Background and Aims To elucidate the genetic architecture of blood pressure (BP) and heart rate (HR) during early life and assess their potential relevance to adult health outcomes.Methods The largest genome-wide association study (GWAS) meta-analyses to date of childhood systolic BP, diastolic BP, pulse pressure, and mean arterial pressure (n = 28 425) and HR (n = 22 565) were conducted in children of European ancestry aged 4-17 years. Follow-up analyses included comparisons with adult GWAS results, polygenic risk score (PRS) analyses in independent cohorts of diverse ancestries, and a phenome-wide association study in the UK Biobank.Results Eight genome-wide significant loci were identified for childhood BP (KIAA2013, CACNB2, PLCE1, PAX2, COL4A2, RP11-236L14.1, CFDP1, TPX2) and three loci for childhood HR (CCDC141, ACHE, MYH6); all novel in children but previously reported in adults. Childhood PRSs explained up to 1.6% of BP variance and 5.2% of HR variance among children of European ancestry. Genetic correlations between childhood and adulthood BP traits were moderate (rg = 0.4-0.7), suggesting age-specific genetic effects on BP. In the UK Biobank, higher childhood BP PRS levels were significantly associated with a broad range of adult health outcomes, particularly cardiometabolic outcomes such as hypertension, angina, myocardial infarction, and cardiovascular disease-related mortality.Conclusions These findings advance the understanding of the genetic architecture of childhood BP and HR and provide compelling genetic evidence linking childhood BP to a broad spectrum of adult health outcomes-particularly cardiometabolic conditions-which may inform targeted prevention strategies from a young age.

Short Abstract Emerging evidence indicates that oral and systemic health are interconnected, yet the basis of this relationship remains incompletely understood. In a genome-wide association study of objectively measured dental caries in permanent dentition among Danish children and adolescents (DC CA ) (N = 151,521), we identified 14 independent loci. Genes at DC CA -associated loci were enriched for expression in immune, secretory and epithelial cell populations. We found genetic correlations and evidence for shared causal variants with several cardiometabolic traits. Leveraging data from UK Biobank (N max = 501,936) and independent pediatric cohorts (N max = 3,412), we showed that genetic liability to DC CA associated with dentures, risk of coronary artery disease and type 2 diabetes in adults, and with HbA1C, lipid, liver enzyme levels, and plasma proteins implicated in oral, metabolic and hepatic biology in both populations. Our results provide new insights into the genetic architecture underlying the relationship between DC CA and cardiometabolic disease.

Abstract Background Type 2 diabetes (T2D) is a leading cause of morbidity and mortality worldwide. Despite the availability of multiple glucose-lowering agents, only half of individuals with T2D achieve the recommended HbA1c target of < 7.0%. Precision medicine approaches that leverage patient-specific markers offer a promising strategy to improve therapeutic outcomes. The PAM gene encodes the sole enzyme responsible for amidating bioactive hormones, including GLP-1, and harbors two hypomorphic T2D-risk alleles (p.D563G and p.S539W); however, whether PAM regulates GLP-1, a key amidated incretin hormone, and whether this influences response to GLP-1 receptor agonist (GLP-1RA) therapy, remains unknown. Methods PAM amidation activity, postprandial GLP-1 levels, and the incretin effect were measured in carriers of PAM T2D-risk alleles and matched non-carriers from the Oxford Biobank in a prospective observational study and in Danish cohorts. Inducible whole-body Pam knockout mice were generated; gastric emptying was assessed by paracetamol absorption assay with and without exendin-4. Glycemic response to GLP-1RAs was evaluated in a meta-analysis of 1,119 participants across three cohorts (IMI-DIRECT, GoDARTS, PRIBA), with comparative assessment of sulphonylurea, metformin, and DPP-4 inhibitor response. Results Carriers of p.S539W and p.D563G alleles demonstrated 52% and 20% reductions in serum PAM amidation activity, respectively. Both human carriers and Pam knockout mice exhibited elevated circulating GLP-1 levels; however, p.S539W carriers showed an 18% reduction in endogenous GLP-1 sensitivity. PamKO mice displayed accelerated gastric emptying that was refractory to exendin-4, alongside impaired cAMP signaling downstream of the GLP-1 receptor in the pylorus. In the clinical meta-analysis, p.S539W carriers showed a significantly attenuated HbA1c reduction following GLP-1RA therapy (− 0.69% vs. − 1.24% in non-carriers; p = 0.025), representing a 44% relative loss of glycemic benefit; only 11.5% of carriers achieved HbA1c < 7% compared with 25.3% of non-carriers. No differences in response to sulphonylureas, metformin, or DPP-4 inhibitors were observed. Conclusions Hypomorphic PAM T2D-risk alleles reduce amidating enzyme activity, elevate circulating GLP-1 levels, and impair GLP-1 post-receptor signaling, culminating in a selective and clinically meaningful reduction in GLP-1RA efficacy. These findings establish PAM genotype as a novel pharmacogenomic determinant of GLP-1RA response, supporting its incorporation into precision medicine frameworks to optimize drug selection in T2D management. Trial registration NCT02723110, NCT02465515 and NCT01144338.

Alcohol is an ancient and enduring component of the human diet, yet it is a dose-dependent cytotoxin and teratogen, raising the possibility that endogenous, state-dependent mechanisms constrain intake. Growth differentiation factor 15 (GDF15) is an endocrine hormone that rises during pregnancy—predominantly via secretion from blastocyst-derived placental trophoblasts into the maternal circulation—and is also induced in other tissues, particularly hepatocytes, by toxins and cellular stress. However, its function in humans remains unclear. Here, we show that circulating GDF15 levels are elevated 5-fold in individuals with alcohol dependence, identify a rare loss-of-function variant in the GDF15 receptor gene GFRAL associated with approximately 2.6 additional UK alcohol units (~21 g ethanol) per week, and demonstrate that recombinant GDF15 reduces alcohol drinking in mice. Collectively, these findings support a model in which GDF15 acts as an endocrine signal induced by chronic alcohol exposure—and potentially during pregnancy—to limit alcohol intake in humans.

Objective The aim of this study was to assess whether daily step counts and genetic risk interact to influence the risk of developing type 2 diabetes.Research Design and Methods We analyzed data from 9501 participants in the All of Us Research Program with both genetic and wearable device-derived physical activity data and without diabetes at baseline and a median age of 56 years (42-66). Physical activity was quantified using daily step counts. Genetic risk was assessed using a global polygenic score. Incident type 2 diabetes was identified using electronic health record-linked diagnostic codes. Multivariable Cox proportional hazards models estimated hazard ratios (HRs) for type 2 diabetes across genetic risk and physical activity levels. We tested for additive interaction using the relative excess risk due to interaction (RERI). In secondary analyses, we used physical-activity intensity measures using wearable-derived and self-reported intensity levels.Results Type 2 diabetes incidence rates ranged from 4.1 per 1000 person-years (95% CI, 2.5-5.7) in individuals with high physical activity and low genetic risk to 18.4 (95% CI, 15.2-21.6) in those with low physical activity and high genetic risk (HR, 6.2 (95% CI: 3.97, 9.6)). A significant additive interaction was observed (RERI, 0.20; 95% CI, 0.04-0.36; P = .007), with 15% (95% CI, 2-27) of excess risk attributed to the interaction. Similar interaction patterns were found using device-based intensity metrics and self-reported physical activity measures.Conclusion These findings provide evidence of additive interactions between genetic risk and physical activity, underscoring the potential value of integrating genomic and device-derived data to identify individuals who would more likely benefit from increasing physical activity.

Background The interplay between genetic susceptibility and clinical risk for incident atrial fibrillation (AF) is unclear.Methods We used a case-cohort study design and included AF cases and a randomly drawn subcohort of 4040 participants from the Danish Diet, Cancer and Health cohort. The simplified version of the Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF) risk score was used to quantify individual participant clinical risk of incident AF as low (0–3 points), high (4–6 points) and very high risk (7–14 points). We calculated individual participant Genetic Risk Scores (GRS) from 142 variants to categorise participants as low (quintile 1), intermediate (quintile 2–4) or high (quintile 5) genetic risk of AF. We used weighted Cox proportional hazards regression to quantify risk of incident AF according to FIND-AF risk and GRS and assessed the relative excess risk due to interaction (RERI) for interaction on an additive scale.Results During a median follow-up of 12.9 years, 3094 participants developed AF. Compared with individuals with low FIND-AF risk score and low GRS, the multivariable-adjusted HR for AF was 3.47 (95% CI 2.64 to 4.55) for those with high FIND-AF risk score and high GRS and 12.76 (95% CI 5.07 to 32.11) for those with very high FIND-AF risk score and high GRS. The RERI was 0.56 (95% CI 0.43 to 0.70), indicating a positive additive interaction between GRS and FIND-AF risk score.Conclusions Genetic susceptibility and clinical risk interacted on an additive scale to elevate AF risk. These results highlight the need for future research on prevention and screening among individuals with both high genetic and clinical risk for AF.

An intronic variant (rs10830963) in MTNR1B (encoding the melatonin receptor type 2 [MT2]) has been shown to strongly associate with impaired glucose regulation and elevated type 2 diabetes prevalence. However, MTNR1B missense variants have shown conflicting results on type 2 diabetes. Thus, we aimed to gain further insights into the impact of MTNR1B coding variants on type 2 diabetes prevalence and related phenotypes. We conducted a cross-sectional study, performing MTNR1B variant burden testing of glycaemic phenotypes (N=248,454, without diabetes), other cardiometabolic phenotypes (N=330,453) and type 2 diabetes prevalence (case–control study; N=263,739) in the UK Biobank. Similar burden testing with glycaemic phenotypes was performed in Danish Inter99 participants without diabetes (N=5711), and type 2 diabetes prevalence (DD2 cohort serving as cases [N=2930] and Inter99 serving as controls [N=4243]). Finally, we evaluated the effects of MTNR1B variants on the melatonin-induced glucose regulation response in a recall-by-genotype study of individuals without diabetes. In the UK Biobank, MTNR1B variants were not associated with cardiometabolic phenotypes, including type 2 diabetes prevalence, except that carriers of missense MTNR1B variants causing impaired MT2 signalling exhibited higher HbA1c levels compared with non-carriers (effect size, β, 0.087 SD [95 https://dd2.dk/forskning/ansoeg-om-data . Access to UK Biobank data can be requested through the UK Biobank website ( https://www.ukbiobank.ac.uk/enable-your-research ).

Circulating proteins play essential roles in complex diseases, yet protein quantitative trait locus (pQTL) studies in non-European, isolated populations remain limited. We analyzed genotypes and plasma proteomics data (Olink Target 96 Inflammation and Cardiovascular II panels) from 3,707 Greenlandic individuals (mean age: 47.9 years; 54.5% female), using linear mixed models to account for relatedness and population structure. Among 177 proteins, we identified 251 primary pQTLs—235 additive (84 cis, 8 semi-cis, 12 semi-trans, and 131 trans) and 16 recessive (1 cis, 2 semi-trans, and 13 trans)—48 secondary pQTLs, and 70 (28%) novel associations. Several common pQTLs in Greenlanders explained a substantial proportion of variance in protein levels (>30% for interleukin [IL]-27, IgG Fc receptor II-b, IL-16, and Galectin-9) compared to Europeans. A novel cis pQTL for IL-6 (rs7802307) was associated with increased cardiovascular disease risk based on registry data. Associations between Arctic-enriched variants in CPT1A (rs80356779), HNF1A (rs2135845768), TBC1D4 (rs61736969), LDLR (rs730882082), and PCSK9 (rs4609471) and altered protein abundance provide mechanistic insights into cardiometabolic disease in this population. These findings underscore the importance of pQTL studies in genetically diverse populations.

Greenlandic Inuit and other indigenous populations are underrepresented in genetic research1,2, leading to inequity in healthcare opportunities. To address this, we performed analyses of sequenced or imputed genomes of 5,996 Greenlanders with extensive phenotypes. We quantified their historical population bottleneck and how it has shaped their genetic architecture to have fewer, but more common, variable sites. Consequently, we find twice as many high-impact genome-wide associations to metabolic traits in Greenland compared with Europe. We infer that the high-impact variants arose after the population split from Native Americans and thus are Arctic-specific, and show that some of them are common due to not only genetic drift but also selection. We also find that European-derived polygenic scores for metabolic traits are only half as accurate in Greenlanders as in Europeans, and that adding Arctic-specific variants improves the overall accuracy to the same level as in Europeans. Similarly, lack of representation in public genetic databases makes genetic clinical screening harder in Greenlandic Inuit, but inclusion of Greenlandic data remedies this by reducing the number of non-causal candidate variants by sixfold. Finally, we identify pronounced genetic fine structure that explains differences in prevalence of monogenic diseases in Greenland and, together with recent changes in mobility, leads to a predicted future reduction in risk for certain recessive diseases. These results illustrate how including data from Greenlanders can greatly reduce inequity in genomic-based healthcare.

Insulin sensitivity (IS) is a key determinant of metabolic health and may share genetic factors with obesity-related traits. Previous large-scale genetic studies have identified variants associated with IS as well as obesity related traits like body mass index (BMI) and waist-to-hip ratio (WHR). Notably, many of these associations are shared across traits, indicating a potential genetic overlap. However, the genetic intersection between IS and obesity-related traits remains underexplored. To explore this gap, we investigated associations between six IS indices, including fasting and post-glucose load measures, and genetic variants linked to BMI and WHR to determine their influence on IS and related cardiometabolic traits. To achieve this, we calculated six IS indices using fasting and oral glucose tolerance test (OGTT) data from 5,007 non-diabetic individuals, grouping them into fasting, OGTT0,120, and OGTT0,30,120 categories. A total of 678 BMI-associated and 265 WHR-associated genetic variants were analysed using linear regression, adjusting for age and sex, with sex-specific analyses for WHR. Analyses were conducted with and without BMI adjustments and corrected for multiple testing (padj). Additionally, we explored the relationship between IS-linked variants and their associations with type 2 diabetes (T2D), coronary artery disease (CAD) and stroke. Among the 678 BMI-associated variants, 100 showed nominal associations (p < 0.05) with at least one IS index; and 20 remained significant after multiple testing correction (padj < 0.05) when not adjusting for BMI. After adjusting for BMI, 70 variants retained nominal associations, and six remained significant (padj < 0.05). In sex-specific analyses of the 265 WHR-associated variants, 12 variants were associated in females when adjusted for BMI, whereas no significant associations were observed in males. Furthermore, BMI- and WHR-associated variants linked to decreased IS, such as those in FTO and VPS13C loci, were also associated with increased T2D and stroke risk, whereas IS-increasing variants, including those in VPS13C and PPARG, were linked to lower T2D and stroke risk, with some, like THADA, showing opposing effects on CAD. This study offers insights into genetic variants that influence both IS and obesity-related traits, revealing BMI- and WHR-associated variants with both positive and negative effects on IS and their potential impact on cardiometabolic health.

FGF21 is a hormone secreted from the liver in response to various nutritional stressors, suggested to act to balance dietary intake through negative feedback regulation. This meal study aimed to investigate two different potential nutrient interactions on postprandial FGF21 secretion in healthy human participants: 1) between intake of alcohol and protein, and 2) between intake of alcohol and vitamin A (retinol). In a 4-arm, randomized, double-blinded, cross-over meal study (NCT06105476), postprandial circulating concentrations of FGF21, glucose, insulin, ethanol, and acetate were compared after intake of four different test drinks containing alcohol, alcohol + protein, alcohol + retinol, or retinol in 27 healthy humans. The postprandial FGF21 response to the alcohol + protein drink was severely attenuated compared with the alcohol drink. The FGF21 response to the alcohol + retinol drink was similar to the alcohol drink, whereas there was no FGF21 response to the drink with retinol only. In conclusion, intake of protein inhibited the secretory FGF21 response to alcohol intake, whereas retinol intake did not appear to influence FGF21 secretion.NEW & NOTEWORTHY The hepatic hormone FGF21 is regulated by dietary intake. The results of this human meal study suggest that coconsumption of protein inhibits alcohol-induced FGF21 secretion in humans, similar to how protein intake previously has been shown to inhibit sugar-induced FGF21 secretion. This indicates that dietary protein is a consistent downregulator of FGF21. We found no indication that intake of retinol influences FGF21 regulation.

BACKGROUND:Taste liking, a complex trait, plays an important role in food choice and eating behavior, thereby influencing risk of diet-related diseases. OBJECTIVES:This study aimed to identify novel loci that could explain differences in liking of 5 basic tastes, fat sensation, and 2 oral sensations, represented by several food items. METHODS:Liking scores were derived using a newly developed taste liking questionnaire (TasteLQ), validated in the Danish population. We conducted a genome-wide association study (GWAS) of liking of 6 modalities (sweet, salty, sour, bitter-astringency, umami, and pungency) and 9 factors representing modality subgroups among 6,437 Danish adults. As a secondary analysis, GWASs of 44 single food items from TasteLQ were also undertaken. RESULTS:We identified 1 genome-wide significant variant, rs170518 (minor allele frequency = 0.16), on chromosome 5, associated with liking of an umami factor characterized by glutamate-rich food items [P = 3.7 × 10-8, beta = 0.14 standard deviation (SD) (standard error (SE)) = 0.03]. When analyzing individual food items, 4 single nucleotide polymorphisms (SNPs) within 1 locus, annotated to the bitter taste receptor gene, TAS2R38, were associated with liking of bitter-tasting rocket salad. Finally, our data confirmed some of the previously associated genomic variants with taste perception, food liking, and intake. CONCLUSIONS:Although our findings provide insight into loci involved in taste liking, they remain preliminary and warrant additional validation due to lack of replication in an independent population and limited number of genome-wide significant associations.

Objectives: Population studies have identified common genetic variants contributing substantially to the burden of diabetes in Greenland. However, the handling of suspected monogenic diabetes in diabetes clinics in Greenland has not been described. In this study we aimed to describe the referral rate, prevalence, and genetic causes of clinically identified monogenic diabetes in Greenland. Methods: All diabetes patients in Greenland referred for genetic testing due to suspected monogenic diabetes between 2014 and July 2022 were tallied. Targeted short-read sequencing and Sanger sequencing of probands and their family members were used to screen for potentially deleterious variants in the maturity-onset diabetes of the young (MODY) genes GCK, HNF1A, HNF1B, and HNF4A. Clinical data were extracted from the electronic medical records, and whole-genome sequencing was performed for families with potentially deleterious variants for genetic ancestry analysis. Results: Between 2014 and July 2022, 58 probands were referred for genetic testing, equivalent to 0.1% of the population. Five variants were identified: GCK p.F133L, GCK p.D205E, HNF1A c.1108G>T, HNF1B p.Q182*, and HNF4A -178A>G. These variants were found in 11 probands and 19 family members, equivalent to a population prevalence of monogenic diabetes of 0.05%. Local ancestry analysis revealed that all the variants were found exclusively in Inuit haplotypes, despite all individuals being admixed with both Inuit and European genetic ancestry. Conclusions: The rate of referral and prevalence of monogenic diabetes is substantially higher in Greenland than in other populations, and both rare and more common population-specific variants of (c) 2025 The Author(s). Published on behalf of the Canadian Diabetes Association. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Regular physical activity is a well-established protective factor against type 2 diabetes (T2D), yet large variability exists in its metabolic benefits. Genetic factors could partially explain this variability, but studies examining gene-by-physical activity interactions in incident T2D are limited. Here, we used data from 10,627 participants from two population-based cohorts in the United States (All of Us Research Program) and Denmark (Inter99) to investigate how genetic risk and physical activity jointly influence T2D risk. Genetic risk was characterized using a polygenic score for T2D. Physical activity was measured using wearable devices in All of Us and self-reported questionnaires in Inter99. In All of Us, T2D incidence rates per 1,000 person-years were 2.1 (95% CI: 0.3, 3.9) for individuals with high physical activity and low genetic risk and 18.3 (95% CI: 13.4, 23.3) for those with low physical activity and high genetic risk (multivariable-adjusted hazard ratio of 6.9 (95% CI: 3.3, 14.4)). The interaction between physical activity and genetic risk deviated from additivity, with a relative excess risk due to interaction of 0.40 (95% CI: 0.11, 0.69; p = 0.003), accounting for 27% (95% CI: 5, 50) of excess T2D risk. These results were replicated in Inter99, where 44% (95% CI: 22, 67) of excess T2D risk was attributed to the interaction. These findings provide consistent evidence of interactions between genetic risk and physical activity on T2D risk, indicating that increasing physical activity among those with high genetic risk may represent an effective strategy for precision T2D prevention. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement We gratefully acknowledge All of Us and Inter99 participants for their contributions, without whom this research would not have been possible. The All of Us Research Program is supported by grants 1 OT2 OD026549, 1 OT2 OD026554, 1 OT2 OD026557, 1 OT2 OD026556, 1 OT2 OD026550, 1 OT2 OD 026552, 1 OT2 OD026553, 1 OT2 OD026548, 1 OT2 OD026551, 1 OT2 OD026555, IAA AOD21037, AOD22003, AOD16037, and AOD21041 (regional medical centers); grant HHSN 263201600085U (federally qualified health centers); grant U2C OD023196 (data and research center); 1 U24 OD023121 (Biobank); U24 OD023176 (participant center); U24 OD023163 (participant technology systems center); grants 3 OT2 OD023205 and 3 OT2 OD023206 (communications and engagement); and grants 1 OT2 OD025277, 3 OT2 OD025315, 1 OT2 OD025337, and 1 OT2 OD025276 (community partners) from the National Institutes of Health (NIH). This study was also supported by the Novo Nordisk Foundation grant NNF23SA0084103 and the European Union. JM was additionally supported by grants from the European Commission (HORIZON-EIC-2023-PATHFINDERCHALLENGES-01 - 101161509) and the EFSD/NNF Future Leaders Award (#0094134). RL was additionally supported by personal grants from the Novo Nordisk Foundation (Laureate award no. NNF20OC0059313) and the Danish National Research Fund (Chair DNRF161). TOK and MRC and were additionally supported by grants from the Novo Nordisk Foundation (NNF22OC0074128) and EFSD/Lilly European Diabetes Research Programme. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: N/A I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes To ensure privacy of participants, data used for this study are available to approved researchers following registration, completion of ethics training and attestation of a data use agreement through the All of Us Research Workbench platform, which can be accessed via https://workbench.researchallofus.org/login. Code used for this study can be made available to users of the All of Us Research Workbench platform by contacting our study team. Data from Inter99 are available upon request and approval.

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.

The genetics of beta-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)(1,2). Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies(3-7), large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants(10-14). Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size(15,16) and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing beta-cells(17,18). We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of beta-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from similar to 26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in beta-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology.

The combination of decreasing food intake and increasing energy expenditure represents a powerful strategy for counteracting cardiometabolic diseases such as obesity and type 2 diabetes1. Yet current pharmacological approaches require conjugation of multiple receptor agonists to achieve both effects2-4, and so far, no safe energy-expending option has reached the clinic. Here we show that activation of neurokinin 2 receptor (NK2R) is sufficient to suppress appetite centrally and increase energy expenditure peripherally. We focused on NK2R after revealing its genetic links to obesity and glucose control. However, therapeutically exploiting NK2R signalling has previously been unattainable because its endogenous ligand, neurokinin A, is short-lived and lacks receptor specificity5,6. Therefore, we developed selective, long-acting NK2R agonists with potential for once-weekly administration in humans. In mice, these agonists elicit weight loss by inducing energy expenditure and non-aversive appetite suppression that circumvents canonical leptin signalling. Additionally, a hyperinsulinaemic-euglycaemic clamp reveals that NK2R agonism acutely enhances insulin sensitization. In diabetic, obese macaques, NK2R activation significantly decreases body weight, blood glucose, triglycerides and cholesterol, and ameliorates insulin resistance. These findings identify a single receptor target that leverages both energy-expending and appetite-suppressing programmes to improve energy homeostasis and reverse cardiometabolic dysfunction across species.

Background Birth weight (BW) is associated with risk of cardiometabolic disease (CMD) in adulthood, which may depend on the state of obesity, in particular if developed at a young age. We hypothesised that BW and a polygenic score (PGS) for BW were associated with cardiometabolic risk and related plasma protein levels in children and adolescents. We aimed to determine the modifying effect of childhood obesity on these associations. Methods We used data from The cross-sectional HOLBAEK Study with 4263 participants (median [IQR] age, 11.7 [9.2, 14.3] years; 57.1% girls and 42.9% boys; 48.6% from an obesity clinic and 51.4% from a population-based group). We gathered information on BW and gestational age, anthropometrics, cardiometabolic risk factors, calculated a PGS for BW, and measured plasma proteins using Olink Inflammation and Cardiovascular II panels. We employed multiple linear regression to examine the associations with BW as a continuous variable and performed interaction analyses to assess the effect of childhood obesity on cardiometabolic risk and plasma protein levels. Findings BW and a PGS for BW associated with cardiometabolic risk and plasma protein levels in childhood and adolescence. Childhood obesity modified the associations between BW and measures of insulin resistance, including HOMA-IR (beta adj [95% CI per SD] for obesity: -0.12 [-0.15, -0.08]; normal weight: -0.04 [-0.08, 0.00]; Pinteraction = 0.004), c-peptide (obesity: -0.11 [-0.14, -0.08]; normal weight: -0.02 [-0.06, 0.02]; Pinteraction = 5.05E-04), and SBP SDS (obesity: -0.12 [-0.16, -0.08]; normal weight: -0.06 [-0.11, -0.01]; Pinteraction = 0.0479). Childhood obesity also modified the associations between BW and plasma levels of 14 proteins (e.g., IL15RA, MCP1, and XCL1; Pinteraction < 0.05). Interpretation We identified associations between lower BW and adverse metabolic phenotypes, particularly insulin resistance, blood pressure, and altered plasma protein levels, which were more pronounced in children with obesity. Developing effective prevention and treatment strategies for this group is needed to reduce the risk of future CMD. Copyright (c) 2024 The Author(s). Published by Elsevier B.V.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.