Short-term exposure to intermittent hypoxia leads to changes in gene expression seen in chronic pulmonary disease
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Summary: Obstructive sleep apnea is an important medical problem, with elevated cardiovascular risk as a common association. Intermittent hypoxic episodes are a good predictor of such risk so a connection is indeed plausible. The authors use single cell genomics to delineate the changes in intermittent hypoxia models, with interesting insights, but what limits enthusiasm is validation of some hypothesis generating findings from single cell data, limiting potential mechanistic insights that are translatable to OSA.
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Abstract
Obstructive sleep apnea (OSA) results from episodes of airway collapse and intermittent hypoxia (IH) and is associated with a host of health complications. Although the lung is the first organ to sense changes in oxygen levels, little is known about the consequences of IH to the lung hypoxia-inducible factor-responsive pathways. We hypothesized that exposure to IH would lead to cell-specific up- and downregulation of diverse expression pathways. We identified changes in circadian and immune pathways in lungs from mice exposed to IH. Among all cell types, endothelial cells showed the most prominent transcriptional changes. Upregulated genes in myofibroblast cells were enriched for genes associated with pulmonary hypertension and included targets of several drugs currently used to treat chronic pulmonary diseases. A better understanding of the pathophysiologic mechanisms underlying diseases associated with OSA could improve our therapeutic approaches, directing therapies to the most relevant cells and molecular pathways.
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Reviewer #3:
Obstructive sleep apnea (OSA) is a common disease associated with intermittent hypoxia (IH) and is linked to health complications. The lung is the first organ to experience the IH and in this study Wu et al uses a mouse model of OSA to identify transcriptional changes in the lung as a whole organ. The authors then also use single cell RNA sequencing (scRNAseq) to further identify transcriptional changes in different cellular populations of the lung. The authors found changes in circadian and immune pathways and that endothelial cells in the lung specifically showed the greatest transcriptional changes. The data will be useful as a reference for the field in understanding transcriptional responses in lung cells exposed to IH.
scRNASeq is an exciting technique that has the potential to identify how different cell populations …
Reviewer #3:
Obstructive sleep apnea (OSA) is a common disease associated with intermittent hypoxia (IH) and is linked to health complications. The lung is the first organ to experience the IH and in this study Wu et al uses a mouse model of OSA to identify transcriptional changes in the lung as a whole organ. The authors then also use single cell RNA sequencing (scRNAseq) to further identify transcriptional changes in different cellular populations of the lung. The authors found changes in circadian and immune pathways and that endothelial cells in the lung specifically showed the greatest transcriptional changes. The data will be useful as a reference for the field in understanding transcriptional responses in lung cells exposed to IH.
scRNASeq is an exciting technique that has the potential to identify how different cell populations respond to a stimulus (in this case intermittent hypoxia). However, it provides an enormous amount of data which requires significant processing and interpretation. This paper contains a huge amount of data generated by scRNASeq, yet the actual data section is very short. Given the complexity of information obtained, I think it warrants a more detailed analysis in the results section and discussion. It would be helpful to me if the authors could distil the very large volumes of information into a more extensive discussion of their findings (particularly discussing the figures in more detail). Is the summary finding of this paper that early changes in hypoxia and circadian gene expression drive later disease in the lungs of OSA patients? The abstract seems to focus on hypoxia, circadian and immune changes but the data text section focuses very little on these pathways. More details on the figures shown and tying the figures to the results text would improve this paper and enable further interpretation by readers.
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Reviewer #2:
General assessment of work:
In contrast to the author's claim of OSA, the experimental design mostly focused on intermittent hypoxia neglecting sleep pattern and arterial oxygen level. The entire study is based on exploratory approach without any validation, confirmatory experiments. The selection of marker to cluster many cells is not critical. It seems that this selection method caused various abnormal biological process patterns, types and proportion of certain reported cells in the lung.
Summary:
- OSA is having complex pathophysiology and IH is the one aspect of OSA. As it seems that the authors did not measure arterial oxygen pressure upon the induction of IH and also it was not sure IH was induced when the animals were really on sleeping mode. In Figure 6, they should have tested the gene expression of OSA patients to …
Reviewer #2:
General assessment of work:
In contrast to the author's claim of OSA, the experimental design mostly focused on intermittent hypoxia neglecting sleep pattern and arterial oxygen level. The entire study is based on exploratory approach without any validation, confirmatory experiments. The selection of marker to cluster many cells is not critical. It seems that this selection method caused various abnormal biological process patterns, types and proportion of certain reported cells in the lung.
Summary:
- OSA is having complex pathophysiology and IH is the one aspect of OSA. As it seems that the authors did not measure arterial oxygen pressure upon the induction of IH and also it was not sure IH was induced when the animals were really on sleeping mode. In Figure 6, they should have tested the gene expression of OSA patients to make sure that their models are physiologically relevant. So it would be better to avoid OSA in the manuscript but they can mention the IH.
Results:
While it is understood that the authors tried to mimic OSA by doing the experiments in "inactive phase" to conduct IH, what will happen if they do in active phase? Do the authors expect the changes in circadian rhythm related genes when they induce IH in active phase? As the authors did not focus on sleep pattern (it seems), "inactive" and "active phase" should not be an issue. The authors should clearly mention that what is the sleep pattern during "inactive" or experimental phase. As they are exposed to IH inactive phase, it seems there is no surprise in getting circadian rhythm related pathways. What will happen if they do the experiments in active phase? Then also they will find circadian gene effects?
The induction of hypoxia might have disturbed the sleep pattern and this could have precipitated the endogenous stress via HPA axis. It is well known that HPA axis is linked with reduction in immune response. So the authors should check these.
Figure 1:
Angiogenesis is a kind of compensatory mechanism for hypoxia. Similarly other biological processes mentioned in Figure 1B should have some mechanisms related to hypoxia. This should be explained. Because some biological process like organ development has less meaning.
Though they found the alteration in the proportion of different cell types in the lung based on the analysis, this should have been confirmed with the other techniques like flow cytometry. At least a few cell types that have seen gross alteration should have been checked. This is very crucial as most of the story is woven with the type of cells. BAL should have been performed to see the cellular proportions in the airway.
Though it is not surprising to see the changes in endothelial cells, the change in myofibroblasts is interesting and this should be explained.
It is not clear the downregulated genes in immune cells are due to reduction in cell number? Did they normalize to the number of cells? If cell numbers are reduced, what could be the possible reason? Was there any change in pathways related to apoptosis?
Figure 2:
In the context of almost 60% airway epithelial cells are non-ciliated and among these cells clara cells are predominant one and more than 95% of non-ciliated cells are Clara cells. In fact, Clara cells reside throughout the tracheobronchial and bronchiolar epithelium. Surprisingly the authors did not find Clara or Club cells in Figure 2. Also smooth muscle cells have not shown. What could be the reasons behind these? How have these markers been selected to segregate each cell type? How to explain the presence of abundant erythroblasts that are generally observed in bone marrow.
While it is known that single cell sequencing has indicated the possible presence of new cell types, it should not ignore the already well known cell types. It is really surprising to see the predominant presence of endothelial cells. This is different from available literature based on single cell sequencing based molecular cell atlas. In general, Sox17, a marker of endoderm, is also expressed by other endoderm derived derivatives like epithelia. (Park et al, Am J Respir Cell Mol Biol. 2006 Feb;34(2):151-7). Please clarify.
Amine oxidase C3 is a relatively new marker of myofibroblasts (Hsia et al, Proc Natl Acad Sci U S A. 2016 Apr 12;113(15):E2162-71). But this ectoenzyme is also expressed abundantly in adipocytes, endothelial cells and other cells. Please clarify.
It is not clear why the authors have not chosen a well established marker to identify the cells.
Figure 3: Top panel, it seems that hypoxia images had shown the lungs seem to be congested with relative thickening of the alveolar wall. This is well evident with HOPX staining in which one can see clear cut higher expression of HOPX in hypoxic mice. Same thing is partially true for Pro-SFTPC as well. All these seem to be a representative picture and so, the morphometry may be required to see the overall status of each marker.
Figure 5:
Though it is known that endothelial cells are able to phagocytose cells like red blood cells in conditions like aging, it is not clearly known that alveolar capillary endothelial cells, capillary aerocytes, will have professional phagocytic function in the context of main function in gas exchange. In this context, biological processes derived from softwares could lead to abnormal patterns. Also, how to explain decreased "vasculogenesis" and "regulation of angiogenesis" in capillary general cells while Figure 1B mentioned about increased angiogenesis.
In a dynamic environment, these biological processes derived from the altered gene expression without actual demonstrative studies could lead to distortion in biological understanding. This is also evident in Figure 4: Figure supplement 2 where both upregulation and downregulation are observed in Erythroblasts (inflammatory response) and MPhage-DC (apoptotic process related). Similar dual altered pattern is observed in Figure 4.
Figure 6: It is worrisome as there is no single validation or demonstrative experiment.
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Reviewer #1:
Obstructive sleep apnea is an important medical problem, with elevated cardiovascular risk as a common association. Intermittent hypoxic episodes are a good predictor of such risk so a connection is indeed plausible. Thus the manuscript starts with a good premise, but what limits my enthusiasm is the large number of loose ends in the story that make it likely that what we are seeing is a small amount of signal, with a large amount of noise, limiting potential mechanistic insights that are translatable.
Major comments:
OSA and intermittent hypoxia are clearly different things. Further the hypoxia of OSA is much less in the lung compared to the systemic organs. To illustrate this point, an upper estimate for alveolar CO2 is the venous CO2, or more commonly 10-15 mm Hg elevation over normal i.e. 55 mm Hg. At even 60 mm Hg CO2, …
Reviewer #1:
Obstructive sleep apnea is an important medical problem, with elevated cardiovascular risk as a common association. Intermittent hypoxic episodes are a good predictor of such risk so a connection is indeed plausible. Thus the manuscript starts with a good premise, but what limits my enthusiasm is the large number of loose ends in the story that make it likely that what we are seeing is a small amount of signal, with a large amount of noise, limiting potential mechanistic insights that are translatable.
Major comments:
OSA and intermittent hypoxia are clearly different things. Further the hypoxia of OSA is much less in the lung compared to the systemic organs. To illustrate this point, an upper estimate for alveolar CO2 is the venous CO2, or more commonly 10-15 mm Hg elevation over normal i.e. 55 mm Hg. At even 60 mm Hg CO2, local oxygen tension in lungs would be above 80 mm Hg. Systemic desaturation is because of widening A-a gaps and physiological/pathophysiological shunts. While severe OSA with prolonged apnea could indeed be worse, the clinical associations are seen even with milder disease. Thus a-priori it is very unlikely that the model reflects the disease accurately.
Given the limitations of the model, it is imperative that at least the pathways elicited by intermittent hypoxia be clearly defines so that even if we do not gain fully understanding of OSA, we may understand the consequence of intermittent hypoxia that may be relevant in another context. Here too the manuscript is lacking. The genomic analysis is interesting and indeed data rich. However, more attention could have been paid by exploring a hypothesis, ensuring multiple markers for target cell populations, and building a mechanistic model. In current form, the work is hypothesis generating, based on limited markers and analysis, and is extrapolated widely to other pulmonary disease without a solid rationale.
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Summary: Obstructive sleep apnea is an important medical problem, with elevated cardiovascular risk as a common association. Intermittent hypoxic episodes are a good predictor of such risk so a connection is indeed plausible. The authors use single cell genomics to delineate the changes in intermittent hypoxia models, with interesting insights, but what limits enthusiasm is validation of some hypothesis generating findings from single cell data, limiting potential mechanistic insights that are translatable to OSA.
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