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OBJECTIVE: The potential for choline metabolism to influence the development of diabetes has received increased attention. Previous studies on circulating choline metabolites and incident diabetes have been conducted in samples of older adults, often with a high prevalence of risk factors. RESEARCH DESIGN AND METHODS: Participants were from year 15 of follow-up (2000-2001) in the Coronary Artery Risk Development in Young Adults (CARDIA) Study (n = 3,133, aged 33-45 years) with plasma choline metabolite (choline, betaine, and trimethylamine N-oxide [TMAO]) data. We quantified associations between choline metabolites and 15-year risk of incident diabetes (n = 387) among participants free of diabetes at baseline using Cox proportional hazards regression models adjusted for sociodemographics, health behaviors, and clinical variables. RESULTS: Betaine was inversely associated with 15-year risk of incident diabetes (hazard ratio 0.76 [95% CI 0.67, 0.88] per 1-SD unit betaine), and TMAO was positively associated with 15-year risk of incident diabetes (1.11 [1.01, 1.22] per 1-SD unit). Choline was not significantly associated with 15-year risk of incident diabetes (1.05 [0.94, 1.16] per 1-SD). CONCLUSIONS: Our findings are consistent with other published literature supporting a role for choline metabolism in diabetes. Our study extends the current literature by analyzing a racially diverse population-based cohort of early middle-aged individuals in whom preventive activities may be most relevant.

BACKGROUND: The University of Californias Diabetes Prevention Program (UC DPP) Initiative was implemented systemwide to address diabetes and obesity risk on all 10 campuses. As little is known about implementing lifestyle change programs in university settings, we examined implementation partners (i.e., UC DPP leaders and campus leads) perceptions of factors influencing program success on UC campuses. METHODS: We conducted qualitative interviews with UC DPP leaders and campus leads to examine challenges and opportunities with university-based DPP delivery models. Interviews were recorded, professionally transcribed, and reviewed in detail by the research team. Transcripts were analyzed using rapid qualitative analysis (RQA). The study was approved by the UCLA Institutional Review Board. All implementation partners provided verbal informed consent. RESULTS: Twenty-six implementation partners (8 UC DPP leaders and 18 campus leads) completed interviews in 2021. Seven themes were identified as critical for implementation, including (1) marketing and recruitment (i.e., market and recruit broadly through established channels as well as target at-risk populations); (2) enrollment (i.e., offer the program during convenient times and let participants know what to expect); (3) use an adaptable, evidence-based program; (4) secure funding for the program, participants, lifestyle coaches, and space; (5) hire experienced and dedicated staff and lifestyle coaches; (6) ensure leadership support; and (7) utilize campus linkages and resources. Perceptions of challenges faced with respect to these themes are also described. CONCLUSIONS: This is one of the first studies to examine the challenges and opportunities of delivering an intensive lifestyle change program across 10 university sites. Understanding factors that enhance success of university-based diabetes prevention programs can facilitate UC DPP efforts and help inform delivery strategies of health and wellness programs across other university settings more broadly.

Type 2 diabetes mellitus (T2DM) increases the risk of neurological diseases, yet how brain oscillations change as age and T2DM interact is not well characterized. To delineate the age and diabetic effect on neurophysiology, we recorded local field potentials with multichannel electrodes spanning the somatosensory cortex and hippocampus (HPC) under urethane anesthesia in diabetic and normoglycemic control mice, at 200 and 400 days of age. We analyzed the signal power of brain oscillations, brain state, sharp wave associate ripples (SPW-Rs), and functional connectivity between the cortex and HPC. We found that while both age and T2DM were correlated with a breakdown in long-range functional connectivity and reduced neurogenesis in the dentate gyrus and subventricular zone, T2DM further slowed brain oscillations and reduced theta-gamma coupling. Age and T2DM also prolonged the duration of SPW-Rs and increased gamma power during SPW-R phase. Our results have identified potential electrophysiological substrates of hippocampal changes associated with T2DM and age. The perturbed brain oscillation features and diminished neurogenesis may underlie T2DM-accelerated cognitive impairment.

Diabetes is the leading cause and a common comorbidity of advanced chronic kidney disease. Glycaemic management in this population is challenging and characterised by frequent excursions of hypoglycaemia and hyperglycaemia. Current glucose monitoring tools, such as HbA1c, fructosamine and glycated albumin, have biases in this population and provide information only on mean glucose exposure. Revolutionary developments in glucose sensing and insulin delivery technology have occurred in the last decade. Newer factory-calibrated continuous glucose monitors provide real-time glucose data, with predictive alarms, allowing improved assessment of glucose excursions and preventive measures, particularly during and between dialysis sessions. Furthermore, integration of continuous glucose monitors and their predictive alerts with automated insulin delivery systems enables insulin administration to be decreased or stopped proactively, leading to improved glycaemic management and diminishing glycaemic fluctuations. While awaiting regulatory approval, emerging studies, expert real-world experience and clinical guidelines support the use of diabetes technology devices in people with diabetes and advanced chronic kidney disease.

Understanding chronic kidney disease (CKD) through the lens of evolutionary biology highlights the mismatch between our Paleolithic-optimized genes and modern diets, which led to the dramatically increased prevalence of CKD in modern societies. In particular, the Standard American Diet (SAD), high in carbohydrates and ultra-processed foods, causes conditions like type 2 diabetes (T2D), chronic inflammation, and hypertension, leading to CKD. Autosomal dominant polycystic kidney disease (ADPKD), a genetic form of CKD, is characterized by progressive renal cystogenesis that leads to renal failure. This review challenges the fatalistic view of ADPKD as solely a genetic disease. We argue that, just like non-genetic CKD, modern dietary practices, lifestyle, and environmental exposures initiate and accelerate ADPKD progression. Evidence shows that carbohydrate overconsumption, hyperglycemia, and insulin resistance significantly impact renal health. Additionally, factors like dehydration, electrolyte imbalances, nephrotoxin exposure, gastrointestinal dysbiosis, and renal microcrystal formation exacerbate ADPKD. Conversely, carbohydrate restriction, ketogenic metabolic therapy (KMT), and antagonizing the lithogenic risk show promise in slowing ADPKD progression. Addressing disease triggers through dietary modifications and lifestyle changes offers a conservative, non-pharmacological strategy for disease modification in ADPKD. This comprehensive review underscores the urgency of integrating diet and lifestyle factors into the clinical management of ADPKD to mitigate disease progression, improve patient outcomes, and offer therapeutic choices that can be implemented worldwide at low or no cost to healthcare payers and patients.

BACKGROUND: This study aimed to test the efficacy of patient-centered self-management intervention (PACE-SMI) to improve HbA1c, self-efficacy, and self-care behaviors in adults with type 2 diabetes mellitus (T2DM). METHODS: In this multicenter, parallel two-arm randomized controlled trial, 612 adults with T2DM and HbA1c ≥ 7% were enrolled and assigned to the control group (n = 310) and the intervention group (n = 302) using stratified permuted block randomization. The control group received usual care, whereas the intervention group received usual care plus nurse-led, theory-driven, culturally tailored PACE-SMI, comprising eight weekly sessions of individualized education, counseling, behavioral training, and home visit. Outcomes were assessed at baseline, postintervention, and 3 months follow-up. RESULTS: Data at 3 months were provided by 583 participants (control: n = 295, intervention: n = 288). Per-protocol analysis showed that the intervention group had a lower mean HbA1c (8.49% [standard deviation (SD), 1.58]) than the control group (8.74% [SD, 1.62]), with small yet statistically significant mean difference of 0.25% (95% confidence interval [CI], -0.01 to 0.51; Cohens d = 0.16; p = 0.03). Self-efficacy and self-care behaviors significantly improved in the intervention group (116.89 [SD, 25.50] and 70.01 [SD, 17.97]) compared to the control group (75.43 [SD, 18.99] and 51.54 [SD, 12.04]), with mean differences of 41.48 (95% CI, 37.83-45.13; Cohens d = 1.84; p

This article summarises the state of the science on the role of the gut microbiota (GM) in diabetes from a recent international expert forum organised by Diabetes, Diabetes Care, and Diabetologia, which was held at the European Association for the Study of Diabetes 2023 Annual Meeting in Hamburg, Germany. Forum participants included clinicians and basic scientists who are leading investigators in the field of the intestinal microbiome and metabolism. Their conclusions were as follows: (1) the GM may be involved in the pathophysiology of type 2 diabetes, as microbially produced metabolites associate both positively and negatively with the disease, and mechanistic links of GM functions (e.g. genes for butyrate production) with glucose metabolism have recently emerged through the use of Mendelian randomisation in humans; (2) the highly individualised nature of the GM poses a major research obstacle, and large cohorts and a deep-sequencing metagenomic approach are required for robust assessments of associations and causation; (3) because single time point sampling misses intraindividual GM dynamics, future studies with repeated measures within individuals are needed; and (4) much future research will be required to determine the applicability of this expanding knowledge to diabetes diagnosis and treatment, and novel technologies and improved computational tools will be important to achieve this goal.

Objectives: Fractal analysis is a numerical method that indicates the structural patterns and complexity of the trabecular bone on radiographs. The aim of this cross-sectional study was to evaluate the trabecular bone structure in systemically healthy patients and diabetes mellitus patients with periodontitis using fractal analysis. Method and materials: The study included 125 mandibular first molars of nonsmoker patients. The subjects were divided into five subgroups: diabetes mellitus patients with mild-moderate periodontitis, diabetes mellitus patients with advanced periodontitis, systemically healthy individuals with mild-moderate periodontitis, systemically healthy individuals with advanced periodontitis, and systemically healthy individuals with gingivitis (control group). Clinical periodontal parameters (pocket depth, bleeding on probing, clinical attachment loss, and bone loss) were recorded. Two specific sites located in the mesial-distal regions (n = 250) of the mandibular first molars were identified using periapical radiographs captured with a parallel technique. Fractal analysis values were calculated using the box-counting method. One-way analysis of variance (ANOVA), and Pearson correlation analysis were used forstatistical evaluation. Results: The highest fractal analysis values were observed in systemically healthy with gingivitis patients (mesial fractal analysis: 1.86 ± 0.01; distal fractal analysis: 1.85 ±0.01). Patients with periodontitis (mesial fractal analysis: 1.78 ±0.02; distal fractal analysis: 1.79 ± 0.01) exhibited lower fractal analysis values compared to the control group. There was no significant difference in mesial and distal fractal analysis values between all periodontitis groups. No correlation was found between age, sex, clinical attachment loss, bone loss, and fractal analysis (P>.05). Conclusions: Although fractal analysis values were lower in the periodontitis groups compared to the control group, fractal analysis did not demonstrate any periodontitis-associated changes of bone tra-beculationin diabetes at any stage of periodontitis. Furthermore, there was no significant association between fractal analysis values and age, sex, clinical attachment, and bone loss. [ABSTRACT FROM AUTHOR]

Aberration of the "gut-liver axis" contributes to the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Here, we use multi-omics to analyze the gut microbiota composition and metabolic profile of patients with type-2 diabetes mellitus (T2DM). T2DM patients were screened for liver disease by blood tests, ultrasound, and liver stiffness measurements. Stool microbiota was analyzed by 16S rRNA gene sequencing; metabolomic profiling by Nuclear Magnetic Resonance spectroscopy and Ultra-High Performance-Mass Spectrometry. Microbiome and metabolic signatures were analyzed in the whole cohort and in matched subsets to identify signatures specific for steatosis (MASLD±) or fibrosis (Fibrosis±). Gut permeability was assessed in-vitro using monolayers of MDCK cells and trans-epithelial electric resistance (TEER). Cytokine profile was assessed in serum and stools.Overall, 285 patients were enrolled: 255 serum, 252 urine and 97 stool samples were analyzed. Anaeroplasma and Escherichia/Shigella ASVs were higher, while Butyricicoccus ASVs were lower in those with normal liver. In MASLD±, Butyricicoccus ASV was significantly higher in those with steatosis. In the Fibrosis±, Butyricicoccus ASV was significantly lower in those with fibrosis. Glycochenodeoxycholic acid-3-sulfate (G-UDCA-3S) appeared to be higher in MASLD with fibrosis. Fecal water from patients with MASLD and fibrosis caused the greatest drop in the TEER vs those with normal liver; this was reversed with protease inhibitors. Finally, fecal IL-13 was lower in MASLD with fibrosis. We identified microbiome signatures which were specific for steatosis and fibrosis and independent of other metabolic risk factors. Moreover, we conclude that protease-related gut permeability plays a role in those MASLD patients with fibrosis, and that disease progression is linked to a gut-liver axis which is at least partially independent of T2DM.

Long-lived PFKFB3-expressing β-cells are dysfunctional partly because of prevailing glycolysis that compromises metabolic coupling of insulin secretion. Their accumulation in type 2 diabetes (T2D) appears to be related to the loss of apoptotic competency of cell fitness competition that maintains islet function by favoring constant selection of healthy winner cells. To investigate how PFKFB3 can disguise the competitive traits of dysfunctional loser β-cells, we analyzed the overlap between human β-cells with bona fide loser signature across diabetes pathologies using the HPAP scRNA-seq and spatial transcriptomics of PFKFB3-positive β-cells from nPOD T2D pancreata. The overlapping transcriptional profile of loser β-cells was represented by down-regulated ribosomal biosynthesis and genes encoding for mitochondrial respiration. PFKFB3-positive loser β-cells had the reduced expression of HLA class I and II genes. Gene-gene interaction analysis revealed that PFKFB3 rs1983890 can interact with the anti-apoptotic gene MAIP1 implicating positive epistasis as a mechanism for prolonged survival of loser β-cells in T2D. Inhibition of PFKFB3 resulted in the clearance of dysfunctional loser β-cells leading to restored glucose tolerance in the mouse model of T2D.