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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2006-0653
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 1 235-239
Copyright © 2007 by The Endocrine Society

A Common Mitochondrial DNA Variant and Increased Body Mass Index as Associated Factors for Development of Type 2 Diabetes: Additive Effects of Genetic and Environmental Factors

Chia-Wei Liou, Tsu-Kung Lin, Hsu Huei Weng, Cheng-Feng Lee, Tzu-Ling Chen, Yau-Huei Wei, Shang-Der Chen, Yao-Chung Chuang, Shao-Wen Weng and Pei-Wen Wang

Departments of Neurology (C.-W.L., T.-K.L., S.-D.C., Y.-C.C.), Radiology (H.H.W.), and Internal Medicine (S.-W.W., P.-W.W.), Chang Gung Memorial Hospital, Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung, Taiwan 83305; Department of Biochemistry and Center for Cellular and Molecular Biology (C.-F.L., T.-L.C., Y.-H.W.), National Yang-Ming University, Taipei, Taiwan 112

Address all correspondence and requests for reprints to: Pei-Wen Wang, M.D., Department of Internal Medicine, Chang Gung Memorial Hospital, Kaohsiung, 123, Ta-Pei Road, Niao Sung Hsiang, Kaohsiung, Taiwan 83305. E-mail: cwliou{at}ms22.hinet.net.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Objective: The suggested correlation between a T-to-C transition at the nucleotide 16189 in mitochondrial DNA (mtDNA) with increasing insulin resistance and adult-onset diabetes mellitus (DM) is debatable.

Methods: Our study examined mtDNA from 462 subjects with type 2 diabetes (T2DM) and 592 normoglycemic controls (non-DM). Each participant’s body mass index (BMI), fasting plasma glucose, fasting insulin concentration, insulin resistance index, and ß-cell function were measured. Sequencing for mtDNA, focusing on exploration of the hypervariable polycytosine tract within the control region, was also conducted in all subjects.

Results: Prevalence of the mtDNA 16189 variant was significantly different between DM and non-DM subjects (39.2% vs. 30.7% respectively; P = 0.004). Increased incidence of DM was noted in those harboring the 16189 variant compared with those lacking the variant (multivariate odds ratio, 1.38; 95% confidence interval, 1.07–1.80). Moreover, increased BMI was identified as an aggravating factor for development of DM in subjects harboring the variant. Odds ratio determinations yielded 2.14 in overweight and 4.63 in obese subjects harboring the variant in comparison with subjects without (1.83 in overweight and 2.16 in obese subjects). This is consistent with a progressively increased prevalence of the mtDNA 16189 variant in the non-DM groups with higher fasting insulin concentration, insulin resistance index, and ß-cell function (all Ptrend < 0.005).

Conclusion: The mtDNA 16189 variant can influence development of T2DM. The demonstrated dynamic between the 16189 variant and increased BMI exemplify an additive effect of genetic and environmental factors on the pathogenesis of T2DM.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
VARIANTS IN MITOCHONDRIAL DNA (mtDNA) may contribute to the pathophysiology of type 2 diabetes mellitus (DM). An A-to-G substitution at nucleotide (nt) pair 3243 in the tRNALeu(UUR) gene of mtDNA is a well-delineated diabetogenic factor with no racial exclusivity (1). Other potential influences include mtDNA rearrangements and several other point mutations (2, 3, 4). Variations in mtDNA are passed on to the next generation maternally, and this is compatible with observations from several epidemiological studies of type 2 DM (5). However, screening for the incidence of the A3243G mutation of mtDNA in diabetic patients has not revealed an appreciable incidence (1). The rarity of patients suggests that this pathology cannot fully explain the pathogenesis of the frequently prevalent DM. In 1995, Morten et al. (6) reported the observation of an unusually high frequency of the transitional variant with a T-to-C point mutation at nt 16189 among a group of patients with mitochondrial encephalomyopathy lactic acidosis and stroke-like episodes (MELAS) syndrome. The variant may indicate a propensity for the occurrence or persistence of the 3243 G:C mutation and perhaps of other tRNALeu mutations and mutations associated with diabetes (7). Indeed, a positive correlation was subsequently described between patients harboring this mtDNA variant and development of insulin resistance in their adult life (8). Although the result was recently challenged again by a second study from Newcastle that showed no significant correlation between the mtDNA variant and DM (9), previous reports from Oxford in 1998 and 2002 and an intervening report from Beijing showed positive correlations (8, 10, 11). Our group has previously reported on the association of this mtDNA variant with metabolic syndrome in a sample of ethnic Chinese subjects in Taiwan (n = 615) (12). In this article, we report our findings from the investigation of a larger group of ethnic Chinese subjects in Taiwan (n = 1054) and attempt to explore additional factors that were not accounted for in the previous reports on the relationship between the mtDNA 16189 variant and DM.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Subjects

A total of 1054 unrelated Taiwanese of ethnic Chinese backgrounds were enrolled in this study. The subjects were divided into two groups according to their personal history and presence of DM. Group 1 (DM group) consisted of 462 subjects with known past histories of type 2 DM who were receiving regular follow-up care in our hospital. Individuals who had received supplementary insulin therapy for DM because of long-term decline of pancreatic function and who had diabetes onset before the age of 30 were not included in our study. Of the DM group, 5.6% were on diet control, 6.5% were treated with insulin sensitizer, and 87.9% were taking insulin secretogogues. Group 2 (non-DM group) comprised 592 nondiabetic subjects randomly selected from the health screening center or outpatient service. The nondiabetic status was determined by the patient’s history and fasting plasma glucose (FPG) less than 110 mg/dl. Informed prior consent was given by all subjects. The studies were conducted according to the guidelines of the Declaration of Helsinki, and the study protocols were accepted by the Ethics Committee of the Chang Gung Memorial Hospital.

Participants were all older than 41 yr, with the oldest being 80 yr old. In each group, subjects were further divided into four different subgroups according to their age at the time of the study. The age subgroups were 41–50, 51–60, 61–70, and older than 71 yr. Each subgroup contained variable case numbers ranging from 61 to 216. The uneven number of diabetic subjects in the four age subgroups results from the random selection of subjects from the out-patient service. Table 1Go summarizes the demographic data of these subjects.


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  		TABLE 1. Characteristics, prevalence of the 16189 variant, and multivariate ORs for DM in our patient groups

 
Body mass index (BMI) in the diabetic patients was determined according to their body height and maximal body weight at the point of the first diagnosis of DM. These data were acquired by reviewing medical records in 84% and by recall in 16% of patients. At the time of study, the BMI of diabetic patients was also recorded for comparison. However, these data were not used for comparative study in consideration of possible modification of BMI due to lifestyle changes in DM patients after diagnosis. Non-DM subjects’ body height and body weight were measured at the beginning of the study. Three different weight subgroups were defined according to the Taiwanese definition for overweight and obesity. These subgroups were obese (BMI ≥ 27 kg/m2), overweight (24 kg/m2 ≤ BMI < 27 kg/m2), and normal (BMI < 24 kg/m2). This standard is generally used and is widely accepted in the assessment of Taiwanese people (13). Patients were allocated into the weight subgroups (Table 1Go).

Insulin resistance (HOMA-IR) and pancreatic ß-cell function (HOMA-BCF) were calculated using the homeostasis model assessment (HOMA) via the quantitative determination of fasting state plasma glucose and insulin (14). The equations were simplified as: HOMA-IR = [fasting insulin concentration (FIC) x FPG]/22.5 and HOMA-BCF (%) = (20 x FIC)/(FPG – 3.5). FIC is fasting serum insulin concentration (µU/ml), and FPG is fasting plasma glucose (mmol/liter).

DNA analyses

Total DNA was extracted from peripheral leukocytes and amplified using the PCR techniques as described previously (15). Two primers were used to amplify the mtDNA sequence of interest. The forward primer consisted of nt 15971–15990 of mtDNA and the reverse primer spanned nt 16471–16452 of the mtDNA. The presence of 16189 mtDNA variant was determined by using a combination of PCR-restriction fragment length polymorphism analysis with the enzyme MnlI. PCR products were digested with 1 U of the enzyme for at least 1 h at 37 C and subjected to electrophoresis with both positive and negative controls on a 2% agarose gel for 45 min at 80 V. DNA bands were visualized under high-intensity UV illumination after ethidium bromide staining. Moreover, for verification of the presence of this polycytosine tract within the mtDNA control region, we also performed DNA sequencing using an ABI 377 automated sequencer (Applied Biosystems, Warrington, UK) in all subjects. A polycytosine tract was defined as having eight or more continuous cytosines between the bp region 16184–16193. Table 2Go lists the different sequencing patterns and their prevalence in the available data for 1038 patients. Data from 16 patients were deemed to be unusable because of incomplete sequencing.


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  		TABLE 2. Relative frequencies of polymorphic mtDNA sequences between nucleotide 16184 and 16193 in 1038 Taiwanese people

 
Statistical analysis

Statistical analysis was performed using the Statistical Package for Social Science program (SPSS for Windows, version 11.5; SPSS, Chicago, IL), and data were calculated using Excel software (Microsoft, Seattle, WA). Continuous variables were expressed as means ± SD values and compared by performing the Student’s t test. For comparison of data regarding the proportion of mtDNA variant, the {chi}2 test was performed. Stepwise logistic regression analysis was used to identify the most accurate linear combinations of distinguishing variables (patient age categories, patient sex, BMI categories, and the 16189 mtDNA variant). Baseline variables with inclusion threshold of P < 0.05 and exclusion threshold of P > 0.1 were entered as predictor variables to control for confounding effects. Results of the logistic regression model were presented as the odds ratio (OR) and 95% confidence interval (CI).


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
As compared with the non-DM subjects, patients in the DM group showed a significantly higher prevalence of mtDNA 16189 variant (P = 0.004). The presence of the variant was associated with an increased risk for generation of DM. The results remained consistent after accounting for adjustments in age, sex and BMI (Table 1Go; multivariate OR, 1.38; 95% CI, 1.07–1.80). Moreover, a higher BMI was also associated with DM (P < 0.001). The results also maintained consistency after multivariate analysis. As compared with subjects with normal BMI, overweight and obese subjects had multivariate ORs of 1.84 (95% CI, 1.37–2.47) and 2.62 (95% CI, 1.91–3.61) for development of DM, respectively (Table 1Go). In our series, there is no evidence pointing to a two-way interaction between the mtDNA 16189 variant and BMI (P = 0.75 and 0.10, respectively). These observations suggest that both the mtDNA 16189 variant and the higher BMI are two independent risk factors for development of DM in our population.

Distribution of our randomly selected diabetic patients showed the highest proportion of subjects in the age group 61–70 (38.7%, 179 of 462) followed by 71–80 (24.7%, 114 of 462) and 51–60 (23.4%, 108 of 462) (Table 1Go). This distribution is compatible with the reported prevalence of DM in present-day Taiwan (16). Comparisons between the corresponding age subgroups within the two major groups noted higher 16189 variant rates in all the diabetic age subgroups (Table 1Go). The rate difference was particularly significant in the 61–70 subgroup. However, rate differences were insignificant following the multivariate adjustments for sex and BMI in all age subgroups (Table 1Go).

Comparisons of average BMI between subjects with and without the mtDNA 16189 variant within the overall group, within the DM and non-DM groups, within separate gender groups and four different age subgroups are shown in Table 3Go. The BMI comparisons exhibited no statistical differences between subjects with or without the variant within all groups and subgroups. There is evident interrelation between both increased BMI and/or the presence of the mtDNA 16189 variant, and the development of DM but there is no direct evidence pointing to the 16189 variant causing increased BMI. The age groups 51–60 and 61–70 have a higher percentage of DM patients and are notable for their association with an increased prevalence of the mtDNA 16189 variant as well as increased BMI, which implicates a combined effect of these factors on the development of DM in these age groups. Accordingly we further analyzed the combined influence of the mtDNA variant and increased BMI on development of DM and rendered a crescendo increase of OR from 1 to 4.63 for development of DM (Table 4Go). The results show the effect of independent genetic and environmental factors combining to accentuate the generation of DM.


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  		TABLE 3. Comparisons of average BMI between variant and wild-type 16189 mtDNA in our patient groups

 

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  		TABLE 4. ORs for DM in relationship to 16189 variant in various BMI subgroups

 
Determinations for the prevalence of the mtDNA 16189 variant in the non-DM groups by fasting insulin concentration, insulin resistance index, and HOMA ß-cell function quartiles are listed in Fig. 1Go. The proportion of subjects with the mtDNA 16189 variant increased with higher fasting insulin concentration, insulin resistance index, and HOMA ß-cell function quartiles. There are significant differences between the quartiles (all Ptrend < 0.005).


Figure 1
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  		FIG. 1. Prevalence of the 16189 variant by FIC, insulin resistance index, and ß-cell function quartiles in the non-DM patient groups. There are significant differences between these quartiles (P values all < 0.005).

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The overall prevalence of the mtDNA 16189 variant in our study group of Taiwanese subjects is 34.4%. This rate is higher than the reported results for either DM or non-DM subjects from England and Korea and for Chinese people living in Beijing (8, 10, 11, 17), but is similar to the report from Japan (18). These observations may reflect the fact that, although Taiwanese people historically originated mainly from China, interbreeding occurred over subsequent generations with aboriginals from southern China and others sharing similar genetic origins from the South Pacific region, which reports a high prevalence of mtDNA 16189 variant (19). Thus, the present results would be expected to be different from those in China. The incidence of type 2 DM in Taiwan has been increasing more rapidly in recent years than in Western countries (20, 21). This is associated with a higher average BMI in the general population than the previous decade (22). Moreover, it is also accompanied by an increased daily consumption of fat, carbohydrates, and proteins as reflected in the improved economic condition (13, 23). Although a higher BMI and increased caloric intake may directly influence the higher incidence of type 2 DM, additional factors may contribute. Whether the increasing incidence of DM reflects an underlying racial-specific genetic factor or a higher prevalence of the 16189 variant requires further research.

Presently we have demonstrated that the prevalence of the 16189 variant is higher in type 2 DM patients than in the age- and sex-matched non-DM subjects. The OR for the presence of the variant in the diabetic patients is 1.38. A multivariate logistic regression analysis identified this variant as an independent risk factor for development of DM. These results are in agreement with two previous investigations of different ethnic origin and are also consistent with the findings of higher levels of fasting insulin, insulin resistance, and ß-cell function in our subjects who harbored the 16189 variant (8, 11). The latter findings are often suggested as being indicative of a pre-diabetic state. Although this study did not offer haplogroup analysis for determination of racial-specific characteristics, similar reports from two Chinese institutions located in two geographically disparate regions may weaken the possibility of a founder effect in this mtDNA variant (11, 24) and strengthen the possibility that its occurrence is independent. This study also demonstrates that increased BMI additionally contributes to the development of DM in subjects harboring the 16189 variant, compared with those lacking the variant in Taiwan’s population. This association is particularly significant with an increased OR (from 2.16 to 4.63) in the presence of DM compared with obese subjects not harboring the mtDNA variant. Odds ratios also increased from 1.83 to 2.14 in the overweight subgroup harboring the variant. These results are consistent with the suggestion that both the presence of the mtDNA variant and BMI change contributed to the development of DM. Furthermore, being an environmental factor, increased BMI may be superimposed on the mtDNA genetic factors aggravating the development of DM. Our study offer substantial support for the recent suggestion that genetic as well as environmental factors are all important determinants for type 2 DM (25, 26).

Prevalence of the mtDNA 16189 variant is higher in all DM age subgroups compared with the corresponding non-DM age subgroups. The rate difference is particularly significant in the 61–70 subgroup. However, the difference shows no statistical significance following a multivariate adjustment for BMI. These findings are consistent with the idea that age differences might not be implicated in the pathological mechanism of development of DM in people who harbor the 16189 variant, but rather people in this age category have another factor involved in the determination. This suggestion is reflected in the higher BMIs observed in those aged 51–70 than in those younger than 50 and older than 70 yr. The discrepancies in BMI increases in certain age subgroups are associated with the economic and nutritional improvements that have occurred in Taiwan in the years after World War II (13, 22). All these observations may be helpful in proving the positive interrelation between the 16189 variant, increased BMI, and development of DM. However, more reproducible data in other Asian nations sharing similar social development is required.

In the present study, we did not unearth a correlation between the presence of the mtDNA 16189 variant and a higher average BMI over all subjects in either the DM or the non-DM group. Similarly, associations were absent in various age subgroups of the DM and non-DM groups. These observations are at variance with a previous study from Korea, in which a higher average BMI was associated with the presence of the 16189 variant in normal non-diabetic subjects (17). Earlier presumptions that the 16189 variant is possibly related to body weight are not strengthened by our study results (17, 27, 28). Some other genetic factors or effects of climatic differences between temperate northern countries and more tropical regions may be a determining factor for BMI discrepancies but requires more comparative study (29). It is hypothesized that a T-to-C transition at nt 16189 in the non-coding nt position of mtDNA creates an unstable polycytosine tract, which may interfere with normal mtDNA replication and transcription (7). Moreover, it is also possible that an increased BMI, acting as an additional environmental factor, aggravates the oxidative stress status, exerting compensatory pressure on mitochondria that cannot adequately respond in subjects harboring a functionally subnormal 16189 mtDNA variant (30, 31).


   Acknowledgments
 
We thank Chih-Yun Lin for her assistance in partial statistical works.


   Footnotes
 
This work was supported by research grants from the National Science Council, Executive Yuan (ROC), NSC-91-2314-B-182A-040, NSC-92-2314-B-182A-119, and CMRPG850251.

Disclosure Statement: The authors have nothing to disclose.

First Published Online October 10, 2006

Abbreviations: BMI, Body mass index; CI, confidence interval; DM, diabetes mellitus; FIC, fasting insulin concentration; FPG, fasting plasma glucose; HOMA, homeostasis model assessment; mtDNA, mitochondrial DNA; nt, nucleotide; OR, odds ratio.

Received March 24, 2006.

Accepted September 29, 2006.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. Gerbitz KD, van den Ouweland JM, Maassen JA, Jaksch M 1995 Mitochondrial diabetes mellitus: a review. Biochim Biophys Acta 1271:253–260[Medline]
  2. Ballinger SW, Shoffner JM, Gebhart S, Koontz DA, Wallace DC 1994 Mitochondrial diabetes revisited. Nat Genet 7:458–459[CrossRef][Medline]
  3. Nakagawa Y, Ikegami H, Yamato E, Takekawa K, Fujisawa T, Hamada Y, Ueda H, Uchigata Y, Miki T, Kumahara Y 1995 A new mitochondrial DNA mutation associated with non-insulin-dependent diabetes melllitus. Biochem Biophys Res Commun 209:664–668[CrossRef][Medline]
  4. Hirai M, Suzuki S, Onoda M, Hinokio Y, Ai L, Hirai A, Ohtomo M, Komatsu K, Kasuga S, Satoh Y, Akai H, Toyota T 1996 Mitochondrial DNA 3394 mutation in the NADH dehydrogenase subunit I associated with non-insulin-dependent diabetes mellitus. Biochem Biophys Res Commun 219:951–955[CrossRef][Medline]
  5. Alcolado JC, Alcolado R 1991 Importance of maternal history of non-insulin dependent diabetic patients. BMJ 302:1178–1180[Abstract/Free Full Text]
  6. Morten KJ, Poulton J, Sykes B 1995 Multiple independent occurrence of the 3243 mutation in mitochondrial tRNAleuUUR in patients with the MELAS phenotype. Hum Mol Genet 4:1689–1691[Free Full Text]
  7. Marchington DR, Poulton J, Sellar A, Holt IJ 1996 Do sequence variants in the major non-coding region of mitochondrial genome influence mitochondrial mutations associated with disease? Hum Mol Genet 5:473–479[Abstract/Free Full Text]
  8. Poulton J, Scott Brown M, Cooper A, Marchington DR, Phillips DIW 1998 A common mitochondrial DNA variant is associated with insulin resistance in adult life. Diabetologia 41:54–58[CrossRef][Medline]
  9. Chinnery PF, Elliott HR, Patel S, Lambert C, Keers SM, Durham SE, McCarthy MI, Hitman GA, Hattersley A, Walker M 2005 Role of the mitochondrial DNA 16184–16193 poly-C tract in type 2 diabetes. Lancet 366:1650–1651[CrossRef][Medline]
  10. Poulton J, Luan J, Macaulay V, Hennings S, Mitchell J, Wareham NJ 2002 Type 2 diabetes is associated with a common mitochondrial variant: evidence from a population-based case-control study. Hum Mol Genet 11:1581–1583[Abstract/Free Full Text]
  11. Ji L, Gao L, Han X 2001 Association of 16189 variant (T–>C transition) of mitochondrial DNA with genetic predisposition to type 2 diabetes in Chinese populations. Zhonghua Yi Xue Za Zhi 81:711–714[Medline]
  12. Weng SW, Liou CW, Lin TK, Wei YH, Lee CF, Eng HL, Chen SD, Liu RT, Chen JF, Chen IY, Chen MH, Wang PW 2005 Association of mitochondrial DNA 16189 variant (T->C transition) with metabolic syndrome in Chinese adults. J Clin Endocrinol Metab 90:5037–5040[Abstract/Free Full Text]
  13. Lin YC, Yen LL, Chen SY, Kao MD, Tzeng MS, Huang PC, Pan WH 2003 Prevalence of overweight and obesity and its associated factors: findings from National Nutrition and Health Survey in Taiwan, 1993–1996. Prev Med 37:233–241[CrossRef][Medline]
  14. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC 1985 Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419[CrossRef][Medline]
  15. Shih KD, Yen TC, Pang CY, Wei YH 1991 Mitochondrial DNA mutation in a Chinese family with myoclonic epilepsy and ragged-red fiber disease. Biochem Biophys Res Commun 174:1109–1116[CrossRef][Medline]
  16. Lu FH, Yang YC, Wu JS, Wu CH, Chang CJ 1998 A population-based study of the prevalence and associated factors of diabetes mellitus in southern Taiwan. Diabet Med 15:564–572[CrossRef][Medline]
  17. Kim JH, Park KS, Cho YM, Kang BS, Kim SK, Jeon HJ, Kim SY, Lee HK 2002 The prevalence of the mitochondrial DNA 16189 variant in non-diabetic Korean adults and its association with higher fasting glucose and body mass index. Diabet Med 19:681–684[CrossRef][Medline]
  18. Horai S, Hayasaka K 1990 Intraspecific nucleotide sequence differences in the major noncoding region of human mitochondrial DNA. Am J Hum Genet 46:828–842[Medline]
  19. Sudoyo H, Suryadi H, Sitorus N, Soegondo S, Pranoto A, Marzuki S 2003 Mitochondrial genome and susceptibility to diabetes mellitus. Adv Exp Med Biol 531:19–36[Medline]
  20. Wang SL, Pan WH, Hwu CM, Ho LT, Lo CH, Lin SL, Jong YS 1997 Incidence of NIDDM and the effects of gender, obesity and hyperinsulinaemia in Taiwan. Diabetologia 40:1431–1438[CrossRef][Medline]
  21. Amos AF, McCarty DJ, Zimmet P 1997 The rising global burden of diabetes and its complications: estimates and projections to the year 2010. Diabet Med 14 Suppl 5:S7–S85
  22. Pan WH, Flegal KM, Chang HY, Yeh WT, Yeh CJ, Lee WC 2004 Body mass index and obesity-related metabolic disorders in Taiwanese and US whites and blacks: implications for definitions of overweight and obesity for Asians. Am J Clin Nutr 79:31–39[Abstract/Free Full Text]
  23. Pan WH, Chang YH, Chen JY, Wu SJ, Tzeng MS, Kao MD 1999 Nutrition and Health Survey in Taiwan (NAHSIT) 1993–1996: dietary nutrient intakes assessed by 24-hour recall. Nutr Sci J 24:11–39
  24. Tang DL, Zhou X, Zhou KY, Li X, Zhao L, Liu F, Zheng F, Liu SM 2005 Association of mitochondrial DNA variation with type 2 diabetes mellitus. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 22:636–640[Medline]
  25. Willett WC 2002 Balancing life-style and genomics research for disease prevention. Science 296:695–698[Abstract/Free Full Text]
  26. van Dam RM 2003 The epidemiology of lifestyle and risk for type 2 diabetes. Eur J Epidemiol 18:1115–1125[CrossRef][Medline]
  27. Poulton J 1998 Does a common mitochondrial DNA polymorphism underlie susceptibility to diabetes and the thrifty genotype? Trends Genet 14:387–389[CrossRef][Medline]
  28. Casteels K, Ong K, Phillips D, Bendall H, Pembrey M, Poulton J, Dunger D 1999 Mitochondrial 16189 variant, thinness at birth, and type-2 diabetes. Lancet 353:1499–1500[CrossRef][Medline]
  29. Katzmarzyk PT, Leonard WR 1998 Climatic influences on human body size and proportions: ecological adaptations and secular trends. Am J Phys Anthropol 106:483–503[CrossRef][Medline]
  30. Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, Nakayama O, Makishima M, Matsuda M, Shimomura I 2004 Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest 114:1752–1761[CrossRef][Medline]
  31. Lin TK, Chen SD, Wang PW, Wei YH, Lee CF, Chen TZ, Lee CF, Chuang YC, Tan TY, Chang KC, Liou CW 2005 Increased oxidative damage with altered antioxidative status in type 2 diabetic patients harboring the 16189 T to C variant of mitochondrial DNA. Ann NY Acad Sci 1042:64–69[CrossRef][Medline]



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