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              Printable Handouts
Navigable Slide Index
- Introduction
- Genetic epidemiology, 2005 onwards
- Genome-wide association analyses, 2005 onwards
- The advantages of genome-wide association
- Genome-wide association studies (GWAS)
- Published genome-wide associations
- Cumulative number of obesity susceptibility loci
- Results of latest GWAS for BMI
- GWAS results for WHRadjBMI
- Further insight into GWAS for BMI
- Effect size of 32 BMI loci (white adult Europeans)
- ‘Adult’ BMI loci do not influence birth weight
- ‘Adult’ BMI loci influence childhood BMI
- Life course effects of the FTO and near MC4R loci
- Cumulative effects attenuated by healthy lifestyle
- Explained variation and predictive value is limited
- From common loci to causal/functional gene/variant
- BMI-associated loci; food intake regulation
- WHRadjBMI-associated loci; peripheral pathways
- Is FTO the obesity gene? (1)
- Is FTO the obesity gene? (2)
- GWAS for body fat percentage
- Body fat percentage accurately assesses adiposity
- Near-IRS1 locus & measures of body composition
- The near-IRS1 locus and disease risk
- The near-IRS1 locus and fat distribution (CT data)
- The near-IRS1 locus & functional implications
- The near-IRS1 locus (summary)
- Conclusion: GWAS
- Future research: low-frequency rare variants
- Overall conclusion and summary
Topics Covered
- Obesity and genome-wide association (GWAS)
- GWAS for body-mass index
- The obesity gene
- GWAS for body-fat percentage
- The near-IRS1 locus
- Future research
Links
Series:
Categories:
Therapeutic Areas:
Talk Citation
Loos, R. (2015, November 30). Genetic epidemiology of obesity 2 [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved October 31, 2025, from https://doi.org/10.69645/NQMZ6130.Export Citation (RIS)
Publication History
- Published on November 30, 2015
Financial Disclosures
- Prof. Ruth Loos has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Genetic epidemiology of obesity 2
                  Published on November 30, 2015
                  
                    
                      
                        
                      
                    
                  
                  
                    37 min
                
              Other Talks in the Series: Obesity: Science, Medicine and Society
Transcript
Please wait while the transcript is being prepared...
      
      
        
                  0:04
                
                
                  
                    Moving on to a new era,
it's 2005.
                  
                    So in 2005
there was a major change.
                  
                    And again, that change
was driven through
                  
                    advances in technology.
                  
                
              
                  0:16
                
                
                  
                    In 2005,
                  
                    the genome-wide association
approach was introduced
                  
                    and genome-wide association
                  
                    as oppose to
genome-wide linkage
                  
                    allows you to identify
more exact chromosomal locations
                  
                    because you can screen
a genome with higher resolution.
                  
                
              
                  0:34
                
                
                  
                    Genome-wide association
is also hypothesis generating
                  
                    but it has a much
higher resolution
                  
                    than genome-wide linkage.
                  
                    It's always designed
as a two-stage design
                  
                    as opposed to
genome-wide linkage.
                  
                    It has a discovery stage
and whatever is discovered
                  
                    needs to be replicated
within the same study.
                  
                    And I'll come back to that
in the next slide.
                  
                    And genome-wide
association studies
                  
                    turn out to have
large sample sizes.
                  
                    And the reason for that
is that very early on
                  
                    genome-wide association
studies were very expensive.
                  
                    The chips that where designed
to do these genotyping
                  
                    were extremely expensive,
so people realized that
                  
                    to get a return
on their investment
                  
                    they needed to collaborate.
                  
                    And that has lead to currently
                  
                    very large collaborations
in large consortiums.
                  
                    Genome-wide
association is the result
                  
                    of advances in technology.
                  
                    Predominately the advances
in the genotyping technology
                  
                    which allowed to generate
                  
                    catalogues
of genetic variation.
                  
                    And I'm showing you
a few pictures
                  
                    of the Human Genome Project,
the HapMap project,
                  
                    the 1000 genomes project.
                  
                    These are projects that
have generated catalogues
                  
                    of genetic variations
throughout the year.
                  
                    So the Human genome project
was the oldest
                  
                    and then international HapMap
and 1000 genomes are more recent
                  
                    and more complete ones.
                  
                    But these catalogues
have allowed companies
                  
                    to develop these high-throughput
genotyping SNP chips.
                  
                    You see these pictures
of these chips
                  
                    that allow you to genotype
hundreds, thousands,
                  
                    up to millions of variants
in a very short time period.
                  
                
              