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Alzforum webinar discussion
Jeremy Miller
23 May 2013
Advances of “Integrated Systems…” over many
network studies of dementia
• Large sample size (N>500) produces high-
confidence co-expression measurements.
• Extensive characterization of brain pathology
allows modules to be better associated with
Alzheimer’s disease.
– Pre-mortem assessments of cognitive and
neuropsychiatric impairment (i.e., MMSE, NPI)
are also ideal.
• Concurrent SNP genotyping of samples
leads to causal (directed) rather than
correlational (undirected) networks.
Experimental design
1) Obtain post mortem human hippocampi
from 16 control and 16 AD patients
2) Extract RNA from CA1/CA3 of frozen
hippocampal sections using microscope-
aided dissection
3) Run Illumina microarrays from the RNA
4) Analyze the data using differential
expression and co-expression analysis
*Experiment was performed in
the lab of Dr. Dan Geschwind
AD is a disease of many brain cell types
0.5
0.75
1
1-TO
We performed a network analysis (WGCNA)
on these samples and found several modules
associated with cell type.
A neuronal module shows decreased expression
with AD in CA1 and CA3.
An astrocyte module shows increased
expression with AD in CA1 and CA3.
An oligodendrocyte module is unchanged with
disease, but show increased expression with age
in control.
A microglia module shows increased expression
with increased NFT burden in controls.
Microglia / inflammation markers as an early sign of AD
This microglial module
was a subset of ~400 genes
that showed significantly
increased expression with
NFT burden in controls.
TYROBP is the top hub
gene in this module based
on co-expression!
Many of these hubs
(including TYROBP) are
upregulated in
neurofibrillary tangle-
bearing neurons relative to
non-tangle-bearing neurons
in entorhinal cortex
(Dunckley et al 2006).
These results are consistent with TYROBP as an important
microglial gene, and with microglia playing an important
role in early AD pathogenesis, potentially associated with
NFTs in addition to amyloid pathologies.
Acknowledgements
UCSF:
Mike Oldham
UCLA:
Dan Geschwind
Steve Horvath
Jeff Goodenbour
Peter Langfelder
Geschwind Lab
Oregon Health Sciences University:
Randy Woltjer
Patti Kramer
Jeff Kaye
NRSA (Award #F31 AG031649)
Neurobehavioral genetics training program
Oregon Alzheimer’s Disease Center
Human Brain and Spinal Fluid Resource Center
Funding:
Tissue:
Data discussed will soon be available in:
Jeremy A Miller, Randall L Woltjer, Jeff M Goodenbour,Steve Horvath, and
Daniel H Geschwind, "Genes and pathways underlying regional and cell
type changes in Alzheimer's disease." Genome Medicine 2013: In Press.

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Alz forumslides jam2

  • 2. Advances of “Integrated Systems…” over many network studies of dementia • Large sample size (N>500) produces high- confidence co-expression measurements. • Extensive characterization of brain pathology allows modules to be better associated with Alzheimer’s disease. – Pre-mortem assessments of cognitive and neuropsychiatric impairment (i.e., MMSE, NPI) are also ideal. • Concurrent SNP genotyping of samples leads to causal (directed) rather than correlational (undirected) networks.
  • 3. Experimental design 1) Obtain post mortem human hippocampi from 16 control and 16 AD patients 2) Extract RNA from CA1/CA3 of frozen hippocampal sections using microscope- aided dissection 3) Run Illumina microarrays from the RNA 4) Analyze the data using differential expression and co-expression analysis *Experiment was performed in the lab of Dr. Dan Geschwind
  • 4. AD is a disease of many brain cell types 0.5 0.75 1 1-TO We performed a network analysis (WGCNA) on these samples and found several modules associated with cell type. A neuronal module shows decreased expression with AD in CA1 and CA3. An astrocyte module shows increased expression with AD in CA1 and CA3. An oligodendrocyte module is unchanged with disease, but show increased expression with age in control. A microglia module shows increased expression with increased NFT burden in controls.
  • 5. Microglia / inflammation markers as an early sign of AD This microglial module was a subset of ~400 genes that showed significantly increased expression with NFT burden in controls. TYROBP is the top hub gene in this module based on co-expression! Many of these hubs (including TYROBP) are upregulated in neurofibrillary tangle- bearing neurons relative to non-tangle-bearing neurons in entorhinal cortex (Dunckley et al 2006). These results are consistent with TYROBP as an important microglial gene, and with microglia playing an important role in early AD pathogenesis, potentially associated with NFTs in addition to amyloid pathologies.
  • 6. Acknowledgements UCSF: Mike Oldham UCLA: Dan Geschwind Steve Horvath Jeff Goodenbour Peter Langfelder Geschwind Lab Oregon Health Sciences University: Randy Woltjer Patti Kramer Jeff Kaye NRSA (Award #F31 AG031649) Neurobehavioral genetics training program Oregon Alzheimer’s Disease Center Human Brain and Spinal Fluid Resource Center Funding: Tissue: Data discussed will soon be available in: Jeremy A Miller, Randall L Woltjer, Jeff M Goodenbour,Steve Horvath, and Daniel H Geschwind, "Genes and pathways underlying regional and cell type changes in Alzheimer's disease." Genome Medicine 2013: In Press.