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Inflammation is a probable biological pathway underlying the relationship between diabetes and depression, but data on differences between diabetes types and symptom clusters of depression are scarce. Therefore, this cross-sectional study aimed to compare associations of a multimarker panel of biomarkers of inflammation with depressive symptoms and its symptom clusters between people with type 1 diabetes (T1D) and type 2 diabetes (T2D). This cross-sectional study combined data from five studies including 1260 participants (n = 706 T1D, n = 454 T2D). Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression Scale (CES-D). Serum levels of 92 biomarkers of inflammation were quantified with proximity extension assay technology. After quality control, 76 biomarkers of inflammation remained for statistical analysis. Associations between biomarkers and depressive symptom scores and clusters (cognitive-affective, somatic, anhedonia) were estimated with multivariable linear regression models. Nine biomarkers were positively associated with depressive symptoms in the total sample (CCL11/eotaxin, CCL25, CDCP1, FGF-21, IL-8, IL-10RB, IL-18, MMP-10, TNFRSF9; all p < 0.05) without interaction by diabetes type. Associations differed for eight biomarkers (p interaction  < 0.05). TNFβ was inversely associated with depressive symptoms in T1D, whereas three biomarkers (GDNF, IL-18R1, LIF-R) were positively associated with depressive symptoms in T2D. For the remaining four biomarkers (CD6, CD244, FGF-5, IFNγ) associations were not significant in either subgroup. Biomarker associations were more pronounced with somatic and anhedonia than with cognitive-affective symptoms. These results indicate that different proinflammatory pathways may contribute to depression in T1D and T2D and that there may be a symptom specificity in the link between subclinical inflammation and depression., Competing Interests: Competing interests: MR received lecture fees or served on advisory boards for AstraZeneca, Boehringer-Ingelheim, Echosens, Eli Lilly, Madrigal, MSD Sharp & Dohme, Novo Nordisk and Target RWE and performed investigator-initiated research with support from Boehringer-Ingelheim, Novo Nordisk and Nutricia/Danone to the German Diabetes Center (DDZ). NH reports advisory board member fees from Abbott Diabetes Care, Roche Diabetes Care and Insulet as well as honoraria for lectures from Berlin Chemie AG, Becton Dickenson, Sanofi Germany, Roche Diabetes Care and Dexcom Germany. DE reports advisory board member fees from Dexcom Germany and Roche Diabetes Care as well as honoraria for lectures from Berlin Chemie AG, Dexcom Germany, Sanofi-Aventis Germany and Roche Diabetes Care. All other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work., (© 2025. The Author(s).)

Aim: To analyse the potential drivers (glucose level, complications, diabetes type, gender, age and mental health) of diabetes symptoms using continuous glucose monitoring (CGM) and ecological momentary assessment., Materials and Methods: Participants used a smartphone application to rate 25 diabetes symptoms in their daily lives over 8 days. These symptoms were grouped into four blocks so that each symptom was rated six times on 2 days (noon, afternoon and evening). The symptom ratings were associated with the glucose levels for the previous 2 hours, measured with CGM. Linear mixed-effects models were used, allowing for nested random effects and the conduct of N = 1 analysis of individual associations., Results: In total, 192 individuals with type 1 diabetes and 179 with type 2 diabetes completed 6380 app check-ins. Four symptoms showed a significant negative association with glucose values, indicating higher ratings at lower glucose (speech difficulties, P = .003; coordination problems, P = .00005; confusion, P = .049; and food cravings, P = .0003). Four symptoms showed a significant positive association with glucose values, indicating higher scores at higher glucose (thirst, P = .0001; urination, P = .0003; taste disturbances, P = .021; and itching, P = .0120). There were also significant positive associations between microangiopathy and eight symptoms. Elevated depression and diabetes distress were associated with higher symptom scores. N = 1 analysis showed highly idiosyncratic associations between symptom reports and glucose levels., Conclusions: The N = 1 analysis facilitated the creation of personalized symptom profiles related to glucose levels with consideration of factors such as complications, gender, body mass index, depression and diabetes distress. This approach can enhance precision monitoring for diabetes symptoms in precision medicine., (© 2024 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)