Distinct Neurobiological Signatures of Early-Stage Depression and Psychosis

Post by Shalana Atwell

The takeaway

Neurobiological signatures can distinguish early-stage depression and psychosis and may help uncover mechanistic pathways and guide targeted interventions. 

What's the science?

Immune system alterations have been repeatedly linked to mood and psychotic disorders. Previous research has identified distinct and overlapping inflammatory markers in depression and psychosis whose dysregulation is associated with changes in brain gray matter volume (GMV). However, we need a more holistic view of the anatomical changes and inflammatory markers that are related to distinct pathologies of depression and psychosis. Furthermore, the complex relationship between immune factors and GMV makes univariate approaches poorly suited to capture higher-order patterns. Recently, in JAMA Psychiatry, Popovic and colleagues aimed to determine if multivariate patterns linking peripheral inflammatory markers with whole-brain gray matter volume could (1) distinguish early-stage depression and psychosis and (2) reveal how clinical factors such as childhood trauma and cognition relate to these biological signatures. 

How did they do it?

The authors analyzed baseline data from individuals with recent-onset depression, recent-onset psychosis, clinical high-risk state of psychosis, and healthy controls. All groups were medication-naïve or minimally medicated to reduce the confounding effects of antipsychotics and antidepressants. Peripheral blood was assayed for a panel of inflammatory and related markers such as interleukin (IL), tumor necrosis factor-alpha (TNF- α), and C-reactive protein (CRP), to name a few. These protein readouts were combined with demographic and technical covariates (age, sex, BMI, study group, MRI image quality) into a ‘blood’ domain. The ‘brain’ domain was generated using voxelwise gray matter volume (GMV) maps from structural MRI, which were mapped onto anatomical and functional network atlases to interpret where in the brain the signatures were expressed. To identify multivariate brain-blood domain relationships, the authors utilized sparse partial least squares regression (SPLS), which generates latent variables (LVs) that maximize covariance between the blood markers and GMV voxels. Each LV consists of weight vectors for blood markers and GMV voxels. Individual scores were computed by projecting each person’s data onto these weight vectors, and the correlation between blood and brain scores quantified how strongly the LV captures shared variance. Next, the authors used machine learning (linear support vector machine classification – SVM-C) to test whether life history (e.g., childhood trauma), cognitive function, and medications could predict high vs low expression of the psychosis-related and depression-related signatures. 

What did they find?

The authors found two significant brain-blood signatures that indicated a separation of psychotic and depressive disorders. Those with clinical high-risk status had higher levels of CRP compared to recent-onset psychosis, while recent-onset psychosis was associated with higher age, BMI, and certain inflammatory proteins (IL-6 and TNF- α). Additionally, they found disruptions in GMV mainly in cortico-thalamo-cerebellar circuitry that supports sensory integration and salience attribution. These findings suggest a different immune profile in high-risk and psychosis groups, as well as circuit disruptions that might serve as a neurobiological marker for defining different states of psychosis. In the depression signature, recent-onset depression was associated with higher levels of a mix of pro- and anti-inflammatory proteins (IL-1RA, IL-4, S100B, IL-1β, IL-2, and BDNF) and reductions in GMV in limbic system structures, such as the hippocampus and amygdala, compared to healthy controls. These findings support a complex immune-inflammatory and compensatory response as well as limbic-cortical dysregulation as a core neurobiological feature of depression.  

What's the impact?

This study is one of the first large, minimally medicated, transdiagnostic investigations to show that early-stage depression and psychosis are associated with distinct multivariate immune-brain signatures. Furthermore, the authors demonstrate that these signatures are shaped by childhood trauma and cognition, supporting stage-specific differentiation of psychosis and depression, which could guide targeted early interventions.

Access the original scientific publication here.

Playing Rhythm Games May Improve Stuttering

Post by Anastasia Sares

The takeaway

This proof-of-concept study tested a computer game intervention with children who stutter. Those who played a rhythm-based game had improved rhythm and speech motor skills at the end of the study, but more work is needed to establish the efficacy of this gamified intervention.

What's the science?

Developmental stuttering is a disorder of speech that is characterized by involuntary pauses, repetitions, or extensions of speech sounds. Sometimes a stutter disappears naturally as children get older, but for about 1% of the population, stuttering continues into adulthood. There is a growing body of research showing that rhythmic abilities, like tapping to a beat or hearing differences in rhythmic patterns, are linked to language abilities, like reading and speaking. Scientists are beginning to test whether rhythm training might lead to improvements in language-related disorders like dyslexia and stuttering.

This week in Annals of the New York Academy of Sciences, Jamey and colleagues tested whether playing a rhythm game would improve speech fluency in people who stutter.

How did they do it?

About 20 children who stutter (ages 9-12) were recruited to participate in the study. These participants were divided into two groups: the rhythm-based intervention group and the non-rhythm-based intervention group. Both groups were tested on attention/cognition, rhythm ability, speech motor ability, and stuttering frequency before the intervention began and after it was over.

The rhythm-based intervention was a game called Rhythm Workers, in which the player must tap on the screen in synchrony with the music to help construction workers build a building, with levels being added to the building based on accurate synchronization. The non-rhythm-based game was based on an open-source version of the game Frozen Bubbles, where players must shoot bubbles out of a cannon to make clusters of colored bubbles on the screen and eliminate them. The same music was played in the background of both games, and they required similar amounts of tapping on the screen. Each group played their respective games for three weeks, and were told to aim for 30 minutes to one hour each day. The use of an “active control” condition is important in this kind of work to make sure that it is the rhythmic aspect of the game, not just the gamification itself or the time and attention required, that is responsible for any gains.

What did they find?

On average, both groups completed over 90% of the target amount of play time and reported enjoying the games, though there was variation between individuals in terms of their dedication and enjoyment. Both groups started out with similar scores on rhythmic behavior, attention/cognition, and speech, but the Rhythm Workers group showed some improvements in each category by the end of the intervention, while the Frozen Bubbles group did not. The more time participants spent in the Rhythm Workers game, the better their rhythm and stuttering scores were at the end of the intervention, while time spent in the Frozen Bubbles game was not related to rhythm or stuttering scores. Improvement in rhythm scores was also related to reduced stuttering.

However, the main group difference of interest—whether stuttering scores improved more with the Rhythm Workers game than the Frozen Bubbles game—did not reach significance.

What's the impact?

This study, though the sample size is small, shows promise for rhythm-based interventions in speech disorders such as stuttering. The next step will be to replicate these findings and to test whether the Rhythm Workers game (or a similar intervention) could actually lead to significant reductions in stuttering in a larger sample.

Access the original scientific publication here.

Are Type 2 Diabetes and Dementia Linked?

Post by Rebecca Glisson

The takeaway

Type 2 diabetes can lead to worse cognitive health and even dementia. This study found that in a large sample of over 350,000 individuals, type 2 diabetes leads to a higher risk of Alzheimer’s disease.

What's the science?

The relationship between type 2 diabetes and brain health is not yet understood; however, some evidence suggests that diabetes symptoms are related to dementia symptoms. One common symptom of diabetes is the level of glucose (sugar) in the bloodstream 2 hours after eating, which should typically return to baseline levels in healthy individuals but stays high in diabetic individuals because they lack insulin to process glucose out of the bloodstream. This week in Diabetes, Obesity and Metabolism, Mason and colleagues studied the possible mechanisms of how diabetes is linked to dementia.

How did they do it?

The authors used a large database of survey questions and health measurements to test for correlations between diabetes and cognitive function. They used data from 357,883 participants who were between 40 and 69 years old (54.1% female). They tested cognitive functioning using MRI scans to measure volume in the hippocampus, a brain region involved in memory processing, along with total brain volume. To measure diabetes symptoms, the authors obtained blood samples from participants.

What did they find?

The authors found that individuals who had elevated levels of glucose had a 23% increased risk of dementia, and a 69% increased risk of Alzheimer’s disease. This supports the idea that individuals with type 2 diabetes are more at risk for developing cognitive disorders. However, the authors did not find any link between diabetes symptoms or brain measurements. This suggests that the increased risk for dementia from diabetes likely acts through other mechanisms. The authors suggest that future research should look into tau and amyloid plaques, which are other markers of Alzheimer’s disease and could be one cause for the link between diabetes and risk of developing dementia.

What's the impact?

This study is the first to show a clear link between diabetes symptoms and symptoms of cognitive dysfunction. However, the mechanism for this link is still unclear and needs further study. An important caveat is that only white, British participants were included in the study due to a lack of data availability for other groups, and further study should be conducted on diverse populations.

Access the original scientific publication here.