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Roux-en-Y gastric bypass, but not sleeve gastrectomy,
decreases plasma PCSK9 levels in morbidly obese
patients
C. Blanchard, S. Ledoux, A. Verhaegen, M. Wargny, E. Letessier, A.
Stepanian, N. Huten, D. Jacobi, M. Le Bras, Michel Krempf, et al.
To cite this version:
C. Blanchard, S. Ledoux, A. Verhaegen, M. Wargny, E. Letessier, et al.. Roux-en-Y gastric bypass, but not sleeve gastrectomy, decreases plasma PCSK9 levels in morbidly obese patients. Journal of Diabetes & Metabolism, OMICS International, 2020, 46 (6), pp.480-487. �10.1016/j.diabet.2020.01.003�. �hal-03013255�
1
Roux en Y Gastric Bypass, but not sleeve gastrectomy, decreases plasma PCSK9 levels in morbidly obese patients
Claire Blancharda,b, MD, PhD ; Séverine Ledouxc* , MD ; Ann Verhaegen, MDd*, Matthieu Wargnya,e, MD, Eric Letessierb, MD ; Alain Stepanianf, MD ; Noel Huteng, MD, David Jacobia,g, MD, PhD, Michel Krempfe,h, MD, PhD ; Maëlle Le Brase, MD ; Marie Perrocheau Guillouchee, MD ; Lucie Arnauda, MD ; Matthieu Pichelina,e, Pharm D ; Luc Van Gaald,MD, PhD, Bertrand Carioua,e, MD, PhD*, Cedric Le Maya, PhD*
a Université de Nantes, CNRS, INSERM, l’institut du thorax, F-44000 Nantes, France b Service de Clinique de Chirurgie Digestive et Endocrinienne, CHU de Nantes, France
c Service des Explorations Fonctionnelles, Centre Intégré Nord Francilien de prise en charge
de l’Obésité (CINFO), Hôpital Louis Mourier (AP-HP.7), Université de Paris, France
d Department of Endocrinology, Diabetology and Metabolism, Antwerp University Hospital,
University of Antwerp, Antwerp, Belgium
e L’institut du thorax, Department of Endocrinology, CIC 1413 INSERM, CHU Nantes, Nantes,
France
f AP-HP, Hôpital Lariboisière, Service d'Hématologie biologique, Paris, France
g Service de Chirurgie Digestive, Endocrinienne, Oncologique et Transplantation Hépatique,
CHU de Tours, France
h INRA, UMR 1280, Physiologie des Adaptations Nutritionnelles, CHU Hôtel-Dieu, F-44000
Nantes, France
* These authors contributed equally to this work
# Corresponding author: L’institut du thorax, INSERM UMR 1087-CNRS UMR 6291, Nantes, France, cedric.lemay@univ-nantes.fr.
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ABSTRACT
Aim
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a master regulator of low-density
lipoprotein cholesterol (LDL-C) metabolism, acting as an endogenous inhibitor of the LDL
receptor. While it has been shown that bariatric surgeries differentially affect plasma LDL-C
levels, little is known about their effects on plasma PCSK9 concentrations. Here, we aim: i) to
investigate the effect of sleeve gastrectomy (SG) and Roux en Y Gastric Bypass (RYGB) on
plasma PCSK9 concentrations; ii) to correlate baseline or post-operative plasma PCSK9
concentrations variation with anthropometric and metabolic parameters.
Methods
Fasting plasma PCSK9 levels were measured by ELISA in morbidly obese patients before and
6 months after bariatric surgery. Patients were recruited from three prospective cohorts (Nantes
and Colombes, France; Antwerp, Belgium).
Results
One hundred fifty-six patients were included: 34 SG and 122 RYGB. Plasma PCSK9, LDL-C
and non-high-density lipoprotein-C (non-HDL-C) levels were significantly reduced after
RYGB (-19.6%; -16.6%; -19.5%, respectively; p<0.0001) but not after SG. In the whole
population, post-operative PCSK9 change was positively correlated with fasting plasma
glucose (r=0.22, p=0.007), HOMA-IR (r=0.24, p=0.005), total cholesterol (r=0.17, p=0.037)
and non-HDL-C (r=0.17, p=0.038) variations, but not correlated with LDL-C. In contrast to
what observed for glucose parameters (FPG and HOMA-IR), the correlation between PCSK9
3
Conclusion
RYGB, but not SG, promotes a significant reduction in plasma PCSK9 levels. The change in
circulating PCSK9 after RYGB levels seems to be more associated with improvement in
4
INTRODUCTION
Obesity is a rising morbid condition, gaining epidemic characteristics, with more than
one in 20 adults being affected [1]. A majority of morbidly obese patients displays several
comorbidities such as type 2 diabetes (T2D), hypertension, dyslipidemia, cardiovascular
diseases (CVD) and cancer [2,3]. Currently, bariatric surgery emerges as the most efficient
therapeutic option for severe obese patients and the number of procedures progresses constantly
worldwide [4]. Sleeve gastrectomy (SG), a restrictive procedure, and Roux-en-Y gastric bypass
(RYGB) a restrictive and malabsorptive mixed procedure with intestinal derivation, are
currently the two most commonly used bariatric procedures in clinical practice [4]. Several
meta-analyses have demonstrated that bariatric surgeries significantly reduce body weight and
improve metabolic comorbidities, with a global higher efficiency for RYGB compared to SG
[5-8].
The Swedish Obesity Study showed that obese patients undergoing bariatric surgery
could benefit from a 53% reduction in cardiovascular mortality compared to those who did not
[9]. Dyslipidemia is clearly improved after bariatric surgery, but in a different manner according
to the surgical techniques [5-8]. In large meta-analyses, both SG and RYGB decrease plasma
triglycerides (TG) and increase high-density lipoprotein cholesterol (HDL-C) levels in a similar
extent [6-8]. In contrast, the decrease of plasma low-density lipoprotein cholesterol (LDL-C)
concentration is more pronounced after a malabsorptive procedure (RYGB, biliopancreatic
diversion) than after a restrictive surgery (SG, gastric banding). [6-8]. These clinical
observations suggest that the underlying cellular and molecular mechanisms differ between
bariatric procedures regarding lipid and LDL-C metabolism. Using mouse models of SG and
RYGB, we recently confirmed these clinical observations [10]. We also brought some
mechanistic explanations by showing that RYGB, but not SG, promotes fecal cholesterol
5
inhibiting the intestinal absorption of cholesterol [10].
Proprotein convertase subtilisin/kexin type 9 (PCSK9) was identified in 2003 as the
third gene involved in the autosomal dominant hypercholesterolemia (ADH) [11]. PCSK9 is
secreted in the plasma by the liver, binds to the LDL-receptor (LDLR) and promotes its
lysosomal degradation [12]. While PCSK9 “gain-of-function” mutations are associated with
ADH, PCSK9 “loss-of-function” mutations are conversely related to low LDL-C levels and an
impressive reduction of the incidence of coronary events [13]. PCSK9 inhibitors have quickly
emerged as a novel therapeutic option for hypercholesterolemia and CVD [14] and human
monoclonal antibodies directed against PCSK9 reduce major cardiovascular events in dedicated
cardiovascular outcomes trials [15,16].
Interestingly, some studies highlighted a relationship between PCSK9 concentrations
and fat mass. For instance, circulating PCSK9 regulates fat accumulation in mouse adipocytes
through a VLDL receptor down-regulation [17]. Moreover, plasma PCSK9 levels were found
to be positively associated with body mass index (BMI) [18, 19] and percent body fat in humans
[20]. While caloric restriction reduces circulating PCSK9 levels in adults [21] and adolescents
[22], biliopancreatic diversion has been shown recently to concomitantly decrease plasma
LDL-C and PLDL-CSK9 levels [23]. However, there is currently no data comparing the effect of restrictive
or malabsorptive bariatric procedure on plasma PCSK9 concentrations.
The objective of our study is to investigate in morbidly obese patients the relationship
between the changes in circulating PCSK9 concentrations and anthropometric and metabolic
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MATERIALS AND METHODS
Study subjects
Obese patients who were eligible for SG or RYGB, were recruited from 3 prospective cohorts:
one conducted in Nantes and Tours (NCT00422006), one in Colombes (NCT00632671) and
one in Antwerp (LSHM-CT-2005-018734). Patients recruited in Tours were excluded because
the blood sampling was not performed under fasting conditions, a situation that alters the
concentration of PCSK9 [24]. The population participating in these studies included adult
patients with morbid (BMI ≥ 40 kg/m²) or severe obesity (BMI ≥ 35 kg/m²) with associated
comorbidities. To avoid interference with plasma PCSK9 concentration, we excluded patients
treated with insulin sensitizer (metformin and/or glitazones) and lipid-lowering therapies
(statin, fibrates, ezetimibe, bile acid sequestrants).
Bariatric procedures
All patients were evaluated by an extensive pre-operative multidisciplinary committee according to the National Institutes of Health recommendations (gastrointestinal surgery NIH 1991, HAS recommendations 2009). Bariatric procedures were standardized and done
laparoscopically.SG procedure consists of the removal of 80% of the stomach by discarding
the greater curvature and the entire fundus of the stomach. RYGB consisted of a small gastric
pouch (30 cc), a 150 cm alimentary limb, and a 50 cm biliary limb.
Biochemical measurements
Clinical and biological data were measured preoperatively and 6 months after bariatric surgery.
All the blood samples were collected in the morning, after at least 12 hours of fasting. All
plasma PCSK9 concentrations were determined using a commercially available ELISA kit
7
in accredited biochemical laboratories of each hospital, using enzymatic methods. LDL-C was calculated using the Friedewald formula. Non-HDL-C was calculated with this formula: total cholesterol - HDL-C. HOMA-IR was calculated with the following formula: (fasting insulinemia (µUI/mL) * fasting blood glucose(mmol/L))/22.5 [26]. QUICKI was calculated as:
(1/(log(fasting insulinemia (µUI/mL)) + log(fasting blood glucose(mmol/L))) [27]. The weight
loss was expressed as percent of total weight loss (%TWL).
Ethics statement
The study was conducted according to the principles of the Declaration of Helsinki and in
compliance with the international Conference on Harmonization/Good Clinical Practice
regulations. According to the French regulatory, the studies has been registrated at “Direction
Générale de la Santé - Ministère de la Santé et des Solidarités” after approval by the Ethics
committee of Colombes (Paris) and CPP Ouest II of Angers with the following number: Nantes
(2006-31) and Colombes (NCT00632671) and Antwerp (LSHM-CT-2005-018734). For all
patients, a written informed consent was obtained before participating in each study.
Statistical Methods
Baseline characteristics of the population are presented as n (%) for categorical variables and mean ± standard deviations (SD) for quantitative variables. We used Wilcoxon Student’s T-test to compare the distribution of these parameters between baseline and 6 months after surgery. The correlation between PCSK9 levels and its variations with other parameters is described using Spearman’s rank correlation coefficient. A p-value < 0.05 was considered as statistically significant.
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RESULTS
Baseline characteristics
A total of 156 (131 women, 25 men) subjects who had undergone RYGB or SG and completed
6 months of follow-up by the time of analysis, were enrolled in 3 prospective studies: 44 patients
from Nantes, 38 from Colombes and 74 from Antwerp. Thirty-four patients (22%) underwent
SG and 122 patients (78%) a RYGB. In cohorts of Colombes and Antwerp, only RYGB
procedures were included in the study whereas in Nantes cohort 61% of patients underwent SG.
Twenty-four patients from Nantes, 6 patients from Colombes and 10 patients from Antwerp
had T2D preoperatively. Only patients who were not on lipid-lowering therapies were included.
Baseline clinical and metabolic data are summarized for the whole study population in Table
1.
RYGB but not SG decreases plasma PCSK9 levels at 6 months
As expected, several metabolic parameters were improved 6 months after bariatric surgery in
the whole population (Table 1). Plasma PCSK9 concentrations were significantly reduced by
20% after bariatric surgery (301 ± 149 vs 241 ± 100 ng/ml, p < 0.0001). The main metabolic
differences observed between centers at 6 months was the absence of significant reduction of
LDL-C and total cholesterol concentrations in Nantes compared to Antwerp and Colombes.
This finding is probably due to the fact that SG was the main procedure performed in Nantes.
We next assessed whether bariatric procedures differentially affected metabolic parameters
(Table 2). While both SG and RYGB statistically improved both glucose parameters (FPG and
HbA1C) and insulin sensitivity (HOMA-IR and QUICKI indexes), only RYGB reduced
significantly lipid parameters (LDL-C and non-HDL-C concentrations). Importantly,
circulating PCSK9 levels were significantly reduced after RYGB (-19.6%; p<0.001), but not
9
Correlations between plasma PCSK9 concentrations and metabolic parameters
At baseline: We first assessed correlations between PCSK9 levels and anthropometric and
metabolic parameters (Supplemental Table 1). Spearman analyses only found a significant
positive association between circulating PCSK9 and LDL-C (r=0.19, p=0.022), HbA1C (r=0.17,
p=0.036) and FPG (r=0.28, p<0.001).In contrast, there was no significant correlation between
PCSK9 and BMI or waist size.
After bariatric procedures: We then investigate the correlations between changes in plasma
PCSK9 levels and metabolic parameters from baseline to 6 months after bariatric surgery
(Table 3). We found a weak positive correlation between PCSK9 and non-HDL-C changes in
the whole population only. However, PCSK9 and LDL-C changes were not correlated,
suggesting that the decrease of LDL-C levels observed after RYGB was mainly independent of
PCSK9 regulation. In the SG group, PCSK9 change was positively correlated with plasma TG
change. Interestingly, change in PCSK9 levels after bariatric surgery was more strongly
correlated with change in glucose homeostasis parameters (Table 3 and figure 2A). These
correlations persisted in RYGB group, whereas they are not maintained in the SG group (Table
3 and Figures 2E).
As expected, a strong positive correlation between the percentage of total weight loss (%TWL)
and HOMA-IR change (r=0.29, p=0.00045) was observed after bariatric surgery (Figure 2B).
Moreover, this correlation seemed to partly explain the relationship between HOMA-IR and
PCSK9 changes, as this relation was no more significant when adjusting on %TWL (Table 4).
In contrast, there was no correlation between %TWL and non-HDL-C changes (r=-0.05,
p=0.56) (Figure 1C), suggesting that the improvement of non-HDL-C following bariatric
10
DISCUSSION
The present study aims to investigate RYGB and SG effects on plasma PCSK9
concentrations. The main finding of this study is that bariatric procedures differentially alter
plasma PCSK9 levels. While RYGB significantly decreases circulating PCSK9 concentrations,
SG has a neutral effect.
In humans, previous studies have shown that LDL-C decreased significantly after
bariatric surgery [5-8]. More precisely, meta-analyses show that RYGB, but not SG, reduces
rapidly and sustainably LDL-C levels [6,8]. In accordance with these results, we showed that
RYGB significantly reduces LDL-C, non-HDL-C and total cholesterol levels in patients with
severe obesity. By contrast, there were no significant changes of these parameters six months
after SG. These observations suggest that the underlying cellular and molecular mechanisms
regulating LDL-C metabolism differ between bariatric procedures.
To date, the putative involvement of PCSK9 in the beneficial effects of bariatric surgeries
remains poorly documented. Here, we compared for the first time the effect of restrictive (i.e.
SG) and malabsorptive (i.e. RYGB) procedures on plasma PCSK9 levels by using three
independent cohorts. Circulating PCSK9 levels decreased (by about 20% when compared to
baseline) after RYGB, but not after SG. This result is in line with the study of Boyer et al [23]
showing that biliopancreatic diversion with duodenal switch significantly reduces plasma
PCSK9 concentrations by about 10% at 6 and 12 months. While biliopancreatic diversion is the
most effective procedure for lowering LDL-C [5, 6], its clinical use remains limited due to the
risk of severe malnutrition. Altogether, these results suggest that malabsorptive but not
restrictive procedures are associated with a decrease in circulating PCSK9 levels. It cannot be
excluded that this effect is linked to the extent of TWL, which is more important after RYGB
and biliopancreatic diversion than after SG. In accordance with this hypothesis, TWL was
11
relatively weak in our study (Table 3). Alternatively, we can hypothesize that the observed
changes of circulating PCSK9 levels might be related to bile acid metabolism alteration. Indeed,
plasma bile acids is significantly increased after RYGB in humans, pigs, rats and mice.
[10,28,29,30]. It was also recently suggested that the concentration of circulating bile acids was
increased after RYGB surgery independently of caloric restriction [31] and was strongly
correlated with improvement in lipid metabolism [29,30]. Our team first reported that farnesoid
X receptor (FXR) activation in human hepatocytes represses PCSK9 expression [32]. More
recently, it was shown that treatment with chenodeoxycholic acid (natural FXR agonist) in
healthy patients reduces circulating PCSK9 levels [33]. Additional studies are warranted to
determine the contribution of bile acids signaling in the regulation of circulating PCSK9 levels
after RYGB. Another hypothesis is the link between insulin resistance (IR) and circulating
PCSK9 levels. Plasma PCSK9 levels are positively associated with HOMA-IR in several
cohorts [16, 34]. Moreover, we previously reported a positive association between plasma
PCSK9 levels and hepatic IR assessed during hyperinsulinemic-euglycemic clamps in healthy
subjects fed with a high-fructose diet [25]. As RYGB surgery is known to improve IR [35], it
is tempting to suggest that such a reduction could contribute to decrease circulating PCSK9
levels. However, both RYGB and SG efficiently reduce HOMA-IR 6 months after surgery
(Table 2) but curiously only variations in HOMA-IR following RYGB, but not SG, are
positively correlated with changes in PCSK9 concentrations (Table 3). Although we cannot
exclude a lack of statistical power in the SG group, it seems unlikely that IR improvement following bariatric surgery can explain by itself circulating PCSK9 change.
While we confirmed that baseline PCSK9 levels are associated with LDL-C [16, 36], we
failed to detect a significant association between PCSK9 and LDL-C changes either in RYGB
or in SG, suggesting that PCSK9 is not the molecular link for the LDL-lowering effect of
12
The main limitation of our study is the small number of patients included in the SG group
(n=34). While our results did not show substantial decrease on plasma PCSK9 levels with SG,
we cannot exclude that this result is attributable to a lack of power. Unfortunately, we did not
have access to liver and/or intestinal biopsies collected before and after surgery to directly
measure PCSK9 expression in these tissues and thus better understand the molecular
mechanisms that sustain plasma PCSK9 reduction after RYGB. The observational design of
our study allows us to draw some associations but not causation, regarding the role of PCSK9
in the metabolic effects of bariatric surgery.
In conclusion, our results demonstrate that RYGB, but not SG, is associated with a
reduction of plasma PCSK9, LDL-C and non-HDL-C levels. The underlying molecular
mechanisms by which RYGB affect plasma PCSK9 remain to be established. We believe that
our results are of clinical relevance to better select dyslipidemic obese patients towards a
bariatric procedure (i.e. RYGB) that allows the simultaneous reduction of several risk factors,
such as LDL-C and plasma PCSK9 concentrations, that influence cardiovascular diseases
13
Grant Information, and non-blinded COI Statement
We pooled the analyses of 2 prospective French study: Nantes (NCT00422006), This study was
supported by a grant from the Fondation Leducq (#13CVD03), the French Ministry of Health:
PHRCI 2006 GO-26 and Colombes (COLOMBES Study) (NCT00632671) and one cohort
Belgian study (Hepatic and adipose tissue and functions in the metabolic syndrome: HEPADIP
EU consortium Contract LSHM-CT-2005-018734).
Detailed Acknowledgments
We thank all the participants in this study.
C.B, B.C and C.LM designed the study, supervised the analyses and wrote the first draft of
the manuscript. M.W performed the statistical analyses. S.L, A.V, E.L, A.S, N.H, D.J, M.K,
M.LB, M.PG, L.VG, enrolled the patients and contributed to data collection. L.A performed
the dosages of PCSK9. M.P. supervised the recruitment and performed the data management.
All the authors participated in the critical revision of the manuscript.
Financial Disclosures
B.C. has received research funding from Amgen, Pfizer and Sanofi and Regeneron
Pharmaceuticals Inc outside of the present work; and has served on scientific advisory boards
and received honoraria or consulting fees from Amgen, Regeneron and Sanofi. The other
14
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HIGHLIGHTS
• Roux en Y gastric bypass but not sleeve gastrectomy reduces plasma PCSK9 levels • Plasma PCSK9 changes after RYGB are not associated with changes in LDL-C • Changes in plasma PCSK9 are correlated with changes in glucose parameters after
21 Whole population N = 156 RYGB N = 122 SG N = 34
Preop. M6 P-value Preop. M6 P-value Preop. M6 P-value
Waist size (cm) 126 ± 14.3 105.4 ± 14.2 <0.0001 123.2 ± 12.8 102.8 ± 12.3 <0.0001 144.1 ± 9.4 122.3 ± 14.2 <0.0001 BMI (kg/m²) 43.8 ± 6.1 34.0 ± 6.0 <0.0001 43.1 ± 5.8 33.1 ± 5.1 <0.0001 46.2 ± 6.8 37.5 ± 7.6 <0.0001 HbA1c (%) 5.9 ± 0.8 5.5 ± 0.5 <0.0001 5.8 ± 0.8 5.5 ± 0.5 <0.0001 6.1 ± 0.7 5.7 ± 0.4 0.019 HbA1c (mmol/mol) 40.6 ± 8.8 36.6 ± 5.4 <0.0001 40.1 ± 8.9 36.1 ± 5.5 <0.0001 42.8 ± 7.9 38.7 ± 4.6 0.019 FPG (mg/dL) 96 ± 31 85 ± 13 <0.0001 96 ± 34 85 ± 14 0.0001 94 ± 16 85 ± 8 0.0069 HOMA-IR 4.57 ± 3.46 1.84 ± 1.25 <0.0001 4.58 ± 3.61 1.76 ± 1.25 <0.0001 4.51 ± 2.77 2.18 ± 1.23 0.0002 QUICKI 0.32 ± 0.03 0.36 ± 0.03 <0.0001 0.32 ± 0.03 0.36 ± 0.03 <0.0001 0.32 ± 0.02 0.35 ± 0.03 <0.0001 TC (mg/dL) 205 ± 42 185 ± 36 <0.0001 203 ± 41 177 ± 31 <0.0001 209 ± 45 212 ± 40 0.57 LDL-C (mg/dL) 125 ± 35 110 ± 33 <0.0001 125 ± 34 105 ± 28 <0.0001 122 ± 38 130 ± 39 0.11 HDL-C (mg/dL) 48 ± 14 52 ± 13 <0.0001 46 ± 12 50 ± 13 <0.0001 53 ± 18 59 ± 13 0.028 Non-HDL-C (mg/dL) 157 ± 43 133 ± 35 <0.0001 157 ± 41 127 ± 31 <0.0001 157 ± 49 153 ± 43 0.51 Triglycerides (mg/dL) 172 ± 116 109 ± 37 <0.0001 173 ± 123 110 ± 37 <0.0001 168 ± 90 103 ± 38 <0.0001 ASAT (µkat/L) 0.41 ± 0.31 0.33 ± 0.13 0.0022 0.38 ± 0.2 0.33 ± 0.13 0.0038 0.53 ± 0.54 0.35 ± 0.12 0.074 ALAT (µkat/L) 0.57 ± 0.42 0.36 ± 0.15 <0.0001 0.58 ± 0.4 0.37 ± 0.14 <0.0001 0.52 ± 0.5 0.34 ± 0.18 0.044 ƔGT (µkat/L) 0.75 ± 0.78 0.47 ± 0.5 <0.0001 0.77 ± 0.81 0.44 ± 0.43 <0.0001 0.67 ± 0.69 0.60 ± 0.68 0.46 ALP (µkat/L) 1.31 ± 0.34 1.41 ± 0.52 0.0031 1.37 ± 0.33 1.47 ± 0.55 0.015 1.11 ± 0.3 1.20 ± 0.34 0.026 PCSK9 (ng/ml) 301 ± 149 241 ± 100 <0.0001 314 ± 160 245 ± 105 <0.0001 251 ± 86 230 ± 79 0.18
Table 1. Anthropometric and biological parameters, in whole population and according to surgery.
Quantitative parameters are expressed with mean ± SD. Groups are compared using Student’s T-test for paired series. SG, Sleeve Gastrectomy; RYGB, Roux en Y Gastric Bypass; Preop., preoperative period; M6, 6-month post-operative period; FPG: fasting plasma glucose; TC: total cholesterol; TG:
triglycerides; ALP: alkaline phosphatase; ASAT, ASpartate Transferase; Alanine; Amino-Transferase; ƔGT, Gamma glutamyl transpeptidase.
22
Whole population
N = 156 N = 122 RYGB N = 34 SG Individual
change P Individual change P Individual change P
Waist size (cm) [-20.4%; -12.4%] -16.1 % <0.0001 [-20.4%; -12.8%] -16.3% <0.0001 [-19.9%; -11.1%] -13.9% 0.0025 BMI (kg/m²) [-26.6%; -18.4%] -22.9% <0.0001 [-27.1%; -19.5%] -23.4% <0.0001 [-25.4%; -14.7%] -19.5% <0.0001 HbA1c (%) [-9.8%; 0%] -3.4% <0.0001 [-9.7%; 0%] -3.4% <0.0001 [-8.8%; 0%] -1.6% 0.0021 HbA1C (mmol/mol) [-15.4%; 0%] -5.6% <0.0001 [-15.7%; 0%] -5.6% <0.0001 [-13.5%; 0%] -2.6% 0.0012 FPG (mg/dL) [-14.2%; 0%] -7.2% <0.0001 [-13.3%; 0%] -7.2% <0.0001 [-15.8%; 0%] -5.8% 0.0064 HOMA-IR [-70.7%; -32.5%] -56.3% <0.0001 [-72.8%; -39.2%] -56.6% <0.0001 [-69.9%; -16.5%] -45% 0.0001 QUICKI [+6.2%; +19.8%] +12.5% <0.0001 [7.4%; 20.7%] +12.5% <0.0001 [3.1%; 17.5%] +9.1% 0.0001 TC (mg/dL) [-19%; 1.2%] -10.1% <0.0001 [-20.9%; -3.8%] -12.5% <0.0001 [-4.5%; 12.6%] -0.2% 0.56 LDL-C (mg/dL) [-27.8%; 4.1%] -12.5% <0.0001 [-29.1%; -2.6%] -16.6% <0.0001 [-8.8%; 24%] +6.4% 0.12 HDL-C (mg/dL) [2.3%; 23.5%] +9.7% <0.0001 [-3.7%; 20.1%] +7.6% <0.0001 [5.3%; 28.7%] +16.1% 0.0003 Non-HDL-C (mg/dL)) [-26.6%; -0.5%] -13.7% <0.0001 [-29.1%; -5.8%] -19.5% <0.0001 [-13.1%; 12.3%] +2.1% 0.84 TG (mg/dL) [-48.7%; -0.2%] -30.5% <0.0001 [-48.2%; 3%] -27% <0.0001 [-48.8%; -22.8%] -37.3% <0.0001 ASAT (µkat/L) [-29.6%; 9.5%] -9.1% 0.0001 [-31.5%; 10.9%] -7.7% 0.0011 [-29.5%; 8.7%] -15.9% 0.033 ALAT (µkat/L) [-52.3%; 5.9%] -22.2% <0.0001 [-52.9%; 4.9%] -21.2% <0.0001 [-49.7%; 8.9%] -23.6% 0.019 ƔGT (µkat/L) [-48.5%; -22.9%] -36.2% <0.0001 [-50.7%; -26.1%] -38.5% <0.0001 [-42.8%; -12.2%] -25.8% 0.01 APL (µkat/L) [-4.1%; +19.6%] +7.6 % <0.0001 [-6.3%; 21.4%] +8.7% 0.0004 [-2.3%; 16.6%] +5.5% 0.016 PCSK9 (ng/mL) [-31.8%; 3.5%] -14.8% <0.0001 [-34.1%; -0.6%] -19.6% <0.0001 -4.6% [-25.0%; 9.1%] 0.11
Table 2. Individual changes in anthropometric and biological parameters, between preoperative and
6-months post-operative periods, in whole population and according to surgery.
Changes are expressed as median [25th and 75th percentiles%] of individual changes. SG, Sleeve
gastrectomy; RYGB = Roux en Y Bypass. Preop., preoperative period; FPG: fasting plasma glucose; TC: total cholesterol; TG: triglycerides; ALP: alkaline phosphatase; ASAT, ASpartate Amino-Transferase; Alanine; Amino-Transferase; ƔGT, Gamma glutamyl transpeptidase.
23
Whole population RYGB population SG population
Changes (%) Rho P-value Rho P-value Rho P-value
Waist size 0.13 0.21 0.12 0.30 0.02 0.96 Weight loss -0.16 0.047 -0.14 0.12 -0.05 0.80 HbA1c 0.06 0.48 0.03 0.72 0.08 0.69 FPG 0.22 0.007 0.23 0.011 0.25 0.16 HOMA-IR 0.24 0.005 0.22 0.017 0.26 0.19 QUICKI -0.23 0.007 -0.21 0.024 -0.24 0.23 TC 0.17 0.037 0.16 0.08 -0.11 0.54 LDL-C 0.12 0.15 0.11 0.23 -0.22 0.22 HDL-C 0.01 0.85 -0.03 0.78 0.05 0.78 Non-HDL-C 0.17 0.038 0.18 0.054 -0.18 0.32 TG 0.15 0.073 0.14 0.13 0.38 0.031
Table 3: Correlation between PCSK9 change and change in anthropometric and metabolic parameters,
in the whole population and according to surgery. Spearman’s correlation coefficients with associated
24
Dependent parameter: PCSK9 change (ng/mL) HOMA-IR change Non-HDL-c change (mg/dL)
Adjustment model (linear regressions) β coeff [95% CI) P-value β coeff [95% CI) P-value
No adjustment 0.19 [0.03; 0.35] 0.021 0.22 [-0.05; 0.48] 0.12
Adjusted on bariatric procedure 0.18 [0.02; 0.34] 0.027 0.16 [-0.13; 0.45] 0.27
Adjusted on weight loss 0.11 [-0.06; 0.27] 0.21 0.25 [-0.01; 0.51] 0.06
Adj. on weight loss and bariatric procedure 0.11 [-0.06; 0.27] 0.21 0.24 [-0.05; 0.53] 0.10
Table 4: Study of the association between changes for (i) HOMA-IR and PCSK9 and (ii) non-HDL-c and PCSK9, before and after adjustment on bariatric
