Understanding the Influence of Personality Traits on Risk of Suicidal Behaviour in Schizophrenia Spectrum Disorders: A Systematic Review

Risk of suicidal behaviour (SB) in schizophrenia spectrum disorders (SSD) is a major concern, particularly in early stages of the illness, when suicide accounts for a high number of premature deaths. Although some risk factors for SB in SSD are well understood, the extent to which personality traits may affect this risk remains unclear, which may have implications for prevention. We conducted a systematic review of previous studies indexed in MEDLINE, PsycINFO and Embase examining the relationship between personality traits and SB in samples of patients with SSD. Seven studies fulfilled predetermined selection criteria. Harm avoidance, passive-dependent, schizoid and schizotypal personality traits increased the risk of SB, while self-directedness, cooperativeness, excluding persistence and self-transcendence acted as protective factors. Although only seven studies were retrieved from three major databases after applying predetermined selection criteria, we found some evidence to support that personality issues may contribute to SB in patients with SSD. Personality traits may therefore become part of routine suicide risk assessment and interventions targeting these personality-related factors may contribute to prevention of SB in SSD

Insight and risk of suicidal behaviour in two first-episode psychosis cohorts: effects of previous suicide attempts and depression

ABSTRACT Background: The role of insight dimensions – illness recognition (IR), symptoms relabelling (SR), treatment compliance (TC) - in suicide risk in first-episode psychosis (FEP) remains unclear. Method: The AESOP (n=181) and GAP (n=112) FEP cohorts were followed-up over 10- and 5 years. Survival analysis modelled time to first suicidal event in relation to baseline scores on the Schedule for the Assessment of Insight, whilst adjusting for demographic, clinical, psychopathological and neuropsychological variables.This work represents independent research which was supported by the UK Medical Research Council (grant number G0500817) and partly-funded by the UK Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Centre for Mental Health award to the South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry, Psychology and Neuroscience at Kings College London. JDLM was funded by the British Medical Association via the Margaret Temple Research Award for Schizophrenia. PBJ received funding support from the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care (CLAHRC), East of England. RMM was supported by the Medical Research Council and Lord Leverhulme Trust. CM is funded by grants from the Medical Research Council (grant number MR/P025927/1) and EU (grant number ERC Ref: 648837 REACH). RD is funded by a Clinician Scientist Fellowship awarded by the Academy of Medical Sciences in partnership with The Health Foundation. ASD is supported by National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and Kings College London

Gut-central nervous system axis is a target for nutritional therapies

Historically, in the 1950s, the chemist Linus Pauling established a relationship between decreased longevity and obesity. At this time, with the advent of studies involving the mechanisms that modulate appetite control, some researchers observed that the hypothalamus is the "appetite centre" and that peripheral tissues have important roles in the modulation of gut inflammatory processes and levels of hormones that control food intake. Likewise, the advances of physiological and molecular mechanisms for patients with obesity, type 2 diabetes mellitus, inflammatory bowel diseases, bariatric surgery and anorexia-associated diseases has been greatly appreciated by nutritionists. Therefore, this review highlights the relationship between the gut-central nervous system axis and targets for nutritional therapies

The right occipital lobe and poor insight in first-episode psychosis

Lack of insight is a core feature of non-affective psychosis and has been associated with poorer outcomes. Brain abnormalities underlying lack of insight have been suggested, mostly in the frontal lobe, although previous research showed mixed results. We used a voxel-based morphometry (VBM) analysis in 108 first-episode non-affective psychosis patients to investigate the pattern of brain structural abnormalities related to lack of insight. In addition, 77 healthy volunteers were compared with the patients classified as having poor and good insight. The shortened version of the Scale to Assess Unawareness of Mental Disorder was used to evaluate insight. Patients with poor insight (n = 68) compared with patients with good insight (n = 40) showed a single significant cluster (kc = 5834; PcFWE = 0.001) of reduced grey matter volume (GMV) in the right occipital lobe extending to its lateral and medial surfaces, the cuneus, and the middle temporal gyrus. In addition, GMV at this cluster showed a negative correlation with the score of the SUMD (r = -0.305; p = 0.001). When comparing patients with poor insight with healthy subjects overall reductions of GMV were found, mainly in frontal and occipital lobes. Hence, poor insight in non-affective psychosis seems to be associated with specific brain abnormalities in the right occipital and temporal cortical regions. Dysfunction in any combination of these areas may contribute to lack of insight in non-affective psychosis. Specifically, the 'right' hemisphere dysfunction underlying impaired insight in our sample is consistent with previously reported similarities between lack of insight in psychosis and anosognosia in neurological disorders

Socio-demographic and clinical characteristics of the study groups.

<p>Socio-demographic and clinical characteristics of the study groups.</p

SPM results; areas where patients with poor illness insight show less grey matter volume than patients with good illness insight.

<p>(good IMI > poor IMI).</p

SPM results; areas where patients with poor illness insight show less grey matter volume than healthy controls.

<p>(HC > poor IMI).</p

SPM results; areas where patients with poor illness insight show less grey matter volume than healthy controls (HC > poor IMI).

<p>SPM results; areas where patients with poor illness insight show less grey matter volume than healthy controls (HC > poor IMI).</p