White matter, cognition and psychotic-like experiences in UK Biobank.

BACKGROUND: Psychotic-like experiences (PLEs) are risk factors for the development of psychiatric conditions like schizophrenia, particularly if associated with distress. As PLEs have been related to alterations in both white matter and cognition, we investigated whether cognition (g-factor and processing speed) mediates the relationship between white matter and PLEs. METHODS: We investigated two independent samples (6170 and 19 891) from the UK Biobank, through path analysis. For both samples, measures of whole-brain fractional anisotropy (gFA) and mean diffusivity (gMD), as indications of white matter microstructure, were derived from probabilistic tractography. For the smaller sample, variables whole-brain white matter network efficiency and microstructure were also derived from structural connectome data. RESULTS: The mediation of cognition on the relationships between white matter properties and PLEs was non-significant. However, lower gFA was associated with having PLEs in combination with distress in the full available sample (standardized ß = -0.053, p = 0.011). Additionally, lower gFA/higher gMD was associated with lower g-factor (standardized ß = 0.049, p < 0.001; standardized ß = -0.027, p = 0.003), and partially mediated by processing speed with a proportion mediated of 7% (p = < 0.001) for gFA and 11% (p < 0.001) for gMD. CONCLUSIONS: We show that lower global white matter microstructure is associated with having PLEs in combination with distress, which suggests a direction of future research that could help clarify how and why individuals progress from subclinical to clinical psychotic symptoms. Furthermore, we replicated that processing speed mediates the relationship between white matter microstructure and g-factor.

Experience of clinical services shapes attitudes to mental health data sharing: findings from a UK-wide survey.

BACKGROUND: Routinely-collected mental health data could deliver novel insights for mental health research. However, patients' willingness to share their mental health data remains largely unknown. We investigated factors influencing likelihood of sharing these data for research purposes amongst people with and without experience of mental illness. METHODS: We collected responses from a diverse sample of UK National Health Service (NHS) users (n = 2187) of which about half (n = 1087) had lifetime experience of mental illness. Ordinal logistic regression was used to examine the influence of demographic factors, clinical service experience, and primary mental illness on willingness to share mental health data, contrasted against physical health data. RESULTS: There was a high level of willingness to share mental (89.7%) and physical (92.8%) health data for research purposes. Higher levels of satisfaction with the NHS were associated with greater willingness to share mental health data. Furthermore, people with personal experience of mental illness were more willing than those without to share mental health data, once the variable of NHS satisfaction had been controlled for. Of the mental illnesses recorded, people with depression, obsessive-compulsive disorder (OCD), personality disorder or bipolar disorder were significantly more likely to share their mental health data than people without mental illness. CONCLUSIONS: These findings suggest that positive experiences of health services and personal experience of mental illness are associated with greater willingness to share mental health data. NHS satisfaction is a potentially modifiable factor that could foster public support for increased use of NHS mental health data in research.

Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank.

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.

The role of neuroticism in self-harm and suicidal ideation: results from two UK population-based cohorts.

BACKGROUND: Self-harm is common, debilitating and associated with completed suicide and increased all-cause mortality, but there is uncertainty about its causal risk factors, limiting risk assessment and effective management. Neuroticism is a stable personality trait associated with self-harm and suicidal ideation, and correlated with coping styles, but its value as an independent predictor of these outcomes is disputed. METHODS: Prior history of hospital-treated self-harm was obtained by record-linkage to administrative health data in Generation Scotland:Scottish Family Health Study (N = 15,798; self-harm cases = 339) and by a self-report variable in UK Biobank (N = 35,227; self-harm cases = 772). Neuroticism in both cohorts was measured using the Eysenck Personality Questionnaire-Short Form. Associations of neuroticism with self-harm were tested using multivariable regression following adjustment for age, sex, cognitive ability, educational attainment, socioeconomic deprivation, and relationship status. A subset of GS:SFHS was followed-up with suicidal ideation elicited by self-report (n = 3342, suicidal ideation cases = 158) and coping styles measured by the Coping Inventory for Stressful Situations. The relationship of neuroticism to suicidal ideation, and the role of coping style, was then investigated using multivariable logistic regression. RESULTS: Neuroticism was positively associated with hospital-associated self-harm in GS:SFHS (per EPQ-SF unit odds ratio 1.2 95% credible interval 1.1-1.2, pFDR 0.0003) and UKB (per EPQ-SF unit odds ratio 1.1 95% confidence interval 1.1-1.2, pFDR 9.8 × 10-17). Neuroticism, and the neuroticism-correlated coping style, emotion-oriented coping (EoC), were also associated with suicidal ideation in multivariable models. CONCLUSIONS: Neuroticism is an independent predictor of hospital-treated self-harm risk. Neuroticism and emotion-orientated coping styles are also predictive of suicidal ideation.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study.

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (ß = 0.132, pFDR = 0.040), arcuate (ß = 0.291, pFDR = 0.040), anterior thalamic radiations (ß = 0.215, pFDR = 0.040) and cingulum (ß = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (ß = -0.039, pFDR = 0.048) and strength (ß = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

Is there a symptomatic distinction between the affective psychoses and schizophrenia? A machine learning approach.

Dubiety exists over whether clinical symptoms of schizophrenia can be distinguished from affective psychosis, the assumption being that absence of a "point of rarity" indicates lack of nosological distinction, based on prior group-level analyses. Advanced machine learning techniques, using unsupervised (hierarchical clustering) and supervised (regularized logistic regression algorithm and nested-cross-validation) were applied to a dataset of 202 patients with functional psychosis (schizophrenia n = 120, affective psychosis, n = 82). Patients were initially assessed with the Present State Examination (PSE), and followed up 2.5 years later, when DSM III diagnoses were applied (independent of initial PSE). Based on PSE syndromes, unsupervised learning discriminated depressive (approximately unbiased probability, AUP = 0.92) and mania/psychosis (AUP = 0.94) clusters. The mania/psychosis cluster further split into two groups - a mania (AUP = 0.84) and a psychosis cluster (AUP = 0.88). Supervised machine learning classified schizophrenia or affective psychosis with 83.66% (95% CI = 77.83% to 88.48%) accuracy. Area under the ROC curve (AUROC) was 89.14%. True positive rate for schizophrenia was 88.24% (95%CI = 81.05-93.42%) and affective psychosis 77.11% (95%CI = 66.58-85.62). Classification accuracy and AUROC remained high when PSE syndromes corresponding to affective symptoms (those that corresponded to the depressive and mania clusters) were removed. PSE syndromes, based on clinical symptoms, therefore discriminated between schizophrenia and affective psychosis, suggesting validity to these diagnostic constructs.

Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study.

BACKGROUND: Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia. METHODS: The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes. RESULTS: We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification. CONCLUSIONS: These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.

Risk of transition to schizophrenia following first admission with substance-induced psychotic disorder: a population-based longitudinal cohort study.

BACKGROUND: The potential for drugs of abuse to induce acute psychotic symptoms is well recognised. However, the likelihood of transition from initial substance-induced psychotic disorder (SIPD) to chronic psychosis is much less well understood. This study investigated the rate of SIPD transition to schizophrenia (F20), the time to conversion and other possible related factors. METHODS: Using data from the Scottish Morbidity Record, we examined all patients (n = 3486) since their first admission to psychiatric hospital with a diagnosis of SIPD [International Classification of Diseases, Tenth Revision (ICD-10) codes F10-F19, with third digit five] from January 1997 to July 2012. Patients were followed until first episode of schizophrenia (ICD-10 code F20, with any third digit) or July 2012. Any change in diagnosis was noted in the follow-up period, which ranged from 1 day to 15.5 years across the groups. RESULTS: The 15.5-year cumulative hazard rate was 17.3% (s.e. = 0.007) for a diagnosis of schizophrenia. Cannabis, stimulant, opiate and multiple drug-induced psychotic disorder were all associated with similar hazard rates. The mean time to transition to a diagnosis of schizophrenia was around 13 years, although over 50% did so within 2 years and over 80% of cases presented within 5 years of SIPD diagnosis. Risk factors included male gender, younger age and longer first admission. CONCLUSIONS: SIPD episodes requiring hospital admission for more than 2 weeks are more likely to be associated with later diagnosis of schizophrenia. Follow-up periods of more than 2 years are needed to detect the majority of those individuals who will ultimately develop schizophrenia.

Dissection of major depressive disorder using polygenic risk scores for schizophrenia in two independent cohorts.

Major depressive disorder (MDD) is known for its substantial clinical and suspected causal heterogeneity. It is characterized by low mood, psychomotor slowing and increased levels of the personality trait neuroticism; factors also associated with schizophrenia (SCZ). It is possible that some cases of MDD may have a substantial genetic loading for SCZ. The presence of SCZ-like MDD subgroups would be indicated by an interaction between MDD status and polygenic risk of SCZ on cognitive, personality and mood measures. Here, we hypothesized that higher SCZ polygenic risk would define larger MDD case-control differences in cognitive ability, and smaller differences in distress and neuroticism. Polygenic risk scores (PRSs) for SCZ and their association with cognitive variables, neuroticism, mood and psychological distress were estimated in a large population-based cohort (Generation Scotland: Scottish Family Health Study, GS:SFHS). The individuals were divided into those with, and without, depression (n=2587 and n=16 764, respectively) to test for the interactions between MDD status and schizophrenia risk. Replication was sought in UK Biobank (UKB; n=6049 and n=27 476 cases and controls, respectively). In both the cohorts, we found significant interactions between SCZ-PRS and MDD status for measures of psychological distress (ßGS=-0.04, PGS=0.014 and ßUKB=-0.09, PUKB⩽0.001 for GS:SFHS and UKB, respectively) and neuroticism (ßGS=-0.04, PGS=0.002 and ßUKB=-0.06, PUKB=0.023). In both the cohorts, there was a reduction of case-control differences on a background of higher genetic risk of SCZ. These findings suggest that depression on a background of high genetic risk for SCZ may show attenuated associations with distress and neuroticism. This may represent a causally distinct form of MDD more closely related to SCZ.

Social responsiveness to inanimate entities: Altered white matter in a 'social synaesthesia'.

Judgments about personalities and social traits can be made by relatively brief exposure to animate living things. Here we show that unusual architecture in the microstructure of the human brain is related to atypical mental projections of personality and social structure onto things that are neither living nor animate. Our participants experience automatic, life-long and consistent crossmodal associations between language sequences (e.g., letters, numbers and days) and complex personifications (e.g., A is a businessman; 7 a good-natured woman). Participants with this 'Ordinal Linguistic Personification' (Simner and Hubbard, 2006) which we describe here as a form of social synaesthesia, showed lower fractional anisotropy (FA) values in five clusters at whole-brain significance, compared with non-synaesthetes (in the pre-postcentral gyrus/dorsal corticospinal tract, left superior corona radiata, and the genu, body and left side of the corpus callosum). We found no regions of the brain with increased FA in synaesthetes. A number of these regions with reduced FA play a role in social responsiveness, and our study is the first to show that unusual differences in white matter microstructure in these regions is associated with compelling feelings of social cohesion and personality towards non-animate entities. We show too that altered patterns of connectivity known to typify synaesthesia are not limited to variants involving a 'merging of the senses', but also extend to what might be thought of as a cogno-social variant of synaesthesia, linking language and personality attributes in this surprising way.

Shall we really say goodbye to first rank symptoms?

BACKGROUND: First rank symptoms (FRS) of schizophrenia have been used for decades for diagnostic purposes. In the new version of the DSM-5, the American Psychiatric Association (APA) has abolished any further reference to FRS of schizophrenia and treats them like any other "criterion A" symptom (e.g. any kind of hallucination or delusion) with regard to their diagnostic implication. The ICD-10 is currently under revision and may follow suit. In this review, we discuss central points of criticism that are directed against the continuous use of first rank symptoms (FRS) to diagnose schizophrenia. METHODS: We describe the specific circumstances in which Schneider articulated his approach to schizophrenia diagnosis and discuss the relevance of his approach today. Further, we discuss anthropological and phenomenological aspects of FRS and highlight the importance of self-disorder (as part of FRS) for the diagnosis of schizophrenia. Finally, we will conclude by suggesting that the theory and rationale behind the definition of FRS is still important for psychopathological as well as neurobiological approaches today. RESULTS: Results of a pivotal meta-analysis and other studies show relatively poor sensitivity, yet relatively high specificity for FRS as diagnostic marker for schizophrenia. Several methodological issues impede a systematic assessment of the usefulness of FRS in the diagnosis of schizophrenia. However, there is good evidence that FRS may still be useful to differentiate schizophrenia from somatic causes of psychotic states. This may be particularly important in countries or situations with little access to other diagnostic tests. FRS may thus still represent a useful aid for clinicians in the diagnostic process. CONCLUSION: In conclusion, we suggest to continue a tradition of careful clinical observation and fine-grained psychopathological assessment, including a focus on symptoms regarding self-disorders, which reflects a key aspect of psychosis. We suggest that the importance of FRS may indeed be scaled down to a degree that the occurrence of a single FRS alone should not suffice to diagnose schizophrenia, but, on the other hand, absence of FRS should be regarded as a warning sign that the diagnosis of schizophrenia or schizoaffective disorder is not warranted and requires specific care to rule out other causes, particularly neurological and other somatic disorders. With respect to the current stage of the development of ICD-11, we appreciate the fact that self-disorders are explicitly mentioned (and distinguished from delusions) in the list of mandatory symptoms but still feel that delusional perceptions and complex hallucinations as defined by Schneider should be distinguished from delusions or hallucinations of "any kind". Finally, we encourage future research to explore the psychopathological context and the neurobiological correlates of self-disorders as a potential phenotypic trait marker of schizophrenia.

Prospective longitudinal voxel-based morphometry study of major depressive disorder in young individuals at high familial risk.

BACKGROUND: Previous neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development. METHOD: Unaffected individuals (16-25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls ('low risk', n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures. RESULTS: Significant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline. CONCLUSIONS: These longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.

Childhood adversity and hippocampal and amygdala volumes in a population at familial high risk of schizophrenia.

BACKGROUND: There is an established link between childhood adversity (CA) and schizophrenia. Hippocampus and amygdala abnormalities pre-date onset in those at high familial risk (fHR) of schizophrenia, but it is not clear whether these alterations are associated with CA in those at elevated risk of schizophrenia. METHODS: We examined hippocampal and amygdala volumes in those at fHR who had been referred to a social worker or the Children's Panel compared to those who had not. RESULTS: The right hippocampus and left amygdala were significantly smaller in those that had been referred to social work and Children's Panel. CONCLUSIONS: Our findings suggest that CA can influence structural changes in the brain in a cohort at fHR of schizophrenia. These findings provide further evidence that while genetic factors contribute to the structural changes found in schizophrenia, environmental factors such as CA can have a lasting impact on specific brain regions.

Longitudinal changes in hippocampal volume in the Edinburgh High Risk Study of Schizophrenia.

Schizophrenia is associated with structural brain abnormalities that are likely to be present before disease onset. It remains unclear to what extent these represent general vulnerability indicators or are associated with the developing clinical state itself. It also remains unclear whether such state or trait alterations may be evident at any given time-point, or whether they progress over time. To investigate this, structural brain scans were acquired at two time-points (mean scan-interval 1.87years) in a cohort of young unaffected individuals at high familial risk of schizophrenia (baseline, n=142; follow-up, n=64) and healthy controls (baseline, n=36; follow-up, n=18). Sub-cortical reconstructions of the hippocampus and amygdala were generated using the longitudinal pipeline available with Freesurfer. The high risk cohort was subdivided into individuals that remained well during the study (HR[well], baseline, n=68; follow-up, n=30), transient and/or partial symptoms that were insufficient to support a formal diagnosis (HR[symp], baseline, n=57; follow-up, n=26) and individuals that subsequently developed schizophrenia according to ICD-10 criteria (HR[ill], baseline, n=17; follow-up, n=8). Longitudinal change in the hippocampus and amygdala was compared, focusing first on overall differences between high-risk individuals and controls and then on sub-group differences within the high-risk cohort. We found a significantly altered developmental trajectory for all high risk individuals compared to controls, with controls showing a significant increase in hippocampal volume over time compared to those at high risk. We did not find evidence of altered longitudinal trajectories based on clinical outcome within the high risk cohort. These results suggest that an altered developmental trajectory of hippocampal volume is associated with a general familial predisposition to develop schizophrenia, as this alteration was not related to subsequent clinical outcome.

Childhood adversity and cortical thickness and surface area in a population at familial high risk of schizophrenia.

BACKGROUND: There is now a well-established link between childhood adversity (CA) and schizophrenia. Similar structural abnormalities to those found in schizophrenia including alterations in grey-matter volume have also been shown in those who experience CA. METHOD: We examined whether global estimates of cortical thickness or surface area were altered in those familial high-risk subjects who had been referred to a social worker or the Children's Panel compared to those who had not. RESULTS: We found that the cortical surface area of those who were referred to the Children's Panel was significantly smaller than those who had not been referred, but cortical thickness was not significantly altered. There was also an effect of social work referral on cortical surface area but not on thickness. CONCLUSIONS: Cortical surface area increases post-natally more than cortical thickness. Our findings suggest that CA can influence structural changes in the brain and it is likely to have a greater impact on cortical surface area than on cortical thickness.

Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression.

BACKGROUND: Neurocognitive performance deficits have been observed in mood disorder patients and their unaffected relatives and may therefore qualify as endophenotypes. However, the precise time course of neurocognitive deficits has not been studied so that it is unknown whether neurocognitive abnormalities reflect the early effects of familial vulnerability to mood disorders or if they emerge at illness onset. METHOD: A neuropsychological test battery was administered at baseline and after a 2-year follow-up interval in 111 initially unaffected young adults at high familial risk of mood disorders and 93 healthy controls (HC). During the follow-up period, 20 high-risk subjects developed major depressive disorder (HR-MDD), with the remainder remaining well (HR-well). Linear mixed-effects models were used to investigate differences and longitudinal changes in the domains of attentional processing, working memory, verbal learning and memory, and cognitive flexibility. RESULTS: Reduced long delay verbal memory and extradimensional set-shifting performance across both time points were found in the HR-well group relative to controls. The HR-MDD group displayed decreased extradimensional set-shifting abilities across both time points as compared with the HC group only. There were no significant performance differences between the two high-risk groups. CONCLUSIONS: Reduced verbal memory and cognitive flexibility are familial trait markers for vulnerability to mood disorders in individuals with a close family history of bipolar disorder. Both neurocognitive performance deficits appear to be relatively stable over a 2-year time period and do not appear to be linked to the onset of MDD. These findings support their use as stable quantitative endophenotypes for mood disorders.

Dysfunction of emotional brain systems in individuals at high risk of mood disorder with depression and predictive features prior to illness.

BACKGROUND: Abnormalities of emotion-related brain circuitry, including cortico-thalamic-limbic regions underpin core symptoms of bipolar disorder (BD) and major depressive disorder (MDD). It is unclear whether these abnormalities relate to symptoms of the disorder, are present in unaffected relatives, or whether they can predict future illness. METHOD: The Bipolar Family Study (BFS) is a prospective longitudinal study that has examined individuals at familial risk of mood disorder and healthy controls on three occasions, 2 years apart. The current study concerns imaging data from the second assessment; 51 controls and 81 high-risk (HR) individuals performing an emotional memory task. The latter group was divided into 61 HR individuals who were well, and 20 who met diagnostic criteria for MDD. At the time of the third assessment a further 11 HR individuals (from the Well group) had developed MDD. The current analyses focused on (i) differences between groups based on diagnostic status at the time of the scan, and (ii) predictors of future illness, comparing the 11 HR individuals who became unwell after the second scanning assessment to those who remained well. RESULTS: All groups demonstrated typical emotional modulation of memory and associated brain activations. For analysis (i) the HR MDD group demonstrated increased thalamic activation v. HR Well. (ii) HR Well individuals who subsequently became ill showed increased activation of thalamus, insula and anterior cingulate compared to those who remained well. CONCLUSIONS: These findings suggest evidence for specific changes related to the presence of illness and evidence that changes in brain function in cortico-thalamic-limbic regions precede clinical illness.

Structural magnetic resonance imaging markers of susceptibility and transition to schizophrenia: a review of familial and clinical high risk population studies.

There is a growing consensus that a symptomatology as complex and heterogeneous as schizophrenia is likely to be produced by widespread perturbations of brain structure, as opposed to isolated deficits in specific brain regions. Structural brain-imaging studies have shown that several features of the brain, such as grey matter, white matter integrity and the morphology of the cortex differ in individuals at high risk of the disorder compared to controls, but to a lesser extent than in patients, suggesting that structural abnormalities may form markers of vulnerability to the disorder. Research has had some success in delineating abnormalities specific to those individuals that transition to psychosis, compared to those at high risk that do not, suggesting that a general risk for the disorder can be distinguished from alterations specific to frank psychosis. In this paper, we review cross-sectional and longitudinal studies of individuals at familial or clinical high risk of the disorder. We conclude that the search for reliable markers of schizophrenia is likely to be enhanced by methods which amalgamate structural neuroimaging data into a coherent framework that takes into account the widespread distribution of brain alterations, and relates this to leading hypotheses of schizophrenia.