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Better measurementand visualization
Better mathematical tools to interpret data
Systems approachto biology
Systems medicine
P4 Medicine
Predictivemedicine
Preventivemedicine
Personalizedmedicine
Participatorymedicine
biology as an information science
Software generates the hardware !! Only portion of the program is executed in a
particular cell at a given time. How?? Two kinds of information characterize all central
mechanisms of life Digital information of the genome + environmental
signals Information handling structures: DNA, RNA Hierarchical levels of information: genes, proteins,
individual phenotype, gene pools, biome etc
systems approach to disease
The whole is more than the sum of its parts Whole - ∑ (parts) = emergent
properties Diseases are just network perturbations Dynamic alteration of expression of
information Interactome = Genome + Epigenome +
Transcriptome + Proteome + Metabolome + ….
emerging technologies
Family genome sequencing Proteomics Metabolomics Single cell analysis Imaging Induced pluripotent stem cells
family genome sequencing In the next 10 years or so, individual genome
sequencing would be routine clinical practice 70% sequencing errors could be identified by using
plausability checks based on Mendelian genetics Rare variants would be identified immediately Accelerate search for disease-causing genes Actionable gene variants would allow specification of
how a patient can improve his health Get SNP’ed: know your pre-disposition to diseases
proteomics
20,000 human genes code for millions of proteins Comparing proteome across space and time
would enable new markers for diagnostics and drug design
Targeted proteomics: democratization of human proteins
Powerful tools in analyzing disease mechanisms, approaches to identification of biomarkers
metabolomics Using stable isotopes to follow the fate and rate of
individual metabolites, the measurement of metabolite fluxes
More information on disease progression and potential adaptive, compensatory physiological and patho-physiological mechanisms
MS-based methods to be complemented by pattern-recognition array-sensors to capture volatile metabolites in exhaled breath, providing disease-specific molecular signatures
E-noses: Non-invasive diagnostic devices
single cell analysis
Microfluidic technologies to study individual cells at the genomic and the proteomic levels
Number of discrete cell populations in a particular tissue or organ
Identification of cell surface molecules to categorize discrete populations
Characterization of disease states by cell surface molecules
imaging
Spatial and temporal information is critical for developing reliable disease models
Would allow identification of actionable network components
Need to develop advance high-resolution, high-content imaging
Would enable reliable interpretation of molecular processes in health and disease
Integrated into molecular diagnostics, medical decision support systems
induced pluripotent stem cells
First derived by Takahashi and Yamanaka (2006) Is a technique for cellular reprogramming Will be useful in exploring mechanisms of
disease initiation and progression Would reveal many secrets of development Will be crucial for curing antigen-specific
autoimmunity and allergies Accelerator for regenerative medicine Minimal immune response
the promise of p4 medicine
Will quantify wellness and demystify disease Each individual will be associated with a virtual
data cloud of billions of data points Data cloud will be reduced to simple
hypotheses on health and disease for each individual
Quantized self will provide real-time, readily-digestible insights into optimizing wellness
Stratification of diseases will revolutionize drug discovery
predictive medicine
Blood as a window into disease Molecular fingerprints of diseases Assessment of susceptibility to diseases based
on the genetic makeup (SNPs, ethnicity etc) HLA complex is associated with susceptibility
to >50 diseases Relative risk = % affected among those with allele % affected in the general population DR2 130X prone to nacrolepsy
preventive medicine
Designing therapeutic, preventive drugs via systems approaches
Systems approaches to create vaccines will transform prevention against infectious diseases
Reengineering of disease perturbed networks at the earliest
Shift from focus on disease to focus on wellness
personalized medicine
Different drugs for different genetic subsets of the population
Each person would be his/her own control Real-time monitoring of single cells to suggest
changes in the therapy being provided Need to safeguard against misuse by employers
or insurance companies
participatory medicine
Patient-driven social networks Cloud computing and crowd sourcing of medical
data Radical changes in medical school curricullum Big changes in the Big Pharma Emergence of new companies for development
and transfer of technologies involved Democratization of medicine Adequate healthcare affordable to all
systems approach to the prion disease
To identify DEGs, diseased brain transcriptomes were subtracted from control transcriptomes at 10 time points across disease progression.
7400 RNA transcripts, encoded by 1/3rd of mice genes were altered
4 major networks, involving 300 DEGs, appeared to participate in prion disease and the networks were altered sequentially
Dynamics of transcriptome alterations explained pathophysiology of disease
>100 brain-specific mouse transcripts could be identified, many of them encoding proteins secreted into blood
A brain-specific blood fingerprint that could distinguish for the brain –health from disease, and in case of disease, the type of disease– can be developed
“ ….In next 10-15 years, we will have a hand-held device which would measure around 50 proteins of each of the about 50 major organs
from just nanolitres of blood…. ”
reference
Hood, L., Balling, R., Auffray, C., Revolutionizing medicine in the 21st century through systems approaches, Biotechnol. J. 2012, 7, 992-1001
TED and other talks by Dr Leroy Hood