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Abstract

Adipocyte dysfunction plays a critical role in the pathogenesis of metabolic diseases, including type 2 diabetes (T2D). Human induced pluripotent stem cells (hiPSCs) offer a powerful platform for generating white, beige, and brown adipocytes, supporting both disease modeling and therapeutic research. This review provides a comprehensive summary of current differentiation methods to produce three functionally mature adipocyte types from pluripotent stem cells (PSCs), including forced gene expression techniques, developmental biology-inspired approaches, and advanced three-dimensional (3D) culture systems that enhance cellular maturity and functional relevance. PSC-derived white adipocytes contribute to modeling adipocyte dysfunction not only in conditions such as insulin resistance, lipodystrophy, and premature aging but also in more complex metabolic diseases, including T2D, facilitating the investigation of disease mechanisms and the identification of novel therapeutic targets. In addition, iPSC-based models provide a robust platform for exploring genetic regulation by genome-wide association studies (GWAS)–identified variants through population genetics. This review also evaluates the therapeutic potential of iPSC-derived white, beige, and brown adipocytes in cell transplantation therapy for metabolic diseases, with a focus on engraftment potential and metabolic improvement. Enhancing the maturity and subtype specificity of PSC-derived adipocytes is expected to accelerate the development of personalized medicine and innovative therapeutic strategies for metabolic diseases.

Graphical Abstract

Keywords

pluripotent stem cells white adipocytes beige adipocytes brown adipocytes transplantation

Introduction

The global prevalence of obesity is rising¹, contributing to an increased incidence of metabolic diseases such as type 2 diabetes (T2D), metabolic dysfunction-associated steatotic liver disease (MASLD), and coronary artery disease^2,3. Obesity is characterized by excessive adipose tissue accumulation, and adipose tissue plays a critical role in maintaining systemic energy homeostasis. Adipocytes are categorized into white, beige, and brown adipocytes, each with distinct functional properties^4,5. White adipocytes primarily store excess energy as lipids and secrete various adipokines that influence metabolic functions⁶. Both an excess and a deficiency of white adipose tissue (WAT), as seen in obesity and lipodystrophy, respectively, are associated with metabolic dysfunction, including T2D^4,7. Brown adipocytes are thermogenic cells that produce heat through uncoupling protein 1 (UCP1)-mediated nonshivering thermogenesis, burning lipids and glucose^8–11. Beige adipocytes, also known as “brite” or “inducible brown” adipocytes, emerge in WAT under cold exposure or β-adrenergic stimulation, activating UCP1 and switching to a thermogenic state^5,12,13. Notably, the quantity and activity of thermogenic adipocytes are reduced in obese individuals^5,9,14,15, suggesting that activation or transplantation of these cells could be a promising therapy for metabolic diseases^16,17. Given the strong association between adipocyte dysfunction and metabolic disorders, studying adipocyte biology is essential for understanding the pathophysiology of these conditions.

Historically, adipocyte research has relied heavily on rodent models¹⁸. However, significant species-specific differences in genome, anatomical structure, function, metabolism, and drug responses complicate the translation of findings to human physiology^19–22. Human adipocyte sources include primary cells—such as adipocytes, preadipocytes, and adipose-derived stem cells (ADSCs)—isolated directly from human tissue and immortalized cell lines. Primary cells maintain physiological relevance but are difficult to obtain, limited in quantity, and challenging to culture long-term. In contrast, cell lines provide a stable and scalable option but are often immortalized using genetic modifications and typically represent a single genetic background limiting their ability to reflect the diversity of human genetic backgrounds^23,24. Consequently, there is a need for a more robust and genetically diverse human adipocyte model.

Human induced pluripotent stem cells (hiPSCs) provide a promising alternative for adipocyte research. iPSCs offer significant advantages, including overcoming the ethical concerns associated with human embryonic stem cells (hESCs) and providing an unlimited source of cells that can differentiate into any cell type²⁵. Moreover, iPSCs retain the donor’s genetic information, enabling the generation of patient-specific iPSC lines^26–28. These cells serve as a valuable platform for in vitro disease modeling, mechanistic studies, and drug discovery. When combined with advanced genome-editing technologies such as CRISPR-Cas9, iPSCs allow for the creation of isogenic cell lines to investigate the effects of specific genetic mutations on disease development^29–31. In addition, iPSC-based models facilitate the functional analysis of disease-associated risk alleles identified through genome-wide association studies (GWAS)^32,33.

Beyond disease modeling, iPSC-derived adipocytes show significant promise for transplantation therapies³⁴. The ability to generate scalable, uniform adipocyte populations from iPSCs creates opportunities for both allogeneic and autologous transplantation. When derived from patient-specific cells, iPSCs can potentially eliminate the need for immunosuppression and reduce the risk of graft rejection. In addition, combining iPSC technology with genetic editing tools enables the transplantation of genetically corrected, healthy adipocytes, providing a novel approach for treating metabolic diseases such as lipodystrophy. The thermogenic properties of brown and beige adipocytes offer unique therapeutic potential^5,17, as their transplantation could enhance energy expenditure, improve insulin sensitivity, and mitigate obesity-related metabolic dysfunctions.

This review summarizes the differentiation methods for generating white, beige, and brown adipocytes from hPSCs, highlights their utility in metabolic disease modeling and transplantation therapies, and explores their transformative potential in personalized treatment strategies. Furthermore, it discusses recent advancements in population genetics, current challenges, and future directions in the field of iPSC-derived adipocyte research.

Pluripotent stem cell-derived white, beige, and brown adipocytes

White adipocyte differentiation methods

Efficient methods to differentiate hiPSCs into functional white, brown, and beige adipocytes have been developed, enabling advanced metabolic research and therapeutic applications. Early studies on ESCs highlighted their adipogenic potential^35,36, demonstrating PSCs as a viable tool for adipocyte generation. Taura et al. first demonstrated iPSC differentiation into white adipocytes using an embryoid body (EB)–based protocol, which involved transient retinoic acid (RA) treatment during EB formation and subsequent adipogenic induction on adherent plates. This approach demonstrated adipogenic potential comparable with that of hESCs³⁷. Subsequently, forced gene expression strategies were introduced to enhance adipogenesis. Notably, Ahfeldt et al. expanded mesenchymal progenitor cells (MPCs) derived from EBs and applied transient overexpression of PPARG2 in a doxycycline-inducible system, significantly improving the efficiency of white adipocyte differentiation. After 7 days of suspension culture, the formed EBs were replated onto dishes, and fibroblast-like outgrowth cells were serially passaged. These fibroblast-like cells (i.e. MPCs) exhibited proliferative capacity and expressed MSC markers, and were subsequently transduced with a doxycycline-inducible PPARG2 construct. Following successful transduction, with an efficiency of nearly 98% in MPCs, adipogenic induction was initiated with doxycycline treatment for 16 days, followed by 5 days without doxycycline, resulting in over 85% of cells differentiating into mature adipocytes with transcriptional and functional profiles comparable with primary white adipocytes, including lipolysis, adiponectin secretion, de novo lipogenesis, insulin signaling, and glucose uptake³⁸.

Like EB-derived MPCs, iPSC-derived mesenchymal stem cells (iMSCs) can be generated using various methods^39,40. However, as observed in Ahfeldt et al.’s study, where adipogenic differentiation was extremely inefficient without forced gene expression, these iMSCs exhibit lower adipogenic potential than ADSCs or bone marrow–derived MSCs^41,42. As a result, many studies report only a limited propensity of iMSCs for differentiation toward adipocyte lineages rather than robust adipogenesis^43,44, making these cells less suitable for the analysis of mature white adipocyte functions.

Brown and beige adipocyte differentiation methods

Like white adipocytes, brown adipocytes can be differentiated through the forced expression of key transcription factors. Overexpression of PPARG2, CEBPB, and PRDM16 in MPCs promotes their differentiation into brown adipocytes. The resulting brown adipocytes showed increased glycerol release in response to forskolin stimulation, along with enhanced mitochondrial activity³⁸. Using a similar approach, Kishida et al.⁴⁵ developed a method to generate brown adipocytes from hiPSCs by introducing PRDM16 into EBs cultured with RA. In addition, Nishio et al. focused on the bone marrow microenvironment, which enhances adipogenic differentiation, and developed a method to generate functional brown adipocytes from hiPSCs using hematopoietic cytokines. Their protocol involves an 8-day suspension culture, during which cells transiently express myoblastic markers such as MYF5, followed by adherent culture for several days, which yields adipocytes with characteristic multilocular lipid droplets⁴⁶. To refine this approach, Oka et al.⁴⁷ developed a cytokine-free method by culturing iPSCs as size-controlled spheroids, facilitating spontaneous differentiation into a brown-like phenotype, although the molecular mechanisms underlying this differentiation method remain unclear.

Mohsen-Kanson et al. demonstrated that in an EB-based adipogenic differentiation system, RA treatment during the EB stage promotes white adipocyte formation, whereas its absence favors the emergence of adipocytes expressing brown markers. In their protocol, EBs were replated and expanded for 10 days, followed by an additional 10 days of adipogenic induction to generate white and brown adipocytes. Furthermore, they demonstrated that forced expression of Pax3 at the progenitor stage for white adipocyte differentiation, followed by adipogenic induction, resulted in a phenotypic shift toward brown adipocytes, underscoring the critical role of Pax3 in driving brown adipocyte differentiation⁴⁸. Furthermore, following a similar approach, Hafner et al.⁴⁹ increased differentiation efficiency for brown adipocytes by inhibiting the TGFβ pathway, highlighting the significance of TGFβ signaling in brown adipocyte differentiation. In contrast, the adipocytes generated by Guénantin et al. did not express brown adipocyte markers but instead exhibited beige adipocyte-specific markers. They employed a short-term (~20-day) differentiation protocol involving mesodermal induction using BMP4 and Activin A, followed by adipogenic stimulation, resulting in beige adipocytes with functional thermogenic properties upon cAMP analog activation⁵⁰.

Recent studies on murine adipocyte development^51–57 have led to differentiation methods that more accurately recapitulate in vivo lineage trajectories. Su et al. established a stepwise differentiation protocol to generate functional beige adipocytes by directing hiPSCs through FOXF1⁺ splanchnic mesoderm. This mesoderm gives rise to an expandable, mural-like MSC population. Upon treatment with a TGF-β inhibitor and adipogenic induction, these MSCs differentiate into adipogenic precursors enriched for PDGFRα and EBF2. Further induction produces mature beige adipocytes with high UCP1 expression, uncoupled respiration, and secretion of metabolically beneficial factors⁵⁸. In contrast, Zhang et al. established a differentiation method to generate functional brown adipocytes from hPSCs by guiding them through a paraxial mesoderm intermediate. The resulting paraxial mesoderm express FOXC1, PAX3, and MYF5, and upon adipogenic induction with browning factors, differentiate into brown adipocytes characterized by multilocular lipid droplets, high mitochondrial density, robust UCP1 expression, and enhanced glycolytic and oxidative metabolism in response to cAMP signaling⁵⁹. Complementing these approaches, Rao et al. used single-cell RNA sequencing of developing mouse interscapular brown fat to identify a transient GATA6⁺ precursor stage. By replicating these developmental cues, they established a multistep differentiation protocol that directs hiPSCs through the dermomyotome and a GATA6⁺ brown adipocyte precursor phase. This approach yielded functional UCP1⁺ brown adipocytes with multilocular lipid droplets, abundant mitochondria, and thermogenic activity, providing a differentiation strategy closely aligned with in vivo lineage progression⁶⁰. Collectively, these studies provide robust, developmentally informed, and scalable platforms for generating beige and brown adipocytes from hPSCs, offering valuable models for metabolic research and potential applications in cell therapy for obesity and diabetes. A schematic representation of representative adipocyte differentiation methods is shown in Fig. 1.

Figure 1.

Differentiation methods of PSC-derived adipocytes: white, beige, and brown lineages. This figure illustrates the various methodologies for differentiating pluripotent stem cells (PSCs) into white, beige, and brown adipocytes via distinct intermediate stages and culture conditions. Dashed arrows denote suspension culture, while solid arrows indicate adherent culture methods. Adipocyte types are color-coded: yellow for white adipocytes, light brown for beige adipocytes, and dark brown for brown adipocytes. ESC: embryonic stem cells; iPSC: induced pluripotent stem cells; MPC: mesenchymal progenitor cells; WAP: white adipocyte progenitor; BAP: brown adipocyte progenitor; RA: retinoic acid; MSC: mesenchymal stem cells. Created with BioRender.com.

Three-dimensional organoid and microphysiological systems for adipocyte maturation

Recent advances have highlighted the potential of 3D organoid and microphysiological systems (MPS), namely, organ-on-a-chip platforms^61–63, in enhancing the functionality and application of iPSC-derived adipocytes. Yao and Dani developed a 3D vascularized spheroid model by co-culturing hiPSC-derived brown adipocyte progenitors with human dermal microvascular endothelial cells (HDMECs), enabling the formation of prevascularized adipospheres that more closely mimic the native adipose tissue microenvironment. This coculture system not only enhanced lipid accumulation and UCP1 expression within the spheroids but also promoted extracellular matrix organization and vascular network formation, leading to improved adipocyte maturation and metabolic functionality compared with conventional two-dimensional (2D) cultures⁶⁴. In addition, Qi et al. established a sophisticated MPS that incorporates hiPSC-derived adipocytes with macrophages and hepatocytes, enabling the reconstitution of complex tissue interactions (described in detail in the later section on Modeling Physiological Insulin Sensitivity and Resistance)^65–67. These innovative 3D culture systems provide advanced platforms for modeling human metabolic diseases and hold promise for future therapeutic development.

Applications and remaining challenges of differentiation methods

While numerous methods have been developed to differentiate PSCs into white, beige, and brown adipocytes, selecting the appropriate approach should be guided by specific research objectives. For example, forced gene expression models enable relatively uniform production of mature adipocytes, making them particularly suitable for terminal differentiation phenotype analyses or comparative studies across multiple iPSC lines. In contrast, gene-free, stepwise differentiation protocols that mimic natural developmental pathways are better suited for investigating developmental processes, assessing gene function within physiological contexts, and advancing human transplantation studies.

However, these differentiation protocols are associated with several critical challenges. First, some protocols may generate immature adipocytes. Morphologically, white adipocytes derived through these methods often lack characteristic unilocular lipid droplets, while the functional properties of brown adipocytes—such as UCP1 expression and thermogenic activity—are often insufficiently characterized in comparison with primary adipocytes. This immaturity may compromise their ability to accurately model slight phenotypic changes associated with multifactorial, late-onset metabolic diseases and could limit their effectiveness in transplantation therapy.

Second, adipocyte heterogeneity remains a major challenge, particularly among white adipocytes. Subcutaneous and visceral adipocytes are known to differ significantly, often exerting opposing effects on metabolic disease risk. Subcutaneous adipose tissue is the safest and most optimal site for storing excess lipids. In contrast, increased accumulation in visceral adipose tissue is associated with a higher risk of metabolic diseases^68,69. Nevertheless, current differentiation models rarely specify which adipocyte subtype is generated, posing a considerable obstacle for disease modeling and therapeutic applications. Lineage tracing studies in mice have revealed that subcutaneous and visceral adipocytes originate from distinct progenitor populations⁵¹. Posterior lateral plate mesoderm derivatives, labeled by HoxB6-CreERT, give rise to both subcutaneous and visceral fat⁵². The Prx1-Cre lineage predominantly contributes to subcutaneous WAT⁵³, whereas Wt1-CreERT2 marks visceral depots⁵⁴. Together, these findings suggest that subcutaneous and visceral adipocytes share a common embryonic origin in the posterior lateral plate mesoderm, which subsequently segregates into somatic mesoderm producing subcutaneous fat and splanchnic mesoderm giving rise to visceral fat. However, current differentiation protocols do not account for these mesodermal lineage differences. In addition, single-cell RNA sequencing of mouse and human adipose tissue has identified multiple subpopulations within the adipocyte progenitor pool, including adipose stem cells, preadipocytes, and anti-adipogenic progenitors, each with distinct proliferative and adipogenic potentials^70–72, and has also revealed heterogeneity among mature adipocytes⁷³. These findings provide insights into the various cellular states that adipocytes transition through, offering valuable reference points for the development of differentiation protocols. Future differentiation protocols should be designed to generate specific adipocyte subtypes, guided by detailed lineage maps and/or single-cell analyses to better capture the inherent cellular diversity within adipose tissues.

Metabolic disease modeling

Adipocyte dysfunction is a key contributor to various metabolic diseases^4,7, and modeling the pathological states of human adipocytes in vitro is essential for disease research. Two main strategies exist for constructing adipocyte disease models: physiological modeling through culture conditions and cell–cell interactions, and genetic modeling based on disease-relevant genomic backgrounds. The following sections detail specific models of metabolic diseases, demonstrating how hPSC-based approaches enhance our understanding of adipocyte dysfunction and support personalized treatment strategies.

Modeling physiological insulin sensitivity and resistance

Dysfunction in adipocyte insulin signaling is a critical factor in the pathogenesis of metabolic diseases, including T2D⁷⁴. Insulin resistance in adipocytes not only contributes to impaired glucose homeostasis but also precedes the onset of T2D⁷⁵, highlighting the need for in vitro models that can accurately replicate physiological insulin responses. However, traditional in vitro adipocyte models often fail to mimic in vivo insulin signaling, largely due to nonphysiological and suboptimal culture conditions^18,76. These limitations hinder mechanistic studies of insulin signaling and resistance, thereby constraining the development of effective therapeutic strategies. Friesen et al. developed a novel culture method for generating an hPSC-derived white adipocyte model that accurately mimics physiological insulin sensitivity and resistance. By optimizing nutrient conditions and treating adipocytes with a physiological sensitization medium for 5 days, they enhanced insulin-stimulated glucose uptake and AKT2 phosphorylation. They established a physiologically relevant insulin resistance model using chronic hyperinsulinemia and demonstrated TNFα treatment as an alternative approach to induce insulin resistance⁷⁷.

As mentioned above, three recent studies utilized 3D MPS to model insulin sensitivity and resistance using hiPSC-derived white adipocytes (iADIPO) and macrophages (iMAC). In the first study, Qi et al. developed a 3D iADIPO-MPS by differentiating adipocyte progenitors into mature white adipocytes within a hydrogel matrix encapsulated in a microfluidic device. This system provided an insulin-responsive adipocyte model, characterized by enhanced adipogenic maturation with large unilocular lipid droplets, robust insulin-stimulated glucose and fatty acid uptake, and hormonally regulated lipolysis, reflecting functional competence similar to in vivo human white adipose tissue⁶⁵. Building upon this platform, a subsequent study introduced a macrophage-adipocyte coculture model (iMAC-iADIPO-MPS), in which proinflammatory M1 macrophages were added to induce insulin resistance and dysregulated lipolysis in the adipocytes, effectively modeling chronic inflammation in white adipose tissue. In this system, M1 macrophages actively migrated into adipocyte clusters, formed crown-like structures (CLS) around damaged adipocytes, and established a reciprocal proinflammatory loop that impaired insulin signaling⁶⁶. Expanding the complexity further, the latest study integrated adipocytes, hepatocytes, and proinflammatory macrophages into a multitissue MPS to recapitulate the crosstalk between adipose tissue and liver in metabolic disease. This system showed that adipocyte inflammation increased lipolysis and fatty acid transfer to hepatocytes, causing lipid accumulation, inflammation, and insulin resistance. These effects were reversed by semaglutide and metformin, demonstrating the platform’s utility for mechanistic studies and drug screening⁶⁷. Together, these studies represent a logical progression from basic insulin sensitivity assays to complex multitissue models, advancing human-specific modeling of metabolic dysfunction.

Monogenic disease models

Lipodystrophy

Lipodystrophies comprise a group of rare disorders characterized by abnormal adipose tissue distribution, which lead to severe metabolic complications such as insulin resistance, hypertriglyceridemia, and hepatic steatosis^78,79. Given the limitations of traditional mice models in capturing human-specific pathophysiology⁸⁰, iPSC technology offers a powerful platform to model lipodystrophic conditions, enabling detailed investigations of adipocyte function and the development of targeted therapies.

Mori et al. in our laboratory generated iPSCs from patients with congenital generalized lipodystrophy (CGL) caused by BSCL2 (SEIPIN) mutations and differentiated them into adipocytes. These BSCL2-iPSCs showed impaired adipogenesis with reduced lipid droplet formation and disrupted adipose differentiation-related protein (ADRP) localization. The adipogenic defects were rescued by the forced expression of wild-type BSCL2, demonstrating SEIPIN’s critical role in lipid accumulation and adipocyte differentiation⁸¹. Friesen and Cowan established iPSCs from familial partial lipodystrophy type 2 (FPLD2) patients with the LMNA R482W mutation. The iPSC-derived adipocytes exhibited reduced adipogenic capacity, increased insulin resistance, and elevated lipolysis and autophagy⁸².

Recent advancements in genome-editing technologies have enabled the creation of isogenic models for monogenic disorders, including congenital lipodystrophies. These approaches allow for the precise introduction of pathogenic mutations into normal ES or iPS cells, as well as the correction of mutations in patient-derived iPS cells, facilitating robust disease modeling and therapeutic research. Ding et al. demonstrated this approach by introducing a frameshift mutation in the PLIN1 gene, a cause of congenital partial lipodystrophy, into hESCs using TALEN technology. The resulting adipocytes showed increased lipolysis, replicating the lipodystrophic phenotype. They further generated adipocyte models with SORT1 and AKT2 mutations, demonstrating changes in insulin-stimulated GLUT4 translocation, glucose uptake, and triglyceride metabolism⁸³. This study established a robust framework for generating isogenic cellular models of metabolic diseases. By leveraging advanced genome and epigenome editing tools such as CRISPR/Cas9⁸⁴, base editing⁸⁵, prime editing⁸⁶, and dCas9-based epigenetic modulators⁸⁷, disease-associated variants identified in GWAS and epigenome-wide association study (EWAS) for T2D^88-90 and obesity⁹¹ can be precisely introduced into iPSCs. This approach enables the accurate modeling of complex metabolic diseases, providing valuable insights into disease mechanisms and advancing targeted therapy development.

Premature aging

Aging is a critical risk factor for T2D and is associated with an accumulation of senescent cells in adipose tissue. Senescent preadipocytes⁹² and adipocytes^93,94 promote inflammation through the senescence-associated secretory phenotype (SASP) and exhibit reduced insulin sensitivity, contributing to metabolic dysfunction^95,96. Developing in vitro models of adipocyte aging is crucial to better understand age-related metabolic diseases.

Studies using hPSC models of adipogenesis, particularly those modeling premature aging syndromes, offer valuable insights into cellular senescence. Goh et al. developed a premature aging model using hPSC to study Werner syndrome and Bloom syndrome, both characterized by defective DNA damage repair and early-onset metabolic complications. They generated WRN^−/− and BLM^−/− hESC lines using CRISPR/Cas9 and differentiated these cells into preadipocytes. These preadipocytes exhibited a markedly increased senescence phenotype, characterized by reduced proliferation rates, shortened telomeres, elevated SA-β-gal staining, and upregulation of senescence-associated markers. Subsequent adipogenic induction of these senescent preadipocytes resulted in significantly impaired differentiation into mature adipocytes with decreased adiponectin secretion, contributing to a “lipodystrophy-like” insulin resistance phenotype⁹⁷. This not only advances the understanding of premature aging syndromes but also highlights the potential of this model as a valuable tool for studying adipocyte aging.

Traditional in vitro models of adipocyte and preadipocyte senescence often use primary cells from aged or obese mice⁹² or external stressors such as irradiation, H₂O₂, and doxorubicin to induce aging phenotypes^93,98,99, effectively replicating age-related morphological and functional changes. Diverse approaches to induce senescence have also been successfully implemented in other iPSC-derived differentiated cells. For instance, iPSC-derived neurons have been subjected to various senescence-inducing strategies¹⁰⁰, including chemical treatments (e.g. telomerase inhibitor BIBR1532¹⁰¹), genetic manipulation (e.g. progerin overexpression¹⁰²), and prolonged culture conditions¹⁰³. Applying these advanced methodologies to adipocytes could significantly improve our understanding of adipose tissue aging and its broader implications for metabolic health.

Complex metabolic disease modeling

Insulin resistance and T2D are multifactorial diseases influenced by multiple genetic and environmental factors. To elucidate the impact of polygenic risk factors specific to individual patients, iPSC technology offers a powerful platform for generating patient-specific cellular models. By differentiating iPSCs into relevant cell types, researchers can investigate disease mechanisms in a controlled in vitro environment, minimizing the confounding effects of systemic interactions present in vivo.

The use of iPSC-derived adipocytes in studies remains limited, with only an example from polycystic ovary syndrome (PCOS) patients¹⁰⁴. However, more substantial progress has been made with other insulin-responsive tissues¹⁰⁵. For instance, several studies have successfully recreated insulin resistance using iPSCs derived from insulin-resistant^106–108 or T2D patients^109–111. iPSC-derived myoblasts (iMyos) from individuals with T2D, nondiabetic individuals with insulin resistance, and insulin-sensitive controls exhibited significant differences in protein phosphorylation networks, depending on insulin resistance status¹⁰⁹. Many signaling changes in insulin-resistant nondiabetic iMyos overlapped with those in cells from individuals with T2D, and donor sex further influenced cellular signaling and downstream responses¹¹¹. Furthermore, cell-autonomous changes in gene expression associated with insulin resistance in iPSC-derived myoblasts were identified, demonstrating that these changes were regulated independently of DNA methylation¹¹⁰.

These findings underscore the potential of iPSC models to uncover cell-intrinsic mechanisms of insulin resistance, which could be particularly informative if extended to adipocytes. Generating iPSCs from T2D patient populations representing racially¹¹² and genetically defined disease subtypes⁸⁹ could reveal subtype-specific phenotypes in white and brown adipocytes. Such research could help elucidate the genetic and cellular bases of metabolic heterogeneity and facilitate the development of tailored therapeutic approaches.

Population genetics approach

iPSC-based models offer a powerful platform for exploring how genetic risk variants influence gene regulation in complex diseases. GWAS have identified numerous loci associated with these diseases. Notably, more than 90% of these loci reside in noncoding regions, implying that they contribute to disease through regulatory changes rather than direct protein-coding alterations^113,114. However, the small effect sizes of individual variants and their cell type-specific and context-dependent impacts present challenges in deciphering their regulatory mechanisms^115,116.

A promising strategy to overcome these challenges involves generating specific cell types from iPSCs and applying population genetics approaches. An early example of this approach focused on cardiometabolic diseases, where researchers reprogrammed peripheral blood cells collected from participants in the Framingham Heart Study into iPSCs, differentiating them into white adipocytes and hepatocyte-like cells (HLCs). Quantitative trait locus (QTL) analysis of 68 iPSC lines revealed that the rs12740374 variant at the 1p13 locus significantly influenced lipid accumulation and gene expression, particularly in HLCs¹¹⁷. This study established a critical proof of concept, demonstrating that iPSC-derived cells could effectively validate the functional impact of noncoding GWAS variants, highlighting the method’s potential in decoding complex genetic contributions to metabolic diseases.

Despite these advancements, iPSC-based population genetics approaches still face several challenges. Differentiation efficiency and cellular phenotypes show substantial variability across iPSC lines derived from different donors^118,119, complicating the interpretation of genotype–phenotype relationships. Moreover, achieving sufficient statistical power to detect moderate-effect genetic variants typically requires relatively large cohorts—generally 20 to 80 individuals¹²⁰. Another limitation is that traditional static QTL analyses may not adequately reflect the dynamic regulatory effects of genetic variants under varying physiological or environmental conditions. To address the challenges, innovative approaches such as dynamic QTL analyses are being developed³³. By integrating single-cell RNA sequencing and temporal analysis, these methods can assess how genetic variants affect cellular responses to stimuli over time, offering a more nuanced understanding of regulatory networks^115,116. Such dynamic analyses could significantly enhance the utility of iPSC models in population genetics.

Transplantation

White adipocytes

Lipodystrophy is characterized by abnormal loss of adipose tissue and associated systemic metabolic dysfunction. Adipose tissue transplantation has been shown to ameliorate metabolic abnormalities in lipodystrophy¹²¹ and is also effective for soft tissue reconstruction following tumor resection¹²². Therefore, PSC-derived white adipocytes represent a promising cellular source for therapeutic applications in lipodystrophy and soft tissue regeneration.

Noguchi et al. demonstrated that white adipocytes differentiated from hiPSCs and ESCs successfully engraft after transplantation into mice. Their protocol involved EB formation, followed by adipogenic induction in adherent culture and subcutaneous transplantation of Matrigel-embedded adipocytes into immunodeficient mice. Surviving cells were detected for up to 4 weeks post-transplantation¹²³. In parallel, Ahfeldt et al.³⁸ reported that white adipocytes induced from PSC-derived MPCs through forced expression of PPARG2 retained CEBPA expression for 4 to 6 weeks in vivo.

Although these studies demonstrated that PSC-derived white adipocytes can survive for a certain period in vivo, their effects on systemic metabolism have not been investigated, and the therapeutic potential of PSC-derived white adipocyte transplantation for metabolic diseases remains unclear. Previous studies have shown that white adipocyte transplantation may improve or exacerbate metabolic parameters, depending on the characteristics of the transplanted cells^{46,121,124,125}. White adipocytes are classified into subcutaneous and visceral adipocytes based on their anatomical origin, each exerting distinct effects on metabolic health. Current iPSC-derived white adipocyte models fail to specify which anatomical subtype they represent. For future transplantation therapies, efforts should focus on generating subcutaneous-like “healthy” white adipocytes that provide metabolic benefits to optimize treatment outcomes for metabolic disorders^34,124.

Brown and beige adipocytes

In humans, the quantity and activity of brown and beige adipocytes are reduced in individuals with obesity and aging^9,14,15,126. As thermogenic adipocytes improve insulin sensitivity and metabolic health^5,127,128, their transplantation represents a promising therapeutic approach for metabolic diseases^16,129.

Ahfeldt et al. demonstrated the transplantation potential of hPSC-derived brown adipocytes by inducing PPARG2, CEBPB, and PRDM16 expression in MPCs. Following subcutaneous transplantation into immunodeficient mice, these cells formed ectopic fat pads with morphology characteristic of primary brown adipocytes. Notably, positron-emission tomography imaging showed high ¹⁸FDG uptake in transplanted brown adipocytes³⁸. Nishio et al. were the first to demonstrate that transplantation of PSC-derived brown adipocytes could improve systemic metabolism in mice. The transplanted BAs enhanced glucose and lipid metabolism soon after transplantation, with improvements in glucose metabolism sustained for at least 3 weeks post-transplantation⁴⁶. In addition, Kishida et al. showed that iPSC-derived brown adipocytes could significantly reduce diet-induced obesity and insulin resistance in mice. The transplanted brown adipocytes exhibited UCP1-dependent thermogenic activity, improving glucose tolerance and lipid profile⁴⁵. Furthermore, BAs generated by Zhang et al. engrafted within the interscapular region of recipient mice and exhibited thermogenic activity. The recipient animals showed increased metabolic activity, respiratory exchange ratio, and whole-body energy expenditure, leading to improved glucose homeostasis⁵⁹. The generation of functional PSC-derived BAs has demonstrated potential as a therapeutic source for metabolic disease by improving glucose and lipid metabolism in transplanted mice.

As a transplantation therapy using beige adipocytes, Guénantin et al. embedded hPSC-derived beige adipocytes in Matrigel and transplanted them into mice. The transplanted cells organized into well-structured, vascularized adipose tissue. After treating the recipient mice with isoproterenol for 7 days, the transplanted adipocytes showed increased expression of thermogenic markers, along with reduced lipid droplet size and enhanced mitochondrial content, resulting in a more pronounced thermogenic phenotype⁵⁰. These findings suggest that adjunctive therapies post-transplantation could enhance graft function and amplify therapeutic effects.

The use of reprogrammed cells from metabolic disease patients represents one potential strategy for transplantation therapy, as exemplified by Su et al. They investigated the potential of autologous iPSC-derived beige adipocytes for transplantation in patients with T2D who have impaired beige adipocyte formation. They reprogrammed primary adipogenic precursors in WAT from elderly T2D patients into iPSCs and differentiated them into beige adipocytes with enhanced thermogenic capacity. These iPSC-derived beige adipocytes also secreted factors that improved insulin sensitivity in the patients’ primary adipocytes, highlighting their potential for providing both thermogenic and antidiabetic benefits⁵⁸. The detailed results of each adipocyte transplantation experiment were summarized in Table 1.

Table 1.

Metabolic effects of iPSC- and ESC-derived adipocyte transplantation in mouse models.

Study	Cell origin	Adipocyte type	Number of cells transplanted	Recipient mice(transplantation site)	Metabolic evaluation
White adipocyte
Ahfeldt et al.³⁸ (White)	Human ESC	White adipocytes	-	Rag2 KO, IL2rg KO mice (Subcutaneous)	Survived for 4 to 6 weeks after transplantation
Noguchi et al.¹²³	Human ESC/iPSC	White adipocytes	2 × 10⁷ cells in Matrigel	BALB/cA nude mice (Subcutaneous on the back)	Survived for at least 4 weeks after transplantation
Brown/Beige adipocyte
Ahfeldt et al.³⁸ (Brown)	Human ESC	Brown adipocytes	-	Rag2 KO, IL2rg KO mice (Subcutaneous)	Survived for 4 to 6 weeks after transplantation, demonstrating¹⁸ FDG uptake
Nishio et al.⁴⁶	Human ESC	Brown adipocytes	1 × 10⁶ cells in saline	ICR mice or NOG mice (Subcutaneous)	Improved lipid and glucose metabolism following isoproterenol administration, with maintained reduction in fasting blood glucose for at least 3 weeks post-transplantation
Kishida et al.⁴⁵	Mouse iPSC derived from recipient mice	Brown adipocytes	Cells from two confluent 100 mm dishes in Matrigel	C57BL/6 mice with high-fat diet or KK-Ay/Tajcl mice (Subcutaneous)	Suppressed weight gain and dyslipidemia under a high-fat diet, along with reduced weight gain and blood glucose elevation in T2D diabetic mice
Guénantin et al.⁵⁰	Human iPSC	Beige adipocytes (cells at day 18)	1 × 10⁷ cells in Matrigel	FoxN1^Nu athymic mice (Subcutaneous on the back)	Enhanced thermogenic phenotype in vivo following 7 days of isoproterenol administration
Zhang et al.⁵⁹	Human ESC	Brown adipocytes	2 cm² size cell culture sheet (approximately equals to 5 × 10⁶ cells)	NOD/SCID mice or SCID mice treated with streptozotocin (Subcutaneous cavity near interscapular region)	Elevated O₂ consumption, respiratory rates, and whole-body energy expenditure in nondiabetic mice, with reduced circulating glucose levels over 7 days in hyperglycemic mice

iPSC: induced pluripotent stem cells; ESC: embryonic stem cells.

Challenges and prospects for human transplantation

Currently, there are no reports of PSC-derived adipocyte transplantation in humans, and several critical challenges must be addressed for clinical application. First, immune rejection is a major concern for allogeneic transplantation, which typically necessitates immunosuppressive therapy. Autologous transplantation using patient-derived cells avoids immune rejection, but generating clinical-grade patient-specific iPSC lines remains costly and time-consuming¹³⁰. A more practical alternative is the use of preestablished allogeneic iPSC banks¹³¹, such as the GMP-grade haplobank from CiRA in Japan, which provides 27 HLA-matched iPSC lines covering approximately 40% of the Japanese population¹³². Another promising approach to reducing immune rejection is the development of hypoimmunogenic cell lines by genetically editing cells by deleting MHC class I and class II molecules and introducing immune-evasive molecules such as CD47, CD64, HLA-E, and HLA-G¹³³. Second, the risk of tumor formation remains a significant safety concern with PSC-derived cells. While no tumors have been reported in regulated clinical trials to date¹³⁴, a case in China has been reported where a patient developed an immature teratoma and lymph node metastases after receiving autologous hiPSC-derived beta islet cells outside a regulated trial¹³⁵. This highlights the importance of strict protocols and rigorous quality control under regulatory oversight to ensure safety. Third, the long-term survival and functional maintenance of transplanted adipocytes pose another critical challenge. Even in human adipose tissue, where approximately 10% of adipocytes turn over annually¹³⁶, the long-term survival of PSC-derived adipocytes after transplantation remains uncertain. To improve engraftment and sustained functionality, optimizing the transplantation site, adjusting the cell dose, employing cell encapsulation techniques, and controlling the differentiation stage at transplantation are crucial^137,138. In addition, obesity-related cellular stress can promote adipocyte apoptosis¹³⁹; thus, strategies to prevent excessive nutritional or metabolic stress after transplantation may be necessary to improve graft survival. Fourth, particularly for brown adipocyte transplantation, metabolic enhancement should be restricted to conditions of obesity or hyperglycemia. Experimental data from mouse studies show that transplanted hESC-derived brown adipocytes do not significantly reduce body weight under normal conditions as observed in mouse-derived BAT transplantations^59,140. However, sustained metabolic enhancement after the normalization of body weight and metabolic function may lead to undesirable side effects. Beige adipocyte transplantation may be advantageous because their metabolic activity could potentially be controlled pharmacologically⁵⁰, allowing metabolic effects to be activated or deactivated as clinically necessary. Resolving these challenges comprehensively will enable PSC-derived adipocyte transplantation to become a novel and effective therapeutic approach for treating metabolic diseases.

Conclusion

In an era that increasingly emphasizes the importance of human models for elucidating disease pathophysiology and advancing drug discovery, iPSC-derived differentiated cells are becoming an increasingly valuable source for research and therapeutic applications. Early adipocyte differentiation models were characterized by undefined developmental origins and relied solely on lipid accumulation and adipogenic marker expression to identify adipocytes. In contrast, more recent approaches aim to faithfully replicate developmental processes, enabling the generation of adipocytes with enhanced functionality and maturity. Utilizing adipocytes with more precisely defined identities will not only improve the resolution of disease modeling but also open new avenues for therapeutic development, including strategies targeting specific adipocyte subtypes. Furthermore, combining practical expertise gained from the rapidly advancing field of iPSC-based transplantation^134,141,142 with innovative technologies such as immune-evasive iPSCs holds the potential to transform these models into practical, next-generation therapeutic strategies for metabolic diseases.

Footnotes

ORCID iDs

Yamato Keidai

Junji Fujikura

Ethical considerations

This manuscript is a review article and does not involve any ethical issues. All authors reviewed and approved the final version of the manuscript.

Author contributions

Y.K. designed the review structure, conducted the literature review, and drafted the manuscript. J.F. and D.Y. supervised the study and provided critical feedback and revisions. All authors contributed to the finalization of the manuscript and approved the final version.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Japan Society for the Promotion of Science KAKENHI (Grant No. 24K14720), the Grants from Japan Society of Metabolism and Clinical Nutrition (Grant No. 2023-YR004), and JST SPRING (Grant No. JPMJSP2110).

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Statement of human and animal rights

This article does not contain any studies with human or animal subjects.

Statement of informed consent

There are no human subjects in this article and informed consent is not applicable.

Data availability statement

All information in this review was obtained from previously published literature. Therefore, no new data were generated or analyzed, and all referenced data are publicly available.

References

Okunogbe

Nugent

Spencer

Ralston

Wilding

. Economic impacts of overweight and obesity: current and future estimates for eight countries. BMJ Glob Health. 2021;6(10):e006351.

Eckel

Grundy

Zimmet

. The metabolic syndrome. Lancet. 2005;365(9468):1415–28.

Lin

. Obesity: epidemiology, pathophysiology, and therapeutics. Front Endocrinol (Lausanne). 2021;12:706978.

Kahn

Wang

Lee

. Altered adipose tissue and adipocyte function in the pathogenesis of metabolic syndrome. J Clin Invest. 2019;129(10):3990–4000.

Harms

Seale

. Brown and beige fat: development, function and therapeutic potential. Nat Med. 2013;19(10):1252–63.

Morigny

Boucher

Arner

Langin

. Lipid and glucose metabolism in white adipocytes: pathways, dysfunction and therapeutics. Nat Rev Endocrinol. 2021;17(5):276–95.

Cusi

. The role of adipose tissue and lipotoxicity in the pathogenesis of type 2 diabetes. Curr Diab Rep. 2010;10(4):306–15.

Virtanen

Lidell

Orava

Heglind

Westergren

Niemi

Taittonen

Laine

Savisto

Enerback

Nuutila

. Functional brown adipose tissue in healthy adults. N Engl J Med. 2009;360(15):1518–25.

Cypess

Lehman

Williams

Tal

Rodman

Goldfine

Kuo

Palmer

Tseng

Doria

Kolodny

, et al. Identification and importance of brown adipose tissue in adult humans. N Engl J Med. 2009;360(15):1509–17.

10.

Chechi

Carpentier

Richard

. Understanding the brown adipocyte as a contributor to energy homeostasis. Trends Endocrinol Metab. 2013;24(8):408–20.

11.

Cannon

Nedergaard

. Brown adipose tissue: function and physiological significance. Physiol Rev. 2004;84(1):277–359.

12.

Bostrom

Sparks

Choi

Giang

Khandekar

Virtanen

Nuutila

Schaart

Huang

, et al. Beige adipocytes are a distinct type of thermogenic fat cell in mouse and human. Cell. 2012;150(2):366–76.

13.

Pilkington

Paz

Wankhade

. Beige adipose tissue identification and marker specificity-overview. Front Endocrinol (Lausanne). 2021;12:599134.

14.

Chung

Chatzigeorgiou

Economopoulou

Garcia-Martin

Alexaki

Mitroulis

Nati

Gebler

Ziemssen

Goelz

Phieler

, et al. A self-sustained loop of inflammation-driven inhibition of beige adipogenesis in obesity. Nat Immunol. 2017;18(6):654–64.

15.

Carey

Vorlander

Reddy-Luthmoodoo

Natoli

Formosa

Bertovic

Anderson

Duffy

Kingwell

. Reduced UCP-1 content in in vitro differentiated beige/brite adipocytes derived from preadipocytes of human subcutaneous white adipose tissues in obesity. PLoS ONE. 2014;9(3):e91997.

16.

Stanford

Middelbeek

Townsend

Nygaard

Hitchcox

Markan

Nakano

Hirshman

Tseng

Goodyear

. Brown adipose tissue regulates glucose homeostasis and insulin sensitivity. J Clin Invest. 2013;123(1):215–23.

17.

Peirce

Vidal-Puig

. Regulation of glucose homoeostasis by brown adipose tissue. Lancet Diabetes Endocrinol. 2013;1(4):353–60.

18.

Horrobin

. Modern biomedical research: an internally self-consistent universe with little contact with medical reality. Nat Rev Drug Discov. 2003;2(2):151–54.

19.

Chusyd

Wang

Huffman

Nagy

. Relationships between rodent white adipose fat pads and human white adipose fat depots. Front Nutr. 2016;3:10.

20.

Chandrasekera

Pippin

. Of rodents and men: species-specific glucose regulation and type 2 diabetes research. ALTEX. 2014;31(2):157–76.

21.

Riis-Vestergaard

Richelsen

Bruun

Hansen

Pedersen

. Beta-1 and not beta-3 adrenergic receptors may be the primary regulator of human brown adipocyte metabolism. J Clin Endocrinol Metab. 2020;105(4):dgz298.

22.

Samuelson

Vidal-Puig

. Studying brown adipose tissue in a human in vitro context. Front Endocrinol (Lausanne). 2020;11:629.

23.

Zilberfarb

Piétri-Rouxel

Jockers

Krief

Delouis

Issad

Strosberg

. Human immortalized brown adipocytes express functional beta3-adrenoceptor coupled to lipolysis. J Cell Sci. 1997;110(pt 7):801–807.

24.

Markussen

Isidor

Breining

Andersen

Rasmussen

Petersen

Pedersen

Richelsen

Hansen

. Characterization of immortalized human brown and white pre-adipocyte cell models from a single donor. PLoS ONE. 2017;12(9):e0185624.

25.

Takahashi

Tanabe

Ohnuki

Narita

Ichisaka

Tomoda

Yamanaka

. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861–72.

26.

Rowe

Daley

. Induced pluripotent stem cells in disease modelling and drug discovery. Nat Rev Genet. 2019;20(7):377–88.

27.

Sharma

Sances

Workman

Svendsen

. Multi-lineage human iPSC-derived platforms for disease modeling and drug discovery. Cell Stem Cell. 2020;26(3):309–29.

28.

Fujikura

Nakao

Sone

Noguchi

Mori

Naito

Taura

Harada-Shiba

Kishimoto

Watanabe

Asaka

, et al. Induced pluripotent stem cells generated from diabetic patients with mitochondrial DNA A3243G mutation. Diabetologia. 2012;55(6):1689–98.

29.

Nakamura

Fujikura

Ito

Keidai

Inagaki

. Human RFX6 regulates endoderm patterning at the primitive gut tube stage. PNAS Nexus. 2024;3(1):pgae001.

30.

Cowan

. Minireview: genome editing of human pluripotent stem cells for modeling metabolic disease. Mol Endocrinol. 2016;30(6):575–86.

31.

Hockemeyer

Jaenisch

. Induced pluripotent stem cells meet genome editing. Cell Stem Cell. 2016;18(5):573–86.

32.

Ward

Kellis

. Interpreting noncoding genetic variation in complex traits and human disease. Nat Biotechnol. 2012;30(11):1095–106.

33.

Farbehi

Neavin

Cuomo

ASE

Studer

MacArthur

Powell

. Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases. Nat Genet. 2024;56(5):758–66.

34.

Tran

Kahn

. Transplantation of adipose tissue and stem cells: role in metabolism and disease. Nat Rev Endocrinol. 2010;6(4):195–213.

35.

Xiong

Xie

Zhang

Thompson

Yang

Chen

. Derivation of adipocytes from human embryonic stem cells. Stem Cells Dev. 2005;14(6):671–75.

36.

van Harmelen

Aström

Strömberg

Sjölin

Dicker

Hovatta

Rydén

. Differential lipolytic regulation in human embryonic stem cell-derived adipocytes. Obesity (Silver Spring). 2007;15(4):846–52.

37.

Taura

Noguchi

Sone

Hosoda

Mori

Okada

Takahashi

Homma

Oyamada

Inuzuka

Sonoyama

, et al. Adipogenic differentiation of human induced pluripotent stem cells: comparison with that of human embryonic stem cells. FEBS Lett. 2009;583(6):1029–33.

38.

Ahfeldt

Schinzel

Lee

Hendrickson

Kaplan

Lum

Camahort

Xia

Shay

Rhee

Clish

, et al. Programming human pluripotent stem cells into white and brown adipocytes. Nat Cell Biol. 2012;14(2):209–19.

39.

Vodyanik

Zhang

Tian

Stewart

Thomson

Slukvin II . A mesoderm-derived precursor for mesenchymal stem and endothelial cells. Cell Stem Cell. 2010;7(6):718–29.

40.

Dupuis

Oltra

. Methods to produce induced pluripotent stem cell-derived mesenchymal stem cells: mesenchymal stem cells from induced pluripotent stem cells. World J Stem Cells. 2021;13(8):1094–111.

41.

Hafner

Dani

. Human induced pluripotent stem cells: a new source for brown and white adipocytes. World J Stem Cells. 2014;6(4):467–72.

42.

Chen

Pelekanos

Ellis

Horne

Wolvetang

Fisk

. Small molecule mesengenic induction of human induced pluripotent stem cells to generate mesenchymal stem/stromal cells. Stem Cells Transl Med. 2012;1(2):83–95.

43.

Hynes

Menicanin

Mrozik

Gronthos

Bartold

. Generation of functional mesenchymal stem cells from different induced pluripotent stem cell lines. Stem Cells Dev. 2014;23(10):1084–96.

44.

Rodríguez Ruiz

Dicks

Tuerlings

Schepers

van Pel

Nelissen

Freund

Mummery

Orlova

Guilak

Meulenbelt

, et al. Cartilage from human-induced pluripotent stem cells: comparison with neo-cartilage from chondrocytes and bone marrow mesenchymal stromal cells. Cell Tissue Res. 2021;386(2):309–20.

45.

Kishida

Ejima

Yamamoto

Tanaka

Yamamoto

Mazda

. Reprogrammed functional brown adipocytes ameliorate insulin resistance and dyslipidemia in diet-induced obesity and type 2 diabetes. Stem Cell Reports. 2015;5(4):569–81.

46.

Nishio

Yoneshiro

Nakahara

Suzuki

Saeki

Hasegawa

Kawai

Akutsu

Umezawa

Yasuda

Tobe

, et al. Production of functional classical brown adipocytes from human pluripotent stem cells using specific hemopoietin cocktail without gene transfer. Cell Metab. 2012;16(3):394–406.

47.

Oka

Kobayashi

Matsumura

Nishio

Saeki

. Exogenous cytokine-free differentiation of human pluripotent stem cells into classical brown adipocytes. Cells. 2019;8(4):373.

48.

Mohsen-Kanson

Hafner

Wdziekonski

Takashima

Villageois

Carrière

Svensson

Bagnis

Chignon-Sicard

Svensson

Casteilla

, et al. Differentiation of human induced pluripotent stem cells into brown and white adipocytes: role of Pax3. Stem Cells. 2014;32(6):1459–67.

49.

Hafner

Contet

Ravaud

Yao

Villageois

Suknuntha

Annab

Peraldi

Binetruy

Slukvin II Ladoux

, et al. Brown-like adipose progenitors derived from human induced pluripotent stem cells: identification of critical pathways governing their adipogenic capacity. Sci Rep. 2016;6:32490.

50.

Guénantin

Briand

Capel

Dumont

Morichon

Provost

Stillitano

Jeziorowska

Siffroi

Hajjar

Fève

, et al. Functional human beige adipocytes from induced pluripotent stem cells. Diabetes. 2017;66(6):1470–78.

51.

Sebo

Rodeheffer

. Assembling the adipose organ: adipocyte lineage segregation and adipogenesis in vivo. Development. 2019;146(7):dev172098.

52.

Sebo

Jeffery

Holtrup

Rodeheffer

. A mesodermal fate map for adipose tissue. Development. 2018;145(17):dev166801.

53.

Sanchez-Gurmaches

Hsiao

Guertin

. Highly selective in vivo labeling of subcutaneous white adipocyte precursors with Prx1-Cre. Stem Cell Reports. 2015;4(4):541–50.

54.

Chau

Bandiera

Serrels

Martínez-Estrada

Qing

Lee

Slight

Thornburn

Berry

McHaffie

Stimson

, et al. Visceral and subcutaneous fat have different origins and evidence supports a mesothelial source. Nat Cell Biol. 2014;16(4):367–75.

55.

Atit

Sgaier

Mohamed

Taketo

Dufort

Joyner

Niswander

Conlon

. Beta-catenin activation is necessary and sufficient to specify the dorsal dermal fate in the mouse. Dev Biol. 2006;296(1):164–76.

56.

Long

Svensson

Tsai

Zeng

Roh

Kong

Rao

Lou

Lokurkar

Baur

Castellot

Jr , et al. A smooth muscle-like origin for beige adipocytes. Cell Metab. 2014;19(5):810–20.

57.

Wang

Seale

. Control of brown and beige fat development. Nat Rev Mol Cell Biol. 2016;17(11):691–702.

58.

Guntur

Nguyen

Fakory

Doucette

Leech

Lotana

Kelley

Kohli

Martino

Sims-Lucas

, et al. A renewable source of human beige adipocytes for development of therapies to treat metabolic syndrome. Cell Rep. 2018;25(11):3215–28.e9.

59.

Zhang

Avery

Yin

Singh

Cliff

Yin

Dalton

. Generation of functional brown adipocytes from human pluripotent stem cells via progression through a paraxial mesoderm state. Cell Stem Cell. 2020;27(5):784–97.e11.

60.

Rao

Djeffal

Chal

Marchiano

Wang

Al Tanoury

Gapon

Mayeuf-Louchart

Glass

Sefton

Habermann

, et al. Reconstructing human brown fat developmental trajectory in vitro. Dev Cell. 2023;58(21):2359–75.e8.

61.

Rogal

Binder

Kromidas

Roosz

Probst

Schneider

Schenke-Layland

Loskill

. WAT-on-a-chip integrating human mature white adipocytes for mechanistic research and pharmaceutical applications. Sci Rep. 2020;10(1):6666.

62.

Compera

Atwell

Wirth

von Torne

Hauck

Meier

. Adipose microtissue-on-chip: a 3D cell culture platform for differentiation, stimulation, and proteomic analysis of human adipocytes. Lab Chip. 2022;22(17):3172–86.

63.

Tavakol

Fleischer

Vunjak-Novakovic

. Harnessing organs-on-a-chip to model tissue regeneration. Cell Stem Cell. 2021;28(6):993–1015.

64.

Yao

Dani

. A simple method for generating, clearing, and imaging pre-vascularized 3D adipospheres derived from human iPS cells. Methods Mol Biol. 2022;2454:495–507.

65.

Zushin

Chang

Lee

Alba

Koliwad

Stahl

. Probing insulin sensitivity with metabolically competent human stem cell-derived white adipose tissue microphysiological systems. Small. 2022;18(3):e2103157.

66.

Matsuo

Pereira

Lee

Zhong

Zushin

Gröger

Sharma

Willenbring

Hsiao

, et al. Human iPSC-derived proinflammatory macrophages cause insulin resistance in an isogenic white adipose tissue microphysiological system. Small. 2023;19(34):e2203725.

67.

Groeger

Sharma

Goswami

Chen

Zhong

Ram

Healy

Hsiao

Willenbring

Stahl

. Adipocyte inflammation is the primary driver of hepatic insulin resistance in a human iPSC-based microphysiological system. Nat Commun. 2024;15(1):7991.

68.

Fox

Massaro

Hoffmann

Pou

Maurovich-Horvat

Liu

Vasan

Murabito

Meigs

Cupples

D’Agostino

Sr , et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007;116(1):39–48.

69.

Tchkonia

Thomou

Zhu

Karagiannides

Pothoulakis

Jensen

Kirkland

. Mechanisms and metabolic implications of regional differences among fat depots. Cell Metab. 2013;17(5):644–56.

70.

Schwalie

Dong

Zachara

Russeil

Alpern

Akchiche

Caprara

Sun

Schlaudraff

Soldati

Wolfrum

, et al. A stromal cell population that inhibits adipogenesis in mammalian fat depots. Nature. 2018;559(7712):103–108.

71.

Lecoutre

Rebière

Maqdasy

Lambert

Dussaud

Abatan

Dugail

Gautier

Clément

Marcelin

. Enhancing adipose tissue plasticity: progenitor cell roles in metabolic health. Nat Rev Endocrinol. 2025;21(5):272–88.

72.

Ferrero

Rainer

Deplancke

. Toward a consensus view of mammalian adipocyte stem and progenitor cell heterogeneity. Trends Cell Biol. 2020;30(12):937–50.

73.

Emont

Jacobs

Essene

Pant

Tenen

Colleluori

Di Vincenzo

Jorgensen

Dashti

Stefek

McGonagle

, et al. A single-cell atlas of human and mouse white adipose tissue. Nature. 2022;603(7903):926–33.

74.

Santoro

McGraw

Kahn

. Insulin action in adipocytes, adipose remodeling, and systemic effects. Cell Metab. 2021;33(4):748–57.

75.

Haffner

. Pre-diabetes, insulin resistance, inflammation and CVD risk. Diabetes Res Clin Pract. 2003;61(Suppl 1):S9–18.

76.

Poulos

Dodson

Hausman

. Cell line models for differentiation: preadipocytes and adipocytes. Exp Biol Med (Maywood). 2010;235(10):1185–93.

77.

Friesen

Khalil

Barrasa

Jeppesen

Mooney

Jaenisch

. Development of a physiological insulin resistance model in human stem cell-derived adipocytes. Sci Adv. 2022;8(24):eabn7298.

78.

Garg

. Clinical review#: lipodystrophies: genetic and acquired body fat disorders. J Clin Endocrinol Metab. 2011;96(11):3313–25.

79.

Semple

Savage

Cochran

Gorden

O’Rahilly

. Genetic syndromes of severe insulin resistance. Endocr Rev. 2011;32(4):498–514.

80.

Le Lay

Magré

Prieur

. Not enough fat: mouse models of inherited lipodystrophy. Front Endocrinol (Lausanne). 2022;13:785819.

81.

Mori

Fujikura

Noguchi

Nakao

Matsubara

Sone

Taura

Kusakabe

Ebihara

Tanaka

Hosoda

, et al. Impaired adipogenic capacity in induced pluripotent stem cells from lipodystrophic patients with BSCL2 mutations. Metabolism. 2016;65(4):543–56.

82.

Friesen

Cowan

. FPLD2 LMNA mutation R482W dysregulates iPSC-derived adipocyte function and lipid metabolism. Biochem Biophys Res Commun. 2018;495(1):254–60.

83.

Ding

Lee

Schaefer

Peters

Veres

Kim

Kuperwasser

Motola

Meissner

Hendriks

Trevisan

, et al. A TALEN genome-editing system for generating human stem cell-based disease models. Cell Stem Cell. 2013;12(2):238–51.

84.

Ran

Hsu

Wright

Agarwala

Scott

Zhang

. Genome engineering using the CRISPR-Cas9 system. Nat Protoc. 2013;8(11):2281–308.

85.

Komor

Badran

Liu

. CRISPR-based technologies for the manipulation of eukaryotic genomes. Cell. 2017;168(1–2):20–36.

86.

Anzalone

Randolph

Davis

Sousa

Koblan

Levy

Chen

Wilson

Newby

Raguram

Liu

. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature. 2019;576(7785):149–57.

87.

Vojta

Dobrinic

Tadic

Bockor

Korac

Julg

Klasic

Zoldos

. Repurposing the CRISPR-Cas9 system for targeted DNA methylation. Nucleic Acids Res. 2016;44(12):5615–28.

88.

Mahajan

Spracklen

Zhang

MCY

Petty

Kitajima

Rüeger

Speidel

Kim

Horikoshi

, et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet. 2022;54(5):560–72.

89.

Suzuki

Hatzikotoulas

Southam

Taylor

Yin

Lorenz

Mandla

Huerta-Chagoya

Melloni

GEM

Kanoni

Rayner

, et al. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024;627(8003):347–57.

90.

Fraszczyk

Spijkerman

AMW

Zhang

Brandmaier

Day

Zhou

Wackers

Dollé

MET

Bloks

Gào

Gieger

, et al. Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts. Diabetologia. 2022;65(5):763–76.

91.

Wahl

Drong

Lehne

Loh

Scott

Kunze

Tsai

Ried

Zhang

Yang

Tan

, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature. 2017;541(7635):81–86.

92.

Gustafson

Nerstedt

Smith

. Reduced subcutaneous adipogenesis in human hypertrophic obesity is linked to senescent precursor cells. Nat Commun. 2019;10(1):2757.

93.

Gustafson

Nerstedt

Spinelli

Beguinot

Smith

. Type 2 diabetes, independent of obesity and age, is characterized by senescent and dysfunctional mature human adipose cells. Diabetes. 2022;71(11):2372–83.

94.

Hagberg

Silva Cascales

Lang

Hyvönen

Salehzadeh

Chen

Alexandersson

Terezaki

Harms

Kutschke

, et al. Obesity and hyperinsulinemia drive adipocytes to activate a cell cycle program and senesce. Nat Med. 2021;27(11):1941–53.

95.

Schosserer

Grillari

Wolfrum

Scheideler

. Age-induced changes in white, brite, and brown adipose depots: a mini-review. Gerontology. 2018;64(3):229–36.

96.

Spinelli

Baboota

Gogg

Beguinot

Bluher

Nerstedt

Smith

. Increased cell senescence in human metabolic disorders. J Clin Invest. 2023;133(12):e169922.

97.

Goh

Chen

Rocha

Semple

. Human pluripotent stem cell-based models suggest preadipocyte senescence as a possible cause of metabolic complications of Werner and Bloom Syndromes. Sci Rep. 2020;10(1):7490.

98.

Vergoni

Cornejo

Gilleron

Djedaini

Ceppo

Jacquel

Bouget

Ginet

Gonzalez

Maillet

Dhennin

, et al. DNA damage and the activation of the p53 pathway mediate alterations in metabolic and secretory functions of adipocytes. Diabetes. 2016;65(10):3062–74.

99.

Ishaq

Tchkonia

Kirkland

Siervo

Saretzki

. Palmitate induces DNA damage and senescence in human adipocytes in vitro that can be alleviated by oleic acid but not inorganic nitrate. Exp Gerontol. 2022;163:111798.

100.

de Luzy

Lee

Mobley

Studer

. Lessons from inducible pluripotent stem cell models on neuronal senescence in aging and neurodegeneration. Nat Aging. 2024;4(3):309–18.

101.

Vera

Bosco

Studer

. Generating late-onset human iPSC-based disease models by inducing neuronal age-related phenotypes through telomerase manipulation. Cell Rep. 2016;17(4):1184–92.

102.

Miller

Ganat

Kishinevsky

Bowman

Liu

Mandal

Vera

Shim

Kriks

Taldone

, et al. Human iPSC-based modeling of late-onset disease via progerin-induced aging. Cell Stem Cell. 2013;13(6):691–705.

103.

Shaker

Aguado

Chaggar

Wolvetang

. Klotho inhibits neuronal senescence in human brain organoids. NPJ Aging Mech Dis. 2021;7(1):18.

104.

Yang

Ding

Jiang

Sun

. Establishment and adipocyte differentiation of polycystic ovary syndrome-derived induced pluripotent stem cells. Cell Prolif. 2016;49(3):352–61.

105.

Elsayed

Vimalraj

Nandakumar

Abdelalim

. Insulin resistance in diabetes: the promise of using induced pluripotent stem cell technology. World J Stem Cells. 2021;13(3):221–35.

106.

Iovino

Burkart

Kriauciunas

Warren

Hughes

Molla

Lee

Patti

Kahn

. Genetic insulin resistance is a potent regulator of gene expression and proliferation in human iPS cells. Diabetes. 2014;63(12):4130–42.

107.

Balhara

Burkart

Topcu

Lee

Cowan

Kahn

Patti

. Severe insulin resistance alters metabolism in mesenchymal progenitor cells. Endocrinology. 2015;156(6):2039–48.

108.

Iovino

Burkart

Warren

Patti

Kahn

. Myotubes derived from human-induced pluripotent stem cells mirror in vivo insulin resistance. Proc Natl Acad Sci U S A. 2016;113(7):1889–94.

109.

Batista

Jayavelu

Wewer Albrechtsen

Iovino

Lebastchi

Pan

Dreyfuss

Krook

Zierath

Mann

Kahn

. A cell-autonomous signature of dysregulated protein phosphorylation underlies muscle insulin resistance in type 2 diabetes. Cell Metab. 2020;32(5):844–59.e5.

110.

Haider

Kahn

. Interactions among insulin resistance, epigenetics, and donor sex in gene expression regulation of iPSC-derived myoblasts. J Clin Invest. 2024;134(2):e172333.

111.

Haider

Lebastchi

Jayavelu

Batista

Pan

Dreyfuss

Carcamo-Orive

Knowles

Mann

Kahn

. Signaling defects associated with insulin resistance in nondiabetic and diabetic individuals and modification by sex. J Clin Invest. 2021;131(21):e151818.

112.

Kodama

Tojjar

Yamada

Toda

Patel

Butte

. Ethnic differences in the relationship between insulin sensitivity and insulin response: a systematic review and meta-analysis. Diabetes Care. 2013;36(6):1789–96.

113.

Umans

Battle

Gilad

. Where are the disease-associated eQTLs. Trends Genet. 2021;37(2):109–24.

114.

Tak

Farnham

. Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome. Epigenetics Chromatin. 2015;8:57.

115.

Neavin

Nguyen

Daniszewski

Liang

Chiu

Wee

Senabouth

Lukowski

Crombie

Lidgerwood

Hernandez

, et al. Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells. Genome Biol. 2021;22(1):76.

116.

Yazar

Alquicira-Hernandez

Wing

Senabouth

Gordon

Andersen

Rowson

Taylor

TRP

Clarke

Maccora

, et al. Single-cell eQTL mapping identifies cell type-specific genetic control of autoimmune disease. Science. 2022;376(6589):eabf3041.

117.

Warren

O’Sullivan

Friesen

Becker

Zhang

Liu

Wakabayashi

Morningstar

Shi

Choi

Xia

, et al. Induced pluripotent stem cell differentiation enables functional validation of GWAS variants in metabolic disease. Cell Stem Cell. 2017;20(4):547–57.e7.

118.

Bock

Kiskinis

Verstappen

Boulting

Smith

Ziller

Croft

Amoroso

Oakley

Gnirke

, et al. Reference maps of human ES and iPS cell variation enable high-throughput characterization of pluripotent cell lines. Cell. 2011;144(3):439–52.

119.

Kilpinen

Goncalves

Leha

Afzal

Alasoo

Ashford

Bala

Bensaddek

Casale

Culley

Danecek

, et al. Common genetic variation drives molecular heterogeneity in human iPSCs. Nature. 2017;546(7658):370–75.

120.

Schwartzentruber

Foskolou

Kilpinen

Rodrigues

Alasoo

Knights

Patel

Goncalves

Ferreira

Benn

Wilbrey

, et al. Molecular and functional variation in iPSC-derived sensory neurons. Nat Genet. 2018;50(1):54–61.

121.

Gavrilova

Marcus-Samuels

Graham

Kim

Shulman

Castle

Vinson

Eckhaus

Reitman

. Surgical implantation of adipose tissue reverses diabetes in lipoatrophic mice. J Clin Invest. 2000;105(3):271–78.

122.

Claro

Jr Figueiredo

Zampar

Pinto-Neto

. Applicability and safety of autologous fat for reconstruction of the breast. Br J Surg. 2012;99(6):768–80.

123.

Noguchi

Hosoda

Nakane

Mori

Nakao

Taura

Yamamoto

Kusakabe

Sone

Sakurai

Fujikura

, et al. In vitro characterization and engraftment of adipocytes derived from human induced pluripotent stem cells and embryonic stem cells. Stem Cells Dev. 2013;22(21):2895–905.

124.

Tran

Yamamoto

Gesta

Kahn

. Beneficial effects of subcutaneous fat transplantation on metabolism. Cell Metab. 2008;7(5):410–20.

125.

Pirtskhalava

Farr

Weigand

Palmer

Weivoda

Inman

Ogrodnik

Hachfeld

Fraser

Onken

, et al. Senolytics improve physical function and increase lifespan in old age. Nat Med. 2018;24(8):1246–56.

126.

Berry

Jiang

Arpke

Uchida

Reading

Berglund

Kyba

Graff

. Cellular aging contributes to failure of cold-induced beige adipocyte formation in old mice and humans. Cell Metab. 2017;25(1):166–81.

127.

Kontani

Wang

Kimura

Inokuma

Saito

Suzuki-Miura

Wang

Sato

Mori

Yamashita

. UCP1 deficiency increases susceptibility to diet-induced obesity with age. Aging Cell. 2005;4(3):147–55.

128.

Chondronikola

Volpi

Borsheim

Porter

Annamalai

Enerback

Lidell

Saraf

Labbe

Hurren

Yfanti

, et al. Brown adipose tissue improves whole-body glucose homeostasis and insulin sensitivity in humans. Diabetes. 2014;63(12):4089–99.

129.

Liu

Zheng

Zhu

Meng

Shen

Chi

Wang

Zhang

, et al. Brown adipose tissue transplantation improves whole-body energy metabolism. Cell Res. 2013;23(6):851–54.

130.

Huang

Liu

Ting

Chiu

Cheng

Nicholson

Hsieh

PCH

. Human iPSC banking: barriers and opportunities. J Biomed Sci. 2019;26(1):87.

131.

Fujikura

Anazawa

Toyoda

Ito

Kimura

Yabe

. Toward a cure for diabetes: iPSC and ESC-derived islet cell transplantation trials. J Diabetes Investig. 2025;16(3):384–88.

132.

Yoshida

Kato

Sato

Umekage

Ichisaka

Tsukahara

Takasu

Yamanaka

. A clinical-grade HLA haplobank of human induced pluripotent stem cells matching approximately 40% of the Japanese population. Med. 2023;4(1):51–66.e10.

133.

White

Olroyd

DeJesus

Dominguez

Dowdle

Friera

Young

Wells

Chu

Ito

, et al. Hypoimmune induced pluripotent stem cells survive long term in fully immunocompetent, allogeneic rhesus macaques. Nat Biotechnol. 2024;42(3):413–23.

134.

Kirkeby

Main

Carpenter

. Pluripotent stem-cell-derived therapies in clinical trial: a 2025 update. Cell Stem Cell. 2025;32(1):10–37.

135.

Han

Yang

Meng

Chen

Zhang

. Distinctive clinical and pathologic features of immature teratomas arising from induced pluripotent stem cell-derived beta cell injection in a diabetes patient. Stem Cells Dev. 2022;31(5–6):97–101.

136.

Spalding

Arner

Westermark

Bernard

Buchholz

Bergmann

Blomqvist

Hoffstedt

Naslund

Britton

Concha

, et al. Dynamics of fat cell turnover in humans. Nature. 2008;453(7196):783–87.

137.

Xining

Sai

. The evolving function of vasculature and pro-angiogenic therapy in fat grafting. Cell Transplant. 2024;33:9636897241264976.

138.

Dewal

Yang

Baer

Vidal

Hernandez-Saavedra

Seculov

Ghosh

Noe

Togliatti

Hughes

DeBari

, et al. Transplantation of committed pre-adipocytes from brown adipose tissue improves whole-body glucose homeostasis. iScience. 2024;27(2):108927.

139.

Alkhouri

Gornicka

Berk

Thapaliya

Dixon

Kashyap

Schauer

Feldstein

. Adipocyte apoptosis, a link between obesity, insulin resistance, and hepatic steatosis. J Biol Chem. 2010;285(5):3428–38.

140.

Zhu

Spicer

Gavini

Goudjo-Ako

Novak

Shi

. Enhanced sympathetic activity in mice with brown adipose tissue transplantation (transBATation). Physiol Behav. 2014;125:21–29.

141.

Nakamura

Fujikura

Inagaki

. Advancements in transplantation therapy for diabetes: pancreas, islet and stem cell. J Diabetes Investig. 2021;12(2):143–45.

142.

Wei

Yan

Shah

Zhang

Wang

Liu

Xue

Cao

Hou

Zhang

Yan

, et al. Advancements and challenges in stem cell transplantation for regenerative medicine. Heliyon. 2024;10(16):e35836.

Application of human iPSC-derived white,beige,and brown adipocytes for metabolic disease modeling and transplantation therapy

Abstract

Keywords

Introduction

Pluripotent stem cell-derived white, beige, and brown adipocytes

White adipocyte differentiation methods

Brown and beige adipocyte differentiation methods

Three-dimensional organoid and microphysiological systems for adipocyte maturation

Applications and remaining challenges of differentiation methods

Metabolic disease modeling

Modeling physiological insulin sensitivity and resistance

Monogenic disease models

Lipodystrophy

Premature aging

Complex metabolic disease modeling

Population genetics approach

Transplantation

White adipocytes

Brown and beige adipocytes

Challenges and prospects for human transplantation

Conclusion

Footnotes

ORCID iDs

Ethical considerations

Author contributions

Funding

Declaration of conflicting interests

Statement of human and animal rights

Statement of informed consent

Data availability statement

References