Living near a freeway is associated with lower bone mineral density among Mexican Americans.

UNLABELLED: We hypothesized that chronic exposures to traffic combustion products may lower bone mineral density (BMD). We found that proximity to freeways was associated with reduced BMD. Our findings suggest that traffic-related pollution may contribute to the occurrence of osteopenia and osteoporosis. INTRODUCTION: Adults residing in rural areas have been linked with higher BMD. We aimed to determine if this difference is due in part to air pollution by examining the relationships between traffic metrics and ambient air pollution with total body and pelvic BMD. METHODS: Mexican American adults (n = 1,175; mean 34 years; 72 % female) who had participated in the BetaGene study of air pollution, obesity, and insulin resistance were included in this analysis. Total body and pelvic BMD were estimated using dual-energy X-ray absorptiometry. Traffic and ambient air pollutant exposures were estimated at residences using location and ambient monitoring data. Variance component models were used to analyze the associations between residential distance to the nearest freeway and ambient air pollutants with BMD. RESULTS: Residential proximity to a freeway was associated with lower total body BMD (p-trend = 0.01) and pelvic BMD (p-trend = 0.03) after adjustment for age, sex, weight, and height. The adjusted mean total body and pelvic BMD in participants living within 500 m of a freeway were 0.02 and 0.03 g/cm(2) lower than participants living greater than 1,500 m from a freeway. These associations did not differ significantly by age, sex, or obesity status. Results were similar after further adjustment for body fat and weekly physical activity minutes. Ambient air pollutants (NO2, O3, and PM2.5) were not significantly associated with BMD. CONCLUSIONS: Traffic-related exposures in overweight and obese Mexican Americans may adversely affect BMD. Our findings indicate that long-term exposures to traffic may contribute to the occurrence of osteoporosis and its consequences.

HOMA and Matsuda indices of insulin sensitivity: poor correlation with minimal model-based estimates of insulin sensitivity in longitudinal settings.

AIMS/HYPOTHESIS: Little is known about the performance of surrogates in assessing changes in insulin sensitivity over time. This report compared updated HOMA of insulin sensitivity (HOMA2-%S) and the Matsuda index from OGTTs with minimal model-based estimates of insulin sensitivity (SI) from frequently sampled IVGTTs (FSIGTs) in longitudinal settings and cross-sectional settings. METHODS: Two longitudinal studies were used: one a natural observational study in which 338 individuals were followed for a median of 4 years; one a clinical treatment study in which 97 individuals received pioglitazone treatment and were followed for 1 year. Pairs of OGTTs and FSIGTs were performed at baseline and follow-up. Correlations were computed. Impact of measurement uncertainty was investigated through simulation studies. RESULTS: Correlations between HOMA2-%S and SI from baseline or follow-up data were in the range reported previously (0.61-0.69). By contrast, correlations for changes over time were only 0.35-0.39. The corresponding correlations between the Matsuda index and SI were 0.66-0.72 for cross-sectional data and 0.40-0.48 for longitudinal change. Correlations for changes were significantly lower than the cross-sectional correlations in both studies (p < 0.03). Simulation results demonstrated that the reduced correlations for change were not explained by error propagation, supporting a real limitation of surrogates to fully capture longitudinal changes in insulin sensitivity. CONCLUSIONS/INTERPRETATION: HOMA and Matsuda indices derived from cross-sectional data should be used cautiously in assessing longitudinal changes in insulin sensitivity.

Compensatory responses to insulin resistance in obese African-American and Latina girls.

PURPOSE: Insulin responses to oral and intravenous glucose markedly differ by ethnicity. This study examined whether ethnic differences in pancreatic insulin secretion, hepatic insulin extraction and clearance explain these disparate findings in 35 obese African-American and 41 Latina girls (Tanner Stages: IV-V; ages: 14-18; body mass index percentile: 85.9-99.8%). METHODS: Pancreatic insulin secretion, hepatic insulin extraction and clearance were estimated by C-peptide and insulin modeling during an oral glucose tolerance test. Insulin sensitivity (SI), acute insulin response to glucose (AIRG ) and disposition index were derived from a frequently sampled intravenous glucose tolerance test. RESULTS: Compared to Latinas, obese African-American adolescents had lower pancreatic insulin secretion (21.3%; P < 0.01), glucose incremental area under the curve (IAUC) (41.7%, P = 0.02), C-peptide IAUC (25.1%, P < 0.01) and SI (33.7%; P < 0.01). There were no ethnic differences in hepatic insulin extraction and clearance (P's > 0.05). CONCLUSIONS: Compensatory mechanisms to insulin resistance do not appear to explain the ethnic differences in insulin responses to oral and intravenous glucose in obese African-American and Latina girls.

Variation in the resistin gene is associated with obesity and insulin-related phenotypes in Finnish subjects.

AIMS/HYPOTHESIS: Resistin is a peptide hormone produced by adipocytes that is present at high levels in sera of obese mice and may be involved in glucose homeostasis through regulation of insulin sensitivity. Several studies in humans have found associations between polymorphisms in the resistin gene and obesity, insulin sensitivity and blood pressure. An association between variation in the resistin gene and type 2 diabetes has been reported in some, but not all studies. The aim of this study was to analyse variants of the resistin gene for association with type 2 diabetes and related traits in a Finnish sample. METHODS: In 781 cases with type 2 diabetes, 187 spouse controls and 222 elderly controls of Finnish origin, we genotyped four previously identified non-coding single-nucleotide polymorphisms (SNPs): -420C>G from the promoter region, +156C>T and +298G>A from intron 2, and +1084G>A from the 3' untranslated region. We then tested whether these SNPs were associated with type 2 diabetes and related traits. RESULTS: The SNPs were not significantly associated with type 2 diabetes. However, SNPs -420C>G, +156C>T and +298G>A and the common haplotype for these three markers were associated with increased values of weight-related traits and diastolic blood pressure in cases, lower weight in elderly control subjects, and lower insulin sensitivity and greater acute insulin response in spouses. Furthermore, the +1084G allele was associated with lower HDL cholesterol in both cases and controls, higher systolic blood pressure and waist circumference in cases, and greater acute insulin response in spouse controls. CONCLUSIONS/INTERPRETATION: Our results add to growing evidence that resistin is associated with variation in weight, fat distribution and insulin resistance.

The multiphasic profile of free fatty acids during the intravenous glucose tolerance test is unresponsive to exogenous insulin.

As small increments in insulin concentration profoundly affect lipolysis, our goal was to describe the free fatty acid (FFA) profile during the frequently sampled intravenous glucose tolerance test (FSIGT) and determine if both endogenous and exogenous insulin influenced the FFA profile. Thirteen subjects had both a glucose-only (GO-FSIGT) and insulin-modified FSIGT (IM-FSIGT). Both protocols were of 6 hours duration. At baseline an intravenous glucose bolus (0.3 g/kg) was given. In the IM-FSIGT, insulin was infused from 20 to 25 minutes (4 mU/kg. min). Six additional subjects had both an IM-FSIGT and a normal saline study (NS-Study). For the NS-Study, normal saline solution was infused instead of glucose and insulin. Fasting glucose, insulin, FFA and epinephrine concentrations were similar for all tests. Endogenous insulin peaked at 4 +/- 1 minute in both FSIGTs. The mean calculated peak time of exogenous insulin in the IM-FSIGT was 26 +/- 1 minute. Glucose concentrations were lower and epinephrine concentrations higher in the IM-FSIGT versus GO-FSIGT. During the FSIGTs, the FFA time course revealed four distinct phases, which did not differ between protocols. In phase I (0 to 11 minutes), FFA levels remained near basal (491 +/- 183 micromol/L); in phase II (11 to 79 minutes), FFA levels declined achieving a nadir of 139 +/- 63 micromol/L; in phase III (79 to 188 minutes), FFA levels rose linearly and reattained basal levels; and in phase IV (188 to 360 minutes), FFA levels rose above basal and plateaued at 732 +/- 214 micromol/L (P <.001). In the NS-Study, FFA levels remained near baseline (388 +/- 118 mEq/L) until 180 minutes and then trended upward to 618 +/- 258 micromol/L at 360 minutes. FFA concentrations from 180 to 360 minutes did not differ in the IM-FSIGT versus NS-Study. As the 4 FFA phases did not differ between protocols, the insulin effect on FFA levels in the FSIGT can be attributed to endogenous insulin. But the similarity in FFA levels from 180 to 360 minutes in the IM-FSIGT and NS-Study suggests diurnal variation and not a dynamic related to insulin or the FSIGT protocol is responsible for the final suprabasal FFA plateau.

Linkage disequilibrium between microsatellite markers extends beyond 1 cM on chromosome 20 in Finns.

Linkage disequilibrium (LD) is a proven tool for evaluating population structure and localizing genes for monogenic disorders. LD-based methods may also help localize genes for complex traits. We evaluated marker-marker LD using 43 microsatellite markers spanning chromosome 20 with an average density of 2.3 cM. We studied 837 individuals affected with type 2 diabetes and 386 mostly unaffected spouse controls. A test of homogeneity between the affected individuals and their spouses showed no difference, allowing the 1223 individuals to be analyzed together. Significant (P < 0.01) LD was observed using a likelihood ratio test in all (11/11) marker pairs within 1 cM, 78% (25/32) of pairs 1-3 cM apart, and 39% (7/18) of pairs 3-4 cM apart, but for only 12 of 842 pairs more than 4 cM apart. We used the human genome project working draft sequence to estimate kilobase (kb) intermarker distances, and observed highly significant LD (P < 10(-10)) for all six marker pairs up to 350 kb apart, although the correlation of LD with cM is slightly better than the correlation with megabases. These data suggest that microsatellites present at 1-cM density are sufficient to observe marker-marker LD in the Finnish population.

The peroxisome proliferator-activated receptor-gamma2 Pro12A1a variant: association with type 2 diabetes and trait differences.

Recent studies have identified a common proline-to-alanine substitution (Pro12Ala) in the peroxisome proliferator-activated receptor-gamma2 (PPAR-gamma2), a nuclear receptor that regulates adipocyte differentiation and possibly insulin sensitivity. The Pro12Ala variant has been associated in some studies with diabetes-related traits and/or protection against type 2 diabetes. We examined this variant in 935 Finnish subjects, including 522 subjects with type 2 diabetes, 193 nondiabetic spouses, and 220 elderly nondiabetic control subjects. The frequency of the Pro12Ala variant was significantly lower in diabetic subjects than in nondiabetic subjects (0.15 vs. 0.21; P = 0.001). We also compared diabetes-related traits between subjects with and without the Pro12Ala variant within subgroups. Among diabetic subjects, the variant was associated with greater weight gain after age 20 years (P = 0.023) and lower triglyceride levels (P = 0.033). Diastolic blood pressure was higher in grossly obese (BMI >40 kg/m2) diabetic subjects with the variant. In nondiabetic spouses, the variant was associated with higher fasting insulin (P = 0.033), systolic blood pressure (P = 0.021), and diastolic blood pressure (P = 0.045). These findings support a role for the PPAR-gamma2 Pro12Ala variant in the etiology of type 2 diabetes and the insulin resistance syndrome.

The Finland-United States investigation of non-insulin-dependent diabetes mellitus genetics (FUSION) study. I. An autosomal genome scan for genes that predispose to type 2 diabetes.

We performed a genome scan at an average resolution of 8 cM in 719 Finnish sib pairs with type 2 diabetes. Our strongest results are for chromosome 20, where we observe a weighted maximum LOD score (MLS) of 2.15 at map position 69.5 cM from pter and secondary weighted LOD-score peaks of 2.04 at 56.5 cM and 1.99 at 17.5 cM. Our next largest MLS is for chromosome 11 (MLS = 1.75 at 84.0 cM), followed by chromosomes 2 (MLS = 0.87 at 5.5 cM), 10 (MLS = 0.77 at 75.0 cM), and 6 (MLS = 0.61 at 112.5 cM), all under an additive model. When we condition on chromosome 2 at 8.5 cM, the MLS for chromosome 20 increases to 5.50 at 69.0 cM (P=.0014). An ordered-subsets analysis based on families with high or low diabetes-related quantitative traits yielded results that support the possible existence of disease-predisposing genes on chromosomes 6 and 10. Genomewide linkage-disequilibrium analysis using microsatellite marker data revealed strong evidence of association for D22S423 (P=.00007). Further analyses are being carried out to confirm and to refine the location of these putative diabetes-predisposing genes.

The Finland-United States investigation of non-insulin-dependent diabetes mellitus genetics (FUSION) study. II. An autosomal genome scan for diabetes-related quantitative-trait loci.

Type 2 diabetes mellitus is a complex disorder encompassing multiple metabolic defects. We report results from an autosomal genome scan for type 2 diabetes-related quantitative traits in 580 Finnish families ascertained for an affected sibling pair and analyzed by the variance components-based quantitative-trait locus (QTL) linkage approach. We analyzed diabetic and nondiabetic subjects separately, because of the possible impact of disease on the traits of interest. In diabetic individuals, our strongest results were observed on chromosomes 3 (fasting C-peptide/glucose: maximum LOD score [MLS] = 3.13 at 53.0 cM) and 13 (body-mass index: MLS = 3.28 at 5.0 cM). In nondiabetic individuals, the strongest results were observed on chromosomes 10 (acute insulin response: MLS = 3.11 at 21.0 cM), 13 (2-h insulin: MLS = 2.86 at 65.5 cM), and 17 (fasting insulin/glucose ratio: MLS = 3.20 at 9.0 cM). In several cases, there was evidence for overlapping signals between diabetic and nondiabetic individuals; therefore we performed joint analyses. In these joint analyses, we observed strong signals for chromosomes 3 (body-mass index: MLS = 3.43 at 59.5 cM), 17 (empirical insulin-resistance index: MLS = 3.61 at 0.0 cM), and 19 (empirical insulin-resistance index: MLS = 2.80 at 74.5 cM). Integrating genome-scan results from the companion article by Ghosh et al., we identify several regions that may harbor susceptibility genes for type 2 diabetes in the Finnish population.

Accurate measurement of endogenous insulin secretion does not require separate assessment of C-peptide kinetics.

The implication of beta-cell failure as an early defect in type 2 diabetes exacerbates the need for accurate but facile assessment of islet cell secretory rate, particularly in large group studies in which individual assessment of C-peptide kinetics is impractical. This study was designed to examine whether it is possible to obtain accurate secretory rates from the extended combined model, which provides insulin and C-peptide kinetics from plasma measurements of the two peptides. Equimolar intraportal infusions of insulin and C-peptide that are designed to simulate insulin secretion rates during both oral and intravenous glucose tolerance tests were used to generate plasma insulin and C-peptide data in conscious dogs that were examined under clamped glucose conditions. The plasma peptide kinetics were analyzed using the extended combined model to generate estimates of prehepatic insulin secretion that were then compared with the known intraportal infusion rates. The extended combined model was able to reproduce the known intraportal infusion profiles. The model-predicted rates were similar to those calculated with methods that require separate assessment of C-peptide kinetics. Simulation results supported lesser clearance of insulin during rapid changes of portal insulin (as measured by an intravenous glucose tolerance test) versus slow changes in portal insulin (as measured by an oral glucose tolerance test). The extended combined model accurately calculates prehepatic insulin appearance. It may be possible to apply this approach to large studies of beta-cell function designed to identify changes in islet function in subjects at risk for diabetes. Such an approach could strengthen epidemiological and genetic studies of the pathogenesis of diabetes.

The effect of phenotype variation on detection of linkage in the COGA data.

Error in phenotypic measurement can significantly compromise ability to detect linkage. We assessed the impact of introducing phenotypic measurement error on our ability to detect a quantitative trait locus in the Collaborative Study on the Genetics of Alcoholism (COGA) data. The impact of introducing three different types of errors was evaluated: 1) errors generated by sampling from a normal distribution; 2) errors generated by permuting phenotype values between subjects; and 3) errors generated by sampling from a uniform error distribution.

Identifying influential individuals in linkage analysis: application to a quantitative trait locus detected in the COGA data.

Once linkage is detected to a quantitative trait locus (QTL), the next step towards localizing the gene involved may be to identify those families, or individuals, in whom the putative mutations are segregating. In this paper, we describe a jackknife procedure for identifying individuals (and families) who contribute disproportionately to the linkage. Following initial detection of linkage to a QTL, the strategy involves sequentially removing each individual (or each family) from the analysis and recomputing the lod score associated with the linked region using data from all remaining subjects (or families). This procedure can be used to determine if particular observations have substantial impact on evidence for linkage. Identification of such observations may provide insights for further efforts to localize the QTL.

Application of an ordered subset analysis approach to the genetics of alcoholism.

For complex diseases, underlying etiologic heterogeneity may reduce power to detect linkage. Thus, methods to identify more homogeneous subgroups within a given sample in a linkage study may improve detection of putative susceptibility loci. In this study we describe an ordered subsetting approach that utilizes disease-related quantitative trait data to complement traditional linkage analysis. This approach uses family-based lod scores derived from the initial genome screen and a family-based descriptor of the trait of interest. The goal of the approach is to identify more homogeneous subgroups of the data by ranking families based on their quantitative trait data. Permutation testing is used to assess statistical significance. This approach can be adapted to a variety of linkage methods and may provide a means to dissect some of the underlying heterogeneity in complex disease genetics.

Familiality of quantitative metabolic traits in Finnish families with non-insulin-dependent diabetes mellitus. Finland-United States Investigation of NIDDM Genetics (FUSION) Study investigators.

Type 2 diabetes mellitus (NIDDM) is a complex disorder encompassing multiple metabolic defects. There exists strong evidence for a genetic component to NIDDM; however, to date there have been few reports of linkage between genetic markers along the genome and NIDDM or NIDDM-related quantitative traits. We sought to determine whether individual quantitative traits which determine glucose tolerance exhibit familiality in Finnish families with at least one NIDDM-affected sibling pair. Tolbutamide-modified frequently sampled intravenous glucose tolerance tests (FSIGT) were performed on unaffected offspring (n = 431) and spouses (n = 154) of affected sibling pairs sampled for the Finland-United States Investigation of NIDDM Genetics (FUSION) study. FSIGT data were analyzed using the Minimal Model to obtain quantitative measures of insulin sensitivity (SI), glucose effectiveness (SG), and insulin secretion assessed as the acute insulin response to glucose (AIR). The disposition index (DI), a measure of insulin resistance-corrected beta-cell function, was also derived as the product of SI and AIR. Variance components analysis was used to determine for each trait, the heritability (h2), the proportion of the total trait variance accounted for by additive genes. After adjustment for age, gender, and body mass index, h2 estimates were: SG: 18 +/- 9%, SI: 28 +/- 8%, AIR: 35 +/- 8%, and DI: 23 +/- 8%. We conclude that there is strong evidence for modest heritability of Minimal-Model-derived NIDDM-related quantitative traits in unaffected spouses and offspring of Finnish affected sibling pairs.

The W64R variant of the beta3-adrenergic receptor is not associated with type II diabetes or obesity in a large Finnish sample.

Recent studies have suggested an association between Type II (non-insulin-dependent) diabetes mellitus-related phenotypes and a cytosine-to-thymidine substitution that results in the replacement of tryptophan by arginine at codon 64 (Trp64Arg or W64R) of the beta3-adrenergic receptor gene. Here, we present the results of possibly the largest association study to date on the variant in a sample of 526 families with a total of 1725 subjects, 1053 of whom had Type II diabetes. Preliminary calculations suggested that we had excellent power to detect the moderate associations which were reported in previous studies. No associations were found between the W64R variant and the following phenotypes in our sample: Type II diabetes, age at diagnosis for Type II diabetes, measures of obesity, fasting glucose, fasting insulin, minimal model variables, and systolic and diastolic blood pressures. In the analysis of plasma lipids, we detected an association between the variant and HDL ratios (HDL cholesterol/total cholesterol) (p = 0.013), which remained significant even after adjusting for sex, affection status and age. Since W64R homozygotes (n = 11) had the highest HDL ratios, however, heterozygotes had the lowest and the wild-type subjects had intermediate values, we conclude that the W64R variant is unlikely to reduce HDL ratios in a dose-dependent, pathogenic manner.

Type 2 diabetes: evidence for linkage on chromosome 20 in 716 Finnish affected sib pairs.

We are conducting a genome scan at an average resolution of 10 centimorgans (cM) for type 2 diabetes susceptibility genes in 716 affected sib pairs from 477 Finnish families. To date, our best evidence for linkage is on chromosome 20 with potentially separable peaks located on both the long and short arms. The unweighted multipoint maximum logarithm of odds score (MLS) was 3.08 on 20p (location, chi = 19.5 cM) under an additive model, whereas the weighted MLS was 2.06 on 20q (chi = 57 cM, recurrence risk,lambda(s) = 1. 25, P = 0.009). Weighted logarithm of odds scores of 2.00 (chi = 69.5 cM, P = 0.010) and 1.92 (chi = 18.5 cM, P = 0.013) were also observed. Ordered subset analyses based on sibships with extreme mean values of diabetes-related quantitative traits yielded sets of families who contributed disproportionately to the peaks. Two-hour glucose levels in offspring of diabetic individuals gave a MLS of 2. 12 (P = 0.0018) at 9.5 cM. Evidence from this and other studies suggests at least two diabetes-susceptibility genes on chromosome 20. We have also screened the gene for maturity-onset diabetes of the young 1, hepatic nuclear factor 4-a (HNF-4alpha) in 64 affected sibships with evidence for high chromosomal sharing at its location on chromosome 20q. We found no evidence that sequence changes in this gene accounted for the linkage results we observed.

A large sample of finnish diabetic sib-pairs reveals no evidence for a non-insulin-dependent diabetes mellitus susceptibility locus at 2qter.

In the first reported positive result from a genome scan for non-insulin-dependent diabetes mellitus (NIDDM), Hanis et al. found significant evidence of linkage for NIDDM on chromosome 2q37 and named the putative disease locus NIDDM1 (Hanis et al. 1996. Nat. Genet. 13:161-166). Their total sample was comprised of 440 Mexican-American affected sib-pairs from 246 sibships. The strongest evidence for linkage was at marker D2S125 and best estimates of lambdas (risk to siblings of probands/population prevalence) using this marker were 1.37 under an additive model and 1.36 under a multiplicative model. We examined this chromosomal region using linkage analysis in a Finnish sample comprised of 709 affected sib-pairs from 472 sibships. We excluded this region in our sample (multipoint logarithm of odds score /= 1.37. We discuss possible reasons why linkage to 2q37 was not found and conclude that this region is unlikely to be playing a major role in NIDDM susceptibility in the Finnish Caucasian population.

Mapping genes for NIDDM. Design of the Finland-United States Investigation of NIDDM Genetics (FUSION) Study.

OBJECTIVE: To map and identify susceptibility genes for NIDDM and for the intermediate quantitative traits associated with NIDDM. RESEARCH DESIGN AND METHODS: We describe the methodology and sample of the Finland-United States Investigation of NIDDM Genetics (FUSION) study. The whole genome search approach is being applied in studies of several different ethnic groups to locate susceptibility genes for NIDDM. Detailed description of the study materials and designs of such studies are important, particularly when comparing the findings in these studies and when combining different data sets. RESULTS: Using a careful selection strategy, we have ascertained 495 families with confirmed NIDDM in at least two siblings and no history of IDDM among the first-degree relatives. These families were chosen from more than 22,000 NIDDM patients, representative of patients with NIDDM in the Finnish population. In a subset of families, a spouse and offspring were sampled, and they participated in a frequently sampled intravenous glucose tolerance test (FSIGT) analyzed with the Minimal Model. An FSIGT was completed successfully for at least two nondiabetic offspring in 156 families with a confirmed nondiabetic spouse and no history of IDDM in first-degree relatives. CONCLUSIONS: Our work demonstrates the feasibility of collecting a large number of affected sib-pair families with NIDDM to provide data that will enable a whole genome search approach, including linkage analysis.

Critical evaluation of the combined model approach for estimation of prehepatic insulin secretion.

The combined model approach uses kinetic analysis of both plasma insulin and C-peptide dynamics to estimate prehepatic insulin secretion rates and parameters of insulin and C-peptide kinetics. The original model used single-compartment kinetics to describe both insulin and C-peptide despite knowledge that C-peptide follows two-compartment kinetics. The performance of the model under rapidly changing secretory conditions has come into question. Thus a more complex combined model is introduced, incorporating two-compartmental C-peptide disappearance. The addition of two-compartment C-peptide kinetics required a novel numerical approach to allow estimation of model parameters. This simulation study was undertaken to 1) compare the performance of the original combined model and 2) examine the numerical method used to identify parameters for the extended combined model with two-compartment C-peptide kinetics under simulated conditions of rapidly changing insulin and C-peptide. Monte Carlo simulation revealed that the original combined model does not provide accurate estimates of prehepatic insulin secretion under rapid kinetics. However, the extended combined model provides accurate reconstruction of prehepatic insulin secretory profile without separate quantification of C-peptide kinetics.