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YOUR DAILY DOSE OF SCIENCE 11

GREY MATTER

VOLUME FROM

BRAIN MRI COULD

INFORM TREATMENT

DECISIONS FOR

MENTAL HEALTH

DISORDERS

The brain structure of

patients with recent onset

psychosis and depression can
offer important biological insights

into these illnesses and how

they might develop.

Researchers at the Univer- tools to use in planning strongly to their likelihood Evidence also showed illness, the more likely it was
sity of Birmingham show treatments.” of recovery. that patients in the cluster that a patient would fit into
that by examining structur- with lower volumes of grey the first cluster with lower
al MRI scans of the brain, In the study, the research- In the first cluster, lower matter in their brain scans grey matter volume. That
it’s possible to identify ers used data from around volumes of grey matter – may have higher levels really adds to the evidence
patients most susceptible 300 patients with recent the darker tissue inside the of inflammation, poorer that structural MRI scans
to poor outcomes. onset psychosis and recent brain involved in muscle concentration, and other may be able to offer useful
onset depression taking control and functions such cognitive impairments diagnostic information to
By identifying these pa- part in the PRONIA study. as memory, emotions, and previously associated with help guide targeted treat-
tients in the early stages of PRONIA is a European decision-making – were depression and schizo- ment decisions.”
their illness, clinicians will be Union-funded cohort study associated with patients phrenia.
able to offer more targeted investigating prognostic who went on to have The next step for the team
and effective treatments. tools for psychoses which is poorer outcomes. In the Finally, the team tested is to start to validate the
taking place across seven second group, in contrast, the clusters in other large clusters in the clinic, gath-
“Currently, the way we European research centers higher levels of grey matter cohort studies in Germany ering patient data in real
diagnose most mental including Birmingham. signaled patients who were and the US and were able time, before planning larger
health disorders is based more likely to recover well to show that the same scale clinical trials.
on a patient’s history, The researchers used a from their illness. identified clusters could
symptoms, and clinical machine learning algo- be used to predict patient Reference: “Neurobiologi-
observations, rather than rithm to assess data from A second algorithm was outcomes. cally Based Stratification of
on biological information,” patients’ brain scans and then used to predict the Recent Onset Depression
says lead author Paris sort these into groups, or patients’ condition nine “While the PRONIA study and Psychosis: Identifica-
Alexandros Lalousis. “That clusters. Two clusters were months following the initial contained people who tion of Two Distinct Trans-
means patients might have identified based on the diagnosis. The research- were recently diagnosed diagnostic Phenotypes” by
similar underlying biological scans, each of which con- ers found a higher level with their illness, the other Paris Alexandros Lalousis.
mechanisms in their illness, tained both patients with of accuracy in predicting datasets we used con-
but different diagnoses. psychosis and patients with outcomes when using the tained people with chronic
By understanding those depression. Each cluster biologically based clusters conditions,” explains
mechanisms more fully, we revealed distinctive char- compared to traditional Lalousis. “We found that
can give clinicians better acteristics which related diagnostic systems. the longer the duration of