Compound heterozygous PROC mutations cause lipedema in humans

Compound heterozygous PROC mutations cause lipedema in humans | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Compound heterozygous PROC mutations cause lipedema in humans Jiqiu Wang, Ruikai Yang, Mengshan Ni, Weiqiong Gu, Bin Gu, Juan Zhang, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5876962/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Lipedema is a hereditary disorder characterized by excessive accumulation of subcutaneous adipose tissue in the limbs. The genetic causes and mechanisms underlying abnormal adipocyte expansion in lipedema, however, remain unknown. Here, we identify compound heterozygous mutations in the PROC gene in three lipedema patients from two unrelated consanguineous families. In vitro studies demonstrate the wild-type Protein C (PC), encoded by PROC , plays an inhibitory role in adipogenesis; conversely, the identified PC mutants, p.R271Q and p.R272H, fail to inhibit this process. In mice, the receptor of PC (PROCR) marks adipocyte progenitors, and conditional deletion of PROCR in these cells leads to an increased number of newborn adipocytes within white adipose tissue (WAT). Transcriptomic analysis alongside chemical blockage tests identifies HIF-1α as a primary downstream transcription factor mediating PC–PROCR signaling in adipogenesis. Furthermore, adipose biopsy samples from the patients’ thighs exhibit hyperplastic expansion of adipocytes, while single-nucleus RNA sequencing confirms increased adipogenic capacity and down-regulated HIF-1α activity in affected subjects. These findings establish PROC as the first causal gene for human lipedema and unveil a previously unexpected role of the PC–PROCR axis in orchestrating adipogenesis. Biological sciences/Developmental biology/Stem cells Health sciences/Diseases/Metabolic disorders Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Lipedema was first identified by Allen and Hines at the Mayo Clinic in 1940 1 , and its cause remains unknown but is believed to involve genetics and hormonal factors 2 . Lipedema is characterized by the abnormal accumulation of subcutaneous adipose tissue (SAT) in the limbs, often observed in Caucasian descents 3 . Patients with lipedema typically exhibit a disproportionate figure with symmetrically enlarged lower bodies, particularly affecting both legs and then extending up to the hips and buttocks 1 . This condition usually manifests at puberty and progresses gradually over time. It has been shown that the enlarged lower limbs in lipedema patients are owing to abnormally expanded adipose tissue, rather than edema or lymphedema. Adipose tissue could expand through hypertrophy (increase in adipocyte size) or hyperplasia (increase in adipocyte number) 4 . The latter refers to the process of enhanced adipogenesis, which involves the accelerated commitment of preadipocytes followed by the neogenesis of mature adipocytes. However, there is little evidence about whether adipocyte hypertrophy or hyperplasia occurs in lipedema. Notably, lipedema has been established as a genetic condition through classic familial studies (Online Mendelian Inheritance in Man [OMIM] number, 614103) 5 . Several groups have applied candidate gene sequencing or whole-exome sequencing (WES) to pedigrees or cases to explore pathogenic genes 6 – 9 . Unfortunately, the valid genetic factors and underlying mechanisms responsible for fat deposition in lipedema remain poorly understood. Mature adipocytes are considered to be developed from multipotent mesenchymal progenitor cells, which first commit into preadipocytes and then further differentiate into mature adipocytes. Mouse subcutaneous adipocyte progenitors have been identified as a population of Dpp4-expressing mesenchymal cells 10 . PROCR, also known as EPCR, has been established by our and other groups as a functional adult stem cell maker in many organs, including the mammary gland 11 , hematopoietic system 12 and pancreatic islets 13 . The role of PROCR in adipose progenitors is unclear. Protein C (PC), encoded by the PROC gene and acting as a plasma serine protease zymogen, is the solely known extracellular ligand of PROCR. PC is primarily expressed by liver cells and secreted into circulation to bind to PROCR in other tissues 14 . The currently established role of PC is for anticoagulation 15 . Once binding with PROCR on the endothelial surface, PC zymogen (inactive PC) is cleaved and converted into activated Protein C (aPC) by thrombin-thrombomodulin complex 16 . aPC exerts potent anticoagulation activity by inactivating coagulation factors Va and VIIIa 17 . The serum concentrations of PC are approximately 70 nM, whereas those of aPC are less than 40 pM 14 . In addition to its role in anticoagulation, we have demonstrated that aPC can trigger the activation of the Src-IGF1R axis in mammary gland stem cells when binding with PROCR 18 . Whether inactive PC also plays similar intracellular signaling roles remains unclear. It is also unknown whether PC or aPC contributes to adipogenesis. In this study, we aim to explore the causal factors of lipedema in patients from unrelated pedigrees. We filtered their genetic mutations by whole-genome sequencing (WGS) and identified that the PROC gene is the only candidate shared by these patients. We investigated the functional role of PC zymogen in adipocyte progenitors, unveiling a PC–PROCR–HIF-1α signaling axis in the regulation of adipogenesis. These findings first establish that PROC is a causal gene of lipedema. Methods Study participants The clinical features of the two probands were comprehensively evaluated and clinically diagnosed by two endocrine physicians. Subsequently, both patients and their family members were recruited for clinical information and sample collection. Blood samples from patients and unaffected family members were taken to extract genomic DNA. In addition to routine procedures of anthropometric measurements and laboratory biochemical tests, imaging examinations, including magnetic resonance imaging (MRI), were performed to evaluate fat accumulation, particularly in the lower body of the two probands. Thigh subcutaneous fat tissues were biopsied by surgeons from the patients as well as from age- and sex-matched healthy volunteers for histological examination with hematoxylin and eosin (H&E). To detect changes of cellular and molecular profiles, single-nucleus RNA sequencing (snRNA-seq) was performed to the samples from Patient 1 and the corresponding control. The study was approved by the Institutional Review Board of Ruijin Hospital, SJTUSM, and was conducted in accordance with the principles of the Helsinki Declaration II. Written informed consent was obtained from all participants. Whole genome sequencing and genetic analysis Three patients and all their unaffected family members from the two pedigrees underwent a detailed pedigree assessment to ascribe phenotypes to likely recessive, dominant, or de novo inheritance patterns. Following this assessment, whole-genome sequencing (WGS) was performed on the Illumina HiSeq2000 platform. Genomic DNA of ten participants (generations Ⅱ and Ⅲ) in total was extracted from blood cells according to the QIAamp DNA Mini Kit (Qiagen, 56304), randomly fragmented and then sequenced using 150 bp paired-end reads to achieve mean approximately 40× genomic coverage per library. Reads were aligned to GRCh37. Variants were called in accordance with the best practices of the Genome Analysis Toolkit (GATK) 40 , and ANNOVAR was used for annotation as described in previous studies 41 . WGS generated ~4.3 million single nucleotide variants (SNVs) per genome among all participants. To explore the potential pathogenic variant(s), the following filters were applied: 1) variants that are rare (minor allele frequency (MAF) ≤ 1% in the 1000 Genomes Project, Genome Aggregation Database (gnomAD), and Exome Sequencing Project (ESP6500)); 2) exonic and protein-altering variants; 3) variants predicted to be damaged by more than two algorithm methods among SIFT 21 , CADD 22 , Polyphen-2 23 , and MutationTaster 24 ; 4) variants that were homogeneous or compound heterozygous. All four identified candidate variants in the PROC gene were confirmed with Sanger sequencing. These likely causative variants were further determined according to American College of Medical Genetics and Genomics (ACMG) guidelines as pathogenic or likely pathogenic 25 . Protein sequence alignment was performed with the EMBL-EBI Clustal Omega online tool. The molecular structure of human PROC was retrieved from the Protein Data Bank (PDB) (code 6M3C) 42 , and graphics were generated using PyMOL software. Biopsy of human adipose tissues In brief, biopsy specimens of thigh subcutaneous adipose tissues (tSAT) were obtained from the upper one-third of the front thighs of the two patients (patient 1 and patient 3). Control tSAT samples from a similar thigh site were collected by surgeons from two sex- and age-matched, metabolic healthy female subjects. A part of the tSAT samples was immediately fixed in 10% neutral-buffered formalin, paraffin-embedded, and stained with H&E for histopathological examination. Adipocyte size and number were analyzed using AdipoCount software 43 . The remaining samples were flash-frozen immediately after collection and stored in liquid nitrogen until needed for genetic and molecular evaluation. Mice The Pdgfrα- Cre ERT2 (JAX number #018280), Rosa26-mTomato-stop-mGFP (JAX number #007576), and Procr flox/flox mice 18 were used in the study. The Procr flox/flox alleles were generated with two loxP sites flanking exon 2–4. To obtain the conditional deletion of Procr in adipose precursor cells, Pdgfrα- Cre ERT2 ; Procr flox/flox (cKO) and littermate Procr flox/flox (control) mice received intraperitoneal injections of tamoxifen (80 mg/kg) (Sigma-Aldrich, T5648) diluted in sunflower oil, and the timing points of injection are as illustrated in the corresponding figures. For in vitro experiments, adipose PDGFRα + precursors were sorted from cKO or control mice. For fate mapping of PDGFRα + cells with or without Procr -deletion, a single dose of tamoxifen (80 mg/kg) was administered intraperitoneally to 8-week-old cKO and control mice, and analyses were conducted 2 months later. Mice were housed in standard cages within a specific-pathogen-free (SPF) facility under a 12-h light/dark cycle at 22 ± 2 °C, with ad libitum access to food and water. All animal procedures were conducted in accordance with the guidelines for the care and use of laboratory animals and were approved by the Animal Care and Use Committee of Shanghai Institute of Biochemistry and Cell Biology (SIBCB), Chinese Academy of Sciences, with a project license number of IBCB0065. Preparation of primary adipose single-cell suspension and FACS analysis The inguinal subcutaneous fat pads were isolated from transgenic or wild-type mice, then minced and digested with 2 mg/mL collagenase type III (Worthington, LS004183) for 2 hours in a shaker at 100 rpm and 37 °C. The digested mixture was then centrifuged to separate the floating mature adipocyte fraction from the pelleted stromal vascular fraction (SVF). SVF cells were pelleted and treated with red blood cell lysis buffer (Sigma, R7757) for 5 minutes, followed by sequential incubation with 0.05% trypsin-EDTA (Gibico, 25300054) at 37 °C for 5 minutes and 0.1 mg/mL DNase I (Sigma, D4263) for 5 minutes. The single-cell suspension was then filtered through a 100-μm cell strainer. For cell labeling, the following antibodies were used: FITC-conjugated CD31 (BD, 553372), FITC-conjugated CD45 (BD, 553080), FITC-conjugated TER119 (BD, 557915), PE-conjugated CD140a (Invitrogen, 12-1401-81), Biotin-conjugated CD201 (Invitrogen, 13-2012-82), APC-conjugated CD55 (Biolegend, 131812), APC-conjugated CD54 (Biolegend, 116120), Rabbit anti-CD142 (Sino Biological, 50413-R001), and Streptavidin-V450 (BD, 560797). Antibody incubation was performed on ice for 25 minutes in PBS with 5% fetal bovine serum (FBS) (PAN, P30-3302). Before FACS sorting, cells were filtered through a 50-μm cell strainer, and then sorted using FACSJazz (Becton Dickinson). For PDGFRα + adipose precursor cells, live singlets from SVF cells were gated for the absence of Ter119, CD31 and CD45 (blood lineage, Lin - ), as well as EpCAM (epithelial cells), then for PDGFRα expression, representing adipose precursor cells. The same strategy was consistently applied throughout the study. The purity of the sorted population was routinely checked and ensured to be more than 95%. Adipocyte differentiation in vitro For adipogenic differentiation, SVF or precursor cells were seeded on 96-well or 384-well plates and allowed to attach for 24 to 48 hours until reaching the confluence. Adipogenic differentiation was carried out in DMEM/F12 medium containing 10% FBS with the addition of a full adipogenic cocktail: 5 μg/mL insulin (Eli Lilly), 1 μM dexamethasone (Sigma, D1756), and 0.5 mM 3-isobutyl-1-methylxanthine (IBMX) (Sigma, I7018). Cells were incubated in the full adipogenic cocktail for 2 days and then switched to an adipogenic maintenance medium containing 5 μg/mL insulin for 6 days. Medium changes were performed every 2 days. Recombinant Protein C was expressed in CHO-R1c cells and purified with Flag-tag as described previously 44 . Throughout the induction, cultures were treated with recombinant Protein C (20 μg/ml), active Protein C (Sigma-Aldrich, P2200), or the HIF-1α inhibitors TAT-cyclo-CLLFVY (5 mM) (MCE, HY-P1420-1) and IDF-11774 (5 mM) (Sigma, S8771). Adipogenesis was assessed at 8 days post-induction by staining lipid droplet accumulation with BODIPY 493/503 (Invitrogen, D3922). The stained cells were imaged using an inverted fluorescence microscope (Agilent BioTek Cytation 5) with green fluorescent protein (GFP) filters. Whole mount staining Whole mount staining was performed as described previously 45 , with minor modifications. In brief, inguinal subcutaneous fat pads of cKO and control tracing mice were dissected into small pieces, then processed in digestion buffer containing RPMI 1640 with 25 mM HEPES, 5% FBS, 1% penicillin–streptomycin (PS) (Thermo Fisher, 15140-122), and 300 U/ml collagenase III for 30 min at 37 °C, and then fixed in 4% paraformaldehyde (PFA). Tissues were washed three times with PBST (PBS, 0.1% Triton-X 100 (Sigma-Aldrich, T9284)) for 5 min and incubated overnight at 4 °C with primary antibody anti-chicken GFP (Invitrogen, A10262). Tissues were then washed and incubated overnight at 4 °C with secondary antibody anti-chicken Alexa 488 (Invitrogen, A78948) plus 4',6-diamidino-2-phenylindole (DAPI) (Thermo Fisher, D1306). On the following day, tissues were washed and incubated in 80% glycerol overnight before dissection for 3D imaging. Stained samples were imaged using a ZEISS LSM 710 confocal laser-scanning microscope and analyzed using ZEISS ZEN microscope software. For quantification, all GFP + cells were scored as adipocytes or stromal cells based on their distinct spherical morphology and attached nucleus. RNA extraction and quantitative real-time PCR analysis Total RNA from cultured cells was extracted following the manufacturer’s instructions. Samples were lysed in RNAiso plus (Takara, 9109). Extracted RNA was reverse transcribed into cDNA using the Primerscript RT master kit (Takara, RR036A). qPCR samples were prepared with SYBR Green Mixture (Roche, 04913914001) and detected using an Applied Biosystems StepOne Plus (Thermo Fisher, 4376600) platform. The comparative 2 -ΔΔCT method was used to evaluate the relative mRNA levels, with the housekeeping gene Gapdh serving as the internal control. All the qPCR primers are listed in Supplementary Table 3 . Bulk RNA sequencing and analysis Total RNA was extracted from cultured cells according to the manufacturer’s instructions. The concentration of total mRNA was determined with an bioanalyzer (Agilent 2100). RNA-seq libraries were prepared according to the manufacturer’s instructions and then sequenced on a DNBSEQ platform (BGI). Briefly, approximately 50 million reads were obtained for each sample, and these reads were uniquely mapped to the mm9 mouse genome, with a mapping rate > 75% for both samples. Genes with an FPKM > 1 in at least one sample across all samples were retained for further analysis. Differential gene expression analysis was performed, and genes with significant changes were extracted using DAVID Bioinformatics Resources 6.8. The differentially expressed genes (DEG) were then used to infer the regulatory network of transcription factors with the iRegulon plugin (http://iregulon.aertslab.org/). Gene-set enrichment analysis (GSEA) was conducted using GSEA software (v4.1.0), with the threshold of significant enrichment set based on the permutation test (the number of permutations = 1000, p-value < 0.05), applying default weighting statistics for each parameter. Enriched results from the GSEA analysis were visualized using the R packages ClusterProfler, ggplot2 and enrichplot. The presented GSEA terms are selected from MSigDB (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Western blotting Total protein from frozen adipose tissues or culture cells was extracted using RIPA lysis buffer (Biocolor bioscience, R20095) with a protease inhibitor cocktail (Thermo Fisher Scientific, 78442). Proteins were separated by SDS-PAGE and transferred to nitrocellulose membrane (GE company). Bolts were blocked with 3% BSA in TBST (50 mM Tris-HCl, 150 mM NaCl, 0.05% Tween-20, pH 7.5) for 1 hour and then incubated with primary antibodies at 4 ℃ overnight. This was followed by incubation with secondary IgG-HRP antibodies for 2 hours at room temperature. Protein bands were visualized with a chemiluminescent reagent and exposed to a Mini Chemiluminescent Imager (MiniChemi 610 Plus). The following primary antibodies were used: anti-HIF-1α (1:2000 dilution) (CST, 36169S) and HSP90 (1:1,000 dilution) (CST, 4877). HRP-linked ti-rabbit IgG (1:2000 dilution) (CST, 7074S) was used as the secondary antibody. Analysis of the public scRNA-seq dataset The scRNA-seq count matrices of human and mouse subcutaneous WAT SVF cells from Merrick et al 10 were downloaded from the Gene Expression Omnibus (GEO) repository (accession number: GSM3717979, GSM3717977). Cell types were annotated according to the previous publication 10 . The subset matrices were renormalized using Seurat v3 pipelines. Significant principal component (PC) dimensionalities were identified using the ElbowPlot method. 10 PCs were used for p12 pups, and 15 PCs were used for the human single-cell study. Dimensional reduction was performed with the Uniform Manifold Approximation and Projection (UMAP) method. Cell clustering was based on the shared-nearest neighbor (SNN) method, and the resolution was set to 0.6. Analysis of differential gene expression (DGE) among clusters was performed by using the Seurat function FindMarkers with the Wilcox test. Heatmaps and individual UMAP plots for the given genes were generated by using the Seurat toolkit DoHeatmap, and FeaturePlot functions, respectively. Single-nucleus RNA sequencing Nuclei were isolated from frozen human thigh fat samples for 10× single-nucleus RNA sequencing (snRNA-seq). The samples were kept frozen in liquid nitrogen before nuclei isolation, and all sample handling steps were performed on ice. The samples were homogenized in a Dounce homogenizer using lysis buffer with 1 mM DTT (solarbio, D8220) and 1 U/μl RNase inhibitor (Roche, 3335402001), followed by incubation on ice for 5 minutes. The suspension was then filtered through a 40 μm filter to remove debris and centrifuged at 4 °C, 500 g for 5 minutes. After resuspending the nuclei in 300 μl of lysis buffer and 300 μl of RB buffer in a 2 ml tube, the mixture was centrifuged using a density gradient to separate the nuclei from cell debris, and the intermediate layer was washed with RB buffer and collected. An aliquot of nuclei from each sample was stained with Trypan Blue, counted in an automatic cell counter to identify intact nuclei, and then immediately loaded onto the 10× Chromium controller following the manufacturer’s protocol (10× Genomics). For each sample, 10,000–16,500 nuclei were loaded in one channel of a Chromium Chip. Full-length cDNA synthesis, amplification, and subsequent library construction were performed using the Chromium Single-Cell 3′ GEM, Library & Gel Bead kit V3.1 (10× Genomics, 1000121). Complementary DNAs and their corresponding 10× libraries were evaluated and quantified using the Agilent 4200 Bioanalyzer system. Gene expression libraries were multiplexed and sequenced on the Illumina Novaseq6000 with a sequencing depth of at least 100,000 reads per cell, following a pair-end 150 bp strategy. Single-nucleus RNA-seq data analysis The Cell Ranger software pipeline (version 5.0.0) provided by 10× Genomics was used to demultiplex cellular barcodes, map reads to the GRCh38 genome assembly using the STAR aligner, and generate feature-barcode matrices for downstream analysis. The data was further processed and analyzed using the Seurat software (version 3.1.2). Cells were filtered out if they met any of the following criteria: fewer than 200 genes detected, a gene number ranking in the top 1%, or a mitochondrial gene ratio exceeding 25%. Dimensionality reduction was performed using principal component analysis (PCA), and visualization was achieved using t-Distributed Stochastic Neighbor Embedding (tSNE) and UMAP. Clusters were identified based on canonical marker genes. For GSEA analysis, genes that are differentially expressed in the progenitor population were utilized. The gene sets were selected from the MSigDB and included those that were upregulated or downregulated by HIF-1α. Enriched results from the GSEA analysis and visualization were visualized using the R packages ClusterProfler, ggplot2 and enrichplot. The p-value cutoff was set to 0.05. Pseudotime trajectory analysis The pseudotime trajectories were reconstructed using the R package Monocle 2 (version 2.9.0) as follows: first, the Seurat object was converted to the CellDataSet format using the importCDS function. Ordering genes were screened through the differentialGeneTest function with q value < 0.01. Dimensionality reduction was then performed with the reduceDimension algorithm. Finally, cell trajectory was inferred using the orderCells function, specifying the starting pseudotime state and direction 46 . Statistical analysis Data are presented as mean ± SEM. Statistical significance was determined using Student’s t-test or one-way ANOVA, followed by Tukey’s post hoc test, as appropriate. GraphPad Prism 10.2.0 (GraphPad Software) was used for generating figures and conducting statistical analyses. For snRNA-seq data analysis, differences among groups were assessed using the chi-squared test of independence with Bonferroni-adjusted P values. Details of the statistical tests used were provided in the figure legends. A two-tailed P -value of less than 0.05 was considered statistically significant. RESULTS Clinical characteristics of lipedema in two unrelated pedigrees The pedigrees of two unrelated Chinese families affected by lipedema are illustrated in Fig. 1 . Family 1 includes three affected members—two females and one male. Notably, the elder sister of the proband died at 52 years of age due to mesenteric venous thrombosis. Family 2 has one affected young female patient. All three patients (termed as Patients 1, 2, and 3) from the two families exhibited symmetrically enlarged lower extremities ( Fig. 1c-e ), whereas unaffected family members showed normal lower body shapes ( Fig. 1f, g; Table 1 ). The symptoms initially occurred proximal to the ankles and progressively extended upward to the lower and upper thighs, hips and buttocks, but sparing the feet, trunk and upper limbs. A possibility of edema or lymphedema was first excluded 19 . Transaxial and coronal magnetic resonance imaging (MRI) of Patients 1 and 3 confirmed the presence of excessive subcutaneous fat deposits without the accumulation of free fluid in the legs ( Fig. 1h, i ). These symptoms and signs manifested in all three patients during puberty and exacerbated over time (Table 1 ). It is noted that Patient 3 underwent cosmetic liposuction surgery on the lower legs at 25 years old in 2013; however, this procedure did not effectively halt the progress of the disease (MRI images collected 5 years post-surgery) ( Fig. 1e) . Given the familial clustering and inheritance pattern of these clinical features, the disorder appears to be a highly penetrant autosomal recessive trait. Table 1 Clinical characteristics of three patients with lipedema. Patient 1 Patient 2 Patient 3* Basic information Ethnic origin Han Chinese Han Chinese Han Chinese Sex Female Male Female Age at diagnosis (years) 48 43 30 Age at symptom onset (years) 15 12 14 Clinical phenotype Disproportionate fatdistribution on the limbs + + + Bilateral, symmetrical + + + Nonpitting edema + + + Limb pain and/or bruising + + + Increased sensitivity to touch or limb fatigue + + + Reduction of pain or discomfort with limb lift - - - Worsening of symptoms + + + Cuff sign + + + Stemmer sign - - - Type Ⅲ Ⅲ Ⅲ Stage 3 3 1 Anthropometric measurement BMI (kg m − 2 ) 27.7 32.4 21.2 WHR 0.73 0.98 0.76 Circumference of upper legs (cm) 75.3 (left) 77.5 (right) 78.6 (left) 73.5 (right) 62.5 (left) 62.5 (right) Circumference of lower legs (cm) 53.0 (left) 55.7 (right) 51.8 (left) 50.3 (right) 42.0 (left) 42.6 (right) * 5 years after liposuction surgery. Identification of the PROC mutations in lipedema patients To identify the underlying genetic factors, we performed WGS sequencing to both families, using DNA samples from three affected patients along with their unaffected parents and siblings. Based on the autosomal recessive inheritance pattern, we first prioritized homozygous or compound heterozygous rare variants in or around the coding regions after standard filtering procedures ( Fig. 2a ). As a result, we identified three and six candidate genes in the two families, respectively, in line with a Mendelian inheritance pattern of the autosomal recessive trait. No homozygous mutations were shared by the two families; strikingly, only one gene— PROC —showed compound heterozygous mutations in both families ( Fig. 2a ). Patients 1 and 2 from Family 1 harbored two missense mutations (p.R272H and p.G334S), while Patient 3 from Family 2 carried two other mutations (p.R271Q and p.D279H). These mutations were confirmed by Sanger sequencing, with the parents of these patients being heterozygous ( Fig. 2b, c ). Importantly, the compound heterozygous mutations co-segregated well with the lipedema phenotypes within both families, indicating PROC as a strong candidate gene for lipedema ( Supplementary Fig. 1a, b ). PROC encodes a secreted protein, Protein C (PC), which comprises four domains: the Gla (γ-carboxyglutamic acid) domain, two EGF (epidermal growth factor)-like domains, and a trypsin-like serine protease domain 20 . All four identified mutations are located within the trypsin-like serine protease domain and are highly conserved across various mammalian species ( Fig. 2d ). Notably, both the R271 and R272 residues map to the Ca 2+ -binding loop on the protease domain, while the D279 residue is located on a β-strand adjacent to the same loop ( Supplementary Fig. 1c) . The loss of charge (substitution of Arg-271 with Gln) and the reversal of charge (substitution of Asp-279 with His) may alter the conformational structure of this exposed surface loop, impacting its electrostatic interaction with the metal cation. Moreover, these mutations were either absent or exceedingly rare in published databases of general populations, and predicted to be damaging by multiple prediction algorithms 21 – 24 ( Supplementary Table 1 ). These findings meet the American College of Medical Genetics and Genomics (ACMG) criteria 25 , classifying the mutations as pathogenic or likely pathogenic ( Supplementary Table 1 ). Next, we investigated the potential role of PC on adipogenesis that may be associated with adipose accumulation in lipedema patients. We constructed the plasmids of wild-type (WT) or all mutant PC and successfully purified their secreted proteins ( Supplementary Fig. 1d ). We employed the in vitro adipocyte differentiation assay by using freshly isolated mouse stromal vascular fraction (SVF) cells 26 ( Fig. 2e ). Purified WT PC proteins were added into the differentiation medium during the first two days. Notably, we observed a dramatic inhibitory effect of WT PC on adipocyte differentiation, suggesting that PC suppresses adipogenesis ( Fig. 2f ). In contrast, when the mutant p.R271Q and p.R272H PC proteins were added, the inhibitory effects on adipogenesis were largely blunted. However, mutant p.D279H and p.G334S PC proteins did not show such strong functional damages ( Fig. 2f ). Collectively, our genetic and in vitro functional data support the notion that the loss-of-function PROC mutations probably lead to excessive adipogenesis in these lipedema patients. PC inhibits adipogenesis by targeting PROCR adipocyte progenitors To understand the potential pathogenic mechanism of PROC dysfunction in lipedema, we then investigated how PC inhibits adipocyte differentiation. The PROC gene is predominantly expressed in hepatocytes, with little evidence regarding its expression in WAT ( https://www.gtexportal.org/home/gene/PROC ). Therefore, we utilized published single-cell RNA sequencing (scRNA-seq) data of SVF cells isolated from human and mouse subcutaneous WAT 10 . Human adipose precursor cells, primarily expressing PDGFRα (a common mesenchymal cell marker), were divided into two subsets: early adipocyte progenitors and committed preadipocytes ( Fig. 3a ). Our analysis revealed that PROC expression was not detectable in any of these cell clusters. However, PROCR, the known receptor of PC, was abundantly expressed in early adipocyte progenitors, which are marked by CD55 and DPP4 expression ( Fig. 3a and Supplementary Fig. 2a ). Similar Procr expression patterns were observed in mouse inguinal WAT (iWAT) ( Fig. 3b and Supplementary Fig. 2b ), in line with a recent report 27 . Proc and Procr expression in SVF cells and adipocytes were further validated in mouse iWAT, in which Proc expression was not detected in either cell type, and Procr expression was highly enriched in SVF cells ( Supplementary Fig. 2c) . We confirmed PROCR protein expression in adipose precursor cells by fluorescence-activated cell sorting (FACS) analysis ( Supplementary Fig. 2d ). Adipose precursor cells feature negative expression of hematopoietic and endothelial cell markers (Ter119 − , CD45 − , and CD31 − , hereafter abbreviated “Lin − ”) and epithelial cell markers (EpCAM − ), and positive expression of mesenchymal cell markers (PDGFRα + ). We found that PROCR-expressing (PROCR + ) cells accounted for about 26.5 ± 3.0% of the Lin − EpCAM − PDGFRα + population ( Supplementary Fig. 2d ), constituting a notable subset of adipose precursor cells. To investigate the in vivo function of PC–PROCR axis in these precursors, we generated Pdgfrα CreERT/+ ; Procr flox/flox (cKO) mice 18 ( Fig. 3c ). Tamoxifen (TAM) was administered at 8-week-old mice to induce recombination, which thereby conditionally deleted Procr in Pdgfrα -expressing precursors. Seven days after TAM administration, the knockout efficiency was validated by FACS, demonstrating a significantly reduced percentage of Procr + (Lin − ; EpCAM − ; Procr + ) cells in cKO mice compared to control ( Procr flox/flox ) mice ( Fig. 3d ). Next, we isolated adipose precursor cells from the iWAT of both groups and performed in vitro adipocyte differentiation assays in the presence or absence of PC proteins. In the absence of PC, when compared to the controls, the precursors from the cKO group displayed enhanced ability of adipogenesis ( Fig. 3e ). Of note, in the presence of PC, the adipogenesis was consistently inhibited in the control group ( Fig. 2f and Fig. 2e ), and PC also suppressed the expression of adipocyte differentiation genes in these PDGFRα + cells ( Supplementary Fig. 2f ). Most importantly, deletion of Procr abolished the inhibitory effect of PC on adipocyte differentiation ( Fig. 3e, f and Supplementary Fig. 2f ). Together, these results indicate that PROCR is expressed in adipocyte progenitors and, importantly, an intact PC–PROCR axis is essential for suppressing adipocyte progenitors differentiation. To explore how disruption of the PC–PROCR axis impacts in vivo adipogenesis, we further introduced the Cre-dependent Rosa26-loxP-mtdTomato-loxP-mGFP fluorescent reporter allele ( R26 mTmG ) into our genetic models ( Fig. 3c ) and generated Pdgfrα creERT/+ ; R26 mTmG/+ (Ctrl;mTmG) and Pdgfrα CreERT/+ ; Procr flox/flox ; R26 mTmG/+ (cKO;mTmG) mice, for fate mapping of the progeny of PDGFRα + adipocyte precursor cells ( Fig. 3g ). In this experiment, a single dose of TAM (100 mg/kg) was administered to 8-week-old mice, and adipose tissues were collected at 2 months later ( Fig. 3g ). An effective deletion of Procr was validated in cKO;mTmG mice ( Supplementary Fig. 2g ). Meanwhile, abundant mGFP + offspring stromal cells and adipocytes were observed in both groups, indicating sufficient labeling efficiency ( Fig. 3h ). In the controls, 72.9% of the mGFP + cells in iWAT were PDGFRα + precursors cells, and only 27.0% of the cells were terminally differentiated mature adipocytes ( Fig. 3h ), consistent with previous studies 28 . In contrast, cKO;mTmG mice showed a dramatic decrease (20.4%) in precursor cells and a significant increase (79.6%) in mGFP + mature adipocytes ( Fig. 3h, i ). We further examined the various subpopulations of mGFP + precursor cells, i.e., CD55 + adipose progenitor cells as well as ICAM + and CD142 + preadipocyte populations 10 . We observed a significant decrease (from 45.2 ± 7.4% to 18.1 ± 1.3%) in CD55 + adipose progenitor cells, suggesting likely excessive differentiation originating from the adipose stem cell pool or excessive exhaustion upon Procr deletion ( Fig. 3j, k ). Intriguingly, the proportion of ICAM1 + preadipocytes significantly increased (from 56.0 ± 4.2% to 88.5 ± 0.7%) in cKO;mTmG mice, while CD142 + preadipocyte subsets remained unchanged compared to their controls ( Fig. 3j, k ). These results suggest that impaired PC–PROCR signaling may augment the differentiation of adipose progenitor cells into more committed ICAM1 + preadipocytes, which consequently contribute to mature adipocytes. Together, both in vitro and in vivo experiments demonstrate that PC–PROCR signaling inhibits adipogenesis. PC activates HIF-1α to inhibit adipogenesis Next, we investigated the molecular mechanisms by which PC–PROCR signaling suppresses adipogenesis. As mentioned before, there are two forms of PC in the blood circulation system, inactive (PC) and active (aPC) proteins, and the latter one has experienced thrombin cleavage 18 . Although PC can inhibit adipocyte differentiation, surprisingly, we found that aPC exerts no effects on the differentiation of adipose progenitor cells ( Fig. 4a-c ). Therefore, we performed transcriptomic analyses to identify factors that are altered specifically by PC treatment. PDGFRα + cells were pre-incubated with PBS control, PC, or aPC proteins for 24 hours, followed by RNA sequencing analysis. Upregulated differentially expressed genes (DEGs) in the PC group rather than the aPC group (|log2 fold change (FC)| ≥ 1, adjusted P < 0.05) were screened out to predict the regulated transcription factors using iRegulon analysis 29 ( Fig. 4d and Supplementary Table 2 ). After scoring transcriptional activity based on both the number of target genes and the strength of transcription factor binding, we identified a set of transcription factors that show upregulated transcriptional activity specifically in the PC group, with HIF-1α being the top prominent ( Fig. 4e ). Pathway enrichment analysis through Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) revealed that both PC and aPC proteins shared similar biological functions in regulating immune responses, consistent with previous studies 30 , for instance, IL-17 signaling activity, NOD-like receptor signaling pathway, and cytokine-cytokine receptor interaction ( Supplementary Fig. 3a, b ). Notably, we found that the HIF-1α signaling activity was specifically upregulated in the PC group but not in the aPC group ( Fig. 4f and Supplementary Fig. 3a, b ). Western blot analysis revealed the accumulation of total HIF-1α protein in the PC treatment group ( Fig. 4g, h ). Immunostaining results further validated that PC promoted nuclear HIF-1α localization ( Fig. 4i ), consistent with the enhanced transcription of its target genes ( Fig. 4e, f ). The potential PC–PROCR–HIF-1α axis was further validated in vivo using the cKO model. iWAT samples of both groups were harvested 7 days after TAM injection, and then PDGFRα + precursor cells were FACS isolated and subjected to Western analysis ( Fig. 4j) . We found that Procr -cKO cells indeed exhibit significantly lower HIF-1α protein levels compared to controls ( Fig. 4k, l ). Next, to determine whether HIF-1α mediates the effects of PC in restraining adipogenesis, we utilized two distinct HIF-1α inhibitors, IDF-11774 or TAT-cyclo-CLLFVY 31 , 32 . We found that both inhibitors can attenuate the inhibitory effects of PC on adipocyte differentiation of PDGFRα + precursor cells ( Fig. 4m, n ). Together, these results indicate that the anti-adipogenic effects of PC–PROCR signaling are, at least in part, mediated by the active HIF-1α. Adipose hyperplasia and downregulated HIF-1α signaling in lipedema Next, we investigated whether impaired adipogenesis and HIF-1α signaling occur in the adipose tissues of PROC -mutant lipedema patients. We conducted biopsies to the thigh subcutaneous adipose tissues (tSAT) of Patients 1 and 3 (Fig. 5a and Supplementary Fig. 4a, b) . Unexpectedly, despite excessive fat volume in patients ( Fig. 1h-i ), histological analysis of tSAT revealed that the distribution of adipocyte sizes in patients was comparable to that from equivalent anatomical sites of respective sex- and age-matched healthy volunteers ( Fig. 5b, c and Supplementary Fig. 4a, b ). This suggests an abnormal increase of adipocyte number (hyperplasia) rather than enlarged adipocyte size (hypertrophy) in lipedema. To gain more detailed insights into the pathogenic mechanisms, we performed single-nucleus RNA sequencing (snRNA-seq) on the tSAT samples from the patient and matched healthy volunteer. Integration of snRNA-seq data identified canonical cell types commonly found in human abdominal SAT 33 , including adipose progenitor cells, preadipocytes, adipocytes, vascular cells, and immune cells ( Fig. 5f and Supplementary Fig. 4c ). Notably, there was a significant decrease in the population of adipose progenitors ( CD55 + ) in parallel with an increase in the percentage of preadipocytes ( ICAM + ) and adipocytes ( ADIPOQ + ) in the PROC -mutant patient compared to the healthy control ( Fig. 5g ). These findings are consistent with the hyperplastic features of fat depot observed in morphological examinations ( Fig. 5b, c ) and align with the results observed in conditional Procr knockout mice ( Fig. 3g-k ). To investigate the adipogenesis progress in lipedema, we conducted a computational pseudotime trajectory analysis of adipose progenitor cells, preadipocytes, and adipocytes. The results clearly depicted the progression of adipocyte differentiation from the progenitors to mature adipocytes, with the progenitors located at the root and adipocytes at the end of the differentiation process ( Fig. 5h ). Importantly, cell cluster frequencies from the pseudotime trajectory analysis revealed a higher prevalence of progenitors transitioning into adipocytes in the patient ( Fig. 5i ). Furthermore, the expression levels of key adipogenic genes, such as PPARG , FABP4 ( aP2 ), and ADIPOQ ( Adiponectin ), were significantly increased in the patient, providing additional evidence of enhanced adipogenesis in lipedema patients ( Fig. 5j ). Finally, to investigate the molecular property of adipose progenitor cells harboring PROC mutations, we performed GSEA analysis and found that genes downregulated in response to both hypoxia and overexpression of HIF-1α 34 were enriched in the patient; conversely, genes upregulated in response to hypoxia mimetic compound 35 were enriched in the control group ( Fig. 5k ), suggesting the impaired HIF-1α signaling occurring in the patient with PROC mutations. This observation reinforces the findings that HIF-1α acts as a key downstream effector of PC–PROCR signaling in suppressing adipogenesis ( Fig. 4m, n , and Fig. 5i ). Discussion Lipedema is a hereditary disorder that is characterized by excessive subcutaneous adipose tissue deposition. In this study, we investigated genetic causes and underlying mechanisms leading to lipedema using pedigree genetics in combination with deep genome sequencing and biopsy tissue snRNA-seq, gene knockout and fate-tracing mouse models, and in vitro adipocyte differentiation. We found that compound heterozygous mutations in the PROC gene co-segregated with lipedema in two non-consanguineous Chinese families, demonstrating an autosomal dominant inheritance pattern. This provides compelling evidence that PROC mutations are the first disclosed genetic cause for the disease. Furthermore, our functional and mechanistic studies revealed an unknown PC–PROCR–HIF-1α regulatory axis in suppressing adipogenesis. PC, a secreted protein encoded by PROC , likely targets PROCR-expressing adipocyte progenitors to promote HIF-1α accumulation, thus inhibiting adipocyte differentiation. This work demonstrates the critical role of PC in blocking adipogenesis, offering novel insights into the pathogenesis of lipedema. PC has traditionally been recognized for its anti-coagulation role 15 . A variety of heterozygous PROC mutations that damage the activation of PC has been identified in patients with venous thrombosis 36 , 37 . This study reveals a novel function of PC in inhibiting the differentiation of adipose progenitor cells. This function of PC primarily relies on its cell surface receptor, PROCR, which is specifically expressed in the progenitor cells of adipose tissues. Intriguingly, our in vitro experiments indicate that the PC zymogen (inactive PC), but not the activated PC (aPC), can transduce signaling to activate HIF-1α, thereby suppressing adipogenesis. Although the concentrations of PC in circulation are approximately 1000 times higher than those of aPC, the biological roles of PC have not been fully explored. Our study here uncovers an unexpected function of the abundant PC zymogen in the regulation of adipogenesis. Align with previous studies demonstrating HIF-1α signaling in the control of adipogenesis 38 , our work implicates HIF-1α as the downstream mediator of PC–PROCR signaling in a subpopulation (PDGFRα + PROCR + ) of adipose precursor cells. PC (but not aPC) can active HIF-1α in these precursor cells; consistently, PROCR deletion reduces their HIF-1α activity. Furthermore, inhibition of HIF-1α activity abolishes PC's ability to inhibit adipocyte differentiation, in line with impaired HIF-1α activity in the progenitor cells of tSAT of the patient carrying PROC mutants. As an aspect of pathophysiology, very few studies have provided evidence of adipocyte hyperplasia in lipedema 2 . Our morphological examinations and snRNA sequencing of biopsied tSAT revealed enhanced adipogenesis, contributing to hyperplasia rather than hypertrophy in lipedema. Furthermore, our results demonstrated that the PC–PROCR–HIF-1α pathway physiologically inhibits the differentiation of adipose progenitors into mature adipocytes, thus suppressing excessive hyperplasia and fat expansion. In support of our findings, a recent genome-wide proteomics study revealed that the PROCR gene is strongly associated with body fat distribution (upper trunk to lower body) 39 . More recently, a population of PROCR high-expressing mesenchymal progenitors was identified in the adventitial layer of human blood vessels, which are capable of both osteogenesis and adipogenesis in vitro 27 . Based on these observations, we postulate that loss-of-function mutations or abnormal downregulation in PROCR and HIF-1α might also be involved in the development of lipedema, implying additional causes for those without a definite genetic etiology. In conclusion, we identified compound heterozygous mutations in PROC as the first genetic cause of excessive fat expansion in the lower body of lipedema patients. Further elucidation of PC’s anti-adipogenic function relies on its receptor, PROCR, which marks a subpopulation of adipose progenitors. In the future, the development of drugs targeting the PC–PROCR–HIF-1α pathway may provide potential therapeutic options for lipedema, for which no effective treatment currently exists 3 . Declarations Acknowledgments We thank the patients and their families, as well as healthy volunteers, for participating in this study, and we thank Prof. Chi-Chung Hui from the University of Toronto for his valuable suggestions. Funding This work was supported by grants from the National Key Research and Development Program of China (2022YFC2505201 to J.W.; 2020YFA0509002 to Y.A.Z.; 2021YFA1301103 to J.W.), the National Natural Science Foundation of China (U24A20675, 82088102, 92457302, 92157204, 82250901 and 91957124 to J.W.), Shanghai Municipal Science and Technology Commission (22JC1402202 to Y.A.Z.), the Innovative research team of high-level local universities in Shanghai, Shanghai Municipal Education Commission (2023ZKZD22 to J.W.), Shanghai Outstanding Academic Leaders Plan of Shanghai Municipality (LJ2023078 to J.W.). Author contributions J.W. and Y.A.Z. conceived and supervised the study. W.G. and B.G. collected the clinical data of pedigrees. M.N. and R.Y. performed the experiments. J.W., M.N. and R.Y. wrote the manuscript. B.Y. and Q.B contributed to the healthy control adipose tissue collection (lower body). H.X. contribute to adipose tissue collection (upper and lower body). 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Reversed graph embedding resolves complex single-cell trajectories. Nature Methods 14 , 979-982 (2017). Emont, M.P. et al. A single-cell atlas of human and mouse white adipose tissue. Nature (2022). Supplementary tables Supplementary tables 2 and 3 are not available with this version Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryFigs.pdf Supplementarytable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5876962","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":409899403,"identity":"25b18255-6042-4b6f-a571-b85d81c9639b","order_by":0,"name":"Jiqiu 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1","display":"","copyAsset":false,"role":"figure","size":1334398,"visible":true,"origin":"","legend":"\u003cp\u003eClinical features of lipedema in two unrelated families a,b, Pedigrees of two Chinese families displaying affected cases indicative recessive inheritance. Squares represent males, and circles represent females; open symbols indicate unaffected, while black symbols denote affected. The black arrow points to the proband, and a diagonal slash indicates the deceased case. c-e, Frontal view (left) and dorsal view (right) of Patient 1 (c) and Patient 2 (d) from Family 1, as well as Patient 3 (e) from Family 2, illustrating the abnormal thickness of the lower body while sparing of the feet. f, Dorsal view of unaffected family members from Family 1. g, Frontal view of unaffected family members from Family 2. h,i, Transaxial (left) and coronal (right) T2-weighted MR images of the upper legs in Patient 1 (h) and Patient 3 (i), showing excessive subcutaneous fat deposits (bright) without accumulation of free fluid. Annotations: for Patient 1, the bore size of MR scanners is relatively small (c.a. 530 mm of a standard 1.5T clinical scanner), making it difficult to accommodate her lower body and capture the full images (h); for Patient 2, the picture (e) was taken 5 years after her liposuction surgery.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/dbaa2ed0c757b0d1e14898ce.png"},{"id":75704479,"identity":"d60e875e-be4e-42c3-a2a7-312500fb5db0","added_by":"auto","created_at":"2025-02-07 09:57:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":332564,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of PROC mutations in lipedema patients. a, Genetic variant detection and filtering pipeline for whole genome sequencing data from the two families. b,c gDNA Sanger sequencing data of the PROC gene in Patients 1 and 2 (b) as well as Patient 3 (c), along with their parents. In b and c, the mutations are indicated by arrows. d, Schematic diagram illustrating the amino acid residues of the four identified mutants in the serine protease domain of the PC protein (encoded by PROC) and sequence conservation of these homologous residues across species. Mutants are represented with stars (red for Patients 1 and 2; blue for Patient 3). Gla denotes the γ-carboxyglutamic acid rich, and EGF denotes the epidermal growth factor. e, Schematic illustration of the in vitro adipogenic differentiation experiments of SVF cells. Wild type PC or mutant PC protein were added from day 0 to day 2. f, BODIPY lipid staining of adipocytes (green) differentiated from stromal vascular fraction (SVF) cells. These cells were induced to differentiate in the presence of either vehicle (PBS), recombinant wild-type (WT) human PC or mutant PC (20 μg/ml). Scale bar, 100 μm. Data are pooled from n = 3 biological replicates and presented as mean ± SEM (f)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/45207782b1c7fcdfd60eefd2.png"},{"id":75704482,"identity":"1c655bb7-6fd7-42ed-b90e-900824c0be8f","added_by":"auto","created_at":"2025-02-07 09:57:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":782512,"visible":true,"origin":"","legend":"\u003cp\u003ePC inhibits adipogenesis by targeting PROCR+ adipocyte progenitors a,b, Uniform manifold approximation and projection (UMAP) plot (left) of 11,338 stromal vascular fraction (SVF) cells from adult human subcutaneous white adipose tissue (WAT) (a) or 11,423 SVF cells from mouse (P12) subcutaneous WAT (b) derived from the study by Merrick et al 10. The feature plots (right) show the expression of PC and PROCR in adipose progenitor cells (human, CD55; mouse, Cd55). c, Schematic illustration of the in vitro adipogenic differentiation experiments using Pdgfrα+ adipose precursor cells from subcutaneous WAT of Procrflox/flox (Ctrl) and Pdgfra-CreERT/+;Procrflox/flox (Procr-cKO) mice. Tamoxifen (TAM, 100 mg/kg) was administered intraperitoneally to 6-week-old male mice of both genotypes (Ctrl and Procr-cKO) daily for 4 days to induce Procr knockout. After 7 days, Pdgfrα+ precursor cells were isolated from subcutaneous WAT depots and cultured for adipogenic differentiation. d, FACS scatterplots demonstrating the efficiency of Procr knockout in adipose precursor cells. e, BODIPY lipid staining of adipocytes (green) differentiated from Pdgfrα+ precursor cells isolated from Ctrl or Procr-cKO mice. These cells were induced to differentiate in the presence of either vehicle (PBS) or recombinant PC (20 μg/ml). Scale bar, 100 μm. f, Quantification of adipogenesis in differentiated cells treated as described in (e). g, Schematic illustration of the lineage tracing experiments for Pdgfrα lineage reporter (Pdgfrα-CreERT;R26mTmG) mice with (Ctrl;mTmG) or without (Procr cKO;mTmG) Procr expression. h, Whole mount staining of subcutaneous WAT showing undifferentiated mGFP+ stromal cells (purple arrows) and newly-differentiated mature adipocytes (yellow asterisk) at 2 months post-tamoxifen administration. Scale bar, 100 μm. i, Percentages of mGFP+ stromal cells and adipocytes treated as described in (h). j,k, FACS analysis (j) and proportion (k) of mGFP+ adipose stromal cell subsets, including CD55+ progenitors, ICAM1+ preadipocytes, and Group 3 (CD142+) cells in subcutaneous WAT at 2 months post-tamoxifen administration. Data are pooled from n = 3 biological replicates and presented as mean ± SEM (d, e, h, j). Statistical significance was determined by Dunnett's multiple comparisons tests (two-way ANOVA) (f), Sidak's multiple comparisons tests (two way ANOVA) (i), and Unpaired t-test (k). *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/b112eb864e8bd17921f42971.png"},{"id":75704829,"identity":"a36053c2-d6f8-4f37-85cd-cf8ec7b52124","added_by":"auto","created_at":"2025-02-07 10:05:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":886196,"visible":true,"origin":"","legend":"\u003cp\u003ePC activates HIF-1α to inhibit adipogenesis a, Schematic illustration of the in vitro adipogenic differentiation experiments. b, BODIPY lipid staining of adipocytes (green) differentiated from PDGFRα+ precursor cells isolated from C57BL/6J mice. Cells were induced to differentiate in the presence of either vehicle (PBS), recombinant PC (20 μg/ml), or aPC (20 μg/ml). BODIPY lipid staining was performed 8 days after the induction of adipogenic differentiation. Scale bar, 100 μm. c, Quantification of adipogenesis in differentiated cells treated as described in (a). d, Schematic illustration of bulk mRNA-seq harvesting from PDGFRα+ precursor cells treated with PBS, recombinant PC (20 μg/ml), or aPC (20 μg/ml) for 24 hours. Differentially expressed genes (DGEs) were screened by comparing the PC or aPC group with the vehicle group. 1583 DEGs specific to the PC group but not present in the aPC group and top 202 DEGs were selected to predict the regulated transcription factors (TFs) via iRegulon analysis. e, Top 8 transcription factors predicted via iRegulon analysis to be specifically upregulated in the PC group. f, Gene set enrichment analysis (GSEA) of upregulated DGEs in the PC group compared with the vehicle group. g-i, Western blot analysis (g, h) and immunofluorescence staining (i) of HIF-1α in PDGFRα+ adipose precursor cells treated with PBS, recombinant PC (20 μg/ml), or aPC (20 μg/ml) for 12 hours. Scale bar, 25 μm. j-l, Experimental setup and western blot analysis for HIF-1α in PDGFRα+;CD55+ adipose progenitor cells from Ctrl or cKO mice. m,n, BODIPY lipid staining of adipocytes (green) differentiated from PDGFRα+ precursor cells isolated from C57BL/6J mice. Cells were induced to differentiate in the presence of either PBS or recombinant PC (20 μg/ml) plus DMSO or HIF1α inhibitors, including TAT-cyclo-CLLFVY (5mM) and IDF-11774 (5mM). BODIPY lipid staining (m) and quantification of adipogenesis (n) was performed 8 days after the induction of adipogenesis. Scale bar, 100 μm. Data are pooled from n = 3 biological replicates and presented as mean ± SEM (b, g, i, k, m). Statistical significance was determined by Dunnett's multiple comparisons test (one-way ANOVA) (c, h), Unpaired t-test (l), and Newman-Keuls multiple comparisons test (one-way ANOVA) (n). *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/eed71a45f9dc7d5f01e4bc8a.png"},{"id":75704485,"identity":"860ac63f-e4a6-476e-8a93-65a6e5859731","added_by":"auto","created_at":"2025-02-07 09:57:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":481558,"visible":true,"origin":"","legend":"\u003cp\u003eAdipose hyperplasia along with attenuated HIF-1α signaling in PROC-mutant lipedema a, Schematic representation of thigh subcutaneous adipose tissue (tSAT) biopsies from Patient 1 as well as age- and sex-matched healthy control for histological examination and single-nucleus RNA sequencing (snRNA-seq). b,c, HE staining (b) and distribution of adipocyte size (c) of tSAT samples from the patient 1 and the healthy control subject. Scale bar, 200 μm. Scale bar, 200 μm. Dots represent the percentage of adipocytes with each size interval (c). d, UMAP plots of all sequenced tSAT cells split by the patient and the control subject, annotated according to known cell-type markers47. e, Proportional distribution of cell types as revealed by the snRNA-seq analysis. f, Pseudotemporal cell ordering of progenitors, preadipocytes, and adipocytes along differentiation trajectories by using Monocle. g, Violin plots showing proportion analysis of progenitors, preadipocytes, and adipocytes along with pseudotime. The median is represented by a black line in the box. h, Violin plots showing gene expression levels of key adipogenic genes (PPARγ, FABP4, and ADIPOQ) in progenitors, preadipocytes, and adipocytes, respectively. i, GSEA analysis indicating impaired HIF-1α signaling in adipose progenitors of tSAT in the patient with lipedema. j, Graphic summary of the main findings of the study: In normal conditions, PC binds to and activates PROCR, enhancing HIF-1α activities, which leads to the suppression of adipogenesis in adipose progenitors. When PC mutants fail to activate the signaling pathway, lipedema occurs in the lower body. Statistical significance was determined using the chi squared test (c), the chi-squared test of independence with Bonferroni-adjusted P values (e), Wilcoxon test (g), and Benjamini \u0026amp; Hochberg test (h). *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/b337eee541fe16e2c944f967.png"},{"id":76679785,"identity":"18e74210-f59d-443a-8119-626e2f04e1de","added_by":"auto","created_at":"2025-02-19 14:59:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5382812,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/b357f368-18ab-4626-84fa-8b7b6f7b09c1.pdf"},{"id":75704828,"identity":"52195401-9656-4921-95ce-90a7eb274b9f","added_by":"auto","created_at":"2025-02-07 10:05:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3711819,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigs.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/71d84c108ea4ddab5eaa6ee0.pdf"},{"id":75704826,"identity":"6f6a0242-3f91-4006-8500-33853bdc9d28","added_by":"auto","created_at":"2025-02-07 10:05:55","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":44461,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-5876962/v1/c97a6d87d4b5551a133c0fbd.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Compound heterozygous PROC mutations cause lipedema in humans","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLipedema was first identified by Allen and Hines at the Mayo Clinic in 1940\u003csup\u003e1\u003c/sup\u003e, and its cause remains unknown but is believed to involve genetics and hormonal factors\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Lipedema is characterized by the abnormal accumulation of subcutaneous adipose tissue (SAT) in the limbs, often observed in Caucasian descents\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Patients with lipedema typically exhibit a disproportionate figure with symmetrically enlarged lower bodies, particularly affecting both legs and then extending up to the hips and buttocks\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. This condition usually manifests at puberty and progresses gradually over time. It has been shown that the enlarged lower limbs in lipedema patients are owing to abnormally expanded adipose tissue, rather than edema or lymphedema. Adipose tissue could expand through hypertrophy (increase in adipocyte size) or hyperplasia (increase in adipocyte number)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The latter refers to the process of enhanced adipogenesis, which involves the accelerated commitment of preadipocytes followed by the neogenesis of mature adipocytes. However, there is little evidence about whether adipocyte hypertrophy or hyperplasia occurs in lipedema. Notably, lipedema has been established as a genetic condition through classic familial studies (Online Mendelian Inheritance in Man [OMIM] number, 614103)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Several groups have applied candidate gene sequencing or whole-exome sequencing (WES) to pedigrees or cases to explore pathogenic genes\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Unfortunately, the valid genetic factors and underlying mechanisms responsible for fat deposition in lipedema remain poorly understood.\u003c/p\u003e \u003cp\u003eMature adipocytes are considered to be developed from multipotent mesenchymal progenitor cells, which first commit into preadipocytes and then further differentiate into mature adipocytes. Mouse subcutaneous adipocyte progenitors have been identified as a population of Dpp4-expressing mesenchymal cells\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. PROCR, also known as EPCR, has been established by our and other groups as a functional adult stem cell maker in many organs, including the mammary gland\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, hematopoietic system\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and pancreatic islets\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The role of PROCR in adipose progenitors is unclear.\u003c/p\u003e \u003cp\u003eProtein C (PC), encoded by the \u003cem\u003ePROC\u003c/em\u003e gene and acting as a plasma serine protease zymogen, is the solely known extracellular ligand of PROCR. PC is primarily expressed by liver cells and secreted into circulation to bind to PROCR in other tissues\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The currently established role of PC is for anticoagulation\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Once binding with PROCR on the endothelial surface, PC zymogen (inactive PC) is cleaved and converted into activated Protein C (aPC) by thrombin-thrombomodulin complex\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. aPC exerts potent anticoagulation activity by inactivating coagulation factors Va and VIIIa\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The serum concentrations of PC are approximately 70 nM, whereas those of aPC are less than 40 pM \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In addition to its role in anticoagulation, we have demonstrated that aPC can trigger the activation of the Src-IGF1R axis in mammary gland stem cells when binding with PROCR \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Whether inactive PC also plays similar intracellular signaling roles remains unclear. It is also unknown whether PC or aPC contributes to adipogenesis.\u003c/p\u003e \u003cp\u003eIn this study, we aim to explore the causal factors of lipedema in patients from unrelated pedigrees. We filtered their genetic mutations by whole-genome sequencing (WGS) and identified that the \u003cem\u003ePROC\u003c/em\u003e gene is the only candidate shared by these patients. We investigated the functional role of PC zymogen in adipocyte progenitors, unveiling a PC\u0026ndash;PROCR\u0026ndash;HIF-1α signaling axis in the regulation of adipogenesis. These findings first establish that \u003cem\u003ePROC\u003c/em\u003e is a causal gene of lipedema.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical features of the two probands were comprehensively evaluated and clinically diagnosed by two endocrine physicians. Subsequently, both patients and their family members were recruited for clinical information and sample collection. Blood samples from patients and unaffected family members were taken to extract genomic DNA. In addition to routine procedures of anthropometric measurements and laboratory biochemical tests, imaging examinations, including magnetic resonance imaging (MRI), were performed to evaluate fat accumulation, particularly in the lower body of the two probands. Thigh subcutaneous fat tissues were biopsied by surgeons from the patients as well as from age- and sex-matched healthy volunteers for histological examination with hematoxylin and eosin (H\u0026amp;E). To detect changes of cellular and molecular profiles, single-nucleus RNA sequencing (snRNA-seq) was performed to the samples from Patient 1 and the corresponding control. The study was approved by the Institutional Review Board of Ruijin Hospital, SJTUSM, and was conducted in accordance with the principles of the Helsinki Declaration II. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhole genome sequencing and genetic analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree patients and all their unaffected family members from the two pedigrees underwent a detailed pedigree assessment to ascribe phenotypes to likely recessive, dominant, or \u003cem\u003ede novo\u003c/em\u003e inheritance patterns. Following this assessment, whole-genome sequencing (WGS) was performed on the Illumina HiSeq2000 platform. Genomic DNA of ten participants (generations Ⅱ and Ⅲ) in total was extracted from blood cells according to the QIAamp DNA Mini Kit (Qiagen, 56304), randomly fragmented and then sequenced using 150 bp paired-end reads to achieve mean approximately 40\u0026times; genomic coverage per library. Reads were aligned to GRCh37. Variants were called in accordance with the best practices of the Genome Analysis Toolkit (GATK)\u003csup\u003e40\u003c/sup\u003e, and ANNOVAR was used for annotation as described in previous studies\u003csup\u003e41\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003eWGS generated ~4.3 million single nucleotide variants (SNVs) per genome among all participants. To explore the potential pathogenic variant(s), the following filters were applied: 1) variants that are rare (minor allele frequency (MAF) \u0026le; 1% in the 1000 Genomes Project, Genome Aggregation Database (gnomAD), and Exome Sequencing Project (ESP6500)); 2) exonic and protein-altering variants; 3) variants predicted to be damaged by more than two algorithm methods among SIFT\u003csup\u003e21\u003c/sup\u003e, CADD\u003csup\u003e22\u003c/sup\u003e, Polyphen-2\u003csup\u003e23\u003c/sup\u003e, and MutationTaster\u003csup\u003e24\u003c/sup\u003e; 4) variants that were homogeneous or compound heterozygous. All four identified candidate variants in the \u003cem\u003ePROC\u003c/em\u003e gene were confirmed with Sanger sequencing. These likely causative variants were further determined according to American College of Medical Genetics and Genomics (ACMG) guidelines as pathogenic or likely pathogenic\u003csup\u003e25\u003c/sup\u003e. Protein sequence alignment was performed with the EMBL-EBI Clustal Omega online tool. The molecular structure of human PROC was retrieved from the Protein Data Bank (PDB) (code 6M3C)\u003csup\u003e42\u003c/sup\u003e, and graphics were generated using PyMOL software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiopsy of human adipose tissues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn brief, biopsy specimens of thigh subcutaneous adipose tissues (tSAT) were obtained from the upper one-third of the front thighs of the two patients (patient 1 and patient 3). Control tSAT samples from a similar thigh site were collected by surgeons from two sex- and age-matched, metabolic healthy female subjects. A part of the tSAT samples was immediately fixed in 10% neutral-buffered formalin, paraffin-embedded, and stained with H\u0026amp;E for histopathological examination. Adipocyte size and number were analyzed using AdipoCount software\u003csup\u003e43\u003c/sup\u003e. The remaining samples were flash-frozen immediately after collection and stored in liquid nitrogen until needed for genetic and molecular evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u003cem\u003e Pdgfr\u0026alpha;-\u003c/em\u003eCre\u003cem\u003e\u003csup\u003eERT2\u003c/sup\u003e\u003c/em\u003e (JAX number #018280), \u003cem\u003eRosa26-mTomato-stop-mGFP\u003c/em\u003e (JAX number #007576), and\u003cem\u003e Procr\u003csup\u003eflox/flox\u003c/sup\u003e \u003c/em\u003emice\u003csup\u003e18\u003c/sup\u003e were used in the study. The \u003cem\u003eProcr\u003csup\u003eflox/flox\u003c/sup\u003e\u003c/em\u003e alleles were generated with two \u003cem\u003eloxP\u003c/em\u003e sites flanking exon 2\u0026ndash;4. To obtain the conditional deletion of \u003cem\u003eProcr \u003c/em\u003ein adipose precursor cells, \u003cem\u003ePdgfr\u0026alpha;-\u003c/em\u003eCre\u003cem\u003e\u003csup\u003eERT2\u003c/sup\u003e\u003c/em\u003e;\u003cem\u003eProcr\u003csup\u003eflox/flox\u003c/sup\u003e\u003c/em\u003e (cKO) and littermate \u003cem\u003eProcr\u003csup\u003eflox/flox\u003c/sup\u003e\u003c/em\u003e (control) mice received intraperitoneal injections of tamoxifen (80 mg/kg) (Sigma-Aldrich, T5648) diluted in sunflower oil, and the timing points of injection are as illustrated in the corresponding figures. For \u003cem\u003ein vitro\u003c/em\u003e experiments, adipose PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e precursors were sorted from cKO or control mice. For fate mapping of PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e cells with or without \u003cem\u003eProcr\u003c/em\u003e-deletion, a single dose of tamoxifen (80 mg/kg) was administered intraperitoneally to 8-week-old cKO and control mice, and analyses were conducted 2 months later. Mice were housed in standard cages within a specific-pathogen-free (SPF) facility under a 12-h light/dark cycle at 22 \u0026plusmn; 2 \u0026deg;C, with \u003cem\u003ead libitum\u003c/em\u003e access to food and water. All animal procedures were conducted in accordance with the guidelines for the care and use of laboratory animals and were approved by the Animal Care and Use Committee of Shanghai Institute of Biochemistry and Cell Biology (SIBCB), Chinese Academy of Sciences, with a project license number of IBCB0065.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of primary adipose single-cell suspension and FACS analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inguinal subcutaneous fat pads were isolated from transgenic or wild-type mice, then minced and digested with 2 mg/mL collagenase type III (Worthington, LS004183) for 2 hours in a shaker at 100 rpm and 37 \u0026deg;C. The digested mixture was then centrifuged to separate the floating mature adipocyte fraction from the pelleted stromal vascular fraction (SVF). SVF cells were pelleted and treated with red blood cell lysis buffer (Sigma, R7757) for 5 minutes, followed by sequential incubation with 0.05% trypsin-EDTA (Gibico, 25300054) at 37 \u0026deg;C for 5 minutes and 0.1 mg/mL DNase I (Sigma, D4263) for 5 minutes. The single-cell suspension was then filtered through a 100-\u0026mu;m cell strainer. For cell labeling, the following antibodies were used: FITC-conjugated CD31 (BD, 553372), FITC-conjugated CD45 (BD, 553080), FITC-conjugated TER119 (BD, 557915), PE-conjugated CD140a (Invitrogen, 12-1401-81), Biotin-conjugated CD201 (Invitrogen, 13-2012-82), APC-conjugated CD55 (Biolegend, 131812), APC-conjugated CD54 (Biolegend, 116120), Rabbit anti-CD142 (Sino Biological, 50413-R001), and Streptavidin-V450 (BD, 560797). Antibody incubation was performed on ice for 25 minutes in PBS with 5% fetal bovine serum (FBS) (PAN, P30-3302). Before FACS sorting, cells were filtered through a 50-\u0026mu;m cell strainer, and then sorted using FACSJazz (Becton Dickinson). For PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e adipose precursor cells, live singlets from SVF cells were gated for the absence of Ter119, CD31 and CD45 (blood lineage, Lin\u003csup\u003e-\u003c/sup\u003e), as well as EpCAM (epithelial cells), then for PDGFR\u0026alpha; expression, representing adipose precursor cells. The same strategy was consistently applied throughout the study. The purity of the sorted population was routinely checked and ensured to be more than 95%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdipocyte differentiation \u003cem\u003ein vitro\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor adipogenic differentiation, SVF or precursor cells were seeded on 96-well or 384-well plates and allowed to attach for 24 to 48 hours until reaching the confluence. Adipogenic differentiation was carried out in DMEM/F12 medium containing 10% FBS with the addition of a full adipogenic cocktail: 5 \u0026mu;g/mL insulin (Eli Lilly), 1 \u0026mu;M dexamethasone (Sigma, D1756), and 0.5 mM 3-isobutyl-1-methylxanthine (IBMX) (Sigma, I7018). Cells were incubated in the full adipogenic cocktail for 2 days and then switched to an adipogenic maintenance medium containing 5 \u0026mu;g/mL insulin for 6 days. Medium changes were performed every 2 days. Recombinant Protein C was expressed in CHO-R1c cells and purified with Flag-tag as described previously\u003csup\u003e44\u003c/sup\u003e. Throughout the induction, cultures were treated with recombinant Protein C (20 \u0026mu;g/ml), active Protein C (Sigma-Aldrich, P2200), or the HIF-1\u0026alpha; inhibitors TAT-cyclo-CLLFVY (5 mM) (MCE, HY-P1420-1) and IDF-11774 (5 mM) (Sigma, S8771). Adipogenesis was assessed at 8 days post-induction by staining lipid droplet accumulation with BODIPY 493/503 (Invitrogen, D3922). The stained cells were imaged using an inverted fluorescence microscope (Agilent BioTek Cytation 5) with green fluorescent protein (GFP) filters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhole mount staining \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhole mount staining was performed as described previously\u003csup\u003e45\u003c/sup\u003e, with minor modifications. In brief, inguinal subcutaneous fat pads of cKO and control tracing mice were dissected into small pieces, then processed in digestion buffer containing RPMI 1640 with 25 mM HEPES, 5% FBS, 1% penicillin\u0026ndash;streptomycin (PS) (Thermo Fisher, 15140-122), and 300 U/ml collagenase III for 30 min at 37 \u0026deg;C, and then fixed in 4% paraformaldehyde (PFA). Tissues were washed three times with PBST (PBS, 0.1% Triton-X 100 (Sigma-Aldrich, T9284)) for 5 min and incubated overnight at 4 \u0026deg;C with primary antibody anti-chicken GFP (Invitrogen, A10262). Tissues were then washed and incubated overnight at 4 \u0026deg;C with secondary antibody anti-chicken Alexa 488 (Invitrogen, A78948) plus 4\u0026apos;,6-diamidino-2-phenylindole (DAPI) (Thermo Fisher, D1306). On the following day, tissues were washed and incubated in 80% glycerol overnight before dissection for 3D imaging. Stained samples were imaged using a ZEISS LSM 710 confocal laser-scanning microscope and analyzed using ZEISS ZEN microscope software. For quantification, all GFP\u003csup\u003e+\u003c/sup\u003e cells were scored as adipocytes or stromal cells based on their distinct spherical morphology and attached nucleus. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA extraction and quantitative real-time PCR\u003c/strong\u003e \u003cstrong\u003eanalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA from cultured cells was extracted following the manufacturer\u0026rsquo;s instructions. Samples were lysed in RNAiso plus (Takara, 9109). Extracted RNA was reverse transcribed into cDNA using the Primerscript RT master kit (Takara, RR036A). qPCR samples were prepared with SYBR Green Mixture (Roche, 04913914001) and detected using an Applied Biosystems StepOne Plus (Thermo Fisher, 4376600) platform. The comparative 2\u003csup\u003e-\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method was used to evaluate the relative mRNA levels, with the housekeeping gene \u003cem\u003eGapdh\u003c/em\u003e serving as the internal control. All the qPCR primers are listed in \u003cstrong\u003eSupplementary Table 3\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBulk RNA sequencing and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from cultured cells according to the manufacturer\u0026rsquo;s instructions. The concentration of total mRNA was determined with an bioanalyzer (Agilent 2100). RNA-seq libraries were prepared according to the manufacturer\u0026rsquo;s instructions and then sequenced on a DNBSEQ platform (BGI). Briefly, approximately 50 million reads were obtained for each sample, and these reads were uniquely mapped to the mm9 mouse genome, with a mapping rate \u0026gt; 75% for both samples. Genes with an FPKM \u0026gt; 1 in at least one sample across all samples were retained for further analysis. Differential gene expression analysis was performed, and genes with significant changes were extracted using DAVID Bioinformatics Resources 6.8. The differentially expressed genes (DEG) were then used to infer the regulatory network of transcription factors with the iRegulon plugin (http://iregulon.aertslab.org/). Gene-set enrichment analysis (GSEA) was conducted using GSEA software (v4.1.0), with the threshold of significant enrichment set based on the permutation test (the number of permutations = 1000, p-value \u0026lt; 0.05), applying default weighting statistics for each parameter. Enriched results from the GSEA analysis were visualized using the R packages ClusterProfler, ggplot2 and enrichplot. The presented GSEA terms are selected from MSigDB (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal protein from frozen adipose tissues or culture cells was extracted using RIPA lysis buffer (Biocolor bioscience, R20095) with a protease inhibitor cocktail (Thermo Fisher Scientific, 78442). Proteins were separated by SDS-PAGE and transferred to nitrocellulose membrane (GE company). Bolts were blocked with 3% BSA in TBST (50 mM Tris-HCl, 150 mM NaCl, 0.05% Tween-20, pH 7.5) for 1 hour and then incubated with primary antibodies at 4 ℃ overnight. This was followed by incubation with secondary IgG-HRP antibodies for 2 hours at room temperature. Protein bands were visualized with a chemiluminescent reagent and exposed to a Mini Chemiluminescent Imager (MiniChemi 610 Plus). The following primary antibodies were used: anti-HIF-1\u0026alpha; (1:2000 dilution) (CST, 36169S) and HSP90 (1:1,000 dilution) (CST, 4877). HRP-linked ti-rabbit IgG (1:2000 dilution) (CST, 7074S) was used as the secondary antibody.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of the public scRNA-seq dataset\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scRNA-seq count matrices of human and mouse subcutaneous WAT SVF cells from Merrick et al\u003csup\u003e10\u003c/sup\u003e were downloaded from the Gene Expression Omnibus (GEO) repository (accession number: GSM3717979, GSM3717977). Cell types were annotated according to the previous publication\u003csup\u003e10\u003c/sup\u003e. The subset matrices were renormalized using Seurat v3 pipelines. Significant principal component (PC) dimensionalities were identified using the ElbowPlot method. 10 PCs were used for p12 pups, and 15 PCs were used for the human single-cell study. Dimensional reduction was performed with the Uniform Manifold Approximation and Projection (UMAP) method. Cell clustering was based on the shared-nearest neighbor (SNN) method, and the resolution was set to 0.6. Analysis of differential gene expression (DGE) among clusters was performed by using the Seurat function FindMarkers with the Wilcox test. Heatmaps and individual UMAP plots for the given genes were generated by using the Seurat toolkit DoHeatmap, and FeaturePlot functions, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-nucleus RNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNuclei were isolated from frozen human thigh fat samples for 10\u0026times; single-nucleus RNA sequencing (snRNA-seq). The samples were kept frozen in liquid nitrogen before nuclei isolation, and all sample handling steps were performed on ice. The samples were homogenized in a Dounce homogenizer using lysis buffer with 1 mM DTT (solarbio, D8220) and 1 U/\u0026mu;l RNase inhibitor (Roche, 3335402001), followed by incubation on ice for 5 minutes. The suspension was then filtered through a 40 \u0026mu;m filter to remove debris and centrifuged at 4 \u0026deg;C, 500 g for 5 minutes. After resuspending the nuclei in 300 \u0026mu;l of lysis buffer and 300 \u0026mu;l of RB buffer in a 2 ml tube, the mixture was centrifuged using a density gradient to separate the nuclei from cell debris, and the intermediate layer was washed with RB buffer and collected. An aliquot of nuclei from each sample was stained with Trypan Blue, counted in an automatic cell counter to identify intact nuclei, and then immediately loaded onto the 10\u0026times; Chromium controller following the manufacturer\u0026rsquo;s protocol (10\u0026times; Genomics). For each sample, 10,000\u0026ndash;16,500 nuclei were loaded in one channel of a Chromium Chip. Full-length cDNA synthesis, amplification, and subsequent library construction were performed using the Chromium Single-Cell 3\u0026prime; GEM, Library \u0026amp; Gel Bead kit V3.1 (10\u0026times; Genomics, 1000121). Complementary DNAs and their corresponding 10\u0026times; libraries were evaluated and quantified using the Agilent 4200 Bioanalyzer system. Gene expression libraries were multiplexed and sequenced on the Illumina Novaseq6000 with a sequencing depth of at least 100,000 reads per cell, following a pair-end 150 bp strategy. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-nucleus RNA-seq data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Cell Ranger software pipeline (version 5.0.0) provided by 10\u0026times; Genomics was used to demultiplex cellular barcodes, map reads to the GRCh38 genome assembly using the STAR aligner, and generate feature-barcode matrices for downstream analysis. The data was further processed and analyzed using the Seurat software (version 3.1.2). Cells were filtered out if they met any of the following criteria: fewer than 200 genes detected, a gene number ranking in the top 1%, or a mitochondrial gene ratio exceeding 25%. Dimensionality reduction was performed using principal component analysis (PCA), and visualization was achieved using t-Distributed Stochastic Neighbor Embedding (tSNE) and UMAP. Clusters were identified based on canonical marker genes. For GSEA analysis, genes that are differentially expressed in the progenitor population were utilized. The gene sets were selected from the MSigDB and included those that were upregulated or downregulated by HIF-1\u0026alpha;. Enriched results from the GSEA analysis and visualization were visualized using the R packages ClusterProfler, ggplot2 and enrichplot. The p-value cutoff was set to 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePseudotime trajectory analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pseudotime trajectories were reconstructed using the R package Monocle 2 (version 2.9.0) as follows: first, the Seurat object was converted to the CellDataSet format using the importCDS function. Ordering genes were screened through the differentialGeneTest function with q value \u0026lt; 0.01. Dimensionality reduction was then performed with the reduceDimension algorithm. Finally, cell trajectory was inferred using the orderCells function, specifying the starting pseudotime state and direction\u003csup\u003e46\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are presented as mean \u0026plusmn; SEM. Statistical significance was determined using Student\u0026rsquo;s t-test or one-way ANOVA, followed by Tukey\u0026rsquo;s post hoc test, as appropriate. GraphPad Prism 10.2.0 (GraphPad Software) was used for generating figures and conducting statistical analyses. For snRNA-seq data analysis, differences among groups were assessed using the chi-squared test of independence with Bonferroni-adjusted \u003cem\u003eP\u003c/em\u003e values. Details of the statistical tests used were provided in the figure legends. A two-tailed \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eClinical characteristics of lipedema in two unrelated pedigrees\u003c/h2\u003e\n \u003cp\u003eThe pedigrees of two unrelated Chinese families affected by lipedema are illustrated in \u003cstrong\u003eFig.\u0026nbsp;1\u003c/strong\u003e. Family 1 includes three affected members\u0026mdash;two females and one male. Notably, the elder sister of the proband died at 52 years of age due to mesenteric venous thrombosis. Family 2 has one affected young female patient. All three patients (termed as Patients 1, 2, and 3) from the two families exhibited symmetrically enlarged lower extremities (\u003cstrong\u003eFig.\u0026nbsp;1c-e\u003c/strong\u003e), whereas unaffected family members showed normal lower body shapes (\u003cstrong\u003eFig.\u0026nbsp;1f, g;\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The symptoms initially occurred proximal to the ankles and progressively extended upward to the lower and upper thighs, hips and buttocks, but sparing the feet, trunk and upper limbs. A possibility of edema or lymphedema was first excluded\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Transaxial and coronal magnetic resonance imaging (MRI) of Patients 1 and 3 confirmed the presence of excessive subcutaneous fat deposits without the accumulation of free fluid in the legs (\u003cstrong\u003eFig.\u0026nbsp;1h, i\u003c/strong\u003e). These symptoms and signs manifested in all three patients during puberty and exacerbated over time (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). It is noted that Patient 3 underwent cosmetic liposuction surgery on the lower legs at 25 years old in 2013; however, this procedure did not effectively halt the progress of the disease (MRI images collected 5 years post-surgery) (\u003cstrong\u003eFig.\u0026nbsp;1e)\u003c/strong\u003e. Given the familial clustering and inheritance pattern of these clinical features, the disorder appears to be a highly penetrant autosomal recessive trait.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical characteristics of three patients with lipedema.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatient 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatient 2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatient 3*\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasic information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnic origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHan Chinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHan Chinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHan Chinese\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge at diagnosis (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge at symptom onset (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical phenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisproportionate fatdistribution on the limbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilateral, symmetrical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNonpitting edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimb pain and/or bruising\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreased sensitivity to touch or limb fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReduction of pain or discomfort with limb lift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWorsening of symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCuff sign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStemmer sign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnthropometric measurement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI (kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCircumference of upper legs (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.3 (left)\u003c/p\u003e\n \u003cp\u003e77.5 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.6 (left)\u003c/p\u003e\n \u003cp\u003e73.5 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.5 (left)\u003c/p\u003e\n \u003cp\u003e62.5 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCircumference of lower legs (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.0 (left)\u003c/p\u003e\n \u003cp\u003e55.7 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.8 (left)\u003c/p\u003e\n \u003cp\u003e50.3 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.0 (left)\u003c/p\u003e\n \u003cp\u003e42.6 (right)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e* 5 years after liposuction surgery.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eIdentification of the\u003c/strong\u003e \u003cstrong\u003ePROC\u003c/strong\u003e \u003cstrong\u003emutations in lipedema patients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTo identify the underlying genetic factors, we performed WGS sequencing to both families, using DNA samples from three affected patients along with their unaffected parents and siblings. Based on the autosomal recessive inheritance pattern, we first prioritized homozygous or compound heterozygous rare variants in or around the coding regions after standard filtering procedures (\u003cstrong\u003eFig.\u0026nbsp;2a\u003c/strong\u003e). As a result, we identified three and six candidate genes in the two families, respectively, in line with a Mendelian inheritance pattern of the autosomal recessive trait. No homozygous mutations were shared by the two families; strikingly, only one gene\u0026mdash;\u003cem\u003ePROC\u003c/em\u003e\u0026mdash;showed compound heterozygous mutations in both families (\u003cstrong\u003eFig.\u0026nbsp;2a\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003ePatients 1 and 2 from Family 1 harbored two missense mutations (p.R272H and p.G334S), while Patient 3 from Family 2 carried two other mutations (p.R271Q and p.D279H). These mutations were confirmed by Sanger sequencing, with the parents of these patients being heterozygous (\u003cstrong\u003eFig.\u0026nbsp;2b, c\u003c/strong\u003e). Importantly, the compound heterozygous mutations co-segregated well with the lipedema phenotypes within both families, indicating \u003cem\u003ePROC\u003c/em\u003e as a strong candidate gene for lipedema (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1a, b\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePROC\u003c/em\u003e encodes a secreted protein, Protein C (PC), which comprises four domains: the Gla (\u0026gamma;-carboxyglutamic acid) domain, two EGF (epidermal growth factor)-like domains, and a trypsin-like serine protease domain\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. All four identified mutations are located within the trypsin-like serine protease domain and are highly conserved across various mammalian species (\u003cstrong\u003eFig.\u0026nbsp;2d\u003c/strong\u003e). Notably, both the R271 and R272 residues map to the Ca\u003csup\u003e2+\u003c/sup\u003e-binding loop on the protease domain, while the D279 residue is located on a \u0026beta;-strand adjacent to the same loop (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1c)\u003c/strong\u003e. The loss of charge (substitution of Arg-271 with Gln) and the reversal of charge (substitution of Asp-279 with His) may alter the conformational structure of this exposed surface loop, impacting its electrostatic interaction with the metal cation. Moreover, these mutations were either absent or exceedingly rare in published databases of general populations, and predicted to be damaging by multiple prediction algorithms\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e (\u003cstrong\u003eSupplementary Table\u0026nbsp;1\u003c/strong\u003e). These findings meet the American College of Medical Genetics and Genomics (ACMG) criteria\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, classifying the mutations as pathogenic or likely pathogenic (\u003cstrong\u003eSupplementary Table\u0026nbsp;1\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003eNext, we investigated the potential role of PC on adipogenesis that may be associated with adipose accumulation in lipedema patients. We constructed the plasmids of wild-type (WT) or all mutant PC and successfully purified their secreted proteins (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1d\u003c/strong\u003e). We employed the \u003cem\u003ein vitro\u003c/em\u003e adipocyte differentiation assay by using freshly isolated mouse stromal vascular fraction (SVF) cells\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e (\u003cstrong\u003eFig.\u0026nbsp;2e\u003c/strong\u003e). Purified WT PC proteins were added into the differentiation medium during the first two days. Notably, we observed a dramatic inhibitory effect of WT PC on adipocyte differentiation, suggesting that PC suppresses adipogenesis (\u003cstrong\u003eFig.\u0026nbsp;2f\u003c/strong\u003e). In contrast, when the mutant p.R271Q and p.R272H PC proteins were added, the inhibitory effects on adipogenesis were largely blunted. However, mutant p.D279H and p.G334S PC proteins did not show such strong functional damages (\u003cstrong\u003eFig.\u0026nbsp;2f\u003c/strong\u003e). Collectively, our genetic and \u003cem\u003ein vitro\u003c/em\u003e functional data support the notion that the loss-of-function \u003cem\u003ePROC\u003c/em\u003e mutations probably lead to excessive adipogenesis in these lipedema patients.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePC inhibits adipogenesis by targeting PROCR adipocyte progenitors\u003c/h3\u003e\n\u003cp\u003eTo understand the potential pathogenic mechanism of \u003cem\u003ePROC\u003c/em\u003e dysfunction in lipedema, we then investigated how PC inhibits adipocyte differentiation. The \u003cem\u003ePROC\u003c/em\u003e gene is predominantly expressed in hepatocytes, with little evidence regarding its expression in WAT (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gtexportal.org/home/gene/PROC\u003c/span\u003e\u003c/span\u003e). Therefore, we utilized published single-cell RNA sequencing (scRNA-seq) data of SVF cells isolated from human and mouse subcutaneous WAT\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Human adipose precursor cells, primarily expressing PDGFR\u0026alpha; (a common mesenchymal cell marker), were divided into two subsets: early adipocyte progenitors and committed preadipocytes (\u003cstrong\u003eFig.\u0026nbsp;3a\u003c/strong\u003e). Our analysis revealed that \u003cem\u003ePROC\u003c/em\u003e expression was not detectable in any of these cell clusters. However, PROCR, the known receptor of PC, was abundantly expressed in early adipocyte progenitors, which are marked by \u003cem\u003eCD55\u003c/em\u003e and \u003cem\u003eDPP4\u003c/em\u003e expression (\u003cstrong\u003eFig.\u0026nbsp;3a\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;2a\u003c/strong\u003e). Similar \u003cem\u003eProcr\u003c/em\u003e expression patterns were observed in mouse inguinal WAT (iWAT) (\u003cstrong\u003eFig.\u0026nbsp;3b\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;2b\u003c/strong\u003e), in line with a recent report\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProc\u003c/em\u003e and \u003cem\u003eProcr\u003c/em\u003e expression in SVF cells and adipocytes were further validated in mouse iWAT, in which \u003cem\u003eProc\u003c/em\u003e expression was not detected in either cell type, and \u003cem\u003eProcr\u003c/em\u003e expression was highly enriched in SVF cells (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2c)\u003c/strong\u003e. We confirmed PROCR protein expression in adipose precursor cells by fluorescence-activated cell sorting (FACS) analysis (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2d\u003c/strong\u003e). Adipose precursor cells feature negative expression of hematopoietic and endothelial cell markers (Ter119\u003csup\u003e\u0026minus;\u003c/sup\u003e, CD45\u003csup\u003e\u0026minus;\u003c/sup\u003e, and CD31\u003csup\u003e\u0026minus;\u003c/sup\u003e, hereafter abbreviated \u0026ldquo;Lin\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026rdquo;) and epithelial cell markers (EpCAM\u003csup\u003e\u0026minus;\u003c/sup\u003e), and positive expression of mesenchymal cell markers (PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e). We found that PROCR-expressing (PROCR\u003csup\u003e+\u003c/sup\u003e) cells accounted for about 26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0% of the Lin\u003csup\u003e\u0026minus;\u003c/sup\u003eEpCAM\u003csup\u003e\u0026minus;\u003c/sup\u003ePDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e population (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2d\u003c/strong\u003e), constituting a notable subset of adipose precursor cells.\u003c/p\u003e\n\u003cp\u003eTo investigate the \u003cem\u003ein vivo\u003c/em\u003e function of PC\u0026ndash;PROCR axis in these precursors, we generated \u003cem\u003ePdgfr\u0026alpha;\u003c/em\u003e\u003csup\u003eCreERT/+\u003c/sup\u003e;\u003cem\u003eProcr\u003c/em\u003e\u003csup\u003e\u003cem\u003eflox/flox\u003c/em\u003e\u003c/sup\u003e (cKO) mice\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e (\u003cstrong\u003eFig.\u0026nbsp;3c\u003c/strong\u003e). Tamoxifen (TAM) was administered at 8-week-old mice to induce recombination, which thereby conditionally deleted \u003cem\u003eProcr\u003c/em\u003e in \u003cem\u003ePdgfr\u0026alpha;\u003c/em\u003e-expressing precursors. Seven days after TAM administration, the knockout efficiency was validated by FACS, demonstrating a significantly reduced percentage of Procr\u003csup\u003e+\u003c/sup\u003e (Lin\u003csup\u003e\u0026minus;\u003c/sup\u003e; EpCAM\u003csup\u003e\u0026minus;\u003c/sup\u003e; Procr\u003csup\u003e+\u003c/sup\u003e) cells in cKO mice compared to control (\u003cem\u003eProcr\u003c/em\u003e\u003csup\u003e\u003cem\u003eflox/flox\u003c/em\u003e\u003c/sup\u003e) mice (\u003cstrong\u003eFig.\u0026nbsp;3d\u003c/strong\u003e). Next, we isolated adipose precursor cells from the iWAT of both groups and performed \u003cem\u003ein vitro\u003c/em\u003e adipocyte differentiation assays in the presence or absence of PC proteins. In the absence of PC, when compared to the controls, the precursors from the cKO group displayed enhanced ability of adipogenesis (\u003cstrong\u003eFig.\u0026nbsp;3e\u003c/strong\u003e). Of note, in the presence of PC, the adipogenesis was consistently inhibited in the control group (\u003cstrong\u003eFig.\u0026nbsp;2f\u003c/strong\u003e and \u003cstrong\u003eFig.\u0026nbsp;2e\u003c/strong\u003e), and PC also suppressed the expression of adipocyte differentiation genes in these PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e cells (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2f\u003c/strong\u003e). Most importantly, deletion of \u003cem\u003eProcr\u003c/em\u003e abolished the inhibitory effect of PC on adipocyte differentiation (\u003cstrong\u003eFig.\u0026nbsp;3e, f\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;2f\u003c/strong\u003e). Together, these results indicate that PROCR is expressed in adipocyte progenitors and, importantly, an intact PC\u0026ndash;PROCR axis is essential for suppressing adipocyte progenitors differentiation.\u003c/p\u003e\n\u003cp\u003eTo explore how disruption of the PC\u0026ndash;PROCR axis impacts \u003cem\u003ein vivo\u003c/em\u003e adipogenesis, we further introduced the Cre-dependent \u003cem\u003eRosa26-loxP-mtdTomato-loxP-mGFP\u003c/em\u003e fluorescent reporter allele (\u003cem\u003eR26\u003c/em\u003e\u003csup\u003e\u003cem\u003emTmG\u003c/em\u003e\u003c/sup\u003e) into our genetic models (\u003cstrong\u003eFig.\u0026nbsp;3c\u003c/strong\u003e) and generated \u003cem\u003ePdgfr\u0026alpha;\u003c/em\u003e\u003csup\u003e\u003cem\u003ecreERT/+\u003c/em\u003e\u003c/sup\u003e;\u003cem\u003eR26\u003c/em\u003e\u003csup\u003e\u003cem\u003emTmG/+\u003c/em\u003e\u003c/sup\u003e (Ctrl;mTmG) and \u003cem\u003ePdgfr\u0026alpha;\u003c/em\u003e\u003csup\u003e\u003cem\u003eCreERT/+\u003c/em\u003e\u003c/sup\u003e;\u003cem\u003eProcr\u003c/em\u003e\u003csup\u003e\u003cem\u003eflox/flox\u003c/em\u003e\u003c/sup\u003e;\u003cem\u003eR26\u003c/em\u003e\u003csup\u003e\u003cem\u003emTmG/+\u003c/em\u003e\u003c/sup\u003e (cKO;mTmG) mice, for fate mapping of the progeny of PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e adipocyte precursor cells (\u003cstrong\u003eFig.\u0026nbsp;3g\u003c/strong\u003e). In this experiment, a single dose of TAM (100 mg/kg) was administered to 8-week-old mice, and adipose tissues were collected at 2 months later (\u003cstrong\u003eFig.\u0026nbsp;3g\u003c/strong\u003e). An effective deletion of \u003cem\u003eProcr\u003c/em\u003e was validated in cKO;mTmG mice (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2g\u003c/strong\u003e). Meanwhile, abundant mGFP\u003csup\u003e+\u003c/sup\u003e offspring stromal cells and adipocytes were observed in both groups, indicating sufficient labeling efficiency (\u003cstrong\u003eFig.\u0026nbsp;3h\u003c/strong\u003e). In the controls, 72.9% of the mGFP\u003csup\u003e+\u003c/sup\u003e cells in iWAT were PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e precursors cells, and only 27.0% of the cells were terminally differentiated mature adipocytes (\u003cstrong\u003eFig.\u0026nbsp;3h\u003c/strong\u003e), consistent with previous studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In contrast, cKO;mTmG mice showed a dramatic decrease (20.4%) in precursor cells and a significant increase (79.6%) in mGFP\u003csup\u003e+\u003c/sup\u003e mature adipocytes (\u003cstrong\u003eFig.\u0026nbsp;3h, i\u003c/strong\u003e). We further examined the various subpopulations of mGFP\u003csup\u003e+\u003c/sup\u003e precursor cells, i.e., CD55\u003csup\u003e+\u003c/sup\u003e adipose progenitor cells as well as ICAM\u003csup\u003e+\u003c/sup\u003e and CD142\u003csup\u003e+\u003c/sup\u003e preadipocyte populations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. We observed a significant decrease (from 45.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4% to 18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3%) in CD55\u003csup\u003e+\u003c/sup\u003e adipose progenitor cells, suggesting likely excessive differentiation originating from the adipose stem cell pool or excessive exhaustion upon \u003cem\u003eProcr\u003c/em\u003e deletion (\u003cstrong\u003eFig.\u0026nbsp;3j, k\u003c/strong\u003e). Intriguingly, the proportion of ICAM1\u003csup\u003e+\u003c/sup\u003e preadipocytes significantly increased (from 56.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2% to 88.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7%) in cKO;mTmG mice, while CD142\u003csup\u003e+\u003c/sup\u003e preadipocyte subsets remained unchanged compared to their controls (\u003cstrong\u003eFig.\u0026nbsp;3j, k\u003c/strong\u003e). These results suggest that impaired PC\u0026ndash;PROCR signaling may augment the differentiation of adipose progenitor cells into more committed ICAM1\u003csup\u003e+\u003c/sup\u003e preadipocytes, which consequently contribute to mature adipocytes. Together, both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e experiments demonstrate that PC\u0026ndash;PROCR signaling inhibits adipogenesis.\u003c/p\u003e\n\u003ch3\u003ePC activates HIF-1\u0026alpha; to inhibit adipogenesis\u003c/h3\u003e\n\u003cp\u003eNext, we investigated the molecular mechanisms by which PC\u0026ndash;PROCR signaling suppresses adipogenesis. As mentioned before, there are two forms of PC in the blood circulation system, inactive (PC) and active (aPC) proteins, and the latter one has experienced thrombin cleavage\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Although PC can inhibit adipocyte differentiation, surprisingly, we found that aPC exerts no effects on the differentiation of adipose progenitor cells (\u003cstrong\u003eFig.\u0026nbsp;4a-c\u003c/strong\u003e). Therefore, we performed transcriptomic analyses to identify factors that are altered specifically by PC treatment. PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e cells were pre-incubated with PBS control, PC, or aPC proteins for 24 hours, followed by RNA sequencing analysis. Upregulated differentially expressed genes (DEGs) in the PC group rather than the aPC group (|log2 fold change (FC)| \u0026ge; 1, adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were screened out to predict the regulated transcription factors using iRegulon analysis\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e (\u003cstrong\u003eFig.\u0026nbsp;4d\u003c/strong\u003e and \u003cstrong\u003eSupplementary Table\u0026nbsp;2\u003c/strong\u003e). After scoring transcriptional activity based on both the number of target genes and the strength of transcription factor binding, we identified a set of transcription factors that show upregulated transcriptional activity specifically in the PC group, with HIF-1\u0026alpha; being the top prominent (\u003cstrong\u003eFig.\u0026nbsp;4e\u003c/strong\u003e). Pathway enrichment analysis through Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) revealed that both PC and aPC proteins shared similar biological functions in regulating immune responses, consistent with previous studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, for instance, IL-17 signaling activity, NOD-like receptor signaling pathway, and cytokine-cytokine receptor interaction (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;3a, b\u003c/strong\u003e). Notably, we found that the HIF-1\u0026alpha; signaling activity was specifically upregulated in the PC group but not in the aPC group (\u003cstrong\u003eFig.\u0026nbsp;4f\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;3a, b\u003c/strong\u003e). Western blot analysis revealed the accumulation of total HIF-1\u0026alpha; protein in the PC treatment group (\u003cstrong\u003eFig.\u0026nbsp;4g, h\u003c/strong\u003e). Immunostaining results further validated that PC promoted nuclear HIF-1\u0026alpha; localization (\u003cstrong\u003eFig.\u0026nbsp;4i\u003c/strong\u003e), consistent with the enhanced transcription of its target genes (\u003cstrong\u003eFig.\u0026nbsp;4e, f\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eThe potential PC\u0026ndash;PROCR\u0026ndash;HIF-1\u0026alpha; axis was further validated \u003cem\u003ein vivo\u003c/em\u003e using the cKO model. iWAT samples of both groups were harvested 7 days after TAM injection, and then PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e precursor cells were FACS isolated and subjected to Western analysis (\u003cstrong\u003eFig.\u0026nbsp;4j)\u003c/strong\u003e. We found that \u003cem\u003eProcr\u003c/em\u003e-cKO cells indeed exhibit significantly lower HIF-1\u0026alpha; protein levels compared to controls (\u003cstrong\u003eFig.\u0026nbsp;4k, l\u003c/strong\u003e). Next, to determine whether HIF-1\u0026alpha; mediates the effects of PC in restraining adipogenesis, we utilized two distinct HIF-1\u0026alpha; inhibitors, IDF-11774 or TAT-cyclo-CLLFVY\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. We found that both inhibitors can attenuate the inhibitory effects of PC on adipocyte differentiation of PDGFR\u0026alpha;\u003csup\u003e+\u003c/sup\u003e precursor cells (\u003cstrong\u003eFig.\u0026nbsp;4m, n\u003c/strong\u003e). Together, these results indicate that the anti-adipogenic effects of PC\u0026ndash;PROCR signaling are, at least in part, mediated by the active HIF-1\u0026alpha;.\u003c/p\u003e\n\u003ch3\u003eAdipose hyperplasia and downregulated HIF-1\u0026alpha; signaling in lipedema\u003c/h3\u003e\n\u003cp\u003eNext, we investigated whether impaired adipogenesis and HIF-1\u0026alpha; signaling occur in the adipose tissues of \u003cem\u003ePROC\u003c/em\u003e-mutant lipedema patients. We conducted biopsies to the thigh subcutaneous adipose tissues (tSAT) of Patients 1 and 3 \u003cstrong\u003e(Fig.\u0026nbsp;5a\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;4a, b)\u003c/strong\u003e. Unexpectedly, despite excessive fat volume in patients (\u003cstrong\u003eFig.\u0026nbsp;1h-i\u003c/strong\u003e), histological analysis of tSAT revealed that the distribution of adipocyte sizes in patients was comparable to that from equivalent anatomical sites of respective sex- and age-matched healthy volunteers (\u003cstrong\u003eFig.\u0026nbsp;5b, c\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;4a, b\u003c/strong\u003e). This suggests an abnormal increase of adipocyte number (hyperplasia) rather than enlarged adipocyte size (hypertrophy) in lipedema. To gain more detailed insights into the pathogenic mechanisms, we performed single-nucleus RNA sequencing (snRNA-seq) on the tSAT samples from the patient and matched healthy volunteer. Integration of snRNA-seq data identified canonical cell types commonly found in human abdominal SAT\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, including adipose progenitor cells, preadipocytes, adipocytes, vascular cells, and immune cells (\u003cstrong\u003eFig.\u0026nbsp;5f\u003c/strong\u003e and \u003cstrong\u003eSupplementary Fig.\u0026nbsp;4c\u003c/strong\u003e). Notably, there was a significant decrease in the population of adipose progenitors (\u003cem\u003eCD55\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e) in parallel with an increase in the percentage of preadipocytes (\u003cem\u003eICAM\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e) and adipocytes (\u003cem\u003eADIPOQ\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e) in the \u003cem\u003ePROC\u003c/em\u003e-mutant patient compared to the healthy control (\u003cstrong\u003eFig.\u0026nbsp;5g\u003c/strong\u003e). These findings are consistent with the hyperplastic features of fat depot observed in morphological examinations (\u003cstrong\u003eFig.\u0026nbsp;5b, c\u003c/strong\u003e) and align with the results observed in conditional \u003cem\u003eProcr\u003c/em\u003e knockout mice (\u003cstrong\u003eFig.\u0026nbsp;3g-k\u003c/strong\u003e). To investigate the adipogenesis progress in lipedema, we conducted a computational pseudotime trajectory analysis of adipose progenitor cells, preadipocytes, and adipocytes. The results clearly depicted the progression of adipocyte differentiation from the progenitors to mature adipocytes, with the progenitors located at the root and adipocytes at the end of the differentiation process (\u003cstrong\u003eFig.\u0026nbsp;5h\u003c/strong\u003e). Importantly, cell cluster frequencies from the pseudotime trajectory analysis revealed a higher prevalence of progenitors transitioning into adipocytes in the patient (\u003cstrong\u003eFig.\u0026nbsp;5i\u003c/strong\u003e). Furthermore, the expression levels of key adipogenic genes, such as \u003cem\u003ePPARG\u003c/em\u003e, \u003cem\u003eFABP4\u003c/em\u003e (\u003cem\u003eaP2\u003c/em\u003e), and \u003cem\u003eADIPOQ\u003c/em\u003e (\u003cem\u003eAdiponectin\u003c/em\u003e), were significantly increased in the patient, providing additional evidence of enhanced adipogenesis in lipedema patients (\u003cstrong\u003eFig.\u0026nbsp;5j\u003c/strong\u003e). Finally, to investigate the molecular property of adipose progenitor cells harboring \u003cem\u003ePROC\u003c/em\u003e mutations, we performed GSEA analysis and found that genes downregulated in response to both hypoxia and overexpression of HIF-1\u0026alpha;\u003csup\u003e34\u003c/sup\u003e were enriched in the patient; conversely, genes upregulated in response to hypoxia mimetic compound\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e were enriched in the control group (\u003cstrong\u003eFig.\u0026nbsp;5k\u003c/strong\u003e), suggesting the impaired HIF-1\u0026alpha; signaling occurring in the patient with \u003cem\u003ePROC\u003c/em\u003e mutations. This observation reinforces the findings that HIF-1\u0026alpha; acts as a key downstream effector of PC\u0026ndash;PROCR signaling in suppressing adipogenesis (\u003cstrong\u003eFig.\u0026nbsp;4m, n\u003c/strong\u003e, and \u003cstrong\u003eFig.\u0026nbsp;5i\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLipedema is a hereditary disorder that is characterized by excessive subcutaneous adipose tissue deposition. In this study, we investigated genetic causes and underlying mechanisms leading to lipedema using pedigree genetics in combination with deep genome sequencing and biopsy tissue snRNA-seq, gene knockout and fate-tracing mouse models, and \u003cem\u003ein vitro\u003c/em\u003e adipocyte differentiation. We found that compound heterozygous mutations in the \u003cem\u003ePROC\u003c/em\u003e gene co-segregated with lipedema in two non-consanguineous Chinese families, demonstrating an autosomal dominant inheritance pattern. This provides compelling evidence that \u003cem\u003ePROC\u003c/em\u003e mutations are the first disclosed genetic cause for the disease. Furthermore, our functional and mechanistic studies revealed an unknown PC\u0026ndash;PROCR\u0026ndash;HIF-1α regulatory axis in suppressing adipogenesis. PC, a secreted protein encoded by \u003cem\u003ePROC\u003c/em\u003e, likely targets PROCR-expressing adipocyte progenitors to promote HIF-1α accumulation, thus inhibiting adipocyte differentiation. This work demonstrates the critical role of PC in blocking adipogenesis, offering novel insights into the pathogenesis of lipedema.\u003c/p\u003e \u003cp\u003ePC has traditionally been recognized for its anti-coagulation role\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. A variety of heterozygous \u003cem\u003ePROC\u003c/em\u003e mutations that damage the activation of PC has been identified in patients with venous thrombosis\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This study reveals a novel function of PC in inhibiting the differentiation of adipose progenitor cells. This function of PC primarily relies on its cell surface receptor, PROCR, which is specifically expressed in the progenitor cells of adipose tissues. Intriguingly, our \u003cem\u003ein vitro\u003c/em\u003e experiments indicate that the PC zymogen (inactive PC), but not the activated PC (aPC), can transduce signaling to activate HIF-1α, thereby suppressing adipogenesis. Although the concentrations of PC in circulation are approximately 1000 times higher than those of aPC, the biological roles of PC have not been fully explored. Our study here uncovers an unexpected function of the abundant PC zymogen in the regulation of adipogenesis.\u003c/p\u003e \u003cp\u003eAlign with previous studies demonstrating HIF-1α signaling in the control of adipogenesis\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, our work implicates HIF-1α as the downstream mediator of PC\u0026ndash;PROCR signaling in a subpopulation (PDGFRα\u003csup\u003e+\u003c/sup\u003ePROCR\u003csup\u003e+\u003c/sup\u003e) of adipose precursor cells. PC (but not aPC) can active HIF-1α in these precursor cells; consistently, \u003cem\u003ePROCR\u003c/em\u003e deletion reduces their HIF-1α activity. Furthermore, inhibition of HIF-1α activity abolishes PC's ability to inhibit adipocyte differentiation, in line with impaired HIF-1α activity in the progenitor cells of tSAT of the patient carrying \u003cem\u003ePROC\u003c/em\u003e mutants.\u003c/p\u003e \u003cp\u003eAs an aspect of pathophysiology, very few studies have provided evidence of adipocyte hyperplasia in lipedema\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Our morphological examinations and snRNA sequencing of biopsied tSAT revealed enhanced adipogenesis, contributing to hyperplasia rather than hypertrophy in lipedema. Furthermore, our results demonstrated that the PC\u0026ndash;PROCR\u0026ndash;HIF-1α pathway physiologically inhibits the differentiation of adipose progenitors into mature adipocytes, thus suppressing excessive hyperplasia and fat expansion. In support of our findings, a recent genome-wide proteomics study revealed that the \u003cem\u003ePROCR\u003c/em\u003e gene is strongly associated with body fat distribution (upper trunk to lower body)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. More recently, a population of PROCR high-expressing mesenchymal progenitors was identified in the adventitial layer of human blood vessels, which are capable of both osteogenesis and adipogenesis \u003cem\u003ein vitro\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Based on these observations, we postulate that loss-of-function mutations or abnormal downregulation in PROCR and HIF-1α might also be involved in the development of lipedema, implying additional causes for those without a definite genetic etiology.\u003c/p\u003e \u003cp\u003eIn conclusion, we identified compound heterozygous mutations in \u003cem\u003ePROC\u003c/em\u003e as the first genetic cause of excessive fat expansion in the lower body of lipedema patients. Further elucidation of PC\u0026rsquo;s anti-adipogenic function relies on its receptor, PROCR, which marks a subpopulation of adipose progenitors. In the future, the development of drugs targeting the PC\u0026ndash;PROCR\u0026ndash;HIF-1α pathway may provide potential therapeutic options for lipedema, for which no effective treatment currently exists\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients and their families, as well as healthy volunteers, for participating in this study, and we thank Prof. Chi-Chung Hui from the University of Toronto for his valuable suggestions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Key Research and Development Program of China (2022YFC2505201 to J.W.; 2020YFA0509002 to Y.A.Z.; 2021YFA1301103 to J.W.), the National Natural Science Foundation of China (U24A20675, 82088102, 92457302, 92157204, 82250901 and 91957124 to J.W.), Shanghai Municipal Science and Technology Commission (22JC1402202 to Y.A.Z.), the Innovative research team of high-level local universities in Shanghai, Shanghai Municipal Education Commission (2023ZKZD22 to J.W.), Shanghai Outstanding Academic Leaders Plan of Shanghai Municipality (LJ2023078 to J.W.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.W. and Y.A.Z. conceived and supervised the study. W.G. and B.G. collected the clinical data of pedigrees. M.N. and R.Y. performed the experiments. J.W., M.N. and R.Y. wrote the manuscript. B.Y. and Q.B contributed to the healthy control adipose tissue collection (lower body). H.X. contribute to adipose tissue collection (upper and lower body). Q.D. contribute to clinical data of family 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWold, L.E., Hines, E.A., Jr. \u0026amp; Allen, E.V. 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The genetic causes and mechanisms underlying abnormal adipocyte expansion in lipedema, however, remain unknown. Here, we identify compound heterozygous mutations in the \u003cem\u003ePROC\u003c/em\u003e gene in three lipedema patients from two unrelated consanguineous families. \u003cem\u003eIn vitro\u003c/em\u003e studies demonstrate the wild-type Protein C (PC), encoded by \u003cem\u003ePROC\u003c/em\u003e, plays an inhibitory role in adipogenesis; conversely, the identified PC mutants, p.R271Q and p.R272H, fail to inhibit this process. In mice,\u003cem\u003e \u003c/em\u003ethe receptor of PC (PROCR) marks adipocyte progenitors, and\u003cem\u003e \u003c/em\u003econditional deletion of \u003cem\u003ePROCR\u003c/em\u003e in these cells leads to an increased number of newborn adipocytes within white adipose tissue (WAT). Transcriptomic analysis alongside chemical blockage tests identifies HIF-1α as a primary downstream transcription factor mediating PC–PROCR signaling in adipogenesis. Furthermore, adipose biopsy samples from the patients’ thighs exhibit hyperplastic expansion of adipocytes, while single-nucleus RNA sequencing confirms increased adipogenic capacity and down-regulated HIF-1α activity in affected subjects. These findings establish \u003cem\u003ePROC \u003c/em\u003eas the first causal gene for human lipedema and unveil a previously unexpected role of the PC–PROCR axis in orchestrating adipogenesis.\u003c/p\u003e","manuscriptTitle":"Compound heterozygous PROC mutations cause lipedema in humans","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-07 09:57:51","doi":"10.21203/rs.3.rs-5876962/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"325fd861-3d92-487a-82f5-6757afe52e39","owner":[],"postedDate":"February 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43709317,"name":"Biological sciences/Developmental biology/Stem cells"},{"id":43709318,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2025-02-19T14:51:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-07 09:57:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5876962","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5876962","identity":"rs-5876962","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}