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Genetic biomarkers in Dementias
Christos Kroupis, MSc, PhD, EuSpLM
Asst. Prof. Clinical Biochemistry and Molecular Diagnostics
Attikon University General Hospital
Medical School, National and Kapodistrian University of Athens
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Talk topics
Dementias
Genetic markers
in Peripheral blood:
Alzheimer’s disease (AD) genes
ApoE genotyping
Frontotemporal Dementia (FTD) genes
in CSF and plasma:
miRNAs
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Dementias
Four most common types of dementia:
Alzheimer’s disease Lewy-body dementia
Frontotemporal dementia (FTD)
Vascular dementia
Other causes of cognitive impairment:
Parkinson’s disease (PD), Creutzfeldt-Jakob Disease, Wernicke-
Korsakoff syndrome, Normal-pressure Hydrocephalus (NPH) etc
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Genetic markers for AD
Karch CM and AM Goate “Alzheimer's disease risk genes and mechanisms of disease
pathogenesis” Biol. Psychiatry (2015), 17, 43-51
Early-onset (5%) Late-onset (95%) Julianne Moore (“Still Alice”)
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APOE GENE 19q13.2
E3 wt
Ε3/Ε3
Ε3/Ε4
Ε2/Ε3
Ε2/Ε4
Ε4/Ε4
Ε2/Ε2
Wu L. and L. Zhao “ApoE2 and AD: time to take a closer look” Neural Regen Res (2016) 11, 412–3
ApoE4 is present in about 20% of most populations; however, goes up to 40-50% of AD patients
4 helices
in N-term
(LDL-R, LPR, SR-BI)
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APOE isoforms in AD
APOE4 confers greater AD risk in women
Altman A. et al., “Sex Modifies the APOE-Related Risk of Developing Alzheimer's Disease”
Ann Neurol (2014), 74, 563-74
ApoE is expressed in astrocytes and microglia cells in brain
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FDA approved APOE testing
DTC (direct-to-consumer testing) from saliva DNA
Odds ratio for developing AD
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APOE carriers site: https://www.apoe4.info/wp/
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-dF1/dT (530 nm)
-dF2/dT
(640 nm)
dbSNP rs429358
E4 allele
C112R
dbSNP rs7412
E2 allele
R158C
APOE GENOTYPING: Real-time PCR MELTING CURVE
LightMix (Roche)
CE-IVD Kit
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HhaI digest
APOE GENOTYPING: PCR – RFLP
Hixson J.E. and D.T. Ve rnier “Restriction isotyping of human APOE by gene amplification and cleavage with HhaI” J Lipid Res (1990), 31, 545-8
Confirmation method
EQAs important
ISO15189
accreditation
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FrontoTemporal Dementia (FTD)
bvFTD SD
PPA (PNFA)
LPA
PSP
CBS
Primary
Progressive
Aphasia
behavioral (frontal) variant
FTD-MND (Motor Neuron Disease)
FTD/ALS
FTDP
-17
Josephs KA. Frontotemporal dementia and related disorders: deciphering the enigma. Ann Neurol 2008;64: 4-14
Kertesz A, et al. The evolution and pathology of frontotemporal dementia. Brain 2005;128: 1996-2005
Semantic
Logopenic
Progressive
Supernuclear
Palsy
Cortico-
Basal
Syndrome
Amyotrophic Lateral Sclerosis
either familial (30-50%) or sporadic, as common as Alzheimer's in
people<65 years old (majority of cases between 45 – 64 y)
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FrontoTemporal lobar
Degeneration (FTLD) Anatomy
FTLD-TAU FTLD-U
[ubiquitin(+)]
FTLD-TDP
FTLD-FUS
FTLD-UPS
[ATYPICAL
TDP(- )/
FUS(-)]
Histology (IHC) +
Goedert M, et al. FTD: implications for understanding Alzheimer disease. Cold Spring Harb Perspect Med 2012;2: a006254
Rohrer JD. Structural brain imaging in frontotemporal dementia. Biochim Biophys Acta 2012;1822: 325-32
Rabinovici GD and Miller BL. FTD: epidemiology, pathophysiology, diagnosis and management. CNS Drugs 2010;24: 375-98
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Genetic markers for FTD
MAPT FTLD-TAU FTLD-TAU
GRN
C9orf72 FTLD-TDP
TARDBP
VCP
FUS FTLD-FUS
CHMP2B FTLD-UPS
SQSTM1
TMEM106B
SQSTM1 ΣΠΑΝΙΕΣ ΠΕΡΙΠΤΩΣΕΙΣ
PSEN1, PSEN2
PRNP
FTLD-TAU
FTLD-TDP
FTLD-FUS
FTLD-UPS
GENES PROTEINOPATHY
rarely
Takada LT. “The Genetics of Monogenic Frontotemporal Dementia” Dementia & Neuropsychologia (2015), 9: 219-29
Goldman JS, et al., “Frontotemporal dementia: genetics and genetic counseling dilemmas” Neurologist (2004),10, 227-34
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FTD Diagnosis
MRI
PET /
SPECT
NEURO-
PSYCH
OLOGY
CSF
PLASMA
SERUM
FTLD-TAU PiD MAPT
Non-classified
cases
Type A GRN
FTLD-TDP Type D VCP
TARDBP
Types A/B C9orf72
Non-classified
cases
FTLD-FUS aFTLD-U FUS
FTLD-UPS CHMP2B
Histopathology Subtypes Related genes Clinical phenotypes
bvFTD, FTDP-17, PNFA, SD, CBS,
PSP, FTD/MND (ALS)
bvFTD, FTDP-17, PNFA, CBS
bvFTD, FTD/MND(ALS), SD, CBS
bvFTD, FTD/MND(ALS), SD, CBS
bvFTD, FTD/MND(ALS)
bvFTD, FTD/MND(ALS)
bvFTD, FTD/MND(ALS), PNFA
GENE
TESTING
Snowden J, et al. Frontotemporal lobar degeneration: clinical and pathological relationships. Acta Neuropathol 2007;114: 31-8
Warren JD, Rohrer JD, Rossor MN. Clinical review. Frontotemporal dementia. BMJ 2013;347: f4827
Benussi A, et al. Phenotypic Heterogeneity of Monogenic Frontotemporal Dementia. Front Aging Neurosci 2015;7: 171
Neary D, et al. Frontotemporal dementia. Lancet Neurol 2005;4: 771-80
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C9orf72 gene (9p21.2)
Toxic RNA
(G-quadruplexes)
Dipeptide Repeat
Toxic peptides
(Gly-Ala, Gly-Pro, Gly-Arg)
Repeat
Associated
Non-ATG
translation
Unknown function
Hexanucleotide repeat
Taylor, J.P. et al., Nature (2016) e539, 197–206)
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C9orf72 assay
DeJesus-Hernandez M. et al., “Expanded GGGGCC Hexanucleotide Repeat in Noncoding
Region of C9ORF72 Causes Chromosome 9p-Linked FTD and ALS” Neuron (2011), 72, 245-56
Repeat-primed PCR
Fragment analysis
Long PCR
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MICROTUBULE ASSOCIATED PROTEIN TAU
GENE (MAPT) 17q21.31
Wang JZ, Gao X, Wang ZH. “The physiology and pathology of microtubule-associated
protein tau” Essays Biochem (2014),56, 111-23
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Tau hyperphosphorylation
Mazanetz MP and PM Fischer “Untangling tau hyperphosphorylation in drug design for
neurodegenerative diseases” Nature Reviews Drug Discovery (2007), 6, 464–79
Paired
Helical
Filaments Neurofilament Tangles
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MAPT mutations
Iqbal K. et al., “Tau and neurodegenerative disease: the story so far” Nature Reviews
Neurology (2016), 12, 15–27
MAPT mutations in 3-14% FTD pts (9-38% / 50% in familial cases and 0-3% in
sporadic cases)
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GRANULIN GENE (PGRN) 17q21.31
Nguyen AD, et al. “Progranulin: at the interface of neurodegenerative and metabolic diseases”
Trends Endocrinol Metab (2013), 24, 597-606
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PGRN mutations
Gass J. et al., “Progranulin: An emerging target for FTLD therapies” Brain Res (2012),
1462, 118-28
PGRN Mutations in 1-16% of FTD pts (7-28% in familial cases and 1-4% in sporadic cases)
Mutations lead to haploinsufficiency (50% of PGRN activity)
Progranulin neurotrophic agent that acts along with its receptor
(SORT1) for protein lysosome transfer and degradation
Worst FTD prognosis
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PGRN exon 3 screening
* Frameshift mutation: c.264delG, E88fs
• Female FTD patient, 63 years, with family PD history (father)
• Hasn’t been reported before (FTD MOLGEN mutation database)
http://www.molgen.ua.ac.be/ADMutations/
HRMA
in Rotor
Gene
DNA
Seq
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PGRN exon 12 screening
* Missense variant: c.G1445A (p.C482Y)
• SD male
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MAPT gene exon 13 screening
* Missense mutation: c.2092G>A, p.V698I
• CBD female 59 years, no family history
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DNA Sequencing
Sanger: NGS (Next Generation Sequencing)
or Massive Parallel Sequencing:
Whole Genome Sequencing (WGS)
3 billion nucleotides
Whole Exome Sequencing (WES)
30 million nucleotides
(1-2% of whole genome)
Targeted sequencing
(100-200 genes)
Per genomic area:
4 runs per gel or per 1 capillary
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NGS Steps Blood or tissue
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Adding barcodes/adaptors
Potential for massive parallel sequencing of many different
samples altogether (e.g. 10-50 samples): each one with its
unique «barcode» nucleotide sequence (Tags 1 και 2) e.g.
Sample 1: ACTACCAGTG
Sample 2: TTGCAGTAAC
Sample 3: GGCATACTGA
……..
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NGS Steps #2
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Obtaining info in NGS
Image capture
per nucleotide
addition cycle
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Sequence alignment
Validated bioinformatics software necessary for analysis
Barcodes
hg19
(Human Genome
version 19)
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Base calling in NGS: Mutation or
polymorphism detection
Coverage 23x (reads):
11 G’s (48%) and 12 A’s (52%) → Heterozygosity G/A
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NGS collaboration for FTD in Greece
Frontotemporal dementia spectrum: first genetic screen in a Greek cohort (submitted)
familial (n=46) and
sporadic (n=57) cases
TARDBP p.Ile383Val in 3 patients (1 bvFTD, 2 svPPA)
2nd Neurology
Dept.
Attikon
General
University
Hospital
(Assoc. Prof.
S. Papageorgiou)
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Biogenesis of miRNAs Small, non-coding RNA, 22 nt (mature miRNAs)
DGCR8: Di
George
Critical
Region 8
TRBP: Transactivator
RNA
Binding
Protein
RISC: RNA-
Induced
Silencing
Complex
Passenger miRNA
(leading)
Majority of
miRNAs in regions
between genes
(60%), the rest in
gene introns
6% of human miRNAs
are processed by
RNA editing
(IsomiRs)
Kuzhandai Velu V. et al., Journal of Clin and Diagn Res (2012), 6, 1791-95
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Action of miRNAs in mRNA
mRNA target cleavage Translational repression mRNA deadenylation
miRNA ↑ mRNA ↓
miRNA ↓ mRNA ↑
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miRNAome
1881 miRNA sequences in database:
http://www.mirbase.org/
When the expression of a miRNA is deregulated (through deletion,
polymorphism, epigenetic modifications, induction etc),
It can have as a consequence the expression change of many gene targets!
One mRNA could be a target of many miRNAs
Up to 30% of genes are miRNAs’ targets
[Lim L.P., et al., Nature (2005), 433, 769–73]
Correlations with diseases: http://www.mir2disease.org
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miRNAs expression
in AD brain tissues
Hill J.M. et al., Front. Neur. (2015), 6, 232
Isolation of total RNA → cDNA
CFH
mRNA
Microarray evaluation
AD
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Reduced expression of hsa-miR-27a-3p in CSF of
patients with Alzheimer disease
Collection of CSF samples → RNA→ cDNA
Frigerio C.S. et al., Neurology (2013), 81, 2103–6
Test cohort Validation cohort
Negative
controls
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Real-time qPCR Higher concentrations → lower
Ct
Threshold
Baseline
Relative quantification with reference gene 2-ΔΔCt Method
Ct =
Cycle
threshold
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miRNA screen
752 miRNAs were evaluated and those with >75% positivity in
one of the two groups were recorded
86 miRNAs were positive in controls (11%) and 65 miRNAs in AD (9%)
Normalize results with miR-30 και miR-101-3p as a reference
In CSF cDNA samples from 8 AD and 8 CT (controls)
V2.0 miRCURY LNA Universal RT microRNA PCR Human panel I+II and SYBR Green
Universal Master Mix (Exiqon) in LightCycler 480 real-time PCR instrument (Roche)
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miRNA screen
results
Lower expression in AD (< -1):
hsa-miR-451a, hsa-miR-27a-3p,
hsa-miR-16-5p, hsa-miR-20a-5p,
hsa-miR-143-3p, hsa-miR-23a-3p,
hsa-miR-486-5p, hsa-miR-150-5p
Higher expression in AD (>1):
hsa-miR-216a-5p, hsa-miR-2110
Validation of 10 selected miRNAs
with separate real-time qPCR
assays in cohort Α
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miR-27a-3p qPCR results
n=20 n=19 n=15 n=19
AD controls AD controls
Cohort A Cohort B
Validation in B cohort
Relative
expression
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Correlation with established CSF biomarkers
r = -0.6025
p < 0.0001
r =-0.5304
p =0.0005
r = -0.3829,
p = 0.0279
r= -0.4030
p =0.0201
r= 0.4361
p= 0.0055
r= 0.4692
p= 0.0059
Cohort A
Cohort B
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Effect of hsa-miR-27a-3p in other genes
BACE1: 60% reduction, p=0.0054; GSK3B: 44% reduction, p=0.0010;
MAPT: 35% reduction, p=0.0038; PSEN1: 44% reduction, p=0.0046
TargetScan (target prediction
algorithm)
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Limitations – future goals
Limited number of CSF samples for miRNA screen due to cost
(less statistical value)
Post-mortem CSF samples were evaluated as well: 445 were
detected in 4 AD and 4 CT samples possibly due to different
sampling area in post-mortem, compromised integrity of the blood-
brain barrier and/or of brain cells after death
miRNAs more stable molecules and therefore,
ideal biomarkers in CSF or in blood in the future
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And the quest continues…
Molasy M. et al., Journal of Human Genetics (2017), 62, 105–12
Investigation of miRNAs in CSF in other type dementias (FTD etc)
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Thank for your attention
Keep your brains healthy!