AIMS:General population distributions of lipoprotein(a) (Lp(a)) are well-characterized. However, less is known about its distributions and associated event rates within high-risk populations, including individuals with atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD) and varying levels of subclinical atherosclerosis and calcific aortic valve disease. Yet, such insights will facilitate clinical implementation of Lp(a) testing and enhance the design of clinical trials with Lp(a)-lowering agents. METHODS:Data from 5,129 participants in the population-based Rotterdam Study were used to assess Lp(a) distributions, prevalence of Lp(a) levels exceeding thresholds used in ongoing trials (i.e. >150, >175, and >200 nmol/L), accompanying numbers needed to screen (NNS), and major adverse cardiovascular event (MACE) rates across high-risk groups. RESULTS:Lp(a) distributions were right skewed across all groups. Among participants with ASCVD, 13.5% (11.9-15.3%) had Lp(a) >150 nmol/L and 6.5% (5.3-7.8%) had >200 nmol/L, with corresponding NNS 7.4 and 15.4. Similar distributions were observed between participants with coronary artery calcium (CAC) score >300 and participants with coronary heart disease (CHD). Prevalence in participants with aortic valve calcification (AVC) scores >300 was double that of the general population: 20.2% (13.0-27.4) at >150 nmol/L and 11.8% (6.6-19.0) at >200 nmol/L, with the lowest NNS across all groups (5.0-8.5). MACE rates varied by group and increased progressively with higher Lp(a) thresholds. CONCLUSIONS:Lp(a) distributions and MACE rates substantially vary across high-risk groups in the general population. These findings can facilitate design and recruitment strategies of studies with emerging Lp(a)-lowering therapies, while also aiding in identification of populations who may benefit from such therapies.

Apolipoprotein A-IV (apoA-IV) plays key roles in lipid metabolism, reverse cholesterol transport, and kidney function, yet its genetic determinants remain poorly defined. We conduct a genome-wide association study (GWAS) meta-analysis of apoA-IV concentrations measured by ELISA in 25,181 individuals and combine these with proteomic data from 33,995 UK Biobank participants (Olink platform), yielding a total sample of 59,176. We perform genetic correlations and colocalization analyses to explore links with lipid, renal, and other complex traits. The GWAS identifies several novel loci to be associated with apoA-IV concentrations (TDRD5, DPP4, MYL3, MORC1, MCUB, GATA4, ZPR1, UMOD, GLP2R, SLC38A10 and APOE) besides two previously identified loci (APOA5-A4-C3-A1 cluster and KLKB1). Cross-platform comparison shows strong concordance of effect directions and magnitudes, underscoring the robustness of findings across measurement techniques. Global genetic correlation reveals significant shared genetic architecture between apoA-IV, kidney function and HDL-cholesterol, while colocalization supports shared causal variants with lipid, renal, and hematological phenotypes, suggesting biologically relevant pathways. These results provide a comprehensive overview of the genetic architecture of apoA-IV and suggest mechanistic links to lipid metabolism, kidney function and blood-related traits. Our findings refine the role of apoA-IV as a potential biomarker and inform future epidemiological research.

N-glycans are essential components of glycoproteins, influencing their properties and functions. While biochemical pathways of glycosylation are well-characterized, their genetic regulation remains poorly understood. This study utilizes matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) and ultra-high performance liquid chromatography-fluorescence detection (UHPLC-FD) to strengthen replication and further characterize previously identified genome-wide association signals for the total human plasma N-glycome (TPNG). Univariate and multivariate genetic association meta-analyses involved 3385 samples across 143 N-glycome traits from the Hoorn Diabetes Care System and DiaGene cohorts as well as 3224 samples across 117 N-glycome traits from TwinsUK, CEDAR, QMDiab and SABRE cohorts. We successfully replicated ten previously identified but not replicated glycosylation quantitative trait loci (glyQTLs) and prioritized five high-confidence putative causal genes, including the glycosyltransferase MGAT4B and inflammation-related genes - C3 and FCGR2B. The linkage-specific sialic acid derivatization in MALDI-MS enabled delineation of genetic effects on α2,3- and α2,6-sialylation. Mass spectrometry analysis, triggered and guided by association to a locus containing B3GAT1 glucuronosyltransferase, provided evidence for hexuronic acid-containing glycans in human blood plasma. These findings advance our understanding of the genetic regulation of protein N-glycosylation and highlight the complementarity of different analytical approaches in glycomics research.

For the treatment of Type 2 Diabetes, high efficacy approaches such as Glucagon-like peptide 1 (GLP-1)-based therapies are recommended for glucose control. Prediction of the clinical outcome of these therapies on glucose and hemoglobin A1c (HbA1c), using early available pharmacokinetic and in vitro efficacy information, can be a valuable tool for compound selection and supporting drug development. Our previously developed glucose homeostasis model (the 4GI model) is a systems model that is able to quantify drug effects on glucose based on in vitro potency and PK information. In this research, the model was coupled to an existing integrated glucose-red blood cell-HbA1c (IGRH) model for predicting the effects of GLP-1 and GLP-1/glucagon (dual) receptor agonists, liraglutide and cotadutide, on glucose and HbA1c. The 4GI model was validated for predicting 24-h glucose (Cglc,av) with minimal model calibration using short-term Ph2a continuous glucose monitoring (CGM) data. Subsequently, the predicted Cglc,av served as input for the HbA1c model to assess the predictiveness of the combined 4GI-HbA1c model on HbA1c. The resulting combined model was used in cotadutide's clinical development by providing predictive insights into the 26 weeks glucose and HbA1c dynamics of the Ph2b study prior to its initiation. Retrospective analysis showed that the model adequately predicted the effect of cotadutide and liraglutide on fasting plasma glucose and HbA1c (Root Means Square Percent Error (RMSPE) 5.9% and 13%, respectively). This demonstrates the potential of the 4GI-HbA1c systems model as a valuable tool in supporting the clinical development of novel GLP-1 and/or glucagon agonists.

Background Lp(a) causes atherosclerosis and degenerative aortic valve disease, but concerns have risen that mass- based assays may be affected by isoform sizes and provide inaccurate estimates of Lp(a) exposure. Methods We compared contemporary immunoturbidimetric assays reporting either mass-based (Randox) or molar- based (Roche) using data from 5,129 unselected participants from the prospective population-based Rotterdam Study cohort. We studied the association of both Lp(a) measurements with the burden of coronary artery calcium (CAC) and aortic valve calcification (AVC) in a random subset of participants who underwent cardiac CT. Results There was a near perfect linear correlation between Lp(a) concentrations from both immunoassays (R2 98.8%) with most pronounced differences apparent only at very high Lp(a) concentrations. Lp(a) concentrations were related with natural logtransformed Agatston scores (Randox standardized linear 9 0.1003, P = 5.610-8; Roche standardized linear 9 0.1004, P = 5.410-8). Lp(a) concentrations were strongly but similarly related to natural log-transformed AVC Agatston scores (Randox standardized linear 9 0.1525, P = 9.210-16; Roche standardized linear 9 0.1539, P = 4.810-16). Conclusion We demonstrate that these immunoassays provide interchangeable Lp(a) measurements, and that associations with CAC and AVC were near-identical. This provides opportunities to directly compare findings from research done with either immunoassay. Trial Registration The Rotterdam Study has been entered in the Netherlands National Trial Register and the WHO International Clinical Trials Registry Platform under shared catalog number NTR6831. (Am Heart J 2025;284:42-46.)

AbstractObesity has become a major public health concern worldwide. Pharmacological interventions with the glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) have shown promising results in facilitating weight loss and improving metabolic outcomes in individuals with obesity. Quantifying drug effects of GLP‐1RAs on energy intake (EI) and body weight (BW) using a QSP modeling approach can further increase the mechanistic understanding of these effects, and support obesity drug development. An extensive literature‐based dataset was created, including data from several diet, liraglutide and semaglutide studies and their effects on BW and related parameters. The Hall body composition model was used to quantify and predict effects on EI. The model was extended with (1) a lifestyle change/placebo effect on EI, (2) a weight loss effect on activity for the studies that included weight management support, and (3) a GLP‐1R agonistic effect using in vitro potency efficacy information. The estimated reduction in EI of clinically relevant dosages of semaglutide (2.4 mg) and liraglutide (3.0 mg) was 34.5% and 13.0%, respectively. The model adequately described the resulting change in BW over time. At 20 weeks the change in BW was estimated to be −17% for 2.4 mg semaglutide and −8% for 3 mg liraglutide, respectively. External validation showed the model was able to predict the effect of semaglutide on BW in the STEP 1 study. The GLP‐1RA body composition model can be used to quantify and predict the effect of novel GLP‐1R agonists on BW and changes in underlying processes using early in vitro efficacy information.

Apolipoprotein-CIII (apo-CIII) inhibits the clearance of triglycerides from circulation and is associated with an increased risk of diabetes complications. It exists in four main proteoforms: O-glycosylated variants containing either zero, one, or two sialic acids and a non-glycosylated variant. O-glycosylation may affect the metabolic functions of apo-CIII. We investigated the associations of apo-CIII glycosylation in blood plasma, measured by mass spectrometry of the intact protein, and genetic variants with micro- and macrovascular complications (retinopathy, nephropathy, neuropathy, cardiovascular disease) of type 2 diabetes in a DiaGene study (n = 1571) and the Hoorn DCS cohort (n = 5409). Mono-sialylated apolipoprotein-CIII (apo-CIII1) was associated with a reduced risk of retinopathy (β = −7.215, 95% CI −11.137 to −3.294) whereas disialylated apolipoprotein-CIII (apo-CIII2) was associated with an increased risk (β = 5.309, 95% CI 2.279 to 8.339). A variant of the GALNT2-gene (rs4846913), previously linked to lower apo-CIII0a, was associated with a decreased prevalence of retinopathy (OR = 0.739, 95% CI 0.575 to 0.951). Higher apo-CIII1 levels were associated with neuropathy (β = 7.706, 95% CI 2.317 to 13.095) and lower apo-CIII0a with macrovascular complications (β = −9.195, 95% CI −15.847 to −2.543). In conclusion, apo-CIII glycosylation was associated with the prevalence of micro- and macrovascular complications of diabetes. Moreover, a variant in the GALNT2-gene was associated with apo-CIII glycosylation and retinopathy, suggesting a causal effect. The findings facilitate a molecular understanding of the pathophysiology of diabetes complications and warrant consideration of apo-CIII glycosylation as a potential target in the prevention of diabetes complications.

Background Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. Methods We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger’s Z -test and further validated in a pediatric cohort without diabetes (aged 9–12 years old, n = 3866). Results We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta − 0.08 SD, 95% CI [− 0.10–0.07], p = 6.50 × 10 −32 ) and beta-cell dysfunction (Beta − 0.10 SD, 95% CI [− 0.12, − 0.08], p = 1.46 × 10 −47 ) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06–0.10, p = 8.0 × 10 −33 ). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02–1.62, p = 0.03). Conclusions We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.

Introduction. Increased monocyte and macrophage inflammatory state and pro-inflammatory cytokine production are linked to type 2 diabetes (T2D). Research design and Methods. This is a case-control study aimed to examine the expression of 23 monocyte genes related to inflammation, adhesion, and repair in individuals with mild (mean HbA1c 7.3%, illness duration 5.6 years) and severe type 2 diabetes (mean HbA1c 8.4%, disease duration 14.2 years) compared also with lean and obese controls. In addition, we determined a set of serum inflammatory cytokines and growth factors. Results. The monocytes of mild T2D patients (who were in general overweight/obese) showed overexpression of a subset of genes related to adhesion (CD9), vascular repair and growth (HGF). The monocytes of the severe T2D patients showed in contrast an upregulation of many of the pro-inflammatory genes, without a significantly increased expression of the repair gene HGF and the adhesion gene CD9. Serum cytokine expression in the severe T2D patients supported the increased inflammatory state of the patients showing high levels of IL-6, IL-1β, and TNF-α. Conclusions. This study, therefore, shows a pro-inflammatory gene expression profile of monocytes of severe T2D patients, while patients with mild T2D did not show such monocyte profile.

Background and Purpose: Cotadutide is a dual GLP-1 and glucagon receptor agonist with balanced agonistic activity at each receptor designed to harness the advantages on promoting liver health, weight loss and glycaemic control. We characterised the effects of cotadutide on glucose, insulin, GLP-1, GIP, and glucagon over time in a quantitative manner using our glucose dynamics systems model (4GI systems model), in combination with clinical data from a multiple ascending dose/Phase 2a (MAD/Ph2a) study in overweight and obese subjects with a history of Type 2 diabetes mellitus (NCT02548585). Experimental Approach: The cotadutide PK-4GI systems model was calibrated to clinical data by re-estimating only food related parameters. In vivo cotadutide efficacy was scaled based on in vitro potency. The model was used to explore the effect of weight loss on insulin sensitivity and predict the relative contribution of the GLP-1 and glucagon receptor agonistic effects on glucose. Key Results: Cotadutide MAD/Ph2a clinical endpoints were successfully predicted. The 4GI model captured a positive effect of weight loss on insulin sensitivity and showed that the stimulating effect of glucagon on glucose production counteracts the GLP-1 receptor-mediated decrease in glucose, resulting in a plateau for glucose decrease around a 200-mu g cotadutide dose. Conclusion and Implications: The 4GI quantitative systems pharmacology model was able to predict the clinical effects of cotadutide on glucose, insulin, GLP-1, glucagon and GIP given known in vitro potency. The analyses demonstrated that the quantitative systems pharmacology model, and its successive refinements, will be a valuable tool to support the clinical development of cotadutide and related compounds.

APOE4 encoding apolipoprotein (Apo)E4 is the strongest genetic risk factor for Alzheimer's disease (AD). ApoE is key in intercellular lipid trafficking. Fatty acids are essential for brain integrity and cognitive performance and are implicated in neurodegeneration. We determined the sex- and age-dependent effect of AD and APOE4 on brain free fatty acid (FFA) profiles. FFA profiles were determined by LC-MS/MS in hippocampus, cortex, and cerebellum of female and male, young (≤3 months) and older (>5 months), transgenic APOE3 and APOE4 mice with and without five familial AD (FAD) mutations (16 groups; n = 7-10 each). In the different brain regions, females had higher levels than males of either saturated or polyunsaturated FFAs or both. In the hippocampus of young males, but not of older males, APOE4 and FAD each induced 1.3-fold higher levels of almost all FFAs. In young and older females, FAD and to a less extent APOE4-induced shifts among saturated, monounsaturated, and polyunsaturated FFAs without affecting total FFA levels. In cortex and cerebellum, APOE4 and FAD had only minor effects on individual FFAs. The effects of APOE4 and FAD on FFA levels and FFA profiles in the three brain regions were strongly dependent of sex and age, particularly in the hippocampus. Here, most FFAs that are affected by FAD are similarly affected by APOE4. Since APOE4 and FAD affected hippocampal FFA profiles already at young age, these APOE4-induced alterations may modulate the pathogenesis of AD.

Abstract Context Hyperglycemia and autonomic dysfunction are bidirectionally related. Objective We investigated the association of longitudinal evolution of heart rate variability (HRV) with incident type 2 diabetes (T2D) among the general population. Methods We included 7630 participants (mean age 63.7 years, 58% women) from the population-based Rotterdam Study who had no history of T2D and atrial fibrillation at baseline and had repeated HRV assessments at baseline and during follow-up. We used joint models to assess the association between longitudinal evolution of heart rate and different HRV metrics (including the heart rate–corrected SD of the normal-to-normal RR intervals [SDNNc], and root mean square of successive RR-interval differences [RMSSDc]) with incident T2D. Models were adjusted for cardiovascular risk factors. Bidirectional Mendelian randomization (MR) using summary-level data was also performed. Results During a median follow-up of 8.6 years, 871 individuals developed incident T2D. One SD increase in heart rate (hazard ratio [HR] 1.20; 95% CI, 1.09-1.33), and log(RMSSDc) (HR 1.16; 95% CI, 1.01-1.33) were independently associated with incident T2D. The HRs were 1.54 (95% CI, 1.08-2.06) for participants younger than 62 years and 1.15 (95% CI, 1.01-1.31) for those older than 62 years for heart rate (P for interaction <.001). Results from bidirectional MR analyses suggested that HRV and T2D were not significantly related to each other. Conclusion Autonomic dysfunction precedes development of T2D, especially among younger individuals, while MR analysis suggests no causal relationship. More studies are needed to further validate our findings.

BACKGROUND:Severe hypercholesterolemia, defined as LDL (low-density lipoprotein) cholesterol (LDL-C) measurement & GE;190 mg/dL, is associated with increased risk for coronary artery disease (CAD). Causes of severe hypercholesterolemia include monogenic familial hypercholesterolemia, polygenic hypercholesterolemia, elevated lipoprotein(a) [Lp(a)] hypercholesteremia, polygenic hypercholesterolemia with elevated Lp(a) (two-hit), or nongenetic hypercholesterolemia. The added value of using a genetics approach to stratifying risk of incident CAD among those with severe hypercholesterolemia versus using LDL-C levels alone for risk stratification is not known.METHODS:To determine whether risk stratification by genetic cause provided better 10-year incident CAD risk stratification than LDL-C level, a retrospective cohort study comparing incident CAD risk among severe hypercholesterolemia subtypes (genetic and nongenetic causes) was performed among 130 091 UK Biobank participants. Analyses were limited to unrelated, White British or Irish participants with available exome sequencing data. Participants with cardiovascular disease at baseline were excluded from analyses of incident CAD.RESULTS:Of 130 091 individuals, 68 416 (52.6%) were women, and the mean (SD) age was 56.7 (8.0) years. Of the cohort, 9.0% met severe hypercholesterolemia criteria. Participants with LDL-C between 210 and 229 mg/dL and LDL-C & GE;230 mg/dL showed modest increases in incident CAD risk relative to those with LDL-C between 190 and 209 mg/dL (210-229 mg/dL: hazard ratio [HR], 1.3 [95% CI, 1.1-1.7]; & GE;230 mg/dL: HR, 1.3 [95% CI, 1.0-1.7]). In contrast, when risk was stratified by genetic subtype, monogenic familial hypercholesterolemia, elevated Lp(a), and two-hit hypercholesterolemia subtypes had increased rates of incident CAD relative to the nongenetic hypercholesterolemia subtype (monogenic familial hypercholesterolemia: HR, 2.3 [95% CI, 1.4-4.0]; elevated Lp(a): HR, 1.5 [95% CI, 1.2-2.0]; two-hit: HR, 1.9 [95% CI, 1.4-2.6]), while polygenic hypercholesterolemia did not.CONCLUSIONS:Genetics-based subtyping for monogenic familial hypercholesterolemia and Lp(a) in those with severe hypercholesterolemia provided better stratification of 10-year incident CAD risk than LDL-C-based stratification.

Background: Relative fat mass (RFM) is a novel sex-specific anthropometric equation (based on height and waist measurements) to estimate whole-body fat percentage. Objective: To examine associations of RFM with incident type-2 diabetes (T2D), and to benchmark its perfor-mance against body-mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR). Methods: This prospective longitudinal study included data from three Dutch community-based cohorts free of baseline diabetes. First, we examined data from the PREVEND cohort (median age and follow-up duration: 48.0 and 12.5 years, respectively) using Cox regression models. Validation was performed in the Lifelines (median age and follow-up duration: 45.5 and 3.8 years, respectively) and Rotterdam (median age and follow-up duration: 68.0 and 13.9 years, respectively) cohorts. Results: Among 7961 PREVEND participants, 522 (6.6%) developed T2D. In a multivariable model, all adiposity indices were significantly associated with incident T2D (Pall<0.001). While 1 SD increase in BMI, WC and WHR were associated with 68%, 77% and 61% increased risk of developing T2D [Hazard ratio (HR)BMI: 1.68 (95%CI: 1.57-1.80), HRWC: 1.77 (95% CI: 1.63-1.92) and HRWHR: 1.61 (95%CI: 1.48-1.75)], an equivalent increase in RFM was associated with 119% increased risk [HR: 2.19 (95%CI: 1.96-2.44)]. RFM was associated with incident T2D across all age groups, with the largest effect size in the youngest (<40 years) age category [HR: 2.90 (95%CI: 2.15-3.92)].Results were broadly similar in Lifelines (n = 93,870) and Rotterdam (n = 5279) cohorts. Conclusions: RFM is strongly associated with new-onset T2D and displays the potential to be used in the general practice setting to estimate the risk of future diabetes.

Apolipoprotein-CIII (apo-CIII) is involved in triglyceride-rich lipoprotein metabolism and linked to beta-cell damage, insulin resistance, and cardiovascular disease. Apo-CIII exists in four main proteoforms: non-glycosylated (apo-CIII0a), and glycosylated apo-CIII with zero, one, or two sialic acids (apo-CIII0c, apo-CIII1 and apo-CIII2). Our objective is to determine how apo-CIII glycosylation affects lipid traits and type 2 diabetes prevalence, and to investigate the genetic basis of these relations with a genome-wide association study (GWAS) on apo-CIII glycosylation. We conducted GWAS on the four apo-CIII proteoforms in the DiaGene study in people with and without type 2 diabetes (n = 2318). We investigated the relations of the identified genetic loci and apo-CIII glycosylation with lipids and type 2 diabetes. The associations of the genetic variants with lipids were replicated in the Diabetes Care System (n = 5409). Rs4846913-A, in the GALNT2-gene, was associated with decreased apo-CIII0a. This variant was associated with increased high-density lipoprotein cholesterol and decreased triglycerides, while high apo-CIII0a was associated with raised high-density lipoprotein-cholesterol and triglycerides. Rs67086575-G, located in the IFT172-gene, was associated with decreased apo-CIII2 and with hypertriglyceridemia. In line, apo-CIII2 was associated with low triglycerides. On a genome-wide scale, we confirmed that the GALNT2-gene plays a major role i O-glycosylation of apolipoprotein-CIII, with subsequent associations with lipid parameters. We newly identified the IFT172/NRBP1 region, in the literature previously associated with hypertriglyceridemia, as involved in apolipoprotein-CIII sialylation and hypertriglyceridemia. These results link genomics, glycosylation, and lipid metabolism, and represent a key step towards unravelling the importance of O-glycosylation in health and disease.

Abstract Funding Acknowledgements Type of funding sources: None. Background Achieving blood pressure targets is a key component of type 2 diabetes (T2D) management and is considered important in reducing mortality risk. However, little is known about whether different multimorbidity patterns would modify the associations between blood pressure and mortality among patients with T2D. Method In the prospective population-based UK Biobank cohort, prevalent T2D was defined as fasting blood glucose ≥7.0 mmol/L (126 mg/dL), non-fasting blood glucose ≥11.1 mmol/L (200 mg/dL), HbA1c level ≥47.5 mmol/mol (6.5%), self-reported physician-diagnosed diabetes, current use of blood glucose-lowering medication, or having hospital inpatient records occurring before the baseline study assessment. We qualitatively assessed multimorbidity (defined as the presence of the 39 self-reported long-term health conditions [in addition to T2D]) in three ways: total, concordant, and discordant condition, and calculated disease counts for each multimorbidity type. Cox regression models were used to estimate the associations of blood pressure and all-cause/cause-specific mortality within different multimorbidity patterns. Results 24,647 participants with prevalent T2D at baseline were included (mean age 59.8 years, 36.9% women). During a median follow-up time of 11.8 years (interquartile range: 11.0-12.6), 4114 (16.7%) individuals died, of whom 1189 (4.8%) died of cardiovascular disease. A U-shaped association was found between systolic blood pressure (SBP) and risk of mortality among T2D patients across total, concordant, and discordant multimorbidity patterns, and the related effect estimations increased with accumulating multimorbidity counts; whereas a reverse J-shaped association was indicated for diastolic blood pressure (DBP) in specific multimorbidity patterns. Notably, the lowest risk of death was consistently observed around 130~140 mmHg for SBP and 80~90 mmHg for DBP within different multimorbidity patterns. Among participants with none, one, two, and more than two total multimorbidity counts, respectively, those having SBP <120 mmHg, compared to having SBP around 130~139 mmHg, had a higher risk of all-cause mortality with a hazard ratio (HR) 1.08 (95 %CI: 0.81, 1.43), 1.36 (1.11, 1.67), 1.33 (1.04, 1.69), and 1.43 (1.09, 1.87), respectively; and those with DBP <70 mmHg, compared to having DBP 80~89 mmHg, had an HR (95%CI) of 1.21 (0.99, 1.48), 1.52 (1.30, 1.79), 1.35 (1.10, 1.65), and 1.34 (1.08, 1.67) for all-cause mortality, and 1.75 (1.20, 2.56), 2.03 (1.52, 2.70), 1.41 (1.00, 1.99), and 1.71 (1.17, 2.50) for cardiovascular mortality. Conclusion Low and high SBP and low DBP were related to a higher risk of all-cause and cardiovascular mortality in individuals with T2D, regardless of their multimorbidity patterns. This implies that different multimorbidity counts or types should not affect optimal blood pressure target in diabetes management.

Objectives:Individuals with familial hypercholesterolemia (FH) are at an increased risk for coronary artery disease (CAD). While prior research has shown variability in coronary artery calcification (CAC) among those with FH, studies with small sample sizes and single-center recruitment have been limited in their ability to characterize CAC and plaque burden in subgroups based on age and sex. Understanding the spectrum of atherosclerosis may result in personalized risk assessment and tailored allocation of costly add-on, non-statin lipid-lowering therapies. We aimed to characterize the presence and burden of CAC and coronary plaque on computed tomography angiography (CTA) across age- and sex-stratified subgroups of individuals with FH who were without CAD at baseline. Methods:We pooled 1,011 patients from six cohorts across Brazil, France, the Netherlands, Spain, and Australia. Our main measures of subclinical atherosclerosis included CAC ranges (i.e., 0, 1-100, 101-400, >400) and CTA-derived plaque burden (i.e., no plaque, non-obstructive CAD, obstructive CAD). Results:Ninety-five percent of individuals with FH (mean age: 48 years; 54% female; treated LDL-C: 154 mg/dL) had a molecular diagnosis and 899 (89%) were on statin therapy. Overall, 423 (42%) had CAC=0, 329 (33%) had CAC 1-100, 160 (16%) had CAC 101-400, and 99 (10%) had CAC >400. Compared to males, female patients were more likely to have CAC=0 (48% [n = 262] vs 35% [n = 161]) and no plaque on CTA (39% [n = 215] vs 26% [n = 120]). Among patients with CAC=0, 85 (20%) had non-obstructive CAD. Females also had a lower prevalence of obstructive CAD in CAC 1-100 (8% [n = 15] vs 18% [n = 26]), CAC 101-400 (32% [n = 22] vs 40% [n = 36]), and CAC >400 (52% [n = 16] vs 65% [n = 44]). Female patients aged 50-59 years were less likely to have obstructive CAD in CAC >400 (55% [n = 6] vs 70% [n = 19]). Conclusion:In this large, multi-national study, we found substantial age- and sex-based heterogeneity in CAC and plaque burden in a cohort of predominantly statin-treated individuals with FH, with evidence for a less pronounced increase in atherosclerosis among female patients. Future studies should examine the predictors of resilience to and long-term implications of the differential burden of subclinical coronary atherosclerosis in this higher risk population.

Aims/hypothesis Inflammation is important in development of type 2 diabetes complications. The N-glycosylation of IgG influences its role in inflammation. Until now, the association of IgG N-glycosylation with type 2 diabetes complications has not been extensively investigated. We hypothesized that N-glycosylation of IgG may be related to development of complications of type 2 diabetes. Methods In three independent type 2 diabetes cohorts, IgG N-glycosylation was measured by UPLC (DiaGene n=1815, GenodiabMar n=640) and mass spectrometry (DCS n=1266). We investigated the associations of IgG N-glycosylation (fucosylation, galactosylation, sialylation and bisection) with incident and prevalent nephropathy, retinopathy and macrovascular disease using Cox- and logistic regression, followed by meta-analyses. The models were adjusted for age, sex and additionally for clinical risk factors. Results IgG galactosylation was negatively associated with prevalent and incident nephropathy after adjustment for clinical risk factors. Sialylation was negatively associated with incident diabetic nephropathy. For retinopathy, similar associations were found for galactosylation in the basic model. For macrovascular complications, negative associations with galactosylation and sialylation were confined to the cross-sectional analyses. Conclusions We showed that IgG N-glycosylation traits are associated with higher prevalence and future development of nephropathy, after correction for clinical risk factors. For other complications, IgG

Aim:Rare genetic variants in the CUBN gene encoding the main albumin-transporter in the proximal tubule of the kidneys have previously been associated with microalbuminuria and higher urine albumin levels, also in diabetes. Sequencing studies in isolated proteinuria suggest that these variants might not affect kidney function, despite proteinuria. However, the relation of these CUBN missense variants to the estimated glomerular filtration rate (eGFR) is largely unexplored. We hereby broadly examine the associations between four CUBN missense variants and eGFRcreatinine in Europeans with Type 1 (T1D) and Type 2 Diabetes (T2D). Furthermore, we sought to deepen our understanding of these variants in a range of single- and aggregate- variant analyses of other kidney-related traits in individuals with and without diabetes mellitus.Methods:We carried out a genetic association-based linear regression analysis between four CUBN missense variants (rs141640975, rs144360241, rs45551835, rs1801239) and eGFRcreatinine (ml/min/1.73 m2, CKD-EPIcreatinine(2012), natural log-transformed) in populations with T1D (n ~ 3,588) or T2D (n ~ 31,155) from multiple European studies and in individuals without diabetes from UK Biobank (UKBB, n ~ 370,061) with replication in deCODE (n = 127,090). Summary results of the diabetes-group were meta-analyzed using the fixed-effect inverse-variance method.Results:Albeit we did not observe associations between eGFRcreatinine and CUBN in the diabetes-group, we found significant positive associations between the minor alleles of all four variants and eGFRcreatinine in the UKBB individuals without diabetes with rs141640975 being the strongest (Effect=0.02, PeGFR_creatinine=2.2 × 10-9). We replicated the findings for rs141640975 in the Icelandic non-diabetes population (Effect=0.026, PeGFR_creatinine=7.7 × 10-4). For rs141640975, the eGFRcreatinine-association showed significant interaction with albuminuria levels (normo-, micro-, and macroalbuminuria; p = 0.03). An aggregated genetic risk score (GRS) was associated with higher urine albumin levels and eGFRcreatinine. The rs141640975 variant was also associated with higher levels of eGFRcreatinine-cystatin C (ml/min/1.73 m2, CKD-EPI2021, natural log-transformed) and lower circulating cystatin C levels.Conclusions:The positive associations between the four CUBN missense variants and eGFR in a large population without diabetes suggests a pleiotropic role of CUBN as a novel eGFR-locus in addition to it being a known albuminuria-locus. Additional associations with diverse renal function measures (lower cystatin C and higher eGFRcreatinine-cystatin C levels) and a CUBN-focused GRS further suggests an important role of CUBN in the future personalization of chronic kidney disease management in people without diabetes.

Background and Aims: After diagnosis, patients with familial hypercholesterolemia (FH) are advised lifelong cholesterol-lowering treatment. Although without trial evidence, we always propose to combine a healthy lifestyle with statins as the first line of therapy. The geographic variation of life expectancy in the Netherlands has enabled a trial by nature of the same untreated FH mutation in a beneficial and general environment. Methods: We performed a nationwide cascade screening and obtained a large pedigree with the S306L mutation in the low-density lipoprotein receptor (LDLR ) gene. Before the statins became available in 1990, we determined the all-cause standardized mortality ratio (SMR). Patients and spouses were compared with Poisson regression (relative risk). Results: Between 1800 and 1989, 147 deaths occurred in 14,152 person-years. Overall, the SMR was 1.25 (95% CI 1.05-1.46; P = 0.0056). The spouses in a beneficial environment had an SMR of 0.75 (95% CI 0.55-0.99; P =0.0547). The mortality in this beneficial environment was not increased (SMR 1.16; 95% CI 0.85-1.54 ; P =0.1794), while other parts confirmed the known overall excess mortality from untreated FH (SMR 1.29; 95% CI 1.05-1.57; P = 0.0076). However, the FH patients in the beneficial environment had 1.5 times more deaths relative to their spouses (RR 1.46; 95% CI 0.96-2.22; P =0.07388). Conclusions: A favorable local environment decreased excess mortality significantly. However, the S306L mutation in the LDLR gene still caused the expected excess mortality locally. Our findings show that a beneficial lifestyle is an add-on but not an alternative for the immediate start of cholesterol-lowering treatment.