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Reply: PGD and aneuploidy screening for 24 chromosomes by genome-wide SNP analysis: a responsible path towards greater utility

Published:November 17, 2011DOI:https://doi.org/10.1016/j.rbmo.2011.11.004
      There are probably more areas of agreement than disagreement between Professor Handyside and us (

      Bisignano, A., Wells, D., Harton, G., Munne, S., 2011. PGD and aneuploidy screening for 24 chromosomes: advantages and disadvantages of competing platforms. Reprod. Biomed. Online 23, 677-685

      ,

      Handyside, AH. (2011). PGD and aneuploidy screening for 24 chromosomes by genome-wide SNP analysis: seeing the wood and the trees. Reprod. BioMed. Online 23, 686-691

      ). We certainly agree with him that accurate validation is of paramount importance and that a consensus on the best way to achieve this is urgently required. At this point in time, our opinion is that array comparative genomic hybridization (CGH) has the most well-defined accuracy rate of the new comprehensive chromosome screening methods. The array-CGH approach has been evaluated in several independent laboratories, using various strategies and validated with several different cytogenetic techniques. These studies, which have been published in the literature following peer review, have all provided reassuring results concerning accuracy.
      Professor Handyside suggests that we were dismissive of the value of single-nucleotide polymorphism (SNP) data, especially in regard to its potential for detecting uniparental disomy (UPD) and providing information on parental origin of abnormalities. It is unfortunate if our article came across this way. We do see the potential merits in SNP analysis and have actually explored the use of SNP microarrays in our own laboratories. Our point is that to attempt to use this information clinically is premature. The accuracy of the data on parental origin is not clear, particularly when applied at the cleavage stage, where chromosomal mosaicism is common. Similarly, it is unclear whether UPD detected at the cleavage stage affect the entire embryo or whether they are typically present in a mosaic form. The necessary studies to determine the accuracy of parental origin and UPD analysis have not been published. Furthermore, the clinical impacts of many types of UPD remain poorly defined. Even if every cell of the embryo is affected, it is likely that many types of UPD are entirely harmless. The use of the information generated for clinical decision making and patient counselling before it is fully understood risks doing a disservice to patients and may have a negative impact on pregnancy rates.
      Our thesis is not that ‘microarray-based comparative genomic hybridization (array-CGH) is superior to the use of single-nucleotide polymorphism (SNP) genotyping arrays’ (

      Handyside, AH. (2011). PGD and aneuploidy screening for 24 chromosomes by genome-wide SNP analysis: seeing the wood and the trees. Reprod. BioMed. Online 23, 686-691

      ) but rather that, given current shortcomings of specific methods of SNP genotyping approaches and uncertainties concerning the clinical interpretation of the data produced, the technology needs more work before widespread clinical application. We agree that approaches such as karyomapping hold significant promise for the future, particularly if used for PGD of single gene disorders in conjunction with detection of chromosomal abnormalities. However, the accuracy rates need to be verified urgently. Furthermore, the price of such assays needs to be reduced and methods need to be optimized to allow results to be obtained more rapidly.
      Professor Handyside further warrants that we are directly criticizing one laboratory that uses parental support to make up for poor-quality single-cell data. Our criticism is in regard to a specific approach used to interpret data from SNP arrays and applies to any laboratory that attempts to make use of parental data, HapMap data or other unproven and undisclosed methods of haplotype reconstruction in making clinical decisions on embryos. However, we do not argue that these methods will always be untenable, but rather that in their current iteration they may be unsuitable for clinical diagnostics. In retrospect, we should have mentioned laboratories that make excellent use of SNP microarrays without relying heavily on data-imputation methods. The approach pioneered by Kearns and Treff and their colleagues (
      • Brezina P.R.
      • Benner A.
      • Rechitsky S.
      • Kuliev A.
      • Pomerantseva E.
      • Pauling D.
      • Kearns W.G.
      Single-gene testing combined with single nucleotide polymorphism microarray preimplantation genetic diagnosis for aneuploidy: a novel approach in optimizing pregnancy outcome.
      ,
      • Treff N.R.
      • Su J.
      • Tao X.
      • Levy B.
      • Scott Jr, R.T.
      Accurate single cell 24 chromosome aneuploidy screening using whole genome amplification and single nucleotide polymorphism microarrays.
      ) relies on high initial call rates and data integrity so as not to require an algorithm such as parental support. As opposed to arguing that array-CGH is better than SNP analyses, our true goal was to encourage more integrity in data analysis and validation of diagnostic capabilities.
      A specific and somewhat understandable point brought up by Professor Handyside is that our analysis of algorithms that use parental data to reconstruct faulty or missing data relies on a degree of guesswork and that we do not have access to proprietary algorithms employed by laboratories that use this technique. In our commentary, we consulted with the most current and relevant publications when considering our data analysis. We attempted to determine via simulation our ability to make use of alternative data (parental genotypes) to reconstruct faulty single-cell data. With our simulation, there were still too many errors that could not be reduced from the data. Any diagnoses drawn from this data would have been wrought with high intrinsic error rates. We admit that we cannot properly ‘simulate’ another laboratory’s proprietary algorithm so our ‘failure’ to produce reliable results may have been flawed. However, without any knowledge of the methods used by a laboratory, how can anyone verify that a technique truly yields reliable results? The concept of publishing materials and methods followed by results and conclusions is central to modern science, allowing others to verify findings and further the scientific process. Proprietary algorithms are a particularly difficult group of diagnostic tools to evaluate, and so this issue moves into a very different discussion on validation and accountability for undisclosed techniques.
      Concerning commercial issues and questions of conflict of interest, we would like to point out that none of us have any intellectual property related to array-CGH, nor do we have any interests in companies that sell microarrays. Our laboratories are not wedded to any particular technique and we would gladly switch to alternative methods of chromosome analysis if they were shown to be superior. Indeed, for many years we have been at the forefront of exploring new technologies for chromosome analysis. Conversely, many of the companies and individuals that promote the use of SNP-arrays for embryo testing have a vested interest in the technology, since they own intellectual property and/or shares linked to that specific technology.

      References

      1. Bisignano, A., Wells, D., Harton, G., Munne, S., 2011. PGD and aneuploidy screening for 24 chromosomes: advantages and disadvantages of competing platforms. Reprod. Biomed. Online 23, 677-685

        • Brezina P.R.
        • Benner A.
        • Rechitsky S.
        • Kuliev A.
        • Pomerantseva E.
        • Pauling D.
        • Kearns W.G.
        Single-gene testing combined with single nucleotide polymorphism microarray preimplantation genetic diagnosis for aneuploidy: a novel approach in optimizing pregnancy outcome.
        Fertil. Steril. 2011; 95 (e5–8): 1786
      2. Handyside, AH. (2011). PGD and aneuploidy screening for 24 chromosomes by genome-wide SNP analysis: seeing the wood and the trees. Reprod. BioMed. Online 23, 686-691

        • Treff N.R.
        • Su J.
        • Tao X.
        • Levy B.
        • Scott Jr, R.T.
        Accurate single cell 24 chromosome aneuploidy screening using whole genome amplification and single nucleotide polymorphism microarrays.
        Fertil. Steril. 2010; 94: 2017-2021

      Linked Article

      • PGD and aneuploidy screening for 24 chromosomes: advantages and disadvantages of competing platforms
        Reproductive BioMedicine OnlineVol. 23Issue 6
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          Diagnosis of embryos for chromosome abnormalities, i.e. aneuploidy screening, has been invigorated by the introduction of microarray-based testing methods allowing analysis of 24 chromosomes in one test. Recent data have been suggestive of increased implantation and pregnancy rates following microarray testing. Preimplantation genetic diagnosis for infertility aims to test for gross chromosome changes with the hope that identification and transfer of normal embryos will improve IVF outcomes. Testing by some methods, specifically single-nucleotide polymorphism (SNP) microarrays, allow for more information and potential insight into parental origin of aneuploidy and uniparental disomy.
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