• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    LC-MS-based lipidomic analysis in distinguishing patients with nonalcoholic steatohepatitis from nonalcoholic fatty liver

    2021-11-08 08:33:40ZhongHuWngKnnthZhngXioDongWngJinQioYngYngLiLiZhngMingHuZhngJinWu

    Zhong-Hu Wng ,Knnth I Zhng ,Xio-Dong Wng ,,,Jin Qio ,Yng-Yng Li ,Li Zhng ,Ming-Hu Zhng ,,,Jin Wu ,g,h,?

    a Department of Medical Microbiology and Parasitology, MOE/NHC/CAMS Key Laboratory of Medical Molecular Virology, School of Basic Medical Sciences, Fudan University Shanghai Medical College, Shanghai 20 0 032, China

    b NAFLD Research Center, Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 3250 0 0, China

    c Institute of Hepatology, Wenzhou Medical University, Wenzhou 3250 0 0, China

    d Th e Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou 3250 0 0, China

    e Department of General Practice, Huaihai Middle Road Community Health Service Center of Huangpu District, Shanghai 20 0 025, China

    f Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 3250 0 0, China

    g Department of Gastroenterology and Hepatology, Zhongshan Hospital of Fudan University, Shanghai 20 0 032, China

    h Laboratory of Fatty Liver and Metabolic Diseases, Shanghai Institute of Liver Diseases, Fudan University Shanghai Medi cal College, Shanghai 20 0 032, China

    Keywords: Lipidomics Nonalcoholic steatohepatitis Nonalcoholic fatty liver disease Biomarker Nonalcoholic activity score Hepatic fibrosis

    ABSTRACT Background: Nonalcoholic fatty liver disease (NAFLD) is one of the main liver diseases, and its pathologic profile includes nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH). However, there is no reliable non-invasive parameter in distinguishing NASH from NAFL in clinical practice. The present study was to find a non-invasive way to differentiate these two categories of NAFLD via lipidomic analysis. Methods: Lipidomic analysis was used to determine the changes of lipid moieties in blood from 20 NAFL and 10 NASH patients with liver biopsy. Liver histology was evaluated after hematoxylin and eosin stain-ing and Masson’s trichrome staining. The profile of lipid metabolites in correlation with steatosis, inflam-mation, hepatocellular necroptosis, fibrosis, and NAFLD activity score (NAS) was analyzed. Results: Compared with NAFL patients, NASH patients had higher degree of steatosis, ballooning de-generation, lobular inflammation. A total of 434 different lipid molecules were identified, which were mainly composed of various phospholipids and triacylglycerols. Many lipids, such as phosphatidyl-choline (PC) (P-22:0/18:1), sphingomyelin (SM) (d14:0/18:0), SM (d14:0/24:0), SM (d14:0/22:0), phos-phatidylethanolamine (PE) (18:0/22:5), PC (O-22:2/12:0), and PC (26:1/11:0) were elevated in the NASH group compared to those in the NAFL group. Specific analysis revealed an overall lipidomic profile shift from NAFL to NASH, and identified valuable lipid moieties, such as PCs [PC (14:0/18:2), PE (18:0/22:5) and PC (26:1/11:0)] or plasmalogens [PC (O-22:0/0:0), PC (O-18:0/0:0), PC (O-16:0/0:0)], which were signifi-cantly altered in NASH patients. In addition, PC (14:0/18:2), phosphatidic acid (18:2/24:4) were positively correlated with NAS; whereas PC (18:0/0:0) was correlated positively with fibrosis score. Conclusions: The present study revealed overall lipidomic profile shift from NAFL to NASH, identified valuable lipid moieties which may be non-invasive biomarkers in the categorization of NAFLD. The cor-relations between lipid moieties and NAS and fibrosis scores indicate that these lipid biomarkers may be used to predict the severity of the disease.

    Introduction

    Nonalcoholic fatty liver disease (NAFLD) is one of the main liver diseases and its pathologic profile ranged from nonalcoholic fatty liver (NAFL), nonalcoholic steatohepatitis (NASH) with varying de-grees of fibrosis and, in some cases, to cirrhosis [1] . NAFLD has be-come the most common metabolic disease underlying obesity, dys-lipidemia, metabolic syndrome and type 2 diabetes with a preva-lence of 15% in China [2],and 30% or higher in the North America and Europe [ 3–5 ]. The main difference between NASH and NAFL is the presence of hepatic inflammation, hepatocellular injury and cell death. Approximately 25% of patients with NAFL may develop NASH, 15%-20% of patients with NASH may further progress to fi-brosis and eventually cirrhosis, and at least 1%-2% of them may develop to HCC each year [ 3,5 ]. The progression from NAFL to NASH with fibrosis is a manifestation of disease activity, and the severity of liver fibrosis is a long-term determinant of complica-tions and death in NASH patients [ 6–8 ]. Thus, it is crucial to iden-tify NASH patients with fibrosis and take preventive measures to stop or reverse NASH progression. However, it is difficult to dis-tinguish NASH from NAFL with current laboratory tests and imag-ing modalities, and often requires invasive liver biopsy. Therefore, novel biomarkers are needed for noninvasive differentiating diag-nosis of NASH from NAFL and assessment of treatment responses in clinical practice.

    Metabolomics has drawn great scientific attention due to its powerful measurement of numerous metabolites at accurate levels. Metabolomic methodology allows to understand overall metabolic alterations during the transition from healthy liver, NAFL to NASH [9] . Lipidomics is an important branch of metabolomics. It accurately analyzes the changes of lipid metabolites, determines the characteristics of lipid metabolism in different stages of dis-ease progression, and identifies valuable diagnostic indicators. As a metabolic disorder, NASH possesses tremendous metabolic ab-normalities in carbohydrates, lipids and other metabolites. General metabolomics may provide an overall profile of metabolic changes; whereas lipidomic analysis with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) is able to re-veal lipids that are not seen in established analytical techniques, thus, may identify unusual lipid metabolic pathways or possible biomarkers for differentiating NASH from NAFL [10] . Moreover, routine lipid panels in clinical laboratory only examine limited range of lipids in the liver or bloodstream, and substantial changes in numerous lipids outside of these moieties are not commonly measured in a metabolomic panel. Given the important biological activity among lipids, especially for lipid species that are not rec-ognized, such as in informatory signaling pathways, lipidomic anal-ysis in pathologically confirmed patients may provide deep insights into the pathophysiology in the transition from NAFL to NASH as well as further fibrotic progression [11] . To explore the differenti-ating potential of lipidomic analysis in NAFLD patients, the UHPLC-MS/MS lipidomic platform was used to measure serum lipids of NASH patients and NAFL controls with liver biopsy, and to explore the relationship between abnormalities in blood lipid metabolism and extent of steatohepatitis and fibrosis in NASH patients. The ul-timate goal is to identify new biomarkers for noninvasive diagnosis and effective prevention of NASH.

    Materials and methods

    Patients and sample collection

    Human serum samples of this study were obtained from the First Affiliated Hospital of Wenzhou Medical University. The study was approved by the Institutional Review Board of the First Affili-ated Hospital of Wenzhou Medical University and the Ethics Com-mittee of Fudan University School of Basic Medical Sciences. In our study, all subjects were enrolled in accordance with ethical guide-lines, and written informed consent was obtained prior to the par-ticipation. All clinical procedures involved in this study were per-formed in accordance with the relevant guidelines and regulations. All subjects were ruled out of alcoholic liver or other causes of liver diseases (hepatitis B, or C infection, autoimmune hepatitis, drug toxicity, etc.) by methods previously described [12] .

    According to liver histology, serum from 30 subjects was di-vided into two groups: NAFL control group (n= 20) and NASH group (n= 10). Blood samples were collected from subjects who were fasted overnight (8 h) and placed in cold tubes containing ethylene diamine tetraacetic acid (EDTA) (6 mmol/L). Serum was separated by centrifugation (2500 rpm, 15 min) and aliquots were immediately frozen at -80 °C until analysis (avoiding repeated freezing and thawing) [13] . Table 1 summarizes the demographic information and results of clinical laboratory parameters of the enrolled subjects, including NAFLD activity score (NAS), index of homeostasis model assessment insulin resistance (HOMA-IR), con-trolled attenuation parameter (CAP) from ultrasound stiffness ex-amination, and semiquantitative score of fibrosis. The calculation of HOMA-IR was made according to the formula as described pre-viously [14] .

    Table 1 Clinical and biological characteristics of NASH and NAFL patients.

    Ultrasonographical examination for hepatic steatosis

    All patients have undergone sonographic examination for hep-atic fatty content measurement of CAP by a well-trained special-ist. The CAP measures ultrasonic attenuation in the liver at 3.5 MHz using signals acquired by the FibroScan?M probe based on vibration-controlled transient elastography (VCTETM). The princi-ples were described previously [15] .

    Tissue staining of liver biopsy

    An ultrasound-guided liver biopsy was performed under se-dation using an 18-gauge Hepafix needle (Gallini, Modena, Italy). Biopsy specimens were fixed in 10% formalin, embedded in paraf-fin, cut and stained with hematoxylin and eosin and Masson’s trichrome. Histopathology of all biopsies was examined by an ex-perienced and board-certified liver pathologist (Dr. Yang-Yang Li), who was blinded to clinical and laboratory data of participants. The histologic features of NAFLD were scored according to the NASH Clinical Research Network classification [16] . Each slide was evaluated for two aspects, NAS (0–8) and fibrosis stage (1–4). NAS was calculated based on the unweighted sum of the scores for steatosis (0–3), lobular inflammation (0–3) and hepatocellular bal-looning (0–2) [16] . Fibrosis was staged in both HE and trichrome staining sections according to Ludwig’s and Scheuer’s classifica-tions, from 0 to 4: 0 = no fibrosis; 1 = perisinusoidal or portal fi-brosis; 2 = perisinusoidal and portal/periportal fibrosis; 3 = bridg-ing fibrosis; 4 = highly suspicious or definite cirrhosis [ 17–19 ]. If NAS of a liver specimen is ≥5, the section is defined as “NASH”. If NAS is ≤4, it represents as “NAFL”[16] . All stained sections were photographed under light microscopy with ×200 amplification.

    Non-targeted lipidomics

    The ultra-high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF/MS) analysis was performed utilizing an UHPLC system (1290 series, Agilent Technologies, Santa Clara, CA, USA) coupled to a quadru-ple time-of-flight (QTOF) mass spectrometer (Agilent 6550 iFunnel QTOF, Agilent Technologies). A Waters ACQUITY UPLC BEH Amide column [particle size, 1.7μm; 100 mm (length) ×2.1 mm (i.d.)] was used for the lipid extract (LE) separation, and the column temperature was maintained at 25 °C. The flow rate was set as 0.6 mL/min, and the sample injection volume was 2μL. The mo-bile phase A was 25 mM ammonium hydroxide (NH4OH) + 25 mM ammonium acetate (NH 4 OAc) in water, and B was acetonitrile (ACN) in positive mode (ESI + ). The gradient was set as follows: 0–0.5 min, 95% B; 0.5–7 min, 95% B to 65% B; 7–8 min, 65% B to 40% B; 8–9 min, 40% B; 9–9.1 min, 40% B to 95% B; 9.1–12 min, 95% B. The acquisition rate was set as 4 spectra/second, and the time-of-fight (TOF) mass range was set as m/z 50–1200 Da in a positive mode. The parameters of mass spectrometry (MS) data ac-quisition were set as follows: sheath gas temperature, 400 °C; dry gas temperature, 250 °C; sheath gas flow, 12 L/min; dry gas flow, 16 L/min; capillary voltage, 30 0 0 V; nozzle voltage, 0 V; and neb-ulizer pressure, 20 psi. Tandem mass spectrometry (MS/MS) data acquisition was performed using another QTOF S2 mass spectrom-eter (Triple TOF 5600 +,AB SCIEX, USA). Quality control samples were used for MS/MS data acquisition. To expand the coverage of MS/MS spectra, the mass range was divided into 4 segments: 50–30 0 Da, 290–60 0 Da, 590–90 0 Da, and 890–1200 Da. The acquired MS/MS spectra were matched against in-house tandem MS/MS li-brary for metabolite identification. The source parameters were set as follows: GAS1, 60; GAS2, 60; CUR, 30; TEM, 600 °C; and ISVF, 5500 V [20] . The analysis was performed in the Lipidomics Service Platform [21],Shanghai Life Science Institutes, Chinese Academy of Sciences, Shanghai, China.

    Raw data preprocessing

    The ionization source of the LC-QTOFMS platform is electro-spray ionization. There are two ionization modes: positive ion mode (POS) and negative ion mode (NEG). The raw data of the pos-itive ion mode contained 4 quality control samples, 20 NAFL and 10 NASH samples. A total of 327 peaks were extracted from them. In order to better analyze the data, a series of preparation and data management on the original data were undertaken. They mainly included the following steps: (1) filtering a single peak to remove noise. The deviation was filtered based on the relative standard de-viation (RSD), or coefficient of variation (CV). (2) Filtering on a sin-gle peak. Only peak area data with no more than 50% null values in a single group or no more than 50% null values in all groups were retained. Missing value recoding was performed on the orig-inal data. The numerical simulation method was to fill in half of the minimum value. Data normalization was performed using the total ion current (TIC) of each sample. After preprocessing, 327 sta-tistically significant peaks were retained.

    Statistical analysis

    All statistical analyses were conducted using the SPSS Version 2.0 (SPSS, Chicago, IL, USA). Data were presented as means ±stan-dard deviation (SD) or frequencies. Baseline characteristics of the study population were compared using the one-way ANOVA analy-sis for continuous variables. The final dataset containing the infor-mation of peak number, sample name and normalized peak area were imported to SIMCA15.0.2 software package (Sartorius Stedim Data Analytics AB, Ume?, Sweden) for multivariate analysis. Data were scaled and logarithmic transformed to minimize the impact of both noise and high variance of the variables. After these trans-formations, principle component analysis (PCA) was carried out to visualize the distribution and the grouping of the samples. We used 95% confidence interval in the PCA score plot as the thresh-old to identify potential outliers in the dataset. In order to visualize group separation and find significantly altered metabolites, super-vised orthogonal projection to latent structures-discriminate anal-ysis (orthogonal partial least-square, OPLS-DA) was applied. Then, a 7-fold cross validation was performed to calculate the value of R2and Q2. R2indicates how well the variation of a variable is ex-plained and Q2means how well a variable could be predicted. To check the robustness and predictive ability of the OPLS-DA model, 200 times of permutations were further conducted. Afterward, the R2and Q2intercept values were obtained. Here, the intercept value of Q2represents the robustness of the model, the risk of over-fitting and the reliability of the model, and the smaller the bet-ter. Furthermore, the value of variable importance in the projec-tion (VIP) of the first principal component in OPLS-DA analysis was obtained. It summarizes the contribution of each variable to the model. The metabolites with VIP>1 andP<0.05 (Student’sttest) were considered as significantly altered. Spearman rank cor-relation was used to analyze the correlation between lipids and liver pathological scores. At the same time, the lipidomic data were also verified by the PLS-DA model to confirm suitability and lia-bility of OPLS-DA modeling (Fig. S1) [22] . As shown in the figure, the PLS-DA model was used to re-analyze the data from two NASH and NAFL groups. Through the analysis, it is clear that there is no significant difference in the first and second principal component analyses between the groups. The parameters (PLS-DA model pa-rameter table) used in PLS-DA analysis are the same as in the pre-vious OPLS-DA model. The only difference is that PLS-DA lacks pos-itive exchange calculation analysis; whereas OPLS-DA model may filter out the signals that are not related to the model classifica-tion, hence its interpretation ability is stronger than PLS-DA.

    Fig. 1. Lipid profiles of serum samples from the NAFL and NASH groups and preliminary data processing. A: Proportion of major lipid components. B: Principal component analysis (PCA) score plot of metabolic profile of the NASH and NAFL groups after mean-centering and not (Ctr) scaling. C: OPLS-DA score plot of lipid profile of the NASH and NAFL groups after unit variance (uv) scaling. D: Score plot of OPLS-DA model obtained from C . The resulting R 2 and Q 2 values were plotted. The red dots represent the R 2 Y values obtained from the displacement test; the blue square dots represent the Q 2 values obtained from the displacement test; and the two dashed lines represent the regression lines of R 2 Y and Q 2,respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Fig. 2. Heatmap of hierarchical cluster analysis of differential metabolites in the NASH and NAFL groups. The columns at the left side of the solid line represent the samples from the NASH group; while those at the right side of the solid line represent the samples from the NAFL group. Levels of the discriminating metabolites in all samples are shown in color. Up-regulated metabolites are presented with the red color, while the down-regulated metabolites are shown with the blue color. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).

    Results

    Demographics

    Thirty NAFLD patients (20 cases of NAFL and 10 cases of NASH) were included in the present study. The detailed baseline charac-teristics including demographics, body mass index (BMI), biochem-ical tests, HOMA-IR, CAP value and histopathologic description of liver biopsy from all patients are detailed in Table 1 . It is clear that NASH patients had a higher BMI (P= 0.02), higher serum levels of AST/ALT ratio (P= 0.05) and slightly higher GGT (P>0.05) than NAFL patients. Fasting serum insulin levels tended to be higher in NASH patients than NAFL patients, however, statistical analysis did not show any significance (P>0.05). Routine liver biochemical and metabolic tests [such as serum glucose, bilirubin, high density lipoprotein (HDL), low density lipoprotein (LDL), triglyceride (TG), total cholesterol did not significantly differ between the NASH and NAFL groups ( Table 1 ). Due to very close serum glucose and fast-ing insulin levels, HOMA-IR did not show any difference between these two groups although both of them were above the normal range (5.80 and 8.17), and there was a tendency that NASH patients had a more severe insulin resistance than NAFL patients. Compared to the NAFL group, patients in NASH group had much higher NAS levels with a severe degree of steatosis (CAP and histology), bal-looning degeneration, lobular inflammation, and there was a ten-dency that NASH group had higher semiquantitative score of hep-atic fibrosis in Masson’s staining. Thus, AST/ALT ratio, CAP read-ing, NAS and extent of fibrosis were separable in patients between NAFL and NASH, and were consistent with clinical and patholog-ical diagnosis. As the most reliable pathologic variables, NAS and semi-quantitative fibrosis score were used as two major references to determine differential values of lipidomic measurements as well as the base for correlation analysis, although there was no sig-nificantly statistical difference in fibrosis score between these two groups.

    Composition of serum lipid extracts

    A total of 434 different lipid molecules, which were predom-inantly composed of various phospholipids (PLs), were identi-fied from analyzed serum samples. There were 166 phosphatidyl-cholines (PC), 108 phosphatidylethanolamines (PE), 59 sphin-gomyelins (SM), 37 lyso-phosphatidylcholines (LPC), 21 phos-phatidylglycerols (PG), 17 phosphatidylinositols (PI), 13 phospha-tidic acids (PA), 12 lyso-phosphatidylethanolamines (LPE), and 1 phosphatidylserines (PS) in the identified lipid pool, which were further analyzed. The percentage of each lipid in the total pool is shown in Fig. 1 A and Table S1.

    The results of multivariate statistical analysis

    To evaluate whether NASH affects lipid synthesis and compo-sition, 327 peaks remained after the removal of noise based on the interquartile range and normalization using TIC of each sam-ple. After obtaining the collated data, a series of multivariate pat-tern recognition analysis was undertaken. First, PCA was initially applied to the spectra to visualize inherent clustering between the NAFL control and NASH groups. As shown in the PCA score map, the isolated samples were basically within the 95% confi-dence interval (Hotelling’s T-squared ellipse); however, there was some overlap between the NAFL and NASH groups ( Fig. 1 B). In order to obtain a high level of group separation and for a better understanding of the variables responsible for classification, super-vised OPLS-DA was applied. From the OPLS-DA score ( Fig. 1 C), it is evident that isolated samples have a clear separation between these two groups. Then it was further verified whether the model established in this way reflects the actual situation of the lipid data by OPLS-DA permutation test. As shown in Fig. 1 D, the original R2Y model was very close to 1, indicating that the OPLS-DA model was consistent with the actual situation of the lipid data. In general, the original model may explain the differences in lipid distribution between these two groups in convincing robustness and there was no over-fitting phenomenon (R2Y = 0.65).

    Dif ferences in lipid metabolites between the NAFL and NASH groups

    In order to find out the lipid moieties whose concentrations were altered in the NASH group compared to those in the NAFL group, all the ion peaks were defined with their VIP in the OPLS-DA model, which was superior to 1. A Student’sttest was performed between these two groups. Peak areas withPvalue higher than 0.05 were excluded as indicated in Fig. S2. Then the heatmap was created to perform hierarchical clustering analysis on such features ( Fig. 2 ), which aids in classifying lipid moieties with the same features into one class and exhibits the signifi-cant difference between the NASH and NAFL groups. From the heatmap, it is clear that PC (P-22:0/18:1) (1.3:1,P= 0.037), SM (d14:0/18:0) (1.3:1,P= 0.003), SM (d14:0/24:0) (1.4:1,P= 0.012), SM (d14:0/22:0) (1.6:1,P= 0.033), PE (18:0/22:5) (1.4:1,P= 0.025), PC (O-22:2/12:0) (1.4:1,P= 0.045), and PC (26:1/11:0) (P= 0.011) in the NASH group were significantly higher than the NAFL group. Whereas PC (22:6/0:0) (0.6:1,P= 0.0 0 01), PC (16:1/0:0) (0.7:1,P= 0.001) and SM (d14:0/12:0) (0.77:1,P= 0.023) in the NASH group were lower than the NAFL group. Therefore, the value of these lipid moieties appears to be differentially distributed be-tween the NASH and NAFL groups. Relevant data are shown in Ta-ble S1.

    Fig. 3. Pathological staining and correlation analysis. A: Masson trichrome and hematoxylin-eosin (HE) staining of liver biopsy tissue from the NASH and NAFL groups. a, b, e, f represent the samples from the NAFL group, while c, d, g, h represent the samples from the NASH group. B : Correlation between lipid changes and liver pathological scores. FS: fibrosis score. Negative and positive regression value is presented in color. NAS: NAFLD activity score. Images were taken at original magnification ( ×200). Scale bars = 60 μm ( e,f,g,h )

    Hepatocellular steatosis and fibrosis in NAFL and NASH

    To determine the extent of hepatic fibrosis, Masson’s trichrome staining of liver biopsy tissue was performed. It is evident that collagenous fibrils were deposited in the pericellular space in the NASH group ( Fig. 3 Ac,d), which was more severe than the NAFL group ( Fig. 3 Aa,b). Hepatocytes in the NASH group appeared to be steatotic in severe degrees as shown by HE staining ( Fig. 3 Ag, h), whereas steatosis in the NAFL group ( Fig. 3 Ae, f) was mild and less visible in comparison to the NASH group. Thus, the main patho-logic difference of NASH from NAFL was the severity of steatosis, occurrence of inflammatory reaction, and fibrotic progression as observed in HE and Masson’s staining, and they were well reflected by NAS and fibrosis scores in Table 1 . The statistical difference in NAS between the NASH and NAFL groups was striking (P<0.0 0 01 in NAS), although the fibrosis score did not reach statistical sig-nificance (P= 0.08). The NAS and fibrosis score are well-accepted semiquantitative parameters to reflect the severity of NASH with fibrotic progression.

    Correlation between lipid changes and semi-quantitative scores of pathological assessments

    NAS and fibrosis scores were used to further define whether al-tered profile of lipid metabolites in the NASH group reflects un-derlying pathologic changes of steatosis, inflammation, hepatocel-lular necroptosis, and fibrosis. As shown in Fig. 3 B, PE (18:0/22:5) and PC (14:0/18:2) are positively correlated with NAS (regression values: 0.46 and 0.43,P= 0.01, respectively). In contrast, PCs (sat-urated or monounsaturated), such as PC (22:6/0:0), PC (20:4/0:0) and PC (16:1/0:0) were negatively correlated with NAS (regression value: -0.56, -0.58 and -0.56,P= 0.0 01, 0.0 0 06 and 0.0 01, respec-tively). Of note, PC (18:0/0:0) was positively correlated with liver fibrosis score (regression value: 0.36,P= 0.04). Moreover, a large proportion of plasmalogens, such as PC (O-22:2/16:1) and PC (O-22:0/0:0) were negatively correlated with liver fibrosis scores (re-gression values: -0.45 and -0.41,P= 0.01 and 0.02, respectively). In summary, lipid moieties are differentially distributed in the NASH and NAFL groups with positive or negative correlation to the sever-ity of NASH and fibrosis progression. These correlations may im-ply pathophysiologic importance and potential clinical references of significantly altered lipid moieties as biomarkers for NASH pro-gression. Presumably, a combination of these lipid moieties may help to differentiate NASH from NAFL.

    Discussion

    It is well known that the changes in lipid homeostasis, such as cholesterol esters, TG, diacylglycerol, and sphingomyelin in blood and liver tissues are the feature of NAFLD [ 23–26 ]. Existing studies have shown that there are significant differences in lipid profiles between healthy subjects and NAFLD patients [10] . However, it re-mains a real challenge in using lipid data to distinguish NASH from NAFL patients. The biological effects of changes in lipid composi-tion are very complex and multifaceted, and depend on their rel-ative cellular and subcellular locations [ 27,28 ]. They may function as key signaling molecules, transcription regulators or check-point substances in metabolism, immunity, or cellular responses [ 29–31 ]. They may further affect membrane fluidity. Lipid peroxidation may occur under oxidant stress, and cause lipotoxicity [32] .

    Several studies employing metabolomics or lipidomics are avail-able to determine metabolic or lipidomic profile changes among controls, NAFL and NASH [ 33–35 ]. Puri and colleagues demon-strated that [33] serum 5-hydroxyeicosatetraenoic acid (5-HETE), 8-HETE, and 15-HETE are increased in a stepwise manner in the progression from normal to NAFL, further to NASH. Our present study identified the differences in lipid characteristics between NAFL and NASH patients. Through rigorous statistical analysis, we found that phospholipids: PC (P-22:0/18:1), PC (26:1/11:0), PE (18:0/22:5) and PE (18:0/22:5) were increased in patients with NASH; whereas PC (22:6/0:0), PC (16:1/0:0) and SM (d14:0/12:0) were decreased in these patients compared to NAFL. Therefore, NASH lipidomic profile was much shifted from NAFL, and the changes in individual PC, PE components demonstrated signifi-cant alteration in lipid metabolism in NASH patients, suggesting that abnormal phospholipid metabolism is involved in the tran-sition from NAFL to steatohepatitis. Furthermore, individual moi-eties of lipids which were either increased or decreased in NASH patients from this study were different from those previously re-ported [ 33,34 ]. Thus, our findings are additive to the previous stud-ies in terms of changes in specific individual lipid moieties in the transition from NAFL to NASH.

    With the availability of pathological evidence, we found that the changes in individual lipid moieties were correlated with the severity of NASH and fibrotic progression. Through cluster analysis combined with small lipid molecules in the correlation with NAS and fibrosis score, we found that PC (18:0/0:0) was positively cor-related with fibrosis score, and PC (14:0/18:2), PA (18:2/24:4) were positively correlated with NAS. Therefore, the lipid moieties may be non-invasive serum markers indicating NASH progression. This is a significant advance in this field, since, to our knowledge, this is the first study to reveal these correlations in NAFLD patients. Moreover, a combinatory modeling with 10 increased lipid species predicts the presence of liver fibrosis in NASH patients [11] . With healthy controls and a better cross-section study, polyunsaturated fatty acid metabolites, such as 13,14-dihydro-15-keto prostaglandin D2 (dhk PGD2) and 20-carboxy arachidonic acid (20-COOH AA) were found to be of diagnostic values for NAFL and NASH [36] .

    In conclusion, the findings of this study demonstrated overall lipidomic profile shift from NAFL to NASH, and identified valuable lipid moieties. The correlations of altered lipids to NAS and fibro-sis scores indicate differential value of these lipid biomarkers in NAFLD.

    Acknowledgments

    We are grateful to Prof. Hui-Yong Yin and his team from the Shanghai Life Science Institutes, Chinese Academy of Sciences, Shanghai, China for careful analysis of lipidomic and valuable assis-tance in data analysis. We are in debt to Prof. Xiu-Ping Liu from the Department of Pathology, Fudan University School of Basic Medical Sciences in helping with micrographs of histopathologic images.

    CRediT authorship contribution statement

    Zhong-Hua Wang :Data curation, Formal analysis, Investi-gation, Writing original draft.Kenneth I Zheng :Investigation.Xiao-Dong Wang :Investigation. Jin Qiao :Data curation, Formal analysis.Yang-Yang Li :Investigation.Li Zhang:Data curation, In-vestigation.Ming-Hua Zheng :Data curation, Investigation, Super-vision.Jian Wu :Conceptualization, Data curation, Funding acquisi-tion, Supervision, Writing review & editing.

    Funding

    This study was supported by grants from the Ministry of Sci-ence & Technology of China ( 2016YFE0107400 ), the National Nat-ural Science Foundation of China ( 81272436,81572356,81871997,81500 6 65 and 82070588 ) and High Level Creative Talents from De-partment of Public Health in Zhejiang Province (S203210260 0 032) and Project of New Century 551 Talent Nurturing in Wenzhou.

    Ethical approval

    The study was approved by the Institutional Review Board of the First Affiliated Hospital of Wenzhou Medical University and the Ethics Committee of Fudan University School of Basic Medical Sci-ences. In our study all subjects were collected in accordance with ethical guidelines, and written informed consent was received. All patients were approached based on approved ethical guidelines, and patients who agreed to participate in this study were required to sign consent forms before being included in the study.

    Competing interest

    No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the sub-ject of this article.

    Supplementary materials

    Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.hbpd.2021.05.008 .

    神马国产精品三级电影在线观看| 精品久久久久久成人av| 国产成人freesex在线 | 99久久成人亚洲精品观看| 国产在线男女| 22中文网久久字幕| 亚洲熟妇中文字幕五十中出| 高清毛片免费观看视频网站| 日本一本二区三区精品| 不卡一级毛片| 成人毛片a级毛片在线播放| 99热网站在线观看| 男人的好看免费观看在线视频| 免费看日本二区| 亚洲精华国产精华液的使用体验 | 在线免费观看的www视频| 夜夜爽天天搞| 欧洲精品卡2卡3卡4卡5卡区| av天堂中文字幕网| 一级a爱片免费观看的视频| 嫩草影院精品99| 能在线免费观看的黄片| 亚洲中文日韩欧美视频| 久久精品人妻少妇| 中国国产av一级| 可以在线观看的亚洲视频| 国产色婷婷99| 国产女主播在线喷水免费视频网站 | 简卡轻食公司| 亚洲av中文字字幕乱码综合| 99国产极品粉嫩在线观看| 亚洲国产欧美人成| 在线看三级毛片| 看片在线看免费视频| 亚洲一区二区三区色噜噜| 美女黄网站色视频| 日韩亚洲欧美综合| 99久久精品一区二区三区| 麻豆久久精品国产亚洲av| 97超视频在线观看视频| 国产真实乱freesex| 成人美女网站在线观看视频| 悠悠久久av| 欧美精品国产亚洲| 欧美xxxx性猛交bbbb| 日韩一区二区视频免费看| av在线蜜桃| 亚洲国产欧洲综合997久久,| 久久精品夜色国产| 国产精品野战在线观看| 蜜臀久久99精品久久宅男| 一级毛片电影观看 | a级毛片a级免费在线| 最近2019中文字幕mv第一页| 欧美+日韩+精品| 色在线成人网| 一个人观看的视频www高清免费观看| 欧美成人免费av一区二区三区| 国产探花极品一区二区| avwww免费| 亚洲aⅴ乱码一区二区在线播放| 精品日产1卡2卡| 少妇熟女aⅴ在线视频| 成人三级黄色视频| 97热精品久久久久久| 日本三级黄在线观看| 亚洲av五月六月丁香网| 国产精品国产三级国产av玫瑰| 国模一区二区三区四区视频| 国内精品久久久久精免费| 不卡一级毛片| 久久久精品94久久精品| 女人被狂操c到高潮| 国产午夜精品论理片| 国产精品福利在线免费观看| 久久韩国三级中文字幕| 国产 一区 欧美 日韩| 精品熟女少妇av免费看| 在线免费观看的www视频| 亚洲va在线va天堂va国产| 国产aⅴ精品一区二区三区波| 中文亚洲av片在线观看爽| 免费电影在线观看免费观看| 亚洲欧美中文字幕日韩二区| 搡老熟女国产l中国老女人| 精品人妻视频免费看| 日韩成人av中文字幕在线观看 | 国产精品免费一区二区三区在线| 最近在线观看免费完整版| 真实男女啪啪啪动态图| 男女啪啪激烈高潮av片| 欧美日韩乱码在线| 亚洲国产精品国产精品| av.在线天堂| 国产男人的电影天堂91| 一级黄片播放器| 亚洲性久久影院| 色在线成人网| 成人无遮挡网站| 丝袜喷水一区| 欧美又色又爽又黄视频| 深爱激情五月婷婷| 久久草成人影院| 亚洲经典国产精华液单| АⅤ资源中文在线天堂| 久久人人爽人人片av| 国产亚洲精品av在线| 成人三级黄色视频| 久久国内精品自在自线图片| 成人精品一区二区免费| 欧美bdsm另类| 久久午夜亚洲精品久久| 国产亚洲精品av在线| 婷婷色综合大香蕉| 春色校园在线视频观看| 日韩在线高清观看一区二区三区| 看非洲黑人一级黄片| 色播亚洲综合网| 尤物成人国产欧美一区二区三区| 成人毛片a级毛片在线播放| 我要看日韩黄色一级片| 亚洲精品456在线播放app| 一个人看的www免费观看视频| 免费av毛片视频| 一本一本综合久久| 国产伦在线观看视频一区| 国产一区二区在线观看日韩| 高清毛片免费观看视频网站| 久久亚洲国产成人精品v| 精华霜和精华液先用哪个| 免费搜索国产男女视频| 中文字幕久久专区| 亚洲乱码一区二区免费版| 岛国在线免费视频观看| 国产色婷婷99| 精品久久久久久久久亚洲| 午夜老司机福利剧场| 精品久久久噜噜| 日韩一本色道免费dvd| 日韩欧美免费精品| 国产高清三级在线| 国产三级在线视频| 男人的好看免费观看在线视频| 日韩一区二区视频免费看| 国产一区二区三区av在线 | 最后的刺客免费高清国语| 天堂网av新在线| 日产精品乱码卡一卡2卡三| av视频在线观看入口| 久久久a久久爽久久v久久| 国产精品综合久久久久久久免费| 91久久精品国产一区二区成人| 中文字幕人妻熟人妻熟丝袜美| 身体一侧抽搐| 两个人视频免费观看高清| 级片在线观看| 自拍偷自拍亚洲精品老妇| 免费人成视频x8x8入口观看| 亚洲丝袜综合中文字幕| 欧美bdsm另类| 狂野欧美白嫩少妇大欣赏| 不卡视频在线观看欧美| 高清日韩中文字幕在线| 国产精品一区www在线观看| av在线亚洲专区| 在线观看一区二区三区| 亚洲人与动物交配视频| 少妇熟女aⅴ在线视频| 丰满人妻一区二区三区视频av| 精品一区二区三区视频在线| 日韩精品中文字幕看吧| 女生性感内裤真人,穿戴方法视频| 女人被狂操c到高潮| 99视频精品全部免费 在线| 国产黄a三级三级三级人| 干丝袜人妻中文字幕| 国语自产精品视频在线第100页| 精品午夜福利在线看| 成年免费大片在线观看| av.在线天堂| 国产精品精品国产色婷婷| 欧洲精品卡2卡3卡4卡5卡区| 亚洲精品一区av在线观看| 亚洲五月天丁香| 啦啦啦韩国在线观看视频| 午夜福利18| 亚洲精品国产av成人精品 | 亚洲五月天丁香| 一级毛片aaaaaa免费看小| 亚洲精品成人久久久久久| 亚洲精品国产av成人精品 | 国模一区二区三区四区视频| 波多野结衣巨乳人妻| 久久精品久久久久久噜噜老黄 | 午夜免费激情av| 97超碰精品成人国产| 久久99热这里只有精品18| 可以在线观看的亚洲视频| 少妇高潮的动态图| 亚洲内射少妇av| 亚洲欧美精品综合久久99| 永久网站在线| 欧美zozozo另类| 中文字幕久久专区| 久久精品国产清高在天天线| 亚洲精品456在线播放app| 午夜福利在线观看免费完整高清在 | 少妇猛男粗大的猛烈进出视频 | 此物有八面人人有两片| 久久午夜亚洲精品久久| av天堂中文字幕网| 国产高清有码在线观看视频| 97超碰精品成人国产| 国产私拍福利视频在线观看| 欧美色欧美亚洲另类二区| 99视频精品全部免费 在线| 亚洲性夜色夜夜综合| 日韩欧美国产在线观看| 黄片wwwwww| 欧美色视频一区免费| 两性午夜刺激爽爽歪歪视频在线观看| 99热只有精品国产| 午夜精品国产一区二区电影 | 美女免费视频网站| 久久精品夜色国产| 亚洲一区二区三区色噜噜| av视频在线观看入口| 国产激情偷乱视频一区二区| 久久久久久久久大av| a级毛色黄片| 成年女人看的毛片在线观看| 免费搜索国产男女视频| 久久精品国产亚洲av涩爱 | 久久久色成人| 免费无遮挡裸体视频| 成年女人永久免费观看视频| 真实男女啪啪啪动态图| 国产蜜桃级精品一区二区三区| 麻豆精品久久久久久蜜桃| 亚洲中文字幕日韩| 久久午夜福利片| 久久久久免费精品人妻一区二区| АⅤ资源中文在线天堂| av在线老鸭窝| 日韩中字成人| 国产精品一二三区在线看| 夜夜看夜夜爽夜夜摸| 欧美性感艳星| 久久久欧美国产精品| av免费在线看不卡| 久久久国产成人精品二区| 三级国产精品欧美在线观看| videossex国产| 91狼人影院| 国产亚洲91精品色在线| 久久久a久久爽久久v久久| 美女免费视频网站| 女人被狂操c到高潮| 欧美一区二区精品小视频在线| 六月丁香七月| 黄色一级大片看看| 深爱激情五月婷婷| 国产亚洲精品综合一区在线观看| 国产av不卡久久| 亚洲美女搞黄在线观看 | 99久久成人亚洲精品观看| 色在线成人网| 国产精品一二三区在线看| 人妻夜夜爽99麻豆av| 亚洲精品影视一区二区三区av| 亚洲成av人片在线播放无| 深夜精品福利| 亚洲天堂国产精品一区在线| 日韩欧美一区二区三区在线观看| 亚洲av不卡在线观看| 亚洲av中文av极速乱| 男插女下体视频免费在线播放| 亚洲国产精品合色在线| 少妇裸体淫交视频免费看高清| 啦啦啦观看免费观看视频高清| 99久久精品热视频| 亚洲人成网站在线播| 国产av在哪里看| 亚洲国产精品成人久久小说 | 99热只有精品国产| 老师上课跳d突然被开到最大视频| 无遮挡黄片免费观看| 能在线免费观看的黄片| 一区二区三区高清视频在线| 春色校园在线视频观看| 高清午夜精品一区二区三区 | 女的被弄到高潮叫床怎么办| 搡老岳熟女国产| 中文字幕精品亚洲无线码一区| 国产亚洲精品久久久久久毛片| 亚洲av第一区精品v没综合| 日韩一区二区视频免费看| 69人妻影院| a级一级毛片免费在线观看| 日韩欧美三级三区| 十八禁国产超污无遮挡网站| 99热网站在线观看| 精品久久久久久久久久久久久| 婷婷色综合大香蕉| 亚洲欧美精品综合久久99| 日日啪夜夜撸| 少妇人妻精品综合一区二区 | 色在线成人网| 啦啦啦啦在线视频资源| 日本五十路高清| 人妻少妇偷人精品九色| 两个人的视频大全免费| 国产精华一区二区三区| 在线天堂最新版资源| 欧美成人a在线观看| 熟妇人妻久久中文字幕3abv| 观看美女的网站| 18+在线观看网站| 少妇的逼好多水| 国产又黄又爽又无遮挡在线| 久久久久久伊人网av| 精品99又大又爽又粗少妇毛片| 亚洲美女黄片视频| 非洲黑人性xxxx精品又粗又长| 一区二区三区高清视频在线| 能在线免费观看的黄片| 悠悠久久av| 亚洲av免费高清在线观看| 国产老妇女一区| 美女内射精品一级片tv| 欧美日韩综合久久久久久| 偷拍熟女少妇极品色| 看片在线看免费视频| 国产成人福利小说| 看片在线看免费视频| 变态另类丝袜制服| 精品国内亚洲2022精品成人| 久久精品影院6| 精品久久久噜噜| 亚州av有码| 老师上课跳d突然被开到最大视频| 久久婷婷人人爽人人干人人爱| 成人亚洲精品av一区二区| 亚洲自拍偷在线| 日本撒尿小便嘘嘘汇集6| 亚洲精品日韩在线中文字幕 | 看黄色毛片网站| 久久久久久久午夜电影| 少妇的逼水好多| 亚洲内射少妇av| 免费观看精品视频网站| 久久久久久国产a免费观看| 可以在线观看毛片的网站| 亚洲av成人av| 一级毛片aaaaaa免费看小| 国产国拍精品亚洲av在线观看| 国产色爽女视频免费观看| 国产精品久久久久久精品电影| 精品99又大又爽又粗少妇毛片| 国产不卡一卡二| 国产精品久久久久久久久免| 一a级毛片在线观看| 蜜桃亚洲精品一区二区三区| 无遮挡黄片免费观看| 成人鲁丝片一二三区免费| 亚洲成人精品中文字幕电影| 蜜桃亚洲精品一区二区三区| 成人国产麻豆网| 中文字幕免费在线视频6| 精华霜和精华液先用哪个| 亚洲欧美精品综合久久99| 3wmmmm亚洲av在线观看| 亚洲久久久久久中文字幕| 日本 av在线| 欧美高清性xxxxhd video| 亚洲欧美成人综合另类久久久 | 亚洲精品456在线播放app| 少妇人妻一区二区三区视频| 一卡2卡三卡四卡精品乱码亚洲| 美女免费视频网站| 国产久久久一区二区三区| 日韩制服骚丝袜av| 久久久久久久亚洲中文字幕| 少妇的逼好多水| 日日摸夜夜添夜夜添小说| 国产精品三级大全| 欧美高清成人免费视频www| 综合色av麻豆| 一个人看视频在线观看www免费| 日本a在线网址| 免费看光身美女| а√天堂www在线а√下载| 日本熟妇午夜| 国产成人a∨麻豆精品| 国产精品一区二区三区四区免费观看 | 成人一区二区视频在线观看| 成人特级av手机在线观看| 亚洲欧美成人精品一区二区| а√天堂www在线а√下载| 婷婷亚洲欧美| 一本久久中文字幕| 99久久久亚洲精品蜜臀av| 精品人妻熟女av久视频| 国产精品福利在线免费观看| 午夜福利成人在线免费观看| 香蕉av资源在线| 一本精品99久久精品77| 长腿黑丝高跟| 波多野结衣巨乳人妻| 欧美性感艳星| 欧美不卡视频在线免费观看| 春色校园在线视频观看| 久久热精品热| 成年免费大片在线观看| 精品国产三级普通话版| 久久久a久久爽久久v久久| 十八禁网站免费在线| 精品久久久久久久人妻蜜臀av| 我要看日韩黄色一级片| 日韩精品中文字幕看吧| 高清毛片免费观看视频网站| 日韩欧美 国产精品| 国产中年淑女户外野战色| 色在线成人网| 别揉我奶头 嗯啊视频| 香蕉av资源在线| 黄色欧美视频在线观看| 我要看日韩黄色一级片| 国产精品一区二区三区四区免费观看 | 91在线观看av| 亚洲aⅴ乱码一区二区在线播放| 三级男女做爰猛烈吃奶摸视频| 久久国内精品自在自线图片| 日韩精品青青久久久久久| 99热这里只有是精品在线观看| 精华霜和精华液先用哪个| 日本在线视频免费播放| 日本精品一区二区三区蜜桃| 久久久欧美国产精品| 最近中文字幕高清免费大全6| 欧美不卡视频在线免费观看| 久久国内精品自在自线图片| 波多野结衣高清无吗| 干丝袜人妻中文字幕| 成人国产麻豆网| 国产又黄又爽又无遮挡在线| 丰满乱子伦码专区| 内射极品少妇av片p| 夜夜爽天天搞| 国产免费一级a男人的天堂| 韩国av在线不卡| eeuss影院久久| 亚洲国产精品久久男人天堂| АⅤ资源中文在线天堂| 成人永久免费在线观看视频| 嫩草影院入口| 成人毛片a级毛片在线播放| 免费在线观看成人毛片| 久久精品国产自在天天线| 一本精品99久久精品77| 亚洲无线在线观看| 日韩,欧美,国产一区二区三区 | 在线免费观看的www视频| 国产色婷婷99| 我要看日韩黄色一级片| 人人妻人人澡人人爽人人夜夜 | 亚洲精品一卡2卡三卡4卡5卡| 春色校园在线视频观看| 国产精品久久久久久亚洲av鲁大| 欧美成人精品欧美一级黄| 国产精品久久久久久精品电影| 黄色欧美视频在线观看| 免费大片18禁| av天堂中文字幕网| 亚洲人与动物交配视频| 一a级毛片在线观看| 久久久久久久亚洲中文字幕| av在线天堂中文字幕| 一个人看的www免费观看视频| 老司机影院成人| 日产精品乱码卡一卡2卡三| 精品久久久久久成人av| 99在线人妻在线中文字幕| 午夜视频国产福利| 免费人成视频x8x8入口观看| 国产女主播在线喷水免费视频网站 | 51国产日韩欧美| av在线蜜桃| 好男人在线观看高清免费视频| 日韩av不卡免费在线播放| 老司机午夜福利在线观看视频| 免费av毛片视频| 麻豆一二三区av精品| 狠狠狠狠99中文字幕| 亚洲中文字幕日韩| 99热这里只有是精品在线观看| 草草在线视频免费看| 欧美潮喷喷水| 男女之事视频高清在线观看| 欧美日韩综合久久久久久| 一进一出抽搐动态| 久久精品夜夜夜夜夜久久蜜豆| 欧美一级a爱片免费观看看| 乱人视频在线观看| 国产视频一区二区在线看| 在线免费观看不下载黄p国产| 久久精品久久久久久噜噜老黄 | 国产aⅴ精品一区二区三区波| 亚洲无线在线观看| .国产精品久久| 能在线免费观看的黄片| 最新中文字幕久久久久| 欧美最黄视频在线播放免费| 国产一区二区三区在线臀色熟女| 国产黄片美女视频| 狂野欧美白嫩少妇大欣赏| avwww免费| 亚洲丝袜综合中文字幕| 99国产精品一区二区蜜桃av| 91久久精品电影网| 女人被狂操c到高潮| 色噜噜av男人的天堂激情| 亚洲欧美精品综合久久99| 国产不卡一卡二| 尤物成人国产欧美一区二区三区| 久久精品影院6| 成人高潮视频无遮挡免费网站| 国模一区二区三区四区视频| 午夜福利在线在线| 午夜久久久久精精品| or卡值多少钱| 国产高清不卡午夜福利| 麻豆乱淫一区二区| 国产私拍福利视频在线观看| 久久久久免费精品人妻一区二区| 亚洲精品国产av成人精品 | 中文字幕人妻熟人妻熟丝袜美| 淫秽高清视频在线观看| 日本成人三级电影网站| 桃色一区二区三区在线观看| 美女黄网站色视频| 搞女人的毛片| 一本一本综合久久| 黄片wwwwww| 美女被艹到高潮喷水动态| 卡戴珊不雅视频在线播放| 12—13女人毛片做爰片一| 亚洲av电影不卡..在线观看| 麻豆国产97在线/欧美| 日韩精品中文字幕看吧| 一进一出抽搐动态| 国产成人91sexporn| 中国美白少妇内射xxxbb| 欧美xxxx黑人xx丫x性爽| 蜜臀久久99精品久久宅男| 国产大屁股一区二区在线视频| 美女xxoo啪啪120秒动态图| 插逼视频在线观看| 国产亚洲欧美98| 日本精品一区二区三区蜜桃| 久久久久国产网址| 精品人妻熟女av久视频| a级毛片a级免费在线| 精品少妇黑人巨大在线播放 | 最后的刺客免费高清国语| 2021天堂中文幕一二区在线观| 亚洲人成网站高清观看| 成人午夜高清在线视频| 中文字幕av成人在线电影| 99久久成人亚洲精品观看| 成人漫画全彩无遮挡| 亚洲国产高清在线一区二区三| 蜜桃亚洲精品一区二区三区| 变态另类丝袜制服| av福利片在线观看| 欧美丝袜亚洲另类| 国产精品国产三级国产av玫瑰| 日韩国内少妇激情av| 乱系列少妇在线播放| 久久这里只有精品中国| 搡老熟女国产l中国老女人| 男人和女人高潮做爰伦理| avwww免费| 在线播放无遮挡| 午夜福利视频1000在线观看| 18禁黄网站禁片免费观看直播| 欧美最黄视频在线播放免费| 精品久久久久久久末码| 午夜福利18| 啦啦啦韩国在线观看视频| 亚洲婷婷狠狠爱综合网| 亚洲自拍偷在线| av专区在线播放| 免费人成视频x8x8入口观看| 国产精品久久久久久亚洲av鲁大| 又黄又爽又刺激的免费视频.| 久久6这里有精品| 久久久午夜欧美精品| 观看免费一级毛片| 久久6这里有精品| 亚洲精品在线观看二区| 欧美一级a爱片免费观看看| 天天躁日日操中文字幕| 亚洲精品在线观看二区| 精品久久久噜噜| 美女内射精品一级片tv| 国产一区二区三区av在线 | 国产精品久久久久久亚洲av鲁大| 国产在线精品亚洲第一网站| av视频在线观看入口| 又粗又爽又猛毛片免费看| 久久人妻av系列| 欧美zozozo另类| 亚洲精品一区av在线观看| 免费人成在线观看视频色|