Targeted newborn metabolomics: prediction of gestational age from cord blood.
Ontology highlight
ABSTRACT: Objective
Our study sought to determine whether metabolites from a retrospective collection of banked cord blood specimens could accurately estimate gestational age and to validate these findings in cord blood samples from Busia, Uganda.Study design
Forty-seven metabolites were measured by tandem mass spectrometry or enzymatic assays from 942 banked cord blood samples. Multiple linear regression was performed, and the best model was used to predict gestational age, in weeks, for 150 newborns from Busia, Uganda.Results
The model including metabolites and birthweight, predicted the gestational ages within 2 weeks for 76.7% of the Ugandan cohort. Importantly, this model estimated the prevalence of preterm birth <34 weeks closer to the actual prevalence (4.67% and 4.00%, respectively) than a model with only birthweight which overestimates the prevalence by 283%.Conclusion
Models that include cord blood metabolites and birth weight appear to offer improvement in gestational age estimation over birth weight alone.
SUBMITTER: Jasper EA
PROVIDER: S-EPMC8830770 | biostudies-literature | 2022 Feb
REPOSITORIES: biostudies-literature
Publications
Targeted newborn metabolomics: prediction of gestational age from cord blood.
Jasper Elizabeth A EA Oltman Scott P SP Rogers Elizabeth E EE Dagle John M JM Murray Jeffrey C JC Kamya Moses M Kakuru Abel A Kajubi Richard R Ochieng Teddy T Adrama Harriet H Okitwi Martin M Olwoch Peter P Jagannathan Prasanna P Clark Tamara D TD Dorsey Grant G Ruel Theodore T Jelliffe-Pawlowski Laura L LL Ryckman Kelli K KK
Journal of perinatology : official journal of the California Perinatal Association 20220124 2
<h4>Objective</h4>Our study sought to determine whether metabolites from a retrospective collection of banked cord blood specimens could accurately estimate gestational age and to validate these findings in cord blood samples from Busia, Uganda.<h4>Study design</h4>Forty-seven metabolites were measured by tandem mass spectrometry or enzymatic assays from 942 banked cord blood samples. Multiple linear regression was performed, and the best model was used to predict gestational age, in weeks, for ...[more]
Similar Datasets
Project description:ContextNewborn adiposity is associated with childhood obesity. Cord blood metabolomics is one approach that can be used to understand early-life contributors to adiposity and insulin resistance.ObjectiveTo determine the association of cord blood metabolites with newborn adiposity and hyperinsulinemia in a multiethnic cohort of newborns.DesignCross-sectional, observational study.SettingHyperglycemia and Adverse Pregnancy Outcome study.ParticipantsOne thousand six hundred multiethnic mother-newborn pairs.Main outcome measureCord blood C-peptide, birthweight, and newborn sum of skinfolds.ResultsMeta-analyses across four ancestry groups (Afro-Caribbean, Northern European, Thai, and Mexican American) demonstrated significant associations of cord blood metabolites with cord blood C-peptide, birthweight, and newborn sum of skinfolds. Several metabolites, including branched-chain amino acids (BCAAs), medium- and long-chain acylcarnitines, nonesterified fatty acids, and triglycerides were negatively associated with cord C-peptide but positively associated with birthweight and/or sum of skinfolds. 1,5-Anhydroglucitol, an inverse marker of recent maternal glycemia, was significantly inversely associated with birthweight and sum of skinfolds. Network analyses revealed groups of interrelated amino acid, acylcarnitine, and fatty acid metabolites associated with all three newborn outcomes.ConclusionsCord blood metabolites are associated with newborn size and cord blood C-peptide levels after adjustment for maternal body mass index and glucose during pregnancy. Negative associations of metabolites with C-peptide at birth were observed. 1,5-Anhydroglucitol appears to be a marker of adiposity in newborns. BCAAs were individually associated with birthweight and demonstrated possible associations with newborn adiposity in network analyses.
| S-EPMC6735762 | biostudies-literature
Project description:BackgroundEarly access to antenatal care and high-cost technologies for pregnancy dating challenge early neonatal risk assessment at birth in resource-constrained settings. To overcome the absence or inaccuracy of postnatal gestational age (GA), we developed a new medical device to assess GA based on the photobiological properties of newborns' skin and predictive models.ObjectiveThis study aims to validate a device that uses the photobiological model of skin maturity adjusted to the clinical data to detect GA and establish its accuracy in discriminating preterm newborns.MethodsA multicenter, single-blinded, and single-arm intention-to-diagnosis clinical trial evaluated the accuracy of a novel device for the detection of GA and preterm newborns. The first-trimester ultrasound, a second comparator ultrasound, and data regarding the last menstrual period (LMP) from antenatal reports were used as references for GA at birth. The new test for validation was performed using a portable multiband reflectance photometer device that assessed the skin maturity of newborns and used machine learning models to predict GA, adjusted for birth weight and antenatal corticosteroid therapy exposure.ResultsThe study group comprised 702 pregnant women who gave birth to 781 newborns, of which 366 (46.9%) were preterm newborns. As the primary outcome, the GA as predicted by the new test was in line with the reference GA that was calculated by using the intraclass correlation coefficient (0.969, 95% CI 0.964-0.973). The paired difference between predicted and reference GAs was -1.34 days, with Bland-Altman limits of -21.2 to 18.4 days. As a secondary outcome, the new test achieved 66.6% (95% CI 62.9%-70.1%) agreement with the reference GA within an error of 1 week. This agreement was similar to that of comparator-LMP-GAs (64.1%, 95% CI 60.7%-67.5%). The discrimination between preterm and term newborns via the device had a similar area under the receiver operating characteristic curve (0.970, 95% CI 0.959-0.981) compared with that for comparator-LMP-GAs (0.957, 95% CI 0.941-0.974). In newborns with absent or unreliable LMPs (n=451), the intent-to-discriminate analysis showed correct preterm versus term classifications with the new test, which achieved an accuracy of 89.6% (95% CI 86.4%-92.2%), while the accuracy for comparator-LMP-GA was 69.6% (95% CI 65.3%-73.7%).ConclusionsThe assessment of newborn's skin maturity (adjusted by learning models) promises accurate pregnancy dating at birth, even without the antenatal ultrasound reference. Thus, the novel device could add value to the set of clinical parameters that direct the delivery of neonatal care in birth scenarios where GA is unknown or unreliable.International registered report identifier (irrid)RR2-10.1136/bmjopen-2018-027442.
| S-EPMC9494223 | biostudies-literature
Project description:Per- and polyfluoroalkyl substances (PFASs) can disrupt lipid metabolism, and changes in cord blood fatty acid composition have been observed in small newborns. Emerging evidence suggests that exposure to PFASs during pregnancy is linked to decreased newborn size, although the evidence is not consistent. The modifying effect of fatty acids on the associations of gestational PFAS exposure with newborn size is still unknown. Here we show that the nutritional status of the fetus, as indicated by the level of fatty acids in the cord blood, mitigates the adverse effects of gestational PFAS exposure on the size of the newborn. Our study confirms the adverse developmental effects of PFASs and identifies emerging short-chain PFASs as the primary drivers of reduced newborn size, despite their lower exposure burden compared to legacy PFASs. Additionally, we find the protective role of cord blood fatty acids, suggesting potential strategies for mitigating the detrimental effects of emerging environmental exposures on human health. Our findings provide new evidence of the potential toxicity of emerging PFASs and call for further toxicity evaluations of these pollutants for regulatory purposes. Future studies should consider the complex interaction between exposure and nutrition within the human body, particularly during the first thousand days of life, to promote lifelong health.
| S-EPMC11369372 | biostudies-literature
Project description:BackgroundThyroid disease is one of the common endocrine disorders affecting the pregnant women, in which thyroid autoimmunity can alter the progress and the outcome of pregnancy. Women with euthyroid status but anti-thyroid peroxidase (anti-TPO) antibodies positivity before pregnancy are prone to subclinical gestational hypothyroidism. However, the connections between anti-TPO antibodies positivity and gestational hypothyroidism remain largely unknown. The aim of the present study is to investigate the differences of fetal metabolic profile at birth according to maternal anti-TPO status.MethodsWe performed 1H-NMR metabolomics on cord blood of a nested case control cohort of 22 pregnant women with matched thyroid hormone levels and demographic data, including 11 women with euthyroid status but anti-thyroid antibodies positivity (into the anti-TPO antibodies positivity group) and 11 matched women as controls with euthyroid status and negative anti-thyroid antibodies (into the control group).ResultsDistinct metabolic profiles were observed between the anti-TPO antibody positivity group and the nested control group, from which a total of 10 metabolites with between-group altered abundances were structurally identified. Five out of the 10 metabolites were up-regulated in the anti-TPO antibodies positivity group, including D-Glucose, L-Glutamine, 3-Hydroxybutyric acid, Myo-Inositol, Creatinine. The other 5 metabolites were down-regulated in the anti-TPO antibodies positivity group, including L-Leucine, L-Lysine, L-Glutamic acid, L-Tyrosine, and L-Phenylalanine. All the 10 metabolites have been previously reported to be correlated with hypothyroidism. Metabolite set enrichment analysis and pathway analysis suggested that amino acid metabolism pathways (especially the phenylalanine metabolism) were associated with anti-TPO antibodies positivity.ConclusionThe results of this study suggested that fetal metabolic disorder is correlated with anti-TPO antibodies positivity, representing by abundance alteration of hypothyroidism associated metabolites and the related disturbance of amino acid metabolism pathways.
| S-EPMC8952885 | biostudies-literature
Project description:ObjectiveNo validated biomarker at birth exists to predict which newborns will develop severe hyperbilirubinemia. This study's primary aim was to build and validate a prediction model for severe hyperbilirubinemia using umbilical cord blood bilirubins (CBB) and risk factors at birth in neonates at risk for maternal-fetal blood group incompatibility. This study's secondary aim was to compare the accuracy of CBB to the direct antigen titer.MethodsInclusion criteria for this prospective cohort study included: ≥35 weeks gestational age, mother with blood type O and/or Rh negative or positive antibody screen, and <24 hours of age. The primary outcome was severe hyperbilirubinemia, defined as phototherapy during the initial hospital stay. Secondary outcomes were a total serum bilirubin concentration >95th and >75th percentile during the initial hospital stay. The predictive performance and accuracy of the two tests (CBB and direct antigen titer) for each outcome was assessed using area under a receiver-operating characteristic curve (AUC), sensitivity, and specificity.ResultsWhen compared to neonates who did not receive phototherapy (n = 463), neonates who received phototherapy (n = 36) had a greater mean CBB ± standard deviation (2.5 ± 0.7 vs. 1.6 ± 0.4 mg/dL, p<0.001). For every 0.3 mg/dL increase in CBB, a neonate was 3.20 (95% confidence interval, 2.31-4.45), 2.10 (1.63-2.70), and 3.12 (2.44-3.99) times more likely to receive phototherapy or have a total serum bilirubin concentration >95th and >75th percentile, respectively. The AUC ± standard error (95% confidence interval) for CBB for phototherapy and a total serum bilirubin concentration >95th and >75th percentile was 0.89 ± 0.03 (0.82-0.95), 0.81 ± 0.04 (0.73-0.90), and 0.84 ± 0.02 (0.80-0.89), respectively. However, the AUC for gestational age and maternal Asian race for these outcomes was only 0.55 ± 0.05 (0.45-0.66), 0.66 ± 0.05 (0.56-0.76), and 0.57 ± 0.04 (0.05-0.64), respectively. When the CBB was combined with gestational age and maternal Asian race, the AUC for a total serum bilirubin concentration >95th percentile improved to 0.87 ± 0.03 (0.81-0.92) (p = 0.034 vs. the model with CBB only and p<0.001 vs. the model with clinical risk factors only). In a sub-group of subjects (n = 189), the AUC for the direct antigen titer for phototherapy was 0.64 ± 0.06 (0.52-0.77) with a 52% sensitivity and 77% specificity. In contrast, a CBB cut-point of 1.85 mg/dL was 92% sensitive and 70% specific for phototherapy with an AUC of 0.87 ± 0.04 (0.80-0.95).ConclusionCBB, in combination with gestational age and maternal race, may be a useful, non-invasive test to predict shortly after birth which neonates will develop severe hyperbilirubinemia.
| S-EPMC5983417 | biostudies-literature
Project description:DNA methylation is highly sensitive to in utero perturbations and has an established role in both embryonic development and regulation of gene expression. The foetal genetic component has been previously shown to contribute significantly to the timing of birth, yet little is known about the identity and behaviour of individual genes. The aim of this study was to test the extent genome-wide DNA methylation levels in umbilical cord blood were associated with gestational age at birth (GA). Findings were validated in an independent sample and evidence for the regulation of gene expression was evaluated for cis gene relationships in specimens with multi-omic data. Genome-wide DNA methylation, measured by the Illumina Infinium Human Methylation 450 K BeadChip, was associated with GA for 2,372 CpG probes (5% FDR) in both the Pregnancy, Race, Environment, Genes (PREG) and Newborn Epigenetic Study (NEST) cohorts. Significant probes mapped to 1,640 characterized genes and an association with nearby gene expression measures obtained by the Affymetrix HG-133A microarray was found for 11 genes. Differentially methylated positions were enriched for actively transcribed and enhancer chromatin states, were predominately located outside of CpG islands, and mapped to genes enriched for inflammation and innate immunity ontologies. In both PREG and NEST, the first principal component derived from these probes explained approximately one-half (58.1% and 47.8%, respectively) of the variation in GA. Gene pathways identified are consistent with the hypothesis of pathogen detection and response by the immune system to elicit premature labour as a consequence of unscheduled inflammation.
| S-EPMC7595591 | biostudies-literature
Project description:Gestational age is associated with greater school achievement and variation in newborn metabolic markers. Whether metabolic markers are related to gestational age differences in achievement is unknown. This study examines whether newborn metabolic markers are associated with gestational age differences in performance on standardized school tests. This retrospective cohort study linked birth certificates of children born in Iowa between 2002 and 2010 to newborn screening records and school tests between 2009 and 2018. The analytical sample includes up to 229,679 children and 973,247 child-grade observations. Regression models estimate the associations between gestational age and 37 newborn metabolic markers with national percentile ranking (NPR) scores on math, reading comprehension, and science tests. An additional gestational week is associated with 0.6 (95% CI: 0.6, 0.7), 0.5 (95% CI: 0.4, 0.5), and 0.4 (95% CI: 0.4, 0.5) higher NPRs on math, reading, and science, respectively. Compared to full term children (37-44 weeks), preterm children (32-36 weeks) have 2.2 (95% CI: -2.6, -1.8), 1.5 (95% CI: -1.9, -1.1), and 1.0 (95% CI: -1.4, -0.7) lower NPRs on math, reading comprehension, and science. Very preterm children (20-31 weeks) have 8.3 (95% CI: -9.4, -7.2), 5.2 (95% CI: -6.2, -4.0), and 4.7 (95% CI: -5.6, -3.8) lower NPRs than full term children on math, reading, and science. Metabolic markers are associated with 27%, 36%, and 45% of gestational age differences in math, reading, and science scores, respectively, and over half of the difference in test scores between preterm or very preterm and full term children. Newborn metabolic markers are strongly related to gestational age differences in school test scores, suggesting that early metabolic differences are important markers of long-term child development.
| S-EPMC8834716 | biostudies-literature
Project description:BackgroundDysregulated adipokine levels are associated with type 2 diabetes and gestational diabetes. Adiponectin and leptin are involved in nutrient transport, thereby affecting fetal growth and metabolism. We aimed to determine whether type 2 diabetes and gestational diabetes were associated different levels of serum and cord blood adiponectin, leptin, insulin and offspring birthweight.MethodsSerum, cord blood, gestational age and birthweight were collected for First Nations mothers and infants who were enrolled in the Next Generation Cohort Study. A total of 173 maternal and 188 neonatal samples were available for analysis. Of those, 136 were matched maternal infant dyads that we used for paired mother-infant analyses. Pairs were sorted into groups based on maternal diagnoses of pre-existing type 2 diabetes, gestational diabetes or no diabetes (control). Adiponectin and leptin were measured by enzyme linked immunosorbent assay.ResultsMothers with gestational diabetes had lower serum adiponectin (6.48 ± 3.64 µg/mL) in the third trimester relative to mothers with type 2 diabetes (8.55 ± 5.24 µg/mL, p < 0.05) or no diabetes (7.73 ± 3.47 µg/mL). However, cord blood adiponectin was lower only in normal weight pregnancies complicated by type 2 diabetes. Cord blood glucose, insulin and leptin were increased in infants of type 2 diabetes mothers and increased leptin was positively correlated with maternal leptin and birth weight. Female infants exposed to pregestational type 2 diabetes had a significantly higher birthweight z-score than female control infants.ConclusionsIn this study, exposure to type 2 diabetes, but not gestational diabetes, impacted cord blood levels of glucose, insulin and leptin and birthweight. Collectively, these factors may contribute to the greater impact of pregestational type 2 diabetes exposure on offspring health relative to gestational diabetes.
| S-EPMC11881472 | biostudies-literature
Project description:BackgroundAccurate assessment of gestational age (GA) and identification of preterm birth (PTB) at delivery is essential to guide appropriate post-natal clinical care. Undoubtedly, dating ultrasound sonography (USG) is the gold standard to ascertain GA, but is not accessible to the majority of pregnant women in low- and middle-income countries (LMICs), particularly in rural areas and small secondary care hospitals. Conventional methods of post-natal GA assessment are not reliable at delivery and are further compounded by a lack of trained personnel to conduct them. We aimed to develop a population-specific GA model using integrated clinical and biochemical variables measured at delivery.MethodsWe acquired metabolic profiles on paired neonatal heel prick (nHP) and umbilical cord blood (uCB) dried blood spot (DBS) samples (n = 1278). The master data set consists of 31 predictors from nHP and 24 from uCB after feature selection. These selected predictors including biochemical analytes, birth weight, and placental weight were considered for the development of population-specific GA estimation and birth outcome classification models using eXtreme Gradient Boosting (XGBoost) algorithm.ResultsThe nHP and uCB full model revealed root mean square error (RMSE) of 1.14 (95% confidence interval (CI) = 0.82-1.18) and of 1.26 (95% CI = 0.88-1.32) to estimate the GA as compared to actual GA, respectively. In addition, these models correctly estimated 87.9 to 92.5% of the infants within ±2 weeks of the actual GA. The classification models also performed as the best fit to discriminate the PTB from term birth (TB) infants with an area under curve (AUC) of 0.89 (95% CI = 0.84-0.94) for nHP and an AUC of 0.89 (95% CI = 0.85-0.95) for uCB.ConclusionThe biochemical analytes along with clinical variables in the nHP and uCB data sets provide higher accuracy in predicting GA. These models also performed as the best fit to identify PTB infants at delivery.
| S-EPMC11225965 | biostudies-literature
Project description:Natural antibodies are an innate-like subset of serum antibodies involved in host defense, tumor surveillance, homeostasis, and autoimmunity. Defining the natural antibody repertoire is critical for identifying biomarkers, developing vaccines, controlling and preventing autoimmunity, and understanding the development and organization of the immune system. While natural antibodies to protein antigens have been studied in depth, little is known about natural antibodies to carbohydrate antigens. To address this, we profiled IgM from umbilical cord blood and matched maternal sera on a glycan microarray. Since standard methods to detect maternal contamination in cord serum did not have sufficient sensitivity for our study, we developed a highly sensitive microarray-based assay. Using this method, we found that over 50% of the cord samples had unacceptable levels of maternal contamination. For the cord samples with high purity, anti-glycan IgM antibodies were prevalent and recognized a broad range of non-human and human glycans. Using principal component analysis and hierarchical clustering, cord IgM repertoires showed a high degree of similarity with each other but were distinct from maternal IgM repertoires. Our results demonstrate that many anti-glycan antibodies in human serum are natural antibodies and provide new insights into the development of anti-glycan antibody repertoires.
| S-EPMC6668783 | biostudies-literature