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New Technology for Human Genetics

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New Technology for Human Genetics. Stanley F. Nelson, MD. Professor. Department of Human Genetics. David Geffen School of Medicine at UCLA. Common Diseases ... – PowerPoint PPT presentation

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Title: New Technology for Human Genetics


1
New Technology for Human Genetics
  • Stanley F. Nelson, MD
  • Professor
  • Department of Human Genetics
  • David Geffen School of Medicine at UCLA

2
Common Diseases
  • Inherited combinations of common alleles each
    with a modest effect combine in that are unique
    and lead to increased risk of disease likely
    with environmental factors
  • Millions of differences
  • Between any two unrelated
  • Humans which ones
  • Change risk?

3
Genome-wide SNP analysis
A60 B40
A50 B50
4
Can now look everywhere in the genome for many
different diseases
5
1M
500K
300K
100K
6
Direct to consumer genetic testing
Disclosure S. Nelson is on the Scientific
Advisory Board of 23andme
7
Personal risk profile at the type 2 diabetes
genes
8
What is good
  • More and personally relevant information
    provided changes perspective of individual risk
  • Motivation to see world of potential diseases and
    possible behavioral changes will this motivate
    us to take some disease areas more seriously?
    This affects me more? This disease is common
    and I ought to watch my weight
  • New genetic information can be interpreted new
    literature finding will motivate greater
    attention on genetics.
  • Broader involvement in genetics will increase our
    public understanding, appreciation of genetics.

9
What is missing?
  • Most of the genetic risk is not currently known
    typical estimates of 2-25
  • Identified genes have small risk
  • How do we combine the risk alleles
  • Much of the disease risk is environmental
  • How do we combine the environmental information
    with the genetic information

10
Autism Example
  • Is not one disease but a group of diseases each
    with a rare and mostly genetic cause
  • Progress is impeded by lack of sufficiently large
    samples

11
Can we obtain a sufficient Autismsample
(20,000)?
  • Possible now with Direct saliva DNA Collection
  • Web based patient assessment
  • Cost effective and feasible to genotype tens of
    thousands of affected children to identify the
    root causes
  • Register at www.ianproject.org

12
Cancer example
  • Genetic disease (100)
  • Most is somatic mutations occurring in brain
    cells that lead to brain cancer, but does not
    increase chances of brain cancer in your children
  • Complete genome sequencing permits identification
    of mutations in all genes

13
Spectrum of mutations is highly diverse in human
cancers
Cancer Types
genes
14
Even within brain cancers pattern is very diverse
Genes
Brain Tumor Samples
15
Some Brain tumors mutate many genes
Genes
Brain Tumor Samples
16
Some genes are more commonly mutated in brain
cancers
Genes
Brain Tumor Samples
17
Whole genome sequencing prospects
  • Human Genome Project Used ABI capillary
    sequencers capable of 2.8 million bases per day.
    Community set up hundreds of machines and in
    about one year generated most of the data that is
    now known as the reference sequence of the human
    genome estimated costs to sequence next genome
    30 million, 30 machines, 1-2 years.
  • Next generation sequencing Illumina/ABI Single
    machine generates up to 3 BILLION bases per day.
    1000x speed and much reduced costs 30,000, one
    machine in 6 weeks.

18
Whole genome sequencing prospects
19
Whole genome sequencing
  • Will whole genome individual sequencing be
    possible?
  • Yes Further improvements reasonable to expect
    under 5,000 whole genome sequencing possible in
    under two years.
  • Will whole genome individual sequencing be cost
    effective?
  • Depends on who is paying.
  • Will whole genome sequencing be worthwhile?
  • Yes fantastic resource for gene function
    discovery
  • Incidental findings previously unknown serious
    disease risk discovered Good if preventive care.
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