Search
Close
Search
Advanced Search
Search Menu

Abstract

Context

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of low-density lipoprotein cholesterol (LDL-C) concentrations. In patients with severe obesity, biliopancreatic diversion with duodenal switch (BPD-DS) surgery induces substantial weight loss and influences lipoprotein metabolism. The effect of BPD-DS on PCSK9 levels is unknown.

Objectives

To determine the acute and chronic impact of BPD-DS on PCSK9 levels and whether the acute impact of BPD-DS could be explained by BPD-DS–associated caloric restriction (CR).

Design, Settings, and Participants

PCSK9 levels were measured in 20 men and 49 women (age, 41.5 ± 11.1 years) with severe obesity before, 24 hours, 5 days, and 6 and 12 months after BPD-DS and in a comparable control group (n = 31) at baseline and at 6 and 12 months. PCSK9 levels were also measured during 3-day CR in patients (n = 7) with severe obesity and type 2 diabetes.

Results

PCSK9 levels increased 13.4% after 24 hours (248.7 ± 64.8 to 269.7 ± 63.8 ng/mL; P = 0,02) and decreased 9.5% at 12 months compared with baseline (217.6 ± 43.0 ng/mL; P < 0,0001). LDL-C levels decreased 36.2% after 24 hours (2.6 ± 0.7 to 1.7 ± 0.6 mmol/L; P < 0.0001) and 30% at 12 months compared with baseline (1.7 ± 0.5 mmol/L; P < 0.0001). Compared with baseline levels, PCSK9 levels were lower at day 2 but not at day 1 or 3 after CR.

Conclusion

BPD-DS is associated with acute increases in PCSK9 levels that do not appear to be explained by CR but may be due to an acute response following surgery. BPD-DS induces chronic reductions in both PCSK9 and LDL-C levels.

The prevalence of severe obesity is increasing globally (1). A high proportion of patients with severe obesity are insulin resistant and dyslipidemic and are at increased risk for type 2 diabetes (T2D) and cardiovascular disease (CVD) (2, 3). Bariatric surgery is the only established treatment leading to long-term extensive and durable weight loss, as well as a sustainable remission/improvement of comorbidities associated with excess body weight in most patients (4). Over the past several years, many bariatric surgery procedures have been shown to improve insulin sensitivity and the cardiometabolic risk profile of patients with severe obesity. Sleeve gastrectomy, Roux-en-Y gastric bypass surgery (RYGB), and biliopancreatic diversion with duodenal switch (BPD-DS) surgery are the most effective surgeries for sustainable weight loss and resolution of comorbidities (5, 6). Data from the Swedish Obesity Study have suggested that patients undergoing bariatric surgery could benefit from a 53% reduction in cardiovascular mortality compared with severely obese individuals who did not undergo bariatric surgery (7). A recently published meta-analysis has shown that contemporary bariatric surgery is associated with an improvement in the lipoprotein-lipid profile (8). However, the biological mechanisms underlying dyslipidemia resolution following bariatric surgery remain unclear.

Large-scale genetic association studies and family-based investigations have identified a pivotal role for proprotein convertase subtilisin/kexin type 9 (PCSK9) in the regulation of plasma cholesterol levels (9, 10). PCSK9 is secreted by the liver, binds to and targets the low-density lipoprotein (LDL) receptor for lysosomal degradation, thereby decreasing LDL receptor density on hepatocytes (11, 12). A recent study demonstrated that elevated plasma PCSK9 concentrations are associated with future risk for CVD even after adjustments for established CVD risk factors (13). Factors that regulate PCSK9 expression and secretion are not well understood. Plasma PCSK9 levels can be influenced by insulin levels in humans. Although some in vitro and in vivo studies in rodents have suggested an association between insulin and PCSK9 gene expression (14, 15), whether this association is causal in humans is unknown (16, 17). Additionally, several studies have also shown that statin therapy increases PCSK9 levels (18).

We have recently shown that a 1-year lifestyle modification program that included both improvements in physical activity levels and dietary quality failed to influence plasma PCSK9 levels in patients with abdominal obesity and patients with coronary artery disease (19, 20). In patients with coronary artery disease, we unexpectedly found that patients treated with hypolipidemic agents who decreased their amount of visceral fat and increased their cardiorespiratory fitness levels had higher PCSK9 levels at the end of the 1-year lifestyle modification program compared with baseline levels (20). However, the effects of interventions that lead to greater weight loss and substantial metabolic changes, such as bariatric surgery, on plasma PCSK9 levels are unknown.

The objective of our study was to determine the acute and long-term impact of bariatric surgery on plasma lipid-lipoprotein profile and PCSK9 levels in patients with severe obesity. We also sought to determine whether the acute impact of bariatric surgery on plasma PCSK9 could be explained by bariatric surgery–associated caloric restriction (CR).

Material and Methods

Study participants

Patients were recruited at the bariatric surgery clinic of the Institut universitaire de cardiologie et de pneumologie de Québec, as previously described (21). A total of 69 randomly selected men and women with severe obesity [body mass index (BMI) ≥ 40 or ≥ 35 kg/m2 with associated comorbidities] who were 18 years of age or older were included in this study. A control group that included 31 participants, also with severe obesity, was randomly selected from the waiting list to match patients in the BPD-DS group for age and sex. Blood samples were obtained before BPD-DS surgery (baseline), 1 and 5 days after surgery, and 6 and 12 months after surgery. For the control group, blood samples were obtained at baseline and at 6 and 12 months. The ethics committee of the Institut universitaire de cardiologie et de pneumologie de Québec approved the protocol, and all patients gave their written informed consent before being included in the study.

Anthropometric measurements

Weight, BMI, fat mass, and fat-free mass were measured with an electrical bioimpedance balance (TBF-310; Tanita, Tokyo, Japan) after a 12-hour fast. Medical history and pharmacotherapy were collected from clinical file consultations for the presence of diabetes, hypertension, CVD, and dyslipidemia.

Plasma lipid-lipoprotein profile

After a 12-hour overnight fast, blood samples were collected into Vacutainer tubes containing EDTA for the measurement of plasma lipid and lipoprotein levels (BD, Franklin Lakes, NJ). Plasma was then divided into aliquots in microtubes and stored at −80°C until analysis. Hemoglobin A1c (HbA1c) was measured in fresh samples by turbidimetric inhibition immunoassay. Assays were performed in the hospital clinical biochemistry laboratory using standard methods (fasting plasma glucose, cholesterol, triglyceride, and high-density lipoprotein cholesterol [HDL-C]) or in the research laboratory. LDL cholesterol (LDL-C) concentration was calculated by using the Friedewald formula. Apolipoprotein B levels were measured by immunoturbidimetric method (Integra 800 System; Roche Diagnostics, Indianapolis, IN). Plasma cholesterol, triglyceride, HDL-C, and glucose were measured by using colorimetric enzymatic kits (cholesterol, triglycerides, and HDL-C: Roche Diagnostics; glucose: Wako Chemicals, Richmond, VA). Plasma insulin and adiponectin levels were measured by enzyme-linked immunosorbent assay (ELISA) kit (Crystal Chem Inc., Downers Grove, IL). Homeostatic model assessment of insulin resistance was calculated from fasting plasma insulin and glucose levels as (insulin × glucose)/22.5, where the insulin concentration is reported as milliunits per liter and glucose as millimolar concentrations. PCSK9 levels were measured by ELISA (R&D Systems, Minneapolis, MN).

CR study

Eight patients with T2D and severe obesity (three men and five women) who were eligible for BPD-DS surgery were selected for the CR substudy as previously described (22). All participants had stable weight for 2 months before inclusion. Approximately 2 months before surgery, patients underwent a CR protocol during which energy intake matched the average quantity of food ingested routinely after BPD-DS. During this CR protocol, patients were administered a mixed intravenous solution (NaCl 0.9% at 30 mL/h and dextrose 5% at 60 mL/h). Patients who undergo bariatric surgery receive saline plus dextrose infusions to avoid postsurgery dehydration. To avoid any residual effect of this compound, we administered saline plus dextrose infusions during the CR protocol to make sure that the only differences between treatments were the surgery itself and not the saline plus dextrose infusions. Plasma PCSK9 levels were measured in seven of these patients after an overnight fast during a 3-day CR phase and before and after BPD-DS surgery. The CR protocol and BPD-DS surgery were performed approximately 2 months apart.

Statistical analyses

Student t tests and χ2 tests were, respectively, used to assess differences between continuous and categorical clinical variables at baseline in the surgery vs control group. Stepwise multiple regression analyses were computed to quantify the contribution of cardiometabolic risk markers to the variance in log-transformed PCSK9 levels. Student t tests were also used to test the differences in plasma PCSK9 levels across patient subgroups (sex, statin use, and T2D status). For the bariatric surgery patients, to analyze significant changes among scheduled endpoints measurements (baseline, 24 hours, 5 days, and 6 and 12 months), data were analyzed by using a mixed model with two experimental factors defined: one linked to the variability among patients (a random factor) and the other associated with the comparison among the different time periods (a fixed factor). The latter was analyzed as a repeated-measure factor with the use of a heterogeneous compound symmetric covariance structure. To compare with the control group at baseline, 6 months, and 12 months, a second fixed factor was introduced in the statistical mixed model with an interaction term. The impact of CR vs bariatric surgery was also tested by using the statistical mixed model with an interaction term. When appropriate, some variables were analyzed by using log-transformation to fulfill the model assumptions; reported P values are based on these transformations. Spearman rank-correlation coefficients were computed to determine the association between PCSK9 levels and other cardiometabolic parameters at baseline. Spearman rank-correlation coefficients were also computed to determine the association between changes in PCSK9 levels and 6- and 12-month changes in other cardiometabolic parameters. All statistical analyses were performed with SAS software, version 9.3 (SAS Institute, Inc., Cary, NC).

Results

Baseline anthropometric and clinical characteristics of the 100 patients are presented in Table 1. Patients who underwent BPD-DS had a higher BMI (49.9 ± 7.0 vs 45.3 ± 7.7 kg/m2; P = 0.004), which appeared to be mostly explained by a greater fat mass (70.6 ± 17.5 vs 60.5 ± 17.7 kg; P = 0.008). There was no significant difference in baseline PCSK9 levels between the BPD-DS and control groups. Stepwise multiple regression analyses revealed that HbA1c, sex, and statin treatment together explained 33.7% (P = 0.01) of the variance in log-transformed PCSK9 levels. Accordingly, we observed differences in PCSK9 levels at baseline in some subgroups, such as patients with vs without diabetes (Fig. 1A), patients receiving statins vs patients not receiving statins (Fig. 1B), and men vs women (Fig. 1C).

Table 1.

Baseline Characteristics of Study Patients

CharacteristicBariatric SurgeryControlsP Value
Patients, n6931
Age, y41.5 ± 11.141.8 ± 10.30.9
Men, n (%)20 (29.0)11 (35.5)<0.0001
Statin users, n (%)23 (33.3)17 (54.8)<0.0001
Smokers, n (%)13 (18.8)8 (25.8)<0.0001
T2D, n (%)34 (49.3)10 (32.3)<0.0001
Coronary artery disease, n (%)11 (11.1)1 (1.01)<0.0001
Hypertension, n (%)46 (45.5)20 (19.8)<0.0001
Weight, kg136.6 ± 26.4127.1 ± 28.40.1
BMI, kg/m249.9 ± 7.045.3 ± 7.70.004
Fat mass, kg70.6 ± 17.560.5 ± 17.70.008
Fat-free mass, kg66.0 ± 13.566.7 ± 16.10.8
LDL-C, mmol/L2.61 ± 0.722.56 ± 0.860.8
HDL-C, mmol/L1.27 ± 0.291.12 ± 0.270.02
Triglycerides, mmol/L1.70 ± 1.071.88 ± 0.750.3
Apolipoprotein B, g/L0.78 ± 0.190.8 ± 0.20.6
Insulin, pmol/L199.4 ± 133,5180.0 ± 140.00.5
Glucose, mmol/L6.77 ± 2.406.62 ± 2.910.9
HOMA-IR8.92 ± 7.158.04 ± 6.580.6
HbA1c, %6.24 ± 1.05 6.51 ± 1.320.3
Adiponectin, ng/mL5414 ± 35319163 ± 86630.03
PCSK9, ng/mL248.7 ± 64.8241.6 ± 53.40.6
CharacteristicBariatric SurgeryControlsP Value
Patients, n6931
Age, y41.5 ± 11.141.8 ± 10.30.9
Men, n (%)20 (29.0)11 (35.5)<0.0001
Statin users, n (%)23 (33.3)17 (54.8)<0.0001
Smokers, n (%)13 (18.8)8 (25.8)<0.0001
T2D, n (%)34 (49.3)10 (32.3)<0.0001
Coronary artery disease, n (%)11 (11.1)1 (1.01)<0.0001
Hypertension, n (%)46 (45.5)20 (19.8)<0.0001
Weight, kg136.6 ± 26.4127.1 ± 28.40.1
BMI, kg/m249.9 ± 7.045.3 ± 7.70.004
Fat mass, kg70.6 ± 17.560.5 ± 17.70.008
Fat-free mass, kg66.0 ± 13.566.7 ± 16.10.8
LDL-C, mmol/L2.61 ± 0.722.56 ± 0.860.8
HDL-C, mmol/L1.27 ± 0.291.12 ± 0.270.02
Triglycerides, mmol/L1.70 ± 1.071.88 ± 0.750.3
Apolipoprotein B, g/L0.78 ± 0.190.8 ± 0.20.6
Insulin, pmol/L199.4 ± 133,5180.0 ± 140.00.5
Glucose, mmol/L6.77 ± 2.406.62 ± 2.910.9
HOMA-IR8.92 ± 7.158.04 ± 6.580.6
HbA1c, %6.24 ± 1.05 6.51 ± 1.320.3
Adiponectin, ng/mL5414 ± 35319163 ± 86630.03
PCSK9, ng/mL248.7 ± 64.8241.6 ± 53.40.6

Data are presented as mean ± standard deviation or n (%). HOMA-IR, homeostatic model of insulin resistance.

Open in new tab
Table 1.

Baseline Characteristics of Study Patients

CharacteristicBariatric SurgeryControlsP Value
Patients, n6931
Age, y41.5 ± 11.141.8 ± 10.30.9
Men, n (%)20 (29.0)11 (35.5)<0.0001
Statin users, n (%)23 (33.3)17 (54.8)<0.0001
Smokers, n (%)13 (18.8)8 (25.8)<0.0001
T2D, n (%)34 (49.3)10 (32.3)<0.0001
Coronary artery disease, n (%)11 (11.1)1 (1.01)<0.0001
Hypertension, n (%)46 (45.5)20 (19.8)<0.0001
Weight, kg136.6 ± 26.4127.1 ± 28.40.1
BMI, kg/m249.9 ± 7.045.3 ± 7.70.004
Fat mass, kg70.6 ± 17.560.5 ± 17.70.008
Fat-free mass, kg66.0 ± 13.566.7 ± 16.10.8
LDL-C, mmol/L2.61 ± 0.722.56 ± 0.860.8
HDL-C, mmol/L1.27 ± 0.291.12 ± 0.270.02
Triglycerides, mmol/L1.70 ± 1.071.88 ± 0.750.3
Apolipoprotein B, g/L0.78 ± 0.190.8 ± 0.20.6
Insulin, pmol/L199.4 ± 133,5180.0 ± 140.00.5
Glucose, mmol/L6.77 ± 2.406.62 ± 2.910.9
HOMA-IR8.92 ± 7.158.04 ± 6.580.6
HbA1c, %6.24 ± 1.05 6.51 ± 1.320.3
Adiponectin, ng/mL5414 ± 35319163 ± 86630.03
PCSK9, ng/mL248.7 ± 64.8241.6 ± 53.40.6
CharacteristicBariatric SurgeryControlsP Value
Patients, n6931
Age, y41.5 ± 11.141.8 ± 10.30.9
Men, n (%)20 (29.0)11 (35.5)<0.0001
Statin users, n (%)23 (33.3)17 (54.8)<0.0001
Smokers, n (%)13 (18.8)8 (25.8)<0.0001
T2D, n (%)34 (49.3)10 (32.3)<0.0001
Coronary artery disease, n (%)11 (11.1)1 (1.01)<0.0001
Hypertension, n (%)46 (45.5)20 (19.8)<0.0001
Weight, kg136.6 ± 26.4127.1 ± 28.40.1
BMI, kg/m249.9 ± 7.045.3 ± 7.70.004
Fat mass, kg70.6 ± 17.560.5 ± 17.70.008
Fat-free mass, kg66.0 ± 13.566.7 ± 16.10.8
LDL-C, mmol/L2.61 ± 0.722.56 ± 0.860.8
HDL-C, mmol/L1.27 ± 0.291.12 ± 0.270.02
Triglycerides, mmol/L1.70 ± 1.071.88 ± 0.750.3
Apolipoprotein B, g/L0.78 ± 0.190.8 ± 0.20.6
Insulin, pmol/L199.4 ± 133,5180.0 ± 140.00.5
Glucose, mmol/L6.77 ± 2.406.62 ± 2.910.9
HOMA-IR8.92 ± 7.158.04 ± 6.580.6
HbA1c, %6.24 ± 1.05 6.51 ± 1.320.3
Adiponectin, ng/mL5414 ± 35319163 ± 86630.03
PCSK9, ng/mL248.7 ± 64.8241.6 ± 53.40.6

Data are presented as mean ± standard deviation or n (%). HOMA-IR, homeostatic model of insulin resistance.

Open in new tab
Figure 1.
Baseline PCSK9 levels according to (A) T2D status, (B) statin use, and (C) sex.
Open in new tabDownload slide

Baseline PCSK9 levels according to (A) T2D status, (B) statin use, and (C) sex.

Changes in PCSK9 and LDL-C levels during follow-up in both groups are presented in Fig. 2. One day after surgery, PCSK9 levels significantly increased, whereas LDL-C levels decreased in comparison with baseline levels. LDL-C levels remained significantly lower during follow-up. PCSK9 also decreased following day 1 after BPD-DS and reduced to levels similar to baseline levels at day 5. PCSK9 levels, however, were significantly lower at 6 and 12 months compared with baseline levels. Significant time–group interactions were found for both PCSK9 (P = 0.04) and LDL-C (P < 0.0001) levels. Analyses of least-square means considering changes in both study groups revealed that LDL-C and PCSK9 levels were significantly lower at 6 and 12 months in the surgery group compared with the control group. In the intervention group, we also found that plasma apolipoprotein B levels decreased at 6 months (change, −18.9% ± 25.2%; P < 0.0001) and 12 months (−29.6% ± 23.4%; P < 0.0001).

Figure 2.
Acute and chronic changes in (A) LDL-C and (B) PCSK concentrations in patients who underwent bariatric surgery and in controls. *Significantly different from baseline at P < 0.05.
Open in new tabDownload slide

Acute and chronic changes in (A) LDL-C and (B) PCSK concentrations in patients who underwent bariatric surgery and in controls. *Significantly different from baseline at P < 0.05.

All patients in the surgery group who were receiving statins at baseline (n = 23) stopped using them after surgery. Because statin therapy influences PCSK9 levels, we evaluated changes in PCSK9 levels in patients who were not receiving statins and in patients treated with statins at baseline. Results presented in Fig. 3 suggest that although PCSK9 levels decreased in both subgroups of patients, these changes appeared to be more pronounced in patients who were receiving statins at baseline. PCSK9 levels were, however, not significantly different in both groups at 6 and 12 months.

Figure 3.
Acute and chronic changes in PCSK9 levels in the surgery group according to baseline statin use. *Significantly different from baseline at P < 0.05; ‡P < 0.005.
Open in new tabDownload slide

Acute and chronic changes in PCSK9 levels in the surgery group according to baseline statin use. *Significantly different from baseline at P < 0.05; ‡P < 0.005.

Spearman correlation coefficients between PCSK9 levels and cardiometabolic risk markers at baseline and between 6- and 12-month changes in PCSK9 levels and changes in cardiometabolic risk markers are presented in Table 2. At baseline, PCSK9 levels were negatively associated with body weight and fat mass and positively associated with glucose levels and HbA1c. Six-months changes in PCSK9 levels were positively associated with changes in insulin levels whereas the homeostatic model assessment of insulin resistance and 12-month changes in PCSK9 were positively associated with changes in HDL-C and adiponectin levels as well as with HbA1c (Table 2).

Table 2.

Associations Between PCSK9 and Cardiometabolic Risk Markers at Baseline and Association Between Changes in PCSK9 and Changes in Cardiometabolic Risk Markers in the Surgery Group

VariableBaseline6-Month Changes12-Month Changes
PCSK9LDL-CApoBPCSK9LDL-CApoBPCSK9LDL-CApoB
Weight−0.22 (0.02)−0.12 (0.23)−0.08 (0.39)−0.06 (0.63)−0.21 (0.08)−0.23 (0.06)−0.11 (0.36)−0.13 (0.27)−0.08 (0.48)
BMI−0.11 (0.25)−0.11 (0.22)−0.09 (0.32)−0.07 (0.60)−0.20 (0.09)−0.26 (0.03)−0.11 (0.35)−0.16 (0.17)−0.14 (0.22)
Fat percentage−0.11 (0.26)0.02 (0.80)0.03 (0.69)0.04 (0.73)−0.03 (0.84)−0.07 (0.58)0.13 (0.28)0.04 (0.77)0.04 (0.71)
Fat mass−0.21 (0.03)−0.09 (0.34)−0.08 (0.43)−0.08 (0.53)−0.17 (0.16)−0.22 (0.07)−0.17 (0.17)−0.12 (0.30)−0.08 (0.48)
Fat-free mass−0.18 (0.06)−0.16 (0.09)−0.12 (0.22)−0.06 (0.61)−0.11 (0.37)0.009 (0.94)−0.01 (0.9)−0.12 (0.33)−0.08 (0.53)
ApoB−0.09 (0.34)0.85 (<0.0001)—−0.16 (0.18)0.82 (<0.0001)—−0.19 (0.11)0.85 (<0.0001)—
LDL-C−0.10 (0.32)—0.85 (<0.0001)−0.12 (0.34)—0.82 (<0.0001)−0.15 (0.22)—0.85 (<0.0001)
HDL-C0.02 (0.81)0.08 (0.42)−0.06 (0.57)−0.22 (0.07)−0.002 (0.99)−0.09 (0.47)0.34 (0.005)−0.15 (0.21)−0.21 (0.07)
Triglycerides0.09 (0.36)0.20 (0.04)0.45 (<0.0001)−0.07 (0.54)0.38 (0.0008)0.43 (<0.0001)0.20 (0.09)0.22 (0.06)0.41 (0.0003)
Insulin0.04 (0.67)−0.10 (0.32)−0.007 (0.95)0.25 (0.04)−0.14 (0.24)−0.10 (0.42)−0.08 (0.50)−0.08 (0.51)0.05 (0.68)
Glucose0.37 (<0.0001)−0.19 (0.05)−0.05 (0.63)0.08 (0.49)0.10 (0.39)0.16 (0.18)0.17 (0.16)−0.06 (0.60)−0.02 (0.88)
HOMA-IR0.16 (0.10)−0.11 (0.26)0.03 (0.77)0.25 (0.04)−0.08 (0.51)−0.03 (0.80)−0.08 (0.5)−0.08 (0.49)0.03 (0.79)
HbA1c0.33 (0.0006)−0.19 (0.05)−0.06 (0.56)0.20 (0.12)−0.15 (0.27)−0.07 (0.60)0.29 (0.02)−0.16 (0.17)−0.13 (0.27)
Adiponectin−0.005 (0.9)0.15 (0.14)0.06 (0.56)0.23 (0.07)0.04 (0.75)−0.03 (0.81)0.39 (0.001)−0.25 (0.04)−0.19 (0.12)
PCSK9—−0.10 (0.32)−0.09 (0.34)—−0.12 (0.34)−0.16 (0.18)—−0.15 (0.22)−0.19 (0.11)
VariableBaseline6-Month Changes12-Month Changes
PCSK9LDL-CApoBPCSK9LDL-CApoBPCSK9LDL-CApoB
Weight−0.22 (0.02)−0.12 (0.23)−0.08 (0.39)−0.06 (0.63)−0.21 (0.08)−0.23 (0.06)−0.11 (0.36)−0.13 (0.27)−0.08 (0.48)
BMI−0.11 (0.25)−0.11 (0.22)−0.09 (0.32)−0.07 (0.60)−0.20 (0.09)−0.26 (0.03)−0.11 (0.35)−0.16 (0.17)−0.14 (0.22)
Fat percentage−0.11 (0.26)0.02 (0.80)0.03 (0.69)0.04 (0.73)−0.03 (0.84)−0.07 (0.58)0.13 (0.28)0.04 (0.77)0.04 (0.71)
Fat mass−0.21 (0.03)−0.09 (0.34)−0.08 (0.43)−0.08 (0.53)−0.17 (0.16)−0.22 (0.07)−0.17 (0.17)−0.12 (0.30)−0.08 (0.48)
Fat-free mass−0.18 (0.06)−0.16 (0.09)−0.12 (0.22)−0.06 (0.61)−0.11 (0.37)0.009 (0.94)−0.01 (0.9)−0.12 (0.33)−0.08 (0.53)
ApoB−0.09 (0.34)0.85 (<0.0001)—−0.16 (0.18)0.82 (<0.0001)—−0.19 (0.11)0.85 (<0.0001)—
LDL-C−0.10 (0.32)—0.85 (<0.0001)−0.12 (0.34)—0.82 (<0.0001)−0.15 (0.22)—0.85 (<0.0001)
HDL-C0.02 (0.81)0.08 (0.42)−0.06 (0.57)−0.22 (0.07)−0.002 (0.99)−0.09 (0.47)0.34 (0.005)−0.15 (0.21)−0.21 (0.07)
Triglycerides0.09 (0.36)0.20 (0.04)0.45 (<0.0001)−0.07 (0.54)0.38 (0.0008)0.43 (<0.0001)0.20 (0.09)0.22 (0.06)0.41 (0.0003)
Insulin0.04 (0.67)−0.10 (0.32)−0.007 (0.95)0.25 (0.04)−0.14 (0.24)−0.10 (0.42)−0.08 (0.50)−0.08 (0.51)0.05 (0.68)
Glucose0.37 (<0.0001)−0.19 (0.05)−0.05 (0.63)0.08 (0.49)0.10 (0.39)0.16 (0.18)0.17 (0.16)−0.06 (0.60)−0.02 (0.88)
HOMA-IR0.16 (0.10)−0.11 (0.26)0.03 (0.77)0.25 (0.04)−0.08 (0.51)−0.03 (0.80)−0.08 (0.5)−0.08 (0.49)0.03 (0.79)
HbA1c0.33 (0.0006)−0.19 (0.05)−0.06 (0.56)0.20 (0.12)−0.15 (0.27)−0.07 (0.60)0.29 (0.02)−0.16 (0.17)−0.13 (0.27)
Adiponectin−0.005 (0.9)0.15 (0.14)0.06 (0.56)0.23 (0.07)0.04 (0.75)−0.03 (0.81)0.39 (0.001)−0.25 (0.04)−0.19 (0.12)
PCSK9—−0.10 (0.32)−0.09 (0.34)—−0.12 (0.34)−0.16 (0.18)—−0.15 (0.22)−0.19 (0.11)

Values are given as Spearman correlation coefficients (P value). ApoB, apolipoprotein B; HOMA-IR, homeostatic model of insulin resistance.

Open in new tab
Table 2.

Associations Between PCSK9 and Cardiometabolic Risk Markers at Baseline and Association Between Changes in PCSK9 and Changes in Cardiometabolic Risk Markers in the Surgery Group

VariableBaseline6-Month Changes12-Month Changes
PCSK9LDL-CApoBPCSK9LDL-CApoBPCSK9LDL-CApoB
Weight−0.22 (0.02)−0.12 (0.23)−0.08 (0.39)−0.06 (0.63)−0.21 (0.08)−0.23 (0.06)−0.11 (0.36)−0.13 (0.27)−0.08 (0.48)
BMI−0.11 (0.25)−0.11 (0.22)−0.09 (0.32)−0.07 (0.60)−0.20 (0.09)−0.26 (0.03)−0.11 (0.35)−0.16 (0.17)−0.14 (0.22)
Fat percentage−0.11 (0.26)0.02 (0.80)0.03 (0.69)0.04 (0.73)−0.03 (0.84)−0.07 (0.58)0.13 (0.28)0.04 (0.77)0.04 (0.71)
Fat mass−0.21 (0.03)−0.09 (0.34)−0.08 (0.43)−0.08 (0.53)−0.17 (0.16)−0.22 (0.07)−0.17 (0.17)−0.12 (0.30)−0.08 (0.48)
Fat-free mass−0.18 (0.06)−0.16 (0.09)−0.12 (0.22)−0.06 (0.61)−0.11 (0.37)0.009 (0.94)−0.01 (0.9)−0.12 (0.33)−0.08 (0.53)
ApoB−0.09 (0.34)0.85 (<0.0001)—−0.16 (0.18)0.82 (<0.0001)—−0.19 (0.11)0.85 (<0.0001)—
LDL-C−0.10 (0.32)—0.85 (<0.0001)−0.12 (0.34)—0.82 (<0.0001)−0.15 (0.22)—0.85 (<0.0001)
HDL-C0.02 (0.81)0.08 (0.42)−0.06 (0.57)−0.22 (0.07)−0.002 (0.99)−0.09 (0.47)0.34 (0.005)−0.15 (0.21)−0.21 (0.07)
Triglycerides0.09 (0.36)0.20 (0.04)0.45 (<0.0001)−0.07 (0.54)0.38 (0.0008)0.43 (<0.0001)0.20 (0.09)0.22 (0.06)0.41 (0.0003)
Insulin0.04 (0.67)−0.10 (0.32)−0.007 (0.95)0.25 (0.04)−0.14 (0.24)−0.10 (0.42)−0.08 (0.50)−0.08 (0.51)0.05 (0.68)
Glucose0.37 (<0.0001)−0.19 (0.05)−0.05 (0.63)0.08 (0.49)0.10 (0.39)0.16 (0.18)0.17 (0.16)−0.06 (0.60)−0.02 (0.88)
HOMA-IR0.16 (0.10)−0.11 (0.26)0.03 (0.77)0.25 (0.04)−0.08 (0.51)−0.03 (0.80)−0.08 (0.5)−0.08 (0.49)0.03 (0.79)
HbA1c0.33 (0.0006)−0.19 (0.05)−0.06 (0.56)0.20 (0.12)−0.15 (0.27)−0.07 (0.60)0.29 (0.02)−0.16 (0.17)−0.13 (0.27)
Adiponectin−0.005 (0.9)0.15 (0.14)0.06 (0.56)0.23 (0.07)0.04 (0.75)−0.03 (0.81)0.39 (0.001)−0.25 (0.04)−0.19 (0.12)
PCSK9—−0.10 (0.32)−0.09 (0.34)—−0.12 (0.34)−0.16 (0.18)—−0.15 (0.22)−0.19 (0.11)
VariableBaseline6-Month Changes12-Month Changes
PCSK9LDL-CApoBPCSK9LDL-CApoBPCSK9LDL-CApoB
Weight−0.22 (0.02)−0.12 (0.23)−0.08 (0.39)−0.06 (0.63)−0.21 (0.08)−0.23 (0.06)−0.11 (0.36)−0.13 (0.27)−0.08 (0.48)
BMI−0.11 (0.25)−0.11 (0.22)−0.09 (0.32)−0.07 (0.60)−0.20 (0.09)−0.26 (0.03)−0.11 (0.35)−0.16 (0.17)−0.14 (0.22)
Fat percentage−0.11 (0.26)0.02 (0.80)0.03 (0.69)0.04 (0.73)−0.03 (0.84)−0.07 (0.58)0.13 (0.28)0.04 (0.77)0.04 (0.71)
Fat mass−0.21 (0.03)−0.09 (0.34)−0.08 (0.43)−0.08 (0.53)−0.17 (0.16)−0.22 (0.07)−0.17 (0.17)−0.12 (0.30)−0.08 (0.48)
Fat-free mass−0.18 (0.06)−0.16 (0.09)−0.12 (0.22)−0.06 (0.61)−0.11 (0.37)0.009 (0.94)−0.01 (0.9)−0.12 (0.33)−0.08 (0.53)
ApoB−0.09 (0.34)0.85 (<0.0001)—−0.16 (0.18)0.82 (<0.0001)—−0.19 (0.11)0.85 (<0.0001)—
LDL-C−0.10 (0.32)—0.85 (<0.0001)−0.12 (0.34)—0.82 (<0.0001)−0.15 (0.22)—0.85 (<0.0001)
HDL-C0.02 (0.81)0.08 (0.42)−0.06 (0.57)−0.22 (0.07)−0.002 (0.99)−0.09 (0.47)0.34 (0.005)−0.15 (0.21)−0.21 (0.07)
Triglycerides0.09 (0.36)0.20 (0.04)0.45 (<0.0001)−0.07 (0.54)0.38 (0.0008)0.43 (<0.0001)0.20 (0.09)0.22 (0.06)0.41 (0.0003)
Insulin0.04 (0.67)−0.10 (0.32)−0.007 (0.95)0.25 (0.04)−0.14 (0.24)−0.10 (0.42)−0.08 (0.50)−0.08 (0.51)0.05 (0.68)
Glucose0.37 (<0.0001)−0.19 (0.05)−0.05 (0.63)0.08 (0.49)0.10 (0.39)0.16 (0.18)0.17 (0.16)−0.06 (0.60)−0.02 (0.88)
HOMA-IR0.16 (0.10)−0.11 (0.26)0.03 (0.77)0.25 (0.04)−0.08 (0.51)−0.03 (0.80)−0.08 (0.5)−0.08 (0.49)0.03 (0.79)
HbA1c0.33 (0.0006)−0.19 (0.05)−0.06 (0.56)0.20 (0.12)−0.15 (0.27)−0.07 (0.60)0.29 (0.02)−0.16 (0.17)−0.13 (0.27)
Adiponectin−0.005 (0.9)0.15 (0.14)0.06 (0.56)0.23 (0.07)0.04 (0.75)−0.03 (0.81)0.39 (0.001)−0.25 (0.04)−0.19 (0.12)
PCSK9—−0.10 (0.32)−0.09 (0.34)—−0.12 (0.34)−0.16 (0.18)—−0.15 (0.22)−0.19 (0.11)

Values are given as Spearman correlation coefficients (P value). ApoB, apolipoprotein B; HOMA-IR, homeostatic model of insulin resistance.

Open in new tab

To determine whether acute changes in PCSK9 levels after bariatric surgery (Fig. 2) could be due to BPD-DS–associated CR, we submitted patients with severe obesity and T2D to a 3-day CR protocol that matched the energy intake before and immediately after BPD-DS surgery 2 months prior to their bariatric surgery. PCSK9 levels were measured during the 3-day CR protocol and (approximately) 2 months later, before and after BPD-DS. Results presented in Fig. 4 show the acute elevation in PCSK9 levels following BPD-DS (an elevation that appears to peak 2 days after surgery). On the other hand, PCSK9 levels did not increase upon CR. In fact, PCSK9 levels were even significantly lower 2 days after the initiation of severe CR compared with baseline level. No differences were observed at day 1 and day 3 (Fig. 4).

Figure 4.
Changes in PCSK9 concentration in patients who underwent CR followed by BPD-DS surgery. *Significantly different compared with before BPD-DS at P < 0.05.
Open in new tabDownload slide

Changes in PCSK9 concentration in patients who underwent CR followed by BPD-DS surgery. *Significantly different compared with before BPD-DS at P < 0.05.

Discussion

Our findings suggest that BPD-DS surgery positively influences LDL metabolism in patients with severe obesity. Indeed, we found that LDL-C levels rapidly dropped in the acute phase after BPD-DS surgery and that it remained low in the chronic phase. Conversely, we found that plasma PCSK9 levels significantly increased in the acute phase following BPD-DS. Similar to LDL-C levels, however, PCSK9 levels decreased compared with baseline levels in the chronic phase of the response to surgery. By exploring the acute and chronic effect of BPD-DS surgery on plasma PCSK9 levels, our study provides additional information on the modulation of PCSK9 levels and underscores that long-term weight loss induced by malabsorptive surgery could reduce both PCSK9 and LDL-C levels in patients with severe obesity.

We also found that PCSK9 levels could be influenced by the baseline characteristics of the patients; women had higher PCSK9 levels than men, and patients treated with statins had higher PCSK9 levels than patients who were not treated with statins. Although these observations have been previously reported by others (18, 23), our results extend these findings by showing that the same applies to the population of patients with severe obesity. In our sample, patients with T2D had higher PCSK9 levels than patients without T2D. PCSK9 levels were also associated with glucose levels and HbA1c at baseline, as previously reported in a smaller cohort (24). However, another study found no differences between PCSK9 levels in patients with vs those without T2D (25). Important questions still remain regarding the directionality and causality of this association. In that respect, insulin has been shown to enhance PCSK9 expression, which may argue in favor of T2D causing elevations in PCSK9 levels (14, 15).

Several studies have shown that LDL-C decreased significantly after bariatric surgery. Recently, Carswell et al. (26) showed in a meta-analysis of 7815 study participants that RYGB surgery could decrease LDL-C levels within 1 month and up to 4 years. In our study, PCSK9 levels significantly increased 1 day after the surgery, and levels returned close to baseline at day 5. The biological mechanisms underlying this finding are not known. Because it was not possible in this study to determine whether the acute impact of BPD-DS surgery on cardiometabolic risk markers is due to BPD-DS per se or to the severe CR accompanying this procedure, we conducted a crossover trial and showed that severe CR was accompanied by decreases in PCSK9 levels, whereas BPD-DS led to acute increases in PCSK9 levels. This suggests that CR associated with BPD-DS surgery may not be responsible for the acute increase in PCSK9 levels after BPD-DS surgery. Previously studies had already reported similar results about CR in healthy and lean individuals (27). Our results extend these findings to patients with severe obesity.

Because BPD-DS could induce an acute inflammatory phase response, the rapid increase in PCSK9 levels could therefore be explained by the surgery itself. In a cohort of >2000 patients, PCSK9 levels increased 12 to 24 hours after an acute coronary syndrome, suggesting a possible upregulation of PCSK9 levels in the acute context of acute coronary syndrome (28). PCSK9 gene transcript and plasma PCSK9 levels were also increased 1 to 2 days after acute myocardial infarction in a study conducted in rats (29). Plasma C-reactive protein (CRP) levels may increase (up to 1000-fold) in the acute phase response, and CRP was recently shown to increase PCSK9 gene expression in cultured hepatocytes (30). As expected, CRP-mediated PCSK9 increases were simultaneously associated with lower LDL receptor density at the surface of these cells, which is likely to decrease LDL clearance. This observation, however, does not explain the discordance between increases in PCSK9 levels and decreases in LDL-C levels observed at 24 hours, and more data are needed to consider PCSK9 as an acute phase reactant.

In the chronic phase, PCSK9 levels were significantly decreased in patients who underwent BPD-DS surgery. This decrease in PCSK9 levels could be due to the longer-term weight loss CR induced by the bariatric surgery and by sustained reductions in total food intake. In a recent study, we showed that among abdominally obese men with dyslipidemia, improving dietary quality and increasing physical activity levels did not lead to reductions in plasma PCSK9 levels, thereby suggesting that modest weight loss may not decrease plasma PCSK9 levels (19). In contrast, Richard et al. (31) have shown that a Mediterranean diet could reduce plasma PCSK9 and LDL-C levels by approximately 10% in men with the metabolic syndrome, even in the absence of weight loss. On top of total body weight, previous studies have shown that PCSK9 levels are correlated with hepatic fat accumulation, the severity of hepatic steatosis, and very-low-density-lipoprotein and triglyceride levels (32, 33). Because bariatric surgery has been shown to reduce the prevalence of comorbidities associated with obesity, including fatty liver and steatosis (34), the reduction of hepatic fat induced by bariatric surgery could contribute to decrease circulating PCSK9 levels. Biliopancreatic diversion with or without duodenal switch induces a rapid improvement in insulin sensitivity and glucose control in most patients (6, 22).

Among other factors involved in the regulation of PCSK9, insulin may exert a substantial impact by, for instance, promoting the degradation of the LDL receptor in a PCSK9-dependent manner in vivo (15). In our cohort of abdominally obese men, PCSK9 levels were associated with insulin levels during an oral glucose tolerance test (19).

Another recent study found that PCSK9 gene and protein expression appeared to be downregulated in the small intestine of obese patients with insulin resistance compared with insulin-sensitive patients (35). Although the contribution of the intestine to circulating PCSK9 levels is unknown, studies have shown that PCSK9 could be secreted by the basolateral compartment of intestinal cells, where it colocalizes with the LDL receptor (36). Furthermore, in intestinal cells, PCSK9 expression could be regulated by sterol and bile acids via the farnesoid X receptor (37). It was also recently suggested that the concentration of circulating bile acids was increased after RYGB surgery, independent of CR (38). The alterations in bile flow that result from anatomic changes caused by bariatric surgery and changes in gut microbiome may consequently influence circulating bile acids concentrations and could subsequently contribute to decreases in PCSK9 levels. Finally, improved adipose tissue function and adipokine secretion modulation after BPD-DS surgery may also explain the reductions in PCSK9 levels in the chronic phase. Indeed, resistin and leptin were recently identified as potential modulators of both PCSK9 and LDL-C levels (39, 40).

One third of patients who underwent bariatric surgery in our sample were treated with statins, and all of them stopped taking those drugs after the surgery. Investigating the impact of BPD-DS surgery in patients who were receiving statins vs patients who were not, we found that, as expected, patients who underwent BPD-DS surgery and who simultaneously stopped taking statins appeared to have experienced a more important reduction in plasma PCSK9 levels. On the basis of the absence of any significant correlations between PCSK9 and LDL-C levels at baseline, or changes in PCSK9 levels during the follow-up and changes in LDL-C, we conclude that the variability in LDL-C levels after surgery was not explained by concomitant changes in PCSK9 levels. Finally, in this study, we measured plasma PCSK9 levels by ELISA, which takes into account both lipoprotein-bound and free PCSK9 levels. Other studies, such as the one by Gauthier et al. (41), used a mass spectrometric immunoassay to monitor up to seven PCSK9 peptides, many of which were correlated with LDL-C levels in a cohort of obese patients.

In conclusion, our results suggest that BPD-DS surgery is associated with reductions in circulating levels in both PCSK9 and LDL-C levels. Additional studies are needed to improve our comprehension about the mechanisms underlying the effect of BPD-DS surgery on PCSK9 levels, as well as to identify the clinical impact of BPD-DS surgery on PCSK9 in terms of CVD risk.

Abbreviations

     
  • BMI

    body mass index

    •  
  • BPD-DS

    biliopancreatic diversion with duodenal switch

    •  
  • CR

    caloric restriction

    •  
  • CRP

    C-reactive protein

    •  
  • CVD

    cardiovascular disease

    •  
  • ELISA

    enzyme-linked immunosorbent assay

    •  
  • HbA1c

    hemoglobin A1c

    •  
  • HDL-C

    high-density lipoprotein cholesterol

    •  
  • LDL

    low-density lipoprotein

    •  
  • LDL-C

    low-density lipoprotein cholesterol

    •  
  • PCSK9

    proprotein convertase subtilisin/kexin type 9

    •  
  • RYGB

    Roux-en-Y gastric bypass surgery

    •  
  • T2D

    type 2 diabetes.

Acknowledgments

We thank Sylvain Pouliot for technical help.

Financial Support: This work was supported by operating grants from the Canadian Institutes of Health Research. M.-E.P. is recipient of a studentship from the Fonds de Recherche du Québec-Santé (FRQS). A.C.C. is the recipient of the GlaxoSmithKline Chair in Diabetes of the Université de Sherbrooke. P.P. is a senior scholars from the FRQS. B.J.A. holds a junior scholar award from the FRQS.

Disclosure Summary: L.B. and A.T. receive research funding from Johnson & Johnson Medical Companies for scientific work on bariatric surgery, and B.J.A. has received research funding from Pfizer for scientific work on PCSK9. The remaining authors have nothing to disclose.

References

1.

NCD Risk Factor Collaboration (NCD-RisC)
.
Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants
.
Lancet
.
2016
;
387
(
10026
):
1377
–
1396
.

Crossref
Search ADS
PubMed

 
2.

Kahn
SE
,
Hull
RL
,
Utzschneider
KM
 .
Mechanisms linking obesity to insulin resistance and type 2 diabetes
.
Nature
.
2006
;
444
(
7121
):
840
–
846
.

Google Scholar

Crossref
Search ADS
PubMed

 
3.

Poirier
P
,
Giles
TD
,
Bray
GA
,
Hong
Y
,
Stern
JS
,
Pi-Sunyer
FX
,
Eckel
RH
;
American Heart Association
;
Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism
.
Obesity and cardiovascular disease: Pathophysiology, evaluation, and effect of weight loss: An update of the 1997 American Heart Association scientific statement on obesity and heart disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism
.
Circulation
.
2006
;
113
(
6
):
898
–
918
.

Google Scholar

Crossref
Search ADS
PubMed

 
4.

Courcoulas
AP
,
Christian
NJ
,
Belle
SH
,
Berk
PD
,
Flum
DR
,
Garcia
L
,
Horlick
M
,
Kalarchian
MA
,
King
WC
,
Mitchell
JE
,
Patterson
EJ
,
Pender
JR
,
Pomp
A
,
Pories
WJ
,
Thirlby
RC
,
Yanovski
SZ
,
Wolfe
BM
 .
Weight change and health outcomes at 3 years after bariatric surgery among individuals with severe obesity
.
JAMA
.
2013
;
310
(
22
):
2416
–
2425
.

Google Scholar

PubMed
OpenURL Placeholder Text

 
5.

Poirier
P
,
Cornier
M-A
,
Mazzone
T
,
Stiles
S
,
Cummings
S
,
Klein
S
,
McCullough
PA
,
Ren Fielding
C
,
Franklin
BA
;
American Heart Association Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism
.
Bariatric surgery and cardiovascular risk factors: a scientific statement from the American Heart Association
.
Circulation
.
2011
;
123
(
15
):
1683
–
1701
.

Google Scholar

Crossref
Search ADS
PubMed

 
6.

Buchwald
H
,
Estok
R
,
Fahrbach
K
,
Banel
D
,
Jensen
MD
,
Pories
WJ
,
Bantle
JP
,
Sledge
I
 .
Weight and type 2 diabetes after bariatric surgery: systematic review and meta-analysis
.
Am J Med
.
2009
;
122
(
3
):
248
–
256.e5
.

Google Scholar

Crossref
Search ADS
PubMed

 
7.

Sjöström
L
,
Peltonen
M
,
Jacobson
P
,
Sjöström
CD
,
Karason
K
,
Wedel
H
,
Ahlin
S
,
Anveden
Å
,
Bengtsson
C
,
Bergmark
G
,
Bouchard
C
,
Carlsson
B
,
Dahlgren
S
,
Karlsson
J
,
Lindroos
A-K
,
Lönroth
H
,
Narbro
K
,
Näslund
I
,
Olbers
T
,
Svensson
P-A
,
Carlsson
LMS
 .
Bariatric surgery and long-term cardiovascular events
.
JAMA
.
2012
;
307
(
1
):
56
–
65
.

Google Scholar

Crossref
Search ADS
PubMed

 
8.

Heffron
SP
,
Parikh
A
,
Volodarskiy
A
,
Ren-Fielding
C
,
Schwartzbard
A
,
Nicholson
J
,
Bangalore
S
 .
Changes in lipid profile of obese patients following contemporary bariatric surgery: a meta-analysis
.
Am J Med
.
2016
;
129
(
9
):
952
–
959
.

Google Scholar

Crossref
Search ADS
PubMed

 
9.

Teslovich
TM
,
Musunuru
K
,
Smith
AV
,
Edmondson
AC
,
Stylianou
IM
,
Koseki
M
,
Pirruccello
JP
,
Ripatti
S
,
Chasman
DI
,
Willer
CJ
,
Johansen
CT
,
Fouchier
SW
,
Isaacs
A
,
Peloso
GM
,
Barbalic
M
,
Ricketts
SL
,
Bis
JC
,
Aulchenko
YS
,
Thorleifsson
G
,
Feitosa
MF
,
Chambers
J
,
Orho-Melander
M
,
Melander
O
,
Johnson
T
,
Li
X
,
Guo
X
,
Li
M
,
Shin Cho
Y
,
Jin Go
M
,
Jin Kim
Y
,
Lee
JY
,
Park
T
,
Kim
K
,
Sim
X
,
Twee-Hee Ong
R
,
Croteau-Chonka
DC
,
Lange
LA
,
Smith
JD
,
Song
K
,
Hua Zhao
J
,
Yuan
X
,
Luan
J
,
Lamina
C
,
Ziegler
A
,
Zhang
W
,
Zee
RY
,
Wright
AF
,
Witteman
JC
,
Wilson
JF
,
Willemsen
G
,
Wichmann
HE
,
Whitfield
JB
,
Waterworth
DM
,
Wareham
NJ
,
Waeber
G
,
Vollenweider
P
,
Voight
BF
,
Vitart
V
,
Uitterlinden
AG
,
Uda
M
,
Tuomilehto
J
,
Thompson
JR
,
Tanaka
T
,
Surakka
I
,
Stringham
HM
,
Spector
TD
,
Soranzo
N
,
Smit
JH
,
Sinisalo
J
,
Silander
K
,
Sijbrands
EJ
,
Scuteri
A
,
Scott
J
,
Schlessinger
D
,
Sanna
S
,
Salomaa
V
,
Saharinen
J
,
Sabatti
C
,
Ruokonen
A
,
Rudan
I
,
Rose
LM
,
Roberts
R
,
Rieder
M
,
Psaty
BM
,
Pramstaller
PP
,
Pichler
I
,
Perola
M
,
Penninx
BW
,
Pedersen
NL
,
Pattaro
C
,
Parker
AN
,
Pare
G
,
Oostra
BA
,
O’Donnell
CJ
,
Nieminen
MS
,
Nickerson
DA
,
Montgomery
GW
,
Meitinger
T
,
McPherson
R
,
McCarthy
MI
,
McArdle
W
,
Masson
D
,
Martin
NG
,
Marroni
F
,
Mangino
M
,
Magnusson
PK
,
Lucas
G
,
Luben
R
,
Loos
RJ
,
Lokki
ML
,
Lettre
G
,
Langenberg
C
,
Launer
LJ
,
Lakatta
EG
,
Laaksonen
R
,
Kyvik
KO
,
Kronenberg
F
,
König
IR
,
Khaw
KT
,
Kaprio
J
,
Kaplan
LM
,
Johansson
A
,
Jarvelin
MR
,
Janssens
AC
,
Ingelsson
E
,
Igl
W
,
Kees Hovingh
G
,
Hottenga
JJ
,
Hofman
A
,
Hicks
AA
,
Hengstenberg
C
,
Heid
IM
,
Hayward
C
,
Havulinna
AS
,
Hastie
ND
,
Harris
TB
,
Haritunians
T
,
Hall
AS
,
Gyllensten
U
,
Guiducci
C
,
Groop
LC
,
Gonzalez
E
,
Gieger
C
,
Freimer
NB
,
Ferrucci
L
,
Erdmann
J
,
Elliott
P
,
Ejebe
KG
,
Döring
A
,
Dominiczak
AF
,
Demissie
S
,
Deloukas
P
,
de Geus
EJ
,
de Faire
U
,
Crawford
G
,
Collins
FS
,
Chen
YD
,
Caulfield
MJ
,
Campbell
H
,
Burtt
NP
,
Bonnycastle
LL
,
Boomsma
DI
,
Boekholdt
SM
,
Bergman
RN
,
Barroso
I
,
Bandinelli
S
,
Ballantyne
CM
,
Assimes
TL
,
Quertermous
T
,
Altshuler
D
,
Seielstad
M
,
Wong
TY
,
Tai
ES
,
Feranil
AB
,
Kuzawa
CW
,
Adair
LS
,
Taylor
HA
, Jr ,
Borecki
IB
,
Gabriel
SB
,
Wilson
JG
,
Holm
H
,
Thorsteinsdottir
U
,
Gudnason
V
,
Krauss
RM
,
Mohlke
KL
,
Ordovas
JM
,
Munroe
PB
,
Kooner
JS
,
Tall
AR
,
Hegele
RA
,
Kastelein
JJ
,
Schadt
EE
,
Rotter
JI
,
Boerwinkle
E
,
Strachan
DP
,
Mooser
V
,
Stefansson
K
,
Reilly
MP
,
Samani
NJ
,
Schunkert
H
,
Cupples
LA
,
Sandhu
MS
,
Ridker
PM
,
Rader
DJ
,
van Duijn
CM
,
Peltonen
L
,
Abecasis
GR
,
Boehnke
M
,
Kathiresan
S
 .
Biological, clinical and population relevance of 95 loci for blood lipids
.
Nature
.
2010
;
466
(
7307
):
707
–
713
.

Google Scholar

Crossref
Search ADS
PubMed

 
10.

Abifadel
M
,
Varret
M
,
Rabès
JP
,
Allard
D
,
Ouguerram
K
,
Devillers
M
,
Cruaud
C
,
Benjannet
S
,
Wickham
L
,
Erlich
D
,
Derré
A
,
Villéger
L
,
Farnier
M
,
Beucler
I
,
Bruckert
E
,
Chambaz
J
,
Chanu
B
,
Lecerf
JM
,
Luc
G
,
Moulin
P
,
Weissenbach
J
,
Prat
A
,
Krempf
M
,
Junien
C
,
Seidah
NG
,
Boileau
C
 .
Mutations in PCSK9 cause autosomal dominant hypercholesterolemia
.
Nat Genet
.
2003
;
34
(
2
):
154
–
156
.

Google Scholar

Crossref
Search ADS
PubMed

 
11.

Lagace
TA
,
Curtis
DE
,
Garuti
R
,
McNutt
MC
,
Park
SW
,
Prather
HB
,
Anderson
NN
,
Ho
YK
,
Hammer
RE
,
Horton
JD
 .
Secreted PCSK9 decreases the number of LDL receptors in hepatocytes and in livers of parabiotic mice
.
J Clin Invest
.
2006
;
116
(
11
):
2995
–
3005
.

Google Scholar

Crossref
Search ADS
PubMed

 
12.

Seidah
NG
,
Awan
Z
,
Chrétien
M
,
Mbikay
M
 .
PCSK9: a key modulator of cardiovascular health
.
Circ Res
.
2014
;
114
(
6
):
1022
–
1036
.

Google Scholar

Crossref
Search ADS
PubMed

 
13.

Leander
K
,
Mälarstig
A
,
Van’t Hooft
FM
,
Hyde
C
,
Hellénius
ML
,
Troutt
JS
,
Konrad
RJ
,
Öhrvik
J
,
Hamsten
A
,
de Faire
U
 .
Circulating proprotein convertase subtilisin/kexin type 9 (pcsk9) predicts future risk of cardiovascular events independently of established risk factors
.
Circulation
.
2016
;
133
(
13
):
1230
–
1239
.

Google Scholar

Crossref
Search ADS
PubMed

 
14.

Costet
P
,
Cariou
B
,
Lambert
G
,
Lalanne
F
,
Lardeux
B
,
Jarnoux
AL
,
Grefhorst
A
,
Staels
B
,
Krempf
M
 .
Hepatic PCSK9 expression is regulated by nutritional status via insulin and sterol regulatory element-binding protein 1c
.
J Biol Chem
.
2006
;
281
(
10
):
6211
–
6218
.

Google Scholar

Crossref
Search ADS
PubMed

 
15.

Miao
J
,
Manthena
PV
,
Haas
ME
,
Ling
AV
,
Shin
DJ
,
Graham
MJ
,
Crooke
RM
,
Liu
J
,
Biddinger
SB
 .
Role of insulin in the regulation of proprotein convertase subtilisin/kexin type 9
.
Arterioscler Thromb Vasc Biol
.
2015
;
35
(
7
):
1589
–
1596
.

Google Scholar

Crossref
Search ADS
PubMed

 
16.

Saavedra
YG
,
Dufour
R
,
Baass
A
 .
Familial hypercholesterolemia: Pcsk9 insleu genetic variant and prediabetes/diabetes risk
.
J Clin Lipidol
.
2015
;
9
:
786
–
793
.

Google Scholar

Crossref
Search ADS
PubMed

 
17.

Bonnefond
A
,
Yengo
L
,
Le May
C
,
Fumeron
F
,
Marre
M
,
Balkau
B
,
Charpentier
G
,
Franc
S
,
Froguel
P
,
Cariou
B
;
DESIR study group
.
The loss-of-function PCSK9 p.R46L genetic variant does not alter glucose homeostasis
.
Diabetologia
.
2015
;
58
(
9
):
2051
–
2055
.

Google Scholar

Crossref
Search ADS
PubMed

 
18.

Sahebkar
A
,
Simental-Mendía
LE
,
Guerrero-Romero
F
,
Golledge
J
,
Watts
GF
 .
Effect of statin therapy on plasma proprotein convertase subtilisin kexin 9 (PCSK9) concentrations: a systematic review and meta-analysis of clinical trials
.
Diabetes Obes Metab
.
2015
;
17
(
11
):
1042
–
1055
.

Google Scholar

Crossref
Search ADS
PubMed

 
19.

Arsenault
BJ
,
Pelletier-Beaumont
E
,
Alméras
N
,
Tremblay
A
,
Poirier
P
,
Bergeron
J
,
Després
JP
 .
PCSK9 levels in abdominally obese men: association with cardiometabolic risk profile and effects of a one-year lifestyle modification program
.
Atherosclerosis
.
2014
;
236
(
2
):
321
–
326
.

Google Scholar

Crossref
Search ADS
PubMed

 
20.

Boyer
M
,
Lévesque
V
,
Poirier
P
,
Marette
A
,
Mathieu
P
,
Després
J-P
,
Larose
É
,
Arsenault
BJ
 .
Impact of a 1-year lifestyle modification program on plasma lipoprotein and PCSK9 concentrations in patients with coronary artery disease
.
J Clin Lipidol
.
2016
;
10
(
6
):
1353
–
1361
.

Google Scholar

Crossref
Search ADS
PubMed

 
21.

Piché
M-È
,
Martin
J
,
Cianflone
K
,
Bastien
M
,
Marceau
S
,
Biron
S
,
Hould
F-S
,
Poirier
P
 .
Changes in predicted cardiovascular disease risk after biliopancreatic diversion surgery in severely obese patients
.
Metabolism
.
2014
;
63
(
1
):
79
–
86
.

Google Scholar

Crossref
Search ADS
PubMed

 
22.

Plourde
C-É
,
Grenier-Larouche
T
,
Caron-Dorval
D
,
Biron
S
,
Marceau
S
,
Lebel
S
,
Biertho
L
,
Tchernof
A
,
Richard
D
,
Carpentier
AC
 .
Biliopancreatic diversion with duodenal switch improves insulin sensitivity and secretion through caloric restriction
.
Obesity (Silver Spring)
.
2014
;
22
(
8
):
1838
–
1846
.

Google Scholar

Crossref
Search ADS
PubMed

 
23.

Lakoski
SG
,
Lagace
TA
,
Cohen
JC
,
Horton
JD
,
Hobbs
HH
 .
Genetic and metabolic determinants of plasma PCSK9 levels
.
J Clin Endocrinol Metab
.
2009
;
94
(
7
):
2537
–
2543
.

Google Scholar

Crossref
Search ADS
PubMed

 
24.

Yang
S-H
,
Li
S
,
Zhang
Y
,
Xu
R-X
,
Guo
Y-L
,
Zhu
C-G
,
Wu
N-Q
,
Cui
C-J
,
Sun
J
,
Li
J-J
 .
Positive correlation of plasma PCSK9 levels with HbA1c in patients with type 2 diabetes
.
Diabetes Metab Res Rev
.
2016
;
32
(
2
):
193
–
199
.

Google Scholar

Crossref
Search ADS
PubMed

 
25.

Brouwers
MC
,
Troutt
JS
,
van Greevenbroek
MM
,
Ferreira
I
,
Feskens
EJ
,
van der Kallen
CJ
,
Schaper
NC
,
Schalkwijk
CG
,
Konrad
RJ
,
Stehouwer
CD
 .
Plasma proprotein convertase subtilisin kexin type 9 is not altered in subjects with impaired glucose metabolism and type 2 diabetes mellitus, but its relationship with non-HDL cholesterol and apolipoprotein B may be modified by type 2 diabetes mellitus: The CODAM study
.
Atherosclerosis
.
2011
;
217
(
1
):
263
–
267
.

Google Scholar

Crossref
Search ADS
PubMed

 
26.

Carswell
KA
,
Belgaumkar
AP
,
Amiel
SA
,
Patel
AG
 .
A systematic review and meta-analysis of the effect of gastric bypass surgery on plasma lipid levels
.
Obes Surg
.
2016
;
26
(
4
):
843
–
855
.

Google Scholar

Crossref
Search ADS
PubMed

 
27.

Browning
JD
,
Horton
JD
 .
Fasting reduces plasma proprotein convertase, subtilisin/kexin type 9 and cholesterol biosynthesis in humans
.
J Lipid Res
.
2010
;
51
(
11
):
3359
–
3363
.

Google Scholar

Crossref
Search ADS
PubMed

 
28.

Gencer
B
,
Montecucco
F
,
Nanchen
D
,
Carbone
F
,
Klingenberg
R
,
Vuilleumier
N
,
Aghlmandi
S
,
Heg
D
,
Räber
L
,
Auer
R
,
Jüni
P
,
Windecker
S
,
Lüscher
TF
,
Matter
CM
,
Rodondi
N
,
Mach
F
 .
Prognostic value of PCSK9 levels in patients with acute coronary syndromes
.
Eur Heart J
.
2016
;
37
(
6
):
546
–
553
.

Google Scholar

Crossref
Search ADS
PubMed

 
29.

Zhang
Y
,
Liu
J
,
Li
S
,
Xu
R-X
,
Sun
J
,
Tang
Y
,
Li
J-J
 .
Proprotein convertase subtilisin/kexin type 9 expression is transiently up-regulated in the acute period of myocardial infarction in rat
.
BMC Cardiovasc Disord
.
2014
;
14
:
192
.

Google Scholar

Crossref
Search ADS
PubMed

 
30.

Cui
CJ
,
Li
S
,
Zhu
CG
,
Sun
J
,
Du
Y
,
Zhang
Y
,
Wu
NQ
,
Guo
YL
,
Xu
RX
,
Gao
Y
,
Li
JJ
 .
Enhanced pro-protein convertase subtilisin/kexin type 9 expression by C-reactive protein through p38MAPK-HNF1α pathway in HepG2 cells
.
J Cell Mol Med
.
2016
;
20
(
12
):
2374
–
2383
.

Google Scholar

Crossref
Search ADS
PubMed

 
31.

Richard
C
,
Couture
P
,
Desroches
S
,
Benjannet
S
,
Seidah
NG
,
Lichtenstein
AH
,
Lamarche
B
 .
Effect of the Mediterranean diet with and without weight loss on surrogate markers of cholesterol homeostasis in men with the metabolic syndrome
.
Br J Nutr
.
2012
;
107
(
5
):
705
–
711
.

Google Scholar

Crossref
Search ADS
PubMed

 
32.

Cariou
B
,
Langhi
C
,
Le Bras
M
,
Bortolotti
M
,
Lê
K-A
,
Theytaz
F
,
Le May
C
,
Guyomarc’h-Delasalle
B
,
Zaïr
Y
,
Kreis
R
,
Boesch
C
,
Krempf
M
,
Tappy
L
,
Costet
P
 .
Plasma PCSK9 concentrations during an oral fat load and after short term high-fat, high-fat high-protein and high-fructose diets
.
Nutr Metab (Lond)
.
2013
;
10
(
1
):
4
.

Google Scholar

Crossref
Search ADS
PubMed

 
33.

Ruscica
M
,
Ferri
N
,
Macchi
C
,
Meroni
M
,
Lanti
C
,
Ricci
C
,
Maggioni
M
,
Fracanzani
AL
,
Badiali
S
,
Fargion
S
,
Magni
P
,
Valenti
L
,
Dongiovanni
P
 .
Liver fat accumulation is associated with circulating PCSK9
.
Ann Med
.
2016
;
48
(
5
):
384
–
391
.

Google Scholar

Crossref
Search ADS
PubMed

 
34.

Andrade-Silva
SG
,
Caranti
DA
,
Sallet
JA
,
Leal
LPFF
,
Leal
AJF
,
Dâmaso
AR
 .
Age and gender may influence the results of Roux-en-Y gastric bypass? Metabolic syndrome parameters
.
Arq Gastroenterol
.
2014
;
51
(
3
):
171
–
179
.

Google Scholar

Crossref
Search ADS
PubMed

 
35.

Veilleux
A
,
Grenier
E
,
Marceau
P
,
Carpentier
AC
,
Richard
D
,
Levy
E
 .
Intestinal lipid handling: evidence and implication of insulin signaling abnormalities in human obese subjects
.
Arterioscler Thromb Vasc Biol
.
2014
;
34
(
3
):
644
–
653
.

Google Scholar

Crossref
Search ADS
PubMed

 
36.

Levy
E
,
Ben Djoudi Ouadda
A
,
Spahis
S
,
Sane
AT
,
Garofalo
C
,
Grenier
É
,
Emonnot
L
,
Yara
S
,
Couture
P
,
Beaulieu
J-F
,
Ménard
D
,
Seidah
NG
,
Elchebly
M
 .
PCSK9 plays a significant role in cholesterol homeostasis and lipid transport in intestinal epithelial cells
.
Atherosclerosis
.
2013
;
227
(
2
):
297
–
306
.

Google Scholar

Crossref
Search ADS
PubMed

 
37.

Leblond
F
,
Seidah
NG
,
Précourt
L-P
,
Delvin
E
,
Dominguez
M
,
Levy
E
 .
Regulation of the proprotein convertase subtilisin/kexin type 9 in intestinal epithelial cells
.
Am J Physiol Gastrointest Liver Physiol
.
2009
;
296
(
4
):
G805
–
G815
.

Google Scholar

Crossref
Search ADS
PubMed

 
38.

Jahansouz
C
,
Xu
H
,
Hertzel
AV
,
Serrot
FJ
,
Kvalheim
N
,
Cole
A
,
Abraham
A
,
Luthra
G
,
Ewing
K
,
Leslie
DB
,
Bernlohr
DA
,
Ikramuddin
S
 .
Bile acids increase independently from hypocaloric restriction after bariatric surgery
.
Ann Surg
.
2016
;
264
(
6
):
1022
–
1028
.

Google Scholar

Crossref
Search ADS
PubMed

 
39.

Melone
M
,
Wilsie
L
,
Palyha
O
,
Strack
A
,
Rashid
S
 .
Discovery of a new role of human resistin in hepatocyte low-density lipoprotein receptor suppression mediated in part by proprotein convertase subtilisin/kexin type 9
.
J Am Coll Cardiol
.
2012
;
59
(
19
):
1697
–
1705
.

Google Scholar

Crossref
Search ADS
PubMed

 
40.

Du
Y
,
Li
S
,
Cui
C-J
,
Zhang
Y
,
Yang
S-H
,
Li
J-J
 .
Leptin decreases the expression of low-density lipoprotein receptor via PCSK9 pathway: linking dyslipidemia with obesity
.
J Transl Med
.
2016
;
14
(
1
):
276
.

Google Scholar

Crossref
Search ADS
PubMed

 
41.

Gauthier
M-S
,
Pérusse
JR
,
Awan
Z
,
Bouchard
A
,
Tessier
S
,
Champagne
J
,
Krastins
B
,
Byram
G
,
Chabot
K
,
Garneau
P
,
Rabasa-Lhoret
R
,
Faubert
D
,
Lopez
MF
,
Seidah
NG
,
Coulombe
B
 .
A semi-automated mass spectrometric immunoassay coupled to selected reaction monitoring (MSIA-SRM) reveals novel relationships between circulating PCSK9 and metabolic phenotypes in patient cohorts
.
Methods
.
2015
;
81
:
66
–
73
.

Google Scholar

Crossref
Search ADS
PubMed

 
Copyright © 2017 Endocrine Society
Issue Section:
Lipids and Cardiovascular
Download all slides