Patients with type 1 diabetes receiving regular care were recruited in this observational cross-sectional study and divided into four groups according to their Lp(a) levels in nmol/L (very low <10, low 10–30, intermediate 30–120, high >120). Prevalence of vascular complications was compared between the groups. In addition, the association between metabolic control, measured as HbA_1c, and Lp(a) was studied.

The patients (n = 1,860) had a median age of 48 years, diabetes duration of 25 years, and HbA_1c of 7.8% (61 mmol/mol). The median Lp(a) was 19 (interquartile range 10–71) nmol/L. No significant differences between men and women were observed, but Lp(a) levels increased with increasing age. Patients in the high Lp(a) group had higher prevalence of complications than patients in the very low Lp(a) group. The age- and smoking-status–adjusted relative risk ratio of having any macrovascular disease was 1.51 (95% CI 1.01–2.28, P = 0.048); coronary heart disease, 1.70 (95% CI 0.97–3.00, P = 0.063); albuminuria, 1.68 (95% CI 1.12–2.50, P = 0.01); and calcified aortic valve disease, 2.03 (95% CI 1.03–4.03; P = 0.042). Patients with good metabolic control, HbA_1c <6.9% (<52 mmol/mol), had significantly lower Lp(a) levels than patients with poorer metabolic control, HbA_1c >6.9% (>52 mmol/mol).

Lp(a) is a significant risk factor for macrovascular disease, albuminuria, and calcified aortic valve disease in patients with type 1 diabetes. Poor metabolic control in patients with type 1 diabetes is associated with increased Lp(a) levels.

A cross-sectional study of 193 patients with type 2 diabetes and 20 age- and sex-matched controls. Cardiovascular magnetic resonance was used in order to evaluate left ventricular structure and function, and MBF at rest and during adenosine-induced stress. MBF was derived as the mean of the flow within all segments of a midventricular slice.

Patients with type 2 diabetes had higher global MBF at rest (0.81 ± 0.19 mL/min/g) and lower global MBF during stress (2.4 ± 0.9 mL/min/g) than did controls (0.61 ± 0.11 at rest, 3.2 ± 0.8 mL/min/g under stress; both P < 0.01). Patients with macroalbuminuria had lower MBF during stress (1.6 ± 0.5 mL/min/g) than did patients with microalbuminuria (2.1 ± 0.7 mL/min/g; P = 0.04), who in turn had lower MBF during stress than did normoalbuminuric patients (2.7 ± 0.9 mL/min/g; P < 0.01). Patients with severe retinopathy had lower MBF during stress (1.8 ± 0.6 mL/min/g) than did patients with simplex retinopathy (2.3 ± 0.7 mL/min/g; P < 0.05) and those who did not have retinopathy (2.6 ± 1.0 mL/min/g; P < 0.05). Albuminuria and retinopathy were associated with reduced MBF during stress in a multiple regression analysis. Stress-related MBF inversely correlated with myocardial extracellular volume (P < 0.001; R² = 0.37), a measure of diffuse myocardial fibrosis. A trend toward lower basal MBF was observed in patients treated with sodium–glucose cotransporter 2 inhibitors (P = 0.07).

Patients with type 2 diabetes have higher global MBF at rest and lower maximal MBF during vasodilator-induced stress than do controls. Reduced MBF during stress is associated with diabetes complications (albuminuria and retinopathy) and is inversely correlated with diffuse myocardial fibrosis.

A total of 21 exons and exon-intron boundaries of ATP7B were identified by Sanger sequencing.

Two novel compound heterozygous mutations (c.525 dupA/ Val176Serfs*28 and c.2930 C>T/ p.Thr977Met) were detected in ATP7B. After d-penicillamine (D-PCA) therapy, serum aminotransferase and ceruloplasmin levels in this patient were normalized and levels of HbA_1c decreased. However, when the patient ceased to use D-PCA due to an itchy skin, serum levels of fasting blood glucose increased. Dimercaptosuccinic acid capsules were prescribed and memory recovered to some extent, which was accompanied by decreased insulin dosage for glucose control by 5 units.

This is the first report of diabetes caused by WD.

A cohort study was conducted in 54,075 adults without diabetes who underwent 3-min HRV measurement during health checkups between 2011 and 2014 at Kangbuk Samsung Hospital. We analyzed the time domain (SD of the normal-to-normal interval [SDNN] and root mean square differences of successive normal-to-normal interval [RMSSD]) and the frequency domain (total power, normalized low-frequency power [LF], and normalized high-frequency power [HF] and LF/HF ratio). We compared the risk of diabetes until 2017 according to tertiles of heart rate and HRV variables, with tertile 1 serving as the reference group.

During 243,758.2 person-years, 1,369 subjects were diagnosed with diabetes. Both time and frequency domain variables were lower in the group with diabetes, with the exception of those with normalized LF and LF/HF ratio. In Cox analysis, as SDNN, RMSSD, and normalized HF tertiles increased, the risk of diabetes decreased (hazard ratios [95% CIs] of tertile 3: 0.81 [0.70–0.95], 0.76 [0.65–0.90], and 0.78 [0.67–0.91], respectively), whereas the risk of diabetes increased in the case of heart rate, normalized LF, and LF/HF ratio (hazard ratios [95% CIs] of tertile 3: 1.41 [1.21–1.65], 1.32 [1.13–1.53], and 1.31 [1.13–1.53), respectively) after adjusting for age, sex, BMI, smoking, drinking, systolic blood pressure, lipid level, CRP, and HOMA of insulin resistance.

Abnormal HRV, especially decreased vagal activity and deviation in sympathovagal imbalance to sympathetic activity, might precede incident diabetes.

This age-, sex-, BMI-, and diabetes duration–matched cohort study used data from a U.K. primary care database from 1 January 2005 to 17 January 2018. Participants aged ≥16 years with type 2 diabetes were included. Exposed participants were those who developed OSA after their diabetes diagnosis; unexposed participants were those without diagnosed OSA. Outcomes were composite CVD (ischemic heart disease [IHD], stroke/transient ischemic attack [TIA], heart failure [HF]), peripheral vascular disease (PVD), atrial fibrillation (AF), peripheral neuropathy (PN), diabetes-related foot disease (DFD), referable retinopathy, chronic kidney disease (CKD), and all-cause mortality. The same outcomes were explored in patients with preexisting OSA before a diagnosis of type 2 diabetes versus diabetes without diagnosed OSA.

A total of 3,667 exposed participants and 10,450 matched control participants were included. Adjusted hazard ratios for the outcomes were as follows: composite CVD 1.54 (95% CI 1.32, 1.79), IHD 1.55 (1.26, 1.90), HF 1.67 (1.35, 2.06), stroke/TIA 1.57 (1.27, 1.94), PVD 1.10 (0.91, 1.32), AF 1.53 (1.28, 1.83), PN 1.32 (1.14, 1.51), DFD 1.42 (1.16, 1.74), referable retinopathy 0.99 (0.82, 1.21), CKD (stage 3–5) 1.18 (1.02, 1.36), albuminuria 1.11 (1.01, 1.22), and all-cause mortality 1.24 (1.10, 1.40). In the prevalent OSA cohort, the results were similar, but some associations were not observed.

Patients with type 2 diabetes who develop OSA are at increased risk of CVD, AF, PN, DFD, CKD, and all-cause mortality compared with patients without diagnosed OSA. Patients with type 2 diabetes who develop OSA are a high-risk population, and strategies to detect OSA and prevent cardiovascular and microvascular complications should be implemented.

Asymptomatic patients (8–45 years) were screened for CD. Biopsy-confirmed CD participants were randomized to GFD or gluten-containing diet (GCD) to assess changes in HbA_1c and continuous glucose monitoring over 12 months.

Adults had higher CD-seropositivity rates than children (6.8% [95% CI 4.9–8.2%, N = 1,298] vs. 4.7% [95% CI 3.4–5.9%, N = 1,089], P = 0.035) with lower rates of prior CD screening (6.9% vs. 44.2%, P < 0.0001). Fifty-one participants were randomized to a GFD (N = 27) or GCD (N = 24). No HbA_1c differences were seen between the groups (+0.14%, 1.5 mmol/mol; 95% CI –0.79 to 1.08; P = 0.76), although greater postprandial glucose increases (4-h +1.5 mmol/L; 95% CI 0.4–2.7; P = 0.014) emerged with a GFD.

CD is frequently observed in asymptomatic patients with type 1 diabetes, and clinical vigilance is warranted with initiation of a GFD.

A total of 4,699 people with diabetes who enrolled in the National Health and Nutrition Examination Survey from 2003 to 2014 were recruited for this study. Energy and macronutrient intake was measured by a 24-h dietary recall. The differences () in energy and macronutrient intake between dinner and breakfast ( = dinner – breakfast) were categorized into quintiles. Death information was obtained from the National Death Index until 2015. Cox proportional hazards regression models were developed to evaluate the survival relationship between and diabetes, cardiovascular disease (CVD), and all-cause mortality.

Among the 4,699 participants, 913 deaths, including 269 deaths due to diabetes and 314 deaths due to CVD, were documented. After adjustment for potential confounders, compared with participants in the lowest quintile of in terms of total energy and protein, participants in the highest quintile were more likely to die due to diabetes (hazard ratio [HR]_energy 1.92, 99% CI 1.08–3.42; HR_protein 1.92, 99% CI 1.06–3.49) and CVD (HR_energy 1.69, 99% CI 1.02–2.80; HR_protein 1.96, 99% CI 1.14–3.39). The highest quintile of total fat was related to CVD mortality (HR 1.67, 99% CI 1.01–2.76). Isocalorically replacing 5% of total energy at dinner with breakfast was associated with 4% and 5% lower risk of diabetes (HR 0.96, 95% CI 0.94–0.98) and CVD (HR 0.95, 95% CI 0.93–0.97) mortality, respectively.

Higher intake of energy, total fat, and protein from dinner than breakfast was associated with greater diabetes, CVD, and all-cause mortality in people with diabetes.

Blood, medical history, and personal data were collected in a substudy of 888 participants in the Sleep Apnea Cardiovascular End Points (SAVE) trial in which patients with OSA and stable CVD were randomized to receive CPAP plus usual care, or usual care alone. Serum glucose and glycated hemoglobin A_1c (HbA_1c) were measured at baseline, 6 months, and 2 and 4 years and incident diabetes diagnoses recorded.

Median follow-up was 4.3 years. In those with preexisting diabetes (n = 274), there was no significant difference between the CPAP and usual care groups in serum glucose, HbA_1c, or antidiabetic medications during follow-up. There were also no significant between-group differences in participants with prediabetes (n = 452) or in new diagnoses of diabetes. Interaction testing suggested that women with diabetes did poorly in the usual care group, while their counterparts on CPAP therapy remained stable.

Among patients with established CVD and OSA, we found no evidence that CPAP therapy over several years affects glycemic control in those with diabetes or prediabetes or diabetes risk over standard-of-care treatment. The potential differential effect according to sex deserves further investigation.

UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes.

Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0–47.9 mmol/mol [6.0–6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69–1.97) and 2.26 (95% CI 1.96–2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03–1.20) and 1.20 (1.04–1.38), respectively. Adding HbA_1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001–0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models.

The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA_1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA_1c measurements before the outcomes were evaluated. We used the previously reported HbA_1c variability score (HVS), calculated as the percentage of the number of changes in HbA_1c >0.5% (5.5 mmol/mol) among all HbA_1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models.

We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, HVS >80 to ≤100 vs. HVS ≥0 to ≤20, hazard ratio 2.38 [95% CI 1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA_1c, confirmed the robustness of the results.

Our study shows that higher HbA_1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA_1c.

This study applied observational and one-sample Mendelian randomization (MR) analyses to individual-level data from 117,193 Danish individuals, and validation by two-sample MR analyses on summary-level data from 133,010 individuals from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), 117,165 from the CKDGen Consortium, and 452,264 from the UK Biobank.

Observationally, glucose levels in the normoglycemic range and higher were associated with high risks of retinopathy, neuropathy, diabetic nephropathy, PAD, and MI (all P for trend <0.001). In genetic causal analyses, the risk ratio for a 1 mmol/L higher glucose level was 2.01 (95% CI 1.18–3.41) for retinopathy, 2.15 (1.38–3.35) for neuropathy, 1.58 (1.04–2.40) for diabetic nephropathy, 0.97 (0.84–1.12) for estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m², 1.19 (0.90–1.58) for PAD, and 1.49 (1.02–2.17) for MI. Summary-level data from the MAGIC, the CKDGen Consortium, and the UK Biobank gave a genetic risk ratio of 4.55 (95% CI 2.26–9.15) for retinopathy, 1.48 (0.83–2.66) for peripheral neuropathy, 0.98 (0.94–1.01) for eGFR <60 mL/min/1.73 m², and 1.23 (0.57–2.67) for PAD per 1 mmol/L higher glucose level.

Glucose levels in the normoglycemic range and higher were prospectively associated with a high risk of retinopathy, neuropathy, diabetic nephropathy, eGFR <60 mL/min/1.73 m², PAD, and MI. These associations were confirmed in genetic causal analyses for retinopathy, neuropathy, diabetic nephropathy, and MI, but they could not be confirmed for PAD and seemed to be refuted for eGFR <60 mL/min/1.73 m².

In CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation—a cohort of 528 individuals with no previous cardiovascular event undergoing CCTA), participants were grouped into CAD^– (clean coronaries) and CAD⁺ (diffuse lumen narrowing or plaques). Plasma proteins were screened by aptamer analysis. Two-way partial least squares was used to simultaneously rank proteins by diabetes status and CAD.

Though CAD⁺ was more prevalent among participants with T2D (HbA_1c 6.7 ± 1.1%) than those without diabetes (56 vs. 30%, P < 0.0001), CCTA-based atherosclerosis burden did not differ. Of the 20 top-ranking proteins, 15 were associated with both T2D and CAD, and 3 (osteomodulin, cartilage intermediate-layer protein 15, and HTRA1) were selectively associated with T2D only and 2 (epidermal growth factor receptor and contactin-1) with CAD only. Elevated renin and GDF15, and lower adiponectin, were independently associated with both T2D and CAD. In multivariate analysis adjusting for the Framingham risk panel, patients with T2D were "protected" from CAD if female (P = 0.007), younger (P = 0.021), and with lower renin levels (P = 0.02).

We concluded that 1) CAD severity and quality do not differ between participants with T2D and without diabetes; 2) renin, GDF15, and adiponectin are shared markers by T2D and CAD; 3) several proteins are specifically associated with T2D or CAD; and 4) in T2D, lower renin levels may protect against CAD.