Diabetes Genetic Risk Research Articles

Type 1 diabetes genetic risk contributes to phenotypic presentation in monogenic autoimmune diabetes.

Disease-causing variants in key immune homeostasis genes can lead to monogenic autoimmune diabetes. Some individuals carrying disease-causing variants do not develop autoimmune diabetes, even though they develop other autoimmune disease. We aimed to determine whether type 1 diabetes polygenic risk contributes to phenotypic presentation in monogenic autoimmune diabetes. We used a 67 SNP type 1 diabetes genetic risk score (T1D-GRS) to determine polygenic risk in 62 individuals with monogenic autoimmune diabetes and 180 non-autoimmune neonatal diabetes (NDM) controls. We used population-based controls (n=10,405) and individuals with type 1 diabetes (n=285) as a comparator. Individuals with monogenic autoimmune diabetes had higher T1D-GRSs compared to non-autoimmune NDM (mean 11.3 vs. 9.8; P=1.7×10−5) and controls (mean 10.3; P=7.5×10−6) but were markedly lower than type 1 diabetes (14.9; P= 3.3 × 10−21). These differences were explained by monogenic autoimmune diabetes cases having higher Class II HLA genetic risk, specifically from the DRB1*03:01-DQA1*05:01-DQB1*02:01 haplotype (DR3-DQ2) (P<0.01). In the presence of monogenic autoimmunity, the polygenic class II HLA susceptibility contributes to development of autoimmune diabetes. This suggests a role of class II HLA in targeting the dysregulated immune response towards the beta-cell.

Association between genetic predisposition of AF and the risk of ischemic stroke and thromboembolism

Abstract Background Ischemic stroke and thromboembolism are the major complications of atrial fibrillation (AF), however, its association with genetic background of AF remains unclear. To investigate the association between genetic predisposition of AF underlying common variants and the risk of ischemic stroke and thromboembolism. Methods We included unrelated individuals with non-valvular AF from UK biobank. The polygenic risk scores of AF (PRSAF) was calculated for each individual using the effect weight from a previous study which has been validated in both European and mixed-ancestry population[1, 2]. The SNPs from the original score were lifted over to GRCh38 and 6514708 of 6730541 were available in the UK biobank genotype data. The clinical data was defined by ICD-10 code. The primary endpoint is ischemic stroke or thromboembolism resulting in hospitalization after first AF diagnosis. Results A total of 28810 unrelated patients were included in the study. Among them, 4064 had PRSAF over 90th percentile of the general population, and were considered having high genetic risk. The rest 18746 with per SD increase in PRSAF lower than 90th percentile of the general population were considered having lower genetic risk. Generally, age and sex adjusted model demonstrated that per standard deviation change in PRSAF is associated with 9% increase in the risk of stroke or thromboembolism (HR=1.09, 95%CI: 1.03-1.14), and patients with high genetic risk was associated with 15% increase in the risk of stroke or thromboembolism (HR=1.15, 95%CI: 1.02-1.31).The result remained stable when further adjusted for clinical risk factors (1.09, 95%CI: 1.04-1.15 per SD increase in PRSAF) and competing risk of death (1.10, 95%CI: 1.05-1.16 per SD increase in PRSAF). There was no interaction between CHA2DS2-VASc score risk stratification and the per SD increase in PRSAF (P interaction = 0.751, Figure 1A). However, the association between per SD increase in PRSAF and the event tended to be affected by age at AF onset (HR = 1.02 95%CI: 0.94, 1.11 for early onset AF; HR = 1.12 95%CI: 1.05, 1.19 for non-early onset AF, P for interaction = 0.062, Figure 1B). Multi-variate COX regression including PRSAF, components of CHA2DS2-VASc score, and other AF risk factors revealed that history of stroke/thromboembolism, age over 65 years, hypertension, diabetes and high AF genetic risk were significantly associated with the outcome (Figure 1C). To evaluate the importance of these risk factors, average population attributable fraction for 10-year risk of stroke/thromboembolism in the study population was calculated, indicating that genetic risk of AF is responsible for 3.26% (0.89%-5.63%) of the events (Figure 1D). Conclusion Genetic predisposition of AF underlying common variants is associated with ischemic stroke and thromboembolism independent of clinical risk factors. But its role in different AF populations, like early onset AF, remains further investigation.Figure 1

Random C-Peptide and Islet Antibodies at Onset Predict β Cell Function Trajectory and Insulin Dependence in Pediatric Diabetes

ContextIdentification of prognostic biomarkers in pediatric diabetes is important for precision medicine. ObjectiveWe assessed whether C-peptide and islet autoantibodies are useful to predict the natural history of children with new-onset diabetes. MethodsWe prospectively studied 72 children with new-onset diabetes (median follow-up: 8 months) by applying the Aβ classification system (“A+”: islet autoantibody positive, “β+”: random serum C-peptide≥1.3 ng/mL at diagnosis). Beta-cell function was assessed longitudinally with 2h post-prandial/stimulated urinary C-peptide-to-creatinine ratio (UCPCR) 3-12 weeks (V1) and 6-12 months after diagnosis (V2). We obtained a type 1 diabetes genetic risk score (T1D GRS2) for each participant, and compared characteristics at baseline, and clinical outcomes at V2. ResultsThe cohort was 50% male. Racial distribution was 76.4% White, 20.8% Black and 2.8% Asian or other races. A total of 46.5% participants were Hispanic. Median age (Q1-Q3) was 12.4 (8.3-14.5) years. The Aβ subgroup frequencies were 46 A+β-(63.9%), 1 A-β-(1.4%), 4 A+β+(5.6%), and 21 A-β+(29.2%). Baseline serum C-peptide correlated with UCPCR at both V1 (r=0.36, p=0.002) and V2 (r=0.47, p<0.001). There were significant subgroup differences in age, race, frequency of diabetic ketoacidosis and T1D GRS2 (p<0.01). At V2, the two β- subgroups had lower UCPCR and higher HbA1c compared with the two β+ subgroups (p<0.001 and p=0.02, respectively). Thirty-eight percent of A-β+ but none of the other subgroups were insulin-independent at V2 (p<0.001). ConclusionsC-peptide and islet autoimmunity at diagnosis define distinct phenotypes and predict beta-cell function and insulin dependence 6-12 months later in racially/ethnically diverse children with new-onset diabetes.

Autoantibodies to truncated GAD(96-585) antigen stratify risk of early insulin requirement in adult-onset diabetes.

We investigated whether characterisation of full-length (f-)GADA responses could identify early insulin requirement in adult-onset diabetes. In 179 f-GADA positive participants diagnosed with type 2 diabetes, we assessed associations of truncated (t-)GADA positivity, f-GADA IgG subclasses, and f-GADA affinity with early insulin requirement (<5 years), type 1 diabetes genetic risk score (T1D GRS), and C-peptide. t-GADA positivity was lower in f-GADA positive without early insulin in comparison to f-GADA positive type 2 diabetes requiring insulin within 5 years, and type 1 diabetes (75% vs. 91% and 95% respectively, p<0.0001). t-GADA positivity (in those f-GADA positive) identified a group with a higher type 1 diabetes genetic susceptibility (mean T1D GRS 0.248 vs. 0.225, p=0.003), lower C-peptide (1156 pmol/L vs. 4289 pmol/L, p=1x10-7), and increased IA-2A positivity (23% vs. 6%, p=0.03). In survival analysis, t-GADA positivity was associated with early insulin requirement compared with those only positive for f-GADA, independently from age of diagnosis, f-GADA titre and duration of diabetes [adjusted HR 5.7 (95% CI 1.4, 23.5), p=0.017]. The testing of t-GADA in f-GADA positive individuals with type 2 diabetes identifies those who have genetic and clinical characteristics comparable to type 1 diabetes and stratifies those at higher risk of early insulin requirement.

Islet autoantibody frequency in relatives of children with type 1 diabetes who have a type 2 diabetes diagnosis.

This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes. Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests. Among 226 relatives (64% men; mean age at sampling 41 years; mean age 54 years at diagnosis), 32 (14%) were islet autoantibody-positive for at least one autoantibody more than a decade before diagnosis. Approximately half of these (n = 15) were treated with insulin. GADA-positivity was higher in insulin-treated relatives than in non-insulin-treated relatives (12/18 [67%] vs. 6/18 [33%], p < 0.001). IAA-positivity was observed in 13/32 (41%) of relatives with autoantibodies. GRS2 scores were increased in autoantibody-positive relatives (p = 0.032), but there was no clear evidence for a difference according to treatment (p = 0.072). This study highlights the importance of measuring islet autoantibodies, including IAA, in relatives of people with type 1 diabetes to avoid misdiagnosis.

68-OR: Influence of the Type 1 Diabetes Genetic Risk Score on Response to Immunotherapies for Type 1 Diabetes Prevention

68-OR: Influence of the Type 1 Diabetes Genetic Risk Score on Response to Immunotherapies for Type 1 Diabetes Prevention

Genetic Associations with C-peptide Levels before Type 1 Diabetes Diagnosis in At-Risk Relatives.

We sought to determine whether the type 1 diabetes genetic risk score-2 (T1D-GRS2) and single nucleotide polymorphisms (SNPs) are associated with C-peptide preservation before type 1 diabetes diagnosis. We conducted a retrospective analysis of 713 autoantibody-positive participants who developed type 1 diabetes in the TrialNet Pathway to Prevention Study who had T1DExomeChip data. We evaluated the relationships of 16 known SNPs and T1D-GRS2 with area under the curve (AUC) C-peptide levels during oral glucose tolerance tests conducted in the 9 months before diagnosis. Higher T1D-GRS2 was associated with lower C-peptide AUC in the 9 months before diagnosis in univariate (β=-0.06, P<0.0001) and multivariate (β=-0.03, P=0.005) analyses. Participants with the JAZF1 rs864745 T allele had lower C-peptide AUC in both univariate (β=-0.11, P=0.002) and multivariate (β=-0.06, P=0.018) analyses. The type 2 diabetes-associated JAZF1 rs864745 T allele and higher T1D-GRS2 are associated with lower C-peptide AUC prior to diagnosis of type 1 diabetes, with implications for the design of prevention trials.

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project

BackgroundPopulation screening for risk of type 1 diabetes (T1D) has been proposed to identify those with islet autoimmunity (presence of islet autoantibodies). As islet autoantibodies can be transient, screening with a genetic risk score has been proposed as an entry into autoantibody testing.MethodsChildren were recruited from eight general pediatric and specialty clinics across Virginia with diverse community settings. Recruiters in each clinic obtained informed consent/assent, a medical history, and a saliva sample for DNA extraction in children with and without a history of T1D. A custom genotyping panel was used to define T1D genetic risk based upon associated SNPs in European- and African-genetic ancestry. Subjects at “high genetic risk” were offered a separate blood collection for screening four islet autoantibodies. A follow-up contact (email, mail, and telephone) in one half of the participants determined interest and occurrence of subsequent T1D.ResultsA total of 3818 children aged 2–16 years were recruited, with 14.2% (n = 542) having a “high genetic risk.” Of children with “high genetic risk” and without pre-existing T1D (n = 494), 7.0% (34/494) consented for autoantibody screening; 82.4% (28/34) who consented also completed the blood collection, and 7.1% (2/28) of them tested positive for multiple autoantibodies. Among children with pre-existing T1D (n = 91), 52% (n = 48) had a “high genetic risk.” In the sample of children with existing T1D, there was no relationship between genetic risk and age at T1D onset. A major factor in obtaining islet autoantibody testing was concern over SARS-CoV-2 exposure.ConclusionsMinimally invasive saliva sampling implemented using a genetic risk score can identify children at genetic risk of T1D. Consent for autoantibody screening, however, was limited largely due to the SARS-CoV-2 pandemic and need for blood collection.

Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study.

With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS). Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995-0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88-0.96) and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92). Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D.

Penetrance and expressivity of mitochondrial variants in a large clinically unselected population.

Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.

Genetics of Pulmonary Pressure and Right Ventricle Stress Identify Diabetes as a Causal Risk Factor.

Background Epidemiologic studies have identified risk factors associated with pulmonary hypertension and right heart failure, but causative drivers of pulmonary hypertension and right heart adaptation are not well known. We sought to leverage unbiased genetic approaches to determine clinical conditions that share genetic architecture with pulmonary pressure and right ventricular dysfunction. Methods and Results We leveraged Vanderbilt University's deidentified electronic health records and DNA biobank to identify 14 861 subjects of European ancestry who underwent at least 1 echocardiogram with available estimates of pulmonary pressure and right ventricular function. Analyses of the study were performed between 2020 and 2022. The final analytical sample included 14 861 participants (mean [SD] age, 63 [15] years and mean [SD] body mass index, 29 [7] kg/m2). An unbiased phenome-wide association study identified diabetes as the most statistically significant clinical International Classifications of Diseases, Ninth Revision (ICD-9) code associated with polygenic risk for increased pulmonary pressure. We validated this finding further by finding significant associations between genetic risk for diabetes and a related condition, obesity, with pulmonary pressure estimate. We then used 2-sample univariable Mendelian randomization and multivariable Mendelian randomization to show that diabetes, but not obesity, was independently associated with genetic risk for increased pulmonary pressure and decreased right ventricle load stress. Conclusions Our findings show that genetic risk for diabetes is the only significant independent causative driver of genetic risk for increased pulmonary pressure and decreased right ventricle load stress. These findings suggest that therapies targeting genetic risk for diabetes may also potentially be beneficial in treating pulmonary hypertension and right heart dysfunction.

1829-PUB: Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes Randomised Controlled Trial (PRISM-RCT) in Chinese Patients with Young-Onset Diabetes—Study Design and Baseline Profile

Background: Young-onset diabetes (YOD) is heterogenous in aetiologies and clinical phenotypes. The PRISM study is a 3-year randomised controlled trial to evaluate the effect of precision treatment algorithm guided by biogenetic information on clinical outcomes in Chinese with YOD. Methods: In 2020-2021, we randomized 884 Chinese (18-50 years) with non-type 1 diabetes diagnosed ≤40 years to PRISM (n=443) or usual care (n=441). The PRISM group underwent assessment including biogenetic markers (anti-glutamic acid decarboxylase antibody [GADA], C-peptide, monogenic diabetes gene mutations and genetic risk scores predicting YOD, insulin requirement and complications) for issue of a personalized report to guide multidisciplinary care comprising endocrinologist consultation, counselling, empowerment on self-care, and reminders by supporting staff for 1 year at the Diabetes Research Centre before return to usual care. All patients return for assessment at year 3 for ascertainment of all-diabetes related endpoints. Results: Amongst 884 patients (mean±SD: age 40.7±6.5 years, median [IQR] age at diagnosis 34 [29,38] years, disease duration 7 [3,12] years, HbA1c 7.5±1.7%, 96.2% on glucose-lowering drugs, 27.7% on insulin), 74.7% had family history (19.7% both parents affected), 66.7% hypertension, 76.4% dyslipidaemia, 83% overweight and 35.4% albuminuria. Median fasting C-peptide was 0.6 (0.4, 0.9) nmol/L, 9.5% had C-peptide &amp;lt;0.2 nmol/L, 5.1% were GADA positive. In the PRISM group, 21.9% had low birthweight, 50.7%, childhood obesity, 5.7%, steroid exposure in childhood, 1.8-17.3%, co-existing endocrinopathies (thyroid disease, Cushing’s syndrome, polycystic ovarian syndrome), 7.5%, thalassaemia trait, 7.1%, chronic hepatitis B infection and 10.3%, mental illness. Conclusions: Lifecourse factors, endocrinopathies and mental illnesses are prevalent in YOD. Disclosure A.Luk: Research Support; Novo Nordisk, Boehringer-Ingelheim, Bayer Inc., Speaker's Bureau; Eli Lilly and Company. E.Chow: Research Support; Medtronic, Merck KGaA, Speaker's Bureau; Novartis, Bayer Inc., Sanofi. A.P.Kong: Advisory Panel; Abbott, Kyowa Kirin Co., Ltd., Speaker's Bureau; Abbott, AstraZeneca, Lilly, Bayer Inc., Boehringer Ingelheim Inc. J.C.Chan: Board Member; Asia Diabetes Foundation, Consultant; Bayer Inc., Celltrion, Boehringer Ingelheim and Eli Lilly Alliance, Sanofi, Research Support; AstraZeneca, Servier Laboratories, Viatris Inc., Hua Medicine, Merck KGaA, Applied Therapeutics Inc., Lee Powder, Pfizer Inc., Speaker's Bureau; Novartis, Stock/Shareholder; GemVCare Ltd. Y.Fan: None. B.Fan: None. C.K.P.Lim: Stock/Shareholder; GemVCare Ltd. E.S.H.Lau: None. E.W.M.Poon: None. S.T.F.Tsoi: None. R.Ozaki: None. R.C.Ma: Advisory Panel; AstraZeneca, Merck &amp; Co., Inc., Other Relationship; Bayer Inc., Boehringer-Ingelheim, Research Support; Tricida, Inc., Roche Diagnostics, Novo Nordisk. Funding Health and Medical Research Fund (CFS-CUHK2)

218-LB: Younger Veterans with Adult-Onset Diabetes Who Have High Type 1 Diabetes (T1D) Genetic Risk Are Disproportionately of Minority Ancestry and Have Features Typical of T1D but Are Often Unrecognized—A Health Disparity

Diabetes in Veterans is usually presumed to be T2D because T1D precludes enlistment, but T1D may present in adults; how T1D genetic risk impacts different racial/ethnic groups is unknown. To assess the contributions of T1D genetic risk, we examined 109,954 Veterans in the VA's Million Veteran Program (MVP), using a 30 SNP T1D genetic risk score (GRS) for those with European, Hispanic, and Asian ancestry, and a separate 7-SNP GRS for those of African ancestry. High T1D genetic risk (GRS ≥90th percentile) was characterized according to age at diabetes onset (20-39, 40-59, and 60+ years). High T1D genetic risk was more common with the earliest onset group (13.2%, 10.0% and 9.0%, respectively), and that group had the highest proportion of minority ancestry (47%, 37%, and 25%), all p&amp;lt;0.001. The three high T1D risk groups had similar follow-up (13, 12, and 11 years), GAD antibodies if tested (39%, 41%, and 40%), and low C-peptide levels if measured (36%, 23%, and 33%). However, typical T1D features were more common with earlier onset: use of insulin (80%, 63%, and 43%), time to insulin (0.2, 2.4, and 1.4 yr), diabetic ketoacidosis (11%, 3%, and 0.8%), and severe hypoglycemia prompting an ED visit (10%, 5%, and 3%), all p&amp;lt;0.001. While earlier age of onset groups had more use of T1D ICD codes (50%, 25% and 13%), testing for GAD antibodies (18%, 4%, and 2%), and testing for C-peptide (24%, 9%, and 3%), respectively, all p&amp;lt;0.001, less than half of any group had diagnostic testing for T1D. Conclusions: Increased T1D genetic risk is associated with earlier age of diabetes onset in adults and increased prevalence of typical T1D characteristics, but similar GAD antibodies and C-peptide levels. Since individuals with high T1D risk and early diabetes onset are disproportionately of minority ancestry, health policies aimed to improve T1D recognition and management are needed to remedy this health disparity. Disclosure P. K. Yang: None. L. S. Phillips: Other Relationship; Diasyst Inc., Research Support; Abbott Diabetes, Janssen Pharmaceuticals, Inc., Pfizer Inc., Kowa Pharmaceuticals America, Inc., GlaxoSmithKline plc. Y. Sun: None. S. Raghavan: None. E. M. Litkowski: None. B. T. Legvold: None. M. K. Rhee: Research Support; Kowa Research Institute, Inc. M. Vujkovic: None. P. Reaven: Research Support; Dexcom, Inc. A. Leong: Other Relationship; Merck &amp; Co., Inc. Funding National Institutes of Health (U01DK098245, P30DK111024, AI156161, DK127083); U.S. Department of Veterans Affairs (I01-CX001025, I01-BX005831, I01-BX003340, CX001899, I01CX001737)

Genetic determinants of type 1 diabetes in individuals with weak evidence of islet autoimmunity at disease onset.

Islet autoantibodies (AAbs) are detected in >90% of individuals with clinically suspected type 1 diabetes at disease onset. A single AAb, sometimes at low titre, is often detected in some individuals, making their diagnosis uncertain. Type 1 diabetes genetic risk scores (GRS) are a useful tool for discriminating polygenic autoimmune type 1 diabetes from other types of diabetes, particularly the monogenic forms, but testing is not routinely performed in the clinic. Here, we used a type 1 diabetes GRS to screen for monogenic diabetes in individuals with weak evidence of autoimmunity, i.e. with a single AAb at disease onset. In a pilot study, we genetically screened 142 individuals with suspected type 1 diabetes, 42 of whom were AAb-negative, 27 of whom had a single AAb (single AAb-positive) and 73 of whom had multiple AAbs (multiple AAb-positive) at disease onset. Next-generation sequencing (NGS) was performed in 41 AAb-negative participants, 26 single AAb-positive participants and 60 multiple AAb-positive participants using an analysis pipeline of more than 200 diabetes-associated genes. The type 1 diabetes GRS was significantly lower in AAb-negative individuals than in those with a single and multiple AAbs. Pathogenetic class 4/5 variants in MODY or monogenic diabetes genes were identified in 15/41 (36.6%) AAb-negative individuals, while class 3 variants of unknown significance were identified in 17/41 (41.5%). Residual C-peptide levels at diagnosis were higher in individuals with mutations compared to those without pathogenetic variants. Class 3 variants of unknown significance were found in 11/26 (42.3%) single AAb-positive individuals, and pathogenetic class 4/5 variants were present in 2/26 (7.7%) single AAb-positive individuals. No pathogenetic class 4/5 variants were identified in multiple AAb-positive individuals, but class 3 variants of unknown significance were identified in 19/60 (31.7%) patients. Several patients across the three groups had more than one class 3 variant. These findings provide insights into the genetic makeup of patients who show weak evidence of autoimmunity at disease onset. Absence of islet AAbs or the presence of a single AAb together with a low type 1 diabetes GRS may be indicative of a monogenic form of diabetes, and use of NGS may improve the accuracy of diagnosis.

The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes

Aims/hypothesisThe reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults.MethodsWe analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants.ResultsThe T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4).Conclusions/interpretationThe inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.Graphical abstract

Immunophenotype and genetic risk scores to improve autoantibody negative type 1 diabetes classification: study protocol

&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;An estimated 10-30% of type 1 diabetes (T1D) individuals do not have detectable autoantibodies at diagnosis, thus are classified as “idiopathic” or “non-immune.” Given the non-pathogenic role of islet autoantibodies, the validity of excluding an immune basis for disease in such individuals needs to be questioned. The pan-autoantibody negative type 1 diabetes in adults (PANDA) study aims to characterise the immune, clinical and metabolic phenotype of autoantibody negative T1D individuals.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This is a two-part, multi-centre study which is recruiting 100 participants: autoantibody positive T1D (N=25), autoantibody negative T1D (N=25), latent autoimmune diabetes in adults (N=25) and age- and sex-matched normoglycaemic control (N=25) individuals. Study 1 involves baseline pathology collection and high dimensional immune-phenotyping using flow cytometry. DNA will be extracted from saliva samples to calculate type 1 diabetes genetic risk scores (T1DGRS). Autoantibody negative individuals will undergo monogenic diabetes testing. Study 2 is a prospective, longitudinal sub-study of study 1 participants within 5 years of diagnosis. Beta cell function will be assessed using glucagon stimulated C-peptide at 0, 9 and 18 months. The primary outcome of study 1 is to determine the phenotype of immune cells in autoantibody positive and negative T1D compared to healthy controls. Secondary outcomes of study 1 include clinical and metabolic characteristics and the T1DGRS. The primary outcome of study 2 is the rate of decline of stimulated C-peptide over time. &lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The PANDA study is the first study of its kind which aims to improve diagnosis and characterisation of autoantibody negative T1D.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Routine Islet Autoantibody Testing in Clinically Diagnosed Adult-Onset Type 1 Diabetes Can Help Identify Misclassification and the Possibility of Successful Insulin Cessation.

Recent joint American Diabetes Association and European Association for the Study of Diabetes guidelines recommend routine islet autoantibody testing in all adults newly diagnosed with type 1 diabetes. We aimed to assess the impact of routine islet autoantibody testing in this population. We prospectively assessed the relationship between islet autoantibody status (GADA, IA-2A, and ZNT8A), clinical and genetic characteristics, and progression (annual change in urine C-peptide-to-creatinine ratio [UCPCR]) in 722 adults (≥18 years old at diagnosis) with clinically diagnosed type 1 diabetes and diabetes duration <12 months. We also evaluated changes in treatment and glycemia over 2 years after informing participants and their clinicians of autoantibody results. Of 722 participants diagnosed with type 1 diabetes, 24.8% (179) were autoantibody negative. This group had genetic and C-peptide characteristics suggestive of a high prevalence of nonautoimmune diabetes: lower mean type 1 diabetes genetic risk score (islet autoantibody negative vs. positive: 10.85 vs. 13.09 [P < 0.001] [type 2 diabetes 10.12]) and lower annual change in C-peptide (UCPCR), -24% vs. -43% (P < 0.001).After median 24 months of follow-up, treatment change occurred in 36.6% (60 of 164) of autoantibody-negative participants: 22.6% (37 of 164) discontinued insulin, with HbA1c similar to that of participants continuing insulin (57.5 vs. 60.8 mmol/mol [7.4 vs. 7.7%], P = 0.4), and 14.0% (23 of 164) added adjuvant agents to insulin. In adult-onset clinically diagnosed type 1 diabetes, negative islet autoantibodies should prompt careful consideration of other diabetes subtypes. When routinely measured, negative antibodies are associated with successful insulin cessation. These findings support recent recommendations for routine islet autoantibody assessment in adult-onset type 1 diabetes.

Proteomic analysis of diabetes genetic risk scores identifies complement C2 and neuropilin-2 as predictors of type 2 diabetes: the Atherosclerosis Risk in Communities (ARIC) Study.

Genetic predisposition to type 2 diabetes is well-established, and genetic risk scores (GRS) have been developed that capture heritable liabilities for type 2 diabetes phenotypes. However, the proteins through which these genetic variants influence risk have not been thoroughly investigated. This study aimed to identify proteins and pathways through which type 2 diabetes risk variants may influence pathophysiology. Using a proteomics data-driven approach in a discovery sample of 7241 White participants in the Atherosclerosis Risk in Communities Study (ARIC) cohort and a replication sample of 1674 Black ARIC participants, we interrogated plasma levels of 4870 proteins and four GRS of specific type 2 diabetes phenotypes related to beta cell function, insulin resistance, lipodystrophy, BMI/blood lipid abnormalities and a composite score of all variants combined. Twenty-two plasma proteins were identified in White participants after Bonferroni correction. Of the 22 protein-GRS associations that were statistically significant, 10 were replicated in Black participants and all but one were directionally consistent. In a secondary analysis, 18 of the 22 proteins were found to be associated with prevalent type 2 diabetes and ten proteins were associated with incident type 2 diabetes. Two-sample Mendelian randomisation indicated that complement C2 may be causally related to greater type 2 diabetes risk (inverse variance weighted estimate: OR 1.65 per SD; p=7.0 × 10-3), while neuropilin-2 was inversely associated (OR 0.44 per SD; p=8.0 × 10-3). Identified proteins may represent viable intervention or pharmacological targets to prevent, reverse or slow type 2 diabetes progression, and further research is needed to pursue these targets.

Economic evaluation of using polygenic risk score to guide risk screening and interventions for the prevention of type 2 diabetes in individuals with high overall baseline risk.

Type 2 diabetes (T2D) with increasing prevalence is a significant global public health challenge. Obesity, unhealthy diet, and low physical activity are one of the major determinants of the rise in T2D prevalence. In addition, family history and genetic risk of diabetes also play a role in the process of developing T2D. Therefore, solutions for the early identification of individuals at high risk for T2D for early targeted detection of T2D, prevention, and intervention are highly preferred. Recently, novel genomic-based polygenic risk scores (PRSs) have been suggested to improve the accuracy of risk prediction supporting the targeting of preventive interventions to those at highest risk for T2D. Therefore, the aim of the present study was to assess the cost-utility of an additional PRS testing information (as a part of overall risk assessment) followed by a lifestyle intervention and an additional medical therapy when estimated 10-year overall risk for T2D exceeded 20% among Finnish individuals screened as at the high-risk category (i.e., 10%–20% 10-year overall risk of T2D) based on traditional risk factors only. For a cost-utility analysis, an individual-level state-transition model with probabilistic sensitivity analysis was constructed. A 1-year cycle length and a lifetime time horizon were applied in the base-case. A 3% discount rate was used for costs and QALYs. Cost-effectiveness acceptability curve (CEAC) and estimates for the expected value of perfect information (EVPI) were calculated to assist decision makers. The use of the targeted PRS strategy reclassified 12.4 percentage points of individuals to be very high-risk individuals who would have been originally classified as high risk using the usual strategy only. Over a lifetime horizon, the targeted PRS was a dominant strategy (i.e., less costly, more effective). One-way and scenario sensitivity analyses showed that results remained dominant in almost all simulations. However, there is uncertainty, since the probability (EVPI) of cost-effectiveness at a WTP of 0€/QALY was 63.0% (243€) indicating the probability that the PRS strategy is a dominant option. In conclusion, the results demonstrated that the PRS provides moderate additional value in Finnish population in risk screening leading to potential cost savings and better quality of life when compared with the current screening methods for T2D risk.