Baseline serum C-reactive protein levels may predict antidepressant treatment responses in patients with major depressive disorder

Zhang, Jun; Yue, Yingying; Thapa, Ashok; Fang, Jianzhong; Zhao, Shengjun; Shi, Wei; Yang, Zhong; Li, Yanfang; Yuan, Yonggui

doi:10.1016/j.jad.2019.03.001

Cited by 26 publications

(16 citation statements)

References 35 publications

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“…A reduction in IL-6 after treatment has been observed, but not in CRP and TNF-α (Więdłocha et al, 2018), although these findings are not in consensus (Arteaga-Henríquez et al, 2019). In fact, the anti-inflammatory effects of antidepressants may be influenced by the pre-treatment level of inflammation (Arteaga-Henríquez, et al, 2019; Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Changes in inflammatory biomarkers are related to the antidepressant effects of Ayahuasca

et al. 2020

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Background: Ayahuasca is a traditional Amazon brew and its potential antidepressant properties have recently been explored in scientific settings. We conducted a double-blind placebo-controlled trial of ayahuasca with treatment-resistant depression patients ( n = 28) and healthy controls ( n = 45). Aims: We are evaluating the blood inflammatory biomarkers: C-reactive protein and interleukin 6, as a potential consequence of ayahuasca intake and their correlation with serum cortisol and brain-derived neurotrophic factor levels. Blood samples were collected at pre-treatment and 48 hours after substance ingestion to assess the concentration of inflammatory biomarkers, together with administration of the Montgomery-Åsberg Depression Rating Scale. Results: At pre-treatment, patients showed higher C-reactive protein levels than healthy controls and a significant negative correlation between C-reactive protein and serum cortisol levels was revealed ( rho = –0.40, n = 14). C-reactive protein in those patients was not correlated with Montgomery-Åsberg Depression Rating Scale scores. We observed a significant reduction of C-reactive protein levels across time in both patients and controls treated with ayahuasca, but not with placebo. Patients treated with ayahuasca showed a significant correlation ( rho = + 0.57) between larger reductions of C-reactive protein and lower depressive symptoms at 48 hours after substance ingestion (Montgomery-Åsberg Depression Rating Scale). No significant result with respect to interleukin 6 and brain-derived neurotrophic factor was found. Furthermore, these biomarkers did not predict the antidepressant response or remission rates observed. Conclusions: These findings enhance the understanding of the biological mechanisms behind the observed antidepressant effects of ayahuasca and encourage further clinical trials in adults with depression.

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Section: Introductionmentioning

confidence: 99%

Changes in inflammatory biomarkers are related to the antidepressant effects of Ayahuasca

et al. 2020

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“…CRP is a pentameric protein synthesized by the liver, whose level rises in response to inflammation (Nehring et al., 2020). Numerous clinical studies have shown that a significantly higher circulating CRP level was involved in patients with depression (Iob et al., 2020; Osimo et al., 2019; Wang et al., 2018) and has a lower antidepressants efficacy (Li et al., 2019; Zhang, Yue, et al., 2019). Some other works have showed that heart diseases, cancer patients with depressive symptoms also had a higher CRP level (McFarland et al., 2019; Ravona‐Springer et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Prenatal stress induced depressive‐like behavior and region dependently high CRP level in offspring rats

Zhang

Gao

et al. 2021

Brain and Behavior

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Introduction To explore the changes in C‐reactive protein (CRP) level in different regions of one old offspring rats exposed to prenatal stress (PS). Methods The rat model was constructed with prenatal restraint stress on pregnant dams on days 14–20 of gestation. Offspring rats were randomly divided into PS susceptibility (PS‐S) group and control (CON) group. Behavioral experiments including sucrose preference test (SPT), open‐field test (OFT), and forced swimming test (FST) were used to measure depressive‐like behaviors. Immunohistochemistry, qRT‐PCR, and Western blotting were applied to detect the changes in CRP level. Results The results showed that PS could cause depressive‐like behaviors in all SPT, OFT, and FST. Concomitantly, CRP mRNA and protein expression significantly increased in hippocampus, prefrontal cortex, and hypothalamus in the PS‐S group when compared that in the CON group, while no significantly changes in liver, heart, olfactory bulb, striatum, and cerebellum in the PS‐S group when compared that in the CON group. Conclusion Increasing of CRP expression in hippocampus, prefrontal cortex, and hypothalamus may play a critical role in the mechanism under depressive‐like behavior in offspring rats exposed to PS.

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“…Clinical studies also indicated potential usefulness of these biomarkers in predicting treatment outcomes [191]. For example, baseline serum CRP levels in patients with MDD could predict antidepressant treatment response [192].…”

Section: Pro-inflammatory Signaling Factorsmentioning

confidence: 99%

“…These potential genetic biomarkers, with exception of a few pharmacogenetic-guided decision support tools, still awaits clinical validation and is not introduced in routine clinical practice. Same as in CRP MDD, BD [49,69,70,71,173,192] IFN-α/β pathway MDD [171] cortisol MDD, BD, SCZ [30,51,179,195,196,197,198,199,200] insulin SCZ [30,199,200,207,213] the previous section, below are given several examples of genetic biomarkers holding promise for future clinical use.…”

Section: Examples Of Genetic Studies Relevant To Personalized Psychiatrymentioning

confidence: 99%

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

Levchenko

Nurgaliev

Kanapin

et al. 2020

Heliyon

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A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category.In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

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Baseline serum C-reactive protein levels may predict antidepressant treatment responses in patients with major depressive disorder

Cited by 26 publications

References 35 publications

Changes in inflammatory biomarkers are related to the antidepressant effects of Ayahuasca

Changes in inflammatory biomarkers are related to the antidepressant effects of Ayahuasca

Prenatal stress induced depressive‐like behavior and region dependently high CRP level in offspring rats

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

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