Cardiac autonomic neuropathy may play a role in pathogenesis of atherosclerosis in type 1 diabetes mellitus

Quantification of lipoproteins by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves the prediction of cardiac autonomic dysfunction in patients with type 1 diabetes

AIMS

To assess if advanced characterization of serum glycoprotein and lipoprotein profile, measured by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves a predictive clinical model of cardioautonomic neuropathy (CAN) in subjects with type 1 diabetes (T1D).

METHODS

Cross-sectional study (ClinicalTrials.gov Identifier: NCT04950634). CAN was diagnosed using Ewing's score. Advanced characterization of macromolecular complexes including glycoprotein and lipoprotein profiles in serum samples were measured by 1H-NMRS. We addressed the relationships between these biomarkers and CAN using correlation and regression analyses. Diagnostic performance was assessed by analyzing their areas under the receiver operating characteristic curves (AUCROC).

RESULTS

Three hundred and twenty-three patients were included (46% female, mean age and duration of diabetes of 41 ± 13 years and 19 ± 11 years, respectively). The overall prevalence of CAN was 28% [95% confidence interval (95%CI): 23; 33]. Glycoproteins such as N-acetylglucosamine/galactosamine and sialic acid showed strong correlations with inflammatory markers such as high-sensitive C-reactive protein, fibrinogen, IL-10, IL-6, and TNF-α. On the contrary, we did not find any association between the former and CAN. A stepwise binary logistic regression model (R2 = 0.078; P = 0.003) retained intermediate-density lipoprotein-triglycerides (IDL-TG) [β:0.082 (95%CI: 0.005; 0.160); P = 0.039], high-density lipoprotein-triglycerides (HDL-TGL)/HDL-Cholesterol [β:3.633 (95%CI: 0.873; 6.394); P = 0.010], and large-HDL particle number [β: 3.710 (95%CI: 0.677; 6.744); P = 0.001] as statistically significant determinants of CAN. Adding these lipoprotein particles to a clinical prediction model of CAN that included age, duration of diabetes, and A1c enhanced its diagnostic performance, improving AUCROC from 0.546 (95%CI: 0.404; 0.688) to 0.728 (95%CI: 0.616; 0.840).

CONCLUSIONS

When added to clinical variables, 1H-NMRS-lipoprotein particle profiles may be helpful to identify those patients with T1D at risk of CAN.

The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey

Background

Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters.

Objective

The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management.

Methods

A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts.

Results

On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices.

Conclusions

Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.

Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease

Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.

Relationship between peripheral neuropathy, diastolic function and adverse cardiovascular outcome in individuals with type 1 diabetes mellitus without known cardiovascular disease: Results from the Thousand & 1 Study

AIMS

To investigate the association between measures of peripheral neuropathy (PN) and impaired left ventricular diastolic function, and the prognosis in patients with type 1 diabetes (T1DM) and no known cardiovascular disease (CVD), and to test the incremental prognostic value of including measures of PN and diastolic function to the established Steno T1 Risk Engine.

METHODS

Echocardiography and quantitative biothesiometry was performed to evaluate diastolic function and PN. The participants were categorized according to severity of diastolic function and PN. The study endpoint was combined cardiovascular (CV) events and all-cause death. Associations were analysed using multivariable regression models. The prognostic capability was assessed with Harrell's C-statistics and tested against the Steno T1 Risk Engine.

RESULTS

A total of 946 individuals (51.5% men) were included. The mean (SD) follow-up was 6 (1.3) years. The total number of CV events and all-cause death were 100. In the multi-adjusted analysis, both PN and impaired diastolic function were associated with increased risk of CV events and all-cause death: severe PN versus no PN: hazard ratio (HR) 2.23 (95% confidence interval [CI] 1.06-4.68; P = 0.035); severe diastolic impairment versus normal function: HR 2.27 (95% CI 1.16-4.44; P = 0.016). Measures of diastolic function improved prognostic capability when added to the Steno T1 Risk Engine: C-statistic 0.797 (95% CI 0.793-0.817) versus 0.785 (95% CI 0.744-0.825; P = 0.006).

CONCLUSION

Peripheral neuropathy and impaired diastolic function are associated with an increased risk of CV events and all-cause death in patients with T1DM. Measures of diastolic function improved prediction of prognosis by the Steno T1 Risk Engine.

Peripheral Nerve Conduction And Sympathetic Skin Response Are Reliable Methods to Detect Diabetic Cardiac Autonomic Neuropathy

AIM

This study aimed to investigate the role of nerve conduction studies (NCS) and sympathetic skin response (SSR) in evaluating diabetic cardiac autonomic neuropathy (DCAN).

METHODS

DCAN was diagnosed using the Ewing test combined with heart rate variability analysis. NCS and SSR were assessed by electrophysiological methods. The association between NCS/SSR and DCAN was assessed via multivariate regression and receiver-operating characteristic analyses.

RESULTS

The amplitude and conduction velocity of the motor/sensory nerve were found to be significantly lower in the DCAN+ group (all P < 0.05). A lower amplitude of peroneal nerve motor fiber was found to be associated with increased odds for DCAN (OR 2.77, P < 0.05). The SSR amplitude was lower while the SSR latency was longer in the DCAN+ group than in the DCAN- group. The receiver-operating characteristic analysis revealed that the optimal cutoff points of upper/lower limb amplitude of SSR to indicate DCAN were 1.40 mV (sensitivity, 61.9%; specificity, 66.3%, P < 0.001) and 0.85 mV (sensitivity, 66.7%; specificity, 68.5%, P < 0.001), respectively. The optimal cutoff points of upper/lower limb latency to indicate DCAN were 1.40 s (sensitivity, 61.9%; specificity, 62%, P < 0.05) and 1.81 s (sensitivity, 69.0%; specificity, 52.2%, P < 0.05), respectively.

CONCLUSIONS

NCS and SSR are reliable methods to detect DCAN. Abnormality in the peroneal nerve (motor nerve) is crucial in predicting DCAN. SSR may help predict DCAN.

Association between Cardiac Autonomic Neuropathy and Coronary Artery Lesions in Patients with Type 2 Diabetes

Objective

Cardiac autonomic neuropathy (CAN) is a common and serious complication of diabetes mellitus with various systemic involvements, such as atherosclerotic cardiovascular disease. We aimed to evaluate the association between CAN and coronary artery lesions in patients with type 2 diabetes. Research Design and Methods. We retrospectively reviewed the medical records of 104 patients with type 2 diabetes and coronary artery disease (CAD). We evaluated heart rate variability (HRV) parameters (SDANN, SDNN, and pNN50) to assess cardiac autonomic function. The severity of coronary lesions was assessed by the Gensini scores and the number of affected vessels. Correlation analyses between HRV parameters and the severity of coronary lesions and clinical parameters were performed.

Results

Spearman's correlation analysis showed a significant negative correlation between SDANN and Gensini scores (r = −0.22, P = 0.03). Interestingly, this finding remained significant after adjusting for clinical covariates (r = −0.23, P = 0.03). However, there was no association between HRV parameters and the severity of coronary lesions as assessed by the number of affected vessels. Clinical parameters were not significantly correlated with HRV parameters (all P > 0.05).

Conclusions

Cardiac autonomic neuropathy might be related to the degree of coronary atheromatous burden in patients with type 2 diabetes. Screening for cardiac autonomic neuropathy might potentially be beneficial in the risk stratification of patients with type 2 diabetes.

Leukotriene Pathway Activation Associates with Poor Glycemic Control and with Cardiovascular Autonomic Neuropathy in Type 1 Diabetes

Background and Aims

Since hyperglycemia promotes inflammation by different pathways and inflammation participates in the development of chronic diabetes complications, we investigated the association between the leukotriene (LT) pathway and microvascular diabetes complications.

Methods and Results

Quantitative polymerase chain reaction was employed to quantify the expression of ALOX5 (encodes 5-lipoxygenase), LTB4R (encodes one of the LTB4 receptors), and MYD88 in peripheral blood mononuclear cells from 164 type 1 diabetes (T1D) individuals presenting or not diabetes kidney disease, retinopathy, peripheral neuropathy, and cardiovascular autonomic neuropathy (CAN); 26 nondiabetic subjects were included as controls. LTB4 plasmatic concentrations were also evaluated. The expression of LTB4R was significantly higher in T1D individuals than in controls. T1D individuals with microvascular complications presented lower MYD88 mRNA expression when compared to those without microvascular complications. Higher LTB4 concentrations were found in individuals with CAN versus without CAN. The observation of two distinct subgroups of T1D individuals in the correlation analyses motivated us to evaluate the characteristics of each one of these groups separately. The group presenting higher expression of ALOX5 and of LTB4R also presented higher values of HbA₁C, of fructosamine, and of plasmatic LTB4.

Conclusion

In the diabetes setting, the LT pathway is not only activated by hyperglycemia but is also modulated by the status of the autonomic nervous system.

Association of Cardiovascular Autonomic Dysfunction With Peripheral Arterial Stiffness in Patients With Type 1 Diabetes

CONTEXT

Cardiovascular autonomic neuropathy (CAN) appears to contribute to peripheral arterial stiffness (AS) in type 1 diabetes. Whether CAN in patients with AS is associated with concomitant asymptomatic peripheral arterial disease (aPAD) remains unclear.

OBJECTIVE

To assess the risk of CAN in patients with type 1 diabetes and AS and its potential association with atherosclerosis.

DESIGN

Cross-sectional study.

SETTING

Type 1 diabetes clinic in an academic hospital.

PATIENTS

Two hundred sixty-four patients with type 1 diabetes.

INTERVENTION

AS was defined as an ankle-brachial index (ABI) >1.2, aPAD by the toe-brachial index and Doppler sonography, and CAN by blood pressure and heart rate responses to active standing and Ewing and Clarke tests.

MAIN OUTCOME MEASURES

Odds of having CAN among patients with AS. Odds for CAN were also calculated as a function of the presence of AS and concomitant aPAD.

RESULTS

The study population's mean age was 35 ± 11 years, with a duration of disease of 19 ± 10 years and mean hemoglobin A1c of 7.5% ± 1.3%. Seventy-three patients (28%) had peripheral AS, of whom 28 showed aPAD. The prevalence of CAN among patients with AS was 48% but it was only 23% in subjects with normal ABI (OR: 3.1 [1.7; 5.4]). Concomitant aPAD increased the OR for CAN (OR: 4.5 [2.0; 10.1]). After adjustments for aPAD and relevant cardiovascular risk factors, AS remained associated with parasympathetic dysfunction.

CONCLUSIONS

In type 1 diabetes, both peripheral AS and atherosclerosis were associated with CAN. A simple method, such as the ABI, may identify a subset of patients with undiagnosed dysautonomia.

The early detection of atherosclerosis in type 1 diabetes: why, how and what to do about it

The major cause of morbidity and often premature mortality in people with type I diabetes (T1D) is cardiovascular disease owing to accelerated atherosclerosis. We review publications relating to the rationale behind, and clinical tests for, detecting and treating early atherosclerosis in people with T1D. Currently available tools for atherosclerosis assessment include risk equations using vascular risk factors, arterial intima-media thickness, the ankle-brachial index, coronary artery calcification and angiography, and for more advanced lesions, intravascular ultrasound and optical coherence tomography. Evolving research tools include risk equations incorporating novel clinical, biochemical and molecular tests; vascular MRI and molecular imaging. As yet there is little information available to quantify early atherosclerosis. With better means to control the vascular risk factors, such as hypertension, dyslipidaemia and glycaemic control, and emerging therapies to control novel risk factors, further epidemiologic and clinical trials are merited to facilitate the translation into clinical practice of robust means to detect, monitor and treat early atherosclerosis in those with T1D.