Serum cFAS Content Correlates With Incidence of Peripheral Arterial Disease

Visual Abstract

Highlights

• •PAD lacks reliable serum biomarkers for diagnosis, which creates challenges in early detection and disease stratification. Our study identifies cFAS as a promising, independent biomarker for PAD and CLTI.
• •Patients with PAD or CLTI exhibited significantly higher serum cFAS levels compared with individuals without disease, supporting a strong association between cFAS and atherosclerotic pathology.
• •Optimal cFAS cutoff values distinguished between those with and without PAD or CLTI, and further separated PAD from CLTI cases, indicating possible utility for disease staging.
• •These findings position cFAS as a serum-based diagnostic tool that could improve PAD detection and enhance risk stratification strategies to guide clinical decision-making.

Summary

There are currently no reliable serum biomarkers to aid in the diagnosis of peripheral artery disease (PAD). We hypothesized that circulating fatty acid synthase (cFAS) can be an independent diagnostic biomarker for PAD. Serum cFAS and demographics were compared for patients with and without PAD or chronic limb threatening ischemia (CLTI). Patients with PAD or CLTI had significantly higher serum cFAS content. We observed optimal cutoffs for cFAS in distinguishing between individuals with and without PAD or CLTI. Our study demonstrates that cFAS is an independent serum-based diagnostic biomarker for PAD, can distinguish between patients with PAD vs CLTI, and may predict disease severity.

Peripheral artery disease (PAD) affects over 230 million people worldwide, including 8.5 million in the United States alone.1, 2, 3 Managing PAD in the United States imposes an annual cost exceeding $20 billion, placing a substantial burden on the health care system.^4,5 Individuals with PAD face an elevated risk of polyvascular complications, including myocardial infarction and stroke, which lead to increased morbidity and mortality.^1,2,6 The majority of individuals with PAD are asymptomatic and often only receive a diagnosis after progressing to disabling symptoms.^7,8 Given that only 11% of patients present with “classical” claudication symptoms,⁷ and up to 25% may advance to severe disease stages, such as chronic limb-threatening ischemia (CLTI),³ improved early detection strategies are crucial. Despite the strong association between PAD and high-risk atherosclerotic profiles, individuals with undiagnosed PAD are less likely to receive risk factor modification and preventive therapies.^7,8 Evidence is mounting that enhanced early diagnosis of PAD in high-risk populations can mitigate disease progression and related complications.9, 10, 11

Current clinical guidelines emphasize the importance of assessing atherosclerotic cardiovascular disease (ASCVD) risk using serum low-density lipoprotein (LDL) levels and tools like the ASCVD 10-year risk calculator to estimate patient cardiovascular risk profiles.⁹ Although LDL correlates with cardiac disease progression, studies have yet to establish its association with PAD severity, and it has not been shown that statin therapy can reduce the risk of major lower-extremity amputations resulting from PAD or CLTI.12, 13, 14 The ankle brachial index (ABI) remains the most commonly used tool for PAD diagnosis^15,16; however, both the U.S. Preventive Services Task Force and 2016 American Heart Association (AHA)/American College of Cardiology (ACC) guidelines highlight insufficient evidence supporting the reliability of ABIs as a screening test for asymptomatic patients.^2,17 Moreover, ABI results can be falsely elevated in populations such as those with diabetes or end-stage renal disease, further limiting its accuracy.^7,15,18,19 Despite these limitations, ABI remains the primary screening tool for PAD, underscoring the need for more reliable and accessible diagnostic options.^7,15,16

Fatty acid synthase (FAS) is a multifunctional enzyme that catalyzes the biosynthesis of fatty acids, which are vital for cellular membrane integrity and secondary signaling functions across nearly all life forms.^20,21 Recently, a circulating serum form of fatty acid synthase (cFAS) was identified in individuals with an elevated atherosclerotic disease burden.^22,23 In an initial cohort of patients with chronic limb-threatening ischemia (CLTI), cFAS emerged as an independent risk factor for disease severity, irrespective of diabetes status or smoking history.²³ Further evidence suggests that cFAS is not merely a byproduct but may actively contribute to the pathogenesis of atherosclerosis.^24,25 Given these observations, we investigated whether cFAS could serve as a sensitive serum biomarker for detecting PAD across varying levels of disease severity.

Methods

Patient cohort

We conducted a retrospective review of individuals who participated in the vascular biobank over a 9-year period (2014-2023). Participants were categorized as healthy control subjects without PAD, individuals with PAD, or individuals with CLTI, based on the ABI and Rutherford score.^3,26 Control participants were screened by detailed clinical history and bilateral ABI measurement. Only individuals with ABI ≥0.90 in both limbs and Rutherford class 0 were included. Patients were excluded if they had been included in prior published studies or had a history of stage 4 or 5 chronic kidney disease (CKD), alcohol abuse, or advanced liver disease (Figure 1). Demographic data collected included age at the time of serum sampling, sex, body mass index, race/ethnicity, and smoking status (prior/current). Medical history, medication use, and laboratory values were obtained from clinical chart reviews. To calculate the Framingham Risk Score,²⁷ available patient demographics were entered into the 2018 Prevention Guidelines CV Risk Calculator.^9,28 Patient values outside the calculator’s parameters were rounded to the nearest valid value (eg, age <40 years was rounded up to 40 years, and triglycerides <130 mg/dL was rounded up to 130 mg/dL).

Figure 1.

Flowchart of Study Patients

Patients were selected for the study from an initial pool of 1,081 patients in our vascular biobank. A total of 734 patients were excluded for reasons including lack of serum samples (n = 198), presence of other significant vascular disease (n = 140), prior inclusion in other studies (n = 100), unverified peripheral artery disease (PAD) status (n = 152), advanced chronic kidney disease (CKD) (stage 4/5; n = 54), history of alcohol abuse (n = 35), repeat patients (n = 28), anticoagulation use without PAD (n = 10), smoking history without PAD (n = 12), and cardiovascular disease without PAD (n = 5). The final cohort included 347 patients, categorized as 34 healthy control subjects without PAD, 164 with PAD, and 149 with chronic limb threatening ischemia (CLTI).

Blood collection and processing

Intravenous whole blood samples were collected from consenting individuals who were fasting for at least 6 hours before a planned elective surgery. As previously described, whole blood samples were collected in red- and green-topped vacutainer tubes, and immediately processed in the laboratory with centrifugation to isolate serum and plasma components.²⁹ Serum and plasma were then aliquoted into 100 μL fractions and stored at −80 °C for future analytical use.

Serum and plasma analysis

As previously described, serum aliquots were used to measure cFAS with a commercially available ELISA (Aviva Systems Biology).22, 23, 24 To account for variations in the duration of fasting prior to surgery, total protein levels were determined via Bradford assay and used to normalize serum cFAS concentrations. Plasma samples were analyzed at the Washington University Diabetes Research Center Core Laboratory for Clinical Studies for measurement of total cholesterol, triglycerides, direct high-density lipoprotein (HDL), and LDL.

Statistical analysis

Area under the receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance of cFAS. The area under the curve (AUC) with 95% CIs was calculated using DeLong’s method as a measure of the biomarker’s ability to discriminate between groups. The optimal cutoff point was determined by maximizing Youden’s index (J = sensitivity + specificity − 1). At this threshold, sensitivity and specificity with 95% CIs were reported. AUC values were interpreted as follows: 0.7 to 0.8 as acceptable, 0.8 to 0.9 as excellent, and >0.9 as outstanding. Area under the receiver-operating characteristic curve analyses were conducted to determine the optimal cutoff points for cFAS levels in distinguishing between different groups of patients: those who are healthy control subjects, those with PAD, and those with CLTI. Multivariable regressions were built to measure the independent effect of cFAS threshold on patient group classifications. Candidate variables with univariable P < 0.15 were entered into a multivariable logistic regression using backward regression to maximize Akaike’s information criterion. Categorical variables were summarized as number (percentage) and compared between groups using the chi-square test or Fisher exact test when expected cell counts were <5. Continuous variables were assessed for normality using the Shapiro-Wilk test. Because most variables were not normally distributed, they are presented as median with IQR (25th-75th percentile, Q1-Q3) and compared using the Mann-Whitney U test for 2-group comparisons or the Kruskal-Wallis test for comparisons across 3 groups. All statistical analyses were performed using R software version 4.3.1 (R Foundation for Statistical Computing).³⁰

Ethics

This study was approved by the Washington University in St. Louis School of Medicine Institutional Review Board. All patients included in this study provided written informed consent to participate in a prospective maintained institutional vascular surgery registry and serum biobank.

Results

Differences between study groups

Of the 1,081 patients reviewed in the vascular biobank, a total of 347 patients met the inclusion criteria (Figure 1). Of these, 34 (9.8%) were healthy control subjects (no PAD group), 164 (47.3%) had PAD, and 149 (42.9%) had CLTI (Figure 2). Median cFAS values were 46.89 pg/mg (Q1-Q3: 0.00-320.60 pg/mg), 326.17 pg/mg (Q1-Q3: 0.00-839.26 pg/mg), and 423.81 pg/mg (Q1-Q3: 0.00-897.28 pg/mg) in control subjects, PAD, and CLTI, respectively (P = 0.002). cFAS correlated inversely with ABI (ρ = −0.22; P < 0.001) and directly with Rutherford score (ρ = 0.18; P < 0.001). The healthy group without PAD had a significantly younger mean age of 25.50 years (Q1-Q3: 22.25-29.00 years) compared with the PAD group at 64.00 years (Q1-Q3: 59.00-73.00 years) and the CLTI group at 64.00 years (Q1-Q3: 57.00-70.00 years). The body mass index was numerically higher in the PAD group 28.20 kg/m² (Q1-Q3: 25.25-31.81 kg/m²) and CLTI group 26.29 (Q1-Q3: 23.08-30.68 kg/m²) compared with the no PAD group 25.87 (Q1-Q3: 22.09-28.93 kg/m²). Gender distribution revealed a higher proportion of men in the PAD (64.6%) and CLTI (67.8%) groups compared with the no PAD group (41.2%; P = 0.016) (Table 1).

Figure 2.

Violin Plot Displaying Serum cFAS levels Across 3 Patient Groups: No PAD, PAD, and CLTI

The distribution and density of serum circulating fatty acid synthase (cFAS) levels are shown for each group, with individual data points overlaid. The median and IQRs are represented within the box plots embedded in each violin. Serum cFAS levels are markedly higher in the PAD and CLTI groups compared with the no PAD group, with the highest levels observed in patients with CLTI, indicating a potential association between cFAS levels and PAD severity. Abbreviations as in Figure 1.

Table 1.

Baseline Demographic, Clinical, and Laboratory Characteristics of Study Participants

	No PAD (n = 34)	PAD (n = 164)	CLTI (n = 149)	P Value
cFAS, pg/mg	46.89 (0.00-320.60)	326.17 (0.00-839.26)	423.81 (0.00-897.28)	0.002
Age, y	25.50 (22.25-29.00)	64.00 (59.00-73.00)	64.00 (57.00-70.00)	<0.001
Body mass index, kg/m2	25.87 (22.09-28.93)	28.20 (25.25-31.81)	26.29 (23.08-30.68)	0.018
Male	14 (41.2)	106 (64.6)	101 (67.8)	0.014
Creatinine, mg/dL	0.81 (0.73-0.98)	0.97 (0.80-1.18)	0.96 (0.78-1.19)	0.031
Estimated GFR	107.92 (95.18-116.06)	78.70 (60.97-94.92)	81.47 (63.98-98.90)	<0.001
Triglycerides, mg/dL	77.00 (56.25-106.25)	132.00 (88.75-181.50)	123.50 (92.50-169.75)	<0.001
Total cholesterol, mg/dL	167.00 (141.50-183.75)	142.50 (117.75-175.00)	133.50 (115.25-159.00)	0.002
Direct HDL cholesterol, mg/dL	48.00 (40.25-58.00)	39.00 (32.00-48.00)	36.00 (29.25-43.00)	<0.001
Direct LDL cholesterol, mg/dL	100.00 (74.00-119.75)	80.00 (53.00-103.50)	71.50 (52.00-95.75)	0.001
Framingham risk score	0.01 (0.00-0.01)	0.22 (0.13-0.35)	0.19 (0.11-0.29)	<0.001
History of stroke	0 (0.0)	29 (17.7)	15 (10.1)	0.005
History of hemiplegia	0 (0.0)	2 (1.2)	1 (0.7)	0.999
History of dementia	0 (0.0)	1 (0.6)	3 (2.0)	0.57
Carotid artery disease	0 (0.0)	33 (20.1)	15 (10.1)	0.001
Daily aspirin use	0 (0.0)	119 (72.6)	105 (70.5)	<0.001
Statin use	0 (0.0)	121 (73.8)	111 (74.5)	<0.001
Insulin use	0 (0.0)	28 (17.1)	32 (21.5)	0.01
Smoking or tobacco use status				<0.001
Never	32 (94.1)	13 (7.9)	14 (9.4)
Current	0 (0.0)	78 (47.6)	76 (51.0)
Former	2 (5.9)	73 (44.5)	59 (39.6)
Diabetes mellitus	0 (0.0)	76 (46.3)	49 (32.9)	<0.001
History of myocardial infarction	0 (0.0)	35 (21.3)	30 (20.1)	0.01
History of coronary artery disease	0 (0.0)	80 (48.8)	61 (40.9)	<0.001
History of hypertension	0 (0.0)	139 (84.8)	118 (79.2)	<0.001
History of cerebrovascular disease	0 (0.0)	58 (35.4)	33 (22.1)	<0.001

Values are median (Q1-Q3) or n (%).

CLTI = chronic limb threatening ischemia; GFR = glomerular filtration rate; HDL = high-density lipoprotein; LDL = low-density lipoprotein; PAD = peripheral artery disease.

Subgroup analyses demonstrated no significant effect of statin therapy, daily aspirin, insulin therapy, coronary artery disease history, or asymptomatic carotid stenosis (P = 0.569) on serum cFAS. Adjusted models including these covariates yielded an unchanged cFAS-PAD OR. cFAS did not differ between patients with asymptomatic carotid stenosis and those without, suggesting that lower-extremity PAD severity is the primary determinant of cFAS elevation in our cohort. Other notable findings observed between groups includes differences in total cholesterol (no PAD 167.00 mg/dL [Q1-Q3: 141.50-183.75 mg/dL] vs PAD 142.50 mg/dL [Q1-Q3: 117.75-175.00 mg/dL] vs CLTI 133.50 mg/dL [Q1-Q3: 115.25-159.00 mg/dL]; P = 0.002), triglycerides (No PAD 77.00 mg/dL [Q1-Q3: 56.25-106.25 mg/dL] vs PAD 132.00 mg/dL [Q1-Q3: 88.75-181.50 mg/dL] vs CLTI 123.50 mg/dL [Q1-Q3: 92.50-169.75 mg/dL]; P < 0.001), LDL (No PAD 100.00 mg/dL [Q1-Q3: 74.00-119.75 mg/dL] vs PAD 80.00 mg/dL [Q1-Q3: 53.00-103.50 mg/dL] vs CLTI 71.50 mg/dL [Q1-Q3: 52.00-95.75 mg/dL]; P = 0.001), HDL (No PAD 48.00 mg/dL [Q1-Q3: 40.25-58.00 mg/dL] vs PAD 39.00 mg/dL [Q1-Q3: 32.00-48.00 mg/dL] vs CLTI 36.00 mg/dL [Q1-Q3: 29.25-43.00 mg/dL]; P < 0.001), and Framingham Risk Score (No PAD 0.01 [Q1-Q3: 0.00-0.01] vs PAD 0.22 [Q1-Q3: 0.13-0.35] vs CLTI 0.19 [Q1-Q3: 0.11-0.29]; P < 0.001).

cFAS Differences between study groups

Area under the receiver-operating characteristic curve analysis identified 2 Youden-optimal cutoffs for cFAS. For differentiating PAD/CLTI from control subjects (Supplemental Table 1), the optimal threshold was 340 pg/mg with an AUC of 0.679 (95% CI: 0.600-0.759). At this threshold, the true-positive rate was 52.4% (95% CI: 1.0%-83.3%) and the false-positive rate was 20.6% (95% CI: 1.0%-73.2%) (Figure 3). For distinguishing CLTI from non-CLTI (Supplemental Table 2), the optimal threshold was 490 pg/mg with an AUC of 0.553 (95% CI: 0.492-0.614). At this threshold, the true-positive rate was 49.0% (95% CI, 1.0%–77.1%) and the false-positive rate was 35.9% (95% CI: 23.7%-0%) (Figure 4, Supplemental Table 3).

Figure 3.

Area Under the Receiver-Operating Characteristic Curve Illustrating the Diagnostic Performance of Serum cFAS Levels for Distinguishing Peripheral Artery Disease From No Peripheral Artery Disease

The empirical area under the receiver-operating characteristic curve (solid line) shows sensitivity (true positive rate [TPR]) vs 1-specificity (false positive rate [FPR]) for various circulating fatty acid synthase (cFAS) thresholds. The optimal cutoff point, determined using the Youden Index, is marked at cFAS = 340 pg/mg, which maximizes sensitivity and specificity. The dashed line represents the chance line, indicating random classification performance. This optimal cutoff highlights the diagnostic potential of cFAS for peripheral artery disease detection.

Figure 4.

Area Under the Receiver-Operating Characteristic Curve Showing the Diagnostic Performance of Serum CFAS Levels for Distinguishing Chronic Limb Threatening Ischemia From No Peripheral Artery Disease or Peripheral Artery Disease

The empirical area under the receiver-operating characteristic curve (solid line) plots sensitivity (TPR) vs 1-specificity (FPR) across various cFAS thresholds. The optimal cutoff point, determined by the Youden Index, is indicated at cFAS = 490 pg/mg, maximizing sensitivity and specificity for chronic limb threatening ischemia detection. The dashed line represents the chance line, illustrating random classification. This cutoff underscores the potential of cFAS as a marker for advanced peripheral artery disease stages such as chronic limb threatening ischemia. Abbreviations as in Figure 3.

Univariable analysis comparing individuals without PAD to those with PAD or CLTI indicated that a cFAS level of ≥340 pg/mg was associated with significantly higher odds of having PAD or CLTI, with an OR of (1.14, 95% CI 1.07-1.21; P < 0.001) (Table 2). This finding suggests that elevated cFAS levels strongly correlate with the presence of PAD or CLTI. In a multivariable model adjusted for factors including age, diabetes status, HDL cholesterol, renal insufficiency, and statin and aspirin use, the association remained significant with an OR of 1.05 (95% CI: 1.01-1.09; P = 0.015) (Table 2), reinforcing the independent relationship between elevated cFAS levels and PAD or CLTI.

Table 2.

Univariable and Multivariable Logistic Regression Analyses

Outcome and Model	Characteristic	Coefficient	95% CI (Coefficient)	P Value	OR	95% CI (OR)	P Value
PAD/CLTI vs No PAD – Univariable	cFAS ≥340 pg/mg	0.13	0.07–0.19	<0.001	1.14	1.07–1.21	<0.001
	Age at surgery	0.01	0.01–0.02	<0.001	1.01	1.01–1.02	<0.001
	Daily aspirin	0.26	0.20–0.32	<0.001	1.3	1.22–1.38	<0.001
	Diabetes	0.14	0.08–0.20	<0.001	1.15	1.08–1.22	<0.001
PAD/CLTI vs No PAD – Multivariable	cFAS ≥340 pg/mg	0.05	0.01–0.09	0.015	1.05	1.01–1.09	0.015
	Age at surgery	0.01	0.01–0.01	<0.001	1.01	1.01–1.01	<0.001
	Daily aspirin	0.11	0.06–0.15	<0.001	1.12	1.06–1.16	<0.001
	Diabetes	0.04	−0.01 to 0.08	0.104	1.04	0.99–1.08	0.10
CLTI vs (PAD + No PAD) – Univariable	cFAS ≥490 pg/mg	0.14	0.03–0.24	0.013	1.15	1.03–1.27	0.013
	Age at surgery	0.01	0.00–0.01	0.003	1.01	1.00–1.01	0.003
	Direct HDL (mg/dL)	−0.01	−0.01 to −0.00	0.004	0.99	0.99–1.00	0.004
	Statin	0.17	0.05–0.28	0.004	1.19	1.05–1.32	0.004
	Diabetes	−0.06	−0.18 to 0.05	0.251	0.94	0.84–1.05	0.25
	Renal insufficiency	−0.05	−0.19 to 0.08	0.441	0.95	0.83–1.08	0.44
CLTI vs (PAD + No PAD) – Multivariable	cFAS ≥490 pg/mg	0.1	−0.00 to 0.21	0.055	1.11	1.00–1.23	0.055
	Age at surgery	0	0.00–0.01	0.033	1.00	1.00–1.01	0.033
	Direct HDL (mg/dL)	−0.01	−0.01 to −0.00	0.009	0.99	0.99–1.00	0.009
	Statin	0.1	−0.03 to 0.22	0.135	1.11	0.97–1.25	0.14
	Diabetes	−0.12	−0.23 to −0.01	0.035	0.89	0.79–0.99	0.035
	Renal insufficiency	−0.10	−0.24 to 0.03	0.128	0.90	0.79–1.03	0.13

cFAS = circulating fatty acid synthase; other abbreviations as in Table 1.

In comparisons of individuals with no PAD or PAD, vs those with CLTI, the univariable model showed that a cFAS level of ≥490 pg/mg was associated with an OR of 1.15 (95% CI: 1.03-1.27; P = 0.013) (Table 2). This suggested that individuals with cFAS levels above this threshold are more likely to have CLTI than those without CLTI. In the multivariable model, adjusting for relevant factors, the adjusted OR was 1.11 (95% CI: 1.00-1.23; P = 0.055) (Table 2), suggesting that elevated cFAS levels may also independently correlate with CLTI.

Discussion

Our study evaluated whether serum cFAS could serve as a biomarker for PAD across varying levels of disease severity. We investigated the association between cFAS levels and PAD incidence, while adjusting for confounding factors such as age, sex, and comorbidities such as diabetes and smoking. Area under the receiver-operating characteristic curve analysis revealed that serum cFAS levels were significantly associated with the presence of PAD and CLTI, highlighting its potential utility as a diagnostic marker. In our cohort of 347 tested patients, cFAS could identify PAD or CLTI (cutoff ≥340 pg/mg) with 52.4% sensitivity and 79.9% specificity. For identifying CLTI alone, a higher cutoff (≥490 pg/mg) demonstrated a sensitivity of 49% and specificity of 64.1%. Serum cFAS at ∼340 pg/mg may flag high-risk or equivocal-ABI patients for definitive evaluation. Among PAD patients, levels ≥490 pg/mg may identify those at highest risk of progression to CLTI, informing surveillance frequency and early intervention.

Recent studies support the association between serum cFAS levels and peripheral arterial disease beyond the coronary arteries.22, 23, 24 For instance, elevated serum cFAS has been observed in patients with carotid artery stenosis, particularly those with concomitant diabetes.²² Immunoprecipitation studies have demonstrated that the 275 kDa cFAS protein associates with apolipoprotein B (ApoB), the primary apolipoprotein in LDL particles.²² Conditional knockdown of the Fasn gene in the liver significantly reduces serum cFAS levels, as seen in Fasn^fl/fl Apoe^−/− mice, which also show reduced atherosclerotic plaque formation when maintained on a high-fat diet.²⁴ In humans, elevated serum cFAS has been linked with higher FAS and saturated fatty acid content in the peripheral arteries, contributing to macrophage foam cell formation and atherosclerosis progression.^23,24 These findings suggest that serum cFAS may serve as an indicator of atherosclerotic disease severity. In our current study, we further demonstrate that cFAS levels are elevated in patients with confirmed PAD and reach the highest levels in those with CLTI.

This study deliberately excluded serum samples from patients included in previous publications to provide a new and independent assessment of cFAS as a marker for PAD.^22,23 In our multivariable model, cFAS maintained its association with PAD and CLTI independent of other traditional vascular disease risk factors, building on earlier pilot studies and suggesting that cFAS may predict PAD disease risk better than LDL or ABI alone.²³ Other studies have proposed that markers of fatty acid synthesis, such as saturated fatty acids, actively contribute to atherosclerotic disease progression beyond simple LDL risk stratification.^25,31,32 Although the association between cFAS and PAD severity did not reach statistical significance at the higher threshold for CLTI, the observed trend suggests that cFAS could be valuable for identifying advanced disease stages in larger studies. This aligns with evidence indicating that CLTI encompasses a spectrum of end-stage PAD complications, including rest pain, nonhealing wounds, tissue necrosis, and gangrene.^2,3 Due to the limitations of our sample size, we did not stratify CLTI cases beyond Rutherford Class and did not base our assessments on anatomical disease severity or differentiate between atherosclerotic or thrombotic obstructions. Future studies should address the capacity of cFAS to provide a more nuanced diagnostic signal in patients with varying CLTI severities caused by atherosclerosis.

The 2019 ASCVD guidelines reinforced LDL as a primary marker for cardiovascular risk assessment, largely based on studies showing reduced cardiovascular events in patients with lower LDL levels or those on statin therapy.⁹ Initially developed by the ACC and AHA in 2013,¹³ these guidelines have since expanded to include a broader range of vasculopathies, including PAD and its complications. In the absence of a PAD-specific biomarker, LDL and ABI are frequently used as surrogate indicators of disease risk.^15,27,33 However, large-scale studies consistently show significant underdiagnosis of PAD, particularly among asymptomatic individuals and those with atypical symptoms.^7,8 For example, both the REACH (REduction of Atherothrombosis for Continued Health) Registry and the PARTNERS (PAD Awareness, Risk, and Treatment: New Resources for Survival) study reported that conventional screening measures failed to identify PAD in approximately 25% to 50% of cases,^7,8 underscoring the need for more reliable diagnostic modalities in current clinical practice.

Our study showed that LDL did not correlate with the presence of PAD or CLTI. In fact, total cholesterol and LDL levels were generally lower among patients with PAD and CLTI compared with those without PAD, likely caused by the use of cholesterol-lowering medications such as statins. Current AHA/ACC guidelines recommend LDL as an indicator for atherosclerosis and a trigger for statin therapy, alongside ABI for PAD screening.⁹ However, large-scale randomized controlled trials demonstrating LDL as a predictor for PAD are limited, and some studies suggest that LDL may not be a strong determinant of cardiovascular risk in specific populations, such as women.^9,34, 35, 36 Our study found that cFAS was equally diagnostic in men and women, with sex not significantly influencing cFAS levels.

All participants in this study underwent an ABI test as the gold standard for diagnosing PAD and CLTI. The ACC/AHA guidelines reference Feigelson et al,¹⁸ which rigorously assessed ABI for PAD screening, noting an ABI <0.8 had a 39% sensitivity and 70% specificity for detecting PAD. Other studies have similarly shown variability in ABI sensitivity, depending on whether the ABI is high or low, and affected by operator expertise.^15,27,33,37 Due to these limitations, the U.S. Preventive Services Task Force does not currently endorse ABI testing for PAD screening, and the ABI is not reimbursed by CMS for asymptomatic patients.¹⁷ In contrast, a serum biomarker like cFAS, which has comparable sensitivity and specificity and requires only a small volume blood sample, could be accessible to primary care providers and has the potential identify patients with PAD.

Study limitations

Our patient cohort included individuals with varying medical histories and potential confounding variables that may have influenced the outcomes. Additionally, the negative control samples relied on self-reported patient histories, introducing potential recall bias. Our sample was also limited in capturing truly asymptomatic PAD cases, because our institutional biobank predominantly includes patients scheduled for surgical intervention. Although we included a no PAD control group, these individuals were generally younger and healthy except for thoracic outlet syndrome, which limits the generalizability of our findings. To enhance the analytical validity of cFAS as a biomarker, it will be essential to develop a more robust and rapid serum cFAS test. Although incorporating factors such as age, gender, smoking status, and diabetes into our multivariable model was beneficial, it is possible that other confounding variables were not adequately represented in our area under the receiver-operating characteristic curve analyses. Serial prerevascularization and postrevascularization cFAS measurements are needed to determine if restored perfusion leads to reductions in cFAS levels. Finally, future prospective studies should evaluate whether elevated baseline cFAS predicts major or minor amputations in PAD and CLTI patients.

Conclusions

Our findings identify cFAS as a novel and independent serum biomarker for PAD. Elevated cFAS levels effectively distinguish individuals with PAD and CLTI and correlate with disease severity. These results support the potential clinical utility of cFAS as a noninvasive diagnostic and risk-stratification tool for patients with atherosclerotic vascular disease.

Perspectives.

COMPETENCY IN MEDICAL KNOWLEDGE: PAD lacks reliable serum biomarkers for diagnosis and staging. cFAS, a key enzyme in lipid biosynthesis, is significantly elevated in PAD and highest in CLTI, offering potential for improved detection and risk stratification.

TRANSLATIONAL OUTLOOK: No blood test currently aids PAD diagnosis. cFAS shows promise as a noninvasive biomarker to identify PAD, differentiate CLTI, and assess disease severity. Larger, prospective studies are needed to validate diagnostic cutoffs and integrate cFAS into clinical algorithms.

Funding Support and Author Disclosures

This work was supported by grants from Washington University School of Medicine Diabetes Research Center National Institutes of Health/NIDDK P30DK020589, National Institutes of Health/NHLBI R01HL153262 (to Dr Zayed), NIH/NHLBI R01HL150891 (to Dr Zayed), National Institutes of Health/NIDDK R01DK101392 (to Dr Semenkovich), and National Institutes of Health/NHLBI R01HL157154 (to Dr Semenkovich). Dr Mohamed Zayed and Dr Stephen Wu are cofounders of AirSeal CardioVascular, Inc, a biomedical startup company that aims to clinically translate diagnostic approaches for individuals with complications related to atherosclerotic cardiovascular disease. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.