Identification of circulating apolipoprotein M as a new determinant of insulin sensitivity and relationship with adiponectin

doi:10.21203/rs.3.rs-3569355/v1

Download PDF

Article

Identification of circulating apolipoprotein M as a new determinant of insulin sensitivity and relationship with adiponectin

https://doi.org/10.21203/rs.3.rs-3569355/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background.

Adiponectin and apolipoprotein M (apoM) are adipokines indicatives of healthy adipose tissue and down-regulated with obesity. We compared circulating apoM with adiponectin regarding their relationship with metabolic parameters and insulin sensitivity and examined their gene expression patterns in adipocytes and in the adipose tissue.

Methods.

Circulating apoM and adiponectin were examined in 169 men with overweight in a cross-sectional study, and 13 patients with obesity during a surgery-induced slimming program. Correlations with clinical parameters including the insulin resistance index (HOMA-IR) were analyzed. Multiple regression analyses were performed on HOMA-IR. The APOM and ADIPOQ gene expression were measured in the adipose tissue from 267 individuals with obesity and a human adipocyte cell line.

Results.

Participants with type 2 diabetes had lower circulating adiponectin and apoM, while apoM was higher in individuals with dyslipidemia. Similar to adiponectin, apoM showed negative associations with HOMA-IR and hs-CRP (r>-0.2), and positive correlations with HDL markers (HDL-C and apoA-I, r > 0.3). Unlike adiponectin, apoM was positively associated with LDL markers (LDL-C and apoB100, r < 0.20) and negatively correlated with insulin and age (r>-0.2). The apoM was the sole negative determinant of HOMA-IR in multiple regression models, while adiponectin not contributing significantly. After surgery, the change in HOMA-IR was negatively associated with the change in circulating apoM (r=-0.71), but not with the change in adiponectin. The APOM and ADIPOQ gene expression positively correlated in adipose tissue (r > 0.44) as well as in adipocytes (r > 0.81). In adipocytes, APOM was downregulated by inflammatory factors and upregulated by adiponectin.

Conclusions.

The apoM rises as a new partner of adiponectin regarding insulin sensitivity. At the adipose tissue level, the adiponectin may be supported by apoM to promote a healthy adipose tissue.

Trial registration

NCT01277068, registered 13 January 2011; NCT02332434, registered 5 January 2015; and NCT00390637, registered 20 October 2006.

Biological sciences/Physiology/Metabolism/Fat metabolism

Biological sciences/Biochemistry/Hormones

Obesity is a global concern as excessive body fat is linked to metabolic syndrome, type 2 diabetes (T2D), and cardiovascular diseases [1]. Adipose tissue (AT) produces various factors, including numerous adipokines with local and broad systemic effects on whole-body homeostasis [2].

Most adipokines are secreted at higher levels with increasing fat and play a detrimental role in the development of metabolic disorders associated with obesity [2]. Conversely, few adipokines, like adiponectin, are inversely associated with body fat [2]. Adiponectin is an adipose-specific protein, encoded by ADIPOQ, which blood concentration decreases with obesity, metabolic syndrome, or T2D [3]. Adiponectin possesses anti-inflammatory, anti-diabetic, anti-atherogenic, and cardioprotective properties [4].

Recently, apolipoprotein M (apoM), predominantly produced by the liver and kidney, was found to be secreted by adipocytes [5]. Gene expression of APOM in AT is lower in individuals with high body fat, metabolic syndrome, or insulin resistance (IR) compared to lean healthy individuals [5]. Accordingly, blood levels of apoM are reduced in obesity, metabolic syndrome, and T2D [6–8]. Overall, apoM is an adipokine that exhibits a similar expression profile in AT and in the circulation to that of adiponectin [9]. Therefore, we hypothesized that both adiponectin and apoM could similarly predict changes in insulin sensitivity.

In this study, we conducted a comparative analysis of these two beneficial adipokines concerning obesity-related disorders, with a particular focus on glucose homeostasis. We investigated whether their blood concentrations were associated with lipid and glucose homeostasis parameters, and whether they could contribute to insulin sensitivity. Furthermore, we explored the relationship between apoM and adiponectin at the level of the adipocyte.

Study participants

The studies, referred as cohorts A, B and C, were conducted in accordance with the ethical principles of the Declaration of Helsinki. Before any procedure, all participants received oral information and signed a written informed consent form before they participated in any of the study procedures. Figure S1 illustrates the participants’ flowchart.

Cohort A: The protocol received approval from the local ethics committee (CCPPRB, Toulouse/Sud-Ouest, file #1-99-48, Feb 2000). The biological sample collection was registered as DC-2008-463 #1 to the Ministry of Research and to the Regional Health authority. Cohort A consisted of male participants selected from the Genetique et ENvironnement en Europe du Sud (GENES) cross-sectional case-control study. In this ancillary analysis, the patients with coronary artery disease (CAD) (referred to as cases) were age-matched to individuals without CAD (controls), and apoM was quantified using a multiplex liquid chromatography-tandem mass spectrometry (LC-MS/MS) method [10]. Subjects with missing data for fasting serum insulin and adiponectin levels were excluded, resulting in a final sample of 169 participants (mean age 60.6 years [SD, 8.1]), comprising 102 controls and 67 cases. Detailed procedures have been reported previously [11]. Anthropometric measurements, including fat mass assessment using Bioimpedance, and clinical variables were recorded. Venous blood was sampled after an overnight fast. Standardized interviews, conducted by a single physician, gathered information on environmental characteristics, medical history, and cardiometabolic risk factors. Alcohol consumption was calculated as the sum of different types of drinks. Physical activity was assessed using a standardized questionnaire and categorized into two levels: “high” if physical activity was performed for ≥ 20 min twice a week, or “low” if physical activity was performed for < 20 min once a week or less. Dyslipidemia was defined as treatment with drugs or fasting serum total cholesterol ≥ 2.50 g/L as described in [12]. Hypertension was defined as treatment with drugs or systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. T2D was defined as treatment with drugs or fasting blood glucose ≥ 7.0 mmol/L.

Cohort B

The approval was received by the Research Ethics Board of Aix-Marseille University (NCT01277068 and NCT02332434). Cohort B comprised 13 individuals with obesity of both sexes (77% women) with a mean age of 37.6 years [SD, 9.1], who underwent sleeve gastrectomy at the General and Endocrine Surgery Department of La Conception Hospital (Marseille, France), as previously described [13]. The clinical evaluation and laboratory tests were conducted at the Nutrition Department of La Conception Hospital. Patients were examined one month before (baseline) and one year after gastric sleeve surgery to reach steady weight loss. Each visit included measuring anthropometric parameters and blood sampling after an overnight fast [13].

Cohort C

This study is part of the Diet, Obesity, and Genes (DiOGenes) trial, which involved individuals with overweight or obesity recruited between 2005 and 2007 in 8 European countries [14]. The protocol received approval from the ethical boards of each of the 8 centers (NCT00390637). For the present study, a subgroup of 267 individuals (95 men and 172 women) with a mean age of 42.7 years [SD, 6.4]) was selected. Anthropometric measurements, blood sampling and subcutaneous abdominal AT needle biopsies were performed after an overnight fast. Clinical measures and subcutaneous abdominal AT samples were analysed at baseline (before any intervention), as described in [15].

Biochemical analyses

Fasting blood glucose, triglycerides (TG), cholesterol, high-density lipoprotein-cholesterol (HDL-C), γ-glutamyltransferase (γ-GT), and high-sensitivity C-reactive protein (hs-CRP) were assayed with enzymatic reagents on an automated analyzer (Hitachi 912 and Cobas® Analyzer, Roche Diagnostics). Low-density lipoprotein-cholesterol (LDL-C) was calculated using the Friedewald formula. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Insulin concentration was measured by electrochemiluminescence immunoassay (Advia Centaur, Siemens Healthineers, cohort A and Cobas® Analyzer, Roche Diagnostics, cohort B). IR was assessed using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) index, calculated as [fasting glucose (mM) x fasting insulin (mU/L)/22.5]. Adiponectin serum levels were measured using a specific enzyme-linked immunosorbent assay kit (Quantikine® Human Adiponectin, R&D Systems). Apolipoprotein A-I (apoA-I), apolipoprotein B100 (apoB100), and apolipoprotein C-III (apoC-III) were determined by immunoturbidimetric assay on an automated analyzer (Cobas® Analyzer, Roche Diagnostics, Cohort A) and by immunonephelometric assay (Roche Diagnostics) using a BN ProSpec analyzer (Siemens Healthineers). ApoM was measured by the LC-MS/MS method, as described previously [13].

Cell culture

Cells were incubated at 37°C in a humidified atmosphere containing 5% CO2. Human multipotent adipose-derived stem cells (hMADS) were cultivated as described in [5]. Briefly, hMADS cells were differentiated for 13 days in 50/50 DMEM 1g/L glucose (Sigma-Aldrich) and Ham’s F-12 (Lonza) medium, with 125 nM transferrin, 10 nM insulin, 0.2 nM triiodothyronine, 100 µM 3-isobutyl-1-methylxanthine (IBMX), 1 µM dexamethasone (Sigma-Aldrich), and 100 nM rosiglitazone (Cayman). ThP-1 monocytes were cultured in RPMI-1640 medium containing 10% FBS, 1 mM sodium pyruvate, 50 µM 2-mercaptoethanol (Invitrogen), and 36 mM glucose (Sigma-Aldrich). For differentiation into M0 macrophages, the cells were seeded in a serum-free, 2-mercaptoethanol-free RPMI medium containing 100 nM 12-phorbol-13-myristate acetate (Sigma-Aldrich) for 48h. Macrophages were then polarized for 3 days, inducing the M2-like anti-inflammatory phenotype with 20 ng/mL IL-4 (Sigma-Aldrich) or the M1-like pro-inflammatory phenotype with 2 ng/mL Escherichia coli lipopolysaccharide and 10 ng/mL IFNγ (Sigma-Aldrich).

Cell treatment

After 10 days of differentiation, the hMADS cells were treated with recombinant globular adiponectin (PeproTech), or CRP (Merck Millipore) or exposed to 50/50 conditioned media from M1-like or M2-like polarized ThP-1 for 72 hours. The cells were transduced with AAVs vectors (serotype 8) encoding either apoM or mCherry (designed and produced by the Vectorology platform of the Cancerology Research Center of Toulouse, Inserm UMR1037) for 72 hours, as described in [16]. Subsequently, cells were lysed using RLT buffer (Qiagen) containing 1% 2-mercaptoethanol (Sigma-Aldrich), flash frozen and stored at -80°C.

Gene expression

RNA was extracted using a Rneasy mini kit (Qiagen) following manufacturer’s instructions. Total RNA was reverse transcribed using Superscript II reverse transcriptase (Invitrogen). Real-time PCR was performed using Taqman probes or SyberGreen primers assays with a QuantStudio 5 Real-Time PCR system (Applied Biosystems). For the AT samples, expression of APOM (Hs00219533_m1) or ADIPOQ (Hs00605917_m1) data were normalized to PUM1 (Hs00472881_m1). For the hMADS cells, expression of APOM or ADIPOQ (forward GCAGAGATGGCACCCCTG, reverse GGTTTCACCGATGTCTCCCTTA) were normalized to LRP10 (Hs01047362_m1).

Statistical analyses

The categorical parameters are expressed as numbers (%) and the quantitative parameters as means ± the standard deviation (SD). Shapiro–Wilks test was used to examine the normality of distribution of residuals and Levene’s test to determine the homogeneity of the variances. When comparing cases to controls or baseline versus after surgery, the mean values of the quantitative variables were analyzed by Student’s t-test. When the basic assumptions of Student’s t-test were not satisfied, the data were logarithmically transformed or subjected to a Wilcoxon–Mann–Whitney test. Associations of apoM, adiponectin, and HOMA-IR with anthropometric parameters, biological markers, and environmental factors were tested using Spearman’s rank correlations with P-value adjustment using false discovery rate. For regression analyses of HOMA-IR, a backward stepwise selection was used. The F-statistics for a variable to stay in the model had to be significant at P < 0.10. Variables were maintained in the model when the F-statistic was significant at P < 0.05. For each quantitative variable, regression analyses were performed with polynomial models to look for possible nonlinear relationships with dependent variables. Lack of multicollinearity was assessed by examining the variance inflation factors in the final models.

Circulating adiponectin versus apoM relationship with cardiometabolic status

The clinical and biological characteristics of cohort A are presented in Table S1. Cohort A comprised overweight men (BMI, 26.7 kg/m², [SD, 3.5]), of who 39.6% were patients with CAD (cases).

Compared with the control participants, the CAD patients had less physical activity and were diagnosed or treated more often for hypertension, dyslipidemia, or T2D, with a larger proportion suffering from T2D (25.4% versus 6.9% in the controls). The body fat mass percentage and waist circumference were also higher in cases than in the controls. Among the biological markers, the levels of total cholesterol and LDL-C were lower in cases, probably reflecting the effects of lipid-lowering drugs in patients. However, individuals with CAD displayed higher levels of TG, hs-CRP, and γ-GT. HDL markers (HDL-C and apoA-I) were lower. Finally, the cases exhibited higher HOMA-IR and lower adiponectin levels than the control participants, while the apoM levels were similar between the two groups.

Blood levels of apoM and adiponectin were then considered according to other disease conditions, including T2D, dyslipidemia, and hypertension (Table S2). Adiponectin and apoM levels were lower in participants diagnosed or treated for T2D. Unlike adiponectin, apoM levels were lower in participants with hypertension, while they were higher in subjects with dyslipidemia than in the individuals without these conditions. These observations were weakened when only the treatment conditions were considered (Table S3), except for adiponectin, for which the levels were lower in participants treated for dyslipidemia and T2D.

Circulating apoM is a negative determinant of insulin resistance

Correlations between circulating levels of apoM and biological and clinical parameters relative to cardiovascular and T2D risk factors were investigated in the entire study population (cohort A). These correlations were compared with equivalent correlation for adiponectin and HOMA-IR (Table 1).

Table 1

Spearman correlation coefficients of adiponectin, apoM and HOMA-IR with anthropometric parameters, biological markers and environmental factors in cohort A
	Adiponectin (µg/mL)	ApoM (mg/L)	HOMA-IR
Adiponectin	1	-	-
ApoM	-0.01 (-0.17;0.14)	1	-
HOMA-IR	-0.19 (-0.33;-0.04)*	-0.29 (-0.42;-0.14)***	1
Insulin	-0,17 (-0.32;-0.02)	-0.31 (-0.44;-0.161)***	-
Glucose	-0.06 (-0.21;0.09)	-0.085 (-0.234;0.068)	-
BMI	-0.21 (-0.35;-0.06)*	-0.05 (-0.20;0.10)	0.43 (0.30;0.55)***
Waist circumference	-0.25 (-0.38;-0.10)**	-0.11 (-0.29;0.04)	0.49 (0.36;0.60)***
Fat mass percent	-0.09 (-0.25;0.07)	-0.26 (-0.40;-0.10)**	0.42 (0.28;0.54)***
Triglycerides	-0.30 (-0.43;-0.15)***	-0.01 (-0.16;0.15)	0,41 (0.28;0.53)***
Total cholesterol	0.13 (-0.03;0.27)	0.36 (0.22;0.48)***	-0.05 (-0.20;0.10)
LDL-C	0.09 (0.07;0.23)	0.27 (0.12;0.40)**	-0.05 (-0.20;0.10)
HDL-C	0.41 (0.27;0.53)***	0.32 (0.18;0.45)***	-0.34 (-0.47;-0.20)***
ApoA-I	0.34 (0.19;0.46)***	0.32 (0.17;0.45)***	-0.26 (-0.40;-0.11)***
ApoB100	-0.06 (-0.21;0.09)	0.20 (0.04;0.34)**	0.14 (-0.01;0.29)
ApoC-III	0.06 (-0.03;0.21)	0.19 (0.04;0.34)*	0.28 (0.13;0.41)***
hs-CRP	-0.22 (-0.36;-0.07)*	-0,28 (-0.42;-0.13)***	0,30 (0,15;0,43)***
γ-GT	-0.14 (-0.29;0.01)	-0.04 (-0.19;0.11)	0.41 (0.27;0.53)***
Age	0.09 (-0.06;0.24)	-0.25 (-0.38;-0.11)**	0.08 (-0.07;0.23)
Alcohol	-0.01 (-0.16;0.14)	0.19 (0.04;0.34)*	-0.03 (-0.18;0.12)
Smoking	0.04 (-0.11;0.19)	0.02 (-0.13;0.17)	0.05 (-0.11;0.20)
Physical activity	0.05 (-0.10;0.20)	0.01 (-0.15;0.16)	-0.26 (-0.39;-0.11)***
Systolic blood pressure	-0.03 (-0.18;0.13)	-0.12 (-0.27;0.03)	0.07 (-0.08;0.22)
Diastolic blood pressure	-0.03 (-0.18;0.12)	0.03 (-0.12;0.19)	0.07 (-0.08;0.22)
Resting heart rate	0.11 (-0.06;0.25)	-0.15 (-0.29;0.01)	0.23 (0.08;0.37)**
Spearman rank correlation (95% confidence interval), n = 169.
FDR < 0.05, * FDR < 0.01, *** FDR < 0.001. FDR < 0.05 are indicated in bold.
ApoA-I: apolipoprotein A-I; ApoB-100: apolipoprotein B100; ApoC-III: apolipoprotein C-III; BMI, body mass index; FDR, false discovery rate; hs-CRP, high-sensitivity C-reactive protein; γ-GT, gamma glutamyl transferase; HDL-C, high-density lipoprotein-cholesterol; HOMA-IR: Homeostasis Model Assessment of Insulin Resistance; LDL-C, low-density lipoprotein-cholesterol.

The blood level of apoM did not show any significant correlation with that of adiponectin. However, similar to adiponectin, apoM exhibited a negative association with hs-CRP (r=-0.28) and HOMA-IR (r=-0.29), while it was positively associated with HDL markers (r = 0.32, for both HDL-C and apoA-I). Unlike adiponectin, apoM did not correlate with TG, but it was positively associated with total cholesterol (r = 0.36), LDL markers (LDL-C and apoB100, r = 0.27; and r = 0.20, respectively), and apoC-III (r = 0.19). No association was observed between apoM and cardiac functions (systolic blood pressure, heart rate), or environmental factors (smoking, physical activity), except for a positive correlation between apoM and alcohol consumption (r = 0.19). Of note, apoM was negatively associated with fat mass (r=-0.26) and age (r=-0.28).

In addition to the expected negative correlations with apoM and adiponectin, HOMA-IR displayed negative correlations with HDL markers (apoA-I and HDL-C) and physical activity and positive correlations with adiposity markers (BMI, fat mass, and waist circumference), TG, apoC-III, hs-CRP, and γ-GT (Table 1).

To further identify the determinants of IR among these variables associated with HOMA-IR, we conducted a multiple regression analysis with HOMA-IR as the dependent variable. The model included apoM and adiponectin as potent explanatory variables, along with BMI, waist circumference, physical activity, TG, HDL-C, hs-CRP, γ-GT, apoC-III, apoB100, T2D, dyslipidemia, hypertension, and case-control status. This model explained 39% of the variability in HOMA-IR and revealed that diabetes status and four variables were determinants of HOMA-IR variability, which included apoM but not adiponectin (Table 2). Among the identified determinants, waist circumference and γ-GT showed the strongest positive associations with HOMA-IR, explaining 13.6% and 9.6% of the variability, respectively. In contrast, apoM displayed an inverse association, accounting for 5.6% of the variability in HOMA-IR. Notably, no significant interaction between apoM and case-control status was observed (P = 0.58). Furthermore, even after removing apoM from the set of variables at entry, adiponectin still did not contribute to the variability of HOMA-IR (data not shown).

Table 2

Multiple linear regression analysis on HOMA-IR in cohort A
R² = 39
	β estimate	SE	P-value	%^b
ApoM	-0.133	0.045	0.0035	5.6
Waist circumference^a	0.177	0.046	0.0002	13.6
γ-GT^a	0.181	0.046	0.0001	9.6
ApoC-III^a	1.421	0.044	0.0016	4.5
Diabetes	0.353	0.132	0.0084	2.8
Variables at entry: Adiponectin, apoC-III, apoB-100, apoM, BMI, γ-GT, hs-CRP, HDL-C, physical activity, triglycerides, waist circumference, diabetes (fasting blood glucose ≥ 7.0 mmol/L or treatment vs. no), dyslipidemia (total cholesterol ≥ 2.50 g/L or treatment), hypertension (systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or treatment) and case-control status. Continuous variables were standardised. β estimates were given for one standard deviation variation.
^aLog-transformed data; ^bPercentage of variance explained.
ApoB-100: apolipoprotein B100; ApoC-III: apolipoprotein C-III; ApoM: apolipoprotein M; BMI: body mass index; γ-GT: gamma-glutamyltransferase; HDL-C: high-density lipoprotein cholesterol; hs-CRP: high-sensitivity C-Reactive Protein; HOMA-IR, Homeostasis Model Assessment of Insulin Resistance; LDL-C: low-density lipoprotein cholesterol.

Increased circulating apoM is closely related to insulin resistance relief after sleeve gastrectomy

To further study the association between apoM and IR, we examined the changes in circulating apoM after sleeve gastrectomy in patients with obesity and analyzed their correlation with the improvement in HOMA-IR. Anthropometric and biochemical characteristics of these patients at baseline (i.e., before gastric sleeve surgery) and one year after surgery are presented in Table S4. One year after surgery, all individuals showed a decrease in adiposity markers (BMI, fat mass, and waist circumference) and displayed an improved lipid profile, including reduced atherogenic lipids (TG and LDL-C) and increased HDL markers (HDL-C and apoA-I). Additionally, there was a significant decrease in HOMA-IR (from 4.26, [SD, 1.49] to 1.39, [SD, 0.69]) and an increase in adiponectin levels (from 5.54 µg/L, [SD, 1.61] to 10.47 µg/L [SD, 4.07]). Circulating levels of apoM were not significantly changed (Table S4); however, we found a strong inverse relationship between the changes in HOMA-IR and changes in circulating apoM (r=-0.71), while no significant association was observed with changes in adiponectin (Fig. 2). Of note, there was a trend of a positive correlation between changes in circulating apoM and changes in adiponectin (r = 0.57, P = 0.08, not shown).

Positive association between ADIPOQ and APOM mRNA level in AT

We compared the gene expression of adiponectin and apoM in human subcutaneous AT from individuals with overweight or obesity (cohort C, Fig. 2A and Table S5). ADIPOQ gene expression in AT was higher than APOM gene expression and both were positively correlated (Fig. 2A, r = 0.441). Additionally, HOMA-IR negatively correlated with AT expression of ADIPOQ (r = 0.147, Fig. 2B), and APOM gene expression in AT (r=-0.1226, Fig. 2C).

Inflammatory factors downregulate ADIPOQ and APOM expression in adipocytes

Due to the close association of IR with AT inflammation, we aimed to mimic the impact of inflammatory conditions on ADIPOQ and APOM expression in adipocytes. We treated hMADS adipocytes with conditioned media from pro-inflammatory M1-like or anti-inflammatory M2-like polarized ThP-1 macrophages. The former media led to down-regulation of both ADIPOQ and APOM gene expressions (Fig. 3A). A strong correlation between ADIPOQ and APOM gene expression was observed in these adipocytes (r = 0.91, Fig. 3B). Similarly, a treatment with CRP also downregulated the expression of ADIPOQ and APOM genes in hMADS cells (Fig. 3C), while the positive correlation between ADIPOQ and APOM mRNA levels persisted under this condition (r = 0.82, Fig. 3D).

Adiponectin promotes APOM expression in adipocytes

Adipocytes express specific adiponectin receptors, whereas apoM lacks known specific receptor. To further investigate the relationship between the two adipokines, we examined the effect of adiponectin on APOM gene expression. Treating hMADS adipocytes with increasing concentrations of adiponectin resulted in a dose dependent increase in APOM expression, with a mean 1.6-fold [SD, 0.9]) rise at 1µM adiponectin (Fig. 4).

Here, we explored the relationship between the circulating concentrations of two beneficial adipokines, namely adiponectin and apoM, and cardiometabolic parameters in high-risk populations. We also examined the relationship between the two adipokines at the adipose level.

Firstly, despite the strong correlation of APOM and ADIPOQ gene expression in adipocytes and AT, the apoM concentration did not correlate with that of adiponectin, as a hallmark of their distinct tissue origin. While their respective circulating levels were lower in participants with T2D, their level may still reflect distinct cardiometabolic states.

As anticipated, our study validated previously reported associations between blood levels of adiponectin and lipids [17, 18]. Adiponectin displayed an inverse correlation with TG and a positive association with HDL markers such as HDL-C and apoA-I. In contrast, the circulating apoM level was not associated with plasma TG but displayed a positive correlation with both anti-atherogenic HDL (HDL-C, apoA-I) and atherogenic LDL (LDL-C, apoB100) markers. This association of apoM with both HDL and LDL markers has been reported previously [6, 19] and is likely due to the fact that apoM is transported by both HDL and LDL rather than having a specific role in lipoprotein metabolism [19]. However, it is important to note that apoM is predominantly transported by HDL, and a recent report has shown that low plasma apoM is independently associated with heart failure [20]. This suggest that apoM may play a role in some HDL cardioprotective functions [9].

An expected reduced level of adiponectin was found in patients with CAD [17]. In humans, the ADIPOQ gene, located on chromosome 3q27, contains polymorphisms that influence the level and activity of adiponectin, SNP 276 (G > T) and I164T. The former is associated with obesity, IR, and T2D [21], while the latter is a missense mutation associated with metabolic syndrome and CAD [22]. There is consistent evidence of an inverse relationship between plasma adiponectin and metabolic syndrome, low-grade inflammation, T2D, and cardiovascular risk [23–25]. Of note, circulating adiponectin has paradoxically been associated with increased all-cause and cardiovascular mortality [26, 27]. Adiponectin resistance in vessels might be a clue to explain this unexpected outcome on the prognostic value of circulating adiponectin [27].

ApoM concentration was found to be higher in participants with dyslipidemia, consistent with previous studies [8]. This observation aligns with the previously mentioned positive association of apoM with LDL-C. Interestingly, the relationship between apoM and dyslipidemia status was no longer observed when only the treated patients (the majority of whom were on statin treatment) were considered among the subjects with dyslipidemia. This is consistent with the effect of statins in lowering apoM levels [6]. Additionally, apoM levels were lower in subjects with hypertension, in accordance with its role in reducing blood pressure in hypertensive mice [28].

Similarly to APOM expression in AT [5] and consistent with previous reports [18, 20], circulating apoM was found to be negatively associated with body fat and hs-CRP level, a biomarker of systemic inflammation. Additionally, our in vitro studies on adipocytes indicate that conditions mimicking an inflammatory context, including treatments with conditioned media from pro-inflammatory macrophages or CRP, down-regulate APOM gene expression. This is in line with our previous study reporting a negative effect of TNFα on APOM gene expression in adipocytes [5]. This suggests that a low circulating apoM may serve as a potential marker of systemic inflammation and dysfunctional AT.

While adiponectin is a key adipokine in preventing metabolic syndrome and associated pathologies, much less is known about apoM, especially regarding its expression in adipocytes. ApoM is distributed in various tissues, with primary expression in hepatocytes and proximal tubular kidney cells, and to a lesser extent in endothelial cells and adipocytes [9, 29]. The human APOM gene is located on chromosome 6p21.33. There is evidence that T-778C polymorphism in the proximal promoter region of the APOM gene confers susceptibility to the development of T2D [30]. Another variant, rs1266078, resulted in an 11% lower circulating apoM, but no association was found with the risk of T2D [31]. Similar to adiponectin, we found a lower level of apoM in participants with T2D and an inverse association with IR. Surprisingly, in a multiple linear regression model, the apoM level in cohort A was the only negative determinant of HOMA-IR, independently of coronary status, while adiponectin did not contribute to the variability of HOMA-IR. This indicates that in men with overweight, blood apoM has a stronger association to HOMA-IR than circulating adiponectin.

To investigate the relationship between these two adipokines and IR, we examined whether weight-reduction surgery in patients with obesity (cohort B) could influence the levels of apoM and its association with IR. As reported elsewhere, patients with obesity (cohort B, baseline) exhibited lower circulating levels of adiponectin [32] and apoM [33] compared to individuals with overweight (cohort A), consistent with the previously mentioned negative association of plasma adiponectin and apoM with fat mass. Bariatric surgery offers an efficient approach for managing obesity, with various surgical procedures available [34]. Among these, sleeve gastrectomy accounts for 55.4% of all bariatric surgeries thanks to its minimal invasiveness [35] and has been shown to resolve IR and T2D [36]. In our study, one year after sleeve gastrectomy, all patients exhibited a HOMA-IR below 2.5 and a two-fold increase in adiponectin concentration. The minor increase (+ 13%) in apoM levels did not reach statistical significance (P > 0.1). Circulating apoM has been reported to be filtered then taken up from urine by tubular kidney cells via the megalin receptor [37]. Given that people with class 3 obesity (BMI > 40 kg/m²) often present kidney disease that could be alleviated after sleeve gastrectomy, one might expect an increase in plasma apoM levels associated with improved renal function. However, the patients of Cohort B had mild CKD as measured by eGFR, and no significant change in eGFR was found, in line with a recent report [38]. Conversely, improvement in insulin sensitivity following surgery was strongly associated with increase in circulating apoM. This reciprocal correlation between apoM and HOMA-IR suggests that increased circulating apoM could improve glucose homeostasis by reducing IR. This provides additional evidence that, in complement to adiponectin, apoM may be an additional beneficial factor of glycaemic control.

Next, we examined the relationship between adiponectin and apoM at the AT level. For the first time, we reported here a strong positive correlation between ADIPOQ and APOM gene expression in human AT and adipocytes, independently of the inflammatory context. Interestingly, adiponectin was found to promote the expression of APOM in adipocytes. Although further studies are needed to identify the pathways regulating apoM expression and secretion in adipocytes, our observations suggest a positive feedback loop between adiponectin and apoM that controls local AT inflammation and might help prevent insulin sensitivity decline. Considering the importance of AT inflammation in systemic IR [4], our study suggests that the adipose apoM might play a noticeable role in maintaining a healthy AT environment and promoting systemic insulin sensitivity, alongside with adiponectin.

Several limitations of this study warrant mention. Firstly, we focused solely on one form of circulating adiponectin. Considering that the high molecular weight isoform is considered as the active form [32], further investigations to explore isoform specificity would be necessary. Secondly, additional studies are required to determine if AT is a significant site of apoM production and to understand the mechanism through which apoM may contribute to preventing IR.

In conclusion, the present study examined for the first time the relative contributions of adiponectin and apoM regarding insulin sensitivity. We found a close relationship between adipose apoM and adiponectin, and that plasma apoM, but not adiponectin, was a negative explanatory variable of HOMA-IR, independently of coronary status. The stronger relationship of insulin sensitivity with apoM rather than adiponectin was unexpected. This establishes apoM as a novel factor associated to insulin sensitivity.

Acknowledgments

We are grateful to all individuals participating in this study. This research was funded by the Region Occitanie Pyrénées-Méditerranée (GRAINE HEPATOCARE, Reference number: no. 19014226), Inserm, Toulouse 3 University, and grants from Société Française de Nutrition. L.F. was supported by a Ph.D. fellowship from Region Occitanie Pyrénées-Méditerranée and Inserm.

Author Contributions

Conceptualization, L.O.M. and N.V.; methodology, LO.M., L.F., G.C., J.F., B.P., E.E.B, R.V., M.C., and N.V.; formal analysis, J.B.R. and M.M.; data curation, L.F., J.B.R., J.R., and M.C.; draft preparation, L.O.M. and N.V.; review and editing, L.F., J.B.R., M.M., G.C., J.R, P.S.R., J.F.; B.P.; C.M.; R.V.; M.C., E.E.B, L.O.M, and N.V.; supervision, L.O.M. and N.V.; funding acquisition, L.O.M. and N.V..

Competing Interests

The authors have no conflicts of interest to declare.

Data Availability

The datasets are available from the corresponding authors on reasonable request.

Longo M, Zatterale F, Naderi J, Parrillo L, Formisano P, Raciti GA et al. Adipose Tissue Dysfunction as Determinant of Obesity-Associated Metabolic Complications. International journal of molecular sciences 2019; 20(9).
Scheja L, Heeren J. The endocrine function of adipose tissues in health and cardiometabolic disease. Nature reviews. Endocrinology 2019; 15(9): 507–524.
Maeda N, Funahashi T, Matsuzawa Y, Shimomura I. Adiponectin, a unique adipocyte-derived factor beyond hormones. Atherosclerosis 2020; 292: 1–9.
Li X, Zhang D, Vatner DF, Goedeke L, Hirabara SM, Zhang Y et al. Mechanisms by which adiponectin reverses high fat diet-induced insulin resistance in mice. Proceedings of the National Academy of Sciences of the United States of America 2020; 117(51): 32584–32593.
Sramkova V, Berend S, Siklova M, Caspar-Bauguil S, Carayol J, Bonnel S et al. Apolipoprotein M: a novel adipokine decreasing with obesity and upregulated by calorie restriction. The American journal of clinical nutrition 2019; 109(6): 1499–1510.
Kappelle PJ, Ahnstrom J, Dikkeschei BD, de Vries R, Sluiter WJ, Wolffenbuttel BH et al. Plasma apolipoprotein M responses to statin and fibrate administration in type 2 diabetes mellitus. Atherosclerosis 2010; 213(1): 247–250.
Li T, Yang L, Zhao S, Zhang S. Correlation Between Apolipoprotein M and Inflammatory Factors in Obese Patients. Medical science monitor: international medical journal of experimental and clinical research 2018; 24: 5698–5703.
Zhang P, Gao J, Pu C, Feng G, Wang L, Huang L et al. Effects of hyperlipidaemia on plasma apolipoprotein M levels in patients with type 2 diabetes mellitus: an independent case-control study. Lipids in health and disease 2016; 15(1): 158.
Tavernier G, Caspar-Bauguil S, Viguerie N. Apolipoprotein M: new connections with diet, adipose tissue and metabolic syndrome. Current opinion in lipidology 2020; 31(1): 8–14.
Genoux A, Duparc T, Ruidavets JB, Ingueneau C, Najib S, Ferrieres J et al. A reference measurement of circulating ATPase inhibitory factor 1 (IF1) in humans by LC-MS/MS: Comparison with conventional ELISA. Talanta 2020; 219: 121300.
Genoux A, Ruidavets JB, Ferrieres J, Combes G, Lichtenstein L, Pons V et al. Serum IF1 concentration is independently associated to HDL levels and to coronary heart disease: the GENES study. Journal of lipid research 2013; 54(9): 2550–2558.
Roeykens J, Rogers R, Meeusen R, Magnus L, Borms J, de Meirleir K. Validity and reliability in a Flemish population of the WHO-MONICA Optional Study of Physical Activity Questionnaire. Med Sci Sports Exerc 1998; 30(7): 1071–1075.
Poirier J, Cloteau C, Aguesse A, Billot X, Thevenot E, Krempf M et al. Bariatric Surgery Improves the Atherogenic Profile of Circulating Methylarginines in Obese Patients: Results from a Pilot Study. Metabolites 2021; 11(11).
Larsen TM, Dalskov SM, van Baak M, Jebb SA, Papadaki A, Pfeiffer AF et al. Diets with high or low protein content and glycemic index for weight-loss maintenance. The New England journal of medicine 2010; 363(22): 2102–2113.
Bolton J, Montastier E, Carayol J, Bonnel S, Mir L, Marques MA et al. Molecular Biomarkers for Weight Control in Obese Individuals Subjected to a Multiphase Dietary Intervention. The Journal of clinical endocrinology and metabolism 2017; 102(8): 2751–2761.
Jimenez V, Munoz S, Casana E, Mallol C, Elias I, Jambrina C et al. In vivo adeno-associated viral vector-mediated genetic engineering of white and brown adipose tissue in adult mice. Diabetes 2013; 62(12): 4012–4022.
Hascoet S, Elbaz M, Bongard V, Bouisset F, Verdier C, Vindis C et al. Adiponectin and long-term mortality in coronary artery disease participants and controls. Arteriosclerosis, thrombosis, and vascular biology 2013; 33(1): e19-29.
Schulze MB, Rimm EB, Shai I, Rifai N, Hu FB. Relationship between adiponectin and glycemic control, blood lipids, and inflammatory markers in men with type 2 diabetes. Diabetes care 2004; 27(7): 1680–1687.
Christoffersen C, Benn M, Christensen PM, Gordts P, Roebroek AJM, Frikke-Schmidt R et al. The plasma concentration of HDL-associated apoM is influenced by LDL receptor-mediated clearance of apoB-containing particles. Journal of lipid research 2012; 53(10): 2198–2204.
Chirinos JA, Zhao L, Jia Y, Frej C, Adamo L, Mann D et al. Reduced Apolipoprotein M and Adverse Outcomes Across the Spectrum of Human Heart Failure. Circulation 2020; 141(18): 1463–1476.
Vasseur F, Helbecque N, Dina C, Lobbens S, Delannoy V, Gaget S et al. Single-nucleotide polymorphism haplotypes in the both proximal promoter and exon 3 of the APM1 gene modulate adipocyte-secreted adiponectin hormone levels and contribute to the genetic risk for type 2 diabetes in French Caucasians. Hum Mol Genet 2002; 11(21): 2607–2614.
Ohashi K, Ouchi N, Kihara S, Funahashi T, Nakamura T, Sumitsuji S et al. Adiponectin I164T mutation is associated with the metabolic syndrome and coronary artery disease. Journal of the American College of Cardiology 2004; 43(7): 1195–1200.
Duncan BB, Schmidt MI, Pankow JS, Bang H, Couper D, Ballantyne CM et al. Adiponectin and the development of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes 2004; 53(9): 2473–2478.
Mojiminiyi OA, Abdella NA, Al Arouj M, Ben Nakhi A. Adiponectin, insulin resistance and clinical expression of the metabolic syndrome in patients with Type 2 diabetes. Int J Obes (Lond) 2007; 31(2): 213–220.
Okamoto Y, Kihara S, Funahashi T, Matsuzawa Y, Libby P. Adiponectin: a key adipocytokine in metabolic syndrome. Clin Sci (Lond) 2006; 110(3): 267–278.
Beatty AL, Zhang MH, Ku IA, Na B, Schiller NB, Whooley MA. Adiponectin is associated with increased mortality and heart failure in patients with stable ischemic heart disease: data from the Heart and Soul Study. Atherosclerosis 2012; 220(2): 587–592.
Wang Y, Ma XL, Lau WB. Cardiovascular Adiponectin Resistance: The Critical Role of Adiponectin Receptor Modification. Trends in endocrinology and metabolism: TEM 2017; 28(7): 519–530.
Swendeman SL, Xiong Y, Cantalupo A, Yuan H, Burg N, Hisano Y et al. An engineered S1P chaperone attenuates hypertension and ischemic injury. Science signaling 2017; 10(492).
Bisgaard LS, Christoffersen C. Apolipoprotein M/sphingosine-1-phosphate: novel effects on lipids, inflammation and kidney biology. Current opinion in lipidology 2019; 30(3): 212–217.
Niu N, Zhu X, Liu Y, Du T, Wang X, Chen D et al. Single nucleotide polymorphisms in the proximal promoter region of apolipoprotein M gene (apoM) confer the susceptibility to development of type 2 diabetes in Han Chinese. Diabetes/metabolism research and reviews 2007; 23(1): 21–25.
Liu D, Pan JM, Pei X, Li JS. Interaction Between Apolipoprotein M Gene Single-Nucleotide Polymorphisms and Obesity and its Effect on Type 2 Diabetes Mellitus Susceptibility. Scientific reports 2020; 10(1): 7859.
Wang ZV, Scherer PE. Adiponectin, the past two decades. Journal of molecular cell biology 2016; 8(2): 93–100.
Ooi EM, Watts GF, Chan DC, Nielsen LB, Plomgaard P, Dahlback B et al. Association of apolipoprotein M with high-density lipoprotein kinetics in overweight-obese men. Atherosclerosis 2010; 210(1): 326–330.
Breen DM, Rasmussen BA, Kokorovic A, Wang R, Cheung GW, Lam TK. Jejunal nutrient sensing is required for duodenal-jejunal bypass surgery to rapidly lower glucose concentrations in uncontrolled diabetes. Nature medicine 2012; 18(6): 950–955.
Angrisani L, Santonicola A, Iovino P, Ramos A, Shikora S, Kow L. Bariatric Surgery Survey 2018: Similarities and Disparities Among the 5 IFSO Chapters. Obes Surg 2021; 31(5): 1937–1948.
Salman AA, Salman MA, Marie MA, Rabiee A, Helmy MY, Tourky MS et al. Factors associated with resolution of type-2 diabetes mellitus after sleeve gastrectomy in obese adults. Scientific reports 2021; 11(1): 6002.
Bisgaard LS, Christoffersen C. The apoM/S1P Complex-A Mediator in Kidney Biology and Disease? Front Med (Lausanne) 2021; 8: 754490.
Kassam AF, Taylor ME, Morris MC, Watkins BM, Thompson JR, Schauer DP et al. The impact of sleeve gastrectomy on renal function in patients with chronic kidney disease varies with severity of renal insufficiency. Surg Obes Relat Dis 2020; 16(5): 607–613.

There is NO conflict of interest to disclose

FrancesIJOSupplementaryinformation.docx

Download PDF

Editorial decision: revise
13 Dec, 2023
Review #2 received at journal
26 Nov, 2023
Review #1 received at journal
25 Nov, 2023
Reviewer #2 agreed at journal
13 Nov, 2023
Reviewer #1 agreed at journal
13 Nov, 2023
Reviewers invited by journal
12 Nov, 2023
Submission checks completed at journal
07 Nov, 2023
First submitted to journal
06 Nov, 2023
Editor assigned by journal
06 Nov, 2023

You are reading this latest preprint version

Identification of circulating apolipoprotein M as a new determinant of insulin sensitivity and relationship with adiponectin

Status:

Version 1

Abstract

Figures

Introduction

Methods

Study participants

Biochemical analyses

Cell culture

Cell treatment

Gene expression

Statistical analyses

Results

Circulating adiponectin versus apoM relationship with cardiometabolic status

Circulating apoM is a negative determinant of insulin resistance

Increased circulating apoM is closely related to insulin resistance relief after sleeve gastrectomy

Positive association between ADIPOQ and APOM mRNA level in AT

Inflammatory factors downregulate ADIPOQ and APOM expression in adipocytes

Adiponectin promotes APOM expression in adipocytes

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1