Retrospective Study
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Exp Med. Nov 20, 2015; 5(4): 232-243
Published online Nov 20, 2015. doi: 10.5493/wjem.v5.i4.232
Association of insulin resistance with serum ferritin and aminotransferases-iron hypothesis
Jean Huang, Rudruidee Karnchanasorn, Horng-Yih Ou, Wei Feng, Lee-Ming Chuang, Ken C Chiu, Raynald Samoa
Jean Huang, Wei Feng, Ken C Chiu, Raynald Samoa, Department of Clinical Diabetes, Endocrinology, and Metabolism, City of Hope National Medical Center, Duarte, CA 91010, United States
Jean Huang, Wei Feng, Ken C Chiu, Raynald Samoa, Division of Endocrinology, Metabolism and Nutrition, Department of Internal Medicine, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
Rudruidee Karnchanasorn, Division of Endocrinology, Department of Medicine, University of Kansas Medical Center, Kansas City, KS 66160, United States
Horng-Yih Ou, Division of Endocrinology and Metabolism, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan
Lee-Ming Chuang, Graduate Institute of Preventive Medicine, School of Public Health, National Taiwan University, Taipei 100, Taiwan
Author contributions: Chuang LM, Chiu KC and Samoa R conceived and designed the study; Huang J, Karnchanasorn R and Ou HY obtained data under the direction of Chiu KC, Chuang LM and Samoa R; Feng W, Chiu KC and Samoa R reviewed data; Huang J, Karnchanasorn R, Chuang LM, Chiu KC and Samoa R did statistical analyses and interpreted data; Huang J, Chiu KC and Samoa R drafted the manuscript; all authors revised the manuscript for important intellectual content; Feng W, Chiu KC and Samoa R provided administrative, technical, and material support; Chiu KC and Samoa R contributed equally as senior authors of this study.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Institutional review board statement: The National Center for Health Statistics of the Centers for Disease Control and Prevention conducted the NHANES III in the United States from 1988 through 1994. This survey was designed to assess the health and nutrition status of a large representative sample in the United States. The survey and data collection was approved by the NHANES Institutional Review Board (IRB).
Informed consent statement: Documented consent was obtained from participants of the NHANES III at the participation of survey.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Ken C Chiu, MD, FACE, Department of Clinical Diabetes, Endocrinology, and Metabolism, City of Hope National Medical Center, 1500 E Duarte Rd, Duarte, CA 91010, United States. kchiu@coh.org
Telephone: +1-626-2180111 Fax: +1-626-2188489
Received: May 10, 2015
Peer-review started: May 12, 2015
First decision: July 27, 2015
Revised: October 19, 2015
Accepted: November 3, 2015
Article in press: November 4, 2015
Published online: November 20, 2015

Abstract

AIM: To investigate the relationship of iron indices with diabetes mellitus (DM) in those without hemochromatosis.

METHODS: This cross-sectional study examined data collected during the Third National Health and Nutrition Examination Survey (NHANES III). Only those who fasted properly and were not anemic with transferrin saturation < 45% were included (n = 6849). Insulin sensitivity and beta cell function were calculated from fasting glucose and insulin concentrations. Indices of iron metabolism were examined in the presence or absence of DM. We examined the relationship of insulin sensitivity and beta cell function with serum ferritin concentration. The influence of C-reactive protein and liver enzymes was also investigated.

RESULTS: Serum ferritin concentration was significantly higher in diabetic subjects (P = 0.0001 to < 0.000001). The difference remained significant after adjustment for age, body mass index, alcohol consumption, and mineral/iron supplement (P = 0.03 to < 0.000001). In those who did not take insulin, serum ferritin concentration was negatively associated with insulin sensitivity (P = 0.05 to 0.00001), but not with beta cell function. The alanine aminotransferase was correlated with serum ferritin concentration (P = 0.02 to < 0.000001) but not with insulin sensitivity, suggesting the role of the liver in iron-associated insulin resistance.

CONCLUSION: As most of diabetes is type 2 diabetes and insulin resistance is a cardinal feature of type 2 diabetes, disordered iron metabolism could play a role in the pathogenesis of insulin resistance and type 2 diabetes through its effect on liver function.

Key Words: Diabetes mellitus, Insulin sensitivity, Beta cell function, Ferritin, Liver

Core tip: Hemochromatosis and excess iron load has been implicated to play a role in the pathogenesis of diabetes mellitus. Serum ferritin concentration was significantly higher in diabetic subjects. Serum ferritin concentration was negatively associated with insulin sensitivity, but not with beta cell function. The association of alanine aminotransferase correlated with serum ferritin concentration, but not insulin sensitivity, suggesting the role of the liver in iron-associated insulin resistance. Disordered iron metabolism could play a role in the pathogenesis of insulin resistance and type 2 diabetes mellitus through its effect on liver function.



INTRODUCTION

Diabetes mellitus (DM) is a common manifestation (53%-80%) of hereditary hemochromatosis[1], which is an autosomal recessive disorder caused by mutations in a gene designated HFE (OMIM: 235200). A mutation, C282Y, was detected in 83% of the patients, while it was only found in 3.2% of control chromosomes[2]. However, the allelic frequencies of C282Y mutation were similar between diabetic and control groups (6.3% vs 5.5%) in a large population from the United Kingdom[3]. Meta-analysis of published studies showed no evidence for over-representation of this allele in patients with type 2 diabetes[3]. Therefore, the C282Y mutation does not play a role in the pathogenesis of type 2 diabetes. Nevertheless, the role of iron metabolism in the pathogenesis of diabetes in the general population has been suggested in many cross-sectional studies[4-7]. Furthermore, a nested case-control study suggested a potential interaction between the HFE genotypes and heme iron in relation to the risk of type 2 diabetes[8].

In hereditary hemochromatosis, both insulin resistance and impaired insulin secretion have been suggested to play a role in its pathogenesis[9]. The role of insulin resistance in patients with secondary hemochromatosis from thalassemia major has been reported, while an additional defect in beta cell secretion cannot be excluded[10]. The association of serum ferritin concentration and insulin resistance has been reported in various liver diseases[11,12]. Furthermore, the underlying mechanism of iron-associated abnormal glucose homeostasis in the general population is not well understood.

To examine the role of iron in the pathogenesis of diabetes, we investigated the iron indices and the relative influence of an inflammatory marker and liver enzymes on glucose homeostasis in a nationally representative survey, third National Health and Nutrition Examination Survey (NHANES III).

MATERIALS AND METHODS
Ethics statement

The National Center for Health Statistics of the Centers for Disease Control and Prevention conducted the NHANES III in the United States from 1988 through 1994. This survey was designed to assess the health and nutrition status of a large representative sample in the United States. The survey and data collection was approved by the NHANES Institutional Review Board and documented consent was obtained from participants. Analysis of de-identified data from the survey is exempt from the federal regulations for the protection of human research participants. Only de-identified data from the survey was used in this study.

Study design and study sample

Detailed descriptions of the survey and the analytical methods of various assays have been published[13] and are also available at its website (http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm#NHANESIII ).

Race and ethnicity were self-reported by the participants. NHANES III was designed to provide reliable information from three major racial/ethnic groups: Non-Hispanic whites (NHW), non-Hispanic blacks (NHB), and Hispanics. The 4th group was excluded from this analysis for its small sample size and for encompassing a heterogeneous racial/ethnic group. There were 15021 subjects who had serum ferritin, fasting glucose and insulin concentration measured. Proper fasting is required to define diabetes status and to calculate insulin sensitivity and beta cell function from the fasting samples[14,15]. Only those who fasted for ≥ 8 h and ≤ 16 h were included (n = 7701). We excluded 180 subjects with hemoglobin < 11 g/dL, which is frequently associated with iron deficiency and falsely low HbA1C. Since hemochromatosis is an established cause of diabetes, those with transferrin saturation ≥ 45 were also excluded[16] (n = 672), which identified 98% of iron-overloaded subjects[17].

Ascertainment of DM

Diabetes was defined as a fasting glucose concentration ≥ 126 mg/dL (7.0 mmol/L) or a 2-h postchallenged glucose concentration ≥ 200 mg/dL (11.1 mmol/L)[14]. Without the 2-h postchallenged glucose concentration, the diagnosis of diabetes is frequently missed in those with elevated 2-h postchallenged glucose concentrations and normal fasting glucose concentrations[18]. However, only 3010 subjects had 2-h postchallenged glucose concentration measured. Their HbA1C was very well correlated with 2-h postchallenged glucose concentration (r = 0.7558, P < 0.000001) and 2-h postchallenged glucose concentration of 200 mg/dL (11.1 mmol/L) was equivalent to HbA1C of 6.3%. Therefore, we also defined diabetes in those with HbA1C ≥ 6.3%.

Calculation of beta cell function and insulin sensitivity

Beta cell function (%B) and insulin sensitivity (%S) were calculated based on the homeostasis model assessment (HOMA)[15,19].

%B=(20 × fasting insulin concentration in mU/L)/(fasting glucose concentration in mmol/L - 3.5).

%S = 22.5/(fasting insulin concentration in mU/L × fasting glucose concentration in mmol/L).

Those with fasting glucose concentration < 3.5 mmol/L were excluded from analysis, since they had negative %B (n = 9). %B and %S obtained from the HOMA had been shown to correlate very well with the measured beta cell function and insulin sensitivity from various methods[15,20-22]. A quantitative insulin sensitivity check index (QUICKI), which had been shown to correlate with the measured insulin sensitivity by hyperinsulinemic euglycemic clamp very well[23], was also used.

QUICKI=1/[log10(fasting insulin concentration in mU/L) + log10(fasting glucose concentration in mg/dL)].

All of these methods have been validated in both non-diabetic subjects and diabetic subjects who did not take insulin[21-23]. Those who took insulin were excluded from these analyses (n = 51).

Statistical analysis

General descriptive variables were expressed as means ± SD. Since gender and ethnicity could potentially affect both iron metabolism and glucose homeostasis, the data were analyzed separately by gender and ethnic groups. Continuous variables were compared using two-tail Student t test between two groups or Analysis of Variance for more than two groups. Continuous data were expressed as means with 95%CI. Analysis of variance was used to examine the influence of covariates [age and body mass index (BMI)] on continuous variables between two groups. Least square regression analysis was used to investigate the relationship between two continuous variables. The influence of covariates (age, BMI, alcohol consumption, and mineral/iron intake) was also accounted for least square regression analysis. To further assess the association of serum ferritin concentration with estimated beta function and insulin sensitivity indices as well as the association of liver aminotransferases and C-reactive protein (CRP) with serum ferritin concentration and estimated insulin sensitivity indices, we also examine the trend across the quintile of serum ferritin concentration, liver aminotransferases and CRP. The comparisons were also adjusted for age, BMI, alcohol consumption, and mineral/iron intake. All the analyses were conducted in SYSTAT 11, Systat Software, Inc., Point Richmond, California, United States. A P value less than 0.05 was considered significant.

RESULTS
Study populations

The clinical features of the studied subjects were shown by gender and ethnic groups in Table 1. Based on previously published upper reference ranges[24], in male participants, 8.2% had elevated aspartate aminotransferase (AST > 37 U/L) and 9.6% had elevated alanine aminotransferase (ALT > 40 U/L) and in female participants, 7.7% had elevated AST (> 37 U/L) and 7.1% had elevated ALT (> 37 U/L).

Table 1 Clinical features of studied subjects.
Non-Hispanic whites
Non-Hispanic blacks
Hispanics
MaleFemaleMaleFemaleMaleFemale
n137316028961057957964
Age (yr)55 ± 1954 ± 2043 ± 1742 ± 1642 ± 1741 ± 17
Systolic blood pressure (mmHg)130 ± 18125 ± 21128 ± 18122 ± 20125 ± 17120 ± 20
Diastolic blood pressure (mmHg)76 ± 1072 ± 979 ± 1174 ± 1176 ± 1071 ± 10
Body mass index (kg/m2)26.75 ± 4.6326.39 ± 5.8026.74 ± 5.3429.07 ± 7.2227.10 ± 4.6428.26 ± 5.97
Transferrin saturation (%)27.93 ± 8.3924.58 ± 8.7826.22 ± 8.1121.75 ± 8.5128.23 ± 8.5922.95 ± 8.98
Ferritin (mcg/L)176 ± 14295 ± 104215 ± 17093 ± 111169 ± 14267 ± 95
Aspartate aminotransferase (U/L)22 ± 819 ± 825 ± 1722 ± 827 ± 1623 ± 19
Alanine aminotransferase (U/L)18 ± 1114 ± 1019 ± 1318 ± 1128 ± 2421 ± 23
Gamma glutamyl transferase (U/L)35 ± 5521 ± 2046 ± 5935 ± 5546 ± 5330 ± 31
C-reactive protein (mg/dL)0.43 ± 0.760.45 ± 0.620.48 ± 0.790.53 ± 0.650.44 ± 0.840.53 ± 0.80
Comparison of indices of iron metabolism in the presence or absence of diabetes

Iron, total iron binding capacity (TIBC), transferrin saturation, and serum ferritin concentration were compared between those with or without diabetes (Table 2). No consistent results were observed for iron, TIBC, and transferrin saturation, while serum ferritin concentration was markedly higher in diabetic than in non-diabetic subjects in all six groups. Diabetic subjects were older than non-diabetic subjects by 14-16 years (P < 0.000001) and were also more obese than non-diabetic subjects per BMI by 2.40-4.81 kg/m2 (P < 0.000001). The difference in ferritin concentration between diabetic and non-diabetic subjects remained significant after adjustment of age, BMI, alcohol intake, and mineral/iron supplement. Thus, diabetes was associated with elevated serum ferritin concentration.

Table 2 Comparison of serum indices of iron by the presence or absence of diabetes mellitus.
Non-Hispanic whites
Non-Hispanic blacks
Hispanics
Male
Female
Male
Female
Male
Female
DMNon-DMDMNon-DMDMNon-DMDMNon-DMDMN0n-DMDMNon-DM
n1661207137146598798106951115842132832
Iron (mcg/dL)
Mean939583878287707590988284
(95%CI)(89, 97)(94, 97)(78, 88)(86, 89)(77, 87)(85, 89)(64, 75)(74, 77)(84, 97)(96, 100)(76, 87)(82, 86)
P1NSNSNSNS0.01NS
P2NSNSNSNSNSNS
P3NSNSNSNSNSNS
Total iron binding capacity (mcg/dL)
Mean351344359360333334342353353354362377
(95%CI)(343, 359)(341, 346)(350, 368)(357, 363)(322, 344)(330, 337)(331, 352)(349, 356)(343, 363)(351, 358)(351, 373)(372, 381)
P1NSNSNSNSNS0.01
P20.002NSNSNSNSNS
P3NSNSNSNSNSNS
Transferrin saturation (%)
Mean272823252526212226282323
(95%CI)(26, 28)(28, 29)(22, 25)(24, 25)(23, 26)(26, 27)(19, 22)(21, 22)(24, 28)(27, 28)(22, 25)(22, 23)
P1NSNSNSNS0.03NS
P2NSNSNSNSNSNS
P3NSNSNSNSNSNS
Ferritin (mcg/L)
Mean228169152842822061678623015013856
(95%CI)(200, 256)(161, 177)(129, 175)(79, 89)(237, 327)(195, 218)(139, 195)(79, 92)(190, 270)(142, 159)(104, 171)(52, 60)
P1< 0.000001< 0.0000010.00003< 0.000001< 0.000001< 0.000001
P20.00010.0000030.020.00010.00001< 0.000001
P30.00020.0000030.030.00010.000004< 0.000001
Association of serum ferritin concentration with beta cell function and insulin sensitivity

Diabetes results from an imbalance between beta cell function and insulin sensitivity. Thus, serum ferritin concentration could potentially be associated with either beta cell function, insulin sensitivity, or both. No association between %B and serum ferritin concentration was found after adjustment for both age and BMI (Table 3). In contrast, serum ferritin concentration was negatively associated with %S and QUICKI in all six groups. This relationship persisted after adjustment for age, BMI, alcohol consumption, and mineral/iron supplement. Therefore, we concluded that ferritin concentration was negatively associated with insulin sensitivity.

Table 3 Estimated beta cell function and insulin sensitivity indices by quintile of serum ferritin concentrations.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5P1P2P3
Beta cell function by the homeostasis model assessment (%B)4
Non-Hispanic white males103 (96, 110)98 (92, 105)97 (90, 104)106 (94, 118)113 (102, 124)NSNSNS
Non-Hispanic white females117 (110, 124)115 (108, 122)109 (103, 114)111 (104, 119)110 (102, 118)NSNSNS
Non-Hispanic black males113 (104, 122)118 (107, 130)112 (103, 120)144 (107, 181)117 (106, 129)NSNSNS
Non-Hispanic black females177 (156, 197)178 (161, 196)151 (137, 164)135 (121, 150)135 (123, 147)0.000001NSNS
Hispanic males104 (91, 118)112 (101, 124)106 (97, 114)123 (106, 141)128 (116, 140)0.004NSNS
Hispanic females152 (140, 165)150 (135, 164)140 (129, 150)136 (124, 147)130 (119, 141)0.003NSNS
Insulin sensitivity by the homeostasis model assessment (%S)5
Non-Hispanic white males0.503 (0.472, 0.535)0.549 (0.513, 0.585)0.518 (0.484, 0.553)0.494 (0.463, 0.525)0.421 (0.388, 0.455)0.00005NS0.05
Non-Hispanic white females0.643 (0.610, 0.677)0.603 (0.570, 0.637)0.574 (0.539, 0.609)0.555 (0.519, 0.591)0.455 (0.420, 0.491)< 0.0000010.040.02
Non-Hispanic black males0.562 (0.516, 0.608)0.553 (0.504, 0.601)0.559 (0.512, 0.605)0.555 (0.498, 0.611)0.48 (0.426, 0.535)0.04NS0.05
Non-Hispanic black females0.510 (0.476, 0.545)0.479 (0.437, 0.522)0.453 (0.421, 0.485)0.458 (0.422, 0.495)0.379 (0.343, 0.414)0.0000010.020.007
Hispanic males0.538 (0.495, 0.580)0.533 (0.489, 0.578)0.527 (0.472, 0.583)0.524 (0.460, 0.588)0.338 (0.307, 0.370)< 0.0000010.010.007
Hispanic females0.523 (0.482, 0.563)0.535 (0.484, 0.587)0.464 (0.426, 0.502)0.444 (0.403, 0.485)0.321 (0.289, 0.352)< 0.0000010.0050.003
Insulin sensitivity by the simple QUICKI6
Non-Hispanic white males0.339 (0.336, 0.342)0.343 (0.340, 0.346)0.340 (0.336, 0.343)0.337 (0.334, 0.341)0.327 (0.323, 0.331)< 0.0000010.0080.002
Non-Hispanic white females0.352 (0.349, 0.355)0.348 (0.345, 0.351)0.345 (0.342, 0.348)0.343 (0.340, 0.346)0.33 (0.327, 0.334)< 0.0000010.000050.00001
Non-Hispanic black males0.344 (0.339, 0.348)0.342 (0.338, 0.347)0.343 (0.339, 0.348)0.341 (0.335, 0.346)0.333 (0.328, 0.338)0.0030.030.01
Non-Hispanic black females0.340 (0.336, 0.343)0.335 (0.331, 0.339)0.333 (0.329, 0.337)0.333 (0.329, 0.337)0.322 (0.317, 0.326)< 0.0000010.00060.0001
Hispanic males0.341 (0.336, 0.345)0.34 (0.336, 0.345)0.339 (0.335, 0.344)0.337 (0.332, 0.342)0.318 (0.314, 0.322)< 0.0000010.00010.00001
Hispanic females0.340 (0.336, 0.344)0.340 (0.336, 0.345)0.334 (0.330, 0.338)0.330 (0.326, 0.335)0.315 (0.310, 0.319)< 0.0000010.000030.00002
Role of inflammation in association between serum ferritin concentration and insulin sensitivity

In addition to reflection of the body iron store, serum ferritin is also an acute reactant. To explore the role of inflammation on the observed correlation, we examined the relationship of these indices with a marker of inflammation, CRP. No consistent association of CRP with either %S or QUICKI was observed (Table 4). A positive association between CRP and serum ferritin concentration was observed in NHW (both males and females), non-Hispanic black females, and Hispanic females, but not in non-Hispanic black. The associations remained unchanged after adjustment for age, BMI, alcohol intake, and mineral/iron supplement. Therefore, inflammation could not provide a uniform explanation for the underlying mechanism of the observed correlation between serum ferritin concentration and insulin sensitivity.

Table 4 Serum ferritin concentration and estimated insulin sensitivity indices by quintile of inflammatory marker - C-reactive protein.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5P1P2P3
Serum ferritin concentration (mcg/L)
Non-Hispanic white males142 (130, 155)157 (144, 170)179 (164, 195)201 (180, 222)201 (181, 221)< 0.0000010.0000020.000005
Non-Hispanic white females19 (18, 20)49 (48, 50)120 (116, 125)152 (134, 171)108 (95, 120)0.0000030.000030.00003
Non-Hispanic black males186 (163, 209)187 (167, 207)267 (236, 298)227 (202, 253)254 (281, 228)NSNSNS
Non-Hispanic black females90 (74, 106)79 (66, 91)77 (65, 89)102 (87, 118)115 (98, 132)0.0020.00090.001
Hispanic males150 (134, 166)157 (135, 179)161 (137, 185)157 (136, 178)172 (154, 191)NSNSNS
Hispanic females52 (44, 60)56 (48, 64)63 (53, 72)72 (60, 84)92 (68, 115)0.000010.0070.006
Insulin sensitivity by the homeostasis model assessment (%S)4
Non-Hispanic white males0.541 (0.505, 0.578)0.531 (0.500, 0.562)0.546 (0.509, 0.582)0.459 (0.425, 0.494)0.412 (0.383, 0.440)< 0.0000010.050.03
Non-Hispanic white females0.684 (0.651, 0.718)0.627 (0.592, 0.661)0.596 (0.558, 0.634)0.494 (0.461, 0.526)0.422 (0.392, 0.452)< 0.0000010.0040.004
Non-Hispanic black males0.562 (0.517, 0.607)0.572 (0.526, 0.618)0.561 (0.499, 0.623)0.549 (0.488, 0.611)0.478 (0.426, 0.530)0.05NSNS
Non-Hispanic black females0.524 (0.489, 0.558)0.524 (0.487, 0.560)0.497 (0.464, 0.530)0.404 (0.369, 0.438)0.327 (0.288, 0.365)< 0.0000010.0040.002
Hispanic males0.558 (0.507, 0.608)0.484 (0.438, 0.530)0.525 (0.472, 0.578)0.513 (0.460, 0.566)0.372 (0.334, 0.411)0.00001NSNS
Hispanic females0.538 (0.495, 0.582)0.53 (0.481, 0.579)0.471 (0.430, 0.513)0.392 (0.355, 0.429)0.353 (0.319, 0.387)< 0.000001NSNS
Insulin sensitivity by the simple QUICKI5
Non-Hispanic white males0.342 (0.339, 0.346)0.342 (0.339, 0.345)0.342 (0.339, 0.346)0.332 (0.328, 0.336)0.328 (0.325, 0.331)< 0.0000010.010.008
Non-Hispanic white females0.356 (0.354, 0.359)0.351 (0.348, 0.354)0.347 (0.343, 0.350)0.336 (0.333, 0.340)0.328 (0.324, 0.331)< 0.0000010.0040.005
Non-Hispanic black males0.345 (0.341, 0.349)0.345 (0.340, 0.349)0.341 (0.336, 0.346)0.34 (0.334, 0.345)0.332 (0.327, 0.338)0.01NSNS
Non-Hispanic black females0.341 (0.337, 0.345)0.341 (0.337, 0.345)0.339 (0.335, 0.342)0.327 (0.323, 0.331)0.314 (0.310, 0.319)< 0.0000010.0000020.000001
Hispanic males0.342 (0.338, 0.347)0.335 (0.331, 0.340)0.338 (0.333, 0.343)0.338 (0.333, 0.342)0.321 (0.317, 0.326)< 0.000001NSNS
Hispanic females0.342 (0.338, 0.346)0.34 (0.336, 0.344)0.334 (0.329, 0.338)0.325 (0.321, 0.329)0.319 (0.314, 0.323)< 0.0000010.020.03
Role of the liver in association between serum ferritin concentration and insulin sensitivity

Elevated liver enzymes could result from iron deposition in the liver. To examine the role of the liver in the association of serum ferritin concentration with insulin sensitivity, we investigated the association of liver enzymes with serum ferritin concentration and insulin sensitivity. We focused on AST or SGOT, gamma glutamyl transpeptidase (GGT), and ALT or SGPT.

The association of AST with %S and QUICKI was only noted in Hispanic males, but not in other 5 groups (Table 5). Adjustment for age, BMI, alcohol consumption, and mineral/iron supplement had no impact on the results. In contrast, a very close association was noted between AST and ferritin concentration in all 6 groups. Since AST is present in many tissues, including heart, skeletal muscle, kidney, and brain, we could not exclude the role of the liver based on no association between AST and insulin sensitivity in some groups.

Table 5 Serum ferritin concentration and estimated insulin sensitivity indices by quintile of aspartate aminotransferase.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5P1P2P3
Serum ferritin concentration(mcg/L)
Non-Hispanic white males148 (134, 162)154 (140, 167)180 (165, 196)170 (155, 186)228 (205, 251)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females58 (51, 65)61 (55, 68)85 (76, 94)102 (91, 112)140 (122, 158)0.00040.020.02
Non-Hispanic black males175 (155, 196)203 (178, 228)197 (173, 222)227 (203, 251)267 (236, 298)0.050.0030.004
Non-Hispanic black females84 (71, 96)77 (66, 88)80 (67, 92)95 (81, 109)127 (106, 149)0.000010.0040.005
Hispanic males139 (124, 153)134 (118, 151)149 (134, 163)155 (132, 177)223 (194, 251)< 0.000001< 0.000001< 0.000001
Hispanic females47 (39, 56)49 (42, 55)59 (50, 68)79 (57, 101)101 (86, 115)< 0.0000010.000010.00002
Insulin sensitivity by the homeostasis model assessment (%S)4
Non-Hispanic white males0.491 (0.457, 0.526)0.517 (0.484, 0.550)0.497 (0.466, 0.528)0.506 (0.471, 0.541)0.478 (0.441, 0.514)NSNSNS
Non-Hispanic white females0.575 (0.544, 0.607)0.597 (0.559, 0.630)0.591 (0.554, 0.628)0.555 (0.521, 0.588)0.506 (0.470, 0.543)0.02NSNS
Non-Hispanic black males0.512 (0.465, 0.559)0.531 (0.479, 0.584)0.528 (0.486, 0.569)0.557 (0.508, 0.605)0.561 (0.499, 0.623)NSNSNS
Non-Hispanic black females0.447 (0.410, 0.484)0.452 (0.418, 0.487)0.472 (0.437, 0.506)0.461 (0.424, 0.499)0.443 (0.401, 0.485)NSNSNS
Hispanic males0.501 (0.460, 0.542)0.55 (0.495, 0.604)0.524 (0.473, 0.574)0.477 (0.424, 0.530)0.404 (0.359, 0.449)< 0.000001< 0.000001< 0.000001
Hispanic females0.472 (0.430, 0.514)0.48 (0.443, 0.516)0.468 (0.430, 0.507)0.49 (0.442, 0.539)0.374 (0.330, 0.418)0.006NSNS
Insulin sensitivity by the simple QUICKI5
Non-Hispanic white males0.337 (0.333, 0.340)0.34 (0.337, 0.343)0.338 (0.335, 0.341)0.338 (0.334, 0.342)0.334 (0.330, 0.338)NSNSNS
Non-Hispanic white females0.346 (0.343, 0.349)0.347 (0.344, 0.350)0.347 (0.343, 0.350)0.343 (0.340, 0.346)0.336 (0.332, 0.340)0.009NSNS
Non-Hispanic black males0.337 (0.332, 0.342)0.339 (0.334, 0.344)0.341 (0.337, 0.345)0.343 (0.338, 0.348)0.3417 (0.336, 0.346)NSNSNS
Non-Hispanic black females0.331 (0.327, 0.335)0.332 (0.328, 0.336)0.335 (0.332, 0.339)0.333 (0.329, 0.337)0.33 (0.326, 0.334)NSNSNS
Hispanic males0.337 (0.333, 0.342)0.342 (0.337, 0.346)0.338 (0.333, 0.343)0.333 (0.328, 0.338)0.325 (0.320, 0.329)< 0.000001< 0.000001< 0.000001
Hispanic females0.334 (0.329, 0.338)0.336 (0.332, 0.340)0.334 (0.330, 0.338)0.335 (0.331, 0.340)0.32 (0.315, 0.325)0.0001NSNS

GGT is a very sensitive indicator of hepatobiliary diseases and is found predominately throughout the hepatobiliary system, but also in other tissues. It was negatively associated with %S and QUICKI in all 6 groups (Table 6). The association remained after adjustment for age, BMI, alcohol consumption, and mineral/iron supplement. It was positively associated with serum ferritin concentration after adjustment for age and BMI. Therefore, the relationship of GGT with insulin sensitivity and serum ferritin concentration could provide a mechanistic insight of the liver in the association between insulin sensitivity and serum ferritin concentration.

Table 6 Serum ferritin concentration and estimated insulin sensitivity indices by quintile of gamma glutamyl transferase.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5P1P2P3
Serum ferritin concentration (mcg/L)
Non-Hispanic white males141 (125, 157)146 (131,161)174 (156, 191)179 (162, 196)227 (204, 250)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females55 (48, 62)70 (61, 78)95 (81, 110)92 (77, 107)137 (121, 154)< 0.000001< 0.000001< 0.000001
Non-Hispanic black males165 (144, 187)191 (163, 219)221 (195, 247)220 (194, 246)298 (263, 333)< 0.000001< 0.000001< 0.000001
Non-Hispanic black females60 (45, 74)79 (68, 91)84 (67, 100)97 (83, 112)141 (119, 163)< 0.000001< 0.000001< 0.000001
Hispanic males105 (93, 117)137 (121, 153)152 (132, 172)173 (144, 202)240 (208, 272)< 0.000001< 0.000001< 0.000001
Hispanic females38 (30, 47)38 (32, 44)59 (47, 70)82 (70, 93)109 (90, 129)< 0.000001< 0.000001< 0.000001
Insulin sensitivity by the homeostasis model assessment (%S)4
Non-Hispanic white males0.622 (0.584, 0.659)0.521 (0.486, 0.556)0.5061 (0.465, 0.546)0.422 (0.387, 0.458)0.402 (0.367, 0.436)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females0.732 (0.695, 0.769)0.648 (0.609, 0.686)0.587 (0.547, 0.626)0.48 (0.444, 0.516)0.397 (0.361, 0.433)< 0.000001< 0.000001< 0.000001
Non-Hispanic black males0.607 (0.560, 0.654)0.588 (0.522, 0.653)0.537 (0.491, 0.583)0.489 (0.429, 0.548)0.462 (0.404, 0.520)0.0001NS0.05
Non-Hispanic black females0.554 (0.515, 0.594)0.454 (0.419, 0.489)0.45 (0.409, 0.491)0.407 (0.372, 0.442)0.383 (0.332, 0.434)< 0.0000010.00020.00002
Hispanic males0.67 (0.625, 0.715)0.562 (0.486, 0.638)0.423 (0.383, 0.463)0.439 (0.376, 0.501)0.359 (0.299, 0.419)< 0.0000010.000050.000005
Hispanic females0.623 (0.569, 0.677)0.494 (0.448, 0.539)0.424 (0.381, 0.466)0.338 (0.301, 0.375)0.343 (0.298, 0.389)< 0.0000010.0000020.000003
Insulin sensitivity by the simple QUICKI5
Non-Hispanic white males0.351 (0.348, 0.354)0.341 (0.338, 0.344)0.339 (0.335, 0.342)0.328 (0.324, 0.332)0.325 (0.321, 0.330)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females0.361 (0.358, 0.364)0.353 (0.350, 0.356)0.347 (0.344, 0.350)0.335 (0.332, 0.339)0.323 (0.319, 0.327)< 0.000001< 0.000001< 0.000001
Non-Hispanic black males0.349 (0.345, 0.353)0.344 (0.338, 0.350)0.342 (0.337, 0.346)0.334 (0.328, 0.339)0.331 (0.325, 0.337)< 0.0000010.010.004
Non-Hispanic black females0.345 (0.341, 0.348)0.334 (0.330, 0.338)0.332 (0.328, 0.337)0.327 (0.323, 0.332)0.321 (0.315, 0.326)< 0.000001< 0.000001< 0.000001
Hispanic males0.356 (0.352, 0.360)0.341 (0.335, 0.347)0.330 (0.325, 0.334)0.329 (0.323, 0.334)0.318 (0.312, 0.324)< 0.000001< 0.000001< 0.000001
Hispanic females0.351 (0.346, 0.355)0.338 (0.334, 0.342)0.329 (0.325, 0.334)0.318 (0.313, 0.323)0.316 (0.311, 0.322)< 0.000001< 0.000001< 0.000001

The primary source of ALT is the liver. It was negatively associated with both %S and QUICKI in all six groups, and remained highly significant regardless of the adjustment for age, BMI, alcohol consumption, and mineral/iron supplement (Table 7). This relationship indicated an association of insulin resistance and liver diseases. Serum ferritin concentration was positively associated with ALT and also this association remained significant regardless of adjustment for age, BMI, alcohol consumption, and mineral/iron supplement. Since ALT is an indicator of liver diseases, a positive association between ALT and serum ferritin concentration suggests that increased iron deposition in the liver is associated with liver dysfunction. Furthermore, a positive association between ALT and serum ferritin concentration and a negative association between ALT and insulin sensitivity suggests a negative association of serum ferritin concentration with insulin sensitivity as we had observed.

Table 7 Serum ferritin concentration and estimated insulin sensitivity indices by quintile of alanine aminotransferase.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5P1P2P3
Serum ferritin concentration (mcg/L)
Non-Hispanic white males147 (132, 162)169 (153, 185)168 (152, 183)177 (159, 194)220 (200, 241)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females71 (63, 79)71 (61, 82)86 (77, 95)95 (84, 107)123 (107, 139)0.050.020.02
Non-Hispanic black males168 (147, 189)187 (165, 210)201 (177, 225)247 (219, 275)267 (238, 296)0.010.000050.00005
Non-Hispanic black females80 (67, 92)79 (68, 89)87 (73, 100)98 (81, 114)120 (100, 140)0.000030.0000040.000005
Hispanic males128 (113, 143)128 (116, 140)142 (126, 157)172 (144, 200)229 (206, 253)< 0.000001< 0.000001< 0.000001
Hispanic females42 (35, 49)70 (48, 93)57 (49, 65)64 (55, 73)101 (87, 116)< 0.0000010.0000090.000009
Insulin sensitivity by the homeostasis model assessment (%S)4
Non-Hispanic white males0.551 (0.517, 0.584)0.544 (0.511, 0.578)0.512 (0.476, 0.549)0.483 (0.448, 0.518)0.399 (0.370, 0.429)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females0.634 (0.602, 0.666)0.628 (0.591, 0.664)0.583 (0.546, 0.622)0.55 (0.519, 0.582)0.429 (0.395, 0.463)0.000020.0040.002
Non-Hispanic black males0.63 (0.576, 0.684)0.576 (0.522, 0.630)0.564 (0.514, 0.615)0.478 (0.423, 0.524)0.44 (0.397, 0.482)0.000020.0030.003
Non-Hispanic black females0.527 (0.490, 0.563)0.498 (0.462, 0.534)0.462 (0.424, 0.500)0.427 (0.389, 0.465)0.363 (0.330, 0.396)< 0.000001< 0.000001< 0.000001
Hispanic males0.635 (0.569, 0.700)0.57 (0.525, 0.615)0.48 (0.430, 0.530)0.448 (0.410, 0.486)0.324 (0.295, 0.352)< 0.000001< 0.000001< 0.000001
Hispanic females0.55 (0.509, 0.591)0.528 (0.484, 0.571)0.468 (0.427, 0.509)0.409 (0.365, 0.452)0.331 (0.295, 0.368)< 0.0000010.0000030.000002
Insulin sensitivity by the simple QUICKI5
Non-Hispanic white males0.344 (0.341, 0.347)0.343 (0.339, 0.346)0.339 (0.335, 0.342)0.335 (0.332, 0.339)0.326 (0.322, 0.329)< 0.000001< 0.000001< 0.000001
Non-Hispanic white females0.352 (0.349, 0.355)0.35 (0.347, 0.345)0.346 (0.342, 0.349)0.343 (0.340, 0.346)0.327 (0.324, 0.331)0.0000010.00050.0002
Non-Hispanic black males0.349 (0.344, 0.354)0.344 (0.339, 0.349)0.343 (0.338, 0.348)0.335 (0.330, 0.339)0.33 (0.326, 0.335)0.000050.010.009
Non-Hispanic black females0.341 (0.337, 0.345)0.338 (0.334, 0.342)0.333 (0.329, 0.337)0.33 (0.326, 0.334)0.321 (0.316, 0.325)< 0.000001< 0.000001< 0.000001
Hispanic males0.348 (0.343, 0.353)0.345 (0.341, 0.349)0.333 (0.328, 0.338)0.332 (0.328, 0.336)0.317 (0.313, 0.321)< 0.000001< 0.000001< 0.000001
Hispanic females0.343 (0.339, 0.347)0.34 (0.336, 0.344)0.334 (0.330, 0.338)0.327 (0.323, 0.331)0.315 (0.311, 0.320)< 0.000001< 0.000001< 0.000001
DISCUSSION

To examine the role of iron metabolism in diabetes, the indices of iron metabolism were compared in patients with and without diabetes. We found that subjects with diabetes had a higher serum ferritin concentration than those without diabetes. To explore the underlying pathophysiology, we observed that serum ferritin concentration was negatively associated with insulin sensitivity (%S and QUICKI), but not with beta cell function. Therefore, a high serum ferritin concentration is associated with insulin resistance and is a risk factor for DM.

Since ferritin contains the second largest pool of iron in the body next to hemoglobin[16], serum ferritin concentration closely correlates with total body iron stores, mainly in the liver[26]. In this study, serum ferritin concentration is negatively associated with insulin sensitivity, suggesting an association of insulin resistance with total body iron stores. However, it is well known that ferritin is also an acute phase reactant[26]. To further explore this issue, we examined the correlation of CRP, an inflammatory marker[27], with insulin sensitivity and serum ferritin concentration. Without a consistent result across 3 ethic/racial groups and both genders, we concluded that in this study, no consistent relationship of CRP with either insulin sensitivity or serum ferritin concentration was observed in all 6 groups. Furthermore, in this population only 1.28% (range: 0.64% in Hispanic males to 1.95% in non-Hispanic black males) of the participants had an elevated CRP ≥ 3 mg/L, which is the 90th percentile for healthy young adults[28]. After exclusion of those with a CRP ≥ 3 mg/L, association of CRP with insulin sensitivity was only observed in NHW females (P = 0.006 for %S and P = 0.00002 for QUICKI) and NHB females (P = 0.03 for %S and P = 0.0001 for QUICKI) and correlation of CRP with ferritin concentration was only observed in NHW females (P = 0.005), NHB females (P = 0.001), and MA females (P = 0.01), after adjustment for age and BMI. Therefore, it is very unlikely that inflammation is the underlying mechanism for the observed negative association between serum ferritin concentration and insulin sensitivity.

Next we examined the role of the liver on the observed association between insulin sensitivity and serum ferritin concentration. Among these three liver enzymes, AST is the least specific liver maker and ALT is the most liver specific marker. All three liver enzymes were correlated with serum ferritin concentration very well, suggesting a closed association between elevated serum ferritin and liver dysfunction. However, we observed the different strengths of the correlation of insulin sensitivity across three liver enzymes. Among them, AST is the least specific for the liver diseases, the association between AST and insulin sensitivity only observed in Hispanic male group. In contrast, a negative association of ALT and GGT with insulin sensitivity was observed in all 6 groups. The negative correlation of liver enzymes with insulin sensitivity indicates the role of hepatic dysfunction in insulin resistance. Therefore, these observations imply the role of iron-associated elevated ALT and GGT in the pathogenesis of insulin resistance. The role of the liver in the pathogenesis of DM is well-established[29,30]. Furthermore, the relationship of elevated ALT concentration with diabetes and insulin resistance has been reported[31]. In Pima Indians, elevated ALT was associated with hepatic insulin resistance but not with whole body insulin resistance or beta cell function[32]. Insulin sensitivity obtained from the HOMA as used in this study, has been demonstrated to be correlated with hepatic insulin sensitivity[33]. Thus from the observations in this study, iron could play a role in hepatic insulin resistance.

The role of serum ferritin concentration in diabetes[4] has been examined in this population. Elevated ferritin concentration has been reported to be associated with an increased risk of diabetes, but the role of inflammation could not be excluded[4]. Elevated serum ferritin concentration also has been reported to be associated with insulin resistance[34]. In the present study, we confirmed the association of serum ferritin concentration with DM and insulin sensitivity assessed by both %S and QUICKI. Although the association of inflammation and insulin resistance has been demonstrated in this population[35], we demonstrated that the inflammatory hypothesis is not likely the underlying mechanism of the reported associations in this study. In addition, from the observed associations of ALT and GGT with serum ferritin concentration and insulin sensitivity, we provided the evidence suggesting that the role of liver in the pathogenesis of iron-associated insulin resistance.

Iron-induced oxidant stress has proposed to play a key role in iron-mediated tissue damage[36-38]. Although the molecular events of iron-mediated tissue damage have not been fully elucidated, mitochondria are the targets of iron-mediated damage and iron may be preferentially toxic to cells with high mitochondrial activity[39], such as hepatocytes and pancreatic beta cells. Impaired mitochondrial activity has been observed in the insulin-resistant offspring of patients with type 2 diabetes[40] and mitochondrial defect can also lead to the metabolic syndrome[41]. Therefore, iron-induced oxidative stress with mitochondrial dysfunction could be one of the underlying mechanisms in these metabolic disorders.

Because of the cross-sectional nature of the study, a temporal relationship and the biological basis of the association between serum ferritin concentration and these metabolic disorders could not be established. However, our observations have some bearing on the plausible mechanisms. Furthermore, the caustic role of iron in these processes is suggested by interventional studies. In patients with clinical evidence of non-alcoholic fatty liver disease, quantitative phlebotomy induced iron depletion to a level of near-iron deficiency results in a 40%-55% improvement of both fasting and glucose-stimulated plasma insulin concentrations and near-normalization of ALT[42]. Quantitative phlebotomy also leads to improvement in insulin sensitivity in a group of subjects with high-ferritin type 2 diabetes[43]. Therefore, iron could be the culprit of these conditions.

The current sample set did provide enough information to distinguish type 1 and type 2 diabetes. However, as 95% of diabetes is type 2 diabetes and insulin resistance is a cardinal feature of type 2 diabetes, the current study is most applicable to type 2 diabetes. Our observations are consistent with the published results[44-46] with some new clinical implications. In this study, even without clinical evidence of iron overload, iron could be associated with liver damage and insulin resistance. A clinical trial of quantitative phlebotomy in the subjects with elevated ferritin concentration is warranted to test this hypothesis. Once it is demonstrated, quantitative phlebotomy could be recommended for those patients with DM or insulin resistance, who also have elevated serum ferritin concentration. Although the underlying molecular mechanism of the association remains to be elucidated, our observations imply that the liver could play a role in iron-associated insulin resistance.

ACKNOWLEDGMENTS

The authors are in debt to Karen Ramos for excellent logistic and administrative support of this research endeavor.

COMMENTS
Background

Liver has been noted to play a role in the pathogenesis of type 2 diabetes. Hemochromatosis and excess iron load has been implicated to play a role in the pathogenesis of type 2 diabetes. Iron metabolism could a role in the pathogenesis of type 2 diabetes.

Research frontiers

Diabetes mellitus is a common manifestation of hemochromatosis. Although the common mutation of HFE is not associated with type 2 diabetes, the iron metabolism could play a role in the pathogenesis of diabetes. In hemochromatosis, both insulin resistance and impaired insulin secretion have been suggested to play a role in its pathogenesis. However, the underlying mechanism of iron-associated abnormal glucose homeostasis in the general population is not well understood.

Innovations and breakthroughs

In this study, the authors found that subjects with diabetes had a higher serum ferritin concentration than those without diabetes. The authors also observed that serum ferritin concentration was negatively associated with insulin sensitivity (%S and QUICKI), but not with beta cell function. Therefore, a high serum ferritin concentration is associated with insulin resistance and is a risk factor for diabetes mellitus. The authors further demonstrated that the inflammatory hypothesis is not likely the underlying mechanism of the reported associations in this study. In addition, from the observed associations of alanine aminotransferase (ALT) and gamma glutamyl transpeptidase with serum ferritin concentration and insulin sensitivity, the authors provided the evidence suggesting that the role of liver in the pathogenesis of iron-associated insulin resistance. Iron-induced oxidant stress has proposed to play a key role in iron-mediated tissue damage and iron-induced oxidative stress with mitochondrial dysfunction could be one of the underlying mechanisms in these metabolic disorders.

Applications

As in patients with clinical evidence of non-alcoholic fatty liver disease, quantitative phlebotomy induced iron depletion to a level of near-iron deficiency results in a 40%-55% improvement of both fasting and glucose-stimulated plasma insulin concentrations and near-normalization of ALT and quantitative phlebotomy also leads to improvement in insulin sensitivity in a group of subjects with high-ferritin type 2 diabetes, a clinical trial of quantitative phlebotomy in the subjects with elevated ferritin concentration is warranted to test this hypothesis. Once it is demonstrated, quantitative phlebotomy could be recommended for those patients with diabetes mellitus or insulin resistance, who also have elevated serum ferritin concentration.

Terminology

Ferritin: Ferritin is a protein in the body that binds to iron; most of the iron stored in the body is bound to ferritin. In humans, it acts as a buffer against iron deficiency and iron overload. Serum ferritin concentration closely correlates with total body iron stores, mainly in the liver.

Peer-review

This is an interesting study. The authors have evaluated the relationship of iron with diabetes mellitus (DM) and concluded that disordered iron metabolism could play a role in the pathogenesis of insulin resistance and DM through its effect on liver function.

Footnotes

P- Reviewer: Sugawara I, Santos MM, Xie JX S- Editor: Song XX L- Editor: A E- Editor: Wu HL

References
1.  Witte DL, Crosby WH, Edwards CQ, Fairbanks VF, Mitros FA. Practice guideline development task force of the College of American Pathologists. Hereditary hemochromatosis. Clin Chim Acta. 1996;245:139-200.  [PubMed]  [DOI]
2.  Feder JN, Penny DM, Irrinki A, Lee VK, Lebrón JA, Watson N, Tsuchihashi Z, Sigal E, Bjorkman PJ, Schatzman RC. The hemochromatosis gene product complexes with the transferrin receptor and lowers its affinity for ligand binding. Proc Natl Acad Sci USA. 1998;95:1472-1477.  [PubMed]  [DOI]
3.  Halsall DJ, McFarlane I, Luan J, Cox TM, Wareham NJ. Typical type 2 diabetes mellitus and HFE gene mutations: a population-based case - control study. Hum Mol Genet. 2003;12:1361-1365.  [PubMed]  [DOI]
4.  Ford ES, Cogswell ME. Diabetes and serum ferritin concentration among U.S. adults. Diabetes Care. 1999;22:1978-1983.  [PubMed]  [DOI]
5.  Haap M, Fritsche A, Mensing HJ, Häring HU, Stumvoll M. Association of high serum ferritin concentration with glucose intolerance and insulin resistance in healthy people. Ann Intern Med. 2003;139:869-871.  [PubMed]  [DOI]
6.  Jiang R, Manson JE, Meigs JB, Ma J, Rifai N, Hu FB. Body iron stores in relation to risk of type 2 diabetes in apparently healthy women. JAMA. 2004;291:711-717.  [PubMed]  [DOI]
7.  Tuomainen TP, Nyyssönen K, Salonen R, Tervahauta A, Korpela H, Lakka T, Kaplan GA, Salonen JT. Body iron stores are associated with serum insulin and blood glucose concentrations. Population study in 1,013 eastern Finnish men. Diabetes Care. 1997;20:426-428.  [PubMed]  [DOI]
8.  Qi L, Meigs J, Manson JE, Ma J, Hunter D, Rifai N, Hu FB. HFE genetic variability, body iron stores, and the risk of type 2 diabetes in U.S. women. Diabetes. 2005;54:3567-3572.  [PubMed]  [DOI]
9.  Yaouanq JM. Diabetes and haemochromatosis: current concepts, management and prevention. Diabete Metab. 1995;21:319-329.  [PubMed]  [DOI]
10.  Cario H, Holl RW, Debatin KM, Kohne E. Insulin sensitivity and beta-cell secretion in thalassaemia major with secondary haemochromatosis: assessment by oral glucose tolerance test. Eur J Pediatr. 2003;162:139-146.  [PubMed]  [DOI]
11.  Furutani M, Nakashima T, Sumida Y, Hirohama A, Yoh T, Kakisaka Y, Mitsuyoshi H, Senmaru H, Okanoue T. Insulin resistance/beta-cell function and serum ferritin level in non-diabetic patients with hepatitis C virus infection. Liver Int. 2003;23:294-299.  [PubMed]  [DOI]
12.  Hsiao TJ, Chen JC, Wang JD. Insulin resistance and ferritin as major determinants of nonalcoholic fatty liver disease in apparently healthy obese patients. Int J Obes Relat Metab Disord. 2004;28:167-172.  [PubMed]  [DOI]
13.  Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. Series 1: programs and collection procedures. Vital Health Stat 1. 1994;1-407.  [PubMed]  [DOI]
14.  American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2004;27 Suppl 1:S5-S10.  [PubMed]  [DOI]
15.  Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412-419.  [PubMed]  [DOI]
16.  Pietrangelo A. Hereditary hemochromatosis--a new look at an old disease. N Engl J Med. 2004;350:2383-2397.  [PubMed]  [DOI]
17.  McLaren CE, McLachlan GJ, Halliday JW, Webb SI, Leggett BA, Jazwinska EC, Crawford DH, Gordeuk VR, McLaren GD, Powell LW. Distribution of transferrin saturation in an Australian population: relevance to the early diagnosis of hemochromatosis. Gastroenterology. 1998;114:543-549.  [PubMed]  [DOI]
18.  Barr RG, Nathan DM, Meigs JB, Singer DE. Tests of glycemia for the diagnosis of type 2 diabetes mellitus. Ann Intern Med. 2002;137:263-272.  [PubMed]  [DOI]
19.  Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998;21:2191-2192.  [PubMed]  [DOI]
20.  Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000;23:57-63.  [PubMed]  [DOI]
21.  Hermans MP, Levy JC, Morris RJ, Turner RC. Comparison of insulin sensitivity tests across a range of glucose tolerance from normal to diabetes. Diabetologia. 1999;42:678-687.  [PubMed]  [DOI]
22.  Hermans MP, Levy JC, Morris RJ, Turner RC. Comparison of tests of beta-cell function across a range of glucose tolerance from normal to diabetes. Diabetes. 1999;48:1779-1786.  [PubMed]  [DOI]
23.  Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab. 2000;85:2402-2410.  [PubMed]  [DOI]
24.  Clark JM, Brancati FL, Diehl AM. The prevalence and etiology of elevated aminotransferase levels in the United States. Am J Gastroenterol. 2003;98:960-967.  [PubMed]  [DOI]
25.  Cook JD. Clinical evaluation of iron deficiency. Semin Hematol. 1982;19:6-18.  [PubMed]  [DOI]
26.  Hulthén L, Lindstedt G, Lundberg PA, Hallberg L. Effect of a mild infection on serum ferritin concentration--clinical and epidemiological implications. Eur J Clin Nutr. 1998;52:376-379.  [PubMed]  [DOI]
27.  Pepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest. 2003;111:1805-1812.  [PubMed]  [DOI]
28.  Shine B, de Beer FC, Pepys MB. Solid phase radioimmunoassays for human C-reactive protein. Clin Chim Acta. 1981;117:13-23.  [PubMed]  [DOI]
29.  Cherrington AD. Banting Lecture 1997. Control of glucose uptake and release by the liver in vivo. Diabetes. 1999;48:1198-1214.  [PubMed]  [DOI]
30.  DeFronzo RA. Lilly lecture 1987. The triumvirate: beta-cell, muscle, liver. A collusion responsible for NIDDM. Diabetes. 1988;37:667-687.  [PubMed]  [DOI]
31.  Hanley AJ, Williams K, Festa A, Wagenknecht LE, D’Agostino RB, Kempf J, Zinman B, Haffner SM. Elevations in markers of liver injury and risk of type 2 diabetes: the insulin resistance atherosclerosis study. Diabetes. 2004;53:2623-2632.  [PubMed]  [DOI]
32.  Vozarova B, Stefan N, Lindsay RS, Saremi A, Pratley RE, Bogardus C, Tataranni PA. High alanine aminotransferase is associated with decreased hepatic insulin sensitivity and predicts the development of type 2 diabetes. Diabetes. 2002;51:1889-1895.  [PubMed]  [DOI]
33.  Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22:1462-1470.  [PubMed]  [DOI]
34.  Jehn M, Clark JM, Guallar E. Serum ferritin and risk of the metabolic syndrome in U.S. adults. Diabetes Care. 2004;27:2422-2428.  [PubMed]  [DOI]
35.  Chen J, Wildman RP, Hamm LL, Muntner P, Reynolds K, Whelton PK, He J. Association between inflammation and insulin resistance in U.S. nondiabetic adults: results from the Third National Health and Nutrition Examination Survey. Diabetes Care. 2004;27:2960-2965.  [PubMed]  [DOI]
36.  Reddy MB, Clark L. Iron, oxidative stress, and disease risk. Nutr Rev. 2004;62:120-124.  [PubMed]  [DOI]
37.  Pietrangelo A. Iron-induced oxidant stress in alcoholic liver fibrogenesis. Alcohol. 2003;30:121-129.  [PubMed]  [DOI]
38.  Tuomainen TP, Diczfalusy U, Kaikkonen J, Nyyssönen K, Salonen JT. Serum ferritin concentration is associated with plasma levels of cholesterol oxidation products in man. Free Radic Biol Med. 2003;35:922-928.  [PubMed]  [DOI]
39.  Eaton JW, Qian M. Molecular bases of cellular iron toxicity. Free Radic Biol Med. 2002;32:833-840.  [PubMed]  [DOI]
40.  Petersen KF, Dufour S, Befroy D, Garcia R, Shulman GI. Impaired mitochondrial activity in the insulin-resistant offspring of patients with type 2 diabetes. N Engl J Med. 2004;350:664-671.  [PubMed]  [DOI]
41.  Wilson FH, Hariri A, Farhi A, Zhao H, Petersen KF, Toka HR, Nelson-Williams C, Raja KM, Kashgarian M, Shulman GI. A cluster of metabolic defects caused by mutation in a mitochondrial tRNA. Science. 2004;306:1190-1194.  [PubMed]  [DOI]
42.  Facchini FS, Hua NW, Stoohs RA. Effect of iron depletion in carbohydrate-intolerant patients with clinical evidence of nonalcoholic fatty liver disease. Gastroenterology. 2002;122:931-939.  [PubMed]  [DOI]
43.  Fernández-Real JM, Peñarroja G, Castro A, García-Bragado F, Hernández-Aguado I, Ricart W. Blood letting in high-ferritin type 2 diabetes: effects on insulin sensitivity and beta-cell function. Diabetes. 2002;51:1000-1004.  [PubMed]  [DOI]
44.  Shi Z, Hu X, Yuan B, Pan X, Meyer HE, Holmboe-Ottesen G. Association between serum ferritin, hemoglobin, iron intake, and diabetes in adults in Jiangsu, China. Diabetes Care. 2006;29:1878-1883.  [PubMed]  [DOI]
45.  Fumeron F, Péan F, Driss F, Balkau B, Tichet J, Marre M, Grandchamp B. Ferritin and transferrin are both predictive of the onset of hyperglycemia in men and women over 3 years: the data from an epidemiological study on the Insulin Resistance Syndrome (DESIR) study. Diabetes Care. 2006;29:2090-2094.  [PubMed]  [DOI]
46.  Choi KM, Lee KW, Kim HY, Seo JA, Kim SG, Kim NH, Choi DS, Baik SH. Association among serum ferritin, alanine aminotransferase levels, and metabolic syndrome in Korean postmenopausal women. Metabolism. 2005;54:1510-1514.  [PubMed]  [DOI]