Cardiac autonomic neuropathy (CAN) may contribute to vascular complications in diabetes. We hypothesized that adolescents with CAN are at greater risk of diabetic retinopathy and early kidney dysfunction.
In this prospective longitudinal study of 725 adolescents with type 1 diabetes without retinopathy and albuminuria at baseline, early CAN was defined as one or more abnormalities in seven heart rate tests derived from a 10-min electrocardiogram. Retinopathy was defined as the presence of one or more microaneurysms, early kidney dysfunction as an albumin excretion rate (AER) >7.5 μg/min, and albuminuria as an AER >20 μg/min. Multivariable generalized estimating equations were used to examine the association between CAN and retinopathy or early kidney dysfunction. Cox proportional hazards regression analysis was used to assess cumulative risks of incident retinopathy and albuminuria.
At baseline, the mean age of the sample was 13.6 ± 2.6 years, 52% were male, and mean diabetes duration was 6.1 ± 3.3 years. Over a median follow-up of 3.8 (interquartile range 2.2–7.5) years, the complication rate 27% for retinopathy, 16% for early kidney dysfunction, and 3% for albuminuria. The mean study HbA1c was 72.3 ± 16 mmol/mmol (8.6 ± 1.4%). CAN predicted incident retinopathy (odds ratio 2.0 [95% CI 1.4, 2.9]) and early kidney dysfunction (1.4 [1.0, 2.0]) after adjusting for HbA1c and diabetes duration. CAN also predicted retinopathy (hazard ratio 1.57 [95% CI 1.09, 2.26]) and albuminuria (2.30 [1.05, 5.04]) independently of HbA1c.
CAN predicted incident retinopathy and kidney dysfunction in adolescents with type 1 diabetes, likely reflecting autonomic microvascular dysregulation contributing to complications. Therefore, screening and interventions to reduce CAN may influence the risk of complications.
Introduction
Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are well recognized microvascular complications and are associated with increased morbidity and mortality (1,2). While overt microvascular complications are uncommon in youth, subclinical complications are frequently observed (3). The incidence of DR is variable but has been reported to be as high as 39% (4); nevertheless, adolescents are at increased risk of rapid progression to vision-threatening DR (5,6), especially those with suboptimal glycemic control. DKD affects 33% of Australians with diabetes (7), and it accounts for 40% of end-stage kidney disease. It is a significant cause of morbidity and mortality in diabetes. Those with an abnormal albumin excretion rate (AER) are at increased risk of macrovascular disease and premature death (2,8). Early predictors of DR and DKD are necessary to identify high-risk individuals, but this remains a challenge.
Autonomic nerve dysfunction leads to impaired hemodynamics/autoregulation and may be the initiating event for DR and DKD. Cardiac autonomic neuropathy (CAN), defined as abnormal heart rate variability (HRV), is an underrecognized complication in type 1 diabetes. Subclinical CAN may occur within a few years of diagnosis (3,9). We previously documented an increase in CAN during follow-up in the adolescent age-group (10), indicating an increased risk during puberty for those with suboptimal glycemia and longer diabetes duration (3,11–13). Current methods, including time domain and power spectral analysis, for detecting CAN are more sensitive than the traditional methods that use cardiovascular maneuvers (14–16). We hypothesized that adolescents with abnormal HRV are at greater risk of retinopathy and early kidney dysfunction.
Research Design and Methods
Study Population
This longitudinal study comprised adolescents with type 1 diabetes assessed for diabetes complications at The Children’s Hospital at Westmead in Sydney, Australia, from 2009 to 2019, culminating in 1,693 visits. Inclusion criteria were age 12–20 years, type 1 diabetes for at least 2 years, gradable retinal photographs and absence of DR and early kidney dysfunction at baseline, and at least two assessments for complications. Visits with missing data were excluded from the analysis. Ethnicity was recorded at the initial visit and based on the Australian Bureau of Statistics (17) classification as follows: Australian, European, and other, including Asian, Indian, Middle Eastern, American, and African. Socioeconomic status was determined from the postal code of residence according to the Australian Bureau of Statistics Socio-Economic Indexes for Areas database (18). The lower two deciles were classified as the socioeconomically disadvantaged group. The Sydney Children’s Hospitals Network Ethics Committee approved the study, and we obtained written informed consent from the parents of all participants. Adolescents excluded from the study (Supplementary Figure) because of a single visit did not differ from participants for metabolic control or demographic factors but were slightly older and had longer diabetes duration (Supplementary Table).
Complications Assessment
Participants were assessed at each study visit by standardized interviews, clinical examinations, and laboratory investigations as previously described (19). Briefly, height and weight were measured to estimate BMI (kg/m2), and SDSs were determined using the U.S. Centers for Disease Control and Prevention population-based data. Blood pressure was measured after 5 min of rest with a sphygmomanometer using an appropriately sized cuff while the participant was seated. Venous blood samples were obtained to measure total cholesterol levels and glycemic control, which was assessed by HbA1c using high-performance liquid chromatography (Diamat analyzer; Bio-Rad, Hercules, CA). Urinary albumin excretion was measured using an Immulite analyzer (Siemens, Los Angeles, CA). All study visit measurements of HbA1c were used in the analysis.
CAN
After a 10-min rest in a quiet room, participants underwent a 10-min continuous electrocardiogram in a supine position. LabChart Pro (ADInstruments, Sydney Australia) was used to assess HRV. The entire 10 min was used, with the exclusion of ectopic beats (<500 ms, >1,100 ms). All traces were analyzed by a single operator and checked for artifacts and ectopic beats. Early CAN was defined as one or more abnormal HRV test. Time domain–derived measures of HRV were the SD of mean NN intervals (NN used in place of RR and determined from adjacent QRS complexes) and root mean square of the successive differences of NN intervals, which are estimates of overall HRV. Frequency domain measures included low-frequency (LF) components, defined as >0.04 Hz and <0.15 Hz; high-frequency (HF) components, defined as >0.15 Hz and <0.4 Hz; and the LF:HF ratio, considered to be an estimate of the relative sympathetic and parasympathetic balance. Geometric domain analyses were performed using the triangular index, the total number of all NN intervals divided by the height of the histogram of all NN intervals measured on a discrete scale of bins of 7.8125 ms (1/128 s). Normal reference ranges were derived from HRV measured using the same device on contemporary local control subjects (healthy school-aged adolescents) without diabetes. The normal range was defined as >5th percentile for age and sex for HRV parameters log10 (SD of mean NN intervals), log10 (root mean square of successive differences of NN intervals), log10 (triangular index), and <95th percentile for age and sex for heart rate and log10 (LF:HF ratio) (20).
Retinal Photography
Mydriatic seven-field stereoscopic fundal photography of both eyes was performed using a Topcon TRC-50VT fundus camera (Tokyo Optical, Tokyo, Japan) to assess retinopathy (21). Camera settings, including the angle of retinal photography, remained unchanged.
DR was defined as the presence of at least one microaneurysm or hemorrhage from seven standard fields. We used the International Clinical Classification of Diabetic Retinopathy, which has five stages based on the modified Airlie House classification used in the Early Treatment of Diabetic Retinopathy Study (ETDRS).
Definition of Early Kidney Dysfunction
Statistical Analysis
Descriptive statistics are reported as mean ± SD for parametric data or median (interquartile range) for skewed data. Participant characteristics are described based on CAN status. Continuous variables were compared across the CAN and non-CAN groups using ANOVA. Differences between groups of categorical variables were compared using the χ2 test. The primary outcome measures were retinopathy and early kidney dysfunction. Generalized estimating equations (GEEs) were used to study the correlation between repeated measures. We examined the association between CAN and incident retinopathy and early kidney dysfunction. Results are expressed as odds ratios (ORs) and 95% CIs. Cox proportional hazards regression analysis was used to study the effect of abnormal HRV on the risk of developing retinopathy and albuminuria with other significant variables. Analyses were performed using SPSS version 27 statistical software (IBM Corporation).
Data Availability
Data are available from the authors upon reasonable request.
Results
Characteristics of youth with type 1 diabetes stratified by CAN at any time point during the study are shown in Table 1. All participants were retinopathy free and had normal AER at baseline, but CAN was present in 22%. At baseline, participants’ mean age was 13.6 ± 2.6 years, diabetes duration was 6.1 ± 3.3 years, and HbA1c was 68 ± 16 mmol/mmol (8.4 ± 1.4%). Mean HbA1c, including all the visits (both study visits and clinic visits before the start of the study), was 71.4 ± 14.5 mmol/mmol (8.7 ± 1.3%); mean study HbA1c was 72.3 ± 16 mmol/mmol (8.6 ± 1.4%). Those who developed CAN (51%) were older and had higher BMI, HbA1c, and blood pressure than those without CAN. There was no significant difference in sex, ethnicity, and socioeconomic status between the CAN and non-CAN groups.
Patient characteristics based on the finding of CAN at any time point
. | All participants (n = 725) . | Partcipants with CAN (n = 372) . | Partcipants without CAN (n = 353) . | P . |
---|---|---|---|---|
Age (years) | ||||
At baseline | 13.6 ± 2.6 | 13.8 ± 2.6 | 13.4 ± 2.6 | 0.028 |
At diagnosis | 7.6 ± 3.7 | 7.8 ± 3.7 | 7.4 ± 3.6 | 0.102 |
Study follow-up (years) | 4.1 ± 2.2 | 4.4 ± 2.3 | 3.8 ± 2.0 | <0.001 |
Mean HbA1c from all study visits | ||||
% | 8.6 ± 1.4 | 8.8 ± 1.5 | 8.4 ± 1.4 | <0.001 |
mmol/mmol | 72.3 ± 15.6 | 74.6 ± 16.9 | 70.3 ± 14.1 | <0.001 |
Mean HbA1c from all clinic visits | ||||
% | 8.7 ± 1.3 | 8.8 ± 1.4 | 8.5 ± 1.2 | <0.001 |
mmol/mmol | 71.4 ± 14.5 | 73.2 ± 15.4 | 69.5 ± 13.1 | <0.001 |
Diabetes duration (years) | ||||
At baseline | 6.1 ± 3.3 | 6.0 ± 3.3 | 6.1 ± 3.3 | 0.986 |
At last visit (years) | 10.2 ± 4.1 | 10.5 ± 4.4 | 9.8 ± 3.7 | 0.024 |
Height SDS | 0.32 ± 1.05 | 0.27 ± 1.05 | 0.37 ± 1.04 | 0.199 |
Weight SDS | 0.69 ± 0.93 | 0.73 ± 0.98 | 0.64 ± 0.86 | 0.198 |
BMI SDS | 0.64 ± 0.87 | 0.71 ± 0.90 | 0.57 ± 0.84 | 0.032 |
Systolic blood pressure SDS | −0.28 ± 1.01 | −0.17 ± 1.04 | −0.40 ± 0.95 | 0.002 |
Diastolic blood pressure SDS | −0.18 ± 0.97 | −0.04 ± 0.99 | −0.34 ± 0.93 | <0.001 |
Ethnicity | ||||
Australian | 338 (46) | 168 (45) | 170 (48) | |
European | 186 (26) | 101 (27) | 85 (24) | |
Other | 201 (28) | 103 (28) | 98 (28) | |
Social disadvantage* | 102 (14) | 55 (15) | 47 (13) | 0.945 |
. | All participants (n = 725) . | Partcipants with CAN (n = 372) . | Partcipants without CAN (n = 353) . | P . |
---|---|---|---|---|
Age (years) | ||||
At baseline | 13.6 ± 2.6 | 13.8 ± 2.6 | 13.4 ± 2.6 | 0.028 |
At diagnosis | 7.6 ± 3.7 | 7.8 ± 3.7 | 7.4 ± 3.6 | 0.102 |
Study follow-up (years) | 4.1 ± 2.2 | 4.4 ± 2.3 | 3.8 ± 2.0 | <0.001 |
Mean HbA1c from all study visits | ||||
% | 8.6 ± 1.4 | 8.8 ± 1.5 | 8.4 ± 1.4 | <0.001 |
mmol/mmol | 72.3 ± 15.6 | 74.6 ± 16.9 | 70.3 ± 14.1 | <0.001 |
Mean HbA1c from all clinic visits | ||||
% | 8.7 ± 1.3 | 8.8 ± 1.4 | 8.5 ± 1.2 | <0.001 |
mmol/mmol | 71.4 ± 14.5 | 73.2 ± 15.4 | 69.5 ± 13.1 | <0.001 |
Diabetes duration (years) | ||||
At baseline | 6.1 ± 3.3 | 6.0 ± 3.3 | 6.1 ± 3.3 | 0.986 |
At last visit (years) | 10.2 ± 4.1 | 10.5 ± 4.4 | 9.8 ± 3.7 | 0.024 |
Height SDS | 0.32 ± 1.05 | 0.27 ± 1.05 | 0.37 ± 1.04 | 0.199 |
Weight SDS | 0.69 ± 0.93 | 0.73 ± 0.98 | 0.64 ± 0.86 | 0.198 |
BMI SDS | 0.64 ± 0.87 | 0.71 ± 0.90 | 0.57 ± 0.84 | 0.032 |
Systolic blood pressure SDS | −0.28 ± 1.01 | −0.17 ± 1.04 | −0.40 ± 0.95 | 0.002 |
Diastolic blood pressure SDS | −0.18 ± 0.97 | −0.04 ± 0.99 | −0.34 ± 0.93 | <0.001 |
Ethnicity | ||||
Australian | 338 (46) | 168 (45) | 170 (48) | |
European | 186 (26) | 101 (27) | 85 (24) | |
Other | 201 (28) | 103 (28) | 98 (28) | |
Social disadvantage* | 102 (14) | 55 (15) | 47 (13) | 0.945 |
Data are mean ± SD or n (%). Differences between groups of categorical variables were compared using the χ2 test.
Defined as the lower two deciles of Socio-Economic Indexes for Areas based on postal code of residence (18).
Over a median follow-up of 3.8 (interquartile range 2.2–7.5) years, 27% of adolescents developed retinopathy, and 22% developed early kidney dysfunction. Twenty-two adolescents developed albuminuria (3%).
Predictors of Retinopathy and Early Kidney Dysfunction
In univariable GEE models, CAN, HbA1c, and diabetes duration were significant predictors of incident retinopathy and early kidney dysfunction. Sex, blood pressure, and BMI were not significant predictors. In multivariable GEE models, CAN was a significant predictor of incident retinopathy (OR 2.03 [95% CI 1.41, 2.89]) and early kidney dysfunction (1.44 [1.02, 2.04]), after adjusting for HbA1c and diabetes duration (Table 2).
CAN predicts incident retinopathy and early kidney dysfunction
. | Univariable . | P . | Multivariable . | P . |
---|---|---|---|---|
Retinopathy | ||||
CAN at any visit | 2.46 (1.76, 3.42) | <0.001 | 2.03 (1.41, 2.89) | <0.001 |
HbA1c (%) | 1.34 (1.21, 1.48) | <0.001 | 1.29 (1.15, 1.42) | <0.001 |
Total type 1 diabetes duration (years) | 1.27 (1.21, 1.33) | <0.001 | 1.27 (1.21, 1.33) | <0.001 |
Early kidney dysfunction AER <7.5 μg/min | ||||
CAN | 1.64 (1.33, 2.55) | <0.001 | 1.44 (1.02, 2.04) | 0.036 |
HbA1c (%) | 1.42 (1.30, 1.55) | <0.001 | 1.38 (1.26, 1.50) | <0.001 |
Total type 1 diabetes duration (years) | 1.11 (1.07, 1.15) | <0.001 | 1.10 (1.05, 1.14) | <0.001 |
. | Univariable . | P . | Multivariable . | P . |
---|---|---|---|---|
Retinopathy | ||||
CAN at any visit | 2.46 (1.76, 3.42) | <0.001 | 2.03 (1.41, 2.89) | <0.001 |
HbA1c (%) | 1.34 (1.21, 1.48) | <0.001 | 1.29 (1.15, 1.42) | <0.001 |
Total type 1 diabetes duration (years) | 1.27 (1.21, 1.33) | <0.001 | 1.27 (1.21, 1.33) | <0.001 |
Early kidney dysfunction AER <7.5 μg/min | ||||
CAN | 1.64 (1.33, 2.55) | <0.001 | 1.44 (1.02, 2.04) | 0.036 |
HbA1c (%) | 1.42 (1.30, 1.55) | <0.001 | 1.38 (1.26, 1.50) | <0.001 |
Total type 1 diabetes duration (years) | 1.11 (1.07, 1.15) | <0.001 | 1.10 (1.05, 1.14) | <0.001 |
Data are OR (95% CI). Only significant results are included. Sex, blood pressure, and BMI were not significant predictors for incident retinopathy and early kidney dysfunction.
Risk of Microvascular Complications
Cumulative survival probabilities for retinopathy and albuminuria are shown in Fig. 1. In multivariable Cox proportional hazards regression analysis, CAN predicted higher cumulative risk of retinopathy (hazard ratio 1.57 [95% CI 1.09, 2.26]) independently of mean HbA1c. CAN predicted albuminuria (2.30 [1.05, 5.04]) but not elevated AER.
Cox proportional hazards regression analysis. A: DR-free survival probability stratified by the presence or absence of CAN during the study period. B: Albuminuria-free survival probability stratified by the presence or absence of CAN during the study period.
Cox proportional hazards regression analysis. A: DR-free survival probability stratified by the presence or absence of CAN during the study period. B: Albuminuria-free survival probability stratified by the presence or absence of CAN during the study period.
Conclusions
This is the first longitudinal study to examine CAN and the development of microvascular complications (retinopathy and kidney dysfunction) in adolescents with type 1 diabetes. We demonstrate that abnormal HRV is a significant predictor of retinopathy and early kidney dysfunction independently of HbA1c and diabetes duration.
We previously demonstrated that narrower pupillary diameter predicted development of retinopathy and albuminuria 12 years later, suggesting that early autonomic dysfunction plays a role in the pathogenesis of microvascular complications (25). Furthermore, clinical CAN has been associated with proliferative retinopathy in youth with type 1 diabetes (26). Our data support the hypothesis that chronic dysglycemia that results in abnormal sympathetic/parasympathetic tone and impaired retinal blood flow contributes to the development of DR. This is also in keeping with findings that autonomic dysfunction results in activation of the renin-angiotensin-aldosterone axis and changes in glomerular blood flow, contributing to DKD (27,28).
Participants had no demonstrable retinopathy or kidney dysfunction at baseline, but 22% had CAN. This suggests that autonomic dysfunction predates the other microvascular complications. In keeping with this chronology, during follow-up, the proportion developing the earliest signs of DR and albuminuria remained lower than the proportion with CAN. The neurovascular unit plays a significant role in the autoregulation of retinal blood flow (29). Loss of autonomic control could lead to impaired autoregulation of blood flow in the retina, an essential event in the pathogenesis of retinopathy. Studies investigating CAN and these early functional retinal changes would be valuable.
The relationship between CAN and albuminuria has been explored in adult studies (30,31). In a multicenter study involving youth with type 1 diabetes, adolescents at risk for developing DKD had CAN (20). In the SEARCH for Diabetes in Youth (SEARCH) study, lower HRV was associated with albuminuria (32). In this study, we found a significant risk of incident albuminuria in patients with CAN. The mechanism linking CAN and albuminuria remains unclear. An impaired nocturnal dip in blood pressure precedes and possibly contributes to albuminuria in adolescents with diabetes (33).
Higher HbA1c and longer diabetes duration play a significant role in the pathogenesis of DR and contribute to autonomic dysfunction (34). The SEARCH study also demonstrated that suboptimal glycemic control was a powerful predictor of CAN in adolescents (35). In addition, the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) showed less CAN in the 13th or 14th year of follow-up in the intensive compared with the conventional treatment group (36).
Major strengths of this study are the large longitudinal cohort of adolescents and the standardized methods for retinal, AER, and HRV assessments. Our center cares for a broad demographic likely representative of the general population. Limitations include lack of data on pubertal status or continuous glucose monitoring. Other limitations are lack of availability of data on glomerular filtration rate values, biomarkers for tubular injury, and kidney tissue. The inclusion of inflammatory markers and retinal vascular caliber changes may have clarified the findings.
In conclusion, early CAN predicted retinopathy and kidney dysfunction in adolescents with type 1 diabetes, suggesting that early autonomic dysfunction plays a significant role in the pathogenesis of microvascular complications. Further studies during young adulthood and after a longer duration of follow-up will further elucidate the role of autonomic dysfunction as a predictor of microvascular complications.
This article contains supplementary material online at https://doi.org/10.2337/figshare.20405694.
Article Information
Acknowledgments. The authors thank Janine Cusumano (for analysis of HRV traces) and Alison Pryke, both from the Diabetes Complications Assessment Service, The Children’s Hospital at Westmead, and the participants and their families.
Duality of Interest. No potential conflicts of interest relevant to this article were reported.
Author Contributions. V.V. analyzed the data. V.V., P.B.-A., and K.D. wrote the manuscript. P.B.-A., M.C., Y.H.C., and K.D. devised the study design, collected the data, and edited the manuscript. G.L. was involved in the discussion and editing of the manuscript. All the authors have approved the final version of the manuscript. K.D. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for integrity of the data and the accuracy of the data analysis.