MAY 9, 2018
At a growing number of research centers across
the country, scientists are scanning brains of patients with depression, drawing their blood, asking about
their symptoms, and then scouring that data for patterns. The goal: pinpoint
subtypes of depression, then figure out which treatments have the best chance
of success for each particular variant of the disease.
The idea of precision medicine for depression is
quickly gaining ground — just last month, Stanford announced it is establishing
a Center for Precision Mental Health and Wellness. And depression is one of
many diseases targeted by All of Us, the National Institute of Health
campaign launched this month to collect DNA and other data from 1 million Americans. Doctors have
been treating cancer patients this way for
years, but the underlying biology of mental illness is not as well understood.
“There’s not currently a way to match people
with treatment,” said Dr. Madhukar Trivedi, a depression researcher at the
University of Texas Southwestern Medical Center. “That’s why this is a very
exciting field to research.”
A precision approach would be welcome news for
many patients with depression. There’s a well-documented cycle of trial and
error for these patients, who wait weeks for drugs to kick in, only to find out
they don’t work. Then they might have to repeat the process, often more than
once.
But it’s not an easy task to break down the many
factors that contribute to depression into clean categories with clear
treatments. While some in the field are excited about the promise of precision
medicine to better tailor treatments for depression, others are worried the
idea is being overhyped.
“It remains to be shown that depression
coalesces into neat subcategories, as opposed to being a fuzzy set,” said Dr.
Steven Hyman, director of the Stanley Center for Psychiatric Research at the
Broad Institute of MIT and Harvard.
Bringing precision medicine to depression would
be difficult for the same reason it would be useful — depression is a
heterogeneous disease that varies wildly from one patient to the next.
Take someone with a family history of
depression, who first experiences symptoms during adolescence and has several
instances of depression over her lifetime, and compare her to a 70-year-old man
who is in the early stages of Alzheimer’s disease and is experiencing symptoms
of depression for the first time.
“The [Diagnostic and Statistical Manual] would
give you the same diagnosis, and clearly there’s reason to think those are
very, very different,” said Hyman, a former director of the National Institute
of Mental Health.
Leanne Williams, the director of Stanford’s new
precision mental health center, acknowledged the task will be tricky,
but she believes it’s worth trying to bring more order to depression
treatment by making a coordinated push to gather as much data as possible. The
center — which will be the focus of a dedicated funding drive — will build on
$5 million in grants awarded to the researchers involved. Williams hopes to
launch a study to follow patients with depression for years, which would
cost much more.
The center’s roughly 35 faculty collaborators —
including psychiatrists, engineers, geneticists, and data scientists — are
using functional and structural MRI scans to analyze how depression disrupts
neural circuits in research subjects’ brains. They’re also sequencing patients’
genomes to find common mutations that might play a role, as well as gathering
clinical data on their symptoms.
“We want to use that information [to] guide the
treatment by subtype,” she said.
Once researchers define depression subtypes,
however, there’s still the question of whether — and how — doctors could use
data from genetic studies and brain scans to guide treatment. Williams is
planning a pilot project involving
roughly 75 patients with depression to answer that question. All of the
patients will undergo genetic testing, structural and functional MRIs,
diagnostic interviews, and other clinical assessments.
For about half of those patients, the
psychiatric team will get that information before coming up with a treatment
plan. For the other half, their doctors will get the data after 12 weeks of
treatment. Ultimately, Williams wants to find tests that physicians can use to
guide their depression treatment decisions. But the onus is on researchers to
show whether such tests “can shift the needle enough” to make them
worthwhile for doctors to use — and insurers to pay for, she said.
Elsewhere, researchers are on the hunt for
genetic mutations and biomarkers in the blood that could be used to diagnose
depression — and guide treatment. In his lab at UT Southwestern, Trivedi has
his eye on several potential depression biomarkers, including C-reactive
protein, which is a marker of inflammation.
In a study published last year, Trivedi and his
colleagues randomly assigned 100 patients with depression to receive one of two
depression treatments. Patients with lower CRP levels had a higher remission
rate on one treatment, while patients with higher CRP levels had a higher
remission rate on the other.
But while the finding is intriguing, it’s just a
small study. And that, experts say, is part of the problem.
Hyman, for his part, is skeptical — not of the
idea of precision medicine for depression, but of the quality of the data.
“My skepticism is not that it’s a bad project,
but we better not get ahead of ourselves and overhype,” he said. “I just think
people are just a bit ahead of what the data will permit.”
He pointed to several concerns. With fMRI scans,
for example, it’s difficult to tease out what might be caused by depression,
what might be a cause of depression, what might be due to prior treatment
attempts, and what’s just noise. It’s also challenging to collect brain scans
from enough patients to have a well-designed study that includes enough
patients to make the findings translatable to the general population.
And stratifying patients based on genetic
mutations is messy. Depression is highly polygenic, meaning there are likely
thousands of genetic variations in different combinations that can contribute
to the condition. And depression can’t be explained solely by genetics:
Environmental factors, particularly during development, also seem to play a
role.
“It’s some grab bag of these thousands of [genetic]
variants, plus bad luck as the brain develops, plus lived environments,” Hyman
said.
Williams said she hopes to set up a large-scale
study to create the kind of data set needed to better understand the factors at
play in depression. She sees the Framingham Heart Study — a
long-term study that began in 1948 and has followed patients for decades,
as a way to identify risk factors for heart disease — as a model for depression
research.
“We’ll start with what we can and keep building
on it,” she said.
Trivedi, the UT researcher, said he’s well aware
that there’s relatively little research on biomarkers that could be used to
guide depression treatments — but he and colleagues say each study inches the
field toward answers.
“Right now, we are throwing everything at the
wall and seeing what sticks,” he said. “Precision medicine is deciding what to throw
at the wall so the chances of sticking are better.”
https://www.statnews.com/2018/05/09/precision-medicine-depression-treatment/?itx[idio]=8812325&ito=792&itq=d21a3408-0a38-49d1-8c02-574a19b36a9e
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