Diabetologia

ObjectiveCertain ethnicities such as South Asians and East Asians have higher rates of type 2 diabetes mellitus, in part, driven by insulin deficiency. Insulin deficiency can be due to beta-cell insufficiency, low beta-cell mass, or early cell death. Transcription factor XBP1 maintains beta-cell function and prevents early cell death by mitigating cellular endoplasmic reticulum stress. We examine the role of XBP1 expression in maintaining glucose homeostasis, glycaemic control, and response to diabetes therapeutics. Research Design and MethodsColocalisation analyses were used to determine if expression of XBP1 in pancreatic islets and type 2 diabetes shared common causal genetic variants. We identify a lead eQTL variant associated exclusively with XBP1 expression and examine its association HOMA-B and stimulated glucose in cohorts of newly diagnosed Asian Indians from Dr. Mohans Diabetes Specialities Centre, India (DMDSC) and the Telemedicine Project for Screening diabetes and complications in rural Tamil Nadu (TREND). We then examine longer term glycaemic control using HbA1c in Asian Indian cohorts, the Tayside Diabetes Study (TDS) of white European ancestry in Scoltand, and the Genes & Health (G&H) study of British South Asian Bangladeshi and Pakistani ancestry. Finally, we assess the effect of eQTL variant on drugs designed to improve insulin secretion (sulphonylureas and GLP1-RA). ResultsVariants affecting XBP1 expression in the pancreatic islets colocalised with variants associated with T2DM risk in East Asians but not in white Europeans. Lower expression of XBP1 was associated with higher risk of T2DM. rs7287124 was the lead eQTL variant and had a higher risk allele frequency in East (65%) and South Asians (50%) compared to white Europeans (25%). In 470 South Asian Indians, the variant was associated with lower beta-cell function and higher stimulated glucose ({beta}log HOMAB =-0.14, P=5x10-3). Trans-ancestry meta-analysed effect of the variant in 179,668 individuals was 4.32 mmol/mol (95%CI:2.60,6.04, P=8x10-7) per allele. In 477 individuals with young onset diabetes with non-obese BMI, the per allele effect was 6.41 mmol/mol (95%CI:3.04, 9.79, P =2x10-4). Variant carriers showed impaired response to sulphonylureas. ConclusionXBP1 expression is a novel target for T2DM with particular value for individuals of under-researched ancestries who have greater risk of young, non-obese onset diabetes. The effect of XBP1 eQTL variant was found to be comparable with or greater that the effect of novel glucose-lowering therapies. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/23289501v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1f6a99aorg.highwire.dtl.DTLVardef@f8fc04org.highwire.dtl.DTLVardef@6983baorg.highwire.dtl.DTLVardef@1473e16_HPS_FORMAT_FIGEXP M_FIG Visual abstract: ER: Endoplasmic Reticulum, UPR: Unfolded Protein Response, IRE1:Inositol-Requiring Enzyme 1, mRNA: messenger ribonucleic acid, ERAD: Endoplasmic Reticulum Associated protein Degradation, eQTL: expression Quantitative Trait Loci, HbA1c: glycated haemoglobin. Created with Biorender.com C_FIG

Diabetic kidney disease (DKD) is considered partially hereditary, but the genetic factors underlying disease remain largely unknown. A key barrier to our understanding stems from its heterogeneity, and likely polygenic etiology. Proteinuric and non-proteinuric DKD are two sub-classes of DKD, defined by high urinary albumin-to-creatinine ratio (UACR) and low creatinine estimated glomerular filtration rate (eGFR). Prior genome-wide association studies (GWAS) have identified multiple loci associated with eGFR and UACR. We aimed to combine summary statistics from previous GWAS for eGFR and UACR in one prediction model and associate it with DKD prevalence. We then tested this using genetic data from 18,841 individuals diagnosed with type 2 diabetes in UK Biobank. We computed two genome-wide polygenic risk scores (GPS) aggregating effects of common variants associated with the two measurements, eGFR and UACR. We show that including both GPS in a single model confers significant improvement in comparison with the single GPS model generated from GWAS summary statistics for DKD. We also find in replication analysis in 5,389 individuals in the multi-ethnic BioMe Biobank, that although the combined model had consistent direction of association, the lowest performance was in individuals with recent African ancestry. In summary, we show that joint modeling of polygenic associations of eGFR and UACR is more significantly associated with DKD than individual modeling as well as a GPS comprised of only DKD summary statistics and may be used to gain insights into biology and progression. However, efforts should be made to develop and validate polygenic approaches in diverse populations.

BackgroundType 2 diabetes (T2D) increases the risk of pancreatic ductal adenocarcinoma (PDAC), which could be due to an epigenetic mechanism. MethodsWe explored the association between T2D and whole pancreas methylation in 141 individuals, of which 28 had T2D, using Illumina MethylationEPIC 850K BeadChip arrays. We performed downstream functional assessment in the rat acinar pancreas cell line AR42J. To further understand the role of our candidate gene in humans, we tested whether null variants were associated with T2D and related traits using the UK biobank. ResultsMethylation analysis identified one significant CpG associated with T2D: hypermethylation in an enhancer in PNLIPRP1, an acinar-specific gene. PNLIPRP1 expression was decreased in T2D individuals. Using a rat acinar cell line, we 1/ confirmed decreased Pnliprp1 in response to a diabetogenic treatment, and 2/ in Pnliprp1 knockdown, an up-regulation of cholesterol biosynthesis, cell cycle down-regulation, decreased expression of acinar markers and increased expression of ductal markers pointing towards acinar-to-ductal metaplasia (ADM), a hallmark of PDAC initiation. Using exome data from UK Biobank, we show that rare PNLIPRP1 null variants associated with increased glucose, BMI and LDL-cholesterol. Conclusions/interpretationWe present evidence that an epigenetically-regulated gene associates with T2D risk, and might promote ADM and PDAC progression, opening new insights into early prevention of PDAC.

Aims/hypothesisCurrent guidelines recommend use of sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) for kidney protection in people with type 2 diabetes and early-stage chronic kidney disease (CKD) based on a urinary albumin/creatinine ratio (uACR) of [&ge;]3 mg/mmol. However, individuals with a normal uACR or low-level albuminuria were not represented in kidney outcome trials, leaving uncertainty about absolute treatment benefit in this group. To address this gap and support treatment decisions in clinical practice, we developed and validated a model to predict individual-level kidney protection benefit through use of SGLT2 inhibitors. MethodsThis observational cohort study used electronic health record data from UK primary care (Clinical Practice Research Datalink, 2013-2020) of adults with type 2 diabetes, eGFR [&ge;]60 ml/min per 1.73 m2 and uACR <30 mg/mmol, without heart failure or atherosclerotic vascular disease, who were starting treatment with either SGLT2 inhibitors or the comparator drugs dipeptidyl peptidase-4 (DPP4) inhibitors/sulfonylureas. First, we confirmed the real-world applicability of the relative treatment effect from a previous SGLT2 inhibitor trial meta-analysis, using overlap-weighted Cox proportional hazards models. Second, we assessed calibration of the CKD-PC risk score for kidney disease progression ([&ge;]50% eGFR decline, end-stage kidney disease or kidney-related death). Third, we integrated the relative treatment effect with the risk score to predict 3-year individual-level absolute risk reductions for SGLT2 inhibitors, and validated the accuracy of predictions vs overlap-weighted estimates based on observed data. Finally, we compared the clinical utility of a model-based treatment strategy with that of the [&ge;]3 mg/mmol albuminuria threshold. ResultsIn 53,096 initiations of SGLT2 inhibitor treatment compared with 88,404 initiations of DPP4 inhibitor/sulfonylurea treatment, there was a 42% lower relative risk of kidney disease progression with SGLT2 inhibitors (HR 0.58; 95% CI 0.48, 0.69), consistent with a previous trial meta-analysis. The CKD-PC risk score did not require recalibration (calibration slope 1.05; 95% CI 0.94, 1.17). The median overall model-predicted absolute risk reduction with SGLT2 inhibitors was 0.37% at 3 years (IQR 0.26-0.55), and showed good calibration (calibration slope 1.10; 95% CI 1.09, 1.12). As an illustration of clinical utility, using the model predictions to target the same proportion of the population (n=25,303, 17.9%) as the albuminuria threshold would prevent over 10% more events over 3 years (253 vs 228) by identifying a subgroup of 6.7% of individuals with uACR <3 mg/mmol who showed significantly greater absolute risk reduction in response to SGLT2 inhibitor treatment than the remainder with uACR <3 mg/mmol (3.2% vs 1.2% in extended 5-year observational analyses, p=0.05). Conclusions/interpretationA model adapting the international CKD-PC risk score can accurately predict the individual-level kidney protection benefit from treatment with SGLT2 inhibitors in people with type 2 diabetes and no or early-stage CKD. This could guide treatment decisions in clinical practice worldwide. and could target treatment more effectively than the [&ge;]3 mg/mmol albuminuria threshold recommended by current international guidelines. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LISodium-glucose cotransporter-2 (SGLT2) inhibitors reduce the risk of kidney failure in people with type 2 diabetes C_LIO_LICurrent guidelines recommend use of SGLT2 inhibitors for kidney protection in individuals with type 2 diabetes and urinary albumin/creatinine ratio [&ge;]3 mg/mmol, but this is an extrapolation beyond current evidence from kidney outcome trials C_LIO_LIIt is unclear which people with type 2 diabetes and preserved eGFR and a normal urinary albumin/creatinine ratio or low-level albuminuria have clinically relevant kidney protection benefit from SGLT2 inhibitors C_LI What is the key question?O_LICan a model integrating an established risk score with the relative treatment effect from a SGLT2 inhibitor trial meta-analysis accurately predict individual-level kidney protection benefit? C_LI What are the new findings?O_LIThe model accurately predicted individual-level kidney protection benefit with SGLT2 inhibitor treatment in an external validation using UK primary care data C_LIO_LICompared with the [&ge;]3 mg/mmol albuminuria threshold, the model more effectively identified individuals who are likely to benefit, and could prevent more adverse kidney events C_LI How might this impact on clinical practice in the foreseeable future?O_LIThe model enables individualised prescribing of SGLT2 inhibitors for kidney protection, which could optimise treatment allocation and improve kidney outcomes C_LI

The molecular mechanisms of SGLT2 inhibitors (SGLT2i) remain incompletely understood. Single-cell RNA sequencing and morphometrics data were collected from research kidney biopsies donated by participants with youth onset type 2 diabetes (T2D), aged 12-21 years of age, and healthy controls (HC) to study the effects of SGLT2i on kidney transcriptomics. Participants with T2D were more obese, had higher glomerular filtration rate, mesangial and glomerular volumes than HC. There were no clinically significant differences between participants prescribed SGLT2i (T2Di(+), n=10) and other T2D (T2Di(-), n=6). Transcriptional profiles showed SGLT2 expression exclusively in the proximal tubular (PT) cluster. Transcriptional alterations in T2Di(+) compared to T2Di(-) were seen across most nephron segments, most prominently in the distal nephron. SGLT2i treatment was associated with suppression of genes in the glycolysis, gluconeogenesis, tricarboxylic acid cycle pathways in PT, but enhanced expression in thick ascending limb. The energy sensitive mTOR signaling pathway transcripts were suppressed towards HC level in all nephron segments in T2Di(+). These transcriptional changes were confirmed in a diabetes mouse model treated with SGLT2i. Therefore, the beneficial effects of SGLT2i treatment to the kidneys might be from mitigating diabetes-induced metabolic perturbations via suppression of mTORC1 signaling across nephron segments, including those not expressing SGLT2.

BackgroundThere are substantial differences in the clinical presentation of type 1 diabetes (T1D) depending on the first-developing autoantibody, although the underlying mechanisms are poorly understood. The DR3-DQ2 (DR3) and DR4-DQ8 (DR4) haplotypes at the MHC locus closely associate with GAD and IAA as the first-developing autoantibody, respectively, and can therefore be used as proxies for first autoantibody development in large cohort studies of T1D cases and controls. MethodsWe performed the first genome-wide association study of T1D stratified by DR3 and DR4 status using 9,091 T1D cases and 14,157 controls from multiple cohorts. We estimated heritability and genetic correlation between DR3-T1D and DR4-T1D, and with other immune and glycaemic phenotypes. We assessed heterogeneity in effects on T1D between DR3 and DR4 individuals at known T1D loci. We determined enrichment of T1D heritability in DR3 and DR4 among variants in cell type-specific cis-regulatory elements (cREs) and biological pathways, and annotated risk variants in cREs. ResultsWe observed only moderate genetic correlation between DR4- and DR3-T1D (rg=0.6), which was lower compared to stratifications based on age of onset and sex, and distinct patterns of genetic correlations with other autoimmune diseases. Among T1D-associated loci, the IL2 locus had significantly larger effect on T1D in DR4 while several other loci (TAGAP, KLRG1) had more nominal heterogeneity. There was stronger enrichment of DR4-T1D associated variants in T cell cREs and T cell-related pathways, while DR3-T1D associated variants were specifically enriched in mast cell cREs. We finally prioritized specific loci annotated in mast cells with stronger effects on T1D in DR3 individuals. ConclusionWe performed the first GWAS of T1D stratified by DR3 and DR4 status, which revealed heterogeneity in genetic risk and biological mechanisms dependent on high-risk HLA background.

ObjectivesGenetic Risk scores (GRS) classify diabetes types, type 1 (T1D) and type 2 (T2D) in Europeans but the power is limited in other ancestries. We explored the performance of T1DGRS and potential reasons for inferior discrimination ability in diabetes-type classification in Indians. Research Design and MethodsIn a well-characterized Indian cohort comprising 645 clinically diagnosed T1D, 1153 T2D and 327 controls, we estimated the discriminative ability of T1DGRS (comprising 67 SNPs from Europeans) using receiver operating characteristics-area under the curve (ROC-AUC). We also compared the islet autoantibody status (AA), frequency and effect size of various HLA alleles/haplotypes between Indians and Europeans. ResultsThe T1DGRS was discriminative of T1D from T2D and controls but the ability is lower in Indians than Europeans (AUC=0.83 vs 0.92 respectively, p<0.0001). The T1DGRS was higher in AA-positive patients compared to AA-negative patients [13.01 (12.79-13.23) vs 12.09 (11.64-12.56)], p<0.0001) and showed greater discrimination in the AA-positive T1D (ROC-AUC 0.85). While association of common HLA-DQA1[~]HLA-DQB1 haplotypes with T1D is replicated, important differences in the risk allele frequency, nature/direction and magnitude of association between Indians and Europeans were noted. ConclusionsA T1DGRS derived from Europeans is discriminative of T1D in Indians, highlighting similarity in heritability of T1D. Differences in allele frequency, effect size and directionality, especially in the HLA region are important contributors to inferior discrimination performance of T1DGRS in Indians. Further studies of diverse populations may improve its performance.

AimsWe investigated the relationship between polygenic score (PGS) for BMI and other adiposity PGS with age at type 2 diabetes onset in white European (EUR) and south Asian (SAS) ancestries, and the mediating role of BMI. MethodsIn this retrospective study, using polygenic score (PGS) for BMI, clinically measured BMI and age at type 2 diabetes onset, we conducted mediation analysis separately for SAS (n=3,901, Genes & Health) and EUR (n=729, UK Biobank) aged 40 years or older. For SAS, we also used multivariable linear regression with backward selection to identify the best adiposity PGS (waist circumference (WC), waist-to-hip ratio (WHR), visceral adipose tissue (VAT), body fat (BF), trunk fat (TF) and gluteofemoral fat (GFAT), hand-grip strength (HGS)) predicting age at type 2 diabetes onset. ResultsA one SD increment in BMI-PGS was associated with earlier type 2 diabetes onset by -0.73 years (95%CI -1.01; -0.45) in SAS and -0.57 years (95%CI -1.05; -0.08) in EUR. BMI fully mediated the PGS effect in EUR (100%) and only partially in SAS (28%). Alongside BMI-PGS, WC-PGS and TF-PGS were good at discriminating measured BMI, WC and WHTR in SAS and were correlated with BMI-PGS. Other best predictors of early onset type 2 diabetes in SAS were WC-PGS, WHR-PGS, BF-PGS and GFAT-PGS, which differed between SAS subgroups and by sex. ConclusionsThese findings underscore the importance of incorporating adiposity-related genetics in predicting type 2 diabetes onset among SAS and demonstrate the limitations of using BMI alone to capture associated risk, particularly in diverse populations with typically lower BMI. Research in contextWhat is already known about this subject? O_LISouth Asians develop type 2 diabetes, on average, a decade earlier than white Europeans and at lower BMI levels. C_LIO_LIThe well-established association between BMI and type 2 diabetes risk in white Europeans is more complex in south Asians, who have different patterns of adipose tissue distribution that are not well reflected in BMI. C_LIO_LIThe contribution of adiposity-related polygenic scores (PGS) to type 2 diabetes onset has not been examined across ancestries. C_LI What is the key question? O_LIWhat is the association between adiposity PGS and type 2 diabetes onset across ancestries, what how much of this effect is mediated by BMI? C_LI What are the new findings? O_LIHigher BMI-PGS is associated with earlier type 2 diabetes onset in both south Asians and white Europeans; this relationship is fully mediated by BMI in white Europeans but only partially in south Asians. C_LIO_LIOther PGS for central adiposity are significant predictors of early type 2 diabetes onset and central adiposity anthropometrics in south Asians. C_LI How might this impact on clinical practice in the foreseeable future? O_LIThese findings highlight the importance of incorporating adiposity-related genetics in predicting type 2 diabetes onset in diverse populations and underscore the need to move beyond BMI when assessing metabolic risk and potentially evaluating the effectiveness of interventions. C_LI

BackgroundGenetic risk scores (GRS) for type 1 diabetes (T1D) have been developed primarily in European populations, limiting their generalisability across ancestries. Indians differ from Europeans in clinical characteristics of T1D and overall genetic architecture, yet systematic evaluation of T1D GRS performance in multi-regional Indian cohorts is lacking. MethodsThe study included 597 T1D patients and 3347 non-diabetic controls from different regions in India. Genotyping, imputation, quality control analysis, and construction of the 67-SNPs T1D GRS were performed using standardised pipelines. Discriminative performance was assessed using Receiver Operative Curve-Area under Curve (ROC-AUC) analysis, and optimal thresholds were derived using Youdens index. HLA-DQ diplotype frequencies were compared, and association analysis was conducted using multivariable logistic regression. FindingsT1D GRS showed consistent discriminative performance across Indian cohorts [ROC-AUC=0.84 (range=0{middle dot}78-0{middle dot}87)], supporting its comprehensive use for T1D classification in India. Notably, its performance was lower in islet cell autoantibody (IA) negative compared with IA positive T1D patients (ROC-AUC, 0{middle dot}75 vs 0{middle dot}85) and in adult-onset than in childhood-onset patients (0{middle dot}74 vs 0{middle dot}84). We observed a lower frequency of protective HLA-DQ diplotypes and a strong association of HLA-DQ81 containing diplotypes in childhood-onset T1D. Application of an India-specific T1D GRS score improved the sensitivity than the European cut-off. InterpretationT1D GRS is a valuable unified diagnostic tool in Indians, but its performance varies by islet cell autoantibody status and age at onset, likely reflecting population-specific HLA architecture. European-derived T1D GRS thresholds under-classify the genetic risk, highlighting the importance of ancestry-aware optimisation in Indians. FundingCDRC grant CDRC202111026 and CSIR Intramural Grant P50. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown that a 67-SNPs T1D genetic risk score (GRS) can distinguish T1D patients from non-diabetic controls and other forms of diabetes, but its performance varies across ancestries. Islet cell autoantibodies (IA) have important diagnostic value for classifying type 1 diabetes (T1D). However, their prevalence in India varies widely, with up to one-quarter of patients testing negative, limiting their clinical utility. Evidence supporting the use of the T1D GRS in India, combined with IA antibodies status is limited to a single cohort representing one linguistic group. The applicability of T1D GRS across multi-centric clinical settings has not been systematically evaluated. Added value of this studyThis study validates the 67-SNPs T1D GRS across multiple Indian cohorts representing major linguistic groups, supporting its use as a unified diagnostic tool. Differences in T1DGRS performance between childhood-and adult-onset T1D are linked to enrichment of protective HLA-DQ diplotypes in adult-onset disease, providing genetic insight into disease heterogeneity. The study also demonstrates that European-derived GRS thresholds systematically under-classify genetic risk in Indians and the population-specific threshold is essential. Implications of all the available evidenceThe European-derived T1D GRS can be applied across Indian clinical settings with consistent discriminative performance. However, its utility is influenced by islet cell autoantibody status and the age at onset of disease. Ancestry-aware threshold optimisation substantially improves diagnostic accuracy and is essential for equitable implementation of T1D GRS in Indians. Larger studies are needed to identify population-specific risk variants and further refine genetic tools for clinical diagnosis.

Novel biomarkers of type 1 diabetes (T1D) are needed for earlier detection of disease and identifying therapeutic targets. We identified biomarkers of T1D by combining plasma cis and trans protein QTLs (pQTLs) for 2,922 proteins in the UK Biobank with a T1D genome-wide association study (GWAS) in 157k samples. T1D risk variants at over 20% of known loci colocalized with cis or trans pQTLs, and distinct sets of T1D loci colocalized with immune, pancreatic secretion, or gut-related proteins. We identified 23 proteins with evidence for a causal role in using pQTLs as genetic instruments in Mendelian Randomization which included multiple sensitivity analyses. Proteins increasing T1D risk were involved in immune processes (e.g. HLA-DRA) and, more surprisingly, T1D protective proteins were enriched in pancreatic secretions (e.g. CPA1), cholesterol metabolism (e.g. APOA1), and gut homeostasis. Genetic variants associated with plasma levels of T1D-protective pancreatic enzymes such as CPA1 were enriched in cis-regulatory elements in pancreatic exocrine and gut enteroendocrine cells, and the protective effects of CPA1 and other enzymes on T1D were consistent when using instruments specific to acinar cells. Finally, pancreatic enzymes had decreased acinar expression in T1D, including CPA1 which was altered prior to onset. Together, these results reveal causal biomarkers and highlight processes in the exocrine pancreas, immune system, and gut that modulate T1D risk.

BackgroundHuman genetic studies suggest that the branched chain amino acids (BCAA) valine, leucine and isoleucine have a causal association with type 2 diabetes. However, inferences are based on analyses of a limited number of genetic loci associated with BCAAs. Whether these conclusions are supported when using instrumental variables for BCAAs that capture a broad set of genetic mechanisms is not known. MethodsWe constructed and validated instrumental variables for each BCAA using large well-powered datasets and tested their association with type 2 diabetes using the two-sample inverse variance weighted (IWV) Mendelian randomization (MR) approach. Sensitivity analyses were performed to ensure the accuracy of the findings. Instrumental variables for type 2 diabetes, fasting insulin and body mass index (BMI) were also tested for associations with BCAA levels. ResultsThere were no significant associations with diabetes for valine (beta=0.17 change in log-odds per standard deviation change in valine, [95% CI, -0.28 - 0.62], p=0.45), leucine (beta=0.19 [-0.30 - 0.68] p=0.45) or isoleucine (beta=0.02 [-0.54 - 0.59], p=0.94). In contrast, type 2 diabetes was associated with each BCAA (valine: beta=0.08 per standard deviation change in levels per log-odds change in type 2 diabetes, [0.05 - 0.10], p=1.8x10-9), (leucine: beta= 0.06 [0.04 - 0.09], p=4.5x10-8) and isoleucine (beta= 0.06 [0.04 - 0.08], p=2.8x10-8). The type 2 diabetes associations were replicated in an independent population, but not in a second population where type 2 diabetes cases were removed, highlighting the consistency and specificity of the association. Similar positive associations were seen for fasting insulin and BMI with the BCAAs. In multivariable MR analyses, type 2 diabetes and fasting insulin had consistent independent associations with each BCAA. ConclusionsThese data suggest that the BCAAs are not mediators of type 2 diabetes risk but are biomarkers of diabetes and higher insulin.

BackgroundType 2 diabetes (T2D) results from a complex interplay between genetic predisposition and lifestyle factors. Both genetic susceptibility and unhealthy lifestyle are known to be associated with elevated T2D risk. However, their combined effects on T2D risk are not well studied. We aimed to determine whether unhealthy modifiable health behaviors were associated with similar increases in the risk of incident T2D among individuals with different levels of genetic risk. MethodsWe performed a genetic risk score (GRS) by lifestyle interaction analysis within 332,251 non-diabetic individuals at baseline from the UK Biobank. Multi-ancestry GRS were calculated by summing the effects of 783 T2D-associated variants and ranked into tertiles. We used baseline self-reported data on smoking, BMI, physical activity level, and diet quality to categorize participants as having a healthy, intermediate, or unhealthy lifestyle. Cox proportional hazards regression models were used to generate adjusted hazards ratios (HR) of T2D risk and associated 95% confidence intervals (CI). ResultsDuring follow-up (median 13.6 years), 13,128 (4.0%) participants developed T2D. GRS (P < 0.001) and lifestyle classification (P < 0.001) were independently associated with increased risk for T2D. Compared with healthy lifestyle, unhealthy lifestyle was associated with increased T2D risk in all genetic risk strata, with adjusted HR ranging from 7.11 (low genetic risk) to 16.33 (high genetic risk). ConclusionsHigh genetic risk and unhealthy lifestyle were the most significant contributors to the development of T2D. Individuals at all levels of genetic risk can greatly mitigate their risk for T2D through lifestyle modifications.

Histopathological heterogeneity in human pancreas has been well documented; however, functional evidence at the tissue level is scarce. Herein we investigated in situ glucose-stimulated islet and carbachol-stimulated acinar cell secretion across the pancreas head (PH), body (PB), and tail (PT) regions in no diabetes (ND, n=15), single islet autoantibody-positive (1AAb+, n=7), and type 1 diabetes donors (T1D, <14 months duration, n=5). Insulin, glucagon, pancreatic amylase, lipase, and trypsinogen secretion along with 3D tissue morphometrical features were comparable across the regions in ND. In T1D, insulin secretion and beta-cell volume were significantly reduced within all regions, while glucagon and enzymes were unaltered. Beta-cell volume was lower despite normal insulin secretion in 1AAb+, resulting in increased volume-adjusted insulin secretion versus ND. Islet and acinar cell secretion in 1AAb+ were consistent across PH, PB and PT. This study supports low inter-regional variation in pancreas slice function and potentially, increased metabolic demand in 1AAb+.

BackgroundEarly-onset Type 1 diabetes (EOT1D) is considered a disease subtype with distinctive immunological and clinical features. While both Human Leukocyte Antigen (HLA) and non-HLA variants contribute to age at T1D diagnosis, detailed analyses of EOT1D-specific genetic determinants are still lacking. This study scrutinized the involvement of the HLA class II locus in EOT1D genetic control. MethodsWe conducted genetic association and regularized logistic regression analyses to evaluate genotypic, haplotypic and allelic variants in DRB1, DQA1 and DQB1 genes in children with EOT1D (diagnosed at [&le;]5 years of age; n=97), individuals with later-onset disease (LaOT1D; diagnosed 8-30 years of age; n=96) and nondiabetic control subjects (n=169), in the Portuguese population. FindingsAnalysis of EOT1D and LaOT1D unrelated patients in comparison with controls, revealed the rare DRB1*04:08-DQ8 haplotype is specifically associated with EOT1D (corrected p-value=1.4x10-5) and represents the major discriminative HLA class II genetic factor. Allelic association further indicated the DRB1*04:08 allele is a distinctive EOT1D susceptibility factor (corrected p-value=7.0x10-7). Conversely, the classical T1D risk allele DRB1*04:05 was absent in EOT1D children while was associated with LaOT1D (corrected p-value=1.4x10-2). InterpretationThis study uncovered that EOT1D holds a distinctive spectrum of HLA class II susceptibility loci, which includes risk factors overlapping with LaOT1D and discriminative genetic configurations. These findings warrant replication studies in larger multicentric settings and may impact target screening strategies and follow-up of young children with high T1D genetic risk. FundingEuropean Foundation for the Study of Diabetes, Maratona da Saude and Fundacao para a Ciencia e a Tecnologia.

Determining how high body-mass index (BMI) at different time points influences the risk of developing type two diabetes (T2D), and affects insulin secretion and insulin sensitivity, is critical. By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice-versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from high adulthood BMI on the risk of T2D and insulin related phenotypes using Mendelian randomisation and studies of T2D, and oral and intravenous measures of insulin secretion and sensitivity. We found that a 1.s.d. (= 1.97kg/m2) higher childhood BMI, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including an increased insulin sensitivity index ({beta} = 0.15 [0.067, 0.225], p = 2.79x10-4), and reduced fasting glucose ({beta} = -0.053 [-0.089, -0.017], p = 4.31x10-3). There was however little to no evidence of a direct protective effect on T2D (OR = 0.94 [0.85 - 1.04], p = 0.228), independently of genetic liability to adulthood BMI. Our results thus cumulatively provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty in biological pathway of these effects, and the limitations of this type of study. Research in ContextO_LIHigh BMI in adulthood is associated with higher risk of type two diabetes, coupled with lower insulin sensitivity and secretion. C_LIO_LIRichardson et al [2020] used genetics to show that high BMI in childhood does not appear to increase the risk of type diabetes independently from its effect on adult BMI. C_LIO_LIWe asked: does high childhood BMI affect insulin related traits such as fasting glucose and insulin sensitivity, independently of adulthood BMI? C_LIO_LIWe used genetics to show that high childhood BMI has a protective effect on seven insulin sensitivity and secretion traits, including fasting glucose and measures of insulin sensitivity and secretion, independently of adulthood BMI. C_LIO_LIOur work has the potential to turn conventional understanding on its head - high BMI in childhood improves insulin sensitivity (when adjusting for knock on effects to high adult BMI) and opens up important questions about plasticity in childhood and compensatory mechanisms. C_LI

BackgroundCVD prediction models do not perform well in people with diabetes. We therefore aimed to identify novel predictors for six facets of CVD, (including coronary heart disease (CHD), Ischemic stroke, heart failure (HF), and atrial fibrillation (AF)) in people with T2DM. MethodsAnalyses were conducted using the UK biobank and were stratified on history of CVD and of T2DM: 459,142 participants without diabetes or a history of CVD, 14,610 with diabetes but without CVD, and 4,432 with diabetes and a history of CVD. Replication was performed using a 20% hold-out set, ranking features on their permuted c-statistic. ResultsOut of the 600+ candidate features, we identified a subset of replicated features, ranging between 32 for CHD in people with diabetes to 184 for CVD+HF+AF in people without diabetes. Classical CVD risk factors (e.g. parental or maternal history of heart disease, or blood pressure) were relatively highly ranked for people without diabetes. The top predictors in the people with diabetes without a CVD history included: cystatin C, self-reported health satisfaction, biochemical measures of ill health (e.g. plasma albumin). For people with diabetes and a history of CVD top features were: self-reported ill health, and blood cell counts measurements (e.g. red cell distribution width). We additionally identified risk factors unique to people with diabetes, consisting of information on dietary patterns, mental health and biochemistry measures. Consideration of these novel features improved risk classification, for example per 1000 people with diabetes 133 CVD and 165 HF cases appropriately received a higher risk. ConclusionThrough data-driven feature selection we identified a substantial number of features relevant for prediction of cardiovascular risk in people with diabetes, the majority of which related to non-classical risk factors such as mental health, general illness markers, and kidney disease.

BackgroundThe importance of adolescent cardiorespiratory fitness for long-term risk of type 2 diabetes (T2D) remains poorly investigated, and whether the association is influenced by unobserved familial confounding is unknown. MethodsWe conducted a sibling-controlled cohort study based on all Swedish men who participated in mandatory military conscription examinations from 1972 to 1995 around the age of 18, and who completed standardized cardiorespiratory fitness testing. The outcome was T2D, defined as a composite endpoint of diagnosis in inpatient or specialist outpatient care, or dispensation of antidiabetic medication, until 31 December 2023. Findings1 124 049 men, of which 477 453 were full siblings, with a mean age of 18.3 years at baseline were included. During follow-up, 115 958 men (48 089 full siblings) experienced a first T2D event at a median age of 53.4 years. Compared to the first decile of fitness, higher fitness levels were associated with a progressively lower risk of T2D. In cohort analysis, the hazard ratio (HR) in the second decile was 0.83 (95% CI, 0.81 to 0.85), with a difference in the standardized cumulative incidence at age 65 of 4.3 (3.8 to 4.8) percentage points, dropping to a HR of 0.38 (0.36 to 0.39; incidence difference 17.8 [17.3 to 18.3] percentage points) in the tenth decile. When comparing full siblings, and thus controlling for all unobserved behavioral, environmental, and genetic confounders that they share, the association replicated, although with attenuation in magnitude. The HR in the second decile was 0.89 (0.85 to 0.94; incidence difference 2.3 [1.3 to 3.3] percentage points), and in the tenth decile it was 0.53 (0.50 to 0.57; incidence difference 10.9 [9.7 to 12.1] percentage points). Hypothetically shifting everyone in the first decile of fitness to the second decile was estimated to prevent 7.2% (6.4 to 8.0) of cases at age 65 in cohort vs. 4.6% (2.6 to 6.5) in full-sibling analysis. The association was similar in those with overweight as in those without. InterpretationHigher levels of adolescent cardiorespiratory fitness are associated with lower risk of T2D in late adulthood, with clinically relevant associations starting already from very low levels of fitness, and similarly in those with overweight compared to those without. The association replicates, but becomes weaker, after adjusting for unobserved familial confounders shared between full siblings. This suggests that adolescent cardiorespiratory fitness is a robust marker of long-term T2D risk, but that conventional observational analysis may yield biased estimates. FundingNone. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSType 2 diabetes is a growing public health issue, affecting at least half a billion people globally. Modifiable factors such as physical activity and the closely related trait cardiorespiratory fitness, which are inversely associated with type 2 diabetes, are declining, particularly among youth. Since these traits track from youth into adulthood, early-life interventions might have important implications for prevention. However, previous studies have typically focused on middle-aged individuals, leaving gaps in understanding whether fitness in youth is associated with type 2 diabetes in the long-term. Moreover, they have not been designed to adequately account for unobserved confounders. Triangulating the evidence across different methods, such as using sibling comparison analysis, would be important to obtain more accurate and reliable estimates of the causal relationship. Added value of this studyIn this nationwide sibling-controlled cohort study encompassing more than 1 million young men, of which half a million were full siblings, higher levels of adolescent cardiorespiratory fitness were associated with a substantially lower risk of developing type 2 diabetes up to five decades later. The association was clinically relevant already from low levels of fitness, and it appeared similar in those with overweight as in those without overweight. While the association replicated after adjusting for unobserved familial confounders shared between full siblings, the magnitude of association attenuated by an amount that appeared clinically relevant. For example, the incidence differences between deciles of fitness were about 40% smaller in sibling-comparison analyses as compared to cohort analysis, and the preventable share of type 2 diabetes associated with hypothetical interventions shifting the population-level of fitness was reduced by about one-third. Implications of all the available evidenceAdolescent cardiorespiratory fitness is a strong marker of long-term risk of type 2 diabetes, both in those with and without overweight. These findings render support to large-scale surveillance of fitness from a prevention perspective, and if the findings are confirmed using other lines of causal analysis, they may render support to interventions targeting fitness already from a young age. Yet, these findings also highlight the importance of triangulation for obtaining more reliable evidence of the magnitude of association, and shed light on the pitfalls of conventional observational analysis which may yield biased estimates.

Risk prediction models for type 2 diabetes can be useful for the early detection of individuals at high risk. However, models may also bias clinical decision-making processes, for instance by differential risk miscalibration across racial groups. We investigated whether the Prediabetes Risk Test (PRT) issued by the National Diabetes Prevention Program, and two prognostic models, the Framingham Offspring Risk Score, and the ARIC Model, demonstrate racial bias between non-Hispanic Whites and non-Hispanic Blacks. We used National Health and Nutrition Examination Survey (NHANES) data, sampled in six independent two-year batches between 1999 and 2010. A total of 9,987 adults without a prior diagnosis of diabetes and with fasting blood samples available were included. We calculated race- and year-specific average predicted risks of type 2 diabetes according to the risk models. We compared the predicted risks with observed ones extracted from the US Diabetes Surveillance System across racial groups (summary calibration). All investigated models were found to be miscalibrated with regards to race, consistently across the survey years. The Framingham Offspring Risk Score overestimated type 2 diabetes risk for non-Hispanic Whites and underestimated risk for non-Hispanic Blacks. The PRT and the ARIC models overestimated risk for both races, but more so for non-Hispanic Whites. The risk of type 2 diabetes extracted from these landmark models were more severely overestimated for non-Hispanic Whites compared to non-Hispanic Blacks, potentially resulting in a larger fraction of non-Hispanic Whites being prioritized for a preventive intervention, but also more likely to be overdiagnosed and overtreated, with a larger fraction of non-Hispanic Blacks being potentially underprioritized and undertreated.

We developed a multi-Polygenic risk score (multiPRS) to predict the risk of nephropathy, stroke, and myocardial infarction in people with type 2 diabetes of European descent. The underrepresentation of non-European populations remains a major challenge in genomics research. Objective: To evaluate the ability of our multiPRS model to accurately predict these complications in patients of African and South Asian descents. Method: The multiPRS was developed using 4098 participants with type 2 diabetes of European origin from the ADVANCE trial. Its predictive performance was tested on 17,574 White British, 1,145 South Asian and 749 African participants with type 2 diabetes from the UK Biobank using different machine learning prediction models, including techniques tailored for imbalanced datasets. Results: Globally, linear discriminant analysis and logistic regression had the best performance to predict the risk of nephropathy, stroke, and myocardial infarction in people with type 2 diabetes for the three ethnic groups. Mondrian Cross-Conformal Prediction method when added to logistic regression improved the AUROC values and case detection, particularly in South Asians and Africans, while in White British, performance varied by phenotype. Conclusion: Logistic regression, when used as the underlying model within the Modrian Cross-Conformal Prediction framework, improved the prediction performance, with a confidence level, of diabetes complications and allows better translation of a multiPRS derived from European populations to other ethnic groups.

Background Glycated haemoglobin (HbA1c) underpins type 2 diabetes (T2D) and prediabetes management worldwide and reflects both glycaemia and erythrocyte biology. A missense variant in PIEZO1 (rs563555492T), carried by 1 in 12 South Asians, has been associated with a nonglycaemic reduction in HbA1c. We aimed to further characterise this association and evaluate its clinical consequences. Methods We undertook genetic and linked health data analyses across two cohorts: 19,898 (37.4% female) South Indians from the Madras Diabetes Research Foundation (MDRF) and 43,011 (54.4% female) British Bangladeshis and British Pakistanis in Genes & Health. In MDRF, we tested associations with glycaemic and erythrocytic traits using additive genetic models. In Genes & Health we modelled diagnosis of prediabetes, T2D, and diabetic eye disease using flexible parametric survival models. Ten-year absolute risks were estimated for a population aged 40-50 years. Findings PIEZO1 rs563555492T was associated with erythrocytic traits and lower HbA1c, but not with fasting glucose, postprandial glucose, or C-peptide. This variant reduced risk of prediabetes (HR 0.63, 95% CI 0.58-0.69) and T2D (0.85, 0.78-0.93) diagnosis, and increased risk of diabetic eye disease among individuals with T2D (1.20, 1.01-1.43). Modelling suggested approximately 1,019 missed prediabetes and 303 missed T2D diagnoses per 100,000 adults over 10 years. Interpretation An ancestry-enriched PIEZO1 variant is associated with lower HbA1c independent of glycaemia, reduced prediabetes and T2D diagnosis suggesting delayed detection, and increased complication risk. Reliance on HbA1c may systematically underestimate glycaemic risk in a substantial minority of South Asians. Funding The Wellcome Trust; NIHR