Diabetes Research and Clinical Practice

Introduction. Diabetes is a growing global health challenge, necessitating effective management strategies. Glycosylation, a highly regulated post-translational protein modification, has emerged as a pivotal factor in diabetes pathophysiology. However, the modulation of protein glycosylation by antidiabetic treatment is still largely unknown. This study explored the longitudinal effects of four distinct antidiabetic therapies - metformin, insulin, sodium-glucose cotransporter-2 (SGLT2) inhibitors, and glucagon-like peptide-1 receptor agonists (GLP-1RA) - on plasma protein and immunoglobulin G (IgG) glycosylation in patients with type 2 diabetes (T2D). Research Design and Methods. Plasma protein and IgG N-glycans were enzymatically released, purified and chromatographically profiled in a cohort of 124 patients, examined at four time points, to assess therapy-induced glycan alterations. Linear mixed models adjusting for covariates and multiple testing (FDR<0.05) were used to investigate the associations between plasma protein and IgG N-glycosylation and antidiabetic therapy. Results. Our findings reveal that metformin, SGLT2 inhibitors, and GLP-1RA induce significant alterations in IgG glycosylation, including the increased core fucosylation and galactosylation, features associated with a reduced inflammatory IgG potential. Notably, IgG monogalactosylation, previously linked to cardioprotective effects in women, was elevated in response to GLP-1RA and SGLT2 inhibitor treatments. Plasma protein glycosylation changes were more limited, with distinct alterations observed for each therapy. Metformin and GLP-1RA similarly reduced certain fucosylated and sialylated glycans, while SGLT2 inhibitors decreased a high-mannose glycan, previously positively associated with diabetes progression. Insulin therapy had a minimal effect on protein glycosylation, with only one plasma glycan significantly altered. Conclusions. Our findings emphasise the importance of protein glycosylation as a dynamic and responsive marker in T2D treatment. The distinct glycan alterations observed in response to metformin, SGLT2 inhibitors, and GLP-1 receptor agonists provide novel insights into the molecular effects of these therapies, potentially contributing to the development of glycan-based biomarkers for personalized diabetes management.

Background: Metabolic syndrome (MetS) has been associated with cognitive decline. Considering its increasing prevalence worldwide, the goal of this study was to evaluate the feasibility and efficacy of a short-term, self-administered computerized cognitive training programme in individuals with metabolic syndrome and low cognitive performances. Methods: Thirty six participants, aged 40-72 years (mean age: 57.8 years), were randomly assigned to the cognitive training or the passive control group. The cognitive training component of Long Lasting Memories (LLM) Care was used as an interactive software to enhance participants' cognitive functions. Up to 24 sessions, each lasting 45 minutes, were self-administered at home twice per week for 3 months. Thorough cognitive assessments with were performed at baseline (randomization), at the end of intervention, and 12 months after baseline. The primary outcome was performance at nine neuropsychological tests, and the secondary outcome was a self-reported questionnaire assessing everyday functional abilities. Primary analyses were performed employing mixed-effect models using the intention-to-treat principle. Results: Low adherence was observed in the study, as only 9 participants (50%) completed at least 8 sessions of the cognitive training programme (range 9-24 sessions, median 15 sessions). No statistically significant effect of the cognitive training programme on performance in neuropsychological tests or everyday functioning was found. At the end of the 3-month intervention programme, effect for visual memory enhancement in immediate ({beta} = 1.58, 95% CI = -1.84 to 4.99, Cohen's d = 0.39) and delayed recall ({beta} = 2.17, 95% CI = -1.68 to 6.01, Cohen's d = 0.45) was moderate in favour of the intervention group, and at 12-month follow-up, semantic verbal fluency gains for the intervention group were detected ({beta} = 2.78, 95% CI = -0.92 to 6.49, Cohen's d = 0.70), though with wide confidence intervals. Conclusions: Despite some small effects observed in memory and verbal fluency, cognitive training did not yield statistically significant improvements. The observed low adherence and limited benefits on mild cognitive deficits in mostly middle-aged individuals with MetS are likely associated with the self-administered and short-term nature of the computerized intervention. This highlights the need for more intensive and clinician-delivered approaches to enhance engagement. Registry: ClinicalTrials.gov, TRN: NCT05658354, Registration date: 08 December 2022. Keywords: Metabolic syndrome, cognitive deficits, cognitive training, computerized, adults

Background Besides hyperglycemia, type 2 diabetes (T2D) is characterized by dyslipidemia, which is typically assessed using traditional clinical lipid measurements. However, molecular plasma lipids beyond these traditional markers can provide additional information about an individuals health status. For molecular lipids to be used effectively, certain characteristics, such as their temporal variability, need to be determined. Methods We analyzed the plasma lipidome for three consecutive time points, each three months apart, of 51 individuals with T2D using targeted liquid chromatography coupled to mass spectrometry (LC-MS). 513 lipid species across 25 (sub)classes were quantified by this approach and the temporal variability were calculated. Moreover, to identify sex differences in the plasma lipidome, we analyzed 914 samples of a cross-sectional T2D cohort with the same approach. Results Neutral lipids and phosphatidylserine had the highest temporal variability which was independent of their platform-specific variability. In contrast, glycosphingolipids were found to be relatively stable over time in individuals with T2D. Acyl-chain analysis revealed generally similar variability in the acyl-chain groups but indicated a higher temporal variability in medium-length acyl-chains. Lipid-sex association analysis showed markedly higher sphingomyelins, phosphatidylcholines, and phosphatidylethanolamines in women and higher acylcarnitines in men. Overall, approximately one-third of measured lipids showed significant sex differences independent of age, BMI, diabetes duration, glycemic control, and medication use. Conclusions Our findings provide insights into temporal variability of molecular lipids. This variability should be considered when assessing novel lipid biomarkers. Likewise, sex differences in these lipids need to be considered in precision medicine for diabetes management.

Continuous glucose monitoring (CGM) is increasingly used for inpatient glycemic surveillance, but evidence in non-critical care wards remains limited, particularly in real-world public healthcare settings. Intermittent capillary glucose testing may fail to detect transient, nocturnal, or asymptomatic dysglycemia. We sought to evaluate whether CGM improves detection of clinically significant dysglycemia compared with seven-point capillary glucose monitoring in hospitalized patients with type 2 diabetes mellitus or hyperglycemia. This is a prospective, observational, non-randomized, real-world study performed in a tertiary referral center in Mexico. 56 hospitalized patients were included: 28 underwent flash CGM and 28 underwent seven-point capillary glucose monitoring. Patients were followed for up to 6 hospitalization days. The main analytical focus was detection of clinically significant dysglycemia, including hypoglycemia <70 mg/dL, clinically significant hypoglycemia <54 mg/dL, and severe hyperglycemia >250 mg/dL. Secondary outcomes included time in range, mean daily glucose, insulin requirements, infectious complications, length of stay, and mortality. CGM detected more hypoglycemia <70 mg/dL than capillary monitoring (71.4% vs 35.7%, p=0.005), more clinically significant hypoglycemia <54 mg/dL (median 3 [IQR 0-6.5] vs 0, p=0.030), and more severe hyperglycemia >250 mg/dL (median 8.5 [IQR 0.5-17] vs 0 [IQR 0-9.52], p=0.030). Time in range was not significantly different between groups (59.86 +/- 23.46% vs 69.28 +/- 24.99%, p=0.151). After adjustment for age, diabetes duration, and admission hyperglycemia, CGM remained associated with hypoglycemia detection (OR 4.7, 95% CI 1.2-19.0, p=0.027). We concluded that CGM improved detection of clinically significant dysglycemia during up to 6 hospitalization days. Although CGM did not improve time in range or short-term clinical outcomes, it provided superior glycemic surveillance compared with intermittent capillary glucose testing.

Background: Insulin resistance is a core pathophysiologic feature of metabolic disease, but its reference-standard assessment by steady-state plasma glucose (SSPG) testing is procedurally demanding and labor-intensive, limiting use in routine clinical care and large-scale research. Because OGTT glucose profiles are widely available, we aimed to develop a glucose-only metric to characterize dynamic glucose responses and estimate SSPG-measured insulin resistance. Methods: We developed the Width-Delay Index (WDI), a glucose-only OGTT metric integrating relative exposure width, delayed exposure timing, and glycemic floor. In a dataset of 32 subjects with 16-point venous OGTT profiles and paired SSPG measurements, WDI performance was assessed using leave-one-out cross-validation (LOOCV) for SSPG prediction, together with insulin-resistance discrimination and sparse-sampling robustness analyses. Results: The 15-120 min OGTT window yielded the strongest WDI performance. WDI15-120 predicted SSPG with LOOCV R2 = 0.57 (95% CI, 0.27-0.77), Pearson r = 0.77, and Spearman rho = 0.74. WDI15-120 showed higher predictive performance than standard OGTT glucose measures and insulin-derived indices, including HOMA-IR, Matsuda index, and disposition index. WDI15-120 also discriminated insulin-resistant from insulin-sensitive subjects with AUROC = 0.969. When recalculated from conventional 5-point OGTT sampling, WDI15-120 retained substantial performance, with LOOCV R2 = 0.41 and AUROC = 0.945. Conclusions: WDI provides a simple, glucose-only, physiologically interpretable approach for estimating SSPG-measured insulin resistance from OGTT glucose dynamics.

Background: Epidemiological evidence links type 2 diabetes (T2D) to an increased risk of dementia, including Alzheimers disease (AD). However, previous syntheses often combined heterogeneous diabetes and dementia definitions and have not comprehensively quantified AD incidence among individuals with T2D. We aimed to estimate both the incidence of AD among individuals with T2D and the association between T2D and AD using studies with well-defined T2D and AD outcomes. Methods: We systematically searched MEDLINE, CINAHL (via EBSCO), Embase (via Ovid), and Scopus from inception to April 2026 for studies investigating the incidence of AD among individuals with T2D or the association between T2D and AD. Data were pooled using random-effects models and presented as incidence rates and adjusted relative risks (RRs) with 95% confidence intervals (CIs). Results Of the 9,430 articles identified, 40 studies involving 27,102,559 participants were included. Twenty-three studies contributed incidence data, and 26 reported adjusted relative risks (aRR). The pooled incidence of AD among individuals with T2D was 4.71 per 1,000 person-years (95% CI 3.31, 6.71). T2D was associated with an increased risk of AD (aRR 1.53, 95% CI 1.38, 1.70). Subgroup findings were generally consistent, results were robust in sensitivity analyses, and no publication bias was detected. Conclusions: This study provides a comprehensive quantification of the AD burden associated with T2D by focusing on well-defined AD and T2D outcomes and advancing the field beyond prior broad dementia syntheses. Integrating incidence and relative risk estimates clarifies both the absolute and relative burden of AD in T2D and extends previous syntheses that primarily emphasised relative risk. Individuals with T2D experienced approximately five AD cases per 1,000 person-years and a 53% higher risk of AD, supporting the rationale for integrating cognitive risk prevention into diabetes care.

Introduction Type 2 diabetes (T2D) prevalence, severity, duration, and control are associated with dementia incidence, but prior literature is focused on specific pharmacologic, dietary, and exercise interventions in isolation while controlling for other co-occurring factors. Accounting for comprehensive life course experiences of the timing of diabetes onset, severity, treatment, and progression over a period of decades would provide a more comprehensive description of how life course diabetes progression and control is associated with dementia. Trajectories of diabetes diagnosis, pharmacological management, and disease progression are heterogeneous, and classifying these trajectories presents a significant methodological challenge. Methods Using deidentified survey and electronic health record data from Kaiser Permanente Northern California (KPNC) from the Research Program on Genes, Environment, and Health (RPGEH), we defined annual "states" for each eligible participant with T2D diagnosed between ages 50 and 70 based on KPNC, diabetes diagnosis, glycated hemoglobin, antidiabetes prescription count, and kidney dysfunction. We then employed sequence and cluster analyses to group participants into clusters with similar trajectories of these states. Finally, we estimated hazard ratios for incidence of Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) for each of these clusters as well as individuals with type 1 or other diabetes types, relative to participants without diabetes at age 70, using covariate-adjusted Cox proportional hazards models. Results Using the 18,688 participants with T2D included in the diabetes trajectory assessment, sequence and cluster analysis identified 9 clusters of T2D treatment and control histories between ages 50 and 70. Clusters differed markedly in timing of onset of T2D, glucose control, antidiabetes drug use and kidney function. Associations of these clusters with incident AD/ADRD after age 70 was heterogeneous and patterned by diabetes control and treatment history, particularly by diabetes duration and treatment regime. Conclusions In conclusion, in this real-world data context, we find increased diabetes severity, increased medication use, and faster progression to kidney disease is associated with increased risk of dementia. We find some patterns of diabetes severity and control are associated with greater dementia risk. This information may be useful in the context of targeted screening and allocation of preventative services for ADRD.

Circulating biomarkers are increasingly used for patient risk stratification in chronic kidney disease (CKD) and heart failure with preserved ejection fraction (HFpEF). However, clinically relevant circulating biomarkers remain insufficiently characterized in rodent models recapitulating diabetic cardiorenal disease with HFpEF. To address this gap, we evaluated 20 translationally relevant inflammation-associated biomarkers in the diabetic db/db uninephrectomized (UNx)-ReninAAV mouse model of CKD and HFpEF. db/db UNx-ReninAAV mice exhibited marked increases in circulating soluble urokinase-type plasminogen activator receptor (suPAR) and monocyte chemoattractant protein-1 (MCP-1), and in interleukin 10 (IL-10) at late stages of disease. Histological analyses confirmed increased tissue expression of suPAR in the heart and kidney and of MCP-1 in the heart. Notably, circulating suPAR levels correlated with disease severity, including systolic and diastolic cardiac dysfunction and albuminuria. Together, these results provide a systematic analysis of biomarkers in a rodent model of diabetes, CKD and HFpEF and identify suPAR as the biomarker most closely associated with disease severity.

The coexistence of obesity and insulin resistance is associated with elevated plasma amino acid concentrations. However, it remains unclear whether adiposity or insulin resistance is the stronger determinant of plasma amino acid dysregulation in this setting. Twenty-two adults (10 women, 12 men) spanning a broad range of body mass index (BMI) and insulin resistance underwent a 75-g oral glucose tolerance test (OGTT) after an overnight fast. Plasma glucose, insulin, and amino acid concentrations were measured serially, and insulin resistance/sensitivity was estimated from OGTT-derived glucose and insulin responses, using the homeostasis model assessment of insulin resistance (HOMA-IR) and the Matsuda insulin sensitivity index (Matsuda-ISI). Principal component analysis (PCA) of fasting plasma amino acid concentrations showed no clear separation by obesity or insulin resistance classifications. In contrast, PCA of OGTT-stimulated plasma amino acid concentrations revealed clearer clustering by BMI, fat mass, and waist circumference, whereas separation by HOMA-IR and Matsuda-ISI was less distinct. Importantly, regression analyses showed that BMI, fat mass, and waist circumference were significant predictors of OGTT-stimulated, but not fasting, amino acid responses, with waist circumference accounting for the greatest proportion of the variance in branched-chain amino acid responses during the OGTT (R2 = 0.54). In conclusion, measures of adiposity, particularly total fat mass and waist circumference, accounted for a greater proportion of the variance in plasma amino acid responses under physiologically stimulated conditions than indices of insulin resistance. These findings support the view that plasma amino acid concentrations reflect adiposity-related metabolic alterations more strongly than insulin resistance.

Background: Poor glycemic control is associated with cardiovascular disease (CVD) risk. However, it is unknown whether glycemic control is related to abdominal aortic calcification (AAC), a marker of subclinical CVD. We investigated the association between glycated hemoglobin (HbA1c) and moderate-to-high automated AAC among middle-aged to older adults from the general population. Methods:We included UK Biobank Imaging Study participants free of atherosclerotic CVD at baseline. HbA1c was measured at baseline (2006-2010) and categorized as normoglycemia (<39.0 mmol/mol), prediabetes (39.0-47.9 mmol/mol), undiagnosed diabetes (HbA1c [&ge;]48 mmol/mol), and diagnosed diabetes. Machine learning-derived AAC24 (ML-AAC24) scores were estimated using a validated automated algorithm applied to dual-energy X-ray absorptiometry lateral spine images (2014-2022). The associations of HbA1c with moderate-to-high ML-AAC24 (defined as a score [&ge;]2) were assessed using logistic regression adjusting for cardiovascular risk factors. Results: Of the included 48,912 participants (mean {+/-} SD age 55 {+/-} 7.6 years, 52% women), 9.7% had prediabetes (HbA1c 39.0-47.9 mmol/mol [5.7-6.4%]), 0.4% had undiagnosed diabetes, and 2.7% had diagnosed diabetes. Each 1-SD increase in log-transformed HbA1c was associated with higher odds of moderate-to-high ML-AAC24 (adjusted odds ratio [aOR] 1.12, 95% CI: 1.09-1.16). Amongst individuals with normal HbA1c, this association was consistent but somewhat weaker for each 1-SD increase in log-transformed HbA1c (aOR 1.07, 95% CI 1.03-1.10). Compared to participants with normal HbA1c, those with prediabetes (aOR 1.19, 95% CI: 1.08-1.30) or diagnosed diabetes (1.64, 95% CI: 1.39-1.94) had higher odds of moderate-to-high ML-AAC24. These associations were consistent in stratified analyses by sex, age groups, body mass index, smoking status and total cholesterol Conclusions: Linear associations between HbA1c levels and ML-AAC24 were observed in UK adults, even in those with normal HbA1c levels. These findings indicate that AAC may develop early in the dysglycemic continuum, supporting earlier cardiometabolic risk assessment even amongst people with ?normal? levels.

Background: Glucagon-like peptide-1 receptor agonist-based therapies (GLP) have recently emerged as promising treatments across a wide range of health conditions. These medications may have protective effects against severe long-term consequences of COVID-19 by promoting weight loss, exerting antihyperglycemic and anti-inflammatory effects, and providing cardiovascular and endothelial protection. Methods: We evaluated electronic health record data from a retrospective cohort of individuals in the National Clinical Cohort Collaborative. We included individuals with type 2 diabetes mellitus and comorbid COVID-19 who were prescribed either GLP (treatment) or a sodium-glucose co-transporter 2 inhibitor (SGLT2i) and subsequently developed acute COVID-19 between October 1, 2021, and April 1, 2023. We compared the 12-month cumulative incidence of mortality and Long COVID (Long COVID diagnosis and probable Long COVID via computational phenotype) between groups. We applied targeted maximum likelihood estimation to compare outcome risks by exposure status, controlling for covariates of interest. Results: We analyzed data from 14,215 individuals with COVID-19 and comorbid type 2 diabetes (mean age, 60 years; mean BMI, 37). Compared to SGLT2i, a prescription for GLP medication was associated with a lower risk of mortality (adjusted risk ratio [aRR] 0.71; 95% CI 0.53, 0.95), but not Long COVID diagnosis (aRR 1.01; 95% CI 0.80, 1.27) or probable Long COVID (aRR 0.94; 95% CI 0.88, 1.01). Conclusions: We found that among individuals with type 2 diabetes and comorbid COVID-19, a prescription for GLP vs. SGLT2i medications was associated with a lower risk of mortality, but not Long COVID.

Abstract Background: Sarcopenia is associated with anabolic resistance, a blunted muscle protein synthesis response to protein ingestion. Here, we hypothesized that anabolic resistance may be associated with a delayed postprandial decline in circulating plasma amino acids following protein ingestion. We therefore wanted to investigate whether an oral protein tolerance test (OPTT) combined with untargeted plasma metabolomics can detect age-related or sarcopenia-related differences in amino acid time courses consistent with altered postprandial amino acid handling, which could potentially reflect reduced anabolic sensitivity. Moreover, we investigated whether metabolites other than amino acids reacted to the OPTT. Methods: Twelve young healthy adults (controls: 22-28 years) and 12 older adults with clinically diagnosed probable or confirmed sarcopenia (70-91 years) ingested 20 g of whey protein after an overnight fast. We collected venous blood at baseline, 1 h, and 2 h post-ingestion and analyzed the samples by untargeted LC-HRMS plasma metabolomics. Linear mixed-effects models were fitted for 2,968 metabolic features with Benjamini-Hochberg FDR correction. For each category (branched-chain amino acid, essential amino acid [EAA], total amino acid) we summed the within-subject log2 fold changes (FC); fold changes (FC) of the constituent amino acids. This composite is reported as the summed log2FC. Results: 201 metabolites were structurally annotated including 58 amino acid-related metabolites and 97 lipids. Fourteen of 17 proteinogenic amino acids increased significantly after protein ingestion (FDR<0.05). In young controls, essential amino acids rose more steeply at 1 h than in sarcopenic individuals (+10.06 +/- 1.05 vs. +7.84 +/- 1.58 summed log2FC) and declined more between 1 and 2 h (-4.93 +/- 1.29 vs. -0.20 +/- 2.27 summed log2FC). Leucine exemplified this pattern best, rising 1.74 log2FC in controls and declining to 0.96 at 2 h, while remaining elevated at 1.61 log2FC in the sarcopenic group at 2 h (p=0.009). Beyond amino acids, whey protein lowered circulating free fatty acids in both groups (FA 18:2, FA 18:1, FA 16:0; all FDR<0.05). Medium- and long-chain acylcarnitines (Car 8:0, Car14:2) declined postprandially in controls but remained elevated in sarcopenic individuals (p<0.05), suggesting altered postprandial lipid metabolism. Conclusion: In this proof-of-concept study, an OPTT showed that plasma EAAs declined more slowly from their postprandial peak in older adults with sarcopenia than in young adults, consistent with altered postprandial amino acid handling that may reflect anabolic resistance. Whey protein ingestion additionally modulates lipid and acylcarnitine metabolism in an age-dependent manner, suggesting broader alterations in postprandial metabolic regulation in older adults with sarcopenia.

Background: Metformin is one of the most commonly prescribed medications for individuals with diabetes and may provide protection against long-term sequelae of COVID-19. Methods: We evaluated a retrospective cohort of individuals in the National Clinical Cohort Collaborative with type 2 diabetes mellitus and COVID-19 who were prescribed metformin or a dipeptidyl peptidase-4 inhibitor (DPP4i) at least 30 days before the onset of acute COVID-19 between October 1, 2021, and November 15, 2023. We compared the 12-month cumulative incidence of Long COVID diagnosis (ICD-10 U09.9: Post COVID-19 condition, unspecified), probable Long COVID (based on a model-derived phenotype), and mortality between individuals prescribed metformin vs. DPP4i. We applied Super Learner and targeted maximum likelihood estimation to obtain risk ratios while adjusting for covariates of interest. Results: In our sample of 53,332 individuals with type 2 diabetes and COVID-19, we found that metformin prescription was associated with a lower risk of all-cause mortality after COVID-19 (adjusted risk ratio [aRR] 0.61, 95% CI 0.51, 0.73). We also observed that metformin users, compared to DPP4i users, had a slightly lower risk of probable Long COVID (aRR 0.87, 95% CI 0.81, 0.94) but did not detect a significant relationship with Long COVID diagnosis (aRR 0.90, 95% CI 0.68, 1.20), although we observed similar point estimates across Long COVID outcomes. Conclusions: These findings support the hypothesis that metformin prescription during acute COVID-19 may be associated with lower mortality among adults with diabetes. These analyses also provide modest evidence of a protective association against Long COVID in adults with diabetes, although estimates were imprecise.

Background and Objective: Diabetes mellitus (DM) causes autonomic neuropathy, which may alter nocturnal respiratory rate (NRR). To test the association between DM and NRR, we analyzed elective polysomnograms of four large observational cohorts. Research Design and Methods: We performed cross-sectional analysis of over 25,000 individuals with polysomnograms (PSGs) from the Sleep Heart Health Study (SHHS), Hispanic Community Health Study/Study of Latinos (HCHS/SOL), Osteoporotic Fractures in Men Study (MrOS), and Wisconsin Sleep Cohort (WSC). Patient-level NRRs were derived from inductance plethysmography waveforms. DM status was determined by self-report, physician diagnosis, medication use, or laboratory values, depending on the cohort. We related DM and NRR (continuous and dichotomized) using logistic regression models and adjusted for potential confounders. Cohort-specific results were combined using random-effects meta-analysis. Results: Meta-analysis of unadjusted models showed a pooled odds ratio (OR) of 1.10 (95% CI:1.04-1.17) for each breath-per-minute (brpm) increase in NRR. This association remained significant after multivariable adjustment (OR:1.06, 95% CI:1.02-1.11). Dichotomized analyses similarly showed higher odds of DM across dichotomization thresholds ranging from 15 to 21 brpm. At a threshold of 18 brpm, the unadjusted pooled OR was 1.77 (95% CI:1.23-2.55, P=0.0022), and the adjusted OR was 1.49 (95% CI:1.10-2.02, P=0.0098). Conclusions: Clinically stable outpatients with elevated NRR have an increased prevalence of DM. Additional studies are needed to investigate whether the mechanism is autonomic neuropathy and whether monitoring NRR can detect early complications of DM.

This study enrolled 152 hypertensive patients with an ARR > 3.7 to assess the relationship between the traditional hypokalemia cutoff (3.5 mmol/L) and primary aldosteronism (PA) screening, and to establish a new cutoff. Under the traditional cutoff, only 35.7% of PA patients presented with hypokalemia. ROC curve analysis identified a new cutoff of 4.22 mmol/L, which increased sensitivity from 35.7% to 77.5%, with a specificity of 91.1% and an AUC of 0.897. The findings indicate that the traditional cutoff is insufficiently sensitive, while the new cutoff markedly improves screening sensitivity and facilitates early detection of PA.

Background Despite evidence that early intervention can prevent or delay progression to type 2 diabetes, more than 80% of individuals with prediabetes in the United States remain undiagnosed, underscoring the need for scalable strategies to increase uptake. In this study, we evaluated whether a single text message could increase completion of HbA1c-based diabetes screening in routine clinical practice. Methods We conducted a pragmatic randomized controlled trial within Duke University Health System (DUHS). Patients aged 35 years or older who met American Diabetes Association 2022 screening criteria, had no previous diagnosis of diabetes, had not undergone HbA1c testing within the preceding 3 years, and had opted to receive text messages from DUHS were randomly assigned to receive either a single text message encouraging guideline-based diabetes screening and discussion with a primary care provider (intervention group; n=55,494) or usual care (control group; n=5,748). The primary outcome was HbA1c test completion within 24 weeks following message delivery (or no message for controls), analyzed using a Cox proportional hazards model stratified by wave. Secondary outcomes included piecewise hazard ratios for early (weeks 1-4), mid (weeks 5-12), and late (weeks 13-24) intervals and the between-group difference in cumulative testing rate. Findings Text message outreach significantly increased HbA1c test completion over 24 weeks (HR, 1.18 [95% CI, 1.07-1.03]) with the strongest effect in the first four weeks (HR, 1.48 [95% CI, 1.18-1.86]). By the end of the 24-week observation period, cumulative testing reached 9.14% in the messaged group vs 7.83% in controls (between-group difference, 1.31% [95% CI, 0.59-2.07]), corresponding to one additional HbA1c test per 76 messages delivered ($0.51 in messaging costs per additional HbA1c test performed). Rates of prediabetes and diabetes among those screened were similar between groups, indicating no selection bias of higher-risk patients. One additional dysglycemia case was identified per 213 messages sent ($1.43 per case detected).

OBJECTIVE To characterize the prevalence and penetrance of maturity-onset diabetes of the young (MODY) in a multi-ancestry population using a genotype-first design. RESEARCH DESIGN AND METHODS We analyzed whole-genome sequencing and clinical data from 374,973 unrelated All of Us participants (42.0% non-European ancestry). We identified pathogenic or likely pathogenic (P/LP) variants in 10 established MODY genes and assessed carrier prevalence, diabetes penetrance, and glycemic profiles. We evaluated age-dependent diabetes risk by comparing carriers with non-carriers stratified by type 2 diabetes polygenic risk score (T2D PRS). RESULTS We identified 370 carriers of P/LP MODY gene variants (0.099%; 1 in 1,013), with similar carrier prevalence among European- and African-ancestry participants (0.105% in both groups). Diabetes penetrance was incomplete (13.4% by age 40; 43.5% by age 60) and varied by etiology: highest for GCK (56.0% by age 60), intermediate for HNF genes (HNF1A/HNF1B/HNF4A; 45.4%), and lowest for non-GCK/HNF genes (ABCC8/INS/KCNJ11/NEUROD1/PDX1/RFX6; 29.0%). In multivariable Cox models using non-carriers in the middle 80% of the T2D PRS as the reference, non-GCK/HNF gene variant carriers had modestly increased diabetes risk (HR, 1.57), similar to non-carriers in the top 10% of T2D PRS (HR, 1.64). These associations were observed in both European- and non-European-ancestry individuals. HbA1c profiles differed by etiology, with stable mild hyperglycemia in GCK variant carriers and greater variability among HNF and non-GCK/HNF gene variant carriers. CONCLUSIONS MODY gene variants showed incomplete, etiology-dependent penetrance across ancestries. Carriers of P/LP variants in lower-penetrance genes had diabetes risk comparable to that of non-carriers with high polygenic susceptibility.

Importance: Higher coffee intake has been associated with lower risk of type 2 diabetes (T2D), but the underlying biological pathways remain incompletely understood. Objective: To examine associations of coffee intake with insulin sensitivity, adiposity, and T2D risk, and assess whether coffee intake modifies associations between pathway-specific genetic susceptibility and incident T2D. Design, Setting, and Participants: Cross-sectional analyses among 806 participants without T2D in the VITamin D and OmegA-3 TriaL (VITAL) clinical sub-cohort, who underwent repeated dietary assessment, clinical phenotyping, and dual-energy X-ray absorptiometry imaging at baseline and year-2. Prospective analyses among 333,053 UK Biobank participants without T2D at baseline who had dietary and genetic data and were followed for a median of 13.3 years. Exposures: Coffee intake assessed by food frequency questionnaires. In UK Biobank, 12 pathway-specific polygenic scores (pPS) representing distinct T2D pathophysiological mechanisms were evaluated. Main Outcomes and Measures: The primary outcomes, in VITAL, were HbA1c, oral glucose tolerance test-derived measures of glucose response and insulin sensitivity, beta-cell function, and overall, truncal, and visceral adiposity; in UK Biobank, was incident T2D. Results: In VITAL, higher coffee intake was associated with higher insulin sensitivity (standardized beta; per cup/day, 0.046; P = .004) and lower visceral adipose tissue mass (beta -0.047; P = .006), after adjusting for demographic, lifestyle, and clinical factors, including body mass index. In UK Biobank, higher coffee intake was associated with lower T2D incidence (hazard ratio per cup/day, 0.96; 95% CI, 0.95-0.97), lower triglyceride-to-HDL cholesterol ratio (beta: -0.01; P = 2.51 x 10-19), and lower visceral adipose tissue mass (beta: -0.01; P = 4.28 x 10-9). Associations of 3 pPS related to insulin resistance and fat distribution with incident T2D were attenuated among participants consuming higher amount of coffee than among non-consumers (P for interaction < .0043). Conclusions and Relevance: Higher coffee intake was associated with greater insulin sensitivity, lower visceral adiposity, and lower risk of T2D. Together with the attenuation of associations between pathway-specific genetic susceptibility and T2D risk among higher coffee consumers, these findings suggest that insulin resistance and visceral adiposity-related pathways may contribute to the association between coffee intake and T2D risk.

Background: The urinary sodium-to-potassium (Na/K) ratio is an integrated biomarker associated with cardiovascular risk. However, its association with deep white matter lesions (DWMLs), a manifestation of cerebral small vessel disease (CSVD), remains unclear. We investigated the associations of the urinary Na/K ratio and albuminuria with DWMLs. Methods: We conducted a cross-sectional study of 296 Japanese adults (mean age, 68.7 years). Brain magnetic resonance imaging was used to assess DWMLs using the Fazekas scale, and lesions were classified as absent (grade 0) or present (grades 1?3). The urinary Na/K ratio and albumin excretion were measured using 24-h urine collections. Multivariable logistic regression models examined the associations between urinary biomarkers and DWMLs. Results: DWMLs were present in 119 (40.2%) participants. A higher urinary Na/K ratio was independently associated with DWMLs (odds ratio per 1?standard deviation increase, 1.44; 95% confidence interval, 1.09?1.90; P=0.010). Participants in the highest quartile had greater odds of DWMLs than those in the lowest quartile (odds ratio, 2.48; 95% confidence interval, 1.16?5.29; P=0.019). Urinary potassium excretion was inversely associated with DWMLs, whereas urinary sodium excretion alone showed no significant association. Findings were consistent across sensitivity and subgroup analyses. Conclusions: A higher 24-h urinary Na/K ratio was independently associated with DWMLs in older adults. This association appeared to be driven primarily by lower urinary potassium excretion rather than higher sodium excretion alone. The urinary Na/K ratio may serve as a simple, noninvasive marker of CSVD.

Background: The joint association of the C-reactive protein-triglyceride glucose index-frailty index (CTI-FI) and non-exercise estimated cardiorespiratory fitness (eCRF) with all-cause mortality (ACM) in adults aged [&ge;]45 years with cardiovascular-kidney-metabolic (CKM) syndrome stages 0-3 remains unexplored. Methods: Participants were enrolled from the National Health and Nutrition Examination Survey (NHANES; derivation cohort) and the China Health and Retirement Longitudinal Study (CHARLS; external validation). Covariate selection was performed using LASSO regression. Weighted Cox models were applied across four adjustment models to evaluate the independent associations of CTI-FI and eCRF with ACM. Dose-response patterns were examined with restricted cubic splines (RCS). Subgroup, sex-stratified, and mediation analyses tested robustness and pathways. Results: A total of 6,662 participants from NHANES (median follow-up 10 years; 1,276 ACM, 19.2%) and 3,418 participants from CHARLS (9 years; 391 deaths, 11.4%) were included. Per 1-unit increase in CTI-FI, the risks increased by 44% for ACM (HR 1.44; 95% CI 1.31-1.57) and by 54% for cardiovascular mortality (CVM, HR 1.54; 95% CI 1.33-1.79); per 1-MET increase in eCRF, the risks decreased by 10% (HR 0.90; 95% CI 0.85-0.94) and by 18% (HR 0.82; 95% CI 0.75-0.90), respectively (all P < 0.001). Compared with the low CTI-FI + high eCRF group, the high CTI-FI + low eCRF group was associated with a significantly higher risk of ACM (HR 2.74; 95% CI 2.20-3.40) and CVM (HR 5.04; 95% CI 3.02-8.40). RCS analysis showed a nonlinear CTI-FI-ACM association. The model with CTI-FI and eCRF achieved a C-index of 0.78 for ACM and 0.825 for CVM. CTI-FI and eCRF bidirectionally mediated each other's associations with ACM and CVM. Specifically, eCRF accounted for 16.4%-23.5% of CTI-FI-related mortality risk, whereas CTI-FI accounted for 23.9%-32.2% of eCRF's survival benefit (all P < 0.001). Conclusions: Higher CTI-FI and lower eCRF independently and jointly predict increased mortality, with bidirectional mediation indicating that improving one may partially offset the adverse effect of the other. These findings highlight potential therapeutic targets for early CKM syndrome management.