Pathologic Background of Abnormal Serum Amyloid A

and Interleukin-6 Levels Revealed by a Piecewise Linear

Regression Model in the Population of Diabetic Patients

Yojiro Maehata, Masaichi-Chang-il Lee, Eisuke Maehata, Minoru Inoue, Fukashi Ishibashi, Chieko Kudo, Minoru Yamakado, Teruo Shiba

Hiroji Shimomura, Tetsuo Adachi, Yoshinori Tsurusaki, Ikukatsu Suzuki Kiyoshi Hirosawa, Takahiro Imazato, Noriko Ishida, Naoya Kishikawa, Naotaka Kuroda, Naoko Ikoshi, Yutaka Midorikawa, Tatsuya Ashikawa

Background The relationship between serum amyloid A (SAA) as an inflammation marker and

interleukin-6 (IL-6) as a factor inducing SAA provides an important insight into vascular lesions in a

population of diabetic patients. Methods We investigated the use of piecewise linear regression as a replacement for the simple correla-tion diagram method in order to uncover the pathologic condition hidden behind their correlation. Results and Conclusions Significant associations were found between SAA and IL-6 (r=0.469) and be-tween ferritin (Ft) and lipoprotein lipase (LPL) mass (r=0.314). We attempted to detect pathologic tenden-cies related to SAA in the abnormal range using the piecewise linear regression method, and confirmed the close relationship between SAA and IL-6 related to the mechanism for cytokine induction. In addi-

tion, our analyses characterized how the inflammation marker SAA was related to LPL mass as a marker of endothelial cell damage and Ft as an oxidative stress marker protein with antioxidant properties. (Nin-

gen Dock 2009 ; 23 : 7 -13)

Key Words : serum amyloid A (SAA), interleukin-6 (IL-6), piecewise linear hazard regression, oxidative stress marker, endothelial cell damage

The essential pathological features of type 2 dia- betes mellitus (DM) are lowered insulin secre----- tion and the development of insulin resistance.

Poor blood sugar control promotes insulin resistance,

From the "Department of Clinical Care Medicine, Division of Pharmacology, Kanagawa Dental College, 2)Division of Endocrinol-ogy and Metabolism, Department of Internal Medicine, Showa University Fujigaoka Hospital, and Hirosawa Research Institute of Health Science, 31Department of Endocrinology and Metabolism, PL Health Care Center, 44shibashi Clinic, 'Department of Pathophysiology-Periodontal Science, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, 6)Cen-ter for Multiphasic Health Testing and Services, Mitsui Memorial Hospital, 'Department of Internal Medicine, Mitsui Memorial Hos-pital, °Faculty of Health Science Technology, Bunkyo Gakuin University, 'Laboratory of Clinical Pharmaceutics, Gifu Pharmaceu-tical University, ID'Hirosawa Research Institute of Health Science, "'Clinical Laboratories, Sasebo Chuo Hospital, 12'Graduate School of Science and Technology, Nagasaki University, "'Division of Analytical Chemistry, Course of Pharmaceutical Sciences, Depart-ment of Environmental and Pharmaceutical Sciences, Graduate School of Biomedical Sciences, Nagasaki University, "Laboratory of Clinical Nutrition and Medicine, Kagawa Nutrition University, 15)Suzuka University of Medical Science, and "Eiken Chemical Co., Ltd. Address for Reprints : Yojiro Maehata, Department of Clinical Care Medicine, Division of Pharmacology, Kanagawa Dental College, 82 Inaoka-cho, Yokosuka-city, Kanagawa 238-8580, Japan. Tel. +81— 46-822-8836;Fax. +81-46-822-8868;E-mail. maehata@kcicnet.ac.jp Received April 7, 2008 ; Revised June 8, 2008 ; Accepted July 10, 2008

leading to the development of metabolic syndrome. This frequently produces oxidative stress conditions,2 and finally creates a basis for diabetic macroangiopathy typified by atherosclerosis.

Serum amyloid A (SAA) is a single-chain protein with a molecular weight of 12,000 containing no sugar. It is synthesized in the liver responding to the stimulation of cytokines, and mostly occurs in the form bound to HDL3. We have been using a latex re- agent (Eiken Chemical Co., Ltd., Tokyo, Japan) based

on the method of Yamada et c11.3,4 in the studies com-

paring SAA and hs-CRP levels in the groups of pa-tients with DM and patients with tuberculosis.5.6 The results have empirically demonstrated the usefulness of these substances as inflammatory proteins that increase reflecting pathologic conditions. On the other hand, we realized the limitation of conventional mass analysis in accurately grasping the relationship between interleukin-6 (IL-6) as a factor effecting the elevation of SAA

production and SAA, and considered that a search for information suggesting preclinical conditions hidden in the sampled population may reveal a solution. How-ever, because the target of analysis was the nonlinear relationships in the data, application of a linear model might be misleading.

For this reason, we applied a nonlinear model with Nakamura' s piecewise hazard regression method (called the regression method in this paper),7 which automati-

8 Ningen Dock 2009 ; 23 : 7 —13

cally determines the settings. Adapting this method to the analysis of the population of clinical laboratory data involving SAA, we conducted a series of exami-nations to gain information on new SAA abnormalities related to IL-6.

Methods

Subjects We randomly selected 104 outpatients with DM (age 58±11). Blood and urine were collected when the 'pa-tients visited the Outpatient Department in fasting con-dition.

Methods

(i) Metabolic syndrome markers : TG and HDL cholesterol (HDL-C) measured with enzymatic

assay.

(ii) Adipocytokine marker : IL-6 measured with a LUMIPULSE-IL-6 Kit (Fujirebio, Inc., Tokyo,

Japan).

(iii) Oxidative stress (antioxidant protein) marker : Ferritin (Ft) measured with latex agglutination

turbidimetric immunoassay (Eiken Chemical Co., Ltd.).

(iv) Inflammatory . markers : SAA and hs-CRP meas- ured with latex agglutination turbidimetric im-

munoassay (Eiken Chemical Co., Ltd.).

(v) Arteriosclerosis marker : Adiponectin (Adipo) measured with an enzyme-linked immunosorbent

assay (ELISA) method (High Molecular Weight Adiponectin Kit) (Fujirebio, Inc.).

(vi) Insulin resistance marker : Homeostasis model as- sessment ratio (HOMA-R) according to the for-

mula of Matthews (HOMA-R=fasting blood sugar

(FBS) (mg/dl) x fasting immunoreactive insulin (FIRI) (41/m1)/405).8

(vii) Vascular endothelial cell injury markers : Albu- min excretion index (AEI) measured as the

Bennett index,9 lipoprotein lipase protein mass (LPL mass) measured with an ELISA method

(LPL ELISA "DAIICHI" ; Daiichi Pure Chemi- cals Co., Ltd., Tokyo, Japan), and extracellular

superoxide dismutase (EC-SOD) measured with the ELISA-Adachi method.10

(viii) DM markers : blood sugar (Glu) measured with enzymatic assay (Glu-D method) and glycohe-

moglobin (HbAic) measured with a high-

performance liquid chromatography (HPLC) method (HA-8150 ; ARKRAY, Inc., Kyoto, Ja-

pan).

Analysis Using the Regression Method Using an ordinary linear model in the analysis of

clinical data involving nonlinear relationships may cause problems such as insufficient power of test and an inappropriately high level of significance. We there-fore used a piecewise linear model method that was capable of automatically determining nonlinear models with satisfactory goodness of fit. Due to the good fit of the model to data, piecewise linear models are rela-tively immune to the lowering of the power of test and the increase in the level of significance. Regres- sion equations were determined using a stepwise re-

gression method. In this process, the candidate for the

change point in the regression of SAA vs. IL-6 was set at 814/m1 vs. 3 pg/ml, and that of Ft vs. LPL mass was set at 300 ng/ml vs. 50 ng/ml, adopting the standard cut-off levels.

Results

Features in Profile Data The profile data related to the markers of lifestyle

related disease were BP (systolic) of 136±7 mmHg, AEI of 132±410 mg/g Cr, Glu of 155±42 mg/dl, HbA lc of 6.8±1.2%, HOMA-R of 3.5±3.3, TG of 135 ±110 mg/dl, and HDL-C of 57±15 mg/dl. The abnor-mality of items related to DM was characteristically shown in the markers of lifestyle related disease.

Association Tendencies in Insulin Resistant Condition The levels of HOMA-R (mean±SD) in the normal

range (n=43 ; HOMA-R<2) were 1.3±0.4, those in the borderline range (n=21 ; 2 HOMA-R<3) were 2.4± 0.3, and those in the established range (n=40 ; HOMA-R 3) were 6.5±3.7. We examined the rise in the level of markers related to endothelial cell damage in these 3 ranges.

In these ranges, mean SAA levels changed from 6.1 to 9.6 and to 8.2 [ig/ml, showing a peak in the bor-derline range, while hs-CRP showed a tendency to

gradual increases from 0.07 to 0.11 and to 0.16 mg/dl. Among the markers related to endothelial cell dam-

age, AEI increased from 89 to 105 and to 191 mg/g Cr, and Ft increased from 121 to 145 and to 202 ng/ml. These changes were kinetic. In contrast, LPL mass decreased from 71 to 62 and to 54 ng/ml, and Adipo also decreased from 9.3 to 6.2 and to 5.6

1..tg/ml. The pathologic tendencies clearly demonstrated the antagonistic mechanism (atherosclerotic vs. anti-atherosclerotic actions) in the insulin resistant condition.

Progression of SAA Abnormality (Fig. 1) We examined the association tendencies observed

with the progression of SAA abnormality from slight

(SAA<10 p,g/m1) to moderate (10 SAA<201u.g/m1) and to severe (SAA 20 ptg/m1). The items that showed as-sociated increasing tendencies were hs-CRP (0.08-0.21---0.33 mg/dl) and IL-6 (2.63—.3.40—^12.35 pg/ml), while an inversely associated decreasing tendency was seen in Ft (165—÷133—^115 ng/ml). The relationship between Ft and SAA was antagonistic.

The result regarding the relationship between SAA and the adipocytokine-like substance (IL-6) suggested the influence of oxidative stress (Ft) in the early stage of pathological elevation.

Regression of SAA vs. IL-6 (Figs. 2 and 3) The simple correlation between SAA and 1L-6 (n=

104) was significant (p<0.001) with the correlation co-efficient of r=0.469. We further examined the details of the pathologic condition using the regression method. The piecewise linear regression line was de-fined based on the change point, and the areas above and below the line were respectively designated as the

(+) area and the (—) area. We examined the relation-ship between the levels of other parameters in the (+)

group (n=33) vs. the (—) group (n=21), aiming at identifying and characterizing the ability to detect the

Fig. 2. Relationship between serum amyloid A (SAA) and interleukin-6 (IL-6) in the piecewise liner regres-sion model. Correlation between SAA and IL-6 is sig-nificant (r=0.469, p<0.001). IL-6 and hs-CRP rise in the regression (+) area (•). Homeostasis model as-sessment ratio (HOMA-R) and TG rise in the regres-sion (—) area (0).

underlying pathologic condition. The results showed that TG in the (+) group vs. the

(—) group was 118 vs. 163 mg/dl, while HOMA-R was 3.9 vs. 4.7. Both items showed increases in the (—) group. On the other hand, IL-6 was 7.6 vs. 2.3 pg/ml and hs-CRP was 0.21 vs. 0.11 mg/dl, showing in-creases in the (+) group. According to the above re-sults of the piecewise linear regression analysis of SAA vs. IL-6, the abnormal changes in the (+) group

were characterized by the items related to inflammation

(IL-6 and hs-CRP), while those in the (—) group were characterized by induced lipoprotein abnormality (TG and HOMA-R).

Regression of Ft vs. LPL Mass (Figs. 4 and 5) The simple correlation between Ft and LPL mass (n=

104) was significant (p<0.01) with the correlation coef-ficient of r=0.314. In this analysis, the items that tended to increase in the (+) group (n=50) were SAA

(mean 7.8 µg/m1), EC-SOD (mean 132.8 ng/ml), and Adipo (mean 8.9 µg/ml). On the other hand, features in the (—) group were the increases in HOMA-R and TG, similarly to the result in above. Based on this re-sult of analysis, we focused attention on how the pa-thologic condition was reflected in the level of SAA as an acute-phase inflammation marker. We therefore estimated the inductive effect of IL-6 and examined the association between SAA and IL-6 in this analytical

group.

Correlation Between SAA and IL-6 in the (+) Group in Ft vs. LPL Mass Regression (Figs. 6 and 7)

The simple correlation (n=50) between Ft and LPL mass in the (+) group defined by piecewise linear re-

gression was significant (p<0.01) with the correlation coefficient of r=0.442. In addition, it was found that the data points were broadly divided into the kinetic

group (signed II) with IL-6 levels below 6 pg/ml, where IL-6 was essentially related to the expression (n=10, r=0.910, p<0.001) of SAA, and the non-kinetic group (signed 0) with IL-6 levels exceeding 6 pg/ml lack-ing such relationship (n=40, r=0.042, p=N.S). Using this classification, we made a comparison of DM mor-bidity levels between the IL-6<6 pg/ml group (signed

Fig. 4. Relationship between ferritin (Ft) and lipo-

protein lipase (LPL) mass in the piecewise linear re- gression model. The correlation between LPL mass

and Ft is significant (r=0.314, p<0.01). Serum amy- loid A (SAA), adiponectin (Adipo), and extracellular

superoxide dismutase (EC-SOD) rise in the regres- sion (+) area (0). Homeostasis model assessment

ratio (HOMA-R) and TG rise in the (—) area (0).

0) and the IL-6 z 6 pg/ml group (signed 0) regard-ing the mean levels of HOMA-R, Glu, and HbA lc. In these groups, HOMA-R was 2.3 and 3.4, HbA 1 c was 6.6 and 7.7% and Glu was 144 and 181 mg/dl, respec-

tively. Each of these items showed higher levels in the IL-6>6 pg/inl group, indicating a feature consistent with the established DM condition (Fig. 7). This result sug-

gested that the kinetic group in SAA analysis had been affected by oxidative stress and in a condition in-duced by IL-6, and this was inferred to be responsible for the elevation of SAA expression. On the other hand, the non-kinetic group was considered to have had cytokine-mediated inflammation, resulting in the rise in SAA alone.

Discussion

SAA is the precursor of amyloid A protein deposits in secondary amyloidosis as a complication of chronic inflammatory diseases.1I In blood, most SAA is bound to HDL3. While the isoforms SA/6i' and SAA2 behave as acute-phase inflammatory proteins, SAA 1 plays the central role. SAA is the inflammatory protein showing the highest rate of increase. While its half-life is shorter than that of CRP, it increases more extensively and more shai;ply. ' 2 Based on these facts, a study has been conducted to evaluate the pathologic condition from the SAA/CRP ratio.13 As an inflammatory mecha-nism is involved in atherosclerosis, the inflammation marker CRP increases in the atherosclerotic process, and SAA correlated with it accompanies this increase.

The use of this inflammatory marker as a test for evaluating the pathologic condition in patients with DM has been promoted partly as a result of increased emphasis on vascular lesions in lifestyle related disease at the stage of prophylactic screening. This trend is

Fig. 6. Correlation between serum amyloid A (SAA) and interleukin-6 (1L-6) in the (+) group identified in the piecewise linear regression of .ferritin (Ft) vs. lipo-protein lipase (LPL) mass. Correlation between 1L-6 and SAA is significant (r=0.442, p<0.01). No correla-tion (r=0.042, p=NS) in the IL-6<6 pg/ml group (0, n= 40). Marked correlation (r=0.910, p<0.001) in the IL-6

z6 pg/ml group (0, n=10).

spurred by the national project to tackle metabolic syn-drome, which introduces special health examination and

guidance for the users of medical services (insured persons and their dependents) aged 40 or over, starting in 2008. Considering the extent of the effects of insu-lin resistance, it is necessary to look into pathological changes in metabolic syndrome focusing on not only oxidative stress due to active oxygen species'= and in-flammatory cytokines such as tumor necrosis factor-a (TNF-a) and IL-6 released from fat cells but also the close involvement of adipocytokines ' 5. Furthermore, the elevation of oxidative stress induces an increase in gly-cation, lowering of the affinity of heparin-like sub-stances, and the release of endothelial cell-bound EC-SOD'6, as well as the removal of LPL mass, which also has anti-atherosclerotic properties, from the cell surface. We therefore decided to examine how the pa-thologic condition is reflected in the anti-oxidative pro-tein Ft and other parameters.

Vascular lesions in the presence of metabolic syn-drome usually show a kinetic association between SAA and CRP during the acute phase of inflammation, but these parameters move independently of each other in some patients in the chronic phase. In our past exami-nation, the group of DM patients showing abnormally

Fig. 7. Behavior of homeostasis model assessment ratio (HOMA-R), glycohemoglobin (HbArc), and blood sugar (Glu) in the (+) group identified in the piecewise linear regression of ferritin

(Ft) vs. lipoprotein lipase (LPL) mass. In the comparison of interleukin-6 (IL-6).6 vs. IL-6>6 pg/ml, increasing tendencies are seen with HOMA-R (2.3±2.8 vs. 3.4±2.7) and HbAic (6.6± 0.9% vs. 7.7±1.7%), while Glu shows a significant rising tendency of 144±30 vs. 181±45 mg/dl.

high levels in the comparative .examination of SAA and hs-CRP could be clearly classified into the hyper-lipidemia group and the diabetic nephropathy group.5 We also demonstrated that high SAA in patients with tuberculosis was significantly correlated with HOMA-R, and we also looked into the relationship with endothe-lial cell damage.6 We considered that an effective way to study the pathology of vascular lesions would be to examine the associations among inflammation markers,

pro-inflammatory cytokines, oxidative stress markers, and endothelial cell damage markers. Focusing on the vascular lesions in DM, we decided to determine the concrete pathologic condition related to IL-6 and SAA, as well as Ft and LPL mass. In such an attempt, the application of ordinary linear models to the data in-volving nonlinear associations would result in the in-ability to detect significant associations and the false detection of nonexistent associations. This problem was overcome by the use of Nakamura's regression method.?

We used the regression method in an ingenious way, in which the settings for piecewise linear regression were determined based on the change point. The result was that the (+) group in the regression analysis of the SAA vs. IL-6 correlation (Fig. 2) was character-ized by the increases in IL-6 and hs-CRP, while the

(+) group in the analysis of the Ft vs. LPL mass cor-relation (Fig. 4) was characterized by the increases in SAA, Adipo, and EC-SOD. On the other hand, the (—)

group showed the increases in HOMA-R and TG in both of these correlations, revealing the characteristic features of pathologic tendencies. With respect to the relationship between the anti-oxidative protein Ft (oxi-dative stress marker) and anti-atherosclerotic LPL mass

(endothelial cell damage marker), the (+) group showed a rise in SAA under the influence of oxidative stress, and a close relationship with IL-6 values was sug-

gested. The group plotted with signed • (n=10) on the correlation chart (Fig. 6) was the kinetic group, in

which IL-6 was considered to play an essential role as a cytokine inducing the expression of SAA. On the other hand, the group plotted with signed 0 (n=40) was the non-kinetic group, which was considered to represent a simple inflammation phenomenon without the relationship with IL-6. To summarize the changes in the pathologic condition related to SAA, we com-pared the levels of SAA and •hs-CRP inflammation markers, considering the fact that the peak activity was observed in the AEI-Micro group. In the group plotted with signed 0 (n=40), SAA showed significant corre-lations with HOMA-R and HbAlc, but hs-CRP showed no correlations. This result confirmed the observation reported by Muramoto et al .17 regarding HOMA-R in the early stage of DM. On the other hand, these data indicated that the pro-inflammatory cytokine IL-6 is es-sential to the expression of SAA in this group and suggested the presence of a close relationship. Because SAA occurs in the form bound to HDL, the relation-ship with HDL is likely important, and an investiga-tion focusing on this action mechanism is considered necessary. It has been reported that the SAA produced in the liver works in the reverse cholesterol transport system and exerts an anti-atherosclerotic action when it is bound to HDL, while it exerts a pro-atherosclerotic action when it is bound to LDL.11

In the present study, the groups with SAA levels below 1014/ml, 10-20 µg/ml, and above 2014/ml showed slight increases in HDL-C levels from 56 to 58 and to 59 mg/dl, respectively (Fig. 1).

The concomitant relationship between SAA and HDL may be a source of valuable pathologic information,

which should not be overlooked. We plan to investi-

gate this theme in future studies. This report describes the findings regarding SAA obtained by the use of the

regression method. This analytical method confirms the

essential involvement of IL-6 in SAA expression and

characterizes the relationship between these parameters.

Conclusion

We investigated novel relationships involving SAA and IL-6 using the regression method in an analysis of the population of DM patients. In this process, we set the change point according to accepted standard levels, and defined the (+) group and the (-) group corre-sponding to the areas above and below the regression line. We examined the changes in various parameters in this setting, and the results enabled us to identify such parameters as Ft. EC-SOD, and LPL mass as the means to grasp the relationship with the underlying pa-thologic condition. In particular, the understanding of the involvement of IL-6 in the elevation of SAA pro-duction provides valuable information supporting the

prediction of angiopathy aggravation and progression. As a result of this analysis, we identified a condition with the induction of SAA under the influence of oxi-dative stress.

In conclusion, our results suggest the relevance of SAA measurement as an indicator of vascular lesions in metabolic syndrome.

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