Data-driven profiles of psychosis stages reveal distinct and overlapping clinical, cognitive, and neuroanatomical phenotypes

This study utilizes a unique multimodal dataset to demonstrate that while affective and functional disturbances emerge in early psychosis stages, cognitive and neuroanatomical abnormalities characterize more advanced phases, yet significant overlapping phenotypes across risk groups underscore the need for personalized care beyond traditional diagnostic boundaries.

The Gist

Imagine the human mind as a complex, high-tech city. Sometimes, this city starts to experience "power outages" or "traffic jams" that lead to a condition called psychosis. For a long time, doctors have tried to sort people into neat boxes based on how severe their symptoms are:

1. The "At-Risk" Family (FHR): People who have a family history of the city's blackouts but haven't seen any smoke yet.
2. The "Warning Signs" Group (CHR): People who are starting to see flickering lights and hear strange noises (sub-threshold symptoms) and are asking for help.
3. The "First Blackout" Group (FEP): People who have just experienced their first major power failure (a first episode of psychosis).

This study is like a massive, data-driven city inspection. The researchers didn't just look at the "blackout" itself; they looked at the whole city—its mood, its traffic (cognition), its functioning, and even its physical infrastructure (brain structure)—across all three groups to see how the problem evolves.

Here is what they found, translated into everyday terms:

1. The "Mood" vs. The "Hardware"

The researchers discovered that the problems show up in different parts of the city at different times.

• The "Warning Signs" Group (CHR) is emotionally overwhelmed. Imagine a neighborhood where the residents are incredibly anxious, depressed, and struggling to keep their jobs or social lives together. However, the physical buildings (the brain structure) still look mostly intact. They are suffering a lot, but the "hardware" hasn't crumbled yet.
• The "First Blackout" Group (FEP) has structural damage. Once the first major episode hits, the city's physical infrastructure starts to show wear and tear. The "buildings" (cortical thickness in the brain) begin to thin out, and the "traffic" (cognitive thinking skills) gets significantly worse. This is the stage where the brain starts to look like it does in established schizophrenia.

The Takeaway: Emotional distress and trouble functioning often start early, but the physical changes to the brain and deep cognitive struggles seem to arrive with the first full-blown episode.

2. The "Universal Blueprint"

The researchers used a special tool (a data-driven map) to see if there was a single "blueprint" that connected how people felt to how their brains looked, regardless of which group they were in.

They found a strong link: When the brain's "buildings" get thinner, the city's "thinking traffic" slows down.

Surprisingly, this pattern was the same for both the "Warning Signs" group and the "First Blackout" group. Even though the "Warning Signs" group didn't have as much damage on average, the individuals who did have some thinning were the same ones struggling with thinking and functioning. It's like realizing that even in a neighborhood with mostly good buildings, the few houses with cracks are the ones where the residents are having the hardest time.

3. What Predicts the Future?

The team also looked at who would struggle the most six months later. They asked: "Who will have the hardest time functioning in the future?"

The answer wasn't the severity of the "psychosis" symptoms (like hearing voices). Instead, it was depression and negative symptoms (like feeling empty, unmotivated, or withdrawn).

Think of it this way: If you are trying to fix a broken car, the loud engine noise (psychosis) is scary, but the fact that the driver is too depressed to get out of the seat (depression/negative symptoms) is what actually stops the car from moving forward. This was true for everyone, whether they were in the early "warning" stage or the "first blackout" stage.

4. The "Gray Area" Reality

The biggest lesson from this paper is that human experience doesn't fit into neat boxes.

While the researchers tried to sort people into three distinct stages, they found a huge amount of overlap. Some people in the "Warning Signs" group had brain patterns just as severe as the "First Blackout" group. Some people in the "First Blackout" group had milder symptoms than expected.

The Metaphor: Imagine a staircase. We used to think you were either on step 1, step 2, or step 3. This study shows that people are actually standing on a ramp. You can be high up on the ramp but still have some of the same struggles as someone lower down.

Why This Matters

This study suggests that we need to stop treating these groups as completely different species.

• For the "Warning Signs" group: We shouldn't just focus on preventing the "blackout." We need to treat the anxiety, depression, and functional struggles now, because those are what are hurting them the most.
• For everyone: Since the link between brain health and thinking skills is the same across the board, treatments that help the brain (like cognitive remediation) might help people at any stage, not just those with a full diagnosis.

In short, the city of the mind is complex. The "smoke" (anxiety/depression) often appears before the "fire" (brain changes), but the fire changes the landscape permanently. To help the residents, we need to look at the whole city, not just the stage they are currently on.

Technical Summary

1. Problem Statement

Psychotic disorders are increasingly viewed as the extreme end of a progressive continuum, ranging from asymptomatic familial high-risk (FHR) to clinical high-risk (CHR) and first-episode psychosis (FEP). While clinical staging models exist, there is a critical lack of comprehensive, multimodal data comparing these three specific stages within the same clinical and sociodemographic setting.

• Knowledge Gaps: It remains unclear which markers (clinical, cognitive, functional, neuroanatomical) best define the transition points between stages.
• Limitations of Current Models: Existing literature often treats stages as discrete categories, failing to account for the multidimensional overlap of phenotypes (e.g., depression, cognitive deficits, cortical thinning) across the spectrum.
• Objective: To perform the first direct, in-depth comparison of FHR, CHR, and FEP groups using a unified dataset to identify distinct versus overlapping phenotypes and to determine if data-driven axes of variability align with established clinical stages.

2. Methodology

The study utilized a cross-sectional design with a preliminary longitudinal component, recruiting 194 participants (aged 14–35) from the Douglas Mental Health University Institute in Montreal.

• Cohorts:
  • FEP (N=70): First-episode psychosis (affective or non-affective), currently receiving treatment.
  • CHR (N=40): Clinical high-risk (help-seeking, subthreshold symptoms).
  • FHR (N=43): Familial high-risk (asymptomatic siblings of FEP patients).
  • HC (N=41): Healthy controls.
• Assessments:
  • Clinical/Functional: PANSS-6, SIPS, SANS, SAPS, BAI, DASS-21, GAF, SOFAS, and others.
  • Cognitive: Cogstate Research Battery (7 domains), Wechsler Memory Scale (WMS), Beck Cognitive Insight Scale.
  • Neuroimaging: T1-weighted MRI (3T Siemens) processed via FreeSurfer (ENIGMA protocol) to derive cortical thickness in 68 Desikan-Killiany-Tourky regions.
• Analytical Approaches:
  1. Group Comparisons: One-way ANOVAs and Tukey's post-hoc tests with Holm-Bonferroni correction for summary scores.
  2. Factor Analysis: Exploratory factor analysis (oblique rotation) to identify latent dimensions of psychopathology across the sample.
  3. Longitudinal Modeling: Linear models predicting 6-month Global Assessment of Functioning (GAF) from baseline symptoms, controlling for baseline GAF.
  4. Neuroanatomical Profiling:
     • Calculation of Hedges' g effect sizes for cortical thickness differences relative to controls.
     • Spatial correlation of group effect size maps against meta-analytic maps from the ENIGMA toolbox (Schizophrenia, Bipolar, ADHD, ASD, etc.).
  5. Joint Clinical-Anatomical Analysis: Partial Least Squares (PLS) correlation to identify latent variables (LVs) maximizing covariance between clinical symptoms and cortical thickness, independent of group status.

3. Key Results

A. Clinical, Cognitive, and Functional Profiles

• CHR vs. FEP: Both groups exhibited equivalent levels of psychosis symptoms and functional impairment (GAF/SOFAS).
• Depression/Anxiety: The CHR group showed significantly higher levels of depression and anxiety compared to FEP, FHR, and HC.
• Cognition: FEP was uniquely characterized by significant cognitive impairments compared to both high-risk groups and controls.
• FHR: Did not differ significantly from healthy controls on any assessed scale.

B. Factor Analysis

Three primary dimensions emerged:

1. Psychosis/Functioning: CHR and FEP scores were indistinguishable.
2. Depression/Anxiety: CHR scored highest.
3. Negative Symptoms/Cognition: FEP trended highest, but significant overlap existed across groups.

• Finding: Individual phenotypes showed marked overlap across diagnostic boundaries, suggesting stages are not discrete cut-offs.

C. Longitudinal Predictors

• Baseline depressive and negative symptoms were the strongest predictors of lower functioning at 6-month follow-up.
• This relationship held true across all groups (CHR and FEP), with no significant group-by-symptom interactions.

D. Neuroanatomical Findings

• Cortical Thickness: Only the FEP group showed widespread cortical thickness reductions relative to controls, resembling the pattern seen in established schizophrenia (and Bipolar Disorder/OCD).
• High-Risk Groups: Neither CHR nor FHR showed a schizophrenia-like cortical thinning pattern.
  • The CHR map showed a non-significant trend toward resembling 22q11.2 deletion syndrome.
  • The FHR map showed an inverse relationship with Autism Spectrum Disorder.
• Replication: The CHR anatomical pattern failed to replicate in two held-out international cohorts.

E. Joint Clinical-Anatomical Continuum (PLS)

• The dominant latent variable (LV1) linked reduced cortical thickness with lower cognitive performance, lower functioning, and higher negative/depressive symptoms.
• Crucial Finding: Despite group-level differences in mean cortical thickness, CHR and FEP individuals overlapped significantly on this data-driven continuum. Individuals in the CHR group expressed the same brain-behavior covariance pattern as those in the FEP group, even if the group means differed.

4. Key Contributions

1. First Multimodal Comparison: This is the first study to simultaneously profile FHR, CHR, and FEP using identical clinical, cognitive, and neuroimaging protocols within a single cohort.
2. Decoupling Stages from Phenotypes: Demonstrates that while clinical stages (CHR vs. FEP) differ in specific markers (e.g., cognition, cortical thinning), the underlying multidimensional phenotypes (especially the brain-behavior axis) are continuous and overlapping.
3. Transdiagnostic Insights: Identifies that depression and negative symptoms are the primary drivers of functional decline across all early stages, regardless of psychosis severity.
4. Neuroanatomical Timing: Suggests that widespread cortical thinning characteristic of schizophrenia emerges primarily at the FEP stage (or shortly after), rather than being a pre-existing marker in the CHR state.

5. Significance and Implications

• Clinical Staging: The findings challenge rigid diagnostic boundaries. The data supports a transdiagnostic clinical staging framework where care is tailored to individual symptom profiles (e.g., targeting depression/anxiety in CHR) rather than just the risk of conversion to psychosis.
• Intervention Targets: Since depression and negative symptoms predict functional outcomes across all stages, interventions should prioritize these domains early, potentially before full psychosis onset.
• Cognitive Remediation: Given that cognitive deficits and cortical thinning are linked and emerge prominently in FEP, cognitive remediation therapies should be integrated early in the treatment of FEP and potentially high-risk individuals showing these specific markers.
• Biomarker Utility: Cortical thickness may serve as a marker for the transition to full-threshold disorder (FEP) rather than a marker for the high-risk state itself, refining the utility of neuroimaging in early intervention programs.

Limitations Noted: The study is a preprint (not yet peer-reviewed); the CHR group had a small sample size for neuroimaging replication; and medication effects in the FEP group, while controlled for, cannot be fully deconfounded.