The formation of atherosclerotic plaques is one of the main sources of cardiovascular disease. In addition to known risk factors such as dyslipidemia, diabetes, obesity, and hypertension, endothelial dysfunction has been shown to play a key role in the formation and progression of atherosclerosis. Peroxisome proliferator-activated receptor-gamma (PPARγ), a transcription factor belonging to the steroid superfamily, is expressed in the aorta and plays a critical role in protecting endothelial function. It thereby serves as a target for treating both diabetes and atherosclerosis. Although many studies have examined endothelial cell disorders in atherosclerosis, the role of PPARγ in endothelial dysfunction is still not well understood. In this review, we summarize the possible mechanisms of action behind PPARγ regulatory compounds and post-translational modifications (PTMs) of PPARγ in the control of endothelial function. We also explore the potential use of endothelial PPARγ-targeted agents in the prevention and treatment of atherosclerosis. Endothelial dysfunction plays important roles in atherosclerosis initiation and progression. Atherosclerosis poses a major threat to human health and is one of the leading causes of morbidity and mortality in type 2 diabetes (T2DM) patients ,2. Much Peroxisome proliferator-activated receptor gamma (PPARγ), a nuclear receptor of the steroid superfamily, is a potent target for counteracting risk factors of atherosclerosis. Thiazolidinediones (TZDs), synthetic ligands of PPARγ, have been shown to reduce the incidence of atherosclerosis . PPARγ hPPARγ, increasing attention has been directed towards these PTMs [PPARγ can be regulated by altering the activity of PPARγ or modulating its downstream pathways. With regard to the former, the bioactivity of PPARγ can be regulated by ligands that bind to peroxisome proliferator response elements (PPREs), the corepressor complex, and the co-activator complex through different domains ,23. PPARese PTMs ,25,26,27The cardiovascular system is responsible for distributing nutrients and oxygen throughout the body , and oneIn terms of physiologic function, the endothelial barrier is responsible for the exchange of substances entering or exiting the blood ,34. The ECs also play critical roles in maintaining the appropriate hemostasis by interacting with coagulation and fibrinolytic system . ActivatSimilarly, certain substances in the blood are involved in regulating the vascular function of endothelium. For example, high levels of Thyroid Stimulating Hormone (TSH) in blood can trigger excessive opening of the mitochondrial permeability transition pore as well as increased mitochondrial oxidative damage in ECs . BlockinECs secrete connective tissue components, collagen molecules, proteoglycans, and elastin to regulate cell-to-cell or matrix binding, which plays an important role in the stability of early plaques. However, with progressive age, rupture of collagen fibers and degradation of the extracellular matrix occurs, resulting in plaque rupture and subsequent cardiovascular events. Reducing monocyte adhesion to the aortic endothelium and modulating levels of vascular cell adhesion molecules have demonstrated beneficial effects ,50.The function of ECs can be evaluated by testing the impairment of vascular dilation with acetylcholine ,52, and Atherosclerosis is widely recognized as a chronic inflammatory disease ,56. PlaqThe term “endothelial dysfunction” can be used to refer to the impairment of vascular function caused by abnormal production or activity of endothelium-derived NO . Here, hPPARγ has several PTM patterns, including phosphorylation, SUMOylation, and acetylation . These PPPARγ is involved in several molecular pathways that promote endothelial function , as outlPhosphorylation and inactivation of PPARγ is directly catalyzed by extracellular regulated protein kinase 1/2 (ERK1/2), a pro-inflammatory kinase . FurtherNO production and eNOS activity also play integral roles in the effect of PPARγ on endothelial function ,69,70,71PPARγ participates in the recruitment of leukocytes; in particular, recruitment of monocytes to activated vascular ECs is a critical step in the inflammatory cascade . PPARγ a2O2-induced injury [NF-κB is involved in PPARγ-mediated endothelial protection ,81,82,83d injury . Susceptd injury .Lectin-like receptor for oxidized LDL (LOX-1), located on the membrane of ECs, can recognize oxLDL, TNFα, and other stimuli, and plays an important role in the progression of atherosclerosis ,86. In bOther mechanisms of endothelial protection by PPARγ have been identified, including its role in apoptosis. Upregulation of PPARγ was found to induce the upregulation of p53 and promote apoptosis of HUVECs . Activat−/−) mice, endothelial PPARγ demonstrated anti-inflammatory and hypopermeability properties, thereby contributing to a protective effect against atherogenesis [Furthermore, gene knockout and overexpression techniques have facilitated research efforts into the endothelial-protective role of PPARγ. In a comparison between endothelial-specific and macrophage-specific PPARγ disruption in LDL receptor-knockout  signal pathway, thus producing anti-inflammatory effects . BerberiNotoginsenoside Fc, ginsenoside-Rb1, and 7,8-didehydrocimigenol  are members of the saponin and triterpene class. Notoginsenoside Fc was found to attenuate high glucose (HG)-induced EC injury through the inhibition of pro-inflammatory cytokines and apoptosis as well as increased PPARγ proliferation in rat aortic ECs . ActivatGenistein and formononetin are examples of isoflavones. Genistein inhibits monocyte adhesion to the endothelium via PPARγ and the physical forces associated with blood flow, rather than by regulating the expression of adhesion molecules . Activat2-methoxyestradiol and urolithin A(UA) are biological metabolites. 2-methoxyestradiol is an endogenous estradiol metabolite with antiatherogenic properties. This molecule has been found to promote the release of NO primarily through the PPARγ/PI3K/Akt/eNOS cascade, thereby encouraging endothelial-dependent vasodilation . UA, an Dual PPARα/γ agonists include TAK-559 and conjugated linoleic acid ,109. TAKThis category consists of compounds that do not fall into any of the aforementioned groups.15-deoxy-Delta -prostaglandin J2 (15d-PGJ2) is a prostaglandin that is a strong, naturally existing PPARγ agonist . 15d-PGJTelmisartan, an angiotensin II-receptor blocker (ARB), was recently reported to have PPARγ partial agonist properties ,70. TelmKR-62980, a new PPARγ agonist, impaired angiogenesis in HUVECs and promoted apoptosis through PPARγ-mediated downregulation of VEGF receptor 2 (VEGFR-2) and upregulation of chromosome 10 (PTEN) .Tert-Butylhydroquinone is an activator of Nrf2 that may increase the expression of eNOS by up-regulating the transcription and translation of PPARγ, subsequently increasing endothelial NO production .Magnolol is a dual agonist of RXRα and PPARγ. In cultured HUVECs, incubation with magnolol enhanced the release of NO and promoted insulin-induced vasodilation through the PPARγ-dependent Akt/eNOS/NO cascade .Cyclic phosphatidic acid (cPA) potentially inhibits neointima formation by attenuating VEGF-mediated growth and migration through upregulation of the cPA-PPARγ axis in human coronary artery ECs from patients with diabetes .1,8-Cineole may protect the endothelium from inflammatory infiltration by upregulating PPARγ expression and inhibiting NF-κB p65 phosphorylation .Carbon monoxide derived from CO-releasing molecule-2 (CORM-2) exhibited anti-atherogenic effects through attenuation of HG-induced endothelial ICAM-1 via the AMPK/PPARγ pathway .Simvastatin, a member of the statin class, demonstrated benefits in maintaining thrombotic homeostasis of saphenous vein ECs challenged by advanced glycation endproducts. Decreased PPARγ expression was significantly improved by simvastatin in saphenous vein ECs from non-diabetic patients in vitro. There was also a slight, but not statistically significant, increase in PPARγ expression in ECs obtained from diabetic patients treated with simvastatin .PTMs of PPARγ play critical roles in finely regulating its activity. PTMs of PPARγ, such as acetylation, phosphorylation, and SUMOylation, are known to regulate glucose and lipid metabolism ,27. Here−/− mice [PPARγ acetylation regulates PPARγ activity, and the dynamics of acetylation are disturbed in obesity and aging . PPARγ i−/− mice ,124. Thi−/− mice . PPARγ d−/− mice . Adminis−/− mice . As suchSUMOylation is another PTM that can selectively regulate PPARγ activity. PPARγ-K107R-mutant mice (K107R prevents SUMOylation) were found to have increased insulin sensitivity without the associated increase in adiposity that typically accompanies TZD treatment . DeSUMOyGiven the importance of PPARγ in EC dysfunction and the role of EC disorders in atherosclerosis progression, it is essential that we understand the mechanisms behind PPARγ signaling in endothelial function. This can serve as a springboard for the development of novel PPARγ-targeted drug therapies in the future. Furthermore, understanding how PPARγ-modulating compounds and PTMs alter EC function may aid in identifying new therapeutic targets, such as deacetylation or deSUMOylation processes.A PTM we did not cover in this review is PPARγ phosphorylation, as few studies have been conducted on this topic and its significance remains unclear. Based on existing studies, PPARγ phosphorylation at various sites has demonstrated a range of glucose and lipid metabolic effects. For example, phosphorylation at S273 by cyclin-dependent kinase 5 (CDK5) has been shown to increase proinflammatory factors including TNF-α, IL-1β, and foam cell formation, which worsen atherosclerosis . Both PPTo conclude, we can reasonably anticipate: (1) The use of next-generation sequencing technologies, such as RNA sequencing, and other omics techniques to further evaluate the molecular basis of PPARγ regulation of EC dysfunction in the context of atherosclerosis. This will allow us to establish a more comprehensive regulatory network incorporating upstream and downstream targets of PPARγ. (2) There is growing evidence that selective activation of PPARγ may reveal novel therapeutic targets for future generations of drugs in the treatment of both T2DM and atherosclerosis, and PTMs of PPARγ have shown great potential in this regard. (3) Given the many different PTMs and regulatory sites of PPARγ, along with their apparent involvement in EC dysfunction, increasing attention will continue to be directed towards PPARγ regulation in other metabolic and cardiovascular diseases.


Analysis of legumain mutant zebrafish shows a requirement for early ECM remodeling and efficient ligament regeneration. Our study establishes a new model of adult scar-free ligament regeneration and highlights roles of immune-mesenchyme cross-talk in ECM remodeling that initiates regeneration.After traumatic injury, healing of mammalian ligaments is typically associated with fibrotic scarring as opposed to scar-free regeneration. In contrast, here we show that the ligament supporting the jaw joint of adult zebrafish is capable of rapid and complete scar-free healing. Following surgical transection of the jaw joint ligament, we observe breakdown of ligament tissue adjacent to the cut sites, expansion of mesenchymal tissue within the wound site, and then remodeling of extracellular matrix (ECM) to a normal ligament morphology. Lineage tracing of mature ligamentocytes following transection shows that they dedifferentiate, undergo cell cycle re-entry, and contribute to the regenerated ligament. Single-cell RNA sequencing of the regenerating ligament reveals dynamic expression of ECM genes in neural-crest-derived mesenchymal cells, as well as diverse immune cells expressing the endopeptidase-encoding gene  Healed ligaments fail to recapitulate the highly organized structure of the uninjured tissue. Foundational research using non-regenerative models has highlighted that the failure to regenerate ligaments without scarring is common among mammals5. Early studies investigating repair of the medial collateral ligament (MCL) following rupture showed that the healed ligament undergoes more deformation under the same load, coincident with disorganization of the collagen fibers at the wound site6. The first 10 days of ligament healing in mammals are characterized by an invasion of fibroblasts, vasculature, and pro-inflammatory immune cells along the ligament7. While ligament repair continues for 14 weeks, an incomplete remodeling of both the cellular and extracellular matrix (ECM) composition occurs, ending with a fibrotic scar bridging the injury. Similarly, in human and murine tendon and ligament injuries, the stubs are bridged by α-Smooth Muscle Actin-positive scarring myofibroblasts11. Notably, these myofibroblasts do not express tendon and ligament marker Scleraxis (Scx), indicating that they are not true ligamentocytes8. Existing studies on adult connective tissue injury highlight the importance of the reestablishment of cell fate and ligament ECM through regeneration.Ligament injuries typically heal with biomechanically inferior scar tissue that compromises joint stability and increases the risk of developing painful and debilitating osteoarthritis8. In this neonatal repair context, Scx-positive tenocytes retain their developmental potency to proliferate, migrate to the wound site, and heal without forming a fibrotic scar8. Further studies on developmental regenerative potential have been performed using juvenile zebrafish, which described that BMP-dependent activation of perichondrial progenitors is necessary for tendon regeneration after tendon cell ablation injury12. However, while these models interrogate scar-free tendon regeneration in the context of development, there are currently no models to study scar-free ligament regeneration in mature adult ligaments. To address this need, we utilized the highly regenerative zebrafish, as they are a well-established model for heart, spinal cord, and tail fin regeneration15 and moreover possess regenerative synovial joints supported by ligaments18.Recent advances in tendon injury modeling showed that neonatal mice are capable of scar-free regeneration after Achilles tendon transection18. Here we characterize the cellular and molecular events underlying the three overlapping phases of ligament healing: inflammation, proliferation, and remodeling. We also used single-cell RNA sequencing (scRNAseq) to characterize the dynamics of cell populations during regeneration and identified legumain (lgmn) as a gene highly enriched in macrophages that invade the injury site. Legumain is a member of the C13 family of cysteine proteases that regulate ECM factors such as cathepsins, fibronectin1 (Fn1), and matrix metalloprotease-2 (MMP-2)20. Through injury analyses in a zebrafish mutant for lgmn, we uncovered an essential role in regulating ECM remodeling and scar-free ligament regeneration. Our findings highlight the important role of immune-mediated ECM remodeling for successful scar-free regeneration.In the course of establishing a post-traumatic osteoarthritis model, we had observed rapid regeneration of the craniofacial interopercular-mandibular (IOM) ligament, which supports the zebrafish jaw joint, following complete transection in one-year-old fishThe IOM ligament connects the interopercular bone to the retroarticular bone of the mandible to control movement of the zebrafish jaw joint. Following complete transection of the IOM ligament in adult zebrafish, a time-course of histological analysis revealed dynamic morphological changes during ligament regeneration Fig. . The uniscxa:mCherry transgenic line. In these fish, mCherry expression is driven by the regulatory region surrounding the scleraxis a (scxa) gene, which encodes a transcription factor highly expressed in ligament and tendon cells22. In uninjured adults, live imaging revealed scxa:mCherry fluorescence in each of the bilateral IOM ligaments  sequencing data of zebrafish cranial neural crest-derived cells24 identified a 635 bp region within intron 13 of the thrombospondin 4a (thbs4a) gene that was selectively accessible in the tendon and ligament cluster  to DsRed fluorescent protein -inducible CreERT2 (thbs4a_p1:CreERT2) in combination with the ubiquitously-expressed actb2:loxP-BFP-STOP-loxP-DsRed reporter. Treatment of adult double transgenic fish with 3 doses of 4-OHT resulted in DsRed fluorescence throughout the IOM ligaments  and collagen 12 alpha 1a (col12a1a), which label injury mesenchyme in zebrafish spinal cord and heart regeneration28. While fn1a is minimally expressed in the uninjured ligament, we see abundant fn1a transcripts in DsRed+ thbs4a-lineage cells in both the injured ligament stubs, as well as in the bridging regenerative mesenchyme . These data support typically quiescent ligamentocytes re-entering the cell cycle upon injury and contributing to the regenerated ligament.In addition, we observed extensive proliferation, based on immunofluorescence staining for Proliferating Cell Nuclear Antigen (PCNA), within both the regenerative mesenchyme and ligament stubs adjacent to the transection site. Compared to only minimal PCNA+ cells prior to injury and at 1 dplt, 39% of cells within the ligament stub domain and 47.5% cells within the regenerative mesenchyme domain were PCNA+ at 3 dplt  on micro-dissected IOM ligaments, including adjacent joint and mesenchymal tissues, before and during early stages of regeneration. We used FACS in ent Fig. . After pkrt5+), superficial cells , and mucosal cells   and macrophages , and Immune 2 cluster consisted primarily of neutrophils . We also detected an endothelial cluster . Two superclusters, enriched for DsRed+ cells  or the chondrocyte genes col2a1a and mia (NC-Derived 2) , and endothelial cells Fig. . Epithellls Fig. , represe 2) Fig. .ifitm5+), chondrocytes (col2a1a+), superficial chondrocytes and synoviocytes (prg4b+), ligamentocytes , two types of dermal fibroblasts (pah+), periosteal cells (mmel1+), three types of stromal cells , and glial cells (mbpa+)24  and fibronectin 1a (fn1a) , a marker of pro-scarring fibroblasts in mammals. These data are consistent with regenerative mesenchyme cells producing new ligamentocytes as opposed to scar tissue during regeneration.Re-clustering of the two neural crest-derived superclusters revealed clusters of osteoblasts , macrophages (mpeg1.1+/mfap4+), dendritic cells (mpeg1.1+/mfap4-), two types of T helper cells (il21r.2+ or il4+), proliferative cells (mki67+), and four types of lymphocytes (lck+), including two T cell-containing clusters (cd8a+), NK cells (s1pr5a+)29, and activated NK cells (ifng1+/gzmk+)  Fig. . The Neumpeg1.1+/mfap4+ macrophage cluster, we noted a subpopulation of macrophages with enriched composition of 1 dplt cells and selective expression of fn1a   are anatomically similar to wild types with no overt differences in the gross morphology of their uninjured ligaments  Fig. . Homozygnts Fig. . To charnts Fig. . In wildlgmn mutants, we first measured apoptosis and proliferation using TUNEL and PCNA immunofluorescence assays, respectively. After transection in wild types, we observed 7.4% TUNEL+ ligamentocyte nuclei at 1 dplt and 2.5% TUNEL+ at 3 dplt  and a trend toward lower proliferation in ligament tissue adjacent to the transection site (p = 0.4660)  Fig. .lgmn mutants, we first quantified neutrophils at 1 and 3 dplt using immunofluorescence for the neutrophil marker, Mpx   were immunostained for eGFP and PCNA. At 1 dplt, we observed that ligamentocytes within the ligament stub re-enter the cell cycle without coincident macrophages 51, Tg(actab2:loxP-BFP-STOP-loxP-dsRed)sd2752, Tg(Mmu.Sox10-Mmu.Fos:Cre)zf38453, Tg(mpx:mCherry)uwm754, and Tg(mpeg1:EGFP)gl2255. Embryos were raised in a methylene blue salt solution at 28.5 °C. Juvenile and adult fish were housed in groups of 15-30 individuals. All surgical injuries were performed in size-matched 3-6 months post fertilization (mpf) adult zebrafish using standard body length (SL) measurements.The Institutional Animal Care and Use Committees of Columbia University and the University of Southern California approved all zebrafish experiments. Published Zebrafish lines used in this study include lgmnsa22350 mutant allele containing a G > T point mutation resulting in a premature stop codon was used to generate homozygous lgmn mutants (referred to as lgmnMUT). Zebrafish were genotyped by PCR with primers flanking intron 1 (lgmn forward primer: AGATCTTATGATCCCAGATCCAATGACT) and end of exon 2 (lgmn reverse primer: GGTGAGAAAATGAAACCCGAAACTAGTCT). The 500 bp PCR product was digested with NspI  that recognizes a RCATG/Y cut site only present in mutants. Mutant alleles were then identified by presence of the cleaved 358 bp and 142 bp bands.Tg(thbs4a_p1:CreERT2)el913 and Tg(thbs4a_p1:eGFP)el912 alleles were generated using Gateway cloning and Tol2 transgenesis. p5E plasmid including the 635 bp thbs4a_p1 enhancer and minimal E1B promoter sequence was generated using synthesized gBlock DNA (IDT) in a BP cloning reaction (see Supplementary Methods thbs4a_p1 gBlock sequence). The thbs4a_p1:eGFP transgene was generated by combining p5E-thbs4a_p1:E1B, pME-eGFP, p3E-polyA, and pDestTol2AB2. The thbs4a_p1:CreERT2 transgene was generated by combining p5E-thbs4a_p1:E1B, pME-CreERT2, p3E-polyA, and pDestTol2CG2. Transgenes were injected into one-cell stage zebrafish embryos at 30 ng/ul plasmid DNA with 50 ng/ul Tol2 mRNA. Injected F0 animals were raised to adulthood and outcrossed to Tübingen or Tg(actab2:loxP-BFP-STOP-loxP-dsRed)sd27 animals. F1 founders were screened for the presence of eye CFP (thbs4a_p1:eGFP) or heart GFP and successful 4-OHT conversion in progeny (thbs4a_p1:CreERT2), respectively.The gthbs4a_p:CreERT2e18. Briefly, adult zebrafish were anesthetized with Tricaine MS-222 and restrained in a damp sponge. Using 3-mm Vannas spring scissors , the IOM ligament was severed with a single cut and a pull test performed on the IOP bone to confirm transection. Fish were then revived in clean system water, housed on-system, and received daily post-operative health checks for three days. At experimental endpoints, zebrafish were euthanized using a lethal dose of Tricaine MS-222 with rapid chilling on ice.Interopercular-mandibular (IOM) ligament transection surgery was adapted from Smeeton et al.Adult zebrafish samples were fixed in 4% PFA at 4 °C overnight. Following fixation, samples were washed twice for 30 minutes in 1xPBS and cut to facilitate embedding and sectioning of the head. Samples were decalcified in 0.5 M EDTA solution for 10 days rocking at room temperature. For embedding, the tissue was dehydrated in 20 min increments with a series of ethanol dilutions . The water was then replaced with Hemo-De Xylene Substitute  in a series  of 15 min washes. Then the samples were incubated in a 1:1 Hemo-De:Paraffin solution at 65 °C for an hour before overnight incubation in 100% paraffin at 65 °C. Samples were then embedded in freshly melted paraffin. Paraffin sectioning was performed using Thermo HM355S automatic microtome to collect 5 μm sections.For AFOG staining, 5μm paraffin sections were deparaffinized with Hemo-De and re-hydrated through an ethanol series  diluted with water. Sections were then fixed in 4% PFA for 5 min at RT, then washed 3x for 5 min with 1xPBS and then washed 1x for 5 min in water. Following washes, samples were incubated in Bouin’s solution  that was preheated to 60 °C for 2-hours and cooled to room temperature for another hour. Slides were then washed 5-6x for 5 min with water and then rinsed in 1% Phosphomolybdic acid  for 10 min and rinsed in water for 5 min. Slides were then incubated in AFOG staining solution  for 7 min at RT and then rinsed 1x for 2 min with water. Samples were dehydrated with a series of ethanol dilutions  and 1x in Hemo-De for 5 min before mounted with Cytoseal .For Toluidine Blue/Fast Green staining, zebrafish tissue was fixed and paraffin-embedded according to the aforementioned paraffin embedding protocol. Paraffin blocks were sectioned using HM 355 S automated microtome and MX35 microtome blades at 5μm. Sections were floated in DEPC-treated water  in a waterbath and collected onto Leica adhesive slides, then allowed to air dry at room temperature at least overnight. Slides were then processed for toluidine blue staining with the following procedure: two 5-minute washes in xylene substitute Hemo-De, two 1-minute washes in 100% ethanol; serial washes  in EtOH/H2O for 1 minute per wash; and three 1-minute washes in tap water. Slides were then placed in 0.04% toluidine blue solution  for 10 minutes, followed by three 1-minute washes in tap water. Slides were then placed in 0.1% fast green solution  for 3 minutes, followed by three 1-minute washes in tap water. Stained slides were then given two 1-minute washes in 100% isopropanol and two 1-minute washes in Hemo-De. Lastly, coverslips were mounted on the slides using CytoSeal and allowed to air dry for 30 minutes to overnight.56) for use with zebrafish. Whole adult zebrafish were fixed overnight in the dark at 4 °C in 4% PFA. Tissue was then washed twice in PBS for at least 30 minutes per wash and heads were separated from the trunk of the body. At a ratio of 5 zebrafish heads per 50 mL of solution, tissue was incubated in the dark at 37 °C in CUBIC-1 solution with gentle rocking for at least 3 days. Tissue was then transferred to new CUBIC-1 to incubate until tissue was transparent and iridophores were cleared (2-4 days). Tissue was then washed twice in PBS for at least 30 minutes per wash, then immersed in 20% sucrose in PBS at room temperature until tissue was no longer floating in solution and once again opaque, 2 hours to overnight. Lastly, the tissue was immersed in CUBIC-2 solution and incubated in the dark at room temperature with gentle rocking for at least 1 day before imaging. Fluorescent microscopy images were captured using a Leica SP8 confocal microscope and processed in Fiji. CUBIC-1 was prepared as a mixture of 25 wt% urea, 25 wt% N,N,N’,N’-tetrakis(2-hydroxypropyl) ethylenediamine  and 15 wt% Triton X-100. To minimize water evaporation, solution was prepared with heat not exceeding 100 °C and inside bottles with caps just screwed on. Deionized water was heated prior to the addition of urea. Once urea was dissolved and the solution was no longer cold, N,N,N’,N’-Tetrakis(2-hydroxypropyl)ethylenediamine was mixed until homogenous. Solution was removed from heat and allowed to cool to room temperature, then Triton-X-100 was added with gentle stirring to minimize the production of bubbles. CUBIC-1 solution was stored in the dark at room temperature and used within 1 week.CUBIC tissue clearing protocol was adapted from , and 0.1% (v/v) Triton X-100. To minimize water evaporation, solution was prepared with heat not exceeding 100 °C and inside bottles with caps just screwed on. Deionized water was heated prior to the addition of urea. Once urea was dissolved and the solution was no longer cold, 2,2′,2′′-Nitrilotriethanol was mixed until homogenous. Sucrose was mixed with continued heat until the solution was clear with a pale yellow tint. Solution was removed from heat and allowed to cool to room temperature, then Triton-X-100 was added with gentle stirring to minimize the production of bubbles. CUBIC-2 solution was stored in the dark at room temperature and used within 1 week.We collected 5μm formalin-fixed paraffin-embedded (FFPE) tissue sections. For immunofluorescence, sections were deparaffinized with Hemo-De and rehydrated through an ethanol series, then subjected to antigen retrieval in sodium citrate buffer, blocked with Agilent Dako protein block (cat. X090930-2), and incubated with primary antibody   ,  overnight at 4 °C, washed, and incubated with secondary antibody . TUNEL staining was performed as per manufacturer’s instructions using the Apoptag Fluorescein In Situ Apoptosis Detection Kit . Slides were mounted and counterstained with Fluoromount-G + DAPI . Single-molecule fluorescence in situ hybridization was performed on 5μm FFPE sections according to manufacturer guidelines using RNAScope Multiplex Fluorescent Reagent Kit v2 Assay (ACD Bio). Slides were treated with 1x Target Retrieval Reagent for 4 min in a steamer. RNAScope probes used were Dr-acta2 (508581-C4), Dr-col12a1a (556481-C2), DsRed-C2 (481361-C2), Dr-fn1a (1097911-C1), Dr-scxa (564451), Dr-lgmn (1003381-C2), Dr-mpeg1.1 (536171-C3), and Dr-thbs4a (812151) from ACD Bio. Opal 520, 570, and 690 fluorophores were used to visualize expression . Sections were counterstained and mounted with Fluoromount-G + DAPI.thbs4a_p1:CreERT2 zebrafish lines were converted with three 5 µM (Z)-4-Hydroxytamoxifen, ≥98% Z isomer  overnight treatments in the dark. Following drug treatment, adults were screened for conversion using Leica M165FC stereo microscope and then washed 2 ×1 hour in system water before being re-housed on-system.Adult n = 22 joints per 1 dplt and 3 dplt time points), sham surgery (n = 22 joints per 1 d and 3 d time point) was performed on size-matched Sox10Cre;actb2:loxP-BFP-loxP-DsRed fish at 3-4 mpf. The jaw joint region of each fish and uninjured control (25 joints) was microdissected and incubated in protease solution  with mechanical dissociation by nutation and agitation with a P1000 pipette every 5 min for 1 h at 28 °C. Cells were FACS sorted and immediately processed to create single-cell RNA Sequencing libraries using the Chromium Single Cell 3′ Library & Gel Bead Kit v2 (10X Genomics), according to the manufacturer’s recommendations. To determine cell count, libraries were sequenced at the CHLA Center for Personalized Medicine Genomics Core using a MiSeq Nano v2  with 26 bp sequencing for Read1, 8 bp sequencing for Index1, and 120 bp sequencing for Read2. Libraries were pooled for even coverage per cell and were sequenced at the CHLA Center for Personalized Medicine Molecular Genomics Core on the NextSeq 550  with 26 bp sequencing for Read1, 8 bp sequencing for Index1, and 120 bp sequencing for Read2. All samples were sequenced to an average read depth of greater than 130,000 reads per cell. CellRanger v3.0.0 (10X Genomics) was used with default parameters for alignment to GRCz11 to generate gene-by-cell count matrices.Ligament transection (p < 0.05). Principal components 1-68 were used for K-nearest-neighbor graph construction (KNN). Clustering was performed at low resolution (r = 0.02) to identify broad superclusters for downstream analysis . Principal components 1-38 were used for KNN and graphed using UMAP-non-linear dimensional reduction before clustering at r = 0.95. Cluster 13, which showed uncharacteristically high unique feature counts and markers for epithelial cells , were excluded as a likely doublet cluster. Markers for each cluster were identified with function FindAllMarkers using a Wilcoxon Rank Sum test for features expressed in at least 10% of the cluster and a minimum of 0.2 log-fold-change higher expression than the other cells in the neural crest-derived superclusters.Analysis of scRNAseq data from neural crest-derived cells were performed by subsetting and merging the superclusters containing cells from the DsRed-enriched samples Fig. . Using tAnalysis of scRNAseq data from immune cells were performed by subsetting and merging the superclusters Immune 1 and Immune 2 Fig. . Using tmpeg1.1:eGFP+ macrophages and PCNA+ cells were generated from z-stacks obtained from 63x confocal imaging using the LASX-3D software v3.5.7.23225.Images of histological sections were captured using a Keyence BZ-X810 microscope and software, then processed in Fiji. Live imaging was performed using a Leica M165FC stereo microscope with Leica K5 sCMOS camera and LASX software v3.7.4.23463. Fluorescence imaging was performed using a Leica SP8 confocal microscope with LASX software v3.5.7.23225. The 3-D projections of lgmn mutant PCNA staining and quantification were performed concurrently and wild type quantification is shown both in Fig. fn1a expression levels from smFISH images. Ligament domains and mesenchyme domains were drawn based on regional nuclear morphology in the tissue section. To calculate the corrected total fluorescence, an ROI was drawn to measure the integrated density for each channel using the same ROI for each channel. To account for tissue autofluorescence and background signal, 3 background regions of each image were measured, and the average mean gray value was calculated. To calculate the corrected total fluorescence (CTF), we used the following formula CTF = Integrated Density-(area of ROI*background mean). ImageJ was used on smFISH images to quantify the proportion of mpeg1.1+ cells that were also positive for fn1a and/or lgmn that surrounded the ligament stub by a blinded observer. The ROI for quantification was drawn to include 2-3 cell layers most proximal to the ligament stub excluding skin cells. ImageJ was used to quantify the number of Mpx+ cells by a blinded observer. The region of interest for quantification of Mpx+ cells was drawn to include the entire injury area.Proliferation was quantified as a percentage PCNA+ cells of total DAPI+ cells in a region of interest (ROI) in the uninjured ligament domain, ligament stub domain, or regenerative mesenchyme domain and scored by an observer blinded to treatment and/or genotype. Wild type and lgmn mutant proliferation, TUNEL, and fn1a transcript expression were each performed by 2-way ANOVA with Šídák’s multiple comparisons test. Comparison of wild type to lgmn mutant Mpx+/ROI was performed by 2-way ANOVA with Tukey’s multiple comparisons test. Comparison of wild type and lgmn mutant macrophage expression of fn1a and/or lgmn, and mpeg1.1:eGFP+ cell abundance were performed with Student’s T-test.All statistical analysis was carried out using GraphPad Prism 9. Proliferation in wild type animals was performed by ordinary 1-way ANOVA with Tukey’s multiple comparison test. Comparison of wild type to Further information on research design is available in the Supplementary InformationSupplementary Table 1Supplementary Table 2Supplementary Table 3Reporting SummarySupplementary Video 1Supplementary Video 2Supplementary Video 3Supplementary Video 4


This study aimed to investigate the interaction of the healthy eating index (HEI) and the dietary approach to stop hypertension (DASH) diet scores with FTO polymorphisms in relation to change in obesity traits. A total of 4480 subjects aged ≥ 18 years were selected from participants of the Tehran lipid and glucose study and followed-up 3 years. Selected polymorphisms  were genotyped and genetic risk score (GRS) was computed. HEI and DASH scores were computed based on dietary data. Changes in body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and visceral adiposity index (VAI) were measured. Higher adherence to both DASH and HEI scores were increased with higher ages. Individuals with high GRS had a lower change in BMI when they had higher adherence to HEI, compared to subjects with lower HEI score (P trend = 0.01). Change in WC in participants in the fourth quartile of HEI score in minor allele carriers of FTO variants was lower compared to the first quartile; conversely, higher adherence to the DASH score by this genotypic group was related to increase in WC. No significant interaction was seen between FTO polymorphisms and both diet scores regarding changes in any of obesity traits. In conclusion, in individuals with high GRS higher adherence to HEI score was associated with lower change in BMI and WC, while higher adherence to DASH diet was associated with higher change in WC, compared to individuals with lower adherence to both scores.The online version contains supplementary material available at 10.1186/s13104-023-06463-3. Obesity is a condition in which excess fat accumulates in the body and could adversely affect one’s health . AccordiMainstream medicine views obesity as a result of chronic energy imbalance. In recent decades, changes in dietary and physical activity patterns have contributed to the increased rate of obesity , affirmiAdvances in genetic technology have helped us to identify several common genetic variants associated with obesity. The most commonly implicated gene is fat mass and obesity associated gene (FTO) . There aOf lifestyle factors affecting body composition, diet is of utmost importance. Dietary approaches to stop hypertension (DASH) which is advised for preventing and treating high blood pressure, has been attributed to lower risk of cardiovascular diseases (CVD), cancer, insulin resistance, and blood lipid markers . HealthySubjects of this cohort study were chosen from participants of the Tehran Lipid and Glucose Study (TLGS), a population-based ongoing study performed to determine risk factors for non-communicable diseases in a group of residents of District 13 of Tehran, the capital of Iran. The first survey was done from 1999 to 2001 on 15,005 individuals aged ≥ 3 years, using the multistage stratified cluster random sampling technique, and follow-up surveys were performed every 3 years; 2002–2005 (survey 2), 2005–2008 (survey 3), 2008–2011(survey 4), and 2012–2015 (survey 5) to find out recently non-communicable diseases .Of 12,823 individuals attending the fourth phase of the TLGS (2008–2011) 8843 adults were ≥ 18 years. Subjects were removed due to anthropometric and nutritional missing data (n = 1961), so the data of 6882 subjects entered in this study as the baseline population and were followed-up to the survey 5 (2011–2014). Exclusion criteria were in these ways; subjects who had not DNA samples or lacking DNA purification in the range of 1.7 < A260/A280 < 2 or incomplete follow up data (n = 1600), pregnant (n = 80) or lactating women (n = 85), those with under- or over-reporting of energy intake  (n = 637). Overall, data provided by 4480 subjects were entered in this study.A written informed consent form was signed by all participants before entering the study. The ethics committee of the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences accepted the study protocol. All methods were carried out according to their relevant regulations and guidelines.A valid and reliable 168-item semi-quantitative food frequency questionnaire (FFQ) was applied for dietary assessment . SkilledThe DASH diet primarily developed to prevent hypertension. The DASH index is a posteriori-dietary pattern which calculates diet quality score. The index score (ranging 8–40) was based on eight food groups or nutrients including fruit, vegetable, nuts and legumes, low-fat dairy products, whole grains, sodium, sweetened beverages, red and processed meats intakes. Individual dietary food groups were calculated per 1000 kcal intake for each item, and then were categorized into quintiles. Subjects were given a score of 1 to 5 for each item. Subjects in the highest quintile intake of sodium, red and processed meat, and sweetened beverage were given a score of 0, and those in the lowest quintile of these food items were given a score of five. For fruit, vegetable, whole grain, low fat dairy, nuts and legumes, those in the highest quintile was given a score of 5 .The HEI is based on key recommendations of the 2015–2020 dietary guidelines for Americans which is composed of 13 dietary integrals; nine of them are adequacy components, including total fruits, whole fruits, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood and plant proteins, and fatty acids. Four of them are moderation components (those that should be limited) including refined grain, sodium, added sugars, and saturated fats. The HEI score is depend on density, so the amount per 1000 kcal of food groups and ratio of fatty acids was calculated. Recommendations are in the range of 1200–2400 kcal. Six components of adequacy components, including total fruit, whole fruit, total vegetables, greens and beans, total protein foods, seafood and plant proteins, each acquired a score of 0 and 5 for the lowest and highest intake, respectively. The other three adequacy components  were scored from 0 to 10 for the lowest and highest intake, respectively. The four moderation components including refined grains, sodium, added sugars, and saturated fats (SFA), gave a score of 0 and 10, respectively for the highest and lowest intakes. The score of intermediate intakes (between the minimum and maximum) were estimated. The sum of 13 integral scores was computed for a total HEI score ranging from 0 to 100. Individuals with a higher total HEI score had greater adherence to dietary guideline recommendations [Trained technician measured participants’ body weight with minimal clothing using a calibrated digital scale  and rounded to the nearest 0.1 kg. They measured heights (cm) by a stadiometer  and rounded to the nearest 0.5 cm, while the subjects standing without shoes in a normal position. Waist circumference (WC) was measured over light clothing, without exerting any pressure on the umbilicus using an un-stretched tape meter. Hip circumference was assessed at the level of maximal protrusion of the gluteal muscles. By dividing WC (cm) to hip circumference (cm), the waist to hip ratio (WHR) was calculated.VAI was estimated by the following formulas for men and women separately .\documenAnthropometric changes were considered as the outcomes or dependent variables in this study. BMI change was calculated by subtracting the BMIs obtained at the following survey from its corresponding at the baseline. The increase or decrease in BMI was determined if the BMI change was > 0 or ≤ 0 respectively. WHR, WC, and VAI change was computed using the same principle.Trained interviewer questioned physical activity with the Persian-translated modifiable activity questionnaire (MAQ). MAQ has high reliability and moderate validity. Data on the time and frequency of light, moderate, hard and very hard intensity typical activities over the last year were collected. The level of physical activity levels were estimated based on metabolic equivalent (MET)-hours/week (MET/h/week) .− 7. Six FTO single nucleotide polymorphisms (SNPs) were selected which were related to both dietary patterns and obesity phenotypes, including rs1421085, rs1121980, rs17817449, rs8050136, rs9939973, and rs3751812. There were a strong correlation between rs8050136, rs1421085, and rs1121980 (r2 > 0.8) with the other three SNPs in our analyses, so we applied these SNPs in our study. Also, there were a moderate relationship (r2 < 0.7) between these three SNPs [The region of the FTO gene was evaluated based on the Phenotype-Genotype Integrator and the authenticated catalog of published genome-wide related studies. FTO SNPs were chosen based on the available data, minor allele frequency > 0.2, and P values < 10ree SNPs .Genomic DNA was derived from non-coagulated whole blood samples, using a standard proteinase K, salting-out method. The evaluation of DNA quality was done by a Thermo Scientific NanoDrop 1000 Spectrophotometer. DNA purification outside the range of 1.7 < A260/A280 < 2 were excluded due to low quality. Extracted DNAs were aliquoted into 1.5-ml tubes and kept in ultra-freezers at -80 C, for preservation. HumanOmniExpress-24-v1-0 bead chips, containing 649,932 SNP loci was used to genotype the portions of DNA samples according to the manufacturer’s qualifications , an average mean distance of 4 kb at the deCODE genetics company  was regarded. PLINK program (V 1.07) and R statistic (V 3.2) were used to evaluate the quality, with a total genotyping rate of 0.9774. Finally, genotyping data of FTO SNPs  were analyzed [The weighted method was applied for GRS calculation based on 3 selected SNPs. Based on the existence of risk alleles , the coefficients of 0, 1, and 2 were allocated to each SNP. The weight of each SNP was obtained from the logistic regression analysis performed on the study population. GRS score is calculated by multiplying the coefficient of its risk alleles with the weight of each SNP.GRS = (OR1 × SNP1 + OR2 × SNP2 + OR3 × SNP3) × (n/sum of the ORs).OR is the odds ratio of each individual SNP on BMI. The logistic regression analysis was used to determine coefficients for the standardized weighted GRS in our population. The coefficients for risk alleles of rs1121980, rs1421085 and rs8050136 were respectively 0.21, 0.23, 0.24. Three SNPs (dominant model) were considered as independent variables and obesity (BMI ≥ 30 and BMI < 30) as dependent variable .Data were analyzed using SPSS version 21, and the statistical significance was considered as P < 0.05. To evaluate the qualitative and quantitative variables across quartiles of DASH and HEI scores, Chi-square and ANOVA tests were used respectively. The Pearson’s Chi-square test was applied to test The Hardy-Weinberg equilibrium.The interaction of diet quality scores with FTO gene variants (dominant model) or GRS concerning WHR, WC, VAI, and BMI alteration was estimated using a general linear model (ANCOVA). Participants were categorized into 8 groups based on three SNP polymorphisms (dominant model) and quartiles of dietary scores (HEI and DASH) to estimate mean ± SEM changes of obesity phenotypes. Participants were categorized into two groups based on the median of GRS (> 6.81 and ≤ 6.81). General linear models were performed to estimate the interactions of GRS with quartiles of DASH and HEI score concerning changes of WHR, WC, VAI, and BMI.The potential confounders, including smoking status , age, gender, physical activity , education levels (> 14 and ≤ 14 years), and energy intake were taken into account in all models.Baseline characteristics of participants across quartiles of HEI and DASH scores are presented in Table There was no statistically significant deviation from the Hardy–Weinberg equilibrium for the three polymorphisms. The median of GRS among participants was 6.81.Interactions of HEI and DASH scores by FTO SNPs  and GRS concerning changes in BMI and WHR were described in Table The interaction between HEI and DASH scores by FTO SNPs  and GRS concerning changes in VAI and WC were shown in Table In the present study, no significant interactions between DASH and HEI scores and genetic predisposition in relation to changes in obesity phenotypes including BMI, WC, WHR, or VAI were found. To the best of our knowledge, few studies have investigated the interactions between HEI and DASH diets and multiple FTO genetic variants in relation to adiposity features in a population. Moreover, participants with higher GRS and minor allele carriers of FTO SNPs 1,121,980 had a lower increase in BMI and WC in the highest quartile of HEI score, compared to the lowest quartile. Adherence to the DASH diet was also associated with higher increase in WHR and WC in participants with high GRS and minor allele carriers of FTO SNPs.Our findings are important for public health because the SNPs of FTO gene are common in our population and a high percentage of people carry these risk alleles. Moreover, Previous studies more emphasized on the interaction of certain food groups or nutrients with genetic predisposition in relation to obesity. The human diet contains numerous chemical compounds which make it difficult to investigate their separate effects on diseases; therefore, determining posteriori or priori dietary patterns and their association with obesity has been recommended. Identifying the best posteriori dietary pattern which modifies the association of FTO polymorphisms with obesity can help people adhere preventive recommendations especially in individuals with greater genetic susceptibility to obesity.FTO is identified as a gene of interest for obesity and has been subject to many investigations, most of which confirming that there is a notable association between FTO polymorphism and obesity traits , 27. StuPrevious studies showed that SIRT1 potentially prevented excessive accumulation of fat in adipose tissue. The interesting point is that recent studies have shown that sirtuins exert their role in energy metabolism in response to nutrient signals. Giving resveratrol to rats fed a high-fat diet protected them from high-fat-induced obesity, and this protective effect was due to increased activation of sirtuins by resveratrol , 37. TheInvestigating a whole dietary pattern could provide a better insight into the progression of a certain condition, compared to evaluating the effects of a single nutrient or food . It is wIn the current study, lower adherence to HEI in minor allele carriers of FTO variants led to a higher increase in BMI and WC. Moreover, individuals in the highest quartile of the DASH diet had a lower increase in WHR and WC compared to the individuals in the lowest quartile. However, no significant interaction was seen between FTO polymorphisms and DASH and HEI diets regarding changes in obesity indices. Recent studies regarding the gene-diet interaction reported controversial findings; in line with our results, a recent meta-analysis did not detect any interactions between protein intake and genetic predisposition to obesity on BMI, WC, or WHR . LivingsOn the other hand, there are a number of studies in which significant diet-gene interplay had been discovered. A recent study reported a notable interaction between GRS and intakes of energy, protein, total fat, SFA, poly-unsaturated fat (PUFA), and carbohydrate on BMI, body fat mass, and WC . A signiResults of the present study on DASH score and WC/ WHR in individuals with minor allele of FTO variants are opposite of the reports of previous studies, which suggested that high adherence to DASH diet is associated with reduction in the risk of abdominal obesity . This coDifferent findings might also be explained by the different definition of the DASH diet among studies. For example, in our study, nuts and legumes were in the same group and they are scored together. Also DASH dietary pattern depends on energy intake reduction to exert protective effects on abdominal obesity management and if this reduction in caloric intake does not occur, abdominal obesity may increase, so DASH score was not a good choice for weight management in minor allele  carriers of rs1121980, rs1421085 and rs8050136.The strengths of our study include its prospective design and utilizing a pre-defined dietary pattern analysis to better investigate the effect of overall dietary composition. Detailed information on physical activity, BMI, smoking status allowed extensive adjustment for obesity risk factors.There are some limitations that should be noted; our study population was highly homogenous as the subjects reside roughly in the same part of the town. These findings should be determined in other race and ethnicities. Moreover, there might be other potential confounders like economical influence and other social factors that could not be measured or adjusted. Our study included only three SNPs of the FTO gene whereas there are certainly more polymorphisms of FTO and other genes like MC4R, OLFM4, TCF7L2, ADCY3, GNPDA2, MAP2K5, and NRXN3 to be investigated. Besides, despite FFQ benefits, is not a robust tool to measure an individual’s exact dietary assessment. The major limitation of our study is calculating the DASH score, as the quintile levels of each food group was based on individuals’ dietary intake, so the range of each food group intake in each quintile of our study may be inconsistent with other studies. Finally, in order to have more conclusive findings, further studies with longer follow-up period are warranted.Our study revealed that there was no notable interaction between adherence to DASH diet or HEI and genetic predisposition on the obesity indices. However, adherence to HEI and DASH diets modified the association between FTO genetic variations and obesity phenotypes. In minor allele  carriers of FTO polymorphisms, low change in BMI and WC were seen with high adherence to the HEI. Conversely, high adherence to the DASH diet by this genotypic group was related to increasing WC.Below is the link to the electronic supplementary material.Supplementary Table 1. STROBE-nut: An extension of the STROBE statement for nutritional epidemiology