Alzheimer's disease (AD) is a complex neurodegenerative disorder. Circulating miRNAs hold great promise in the discovery of non-invasive and novel biomarkers for AD diagnosis and prognosis. This slideshow presents the role of miRNAs in AD and details current progress in biomarker discovery. Various tools for pathway-focused and genome-wide miRNA expression profiling, miRNA functional studies and target identification are also included.

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Circulating Biomarkers for Alzheimer’s Disease
Ali Bierly, Ph.D.
allison.bierly@qiagen.com
Molecular Mechanisms of Neurodegeneration 1
Welcome!
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Welcome to our three-part webinar series on neurodegeneration
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Neurodegenerative disorders: molecular
mechanisms and circulating biomarker discovery –
a three-part webinar series
 Part 1: Molecular Mechanisms of Neurodegeneration
 Part 2: The Central Roles of Non-coding RNAs in Neurodegenerative
Disorders
 Part 3: Circulating Biomarkers for Alzheimer’s Disease

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Legal disclaimer
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 QIAGEN products shown here are intended for molecular biology
applications. These products are not intended for the diagnosis,
prevention or treatment of a disease.
 For up-to-date licensing information and product-specific
disclaimers, see the respective QIAGEN kit handbook or user
manual. QIAGEN kit handbooks and user manuals are available
at www.QIAGEN.com or can be requested from QIAGEN
Technical Services or your local distributor.

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Recent Alzheimer’s disease miRNA biomarkers4
Agenda
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Alzheimer‘s disease1
Biomarkers for detecting diseases2
miRNA as biomarker signatures3
QIAGEN tools for biomarker discovery5

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Alzheimer’s disease
 Chronic neurodegenerative disease affecting 21–35 million people worldwide
 Most common cause of dementia
 Early symptoms often mistaken for normal aging
 Four stages of AD:
Pre-dementia
MCI – Mild
cognitive
impairment
(short-term
memory loss,
apathy)
Early
Increased
difficulty with
learning and
memory,
definitive
diagnosis
Moderate
Paraphasia,
loss of reading
and writing,
long-term
memory
problems,
behavioral
symptoms
Advanced
Eventual loss of
speech, inability
to perform basic
tasks, apathy
and exhaustion

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Molecular basis for AD
 Mutations in APP, PSEN1, PSEN2 cause
early-onset autosomal dominant AD
 APOE4 e4 allele predisposes to sporadic AD,
but other factors need to be investigated
 Two major protein abnormalities:
 Amyloid plaques (amyloid-beta peptide, a
fragment of APP, and cellular material)
 Neurofibrillary tangles (hyperphosphorylated Tau,
a microtubule-associated protein)
 Neurons and synapses are lost in the
cerebral cortex and some subcortical regions
leading to atrophy
 Inflammation also appears to play a role
Two types of AD: Familial (less than 5%)
and sporadic

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Recent Alzheimer’s disease miRNA biomarkers4
Agenda
7
Alzheimer‘s disease1
Biomarkers for detecting diseases2
miRNA as biomarker signatures3
QIAGEN tools for biomarker discovery5

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Why do we need early Alzheimer’s biomarkers?
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 Current diagnosis combines neuropsychological evaluation, neuroimaging and
Ab and Tau CSF levels, but sensitivity is only ~93% and specificity only ~55%
 Evidence shows that treatment at earlier stages of AD can prevent cognitive
decline, whereas treatment at later stages isn’t as effective. Experiments like the
A4 study (http://www.adcs.org/Studies/A4.aspx) evaluate the efficacy of drugs
before the onset of symptoms
Better biomarkers could provide an early sign before symptoms
start to show, enabling more effective prevention and treatment

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Biomarkers could detect AD before irreversible decline
What types of biomarkers are being investigated in AD?
Plasma phospholipids
(Mapstone, M. et al.
2014, Nat. Med.)
CSF proteins (Tau, amyloid beta)
(Frankfort S.V. et al. 2008, Curr.
Clin. Pharmacol.)
Blood levels of Tau and amyloid
beta (Frankfort S.V. et al. 2008,
Curr. Clin. Pharmacol.)
microRNA levels in the
blood
Possible AD
biomarkers

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Circulating biomarkers in neurodegenerative disease
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 Benefits of circulating biomarkers:
 Some samples, like CSF, can be painful to
collect. Blood samples are less invasive and
can be drawn regularly.
 Circulating biomarkers identified in
neurodegenerative disorders:
 AD: amyloid beta, Tau, low mtDNA, p21, p53
 MS: serum lactate
 PD: alpha-synuclein, HNF4A & PTBP1 mRNA,
SRRM2 (RNA splicing factor)
Biomarker
“A characteristic that is objectively
measured and evaluated as an
indicator of normal biological
processes, pathogenic processes, or
pharmacologic responses to a
therapeutic intervention.”
1998, NIH Biomarkers Definitions
Working Group

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Recent Alzheimer’s disease miRNA biomarkers4
Agenda
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Alzheimer‘s disease1
Biomarkers for detecting diseases2
miRNA as biomarker signatures3
QIAGEN tools for biomarker discovery5

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microRNAs in gene regulation
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miRNAs
 Small non-coding RNAs, 18–25 nt
 Found in animals, plants and some viruses
 Base-pair with complementary mRNA sequences
in the 3’ UTR, resulting in silencing by either
degradation of the strand or prevention of
translation
 A single miRNA can regulate up to 200 mRNAs,
and several miRNAs can target the same mRNA
 Involved in normal biological processes like
inflammation, apoptosis and development
 Implicated in numerous disease states, including
cancer, heart disease and nervous system
disorders

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microRNAs in circulation
Shielded in exosomes or bound to Argonaute2 or HDL, miRNAs can be stable in blood and,
therefore, a suitable candidate for circulating biomarkers

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microRNAs as biomarkers in CNS disorders
Small molecules with a substantial impact
 Several miRNAs are involved in normal neurological development, including miR-124-
3p, miR-125b-5p, miR-132-3p, miR-134, miR-138-5p and miR-9-5p. miRNAs are highly
expressed in brain and spinal fluid
 Circulating miRNA biomarker signatures are being investigated in many
neurodegenerative diseases, such as:
 Alzheimer’s disease: (to be discussed later in the presentation)
 Parkinson’s disease: miR-331-5p, -1826, -450b-3p, -626, -505
 Amyotrophic lateral sclerosis (ALS): in leukocytes, miR-451, miR-1275, miR-328
and 5 others were identified as potential candidates
 Huntington’s disease: possibly miR-34b

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Techniques for detecting microRNA in blood
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 qPCR
 Focused profiling of pathway-related miRNAs
 Whole miRNome profiling of all known miRNAs
 Individual assays
 Next-generation sequencing
 Can detect currently-unknown miRNAs
 Results can then be verified with qPCR or microarray
 Microarray
Basic structure of a microRNA biomarker discovery study:
Screen for miRNAs
differentially expressed
between disease and
control
Verification of signature
by another technique or
in another cohort
Determine which
genes and pathways
are being targeted

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Recent Alzheimer’s disease miRNA biomarkers4
Agenda
16
Alzheimer‘s disease1
Biomarkers for detecting diseases2
miRNA as biomarker signatures3
QIAGEN tools for biomarker discovery5

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Identifying miRNA signatures in AD
 Leidinger et al. (2013) A blood based 12-miRNA signature of Alzheimer disease
patients. Genome Biology 14, R78.
 Identified a new AD miRNA biomarker signature by NGS and verified with miScript
Primer Assays
 Kumar et al. (2013) Circulating miRNA biomarkers for Alzheimer’s disease. PLOS
One 8, e69807.
 Used Nanostring technology to identify a circulating miRNA biomarker signature
and elucidated the neurology-related pathways involving genes targeted by these
miRNAs using Ingenuity Pathway Analysis (IPA) software
Literature examples

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Study 1: a 12-miRNA AD signature in blood
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Leidinger et al., 2013
 Goal: to develop a miRNA expression signature specific to Alzheimer’s disease that
could be translated for use in combination with other non-invasive diagnostic techniques
like amyloid load imaging
 Approach:
 Used next-generation sequencing to analyze blood from AD patients and healthy
age-matched controls
 Classified AD and control samples to determine an effective signature for AD
 Verified the signature using qPCR (the miScript system) and non-AD patients with
other neurological disorders
 Predicted miRNA targets using miRDB

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Study 1: a 12-miRNA AD signature in blood
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Results
 NGS results
 Found 140 unique mature miRNAs that were significantly altered between AD
patients and normal controls (58 downregulated, 82 upregulated)
 Found 15 novel miRNAs upregulated in AD (brain miRNAs)
 Families heavily represented: miR-30 (5 miRNAs upregulated), let-7 (9
downregulated)
 Selected 12 miRNAs specific to AD to form the final signature
 qPCR verification
 Ten of the 12 showed dysregulation in the same direction by NGS and qPCR
 No stage dependence – mild and moderate AD groups were both equally identified
using the signature
 The signature also distinguished major depression, schizophrenia and bipolar
patients from controls, but was only about 75% accurate at distinguishing AD from
Parkinson’s, MS and the psychological disorders, so it may need to be refined for
that purpose
 Target prediction
 Target genes were enriched in nervous system development and neuron projection

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Study 2: a 7-miRNA signature for AD
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Kumar et al., 2013
 Goal: develop a signature that could someday translate to the clinic not only in
diagnostics, but also in patient stratification for drug trials and monitoring patient
response to the treatment.
 Approach:
 Profiled 654 miRNAs from 11 AD patients and 20 controls using NanoString
 Verified the miRNA signature using qPCR
 Verified signature in a different cohort with 20 AD and 17 control samples
 Analyzed targets to identify related biological pathways using Ingenuity Pathway
Analysis (looked at mRNAs targeted by two or more of the signature miRNAs)

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Study 2: circulating biomarkers for AD
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Results
 NanoString results:
 Identified 12 microRNAs with differential expression in AD samples of at least
1.5-fold
 let-7d-5p, let-7g-5p, miR-15b-5p, miR-142-3p, miR-191-5p, miR-301a-3p, miR-323b-
5p, miR-545-3p, miR-563, miR-600, miR-1274a, miR-1975
 qPCR verification:
 Seven of the 12 miRNAs identified by NanoString also showed differential expression
in AD by qPCR assays (let-7d-5p, let-7g-5p, miR-15b-5p, miR-142-3p, miR-191-5p,
miR-301a-3p, miR-545-3p)
 Independent cohort verification:
 Combination of miR-545-3p, let-7g-5p, and miR-15b-5p gave 94.1% specificity and
95% sensitivity.
 Best standalone biomarkers were miR-191-5p, miR-15b-5p and let-7d-5p
 Target analysis
 Axonal guidance signaling, ephrin receptor signaling, actin cytoskeleton signaling,
rhoA signaling, clathrin-mediated endocytosis and others were targeted

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Recent Alzheimer’s disease miRNA biomarkers4
Agenda
22
Alzheimer‘s disease1
Biomarkers for detecting diseases2
miRNA as biomarker signatures3
QIAGEN tools for biomarker discovery5

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QIAGEN tools for circulating miRNA biomarker discovery
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miRNeasy Serum / Plasma
Kit – purifies RNA from 18 nt
upwards (both miRNA and
mRNA)
Employs a spike-in control for
normalization (a C. elegans
miR-39 mimic)
Automatable on the QIAcube
Ingenuity Pathway Analysis
(IPA) – software for analysis,
integration and understanding
of data from gene expression,
miRNA and SNP microarrays,
as well as metabolomics,
proteomics and RNA-seq
experiments
miScript Primer Assays –
quantify any mature human,
dog, rat or mouse miRNA in
miRBase
miScript miRNA PCR Arrays
– arrays of related miRNA
assays arranged by pathway
or disease. miRNome arrays
updated through miRBase
version 21
miScript PreAMP PCR Kit –
preamplifies up to 400 targets
in one reaction for limited
samples
Isolation Data interpretationDetection (qPCR)

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miRNA expression – miScript miRNA PCR Arrays
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 miRNome
 Human: miRBase v21, covers 2,402 primer assays
 Mouse: miRBase v21, covers 1,765 primer assays
 Rat: 653 primer assays
 Dog: 277 primer assays
 Rhesus macaque: 469 primer assays
 Cow: 744 primer assays
 Pathway-focused arrays (over 20 arrays)
 miFinder
 Neurological development and disease
 Neuropathic and inflammatory pain
 Apoptosis
 Cell development and differentiation
 Brain cancers
 Serum and plasma miRNAs
 miScript PreAMP Kit
 Optional step for small or precious samples
 Full miRNome profiling from as little as 1 ng RNA
http://www.qiagen.com/products/catalog/assay-technologies/mirna/miscript-mirna-pcr-arrays
Pre-formatted, single-use PCR arrays with wet lab-verified assays

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Ingenuity Pathway Analysis (IPA)
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Features numerous tools to help interpret complex miRNA data:
 miRNA Target Filter: gives microRNA-mRNA pairings and biological effects using
experimentally verified interactions from TarBase and miRecords, and predicted miRNA-
mRNA interactions from TargetScan
 Pathway analysis, canonical pathways, overlapping pathways, pathway import and
scoring: Helps you determine the most significantly affected pathways
 Network analysis: Build miRNA–mRNA networks

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Thank you for attending
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Thank you for attending today’s webinar!
Contact QIAGEN
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Email: BRCsupport@QIAGEN.com
Questions?
Ali Bierly, Ph.D.
allison.bierly@qiagen.com
For up-to-date licensing information and product-specific disclaimers, see the respective
QIAGEN kit handbook or user manual. QIAGEN kit handbooks and user manuals are available
at www.QIAGEN.com or can be requested from QIAGEN Technical Services or your local
distributor.