A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study.

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.

Age at lung cancer diagnosis in females versus males who never smoke by race and ethnicity.

BACKGROUND: We characterized age at diagnosis and estimated sex differences for lung cancer and its histological subtypes among individuals who never smoke. METHODS: We analyzed the distribution of age at lung cancer diagnosis in 33,793 individuals across 8 cohort studies and two national registries from East Asia, the United States (US) and the United Kingdom (UK). Student's t-tests were used to assess the study population differences (Δ years) in age at diagnosis comparing females and males who never smoke across subgroups defined by race/ethnicity, geographic location, and histological subtypes. RESULTS: We found that among Chinese individuals diagnosed with lung cancer who never smoke, females were diagnosed with lung cancer younger than males in the Taiwan Cancer Registry (n = 29,832) (Δ years = -2.2 (95% confidence interval (CI):-2.5, -1.9), in Shanghai (n = 1049) (Δ years = -1.6 (95% CI:-2.9, -0.3), and in Sutter Health and Kaiser Permanente Hawai'i in the US (n = 82) (Δ years = -11.3 (95% CI: -17.7, -4.9). While there was a suggestion of similar patterns in African American and non-Hispanic White individuals. the estimated differences were not consistent across studies and were not statistically significant. CONCLUSIONS: We found evidence of sex differences for age at lung cancer diagnosis among individuals who never smoke.

Phenotypic and genetically predicted leucocyte telomere length and lung cancer risk in the prospective UK Biobank.

We investigated phenotypic leucocyte telomere length (LTL), genetically predicted LTL (gTL), and lung cancer risk among 371 890 participants, including 2829 incident cases, from the UK Biobank. Using multivariable Cox regression, we found dose-response relationships between longer phenotypic LTL (p-trendcontinuous=2.6×10-5), longer gTL predicted using a polygenic score with 130 genetic instruments (p-trendcontinuous=4.2×10-10), and overall lung cancer risk, particularly for adenocarcinoma. The associations were prominent among never smokers. Mendelian Randomization analyses supported causal associations between longer telomere length and lung cancer (HRper 1 SD gTL=1.87, 95% CI: 1.49 to 2.36, p=4.0×10-7), particularly adenocarcinoma (HRper 1 SD gTL=2.45, 95%CI: 1.69 to 3.57, p=6.5×10-6).

Epigenome-wide association study of lung cancer among never smokers in two prospective cohorts in Shanghai, China.

BACKGROUND: The aetiology of lung cancer among individuals who never smoked remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Epigenetic alterations, particularly DNA methylation (DNAm) changes, have emerged as potential drivers. Yet, few prospective epigenome-wide association studies (EWAS), primarily focusing on peripheral blood DNAm with limited representation of never smokers, have been conducted. METHODS: We conducted a nested case-control study of 80 never-smoking incident lung cancer cases and 83 never-smoking controls within the Shanghai Women's Health Study and Shanghai Men's Health Study. DNAm was measured in prediagnostic oral rinse samples using Illumina MethylationEPIC array. Initially, we conducted an EWAS to identify differentially methylated positions (DMPs) associated with lung cancer in the discovery sample of 101 subjects. The top 50 DMPs were further evaluated in a replication sample of 62 subjects, and results were pooled using fixed-effect meta-analysis. RESULTS: Our study identified three DMPs significantly associated with lung cancer at the epigenome-wide significance level of p<8.22×10-8. These DMPs were identified as cg09198866 (MYH9; TXN2), cg01411366 (SLC9A10) and cg12787323. Furthermore, examination of the top 1000 DMPs indicated significant enrichment in epithelial regulatory regions and their involvement in small GTPase-mediated signal transduction pathways. Additionally, GrimAge acceleration was identified as a risk factor for lung cancer (OR=1.19 per year; 95% CI 1.06 to 1.34). CONCLUSIONS: While replication in a larger sample size is necessary, our findings suggest that DNAm patterns in prediagnostic oral rinse samples could provide novel insights into the underlying mechanisms of lung cancer in never smokers.

Exposure to smoky coal combustion emissions and leukocyte Alu retroelement copy number.

Household air pollution (HAP) from indoor combustion of solid fuel is a global health burden that has been linked to multiple diseases including lung cancer. In Xuanwei, China, lung cancer rate for non-smoking women is among the highest in the world and largely attributed to high levels of polycyclic aromatic hydrocarbons (PAHs) that are produced from combustion of smoky (bituminous) coal. Alu retroelements, repetitive mobile DNA sequences that can somatically multiply and promote genomic instability have been associated with risk of lung cancer and diesel engine exhaust exposure. We conducted analyses for 160 non-smoking women in an exposure assessment study in Xuanwei, China with a repeat sample from 49 subjects. Quantitative PCR was used to measure Alu repeat copy number relative to albumin gene copy number (Alu/ALB ratio). Associations between clusters derived from predicted levels of 43 HAP constituents, 5-methylchrysene (5-MC), a PAH previously associated with lung cancer in Xuanwei and was selected a priori for analysis, and Alu repeats were analyzed using generalized estimating equations. A cluster of 31 PAHs reflecting current exposure was associated with increased Alu copy number (ß:0.03 per standard deviation change; 95% confidence interval (CI):0.01,0.04; P-value = 2E-04). One compound within this cluster, 5-MC, was also associated with increased Alu copy number (P-value = 0.02). Our findings suggest that exposure to PAHs due to indoor smoky coal combustion may contribute to genomic instability. Additionally, our study provides further support for 5-MC as a prominent carcinogenic component of smoky coal emissions. Further studies are needed to replicate our findings.

A nested case-control study of untargeted albumin adductomics and acute myeloid leukemia.

Environmental exposures often produce reactive electrophiles in vivo, leading to oxidative stress, which plays a major role in carcinogenesis. These electrophiles frequently form adducts with human albumin, which can be measured to assess in vivo oxidative stress. Here, we aimed to examine the associations between circulatory albumin adducts and acute myeloid leukemia (AML), the most common adult myeloid leukemia that showed consistent associations with environmental exposures. We conducted a nested case-control study of 52 incident AML cases and 103 controls matched on age, sex and race within two prospective cohorts: the CLUE and PLCO studies. We measured 42 untargeted albumin adducts in prediagnostic samples using liquid chromatography-high-resolution mass spectrometry. Circulatory albumin adducts were associated with AML in conditional logistic regression models. For instance, higher levels of Cys34 disulfide adduct of the S-γ-glutamylcysteine, a precursor of the essential antioxidant, glutathione were associated with a lower risk of AML (odds ratios [95% confidence intervals]) for the 1st, 2nd and 3rd tertiles were 1.0, 0.65 (0.31-1.36) and 0.31 (0.12-0.80), respectively (P-trend = .01). These associations were largely driven by effects present among cases diagnosed at or above the median follow-up time of 5.5 years. In conclusion, applying a novel approach to characterize exposures in the prediagnostic samples, we found evidence supporting the notion that oxidative stress may play a role in the pathogenesis of AML. Our findings offer insight into AML etiology and may be relevant in identifying novel therapeutic targets.

Exploring preconception signatures of metabolites in mothers with gestational diabetes mellitus using a non-targeted approach.

BACKGROUND: Metabolomic changes during pregnancy have been suggested to underlie the etiology of gestational diabetes mellitus (GDM). However, research on metabolites during preconception is lacking. Therefore, this study aimed to investigate distinctive metabolites during the preconception phase between GDM and non-GDM controls in a nested case-control study in Singapore. METHODS: Within a Singapore preconception cohort, we included 33 Chinese pregnant women diagnosed with GDM according to the IADPSG criteria between 24 and 28 weeks of gestation. We then matched them with 33 non-GDM Chinese women by age and pre-pregnancy body mass index (ppBMI) within the same cohort. We performed a non-targeted metabolomics approach using fasting serum samples collected within 12 months prior to conception. We used generalized linear mixed model to identify metabolites associated with GDM at preconception after adjusting for maternal age and ppBMI. After annotation and multiple testing, we explored the additional predictive value of novel signatures of preconception metabolites in terms of GDM diagnosis. RESULTS: A total of 57 metabolites were significantly associated with GDM, and eight phosphatidylethanolamines were annotated using HMDB. After multiple testing corrections and sensitivity analysis, phosphatidylethanolamines 36:4 (mean difference ß: 0.07; 95% CI: 0.02, 0.11) and 38:6 (ß: 0.06; 0.004, 0.11) remained significantly higher in GDM subjects, compared with non-GDM controls. With all preconception signals of phosphatidylethanolamines in addition to traditional risk factors (e.g., maternal age and ppBMI), the predictive value measured by area under the curve (AUC) increased from 0.620 to 0.843. CONCLUSIONS: Our data identified distinctive signatures of GDM-associated preconception phosphatidylethanolamines, which is of potential value to understand the etiology of GDM as early as in the preconception phase. Future studies with larger sample sizes among alternative populations are warranted to validate the associations of these signatures of metabolites and their predictive value in GDM.

Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA.

BACKGROUND: We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS: In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS: Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1ß (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS: DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.

Trans-ethnic meta-analysis of genome-wide association studies identifies maternal ITPR1 as a novel locus influencing fetal growth during sensitive periods in pregnancy.

Abnormal fetal growth is a risk factor for infant morbidity and mortality and is associated with cardiometabolic diseases in adults. Genetic influences on fetal growth can vary at different gestation times, but genome-wide association studies have been limited to birthweight. We performed trans-ethnic genome-wide meta-analyses and fine mapping to identify maternal genetic loci associated with fetal weight estimates obtained from ultrasound measures taken during pregnancy. Data included 1,849 pregnant women from four race/ethnic groups recruited through the NICHD Fetal Growth Studies. We identified a novel genome-wide significant association of rs746039 [G] (ITPR1) with reduced fetal weight from 24 to 33 weeks gestation (P<5x10-8; log10BF>6). Additional tests revealed that the SNP was associated with head circumference (P = 4.85x10-8), but not with abdominal circumference or humerus/femur lengths. Conditional analysis in an independent sample of mother-offspring pairs replicated the findings and showed that the effect was more likely maternal but not fetal. Trans-ethnic approaches successfully narrowed down the haplotype block that contained the 99% credible set of SNPs associated with head circumference. We further demonstrated that decreased placental expression of ITPR1 was correlated with increased placental epigenetic age acceleration, a risk factor for reduced fetal growth, among male fetuses (r = -0.4, P = 0.01). Finally, genetic risk score composed of known maternal SNPs implicated in birthweight among Europeans was associated with fetal weight from mid-gestation onwards among Whites only. The present study sheds new light on the role of common maternal genetic variants in the inositol receptor signaling pathway on fetal growth from late second trimester to early third trimester. Clinical Trial Registration: ClinicalTrials.gov, NCT00912132.

Admixture mapping identifies African and Amerindigenous local ancestry loci associated with fetal growth.

Fetal growth is an important determinant of cardiometabolic disease risk during childhood and adulthood. The genetic architecture of fetal growth remains largely understudied in ancestrally diverse populations. We conducted genome-wide admixture mapping scan and analysis of genetic ancestry among Hispanic American, African American, European American, and Asian American pregnant women to identify genetic loci associated with fetal growth measures across 13-40 weeks gestation. Fetal growth measures were associated with genome-wide average African, European, Amerindigenous and East Asian ancestry proportions (P ranged from10-3 to 4.8 × 10-2). Admixture mapping analysis identified ten African ancestry loci and three Amerindigenous ancestry loci significantly associated with fetal growth measures at Bonferroni-corrected levels of significance (P ranged from 2.18 × 10-8 to 3.71 × 10-6). At the chr2q23.3-24.2 locus in which higher African ancestry was associated with long bone (femur and humerus) lengths, the T allele of rs13030825 (GALNT13) was associated with longer humerus length in African Americans (ß = 0.44, P = 6.25 × 10-6 at week 27; ß = 0.39, P = 7.72 × 10-5 at week 40). The rs13030825 SNP accounted for most of the admixture association at the chr2q23.3-24.2 locus and has substantial allele frequency difference between African and European reference samples (FST = 0.55, P = 0.03). Regulatory annotation shows that rs13030825 overlaps with the serum response factor (SRF) transcription factor previously implicated in postnatal bone development of mice. Overall, we identified ancestry-related maternal genetic loci that influence fetal growth, shedding light on molecular pathways that regulate fetal growth and potential effects on health across the lifespan.Clinical trials registration ClinicalTrials.gov, NCT00912132.

A prospective study of maternal adiposity and glycemic traits across pregnancy and mid-childhood metabolomic profiles.

BACKGROUND: Fetal exposure to maternal excess adiposity and hyperglycemia is risk factors for childhood adverse metabolic outcomes. Using data from a prospective pre-birth cohort, we aimed to further understand the prenatal determinants of fetal metabolic programming based on analyses of maternal adiposity and glycemic traits across pregnancy with childhood metabolomic profiles. METHODS: This study included 330 mother-child pairs from the Gen3G cohort with information on maternal adiposity and glycemic markers at 5-16 (visit 1) and 24-30 (visit 2) weeks of pregnancy. At mid-childhood (4.8-7.2 years old), we collected fasting plasma and measured 1116 metabolites using an untargeted approach. We constructed networks of interconnected metabolites using a weighted-correlation network analysis algorithm. We estimated Spearman's partial correlation coefficients of maternal adiposity and glycemic traits across pregnancy with metabolite networks and individual metabolites, adjusting for maternal age, gravidity, race/ethnicity, history of smoking, and child's sex and age at blood collection for metabolite measurement. RESULTS: We identified a network of 16 metabolites, primarily glycero-3-phosphoethanolamines (GPE) at mid-childhood that showed consistent negative correlations with maternal body mass index, waist circumference, and body-fat percentage at visits 1 and 2 (ρadjusted = -0.14 to -0.21) and post-challenge glucose levels at visit 2 (ρadjusted = -0.10 to -0.13), while positive correlations with Matsuda index (ρadjusted = 0.13). Within this identified network, 1-palmitoyl-2-decosahexaenoyl-GPE and 1-stearoyl-2-decosahexaenoyl-GPE appeared to be driving the associations. In addition, a network of 89 metabolites, primarily phosphatidylcholines, plasmalogens, sphingomyelins, and ceramides showed consistent negative correlations with insulin at visit 1 and post-challenge glucose at visit 2, while positive correlation with adiponectin at visit 2. CONCLUSIONS: Prenatal exposure to maternal higher adiposity and hyperglycemic traits and lower insulin sensitivity markers were associated with a unique metabolomic pattern characterized by low serum phospho- and sphingolipids in mid-childhood.

Prospective Association Between Manganese in Early Pregnancy and the Risk of Preeclampsia.

BACKGROUND: Manganese, an essential micronutrient, has been found in lower concentrations among women with preeclampsia in cross-sectional and case-control studies without establishment of a temporal relationship. METHODS: We evaluated the prospective association of manganese (in red blood cells) in first trimester of pregnancy with incidence of preeclampsia (ascertained by reviewing medical records) among 1,312 women in eastern Massachusetts (Project Viva, 1999-2002). We used log-binomial regression to examine the manganese-preeclampsia relationship, adjusting for maternal age, race/ethnicity, parity, prepregnancy body mass index, blood pressure, and hematocrit. RESULTS: The median (25th, 75th percentile) manganese concentrationin red blood cells was 16.2 ng/g (13.1, 20.4) and 48 (4%) women developed preeclampsia. We observed an inverse dose-response relationship between manganese and preeclampsia. Compared with women in the lowest tertile, women in the middle manganese tertile had 0.81 times the risk of preeclampsia (95% CI: 0.43, 1.5) and those in the highest tertile had 0.50 (95% CI: 0.25, 0.99) times the risk. CONCLUSIONS: Our results provide insight into a potentially modifiable way to prevent preeclampsia.

Plasma phospholipid n-3 and n-6 polyunsaturated fatty acids in relation to cardiometabolic markers and gestational diabetes: A longitudinal study within the prospective NICHD Fetal Growth Studies.

BACKGROUND: Despite dietary recommendations of polyunsaturated fatty acids (PUFAs) for cardiometabolic health, n-3 and n-6 PUFAs and their interplay in relation to diabetes risk remain debated. Importantly, data among pregnant women are scarce. We investigated individual plasma phospholipid n-3 and n-6 PUFAs in early to midpregnancy in relation to subsequent risk of gestational diabetes mellitus (GDM). METHODS AND FINDINGS: Within the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singleton Cohort (n = 2,802), individual plasma phospholipid n-3 and n-6 PUFAs levels were measured at gestational weeks (GWs) 10-14, 15-26, 23-31, and 33-39 among 107 GDM cases (ascertained on average at GW 27) and 214 non-GDM controls. Conditional logistic regression was used, adjusting for major risk factors for GDM. After adjusting for covariates, individual n-3 eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) were inversely correlated with insulin-resistance markers, whereas individual n-6 dihomo-gamma-linolenic acid (DGLA) was positively correlated with insulin-resistance markers. At GW 15-26, a standard deviation (SD) increase in total n-3 PUFAs and individual n-3 DPA was associated with a 36% (adjusted odds ratio 0.64; 95% CI 0.42-0.96; P = 0.042) and 33% (0.67; 95% CI 0.45-0.99; P = 0.047) lower risk of GDM, respectively; however, the significance did not persist after post hoc false-discovery rate (FDR) correction (FDR-corrected P values > 0.05). Associations between total n-6 PUFAs and GDM were null, whereas associations with individual n-6 PUFAs were differential. Per SD increase, gamma-linolenic acid (GLA) at GWs 10-14 and DGLA at GWs 10-14 and 15-26 were significantly associated with a 1.40- to 1.95-fold higher risk of GDM, whereas docosatetraenoic acid (DTA) at GW 15-26 was associated with a 45% (0.55; 95% CI 0.37-0.83) lower risk of GDM (all FDR-corrected P values < 0.05). Null associations were observed for linoleic acid (LA) in either gestational window in relation to risk of GDM. Women with high (≥median) n-3 PUFAs and low (

A Prospective Cohort Study Examining the Associations of Maternal Arsenic Exposure With Fetal Loss and Neonatal Mortality.

Arsenic crosses the placenta, possibly increasing the risk of adverse reproductive outcomes. We aimed to examine the association between maternal arsenic exposure and fetal/neonatal survival using data from a prospective cohort study of 1,616 maternal-infant pairs recruited at a gestational age of ≤16 weeks in Bangladesh (2008-2011). Arsenic concentration in maternal drinking water was measured at enrollment. Extended Cox regression (both time-dependent coefficients and step functions) was used to estimate the time-varying association between maternal arsenic exposure and fetal/neonatal death (all mortality between enrollment and 1 month after birth). In a sensitivity analysis, we assessed gestational arsenic exposure using maternal urine samples taken at enrollment. We observed 203 fetal losses and 20 neonatal deaths. Higher arsenic exposure was associated with a slightly decreased mortality rate up to the middle of the second trimester, and then the mortality rate switched directions around 20 weeks' gestation. In the step function model, the hazard ratios for combined mortality (fetal loss and neonatal death) per unit increase in the natural log of drinking water arsenic concentration (µg/L) ranged from 1.35 (95% CI: 1.08, 1.69) in weeks 25-28 to 0.81 (95% CI: 0.65, 1.02) in weeks 9-12. This nonlinear association suggests that arsenic may exert survival pressure on developing fetuses, potentially contributing to survival bias, and may also indicate that arsenic toxicity differs by fetal developmental stage.

Plasma metabolomic profile of adiposity and body composition in childhood: The Genetics of Glucose regulation in Gestation and Growth cohort.

OBJECTIVE: This study identified metabolite modules associated with adiposity and body fat distribution in childhood using gold-standard measurements. METHODS: We used cross-sectional data from 329 children at mid-childhood (age 5.3 ± 0.3 years; BMI 15.7 ± 1.5 kg/m2) from the Genetics of Glucose regulation in Gestation and Growth (Gen3G), a prospective pre-birth cohort. We quantified 1038 plasma metabolites and measured body composition using the gold-standard dual-energy x-ray absorptiometry (DXA), in addition to skinfold, waist circumference, and BMI. We applied weighted-correlation network analysis to identify a network of highly correlated metabolite modules. Spearman's partial correlations were applied to determine the associations of adiposity with metabolite modules and individual metabolites with false discovery rate (FDR) correction. RESULTS: We identified a 'green' module of 120 metabolites, primarily comprised of lipids (mostly sphingomyelins and phosphatidylcholine), that showed positive correlations (all FDR p < 0.05) with DXA estimates of total and truncal fat (ρadjusted = 0.11-0.19), skinfold measures (ρadjusted = 0.09-0.26), and BMI and waist circumference (ρadjusted = 0.15 and 0.18, respectively). These correlations were similar when stratified by sex. Within this module, sphingomyelin (d18:2/14:0, d18:1/14:1)*, a sphingomyelin sub-specie that is an important component of cell membranes, showed the strongest associations. CONCLUSIONS: A module of metabolites was associated with adiposity measures in childhood.

Metabolomic Biomarkers of Dietary Approaches to Stop Hypertension (DASH) Dietary Patterns in Pregnant Women.

Objective: the aim of this study was to identify plasma metabolomic markers of Dietary Approaches to Stop Hypertension (DASH) dietary patterns in pregnant women. Methods: This study included 186 women who had both dietary intake and metabolome measured from a nested case-control study within the NICHD Fetal Growth Studies-Singletons cohort (FGS). Dietary intakes were ascertained at 8-13 gestational weeks (GW) using the Food Frequency Questionnaire (FFQ) and DASH scores were calculated based on eight food and nutrient components. Fasting plasma samples were collected at 15-26 GW and untargeted metabolomic profiling was performed. Multivariable linear regression models were used to examine the association of individual metabolites with the DASH score. Least absolute shrinkage and selection operator (LASSO) regression was used to select a panel of metabolites jointly associated with the DASH score. Results: Of the total 460 known metabolites, 92 were individually associated with DASH score in linear regressions, 25 were selected as a panel by LASSO regressions, and 18 were identified by both methods. Among the top 18 metabolites, there were 11 lipids and lipid-like molecules (i.e., TG (49:1), TG (52:2), PC (31:0), PC (35:3), PC (36:4) C, PC (36:5) B, PC (38:4) B, PC (42:6), SM (d32:0), gamma-tocopherol, and dodecanoic acid), 5 organic acids and derivatives (i.e., asparagine, beta-alanine, glycine, taurine, and hydroxycarbamate), 1 organic oxygen compound (i.e., xylitol), and 1 organoheterocyclic compound (i.e., maleimide). Conclusions: our study identified plasma metabolomic markers for DASH dietary patterns in pregnant women, with most of being lipids and lipid-like molecules.

Healthy dietary patterns are associated with exposure to environmental chemicals in a pregnancy cohort.

Healthy dietary patterns, such as the alternate Mediterranean diet and alternate Healthy Eating Index, benefit cardiometabolic health. However, several food components of these dietary patterns are primary sources of environmental chemicals. Here, using data from a racially and ethnically diverse US cohort, we show that healthy dietary pattern scores were positively associated with plasma chemical exposure in pregnancy, particularly for the alternate Mediterranean diet and alternate Healthy Eating Index with polychlorinated biphenyls and per- and poly-fluoroalkyl substances. The associations appeared stronger among Asian and Pacific Islanders. These findings suggest that optimizing the benefits of a healthy diet requires concerted regulatory efforts aimed at lowering environmental chemical exposure.

Longitudinal lipidomic profiles during pregnancy and associations with neonatal anthropometry: findings from a multiracial cohort.

BACKGROUND: Maternal lipidomic profiling offers promise for characterizing lipid metabolites during pregnancy, but longitudinal data are limited. This study aimed to examine associations of longitudinal lipidomic profiles during pregnancy with multiple neonatal anthropometry using data from a multiracial cohort. METHODS: We measured untargeted plasma lipidome profiles among 321 pregnant women from the NICHD Fetal Growth Study-Singletons using plasma samples collected longitudinally during four study visits at gestational weeks (GW) 10-14, 15-26, 23-31, and 33-39, respectively. We evaluated individual lipidomic metabolites at each study visit in association with neonatal anthropometry. We also evaluated the associations longitudinally by constructing lipid networks using weighted correlation network analysis and common networks using consensus network analysis across four visits using linear mixed-effects models with the adjustment of false discover rate. FINDINGS: Multiple triglycerides (TG) were positively associated with birth weight (BW), BW Z-score, length and head circumference, while some cholesteryl ester (CE), phosphatidylcholine (PC), sphingomyelines (SM), phosphatidylethanolamines (PE), and lysophosphatidylcholines (LPC 20:3) families were inversely associated with BW, length, abdominal and head circumference at different GWs. Longitudinal trajectories of TG, PC, and glucosylcermides (GlcCer) were associated with BW, and CE (18:2) with BW z-score, length, and sum of skinfolds (SS), while some PC and PE were significantly associated with abdominal and head circumference. Modules of TG at GW 10-14 and 15-26 mainly were associated with BW. At GW 33-39, two networks of LPC (20:3) and of PC, TG, and CE, showed inverse associations with abdominal circumference. Distinct trajectories within two consensus modules with changes in TG, CE, PC, and LPC showed significant differences in BW and length. INTERPRETATION: The results demonstrated that longitudinal changes of TGs during early- and mid-pregnancy and changes of PC, LPC, and CE during late-pregnancy were significantly associated with neonatal anthropometry. FUNDING: National Institute of Child Health and Human Development intramural funding.

Associations between Longer Leukocyte Telomere Length and Increased Lung Cancer Risk among Never Smokers in Urban China.

BACKGROUND: The complex relationship between measured leukocyte telomere length (LTL), genetically predicted LTL (gTL), and carcinogenesis is exemplified by lung cancer. We previously reported associations between longer pre-diagnostic LTL, gTL, and increased lung cancer risk among European and East Asian populations. However, we had limited statistical power to examine the associations among never smokers by gender and histology. METHODS: To investigate further, we conducted nested case-control analyses on an expanded sample of never smokers from the prospective Shanghai Women's Health Studies (798 cases and 792 controls) and Shanghai Men's Health Studies (161 cases and 162 controls). We broke the case-control matching and used multivariable unconditional logistic regression models to estimate the ORs and 95% confidence intervals (CI) of incident lung cancer and adenocarcinoma (LUAD), in relation to LTL measured using quantitative PCR and gTL determined using a polygenic score. In addition, we conducted Mendelian randomization (MR) using MR-PRESSO. RESULTS: We found striking dose-response relationships between longer LTL and gTL, and increased lung cancer risk among never-smoking women (P trendLTL = 4×10-6; P trendgTL = 3×10-4). Similarly, among never-smoking men, longer measured LTL was associated with over triple the risk compared with those with the shortest (OR, 3.48; 95% CI, 1.85-6.57). The overall results were similar for LUAD among women and men. MR analyses supported causal associations with LUAD among women (OR1 SD gTL, 1.19; 95% CI, 1.03-1.37; P = 0.03). CONCLUSIONS: Longer pre-diagnostic LTL is associated with increased lung cancer risk among never smokers. IMPACT: Our findings firmly support the role of longer telomeres in lung carcinogenesis.

Metabolomic biomarkers of the mediterranean diet in pregnant individuals: A prospective study.

BACKGROUND AND AIMS: Metabolomic profiling is a systematic approach to identifying biomarkers for dietary patterns. Yet, metabolomic markers for dietary patterns in pregnant individuals have not been investigated. The aim of this study was to identify plasma metabolomic markers and metabolite panels that are associated with the Mediterranean diet in pregnant individuals. METHODS: This is a prospective study of 186 pregnant individuals who had both dietary intake and metabolomic profiles measured from the Fetal Growth Studies-Singletons cohort. Dietary intakes during the peri-conception/1st trimester and the second trimester were accessed at 8-13 and 16-22 weeks of gestation, respectively. Adherence to the Mediterranean diet was measured by the alternate Mediterranean Diet (aMED) score. Fasting plasma samples were collected at 16-22 weeks and untargeted metabolomics profiling was performed using the mass spectrometry-based platforms. Metabolites individually or jointly associated with aMED scores were identified using linear regression and least absolute shrinkage and selection operator (LASSO) regression models with adjustment for potential confounders, respectively. RESULTS: Among 459 annotated metabolites, 64 and 41 were individually associated with the aMED scores of the diet during the peri-conception/1st trimester and during the second trimester, respectively. Fourteen metabolites were associated with the Mediterranean diet in both time windows. Most Mediterranean diet-related metabolites were lipids (e.g., acylcarnitine, cholesteryl esters (CEs), linoleic acid, long-chain triglycerides (TGs), and phosphatidylcholines (PCs), amino acids, and sugar alcohols. LASSO regressions also identified a 10 metabolite-panel that were jointly associated with aMED score of the diet during the peri-conception/1st trimester (AUC: 0.74; 95% CI: 0.57, 0.91) and a 3 metabolites-panel in the 2nd trimester (AUC: 0.68; 95% CI: 0.50, 0.86). CONCLUSION: We identified plasma metabolomic markers for the Mediterranean diet among pregnant individuals. Some of them have also been reported in previous studies among non-pregnant populations, whereas others are novel. The results from our study warrant replication in pregnant individuals by future studies. CLINICAL TRIAL REGISTRATION NUMBER: This study was registered at ClinicalTrials.gov.