introduction
Understanding the impact of human genetic variation on complex diseases is a key challenge in modern biomedical research. Human pluripotent stem cells (hPSCs) have become an important model for the study of human biology due to their ability to differentiate into multiple cell types. Recently, technological advances have made large-scale hPS cell studies possible, which provide new avenues for exploring the genetic regulation of molecular phenotypes and their contribution to human disease. By combining single-cell sequencing technology, researchers can identify environment-dependent genetic effects during cell development or experimental manipulation. hPS cells, including embryonic stem cells (ES cells) and induced pluripotent stem cells (iPS cells), play an important role in biological research. iPS cells reprogram somatic cells (e.g., skin cells or blood cells) to express specific pluripotency transcription factors (e.g., OCT3/4, SOX2, KLF4, and c-MYC) to obtain gene expression and epigenetic status similar to ES cells. This allows each hPS cell to carry the donor's genome, making it an ideal tool for studying human phenotypes and genetic drivers of disease. Traditionally, hPS cells have been used primarily to study rare diseases determined by a small number of loci. However, complex diseases (such as Parkinson's disease, glaucoma, and cardiovascular disease) are often determined by a combination of multiple genetic variants and environmental factors, and hPS cells are relatively unused in this area. Although genome-wide association studies (GWAS) have identified many loci associated with complex diseases, more than 90% of loci are located in intergenic regions that may play a role by altering genomic regulation. To complicate matters further, there is growing evidence that the effects of many loci depend on cell type or specific environmental conditions. Although the use of hPS cells in the study of gene regulation is still in its infancy, it has been shown to have strong potential. For example, hPS cells have been used to discover the effects of non-coding regulatory mutations, predict drug toxicity, and develop cell replacement therapies. However, most studies are based on only a small number of donor cell lines, which limits the broad applicability of the findings. In practice, there are many challenges in conducting large-scale hPS cell experiments, such as variation between cell lines, complexity of cell culture and differentiation, and experimental cost. Fortunately, the development of stem cell banks, such as HipSci and iPSCORE, and automated cell processing technologies, have overcome these limitations to some extent, making it possible to use hPS cells for innovative population genomics studies. The May 13 Nature Genetics article, "Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases," explores how the integration of stem cell biology, population genetics, and cellular genomics can help unravel the functional consequences of human genetic variation. It also discusses the key challenges of combining these areas and their solutions. Two areas of human biology were highlighted, particularly in unraveling mechanisms of complex disease risk loci and assessing the phenotypic relationship between common genetic variants and drug treatments, with the potential for enormous benefits of hPS cell research. As technology advances and research advances, significant advances are expected to improve medical outcomes by unraveling how genetic variation affects disease phenotypes and drug responses.
Application of hPS Cells in Biomedical ResearchTypes and Characteristics of Pluripotent Stem Cells Human pluripotent stem cells (hPSCs) include two main types: embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). ESCs are derived from cell clusters within early embryonic embryos and have the ability to self-renew and differentiate into any somatic cell type. iPSCs, on the other hand, are generated by somatic cell reprogramming technology, which restores pluripotency to a pluripotent state by forcing the expression of pluripotency transcription factors such as OCT3/4, SOX2, KLF4, and MYC in somatic cells. iPSCs and ESCs are highly similar in gene expression profiles and epigenetic status, and share almost identical pluripotency characteristics. This means that iPSCs are able to differentiate into various types of somatic cells in vitro, including nerve cells, cardiomyocytes, hepatocytes, etc. As a result, hPS cells are widely used to mimic human developmental processes, study disease mechanisms, and screen potential drugs.
Somatic cell reprogramming and iPSCs generation The process of generating iPSCs typically involves the following steps: Somatic cell selection: Somatic cell samples are obtained from donors, such as skin fibroblasts or blood cells. Transgene introduction: Pluripotency transcription factor genes (e.g., OCT3/4, SOX2, KLF4, and MYC) are introduced into somatic cells using viral vectors or other methods. Pluripotency induction: Under specific culture conditions, somatic cells are reprogrammed to a pluripotent state through the expression of pluripotent transcription factors to form iPSCs. iPSCs Screening and Expansion: Successfully reprogrammed cell populations are screened from culture for further expansion for research use.
Applications of hPS cells in genetic researchSince hPS cells contain complete genetic information from donors, researchers can use these cells to study how genetic variation affects human phenotypes. For example, by differentiating iPSCs from different individuals and observing the effects of different genotypes on cell development and function, it is possible to gain insight into the genetic basis and individual differences of the disease.
Construction of disease modelshPSCs are particularly suitable for constructing in vitro models of various diseases, especially those that are difficult to study directly in vivo. For example, researchers can study the pathological mechanisms of neurodegenerative diseases such as Alzheimer's disease or Parkinson's disease by differentiating hPS cells into nerve cells. In addition, the use of iPSCs to generate cardiomyocytes can be used to study the pathogenesis of heart disease and screen for potential therapeutic agents.
Drug Screening & Toxicity Testing: hPSCs also play an important role in drug screening and toxicity testing. By differentiating hPS cells into specific target cell types, such as hepatocytes or cardiomyocytes, researchers can evaluate the efficacy and safety of new drugs in vitro. For example, by testing the drug's effect on iPSCs-derived cardiomyocytes, the potential toxicity of the drug to the heart can be predicted, reducing the risk in clinical trials.
Application of Parkinson's Disease Parkinson's disease is a complex neurodegenerative disease whose etiology involves a variety of genetic and environmental factors. Researchers used iPSCs to generate pluripotent stem cells from somatic cells of Parkinson's disease patients, and then differentiated them into dopaminergic neurons, revealing the pathological mechanism of Parkinson's disease by observing the functional defects and gene expression changes of these neurons. For example, modifying specific mutated genes in a patient's iPSCs through gene editing technology can further validate the role of these genes in the disease and explore potential gene therapies.
Applied Heart disease in cardiovascular disease is another common and complex disease with risk factors that include multiple genetic variants and lifestyle factors. Using iPSCs from different individuals to generate cardiomyocytes, researchers compared the effects of different genotypes on cardiomyocyte function and found that certain genetic variants may increase the risk of heart disease. In addition, using these cardiomyocytes for drug screening can identify the most effective drugs for patients with specific genotypes and improve the effectiveness of individualized treatment.
人类多能干细胞（hPS）细胞系池的实验设计（Credit: Nature Genetics）
Research Status of Complex DiseasesApplication of hPSCs in the Study of Rare DiseaseshPSCs, especially iPSCs, have played an important role in the study of rare genetic diseases. These diseases are usually caused by a small number of genetic mutations, which are usually located within the gene region that codes for the protein. For example, Duchenne Muscular Dystrophy (DMD) is a genetic disorder caused by mutations in the DMD gene, and by generating iPSCs from a patient's somatic cells and differentiating them into muscle cells, researchers can observe the functional defects of these cells to gain insight into the molecular mechanisms of the disease. In addition, with gene editing technologies such as CRISPR-Cas9, researchers can also repair these mutations, thereby validating their role in the disease and exploring potential gene therapies.
The challenges of complex diseases differ from those of rare diseases, where the risk factors for complex diseases are more diverse, involving multiple genetic variants and environmental factors. For example, the risk of complex diseases such as Parkinson's disease, glaucoma, and cardiovascular disease is not determined by a single gene mutation, but by a combination of many genetic variants and environmental factors. Genome-wide Association Studies (GWAS) has identified many loci associated with these complex diseases, but more than 90% of loci are located in intergenic regions that do not normally code for proteins but rather function by regulating gene expression.
Population-scale hPS cell researchTo better understand the genetic mechanisms of complex diseases, researchers are leveraging population-scale hPS cell studies. These studies involve generating iPSCs from a large number of individuals and sequencing their genomes and molecular phenotyping. With this approach, researchers can explore the role of genetic variation in different cell types and stages of development. Using iPSCs from different Parkinson's disease patients and healthy individuals, the researchers generated dopaminergic neurons and revealed the role of disease-related genes by comparing the function and gene expression of these neurons. For example, mutations in the LRRK2 gene are considered important risk factors for Parkinson's disease, and through the iPSCs model, researchers have found that mutations in this gene cause abnormal function of dopaminergic neurons, thereby increasing the risk of Parkinson's disease.
By differentiating iPSCs from different individuals into cardiomyocytes, researchers can observe the effects of different genotypes on cardiomyocyte function. For example, by studying how certain genetic variants affect how heart muscle cells respond to drugs, researchers can develop more personalized treatment options. In addition, by comparing iPSCs cardiomyocytes from different individuals, the researchers also discovered some new cardiovascular disease risk genes, such as variants in the PCSK9 gene, which are associated with high cholesterol levels and increased risk of cardiovascular disease.
Dynamic QTLs: Identifying genetic effects in specific states is a method to study how genetic effects change in different cellular states, such as drug exposure. Unlike traditional QTL studies, which typically test "static" genetic effects in specific situations, dynamic QTL models are able to increase resolution and identify hidden effects. For example, a genetic effect may only exist when cells are exposed to a drug.
Applications of Dynamic QTLsDynamic QTLs are particularly useful for detecting transient effects that occur in specific cellular states, such as during differentiation. By sampling cells at multiple time points and using dynamic QTL models, it is possible to identify how genetic effects change with cell developmental lineage. For example, sampling cells during hPS cell differentiation and applying dynamic QTL models can reveal the genetic effects of genomic phenotypes at different stages of cell development.
Dynamic QTLs in cardiomyocyte differentiationDuring cardiomyocyte differentiation, researchers used single-cell RNA sequencing technology to reveal dynamic gene regulation. For example, the effect of rs11124033 on FHL2 gene expression was found to be linear during cardiomyocyte differentiation, while the effect of rs28818910 on C15orf39 gene expression was nonlinear. These findings reveal the differential effects of genetic variation on gene expression during the transition of cellular state.
Dynamic QTLs in Endoderm Differentiation During endoderm differentiation, the expression level of THUMPD1 genes changes with the change of cell state. Specifically, when cells are in a pluripotent state, THUMPD1 expression levels are high and there is a significant allele effect (labeled as eSNP rs76148084 [G/A]). However, when cells differentiate into endodermal states, the overall expression level of THUMPD1 decreases, and the allele effect is also weakened. Another example is that the expression of the VAT1L gene exhibits a differential allele effect (labeled as eSNP rs7191422 [T/A]) during the mesodermal developmental stage, which is only observed when the cell is in the intermediate developmental stage, suggesting that individuals carrying the T allele have a faster decline in expression levels during development.
Advantages of dynamic QTLsThe dynamic QTLs approach provides the tools to study genotype (G) and cellular state (C) interactions (G×C), which can be exposure to stimuli or drugs. By combining single-cell sequencing data, dynamic QTLs can be tested in a continuous trajectory of cell states, such as during cell differentiation, where each cell is in a slightly different state (e.g., cell maturity) even when acquired at the same time. The advantage of this approach is the ability to more precisely place cells in the landscape of cellular states, thus improving the detection of dynamic genetic effects.
At present, methods to identify dynamic QTLs are just emerging, and it is shown that these loci are often located in regions of unknown regulatory annotations. These loci may have previously unrecognized regulatory effects at relevant intermediate time points of developmental trajectories that can be characterized by further functional validation in the future. hPS cell experiments will scale from dozens to thousands of cell lines with little impact on overall cost and experimental design. With the convergence of hPS cells, population genetics methods, and cellular genomics, it is expected that these studies will provide valuable tools for the discovery and translation of human genomics.
Advantages of Single-Cell GenomicsSingle-cell sequencing technology has significant advantages over traditional "batch" methods, enabling improved resolution to detect the phenotypic effects of human genetic variation. While traditional batch methods measure the average phenotype of cell populations in research, single-cell sequencing enables the analysis of individual cells to reveal cell-to-cell heterogeneity and potential effects of genetic variation.
Advances in single-cell sequencing for individual cell analysis have allowed researchers to study and characterize individual cell readouts in heterogeneous cell populations. This approach allows researchers to gain a deeper understanding of heterogeneity within cell populations, especially in complex cellular systems such as lineage differentiation and 3D organoid models.
Single-cell genomics in lineage differentiationThe application of single-cell genomics during the lineage differentiation of hPS cells enables researchers to track phenotypic changes in individual cells. By analyzing the gene expression and phenotype of individual cells, it is possible to understand the transcriptional dynamics of cells during differentiation and reveal the complexity of gene expression regulatory networks.
Single-cell genomics in 3D organoid modelsThe application of single-cell genomics allows researchers to study the distribution and function of different cell types within tissues in detail when constructing 3D organoid models. By analyzing the gene expression and phenotype of individual cells, it is possible to identify the characteristics of different cell populations in tissues and reveal their role in tissue function.
With the continuous development and improvement of single-cell sequencing technology, it is foreseeable that single-cell genomics will be more and more widely used in biomedical research. In the future, single-cell technology can be used to better understand the function and regulatory mechanism of cells, so as to provide more accurate and effective methods for the diagnosis and treatment of diseases.
Integrating genetics and stem cells for pharmacology, genomics, and drug development, the impact of genetic variants on drug response, and genetic variants play a key role in patient response to therapeutics. Studies have shown that drug therapies supported by genetic evidence are twice as likely to be successfully brought to market as other therapies. This means that understanding a patient's genetic background can help doctors better choose treatment options and maximize the effectiveness and safety of treatment.
Application of hPS Cells in Drug Development In the preclinical drug development stage, hPS cells and their derived cells, including tissues and organoid systems, have been widely used in the preclinical drug development stage. By utilizing different types of hPS cells, researchers can mimic the response of different tissues in the human body to assess the efficacy and toxicity of drugs. For example, by exposing a drug to hPS cell-derived cardiomyocytes, the effect of the drug on cardiac function can be assessed; Exposure of the drug to a model of liver tissue allows for an assessment of its metabolic and toxic effects.
Distinguish between promising compounds and those that are likely to failUtilizing hPS cell models, researchers can distinguish between promising compounds and compounds that are likely to fail in clinical trials. By evaluating the effects of drugs in different cell types, researchers can more accurately predict how well they will work in patients. This helps to screen out the most promising drug candidates and exclude potential losers at an early stage, saving time and resources.
Detecting Cytotoxic EffectsIn addition to assessing the efficacy of drugs, hPS cell models can also be used to detect cytotoxic effects of drugs. By exposing hPS cells or their derived cell models to drug candidates, researchers can evaluate the effects of the drug on cell survival and function. This helps to identify potential toxic effects and allow for timely intervention and adjustment prior to clinical trials.
Applications in Cardiac Drug DevelopmentIn cardiac drug development, hPS cell models can be used to evaluate the impact of drug candidates on cardiac function. By exposing the drug to hPS cell-derived cardiomyocytes, its effects on myocardial contraction and relaxation can be evaluated, thereby predicting the efficacy and safety of the drug on the heart.
Applications in Hepatotoxicity Screening Hepatotoxicity is a common problem in drug development. Using hPS cell-derived hepatocyte models, researchers can evaluate the impact of drug candidates on liver function, thereby predicting their potential hepatotoxic effects and identifying and addressing these issues early.
With the deepening of the research on hPS cells, it is foreseeable that their application in drug development will become more and more extensive. In the future, as technology continues to advance, a more precise and efficient drug development process can be expected to provide patients with safer and more effective treatment options.
Challenges of hPS cell experiments, cell type, maturation, and precise cell annotationIn single-cell hPS cell genomic studies, proper classification and quantification of cell state is critical. However, hPS cells have multiple differentiation potentials, so there may be a mix of multiple cell types during differentiation. To overcome this challenge, researchers need to develop more precise methods for cell classification and combine single-cell transcriptomic data for accurate annotation of cell status.
Diversity and scalabilityThe diversity and scalability of hPS cells is an important factor to consider when conducting population genomics studies. Due to genetic differences between individuals and uncertainty about cell differentiation, researchers need to ensure that these factors are taken into account in experimental design to ensure the reliability of results and generalizability.
Scale-up ChallengesImpact of Technical RobustnessWhen scaling up hPS cell experiments, technical stability (e.g., batch effects) can have an impact on experimental results. To reduce this effect, researchers need to take steps to standardize experimental procedures and conditions, and use uniform quality control standards to ensure data comparability and reliability.
The hPS cell pool was designed to overcome the effects of technical variation and to include more cell lines without increasing time and cost, and the researchers proposed an approach to use the hPS cell pool. This approach involves the simultaneous cultivation and differentiation of multiple hPS cell lines in a single dish, reducing technical variation between experiments and improving the reproducibility and comparability of experiments.
As a cell model, hPS cells have shown great potential in assessing the effects of human genetic variation on different lineages, developmental states, and cell types. These cell models provide a convenient and scalable platform for experimental validation, especially for reproducing human cell models during human development. Although the maintenance and differentiation of hPS cells is limited in experimental time and cost, technological advances have made it possible to perform population genomics studies using hPS cell models.
To accurately determine how genetic variation affects cellular function, statistical methods that test genotype-by-context (G×C) interactions are needed. It is expected that hPS cell experiments will scale from dozens to thousands of cell lines with little impact on overall cost and experimental design. With the convergence of hPS cells, population genetics methods, and cellular genomics, it is expected that these studies will provide valuable tools for the discovery and translation of human genomics.
Link to original article
Farbehi N, Neavin DR, Cuomo ASE, Studer L, MacArthur DG, Powell JE. Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases. Nat Genet. 2024 May; 56(5):758-766. doi: 10.1038/s41588-024-01731-9. Epub 2024 May 13. PMID: 38741017.
https://www.nature.com/articles/s41588-024-01731-9
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