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Printable Handouts
Navigable Slide Index
- Introduction
- Progress of genomics in the past decade
- Complex traits and common diseases
- Host genetics in infectious diseases (publications)
- Pathogen genetics of infectious diseases
- Public health in the age of genomics
- Disruptive potential of infectious diseases
- SARS: cumulative number of reported cases
- Surveillance and control of infectious diseases
- Without genomic surveillance (example)
- With genomic surveillance (example)
- Concept of genomic surveillance
- Host genetics in infectious diseases
- Brief recap of GWAS in NCDs and complex traits
- GWAS hypothesis
- Association studies: genomic variation
- Sampling & ascertainment
- Association studies: quantitative traits
- ANOVA-based analysis
- Indirect associations
- Commercial genotyping chips
- Chips summarizing the human genome
- HapMap SNPs vs. New SNPs
- 1000 Genomes project
- Burden of infectious diseases
- Summary of lesson 1
- Confounding effects of population structure
- Detecting & correcting for population structure
- Principal components analysis
- Admixed populations
- Admixed populations: Thailand
- Evolution of GWAS
- Diverse populations: design issue
- Meta-analysis across different platforms
- Harmonizing SNP content
- Signals of malaria association in The Gambia
- Diverse populations: genetic diversity issue
- Inter-population LD variation
- Inter-population LD variation (examples)
- Conclusions for lesson 2
- Diverse populations: biological issue
- Out of Africa population migration
- Factors driving genetic dissimilarities
- Heterogeneity in infectious diseases
- Additional complexity in infectious diseases
- Confluence of positive selection & host genetics
- Theory of positive selection
- Genomic signatures of positive natural selection
- Fixed & moderately recent mutations
- Established methods to detect positive selection
- iHS & XP-EHH
- Sickle-cell locus in Africans
- Natural selection in Bangladeshi population
- Genetic association in African Americans
- Positive selection & antimalarial resistance
- Summary
Topics Covered
- Statistical genetics of infectious diseases
- Opportunities & challenges of identifying host genetic factors for infectious diseases
- Convergence in evidence between positive selection & host genetic protection to infection
- Population genetics of communities facing greater burden of infectious diseases
Links
Series:
Categories:
Therapeutic Areas:
Talk Citation
Teo, Y.Y. (2017, April 30). Statistical genetics of infectious diseases [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved October 11, 2024, from https://doi.org/10.69645/RHFX7597.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. Yik Ying Teo has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Other Talks in the Series: Statistical Genetics
Transcript
Please wait while the transcript is being prepared...
0:00
Good day, everyone.
My name is YY Teo.
I'm currently
at the National University of Singapore.
And I'm the center director
for the Center for Infectious Diseases
Epidemiology Research.
Today, we're going to talk about
"Statistical Genetics of Infectious Diseases".
0:18
Now, there has been quite a lot of progress
in genomics over the past 15 years.
So in 2001, we started with the sequencing
of the first draft of the human genome.
And we did a spectrum
of about 10 years or decade.
We have now moved from
just sequencing one human,
to sequencing thousands of humans
and also not just the humans,
but also the organisms, the pathogens
that are inside and on the surface
of the skins of humans.
Now given this rapid progress,
there has been a lot of opportunities
and challenges
for the use of genomics
to look at a spectrum of diseases.
0:55
So, if we look at the developments
that have happened
from the period of 2005 to 2015,
in these 10 years,
we have moved from a case
where we knew very little
about the genetics or complex traits
and common diseases, to knowing
in excess of 4,000 specific positions
in the human genome
that have been found to be associated
with the severity of a condition
or with the onset of a particular condition.
1:24
Now when we think about infectious diseases,
there has been similarly a lot of discoveries
that have been made.
So for example,
there have been identifications
of particular genetic polymorphisms
that protect or are associated
with malaria in the West Africa,
in the Gambia as well as in Ghana,
which uses data from the Gambia
as an add-on
to improve the statistical power to identify
the loci for severe malaria in Ghana.
Now, this was similarly the case in dengue
where again using
a genome-wide association design,
that we have been identifying
genetic polymorphisms
that confers higher risk,
or conversely a protection effect
against dengue as well as
enteric fever and tuberculosis.