ITMO Génétique, génomique et bioinformatique

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ITMO Génétique, génomiqueet bioinformatique

From population genetics to cellular genomics: a path towards personalised medicine

Lluis Quintana-Murci, Institut Pasteur-CNRS

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Genetic variation in health and disease

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ACGTGTACAGAAGGGCCATGAACACTGTTATTACTCTTACACAATTGTGAGGCAGCCCTCGAGCCACAGGCGGGTCCAGCTGTTGGCTATAAACGGATAGCCTACCGGTCTCTGATCGGAGATCACCATGTTTCTGGGTCCCTTGTACCCTGGATGCAGTACCTCGCCCCAGTTTCGCATACAAATTCGCATACAAAACGTGTACAGAAGGGCCATGAACACTGTTATTACTCTTACACAATTGTGAGGCAGCCCTCGAGCCACAGGCGGGTCCAGCTGTTGGCTATAAACGGATAGCCTACCGGTCTCTGATCGGAGATCACCATGTTTCTGGGTCCCTTGTACCCTGGATGCAGTACCTCGCCCCAGTTTCGCATACAAATTTCGCATACAAAAA

Genetic Diversity

Inter-Population Variation

Phenotypic DiversityPhenotypic Diversity

Inter-Individual Variation

Personal genomics

Personalised medicine

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The last decade in human genomics

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1. The complete sequence of the human genome

2. SNP Discovery and the HapMap Project

3. The 1,000 Genomes Project

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Lessons from genome diversity

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tttctccatttgtcgtgacacctttgttgacaccttcatttctgcattctcaattctatttcactggtctatggcagagaacacaaaatatggccagtggcctaaatccagcctactaccttttttttttttttgtaacattttactaacatagccattcccatgtgtttccatgtgtctgggctgcttttgcactctaatggcagagttaagaaattgtagcagagaccacaatgcctcaaatatttactctacagccctttataaaaacagtgtgccaactcctgatttatgaacttatcattatgtcaataccatactgtctttattactgtagttttataagtcatgacatcagataatgtaaatcctccaactttgtttttaatcaaaagtgttttggccatcctagatatactttgtattgccacataaatttgaagatcagcctgtcagtgtctacaaaatagcatgctaggattttgatagggattgtgtagaatctatagattaattagaggagaatgactatcttgacaatactgctgcccctctgtattcgtgggggattggttccacaacaacacccaccccccactcggcaacccctgaaacccccacatcccccagcttttttcccctgctaccaaaatccatggatgctcaagtccatataaaatgccatactatttgcatataacctctgcaatcctcccctatagtttagatcatctctagattacttataatactaataaaatctaaatgctatgtaaatagttgctatactgtgttgagggttttttgttttgttttgttttatttgtttgtttgtttgtattttaagagatggtgtcttgctttgttgcccaggctggagtgcagtggtgagatcatagcttactgcagcctcaaactcctggactcaaacagtcctcccacctcagcctcccaaagtgctgggatacaggtgtgacccactgtgcccagttattattttttatttgtattattttactgttgtattatttttaattattttttctgaatattttccatctatagttggttgaatcatggatgtggaacaggcaaatatggagggctaactgtattgcatcttccagttcatgagtatgcagtctctctgtttatttaaagttttagtttttctcaaccatgtttacttttcagtatacaagactttgacgttttttgttaaatgtatttgtaagtattttattatttgtgatgttatttaaaaagaaattgttgactgggcacagtggctcacgcctgtaatcccagcactttgggaggctgaggcgggcagatcacgaggtcaggagatcaagaccatcctggctaacatggtaaaaccccgtctctactaaaaatagaaaaaaattagccaggcg

3 million differences between individuals

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ga

gc

gc

ga

ga

ga

ga

tc

tc

tc

ga

ga g

c

tc

tc

tc

Most mutations have no (known) phenotypic effects

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ga

gc

gc

ga

ga

ga

ga

tc

tc

tc

ga

ga g

c

tc

tc

tc

Some variants can explain phenotypic variation (in health and disease)

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The burden of deleterious mutations in the human genome

•10,000 amino-acid altering mutations

•300-400 stop/splice/indels disrupting 200-300 genes

•heterozygous at 50-100 mutations associated with an inherited disorder

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Impact of genetic variation on phenotypes

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ACGTGTACAGAAGGGCCATGAACACTGTTATTACTCTTACACAATTGTGAGGCAGCCCTCGAGCCACAGGCGGGTCCAGCTGTTGGCTATAAACGGATAGCCTACCGGTCTCTGATCGGAGATCACCATGTTTCTGGGTCCCTTGTACCCTGGATGCAGTACCTCGCCCCAGTTTCGCATACAAATTCGCATACAAAACGTGTACAGAAGGGCCATGAACACTGTTATTACTCTTACACAATTGTGAGGCAGCCCTCGAGCCACAGGCGGGTCCAGCTGTTGGCTATAAACGGATAGCCTACCGGTCTCTGATCGGAGATCACCATGTTTCTGGGTCCCTTGTACCCTGGATGCAGTACCTCGCCCCAGTTTCGCATACAAATTTCGCATACAAAAA

Genetic Diversity

Inter-Population Variation

Phenotypic DiversityPhenotypic Diversity

Inter-Individual Variation

Personal genomics

Personalised medicine

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Genome-wide association studies - GWAS

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By September 2013:11,304 SNPs associated with 891 traits/diseases (1,701 studies)

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GWAS results in personalised medicine

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Thomas et al. Nature. 2009

• High p-values do not translate to clinically useful diagnostic assays• Strong population variation (only useful in European populations)

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Healthy-based population approaches

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• Understanding patterns of population variation of our genomes • Searching for the signatures of selection in the genome

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Population and evolutionary genetics

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Variation in biological relevance in host defence of immune receptors

Positive selection targeting protective mutations in Europeans

Type-III IFNs and hepatitis CInnate immunity to infection

Quintana-Murci & Clark. Nat Rev Immunol, 2013

Manry et al., J Exp Med, 2011

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Principles of cellular genomics

InfectionDrugs

RadiationUntreated cells Treated cells

Variation in gene expressionGenetic/epigenetic markers

Gene-environment interactions

Complex phenotypesLack of mechanistic understanding

Simpler phenotypesFocus on mechanisms

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Cellular genomics complementing GWAS

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• GWAS of TB have mostly failed in identifying susceptibility genes

• A recent cellular genomics study has identified >100 mutations that affect expression only after infection (response eQTLs)

• These mutations may contribute in an additive manner to susceptibility to develop TB - > added value of cellular genomics

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Integrative genomics

• Importance of taking first basic science approaches

• Need for understanding how genotypes affect phenotypes in BOTH

health and disease

• Need for complementary approaches based on model systems

• Opportunities to tackle these questions at the highest resolution (e.g.,

NGS, rare variants, epigenetics)

• Improve methods in statistical genetics and computational biology

(e.g., epistasis)

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A path towards personalised medicine

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ENVIRONMENTSLIFESTYLE

GENETICScomplete sequences

EPIGENETICSMethylation, Histone modification

HEALTH and DISEASE

BIOMARKERSResponses to treatment Vaccine efficiency, doses

PHENOTYPESMolecular phenotypes (expression)

Cellular phenotypesOrganismal phenotypes (traits or diseases)

Model systems

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Population and evolutionary genetics

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Barreiro & Quintana-Murci, Nat Rev Genet, 2010

180 immunity-related genes targeted by positive selection

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Disease-based approaches

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Approach Clinical genetics Epidemiological genetics

Phenotype Severe/acute(children)

Milder/chronic(adults)

Tools Mendelian Genetics Linkage/association

Sample Small Large

Rare mutationsStrong individual effect

Common polymorphismsModest individual effect

Little public health impact Strong public health impact

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Limitations of “disease-only”-based approaches

• Associations based on strict statistic thresholds• Disease is a complex “phenotype”• Odds ratios remain rather low• Assumption of genes acting “alone”• Causal mutations remain mostly unidentified

-> Need for complementary approaches

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Using “simpler” phenotypes (molecular)

• Expression is a molecular phenotype that varies between individuals and populations

• Levels of expression can be under genetic control (eQTL)

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Genotype mRNA

M. tuberculosis

• 1/3 of the world’s population infected with Mycobacterium tuberculosis (MTB)

• Only 10% of infected individuals will develop the active form of the disease

Environment

ITMO Génétique, génomique et bioinformatique

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