edgeleap: from systems complexity to personalized health
DESCRIPTION
Slides based on talk by EdgeLeap's CEO Marijana Radonjic at the Seminar System Biology, Maastricht, The Netherlands, 26 September 2014 (http://goo.gl/siyibc). This presentation shows EdgeLeap's vision on using data science to empower health research. Shown is also an example on how we combined different public resources (e.g. openSNP, SNPedia), and personal genetics information (23andMe profiles) and analysed these to extract relevant aspects (in this case drugs and food ingredients relevant for a specific disease).TRANSCRIPT
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Marijana Radonjic, PhDThomas Kelder, PhD
FROM SYSTEMS COMPLEXITY
TO PERSONALIZED HEALTH
This presentation remains property of EdgeLeap B.V. and is licensed for reuse under a Creative Commons Attribution 4.0 International License (see http://creativecommons.org/licenses/by/4.0/).
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HEALTH IS COMPLEX…
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…BUT THAT’S OK
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Diameter of the World-wide WebAlbert, Jeong and Barabási, Nature 1999
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GOOGLE MAPS FOR BIOLOGY
http://diseasome.eu/about.html
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EdgeLeap TECHNOLOGY
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UNDERSTANDING SYSTEMS
Micronutrient
Diet
Drugs
Genotype
Protein
microRNA
Vascular stiffness
AdiposityInflammation
Brain activity
Insulin sensitivityGut function
HEALTH FACTORS
MOLECULAR DATA
PATHWAYS & MECHANISTIC
MODELS
PHYSIOLOGY
Socio-economic
status
HEALTH STATUSObesity Cancer Diabetes CVD
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ITERATIVE DISCOVERY
INTERVENE
UNDERSTAND
VISUALIZE
MINE
INTEGRATE
MEASURE
EdgeLeap
client
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PERSONALIZED HEALTH LANDSCAPE
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PEAK INTO THE FUTURE
JAN FEB MAR APR MAY JUN
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PERSONAL HEALTH LANDSCAPE
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BRIDGING FOOD, DRUGS AND DISEASE
13
IngredientGene
FooDB: 9,955 food
ingredients, 858 foods
HMDB: 4,025 associated
enzymes & transporters
Disease
UMLS: 8,521 diseases
DisgeNET: 13,828
associated genes & proteins
GeneticsBiomarkersMechanistic
EnzymesTransporters
Drug
Drug TargetsDrugBank: 4714 drugs,
2179 drug target proteins
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BRIDGING FOOD, DRUGS AND DISEASE
14
Ingredient
Disease
Drug
Gene
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FOOD - DRUG - DISEASE NETWORK
Significance filter(Monte Carlo randomization
procedure p < 0.001)
Projection to disease-drug-
ingredient space
Bipartitedisease-gene-drug-gene-ingredient
network
Disease-Drug-Ingredientnetwork
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Neoplasms
Metabolic syndrome and complications
Mental disorders817 connected diseases316 connected ingredients1,961 disease-ingredient relations(p < 0.001)Network cluster coefficient = 0.42 (v.s. random graph ~0.006)
FOOD - GENOMICS - DISEASE
LANDSCAPE
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NETWORK RECONSTRUCTS DISEASE AND
INGREDIENTS CLASSES
Most or all topology based clusters (47/67 for diseases and 10/10 for ingredients) are significantly enriched with one or more predefined MeSH disease and/or HMDB chemical classes (p < 0.05).
Significant enrichment (p < 0.01)
Clusters enriched with main disease classes
Clusters enriched with main ingredient classes
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Raw data
GOING PERSONALIZED
Rs1234(A;A)
Rs1234(G;G)
Increased risk
Decreased risk
Disconnected information
Personal disease-drug-ingredient
network
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MY FOOD - DISEASE LANDSCAPE
Disease
Decreased risk
Increased risk
Mixed evidence
Linked to variant
Not linked to variant
Ingredient
AtherosclerosisCoronary diseaseHypertensionObesityDiabetesDementia
Cancers
PsychosisAutismMigrane disordersDepression‘as if’ personalityNicotine dependence
Cluster headacheHypertension
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FOOD - ATHEROSCLEROSIS ASSOCIATION
Disease
Increased risk
Linked to variant
Not linked to variant
Ingredient
Vegetables;Fruits;Herbs and Spices;Nuts;Cereals and cereal products;Pulses;Teas;Gourds;Coffee
Fats and oilsCocoa and cocoa products;Fats and oils
Herbs and Spices
Cocoa and cocoa products;Fats and oils
CETP
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WHAT ELSE WILL BE AFFECTED?
Disease
Increased risk
Mixed evidence
Linked to variant
Ingredient
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HOW ABOUT DRUGS?
Linked to variant
Not linked to variant
Ingredient
Drug
Linked to variant
Not linked to variant
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TOWARDS PERSONALIZED PROFILES
23andMe SNP profiles(11 individuals)
Whole foods for which their ingredients enriched in personal networks
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THE VALUE
Understand big picture and mechanisms of diseases
Improved strategies to prevent and treat diseases
Sustainable solutions, reduced health care cost
Personalized profiles for disease risk and prevention
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EdgeLeap FOR YOU
Contract research: we can help you get most out of your data
Partner in H2020 calls: data integration and mining, across the consortium
Consultancy: support in bioinformatics / data analysis aspects
Training: bioinformatics and data analysis tools, from scripting in R to visualization in Cytoscape
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@EdgeLeap
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