October 2016Research at the Lady Davis Institute

Trying to understand the higher likelihood of depression in girls

It’s a scientific conundrum: Twice as many girls as boys develop anxiety and depressive disorders by the time they reach early adolescence.

To better understand this puzzling phenomenon, Dr. Ashley Wazana of the JGH Centre for Child Development and Mental Health is collaborating with teams in Canada, the United Kingdom, the Netherlands and Singapore. Supported by a grant of $1.5 million over five years from the Canadian Institutes for Health Research, they will look at the correlation between pre-birth experiences and children’s eventual psychopathology.

Boys and girls respond differently to stress during early emotional development—a fact that is well documented, Dr. Wazana explains. “Genetic differences in susceptibility to prenatal events are important, and the environment that is reflected in early maternal care might be a significant influence on the effect of prenatal, gender and genetic risk.

“We want to go back to the prenatal period to discover whether the biological factors or underlying environmental factors that emerge in puberty are a result of longer-standing influences that may be dormant.”

Ultimately, he says, the study aims to identify critical time-points when access to care—whether for the mother or the child—could serve a preventive function. “Depression is among the greatest causes of diminished quality of life and comorbidity. For this reason, we are in dire need of models that direct us to targets through which we can reduce the impact of depression. As with any chronic condition, early intervention is crucial.”
Of the roughly 600 families that are participating in the study, 300 will be evaluated by the research team at the JGH. The complex data be will analyzed using the facilities of the Ludmer Centre for Neuroinformatics and Biostatistics. Dr. Celia Greenwood, of the Lady Davis Institute at the JGH, is the principle investigator responsible for biostatistics and complex genetic modeling.

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