Amelioration of non-alcoholic fatty liver disease by targeting adhesion G protein-coupled receptor F1 (Adgrf1)

  1. Mengyao Wu
  2. Tak-Ho Lo
  3. Liping Li
  4. Jia Sun
  5. Chujun Deng
  6. Ka-Ying Chan
  7. Xiang Li
  8. Steve Ting-Yuan Yeh
  9. Jimmy Tsz Hang Lee
  10. Pauline Po Yee Lui
  11. Aimin Xu
  12. Chi-Ming Wong  Is a corresponding author
  1. Department of Chemistry and Chemical Engineering, Guangzhou University, China
  2. Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong
  3. Zhujiang Hospital, Southern Medical University, China
  4. Ionis Pharmaceuticals, United States
  5. Department of Medicine, University of Hong Kong, Hong Kong
  6. State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, China
  7. Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong
  8. Hong Kong Polytechnic University, Shenzhen Research Institute, China

Abstract

Background:

Recent research has shown that the adhesion G protein-coupled receptor F1 (Adgrf1; also known as GPR110; PGR19; KPG_012; hGPCR36) is an oncogene. The evidence is mainly based on high expression of Adgrf1 in numerous cancer types, and knockdown Adgrf1 can reduce the cell migration, invasion, and proliferation. Adgrf1 is, however, mostly expressed in the liver of healthy individuals. The function of Adgrf1 in liver has not been revealed. Interestingly, expression level of hepatic Adgrf1 is dramatically decreased in obese subjects. Here, the research examined whether Adgrf1 has a role in liver metabolism.

Methods:

We used recombinant adeno-associated virus-mediated gene delivery system, and antisense oligonucleotide was used to manipulate the hepatic Adgrf1 expression level in diet-induced obese mice to investigate the role of Adgrf1 in hepatic steatosis. The clinical relevance was examined using transcriptome profiling and archived biopsy specimens of liver tissues from non-alcoholic fatty liver disease (NAFLD) patients with different degree of fatty liver.

Results:

The expression of Adgrf1 in the liver was directly correlated to fat content in the livers of both obese mice and NAFLD patients. Stearoyl-coA desaturase 1 (Scd1), a crucial enzyme in hepatic de novo lipogenesis, was identified as a downstream target of Adgrf1 by RNA-sequencing analysis. Treatment with the liver-specific Scd1 inhibitor MK8245 and specific shRNAs against Scd1 in primary hepatocytes improved the hepatic steatosis of Adgrf1-overexpressing mice and lipid profile of hepatocytes, respectively.

Conclusions:

These results indicate Adgrf1 regulates hepatic lipid metabolism through controlling the expression of Scd1. Downregulation of Adgrf1 expression can potentially serve as a protective mechanism to stop the overaccumulation of fat in the liver in obese subjects. Overall, the above findings not only reveal a new mechanism regulating the progression of NAFLD, but also proposed a novel therapeutic approach to combat NAFLD by targeting Adgrf1.

Funding:

This work was supported by the National Natural Science Foundation of China (81870586), Area of Excellence (AoE/M-707/18), and General Research Fund (15101520) to CMW, and the National Natural Science Foundation of China (82270941, 81974117) to SJ.

Editor's evaluation

These valuable findings presented by Wu et al. advance our understanding in novel cell signaling regulators of hepatic metabolism. The evidence supporting these conclusions is solid, utilizing in vivo and in vitro gain- and loss-of-function studies. This work will be of interest to biologists working in the field of hepatic steatosis.

https://doi.org/10.7554/eLife.85131.sa0

eLife digest

Being overweight or obese increases the risk of developing numerous medical conditions including non-alcoholic fatty liver disease (NAFLD), where excess fat accumulates in the liver. NAFLD is a major global health issue affecting about 25% of the world's population and, if left untreated, can lead to liver inflammation as well as serious complications such as type 2 diabetes, heart disease, and liver cancer.

Currently, there are no medications which specifically treat NFALD. Instead, only medications which help to manage the associated health complications are available. Therefore, a better understanding of NFALD is required to help to develop new strategies for diagnosing and treating the progression of this disease.

A family of proteins known as GPCRs have crucial roles in regulating various bodily processes and are therefore commonly targeted for the treatment of disease. By identifying the GPCRs specifically involved in liver fat accumulation, new treatments for NFALD could be identified. Previous studies identified a GPCR known as Adgrf1 that is mainly found in liver cells, but its role remained unclear.

To investigate the function of Adgrf1 in the liver, Wu et al. studied obese mice and human patients with NAFLD. The experiments showed that elevated levels of Adgrf1 in human and mouse livers led to increased fat accumulation. On the other hand, livers with lower levels of Adgrf1 exhibited reduced fat levels. A technique called RNA sequencing revealed that Adgrf1 induces expression of enzymes involved in fat synthesis, including a key regulator called Scd1. Treating mice with high levels of liver fat with molecules that inhibit Scd1 decreased the symptoms of Adgrf1-mediated fatty liver disease.

These findings suggest therapies that decrease the levels of Adgrf1 may help to stop too much fat accumulating in the liver of human patients who are at risk of developing NAFLD. Further research is needed to confirm the effectiveness and safety of targeting Adgrf1 in humans and to develop suitable candidate drugs for the task.

Introduction

Liver is a vital organ as it is the site for undergoing a number of crucial physiological processes, including digestion, metabolism, immunity, and storage of nutrients (Younossi et al., 2016). Overstorage of lipid in the hepatocytes not caused by alcohol is known as non-alcoholic fatty liver disease (NAFLD), which is the most common liver pathological condition with a worldwide prevalence of 25% (Cotter and Rinella, 2020). The development of NAFLD is contributed by many factors such as lipid metabolism disorders, over- or mal-nutrition, inflammation, virus infection, or liver injuries (Peng et al., 2020). NAFLD usually does not entail any symptoms at early stages. However, if left untreated, NAFLD accounts for approximately 85% of all chronic non-communicable diseases (NCDs), such as type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), and chronic kidney disease (CKD) (Allen et al., 2019; Zhou et al., 2019). In addition, NAFLD may progress to non-alcoholic steatohepatitis (NASH) with fibrosis, cirrhosis, or even hepatocellular carcinoma (HCC) (Rinella and Sanyal, 2016). Therefore, NAFLD imposes high economic and social burdens in terms of work productivity, health-related life quality, and use of healthcare resources (Zhou et al., 2019).

Improvement in managing NAFLD helps to resolve at least partially the progression of these diseases. Stopping the progression of NAFLD by lifestyle modifications such as increasing physical exercise activity and reduction of hypercaloric diet is only effective during the early stages before there is fibrosis. No medication is available to reverse the excessive fat storage in the liver once NASH developed. Therefore, it is urgently needed to unravel the mechanisms of NAFLD in order to accelerate the development, implementation, and explore new targets for the development of diagnostic tests and cost-effective therapies.

G protein-coupled receptors (GPCRs) are the largest and most diverse family of membrane receptor that play important roles in regulating most cellular and physiological processes (Yang et al., 2021). GPCRs are major targets for currently approved drugs (Hauser et al., 2017; Sriram and Insel, 2018). A few GPCRs have been shown to play key roles in NAFLD, and modulating their activities to ameliorate liver-related metabolic syndrome was proposed as NAFLD treatment (Yang and Zhang, 2021; Kurtz et al., 2021). However, currently proposed targets for GPCR-medicated NAFLD treatment are not exclusively expressed in hepatocytes, thus the potential side effects on other organs should be considered.

Human Adgrf1 was identified by phylogenetic analysis based on highly conserved amino acid sequences of the GPCR transmembrane domains in 2002 (Fredriksson et al., 2002). Mouse ortholog of hAdgrf1 was identified by the same research team 2 y later (Bjarnadóttir et al., 2004) and various splice variants were detected in deep sequencing experiments (Bjarnadóttir et al., 2007; Lum et al., 2010). So far, most Adgrf1-related studies focused on its tumorigenicity. In general, overexpression of Adgrf1 was observed in various cancers, and it was required to promote cancer cell survival, proliferation, and migration (Liu et al., 2018; Zhu et al., 2019b; Shi and Zhang, 2017; Bhat et al., 2018; Ma et al., 2017; Nam et al., 2022). Therefore, it was suggested that targeting Adgrf1 may represent a new therapeutic strategy for anticancer treatment. It was also reported that Adgrf1 is required for proper fetal brain development and amelioration of neuroinflammation (Lee et al., 2016a). However, Adgrf1 is predominantly expressed in health adult livers. The function of hepatic Adgrf1 remains unexplored.

In this study, we provide the first evidence that Adgrf1 induces the expression of Scd1, which contributes to NAFLD. By HFD-induced NAFLD mouse model (Nakamura and Terauchi, 2013), it is also shown that the repression of hepatic Adgrf1 expression is a potential protective mechanism of preventing overaccumulation of lipid in liver. Importantly, the findings not only reveal a new mechanism regulation of the progression of NAFLD, but also proposed a novel therapeutic approach to combat NAFLD by targeting Adgrf1.

Methods

Animals

All animal procedures were approved by the Animal Subjects Ethics Sub-Committee of the Hong Kong Polytechnic University and were conducted in accordance with the guidelines of the Centralized Animals Facilities (ethics number: 19-20/78-HTI-R-OTHERS). In general, 8-week-old C57BL/6J male mice were housed in pathogen-free conditions at controlled temperature with a 12 hr light–dark cycle and access to food and water ad libitum. The 8-week-old male mice were divided into two groups and fed with either standard chow diet (STC, 18.3% protein, 10.2% fat, 71.5% carbohydrates, Research Diet Inc, New Brunswick, NJ) or high-fat diet (HFD, 20% protein, 45% fat, 35% carbohydrates, Research Diets Inc) for 8 wk. The sample size was calculated based on previous findings, suggesting that group sizes of n = 7–8 would be sufficient (Sellmann et al., 2017).

The recombinant adeno-associated virus vector rAAV2/8 transduction was conducted as described previously (Lee et al., 2016b; Cheng et al., 2022). Briefly, mice were tail vein injected with 3 × 1011 rAAV2/8 vector harboring either green fluorescent protein (GFP) or Adgrf1. For antisense oligonucleotide (ASO) delivery, validated ASOs against mouse Adgrf1 were provided by Ionis Pharmaceuticals and injected subcutaneously once a week at 5 mg/kg body weight to the mice. For Scd1 inhibitor delivery, MK-8245 (MedChemExpress, NJ) was gavage at 10 mg/kg once a week (Iida et al., 2018). All measurements were carried out in a randomized order.

Primary hepatocyte isolation and adenovirus infection

Primary hepatocytes from different groups of mice were isolated using a two-step perfusion method as previously described (Xu et al., 2022; Huang et al., 2017). Briefly, type II collagenase was perfused to mice at a flow rate of 10 ml/min. Liver was collected and mesh in serum-free DMEM and hepatocytes were pelleted by centrifugation. For the supernatant containing non-parenchymal cells (NPCs), gradient solutions of Percoll were used for extraction. For adenovirus viral infection experiments, serum-starved cells were infected with adenoviruses carrying mouse Adgrf1 cDNA to overexpress Adgrf1. Similar adenoviral vectors encoding the GFP gene were used as controls.

Cell culture and luciferase reporter assay

HEK293T cells were purchased from the ATCC (CRL-11268) with the cell line authentication test conducted by the Hong Kong University Pathology Laboratory, showing that the percent match is higher than 80% threshold for authentication and no mycoplasma contamination. HEK293T cells were cultured in DMEM supplemented with 10% FBS, 100 U/ml penicillin, and 100 μg/ml streptomycin at 37°C and 5% CO2. HEK293T cells were seeded in 6-well plates and were transfected with pGL3-Scd1 promoter and adenoviral vector expressing either Adgrf1 (ADV-Adgrf1) or GFP (ADV-GFP) by using the transfection reagent (#E4981, Promega, WI), following the manufacturer’s instruction. DHEA (C3270, APExBIO, TX) was added into cells at the concentration of 100 μM and incubated at 37°C for 24 hr. For the luciferase reporter assay, pRL-TK (Renilla luciferase) reporter plasmid was used as a transfection control. The luciferase assays were performed by using the Dual-Luciferase Reporter Assay System (#E1960, Promega).

Biochemical analysis

For glucose profile measurement, the blood glucose and insulin level were measured by collecting the blood samples from the tip of the tail using Accu-Chek glucometer (Roche Diagnostics, IN) as described (Wong et al., 2014). For the glucose tolerance test (GTT), insulin tolerance test (ITT), and pyruvate tolerance test (PTT), mice were fasted overnight prior to intraperitoneal injection of glucose (1 g/kg body weight [BW]; Sigma, St. Louis, MO), 0.75 U/kg BW insulin (Novolin R, Novo Nordisk, Bagsvaerd, Denmark), or 1 g/kg BW pyruvate (Sigma). Blood glucose levels were measured from the tip of tail vein at 15, 30, 60, 90, and 120 min after injection. For plasma and hepatic lipid level, serum levels of triglyceride (TG) and total cholesterol (CHO) were measured using commercial kit (BioSino, Biotechnology and Science Inc, China) according to the manufacturer’s instructions. Hepatic lipids were extracted using Folch methodology, and liver extract was dissolved in ethanol for TG and CHO measurement. Both serum and hepatic levels of free fatty acid (FFA) were measured using commercial kit (Solarbio, China) according to the manufacturer’s instructions. For liver function assay, the alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were measured in serum using commercial kits (Stanbio) according to the manufacturer’s instructions.

Histopathological and Western blot analysis

Hematoxylin and eosin (H&E) and Oil Red O (ORO) staining was performed on paraffin-embedded and frozen liver sections, respectively. Detailed procedures of H&E and ORO were described previously (Ye et al., 2016; Chen et al., 2017). Representative histopathological images were acquired with a light microscope (Olympus, Tokyo, Japan). Western blot analysis was performed as previously described (Lee et al., 2016b; Cheng et al., 2022; Xu et al., 2022; Huang et al., 2017). Briefly, total protein was extracted from tissues and cultured cells with RIPA lysis buffer (65 mM Tris-HCl pH 7.5, 150 mM NaCl, 1 mM EDTA, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS). Protein samples were then separated by gel electrophoresis and then transferred to PVDF membranes (IPVH00010, Merck Millipore, CA). The expression of protein was detected by a ChemiDoc MP Imaging System (Bio-Rad, Hercules, CA). Primary antibodies used are shown in Supplementary file 1.

Quantitative real-time PCR analysis

Total RNA was extracted with RNAiso Plus (#9109, TakaRa Bio Inc, Shiga, Japan) as previously described. RNA was reverse transcribed into cDNA with PrimeScript RT reagent Kit (#RR037, TakaRa Bio Inc). cDNA was then amplified with TB green Premix Ex Taq II (Til Rnase H Plus) (##RR820A, TakaRa Bio Inc). The real-time PCR was conducted with a LightCycler 96 RT-qPCR System (Roche, Basel, Switzerland). The relative quantity of the targeted RNA was calculated through normalization to the quantity of the corresponding GAPDH mRNA level. Detailed primer sequences are listed in Supplementary file 2.

Microarray and RNA sequencing

The livers of mice fed with either STC (n = 6) or HFD (n = 6) for 8 wk were sent to Kompetenzzentrum Fluoreszente Bioanalytik (Germany) for gene expression analysis using Affymetrix Mouse Exon 1.0 ST Array. RNA was extracted from the livers of mice treated with rAAV-Adgrf1 and ASO-Adgrf1 using RNeasy Kits (QIAGEN, Hilden, Germany) according to the instructions. RNA concentration was quantified using NanoDrop 2000 Spectrophotometer (Thermo Scientific, Waltham) and RNA quality was assessed using Agilent 2100 Bioanalyzer (Agilent, Santa Clara). 10 μg of total RNA from liver with RNA integrity number (RIN) > 7 was used in RNA-seq. RNA-seq was performed by BGI and analyzed by Dr. Tom system (BGI, Shenzhen, China). A heat map was created based on log2 transformed counts from different samples. To be included in the heat map, genes were required to have at least 1000 counts, totaled over all samples, where the standard deviation of the log2 had to exceed 2.

Human samples

Liver biopsy specimens were collected from nine biopsy-proven NAFLD patients (Xu et al., 2022). Liver sections with H&E staining were subjected to histological evaluation of steatosis. Simple steatosis was defined by the presence of macrovascular steatosis affecting at least 5% of hepatocytes without inflammatory foci and evidence of hepatocellular injury in the form of hepatocyte ballooning (Brunt et al., 1999). Individuals with a heavy alcohol-drinking history (≥40 g/day for up to 2 wk), drug-induced liver disease, and hepatitis virus infection were excluded from the study. Clinical parameters of individuals are summarized in Supplementary file 1. The human study was approved by the Zhujiang Hospital, Southern Medical University, Guangzhou, China (number: 2019-KY-097-01). Written informed consent was obtained from participants prior to their inclusion in the study.

Lipogenesis assay

Lipogenesis assay was performed as previously described (Akie and Cooper, 2015). Primary hepatocytes were seeded into 6-well plates and the cells washed with warm PBS twice one night prior to the assay. The hepatocytes were changed to serum starvation medium with 100 nM insulin and incubated overnight at 37°C. The lipogenesis medium was made up of 100 nM insulin, 10 μM cold acetate, and 0.5 μCi 3H-acetate and added and incubated for 2 hr. Cells were then washed with PBS twice and 0.1 N HCl was used to lyse cells. Lipids were extracted by addition of 500 µl of 2:1 chloroform-methanol (v/v). Total lipid content was then calculated by measuring 3H activity.

Statistical analysis

All experiments were performed at least twice, and each experimental group included n ≥ 7 mice. Representative data are presented as mean ± standard error of mean (SEM). All statistical analyses were performed with the GraphPad Prism software (version 9.0, GraphPad, CA). Statistical differences among the two groups was performed using the unpaired Student’s t-test or Mann–Whitney test for the comparison of variables with or without normal distribution, respectively. Correlation between two groups was assessed by non-parametric Spearman’s test. For multiple comparisons between three or more groups, one-way ANOVA with Bonferroni correction was conducted. In all statistical comparisons, p-values<0.05 were accepted as significant.

Results

Adgrf1 mainly expresses in liver of mice, and its expression is downregulated after HFD treatment

Firstly, we used microarray analysis to examine the change in expression levels of hepatic GPCRs in mice after HFD treatment (Supplementary file 3). In the screening results, we found that Adgrf1 is mainly expressed in liver and its expression is dramatically decreased in the HFD-fed mice compared to their STC-fed littermates. Remarkably, in agreement with previous studies (Ma et al., 2017; Prömel et al., 2012), Adgrf1 is mainly expressed in the liver of adult mice (Figure 1A and B). The Adgrf1 protein expression in those tissues were checked by western blot analysis. GRP110 proteins were mainly detected in liver and kidney samples (Figure 1B). Next, we used cell fractionation to identify the Adgrf1-expressing cells in liver (Figure 1C). The Cd11b mRNAs were used as markers for non-parenchymal cells (NPCs), and albumin mRNA for hepatocytes. Our cell fractionation clearly demonstrated that Adgrf1 mRNA is mainly expressed in hepatocytes (Figure 1C). This finding was further supported by western blot analysis (Figure 1D). Remarkably, in agreement with the microarray data, during HFD treatment for 8 wk, the expression level of hepatic Adgrf1 gradually declined and to almost undetectable level at week 8 as examined by RT-qPCR analysis (Figure 1E). In contrast, the mRNA levels of the NAFLD-related marker Fgf21 were highly induced in the livers of HFD-fed mice at week 8 (Figure 1F; Rusli et al., 2016). Western blot analysis was performed to confirm the declined expression of Adgrf1 is also observed in protein level in the livers of HFD-fed mice (Figure 1G, upper panel). Interestingly, HFD treatment did not affect the renal GRP110 expression (Figure 1G, lower panel). Collectively, the hepatic, but not renal, Adgrf1 level is tightly regulated by nutritional status.

Adgrf1 is mainly expressed in the liver and its expression is downregulated after HFD treatment.

Eight-week-old male C57BL/6J mice were fed with either STC or HFD for 8 wk. (A) mRNA expression levels of Adgrf1 in different organs as determined by RT-qPCR analysis (n = 5). (B) Representative immunoblotting analyses of Adgrf1 expression in different tissues of C57BL/J mice after STC for 8 wk (n = 3). (C) mRNA expression levels of Adgrf1, Cd11b, and albumin in factions of hepatocyte or NPCs isolated from STC-fed mice livers as determined by RT-qPCR. (D) Left panel: representative immunoblotting analyses of Adgrf1, Cd11b, and albumin in fractions of hepatocytes or NPC isolated from mice livers fed with STC, each lane is a sample from different individual; right panel: quantification of protein expression levels of Adgrf1, Cd11b, and albumin. Protein expression levels were normalized to the expression of β-actin. The fraction of hepatocytes was set as 1 for fold-change calculation. (E) mRNA expression levels of FGF21 in mice liver fed with 0, 2, 4, 6, and 8 wk of HFD as determined by RT-qPCR. (F) mRNA expression levels of Adgrf1 in mice liver fed with 0, 2, 4, 6, and 8 wk of HFD as determined by RT-qPCR. (G) Left panel: representative immunoblotting analyses of Adgrf1 in mice fed with either STC or HFD for 8 wk; right panel: quantification of protein expression levels of Adgrf1. Protein expression levels were normalized to the expression of β-tubulin. The sample from STC mice was set as 1 for fold-change calculation. Each lane is a sample from different individual. Adgrf1, G-protein-coupled receptor 110; STC, standard chow diet; HFD, high-fat diet; NPC, non-parenchymal cell. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 1—source data 1

Adgrf1 is mainly expressed in the liver and its expression is downregulated after HFD treatment.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig1-data1-v2.zip

Overexpression of Adgrf11 in hepatocytes accelerates metabolic dysregulation caused by HFD

Based on the dramatic difference in expression levels of hepatic ADGRF1 before and after HFD treatment, we hypothesized that downregulation of Adgrf1 in HFD-fed mice may be involved in the pathogenesis of fatty liver. To evaluate the impacts of high hepatic Adgrf1 level on liver metabolism, Adgrf1 was overexpressed in the hepatocytes of HFD-fed mice by liver-directed rAAV/thyroxine-binding globulin (TBG)-mediated gene expression system (Figure 2A and Figure 2—figure supplement 1A). The overexpression of Adgrf1 in the livers of the mice was validated by RT-qPCR (Figure 2B and Figure 2—figure supplement 1B) and western blot analysis (Figure 2—figure supplement 1C). We also confirmed that rAAV-mediated Adgrf1 overexpression was solely in hepatocytes, but not in NPC, by western blot analysis after cell fractionation (Figure 2C). Renal and adipose Adgrf1 expression level was not affected by liver-directed rAAV/TBG-mediated gene expression (Figure 2—figure supplements 1C and 2A).

Figure 2 with 2 supplements see all
Overexpression of Adgrf1 in hepatocytes exaggerates metabolic dysregulation by HFD treatment.

Eight-week-old male C57BL/6J mice were infected with 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-GFP, i.v.) and received HFD feeding, respectively. (A) Schematic illustration of viral treatments. (B) Hepatic mRNA expression levels of Adgrf1 from rAAV-Adgrf1 mice liver in fractions of hepatocyte or NPCs isolated from HFD-fed mice livers as determined by RT-qPCR. (C) Immunoblotting analyses of Adgrf1, Cd11b, and albumin from rAAV-Adgrf1 mice liver in factions of hepatocyte or NPC isolated from HFD-fed mice livers. Each lane is a sample from a different individual. (D) Body weight, (E) the percentage of fat mass, and (F) lean mass were assessed in different groups. (G) Fasting blood glucose levels were measured biweekly upon rAAV injection. (H) The fasting serum insulin level and (I) HOMA-IR index were measured and calculated according to the formula [Fasting blood glucose (mmol/l) × Fasting blood insulin (mIU/l)]/22.5 for the HFD-fed rAAV-Adgrf1 or rAAV-GFP mice at the end of the experiment. (J) GTT (1 g/kg BW, left) and area under curve (AUC, right) of serum glucose at week 10. (K) PTT (1 g/kg BW, left) and AUC (right) of serum glucose at week 11. (L) ITT (0.5 U/kg BW, left) and AUC (right) of serum glucose at week 12. mRNA expression levels of the target genes were normalized to the expression of mouse Gapdh. rAAV-NC group was set as 1 for fold-change calculation. n = 8 per group. Adgrf1, G-protein-coupled receptor 110; STC, standard chow diet; HFD, high-fat diet; NPC, non-parenchymal cell; BW, body weight; GTT, glucose tolerance test; PTT, pyruvate tolerance test; ITT, insulin tolerance test; AUC, area under curve; NC, negative control; HOMA-IR, homeostasis model assessment-estimated insulin resistance. Data represents as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 2—source data 1

Overexpression of Adgrf1 in hepatocytes exaggerates metabolic dysregulation by HFD treatment.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig2-data1-v2.zip

Overexpressing Adgrf1 in the liver of STC-fed mice did not affect body weight (Figure 2—figure supplement 1D), fasting glucose level (Figure 2—figure supplement 1E), fasting insulin level (Figure 2—figure supplement 1F), and homeostatic model assessment for insulin resistance (HOMA-IR; Figure 2—figure supplement 1G). There was only a slight increase at several time points in the glucose excursion curve in response to the GTT (Figure 2—figure supplement 1H) and hepatic glucose production induced by sodium pyruvate in PTT (Figure 2—figure supplement 1I). No change in insulin sensitivity was observed by insulin tolerance test between STC-fed rAAV-GFP and rAAV-Adgrf1 mice (Figure 2—figure supplement 1J).

However, under HFD treatment, rAAV-Adgrf1 mice gained more body weight (Figure 2D) and body fat mass (Figure 2E–F) than their rAAV-GFP controls. The HFD-fed rAAV-Adgrf1 mice also had higher fasting glucose level (Figure 2G), fasting insulin level (Figure 2H), and HOMA-IR (Figure 2I). Worsened glucose tolerance was observed in HFD-fed rAAV-Adgrf1 mice (Figure 2J). Overexpression of Adgrf1 in livers significantly increased hepatic glucose production induced in PTT (Figure 2K). ITT showed that the glucose levels in HFD-fed rAAV-Adgrf1 mice remained insensitive at 30–60 min after injection of insulin compared to their control HFD-fed rAAV-GFP littermates (Figure 2L). In addition, we placed the rAAV-Adgrf1 mice into metabolic cages to explore their locomotor activities (Figure 2—figure supplement 2B and C), energy expenditure (Figure 2—figure supplement 2D), food intake (Figure 2—figure supplement 2E), water intake (Figure 2—figure supplement 2F), and respiratory exchange ratio (Figure 2—figure supplement 2G). In brief, there were no difference in these metabolic parameters between these HFD-fed rAAV-Adgrf1 and rAAV-GFP littermates (Figure 2—figure supplement 2B–G).

In summary, we observed a mild impairment in glucose homeostasis associated with overexpressing Adgrf1 in the livers of STC-fed mice and more dramatic impairment was observed when the rAAV-Adgrf1 mice was challenged with HFD compared to their rAAV-GFP controls.

Suppressing Adgrf1 improves glucose homeostasis in HFD-fed rAAV-Adgrf1 mice

To confirm that the observations above were due to the rAAV-mediated overexpression of hepatic Adgrf1 in HFD-fed mice, we used two N-acetylgalactaosamine (GalNAc) conjugated antisense oligonucleotides (ASO-Adgrf1s) that bind to different regions of Adgrf1 mRNAs were used to knockdown the hepatic Adgrf1 expression in mice (Figure 3A and Figure 3—figure supplement 1A). To avoid the observation is due to off-target effects, two different sequences of ASO were used. Chronic treatment of either ASO-Adgrf1s only lowered the hepatic, but not renal, Adgrf1 mRNA (Figure 3B and Figure 3—figure supplement 1B) and protein (Figure 3—figure supplement 1C) levels. It is due to the fact that liver hepatocytes abundantly and specifically express the asialoglycoprotein receptor that binds and uptakes circulating glycosylated oligonucleotides via receptor-mediated endocytosis (Cui et al., 2021). Knockdown hepatic Adgrf1 by ASO-Adgrf1s in STC-fed mice did not affect body weight (Figure 3—figure supplement 1D) and fasting glucose (Figure 3—figure supplement 1E), but slightly lowered insulin level (Figure 3—figure supplement 1F) and HOMR-IR (Figure 3—figure supplement 1G) compared to their littermates injected with the negative control – scrambled antisense oligonucleotides (ASO-NC). No difference in the changes of glucose levels in GTT (Figure 3—figure supplement 1H), PTT (Figure 3—figure supplement 1I), and ITT (Figure 3—figure supplement 1J) for both ASO-Adgrf1s and ASO-NC groups under STC feeding conditions.

Figure 3 with 1 supplement see all
Deletion of hepatic Adgrf1 protects against diet-induced glucose intolerance in Adgrf1 overexpress mice.

Eight-week-old male C57BL/6J mice were infected with either 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-GFP, i.v.) and two different sequences of Adgrf1 ASO (ASO1-Adgrf1, ASO2-Adgrf1, 5 mg/kg, one dose per week, s.c.) or scrambled control (ASO-NC, s.c.) received HFD feeding, respectively. (A) Schematic illustration of viral treatments. (B) Hepatic mRNA expression levels of Adgrf1 from different groups of mice received either GFP-NC, Adgrf1-NC, Adgrf1-ASO1, or Adgrf1-ASO2 fed with HFD, respectively, as determined by RT-qPCR analysis. (C) Left panel: immunoblotting analyses of Adgrf1 and β-tubulin from livers of HFD-fed rAAV-GFP or rAAV-Adgrf1 mice treated with either ASO-NC or ASO-Adgrf1. Each lane is a sample from a different individual. Right panel: quantification of protein expression levels of Adgrf1 and β-tubulin. Protein expression levels were normalized to the expression of β-tubulin. (D) BW was measured biweekly upon rAAV and ASO injection. (E) The percentage of fat mass and (F) the percentage of lean mass were measured at the end of the experiment. (G) The fasting blood glucose level of different groups was measured upon rAAV and ASO injection. (H) Fasting serum insulin level and (I) HOMA-IR index were measured and calculated according to the formula [Fasting blood glucose (mmol/l)×Fasting blood insulin (mIU/l)]/22.5 for the HFD-fed rAAV-Adgrf1 or rAAV-GFP mice at the end of the experiment. (J) GTT (1 g/kg BW, left) and AUC (right) of serum glucose at week 10. (K) PTT (1 g/kg BW, left) and AUC (right) of serum glucose at week 11. (L) ITT (0.5 U/kg BW, left) and AUC (right) of serum glucose at week 12. mRNA expression levels of the target genes were normalized to the expression of mouse Gapdh. rAAV-NC group was set as 1 for fold-change calculation. n = 8 per group. STC, standard chow diet; HFD, high-fat diet; ASO, antisense oligonucleotides; BW, body weight; GTT, glucose tolerance test; PTT, pyruvate tolerance test; ITT, insulin tolerance test; AUC, area under curve; NC, negative control; HOMA-IR, homeostasis model assessment-estimated insulin resistance. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 3—source data 1

Deletion of hepatic Adgrf1 protects against diet-induced glucose intolerance in Adgrf1 overexpress mice.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig3-data1-v2.zip

In contrast, chronic ASO-Adgrf1 treatment for 4 wk significantly decreased their body weight (Figure 3D), fat mass ratio (Figure 3E and F), fasting glucose level (Figure 3G), fasting insulin level (Figure 3H), and HOMA-IR (Figure 3F) in HFD-fed rAAV-Adgrf1 mice. In addition, treatment of ASO-Adgrf1s improved glucose tolerance, pyruvate tolerance, and insulin sensitivity in HFD-fed rAAV-Adgrf1 mice as demonstrated by GTT (Figure 3J), PTT (Figure 3K), and ITT (Figure 3L) compared to ASO-NC controls. In consistent to overexpressing Adgrf1 in livers, the depletion of hepatic Adgrf1 by ASOs improves glucose homeostasis in HFD-fed mice.

Treatment of ASO-Adgrf1s alleviates lipid abundance and liver damage in HFD-fed rAAV-Adgrf1 mice

The circulating lipid profiles of the mice were also checked. HFD-fed rAAV-Adgrf1 mice had higher circulating cholesterol (CHO; Figure 4A) and triglyceride (TG; Figure 4B) levels than HFD-fed rAAV-GFP littermates, but their circulating free fatty acid (FFA) levels were similar (Figure 4C). High-density lipoprotein (HDL) cholesterol level was decreased, and low-density lipoprotein (LDL) cholesterol level was increased in HFD-fed rAAV-Adgrf1-NC mice compared to chronic ASO-Adgrf1 treatment group (Figure 4D).

Upregulation of hepatic Adgrf1 exaggerates liver steatosis in HFD-fed mice while downregulation of hepatic Adgrf1 protects mice from diet-induced liver lipid accumulation.

Eight-week-old male C57BL/6J mice were infected with either 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-NC, i.v.) and two different sequences of Adgrf1 antisense oligonucleotides (ASO1-Adgrf1, ASO2-Adgrf1, 5 mg/kg, one dose per week, s.c.) or scrambled control (ASO-NC, s.c.) received HFD feeding, respectively. (A) Serum CHO, (B) serum TG, and (C) serum FFA levels were measured at week 13. (D) Serum HDL and LDL. (E) The levels of serum AST ALT. (F) The ratio of the liver weight against body weight was calculated after sacrificing the mice from four different groups. (G) Representative gross pictures of liver tissues (upper panels), representative images of H&E (middle panels) and Oil Red O (lower panels) staining of liver sections (200 µm). The percentage of lipid area according to H&E staining (right panel). (H) Hepatic CHO, (I) hepatic TG, and (J) hepatic FFA were normalized by the weight of liver samples used for lipid extraction. n = 8 per group. i.v., intravenous injection; s.c., subcutaneous injection; STC, standard chow diet; HFD, high-fat diet; ASO, antisense oligonucleotides; BW, body weight; CHO, cholesterol; TG, triglyceride; FFA, free fatty acid; HDL, high-density lipoprotein; LDL, low-density lipoprotein; AST, aspartate transaminase; ALT, alanine transaminase; H&E, hematoxylin-eosin. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 4—source data 1

Upregulation of hepatic Adgrf1 exaggerates liver steatosis in HFD-fed mice while downregulation of hepatic Adgrf1 protects mice from diet-induced liver lipid accumulation.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig4-data1-v2.zip

Remarkably, chronic ASO-Adgrf1 treatment could lower circulating levels of the liver enzymes aspartate transaminase (AST) and alanine aminotransaminase (ALT), as markers of liver damage and hepatoxicity, in HFD-fed rAAV-Adgrf1-NC mice (Figure 4E). After sacrificing the mice, the hepatic lipid profiles were examined. We found that the livers of HFD-fed rAAV-Adgrf1 mice were significantly heavier (Figure 4F) and paler (Figure 4G, upper panels) than the livers of their rAAV-GFP littermates and ASO-Adgrf1-treated rAAV-GRP110 mice. Consistent with these observations, HFD-induced lipid accumulation within hepatocytes was substantially more abundant in the livers of HFD-fed rAAV-Adgrf1 mice than the rAAV-GFP littermates as determined by hematoxylin and eosin (H&E) staining and Oil Red O staining (Figure 4G, upper and middle rows). Moreover, based on the Masson trichrome staining, more fiber extension and larger fibrous septa formation were observed for the liver samples of rAAV-Adgrf1 mice compared to the livers from rAAV-GFP littermates (Figure 4G, lower row). These alterations were remarkably reduced after ASO-Adgrf1 treatments (Figure 4G). Like the circulating lipid profiles mentioned above, treatment of ASO-Adgrf1s for 8 wk could improve the hepatic lipid profiles of rAAV-Adgrf1 mice in terms of CHO (Figure 4H), TG (Figure 4I), and FFA (Figure 4J). Altogether, overexpression of hepatic Adgrf1 in mice is sufficient to perturb lipid metabolism and hence the progression of NAFLD, especially in obese subjects.

The metabolic dysregulation of rAAV-Adgrf1 mice is correlated to the upregulation of Scd1 expression

To reveal the molecular mechanism underlying the involvement of hepatic Adgrf1 in NAFLD development, RNA-sequencing analysis was performed on RNA samples extracted from the livers of HFD-fed ASO-NC-treated rAAV-GPF, ASO-NC-treated rAAV-Adgrf1, and ASO-Adgrf1-treated rAAV-Adgrf1 mice. In the search for the molecular processes for metabolisms, several lipid metabolism-related genes were altered (Figure 5A and B). We subsequently used RT-qPCR to confirm the RNA sequencing results (Figure 5C). Among them, we are particularly interested in stearoyl CoA desaturase 1 (Scd1), a key lipogenic enzyme responsible for the rate-limiting step in the synthesis of monounsaturated fatty acids (MUFAs), such as oleate and palmitoleate, by forming double bonds in saturated fatty acids (Paton and Ntambi, 2009). MUFAs serve as substrates for the synthesis of various kinds of lipids, and increases in Scd1 activity are involved in the development of NAFLD, hypertriglyceridemia, atherosclerosis, and diabetes (Kotronen et al., 2009; Mar-Heyming et al., 2008). To confirm the role of Adgrf1 in lipogenesis, the de novo lipogenesis assay was performed. Hepatocytes isolated from the rAAV-Adgrf1 group showed the highest lipogenesis activity, while those from the control rAAV-GFP group had lower activity (Figure 5D). Furthermore, the lipogenic activity decreased in the hepatocytes isolated from rAAV-Adgrf1 mice treated with Adgrf1-specific ASOs compared to the control group (Figure 5D). In agreement with the RT-qPCR data mentioned above, the results revealed a direct correlation between the level of Adgrf1 expression and lipogenic activity.

Adgrf1 is a major regulator of hepatic lipid metabolism.

Eight-week-old male C57BL/6J mice were infected with either 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-NC, i.v.) and two Adgrf1 antisense oligonucleotides (ASO1-Adgrf1, ASO2-Adgrf1, 5 mg/kg, one dose per week, s.c.) or scrambled control (ASO-NC, s.c.) and received HFD feeding, respectively. Mice were sacrificed and mRNA of liver from each group were extracted and RNA-seq analysis was conducted. (A) KEGG pathway assay of differential mRNA transcripts in rAAV and ASO groups identified by RNA-seq. (B) Heat map shows the log2 scale fold change in the expression levels of a set of genes involved in lipid metabolism from RNA seq data of livers in HFD-fed mice treated by rAAV-Adgrf1 or rAAV-Adgrf1 plus Adgrf1-ASO1. n = 3 per group. (C) mRNA expression levels of genes according to the heat map from different groups of mice received either GFP-NC, Adgrf1-NC, Adgrf1-ASO1, or Adgrf1-ASO2 fed with HFD, respectively, as determined by RT-qPCR analysis, n = 6 mice per group. (D) De novo lipogenic activity was measured the 3H labeling of lipogenic Acetyl-CoA from 0.5 μCi 3H-acetate. ASO, antisense oligonucleotides. STC, standard chow diet; HFD, high-fat diet; i.v., intravenous injection; s.c., subcutaneous injection; ASO, antisense oligonucleotides; KEGG, Kyoto Encyclopedia of Genes and Genomes; GEO, gene expression omnibus; NAFLD, non-alcoholic fatty liver disease. Data represented as mean ± SEM; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 5—source data 1

Adgrf1 is a major regulator of hepatic lipid metabolism.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig5-data1-v2.zip

The upregulation of Scd1 expression in liver is driven by the presence of Adgrf1

To confirm Scd1 expression is induced by Adgrf1, in vitro assays were performed by using adenovirus-mediated Adgrf1 expression system (ADV-Adgrf1) to overexpress Adgrf1 in primary hepatocytes isolated from STC-fed mice. After infection, the expressions of Scd1 mRNAs (Figure 6A) and protein (Figure 6B) were dramatically induced, but not in control group, which was treated with ADV-GFP. In addition, the Adgrf1 specific ASOs can not only knock down the Adgrf1 expression, but also induced the Scd1 expression by increasing Adgrf1 in the ADV-Adgrf1 primary hepatocytes (Figure 6A and B). In vitro luciferase reporter assay was performed to further validate the expression of Scd1 is transcriptional regulated by Adgrf1. We constructed plasmid harboring luciferase gene driven by the mouse Scd1 promoter (–2000 to +100) and transfected into HEK293T cells that were constructed. There was no change of luciferase activity of pGL3- Scd1 promoter-luciferase-transfected HEK293T cells under the treatment of Adgrf1 ligand DHEA, unless the HEK293T cells were pre-infected with adenovirus-overexpressing Adgrf1 (ADV-Adgrf1; Figure 6C). The overexpression of Adgrf1 in ADV-Adgrf1-infected cells and inductions of Scd1 mRNA expression by treatment of DHEA were also validated by RT-qPCR (Figure 6D). The changes in hepatocyte lipid profiles by the expression level of Adgrf1 and Scd1 were also checked. In agreement with the in vivo studies’ findings, the overexpression of Adgrf1 increased the intracellular CHO (Figure 6E), TG (Figure 6F), and FFA (Figure 6G). Their increases could be completely repressed by ASO against Adgrf1 (Figure 6E–G) and partially repressed by overexpressing Scd1-specific shRNAs (Figure 6F and G). In summary, the transcription level of Scd1 is regulated by Adgrf1. Adgrf1 enhances the lipid accumulation by inducing Scd1 expression.

Scd1 expression is regulated by Adgrf1 in primary hepatocytes.

Primary hepatocytes were isolated from 8-week-old male C57BL/6J mice with STC. (A) Primary hepatocytes were infected with either adenoviral vector expressing Adgrf1 (ADV-Adgrf1) or control adenovirus expressing GFP (ADV-GFP) 24 hr after plating, followed by transfection with ASO1-Adgrf1, ASO2-Adgrf1, or ASO-NC for another 6 hr (n = 6). mRNA expression levels of Adgrf1 and Scd1 from different groups were assessed, as determined by RT-qPCR analysis. (B) Left panel: immunoblotting analysis for the expression level of Adgrf1 and Scd1 from different groups of primary hepatocytes. Right panel: quantification of protein expression levels of Adgrf1 and Scd1. Protein expression levels were normalized to the expression of β-tubulin. Each lane is a sample from a different plate. Right panel: quantification of protein expression levels of Adgrf1, Scd1, and β-tubulin. n = 3 per group. Protein expression levels were normalized to the expression of β-tubulin. The samples for GFP were set as 1 for fold-change calculation. (C, D) HEK293T cells were infected with pGL3-Scd1 promoter-luciferase plasmid and adenoviral vector expressing Adgrf1 (ADV-Adgrf1) or GFP (ADV-GFP) for 48 hr and DHEA was added to the transfected cells at the concentration of 100 μM for 24 hr. Cell lysates were used for (C) luciferase assay or (D) RT-qPCR analysis (n = 3). Lysates from the cell co-transfection with pGL3-Scd1 promoter-luciferase plasmid and ADV-GFP without treatment of DHEA was set as 1 for fold-change calculation. (E–G) Primary hepatocytes were infected with either adenoviral vector expressing Adgrf1 (ADV-Adgrf1) or control ADV-GFP, followed by transfecting with scramble or shScd1-1 or shScd1-2 plasmids for another 72 hr. Intracellular lipids were extracted and (E) CHO, (F) TG, and (G) FFA were assessed (n = 3). STC, standard chow diet; i.v., intravenous injection; s.c., subcutaneous injection; ASO, antisense oligonucleotides. CHO, cholesterol; TG, triglyceride; FFA, free fatty acid. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 6—source data 1

Scd1 expression is regulated by Adgrf1 in primary hepatocytes.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig6-data1-v2.zip

Inhibition of Scd1 in rAAV-Adgrf1 mice partially attenuates most metabolic dysregulations, especially lipid profiles

To examine whether the upregulation of hepatic Scd1 was the cause of metabolic dysregulation in rAAV-Adgrf1 mice, a liver-specific Scd1 inhibitor MK8245 was used to alleviate the metabolic dysregulation by overexpressing Adgrf1 in HFD-fed rAAV-Adgrf1 mice (Figure 7A; Iida et al., 2018). Chronic treatment of MK8245 for 11 wk did not affect the expression of Adgrf1 mRNA (Figure 7B) and protein (Figure 7C) levels in rAAV-GRP110 mice. In agreement with previous studies showing that the chronic treatment of this Scd1 inhibitor improves various metabolic parameters including lipid and glucose profiles in various animal models (Oballa et al., 2011), treatment of MK8245 lowered the body weight (Figure 7D), improved glucose homeostasis in terms of fasting glucose level (Figure 7E) and HOMR-IR (Figure 7G), and performance in GTT (Figure 7H) and PTT (Figure 7I) of HFD-fed rAAV-Adgrf1 mice compared to untreated littermates. But there was no change in insulin sensitivity as demonstrated by ITT (Figure 7J).

Inhibition of Scd1 alleviates the glucose impairment in mice with hepatic Adgrf1 overexpression.

Eight-week-old male C57BL/6J mice were infected with either 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-GFP, i.v.) and Scd1 inhibitor (MK8245, 10 mg/kg/week, p.o.) or inhibitor vehicle (inhibitor-Veh., p.o.) received HFD feeding. (A) Schematic illustration of viral treatments. (B) Hepatic mRNA expression levels of Adgrf1 from different groups of mice received rAAV and inhibitor fed with HFD, respectively, as determined by RT-qPCR analysis. (C) Left panel: immunoblotting analysis for the hepatic protein expression level of Adgrf1 and Scd1 from different groups of mice fed with HFD. Right panel: quantification of protein expression levels of Adgrf1 and Scd1. Protein expression levels were normalized to the expression of β-tubulin. Each lane is a sample from a different individual. (D) BW and (E) fasting blood glucose level were measured at different weeks upon rAAV and inhibitor injection. (F) The fasting blood insulin level and (G) HOMA-IR index were measured and calculated according to the formula [Fasting blood glucose (mmol/l)×Fasting blood insulin (mIU/l)]/22.5 for the HFD-fed rAAV-Adgrf1 or rAAV-GFP mice at the end of the experiment. (H) GTT (1 g/kg BW, left) and AUC (right) of serum glucose at the week of 10. (I) PTT (1 g/kg BW, left) and AUC (right) of serum glucose at week 11. (J) ITT (0.5 U/kg BW, left) and AUC (right) of serum glucose at week of 12. mRNA expression levels of the target genes were normalized to the expression of mouse Gapdh. rAAV-NC group was set as 1 for fold-change calculation. n = 8 per group. HFD, high-fat diet; i.v., intravenous injection; p.o., oral administration; ASO, antisense oligonucleotides; BW, body weight; GTT, glucose tolerance test; PTT, pyruvate tolerance test; ITT, insulin tolerance test; AUC, area under curve; NC, negative control; HOMA-IR, homeostasis model assessment-estimated insulin resistance. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 7—source data 1

Inhibition of Scd1 alleviates the glucose impairment in mice with hepatic Adgrf1 overexpression.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig7-data1-v2.zip

MK8245 treatment also lowered the circulating CHO (Figure 8A) and TG (Figure 8B) levels almost to the levels of HFD-fed rAAV-GFP mice, but there was no change in circulating FFA level (Figure 8C). A relatively higher HDL can be found in the MK8245 group, but there were no differences detected regarding the LDL level (Figure 8D). The AST and ALT levels were also alleviated in the MK8245 group compared to the rAAV-Adgrf1 littermates (Figure 8E). MK8245 treatment partially reduced the liver weight (Figure 8F), degree of paleness, severity of fibrosis (Figure 8G), and lipid accumulations (Figure 8H–J). To conclude, treatment of MK8245 could improve the lipid profiles and alleviate metabolic dysregulation caused by overexpression of hepatic Adgrf1 in mice.

Inhibition of hepatic Scd1 partially alleviates the severity of hepatic steatosis in Adgrf1 overexpression mice.

Eight-week-old male C57BL/6N mice were infected with either 3 × 1011 copies of rAAV encoding Adgrf1 (rAAV-Adgrf1, i.v.) or control (rAAV-GFP, i.v.) and administered with Scd1 inhibitor (MK8245, 10 mg/kg, p.o.) or inhibitor vehicle (inhibitor-Veh., p.o.) received HFD feeding. (A) Serum CHO, (B) serum TG, and (C) serum FFA levels were measured at the end of experiment. (D) Serum HDL and LDL, (E) AST and ALT level of each group of mice were measured at the end of the experiment. (F) The ratio of the liver weight against body weight was calculated after sacrificing the mice from four different groups. (G) Representative gross pictures of liver tissues (upper panels), representative images of H&E (middle panels) and Oil Red O (lower panels) staining of liver sections (200 µm). The percentage of lipid area according to H&E staining (right panel). (H) Hepatic CHO, (I) hepatic TG, and (J) hepatic FFA were normalized by the weight of liver samples used for lipid extraction. n = 8 per group. STC, standard chow diet; HFD, high-fat diet; i.v., intravenous injection; p.o., oral administration; CHO, cholesterol; TG, triglyceride; FFA, free fatty acid; HDL, high-density lipoprotein; LDL, low-density lipoprotein; AST, aspartate transaminase; ALT, alanine transaminase; H&E, hematoxylin-eosin. Data represented as mean ± SEM; repeated with three independent experiments; p-value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 8—source data 1

Inhibition of hepatic Scd1 partially alleviates the severity of hepatic steatosis in Adgrf1 overexpression mice.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig8-data1-v2.zip

Expression of Adgrf1 in liver is closely associated with hepatic steatosis in NAFLD patients

To evaluate the clinical relevance of the findings in mice, we first checked the expression level of Adgrf1 in human liver from a publicized transcriptome dataset Gene Expression Omnibus (GEO; Profile # GDS4881) with human liver biopsy of different phases from control to NAFLD was checked (Ahrens et al., 2013). Healthy obese subjects without NAFLD had lower Adgrf1 mRNA expression than healthy lean subjects, but obese NAFLD subjects had similar Adgrf1 mRNA expression level as healthy lean subjects (Figure 9A). Subsequently, by using the same transcriptome dataset, the correlation in the expression level of Adgrf1 and Scd1 was investigated. The expression level of Adgrf1 was positively correlated with Scd1 in the liver (r = 0.4635, p<0.05; Figure 9B).

Hepatic expression of ADGRF1 is upregulated in obese patients with hepatic steatosis when compared to those with normal liver morphology, which is positively associated with hepatic SCD1 expression level.

NAFLD patients have higher hepatic expression of ADGRF1 accompanied with increased mRNA Scd1 expression. (A) Normalized Log2 mRNA expression of ADGRF1 in lean people without NAFLD (n = 12), obese people without NAFLD (n = 17), or obese patients with NAFLD (n = 8) according to the GEO database (GEO; Profile # GDS4881/8126820). (B) Correlation between ADGRF1 and SCD1 in liver of human subjects based on the GEO database. (C) Representative images of liver tissues with H&E staining (upper panels) and immunohistochemical staining (IHC) of ADGRF1 (lower panels) from patients with different degree of NAFLD (200 µm). The percentage of ADGRF1 positive area according to H&E staining (right panel). The percentage of ADGRF1-positive areas according to IHC staining (right panel); n = 3 per group. (D) Normalized Log2 mRNA expression of IL-1β in lean people without NAFLD (n = 12), obese people without NAFLD (n = 17), or obese patients with NAFLD (n = 8) according to the GEO database (GEO; Profile # GDS4881/8126820). (E) Hepatic mRNA expression levels of lL-1β, (F) Adgrf1, and (G) Scd1 in either STC-fed mice or HFD-fed mice treated with CCl4 or STZ as determined by RT-qPCR. Data represented as mean ± SEM. p-Value analyzed by two-tailed Student’s t-test. *p<0.05, **p<0.01, ***p<0.001.

Figure 9—source data 1

Hepatic expression of ADGRF1 is upregulated in obese patients with hepatic steatosis when compared to those with normal liver morphology, which is positively associated with hepatic SCD1 expression level.

https://cdn.elifesciences.org/articles/85131/elife-85131-fig9-data1-v2.zip

To verify the observation, we performed immunohistochemistry staining with liver sections from biopsy-proven patients with mild, moderate, and severe NAFLD, respectively (Supplementary file 4). The degree of steatosis was determined by non-alcoholic steatohepatitis clinical research network (NASH CRN) scoring system (Brunt et al., 1999). Immunostaining analysis demonstrated that hepatic expression of Adgrf1 protein was higher in the ones with severe steatosis than those with lower degree of NAFLD (Figure 9C). These data collectively suggest that Adgrf1 expression level correlates to hepatic steatosis in humans as well.

To investigate the potential reason for higher hepatic Adgrf1 expression levels in NAFLD patients than in healthy obese individuals, we formulated the multiple-hit hypothesis, which suggests that liver inflammation may alter gene expression during NAFLD pathogenesis (Buzzetti et al., 2016). Supporting the hypothesis, it is found that the mRNA level of IL-1β, a key mediator of low-grade inflammation during NAFLD (Mirea et al., 2018), was significantly higher in NAFLD patients than in healthy obese individuals in the GEO (Profile # GDS4881) (Figure 9D). To validate this hypothesis, HFD-fed mice with either CCl4 or STZ to accelerate and exacerbate their NAFLD pathogenesis (Zhang et al., 2020; Zhong et al., 2020; Hansen et al., 2017) and measured the mRNA level of the hepatic inflammation marker, IL-1β. Remarkably, after treatment with either CCl4 or STZ, the expression of IL-1β mRNA in their livers increased four- to fivefold compared to the respective value of untreated HFD-fed mice (Figure 9E). Notably, the expression of hepatic Adgrf1 mRNA was also significantly increased after CCl4 or STZ treatment compared to the untreated HFD-fed mice (Figure 9F). Additionally, the Scd1 mRNA expression level in the CCl4 or STZ-treated HFD-fed mice was significantly higher than the respective value of untreated HFD-fed mice (Figure 9G). These results suggest that inflammation induced by either CCl4 or STZ treatment can increase the expression of hepatic Adgrf1, in addition to Scd1, which is known to be involved in hepatic lipid metabolism.

Discussion

The present study has uncovered a previously unrecognized role of Adgrf1 in regulating hepatic lipid metabolism. Firstly, we demonstrated that Adgrf1 is highly expressed in liver of healthy subjects, and hepatic Adgrf1 is required for regulating lipid content in liver of diet-induced obese mice by both gain-of-function and loss-of-function approaches. Secondly, we found that the hepatic Adgrf1 expression level of healthy obese human and mouse are downregulated. The downregulation of hepatic Adgrf1 expression level in obese subjects is a protective mechanism to prevent over-accumulation of lipid in liver. The argument mainly based on the findings that HFD-induced steatosis and liver injury were exacerbated in obese mice with high Adgrf1 overexpression level, and knockdown hepatic Adgrf1 alleviated the severity of obesity-induced NAFLD.

The pathophysiology of NAFLD is not well understood, but it is widely accepted that multiple factors, including inflammation, contribute to its acceleration and aggravation (Buzzetti et al., 2016). To explain the observation that hepatic Adgrf1 expression levels in NAFLD patients were higher than in healthy obese individuals, the expression levels of key inflammation markers in different mouse models were measured and it is found that IL-1β and Adgrf1 expression levels dramatically increased in subjects with more severe NAFLD conditions. It is interesting to note that the mechanism by which hepatic Adgrf1 transcription is repressed in healthy obese individuals and induced in NAFLD patients remains to be explored. In addition, although obesity is commonly associated with NAFLD, up to 19% of lean Asians can also develop NAFLD (VanWagner and Armstrong, 2018). It would be interesting to investigate whether the expression levels of hepatic Adgrf1 mRNA in these ‘lean NAFLD’ patients are higher than in lean healthy controls. This could provide further insights into the role of hepatic Adgrf1 in NAFLD pathogenesis and help identify potential therapeutic targets for the treatment of NAFLD in lean individuals.

Subsequently, we performed RNA-sequencing analysis to investigate the mechanism of Adgrf1’s role in regulating lipogenesis and observed that the expression levels of Scd1 mRNAs and protein were dramatically upregulated in the livers of rAAV-Adgrf1 mice and repressed in Adgrf1-ASOs-treated rAAV-Adgrf1 mice. Scd1 is the rate-limiting enzyme that catalyzes the conversion of saturated long-chain fatty acids into monounsaturated fatty acids, and its expression is tightly regulated by various parameters, including hormonal and nutrient factors (Mauvoisin and Mounier, 2011). A recent study demonstrated that Adgrf1 mediates palmitic acids to activate the mTor and Srebp1 pathways to promote fat synthesis in mammary gland tissues (Zhang et al., 2023). Here, Srebp1 is the key transcription factor for regulating Scd1 gene expression (Zhu et al., 2019a). Our RNA sequencing analysis also revealed that the expression of Srebp1 mRNA was dramatically upregulated in the livers of rAAV-Adgrf1 mice and repressed in Adgrf1-ASOs-treated rAAV-Adgrf1 mice, indicating that Adgrf1 might regulate Scd1 expression via Srebp1 in the liver. Importantly, the expression of hepatic Adgrf1 and Scd1 mRNAs can be further increased in the livers of subjects with more severe NAFLD, contributing to its acceleration and aggravation.

To confirm that the upregulation of hepatic Scd1 expression levels was responsible for the changes in metabolic phenotype in the rAAV-Adgrf1 mice, both in vivo and in vitro experiments were carried out using Scd1 shRNAs and inhibitors. We found that pharmacologically inhibiting Scd1 by MK8245 was sufficient to rescue the key metabolic dysregulations caused by Adgrf1 overexpression in the liver. These results strongly support the conclusion that Adgrf1 induces Scd1 expression, leading to an increase in de novo lipogenesis in the liver and exacerbating obese-induced NAFLD.

Previous studies reported that Scd1 global knockout (KO) mice showed improved insulin sensitivity, higher-energy metabolism, and more resistant to diet-induced obesity by the activation of lipid oxidation in addition to the reduction of triglyceride synthesis and storage (Ntambi et al., 2002; Miyazaki et al., 2007; Miyazaki et al., 2009). In addition, the ob/ob mice with Scd1 mutations had significantly reduced storage of triglyceride and lower level of very low-density lipoprotein (VLDL) production (Cohen et al., 2002). Remarkably, liver-specific KO of Scd1 was sufficient to reduce high-carbohydrate diet-induced adiposity with a significant reduction in hepatic lipogenesis and improved glucose tolerance (Miyazaki et al., 2007). Indeed, Scd1 inhibition was proposed to be a therapeutic strategy for the treatment of metabolic syndrome (Jiang et al., 2005).

What are the potential advantages of targeting GRP110 rather than Scd1 for the treatment of NAFLD? First of all, Scd1 is highly expressed in various tissues, especially adipose tissues (Ascenzi et al., 2021). In addition, expression level and activity of Scd1 are very tightly regulated (Mauvoisin and Mounier, 2011; ALJohani et al., 2017). Harmful consequences from inhibiting Scd1 have been reported, such as the inhibition of fat mobilization in adipose tissues, and the promotion of proinflammatory and endoplasmic reticulum stress by accumulation Scd1 substrates (Brown and Rudel, 2010; Leung and Kim, 2013; Liu et al., 2011; Zou et al., 2020). These findings clearly documented that optimal level of Scd1 is required to maintain health. Secondly, in contrast to Scd1, according to the phenotypes of Adgrf1 KO mice in previous studies (Ma et al., 2017; Lee et al., 2016a) and a dramatic reduction in Adgrf1 in the livers of HFD-fed mice and health obese subjects, the hepatic Adgrf1 may be dispensable in adults. Therefore, targeting hepatic Adgrf1 is a potential safe treatment of NAFLD. Thirdly, according to the RNA-sequencing analysis, repressing Adgrf1 can also regulate the expression of many other lipid metabolism genes. Unfortunately, Adgrf1 antagonist is not available at this moment. As demonstrated, the ASO-based strategy is an alternative approach to knockdown the expression of Adgrf1 in liver (Dhuri et al., 2020).

The current study focuses on Adgrf1 in hepatic lipid metabolism. As mentioned above, Adgrf1 is primarily understood to be an oncogene (Lum et al., 2010; Liu et al., 2018; Zhu et al., 2019b; Shi and Zhang, 2017; Bhat et al., 2018; Ma et al., 2017; Nam et al., 2022; Abdulkareem et al., 2021; Sadras et al., 2017; Espinal-Enríquez et al., 2015; Harvey et al., 2010). Notably, recent study reported that deficiency of Adgrf1 can decelerate carcinogen-induced hepatocarcinogenesis in adult mice (Ma et al., 2017). Coincidentally, high expression level of Scd1 is also genetically susceptible to hepatocarcinogenesis (Falvella et al., 2002). It is highly possible that Adgrf1 also accelerates carcinogenesis by inducing Scd1 expression level. Therefore, a further experiment to check the Scd1 expression level in the Adgrf1 induced cancers may be conducted.

In summary, we present evidence demonstrating a novel role of hepatic Adgrf1 in regulating lipid metabolism and explored the mechanism partially via regulation of Scd1 expression level. As the amino acid sequencing of Adgrf1 are highly conserved in humans and mice, targeting Adgrf1 may serve as a novel therapeutic approach for the treatment of NAFLD patients.

Data availability

All data generated or analysed during this study are included in the manuscript and supplementary data are either in the mansucript or source data files.

The following previously published data sets were used
    1. Ahrens M
    2. Ammerpohl O
    3. von Schönfels W
    4. Kolarova J
    (2013) NCBI Gene Expression Omnibus
    ID GDS4881. Postbariatric, morbidly obese patients with nonalcoholic fatty liver disease: liver biopsies.

References

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    10. Yang X
    11. Wang Z
    (2017)
    Gpr110 deficiency decelerates carcinogen-induced hepatocarcinogenesis via activation of the IL-6/STAT3 pathway
    American Journal of Cancer Research 7:433–447.

Decision letter

  1. Matthew A Quinn
    Reviewing Editor; Wake Forest School of Medicine, United States
  2. Mone Zaidi
    Senior Editor; Icahn School of Medicine at Mount Sinai, United States
  3. Weiping Han
    Reviewer; Institute of Molecular and Cellular Biology, Singapore

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Amelioration of non-alcoholic fatty liver disease by targeting G protein-coupled receptor 110: A preclinical study" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our board of Reviewing Editors and the evaluation has been overseen by Mone Zaidi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Weiping Han (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) Show the levels of hepatic lipids and lipogenic gene expression, including SCD-1, in liver tissues from NCD vs. HFD-fed mice.

2) Test whether GPR110 overexpression would affect adipose tissue. Along the same line, they have to carefully investigate the reason of increased body weight gain in GPR110 overexpressed mice (ex., food intake, and energy expenditure).

3) Measurement of de novo lipogenic activity using primary hepatocyte with GPR110 overexpression or knockdown would be valuable to affirm the authors' proposed model.

4) Discuss potential the molecular mechanisms how GPR110 signaling could enhance SCD-1 transcription.

Reviewer #1 (Recommendations for the authors):

This is a well written and rigorously conducted project. My only recommendation for the author is to expand on the disconnect between murine diet-induced obesity and human steatosis with regards to expression of GPR110. In the mouse model, obesity impairs the expression of GPR110, whereas human steatosis enhances GPR110 expression. The authors should elaborate more thoroughly on this disconnect. Specifically, is downregulation of GPR110 in mice compensatory? Is this mechanism lost in humans?

Reviewer #2 (Recommendations for the authors):

Although it is of interest that GPR110/SCD-1 axis could modulate hepatic lipid levels, the underlying mechanisms are not clear. To support the authors' claim, it is necessary to validate the direct role of GPR110 in hepatic lipid metabolism and the detailed mechanisms of which GPR110 signaling could modulate SCD-1 transcription.

Comments/typos

1. Please provide detailed information for GalNAc-siGPR110 design (siRNA sequence, location of GalNAc, and RNA modification).

2. In page 2, knockdown GPR110 can reduced the cell migration → knockdown of GPR110 can reduce the cell migration.

3. In page 2, Reveal a new mechanism regulation the progression of NAFLD → Reveal a new mechanism regulating the progression of NAFLD.

4. Figure 5C: Cy4a12b -> Cyp4a12b.

Reviewer #3 (Recommendations for the authors):

The authors may examine whether GPR110 plays a more critical role at the early stage of NAFLD development, while possibly a second factor is more important for the late stage of NAFLD.

https://doi.org/10.7554/eLife.85131.sa1

Author response

Essential revisions:

1) Show the levels of hepatic lipids and lipogenic gene expression, including SCD-1, in liver tissues from NCD vs. HFD-fed mice.

Thank you for your comment. The levels of key hepatic lipids and lipogenic gene expression in liver tissues from NCD and HFD-fed mice in the supplementary Table 4 on page 62 to show the impact on hepatic lipid metabolism by altering gene expression and promoting lipid accumulation in the liver.

2) Test whether GPR110 overexpression would affect adipose tissue. Along the same line, they have to carefully investigate the reason of increased body weight gain in GPR110 overexpressed mice (ex., food intake, and energy expenditure).

Thank you for your comment. To investigate the effect of our liver-specific GPR110 overexpression system on adipose GPR110 expression, RT-qPCRs were performed. The results showed that GPR110 was overexpressed in the hepatocytes of livers (Figure 2B-C and S1C), but not in adipose tissues (Supplementary Figure 3A on page 50 in the revised manuscript) in the rAAV-GPR110 mice compared to the control group. In addition, the Ct value of adipose GPR110 mRNAs were over 40. It shall be due to the liver-specific thyroxine binding globulin (TBG) promoter was used to drive the expression of GPR110 in the liver via our rAAV-mediated gene expression system.

Metabolic phenotyping using a metabolic cage system revealed no significant differences in daily pedestrian locomotion, distance in cage locomotion, energy expenditure, food intake, water intake, or the respiratory exchange ratio between the rAAV-GFP and rAAV-GPR110 groups (Figure S3C-H on page 50), indicating that these factors did not contribute to the changes in fat mass.

We believe that the increased body weight gain in HFD-fed rAAV-GPR110 mice is mainly due to dysregulation of hepatic lipid metabolism and hence subsequent accumulation of fat mass. Similar phenotyping has been observed in mice with dysregulation of key hepatic genes involved in lipid metabolism (e.g., AMPK, PGC1a, SREBP-1c, Acat2, CD36, PPARα … etc.) [1-9]. Please refer to the following papers for further information.

1. Sachithanandan, N., et al., Liver‐specific suppressor of cytokine signaling‐3 deletion in mice enhances hepatic insulin sensitivity and lipogenesis resulting in fatty liver and obesity 1. Hepatology, 2010. 52(5): p. 1632-1642.

2. Morris, E.M., et al., Reduced liver-specific PGC1a increases susceptibility for short-term diet-induced weight gain in male mice. Nutrients, 2021. 13(8): p. 2596.

3. Ma, Z., et al., Hepatic Acat2 overexpression promotes systemic cholesterol metabolism and adipose lipid metabolism in mice. Diabetologia, 2023. 66(2): p. 390-405.

4. Wilson, C.G., et al., Hepatocyte-specific disruption of CD36 attenuates fatty liver and improves insulin sensitivity in HFD-fed mice. Endocrinology, 2016. 157(2): p. 570-585.

5. Mao, J., et al., Liver-specific deletion of acetyl-CoA carboxylase 1 reduces hepatic

triglyceride accumulation without affecting glucose homeostasis. Proceedings of the National Academy of Sciences, 2006. 103(22): p. 8552-8557.

6. Chakravarthy, M.V., et al., “New” hepatic fat activates PPARα to maintain glucose, lipid, and cholesterol homeostasis. Cell metabolism, 2005. 1(5): p. 309-322.

7. Dirkx, R., et al., Absence of peroxisomes in mouse hepatocytes causes mitochondrial and ER abnormalities. Hepatology, 2005. 41(4): p. 868-878.

8. Knebel, B., et al., Liver-specific expression of transcriptionally active SREBP-1c is associated with fatty liver and increased visceral fat mass. PLoS One, 2012. 7(2): p. e31812.

9. Garcia, D., et al., Genetic Liver-Specific AMPK Activation Protects against Diet-Induced Obesity and NAFLD. Cell Rep, 2019. 26(1): p. 192-208 e6.

3) Measurement of de novo lipogenic activity using primary hepatocyte with GPR110 overexpression or knockdown would be valuable to affirm the authors' proposed model.

Thank you for your comment. To investigate the effect of GPR110 expression level on de novo lipogenic activity in primary hepatocytes, we used stable isotopes 3H-acetate to measure their de novo lipogenic activities. The data are presented in Figure 5D on page 36 of the revised manuscript. The results indicate a direct correlation between GPR110 expression level and de novo lipogenic activity. The highest 3H-total lipid activity was detected in hepatocytes isolated from the rAAV-GPR110 group compared to the control rAAV-GFP group, while the activity was decreased in hepatocytes isolated from rAAV-GPR110 mice treated with GPR110-specific ASOs compared to the control group. These findings suggest that the expression level of GPR110 plays a crucial role in de novo lipogenic activity.

4) Discuss potential the molecular mechanisms how GPR110 signaling could enhance SCD-1 transcription.

Thank you for your comment. A study published on March 22, 2022, has shown that GPR110 mediates palmitic acid to activate the mTOR and SREBP1 pathways, promoting milk protein and fat synthesis in mammary gland tissues [10]. Our RNA sequencing results revealed a correlation between the expression of hepatic SREBP1 and GPR110. Therefore, we added the mRNA levels of SREBP1 in our experiments, presented in Figure 5B-C on page 36 of the revised manuscript. The expression level of SREBP1 was found to be higher in the GPR110 overexpression group and decreased after using ASOs to knockdown hepatic GPR110 levels. Additionally, we discussed this potential the molecular mechanism of GPR110 in regulating hepatic lipid metabolism through the SREBP1-SCD1 pathway in the revised version of the manuscript on page 21 line 455-464.

Reviewer #1 (Recommendations for the authors):

This is a well written and rigorously conducted project. My only recommendation for the author is to expand on the disconnect between murine diet-induced obesity and human steatosis with regards to expression of GPR110. In the mouse model, obesity impairs the expression of GPR110, whereas human steatosis enhances GPR110 expression. The authors should elaborate more thoroughly on this disconnect. Specifically, is downregulation of GPR110 in mice compensatory? Is this mechanism lost in humans?

Thank you for your positive feedback and for highlighting areas where we can improve. Our study hypothesized that downregulating GPR110 is a protective mechanism against fatty liver development in both mouse and human. Similar to our findings in mice, we observed downregulation of hepatic GPR110 in healthy obese humans compared to lean humans, and a significant increase or restoration of hepatic GPR110 expression levels in NAFLD patients compared to both healthy obese humans and lean humans (see Figure 9A). However, the degree of change in GPR110 expression levels in human livers was not as pronounced as in mice (see Figure 1E-F). This could be due to several potential reasons, such as: (1) it is difficult to find humans with a BMI equivalent to mice treated with more than 12 weeks of HFD [11-15]; (2) we used RT-qPCR to determine hepatic GPR110 expression in mice, while microarrays were used to determine hepatic GPR110 expression in humans in previous study; and (3) furthermore, it's worth noting that the y-axis scales for these methods are different, and the human data from the microarray analysis is presented on a log2 scale, which may affect the impression of the changes of GPR110 mRNA expression in human appear to be less obvious.

Furthermore, inspired by the comments from reviewers, we hypothesized that pathological factors such as liver damage and inflammation in the livers of NAFLD patients may induce hepatic GPR110 expression. We also observed that the key inflammation marker, IL-1β, which mediates low-grade inflammation during NAFLD, was increased in our human study [5]. To mimic these pathological conditions, we induced liver damage and inflammation in the livers of HFD-fed mice using either CCl4 or streptozotocin (STZ) [16-20]. As shown in Figure 9 on page 44 of the revised manuscript, treatment with either CCl4 or STZ significantly increased the expression levels of the key hepatic inflammation marker IL-1β, GPR110, and SCD1 in the livers of the CCl4- or STZ-treated HFD-fed mice compared to their controls without any CCl4 or STZ treatment (Figure 9D-G). In summary, we believe that the mechanism is conserved between humans and mice, whereby the expression of hepatic GPR110 should be repressed in healthy obese individuals to prevent or delay the development of fatty liver. Pathological factors such as inflammation and liver damage may enhance GPR110 expression in NAFLD patients, thereby accelerating lipid accumulation in their livers through the SREBP1/SCD1 pathway.

Reviewer #2 (Recommendations for the authors):

Although it is of interest that GPR110/SCD-1 axis could modulate hepatic lipid levels, the underlying mechanisms are not clear. To support the authors' claim, it is necessary to validate the direct role of GPR110 in hepatic lipid metabolism and the detailed mechanisms of which GPR110 signaling could modulate SCD-1 transcription.

Thank you for the comment. As mentioned in the response to your major comment #4, in line with the recent publication demonstrated that GPR110 mediates palmitic acids to activate the mTOR and SREBP1 pathways to promote milk protein and fat synthesis in mammary gland tissues, we did observe that the expression of key SCD1 transcription factor SREBP1 were correlated to the expression of GPR110. In brief, the expression level of SREBP1 level was found in the GPR110 overexpression group, and the level decreased after using ASOs to knockdown hepatic GPR110 levels. These findings suggest that GPR110 shall regulate hepatic lipid metabolism through the SREBP1-SCD1 pathway, and we added the mRNA levels of SREBP1 in my experiments in Figure 5B-C on page 36 of the revised manuscript.

Comments/typos

1. Please provide detailed information for GalNAc-siGPR110 design (siRNA sequence, location of GalNAc, and RNA modification).

Please find the sequences and modification information of the ASOs in Author response table 1.

Author response table 1
SequenceGalNac positionPosition of 2’ sugar modification
ASO1AGGAAAATTTCGCTGA5’-end3*-10-3*
ASO2GAATTTTAGGACTTGC5’-end3*-10-3*

2. In page 2, knockdown GPR110 can reduced the cell migration → knockdown of GPR110 can reduce the cell migration.

Thank you for pointing out the mistake. The letter 'd' was missing in the word 'reduced'. The correct sentence should be 'knockdown of GPR110 can reduce the cell migration'. Please refer to page 3, lines 31-32 for further clarification.

3. In page 2, Reveal a new mechanism regulation the progression of NAFLD → Reveal a new mechanism regulating the progression of NAFLD.

Thank you for pointing out the mistake. The word “regulation” was replaced by “regulating”. Please refer to page 3 line 50 for further clarification.

4. Figure 5C: Cy4a12b -> Cyp4a12b.

Thank you for pointing out the mistake. The letter “p” was added. Please refer to Figure 5B on page 36.

Reviewer #3 (Recommendations for the authors):

The authors may examine whether GPR110 plays a more critical role at the early stage of NAFLD development, while possibly a second factor is more important for the late stage of NAFLD.

Thank you for the comment. We believe GPR110 plays a more critical role in the early stage of NAFLD, especially for the NAFLD patients beginning with inflammation or other insults that induce the NAFLD pathogenesis. Our argument mainly based on GPR110 is relative are relatively lower in the health obese subject than NAFLD patients, and one of the key differences these two groups is key inflammation marker Il-1β was higher detected in NAFLD patients as compared to health obese subjects. In addition, overexpression of GPR110 induced the expression of hepatic lipids and lipogenic genes and knockdown GPR110 in the rAAV-GPR110 mice can ameliorate of the progression of their NAFLD. The discussion of the important of GPR110 in NAFLD was presented on 20, lines 434-446.

References

1. Sachithanandan, N., et al., Liver‐specific suppressor of cytokine signaling‐3 deletion in mice enhances hepatic insulin sensitivity and lipogenesis resulting in fatty liver and obesity 1. Hepatology, 2010. 52(5): p. 1632-1642.

2. Morris, E.M., et al., Reduced liver-specific PGC1a increases susceptibility for short-term diet-induced weight gain in male mice. Nutrients, 2021. 13(8): p. 2596.

3. Ma, Z., et al., Hepatic Acat2 overexpression promotes systemic cholesterol metabolism and adipose lipid metabolism in mice. Diabetologia, 2023. 66(2): p. 390-405.

4. Wilson, C.G., et al., Hepatocyte-specific disruption of CD36 attenuates fatty liver and improves insulin sensitivity in HFD-fed mice. Endocrinology, 2016. 157(2): p. 570-585.

5. Mao, J., et al., Liver-specific deletion of acetyl-CoA carboxylase 1 reduces hepatic triglyceride accumulation without affecting glucose homeostasis. Proceedings of the National Academy of Sciences, 2006. 103(22): p. 8552-8557.

6. Chakravarthy, M.V., et al., “New” hepatic fat activates PPARα to maintain glucose, lipid, and cholesterol homeostasis. Cell metabolism, 2005. 1(5): p. 309-322.

7. Dirkx, R., et al., Absence of peroxisomes in mouse hepatocytes causes mitochondrial and ER abnormalities. Hepatology, 2005. 41(4): p. 868-878.

8. Knebel, B., et al., Liver-specific expression of transcriptionally active SREBP-1c is associated with fatty liver and increased visceral fat mass. PLoS One, 2012. 7(2): p. e31812.

9. Garcia, D., et al., Genetic Liver-Specific AMPK Activation Protects against Diet-Induced Obesity and NAFLD. Cell Rep, 2019. 26(1): p. 192-208 e6.

10. Zhang, M., et al., Comparative Transcriptomic Analysis of Mammary Gland Tissues Reveals the Critical Role of GPR110 in Palmitic Acid-Stimulated Milk Protein and Fat Synthesis. British Journal of Nutrition, 2023: p. 1-32.

11. Yazdi, F.T., S.M. Clee, and D. Meyre, Obesity genetics in mouse and human: back and forth, and back again. PeerJ, 2015. 3: p. e856.

12. Clee, S.M. and A.D. Attie, The genetic landscape of type 2 diabetes in mice. Endocrine reviews, 2007. 28(1): p. 48-83.

13. Gordon-Larsen, P., et al., Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity. Adv Nutr, 2021. 12(5): p. 2023-2034.

14. Speakman, J., et al., The contribution of animal models to the study of obesity. Laboratory animals, 2008. 42(4): p. 413-432.

15. Kebede, M.A. and A.D. Attie, Insights into obesity and diabetes at the intersection of mouse and human genetics. Trends in Endocrinology and Metabolism, 2014. 25(10): p. 493-501.

16. Zhang, G., et al., Carbon tetrachloride (CCl4) accelerated development of non-alcoholic fatty liver disease (NAFLD)/steatohepatitis (NASH) in MS-NASH mice fed western diet supplemented with fructose (WDF). BMC gastroenterology, 2020. 20(1): p. 1-13.

17. Zhu, N., et al., Metabolomic study of high-fat diet-induced obese (DIO) and DIO plus CCl4induced NASH mice and the effect of obeticholic acid. Metabolites, 2021. 11(6): p. 374.

18. Hansen, H.H., et al., Mouse models of nonalcoholic steatohepatitis in preclinical drug development. Drug discovery today, 2017. 22(11): p. 1707-1718.

19. Tsuneyama, K., et al., Animal models for analyzing metabolic syndrome‐associated liver diseases. Pathology international, 2017. 67(11): p. 539-546.

20. Afrin, R., et al., Curcumin ameliorates liver damage and progression of NASH in NASH-HCC mouse model possibly by modulating HMGB1-NF-κB translocation. International immunopharmacology, 2017. 44: p. 174-182.

21. Zhu, X., et al., Berberine attenuates nonalcoholic hepatic steatosis through the AMPK- SREBP-1c-SCD1 pathway. Free Radical Biology and Medicine, 2019. 141: p. 192-204.

22. Ma, B., et al., Gpr110 deficiency decelerates carcinogen-induced hepatocarcinogenesis via activation of the IL-6/STAT3 pathway. Am J Cancer Res, 2017. 7(3): p. 433-447.

23. Mauvoisin, D. and C. Mounier, Hormonal and nutritional regulation of SCD1 gene expression. Biochimie, 2011. 93(1): p. 78-86.

24. Lounis, M.A., et al., Oleate activates SREBP-1 signaling activity in SCD1-deficient hepatocytes. American Journal of Physiology-Endocrinology and Metabolism, 2017. 313(6): p. E710-E720.

https://doi.org/10.7554/eLife.85131.sa2

Article and author information

Author details

  1. Mengyao Wu

    Department of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou, China
    Contribution
    Data curation, Investigation, Methodology, Writing – original draft
    Competing interests
    has filed the following provisional patent: "Application of GPR110 as target for treating metabolic diseases"; US Provisional Filing Ref No. 63/370,948. The author has no other competing interests to declare
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5748-5780
  2. Tak-Ho Lo

    Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, Hong Kong
    Contribution
    Investigation, Methodology, Writing – original draft
    Competing interests
    No competing interests declared
  3. Liping Li

    Zhujiang Hospital, Southern Medical University, China, China
    Contribution
    Resources, Validation
    Competing interests
    No competing interests declared
  4. Jia Sun

    Zhujiang Hospital, Southern Medical University, China, China
    Contribution
    Resources, Funding acquisition
    Competing interests
    No competing interests declared
  5. Chujun Deng

    Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, Hong Kong
    Contribution
    Validation, Investigation
    Competing interests
    No competing interests declared
  6. Ka-Ying Chan

    Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, Hong Kong
    Contribution
    Validation, Methodology
    Competing interests
    No competing interests declared
  7. Xiang Li

    Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, Hong Kong
    Contribution
    Validation, Methodology
    Competing interests
    No competing interests declared
  8. Steve Ting-Yuan Yeh

    Ionis Pharmaceuticals, Carlsbad, United States
    Contribution
    Resources, Methodology, Writing – original draft
    Competing interests
    is affiliated with Ionis Pharmaceuticals, and holds stock at Ionis. The author has no other competing interests to declare
  9. Jimmy Tsz Hang Lee

    1. Department of Medicine, University of Hong Kong, Hong Kong, Hong Kong
    2. State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, Hong Kong, China
    Contribution
    Conceptualization, Methodology
    Competing interests
    No competing interests declared
  10. Pauline Po Yee Lui

    Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong, Hong Kong
    Contribution
    Validation, Investigation, Writing – original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2446-6203
  11. Aimin Xu

    1. Department of Medicine, University of Hong Kong, Hong Kong, Hong Kong
    2. State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, Hong Kong, China
    Contribution
    Conceptualization, Supervision, Writing – original draft
    Competing interests
    No competing interests declared
  12. Chi-Ming Wong

    1. Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, Hong Kong
    2. State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, Hong Kong, China
    3. Hong Kong Polytechnic University, Shenzhen Research Institute, Hong Kong, China
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing – original draft, Project administration
    For correspondence
    chi-ming.cm.wong@polyu.edu.hk
    Competing interests
    has filed the following provisional patent: "Application of GPR110 as target for treating metabolic diseases"; US Provisional Filing Ref No. 63/370,948. The author has no other competing interests to declare
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0025-7135

Funding

National Natural Science Foundation of China (81870586)

  • Chi-Ming Wong

Hong Kong University Grants Committee, Area of Excellence (AoE/M-707/18)

  • Chi-Ming Wong

Hong Kong University Grants Committee, General Research Fund (15101520)

  • Chi-Ming Wong

National Natural Science Foundation of China (82270941)

  • Jia Sun

National Natural Science Foundation of China (81974117)

  • Jia Sun

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (81870586), Area of Excellence (AoE/M-707/18), and General Research Fund (15101520) to CMW, and National Natural Science Foundation of China (82270941, 81974117) to SJ. We also thank Dr. Oscar Wong and Prof. Zou Xiang for critical review of this manuscript.

Ethics

The human study is approved by the Zhujiang Hospital, Southern Medical University, Guangzhou, China (Number: 2019-KY-097-01).

All animal procedures were approved by the Animal Subjects Ethics Sub-Committee of the Hong Kong Polytechnic University and were conducted in accordance with the guidelines of the Centralized Animals Facilities with the ethics number 19-20/78-HTI-R-OTHERS.

Senior Editor

  1. Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States

Reviewing Editor

  1. Matthew A Quinn, Wake Forest School of Medicine, United States

Reviewer

  1. Weiping Han, Institute of Molecular and Cellular Biology, Singapore

Version history

  1. Received: November 23, 2022
  2. Preprint posted: December 12, 2022 (view preprint)
  3. Accepted: July 28, 2023
  4. Version of Record published: August 15, 2023 (version 1)
  5. Version of Record updated: January 22, 2024 (version 2)

Copyright

© 2023, Wu et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Mengyao Wu
  2. Tak-Ho Lo
  3. Liping Li
  4. Jia Sun
  5. Chujun Deng
  6. Ka-Ying Chan
  7. Xiang Li
  8. Steve Ting-Yuan Yeh
  9. Jimmy Tsz Hang Lee
  10. Pauline Po Yee Lui
  11. Aimin Xu
  12. Chi-Ming Wong
(2023)
Amelioration of non-alcoholic fatty liver disease by targeting adhesion G protein-coupled receptor F1 (Adgrf1)
eLife 12:e85131.
https://doi.org/10.7554/eLife.85131

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