Recently, an A-to-G variant in intron 3 (SNP43) of the calcium-activated neutral protease 10 gene (CAPN10) was identified as a possible type 2 diabetes susceptibility gene through positional cloning in Mexican-Americans. We conducted cross-sectional and prospective studies to evaluate the relation between SNP43 and type 2 diabetes and related traits in middle-aged African-American participants of the Atherosclerosis Risk in Communities Study, a population-based longitudinal study. At baseline, 269 prevalent diabetes cases and 1,159 nondiabetic control subjects were studied. Those with the G/G genotype were more likely to have diabetes than those with the A/G or A/A genotype (odds ratio [OR] 1.41, 95% CI 1.00–1.99, P = 0.05). In the prospective study, 166 of the control subjects developed incident diabetes over 9 years of follow-up. The incidence of diabetes for individuals with the G/G genotype did not differ significantly from those with at least one copy of the A allele (23.3 vs. 19.5 per 1,000 person years, P = 0.29). Pooling prevalent and incident diabetic cases together, individuals with the G/G genotype were ∼40% more likely to have diabetes than those without (OR 1.38, 95% CI 1.04–1.83, P = 0.03). Because of the high frequency of the G allele (0.88), ∼25% of the susceptibility to type 2 diabetes in African-Americans may be attributed to the G/G genotype at SNP43 of CAPN10, although most of the subjects with the G/G genotype did not develop diabetes over the 9 years of follow-up. We conclude from this large prospective study that the G allele of SNP43 of CAPN10 or another allele or gene that is in linkage disequilibrium with it increases susceptibility to type 2 diabetes in African-Americans.

Type 2 diabetes (formerly known as non–insulin-dependent diabetes) is a heterogeneous disorder in which both genetic and nongenetic influences contribute to disease risk (1). The genetic contribution is likely to comprise several gene variants, each with relatively modest effect, which act in combination with each other and with environmental provocations to cause the disease. Genome wide scans have led to the chromosomal localization of susceptibility loci for type 2 diabetes in the Pima Indians of North America (2), in African-Americans, Caucasians, and Japanese Americans from the American Diabetes Association Genetics of NIDDM (GENNID) Study (3), in Mexican-Americans (3,4,5), and in Caucasians from Finland (6,7,8,9), France (10), Utah (U.S.) (11), and the U.K. (12). The first type 2 diabetes susceptibility locus, NIDDM1, was discovered in Mexican-Americans from Starr County, TX, and was localized to the D2S125-D2S140 region on chromosome two (4). Linkage in the region of NIDDM1 has also been observed in French families in some studies (13) but not in other studies (5,14,15,16). Through positional cloning, Horikawa et al. (17) recently identified NIDDM1 as calpain 10 (CAPN10). A common A-to-G single nucleotide polymorphism in intron 3 (SNP-43) of CAPN10 was recessively associated with type 2 diabetes in a Mexican-American population from Starr County, TX (17). Calpains, or calcium-activated neutral proteases, are intracellular nonlysosomal cysteine proteases, which contribute to diverse physiological cell functions (18,19,20,21). Despite these diverse functions, calpains have not previously been implicated in pathways that regulate glucose homeostasis, and thus, the mechanism whereby this variant contributes to diabetes risk is unknown. Furthermore, because SNP43 is in the noncoding region of CAPN10, it is not known how this polymorphism affects CAPN10 activity. Given the unclear role of CAPN10 in diabetes pathogenesis, defining whether SNP43 modifies diabetes risk in other populations is of critical importance.

African-Americans are at increased risk for the development of type 2 diabetes (22). However, few studies have investigated the genetic underpinnings of type 2 diabetes in African-Americans. To define the relevance of SNP43 of CAPN10 in this ethnic group, we examined its relation to type 2 diabetes risk in a large population-based prospective study of middle-aged African-American participants of the Atherosclerosis Risk in Communities (ARIC) Study, who were characterized with respect to diabetes prevalence and incidence.

Study participants.

Subjects of the present analyses were selected from the 4,266 African-American participants of the ARIC Study. The ARIC Study is a prospective epidemiological study that examines clinical and subclinical atherosclerotic disease, characteristics of which have been previously reported (23). The present analyses were based on information obtained at baseline and after 9 years of follow-up, consisting of a total of four clinic visits (V1 through V4) scheduled 3 years apart. African-American individuals were excluded from the sampling frame of the present analyses if they had missing demographic, clinical, dietary, or laboratory data at baseline (n = 998), resulting in a sampling frame of 3,268 individuals (2,006 women and 1,262 men). Subjects who were excluded because of incomplete data did not differ significantly with respect to demographics. Using sex-stratified random sampling to maintain a female:male ratio of 3:2, as in the original cohort, 1,441 individuals were selected for the present analyses (sampling fraction 44%). Study participants were not known to be first-degree relatives of one another.

Diabetic case subjects were defined as individuals with any one of the following characteristics at V1 through V4 of the study: 1) fasting glucose ≥7.0 mmol/l (126 mg/dl), 2) nonfasting glucose ≥11.1 mmol/l (200 mg/dl), 3) current use of medication to treat diabetes, or 4) a positive response to the question “Has a doctor ever told you that you had diabetes (sugar in the blood)?”

Details of baseline and follow-up examinations of ARIC study subjects have been reported elsewhere. For the purposes of this study, information included age, sex, race, personal and family history of diabetes, anthropometry (height, weight, waist, hip, and subscapular and triceps skinfolds), and fasting blood (glucose, insulin, total cholesterol, HDL cholesterol, and triglycerides). Physical activity during leisure time was assessed by a modified version of the questionnaire developed by Baecke et al. (24). Dietary intake was assessed by a modified version of the 61-item food frequency questionnaire developed by Willett et al. (25).

Detection of the SNP43 of the CAPN10 gene.

A polymerase chain reaction was performed (AmpliTaq Gold with GeneAmp; Perkin Elmer Biosystems, Branchburg, NJ) with 20 ng DNA using an upstream primer of 5′-CACGCTTGCTGTGAAGTAATGC-3′ and a downstream primer of 5′-CTCTGATTCCCATGGTCTGTAG-3′ in the presence of 8.5% dimethylsulfoxide (Sigma Chemical, St. Louis, MO). The resulting 144-bp product was digested with Nsi I (New England Biolabs, Beverly, MA) at 37°C for 15–18 h. The digested products were subjected to electrophoresis through a 4% agarose gel (MetaPhor agarose; FMC Bioproducts, Rockland, ME) containing 250 nmol/l ethidium bromide. The homozygous G/G product remained 144 bp after digestion with Nsi I, whereas the homozygous A/A product was cleaved into two products of 121 and 23 bp. The products were visualized in the gel under UV translumination. Genotypes were scored by two independent observers. The accuracy rate based on blind repeats (n = 86) was 96%.

Statistical analysis.

All statistical analyses were performed using the SAS statistical package (Cary, NC). Means ± SD and frequencies of baseline characteristics were calculated. Fasting serum insulin and triglyceride levels were not normally distributed; therefore, those values were natural logarithm-transformed. Allele frequencies were calculated, and a two-sample test for binomial proportions was used to assess differences in allele frequencies between diabetic and nondiabetic individuals. The χ2 goodness-of-fit test was used to assess deviation from Hardy-Weinberg equilibrium of the genotypic frequency by calculating expected frequencies of genotypes.

Based on studies in Mexican-Americans in Starr County, TX, we assumed a recessive mode of inheritance in which the more common genotype G/G is the “at risk” genotype (17). Multiple logistic regression was used to obtain odds ratios (ORs) for diabetes (with 95% CI) after adjustment for age, sex, and other potential covariates. To assess the effect of adiposity on serotypically conferred diabetes risk, stratification analyses were repeated after stratification for adiposity, according to NHLBI criteria: nonoverweight (BMI <25 kg/m2), overweight (BMI 25–29.9 kg/m2), and obese (BMI ≥30 kg/m2). Analysis of variance was used to test for association between each continuous phenotype and SNP43 genotype.

Diabetes-related quantitative traits were measured at each of the four visits of the study. To assess prospective changes in these traits, we used multiple linear regression to look at changes in quantitative traits. Because fasting serum insulin levels were only measured at V1 and V4 of the study, analysis of insulin levels were assessed by examining genotypic influences on prospective changes in insulin between V1 and V4, calculated as the difference between insulin = ln[insulin at V4] – ln[insulin at V1], which becomes ln(insulin at V4/insulin at V1).

Effect modifications of the association between SNP43 genotype and type 2 diabetes by physical activity levels (categorized into quartiles) and total energy intake (categorized into quartiles) were assessed by fitting interaction terms into the multiple logistic regression model. In addition, we examined potential interactions between diet or physical activity and genotype on the continuous variables, BMI, and glucose using analysis of covariance.

Allele frequency and genotype distribution by type 2 diabetes status.

At baseline, 269 prevalent diabetes cases and 1,159 control subjects were randomly selected from 3,268 African-American ARIC participants to be included in the present study, with 86% of the participants from Jackson, MS. The baseline characteristics of the participants were compared between those with and without diabetes in Table 1. In the cross-sectional analysis at baseline, the allele frequency of the G allele was slightly higher in subjects with diabetes (n = 269) than in control subjects (n = 1,159) (90.0 vs. 87.2%, P = 0.08). The genotype frequencies were in accordance with Hardy-Weinberg equilibrium in both strata, with 2.2% of the participants homozygous for the A allele (A/A), 77.7% homozygous for the G allele (G/G), and 20.1% heterozygous (A/G). Based on studies in Mexican-Americans from Starr County, TX, we assumed a recessive mode of inheritance in which the more common G allele is the “at risk” allele (17). Participants with the G/G genotype were more likely to have diabetes than those with at least one copy of the A allele (OR 1.41, 95% CI 1.00–1.99, P = 0.05) (Table 2). Adjusting the OR for BMI did not change the results, nor were there any effects of age or sex on the association of the G/G genotype with diabetes.

In prospective analysis, 166 of the individuals who were nondiabetic at baseline developed incident diabetes during the 9 years of follow-up, leaving 993 participants free of incident type 2 diabetes. The incidence of diabetes for individuals with the G/G genotype did not differ significantly from those with at least one copy of the A allele (23.3 vs. 19.5 per 1,000 person years, P = 0.29). Pooling all prevalent and incident diabetic cases together, individuals with the G/G genotype were significantly more likely to have or to develop diabetes than those who remained free of diabetes throughout the study (OR 1.38, 95% CI 1.04–1.83, P = 0.03) (Table 2). Association between the G/G genotype and diabetes was independent of age, sex, and BMI.

SNP43 genotype distribution, obesity, and diabetes-related quantitative traits at baseline.

To discern potential mechanisms whereby SNP43 genotype might increase diabetes risk, three different analyses were performed. First, we examined diabetes- and obesity-related traits at baseline in G/G homozygotes compared with G/A and A/A genotypes (Table 3). There were no significant differences in subjects with or without diabetes in any of the diabetes- or obesity-related traits (BMI, waist-to-hip ratio, waist circumference, subscapular and triceps skinfold, and glucose) at baseline between the participants carrying at least one copy of the A allele and those homozygous for the G allele at baseline. Similarly, there were no significant differences in the cardiovascular risk factors (HDL and LDL cholesterol, triglycerides, and blood pressure) between genotypes, except for systolic blood pressure, which was significantly higher in nondiabetic subjects homozygous for the G allele compared with those with at least one copy of the A allele (127.5 vs. 124.3 mmHg, P = 0.02).

Second, we examined changes in diabetes- and obesity-related phenotypes in nondiabetic subjects over the 9 years of follow-up (Table 4). There were no significant differences between SNP43 genotypes with respect to changes in any of the obesity-, diabetes-, or cardiovascular-related traits that were examined over the 9 years of follow-up except for triglycerides, in which there were greater increases in the subjects homozygous for the G allele (Table 4). Fasting insulin levels tended to increase more in G/G homozygotes, suggesting the development of greater insulin resistance.

Third, among subjects who developed diabetes during the study (incident cases), we examined associations of genotype with phenotypes measured at the visit just before the development of diabetes. There were no significant differences in any of the obesity or diabetic measures between G/G homozygotes and subjects carrying at least one copy of the A allele before diagnosis. (Table 5). Similarly, there were no differences in any of these traits at the time of diabetes diagnosis (data not shown).

The availability of data on physical activity and dietary intake provided the opportunity to examine potential interactions between these extrinsic factors and SNP43 genotype on diabetes risk. No statistically significant interactions (multiplicative or additive) were detected (data not shown).

The main finding of this study is that among African-Americans, homozygosity for the common G allele of SNP43 of the CAPN10 gene is associated with a modest increase in risk of type 2 diabetes. These results are in agreement of Horikawa et al. (17), who showed that SNP43 of CAPN10 is associated with susceptibility to type 2 diabetes in Mexican-Americans from Starr County, TX. Association of the G allele of SNP43 of CAPN10 with type 2 diabetes in African-Americans persisted when including both prevalent cases and incident cases over the 9 years of follow-up. Despite this association with type 2 diabetes, there were no associations of the G/G genotype with other quantitative traits related to diabetes, such as glucose or insulin levels, as was shown by Baier et al. (26) in Pima Indians. Our results are in contrast to two recent negative studies of SNP43 in large case-control studies, one of Caucasians from the U.K. (27) and another of Oji-Cree Native Canadians (28). A possible reason for these discrepant findings is that Horikawa et al. (17) showed that a combination of two different haplotypes (each containing the G allele at SNP43) confers greater risk of type 2 diabetes. Although haplotypes were not examined directly in this study, the “at risk” haplotypes are much more common in Mexican-Americans, Native Americans, and African-Americans than in Caucasians (17; C.L.H., personal communication).

This well-characterized cohort provided the opportunity to examine potential interactions of extrinsic factors that are known to influence diabetes risk with the SNP43 genotype. We did not detect any interactions between SNP43 genotype and leisure time physical activity or dietary intake, suggesting that these extrinsic risk factors do not play a major role in altering the diabetes risk associated with G/G homozygosity.

This study design has several strengths. First, it is a relatively large and well-characterized study of African-Americans. Second, sampling was population-based, thus reducing potential biases that may result from clinic- or hospital-based ascertainment. However, we cannot exclude the possibility that other factors (e.g., selection bias or preferential attrition rate) may have resulted in a study population that differed from the general African-American population. Third, using 9 years of follow-up data, the present study examined the associations between SNP43 and changes in BMI, waist-to-hip ratio, and fasting serum glucose and insulin levels in order to examine potential mechanisms whereby this variant increases diabetes risk. Finally, the large sample size of the present study and the availability of information on leisure time physical activity and dietary intake provide good power to detect modest gene-environment interactions and provide relatively narrow confidence intervals when no significant associations were detected.

Despite these strengths, several limitations of the present study may have influenced the results. First, characterization of body composition and insulin resistance were limited to anthropometric measures and fasting serum insulin, respectively. Anthropometric measures such as BMI and waist-to-hip ratio represent relatively crude markers for adiposity. Similarly, there is a large degree of variation in dietary and physical activity questionnaires as assessments of caloric intake and expenditure, respectively. The inconsistency between greater BMI and lower caloric intake in subjects with diabetes is likely to reflect systematic under-reporting of caloric intake in subjects with diabetes compared with control subjects (29). Although fasting serum insulin is only a marker of insulin sensitivity, it has been demonstrated in previous studies to correlate reasonably well with more sensitive measures assessed by the euglycemic-hyperinsulinemic clamp or frequently sampled intravenous glucose tolerance tests (30). Second, positive associations reported by the present study may be the result of a type 1 error, although this is mitigated by a strong a priori hypothesis and confirmatory results in other studies (17,31,32). Third, the association between SNP43 and diabetes could be the result of linkage disequilibrium between the candidate gene variant and the true disease-causing variant. Fourth, the lack of changes in diabetes- or obesity-related traits over time in nondiabetic individuals (Table 4) may be caused by the absence of other susceptibility gene variants or the presence of additional gene variants that are protective from the development of diabetes. Finally, we cannot exclude the possibility of false positive or negative associations caused by population stratification.

Although individuals with the G/G SNP43 genotype were ∼40% more likely to have diabetes than those individuals with at least one copy of the A allele, there was no association of SNP43 genotype with any diabetes-related traits (e.g., BMI, fasting insulin) or with changes in these diabetes-related traits over time, leaving further questions regarding a potential mechanism whereby this variant may increase diabetes risk. Calpains are cysteine proteases, which process specific substrates at a limited number of sites, causing activation or inactivation of proteins (33). Calpains have been implicated in adipocyte differentiation in 3T3-L1 cells (34). Calpain 10 is expressed in liver, muscle, and pancreatic islets (17). Thus, altered calpain 10 expression and/or function may have effects in several tissues important for glucose homeostasis (17,35,36,37,38). Studies suggest that the G allele is associated with altered binding of nuclear proteins and decreased transcription (17). Indeed, Pima Indians with the G/G SNP43 genotype had decreased expression of calpain 10 in skeletal muscle and reduced rates of postabsorptive and insulin-stimulated glucose turnover (17), and calpain inhibitors may decrease insulin secretion in isolated islets (39).

The high G allele frequency of SNP43 of CAPN10 in African-Americans suggests that it has a major public health impact. A typical approach to quantify public health impact is calculating population attributable risk (PAR). PAR calculations are generally confined to relations with strong evidence of causality, and association studies cannot prove causality, especially in light of the fact that SNP43 is in the noncoding region of CAPN10. Nonetheless, preliminary calculations are useful to provide context for the research, especially in community-based studies. Assuming causality of SNP43 or a variant in linkage disequilibrium with SNP43 and using Levin’s formula for population attributable risk (40), we found that ∼25% of the susceptibility to type 2 diabetes in African-Americans may be attributed to the G/G genotype at SNP43. However, homozygosity for the G allele constitutes 78% of this African-American sample, which is much greater than the prevalence of type 2 diabetes in this population. These findings suggest that this allele increases diabetes risk on a population-wide basis, but has poor positive predictive value. Possibly, the additive effects of other unlinked yet-to-be-determined gene variants with SNP43 of CAPN10 may better define individual risk. Indeed, there is evidence that a locus on chromosome 15 may interact with CAPN10 or with another gene variant within the NIDDM1 locus (41). Alternatively, SNP43 may be in linkage disequilibrium with a less common variant that might better predict and/or define diabetes risk. In Mexican-Americans, haplotype analysis suggests that the combination of two different CAPN 10 haplotypes, both of which include the G allele of SNP43, are required to confer increased diabetes risk. We cannot rule this out as a possibility in African-Americans because haplotypes in this population-based study have not yet been examined.

In summary, results from the present study indicate a significant association between homozygosity for the common G allele of SNP43 of CAPN10 and typical type 2 diabetes in a large population-based longitudinal study of African-Americans. If this genetic variant is the causative allele, it may account for as much as 25% of the attributable risk of diabetes in this population. Further studies are warranted to define the role of this variant in other populations on diabetes risk and to investigate the pathophysiological, cellular, and molecular mechanisms that underlie these associations.

TABLE 1

Baseline characteristics of 1,428 African-American ARIC participants stratified by diabetes status

Subjects without diabetesSubjects with diabetesP
n 1,159 269  
Age (years) 53.0 ± 5.7  54.9 ± 5.8  <0.001 
Sex (% male) 40.9 39.8 0.74 
Education (%)    
 ≤11 years 39.3 47.6  
 High school graduate 28.9 29.4 0.01 
 Attended college 31.8 23.0  
ARIC Study site (% at Jackson, MS) 85.6 87.4 0.52 
Parental history of diabetes (% yes) 23.3 42.8 <0.001 
BMI (kg/m228.6 ± 5.9  31.3 ± 5.6  <0.001 
Waist-to-hip ratio 0.909 ± 0.074 0.954 ± 0.063 <0.001 
Waist circumference (cm) 96.6 ± 14.6 105.2 ± 12.8  <0.001 
Mean subscapular skinfold (mm) 29.8 ± 13.6 36.0 ± 12.3 <0.001 
Mean triceps skinfold (mm) 25.9 ± 12.2 28.4 ± 11.7 0.002 
Total caloric intake (kcal/day) 1663 ± 798  1461 ± 692  <0.001 
Physical activity    
 Sports related 2.17 ± 0.70 2.14 ± 0.70 0.56 
 Leisure related 2.10 ± 0.57 2.00 ± 0.50 0.01 
Fasting serum glucose (mmol/l) 5.47 ± 0.55 *NR — 
Ln(fasting insulin) (pmol/l) 4.31 ± 0.67 *NR — 
HDL cholesterol (mmol/l) 1.47 ± 0.47 1.29 ± 0.36 <0.001 
LDL cholesterol (mmol/l) 3.53 ± 1.12 3.77 ± 1.23 0.005 
Ln(triglycerides) (mmol/l) 0.03 ± 0.44 0.26 ± .21 <0.001 
Systolic blood pressure (mmHg) 126.7 ± 20.0  133.7 ± 21.4 <0.001 
Diastolic blood pressure (mmHg) 79.7 ± 12.2  78.9 ± 12.3 0.32 
Subjects without diabetesSubjects with diabetesP
n 1,159 269  
Age (years) 53.0 ± 5.7  54.9 ± 5.8  <0.001 
Sex (% male) 40.9 39.8 0.74 
Education (%)    
 ≤11 years 39.3 47.6  
 High school graduate 28.9 29.4 0.01 
 Attended college 31.8 23.0  
ARIC Study site (% at Jackson, MS) 85.6 87.4 0.52 
Parental history of diabetes (% yes) 23.3 42.8 <0.001 
BMI (kg/m228.6 ± 5.9  31.3 ± 5.6  <0.001 
Waist-to-hip ratio 0.909 ± 0.074 0.954 ± 0.063 <0.001 
Waist circumference (cm) 96.6 ± 14.6 105.2 ± 12.8  <0.001 
Mean subscapular skinfold (mm) 29.8 ± 13.6 36.0 ± 12.3 <0.001 
Mean triceps skinfold (mm) 25.9 ± 12.2 28.4 ± 11.7 0.002 
Total caloric intake (kcal/day) 1663 ± 798  1461 ± 692  <0.001 
Physical activity    
 Sports related 2.17 ± 0.70 2.14 ± 0.70 0.56 
 Leisure related 2.10 ± 0.57 2.00 ± 0.50 0.01 
Fasting serum glucose (mmol/l) 5.47 ± 0.55 *NR — 
Ln(fasting insulin) (pmol/l) 4.31 ± 0.67 *NR — 
HDL cholesterol (mmol/l) 1.47 ± 0.47 1.29 ± 0.36 <0.001 
LDL cholesterol (mmol/l) 3.53 ± 1.12 3.77 ± 1.23 0.005 
Ln(triglycerides) (mmol/l) 0.03 ± 0.44 0.26 ± .21 <0.001 
Systolic blood pressure (mmHg) 126.7 ± 20.0  133.7 ± 21.4 <0.001 
Diastolic blood pressure (mmHg) 79.7 ± 12.2  78.9 ± 12.3 0.32 

Data are means ± SE unless otherwise indicated.

*

NR, not reported because diabetes and its treatment may confound glucose and insulin levels;

analysis limited to 212 diabetic individuals who fasted >8 h;

significance assessed by χ2 test of homogeneity.

TABLE 2

Prevalence and incidence rates over 9 years of follow-up of type 2 diabetes in African-American ARIC participants by CAPN10 SNP43 genotype

SNP43 genotype
A/AA/GG/G
Prevalent type 2 diabetes (at V140 222 
 Nondiabetic control subjects 25 247 887 
 OR (95% CI)* 1.00 (reference)
 
1.41 (1.00–1.99) 
 Age of diabetes onset 49.8 ± 8.3 (n = 37)
 
50.7 ± 8.3 (n = 167) 
Incident type 2 diabetes (V2 to V431 133 
 Nondiabetic control subjects 23 216 754 
 Incident rate ratio (95% CI)* 1.00 (reference)
 
1.21 (0.86–1.27) 
 Age of diabetes onset 57.1 ± 5.9 (n = 32)
 
57.7 ± 5.6 (n = 114) 
All type 2 diabetes (V1 to V471 355 
 Nondiabetic control subjects 23 216 754 
 OR (95% CI)* 1.00 (reference)
 
1.38 (1.04–1.83) 
 Age of diabetes onset 53.2 ± 8.1 (n = 69)
 
53.5 ± 7.6 (n = 281) 
SNP43 genotype
A/AA/GG/G
Prevalent type 2 diabetes (at V140 222 
 Nondiabetic control subjects 25 247 887 
 OR (95% CI)* 1.00 (reference)
 
1.41 (1.00–1.99) 
 Age of diabetes onset 49.8 ± 8.3 (n = 37)
 
50.7 ± 8.3 (n = 167) 
Incident type 2 diabetes (V2 to V431 133 
 Nondiabetic control subjects 23 216 754 
 Incident rate ratio (95% CI)* 1.00 (reference)
 
1.21 (0.86–1.27) 
 Age of diabetes onset 57.1 ± 5.9 (n = 32)
 
57.7 ± 5.6 (n = 114) 
All type 2 diabetes (V1 to V471 355 
 Nondiabetic control subjects 23 216 754 
 OR (95% CI)* 1.00 (reference)
 
1.38 (1.04–1.83) 
 Age of diabetes onset 53.2 ± 8.1 (n = 69)
 
53.5 ± 7.6 (n = 281) 

Data are means ± SE unless otherwise indicated. ORs were calculated using a recessive model (i.e., A/X vs. G/G).

*

Adjusted for age at V1 and sex;

P = 0.05;

P = 0.03.

TABLE 3

Selected characteristics by SNP43 genotype in diabetic and nondiabetic African-American ARIC participants

Subjects with diabetes
Subjects without diabetes
A/A or A/GG/GPA/A or A/GG/GP
n 47 222  272 887  
BMI (kg/m231.5 31.3 0.79 28.5 28.7 0.71 
Waist-to-hip ratio 0.955 0.953 0.88 0.904 0.910 0.23 
Waist circumference (cm) 106.1 104.9 0.58 95.9 96.8 0.40 
Subscapular skinfold (mm) 37.2 35.7 0.43 29.6 29.9 0.74 
Triceps skinfold (mm) 29.7 28.1 0.31 25.7 26.0 0.60 
Glucose (mmol/l) *NR *NR — 5.49 5.46 0.58 
Ln(insulin) (pmol/l) *NR *NR — 4.30 4.31 0.77 
HDL cholesterol (mmol/l) 1.28 1.29 0.79 1.49 1.46 0.32 
LDL cholesterol (mmol/l) 3.92 3.74 0.45 3.46 3.56 0.21 
Ln(triglycerides) (mmol/l) 0.28 0.25 0.73 0.003 0.0034 0.31 
Systolic blood pressure (mmHg) 131.3 134.2 0.40 124.3 127.5 0.02 
Diastolic blood pressure (mmHg) 78.2 79.1 0.63 78.7 80.1 0.11 
Subjects with diabetes
Subjects without diabetes
A/A or A/GG/GPA/A or A/GG/GP
n 47 222  272 887  
BMI (kg/m231.5 31.3 0.79 28.5 28.7 0.71 
Waist-to-hip ratio 0.955 0.953 0.88 0.904 0.910 0.23 
Waist circumference (cm) 106.1 104.9 0.58 95.9 96.8 0.40 
Subscapular skinfold (mm) 37.2 35.7 0.43 29.6 29.9 0.74 
Triceps skinfold (mm) 29.7 28.1 0.31 25.7 26.0 0.60 
Glucose (mmol/l) *NR *NR — 5.49 5.46 0.58 
Ln(insulin) (pmol/l) *NR *NR — 4.30 4.31 0.77 
HDL cholesterol (mmol/l) 1.28 1.29 0.79 1.49 1.46 0.32 
LDL cholesterol (mmol/l) 3.92 3.74 0.45 3.46 3.56 0.21 
Ln(triglycerides) (mmol/l) 0.28 0.25 0.73 0.003 0.0034 0.31 
Systolic blood pressure (mmHg) 131.3 134.2 0.40 124.3 127.5 0.02 
Diastolic blood pressure (mmHg) 78.2 79.1 0.63 78.7 80.1 0.11 

All analyses adjusted for age at V1 and sex.

*

NR, not reported because diabetes and its treatment may confound glucose and insulin levels;

analyses of lipid traits limited to 212 diabetic individuals who fasted >8 h (n = 34 for A/A or A/G, n = 178 G/G).

TABLE 4

Change between V1 and V4 of selected characteristics by SNP43 genotype in African-American ARIC participants

SNP43 Genotype
P
 A/A or A/G G/G   
Δ (V4 to V1)Δ (V4 to V1)
BMI* (kg/m20.948 1.025 0.71 
Waist-to-hip ratio 0.031 0.027 0.44 
Waist circumference (cm) 5.59 5.50 0.88 
Fasting glucose (mmol/l)* 0.102 0.177 0.15 
Ln(fasting insulin) (pmol/l)* 0.047 0.193 0.16 
HDL cholesterol (mmol/l) −0.08 −0.07 0.80 
LDL cholesterol (mmol/l) −0.27 −0.34 0.29 
Ln(triglycerides) (mmol/l) 0.02 0.08 0.05 
Systolic blood pressure (mmHg) 8.57 7.73 0.61 
Diastolic blood pressure (mmHg) −2.88 −3.54 0.49 
SNP43 Genotype
P
 A/A or A/G G/G   
Δ (V4 to V1)Δ (V4 to V1)
BMI* (kg/m20.948 1.025 0.71 
Waist-to-hip ratio 0.031 0.027 0.44 
Waist circumference (cm) 5.59 5.50 0.88 
Fasting glucose (mmol/l)* 0.102 0.177 0.15 
Ln(fasting insulin) (pmol/l)* 0.047 0.193 0.16 
HDL cholesterol (mmol/l) −0.08 −0.07 0.80 
LDL cholesterol (mmol/l) −0.27 −0.34 0.29 
Ln(triglycerides) (mmol/l) 0.02 0.08 0.05 
Systolic blood pressure (mmHg) 8.57 7.73 0.61 
Diastolic blood pressure (mmHg) −2.88 −3.54 0.49 

Data are means. All analyses adjusted for age at V1 and sex.

*

Analysis limited to 589 individuals who were nondiabetic at baseline and remained nondiabetic through V4.

TABLE 5

Characteristics by SNP43 genotype in 161 incident diabetic African-American ARIC participants for the visit prior to their diagnosis of type 2 diabetes

Visit of prediagnosis
P
A/A or A/GG/G
BMI (kg/m233.5 ± 1.1 31.5 ± 0.6 0.12 
Waist-to-Hip ratio 0.954 ± 0.012 0.941 ± 0.006 0.34 
Waist circumference (cm) 109.4 ± 2.8 105.2 ± 1.4 0.17 
Fasting glucose (mmol/l)* 6.22 ± 0.09 6.04 ± 0.05 0.09 
Ln(fasting insulin) (pmol/l) 4.90 ± 0.15 4.58 ± 0.07 0.09 
HDL cholesterol (mmol/l)* 1.37 ± 0.07 1.33 ± 0.04 0.64 
LDL cholesterol (mmol/l)* 3.61 ± 0.17 3.41 ± 0.09 0.31 
Ln(triglycerides) (mmol/l)* 0.23 ± 0.08 0.20 ± 0.04 0.69 
Systolic blood pressure (mmHg) 126.9 ± 3.5 128.6 ± 1.8 0.67 
Diastolic blood pressure (mmHg) 77.5 ± 2.2 77.3 ± 0.3 0.94 
Visit of prediagnosis
P
A/A or A/GG/G
BMI (kg/m233.5 ± 1.1 31.5 ± 0.6 0.12 
Waist-to-Hip ratio 0.954 ± 0.012 0.941 ± 0.006 0.34 
Waist circumference (cm) 109.4 ± 2.8 105.2 ± 1.4 0.17 
Fasting glucose (mmol/l)* 6.22 ± 0.09 6.04 ± 0.05 0.09 
Ln(fasting insulin) (pmol/l) 4.90 ± 0.15 4.58 ± 0.07 0.09 
HDL cholesterol (mmol/l)* 1.37 ± 0.07 1.33 ± 0.04 0.64 
LDL cholesterol (mmol/l)* 3.61 ± 0.17 3.41 ± 0.09 0.31 
Ln(triglycerides) (mmol/l)* 0.23 ± 0.08 0.20 ± 0.04 0.69 
Systolic blood pressure (mmHg) 126.9 ± 3.5 128.6 ± 1.8 0.67 
Diastolic blood pressure (mmHg) 77.5 ± 2.2 77.3 ± 0.3 0.94 

Data are means ± SE. All analyses adjusted for age at V1 and sex.

*

Analysis limited to 151 individuals who had fasted for at least 8 h;

analysis limited to 83 individuals who had fasted for at least 8 h and for whom insulin data was available.

This research was supported by National Institutes of Health (NIH) Grant 1R01DK53959-01. F.L.B. was supported by an Established Investigator grant from the American Heart Association, Dallas, TX; W.H.L.K. was supported by NIH Training Grant T32HL077024-23; A.R.S. is supported by NIH K24 Grant DK02673-01A1; and C.L.H. was supported by NIH grant DK47487.

The ARIC Study is carried out as a collaborative study supported by contracts N01-HC-55015, N01-HC-555016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022 from the National Heart, Lung, and Blood Institute.

The authors thank the staff and participants in the ARIC Study for their important contributions and Demian G. Lewis for his assistance with SNP43 genotyping.

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Address correspondence and reprint requests to Alan R. Shuldiner, Department of Medicine, University of Maryland, 660 West Redwood St., Room 494, Baltimore, MD 21201. E-mail. ashuldin@medicine.umaryland.edu.

Received for publication 17 May 2001 and accepted in revised form 12 October 2001.

ARIC, Atherosclerosis Risk in Communities; OR, odds ratio; PAR, population attributable risk.