Disclosures: Brown reports ongoing or recent research funding from the NIMH; the National Institute on Alcohol Abuse and Alcoholism; the National Institute on Aging; the National Heart, Lung, and Blood Institute; the National Center for Complementary and Integrative Health; the Stanley Medical Research Institute; and Otsuka Pharmaceuticals, as well as serving on an advisory board for Allergan. Please see the study for all other authors’ relevant financial disclosures.
December 07, 2020
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Inflammatory biomarker may predict depression symptom severity

Disclosures: Brown reports ongoing or recent research funding from the NIMH; the National Institute on Alcohol Abuse and Alcoholism; the National Institute on Aging; the National Heart, Lung, and Blood Institute; the National Center for Complementary and Integrative Health; the Stanley Medical Research Institute; and Otsuka Pharmaceuticals, as well as serving on an advisory board for Allergan. Please see the study for all other authors’ relevant financial disclosures.
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The novel spectroscopic inflammatory biomarker GlycA was positively associated with depression symptom severity, according to study results published in Journal of Clinical Psychiatry.

“GlycA is a novel inflammatory biomarker that, currently, is not widely used in clinical practice,” E. Sherwood Brown, MD, PhD, of the department of psychiatry at the University of Texas Southwestern Medical Center, told Healio Psychiatry. “High GlycA levels are associated with medical illnesses, such as heart disease and diabetes. GlycA levels also appear to be more stable over time than high-sensitivity C-reactive protein (hs-CRP). Prior studies had not looked at the association between GlycA and depression.”

The investigators obtained data of 3,033 residents of Dallas County, Texas, who were included in The Dallas Heart Study. Participants provided data on depressive symptom severity via the Quick Inventory of Depressive Symptomatology–Self-Report (QIDS-SR). Brown and colleagues hypothesized that the serum GlycA level would statistically significantly predict QIDS-SR scores after control for demographic covariates. They assessed the association between GlycA level and QIDS-SR scores using multiple linear regression, as well as explored the effect of hs-CRP in predicting QIDS-SR scores.

E. Sherwood Brown
E. Sherwood Brown

Results showed GlycA level served as a statistically significant positive predictor of QIDS-SR score with control for age, antidepressant use, sex, ethnicity, smoking status, BMI, drinking status and years of education. GlycA level was not linked to QIDS-SR scores among a subset of adults with moderate-to-severe depression. Further, hs-CRP level did not statistically significantly predict QIDS-SR scores.

“Prediction of clinical response to antidepressants using GlycA would be a good next step,” Brown said. “Some studies suggest that hs-CRP levels predict antidepressant response. Our hope would be that inflammatory biomarkers, such as GlycA, may eventually be used to identify subtypes of depression and determine which antidepressant to use. If someone could get a simple blood test that might provide information about the nature of their depression and what antidepressant they might best respond to, then it might be possible to treat the depression more quickly and effectively.”