Hippocampal Volume in Psychiatric Diagnoses: Should Psychiatry Biomarker Research Account for Comorbidities?

Abstract

Background Many research papers claim that patients with specific psychiatric disorders (major depressive disorder, posttraumatic stress disorder, borderline personality disorder, alcohol use disorder, and others) have smaller hippocampi, but most of those reports compared patients to healthy controls. We hypothesized that if psychiatrically matched controls (psychiatric control, matched for demographics and psychiatric comorbidities) were used, much of the biomarker literature in psychiatric research would not replicate. We used hippocampus and amygdala volume only as examples, as these are very commonly replicated results in psychiatry biomarker research. We propose that psychiatry biomarker research could benefit from using psychiatric controls, as the use of healthy controls results in data that are not disorder-specific. Method Hippocampus/amygdala volumes were compared between major depressive disorder, sex-/age-/race-matched healthy control, and psychiatric control (N = 126/group). Similar comparisons were performed for posttraumatic stress disorder (N = 67), borderline personality disorder (N = 111), and alcohol use disorder (N = 136). Results Major depressive disorder patients had smaller left (p = 8.79 × 10 −3 ) and right (p = 3.13 × 10 −3 ) hippocampal volumes than healthy control. Posttraumatic stress disorder had smaller left (p = 0.018) and right (p = 8.64 × 10 −4 ) hippocampi than healthy control. Borderline personality disorder had smaller right hippocampus (p = 7.90 × 10 −3 ) and amygdala (p = 1.49 × 10 −3 ) than healthy control. Alcohol use disorder had smaller right hippocampus (p = 0.034) and amygdala (p = .024) than healthy control. No differences were found between any of the four diagnostic groups and psychiatric control. Conclusion When psychiatric controls were used, there was no difference in hippocampal or amygdalar volume between any of the diagnoses studied and controls. This strategy (keeping all possible relevant variables matched between experimental groups) has been used to advance science for hundreds of years, and we propose should also be used in biomarker psychiatry research.