Impact of the Human Cell Atlas on medicine

Rood, Jennifer E.; Maartens, Aidan; Hupalowska, Anna; Teichmann, Sarah A.; Regev, Aviv

doi:10.1038/s41591-022-02104-7

Impact of the Human Cell Atlas on medicine

Perspective
Published: 08 December 2022

Volume 28, pages 2486–2496, (2022)
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Abstract

Single-cell atlases promise to provide a ‘missing link’ between genes, diseases and therapies. By identifying the specific cell types, states, programs and contexts where disease-implicated genes act, we will understand the mechanisms of disease at the cellular and tissue levels and can use this understanding to develop powerful disease diagnostics; identify promising new drug targets; predict their efficacy, toxicity and resistance mechanisms; and empower new kinds of therapies, from cancer therapies to regenerative medicine. Here, we lay out a vision for the potential of cell atlases to impact the future of medicine, and describe how advances over the past decade have begun to realize this potential in common complex diseases, infectious diseases (including COVID-19), rare diseases and cancer.

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Main

Disease occurs as a result of aberrations in cells and cellular ecosystems within tissues — driven by genetic variations as well as environmental impacts, from nutrients to pathogens. To understand pathogenesis and discover and deliver new treatments, we need to understand cells, their internal circuits, and their interactions in health and disease. Although this has been appreciated for many decades, technical challenges have limited our ability to simultaneously probe human disease at a large scale and at high molecular and cellular resolution.

Breakthroughs in single-cell and spatial genomics in the past decade have opened the way to single-cell and tissue atlases in health and disease (Table 1), and are poised to impact every aspect of medicine (Fig. 1). These include understanding the cell types and programs in which disease genes act, deciphering mechanisms of disease initiation and progress at the cellular and multicellular levels, defining new signatures for disease monitoring and diagnosis, and discovering and develo** new molecular, gene and cell therapies and tracking their impact in patients.

Table 1 A selection of key experimental methods for construction of cell atlases at different levels of biological organization

Full size table

**Fig. 1: Potential medical impacts of the Human Cell Atlas and remaining challenges.**

As disease is only fully understood in reference to health, and vice versa, achieving this vision will require comprehensive reference maps of all human cells as a basis for both understanding human health and diagnosing, monitoring and treating disease. Map** human cells poses major logistical and technical challenges, which are being met by the international Human Cell Atlas (HCA) initiative¹. When the HCA was being planned, the initial members of the HCA community laid out our plans and goals in a white paper¹⁵⁰ and has even suggested that antihypertensive treatments may ‘prime’ proinflammatory immune cells that are amplified upon infection¹⁵¹.

Single-cell analyses have the potential to inform drug discovery as well as diagnosis and treatment in the clinic, as has been the case in the COVID-19 outbreak. For example, single-cell RNA-sequencing (scRNA-seq) of SARS-CoV-2-binding B cells from patients who had recently recovered COVID-19 (ref. ¹⁵⁰) identified high-quality neutralizing antibodies from memory and activated B cells¹⁵². ScRNA-seq of PBMCs from hospitalized patients helped to identify changes in cell composition¹⁵³ and gene expression along the course of disease progression¹⁵⁴. In the context of the Pfizer–BioNTech mRNA vaccine BNT162b2 against SARS-CoV-2 (ref. ¹⁵⁵), a single-cell atlas of innate and adaptive immune cells collected longitudinally following first and second vaccinations identified a massive expansion of myeloid cells expressing interferon-stimulated genes after second immunization, but not natural infection — providing further insights into the efficacy of this new vaccine technology.

Understanding disease biology: from genes to cells, programs and tissues

From disease-associated genes to cells of action

Genetic variants — both common and rare — contribute to the risk of develo** disease, and human genetic studies have identified more than 100,000 variants associated with different human traits, especially the risk of develo** different diseases. However, to understand the role of these variants in disease, we must understand the cells in which they are expressed and act. In rare diseases, the relevant cell type may be unknown, or even undiscovered. In common complex diseases, the candidate loci from genome-wide association studies (GWAS) and phenome-wide association studies are often in non-coding regions that are difficult to connect to the affected protein-coding gene, cell of action or function. Moreover, even when common and rare diseases have similar clinical phenotypes, these could be the results of variants in different genes, thus making it more challenging to identify common mechanisms at the pathway or cellular level.

Cell atlases provide a way to tackle each of these challenges (Fig. 1). In rare Mendelian genetic disorders, healthy tissue atlases have led to the discovery of novel cell types, including rare ones, that uniquely express key disease genes, and have even corrected long-held assumptions. For example, the pulmonary ionocyte — a novel, rare cell type discovered in cell atlases of the trachea — is the main cell type expressing CFTR^8,9, the causal gene in cystic fibrosis. In particular, studies in the Human Developmental Cell Atlas (HDCA) can shed light on Mendelian disorders that manifest at birth, such as the cellular origins of different Hirschsprung’s disease variants in the develo**¹⁰ versus adult¹¹ enteric nervous system, or the impact of trisomy 21 on bone marrow hematopoietic stem cells and their niche¹².

In common complex diseases, similar analyses have related disease genes in associated loci to specific cell subsets across many inflammatory^13,14,15,16, autoimmune^17,18,19, neurodegenerative^20,21,22,23, respiratory^8,24, fibrotic^25,26 and other^27,28 diseases, using both healthy and disease atlases of the relevant tissue, and revealing novel unexpected associations. For example, integrating the extensive GWAS literature for ulcerative colitis (UC) with single-cell atlas data enabled the identification of key cell types expressing genes associated with UC by GWAS, including epithelial M-like cells — which are exceedingly rare in the healthy colon, but expanded significantly in the inflamed, diseased colon²⁹. Because most risk variants are in non-coding regions³⁰, integration of GWAS summary statistics, single-cell profiles and chromatin data^8,9, as well as joint profiling of chromatin and RNA in single cells³¹, can further facilitate the discovery of such associations³². One such analysis showed that not only is a specific gene program induced in colonic M cells in UC, accounting for overall disease risk heritability, but that common variants in the FERMT1 locus (a gene implicated in a rare form of inflammatory bowel disease (IBD)³³) contribute substantially to this association³⁴. Moreover, because common disease genes are often pleiotropic, broader cross-tissue atlases can help to better decipher their impact throughout the body^35,36,37,38. Finally, atlases also allow us to move from the level of individual risk genes to the modules and programs in which they participate, thus hel** decipher gene function, nominate causal processes, and related diseases with similar morbidities at the level of programs, even when the underlying genes are distinct²⁹. This is illustrated in monogenic and polygenic IBD³⁹, in which programs involving M cells are enriched in both forms of the disease³⁹. Single-cell atlases can also reveal cellular subtypes that are shared across tissues or are unique in particular locations or disease contexts, such as recent surveys of mouse⁴⁰ and human⁴¹ fibroblasts.

Remodeling of cellular composition and multicellular architecture in disease tissue

Both cell-intrinsic and cell-extrinsic changes have key roles in pathogenesis and can be targeted by therapies, but changes in the cell’s internal programs and shifts in cellular composition are often confounded in bulk profiling. The cellular — and increasingly spatial — resolution provided by atlases distinguishes these contributions and allows more accurate and sensitive comparison between health and disease, as shown in studies in IBD, asthma, pulmonary fibrosis, rheumatoid arthritis, diabetic kidney disease, cardiomyopathy, Alzheimer’s disease and many other common diseases^{24,29,40,41,42,43,44,45,46,47,48,49,50,51}.

Both compositional and cell-intrinsic expression changes can be coordinated across multiple cell types, resulting in shifts in multicellular communities in disease. For example, comparing cellular composition in the ileum of patients with Crohn’s disease with the healthy reference atlas identified a unique multicellular community of immune and stromal cells, which was predictive of a lack of response to anti-TNF therapy⁴². Comparison with healthy references also helps decipher the mechanisms driving these coordinated communities, and the gene programs within their constituent cells. For instance, compared with healthy tissue, atopic dermatitis and psoriasis skin lesions are characterized by the expansion of particular classes of macrophages and vascular endothelial cells that interact via the chemokine CXCL8 and its receptor ACKR1, respectively⁵². This interaction, which is suggested to promote lymphocyte recruitment, represents the re-emergence of a prenatal cellular program in disease tissue⁵². Finally, computational methods^{56,57,58,59,60,61,62,63,64,65}, stroma^57,66 and even neural⁶⁷ cells, and their spatial organization^84,85,86 and disease^{64,72,84,87,88} tissue^{62,70,81,84,85} has grown, algorithms have been able to deconvolve low-resolution methods to single-cell resolution⁸⁹, project the spatial expression of genes that were not measured directly^{89,90,91,92,93}, and recover repeatable spatio-molecular features in tissue^70,94. Given sufficient data, algorithms can also map molecular profiles and histology to each other, with the aim of predicting expression from histology⁹⁵, forming the basis of an H&E 2.0 approach.

Early studies are beginning to show the potential impact of such future assays, and how atlases provide the necessary tools to understand why therapeutics work — or don’t work — in patients at the cell and tissue levels, predicting potential on-target toxicities, efficacy and mechanisms underlying intrinsic and acquired resistance. First, a healthy reference is invaluable in predicting the risk of on-target toxicities for both molecular and cellular therapies, on the basis of the cell types in which the therapeutic target is expressed. For example, a recent study has suggested that expression of CD19 by mural cells, vascular smooth muscle cells, and pericytes in the blood–brain barrier might explain neurotoxicity of CD19-targeting chimeric antigen receptor T cells⁹⁶. Cross-species reference atlases for key models in safety assessment, such as rat and macaque⁹⁷, would be invaluable. For response and resistance in cancer, profiling malignant and immune cells in tumors, draining lymph nodes, or the periphery can help monitor response and provide insights into resistance, as shown, for example, in response to anti-PD-L1 therapy^82,98,99 or chemotherapy¹⁰⁰. Although access to patient tissue may be more limiting in some cases, these approaches are as important in other diseases, such as IBD^29,42,51, rheumatoid arthritis^16,47, psoriasis¹⁰¹, atopic dermatitis⁵², and scleroderma²⁵.

High-resolution and massively parallel methods for drug discovery

For molecular drug discovery, reference atlases and single-cell and spatial genomics open the way to high-resolution phenotypic screens for desired cell states by coupling the rich, complex and interpretable phenotypes of molecular profiles, which can be related to cells in patients, to the scale required in screening^102,103 (Fig. 1). Perturb-Seq screens — pooled genetic screens with single-cell genomics readouts — have characterized the impact on single-cell profiles of perturbations in large numbers of genes^{102,104,105,106,107}, non-coding variants associated with common complex disease¹⁰⁸, and coding variants in cancer¹⁰⁹ and developmental disorders^110,111, and can be performed in cell culture or co-culture, in organoids, or in animal models. Focused small-molecule screens with scRNA-seq readouts have also been conducted^112,113. Moreover, machine-learning algorithms can increasingly be trained on such data to yield models that predict the impact of additional perturbations in one or more genes in the same cellular context or of the same perturbations in new biological contexts^{114,115,121,122}, thymic T cells³⁸, and organoid models of the endometrium⁸⁴ or intestines¹²³. Moreover, for in vivo tissue reprogramming, reference atlases help infer differentiation mechanisms and assess whether a therapy has the desired effect, for example to characterize the regenerative capacity of overexpressing proneural transcription factors in Müller glia¹²⁴ or to map networks underpinning retinal regeneration¹²⁵. Finally, for engineered cell therapy, Perturb-Seq methods help screen for perturbations that will yield therapeutically desirable cell states^126,127, and single-cell profiling helps characterize the resulting cell therapy before it is administered to patients and after administration in both common diseases¹²¹ and T cell therapy in cancer^128,129,130.

Challenges for cell atlases in medicine

To realize the transformative potential of cell atlases in medicine, substantial challenges need to be overcome — technical, practical and fundamental (Fig. 1). First and foremost, we must ensure that cell atlases benefit all of humanity, by assembling healthy and disease atlases that reflect human diversity, from ancestry to geography, as well as involving diverse scientists from across the globe who are experts in these approaches. This has been a core aim of the Human Cell Atlas since its inception, and has been overseen by a dedicated equity working group^131,132. For effective deployment in real-world settings, lab methods need to be sufficiently cost-effective and robust to empower screening and enable adoption, including in under-resourced areas. Connections between the lab and the clinic also need to be further enhanced, including building more biobank resources with rich metadata, large-scale profiling of samples from clinically annotated and diverse cohorts, and better experimental methods to tap into banked samples, especially formalin-fixed paraffin-embedded issues, which are still incompatible with many single-cell methods^136,137, they enable the collection of diverse reference atlases across genders, age, ancestry and demographics that are needed for clinical work. They also enable the sort of large-scale sampling within and across human patients that is required to understand and monitor disease, as well as screening experiments that are crucial to drug discovery. Together, these will help deliver the Human Cell Atlas mission: to form a reference map as a basis for understanding human health as well as diagnosing, monitoring, and treating disease.

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Acknowledgements

This paper is part of the Human Cell Atlas. A.M. and S.A.T. acknowledge core funding from Wellcome (grants 206194 and 108413/A/15/D).

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These authors contributed equally: Jennifer E. Rood, Aidan Maartens.

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Genentech, South San Francisco, CA, USA
Jennifer E. Rood, Anna Hupalowska & Aviv Regev
Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
Aidan Maartens & Sarah A. Teichmann
Theory of Condensed Matter, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK
Sarah A. Teichmann

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Jennifer E. Rood
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Aidan Maartens
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Anna Hupalowska
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Sarah A. Teichmann
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A.R. is a co-founder and equity holder of Celsius Therapeutics, an equity holder in Immunitas Therapeutics and, until 31 July 2020, was a scientific advisory board member of Thermo Fisher Scientific, Syros Pharmaceuticals, Asimov and Neogene Therapeutics. From 1 August 2020, A.R. is an employee of Genentech and has equity in Roche. A.R. is a named inventor on multiple patents related to single-cell and spatial genomics filed by or issued to the Broad Institute. J.E.R. and A.H. are employees of Genentech and have equity in Roche. In the past three years, S.A.T. has consulted or been a member of scientific advisory boards at Roche, Genentech, Biogen, GlaxoSmithKline, Qiagen and ForeSite Labs, and is an equity holder of Transition Bio.

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Rood, J.E., Maartens, A., Hupalowska, A. et al. Impact of the Human Cell Atlas on medicine. Nat Med 28, 2486–2496 (2022). https://doi.org/10.1038/s41591-022-02104-7

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Received: 24 August 2022
Accepted: 24 October 2022
Published: 08 December 2022
Issue Date: December 2022
DOI: https://doi.org/10.1038/s41591-022-02104-7
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Abstract

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