Overview1. What are single nucleotide polymorphisms (SNPs)?

1.1 SNP and disease-causing mutations: the same?

1.2 How SNPs are detected?

1.3 What can we do with the SNPs data?

2. GWAS: Genome-Wide Association Study

2.1 GWAS Catalog

3. Complex traits and diseases

3.1 Complex traits and diseases: heritability

3.2 Studying the heritability of complex traits with GWAS

3.3 Multi-stage disease model

3.4 The role of epistasis in complex traits

4. Concluding remarks

5. References

What are single nucleotide polymorphisms (SNPs)?• Single-nucleotide substitutions of one base for

another

• 84,7M SNP (88M variants, The 1000 Genome

Project Consortium, 1 October 2015)

• Most common type of genetic variation

(polymorphism) among individuals

• Goal: Identify SNP correlated with particular

effects in patients.

1

(8 Haplotypes)

Making SNPs Make

Sense. Retrieved

December 7, 2015,

from

http://learn.genetics.

utah.edu/content/ph

arma/snips/

‒ Biomarkers of specific diseases → Asses risk!

‒ Effectiveness of a drug/s

‒ Susceptibility to environmental factors.

‒ Adverse effects of a given drug

SNP and disease-causing mutations: the same?1.1

(8 Haplotypes)

• SNP ≠ disease-causing mutation → point mutations

• SNP are present in at least 1% of the general

population

• Most disease-causing mutations occur within a

coding or regulatory region of a gene affecting the

function of the protein

Any disease-causing mutation is this common

SNP are not

necessarily located

within genes

Two main

categories

Making SNPs Make Sense. Retrieved December 7, 2015, from

http://learn.genetics.utah.edu/content/pharma/snips/

rSNP or

srSNPs

cSNP

How SNPs are detected?

• SNP genotyping: determine the number of SNP in a DNA fragment by examining

the DNA with several methods and comparing it with a reference sequence

1.2

Chen, X., & Sullivan, P. F. (2003). Single nucleotide polymorphism

genotyping: biochemistry, protocol, cost and throughput. The

Pharmacogenomics Journal, 3(2), 77–96. http://doi.org/10.1038/sj.tpj.6500167

Making SNPs Make Sense. Retrieved December 7, 2015,

from http://learn.genetics.utah.edu/content/pharma/snips/

Different

approaches:

Low - high

throughput (next

generation

sequencing)

The scale of the

genotyping and

the cost defines

the study design

SNPs are sorted and

catalogued in databases

(dbSNP, HapMap

project, 1000 Genomes

project…) → rs number

What can we do with the SNPs data?1.3

GWAS

Genomic data

SNPs are associated to

a function or response

Phenotypic data

GWAS: Genome-Wide Association Study• Developed in 2007

• Based on the concept that genetic variation shows considerable linkage

disequilibrium → A given SNP is strongly correlated with other SNPs

• GWAS tests a single Tag SNP from regions of LD to mark the zones in the

genome showing disease association

2

Co-inherited more often than

expected by random events

In a typical study →500K-1000K SNPs are tested → 0,6 – 1,2% of the SNPs already known in

the human genome (2015, 1000 Genome Project) → SNP accepted = p-value ≤ 5.0 × 10-8

Gibson, G. (2010). Hints of hidden heritability in GWAS. Nature Genetics, 42(7),

558–60. http://doi.org/10.1038/ng0710-558

Problem?

GWAS Catalog2.1

All SNP-trait associations with

p-value ≤ 5.0 × 10-8, published

in the GWAS Catalog

GWAS Catalog. Retrieved December 8,

2015, from https://www.ebi.ac.uk/gwas/

5267 SNP-trait associations

Complex traits and diseases3

• The vast majority of diseases complex:

Environmental and genetic interactions (2015). Retrieved from

http://www.genetics.edu.au/Publications-and-Resources/Genetics-Fact-Sheets/

Complex traits and diseases: heritability3.1

• Despite the polygenic feature, heritability in several common diseases can be explained

Sadee, W., Hartmann, K., Seweryn, M., Pietrzak, M., Handelman, S. K., & Rempala, G. A. (2014). Missing heritability of common diseases and treatments outside the

protein-coding exome. Human Genetics, 133(10), 1199–215. http://doi.org/10.1007/s00439-014-1476-7

Studying the heritability of complex traits with GWAS

• Genomics of complex disease remains unresolved

• Genetic factors identified only explain a small portion of heritability estimation → Height

• Only 20% of estimated heritability explained by the combination of all significant SNPs →

SNPs with small individual effects/ low frequent hidden in GWAS

• Heritability can be defined in two ways

3.2

Missing/hidden heritability

h2

H2

Additive effect of individual alleles

Epistasis + epigenetics

5% (50 SNPs)

Multi-stage disease model3.3

Sadee, W., Hartmann, K., Seweryn, M., Pietrzak, M., Handelman, S. K., & Rempala, G. A. (2014). Missing heritability of common diseases and treatments outside the

protein-coding exome. Human Genetics, 133(10), 1199–215. http://doi.org/10.1007/s00439-014-1476-7

(positive selection) (subclinical state) (clinical non-

measurable state )

(clinical measurable

state)

rSNPHigh/low activity SNPs

The role of epistasis in complex traits3.4

• Interactions gene-gene-environment

Epistasis

Non-linear gene-gene-environment interactions

Interactions between SNPs in the same gene

SNPBeneficial

Deleterious

Phenotype

Environment

2nd mutation

Complex traits

Complex diseases

Interactions

DRD2/DAT

DRD2 (Dopamine D2 receptor):

Splicing SNP increases (3X)

lethal risk of cocaine abuse

DAT (dopamine transporter):

variants with no effects

2 interactions

7-8X increased

lethal risk of

cocaine abuse

Total compensation

of the disease risk

Explains missing heritability GWAS issues Wellcome Trust Study

Concluding remarks4

• GWAS studies need to focus on the role of causative SNP, not only on marker SNP

• Redefine GWAS studies with larger number of cases and a different treshold to look for

rare SNPs

• Better study of rSNP and its role affecting epigenetic DNA and chromatin marks → Better

understanding of epigenetics

• SNPs positive selected could cause deleterious effects under certain conditions →

Undetected to GWAS (low score) → Better study of epistasis phenomena

• How can we quantify the effect of environment on human health?

• Cost of sequencing is steadily decreasing → Sequencing more individuals → more SNP

data of both common and rare SNPs

• Re-estimate heritability to contemplate the effects of environment, epigenetics, epistasis…

Unknown in the majority of casesGain or loss of function?

References• Making SNPs Make Sense. Retrieved December 7, 2015, from http://learn.genetics.utah.edu/content/pharma/snips/

• GWAS Catalog. Retrieved December 8, 2015, from https://www.ebi.ac.uk/gwas/

• What are single nucleotide polymorphisms (SNPs)? (2015). Retrieved from http://ghr.nlm.nih.gov/handbook/genomicresearch/snp

• What are complex or multifactorial disorders? (2015). Retrieved from

http://ghr.nlm.nih.gov/handbook/mutationsanddisorders/complexdisorders

• Environmental and genetic interactions (2015). Retrieved from http://www.genetics.edu.au/Publications-and-Resources/Genetics-

Fact-Sheets/

• Nickerson, D. Overview of SNP Genotyping. Retrieved December 9, 2015, from

https://www.niehs.nih.gov/news/assets/docs_p_z/snp_genotyping_508.pdf

• Chen, X., & Sullivan, P. F. (2003). Single nucleotide polymorphism genotyping: biochemistry, protocol, cost and throughput.

The Pharmacogenomics Journal, 3(2), 77–96. http://doi.org/10.1038/sj.tpj.6500167

• Auton, A., Abecasis, G. R., Altshuler, D. M., Durbin, R. M., Bentley, D. R., Chakravarti, A., … Schloss, J. A. (2015). A global reference

for human genetic variation. Nature, 526(7571), 68–74. http://doi.org/10.1038/nature15393

• Atanasovska, B., Kumar, V., Fu, J., Wijmenga, C., & Hofker, M. H. (2015). GWAS as a Driver of Gene Discovery in Cardiometabolic

Diseases. Trends in Endocrinology and Metabolism: TEM, 26(12), 722–732. http://doi.org/10.1016/j.tem.2015.10.004

• Sadee, W., Hartmann, K., Seweryn, M., Pietrzak, M., Handelman, S. K., & Rempala, G. A. (2014). Missing heritability of common

diseases and treatments outside the protein-coding exome. Human Genetics, 133(10), 1199–215. http://doi.org/10.1007/s00439-

014-1476-7

• Donnelly, P. (2008). Progress and challenges in genome-wide association studies in humans. Nature, 456(7223), 728–31.

http://doi.org/10.1038/nature07631

• Maher, B. (2008). Personal genomes: The case of the missing heritability. Nature, 456(7218), 18–21.

http://doi.org/10.1038/456018a

• Gibson, G. (2010). Hints of hidden heritability in GWAS. Nature Genetics, 42(7), 558–60. http://doi.org/10.1038/ng0710-558

5

THANK YOU VERY MUCH FOR YOUR

ATTENTION!

Hidden or

missing

heritability?