This is an overview of PGD, based on a talk in Hangzhou, china in 2009-11-22. It contains (not freat) sound that you can hear by clicking on the sound symbol on the lower right corner of the slide.

1. USA:
Livingston, NJ
Europe:
Barcelona, Spain
Oxford, UK
Hamburg, Germany
Asia:
Kobe, Japan
South America:
Lima, Peru
Santiago MunnéSantiago Munné
PGD: an overview

2. Indications to be discussed:Indications to be discussed:
1.1. PGD for advanced maternal agePGD for advanced maternal age
2.2. PGD for recurrent pregnancy lossPGD for recurrent pregnancy loss
3.3. PGD for translocationsPGD for translocations
4.4. PGD for gene defectsPGD for gene defects

3. - High rate of chromosome abnormalities in embryosHigh rate of chromosome abnormalities in embryos
- Hypothesis: PGD should improve ART outcomeHypothesis: PGD should improve ART outcome
- Results are not consistentResults are not consistent
- Proposed reasons:Proposed reasons: a) Mosaicisma) Mosaicism
b) Self-correctionb) Self-correction
c) Biopsy damagec) Biopsy damage
d) Methods usedd) Methods used
- Optimized methods can produce good results- Optimized methods can produce good results
- New methods (CGH, aCGH) may produce better resultsNew methods (CGH, aCGH) may produce better results
- New methods can also be used for gene defect detectionNew methods can also be used for gene defect detection
PGD for advanced maternal age: summaryPGD for advanced maternal age: summary

4. High rates ofHigh rates of
Chromosome abnormalitiesChromosome abnormalities

5. embryos analyzed: 6054. Morphologically normal embryos: 3751. Source: Munnembryos analyzed: 6054. Morphologically normal embryos: 3751. Source: Munnéé et al. 2007.et al. 2007.
Similar results also found by Munne et al 1995, Marquez et al. 2000, Magli et al. 2007.Similar results also found by Munne et al 1995, Marquez et al. 2000, Magli et al. 2007.
% chromosomally
abnormal embryos
56%
Maternal age
Morphology:
The majority of embryos with ‘good’The majority of embryos with ‘good’
morphology are chromosomally abnormalmorphology are chromosomally abnormal

6. Trisomy 21

7. Despite large studies indicating theDespite large studies indicating the
advantages of aneuploidy screening, theadvantages of aneuploidy screening, the
notion that PGS for infertility is beneficial isnotion that PGS for infertility is beneficial is
not yet shared uniformly.not yet shared uniformly.

8. Contradicting PGD resultsContradicting PGD results
using day 3 biopsy and FISHusing day 3 biopsy and FISH
Positive effect
Gianaroli et al. 1999
Munne et al 1999
Gianaroli et al 2001a
Gianaroli et al. 2001b
Munne et al. 2003
Gianaroli et al. 2004
Munne et al. 2005
Munne et al 2006
Verlinsky et al. 2005
Colls et al. 2007
Garrisi et al. 2009
Rubio et al. 2009
No effect (small)
Werlin et al. 2003
Jansen et al. 2008
Mersereau et al. 2008
Schoolcraft et al. 2009
No effect (Large)
Staessen et al. 2004
Platteau et al. 2005
Negative effect
Mastenbroek et al. 2007
Hardarson et al. 2008

9. Contradicting PGD resultsContradicting PGD results
using day 3 biopsy and FISHusing day 3 biopsy and FISH
Proposed explanations:
1) Mosaicism
2) Embryo biopsy damage
3) Sub-optimal PGD methods

10. MosaicismMosaicism

11. 592 embryos found abnormal by PGD were reanalyzed and found to be:592 embryos found abnormal by PGD were reanalyzed and found to be:
normalnormal 1313
mosaic <49% abnormalmosaic <49% abnormal 2727
mosaic 50-99% abnormalmosaic 50-99% abnormal 124124
mosaic 100% abnormalmosaic 100% abnormal 297297
homogeneously abnormalhomogeneously abnormal 131131
Colls et al. (2007)Colls et al. (2007)
Mosaicism produces <7% misdiagnosisMosaicism produces <7% misdiagnosis
1[13]1[16]2[18]2[21]1[22]
2[13]1[16]2[18]2[21]2[22]
1[13]1[16]2[18]2[21]1[22]
1[16] 2[13]2[16]2[18]2[21]2[22]
2[13]1[16]2[18]1[21]1[22]
2[13]3[18]1[21]1[22]
3[13]1[16]2[18]1[21]3[22]
1[13]1[16]1[18]1[21]1[22]
3[13]1[16]2[18]1[21]3[22]
6.8%6.8%

12. The FISH error of the assay translates into aThe FISH error of the assay translates into a
clinical misdiagnosis rate of 0.5%clinical misdiagnosis rate of 0.5%
NEGATIVE PREDICTIVE VALUE:NEGATIVE PREDICTIVE VALUE: 99.5%99.5%
- Data from >150 IVF centers referring to ReprogeneticsData from >150 IVF centers referring to Reprogenetics
- 10 aneuploid abortions of 2148 implanted fetuses10 aneuploid abortions of 2148 implanted fetuses
- Average maternal age = 37 years- Average maternal age = 37 years
Clinical misdiagnosisClinical misdiagnosis

13. Reasons forReasons for
Contradictory results:Contradictory results:
Not optimized methodsNot optimized methods

14. Optimal PGSOptimal PGS Questionable PGSQuestionable PGS
Biopsy mediaBiopsy media with aminoacidswith aminoacids simple mediasimple media
Biopsy time / embryoBiopsy time / embryo 1 min1 min > 5 min> 5 min
# cells biopsied# cells biopsied oneone twotwo
Fixation methodFixation method Carnoy’sCarnoy’s Tween 20Tween 20
# chromosomes tested# chromosomes tested ≥8≥8 ≤≤66
# analysts / case# analysts / case 22 11
Use of NRR*Use of NRR* yesyes nono
Large experienceLarge experience yesyes nono
Error rateError rate <10%<10% 10-50%10-50%
Number of zygotesNumber of zygotes >5>5 ≤≤ 55
*NRR: No result rescue, or re-testing of dubious chromosome with different probes.
Optimal PGS methodsOptimal PGS methods

15. “ The data presented here clearly indicates that two cell
biopsy significantly impacts clinical outcome. Our
previous report providing no arguments in favour of PGS
(Staessen et al., 2004) was criticised by others arguing
that PGS might have been beneficial if only one cell had
been removed (Cohen et al., 2007). In respect to the
present findings, this criticism seems justified”.
P < 0.001
Two cell biopsy is detrimentalTwo cell biopsy is detrimental

16. CONTROL 2-CELLS
BIOPSIED
Staessen et al (2004)
11.5%
17.1%
Implantation Staessen et al. (2004):
- No significant differences
- But 2 cells biopsied
Studies using two-cell biopsyStudies using two-cell biopsy

17. 1)1) 20% of20% of cyclescycles undiagnosed (literature: 1-3% ofundiagnosed (literature: 1-3% of embryosembryos *)*)
2) 59% implantation reduction due to biopsy:2) 59% implantation reduction due to biopsy:
3)3) Average number of embryos analyzed was only 5Average number of embryos analyzed was only 5
4) Chromosomes 15 and 22 (21% abnormalities) not analyzed4) Chromosomes 15 and 22 (21% abnormalities) not analyzed
59% reduction59% reduction
implantationimplantation
ControlControl 14.7%14.7%
Biopsied, no PGDBiopsied, no PGD 6.0%6.0%
Biopsied and PGDBiopsied and PGD 16.8%16.8%
* 1% Gianaroli et al. (2004), 3.1% Colls et al. (2007)
PGD for AMA: randomized studiesPGD for AMA: randomized studies
Mastenbroek et al. (2007)Mastenbroek et al. (2007)

18. Twin 20 method Carnoy’s methodVelilla et al. 2002
Optimal method: modified Carnoy’sOptimal method: modified Carnoy’s
• Provides largest nuclear diameterProvides largest nuclear diameter
• The least overlapsThe least overlaps
• The lowest error (10% vs. 30%)The lowest error (10% vs. 30%)
Optimal fixation methodsOptimal fixation methods

19. p13
p12
p11.2
q11.2
q21
q22.1
q22.2
q22.3
p13
p12
p11.2
q11.2
q21
q22.1
q22.2
q22.3
Colls et al. (2007)
Probe
LSI 21
Probe
Tel 21q
No Result Rescue (NRR): alternative-locusNo Result Rescue (NRR): alternative-locus
probes to resolve unclear resultsprobes to resolve unclear results

20. NoNo False +False +
ResultsResults ErrorsErrors
Without NRRWithout NRR 7.5%7.5% 7.2%7.2%
NRRNRR 3.2%3.2% 4.7%4.7%
NRR: No Result Rescue, from: Colls et al. (2007)NRR: No Result Rescue, from: Colls et al. (2007)
No Result Rescue (NRR): alternative-locusNo Result Rescue (NRR): alternative-locus
probes to resolve unclear resultsprobes to resolve unclear results

21. Analysis of remaining cells of embryos previously analyzed by PGD:Analysis of remaining cells of embryos previously analyzed by PGD:
studystudy error rateerror rate
Baart et al 2004Baart et al 2004 50.0%50.0%
Li et al. 2005Li et al. 2005 40.0%40.0%
Gleicher et al. 2009Gleicher et al. 2009 15-20%15-20%
Munne et al. 2002Munne et al. 2002 7.2%7.2%
Colls et al., 2007Colls et al., 2007 4.7%4.7%
Magli et al. 2007Magli et al. 2007 3.7%3.7%
Error rate should be <10%Error rate should be <10%

22. At least 9 chromosomes should be tested:At least 9 chromosomes should be tested:
# chromosomes# chromosomes % abnormal% abnormal
analyzedanalyzed fetuses detectablefetuses detectable
55 28%28%
66 47%47%
99 70%70%
1212 80%80%
2424 100%100%
Number of chromosomes analyzedNumber of chromosomes analyzed

23. PGD results usingPGD results using
optimized methodsoptimized methods

24. Aneuploidy rates for chromosomes X,Y,13,18,21. Munne et al. 2006 and Reprogenetics data up
to 10/2007. Average age 37, Observed: Based on 2300 pregnancies after PGD, Expected: Eiben et
al. 1994. Observed and expected adjusted by maternal ages
P<0.001
Significant reduction inSignificant reduction in
Trisomic offspringTrisomic offspring

25. Gianaroli 1999 Munne 2003
Control PGS Control PGS
# cases 135 127 103 103
Mean age 36 36 40 40
Fetal heart 12% 24% 10% 20%
Prospective matched studies. Chromosomes analyzed: X,Y,13,18,21 +Prospective matched studies. Chromosomes analyzed: X,Y,13,18,21 + 15,16,2215,16,22
P<0.001 P<0.005
Gianaroli et al 1999 Munne et al. 2003
Improved implantation rateImproved implantation rate
After PGDAfter PGD

26. 39.4%39.4%
SART-ASRM (2005)
53.3%53.3%
13.3%13.3%
17.7%17.7%
26.2%26.2%
Pregnancy loss in IVFPregnancy loss in IVF

27. Reduction in pregnancyReduction in pregnancy
loss after PGDloss after PGD
Munne et al.
P <0.05 P <0.001

28. Patients 38-42, FISH with 9-probes, 1 cell biopsied, SART data of 5 centers with >10%
PGD cases, 2003-2005, Munné et al. (2007) SART; a= p<0.01 b= p<0.001
Controls PGD
Clinic cycles Loss
rate
Live
birth
cycles Loss
rate
Live
birth
1 505 27% 35% 70 22% 40%
2 210 36% 14% 72 27% 15%
3 1204 34% 12% 120 15% 23%
4 509 29% 15% 236 26% 22%
5 191 25% 17% 208 16% 25%
Total 2619 30%a 18%b 706 21%a 24%b
Ongoing pregnancy rates after PGD:Ongoing pregnancy rates after PGD:
Data from five IVF centersData from five IVF centers

29. PGD for RecurrentPGD for Recurrent
Pregnancy Loss (RPL)Pregnancy Loss (RPL)

30. • Defined as 3 or more lost pregnanciesDefined as 3 or more lost pregnancies
• It occurs in 1% of fertile populationIt occurs in 1% of fertile population
• Attributed to anatomic, endocrine,Attributed to anatomic, endocrine,
immunological or genetic problems but …immunological or genetic problems but …
• ……>50% of RPL cases are UNEXPLAINED>50% of RPL cases are UNEXPLAINED
BACKGROUND OF RPLBACKGROUND OF RPL

31. • Werlin L, et al. (2003) Preimplantation genetic diagnosis (PGD) as both a
therapeutic and diagnostic tool in assisted reproductive technology. Fertil Steril,
80:467
• Munné et al. (2005) Preimplantation genetic diagnosis reduces pregnancy loss in
women 35 and older with a history of recurrent miscarriages. Fertil Steril 84:331
• Munné et al. (2006) PGD for recurrent pregnancy loss can be effective in all age
groups. Abstract PGDIS
• Garrisi et al. (2008) Preimplantation genetic diagnosis (PGD) effectively reduces
idiopathic recurrent pregnancy loss (RPL) among patients with up to 5 previous
consecutive miscarriages after natural conceptions. Fertil. Steril in press
Idiopathic RPL :
All controlled PGD studies on idiopathicAll controlled PGD studies on idiopathic
RPL show a decrease in miscarriagesRPL show a decrease in miscarriages
• Rubio et al. (in press) Prognosis factors for Preimplantation Genetic Screening
in repeated pregnancy loss. Reprod Biomed Online, in press

32. N=122N=122
With ≥3With ≥3
previousprevious
losseslosses
*Munné et al. 2005 and unpublished data, **Brigham et al. 1999*Munné et al. 2005 and unpublished data, **Brigham et al. 1999
P<0.05 P<0.001 P<0.001
8%
16%
12%
33%
44%
39%
94%
85%
89%
*
**
Reduction in miscarriagesReduction in miscarriages
in RPL after PGDin RPL after PGD

33. PGD results according to previous number of miscarriagesPGD results according to previous number of miscarriages
# previous# previous % loss% loss % loss% loss
miscarriagesmiscarriages cyclescycles expectedexpected after PGDafter PGD
22 7676 31%31% 13%13% NSNS
3-53-5 179179 40%40% 14%14% p<0.025p<0.025
>5>5 2424 48%48% 29%29% NSNS
Garrisi et al. (2008)Garrisi et al. (2008)
Reduction in miscarriagesReduction in miscarriages
in RPL after PGDin RPL after PGD

34. PGD results according to age when previous number ofPGD results according to age when previous number of
miscarriages is 3-5miscarriages is 3-5
maternalmaternal % loss% loss % loss% loss
ageage cyclescycles expectedexpected after PGDafter PGD
<38<38 8383 36%36% 14%14% p<0.05p<0.05
≥≥3838 9696 44%44% 14%14% p<0.005p<0.005
Garrisi et al. (2008)Garrisi et al. (2008)
Reduction in miscarriagesReduction in miscarriages
in RPL after PGDin RPL after PGD

35. PGD results according to fertilityPGD results according to fertility
methodmethod cyclescycles % loss% loss % loss% loss %%
conceptionconception expectedexpected after PGDafter PGD pp to termto term
IVFIVF 115115 35%35% 14%14% p<0.01p<0.01 34%34%
naturalnatural 124124 41%41% 15%15% p<0.005p<0.005 37%37%
Average maternal age: 37.5Average maternal age: 37.5
Garrisi et al. (2008)Garrisi et al. (2008)
Reduction in miscarriagesReduction in miscarriages
in RPL after PGDin RPL after PGD

36. • Munné et al (1998). Spontaneous abortions are reduced after pre-conception
diagnosis of translocations. J Assited Reprod Genet 290:
• Munné S et al. (2000) Outcome of Preimplantation Genetic Diagnosis of
translocations. Fertil Steril. 73:1209
• Verlinsky et al. (2005) Preimplantation testing for chromosomal disorders improves
reproductive outcome of poor prognosis patients. Reprod Biomed Online 11:219
• Otani et al.(2006) Preimplantation genetic diagnosis significantly improves the
pregnancy outcome of translocation carriers with a history of recurrent
miscarriage and failing to produce a live birth. Reprod Biomed Online 13: 879
RPL due to translocations:
• Munné S (2006) Preimplantation genetic diagnosis for translocations. Hum Reprod 21:839
All PGD studies on RPL for translocationsAll PGD studies on RPL for translocations
show a decrease in miscarriagesshow a decrease in miscarriages

37. PatientsPatients successfulsuccessful Risk ofRisk of timetime
pregnanciespregnancies miscarriagemiscarriage frameframe
(cumulative)(cumulative)
with PGDwith PGD
11 4343 33%33% 17%17% 1.4 cycles (<4 months)1.4 cycles (<4 months)
22 200200 26%26% 11 %11 % 1.4 cycles (<4 months)1.4 cycles (<4 months)
33 5252 52%52% 18%18% 1.4 cycles1.4 cycles (<4 months)(<4 months)
without PGDwithout PGD
44 4747 32%32% 68%68% 11.5 months11.5 months
55 4747 68%68% 65%65% 23.3 months23.3 months
66 4141 74%74% 26%26% 6 years6 years
77 2828 64%64% 38%38% 4.2 years4.2 years
1: Lim et al.1: Lim et al. (2004), 2: Munne et al. (2006d) and unpublished, 3:(2004), 2: Munne et al. (2006d) and unpublished, 3: Otani et al. (2006) and unpublished results, 4: Sugiura-Otani et al. (2006) and unpublished results, 4: Sugiura-
Ogasawara et al. (2004)(a), 5: Sugiura-Ogasawara et al. (2004)(b), 6: Goddjin et al (2004)(e); 7: Stephenson and sierra (2006)Ogasawara et al. (2004)(a), 5: Sugiura-Ogasawara et al. (2004)(b), 6: Goddjin et al (2004)(e); 7: Stephenson and sierra (2006)
PGD for translocations is better optionPGD for translocations is better option
than natural cyclethan natural cycle

38. Strategies for fullStrategies for full
chromosome countchromosome count

39. • Sequential FISH with 24 probesSequential FISH with 24 probes
• Comparative Genome Hybridization (CGH)Comparative Genome Hybridization (CGH)
• Array CGHArray CGH
• Single Nucleotide Polymorphism (SNP) arraySingle Nucleotide Polymorphism (SNP) array
– Interpretation: standardInterpretation: standard
– Interpretation: bioinformaticsInterpretation: bioinformatics
– Interpretation: KaryomappingInterpretation: Karyomapping
Different strategies forDifferent strategies for
Analyzing all chromosomesAnalyzing all chromosomes

40. Kallioniemi et al. (1992), applied to single cells by Wells et al. (1999)
• Technique related to FISHTechnique related to FISH
• Allows the copy number of every chromosome to be determinedAllows the copy number of every chromosome to be determined
NormalNormal TrisomyTrisomy MonosomyMonosomy
Normal DNANormal DNATest DNATest DNA
Comparative GenomeComparative Genome
Hybridization (CGH)Hybridization (CGH)

41. CGH on blastocyst biopsies:CGH on blastocyst biopsies:
AdvantagesAdvantages
Disadvantages:
-Time consuming: requires embryo freezing
Advantages:
- Reduced impact of embryo biopsy
- More cells biopsied: more robust diagnosis
- Less risk of mosaicism misdiagnosis
- 100% detected aneuploidies
- No need for fixing cells or testing parental DNA

42. CyclesCycles Mat.Mat. Prev.Prev. embryosembryos pregnancy implant.pregnancy implant.
ageage failedfailed replacedreplaced raterate raterate
cyclescycles
Test :Test : 7070 37.737.7 2.42.4 2.02.0 81%81% 62%62%
control :control : 272272 37.137.1 1.21.2 2.72.7 57%57% 35%35%
p<0.0001p<0.0001 p<0.001p<0.001
Schoolcraft et al. (2009, ASRM)Schoolcraft et al. (2009, ASRM)
24 chromosome analysis in24 chromosome analysis in
blastocyst biopsies: clinical resultsblastocyst biopsies: clinical results

43. CGH-based DNACGH-based DNA
Microarray (aCGH)Microarray (aCGH)
Test
DNA
Normal
DNA
2700 probes
Same band resolution as karyotype

44. 47,XY+2

45. aCGH advantagesaCGH advantages
• aCGH Results inaCGH Results in 2424 hours, allowing either PB, day 3 orhours, allowing either PB, day 3 or
blastocyst biopsyblastocyst biopsy
• parental DNAparental DNA notnot needed: procedure can be decided onneeded: procedure can be decided on
same day of biopsysame day of biopsy
• Is quantitative detecting mitotic-origin aneuploidy andIs quantitative detecting mitotic-origin aneuploidy and
MII mitotic errors without crossing-over (SNP arrayMII mitotic errors without crossing-over (SNP array
methods that are only qualitative do not detect them).methods that are only qualitative do not detect them).

46. 46,XX-10 +16
aCGH detectedaCGH detected 50%50% more abnormalities than FISH-12 andmore abnormalities than FISH-12 and 20%20%
more abnormal embryos (Colls et al. 2009)more abnormal embryos (Colls et al. 2009)
Detection of abnormalities:Detection of abnormalities:
aCGH vs FISH-12aCGH vs FISH-12

47. aCGH validation: error rateaCGH validation: error rate
• Validation method: Reanalysis of the rest of the embryoValidation method: Reanalysis of the rest of the embryo
by FISH with 12 chromosomes plus those found abnormalby FISH with 12 chromosomes plus those found abnormal
by aCGHby aCGH
• Error rate (biopsy day 3):Error rate (biopsy day 3): 6%6% (same as expected by(same as expected by
mosaicism)mosaicism)
• Cells with no results:Cells with no results: 1%1%

48. SNP and CNP arrays:SNP and CNP arrays:
For diagnosis of aneuploidyFor diagnosis of aneuploidy

49. • SNP: Single Nucleotide PolymorphismSNP: Single Nucleotide Polymorphism
• They are normally occurring genetic variantThey are normally occurring genetic variant
• 1,854,000 identified so far1,854,000 identified so far
• 99% inherited99% inherited
What are SNPs?What are SNPs?
Microarray Example:Microarray Example:
Affimetrix SNP 6.0 chip can measureAffimetrix SNP 6.0 chip can measure
simultaneously 900,000 SNPs and CNPs atsimultaneously 900,000 SNPs and CNPs at
1.8 million genome locations1.8 million genome locations

50. Analysis with karyomapping:Analysis with karyomapping:
Handyside’ teamHandyside’ team
• SNP array method based on mapping crossovers between
parental haplotypes
• Requires previous genotyping of parents and family
member(s) with SNP arrays
• Mendelian analysis of parental and grandparental
haplotypes
• Construction of karyomaps identifying the parental and
grandparental origin of each chromosome or chromosome
segment in each embryo
• Developed by Handyside, Thornhill, Harton, Mariani, Affara
and Griffin
Slide adapted from A.Handyside

51. Monosomia 11
Trisomia 21

52. Comparison ofComparison of
different approachesdifferent approaches

53. Comparison of platformsComparison of platforms
FISH 12FISH 12 CGHCGH arrayarray SNPSNP
probesprobes CGHCGH arraysarrays
Day 3 biopsy/ day 5 resultsDay 3 biopsy/ day 5 results yesyes nono yesyes yesyes
Parental DNA neededParental DNA needed nono nono nono yesyes
Detect gene defectsDetect gene defects nono nono nono yesyes
Detect polyploidy (risk error)Detect polyploidy (risk error) yesyes no (0.2%)no (0.2%) no (0.2%)no (0.2%) yesyes
Detect MII errors w/o crossoverDetect MII errors w/o crossover yesyes yesyes yesyes no?no?
Detect mitotic errorsDetect mitotic errors yesyes yesyes yesyes no?no?
Error rateError rate 77%% 8%8% 6%6% unkunk
No Results RateNo Results Rate 3.2%3.2% 9%9% 0%0% unkunk
Increased implantation rateIncreased implantation rate ++ + + ++ + + unkunk unkunk
Reprogenetics data.Reprogenetics data.

54. BiopsyBiopsy AnalysisAnalysis cyclecycle implantation Commentsimplantation Comments teamteam
dayday replacedreplaced improvementimprovement
PBPB FISHFISH samesame ++ only MI and MII abnormalitiesonly MI and MII abnormalities RGIRGI
PBPB CGHCGH samesame ++ applied to young donorsapplied to young donors SherSher
day 3day 3 FISHFISH samesame ++ 9-12 chromosomes, 5% errors9-12 chromosomes, 5% errors ReprogeneticsReprogenetics
day 3day 3 FISHFISH samesame ++ 9-12 chromosomes, 5% errors9-12 chromosomes, 5% errors SISMErSISMEr
day 3day 3 FISHFISH samesame - - - -- - - - severe biopsy damage, etc, etcsevere biopsy damage, etc, etc MastenbroekMastenbroek
day 3day 3 CGHCGH samesame ++ // -- SherSher
day 3day 3 aCGHaCGH samesame pre-clinicalpre-clinical ReprogeneticsReprogenetics
day 3day 3 SNP arraySNP array samesame pre-clinicalpre-clinical Some MII errors, mitotic notSome MII errors, mitotic not RMA / BridgeRMA / Bridge
detected?detected? Kearns / GSNKearns / GSN
blastocystblastocyst FISHFISH samesame ++ // -- 5 probes/ scoring too stringent?5 probes/ scoring too stringent? Sydney IVFSydney IVF
blastocystblastocyst CGHCGH nextnext + + ++ + + BEST RESULTS SO FARBEST RESULTS SO FAR Reprogenetics /Reprogenetics /
SchoolcraftSchoolcraft
What matters most?What matters most?
Biopsy or information quality?Biopsy or information quality?

55. PGD forPGD for
gene defectsgene defects

56. PGD for gene disordersPGD for gene disorders
Disease tested: Acetil Co Oxidase type I defficiency, Adrenoleucodistrophy, Alpha-thalassemia, Alport syndrome,
Autosomal Dominant Polycystic Kidney Disease (ADPKD), Autosomal Recesive Polycystic Kidney Disease (ARPKD),
Beta-thalassemia, Branchio-Oto-Renal syndrome (BOR), BRCA1 breast cancer predisposition, BRCA2 breast cancer
predisposition, CanavanCharcot-Marie-Tooth type IA (CMT1a), Choroideremia, Congenital adrenal hyperplasia (CAH),
Congenital neutropenia, Connexin 26 hearing loss, Cystic fibrosis, Duchenne/Becker Muscular Dystrophy (DMD),
Ectrodactyly, Ectodermal dysplasia, and Cleft lip/palate syndrome (EEC1), Fabry Disease, Familial adenomatous poliposis
coli (FAP), Familial dysautonomia, Familial intrahepatic cholestasis 2, Fanconi anemia, Fragile site mental retardation ,
Gangliosidosis type 1 (GM1), Gaucher disease, Glomuvenous malformations (GVM), Glycogen-storage disease type I
(GSD1), Glycosylation type 1C, Hemoglobin SC disease, Hemophilia A, Hemophilia B, Hereditary nonpolyposis colon
cancer (HNPCC), Hereditary pancreatitis, HLA matching Huntington disease, Hurler syndrome, Hypophosphatasia,
Incontinential pigmenti, Krabbe disease (Globoid cell leukodystrophy), Long QT syndrome, Marfan syndrome, Meckle
gruber, Metachromatic leukodystrophy (MLD), Methylmalonic aciduria cblC type (MMACHC), Myotonic Dystrophy 1,
Myotubular myopathy, Neurofibromatosis 1, Neurofibromatosis 2, Niemann-Pick Disease, Noonan syndrome,
Oculocutaneous albinism 1 (OCA1), Ornithine carbamoyltransferase deficiency (OTC), Osteogenesis Imperfecta 1, Rapp
Hodgkin ectodermal dysplasia, Retinitis pigmentosa, Retinoblastoma, Sickle Cell Anemia, Smith-Lemli-Opitz syndrome
(SLOS), Spinal bulbar muscular atrophy (SBMA), Spinal Muscular Atrophy Type 1 (SMA1), Tay Sachs, Tuberous
sclerosis 1 (TSC1), Tuberous sclerosis 2 (TSC2), Von Hippel-Lindau Syndrome (vHL), X-linked dominant Charcot–Marie–
Tooth (CMTX), etc…… (see review Gutierrez et al. (2008))
We can do PGD for any disease with known mutation

57. accurateaccurate
amplificationamplification
of both lociof both loci
ADO affectingADO affecting
normal allelenormal allele
ADO affectingADO affecting
mutation sitemutation site
Mutation siteMutation site
PolymorphicPolymorphic
sitesite
Conventional approach to PGD of geneConventional approach to PGD of gene
defects to avoid Allele Drop Out (ADO)defects to avoid Allele Drop Out (ADO)

58. Maternal DNAMaternal DNA
Paternal DNAPaternal DNA
PossiblePossible
embryoembryo
genotypesgenotypes
ContaminationContamination
Maternal contaminantMaternal contaminant
(e.g. cumulus cell)(e.g. cumulus cell)
Unknown contaminantUnknown contaminant
(e.g. skin cells from(e.g. skin cells from
lab staff)lab staff)
DNA fingerprinting against contaminationDNA fingerprinting against contamination

59. Gene mutation
♂ ♀
Slide adapted from A.Handyside
Detection of gene mutations by SNP arrays

60. Santiago Munné, PhD, DirectorSantiago Munné, PhD, Director
Jacques Cohen, PhD, DirectorJacques Cohen, PhD, Director
munne@reprogenetics.communne@reprogenetics.com
www.reprogenetics.comwww.reprogenetics.com
Pere Colls, PhDPere Colls, PhD
Dagan Wells, PhDDagan Wells, PhD
George Pieczenik, PhDGeorge Pieczenik, PhD
Cristina Gutiérrez, PhDCristina Gutiérrez, PhD
Jorge Sanchez, PhDJorge Sanchez, PhD
John Zheng, MDJohn Zheng, MD
Tomas Escudero, MSTomas Escudero, MS
Kelly Ketterson, MSKelly Ketterson, MS
Jill Fischer, MSJill Fischer, MS
Jessica Vega, MSJessica Vega, MS
Tim Schimmel, BSTim Schimmel, BS
Sasha Sadowy, BSSasha Sadowy, BS
Sophia Tormasi, BSSophia Tormasi, BS
N-neka Goodall, BSN-neka Goodall, BS
Renata Prates, BSRenata Prates, BS
Piedad GarzonPiedad Garzon
Laurie FerraraLaurie Ferrara
Bekka Sellon-WrightBekka Sellon-Wright
Maria FeldhausMaria Feldhaus
USAUSA
SpainSpain
Mireia Sandalinas, MSMireia Sandalinas, MS
Carles Giménez, PhDCarles Giménez, PhD
César Arjona, MSCésar Arjona, MS
Ana Jiménez, PhDAna Jiménez, PhD
Elena Garcia, MSElena Garcia, MS
JapanJapan
Tetsuo Otani, MDTetsuo Otani, MD
Muriel RocheMuriel Roche
Miho MizuikeMiho Mizuike
UKUK
Dagan Wells, PhDDagan Wells, PhD
Elpida Fragouli, PhDElpida Fragouli, PhD
Samer Alfarawati, MSSamer Alfarawati, MS
South AmericaSouth America
Paul Lopez, BSPaul Lopez, BS
Luis Alberto Guzman, BSLuis Alberto Guzman, BS
Francisco Parera, PhDFrancisco Parera, PhD
GermanyGermany
Karsten Held, MDKarsten Held, MD