Cognitive function in early-phase schizophrenia-spectrum disorder: IQ subtypes, brain volume and immune markers

Monomeric C-reactive protein as a biomarker for major depressive disorder

Neuroinflammation has been postulated to be a key factor in the pathogenesis of major depressive disorder (MDD). With this is mind, there has been a wave of research looking into pro-inflammatory mediators as potential biomarkers for MDD. One such mediator is the acute phase protein, C-reactive protein (CRP). While several studies have investigated the potential of CRP as a biomarker for MDD, the results have been inconsistent. One explanation for the lack of consistent findings may be that the high-sensitivity CRP tests utilized in these studies only measure the pentameric isoform of CRP (pCRP). Recent research, however, has indicated that the monomeric isoform of CRP (mCRP) is responsible for the pro-inflammatory function of CRP, while pCRP is weakly anti-inflammatory. The objective of this minireview is to re-examine the evidence of CRP involvement in MDD with a view of mCRP as a potential biomarker.

Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity

OBJECTIVE

Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of inflammation and its effect on grey matter volume (GMV) in patients. We hypothesised that inflammatory subgroups can be identified and that the subgroups will show distinct neuroanatomical and neurocognitive profiles.

METHODS

The total sample consisted of 1067 participants (chronic patients with schizophrenia n = 467 and healthy controls (HCs) n = 600) from the Australia Schizophrenia Research Bank (ASRB) dataset, together with 218 recent-onset patients with schizophrenia from the external Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism (BeneMin) dataset. HYDRA (HeterogeneitY through DiscRiminant Analysis) was used to separate schizophrenia from HC and define disease-related subgroups based on inflammatory markers. Voxel-based morphometry and inferential statistics were used to explore GMV alterations and neurocognitive deficits in these subgroups.

RESULTS

An optimal clustering solution revealed five main schizophrenia groups separable from HC: Low Inflammation, Elevated CRP, Elevated IL-6/IL-8, Elevated IFN-γ, and Elevated IL-10 with an adjusted Rand index of 0.573. When compared with the healthy controls, the IL-6/IL-8 cluster showed the most widespread, including the anterior cingulate, GMV reduction. The IFN-γ inflammation cluster showed the least GMV reduction and impairment of cognitive performance. The CRP and the Low Inflammation clusters dominated in the younger external dataset.

CONCLUSIONS

Inflammation in schizophrenia may not be merely a case of low vs high, but rather there are pluripotent, heterogeneous mechanisms at play which could be reliably identified based on accessible, peripheral measures. This could inform the successful development of targeted interventions.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia

BACKGROUND

Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.

METHODS

A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.

RESULTS

Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).

CONCLUSIONS

These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

Evaluating the predictive performance of subtyping: A criterion for cluster mean-based prediction

Heterogeneity is a frequent issue in population data analyses in medicine, biology, and the social sciences. A common approach for handling heterogeneity is to use a clustering algorithm to group similar samples, considering samples within the same group to be homogeneous. This approach is known as "subtyping" or "subgrouping." Methods for evaluating the validity of subtyping have yet to be fully established. In this study, we propose the cost of cluster mean-based prediction (CCMP) as a metric for evaluating the accuracy of predictions based on subtyping. By selecting the minimum CCMP among several candidate clustering results, the optimal subtype classification in terms of prediction accuracy can be determined. The computational implementation of the CCMP is validated with numerical experiments. We also examine some properties of subtype classification selected by CCMP.

A Comparison of the Relationship Between C-Reactive Protein Levels and Cognitive Functions in Patients with Schizophrenia, First-Episode Psychosis, and Healthy Controls

Background

There are several hypotheses on what causes schizophrenia, some of which include inflammatory responses. Additionally, it might be challenging to control and treat cognitive abnormalities, which represent the primary symptoms, and may be related to inflammation. This study aims to determine whether there is a relationship between C-reactive protein levels and cognitive abilities by assessing neuropsychological tests of drug-free patients with schizophrenia and first-episode psychosis.

Methods

The patient group consisted of 36 patients with schizophrenia or "first-episode psychosis," while the control group comprised 31 healthy people. The control group consisted of healthy participants without any medical or psychiatric diseases. Structured Clinical Interview for DSM-5 axis I disorders was applied for diagnosis, while Wisconsin card sorting test, Stroop color and word test, trail making tests, Rey auditory verbal learning test, and digit span test were applied for cognitive assessment of both groups. Clinical characteristics of patients were evaluated by using the Scale for the Assessment of Positive Symptoms, the Scale for the Assessment of Negative Symptoms, and the Calgary Depression Scale for Schizophrenia. The patient group and healthy control group were evaluated in terms of inflammation levels. The C-reactive protein levels were measured, and their relationship with cognitive status was examined. The serum samples were analyzed by the immunoturbidimetric method in C-reactive protein C8000 Architect (Abbott, Ill, USA) to measure the C-reactive protein levels.

Results

C-reactive protein levels were found to be higher in the patient group (P = .003), while the Scale for the Assessment of Negative Symptoms and Scale for the Assessment of Positive Symptoms scores were found to be positively correlated with C-reactive protein levels. Cognitive functions in the patient group were significantly lower compared to the healthy group. There was a statistically weak correlation between C-reactive protein and the number of word color reading errors in the Stroop test, which was associated with complex and frontal attention; however, no correlation was found with digit span test, Rey auditory verbal learning test, or Wisconsin card sorting test points.

Conclusion

Elevated peripheral levels of C-reactive protein are associated with poorer cognitive function in patients with first-episode psychosis and schizophrenia, particularly, complex attention associated with the Stroop test. Inflammation may have an impact on cognitive impairment in psychosis.