Ancestry-dependent gene expression correlates with reprogramming to pluripotency and multiple dynamic biological processes

Unlocking cellular plasticity: enhancing human iPSC reprogramming through bromodomain inhibition and extracellular matrix gene expression regulation

The transformation from a fibroblast mesenchymal cell state to an epithelial-like state is critical for induced pluripotent stem cell (iPSC) reprogramming. In this report, we describe studies with PFI-3, a small-molecule inhibitor that specifically targets the bromodomains of SMARCA2/4 and PBRM1 subunits of SWI/SNF complex, as an enhancer of iPSC reprogramming efficiency. Our findings reveal that PFI-3 induces cellular plasticity in multiple human dermal fibroblasts, leading to a mesenchymal-epithelial transition during iPSC formation. This transition is characterized by the upregulation of E-cadherin expression, a key protein involved in epithelial cell adhesion. Additionally, we identified COL11A1 as a reprogramming barrier and demonstrated COL11A1 knockdown increased reprogramming efficiency. Notably, we found that PFI-3 significantly reduced the expression of numerous extracellular matrix (ECM) genes, particularly those involved in collagen assembly. Our research provides key insights into the early stages of iPSC reprogramming, highlighting the crucial role of ECM changes and cellular plasticity in this process.

A Preliminary Study on Factors That Drive Patient Variability in Human Subcutaneous Adipose Tissues

Adipose tissue is a dynamic regulatory organ that has profound effects on the overall health of patients. Unfortunately, inconsistencies in human adipose tissues are extensive and multifactorial, including large variability in cellular sizes, lipid content, inflammation, extracellular matrix components, mechanics, and cytokines secreted. Given the high human variability, and since much of what is known about adipose tissue is from animal models, we sought to establish correlations and patterns between biological, mechanical, and epidemiological properties of human adipose tissues. To do this, twenty-six independent variables were cataloged for twenty patients, which included patient demographics and factors that drive health, obesity, and fibrosis. A factorial analysis for mixed data (FAMD) was used to analyze patterns in the dataset (with BMI > 25), and a correlation matrix was used to identify interactions between quantitative variables. Vascular endothelial growth factor A (VEGFA) and actin alpha 2, smooth muscle (ACTA2) gene expression were the highest loadings in the first two dimensions of the FAMD. The number of adipocytes was also a key driver of patient-related differences, where a decrease in the density of adipocytes was associated with aging. Aging was also correlated with a decrease in overall lipid percentage of subcutaneous tissue, with lipid deposition being favored extracellularly, an increase in transforming growth factor-β1 (TGFβ1), and an increase in M1 macrophage polarization. An important finding was that self-identified race contributed to variance between patients in this study, where Black patients had significantly lower gene expression levels of TGFβ1 and ACTA2. This finding supports the urgent need to account for patient ancestry in biomedical research to develop better therapeutic strategies for all patients. Another important finding was that TGFβ induced factor homeobox 1 (TGIF1), an understudied signaling molecule, which is highly correlated with leptin signaling, was correlated with metabolic inflammation. Furthermore, this study draws attention to what we define as "extracellular lipid droplets", which were consistently found in collagen-rich regions of the obese adipose tissues evaluated here. Reduced levels of TGIF1 were correlated with higher numbers of extracellular lipid droplets and an inability to suppress fibrotic changes in adipose tissue. Finally, this study indicated that M1 and M2 macrophage markers were correlated with each other and leptin in patients with a BMI > 25. This finding supports growing evidence that macrophage polarization in obesity involves a complex, interconnecting network system rather than a full switch in activation patterns from M2 to M1 with increasing body mass. Overall, this study reinforces key findings in animal studies and identifies important areas for future research, where human and animal studies are divergent. Understanding key drivers of human patient variability is required to unravel the complex metabolic health of unique patients.

On-Chip Neural Induction Boosts Neural Stem Cell Commitment: Toward a Pipeline for iPSC-Based Therapies

The clinical translation of induced pluripotent stem cells (iPSCs) holds great potential for personalized therapeutics. However, one of the main obstacles is that the current workflow to generate iPSCs is expensive, time-consuming, and requires standardization. A simplified and cost-effective microfluidic approach is presented for reprogramming fibroblasts into iPSCs and their subsequent differentiation into neural stem cells (NSCs). This method exploits microphysiological technology, providing a 100-fold reduction in reagents for reprogramming and a ninefold reduction in number of input cells. The iPSCs generated from microfluidic reprogramming of fibroblasts show upregulation of pluripotency markers and downregulation of fibroblast markers, on par with those reprogrammed in standard well-conditions. The NSCs differentiated in microfluidic chips show upregulation of neuroectodermal markers (ZIC1, PAX6, SOX1), highlighting their propensity for nervous system development. Cells obtained on conventional well plates and microfluidic chips are compared for reprogramming and neural induction by bulk RNA sequencing. Pathway enrichment analysis of NSCs from chip showed neural stem cell development enrichment and boosted commitment to neural stem cell lineage in initial phases of neural induction, attributed to a confined environment in a microfluidic chip. This method provides a cost-effective pipeline to reprogram and differentiate iPSCs for therapeutics compliant with current good manufacturing practices.

Induced pluripotent stem cells (iPSCs): molecular mechanisms of induction and applications

The induced pluripotent stem cell (iPSC) technology has transformed in vitro research and holds great promise to advance regenerative medicine. iPSCs have the capacity for an almost unlimited expansion, are amenable to genetic engineering, and can be differentiated into most somatic cell types. iPSCs have been widely applied to model human development and diseases, perform drug screening, and develop cell therapies. In this review, we outline key developments in the iPSC field and highlight the immense versatility of the iPSC technology for in vitro modeling and therapeutic applications. We begin by discussing the pivotal discoveries that revealed the potential of a somatic cell nucleus for reprogramming and led to successful generation of iPSCs. We consider the molecular mechanisms and dynamics of somatic cell reprogramming as well as the numerous methods available to induce pluripotency. Subsequently, we discuss various iPSC-based cellular models, from mono-cultures of a single cell type to complex three-dimensional organoids, and how these models can be applied to elucidate the mechanisms of human development and diseases. We use examples of neurological disorders, coronavirus disease 2019 (COVID-19), and cancer to highlight the diversity of disease-specific phenotypes that can be modeled using iPSC-derived cells. We also consider how iPSC-derived cellular models can be used in high-throughput drug screening and drug toxicity studies. Finally, we discuss the process of developing autologous and allogeneic iPSC-based cell therapies and their potential to alleviate human diseases.

Machine learning-based morphological quantification of replicative senescence in human fibroblasts

Although aging has been investigated extensively at the organismal and cellular level, the morphological changes that individual cells undergo along their replicative lifespan have not been precisely quantified. Here, we present the results of a readily accessible machine learning-based pipeline that uses standard fluorescence microscope and open access software to quantify the minute morphological changes that human fibroblasts undergo during their replicative lifespan in culture. Applying this pipeline in a widely used fibroblast cell line (IMR-90), we find that advanced replicative age robustly increases (+28-79%) cell surface area, perimeter, number and total length of pseudopodia, and nuclear surface area, while decreasing cell circularity, with phenotypic changes largely occurring as replicative senescence is reached. These senescence-related morphological changes are recapitulated, albeit to a variable extent, in primary dermal fibroblasts derived from human donors of different ancestry, age, and sex groups. By performing integrative analysis of single-cell morphology, our pipeline further classifies senescent-like cells and quantifies how their numbers increase with replicative senescence in IMR-90 cells and in dermal fibroblasts across all tested donors. These findings provide quantitative insights into replicative senescence, while demonstrating applicability of a readily accessible computational pipeline for high-throughput cell phenotyping in aging research.

Addressing the Challenge of Biomedical Data Inequality: An Artificial Intelligence Perspective

Artificial intelligence (AI) and other data-driven technologies hold great promise to transform healthcare and confer the predictive power essential to precision medicine. However, the existing biomedical data, which are a vital resource and foundation for developing medical AI models, do not reflect the diversity of the human population. The low representation in biomedical data has become a significant health risk for non-European populations, and the growing application of AI opens a new pathway for this health risk to manifest and amplify. Here we review the current status of biomedical data inequality and present a conceptual framework for understanding its impacts on machine learning. We also discuss the recent advances in algorithmic interventions for mitigating health disparities arising from biomedical data inequality. Finally, we briefly discuss the newly identified disparity in data quality among ethnic groups and its potential impacts on machine learning.

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1-8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address this significant gap, we present PhyloFrame, the first-ever machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating big data tissue-specific functional interaction networks, global population variation data, and disease-relevant transcriptomic data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. These results demonstrate how AI can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

MATS: a novel multi-ancestry transcriptome-wide association study to account for heterogeneity in the effects of cis-regulated gene expression on complex traits

The Transcriptome-Wide Association Study (TWAS) is a widely used approach which integrates gene expression and Genome Wide Association Study (GWAS) data to study the role of cis-regulated gene expression (GEx) in complex traits. However, the genetic architecture of GEx varies across populations, and recent findings point to possible ancestral heterogeneity in the effects of GEx on complex traits, which may be amplified in TWAS by modeling GEx as a function of cis-eQTLs. Here, we present a novel extension to TWAS to account for heterogeneity in the effects of cis-regulated GEx which are correlated with ancestry. Our proposed Multi-Ancestry TwaS (MATS) framework jointly analyzes samples from multiple populations and distinguishes between shared, ancestry-specific and/or subject-specific expression-trait associations. As such, MATS amplifies power to detect shared GEx associations over ancestry-stratified TWAS through increased sample sizes, and facilitates the detection of genes with subgroup-specific associations which may be masked by standard TWAS. Our simulations highlight the improved Type-I error conservation and power of MATS compared with competing approaches. Our real data applications to Alzheimer's disease (AD) case-control genotypes from the Alzheimer's Disease Sequencing Project (ADSP) and continuous phenotypes from the UK Biobank (UKBB) identify a number of unique gene-trait associations which were not discovered through standard and/or ancestry-stratified TWAS. Ultimately, these findings promote MATS as a powerful method for detecting and estimating significant gene expression effects on complex traits within multi-ancestry cohorts and corroborates the mounting evidence for inter-population heterogeneity in gene-trait associations.

DUX4 double whammy: The transcription factor that causes a rare muscular dystrophy also kills the precursors of the human nose

SMCHD1 mutations cause congenital arhinia (absent nose) and a muscular dystrophy called FSHD2. In FSHD2, loss of SMCHD1 repressive activity causes expression of double homeobox 4 (DUX4) in muscle tissue, where it is toxic. Studies of arhinia patients suggest a primary defect in nasal placode cells (human nose progenitors). Here, we show that upon SMCHD1 ablation, DUX4 becomes derepressed in H9 human embryonic stem cells (hESCs) as they differentiate toward a placode cell fate, triggering cell death. Arhinia and FSHD2 patient-derived induced pluripotent stem cells (iPSCs) express DUX4 when converted to placode cells and demonstrate variable degrees of cell death, suggesting an environmental disease modifier. HSV-1 may be one such modifier as herpesvirus infection amplifies DUX4 expression in SMCHD1 KO hESC and patient iPSC. These studies suggest that arhinia, like FSHD2, is due to compromised SMCHD1 repressive activity in a cell-specific context and provide evidence for an environmental modifier.

Power and optimal study design in iPSC-based brain disease modelling

Studies using induced pluripotent stem cells (iPSCs) are gaining momentum in brain disorder modelling, but optimal study designs are poorly defined. Here, we compare commonly used designs and statistical analysis for different research aims. Furthermore, we generated immunocytochemical, electrophysiological, and proteomic data from iPSC-derived neurons of five healthy subjects, analysed data variation and conducted power simulations. These analyses show that published case-control iPSC studies are generally underpowered. Designs using isogenic iPSC lines typically have higher power than case-control designs, but generalization of conclusions is limited. We show that, for the realistic settings used in this study, a multiple isogenic pair design increases absolute power up to 60% or requires up to 5-fold fewer lines. A free web tool is presented to explore the power of different study designs, using any (pilot) data.

Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts

Chronic environmental stress can profoundly impact cell and body function. Although the underlying mechanisms are poorly understood, epigenetics has emerged as a key link between environment and health. The genomic effects of stress are thought to be mediated by the action of glucocorticoid stress hormones, primarily cortisol in humans, which act via the glucocorticoid receptor (GR). To dissect how chronic stress-driven GR activation influences epigenetic and cell states, human fibroblasts underwent prolonged exposure to physiological stress levels of cortisol and/or a selective GR antagonist. Cortisol was found to drive robust changes in cell proliferation, migration, and morphology, which were abrogated by concomitant GR blockade. The GR-driven cell phenotypes were accompanied by widespread, yet genomic context-dependent, changes in DNA methylation and mRNA expression, including gene loci with known roles in cell proliferation and migration. These findings provide insights into how chronic stress-driven functional epigenomic patterns become established to shape key cell phenotypes.

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Physiological stress levels of cortisol drive robust changes in key cell phenotypes

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Stress-driven changes in cell phenotypes are abrogated by concomitant GR blockade

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GR activation induces functional and phenotypically relevant epigenomic changes

Chromatin openness of donor cells is directly correlated with the in vitro developmental capabilities of cloned buffalo embryos

The Switch/sucrose nonfermentable (SWI/SNF) chromatin remodelling complex is closely related to chromatin openness and gene transcriptional activity. To understand if the chromatin openness of donor cells was related to the development efficiency of somatic cell cloning embryos, two buffalo fetal fibroblasts (BFF), BFF1 and BFF3, with significantly different cloned blastocyst development rates (18.4% and 30.9% respectively), were selected in this study. The expression of SWI/SNF complex genes, chromatin openness, and transcript level of these two cell lines were analysed, and the effect of ATP on the expression of the SWI/SNF complex genes was further explored. The results showed that compared with BFF1, the expression of SWI/SNF complex family genes was higher in BFF3 at the G0/G1 phase, where SMARCC1, SMARCC2 and SMARCE1 were significantly different (p < .05). Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) results showed that, at the genome-wide level, BFF3 had more open chromatin, especially which having more open chromatin peaks at SMARCA4, SMARCA2, and RBPMS2 (RNA Binding Protein, mRNA Processing Factor 2) sites. In total, 2,712 differentially expressed genes (DEGs) were identified by the RNA-Seq method, with 1380 up- and 1332 down-regulated genes in BFF3. Interestingly, the ATPase-related genes ATP1B1 and ATP11A were extreme significantly up-regulated in BFF3 (p < .01). The ATP content and the expression of SWI/SNF complex genes in both BFF1 and BFF3 decreased when treated with rotenone. The above results demonstrated that the SWI/SNF complex contributed to chromatin opening, and chromatin opening of donor cells was essential for cloned embryo development.

Repair, regeneration and rejuvenation require un-entangling pluripotency from senescence

There is a notion that pluripotency and senescence, represent two extremes of life of cells. Pluripotent cells display epigenetic youth, unlimited proliferative capacity and pluripotent differentiating potential whereas cells that reach the Hayflick limit, transit to senescence, undergo permanent inhibition of cell replication and create an aging tissue landscape. However, pluripotency and senescence appear to be intimately linked and are jointly generated in many different contexts such as during embryogenesis or formation of tissue spheroids, in stem cell niches, cancer, or by induction of a pluripotent state (induced pluripotency). Tissue damage and senescence provide signals that are critical to generation of a pluripotent state and, in turn, pluripotency, induces senescence. Thus, it follows, that precisely timed control of senescence is required for harnessing the full benefits of both senescence and its associated pluripotency during tissue regeneration or rejuvenation.

Ancestry of cells must be considered in bioengineering

Bioengineered platforms, intended to be used in the investigation of human health and disease, often incorporate cells of unknown ancestry or that lack diversity. To develop tools and platforms that benefit the entire human population, we must consider the ancestry of cells and intentionally diversify the cells we use in our designs.

Ozone Responsive Gene Expression as a Model for Describing Repeat Exposure Response Trajectories and Interindividual Toxicodynamic Variability In Vitro

Inhaled chemical/material exposures are a ubiquitous part of daily life around the world. There is a need to evaluate potential adverse effects of both single and repeat exposures for thousands of chemicals and an exponentially larger number of exposure scenarios (eg, repeated exposures). Meeting this challenge will require the development and use of in vitro new approach methodologies (NAMs); however, 2 major challenges face the deployment of NAMs in risk assessment are (1) characterizing what apical outcome(s) acute assays inform regarding the trajectory to long-term events, especially under repeated exposure conditions, and (2) capturing interindividual variability as it informs considerations of potentially susceptible and/or vulnerable populations. To address these questions, we used a primary human bronchial epithelial cell air-liquid interface model exposed to ozone (O3), a model oxidant and ubiquitous environmental chemical. Here we report that O3-induced proinflammatory gene induction is attenuated in repeated exposures thus demonstrating that single acute exposure outcomes do not reliably represent the trajectory of responses after repeated or chronic exposures. Further, we observed 10.1-, 10.3-, 14.2-, and 7-fold ranges of induction of interleukin (IL)-8, IL-6, heme oxygenase 1, and cyclooxygenase 2 transcripts, respectively, within in our population of 25 unique donors. Calculation of sample size estimates that indicated that 27, 24, 299, and 13 donors would be required to significantly power similar in vitro studies to identify a 2-fold change in IL-8, IL-6, HMOX1, and cyclooxygenase 2 transcript induction, respectively, to inform considerations of the uncertainty factors to reflect variability within the human population for in vitro studies.

The Future of Gene Therapy for Transfusion-Dependent Beta-Thalassemia: The Power of the Lentiviral Vector for Genetically Modified Hematopoietic Stem Cells

β-thalassemia, a disease that results from defects in β-globin synthesis, leads to an imbalance of β- and α-globin chains and an excess of α chains. Defective erythroid maturation, ineffective erythropoiesis, and shortened red blood cell survival are commonly observed in most β-thalassemia patients. In severe cases, blood transfusion is considered as a mainstay therapy; however, regular blood transfusions result in chronic iron overload with life-threatening complications, e.g., endocrine dysfunction, cardiomyopathy, liver disease, and ultimately premature death. Therefore, transplantation of healthy hematopoietic stem cells (HSCs) is considered an alternative treatment. Patients with a compatible human leukocyte antigen (HLA) matched donor can be cured by allogeneic HSC transplantation. However, some recipients faced a high risk of morbidity/mortality due to graft versus host disease or graft failure, while a majority of patients do not have such HLA match-related donors. Currently, the infusion of autologous HSCs modified with a lentiviral vector expressing the β-globin gene into the erythroid progenitors of the patient is a promising approach to completely cure β-thalassemia. Here, we discuss a history of β-thalassemia treatments and limitations, in particular the development of β-globin lentiviral vectors, with emphasis on clinical applications and future perspectives in a new era of medicine.