Keywords
peripheral arterial disease (PAD) - chronic limb-threatening ischemia (CLTI) - proprotein
convertase subtilisin/kexin type-9 (PCSK9)
Introduction
In patients with type 2 diabetes mellitus (T2DM), peripheral arterial disease (PAD)
has distinctive phenotypic characteristics compared with non-diabetic individuals
including a predisposition for infra-popliteal disease, a more severe level of disease,
and younger age of presentation.[1]
[2]
[3] PAD is often associated with coronary artery disease (CAD) and cerebrovascular disease
(CVD) in the setting of a polyvascular disease, affecting more than 200 million people
worldwide, significantly impacting quality of life, and constituting a social and
economic burden on the healthcare system.[4]
[5]
Management strategies for PAD encompass lifestyle changes, pharmacotherapy, and, in
cases of critical limb ischemia, revascularization procedures.[1]
[6]
[7] Revascularization strategies include endovascular and open surgical approaches,
with endovascular procedure recently becoming an increasingly effective treatment
option for improving prognosis and symptom relief for patients with PAD.[1]
Post revascularization, maintaining rigorous risk modification therapy is crucial
to avert complications, including the risk of restenosis and major adverse limb events
(MALEs) such as acute limb ischemia, limb-threatening ischemia needing urgent revascularization,
and major amputations.[6]
[8] Postoperative medical management aims to minimize the atherosclerotic and thrombotic
burden[6]
[9]
[10]
[11]; however, despite optimal treatment, many patients still experience adverse limb
outcomes post revascularization.[10] This highlights the necessity for identifying biomarkers that can aid in risk stratification
and represent targets to monitor response to novel therapeutic interventions beyond
traditional risk factors.
Cardiovascular complications in patients with diabetes are associated with multiple
mechanisms.
Specifically, our previous research has illustrated in patients with T2DM the significant
association between inflammation biomarkers and the risk of MALEs and major adverse
cardiac events (MACEs) post endovascular revascularization,[1]
[12]
[13] along with factors related to lipid metabolism and calcium homeostasis.[14]
[15]
[16] Cholesterol plays a key role in the formation and progression of atherosclerotic
plaques. Among the molecules influencing atherosclerosis progression and connected
with lipid metabolism, but not part of lipid particles, is the proprotein convertase
subtilisin/kexin type 9 (PCSK9). The primary role of PCSK9 in atherogenesis involves
degrading LDL receptors (LDLr), thereby elevating circulating LDL cholesterol (LDL-C)
levels.[17] Beyond this, PCSK9 is implicated in various pleiotropic and pro-inflammatory mechanisms,
which play a critical role in the development of atherosclerotic cardiovascular disease.[17] PCSK9 has direct and indirect pro-inflammatory effects mediated by interactions
with oxidized lectin-like lipoprotein-1 (LOX-1) and other scavenger receptors (SRs).[17] The secretion of PCSK9 is not limited to hepatocytes but also occurs in endothelial
cells, VSMCs, and macrophages, and is upregulated by factors like tumor necrosis factor
(TNF)-α and lipopolysaccharide (LPS).[17] Moreover, PCSK9 can induce the secretion of pro-inflammatory cytokines from macrophages,
liver cells, and a variety of other tissues, and it can regulate the expression of
Toll-like receptor (TLR)-4 and the activation of nuclear factor kappa-light-chain-enhancer
of activated B cells (NF-κB), indicating its involvement in inflammation, apoptosis,
and autophagy.[17]
The role of PCSK9 inhibitors is well established as an effective intervention for
lowering lipids and reducing cardiovascular adverse events.[18]
[19]
[20]
[21]
[22] Multiple studies have shown that in patients with diabetes, higher PCSK9 levels
are associated with indicators of cardiovascular risk, such as arterial stiffness
or carotid intima–media thickness (IMT).[23]
[24] PCSK9 levels are also associated with the presence of CAD and its severity.[25]
In a study comparing patients with and without PAD, those with PAD had higher levels
of PCSK9.[26] Moreover, in patients with PAD, elevated PCSK9 levels have been linked to a significantly
higher risk of the condition, an association that remains robust even after adjusting
for various risk factors.[26]
Given the multifaceted impact of PCSK9 on cardiovascular health, it is conceivable
that it could serve as a biomarker for the risk of atherosclerotic disease progression
and major cardiovascular events in individuals with PAD and offer a tool for tailoring
patient-specific therapeutic strategies. Thus, this prospective study investigated
the potential role of PCSK9 as a biomarker for the risk of MALE following endovascular
revascularization in patients with T2DM and PAD experiencing chronic limb-threatening
ischemia (CLTI).
Materials and Methods
Study Design
This is a prospective cohort study designed to explore the relationship between levels
of circulating PCSK9 and the occurrence of MALEs in patients with T2DM and PAD experiencing
CLTI and who have undergone endovascular revascularization. The research received
approval from the Ethics Committee of the Fondazione Policlinico Universitario A.
Gemelli IRCCS (approval number: ID 1990 13072/18), ensuring compliance with the Declaration
of Helsinki's ethical guidelines. Participation in the study was contingent upon receiving
informed consent from all enrolled patients.
Study Population and Clinical Assessment
From October 23, 2019 to October 30, 2022, 147 patients with T2DM and PAD, requiring
endovascular revascularization for CLTI, were enrolled at the Cardiovascular Internal
Medicine Unit of Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome, Italy.
To reduce selection bias, consecutive patients who met the predefined inclusion and
exclusion criteria were prospectively enrolled. All patients followed a standardized
diagnostic and therapeutic pathway, and data were collected using uniform procedures.
Eligibility for the study was determined based on the following criteria: individuals
older than 18 years with a diagnosis of T2DM for at least 1 year; an Ankle/Brachial
Index (ABI) below 0.80; ultrasound color Doppler (US) confirmation of lower-extremity
arterial stenosis exceeding 50%; classification of PAD as category 4 or 5 according
to the Rutherford classification[27]; presence of CLTI as already defined[12]; and necessity of endovascular revascularization.
Participants were excluded if they were pregnant; had chronic kidney disease with
an estimated glomerular filtration rate (eGFR) below 30 mL/min as per the Chronic
Kidney Disease Epidemiology Collaboration (CKD-EPI) formula; had undergone lower-extremity
surgical or endovascular revascularization in the preceding month; had active solid
or hematological malignancies; had undergone organ or bone marrow transplantation;
were expected to live less than 12 months; had acute infectious diseases at enrollment
or within the preceding 2 weeks; had autoimmune diseases; had liver disease classified
as Child–Pugh B or C; had known or suspected monogenic hereditary dyslipidemias; had
acquired or congenital thrombocytopenia or thrombophilia; had contraindications to
antiplatelet therapy; had known congenital bleeding disorders or acquired coagulopathies;
had contraindications to endovascular revascularization; or if the revascularization
procedure failed to address the targeted lesion.
All the subjects enrolled in the study underwent ultrasound (US) assessment. Furthermore,
US was performed to confirm the presence of severe stenosis of the lower extremity
in all the patients with an ABI of 1.40 or higher. Osteomyelitis suspicions were excluded
through radiological imaging.
Collected data included age, sex, body mass index (BMI), duration of diabetes, smoking
status, history of hypertension, hypercholesterolemia, CAD, CVD, ABI, Rutherford classification,
and results from laboratory tests. Upon enrollment, patients were on single antiplatelet
therapy, which was escalated to dual antiplatelet therapy (DAPT) for 1 month post
revascularization. All patients received statins and/or ezetimibe as part of their
lipid-lowering treatment, with no use of PCSK9 inhibitors. Post revascularization,
lipid-lowering therapy adjustments aimed for an LDL-C target of less than 55 mg/dL,
following the ESC/EAS Guidelines for dyslipidemia management.[28]
Lower-extremity Endovascular Revascularization and Follow-up
Revascularization of the lower extremities was performed through balloon angioplasty
and/or the insertion of stents, in line with methodologies detailed in previous studies.[12]
[14]
[29] All patients underwent below-the-knee (BTK) endovascular revascularization. The
procedure predominantly consisted of plain balloon angioplasty. Stent implantation
was performed only when necessary, such as in the presence of flow-limiting dissection
or significant elastic recoil after balloon angioplasty. In our cohort, only three
patients (2.0%) underwent stent placement. The procedure was deemed successful when
post-treatment arterial vessel stenosis was reduced to less than 30%. Adhering to
the Society of Interventional Radiology's criteria, no complications associated with
the endovascular procedures were observed.[30] Over a 12-month follow-up period, patients were monitored at intervals of 1, 3,
6, and 12 months following the revascularization to evaluate the occurrence of MALEs.
MALEs were identified as instances of acute limb ischemia, major vascular amputations,
and limb-threatening ischemia that required immediate revascularization.
Blood Test and Biochemical Analysis
Laboratory tests were collected at baseline, before lower-extremity revascularization,
in all the subjects enrolled in the study. Glycated hemoglobin (HbA1c), fasting glucose
(FBG), total cholesterol, LDL-C, triglycerides, and creatinine were analyzed. eGFR
was determined according to CKD-EPI formula. Serum was prepared by centrifugation
of blood samples, which was stored at −80°C until assayed. Serum levels of PCSK9 were
determined by commercially available ELISA kits (EH0251 from Fine Test, Wuhan, China)
according to their protocol. The assay was performed at our institutional laboratory
using research funds.
The precision of the measurements is demonstrated by the intra-assay and inter-assay
coefficients of variation, recorded at 3.5 and 10.5%, respectively. The assay's sensitivity
reached 0.625 ng/mL, calculated from the mean ± 3 standard deviations of the 0 standard.
For each patient, serum levels were quantified twice, and the results averaged to
ensure accuracy.
Statistical Analysis
For the power analysis and sample size calculation, we assumed an effect size (Cohen's
d) of 0.4, an α level of 0.05, and a target power of 0.8. Based on these parameters,
the required sample size was calculated to be 150. Demographic and clinical characteristics
are presented as means with standard deviations or medians with interquartile ranges
(25th–75th percentiles) for continuous data, and as counts with percentages for categorical
data.
To compare baseline characteristics of the study population, Student's t-test was used for comparing means of normally distributed continuous variables, the
chi-square test was applied for assessing associations between categorical variables,
and the Wilcoxon rank-sum (Mann-Whitney) test was used for comparing medians of non-normally
distributed continuous variables. A multivariate stepwise logistic regression was
conducted to adjust for known cardiovascular risk factors and PCSK9 levels, aiming
to identify their association with MALEs. To assess and minimize multicollinearity
among covariates, we calculated the variance inflation factor (VIF) for all variables
included in the multivariable model. Variables with critical collinearity were excluded,
and all remaining variables exhibited acceptable VIF values (<2.5), ensuring the stability
and robustness of the model. The effectiveness of PCSK9 levels in predicting MALEs
was assessed by calculating the area under the receiver-operating characteristic (ROC)
curve.
Additionally, a second predictive model was constructed that included PCSK9 levels
and cardiovascular risk factors (such as age, sex, BMI, duration of diabetes, hypertension,
hypercholesterolemia, history of CAD and CVD, smoking status, total cholesterol, LDL-C,
triglycerides, fasting blood glucose, and HbA1c) to evaluate their collective predictive
value for MALEs. The areas under the ROC curves of these models were compared using
the Roccomp function in STATA software.
All statistical analyses were conducted using STATA version 18.0 for MacOS. A p-value of less than 0.05 was considered statistically significant.
Results
Characteristics of the Study Population
In this investigation, we examined 147 individuals with T2DM and PAD, all of whom
required revascularization of the lower extremities for CLTI. The participants had
a mean age (SD) of 75.2 (± 9.0) years. Among them, 99 (67.3%) were male and 48 (32.7%)
were female. The mean duration of T2DM among the participants was 15 (4.25–30.0) years.
Active smokers were 34 (23.1%), former smokers were 77 (52.4%), and patients who never
smoked were 36 (24.5%). Hypertension was prevalent in 118 (80.3%) patients, while
135 (91.8%) suffered from hypercholesterolemia. A history of CAD was noted in 70 (47.6%)
patients, and CVD history was present in 29 (20%). The severity of PAD was classified
as Rutherford category 4 in 62 (42.2%) patients and category 5 in 85 (57.8%) patients.
The average level of LDL-C was 68.0 mg/dL (49.0–86.0), and the mean HbA1c level was
6.9% (6.2–8.0). The mean circulating levels of PCSK9 stood at 379.1 ng/mL (± 105.6).
[Table 1] provides a detailed overview of the demographic and clinical characteristics of
the study population.
Table 1
Demographic characteristics and clinical data of the study cohort at baseline
|
Number of patients
|
147
|
|
Men/female, n
|
99:48
|
|
Age, years ± SD
|
75.2 ± 9.0
|
|
Diabetes duration, years (IQR)
|
15 (4.25–30.0)
|
|
BMI, kg/m2 (IQR)
|
25.6 (23.2–28.6)
|
|
Smoking (current), n (%)
|
34 (23.1)
|
|
Smoking (former), n (%)
|
77 (52.4)
|
|
Never smoked, n (%)
|
36 (24.5)
|
|
Hypertension, n (%)
|
118 (80.3)
|
|
Hypercholesterolemia, n (%)
|
135 (91.8)
|
|
CAD, n (%)
|
70 (47.6)
|
|
CVD, n (%)
|
29 (20.0)
|
|
Insulin, n (%)
|
64 (43.5)
|
|
Oral antidiabetics, n (%)
|
70 (47.6)
|
|
Statins, n (%)
|
105 (71.4)
|
|
Ezetimibe, n (%)
|
48 (32.7)
|
|
ACEi/ARB, n (%)
|
86 (58.5)
|
|
Other antihypertensive, n (%)
|
68 (46.3)
|
|
Aspirin, n (%)
|
85 (57.8)
|
|
Clopidogrel, n (%)
|
44 (29.9)
|
|
Low-dose rivaroxaban, n (%)
|
1 (0.7)
|
|
ABI (IQR)
|
0.39 (0.33–0.45)
|
|
Rutherford II-4, n (%)
|
62 (42.2)
|
|
Rutherford III-5, n (%)
|
85 (57.8)
|
|
Stenting, n (%)
|
3 (2.0)
|
|
HbA1c, % (IQR)
|
6.9 (6.2–8.0)
|
|
FBG, mg/dL (IQR)
|
120.5 (96.7–150.0)
|
|
Total cholesterol, mg/dL (IQR)
|
127.5 (109.5–152.0)
|
|
LDL cholesterol, mg/dL (IQR)
|
68.0 (49.0–86.0)
|
|
Non-HDL cholesterol, mg/dL (IQR)
|
90.0 (71.0–111.0)
|
|
Triglycerides, mg/dL (IQR)
|
105.0 (81.0–136.5)
|
|
Creatinine, mg/dL (IQR)
|
1.0 (0.8–1.5)
|
|
eGFR, mL/min/1.73 m2 (IQR)
|
85.8 (68.9–93.7)
|
|
PCSK9, ng/mL ± SD
|
379.1 ± 105.6
|
Abbreviations: ABI, Ankle Brachial Index; ACEi, Angiotensin-Converting Enzyme inhibitor;
ARB, Angiotensin II Receptor Blocker; BMI, body mass index; CAD, coronary artery disease;
CVD, cerebrovascular disease; eGFR, estimated glomerular filtration rate; FBG, fasting
blood glucose; HbA1c, glycated hemoglobin; PCSK9, proprotein convertase subtilisin/kexin
type 9.
Note: The data are reported as the means ± standard deviations or median (interquartile
range, IQR, 25–75) for continuous variables and as numbers (percentages) for categorical
variables.
Circulating PCSK9 Levels and Incidence of MALEs during the Follow-up Period after
Lower-extremity Revascularization
During the 12-month follow-up period, 53 patients had a MALE after lower-extremity
revascularization. No differences were observed among patients with and without MALEs
regarding sex (p = 0.40), diabetes duration (p = 0.10), BMI (p = 0.77), active smoking habit (p = 0.76), history of high blood pressure (p = 0.27), hypercholesterolemia (p = 0.14), history of CAD (p = 0.54), history of CVD (p = 0.12), LDL-C levels (p = 0.23), ABI (p = 0.34), and eGFR (p = 0.35). No significant differences were observed in the use of insulin, oral antidiabetic
drugs, statins, ezetimibe, ACE inhibitors/ARBs, or antithrombotic therapies (aspirin,
clopidogrel, low-dose rivaroxaban) between patients with and without MALEs.
Interestingly, patients with MALEs were younger than patients without MALEs (p < 0.01). Moreover, patients with MALEs had a more severe PAD disease, presenting in
the 74% of case with Rutherford 5 category (p < 0.01) and higher levels of HbA1c (6.8 [6.2–7.8] vs. 7.5 [6.5–8.5], p < 0.01).
Circulating PCSK9 levels were higher in patients with MALEs compared with those without
MALE (410.5 ± 112.7 ng/mL vs. 360.6 ± 97.2 ng/mL, p < 0.01; [Fig. 1]). A violin plot was used to visualize the distribution and density of PCSK9 levels
across groups, with clear separation between the two. The complete characteristics
of the population with and without MALEs are described in [Table 2].
Fig. 1 Circulating PCSK9 levels in patients with and without major adverse limb events (MALEs).
The violin plot displays the distribution, median, and interquartile range (IQR) of
serum PCSK9 concentrations in patients stratified by MALE status. Patients with MALEs
showed significantly higher PCSK9 levels compared with those without MALEs (** indicates
p < 0.01). The plot also illustrates the density of values within each group, providing
a visual estimate of the distribution pattern.
Table 2
Demographic and clinical data of study participants without or with MALE
|
No MALE (n = 94)
|
With MALE (n = 53)
|
p-value
|
|
Men/female, n
|
61:33
|
38:15
|
0.40
|
|
Age, years ± SD
|
76.7 ± 8.6
|
72.6 ± 9.2
|
<0.01
|
|
Diabetes duration, years (IQR)
|
14.0 (2.0–25.0)
|
20.0 (7.2–30.0)
|
0.10
|
|
BMI, kg/m2 (IQR)
|
25.6 (23.4–28.7)
|
24.9 (23.1–28.4)
|
0.77
|
|
Smoking (current), n (%)
|
21 (22)
|
13 (25)
|
0.76
|
|
Smoking (former), n (%)
|
47 (50.0)
|
30 (57)
|
0.44
|
|
Never smoked, n (%)
|
26 (28)
|
10 (19)
|
0.23
|
|
Hypertension, n (%)
|
78 (83.0)
|
40 (75)
|
0.27
|
|
Hypercholesterolemia, n (%)
|
84 (89)
|
51 (96)
|
0.14
|
|
CAD, n (%)
|
43 (46)
|
27 (51)
|
0.54
|
|
CVD, n (%)
|
15 (16)
|
14 (27)
|
0.12
|
|
Insulin, n (%)
|
26 (49.1)
|
38 (40.4)
|
0.40
|
|
Oral antidiabetics, n (%)
|
49 (52.7)
|
21 (39.6)
|
0.18
|
|
Statins, n (%)
|
40 (75.5)
|
65 (69.1)
|
0.53
|
|
Ezetimibe, n (%)
|
21 (39.6)
|
27 (28.7)
|
0.24
|
|
ACEi/ARB, n (%)
|
32 (60.4)
|
54 (57.4)
|
0.86
|
|
Other antihypertensive, n (%)
|
42 (44.7)
|
26 (49.1)
|
0.73
|
|
Aspirin, n (%)
|
34 (64.2)
|
51 (54.3)
|
0.32
|
|
Clopidogrel, n (%)
|
19 (35.8)
|
25 (26.6)
|
0.32
|
|
Low-dose rivaroxaban, n (%)
|
0 (0)
|
1 (1.1)
|
1.00
|
|
ABI, (IQR)
|
0.4 (0.33–0.45)
|
0.38 (0.33–0.45
|
0.34
|
|
Rutherford II-4, n (%)
|
48 (51)
|
14 (26)
|
<0.01
|
|
Rutherford III-5, n (%)
|
46 (49)
|
39 (74)
|
<0.01
|
|
Stenting, n (%)
|
3 (3.2)
|
0 (0)
|
0.55
|
|
HbA1c, % (IQR)
|
6.8 (6.2–7.8)
|
7.5 (6.5–8.5)
|
<0.01
|
|
FBG, mg/dL (IQR)
|
120.0 (95.0–146.0)
|
123.0 (100.5–159.0)
|
0.18
|
|
Total cholesterol, mg/dL (IQR)
|
130.5 (109.5–157.5)
|
125.5 (109.5–147.2)
|
0.47
|
|
LDL cholesterol, mg/dL (IQR)
|
70.0 (50.5–89.0)
|
60.0 (45.5–78.0)
|
0.23
|
|
Non-HDL cholesterol, mg/dL (IQR)
|
94.0 (70.0–115.0)
|
86.0 (71.5–98.0)
|
0.34
|
|
Triglycerides, mg/dL (IQR)
|
103.5 (76.5–139.5)
|
107.0 (91.0–132.0)
|
0.47
|
|
Creatinine, mg/dL (IQR)
|
1.0 (0.8–1.5)
|
1.0 (0.9–1.8)
|
0.18
|
|
eGFR, mL/min/1.73 m2 (IQR)
|
86.2 (73.6–94.0)
|
84.3 (64.1–92.9)
|
0.35
|
|
PCSK9, ng/mL ± SD
|
360.6 ± 97.2
|
410.5 ± 112.7
|
<0.01
|
Abbreviations: ABI, Ankle Brachial Index; MALE, major adverse limb event; BMI, body
mass index; CAD, coronary artery disease; CVD, cerebrovascular disease; ACEi, Angiotensin-Converting
Enzyme inhibitor; ARB, Angiotensin II Receptor Blocker; eGFR, estimated glomerular
filtration rate; FBG, fasting blood glucose; HbA1c, glycated hemoglobin; PCSK9, proprotein
convertase subtilisin/kexin type 9.
Note: The data are reported as the means ± standard deviations or median (interquartile
range 25–75) for continuous variables and as numbers (percentages) for categorical
variables. Statistical tests were performed with Student's t-test, chi-square test or Wilcoxon rank-sum (Mann-Whitney) test, when appropriate.
An ROC curve was elaborated to predict the incidence of MALEs based on circulating
PCSK9 levels. The analysis yielded an area under the curve (AUC) of 0.629 (95% CI
0.530, 0.728), indicating modest but statistically meaningful discriminatory power
in identifying patients at higher risk of adverse limb events ([Fig. 2]). A second model was elaborated to predict the incidence of MALEs based on serum-circulating
PCSK9 levels and cardiovascular risk factors (age, sex, diabetes duration, BMI, smoking
status, hypertension, previous CAD and CVD history, total cholesterol, LDL-C, triglycerides,
FBG, HbA1c). The comparison of ROC curves between the baseline model with only cardiovascular
risk factors and the second model including circulating PCSK9 levels and cardiovascular
risk factors demonstrated that including PCSK9 significantly improved (p < 0.05) the prediction of MALEs, with an area under the ROC curve of 0.5889 (95%
CI 0.461, 0.715) for the baseline model and 0.7631 (95% CI 0.662, 0.863) for the model
including PCSK9 ([Fig. 3]). This result highlights the incremental value of PCSK9 in risk stratification beyond
established clinical variables.
Fig. 2 Receiver operating characteristic (ROC) curve for the prediction of major adverse
limb events (MALEs) based on circulating PCSK9 levels. The true-positive rate (sensitivity)
is plotted as a function of the false-positive rate (1 - specificity). The area under
the curve (AUC) is 0.629.
Fig. 3 Comparison of receiver operating characteristic (ROC) curves for the prediction of
major adverse limb events (MALEs). The true-positive rate (sensitivity) is plotted
as a function of the false-positive rate (1 - specificity). The baseline model including
traditional cardiovascular risk factors shows an area under the curve (AUC) of 0.589.
The addition of circulating PCSK9 levels significantly improved the model's discriminative
ability (AUC = 0.763, p < 0.05).
After adjustment for traditional cardiovascular risk factors, a multivariable analysis
was elaborated, showing that Rutherford 4 category (p < 0.01) and circulating PCSK9 levels (p < 0.05) were independent risk factors for MALEs in patients with PAD and CLTI requiring
lower-extremity revascularization. The results are shown in [Table 3] which reports the regression coefficients, standard errors, p-values, and 95% confidence intervals for each variable included.
Table 3
Multivariable logistic regression for MALE
|
MALE
|
Coef.
|
St.Err.
|
t-value
|
p-value
|
[95% confidence
|
interval]
|
Sig
|
|
Age
|
−0.01
|
0.01
|
−1.66
|
0.1
|
−0.02
|
0
|
|
|
Male sex
|
0.04
|
0.11
|
0.34
|
0.73
|
−0.19
|
0.26
|
|
|
BMI
|
0
|
0.01
|
−0.19
|
0.85
|
−0.02
|
0.02
|
|
|
Diabetes duration
|
0
|
0
|
0.97
|
0.33
|
0
|
0.01
|
|
|
Hypertension
|
−0.22
|
0.12
|
−1.87
|
0.06
|
−0.46
|
0.01
|
|
|
Hypercholesterolemia
|
0.12
|
0.18
|
0.66
|
0.51
|
−0.24
|
0.47
|
|
|
CAD
|
−0.09
|
0.1
|
−0.89
|
0.38
|
−0.3
|
0.11
|
|
|
CVD
|
0.19
|
0.13
|
1.50
|
0.14
|
−0.06
|
0.45
|
|
|
Smoking (current)
|
0.15
|
0.15
|
1.01
|
0.31
|
−0.14
|
0.44
|
|
|
Smoking (former)
|
0.19
|
0.14
|
1.39
|
0.17
|
−0.08
|
0.46
|
|
|
ABI
|
−0.3
|
0.71
|
−0.42
|
0.67
|
−1.71
|
1.11
|
|
|
Rutherford II-4
|
−0.26
|
0.1
|
−2.66
|
0.01
|
−0.46
|
−0.07
|
**
|
|
LDL cholesterol
|
0
|
0
|
−1.01
|
0.31
|
−0.01
|
0
|
|
|
FBG
|
0
|
0
|
0.03
|
0.98
|
0
|
0
|
|
|
HbA1c
|
0.06
|
0.05
|
1.19
|
0.24
|
−0.04
|
0.17
|
|
|
Creatinine
|
−0.02
|
0.04
|
−0.48
|
0.64
|
−0.11
|
0.07
|
|
|
eGFR
|
−0.01
|
0
|
−1.85
|
0.07
|
−0.01
|
0
|
|
|
PCSK9
|
0
|
0
|
2.04
|
0.04
|
0
|
0
|
*
|
|
Constant
|
1.02
|
0.83
|
1.22
|
0.23
|
−0.64
|
2.68
|
|
|
Mean dependent var
|
0.36
|
SD dependent var
|
0.48
|
|
|
R-squared
|
0.32
|
Number of obs.
|
104
|
|
|
F-test
|
2.23
|
Prob > F
|
0.01
|
|
|
Akaike crit. (AIC)
|
139.77
|
Bayesian crit. (BIC)
|
190.01
|
|
Abbreviations: ABI, Ankle Brachial Index; BMI, body mass index; CAD, coronary artery
disease; CVD, cerebrovascular disease; eGFR, estimated glomerular filtration rate;
FBG, fasting blood glucose; HbA1c, glycated hemoglobin; MALE, major adverse limb event;
PCSK9, proprotein convertase subtilisin/kexin type 9.
Notes: Multivariable logistic regression analysis for the prediction of major adverse
limb events (MALEs).
The table reports regression coefficients (Coef.), standard errors (St.Err.), p-values, and 95% confidence intervals (CI) for each variable included in the model.
Variables with statistically significant associations are marked (*p < 0.05; **p < 0.01).
In a subgroup analysis limited to patients with Rutherford category 5 (n = 85), circulating PCSK9 levels remained significantly associated with the occurrence
of MALEs in a multivariate logistic regression model adjusted for major cardiovascular
risk factors (p = 0.03) ([Table 4]).
Table 4
Multivariable logistic regression for MALE in Rutherford III-5 patients
|
Coef.
|
St.Err.
|
t-value
|
p-value
|
[95% confidence
|
interval]
|
Sig
|
|
Age
|
0.923
|
0.039
|
−1.90
|
0.057
|
0.85
|
1.003
|
|
|
Male sex
|
1.259
|
1.158
|
0.25
|
0.802
|
0.208
|
7.634
|
|
|
BMI
|
1.052
|
0.087
|
0.61
|
0.54
|
0.895
|
1.237
|
|
|
Diabetes duration
|
1.011
|
0.029
|
0.36
|
0.717
|
0.954
|
1.07
|
|
|
Hypertension
|
0.089
|
0.11
|
−1.96
|
0.051
|
0.008
|
1.006
|
|
|
Hypercholesterolemia
|
3.213
|
4.451
|
0.84
|
0.4
|
0.213
|
48.548
|
|
|
CAD
|
0.519
|
0.421
|
−0.81
|
0.418
|
0.106
|
2.544
|
|
|
CVD
|
7.962
|
9.105
|
1.81
|
0.07
|
0.847
|
74.89
|
|
|
Smoking (current)
|
2.515
|
2.843
|
0.82
|
0.415
|
0.274
|
23.066
|
|
|
Smoking (former)
|
4.986
|
5.232
|
1.53
|
0.126
|
0.638
|
38.988
|
|
|
ABI
|
0.091
|
0.532
|
−0.41
|
0.683
|
0
|
9140.36
|
|
|
LDL cholesterol
|
1.001
|
0.014
|
0.06
|
0.951
|
0.974
|
1.028
|
|
|
FBG
|
0.999
|
0.009
|
−0.12
|
0.907
|
0.982
|
1.017
|
|
|
HbA1c
|
1.514
|
0.652
|
0.96
|
0.336
|
0.651
|
3.522
|
|
|
Creatinine
|
1.083
|
0.31
|
0.28
|
0.782
|
0.617
|
1.898
|
|
|
eGFR
|
0.972
|
0.018
|
−1.52
|
0.128
|
0.937
|
1.008
|
|
|
PCSK9
|
1.01
|
0.005
|
2.19
|
0.029
|
1.001
|
1.019
|
*
|
|
Constant
|
1.564
|
9.77
|
0.07
|
0.943
|
0
|
324,947.9
|
|
|
Mean dependent var
|
0.469
|
SD dependent var
|
0.503
|
|
Pseudo r-squared
|
0.296
|
Number of obs.
|
64
|
|
Chi-square
|
26.170
|
Prob > chi2
|
0.071
|
|
Akaike crit. (AIC)
|
98.303
|
Bayesian crit. (BIC)
|
137.163
|
Abbreviations: ABI, Ankle Brachial Index; BMI, body mass index; CAD, coronary artery
disease; CVD, cerebrovascular disease; eGFR, estimated glomerular filtration rate;
FBG, fasting blood glucose; HbA1c, glycated hemoglobin; MALE, major adverse limb event;
PCSK9, proprotein convertase subtilisin/kexin type 9.
Notes: Multivariable logistic regression analysis for major adverse limb events (MALEs)
in patients classified as Rutherford category III-5.
The table reports regression coefficients (Coef.), standard errors (St.Err.), p-values, and 95% confidence intervals (CI) for each variable included in the model.
In this subgroup analysis, PCSK9 remained significantly associated with MALEs (*p < 0.05).
Discussion
In patients with T2DM and PAD undergoing endovascular revascularization for CLTI,
we found that higher baseline circulating PCSK9 levels were independently associated
with the occurrence of MALEs during follow-up. PCSK9 levels were also higher in younger
patients and correlated with disease severity, in line with previous studies demonstrating
similar patterns, particularly in coronary disease.[25] The link between diabetes and PAD remains a major health issue due to their combined
vascular burden.[31]
We have already shown a relationship between the biomarker of inflammation and risk
of adverse cardiovascular outcomes in patients with T2DM and CLTI, who underwent lower-limb
revascularization.[1]
[12] Interestingly, it has been demonstrated that elevated PCSK9 levels are associated
with being a marker of subclinical atherosclerosis in patients with T2DM.[23] In addition, it was shown that increased PCSK9 levels corresponded to a significant
increase in high-sensitivity C-reactive protein (hs-CRP), fibrinogen, and white blood
cells (WBC), and a reduction in eGFR.[23]
Although several previous evidence highlights a strong association between PCSK9 and
cardiovascular risk, a correlation between circulating PCSK9 and adverse limb events
after revascularization in PAD patients has not yet been evaluated. In our study,
we found that the association between PCSK9 concentrations and MALEs persisted even
after adjusting for traditional cardiovascular risk factors such as age, BMI, smoking
habits, hypertension, blood lipids, glycemic control, and renal function, confirming
PCSK9 as an independent risk factor for vascular events. In this context, we also
evaluated non-HDL cholesterol levels, a broader marker of atherogenic burden. However,
non-HDL cholesterol did not significantly differ between patients with and without
MALEs, further supporting the hypothesis that conventional lipid markers may not fully
account for residual limb risk in this population. Furthermore, in a subgroup analysis
restricted to Rutherford category 5 patients, PCSK9 levels remained independently
associated with MALEs after adjustment for major cardiovascular risk factors. This
finding reinforces the role of PCSK9 as a robust predictor of adverse limb outcomes,
even in patients with more advanced and homogeneous disease severity. In a large prospective
cohort study, Leander et al demonstrated that higher baseline PCSK9 levels were independently
associated with increased risk of various cardiovascular events, even in the absence
of elevated LDL-C.[32] This finding is in line with our result. Indeed, in our cohort, there were no difference
in terms of LDL-C levels among patients with and without MALEs.
The importance of PCSK9 levels as a key biomarker for diabetic vascular disease is
supported by the findings of studies performed in individuals without diabetes. Ridker
and colleagues in a nested case–control prospective study conducted in a cohort of
healthy American women found that baseline circulating PCSK9 did not correlate with
first cardiovascular events.[33] Studies in healthy subjects and patients with diabetes with unknown vascular disease
are not entirely discordant with our study findings, or with findings of other multiple
studies revealing the association of PCSK9 and cardiovascular disease. Findings should
be interpreted as a plausible population-based evidence of the role of PCSK9 in diabetic
patients as a determinant of vascular disease progression and as a biomarker of disease
severity. Our study was conducted among patients with T2DM undergoing lower-extremity
revascularization, representing a later stage in the natural progression of diabetic
vascular disease. The hypothesis of temporal association between PCSK9 and vascular
disease is further supported by findings of multiple observational and interventional
studies establishing the role of PCSK9 inhibitors in reducing the risk of acute cardiovascular
events in people with already known atherosclerotic cardiovascular disease (ASCVD).[19]
[20]
[21] Results from the classification analysis model in our study further support the
hypothesis that PCSK9 biomarker level monitoring is particularly important in later
stages of the peripheral vascular disease. ROC curve analysis showed that PCSK9 maintained
its relevance as a predictive biomarker for MALEs even after adjustment for established
cardiovascular risk factors. Although the discriminatory capacity of PCSK9 alone was
limited, its clinical utility emerges when used in combination with traditional risk
markers. In our cohort, adding PCSK9 to the multivariable model significantly improved
its predictive accuracy, reinforcing the potential role of PCSK9 as a valuable adjunctive
biomarker for risk stratification in T2DM patients with CLTI undergoing revascularization.
Multiple biological models support the predictive value of PCSK9 levels after revascularization
as noted in the study, and the potential therapeutic role of PCSK9 inhibition to further
reduce MALEs after revascularization in patients with diabetic vascular disease. PCSK9
is involved in inflammatory and thrombosis processes which could contribute to acute
events after revascularization.[17] Recently, Shin and colleagues demonstrated that PCSK9 itself enhanced inflammation
directly and independently from LDL metabolism, through a mechanism involving adenylyl
cyclase-associated protein 1 (CAP1), spleen tyrosine kinase (Syk), and protein kinase
C delta (PKCδ). Through the CAP1-Syk-PKCδ pathway, PCSK9 was able to induce NF-κB
and inflammatory genes.[34] It increased the mRNA levels of pro-inflammatory cytokines and adhesion molecules,
in particular TNF-α, IL − 1β, IL-6, VCAM1, ICAM1, and SELE, and scavenger receptors,
like TLR-4 and LOX-1,[34] which are major mediators of LDL-C uptake by macrophages in the process of atherosclerosis.[17] Cheng et al found that higher circulating PCSK9 levels were associated with increased
necrotic core content in coronary plaques, independent of LDL-C, supporting a direct
role of PCSK9 in plaque inflammation and instability.[35] Another key biological pathway, further supporting the association of PCSK9 and
MALEs after revascularization, is the effect of PCSK9 in platelet activation and aggregation,[36] enhancing thrombosis in a phenomenon that could contribute to acute adverse vascular
events in patients with PAD undergoing revascularization.[10]
Taken together, our findings provide crucial insights into the potential of PCSK9
as a biomarker for vascular complications, emphasizing the need for targeted management
strategies in high-risk populations. The implications of the study are 2-fold. First,
it underscores the importance of rigorous cardiovascular risk assessment and management
in patients with T2DM and PAD, incorporating PCSK9 levels as part of the evaluation
process. This approach could enhance the predictive accuracy for adverse outcomes,
enabling clinicians to tailor interventions more effectively. Second, the findings
suggest and advocate for the integration of PCSK9 inhibitors into the therapeutic
arsenal for PAD in all stages of the disease, including patients undergoing revascularization.
PCSK9 biomarker level monitoring should be considered as a therapeutic intervention
beyond standard management of traditional cardiovascular risk factors.
The prospective design of our study and the rigorous assessment of PCSK9 levels and
cardiovascular outcomes provide a robust framework for evaluating the biomarker's
predictive value even in patients with an advanced phenotypic expression of diabetic
vascular disease. Yet we acknowledge significant limitations. It was a single-center
study with intrinsic confounding factors. A further limitation of our study is the
absence of detailed procedural data, including lesion characteristics, type of devices
used, final angiographic results, and skin perfusion pressure measurements. However,
all patients underwent BTK revascularization using a standardized endovascular approach,
and stent implantation was limited to only three patients (2.0%), which precluded
any meaningful subgroup analysis. Although these data could have provided additional
insights, the uniformity of the anatomical site and technique partially mitigates
the potential impact of this limitation. In addition, a small sample size may limit
generalizability of the results as compared with other population-based studies evaluating
the role of PCSK9 as a biomarker at the population-based levels. However, our study
is one of the largest prospective cohorts specifically designed to study the clinical
and biomarker determinants of MALEs after revascularization, an understudied population
exposed to an event thought to have distinctive and poorly understood pathophysiological
characteristics that may lead to poor outcomes despite optimal medical care. In this
context, the limitations of the study further highlight the importance of future research
focusing on multicenter trials to validate the role of PCSK9 not only in patients
with T2DM undergoing revascularization, but also across more demographically diverse
populations and other types of health care settings.
In conclusion, our study highlights the significant association between PCSK9 levels
and the risk of MALEs in patients with T2DM and PAD undergoing revascularization for
CLTI. Findings of this study underscore the potential role of PCSK9 as a predictive
biomarker and therapeutic target for personalized and effective management strategies
beyond optimal management of traditional cardiovascular risk factors.
What is known about this topic?
-
In patients with diabetes, peripheral arterial disease (PAD) is linked to major adverse
limb events (MALEs) and adverse cardiovascular outcomes.
-
Patients with PAD have higher PCSK9 levels, and elevated levels correlate with an
increased risk of PAD, independent of other risk factors.
What does this paper add?
