Association between Skeletal Muscle Characteristics and Arterial Stiffness: Chronic Limb-Threatening Ischemia the Key Element

Skeletal muscle is a highly active endocrine organ that produces several bioactive molecules, myokines, with decisive action in multiple physiologic processes, including inflammation and vascular function.[1] [2] However, the relationship between normal/abnormal skeletal muscle indicators and arterial stiffness is not clear.[3] Thus, this work aimed to evaluate the association between physiological and structural features of skeletal muscle (strength, quantity, histology, myokines) and arterial stiffness.

An observational, prospective study is being conducted since January 2018 at a single institution. The study includes patients that were consecutively attended to vascular surgery consultations of the first author. Patients with diseases responsible for body composition changes or proinflammatory state were excluded.

Statistics: A minimum sample of 51 patients in each group was necessary (with a significance level of 5% and for a power of 80%) to achieve the desired power of the study, calculated with the software G Power 3.1.9.7.

Study approval: The study was approved by the Ethics Committee of the Institution (75/2017). All the participants signed the informed consent.

Arterial stiffness was estimated with carotid-femoral pulse wave velocity (cf-PWV) determined noninvasively with the commercially available SphygmoCor system (Model: SphygmoCor XCEL System; Fabricant: AtCor Medical Pty, U.S.). The study population was dichotomized in two groups according to cf-PWV above or below 10 m/s. The following skeletal muscle features were analyzed: strength, area, mass/density, histology, and serum levels of myokines (irisin and myostatin). Strength was determined with a Jamar hydraulic hand dynamometer (Patterson Medical). The highest average score of each hand was used for evaluation. A transverse computed tomography scan was obtained to quantify the skeletal muscle. The areas of the following muscles at the 3rd lumbar vertebra were added: psoas, erector spinae, quadratus lumborum, transversus abdominis, external and internal oblique abdominal muscle, and rectus abdominis. The area and density (mass) were semiautomatically determined using Fiji (ImageJ). In patients with indication for surgery, samples of sartorius skeletal muscle were collected at the femoral region during the surgical procedure and submitted to histology (hematoxylin-eosin staining) and immunohistochemical (CD 45+ leucocytes and CD 163+ macrophages) characterization. To quantify myokines, myostatin/GDF8 and irisin a Multiplex Human myokine kit (HMYOMAG-56K-01, Millipore, Burlington, Massachusetts, United States) was used.

We included 177 subjects (mean age: 67.16 ± 9.87 years old; 80.23% males), 119 with peripheral arterial disease (65 with claudication and 54 with chronic limb-threatening ischemia), 11 with carotid stenosis ≥ 50%, and 47 with varicose veins ([Table 1]). cf-PWV of the studied population was 10.72 ± 3.37 m/s.

Table 1 Cardiovascular risk factors and comorbidities of the studied population

	PWV < 10 m/s (n = 90)	PWV ≥ 10 m/s (n = 87)	p-Value
Cardiovascular risk factors
Age (y)	63.47 ± 8.66	71.62 ± 7.64	0.000[a]
Male (n; %)	70; 77.78	63; 72.41	0.634
Hypertension (n; %)	60; 66.67	80; 91.95	0.008[a]
Smoker/ex-smoker (n; %)	59; 65.56	46; 52.87	0.268
Smoking load (PY)	26.00 ± 26.31	27.20 ± 32.03	0.890
Dyslipidemia (n; %)	62; 68.89	61; 70.11	0.939
Diabetes (n; %)	30; 33.33	40; 45.98	0.271
HbA1c (%)	6.06 ± 1.77	5.42 ± 3.03	0.995
Coronary artery disease (n; %)	17; 18.89	14; 16.09	0.719
Peripheral arterial disease (n; %)	51; 56.67	68; 78.16	0.038[a]
Varicose veins (n; %)	31; 34.44	16; 18.39	0.085
Carotid stenosis ≥ 50% (n; %)	8; 8.89	3; 3.45	0.719
Medication
Statins (n; %)	68; 75.56	82; 94.25	0.019[a]
Fibrate (n; %)	8; 8.89	2; 2.30	0.303
Ezetimibe (n; %)	3; 3.33	7; 8.04	0.303
Antiplatelet (n; %)	65; 72.22	73; 83.91	0.233
ACEi/ARA-II (n; %)	25; 27.78	32; 36.78	0.399
Beta-blockers (n; %)	17; 18.89	22; 25.29	0.571

Abbreviations: ACEi/ARA, angiotensin-converting enzyme inhibitors/angiotensin II receptor antagonists; HbA1c, glycated hemoglobin; PWV, pulse wave velocity; PY, pack year.

^a p < 0.05.

We found that patients in the group with cf-PWV ≥ 10 m/s had lower skeletal muscle density and strength (23.67 ± 16.49 vs. 14.53 ± 15.28 HU, p = 0.027; 25.26 ± 8.53 vs. 20.40 ± 7.78 Kgf, p = 0.016). No differences were found in the skeletal muscle area (14883.21 ± 3510.36 vs. 19182.20 ± 27221.52 cm², p = 0.727). Sixty-two patients were submitted to surgery and no differences were found between groups in the histology and immunohistochemical analysis of the skeletal muscle samples. In the majority of patients, the serum levels of myokines were below the lower limit of detection. Irisin and myostatin levels were just detected in 4 and 18 patients, respectively. No conclusion was obtained about irisin and no differences were found regarding myostatin between groups (cf-PWV above or below 10 m/s). However, myostatin was strongly and positively correlated with cf-PWV (r = 0.599, p = 0.024).

The multiple linear regression statistical analysis was used to determine the influence of age, hypertension, statins, peripheral arterial disease, skeletal muscle density, and strength on the cf-PWV. The results revealed that age (β = 0.436, t = 4.197, p = 0.000) and peripheral arterial disease were significant predictors of cf-PWV (β = 0.258, t = 2.487, p = 0.015). However, the inclusion of the severe form of peripheral arterial disease, that is, chronic limb-threatening ischemia, in the model diminished the significance of peripheral arterial disease (β = 0.135, t = 1.267, p = 0.210). The model incorporating age (β = 0.366, t = 3.541, p = 0.001) and chronic limb-threatening ischemia emerged as the predictor of arterial stiffness (β = 0.380, t = 3.680, p = 0.000). Other variables, such as strength and skeletal muscle density, had no impact on arterial stiffness.

This is an observational, cross-sectional study with a small sample size of vascular surgery patients, which severely compromises the reproducibility of the results. Another limitation of this research study was the inability to register all the factors that could influence the muscle characteristics such as physical exercise or protein intake. Despite these limitations, skeletal muscle density, strength, and myostatin exhibited a notable association with arterial stiffness in univariate analysis underscoring potentially intriguing connections. However, the multiple linear regression analysis revealed that the true predictors in this cohort were age and the severe form of peripheral arterial disease, that is, chronic limb-threatening ischemia. This insight underscores the intricate interplay between atherosclerosis and sarcopenia as factors intertwined with the aging process, potentially sharing underlying pathological mechanisms, such as chronic inflammation.[4]

Publication History

Article published online:
25 April 2024

• References

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