Christian Herder, Anna Zhu, Andreas Schmitt, Maria C Spagnuolo, Bernhard Kulzer, Michael Roden, Norbert Hermanns, Dominic Ehrmann
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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<sub>interaction</sub> < 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. 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引用次数: 0
摘要
炎症可能是糖尿病和抑郁症之间关系的生物学途径，但关于糖尿病类型和抑郁症症状群之间差异的数据很少。因此，本横断面研究旨在比较1型糖尿病（T1D）和2型糖尿病（T2D）患者之间炎症与抑郁症状及其症状群的多标记生物标志物的相关性。这项横断面研究结合了来自5项研究的数据，包括1260名参与者（n = 706 T1D, n = 454 T2D）。使用流行病学研究中心抑郁量表（CES-D）评估抑郁症状。采用接近延伸法测定92种炎症生物标志物的血清水平。质量控制后，保留76个炎症生物标志物进行统计分析。用多变量线性回归模型估计生物标志物与抑郁症状评分和聚类（认知-情感、躯体、快感缺乏）之间的关联。总样本中有9项生物标志物与抑郁症状呈正相关(CCL11/eotaxin、CCL25、CDCP1、FGF-21、IL-8、IL-10RB、IL-18、MMP-10、TNFRSF9；全p相互作用
Associations between biomarkers of inflammation and depressive symptoms-potential differences between diabetes types and symptom clusters of depression.
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 (pinteraction < 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.
期刊介绍：
Psychiatry has suffered tremendously by the limited translational pipeline. Nobel laureate Julius Axelrod''s discovery in 1961 of monoamine reuptake by pre-synaptic neurons still forms the basis of contemporary antidepressant treatment. There is a grievous gap between the explosion of knowledge in neuroscience and conceptually novel treatments for our patients. Translational Psychiatry bridges this gap by fostering and highlighting the pathway from discovery to clinical applications, healthcare and global health. We view translation broadly as the full spectrum of work that marks the pathway from discovery to global health, inclusive. The steps of translation that are within the scope of Translational Psychiatry include (i) fundamental discovery, (ii) bench to bedside, (iii) bedside to clinical applications (clinical trials), (iv) translation to policy and health care guidelines, (v) assessment of health policy and usage, and (vi) global health. All areas of medical research, including — but not restricted to — molecular biology, genetics, pharmacology, imaging and epidemiology are welcome as they contribute to enhance the field of translational psychiatry.
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