Transcript Strong Heart Family Study Phase VI Genetics Center March

Strong Heart Family Study
Phase VI Genetics Center Aims
October 8, 2009
Overview of genetics presentation
• Progress
– Both from the SHFS Phase V and from
relevant ancillary studies
• Discussion of Genetics Aim
– Capitalize on progress and new screening
procedures
– Data from ongoing studies will solidify which
loci are fine mapped and proposed for further
investigation in Phase VI.
– Will consider adjusting approaches as
technologies change.
Progress
Despite the lack of genome-wide SNP data, we
still have significant progress to follow-up
using state-of-the-art approaches
• In Phase V, the genetics center has had 14
published or in press manuscripts, has 5
manuscripts in the journal submission process,
and has published/presented 18 abstracts.
Progress continued
• Ancillary studies/collaborations
– CALiCo/PAGE – NHGRI consortium to characterize
population- and environmental- specific effects on
GWAS-identified functional SNPs
• not all GWAS results replicate in all population subgroups,
including American Indians, demonstrating the need to
consider population differences and therefore the continued
need for studies such as the SHFS
• Gene localization
– Have unique QTLs, some related to preclinical
markers, identified through linkage and confirmed by
follow-up association analysis in SHFS
Linkage/association progress:
candidates for sequencing follow-up
Trait w QTL in SHFS
Heart rate
presence or absence of
plaque
bilirubin
Candidate Gene (s)
Association
Replication
KIAA1797
Expression correlated with HR in
Mexican Americans of SAFHS
>1 Mb away from GWAS SNPs
22
TXN2 ?
Novel locus
2
UGT1A1
Replicates Framingham and others,
but evidence for additional novel variation
Chr
9
diastolic blood pressure
10
FANK1
Possibly other QTLs
Uric acid
11
SLC22A12
Novel locus
LVM
12
> 2,000 SNPs being
analyzed
Dominican families
BMI
4
IRF2, ENPP6,
LOC442120; Additional
Novel locus, gene poor region
association analyses
ongoing
BMI/obesity
7
> 2,000 SNPs being
analyzed
Replicates reports from multiple populations
Phase VI: Specific Aim 1
• To identify the genetic polymorphisms that
are responsible for variation in phenotypic
risk factors for obesity, diabetes and
preclinical and clinical CVD
– Genotyping
– DNA sequencing
– Gene expression
– Gene x environment
This will be presented in 3 sub-aims
Genetics: Specific Sub Aim 1
Identify the functional variant(s) responsible for one or
more of our linked and associated loci
(Additional fine mapping of QTLs & linkage analysis of new
phenotypes)
Applies state-of-the-art sequencing technologies to
follow-up promising results and ongoing efforts
Genetics: Specific Sub Aim 1
Identify the functional variant/polymorphism(s) responsible for one or
more of our linked and associated loci
•
Using flexible, high-density NimbleGen microarrays to capture any
desired fraction of the human genome for ultra high-throughput
sequencing (Illumina Genetic Analyzer, or “Solexa”) for
polymorphism and rare variant identification
- Up to 5Mb analyzed at one time in 40 to 50 participants
- Individuals chosen from families showing linkage and
representing those with and without the associated allele or
haplotype.
- Technique being established in house
•
Genotyping and association analyses using all identified variation,
including rare variants
- Infinium iSelect, thousands of polymorphisms typed
simultaneously
•
Alternative strategy for some loci: Deep sequencing of candidate
genes
- Hundreds of samples sequenced for a targeted gene region
Have two loci worthy of intensive follow-up, but the opportunity exists
for additional loci to become available as our ongoing studies
progress over the coming months.
Genetics: Specific Sub Aim 2
Whole genome gene expression profiling of lymphocytes
collected at the time of liver/abdominal MRI for functional
pathway analysis and confirmation of linked/associated
loci to liver, subQ and abdominal fat phenotypes
Capitalizes on proposed MRI scans
Genetics: Specific Sub Aim 2
Whole genome gene expression analysis (microarrays) of lymphocytes
collected at the time of liver/abdominal MRI for functional pathway
analysis and confirmation of linked/associated loci to liver, subcutaneous
and abdominal fat phenotypes
•
Lymphocytes chosen as an easily-available tissue for a geneticepidemiological study
•
Discovery and candidate gene association studies
– Select ~250 cases, 250 controls based on extent of fat infiltration of
liver and size of abdominal and subcutaneous fat depots
– Use correlation analysis to identify genes that are up and down
regulated
– Use pathway analysis to discover gene pathways that are
coordinately up and/or down regulated, and to identify genes that
may not be expressed in lymphocytes but are part of pathway
– Use data available from collaborations to identify likely cisregulated genes (SAFHS, baboons, NAFLD study)
– Perform association analysis between genetic variation in promoter
regions of cis-regulated genes in pathway with CVD-related
phenotypes
Genetics: Specific Sub Aim 2 (cont.)
•
Gene identification
– Discovery through linkage/association
analysis on new liver/fat phenotypes (nonexpression)
– For our linked and associated loci to liver/fat
phenotypes, use expression levels to assist in
gene discovery or pathway completion (such
as was done with the heart rate QTL).
• Confirmation of individual expression results
can be done using remaining samples
(TaqMan)
Genetics Specific Sub Aim 3
Refined analyses of existing loci (linked and associated
variants and putative functional variants), incorporating
GxE and/or longitudinal analyses.
Capitalizes on environmental measures (including stress
response from the proposed cold pressor test) and the
rich longitudinal dataset of the SHFS as well as the
Cohort Study.
Genetics: Specific Sub Aim 3
Refined analyses of established loci (linked and associated variant
and putative functional variants), incorporating GxE and/or
longitudinal analyses
•
Will address variant/polymorphism specific questions
•
Types of environmental factors: dietary components, stress,
physical activity parameters, sex, smoking, etc.
– Example: The effect of a heart rate variant may be altered in
individuals who are more susceptible to stress as indicated by
the cold pressor test.
•
Longitudinal data: progression to diabetes, weight gain, change in
BP, etc.
– Example: The effect of a variant on plaque development may
be altered in those who progress, or don’t progress, to diabetes
•
Cohort samples will be genotyped to allow studies in both the
Family Study and Cohort samples.
– Increases longitudinal dataset and available environmental
phenotypes