
CRP as a Biomarker of Antidepressant Efficacy
Is inflammation a biomarker of antidepressant efficacy? Researchers analyzed blood CRP levels as a predictor of response to antidepressants.
RESEARCH UPDATE
CASE VIGNETTE
“Mr Fishburne” is a 35-year-old African American male with a history of
He presents for an outpatient clinic visit, and informs the psychiatrist that he would like to try a different medication. He also states that his primary care physician did routine blood work at his annual visit, and his C-reactive protein (CRP) level was 3 mg/L. As his psychiatrist, how would this additional information influence your decision on his next antidepressant trial? Some features of atypical depression, including
Approximately one-third of patients with MDD do not respond to an antidepressant trial of adequate dose and duration.1 Presently, there are no established peripheral biomarkers of
The Current Study
Pan and colleagues investigated CRP and antidepressant efficacy in a real-world retrospective cohort study of outpatients and inpatients with depression in China.6 Inclusion criteria were ICD-10 diagnosis of depression; aged 12 to 60; antidepressant use for > 4 weeks; and blood CRP measured by turbidimetry. They excluded subjects with cerebrovascular disease, immune-inflammatory, or other serious disease; CRP not available or measured with nephelometry (which only reports a range); elevated CRP (> 5 mg/L); patient diagnosis or first-degree relative with
Patients had a blood draw for CRP levels at baseline and were dichotomized based on CRP < 1 and ≥ 1 mg/L. CRP was also repeated at follow-up. Antidepressant efficacy (dichotomized as yes/no) was based on the Clinical Global Impression-Improvement (CGI-I) scale and was defined as either “significantly” or “very significantly” improved. Data on antidepressant treatment was obtained from patients, family members, and the electronic medical record. The authors compared the efficacy of SSRIs and SNRIs in the low and high CRP groups using chi-square test and Cox proportional hazards regression.
Baseline and follow-up data were available for n=918 patients, of whom 709 (77%) had low CRP and 209 (23%) high CRP. Mean subject age was 24, mean BMI was 22, and 35% of the sample was male. Patients were treated with SSRIs (n=725), SNRIs (n=138), agomelatine (n=32), and mirtazapine (n=11). In patients with high CRP, SNRIs were more efficacious than SSRIs (HR=1.65, 95% CI 1.03-2.65). In patients with low CRP, SSRIs were more efficacious than SNRIs (HR=1.26, 95% CI 1.00-1.57). There was no significant change in CRP levels before and after treatment.
Study Conclusions
The authors concluded that SNRIs were more efficacious in patients with high CRP, and SSRIs were more efficacious in patients with low CRP. This pattern of findings is broadly consistent with previous clinical trials.3-5 Study strengths include the overall large sample size and the use of a real-world effectiveness sample. Study imitations include the retrospective design (including potential recall bias); nonstandardized follow-up; the use of dichotomous outcome measures; inadequate data on cigarette smoking as a potential confounding factor; and inadequate sample sizes to investigate non-SSRI or SNRI antidepressants, as well as specific agents.
The Bottom Line
Blood CRP levels may have utility as a biomarker of antidepressant efficacy. Findings warrant replication in a large, rigorously designed prospective study.
Dr Miller is professor in the Department of Psychiatry and Health Behavior, Augusta University, Augusta, Georgia. He is on the Editorial Board and serves as the schizophrenia section chief for Psychiatric TimesTM. The author reports that he receives research support from Augusta University, the National Institute of Mental Health, and the Stanley Medical Research Institute.
References
1. Rush AJ, Trivedi MH, Wisniewski SR, et al.
2. Gadad BS, Jha MK, Czysz A, et al.
3. Uher R, Tansey KE, Dew T, et al.
4. Jha MK, Minhajuddin A, Gadad BS, et al.
5. Wang D, Yang XH, Zheng YS, et al. Serum level of hs-CRP in patients with depression and its predictive role for the efficiency of antidepressants. J Shandong Univ (Health Sci). 2018;56:51-57.
6. Pan Y, Luo R, Zhang S, et al.
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