The association of obesity with euploidy rates in women undergoing in vitro fertilization with preimplantation genetic testing

Purpose The purpose of this study was to determine the impact of body mass index (BMI) on euploidy rates for in vitro fertilization (IVF) cycles with preimplantation genetic testing (PGT) utilizing primarily next-generation sequencing (NGS).

This retrospective cohort study included women aged ≤ 45 years who underwent IVF/PGT between September 2013 and September 2020 at a single university-affiliated fertility center. The primary outcome was euploidy rate. Secondary outcomes included peak serum estradiol (E2), number of oocytes retrieved, oocyte maturation rate, high-quality blastulation rate, clinical loss rate (CLR), clinical pregnancy rate (CPR), and ongoing pregnancy/live birth rate (OPR/LBR).

The study included 1335 IVF cycles that were stratified according to BMI (normal, n = 648; overweight, n = 377; obese, n = 310). The obese group was significantly older with significantly lower baseline FSH, peak E2, high-quality blastulation rate, and number of embryos biopsied than the normal group. Overall euploidy rates were not significantly different between BMI groups (normal 36.4% ± 1.3; overweight 37.3% ± 1.8; obese 32.3% ± 1.8; p = 0.11), which persisted after controlling for covariates (p = 0.82) and after stratification of euploidy rate by age group and by number of oocytes retrieved per age group. There were no significant differences in CLR, CPR, and OPR/LBR across BMI groups.

Despite a lower high quality blastulation rate with obesity, there is not a significant difference in euploidy rates across BMI groups in women undergoing IVF/PGT.

In vitro fertilization, Preimplantation genetic testing, Euploidy rate, Body mass index

Obesity is one of the most rapidly growing major health challenges facing the world today. In the USA, up to two thirds of women and three fourths of men are overweight or obese [1]. The etiology of obesity is known to be multifactorial, involving genetic, physiologic, environmental, socioeconomic, and behavioral factors [2, 3]. Though obesity is most notably linked to poor health outcomes such as cardiovascular, respiratory, metabolic, and renal complications, there is also a clear association between obesity and worsened reproductive outcomes [2, 3]. For those patients who conceive naturally, obesity has been associated with increased adverse obstetric and neonatal complications including increased risk of miscarriage, stillbirth, congenital anomalies, venous thromboembolism, preeclampsia, gestational diabetes, macrosomia, shoulder dystocia, prematurity, cesarean section, neonatal death, and childhood obesity [4–7]. As such, obese patients undergo extra monitoring during their pregnancy and are often considered high risk. However, it is not always possible for obese patients to conceive naturally. In fact, obesity has been associated with decreased rates of spontaneous conception and fecundity [8, 9]. Though IVF outcomes are often positive in the overweight and obese populations, these outcomes have been shown to be less favorable than in the normal weight population. Female obesity has been associated with adverse clinical outcomes among in vitro fertilization (IVF) cycles including decreased rates of implantation, clinical pregnancy, and live birth with increased rates of miscarriage [10–23]. Obese patients have also been found to have an increased gonadotropin requirement during stimulation, more frequent cycle cancellations, lower estradiol levels, and fewer oocytes retrieved compared to controls [12, 13, 21, 24, 25]. It has been theorized that reduced oocyte quality in obese patients may result in higher rates of aneuploidy which may in turn explain worsened outcomes; however, some studies have found contradictory results prompting a need for further investigation [18, 26, 27]. For example, one study using a high-fat-diet mouse model of obesity concluded that an obese maternal environment can lead to meiotic aneuploidy at the level of the oocyte that in turn contributes to early embryonic loss [26]. In contrast, a study assessing 279 patients at a university-based fertility center found no difference in the number or percentage of euploid embryos according to body mass index (BMI) in patients undergoing IVF with trophectoderm biopsy and array comparative genomic hybridization (aCGH) analysis [27]. Likewise, a recent study showed no association between maternal BMI and aneuploidy of maternal origin after preimplantation genetic testing for aneuploidy (PGT-A) and blastocyst biopsy [28]. In order to more broadly investigate the association between BMI and oocyte quality, we investigated the association of BMI with euploidy rates in IVF with preimplantation genetic testing (PGT) cycles using primarily next-generation sequencing (NGS), the preferred technology for assessing aneuploidy [29], across a 7-year time frame at a single large, university-affiliated fertility center.

Study design and participants This was a retrospective cohort study evaluating the association between BMI and euploidy rates at a large, university-affiliated fertility center from September 2013 through September 2020. Only women ≤ 45 years using autologous oocytes who underwent IVF with PGT with biopsy at the blastocyst stage at the Center for Advanced Reproductive Services in Farmington, CT were included. BMI was calculated using the height and weight measurements from fresh IVF cycle start. For patients with multiple IVF cycles, all cycles meeting the study criteria were included. Exclusion criteria included BMI less than 18.5 kg/m2 due to relatively low sample size in this category, cancelled cycles, donor oocyte cycles, fresh cycles performed at an outside facility, and IVF cycles in which PGT was not utilized. Mosaic embryo transfer was not included in this study. Approval for the study was obtained from the University of Connecticut Health Center institutional review board. Treatment protocol The IVF stimulation protocols used in this study have been previously described [30, 31]. Choice of stimulation protocol was individualized based upon patient factors and physician preference. Trigger medication for final oocyte maturation was administered when ≥ 3 follicles reached approximately 18-mm diameter. Trigger medications included gonadotropin-releasing hormone agonist (GnRHa) (leuprolide acetate, Abbott Laboratories), human chorionic gonadotropin (hCG) (Pregynl, Merck; Novarel, Ferring Pharmaceuticals), or a combination of GnRHa and hCG. Trigger medications were individualized based upon patient factors, physician discretion, protocol type, and risk for ovarian hyperstimulation syndrome. Transvaginal ultrasound-guided oocyte retrieval was performed 35 h after trigger. Oocytes were fertilized with either intracytoplasmic sperm injection or conventional insemination. Trophectoderm biopsy was performed on good quality blastocysts (3BB or higher) according to the Gardner criteria [32] and cryopreserved using vitrification. PGT-A was performed for all cycles using primarily NGS, with limited use of aCGH. The results were reported as euploid, aneuploid, or mosaic. Preimplantation genetic testing for monogenic/single-gene disorders (PGT-M) was included when appropriate if the results of ploidy status were known. Patients with euploid embryos underwent frozen embryo transfer (FET) cycles utilizing natural, letrozole ovulation induction, or programmed cycle protocols based upon the patient’s ovulatory status and physician discretion as previously described [30, 31]. In brief, natural and letrozole ovulation FET cycles consisted of transvaginal ultrasound on cycle day 10 to ensure the presence of a dominant follicle and an endometrial stripe ≥ 7 mm. Daily serum LH monitoring was then performed until the detection of the luteinizing hormone (LH) surge (defined as LH > 20 IU/L) followed by embryo transfer 6 days later. The letrozole ovulation induction FET protocol consisted of 5 mg of letrozole (Femara, Novartis Pharmaceuticals Corporation) from cycle days 3–7 prior to ultrasound on cycle day 10 as described above. Luteal phase supplementation with vaginal progesterone (Crinone, Merck; Endometrin, Ferring Pharmaceuticals) was started 2 days after the LH surge. The programmed FET cycles included GnRHa downregulation in the luteal phase of a preceding cycle, followed by increasing doses of oral or transdermal estradiol following menses and initiation of daily intramuscular progesterone approximately 12 days later or when endometrial thickness reached ≥ 7 mm on ultrasound. Embryo transfer was performed after 6 days of intramuscular progesterone. Outcomes Patient demographic, baseline, IVF cycle, and pregnancy characteristics were obtained from the electronic medical record. The cycles were divided into three groups according to BMI consistent with the World Health Organization BMI categories: normal 18.5–24.9 kg/m2, overweight 25–29.9 9 kg/m2, and obese ≥ 30 kg/m2 [33]. The primary outcome of the study was euploidy rate. Euploidy rate was calculated by dividing the number of embryos with euploid PGT results by the total number of embryos that were biopsied in a given cycle. Euploidy rate was stratified by age group according to the Society for Assisted Reproductive Technology (SART) age categories and by the number oocytes retrieved per age group for each BMI group. Secondary outcomes included IVF cycle and pregnancy outcomes. IVF cycle outcomes included peak serum estradiol (E2) (defined as the highest E2 value on or before the day of trigger for a given IVF stimulation cycle), number of oocytes retrieved, number of metaphase II (MII) oocytes retrieved (defined as the number of oocytes retrieved in metaphase II stage on the day of retrieval), oocyte maturation rate (defined as the number of metaphase II oocytes retrieved divided by the total number of oocytes retrieved), and high-quality blastulation rate (defined as the total number of good quality blastocysts per fertilized oocyte). The percentage of patients undergoing a primary transfer was also analyzed. In the current study, primary transfer refers to the first embryo transfer immediately following a fresh IVF cycle that resulted in a euploid embryo for transfer. Pregnancy outcomes included clinical pregnancy loss rate (defined as total number of pregnancy losses prior to 20-weeks gestation after a confirmed clinical pregnancy on ultrasound divided by total number of clinical pregnancies detected), clinical pregnancy rate (defined as total number of gestational sacs with or without a fetal pole within the uterus on transvaginal ultrasound divided by total number of embryo transfers performed), ongoing pregnancy/live birth rate (defined as the total number of ongoing pregnancies and births of a neonate after confirmation of pregnancy on ultrasound divided by total number of embryo transfers performed), and delivery mode (vaginal versus cesarean section). Statistical analysis Statistical analysis was performed with the use of SPSS Version 28. Chi-square test was used for the analysis of categorical variables. One-way ANOVA with post hoc Tukey test was used for the analysis of continuous variables. To control for multiple cycles per patient a repeated measure linear regression was performed using generalized estimating equations (GEE) to evaluate the effect of BMI on euploidy rates after controlling for potential covariates including age, baseline anti-Müllerian hormone (AMH), baseline follicle-stimulating hormone (FSH), peak E2, number of oocytes retrieved, and number of blastocysts biopsied. A two-sided p value of < 0.05 was considered statistically significant.

A total of 1335 IVF cycles involving 905 patients were included in the study. The cycles were divided into BMI groups: normal (n = 648), overweight (n = 377), and obese (n = 310). Baseline characteristics for all cycles are shown in Table 1. The obese group was significantly older than the normal group (p < 0.01). The mean BMI in the normal, overweight, and obese groups were 22.1 kg/m2, 27.2 kg/m2, and 34.7 kg/m2, respectively (p < 0.01). The obese group was more likely to have a primary infertility diagnosis of anovulation or polycystic ovary syndrome (PCOS). Baseline FSH was significantly lower in the obese group compared to the normal and overweight groups (p < 0.01). The use of PGT-M was not significantly different between the groups (p = 0.68). Table 1. | BMI groups | ||| |---|---|---|---| | Normal | Overweight | Obese | | | Age (years)* | 36.8 ± 0.2a | 37.4 ± 0.2 | 37.9 ± 0.2b | | BMI (kg/m2)* | 22.1 ± 0.1a | 27.2 ± 0.1b | 34.7 ± 0.2c | | Primary infertility diagnosis* | ||| | Anovulation/PCOS | 35/415 (8.4) | 22/247 (8.9) | 37/180 (20.6) | | Tubal factor | 20/415 (4.8) | 13/247 (5.3) | 10/180 (5.6) | | Endometriosis | 27/415 (6.5) | 16/247 (6.5) | 11/180 (6.1) | | Fibroids | 9/415 (2.2) | 9/247 (3.6) | 0/180 (0.0) | | Recurrent pregnancy loss | 64/415 (15.4) | 34/247 (13.8) | 21/180 (11.7) | | Diminished ovarian reserve | 15/415 (3.6) | 9/247 (3.6) | 4/180 (2.2) | | Male factor | 67/415 (16.1) | 44/247 (17.8) | 37/180 (20.6) | | Unexplained | 106/415 (25.5) | 57/247 (23.1) | 27/180 (15.0) | | Other | 72/415 (17.3) | 43/247 (17.4) | 33/180 (18.3) | | Baseline FSH (mIU/mL)* | 7.9 ± 0.1a | 7.3 ± 0.2b | 6.6 ± 0.2c | | AMH (ng/mL) | 2.9 ± 0.1 | 2.8 ± 0.2 | 3.0 ± 0.2 | | PGT-M | 88/639 (13.8) | 60/364 (16.5) | 42/293 (14.3) | Note: Continuous variables presented as mean ± SEM. Categorical variables presented as n (%) *A variable with statistical significance between groups a,b,cStatistical significance across groups. Groups with different letters are significantly different from one another IVF cycle outcomes and FET cycle parameters are shown in Table 2. There were no significant differences in the number of oocytes retrieved, oocyte maturation rate, number of embryos transferred, and fertilization rate between the BMI groups. Peak E2 was significantly lower in the obese group compared to the normal group (p = 0.04). The obese group had a significantly lower blastocyst development rate (p = 0.04) and lower number of embryos biopsied (p = 0.04) than the normal group. Table 2. | BMI groups | ||| |---|---|---|---| | Normal | Overweight | Obese | | | Stimulation type | ||| | Antagonist | 526/655 (80.3) | 300/379 (79.2) | 233/310 (75.2) | | Peak E2 (pg/mL)* | 2395 ± 49a | 2260 ± 56 | 2201 ± 65b | | Trigger type | ||| | GnRH agonist | 307/683 (44.9) | 184/395 (46.6) | 141/324 (43.5) | | hCG | 329/683 (48.2) | 176/395 (44.6) | 156/324 (48.1) | | GnRH agonist + hCG | 47/683 (6.9) | 35/395 (8.9) | 27/324 (8.3) | | NGS | 630/682 (92.4) | 361/396 (91.2) | 306/324 (94.4) | | Oocytes retrieved (n) | 14.4 ± 0.4 | 14.5 ± 0.5 | 14.1 ± 0.5 | | MII oocytes retrieved (n) | 11.0 ± 6.8 | 11.3 ± 7.3 | 11.2 ± 6.3 | | Oocyte maturation rate (%) | 74.0 ± 0.8 | 71.8 ± 1.0 | 73.6 ± 1.1 | | Fertilization rate (%) | 58.1 ± 0.8 | 55.5 ± 1.0 | 58.5 ± 1.0 | | Blastocyst development rate (%)* | 58.2 ± 1.0a | 56.3 ± 1.4 | 53.1 ± 2.0b | | Embryos biopsied (n)* | 4.5 ± 0.1a | 4.1 ± 0.2 | 3.9 ± 0.2b | Note: Continuous variables presented as mean ± SEM. Categorical variables presented n (%) *A variable with statistical significance between groups a,bStatistical significance across groups. Groups with different letters are significantly different from one another The percentage of patients undergoing a primary transfer did not significantly differ between BMI groups at 71.1%, 73.7%, and 73.9% for the normal, overweight, and obese groups, respectively (p = 0.67). The majority of the normal BMI group underwent a natural cycle (52.5% versus 6.7% undergoing a letrozole cycle and 40.7% undergoing a programmed cycle), whereas the majority of the obese BMI group underwent a programmed cycle (52.2% versus 36.7% undergoing a natural cycle and 11.1% undergoing a letrozole cycle) (p = 0.03). The primary outcome of the study is outlined in Table 3. There were no significant differences in the overall euploidy rates between the different BMI groups (p = 0.11). Euploidy rate did not significantly differ per age group across BMI groups with the exception of the 35–37-year-old age group in which a significant difference was observed (p = 0.02). Overall euploidy rate per oocyte retrieved did not differ between the BMI groups (p = 0.14). Moreover, euploidy rate did not significantly differ per oocyte retrieved per age group across BMI groups. Multiple linear regression using GEE did not show a significant association between BMI and euploidy rate (β: 0.001, 95% CI (− 0.02, 0.004), F (7304), p = 0.58). There were no significant differences in aneuploidy rate (p = 0.08) or mosaic rate (p = 0.98) across BMI groups. Table 3. | BMI groups | ||| |---|---|---|---| | Normal | Overweight | Obese | | | Age group | ||| | Total | 36.4 ± 1.3 (646) | 37.3 ± 1.8 (374) | 32.3 ± 1.8 (309) | | < 35 | 48.4 ± 2.1 (208) | 51.0 ± 3.0 (93) | 44.3 ± 3.6 (66) | | 35–37* | 43.9 ± 2.6 (139)a | 56.3 ± 3.6 (73)b | 50.2 ± 3.8 (62) | | 38–40 | 31.7 ± 2.5 (170) | 29.1 ± 3.0 (111) | 29.1 ± 3.0 (91) | | 41–42 | 23.3 ± 4.4 (55) | 20.3 ± 4.2 (66) | 17.1 ± 4.0 (52) | | > 42 | 8.9 ± 2.3 (74) | 17.0 ± 5.4 (31) | 9.9 ± 2.9 (38) | | Per oocyte retrieved | ||| | Total | 11.5 ± 4.8 (648) | 11.0 ± 6.5 (376) | 9.9 ± 5.9 (310) | | < 35 | 15.8 ± 0.86 (208) | 17.0 ± 1.4 (93) | 15.0 ± 1.4 (66) | | 35–37 | 14.8 ± 1.2 (139) | 17.7 ± 1.8 (73) | 14.2 ± 1.2 (62) | | 38–40 | 9.1 ± 0.8 (171) | 7.7 ± 0.7 (112) | 8.9 ± 1.0 (92) | | 41–42 | 7.7 ± 2.0 (56) | 4.2 ± 1.0 (67) | 5.2 ± 1.2 (52) | | > 42 | 2.1 ± 0.5 (74) | 3.5 ± 1.2 (31) | 3.0 ± 1.1 (38) | Note: Rates presented as mean ± SEM (n) *A variable with statistical significance between groups a,bStatistical significance across groups. Groups with different letters are significantly different from one another Pregnancy outcomes are shown in Fig. 1. Pregnancy data was available for 842 IVF cycles: normal (n = 415), overweight (n = 247), and obese (n = 180). There were no significant differences in clinical loss rate (p = 0.72), clinical pregnancy rate (p = 0.30), ongoing pregnancy/live birth rate (p = 0.46), or mode of delivery (p = 0.91) between BMI groups. The percentage of patients undergoing vaginal delivery was 51.3%, 47.8%, and 47.2%, respectively, for the normal, overweight, and obese groups, with the remainder in each group undergoing cesarean delivery.

Our findings demonstrate that increasing BMI does not result in significant differences in euploidy rates in patients undergoing IVF with PGT. Our findings held true even after stratifying euploidy rate by age group and by number of oocytes retrieved per age group across BMI groups. This retrospective cohort study spanning from September 2013 through September 2020 using primarily NGS for PGT analysis builds on the existing literature by demonstrating that the adverse IVF and pregnancy outcomes observed in the obese population may not be related to increased aneuploidy at the level of the oocyte and instead are likely to be related to other factors [18, 27, 29]. Other groups have similarly shown equivalent rates of euploidy across BMI groups. However, the prior studies are limited by shorter time frames and widespread use of inferior molecular techniques for PGT analysis, notably aCGH [18, 27, 34]. Goldman et al. (2015) found no difference in the number or percentage of euploid embryos in 279 women analyzed according to BMI [27]. Kim et al. (2021) also found that euploidy rates were equivalent across BMI and percent body fat groups in a cohort of 1889 infertile couples from June 2016 through January 2019 [34]. Similarly, Cozzolino et al. (2020) found that the number of euploid embryos across BMI groups in 3480 cycles was similar in a database of the seven largest IVF clinics in Spain from January 2016 through April 2019 [18]. Unlike these previous studies, our study showed no significant association between BMI and euploidy rate in IVF/PGT cycles using primarily NGS analysis, which is more reflective of current practice. The potential impact that obesity may have on the developmental competence of the oocyte has also been investigated [25, 35–37]. It has been shown that elevations in insulin, glucose, free fatty acids, and changes in adipokines related to obesity may impair oocyte development [35, 36]. Wittemer et al. (2000) found that the number of collected oocytes was inversely related to BMI; however, this was only in long protocol cycles and did not apply to short protocol cycles [25]. In contrast, Moraganni et al. (2012) found that in patients undergoing a primary fresh autologous ART cycle there was no significant difference in number of oocytes retrieved or number of embryos transferred according to BMI [37]. Similarly, we did not find a significant difference between number of oocytes retrieved, oocyte maturation rate, or number of embryos transferred across the BMI groups in our study. However, we showed that the obese group had significantly lower blastocyst development rates and a significantly lower number of embryos biopsied, consistent with Metwally et al. (2007) who found that obesity had a significant adverse effect on mean embryo grade, embryo utilization rate, and number of embryos cryopreserved in patients < 35 years of age [38]. Additionally, Vitek et al. (2020) analyzed SART registry data and found that obesity was associated with lower oocyte yields despite normal, similar levels of AMH when compared to normal weight controls [39]. Vitek et al. also found that obese patients had a lower day 2–3 FSH which was more notable with increasing obesity suggesting a potential direct inhibitory effect of adipose tissue on gonadotropin production that may in turn suppress the ability to detect day 3 FSH elevation [39]. Consistent with these findings, we found that baseline FSH was significantly lower in the obese group compared to the normal and overweight groups. We also found that AMH levels were similar between groups. However, we did not find a corresponding decrease in the number of oocytes retrieved in the obese group compared to the normal BMI group. Although baseline FSH levels were lower in the BMI group, they were only lower by approximately 1 mIU/mL. Thus, in this particular cohort of obese patients, FSH may not have been sufficiently suppressed by peripheral estrogen production for it to make a meaningful impact on oocyte yield. Alternatively, it is possible that our results were limited by sample size compared to the SART registry study. Peak E2 was significantly lower in the obese group compared to the normal group in our study. This has been found in a prior retrospective cohort study showing that compared to women with a normal BMI, women with elevated BMI have lower estradiol levels when undergoing a first IVF cycle [24]. The low peak E2 observed in the obese population may be related to a lower sex hormone binding globulin observed with increasing BMI [40, 41]. Finally, obesity’s impact on delivery mode outcomes has been previously investigated [5, 6]. Though not statistically significant, the overweight and obese BMI groups underwent a higher percentage of cesarean sections compared to the normal group in our study. The increased risk of cesarean birth for obese patients has been demonstrated in prior studies analyzing obese patients who conceived naturally [5, 6]. We found no significant differences in CPR, CLR, or OPR/LBR across BMI groups. This is contrary to other previous studies which showed lower live birth and higher miscarriage rates in obese women [11, 14, 18]. Pregnancy outcomes were not our primary end points and the lack of statistical significance for these outcomes across the BMI groups in our study may be due to the lower sample size in our study compared to these prior studies. There are many strengths of this study. Data collection extended over a 7-year time frame, making this one of the most expansive investigations on the subject [18, 27, 34]. Additionally, over 91% of PGT analysis was performed through NGS, the preferred technology for assessing aneuploidy [29]. This study also went further than previous work by stratifying euploidy rate per age group and per oocytes retrieved per age group. There are some limitations of this study. This is a retrospective study and thus is subject to selection bias. To account for this, multiple linear regression analysis was performed to help to control for potential confounders. However, there are some factors that were not captured in the data set that could have the potential to impact IVF and pregnancy outcomes. For example, BMI was calculated based on height and weight at the start of a fresh IVF cycle. At our center, BMI is not routinely measured with FET cycle start. Thus, although many patients underwent FET cycle soon after their retrieval cycle and BMI was unlikely to significantly change, it is possible that some patients had a delayed FET cycle start during which time their BMI may have changed. In these cases, we cannot clearly delineate the association between BMI and ploidy as related to uterine or oocyte factors. Additionally, FET protocol type was not controlled for in the study. The obese BMI group was more likely to undergo a programmed cycle compared to the normal BMI group, which may be related to the increased proportion of obese patients with a primary infertility diagnosis of PCOS. There were only 16 underweight patients that underwent IVF with PGT during the study time frame; therefore, underweight patients were not included in the study. Likewise, there were only 33 class 3 obesity patients that underwent IVF with PGT during the study time frame. Given the small number, these patients were analyzed as a part of the obese group rather than analyzed separately. One factor that may have limited the number of class 3 obesity patients specifically is the concern for increased anesthesia complications during IVF procedures with increasing BMI [42]. Due to these concerns, our center, as well as the majority of centers around the country, have strict BMI cutoffs for IVF eligibility with maximum BMI ranging between 35 and 45 kg/m2 [42, 43]. At our center, the current BMI cutoff is at 43 kg/m2, and we require an anesthesia consult for any patient with a BMI over 35 kg/m2. Nevertheless, this study cannot determine whether euploidy rates are different in subjects that have very low or very high BMI. In terms of potential lab variables, our embryologists only biopsy embryos that are 3BB or higher morphologically. Therefore, it is possible that there were embryos that did not meet criteria for biopsy that were discarded and were not accounted for in the current study. Thus, we cannot assess whether subjects in the obese group had other blastocysts compared to the normal BMI group that did not meet criteria for biopsy. Finally, this is a single-center study which may limit the generalizability of the study. However, our center is a large, university-affiliated center with a large diversity of patients and pathology with standardized protocols.

In conclusion, our data indicate that there is no association between BMI and euploidy rate in patients undergoing IVF with PGT. Further studies are needed to determine what other potential factors may explain the worsened IVF and pregnancy outcomes previously reported in this population. Declarations Conflict of interest The authors declare no competing interests. Footnotes Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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