NeuroGrid (and maybe even NeuroPsyGrid)

Stephen Lawrie

Edinburgh

A collaboration between clinical, imaging and e-scientists to create a Grid-based network of neuroimaging centres and a neuroimaging tool-kit, focused on three clinical exemplars: dementia, stroke and psychosis.

Sharing data, experience and expertise will facilitate the archiving, curation, retrieval and analysis of imaging data from multiple sites & enable large clinical studies.

        

 

The main issues in (UK) clinical brain imaging studies

• Potential:- demonstrate effects of risk factors, including genes; - early diagnosis; - treatment response / prognosis prediction;- treatment effect monitoring; - biomarker for novel drug development

• Concerns:- lack of standardisation across scanners and even in basic approach

to e.g. ‘connectivity’; - lack of normative data reference points for relevant age ranges; - safe data storage; - expense; - constantly developing technology

Methodological issues in multi-centre brain imaging

• Multiple influences on brain structure and function

• Scanner, servicing and session effects (see e.g. McGonigle 2000; Marshall 2004)

• Sequences for s&fMRI and tasks for fMRI

• Signal and spatial inhomogeneities

M1

. . .

11 3322 33

Single Subject, 33 sessions over 2 month period, finger-tapping task

M1 SMA

Neurogrid – psychosis exemplar1. Database and ontology, building on EHRS data set (0.5WTE)2. Scanner harmonisation issues, focussing on EHRS use of two machines

(1WTE)3. Combined analysis of psychosis data sets from Oxford & Edinburgh, focussing

on sex / assymmetry (1 WTE)

Registration and Partial Volume Metric for Multi-Center sMRI Scanner Harmonization Moorhead TWJ, Job DE, Gountouna V-E, Johnstone EC, Lawrie SM. HBM2005. NeuroImage 2005

Signal-to-Noise (SNR) and Contrast-to-Noise (CNR) metrics in longitudinal and multicenter MRI studies Gountouna VE, Moorhead TWJ, Job DE, Johnstone EC, Lawrie SM. HBM2005 NeuroImage 2005

Entropy as a measure of scanner and sequences change. Dominic E. Job, T. William J. Moorhead, Eve C. Johnstone, Stephen M. Lawrie. NeuroImage 2006 Volume 31, Supplement 1 Annual Meeting Human Brain Mapping, June 11-15 Florence Italy

Test-retest reliability of the Hayling sentence completion task: assessment for multicenter fMRI using voxel-wise Intraclass Correlation Coefficients (ICCs). Viktoria-Eleni Gountouna, Heather Whalley, T.William Moorhead, Dominic Job, David McGonigle, Eve Johnstone, Stephen Lawrie. HBM2006 NeuroImage 2006 Volume 31,

Methodological (part) solutions‘Harmonisation’ metrics (Gountouna 2005)

Grey Matter Signal to Noise Ratio for repeated visits of 6 subjects.

Methodological (part) solutions‘Harmonisation’ methods (Moorhead 2005)

• Registration:

Default SPM99 pre-processingMetric_reg=0.73

Amended pre-processingStripped Brain Optimised

Metric_reg=0.96

Edinburgh High Risk Study

• Baseline measures- genetic liability- dermatoglyphics- obstetric complications- minor physical anomalies /

neurological ‘soft signs’- CBCL- SIS- RISC

Also took blood for genes at the end of the study

• Repeated measures- substance use- life events- neuropsychology- structural MRI- functional MRI- PSE- PANSS

•A prospective study of ~200 subjects at high risk (HR) of Schizophrenia for genetic reasons i.e. initially healthy subjects aged 16-25 who had two or more close relatives with schizophrenia. Compared to first-episode cases and healthy controls on...

Edinburgh High Risk Study (EHRS)Main Results 1995-2004

Isolated and/or transient symptoms very common

Baseline risk of psychosis 20 / 162 (~12.5%)Risk in HR+ i.e. those with symptoms 18 / 80 (25%)

Most measures differed significantly between those at high risk and controls, typically with the sub-group pattern:

Con </> HR- </> HR+ <</>> HRill

Within high risk subjects, however, only AVLT, CBCL, RISC/SIS and some imaging indices predicted schizophrenia

(Johnstone et al 2005 Br J Psych)

EHRS Baseline predictors

0

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AHC - L AHC - R 3V Thal - L Thal - R

FES

HR

CON

fMRI – HSCT (parametric contrast): AHC/STG

a.) R ahc/stg; b.) R lingual gyrus; c.) L ahc/stg; d.) L cerebellum

* * *

* * *

a

b

d

*

c

*

42314132

4213

4312

Neuro-anatomy: AMYG-HIPP vol & Gyrification Index R PFC

Neuro-psychology: NART IQ, WAIS-R & VRs, RBMT story & especially AVLT 1-5 total score

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CONTROL HR- HR+ ILL

No.

item

s rec

alle

d

EHRS changes towards psychosis

GM densityReducesIn RightUncus,Fusiform &Cerebellum2.5 yrs on avge before Dx

Cannabis use and major life events are associated with psychotic symptoms and (weakly) with psychosis 2-4 yrs later. 0-2 yrs pre-diagnosis, anxiety/depression fall,typical psychotic symptoms supervene and GM density falls. But, no apparent changes in neuropsychological test scores over this time.

-2.5

-2

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-1

-0.5

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Onentry

2ndtime

onfalling

ill

depression

hallucinationsand control

delusions

mania

oddness

anxiety

Mean scores on the six PSE principal components on three occasions of 8 HR subjects who fell ill (relative to NP chronics)

Neuregulin in the EHRS• Law et al (2006) reported that the risk allele

of SNP8NRG243177, part of the original disease-associated haplotype, alters the binding sites for three transcription factors in a promoter region of NRG1 – increasing expression of the type IV transcript

• We found a highly significant effect of SNP8NRG243177 genotype on the development of psychotic symptoms in the EHRS cohort with 100% of individuals homozygous for the risk allele (T/T) developing psychotic symptoms at some time

• Subjects with the risk (T/T) genotype showed significantly decreased activation of right medial PFC and right posterior medial temporal gyrus in the contrast of sentence completion versus rest

• Using the National Adult Reading Test (NART), a measure of pre-morbid IQ, we found a significant effect of genotype on IQ which derived from the T/T group having a significantly decreased IQ

b

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C/C C/T T/T

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e

C/C C/T T/T

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b

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C/C C/T T/T

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c

e

C/C C/T T/T

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Hall et al, 2006Nature Neuroscience

        

 

A health informatics project which builds on the DoH funded UK MHRN. Psygrid aims to develop the MHRN into a functioning “e-community” and build a secure electronic database to hold anonymised clinical data about people presenting to NHS services with first episode psychosis.

Towards multi-centre clinical, genetic and brain imaging studies of people at high risk of psychosis:

MRC Collaboration grant application

NeuroPsyGrid: towards an ontologyand multi-centre brain imaging in early psychosis

 

     

  

Multi-centre organisation

• Scotland

- CaliBrain: multicentre s&fMRI pilot

- SHEFC Pooling for Imaging Project

• UK

- MRC funded NeuroGrid & PsyGrid

• Europe…

• US …

BIRN

• For harmonisation, BIRN have shown that an image/method for gradient non-linearity correction and possibly a phantom for other coil inhomogeneity corrections are very useful.

Neuro/PsyGrid and BIRN

• Shared interests in scanner (clinical and genetic) harmonisation and shared database, metadata and ontology for psychosis

• During discussions about NPG we thought of looking at: - a collaborative ontology; - variations across sites in clinical and biological data acquisition; - using BIRN Bio-Mediator; - 4D spatio-temporal analyses of imaging (fMRI) and genetic data; - joint work on NeuroFMA; - a requirements analysis for NPG-BIRN harmonisation.

Concluding remarks

If brain imaging is to impact on clinical practice in psychiatry, as we know it could, we urgently require:

- Multi-centre clinical studies of people in early stages of major psychiatric disorders

- Standardisation of scanners and imaging acquisition and processing techniques across mental health research networks

- Studies of normal neuro-development across age ranges of relevance to (adult) psychiatric disorders

These would benefit, possibly even depend upon, on e-science approaches to collecting, storing and accessing data.