Background:Adult-onset diabetes comprises subgroups differing in pathophysiology, clinical presentation, and risk of comorbidities. We investigated early phenotypic differences between individuals who later developed diabetes, stratified by subgroup at diabetes diagnosis. Methods:We conducted a pooled analysis of nine prospective European cohorts with 3309 individuals developing incident diabetes and 13,963 age- and sex-matched controls without diabetes. Cases were assigned to previously defined cluster-based subgroups: severe autoimmune (SAID), insulin-deficient (SIDD), or insulin-resistant diabetes (SIRD), and moderate obesity- (MOD) or age-related diabetes (MARD). Clinical and metabolic characteristics were retroactively assessed for three time periods (>12, 6-12, 1-6 years) before diagnosis. Findings:Despite similarly high body mass index (BMI) in MOD and SIRD at diagnosis, MOD differed from controls already >12 years before diagnosis (31% higher than controls), while BMI increased progressively in SIRD (from 14% to 25% higher than controls). Compared to controls in period 1-6 years, age-, sex-, and BMI-adjusted insulin-glucose ratio was higher in SIRD, MOD and MARD at fasting (88%, 45% and 14%, respectively) and 120 min (110%, 70%, 26%) during an oral glucose tolerance test (p < 0.0001 for all), and the first-phase insulin-glucose ratio was higher in SIRD (23% [6; 43] p = 0.0072) but lower in SIDD (-30% [-37; -22], p < 0.0001) and MARD (-29% [-34; -24], p < 0.0001). The autoimmune subgroup SAID also exhibited features of metabolic syndrome. Despite differences in HOMA2-B and HbA1c at diagnosis, insulin and glucose levels did not differ significantly between the SIDD and MARD subgroups 1-6 years earlier suggesting a rapid deterioration in glycemic control in SIDD around diagnosis. Interpretation:Subgroups of diabetes display different trajectories of insulin resistance, insulin deficiency, and features of the metabolic syndrome before diagnosis. Funding:ERC, local governments, private foundations, University of Helsinki, and Research councils of Finland and Sweden.

[This corrects the article DOI: 10.1016/j.lanepe.2026.101715.].

PURPOSE:Proliferative diabetic retinopathy (PDR) is one of the leading causes of blindness in working-age adults. We have previously shown that the risk of PDR is significantly elevated in individuals with intrauterine exposure to famine. However, the genetic mechanisms mediating this association remain unknown. The aim of the current study was to investigate the molecular underpinnings of famine-related PDR by performing genome-wide association (GWAS) and interaction studies (GWIS). METHODS:We analysed n = 2925 patients with type 2 diabetes from the DOLCE cohort of Northern Ukraine, of whom n = 1364 were born during historical famine periods (1929-1949, including the Holodomor and World War II). PDR cases were defined as individuals with either diagnosed proliferative retinopathy, laser-treated diabetic retinopathy (DR) or blindness in either eye. GWAS and GWIS were performed using linear mixed model (LMM) adjusted for established risk factors and genetic relationship matrix. RESULTS:GWAS identified rs3795299 in IL22RA1 as the top signal (pLMM = 1.05 × 10-6), which was also the strongest gene in the gene-based analysis (p = 3.19 × 10-5), with suggestive enrichment of response to ketones (GO) and base excision repair (KEGG) pathways. In the GWIS, the strongest signal was rs1506783 in PAPPA2 (pLMM = 1.29 × 10-7). A second biologically credible candidate was rs2230805 in ABCA1 (pLMM = 4.44 × 10-6), reaching borderline genome-wide significance in gene-based analysis (p = 4.31 × 10-6). Interaction analyses showed suggestive enrichment for nucleosomal DNA binding (GO), tryptophan metabolism and glycerolipid metabolism (KEGG) pathways. Furthermore, at nominal significance, we validated variants in previously reported diabetic retinopathy-associated genes, including TCF7L2, SLC2A1, SLC2A11 and VDR in the GWAS, as well as 13 variants in genes including VEGF, VEGFR1, ANGPT1, PLXDC2, SELP and PON2 in the GWIS. CONCLUSION:Our findings suggest that famine-related PDR susceptibility involves distinct developmental programming mechanisms, including altered insulin-growth signalling (PAPPA2) and lipid metabolism (ABCA1), whereas immune-related pathways (IL22RA1) may contribute to the conventional glycaemia-driven route to PDR through VEGF-mediated angiogenesis. These genes represent potential therapeutic targets and emphasize the importance of the perinatal environment in lifelong vascular health and disease.

BACKGROUND:The global prevalence of type 2 diabetes has nearly doubled between 1990 and 2020. Genetic susceptibility confers increased risk of type 2 diabetes, but environmental exposures could modify this risk. We aimed to investigate how societal changes have affected the prevalence of type 2 diabetes in people with high and low genetic susceptibility, using chronological time as an indicator for these changes. METHODS:This longitudinal, population-based study included observations from four surveys from the HUNT study between 1984 and 2019, for participants aged 20-79 years. Diabetes was indicated by self-report and by non-fasting glucose or HbA1c in secondary analyses. We used a polygenic score for type 2 diabetes including more than 1 100 000 genetic variants to approximate genetic susceptibility. We used generalised estimating equations to estimate diabetes prevalence for the top and bottom deciles of the polygenic score at each timepoint, allowing for three-way interaction between time, polygenic score category, and 20-year age group. To explore underlying mechanisms, we did similar analyses for incidence by polygenic score category and 10-year mortality by diabetes status. FINDINGS:The study included 198 312 observations from 86 194 individuals. 45 654 (53·0%) of 86 194 participants were female and 40 540 (47·0%) were male. From the mid-1980s to the late 2010s, diabetes prevalence increased by 0·4 percentage points (pp; 95% CI 0·1-0·7) among the bottom decile of the polygenic score, 3·0 pp (2·7-3·2) among the mid-80%, and 9·1 pp (8·0-10·1) among the top decile. The difference in diabetes prevalence between the top and bottom deciles of genetic susceptibility increased over time for all age groups. Findings were similar when laboratory measurements were added to define hyperglycaemia. Additional analyses suggested an increasing diabetes incidence in participants aged 20-39 years in the top decile of genetic susceptibility, and improved diabetes survival from 1996-2006 to 2007-17. INTERPRETATION:Our findings suggest an increasing gap in diabetes prevalence between the most and least genetically susceptible. This suggests that people with a high genetic susceptibility to type 2 diabetes could be especially affected by a diabetogenic environment and highlights the need for public health measures. FUNDING:The study was funded by The Liaison Committee for education, research and innovation in Central Norway.

Abstract Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in Type 1 Diabetes (T1D), but a subset of individuals remains free from macrovascular or renal complications despite decades of hyperglycaemia and a significant risk factor burden. We used a targeted proteomic approach (Olink Cardiovascular panel III, targeting 92 proteins) to characterize the proteomic profile of cardiovascular resilience in T1D by comparing 92 patients with long-standing T1D (age 59.8 [53.2, 69.1], duration 40.0 [35.0, 45.2] years) free from macrovascular complications or nephropathy against a reference group of 57 T1D patients with accelerated vascular pathology (age 42.0 [32.0, 56.0], duration 22.0 [18.0, 27.0] years), proliferative retinopathy and/or nephropathy in relation to diabetes duration, termed Rapid Progressors (RP). Twenty proteins differed significantly between RP and Escapers (False Discovery Rate [FDR] < 0.05) after adjustment for age, sex, HbA1c, and eGFR: Caspase-3 was significantly higher in RP (Adjusted difference: + 2.12 Normalized Protein eXpression [NPX], p < 0.001). Proteins associated with platelet activation and leukocyte adhesion with increased levels in RP included Junctional Adhesion Molecule A (+ 1.40 NPX), Glycoprotein VI (GP6: + 1.29 NPX), and P-Selectin (+ 0.82 NPX) (all p < 0.001). PECAM-1 (+ 0.55 NPX) and TNFRSF14 (+ 0.43 NPX), were also elevated. RP also showed higher levels of metabolic and tissue-remodelling proteins; Transferrin Receptor (+ 0.53 NPX) and Fatty Acid Binding Protein 4 (+ 0.52 NPX), as well as higher Bleomycin Hydrolase, Trefoil Factor 3, GDF-15, U-PAR, and Cystatin B. Conversely, von Willebrand Factor (vWF) levels (− 1.35 NPX, p < 0.001) and Paraoxonase 3 (PON3) was lower in RP (− 0.34 NPX, p = 0.003). In conclusion, escaping complications in long-term T1D appears to be associated with active molecular mechanisms. Progression is marked by apoptosis (Caspase-3), fibrosis (CHI3L1) and platelet activation (GP6), whereas resilience is associated with a distinct signature involving higher vWF and PON3. These findings highlight a profound biological divergence between extreme T1D phenotypes and provide a foundation for further research into vascular resilience.

Introduction. The ESCAPER project explores cardiovascular resilience in individuals who, despite a high-risk factor burden-longstanding Type 1 Diabetes (T1D), obesity, or kidney failure-avoid or delay macrovascular complications. This suggests underlying protective mechanisms. Initiated in September 2022, this exploratory study aims to uncover and define these mechanisms, potentially leading to novel therapeutic targets in preventive medicine. Research design and methods. Participants from the Skåne region, Southern Sweden, are divided into three subgroups: (1) T1D patients (>30 years duration) without macrovascular complications or macroalbuminuria, (2) obese individuals with normal cardiac function and no cardiovascular medications, and (3) kidney failure patients awaiting transplantation with no arterial calcification, alongside respective controls. Comprehensive phenotyping includes 24-h blood pressure, ECG monitoring, vascular ultrasound, cardiac MRI, and ergospirometry (in a subgroup), along with laboratory investigations, including biomarker and omics analyses. Arterial biopsies are collected from kidney failure patients. The study leverages Swedish national medical registries for detailed follow-up of healthcare utilization, diagnoses, and prescriptions, enabling longitudinal outcome assessments. Results. Initial findings from 90 T1D patients and 31 obese individuals indicate well-managed cardiovascular risk factors. The T1D subgroup shows a mean BMI of 25.6 kg/m2 and HbA1c of 52 mmol/mol, while the obesity subgroup presents a BMI of 32.9 kg/m2 with normal glucose levels. Conclusions. ESCAPER has the potential to advance understanding of cardiovascular resilience and refine prevention strategies. Its comprehensive methodology and registry-based follow-up provide robust insights into protective mechanisms and long-term outcomes.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Background Diabetes subtypes with different clinical profiles have been found and replicated in adults. However, clinical heterogeneity of paediatric-onset diabetes remains unexplored. Better capture of different aetiologies of the disease could prove a powerful tool towards precision medicine. Methods We performed data-driven clustering analysis in patients with newly diagnosed diabetes (n = 3,064) from the Norwegian Childhood Diabetes Registry. Patients were stratified by autoantibody status and clustered based on five clinical variables: Age at diagnosis, fasting glucose, HbA1c, fasting C-peptide Z-score, and BMI Z-score. We assessed inter-cluster differences regarding severity of disease, early treatment needs, polygenic scores (PS), and serum biomarkers. Findings We identified two clusters of autoantibody-positive and three clusters of autoantibody-negative patients: 1) Childhood severe autoimmune diabetes (CSAID; n = 1482, 48.37 %), characterized by childhood-onset diabetes, milder disease presentation, unaltered lipidic profiles, higher Type 1 diabetes PS, and autoantibody positivity; 2) Adolescence severe autoimmune diabetes (ASAID; n = 1252, 40.86 %) with adolescent-onset of diabetes, more severe disease presentation, higher diabetic ketoacidosis, lipidic profiles signaling towards prolonged metabolic disease, and autoantibody positivity; 3) Childhood severe insulin-deficient diabetes (CSIDD; n = 106, 3.46 %) and 4) Adolescence severe insulin-deficient diabetes (ASIDD; n = 144, 4.70 %) with similar characteristics to CSAID and ASAID, respectively, but no autoantibody positivity; and 5) Adolescence severe insulin-resistant diabetes (ASIRD; n = 80, 2.61 %), the oldest group, with the highest C-peptide, BMI Z-score, and Type 2 diabetes PS. CSAID and ASAID presented similarities to previously described endotypes for type 1 diabetes. Interpretation We grouped patients with paediatric diabetes into five subgroups with varying clinical severity, genetic risk, and metabolic profiles. Similarities between autoantibody-positive and -negative clusters underscore the importance of adopting a personalised, multivariate approach to diabetes management that extends beyond autoantibody status. We hypothesise that our clusters may be connected to previously described endotypes of type 1 diabetes, facilitating patient classification without the need for pancreatic biopsies. Further understanding of this concept could help define the mechanisms involved in disease initiation, time to diagnosis, and progression. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols [https://github.com/ma-juarez/Pediatric\_Diabetes\_Clustering][1] ### Funding Statement This study was supported by the Research Council of Norway (#301178), the European Research Council (#101171420), and the University of Bergen. ### 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: Informed consent was obtained from all registry participants. The administrative board of the Norwegian Childhood Diabetes Registry approved the study protocol. The establishment of the Norwegian Childhood Diabetes Registry and initial data collection was based on a license from the Norwegian Data Protection Agency and approval from The Regional Committee for Medical Research Ethics. The Norwegian Childhood Diabetes Registry cohort is currently regulated by the Norwegian Health Registry Act. The study was approved by the ethical committee REK vest, reference 18836, University of Bergen, Norway. 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 Data from the Norwegian Childhood Diabetes Registry can be made available to researchers, provided approval from the Regional Committees for Medical and Health Research Ethics (REC), compliance with the EU General Data Protection Regulation (GDPR) and approval from the data owners. The consent given by the participants does not open for storage of data on an individual level in repositories or journals. Researchers who want access to data sets for replication should apply to the registry. Access to data sets requires approval from The Regional Committee for Medical and Health Research Ethics in Norway and an agreement with the Norwegian Childhood Diabetes Registry (www.oslodiabetes.no/childhood). [1]: https://github.com/ma-juarez/Pediatric_Diabetes_Clustering

Polyamines are regulatory metabolites with key roles in transcription, translation, cell signalling and autophagy1. They are implicated in multiple neurological disorders, including stroke, epilepsy and neurodegeneration, and can regulate neuronal excitability through interactions with ion channels2. Polyamines have been linked to pain, showing altered levels in human persistent pain states and modulation of pain behaviour in animal models3. However, the systems governing polyamine transport within the nervous system remain unclear. Here, undertaking a genome-wide association study (GWAS) of chronic pain intensity in the UK Biobank (UKB), we found a significant association between pain intensity and variants mapping to the SLC45A4 gene locus. In the mouse nervous system, Slc45a4 expression is enriched in all sensory neuron subtypes within the dorsal root ganglion, including nociceptors. Cell-based assays show that SLC45A4 is a selective plasma membrane polyamine transporter, and the cryo-electron microscopy (cryo-EM) structure reveals a regulatory domain and basis for polyamine recognition. Mice lacking SLC45A4 show normal mechanosensitivity but reduced sensitivity to noxious heat- and algogen-induced tonic pain that is associated with reduced excitability of C-polymodal nociceptors. Our findings therefore establish a role for neuronal polyamine transport in pain perception and identify a target for therapeutic intervention in pain treatment.

Aims Individuals with type 1 diabetes (T1D) are typically diagnosed at a young age and exposed to lifelong hyperglycaemia. Despite improved metabolic control, the risk of vascular complications remains challenging. However, some individuals remain free from developing major diabetic complications even after long duration, so-called “escapers”. This study investigated transcriptomic biomarkers linked to protection from microvascular complications in the Dialong cohort of long-standing T1D. Methods Differential gene expression analysis was conducted to identify differences between patients with long-term T1D without complications (non-progressors), those with vascular complications (progressors), and healthy controls without T1D. Results Among the differentially expressed genes, HERC2, S1PR3, RNASE3, and CD33 were significantly altered between non-progressors and progressors. Functional annotation analyses identified the strongest mechanisms across all groups to be linked to post-translational protein modification, such as Lys-Gly isopeptide bond involved in SUMOylation (p = 5e-17) - a biological process of covalent attachment and detachment of SUMO (Small Ubiquitin-like Modifier) small proteins to modify protein function. The second-ranked pathway was enrichment of DNA repair/damage (p = 6e-5), cell cycle and division (p = 4e-4), and immune response genes (p = 1e-7). Conclusions These findings underscore the role of post-translational protein modifications, DNA repair pathways and immune tolerance in protecting long-standing T1D patients from vascular complications.

We aimed to investigate the genetic associations of neuropathic pain in a deeply phenotyped cohort. Participants with neuropathic pain were cases and compared with those exposed to injury or disease but without neuropathic pain as control subjects. Diabetic polyneuropathy was the most common aetiology of neuropathic pain. A standardised quantitative sensory testing protocol was used to categorize participants based on sensory profile. We performed genome-wide association study, and in a subset of participants, we undertook whole-exome sequencing targeting analyses of 45 known pain-related genes. In the genome-wide association study of diabetic neuropathy (N = 1541), a top significant association was found at the KCNT2 locus linked with pain intensity (rs114159097, P = 3.55 x 10-8). Gene-based analysis revealed significant associations between LHX8 and TCF7L2 and neuropathic pain. Polygenic risk score for depression was associated with neuropathic pain in all participants. Polygenic risk score for C-reactive protein showed a positive association, while that for fasting insulin showed a negative association with neuropathic pain, in individuals with diabetic polyneuropathy. Gene burden analysis of candidate pain genes supported significant associations between rare variants in SCN9A and OPRM1 and neuropathic pain. Comparison of individuals with the "irritable" nociceptor profile to those with a "nonirritable" nociceptor profile identified a significantly associated variant (rs72669682, P = 4.39 x 10-8) within the ANK2 gene. Our study on a deeply phenotyped cohort with neuropathic pain has confirmed genetic associations with the known pain-related genes KCNT2, OPRM1, and SCN9A and identified novel associations with LHX8 and ANK2, genes not previously linked to pain and sensory profiles, respectively.

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.

IntroductionCluster analysis has previously revealed five reproducible subgroups of diabetes, differing in risks of diabetic complications. We aimed to examine the clusters’ predictive ability for vascular complications as compared with established risk factors in a general adult diabetes population.Research design and methodsParticipants from the second (HUNT2, 1995–1997) and third (HUNT3, 2006–2008) surveys of the Norwegian population-based Trøndelag Health Study (HUNT Study) with adult-onset diabetes were included (n=1899). To identify diabetes subgroups, we used the same variables (age at diagnosis, body mass index, HbA1c, homeostasis model assessment estimates of beta cell function and insulin resistance, and glutamic acid decarboxylase antibodies) and the same data-driven clustering technique as in previous studies. We used Cox proportional hazards models to investigate associations between clusters and risks of vascular complications and mortality. We estimated the C-index and R2to compare predictive abilities of the clusters to those of established risk factors as continuous variables. All models included adjustment for age, sex, diabetes duration and time of inclusion.ResultsWe reproduced five subgroups with similar key characteristics as identified in previous studies. During median follow-up of 9–13 years (differing between outcomes), the clusters were associated with different risks of vascular complications and all-cause mortality. However, in prediction models, individual established risk factors were at least as good predictors as cluster assignment for all outcomes. For example, for retinopathy, the C-index for the model including clusters (0.65 (95% CI 0.63 to 0.68)) was similar to that of HbA1c (0.65 (95% CI 0.63 to 0.68)) or fasting C-peptide (0.66 (95% CI 0.63 to 0.68)) alone. For chronic kidney disease, the C-index for clusters (0.74 (95% CI 0.72 to 0.76)) was similar to that of triglyceride/high-density lipoprotein ratio (0.74 (95% CI 0.71 to 0.76)) or fasting C-peptide (0.74 (95% CI 0.72 to 0.76)), and baseline estimated glomerular filtration rate yielded a C-index of 0.76 (95% CI 0.74 to 0.78).ConclusionsCluster assignment did not provide better prediction of vascular complications or all-cause mortality compared with established risk factors.

Background Neuropathic pain, caused by disease or injury to the somatosensory nervous system, affects 7-10 % of the population and severely impacts quality of life. Chronic pain with or without presence of a specific organ damage, the leading cause of disability worldwide, has a significant heritable component (39-50%). Understanding the genetic determinants of chronic pain in general and neuropathic pain in particular can enhance patient stratification, risk prediction, treatment targeting, and the development of new therapies. It is also crucial to understand the genetic relationship between these pain conditions and psychiatric disorders, as they frequently co-occur, to improve overall patient outcomes. Methods To investigate these genetic factors, we conducted two GWASs: one using data from the deeply-phenotyped DOLORisk cohort across 11 European centres for neuropathic pain (N = 2, 740), and another using the 2019 UK Biobank's enhanced pain phenotyping questionnaires for chronic pain intensity (N = 132, 552). To understand the causal relationships between related traits (such as those relevant to mental health, glycaemia, lipid, sleep, and inflammation) we generated Polygenic Risk Scores (PRS) for those traits and tested whether they were predictive of neuropathic pain intensity and chronic pain intensity. Results In the GWAS of diabetic neuropathic pain intensity, a significant association was identified at the KCNT2 locus (rs114159097, p = 3.55 × 10-8). In the GWAS of chronic pain intensity, we identified a total of 49 genome-wide significant SNPs, including two independent loci: rs3905668 (p = 1.35 × 10-8) near the MSL2 gene and rs10625280 (p = 2.74 × 10-8) mapped to the SLC45A4 gene. The PRS for depression and alcohol use disorder showed a consistent positive association with both chronic pain in general and neuropathic pain in particular in the DOLORisk and UK Biobank cohorts. In the DOLORisk study, neuropathic pain in diabetic polyneuropathy was positively associated with PRS for C-reactive protein and insomnia, and negatively associated with fasting insulin. Additionally, the PRS for HbA1c, anxiety, and triglycerides traits were positively associated with chronic pain intensity, while high-density lipoprotein cholesterol was negatively associated with chronic pain intensity in the UK Biobank. Discussion Our study highlights the significant genetic overlap between chronic pain intensity and neuropathic pain intensity with psychiatric disorders, emphasizing the complex interplay of genetic factors in these conditions. The consistent positive associations of PRS for depression and alcohol use disorder with both pain types underscore the importance of considering mental health in pain management strategies.

Polyamines are regulatory metabolites with key roles in transcription, translation, cell signalling and autophagy1. They are implicated in multiple neurological disorders including stroke, epilepsy and neurodegeneration and can regulate neuronal excitability through interactions with ion channels2. Polyamines have been linked to pain showing altered levels in human persistent pain states and modulation of pain behaviour in animal models3. However, the systems governing polyamine transport within the nervous system remain unclear. In undertaking a Genome Wide Association Study (GWAS) of chronic pain intensity in the UK-Biobank we found significant association with variants mapping to the SLC45A4 gene locus. In the mouse nervous system SLC45A4 expression is enriched in all sensory neuron sub-types within the dorsal root ganglion including nociceptors. Cell-based assays show that SLC45A4 is a selective plasma membrane polyamine transporter, whilst the cryo-EM structure reveals a novel regulatory domain and basis for polyamine recognition. Mice lacking SLC45A4 show normal mechanosensitivity but reduced sensitivity to noxious heat and algogen induced tonic pain that is associated with reduced excitability of peptidergic nociceptors. Our findings thus establish a role for neuronal polyamine transport in pain perception and identify a new target for therapeutic intervention in pain treatment.

Diabetes is associated with excess morbidity and mortality due to both micro- and macrovascular complications, as well as a range of non-classical comorbidities. Diabetes-associated microvascular complications are those considered most closely related to hyperglycaemia in a causal manner. However, some individuals with hyperglycaemia (even those with severe hyperglycaemia) do not develop microvascular diseases, which, together with evidence of co-occurrence of microvascular diseases in families, suggests a role for genetics. While genome-wide association studies (GWASs) produced firm evidence of multiple genetic variants underlying differential susceptibility to type 1 and type 2 diabetes, genetic determinants of microvascular complications are mostly suggestive. Identified susceptibility variants of diabetic kidney disease (DKD) in type 2 diabetes mirror variants underlying chronic kidney disease (CKD) in individuals without diabetes. As for retinopathy and neuropathy, reported risk variants currently lack large-scale replication. The reported associations between type 2 diabetes risk variants and microvascular complications may be explained by hyperglycaemia. More extensive phenotyping, along with adjustments for unmeasured confounding, including both early (fetal) and late-life (hyperglycaemia, hypertension, etc.) environmental factors, are urgently needed to understand the genetics of microvascular complications. Finally, genetic variants associated with reduced glycolysis, mitochondrial dysfunction and DNA damage and sustained cell regeneration may protect against microvascular complications, illustrating the utility of studies in individuals who have escaped these complications.

Additional file 5: Table S4. Frequency of lipid-related publications for the PoPS+ prioritized genes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Additional file 17: Table S9. PheWAS UKB-MVP meta-analysis results for each index lipid variant at Bonferroni threshold for multiple testing p<=3.5e-8)

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice. A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.