OBJECTIVE Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions. RESEARCH DESIGN AND METHODS To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci. RESULTS Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci. CONCLUSIONS This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods.

Background and Purpose To yield large amounts of DNA for many genotype analyses and to provide a renewable source of DNA, the Type 1 Diabetes Genetics Consortium (T1DGC) harvested DNA and peripheral blood mononuclear cells (PBMCs) from individuals with type 1 diabetes and their family members in several regions of the world. Methods DNA repositories were established in Asia-Pacific, Europe, North America, and the United Kingdom. To address region-specific needs, different methods and sample processing techniques were used among the laboratories to extract and to quantify DNA and to establish Epstein-Barr virus transformed cell lines. Results More than 98% of the samples of PBMCs were successfully transformed. Approximately 20—25 μg of DNA were extracted per mL of whole blood. Extraction of DNA from the cell pack ranged from 92 to 165 μg per cell pack. In addition, the extracted DNA from whole blood or transformed cells was successfully utilized in each regional human leukocyte antigen genotyping laboratory and by several additional laboratories performing consortium-wide genotyping projects. Limitations Although the isolation of PBMCs was consistent among sites, the measurement of DNA was difficult to harmonize. Conclusions DNA repositories can be established in different regions of the world and produce similar amounts of high-quality DNA for a variety of high-throughput genotyping techniques. Furthermore, even with the distances and time necessary for transportation, highly efficient transformation of PBMCs is possible. For future studies/trials involving several laboratories in different locations, the T1DGC experience includes examples of protocols that may be applicable. In summary, T1DGC has developed protocols that would be of interest to any scientific organization attempting to overcome the logistical problems associated with studies/trials spanning multiple research facilities, located in different regions of the world. Clinical Trials 2010; 7: S65—S74. http://ctj.sagepub.com

Background Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers.Purpose In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years.Methods Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences.Results A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances.Limitations The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required.Conclusions High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies. Clinical Trials 2010; 7: S75-S87. http://ctj.sagepub.com.

Background and Purpose The Type 1 Diabetes Genetics Consortium (T1DGC) is an international project whose primary aims are to: (a) discover genes that modify type 1 diabetes risk; and (b) expand upon the existing genetic resources for type 1 diabetes research. The initial goal was to collect 2500 affected sibling pair (ASP) families worldwide.Methods T1DGC was organized into four regional networks (Asia-Pacific, Europe, North America, and the United Kingdom) and a Coordinating Center. A Steering Committee, with representatives from each network, the Coordinating Center, and the funding organizations, was responsible for T1DGC operations. The Coordinating Center, with regional network representatives, developed study documents and data systems. Each network established laboratories for: DNA extraction and cell line production; human leukocyte antigen genotyping; and autoantibody measurement. Samples were tracked from the point of collection, processed at network laboratories and stored for deposit at National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories. Phenotypic data were collected and entered into the study database maintained by the Coordinating Center.Results T1DGC achieved its original ASP recruitment goal. In response to research design changes, the T1DGC infrastructure also recruited trios, cases, and controls. Results of genetic analyses have identified many novel regions that affect susceptibility to type 1 diabetes. T1DGC created a resource of data and samples that is accessible to the research community.Limitations Participation in T1DGC was declined by some countries due to study requirements for the processing of samples at network laboratories and/or final deposition of samples in NIDDK Central Repositories. Re-contact of participants was not included in informed consent templates, preventing collection of additional samples for functional studies.Conclusions T1DGC implemented a distributed, regional network structure to reach ASP recruitment targets. The infrastructure proved robust and flexible enough to accommodate additional recruitment. T1DGC has established significant resources that provide a basis for future discovery in the study of type 1 diabetes genetics. Clinical Trials 2010; 7: S5-S32. http://ctj.sagepub.com.

Background and Purpose Three network laboratories measured antibodies to islet autoantigens. Antibodies to glutamic acid decarboxylase (GAD65 [GADA]) and the intracellular portion of protein tyrosine phosphatase (IA-2ic [IA-2A]) were measured by similar, but not identical, methods in samples from participants in the Type 1 Diabetes Genetics Consortium (T1DGC). Methods All laboratories used radiobinding assays to detect antibodies to in vitro transcribed and translated antigen, but with different local standards, calibrated against the World Health Organization (WHO) reference reagent. Using a common method to calculate WHO units/mL, we compared results reported on samples included in the Diabetes Autoantibody Standardization Program (DASP), and developed standard methods for reporting in WHO units/mL. We evaluated intra-assay and inter-assay coefficient of variation (CV) in blind duplicate samples and assay comparability in four DASP workshops. Results Values were linearly related in the three laboratories for both GADA and IA-2A, and intra-assay technical errors for values within the standard curve were below 13% for GADA and below 8.5% for IA-2A. Correlations in samples tested 1—2 years apart were >97%. Over the course of the study, internal CVs were 10—20% with one exception, and the laboratories concordantly called samples GADA or IA-2A positive or negative in 96.7% and 99.6% of duplicates within the standard curve. Despite acceptable CVs and general concordance in ranking samples, the laboratories differed markedly in absolute values for GADA and IA-2A reported in WHO units/mL in DASP over a large range of values. Limitations With three laboratories using different assay methods (including calibrators), consistent values among them could not be attained. Conclusions Modifications in the assays are needed to improve comparability of results expressed as WHO units/mL across laboratories. It will be essential to retain high intra- and inter-assay precision, sensitivity and specificity and to confirm the accuracy of harmonized methods. Clinical Trials 2010; 7: S56—S64. http:// ctj.sagepub.com

Background and Purpose This article describes several ethical, legal, and social issues typical of international genetics biobanking, as encountered in the Type 1 Diabetes Genetics Consortium (T1DGC). Methods By studying the examples set and lessons learned from other international biobanking studies and by devoting considerable time and resources to identifying, addressing, and continually monitoring ethical and regulatory concerns, T1DGC was able to minimize the problems reported by some earlier studies. Conclusions Several important conclusions can be drawn based on the experience in this study: (1) Basic international standards for research ethics review and informed consent are broadly consistent across developed countries. (2) When consent forms are adapted locally and translated into different languages, discrepancies are inevitable and therefore require prompt central review and resolution before research is initiated. (3) Providing separate ‘check-box’ consent for different elements of a study creates confusion and may not be essential. (4) Creating immortalized cell lines to aid future research is broadly acceptable, both in the US and internationally. (5) Imposing some limits on the use of stored samples aids in obtaining ethics approvals worldwide. (6) Allowing potential commercial uses of donated samples is controversial in some Asian countries. (7) Obtaining government approvals can be labor-intensive and time-consuming, and can require legal and diplomatic skills. Clinical Trials 2010; 7: S33—S45. http:// ctj.sagepub.com

text has not been submitted. Review on this subject by the lecturer: J Intern Med. 2009 May;265(5):51429. Clinical manifestations and management of patients with autoimmune polyendocrine syndrome type I. Husebye ES, Perheentupa J, Rautemaa R, Kämpe O. Section of Endocrinology, Institute of Medicine, University of Bergen, Bergen, Norway. eyhu@helse-bergen.no. Abstract. Autoimmune polyendocrine syndrome type I (APS-I) is a monogenic model disease of autoimmunity. Its hallmarks are chronic mucocutaneous candidosis, hypoparathyroidism and adrenal insufficiency, but many other Autoimmune polyendocrine syndrome type I (APS-I) is a monogenic model disease of autoimmunity. Its hallmarks are chronic mucocutaneous candidosis, hypoparathyroidism and adrenal insufficiency, but many other autoimmune disease components occur less frequently. The first components usually appear in childhood, but may be delayed to adolescence or early adult life. There is enormous variation in presentation and phenotype, which makes the diagnosis difficult. Antibodies against interferon-omega and -alpha have recently been shown to be sensitive and relatively specific markers for APS-I, and mutational analysis of the autoimmune regulator gene gives the diagnosis in >95% of cases. The treatment and follow-up of patients is demanding and requires the collaboration of specialists of several fields. However, the literature is especially sparse regarding information on treatment and follow-up; hence, we present here a comprehensive overview on clinical characteristics, treatment and follow-up based on personal experience and published studies. PL2 Novel Avenues in Energy Metabolism PL2-3 How the fetal hypothalamus senses maternal glucose metabolism Jens C. Brüning University of Cologne, and Center of Molecular Medicine Cologne, Department of Mouse Genetics and Metabolism, Institute for Genetics, Cologne, Germany Abstract text has not been submitted.text has not been submitted. Review on this subject by the lecturer. Cell Mol Life Sci. 2010 Oct;67(19):3255-73. Epub 2010 Jun 12. Sensing the fuels: glucose and lipid signaling in the CNS controlling energy homeostasis. Jordan SD, Könner AC, Brüning JC. Department of Mouse Genetics and Metabolism, Institute for Genetics and Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD), University of Cologne, Zülpicher Strasse 47, 50674 Cologne, Germany. Abstract. The central nervous system (CNS) is capable of gathering The central nervous system (CNS) is capable of gathering information on the body's nutritional state and it implements appropriate behavioral and metabolic responses to changes in fuel availability. This feedback signaling of peripheral tissues ensures the maintenance of energy homeostasis. The hypothalamus is a primary site of convergence and integration for these nutrient-related feedback signals, which include central and peripheral neuronal inputs as well as hormonal signals. Increasing evidence indicates that glucose and lipids are detected by specialized fuel-sensing neurons that are integrated in these hypothalamic neuronal circuits. The purpose of this review is to outline the current understanding of fuel-sensing mechanisms in the hypothalamus, to integrate the recent findings in this field, and to address the potential role of dysregulation in these pathways in the development of obesity and type 2 diabetes mellitus. Concluding Remarks. The global prevalence of obesity and diabetes mellitus is increasing at an alarming rate and dysregulation of the central control of energy homeostasis has been posited as a causative mechanism of these metabolic diseases. Besides the capability of selective brain regions, especially the hypothalamus, to integrate a variety of neuronal and hormonal signals, increasing evidence indicates that fuel sensing also plays a pivotal role in the central regulation of food intake, energy expenditure, and glucose homeostasis. Recent progress has confirmed the presence of distinct hypothalamic neuron populations that respond to changes in circulating nutrient concentrations by either activating or inhibiting their firing activity. At the molecular level, some proteins required for neuronal fuel sensing have already been identified. Among them, KATP channels and the well-known fuel sensor AMPK represent critical points of interaction between hypothalamic glucose and lipid sensing. A wide range of data further implicates the modulation of neuronal fuel sensing by a variety of hormones such as insulin, leptin, and ghrelin, leading to an increased degree of complexity in the response of these neurons to changes in wholebody energy level. Beyond the scope of this review is another relative new concept in central nutrient sensing involving the role of amino acids in the regulation of energy homeostasis. Studies have demonstrated that increasing or decreasing the dietary intake of leucine, a branched-chain amino acid, as well as ICV administration of this amino acid affects glucose metabolism and food intake. The latter was attributed to changes in hypothalamic Agouti-related protein (AgRP) expression and mechanistically linked to mammalian target of rapamycine (mTOR). A better understanding of the complex interaction of nutrients, hormones, and neuronal circuitries in the modulation of central behavioral and metabolic output signals might point to novel interventions to prevent or treat obesity and type 2 diabetes mellitus. PL2-4 A paradigm of integrative physiology, the crosstalk between bone and energy metabolisms Gerard Karsenty Columbia University Medical Center, Genetics & Development, New York, United States Our laboratory has been testing the hypothesis that bone mass and energy metabolism are co-regulated. This led us first to show that leptin that is made in adipocytes inhibits both bone mass accrual and appetite by inhibiting serotonin synthesis and release by brainstem neurons. Having identified this regulatory loop and many of its molecular components we then asked whether bone was an endocrine organ regulating energy metabolism. This line of research allowed us to show that the osteoblast-specific secreted molecule osteocalcin favors, when undercarboxylated, insulin secretion, insulin sensitivity and energy expenditure. We further showed that osteoblasts express another gene, Esp, that encodes a tyrosine phosphatase and acts as an inhibitor of osteocalcin decarboxylation. How an intracellular tyrosine phosphatase could regulate the carboxylation statues of a secreted molecule like osteocalcin is unknown. Likewise, we do not know what is the human equivalent, if it exists, of Esp that is pseudogene in humans. We have embarked in a systematic study, using biochemical, molecular biology and genetics as tools to answer these two questions. Publications on this subject by the lecturer. Cell Biol. 2010 Oct 4;191(1):7-13. J. The two faces of serotonin in bone biology. Ducy P, Karsenty G. Department of Pathology and Cell Biology and 2 Department of Genetics and Development, Columbia University Medical Center, New York, NY 10032. Abstract. The serotonin molecule has some remarkable properties. It is synthesized by two different genes at two different sites, and, surprisingly, plays The serotonin molecule has some remarkable properties. It is synthesized by two different genes at two different sites, and, surprisingly, plays antagonistic functions on bone mass accrual at these two sites. When produced peripherally, serotonin acts as a hormone to inhibit bone formation. In contrast, when produced in the brain, serotonin acts as a neurotransmitter to exert a positive and dominant effect on bone mass accrual by enhancing bone formation and limiting bone resorption. The effect of serotonin on bone biology could be harnessed pharmacologically to treat diseases such as osteoporosis. Cell. 2010 Jul 23;142(2):296-308. Insulin signaling in osteoblasts integrates bone remodeling and energy metabolism. Ferron M, Wei J, Yoshizawa T, Del Fattore A, DePinho RA, Teti A, Ducy P, Karsenty G. Department of Genetics and Development, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA. Comment in: Cell. 2010 Jul 23;142(2):198-200. Abstract. The broad expression of the insulin receptor suggests that the spectrum of insulin function has not been fully described. A cell type expressing this receptor is the osteoblast, a bone-specific cell favoring glucose metabolism through a hormone, osteocalcin, that becomes active once uncarboxylated. We show here that insulin signaling in osteoblasts is necessary for whole-body glucose homeostasis because it increases osteocalcin activity. To achieve this function insulin signaling in osteoblasts takes advantage of the regulation of osteoclastic bone resorption exerted by osteoblasts. Indeed, since bone resorption occurs at a pH acidic enough to decarboxylate proteins, osteoclasts determine the carboxylation status and function of osteocalcin. Accordingly, increasing or decreasing insulin signaling in osteoblasts promotes or hampers glucose metabolism in a bone resorption-dependent manner in mice and humans. Hence, in a feed-forward loop, insulin signals in osteoblasts activate a hormone, osteocalcin, that promotes glucose metabolism. The broad expression of the insulin receptor suggests that the spectrum of insulin function has not been fully described. A cell type expressing this receptor is the osteoblast, a bone-specific cell favoring glucose metabolism through a hormone, osteocalcin, that becomes active once uncarboxylated. We show here that insulin signaling in osteoblasts is necessary for whole-body glucose homeostasis because it increases osteocalcin activity. To achieve this function insulin signaling in osteoblasts takes advantage of the regulation of osteoclastic bone resorption exerted by osteoblasts. Indeed, since bone resorption occurs at a pH acidic enough to decarboxylat

Background When collecting phenotypic data in clinics across the globe, the Type 1 Diabetes Genetics Consortium (T1DGC) used several techniques that ensured consistency, completeness, and accuracy of the data.Purpose The aim of this article is to describe the procedures used for collection, entry, processing, and management of the phenotypic data in this international study.Methods The T1DGC ensured the collection of high quality data using the following procedures throughout the entire study period. The T1DGC used centralized and localized training, required a pilot study, certified all data entry personnel, created standardized data collection forms, reviewed a sample of form sets quarterly throughout the duration of the study, and used a data entry system that provided immediate feedback to those entering the data.Results Due to the intensive procedures in developing the forms, the study was able to uphold consistency among all clinics and minimal changes were required after implementation of the forms. The train-the-trainer model was efficient and only a small number of clinics had to repeat a pilot study. The study was able to maintain a low percentage of missing data (<0.001%) and low duplicate data entry error rate (0.10%).Conclusions It is critical to provide immediate follow-up in order to reinforce training and ensure the quality of the data collected and entered. Clinical Trials 2010; 7: S46-S55. http://ctj.sagepub.com.

The Type I Diabetes Genetics Consortium (T1DGC) is an international, multicenter research program with two primary goals. The first goal is to identify genomic regions and candidate genes whose variants modify an individual's risk of type I diabetes (T1D) and help explain the clustering of the disease in families. The second goal is to make research data available to the research community and to establish resources that can be used by, and that are fully accessible to, the research community. To facilitate the access to these resources, the T1DGC has developed a Consortium Agreement ( http://www.t1dgc.org ) that specifies the rights and responsibilities of investigators who participate in Consortium activities. The T1DGC has assembled a resource of affected sib-pair families, parent–child trios, and case–control collections with banks of DNA, serum, plasma, and EBV-transformed cell lines. In addition, both candidate gene and genome-wide (linkage and association) studies have been performed and displayed in T1DBase ( http://www.t1dbase.org ) for all researchers to use in their own investigations. In this supplement, a subset of the T1DGC collection has been used to investigate earlier published candidate genes for T1D, to confirm the results from a genome-wide association scan for T1D, and to determine associations with candidate genes for other autoimmune diseases or with type II diabetes that may be involved with β-cell function.

The Type I Diabetes Genetics Consortium (T1DGC) is an international collaboration whose primary goal is to identify genes whose variants modify an individual's risk of type I diabetes (T1D). An integral part of the T1DGC's mission is the establishment of clinical and data resources that can be used by, and that are fully accessible to, the T1D research community ( http://www.t1dgc.org ). The T1DGC has organized the collection and analyses of study samples and conducted several major research projects focused on T1D gene discovery: a genome-wide linkage scan, an intensive evaluation of the human major histocompatibility complex, a detailed examination of published candidate genes, and a genome-wide association scan. These studies have provided important information to the scientific community regarding the function of specific genes or chromosomal regions on T1D risk. The results are continually being updated and displayed ( http://www.t1dbase.org ). The T1DGC welcomes all investigators interested in using these data for scientific endeavors on T1D. The T1DGC resources provide a framework for future research projects, including examination of structural variation, re-sequencing of candidate regions in a search for T1D-associated genes and causal variants, correlation of T1D risk genotypes with biomarkers obtained from T1DGC serum and plasma samples, and in-depth bioinformatics analyses.

OBJECTIVE Type 1 diabetes arises from the actions of multiple genetic and environmental risk factors. Considerable success at identifying common genetic variants that contribute to type 1 diabetes risk has come from genetic association (primarily case-control) studies. However, such studies have limited power to detect genes containing multiple rare variants that contribute significantly to disease risk. RESEARCH DESIGN AND METHODS The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled a collection of 2,496 multiplex type 1 diabetic families from nine geographical regions containing 2,658 affected sib-pairs (ASPs). We describe the results of a genome-wide scan for linkage to type 1 diabetes in the T1DGC family collection. RESULTS Significant evidence of linkage to type 1 diabetes was confirmed at the HLA region on chromosome 6p21.3 (logarithm of odds [LOD] = 213.2). There was further evidence of linkage to type 1 diabetes on 6q that could not be accounted for by the major linkage signal at the HLA class II loci on chromosome 6p21. Suggestive evidence of linkage (LOD ≥2.2) was observed near CTLA4 on chromosome 2q32.3 (LOD = 3.28) and near INS (LOD = 3.16) on chromosome 11p15.5. Some evidence for linkage was also detected at two regions on chromosome 19 (LOD = 2.84 and 2.54). CONCLUSIONS Five non–HLA chromosome regions showed some evidence of linkage to type 1 diabetes. A number of previously proposed type 1 diabetes susceptibility loci, based on smaller ASP numbers, showed limited or no evidence of linkage to disease. Low-frequency susceptibility variants or clusters of loci with common alleles could contribute to the linkage signals observed.

OBJECTIVE— The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods. RESEARCH DESIGN AND METHODS— A total of 2,496 multiplex families with type 1 diabetes were genotyped with a panel of 6,090 single nucleotide polymorphisms (SNPs). Evidence of association to disease was evaluated by the pedigree disequilibrium test. Significant results were followed up by genotyping and analyses in two independent sets of samples: 2,214 parent-affected child trio families and a panel of 7,721 case and 9,679 control subjects. RESULTS— Three of the SNPs most strongly associated with type 1 diabetes localized to previously identified type 1 diabetes risk loci: INS, IFIH1, and KIAA0350. A fourth strongly associated SNP, rs876498 (P = 1.0 × 10−4), occurred in the sixth intron of the UBASH3A locus at chromosome 21q22.3. Support for this disease association was obtained in two additional independent sample sets: families with type 1 diabetes (odds ratio [OR] 1.06 [95% CI 1.00–1.11]; P = 0.023) and case and control subjects (1.14 [1.09–1.19]; P = 7.5 × 10−8). CONCLUSIONS— The T1DGC 6K SNP scan and follow-up studies reported here confirm previously reported type 1 diabetes associations at INS, IFIH1, and KIAA0350 and identify an additional disease association on chromosome 21q22.3 in the UBASH3A locus (OR 1.10 [95% CI 1.07–1.13]; P = 4.4 × 10−12). This gene and its flanking regions are now validated targets for further resequencing, genotyping, and functional studies in type 1 diabetes.

PURPOSE:To study adiponectin, a circulating adipocytokine secreted by adipocytes inversely associated with diabetes and insulin resistance, and factors affecting its levels in the Coronary Artery Risk Development in Young Adults (CARDIA) study. METHODS:Adiponectin in serum was measured by radioimmunoassay in 3355 participants (ages: 23-45 years) categorized by fasting glucose levels as normal, impaired fasting glucose, or diabetes mellitus. RESULTS:Levels of adiponectin were higher in women, in white participants, and with age. Waist circumference, estimating visceral fat, strongly and inversely correlated with levels of adiponectin, more than body mass index. Adiponectin values adjusted for gender and race were lower with higher fasting glucose values in the normal range and still lower with impaired fasting glucose and untreated diabetes mellitus, even further adjusting for waist circumference and fasting insulin levels (p < 0.0001). Gender- and race-adjusted adiponectin levels were inversely associated with insulin resistance at year 15 and with insulin resistance measured 15 years previously and with its change from baseline to year 15 (p < 0.0001). CONCLUSIONS:These data suggest complex and significant physiologic interactions among circulating levels of adiponectin and measures of insulin action throughout young adulthood, even from several years earlier. Central obesity, as measured with waist circumference, is a primary factor affecting levels of circulating adiponectin. Furthermore, levels of glucose and levels of adiponectin may directly influence one another.

Abstract Objective: To examine associations of changes in dietary intake with education in young black and white men and women. Design: The Coronary Artery Risk Development in Young Adults (CARDIA) study, a multi-centre population-based prospective study. Dietary intake data at baseline and year 7 were obtained from an extensive nutritionist-administered diet history questionnaire with 700 items developed for CARDIA. Setting: Participants were recruited in 1985–1986 from four sites: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California. Subjects: Participants were from a general community sample of 703 black men (BM), 1006 black women (BW), 963 white men (WM) and 1054 white women (WW) who were aged 18–30 years at baseline. Analyses here include data for baseline (1985–1986) and year 7 (1992–1993). Results: Most changes in dietary intake were observed among those with high education (≥ 12 years) at both examinations. There was a significant decrease in intake of energy from saturated fat and cholesterol and a significant increase in energy from starch for each race-gender group (P < 0.001). Regardless of education, taste was considered an important influence on food choice. Conclusion: The inverse relationship of education with changes in saturated fat and cholesterol intakes suggests that national public health campaigns may have a greater impact among those with more education.

P71 Little is known about the potential role of dairy consumption in the etiology of cardiovascular disease. We studied associations between reported dairy intake and components of the insulin resistance syndrome in a prospective study of young black and white adults. Participants attended up to five clinic examinations over a 10-year period beginning in 1985/6 (age = 18 to 35 years). The baseline and year-7 exam included a comprehensive diet history interview. Dependent variables include body mass index (BMI), waist-hip ratio (WHR), systolic blood pressure (SBP), and concentrations of fasting serum insulin, plasma triacylglycerol (Trg), and plasma HDL-cholesterol. Final sample size was 2929 after attrition and exclusions for diabetes, medication use, and pregnancy. Year 10 means of these variables were compared across quintiles of total dairy food and beverage intake with adjustment for their baseline values and for age, physical activity, smoking, education, race, sex, and intake of energy, alcohol, saturated fat, dietary fiber, and vitamin supplements. Dairy intake was associated with all components of the insulin resistance syndrome in a protective manner as follows: BMI: quintile 5 (> 28.4 times/wk) - quintile 1 (< 9.5 times/wk) = -0.5 kg/m2, p for linear trend across quintiles = .003; WHR: -0.01, p =.02; SBP: -1.9 mmHg, p=.02; insulin: -0.6 μU/ml, p = .02; Trg: -4.3 mg/dl, p = .04; HDL:+0.9 mg/dl, p = .12. Studies are needed to determine the mechanisms through which dairy intake may modify risk factors for cardiovascular disease.