Schizophrenia and bipolar disorder are complex mental illnesses that are associated with cognitive deficits. There is considerable cognitive heterogeneity that exists within both disorders. Studies that cluster schizophrenia and bipolar patients into subgroups based on their cognitive profile increasingly demonstrate that, relative to healthy controls, there is a severely compromised subgroup and a relatively intact subgroup. There is emerging evidence that telomere shortening, a marker of cellular senescence, may be associated with cognitive impairments. The aim of this study was to explore the relationship between cognitive subgroups in bipolar-schizophrenia spectrum disorders and telomere length against a healthy control sample.

Participants included a transdiagnostic group diagnosed with bipolar, schizophrenia or schizoaffective disorder (n = 73) and healthy controls (n = 113). Cognitive clusters within the transdiagnostic patient group, were determined using K-means cluster analysis based on current cognitive functioning (MATRICS Consensus Cognitive Battery scores). Telomere length was determined using quantitative PCRs genomic DNA extracted from whole blood. Emergent clusters were then compared to the healthy control group on telomere length.

Two clusters emerged within the patient group that were deemed to reflect a relatively intact cognitive group and a cognitively impaired subgroup. Telomere length was significantly shorter in the severely impaired cognitive subgroup compared to the healthy control group.

This study replicates previous findings of transdiagnostic cognitive subgroups and associates shorter telomere length with the severely impaired cognitive subgroup. These findings support emerging literature associating cognitive impairments in psychiatric disorders to accelerated cellular aging as indexed by telomere length.

There is ongoing debate regarding the relationship between clinical symptoms and cognition in schizophrenia spectrum disorders (SSD). The present study aimed to explore the potential relationships between symptoms, with an emphasis on negative symptoms, and social and non-social cognition.

Hierarchical cluster analysis with k-means optimisation was conducted to characterise clinical subgroups using the Scale for the Assessment of Negative Symptoms and Scale for the Assessment of Positive Symptoms in n = 130 SSD participants. Emergent clusters were compared on the MATRICS Consensus Cognitive Battery, which measures non-social cognition and emotion management as well as demographic and clinical variables. Spearman’s correlations were then used to investigate potential relationships between specific negative symptoms and emotion management and non-social cognition.

Four distinct clinical subgroups were identified: 1. high hallucinations, 2. mixed symptoms, 3. high negative symptoms, and 4. relatively asymptomatic. The high negative symptom subgroup was found to have significantly poorer emotion management than the high hallucination and relatively asymptomatic subgroups. No further differences between subgroups were observed. Correlation analyses revealed avolition-apathy and anhedonia-asociality were negatively correlated with emotion management, but not non-social cognition. Affective flattening and alogia were not associated with either emotion management or non-social cognition.

The present study identified associations between negative symptoms and emotion management within social cognition, but no domains of non-social cognition. This relationship may be specific to motivation, anhedonia and apathy, but not expressive deficits. This suggests that targeted interventions for social cognition may also result in parallel improvement in some specific negative symptoms.