Hemoglobin A1c-levels and subsequent risk of depression in individuals with and without diabetes

Comparison of mood status and treatment adherence between dialysis modalities

BACKGROUND

Psychiatric disorders, particularly anxiety and depression, are highly prevalent among dialysis patients and adversely affect clinical outcomes, including adherence to treatment. We aimed to evaluate the impact of dialysis modality on mental health and medication adherence.

METHODS

We conducted a cross-sectional study with 192 patients: 89 on hemodialysis (HD) and 103 on peritoneal dialysis (PD). Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS), while medication adherence was evaluated with the Morisky Medication Adherence Scale-8 (MMAS-8).

RESULTS

HD patients had higher mean HADS-A (8.03 ± 4.41) and HADS-D (9.47 ± 4.97) scores compared to PD patients (HADS-A: 6.7 ± 3.04; HADS-D: 6.46 ± 3.86, p < 0.01). Regression analysis revealed HD as an independent predictor of anxiety. HD patients had a higher risk of depression than PD patients, although this did not reach statistical significance after adjusting for potential confounders. Medication adherence was higher in PD patients, with 18.4% showing high adherence versus 8.9% in HD patients (p < 0.001). Anxiety and depression were not significantly associated with adherence, although trends suggested lower adherence in patients with worse mental health.

CONCLUSION

HD patients experience higher rates of anxiety, depression, and lower medication adherence compared to PD patients. Tailored interventions targeting mental health and adherence could improve clinical outcomes. Future research should explore long-term strategies to optimize care.

Diabetes Control Status and Severity of Depression: Insights from NHANES 2005-2020

Background/Objectives: Examining the risk of depression among patients with diabetes is crucial for understanding the mental health burden of this chronic condition. This study examined the likelihood of depression severity among participants in the National Health And Nutrition Examination Survey (NHANES) from 2005 to 2020, based on glycemic control status. Methods: Depression severity was categorized into three levels using the Patient Health Questionnaire-9 (PHQ-9), and glycemic control status was categorized into five groups based on prior diabetes diagnoses and hemoglobin A1c (HbA1c) levels. Using multinomial logistic regression models, the odds ratio (OR) and 95% confidence intervals (95%CIs) of various severities of depression by glycemic control status were calculated after comprehensive adjustments. Results: Out of 76,496 NHANES participants from 2005 to 2020, 37,037 individuals who met our inclusion criteria were analyzed. The likelihood of depression in individuals with prediabetes was not significantly different from those with normoglycemia. In contrast, participants with diabetes had a higher likelihood of having depression versus individuals with normoglycemia even when they kept their HbA1c within the normal range (lower than 5.7%). Among individuals with diabetes, those with HbA1c < 5.7% had a higher likelihood of mild depression (OR: 1.54, 95%CI: 1.02-2.34), while having HbA1c ≥ 10.0% was significantly associated with a greater likelihood of moderate to severe depression (OR: 1.53, 95%CI: 1.07-2.19) compared to those with HbA1c levels of 5.7-10.0%. Conclusions: Our findings highlight the need for a holistic approach to diabetes care that includes mental health considerations, especially for those who are at the extremes of the HbA1c spectrum.

Effects of glycaemic control on memory performance, hippocampal volumes and depressive symptomology

BACKGROUND

Diabetes and poor glycaemic control have been shown to negatively impact cognitive abilities, while also raising risk of both mood disorders and brain structural atrophy. Sites of atrophy include the hippocampus, which has been implicated in both memory performance and depression. The current study set out to better characterise the associations between poor glycaemic control, memory performance, and depression symptoms, and investigate whether loss of hippocampal volume could represent a neuropathological mechanism underlying these.

METHODS

1331 participants (60.9% female, age range 18-88 (Mean = 44.02), 6.5% with likely diabetes) provided HbA1c data (as an index of glycaemic control), completed a word list learning task, and a validated depression scale. A subsample of 392 participants underwent structural MRI; hippocampal volumes were extracted using FreeSurfer.

RESULTS

Partial correlation analyses (controlling for age, gender, and education) showed that, in the full sample, poorer glycaemic control was related to lower word list memory performance. In the MRI sub-sample, poorer glycaemic control was related to higher depressive symptoms, and lower hippocampal volumes. Total hippocampus volume partially mediated the association between HbA1c levels and depressive symptoms.

CONCLUSIONS

Results emphasise the impact of glycaemic control on memory, depression and hippocampal volume and suggest hippocampal volume loss could be a pathophysiological mechanism underlying the link between HbA1c and depression risk; inflammatory and stress-hormone related processes might have a role in this.

Investigating the Influence of Antidiabetic Medications and Psychosocial Factors

The relationship between type 2 diabetes mellitus (T2DM) and depression presents a significant area of medical concern, characterized by a higher incidence of depression among T2DM patients compared to the general population. This connection is not only evidenced in the prevalence of depressive symptoms in diabetic patients but also in the way these symptoms impact diabetes management. Furthermore, the influence of antidiabetic medications, especially sodium-glucose cotransporter-2 (SGLT2) inhibitors, on depression risk is a topic of ongoing research, with contrasting findings regarding the effects of drugs like metformin and pioglitazone. The aim of this study is to provide a comprehensive analysis of the relationship between T2DM and depression, focusing on the prevalence of depressive symptoms among diabetic patients, and the role of antidiabetic medications in modulating depression risk. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we focused on individuals with T2DM. Depression status was assessed using the nine-item Patient Health Questionnaire (PHQ-9), a validated tool for evaluating depressive symptoms. Participants' depression status was categorized based on PHQ-9 composite scores. The analysis included demographic variables and the use of antidiabetic medications, with a focus on SGLT2 inhibitors. Logistic regression models adjusted for age, race/ethnicity, and BMI were employed. Results Our study involved 23,575 participants, of which 7,862 had T2DM. A significant difference in age and BMI was observed between diabetic and non-diabetic groups. Logistic regression analysis indicated that non-diabetic individuals had a significantly lower likelihood of depression compared to diabetic patients not on SGLT2 inhibitors. However, no statistically significant difference in depression levels was found between diabetic patients on SGLT2 inhibitors and those not on these medications. Conclusion These findings highlight the complex relationship between diabetes, antidiabetic medication, and depression. Notably, we found no significant impact of SGLT2 inhibitors on depression in diabetic patients, challenging previous assumptions about the role of specific antidiabetic drugs in mental health. We also revealed that older diabetic individuals reported fewer depressive symptoms, suggesting the influence of psychosocial factors and the need for age-specific depression management strategies. This research underscores the necessity of further studies to explore the nuanced effects of different antidiabetic medications on mental health outcomes, guiding toward more personalized treatment approaches for the mental health challenges in T2DM.

Sodium-Glucose Cotransporter-2 Inhibitors in Depression

ABSTRACT

Novel treatment strategies that refract existing treatment algorithms for depressive disorders are being sought. Abnormal brain bioenergetic metabolism may represent an alternative, therapeutically targetable neurobiological basis for depression. A growing body of research points to endogenous ketones as candidate neuroprotective metabolites with the potential to enhance brain bioenergetics and improve mood. Sodium-glucose cotransporter-2 (SGLT2) inhibitors, originally approved for the treatment of diabetes, induce ketogenesis and are associated with mood improvement in population-based studies. In this column, we highlight the rationale for the hypothesis that ketogenesis induced by SGLT2 inhibitors may be an effective treatment for depressive disorders.

Diabetes, sleep disorders and risk of depression - A Danish register-based cohort study

AIMS

We examined the influence of comorbid sleep disorder on the association between type 2 diabetes (T2D) and risk of incident depression.

METHODS

The study population (N = 232,489) was based on all individuals registered aged ≥40 years with a T2D diagnosis between January 1, 2000 to December 31, 2012 in the Danish National Diabetes Register and a matched reference population. The risk of incident depression (diagnosis or anti-depressant medication) following T2D and possible effect modification of comorbid sleep disorder was estimated using adjusted Cox proportional hazards regression. Sleep disorder was defined as a diagnosis of insomnia, hypersomnia or sleep-wake schedule disorders or use of sleep medication (z-drugs or melatonin) in the Danish National Patient Registry or the Danish National Prescription Registry.

RESULTS

At study entry, 15.3 % of the participants had a sleep disorder. During follow-up, 2.6 % were diagnosed with depression and 32.1 % received antidepressant medication. The unadjusted hazard ratio (HR) for depression was 1.54 (95%CI 1.52-1.56) for patients with diabetes, which attenuated to 1.50 (1.48-1.52) after adjustment for sleep disorders, which further attenuated to 1.27 (1.26-1.29) in the model further adjusted for psychiatric and somatic comorbidities. The analyses of T2D and sleep disorder as independent and combined variables compared with none of the conditions on risk of depression, showed a HR of 1.27 (95 % CI 1.19-1.35) for T2D without sleep disorder, 1.46 (95 % CI 1.33-1.59) for sleep disorders without T2D, and 1.49 (95%CI 1.37-1.63) for both conditions.

CONCLUSIONS

T2D and sleep disorders were independently associated with subsequent risk of depression and individuals with both conditions experienced the greatest relative risk. Sleep disorders neither explained nor amplified the relation between diabetes and depression.

Higher levels of peripheral blood glucose in the acute stage of stroke increase the risk of Post-stroke Depression: A Systematic Review and Meta-Analysis

BACKGROUND

Multiple investigations have shown that diabetes mellitus is a predictor of post-stroke depression (PSD). However, whether elevated levels of fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are associated with an increased risk of PSD remains controversial.

METHODS

We comprehensively searched databases for eligible studies. Standard mean differences and 95% confidence intervals were used to examine the relationship between peripheral blood glucose levels during the acute phase of stroke and the risk of PSD. Narrative syntheses and meta-analyses were conducted when appropriate unadjusted or adjusted ORs were available.

RESULTS

A total of 21 prospective cohort studies were included in the analysis. PSD patients had significantly higher peripheral blood glucose levels than non-PSD patients (FPG: SMD, 0.28, 95% CI, 0.11-0.45, p＜0.01, HbA1c: SMD, 0.49, 95%CI, 0.20-0.78, p＜0.01, respectively). In the subgroup analyses by classifying the time point of depression assessment, HbA1c was more statistically significant associated with the risk of PSD than FPG. Differences in the prevalence of diabetes were not heterogeneity sources.

CONCLUSION

Higher levels of peripheral blood glucose in the acute phase of stroke increase the risk of PSD. HbA1c might be a better biomarker for the risk of PSD than FPG.

Diabetes, antidiabetic medications and risk of depression - A population-based cohort and nested case-control study

OBJECTIVE

Diabetes type 2 is associated with depression, but the impact of antidiabetic drugs is not clear. The objective was to analyze the association between diabetes type 2, antidiabetic drugs, and depression.

METHODS

This register-based study included 116.699 patients with diabetes type 2 diagnosed from 2000 to 2012 and an age, gender, and municipality matched reference group of 116.008 individuals without diabetes. All participants were followed for a diagnosis of depression or prescription of antidepressant medication. Based on this, a case-control study was nested within the cohort, using risk set sampling. Antidiabetic medication was categorized into insulin, metformin, sulfonylureas and glinides combined, glitazones, dipeptidyl peptidase 4 (DPP4) inhibitors, glucagon-like peptide 1 (GLP1) analogs, sodium-glucose transport protein 2 (SGLT2) inhibitors and acarbose. The association between diabetes and depression was analyzed using Cox proportional hazards regression, whereas conditional logistic regression was used to analyze the association between use of antidiabetic drugs and depression.

RESULTS

Patients with diabetes had higher risk of depression compared to individuals without diabetes (hazard ratio 1.14 (95% confidence interval 1.14-1.15)). Low doses of metformin, DPP4 inhibitors, GLP1 analogs, and SGLT2 inhibitors were associated with lower risk of depression in patients with diabetes compared to non-users, with the lowest risk for sodium-glucose transport protein 2 inhibitor users (odds ratio 0.55 (0.44-0.70)). Use of insulin, sulfonylurea and high doses of metformin were associated with higher risk of depression.

CONCLUSION

Patients with diabetes had increased risk of depression. However, users of specific antidiabetic drugs had lower risk of depression compared to non-users.

The genetic influence of PD-1/PD-L1 axis single nucleotide polymorphisms on the incidence of type 1 diabetes mellitus in pediatric Egyptian patients

Background

The increasing prevalence of diabetes mellitus (DM) is one of the most challenging public health issues. The destruction of insulin-producing cells in the islets of Langerhans is the hallmark of type 1 diabetes mellitus (T1DM) as an autoimmune disease. In the current case–control study, the role of single nucleotide polymorphisms (SNPs) was investigated within the programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitory axis and their association with T1DM susceptibility in a sample of Egyptian pediatric patients. The study included 80 T1DM pediatric patients and 76 healthy control subjects. The patients were recruited from Beni-Suef University Hospital’s Pediatric Endocrinology Outpatient Clinic. Genotyping of PD-1 SNP (rs 34819629) and PD-L1 SNPs (rs 2297137 and rs 4143815) was performed by TaqMan allelic discrimination technique via real-time polymerase chain reaction (RT-PCR). The patients were subjected to a thorough clinical examination and history taking.

Result

Genotyping of PD-1 (rs 34819629) revealed that all of the enrolled patients and the control group inherited the same genotype (GG genotype). With regard to PDL-1 rs4143815 SNP and the risk of T1DM occurrence, our comparison did not reveal the presence of an association between the different genetic models (general, dominant, and recessive) of the SNP and the risk of T1DM (p = 0.078 and p = 0.055; for the general genetic model, p = 0.061 and p = 0.169 for the dominant and the recessive types, respectively). Regarding PDL-1 rs2297137 SNP, the results of this study demonstrated that the risk of T1DM was significantly associated with the recessive genetic model (p = 0.007) as the diabetic group’s predominant G allele was higher compared to the control group.

Conclusion

The findings obtained supported the hypothesis that the predominant G allele of PD-L1 rs2297137 is associated with the development of T1DM. Chronic hyperglycemia and long-standing diabetes problems are linked to both PD-L1 SNPs (rs4143815 and rs2297137). Future studies with a more significant number of patients are required to support our results.