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Discovering the causes of Canada’s most prevalent type of mental illness and selecting the best treatment for each patient is Dr. Sidney Kennedy’s mission
Seeking to solve one of modern medicine’s most complicated puzzles, Dr. Sidney Kennedy is putting down markers. Dr. Kennedy, senior scientist at Toronto’s Krembil Research Institute, is working to discover what causes people to become depressed, and how to select the best treatment for each individual patient. Dr. Kennedy is working with biomarkers – biological measures that are used to detect the presence or risk of a disease or to identify subgroups that could help clinicians select the most appropriate treatment. “We’re particularly interested in identifying clusters of markers that distinguish subtypes of depression and help to predict response to treatments, such as medication, psychotherapy and brain stimulation.”
Through his research, Dr. Kennedy hopes to find important clues to unlock the science of one of the most prevalent and burdensome types of mental illnesses in Canada. Although it is gradually becoming better understood, mental illness is a leading cause of disability in Canada. Nearly 4,000 people die by suicide each year – almost 11 people each day. In a 2016 survey about mental health, 40 per cent of respondents agreed they have experienced anxiety or depression, but have not sought medical help.
Dr. Kennedy and his team at Krembil are expanding upon the
growing knowledge of the neurobiological and environmental factors associated
with depression and suicidal behaviour. “We don’t have the exact biomarkers
yet, though we do see individual variants,” he says. In 2014, The Lancet medical
journal reported that roughly half the risk for suicide could be hereditary.
“There has been a quest, for example, through the Human Genome Project, to
associate specific genes with different psychiatric disorders,” Dr. Kennedy
explains. “While I’m not a geneticist, I think it’s fair to say that no single
gene is specifically linked to depression.”
The search for biomarkers is more complicated than simply
identifying a group of genes. “We do have different clinical profiles that
distinguish patients with depression. For example, some are anxious, others are
slowed down with fatigue and extreme hopelessness, while others gain weight,
oversleep and are overly sensitive in their interactions with others,” says Dr.
Kennedy. “Unfortunately, the individual biomarkers that have been studied are
not consistently linked to any one clinical type and do not help to predict
which treatment is best for an individual patient.”
Those with unusually high cortisol levels “may be constantly
in a fight-or-flight stress mode, even when there isn’t a threat at that
moment. Their systems aren’t sensitive to normal ‘on’ and ‘off’ signals. Within
the brain, the hippocampus – the long ridge on each side of the bottom of our
brains – is a possible biomarker of depression. It forms part of our emotional
and cognitive brain circuitry. It helps with memory function and emotional
responses,” Dr. Kennedy says. “You would find that overall, among the general
population, the brains of those with depression have smaller hippocampi than those
who don’t have depression.”
Another challenge is identifying people who are likely to
become depressed. “We still can’t do a quick MRI [magnetic resonance imaging]
on you and say that, based on the size of your hippocampus, you’re likely to
get depressed in the next year. We don’t have those kinds of biomarkers yet,”
Dr. Kennedy says.
The real question he and his team are trying to solve is:
“Do different antecedents of depression result in different brain
disturbances?” For example, people who experienced emotional or sexual abuse in
childhood; offspring of parents with a history of depression; and individuals
being treated with an antiviral therapy are all at an increased risk of
becoming depressed – but are there different brain mechanisms underlying each
of these pathways to depression, and should different treatments be used?
“In each case the end point is the same,” says Dr. Kennedy.
“Each of these individuals may be sad, hopeless, with no sex drive, no interest
in anything, perhaps wanting to [end their lives]. Are there different pathways
to this disorder? If we identify those pathways, could we predict the correct
treatment more accurately?”
Dr. Kennedy’s research team works with other investigators
across Canada – at the University of British Columbia, University of Calgary,
Western University and McGill University – and in Ontario with McMaster
University, Queen’s University, University of Guelph, Brock University and the
University of Ottawa, CAMH and St. Michael’s Hospital.
“We are an extensive network implementing a broad range of
treatment trials. We try to use overlapping and constant biomarkers,” he says.
The scientists use fMRI (functional magnetic resonance imaging) to look at
changes in specific regions of the brain, and they take blood samples. They are
also applying augmented intelligence (“machine learning,” as Dr. Kennedy calls
it) and big data methods to combine and analyze the information from brain
imaging, clinical and genetic data. “The ultimate goal is to be able to come up
with profiles that can predict responses.” Already, over a four-year period,
300 patients have gone through brain scans and provided blood samples,
including 100 healthy patients whose data can be compared.