While rapamycin has been in use for years in transplant patients as an antirejection drug, more recently it has shown promise in treating diseases of aging, such as neurodegenerative disorders and atherosclerosis. We recently reported that rapamycin reverses the cellular phenotype of fibroblasts from children with the premature aging disease Hutchinson-Gilford progeria syndrome (HGPS). We found that the causative aberrant protein, progerin, was cleared through autophagic mechanisms when the cells were treated with rapamycin, suggesting a new potential treatment for HGPS. Recent evidence shows that progerin is also present in aged tissues of healthy individuals, suggesting that progerin may contribute to physiological aging. While it is intriguing to speculate that rapamycin may affect normal aging in humans, as it does in lower organisms, it will be important to identify safer analogs of rapamycin for chronic treatments in humans in order to minimize toxicity. In addition to its role in HGPS and normal aging, we discuss the potential of rapamycin for the treatment of age-dependent neurodegenerative diseases.

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.

Asthma is etiologically and clinically heterogeneous, making the genomic basis of asthma difficult to identify. We exploited the strain-dependence of a murine model of allergic airway disease to identify different genomic responses in the lung. BALB/cJ and C57BL/6J mice were sensitized with the immunodominant allergen from the Dermatophagoides pteronyssinus species of house dust mite (Der p 1), without exogenous adjuvant, and the mice then underwent a single challenge with Der p 1. Allergic inflammation, serum antibody titers, mucous metaplasia, and airway hyperresponsiveness were evaluated 72 hours after airway challenge. Whole-lung gene expression analyses were conducted to identify genomic responses to allergen challenge. Der p 1–challenged BALB/cJ mice produced all the key features of allergic airway disease. In comparison, C57BL/6J mice produced exaggerated Th2-biased responses and inflammation, but exhibited an unexpected decrease in airway hyperresponsiveness compared with control mice. Lung gene expression analysis revealed genes that were shared by both strains and a set of down-regulated genes unique to C57BL/6J mice, including several G-protein–coupled receptors involved in airway smooth muscle contraction, most notably the M2 muscarinic receptor, which we show is expressed in airway smooth muscle and was decreased at the protein level after challenge with Der p 1. Murine strain–dependent genomic responses in the lung offer insights into the different biological pathways that develop after allergen challenge. This study of two different murine strains demonstrates that inflammation and airway hyperresponsiveness can be decoupled, and suggests that the down-modulation of expression of G-protein–coupled receptors involved in regulating airway smooth muscle contraction may contribute to this dissociation.

Background

Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in four Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and NMR-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis and built a genetic risk score for MetS.

Methods and Results

A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all four study samples (P=7.23×10−9 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 associated with various VLDL, TG, and HDL metabolites (P=0.024-1.88×10−5). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these associated with lipid phenotypes and none with two or more uncorrelated MetS components. A genetic risk score, calculated as the number of alleles in loci associated with individual MetS traits, was strongly associated with MetS status.

Conclusions

Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits such as hypertension and glucose intolerance.

In 2007, the International Knockout Mouse Consortium (IKMC) made the ambitious promise to generate mutations in virtually every protein-coding gene of the mouse genome in a concerted worldwide action. Now, 5 years later, the IKMC members have developed high-throughput gene trapping and, in particular, gene-targeting pipelines and generated more than 17,400 mutant murine embryonic stem (ES) cell clones and more than 1,700 mutant mouse strains, most of them conditional. A common IKMC web portal (www.knockoutmouse.org) has been established, allowing easy access to this unparalleled biological resource. The IKMC materials considerably enhance functional gene annotation of the mammalian genome and will have a major impact on future biomedical research.

Missing phenotype data can be a major hurdle to mapping quantitative trait loci (QTL). Though in many cases experiments may be designed to minimize the occurrence of missing data, it is often unavoidable in practice; thus, statistical methods to account for missing data are needed. In this paper we describe an approach for conjoining multiple imputation and QTL mapping. Methods are applied to map genes associated with increased breathing effort in mice after lung inflammation due to allergen challenge in developing lines of the Collaborative Cross, a new mouse genetics resource. Missing data poses a particular challenge in this study because the desired phenotype summary to be mapped is a function of incompletely observed dose-response curves. Comparison of the multiple imputation approach to two naive approaches for handling missing data suggest that these simpler methods may yield poor results: ignoring missing data through a complete case analysis may lead to incorrect conclusions, while using a last observation carried forward procedure, which does not account for uncertainty in the imputed values, may lead to anti-conservative inference. The proposed approach is widely applicable to other studies with missing phenotype data.

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m2) or 4,123 obese cases (BMI≥30 kg/m2), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10−9, OR = 1.13 [95% CI 1.09–1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00–1.06]). A variant in HMG20A—previously identified in South Asians but not Europeans—was associated with type 2 diabetes in obese cases (P = 1.3×10−8, OR = 1.11 [95% CI 1.07–1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02–1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10–1.17], P = 3.2×10−14. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05–1.08], P = 2.2×10−16. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.

Author Summary

Individuals with Type 2 diabetes (T2D) can present with variable clinical characteristics. It is well known that obesity is a major risk factor for type 2 diabetes, yet patients can vary considerably—there are many lean diabetes patients and many overweight people without diabetes. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2). Specifically, as lean T2D patients had lower risk than obese patients, they must have been more genetically susceptible. Using genetic data from multiple genome-wide association studies, we tested genetic markers across the genome in 2,112 lean type 2 diabetes cases (BMI<25 kg/m2), 4,123 obese cases (BMI≥30 kg/m2), and 54,412 healthy controls. We confirmed our results in an additional 2,881 lean cases, 8,702 obese cases, and 18,957 healthy controls. Using these data we found differences in genetic enrichment between lean and obese cases, supporting our original hypothesis. We also searched for genetic variants that may be risk factors only in lean or obese patients and found two novel gene regions not previously reported in European individuals. These findings may influence future study design for type 2 diabetes and provide further insight into the biology of the disease.

OBJECTIVE

We investigated the effects of 34 genetic risk variants for hyperglycemia/type 2 diabetes on lipoprotein subclasses and particle composition in a large population-based cohort.

RESEARCH DESIGN AND METHODS

The study included 6,580 nondiabetic Finnish men from the population-based Metabolic Syndrome in Men (METSIM) study (aged 57 ± 7 years; BMI 26.8 ± 3.7 kg/m2). Genotyping of 34 single nucleotide polymorphism (SNPs) for hyperglycemia/type 2 diabetes was performed. Proton nuclear magnetic resonance spectroscopy was used to measure particle concentrations of 14 lipoprotein subclasses and their composition in native serum samples.

RESULTS

The glucose-increasing allele of rs780094 in GCKR was significantly associated with low concentrations of VLDL particles (independently of their size) and small LDL and was nominally associated with low concentrations of intermediate-density lipoprotein, all LDL subclasses, and high concentrations of very large and large HDL particles. The glucose-increasing allele of rs174550 in FADS1 was significantly associated with high concentrations of very large and large HDL particles and nominally associated with low concentrations of all VLDL particles. SNPs rs10923931 in NOTCH2 and rs757210 in HNF1B genes showed nominal or significant associations with several lipoprotein traits. The genetic risk score of 34 SNPs was not associated with any of the lipoprotein subclasses.

CONCLUSIONS

Four of the 34 risk loci for type 2 diabetes or hyperglycemia (GCKR, FADS1, NOTCH2, and HNF1B) were significantly associated with lipoprotein traits. A GCKR variant predominantly affected the concentration of VLDL, and the FADS1 variant affected very large and large HDL particles. Only a limited number of risk loci for hyperglycemia/type 2 diabetes significantly affect lipoprotein metabolism.

Large prospective cohort studies are critical for identifying etiologic factors for disease, but they require substantial long-term research investment. Such studies can be conducted as multisite consortia of academic medical centers, combinations of smaller ongoing studies, or a single large site such as a dominant regional health-care provider. Still another strategy relies upon centralized conduct of most or all aspects, recruiting through multiple temporary assessment centers. This is the approach used by a large-scale national resource in the United Kingdom known as the “UK Biobank,” which completed recruitment/examination of 503,000 participants between 2007 and 2010 within budget and ahead of schedule. A key lesson from UK Biobank and similar studies is that large studies are not simply small studies made large but, rather, require fundamentally different approaches in which “process” expertise is as important as scientific rigor. Embedding recruitment in a structure that facilitates outcome determination, utilizing comprehensive and flexible information technology, automating biospecimen processing, ensuring broad consent, and establishing essentially autonomous leadership with appropriate oversight are all critical to success. Whether and how these approaches may be transportable to the United States remain to be explored, but their success in studies such as UK Biobank makes a compelling case for such explorations to begin.

Hematological parameters, including red and white blood cell counts and hemoglobin concentration, are widely used clinical indicators of health and disease. These traits are tightly regulated in healthy individuals and are under genetic control. Mutations in key genes that affect hematological parameters have important phenotypic consequences, including multiple variants that affect susceptibility to malarial disease. However, most variation in hematological traits is continuous and is presumably influenced by multiple loci and variants with small phenotypic effects. We used a newly developed mouse resource population, the Collaborative Cross (CC), to identify genetic determinants of hematological parameters. We surveyed the eight founder strains of the CC and performed a mapping study using 131 incipient lines of the CC. Genome scans identified quantitative trait loci for several hematological parameters, including mean red cell volume (Chr 7 and Chr 14), white blood cell count (Chr 18), percent neutrophils/lymphocytes (Chr 11), and monocyte number (Chr 1). We used evolutionary principles and unique bioinformatics resources to reduce the size of candidate intervals and to view functional variation in the context of phylogeny. Many quantitative trait loci regions could be narrowed sufficiently to identify a small number of promising candidate genes. This approach not only expands our knowledge about hematological traits but also demonstrates the unique ability of the CC to elucidate the genetic architecture of complex traits.

Defining the genetic contribution of rare variants to common diseases is a major basic and clinical science challenge that could offer new insights into disease etiology and provide potential for directed gene- and pathway-based prevention and treatment. Common and rare nonsynonymous variants in the GCKR gene are associated with alterations in metabolic traits, most notably serum triglyceride levels. GCKR encodes glucokinase regulatory protein (GKRP), a predominantly nuclear protein that inhibits hepatic glucokinase (GCK) and plays a critical role in glucose homeostasis. The mode of action of rare GCKR variants remains unexplored. We identified 19 nonsynonymous GCKR variants among 800 individuals from the ClinSeq medical sequencing project. Excluding the previously described common missense variant p.Pro446Leu, all variants were rare in the cohort. Accordingly, we functionally characterized all variants to evaluate their potential phenotypic effects. Defects were observed for the majority of the rare variants after assessment of cellular localization, ability to interact with GCK, and kinetic activity of the encoded proteins. Comparing the individuals with functional rare variants to those without such variants showed associations with lipid phenotypes. Our findings suggest that, while nonsynonymous GCKR variants, excluding p.Pro446Leu, are rare in individuals of mixed European descent, the majority do affect protein function. In sum, this study utilizes computational, cell biological, and biochemical methods to present a model for interpreting the clinical significance of rare genetic variants in common disease.

Background

Long-range regulatory elements, such as enhancers, exert substantial control over tissue-specific gene expression patterns. Genome-wide discovery of functional enhancers in different cell types is important for our understanding of genome function as well as human disease etiology.

Results

In this study, we developed an in silico approach to model the previously reported phenomenon of transcriptional pausing, accompanied by divergent transcription, at active promoters. We then used this model for large-scale prediction of non-promoter-associated bidirectional expression of short transcripts. Our predictions were significantly enriched for DNase hypersensitive sites, histone H3 lysine 27 acetylation (H3K27ac), and other chromatin marks associated with active rather than poised or repressed enhancers. We also detected modest bidirectional expression at binding sites of the CCCTC-factor (CTCF) genome-wide, particularly those that overlap H3K27ac.

Conclusions

Our findings indicate that the signature of bidirectional expression of short transcripts, learned from promoter-proximal transcriptional pausing, can be used to predict active long-range regulatory elements genome-wide, likely due in part to specific association of RNA polymerase with enhancer regions.

Summary

Identifying cis-regulatory elements is important to understand how human pancreatic islets modulate gene expression in physiologic or pathophysiologic (e.g., diabetic) conditions. We conducted genome-wide analysis of DNase I hypersensitive sites, histone H3 lysine methylation modifications (K4me1, K4me3, K79me2), and CCCTC factor (CTCF) binding in human islets. This identified ~18,000 putative promoters (several hundred unannotated and islet-active). Surprisingly, active promoter modifications were absent at genes encoding islet-specific hormones, suggesting a distinct regulatory mechanism. Of 34,039 distal (non-promoter) regulatory elements, 47% are islet-unique and 22% are CTCF-bound. In the 18 type 2 diabetes (T2D)-associated loci, we identified 118 putative regulatory elements and confirmed enhancer activity for 12/33 tested. Among 6 regulatory elements harboring T2D-associated variants, 2 exhibit significant allele-specific differences in activity. These findings present a global snapshot of the human islet epigenome and should provide functional context for non-coding variants emerging from genetic studies of T2D and other islet disorders.

Objective

Children with Hutchinson–Gilford progeria syndrome (HGPS) exhibit dramatically accelerated cardiovascular disease (CVD) causing death from myocardial infarction or stroke between ages 7 and 20 years. We undertook the first histological comparative evaluation between genetically confirmed HGPS and the CVD of aging.

Methods and Results

We present structural and immunohistological analysis of cardiovascular tissues from two children with HGPS, who died of myocardial infarction. Both had features classically associated with the atherosclerosis of aging, as well as arteriolosclerosis of small vessels. Additionally, vessels exhibited prominent adventitial fibrosis, a previously undescribed feature of HGPS. Importantly, though progerin was detected at higher rates in the HGPS coronary arteries, it was also present in non-HGPS individuals. Between ages one month and 97 years, progerin staining increased an average of 3.34% per year (P<0.0001) in coronary arteries.

Conclusion

We find concordance between many aspects of cardiovascular pathology in both HGPS and geriatric patients. HGPS generates a more prominent adventitial fibrosis than typical CVD. Vascular progerin generation in young non-HGPS individuals, which significantly increases throughout life, strongly suggests that progerin has a role in the CV aging of the general population.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant syndrome caused by mutations in the MEN1 tumor suppressor gene. Loss of the functional second copy of the MEN1 gene causes individuals to develop multiple endocrine tumors, primarily affecting the parathyroid, pituitary, and pancreas. While it is clear that the protein encoded by MEN1, menin, suppresses endocrine tumors, its biochemical functions and direct downstream targets remain unclear. Recent studies have suggested that menin may act as a scaffold protein to coordinate gene transcription, and that menin is an oncogenic cofactor for homeobox (HOX) gene expression in hematopoietic cancer. The role of HOX genes in adult cell differentiation is still obscure, but growing evidence suggests that they may play important roles in the development of cancer. Therefore, we hypothesized that specific HOX genes were regulated by menin in parathyroid tumor development. Utilizing quantitative TaqMan RT-PCR, we compared expression profiles of the 39 HOX genes in human familial MEN1 (fMEN1) parathyroid tumors and sporadic parathyroid adenomas with normal samples. We identified a large set of 23 HOX genes whose deregulation is specific for fMEN1 parathyroid tumors, and only 5 HOX genes whose misexpression are specific for sporadic parathyroid tumor development. These findings provide the first evidence that loss of the MEN1 tumor suppressor gene is associated with deregulation of specific HOX gene expression in the development of familial human parathyroid tumors. Our results strongly reinforce the idea that abnormal expression of developmental HOX genes can be critical in human cancer progression.

Hutchinson-Gilford progeria syndrome (HGPS), a devastating premature aging disease, is caused by a point mutation in the lamin A gene (LMNA). This mutation constitutively activates a cryptic splice donor site, resulting in a mutant lamin A protein known as progerin. Recent studies have demonstrated that progerin is also produced at low levels in normal human cells and tissues. However, the cause-and-effect relationship between normal aging and progerin production in normal individuals has not yet been determined. In this study, we have shown in normal human fibroblasts that progressive telomere damage during cellular senescence plays a causative role in activating progerin production. Progressive telomere damage was also found to lead to extensive changes in alternative splicing in multiple other genes. Interestingly, elevated progerin production was not seen during cellular senescence that does not entail telomere shortening. Taken together, our results suggest a synergistic relationship between telomere dysfunction and progerin production during the induction of cell senescence, providing mechanistic insight into how progerin may participate in the normal aging process.

OBJECTIVE

Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action.

RESEARCH DESIGN AND METHODS

We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084).

RESULTS

The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 × 10−71). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction.

CONCLUSIONS

Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.

BACKGROUND

Hutchinson–Gilford progeria syndrome is a rare, sporadic, autosomal dominant syndrome that involves premature aging, generally leading to death at approximately 13 years of age due to myocardial infarction or stroke. The genetic basis of most cases of this syndrome is a change from glycine GGC to glycine GGT in codon 608 of the lamin A (LMNA) gene, which activates a cryptic splice donor site to produce abnormal lamin A; this disrupts the nuclear membrane and alters transcription.

METHODS

We enrolled 15 children between 1 and 17 years of age, representing nearly half of the world's known patients with Hutchinson–Gilford progeria syndrome, in a comprehensive clinical protocol between February 2005 and May 2006.

RESULTS

Clinical investigations confirmed sclerotic skin, joint contractures, bone abnormalities, alopecia, and growth impairment in all 15 patients; cardiovascular and central nervous system sequelae were also documented. Previously unrecognized findings included prolonged prothrombin times, elevated platelet counts and serum phosphorus levels, measured reductions in joint range of motion, low-frequency conductive hearing loss, and functional oral deficits. Growth impairment was not related to inadequate nutrition, insulin unresponsiveness, or growth hormone deficiency. Growth hormone treatment in a few patients increased height growth by 10% and weight growth by 50%. Cardiovascular studies revealed diminishing vascular function with age, including elevated blood pressure, reduced vascular compliance, decreased ankle–brachial indexes, and adventitial thickening.

CONCLUSIONS

Establishing the detailed phenotype of Hutchinson–Gilford progeria syndrome is important because advances in understanding this syndrome may offer insight into normal aging. Abnormal lamin A (progerin) appears to accumulate with aging in normal cells.

The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.

OBJECTIVE

We investigated the effects of 18 confirmed type 2 diabetes risk single nucleotide polymorphisms (SNPs) on insulin sensitivity, insulin secretion, and conversion of proinsulin to insulin.

RESEARCH DESIGN AND METHODS

A total of 5,327 nondiabetic men (age 58 ± 7 years, BMI 27.0 ± 3.8 kg/m2) from a large population-based cohort were included. Oral glucose tolerance tests and genotyping of SNPs in or near PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, LOC387761, CDKN2B, IGF2BP2, CDKAL1, HNF1B, WFS1, JAZF1, CDC123, TSPAN8, THADA, ADAMTS9, NOTCH2, KCNQ1, and MTNR1B were performed. HNF1B rs757210 was excluded because of failure to achieve Hardy-Weinberg equilibrium.

RESULTS

Six SNPs (TCF7L2, SLC30A8, HHEX, CDKN2B, CDKAL1, and MTNR1B) were significantly (P < 6.9 × 10−4) and two SNPs (KCNJ11 and IGF2BP2) were nominally (P < 0.05) associated with early-phase insulin release (InsAUC0–30/GluAUC0–30), adjusted for age, BMI, and insulin sensitivity (Matsuda ISI). Combined effects of these eight SNPs reached −32% reduction in InsAUC0–30/GluAUC0–30 in carriers of ≥11 vs. ≤3 weighted risk alleles. Four SNPs (SLC30A8, HHEX, CDKAL1, and TCF7L2) were significantly or nominally associated with indexes of proinsulin conversion. Three SNPs (KCNJ11, HHEX, and TSPAN8) were nominally associated with Matsuda ISI (adjusted for age and BMI). The effect of HHEX on Matsuda ISI became significant after additional adjustment for InsAUC0–30/GluAUC0–30. Nine SNPs did not show any associations with examined traits.

CONCLUSIONS

Eight type 2 diabetes–related loci were significantly or nominally associated with impaired early-phase insulin release. Effects of SLC30A8, HHEX, CDKAL1, and TCF7L2 on insulin release could be partially explained by impaired proinsulin conversion. HHEX might influence both insulin release and insulin sensitivity.

The extent to which variation in chromatin structure and transcription factor binding may influence gene expression, and thus underlie or contribute to variation in phenotype, is unknown. To address this question, we cataloged both individual-to-individual variation and differences between homologous chromosomes within the same individual (allele-specific variation) in chromatin structure and transcription factor binding in lymphoblastoid cells derived from individuals of geographically diverse ancestry. Ten percent of active chromatin sites were individual-specific; a similar proportion were allele-specific. Both individual-specific and allele-specific sites were commonly transmitted from parent to child, which suggests that they are heritable features of the human genome. Our study shows that heritable chromatin status and transcription factor binding differ as a result of genetic variation and may underlie phenotypic variation in humans.

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.