Effect of frozen-thawed embryo transfer on metabolism of children in early childhood

doi:10.21203/rs.3.rs-1625041/v1

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Effect of frozen-thawed embryo transfer on metabolism of children in early childhood

https://doi.org/10.21203/rs.3.rs-1625041/v1

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Background:

As a routine procedure in assisted reproductive technology (ART), it is crucial to assess the safety of frozen and thawed embryo transfer (FET). We aimed to investigate the metabolic profile of children conceived through FET between the ages of 1.5 and 4.

Method:

284 children between the ages of 1.5 and 4 years old, conceived through FET or spontaneously conceived, were recruited. A total of 147 children were included in the biochemical and metabolomics analysis (118 were born following FET and 29 were conceived spontaneously).

Results:

Children in the FET group had higher plasma ApoE and lower fasting insulin than those in the NC group. There were 11 small molecule metabolities that differed between the FET and NC groups: short chain fatty acid and secondary bile acid were higher in the FET group, whereas medium and long chain fatty acids were lower.

Conclusion:

We found that the fasting insulin level and HOMA-IR index which related to glycometabolism were decreased in FET group. Increased level of ApoE and decreased level of medium and long chain fatty acids in FET group indicated the abnormal lipid metabolism of children born after FET. Meanwhile, the increase of SCFAs (short chain fatty acids) level and secondary bile acids in FET group may suggeste the active metabolism of intestinal flora of children conceived from FET.

frozen-thawed embryo transfer

metabolomic

metabolite

BMI

fatty acids

As the most widely used treatment for infertility, more than 8 million children worldwide have been born through assisted reproduct technology (ART) up to 2018[1]. Since the first successful frozen-thawed embryo transfer (FET) was reported in 1983, it has become a very important part of assisted reproductive technology (ART)[2]. Despite the fact that FET can greatly enhance the cumulative pregnancy rate and lower the risk of multiple gestations and ovarian hyperstimulation syndrome (OHSS)[3], there have been concerns expressed regarding its potential drawbacks. FET has been identified as a potential risk factor for pregnancy-induced hypertension, large for gestational age, and macrosomia [4-7], all of which might raise the risk of metabolic dysfunction and cardiovascular problems [8, 9].

At the same time, the expositon of gametes and embryos to the non-physiological environment during the critical preimplamtation period may lead to epigenetic disorder of growth and metabolic systems in the offspring and result in long-term effect in their later life.

Animal studies have shown that IVF-ET (in vitro fertilization and embryo transfer) offspring have impaired glucose metabolism, including altered fasting glucose levels and impaired glucose tolerance (IGT). [10-13]. Recently, we discovered that FET-conceived male mouse offspring had glucose metabolic abnormalities, mainly manifesting insulin resistance [14]. Observations from human studies indicate that body fat composition in IVF children is disturbed and children conceived by IVF/ICSI (intracytoplasmic sperm injection) have a less favourable glucose and cardiovascular metabolic profile in childhood when compared with naturally conceived children [15, 16]. However, human research on the metabolic profile of children conceived through FET is limited. One follow-up study found that children conceived through FET frequently have abnormal lipid metabolism. [17].

Metabolomics, also known as the comprehensive profiling of small molecule metabolites in cells, is the study of the types, quantities and changes of endogenous metabolites in biological systems, has undergone a rapid evolution in the past two decades [18]. We aimed to investigate the metabolic profile of FET offspring in the early childhood, through the level of macromolecular metabolities and small molecule changes, and explore its potential impact on the metabolism in early childhood.

1. Study design and population

The present study investigated the metabolic profile and its relationship with FET in children aged 1.5 to 4 years. From September 2018 to November 2019, 182 children born from FET and 66 naturally conceived children were recruited based on the data from electronic Case Report Forms (e-CRF) in the International Peace Maternity and Child Health Hospital (IPMCHH). For biochemical and metabolomic analyses, a subgroup of 118 children from the FET group and 29 from the NC group who provided venous blood were included.

This study was approved by the hospital's scientific research ethics committee ((GKLW) 2016-21), and each participating signed an informed consent form for sample and data collection.

2. Inclusion and exclusion criteria：

Given that early childhood is a critical period for early health intervention, and the small diameter of the blood vessel can make peripheral blood collection difficult, the main inclusion criteria were singleton birth children born after 28 gestational weeks and aged 1.5-4 years on the follow-up day.The exclusion criteria were as follows: 1) The mother had a history of severe liver and kidney dysfunction, diabetes, cancer, or autoimmune system disease; 2) One or both of their parents’ BMI was greater than 40 prior to pregnancy; 3) Children with severe congenital malformations, chromosomal abnormalities,or congenital metabolic diseases ( as described in the previous study [19, 20] ); 4) Children developed from embryo preserved by conventional slow freezing method.

In addition, our previous study suggested the transfer of embryos with blastomere loss is associated with increased risk of small for gestational age[21], which is related to obesity combined with insulin resistance, fatty liver and cardiovascular abnormalities and other chronic diseases in adulthood[22-25]. Animal studies have also suggested that adult PGT-born mice may be at risk of insulin resistance[26, 27]. Therefore, FET group was subdivided based on IVF-related information, such as blastomere loss group (all embryos transferred with at least one blastomere lost), intact group (all embryos transferred were intact), PGT (preimplantation genetic testing) group (having undergone PGT without other blastomere loss).

3. Medical History

Sociodemographic characteristics, birth characteristics, and other potential confounding factors were collected by a questionnaire that was administered by a specially trained investigator. Specifically, month age = (date of examination - date of birth)/ 30， gestational week (GW) refers to the exact days of gestational week ( e.g. 39 weeks + 5 days = 39.7 weeks). The diagnosis of GDM (gestational diabetes mellitus)was confirmed if fasting blood glucose ≥ 110 mg/dl (6.1mmol/ L) or 2-hour blood glucose ≥ 140mg/ dL (7.8mmol/ L) according to the threshold recommended by WHO [28]. Preterm birth (PTB): gestational week < 37 weeks; low birthweight (LB): birthweight <2500g; macrosomia: birth weight ≥4000g; birth weight ≤ 10th percentile was defined as small for gestational age (SGA), and ≥ 90th percentile was defined as large for gestational age (LGA). In the case of alcohol consumption, a positive result was defined as having consumed alcohol at least once one year before childbirth. A positive result for smoking was defined as a history of smoking, whereas a positive result for passive smoking was defined as exposure to second-hand smoking during pregnancy.

4. IVF Procedures

The ovarian stimulation protoclol include conventional protocols (GnRH-agonist long protocol, short protocol, and GnRH antagonist protocol), modified mild protocol and individualized combinated protocol [29-32]. The choice of different protocol based upon patient age, infertility diagnosis and ovarian reserve testing result. Oocytes were collected 34-36 hours after ovulation was triggered [33] and inseminated using traditional IVF or ICSI. Fertilized oocytes were cultured in cleavage medium until day 2 or day 3 before being cryopreserved via vitrification[34]. Natural cycles, hormone replacement cycles, and human menopausal gonadotropin (HMG)-stimulated cycles were used to administer endometrial preparation. [35]. The embryos were thawed and transferred on a day when the oestradiol levels and endometrial thickness were well-prepared.

5. Biochemical analysis

The children's peripheral venous blood was drawn while they were fasting (>8 hours) and centrifuged at 3000g for 10 minutes. Prior to analysis, the plasma was kept in an - 80 °C refrigerator. Fasting blood glucose (FBG) was measured using a glucometer ((ACCU-CHEK (Roche) glucose meter). Plasma concentrations of total cholesterol (CHOD-POD method), triglyceride (GPO-PAP method), HDL-cholesterol (direct method), LDL-cholesterol (direct method) were measured by TBA 120 FR chemistry analyzer (Toshiba Co., Japan) [36]. The original formula was used to calculate the homeostasis model assessment (HOMA) as a marker of insulin resistance[37].

6. Metabolomic analysis

6.1Sample Preparation

All targeted metabolite standards were obtained from Sigma-Aldrich (St. Louis, MO, USA), Steraloids Inc. (Newport, RI, USA), and TRC Chemicals (Toronto, ON, Canada). All standards were precisely weighed and prepared in water, methanol, sodium hydroxide solution, or hydrochloric acid solution to yield individual stock solutions containing 5.0 mg / mL. To create stock calibration solutions, an appropriate amount of each stock solution was mixed.To reduce sample degradation, samples were thawed on ice, 25μL of plasma was added to a 96-well plate, and the plate was transferred to the Biomek 4000 workstation (Biomek 4000, Beckman Coulter, Inc., Brea, California, USA). Each sample received 100L of ice methanol with partial internal standards and was vortexed vigorously for 5 minutes.

The plate was returned to the workstation after centrifugation at 4000g for 30 minutes (Allegra X-15R, Beckman Coulter, Inc., Indianapolis, IN, USA). 30 μL of supernatant was transferred to a clean 96-well plate, and each well received 20μL of freshly prepared derivative reagents. 350μL of ice-cold 50% percent methanol solution was added to dilute the sample after it had been sealed and derivatized at 30°C for 60 minutes. The plate was then stored at -20°C for 20 minutes before being centrifuged at 4 °C for 30 minutes. 135μL of supernatant was transferred to a new 96-well plate, each with 15 μL internal standards. The left wells were treated with serial dilutions of derivatized stock standards.

6.2 Data analysis and processing

Metabolomic analysis was performed against 210 standard metabolites using an ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) system (ACQUITY UPLC-Xevo TQ-S, Waters Corp., Milford, MA, USA); a similar method was prescribed in previous studies.[38, 39]. The following are brief descriptions of the optimized instrument settings: Temperatures for the sample manager and column were set to 10°C and 40°C, respectively. The injection volume was set at 5μL, with a flow rate of 0.4ml/min. The mobile phases were 0.1% formic acid (A) and acetonitrile (B). The gradient conditiona were set as follows: 0 - 1 min, 5% B; 1 - 12min, 5 → 80%B; 12 - 15min, 80%-95% B; 15 - 16min, 100% B; 18 - 18.1min, 100% → 5% B, 18.1-20min, 5%B. The following instrument parameters were chosen for the mass spectrometer: capilary voltage,1.5Kv (ESI+)2.0(ESI-), source temperature, 150 °C; desolvation temperature, 550 °C; desolvation gas flow, 1000L/h. The raw data files generated by UPLC-MS/MS were processed using the QuanMETsoftware (v2.0, Metabo- Profile, Shanghai, China) to perform peak integration, calibration, and quantification of each metabolite.

7. Statistical Analysis

Statistical data analysis was conducted using SPSS (IBM, USA). Continuous viriables with normal distribution were presented as mean ± standard deviation (SD), while continuous variables with nonnormal distribution were presented as median (first quartile, third quartile), the differences in the continuous variables between two groups were tested using the t test or Mann-Whitney U test. Noncontinuous data were presented as percentage, and differences were detected uisng the Pearson χ2 test or Fisher’s exact test. A p -value less than 0.05 was deemed significant. Based on XploreMET one-stop analysis software platform (including embedded statistical R software (3.2.1) code and a link to the KEGG database) for metabolomic data analysis, interpretation, and visual mapping. For group discrimination, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structure discriminant analysis (OPLS-DA) were used in multivariate statistical analysis. A permutation test (1000 times) was performed for the statistical validation of the OPLS-DA model. Univiarite analysis was also performed t test or Mann-Whitney U Test) to determine the differential metabolites. VIP > 1 was regarded as significant. The concentration of each metabolite (mol/L) was standardized into a Z score, and color-coded heat maps based on the normalized Z-score were plotted to show the up-down regulation of metabolites between two groups. The altered metabolites' involved pathways were identified using the KEGG-hsa library (http://www.genome.jp/kegg-bin/showpathway).

1. Baseline characteristics

There were 118 children conceived through FET and 29 children conceived naturally among the 147 children included for metabolism analysis. The FET group was further subdivided by IVF information, with 10 children in the blastomere loss group, 83 children in the intact group, and 25 children in the PGT group. The comparison of baseline characteristics between FET group and NC group were summarized in TableS1. with the NC group having an age distribution of 36.80 (32.40-41.40) and the FET group having an age distribution of 32.70 (26.08-35.38) (P < 0.001). Children in the FET group had a significantly higher BMI [16.10 (15.28-17.00)] than children in the NC group [15.40 (14.85-16.1) (p = 0.038). In addition, in the FET group, more mothers had consumed alcohol one year prior to delivery than in the NC group.

Baseline characteristics of children from various FET subgroups and NC group were described in Table1. Children from NC group were older than children from various FET subgroups. When compared to the NC group, the intact group had a higher BMI.The birthweight of children in the blastomere loss group was significantly lower than that of the NC group, with no significant difference between the other FET subgroups and the NC group. The total duration of breastfeeding was shorter in the intact group than in the NC group.

Furthermore, possibly due to sample size limitations, no increase in the incidence of SGA was observed in the blastomere loss group, whereas the incidence of SGA in the PGT group was significantly higher than that in the NC group.

2. Biochemical profile

A broad spectrum of biochemical change in FET subgroups compared with the NC group were presented in Table2. Significant increased of HDL level was observed in intact group than NC group. Children from two FET subgroups (intact group and PGT group) had higher ApoE concentrations than children from the NC group. As for glucose metabolism, the fasting insulin level and HOMA-IR index were dereased in intact group, while the FT3 level were increased as compared to NC group.

The biochemical profile comparison of the whole FET group and NC group was summarized in TableS2. FET-conceived children had lower fasting insulin levels and HOMA-IR indexes than naturally conceived children (p < 0.001). ApoE, on the other hand, was significantly higher in the FET group when compared to the NC group (p = 0.006). Other biochemical levels between the two groups were nearly comparable.

3. Metabolomic profile

210 small molecule metabolites (µmol/L) from three metabolic pathways including glucose, amino acid and lipid metabolism were detected in plasma, detais of category and KEGG number were presented in Table S3. The stacked bars of relative abundance of various metabolite types in each sample are shown in Figure S1.

The results of principal component analysis (PCA) on the population structure, as well as OPLS-DA (orthogonal partial least-squares discrimination analysis) score plots and the permutation test for each FET subgroup, FET group, and NC group were presented in Figure 1. However, successful PCA was only observed beween blastomereloss group and NC group, with 49 different small metabolites detected beween the two groups. For other two groups comparision, the permutation test indicated the overfitting of the multiple analysis modle. Based on univariate analysis, the volcano plot (Figure2) and Z-score heatmap (Figure3) displayed the differential metabolites screened. There were 10 and 15 different metabolites between the intact group, PGT group, and NC group, respectively. The differential metabolities screened based on both multiple analysis and univariate analysis were presented in Figure3c for the blatomere loss group, with 15 differential metabolites detected between the two groups. (FigureS2). When compared to the NC group, the FET group had 9 altered metabolites (Figure 2d). The metabolite concentrations responsible for the differences between the groups were identified and summarized in Table S4 and Figure S3-S6 (box plot).

3.1 Decreased middle and long chain fatty acid in FET groups

The results revealed that all three FET subgroups and the FET group had lower levels of fatty acid than the NC group. In the FET subgroup, the PGT and blastomere loss groups had significantly lower levels of 6 and 3 types of fatty acids, respectively, than the NC group. When compared to the NC group, the FET group had significantly lower levels of three types of fatty acids: 9-Pentadecenoic acid, trans-10-Hepadecenoic acid, and Tridecanoic acid.

3.2 Increased short chain fatty acid (SCFAs) in FET groups

The results revealed that all three FET subgroups and the FET group had higher levels of short chain fatty acid than the NC group. Butyric acid levels were significantly higher in two FET subgroups (intact and blastomere loss) and the FET group when compared to the NC group. And the isocaproic acid level was significantly higher in all FET subgroups and in the FET group than in the NC group. In addition, pyruvic acid in the PGT group and propanoic acid in the blastomere loss group were significantly higher than in the NC group.

3.3 Increased D-Xylose and bile acid in FET groups

When compared to the NC group, D-Xylose levels were significantly higher in the intact, PGT, and FET groups. When it came to bile acid, taurolithocholic acid (secondary bile acid) was significantly higher in the intact group and in the FET group when compared to the NC group. And the blastomere loss group had significantly higher level of chenodeoxycholic acid (primary bile acid) than NC group.

3.4 Amio acid levels differ across groups

Compared to NC group, L-Arginine was increased in intact group, L-Homocitrullinr was increased in PGT group, L-Cystine, L-Leucine and Sarcosine were increased in blastomere loss group, on the contrary，orithine was decreased in intcat group, Methylcysteine was decreased in PGT group, methylcysteine and ornithine were decreased in FET group.

3.5 Metabolic pathways assocaited with FET

According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database，metabolic oathway associated with FET were summarized in Figure4. The affected metabolic pathways in chidren borned from FET were d-arginine and d-ornithine metabolic pathway. For PGT group, the affected metabolic pathway included Citric acid cycle (TCA cycle), glyoxylic acid and dicarboxylic acid metabolism, arginine and proline metabolism, pyruvate metabolism, glutathione metabolism, glycine, serine and threonine metabolism, cysteine and methionine metabolism, D-arginine and D-ornithine metabolism, biotin metabolism. For intact group, there were four affected pathways, in which ornithine was enriched in D-arginine and D-ornithine metabolic pathway. There were no affected metabolic pathways in blastomere loss group.

The current study found that children conceived through FET have a different metabolite profile than naturally conceived children.Evidence obtained from animal stdudy revealed that embryonic exposure to culture components had an effect on the body mass and adiposity of adult offspring in mice[40]. A human study demonstrated that children born after IVF have exaggerated weight gain in late infancy, and that such catch-up growth appeared to correlate with the fetal growth pattern itself, regardless of birthweight[41]. In the current study, higher body mass index (BMI) was observed in children born after FET compared to the NC group, which may indicate that children born after FET have a higher weight gain and are at a higher risk of obesity.

Glucose homeostasis plays critical role in sustaining stable growth and metabolic status for individual. A meta-analysis found that ART offspring had higher fasting insulin levels, but no significant difference in fasting glucose or HOMA-IR when compared to non-ART offspring[42]. Human study demonstrated that the children conceived by ART have significantly higher fasting blood glucose and serum insulin levels than chidren children conceived naturally. [16]. Our animal study showed the decreased insulin tolerance of FET conceived male offspring, with higher HOMA-IR index and higher serum insulin level post glucose injected than the mouse conceived of natural conception[14].

In the present study, fast blood glucose was measured in the children who were initially recruited, and the index was comparable between the FET and NC groups. However, the fast insulin level was significantly decreased in the FET group (especially the intact group) than in the NC group, which appears to contradict previous findings. It cannot be ruled out that children conceived through FET have decreased insulin secretion from beta cells in the pancreatic islet in the early childhood phase (aged between 1.5 to 4 years). Another reason could be the study's small sample size.

Our previous animal study found that at the age of 20 weeks, mice offspring in both the IVF-chow and FET-chow groups had higher serum TG, LDL, and lower HDL levels than those in the NC-chow group, indicating dyslipidemia.[14]. The levels of plasma lipids such as cholesterol, triglycerides, HDL, and LDL were comparable between the FET and NC groups in the current study, but the level of HDL was higher in the intcat group compared to the NC group, and the level of ApoE was higher in the FET group (especially in the intact group). Apolipoprotein E (APOE), a type of lipid transport protein, is a key regulator of lipid metabolism. The higher ApoE level may indicate that children born after FET have improved lipid metabolism.

In terms of metabolomic analysis, the concentration of medium or long-chain fatty acids decreased while the concentration of SCFAs increased significantly in all three subgroups or the FET group compared to the NC group. A previous study analyzed the plasma metabolomics of 10 ICSI and 10 NC children and discovered significant differences in the distribution of 36 metabolites related to obesity and insulin resistance between the two groups. Furthermore, the concentrations of citric acid and isocitric acid increased, indicating that the level of lipid oxidative metabolism increased[43]. It suggests that ART may have an effect on the metabolic state of offspring, making them more susceptible to metabolic disorders. A large number of previous adult-based studies show that the acceleration of lipid decomposition, the entry of total free fatty acid (FFA) into the blood, and the promotion of inflammation are potential intermediate mechanisms of the interaction between obesity and insulin resistance. Adults with obesity and insulin resistance have an accumulation of total FFA, particularly saturated fatty acids (high risk factor for type 2 diabetes). It is also accompanied by extensive fatty acid oxidation defects, with the products of incomplete fatty acid oxidation accumulating in the circulation. There were no significant differences in total FFA (free fatty acids) or SFA (saturated fatty acids) concentrations between groups, according to our findings (Table S4). Obese children and adolescents, on the other hand, may have a different metabolic state than adults. A previous study looked at plasma metabolomics in 39 normal-weight, 64 obese, and 17 type 2 diabetes adolescents and discovered that the diabetes group had higher fatty acid oxidation levels than normal adolescents[44]. Unlike obese adults, who have extensive metabolic defects and fatty acid accumulation, the adolescent Obesity-MS (metabolic syndrome) population may have strong compensatory ability and adaptive plasticity, which can prevent the process of obesity by decomposing fatty acids.

Furthermore, SCFAs are primarily produced by proximal gut microbes through the fermentation of dietary fiber or carbohydrates[45], and can be absorbed into the blood via epithelial cells. Some studies have reported that intestinal SCFAs concentrations were significantly increased in obese individuals [46-48], and high levels of SCFAs may be caused by an imbalance of phyla Firmicutes and Bacteroidetes. A study based on adolescents suggested the plasma SCFA concentrations were positively related to phyla Firmicutes /Bacteroidetes, body mass index, and visceral fat [47]. A high-quality study also revealed that individuals with dysbiosis associated with high fecal SCFAs are prone to increased intestinal permeability, obesity and cardiovascular disease[49].

Obesity and metabolic syndrome (MS) are defined by abdominal obesity, hypertension, hyperglycemia, dyslipidemia, hyperinsulin or insulin resistance, and cardiovascular and metabolic disorders[50]. In the children's study, amino acids linked to the aforementioned insulin resistance, obesity, and impaired glucose tolerance included branched-chain amino acids (BCCAs), phenylalanine (aromatic amino acid), aspartic acid, arginine, histidine, sarcosine, and others, with abnormally high levels of BCCAs being potentially important risk biomarkers.[51-54]. Obesity and insulin resistance patients have been shown to have increased skeletal muscle depletion [55-57], with BCCAs prone to accumulate in the blood [57, 58]. Enhanced level of above-mentioned amio acid were observed in FET subgroups as compared to NC group, with the blastomere loss group had the most of such amio acid. FET subgroups had higher levels of the above-mentioned amio acid than the NC group, with the blastomere loss group having the highest level of such amio acid.

As a result, we hypothesized that the increased metabolism of long-chain fatty acids and the increased level of SCFAs in the FET group could be a special metabolic disorder in children at risk of obesity and metabolic disorder. Multiple analyses were only successful between the blastomere loss group and the NC group, and we discovered that transferring blastomere-loss embryos is associated with an increased risk of small for gestational age. It cannot be ignored that the offspring of the FET group (particularly the blastomere loss group) may develop a metabolic disorder with age and may have the fatty acid metabolism defect suggested in adult studies, implying a potential risk of long-term Obesity-MS.

D-xylose is a 5-carbon sugar produced by hydrolysis of hemicellulose-rich plants such as sawdust, straw, and corn cob. D-xylose can selectively promote the proliferation of beneficial bacteria such as intestinal bifidobacteria, allowing it to become the dominant bacterial community in the intestine, regulating the intestinal microecological balance and promoting intestinal health. A study found that when bifidobacteria coexist with other carbohydrate-competing gut microorganisms, xylose metabolism improves[59]. Bifidobacterium is a normal intestinal flora that can selectively metabolize D-xylose to produce a large number of SCFAs.On the contrary, Staphylococcus, Escherichia coli and many kinds of Clostridium in the intestinal cannot use D-xylose. The SCFAs produced by bifidobacteria metabolism of d-xylose are primarily lactic acid and acetic acid, which can lower the pH of the intestinal tract, inhibit the reproduction of other harmful bacteria, and significantly reduce indoles, phenols, ammonia, caderamine, and other harmful metabolites in the human body. Furthermore, D-xylose can inhibit bile acid absorption in the intestine. In the current study, SCFAs increased significantly in the FET group, possibly due to increased D-xylose metabolism, with indoles and taurolithocholic acid levels decreased in our results.

UFA (unsaturated fatty acids), as we all know, play several important physiologic roles in the body, such as inhibiting inflammation and related metabolic disorders and promoting brain development. The risk of autistic disorder associated with ICSI using frozen embryos were found to be significant in a human study[60-63].While, in our study, UFA, MUFA (monounsaturated fatty acid), PUFA (polyunsaturated fatty acid), ω-3 and ω-6, which are crucial for the neurobehavioral development of infants and children were significantly increased in FET group when compared with NC groups (TableS5).

To summarize, our research found that children conceived through FET have a different metabolite profile than children conceived naturally in early childhood. The decrease in fasting insulin level and HOMA-IR index in the FET group suggested that the glucose metabolism of FET offspring was abnormal. The increase in ApoE levels, decrease in medium and long chain fatty acids, and increase in SCFAs in the FET group all suggested improved lipid metabolism. Meanwhile, an increase in SCFAs levels and secondary bile acids in the FET group may indicate an intestinal flora disorder.

To our knowledged, we demonstrated the metabolic profile of chidren born after FET in early childhood for the first time. However, there are some limitations of our study. To begin, because of the small sample size, a larger sample size and a longer follow-up period will be required to observe the long-term metabolic profile and neurobehavioral performance of FET offspring. Second, we did not rule out other factors that could influence children's metabolism. Futher researches are needed to detect the intestinal flora and fecal metabolomics of FET offspring in order to validate some of our hypotheses.

The fasting insulin level and the HOMA-IR score, both of which are related to glycometabolism, were shown to be lower in the FET group. Increased ApoE levels and lower levels of medium and long chain fatty acids in the FET group showed aberrant lipid metabolism in infants born after FET. Increased level of ApoE and decreased level of medium and long chain fatty acids decreased in FET group indicated the abnormal lipid metabolism of children born after FET.Meanwhile, the rise in SCFAs levels and secondary bile acids in the FET group may indicate that the gut flora of infants born through FET is active.

Acknowledgements

The authors thank the children and their parents for their contribution to this study. We also thank the doctors and nurses who assisted with recruitment for this study.

Funding

The study was supported by the National Key Research and Development Program of China (2016YFC1000203), the International Cooperation Project of China and Canada NSFC (81661128010), the Shanghai Municipal Health Commission (201840210), the Shanghai Shenkang Hospital Development Center (SHDC12018X17), the National Natural Science Foundation of China (82001571), and the Clinical Research Project of Shanghai Municipal Commission of Health and Family planning (20184Y0349). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Affiliations

International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China

Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China

Key Laboratory of Reproductive Genetics (Ministry of Education), Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

Contributions

ZHD contributed to the study design, the literature search, the data analysis. TW contributed to the data analysis, creation and presentation of the published work.TNF and CZ contributed to the study design .YW, HL, and NXQ contributed to the collection of blood and manuscript revision. YYW, JJX, and HL contributed to the children recruitment and questionnaire design. WY, LJ, and YD visits. LC and LW conducted the statistical analysis. XHL, ZWL and JZS critically revised the manuscript. HFH and YTW contributed to the study design and critical discussion. HFH and YTW also analyzed and interpreted the data and contributed to the manuscript revision. All authors commented on the drafts and approved the final draft.

Corresponding author

He-Feng Huang, Yan-Ting Wu.

Ethical approval and consent to participate

This study was approved by the hospital's scientific research ethics committee ((GKLW) 2016-21), and each participating signed an informed consent form for sample and data collection.

Consent for publication

Not applicable

Conflict of interest

None of the authors has any potential conflict of interest related to this manuscript.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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Table 1. Baseline characteristics of singleton children and their family members in groups
Characteristics	FET (n=118)			NC (n=29)
Characteristics	Intact (n=83)	PGT (n=25)	Blastomere loss (n=10)	NC (n=29)
Children factors
Age at follow up (month)	34.40 (29.80-36.80) **	26.10 (22.20-29.75) ***	31.40 (22.33-33.35) **	36.80 (32.35-41.35)
Gender
Boy	40 (48.2%)	15 (60.0%)	4 (40.0%)	14 (48.3%)
Girl	43 (51.8%)	10 (40.0%)	6 (60.0%)	15 (20.3%)
BMI (kg/m²)	16.30 (15.30-17.39) *	16.00 (15.30-16.75)	15.90 (14.30-17.20)	15.40 (14.85-16.10)
Gestational week	39.00 (38.00-39.00)	38.80 (37.15-39.80)	38.00 (36.70-39.40)	39.00 (38.20-39.50)
PTB (< 37 weeks)	11 (13.3%)	3 (12.0%)	2 (20.0%)	0 (0.0%)
Birthweight (g)	3480.00 (3150.00-3800.00)	3450.00 (2882.50-3652.50)	3200.00 (2712.50-3362.50) *	3400.00 (3200.00-3625.00)
LBW (< 2500g)	6 (7.2%)	1 (4.0%)	2 (20.0%)	0 (0.0%)
Macrosomia (> 4000g)	14 (16.9%)	1 (4.0%)	1 (5.9%)	1 (3.4%)
SGA	2 (2.4%)	6 (24.0%) **	0 (0.0%)	0 (0.0%)
LGA	17 (20.5%)	2 (8.0%)	1 (10.0%)	2 (6.9%)
NICU	11（13.3%）	1（4.0%）	1（10.0%）	0(0.0%)
Breastfeeding total duration (month)	6.00 (3.00-8.00) *	9.00 (5.50-12.00)	9.00 (1.75-12.00)	8.00 (6.00-11.00)
Maternal factors
ovum age (years) ^a	32.00 (29.00-35.00)	32.00 (28.50-35.00)	32.00 (29.50-37.25)	30.00 (27.50-34.00)
Pregnant age (years)	32.00 (29.00-35.00)	33.00 (29.00-35.50)	31.50 (28.75-34.50)	30.00 (27.50-34.00)
BMI (kg/m²)	21.20 (19.70-23.60)	23.10 (22.25-24.65)	20.65 (18.65-21.63)	24.10 (21.45-26.50)
Type of delivery
Cesarean section	29 (34.94%)	6 (24.00%)	5 (50.00%)	11 (37.93%)
Vaginal	54 (65.06%)	19 (76.0%)	5 (50.0%)	18 (62.07%)
Smoking	2 (2.4%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
Passive smoking	41 (49.4%)	11 (44.0%)	7 (77.8%)	11 (37.9%)
Drinking	8 (9.6%)	5 (20.0%)	3 (11.5%)	10 (14.5%）
GDM	11 (13.30%)	6 (24.0%)	3 (30.0%)	1 (3.40%)
Prenatal factors
Sperm age ^b	33.00 (31.00-37.00)	33.00 (30.00-36.50)	33.50 (29.75-38.25)	32.00 (28.50-35.00)
BMI (kg/m²)	24.10 (22.00-26.70)	21.40 (20.05-24.35)	25.85 (23.70-28.55)	20.30 (18.40-23.75)
Smoking	32 (38.6%)	7 (28.0%)	4 (40.0%)	6 (20.7%)

Abbreviations: NC: naturally conception; FET: frozen embryo transfer; LBW: low birth weight; BMI: body mass index; LGA: large for gestational age; SGA: small for gestaional age; NICU: neonatal intensive care unit; GDM: gestational diabetes mellitus; PTB: preterm birth (gestational week < 37weeks); PGT: preimplantation genetic examination; a: the mother's age at the time of pregnancy for natural conception; the mother's age at the time of ovum collection for FET; b: the father’s age at the time of the mother's pregnancy for natural conception; the father’s age at the time of sperm collection for FET; * P < 0.05, * * P < 0.01, * * * P < 0.001, all compared to the NC group.

Table 2. Comparison of fasting blood glucose and plasma biochemical markers between FET subgroup and NC group
Characteristics	FET			NC
Characteristics	Intact	PGT	Blastomere loss	NC
Fasting blood glucose ^a	5.10 (4.80-5.40)	5.20 (4.85-5.40)	5.05 (4.73-5.23)	5.00 (4.80-5.20)
TC (mmol/L)	4.14 (3.78-4.96)	4.33 (3.75-4.72)	3.99 (3.59-4.38)	4.37 (3.81-4.81)
TG (mmol/L)	0.67 (0.56-0.80)	0.72 (0.63-0.83)	0.71 (0.51-0.89)	0.67 (0.53-0.85)
HDL (mmol/L)	1.38 ± 0.29*	1.36± 0.28	1.26 ± 0.29	1.27 ± 0.26
LDL (mmol/L)	2.24 (1.91-2.71)	2.25 (1.93-2.60)	2.28 (1.53-2.59)	2.25 (1.87-2.77)
Apo E (g/L)	261.20(152.84-363.80) *	265.75 (224.89-389.87) **	253.67 (159.15-348.76)	207.83 (142.20-235.66)
Insulin (IU/L)	3.18 (2.89-3.82) ***	4.02 (3.32-4.52)	4.14 (3.09-5.45)	4.12 (3.65-5.46)
HOMA-IR	0.74 (0.65-0.84) ***	0.86 (0.80-1.11)	0.87 (0.81-1.01)	0.93 (0.79-1.21）
Leptin (pg/ml)	253.46(127.52-346.31)	204.69 (156.51-294.86)	177.34 (116.03-185.41)	206.14 (124.26-255.88)
FT3 (pmol/L)	5.24 (4.35-6.98) *	4.65 (4.07-6.88)	4.00 (2.45-6.08)	4.39 (3.57-6.34)
FT4 (pmol/L)	15.75 (13.28-17.74)	15.35 (13.89-16.77)	15.58 (14.43-17.00)	15.72 (14.77-16.55)
TSH (mIU/L)	4.53 (3.92-5.26)	4.02 (3.32-4.52)	4.14 (3.09-5.45)	4.16 (3.22-5.18)
CRP (ng/ml)	838.28 (455.94-4356.38)	605.92 (343.16-4968.56)	651.59 (445.98-1718.70)	1190.20(613.73-3471.62)

Abbreviations:TG: triglyceride; HDL: high density lipoprotein; LDL: low density lipopretein;^* P < 0.05,^{* *} P < 0.01, ^{* * *}P < 0.001, all compared to the

NC group; ^a fasting glucose levels were measured in the original FET group (n=182) and the NC group (n=66).

No competing interests reported.

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Effect of frozen-thawed embryo transfer on metabolism of children in early childhood

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