Positive Association of High Leptin Level and Abdominal Aortic Calcification in Men　― The Prospective MINOS Study ―

Pawel Szulc; Ez Zoubir Amri; Annie Varennes; Patricia Panaia-Ferrari; Eric Fontas; Joëlle Goudable; Roland Chapurlat; Véronique Breuil

doi:10.1253/circj.CJ-18-0517

Abstract

Background: Severe abdominal aortic calcification (AAC) points to high cardiovascular risk and leptin stimulates arterial calcification; however, clinical data on their association are scarce. We studied the link between serum leptin and AAC severity and progression, and the effect of smoking and lipid levels, on this association in men.

Methods and Results: At baseline, 548 community-dwelling men aged 50–85 years underwent blood collection and lateral lumbar spine radiography. In 448 men, X-ray was repeated after 3 and 7.5 years. AAC was assessed using Kauppila’s semiquantitative score. In multivariable models, high leptin was associated with higher odds of severe AAC (odds ratio [OR]=1.71 per SD, 95% confidence interval [CI]: 1.22–2.40). The odds of severe AAC were the highest in men who had elevated leptin levels and either were ever-smokers (OR=9.22, 95% CI: 3.43–24.78) or had hypertriglyceridemia (vs. men without these characteristics). Higher leptin was associated with greater AAC progression (OR=1.34 per SD, 95% CI: 1.04–1.74). The risk of AAC progression was the highest in men who had elevated leptin levels and either were current smokers or had high low-density lipoprotein-cholesterol levels (OR=5.91, 95% CI: 2.46–14.16 vs. men without these characteristics). These links remained significant after adjustment for baseline AAC and in subgroups defined according to smoking and low-density lipoprotein-cholesterol levels.

Conclusions: In older men, high leptin levels are associated with greater severity and rapid progression of AAC independent of smoking, low-density lipoprotein-cholesterol or triglycerides.

Leptin regulates energy homeostasis and vascular metabolism,¹ but data on the link between leptin and abdominal aortic calcification (AAC) are limited. This is important because leptin analogs may be used in the treatment of obesity and severe AAC predicts cardiovascular morbidity and mortality.²^,³

In experimental studies, leptin has induced aortic calcification and osteoblastic differentiation of vascular smooth muscle cells (VSMC).⁴^,⁵ In patients with calcific aortic valve disease, leptin is expressed mainly in the calcified aortic wall.⁵ Although clinical studies show that patients with calcification of the aortic valve or carotid artery have higher leptin levels,⁵^,⁶ data on the association between serum leptin levels and coronary artery calcification are discordant.⁷^–¹⁰ Data on the link between serum leptin and AAC are also scarce and discordant,¹¹^–¹³ thus requiring further studies.

The inconclusive clinical data on leptin and AAC may relate to the confounding effect of factors associated with both. Smokers have more severe AAC,¹⁴^,¹⁵ but the data on leptin levels in smokers are inconsistent, possibly because of inadequate control of body weight.¹⁶^–¹⁸ Smoking and obesity increase the AAC risk, but obesity is associated with high leptin levels and smokers are generally slim.¹⁹^,²⁰ As smoking may promote AAC through the direct effect of tobacco and reduce it by lowering the leptin level, the study of the link between leptin and AAC should account for smoking habit.

Blood levels of leptin and lipids correlate positively. Lipid accumulation in the aortic wall increases osteogenic differentiation of VSMC and calcification.²¹ However, the link between serum lipids and AAC has been poorly studied.¹⁴^,¹⁵^,²²^,²³ Obesity is associated with AAC and high levels of leptin and lipids. As leptin may influence AAC or be a bystander in hyperlipidemia, study of the link between leptin and AAC should account for lipids.

Thus, the linkage of serum leptin with AAC severity and progression and the potential effect of smoking and lipids on this relation are poorly studied. Therefore, our primary aim was to study the association of serum leptin with AAC severity and progression in older men. The secondary aim was to analyze the additive effects of leptin and other factors (smoking, lipids) in their associations with AAC severity and progression.

Methods

The MINOS Cohort

The MINOS study is a prospective single-center cohort study of osteoporosis in men aged 50–85 years.²⁴ This collaborative project involves the Institut National de la Santé et de la Recherche Médicale and Société de Secours Minière de Bourgogne, a health insurance service for families of mineworkers living in Montceau-les-Mines. The study was approved by the Ethical Board and performed according to the Declaration of Helsinki (1983). The men (n=783) provided informed consent and blood was collected in 1995–1996. The cross-sectional study was performed in 548 men who had enough serum for leptin assays. They did not differ from the other men (Table S1) and were followed for 7.5 years. The prospective study was performed in 448 men who had follow-up spine X-rays (100 men dropped out because of death or health status).

Leptin Measurements

Fasting blood samples were collected at 08.00 hours. Blood was centrifuged and separated. Serum aliquots were stored at −80℃ without thawing until the assay in 2011.²⁴ In order to limit the interassay variability, measurements were performed using kits from a single series (Table 1).

Table 1. Biological Assays

	Method	Provider	Detection limit	Interassay CV
Leptin	ELISA	TECO-Medical, Switzerland	0.2 ng/mL	7.6%
Glucose	Hexokinase assay	Modular Analyzer, Roche, Meylan, France	2 mg/dL	1.0%
Triglycerides	Enzymatic colorimetry		4 mg/dL	1.5%
Cholesterol, HDL-C	Enzymatic colorimetry		3 mg/dL	0.6–0.9%
Testosterone	RIA		0.06 nmol/L	7.8%
17β-estradiol	RIA		11 pmol/L	6–9%
Parathyroid hormone	Immunochemoluminometry	Magic Lite; Ciba Corning Diagnostic, Medfield, MA, USA	0.2 pmol/L	7%
25-hydroxycholecalciferol	Acetonitrile extraction, RIA	Incstar Corp., Stillwater, MN, USA	3 ng/mL	10%
Osteocalcin	IRMA assay	CISBioInternational, Bagnols, France	0.4 ng/mL	6%

CV, coefficient of variation; HDL-C, high-density lipoprotein-cholesterol; IRMA, immunoradiometric assay; RIA, radioimmunoassay

AAC

AAC was assessed from lumbar spine lateral radiographs using a semiquantitative score.²⁵ Calcification of the anterior and posterior aortic walls, adjacent to the first 4 lumbar vertebrae, was scored (Figure). Severity scores for each segment were added to yield the global AAC score (0–24). AAC progression was calculated as the difference between the score on the last X-ray (3 or 7.5 years) and the baseline score divided by the follow-up duration. AAC was assessed in 2005–2006 (thus, without knowing leptin levels) by P.S. who evaluated the baseline and the follow-up X-rays side by side, knowing their order. Reproducibility was assessed on 30 X-rays. The short- and long-term intra-observer reproducibility was excellent: intraclass correlation coefficient (ICC) of 0.95 and 0.91, respectively. The interobserver reproducibility was also excellent: ICC=0.92. As the difference between 2 readings was ≤1 point, a difference ≥2 points between the last and the first X-ray (>0.25 point/year for 7.5 years) was defined as meaningful AAC progression. This cutoff was selected arbitrarily because it was considered to exclude false positives and did not exclude moderate progression.

Figure.

Abdominal aortic calcification (AAC) assessed using Kauppila’s score: (Left) no AAC (score=0); (Middle) mild AAC (score=4); (Right) severe AAC (score=21).

Questionnaire

Lifestyle and health status were assessed using interviewer-administered questionnaires at baseline.²⁴ If possible, all information was checked. Smoking was categorized as current, former, and never. Alcohol intake was assessed as total weekly intake of wine, beer, and spirits, expressed in g/week. Daily calcium intake was assessed by food questionnaire that was adapted for French dietary habits. Education level was categorized as >8 vs. ≤8 years of school. Occupational physical activity was assessed by a self-reported;’ scale (low, medium, hard, very hard). Leisure current physical activity was calculated as the overall amount of time (hours/week) spent walking, gardening, and participating in sports activities. Diagnoses were self-reported as present vs. absent. They included ischemic heart disease, hypertension, diabetes mellitus. Participants self-reported current medications (vitamin K antagonists, fibrates and statins). Weight, height, and waist and hip circumference were measured by P.S.

Biological Assays

Glucose, triglycerides, cholesterol and high-density lipoprotein-cholesterol (HDL-C) were measured as previously described.²⁵ Low-density lipoprotein-cholesterol (LDL-C) was calculated by Friedewald’s equation.²⁶ Testosterone, 17β-estradiol, 25-hydroxycholecalciferol (25OHD) parathyroid hormone (PTH) and osteocalcin were measured as described previously.²⁴^,²⁵ Glomerular filtration rate (GFR) was calculated using the CKD-EPI equation.

Statistical Analysis

Statistical analyses were performed using SAS9.4 software (SAS Institute, Cary, NC, USA). Bivariate comparisons were assessed by analysis of variance, Kruskall-Wallis test, chi-square test, and Fisher’s exact test. The relationship between AAC severity (AAC >6 vs. 0–6) and leptin was assessed by logistic regression. This threshold is comparable to the cutoff of AAC scores strongly associated with cardiovascular risk.³ The variables were selected based on the results of unadjusted tests and biological plausibility. We assessed age, body mass index (BMI; or weight, waist, waist/hip ratio), education level, smoking, alcohol intake, occupational and leisure physical activities, ischemic heart disease, hypertension, diabetes, statins, fibrates, vitamin K antagonists, serum levels of testosterone, 17β-estradiol, 25OHD, PTH, glucose, triglycerides, total, HDL- and LDL-cholesterol, and osteocalcin, and GFR. Variables associated with AAC at P<0.15 or changing the odds ratio (OR) by 5% were retained (see Results). The most relevant index of obesity was selected based on the AIC criterion and on the Hesmer-Lemeshow goodness-of-fit test. The most discriminating thresholds were established using Youden’s index. The same approach was used for the development of the model for the meaningful AAC progression (>0.25 vs. ≤0.25 point/year). The final model was further adjusted for baseline AAC severity.

Results

Descriptive Analysis

Weight, BMI, waist, hip circumference, waist/hip ratio, prevalence of hypertension and diabetes, AAC score and serum triglyceride and glucose levels increased across the leptin quartiles (Table 2). Serum HDL-C, osteocalcin, and testosterone levels, and GFR decreased across the leptin quartiles. The trends remained significant after adjustment for age.

Table 2. Description of the Participants According to the Leptin Quartiles

	Q1 (<3.86ng/mL) (n=137)	Q2 (3.86–6.43ng/mL) (n=137)	Q3 (6.43–10.15ng/mL) (n=137)	Q4 (>10.15ng/mL) (n=137)	P value^a	P value^b
Age (years)	65±8	64±7	65±7	65±7	0.09
Body weight (kg)	70.9±8.9	78.2±9.2	80.9±10.2	88.9±14.9	<0.001	<0.001
Height (cm)	168.9±5.6	169.3±6.5	168.7±6.1	169.1±7.0	0.86
BMI (kg/m²)	24.86±2.59	27.26±2.46	28.40±3.07	30.94±3.90	<0.001	<0.001
Waist (cm)	91±8	97±7	100±8	107±9	<0.001	<0.001
Hip (cm)	97±6	99±6	99±6	103±7	<0.001	<0.001
Waist-hip ratio	0.95±0.07	0.99±0.07	1.01±0.08	1.04±0.08	<0.001	<0.001
Smokers (n, %)
Ccurrent	26 (19)	16 (12)	15 (11)	14 (10)	0.18
Former	64 (47)	78 (57)	82 (60)	82 (60)
Never	47 (34)	43 (31)	40 (29)	41 (30)
Alcohol intake (g/week)	219 [31; 359]	234 [78; 437]	219 [47; 344]	234 [109; 437]	0.18
Calcium intake (mg/day)	741±254	716±210	732±229	736±235	0.83
Education level (>8 years, n, %)	34 (25)	29 (21)	36 (26)	40 (29)	0.30
Occupational activity (weak, n, %)	10 (7)	5 (4)	3 (2)	9 (6)	0.16
Leisure physical activity (g/week)	21 [12; 30]	22 [13; 28]	21 [15; 30]	18 [12; 27]	<0.05	0.12
IHD (n, %)	17 (12)	14 (10)	25 (18)	24 (17)	0.18
Hypertension (n, %)	25 (18)	28 (21)	34 (25)	47 (34)	<0.05	<0.05
Diabetes mellitus (n, %)	5 (4)	5 (4)	13 (9)	18 (13)	<0.005	<0.01
AAC score	2 [0; 5]	1 [0; 4]	2 [0; 7]	4 [1; 8]	<0.001	<0.001
VKA (n, %)	5 (4)	2 (1)	7 (5)	2 (1)	0.20
Statins (n, %)	2 (1)	7 (5)	9 (7)	10 (7)	0.13
Fibrates (n, %)	13 (9)	24 (18)	16 (12)	23 (17)	0.17
Leptin (ng/mL)	2.08±1.15	5.22±0.68	8.12±1.09	15.44±5.49	<0.001	<0.001
Glycemia (mg/dL)	104.1±27.2	107.0±21.5	111.3±27.0	113.2±24.0	<0.05	<0.01
Cholesterol (mg/dL)	227±37	231±40	230±36	226±41	0.64
HDL-C (mg/dL)	55.0±16.4	50.4±13.8	48.4±11.4	47.4±15.2	<0.001	<0.001
Triglycerides (mg/dL)	137±60	175±107	177±98	192±110	<0.001	<0.001
LDL-C (mg/dL)	144±36	146±39	146±35	141±36	0.53
Testosterone (nmol/L)	20.4±6.7	19.1±7.0	16.4±6.4	14.8±6.9	<0.001	<0.001
17β-estradiol (pmol/L)	116±30	116±27	111±27	110±29	0.16
25-hydroxycholecalciferol (ng/mL)	28±12	29±11	26±10	26±10	0.06	0.16
PTH (pg/mL)	38.4±17.3	37.9±15.7	40.9±17.3	40.7±18.5	0.38
Osteocalcin (ng/mL)	20.7±7.5	19.4±5.6	18.4±6.5	18.3±6.2	<0.005	<0.005
GFR (mL/min/1.73 m²)	81±12	81±12	77±14	77±15	<0.005	<0.05

^aAnalysis of variance. ^bAge-adjusted. AAC, abdominal aortic calcification; BMI, body mass index; GFR, glomerular filtration rate; HDL-C, high-density lipoprotein-cholesterol; IHD, ischemic heart disease; LDL-C, low-density lipoprotein-cholesterol; PTH, parathyroid hormone; VKA, vitamin K antagonist.

Cross-Sectional Study

The percentage of men with severe AAC (>6) increased across the leptin quartiles (trend P<0.001) (Table 3). In the multivariable models higher leptin level was associated with higher odds of severe AAC. The most discriminating threshold of leptin was 8.93 ng/mL.

Table 3. Association Between Serum Leptin and Severe Abdominal Aortic Calcification (>6 vs. 0–6)

Serum leptin	Prevalence	Adjusted for age and waist^b		Adjusted for age, waist,^b lifestyle,^c comorbidities^d		Adjusted for age, waist,^b lifestyle,^c comorbidities,^d treatments,^e biological assays^f
Per SD increase		1.76 (1.31–2.76)	<0.001	1.75 (1.27–2.39)	<0.001	1.71 (1.22–2.40)	<0.001
Q1	22/137 (16%)	1.00		1.00		1.00
Q2	23/137 (17%)	1.42 (0.71–2.84)	0.19	1.35 (0.65–2.80)	0.23	1.14 (0.54–2.44)	0.24
Q3	35/137 (25%)	2.24 (1.14–4.41)	0.0165	2.20 (1.08–4.48)	0.0170	2.15 (1.02–4.50)	0.0421
Q4	47/137 (34%)	3.62 (1.72–7.62)	<0.001	3.69 (1.68–8.12)	<0.001	3.32 (1.46–7.55)	0.0012
Trend	<0.001	<0.001		<0.001		<0.005
≤8.93 ng/mL^a	67/370 (18%)	1.00		1.00		1.00
>8.93 ng/mL	60/178 (34%)	2.31 (1.41–3.80)	<0.001	2.28 (1.35–3.85)	<0.001	2.49 (1.39–4.46)	0.0020

Q1: <3.86 ng/mL, Q2: 3.86–6.43 ng/mL, Q3: >6.43–10.15 ng/mL, Q4: >10.15 ng/mL. ^aThreshold established using Youden’s index. ^bIndex of obesity selected using the AIC criterion and Hosmer-Lemeshow’s goodness-of-fit test. ^cLifestyle: smoking, alcohol intake, dietary calcium intake, occupational physical activity. ^dComorbidities: ischemic heart disease, hypertension, diabetes mellitus. ^eTreatments: statins, fibrates. ^fBiological assays: osteocalcin, parathyroid hormone, triglycerides, glomerular filtration rate.

Leptin levels did not differ among the current, former and never smokers (P=0.15). As predicted probabilities of severe AAC were similar for current and former smokers, men were divided into ever-smokers (former/current) and never-smokers. Ever-smokers had higher odds of severe AAC vs. never-smokers in the multivariable models (OR=2.67, 95% CI: 1.51–4.74, P<0.001). In the multivariable models, ever-smoking and high leptin contributed jointly to severe AAC (Table 4). The odds of severe AAC were higher in the ever-smokers with higher leptin vs. the reference group (never-smokers, low leptin).

Table 4. Odds of Severe Abdominal Aortic Calcification (>6 vs. 0–6) Associated With Leptin Levels and Other Risk Factors

Leptin^a	Covariate	Prevalence	Analysis in the entire cohort		Analysis in the subgroups of the covariates
Leptin^a	Covariate	Prevalence	OR (95% CI)	P value	Covariate	OR (95% CI)	P value
	Smoking				Smoking
≤8.93 ng/mL	Never	12/119 (10%)	1.00		Never	1.00	0.24
>8.93 ng/mL	Never	12/ 51 (24%)	4.29 (1.27–14.49)	0.0312	Never	2.90 (0.49–17.29)	0.24
≤8.93 ng/mL	Ever	55/251 (22%)	4.08 (1.65–10.06)	0.0062	Ever	1.00	0.0066
>8.93 ng/mL	Ever	48/127 (38%)	9.22 (3.43–24.78)	<0.001	Ever	2.41 (1.28–4.54)	0.0066
	Hyper-TG				Hyper-TG
≤8.93 ng/mL	No	27/214 (13%)	1.00		No	1.00	0.0042
>8.93 ng/mL	No	22/ 78 (28%)	3.13 (1.35– 7.29)	0.0081	No	4.44 (1.60–12.32)	0.0042
≤8.93 ng/mL	Yes	40/156 (26%)	2.27 (1.09– 4.74)	0.0321	Yes	1.00	0.20
>8.93 ng/mL	Yes	38/100 (38%)	4.98 (2.13–11.63)	0.0043	Yes	1.65 (0.76–3.60)	0.20

Adjusted for age, waist circumference,^b alcohol intake, dietary calcium intake, occupational physical activity, ischemic heart disease, hypertension, diabetes mellitus, statins, osteocalcin, parathyroid hormone, glomerular filtration rate, and mutually exclusively for hypertriglyceridemia (triglycerides >164 mg/dL^a or treatment with fibrates) or for smoking habit. ^aEstablished using Youden’s index. ^bIndex of obesity selected using the AIC criterion and Hosmer-Lemeshow’s goodness-of-fit test.

In the multivariable models, hypertriglyceridemia (>164 mg/dL obtained by Youden index, or therapy with fibrates) was associated with higher odds of severe AAC (OR=2.45, 95% CI: 1.43–4.18, P<0.001). High triglyceride and leptin levels were associated with higher odds of severe AAC jointly and independently of each other. After adjustment for confounders, the odds of severe AAC were higher in the men who had hypertriglyceridemia and higher leptin levels vs. the reference group (normal triglycerides, lower leptin levels).

Higher leptin tended to be associated with severe AAC in the subgroups analyzed separately, but the link was not always significant because of poor statistical power. The interactions of leptin with smoking and hypertriglyceridemia were not significant (P=0.33 and P=0.47, respectively).

In all the models, abdominal circumference and other alternative indices of obesity were not significant (P>0.30). Adjustment for other measures of obesity did not change the link of leptin with severe AAC (e.g., with BMI: OR=1.66 per SD, 95% CI: 1.16–2.30, P=0.0017; highest vs. lowest quartile: OR=3.25, 95% CI: 1.40–7.48, P=0.0042).

Prospective Study

Men lost to follow-up were older and more often reported hypertension and ischemic heart disease (Table S2). They had higher waist-hip ratio, AAC and PTH, but less physical activity and 25OHD. Most differences lost significance after adjustment for age.

The median increase in AAC was 0.27 points/year (interquartile range: 0.13; 0.67 points/year). The percentage of men who had meaningful progression in AAC severity (>0.25 points/year) increased across the leptin quartiles (trend P<0.001) (Table 5). In a multivariable model high leptin was associated with higher risk of AAC progression for all the approaches (continuous, quartiles, threshold). The relation persisted after adjustment for baseline AAC.

Table 5. Association Between Serum Leptin Concentration and Risk of Meaningful AAC Progression

Serum leptin	Prevalence	Adjusted for age, weight,^b lifestyle,^c comorbidities^d		Adjusted for age, weight,^b lifestyle,^c comorbidities,^d treatments,^e biological assays^f		Adjusted for age, weight,^b lifestyle,^c comorbidities,^d treatments,^e biological assays,^f AAC at baseline
Per SD increase		1.37 (1.06–1.78)	0.0105	1.34 (1.04–1.74)	0.0270	1.33 (1.06–1.66)	0.0251
Q1	58/109 (53%)	1.00		1.00		1.00
Q2	66/115 (57%)	1.21 (0.69–2.11)	0.25	1.07 (0.60–1.91)	0.19	1.05 (0.59–1.85)	0.22
Q3	76/120 (63%)	1.43 (0.80–2.55)	0.11	1.35 (0.74–2.45)	0.14	1.20 (0.67–2.14)	0.16
Q4	79/104 (76%)	2.61 (1.29–5.30)	0.0082	2.41 (1.17–4.99)	0.0097	2.34 (1.25–4.94)	0.0052
≤9.75 ng/mL^a	190/332 (57%)	1.00		1.00
>9.75 ng/mL	89/116 (77%)	2.28 (1.32–3.95)	0.0032	2.27 (1.30–3.98)	0.0041	2.07 (1.24–3.48)	0.0058

Q1: <3.86 ng/mL, Q2: 3.86–6.43 ng/mL, Q3: >6.43–10.15 ng/mL, Q4: >10.15 ng/mL. ^aThreshold established using Youden’s index. ^bIndex of obesity selected using the AIC criterion and Hosmer-Lemeshow’s goodness-of-fit test. ^cLifestyle: current smoking, alcohol intake, education level, occupational physical activity. ^dComorbidities: ischemic heart disease, hypertension, diabetes mellitus. ^eTreatments: statins, fibrates. ^fBiological assays: parathroid hormone, triglycerides, low-density lipoprotein-cholesterol, glomerular filtration rate. AAC, abdominal aortic calcification.

Current smokers had a higher risk of AAC progression vs. never-smokers (OR=3.00, 95% CI: 1.43–6.30, P<0.01), whereas former smokers did not (OR=1.36, 95% CI: 0.87–2.12, P=0.40). Current smokers had a higher risk of AAC progression vs. non-smokers (former and never): OR=2.53, 95% CI: 1.27–5.03, P<0.01. The interaction between smoking and leptin was not significant (P=0.31), but the risk of AAC progression was higher in current smokers with high leptin vs. the reference group (non-smokers, low leptin) (Table 6). This link persisted after adjustment for baseline AAC (OR=15.58, 95% CI: 1.83–132.30, P=0.0305). Moreover, higher leptin was associated with AAC progression in the subgroups analyzed separately.

Table 6. Odds of Meaningful AAC Progression Associated With Serum Leptin Concentrations and Other Risk Factors

Leptin^a	Covariate	Prevalence	Analysis in the entire cohort		Analysis in the subgroups of the covariates
Leptin^a	Covariate	Prevalence	OR (95% CI)	P value	Covariate	OR (95% CI)	P value
	Current smoking				Current smoking
≤9.75 ng/mL	No	165/293 (56%)	1.00		No	1.00	0.0240
>9.75 ng/mL	No	77/103 (75%)	2.09 (1.14–3.64)	0.0327	No	1.86 (1.09–3.18)	0.0240
≤9.75 ng/mL	Yes	25/ 39 (64%)	1.91 (0.90–4.06)	0.07	Yes	1.00	0.0260
>9.75 ng/mL	Yes	12/ 13 (92%)	14.95 (1.83–122.2)	0.0154	Yes	61.52 (1.64–>999)	0.0260
	High LDL				High LDL
≤9.75 ng/mL	No	83/165 (50%)	1.00		No	1.00	0.0107
>9.75 ng/mL	No	47/ 66 (72%)	2.08 (1.04–4.19)	0.0414	No	2.36 (1.22–4.56)	0.0107
≤9.75 ng/mL	Yes	107/167 (64%)	1.98 (1.24–3.15)	0.0156	Yes	1.00	0.0043
>9.75 ng/mL	Yes	42/ 50 (84%)	5.91 (2.46–14.16)	0.0021	Yes	4.12 (1.56–10.87)	0.0043

Adjusted for age, weight,^b alcohol intake, education level, occupational physical activity, ischemic heart disease, hypertension, diabetes mellitus, fibrates, parathyroid hormone, triglycerides, glomerular filtration rate, and mutually exclusively for high LDL-C (>146 mg/dL^a or treatment with statins) or current smoking. ^aEstablished using Youden’s index. ^bIndex of obesity selected using the AIC criterion and Hosmer-Lemeshow’s goodness-of-fit test. AAC, abdominal aortic calcification; CI, confidence interval; LDL-C, low-density lipoprotein-cholesterol; OR, odds ratio.

Men with high LDL-C (>146 mg/dL by Youden’s index, or with statins) had a higher risk of AAC progression vs. men with normal LDL (OR=1.84, 95% CI: 1.22–2.79, P=0.0083). Higher leptin and LDL-C contributed jointly to the higher risk of AAC progression. The interaction between leptin and LDL-C was not significant (P=0.29), but the risk of AAC progression was higher in men with high LDL-C and leptin levels vs. the reference group (normal LDL-C, low leptin). This pattern remained significant after further adjustment for baseline AAC (OR=5.83, 95% CI: 2.41–14.13, P=0.0013). Moreover, higher leptin was associated with AAC progression in the subgroups analyzed separately.

In all the models, none of the alternative indices of obesity were significant (P>0.40). After adjustment for other measures of obesity (e.g., BMI), leptin remained predictive of rapid AAC progression (OR=1.28 per SD, 95% CI: 1.00–1.59, P=0.0500; highest vs. lowest quartile: OR=1.98, 95% CI: 1.01–4.02, P=0.0480).

Discussion

In a cohort of older men, high serum leptin levels were associated with higher odds of severe AAC and of meaningful AAC progression after adjustment for confounders. The associations of leptin with AAC were additive with those of smoking habit and serum levels of triglycerides and LDL-C.

Data on the association between serum leptin and AAC are scarce: a weak negative relation in 1 study, no link in others.¹¹^,¹² Those studies did not provide the prevalence of severe AAC. They analyzed AAC as present/absent, which is not specific enough to study its associations with other factors. The link between leptin and AAC severity/progression has been poorly studied; it may be bystander of the link between obesity and AAC, but in the present study it was significant after adjustment for all indices of obesity, which themselves were non-significant in the models, including leptin.

The arterial wall may be a target for leptin. Leptin acts via its receptor on calcifying vascular cells in the calcifying aortic media.²⁷ Leptin may stimulate osteoblastic differentiation. It activated transcription factor, Runx2, induces phosphorylation of the kinases Erk-1 and Erk-2, stimulates expression of osteoblast-specific proteins and calcification.⁴^,²⁷^,²⁸ It exerts these effects by enhancing the expression of RANKL and bone morphogenetic protein 4 (BMP4).²⁸ A high fat diet increases leptin expression and the development of vascular lesions in the carotid arteries.²⁹ Thus, our results are consistent with experimental data showing that leptin contributes to the development of calcification in the aortic media.

High leptin levels and smoking are associated with greater AAC severity and progression independently of each other. As smoking cessation cannot reverse calcific deposits, severe AAC is found in ever-smokers. Only current smoking is associated with AAC progression. Severe AAC has been found mainly in heavy smokers.¹⁴^,¹⁵ Data on the effect of smoking and its cessation on leptin levels are discordant, even after adjustment for weight.⁶^,¹⁶^–¹⁹ Several mechanisms of the effect of tobacco on AAC are raised: insulin resistance, chronic inflammation, oxidative stress.¹⁴^,³⁰ The link between leptin, smoking and AAC is unclear; however, our data suggested that tobacco and leptin contribute additively to AAC development and independently of each other, being involved in different mechanisms.

Experimental studies suggest distinct pathways for the effect of leptin and lipids on AAC. Leptin-deficient mice fed a high fat diet had smaller atherosclerotic lesions (despite high triglyceride levels) vs. wild-type mice.²⁹^,³¹ In these mice, exogenous leptin decreased fat mass and the levels of serum cholesterol and triglycerides, but accelerated the progression of vascular lesions. In LDL receptor-deficient mice, a high fat diet induced vascular calcification by mechanisms involving BMP2 and reactive oxygen species.³² Thus, leptin, triglycerides, and LDL may stimulate AAC by distinct pathways. LDL can enter dysfunctional arterial endothelium and induce the formation of calcifying atherosclerotic plaques.³¹^,³² This process, found mainly in the coronary arteries, may contribute to AAC progression, which is in line with our data that high LDL-C was associated with a greater increase in the AAC score. Kauppila’s score cannot measure the increase in calcium content in existing deposits. The increase in the AAC score reflects formation of new calcific foci, in line with the possible role of LDL.

Leptin-deficient mice had few atherosclerotic lesions and a high HDL-C level.³³ In such mice, leptin injection lowered the HDL-C level.³⁴ Exogenous HDL inhibited osteoblastic differentiation and calcification of calcifying vascular cells.³⁵ However, in our study HDL-C was not associated with AAC severity/progression (data not shown). Because the data on the link between HDL-C and vascular calcification are discordant,¹⁰^,¹²^,¹⁵^,²²^,²³ the relationships between leptin, HDL and AAC need further study.

Our data have clinical importance. High leptin levels are associated with AAC severity and progression, after adjustment for measures of obesity. The link is significant regardless of the model, which suggests that leptin is an independent predictor of AAC progression. Regardless of its scientific novelty, our finding may stimulate further studies; for example, the possible use of leptin measurement to improve identification of men at high risk of rapid AAC progression.

High levels of serum leptin have been associated with measures of cardiovascular risk (calcification of aortic valve, carotid artery or coronary arteries, number of stenotic coronary vessels),⁶^–¹⁰^,³⁶ but the data are limited, inconsistent and mainly from cross-sectional studies. AAC is interesting because severe AAC and rapid AAC progression strongly predict cardiovascular morbidity and mortality.³^,³⁷ Identification of men at high risk of rapid AAC progression enables earlier treatment and thus more efficacious reduction of their cardiovascular risk. AAC may be detected on an X-ray ordered for another reason, so its assessment is easily available and inexpensive.

The potential effects of interventional modification of leptin levels (weight loss), of LDL levels (statins) or smoking cessation on AAC progression remain to be studied. Leptin and its analogs have been used in the treatment of obesity,² but their side effects on AAC need studies; AAC may be increased by leptin directly or inhibited because of the improved metabolic status.

Adiponectin is an anti-inflammatory adipokin secreted by adipocytes and involved in the regulation of vascular metabolism.³⁸ It inhibits VSMC proliferation and platelet aggregation. Low serum adiponectin levels are associated with higher vascular wall thickness in some,¹¹^,¹²^,³⁹ but not all⁶^,⁸^,⁴⁰ studies. Thus, unlike leptin, serum adiponectin does not seem to be clinically useful for the identification of individuals at high risk of AAC or its progression.

Study Limitations

The study cohort including mainly low–middle-class community-dwelling men is not representative of the French population. We cannot extrapolate our results to women. Leptin was assayed in sera stored for 16 years, but unavoidable partial loss of leptin during the storage was probably similar in all samples (systematic error). A single assay may not reflect metabolic status. Information on lifestyle and diseases was self-reported at baseline. Duration and severity of diseases may produce residual confounding. Kauppila’s score provides less accurate assessment of AAC than computed tomography (CT). It depends mainly on the length of deposits in the anterior and posterior aortic walls. CT results also reflect thickness, calcium density and calcific deposits in lateral areas. However, AAC assessed using this score predicts cardiovascular risk in the general population and in patients with chronic kidney disease.⁴¹^,⁴² We assessed AAC progression in men who returned for follow-up visits. The sickest men who did not return may have had higher AAC progression. In prospective studies, an increase in Kauppila’s score reflects new calcific deposits, rather than thickening or mineralization of the existing ones. Thus, for the assessment of aggravation of AAC in longitudinal studies, the semiquantitative score is more specific but less sensitive than CT. The advantages of this score vs. CT include availability, affordability and low radiation dose, which is important, especially for the repeated measures in longitudinal studies. The choice of the AAC threshold (4th quartile, ≥2 points increase) was arbitrary; however, no guidelines define the threshold of clinically relevant AAC severity or progression. As the normal AAC score is zero and higher cardiovascular risk is found in patients with severe AAC,³ the highest quartile is a tradeoff between sensitivity and specificity. The 2-point increase in AAC score exceeds a change in AAC score related to a random error of the rater. We did not assess other metabolic measures (e.g., insulin, adipokines) and it is no longer possible to do so.

In conclusion, we showed that high leptin levels were associated with greater severity and rapid progression of AAC in older men. The clinical data confirmed experimental studies showing an effect of leptin on arterial calcification. Leptin may be involved in pathways that are distinct from those associated with smoking or lipids. The robust association between leptin levels and AAC progression showed that leptin was a strong predictor of rapid AAC progression and invites further studies on this topic. Our findings suggested that studies of the therapeutic use of leptin or its analogs should include an assessment of arterial calcification.

Conflict of Interest

The authors report no conflicts of interest.

Author Contributions

P.S. was responsible for the study, assessed aortic calcification, made the statistical analyses and wrote the manuscript. E.Z.A. performed measurements of leptin and contributed to data interpretation and the discussion. A.V. was responsible for the measurement of glycemia and lipids. P.P.-F. performed the assays of leptin and contributed to data interpretation and the discussion. E.F. contributed to data interpretation and the discussion. J.G. supervised the measurement of glycemia and lipids, reviewed the manuscript and contributed to the discussion. R.C. reviewed the manuscript and contributed to the discussion. V.B. was responsible for the measurement of leptin (including funding), contributed to data interpretation and the discussion, and revised the manuscript. P.S. is the guarantor of this work, had full access to all the data in the study and takes responsibility for the integrity and accuracy of the data analysis.

Funding

Grants from INSERM/Merck Sharp & Dohme Chibret, France and by ‘‘Programme Hospitalier de Recherche Clinique InterRégional–Interrégion Sudméditerrannée-2011” of the French Ministry of Health. Clinical Trials.gov identifier: NCT01192893.

Supplementary Files

Supplementary File 1

Table S1. Comparison of baseline characteristics in men who did or did not have leptin measurements

Table S2. Comparison of baseline characteristics in men who were or were not followed up

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-18-0517

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