Gene Profiling: Clinical Application in Infectious Diseases

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Gene Profiling: Clinical Application in Infectious Diseases

Octavio Ramilo

OR April 2007

1. Instead of traditional pathogen based diagnosis

2. Analysis of host response

ALTERNATIVE TO TRADITIONAL MICROBIOLOGIC DIAGNOSIS

Microbe CMicrobe A Microbe B

Immune Response A

Pattern RecognitionReceptors

Immune Response B

Immune Response C

DIFFERENT PATHOGENS STIMULATE DISTINCT HOST IMMUNE RESPONSES

DC DC DC

TRANSCRIPTIONAL PROFILES IN DISEASE PATHOGENESIS

Patient Genotype(DNA)

Expression Profiles(mRNA)

Clinical Disease

Environment

HostFactors

Other unknownfactors

MICROBE

1. S. aureus infections

2. Febrile infants

3. Respiratory infections

GENE PROFILING CLINICAL APPLICATIONS

Staphylococcus aureus

• Gram-positive spherical bacteria• Skin / Nose Commensal• Causes a range of illnesses

– Skin Abscesses– Bacteremia– Osteoarticular infections– Pneumonia– Death

• Caused >18,000 deaths in the U.S. in 2005;• Cost $14 billion to hospitals in extended length of stay

Study Design

Tempus Tubes

DC

B PC

TM

NK

Er

N E B

RNA Extraction

Globin Reduction

Amplification and cRNA Synthesis

Hybridization and Scan

99 patients vs. 44 healthy controls split into independent training and test sets

Age range: 7 years (0.06 – 17)

Average draw day: 5 days (1 – 35)

Treatment: antibiotics, no steroids

No co-infection

Patient Demographics and Lab Characteristics

Clinical Presentation Classification

Characterization of 63 Cultured Isolates

Toxin Profiling Reveals High Homogeneity Among Bacterial Isolates

1,458 Transcripts Differentiate Patients with S. aureus Infection from Healthy Controls

Student T-Test, p<0.01, Benjamini-Hochberg Correction, 1.25 fold changeHierarchical clustering (Spearman correlation)

Increased Inflammatory Response and Decreased Adaptive Immunity in Patients with S. aureus Infection

Myeloid LineageNeutrophilsInflammationCoagulationHematopoiesis

T CellsB CellsCytotoxicity / NK CellsProtein Synthesis

Increased Numbers of Circulating Inflammatory Cells and APCs during S. aureus Infection

From Hospital WBC From Flow Cytometry on PBMC

13 Healthy Controls23 PatientsHealthy Controls S. aureus patients

*

*

*

*

Group Signature vs. Individual Signature

S. aureus patient cohort signature

Individual Signature

Hospitalization StageBacterial Strain

Disease SeverityClinical Presentation

Treatment

Correlating Clinical Heterogeneity with the Molecular Signature

Signature Clinic

Molecular signatures derived for each patient

Patients are clustered based on signature

X clusters are identified

Distribution of clinical observations is studied for each cluster

Group patients based on clinical observations

Distribution of signatures studied for each group

Clinic Signature

The Draw Index as a Measure of Progression to Recovery

16

3225

26

Admission Draw Discharge

Hospitalization Duration

Time to Draw

Draw Index =Time to Draw

Hospitalization Duration

0 <= Draw Index <= 1

99 Patients

Can we measure disease activity at the molecular level ?

Molecular Distance to Health (MDTH): Metric that summarizes in a single score all

the information derived from whole genome transcriptional analysis in a way that can be

applied in the clinical context

The Transcriptional Signature of S. aureus Infection is Heterogeneous

99 Patients

Cluster C1 Displays Increased Inflammation Clinically

Clinical Presentations Vary Between Clusters

+ no correlation between clusters and clinical isolate characteristics

MDTH Positively Correlates with Inflammation Markers

Correlating Clinical Heterogeneity with the Molecular Signature

Signature Clinic

Molecular signatures derived for each patient

Patients are clustered based on signature

X clusters are identified

Distribution of clinical observations is studied for each cluster

Group patients based on clinical observations

Distribution of signatures studied for each group

Clinic Signature

The MDTH Decreases as Patients Get Closer to Discharge

MDTH Increases With Infection Dissemination

MDTH Varies With Clinical Presentation

Patients With Osteoarticular Infection Display Increased Expression of 14 Modules

Patients With Osteoarticular Infection Display Increased Coagulation and Erythropoiesis Signatures

Question:

Can we differentiate between patients presenting with acute febrile syndromes?

MODULAR ANALYSIS DIAGNOSIS: DISEASE FINGERPRINTS

Chaussabel, et al Immunity 2008 29(1): 150-64; Pankla R et al Genome Biol 2009 10(11), Ardura, et al . Plos One 2009; 4(5), O’Garra 2010 Nature 2010; 466: 973-7

Biosignatures for Diagnosis of Febrile Infants

Pediatric Emergency Care and Research Network (PECARN)

SBI+

SBI-

WHOLE BLOOD MODULAR ANALYSIS

OR April 2007

Question:

Can we differentiate between patients presenting with similar clinical findings?

IMPACT OF RESPIRATORY INFECTIONS IN IMPACT OF RESPIRATORY INFECTIONS IN CHILDHOODCHILDHOOD

First cause of children morbidity & mortality in the world Viral respiratory infections are responsible for a large

number of visits to the pediatrician, to the ER and hospital admissions

First cause of asthma attacks Important morbidity in immunocompromised patients

and children with chronic illnesses (i.e., BPD, congenital heart disease)

OR April 2007

ANALYSIS OF PNEUMONIA(LOWER RESPIRATORY TRACT INFECTION)

Genes used to classify different patient groups (n=137)

All patients who presented with pneumonia (n=30) Healthy controls (n=8) Cluster analysis

OR April 2007

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.2

1.5

2.0

2.5

3.0

4.0

5.04.0

3.0

2.5

2.0

1.5

1.2

1.0

0.8

0.7

0.6

0.5

0.4

0.3

S.pneumoniae

S.aureus

Influenza A

Healthy

38 Samples

13

7 G

en

es

Selected Gene Tree: Respiratory INF_FLU_Staph_Strep_38 (137 Classification Genes)Selected Condition Tree:Respiratory INF_FLU_Staph_Strep_38 (137 Classification Genes)Branch color parameter::

Colored by: Respiratory INF_FLU_Staph_Strep_38 (Default Interpretation)Gene List: Classification Genes 137 (137)

Respiratory INF_FLU_St...

:

*

CLUSTER ANALYSIS IN PATIENTS WITH PNEUMONIA

CLUSTER ANALYSIS IN PATIENTS WITH PNEUMONIA

Interferon Genes Neutrophil

Genes

Mixed Signature

S. pneumoniaeS. aureusInfluenza AHealthy

And what about children….Can we apply this technology to patients with Can we apply this technology to patients with

respiratory viral infections?respiratory viral infections?

And what about children….Can we apply this technology to patients with Can we apply this technology to patients with

respiratory viral infections?respiratory viral infections?

193 samples

16,4

69 g

enes

HEALTHY (n=40) RSV (n=91) Influenza (n=32) HRV (n=30)

VIRAL RESPIRATORY SIGNATURE IN CHILDRENUNSUPERVISED ANALYSIS

QC: PAL2_2xUDAL10%: 16, 469

Can we measure disease activity in pathogens that do not cause blood

stream infections?

Molecular Distance to Health (MDTH):

HEALTHY (n=40)

193 samples

16,4

69 g

enes

RSV (n=91) Influenza (n=32) HRV (n=30)

VIRAL RESPIRATORY SIGNATURE IN CHILDREN

Ctrl (n=40) RSV (n=91) Flu (n=32) RV (n=30)

Wei

ghte

d M

DTH

Sco

res

QC: PAL2_2xUDAL10%: 16, 469

Disease Severity in Children with RSV vs RV Bronchiolitis

Kruskal-Wallis (median 10-90 percentile)Garcia C,….Mejias A. IDSA 2010

p<0.01Disease Severity Score* •% Sp O2

•Respiratory rate•Retractions•Wheezing•General Condition

Dis

ease

Severi

ty S

core

n=128 n=108 n=26

* Wang et al (modified). Am Rev Respir Dis 1992;145:106

RV RSV Co-infx

MDTH Scores Correlates with RSV Disease Severity

Spearman Correlation

r = 0.5p = 0.002

Clinical Disease Severity Score*

MD

TH S

core

s

Length of Hospitalization

r = 0.6p < 0.01

Disease Severity Score: % Sp O2; respiratory rate; IVF; retractions; auscultation

OR April 2007

1. Pathogens induce distinct transcriptional profiles

2. Profiles can be used to identify common features and also differences between patients

3. Modular analysis: disease fingerprints useful for differential diagnosis

4. New perspective on disease pathogenesis

5. New tool for assessing disease severity

SUMMARY

Acknowledgements

Asuncion MejíasMonica ArduraCarla GarciaSusana Chavez-BuenoAna GomezEvelyn TorresJuanita LozanoAlejandro Jordan Juan P. TorresBuddy Creech (VUMC)Prashant Mahajan

Romain BanchereauDamien ChaussabelBlerta DimoHasan JafriMichael ChangJacques BanchereauDerek BlankershipCasey GlaserPhuong NguyenNate Kupperman Pablo Sanchez

NIH (NIAID), Medimmune, PECARN, HRSA EMSC, Dana Foundation

UT Southwestern Medical Center Baylor Institute for Immunology Research