BMJ Open Diabetes Research & Care最新文献

Introduction: Diabetes is linked to neurodegenerative diseases (NDs), but data in type 1 diabetes are scarce. Our aim was to assess the standardized incidence ratios (SIRs) of different NDs in type 1 diabetes, and to evaluate the impact of diabetic vascular complications and age at diabetes onset.

Research design and methods: In this observational cohort study, we included 4261 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study, and 11 653 matched population-based controls without diabetes. NDs were identified from registers until the end of 2017. Diabetic complications were assessed at the baseline study visit. SIRs were calculated from diabetes onset, except for impact of complications that was calculated from baseline study visit.

Results: The SIRs for NDs were increased in type 1 diabetes: any dementia 2.24 (95% CI 1.79 to 2.77), Alzheimer's disease 2.13 (95% CI 1.55 to 2.87), vascular dementia 3.40 (95% CI 2.08 to 5.6), other dementias 1.70 (95% CI 1.22 to 2.31), and Parkinson's disease 1.61 (95% CI 1.04 to 2.37). SIR showed a twofold increased incidence already in those without albuminuria (1.99 (1.44-2.68)), but further increased in presence of diabetic complications: kidney disease increased SIR for Alzheimer's disease, while cardiovascular disease increased SIR for both Alzheimer's disease and other dementias. Diabetes onset <15 years, compared with ≥15 years, increased SIR of Alzheimer's disease, 3.89 (2.21-6.35) vs 1.73 (1.16-2.48), p<0.05, but not the other dementias.

Conclusions: ND incidence is increased 1.7-3.4-fold in type 1 diabetes. The presence of diabetic kidney disease and cardiovascular disease further increased the incidence of dementia.

Introduction: Diabetes disparities exist based on socioeconomic status, race, and ethnicity. The aim of this study is to compare two cohorts with diabetes from California and Florida to better elucidate how health outcomes are stratified within underserved communities according to state location, race, and ethnicity.

Research design and methods: Two cohorts were recruited for comparison from 20 Federally Qualified Health Centers as part of a larger ECHO Diabetes program. Participant-level data included surveys and HbA1c collection. Center-level data included Healthcare Effectiveness Data and Information Set metrics. Demographic characteristics were summarized overall and stratified by state (frequencies, percentages, means (95% CIs)). Generalized linear mixed models were used to compute and compare model-estimated rates and means.

Results: Participant-level cohort: 582 adults with diabetes were recruited (33.0% type 1 diabetes (T1D), 67.0% type 2 diabetes (T2D)). Mean age was 51.1 years (95% CI 49.5, 52.6); 80.7% publicly insured or uninsured; 43.7% non-Hispanic white (NHW), 31.6% Hispanic, 7.9% non-Hispanic black (NHB) and 16.8% other. Center-level cohort: 32 796 adults with diabetes were represented (3.4% with T1D, 96.6% with T2D; 72.7% publicly insured or uninsured). Florida had higher rates of uninsured (p<0.0001), lower continuous glucose monitor (CGM) use (18.3% Florida; 35.9% California, p<0.0001), and pump use (10.2% Florida; 26.5% California, p<0.0001), and higher proportions of people with T1D/T2D>9% HbA1c (p<0.001). Risk was stratified within states with NHB participants having higher HbA1c (mean 9.5 (95% CI 8.9, 10.0) compared with NHW with a mean of 8.4 (95% CI 7.8, 9.0), p=0.0058), lower pump use (p=0.0426) and CGM use (p=0.0192). People who prefer to speak English were more likely to use a CGM (p=0.0386).

Conclusions: Characteristics of medically underserved communities with diabetes vary by state and by race and ethnicity. Florida's lack of Medicaid expansion could be a factor in worsened risks for vulnerable communities with diabetes.

Introduction: Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.

Research design and methods: Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).

Results: The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).

Conclusions: Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

The prevalence of type 2 diabetes (T2D) is increasing relentlessly all over the world, in parallel with a similar increase in obesity, and is striking ever younger patients. Only a minority of patients with T2D attain glycemic targets, indicating a clear need for novel antidiabetic drugs that not only control glycemia but also halt or slow the progressive loss of β-cells. Two entirely novel classes of antidiabetic agents-glucokinase activators and imeglimin-have recently been approved and will be the subject of this review.Allosteric activators of glucokinase, an enzyme stimulating insulin secretion in β-cells and suppressing hepatic glucose production, are oral low-molecular-weight drugs. One of these, dorzagliatin, is approved in China for use in adult patients with T2D, either as monotherapy or as an add-on to metformin. It remains to be seen whether the drug will produce sustained antidiabetic effects over many years and whether the side effects that led to the discontinuation of early drug candidates will limit the usefulness of dorzagliatin.Imeglimin-which shares structural similarities with metformin-targets mitochondrial dysfunction and was approved in Japan against T2D. In preclinical studies, the drug has also shown promising β-cell protective and preservative effects that may translate into disease-modifying effects.Hopefully, these two newcomers will contribute to filling the great medical need for new treatment modalities, preferably with disease-modifying potential. It remains to be seen where they will fit in contemporary treatment algorithms, which combinations of drugs are effective and which should be avoided. Time will tell to what extent these new antidiabetic agents will add value to the current treatment options against T2D in terms of sustained antidiabetic effect, acceptable safety, utility in combination therapy, and impact on hard end-points such as cardiovascular disease.

Introduction: Adipsin or complement factor D is an adipokine that augments insulin secretion, is altered in various degrees of obesity, and is involved in alternative complement pathway. However, whether adipsin has any independent association with risk factors and biomarkers in patients with type 2 diabetes (T2D) remains elusive.

Research design and methods: We performed an oral glucose tolerance test on a subset of 43 patients with T2D from the community health cohort to access the role of adipsin in insulin secretion. We further cross-sectionally examined the role of adipsin in plasma, adipose tissue (AT), and secretion in a community cohort of 353 subjects and a hospital cohort of 52 subjects.

Results: We found that plasma adipsin has no significant correlation with insulin secretion in people with diabetes. Among the risk factors of T2D, adipsin levels were independently associated only with age, and a positive correlation between plasma adipsin and age among subjects without T2D was lost in patients with T2D. Plasma adipsin levels, AT adipsin expression, and secretion were upregulated both in T2D and aging, with a corresponding drop in Homeostatic Model Assessment for assessing β-cell function. Adipsin expression was positively associated with other aging biomarkers, such as β-galactosidase, p21, and p16. These results also corroborated with existing plasma proteomic signatures of aging, including growth, and differentiation factor-15, which strongly correlated with adipsin.

Conclusions: Our results demonstrate an increase in circulating adipsin in T2D and aging, and it scores as a candidate plasma marker for aging specifically in non-T2D population.

Introduction: In Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health problem, the empirical understanding of the actual risks remains limited. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.

Research design and methods: We placed custom-designed particle samplers in Kuwait to collect daily dust samples for 2 years from 2017 to 2019. Samples were analyzed for elemental concentrations to identify and quantify dust pollution days. Temperature data were collected from meteorological stations. We then collected hospitalization data for unplanned diabetic admissions in all public hospitals in Kuwait. We used a case-crossover study design and conditional quasi-Poisson models to compare hospitalization days to control days within the same subject. Finally, we fitted generalized additive models to explore the smoothed interaction between temperature and dust days on diabetes hospitalization.

Results: There were 11 155 unplanned diabetes hospitalizations over the study period. We found that each year, there was an excess of 282 diabetic admissions attributed to hot days (95% CI: -14 to 473). Additionally, for every 10 µg/m³ increase in dust levels, there were about 114 excess diabetic admissions annually (95% CI: 11 to 219). Compared with mild non-dusty days (33°C (0 µg/m³)), hot-dusty days jointly increased the relative risk of diabetic admissions from 1.11 at 42°C (85 µg/m³) to 1.36 at 42°C (150 µg/m³).

Conclusions: Both heat and dust seem to contribute to the increased diabetes morbidity, with combined hot-dusty conditions exacerbating these risks even further.

Introduction: We undertook phenotypic characterization of early-onset and late-onset type 2 diabetes (T2D) in adult black African and white European populations with recently diagnosed T2D to explore ethnic differences in the manifestation of early-onset T2D.

Research design and methods: Using the Uganda Diabetes Phenotype study cohort of 500 adult Ugandans and the UK StartRight study cohort of 714 white Europeans with recently diagnosed islet autoantibody-negative T2D, we compared the phenotypic characteristics of participants with early-onset T2D (diagnosed at <40 years) and late-onset T2D (diagnosed at ≥40 years).

Results: One hundred and thirty-four adult Ugandans and 113 white Europeans had early-onset T2D. Compared with late-onset T2D, early-onset T2D in white Europeans was significantly associated with a female predominance (52.2% vs 39.1%, p=0.01), increased body mass index (mean (95% CI) 36.7 (35.2-38.1) kg/m² vs 33.0 (32.4-33.6) kg/m², p<0.001), waist circumference (112.4 (109.1-115.6) cm vs 108.8 (107.6-110.1) cm, p=0.06), and a higher frequency of obesity (82.3% vs 63.4%, p<0.001). No difference was seen with the post-meal C-peptide levels as a marker of beta-cell function (mean (95% CI) 2130.94 (1905.12-2356.76) pmol/L vs 2039.72 (1956.52-2122.92), p=0.62).In contrast, early-onset T2D in Ugandans was associated with less adiposity (mean (95% CI) waist circumference 93.1 (89.9-96.3) cm vs 97.4 (95.9-98.8) cm, p=0.006) and a greater degree of beta-cell dysfunction (120 min post-glucose load C-peptide mean (95% CI) level 896.08 (780.91-1011.24) pmol/L vs 1310.10 (1179.24-1440.95) pmol/L, p<0.001), without female predominance (53.0% vs 57.9%, p=0.32) and differences in the body mass index (mean (95% CI) 27.3 (26.2-28.4) kg/m² vs 27.9 (27.3-28.5) kg/m², p=0.29).

Conclusions: These differences in the manifestation of early-onset T2D underscore the need for ethnic-specific and population-specific therapeutic and preventive approaches for the condition.

Introduction: People with diabetes are at risk of developing chronic kidney disease. However, limited data are available to quantify their risk of kidney function decline in South Asia. This study evaluates the rate and predictors of kidney function decline among people with type 2 diabetes in South Asia.

Research design and methods: We analyzed data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) Trial to quantify the rate of decline in estimated glomerular filtration rate (eGFR) in people with type 2 diabetes (n=1146) over 2.5 years of follow-up. The CARRS Trial evaluated a multicomponent intervention of decision-supported electronic health records and non-physician care coordinator to improve diabetes management at 10 diabetes clinics in India and Pakistan. We used linear mixed models to estimate eGFR slope among all participants and tested the association of eGFR slope with demographic, disease-related, and self-care parameters, accounting for randomization and site.

Results: The mean age of participants was 54.2 years, with a median duration of diabetes of 7.0 years (IQR: 3.0 - 12.0) and median CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) eGFR of 83.6 (IQR: 67.7 to 97.9) mL/min/1.73 m². The overall mean eGFR slope was -1.33/mL/min/1.73 m²/year. There were no differences in the eGFR slope by treatment assignment to intervention versus usual care. In the adjusted regression model, pre-existing diabetic retinopathy (slope difference: -2.11; 95% CI: -3.45 to -0.77), previous cardiovascular disease (-1.93; 95% CI: -3.45 to -0.40), and statins use (-0.87; 95% CI: -1.65 to -0.10) were associated with faster eGFR decline.

Conclusions: People with diabetes receiving care at urban diabetes clinics in South Asia experienced annual eGFR decline at two times higher rate than that reported from other contemporary international diabetes cohorts. Risk factors for faster decline were similar to those previously established, and thus care delivery models must put an additional emphasis on kidney protective therapies among subgroups with microvascular and macrovascular diabetes complications.

Trial registration number: NCT01212328.

Introduction: The prevalence of non-diabetic hyperglycemia (NDH) and type 2 diabetes mellitus (T2DM) is increasing. While T2DM is recognised to be associated with multimorbidity and early mortality, people with NDH are frequently thought to be devoid of such complications, potentially exposing individuals with NDH to suboptimal care. We therefore used the Discover London Secure Data Environment (SDE) dataset to appreciate the relationship of NDH/T2DM with multimorbidity, healthcare usage, and clinical outcomes.

Research design and methods: The dataset was retrospectively analysed between January 1, 2015 and December 31, 2020 to understand the relationship between NDH/T2DM and multimorbidity primary/secondary healthcare usage and clinical outcomes. This was compared with a cohort of individuals with thyroid disease but no NDH/T2DM.

Results: The dataset identified 152,384 and 124,190 adults with NDH and T2DM compared with 11,626 individuals with thyroid disease (control group). Individuals with NDH and individuals with T2DM had a high burden of disease, with only 13.1% of individuals with either NDH or T2DM not found to be suffering from at least one of the disease states of interest. The three most common comorbidities experienced by individuals with NDH were hypertension (41.4%), hypercholesterolemia (37.5%), and obesity (29.8%) compared with retinopathy (68.7%), hypertension (59.4%), and obesity (45.8%) in individuals with T2DM. Comparatively, the most common comorbidities in the control group were depression (30.8%), hypercholesterolemia (24.4%), and hypertension (17.1%). 28 (control group), 12 (NDH), and 16 (T2DM) primary care contacts per individual per year were identified, with 27,881, 282,371, and 314,880 inpatient admissions for the control, NDH, and T2DM cohorts, respectively. Prescription of drugs used to treat T2DM in individuals with NDH and T2DM was 27,772 (18.2%) and 109,361 (88.1%), respectively, accounting for approximately one in five individuals with NDH developing T2DM.

Conclusion: Both NDH and T2DM were associated with significant multimorbidity alongside primary and secondary care utilisation. Given the morbidity highlighted with NDH, we highlight the need for earlier detection of NDH, recognition of multimorbidity associated with both NDH and T2DM, as well as the need for the further implementation of interventions to prevent progression to T2DM/multimorbidity.

Introduction: Chronic hyperglycemia affects neutrophil functions, leading to reduced pathogen killing and increased morbidity. This impairment has been directly linked to increased glycemia, however, how this specifically affects neutrophils metabolism and their differentiation in the bone marrow is unclear and difficult to study.

Research design and methods: We used high-resolution respirometry to investigate the metabolism of resting and activated donor neutrophils, and flow cytometry to measure surface CD15 and CD11b expression. We then used HL-60 cells differentiated towards neutrophil-like cells in standard media and investigated the effect of doubling glucose concentration on differentiation metabolism. We measured the oxygen consumption rate (OCR), and the enzymatic activity of carnitine palmitoyl transferase 1 (CPT1) and citrate synthase during neutrophil-like differentiation. We compared the surface phenotype, functions, and OCR of neutrophil-like cells differentiated under both glucose concentrations.

Results: Donor neutrophils showed significant instability of CD11b and OCR after phorbol 12-myristate 13-acetate stimulation at 3 hours post-enrichment. During HL-60 neutrophil-like cell differentiation, there was a significant increase in surface CD15 and CD11b expression together with the loss of mitochondrial mass. Differentiated neutrophil-like cells also exhibited higher CD11b expression and were significantly more phagocytic. In higher glucose media, we measured a decrease in citrate synthase and CPT1 activities during neutrophil-like differentiation.

Conclusions: HL-60 neutrophil-like differentiation recapitulated known molecular and metabolic features of human neutrophil differentiation. Increased glucose concentrations correlated with features described in hyperglycemic donor neutrophils including increased CD11b and phagocytosis. We used this model to describe metabolic features of neutrophil-like cell differentiation in hyperglycemia and show for the first time the downregulation of CPT1 and citrate synthase activity, independently of mitochondrial mass.