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Metabolic profiles of children aged 2–5 years born after frozen and fresh embryo transfer: A Chinese cohort study

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Metabolic profiles of children aged 2–5 years born after frozen and fresh embryo transfer: A Chinese cohort study

Abstract

Author summary

Citation: Zhou W, Feng W, Chang J, Hu J, Li F, Hu K, et al. (2024) Metabolic profiles of children aged 2–5 years born after frozen and fresh embryo transfer: A Chinese cohort study. PLoS Med 21(6):
e1004388.

https://doi.org/10.1371/journal.pmed.1004388

Received: November 23, 2023; Accepted: March 27, 2024; Published: June 6, 2024

Copyright: © 2024 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data set cannot be shared directly under current legislation for data protection and must be requested directly from the Birth Cohort Data Management Committee at the State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University (ARTKID_sdu@163.com), after approval by the ethics committees at the Reproductive Medical Center of Shandong University (lifuxia@sduivf.com).

Funding: This study was supported by the National Key Research and Development Program of China (2021YFC2700700 to LC), CAMS Innovation Fund for Medical Sciences (2021-I2M-5-001 to Z-JC), Basic Science Center Program of NSFC (31988101 to Z-JC, 82171692 to LC), Shandong Provincial Natural Science Foundation (ZR2022JQ33 to LC), General Program of Shandong Provincial Natural Science Foundation of China (ZR2022MH087 to WZ), National Special Support Program for High-level Talents (no Grant numbers to LC), and Taishan Scholars Program for Young Experts of Shandong Province (tsqn201909195 to LC).The study funders had no role in the study design, data collection or analysis, decision to publish, or preparation of the study.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations:
APOE,
Apolipoprotein E; ART,
assisted reproductive technology; ARTKID,
Assisted Reproductive Technology borned KIDs; BMI,
body mass index; DOHaD,
Developmental Origins of Health and Disease; FBG,
fasting blood glucose; FDR,
false discovery rate; FET,
frozen embryo transfer; GDM,
gestational diabetes mellitus; GIUT,
gamete intrauterine transfer; HDL-C,
high-density lipoprotein-cholesterol; ICSI,
intracytoplasmic sperm injection; IVF,
in vitro fertilization; IVM,
in vitro maturation; LDL-C,
low-density lipoprotein-cholesterol; LGA,
large for gestational age; MD,
mean difference; OHSS,
ovarian hyperstimulation syndrome; PGT,
preimplantation genetic testing; PIH,
pregnancy-induced hypertension; SDS,
standard deviation score; TC,
total cholesterol; TG,
triglyceride

Introduction

As the most widely used treatment for infertility, over 10 million children worldwide were conceived through assisted reproductive technology (ART) by 2022 [1]. Previous studies on offspring born via ART during early childhood have indicated an increased risk of impaired metabolism, including higher fasting blood glucose (FBG), insulin, triglycerides (TG), and lower low-density lipoprotein-cholesterol (LDL-C) levels [2–4]. According to the Developmental Origins of Health and Disease (DOHaD) theory, exposures during early life can lead to metabolic alterations that manifest later in life [5]. Therefore, it is essential to identify the key factors related to ART techniques that transmit metabolic risks to the next generation.

Frozen embryo transfer (FET) has become a well-established and widely used ART technique [6,7]. The use of FET is increasing substantially due to the reduced risk of ovarian hyperstimulation syndrome (OHSS), multiple gestations, and higher singleton livebirth rate [8–10]. However, compared to Fresh-ET, FET has shown an increased risk of pregnancy-induced hypertension (PIH), macrosomia, large for gestational age (LGA), and elevated birth weight [6,11–13]. All of these conditions are well-recognized risk factors for metabolic dysfunction and cardiovascular disease later in life [14–17]. FET was associated with a 1.5-fold increased risk of obesity than Fresh-ET offspring at age 5 to 8 years [18]. And, decreased body mass index (BMI) in offspring was observed in 2 to 3 aged offspring conceived by Fresh-ET but not FET compared with those who were naturally conceived [19]. Nevertheless, limited studies have reported on the metabolic profiles of children conceived through FET, especially in comparison to fresh controls. A cross-sectional study found more favourable lipid profiles were evident in fresh but not frozen prepubertal offspring compared with the naturally conceived counterparts [20], while another cohort study observed no differences among offspring born after fresh, frozen ET, and naturally conceived [9]. More importantly, given the limited sample size of these observed studies, the long-term metabolic safety of offspring born after FET is largely unknown.

Therefore, we conducted a prospective cohort study to compare the glucose and lipid profiles of children born following FET and Fresh-ET during early childhood.

Material and methods

Study design and participants

We conducted a prospective birth cohort of offspring born via ART, named “Assisted Reproductive Technology borned KIDs (ARTKID)” cohort, at the Institute of Women, Children and Reproductive Health, Shandong University, China. All the participants had assigned the informed consents for the follow-up before ART treatment started and the pregnancy and neonatal outcomes were recorded according to the request of our government (S1 and S2 Files). In 2013, we completed a further cohort design for adolescents and got the additional approval of the ethics committees at the Reproductive Medical Center of Shandong University (S3 File). All the data of kids were collected prospectively thereafter and analyzed until 2021. The “ARTKID” cohort focus on growth and metabolic health of children. The follow-up was conducted in 3 stages: infancy, toddlerhood, and puberty, with each stage comprising 2 to 3 follow-up visits based on age. Offspring who did not undergo growth assessment measurements are considered lost to follow-up. We contacted mothers via telephone and invited them, along with their offspring, to participate in our face-to-face visits. During follow-up, measurements of height and weight were taken to assess growth and development, relevant questionnaires were completed, and blood samples were provided. These assessments were performed by either well-trained pediatricians or nurses. And regular quality control measures were implemented to ensure the accuracy of the information collected.

Offspring included in this study were born between November 2008 and May 2019 and were followed up until August 2021. The offspring included in this study were singletons conceived through either in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), and their ages ranged from 2 to 5 years on the follow-up day. Offspring conceived by oocyte donation, preimplantation genetic testing (PGT), gamete intrauterine transfer (GIUT), or in vitro maturation (IVM) were excluded from the study. In total, 14,322 singletons of the whole “ARTKID” cohort met the criterion. A total of 8,765 individuals completed growth assessments, and follow-up rate are 61.2% (8,765/14,322) until August 2021. Moreover, 2,181 children conceived by FET and 2,065 conceived by Fresh-ET provided blood samples for the assessment of glucose and lipid biochemical parameters and were included in the present analysis. All offspring born from FET used vitrification of embryos. In our longitudinal study, we implemented a 3 times follow-up design targeting specific age ranges: 2.0 to 2.4 years, 2.5 to 3.9 years, and 4.0 to 5.9 years. We required offspring to be followed up for at least once. Most offspring participated only once, and a few returned for follow-up assessments twice (183 children born from FET and 179 born from Fresh-ET) or 3 times (4 children born from FET). The mean length of follow-up across the cohort was 3.6 years, with a standard deviation of 0.8 years, and ranging from 2.0 to 5.9 years. And there were 97 sibling pairs (38 sibling pairs conceived by FET and 59 conceived by Fresh-ET) born to the same mothers included in our study. This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Table). The flow chart of the study is showed in Fig 1.

Fig 1. Flow chart of the study.

Note: The follow-up stage during toddlerhood comprised 3 visits, encompassing ages 2.0–2.4, 2.5–3.9, and 4.0–5.9 years. In total, there were 9,962 visits from 8,765 offspring during the toddlerhood follow-up stage. All images/clip-art within the figure panels were hand-drawn by the authors. “ARTKID”, “Assisted Reproductive Technology borned KIDs”; ET, embryo transfer; GIUT, gamete intrauterine transfer; ICSI, intracytoplasmic sperm injection; IVF, in vitro fertilization; IVM, in vitro maturation; PGT, preimplantation genetic testing.


https://doi.org/10.1371/journal.pmed.1004388.g001

Baseline characteristics included parental ages, BMI, diabetes status, education (college or higher, high school diploma or less), paternal smoking, parity (0 or more), stage of embryo transfer (cleavage or blastocyst), fertilization mode (IVF or ICSI), gestational diabetes mellitus (GDM), PIH, cesarean section, offspring sex (male or female), gestational age, birth weight, and age at visit. Parental characteristics were collected by standardized measurements and questionnaires administered during face-to-face interviews. ART treatment information was extracted by reviewing medical records. Parental ages at the time the child was born were calculated based on the date of parental birth and the offspring’s birth date. Information about offspring births was obtained from the offspring’s birth certificates. The birthweight values in standard deviation scores (SDS) were calculated based on the Chinese reference for sex- and gestational age-specific birthweight [21].

Outcomes

The primary outcomes are FBG and LDL-C. FBG is crucial in diagnosing and managing diabetes [22]. LDL-C is the instigator of atherosclerotic plaques and main therapeutic target to prevent future cardiovascular events [23,24]. The secondary outcomes include insulin, The Homeostatic Model Assessment of Insulin Resistance Index using the HOMA2 Calculator (HOMA-IR2), TG, total cholesterol (TC), LDL-C, and high-density lipoprotein-cholesterol (HDL-C). Fasting blood samples were obtained in the morning and preserved at −80°C until subjected to analysis. FBG levels were assessed by the hexokinase method employing the Cobas c702 instrument (Roche Diagnostics, Germany). Fasting insulin levels were quantified in serum utilizing an electrochemiluminescence immunoassay conducted on the Cobas e601 instrument (Roche Diagnostics, Germany). Serum levels of TG, TC, LDL-C, and HDL-C were determined through a homogeneous assay employing the Cobas c702 instrument (Roche Diagnostics, Germany). The HOMA-IR2 score was computed using the HOMA calculator v2.2.3 (https://www2.dtu.ox.ac.uk/homacalculator/).

Statistical analyses

Based on previous cohort and cross-sectional controlled data, the target mean differences were 0.09 mmol/L for FBG and 0.2 mmol/L for LDL-C, with standard deviations of 0.3 and 0.4, respectively [9,20]. The power was calculated using our sample size (n = 2,181 for FET and n = 2,065 for Fresh-ET) at a 2-sided alpha level of 0.05. The power was found to be nearly 100% for both FBG and LDL-C. Baseline characteristics between study offspring were compared using the linear regression for continuous variables and the logistic regression for categorical variables. The comparison of metabolic measurements between offspring conceived by fresh and frozen embryo transfer was used a linear mixed-effects regression model. The mixed-effects model allowed us to account for the potential confounding effects of 2 variations, including repeated measurements taken from the same child at different time points and siblings born to the same mothers. Potential confounders were defined based on priori literatures, including maternal age [25,26], paternal age [27], maternal BMI [28], paternal BMI [29], paternal smoking [30], parity [31], parental education [32], offspring age and sex [33,34]. Only less than 0.1% data were missing in the baseline variables and outcomes. Thus, the missing data were directly deleted in the final analysis.

Subgroup analyses were carried out according to offspring sex (male or female), the stages of embryo transfer (cleavage or blastocyst) and the mode of fertilization (IVF or ICSI). We conducted correlation analyses using Pearson’s correlation coefficient and found significant associations between FBG and insulin, as well as HOMA-IR2. Additionally, TC exhibited strong correlations with HDL and LDL levels (S2 Table). However, correlations with other indicators were not as pronounced. Therefore, Benjamin–Hochberg’s procedure was used to control false discovery rate (FDR) at a 5% level for multiple comparisons of FBG, TG, HDL, and LDL. To assess the robustness of study findings, we conducted a sensitivity analysis based on children matched for age within the study. This age matching was achieved through a one-to-one matching process employing nearest neighbour matching, with a calliper width set at 0.5 years.

The initial analysis conducted since September 2021 involved comparing metabolic variables between offspring born after fresh and frozen ET, as well as subgroup analyses based on the stages of embryo transfer (cleavage or blastocyst) and the mode of fertilization (IVF or ICSI), along with sensitivity analysis after matching for offspring age. However, considering the potential impact of offspring sex on metabolism, additional stratified analyses based on offspring sex (female or male) were conducted in February 2024. The statistical analyses were conducted using the R statistical software, version 4.2.3.

Results

Baseline characteristics of study offspring conceived by fresh and frozen embryo transfer are summarized in Table 1, encompassing parental, ART, pregnancy, and offspring characteristics. Maternal age and paternal age were significantly lower in offspring conceived by FET than those conceived by fresh embryos [maternal age: 30.9(28.4, 34.1) versus 31.3(28.4, 34.8); paternal age: 31.4(28.7, 34.9) versus 32.0(28.8, 35.6)]. Parental BMI, incidence of diabetes, educational level, paternal smoking status, and parity were comparable between offspring conceived by fresh and frozen embryo transfer. Offspring born after FET were more likely to undergo blastocyst ET and IVF than their fresh counterparts [blastocyst: 94% (2,051/2,181) versus 17.8% (368/2,065); IVF: 72.1% (1,572/2,181) versus 68.3% (1,410/2,065)]. Furthermore, mothers who received FET were more prone to developing PIH and undergoing cesarean sections compared to those who received fresh embryo transfer [PIH: 6.5% (141/2,181) versus 4.1% (84/2,065); cesarean sections: 74.9% (1,634/2,181) versus 72% (1,486/2,065)]. Birth weight was higher, and the age at the time of the visit was younger in the offspring conceived by frozen embryo transfer [birth weight SDS 0.55(−0.11, 1.31) versus 0.34(−0.30, 1.88); offspring age: 3.21(3.00, 4.01) versus 3.43(3.05, 4.16)]. There were no significant differences in the incidence of GDM, offspring sex distribution, or gestational age between offspring born after fresh and frozen embryo transfer.

We compared baseline characteristics between the included and not included offspring in the whole “ARTKID” cohort (S3 Table). Notably, our sample size is relatively large. Despite differences observed in parental age, paternal BMI, parity, embryo transfer stage, fertilization mode, and cesarean section rates, the actual difference were relatively small. For instance, the maternal age difference between those included and not included was merely 0.36 years in offspring conceived by fresh embryo transfer. The biochemical profile of offspring conceived by FET, compared with the fresh counterparts, is presented in Tables 2 and S4. No significant difference was observed in FBG, insulin, HOMA-IR2, TC, TG, and LDL-C levels between offspring conceived by fresh and frozen embryo transfer in crude and adjusted model. However, offspring born after FET showed a significantly increased HDL-C levels when compared to those born after Fresh-ET [mean difference (MD) (95% CI): crude model, 0.02(0.0005, 0.04); adjusted model, 0.02(0.002, 0.04)]. It is important to note that the significance of this difference was attenuated after the FDR correction (FDR q value: crude model, 0.16; adjusted model, 0.12).

We stratified the offspring into 2 subgroups based on sex (female and male) (Tables 3 and S5). Within both subgroups, we found no significant differences in metabolic biochemical parameters between the study offspring even after adjusting parental characteristics and offspring age. Next, we stratified the population into 2 subgroups based on embryo transfer stage (cleavage and blastocyst) (Tables 4 and S6). Within both subgroups, we also found no significant differences in metabolic biochemical parameters between the study offspring. In the blastocyst ET subgroup, offspring born after FET had significantly higher TG levels than those born after Fresh-ET. However, this difference disappeared after FDR adjustment (FDR q value: adjusted model, 0.08). Furthermore, we grouped the children by fertilization mode (IVF and ICSI) (Tables 5 and S7). Similar to our previous analysis, there were no statistically significant interactions between fertilization mode and study offspring. In both IVF and ICSI subgroups, no significant differences were observed in any metabolic biochemical parameters between offspring conceived by fresh and frozen embryo transfer.

Considering the offspring age in offspring conceived by FET was notably younger compared to the fresh counterparts (3.52 ± 0.74 versus 3.66 ± 0.74, p p = 0.45). Consistent with our prior findings, we found no statistically significant differences in metabolic biochemical parameters between offspring born after fresh and frozen embryo transfer (S8 and S9 Tables).

Discussion

The long-term safety of FET technology has historically been a concern because of adverse perinatal outcomes. Fortunately, our findings found no significant effect of frozen versus fresh embryo transfer on glucose and lipid biochemical parameters during early childhood.

Previous research has yielded inconsistent findings regarding the effect of FET on offspring metabolism. A Swedish study explored the risk of type 1 diabetes in singletons born after ART and found that offspring conceived by FET showed an increased risk of type 1 diabetes than those after Fresh-ET before 18 years in subgroup analysis (adjusted hazard ratio 1.52; 95% CI, 1.08 to 2.14) [35]. A New Zealand study reported that 115 children aged 3.5 to 11.0 years conceived through FET showed unfavourable lipid metabolism compared to those conceived through Fresh-ET, including higher TG and lower HDL-C [20]. Moreover, a rodent study has also observed that male offspring conceived by FET exhibit insulin resistance compared to their fresh counterparts [36].

In contrast, our study found no notable differences in glucose and lipid levels between 4,246 singletons aged 2 to 5 years born from frozen or fresh ET. The finding remained the same after adjusting for factors like parental, perinatal, and offspring characteristics. Several studies supported our research finding. A Finnish study observed that the endocrine, nutritional, and metabolic diseases in singletons born after FET do not differ from those born after Fresh-ET, with a mean follow-up time of 18 to 20 years [37]. A Danish cohort study found no statistically significant glucose and lipid profile differences among 150 singletons aged 8 to 9 years conceived after FET, Fresh-ET, and naturally conceived children [9]. These contradictory findings may be attributed to differences in sample size, offspring ethnicity, age, and potential confounding factors.

A higher proportion of blastocysts is transferred as frozen-thawed embryos [38]. Two previous meta-analyses have reported a significant higher risk of LGA in offspring born after blastocyst-stage embryo transfer compared with cleavage-stage transfer in frozen cycles, but not in fresh cycles [38,39]. Considering the potential different impact of embryo stage on the metabolic profiles of offspring, we conducted a subgroup analysis in children born after different stage. However, no significant differences in the metabolic profiles between frozen and Fresh-ET in subgroup analysis. And no interaction effects were found between these procedures and study offspring.

A study conducted by Green and colleagues identified adverse lipid metabolism among children conceived through FET than those conceived via Fresh-ET at the cleavage stage, including higher TG levels and lower HDL-C levels [20]. The study focused on children born between 1993 and 2005. Embryo cryopreservation, storage, and thawing techniques have significantly evolved in recent years, which may have contributed to the improvement of the metabolic health of frozen embryo offspring. Sample size and ethnic differences may also explain the inconsistent results. It is worth noting that there is a significantly higher proportion of blastocyst transfers among children born after FET and Fresh-ET [the proportion of blastocyst transfers: 94% (2,051/2,181) versus 17.8% (368/2,065)]. This disparity limited the statistical power and robustness of the findings within the embryo transfer stage subgroup. Consequently, these findings necessitate larger sample cohorts to be confirmed.

The gamete manipulation in ICSI may lead to epigenetic and imprinting alterations in the embryo [40]. A retrospective cohort study showed that birth weight of offspring born after ICSI was lower compared to those born after IVF [41]. Another recent study conducted by Catford and colleagues reported a significantly lower fasting glucose in 121 ICSI-conceived singletons compared with 74 IVF-conceived controls aged 18 to 24 years [42]. In our study, the proportion of ICSI was lower in offspring conceived by FET. Therefore, we further conducted subgroup analysis on the fertilization model to mitigate the potential impact of this confounding factor. These results remained consistent with the overall comparison of study offspring, further substantiating the robustness of the principal conclusion.

Our findings suggested there were no significant differences in glucose and lipid metabolism between fresh and frozen embryo offspring. However, previous studies have indicated that compared to natural conceived offspring, children conceived through FET or Fresh-ET often exhibit metabolic differences. Prior research highlights differences in metabolic markers, such as higher levels of FBG and Apolipoprotein E (APOE), as well as lower levels of HDL-C in children conceived through FET [2,20,43]. Children conceived through Fresh-ET also tend to have less favourable glucose and cardiovascular metabolic profiles than naturally conceived children [2]. Our study provides valuable insights into the strategy of embryo transfer for infertile couples undergoing IVF/ICSI. But the long-term metabolic health of offspring conceived through FET remains a concern, and continuous monitoring of their long-term metabolic health is necessary.

In comparison to prior related studies, our study exhibits several strengths. Firstly, the substantial sample size of 4,246 children enhances the robustness of our conclusions by providing a higher level of statistical power. Additionally, the large sample size enables us to conduct meaningful subgroup analyses. This provides more comprehensive information for both infertility couples and clinicians when discussing the pros and cons of various transfer and fertilized techniques. Secondly, our study focused on children aged 2 to 5 years, ensuring that they were not affected by minipuberty (1 to 6 months) or undergoing pubertal development. Finally, the data were highly homogeneous due to the use of single laboratory measurements for all participants and tests, which helped reduce confounding effects to some extent.

However, the study has certain limitations. Firstly, our study was based on an ART birth cohort and we did not include naturally conceived offspring in this cohort. Thus, it was not possible for us to include offspring conceived naturally. Our study focused on the strategy of embryo transfer for couples undergoing ART treatment. Secondly, the substantial disparity was observed in the stages of embryo transfer between offspring born after fresh and frozen embryo transfer. In our study, Fresh-ET primarily at the cleavage stage and FET at the blastocyst stage, which is consistent with other studies [44–47]. Considering that adjustment may not be sufficient to eliminate the imbalance between offspring born after fresh and frozen embryo transfer, we conducted a subgroup analysis. Our results showed that the long-term metabolic profiles were comparable between frozen embryos and fresh embryos, whether they were at the blastocyst or cleavage stage. However, it is important to note that the imbalance in numbers may have affected the interpretation of these results.

Thirdly, not all offspring provided blood samples in the whole “ARTKID” cohort. Possible reasons include failure to reach the follow-up deadline, offspring noncompliance with invasive blood testing, and external factors such as the COVID-19 pandemic during 2020 to 2021, or residing far from our center. We compared baseline characteristics between the included and not included population. The actual differences were relatively small. Thus, we would deduce that selection bias may have little impact on our results.

Fourthly, some potentially confounding information may not have been collected in our study, such as breastfeeding status and smoking during pregnancy. Breastfeeding may be associated with obesity in childhood and thereby the risk of metabolic syndrome [48]. However, there is no previous research focusing on the difference of breastfeeding between FET and Fresh-ET. Thus, it is difficult to assess the impact of breastfeeding on our results. It is well established that maternal tobacco exposure during pregnancy increases offspring obesity and metabolic risk [49,50]. But, only 3.4% of Chinese women were reported to be smokers in the 2010 national survey [51], and about 82.9% of smoking women quit smoking after becoming pregnant [52]. Therefore, the proportion of women smoking during pregnancy is extremely low in China. Moreover, maternal smoking may be unrelated to the selection of embryo transfers. Thus, this bias may have little impact on the results. Fifthly, genetic and socioeconomic factors that affect offspring could be additional potential confounders. A matched sibling cohort can help eliminate the influence of genetic factors, but it may significantly reduce the sample size and make it challenging to maintain offspring age balance. In our study, we collected and adjusted comprehensive parental baseline information to minimize its impact on the results as much as possible.

Another limitation is the “live-birth bias” from only focusing on live births in our cohorts [53]. However, live-birth is one essential inclusion criteria for assessing the long-term outcome of children, potentially inevitably introducing selection bias. Our study may only represent live birth offspring born from ART. Finally, the offspring were aged 2 to 5 years at the time of our study. As they are too young to reveal more comprehensive metabolic phenotypic changes, further longer follow-up studies may be needed.

In conclusion, compared to offspring born after fresh embryo transfer, those born after FET showed no significant adverse metabolic changes during early childhood in our large sample size study. However, the long-term metabolic health of offspring conceived through FET remains a concern, and continuous monitoring of their long-term metabolic health is necessary.

References

  1. 1.
    ESHRE. ART Fact Sheet. 2022. Available from: https://www.eshre.eu/Europe/Factsheets-and-infographics.
  2. 2.
    Cui L, Zhou W, Xi B, Ma J, Hu J, Fang M, et al. Increased risk of metabolic dysfunction in children conceived by assisted reproductive technology. Diabetologia. 2020;63(10):2150–2157. Epub 2020/08/07. pmid:32757153.
  3. 3.
    Guo XY, Liu XM, Jin L, Wang TT, Ullah K, Sheng JZ, et al. Cardiovascular and metabolic profiles of offspring conceived by assisted reproductive technologies: a systematic review and meta-analysis. Fertil Steril. 2017;107(3):622–631.e5. Epub 2017/01/21. pmid:28104241.
  4. 4.
    Sakka SD, Loutradis D, Kanaka-Gantenbein C, Margeli A, Papastamataki M, Papassotiriou I, et al. Absence of insulin resistance and low-grade inflammation despite early metabolic syndrome manifestations in children born after in vitro fertilization. Fertil Steril. 2010;94(5):1693–1699. Epub 2010/01/05. pmid:20045517.
  5. 5.
    Hanson MA, Gluckman PD. Early developmental conditioning of later health and disease: physiology or pathophysiology? Physiol Rev. 2014;94(4):1027–1076. Epub 2014/10/08. pmid:25287859.
  6. 6.
    Maheshwari A, Pandey S, Amalraj Raja E, Shetty A, Hamilton M, Bhattacharya S. Is frozen embryo transfer better for mothers and babies? Can cumulative meta-analysis provide a definitive answer? Hum Reprod Update. 2018;24(1):35–58. Epub 2017/11/21. pmid:29155965.
  7. 7.
    Smeenk J, Wyns C, De Geyter C, Kupka M, Bergh C, Cuevas Saiz I, et al. ART in Europe, 2019: results generated from European registries by ESHRE†. Hum Reprod. 2023;38(12):2321–2338. Epub 2023/10/17. pmid:37847771.
  8. 8.
    Zaat T, Zagers M, Mol F, Goddijn M, van Wely M, Mastenbroek S. Fresh versus frozen embryo transfers in assisted reproduction. Cochrane Database Syst Rev. 2021;2(2):Cd011184. Epub 2021/02/05. pmid:33539543.
  9. 9.
    Mizrak I, Asserhøj LL, Lund MAV, Kielstrup LR, Greisen G, Clausen TD, et al. Cardiovascular function in 8- to 9-year-old singletons born after ART with frozen and fresh embryo transfer. Hum Reprod. 2022;37(3):600–611. Epub 2022/01/12. pmid:35015837.
  10. 10.
    Wei D, Liu JY, Sun Y, Shi Y, Zhang B, Liu JQ, et al. Frozen versus fresh single blastocyst transfer in ovulatory women: a multicentre, randomised controlled trial. Lancet (London, England). 2019;393(10178):1310–1318.Epub 2019/03/05. pmid:30827784.
  11. 11.
    Pinborg A, Henningsen AA, Loft A, Malchau SS, Forman J, Andersen AN. Large baby syndrome in singletons born after frozen embryo transfer (FET): is it due to maternal factors or the cryotechnique? Hum Reprod. 2014;29(3):618–627. Epub 2014/01/15. pmid:24413766.
  12. 12.
    Sha T, Yin X, Cheng W, Massey IY. Pregnancy-related complications and perinatal outcomes resulting from transfer of cryopreserved versus fresh embryos in vitro fertilization: a meta-analysis. Fertil Steril. 2018;109(2):330–342.e9. Epub 2018/01/15. pmid:29331236.
  13. 13.
    Raja EA, Bhattacharya S, Maheshwari A, McLernon DJ. Comparison of perinatal outcomes after frozen or fresh embryo transfer: separate analyses of singleton, twin, and sibling live births from a linked national in vitro fertilization registry. Fertil Steril. 2022;118(2):323–334. Epub 2022/06/19. pmid:35717287.
  14. 14.
    Boney CM, Verma A, Tucker R, Vohr BR. Metabolic syndrome in childhood: association with birth weight, maternal obesity, and gestational diabetes mellitus. Pediatrics. 2005;115(3):e290–e296. Epub 2005/03/03. pmid:15741354.
  15. 15.
    Zhang Y, Liu P, Zhou W, Hu J, Cui L, Chen ZJ. Association of large for gestational age with cardiovascular metabolic risks: a systematic review and meta-analysis. Obesity (Silver Spring, Md). 2023;31(5):1255–1269. Epub 2023/05/04. pmid:37140379.
  16. 16.
    Tripathi RR, Rifas-Shiman SL, Hawley N, Hivert MF, Oken E. Hypertensive Disorders of Pregnancy and Offspring Cardiometabolic Health at Midchildhood: Project Viva Findings. J Am Heart Assoc. 2018;7(3). Epub 2018/02/01. pmid:29382664.
  17. 17.
    Hermann GM, Dallas LM, Haskell SE, Roghair RD. Neonatal macrosomia is an independent risk factor for adult metabolic syndrome. Neonatology. 2010;98(3):238–244. Epub 2010/04/15. pmid:20389129.
  18. 18.
    Laugesen K, Veres K, Hernandez-Diaz S, Chiu YH, Oberg AS, Hsu J, et al. Overweight or obesity in children born after assisted reproductive technologies in Denmark: A population-based cohort study. PLoS Med. 2023;20(12):e1004324. Epub 2023/12/19. pmid:38113196.
  19. 19.
    Elhakeem A, Taylor AE, Inskip HM, Huang J, Tafflet M, Vinther JL, et al. Association of Assisted Reproductive Technology With Offspring Growth and Adiposity From Infancy to Early Adulthood. JAMA Netw Open. 2022;5(7):e2222106. Epub 2022/07/27. pmid:35881399.
  20. 20.
    Green MP, Mouat F, Miles HL, Hopkins SA, Derraik JG, Hofman PL, et al. Phenotypic differences in children conceived from fresh and thawed embryos in in vitro fertilization compared with naturally conceived children. Fertil Steril. 2013;99(7):1898–1904. Epub 2013/03/12. pmid:23472944.
  21. 21.
    Dai L, Deng C, Li Y, Zhu J, Mu Y, Deng Y, et al. Birth weight reference percentiles for Chinese. PLoS ONE. 2014;9(8):e104779. Epub 2014/08/16. pmid:25127131.
  22. 22.
    Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S17–S38. Epub 2021/12/30. pmid:34964875.
  23. 23.
    Goldstein JL, Brown MS. A century of cholesterol and coronaries: from plaques to genes to statins. Cell. 2015;161(1):161–172. Epub 2015/03/31. pmid:25815993.
  24. 24.
    Soppert J, Lehrke M, Marx N, Jankowski J, Noels H. Lipoproteins and lipids in cardiovascular disease: from mechanistic insights to therapeutic targeting. Adv Drug Deliv Rev. 2020;159:4–33. Epub 2020/07/31. pmid:32730849.
  25. 25.
    Cooke CM, Shah A, Kirschenman RD, Quon AL, Morton JS, Care AS, et al. Increased susceptibility to cardiovascular disease in offspring born from dams of advanced maternal age. J Physiol. 2018;596(23):5807–5821. Epub 2018/06/09. pmid:29882308.
  26. 26.
    Velazquez MA, Smith CG, Smyth NR, Osmond C, Fleming TP. Advanced maternal age causes adverse programming of mouse blastocysts leading to altered growth and impaired cardiometabolic health in post-natal life. Hum Reprod. 2016;31(9):1970–1980. Epub 2016/07/13. pmid:27402911.
  27. 27.
    Ahn HY, Hwang IC. Paternal age at birth and metabolic risk factors in adolescents: a nationwide survey. Public Health. 2019;175:1–3. Epub 2019/07/31. pmid:31362168.
  28. 28.
    Santos Ferreira DL, Williams DM, Kangas AJ, Soininen P, Ala-Korpela M, Smith GD, et al. Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts. PLoS Med. 2017;14(8):e1002376. Epub 2017/08/23. pmid:28829768.
  29. 29.
    Noor N, Cardenas A, Rifas-Shiman SL, Pan H, Dreyfuss JM, Oken E, et al. Association of Periconception Paternal Body Mass Index With Persistent Changes in DNA Methylation of Offspring in Childhood. JAMA Netw Open. 2019;2(12):e1916777. Epub 2019/12/28. pmid:31880793.
  30. 30.
    Yen AM, Boucher BJ, Chiu SY, Fann JC, Chen SL, Huang KC, et al. Longer Duration and Earlier Age of Onset of Paternal Betel Chewing and Smoking Increase Metabolic Syndrome Risk in Human Offspring, Independently, in a Community-Based Screening Program in Taiwan. Circulation. 2016;134(5):392–404. Epub 2016/07/28. pmid:27448815.
  31. 31.
    Gaillard R, Rurangirwa AA, Williams MA, Hofman A, Mackenbach JP, Franco OH, et al. Maternal parity, fetal and childhood growth, and cardiometabolic risk factors. Hypertension (Dallas, Tex: 1979). 2014;64(2):266–274. Epub 2014/05/29. pmid:24866145.
  32. 32.
    Silventoinen K, Jelenkovic A, Latvala A, Yokoyama Y, Sund R, Sugawara M, et al. Parental Education and Genetics of BMI from Infancy to Old Age: A Pooled Analysis of 29 Twin Cohorts. Obesity (Silver Spring, Md). 2019;27(5):855–865. Epub 2019/04/06. pmid:30950584.
  33. 33.
    Avnon Ziv C, Banon T, Ben Tov A, Chodick G, Gabay L, Auerbach A, et al. Glucose levels are not the same for everyone: a real-world big data study evaluating fasting serum glucose levels by sex and age among children. J Pediatr Endocrinol Metab. 2023;36(9):851–858. Epub 2023/08/14. pmid:37579024.
  34. 34.
    Azizi-Soleiman F, Khoramdad M, Heshmat R, Ejtahed HS, Motlagh ME, Daniali SS, et al. Reference values for lipid profile in Iranian children and adolescents: the CASPIAN-V study. Lipids Health Dis. 2020;19(1):16. Epub 2020/02/02. pmid:32005167.
  35. 35.
    Norrman E, Petzold M, Clausen TD, Henningsen AK, Opdahl S, Pinborg A, et al. Type 1 diabetes in children born after assisted reproductive technology: a register-based national cohort study. Hum Reprod. 2020;35(1):221–231. Epub 2020/01/25. pmid:31976535.
  36. 36.
    Qin N, Zhou Z, Zhao W, Zou K, Shi W, Yu C, et al. Abnormal Glucose Metabolism in Male Mice Offspring Conceived by in vitro Fertilization and Frozen-Thawed Embryo Transfer. Front Cell Dev Biol. 2021;9:637781. Epub 2021/02/27. pmid:33634140.
  37. 37.
    Terho AM, Tiitinen A, Martikainen H, Gissler M, Pelkonen S. Health of singletons born after frozen embryo transfer until early adulthood: a Finnish register study. Hum Reprod. 2022;37(12):2899–2907. Epub 2022/09/28. pmid:36166701.
  38. 38.
    Marconi N, Allen CP, Bhattacharya S, Maheshwari A. Obstetric and perinatal outcomes of singleton pregnancies after blastocyst-stage embryo transfer compared with those after cleavage-stage embryo transfer: a systematic review and cumulative meta-analysis. Hum Reprod Update. 2022;28(2):255–281. Epub 2021/12/31. pmid:34967896.
  39. 39.
    Alviggi C, Conforti A, Carbone IF, Borrelli R, de Placido G, Guerriero S. Influence of cryopreservation on perinatal outcome after blastocyst- vs cleavage-stage embryo transfer: systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2018;51(1):54–63. Epub 2017/10/28. pmid:29077229.
  40. 40.
    Sciorio R, Esteves SC. Contemporary Use of ICSI and Epigenetic Risks to Future Generations. J Clin Med. 2022;11(8). Epub 2022/04/24. pmid:35456226.
  41. 41.
    Nouri K, Ott J, Stoegbauer L, Pietrowski D, Frantal S, Walch K. Obstetric and perinatal outcomes in IVF versus ICSI-conceived pregnancies at a tertiary care center—a pilot study. Reprod Biol Endocrinol. 2013;11:84. Epub 2013/09/06. pmid:24004836.
  42. 42.
    Catford SR, Halliday J, Lewis S, O’Bryan MK, Handelsman DJ, Hart RJ, et al. The metabolic health of young men conceived using intracytoplasmic sperm injection. Hum Reprod. 2022;37(12):2908–2920. Epub 2022/09/28. pmid:36166702.
  43. 43.
    Dong ZH, Wu T, Zhang C, Su KZ, Wu YT, Huang HF. Effect of Frozen-Thawed Embryo Transfer on the Metabolism of Children in Early Childhood. J Clin Med. 2023;12(6). Epub 2023/03/30. pmid:36983323.
  44. 44.
    Holden EC, Kashani BN, Morelli SS, Alderson D, Jindal SK, Ohman-Strickland PA, et al. Improved outcomes after blastocyst-stage frozen-thawed embryo transfers compared with cleavage stage: a Society for Assisted Reproductive Technologies Clinical Outcomes Reporting System study. Fertil Steril. 2018;110(1):89–94.e2. Epub 2018/06/18. pmid:29908769.
  45. 45.
    Fang C, Huang R, Wei LN, Jia L. Frozen-thawed day 5 blastocyst transfer is associated with a lower risk of ectopic pregnancy than day 3 transfer and fresh transfer. Fertil Steril. 2015;103(3):655–661.e3. Epub 2014/12/30. pmid:25542820.
  46. 46.
    Ishihara O, Araki R, Kuwahara A, Itakura A, Saito H, Adamson GD. Impact of frozen-thawed single-blastocyst transfer on maternal and neonatal outcome: an analysis of 277,042 single-embryo transfer cycles from 2008 to 2010 in Japan. Fertil Steril. 2014;101(1):128–133. Epub 2013/11/26. pmid:24268706.
  47. 47.
    Ishihara O, Kuwahara A, Saitoh H. Frozen-thawed blastocyst transfer reduces ectopic pregnancy risk: an analysis of single embryo transfer cycles in Japan. Fertil Steril. 2011;95(6):1966–1969. Epub 2011/03/08. pmid:21377154.
  48. 48.
    Pena-Leon V, Folgueira C, Barja-Fernández S, Pérez-Lois R, Da Silva LN, Martin M, et al. Prolonged breastfeeding protects from obesity by hypothalamic action of hepatic FGF21. Nat Metab. 2022;4(7):901–917. Epub 2022/07/26. pmid:35879461.
  49. 49.
    Albers L, Sobotzki C, Kuß O, Ajslev T, Batista RF, Bettiol H, et al. Maternal smoking during pregnancy and offspring overweight: is there a dose-response relationship? An individual patient data meta-analysis. Int J Obes (Lond) (2005). 2018;42(7):1249–64. Epub 2018/05/03. pmid:29717267.
  50. 50.
    Riedel C, Schönberger K, Yang S, Koshy G, Chen YC, Gopinath B, et al. Parental smoking and childhood obesity: higher effect estimates for maternal smoking in pregnancy compared with paternal smoking—a meta-analysis. Int J Epidemiol. 2014;43(5):1593–1606. Epub 2014/08/01. pmid:25080528.
  51. 51.
    Liu S, Zhang M, Yang L, Li Y, Wang L, Huang Z, et al. Prevalence and patterns of tobacco smoking among Chinese adult men and women: findings of the 2010 national smoking survey. J Epidemiol Community Health. 2017;71(2):154–161. Epub 2016/09/24. pmid:27660401.
  52. 52.
    Xu X, Rao Y, Wang L, Liu S, Guo JJ, Sharma M, et al. Smoking in pregnancy: a cross-sectional study in China. Tob Induc Dis. 2017;15:35. Epub 2017/07/28. pmid:28747859.
  53. 53.
    Liew Z, Olsen J, Cui X, Ritz B, Arah OA. Bias from conditioning on live birth in pregnancy cohorts: an illustration based on neurodevelopment in children after prenatal exposure to organic pollutants. Int J Epidemiol. 2015;44(1):345–354. Epub 2015/01/22. pmid:25604449.
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