Munne Overview Pgd China 2009 11 With Sound

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This is an overview of PGD, based on a talk in Hangzhou, china in 2009-11-22.
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Munne Overview Pgd China 2009 11 With Sound

  1. 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. 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. 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. 4. High rates ofHigh rates of Chromosome abnormalitiesChromosome abnormalities
  5. 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. 6. Trisomy 21
  7. 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. 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. 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. 10. MosaicismMosaicism
  11. 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. 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. 13. Reasons forReasons for Contradictory results:Contradictory results: Not optimized methodsNot optimized methods
  14. 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. 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. 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. 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. 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. 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. 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. 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. 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. 23. PGD results usingPGD results using optimized methodsoptimized methods
  24. 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. 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. 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. 27. Reduction in pregnancyReduction in pregnancy loss after PGDloss after PGD Munne et al. P <0.05 P <0.001
  28. 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. 29. PGD for RecurrentPGD for Recurrent Pregnancy Loss (RPL)Pregnancy Loss (RPL)
  30. 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. 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. 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. 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. 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. 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. 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. 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. 38. Strategies for fullStrategies for full chromosome countchromosome count
  39. 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. 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. 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. 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. 43. CGH-based DNACGH-based DNA Microarray (aCGH)Microarray (aCGH) Test DNA Normal DNA 2700 probes Same band resolution as karyotype
  44. 44. 47,XY+2
  45. 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. 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. 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. 48. SNP and CNP arrays:SNP and CNP arrays: For diagnosis of aneuploidyFor diagnosis of aneuploidy
  49. 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. 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. 51. Monosomia 11 Trisomia 21
  52. 52. Comparison ofComparison of different approachesdifferent approaches
  53. 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. 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. 55. PGD forPGD for gene defectsgene defects
  56. 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. 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. 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. 59. Gene mutation ♂ ♀ Slide adapted from A.Handyside Detection of gene mutations by SNP arrays
  60. 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

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