Correlation of telomere length between full and preterm neonates and their mothers

Introduction

Human telomeres are nucleoprotein structures consisting of the repeating nucleotide sequence 5'-TTAGGG-3', along with protein complexes, that interact with the DNA. They are located at the end of eucaryotic chromosomes, and their main role is to maintain the stability of chromosomes and their protection from degradation throughout enzymatic decay (1). Telomeres have been found to be at their maximum length after birth and as cells divide over time, they gradually get shorter due to incomplete synthesis of DNA. After 40-60 cell divisions, they reach a critically short length known as Hayflick's limit, that triggers cellular senescence and apoptosis (2,3). To avoid the shortening of telomeres, human somatic cells produce the enzyme telomerase, which adds nucleotides at the 3' end of the telomeres, and thus the telomeres can maintain their length. This enzyme is active in numerous somatic tissues during fetal and early neonatal development, but its activity gradually decreases with age, resulting in inactivation in the somatic cells of adults (4).

Telomere length (TL) is a biomarker of cellular aging and genomic stability, and is influenced by genetic, environmental, and physiological factors. TL is known to be partially inherited and may reflect maternal health and stress exposures. Preterm birth has been associated with adverse intrauterine environments, including inflammation, oxidative stress, and maternal metabolic conditions, all of which may affect telomere dynamics (4). Investigating the correlation of TL between mothers and their neonates, especially comparing full-term and preterm births, may provide insight into how maternal health and gestational age influence early-life biological aging.

TL can differ significantly among individuals of the same age, and this variability is noticeable from birth. During in utero development, the fetus undergoes crucial phases of cellular growth, differentiation, and maturation, that cause modifications in telomere dynamics (5). These alterations can have far-reaching consequences for an individual's health and susceptibility to diseases throughout their life (6). Emerging research suggests that TL in neonates can also impact the development of age-related diseases. Shorter telomeres have been associated with increased risks of cardiovascular diseases, cancer, neurodegenerative disorders, and other chronic conditions (7-10). Therefore, it is highly probable that the TL of an individual as they age is significantly shaped by their TL at birth and the subsequent attrition of telomeres during early life (11).

The typical duration of a human pregnancy is usually between 37 to 42 gestational weeks, during which the developing fetus undergoes cell differentiation and organ maturation, essential for successful survival outside the womb. In this case, the TL that neonates are born with has been estimated to be 9 to 12,5 kilobases (12). When the gestation period is disrupted and childbirth occurs before 37 weeks, childbirth is characterized as premature (13). Preterm birth is a multifactorial phenomenon that, according to the WHO, ranged from 4 to 16% across countries in 2020 (https://www.who.int/news-room/fact-sheets/detail/preterm-birth). It is more prevalent among male infants, with ~55% of preterm births occurring in boys (14), and mortality rates are also higher among premature boys compared with premature girls (15). Multiple pregnancies, obesity, gestational diabetes mellitus (GDM), alcohol use during pregnancy, and smoking are main maternal factors that appear to affect preterm birth, and studies have indicated that these factors can also affect embryonic TL throughout pregnancy (16-20). Previous research has revealed that higher maternal pre-pregnancy body mass index (BMI) is associated with shorter in both mothers and their infants, indicating increased oxidative stress and accelerated cellular aging (11).

The purpose of the present study was to investigate the correlation between neonatal TL and that of their mothers, and to examine potential differences between preterm and full-term neonates. Additionally, associations between maternal characteristics, medical history, and pregnancy-related events with neonatal TL was assessed.

Materials and methods

Patients and ethics approval

The present study was conducted at the Department of Neonatology and the Neonatal Intensive Care Unit, University Hospital of Heraklion (Heraklion, Greece), and at the Laboratory of Toxicology, Medical School, University of Crete (Heraklion, Greece). Ethics approval (approval no. 112/08.09.2021) for the study was obtained from the Research Ethics Committee of the University of Crete (Heraklion, Greece). Informed consent was obtained from all participants for both their own participation and that of their newborns. All participants completed a specialized questionnaire concerning their medical history, habits during pregnancy, and anthropometric characteristics. All samples generated by the present study were anonymized, and personal data were managed according to the EU General Data Protection Regulation (GDPR; https://gdpr-info.eu/).

Blood samples were collected from 54 mothers and their neonates hospitalized at the Department of Neonatology and Neonatal Intensive Care Unit, University Hospital of Heraklion (Heraklion, Greece), from October 2022 to February 2023. Genomic DNA was extracted using the QIAamp DNA Blood Mini Kit (cat no. 51104; QIAGEN) according to the manufacturer's instructions. All the samples were measured using a photometer and the necessary dilutions were made in order to achieve a final DNA concentration of 5 ng/µl in the working solution. Subsequently, quantitative PCR was performed to determine the length of the telomeric ends. The thermocycling conditions were as follows: Initial denaturation at 95˚C for 10 min, denaturation at 95˚C for 20 sec, annealing at 52˚C for 20 sec, extension at 72˚C for 45 sec with 32 number of cycles and hold at 20˚C. The total telomere length of the target sample was calculated as follows: Reference sample telomere length x 2-ΔΔCq (21).

The 2X GoldNStart TaqGreen qPCR Master Mix (cat no. MB6018a-1; ScienCell Research Laboratories, Inc.) was a SYBR® Green dye-based qPCR master mix with a ‘hot-start’ property). The single copy reference (SCR) primer set recognizes and amplifies a 100 bp-long region on rat chromosome 17, and serves as a reference for data normalization. The kit used was the Relative Human Telomere Length Quantification qPCR Assay kit and the primers were part of the kit (cat. no. 8918; ScienCell Research Laboratories, Inc.). The telomere length was calculated based on the instructions of the kit.

Statistical analysis

Data mainly consisted of qualitative data and were expressed as counts and frequencies. Numerical variables were expressed as means and standard deviation. Pearson's χ2 was used to associate discrete (qualitative) data, while Pearson's r or Spearman's ρ coefficient was used to correlate continuous variables. Independent samples t-tests were applied to continuous variables to examine possible differences between two groups, while one-way analysis of variance (ANOVA) followed by LSD post-hoc test, was applied for differences in more than two groups. IBM SPSS Statistics 24.0 (IBM Corp.) was used for analysis, and an a=0.05 was set as the significance level.

Results

Maternal and neonatal characteristics and TL correlations

A total of 54 neonates, resulting from single pregnancies, were included in the present study. Demographic characteristics of participating mothers are presented in Table I. The mean maternal age was 33.8±6.1 years, ranging from 19 to 50 years. The mean BMI increased from from 25.9±6.0 before pregnancy to 29.9±5.8 at delivery. The medical history of the mothers is described in Table II. A total of 39 mothers (72.2%) stated that they had not experienced a miscarriage in the past, while the rest of them had at least one (27.8%). Thyroid disorders were observed in 14 (25.9%) of the examined mothers. In addition, 17 (31.5%) of the mothers developed gestational diabetes. In vitro fertilization (IVF) was performed for 27.8% of the total pregnancies. Gestational age was #x003C;37 weeks in 63.0% of all pregnancies (Table III).

Table I Demographic and somatometric characteristics of participating mothers.

Table I

Demographic and somatometric characteristics of participating mothers.

Variable	Mean	± SD	Median	Min	Max
Age (years)	33.8	6.1	33.5	19	50
Height (cm)	166.1	5.3	166.0	147	176
Weight before (kg)	71.7	17.8	67.0	47	133
Weight at delivery (kg)	82.5	16.8	78.5	58.0	128
BMI before (kg/m2)	25.9	6.0	24.2	18.1	45.6
BMI at delivery (kg/m2)	29.9	5.8	28.7	21.4	50.2

[i] BMI, body mass index.

Table II Medical history of the mothers.

Table II

Medical history of the mothers.

Maternal medical history	n	Percentage (%)
Μiscarriage	15	27.8
Thyroid disorders	14	25.9
Gestational diabetes	17	31.5
Polycystic ovaries	6	11.1
Cushing syndrome	1	1.9
Hypertension	1	1.9

Table III Pregnancy characteristics.

Table III

Pregnancy characteristics.

Pregnancy-related variables	N	Percentage (%)
IVF	15	27.8
Gestational age
Gestational weeks #x003C;37	34	63.0
Gestational weeks ≥37	20	37.0

[i] IVF, in vitro fertilization.

The mean length of newborns was 46.1±5.4 cm, ranging from 28 to 55 cm. The mean weight of the neonates was 2.520±842 g, ranging from 600 to 4,180 g, and the mean BMI of the neonates was 11.4±1.9 kg/m2, ranging from 6.7 to 14.3 kg/m2. Only 19 (35.2%) of the neonates included were females (Table IV). Notably, the maternal mean TL was estimated at 7,689±1,528 bases, while the neonate TL was in the range of 11,874±1,787 bases. A weak to moderate significant correlation was observed between maternal and neonatal TL (Spearman's ρ=0.323; P=0.017) (Fig. 1).

Figure 1 Association of maternal vs. neonatal telomere length (kilobases). TL, telomere length.

Table IV Characteristics of neonates.

Table IV

Characteristics of neonates.

At birth	Mean	Median	± SD	Min	Max
Length (cm)	46.1	47.0	5.4	28.0	55.0
Birth weight (g)	2,520	2,590	842	600	4,180
BMI (kg/m2)	11.4	11.6	1.9	6.7	14.3

[i] BMI, body mass index.

Μaternal TL was negatively correlated with BMI before pregnancy (r=-0.285; P=0.037), while a statistically significant trend was also observed with maternal BMI at delivery (r=0.251; P=0.067; 0.05#x003C;P#x003C;0.100) was observed. Similarly, a trend towards significance was found between maternal TL and weight before pregnancy (r=-0.229; P=0.096; 0.05#x003C; P#x003C;0.100). No significant correlations were observed between maternal TL and neonatal somatometrics and sex (Table V).

Table V Correlation of maternal and neonatal TL with maternal and neonatal somatometrics.

Table V

Correlation of maternal and neonatal TL with maternal and neonatal somatometrics.

	Maternal TL		Neonatal TL
Somatometrics	r	P-value	r	P-value
Mother
Age	0.126	0.364	0.083	0.550
Height (cm)	-0.077	0.582	-0.165	0.234
Weight before pregnancy (kg)	-0.229	0.096	-0.123	0.375
Weight during pregnancy (kg)	-0.179	0.178	-0.087	0.516
BMI (before pregnancy)	-0.285	0.037	-0.091	0.515
BMI (at delivery)	-0.251	0.067	-0.002	0.990
Neonate
Height (cm)	-0.053	0.709	-0.060	0.673
Weight (kg)	-0.037	0.793	-0.127	0.368
BMI (kg/m2)	0.023	0.874	-0.120	0.397
Sex	-0.088	0.525	-0.004	0.979

[i] TL, telomere length; BMI, body mass index.

Neonatal TL was not correlated with maternal age, maternal somatometric measures, neonatal somatometric measures or sex.

The effect of maternal smoking habits and diseases on neonates TL are presented in Table VI. There was no significant effect of smoking before pregnancy (P=0.892), smoking during pregnancy (P=0.724), history of miscarriage (P=0.488), type of conception (P=0.770), thyroid disorders (hyperthyroidism, P=0.153 and hypothyroidism, P=0.971), gestational diabetes (P=0.974) and gestational age at term (P=0.867) on neonatal TL. No significant differences were found between maternal TL and medical or gestational history.

Table VI Association between neonatal TL and maternal smoking habits and medical history.

Table VI

Association between neonatal TL and maternal smoking habits and medical history.

		No			Yes
Neonate TL	n	Mean	SD	n	Mean	SD	P-value
Smoking before pregnancy	37	11.896	1.723	17	11.971	2.199	0.892
Smoking during pregnancy	45	11.961	1.806	9	11.717	2.247	0.724
Miscarriages	39	12.123	1.972	15	11.698	1.603	0.488
Thyroid disorders	40	11.992	2.038	14	11.715	1.285	0.637
Hyperthyroidism	53	11.970	1.846	1	11.970	1.846	0.153
Hypothyroidism	41	11.925	2.057	13	11.903	1.119	0.971
Gestational diabetes	37	11.958	1.915	17	11.837	1.805	0.974
Full-term pregnancy (≥37 weeks)	34	11.953	1.871	20	11.864	1.900	0.867
IVF conception	38	11.954	1.978	15	11.784	1.661	0.770

[i] TL, telomere length; IVF, in vitro fertilization.

Analysis between preterm and full-term groups

This section presents the analysis of maternal and neonate TL in relation to demographics, medical history and other variables comparing preterm and full-term infants. In preterm pregnancies #x003C;37 weeks, maternal TL showed a statistically significant negative correlation with BMI before pregnancy (r=-0.403; P=0.018) and BMI after pregnancy (r=-0.349; P=0.043). A trend towards significance was observed between maternal TL and pre-pregnancy weight (r=-0.313; P=0.072). No significant associations were found between maternal TL and neonate variables (P>0.100) in preterm pregnancies. Similarly, neonatal TL did not show any significant correlations with maternal or neonatal parameters (P>0.100).

In full-term pregnancies (gestational age, ≥37), maternal TL was significantly correlated with neonatal weight after delivery (r=-0.505; P=0.039), while a trend towards significance was also observed between maternal TL with neonatal height (0.05#x003C; P#x003C;0.100). No significant correlations were found between neonatal TL and any of the measured maternal or neonatal variables in full-term pregnancies (Table VII).

Table VII Correlation of maternal and neonatal TL with maternal somatometric variables in preterm and full-term pregnancies.

Table VII

Correlation of maternal and neonatal TL with maternal somatometric variables in preterm and full-term pregnancies.

	Preterm pregnancy (#x003C;37 weeks)		Full-term pregnancy (≥37 weeks)
Variables	Maternal TL r	Neonatal TL r	Maternal TL r	Neonatal TL r
Mother
Age (year)	0.202	0.018	-0.049	0.185
Height (cm)	0.029	-0.018	-0.274	-0.408a
Weight before pregnancy (kg)	-0.313a	-0.161	-0.104	-0.156
Weight during pregnancy (kg)	-0.281	-0.120	-0.051	0.018
BMI before pregnancy (kg/m2)	-0.403b	-0.166	-0.143	-0.051
BMI after pregnancy (kg/m2)	-0.349b	-0.105	-0.164	0.149
Neonate
Height (cm)	0.133	-0.077	-0.462a	-0.116
Weight (g)	-0.048	-0.132	-0.505b	-0.308
BMI (kg/m2)	0.053	0.038	0.156	-0.374
Sex	-0.253	-0.103	0.230	0.142

[i] ^a0.05#x003C; P#x003C;0.100;

[ii] ^bP#x003C;0.05. TL, telomere length; BMI, body mass index.

In addition, no significant differences in maternal and neonatal TL were observed between preterm and full-term pregnancies based on history of miscarriage, smoking habits, thyroid disorders, mode of conception and gestational diabetes (Table VIII).

Table VIII Association of maternal and neonatal TL with smoking status, maternal medical history, and pregnancy characteristics in preterm and full-term pregnancies.

Table VIII

Association of maternal and neonatal TL with smoking status, maternal medical history, and pregnancy characteristics in preterm and full-term pregnancies.

A, Preterm pregnancy
		Maternal TL			Neonatal TL
Variables	Yes/No	Mean	± SD	P-value	Mean	± SD	P-value
Abortions	No	7.929	1.344	0.243	12.064	2.068	0.744
	Yes	7.334	1.548		11.722	1.437
Smoking before pregnancy	No	7.694	1.429	0.772	12.029	1.784	0.885
	Yes	7.826	1.458		11.795	2.125
Smoking during pregnancy	No	7.753	1.439	>0.999	11.953	2.054	0.947
	Yes	7.660	1.442		11.975	1.336
Thyroid disorders	No	7.832	1.435	0.645	11.945	2.054	0.673
	Yes	7.472	1.417		11.975	1.336
Conception	Normal	7.814	1.618	0.813	12.002	2.005	0.598
	IVF	7.791	1.457		11.824	1.791
Gestational diabetes	No	7.984	1.355	0.204	12.075	1.952	0.817
	Yes	7.282	1.476		11.730	1.774
B, Full-term pregnancy
		Maternal TL			Neonatal TL
Variables	Yes/No	Mean	± SD	P-value	Mean	± SD	P-value
Miscarriages	No	7.477	1.291	0.622	12.220	1.874	0.179
	Yes	8.230	1.180		11.033	1.846
Smoking before pregnancy	No	7.823	1.388	0.274	11.679	1.658	0.659
	Yes	7.000	941		12.296	2.501
Smoking during pregnancy	No	7.557	1.403	0.765	11.973	1.873	0.616
	Yes	7.683	623		11.247	2.359
Thyroid disorders	No	7.487	1.354	0.612	12.069	2.080	0.612
	Yes	7.842	1.245		11.247	1.170
Pregnancy	Normal	7.500	1.298	0.442	11.902	2.005	0.674
	IVF	8.263	1.623		11.525	64
Gestational diabetes	No	7.542	1.240	0.933	11.787	1.913	0.612
	Yes	7.676	1.639		12.094	2.064

[i] TL, telomere length.

Discussion

The present study highlighted a weak to moderate, positive and statistically significant correlation between maternal and neonatal TL, irrespective of full-term or preterm pregnancy. Some maternal features, particularly BMI before pregnancy, appeared to be the determinant factor in maternal TL. Additionally, grouping cases into preterm or full-term neonates influenced some of the findings; however, no statistically significant associations were observed between neonatal TL and maternal characteristics, medical history, and pregnancy details (Fig. 2).

Figure 2 Maternal and neonatal characteristics in single pregnancies: Correlations with telomere length.

The mean maternal TL in the present study fell within the reference range of 7 to 9 kilobases for women in their 30s (22), consistent with the mean maternal age in our sample. For neonates, the TL was predicted to fall within 8 to 11 kilobases (22). Most of the neonates examined were preterm and the slightly higher mean TL, supports a previous observation that preterm neonates tend to have longer telomeres than those born at term (23).

A study involving 319 mother-newborn pairs found a significant positive association between maternal and newborn TLs (β=0.31; P#x003C;0.001), indicating that maternal TL is a predictor of neonatal TL (24). Research has shown that preterm infants have significantly longer telomeres than their term-born counterparts. Specifically, TL was negatively correlated with gestational age and birth weight in preterm infants (25). In a cohort of African American women, shorter maternal peripheral blood TL was associated with an increased risk of preterm birth. Notably, for every 10-unit decrease in the telomere-to-single-copy gene (T/S) ratio, the odds of preterm birth increased by a factor of 2.664(26).

Previous studies did not directly correlate maternal BMI with the TL of neonates, in contrast to most previous studies (11,27). Indeed, prior research has identified a negative correlation between maternal BMI and neonatal TL (11). At the molecular level, elevated maternal BMI may promote oxidative stress and inflammation in the fetal environment, which could contribute to telomere shortening during prenatal development (28-30). Additionally, neonatal telomere shortening was more likely to occur in infants born to mothers with higher anxiety scores, elevated fasting blood glucose levels, lower levels of plasma insulin-like growth factor-binding protein 3 (IGFBP-3) and vitamin B12, and who actively smoke status pregnancy (27). However, there are studies which support that a high maternal pre-pregnancy BMI is associated with shorter maternal TL and TL in infants, indicating increased oxidative stress and accelerated cellular aging (31,32).

The lack of association between maternal BMI and neonatal TL contrasts with previous studies (11,27), potentially due to the BMI distribution in this cohort, which consisted primarily of normal-weight participants. Additionally, the variability in qPCR protocols, along with factors such as maternal stress, smoking, or nutrition, which can modulate TL independently of BMI, may confound results. Furthermore, limited statistical power and sample size may lack the statistical power to detect subtle associations (33,34).

Pre-pregnancy maternal BMI was not correlated with neonatal TL as expected but has been found to be related to preterm birth, and the present study aligns with this indication (P=0.017) (Fig. 1). Preterm deliveries resulting from premature labor with cervical dilation or early rupture of membranes are categorized as ‘spontaneous’, while those that are induced or carried out via cesarean section, due to maternal or fetal health concerns, are termed ‘indicated’ preterm births. In the present study, the type of preterm delivery was not provided. Most mothers who participated were categorized as οverweight (BMI between 25 and 30; mean BMI, 26) prior to pregnancy, which could also justify why a significant correlation with neonatal TL was not observed. However, the sample did include individuals from both the underweight and overweight categories, with BMIs ranging from 18.1 to 45.6. Previous studies have found that maternal overweight is more commonly associated with medically indicated preterm births, whereas maternal underweight tends to slightly increase the risk of spontaneous preterm labor (35). The exact mechanisms by which abnormal maternal BMI affects neonatal TL are not fully understood, although these effects may be linked to chronic inflammation and oxidative stress during fetal development (30). Moving forward, this research is planned to be expanded by categorizing participants into different BMI groups. Through this approach, further exploration into how maternal BMI may influence preterm deliveries is expected to be conducted, possibly revealing novel insights into its effects on fetal genotypic outcomes.

When mothers were examined separately, a moderate negative correlation between pre-pregnancy maternal BMI and maternal TL was observed (P=0.037). Previous research has examined the correlation between maternal BMI and TL. For instance, adult women with a BMI exceeding 30 kg/m2, had telomeres that were on average, 240 base pairs shorter compared with women with a BMI below 20 kg/m2, and this difference was equivalent to an aging effect of ~8.8 years (36).

Finally, no evidence of a the relationship between maternal pregnancy complications and neonatal TL was revealed in the present study. This finding appears to be consistent with recent data showing that maternal stress does not exert a significant effect on infant TL of infants as determined by qPCR analysis (37). Currently, the results of the present study appear to contradict previous findings supporting that maternal pregnancy complications can contribute to neonatal telomere shortening (5,24,38-40). The discrepancies among studies can be attributed to the small sample size in previous studies. Indeed, numerous detrimental variables (such as oxidative stress, inflammation, and other genetic/epigenetic, immunological, physiological, lifestyle, and environmental factors, including nutrition) have been shown to result in an advanced aging trajectory and exacerbate placental dysfunction, given that TL reflects the cumulative impact of stressors (41,42). In addition, several pregnancy complications, such as GDM, intrauterine growth restriction, hypertensive disorders and preeclampsia, have been demonstrated to be associated with prematurity and neonatal telomere alterations while still in utero (43,44). In the majority of studies, GDM has been associated with reduced neonatal telomeres (45-49), although some other studies have found similar TLs (43,44,50) or even longer ones in newborns compared with those from mothers without GDM (51). Cardiovascular conditions such as hypertension and preeclampsia have also been associated with shorter telomeres in previous research, although the mechanisms remain unclear (52). The small sample size in the present study limited the ability to assess how pregnancy complications and lifestyle factors (such as alcohol consumption and smoking) affect neonatal TL, and future studies with larger participant pools are required to address these gaps.

Even though a correlation between maternal and neonatal TL was identified in the present study, it has several limitations. Initially, qPCR was used to evaluate relatively average TL, although this technique has been considered more variable than the classically used terminal restriction fragment analysis (53,54). Secondly, evaluating TL in neonates represents only a snapshot of aging at birth, as limited data are available on TL in embryos during pregnancy and childhood.

Indeed, the qPCR method was used to assess maternal and neonatal TL, as only 200 µl of neonatal blood, obtained from the complete blood count, was available for analysis. The collected blood from preterm or full-term neonates was of invaluable and utmost importance since neonate samples are unique, especially that of preterm neonates. It is worth noting that the acquisition of increased blood amounts can result in the reduction of neonatal hematocrit (55). However, the present study did not detect TL differences across chromosomes at a single-cell level, which can be accomplished through metaphase Q-FISH (56,57). The Q-FISH technique can provide an overall analysis of TL distributions, providing measurements for extremely short or extremely long telomeres at the chromosome level (57). Despite this limitation, the present study provides unique insight into the average TL of maternal and full-term or preterm neonates. A limitation was also noted due to the small sample size, which affects the statistical power of sample. However, numerous studies have confirmed the reproducibility of the qPCR method in neonatal samples (58-60).

Another challenge of the study was the limited sample size. In most cases, there was also an insufficient number of participants diagnosed with some of the examined disorders within the timeframe of sample collection. Due to the shortcoming of the sample size, a general overview of neonatal TL in relation to maternal characteristics could not be provided. Therefore, future studies with a more substantial and diverse participant pool are encouraged to validate and strengthen the conclusions derived from the present research.

In conclusion, the present study revealed a weak to moderate, positive and statistically significant correlation between maternal and neonatal TL, regardless of pregnancy duration. No significant differences were observed between maternal TL and maternal habits, medical history, or gestational history. However, maternal BMI before pregnancy appears to have a decisive impact on determining maternal TL. Future studies with a larger sample size and the inclusion of additional parameters, such as socioeconomic status, maternal stress levels, and environmental exposures, are recommended to further clarify these associations.

Acknowledgements

Not applicable.

Funding

Funding: No funding was received.

Availability of data and materials

The data generated in the present study may be requested from the corresponding author.

Authors' contributions

EV, EH, AT and DAS conceived the study. EV, MT and PF acquired and interpreted the data of the study. EM, ZV, NA and FM designed the study. AA, PI, SB, AM, NIP, MTV, TL, EV and AT analyzed the data of the study and were major contributors in the writing of the manuscript. AT and AA confirm the authenticity of all the raw data. EV, EH and AT, provided final approval of the version to be published. All authors have read and agreed to the published version of the manuscript.

Ethics approval and consent to participate

Ethics approval (approval no. 112/08.09.2021) for the study was obtained from the Research Ethics Committee of the University of Crete (Heraklion, Crete). Informed consent was obtained from all participants for both their participation and that of their newborns. All participants completed a specialized questionnaire concerning their medical history, habits during pregnancy, and anthropometric characteristics. All samples generated by the present study were anonymized, and personal data were managed according to the EU General Data Protection Regulation (GDPR; https://gdpr-info.eu/).

Patient consent for publication

Not applicable.

Competing interests

DAS is the editor-in-chief for the journal, but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision, for this article. The other authors declare that they have no competing interests.

References