Genetic Risk For Type Research Articles

Associations of dietary patterns between age 9 and 24 months with risk of celiac disease autoimmunity and celiac disease among children at increased risk

BackgroundHigher gluten intake in childhood is associated with increased incidence of celiac disease autoimmunity (CDA) and celiac disease. It remains to be studied whether different dietary patterns independent of gluten intake contribute to the incidence. ObjectivesThis study aimed to explore associations of dietary patterns by age 2 y with risk of CDA and celiac disease in genetically susceptible children. MethodsData was used from 6726 participants at genetic risk of type 1 diabetes and celiac disease enrolled in the observational cohort, The Environmental Determinants of Diabetes in the Young (TEDDY) study. Children were annually screened for tissue transglutaminase autoantibodies (tTGAs) from age 2 y. Principal component analysis extracted dietary patterns, based on intake of 27 food groups assessed by 3-d food records at age 9 to 24 mo. The primary outcome was CDA (i.e., persistently tTGA-positive in at least 2 consecutive samples), and the secondary outcome was celiac disease. During follow-up to mean age 11.0 (standard deviation 3.6) y, 1296 (19.3%) children developed CDA, and 529 (7.9%) were diagnosed with celiac disease. Associations of adherence to dietary patterns (per 5-unit increase) with the study outcomes were estimated by Cox regression models adjusted for risk factors including gluten intake. ResultsAt age 9 mo, a dietary pattern higher in the food groups vegetable fats and milk was associated with reduced risk of CDA (hazard ratio [HR]: 0.88; 95% confidence interval [CI]: 0.79, 0.98; P = 0.02). At 24 mo, a dietary pattern higher in the food groups wheat, vegetable fats, and juices, and lower in milk, meat, and oats at age 24 mo was associated with increased risk of CDA (HR: 1.18; 95% CI: 1.05, 1.33; P < 0.001) and celiac disease (HR: 1.24; 95% CI: 1.03, 1.50; P = 0.03). ConclusionsDietary patterns in early childhood are associated with risk of CDA and celiac disease in genetically predisposed children, independent of gluten intake.

Type 1 Diabetes Genetic Risk Score Differentiates Subgroups of Ketosis-Prone Diabetes.

To determine whether genetic risk for type 1 diabetes (T1D) differentiates the four Aβ subgroups of ketosis-prone diabetes (KPD), where A+ and A- define the presence or absence of islet autoantibodies and β+ and β- define the presence or absence of β-cell function. We compared T1D genetic risk scores (GRS) of patients with KPD across subgroups, race/ethnicity, β-cell function, and glycemia. Among 426 patients with KPD (54% Hispanic, 31% African American, 11% White), rank order of GRS was A+β- > A+β+ = A-β- > A-β+. GRS of A+β- KPD was lower than that of a T1D cohort, and GRS of A-β+ KPD was higher than that of a type 2 diabetes cohort. GRS was lowest among African American patients, with a similar distribution across KPD subgroups. T1D genetic risk delineates etiologic differences among KPD subgroups. Patients with A+β- KPD have the highest and those with A-β+ KPD the lowest GRS.

Low birthweight is associated with a higher incidence of type 2 diabetes over two decades independent of adult BMI and genetic predisposition

Aims/hypothesisLow birthweight is a risk factor for type 2 diabetes. Most previous studies are based on cross-sectional prevalence data, not designed to study the timing of onset of type 2 diabetes in relation to birthweight. We aimed to examine associations of birthweight with age-specific incidence rate of type 2 diabetes in middle-aged to older adults over two decades.MethodsAdults aged 30–60 years enrolled in the Danish Inter99 cohort in 1999–2001 (baseline examination), with information on birthweight from original birth records from 1939–1971 and without diabetes at baseline, were eligible. Birth records were linked with individual-level data on age at diabetes diagnosis and key covariates. Incidence rates of type 2 diabetes as a function of age, sex and birthweight were modelled using Poisson regression, adjusting for prematurity status at birth, parity, polygenic scores for birthweight and type 2 diabetes, maternal and paternal diabetes history, socioeconomic status and adult BMI.ResultsIn 4590 participants there were 492 incident type 2 diabetes cases during a mean follow-up of 19 years. Type 2 diabetes incidence rate increased with age, was higher in male participants, and decreased with increasing birthweight (incidence rate ratio [95% CI per 1 kg increase in birthweight] 0.60 [0.48, 0.75]). The inverse association of birthweight with type 2 diabetes incidence was statistically significant across all models and in sensitivity analysis.Conclusions/interpretationA lower birthweight was associated with increased risk of developing type 2 diabetes independent of adult BMI and genetic risk of type 2 diabetes and birthweight.Graphical

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

Polygenic Risk of Prediabetes, Undiagnosed Diabetes, and Incident Type 2 Diabetes Stratified by Diabetes Risk Factors.

Early diagnosis of type 2 diabetes is crucial to reduce severe comorbidities and complications. Current screening recommendations for type 2 diabetes include traditional risk factors, primarily body mass index (BMI) and family history, however genetics also plays a key role in type 2 diabetes risk. It is important to understand whether genetic predisposition to type 2 diabetes modifies the effect of these traditional factors on type 2 diabetes risk. This work aimed to investigate whether genetic risk of type 2 diabetes modifies associations between BMI and first-degree family history of diabetes with 1) prevalent prediabetes or undiagnosed diabetes; and 2) incident confirmed type 2 diabetes. We included 431 658 individuals aged 40 to 69 years at baseline of multiethnic ancestry from the UK Biobank. We used a multiethnic polygenic risk score for type 2 diabetes (PRST2D) developed by Genomics PLC. Prediabetes or undiagnosed diabetes was defined as baseline glycated hemoglobin greater than or equal to 42 mmol/mol (6.0%), and incident type 2 diabetes was derived from medical records. At baseline, 43 472 participants had prediabetes or undiagnosed diabetes, and 17 259 developed type 2 diabetes over 15 years follow-up. Dose-response associations were observed for PRST2D with each outcome in each category of BMI or first-degree family history of diabetes. Those in the highest quintile of PRST2D with a normal BMI were at a similar risk as those in the middle quintile who were overweight. Participants who were in the highest quintile of PRST2D and did not have a first-degree family history of diabetes were at a similar risk as those with a family history who were in the middle category of PRST2D. Genetic risk of type 2 diabetes remains strongly associated with risk of prediabetes, undiagnosed diabetes, and future type 2 diabetes within categories of nongenetic risk factors. This could have important implications for identifying individuals at risk of type 2 diabetes for prevention and early diagnosis programs.

The emotional well-being of parents with children at genetic risk for type 1 diabetes before and during participation in the POInT-study.

This study examined the emotional impact that parents experience when confronted with an increased genetic risk of type 1 diabetes (T1D) in their child. Population-based screening of neonates for genetic risk of chronic disease carries the risk of increased emotional burden for parents. Information was collected using a well-being questionnaire for parents of infants identified as having an increased risk for T1D in a multinational research study. Parents were asked to complete this questionnaire after they were told their child had an increased risk for T1D (Freder1k-study) and at several time points during an intervention study (POInT-study), where oral insulin was administered daily. Data were collected from 2595 parents of 1371 children across five countries. Panic-related anxiety symptoms were reported by only 4.9% after hearing about their child having an increased risk. Symptoms of depression were limited to 19.4% of the parents at the result-communication visit and declined over time during the intervention study. When thinking about their child's risk for developing T1D (disease-specific anxiety), 47.2% worried, felt nervous and tense. Mothers and parents with a first-degree relative (FDR) with T1D reported more symptoms of depression and disease-specific anxiety (p < 0.001) than fathers and parents without a FDR. Overall, symptoms of depression and panic-related anxiety are comparable with the German population. When asked about their child's risk for T1D during the intervention study, some parents reported disease-specific anxiety, which should be kept in mind when considering population-based screening. As certain subgroups are more prone, it will be important to continue psychological screening and, when necessary, to provide support by an experienced, multidisciplinary team.

Polygenic risk for type 2 diabetes, lifestyle, metabolic health, and cardiovascular disease: a prospective UK Biobank study

BackgroundFew studies have examined associations between genetic risk for type 2 diabetes (T2D), lifestyle, clinical risk factors, and cardiovascular disease (CVD). We aimed to investigate the association of and potential interactions among genetic risk for T2D, lifestyle behavior, and metabolic risk factors with CVD.MethodsA total of 345,217 unrelated participants of white British descent were included in analyses. Genetic risk for T2D was estimated as a genome-wide polygenic risk score constructed from > 6 million genetic variants. A favorable lifestyle was defined in terms of four modifiable lifestyle components, and metabolic health status was determined according to the presence of metabolic syndrome components.ResultsDuring a median follow-up of 8.9 years, 21,865 CVD cases (6.3%) were identified. Compared with the low genetic risk group, participants at high genetic risk for T2D had higher rates of overall CVD events, CVD subtypes (coronary artery disease, peripheral artery disease, heart failure, and atrial fibrillation/flutter), and CVD mortality. Individuals at very high genetic risk for T2D had a 35% higher risk of CVD than those with low genetic risk (HR 1.35 [95% CI 1.19 to 1.53]). A significant gradient of increased CVD risk was observed across genetic risk, lifestyle, and metabolic health status (P for trend > 0.001). Those with favorable lifestyle and metabolically healthy status had significantly reduced risk of CVD events regardless of T2D genetic risk. This risk reduction was more apparent in young participants (≤ 50 years).ConclusionsGenetic risk for T2D was associated with increased risks of overall CVD, various CVD subtypes, and fatal CVD. Engaging in a healthy lifestyle and maintaining metabolic health may reduce subsequent risk of CVD regardless of genetic risk for T2D.

1267-P: Fine-Mapping Type 1 Diabetes Risk at the MHC Locus

The Major Histocompatibility Complex (MHC) locus regulates the adaptive immune response and self-recognition and is the largest contributor to genetic risk of type 1 diabetes (T1D) . Protein-coding alleles in MHC class II and class I genes have long been known to contribute substantial T1D risk, yet whether additional variants affect T1D risk at this locus particularly in the non-coding genome has not been exhaustively evaluated. We therefore performed high-resolution fine-mapping of the MHC locus to identify additional coding and non-coding variants that contribute to T1D risk. We imputed genotypes for 39,270 samples from six European or American cohorts of T1D cases and controls into the T1DGC reference panel using SNP2HLA. We then performed two analyses to fine-map causal variants, first, stepwise conditional analysis using Firth bias-corrected logistic likelihood ratio test and second, iterative Bayesian stepwise selection analysis using the Sum of Single Effects (SuSiE) method. We identified 33 signals in stepwise conditional analysis with p&amp;lt;1×10-6 and 30 signals in SuSiE, where the results were highly concordant between methods. Both methods identified the known high-risk amino acid residue 57 of HLA-DQB1 as the top signal, as well as most known and several novel protein-coding risk and protective alleles in MHC class I and II genes. In addition, we identified multiple signals where the likely causal variant was non-coding and not linked to a protein-coding variant, including those that mapped to the LST1, HLA-DRA and NOTCH4 genes. We further annotated these non-coding signals using accessible chromatin, and several likely causal variants mapped in immune cell and/or pancreatic islet accessible chromatin. In ongoing analyses, we are replicating these signals in independent cohorts and performing molecular validation studies of their regulatory effects in relevant cell types. In total, high-resolution fine-mapping of the MHC locus identified additional T1D risk including in the non-coding genome. Disclosure C.Mcgrail: None. J.Chiou: Employee; Pfizer Inc. P.Benaglio: None. K.J.Gaulton: Consultant; Genentech, Inc., Stock/Shareholder; Neurocrine Biosciences, Inc., Vertex Pharmaceuticals Incorporated. Funding National Institutes of Health (DK120429) National Institutes of Health (DK122607)

Genetic risk of type 2 diabetes modifies the effects of a lifestyle intervention aimed at the prevention of gestational and postpartum diabetes

Aims/hypothesisThe aim of this study was to assess the interaction between genetic risk and lifestyle intervention on the occurrence of gestational diabetes mellitus (GDM) and postpartum diabetes.MethodsThe RADIEL study is an RCT aimed at prevention of GDM and postpartum diabetes through lifestyle intervention. Participants with a BMI ≥30 kg/m2 and/or prior GDM were allocated to intervention and control groups before pregnancy or in early pregnancy. The study visits took place every 3 months before pregnancy, once in each trimester, and at 6 weeks and 6 and 12 months postpartum. We calculated a polygenic risk score (PRS) based on 50 risk variants for type 2 diabetes.ResultsAltogether, 516 participants provided genetic and GDM data. The PRS was associated with higher glycaemic levels (fasting glucose and/or HbA1c) and a lower insulin secretion index in the second and third trimesters and at 12 months postpartum, as well as with a higher occurrence of GDM and glycaemic abnormalities at 12 months postpartum (n = 356). There was an interaction between the PRS and lifestyle intervention (p=0.016 during pregnancy and p=0.024 postpartum) when analysing participants who did not have GDM at the first study visit during pregnancy (n = 386). When analysing women in tertiles according to the PRS, the intervention was effective in reducing the age-adjusted occurrence of GDM only among those with the highest genetic risk (OR 0.37; 95% CI 0.17, 0.82). The risk of glycaemic abnormalities at 12 months postpartum was reduced in the same group after adjusting additionally for BMI, parity, smoking and education (OR 0.35; 95% CI 0.13, 0.97).Conclusions/interpretationGenetic predisposition to diabetes modifies the response to a lifestyle intervention aimed at prevention of GDM and postpartum diabetes. This suggests that lifestyle intervention may benefit from being tailored according to genetic risk.Clinical trial registrationClinicalTrials.gov identifier: NCT01698385Graphical abstract

Prospective assessment in newborns of diabetes autoimmunity (PANDA): Maternal understanding of infant diabetes risk

Purpose: To assess accuracy of mothers’ understanding of their newborns’ genetic risk for type 1 diabetes and to identify predictors of the comprehension and retention of genetic information.Methods: Mothers of 435 newborns genetically screened at birth were informed of the infant’s risk for type 1 diabetes using a standard script that provided both categorical and numerical risk information. The mothers’ comprehension and retention of this information were assessed by structured interview on two occasions, ∼3.6 weeks and ∼3.9 months postnotification.Results: At the initial interview, 73.1% of mothers gave a correct estimate of their child’s genetic risk, 3.2% overestimated risk, 13.3% underestimated risk, and 10.3% could not recall risk at all. At the follow-up interview, fewer mothers (61.9%) correctly estimated their child’s risk and more mothers (24.4%) underestimated their child’s risk. Maternal accuracy was associated with maternal education, ethnic minority status, infant risk status, maternal ability to spontaneously recall both categorical and numerical risk estimates, and length of time since risk notification. Underestimation of risk was associated with maternal education, family history of diabetes, time since risk notification, and maternal anxiety about the baby’s risk.Conclusion: The accuracy of mothers’ recall of infant risk declines over time, with an increasing number of mothers underestimating the infant’s risk. Effective risk communication strategies need to be developed and incorporated into genetic screening programs.

Evaluation of the Effect of FOXO3 rs13217795 Genotype and Minor Allele (C) on Clinical Chemistry and Genetic Risk of Diabetes Among the Elderly Individuals from Northern India

The forkhead box O family (FOXO) is expressed ubiquitously in a spatio-temporal manner and plays a key role in cellular metabolism, senescence, and aging. Genetic mutations in FOXO lead to metabolic diseases and cancer,and affect the longevity of individuals. Our study investigated how the genetic risk of type 2 diabetes mellitus (T2DM) altered due to an intronic variant rs13217795 of the longevity-associated FOXO3 gene in the geriatric population of North India. Genotypic characteristics of rs13217795 were determined among 347 age sex-matched (177 diabetic cases, 170 healthy controls) elderly individuals by TaqMan SNP assays after clinical assessment. Clinical chemistry and circulating cytokines level were assessed by biochemical and immunoassays. Genotype frequencies were not significantly (p = 0.526) different between cases and controls. The minor allele (C) frequency in diabetic cases and controls was 0.47 and 0.49, respectively (OR = 0.94, 95% CI = 0.69–1.26, p > 0.05). The minor allele was associated with lower fasting plasma glucose (FPG), fasting insulin, HOMA-IR, CRP, TNF-α, and IL-6 (p < 0.05). The homozygous minor allele carriers showed significantly lower levels of FPG, HOMA-IR, and TNF-α in T2DM patients. The minor allele (C) of intronic polymorphism in FOXO3 (rs13217795: T/C) confers the protective role characterized by its association with a decrease in glycemic and insulin resistance and proinflammatory markers.

Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample

Aims/hypothesisAccurate prediction of disease progression in individuals with pre-symptomatic type 1 diabetes has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies. Current tools for predicting risk require multiple blood samples taken during an OGTT. Our aim was to develop and validate a simpler tool based on a single blood draw.MethodsModels to predict disease progression using a single OGTT time point (0, 30, 60, 90 or 120 min) were developed using TrialNet data collected from relatives with type 1 diabetes and validated in independent populations at high genetic risk of type 1 diabetes (TrialNet, Diabetes Prevention Trial–Type 1, The Environmental Determinants of Diabetes in the Young [1]) and in a general population of Bavarian children who participated in Fr1da.ResultsCox proportional hazards models combining plasma glucose, C-peptide, sex, age, BMI, HbA1c and insulinoma antigen-2 autoantibody status predicted disease progression in all populations. In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90 and M120, based on sampling at 60, 90 and 120 min, was 0.760, 0.761 and 0.745, respectively. These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires five OGTT blood samples. In TEDDY, where only 120 min blood sampling had been performed, the M120 AUC was 0.865. In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615.Conclusions/interpretationPrediction models based on a single OGTT blood draw accurately predict disease progression from stage 1 or 2 to stage 3 type 1 diabetes. The operational simplicity of M120, its validity across different at-risk populations and the requirement for 120 min sampling to stage type 1 diabetes suggest M120 could be readily applied to decrease the cost and complexity of risk stratification.Graphical abstract

Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes.

Glucocorticoids are key regulators of glucose homeostasis and pancreatic islet function, but the gene regulatory programs driving responses to glucocorticoid signaling in islets and the contribution of these programs to diabetes risk are unknown. In this study we used ATAC-seq and RNA-seq to map chromatin accessibility and gene expression from eleven primary human islet samples cultured in vitro with the glucocorticoid dexamethasone at multiple doses and durations. We identified thousands of accessible chromatin sites and genes with significant changes in activity in response to glucocorticoids. Chromatin sites up-regulated in glucocorticoid signaling were prominently enriched for glucocorticoid receptor binding sites and up-regulated genes were enriched for ion transport and lipid metabolism, whereas down-regulated chromatin sites and genes were enriched for inflammatory, stress response and proliferative processes. Genetic variants associated with glucose levels and T2D risk were enriched in glucocorticoid-responsive chromatin sites, including fine-mapped variants at 51 known signals. Among fine-mapped variants in glucocorticoid-responsive chromatin, a likely casual variant at the 2p21 locus had glucocorticoid-dependent allelic effects on beta cell enhancer activity and affected SIX2 and SIX3 expression. Our results provide a comprehensive map of islet regulatory programs in response to glucocorticoids through which we uncover a role for islet glucocorticoid signaling in mediating genetic risk of T2D.

Nine residues in HLA-DQ molecules determine with susceptibility and resistance to type 1 diabetes among young children in Sweden

HLA-DQ molecules account over 50% genetic risk of type 1 diabetes (T1D), but little is known about associated residues. Through next generation targeted sequencing technology and deep learning of DQ residue sequences, the aim was to uncover critical residues and their motifs associated with T1D. Our analysis uncovered (αa1, α44, α157, α196) and (β9, β30, β57, β70, β135) on the HLA-DQ molecule. Their motifs captured all known susceptibility and resistant T1D associations. Three motifs, “DCAA-YSARD” (OR = 2.10, p = 1.96*10−20), “DQAA-YYARD” (OR = 3.34, 2.69*10−72) and “DQDA-YYARD” (OR = 3.71, 1.53*10−6) corresponding to DQ2.5 and DQ8.1 (the latter two motifs) associated with susceptibility. Ten motifs were significantly associated with resistance to T1D. Collectively, homozygous DQ risk motifs accounted for 43% of DQ-T1D risk, while homozygous DQ resistant motifs accounted for 25% protection to DQ-T1D risk. Of the identified nine residues five were within or near anchoring pockets of the antigenic peptide (α44, β9, β30, β57 and β70), one was the N-terminal of the alpha chain (αa1), one in the CD4-binding region (β135), one in the putative cognate TCR-induced αβ homodimerization process (α157), and one in the intra-membrane domain of the alpha chain (α196). Finding these critical residues should allow investigations of fundamental properties of host immunity that underlie tolerance to self and organ-specific autoimmunity.

Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder

BackgroundMajor depressive disorder (MDD) and type 2 diabetes mellitus (T2D) are known to share clinical comorbidity and to have genetic overlap. Besides their shared genetics, both diseases seem to be associated with alterations in brain structural connectivity and impaired cognitive performance, but little is known about the mechanisms by which genetic risk of T2D might affect brain structure and function and if they do, how these effects could contribute to the disease course of MDD. MethodsThis study explores the association of polygenic risk for T2D with structural brain connectome topology and cognitive performance in 434 nondiabetic patients with MDD and 539 healthy control subjects. ResultsPolygenic risk score for T2D across MDD patients and healthy control subjects was found to be associated with reduced global fractional anisotropy, a marker of white matter microstructure, an effect found to be predominantly present in MDD-related fronto-temporo-parietal connections. A mediation analysis further suggests that this fractional anisotropy variation may mediate the association between polygenic risk score and cognitive performance. ConclusionsOur findings provide preliminary evidence of a polygenic risk for T2D to be linked to brain structural connectivity and cognition in patients with MDD and healthy control subjects, even in the absence of a direct T2D diagnosis. This suggests an effect of T2D genetic risk on white matter integrity, which may mediate an association of genetic risk for diabetes and cognitive impairments.

Growth and development of islet autoimmunity and type 1 diabetes in children genetically at risk.

We aimed to evaluate the relationship between childhood growth measures and risk of developing islet autoimmunity (IA) and type 1 diabetes in children with an affected first-degree relative and increased HLA-conferred risk. We hypothesised that being overweight or obese during childhood is associated with a greater risk of IA and type 1 diabetes. Participants in a randomised infant feeding trial (N = 2149) were measured at 12month intervals for weight and length/height and followed for IA (at least one positive out of insulin autoantibodies, islet antigen-2 autoantibody, GAD autoantibody and zinc transporter 8 autoantibody) and development of type 1 diabetes from birth to 10-14years. In this secondary analysis, Cox proportional hazard regression models were adjusted for birthweight and length z score, sex, HLA risk, maternal type 1 diabetes, mode of delivery and breastfeeding duration, and stratified by residence region (Australia, Canada, Northern Europe, Southern Europe, Central Europe and the USA). Longitudinal exposures were studied both by time-varying Cox proportional hazard regression and by joint modelling. Multiple testing was considered using family-wise error rate at 0.05. In the Trial to Reduce IDDM in the Genetically at Risk (TRIGR) population, 305 (14.2%) developed IA and 172 (8%) developed type 1 diabetes. The proportions of children overweight (including obese) and obese only were 28% and 9% at 10years, respectively. Annual growth measures were not associated with IA, but being overweight at 2-10years of life was associated with a twofold increase in the development of type 1 diabetes (HR 2.39; 95% CI 1.46, 3.92; p < 0.001 in time-varying Cox regression), and similarly with joint modelling. In children at genetic risk of type 1 diabetes, being overweight at 2-10years of age is associated with increased risk of progression from multiple IA to type 1 diabetes and with development of type 1 diabetes, but not with development of IA. Future studies should assess the impact of weight management strategies on these outcomes. ClinicalTrials.gov NCT00179777.

Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis.

OBJECTIVEObservational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding.RESEARCH DESIGN AND METHODSUsing 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment.RESULTSMR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08–1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17–1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs.CONCLUSIONSThis MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes.

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

Cross-Country Comparisons of Physical Activity and Sedentary Behavior among 5-Year-Old Children.

Purpose Previous studies have observed that physical activity (PA) levels tend to be lower in the U.S. population than in many other countries. Within the U.S., PA levels in children are lower in the South than in other regions. Cross-country and interregional differences in PA have not been studied in young children. Methods In an ongoing study of children at genetic risk for Type 1 diabetes, PA was measured by accelerometry in samples of 5-year-old children (n = 2008) from Finland (n = 370), Germany (n = 85), Sweden (n = 706), and the U.S. (n = 847). The U.S. sample was drawn from centers in Washington State, Colorado, and Georgia/Florida. Children wore accelerometers for 7 days, and the data were reduced to daily minutes of light-, moderate- (MPA), vigorous- (VPA), and moderate-to-vigorous- (MVPA) intensity PA and sedentary behavior. Multiple regression was used to compare children across countries and across regions in the U.S, adjusting for wear time, body mass index, and demographic characteristics. Results After adjusting for previously mentioned factors, MVPA and MPA were lower in U.S. children than those in Finland and Sweden. Estimates of physical activity were higher in Finland than in other countries, although not all comparisons were significantly different. U.S children spent significantly more time in sedentary behavior than children in Finland (p < 0.0001). Within the U.S., children's PA was consistently lowest in Georgia/Florida and highest in Washington. Conclusions Cross-country differences in PA, previously reported for adults and adolescents, are evident in 5-year-old children. In general, PA levels are lower in U.S. children than their European counterparts, and within the U.S., are lower in Georgia/Florida and Colorado than in Washington. Future studies should be designed to identify the factors that explain these differences.

831-P: Children at Increased Risk for Type 1 Diabetes Using a Study Educational Tool Have Better Understanding of Genetic Risk: The TEDDY Study

The Environmental Determinants of Diabetes in the Young (TEDDY) is an international study of 8,676 children from birth to age 15 at increased genetic risk for type 1 diabetes. Before the 10-year study visit, children received a book explaining their increased genetic risk for type 1 diabetes and TEDDY study aims. We compared children who read the book to those who did not read the book on their (1) type 1 diabetes risk perception accuracy, (2) anxiety about their increased risk for type 1 diabetes (using a modified version of Spielberg State Anxiety Inventory for children), (3) actions intended to prevent diabetes, and (4) study satisfaction. Overall, 2064/3306 (62%) children read the book; girls, children from two parent families, and Swedish and Finnish children (all p&amp;lt;0.001) were more likely to read the book. Using generalized linear modeling we examined differences in those who read versus did not read the book on child outcome measures while controlling for demographic (e.g., parent education, first-degree relative with diabetes, child sex) and parent measures (e.g., parent risk perception, anxiety, study satisfaction). Children who read the book had more accurate risk perception (read book = 30% accurate versus 24% accurate; OR=1.41, 95% CI=1.19-1.68, p&amp;lt;0.001) and greater TEDDY study satisfaction measured on a 0-2 scale (average treatment difference = 0.10, 95% CI=0.07-0.13, p&amp;lt;0.001) compared to those who did not read the book. No significant group differences in anxiety or behaviors to prevent diabetes occurred. In conclusion, the use of an educational tool is well accepted, is not related to increased child anxiety about diabetes, and is related to greater child diabetes risk perception accuracy and study satisfaction. However, even after reading the book, 70% of children had inaccurate diabetes risk perception, suggesting additional strategies are needed. Findings have implications for retention and education in long-term research cohorts. Disclosure L.B. Smith: None. R. Tamura: None. R. Karban: None. J. Melin: None. Å.E. Wimar: None. M. Gardiner: None. K.A. Driscoll: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention; JDRF; National Institutes of Health/National Center for Advancing Translational Sciences (UL1TR000064, UL1TR001082)