Roberto Romero

Bio: Roberto Romero is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Amniotic fluid & Chorioamnionitis. The author has an hindex of 151, co-authored 1516 publications receiving 108321 citations. Previous affiliations of Roberto Romero include University of Michigan & Weizmann Institute of Science.

Characterization of the fetal blood transcriptome and proteome in maternal anti-fetal rejection: evidence of a distinct and novel type of human fetal systemic inflammatory response.

Abstract: Background The human fetus is able to mount a systemic inflammatory response when exposed to microorganisms. This stereotypic response has been termed the ‘fetal inflammatory response syndrome’ (FIRS), defined as an elevation of fetal plasma interleukin-6 (IL-6). FIRS is frequently observed in patients whose preterm deliveries are associated with intra-amniotic infection, acute inflammatory lesions of the placenta, and a high rate of neonatal morbidity. Recently, a novel form of fetal systemic inflammation, characterized by an elevation of fetal plasma CXCL10, has been identified in patients with placental lesions consistent with ‘maternal anti-fetal rejection’. These lesions include chronic chorioamnionitis, plasma cell deciduitis, and villitis of unknown etiology. In addition, positivity for human leukocyte antigen (HLA) panel-reactive antibodies (PRA) in maternal sera can also be used to increase the index of suspicion for maternal anti-fetal rejection. The purpose of this study was to determine (i) the frequency of pathologic lesions consistent with maternal anti-fetal rejection in term and spontaneous preterm births; (ii) the fetal serum concentration of CXCL10 in patients with and without evidence of maternal anti-fetal rejection; and (iii) the fetal blood transcriptome and proteome in cases with a fetal inflammatory response associated with maternal anti-fetal rejection. Method of study Maternal and fetal sera were obtained from normal term (n = 150) and spontaneous preterm births (n = 150). A fetal inflammatory response associated with maternal anti-fetal rejection was diagnosed when the patients met two or more of the following criteria: (i) presence of chronic placental inflammation; (ii) ≥80% of maternal HLA class I PRA positivity; and (iii) fetal serum CXCL10 concentration >75th percentile. Maternal HLA PRA was analyzed by flow cytometry. The concentrations of fetal CXCL10 and IL-6 were determined by ELISA. Transcriptome analysis was undertaken after the extraction of total RNA from white blood cells with a whole-genome DASL assay. Proteomic analysis of fetal serum was conducted by two-dimensional difference gel electrophoresis. Differential gene expression was considered significant when there was a P 1.5. Results (i) The frequency of placental lesions consistent with maternal anti-fetal rejection was higher in patients with preterm deliveries than in those with term deliveries (56% versus 32%; P < 0.001); (ii) patients with spontaneous preterm births had a higher rate of maternal HLA PRA class I positivity than those who delivered at term (50% versus 32%; P = 0.002); (iii) fetuses born to mothers with positive maternal HLA PRA results had a higher median serum CXCL10 concentration than those with negative HLA PRA results (P < 0.001); (iv) the median serum CXCL10 concentration (but not IL-6) was higher in fetuses with placental lesions associated with maternal anti-fetal rejection than those without such lesions (P < 0.001); (v) a whole-genome DASL assay of fetal blood RNA demonstrated differential expression of 128 genes between fetuses with and without lesions associated with maternal anti-fetal rejection; and (vi) comparison of the fetal serum proteome demonstrated 20 proteins whose abundance differed between fetuses with and without lesions associated with maternal anti-fetal rejection. Conclusion We describe a systemic inflammatory response in human fetuses born to mothers with evidence of maternal anti-fetal rejection. The transcriptome and proteome of this novel type of fetal inflammatory response were different from that of FIRS type I (which is associated with acute infection/inflammation).

Inflammation-Induced Adverse Pregnancy and Neonatal Outcomes Can Be Improved by the Immunomodulatory Peptide Exendin-4.

Abstract: Preterm birth is the leading cause of neonatal morbidity and mortality worldwide. Inflammation is causally linked to preterm birth; therefore, finding an intervention that dampens maternal and fetal inflammatory responses may provide a new strategy to prevent adverse pregnancy and neonatal outcomes. Using animal models of systemic maternal inflammation [intraperitoneal injection of lipopolysaccharide (LPS)] and fetal inflammation (intra-amniotic administration of LPS), we found that (1) systemic inflammation induced adverse pregnancy and neonatal outcomes by causing a severe maternal cytokine storm and a mild fetal cytokine response; (2) fetal inflammation induced adverse pregnancy and neonatal outcomes by causing a mild maternal cytokine response and a severe fetal cytokine storm; (3) exendin-4 (Ex4) treatment of dams with systemic inflammation or fetal inflammation improved adverse pregnancy outcomes by modestly reducing the rate of preterm birth; (4) Ex4 treatment of dams with systemic, but not local, inflammation considerably improved neonatal outcomes, and such neonates continued to thrive; (5) systemic inflammation facilitated the diffusion of Ex4 through the uterus and the maternal-fetal interface; (6) neonates born to Ex4-treated dams with systemic inflammation displayed a similar cytokine profile to healthy control neonates; and (7) treatment with Ex4 had immunomodulatory effects by inducing an M2 macrophage polarization and increasing anti-inflammatory neutrophils, as well as suppressing the expansion of CD8+ regulatory T cells, in neonates born to dams with systemic inflammation. Collectively, these results provide evidence that dampening maternal systemic inflammation through novel interventions, such as Ex4, can improve the quality of life for neonates born to women with this clinical condition.

Intra-amniotic administration of lipopolysaccharide induces spontaneous preterm labor and birth in the absence of a body temperature change

Abstract: Objective: Intra-amniotic infection is associated with spontaneous preterm labor. In most cases, the infection is subclinical and bacteria are detected in the amniotic cavity rather than in the chorioamniotic membranes. The aims of this study were to establish a model of intra-amniotic lipopolysaccharide (LPS)-induced preterm labor/birth that resembles the subclinical syndrome and to compare this model to two established models of LPS-induced preterm labor/birth.Methods: Pregnant B6 mice received an intra-amniotic, intra-uterine, or intra-peritoneal injection of LPS (100 ng/amniotic sac, 15 μg/25 μL, and 15 μg/200 μL respectively) or PBS (control). Following injection, body temperature (every two hours for a 12-h period), gestational age, and the rate of preterm labor/birth were recorded.Results: An intra-amniotic injection of LPS resulted in preterm labor/birth [LPS 80 ± 24.79% (8/10) versus PBS 0% (0/8); p = 0.001] without causing maternal hypothermia. Intra-peritoneal [LPS 100% (8/8) versus PBS...

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.