Genoom-wijde moleculaire
technologie toegepast in de
genetische diagnostiek
Prof Maryse Bonduelle
Inleiding

Fundamenteel doel van de genetica:
 ontrafelen van het genotype om het fenotype te verklaren
 1977 Sanger sequencing

1 gen per analyse, base per base
 Combinatie van nieuwe instrumenten, databasen, bioinformatica en robotica exponentiele toename aan de
mogelijkheden

Next generation sequencing (NGS)
of Massive parallel sequencing
 Enkele miljoenen of biljoenen sequencies in parallel lezen
en in één enkele “run” analyseren
2
Genoomwijde Technologie Inleiding
21-5-2014

Drastische toename van capaciteit en snelheid 
dalen van de kost

Introductie van genoomwijde technologie in de
dagelijkse diagnostiek
 Toename toepassingen met diagnostische doeleinden
(vb NIPT, gene panels…)
 Nieuwe vragen en uitdagingen (begrijpen van het
functionele genoom van van de variaties)
 Nieuwe bevindingen ‘incidental findings’
(Informed Consent voor array, NIPT, NGS !)
3
Genoomwijde Technologie Inleiding
21-5-2014
Genoomwijde technologiën in de kliniek

Veranderingen in de klinische werking:
 Voor genoomwijde technologiën:
 klinische diagnostiek  Sanger sequencing 1 gen
volgende differentiaal diagnose Sanger sequencing
volgend gen
 Met genoomwijde technologiën:
 Info over een panel van genen betrokken bij aandoening
 Info over varianten (polymorphismen)
 Info over meerdere genen (multicatoriële modellen?)
 Info over nieuwe genen (nog verder wetenschappelijk te
staven via familiestudies en functionele studies)
 Info over andere niet betrokken genen bij de aandoening =
incidental finding ongewenste info, gewenst?

4
…
Genoomwijde Technologie Inleiding
21-5-2014
BRIGHT Platform : UZ Brussel-VUB-ULB
BRIGHT : BRussels Interuniversity Genomics & High Throughput
platform
 Nieuwe diagnostische en research noden!!!
 2012


start zoektocht naar middelen
2013
 toekennen middelen voor high troughput platform

funding door VUB en UZ Brussel
 aankoop van high troughput toestellen, scanners

Opstart platform
 deelname ULB in platform
 samenwerking in IB² bioinformatica platform (VUB-ULB )

2014 organisatie en uitbreiding platform

5
aankoop nieuwe toestellen
Genoomwijde Technologie Inleiding
21-5-2014
Genoom-wijde moleculaire technologie toegepast
in de genetische diagnostiek

Overzicht van de nieuwe diagnostische tools
 Array technologie


Ingevoerd op de werkvloer ter vervanging van de
klassiek karyotypering
Toepassingen in de genetische diagnostiek,
postnataal, prenataal en preimplantatie
 NGS technologie


6
Toelichting van verschillende technologieën
Toepassing in niet-invasieve diagnostiek (NIPT),
mitochondriaal genoom, erfelijke
hartritmestoornissen
Genoomwijde Technologie Inleiding
21-5-2014
Genoom-wijde moleculaire technologie toegepast
in de genetische diagnostiek

Algemene introductie en toepassingen in de kliniek
 Dr M. De Rademaeker & Dr Sci A. Van den Bogaert

Array Technologie: Preimplantatie genetische diagnostiek
 Dr Sci C. Staessen & Prof M. De Rycke

Nieuw Genomics platform op de campus UZ Brussel -VUB
 ir Ben Caljon

Niet Invasieve Prenatale Test (NIPT) met genoomwijde
analyse
 Dr Sci S. Van Dooren & Dr K. Van Berkel

Mitochondriale genoom sequencing zoekt diagnostische
bench.
 Prof S. Seneca

Erfelijke hartritmestoornissen
 Dr Sci S. Van Dooren & Dr M. Meuwissen
7
Genoomwijde Technologie Inleiding
21-5-2014
Algemene introductie en toepassingen in
de kliniek: array technologie
Ann Van Den Bogaert
Marjan De Rademaeker
Array CGH
Array gebaseerde vergelijkende
genoomhybridisatie (array comparative
genomic hybridisation) = array CGH
In 1 test: onderzoek van het volledige
genoom op kleine (submicroscopische)
chromosomale afwijkingen (200-400 kb)
2
Array CGH
22-05-2014
Array CGH
DNA
3
array CGH
22-5-2014
Array CGH-Principe
Referentie DNA
Test DNA
Log 2
test/referentie
winst
0.3
Labeling
0
Cy 5
Cy 3
-0.3
verlies
Mix
Chromosomale
positie
Analyse
Hybridisatie
Scan
4
array CGH
22-5-2014
Array CGH-in praktijk
4x44K arrays
4 keer 44000 unieke oligonucleotiden
(probes/reporters)
60 basen lang
over het gehele genoom verspreid
Aantal oligo’s per gebied ≠
5
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
6
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
7
array CGH
22-5-2014
Random Prime Labeling-Theorie
Binding van korte
primersequenties aan
gedenatureerd DNA
exo-Klenow fragment
van DNA polymerase 1:
verlenging van de
primers
Tijdens elongatie: het
merken van DNA,
resp. met Cy3 en Cy5
->inbouwen van
gemerkte dNTP’s
Ongeveer 10 maal geamplificeerd
8
array CGH
22-5-2014
Random Prime Labeling-Theorie
Genomisch DNA
• Denaturatie van dubbelstrengig DNA
naar enkelstrengig DNA
•Binding van de random primers
• Exo-Klenow fragment bouwt
nucleotiden in vanaf de random primers
+ binding van fluorescente nucleotiden
Fluorescent nucleotide
Exo-Klenow polymerase
Random primer
9
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
10
array CGH
22-5-2014
Array-CGH hybridisatie-Precipitatie
Precipitatie
Cy3 gemerkt patiënt DNA + Cy5 gemerkt referentie
DNA
NaAc
100% EtOH
Precipitatie (30 min. bij -80°C)
11
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
12
array CGH
22-5-2014
Array-CGH hybridisatie-Probebereiding Theorie
Stap 1
Random Prime labeling
Opzuiveren
= verwijderen van niet
ingebouwde nucleotiden
13
array CGH
22-5-2014
Array-CGH hybridisatie-Probebereiding Labo
14
array CGH
22-5-2014
Array-CGH hybridisatie-Probebereiding Theorie
stap 2
Blokking reagent
= blokkeert repetitieve sequenties
Niet-specifieke binding : achtergrondsignaal
15
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
16
array CGH
22-5-2014
Array-CGH hybridisatie-Hybridisatie
Theorie
Hybridisatie:
= de mixen worden aangebracht op de slides
Het gelabelde DNA bindt aan de probes die gespot
zijn op de slide
Vorming dubbelstrengig DNA: binding
complementaire sequenties vanop het
draagglaasje met het gelabelde DNA (mix patiëntreferentie)
17
array CGH
22-5-2014
Array-CGH hybridisatie-Hybridisatie
Theorie
Het array glaasje met 4 keer
44000 unieke oligonucleotiden
(probes/reporters)
Het gelabelde DNA (mix
patiënt/referentie) op het
oppervlak van het array glaasje +
dekglaasje
Hybridisatie: competitie tussen
verschillend gelabeld patiënt en
referentie DNA voor binding met
oligonucleotiden op array glaasje
18
array CGH
22-5-2014
Array-CGH hybridisatie-Hybridisatie
Labo
65°C, 24 uur
19
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
20
array CGH
22-5-2014
Array-CGH hybridisatie-Wassen
Theorie
Wassen
Enkel de probes die specifiek gebonden zijn aan
het gelabelde DNA kunnen een signaal geven
21
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
22
array CGH
22-5-2014
Scannen (Agilent microarray scanner)
Laser -> excitatie
Cy3 en Cy5
23
array CGH
22-5-2014
Scannen (Agilent microarray scanner)
Theorie
Na het scannen
Beelden: Feature Extraction Software
Vindt en plaatst microarrayrooster
De gemeten intensiteiten~gespot stukje van het
genoom (probes)
De intensiteit van één spot en de gemiddelde waarden
van het achtergrondsignaal rond de spots worden
gemeten
24
array CGH
22-5-2014
Feature Extraction Software-Labo
Groen signaal
25
array CGH
Geel signaal
Rood signaal
22-5-2014
Feature Extraction Software-Labo
Duplicatie: het gespot DNA op het glaasje
bevat meer patiënten DNA (Cy3; groen) dan
referentie DNA (Cy5; rood) =>
Groen signaal in de rooster
Deletie: het gespot DNA op het glaasje bevat
minder patiënten DNA (Cy3; groen) dan
referentie DNA (Cy5; rood) =>
Rood signaal in de rooster
Normaal: het gespot DNA op het glaasje
bevat evenveel patiënten DNA (Cy3; groen)
dan referentie DNA (Cy5; rood) => Geel
signaal in de rooster
26
array CGH
22-5-2014
Procedure
Random Prime Labeling
Array-CGH hybridisatie
Precipitatie
Probebereiding
Hybridisatie
Wassen
Scannen
Analyse
27
array CGH
22-5-2014
Analyse-Theorie
Verwerking en visualisatie: arrayCGHbase
(Menten et al., 2005)
Ruwe data wordt geconverteerd en gevisualiseerd
-> interpretatie
Log2-ratio per probe/reporter uitgezet t.o.v. zijn
chromosomale positie
28
array CGH
22-5-2014
Analyse in praktijk
29
array CGH
22-5-2014
Analyse array CGH
Cartagenia:
Labo: array resultaten
Artsen: kliniek
Labo: koppeling tussen genotype/fenotype
Interpretatie onafhankelijk en daarna overleg
tussen wetenschappelijke medewerker en arts
Verschil postnatale-prenatale arrays
30
array CGH
22-5-2014
Copy Number Variants-theorie
CNVs=DNA
fragmenten
>1Kb
Copy
Number
Variants
(CNVs)
= de term
CNP (Copy Number
Polymorphisms)
31
array CGH
“Goedaardig/beninge”
Normaal
15%-25%
van het
humane genoom
is polymorf
Array CGH
Effect op ! Genen
Genetische aandoeningen/pathogeen
22-5-2014
Copy Number Variants-in praktijk
Uitdaging:
Het verschil tussen CNVs die wel of niet bijdragen
tot de kliniek
Publieke databanken
CNVs van gezonde personen
Databank van genomische varianten (DGV)
32
array CGH
22-5-2014
Array CGH in de kliniek
Prenatale diagnose
Indicaties/ Interpretatie
Casuistiek
Postnatale diagnose
Indicaties
Casuistiek
Conclusie
33
array CGH
22-5-2014
Prenatale diagnose
Verhoogd risico op chromosomale afwijking
(leeftijd, abnormale niet invasieve screening)
Verhoogd risico monogene aandoening
Echografische afwijkingen
Psychosociale redenen
34
array CGH
22-5-2014
Prenatale diagnose
België sinds 2013: moleculair karyotype/
array CGH
Nationale consensus Centra Medische
Genetica België1:
Pre en post counseling
Interpretatie resultaten
Protocoleren resultaten
1Implementation
of genomic arrays in prenatal diagnosis: The Belgian approach to meet
the challenges, Eur J Med Genet. 2014 Mar;57(4):151-156
35
array CGH
22-5-2014
Prenatale diagnose
Benign
Pathogeen
“Unclassified”
Toevallige bevinding
Eur J Med Genet. 2014 Mar;57(4):151-156
36
array CGH
22-5-2014
Casus
24 weken
Echografische afwijking: duodenale atresie
37
array CGH
22-5-2014
Casus
38
array CGH
22-5-2014
Casus
39
array CGH
22-5-2014
Casus
Williams syndroom
40
array CGH
22-5-2014
Casus
25 weken
Echografie: cerebellaire atrofie, gedilateerd
pyelum, polyhydramnios, normale groei
41
array CGH
22-5-2014
Casus
Trisomie 18/ Edwards syndroom
Cave: geen laaggradige mozaïcisme!
42
array CGH
22-5-2014
Casus
20 weken
Echografie: afwezigheid neusbeentje
43
array CGH
22-5-2014
Casus
2080,2kb duplicatie 1q21.1-q21.2,
33 genen, GJA5 gen
44
array CGH
22-5-2014
Casus
1q21 duplicatie risico factor
Macrocefalie
Aangeboren afwijkingen
Ontwikkelingsstoornissen (autisme,
leerstoornissen)
Hartafwijkingen (VSD/ASD/PVS/ TOF,..) GJA5
gen
45
array CGH
22-5-2014
Casus
24 weken
Echografie: cardiopathie
46
array CGH
22-5-2014
Casus
9,4MB duplicatie16p13.13p12.2
211 genen, 75 proteine coderende genen
(NDE1, MYH11, ABCC1, ABCC6,...)
47
array CGH
22-5-2014
Casus
16 p13.11 duplicatie risico factor
neurologische problemen (ADHD, autisme,…)
Cardiovasculaire problemen (aorta
dilatatie,bicuspide aortaklep) MYH11 gen
Variabele penetrantie/ expressie
Consortium:
Ouders: overgëerfd
Rapporteren
Cardiopathie / grotere duplicatie (meer genen)
48
array CGH
22-5-2014
Casus
Zwangerschap 16 weken
Indicatie prenatale diagnose: post PGD voor
metabole aandoening
49
array CGH
22-5-2014
Casus
339 kb duplicatie van chromosomenband
6q22.3, PLN gen
PLN gen
puntmutaties of deleties phospholamban associatie
met cardiomyopathie
duplicatie: slechts 1 casus doch associatie met
cardiomyopathie
Consortium:
Ouders: overgeërfd
rapporteren,opvolging mogelijk
50
array CGH
22-5-2014
Postnatale diagnosis
Verstandelijke beperking,
neuropsychiatrische aandoeningen
dysmorfismen, aangeboren afwijkingen
Ouders van individu met chromosomale
afwijking
Abnormaal karyotype verfijnen
51
array CGH
22-5-2014
Casus
Jongen
Pinealoblastoma
52
array CGH
22-5-2014
Casus
Array CGH: 2,4 Mb deletie 22q11
geen deletie van tumorgen SMARCB1
Geen deletie van tumor gen INI1
► 22q11 deletie syndroom (velocardiofaciaal
syndroom), geen verklaring tumor
53
array CGH
22-5-2014
Casus
Jongen
Microftalmie en hypospadias
54
array CGH
22-5-2014
Casus
1.1 Mb deletion 2q23 ZEB2 gen
De novo
ZEB2 gen mutaties/ exon deleties/
Mowat Wilson syndroom
55
array CGH
22-5-2014
Casus
Meisje, pasgeborene
Epileptische encephalopathy
56
array CGH
22-5-2014
Casus
Array CGH: 2235,9kb deletion 15q11.2
Overgeërfd van de moeder
Risico factor postnataal!
Neuropsychiatrische aandoeningen (epilepsie,
autisme, gedrags en taalproblemen, verstandelijke
beperking)
57
array CGH
22-5-2014
Casus
Risico factor → Gekend deletie syndroom
58
array CGH
22-5-2014
Conclusie array CGH
Genoomwijd onderzoek van hoge resolutie
voor opsporing deleties/duplicaties
specifieke postnatale indicaties
alle invasieve prenatale diagnoses
Cave
Beperkte detectie mozaïcisme /geen detectie
gebalanceerde afwijkingen
Detectie afwijkingen van onduidelijke klinische
relevantie
59
array CGH
22-5-2014
Conclusie array CGH
Uitdaging
Voor elke CNV de relatie tot fenotype bepalen
Counseling
60
array CGH
22-5-2014
PGD for chromosomal abnormalities
Catherine Staessen, PhD
Centre of Medical Genetics
The main causes of chromosomal anomalies
Highgenetic
risk

Inheritance of the parental pathology
- true inheritance: e.g.parental translocation
PGD
Low- genetic
risk


Meiotic nondisjunction
80-85% related to oocytes
10-15% related to spermatozoa
Postzygotic mitotic non-disjunction
5-15% of cases of trisomies
PGS
*Hook EB. Cross PK.
Schreinemachers DM.
(1983)
Mat
Age
Risk at
birth
35
0.5%
38
0.98%
40
1.5%
45
4.8%
Carriers of balanced structural chromosomal
abnormalities

Have a greater chance of being infertile,
producing chromosomally abnormal offspring
and having multiple spontaneous abortions

Incidence 0.2% in neonatal population

Higher incidence (Stern et al., 1999)
 Infertile couples (0.6%)
 RA couples (9.2%)
 ICSI population (2 - 3.2%)
Analytical methods for chromosomal
abnormalities (numerical – structural)


FISH-based PGD protocols for chromosomal
abnormalities
Comparative genome hybridization (aCGH)based PGD for chromosomal abnormalities
FISH:principle
Multi - color FISH
1 → 3 consecutive FISH procedures
Y
FISH-based PGD protocols for structural chromosomal
abnormalities: pre PGD work-up

Determination of meiotic segregation for the
specific structural abnormality

Karyotype: confirmation chromosomal abnormality

Design of probe mixture

Lymphocyte FISH work-up: validation of the probe
mixture
Meiotic segregation
reciprocal translocation
Alternate: normal/balanced
Adjacent 1
Adjacent 2
3:1 segregation
4:0 segregation
With/without recombination
Anaphase 2 non-disjunction
Brandriff et al; AJHG, 38:197-208, 1986.
Reciprocal translocation: probe design
46,XX,t(6;11)(q21.1;q22)
CEP 6 SA
Tel 6q SO
CEP 11 SG
Tel 11q SO
Validation of the probe mixture: metaphase interphase
CEP 6 Aqua
Der 6
CEP 11 Green
Der 11
Tel 11q Orange
6
11
Efficiency of probe
mixture: at least 85%
Carrier/partner
PGD- FISH cycle: day 3 biopsy
BIOPSY
ROUND 1
ROUND 2
• Sex determination
FISH
PROCEDURE
(x-linked disorder)
• Chromosomal
aberrations
(numerical and structural)
FIXATION
• Aneuploidy screening
PGD-FISH: reciprocal translocation
CEP 6 aqua
CEP 6 aqua
CEP 11 green
CEP 11 green
Tel 11q orange
Tel 11q orange
Normal/balanced embryo
Unbalanced embryo
PGD
Round 2 : 16 q11.2 Orange
22 q11.2 Green
Round 1 :
X p11.1-q11.1 Blue
Y p11.1-q11.1 Gold
13 q14 Red
18 p11.1-q11.1 Aqua
21 q22.13-q22.2 Green
The causes of misdiagnosis and adverse
outcomes in PGD: data collection I - VIII
0.1% misdiagnosis rate
Wilton et al., Hum. Reprod., 24(5), 1221-28, 2009
Misdiagnosis: possible reasons

Technical: failure FISH signals,
overlapping signals, splitted spots

Human errors: inadequate probe design

Biological: mosaicism
Drawback of FISH - based PGD

FISH technique related limitations
Development of a patient specific protocol = time consuming
Fixation of the cell: critical step (possible loss of micronuclei,
chromosomes)
Subjective analysis of the signals and compromised by weak,
splitted or overlapping signals
Only chromosomes involved in rearrangement are
investigated

Development of genome-wide techniques
Comparative Genomic hybridization (a-CGH; micro-array)
Comparative genome hybridization (aCGH)based PGD for chromosomal abnormalities
Procedure: tubing & Whole Genome
Amplification (WGA)


Tubing of single cell (D3) or multiple cells (D5)
WGA
Amplification (SurePlex kit BlueGnome)
 Lysis of the cell(s)
 Extraction of the DNA
 Random fragmentation to form a library of DNA
 Amplification of DNA by PCR

Electrophoresis (1.5% agarose)
Electrophoresis gel picture after a successfully
WGA experiment
1
2
3
4
5
6 7
8
9
Lines 1,2,3,5,6,7 = amplified DNA
Line 4 = ladder
Line 8 = negative control (PBS)
Line 9 = positive control (genomic DNA)
Array-CGH cytochip BlueGnome (~ 12-24h)
24 sure (1Mb)
24 sure + (0.5 - 0.25
Mb for telomeric
regions)
24 sure cytochip bluegnome
13: 114 Mb; 14: 106 Mb
45,XY, der(13;14)(q10;q10)
Result PGD FISH :
XX Abnormal
(1x LSI 13 Red,
3x LSI 14q32)
carrier 46,XX,t(2;5)(p11;q34)
PGD-FISH: dup(2)(ptel), del(5)(qtel)
3X tel2p
2X tel2q
88 Mb
2X 5p15.2
1X 5q35
24 sure + cytochip (bluegnome)
12,6 Mb
CHR 2
 47,XX, dup(2)(ptel-p11.2), del(5)(q34-qtel), +22
CHR 5
Result: succesful WGA – aCGH (D3)
Total
Number of cycles
24
Embryos biopsied
104
Succesful WGA
99 (95.2%)
Result a-CGH
99 (100%)
Preliminary: aCGH - genetic result
Indication
Translocations
(8 cycles)
PGD enumeration
(8 cycles)
PGS
(8 cycles)
Total
(24 cycles)
N embryos with
diagnosis
N normal
29
4 (13.8%)
38
2 (5.3%)
32
10 (31.3%)
99
16 (16.2%)
Preliminary: aCGH - clinical outcome
Indication
Translocations
(8 cycles)
PGD enumeration
(8 cycles)
PGS
(8 cycles)
Total
(24 cycles)
N of ET
3
N of + HCG
2
+1 too early
2
2
5
2
10
6 (60%)
Summary
PGD a-CGH
Total
Cycles with pick-up
29
Cycles with biopsy
24 (82.8%)
Age
37.6  5.2
COC
9.4  4.6
2PN
Biopsied
Result WGA
Result a-CGH
Normal
Total
N Abnormal
83
5.7  2.7
Detected FISH
Not detected with FISH
64
19
104
(4.32.6)
n ET
10
99 (95.2%)
99
16 (16.2%)
N +HCG
N +FHB
Outcome
Titel van de presentatie
| pag. 25
(22.6%)
6
+ 1 too early
4
1 delivered
rest ongoing
aCGH

Reliability and feasibility demonstrated for detection of
chromosomal imbalances in embryos
(Gutiérrez- Mateo et al., 2011; Colls et al., 2012)

In comparison with FISH:
- Not dependent of critical step of cell fixation
- Evaluating multiple loci along the length of each
chromosome region
- Data analysis performed by computerized analysis of
signal intensities (based on a log2 ratio and quality criteria
(SD, signal-to-noise ratio)) instead of subjective signal
scoring

In the future: automated workstations
- increase of number of samples
- reduces the risk of errors
aCGH:

Allows screening for all chromosomes in addition to the
unbalanced derivatives associated with the specific structural
abnormality

No development of a patient specific ’probe-mixture’ and preclinical
validation
- Detection limits: the probability of detecting an unbalanced
translocation , and therefore the success of the array-CGH based
analysis, is dependent upon the location of the translocation
breakpoints in the chromosomes and the size of the unbalanced
region(s)

Limitations:
- aCGH cannot detect haploidy and some triploidies (69,XXX)
- cannot differentiate normal versus balanced translocation carrier

aCGH represents at this time an expensive option for embryo testing
compared to the FISH technology
PGD: multidisciplinary team work
Center Medical Genetics
Accurate genetic diagnosis
Fertilisation
in vitro
Center Reproductive
Medicine
(IVF or ICSI)
OPU – fertilisation
in vitro
Appropriate genetic
counselling
Genetic Diagnosis
Embryo biopsy
Transfer 2 unaffected
embryos
Preimplantation genetic diagnosis
Martine De Rycke
martine.derycke@uzbrussel.be
Preimplantation Genetic Diagnosis

an alternative to prenatal diagnosis and TOP

involves genetic testing of cells biopsied from in vitro
obtained oocytes and/or in vitro fertilised embryos and
selective transfer of unaffected embryos

for couples at high risk of transmitting
a genetic condition to their children
2
titel
20-5-2014
Preimplantation Genetic Screening

PGS or aneuploidy screening involves selection of
euploid embryos to improve IVF results and
reduce miscarriage rates

for specific IVF patients groups at low risk
(advanced maternal age, recurrent IVF failure or
repeated miscarriages)
3
titel
20-5-2014
History of PGD
• 1990: Handyside et al.:
first PGD for X-linked disease
• 1992: Handyside et al.:
baby after PGD for Cystic Fibrosis
Pregnancies from biopsied human preimplantation embryos sexed by Yspecific DNA amplification
A. H. Handyside, E. H. Kontogianni, K. Hardy & R. M. L. Winston
Institute of Obstetrics and Gynaecology, Royal Postgraduate Medical School, Hammersmith Hospital, Du Cane Road, London W12 ONN, UK
OVER 200 recessive X chromosome-linked diseases, typically affecting only hemizygous males, have been identified. In many
of these, prenatal diagnosis is possible by chorion villus sampling (CVS) or amniocentesis, followed by cytogenetic,
biochemical or molecular analysis of the cells recovered from the conceptus. In others, the only alternative is to determine the
sex of the fetus. If the fetus is affected by the defect or is male, abortion can be offered. Diagnosis of genetic defects in
preimplantation embryos would allow those unaffected to be identified and transferred to the uterus1. Here we report the first
established pregnancies using this procedure, in two couples known to be at risk of transmitting adrenoleukodystrophy and Xlinked mental retardation. Two female embryos were transferred after in vitro fertilization (IVF), biopsy of a single cell at the
six- to eight-cell stage, and sexing by DNA amplification of a Y chromosome-specific repeat sequence. Both women are
confirmed as carrying normal female twins.
4
titel
20-5-2014
History of PGD at UZ Brussel
700
600
500
400
300
200
100
0
PGD-PCR
5
titel
PGD-FISH
PGD-AS
20-5-2014
PGD/PGS: indications

for chromosomal aberrations (numerical and structural)
PGD-FISH/aCGH

sex determination (X-linked disorders)
PGD-FISH/aCGH or PGD-PCR (mutation identified)

for monogenic diseases (X-linked, autosomal
dominant/recessive) and HLA typing PGD-PCR

for aneuploidy screening PGS-aCGH
6
titel
20-5-2014
PGD clinical cycle
10 oocytes
day 0
ICSI
8 normally fertilised oocytes
day 1
6 embryos for biopsy
day 3
genetic testing
day 3/4
transfer
day 5
no diagnosis
unaffected
affected
affected
unaffected
transfer
cryo, if good morphology
unaffected
bad morphology
no transfer
PGD clinical cycle
amplification
embryo biopsy
with laser (day 3)
FISH
8
titel
20-5-2014
Single cell amplification

targeted (2 copies of the region of interest)
=> single cell multiplex PCR (monogenic diseases)
* simultaneous amplification of multiple loci per cell
= flanking Short Tandem Repeat markers +/- mutation locus
* more accurate: allows diagnosis AND reveals contamination & ADO
* fluorescent: allows fragment length detection via capillary electrophoresis
on automated sequencers

9
requires extensive optimisation and validation of PCR
conditions
titel
20-5-2014
Single cell amplification
request for mutation/gene/locus 1 =>
develop single cell PCR 1
request for mutation/gene/locus n =>
develop single cell PCR n
customised protocols: optimisation and validation at the single cell level
has to be repeated each time => pre-PGD workup is labour-intensive
and time-consuming and yields high costs
10
titel
20-5-2014
Single cell amplification
universal single cell Whole Genome Amplification
several µg of DNA
haplotyping: regular PCR of STR
downstream analyses
genome-wide tests
optimisation and validation of single cell whole genome amplification
(WGA): only 1 time!
=> pre-PGD workup labour, time and costs are reduced
11
titel
20-5-2014
PGD: emerging genetic tests
single-cell WGA and SNP arrays
- mutation analysis by haplotyping
- full chromosomal constitution
- Single Nucleotide Polymorphism
single-cell WGA and NGS
- reveal also point mutations
balanced chrom. rearrangements
- high cost, still under validation
emerging platforms are genome-wide
and allow standardisation and automation
12
titel
20-5-2014
SNP bead array preparation
13
titel
20-5-2014
SNP bead array: workflow
MDA based
14
titel
20-5-2014
Whole genome amplification: MDA

Multiple Displacement Amplification, (MDA)
isothermal amplification (30°C) => DNA fragments up to 70 kb,
low error rates
Dean et al., 2002
15
titel
20-5-2014
SNP array: principle
target
denaturation and
hybridisation on beadChip
probe
single base
extension
LaFramboise T , 2009
16
titel
20-5-2014
SNP bead array
A = A/T base
B = G/C base
NC = no call
17
titel
20-5-2014
SNP array: interpretation
genotype information
1) identify informative SNPs
in region of interest
2) phase SNPs in embryo
vs reference
aff
18
titel
wt
aff
aff
unaff
aff
20-5-2014
Genoom-wijde moleculaire technologie
toegepast in de genetische diagnostiek
Nieuw genomics platform op campus UZ Brussel / VUB
22/5/2014
Infrastructure + applications
Ir Ben Caljon
Available Sequencers
VUB/UZ BRUSSEL
CMG ULB
Ion Torrent PGM
MiSeq
GS Junior
HiSeq 1500
3
Nieuw genomics platform
22-05-2014
System Comparison
Run mode
Output range
Run time
Reads per flowcell
Maximum read length
Quality 1x400 bp
Run mode
Output range
Run time
Reads per flowcell
Maximum read length
Quality 2x50 bp
Quality 2x75 bp
Quality 2x100 bp
Quality 2x125 bp
Quality 2x150 bp
Quality 2x250 bp
Quality 2x300 bp
4
Roche GS Junior
PicoTiterPlate
40 Mb
10h
100 thousand
400 bp (average)
>99% > Q20
MiSeq
Nano
500 Mb
4-39h
1 million
2x250 bp
Ion Torrent PGM
314 chip
30-50 Mb
2,3h
400-550 thousand
1x200 bp (400 bp)
Micro
1,2 Gb
4-24h
4 million
2x150 bp
316 chip
300-600 Mb
3,0h
2-3 million
1x200 bp (400 bp)
Standard
15 Gb
4-65h
15-25 million
2x300 bp
318 chip
600 Mb-1 Gb
4,4h
4-4,5 million
1x200 bp (400 bp)
HiSeq 1500
Rapid Run
5-90 Gb
7-40h
300 million
2x150 bp
>85% > Q30
High Output v3
47-300 Gb
2-11 days
1,5 billion
2x100 bp
>85% > Q30
High Output v4
64-500 Gb
1-6 days
2 billion
2x125 bp
>85% > Q30
>80% > Q30
>80% > Q30
>80% > Q30
>80% > Q30
>85% >Q30
>80% > Q30
>75% > Q30
Nieuw genomics platform
>80% > Q30
>75% > Q30
>75% > Q30
22-05-2014
IT infrastructure

IT Infrastructure (UZ Brussel)
 5 servers installed with Opensuse 12.2 (linux)



5 x (16cpu,192Gb Ram, 1.6 Tb HD)
40 Tb Shared Network drive (backuped)
Sever capacity will be doubled in 2014
 2x HP Z600 workstation




24 virtual cores (Intel Xeon E5645 2,4 GHz)
2x2Tb (RAID1)
24 Gb RAM
1x Opensuse 12.2 (linux) + 1x Win7
 Grid management System:


Open Grid Scheduler (ogs/sge)
(IB)²: interuniversity bioinformatics unit
 Collaboration ULB/VUB/UZ Brussel
5
Nieuw genomics platform
22-05-2014
Applications (1)

Whole genome sequencing (WGS)
Shear DNA
(get appropriately sized DNA fragments)
Ligate adapters
(modify DNA fragments to be compatible with
sequencing instruments)
Sequence
(HiSeq for complex, MiSeq for small genomes)
6
Nieuw genomics platform
22-05-2014
Applications (2)

Whole exome sequencing (WES)
Shear DNA
(get appropriately sized DNA fragments)
Ligate adapters
(modify DNA fragments to be compatible with
sequencing instruments)
Enrich targets
(capture specific regions/exons with probes)
Sequence
(HiSeq for complex, MiSeq for small genomes)
7
Nieuw genomics platform
22-05-2014
Applications (3)

Non-Invasive Prenatal Testing (NIPT)
1. Phlebotomy
5. Cluster generation
8
Nieuw genomics platform
2. Plasma isolation
6. Sequencing
3. cfDNA extraction
7. Data-analysis
4. Library preparation
8. Reporting
22-05-2014
Applications (4)

Bisulphite sequencing
Bisulphite treatment +
PCR
(convert unmethylated C to U)
Ligate adapters
(modify DNA fragments to be compatible with
sequencing instruments)
Sequence
(HiSeq for complex, MiSeq for small genomes)
9
Nieuw genomics platform
22-05-2014
Applications (5)

Mitochondrial resequencing
Amplify mtDNA - lrPCR
(select for mtDNA copies)
Shear lrPCR product
(get appropriately sized DNA fragments)
Ligate adapters
(modify DNA fragments to be compatible with
sequencing instruments)
Sequence
(HiSeq for complex, MiSeq for small genomes)
10
Nieuw genomics platform
22-05-2014
Applications (6)

11
mRNA sequencing
Nieuw genomics platform
22-05-2014
Future prospects




12
Small RNA sequencing (miRNA)
ChIP sequencing
rRNA typing (metagenomics)
Molecular Inversion Probe (MIP) assays
Nieuw genomics platform
22-05-2014
Questions?
13
Nieuw genomics platform
22-05-2014
Non-invasive prenatal testing
22/05/2014
Dr. Kim van Berkel Dep. Gynaecology– Centre for Medical Genetics
Dr. Sci. Sonia Van Dooren – Centre for Medical Genetics
What is NIPT ?
1.
2.
3.
4.
5.
6.
7.
Definition
Introduction
NIPT technology
Indications, contra-indications and
limitations
Practical
Future
Conclusions
2013
Definition

NIPT = non-invasive prenatal test

Prenatal screening for aneuploidy

Risk calculation
Introduction

Screening for trisomy 21
 Ultrasound
 PAPP-A/combination test (1T)
 Triple Test (2T)

Invasive prenatal diagnosis
 Chorion villi sampling
 Amniotic fluid punction
Screening for trisomy 21

Ultrasound
 1st trimester:



nuchal translucency (NT)
ductus venosus (DV)
tricuspidalis valve (TV)
 2nd trimester: soft markers
 sensitivity max 70%
Screening for trisomy 21
NT
Screening for trisomy 21
DV
Screening for trisomy 21
TV
Screening for trisomy 21

PAPP-A/combination test
 1st trimester US + biochemical markers in
maternal bloed (ßhCG and PAPP-A)
Screening for trisomy 21

PAPP-A/combination test
 1st trimester echo + biochemical markers in
maternal blood (ßhCG and PAPP-A)
 Combined risk calculation for Down
 Cutoff 1/250
 Sensitivity 80-85%
 5% false positive
Screening for trisomy 21

TT
 AFP, ßhCG and oestriol
Screenen naar trisomie 21

TT
 AFP, ßhCG and oestriol

Second trimester soft-markers






NF, ventriculomegaly
Femur, humerus
Echogene focus
Dense intestines
Pyelectasy
SUA
Screening for trisomy 21
Invasive screening for trisomy 21

Chorionic Villi Sampling (11-13w)

Punction of amniotic fluid (>15w)
Screening for trisomy 21

Conventional
karyotyping

Molecular
karyotyping
Screening for trisomy 21:
non-invasive prenatal testing (NIPT)

NIPT: cell-free fetal DNA
(cffDNA) in maternal
plasma
 shedding of
trophoblast cells
 short half life
(2 h clearance)
 3% to 20% of total
cfDNA
 reliable detection from
11-12 weeks on
Overview NIPT technique
1. Phlebotomy
5. Cluster generation
18
2. Plasma isolation
6. Sequencing
NIPT - Non-invasive prenatal testing
3. cfDNA extraction
4. Library preparation
7. Data-analysis
8. Reporting
20-5-2014
NIPT - sampling
19
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT – Digital PCR (1)
Lo YM, et al. Digital PCR for the molecular detection of fetal chromosomal aneuploidy. Proc Natl Acad Sci U S A. 2007
Aug 7;104(32):13116-21.
22
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT – Digital PCR (2)
23
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT – DMR: MeDIP PCR or qMSP(1)
L. Osherovich, Chromosome triple play,
25
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT – DMR technology (2)

Chromosome 21(MeDIP PCR)
Papageorgiou et al. Fetal-specific DNA methylation ratio permits
noninvasive prenatal diagnosis of trisomy 21. Nat Med. 2011
Apr;17(4):510-3.
26
NIPT - Non-invasive prenatal testing

Chromosome 18 (qMSP)
Lee et al. Non-Invasive Prenatal Testing of Trisomy 18 by an Epigenetic
Marker in First Trimester Maternal Plasma. PLOSOne 2013 Nov; 8(11)
20-5-2014
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT – SNP based approaches
28
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT – tMPS (1)
Sparks AB, et al.. Noninvasive prenatal detection and selective analysis of cell-free DNA obtained from maternal blood:
evaluation for trisomy 21 and trisomy 18. Am J Obstet Gynecol. 2012 Apr;206(4):319.e1-9.
30
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT methodologies
NIPT
cfDNA based
cfRNA based
Clinical utility
SNP based
approaches
Digital PCR
t-MPS
qPCR
(targeted massive
parallel Sequencing)
s-MPS
(shotgun massive
parallel sequencing)
(abs quant
chr21 vs chr 1)
(diff methylated
regions)
RNA
expression
(trophoblast vs maternal )
NIPT – sMPS technology
1. Library preparation
2. Cluster generation
3. Sequencing
32
NIPT - Non-invasive prenatal testing
20-5-2014
NIPT – sMPS data analysis
Millions
4. Coverage: # of reads/sample
5. Aligning raw data
10
8
6
unmapped
reads
4
6. GC correction
NIPT23
NIPT21
NIPT19
NIPT17
NIPT15
NIPT13
NIPT11
NIPT9
NIPT7
NIPT5
NIPT3
0
NIPT1
2
mapped
reads
7. Data normalisation
8. Counting statistics: Z-score calculation
Binning
Loess correction
33
# of data
NIPT - Non-invasive prenatal testing
20-5-2014
Test performance - targeted NIPT
Zimmermann B, et al.. Noninvasive prenatal aneuploidy testing of chromosomes 13, 18, 21, X, and Y, using targeted sequencing of
polymorphic loci. Prenat Diagn. 2012 Dec;32(13):1233-41.
34
NIPT - Non-invasive prenatal testing
20-5-2014
Test performance - genome-wide NIPT
Shaw SW, et al. From Down syndrome screening to noninvasive prenatal testing: 20 years' experience in Taiwan. Taiwan J Obstet Gynecol.
2013 Dec;52(4):470-4.
35
NIPT - Non-invasive prenatal testing
20-5-2014
Claimed accuracy per chromosome
Shaw SW, et al. From Down syndrome screening to noninvasive prenatal testing: 20 years' experience in Taiwan.
Taiwan J Obstet Gynecol. 2013 Dec;52(4):470-4.
Devers PL, Cronister A, Ormond KE, Facio F, Brasington CK, Flodman P. Noninvasive prenatal testing/noninvasive prenatal
diagnosis: the position of the National Society of Genetic Counselors. J Genet Couns. 2013 Jun;22(3):291-5
36
NIPT - Non-invasive prenatal testing
20-5-2014
False positive rates and predictive values
Bianchi et al. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014 Feb 27;370(9):799-808.
Indications for NIPT





Combination test with higher risk
Previous pregnacy with trisomy 21
35 years or older
Psycho social
Other
Contra-indications



Dizygotic twin or multiple pregnancy
Prior blood transfusion, stem cell
therapy, immuno therapy,
transplantation
Chromosomal abberations
 Preferably combination test
Limitations





Mozaicism
Small abberations of chromosome 21
Monogenic disorder
Obesitas
Ultrasound abnormalities
Practical
1st trimester US 1112w
abnormalities
ao abnormalities
Counseling
options
Option1:
Option
combination 2: NIPT
test
high risk
low risk:
US 20w
Nl: US 20w
higher risk
Option3: PND
CVS (11-13w)
AF (>15w)
Future

Current reporting :
 trisomy 21, 18, 13, gender

Future reporting:
 Other chromosomes
 Small chromosomal abberations
 Monogenic disorders?

Reimbursment
Future
Conclusion

NIPT is an intermediate screening test
 currently mainly for trisomy 21, 18 and 13
 risk calculation: HIGH or EQUAL or LOW
 high sensitivity and specificity (false pos. rate 1%)


Preferentially for high-risk pregnancies
Confirmation of abnormal result by invasive
test
 array CGH on chorion villi or amniotic fluid

Evolution towards diagnostic test in the future
Acknowledgements
Medical genetics UZ Brussel

Clinic





Prof .Dr. Maryse Bonduelle
Dr. Kim Van Berkel
Dr. Martine Biervliet
Dr.
Dr.
Dr.
Dr.
Sci.
Sci.
Sci.
Sci.
Sonia Van Dooren
Catherine Staessen
Ann Van de Bogaert
Alexander Gheldof
NGS platform BRIGHT


Ir. Ben Caljon
Dr. Sci. Didier Croes
Clinic


Lab





Gynaecology
Dr. Anniek Vorsselmans
Dr. Kim Van Berkel
Scientific partner

Clinic


Prof. Dr. Eric Legius
Lab


Dr. Sci. Joris Vermeesch
Dr. Sci. Nathalie Brison
MT GENOOM SEQUENCING ZOEKT
DIAGNOSTISCHE BENCH
mtDNA analyze
Prof. Sara Seneca
mt genoom zoekt diagnostische bench
Mitochondriale genoom sekwensing
Wat ? Waarom ?
2
mt genoom zoekt diagnostische bench
20/05/2014
overzicht
Introductie
mt aandoening
mtDNA
MPS
Data analyse & resultaten
platform 1
platform2
3
Conclusies
mt genoom zoekt diagnostische bench
20/05/2014
mitochondriale aandoeningen
4
zeer heterogene groep aandoeningen
multi-systeem ziekte waarbij vele weefsels
en organen betrokken (kunnen) zijn
incidentie 1/5000
geen genezing, noch therapie
vage genotype-fenotype relatie
diagnose is complex
defect vd ademhalingsketen ( of OXPHOS systeem)
mt genoom zoekt diagnostische bench
20/05/2014
illustratie klinisch beeld
5
mt genoom zoekt diagnostische bench
20/05/2014
OXPHOS system
energie (ATP) genererend systeem, in mitochondria
duale genetische controle voor structurele
subeenheden
+ vele nucleair gecodeerde genproducten
direct & indirect
defecten van genproducten van OXPHOS systeem
mt ziekte
Schon 2013
6
mt genoom zoekt diagnostische bench
20/05/2014
mtDNA map 16, 5 kb (1)
kleine circulaire dubbel
strenige molecule
37 genen
13 protein
22 tRNA
2 rRNA
7
mt genoom zoekt diagnostische bench
polymorf
20/05/2014
mtDNA map 16, 5 kb (2)
maternele overerving
polyploid
homoplasmie
heteroplasmie
range 0-100%
drempel effect
afhankelijk mutatie
afhankelijk weefsel/orgaan
afhankelijk leeftijd
drempel
effect
8
mt genoom zoekt diagnostische bench
20/05/2014
diagnostiek mt aandoening
diagnose
studies
patiënt anamnese
klinische onderzoeken
familie historiek
microscopie,
enzymologie, histologie,
immunohistochemie, …
stamboom
genetische test
mtDNA
nucleair DNA
verschillende weefsels
(bloed, epitheelcel,
fibro’s, spier, lever, …)
9
mt genoom zoekt diagnostische bench
20/05/2014
moleculaire diagnostiek (1)
OXPHOS systeem
duale genetische controle
nucleair DNA
mtDNA
hier: focus op analyse mtDNA
10
mt genoom zoekt diagnostische bench
20/05/2014
moleculaire diagnostiek (2)
mtDNA testing : stapsgewijs proces
11
frekwente punt mutaties
PCR gebaseerde screeningstechniek
Sanger sekwensing varianten
kwantificatie van heteroplasmie
deleties : Southern blot of LR-PCR
mt genoom zoekt diagnostische bench
20/05/2014
moleculaire diagnostiek (3)
hot spot regio’s en hot spot posities
melas, merrf, narp, LHON, …
verspreid over ganse genoom
analyse van
volledig mtDNA
nodig
12
mt genoom zoekt diagnostische bench
20/05/2014
Massieve Parallel Sekwensing (MPS)
13
mt genoom zoekt diagnostische bench
20/05/2014
MPS van mtDNA
6/32 stalen
3 patiënten + 3 Cs
32 stalen : piloot studie
28 patiënten + 4 Cs
LR-PCR library :
3 overlappende of
1 groot amplicon
Ion Torrent PGM systeem
pH verandering
14
mt genoom zoekt diagnostische bench
Illumina MiSeq systeem
fluorescentie
20/05/2014
Target enrichment
aanrijking van mtDNA
NUMTs proove
geen amplificatie van nucleaire mt sekwenties
‘PCR based’ methodologie
controle van de primerkoppels op amplificatie
Long Range-PCR
3 amplicons
1 amplicon
15
mt genoom zoekt diagnostische bench
20/05/2014
Massieve Parallel Sekwensing
bepaling van systeem’s detectie drempel
onderscheid ts heteroplasmie en systeemfout
pUC19 plasmide DNA sekwentie
Ion Torrent PGM : ± 0.8%
drempel ≥ 5%
veelvuldige homopolymeer fouten (gekend probleem)
drempel ≥ 5%
MiSeq drempel : ± 0.5%
drempel ≥ 2 %
16
mt genoom zoekt diagnostische bench
20/05/2014
pUC19 analyse
bepaling van detectie drempel systeem
foutenmarge : ratio van # niet referentie
basen met totaal # basen op eenzelfde
specifieke positie
wordt bepaald voor elke positie in genoom
gemid. systeem fout wordt berekend
17
mt genoom zoekt diagnostische bench
20/05/2014
Massieve Parallel Sekwensing
bepaling van systeem’s detectie drempel
onderscheid ts heteroplasmie en systeemfout
pUC19 plasmide DNA sekwentie
Ion Torrent PGM : ± 0.8%
drempel ≥ 2%
veelvuldige homopolymeer fouten (gekend probleem)
drempel ≥ 5%
MiSeq drempel : ± 0.5%
drempel ≥ 2 %
18
mt genoom zoekt diagnostische bench
20/05/2014
Massieve parallel sekwensing
data analyse
Ion Torrent PGM versus
MiSeq
fastq
Torrent
suite v3.6
VCFfile
in-house
pipeline
(BWA; GATK;…)
coverage analysis
(samtools)
VCFfile
Annovar
Mitomap
rapport
varianten + coverage
19
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20/05/2014
Begrip ‘coverage’
Integrative Genomics Viewer (IGV) beeld
20
mt genoom zoekt diagnostische bench
20/05/2014
MPS resultaten
‘non-deleted’ template
‘single large scale’ deleties
21
mt genoom zoekt diagnostische bench
‘multiple’ deleties
20/05/2014
Coverage profiel (1)
relative coverage
3,5
3
2,5
2
1,5
+
1
-
0,5
1
189
377
565
753
941
1129
1317
1505
1693
1881
2069
2257
2445
2633
2821
0
mtDNA position
biased
22
mt genoom zoekt diagnostische bench
20/05/2014
Coverage profiel (2)
onafhankelijk vh DNA staal
onafhankelijk vd primerset in LR-PCR
onafhankelijk vd shearing methodologie
ook zonder 1ste PCR amplificatie
lacZα
amp
pUC19
ori
23
mt genoom zoekt diagnostische bench
20/05/2014
Coverage profiel (3)
Ion Torrent PGM
24
mt genoom zoekt diagnostische bench
MiSeq systeem
20/05/2014
Variant calling – stap 1 - deleties
‘non-deleted’ template
‘single large scale’ deleties
25
mt genoom zoekt diagnostische bench
‘multiple’ deleties
20/05/2014
Variant calling – stap 2 - varianten
26
VCF annotatie van varianten
mt genoom zoekt diagnostische bench
20/05/2014
Variant calling – stap 3 – Q_filtering
detectie limiet
Ion Torent PGM : < 5%
MiSeq : < 2%
27
mt genoom zoekt diagnostische bench
20/05/2014
Variant calling – stap 3 – Q_filtering
detectie limiet
Ion Torent PGM : < 5%
MiSeq : < 2%
28
QC : heteroplasmie vs gemiddelde
systeem fout vgl. mtDNA MPS data set
mt genoom zoekt diagnostische bench
20/05/2014
resultaten van de piloot studie
Ion Torrent
MiSeq
29
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Variant calling (1)
Sanger sekwensing
34
vals negatieven
30
mt genoom zoekt diagnostische bench
MPS sekwensing
828
12
< detectie limiet
Sanger sekwensing
20/05/2014
Variant calling (2)
Sanger versus Ion Torrent PGM sekwensing
piloot studie van 32 DNA stalen
# varianten
Sanger
Ion Torrent PGM
862
828
vals negatieven
34
extra
12
variant
m.302-316
31
mt genoom zoekt diagnostische bench
# stalen
30
m.16183A>C
3
m.7402delC
1
20/05/2014
Variant calling (3)
Sanger sekwensing vs Ion Torrent sekwensing vs
MiSeq
piloot studie van 6 DNA stalen
Sanger
sekwensing
Ion Torrent
PGM
MiSeq
214
208
214
vals negatieven
7
0
extra
4
6
# varianten
variant
32
mt genoom zoekt diagnostische bench
AF
m.5609T>C
4.5%
m.8207C>T
2%
20/05/2014
Conclusies (1)
complete re-sequencing van 28 patiënten stalen
nieuwe (pathogene) varianten
variant
gen
weefsel % heteroplasmie
m.14721G>A MT-TE
spier
48%
m.7402delC
MT-COI
p.(Pro500Hisfs*12)
spier
80%
m.15453T>C
MT-CYB
p.(Leu236Pro)
bloed
100%
33
mt genoom zoekt diagnostische bench
20/05/2014
Conclusies (2)
Sanger
stalen/run
1
MiSeq
tot 12
tot 145
problematisch
uitstekend
neen
+*
+*
+**
AF>15-20%
+
AF>5%
+
AF>2%
neen
problematisch
-
coverage
deleties
punt mutaties
Ion Torrent
homopolymeren
* met bepaling van breekpunten
** 2de techniek nodig voor kwantificatie
34
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20/05/2014
Met dank aan alle medewerkers
REGE VUB
CMG UZ Brussel
35
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Challenges in cardiogenetics
research, diagnostics and
prevention
Sonia Van Dooren
Marije Meuwissen
Inherited cardiac arrhythmias
LQT
SQT
Cardiac
arrhythmia
Primary
cardiac
arrhythmia
BrS
electrical disease
no structural abnormalities
ARVD
CPVT
Secondary
cardiac
arrhythmia
cardiomyopathy
structural
abnormalities
HCM
DCM
Brugada syndrome (BrS)

Incidence:
Lo et al. 2004
 0.05 to 0.6 % in adults
 0.0006 % in children

Congenital primary cardiac arrhythmia
 autosomal dominant
 incomplete penetrance & variable
expression
WF
WG
2012
: BrS
cardi
omic
s
rese
arch
3
20-5-2014
BrS - clinical diagnosis

ECG morphology



Symptoms:





WF
WG
2012
:BrS
cardi
omic
s
rese
arch
spontaneous – drug-induced
(ajmaline)
type: saddle back - coved
syncopes
palpitations
ventricular arrhythmias
sudden cardiac death
Family history
EPS: electrophysiology studies
Mizusawa Y , and Wilde A A Circ Arrhythm Electrophysiol 2012;5:606616
20-5-2014
Molecular basis of BrS

BrS = Channelopathy
 Purely electrophysical disease
 No structural problems

Altered function of ion channels
in the heart
 To date NaCN, CaCN & KCN
 Accessory proteins

Imbalance between inward and
outward ion currents
Rev Esp Cardiol. 2010 May;63(5):620
BrS etiopathogenisis

Basic arrhythmogenic
mechanisms

Principle arrhythmogenic site:
RVOT

Hypotheses:
 depolarization hypothesis:
slow conduction
 repolarization hypothesis
 developmental abnormalities in
cardiac neural crest embryonic
cells in heart development
BrS – genetic diagnosis
type
gene
reference
Sodium channel α-subunit
SCN5A
MAJOR gene
Kapplinger, 2010
(compendium)
Sodium channel β-subunits
SCN1B
Watanabe, 2008
SCN3B
Hu, 2009
KCND3
Giudicessi, 2011
KCNH2
Verkerk, 2005
KCNE3
Delpón, 2008
KCNE5
Ohno, 2011
KCNJ8
Medeiros-Domingo, 2010
Pacemaker channel
HCN4
Ueda, 2009
L-type calcium channels
CACNA1C
Antzelevitch, 2007
CACNB2B
Antzelevitch, 2007
CACNA2D1
Burashnikov, 2010
GPD1-L
London, 2007
MOG1
Kattygnarath, 2011
SLMAP
Ishikawa, 2012
TRPM4
Liu, 2013
Potassium channels
Sodium channel trafficking
Diagnostic yield
up to 30%
+10%
60% remains
genetically
undiagnosed
CMG / UZBrussel experience

Clinical diagnostics @ HRMC




400 BrS families
45 new families/year
150 family screenings/year
Genetic diagnostics @ CMG




SCN5A: ~165 probands
SCN1B-4B: ~83 probands
targeted resequencing: gene panels
whole exome sequencing
SCN5A genetic diagnosis & ECG
BrS
probands
ECG
SCN5A variant
association
BrS: 8 (27,6%)
122
BL type 1: 29 (23,8%)
+: 10 (34,5%)
BL type 2: 27 (22,1%)
+: 4 (14,8%)
Likely pathogenic: 2 (6,9%)
BrS: 2 (7,4%)
Disease ass SNP: 2 (7,4%)
BrS: 6 (9,1%)
Ajm +: 66 (54,1%)
+: 9 (7,4%)
Arrhythmia: 1 (1,5%)
Likely pathogenic: 2 (3,0%)
Baseline (BL) type 1: diagnostic yield ~ literature
Baseline (BL) type 2 and ajm +: added value
Revision of ECGs
ECG Baseline
ECG after Ajmaline testing

proband: BrS +

Ajm +  ST segment elevation > 2mm

family member: conduction abnormality

Ajm doubtfull  ST segment elevation <
2mm

family member: BrS - ?

Ajm -  widening of QRS complex
SCN5A segregation analysis
SCN5A+ probands
24
SCN5A+ families
18
14 mutations
Segregation
4 variants
12 BrS
2 arrhythmia
4 novel
8 complete
44%
0 complete
1 complete
6%
4 major
22%
2 half
11%
3 incomplete
17%
Incomplete segregation of SCN5A mutations and variants
Is the identified mutant/variant the MAJOR causal one?
Incomplete penetrance and variable expression
Recent technological progress

Single gene analysis

GWAS
Sanger sequencing
SNP array
(Genome-wide association study)
Reference: Bezzina et al. 2013 – Nature Genetics

NGS
(Next Generation Sequencing)
Gene panels/whole exome/whole genome
NGS approach
SCN5A
‘Single gene’ (all exons of a gene)
16 BrS genes
‘Gene panel’ (all exons of a package of genes)
all genes
‘Exome’ (all exons of a genome)
± 1 % of the whole human genome
‘All’ coding sequences
of a human genome
(>180,000 exons),
sequenced and analyzed
in one experiment
Reference: Clark et al. 2011 – Nature Biotechnology - Performance
comparison of exome DNA sequencing technologies
Genome-wide technologies: impact on BrS ?

In general: rare disease diagnostics
exome sequencing
 resolution of cases : ~5%  25%

Heterogeneous genetic disorders: more complex

Effect on BrS diagnostic yield?
Cardiac arrhythmias: next generation sequencing
WHOLE EXOME SEQUENCING
TARGETED EXON
RESEQUENCING
16 BrS + / SCN5A - patients (8 families)
Gene panel for primary arrhythmias ( ± 70 genes)
Gene panel for structural cardiopathies (± 70 genes)
2 novel variant in known BrS genes
2 novel candidate genes
4 genetically ‘unresolved’ families
Functional investigations
15 patients with structural cardiopathies
Sequencing extra clinically
+ or – family members
4 known confirmed variants
Validated by Sanger
6 novel variants
+ genetic diagnosis ?
OR
functional studies required?
Brugada syndrome: Family 1
child wish
Known pathogenic SCN5A
mutation
Complete segregation with
phenotype
Brugada syndrome: Family 2
SCN5A variant
Incomplete
segregation
Gene panel in
progress
?
kinderwen
s
Brugada syndrome: Family 3
SCN5A no mutation
Exome sequencing: mutation
in candidate gene
Complete segregation with
phenotype
Challenges in cardiogenetics
diagnostics

Power of Ajmaline testing in clinical diagnosis of BrS







Helpful in genetic diagnosis
Discordancies
Diagnostic criteria too strict? Genotype-phenotype revision needed?
Appropriate patient selection for NGS
Incomplete segregation
Incomplete penetrance and variable expression
Every novel and validated variant  functional studies?
Brugada
syndrome
monogenic
oligogenic
polygenic
Impact on BrS cardiogenetics prevention


Prenatal diagnosis
Pre-implantation genetic diagnosis
 20 years of experience
 ~ 500 PGD cycles/year
 >1600 PGD children born
gene
# requests
# work-ups
# cycles for
couples (total # of
cycles)
# pregnancies
MYBPC3
6
5
3 (4)
1
MYH7
6
5
3 (5)
-
TNNT2
1
1
1
1
KCNQ1
6
6
3 (5)
3
SCN5A
5
5
1 BrS (2)
2 BrS + Steinert
(10)
1 BrS+ Bartter: (4)
2
1
Cardiomyopathies
Primary arrhythmias
!!! caution !!! : monogenic ?  oligogenic ?  complex ?
Conclusions


In order to improve cardiogenetics prevention
invest in genome-wide BrS genetic research &
diagnostics
Given oligogenic to complex nature
 large amounts of genome-wide data required

extra 5 to 10 to … years of further scientific cardiogenetic
progress are needed to resolve questions & current
challenges
Brugada team + acknowledgements
Medical genetics UZ Brussel

Clinic




Prof .Dr. Maryse Bonduelle
Dr. Marije Meuwissen
Staff



Prof. Dr. Pedro Brugada
Prof. Dr. Carlo De Asmundis
Dr. Sophie Van Malderen
Lab




Cardiology UZ Brussel
Sonia Van Dooren, Dr Sci
Dorien Daneels
Uschi Peeters
NGS platform BRIGHT


Ben Caljon
Didier Croes

Research nurse

Gudrun Pappaert
Research partner

Prof. Dr. Ramon Brugada
Funding
Wetenschappelijk fonds Willy Gepts 2010/2012
WOK Prof. P. Brugada
Basis financing RGRG cluster
IB² (Interuniversity Brussels Bioinformatics Institute)
Innoviris (BridgeIris)