Mild-iodine-deficiency based on 24-hour urinary iodine excretion leads to significant metabolic changes in pregnant women at early stages of pregnancy

Mild-iodine-deficiency based on 24-hour urinary iodine excretion leads to significant metabolic changes in pregnant women at early stages of pregnancy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mild-iodine-deficiency based on 24-hour urinary iodine excretion leads to significant metabolic changes in pregnant women at early stages of pregnancy Lijun Fan, Ye Bu, Zhiyong Liu, Sihan Wang, Shiqi Chen, Wei Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3995446/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The effects of mild iodine deficiency during the first and second trimesters on both pregnant women themselves and their offspring exhibited in consistent patterns. In this study, we aimed to address this issue by employing small molecule metabolomics. A total of 98 pregnant women in either the first or second trimester were recruited, with comprehensive data including basic information, 24-hour urine samples and blood samples collected, and subsequent evaluation of birth outcomes for their offspring. The 24-hour urinary iodine excretion (UIE) was detected and used as the dividing criterion to determine the iodine nutrition status of pregnant women. Serum metabolomics assay was performed by Ultra High Performance Liquid Chromatography Orbitrap Exploris Mass Spectrometry (UHPLC-OE-MS) platform. Differential metabolites as the potential iodine deficiency biomarkers were selected by multivariate statistical analysis methods. Association analysis was used to further analyze the relationship between the potential biomarkers and neonatal birth outcomes. As a result, there was no significant difference in maternal thyroid function indicators and neonatal outcomes between mild iodine deficiency and iodine adequate pregnant women. However, the metabolic profile of pregnant women with mild iodine deficiency was significantly disturbed compare to these with iodine adequate. A total of 28 different metabolites were screened, which could be used as the potential biomarkers of iodine deficiency. After adjusted age and pregnancy trimester, the expression of these biomarkers were also changed significantly. Furthermore, these markers were also related to fatty acid biosynthesis, tyrosine metabolism, tryptophan metabolism, arachidonic acid metabolism, and pentose and glucuronate interconversions. In addition, among these markers, 2-(4-Methyl-5-thiazolyl)ethyl octanoate was found to be associated with neonatal TSH, ACar(12:0), (9S,10E,12Z,15Z)-9-Hydroxy-10,12,15-octadecatrienoic acid showed a correlation with body length; whereas (9S,10E,12Z,15Z)-9-Hydroxy-10,12,15-octadecatrienoic acid was linked to body weight. In conclusion, mild iodine deficiency during the first and second trimesters dose not result in overt adverse effects on pregnant women and their offspring. However, at the metabolic level, mild iodine deficiency may disrupt the metabolic profile of pregnant women and impact the development of their offspring. pregnant women metabolomics offspring biomarkers Figures Figure 1 1. Background Iodine is a necessary trace element for the synthesis of thyroid hormone, which plays an vital role in normal growth, development and cell metabolism [ 1 – 2 ] . Especially, thyroid hormone is required for normal neuronal migration and myelination of the brain during fetal early postnatal life [ 3 ] . In pregnant women, maintaining an adequate iodine nutrition status during pregnancy is particularly important during the development of offspring’s brain and central nervous system. At present, the adverse effects of severe iodine deficiency on the health of pregnant women and their offspring are well demonstrated [ 4 – 5 ] . However, the effects of moderate, especially mild iodine deficiency on pregnant women and their offspring remain controversial. A few studies have shown that mild iodine deficiency in pregnant women had adverse effects on themselves and their offspring. A meta-analysis showed mild iodine deficiency was associated with the increase levels of free triiodothyronine (FT3), free thyroxine (FT4) and thyroglobulin antibody (TgAb) in pregnant women, and mild iodine deficiency might elevate the risk of thyroid dysfunction in pregnant women [ 6 ] . Dong J’s study showed that the alteration of development and maturation in cerebellar pinceau in the offspring were observed following maternal marginal and mild iodine deficiency [ 7 ] . However, some studies showed that mild iodine deficiency in pregnant women was not obvious to themselves or their offspring. Nazarpour S’s study showed that maternal urinary iodine concentration was not generally associated with the pregnancy outcomes [ 8 ] . The health effects of iodine showed an irregular, probably a U-shaped relationship, therefore, the effect of mild iodine deficiency on pregnant women needs further and multiple-dimensions studies. China has been implementing the universal salt iodization (USI) policy since 1994. To ensure effective prevention and control of iodine deficiency disorders and maintain optimal iodine nutrition in population, China initiated national surveillance for iodine deficiency disorders two to three years prior to 2016, followed by annual surveillance thereafter [ 9 ] . Recent surveillance results indicated that overall iodine nutrition among the general population in China was adequate, while pregnant women also exhibited an appropriate level [ 10 ] . However, in China, some regions still exhibited mild iodine deficiency among pregnant women. For instance, at the provincial level, there were still six to seven provinces where median urine iodine concentration (MUIC) ranged between 100 ~ 150 µg/L, along with approximately 20% of counties displaying similar values. Metabolomics, in which small-molecule metabolites are detected and evaluated, is used to identify the set of metabolites that are associated with physiological conditions or aberrant processes [ 11 – 12 ] . In recent years, many analyses have shown that metabolites during pregnancy are associated with various gestational disorders. Peng ML’ study showed metabolic disorders were exhibited in gestational diabetes mellitus and 27 metabolites were identified as the differential metabolites [ 13 ] . A metabolomics study and meta-analysis showed that prenatal exposure to β-HCH and mecarbam could decrease the offspring’s birth weight mainly by disrupting thyroid hormone metabolism and glyceraldehyde metabolism [ 14 ] . The above results showed that some diseases during pregnancy can affect the expression of small metabolites of pregnant women, and several key metabolites may be related to the birth outcome of their offspring. However, there are still few studies on the effects of iodine deficiency on the metabolomics of pregnant women. In order to investigate the impact of iodine deficiency on the metabolic profile of pregnant women during the first and second trimesters, as well as its influence on offspring outcomes, we conducted a serum metabolomics study in this population. Employing multivariate analysis methods, we aimed to identify biomarkers associated with iodine-deficiency-induced metabolic changes and examine their correlation with neonatal TSH levels, head circumference, etc. 2. Materials and Methods 2.1 Study Subjects This study recruited healthy pregnant women from June 2021 to December 2021 at the obstetrics clinic of the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China. The results of China national iodine deficiency disorders surveillance in Harbin in recent years showed that the coverage rate of iodized salt was > 95%, the consumption rate of qualified iodized salt was > 90%, the median UIC of children was between 100–300µg/L, and the median UIC of pregnant women was between 150–249µg/L. The inclusion criteria of the participants were as follows: healthy women with a spontaneous, single pregnancy who were willing to cooperate with 24-hour urine collection. The exclusion criteria included pregnant women with kidney diseases or clinical/sub-clinical thyroid dysfunction, those who had taken iodine-containing drugs or supplements, received treatment for thyroid disease (such as radiation therapy), had ultrasound-detected thyroid goiter or nodule, and those who had consumed iodine-rich foods such as seaweed and kelp for three days prior to providing the urine sample. 2.2 Sample Collection The urine voided by each participant was collected over a 24-hour period. Urine volume was accurately measured, and 5 ml of the mixture was stored at -80 ℃. Fasting venous blood was also collected from all pregnant women in the morning. After separating the serum, 300 µL aliquots of each sample were stored at -80°C until further use. 2.3 Follow-up of the Pregnant Women and Their Pregnancy Outcome The delivery outcomes of all pregnant women were monitored, encompassing the timing and mode of delivery. Additionally, comprehensive data on their offspring was collected, including gender, body length, weight, head circumference, Apaka score assessment results, as well as thyroid stimulating hormone (TSH) screening outcomes. 2.4 Iodine Measurements Urine iodine concentration and serum iodine concentration was determined by arsenic and cerium catalytic spectrophotometry recommended by WHO [ 15 ] . The levels of thyroid hormone were also measured. A chemiluminescent immunoassay was used to determine the levels of thyroid hormones, including FT3, FT4, TSH, TgAb and thyroid peroxidase antibody (TPOAb). In China, the recommended nutrient intake for iodine during pregnancy is 230 µg/d, given that the upper intake levels of iodine during pregnancy is 500 µg/d, therefore, in this study, 24-hour urine iodine excretion (UIE) < 207 µg/d was defined as insufficient iodine intake and 24-hour UIE in the range of 207 ~ 450 µg/d is defined as sufficient iodine intake [ 16 ] . 2.5 Metabolic Measurements A 2 µL aliquot of the pretreated sample was injected into a 100 mm × 2.1 mm, 1.7 µm BEH C18 column (Waters, Milford, USA) using an Acquity ultra-performance liquid chromatography system (Waters, Milford, USA). We set the column temperature to 35 ℃ and the flow rate to 0.35 mL/ min. The samples alternated between different iodine nutritional status group. The mobile phase consisted of two solutions, A (water with 0.1% formic acid) and B (acetonitrile), and was eluted in the following proportions. Positive mode involved 2%~20% acetonitrile for 0 ~ 1.5 min, 20% ~ 70% for 1.5 ~ 6 min, and 70% ~ 98% for 6 ~ 10 min; the concentration was then held at 98% for 2 min, returned to 2% for 12% ~ 14 min and finally held at 2% for 14% ~ 16 min. Negative mode involved 2% ~ 30% acetonitrile for 0 ~ 2.0 min, 30% ~ 70% for 2 ~ 3 min, 70% ~ 75% for 3 ~ 7.5 min, and 75% ~ 98% for 7.5 ~ 10.5 min; the concentration was then held at 98% for 1.5 min, returned to 2% for 12 ~ 14 min and finally held at 2% for 14 ~ 16 min. ESI-TOF-MS detection was operated in positive or negative ion mode with the following settings: capillary voltage, 3000 V (positive) or 2800 V (negative); sample cone voltage, 35 V; desolvation gas flow, 600 L/h; desolvation temperature, 320 ℃; extraction cone voltage, 3.0 V; cone gas flow, 15 L/h; source temperature, 110 ℃; collision energy, 6 eV; and scan range, m/z 50 ~ 1000. All analyses were acquired with a locking spray to ensure accuracy and reproducibility. Leucine enkephalin was used for both positive ESI mode ([M + H] + = 556.2771) and negative ESI mode ([M − H] − = 554.2615). 2.6 Data process of metabolomics and identification of metabolites The raw data were transformed and then imported into the R package xcms for preprocessing. A matrix containing the peaks with retention times, m/z values, and corresponding peak areas are listed. Fragmentation patterns of selected metabolites and their structural information were obtained from MS/MS experiments performed. Metabolite identification was conducted based on the retention behavior, mass assignments, MS/MS product ion patterns, nline database queries, and confirmation with standards. The mass tolerance between the measured M/Z values and the exact mass of the components of interest was set to within 30 ppm. The MS/MS product ion spectra of selected metabolites were matched to metabolite structural information (with the same M/Z) obtained from the HMDB ( www.hmdb.ca ), SMPDB ( http://smpdb.ca/ ), METLIN ( http://metlin.scripps.edu/ ) and KEGG ( http://www.genome.jp/kegg/ ) databases. 2.7 Statistical analyses After preprocessing, the data were imported to SIMCA-P 14.1 software (Umetrics, Umea, Sweden). Then, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to reveal the global metabolic changes, and the corresponding variable importance in projection (VIP) values were also calculated in the PLS-DA model. A validation plot was used to assess the validity of the PLS-DA model by comparing the goodness of fit ( R 2 and Q 2 ) of the PLS-DA models with 100Y-permutated models. R 2 is a measure of fit, i.e., how well the model fits the data. Q 2 indicates how well the model predicts new data. In addition, a two-sided Cochran and Cox test was performed to determine the significance of each metabolite. A differential metabolite was selected when the VIP value was greater than 1.2 and the P value was less than 0.05. Statistical analysis was performed on the R platform, with the exception of PCA and PLS-DA, which were performed on SIMCA-P. Pearson’s and Spearman’s correlations were used for correlation analysis. Independent sample t-tests were used to compare differences in age, FT3, FT4, and TSH between iodine deficiency pregnant women and iodine adequate pregnant women. A chi-square test or two-sided Fisher’s exact test was used to compare differences in delivery mode, gender of offspring between the two groups. Wilcoxon rank-sum test was used to compare the difference in median urine iodine concentration (MUIC) between the two groups. Multiple linear regression was used to analyze the relationship between iodine status and the expression of metabolites in different iodine nutrition regions after considering other confounders, such as age and gestational weeks. 3. Results 3.1 Baseline of the pregnant women and their iodine nutritional status The baseline characteristics of the pregnant women and their offspring were presented in Table 1 . Table 1 Baselines of the studied pregnant women and their offspring Population Indicator 24h UIE < 207 µg 24h UIE ≥ 207 µg Statistics P value Pregnant women Age (year) 30.16 ± 3.96 30.10 ± 3.55 -0.08 0.9346 Height (m) 1.63 ± 0.05 1.63 ± 0.06 0.07 0.9423 Weight before pregnant (kg) 59.47 ± 9.89 58.45 ± 9.97 -0.47 0.6368 BMI before pregnant 22.33 ± 3.67 21.96 ± 3.87 -0.46 0.6488 TSH (mU/L) 1.58 ± 0.86 1.65 (0.91 ~ 2.14) 1.90 ± 1.25 1.88 (0.92 ~ 2.30) 1.33 0.92 0.1867 0.3379 FT3 ((pmol/L)) 5.48 ± 2.54 5.05 (4.66 ~ 5.88) 4.98 ± 0.61 4.86 (4.43 ~ 5.46) -1.03 0.69 0.3122 0.4048 FT4 (pmol/L) 17.92 ± 8.15 16.57 (15.26 ~ 18.13) 15.61 ± 2.31 15.52 (13.85 ~ 17.82) -1.47 3.17 0.1531 0.0748 Tg (µg/L) 9.79 (5.54 ~ 20.78) 9.58 (5.53 ~ 13.93) 0.05 0.8236 TgAb 15.75 (14.68 ~ 18.13) 15.62 (14.14 ~ 16.92) 0.52 0.4693 TPOAb 10.74 (8.12 ~ 13.73) 10.08 (8.26 ~ 13.19) 0.01 0.9299 Trimester (stage I/stage II) 14/18 21/45 1.33 0.2477 Delivery pregnancy week (week) 39.20 ± 0.98 39.06 ± 1.41 -0.40 0.6892 Delivery mode (1/2) 9/12 20/17 0.67 0.4124 24h UIE (µg) 162.09 (135.43 ~ 186.29) 312.25 (273.76 ~ 387.54) 64.00 < 0.0001 Offspring TSH (mU/L) 3.92 ± 2.61 3.14 ± 1.61 -1.24 0.2231 Length (cm) 50.19 ± 0.75 49.89 ± 1.51 -1.01 0.3185 Weight (kg) 3.39 ± 0.37 3.41 ± 0.37 0.10 0.9181 Head circumference (cm) 34.49 ± 0.95 34.42 ± 1.07 -0.26 0.7939 The median 24-hour UIE levels in the iodine deficiency group and the iodine adequate group were 166.19 µg (144.84 ~ 195.03 µg) and 317.22 µg (279.68 ~ 404.75 µg), respectively, exhibiting a significant statistical difference ( P < 0.0001). No statistically significant differences were observed between the two groups in terms of age, height, pre-pregnancy weight, pre-pregnancy BMI, thyroid function indicators (including TSH levels, FT3 levels, FT4 levels, abnormal rates of TgAb and TPOAb), or thyroglobulin (Tg) levels. Additionally, there were no statistical differences in gestational age or delivery mode between the two groups. There were no statistically significant differences in body length, weight, and head circumference between the iodine deficiency group (50.19 cm, 3.39 kg, 34.49 cm and 39.17 cm) and the iodine adequate group (49.89 cm, 3.41 kg and 34.42 cm). Although neonatal TSH levels were slightly higher in the iodine deficiency group than in the iodine adequate group, this difference was not statistically significant. 3.2 Metabolic profiles of iodine deficiency and iodine adequate pregnant women The average relative abundance values were slightly higher in the iodine adequate group than in the deficiency group. A total of 5384 and 2454 potential metabolites were determined in the chromatographic analysis in the positive and the negative mode, respectively. As shown in Fig. 1 A and 1 B, the PCA metabolic profiling score plots exhibited distinct differences between the iodine deficiency group and the adequate group in both positive and negative modes. Additionally, the PLS-DA score plots revealed a clear segregation among different iodine nutritional groups in different trimesters (Fig. 1 C and 1 D). R 2 Y of the PLS-DA model was 0.795 and Q 2 of the PLS-DA model was 0.288 (with two principal components) in the positive mode, and the two values were 0.839 and 0.348 (with three principal components) in the negative mode. These parameters indicated that the two models were stable and highly predictive. The permutation validation of the PLS-DA models showed that the random experimental R 2 and Q 2 on the left were lower than the original values on the right, which indicated that the models were valid (Fig. 1 E and 1 F). 3.3 Identification of metabolic biomarkers According to the previous criteria for biomarker discovery and identification, a total of 28 metabolites (19 in positive mode and 9 in negative mode) were selected as potential biomarkers for classifying pregnant women with iodine deficiency and those with adequate iodine levels (Table 2 ). Table 2 Identified differential metabolites between iodine deficiency and iodine adequate in I and II stage pregnant women in the positive and negative ion modes Num Mode Metabolites VIP P value 1 ESI+ 24-Hydroxyglabrolide 1.59 0.0363 2 ESI+ Alpha-dimorphecolic acid 1.51 0.0408 3 ESI+ 2-(4-Methyl-5-thiazolyl)ethyl octanoate 1.38 0.0146 4 ESI+ ACar(6:0) 1.38 0.0239 5 ESI+ Thyroxine 1.36 0.0281 6 ESI+ ACar(10:1) 1.35 0.0179 7 ESI+ 5-Heptyltetrahydro-2-oxo-3-furancarboxylic acid 1.31 0.0540 8 ESI+ 2-Deoxybrassinolide 1.31 0.0166 9 ESI+ Diisobutyl phthalate 1.28 0.0277 10 ESI+ ACar(12:0) 1.28 0.0282 11 ESI+ ACar(8:0) 1.26 0.0352 12 ESI+ ACar(10:0) 1.24 0.0279 13 ESI+ ACar(14:0) 1.21 0.0461 14 ESI+ 2,3-Diethylpyrazine 1.16 0.0246 15 ESI+ DG(15:0/18:4(6Z,9Z,12Z,15Z)/0:0) 1.13 0.0276 16 ESI+ ACar(12:1) 1.11 0.0343 17 ESI+ Indoleacetaldehyde 1.10 0.0315 18 ESI+ Trigonelline 1.10 0.0352 19 ESI+ 1-Acetoxy-4,6-tetradecadiene-8,10,12-triyne 1.00 0.0112 20 ESI- D-Xylulose 1.96 0.0430 21 ESI- Thyroxine 1.70 0.0227 22 ESI- Butylparaben 1.52 0.0050 23 ESI- 9-Decenoic acid 1.38 0.0279 24 ESI- cis,cis-Muconic acid 1.38 0.0006 25 ESI- 5-Hydroperoxyeicosatetraenoic acid 1.33 0.0300 26 ESI- 4-Hydroxybenzaldehyde 1.12 0.0090 27 ESI- FA(22:1) 1.04 0.0484 28 ESI- 13,14-Dihydro-15-keto PGF2a 1.03 0.0409 The confounders were assessed, and logistic and linear regression models were used to verify the independent influence of iodine status on differential metabolites. In the logistic model, the results demonstrated that iodine deficiency status remained associated with the expression of 23 metabolites even after controlling for age and trimester. Similarly, in the linear regression model, iodine deficiency still showed an effect on the expression of 25 metabolites (Table 3 ). Table 3 with deficient iodine status even after adjusting for the confounding factor, including age and trimester Metabolite Logistics regression Liner regression P adjusted P for age* P for trimester* P UIE P age P trimester 24-Hydroxyglabrolide 0.0160 0.9100 0.0670 0.0064 0.119 0.0005 Alpha-dimorphecolic acid 0.0270 0.7683 0.0699 0.0068 < .0001 0.0001 2-(4-Methyl-5-thiazolyl)ethyl octanoate 0.0434 0.6616 0.1628 0.0152 0.9514 0.0193 ACar(6:0) 0.0057 0.3856 0.4427 0.0045 0.0883 0.1231 Thyroxine 0.0121 0.7106 0.3036 0.0059 0.8413 0.9340 ACar(10:1) 0.0055 0.3518 0.4161 0.0037 0.1035 0.1312 5-Heptyltetrahydro-2-oxo-3-furancarboxylic acid 0.0091 0.4718 0.4480 0.0113 0.1473 0.2517 2-Deoxybrassinolide 0.0276 0.9130 0.1726 0.0717 0.3948 0.4111 Diisobutyl phthalate 0.0037 0.2935 0.3751 0.0038 0.056 0.2625 ACar(12:0) 0.0160 0.3774 0.3144 0.0119 0.0462 0.0448 ACar(8:0) 0.0022 0.3645 0.3791 0.0050 0.1338 0.3184 ACar(10:0) 0.0035 0.2669 0.3382 0.0041 0.0621 0.2644 ACar(14:0) 0.0320 0.5193 0.2413 0.0427 0.2219 0.1017 2,3-Diethylpyrazine 0.0713 0.6146 0.2474 0.6384 0.882 0.4317 DG(15:0/18:4(6Z,9Z,12Z,15Z)/0:0) 0.0487 0.9191 0.1358 0.0228 0.0249 0.0200 ACar(12:1) 0.0206 0.4849 0.2563 0.0233 0.2484 0.0478 Indoleacetaldehyde 0.0539 0.6852 0.2473 0.0495 0.704 0.9545 Trigonelline 0.0712 0.5598 0.3149 0.0882 0.2834 0.1590 1-Acetoxy-4,6-tetradecadiene-8,10,12-triyne 0.0503 0.6264 0.2302 0.0414 0.9271 0.8538 D-Xylulose 0.0476 0.6494 0.8245 0.0283 0.3531 0.2415 Thyroxine 0.0241 0.9136 0.9436 0.0180 0.4962 0.7550 Butylparaben 0.0077 0.7721 0.7577 0.0043 0.2494 0.0597 9-Decenoic acid 0.0162 0.9425 0.8929 0.0164 0.1812 0.1706 cis,cis-Muconic acid 0.0012 0.6216 0.8094 0.0002 0.4769 0.0879 5-Hydroperoxyeicosatetraenoic acid 0.0398 0.7739 0.5355 0.0321 0.5496 0.2107 4-Hydroxybenzaldehyde 0.0089 0.8854 0.8135 0.0048 0.7899 0.4267 FA(22:1) 0.0526 0.8918 0.9331 0.0411 0.9184 0.3941 13,14-Dihydro-15-keto PGF2a 0.0359 0.6051 0.4704 0.0363 0.1049 0.3364 Note: P adjusted , the P value for the expression of metabolite on UIE in the logistic model after adjusted for age and gestational weeks; P for age * , the P value for age on UIE in the logistic model; P for trimester * , the P value for trimester on UIE in the logistic model; P UIE , the P value for UIE on the expression of metabolites in the regression model; P age , the P value for age on the expression of metabolites in the regression model; P trimester , the P value for trimester on the expression of metabolites in the regression model. 3.4 Metabolic pathway analysis In order to identify the relevant involved pathways, the differential metabolites were submitted to MetaboAnalyst 4.0 to determine the disturbed pathways. Five pathways, including fatty acid biosynthesis, tyrosine metabolism, tryptophan metabolism, arachidonic acid metabolism, and pentose and glucuronate interconversions were related to iodine deficiency in pregnant women. 3.5 Correlation analysis of potential biomarkers with thyroid function and serum iodine levels in pregnant women We conducted an analysis on the association between metabolic biomarkers and thyroid function in pregnant women. The results showed a negative correlation between 3,5-tetradecadiencarnitine and oxidized glutathione with FT3 ( r = − 0.405, P = 0.045; r = − 0.527, P = 0.007), as well as a negative correlation with FT4 ( r = − 0.418, P = 0.038; r = − 0.465, P = 0.019). Additionally, L-octanoylcarnitine exhibited a positive correlation with TG level ( r = 0.575, P = 0.005). 3.6 Correlation analysis of potential biomarkers for iodine deficiency in the offspring's characteristics. We further investigated the association between maternal potential metabolic markers and their offspring's TSH, body weight and length. The results revealed that newborn TSH levels were negatively correlated with 2-(4-Methyl-5-thiazolyl) ethyl octanoate ( r = -0.273, P = 0.0420). Additionally, body length was positively associated with ACar (12:0) ( r = 0.2839, P = 0.0308), while both body weight and length showed negative correlations with (9S,10E,12Z,15Z)-9- Hydroxy − 10,12,15-octadecatrienoic acid ( r = -0.293, P = 0.0255; r = -0.296, P = 0.0242). 4. Discussion In this study, the metabolic profiles of pregnant women in the first or second trimester with iodine deficiency significantly differed from those of pregnant women with adequate iodine nutrition. A total of 28 distinct metabolites were identified as potential markers for iodine deficiency in pregnant women. The impact of iodine deficiency on metabolic pathways and functions was discussed, providing valuable insights for the prevention and treatment strategies targeting iodine deficiency in pregnancy. At the population level, iodine status is typically evaluated by the MUIC from spot urine samples [ 15 ] . However, at an individual level, spot urine iodine levels may not accurately reflect iodine status due to significant day-to-day and within-day variations in urine iodine concentrations [ 17 – 18 ] . Currently, 24-hour UIE is considered a quasi-reference standard for assessing individual-level iodine status because it reduces hydration-dependent variations in iodine excretion [ 16 ] . Nevertheless, collecting 24-hour urine samples can be challenging due to its elaborate procedure and potential lower compliance rates that could compromise data quality particularly in field studies. In this study, the excretion Angle was employed in this study to assess the dietary iodine intake of pregnant women, which provided a relatively scientific and accurate approach for individual iodine nutrition evaluation during pregnancy. Studies investigating the impact of mild iodine deficiency during the first and second trimesters on offspring development have yielded inconsistent results, which can be attributed to numerous confounding factors or the relatively weak effect of mild iodine deficiency that might be overshadowed by other influential factors [ 19 – 21 ] . In our current study, no significant differences were observed in maternal thyroid function and birth outcomes between pregnant women with low UIE levels and those with normal UIE levels. Therefore, it can be concluded that the effects of mild iodine deficiency on both maternal thyroid function and offspring birth outcomes do not exhibit prominent manifestations in major phenotypes. However, a comprehensive analysis of small molecular metabolites present in pregnant women's blood samples revealed significant distinctions in metabolic profiles between individuals with iodine deficiency and sufficient nutrition, indicating underlying changes at a molecular level despite minimal discernible phenotypic differences. In the current study, the expression of indoleacetaldehyde was significantly changed. Indoleacetaldehyde plays a pivotal role in the metabolic pathway of tryptophan. Empirical evidence suggests that tryptophan metabolism is implicated in the pathogenesis of depression and hyperactivity in pediatric populations [ 22 – 23 ] . During pregnancy, the metabolism of tryptophan also plays a pivotal role [ 24 ] . Zhao YJ’s study shown that tryptophan related metabolites were important in regulating endothelial function during pregnancy [ 25 ] . Lee’s study observed that higher plasma tryptophan concentrations were associated with a lower prevalence of poor sleep quality during pregnancy [ 26 ] . Ünüvar S’s study showed thyroid disorders may lead to changes in tryptophan degradation, neopterin production and catalase enzyme activities [ 27 ] . In our study, alterations in tryptophan metabolism were observed in pregnant women with iodine deficiency, suggesting a potential association between iodine deficiency and its impact on thyroid function, subsequently affecting tryptophan metabolism. In addition, alterations were observed in the metabolism of arachidonic acid. Arachidonic acid plays a crucial role in fetal growth and development, particularly in the development and functioning of the fetal brain and retina [ 28 ] . Ghebremeskel’s study demonstrated reduced levels of arachidonic acid both in maternal serum and newborns born to diabetic mothers [ 29 ] . It is likely that lower level of arachidonic acid in the babies of diabetic mothers were reflection of the impair in placental transfer. In our study, arachidonic acid levels were also decreased in iodine deficient pregnant women, which was consistent with the trend of arachidonic acid changes in diabetic pregnant women. The expression of many lipid-related substances changed in this study. Fatty acid metabolism have been found to affect on the proinflammatory properties and the aggregation of platelets [ 30 – 31 ] . A growing body of evidence suggests that essential fatty acids and their active metabolic byproducts play a crucial role in maintaining the structural and functional integrity of both the central nervous system. These metabolites may contribute to proper development of the nervous system while reducing the likelihood of preterm birth or low birth weight. Additionally, it is believed that several fatty acid could potentially enhance children's learning abilities and academic performance. The majority of brain growth occurs during fetal life, making this period particularly important for adequate nutrient intake [ 32 – 33 ] . The present study unveiled alterations in the fatty acid pathway among pregnant women in the iodine deficient group, indicating that iodine deficiency may potentially impact fetal neurointelligence development by disrupting fatty acid metabolism. The findings in this study presented alterations in the tyrosine metabolism pathway. Iodine serves as an indispensable substrate for thyroid hormone synthesis, and thyroid hormone is intricately associated with tyrosine metabolism. The constituents required for synthesizing thyroid hormone encompass iodine and thyroglobulin, wherein thyroglobulin undergoes iodination at the tyrosine residue to produce thyroid hormone. Thus, iodine deficiency leads to changes in tyrosine metabolism. Due to the limited availability of comprehensive epidemiological survey data, the precise impact of pentose and glucuronate interconversions during pregnancy remains uncertain. However, it is important to note that purine metabolism disorders often coexist with glucose and lipid metabolism disorders as integral components of metabolic syndrome [ 34 – 35 ] . There are certain limitations in this study. Firstly, due to the relatively short recruitment period and other factors, the sample size was comparatively small. Secondly, only a single measurement of 24-hour UIE was utilized instead of multiple collections over a 24-hour period. Thirdly, further validation on a larger external scale is required for the biomarkers used, and additional exploration is necessary to understand their biological roles. In conclusion, although mild iodine deficiency during the first and second trimesters may not lead to overt adverse effects on pregnant women and their offspring, however, at the metabolic level, it could disrupt the metabolic profile of pregnant women and impact fetal development. Declarations Author Contributions All authors revised the report and approved the final version before submission. Funding Statements This work was supported by the Natural Science Foundation of China (NSFC 82173638 and NSFC 81830098), the Natural Science Foundation of Heilongjiang Province (YQ2022H005) and the Special Funds from the Central Finance to Support the Development of Local Universities. Ethics approval and consent to participate The Ethics Committee of Harbin Medical University provided approval for this study (HRBMUCEDC20211002). It was conducted according to the provisions of the Declaration of Helsinki. Written informed consent was obtained from all participants or their guardians. Consent for publication It was not applicable for our study. Author Disclosure Statement All the authors have declared that no competing financial interest exists. References Melse-Boonstra A, Jaiswal N. Iodine deficiency in pregnancy, infancy and childhood and its consequences for brain development[J]. Best Pract Res Clin Endocrinol Metab. 2010;24(1):29–38. 10.1016/j.beem.2009.09.002 . Zimmermann MB. Iodine deficiency[J]. Endocr Rev. 2009;30(4):376–408. 10.1210/er.2009-0011 . Ghassabian A, Henrichs J, Tiemeier H. Impact of mild thyroid hormone deficiency in pregnancy on cognitive function in children: lessons from the Generation R Study[J]. Best Pract Res Clin Endocrinol Metab. 2014;28(2):221–32. 10.1016/j.beem.2013.04.008 . Zimmermann MB. Iodine deficiency in pregnancy and the effects of maternal iodine supplementation on the offspring: a review[J]. Am J Clin Nutr. 2009;89(2):S668–72. 10.3945/ajcn.2008.26811C . Zimmermann MB. The adverse effects of mild-to-moderate iodine deficiency during pregnancy and childhood: a review[J]. Thyroid. 2007;17(9):829–35. 10.1089/thy.2007.0108 . Wan S, Jin B, Ren B, et al. Relationship between mild iodine deficiency in pregnant women and thyroid function: A meta-analysis[J]. J Trace Elem Med Biol. 2023;78:127197. 10.1016/j.jtemb.2023.127197 . Dong J, Song H, Wang Y, et al. Maternal Different Degrees of Iodine Deficiency during Pregnant and Lactation Impair the Development of Cerebellar Pinceau in Offspring[J]. Front Neurosci. 2017;11:298. 10.3389/fnins.2017.00298 . Nazarpour S, Ramezani Tehrani F, Behboudi-Gandevani S, et al. Maternal Urinary Iodine Concentration and Pregnancy Outcomes in Euthyroid Pregnant Women: a Systematic Review and Meta-analysis[J]. Biol Trace Elem Res. 2020;197(2):411–20. 10.1007/s12011-019-02020-x . Sun D, Codling K, Chang S, et al. Eliminating Iodine Deficiency in China: Achievements, Challenges and Global Implications[J]. 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Mulder TA, Korevaar T, Peeters RP, et al. Urinary Iodine Concentrations in Pregnant Women and Offspring Brain Morphology[J]. Thyroid. 2021;31(6):964–72. 10.1089/thy.2020.0582 . Zimmermann MB, Nutrition. Are mild maternal iodine deficiency and child IQ linked?[J]. Nat Rev Endocrinol. 2013;9(9):505–6. 10.1038/nrendo.2013.128 . Prado EL, Dewey KG. Nutrition and brain development in early life[J]. Nutr Rev. 2014;72(4):267–84. 10.1111/nure.12102 . Davidson M, Rashidi N, Nurgali K, et al. The Role of Tryptophan Metabolites in Neuropsychiatric Disorders[J]. Int J Mol Sci. 2022;23(17):9968. 10.3390/ijms23179968 . Correia AS, Vale N. Tryptophan Metabolism in Depression: A Narrative Review with a Focus on Serotonin and Kynurenine Pathways[J]. Int J Mol Sci. 2022;23(15):8493. 10.3390/ijms23158493 . Badawy AA. Tryptophan metabolism, disposition and utilization in pregnancy[J]. Biosci Rep. 2015;35(5):e00261. 10.1042/BSR20150197 . Zhao YJ, Zhou C, Wei YY, et al. Differential Distribution of Tryptophan-Metabolites in Fetal and Maternal Circulations During Normotensive and Preeclamptic Pregnancies[J]. Reprod Sci. 2022;29(4):1278–86. 10.1007/s43032-021-00759-0 . van Lee L, Cai S, Loy SL, et al. Relation of plasma tryptophan concentrations during pregnancy to maternal sleep and mental well-being: The GUSTO cohort[J]. J Affect Disord. 2018;225:523–9. 10.1016/j.jad.2017.08.069 . Ünüvar S, Girgin G, Şahin TT, et al. Tryptophan Degradation and Antioxidant Status in Patients With Thyroid Disorders[J]. Arch Iran Med. 2018;21(9):399–405. Uauy R, Peirano P, Hoffman D, et al. Role of essential fatty acids in the function of the developing nervous system[J]. Lipids. 1996;31 SupplS167–176. 10.1007/BF02637071 . Ghebremeskel K, Thomas B, Lowy C, et al. Type 1 diabetes compromises plasma arachidonic and docosahexaenoic acids in newborn babies[J]. Lipids. 2004;39(4):335–42. 10.1007/s11745-004-1237-z . Crawford MA, Sinclair AJ, Hall B, et al. The imperative of arachidonic acid in early human development[J]. Prog Lipid Res. 2023;91:101222. 10.1016/j.plipres.2023.101222 . Saini RK, Keum YS. Omega-3 and omega-6 polyunsaturated fatty acids: Dietary sources, metabolism, and significance - A review[J]. Life Sci. 2018;203:255–67. 10.1016/j.lfs.2018.04.049 . Schwarzenberg SJ, Georgieff MK. Advocacy for Improving Nutrition in the First 1000 Days to Support Childhood Development and Adult Health[J]. Pediatrics. 2018;141(2):e20173716. 10.1542/peds.2017-3716 . [pii]. Hammoud R, Pannia E, Kubant R, et al. Choline and Folic Acid in Diets Consumed during Pregnancy Interact to Program Food Intake and Metabolic Regulation of Male Wistar Rat Offspring[J]. J Nutr. 2021;151(4):857–65. 10.1093/jn/nxaa419 . Lima WG, Martins-Santos ME, Chaves VE. Uric acid as a modulator of glucose and lipid metabolism[J]. Biochimie. 2015;116:17–23. 10.1016/j.biochi.2015.06.025 . Yan S, Wang D, Teng M, et al. Perinatal exposure to low-dose decabromodiphenyl ethane increased the risk of obesity in male mice offspring[J]. Environ Pollut. 2018;243(Pt A):553–62. 10.1016/j.envpol.2018.08.082 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3995446","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278552431,"identity":"88d52aed-e843-427a-be78-9e026ec630c8","order_by":0,"name":"Lijun Fan","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lijun","middleName":"","lastName":"Fan","suffix":""},{"id":278552432,"identity":"b39b6da6-aa63-44ad-96bc-0a157a998c5f","order_by":1,"name":"Ye Bu","email":"","orcid":"","institution":"The Fourth Affiliation Hospital, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ye","middleName":"","lastName":"Bu","suffix":""},{"id":278552433,"identity":"b2e62425-ec46-4962-a989-5004d35875a0","order_by":2,"name":"Zhiyong Liu","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"Liu","suffix":""},{"id":278552434,"identity":"e8d58c9d-0364-45a6-9d5c-5af59113411f","order_by":3,"name":"Sihan Wang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sihan","middleName":"","lastName":"Wang","suffix":""},{"id":278552435,"identity":"ecbe21b0-8912-447b-b819-4da0500cc8a6","order_by":4,"name":"Shiqi Chen","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shiqi","middleName":"","lastName":"Chen","suffix":""},{"id":278552436,"identity":"607cf553-460d-4aa5-bc07-70b294e7ee79","order_by":5,"name":"Wei Zhang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":278552438,"identity":"52c3dfee-9116-45c4-a255-8ab60a5d0e3a","order_by":6,"name":"Yan He","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"He","suffix":""},{"id":278552441,"identity":"31717700-4655-4001-a275-6fd44c2cc360","order_by":7,"name":"Yashu Zhang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yashu","middleName":"","lastName":"Zhang","suffix":""},{"id":278552442,"identity":"6058ca6e-34c8-4254-a4e8-3a56fa6e8f93","order_by":8,"name":"Dianjun Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBACAwYeEMXMzM/MfPgBaVok29nSDEjSwmBwnkdBgigt5tJnj27m+WPNbnyYB6i/xiaaoBbLvry027xt6cxmh3kPPGA4lpbbQNBhZ3jMbvM2HAZq4UswYGw4TKQWnj+HmY2beQwkSNDCdpjZgJl4LXxpN+cC/SJxGBjICcT5hffYjTd/rJP5+w8ffvChxoawFhhIBpMJxCoHATtSFI+CUTAKRsEIAwAOfjrfA+/pKgAAAABJRU5ErkJggg==","orcid":"","institution":"Chinese Center for Disease Control and Prevention, Harbin Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Dianjun","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2024-02-28 03:00:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3995446/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3995446/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52709795,"identity":"1921ae4e-4921-471d-9389-32dfcdd102d5","added_by":"auto","created_at":"2024-03-14 19:48:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43689,"visible":true,"origin":"","legend":"\u003cp\u003ePartial least-squares discriminate analysis (PLS-DA) score plot based on HPLC-QTOF-MS metabolomics. (A) iodine deficiency group vs. iodine adequate group in positive mode (2 principal components, R2Y = 0.81, Q2 = 0.54); (B) iodine deficiency group vs. iodine adequate group in negative mode (3 principal components, R2Y = 0.86, Q2 = 0.54). (C) Plot of R2 and Q2 from 100 permutation tests in partial least squares discriminant analysis models for the positive mode; (D) Plot of R2 and Q2 from 100 permutation tests in partial least squares discriminant analysis models for the negative mode.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3995446/v1/8de65d4e980126142218fb65.png"},{"id":56032295,"identity":"20ca5209-0d26-4930-b4c4-5a819505bc3c","added_by":"auto","created_at":"2024-05-07 18:06:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1174910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3995446/v1/373062a1-2323-4a56-9c60-34732397d6e2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mild-iodine-deficiency based on 24-hour urinary iodine excretion leads to significant metabolic changes in pregnant women at early stages of pregnancy","fulltext":[{"header":"1. Background","content":"\u003cp\u003eIodine is a necessary trace element for the synthesis of thyroid hormone, which plays an vital role in normal growth, development and cell metabolism \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Especially, thyroid hormone is required for normal neuronal migration and myelination of the brain during fetal early postnatal life \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In pregnant women, maintaining an adequate iodine nutrition status during pregnancy is particularly important during the development of offspring\u0026rsquo;s brain and central nervous system.\u003c/p\u003e \u003cp\u003eAt present, the adverse effects of severe iodine deficiency on the health of pregnant women and their offspring are well demonstrated \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. However, the effects of moderate, especially mild iodine deficiency on pregnant women and their offspring remain controversial. A few studies have shown that mild iodine deficiency in pregnant women had adverse effects on themselves and their offspring. A meta-analysis showed mild iodine deficiency was associated with the increase levels of free triiodothyronine (FT3), free thyroxine (FT4) and thyroglobulin antibody (TgAb) in pregnant women, and mild iodine deficiency might elevate the risk of thyroid dysfunction in pregnant women \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Dong J\u0026rsquo;s study showed that the alteration of development and maturation in cerebellar pinceau in the offspring were observed following maternal marginal and mild iodine deficiency \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. However, some studies showed that mild iodine deficiency in pregnant women was not obvious to themselves or their offspring. Nazarpour S\u0026rsquo;s study showed that maternal urinary iodine concentration was not generally associated with the pregnancy outcomes \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The health effects of iodine showed an irregular, probably a U-shaped relationship, therefore, the effect of mild iodine deficiency on pregnant women needs further and multiple-dimensions studies.\u003c/p\u003e \u003cp\u003eChina has been implementing the universal salt iodization (USI) policy since 1994. To ensure effective prevention and control of iodine deficiency disorders and maintain optimal iodine nutrition in population, China initiated national surveillance for iodine deficiency disorders two to three years prior to 2016, followed by annual surveillance thereafter \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Recent surveillance results indicated that overall iodine nutrition among the general population in China was adequate, while pregnant women also exhibited an appropriate level \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. However, in China, some regions still exhibited mild iodine deficiency among pregnant women. For instance, at the provincial level, there were still six to seven provinces where median urine iodine concentration (MUIC) ranged between 100\u0026thinsp;~\u0026thinsp;150 \u0026micro;g/L, along with approximately 20% of counties displaying similar values.\u003c/p\u003e \u003cp\u003eMetabolomics, in which small-molecule metabolites are detected and evaluated, is used to identify the set of metabolites that are associated with physiological conditions or aberrant processes \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In recent years, many analyses have shown that metabolites during pregnancy are associated with various gestational disorders. Peng ML\u0026rsquo; study showed metabolic disorders were exhibited in gestational diabetes mellitus and 27 metabolites were identified as the differential metabolites \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. A metabolomics study and meta-analysis showed that prenatal exposure to β-HCH and mecarbam could decrease the offspring\u0026rsquo;s birth weight mainly by disrupting thyroid hormone metabolism and glyceraldehyde metabolism \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The above results showed that some diseases during pregnancy can affect the expression of small metabolites of pregnant women, and several key metabolites may be related to the birth outcome of their offspring. However, there are still few studies on the effects of iodine deficiency on the metabolomics of pregnant women.\u003c/p\u003e \u003cp\u003eIn order to investigate the impact of iodine deficiency on the metabolic profile of pregnant women during the first and second trimesters, as well as its influence on offspring outcomes, we conducted a serum metabolomics study in this population. Employing multivariate analysis methods, we aimed to identify biomarkers associated with iodine-deficiency-induced metabolic changes and examine their correlation with neonatal TSH levels, head circumference, etc.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Subjects\u003c/h2\u003e \u003cp\u003eThis study recruited healthy pregnant women from June 2021 to December 2021 at the obstetrics clinic of the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China. The results of China national iodine deficiency disorders surveillance in Harbin in recent years showed that the coverage rate of iodized salt was \u0026gt;\u0026thinsp;95%, the consumption rate of qualified iodized salt was \u0026gt;\u0026thinsp;90%, the median UIC of children was between 100\u0026ndash;300\u0026micro;g/L, and the median UIC of pregnant women was between 150\u0026ndash;249\u0026micro;g/L.\u003c/p\u003e \u003cp\u003eThe inclusion criteria of the participants were as follows: healthy women with a spontaneous, single pregnancy who were willing to cooperate with 24-hour urine collection. The exclusion criteria included pregnant women with kidney diseases or clinical/sub-clinical thyroid dysfunction, those who had taken iodine-containing drugs or supplements, received treatment for thyroid disease (such as radiation therapy), had ultrasound-detected thyroid goiter or nodule, and those who had consumed iodine-rich foods such as seaweed and kelp for three days prior to providing the urine sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample Collection\u003c/h2\u003e \u003cp\u003eThe urine voided by each participant was collected over a 24-hour period. Urine volume was accurately measured, and 5 ml of the mixture was stored at -80 ℃. Fasting venous blood was also collected from all pregnant women in the morning. After separating the serum, 300 \u0026micro;L aliquots of each sample were stored at -80\u0026deg;C until further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Follow-up of the Pregnant Women and Their Pregnancy Outcome\u003c/h2\u003e \u003cp\u003eThe delivery outcomes of all pregnant women were monitored, encompassing the timing and mode of delivery. Additionally, comprehensive data on their offspring was collected, including gender, body length, weight, head circumference, Apaka score assessment results, as well as thyroid stimulating hormone (TSH) screening outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Iodine Measurements\u003c/h2\u003e \u003cp\u003eUrine iodine concentration and serum iodine concentration was determined by arsenic and cerium catalytic spectrophotometry recommended by WHO \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The levels of thyroid hormone were also measured. A chemiluminescent immunoassay was used to determine the levels of thyroid hormones, including FT3, FT4, TSH, TgAb and thyroid peroxidase antibody (TPOAb).\u003c/p\u003e \u003cp\u003eIn China, the recommended nutrient intake for iodine during pregnancy is 230 \u0026micro;g/d, given that the upper intake levels of iodine during pregnancy is 500 \u0026micro;g/d, therefore, in this study, 24-hour urine iodine excretion (UIE)\u0026thinsp;\u0026lt;\u0026thinsp;207 \u0026micro;g/d was defined as insufficient iodine intake and 24-hour UIE in the range of 207\u0026thinsp;~\u0026thinsp;450 \u0026micro;g/d is defined as sufficient iodine intake \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Metabolic Measurements\u003c/h2\u003e \u003cp\u003eA 2 \u0026micro;L aliquot of the pretreated sample was injected into a 100 mm \u0026times; 2.1 mm, 1.7 \u0026micro;m BEH C18 column (Waters, Milford, USA) using an Acquity ultra-performance liquid chromatography system (Waters, Milford, USA). We set the column temperature to 35 ℃ and the flow rate to 0.35 mL/ min. The samples alternated between different iodine nutritional status group. The mobile phase consisted of two solutions, A (water with 0.1% formic acid) and B (acetonitrile), and was eluted in the following proportions. Positive mode involved 2%~20% acetonitrile for 0\u0026thinsp;~\u0026thinsp;1.5 min, 20% ~ 70% for 1.5\u0026thinsp;~\u0026thinsp;6 min, and 70% ~ 98% for 6\u0026thinsp;~\u0026thinsp;10 min; the concentration was then held at 98% for 2 min, returned to 2% for 12% ~ 14 min and finally held at 2% for 14% ~ 16 min. Negative mode involved 2% ~ 30% acetonitrile for 0\u0026thinsp;~\u0026thinsp;2.0 min, 30% ~ 70% for 2\u0026thinsp;~\u0026thinsp;3 min, 70% ~ 75% for 3\u0026thinsp;~\u0026thinsp;7.5 min, and 75% ~ 98% for 7.5\u0026thinsp;~\u0026thinsp;10.5 min; the concentration was then held at 98% for 1.5 min, returned to 2% for 12\u0026thinsp;~\u0026thinsp;14 min and finally held at 2% for 14\u0026thinsp;~\u0026thinsp;16 min. ESI-TOF-MS detection was operated in positive or negative ion mode with the following settings: capillary voltage, 3000 V (positive) or 2800 V (negative); sample cone voltage, 35 V; desolvation gas flow, 600 L/h; desolvation temperature, 320 ℃; extraction cone voltage, 3.0 V; cone gas flow, 15 L/h; source temperature, 110 ℃; collision energy, 6 eV; and scan range, m/z 50\u0026thinsp;~\u0026thinsp;1000. All analyses were acquired with a locking spray to ensure accuracy and reproducibility. Leucine enkephalin was used for both positive ESI mode ([M\u0026thinsp;+\u0026thinsp;H]\u0026thinsp;+\u0026thinsp;=\u0026thinsp;556.2771) and negative ESI mode ([M\u0026thinsp;\u0026minus;\u0026thinsp;H] \u0026minus; = 554.2615).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data process of metabolomics and identification of metabolites\u003c/h2\u003e \u003cp\u003eThe raw data were transformed and then imported into the R package xcms for preprocessing. A matrix containing the peaks with retention times, m/z values, and corresponding peak areas are listed. Fragmentation patterns of selected metabolites and their structural information were obtained from MS/MS experiments performed. Metabolite identification was conducted based on the retention behavior, mass assignments, MS/MS product ion patterns, nline database queries, and confirmation with standards. The mass tolerance between the measured M/Z values and the exact mass of the components of interest was set to within 30 ppm. The MS/MS product ion spectra of selected metabolites were matched to metabolite structural information (with the same M/Z) obtained from the HMDB (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.hmdb.ca\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.hmdb.ca\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), SMPDB (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://smpdb.ca/\u003c/span\u003e\u003cspan address=\"http://smpdb.ca/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), METLIN (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://metlin.scripps.edu/\u003c/span\u003e\u003cspan address=\"http://metlin.scripps.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and KEGG (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genome.jp/kegg/\u003c/span\u003e\u003cspan address=\"http://www.genome.jp/kegg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical analyses\u003c/h2\u003e \u003cp\u003eAfter preprocessing, the data were imported to SIMCA-P 14.1 software (Umetrics, Umea, Sweden). Then, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to reveal the global metabolic changes, and the corresponding variable importance in projection (VIP) values were also calculated in the PLS-DA model. A validation plot was used to assess the validity of the PLS-DA model by comparing the goodness of fit (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) of the PLS-DA models with 100Y-permutated models. \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e is a measure of fit, i.e., how well the model fits the data. \u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e indicates how well the model predicts new data. In addition, a two-sided Cochran and Cox test was performed to determine the significance of each metabolite. A differential metabolite was selected when the \u003cem\u003eVIP\u003c/em\u003e value was greater than 1.2 and the \u003cem\u003eP\u003c/em\u003e value was less than 0.05. Statistical analysis was performed on the R platform, with the exception of PCA and PLS-DA, which were performed on SIMCA-P.\u003c/p\u003e \u003cp\u003ePearson\u0026rsquo;s and Spearman\u0026rsquo;s correlations were used for correlation analysis. Independent sample t-tests were used to compare differences in age, FT3, FT4, and TSH between iodine deficiency pregnant women and iodine adequate pregnant women. A chi-square test or two-sided Fisher\u0026rsquo;s exact test was used to compare differences in delivery mode, gender of offspring between the two groups. Wilcoxon rank-sum test was used to compare the difference in median urine iodine concentration (MUIC) between the two groups. Multiple linear regression was used to analyze the relationship between iodine status and the expression of metabolites in different iodine nutrition regions after considering other confounders, such as age and gestational weeks.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline of the pregnant women and their iodine nutritional status\u003c/h2\u003e \u003cp\u003eThe baseline characteristics of the pregnant women and their offspring were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaselines of the studied pregnant women and their offspring\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24h UIE\u0026thinsp;\u0026lt;\u0026thinsp;207 \u0026micro;g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24h UIE\u0026thinsp;\u0026ge;\u0026thinsp;207 \u0026micro;g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnant women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeight before pregnant (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.47\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.45\u0026thinsp;\u0026plusmn;\u0026thinsp;9.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI before pregnant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.96\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH (mU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003cp\u003e1.65 (0.91\u0026thinsp;~\u0026thinsp;2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003cp\u003e1.88 (0.92\u0026thinsp;~\u0026thinsp;2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1867\u003c/p\u003e \u003cp\u003e0.3379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFT3 ((pmol/L))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.54\u003c/p\u003e \u003cp\u003e5.05 (4.66\u0026thinsp;~\u0026thinsp;5.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003cp\u003e4.86 (4.43\u0026thinsp;~\u0026thinsp;5.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.03\u003c/p\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3122\u003c/p\u003e \u003cp\u003e0.4048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFT4 (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.92\u0026thinsp;\u0026plusmn;\u0026thinsp;8.15\u003c/p\u003e \u003cp\u003e16.57 (15.26\u0026thinsp;~\u0026thinsp;18.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003cp\u003e15.52 (13.85\u0026thinsp;~\u0026thinsp;17.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.47\u003c/p\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1531\u003c/p\u003e \u003cp\u003e0.0748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTg (\u0026micro;g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.79\u003c/p\u003e \u003cp\u003e(5.54\u0026thinsp;~\u0026thinsp;20.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003cp\u003e(5.53\u0026thinsp;~\u0026thinsp;13.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTgAb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.75\u003c/p\u003e \u003cp\u003e(14.68\u0026thinsp;~\u0026thinsp;18.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.62\u003c/p\u003e \u003cp\u003e(14.14\u0026thinsp;~\u0026thinsp;16.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTPOAb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.74\u003c/p\u003e \u003cp\u003e(8.12\u0026thinsp;~\u0026thinsp;13.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.08\u003c/p\u003e \u003cp\u003e(8.26\u0026thinsp;~\u0026thinsp;13.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrimester\u003c/p\u003e \u003cp\u003e(stage I/stage II)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14/18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21/45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelivery pregnancy week (week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelivery mode (1/2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24h UIE (\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.09 (135.43\u0026thinsp;~\u0026thinsp;186.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e312.25 (273.76\u0026thinsp;~\u0026thinsp;387.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOffspring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH (mU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHead circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median 24-hour UIE levels in the iodine deficiency group and the iodine adequate group were 166.19 \u0026micro;g (144.84\u0026thinsp;~\u0026thinsp;195.03 \u0026micro;g) and 317.22 \u0026micro;g (279.68\u0026thinsp;~\u0026thinsp;404.75 \u0026micro;g), respectively, exhibiting a significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). No statistically significant differences were observed between the two groups in terms of age, height, pre-pregnancy weight, pre-pregnancy BMI, thyroid function indicators (including TSH levels, FT3 levels, FT4 levels, abnormal rates of TgAb and TPOAb), or thyroglobulin (Tg) levels. Additionally, there were no statistical differences in gestational age or delivery mode between the two groups.\u003c/p\u003e \u003cp\u003eThere were no statistically significant differences in body length, weight, and head circumference between the iodine deficiency group (50.19 cm, 3.39 kg, 34.49 cm and 39.17 cm) and the iodine adequate group (49.89 cm, 3.41 kg and 34.42 cm). Although neonatal TSH levels were slightly higher in the iodine deficiency group than in the iodine adequate group, this difference was not statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Metabolic profiles of iodine deficiency and iodine adequate pregnant women\u003c/h2\u003e \u003cp\u003eThe average relative abundance values were slightly higher in the iodine adequate group than in the deficiency group. A total of 5384 and 2454 potential metabolites were determined in the chromatographic analysis in the positive and the negative mode, respectively.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, the PCA metabolic profiling score plots exhibited distinct differences between the iodine deficiency group and the adequate group in both positive and negative modes. Additionally, the PLS-DA score plots revealed a clear segregation among different iodine nutritional groups in different trimesters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e Y of the PLS-DA model was 0.795 and \u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e of the PLS-DA model was 0.288 (with two principal components) in the positive mode, and the two values were 0.839 and 0.348 (with three principal components) in the negative mode. These parameters indicated that the two models were stable and highly predictive. The permutation validation of the PLS-DA models showed that the random experimental \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e on the left were lower than the original values on the right, which indicated that the models were valid (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Identification of metabolic biomarkers\u003c/h2\u003e \u003cp\u003eAccording to the previous criteria for biomarker discovery and identification, a total of 28 metabolites (19 in positive mode and 9 in negative mode) were selected as potential biomarkers for classifying pregnant women with iodine deficiency and those with adequate iodine levels (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIdentified differential metabolites between iodine deficiency and iodine adequate in I and II stage pregnant women in the positive and negative ion modes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMetabolites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eVIP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24-Hydroxyglabrolide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0363\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlpha-dimorphecolic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2-(4-Methyl-5-thiazolyl)ethyl octanoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(6:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThyroxine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(10:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5-Heptyltetrahydro-2-oxo-3-furancarboxylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2-Deoxybrassinolide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiisobutyl phthalate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(12:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(8:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(10:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(14:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,3-Diethylpyrazine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDG(15:0/18:4(6Z,9Z,12Z,15Z)/0:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACar(12:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndoleacetaldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrigonelline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1-Acetoxy-4,6-tetradecadiene-8,10,12-triyne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Xylulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThyroxine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eButylparaben\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9-Decenoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecis,cis-Muconic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5-Hydroperoxyeicosatetraenoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4-Hydroxybenzaldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFA(22:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESI-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,14-Dihydro-15-keto PGF2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe confounders were assessed, and logistic and linear regression models were used to verify the independent influence of iodine status on differential metabolites. In the logistic model, the results demonstrated that iodine deficiency status remained associated with the expression of 23 metabolites even after controlling for age and trimester. Similarly, in the linear regression model, iodine deficiency still showed an effect on the expression of 25 metabolites (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ewith deficient iodine status even after adjusting for the confounding factor, including age and trimester\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLogistics regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eLiner regression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eadjusted\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003efor age*\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003efor trimester*\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eUIE\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eage\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003etrimester\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24-Hydroxyglabrolide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlpha-dimorphecolic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-(4-Methyl-5-thiazolyl)ethyl octanoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(6:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroxine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.8413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.9340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(10:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-Heptyltetrahydro-2-oxo-3-furancarboxylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-Deoxybrassinolide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiisobutyl phthalate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(12:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(8:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(10:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(14:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2,3-Diethylpyrazine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDG(15:0/18:4(6Z,9Z,12Z,15Z)/0:0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACar(12:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0478\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndoleacetaldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.9545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrigonelline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-Acetoxy-4,6-tetradecadiene-8,10,12-triyne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.8538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Xylulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroxine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButylparaben\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9-Decenoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecis,cis-Muconic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-Hydroperoxyeicosatetraenoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-Hydroxybenzaldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4267\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFA(22:1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13,14-Dihydro-15-keto PGF2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eadjusted\u003c/em\u003e\u003c/sup\u003e, the \u003cem\u003eP\u003c/em\u003e value for the expression of metabolite on UIE in the logistic model after adjusted for age and gestational weeks; \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003efor\u003c/em\u003e \u003cem\u003eage\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e*\u003c/em\u003e, the \u003cem\u003eP\u003c/em\u003e value for age on UIE in the logistic model; \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003efor trimester\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e*\u003c/em\u003e, the \u003cem\u003eP\u003c/em\u003e value for trimester on UIE in the logistic model; \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eUIE\u003c/em\u003e\u003c/sup\u003e, the \u003cem\u003eP\u003c/em\u003e value for UIE on the expression of metabolites in the regression model; \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003eage\u003c/em\u003e\u003c/sup\u003e, the \u003cem\u003eP\u003c/em\u003e value for age on the expression of metabolites in the regression model; \u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003etrimester\u003c/em\u003e\u003c/sup\u003e, the \u003cem\u003eP\u003c/em\u003e value for trimester on the expression of metabolites in the regression model.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Metabolic pathway analysis\u003c/h2\u003e \u003cp\u003eIn order to identify the relevant involved pathways, the differential metabolites were submitted to MetaboAnalyst 4.0 to determine the disturbed pathways. Five pathways, including fatty acid biosynthesis, tyrosine metabolism, tryptophan metabolism, arachidonic acid metabolism, and pentose and glucuronate interconversions were related to iodine deficiency in pregnant women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Correlation analysis of potential biomarkers with thyroid function and serum iodine levels in pregnant women\u003c/h2\u003e \u003cp\u003eWe conducted an analysis on the association between metabolic biomarkers and thyroid function in pregnant women. The results showed a negative correlation between 3,5-tetradecadiencarnitine and oxidized glutathione with FT3 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.405, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045; \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.527, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), as well as a negative correlation with FT4 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.418, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038; \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.465, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019). Additionally, L-octanoylcarnitine exhibited a positive correlation with TG level (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.575, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Correlation analysis of potential biomarkers for iodine deficiency in the offspring's characteristics.\u003c/h2\u003e \u003cp\u003eWe further investigated the association between maternal potential metabolic markers and their offspring's TSH, body weight and length. The results revealed that newborn TSH levels were negatively correlated with 2-(4-Methyl-5-thiazolyl) ethyl octanoate (\u003cem\u003er\u003c/em\u003e = -0.273, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0420). Additionally, body length was positively associated with ACar (12:0) (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2839, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0308), while both body weight and length showed negative correlations with (9S,10E,12Z,15Z)-9- Hydroxy \u0026minus;\u0026thinsp;10,12,15-octadecatrienoic acid (\u003cem\u003er\u003c/em\u003e = -0.293, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0255; \u003cem\u003er\u003c/em\u003e = -0.296, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0242).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, the metabolic profiles of pregnant women in the first or second trimester with iodine deficiency significantly differed from those of pregnant women with adequate iodine nutrition. A total of 28 distinct metabolites were identified as potential markers for iodine deficiency in pregnant women. The impact of iodine deficiency on metabolic pathways and functions was discussed, providing valuable insights for the prevention and treatment strategies targeting iodine deficiency in pregnancy.\u003c/p\u003e \u003cp\u003eAt the population level, iodine status is typically evaluated by the MUIC from spot urine samples \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. However, at an individual level, spot urine iodine levels may not accurately reflect iodine status due to significant day-to-day and within-day variations in urine iodine concentrations \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Currently, 24-hour UIE is considered a quasi-reference standard for assessing individual-level iodine status because it reduces hydration-dependent variations in iodine excretion \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Nevertheless, collecting 24-hour urine samples can be challenging due to its elaborate procedure and potential lower compliance rates that could compromise data quality particularly in field studies. In this study, the excretion Angle was employed in this study to assess the dietary iodine intake of pregnant women, which provided a relatively scientific and accurate approach for individual iodine nutrition evaluation during pregnancy.\u003c/p\u003e \u003cp\u003eStudies investigating the impact of mild iodine deficiency during the first and second trimesters on offspring development have yielded inconsistent results, which can be attributed to numerous confounding factors or the relatively weak effect of mild iodine deficiency that might be overshadowed by other influential factors \u003csup\u003e[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. In our current study, no significant differences were observed in maternal thyroid function and birth outcomes between pregnant women with low UIE levels and those with normal UIE levels. Therefore, it can be concluded that the effects of mild iodine deficiency on both maternal thyroid function and offspring birth outcomes do not exhibit prominent manifestations in major phenotypes. However, a comprehensive analysis of small molecular metabolites present in pregnant women's blood samples revealed significant distinctions in metabolic profiles between individuals with iodine deficiency and sufficient nutrition, indicating underlying changes at a molecular level despite minimal discernible phenotypic differences.\u003c/p\u003e \u003cp\u003eIn the current study, the expression of indoleacetaldehyde was significantly changed. Indoleacetaldehyde plays a pivotal role in the metabolic pathway of tryptophan. Empirical evidence suggests that tryptophan metabolism is implicated in the pathogenesis of depression and hyperactivity in pediatric populations \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. During pregnancy, the metabolism of tryptophan also plays a pivotal role \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Zhao YJ\u0026rsquo;s study shown that tryptophan related metabolites were important in regulating endothelial function during pregnancy \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Lee\u0026rsquo;s study observed that higher plasma tryptophan concentrations were associated with a lower prevalence of poor sleep quality during pregnancy \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. \u0026Uuml;n\u0026uuml;var S\u0026rsquo;s study showed thyroid disorders may lead to changes in tryptophan degradation, neopterin production and catalase enzyme activities \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. In our study, alterations in tryptophan metabolism were observed in pregnant women with iodine deficiency, suggesting a potential association between iodine deficiency and its impact on thyroid function, subsequently affecting tryptophan metabolism.\u003c/p\u003e \u003cp\u003eIn addition, alterations were observed in the metabolism of arachidonic acid. Arachidonic acid plays a crucial role in fetal growth and development, particularly in the development and functioning of the fetal brain and retina \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Ghebremeskel\u0026rsquo;s study demonstrated reduced levels of arachidonic acid both in maternal serum and newborns born to diabetic mothers \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. It is likely that lower level of arachidonic acid in the babies of diabetic mothers were reflection of the impair in placental transfer. In our study, arachidonic acid levels were also decreased in iodine deficient pregnant women, which was consistent with the trend of arachidonic acid changes in diabetic pregnant women.\u003c/p\u003e \u003cp\u003eThe expression of many lipid-related substances changed in this study. Fatty acid metabolism have been found to affect on the proinflammatory properties and the aggregation of platelets \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. A growing body of evidence suggests that essential fatty acids and their active metabolic byproducts play a crucial role in maintaining the structural and functional integrity of both the central nervous system. These metabolites may contribute to proper development of the nervous system while reducing the likelihood of preterm birth or low birth weight. Additionally, it is believed that several fatty acid could potentially enhance children's learning abilities and academic performance. The majority of brain growth occurs during fetal life, making this period particularly important for adequate nutrient intake \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. The present study unveiled alterations in the fatty acid pathway among pregnant women in the iodine deficient group, indicating that iodine deficiency may potentially impact fetal neurointelligence development by disrupting fatty acid metabolism.\u003c/p\u003e \u003cp\u003eThe findings in this study presented alterations in the tyrosine metabolism pathway. Iodine serves as an indispensable substrate for thyroid hormone synthesis, and thyroid hormone is intricately associated with tyrosine metabolism. The constituents required for synthesizing thyroid hormone encompass iodine and thyroglobulin, wherein thyroglobulin undergoes iodination at the tyrosine residue to produce thyroid hormone. Thus, iodine deficiency leads to changes in tyrosine metabolism.\u003c/p\u003e \u003cp\u003eDue to the limited availability of comprehensive epidemiological survey data, the precise impact of pentose and glucuronate interconversions during pregnancy remains uncertain. However, it is important to note that purine metabolism disorders often coexist with glucose and lipid metabolism disorders as integral components of metabolic syndrome \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere are certain limitations in this study. Firstly, due to the relatively short recruitment period and other factors, the sample size was comparatively small. Secondly, only a single measurement of 24-hour UIE was utilized instead of multiple collections over a 24-hour period. Thirdly, further validation on a larger external scale is required for the biomarkers used, and additional exploration is necessary to understand their biological roles.\u003c/p\u003e \u003cp\u003eIn conclusion, although mild iodine deficiency during the first and second trimesters may not lead to overt adverse effects on pregnant women and their offspring, however, at the metabolic level, it could disrupt the metabolic profile of pregnant women and impact fetal development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors revised the report and approved the final version before submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Natural Science Foundation of China (NSFC 82173638 and NSFC 81830098), the Natural Science Foundation of Heilongjiang Province (YQ2022H005) and the Special Funds from the Central Finance to Support the Development of Local Universities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ethics Committee of Harbin Medical University provided approval for this study (HRBMUCEDC20211002). It was conducted according to the provisions of the Declaration of Helsinki. Written informed consent was obtained from all participants or their guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt was not applicable for our study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Disclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors have declared that no competing financial interest exists.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMelse-Boonstra A, Jaiswal N. Iodine deficiency in pregnancy, infancy and childhood and its consequences for brain development[J]. 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Perinatal exposure to low-dose decabromodiphenyl ethane increased the risk of obesity in male mice offspring[J]. Environ Pollut. 2018;243(Pt A):553\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envpol.2018.08.082\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2018.08.082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"pregnant women, metabolomics, offspring, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-3995446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3995446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe effects of mild iodine deficiency during the first and second trimesters on both pregnant women themselves and their offspring exhibited in consistent patterns. In this study, we aimed to address this issue by employing small molecule metabolomics. A total of 98 pregnant women in either the first or second trimester were recruited, with comprehensive data including basic information, 24-hour urine samples and blood samples collected, and subsequent evaluation of birth outcomes for their offspring. The 24-hour urinary iodine excretion (UIE) was detected and used as the dividing criterion to determine the iodine nutrition status of pregnant women. Serum metabolomics assay was performed by Ultra High Performance Liquid Chromatography Orbitrap Exploris Mass Spectrometry (UHPLC-OE-MS) platform. Differential metabolites as the potential iodine deficiency biomarkers were selected by multivariate statistical analysis methods. Association analysis was used to further analyze the relationship between the potential biomarkers and neonatal birth outcomes. As a result, there was no significant difference in maternal thyroid function indicators and neonatal outcomes between mild iodine deficiency and iodine adequate pregnant women. However, the metabolic profile of pregnant women with mild iodine deficiency was significantly disturbed compare to these with iodine adequate. A total of 28 different metabolites were screened, which could be used as the potential biomarkers of iodine deficiency. After adjusted age and pregnancy trimester, the expression of these biomarkers were also changed significantly. Furthermore, these markers were also related to fatty acid biosynthesis, tyrosine metabolism, tryptophan metabolism, arachidonic acid metabolism, and pentose and glucuronate interconversions. In addition, among these markers, 2-(4-Methyl-5-thiazolyl)ethyl octanoate was found to be associated with neonatal TSH, ACar(12:0), (9S,10E,12Z,15Z)-9-Hydroxy-10,12,15-octadecatrienoic acid showed a correlation with body length; whereas (9S,10E,12Z,15Z)-9-Hydroxy-10,12,15-octadecatrienoic acid was linked to body weight. In conclusion, mild iodine deficiency during the first and second trimesters dose not result in overt adverse effects on pregnant women and their offspring. However, at the metabolic level, mild iodine deficiency may disrupt the metabolic profile of pregnant women and impact the development of their offspring.\u003c/p\u003e","manuscriptTitle":"Mild-iodine-deficiency based on 24-hour urinary iodine excretion leads to significant metabolic changes in pregnant women at early stages of pregnancy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-14 19:48:24","doi":"10.21203/rs.3.rs-3995446/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9e1572f3-7fb0-435b-bc67-0ecc35590f99","owner":[],"postedDate":"March 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-07T16:31:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-14 19:48:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3995446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3995446","identity":"rs-3995446","version":["v1"]},"buildId":"veTbxFhMMB0_faC6-Wkog","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}