Introduction

A blood magnesium (Mg2+) concentration below 0.7 mmol/L is prevalent in people with type 2 diabetes in comparison to non-diabetic subjects, with reported percentages ranging from 13.5 to 47.7%1. Hypomagnesemia is associated with poor glycaemic control and progression from pre-diabetes to diabetes2,3, while some Mg2+ supplementation studies have shown to improve glycaemic control4,5. Moreover, maintaining physiological Mg2+ levels has been suggested to decrease the risk of developing cardiovascular diseases (CVD) in type 2 diabetes6,7,8.

Hypomagnesemia has also been reported in studies with type 1 diabetes individuals in the eighties and early nineties9,10. However, these results cannot be extrapolated to the present as treatment of type 1 diabetes has significantly improved over the past decades, resulting in better glycaemic control. Indeed, a recent study demonstrates that the prevalence of hypomagnesemia is only 4.3% in a cohort of type 1 diabetes11. Hence, novel studies studying the prevalence and identifying the factors that contribute to hypomagnesemia are warranted.

Here we assess the prevalence of hypomagnesemia in a cohort of type 1 diabetes adults and investigate whether Mg2+ levels are associated with clinical characteristics (sex, age, duration of diabetes, smoking and alcohol use), HbA1c, insulin sensitivity, body mass index (BMI), inflammatory markers and adipokines.

Subjects and methods

Subjects

Participants were selected from the outpatient diabetes clinic of the Radboud University Medical Center, the Netherlands. Inclusion criteria were a diagnosis of type 1 diabetes (based on clinical diagnosis) and age above eighteen years. Pregnant women were excluded.

This project is part of the Human Functional Genomics Project (HFGP)12. Ethical approval for the study was obtained from the Institutional Review Board of the Radboud University Medical Center (NL54214.091.15, 2015–1930 and NL42561.091.12, 2012–550). Participant inclusion and experiments were conducted according to the principles expressed in the Declaration of Helsinki. All participants gave written informed consent before participation.

Demographic and laboratory analysis

Clinical characteristics, including age (years), sex (men/women), BMI (kg/m2), blood pressure (mmHg), smoking status (current, former, never), alcohol use (yes, no), duration of diabetes (years), HbA1c (mmol/mol), insulin dose (units’ insulin per day), total cholesterol (mmol/L), triglycerides (TG) (mmol/L) and high density Lipoprotein (HDL) (mmol/L) were obtained from questionnaires and clinical records. Insulin resistance markers were calculated according to Bîcu et al.13. Venous blood was collected after an overnight fasting period. We measured high-sensitivity C-reactive protein (hs-CRP), IL-18 and IL-18 binding protein (IL-18BP), established inflammatory markers that are often elevated in individuals with diabetes, in the EDTA collected plasma samples (R&D duoset ELISA, MN, USA). Serum samples were measured for Mg2+ using a calibrated standardized colorimetric assay with a coefficient of variation of 1.98% (Cobas C8000; Roche Diagnostics, Risch-Rotkreuz, Switzerland).

Statistical analysis

Data are presented as percentages, mean ± SD or median with interquartile range for skewed variables. Pearson’s correlation tests (continuous variables), Point-biserial correlations (dichotomous variables), or one-way ANOVA analysis (> 2 groups) were carried out to determine the correlation or difference between serum Mg2+ concentrations with demographic parameters or other laboratory measurements in total cohort and based on insulin treatment in units per kg body weight. Independent-samples t-test was run to assess differences between the mean of the high insulin dose (> 0.70 units per kg body weight, IU/kg)) versus low insulin dose (≤ 0.70 IU/kg).

Multivariate analysis was used to assess if serum Mg2+ has multiple interaction factors in the association with HbA1c, BMI, hs-CRP and Leptin. The linear relationship between continuous variables was assessed by scatterplot. Multicollinearity was assessed by Pearson correlations (r < 0.9). Hierarchical multiple regression was performed to identify if insulin dose (IU/kg) as continuous variable, significantly moderates the association of serum Mg2+ with HbA1c, BMI, hs-CRP and Leptin. Skewed dependent variables were Log10 transformed. Homoscedasticity was assessed by visual inspection of the studentized residuals plotted against the predicted values for high versus low insulin dose (IU/kg) individuals. The interaction model of serum Mg2+ (mmol/L) * insulin dose (IU/kg) as a continuous variable was adjusted for possible confounders: model 1 is age (years) and sex (men/women) adjusted, model 2 is adjusted for duration of diabetes (years), estimated glomerular filtration rate (eGFR) (< 60, 60–90, > 90 mL/min/1.73m2), alcohol use (yes, no), smoking (current, former, never), TG (mmol/L), LDL cholesterol (mmol/L), systolic blood pressure (mmHg), statins use (yes, no) and proton pump inhibitor (PPI) use (yes, no). Plots of the association of serum Mg2+ with outcome variables, crude and corrected for confounders, are visualized using the PROCESS macro in SPSS14. Missing data (< 13%) were imputed for regression analysis using Predictive Mean Matching combing ten iterations and thirteen imputation sets into one imputation model. All data analyses were performed using SPSS for Windows (v25.0.0.01, IBM). P-values ≤ 0.05 were considered statistically significant.

Results

In total, 241 individuals with type 1 diabetes were included in the cohort. Demographic data and laboratory results are shown in Table 1. The mean serum Mg2+ concentration was 0.84 ± 0.10 mmol/L, with 7 people (2.9%) that had hypomagnesemia (serum Mg2+  < 0.7 mmol/L). Serum Mg2+ concentrations were correlated with duration of diabetes (r = 0.15, P-value = 0.017), serum creatinine (r = 0.14, P-value = 0.032) and eGFR (F (2238) = 3.73, P-value = 0.037). The association of serum Mg2+ with HbA1c was (r = − 0.12, P-value = 0.068). All other variables such as demographic characteristics (sex, age, alcohol use, smoking) and laboratory measurements (cholesterol, inflammatory markers and adipokines) were not associated with serum Mg2+. Since studies in individuals with type 2 diabetes have shown strong negative correlations between serum Mg2+ and parameters related to insulin sensitivity15,16, we divided the cohort into quartiles based on insulin dose, (determined by the amount of insulin treatment in units per kg body weight). In the quartile with high insulin dose (> 0.70 IU/kg) but not in the other quartiles, a clear, inverse, correlation between Mg2+ serum level and HbA1c (r = − 0.26, P-value = 0.047) was found. In this quartile, Mg2+ serum level also correlated with sex (men) (r = 0.30, P-value = 0.021), and inversely with BMI (r = − 0.29, P-value = 0.026), Log10 hs-CRP (r = − 0.39, P-value = 0.003) and Log10 Leptin (r = − 0.37, P-value = 0.004). The correlations of serum Mg2+ with HbA1c, in subjects with a low insulin dose (≤ 0.70 IU/kg), were (r = − 0.07, P-value = 0.362) for, BMI (r = 0.03, P-value = 0.714), Log10 hs-CRP (r = − 0.01, P-value = 0.900) and Log10 Leptin (r = 0.06, P-value = 0.464).

Table 1 Characteristics of individuals with type 1 diabetes in the DM300 cohort (n = 241).

To validate that the high insulin dose (> 0.70 IU/kg) (n = 61) group is truly insulin resistant we assessed widely used insulin resistance markers: TG / HDL ratio, TG levels and total cholesterol/HDL ratio13. All insulin resistance markers were statistically higher in the group that used > 0.70 IU/kg compared to the low insulin use group, with a difference of 0.64 (95% CI: 0.54; 0.86), t(205) = 6.14, P-value =  < 0.001 for TG / HDL ratio, 0.55 (95% CI: 0.33; 0.77), t(205) = 4.97, P-value =  < 0.001 for TG and 0.52 (95% CI: 0.24; 0.80), t(2.13) = 3.64, p-value =  < 0.001.

To identify if there was an interaction between serum Mg2+ with sex and insulin dose on outcome variables HbA1c, BMI, Log10 hs-CRP and Log10 Leptin we performed a multivariate analysis. The interaction effect between sex and serum Mg2+ on the combined dependent variables (HbA1c, BMI, Log10 hs-CRP and Log10 Leptin) was not statistically significant, F(4, 232) = 0.55, P-value = 0.703, partial η2 = 0.009. There was a statistically significant interaction effect between insulin dose and serum Mg2+ on the combined dependent variables, F(4, 232) = 2.97, P-value = 0.024, partial η2 = 0.059. The results of the multivariate analysis per individual dependent variable is reported in Supplementary table 1.

As follow-up analysis, hierarchical multiple regression was used to assess the interaction effect of continuous insulin resistance with serum Mg2+ and analyzed by multivariable linear regression on the association of outcome variables: HbA1c, BMI, Log10 hs-CRP and Log10 Leptin. Insulin dose moderated the effect of serum Mg2+ on HbA1c and Log10 hs-CRP, as evidenced by a statistically significant increase in total variation explained of 5.0% (F(1, 237) = 13.71, P-value =  < 0.001) for HbA1c and 3.5% (F(1, 237) = 8.82, P-value = 0.004) for Log10 hs-CRP. After adjusting for confounders, the moderator effect of insulin dose and serum Mg2+ remained in the association with HbA1c − 71.91 (95% CI: − 119.11; − 24.71), P-value = 0.003) (Table 2) and Log10 hs-CRP − 2.09 (95% CI: − 3.70; − 0.48), P-value = 0.011 (Table 3). Plotting the interaction shows that insulin dose is critical for the negative association of serum Mg2+ with HbA1c and hs-CRP (Fig. 1). The crude associations between serum Mg2+, HbA1c, Log10 hs-CRP and insulin dose are visualized in Supplementary Fig. 1. The interaction effect of insulin resistance and serum Mg2+ with obesity markers BMI and Log10 Leptin were not significant after adjusting for confounders (Supplementary table 2 and 3).

Table 2 Interaction effect of the moderator insulin dose and serum Mg2+ associated with HbA1c.
Table 3 Interaction effect of the moderator insulin dose and serum Mg2+ associated with Log10 hs-CRP.
Figure 1
figure 1

Plots of the association of serum Mg2+ with HbA1c and hs-CRP categorized by insulin dose. (A, C) Crude models and (B, D) Model 2, adjusted for: age, sex adjusted, duration of diabetes (years), eGFR (< 60, 60–90, > 60 mL/min/1.73m2), alcohol use (yes/no), smoking (current, former, never), SBP (mmHg), TG (mmol/L), LDL cholesterol (mmol/L), statins (yes/no) and PPI (yes/no) drugs. eGFR = estimated glomerular filtration rate, HbA1c = hemoglobine A1c, hs-CRP = high-sensitivity C-reactive protein, LDL = low-density lipoprotein, Mg2+ = magnesium, PPI = proton pump inhibitor, SBP = systolic blood pressure, TG = triglycerides.

Discussion

This study shows that the prevalence of hypomagnesemia (Mg2+ blood levels < 0.7 mmol/L) in a contemporary cohort of type 1 diabetes adults is only 2.9%, which is comparable to the normal population17. We also demonstrate an inverse correlation of serum Mg2+ with glycaemic control (as HbA1c) and hs-CRP that seems to be dependent on insulin resistance.

The prevalence of hypomagnesemia in type 1 diabetes in the present cohort is significantly lower than in type 2 diabetes adults (13.5–47.7%) and historic cohorts of insulin-treated outpatients with diabetes1,10,18. Our study thereby confirms the low prevalence of 4.3% in a type 1 diabetes cohort of 207 patients published earlier this year11. In 1989, McNair et al. reported a high prevalence of hypomagnesemia (38%) and inverse correlation of serum Mg2+ with glucose levels10, but since then, diabetes care has substantially improved. The proportion type 1 diabetes individuals with good glycaemic control (HbA1c from < 7.5%) has risen from 25 to 45% while the proportion of people with poor glycaemic control decreased from 40 to 16%19. Indeed, the average HbA1c in our cohort (8.0%) was lower compared to earlier studies9,20, and comparable to the most recent study having a baseline HbA1c of 7.6%11.

Older studies in type 1 diabetes cohorts have reported the negative association of Mg2+ blood levels with fasting glucose or HbA1c20,21. A recent study from Dijk et al. supports that there is no association with HbA1c or obesity markers in a total cohort of people with type 1 diabetes. The study of Dijk et al. did not assess the effect of insulin resistance and also 86% the data regarding insulin dose was missing11. In our study, we show that serum Mg2+ is negatively associated with HbA1c and Log10 hs-CRP in people that are probably insulin resistant. In a cohort with type 1 and 2 diabetes, the likelihood of having high CRP concentration increased with HbA1c levels22. The CRP median in our study is comparable to levels measured in previous type 1 diabetes studies and on average still lower than in individuals with type 2 diabetes23. Interestingly, CRP is associated with a higher risk of developing type 2 diabetes24, while Mg2+ reduces type 2 diabetes incidence25,26. In the general population, low Mg2+ levels are associated with raised CRP concentration27, and oral Mg2+ supplementation reduces serum CRP levels28. Our results suggest that insulin resistance might be an important determinant in the relation of serum Mg2+ with glycaemic control. We did correct for confounders such as TG and SBP, because these are known to be positively correlated with metabolic insulin resistance. Adjusting for TG and SBP as confounders did not attenuate the moderation effect of insulin dose on the association of serum Mg2+ with HbA1c or log transformed hs-CRP29,30. This suggests that there could be other factors than insulin resistance involved that contribute to hypertriglyceridemia and hypertension in people with type 1 diabetes31,32.

The results do explain the high prevalence of hypomagnesemia in type 2 diabetes with insulin resistance being the hallmark of this disorder. Insulin resistance is often associated with being overweight or obese, a factor that is becoming more common in type 1 diabetes too, resulting in the development of “double diabetes”33. The inflammatory marker CRP is even considered as a predictor for pre-diabetes, diabetes and fatty liver disease34,35,36. This suggests that a similar mechanism of hypomagnesaemia might occur in pathologies that are closely-related to the type 2 diabetes phenotype, such as pre-diabetes and fatty liver disease.

The strengths of this study includes the fact that we studied a large cohort over a wide age range, while other type 1 diabetes studies have determined the incidence in rather small sample sizes of children and adolescents18,37. Another advantage is that we have determined adipose tissue specific lipids and inflammatory cytokines. A limitation is the cross-sectional design study, although we do provide some insight in the mechanism of Mg2+ by using an explanatory statistical model.

In summary, this study shows that serum Mg2+ levels are negatively associated with glycaemic control and to inflammation (log10 hs-CRP), but this relationship is limited to people with type 1 diabetes who are probably insulin resistant. These results suggest that hypomagnesemia is not caused by diabetes per se, but that insulin resistance is the main determinant in the association of Mg2+ and glycaemic control in individuals with type 1 and type 2 diabetes.