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Articles by H. J Moller
Total Records ( 3 ) for H. J Moller
  N Koutsouleris , E. M Meisenzahl , C Davatzikos , R Bottlender , T Frodl , J Scheuerecker , G Schmitt , T Zetzsche , P Decker , M Reiser , H. J Moller and C. Gaser
 

Context  Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance imaging–based diagnostic classification of neuropsychiatric patient populations.

Objective  To determine whether multivariate neuroanatomical pattern classification facilitates identification of individuals in different at-risk mental states (ARMS) of psychosis and enables the prediction of disease transition at the individual level.

Design  Multivariate neuroanatomical pattern classification was performed on the structural magnetic resonance imaging data of individuals in early or late ARMS vs healthy controls (HCs). The predictive power of the method was then evaluated by categorizing the baseline imaging data of individuals with transition to psychosis vs those without transition vs HCs after 4 years of clinical follow-up. Classification generalizability was estimated by cross-validation and by categorizing an independent cohort of 45 new HCs.

Setting  Departments of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany.

Participants  The first classification analysis included 20 early and 25 late at-risk individuals and 25 matched HCs. The second analysis consisted of 15 individuals with transition, 18 without transition, and 17 matched HCs.

Main Outcome Measures  Specificity, sensitivity, and accuracy of classification.

Results  The 3-group, cross-validated classification accuracies of the first analysis were 86% (HCs vs the rest), 91% (early at-risk individuals vs the rest), and 86% (late at-risk individuals vs the rest). The accuracies in the second analysis were 90% (HCs vs the rest), 88% (individuals with transition vs the rest), and 86% (individuals without transition vs the rest). Independent HCs were correctly classified in 96% (first analysis) and 93% (second analysis) of cases.

Conclusions  Different ARMSs and their clinical outcomes may be reliably identified on an individual basis by assessing patterns of whole-brain neuroanatomical abnormalities. These patterns may serve as valuable biomarkers for the clinician to guide early detection in the prodromal phase of psychosis.

  G Donohoe , J Walters , D. W Morris , E. M Quinn , R Judge , N Norton , I Giegling , A. M Hartmann , H. J Moller , P Muglia , H Williams , V Moskvina , R Peel , T O'Donoghue , M. J Owen , M. C O'Donovan , M Gill , D Rujescu and A. Corvin
 

Context  Human and animal studies have implicated the gene NOS1 in both cognition and schizophrenia susceptibility.

Objective  To investigate whether a potential schizophrenia risk single-nucleotide polymorphism (rs6490121) identified in a recent genome-wide association study negatively influences cognition in patients with schizophrenia and healthy control subjects.

Design  A comparison of both cases and controls grouped according to NOS1 genotype (GG vs AG vs AA) on selected measures of cognition in 2 independent samples. We tested for association between NOS1 rs6490121 and cognitive functions known to be impaired in schizophrenia (IQ, episodic memory, working memory, and attentional control) in an Irish sample. We then sought to replicate the significant results in a German sample.

Setting  Unrelated patients from general adult psychiatric inpatient and outpatient services and unrelated healthy volunteers from the general population were ascertained.

Participants  Patients with DSM-IV–diagnosed schizophrenia and healthy control subjects from independent samples of Irish (cases, n = 349; controls, n = 230) and German (cases, n = 232; controls, n = 1344) nationality.

Results  A main effect of NOS1 genotype on verbal IQ and working memory was observed in the Irish sample where the homozygous carriers of the schizophrenia risk G allele performed poorly compared with the other genotype groups. These findings were replicated in the German sample, again with the GG genotype carriers performing below other genotype groups. Post hoc analysis of additional IQ measures (full-scale and performance IQ) in the German sample revealed that NOS1 GG carriers underperformed on these measures also.

Conclusions  NOS1 is associated with clinically significant variation in cognition. Whether this is a mechanism by which schizophrenia risk is increased (eg, via an influence on cognitive reserve) is yet to be confirmed.

  N Koutsouleris , G. J.E Schmitt , C Gaser , R Bottlender , J Scheuerecker , P McGuire , B Burgermeister , C Born , M Reiser , H. J Moller and E. M. Meisenzahl
 

Background

Structural brain abnormalities have been described in individuals with an at-risk mental state for psychosis. However, the neuroanatomical underpinnings of the early and late at-risk mental state relative to clinical outcome remain unclear.

Aims

To investigate grey matter volume abnormalities in participants in a putatively early or late at-risk mental state relative to their prospective clinical outcome.

Method

Voxel-based morphometry of magnetic resonance imaging data from 20 people with a putatively early at-risk mental state (ARMS–E group) and 26 people with a late at-risk mental state (ARMS–L group) as well as from 15 participants with at-risk mental states with subsequent disease transition (ARMS–T group) and 18 participants without subsequent disease transition (ARMS–NT group) were compared with 75 healthy volunteers.

Results

Compared with healthy controls, ARMS–L participants had grey matter volume losses in frontotemporolimbic structures. Participants in the ARMS–E group showed bilateral temporolimbic alterations and subtle prefrontal abnormalities. Participants in the ARMS–T group had prefrontal alterations relative to those in the ARMS–NT group and in the healthy controls that overlapped with the findings in the ARMS–L group.

Conclusions

Brain alterations associated with the early at-risk mental state may relate to an elevated susceptibility to psychosis, whereas alterations underlying the late at-risk mental state may indicate a subsequent transition to psychosis.

 
 
 
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