, 14% of labels incorrectly labeled and 18% set to unknown due to highly uncertain labeling (Fig. 5b and Methods).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Uncertain labels were observed specifically in continuous transitions from one cell type to another and among cellular identities not present in the HLCA core, including rare cell identities (erythrocytes (n = 328), chondrocytes (n = 42), myelinating Schwann cells (n = 7), nonmyelinating Schwann cells (n = 29) and nerve-associated fibroblasts (n = 66); Fig. 5b and Extended Data Fig. 6d).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Taken together, these results show that the HLCA core can be used for highly detailed annotation of new datasets, while allowing for the identification of unknown cell types in these datasets based on label transfer uncertainty.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Fig. 5The HLCA core serves as a reference for label transfer and data contextualization.a, UMAP of the jointly embedded HLCA core (gray) and the projected healthy lung dataset (colored by label transfer uncertainty).
PMC10287567	An integrated cell atlas of the lung in health and disease.	HLCA cell types surrounding regions of high uncertainty are labeled.
PMC10287567	An integrated cell atlas of the lung in health and disease.	b, Percentage of cells from the newly mapped healthy lung dataset that are annotated either correctly or incorrectly by label transfer annotation or annotated as unknown, split by original cell type label (number of cells in parentheses).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Cell type labels not present in the HLCA are boxed.
PMC10287567	An integrated cell atlas of the lung in health and disease.	c, Top, percentage of cells derived from tumor tissue, per endothelial cell cluster from the joint HLCA core and lung cancer data embedding.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Only clusters with at least ten tumor cells are shown.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Clusters are named based on the dominant HLCA core cell type annotation in the cluster.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Middle, box plot showing the expression of EDNRB in endothelial cell clusters, split by tissue source.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Bottom, as in the middle plot but for the expression of ACKR1.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Numbers of cells per group were as follows: 6,574 (endothelial cell aerocyte capillary), 7,379 (endothelial cell arterial (I)), 10,906 (endothelial cell general capillary (I)), 3,440 (endothelial cell general capillary (II)), 2,859 (endothelial cell general capillary (III)), 6,318 (endothelial cell venous pulmonary) and 7,161 (endothelial cell venous systemic).
PMC10287567	An integrated cell atlas of the lung in health and disease.	d, Association of HLCA cell types with four different lung phenotypes based on previously performed GWASs.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The horizontal dashed lines indicate a significance threshold of α = 0.05.
PMC10287567	An integrated cell atlas of the lung in health and disease.	P values were calculated using linkage disequilibrium score regression (Methods) and multiple testing corrected with the Benjamini–Hochberg procedure.
PMC10287567	An integrated cell atlas of the lung in health and disease.	e, Cell type proportions in lung bulk expression samples as estimated from HLCA-based cell type deconvolution, comparing controls (n = 281) versus donors with severe COPD (GOLD stage 3/4; n = 83).
PMC10287567	An integrated cell atlas of the lung in health and disease.	f, UMAP of fibroblast-dominated clusters from the jointly embedded HLCA core and mapped healthy lung dataset, colored by spatial cluster, with cells outside of the indicated clusters colored in gray.
PMC10287567	An integrated cell atlas of the lung in health and disease.	For all boxplots, the boxes show the median and interquartile range.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Data points more than 1.5 times the interquartile range outside the low and high quartile are considered outliers.
PMC10287567	An integrated cell atlas of the lung in health and disease.	In c, these are not shown (see Supplementary Fig. 6 for full results), whereas in e, they are shown.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Whiskers extend to the furthest nonoutlier point.
PMC10287567	An integrated cell atlas of the lung in health and disease.	corr.,
PMC10287567	An integrated cell atlas of the lung in health and disease.	corrected; FVC, forced vital capacity; MAIT cells, mucosal-associated invariant T cells; NKT cells, natural killer T cells.
PMC10287567	An integrated cell atlas of the lung in health and disease.	a, UMAP of the jointly embedded HLCA core (gray) and the projected healthy lung dataset (colored by label transfer uncertainty).
PMC10287567	An integrated cell atlas of the lung in health and disease.	HLCA cell types surrounding regions of high uncertainty are labeled.
PMC10287567	An integrated cell atlas of the lung in health and disease.	b, Percentage of cells from the newly mapped healthy lung dataset that are annotated either correctly or incorrectly by label transfer annotation or annotated as unknown, split by original cell type label (number of cells in parentheses).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Cell type labels not present in the HLCA are boxed.
PMC10287567	An integrated cell atlas of the lung in health and disease.	c, Top, percentage of cells derived from tumor tissue, per endothelial cell cluster from the joint HLCA core and lung cancer data embedding.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Only clusters with at least ten tumor cells are shown.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Clusters are named based on the dominant HLCA core cell type annotation in the cluster.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Middle, box plot showing the expression of EDNRB in endothelial cell clusters, split by tissue source.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Bottom, as in the middle plot but for the expression of ACKR1.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Numbers of cells per group were as follows: 6,574 (endothelial cell aerocyte capillary), 7,379 (endothelial cell arterial (I)), 10,906 (endothelial cell general capillary (I)), 3,440 (endothelial cell general capillary (II)), 2,859 (endothelial cell general capillary (III)), 6,318 (endothelial cell venous pulmonary) and 7,161 (endothelial cell venous systemic).
PMC10287567	An integrated cell atlas of the lung in health and disease.	d, Association of HLCA cell types with four different lung phenotypes based on previously performed GWASs.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The horizontal dashed lines indicate a significance threshold of α = 0.05.
PMC10287567	An integrated cell atlas of the lung in health and disease.	P values were calculated using linkage disequilibrium score regression (Methods) and multiple testing corrected with the Benjamini–Hochberg procedure.
PMC10287567	An integrated cell atlas of the lung in health and disease.	e, Cell type proportions in lung bulk expression samples as estimated from HLCA-based cell type deconvolution, comparing controls (n = 281) versus donors with severe COPD (GOLD stage 3/4; n = 83).
PMC10287567	An integrated cell atlas of the lung in health and disease.	f, UMAP of fibroblast-dominated clusters from the jointly embedded HLCA core and mapped healthy lung dataset, colored by spatial cluster, with cells outside of the indicated clusters colored in gray.
PMC10287567	An integrated cell atlas of the lung in health and disease.	For all boxplots, the boxes show the median and interquartile range.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Data points more than 1.5 times the interquartile range outside the low and high quartile are considered outliers.
PMC10287567	An integrated cell atlas of the lung in health and disease.	In c, these are not shown (see Supplementary Fig. 6 for full results), whereas in e, they are shown.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Whiskers extend to the furthest nonoutlier point.
PMC10287567	An integrated cell atlas of the lung in health and disease.	corr.,
PMC10287567	An integrated cell atlas of the lung in health and disease.	corrected; FVC, forced vital capacity; MAIT cells, mucosal-associated invariant T cells; NKT cells, natural killer T cells.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Single-cell studies of disease rely on adequate, matching control samples to allow correct identification of disease-specific changes.
PMC10287567	An integrated cell atlas of the lung in health and disease.	To demonstrate the ability of the HLCA core to serve as a comprehensive healthy control and contextualize disease data, we mapped scRNA-seq data from lung cancer samples to the HLCA core (Methods and Extended Data Fig. 7a–c).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Using HLCA label transfer, we correctly identified cell states missing from the HLCA core as unknown (cancer cells and erythroblasts).
PMC10287567	An integrated cell atlas of the lung in health and disease.	The remaining cells were annotated correctly in 77%, incorrectly in 1% and as unknown in 22% of cases (Extended Data Fig. 7d–g).
PMC10287567	An integrated cell atlas of the lung in health and disease.	A finding of the original study was the separation of endothelial cells into tumor-associated and normal cells.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Clustering of the projected dataset with the HLCA reference showed that cells expressing the suggested tumor-associated marker ACKR1 were also abundant in healthy tissue from the HLCA core, specifically in venous endothelial cells (both pulmonary and systemic, Fig. 5c and Supplementary Fig. 6a–c).
PMC10287567	An integrated cell atlas of the lung in health and disease.	This suggests that ACKR1 is a general marker of venous endothelial cells rather than a tumor-specific endothelial cell marker.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Similarly, the reported normal endothelial cell marker EDNRB characterizes aerocyte capillary endothelial cells, both in tumor and in healthy tissue (Fig. 5c and Supplementary Fig. 6d).
PMC10287567	An integrated cell atlas of the lung in health and disease.	As endothelial cell numbers in the original study were low, correctly identifying and distinguishing these cell types without a larger healthy reference is challenging.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Thus, by serving as a comprehensive healthy control, the HLCA prevents misinterpretation of limitations in sampling and experimental design as meaningful differences between healthy and diseased tissue.
PMC10287567	An integrated cell atlas of the lung in health and disease.	In addition, the HLCA can provide context to the results of large-scale genetic studies of disease.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Genome-wide association studies (GWASs) link disease with specific genomic variants that may confer an increased risk of disease.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Previous studies have linked such variants to cell type-specific mechanistic hypotheses, which are often lacking in the initial association study.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Yet, these studies fail to include all known lung cell types in their cell type reference.
PMC10287567	An integrated cell atlas of the lung in health and disease.	To demonstrate the value of the HLCA core in contextualizing genetic data, we mapped association results from four GWASs of lung function or disease to the HLCA core cell types, by testing significant enrichment of both weakly and strongly disease-associated variants in regions of genes that characterize each cell type (Fig. 5d, Supplementary Fig. 7 and Methods).
PMC10287567	An integrated cell atlas of the lung in health and disease.	We show that genomic variants linked to lung function (forced vital capacity) are associated with smooth muscle (adjusted P value (Padj) = 0.07), alveolar fibroblasts (Padj = 0.07), peribronchial fibroblasts (Padj = 0.07) and myofibroblasts (Padj = 0.07), suggesting that these fibroblast subtypes play a causative role in inherited differences in lung function.
PMC10287567	An integrated cell atlas of the lung in health and disease.	We further find a significant association of lung T cells with asthma-associated single-nucleotide polymorphisms (SNPs) (Padj = 0.005).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Lung adenocarcinoma-associated variants trend towards AT2 cells (Padj = 0.18) and myofibroblasts are significantly associated with chronic obstructive pulmonary disease (COPD) GWAS SNPs (Padj = 0.04).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Thus, by linking genetic predispositions to lung cell types, the HLCA core serves as a valuable resource with which to improve our understanding of lung function and disease.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Finally, the HLCA can be used as a reference for cell type deconvolution of bulk RNA expression samples, which have been shown to reflect cell type proportions more accurately than scRNA-seq datasets.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Inferring cell type proportions from bulk RNA samples from nasal brushings and bronchial biopsies using the HLCA core (Supplementary Table 10, Supplementary Fig. 8a and Methods) revealed no significant cell type compositional changes associated with corticosteroid inhalation or asthma, respectively (Supplementary Fig. 8b,c and Supplementary Table 11).
PMC10287567	An integrated cell atlas of the lung in health and disease.	In contrast, we find that the proportion of capillary endothelial cells in lung resection tissue from the Lung Tissue Database is higher in samples from patients with severe COPD (GOLD stage 3 or 4) than in those from non-COPD controls matched for age and smoking history (Padj = 0.0004).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Conversely, alveolar and interstitial macrophages, AT2 cells and dendritic cells decrease in proportion (Fig. 5e, Supplementary Fig. 8d and Supplementary Table 11; Padj = 0.0007, 0.0003, 0.005 and 3.21 × 10, respectively).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Finally, smooth muscle shows the largest shift in proportion, increasing significantly in patients with severe COPD (P = 1.85 × 10) in line with previous work.
PMC10287567	An integrated cell atlas of the lung in health and disease.	As deconvolution of bulk samples using the HLCA can reveal disease-specific changes in cell type composition, we provide publicly available preprocessed cell type signature matrices based on the HLCA core (https://github.com/LungCellAtlas/HLCA).
PMC10287567	An integrated cell atlas of the lung in health and disease.	As knowledge of cell types in the lung expands, and the sizes of newly generated datasets increase, annotations in the HLCA core will need to be further refined.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The HLCA and its annotations can be updated by learning from new data projected onto the reference.
PMC10287567	An integrated cell atlas of the lung in health and disease.	We simulated such an HLCA update using the previously projected healthy lung dataset, specifically focusing on the cell identities that were distinguished based on their tissue location in matched spatial transcriptomic data (spatially annotated cell types).
PMC10287567	An integrated cell atlas of the lung in health and disease.	These cell identities were present at very low frequencies (median: 0.005% of all cells; Supplementary Fig. 9a).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Both spatially annotated mesenchymal cell types with more than 40 cells (immune-recruiting fibroblasts and chondrocytes) and two rare cell types (myelinating Schwann cells and perineurial nerve-associated fibroblasts) were recovered in distinct clusters (spatially annotated clusters), and three of these (all except chondrocytes) also contained cells from the HLCA core, thereby enabling a refinement of existing HLCA core annotations using the spatial context from the projected dataset (Fig. 5f and Supplementary Fig. 9b,c).
PMC10287567	An integrated cell atlas of the lung in health and disease.	In this manner the HLCA core and its annotations can be refined by mapping new datasets to the atlas and incorporating annotations from these new datasets into the reference.
PMC10287567	An integrated cell atlas of the lung in health and disease.	To extend the atlas and include samples from lung disease, we mapped 1,797,714 cells from 380 healthy and diseased individuals from 37 datasets (four unpublished and 33 published) to the HLCA core using scArches, bringing the HLCA to a total of 2.4 million cells from 486 individuals (Fig. 6a and Supplementary Table 1).
PMC10287567	An integrated cell atlas of the lung in health and disease.	Label transfer from the HLCA core to the newly mapped datasets enabled detailed cell type annotation across datasets even for rare cells, including 2,048 migratory dendritic cells identified across 28 datasets with label transfer, whereas this cell type was originally labeled in only two of 12 labeled datasets (Extended Data Fig. 8).Fig.
PMC10287567	An integrated cell atlas of the lung in health and disease.	6The extended HLCA enables the identification of disease-associated cell states.a, UMAP of the extended HLCA colored by coarse annotation (HLCA core) or in gray (cells mapped to the core).
PMC10287567	An integrated cell atlas of the lung in health and disease.	b, Uncertainty of label transfer from the HLCA core to newly mapped datasets, categorized by several experimental or biological features.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Categories with fewer than two instances are not shown.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The numbers of datasets per category were as follows: 30 cells, 7 nuclei, 23 healthy, 5 IPF, 3 CF, 3 carcinoma, 4 ILD, 8 surgical resection, 7 donor lung, 12 lung explant, 6 bronchoalveolar lavage fluid, 4 autopsy, 9 10x 5′, 31 10x 3′, 4 Drop-Seq and 3 Seq-Well.
PMC10287567	An integrated cell atlas of the lung in health and disease.	c, Bottom, mean label transfer uncertainty per mapped healthy lung sample in the HLCA extension, grouped into age bins and colored by study.
PMC10287567	An integrated cell atlas of the lung in health and disease.	The numbers of mapped samples per age bin were as follows: 43 for 0–10 years, 33 for 10–20 years, 31 for 20–30 years, 23 for 30–40 years, 19 for 40–50 years, 12 for 50–60 years, 9 for 60–70 years, 8 for 70–80 years and 2 for 80–90 years.
PMC10287567	An integrated cell atlas of the lung in health and disease.	Top, bar plot showing the number of donors per age group in the HLCA core.
PMC10287567	An integrated cell atlas of the lung in health and disease.	d, Violin plot of label transfer uncertainty per transferred cell type label for a single mapped IPF dataset, split into cells from healthy donors (blue) and donors with IPF (orange).
PMC10287567	An integrated cell atlas of the lung in health and disease.	e, Uncertainty-based disease signature scores among alveolar fibroblasts and alveolar macrophages, split into cells from control donors (n = 10,453 and 1,812, respectively), and low-uncertainty cells (n = 1,419 and 200, respectively) and high-uncertainty cells (n = 1,172 and 162, respectively) from donors with IPF.
PMC10287567	An integrated cell atlas of the lung in health and disease.	f, UMAP embedding of alveolar fibroblasts (labeled with manual annotation (core) or label transfer (five IPF datasets)) colored by Leiden cluster.

PMC10287567

An integrated cell atlas of the lung in health and disease.

In contrast, in plasma cells, high BMI is associated with downregulation of gene sets associated with immune response and upregulation of gene sets associated with cellular respiration, the cell cycle and DNA repair.

PMC10287567

An integrated cell atlas of the lung in health and disease.

This is consistent with obesity being a known risk factor for multiple myeloma—a plasma cell malignancy.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Thus, the HLCA enables a detailed understanding of the effects of anatomical and demographic covariates on the cellular landscape of the lung and their relation to disease.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Biological and technical factors can also affect cell type proportions.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Indeed, all cell types show changes in abundance as a function of anatomical location (Fig. 4c and Extended Data Fig. 5).

PMC10287567

An integrated cell atlas of the lung in health and disease.

For example, ionocytes are present at comparable proportions in the airway epithelium, from the larger lower airways (CCF score = 0.36) down to the distal lobular airways (CCF score = 0.81), while being largely absent in the lung parenchyma (CCF score = 0.97).

PMC10287567

An integrated cell atlas of the lung in health and disease.

In contrast, neuroendocrine cells are predominantly observed in the larger lower airways but are absent from more distal parts of the bronchial tree (Fig. 4c).

PMC10287567

An integrated cell atlas of the lung in health and disease.

In some cases, these proportions are highly dependent on the tissue sampling method and the dissociation protocol used (for example, for smooth muscle FAM83D cells; Extended Data Fig. 5).

PMC10287567

An integrated cell atlas of the lung in health and disease.

These observations shed light on the effects of biological and technical factors on the abundance of cell types in different parts of the lung and can help guide important choices in study design.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The HLCA core contains an unprecedented diversity of donors, sampling protocols and cell identities, and can serve as a transcriptomic reference for lung research.

PMC10287567

An integrated cell atlas of the lung in health and disease.

New datasets can be mapped to this reference to substantially speed up data analysis by transferring consensus cell identity annotations to the new data.

PMC10287567

An integrated cell atlas of the lung in health and disease.

We tested this on a recently released multimodal lung dataset (Methods, Fig. 6a and Extended Data Fig. 6).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Overall, the transferred labels were correct in the majority of cases, with 68% of the cells correctly labeled, 14% of labels incorrectly labeled and 18% set to unknown due to highly uncertain labeling (Fig. 5b and Methods).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Uncertain labels were observed specifically in continuous transitions from one cell type to another and among cellular identities not present in the HLCA core, including rare cell identities (erythrocytes (n = 328), chondrocytes (n = 42), myelinating Schwann cells (n = 7), nonmyelinating Schwann cells (n = 29) and nerve-associated fibroblasts (n = 66); Fig. 5b and Extended Data Fig. 6d).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Taken together, these results show that the HLCA core can be used for highly detailed annotation of new datasets, while allowing for the identification of unknown cell types in these datasets based on label transfer uncertainty.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Fig. 5The HLCA core serves as a reference for label transfer and data contextualization.a, UMAP of the jointly embedded HLCA core (gray) and the projected healthy lung dataset (colored by label transfer uncertainty).

PMC10287567

An integrated cell atlas of the lung in health and disease.

HLCA cell types surrounding regions of high uncertainty are labeled.

PMC10287567

An integrated cell atlas of the lung in health and disease.

b, Percentage of cells from the newly mapped healthy lung dataset that are annotated either correctly or incorrectly by label transfer annotation or annotated as unknown, split by original cell type label (number of cells in parentheses).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Cell type labels not present in the HLCA are boxed.

PMC10287567

An integrated cell atlas of the lung in health and disease.

c, Top, percentage of cells derived from tumor tissue, per endothelial cell cluster from the joint HLCA core and lung cancer data embedding.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Only clusters with at least ten tumor cells are shown.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Clusters are named based on the dominant HLCA core cell type annotation in the cluster.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Middle, box plot showing the expression of EDNRB in endothelial cell clusters, split by tissue source.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Bottom, as in the middle plot but for the expression of ACKR1.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Numbers of cells per group were as follows: 6,574 (endothelial cell aerocyte capillary), 7,379 (endothelial cell arterial (I)), 10,906 (endothelial cell general capillary (I)), 3,440 (endothelial cell general capillary (II)), 2,859 (endothelial cell general capillary (III)), 6,318 (endothelial cell venous pulmonary) and 7,161 (endothelial cell venous systemic).

PMC10287567

An integrated cell atlas of the lung in health and disease.

d, Association of HLCA cell types with four different lung phenotypes based on previously performed GWASs.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The horizontal dashed lines indicate a significance threshold of α = 0.05.

PMC10287567

An integrated cell atlas of the lung in health and disease.

P values were calculated using linkage disequilibrium score regression (Methods) and multiple testing corrected with the Benjamini–Hochberg procedure.

PMC10287567

An integrated cell atlas of the lung in health and disease.

e, Cell type proportions in lung bulk expression samples as estimated from HLCA-based cell type deconvolution, comparing controls (n = 281) versus donors with severe COPD (GOLD stage 3/4; n = 83).

PMC10287567

An integrated cell atlas of the lung in health and disease.

f, UMAP of fibroblast-dominated clusters from the jointly embedded HLCA core and mapped healthy lung dataset, colored by spatial cluster, with cells outside of the indicated clusters colored in gray.

PMC10287567

An integrated cell atlas of the lung in health and disease.

For all boxplots, the boxes show the median and interquartile range.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Data points more than 1.5 times the interquartile range outside the low and high quartile are considered outliers.

PMC10287567

An integrated cell atlas of the lung in health and disease.

In c, these are not shown (see Supplementary Fig. 6 for full results), whereas in e, they are shown.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Whiskers extend to the furthest nonoutlier point.

PMC10287567

An integrated cell atlas of the lung in health and disease.

corr.,

PMC10287567

An integrated cell atlas of the lung in health and disease.

corrected; FVC, forced vital capacity; MAIT cells, mucosal-associated invariant T cells; NKT cells, natural killer T cells.

PMC10287567

An integrated cell atlas of the lung in health and disease.

a, UMAP of the jointly embedded HLCA core (gray) and the projected healthy lung dataset (colored by label transfer uncertainty).

PMC10287567

An integrated cell atlas of the lung in health and disease.

HLCA cell types surrounding regions of high uncertainty are labeled.

PMC10287567

An integrated cell atlas of the lung in health and disease.

b, Percentage of cells from the newly mapped healthy lung dataset that are annotated either correctly or incorrectly by label transfer annotation or annotated as unknown, split by original cell type label (number of cells in parentheses).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Cell type labels not present in the HLCA are boxed.

PMC10287567

An integrated cell atlas of the lung in health and disease.

c, Top, percentage of cells derived from tumor tissue, per endothelial cell cluster from the joint HLCA core and lung cancer data embedding.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Only clusters with at least ten tumor cells are shown.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Clusters are named based on the dominant HLCA core cell type annotation in the cluster.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Middle, box plot showing the expression of EDNRB in endothelial cell clusters, split by tissue source.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Bottom, as in the middle plot but for the expression of ACKR1.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Numbers of cells per group were as follows: 6,574 (endothelial cell aerocyte capillary), 7,379 (endothelial cell arterial (I)), 10,906 (endothelial cell general capillary (I)), 3,440 (endothelial cell general capillary (II)), 2,859 (endothelial cell general capillary (III)), 6,318 (endothelial cell venous pulmonary) and 7,161 (endothelial cell venous systemic).

PMC10287567

An integrated cell atlas of the lung in health and disease.

d, Association of HLCA cell types with four different lung phenotypes based on previously performed GWASs.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The horizontal dashed lines indicate a significance threshold of α = 0.05.

PMC10287567

An integrated cell atlas of the lung in health and disease.

P values were calculated using linkage disequilibrium score regression (Methods) and multiple testing corrected with the Benjamini–Hochberg procedure.

PMC10287567

An integrated cell atlas of the lung in health and disease.

e, Cell type proportions in lung bulk expression samples as estimated from HLCA-based cell type deconvolution, comparing controls (n = 281) versus donors with severe COPD (GOLD stage 3/4; n = 83).

PMC10287567

An integrated cell atlas of the lung in health and disease.

f, UMAP of fibroblast-dominated clusters from the jointly embedded HLCA core and mapped healthy lung dataset, colored by spatial cluster, with cells outside of the indicated clusters colored in gray.

PMC10287567

An integrated cell atlas of the lung in health and disease.

For all boxplots, the boxes show the median and interquartile range.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Data points more than 1.5 times the interquartile range outside the low and high quartile are considered outliers.

PMC10287567

An integrated cell atlas of the lung in health and disease.

In c, these are not shown (see Supplementary Fig. 6 for full results), whereas in e, they are shown.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Whiskers extend to the furthest nonoutlier point.

PMC10287567

An integrated cell atlas of the lung in health and disease.

corr.,

PMC10287567

An integrated cell atlas of the lung in health and disease.

corrected; FVC, forced vital capacity; MAIT cells, mucosal-associated invariant T cells; NKT cells, natural killer T cells.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Single-cell studies of disease rely on adequate, matching control samples to allow correct identification of disease-specific changes.

PMC10287567

An integrated cell atlas of the lung in health and disease.

To demonstrate the ability of the HLCA core to serve as a comprehensive healthy control and contextualize disease data, we mapped scRNA-seq data from lung cancer samples to the HLCA core (Methods and Extended Data Fig. 7a–c).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Using HLCA label transfer, we correctly identified cell states missing from the HLCA core as unknown (cancer cells and erythroblasts).

PMC10287567

An integrated cell atlas of the lung in health and disease.

The remaining cells were annotated correctly in 77%, incorrectly in 1% and as unknown in 22% of cases (Extended Data Fig. 7d–g).

PMC10287567

An integrated cell atlas of the lung in health and disease.

A finding of the original study was the separation of endothelial cells into tumor-associated and normal cells.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Clustering of the projected dataset with the HLCA reference showed that cells expressing the suggested tumor-associated marker ACKR1 were also abundant in healthy tissue from the HLCA core, specifically in venous endothelial cells (both pulmonary and systemic, Fig. 5c and Supplementary Fig. 6a–c).

PMC10287567

An integrated cell atlas of the lung in health and disease.

This suggests that ACKR1 is a general marker of venous endothelial cells rather than a tumor-specific endothelial cell marker.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Similarly, the reported normal endothelial cell marker EDNRB characterizes aerocyte capillary endothelial cells, both in tumor and in healthy tissue (Fig. 5c and Supplementary Fig. 6d).

PMC10287567

An integrated cell atlas of the lung in health and disease.

As endothelial cell numbers in the original study were low, correctly identifying and distinguishing these cell types without a larger healthy reference is challenging.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Thus, by serving as a comprehensive healthy control, the HLCA prevents misinterpretation of limitations in sampling and experimental design as meaningful differences between healthy and diseased tissue.

PMC10287567

An integrated cell atlas of the lung in health and disease.

In addition, the HLCA can provide context to the results of large-scale genetic studies of disease.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Genome-wide association studies (GWASs) link disease with specific genomic variants that may confer an increased risk of disease.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Previous studies have linked such variants to cell type-specific mechanistic hypotheses, which are often lacking in the initial association study.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Yet, these studies fail to include all known lung cell types in their cell type reference.

PMC10287567

An integrated cell atlas of the lung in health and disease.

To demonstrate the value of the HLCA core in contextualizing genetic data, we mapped association results from four GWASs of lung function or disease to the HLCA core cell types, by testing significant enrichment of both weakly and strongly disease-associated variants in regions of genes that characterize each cell type (Fig. 5d, Supplementary Fig. 7 and Methods).

PMC10287567

An integrated cell atlas of the lung in health and disease.

We show that genomic variants linked to lung function (forced vital capacity) are associated with smooth muscle (adjusted P value (Padj) = 0.07), alveolar fibroblasts (Padj = 0.07), peribronchial fibroblasts (Padj = 0.07) and myofibroblasts (Padj = 0.07), suggesting that these fibroblast subtypes play a causative role in inherited differences in lung function.

PMC10287567

An integrated cell atlas of the lung in health and disease.

We further find a significant association of lung T cells with asthma-associated single-nucleotide polymorphisms (SNPs) (Padj = 0.005).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Lung adenocarcinoma-associated variants trend towards AT2 cells (Padj = 0.18) and myofibroblasts are significantly associated with chronic obstructive pulmonary disease (COPD) GWAS SNPs (Padj = 0.04).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Thus, by linking genetic predispositions to lung cell types, the HLCA core serves as a valuable resource with which to improve our understanding of lung function and disease.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Finally, the HLCA can be used as a reference for cell type deconvolution of bulk RNA expression samples, which have been shown to reflect cell type proportions more accurately than scRNA-seq datasets.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Inferring cell type proportions from bulk RNA samples from nasal brushings and bronchial biopsies using the HLCA core (Supplementary Table 10, Supplementary Fig. 8a and Methods) revealed no significant cell type compositional changes associated with corticosteroid inhalation or asthma, respectively (Supplementary Fig. 8b,c and Supplementary Table 11).

PMC10287567

An integrated cell atlas of the lung in health and disease.

In contrast, we find that the proportion of capillary endothelial cells in lung resection tissue from the Lung Tissue Database is higher in samples from patients with severe COPD (GOLD stage 3 or 4) than in those from non-COPD controls matched for age and smoking history (Padj = 0.0004).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Conversely, alveolar and interstitial macrophages, AT2 cells and dendritic cells decrease in proportion (Fig. 5e, Supplementary Fig. 8d and Supplementary Table 11; Padj = 0.0007, 0.0003, 0.005 and 3.21 × 10, respectively).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Finally, smooth muscle shows the largest shift in proportion, increasing significantly in patients with severe COPD (P = 1.85 × 10) in line with previous work.

PMC10287567

An integrated cell atlas of the lung in health and disease.

As deconvolution of bulk samples using the HLCA can reveal disease-specific changes in cell type composition, we provide publicly available preprocessed cell type signature matrices based on the HLCA core (https://github.com/LungCellAtlas/HLCA).

PMC10287567

An integrated cell atlas of the lung in health and disease.

As knowledge of cell types in the lung expands, and the sizes of newly generated datasets increase, annotations in the HLCA core will need to be further refined.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The HLCA and its annotations can be updated by learning from new data projected onto the reference.

PMC10287567

An integrated cell atlas of the lung in health and disease.

We simulated such an HLCA update using the previously projected healthy lung dataset, specifically focusing on the cell identities that were distinguished based on their tissue location in matched spatial transcriptomic data (spatially annotated cell types).

PMC10287567

An integrated cell atlas of the lung in health and disease.

These cell identities were present at very low frequencies (median: 0.005% of all cells; Supplementary Fig. 9a).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Both spatially annotated mesenchymal cell types with more than 40 cells (immune-recruiting fibroblasts and chondrocytes) and two rare cell types (myelinating Schwann cells and perineurial nerve-associated fibroblasts) were recovered in distinct clusters (spatially annotated clusters), and three of these (all except chondrocytes) also contained cells from the HLCA core, thereby enabling a refinement of existing HLCA core annotations using the spatial context from the projected dataset (Fig. 5f and Supplementary Fig. 9b,c).

PMC10287567

An integrated cell atlas of the lung in health and disease.

In this manner the HLCA core and its annotations can be refined by mapping new datasets to the atlas and incorporating annotations from these new datasets into the reference.

PMC10287567

An integrated cell atlas of the lung in health and disease.

To extend the atlas and include samples from lung disease, we mapped 1,797,714 cells from 380 healthy and diseased individuals from 37 datasets (four unpublished and 33 published) to the HLCA core using scArches, bringing the HLCA to a total of 2.4 million cells from 486 individuals (Fig. 6a and Supplementary Table 1).

PMC10287567

An integrated cell atlas of the lung in health and disease.

Label transfer from the HLCA core to the newly mapped datasets enabled detailed cell type annotation across datasets even for rare cells, including 2,048 migratory dendritic cells identified across 28 datasets with label transfer, whereas this cell type was originally labeled in only two of 12 labeled datasets (Extended Data Fig. 8).Fig.

PMC10287567

An integrated cell atlas of the lung in health and disease.

6The extended HLCA enables the identification of disease-associated cell states.a, UMAP of the extended HLCA colored by coarse annotation (HLCA core) or in gray (cells mapped to the core).

PMC10287567

An integrated cell atlas of the lung in health and disease.

b, Uncertainty of label transfer from the HLCA core to newly mapped datasets, categorized by several experimental or biological features.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Categories with fewer than two instances are not shown.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The numbers of datasets per category were as follows: 30 cells, 7 nuclei, 23 healthy, 5 IPF, 3 CF, 3 carcinoma, 4 ILD, 8 surgical resection, 7 donor lung, 12 lung explant, 6 bronchoalveolar lavage fluid, 4 autopsy, 9 10x 5′, 31 10x 3′, 4 Drop-Seq and 3 Seq-Well.

PMC10287567

An integrated cell atlas of the lung in health and disease.

c, Bottom, mean label transfer uncertainty per mapped healthy lung sample in the HLCA extension, grouped into age bins and colored by study.

PMC10287567

An integrated cell atlas of the lung in health and disease.

The numbers of mapped samples per age bin were as follows: 43 for 0–10 years, 33 for 10–20 years, 31 for 20–30 years, 23 for 30–40 years, 19 for 40–50 years, 12 for 50–60 years, 9 for 60–70 years, 8 for 70–80 years and 2 for 80–90 years.

PMC10287567

An integrated cell atlas of the lung in health and disease.

Top, bar plot showing the number of donors per age group in the HLCA core.

PMC10287567

An integrated cell atlas of the lung in health and disease.

d, Violin plot of label transfer uncertainty per transferred cell type label for a single mapped IPF dataset, split into cells from healthy donors (blue) and donors with IPF (orange).

PMC10287567

An integrated cell atlas of the lung in health and disease.

e, Uncertainty-based disease signature scores among alveolar fibroblasts and alveolar macrophages, split into cells from control donors (n = 10,453 and 1,812, respectively), and low-uncertainty cells (n = 1,419 and 200, respectively) and high-uncertainty cells (n = 1,172 and 162, respectively) from donors with IPF.

PMC10287567

An integrated cell atlas of the lung in health and disease.

f, UMAP embedding of alveolar fibroblasts (labeled with manual annotation (core) or label transfer (five IPF datasets)) colored by Leiden cluster.