Introduction to NIA Genetics of Alzheimer's Disease Data Storage Site

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23 Οκτ 2013 (πριν από 3 χρόνια και 10 μήνες)

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Introduction to

NIA Genetics of Alzheimer's Disease Data
Storage Site


Li
-
San Wang

AD genetics


Genes that affect AD risk may lead to

o
Insight into disease mechanism

o
Therapy targets and preventive measures


APP, PSEN1, PSEN2 mutations lead to early
-
onset AD


APOE was the first gene associated with late
-
onset
AD (1991), explains <20% AD


No other late
-
onset AD genes until genome
-
wide
association studies (GWAS) were introduced



Genome
-
wide association studies

Cost effective
way to screen
genome
-
wide
variability

Compare case and unaffected subjects

Identify genomic
locations that show
difference between
cases and controls

Genetics for AD: Most Recent Progress


GWAS reported 2 new AD genes in 2009


Alzheimer’s Disease Genetics Consortium (ADGC,

PI:
Schellenberg
) led to new discoveries of 4 new AD genes
in 2011








International Genomics of Alzheimer’s Project (IGAP)
reports 11 new loci (unpublished)


New rare variant (TREM2) reported earlier this year












Cost of genomic sequencing is dropping

o
Human
genome project (2000): $3 billion


o
James Watson

s genome (2007): $2 million

o
Current (
2013)
: <
$5,000 (
Illumina
), 600Gb in 11 days

o
Target: sequence a
genome
with <$
1000


Cost of sequencing is going down quickly …

NHGRI

website

… and much faster than decrease in
computing and storage costs

http://
genomebiology.com
/2010/11/5/207

Era of
bigdata

for genetics: Challenges …

Biological
knowledge

Complex
phenotypes

Algorithms

Computing
power

Storage and
transfer

Data
sharing

Path to
therapy and
preventive
measures

Genetic
association
with
biomarkers
and deep
phenotypes

Analyze, manage &
share large


datasets

Use genomic
knowledge to
interpret AD
variants

… and Opportunities for AD genetics
research

NIAGADS


NIA Genetics of Alzheimer’s Disease Data Storage
Site (NIAGADS) was established in 2005 and moved
to Penn in 2009


NIA AD Genetics Data Sharing Plan
:

“…
all
Genetic Data derived from NIA funded studies for the
genetics of late onset Alzheimer’s disease be deposited at
NIAGADS or another NIA approved site or both whenever
possible



NIA
collaborative
research agreement (U24) to
develop a
one
-
stop access portal for AD genetics

NIAGADS Objectives


Enhanced data repository
for sharing complex data
at petabyte scale


Workflows and resources
to assist
the AD research
community


Integrated AD genomics database
to facilitate
access to biological knowledge


Outreach and collaborations

n
iagads.org

User can request account

to receive news alert

Access to data, resources
and other information

Datasets


17 datasets, 35,402 subjects, ~19G genotypes,
more to come


Including a dedicated section for ADGC data

o
15 datasets (6 already deposited), 22,000 subjects


Data submission guidelines on
www.niagads.org

o
Requests
are reviewed
by an independent Data Use
Committee (organized by NIA)

o
Receives decision in 10 business
days


Browse/search on NIAGADS website

Resources


Data analysis software and resources

o
DRAW+SneakPeek

workflow to analyze whole
genome and whole
exome

sequencing using
Amazon Cloud

o
Quality control

information for published GWAS
datasets

o
Genetic imputation
using latest reference panels

DRAW+SneakPeek
:

DNA
-
Seq

analysis
workflow


For small labs with limited
bioinformatics support


$528 for analyzing one
300GB flow cell on Amazon
Cloud in 2 days


Available on
niagads.org

and Amazon Cloud

Alzheimer’s Disease Sequencing
Project (ADSP)


Announced in Feb 2012 by NIH Director Francis
Collins


Will sequence
~12,000 subjects

(genome or
exome
) to discover new AD variants, generating
at
hundereds

of TBs of raw data


NIAGADS serves as the
D
ata
coordinating
center


D
ata
will be
accessible through NIAGADS website


https://www.niagads.org/adsp

NIAGADS and IOA


IOA Pilot Grant was important for receiving the
U24 grant (and other funding)


Penn Alzheimer’s Disease Center (ADC) provides
immediate user feedback


Collaboration with ADC

o
Integrating clinical covariates and biomarkers with
genetic data

o
Adopt
InQuery

to allow clinicians run complex queries

o
Work with ADC genetics core for genetic database


Future collaborations with Penn ADC (and other
ADCs)


Future


Integrated AD genomics database


Complex clinical covariates/phenotypes


Next generation sequencing support (ADSP and
beyond)


Work with ADCs to address needs by the research
community

NIAGADS Team

Amanda
Partch


Daniel
Laufer

Micah
Childress




Otto
Valladares


Li
-
San
Wang

Chiao
-
Feng

Lin

Thanks to


Penn Institute on Aging


Penn
ADC and CNDR

o
John
Trojanowski

o
Virginia Lee

o
Vivianna

Van
Deerlin

o
Young
Baek

o
Rui

Tong


Gerard
Schellenberg

lab


Chris
Stoeckert

lab
(PCBI)





NIA

o
ADC Program

o
ADGC

o
NCRAD

o
NACC


ADSP

o
NHGRI

o
CHARGE

o
Large scale sequencing
centers

o
dbGaP
/SRA


NIAGADS is funded by
U24
-
AG041689