Data Driven Neuropsychiatric Profiling

Qualifying Exam PresentationVanessa SochatAugust 19, 2013

Why do we need a model of disorder?Treatment hinges on diagnostic subtypes

patient assessment

autismADHDbipolar

schizophrenia

diagnosis of

bipolar

treatment

education

finances

research

?diagnosi

s of bipolar

treatment

education

finances

research

The Diagnostic and Statistical Manual of Mental Disorder (DSM)

“loss of interest”“depressed mood”“insomnia”“excessive sleeping”

depression

anxiety

PTSDdepressio

n

autismADHD

bipolar

Autism Spectrum Disorder (ASD):A childhood development disorder

• Afflicts 1 in 100 children • Economic burden of $126 billion annually• Social, communication, and cognitive deficits,

repetitive behaviors and interests

data-driven subtyping of autism spectrum disorders for early diagnosis and tailored, effective treatmentAutism

Asperger’s

PDD-NOS

DSM IV

Autism

DSM V

Unsolved Problem:

data-driven subtyping of neuropsychiatric disorder for early diagnosis and tailored, effective treatment

How might we model disorder?

Genetics

Behavior

Neuroimaging

combinations of genes small effects high heritability a marker of risk, not certainty

biased and unreliable

brain phenotype to define disorder?

Goal

A new model of neuropsychiatric disorder based on patterns of local brain structure

neuropsychiatric profile

brain phenotyp

e

cognitive phenotyp

e

Hypothesis

Mining imaging data will define clinically-useful disease subtypes better than currently possible

using DSM alone.

Aim1: to develop a computational representation of brain phenotype, and use it to define subtypes of neurological disorder

Aim 2: to create a structured normalized representation of cognitive phenotype as a new standard for evaluationAim 3: to evaluate by reproducing known brain-behavioral relationships, and finding subtypes of autism

Specific Aims

Aim1: to develop a computational representation of brain phenotype, and use it to define subtypes of neurological disorder

brain phenotyp

e

cognitive phenotyp

e

DISORDER HEALTHYCONTROL

Start with groupsCollect dataFind differencesInconsistent results

How do we find brain-based differences?

1234

Assumptions about the brain

Assumptions about the groups

How do we find brain-based differences?

make assumptions about spatial meaningfulness voxel-wise features prime to overfitting

diagnostic categories represent homogenous syndromes what about heterogeneity of the healthy controls?

learn groups from the data

make no assumptions about spatial location strive for an abstraction of structure

Collect dataLocal brain phenotypeDefine groupsFind Differences

MRI

How should we find these differences?

1234

1

GROUP A GROUP B4

2

3

groups == proposed subtypes

Aim 2: to create a structured normalized representation of cognitive phenotype as a new standard for evaluation

brain phenotyp

e

cognitive phenotyp

e

BEHAVIORAL & COGNITIVE METRICS

Structure and normalize dataLink to specific traitsCreate cognitive phenotypes

Assessment metrics reflect human traits

123

Assessment 1

Q1…Q10 “Anxiety”

Assessment 2

Q30…Q40 “Anxiety”

2

IQ

anxiety, attention …

T1 T2 T3 …. TN

1

3cognitive phenotyp

e

Aim 3: to define and evaluate subtypes of autism spectrum disorderAim 3: to evaluate by reproducing known brain-behavioral relationships, and finding subtypes of autism

brain phenotyp

e

cognitive phenotyp

e

C1 C2 C3 …. CN

Evaluation of Brain Phenotype:Reproduce known Brain-Behavior Relationships

C1 C2 C3 …. CNT1 T2 T3 …. TN

0.20.50.7

2.9 0.20.1 1.97.2 2.1

Person APerson BPerson C

X1 X2 Y

ClusteringASD

CONTROL

Evaluation of Method:Show that we capture current gold standard

my groupsDSM

Evaluation of Method:Show greater homogeneity in our groups

different

similar

ASD CONTROL

GROUP A GROUP B

my groups

DSM

Evaluation of Method:Show more robust group differences

significant differences?

vs

vs

Summary:Data-driven neuropsychiatric profiling

patient

brain phenotype

MRI diagnosis

treatment

education

finances

research

Future Vision:Extension to other disorders and data types

brain phenotyp

e

AutismWhite MatterADHDBipolar

Gray MatterGene Expression

EHRdoctor visitsi-phone app

geneticmolecularclinical

cognitive phenotyp

e

Informatics Contribution

• Tools to extend Big Data paradigms to neuroscience

• Data-driven model of neuropsychatric profile• Brain phenotype• Cognitive phenotype

• Methods to define subtypes of disorder

Biological Contributions

• Discovery of biomarkers of disorder• Definition of disorder subtypes• Enabling personalized treatment

Acknowledgements

Advisors and PanelDaniel RubinRuss AltmanMark MusenAntonio Hardan

ColleaguesKaustubh SupekarFeature GroupThe MIND Institute

Support StaffJohn DiMarioMary Jeanne & Nancy

FundingMicrosoft ResearchSGF and NSF

Friends and Fellow BMIFrancisco GimenezRebecca SawyerLuke Yancy Jr.Beth PerchaKatie PlaneyTiffany Ting LuLinda SzaboDiego MunozJonathan MortensenThe M&Ms previously known as first years

Thank you!

2

anxiety, attention …

C1 C2 C3 …. CNAssessment X

Subscale Y “Anxiety”

Assessment A

Subscale B “Anxiety”

Cognitive Phenotypes for N = 26

…are meaningful about groups

(OBSERVED DATA)

(MIXING MATRIX) (ORIGINAL DATA)

X = A SX

n x m n x n n x m

fMRI data

time

time

space spacecomponents

components

spatial maps

How do we discover local brain structure?Matrix Decomposition

n x m n x n n x m

How do we discover local brain structure?Matrix Decomposition

sMRI data

brains

brains

components

components

space space

spatial maps

2.9 0.2 1.9brain

phenotype

Clustering GROUP 1

GROUP 2

How do we define subtypes?

GROUP 3GROUP 4

BEHAVIORAL & COGNITIVE METRICS

1. Collect data2. Covariate or control3. Data not used

How do we use assessment metrics?

123

A Mapping from Assessments to TraitsMapping Assessments to TraitsThe Cognitive Atlas

Mapping Assessments to TraitsThe Cognitive Atlas

Mapping Assessments to TraitsThe Cognitive Atlas

Representation Based on TraitsThe Cognitive Phenotype

1 32

Assessment X Subscale X “Anxiety” .04 Subscale Y “Attention” .90

Normalized Score =Total - Raw

Total

3

Representation Based on TraitsThe Cognitive Phenotype

C1 C2 C3 …. CN

Find all assessments for person LOUIE…

4

Find me a cohort defined by anxiety > .5

Are anxious people also impulsive?

brain phenotyp

e