Letter to the Editor: Neuropsychological subgroups are evident in both mood and psychosis spectrum disorders

Lee, R. S. C.; Hickie, Ian B.; Hermens, Daniel F.

doi:10.1017/s0033291714001019

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…An alternative approach to interrogate the longitudinal course of neuropsychological functioning was to use a data-driven cluster analysis to help identify potential discrete cognitive pathways obscured by simple diagnostic aggregation. 67 Three distinct and reliable neuropsychological subgroups emerged, representing predominantly psychomotor slowing and improvements in sustained attention and verbal memory. Diagnostic makeup did not differ between clusters, underscoring the notion that the course of neuropsychological functioning does not appear to be diagnosis specific.…”

Section: Discussionmentioning

confidence: 99%

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Neuropsychological and functional outcomes in recent-onset major depression, bipolar disorder and schizophrenia-spectrum disorders: a longitudinal cohort study

et al. 2015

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Functional disability is the lead contributor to burden of mental illness. Cognitive deficits frequently limit functional recovery, although whether changes in cognition and disability are longitudinally associated in recent-onset individuals remains unclear. Using a prospective, cohort design, 311 patients were recruited and assessed at baseline. One hundred and sixty-seven patients met eligibility criteria (M=21.5 years old, s.d.=4.8) and returned for follow-up (M=20.6 months later, s.d.=7.8). Two-hundred and thirty participants were included in the final analysis, comprising clinically stable patients with major depression (n=71), bipolar disorder (BD; n=61), schizophrenia-spectrum disorders (n=35) and 63 healthy controls. Neuropsychological functioning and self-rated functional disability were examined using mixed-design, repeated-measures analysis, across diagnoses and cognitive clusters, covarying for relevant confounds. Clinical, neuropsychological and functional changes did not differ between diagnoses (all P>0.05). Three reliable neuropsychological subgroups emerged through cluster analysis, characterized by psychomotor slowing, improved sustained attention, and improved verbal memory. Controlling for diagnosis and changes in residual symptoms, clusters with improved neuropsychological functioning observed greater reductions in functional disability than the psychomotor slowing cluster, which instead demonstrated a worsening in disability (P<0.01). Improved sustained attention was independently associated with greater likelihood of follow-up employment (P<0.01). Diagnosis of BD uniquely predicted both follow-up employment and independent living. Neuropsychological course appears to be independently predictive of subjective and objective functional outcomes. Importantly, cognitive phenotypes may reflect distinct pathophysiologies shared across major psychiatric conditions, and be ideal targets for personalized early intervention.

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Section: Discussionmentioning

confidence: 99%

“… 73 By comparison, ‘dimensional psychiatry' using cognitive phenotypes, as exercised in the current study, is better equipped to isolate independent and internally consistent subgroups across diagnostic boundaries to better elucidate how these contribute to disease characteristics and progression. 67 , 74 …”

Section: Discussionmentioning

confidence: 99%

Neuropsychological and functional outcomes in recent-onset major depression, bipolar disorder and schizophrenia-spectrum disorders: a longitudinal cohort study

et al. 2015

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“…For example, a recent meta-analysis summarizing 42 studies observed significant impairments in BD patients across multiple domains such as attention, working memory, verbal/non-verbal memory, visuospatial function, psychomotor speed, language and executive function (Kurtz and Gerraty, 2009). Most recently, several studies have successfully identified unique neurocognitive subgroups using data-driven machine learning algorithms (Brodersen et al, 2014; Burdick et al, 2014; Fair et al, 2012; Heinrichs and Awad, 1993; LEE et al, 2014). Distinctively, a recent longitudinal study reported a data-driven approach able to identify neurocognition subgroups which proved to be useful in predicting longitudinal functional outcomes (Hermens et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning

Mwangi

Bauer

et al. 2017

NeuroImage

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Diagnosis, clinical management and research of psychiatric disorders remains subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and ‘skeletonized’ white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The ‘skeletonized’ white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity = 92%, specificity = 97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65 % accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; affective go/no-go (AGN), Cambridge gambling task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an individual subject level. We suggest a strong clinical utility of the proposed approach in defining and validating biologically meaningful and less heterogenous clinical sub-phenotypes of major psychiatric disorders.

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“…The current study sought to determine the cognitive and clinical factors that underpin NEET status in a transdiagnostic, prospective cohort of young people (aged 15–25 years) with a mental illness. As endorsed by the National Institute of Mental Health Research Domain Criteria initiative in order to advance psychiatric research (Casey et al 2013), a transdiagnostic approach is ideal in that it permits the identification of cognitive and clinical factors that cut across diagnostic boundaries (Lee et al 2014 b ), allows for greater statistical variability to detect more subtle effects, and can provide a unifying framework in which to understand education, employment and training outcomes. The validity of diagnostically constrained approaches is also potentially confounded by significant diagnostic instability among young people with a mental illness (Bukh et al 2016; Tohen et al 2016).…”

Section: Introductionmentioning

confidence: 99%

A transdiagnostic study of education, employment, and training outcomes in young people with mental illness

et al. 2017

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Disengagement with education, employment or training (i.e. being NEET) was reported in about one in four members of this cohort. The initial level of cognitive functioning was the strongest determinant of future NEET status, whereas being academically or vocationally engaged had an impact on future negative symptomatology. If replicated, these findings support the need to develop early interventions that target cognitive phenotypes transdiagnostically.

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Letter to the Editor: Neuropsychological subgroups are evident in both mood and psychosis spectrum disorders

Cited by 4 publications

References 4 publications

Neuropsychological and functional outcomes in recent-onset major depression, bipolar disorder and schizophrenia-spectrum disorders: a longitudinal cohort study

Neuropsychological and functional outcomes in recent-onset major depression, bipolar disorder and schizophrenia-spectrum disorders: a longitudinal cohort study

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning

A transdiagnostic study of education, employment, and training outcomes in young people with mental illness

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