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Harvard Medical School
Massachusetts Institute of Technology
Inferring Nonstationary Gene Networks
from Temporal Gene Expression Data
Hsun-Hsien Chang1, Jonathan J. Smith2, Marco F. Ramoni1
1Children’s
Hospital Informatics Program,
Harvard-MIT Division of Health Sciences and Technology,
Harvard Medical School
2Department of Mathematics,
Massachusetts Institute of Technology
IEEE Workshop on Signal Processing Systems
October 7, 2010
1
Harvard Medical School
Massachusetts Institute of Technology
Background
• Genetic information flows
from DNA to RNA through
transcription.
• Gene expression is the measure
of RNA abundance in cells,
revealing the gene activities.
• Modern microarray technologies
are able to assess expression of
50K genes in parallel.
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Massachusetts Institute of Technology
Clinical Applications
Multiple patients in
distinct biological
conditions.
...
gene
expre.
T0
T1
T2
T3
T4
T5
• Thanks to cost down, more samples can be collected
in a single study. A new clinical application:
– Monitor time-series gene expression in response to drugs,
treatments, vaccines, virus infection, etc.
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Massachusetts Institute of Technology
Time-Series Gene Expression Analysis
• Since genes interact each other in cells, an intriguing
analysis is to infer gene networks:
– Detailed models (e.g., differential equations).
– Abstract models
(e.g., Boolean
networks).
gene on
gene off
– Probabilistic graphical models (e.g., dynamic
Bayesian networks).
• Do not require densely sampled data.
• Model expression levels by random variables to
handle noisy expression measurements and
biological variability.
• Utilize the inferred networks to make prediction.
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Massachusetts Institute of Technology
Data Representation by Bayesian Networks
• Bayesian networks are directed acyclic graphs where:
– Nodes correspond to random variables (i.e.,
expressions of genes, clinical variables).
– Directed arcs encode conditional
probabilities of the target (child) nodes on
the source (parent) nodes.
A
C
B
D
E
• Dynamic Bayesian networks with arcs indicating
temporal dependency.
– Example: variables X and Y
at time T modulate variable
Z at time T+1.
– The network model
can serve as a
prediction tool.
XT
ZT+1
YT
XT
given
ZT+1
predicted
YT
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Massachusetts Institute of Technology
Network Inference Engine
Clinical
variable
VT
VT+1
AT
AT+1
BT
BT+1
CT
CT+1
NT
NT+1
Genes
• First-order Markov process:
data at time T+1 depends
only on the preceding time
T.
• For a variable at a time
T+1, search which set of
variables at time T has the
highest likelihood of
modulating its value at
T+1.
• Step-wise search
algorithm.
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Massachusetts Institute of Technology
Inference of Whole Dynamic Gene Network
• Infer a transition network between every pair of times.
VT
VT+1
VT+2
AT
AT+1
AT+2
BT
BT+1
BT+2
CT
CT+1
CT+2
NT
NT+1
NT+2
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Harvard Medical School
Massachusetts Institute of Technology
Parallelize Learning Individual Transition Nets
VT
VT+1
VT+1
VT+2
VT+2
AT
AT+1
AT+1
AT+2
AT+2
BT
BT+1
BT+1
BT+2
BT+2
CT
CT+1
CT+1
CT+2
CT+2
NT
NT+1
NT+1
NT+2
NT+2
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Massachusetts Institute of Technology
Parallelize Parent Searching of Individual Variables
VT
VT+1
AT
AT+1
BT
BT+1
CT
CT+1
NT
NT+1
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Massachusetts Institute of Technology
Step-by-Step Prediction
given
data
given
predicted
data
predicted
VT
VT+1
VT+2
AT
AT+1
AT+2
BT
BT+1
BT+2
CT
CT+1
CT+2
NT
NT+1
NT+2
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Harvard Medical School
Massachusetts Institute of Technology
Forecasting by Initial Data
given
data
predicted
predicted
VT
VT+1
VT+2
AT
AT+1
AT+2
BT
BT+1
BT+2
CT
CT+1
CT+2
NT
NT+1
NT+2
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Harvard Medical School
Massachusetts Institute of Technology
Clinical Study: HIV Viral Load Tracking
• Global AIDS epidemic is one of the greatest threats to
human health, causing 2 million deaths every year.
• Viral load (i.e., virus density in blood) is:
– associated with clinical outcomes.
– an indicator of which treatment physicians should provide.
• If there is a tool to predict/forecast viral load trajectory,
physicians could foresee how patients progress to AIDS
and could allocate the best treatments upfront.
• Data: Fourteen
(12 Africans, 2
viral load
Americans)
...
untreated adult gene expre.
patients during
acute infection.
Enroll
1
2
4
12
24
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Massachusetts Institute of Technology
Dynamic Gene Network of HIV Viral Load
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Harvard Medical School
Massachusetts Institute of Technology
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Harvard Medical School
Massachusetts Institute of Technology
Accuracy of HIV Viral Load Tracking
• Prediction accuracy:
Fitted Validation Cross Validation
(Accuracy)
(Robustness)
Dynamic Gene Network
97.8%
95.8%
Viral Load Auto-Regression
90.1%
89.5%
• Forecasting accuracy:
Fitted Validation Cross Validation
(Accuracy)
(Robustness)
Dynamic Gene Network
92.9%
91.8%
Viral Load Auto-Regression
88.7%
87.0%
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Massachusetts Institute of Technology
30 Genes Dynamically Interact with Viral Load
AMY1A: amylase, alpha 1a; salivary
OTOF: otoferlin
TNFAIP6 : tumor necrosis factor, alpha-induced protein
6
KIR2DL3: killer cell immunoglobulin-like receptor, two domains,
long cytoplasmic tail, 3
NBPF14: neuroblastoma breakpoint family, member 14
OSBP2: oxysterol binding protein 2
IRF7: interferon regulatory factor 7
CFD: complement factor d (adipsin)
HLA-DQA1: major histocompatibility complex, class ii,
dq alpha 1
HLA-DRB1: major histocompatibility complex, class ii, dr beta 1
RPS23: ribosomal protein s23
GPR56: g protein-coupled receptor 56
IFI44L: interferon-induced protein 44-like
CCL23: chemokine (c-c motif) ligand 23
KLRC2: killer cell lectin-like receptor subfamily c,
member 2
ITIF3: interferon-induced protein with tetratricopeptide
repeats 3
SOS1: son of sevenless homolog 1 (drosophila)
G1P2: interferon, alpha-inducible protein (clone ifi-15k)
LOC652775: similar to ig kappa chain v-v region l7
precursor
CCL3L1: chemokine (c-c motif) ligand 3-like 1
MBP: myelin basic protein
S100P: s100 calcium binding protein p
IFITM3: interferon induced transmembrane protein 3
(1-8u)
MX1: myxovirus (influenza virus) resistance 1, interferoninducible protein p78 (mouse)
HERC5: hect domain and rld 5
NME4: non-metastatic cells 4, protein expressed in
HLA-DQB1: major histocompatibility complex, class ii,
dq beta 1
LOC653157: similar to iduronate 2-sulfatase precursor (alpha-liduronate sulfate sulfatase) (idursulfase)
LOC643313: similar to hypothetical protein loc284701
RSAD2: radical s-adenosyl methionine domain containing 2
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Harvard Medical School
Massachusetts Institute of Technology
Conclusions
• A Bayesian network framework to infer dynamic gene
networks from time-series gene expression microarrays:
– Does not require densely sampled microarray data.
– Able to handle noise and handle biological variability.
– Temporal dependency is captured by first-order Markov
process.
– The optimal network model is achieved by parallelized search
algorithm.
• Application to HIV viral load tracking shows how our
method can be used in clinical studies:
– Our network model tracks viral load trajectories with higher
accuracy than viral load auto-regressive model.
– Our model provides candidate gene targets for drug/vaccine
development.
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Harvard Medical School
Massachusetts Institute of Technology
Acknowledgements
Supported by Center for HIV/AIDS Vaccine Immunology
(CHAVI) # U19 AI067854-06:
•National Institute of Allergy and Infectious Diseases
(NIAID)
•National Institutes of Health (NIH)
•Division of AIDS (DAIDS)
•U.S. Department of Health and Human Services (HHS)
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Harvard Medical School
Massachusetts Institute of Technology
Stationary Network Inference
• All networks between pairs of times are identical.
T+2
VLVL
VL
T T+1
VLT+3
VLVL
T+1T+2
VLT+2
A
ATAT+1T+2
AT+3
AT+2
AT+1
AT+2
BT+2
T+1
BB
T
BT+3
BT+2
BT+1
BT+2
CT+2
T+1
CC
T
CT+3
CT+2
CT+1
CT+2
NT+2
T+1
NN
T
NT+3
NT+2
NT+1
NT+2
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Harvard Medical School
Massachusetts Institute of Technology
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Harvard Medical School
Massachusetts Institute of Technology
Pathway: Immune Response (16/30 genes, p<10-6)
AMY1A: amylase, alpha 1a; salivary
OTOF: otoferlin
TNFAIP6 : tumor necrosis factor, alpha-induced protein
6
KIR2DL3: killer cell immunoglobulin-like receptor, two
domains, long cytoplasmic tail, 3
NBPF14: neuroblastoma breakpoint family, member 14
OSBP2: oxysterol binding protein 2
IRF7: interferon regulatory factor 7
CFD: complement factor d (adipsin)
HLA-DQA1: major histocompatibility complex, class ii,
dq alpha 1
HLA-DRB1: major histocompatibility complex, class ii, dr beta
1
RPS23: ribosomal protein s23
GPR56: g protein-coupled receptor 56
IFI44L: interferon-induced protein 44-like
CCL23: chemokine (c-c motif) ligand 23
KLRC2: killer cell lectin-like receptor subfamily c,
member 2
ITIF3: interferon-induced protein with tetratricopeptide
repeats 3
SOS1: son of sevenless homolog 1 (drosophila)
G1P2: interferon, alpha-inducible protein (clone ifi-15k)
LOC652775: similar to ig kappa chain v-v region l7
precursor
CCL3L1: chemokine (c-c motif) ligand 3-like 1
MBP: myelin basic protein
S100P: s100 calcium binding protein p
IFITM3: interferon induced transmembrane protein 3
(1-8u)
MX1: myxovirus (influenza virus) resistance 1, interferoninducible protein p78 (mouse)
HERC5: hect domain and rld 5
NME4: non-metastatic cells 4, protein expressed in
HLA-DQB1: major histocompatibility complex, class ii,
dq beta 1
LOC653157: similar to iduronate 2-sulfatase precursor (alpha-liduronate sulfate sulfatase) (idursulfase)
LOC643313: similar to hypothetical protein loc284701
RSAD2: radical s-adenosyl methionine domain containing 2
21
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Massachusetts Institute of Technology
Pathway: Antiviral Defense (8/30 genes, p<10-3)
major histocompatibility complex, class ii, dr beta 1
otoferlin
tumor necrosis factor, alpha-induced protein 6
killer cell immunoglobulin-like receptor, two domains, long
cytoplasmic tail, 3
neuroblastoma breakpoint family, member 14
oxysterol binding protein 2
interferon regulatory factor 7
complement factor d (adipsin)
major histocompatibility complex, class ii, dq alpha 1
amylase, alpha 1a; salivary
ribosomal protein s23
g protein-coupled receptor 56
killer cell lectin-like receptor subfamily c, member 2
chemokine (c-c motif) ligand 23
interferon-induced protein 44-like
interferon-induced protein with tetratricopeptide repeats 3
son of sevenless homolog 1 (drosophila)
interferon, alpha-inducible protein (clone ifi-15k)
similar to ig kappa chain v-v region l7 precursor
chemokine (c-c motif) ligand 3-like 1
myelin basic protein
s100 calcium binding protein p
interferon induced transmembrane protein 3 (1-8u)
myxovirus (influenza virus) resistance 1, interferon-inducible
protein p78 (mouse)
hect domain and rld 5
non-metastatic cells 4, protein expressed in
major histocompatibility complex, class ii, dq beta 1
similar to iduronate 2-sulfatase precursor (alpha-l-iduronate
sulfate sulfatase) (idursulfase)
similar to hypothetical protein loc284701
radical s-adenosyl methionine domain containing 2
22
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Massachusetts Institute of Technology
Pathway: Inflammatory Response (5/30 genes, p<0.05)
major histocompatibility complex, class ii, dr beta 1
otoferlin
tumor necrosis factor, alpha-induced protein 6
killer cell immunoglobulin-like receptor, two domains, long
cytoplasmic tail, 3
neuroblastoma breakpoint family, member 14
oxysterol binding protein 2
interferon regulatory factor 7
complement factor d (adipsin)
major histocompatibility complex, class ii, dq alpha 1
amylase, alpha 1a; salivary
ribosomal protein s23
g protein-coupled receptor 56
killer cell lectin-like receptor subfamily c, member 2
chemokine (c-c motif) ligand 23
interferon-induced protein 44-like
interferon-induced protein with tetratricopeptide repeats 3
son of sevenless homolog 1 (drosophila)
interferon, alpha-inducible protein (clone ifi-15k)
similar to ig kappa chain v-v region l7 precursor
chemokine (c-c motif) ligand 3-like 1
myelin basic protein
s100 calcium binding protein p
interferon induced transmembrane protein 3 (1-8u)
myxovirus (influenza virus) resistance 1, interferon-inducible
protein p78 (mouse)
hect domain and rld 5
non-metastatic cells 4, protein expressed in
major histocompatibility complex, class ii, dq beta 1
similar to iduronate 2-sulfatase precursor (alpha-l-iduronate
sulfate sulfatase) (idursulfase)
similar to hypothetical protein loc284701
radical s-adenosyl methionine domain containing 2
23
Harvard Medical School
Massachusetts Institute of Technology
Interferon Family Dominates
major histocompatibility complex, class ii, dr beta 1
otoferlin
tumor necrosis factor, alpha-induced protein 6
killer cell immunoglobulin-like receptor, two domains, long
cytoplasmic tail, 3
neuroblastoma breakpoint family, member 14
oxysterol binding protein 2
interferon regulatory factor 7
complement factor d (adipsin)
major histocompatibility complex, class ii, dq alpha 1
amylase, alpha 1a; salivary
ribosomal protein s23
g protein-coupled receptor 56
killer cell lectin-like receptor subfamily c, member 2
chemokine (c-c motif) ligand 23
interferon-induced protein 44-like
interferon-induced protein with tetratricopeptide repeats 3
son of sevenless homolog 1 (drosophila)
interferon, alpha-inducible protein (clone ifi-15k)
similar to ig kappa chain v-v region l7 precursor
chemokine (c-c motif) ligand 3-like 1
myelin basic protein
s100 calcium binding protein p
interferon induced transmembrane protein 3 (1-8u)
myxovirus (influenza virus) resistance 1, interferon-inducible
protein p78 (mouse)
hect domain and rld 5
non-metastatic cells 4, protein expressed in
major histocompatibility complex, class ii, dq beta 1
similar to iduronate 2-sulfatase precursor (alpha-l-iduronate
sulfate sulfatase) (idursulfase)
similar to hypothetical protein loc284701
radical s-adenosyl methionine domain containing 2
3 pathways;
2 pathways;
1 pathway
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