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..................................................................................................................................................................................... ..................................................................................................................................................................................... Insulin-like growth factor axis (insulin-like growth factor-I/insulin-like growth factor-binding protein-3) as a prognostic predictor of heart failure: association with adiponectin Shin Watanabe 1 , Toshihiro Tamura 1 , Koh Ono 1 , Hisanori Horiuchi 1 , Takeshi Kimura 1 , Toru Kita 2 , and Yutaka Furukawa 2 * 1 Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606–8507, Japan; and 2 Department of Cardiovascular Medicine, Kobe City Medical Center General Hospital, 4-6 Minatojimanakamachi, Chuo-ku, Kobe 650-0046, Japan Received 27 April 2010; revised 13 July 2010; accepted 16 July 2010; online publish-ahead-of-print 17 September 2010 See page 1154 for the editorial comment on this article (doi:10.1093/eurjhf/hfq173) Aims Insulin-like growth factor (IGF)-I is a regulator of glucose/fatty acid metabolism and may be involved in the pathophy- siology of cardiovascular disease, but it remains unclear whether endogenous IGF-I is associated with the prognosis of heart failure (HF). We investigated whether the IGF axis, the ratio of IGF-I to IGF-binding protein-3 (IGFBP-3), was a predictor of clinical outcomes in HF. The association of IGF axis with serum adiponectin level, a prognostic marker of HF as well as a regulator of glucose/fatty acid metabolism, was also analysed. Methods and results We measured serum IGF-I and IGFBP-3 in 142 HF patients with left ventricular systolic dysfunction and 63 control subjects. Patients with HF underwent clinical assessment and measurement of adiponectin and B-type natriuretic peptide (BNP). Compared with controls, HF patients showed significantly decreased serum IGF axis values [median (inter-quartile ranges), 0.114 (0.063–0.150) vs. 0.099 (0.052–0.158), P ¼ 0.042]. In HF patients, the log-transformed IGF axis values were inversely correlated with the log-transformed serum adiponectin levels (r ¼ 20.35, P , 0.0001) and plasma BNP levels (r ¼ 20.25, P ¼ 0.0028). The IGF axis was lower in patients with New York Heart Association (NYHA) functional class III/IV than those with class I/II [0.071 (0.044–0.145) vs. 0.107 (0.068– 0.161), P ¼ 0.022]. Furthermore, a decrease in IGF axis was associated with increased rates of all-cause mortality (P ¼ 0.013), cardiac death (P ¼ 0.035), and a composite of cardiac death and re-hospitalization (P ¼ 0.0085). Conclusion Insulin-like growth factor axis is a significant predictor of clinical outcomes in HF and is significantly associated with serum adiponectin levels. ----------------------------------------------------------------------------------------------------------------------------------------------------------- Keywords Insulin-like growth factor-I Adiponectin Heart failure Outcomes Cardiac metabolism Introduction Heart failure (HF) remains one of the most frequent causes of death in the industrialized world. A shift in cardiac energy metabolism is a common feature of HF. 1 In the healthy adult, free fatty acids are the predominant substrate ( 70%) used by the cardiac muscle. 2 However, hypertrophied or failing hearts demonstrate an increased reliance on glucose while decreasing their fatty acid utilization. 1,3 The cardiometabolic factor insulin-like growth factor (IGF)-I modulates glucose/fatty acid metabolism and may play a role in metabolic disorders in the failing heart. Insulin-like growth factor-I is one of the most potent endogenous activators of the phosphatidylinositol 3-kinase-Akt signalling pathway, which plays a role in anti-apoptosis, cell growth, and energy metabolism. 4,5 Insulin-like growth factor-I, as well as another cardiometabolic factor, adiponectin, stimulates glucose transporter (GLUT) 4 * Corresponding author. Tel: +81 78 302 4321, Fax: +81 78 302 7537, Email: [email protected] Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2010. For permissions please email: [email protected]. European Journal of Heart Failure (2010) 12, 1214–1222 doi:10.1093/eurjhf/hfq166

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Page 1: Insulin-like growth factor axis (insulin-like growth factor-I/insulin-like growth factor-binding protein-3) as a prognostic predictor of heart failure: association with adiponectin

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Insulin-like growth factor axis (insulin-like growthfactor-I/insulin-like growth factor-bindingprotein-3) as a prognostic predictor of heartfailure: association with adiponectinShin Watanabe1, Toshihiro Tamura1, Koh Ono1, Hisanori Horiuchi1, Takeshi Kimura1,Toru Kita2, and Yutaka Furukawa2*

1Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606–8507, Japan; and 2Departmentof Cardiovascular Medicine, Kobe City Medical Center General Hospital, 4-6 Minatojimanakamachi, Chuo-ku, Kobe 650-0046, Japan

Received 27 April 2010; revised 13 July 2010; accepted 16 July 2010; online publish-ahead-of-print 17 September 2010

See page 1154 for the editorial comment on this article (doi:10.1093/eurjhf/hfq173)

Aims Insulin-like growth factor (IGF)-I is a regulator of glucose/fatty acid metabolism and may be involved in the pathophy-siology of cardiovascular disease, but it remains unclear whether endogenous IGF-I is associated with the prognosis ofheart failure (HF). We investigated whether the IGF axis, the ratio of IGF-I to IGF-binding protein-3 (IGFBP-3), was apredictor of clinical outcomes in HF. The association of IGF axis with serum adiponectin level, a prognostic marker ofHF as well as a regulator of glucose/fatty acid metabolism, was also analysed.

Methodsand results

We measured serum IGF-I and IGFBP-3 in 142 HF patients with left ventricular systolic dysfunction and 63 controlsubjects. Patients with HF underwent clinical assessment and measurement of adiponectin and B-type natriureticpeptide (BNP). Compared with controls, HF patients showed significantly decreased serum IGF axis values [median(inter-quartile ranges), 0.114 (0.063–0.150) vs. 0.099 (0.052–0.158), P ¼ 0.042]. In HF patients, the log-transformedIGF axis values were inversely correlated with the log-transformed serum adiponectin levels (r ¼ 20.35,P , 0.0001) and plasma BNP levels (r ¼ 20.25, P ¼ 0.0028). The IGF axis was lower in patients with New YorkHeart Association (NYHA) functional class III/IV than those with class I/II [0.071 (0.044–0.145) vs. 0.107 (0.068–0.161), P ¼ 0.022]. Furthermore, a decrease in IGF axis was associated with increased rates of all-cause mortality(P ¼ 0.013), cardiac death (P ¼ 0.035), and a composite of cardiac death and re-hospitalization (P ¼ 0.0085).

Conclusion Insulin-like growth factor axis is a significant predictor of clinical outcomes in HF and is significantly associated withserum adiponectin levels.

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Keywords Insulin-like growth factor-I † Adiponectin † Heart failure † Outcomes † Cardiac metabolism

IntroductionHeart failure (HF) remains one of the most frequent causes of deathin the industrialized world. A shift in cardiac energy metabolism is acommon feature of HF.1 In the healthy adult, free fatty acids are thepredominant substrate (�70%) used by the cardiac muscle.2

However, hypertrophied or failing hearts demonstrate an increasedreliance on glucose while decreasing their fatty acid utilization.1,3

The cardiometabolic factor insulin-like growth factor (IGF)-Imodulates glucose/fatty acid metabolism and may play a role inmetabolic disorders in the failing heart. Insulin-like growthfactor-I is one of the most potent endogenous activators of thephosphatidylinositol 3-kinase-Akt signalling pathway, which playsa role in anti-apoptosis, cell growth, and energy metabolism.4,5

Insulin-like growth factor-I, as well as another cardiometabolicfactor, adiponectin, stimulates glucose transporter (GLUT) 4

* Corresponding author. Tel: +81 78 302 4321, Fax: +81 78 302 7537, Email: [email protected]

Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2010. For permissions please email: [email protected].

European Journal of Heart Failure (2010) 12, 1214–1222doi:10.1093/eurjhf/hfq166

Page 2: Insulin-like growth factor axis (insulin-like growth factor-I/insulin-like growth factor-binding protein-3) as a prognostic predictor of heart failure: association with adiponectin

translocation in cardiomyocytes and enhances cardiac glucoseuptake, which may also contribute to cell growth and survival.6,7

These properties of IGF-I suggest its potential association withprognosis and symptoms of HF patients.

Insulin-like growth factor-binding proteins (IGFBPs) have a highaffinity for IGF-I and play important roles such as transporter pro-teins and storage pools of IGF-I in serum. Binding of IGF-I toIGFBPs neutralizes IGF-I activity.8 Because IGFBP-3 is the mostabundant IGFBP in serum, the ratio of IGF-1/IGFBP-3 can beused to estimate the activity of IGF-1 in individuals.9 With regardto the role of IGF-I as a prognostic marker for HF, it has beensuggested that low serum IGF-I levels are associated with increasedrisk for mortality in patients with HF.10,11 In contrast, other groupshave reported that high IGF-I levels are independently associatedwith increased all-cause mortality and increased risk for HF.12

Thus, the role of IGF-I as a prognostic marker for HF remainsunclear.11–14

The aim of the present study was to investigate the associationbetween the estimated IGF-I activity represented by the IGF axis,the ratio of serum IGF-I to IGFBP-3 concentrations, with clinicaloutcomes in HF patients. We compared the IGF axis betweenHF patients and control subjects with normal cardiac function.We then determined the predictive potential of the IGF axis formortality, and the associations between the IGF axis, adiponectin,and other markers for HF.

MethodsThis study was approved by the institutional review board of KyotoUniversity Graduate School and Faculty of Medicine. Informedwritten consent was obtained from all study subjects in accordancewith the Declaration of Helsinki.

Study subjects, definition, and follow-upA total of 142 Japanese HF patients with left ventricular (LV) systolicdysfunction who were admitted to hospital between August 2003and December 2006 and 63 control subjects with normal LV systolicfunction were analysed. Left ventricular systolic dysfunction wasdefined as an LV ejection fraction (LVEF) of ,50%. Left ventricularejection fraction was calculated from two-dimensional echocardiogra-phy images using the apical biplane modified Simpson’s method. Thecontrol subjects were matched for age, sex, body mass index (BMI),and the incidence of diabetes mellitus (DM). Patients with end-stagerenal dysfunction were excluded from the study because they report-edly have elevated circulating adiponectin and B-type natriureticpeptide (BNP) levels.15 Clinical and analytical information obtained atbaseline for the HF patients included the New York Heart Association(NYHA) functional classification, BMI calculated from measurementsof height and weight, conditions such as DM and hypertension,blood biochemistry, and echocardiography.

Diabetes mellitus was defined according to whether the patientswere being treated with anti-diabetic drugs or insulin. Patients ondietary treatment alone who met the diagnostic criteria listed in the‘Report of the Committee of Japan Diabetes Society (JDS) on theClassification and Diagnostic Criteria of Diabetes Mellitus’ were alsoconsidered to have diabetes.16 Anaemia was defined according tothe World Health Organization criteria17 as haemoglobin concen-tration ,12 g/dL for women and ,13 g/dL for men. Chronic kidneydisease (CKD) was defined with reference to National Kidney

Foundation guidelines as an estimated glomerular filtration rate(eGFR) ,60 mL/min/1.73 m2.

The HF patients were followed up with regard to mortality andre-hospitalization. All deaths were confirmed by medical records ortelephone interview with the patients’ families.

Measurement of insulin-like growth factor-I,insulin-like growth factor-binding protein-3,adiponectin, and B-type natriureticpeptide levelsAll blood samples were collected by venepuncture. The sera andplasma were kept on ice until centrifugation within 3 h of venepunc-ture. After centrifugation, the sera and plasma were frozen andstored at 2808C until use for assay. All samples were subjected toanalysis within 6 months after storage. Serum concentrations of totalIGF-I, total IGFBP-3, and total adiponectin were measured for eachsample using commercially available enzyme-linked immunosorbentassay kits (IGF-I and IGFBP-3, R&D Systems, Minneapolis, MN, USA;adiponectin, Otsuka Life Science Initiative, Tokyo, Japan). The IGFaxis was calculated as the molar ratio of serum IGF-I to IGFBP-3,and the following molecular masses were used: IGF-I, 7.5 kDa;IGFBP-3, 30.5 kDa.18 The plasma concentration of BNP was measuredusing an enzyme immunoassay (Tosoh Corporation, Tokyo, Japan).

Statistical analysisSerum IGF-I, IGFBP-3, and adiponectin, and plasma BNP levels areexpressed as medians (inter-quartile ranges), since the values are gen-erally non-parametrically distributed. The other continuous variablesare expressed as means+ SD. Statistical significance for the differ-ences in demographic characteristics between the HF and controlsubjects or between the subgroups of HF patients was assessed byStudent’s t-test because the values were distributed parametrically.The Mann–Whitney U-test was used to compare the non-parametricvalues, namely serum IGF-I and IGFBP-3, and the IGF axis betweentwo groups. Pearson’s correlation coefficient was used to assessthe correlations between the log-transformed serum IGF axisvalues (log IGF axis) and the log-transformed serum adiponectin con-centrations (log adiponectin), the log-transformed plasma BNP con-centrations (log BNP), or BMI in the HF patients. Multivariablelinear regression analyses were conducted to examine the correlatesof log IGF axis and included baseline variables that were associatedwith log IGF axis at the P , 0.05 level on univariate analyses. TheKaplan–Meier analysis compared the cumulative event rates of all-cause death, cardiac death, and a composite of cardiac death andre-hospitalization due to HF between the two groups of HFpatients stratified according to the median value of the IGF axis.The Kaplan–Meier analysis was also applied for the comparison ofthe cumulative survival rates between the two groups stratifiedaccording to the median IGF axis in the ischaemic or the non-ischaemic HF subgroups. Differences between the survival curveswere tested using a log-rank test.

Univariate analysis with the Cox proportional hazards model wasused to assess the association between each variable and patient sur-vival. Multivariate analysis with the Cox proportional hazards modelwas used to assess the independence of the predictors of mortality.The covariates included age, sex, and all parameters with P , 0.05 inthe univariate analysis: BMI, anaemia, high (III/IV) NYHA class, renaldysfunction, log BNP, log adiponectin, and log IGF axis. To assessthe independence of log IGF axis with log adiponectin and/or logBNP, four different multivariate models were tested. In these analyses,age, serum total cholesterol, serum triglyceride, log BNP, log

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adiponectin, and log IGF axis were analysed as continuous variables,whereas others were analysed as categorical variables.

All analyses were conducted using JMP version 7 (SAS Institute Inc.,Cary, NC, USA). All reported P-values were two-sided.

Results

Subject demographics, serum insulin-likegrowth factor-I and insulin-like growthfactor-binding protein-3 levels, and theinsulin-like growth factor axisWe studied a total of 142 patients with HF and 63 control subjects(Table 1). Compared with the control subjects, HF patients showedsignificantly increased serum IGF-I [control vs. HF; 42.9 (35.9–48.7) vs. 62.2 (38.6–91.4) ng/mL, P , 0.0001] and IGFBP-3[1544.7 (1070.9–2017.8) vs. 2810.6 (1817.3–3942.5) ng/mL, P ,

0.0001] levels, whereas the IGF axis value was lower in HF subjects[0.099 (0.052–0.158)] than in control [0.114 (0.063–0.150), P ¼0.042] (Figure 1).

The HF patients were then divided into two groups accordingto the median value (0.099) of the IGF axis. Detailed clinicalinformation, baseline circulating biomarker levels, and the useof medications are summarized in Table 2. The low IGF axisgroup included older patients and patients with lower BMI,blood haemoglobin level, and serum triglyceride level, relativeto the high IGF axis group. With respect to the parametersfor the severity of HF such as NYHA class, LVEF, LV end-diastolic dimension (LVDd), serum adiponectin, and renaldysfunction, the low IGF axis group appeared to include moresevere patients.

Associations between the insulin-likegrowth factor axis and other clinicaland biochemical markers in heartfailure patientsSerum IGF-I concentration was significantly lower in patientswith NYHA functional class III/IV than those with class I/II[median (inter-quartile range): NYHA III/IV vs. I/II ¼ 54.6

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Table 1 Background characteristics of the studysubjects

Group Control(n 5 63)

HF(n 5 142)

P-value

Age (years) 67.5+8.3 67.8+12.6 0.92

Male gender, n (%) 45 (70.3) 103 (72.5) 0.74

BMI (kg/m2) 22.6+2.2 21.9+3.8 0.15

Total cholesterol (mg/dL) 182.5+34.3 172.4+40.6 0.088

Triglyceride (mg/dL) 116.9+59.8 112.8+65.9 0.67

DM, n (%) 27 (42.9) 60 (42.3) 0.94

HbA1c (%) 6.1+0.9 6.2+1.2 0.46

Diabetes diagnosis,2 years

16 (59.3) 32 (53.3) 0.29

Diabetes diagnosis≥2, ,5 years

4 (14.8) 4 (6.7)

Diabetes diagnosis≥5 years

7 (25.9) 24 (40.0)

Treatment of diabetes, n (%)

Diet therapy only 16 (25.4) 32 (22.5) 0.73

Insulin 4 (6.4) 11 (7.8) 0.72

Sulfonylurea 4 (6.4) 14 (9.9) 0.41

Biguanide 3 (4.8) 3 (2.1) 0.12

a-Glucosidase 2 (3.2) 12 (8.5) 0.17

Thiazolidinedione 2 (3.2) 2 (1.4) 0.40

HF, heart failure; BMI, body mass index; DM, diabetes mellitus; HbAlc,haemoglobin A1c.

Figure 1 Comparison of serum insulin-like growth factor-I and insulin-like growth factor-binding protein-3 concentrations, and the insulin-likegrowth factor axis (the molar ratio of insulin-like growth factor-I to insulin-like growth factor-binding protein-3) between control and heartfailure (HF) subjects. Data are expressed as median values with inter-quartile and 10–90% ranges.

S. Watanabe et al.1216

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(29.9–74.1) vs. 66.6 (46.3–99.6) ng/mL, P ¼ 0.0028], whereasserum IGFBP-3 was comparable between these two groups[2745.5 (1723.0–3764.6) vs. 2870.1 (1882.3–3980.0) ng/mL,P ¼ 0.70]. As a result, the IGF axis was also significantly lowerin patients with NYHA class III/IV [0.071 (0.044–0.145) vs.0.107 (0.068–0.161), P ¼ 0.022] (see Supplementary materialonline, Figure S1). Log IGF axis showed a significant inverse cor-relation with log adiponectin (r ¼ 20.35, P , 0.0001; Figure 2A)and log BNP (r ¼ 20.25, P ¼ 0.0028; Figure 2B) in HF patients.Since the IGF axis can influence glucose/fatty acid metabolism,we analysed the association between log IGF axis and BMI or

serum triglyceride levels. Although there was no significant cor-relation between log IGF axis and BMI (r ¼ 0.088, P ¼ 0.31;Figure 2C), log IGF axis was positively correlated to the serum tri-glyceride level (r ¼ 0.25, P ¼ 0.0024). Log IGF axis also showed aweak positive correlation with the eGFR (r ¼ 0.18, P ¼ 0.035)and an inverse correlation with the LVDd (r ¼ 20.23, P ¼0.0057) (Table 3).

In stepwise multivariable analyses, three parameters, low serumtriglyceride (P ¼ 0.044), large LVDd (P ¼ 0.0067), and high log adi-ponectin (P ¼ 0.0021), were significant independent predictors forlow serum IGF axis (Table 3).

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Table 2 Clinical information, biochemical marker levels, and medications at baseline in heart failure patients

Overall (n 5 142) IGF axis P-value

<0.099 (n 5 71) ≥0.099 (n 5 71)

Age (years) 67.8+12.6 70.0+11.3 65.6+13.5 0.042

Male gender, n (%) 103 (72.5) 50 (70.4) 53 (74.7) 0.57

BMI (kg/m2) 21.9+3.8 21.0+3.5 22.8+4.0 0.0066

NYHA class III/IV, n (%) 59 (41.5) 36 (50.7) 23 (32.4) 0.027

Ischaemic HF, n (%) 70 (49.3) 31 (44.9) 39 (53.4) 0.31

Haemoglobin (g/dL) 12.1+2.2 11.7+2.2 12.5+2.2 0.019

Smoking status

Current smoker, n (%) 39 (27.5) 17 (23.9) 22 (30.9)

Past smoker, n (%) 35 (24.7) 22 (31.0) 13 (18.3) 0.20

Never smoker, n (%) 68 (47.9) 32 (45.1) 36 (50.7)

Diabetes mellitus, n (%) 60 (42.3) 29 (40.9) 31 (43.7) 0.73

HbA1c (%) 6.2+1.2 6.1+1.1 6.3+1.3 0.50

Hypertension, n (%) 81 (57.0) 40 (56.3) 41 (57.8) 0.87

Hyperlipidaemia, n (%) 58 (42.3) 26 (38.2) 32 (46.4) 0.33

Total cholesterol (mg/dL) 172.4+40.6 166.1+40.8 178.7+39.7 0.033

Triglyceride (mg/dL) 112.8+65.9 93.1+41.0 132.7+79.5 0.0003

Creatinine (mg/dL) 1.04+0.36 1.11+0.42 0.97+0.28 0.025

eGFR (mL/min/1.73 m2) 57.5+19.2 54.1+18.3 61.4+19.5 0.030

BNP (pg/mL) 286.2 (91.0–709.6)a 433.1 (167.2–951.0)a 239.6 (63.3–596.9)a 0.0036

Adiponectin (mg/mL) 12.9 (6.8–20.0)a 14.4 (9.1–24.8)a 10.3 (5.2–16.0)a 0.0030

IGF-I (ng/mL) 62.2 (38.6–91.4)a 43.7 (29.6–59.3)a 86.4 (66.2–118.6)a ,0.0001

IGFBP-3 (ng/mL) 2811.0 (1817–3943)a 3602.9 (2163.1–5200.0)a 2347.5 (1452.2–2940.0)a ,0.0001

LVEF (%) 32.8+10.2 30.5+9.3 35.0+10.6 0.0087

LVDd (mm) 58.9+10.4 60.9+10.2 56.9+10.2 0.021

Medication, n (%)

b-Blocker 98 (69.0) 46 (64.8) 52 (73.2) 0.28

ACEI/ARB 93 (65.5) 44 (62.0) 49 (69.0) 0.38

Statin 57 (40.1) 23 (32.4) 34 (47.9) 0.060

Digitalis 39 (27.5) 25 (35.2) 14 (19.7) 0.039

Diuretics 104 (73.2) 59 (83.1) 45 (63.4) 0.0080

Spironolactone 74 (52.1) 40 (56.3) 34 (47.9) 0.31

Nitrates 42 (29.6) 24 (33.8) 18 (25.4) 0.27

Amiodarone 36 (25.4) 22 (31.0) 14 (19.7) 0.12

PDEI 17 (12.0) 12 (16.9) 5 (7.0) 0.070

BMI, body mass index; NYHA, New York Heart Association; HF, heart failure; HbAlc, haemoglobin A1c; eGFR, estimated glomerular filtration rate; BNP, B-type natriureticpeptide; IGF, insulin-like growth factor; IGFBP-3, IGF-binding protein-3; LVEF, left ventricular ejection fraction; LVDd, left ventricular end-diastolic dimension; ACEI,angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; PDEI, phosphodiesterase inhibitor. Values are expressed as mean+ SD.aValues are expressed as median value (inter-quartile range).

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Cumulative survival of heart failurepatients with high vs. low insulin-likegrowth factor axisThe patients were followed for a median of 2.85 years (inter-quartile range: 0.92–3.30 years). Of the 142 patients, 34 (23.9%)died during the follow-up with 29 cardiac deaths including 13from HF and 7 sudden deaths, and 5 non-cardiac deaths.

The results of the Kaplan–Meier survival method and log-rankanalyses comparing the two groups stratified according to themedian value of the IGF axis are shown in Figure 3. The patientswith low IGF axis showed significantly poorer outcomes thanthose with high IGF axis in regard to the all endpoints.

Predictive potential of the insulin-likegrowth factor axis for mortalityUnivariate analysis with the Cox proportional hazards modelshowed that high age (x2 ¼ 18.56, P , 0.0001), low BMI (x2 ¼

9.68, P ¼ 0.0019), NYHA class III/IV (x2 ¼ 9.15, P ¼ 0.0025),CKD (eGFR , 60 mL/min/1.73 m2; x2 ¼ 6.19, P ¼ 0.013), highlog BNP (x2 ¼ 13.62, P ¼ 0.0002), high log adiponectin (x2 ¼

19.93, P , 0.0001), and low log IGF axis (x2 ¼ 6.56, P ¼ 0.010)were significant predictors of increased mortality (Table 4).

The results of multivariate analysis including age, sex, and foursignificant predictors by univariate analyses; anaemia, BMI, NYHAclass, and CKD, in addition to log IGF axis as variables indicatedthat log IGF axis was significantly and independently associatedwith all-cause mortality [relative risk (RR) ¼ 0.54, 95% confidenceinterval (CI) ¼ 0.30–0.92, P ¼ 0.022; Table 5, Model 1]. Log IGF

axis remained an independent predictor of mortality, afteradditional adjustment for log BNP (RR ¼ 0.55, 95% CI ¼ 0.31–0.94, P ¼ 0.027; Table 5, Model 2). However, when log adiponectin,which has a significant inverse correlation with log IGF axis, wasincluded in the multivariate model, the association between logIGF axis and mortality was lost. Thus, log IGF axis was not an inde-pendent predictor of mortality in the presence of log adiponectinas a covariate (Table 5, Models 3 and 4).

Cumulative survival according toinsulin-like growth factor axis inischaemic or non-ischaemic heartfailure patientsThe clinical backgrounds and biomarker levels in ischaemic andnon-ischaemic patients are shown in Supplementary materialonline, Tables S1 and S2, respectively. The tendency that thelow IGF axis group included older patients and patients withlower BMI, blood haemoglobin level, and serum triglyceride levelwas consistent in these subgroups. The Kaplan–Meier survivalmethod and log-rank analyses comparing the high vs. low IGFaxis groups showed that unadjusted survival was significantlybetter in patients with high IGF axis than in those with low IGFaxis in the non-ischaemic HF subgroup (P ¼ 0.017; see Supplemen-tary material online, Figure S2B). However, there was no significantdifference in unadjusted survival between the two groups in theischaemic HF patients (P ¼ 0.34; see Supplementary materialonline, Figure S2A).

Figure 2 Correlations between log-transformed insulin-like growth factor axis (log IGF axis) and cardiometabolic markers, including log-transformed serum adiponectin concentrations (log adiponectin, A) and plasma B-type natriuretic peptide (BNP) levels (log BNP, B), andbody mass index (BMI, C).

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DiscussionAltered glucose/fatty acid metabolism in cardiomyocytes has beendemonstrated in HF. Glucose/fatty acid metabolism is regulated bya number of circulating cardiometabolic factors, which includeIGF-I and adiponectin. In the present study, we showed that theIGF axis, a marker for serum IGF-I activity, may be a prognosticpredictor in HF.

The precise role of IGF-I in cardiomyocyte growth remainsunclear. A previous study using transgenic animals indicated thata-skeletal actin promoter-mediated overexpression of IGF-I inthe cardiac and skeletal muscles induced not only physiologicalcardiac hypertrophy in the early phases of post-natal developmentbut also pathological hypertrophy in the later phases of develop-ment.19 Insulin-like growth factor-I has also been shown to exertpositive inotropic effects on cardiomyocytes.20 In addition to

Figure 3 Kaplan–Meier analysis for all-cause mortality (A), cardiac mortality (B), or the composite of cardiac death and re-hospitalization dueto heart failure (C) after stratification of patients with heart failure into two groups according to the median value of insulin-like growth factoraxis (0.099).

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Table 3 Univariate and multivariate linear model of log IGF axis in heart failure patients

Variables Univariate correlation coefficient P-value Multivariate b coefficient (SE) P-value

Age (years) 20.15 0.077 20.006 (0.005) 0.23

Male gender 0.09 0.26

BMI (kg/m2) 0.09 0.31

NYHA class III/IV 20.19 0.022

HbA1c (%) 0.06 0.45

Total cholesterol (mg/dL) 0.04 0.61

Triglyceride (mg/dL) 0.25 0.0024 0.002 (0.001) 0.044

Haemoglobin (g/dL) 0.04 0.11

eGFR (mL/min/1.73 m2) 0.18 0.035

LVEF (%) 0.16 0.051

LVDd (mm) 20.23 0.0057 20.017 (0.006) 0.0067

Log adiponectin 20.35 ,0.0001 20.301 (0.096) 0.0021

Log BNP 20.25 0.0028

BMI, body mass index; NYHA, New York Heart Association; HbAlc, haemoglobin A1c; eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; LVDd,left ventricular end-diastolic dimension; BNP, B-type natriuretic peptide.

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these effects of IGF-I that are directly associated with cardiac mor-phology and function, IGF-I plays a regulatory role in cardiomyo-cyte metabolism, including translocation of the insulin-sensitiveGLUT4 to the cell surface. Enhanced glucose utilization may rep-resent a compensatory response in the failing heart, because thedependence on glucose as an energy source rather than freefatty acids is commonly seen in HF.

Because these characteristics of IGF-I suggest its beneficialeffects on metabolism, cell growth/survival, and function of cardio-myocytes, and because growth hormone (GH) is an upstreamstimulator of IGF-I, GH therapy has been tested in HF patients.Indeed, several small studies have shown that exogenous adminis-tration of GH improved symptoms, cardiac performance, and/orprognosis of HF, although the therapeutic benefits of this approach

remain controversial.21,22 Resistance to GH can occur in HFpatients and cause inconsistent benefits of GH therapy for HF.23

It is also unclear whether the activity of endogenous IGF-I isassociated with the prognosis of HF and whether IGF-I activitycan serve as a prognostic marker for HF. An associationbetween low serum IGF-I levels with increased mortality hasbeen reported in patients with HF.10,11 Nevertheless, severalcross-sectional studies that have measured IGF-I in HF patientsand in matched controls have reported conflicting results. Forinstance, Al-Obaidi et al.13 observed increased IGF-I levels inmild-to-moderate HF, whereas others have reported decreasedor unchanged levels in HF patients relative to controls.11,14 Oneof the reasons for these inconsistent results may be a discrepancybetween the circulating levels of IGF-I and the activity ofIGF-I. Therefore, we analysed the IGF axis, the ratio of IGF-I toIGFBP-3, which may represent overall IGF-I activity. The IGF axiswas lower in HF patients, particularly in those with severe HFwith NYHA class III/IV, than in the control subjects. This suggeststhat despite an increase in circulating IGF-I levels, IGF-I activity isactually reduced in HF. Therefore, we also analysed the associationbetween the IGF axis with another cardiometabolic marker adipo-nectin and an established HF marker BNP, because serum adipo-nectin levels predict the prognosis of HF patients.24– 27 Theresults revealed that log IGF axis was inversely correlated to logadiponectin and log BNP in our patients. Thus, it is possible thatthese factors share some of the regulatory mechanisms involvedin the pathological condition of HF. To the best of our knowledge,the present study is the first to show the significant inverserelationship of log IGF axis to log adiponectin and log BNP in HFpatients. Interactions between these factors may also be respon-sible for the correlations. Indeed, both IGF axis and adiponectinare important determinants of body composition. Besides, BNPand atrial natriuretic peptides (ANP) enhance the production ofadiponectin by human adipocytes and intravenous administrationof ANP increases circulating adiponectin levels in patients withHF.28,29

The unadjusted survival analysis indicated that HF patients with alow IGF axis had a poorer prognosis than those with a high IGFaxis. The multivariate Cox proportional hazards model confirmed

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Table 4 Univariate analysis for predictors of mortality

Oddsratio

95% CI x2 P-value

Lower Upper

Age (years) 1.08 1.04 1.12 18.56 ,0.0001

Male gender 1.21 0.57 2.86 0.23 0.63

BMI (kg/m2) 0.51 0.32 0.79 9.68 0.0019

NYHA class III/IV 2.86 1.45 5.88 9.15 0.0025

Anaemia 2.26 1.09 5.14 4.86 0.028

Smoking 0.58 0.29 1.15 2.44 0.12

Total cholesterol(mg/dL)

0.99 0.98 1.00 2.54 0.11

Triglyceride (mg/dL) 0.99 0.98 1.00 2.14 0.14

Chronic kidneydisease

2.85 1.23 7.73 6.19 0.013

Log BNPa 2.04 1.38 3.10 13.62 0.0002

Log adiponectina 2.43 1.62 3.80 19.93 ,0.0001

Log IGF axisa 0.65 0.46 0.90 6.56 0.010

CI, confidence interval; BMI, body mass index; anaemia, haemoglobin ,12 g/dL forwomen and ,13 g/dL for men. Chronic kidney disease, eGFR ,60 mL/min/1.73 m2; BNP, B-type natriuretic peptide; IGF, insulin-like growth factor.aOdds ratios and 95% CIs per 1-SD increment of a log-transformed marker.

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Table 5 Multivariate analysis for predictors of mortality

Odds ratio 95% CI x2 P-value

Lower Upper

Model 1 Log IGF axis 0.54 0.30 0.92 5.25 0.022

Model 2 (Model 1 + BNP) Log IGF axis 0.55 0.31 0.94 4.90 0.027Log BNP 1.04 0.67 1.75 0.03 0.85

Model 3 (Model 1 + adiponectin) Log IGF axis 0.66 0.36 1.16 2.08 0.15Log adiponectin 1.68 0.97 3.10 3.40 0.065

Model 4 (Model 1 + BNP + adiponectin) Log IGF axis 0.66 0.36 1.16 2.02 0.15Log BNP 0.85 0.50 1.50 0.33 0.56Log adiponectin 1.79 0.99 3.51 3.67 0.055

CI, confidence interval; IGF, insulin-like growth factor; BNP, B-type natriuretic peptide. Analyses 1 through 4 included adjustment for age (continuous), gender (male ¼ 1), anaemia(haemoglobin ,12 g/dL for women and ,13 g/dL for men), body mass index (kg/m2), NYHA class (III/IV), and chronic kidney disease (eGFR ,60 mL/min/1.73 m2). All oddsratios and 95% CIs per 1-SD increment of a log-transformed marker.

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the independent predictive value of log IGF axis for all-cause mor-tality, if log adiponectin level was excluded from the covariates.However, when log adiponectin was included in the model, logIGF axis was no longer an independent prognostic predictor.The significant inverse correlation between log IGF axis and logadiponectin might be responsible for this finding. There may beclose interactions between IGF-I and adiponectin in their regulat-ory mechanisms and the effects in the pathophysiology of HF.

Distinctive effects of IGF-I in ischaemic vs. non-ischaemic HFpatients may be expected. Enhanced IGF-I activity can promoteatherosclerosis but improvement of endothelial function byexogenous moderate doses of GH has been reported.30 In thepresent study, we observed a significant difference in mortalitybetween the high and low IGF axis groups only in non-ischaemicHF patients but not in ischaemic HF patients. This suggests amore complex effect of IGF-I in ischaemic HF patients, althoughthe number of patients might not be sufficient for this subgroupanalysis.

With regard to the role of IGF-I as a prognostic predictor, con-flicting results have been reported between HF patients andhealthy subjects. In one study, high IGF-I levels were associatedwith increased all-cause mortality and the risk of developing HFin normal subjects with normal LV systolic function, whereaspatients with established HF and a low IGF-I level had a poor prog-nosis.12,13 This ‘IGF-I paradox’ appears similar to the ‘obesityparadox’ and ‘adiponectin paradox’.25,31 Although healthy subjectswith obesity or low adiponectin levels carry greater risk for cardi-ovascular disease, patients with HF and high BMI or low adiponec-tin show better outcomes than those with low BMI or highadiponectin. Cardiac wasting (not body wasting) significantlyincreases the risk for mortality in HF.32 Weight loss in patientswith HF is associated with an increase in adiponectin, irrespectiveof the actual BMI level.27 Considering the similarity between IGFaxis and adiponectin, a low IGF axis may also serve as a markerfor cardiac cachexia.

LimitationsLimitations that are common to all observational studies should benoted in the interpretation of these results. The present study wasa single-centre study with a relatively small number of subjects;therefore, a prospective larger multicentre study is warrantedto confirm the significance of the IGF axis as a prognostic factorfor HF.

There were significant differences between the HF patients withhigh vs. low IGF axis in terms of some of the clinical and laboratoryparameters, and the treatments used. Although the impact of thesedifferences should be attenuated by the multivariate analysis, it isnot possible to remove all biases. Treatments used were onlyrecorded at the start of the study; thus, any changes in treatmentduring the follow-up could not be incorporated into the analyses.

Insulin-like growth factor-I levels in our control subjects wererelatively low compared with healthy subjects in previousreports.11,14 We analysed control subjects with some co-morbidconditions such as DM and dyslipidaemia to adjust their clinicalbackground to that of the HF patients. This might have causedthe differences in IGF-I levels between our control subjects andthe healthy subjects in previous reports. It is also possible that

there are some racial differences in IGF-I levels, since data onserum IGF-I levels in Japanese populations are limited.

Although we employed the IGF axis, the ratio of IGF-I toIGFBP-3, as a representative parameter of IGF-I activity becauseIGFBP-3 is the most abundant IGFBP in serum, other IGFBPs canalso influence IGF-I activity. In addition, pleiotropic effects ofIGFBP-3 which may enhance rather than inhibit the bioactivity ofIGF-I have been shown in culture cells.33,34 Thus, the IGF axismay not be an ideally accurate measure of IGF-I activity.

ConclusionThe IGF axis is reduced and inversely correlated with serumadiponectin and plasma BNP levels in HF patients. Heart failurepatients with low IGF axis showed increased risk for all-causemortality, cardiac death, and the composite of cardiac death andre-hospitalization. Cardiometabolic parameters including the IGFaxis and adiponectin are significantly associated with the prognosisof HF.

Supplementary materialSupplementary material is available at European Journal of HeartFailure online.

FundingThis work was supported in part by a Grant-in-Aid for ScientificResearch from the Ministry of Education, Culture, Sports, Scienceand Technology (MEXT) of Japan to Y.F., K.O., T.K., and T.K.

Conflict of interest: none declared.

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