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1.
JCI Insight ; 5(3)2020 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-32051340

RESUMO

Few therapeutic methods exist for preventing preterm birth (PTB), or delivery before completing 37 weeks of gestation. In the US, progesterone (P4) supplementation is the only FDA-approved drug for use in preventing recurrent spontaneous PTB. However, P4 has limited effectiveness, working in only approximately one-third of cases. Computational drug repositioning leverages data on existing drugs to discover novel therapeutic uses. We used a rank-based pattern-matching strategy to compare the differential gene expression signature for PTB to differential gene expression drug profiles in the Connectivity Map database and assigned a reversal score to each PTB-drug pair. Eighty-three drugs, including P4, had significantly reversed differential gene expression compared with that found for PTB. Many of these compounds have been evaluated in the context of pregnancy, with 13 belonging to pregnancy category A or B - indicating no known risk in human pregnancy. We focused our validation efforts on lansoprazole, a proton-pump inhibitor, which has a strong reversal score and a good safety profile. We tested lansoprazole in an animal inflammation model using LPS, which showed a significant increase in fetal viability compared with LPS treatment alone. These promising results demonstrate the effectiveness of the computational drug repositioning pipeline to identify compounds that could be effective in preventing PTB.

2.
Am J Clin Nutr ; 111(1): 110-121, 2020 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-31764942

RESUMO

BACKGROUND: Transporter-mediated drug-nutrient interactions have the potential to cause serious adverse events. However, unlike drug-drug interactions, these drug-nutrient interactions receive little attention during drug development. The clinical importance of drug-nutrient interactions was highlighted when a phase III clinical trial was terminated due to severe adverse events resulting from potent inhibition of thiamine transporter 2 (ThTR-2; SLC19A3). OBJECTIVE: In this study, we tested the hypothesis that therapeutic drugs inhibit the intestinal thiamine transporter ThTR-2, which may lead to thiamine deficiency. METHODS: For this exploration, we took a multifaceted approach, starting with a high-throughput in vitro primary screen to identify inhibitors, building in silico models to characterize inhibitors, and leveraging real-world data from electronic health records to begin to understand the clinical relevance of these inhibitors. RESULTS: Our high-throughput screen of 1360 compounds, including many clinically used drugs, identified 146 potential inhibitors at 200 µM. Inhibition kinetics were determined for 28 drugs with half-maximal inhibitory concentration (IC50) values ranging from 1.03 µM to >1 mM. Several oral drugs, including metformin, were predicted to have intestinal concentrations that may result in ThTR-2-mediated drug-nutrient interactions. Complementary analysis using electronic health records suggested that thiamine laboratory values are reduced in individuals receiving prescription drugs found to significantly inhibit ThTR-2, particularly in vulnerable populations (e.g., individuals with alcoholism). CONCLUSIONS: Our comprehensive analysis of prescription drugs suggests that several marketed drugs inhibit ThTR-2, which may contribute to thiamine deficiency, especially in at-risk populations.

3.
Sci Data ; 6(1): 201, 2019 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-31615985

RESUMO

The identification of novel disease associations using big-data for patient care has had limited success. In this study, we created a longitudinal disease network of traced readmissions (disease trajectories), merging data from over 10.4 million inpatients through the Healthcare Cost and Utilization Project, which allowed the representation of disease progression mapping over 300 diseases. From these disease trajectories, we discovered an interesting association between schizophrenia and rhabdomyolysis, a rare muscle disease (incidence < 1E-04) (relative risk, 2.21 [1.80-2.71, confidence interval = 0.95], P-value 9.54E-15). We validated this association by using independent electronic medical records from over 830,000 patients at the University of California, San Francisco (UCSF) medical center. A case review of 29 rhabdomyolysis incidents in schizophrenia patients at UCSF demonstrated that 62% are idiopathic, without the use of any drug known to lead to this adverse event, suggesting a warning to physicians to watch for this unexpected risk of schizophrenia. Large-scale analysis of disease trajectories can help physicians understand potential sequential events in their patients.

4.
Artigo em Inglês | MEDLINE | ID: mdl-31587401

RESUMO

OBJECTIVE: We sought to develop a machine learning (ML) model for prediction of shoulder dystocia (ShD) and to externally validate the model accuracy and potential clinical efficacy in optimizing the use of cesarean delivery (CD) in the context of suspected macrosomia. STUDY DESIGN: We used electronic health records (EHR) from the Sheba Medical Center in Israel to develop the model (derivation cohort) and EHR from the University of California San Francisco Medical Center to validate the model accuracy and clinical efficacy (validation cohort). Subsequent to inclusion and exclusion criteria, the derivation cohort consisted of 686 deliveries [131 complicated by ShD], and the validation cohort of 2,584 deliveries [31 complicated by ShD]. For each of these deliveries, we collected maternal and neonatal delivery outcomes coupled with maternal demographics, obstetric clinical data and sonographic biometric measurements of the fetus. Biometric measurements and their derived estimated fetal weight were adjusted (aEFW) to the date of the delivery. A ML pipeline was utilized to develop the model. RESULTS: In the derivation cohort, the ML model provided significantly better prediction than the current paradigm: using nested cross validation the area under the receiver operator characteristics curve (AUC) of the model was 0.793 ± 0.041, outperforming aEFW and diabetes (0.745 ± 0.044, p-value = 1e-16). The following risk modifiers had a positive beta > 0.02 increasing the risk of ShD: aEFW (0.164), pregestational diabetes (0.047), prior ShD (0.04), female fetal sex (0.04) and adjusted abdominal circumference (0.03). The following risk modifiers had a negative beta < -0.02 protective of ShD: adjusted biparietal diameter (-0.08) and maternal height (-0.03). In the validation cohort the model outperformed aEFW and diabetes (AUC = 0.866 vs. 0.784, p-value = 0.00007). Additionally, in the validation cohort, among the subgroup of 273 women carrying a fetus with aEFW above 4,000 g, the aEFW had no predictive power (AUC = 0.548), and the model performed significantly better (0.775, p-value = 0.0002). A risk-score threshold of 0.5 stratified 42.9% of deliveries to the high-risk group that included 90.9% of ShD cases and all cases accompanied by maternal or newborn complications. A more specific threshold of 0.7 stratified only 27.5% of the deliveries to the high-risk groups that included 72.7% of ShD cases, and all those accompanied by newborn complications. CONCLUSION: We developed a ML model for prediction of ShD. We externally validated the model performance in a different cohort. The model predicted ShD better than EFW+ maternal diabetes and was able to stratify the risk of ShD and neonatal injury in the context of suspected macrosomia. This article is protected by copyright. All rights reserved.

5.
Proc Natl Acad Sci U S A ; 116(37): 18517-18527, 2019 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-31455730

RESUMO

How pathogenic cluster of differentiation 4 (CD4) T cells in rheumatoid arthritis (RA) develop remains poorly understood. We used Nur77-a marker of T cell antigen receptor (TCR) signaling-to identify antigen-activated CD4 T cells in the SKG mouse model of autoimmune arthritis and in patients with RA. Using a fluorescent reporter of Nur77 expression in SKG mice, we found that higher levels of Nur77-eGFP in SKG CD4 T cells marked their autoreactivity, arthritogenic potential, and ability to more readily differentiate into interleukin-17 (IL-17)-producing cells. The T cells with increased autoreactivity, nonetheless had diminished ex vivo inducible TCR signaling, perhaps reflective of adaptive inhibitory mechanisms induced by chronic autoantigen exposure in vivo. The enhanced autoreactivity was associated with up-regulation of IL-6 cytokine signaling machinery, which might be attributable, in part, to a reduced amount of expression of suppressor of cytokine signaling 3 (SOCS3)-a key negative regulator of IL-6 signaling. As a result, the more autoreactive GFPhi CD4 T cells from SKGNur mice were hyperresponsive to IL-6 receptor signaling. Consistent with findings from SKGNur mice, SOCS3 expression was similarly down-regulated in RA synovium. This suggests that despite impaired TCR signaling, autoreactive T cells exposed to chronic antigen stimulation exhibit heightened sensitivity to IL-6, which contributes to the arthritogenicity in SKG mice, and perhaps in patients with RA.

6.
Nat Commun ; 10(1): 3902, 2019 08 29.
Artigo em Inglês | MEDLINE | ID: mdl-31467281

RESUMO

Systemic lupus erythematous (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. Here, we aim to identify SLE subgroups within a multiethnic cohort using an unsupervised clustering approach based on the American College of Rheumatology (ACR) classification criteria. We identify three patient clusters that vary according to disease severity. Methylation association analysis identifies a set of 256 differentially methylated CpGs across clusters, including 101 CpGs in genes in the Type I Interferon pathway, and we validate these associations in an external cohort. A cis-methylation quantitative trait loci analysis identifies 744 significant CpG-SNP pairs. The methylation signature is enriched for ethnic-associated CpGs suggesting that genetic and non-genetic factors may drive outcomes and ethnic-associated methylation differences. Our computational approach highlights molecular differences associated with clusters rather than single outcome measures. This work demonstrates the utility of applying integrative methods to address clinical heterogeneity in multifactorial multi-ethnic disease settings.


Assuntos
Biologia Computacional , Grupos Étnicos/genética , Genômica , Lúpus Eritematoso Sistêmico/genética , Família Multigênica , Estudos de Coortes , Metilação de DNA , Epigenômica , Feminino , Estudos de Associação Genética , Genótipo , Humanos , Masculino , Locos de Características Quantitativas , Índice de Gravidade de Doença , Estados Unidos
7.
Trends Pharmacol Sci ; 40(8): 565-576, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31326236

RESUMO

Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.

8.
Nat Commun ; 10(1): 1906, 2019 04 23.
Artigo em Inglês | MEDLINE | ID: mdl-31015506

RESUMO

Studying immune repertoire in the context of organ transplant provides important information on how adaptive immunity may contribute and modulate graft rejection. Here we characterize the peripheral blood immune repertoire of individuals before and after kidney transplant using B cell receptor sequencing in a longitudinal clinical study. Individuals who develop rejection after transplantation have a more diverse immune repertoire before transplant, suggesting a predisposition for post-transplant rejection risk. Additionally, over 2 years of follow-up, patients who develop rejection demonstrate a specific set of expanded clones that persist after the rejection. While there is an overall reduction of peripheral B cell diversity, likely due to increased general immunosuppression exposure in this cohort, the detection of specific IGHV gene usage across all rejecting patients supports that a common pool of immunogenic antigens may drive post-transplant rejection. Our findings may have clinical implications for the prediction and clinical management of kidney transplant rejection.


Assuntos
Linfócitos B/imunologia , Rejeição de Enxerto/imunologia , Hospedeiro Imunocomprometido , Transplante de Rim , Polimorfismo Genético/imunologia , Receptores de Antígenos de Linfócitos B/imunologia , Insuficiência Renal Crônica/imunologia , Adolescente , Adulto , Linfócitos B/patologia , Criança , Pré-Escolar , Células Clonais , Feminino , Expressão Gênica , Rejeição de Enxerto/genética , Rejeição de Enxerto/patologia , Sobrevivência de Enxerto/genética , Humanos , Lactente , Rim/imunologia , Rim/patologia , Rim/cirurgia , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Receptores de Antígenos de Linfócitos B/genética , Insuficiência Renal Crônica/genética , Insuficiência Renal Crônica/patologia , Insuficiência Renal Crônica/cirurgia , Análise de Sequência de DNA
9.
JAMA Netw Open ; 2(4): e191851, 2019 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-30977847

RESUMO

Importance: There are limited resources providing postdonation conditions that can occur in living donors (LDs) of solid-organ transplant. Consequently, it is difficult to visualize and understand possible postdonation outcomes in LDs. Objective: To assemble an open access resource that is representative of the demographic characteristics in the US national registry, maintained by the Organ Procurement and Transplantation Network and administered by the United Network for Organ Sharing, but contains more follow-up information to help to examine postdonation outcomes in LDs. Design, Setting, and Participants: Cohort study in which the data for the resource and analyses stemmed from the transplant data set derived from 27 clinical studies from the ImmPort database, which is an open access repository for clinical studies. The studies included data collected from 1963 to 2016. Data from the United Network for Organ Sharing Organ Procurement and Transplantation Network national registry collected from October 1987 to March 2016 were used to determine representativeness. Data analysis took place from June 2016 to May 2018. Data from 20 ImmPort clinical studies (including clinical trials and observational studies) were curated, and a cohort of 11 263 LDs was studied, excluding deceased donors, LDs with 95% or more missing data, and studies without a complete data dictionary. The harmonization process involved the extraction of common features from each clinical study based on categories that included demographic characteristics as well as predonation and postdonation data. Main Outcomes and Measures: Thirty-six postdonation events were identified, represented, and analyzed via a trajectory network analysis. Results: The curated data contained 10 869 living kidney donors (median [interquartile range] age, 39 [31-48] years; 6175 [56.8%] women; and 9133 [86.6%] of European descent). A total of 9558 living kidney donors with postdonation data were analyzed. Overall, 1406 LDs (14.7%) had postdonation events. The 4 most common events were hypertension (806 [8.4%]), diabetes (190 [2.0%]), proteinuria (171 [1.8%]), and postoperative ileus (147 [1.5%]). Relatively few events (n = 269) occurred before the 2-year postdonation mark. Of the 1746 events that took place 2 years or more after donation, 1575 (90.2%) were nonsurgical; nonsurgical conditions tended to occur in the wide range of 2 to 40 years after donation (odds ratio, 38.3; 95% CI, 4.12-1956.9). Conclusions and Relevance: Most events that occurred more than 2 years after donation were nonsurgical and could occur up to 40 years after donation. Findings support the construction of a national registry for long-term monitoring of LDs and confirm the value of secondary reanalysis of clinical studies.

10.
J Reprod Immunol ; 132: 16-20, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30852461

RESUMO

PROBLEM: Preterm birth (PTB), or the delivery of an infant prior to 37 weeks of gestation, is a major health concern. Although a variety of social, environmental, and maternal factors have been implicated in PTB, causes of preterm labor have remained largely unknown. There is evidence of effectiveness and safety of influenza vaccination during pregnancy, however fewer studies have looked at vaccination response as an indicator of an innate host response that may be associated with adverse pregnancy outcomes. We carried out a pilot study to analyze the flu vaccine response during pregnancy of women who later deliver preterm or term. METHOD OF STUDY: We performed a secondary analysis of the individual-level data from an influenza vaccination response study (openly available from ImmPort) measured by hemagglutination inhibition assay of 91 pregnant women with term deliveries and 11 women who went on to deliver preterm. Flu vaccination responses for H1N1 and H3N2 influenza strains were compared between term and preterm deliveries. RESULTS: Women who went on to deliver preterm showed a significantly (P < 0.001) greater flu vaccine response for the H1N1 strain than women who delivered at term. The vaccine response for H3N2 was not significantly different between these two groups (P = 0.97). CONCLUSIONS: Although the sample size is limited and additional validation is required, our findings suggest an increased activation of the maternal immune system as shown by the stronger vaccination response to H1N1 in women who subsequently delivered preterm, in comparison to women who delivered at term.

11.
Bioinformatics ; 35(1): 95-103, 2019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30561547

RESUMO

Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information: Supplementary data are available at Bioinformatics online.


Assuntos
Metaboloma , Microbiota , Gravidez , Proteoma , Transcriptoma , Biologia Computacional , Feminino , Humanos
12.
Sci Data ; 5(1): 3, 2018 12 18.
Artigo em Inglês | MEDLINE | ID: mdl-30563979

RESUMO

The original version of the Data Descriptor contained errors in the author list and affiliations. Rita Leite's first name was misspelled as "Rite" and affiliations 4 and 5 were incorrectly swapped. In addition, members of the March of Dimes Prematurity Research Center consortium were not listed in the agreed positions within the author list. These errors have now been corrected in the HTML and PDF versions.

13.
Sci Data ; 5: 180219, 2018 11 06.
Artigo em Inglês | MEDLINE | ID: mdl-30398470

RESUMO

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research.

14.
Eur J Obstet Gynecol Reprod Biol ; 231: 235-240, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30439652

RESUMO

Objective To develop a pre-pregnancy or first-trimester risk score to identify women at high risk of preterm birth. Study design In this retrospective cohort analysis, the sample was drawn from California singleton livebirths from 2007 to 2012 with linked birth certificate and hospital discharge records. The dataset was divided into a training (2/3 of sample) and a testing (1/3 of sample) set for discovery and validation. Predictive models for preterm birth using pre-pregnancy or first-trimester maternal factors were developed using backward stepwise logistic regression on a training dataset. A risk score for preterm birth was created for each pregnancy using beta-coefficients for each maternal factor remaining in the final multivariable model. Risk score utility was replicated in a testing dataset and by race/ethnicity and payer for prenatal care. Results The sample included 2,339,696 pregnancies divided into training and testing datasets. Twenty-three maternal risk factors were identified including several that were associated with a two or more increased odds of preterm birth (preexisting diabetes, preexisting hypertension, sickle cell anemia, and previous preterm birth). Approximately 40% of women with a risk score ≥ 3.0 in the training and testing samples delivered preterm (40.6% and 40.8%, respectively) compared to 3.1-3.3% of women with a risk score of 0.0 [odds ratio (OR) 13.0, 95% confidence interval (CI) 10.7-15.8, training; OR 12.2, 95% CI 9.4-15.9, testing). Additionally, over 18% of women with a risk score ≥ 3.0 had an adverse outcome other than preterm birth. Conclusion Maternal factors that are identifiable prior to pregnancy or during the first-trimester can be used create a cumulative risk score to identify women at the lowest and highest risk for preterm birth regardless of race/ethnicity or socioeconomic status. Further, we found that this cumulative risk score could also identify women at risk for other adverse outcomes who did not have a preterm birth. The risk score is not an effective screening test, but does identify women at very high risk of a preterm birth.


Assuntos
Primeiro Trimestre da Gravidez , Gravidez de Alto Risco , Nascimento Prematuro/etiologia , Cuidado Pré-Natal , Adolescente , Adulto , California , Feminino , Humanos , Recém-Nascido , Idade Materna , Gravidez , Resultado da Gravidez , Estudos Retrospectivos , Medição de Risco , Fatores de Risco , Adulto Jovem
15.
Environ Int ; 121(Pt 2): 1066-1078, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30075861

RESUMO

BACKGROUND: Preterm birth (PTB),2 defined as birth at gestational age <37 weeks, is a major public health concern. Infants born prematurely, comprising of about 10% of the US newborns, have elevated risks of neonatal mortality and a wide array of health problems. Although numerous clinical, genetic, environmental and socioeconomic factors have been implicated in PTB, very few studies investigate the impacts of multiple pollutants and social factors on PTB using large scale datasets. OBJECTIVES: To evaluate association between environmental and socioeconomic factors and PTB in California. METHODS: We linked the birth cohort file maintained by the California Office of Statewide Health Planning and Development from 2009 to 2012 years across 1.8 million births and the CalEnviroScreen 3.0 dataset from California Communities Environmental Health Screening Tool at the census tract level for 56 California counties. CalEnviroScreen contains 7 exposure and 5 environmental effects variables that constitute the Pollution Burden variable, and 5 socioeconomic variables. We evaluated relationships between environmental exposures and the risk of PTB using hierarchical clustering analyses and GIS-based visualization. We also used logistic regression to evaluate the relationship between specific pollutant and exposure indicators and PTB, accounted for socio-demographic determinants such as maternal race/ethnicity, maternal age, maternal education and payment of delivery costs. RESULTS: There exists geographic variability in PTB for groups of counties with similar environmental and social exposure profiles. We found an association between Pollution Burden, particulate matter ≤2.5 µm (PM2.5), and Drinking Water Scores and PTB (adjusted odds ratios were 1.03 (95% Confidence Interval (CI): 1.01, 1.04), 1.03 (95% CI: 1.02,1.04), and 1.04 (95% CI: 1.03,1.05), respectively). Additional findings suggest that certain drinking water contaminants such as arsenic and nitrate are associated with PTB in California. CONCLUSIONS: CalEnviroScreen data combined with birth records offer great opportunity for revealing novel exposures and evaluating cumulative exposures related to PTB by providing useful environmental and social information. Certain drinking water contaminants such as arsenic and nitrate are potentially associated with PTB in California and should be investigated further. Small association signals may involve sizeable population impacts.


Assuntos
Exposição Ambiental , Nascimento Prematuro/epidemiologia , California/epidemiologia , Exposição Ambiental/análise , Exposição Ambiental/estatística & dados numéricos , Feminino , Humanos , Recém-Nascido , Gravidez , Fatores Socioeconômicos
16.
Environ Health ; 17(1): 70, 2018 08 29.
Artigo em Inglês | MEDLINE | ID: mdl-30157858

RESUMO

BACKGROUND: Environmental pollution exposure during pregnancy has been identified as a risk factor for preterm birth. Most studies have evaluated exposures individually and in limited study populations. METHODS: We examined the associations between several environmental exposures, both individually and cumulatively, and risk of preterm birth in Fresno County, California. We also evaluated early (< 34 weeks) and spontaneous preterm birth. We used the Communities Environmental Health Screening Tool and linked hospital discharge records by census tract from 2009 to 2012. The environmental factors included air pollution, drinking water contaminants, pesticides, hazardous waste, traffic exposure and others. Social factors, including area-level socioeconomic status (SES) and race/ethnicity were also evaluated as potential modifiers of the relationship between pollution and preterm birth. RESULTS: In our study of 53,843 births, risk of preterm birth was associated with higher exposure to cumulative pollution scores and drinking water contaminants. Risk of preterm birth was twice as likely for those exposed to high versus low levels of pollution. An exposure-response relationship was observed across the quintiles of the pollution burden score. The associations were stronger among early preterm births in areas of low SES. CONCLUSIONS: In Fresno County, we found multiple pollution exposures associated with increased risk for preterm birth, with higher associations among the most disadvantaged. This supports other evidence finding environmental exposures are important risk factors for preterm birth, and furthermore the burden is higher in areas of low SES. This data supports efforts to reduce the environmental burden on pregnant women.


Assuntos
Poluentes Ambientais/efeitos adversos , Poluição Ambiental/efeitos adversos , Resultado da Gravidez/epidemiologia , Nascimento Prematuro/epidemiologia , Fatores Socioeconômicos , Adolescente , Adulto , California/epidemiologia , Exposição Ambiental/efeitos adversos , Feminino , Humanos , Gravidez , Nascimento Prematuro/induzido quimicamente , Prevalência , Fatores de Risco , Adulto Jovem
17.
Environ Health Perspect ; 126(7): 077009, 2018 07.
Artigo em Inglês | MEDLINE | ID: mdl-30044231

RESUMO

BACKGROUND: In utero exposure to environmental chemicals can adversely impact pregnancy outcomes and childhood health, but minimal biomonitoring data exist on the majority of chemicals used in commerce. OBJECTIVES: We aimed to profile exposure to multiple environmental organic acids (EOAs) and identify novel chemicals that have not been previously biomonitored in a diverse population of pregnant women. METHODS: We used liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) to perform a suspect screen for 696 EOAs, (e.g., phenols and phthalate metabolites) on the maternal serum collected at delivery from 75 pregnant women delivering at two large San Francisco Hospitals. We examined demographic differences in peak areas and detection frequency (DF) of suspect EOAs using a Kruskal-Wallis Rank Sum test or Fisher's exact test. We confirmed selected suspects by comparison with their respective reference standards. RESULTS: We detected, on average, 56 [standard deviation (SD)]: 8) suspect EOAs in each sample (range: 32-73). Twelve suspect EOAs with DF≥60 were matched to 21 candidate compounds in our EOA database, two-thirds of which are novel chemicals. We found demographic differences in DF for 13 suspect EOAs and confirmed the presence of 6 priority novel chemicals: 2,4-Di-tert-butylphenol, Pyrocatechol, 2,4-Dinitrophenol, 3,5-Di-tert-butylsalicylic acid, 4-Hydroxycoumarin, and 2'-Hydroxyacetophenone (or 3'-Hydroxyacetophenone). The first two are high-production-volume chemicals in the United States. CONCLUSION: Suspect screening in human biomonitoring provides a viable method to characterize a broad spectrum of environmental chemicals to prioritize for targeted method development and quantification. https://doi.org/10.1289/EHP2920.


Assuntos
Ácidos/análise , Monitoramento Ambiental/métodos , Poluentes Ambientais/análise , Compostos Orgânicos/análise , Adulto , Cromatografia Líquida , Feminino , Humanos , Espectrometria de Massas , Pessoa de Meia-Idade , Gravidez , Gestantes , São Francisco , Adulto Jovem
19.
Front Immunol ; 9: 993, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29867970

RESUMO

Preterm birth (PTB) is the leading cause of newborn deaths around the world. Spontaneous preterm birth (sPTB) accounts for two-thirds of all PTBs; however, there remains an unmet need of detecting and preventing sPTB. Although the dysregulation of the immune system has been implicated in various studies, small sizes and irreproducibility of results have limited identification of its role. Here, we present a cross-study meta-analysis to evaluate genome-wide differential gene expression signals in sPTB. A comprehensive search of the NIH genomic database for studies related to sPTB with maternal whole blood samples resulted in data from three separate studies consisting of 339 samples. After aggregating and normalizing these transcriptomic datasets and performing a meta-analysis, we identified 210 genes that were differentially expressed in sPTB relative to term birth. These genes were enriched in immune-related pathways, showing upregulation of innate immunity and downregulation of adaptive immunity in women who delivered preterm. An additional analysis found several of these differentially expressed at mid-gestation, suggesting their potential to be clinically relevant biomarkers. Furthermore, a complementary analysis identified 473 genes differentially expressed in preterm cord blood samples. However, these genes demonstrated downregulation of the innate immune system, a stark contrast to findings using maternal blood samples. These immune-related findings were further confirmed by cell deconvolution as well as upstream transcription and cytokine regulation analyses. Overall, this study identified a strong immune signature related to sPTB as well as several potential biomarkers that could be translated to clinical use.


Assuntos
Imunidade Adaptativa/genética , Feto/imunologia , Imunidade Inata/genética , Mães , Nascimento Prematuro/imunologia , Transcriptoma , Biomarcadores/sangue , Citocinas/genética , Citocinas/imunologia , Regulação para Baixo , Feminino , Sangue Fetal/imunologia , Regulação da Expressão Gênica , Humanos , Recém-Nascido , Gravidez , Regulação para Cima
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