EdgeLeap NuGOweek 2014 - Organizing Data To Empower Decision Making

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Presentation of EdgeLeap's CEO Marijana Radonjic at NuGO Week (11 September 2014, Castellammare di Stabia, Italy). This presentation shows how organizing and linking diverse data (food databases, disease associations, genomics, 23andMe genetics profiles) allows us to map a personal food-genomics-health landscape and identify dietary patterns which may affect personal disease risk. For more details see: http://www.edgeleap.com/news/edgeleap-at-nugo-week-2014/

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www.edgeleap.com

Marijana Radonjic, PhD

marijana@edgeleap.com

ORGANIZING DATA TO

EMPOWER DECISION MAKING

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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DATA

DECISION

INFORMATION

KNOWLEDGE

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NuGO week 2014Participant list(hard copy)

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Institute

Person

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In Marijana’s LinkedIn

Not (yet) in Marijana’s LinkedIn

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PERSONALIZED

FOOD-HEALTH LANDSCAPES

marijana@edgeleap.com

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COMPLEXITY OF HEALTH FACTORS

8

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PEAK INTO THE FUTURE

9

JAN FEB MAR APR MAY JUN

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FOOD - GENOMICS - HEALTH

LANDSCAPE

10

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BRIDGING FOOD AND HEALTH

11

Ingredient GeneFooDB: 9,955 food

ingredients, 858 foods

HMDB: 4,025 associated

enzymes & transporters

Disease

UMLS: 8,521 diseasesDisgeNET: 13,828 associated genes & proteins

GeneticsBiomarkersMechanistic

EnzymesTransporters

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BRIDGING FOOD AND HEALTH

12

Ingredient Gene

Disease

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FOOD - GENOMICS - HEALTH NETWORK

13

Significance filter(Monte Carlo randomization

procedure p < 0.001)

Projection to disease-

ingredient space

Bipartitedisease-gene-ingredient

network

Disease-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 - HEALTH

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-ingredient network

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PERSONAL FOOD - GENOMICS - HEALTH

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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NUTS – 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

CETP

Fats and oils

Herbs and Spices

Cocoa and cocoa products;Fats and oils

Cocoa and cocoa products;Fats and oils

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WHAT ELSE WILL BE AFFECTED?

Disease

Increased risk

Mixed evidence

Linked to variant

Ingredient

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FROM INGREDIENTS TO DIET

23andMe SNP profiles(11 individuals)

Whole foods for which their ingredients enriched in personal networks

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CHALLENGES AHEAD

21

• From ingredients to diets: diets in genetics context

• Beyond genetics: involve broader phenotypic data (dietary

questionnaires, activity measurements, self monitoring devices,

medical history)

• Time resolved data (current status, future risk)

• Standardization of knowledge:

• Ontologies to map between resources

• Publish in structured format

• Add directionality of relations: from associations to causal

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MAKING DECISIONS

22

Understand big picture beyond single SNP-

ingredient associations

Improve advice on dietary lifestyle

Develop healthy food

(Re)position existing product

What to eat to stay healthy?

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THANKS

Georg SummerPhD Student, co-supervised by Maastricht University / TNO / EdgeLeap

Thomas KelderEdgeLeap

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info@edgeleap.com

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edgeleap

@EdgeLeap

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