Preimplantation genetic diagnosis (PGD) is a procedure used by fertile or infertile couples at high risk of transmitting a genetic condition and allows diagnosis of single gene disorders, chromosomal abnormalities or HLA typing in embryos prior to transfer and implantation. In this way it offers an alternative to prenatal diagnosis by chorion villus sampling (CVS) or amniocentesis (AC) and termination of pregnancy. Preimplantation genetic screening for aneuploidy (PGS) is a related procedure that is offered to infertile couples with advanced age of the female partner, previously failed in vitro fertilization (IVF) treatment or unexplained recurrent miscarriage, with the aim of improving the success rate of IVF. It allows the enumeration of chosen chromosome pairs and can be considered as an early form of prenatal aneuploidy screening. Ever since the first application of the technique in 1990 (Handyside et al., 1990; Verlinsky et al., 1990), the number of indications for PGD has increased considerably, as has the number of couples filing a request, and over 15000 cycles of PGD/PGS have been registered in Europe alone, resulting in over 2000 births (Sermon et al., 2004; Goossens et al., 2008).
The patients that attend the PGD clinic are often not aware of the risks and benefits, the pros and cons, the larger implications of a treatment with ovarian stimulation, oocyte retrieval, intracytoplasmic sperm retrieval (ICSI) and PGD. Many patients requesting PGD do not suffer from infertility. They request PGD for the mere goal of avoiding their children to be affected or carrier of a specific genetic disorder, or to eradicate a genetic condition from their family. Patients requesting PGS on the other hand, are very much aware of their infertile status, and aim to increase pregnancy rate and avoid miscarriages and trisomic children by genetic selection of their embryos. However they are equally not always informed about the risks and limitations of such techniques. The analyses and results presented in this overview are aimed at providing patients requesting PGD or PGS correct information on reproductive outcome, contribution to that outcome by identifiable factors and risks associated with this technique.
Indications for PGD
The most common indication for PGD is cystic fibrosis (CF) (Gutiérrez-Mateo et al., 2009), which was the first monogenic disorder to be diagnosed by PGD (Handyside et al., 1992) A list of most common indications is shown in Table I. Most couples requesting PGD for CF do so because they have been identified as carriers at screening prior to reproductive treatment. The close interface between genetics and reproductive medicine is illustrated by the fact that a number of these couples have been unsuccessful at conceiving due to obstructive azoospermia secondary to congenital bilateral absence of the vas deferens (CBAVD) which is shown to be associated with carrier or affected status of CF in at least 80% of cases (Lissens et al., 1996). Another challenge for reproductive physicians and geneticists is the reproductive treatment with PGD of CF affected women who often present with significant health problems and use of a significant amount of medication.
Most common indications for PGD or PGS
In the population studied in current PGD practice at our centre, the most common indications for PGD are myotonic dystrophy type 1 (syn: dystrophia myotonica type 1; DM1; Steinert’s disease; OMIM #160900), Huntington disease (OMIM +143100) and Fragile X syndrome (OMIM #300624) (for a list of all indications see Table 2). This selection is mainly due to the expertise developed in the detection of triplet repeat disorders at single cell level, rather than a high incidence of these disorders in the Flemish population. Approximately 30% of the population requesting PGD comes from abroad. The relevance of studying reproductive outcome in this population is again illustrated by the fact that triplet repeat disorders are commonly associated with infertility problems, including poor sperm quality in DM1 men and risk of premature ovarian failure in female fragile X carriers, more in particular those with premutations in the Fragile X mental retardation protein (FMRP) gene (Platteau et al., 2002).
Indications for PGD in the study cohort 1993-2005 at UZ Brussel PGD clinic.
PGS is a technique allowing chromosomal aneuploidy analysis by fluorescence in situ hybridization (FISH) in pre-transfer embryos following in vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI), and can be considered as an early form of prenatal screening for numerical chromosomal abnormalities. Many studies have argued a potential benefit of PGS in couples at high risk of chromosomally abnormal embryos, including in cases of advanced maternal age (Gianaroli et al., 1999; Kuliev et al., 2003; Munné et al., 2003; Platteau et al., 2005a), recurrent miscarriage (Pellicer et al., 1999; Rubio et al., 2005; Gianaroli et al., 2005; Munné et al., 2005; Platteau et al., 2005b) and recurrent implantation failure (Pehlivan et al., 2003; Wilding et al., 2004), whereas other authors have not been able to find an unequivocal benefit (Staessen et al., 2004; Mastenbroek et al., 2007) or have found restrictions to the clinical benefit when a low number of embryos is available for analysis (Munné et al., 2003; Platteau et al., 2005a). The clinical benefit of PGS in improving live birth rate may therefore be under scrutiny, but this technique may appear to be useful in improving selection of euploid embryos, thereby reducing implantation failure and miscarriage rates (for review see Donoso P et al., 2007).
Reproductive techniques used in PGD
In our program, pituitary desensitisation was carried out in an agonist protocol, using GnRH analogues (buserelin, Suprefact°; Hoechst, Frankfurt, Germany), in combination with ovarian stimulation with human menopausal gonadotrophins (hMG) (Menopur°, Ferring Pharmaceuticals A/S, Copenhagen, Denmark) or recombinant FSH (Puregon°, Schering-Plough, Oss, The Netherlands) (Van de Velde et al., 1998), or in an antagonist protocol with a GnRH antagonist (ganirelix, Orgalutran°, Schering-Plough) combined with recombinant FSH or hMG (Kolibianakis et al., 2004). The starting dose of gonadotrophins was based on the female partner’s age, preliminary ovarian response assessment and/or previous response to ovarian stimulation (range 75–450 IU). Human chorionic gonadotrophin (hCG) (10000IU, Pregnyl; Schering-Plough or Profasi°, Merck-Serono, Geneva, Switzerland) was administered for final oocyte maturation. Transvaginal ultrasound-guided oocyte collection (OC) was scheduled 36 hours after hCG administration. Oocyte collection (OC) was carried out under premedication with pethidine 1 mg/kg IM and paracervical block with mepivacaine hydrochloride, or under general anaesthesia as and when indicated (Van de Velde et al., 1998, Kolibianakis et al., 2004).
The details of the IVF and ICSI procedure have been described previously (Van Landuyt et al., 2005). In the event of PGD/PGS, ICSI was the method of choice rather than classical IVF to prevent contamination with residual sperm DNA in case of PCR-based PGD (Liebaers et al., 1998) and to maximise the fertilisation rate in PGS. Fertilisation was assessed 16 to 18 hours after ICSI. Further development was evaluated in the morning of day two and again on day three, when embryos are evaluated before biopsy. According to the number of anucleate fragments, the embryos are subdivided into grades A, B, C and D as described previously (Vandervorst et al., 1998). From the 5-cell stage onwards for FISH analysis and from the 6- cell stage onwards, embryo biopsy of grade A, B and C performed on day 3 of culture. In the initial stages of PGD at our centre, an acid solution (Tyrode’s solution) was used to breach the zona pellucida. Laser assisted biopsy has been applied since June 1999 as previously described (De Vos et al., 2001; Sermon, 2002). Overall the aspiration method was used to remove one or two blastomeres from the embryo (Fig. 1, 2). For PCR analysis, each blastomere was placed in a solution that lyses the cell and releases the DNA (Sermon et al., 2004). For Fluorescence In Situ Hybridisation (FISH) purposes, a blastomere was spread on a slide using the HCl/Tween 20 method (Coonen et al., 1994).
Statistical tools used to assess reproductive outcome in PGD
The statistical methods used in the data analysis leading to this thesis, have shown both strengths and weaknesses.
The aim of the thesis was in the first place to be descriptive on the reproductive outcome in couples undergoing IVF or ICSI associated with PGD. The cumulative live birth delivery rate using Kaplan-Meier analysis expresses the calculated chance of having at least one child following IVF/ICSI + PGD/PGS, on the basis that those couples who started the treatment, completed 6 treatment cycles, and that those couples who stopped the treatment during the course of this period, were included in the cumulative analysis assuming a reproductive prognosis similar to those who in actual fact continued the treatment.
Most reports and registries use pregnancy and birth rates per started cycle, oocyte retrieval or embryo transfer as primary outcome parameter (or miscarriage rate per cycle) as primary adverse outcome parameter. This is in line with the definition of clinical pregnancy rate and especially live birth delivery rate as set out by the ICMART glossary (Zegers-Hochschild et al., 2006). With increasing evidence of the effectiveness of ART, reproductive outcome has been reported on a per-cycle basis rather than a per-patient basis (Daya, 2005). The outcome of a single cycle is of interest, but only as part of the whole treatment in the overall context of patient discomfort, complications and costs (Heijnen et al., 2004). In the current climate of legal restriction on number of embryos transferred under IVF reimbursement laws, as is the case in Belgium (Ombelet et al., 2005; De Neubourg et al., 2006), and a trend towards milder stimulation to avoid complications such as ovarian hyperstimulation, a term singleton delivery is the ideal outcome. Fortunately, and as a result of multiple publications on reproductive outcome analysis, outcome reporting has shifted from biochemical, clinical and ongoing pregnancy rates to live birth rate, delivery rate or by preference singleton term live birth rate per cycle (Fauser et al., 2002; Daya, 2003; Heijnen et al., 2004; Min et al., 2004) or even singleton live birth rate per oocyte as the benchmark prognostic parameter (Pinborg et al., 2004). Because ART treatments are relatively short in duration and several cycles are often needed to succeed, the cumulative delivery rate using life table analysis is frequently employed to estimate the effectiveness of treatment and guide clinical decision-making (Daya, 2005).
The life table method was originally devised for analysing light bulb failure times and was then applied clinically for analysing death rates, so that failure rates resulting from cancer treatment could be ascertained and survival times could be estimated (Berkson and Gage, 1950). This method, usually known as survival analysis, was a significant improvement over the approach of using gross death rates, because it incorporated the actual rates of death as observed at various time points following diagnosis or commencement of treatment. Moreover, this method does not require subjects to enter simultaneously into a study or database, and can make use of data of subjects who dropped out of the study or who were lost for follow-up. The most important aspect of the life table method is the incorporation in the survival analysis of the duration of the time taken to reach the outcome event.
Cumulative outcome analysis (aka life table analysis; survival analysis) is rarely performed in reproductive medicine, for several reasons. The most important reason is that cumulative delivery rate calculation is only possible if drop out cases are non-informative, i.e. if there is no identified reason why patients discontinued the treatment after (n) cycles. Informative censoring may introduce bias into the standard methods used for survival analysis. In reproductive medicine it is assumed that patients discontinue the treatment cycles on the basis that the outcome is limited on medical grounds, be it poor gamete quality, failed fertilisation, poor embryo development, or associated reasons. Although this will surely feature in the group of drop out patients in the PGD population, we assume that a large number of PGD patients discontinue treatment on non-identified and therefore non-informative grounds such as financial reasons, PGD treatment being expensive, ill health not associated with the reproductive status, poor access to the PGD services provided at our centre for patients coming from abroad, and other non-informative reasons.
A second reason why cumulative outcome analysis is rarely performed in reproductive medicine is the fact that the period over which reproductive outcome is assessed is not time, but a number of treatment cycles performed, classically six cycles. The variability in the number of ART cycles couples may undertake and the length of time they may have to wait between successive cycles of treatment contribute to the complexity of assessing effectiveness of ART (Daya, 2005).
A third reason is that patient groups per centre are usually small, in comparison to the large patient groups in oncology where survival analysis was applied.
As Witsenburg et al mentioned in their manuscript on cumulative live birth rates in IVF and ICSI, others have already reported cumulative (live) birth rates or pregnancy rates after multiple IVF/ICSI treatments (Alsalili et al., 1995; Dor et al., 1996; Engmann et al., 1999), whereby the authors usually describe both (expected) cumulative delivery rate and observed (crude, true) cumulative delivery rate, while they prefer the expected rate (Osmanogaoglu et al., 1999; Fukuda et al., 2001; Witsenburg et al., 2005).
Alternatives to reporting reproductive outcome in ART by survival analysis are 1. pregnancy rate per cycle, 2. time-limited analysis using proportions, 3. conservative cycle-based cumulative pregnancy rate, and 4. real-time based cumulative pregnancy rate, of which the latter is recommended as the best option (Daya, 2005).
It is not obvious, yet possible, to see this thesis as an effectiveness analysis of PGD. Whereas the efficacy of PGD has been proven in early years by application of PGD-AS on a large scale (Donoso et al., 2007), albeit with controversial outcome, the effectiveness of the technique in an unselected PGD/PGS population remains to be established. There are several reasons for this.
In the first place we are not dealing with a standard population of patients. The patients are even more inhomogeneous in baseline characteristics than a population undergoing routine IVF/ICSI, for example in view of the different modes of inheritance leading to a different embryo selection level, and the large proportion of patients not suffering with any fertility problems. Poor comparability of subjects on the other hand induces significant bias in outcome reporting in PGD, and the patient who will be informed about the reproductive prognosis on the basis of the analyses presented in this thesis, should be made aware of this.
Secondly, the outcome is not dichotomous in a sense that the result is not only the birth of a child or not, but the genetic health status of that child as well as the genetic status and affected rate of the embryos tested.
Thirdly, this technique cannot be studied in a randomised controlled way.
The right time scale criterion is difficult to determine in PGD. Whereas in conventional IVF/ICSI time to conception is the ideal standard, due to several factors this is difficult to apply in PGD. The time of intake is not usually the start of the treatment i.e. there is usually a significant time lag needed for establishing the details of the genetic condition and preparing the PGD markers and/or probes. This time period until the actual start of the PGD treatment varies according to the genetic condition tested for, and can vary from 2 to 24 months. The interval between different treatments is often shorter due to a higher embryo transfer cancellation rate and a higher degree of priority, especially with those disorders that require PGD associated with HLA matching. The optimum time scale criterion for PGD treatment analysis therefore seems treatment cycle.
Attempts have been made at designing more accurate statistical tools to assess cumulative reproductive outcome in reproductive medicine, including selective dropout exclusion (Stolwijk et al., 1996; Land et al., 1997) and multiple imputation (Soullier et al., 2008).
Despite the limitations of life table analysis for PGD in terms of time scale criterion and informative censoring to some degree, as well as a number of modifications to diagnostic and therapeutic modalities over the years that are studied in this paper, subjects included towards the latter part of the study group are not likely to differ systematically from those who underwent PGD earlier in the study. However secular trends (Daya, 2005) are to some degree inevitable, due to changes in ovarian stimulation regimens (eg. the introduction of antagonist regimens as from 1996), the application of single versus double cell biopsy (Goossens et al., 2008) and the changes in embryo transfer policy, but the changes have been relatively confined by the consistent genetic selection criteria and genetic diagnostic techniques, the limited number of ovarian stimulation protocols available and applied, as well as the consistent ICSI technique applied.
Nevertheless, and in spite of all pros and cons of life table analysis in reproductive medicine and in PGD more particularly, there are few alternatives to establish the cumulative reproductive prognosis other than calculating observed and expected delivery rates. The patient and partner should therefore be guided in their decision to embark on a treatment on an individual basis, taking into account all background characteristics including age, fertility status, parity, estimated or established ovarian response and the genetic condition they are treated for, and recognise that the expected cumulative delivery rate will overestimate, whereas the observed cumulative delivery rate will underestimate their prognosis. The latter will encourage clinics to be more realistic when counseling couples about prognosis and will discourage claims of treatment and clinic superiority (Daya, 2005). Comparison with other centres is difficult, mainly due to a different patient population, and reports such as the ESHRE Consortium reports should therefore be interpreted with caution (Goossens et al., 2008).
Observational studies are suitable to detect rare or late adverse effects of treatment, and are more likely to provide an indication of what is achieved in daily medical practice. Other advantages include the opportunity to study in an unselected population, avoiding selection and therefore publication bias.
Preimplantation Genetic Diagnosis is Unethical and Immoral Essay
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In this day in age, where looks are almost everything when getting and going where you want, having a child with perfect genes is something to brag about. Allowing a parent to choose the perfect genes is not so far off in the future, in fact, it is now possible to pick some of the genes of a baby to make a “perfect” child. A procedure called pre-implantation genetic diagnosis, or PGD, has been used for years by doctors who wanted to reduce the chance of women carrying babies infected with life-threatening diseases. PGD was first used to improve the likelihood of a successful pregnancy for couples suffering with recurring miscarriages and parents who had the chance of passing on genetic diseases to their offspring. Dr. Jeffrey Steinberg, a…show more content…
Even PGD, only used in the best ways possible, to lower the possibility of a child inheriting a disease, was, and is, still a controversial issue and has become an even bigger issue today. Jessica Berg, an associate professor of law and bioethics at Case Western Reserve University, said PGD also raises concerns about how society will begin to perceive people with disabilities, along with the parents who chose to have them. Berg (2003) says: While we hope our children are healthy, the ability to pick ahead of time might lead to some unintended consequences. Society may be inclined to view parents who don't use this technology as irresponsible. Insurance companies may deny coverage to a child born with cystic fibrosis, saying ‘Look, you knew you could have an unhealthy child.’
Although no serious health effects have been linked to PGD, there has not been any rigorous long-term testing on this procedure. Many people agree that it seems highly likely that PGD may have a few long-term health effects because a cell is being removed from an embryo. A few studies using mice as the PGD recipients have shown a higher risk of weight gain and memory loss in adulthood. One main reason why this procedure should be banned is because of the cost of this procedure. No one less than the upper-middle class is able to afford this price. The PGD test itself costs about $3,000.