Evidence for linkage of regions on chromosomes 6 and 11 to plasma glucose concentrations in Mexican Americans

Diabetic macular oedema: under-represented in the genetic analysis of diabetic retinopathy

Diabetic retinopathy, a complication of both type 1 and type 2 diabetes, is a complex disease and is one of the leading causes of blindness in adults worldwide. It can be divided into distinct subclasses, one of which is diabetic macular oedema. Diabetic macular oedema can occur at any time in diabetic retinopathy and is the most common cause of vision loss in patients with type 2 diabetes. The purpose of this review is to summarize the large number of genetic association studies that have been performed in cohorts of patients with type 2 diabetes and published in English-language journals up to February 2017. Many of these studies have produced positive associations with gene polymorphisms and diabetic retinopathy. However, this review highlights that within this large body of work, studies specifically addressing a genetic association with diabetic macular oedema, although present, are vastly under-represented. We also highlight that many of the studies have small patient numbers and that meta-analyses often inappropriately combine patient data sets. We conclude that there will continue to be conflicting results and no meaningful findings will be achieved if the historical approach of combining all diabetic retinopathy disease states within patient cohorts continues in future studies. This review also identifies several genes that would be interesting to analyse in large, well-defined cohorts of patients with diabetic macular oedema in future candidate gene association studies.

Linear mixed model for heritability estimation that explicitly addresses environmental variation

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.

Linkage of type 2 diabetes on chromosome 9p24 in Mexican Americans: additional evidence from the Veterans Administration Genetic Epidemiology Study (VAGES)

OBJECTIVE

Type 2 diabetes (T2DM) is a complex metabolic disease and is more prevalent in certain ethnic groups such as the Mexican Americans. The goal of our study was to perform a genome-wide linkage (GWL) analysis to localize T2DM susceptibility loci in Mexican Americans.

METHODS

We used the phenotypic and genotypic data from 1,122 Mexican-American individuals (307 families) who participated in the Veterans Administration Genetic Epidemiology Study (VAGES). GWL analysis was performed using the variance components approach. Data from 2 additional Mexican-American family studies, the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), were combined with the VAGES data to test for improved linkage evidence.

RESULTS

After adjusting for covariate effects, T2DM was found to be under significant genetic influences (h2 = 0.62, p = 2.7 × 10(-6)). The strongest evidence for linkage of T2DM occurred between markers D9S1871 and D9S2169 on chromosome 9p24.2-p24.1 (LOD = 1.8). Given that we previously reported suggestive evidence for linkage of T2DM at this region also in SAFDGS, we found the significant and increased linkage evidence (LOD = 4.3, empirical p = 1.0 × 10(-5), genome-wide p = 1.6 × 10(-3)) for T2DM at the same chromosomal region, when we performed a GWL analysis of the VAGES data combined with the SAFHS and SAFDGS data.

CONCLUSION

Significant T2DM linkage evidence was found on chromosome 9p24 in Mexican Americans. Importantly, the chromosomal region of interest in this study overlaps with several recent genome-wide association studies involving T2DM-related traits. Given its overlap with such findings and our own initial T2DM association findings in the 9p24 chromosomal region, high throughput sequencing of the linked chromosomal region could identify the potential causal T2DM genes.

Association of genes on chromosome 6, GRIK2 , TMEM217 and TMEM63B (linked to MRPL14 ) with diabetic retinopathy

PURPOSE

Diabetic retinopathy (DR) is one of the most common complications of diabetes mellitus (DM). The susceptibility genes responsible for increasing the risk for DR in type 2 diabetes (T2D) were sought in this study.

METHODS

A case-control study was carried out, comprising 749 unrelated T2D individuals with (n = 174) and without (n = 575) DR. Genotypic distributions of single nucleotide polymorphisms (SNPs) were determined for subjects with and without DR.

RESULTS

Eight chromosome 6 SNPs, having the most significant differences, were delineated: rs10499298, rs10499299, rs17827966, rs1224329, rs1150790, rs713050, rs2518344 and rs487083; all were associated with genes TMEM217, MRPL14 and GRIK2. After adjusting for the duration of DM and levels of hemoglobin A(1c), the TT genotype of rs713050, and the AG + AA genotypes of rs2518344 and rs10499298, differed significantly between those with and without DR. Haplotype analysis revealed haplotype C-A-C, residing in rs10499299, rs10499298 and rs17827966, to have significant linkage disequilibrium.

CONCLUSIONS

We identified new loci on chromosome 6 associated to DR; all loci showed high levels of linkage disequilibrium.

How to deal with genotype uncertainty in variance component quantitative trait loci analyses

Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation-Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

The characterization of Abelson helper integration site-1 in skeletal muscle and its links to the metabolic syndrome

The human Abelson helper integration site-1 (AHI1) gene is associated with both neurologic and hematologic disorders; however, it is also located in a chromosomal region linked to metabolic syndrome phenotypes and was identified as a type 2 diabetes mellitus susceptibility gene from a genomewide association study. To further define a possible role in type 2 diabetes mellitus development, AHI1 messenger RNA expression levels were investigated in a range of tissues and found to be highly expressed in skeletal muscle as well as displaying elevated levels in brain regions and gonad tissues. Further analysis in a rodent polygenic animal model of obesity and type 2 diabetes mellitus identified increased Ahi-1 messenger RNA levels in red gastrocnemius muscle from fasted impaired glucose-tolerant and diabetic rodents compared with healthy animals (P < .002). Moreover, elevated gene expression levels were confirmed in skeletal muscle from fasted obese and type 2 diabetes mellitus human subjects (P < .02). RNAi-mediated suppression of Ahi-1 resulted in increased glucose transport in rat L6 myotubes in both the basal and insulin-stimulated states (P < .01). Finally, single nucleotide polymorphism association studies identified 2 novel AHI1 genetic variants linked with fasting blood glucose levels in Mexican American subjects (P < .037). These findings indicate a novel role for AHI1 in skeletal muscle and identify additional genetic links with metabolic syndrome phenotypes suggesting an involvement of AHI1 in the maintenance of glucose homeostasis and type 2 diabetes mellitus progression.

Assessing a multiple QTL search using the variance component model

Development of variance component algorithms in genetics has previously mainly focused on animal breeding models or problems in human genetics with a simple data structure. We study alternative methods for constrained likelihood maximization in quantitative trait loci (QTL) analysis for large complex pedigrees. We apply a forward selection scheme to include several QTL and interaction effects, as well as polygenic effects, with up to five variance components in the model. We show that the implemented active set and primal-dual schemes result in accurate solutions and that they are robust. In terms of computational speed, a comparison of two approaches for approximating the Hessian of the log-likelihood shows that the method using an average information matrix is the method of choice for the five-dimensional problem. The active set method, with the average information method for Hessian computation, exhibits the fastest convergence with an average of 20 iterations per tested position, where the change in variance components <0.0001 was used as convergence criterion.

Genome-wide linkage scans for type 2 diabetes mellitus in four ethnically diverse populations-significant evidence for linkage on chromosome 4q in African Americans: the Family Investigation of Nephropathy and Diabetes Research Group

BACKGROUND

Previous studies have shown that in addition to environmental influences, type 2 diabetes mellitus (T2DM) has a strong genetic component. The goal of the current study is to identify regions of linkage for T2DM in ethnically diverse populations.

METHODS

Phenotypic and genotypic data were obtained from African American (AA; total number of individuals [N] = 1004), American Indian (AI; N = 883), European American (EA; N = 537), and Mexican American (MA; N = 1634) individuals from the Family Investigation of Nephropathy and Diabetes. Non-parametric linkage analysis, using an average of 4404 SNPs, was performed in relative pairs affected with T2DM in each ethnic group. In addition, family-based tests were performed to detect association with T2DM.

RESULTS

Statistically significant evidence for linkage was observed on chromosome 4q21.1 (LOD = 3.13; genome-wide p = 0.04) in AA. In addition, a total of 11 regions showed suggestive evidence for linkage (estimated at LOD > 1.71), with the highest LOD scores on chromosomes 12q21.31 (LOD = 2.02) and 22q12.3 (LOD = 2.38) in AA, 2p11.1 (LOD = 2.23) in AI, 6p12.3 (LOD = 2.77) in EA, and 13q21.1 (LOD = . 2.24) in MA. While no region overlapped across all ethnic groups, at least five loci showing LOD > 1.71 have been identified in previously published studies.

CONCLUSIONS

The results from this study provide evidence for the presence of genes affecting T2DM on chromosomes 4q, 12q, and 22q in AA; 6p in EA; 2p in AI; and 13q in MA. The strong evidence for linkage on chromosome 4q in AA provides important information given the paucity of diabetes genetic studies in this population.

Association of genetic variation in ENPP1 with obesity-related phenotypes

Ectonucleotide pyrophosphatase phosphodiesterase (ENPP1) is a positional candidate gene at chromosome 6q23 where we previously detected strong linkage with fasting-specific plasma insulin and obesity in Mexican Americans from the San Antonio Family Diabetes Study (SAFDS). We genotyped 106 single-nucleotide polymorphisms (SNPs) within ENPP1 in all 439 subjects from the linkage study, and measured association with obesity and metabolic syndrome (MS)-related traits. Of 72 polymorphic SNPs, 24 were associated, using an additive model, with at least one of eight key metabolic traits. Three traits were associated with at least four SNPs. They were high-density lipoprotein cholesterol (HDL-C), leptin, and fasting plasma glucose (FPG). HDL-C was associated with seven SNPs, of which the two most significant P values were 0.0068 and 0.0096. All SNPs and SNP combinations were analyzed for functional contribution to the traits using the Bayesian quantitative-trait nucleotide (BQTN) approach. With this SNP-prioritization analysis, HDL-C was the most strongly associated trait in a four-SNP model (P=0.00008). After accounting for multiple testing, we conclude that ENPP1 is not a major contributor to our previous linkage peak with MS-related traits in Mexican Americans. However, these results indicate that ENPP1 is a genetic determinant of these traits in this population, and are consistent with multiple positive association findings in independent studies in diverse human populations.

Defining the assumptions underlying modeling of epistatic QTL using variance component methods

Variance component models are commonly used to detect quantitative trait loci (QTL) in general pedigrees. The variance-covariance structure of the random QTL effect is given by the identity by descent (IBD) between genotypes. Epistatic effects have previously been modeled, both for unlinked and linked loci, as a random effect with a variance-covariance structure given by the Hadamard product between the IBD matrices of the direct QTL effects. In the original papers, the model was given but not derived. Here, we identify the underlying assumptions of this previously proposed model. It assumes that either an unlinked QTL or a fully informative marker (i.e., all marker alleles are unique in the base generation) is located between the loci. We discuss the need of developing a general algorithm to estimate the variance-covariance structure of the random epistatic effect for linked loci.

Impact of the sulfonylurea receptor 1 (SUR1) exon 16-3c/t polymorphism on acute hyperglycaemia in type 2 diabetic patients

Epidemiological data collected over the last few decades have demonstrated the significant role of acute (especially postprandial) hyperglycaemia in the development of macrovascular complications in patients with type 2 diabetes. However, the influence of SUR1 exon 16-3c/t polymorphism on impaired insulin secretion during acute hyperglycaemic episodes has not yet been evaluated. We studied 40 type 2 diabetic patients. Single nucleotide polymorphism in the sulfonylurea receptor gene was examined by means of PCR-RLFP. In every patient, fasting insulin, proinsulin, C-peptide and 1,5-anhydro-d-glucitol concentrations were assayed as markers of insulin secretion, peripheral resistance to insulin, and acute hyperglycaemia. The distribution of SUR1 exon 16-3c/t polymorphism was tt 35%, tc -40%, and cc -25%. By means of analysis of covariance, it was revealed that 1,5-anhydro-d-glucitol plasma levels are associated with SUR1 exon 16-3c/t polymorphism. However, the HOMA(IR) score influenced 1,5-anhydro-d-glucitol levels in plasma at a higher level of statistical power than the genetic variant. Our results suggest that SUR1 exon 16-3c/t polymorphism is only a partial determinant of acute hyperglycaemia-cardiovascular risk factor in type 2 diabetes.

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Background

Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix).

Results

We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote.

Conclusion

We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods.

Subsets of Finns with high HDL to total cholesterol ratio show evidence for linkage to type 2 diabetes on chromosome 6q

OBJECTIVES

The purpose of this study was to examine carefully heterogeneity underlying evidence for linkage to type 2 diabetes (T2DM) on chromosome 6q from two sets of FUSION families.

METHODS

Ordered subsets analysis (OSA) was performed on two sets of FUSION families. For OSA results showing significant improvement in evidence for linkage, T2DM-related phenotypes were compared between individuals with T2DM within the subset versus the complement.

RESULTS

OSA analysis revealed 105 families with the highest average HDL to total cholesterol ratio (HDL ratio) that had strongly increased evidence for linkage (MLS = 7.91 at 78.0 cM; uncorrected p = 0.00002). Subjects with T2DM within this subset were significantly leaner, had lower fasting glucose, insulin, and C-peptide, and more favorable cardiovascular risk profile compared to the complement set of subjects with T2DM. OSA also revealed 33 families with the lowest average fasting insulin that had increased evidence for linkage at a second locus (MLS = 3.45 at 128 cM; uncorrected p = 0.017) coincident with quantitative trait locus linkage analysis results for fasting and 2-hour insulin in subjects without T2DM.

CONCLUSIONS

These results suggest two diabetes susceptibility loci on chromosome 6q that may affect subsets of individuals with a milder form of T2DM.

A novel missense mutation in ADRB3 increases risk for type 2 diabetes in a Mexican American family

BACKGROUND

The human beta3-adrenergic receptor gene (ADRB3) has been investigated as a candidate gene for diabetes-related traits in many studies. However, the results have been inconsistent so it is unclear whether variation in ADRB3 is a risk factor for type 2 diabetes. We have identified a novel missense mutation of ADRB3 in a single large pedigree of the San Antonio Family Diabetes/Gallbladder Study (SAFDGS) that is located in the first transmembrane domain at amino acid 62 (Ile62Met). The aim of this study was to investigate the association of this mutation in the SAFDGS with risk for diabetes.

METHODS

Variance components-based statistical methods were used to determine association of this mutation with diabetes traits in the SAFDGS. The ADRB3 gene was also resequenced to identify all variants present in this pedigree.

RESULTS

Significant association was observed for the Ile62Met mutation and type 2 diabetes (p = 0.01, relative risk 2.3), an earlier age of onset (p = 0.01) and 2-h glucose measures (p = 0.006) in the single pedigree. Average age and body mass index do not differ between the two genotypic groups. In a recent genome-wide linkage analysis of SAFDGS, we observed suggestive linkage of diabetes to this region at marker D8S1477 (2pt LOD of 2.55). The variance attributed to Ile62Met accounted for nearly all of the family-specific LOD score.

CONCLUSIONS

These results suggest that this variant in ADRB3 is influencing diabetes risk in this Mexican American family and supports a role for alterations of the beta3-adrenergic receptor in the pathogenesis of type 2 diabetes.

Phenotypical Characterisation of the Isolated Norfolk Island Population Focusing on Epidemiological Indicators of Cardiovascular Disease

OBJECTIVES

Only 193 people from Pitcairn Island, all descended from 9 'Bounty' mutineers and 12 Tahitian women, moved to the uninhabited Norfolk Island in 1856. Our objective was to assess the population of Norfolk Island, several thousand km off the eastern coast of Australia, as a genetic isolate of potential use for cardiovascular disease (CVD) gene mapping.

METHODS

A total of 602 participants, approximately two thirds of the island's present adult population, were characterized for a panel of CVD risk factors. Statistical power and heritability were calculated.

RESULTS

Norfolk Islander's possess an increased prevalence of hypertension, obesity and multiple CVD risk factors when compared to outbred Caucasian populations. 64% of the study participants were descendents of the island's original founder population. Triglycerides, cholesterol, and blood pressures all had heritabilities above 0.2.

CONCLUSIONS

The Norfolk Island population is a potentially useful genetic isolate for gene mapping studies aimed at identifying CVD risk factor quantitative trait loci (QTL).

Genome-wide linkage analyses of type 2 diabetes in Mexican Americans: the San Antonio Family Diabetes/Gallbladder Study

The San Antonio Family Diabetes/Gallbladder Study was initiated to identify susceptibility genes for type 2 diabetes. Evidence was previously reported of linkage to diabetes on 10q with suggestive evidence on 3p and 9p in a genome-wide scan of 440 individuals from 27 pedigrees ascertained through a single diabetic proband. Subsequently, the study was expanded to include 906 individuals from 39 extended Mexican-American pedigrees, two additional examination cycles approximately 5.3 and 7.6 years after baseline, and genotypes for a new set of genome-wide markers. Therefore, we completed a second genome-wide linkage scan. Using information from a participant's most recent exam, the prevalence of diabetes in nonprobands was 21.8%. We performed genome-wide variance components-based genetic analysis on the discrete trait diabetes using a liability model and on the quantitative Martingale residual obtained from modeling age of diabetes diagnosis using Cox proportional hazard models. Controlling for age and age(2), our strongest evidence for linkage to the trait diabetes and the quantitative Martingale residual was on chromosome 3p at marker D3S2406 with multipoint empirical logarithm of odds scores of 1.87 and 3.76, respectively. In summary, we report evidence for linkage to diabetes on chromosome 3p in a region previously identified in at least three independent populations.

Mapping quantitative trait loci in humans: achievements and limitations

Recent advances in statistical methods and genomic technologies have ushered in a new era in mapping clinically important quantitative traits. However, many refinements and novel statistical approaches are required to enable greater successes in this mapping. The possible impact of recent findings pertaining to the structure of the human genome on efforts to map quantitative traits is yet unclear.

Genetics of Type 2 diabetes

Type 2 diabetes (T2D) has become a health-care problem worldwide, with the rise in disease prevalence being all the more worrying as it not only affects the developed world but also developing nations with fewer resources to cope with yet another major disease burden. Furthermore, the problem is no longer restricted to the ageing population, as young adults and children are also being diagnosed with T2D. In recent years, there has been a surge in the number of genetic studies of T2D in attempts to identify some of the underlying risk factors. In this review, I highlight the main genes known to cause uncommon monogenic forms of diabetes (e.g. maturity-onset diabetes of the young--MODY--and insulin resistance syndromes), as well as describe some of the main approaches used to identify genes involved in the more common forms of T2D that result from the interaction between environmental risk factors and predisposing genotypes. Linkage and candidate gene studies have been highly successful in the identification of genes that cause the monogenic variants of diabetes and, although progress in the more common forms of T2D has been slow, a number of genes have now been reproducibly associated with T2D risk in multiple studies. These are discussed, as well as the main implications that the diabetes gene discoveries will have in diabetes treatment and prevention.

Confirmed Locus on Chromosome 11p and Candidate Loci on 6q and 8p for the Triglyceride and Cholesterol Traits of Combined Hyperlipidemia

Background- Combined hyperlipidemia is a common disorder characterized by a highly atherogenic lipoprotein profile and increased risk of coronary heart disease. The etiology of the lipid abnormalities (increased serum cholesterol and triglyceride or either lipid alone) is unknown.

METHODS AND RESULTS

We assembled 2 large cohorts of families with familial combined hyperlipidemia (FCHL) and performed disease and quantitative trait linkage analyses to evaluate the inheritance of the lipid abnormalities. Chromosomal regions 6q16.1-q16.3, 8p23.3-p22, and 11p14.1-q12.1 produced evidence for linkage to FCHL. Chromosomes 6 and 8 are newly identified candidate loci that may respectively contribute to the triglyceride (logarithm of odds [LOD], 1.43; P=0.005) and cholesterol (LOD, 2.2; P=0.0007) components of this condition. The data for chromosome 11 readily fulfil the guidelines required for a confirmed linkage. The causative alleles may contribute to the inheritance of the cholesterol (LOD, 2.04 at 35.2 cM; P=0.0011) component of FCHL as well as the triglyceride trait (LOD, 2.7 at 48.7 cM; P=0.0002).

CONCLUSIONS

Genetic analyses identify 2 potentially new loci for FCHL and provide important positional information for cloning the genes within the chromosome 11p14.1-q12.1 interval that contributes to the lipid abnormalities of this highly atherogenic disorder.

Quantitative trait linkage studies of diabetes-related traits

Genetic linkage methods for diseases with complex inheritance are based on assessment of allele sharing between affected relative pairs, but such methods have low power to detect genes with moderate effects. This may explain the difficulty in replication for many of the putative loci for type 2 diabetes. To enhance power to detect diabetes-susceptibility genes, some investigators have performed quantitative-trait linkage studies for diabetes-related traits, including measures of glycemia, insulin sensitivity, insulin secretion, obesity, lipidemia, and blood pressure. These linkage studies have not provided stronger or more consistent evidence for linkage than studies of diabetes affection status, but have identified several loci that may play an important role in the physiologic processes related to the development of type 2 diabetes.

Variants within the calpain-10 gene on chromosome 2q37 (NIDDM1) and relationships to type 2 diabetes, insulin resistance, and impaired acute insulin secretion among Scandinavian Caucasians

Variations in the calpain-10 gene (CAPN10) have been identified among Mexican-Americans, and an at-risk haplotype combination (112/121) defined by three polymorphisms, UCSNP-43, -19, and -63, confers increased risk of type 2 diabetes. Here we examine the three polymorphisms in 1,594 Scandinavian subjects, including 409 type 2 diabetic patients, 200 glucose-tolerant control subjects, 322 young healthy subjects, 206 glucose-tolerant offspring of diabetic patients, and 457 glucose-tolerant 70-year-old men. The frequency of the 112/121 combination was not significantly different in 409 type 2 diabetic subjects compared with 200 glucose-tolerant control subjects (0.06 vs. 0.05; odds ratio 1.32 [95% CI 0.58-3.30]). In glucose-tolerant subjects, neither the single-nucleotide polymorphisms individually nor the 112/121 combination were associated with alterations in plasma glucose, serum insulin, or serum C-peptide levels at fasting or during an oral glucose tolerance test, estimates of insulin sensitivity, or glucose-induced insulin secretion. In conclusion, the frequency of the 112/121 at-risk haplotype of CAPN10 is low among Scandinavians and we were unable to demonstrate significant associations between the CAPN10 variants and type 2 diabetes, insulin resistance, or impaired insulin secretion.

Genetic determination of biological age in the Mennonites of the Midwestern United States

Numerous studies have shown that longevity is moderately heritable in human populations. Longevity, however, contains limited information on functional status, since individuals may exhibit differential survival patterns. In this study, we employed a stepwise multiple regression approach to estimate biological aging in a Mennonite population, using chronological age as a dependent variable and various predictors of chronological age including subphenotypes related to diabetes, coronary heart disease, hypertension, renal function, and markers of functional ability. The residual (the difference between chronological and predicted ages) is considered a marker of biological age. In fact, two different data sets were used to obtain residuals due to the availability of data. In each analysis, chronological age was regressed on predictor variables in a stepwise manner, retaining the variables significant at the 5% level. The first analysis (N=729) included 6 significant predictors (R(2)=44.3%): glucose, blood urea nitrogen (BUN), cholesterol, albumin, systolic blood pressure (SBP), and ln potassium, and the second analysis (N=232) included 9 significant predictors (R(2)=71.5%): BUN, albumin, SBP, low-density lipoprotein cholesterol, forced expiratory volume in 1 sec (FEV1), grip strength, trunk flexibility, reaction time, and FEV1xsex. Using a variance components approach, we found that the data set-specific residuals were significantly heritable (h(2)+/-SE): first analysis=0.265+/-0.106, and second analysis=0.469+/-0.180. The residuals from the second data set appear to be more informative for biological aging, perhaps due to the inclusion of functional ability-related phenotypes in addition to the blood chemistry variables. In summary, we have shown that markers of biological aging in Mennonites are under substantial additive genetic influences.

Perspective: the search for genes for type 2 diabetes in the post-genome era

Twin and family studies have demonstrated a strong genetic component to type 2 diabetes mellitus (T2DM), but mapping the susceptibility genes that account for this risk has proved difficult. At least seven single gene defects are known to cause T2DM, often with early onset and insulin deficiency, but these causes account for 5% or less of all T2DM. A large number of candidate genes have been evaluated for typical T2DM, but few have been confirmed in multiple studies, and among these, the effect on individual risk is modest. A large number of genome-wide scans have been published in the last few years, and at least four regions show evidence in multiple studies. However, only NIDDM1 has been mapped to a single gene, and that gene (calpain 10) appears to have a major role only in selected populations. Work is ongoing in many laboratories and multiple populations to map additional regions, but T2DM and other complex diseases have proved recalcitrant to current methodology. In addition to the ongoing progress in completing the genome sequence and in developing a comprehensive map of single nucleotide polymorphisms, new statistical models will be needed to incorporate the multiple loci with modest effect and the known environmental interactions that characterize the susceptibility to T2DM.

A genome-wide scan for loci linked to plasma levels of glucose and HbA(1c) in a community-based sample of Caucasian pedigrees: The Framingham Offspring Study

Elevated blood glucose levels are the hallmark of type 2 diabetes as well as a powerful risk factor for development of the disease. We conducted a genome-wide search for diabetes-related genes, using measures of glycemia as quantitative traits in 330 pedigrees from the Framingham Heart Study. Of 3,799 attendees at the 5th Offspring Study exam cycle (1991--1995), 1,461, 1,251, and 771 men (49%) and women provided information on levels of 20-year mean fasting glucose, current fasting glucose, and HbA(1c), respectively, and 1,308 contributed genotype data (using 401 microsatellite markers with an average spacing of 10 cM). Levels of glycemic traits were adjusted for age, cigarette smoking, alcohol and estrogen use, physical activity, and BMI. We ranked standardized residuals from these models, created normalized deviates from the ranks, and used the variance component model implemented in SOLAR (Sequential Oligogenic Linkage Analysis Routines) to evaluate linkage to normalized deviates as quantitative traits. We found peak evidence for linkage to 20-year mean fasting glucose levels on chromosome 1 at approximately 247 cM from p-telomere (pter) (multipoint logarithm of odds [LOD] 2.33) and on chromosome 10 at approximately 86 cM from pter (multipoint LOD 2.07); to current fasting glucose levels on chromosome 1 at approximately 218 cM from pter (multipoint LOD 1.80) and on chromosome 10 at approximately 96 cM from pter (multipoint LOD 2.15); and to HbA(1c) levels on chromosome 1 at approximately 187 cM (multipoint LOD 2.81). This analysis of unselected European Caucasian pedigrees suggests localization of quantitative trait loci influencing glucose homeostasis on chromosomes 1q and 10q. Findings at approximately 187--218 cM on chromosome 1 appear to replicate linkage reported in previous studies of other populations, pointing to this large chromosomal region as worthy of more detailed scrutiny in the search for type 2 diabetes susceptibility genes.

Factors of insulin resistance syndrome--related phenotypes are linked to genetic locations on chromosomes 6 and 7 in nondiabetic mexican-americans

Insulin resistance syndrome (IRS)-related phenotypes, such as hyperinsulinemia, obesity-related traits, impaired glucose tolerance, dyslipidemia, and hypertension, tend to cluster into factors. We attempted to identify loci influencing the factors of IRS-related phenotypes using phenotypic data from 261 nondiabetic subjects distributed across 27 low-income Mexican-American extended families. Principal component factor analyses were performed using eight IRS-related phenotypes: fasting glucose (FG), fasting specific insulin (FSI), BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), HDL cholesterol, ln triglycerides (ln TGs), and leptin (LEP). The factor analysis yielded three factors: factor 1 (BMI, LEP, and FSI), factor 2 (DBP and SBP), and factor 3 (HDL and ln TG). We conducted multipoint variance components linkage analyses on these factors with the program SOLAR using a 10--15 cM map. We found significant evidence for linkage of factor 1 to two regions on chromosome 6 near markers D6S403 (logarithm of odds [LOD] = 4.2) and D6S264 (LOD = 4.9). We also found strong evidence for linkage of factor 3 to a genetic location on chromosome 7 between markers D7S479 and D7S471 (LOD = 3.2). In conclusion, we found substantial evidence for susceptibility loci on chromosomes 6 and 7 that appear to influence the factors representing the IRS-related phenotypes in Mexican-Americans.

Methods for linkage analysis of quantitative trait loci in humans

This paper reviews linkage analysis methods for detecting loci associated with quantitative traits in humans. All such methods are based on the underlying principle that family members who have similar trait values should have higher than expected levels of sharing of genetic material (identity by descent) near the genes that influence those traits. A number of different statistical methods for testing that association between shared trait values and shared identity by descent have been developed over the past 30 or more years. These different types of tests are reviewed here, with emphasis on their theory and derivations. Robustness and power are also discussed.

Genomewide scans of complex human diseases: true linkage is hard to find

Many "complex" human diseases, which involve multiple genetic and environmental determinants, have increased in incidence during the past 2 decades. During the same time period, considerable effort and expense have been expended in whole-genome screens aimed at detection of genetic loci contributing to the susceptibility to complex human diseases. However, the success of positional cloning attempts based on whole-genome screens has been limited, and many of the fundamental questions relating to the genetic epidemiology of complex human disease remain unanswered. Both to review the success of the positional cloning paradigm as applied to complex human disease and to investigate the characteristics of the whole-genome scans undertaken to date, we created a database of 101 studies of complex human disease, which were found by a systematic Medline search (current as of December 2000). We compared these studies, concerning 31 different human complex diseases, with regard to design, methods, and results. The "significance" categorizations proposed by Lander and Kruglyak were used as criteria for the "success" of a study. Most (66.3% [n=67]) of the studies did not show "significant" linkage when the criteria of Lander and Kruglyak (1995) were used, and the results of studies of the same disease were often inconsistent. Our analyses suggest that no single study design consistently produces more-significant results. Multivariate analysis suggests that the only factors independently associated with increased study success are (a) an increase in the number of individuals studied and (b) study of a sample drawn from only one ethnic group. Positional cloning based on whole-genome screens in complex human disease has proved more difficult than originally had been envisioned; detection of linkage and positional cloning of specific disease-susceptibility loci remains elusive.

Analysis of the insulin-sensitive phosphodiesterase 3B gene in type 2 diabetes

We screened for mutations in the gene of insulin-sensitive phosphodiesterase 3B (PDE3B), which regulates antilipolytic actions of insulin via reduction of intracellular cyclic AMP levels, in Japanese patients with type 2 diabetes mellitus and lipoatrophic diabetes mellitus using single-stranded conformation polymorphism analysis and Southern analysis and investigated frequencies of variable number of tandem repeats. A silent polymorphism at the Arg463 codon (AGG-->AGA) in exon 4 was identified after examining all 16 exons and exon-intron splicing junctions of the gene. This polymorphism was found in 53 of 100 subjects with type 2 diabetes mellitus, 2 of 5 lipoatrophic diabetic patients and 24 of 50 control subjects, without any significant difference in allele frequency between groups. An EcoRI restriction fragment length polymorphism was identified in patients with type 2 diabetes mellitus and control subjects, again with no differences in occurrence. The allelic distribution of two polymorphic tandem repeats sequences in introns 5 and 12 of the gene did not differ significantly between patients with type 2 diabetes mellitus and control subjects. In conclusion, alterations in the PDE3B gene are unlikely to contribute importantly to the pathogenesis of type 2 diabetes mellitus or lipoatrophic diabetes mellitus in Japan.

Impact of sulfonylurea receptor 1 genetic variability on non-insulin-dependent diabetes mellitus prevalence and treatment: a population study

The high affinity sulfonylurea receptor 1 (SUR1) is involved in the metabolism of glucose in pancreatic beta-cells. We investigated the impact of the SUR1 intron 16-3t-->c polymorphism on non-insulin-dependent diabetes mellitus (NIDDM) prevalence in a large representative sample of French men and women, 35-64 years old, and explored potential relationships between the SUR1 intron 16 -t-->c polymorphism and sulfonylurea therapy efficiency. This study took place in Lille (northern), Strasbourg (eastern), and Toulouse (southern France). One hundred and twenty-two subjects with NIDDM were registered. We stratified NIDDM subjects according to their medical treatment: sulfonylureas (n = 70) versus other treatments (n = 50). From the three populations, a control group was selected (n = 1,250). Subjects carrying the cc intron 16 genotype had an increased risk of NIDDM [odds ratio (OR) = 1.76, 95% confidence interval (CI) 1.10-2.80; P = 0.017]. Subjects bearing at least one -3c allele and treated with sulfonylurea agents had fasting plasma triglyceride concentrations 35% lower than subjects that were tt homozygous (P = 0.026), whereas no difference could be detected between genotypes in NIDDM subjects treated with other treatments. The SUR1 intron 16 -3t-->c polymorphism was associated with an increased susceptibility to NIDDM in this population study, and seems to modulate the sulfonylurea therapy efficiency on hypertriglyceridemia reduction. This observation may help to better target the various therapies available for treatment of NIDDM.

A major locus for fasting insulin concentrations and insulin resistance on chromosome 6q with strong pleiotropic effects on obesity-related phenotypes in nondiabetic Mexican Americans

Insulin resistance and hyperinsulinemia are strong correlates of obesity and type 2 diabetes, but little is known about their genetic determinants. Using data on nondiabetics from Mexican American families and a multipoint linkage approach, we scanned the genome and identified a major locus near marker D6S403 for fasting "true" insulin levels (LOD score 4.1, empirical P<.0001), which do not crossreact with insulin precursors. Insulin resistance, as assessed by the homeostasis model using fasting glucose and specific insulin (FSI) values, was also strongly linked (LOD score 3.5, empirical P<.0001) with this region. Two other regions across the genome were found to be suggestively linked to FSI: a location on chromosome 2q, near marker D2S141, and another location on chromosome 6q, near marker D6S264. Since several insulin-resistance syndrome (IRS)-related phenotypes were mapped independently to the regions on chromosome 6q, we conducted bivariate multipoint linkage analyses to map the correlated IRS phenotypes. These analyses implicated the same chromosomal region near marker D6S403 (6q22-q23) as harboring a major gene with strong pleiotropic effects on obesity and on lipid measures, including leptin concentrations (e.g., LOD(eq) for traits-specific insulin and leptin was 4.7). A positional candidate gene for insulin resistance in this chromosomal region is the plasma cell-membrane glycoprotein PC-1 (6q22-q23). The genetic location on chromosome 6q, near marker D6S264 (6q25.2-q26), was also identified by the bivariate analysis as exerting significant pleiotropic influences on IRS-related phenotypes (e.g., LOD(eq) for traits-specific insulin and leptin was 4.1). This chromosomal region harbors positional candidate genes, such as the insulin-like growth factor 2 receptor (IGF2R, 6q26) and acetyl-CoA acetyltransferase 2 (ACAT2, 6q25.3-q26). In sum, we found substantial evidence for susceptibility loci on chromosome 6q that influence insulin concentrations and other IRS-related phenotypes in Mexican Americans.

Variance component methods for detecting complex trait loci

Variance component-based linkage analysis has become a major statistical tool for the localization and evaluation of quantitative trait loci influencing complex phenotypes. The variance component approach has many benefits--it can, for example, be used to analyze large pedigrees, and it is able to accommodate multiple loci simultaneously in a true oligogenic model. Important biological phenomena such as genotype-environment interaction and epistasis are also examined easily in a variance component framework. In this chapter, we review the basic statistical features of variance component linkage analysis, with an emphasis on its power and robustness to distributional violations.

Regulated expression of adenosine triphosphate-sensitive potassium channel subunits in pancreatic beta-cells

The regulation of glucose-dependent insulin secretion in pancreatic beta-cells is linked to the expression and function of the ATP-sensitive potassium channel (K(ATP)), which is composed of a sulfonylurea receptor (SUR1) and an inwardly rectifying potassium channel (Kir6.2). Previous animal and human genetic studies have demonstrated that disruption or defective expression of K(ATP) subunit genes has a profound impact on the regulation of insulin secretion. Little is known about how SUR1 and Kir6.2 gene expression is regulated. Here we show that high glucose concentrations lead to a marked decrease (approximately 70%) in Kir6.2 messenger RNA (mRNA) levels in isolated rat pancreatic islets as well as in the INS-1 beta-cell line. This effect is reversible, because exposure to low glucose reinduces Kir6.2 transcript levels. The cognate K(ATP) channel subunit SUR1 showed similar down-regulation at high glucose concentration. The K(ATP) channel activity of INS-1 cells cultivated at high glucose was reduced by 33-51%. In contrast, glucagon-like peptide-1 (GLP-1) induced Kir6.2 mRNA steady state levels and was able to prevent glucose-dependent inhibition of Kir6.2 mRNA and K(ATP) channel activity. To provide further insight into the mechanisms by which glucose and GLP-1 regulate beta-cell K(ATP) channel genes, we have cloned and initiated the characterization of the Kir6.2 gene transcriptional regulatory regions contained within the entire 4.5 kb flanked by the SUR1 and Kir6.2 genes. Transient transfection experiments with five deletion constructs in a pancreatic beta-cell line (INS-1) showed that the proximal 988 bp of the Kir6.2 promoter sequence contributes only 25-30% to the total basal promoter activity. The minimal promoter region -67/+140, also encompassing parts of the 5'-untranslated region, confers sensitivity to GLP-1, which stimulates transcriptional activity of the Kir6.2 minigene by about 2-fold. We propose that glucose- and GLP-1-dependent regulation of K(ATP) subunit genes may be important in the adaptation of beta-cells to changes in secretory demands in physiological and diseased states.

Pathophysiology and pharmacological treatment of insulin resistance

Diabetes mellitus type 2 is a world-wide growing health problem affecting more than 150 million people at the beginning of the new millennium. It is believed that this number will double in the next 25 yr. The pathophysiological hallmarks of type 2 diabetes mellitus consist of insulin resistance, pancreatic beta-cell dysfunction, and increased endogenous glucose production. To reduce the marked increase of cardiovascular mortality of type 2 diabetic subjects, optimal treatment aims at normalization of body weight, glycemia, blood pressure, and lipidemia. This review focuses on the pathophysiology and molecular pathogenesis of insulin resistance and on the capability of antihyperglycemic pharmacological agents to treat insulin resistance, i.e., a-glucosidase inhibitors, biguanides, thiazolidinediones, sulfonylureas, and insulin. Finally, a rational treatment approach is proposed based on the dynamic pathophysiological abnormalities of this highly heterogeneous and progressive disease.

Comparison of variance components and sibpair-based approaches to quantitative trait linkage analysis in unselected samples

We compared the statistical performance of sibpair-based and variance components approaches to multipoint linkage analysis of a quantitative trait in unselected samples. As a benchmark dataset, we used the simulated family data from Genetic Analysis Workshop 10 [Goldin et al., 1997], and each method was used to screen all 200 replications of the GAW10 genome for evidence of linkage to quantitative trait Q1. The sibpair and variance components methods were each applied to datasets comprising single-sibpairs and complete sibships, and for further comparison we also applied the variance components method to the nuclear family and extended pedigree datasets. For each analysis, the unbiasedness and efficiency of parameter estimation, the power to detect linkage, and the Type I error rate were estimated empirically. Sibpair and variance components methods exhibited comparable performance in terms of the unbiasedness of the estimate of QTL location and the Type I error rate. Within the single-sibpair and sibship sampling units, the variance components approach gave consistently superior power and efficiency of parameter estimation. Within each method, the statistical performance was improved by the use of the larger and more informative sampling units.

Multipoint oligogenic linkage analysis of quantitative traits

We present an overview of pedigree-based variance component linkage methods and discuss their extension to oligogenic inheritance. As an example, oligogenic linkage analyses were performed using the quantitative trait Q4 from the GAW10 simulated data set. A strategy involving sequential oligogenic analyses was found to have increased power to detect the three quantitative trait loci (QTL) influencing Q4 when compared to the classical marginal approach of requiring each locus to have a lod score > or = 3. However, it is shown that requiring conditional lod scores > or = 3 in the sequential analyses may be overly conservative and alternative criteria for the acceptance of multilocus models are discussed.

A major susceptibility locus influencing plasma triglyceride concentrations is located on chromosome 15q in Mexican Americans

Although several genetic forms of rare or syndromic hypertriglyceridemia have been reported, little is known about the specific chromosomal regions across the genome harboring susceptibility genes for common forms of hypertriglyceridemia. Therefore, we conducted a genomewide scan for susceptibility genes influencing plasma triglyceride (TG) levels in a Mexican American population. We used both phenotypic and genotypic data from 418 individuals distributed across 27 low-income, extended Mexican American families. For the analyses, TG values were log transformed (ln TG). We used a variance-components technique to conduct multipoint linkage analyses for localizing susceptibility genes that determine variation in TG levels. We used an approximately 10-15-cM map, which was made on the basis of information from 295 microsatellite markers. After accounting for the effects of sex and sex-specific age terms, we found significant evidence for linkage (LOD = 3.88) of ln TG levels to a genetic location between the markers GABRB3 and D15S165 on chromosome 15q. This putative locus explains 39.7+/-7% (P=.000012) of total phenotypic variation in ln TG levels. Suggestive evidence was found for linkage of ln TG levels to two different locations on chromosome 7, which are approximately 85 cM apart from each other. Also, there is some evidence for linkage of high-density lipoprotein cholesterol concentrations to a genetic location near one of the regions on chromosome 7. In conclusion, we found strong evidence for linkage of ln TG levels to a genetic location on chromosome 15q in a Mexican American population, which is prone to disease conditions such as type 2 diabetes and the insulin-resistance syndrome that are associated with hypertriglyceridemia. This putative locus appears to have a major influence on ln TG variation.

Birth weight and the metabolic syndrome: thrifty phenotype or thrifty genotype?

BACKGROUND

Inverse correlations have been reported between birth weight and the Metabolic Syndrome (abdominal obesity, insulin resistance, hyperinsulinemia, glucose intolerance, dyslipidemia, and hypertension). These correlations are thought to reflect primarily nutritional inadequacies during fetal and early life. We explored familial influences on these correlations.

METHODS

Using birth weight data on 602 subjects from 65 pedigrees, we partitioned phenotypic correlations into familial and non-familial. The former are usually regarded as reflecting primarily genetic influences, although they may also reflect environmental influences that are shared by family members, and the latter reflect random environmental influences.

RESULTS

A consistent pattern of positive familial and inverse non-familial correlations were observed. The strongest familial correlations were between birth weight and fasting insulin (r = 0.58, p = 0.002), leptin (r = 0.48, p = 0.021), split proinsulin (r=0.51, p = 0.090), and heart rate (r = 0.39, p = 0.037). An inverse familial correlation was observed with HDL cholesterol (r = -0.28, p = 0.018). Non-familial correlations were weaker and only two-- subscapular-to-triceps skinfold ratio and fasting insulin--were statistically significant.

CONCLUSION

Since the familial and non-familial correlations were in opposite directions, we attribute the former to the pleiotropic effects of genes. Specifically, we conclude that genes that increase birth weight also worsen the Metabolic Syndrome in adult life. Since the inverse correlations reported in the literature reflect mainly cohorts born in the early part of the 20th century, improved maternal nutrition since then may have allowed the expression of genetic influences in our participants, all of whom were born after 1950.

Type 2 diabetes mellitus in minority children and adolescents. An emerging problem

Type 2 diabetes mellitus is a disease of adults and has been considered rare in the pediatric population. Over the last decade, however, there has been a disturbing trend of increasing cases of type 2 diabetes in children, particularly adolescents, and with a greater proportion of minority children being affected. This article reviews the clinical characteristics of youth with type 2 diabetes, presents the risk factors associated with insulin resistance and type 2 diabetes, discusses treatment options, and projects future directions in research. The ultimate goal is to raise awareness of this challenging entity among healthcare professionals.

Linkage of type 2 diabetes mellitus and of age at onset to a genetic location on chromosome 10q in Mexican Americans

Since little is known about chromosomal locations harboring type 2 diabetes-susceptibility genes, we conducted a genomewide scan for such genes in a Mexican American population. We used data from 27 low-income extended Mexican American pedigrees consisting of 440 individuals for whom genotypic data are available for 379 markers. We used a variance-components technique to conduct multipoint linkage analyses for two phenotypes: type 2 diabetes (a discrete trait) and age at onset of diabetes (a truncated quantitative trait). For the multipoint analyses, a subset of 295 markers was selected on the basis of optimal spacing and informativeness. We found significant evidence that a susceptibility locus near the marker D10S587 on chromosome 10q influences age at onset of diabetes (LOD score 3.75) and is also linked with type 2 diabetes itself (LOD score 2.88). This susceptibility locus explains 63.8%+/-9.9% (P=. 000016) of the total phenotypic variation in age at onset of diabetes and 65.7%+/-10.9% (P=.000135) of the total variation in liability to type 2 diabetes. Weaker evidence was found for linkage of diabetes and of age at onset to regions on chromosomes 3p, 4q, and 9p. In conclusion, our strongest evidence for linkage to both age at onset of diabetes and type 2 diabetes itself in the Mexican American population was for a region on chromosome 10q.