Ana Maria Diaz Zuluaga is a MD/PhD from Colombia interested in understanding the genetics and neurobiological mechanisms underlying the pathophysiology of mood and psychotic disorders. She obtained her PhD in Neurosciences (Magna Cum Laude) at the University of Antioquia, under the mentorship of Carlos López Jaramillo, where she was part of a multidisciplinary team collaborating with Nelson Freimer at UCLA. Her PhD work mainly focused on studying the genetic underpinnings and neurobiological correlates of lithium response in bipolar disorder and the effects of lithium at the brain level, both on brain function and structure using magnetic resonance imaging. During this time, she had the opportunity to be part of international collaborations including the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) Consortium, the International Consortium on Lithium Genetics (ConLiGen) and the Latin American Network for the Study of Early Psychosis (ANDES) and contributed to different peer-reviewed journal articles (Complete list of publications can be found at: https://scholar.google.es/citations?user=jkiFEAIAAAAJ&hl=es)
Since moving to UCLA for her postdoctoral training, she continues to play a key role in large-scale international projects between UCLA, Colombia and Brazil aimed at elucidating the genetic factors underlying severe mental illness, its symptoms and behaviors, in admixed Latin populations. Ana has a special focus on cross-disorder phenotypic analyses to better understand and represent psychiatric patients. Under the mentorship of Nelson Freimer and Loes Olde Loohuis, she is studying the reliability of different assessment tools in psychiatry, including a structured psychiatric interview, a self-administered instrument and longitudinal data from electronic health records in a cohort of patients with mood disorders recruited at the UCLA Mood Disorders Clinic and Behavioral Health Services Adult Outpatient Clinic. By studying the concordance, at a diagnosis and symptom level, of the clinical instruments compared to the longitudinal data extracted from the electronic health records, she expects to contribute to the ultimate goal of improving the accuracy of psychiatric diagnosis and risk stratification and thus, improve clinical outcomes and reduce the burden of these diseases on patients and their families.