Influence of Maternal Obesity and Gestational Weight Gain on Maternal and Foetal Lipid Profile

Fatty acids (FAs) are fundamental for a foetus’s growth, serving as an energy source, structural constituents of cellular membranes and precursors of bioactive molecules, as well as being essential for cell signalling. Long-chain polyunsaturated FAs (LC-PUFAs) are pivotal in brain and visual development. It is of interest to investigate whether and how specific pregnancy conditions, which alter fatty acid metabolism (excessive pre-pregnancy body mass index (BMI) or gestational weight gain (GWG)), affect lipid supply to the foetus. For this purpose, we evaluated the erythrocyte FAs of mothers and offspring (cord-blood) at birth, in relation to pre-pregnancy BMI and GWG. A total of 435 mothers and their offspring (237 males, 51%) were included in the study. Distribution of linoleic acid (LA) and α-linolenic acid (ALA), and their metabolites, arachidonic acid, dihomogamma linoleic (DGLA) and ecosapentanoic acid, was significantly different in maternal and foetal erythrocytes. Pre-pregnancy BMI was significantly associated with maternal percentage of MUFAs (Coeff: −0.112; p = 0.021), LA (Coeff: −0.033; p = 0.044) and DHA (Coeff. = 0.055; p = 0.0016); inadequate GWG with DPA (Coeff: 0.637; p = 0.001); excessive GWG with docosaexahenoic acid (DHA) (Coeff. = −0.714; p = 0.004). Moreover, pre-pregnancy BMI was associated with foetus percentage of PUFAs (Coeff: −0.172; p = 0.009), omega 6 (Coeff: −0.098; p = 0.015) and DHA (Coeff: −0.0285; p = 0.036), even after adjusting for maternal lipids. Our findings show that maternal GWG affects maternal but not foetal lipid profile, differently from pre-pregnancy BMI, which influences both.


Introduction
Maternal diet influences foetus growth and is pivotal for the delivery of healthy, full-term newborns [1]. Maternal metabolism and body composition change through the pregnancy to assure Pre-pregnancy body weight was used as reference and, in case of incongruities, the patient's general practitioner was consulted. Pre-pregnancy BMI was calculated as kg/m 2 and classified according to the World Health Organization (WHO) [13]. GDM was diagnosed according to the American Diabetes Association's (ADA's) Standards of Care [14].
GWG was calculated by subtracting the pre-pregnancy weight to the weight reached at time of delivery. According to the Institute of Medicine (IOM) guidelines, we defined adequate gestational weight gain in relation to pre-pregnancy BMI (12.5-18 kg in underweight; 11.5-16.0 kg in normal weight; 7.0-11.5 kg in overweight and 5.0-9.0 kg in obesity). Otherwise, it was defined as inadequate or excessive if weight gain was below or exceeded values recommended for pre-pregnancy BMI classes, respectively.
At each trimester, women underwent a 40-minute interview with a nutritionist (GC) to estimate food consumption frequencies and received recommendations for healthy eating habits.
The following sociodemographic and anthropometric data for both the parents were collected to estimate socioeconomic status (SES); race; level of education; profession; smoking and parity.
Newborns' anthropometrics (body weight, BW; body length, BL and head circumference, HC) were evaluated at birth according to standardized procedures [15]. Standard deviation scores (SDS) for infant weight and height was calculated following the Italian INeS (Italian Neonatal Study) Chart [15].

Samples Collection
Maternal blood samples were withdrawn at fasting, 12-24 h before giving birth, during the pre-partum foetal monitoring. Cord-blood samples (2.5 mL) were collected at birth by venipuncture from the placental portion of the umbilical cord immediately after clamping.
Blood was placed in ethylenediaminetetraacetic acid (EDTA) tubes. Erythrocyte membranes were isolated within 2 h after collection: plasma was separated by centrifugation (980 rpm, 18 min); whereas erythrocytes were added with acid citrate dextrose, washed with distilled water (10:1) and centrifuged (4000 rpm, 5 min) four times. Erythrocytes were frozen immediately at´80˝C and stored until lipid extraction.

Lipid Extraction from Erythrocyte Membranes
Erythrocytes were resuspended into hexane/methanol (1:3) solution and homogenized by vortexing for 1 min. Tubes were stored at 4˝C for 5 min and then 400 µL of acetyl chloride were added, by a careful handling, and incubated at 100˝C for 1 h. After incubation, the tubes were cooled down to 4˝C for 30 min, then 3 mL of K2CO3 (12%) were added.
At the end of CO 2 production, the tubes were homogenized by manual inversion for 1 min. The mixture was then centrifuged at 3500 rpm for 5 min. The supernatant was transferred in gas-chromatography vials and the solvent was removed by using the GeneVac EZ-2 Plus evaporator (GeneVac, New York, NY, USA). The methyl-C11 (2 mg/mL) was added as internal standard.
The oven temperature programming at injection was 50˝C isothermal for 0.2 min, increased to 175˝C at 120˝C/min, then increased to 220˝C at 20˝C/min and finally to 250˝C at 50˝C/min. The carrier gas (H2) flow was maintained at 0.8 mL/min and the volume injected was 0.30 µL. The method was optimized in house according to Destillas et al. [16].
The chromatograms were integrated and identified by comparing the retention times and the peak area with those of a commercial lipid standard of 52 fatty acids (GLC 463 Nuchek; Elysian, MN, USA) and a conjugated linoleic acids mixture (UC-59M Nuchek; Elysian, MN, USA). Quantitative data were obtained by interpolation of the relative areas vs. internal standard (Methyl-C11) area. Data are shown as FAME concentration (ng/mL) or percentage (% of total FAME).

Statistical Analysis
Data are represented as number and percentage in parentheses (%) for categorical variables, or median and interquartile range (IRQ) for continuous variables. To evaluate differences and correlations between maternal and foetal fatty acid compositions, Wilkoxon Signed-Rank test was performed and Spearman correlation coefficient was calculated on concentration (ng/mL) and percentage of total FAs.
Quantile regression analyses were conducted on median percentage of total FAs to investigate the association between pre-pregnancy BMI and classes of GWG and maternal/foetal erythrocyte lipid profile. Multivariate quantile regression analyses, adjusted for maternal characteristics (GWG, pre-pregnancy BMI, smoking, age, educational level, offspring sex, gestational age, parity) were conducted on median maternal lipid profile. Multivariate quantile regressions, adjusted also for maternal lipid profile, were run on foetal lipid profile, in order to estimate the effect of these conditions on foetal erythrocyte fatty acid composition. All covariates were included in the multivariate models and the final one was determined through a backward approach.

Subjects
From the initial cohort of 1000 pregnant women enrolled, 144 (14.4%) mothers withdrew from the study (6 genetic diagnoses, 12 childbirth complications not allowing blood collection, 24 personal reasons, 7 miscarriages, and 95 deliveries in different hospitals). No difference was found in age, anthropometrics and SES of women who participated or withdrew the study (data not reported).
Data on lipid profile were missed in 396 (39.6%) pairs. A complete data set of fatty acid profile was available for 460 mother-infant pairs (46%); 449 (97.6%) Caucasians. Two (0.4%) women had T1D and 6 (1.3%) T2D at time of enrolment, while 17 (3.7%) pregnant women were diagnosed with GMD. The data of 25 (5.4%) women were not considered for the present study and a final sample of 435 mother-infant pairs was used for the analysis. Table 1 shows maternal and foetal characteristics of the sample.  Data are expressed as the median and interquartile range (IQR) 1 or as number and percentage (%) 2 ; BMI, body mass index; GWG, gestational weight gain; SDS, standard deviation score; wk, weeks. Anthropometric measures were taken at study enrolment for mothers, at birth for infants. Table 2 shows maternal and foetal FA composition of erythrocytes, expressed in percentage (% of total FAs). Concentrations are expressed in Table S1. Total saturated fatty acids (SFAs) were reported to be the most represented class, both in maternal and foetal erythrocytes. A significant difference in total SFA between mothers and newborns was detected (p < 0.0001). For example, stearic acid (18:0) was significantly higher in the foetus (p < 0.0001), while we found arachidic acid (20:0, p < 0.0001) and behenic acid (22:0, p < 0.0001) to be lower and higher in maternal than in foetal erythrocytes, respectively.

Saturated Fatty Acids
The SFA/UFA ratio appeared to be significantly higher in foetal erythrocytes (p < 0.0001).

Essential Fatty Acids (EFAs) and Long-Chain Unsaturated Fatty Acids (LC-PUFAs)
Distribution of EFAs was statistically different in maternal erythrocytes compared to cord blood (LA: p < 0.0001; ALA: p < 0.0001). AA was the most represented n-6 LC-PUFA, whereas DHA was the most present n-3 LC-PUFA, in both maternal and foetal total erythrocyte lipids. Among the n-6 LC-PUFAs, AA and DGLA were significantly higher in cord-blood erythrocytes (AA: p < 0.0001; DGLA: p < 0.0001). Among the n-3 LC-PUFAs, EPA and DPA were significantly higher in maternal erythrocytes (p < 0.0001 for both).

Pre-Pregnancy Body Mass Index (BMI) and Gestational Weight Gain (GWG)
Quantile regressions were conducted to explore the possible association between pre-pregnancy BMI or classes of GWG and the maternal/foetal erythrocyte lipid profile (expressed in percentage). Tables S2 and S3 show statistically significant results for univariate quantile regression for maternal and foetal FAs percentages, respectively.

Pre-Pregnancy Body Mass Index (BMI) and Gestational Weight Gain (GWG)
Quantile regressions were conducted to explore the possible association between pre-pregnancy BMI or classes of GWG and the maternal/foetal erythrocyte lipid profile (expressed in percentage). Tables S2 and S3 show statistically significant results for univariate quantile regression for maternal and foetal FAs percentages, respectively.

Dependent Variable Independent Variable
Coeff.

Discussion
Findings of the present study demonstrated first that pre-pregnancy BMI affects maternal and foetal erythrocyte lipid profile, while GWG seems to influence only maternal profile. Pre-pregnancy BMI was negatively associated with maternal LA and MUFAs and positively with DHA. In foetal erythrocytes, pre-pregnancy BMI was inversely associated with PUFAs, DHA and n-6 FAs. Inadequate GWG was, conversely, correlated to an increased maternal DPA while the excessive GWG WAS associated with a decreased maternal DHA, albeit with no effect on foetus lipid profile in both cases.
Maternal lipid profile likely changes during the pregnancy to adapt to the developing foetus demand [1]. By the end of full-term pregnancies (37-41 weeks), we found that the percentage of PUFAs, particularly n-3 FAs and DHA, significantly increased with the gestational age ( Table 2). The Generation R study is the largest cohort study that investigated the influence of pre-pregnancy BMI and GWG in 5636 women on maternal lipid profile, but at mid-pregnancy and on plasmatic concentration of fatty acids. Hence, our findings are only partly comparable to those of the Generation R study, which found a higher pre-pregnancy BMI associated with total SFAs and n-6 PUFAs concentrations in women's plasma and a decrease of LA [10]. In keeping with the Generation R findings [10], we observed a lower percentage of LA at the end of pregnancy in mothers whose pre-pregnancy BMI was higher. In addition, we found that pre-pregnancy BMI was positively associated with DHA percentage in mothers and negatively in foetuses. It is unlikely that the former association reflects a higher fish intake in obese mothers with respect to normal weight since most of them consumed less than three servings per week. On the contrary, it might suggest an impaired transfer of DHA from mother to foetus, which has been previously hypothesised in obese mothers [17]. Obesity, indeed, has been associated with an impaired expression of FAs carriers on the placenta membranes [18]. The clinical impact of the latter association is minimal since it means 0.03% difference in foetuses' DHA percentage per maternal pre-pregnancy BMI point. As to excessive GWG, the Generation R study found an association with plasmatic concentrations of SFAs, MUFAs and n-6 PUFAs in mothers [10].
Very few and only small-sample studies compared maternal and foetal lipid profile on erythrocyte membranes [19][20][21][22]. By comparing pairs' profiles, it seems that AA and DGLA are preferentially transferred across the placenta with respect to LA, ALA n-3 EPA and DPA [19][20][21][22]. In our cohort, the distribution of LA and ALA in maternal and cord-blood erythrocytes, compared to AA, confirms the preferential LC-PUFAs transfer to the foetus [23]. In a large proportion of mothers (55%), we observed a very low percentage of ALA but higher DHA content, supporting the notion of favoured ALA conversion to DHA at the end of pregnancy to supply the foetus's demand. DHA is essential for the foetal neurodevelopment in late pregnancy [3]. Even if foetal tissues are able to convert the precursor ALA into DHA, foetal ability is relatively low [24], hence placental transfer from the mother is the major source of DHA [25]. It has been supposed that in the case of excessive supply of DHA from the mother to the foetus, the passage of DHA through the placenta is inhibited in a process known as "bioattenuation", possibly to prevent DHA competition with AA in infant organs [8]. Conversely, whenever the maternal percentage of DHA is reduced (in our population, below 3.4% of the whole FAs content), the placental transport is favoured, resulting in higher foetal DHA (i.e., "biomagnification") [2,7]. Biomagnification might be confined to populations with low maternal DHA status [8,19]. The percentages of DHA in our sample were comparable, and even lower than the ones detected in populations with low fish consumption [20,26]. Indeed, only~6% of the women included in our sample reported eating three or more portions of fish per week, whereas 6% stated not eating fish at all. Isolating the 27 women with the highest intake of fish, the percentage of DHA rose up to a mean value of~5%. In keeping with this hypothesis by further dividing into two subsamples ( Figure S1), we found different trends in maternal and foetal percentage of DHA.
Our study, including 435 mother-infant pairs, was the largest one in the literature investigating the erythrocyte fatty acids profile of mothers and their offspring at the end of the pregnancy. Erythrocyte FAs reflect dietary intake in the last 40 days of pregnancy and provide a more accurate estimate of fat consumption than any dietary recall [27]. To our knowledge, it was also the first study exploring the association between pre-pregnancy BMI and GWG and maternal and foetal lipid profile. As a major limitation, however, we recognize the lack of information on the eventual DHA supplementation during the pregnancy.
Furthermore, due to a delay in funding, it was not possible to complete the lipid profile of all the stored samples. A complete dataset of fatty acids in both mother and newborn was available in 460 pairs. There was no difference in anthropometrics, clinical and SES characteristics of pairs whose lipid profile was available with respect to mother-newborn pairs whose profile was not analysed.
In conclusion, our results suggest the obesity status more than excessive weight gain can favour an adverse foetal lipid profile at the end of pregnancy. In the present cohort, the pre-pregnancy BMI affected the foetal lipid profile, being associated with decreased PUFAs, both n-6 and DHA, and likely owing to an impaired transfer across the placenta. Even though no association was found between maternal weight gain and foetal lipid profile, caution must be paid to maternal DHA levels and future research is needed in this regard. Further studies are also required to investigate the underlying mechanisms that regulate nutrient sensing across the placenta.
Author Contributions: G.C. wrote the paper; M.F. contributed drafting the paper and revising it for intellectual content; L.R. and M.C. analysed the data; P.V. and R.L. performed the experiments; C.V., E.P., and F.S. contributed materials and followed up the cohort; M.M. conceived and designed the study, obtained funds, analysed data and wrote the paper. All the authors revised the paper for the intellectual content.

Conflicts of Interest:
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.