Emma Johnson

Instructor in Psychiatry

Education & Training


  • PhD in Psychology – Behavioral, Psychiatric, and Statistical Genetics: University of Colorado Boulder, 2017
  • BSPH in Biostatistics: University of North Carolina at Chapel Hill, 2013

Major Awards


  • NIDA-NIAAA Early Career Investigator Showcase awardee, 2021
  • WCPG Early Career Investigator Program – Oral Presentation Award winner, 2019
  • RSA Memorial Award, 2019
  • ASHG Reviewer’s Choice Abstract, 2017

Research Interests


My long-term research goal is to better understand the genetic architecture of psychiatric disorders, particularly focusing on substance use and addictions. Within addictions, I am particularly interested in delineating differences between early stages of casual drug use from later, maladaptive stages of loss of control and impairment. In this context, I have been drawn to the study of common drugs of use, such as alcohol and cannabis. My research aims to link these stages of casual use and use disorders to other, frequently co-occurring psychiatric disorders and relevant mental health conditions, including schizophrenia and suicidal thoughts and behaviors. I am currently one of the analysts for the Psychiatric Genomics Consortium’s Substance Use Disorders working group and a co-investigator in the Collaborative Study on the Genetics of Alcoholism.

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Key Publications


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Funded Research Projects


American Foundation for Suicide Prevention(PI):Elucidating the Polygenic Architecture Underlying Suicidal Thoughts and Behaviors
Brain and Behavior Research Foundation(PI):The impact of prenatal cannabis exposure on placental epigenetics – implications for newborn brain and socio-emotional development
NIAAA(PI): Identifying Contributions to the Genetic Correlation Between Alcohol Use Disorders and Schizophrenia
NIDA(Significant Contributor):7/7 Psychiatric Genomics Consortium: Advancing Discovery and Impact
NIDA(PI):Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics data