The present population-based study had two main findings. First, a more adverse GMS, greater glycemia (estimated from FPG, 2-hour post-load glucose, HbA1c, and SAF) and greater daily glucose variability (estimated from IGP and CGM-assessed standard deviation) were all linearly and –except for CGM-assessed standard deviation– statistically significantly associated with lower RNFL thickness. Second, the associations between indices of daily glucose variability and RNFL thickness did not materially change after additional adjustment for measures of glycemia.
Our findings are in line with and extend observations from most previous studies.13, 19–24 The present study is the first large population-based study to comprehensively report associations of GMS, measures of glycemia, and indices of daily glucose variability with RNFL thickness, and also adjust for an extensive set of potential confounders. Additionally, the present study is the first to present associations of SAF, duration of diabetes, and indices of daily glucose variability with RNFL thickness.
Mechanistically, the linearity of the associations of GMS, measures of glycemia, and indices of daily glucose variability with RNFL thickness most likely reflects the increasing loss of retinal ganglion cells due to both hyperglycemia-induced neurotoxicity and impairment of functioning of retinal cells that contribute to metabolic regulation.4, 5 Such impairment of metabolic regulation can predispose retinal ganglion cells to ischemia.5, 45 Importantly, retinal ganglion cells are thought to be highly susceptible to ischemia, since they are highly active and have an energy demand that exceeds that of brain cells.45
These findings extend our previous work on the “ticking clock hypothesis”,5, 9–12 which postulates that hyperglycemia-induced microvascular and neuronal deterioration is a continuous, gradual process that starts in prediabetes, progresses with the onset of type 2 diabetes, and continues during type 2 diabetes.8 Indeed, we observed that the regression estimate for prediabetes was in between the estimate for type 2 diabetes and the reference category (i.e., NGM), and was directionally and numerically comparable to our previous findings.9–12 However, the association between prediabetes and RNFL thickness was not statistically significant, which is most likely due to insufficient statistical power. We, therefore, additionally tested for a linear trend with GMS deterioration by using the statistically more powerful P for trend analysis, 46 which was consistent with a linear decrease in RNFL thickness with more adverse GMS. In support, all measures of glycemia, regardless of whether they reflect shorter (i.e., FPG, 2-h PG, and HbA1c) or longer (i.e., SAF and duration of diabetes) exposure, were consistently linearly associated with RNFL thickness.
Similarly, a likely explanation why the association between CGM-assessed standard deviation and RNFL thickness was not statistically significant is that the statistical power to detect any such association was too low.47 Indeed, we observed that the association between IGP and RNFL thickness, which included almost fourfold the number of participants (n=2,407 versus n=622), was statistically significant. Moreover, the strength of the associations of IGP and CGM-assessed standard deviation with RNFL thickness were numerically analogous.
A probable explanation why the association between daily glucose variability and RNFL thickness was not materially altered after additional adjustment for measures of average glycemia is that daily glucose variability, measures of glycemia, and GMS represent different underlying constructs.26 While daily glucose variability reflects oscillating glucose levels, other measures under study reflect exposure to average chronic levels of glycemia. Mechanistically, substantial glucose fluctuations entail hyperglycemic peaks, hypoglycemic nadirs (in individuals with type 2 diabetes treated with agents that can induce hypoglycemia), or both, which are thought to be potent inducers of retinal ganglion cell apoptosis.26, 45 Whereas hyperglycemic peaks may be highly neurotoxic, hypoglycemic nadirs likely hamper retinal ganglion cell metabolism as their key nutrient is glucose.45
Our findings can have several implications for clinical practice. First, the strength of the association between type 2 diabetes and RNFL thickness corresponds with 15 years of aging and, thus, indicates that with respect to neurodegeneration substantial “additional aging” occurs in individuals with type 2 diabetes (Supplemental Table S14 shows how this comparison was calculated). Second, RNFL thickness may be a biomarker for the identification of individuals at risk of retinopathy. Use of RNFL thickness measurement is feasible because RNFL thickness assessment is non-invasive,2 relatively inexpensive2 and easier to perform than other tests of early neuronal dysfunction such as 24-hour electrocardiogram,9 magnetic resonance imaging,10, 11 or electromyography.12 Indeed, RNFL thickness has been found to be a promising early biomarker for other neurodegenerative diseases which are in part of a vascular origin (e.g., Alzheimer’s disease).48 Third, early glycemic control, possibly already in prediabetes, is likely crucial in the early prevention of microvascular complications.5 Last, our findings add to growing evidence that control of daily glucose variability besides mean glucose concentrations may be important to prevent microvascular complications.49, 50
Strengths of this study are 1) the large size of this population-based cohort with oversampling of individuals with type 2 diabetes, which enabled accurate comparison of individuals with and without diabetes; 2) the extensive number of potential confounders that were considered; 3) the use of state-of-the-art and novel methods (e.g., CGM)26 to assess all variables included in this study; and 4) the considerable number of additional analyses, which generally yielded consistent findings.
The study has certain limitations. First, due to the cross-sectional nature of the study, causal inferences should be made with caution.51 Mechanistically, hyperglycemia may not only lead to neurodegeneration but the reverse may also be true, thus causing a vicious cycle. Intact neurovascular interaction is required for normal microvascular function and impaired microvascular function may aggravate hyperglycemia.5, 52 Second, we may have underestimated the strength of the associations of GMS, measures of glycemia, and daily glucose variability with RNFL thickness if such an association was similar or stronger in participants that were excluded from the study population (who generally tend to be less healthy).53 The 2-hour post-load glucose and IGP results are most susceptible to this form of selection bias, as no data was available in individuals with the most therapy-intensive diabetes because they were excluded from undergoing an OGTT. Such range restriction may lead to underestimated associations.53 Third, a single OGTT may misclassify GMS, especially in individuals with prediabetes. Because individuals classified with prediabetes based on their first OGTT are relatively more prone to receive a NGM classification based on their second OGTT,54 this would likely lead to an underestimation of the association with RNFL thickness in the prediabetes group. Fourth, although we took an extensive set of confounders into account, we cannot fully exclude bias due to unmeasured confounding (e.g., environmental factors such as air pollution).55 Fifth, due to the relatively low numbers of participants with data on CGM-based glycemic indices (n=622)), and –to a lesser extent– IGP (n=2,407), statistical power of analyses with these determinants was reduced compared to statistical power of analyses with GMS and measures of glycemia (n=5,132 to n=5,455).47 Last, we studied Caucasian individuals aged 40-75 years with access to high-quality diabetes care. Therefore, the generalizability of our results to other populations requires further study.