Joaquín Dopazo Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node, (INB), Bioinformatics in Rare Diseases (BiER-CIBERER), Valencia, Spain. Digging into thousands of variants to find disease genes in Mendelian and complex diseases http://bioinfo.cipf.es http://www.babelomics.org @xdopazo IV DCEX symposium, Barcelona, November 17th, 2015
45
Embed
Digging into thousands of variants to find disease genes in Mendelian and complex diseases
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Joaquín Dopazo
Computational Genomics Department,
Centro de Investigación Príncipe Felipe (CIPF),
Functional Genomics Node, (INB),
Bioinformatics in Rare Diseases (BiER-CIBERER),
Valencia, Spain.
Digging into thousands of variants to
find disease genes in Mendelian and
complex diseases
http://bioinfo.cipf.es http://www.babelomics.org
@xdopazo
IV DCEX symposium, Barcelona, November 17th, 2015
Precision medicine (P4*) is based on a better knowledge of phenotype-
genotype relationships
Requires of a better way of defining diseases by introducing genomic
technologies in the diagnostic procedures and treatment decisions
mechanism-based perspective Transforming gene expression values into another value that accounts for a function. Easiest example of modeling function: signaling pathways. Function: transmission of a signal from a receptor to an effector
Receptors Effectors Important assumption:
collective changes in
gene expression within
the context of a
signaling circuit are
proxies of changes in
protein activation
What would you
predict about the
consequences of
gene activity changes
in the apoptosis
pathway in a case
control experiment of
colorectal cancer?
The figure shows the
gene up-regulations
(red) and down-
regulations (blue)
The effects of changes in gene
activity are not obvious
Apoptosis
inhibition is
not obvious
from gene
expression
Two of the three possible sub-
pathways leading to apoptosis
are inhibited in colorectal
cancer. Upper panel shows the
inhibited sub-pathways in blue.
Lower panel shows the actual
gene up-regulations (red) and
down-regulations (blue) that
justify this change in the activity
of the sub-pathways
Pathway analysis helps, in addition, to
understand disease mechanisms
Fanconi Anemia is a rare chromosome instability syndrome characterized by aplastic
anemia and cancer and leukemia susceptibility. It has been proposed that disruption of the
apoptotic control, a hallmark of FA, accounts for part of the phenotype of the disease.
No
proliferation
No
degradation
Survival
No
degradation
No
apoptosis
Activation
apoptosis
pathway
Cases and controls: Different signaling
As tumor grade / stage
progresses…
Up
• Cell survival
• Proliferation, differentiation
• Cell cycle progression
• Antiapoptosis
Down
• Glucose homeostasis
• Metabolism
• Degradation
Tumor grade / stage
Signaling changes and functionalities affected in
543 Kidney Renal Clear Cell Carcinoma samples
from ICGC/TCGA database
Using circuit activation probabilities
as features for prediction
Circuit activation
probabilities are
mechanism-based
biomarkers
1. Generation of features: signaling
circuit activities 2. Training set
3. Prediction
Prediction of IC50 values from the
activity of signaling circuits
Is gene expression a good proxy
for protein activity?
However, collective changes
in gene expression within the
context of a signalling circuit
can be considered good
proxies of changes in protein
activation
The scarce phosphoproteomic
data available are consistent
with circuit activations
predicted from gene
expression changes
The observation of the expression of a gene does not guarantee that
the corresponding protein is present and active.
Circuit TNF-NPY from the Adipocytokine signaling pathway (hsa04920).
Nodes in red contain proteins found to be hyperphosphorylated when
comparing treated versus untreated lung cancer cells. Nodes in blue
contain proteins found to be dephosphorylated in the same comparison.
Bio
logic
al variabili
ty
Technic
al variabili
ty
Technical variability is enormously
reduced at the pathway level Human neuroblastoma cell lines.
RNA-seq vs microarrays
Errors across genes seem
to be cancelled within the
signaling circuits
Gene1
Gene2
Gene3
Gene4
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
Gene22000
Raw measurement
Transformed
measurement:
Receptor to effector
signaling activities
Circuit1
Circuit2
Circuit3
Circuit4
:
:
:
:
:
:
:
:
Circuit800
:
:
:
Abstraction levels when converting
genomic data into functional information
Second
transformation:
All receptors to
final effector
signaling
activities
Third
transformation:
Final effector
activities to
functions triggered
Some
functions
can be
cancer
hallmarks
Gaining insight into disease
mechanisms and MoA From gene-based to function-based analysis perspective
SNPs, gene
expression,
etc.
GO
Protein
interaction
networks
Models of
cellular
functions
Detection
power
Low (only
very
prevalent
genes)
High High Very high
Information
coverage
Almost all Almost all Low (~9000
genes in
human)
Low (~6700
genes in
human)*
Use Biomarker Illustrative,
give hints
Biomarker Biomarker
that explain
disease
mechanism
*Only ~800 genes in human signaling pathways
The use of new algorithms that enable the transformation of genomic
measurements into cell functionality measurements that account for
disease mechanisms and for drug mechanisms of action will ultimately
allow the real transition from today’s empirical medicine to precision
medicine and provide increasingly personalized medicine
The real transition to precision medicine
Intuitive Based on trial
and error
Identification of probabilistic
patterns
Decisions and actions based on knowledge
Intuitive Medicine Empirical Medicine Precision Medicine
Today Tomorrow
Degree of personalization
Software available
See interactive map of for the last 24h use http://bioinfo.cipf.es/toolsusage Babelomics is the third most cited tool for functional analysis. Includes more than 30 tools for advanced, systems-biology based data analysis
More than 150.000 experiments were analyzed in our tools during the last year
HPC on CPU, SSE4, GPUs on NGS data processing Speedups up to 40X