{"paper_id":"3458f0c1-786b-4dd3-9496-95338e3dedd5","body_text":"Weight Loss-induced Interaction Between Classical Lipolysis and the Autolysosome in Human Subcutaneous Adipose Tissue | 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 Weight Loss-induced Interaction Between Classical Lipolysis and the Autolysosome in Human Subcutaneous Adipose Tissue Edwin Mariman, Marleen van Baak, Freek Bouwman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4246664/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 Background/objectives: During a period of weight loss lipolysis genes in human subcutaneous adipose tissue are downregulated despite the increase in plasma free fatty acids. It has been proposed that lipid breakdown is taken over by the autolysosome. Here we test the relation between lipolysis and the autolysosome. Subjects/methods: Gene and protein expression data from the YoYo-study were used for correlation analysis including genes coding for lipases and regulators of lipolysis, for autolysosome proteins and lysosomal enzymes, and the genes coding for components of a previously identified integrin cluster. For all these genes the cell type and compartment of expression was obtained from databases. Correlation analysis was performed using the gene expression values before weight loss (WL), after WL, and after a subsequent weight stable period (WS), and using the expression changes during WL and WS. Results: During WL a significant negative correlation originated between the lipolysis and autolysosome genes. Genes of the integrin cluster correlated negative with the lipolysis genes and positive with the autolysosome genes. Surprisingly, the lipolysis genes were expressed in mature adipocytes while the autolysosome genes were not, but were expressed in other types of cells of the adipose tissue. Most of the correlated autolysosome genes were secreted or on the plasma membrane. After WL most of the genes reversed their direction of expression. During WS the correlation between lipolysis and autolysosome genes lost significance and the correlation with the integrin genes disappeared. Conclusions: Our findings do not support a transfer of lipid breakdown from lipolysis to the autolysosome in subcutaneous adipocytes during WL. Instead, we observe an intercellular interaction between lipolysis in mature adipocytes and the autolysosome of other cells in the adipose tissue. This interaction is probably mediated by integrin-mediated contact between the cells. A model for the observed interaction based on ECM-stress is presented. Health sciences/Diseases/Nutrition disorders/Obesity Biological sciences/Physiology/Metabolism/Fat metabolism Biological sciences/Biochemistry/Lipids/Fatty acids Biological sciences/Physiology/Metabolism/Homeostasis Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Losing weight is an appropriate approach for people with overweight or obesity to limit the risk of health complications. It is commonly achieved by reduced calorie intake shifting the metabolism to a negative energy balance. In that way fat mass is lost by the use of stored triglycerides as energy source. The breakdown of triglycerides from the adipose tissue is performed by a process referred to as classical lipolysis 1 . Lipolysis is controlled by the enzyme adipose tissue lipase (ATGL; PNPLA2 ), which turns triglycerides into diglycerides and FFA. Next, the enzyme hormone-sensitive lipase (HSL; LIPE ) turns diglycerides into monoglycerides and FFA, and finally monoglycerides are converted to glycerol and FFA by monoacylglycerol lipase (MAGL; MGLL ). The FFA are used as fuel for the adipocytes and are released to the blood stream, bound to albumin, and transferred to other tissues. The glycerol is also released to the blood stream via the membrane-bound aquaporin-7 (AQP7) and is taken up and metabolised by the liver. HSL has a broad substrate specificity and besides diglycerides it is able to break down tri- and monoglycerides. In order to be active, it needs to associate with the lipid droplet in the cell, which is achieved by interacting with the lipid droplet coating protein perilipin-1 (PLIN1) 2 . Various modulators of the classical lipolysis have been identified including metabolic enzymes like insulin, but also factors regulating lipase activity like adrenergic receptors 3 . Several studies have revealed that during a period of weight loss the genes of the classical lipolysis are down-regulated 4–6 . In this respect, it has been proposed from observations in rodents that lipid breakdown in adipocytes could take alternative metabolic routes 7 . One process is called lipophagy 8 in which the autophagosome forms around lipid droplets and then fuses with a lysosome to form an autolysosome particle. Inside the autolysosome, the lysosomal enzymes degrade the lipid droplet components with the FFA being released from the triglycerides by lysosomal acid lipase ( LIPA ). The process of the classical lipolysis as well as lipophagy could be assisted by the breakdown of the lipid droplet coating perilipins by chaperone-mediated autophagy 9 , which exposes the triglycerides to ATGL or allows their uptake into the autolysosome. When RNA from subcutaneous adipose tissue biopsies sampled from a group of people ranging from lean body weight to obesity was analysed, it was observed that several autophagosome genes as well as the gene for lysosomal lipase LIPA are negatively associated with the classical lipolysis genes PNPLA2 and LIPE via ATG7 10 . This points to the existence of an interaction between the classical lipolysis and the activity of the autolysosome in human adipose tissue. In the present study we have further investigated the possible interaction between the classical lipolysis and the autolysosome system in human subcutaneous adipose tissue under a negative energy balance and during the subsequent state of balanced energy. This reveals the transient occurrence of such an interaction. Surprisingly, each of the interacting processes appear to reside in a different cell type of the adipose tissue. MATERIALS AND METHODS The YoYo-study and RNA data The RNA samples used in the present study were obtained from the Yoyo clinical trial that has been described before 11 . In short, participants were weight stable (weight change < 3.0 kg) within 2 months prior to the study. Thereafter, study participants underwent a VLCD (500 kcal/d) or a LCD (1 200 kcal/day) resulting in an average 9% weight loss (WL, T1-T2). Subsequently, participants were maintained on a 4-week energy-balanced diet to retain a stable weight based on their individual energy requirements (WS, T2-T3). After the WS period, the participants' body weight was monitored for 9 months (follow-up, T3-T4). The total duration of the trial was 12–13 months for all participants. This trial is registered at www.clinicaltrials.gov as NCT01559415. At T1, T2 and T3 biopsies of the subcutaneous adipose tissue were sampled, from which total RNA was isolated. The RNA was analysed by microarray-analysis as described before 11 . Array data have been submitted to the Gene Expression Omnibus for the complete cohort (n = 53) (number GSE77962). Selection of genes for classical lipolysis and for the autolysosome system Regarding the classical lipolysis, five genes for triglyceride catabolism were selected: LIPE (HSL), PNPLA2 (ATGL) and MGLL coding for the lipases, as well as the AQP7 gene coding for the aquaporin that releases glycerol from the adipocytes, and PLIN1 as the major lipid coating protein in adipoise tissue that is involved in regulating the access of lipases to the stored lipids. Furthermore, three regulators of lipolysis were selected: ADRB2 , a positive inducer of hormone sensitive lipolysis 12 ; ABHD5 , a stimulator of ATGL 13 ; NPR3 , the natriuretic peptide receptor that regulates lipolysis 3 . The selection of the genes for the autolysosome has been based on the following literature: Bordi et al. 14 ; Romero and Zorzano 15 ; Ferhat et al. 16 ; Shim and Liton 17 . This documentation was used to categorize the selected genes into different phases of autolysosome generation and function: autophagy induction, autophagy elongation, autolysosome formation, lysosomal genes. As lysosomal genes only those coding for proteins with an enzymatic activity were selected without the intention to include all lysosomal enzymes but rather to cover different enzymatic activities like proteases, glycosylases, nucleases, etc. An extra twelve genes already known to be involved in the process of interest but not perse included in the above mentioned articles, were added as well. In all, 134 genes were selected in this way. For 16 of those genes no expression data were available and they were excluded. The final list of 118 classical lipolysis- and autolysosome-related genes is presented in Supplement Table 1 . Table 1 Fold Changes (FC) and P-values of relevant genes at T1-T2 and T2-T3. T1-T2 T2-T3 GENE SYMBOL FC P FC P Classical Lipolysis LIPE -1.09 0.004 1.02 0.58 PNPLA2 -1.14 0.000 1.08 0.008 MGLL -1.15 0.000 1.07 0.008 AQP7 -1.07 0.021 1.09 0.003 PLIN1 -1.05 0.05 1.02 0.49 ADRB2 1.16 0.000 -1.07 0.02 NPR3 -1.61 0.000 1.24 0.001 ABHD5 1.17 0.000 -1.09 0.01 Autolysosome ACP5 1.63 0.000 -1.66 0.000 ATG7 1.12 0.000 -1.09 0.007 ATG16L2 -1.02 0.74 1.06 0.27 RNASET2 1.20 0.001 -1.18 0.003 CTSS 1.31 0.001 -1.35 0.000 LAMP2 1.13 0.000 -1.11 0.001 DRAM1 1.14 0.000 -1.09 0.01 CTSC 1.31 0.000 -1.19 0.000 DAPK1 1.19 0.000 -1.09 0.004 MANBA 1.22 0.000 -1.13 0.001 IFI30 1.51 0.000 -1.64 0.000 HEXB 1.22 0.000 -1.22 0.000 LIPA 1.58 0.000 -1.54 0.000 VAMP8 1.13 0.01 -1.15 0.003 HIF1A 1.15 0.000 -1.09 0.07 CPVL 1.24 0.000 -1.19 0.002 ARSB 1.12 0.000 -1.10 0.001 GAA 1.13 0.005 -1.13 0.003 CTSH 1.13 0.01 -1.13 0.01 FUCA1 1.26 0.000 -1.19 0.001 PRCP 1.06 0.02 -1.05 0.08 SCPEP1 1.09 0.004 -1.11 0.000 CTSL 1.32 0.000 -1.21 0.000 ATG4C 1.17 0.000 -1.09 0.03 CTSK 1.24 0.000 -1.05 0.29 GALC 1.17 0.000 -1.08 0.01 Integrin cluster CTSS 1.31 0.001 -1.35 0.000 ITGAM 1.19 0.004 -1.27 0.000 ITGAX 1.32 0.006 -1.32 0.007 ITGAL 1.05 0.45 -1.03 0.64 ITGB2 1.32 0.003 -1.40 0.000 TGFB1 1.08 0.05 -1.08 0.05 ACTN1 1.13 0.000 -1.01 0.66 ITGA5 1.01 0.63 -1.01 0.65 ICAM3 -1.11 0.09 1.10 0.14 PPIB -1.01 0.73 -1.01 0.66 DMD -1.01 0.80 1.06 0.02 PLOD2 -1.13 0.000 1.02 0.47 SPARCL1 1.00 0.97 1.02 0.51 Data analysis Pearson correlation analysis was performed between the RNA expression levels of the selected genes at T1, T2 and T3 using SSPS version 28.0.1.0. Similarly, Pearson correlation analysis was also applied to the changes of gene expression for T2 minus T1 and T3 minus T2. The correlation coefficients of each gene vs. the five classical lipolysis genes ( LIPE , PNPLA2 , MGLL , PLIN1 , AQP7 ) were summed and the total values (Rt) were used to rank the genes. For ranking of the five lipolysis genes the r-value of 1 of self-correlation was replaced by the average of the four other r-values. For comparison, lines at Rt = 1.5 and Rt = -1.5 were drawn. The value 1.5 was chosen because it would represent an average r-value of 0.3 for each of the five genes, which corresponds to a P-value of 0.03. After ranking, the program Morpheus ( https://software.broadinstitute.org/morpheus/ ) was used to visualize the correlation differences by relative staining (blue for negative correlation, red for positive correlation). The program Morpheus was also used for hierarchical clustering. Cell-specific RNA abundance and subcellular protein abundance In order to assess in which type of cells of the human subcutaneous adipose tissue a specific gene is expressed, the gene symbol was entered into the ProteinAtlas database ( www.proteinatlas.org ). In the category ‘ Tissue Cell Type ’ the section ‘ subcutaneous adipose tissue ’ was examined to determine the relative gene expression level in the different cell types of the tissue including adipocytes, endothelial cells, smooth muscle cells, adipose progenitor cells, macrophages, mast cells, T-cells and plasma cells. To assess to which subcellular structures and compartments the proteins of the genes of interest contributed, for each gene the gene symbol was entered into the GeneCards database ( www.genecards.org ). Then, the information under ‘ subcellular locations from compartments ’ was examined to extract the relative protein abundance per compartment ranging from level 0 (absent) to level 5 (highest). Only compartments with levels 4 and 5 were marked in Table 2. RESULTS Correlation analysis between classical lipolysis and autolysosome genes The Spearman correlation coefficients of each of the selected genes vs. the five classical lipolysis genes ( LIPE , PNPLA2 , MGLL , PLIN1 , AQP7 ) were summed and the total values (Rt) were used to rank the genes. The results are shown in Fig. 1 . As can be seen, at T1 (baseline) the ratio of the number of genes with an Rt < -1.5 vs. that of genes with Rt > 1.5 is 4:28 but at T2 (reduced weight, but negative energy balance) this ratio is 21:10. Comparing T1 with T2 it seems that the interaction between classical lipolysis and the autolysosome system has intensified, revealed by a more predominant negative correlation between the genes of both processes at T2. The correlations of the gene expression changes during WL (T2 minus T1) of each of the selected genes vs. the expression changes of the five classical lipolysis genes is in agreement with such a reinforcement of a negative correlation. At T3 (reduced weight, energy balance) the ratio of the number of genes with an Rt < -1.5 vs. that of genes with an Rt > 1.5 is 2:13. This ratio is similar to that at T1 indicating that the interaction between classical lipolysis and the autolysosome system was reduced again when participants had returned to a state of energy balance while maintaining their weight loss. The correlation results of the gene expression changes during WS (T3 minus T2) of each of the selected genes vs. the expression changes of the five classical lipolysis genes support such a downscaling of the interaction. Notably, the number of genes with an Rt > 1.5 or Rt < -1.5 at T3 is only half of that at T1 or T2. Overall, the correlations are considerably weaker at T3. Analysis of the fold changes of the classical lipolysis and autolysosome genes The fold changes of the genes for classical lipolysis and of the autolysosome genes that negatively correlated with the classical lipolysis genes with an Rt < -1.5 have been listed in Table 1 . For WL (T1-T2) this concerned 16 genes and for WS (T2-T3) 21 genes, of which 11 were shared. During WL the classical lipolysis genes are significantly downregulated, while all the negatively correlating genes except for ATG16L2 , are significantly upregulated. In the WS period the situation reverses for all of the significantly differentially expressed genes. The classical lipolysis genes are upregulated, although LIPE and PLIN1 not significantly. The negatively correlating autolysosome genes are downregulated, but HIF1A , PRCP and CTSK not significantly. The reversal of the direction of the fold change of both groups of genes results in negative correlations during WL as well as WS. Cell-type and tissue-type identification In order to learn whether the interaction between classical lipolysis and the autolysosome is established in mature adipocytes, the relative RNA expression of genes was assessed for different cell types of the subcutaneous adipose tissue consulting the ProteinAltas database (Table 2). In this analysis, the five classical lipolysis genes and the autolysosome genes with an Rt < -1.5 from T1-T2 as well as from T2 were included. This analysis showed that the classical lipolysis genes are expressed exclusively in mature adipocytes whereas the autolysosome genes are not. They are active in other types of cells of the adipose tissue. The included autolysosome genes together covered all phases of autolysosome formation and were not confined to a particular phase. In addition, the subcellular localisation of the proteins of those genes was assessed from the GeneCards database ( www.genecards.org ). The subcellular compartment scoring at the two levels with the highest relative protein abundance (4 and 5) are marked in Table 2. 13 out of 20 autolysosome genes of T2 are marked ‘ lysosome ’ and the same number is marked ‘ extracellular ’. A possible role for integrins The interaction between adipocytes and other cells in the adipose tissue suggests that signals are transferred between the cells, which could involve surface proteins. Previously, we have identified a cluster with leukocyte-specific integrins that plays a role in weight regain of participants of the YoYo-study 18 . To investigate if this cluster could be involved in the present interaction between classical lipolysis and the autolysosome, correlation analysis was performed between the five classical lipolysis genes, autolysosome genes (Rt < -1.5), and the six genes of the identified ‘ narrow integrin cluster ’ ( ITGAM , ITGAX , ITGAL , ITGB2 , TGFB1 , CTSS ). Hierarchical clustering (Suplement Fig. 1 ) shows that the expression changes of the integrin cluster genes correlate negatively with the expression changes of the classical lipolysis genes and positively with the expression changes of the autolysosome genes during WL (T2 minus T1) and WS (T3 minus T2). However, during WS the correlations seem to be less strong as compared to during WL. An overview of the coefficients of the classical lipolysis genes after correlation with the genes of the ‘ broad integrin cluster ’ (narrow cluster including ACTN1 , ITGA5 , ICAM3 , PPIB , DMD , PLOD2 , SPARCL1 ) can be seen in Fig. 2 A for WL and WS, and with the genes of the narrow integrin cluster in Fig. 2 B for T1, T2 and T3. It shows that from T1 to T2 correlation of the classical lipolysis with the integrin cluster intensifies, whereas at T3 the data do no longer support such an interaction. DISCUSSION Here we have investigated the possible interaction of classical lipolysis with the autolysosome in human adipose tissue, which was previously revealed by the negative correlation of ATG7 and associated autolysosome genes with the classical lipolysis genes PNPLA2 and LIPE 10 . In the present study we show that during weight loss, i.e. under a negative energy balance, an interaction between the classical lipolysis and the autolysosome system is indeed established demonstrated by an intensifying of the negative correlation between the genes of both metabolic processes. Surprisingly, whereas the classical lipolysis is active in mature adipocytes, the associated autolysosome system is not but seems to operate from other types of cells of the subcutaneous adipose tissue. After returning to a state of energy balance for 4 weeks, most genes have switched their direction of expression and the interaction between the classical lipolysis and autolysosome system is diminished (Fig. 1 , Table 1 ). To establish the interaction between the two metabolic systems in different cells, a connection between the cells needs to be made. Our observations indicate that this could involve the leukocyte integrin gene cluster that was previously reported in relation to the risk of weight regain in the YoYo-study 18 . Based on the significant differential expression during WL (Table 1 ) and the negative correlations with the classical lipolysis genes (Fig. 2 A), this mainly concerns CTSS , ITGAM , ITGAX , ITGAL , ITGB2 and TGFB1 , referred to as the narrow integrin cluster. A heterodimer between ITGAL (CD11A) and ITGB2 (CD18) represents the receptor for intercellular adhesion molecules (ICAMs). The gene expression changes of ICAM3 correlate positively with the expression changes of the ITGAL gene during WL and WS (Fig. 2 A). However, unlike ITGAL the expression changes of ICAM3 do not correlate negatively with the changes of the classical lipolysis genes. It suggests that ICAM3 is of limited importance for the observed interaction of adipocytes with others cells. Both ITGAM (CD11B) and ITGAX (CD11C) form heterodimers with ITGB2 (CD18) and these dimers function as receptors for fibrinogen and for inactive complement factor C3b (iC3b). In this regard, the ITGAM/ITGB2 dimer is referred to as the iC3b receptor 3 (CR3) and the ITGAX/ITGB2 dimer as the iC3b receptor 4 (CR4). From in vitro experiments we know that mature SGBS adipocytes secrete C3 19 , which is known to spontaneously split into C3a and C3b. Whereas C3a leaves the site to act in the adipose tissue as anaphylatoxin, C3b can attach to glycoproteins on the self-surface of cells by its exposed thioester-containing domain 20 , for instance to fibronectin 21 . There it can be converted to iC3b by the action of Complement Factor I (CFI), Complement Factor H (CFH), Membrane Cofactor Protein (MCP, CD46) and Complement C3b/C4b Receptor 1 (CR1, CD35). The genes for all of these proteins are expressed in the adipose tissue. We therefore speculate that iC3b on the surface of adipocytes in connection with the receptors CR3 and CR4 could establish the contact between adipocytes and other cell types, likely leukocytes. The downregulation of lipolysis genes and upregulation of autolysosome genes during the WL period could both be involved in the release of mechanical stress of the adipocytes. During a negative energy balance the adipocytes shrink and mechanical stress will build up in the adipocyte ECM. To avoid further increase of stress, the shrinking due to the release of lipids, and thus lipolysis, should be diminished. As a second measure to release stress, the ECM could be modified. This can be accomplished by extracellular enzymes able to attack the ECM proteins and their post-transcriptional modifications. Our present findings demonstrate that adipocytes under stress during a negative energy balance invoke the assistance of other cells, which activate their own autolysosome system in order to excrete catabolic enzymes. Recently we have proposed a similar action of leukocytes as part of the immune-based obesogenic memory in relation to weight regain after weight loss 22 . It suggests that modification of the adipocyte ECM with the assistance of leukocytes or other cell types is a general phenomenon that can explain different aspects of weight regulation. At the selection of the genes for this study we have focussed on lysosomal genes that code for enzymes. This allowed us to determine whether the autolysosome action depends on a defined enzymatic activity. At T2, 15 of the 21 genes with an Rt < -1.5 code for an enzyme. 12 of those are marked as ‘ secreted ’ or as present in the ‘ plasma membrane ’ (Table 2). The three remaining genes, LIPA , ATG4C , GALC scored on Genecards ‘2’ or ‘3’ (with ‘5’ being the highest score) for the locations ‘ extracellular ’ and ‘ plasma membrane ’. Overall it shows that at T2 the majority of genes engaged in a negative correlation with the lipolysis genes are secreted or on the outside of the cell. Their enzymatic activities are identified as ‘proteinase or peptidase’ ( ATG4C , CPVL , CTSC , CTSS , PRCP ), ‘glycosidase’ ( CTBS , GLA , GUSB , MANBA ), ‘amidase’ ( GALC , HEXB , NAAA ), ‘thiol reductase’ ( IFI30 ), ‘lipase’ ( LIPA ), and ‘ribonuclease’ ( RNASET2 ). Apparently, the involved autolysosome genes cover a variety of enzymatic activities, of which most can be deployed to modify the ECM. Our findings do not support a transfer of lipid breakdown from classical lipolysis to lipophagy in human adipocytes, although a low level of lipid breakdown cannot be excluded by our present analyses. Despite the reduction of the expression of lipolysis genes during WL, the plasma level of FFA increases by 45% 23 . OF the corresponding proteins for classical lipolysis only data for LIPE, MGLL and PLIN1 are available 24 , which during WL go down with a factor of 1.03x, 1.11x, and 1.03x, respectively. Apparently, protein abundance cannot explain the increase of the plasma FFA level. A possible explanation for the increased FFA level is by the regulation of lipolysis. ADRB2 and ABHD5 which stimulate lipolysis, are significantly upregulated whereas NPR3 , which inhibits lipolysis by the removal of natriuretic peptides 3 , is significantly downregulated (Table 1 ). A likely scenario therefore is that under a negative energy balance, adipocytes shrink leading to ECM stress (Fig. 3 ). This will induce downregulation of the lipolysis genes and proteins, but the energy demand of the body will partly overrule this demand by upregulating lipolysis stimulators and by downregulating lipolysis inhibitors. Adipocytes will then look for another way to be released from ECM stress, i.e. by invoking the assistance of other cells secreting ECM modifying enzymes via their autolysosome system. Notably, this is one of many scenarios, which can now be tested by extra investigations. The autophagic and endolysosomal systems are known to serve as secretory pathways, which has been reviewed by Buratta et al. 25 . Also the cell-endogenous response of autophagy to mechanical stress has been reported 17 . Further, the connection between autophagy and adipose tissue biology, in particular adipogenesis, has been under study 15, 26 27 . Interestingly, it has been observed that ECM components by binding to cell surface receptors can activate the autophagic system 28, 29 . The involvement of integrins in autophagy through ECM binding has also been shown 30 . In the present study we show that these reported findings can work together to establish an interaction in the human adipose tissue between classical lipolysis and the autolysosome in different cells with the supposed purpose of releasing mechanical stress from the shrinking adipocyte. The regulatory mechanism behind this interaction remains presently unknown. As can be seen in Figs. 2 A and 2 B, after return to a situation of balanced energy intake, the interaction of the classical lipolysis with the autolysosome through the integrin cluster is no longer sustained. It suggests that by the end of the WS phase, four weeks after ending the reduced calorie diet, the adipocytes have lost most of their mechanical stress. During the WS period the adipocytes regain 50–60% of the lost volume 23 . As such it seems no longer needed to resolve the stress by modification of the ECM. In summary, we have shown that under a negative energy balance an interaction is established in the human subcutaneous adipose tissue between the classical lipolysis in the adipocytes and the autolysosome system in other cells (Fig. 3 ). Our observations further indicate that the connection between the cells is formed via ITGAM/ITGB2 and ITGAX/ITGB2 integrins, possibly with involvement of iC3b for which these integrins are the receptors. It is proposed that this interaction serves to reduce mechanical stress of shrinking adipocytes by the modification of the ECM when gene and protein regulation do not result in a sufficient downregulation of lipolysis. When energy balance is restored the interaction is no longer sustained. It should be noted that our observations are majorly based on correlation analysis between gene expression data. Although they generate interesting leads for further investigation, molecular biological and cell morphological approaches need to be applied in follow-up experiments to provide more clear evidence and to reveal the regulatory mechanism behind the observed transient interaction. Declarations COMPETING INTERESTS The authors declare that there are no competing financial interests. ACKNOWLEDGEMENTS The authors like to thank Dr. Nadia Roumans for assisting with generating the genomic data. EM performed the analyses and composed the manuscript, FB and MvB advised about the contents of the manuscript. References Watt MJ, Steinberg GR. Regulation and function of triacylglycerol lipases in cellular metabolism. Biochem J 2008; 414(3): 313–25. Granneman JG, Moore HP, Granneman RL, Greenberg AS, Obin MS, Zhu Z. Analysis of lipolytic protein trafficking and interactions in adipocytes. J Biol Chem 2007; 282(8): 5726–35. Lafontan M, Moro C, Berlan M, Crampes F, Sengenes C, Galitzky J. Control of lipolysis by natriuretic peptides and cyclic GMP. Trends Endocrinol Metab 2008; 19(4): 130–7. Capel F, Viguerie N, Vega N, Dejean S, Arner P, Klimcakova E et al. Contribution of energy restriction and macronutrient composition to changes in adipose tissue gene expression during dietary weight-loss programs in obese women. J Clin Endocrinol Metab 2008; 93(11): 4315–22. Koppo K, Valle C, Siklova-Vitkova M, Czudkova E, de Glisezinski I, van de Voorde J et al. Expression of lipolytic genes in adipose tissue is differentially regulated during multiple phases of dietary intervention in obese women. Physiol Res 2013; 62(5): 527–35. Vink RG, Roumans NJ, Fazelzadeh P, Tareen SH, Boekschoten MV, van Baak MA, Mariman EC. Adipose tissue gene expression is differentially regulated with different rates of weight loss in overweight and obese humans. Int J Obes (Lond) 2017; 41(2): 309–316. Goldman S, Zhang Y, Jin S. Autophagy and adipogenesis: implications in obesity and type II diabetes. Autophagy 2010; 6(1): 179–81. Ward C, Martinez-Lopez N, Otten EG, Carroll B, Maetzel D, Singh R et al. Autophagy, lipophagy and lysosomal lipid storage disorders. Biochim Biophys Acta 2016; 1861(4): 269–84. Kaushik S, Cuervo AM. Degradation of lipid droplet-associated proteins by chaperone-mediated autophagy facilitates lipolysis. Nat Cell Biol 2015; 17(6): 759–70. Xu Q, Mariman ECM, Roumans NJT, Vink RG, Goossens GH, Blaak EE, Jocken JWE. Adipose tissue autophagy related gene expression is associated with glucometabolic status in human obesity. Adipocyte 2018; 7(1): 12–19. Vink RG, Roumans NJ, Arkenbosch LA, Mariman EC, van Baak MA. The effect of rate of weight loss on long-term weight regain in adults with overweight and obesity. Obesity (Silver Spring) 2016; 24(2): 321–7. Enocksson S, Shimizu M, Lonnqvist F, Nordenstrom J, Arner P. Demonstration of an in vivo functional beta 3-adrenoceptor in man. J Clin Invest 1995; 95(5): 2239–45. Yu L, Li Y, Grise A, Wang H. CGI-58: Versatile Regulator of Intracellular Lipid Droplet Homeostasis. Adv Exp Med Biol 2020; 1276: 197–222. Bordi M, De Cegli R, Testa B, Nixon RA, Ballabio A, Cecconi F. A gene toolbox for monitoring autophagy transcription. Cell Death Dis 2021; 12(11): 1044. Romero M, Zorzano A. Role of autophagy in the regulation of adipose tissue biology. Cell Cycle 2019; 18(13): 1435–1445. Ferhat M, Funai K, Boudina S. Autophagy in Adipose Tissue Physiology and Pathophysiology. Antioxid Redox Signal 2019; 31(6): 487–501. Shim MS, Liton PB. The physiological and pathophysiological roles of the autophagy lysosomal system in the conventional aqueous humor outflow pathway: More than cellular clean up. Prog Retin Eye Res 2022; 90: 101064. Roumans NJ, Vink RG, Fazelzadeh P, van Baak MA, Mariman EC. A role for leukocyte integrins and extracellular matrix remodeling of adipose tissue in the risk of weight regain after weight loss. Am J Clin Nutr 2017; 105(5): 1054–1062. Qiao Q, Bouwman FG, Renes J, Mariman ECM. An in vitro model for hypertrophic adipocytes: Time-dependent adipocyte proteome and secretome changes under high glucose and high insulin conditions. J Cell Mol Med 2020; 24(15): 8662–8673. Morgan HP, Schmidt CQ, Guariento M, Blaum BS, Gillespie D, Herbert AP et al. Structural basis for engagement by complement factor H of C3b on a self surface. Nat Struct Mol Biol 2011; 18(4): 463–70. Hindmarsh EJ, Marks RM. Complement activation occurs on subendothelial extracellular matrix in vitro and is initiated by retraction or removal of overlying endothelial cells. J Immunol 1998; 160(12): 6128–36. van Baak MA, Mariman ECM. Obesity-induced and weight-loss-induced physiological factors affecting weight regain. Nat Rev Endocrinol 2023; 19(11): 655–670. Vink RG, Roumans NJ, Mariman EC, van Baak MA. Dietary weight loss-induced changes in RBP4, FFA, and ACE predict weight regain in people with overweight and obesity. Physiol Rep 2017; 5(21). Roumans NJT, Vink RG, Bouwman FG, Fazelzadeh P, van Baak MA, Mariman ECM. Weight loss-induced cellular stress in subcutaneous adipose tissue and the risk for weight regain in overweight and obese adults. Int J Obes (Lond) 2017; 41(6): 894–901. Buratta S, Tancini B, Sagini K, Delo F, Chiaradia E, Urbanelli L, Emiliani C. Lysosomal Exocytosis, Exosome Release and Secretory Autophagy: The Autophagic- and Endo-Lysosomal Systems Go Extracellular. Int J Mol Sci 2020; 21(7). Zhang Y, Goldman S, Baerga R, Zhao Y, Komatsu M, Jin S. Adipose-specific deletion of autophagy-related gene 7 (atg7) in mice reveals a role in adipogenesis. Proc Natl Acad Sci U S A 2009; 106(47): 19860–5. Gao Y, Ma K, Kang Y, Liu W, Liu X, Long X et al. Type I collagen reduces lipid accumulation during adipogenesis of preadipocytes 3T3-L1 via the YAP-mTOR-autophagy axis. Biochim Biophys Acta Mol Cell Biol Lipids 2022; 1867(9): 159181. Neill T, Schaefer L, Iozzo RV. Instructive roles of extracellular matrix on autophagy. Am J Pathol 2014; 184(8): 2146–53. Chen CG, Iozzo RV. Extracellular matrix guidance of autophagy: a mechanism regulating cancer growth. Open Biol 2022; 12(1): 210304. Lock R, Debnath J. Extracellular matrix regulation of autophagy. Curr Opin Cell Biol 2008; 20(5): 583–8. Additional Declarations There is NO conflict of interest to disclose Supplementary Files SupplementalInformation.pdf 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-4246664\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":291554820,\"identity\":\"5f1402d8-d1fa-4d1a-a946-82d5ffc412f5\",\"order_by\":0,\"name\":\"Edwin Mariman\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"Maastricht University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Edwin\",\"middleName\":\"\",\"lastName\":\"Mariman\",\"suffix\":\"\"},{\"id\":291554821,\"identity\":\"1905da21-201d-46aa-b16c-6ff01d80e8b0\",\"order_by\":1,\"name\":\"Marleen van Baak\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0003-2592-6363\",\"institution\":\"Maastricht University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Marleen\",\"middleName\":\"van\",\"lastName\":\"Baak\",\"suffix\":\"\"},{\"id\":291554822,\"identity\":\"a676a7b7-03ad-497b-9f37-9f78dea4d098\",\"order_by\":2,\"name\":\"Freek Bouwman\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0002-5582-1370\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Freek\",\"middleName\":\"\",\"lastName\":\"Bouwman\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-10 10:06:26\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4246664/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4246664/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":55082786,\"identity\":\"b73a529f-5614-43a8-bab7-bd78fb95d8be\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 10:18:54\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":372601,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRanking of the selected genes according to the summed correlation coefficients (Rt) of each gene with the five classical lipolysis genes. The relative values of the correlation coefficients are visualized by the intensity of red staining for positive and blue staining for negative correlation. The double arrow separates the classical lipolysis genes from the autolysosome genes. Vertical lines divide genes with Rt\\u0026gt;1.5, with -1.5\\u0026lt;Rt\\u0026lt;1.5, and with Rt\\u0026lt;-1.5, respectively.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1vertical.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4246664/v1/7cde9e7de5c52c4891f16679.png\"},{\"id\":55082787,\"identity\":\"cfc9e898-f4d7-47bf-bd06-7c519683018f\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 10:18:54\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":521348,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCorrelation between absolute values or the expression changes of the classical lipolysis genes and the genes of the integrin cluster. \\u003cu\\u003eA\\u003c/u\\u003e. Correlation of the expression changes during WL and WS of the classical lipolysis genes with the genes of the broad integrin cluster; \\u003cu\\u003eB\\u003c/u\\u003e. correlation of the absolute expression values of the classical lipolysis genes with the genes of the narrow integrin cluster at T1, T2 and T3.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4246664/v1/546bc696bd9db284e19aa865.png\"},{\"id\":55082788,\"identity\":\"b7afe7a0-cb1d-4d1a-bbc9-5335c43a3a01\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 10:18:54\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":93793,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePossible scenario of the interaction between adipocytes and another cell type in subcutaneous adipose tissue. Under negative energy balance ECM stress due to shrinking of the adipocyte downregulates the lipolysis genes. Lipolysis-modifying genes then stimulate the release of FFA and glycerol. Next, other cells are invoked to bind to the adipocyte and secrete ECM modifying enzymes to release stress. Returning to energy balance leads to normalization of the situation.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3vertical.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4246664/v1/c5cd6f3fc8d71f01150a5f86.png\"},{\"id\":56038314,\"identity\":\"9736392b-d6bb-4fd6-971c-2454adca236b\",\"added_by\":\"auto\",\"created_at\":\"2024-05-07 19:00:15\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1748049,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4246664/v1/962486e5-9570-42f5-9a75-ffb910c50bc7.pdf\"},{\"id\":55082789,\"identity\":\"cd54204b-3a48-4b45-8866-ee6052cf50cc\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 10:18:54\",\"extension\":\"pdf\",\"order_by\":6,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":845618,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementalInformation.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4246664/v1/7196ed319a3acaed7f6e5468.pdf\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e conflict of interest to disclose\",\"formattedTitle\":\"\\u003cp\\u003eWeight Loss-induced Interaction Between Classical Lipolysis and the Autolysosome in Human Subcutaneous Adipose Tissue\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"INTRODUCTION\",\"content\":\"\\u003cp\\u003eLosing weight is an appropriate approach for people with overweight or obesity to limit the risk of health complications. It is commonly achieved by reduced calorie intake shifting the metabolism to a negative energy balance. In that way fat mass is lost by the use of stored triglycerides as energy source. The breakdown of triglycerides from the adipose tissue is performed by a process referred to as classical lipolysis\\u003csup\\u003e1\\u003c/sup\\u003e. Lipolysis is controlled by the enzyme adipose tissue lipase (ATGL; \\u003cem\\u003ePNPLA2\\u003c/em\\u003e), which turns triglycerides into diglycerides and FFA. Next, the enzyme hormone-sensitive lipase (HSL; \\u003cem\\u003eLIPE\\u003c/em\\u003e) turns diglycerides into monoglycerides and FFA, and finally monoglycerides are converted to glycerol and FFA by monoacylglycerol lipase (MAGL; \\u003cem\\u003eMGLL\\u003c/em\\u003e). The FFA are used as fuel for the adipocytes and are released to the blood stream, bound to albumin, and transferred to other tissues. The glycerol is also released to the blood stream via the membrane-bound aquaporin-7 (AQP7) and is taken up and metabolised by the liver. HSL has a broad substrate specificity and besides diglycerides it is able to break down tri- and monoglycerides. In order to be active, it needs to associate with the lipid droplet in the cell, which is achieved by interacting with the lipid droplet coating protein perilipin-1 (PLIN1)\\u003csup\\u003e2\\u003c/sup\\u003e. Various modulators of the classical lipolysis have been identified including metabolic enzymes like insulin, but also factors regulating lipase activity like adrenergic receptors\\u003csup\\u003e3\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eSeveral studies have revealed that during a period of weight loss the genes of the classical lipolysis are down-regulated\\u003csup\\u003e4\\u0026ndash;6\\u003c/sup\\u003e. In this respect, it has been proposed from observations in rodents that lipid breakdown in adipocytes could take alternative metabolic routes\\u003csup\\u003e7\\u003c/sup\\u003e. One process is called lipophagy\\u003csup\\u003e8\\u003c/sup\\u003e in which the autophagosome forms around lipid droplets and then fuses with a lysosome to form an autolysosome particle. Inside the autolysosome, the lysosomal enzymes degrade the lipid droplet components with the FFA being released from the triglycerides by lysosomal acid lipase (\\u003cem\\u003eLIPA\\u003c/em\\u003e). The process of the classical lipolysis as well as lipophagy could be assisted by the breakdown of the lipid droplet coating perilipins by chaperone-mediated autophagy\\u003csup\\u003e9\\u003c/sup\\u003e, which exposes the triglycerides to ATGL or allows their uptake into the autolysosome.\\u003c/p\\u003e \\u003cp\\u003eWhen RNA from subcutaneous adipose tissue biopsies sampled from a group of people ranging from lean body weight to obesity was analysed, it was observed that several autophagosome genes as well as the gene for lysosomal lipase LIPA are negatively associated with the classical lipolysis genes \\u003cem\\u003ePNPLA2\\u003c/em\\u003e and \\u003cem\\u003eLIPE\\u003c/em\\u003e via ATG7\\u003csup\\u003e10\\u003c/sup\\u003e. This points to the existence of an interaction between the classical lipolysis and the activity of the autolysosome in human adipose tissue. In the present study we have further investigated the possible interaction between the classical lipolysis and the autolysosome system in human subcutaneous adipose tissue under a negative energy balance and during the subsequent state of balanced energy. This reveals the transient occurrence of such an interaction. Surprisingly, each of the interacting processes appear to reside in a different cell type of the adipose tissue.\\u003c/p\\u003e\"},{\"header\":\"MATERIALS AND METHODS\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eThe YoYo-study and RNA data\\u003c/h2\\u003e \\u003cp\\u003eThe RNA samples used in the present study were obtained from the Yoyo clinical trial that has been described before\\u003csup\\u003e11\\u003c/sup\\u003e. In short, participants were weight stable (weight change\\u0026thinsp;\\u0026lt;\\u0026thinsp;3.0 kg) within 2 months prior to the study. Thereafter, study participants underwent a VLCD (500 kcal/d) or a LCD (1 200 kcal/day) resulting in an average 9% weight loss (WL, T1-T2). Subsequently, participants were maintained on a 4-week energy-balanced diet to retain a stable weight based on their individual energy requirements (WS, T2-T3). After the WS period, the participants' body weight was monitored for 9 months (follow-up, T3-T4). The total duration of the trial was 12\\u0026ndash;13 months for all participants. This trial is registered at \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\u003ca href=\\\"http://www.clinicaltrials.gov\\\" target=\\\"_blank\\\"\\u003ewww.clinicaltrials.gov\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.clinicaltrials.gov\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e as NCT01559415. At T1, T2 and T3 biopsies of the subcutaneous adipose tissue were sampled, from which total RNA was isolated. The RNA was analysed by microarray-analysis as described before\\u003csup\\u003e11\\u003c/sup\\u003e. Array data have been submitted to the Gene Expression Omnibus for the complete cohort (n\\u0026thinsp;=\\u0026thinsp;53) (number GSE77962).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSelection of genes for classical lipolysis and for the autolysosome system\\u003c/h2\\u003e \\u003cp\\u003eRegarding the classical lipolysis, five genes for triglyceride catabolism were selected: \\u003cem\\u003eLIPE\\u003c/em\\u003e (HSL), \\u003cem\\u003ePNPLA2\\u003c/em\\u003e (ATGL) and \\u003cem\\u003eMGLL\\u003c/em\\u003e coding for the lipases, as well as the \\u003cem\\u003eAQP7\\u003c/em\\u003e gene coding for the aquaporin that releases glycerol from the adipocytes, and PLIN1 as the major lipid coating protein in adipoise tissue that is involved in regulating the access of lipases to the stored lipids. Furthermore, three regulators of lipolysis were selected: \\u003cem\\u003eADRB2\\u003c/em\\u003e, a positive inducer of hormone sensitive lipolysis\\u003csup\\u003e12\\u003c/sup\\u003e; \\u003cem\\u003eABHD5\\u003c/em\\u003e, a stimulator of ATGL\\u003csup\\u003e13\\u003c/sup\\u003e; \\u003cem\\u003eNPR3\\u003c/em\\u003e, the natriuretic peptide receptor that regulates lipolysis\\u003csup\\u003e3\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThe selection of the genes for the autolysosome has been based on the following literature: Bordi et al.\\u003csup\\u003e14\\u003c/sup\\u003e; Romero and Zorzano\\u003csup\\u003e15\\u003c/sup\\u003e; Ferhat et al.\\u003csup\\u003e16\\u003c/sup\\u003e; Shim and Liton\\u003csup\\u003e17\\u003c/sup\\u003e. This documentation was used to categorize the selected genes into different phases of autolysosome generation and function: autophagy induction, autophagy elongation, autolysosome formation, lysosomal genes. As lysosomal genes only those coding for proteins with an enzymatic activity were selected without the intention to include all lysosomal enzymes but rather to cover different enzymatic activities like proteases, glycosylases, nucleases, etc. An extra twelve genes already known to be involved in the process of interest but not perse included in the above mentioned articles, were added as well. In all, 134 genes were selected in this way. For 16 of those genes no expression data were available and they were excluded.\\u003c/p\\u003e \\u003cp\\u003eThe final list of 118 classical lipolysis- and autolysosome-related genes is presented in Supplement Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFold Changes (FC) and P-values of relevant genes at T1-T2 and T2-T3.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eT1-T2\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eT2-T3\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGENE SYMBOL\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFC\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFC\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eClassical Lipolysis\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLIPE\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.004\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.58\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePNPLA2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.008\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMGLL\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e 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align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHEXB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLIPA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.58\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd 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colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.002\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eARSB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGAA\\u003c/p\\u003e \\u003c/td\\u003e 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colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCTSL\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eATG4C\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.17\\u003c/p\\u003e \\u003c/td\\u003e 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colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCTSS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.31\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eITGAM\\u003c/p\\u003e 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char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.40\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTGFB1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.05\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.05\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eACTN1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.66\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eITGA5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eICAM3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePPIB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.66\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDMD\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePLOD2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.47\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSPARCL1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData analysis\\u003c/h2\\u003e \\u003cp\\u003ePearson correlation analysis was performed between the RNA expression levels of the selected genes at T1, T2 and T3 using SSPS version 28.0.1.0. Similarly, Pearson correlation analysis was also applied to the changes of gene expression for T2 minus T1 and T3 minus T2. The correlation coefficients of each gene vs. the five classical lipolysis genes (\\u003cem\\u003eLIPE\\u003c/em\\u003e, \\u003cem\\u003ePNPLA2\\u003c/em\\u003e, \\u003cem\\u003eMGLL\\u003c/em\\u003e, \\u003cem\\u003ePLIN1\\u003c/em\\u003e, \\u003cem\\u003eAQP7\\u003c/em\\u003e) were summed and the total values (Rt) were used to rank the genes. For ranking of the five lipolysis genes the r-value of 1 of self-correlation was replaced by the average of the four other r-values. For comparison, lines at Rt\\u0026thinsp;=\\u0026thinsp;1.5 and Rt = -1.5 were drawn. The value 1.5 was chosen because it would represent an average r-value of 0.3 for each of the five genes, which corresponds to a P-value of 0.03. After ranking, the program Morpheus (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://software.broadinstitute.org/morpheus/\\u003c/span\\u003e\\u003cspan address=\\\"https://software.broadinstitute.org/morpheus/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) was used to visualize the correlation differences by relative staining (blue for negative correlation, red for positive correlation). The program Morpheus was also used for hierarchical clustering.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCell-specific RNA abundance and subcellular protein abundance\\u003c/h2\\u003e \\u003cp\\u003eIn order to assess in which type of cells of the human subcutaneous adipose tissue a specific gene is expressed, the gene symbol was entered into the ProteinAtlas database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\u003ca href=\\\"http://www.clinicaltrials.gov\\\" target=\\\"_blank\\\"\\u003ewww.proteinatlas.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.proteinatlas.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). In the category \\u0026lsquo;\\u003cem\\u003eTissue Cell Type\\u003c/em\\u003e\\u0026rsquo; the section \\u0026lsquo;\\u003cem\\u003esubcutaneous adipose tissue\\u003c/em\\u003e\\u0026rsquo; was examined to determine the relative gene expression level in the different cell types of the tissue including adipocytes, endothelial cells, smooth muscle cells, adipose progenitor cells, macrophages, mast cells, T-cells and plasma cells. To assess to which subcellular structures and compartments the proteins of the genes of interest contributed, for each gene the gene symbol was entered into the GeneCards database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\u003ca href=\\\"http://www.clinicaltrials.gov\\\" target=\\\"_blank\\\"\\u003ewww.genecards.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.genecards.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Then, the information under \\u0026lsquo;\\u003cem\\u003esubcellular locations from compartments\\u003c/em\\u003e\\u0026rsquo; was examined to extract the relative protein abundance per compartment ranging from level 0 (absent) to level 5 (highest). Only compartments with levels 4 and 5 were marked in Table\\u0026nbsp;2.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"RESULTS\",\"content\":\"\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCorrelation analysis between classical lipolysis and autolysosome genes\\u003c/h2\\u003e \\u003cp\\u003eThe Spearman correlation coefficients of each of the selected genes vs. the five classical lipolysis genes (\\u003cem\\u003eLIPE\\u003c/em\\u003e, \\u003cem\\u003ePNPLA2\\u003c/em\\u003e, \\u003cem\\u003eMGLL\\u003c/em\\u003e, \\u003cem\\u003ePLIN1\\u003c/em\\u003e, \\u003cem\\u003eAQP7\\u003c/em\\u003e) were summed and the total values (Rt) were used to rank the genes. The results are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. As can be seen, at T1 (baseline) the ratio of the number of genes with an Rt \\u0026lt; -1.5 vs. that of genes with Rt\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.5 is 4:28 but at T2 (reduced weight, but negative energy balance) this ratio is 21:10. Comparing T1 with T2 it seems that the interaction between classical lipolysis and the autolysosome system has intensified, revealed by a more predominant negative correlation between the genes of both processes at T2. The correlations of the gene expression changes during WL (T2 minus T1) of each of the selected genes vs. the expression changes of the five classical lipolysis genes is in agreement with such a reinforcement of a negative correlation.\\u003c/p\\u003e \\u003cp\\u003eAt T3 (reduced weight, energy balance) the ratio of the number of genes with an Rt \\u0026lt; -1.5 vs. that of genes with an Rt\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.5 is 2:13. This ratio is similar to that at T1 indicating that the interaction between classical lipolysis and the autolysosome system was reduced again when participants had returned to a state of energy balance while maintaining their weight loss. The correlation results of the gene expression changes during WS (T3 minus T2) of each of the selected genes vs. the expression changes of the five classical lipolysis genes support such a downscaling of the interaction. Notably, the number of genes with an Rt\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.5 or Rt \\u0026lt; -1.5 at T3 is only half of that at T1 or T2. Overall, the correlations are considerably weaker at T3.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAnalysis of the fold changes of the classical lipolysis and autolysosome genes\\u003c/h2\\u003e \\u003cp\\u003eThe fold changes of the genes for classical lipolysis and of the autolysosome genes that negatively correlated with the classical lipolysis genes with an Rt \\u0026lt; -1.5 have been listed in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. For WL (T1-T2) this concerned 16 genes and for WS (T2-T3) 21 genes, of which 11 were shared. During WL the classical lipolysis genes are significantly downregulated, while all the negatively correlating genes except for \\u003cem\\u003eATG16L2\\u003c/em\\u003e, are significantly upregulated. In the WS period the situation reverses for all of the significantly differentially expressed genes. The classical lipolysis genes are upregulated, although \\u003cem\\u003eLIPE\\u003c/em\\u003e and \\u003cem\\u003ePLIN1\\u003c/em\\u003e not significantly. The negatively correlating autolysosome genes are downregulated, but \\u003cem\\u003eHIF1A\\u003c/em\\u003e, \\u003cem\\u003ePRCP\\u003c/em\\u003e and \\u003cem\\u003eCTSK\\u003c/em\\u003e not significantly. The reversal of the direction of the fold change of both groups of genes results in negative correlations during WL as well as WS.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCell-type and tissue-type identification\\u003c/h2\\u003e \\u003cp\\u003eIn order to learn whether the interaction between classical lipolysis and the autolysosome is established in mature adipocytes, the relative RNA expression of genes was assessed for different cell types of the subcutaneous adipose tissue consulting the ProteinAltas database (Table\\u0026nbsp;2). In this analysis, the five classical lipolysis genes and the autolysosome genes with an Rt \\u0026lt; -1.5 from T1-T2 as well as from T2 were included. This analysis showed that the classical lipolysis genes are expressed exclusively in mature adipocytes whereas the autolysosome genes are not. They are active in other types of cells of the adipose tissue. The included autolysosome genes together covered all phases of autolysosome formation and were not confined to a particular phase.\\u003c/p\\u003e \\u003cp\\u003eIn addition, the subcellular localisation of the proteins of those genes was assessed from the GeneCards database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\u003ca href=\\\"http://www.clinicaltrials.gov\\\" target=\\\"_blank\\\"\\u003ewww.genecards.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.genecards.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). The subcellular compartment scoring at the two levels with the highest relative protein abundance (4 and 5) are marked in Table\\u0026nbsp;2. 13 out of 20 autolysosome genes of T2 are marked \\u0026lsquo;\\u003cem\\u003elysosome\\u003c/em\\u003e\\u0026rsquo; and the same number is marked \\u0026lsquo;\\u003cem\\u003eextracellular\\u003c/em\\u003e\\u0026rsquo;.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eA possible role for integrins\\u003c/h2\\u003e \\u003cp\\u003eThe interaction between adipocytes and other cells in the adipose tissue suggests that signals are transferred between the cells, which could involve surface proteins. Previously, we have identified a cluster with leukocyte-specific integrins that plays a role in weight regain of participants of the YoYo-study\\u003csup\\u003e18\\u003c/sup\\u003e. To investigate if this cluster could be involved in the present interaction between classical lipolysis and the autolysosome, correlation analysis was performed between the five classical lipolysis genes, autolysosome genes (Rt \\u0026lt; -1.5), and the six genes of the identified \\u0026lsquo;\\u003cem\\u003enarrow integrin cluster\\u003c/em\\u003e\\u0026rsquo; (\\u003cem\\u003eITGAM\\u003c/em\\u003e, \\u003cem\\u003eITGAX\\u003c/em\\u003e, \\u003cem\\u003eITGAL\\u003c/em\\u003e, \\u003cem\\u003eITGB2\\u003c/em\\u003e, \\u003cem\\u003eTGFB1\\u003c/em\\u003e, \\u003cem\\u003eCTSS\\u003c/em\\u003e). Hierarchical clustering (Suplement Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) shows that the expression changes of the integrin cluster genes correlate negatively with the expression changes of the classical lipolysis genes and positively with the expression changes of the autolysosome genes during WL (T2 minus T1) and WS (T3 minus T2). However, during WS the correlations seem to be less strong as compared to during WL. An overview of the coefficients of the classical lipolysis genes after correlation with the genes of the \\u0026lsquo;\\u003cem\\u003ebroad integrin cluster\\u003c/em\\u003e\\u0026rsquo; (narrow cluster including \\u003cem\\u003eACTN1\\u003c/em\\u003e, \\u003cem\\u003eITGA5\\u003c/em\\u003e, \\u003cem\\u003eICAM3\\u003c/em\\u003e, \\u003cem\\u003ePPIB\\u003c/em\\u003e, \\u003cem\\u003eDMD\\u003c/em\\u003e, \\u003cem\\u003ePLOD2\\u003c/em\\u003e, \\u003cem\\u003eSPARCL1\\u003c/em\\u003e) can be seen in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA for WL and WS, and with the genes of the narrow integrin cluster in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB for T1, T2 and T3. It shows that from T1 to T2 correlation of the classical lipolysis with the integrin cluster intensifies, whereas at T3 the data do no longer support such an interaction.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"DISCUSSION\",\"content\":\"\\u003cp\\u003eHere we have investigated the possible interaction of classical lipolysis with the autolysosome in human adipose tissue, which was previously revealed by the negative correlation of \\u003cem\\u003eATG7\\u003c/em\\u003e and associated autolysosome genes with the classical lipolysis genes \\u003cem\\u003ePNPLA2\\u003c/em\\u003e and \\u003cem\\u003eLIPE\\u003c/em\\u003e\\u003csup\\u003e10\\u003c/sup\\u003e. In the present study we show that during weight loss, i.e. under a negative energy balance, an interaction between the classical lipolysis and the autolysosome system is indeed established demonstrated by an intensifying of the negative correlation between the genes of both metabolic processes. Surprisingly, whereas the classical lipolysis is active in mature adipocytes, the associated autolysosome system is not but seems to operate from other types of cells of the subcutaneous adipose tissue. After returning to a state of energy balance for 4 weeks, most genes have switched their direction of expression and the interaction between the classical lipolysis and autolysosome system is diminished (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eTo establish the interaction between the two metabolic systems in different cells, a connection between the cells needs to be made. Our observations indicate that this could involve the leukocyte integrin gene cluster that was previously reported in relation to the risk of weight regain in the YoYo-study\\u003csup\\u003e18\\u003c/sup\\u003e. Based on the significant differential expression during WL (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) and the negative correlations with the classical lipolysis genes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA), this mainly concerns \\u003cem\\u003eCTSS\\u003c/em\\u003e, \\u003cem\\u003eITGAM\\u003c/em\\u003e, \\u003cem\\u003eITGAX\\u003c/em\\u003e, \\u003cem\\u003eITGAL\\u003c/em\\u003e, \\u003cem\\u003eITGB2 and TGFB1\\u003c/em\\u003e, referred to as the narrow integrin cluster. A heterodimer between ITGAL (CD11A) and ITGB2 (CD18) represents the receptor for intercellular adhesion molecules (ICAMs). The gene expression changes of \\u003cem\\u003eICAM3\\u003c/em\\u003e correlate positively with the expression changes of the \\u003cem\\u003eITGAL\\u003c/em\\u003e gene during WL and WS (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). However, unlike \\u003cem\\u003eITGAL\\u003c/em\\u003e the expression changes of \\u003cem\\u003eICAM3\\u003c/em\\u003e do not correlate negatively with the changes of the classical lipolysis genes. It suggests that ICAM3 is of limited importance for the observed interaction of adipocytes with others cells. Both ITGAM (CD11B) and ITGAX (CD11C) form heterodimers with ITGB2 (CD18) and these dimers function as receptors for fibrinogen and for inactive complement factor C3b (iC3b). In this regard, the ITGAM/ITGB2 dimer is referred to as the iC3b receptor 3 (CR3) and the ITGAX/ITGB2 dimer as the iC3b receptor 4 (CR4). From in vitro experiments we know that mature SGBS adipocytes secrete C3\\u003csup\\u003e19\\u003c/sup\\u003e, which is known to spontaneously split into C3a and C3b. Whereas C3a leaves the site to act in the adipose tissue as anaphylatoxin, C3b can attach to glycoproteins on the self-surface of cells by its exposed thioester-containing domain\\u003csup\\u003e20\\u003c/sup\\u003e, for instance to fibronectin\\u003csup\\u003e21\\u003c/sup\\u003e. There it can be converted to iC3b by the action of Complement Factor I (CFI), Complement Factor H (CFH), Membrane Cofactor Protein (MCP, CD46) and Complement C3b/C4b Receptor 1 (CR1, CD35). The genes for all of these proteins are expressed in the adipose tissue. We therefore speculate that iC3b on the surface of adipocytes in connection with the receptors CR3 and CR4 could establish the contact between adipocytes and other cell types, likely leukocytes.\\u003c/p\\u003e \\u003cp\\u003eThe downregulation of lipolysis genes and upregulation of autolysosome genes during the WL period could both be involved in the release of mechanical stress of the adipocytes. During a negative energy balance the adipocytes shrink and mechanical stress will build up in the adipocyte ECM. To avoid further increase of stress, the shrinking due to the release of lipids, and thus lipolysis, should be diminished. As a second measure to release stress, the ECM could be modified. This can be accomplished by extracellular enzymes able to attack the ECM proteins and their post-transcriptional modifications. Our present findings demonstrate that adipocytes under stress during a negative energy balance invoke the assistance of other cells, which activate their own autolysosome system in order to excrete catabolic enzymes. Recently we have proposed a similar action of leukocytes as part of the immune-based obesogenic memory in relation to weight regain after weight loss\\u003csup\\u003e22\\u003c/sup\\u003e. It suggests that modification of the adipocyte ECM with the assistance of leukocytes or other cell types is a general phenomenon that can explain different aspects of weight regulation.\\u003c/p\\u003e \\u003cp\\u003eAt the selection of the genes for this study we have focussed on lysosomal genes that code for enzymes. This allowed us to determine whether the autolysosome action depends on a defined enzymatic activity. At T2, 15 of the 21 genes with an Rt \\u0026lt; -1.5 code for an enzyme. 12 of those are marked as \\u0026lsquo;\\u003cem\\u003esecreted\\u003c/em\\u003e\\u0026rsquo; or as present in the \\u0026lsquo;\\u003cem\\u003eplasma membrane\\u003c/em\\u003e\\u0026rsquo; (Table\\u0026nbsp;2). The three remaining genes, \\u003cem\\u003eLIPA\\u003c/em\\u003e, \\u003cem\\u003eATG4C\\u003c/em\\u003e, \\u003cem\\u003eGALC\\u003c/em\\u003e scored on Genecards \\u0026lsquo;2\\u0026rsquo; or \\u0026lsquo;3\\u0026rsquo; (with \\u0026lsquo;5\\u0026rsquo; being the highest score) for the locations \\u0026lsquo;\\u003cem\\u003eextracellular\\u003c/em\\u003e\\u0026rsquo; and \\u0026lsquo;\\u003cem\\u003eplasma membrane\\u003c/em\\u003e\\u0026rsquo;. Overall it shows that at T2 the majority of genes engaged in a negative correlation with the lipolysis genes are secreted or on the outside of the cell. Their enzymatic activities are identified as \\u0026lsquo;proteinase or peptidase\\u0026rsquo; (\\u003cem\\u003eATG4C\\u003c/em\\u003e, \\u003cem\\u003eCPVL\\u003c/em\\u003e, \\u003cem\\u003eCTSC\\u003c/em\\u003e, \\u003cem\\u003eCTSS\\u003c/em\\u003e, \\u003cem\\u003ePRCP\\u003c/em\\u003e), \\u0026lsquo;glycosidase\\u0026rsquo; (\\u003cem\\u003eCTBS\\u003c/em\\u003e, \\u003cem\\u003eGLA\\u003c/em\\u003e, \\u003cem\\u003eGUSB\\u003c/em\\u003e, \\u003cem\\u003eMANBA\\u003c/em\\u003e), \\u0026lsquo;amidase\\u0026rsquo; (\\u003cem\\u003eGALC\\u003c/em\\u003e, \\u003cem\\u003eHEXB\\u003c/em\\u003e, \\u003cem\\u003eNAAA\\u003c/em\\u003e), \\u0026lsquo;thiol reductase\\u0026rsquo; (\\u003cem\\u003eIFI30\\u003c/em\\u003e), \\u0026lsquo;lipase\\u0026rsquo; (\\u003cem\\u003eLIPA\\u003c/em\\u003e), and \\u0026lsquo;ribonuclease\\u0026rsquo; (\\u003cem\\u003eRNASET2\\u003c/em\\u003e). Apparently, the involved autolysosome genes cover a variety of enzymatic activities, of which most can be deployed to modify the ECM.\\u003c/p\\u003e \\u003cp\\u003eOur findings do not support a transfer of lipid breakdown from classical lipolysis to lipophagy in human adipocytes, although a low level of lipid breakdown cannot be excluded by our present analyses. Despite the reduction of the expression of lipolysis genes during WL, the plasma level of FFA increases by 45% \\u003csup\\u003e23\\u003c/sup\\u003e. OF the corresponding proteins for classical lipolysis only data for LIPE, MGLL and PLIN1 are available\\u003csup\\u003e24\\u003c/sup\\u003e, which during WL go down with a factor of 1.03x, 1.11x, and 1.03x, respectively. Apparently, protein abundance cannot explain the increase of the plasma FFA level. A possible explanation for the increased FFA level is by the regulation of lipolysis. \\u003cem\\u003eADRB2\\u003c/em\\u003e and \\u003cem\\u003eABHD5\\u003c/em\\u003e which stimulate lipolysis, are significantly upregulated whereas \\u003cem\\u003eNPR3\\u003c/em\\u003e, which inhibits lipolysis by the removal of natriuretic peptides\\u003csup\\u003e3\\u003c/sup\\u003e, is significantly downregulated (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). A likely scenario therefore is that under a negative energy balance, adipocytes shrink leading to ECM stress (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). This will induce downregulation of the lipolysis genes and proteins, but the energy demand of the body will partly overrule this demand by upregulating lipolysis stimulators and by downregulating lipolysis inhibitors. Adipocytes will then look for another way to be released from ECM stress, i.e. by invoking the assistance of other cells secreting ECM modifying enzymes via their autolysosome system. Notably, this is one of many scenarios, which can now be tested by extra investigations.\\u003c/p\\u003e \\u003cp\\u003eThe autophagic and endolysosomal systems are known to serve as secretory pathways, which has been reviewed by Buratta et al.\\u003csup\\u003e25\\u003c/sup\\u003e. Also the cell-endogenous response of autophagy to mechanical stress has been reported\\u003csup\\u003e17\\u003c/sup\\u003e. Further, the connection between autophagy and adipose tissue biology, in particular adipogenesis, has been under study\\u003csup\\u003e15, 26 27\\u003c/sup\\u003e. Interestingly, it has been observed that ECM components by binding to cell surface receptors can activate the autophagic system\\u003csup\\u003e28, 29\\u003c/sup\\u003e. The involvement of integrins in autophagy through ECM binding has also been shown\\u003csup\\u003e30\\u003c/sup\\u003e. In the present study we show that these reported findings can work together to establish an interaction in the human adipose tissue between classical lipolysis and the autolysosome in different cells with the supposed purpose of releasing mechanical stress from the shrinking adipocyte. The regulatory mechanism behind this interaction remains presently unknown.\\u003c/p\\u003e \\u003cp\\u003eAs can be seen in Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB, after return to a situation of balanced energy intake, the interaction of the classical lipolysis with the autolysosome through the integrin cluster is no longer sustained. It suggests that by the end of the WS phase, four weeks after ending the reduced calorie diet, the adipocytes have lost most of their mechanical stress. During the WS period the adipocytes regain 50\\u0026ndash;60% of the lost volume\\u003csup\\u003e23\\u003c/sup\\u003e. As such it seems no longer needed to resolve the stress by modification of the ECM.\\u003c/p\\u003e \\u003cp\\u003eIn summary, we have shown that under a negative energy balance an interaction is established in the human subcutaneous adipose tissue between the classical lipolysis in the adipocytes and the autolysosome system in other cells (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Our observations further indicate that the connection between the cells is formed via ITGAM/ITGB2 and ITGAX/ITGB2 integrins, possibly with involvement of iC3b for which these integrins are the receptors. It is proposed that this interaction serves to reduce mechanical stress of shrinking adipocytes by the modification of the ECM when gene and protein regulation do not result in a sufficient downregulation of lipolysis. When energy balance is restored the interaction is no longer sustained. It should be noted that our observations are majorly based on correlation analysis between gene expression data. Although they generate interesting leads for further investigation, molecular biological and cell morphological approaches need to be applied in follow-up experiments to provide more clear evidence and to reveal the regulatory mechanism behind the observed transient interaction.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eCOMPETING INTERESTS\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare that there are no competing financial interests.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eACKNOWLEDGEMENTS\\u003c/h2\\u003e \\u003cp\\u003eThe authors like to thank Dr. Nadia Roumans for assisting with generating the genomic data. EM performed the analyses and composed the manuscript, FB and MvB advised about the contents of the manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eWatt MJ, Steinberg GR. Regulation and function of triacylglycerol lipases in cellular metabolism. Biochem J 2008; 414(3): 313\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGranneman JG, Moore HP, Granneman RL, Greenberg AS, Obin MS, Zhu Z. Analysis of lipolytic protein trafficking and interactions in adipocytes. J Biol Chem 2007; 282(8): 5726\\u0026ndash;35.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLafontan M, Moro C, Berlan M, Crampes F, Sengenes C, Galitzky J. Control of lipolysis by natriuretic peptides and cyclic GMP. Trends Endocrinol Metab 2008; 19(4): 130\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCapel F, Viguerie N, Vega N, Dejean S, Arner P, Klimcakova E \\u003cem\\u003eet al.\\u003c/em\\u003e Contribution of energy restriction and macronutrient composition to changes in adipose tissue gene expression during dietary weight-loss programs in obese women. J Clin Endocrinol Metab 2008; 93(11): 4315\\u0026ndash;22.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKoppo K, Valle C, Siklova-Vitkova M, Czudkova E, de Glisezinski I, van de Voorde J \\u003cem\\u003eet al.\\u003c/em\\u003e Expression of lipolytic genes in adipose tissue is differentially regulated during multiple phases of dietary intervention in obese women. Physiol Res 2013; 62(5): 527\\u0026ndash;35.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVink RG, Roumans NJ, Fazelzadeh P, Tareen SH, Boekschoten MV, van Baak MA, Mariman EC. Adipose tissue gene expression is differentially regulated with different rates of weight loss in overweight and obese humans. Int J Obes (Lond) 2017; 41(2): 309\\u0026ndash;316.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoldman S, Zhang Y, Jin S. Autophagy and adipogenesis: implications in obesity and type II diabetes. Autophagy 2010; 6(1): 179\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWard C, Martinez-Lopez N, Otten EG, Carroll B, Maetzel D, Singh R \\u003cem\\u003eet al.\\u003c/em\\u003e Autophagy, lipophagy and lysosomal lipid storage disorders. Biochim Biophys Acta 2016; 1861(4): 269\\u0026ndash;84.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKaushik S, Cuervo AM. Degradation of lipid droplet-associated proteins by chaperone-mediated autophagy facilitates lipolysis. Nat Cell Biol 2015; 17(6): 759\\u0026ndash;70.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eXu Q, Mariman ECM, Roumans NJT, Vink RG, Goossens GH, Blaak EE, Jocken JWE. Adipose tissue autophagy related gene expression is associated with glucometabolic status in human obesity. Adipocyte 2018; 7(1): 12\\u0026ndash;19.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVink RG, Roumans NJ, Arkenbosch LA, Mariman EC, van Baak MA. The effect of rate of weight loss on long-term weight regain in adults with overweight and obesity. Obesity (Silver Spring) 2016; 24(2): 321\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eEnocksson S, Shimizu M, Lonnqvist F, Nordenstrom J, Arner P. Demonstration of an in vivo functional beta 3-adrenoceptor in man. J Clin Invest 1995; 95(5): 2239\\u0026ndash;45.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYu L, Li Y, Grise A, Wang H. CGI-58: Versatile Regulator of Intracellular Lipid Droplet Homeostasis. Adv Exp Med Biol 2020; 1276: 197\\u0026ndash;222.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBordi M, De Cegli R, Testa B, Nixon RA, Ballabio A, Cecconi F. A gene toolbox for monitoring autophagy transcription. Cell Death Dis 2021; 12(11): 1044.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRomero M, Zorzano A. Role of autophagy in the regulation of adipose tissue biology. Cell Cycle 2019; 18(13): 1435\\u0026ndash;1445.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFerhat M, Funai K, Boudina S. Autophagy in Adipose Tissue Physiology and Pathophysiology. Antioxid Redox Signal 2019; 31(6): 487\\u0026ndash;501.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShim MS, Liton PB. The physiological and pathophysiological roles of the autophagy lysosomal system in the conventional aqueous humor outflow pathway: More than cellular clean up. Prog Retin Eye Res 2022; 90: 101064.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRoumans NJ, Vink RG, Fazelzadeh P, van Baak MA, Mariman EC. A role for leukocyte integrins and extracellular matrix remodeling of adipose tissue in the risk of weight regain after weight loss. Am J Clin Nutr 2017; 105(5): 1054\\u0026ndash;1062.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQiao Q, Bouwman FG, Renes J, Mariman ECM. An in vitro model for hypertrophic adipocytes: Time-dependent adipocyte proteome and secretome changes under high glucose and high insulin conditions. J Cell Mol Med 2020; 24(15): 8662\\u0026ndash;8673.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMorgan HP, Schmidt CQ, Guariento M, Blaum BS, Gillespie D, Herbert AP \\u003cem\\u003eet al.\\u003c/em\\u003e Structural basis for engagement by complement factor H of C3b on a self surface. Nat Struct Mol Biol 2011; 18(4): 463\\u0026ndash;70.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHindmarsh EJ, Marks RM. Complement activation occurs on subendothelial extracellular matrix in vitro and is initiated by retraction or removal of overlying endothelial cells. J Immunol 1998; 160(12): 6128\\u0026ndash;36.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003evan Baak MA, Mariman ECM. Obesity-induced and weight-loss-induced physiological factors affecting weight regain. Nat Rev Endocrinol 2023; 19(11): 655\\u0026ndash;670.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVink RG, Roumans NJ, Mariman EC, van Baak MA. Dietary weight loss-induced changes in RBP4, FFA, and ACE predict weight regain in people with overweight and obesity. Physiol Rep 2017; 5(21).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRoumans NJT, Vink RG, Bouwman FG, Fazelzadeh P, van Baak MA, Mariman ECM. Weight loss-induced cellular stress in subcutaneous adipose tissue and the risk for weight regain in overweight and obese adults. Int J Obes (Lond) 2017; 41(6): 894\\u0026ndash;901.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBuratta S, Tancini B, Sagini K, Delo F, Chiaradia E, Urbanelli L, Emiliani C. Lysosomal Exocytosis, Exosome Release and Secretory Autophagy: The Autophagic- and Endo-Lysosomal Systems Go Extracellular. Int J Mol Sci 2020; 21(7).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang Y, Goldman S, Baerga R, Zhao Y, Komatsu M, Jin S. Adipose-specific deletion of autophagy-related gene 7 (atg7) in mice reveals a role in adipogenesis. Proc Natl Acad Sci U S A 2009; 106(47): 19860\\u0026ndash;5.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao Y, Ma K, Kang Y, Liu W, Liu X, Long X \\u003cem\\u003eet al.\\u003c/em\\u003e Type I collagen reduces lipid accumulation during adipogenesis of preadipocytes 3T3-L1 via the YAP-mTOR-autophagy axis. Biochim Biophys Acta Mol Cell Biol Lipids 2022; 1867(9): 159181.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNeill T, Schaefer L, Iozzo RV. Instructive roles of extracellular matrix on autophagy. Am J Pathol 2014; 184(8): 2146\\u0026ndash;53.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen CG, Iozzo RV. Extracellular matrix guidance of autophagy: a mechanism regulating cancer growth. Open Biol 2022; 12(1): 210304.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLock R, Debnath J. Extracellular matrix regulation of autophagy. Curr Opin Cell Biol 2008; 20(5): 583\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4246664/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4246664/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground/objectives:\\u003c/strong\\u003eDuring a period of weight loss lipolysis genes in human subcutaneous adipose tissue are downregulated despite the increase in plasma free fatty acids. It has been proposed that lipid breakdown is taken over by the autolysosome. Here we test the relation between lipolysis and the autolysosome.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSubjects/methods:\\u003c/strong\\u003eGene and protein expression data from the YoYo-study were used for correlation analysis including genes coding for lipases and regulators of lipolysis, for autolysosome proteins and lysosomal enzymes, and the genes coding for components of a previously identified integrin cluster. For all these genes the cell type and compartment of expression was obtained from databases. Correlation analysis was performed using the gene expression values before weight loss (WL), after WL, and after a subsequent weight stable period (WS), and using the expression changes during WL and WS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003eDuring WL a significant negative correlation originated between the lipolysis and autolysosome genes. Genes of the integrin cluster correlated negative with the lipolysis genes and positive with the autolysosome genes. Surprisingly, the lipolysis genes were expressed in mature adipocytes while the autolysosome genes were not, but were expressed in other types of cells of the adipose tissue. Most of the correlated autolysosome genes were secreted or on the plasma membrane. After WL most of the genes reversed their direction of expression. During WS the correlation between lipolysis and autolysosome genes lost significance and the correlation with the integrin genes disappeared.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusions:\\u003c/strong\\u003eOur findings do not support a transfer of lipid breakdown from lipolysis to the autolysosome in subcutaneous adipocytes during WL. Instead, we observe an intercellular interaction between lipolysis in mature adipocytes and the autolysosome of other cells in the adipose tissue. This interaction is probably mediated by integrin-mediated contact between the cells. A model for the observed interaction based on ECM-stress is presented.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Weight Loss-induced Interaction Between Classical Lipolysis and the Autolysosome in Human Subcutaneous Adipose Tissue\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-04-22 10:18:49\",\"doi\":\"10.21203/rs.3.rs-4246664/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"0ea9f8b8-ee10-42d3-8da6-1df6e6651d90\",\"owner\":[],\"postedDate\":\"April 22nd, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":30986326,\"name\":\"Health sciences/Diseases/Nutrition disorders/Obesity\"},{\"id\":30986327,\"name\":\"Biological sciences/Physiology/Metabolism/Fat metabolism\"},{\"id\":30986328,\"name\":\"Biological sciences/Biochemistry/Lipids/Fatty acids\"},{\"id\":30986329,\"name\":\"Biological sciences/Physiology/Metabolism/Homeostasis\"}],\"tags\":[],\"updatedAt\":\"2024-05-07T18:18:30+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-04-22 10:18:49\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4246664\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4246664\",\"identity\":\"rs-4246664\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}