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Weiss, Scott

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Weiss, Scott
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    Hematopoietic mosaic chromosomal alterations increase the risk for diverse types of infection
    (Springer Science and Business Media LLC, 2021-06) Zekavat, Seyedeh M.; Lin, Shu-Hong; Bick, Alexander G.; Liu, Aoxing; Paruchuri, Kaavya; Wang, Chen; Uddin, Md Mesbah; Ye, Yixuan; Yu, Zhaolong; Liu, Xiaoxi; Kamatani, Yoichiro; Bhattacharya, Romit; Pirruccello, James; Pampana, Akhil; Loh, Po-Ru; Kohli, Puja; McCarroll, Steven; Kiryluk, Krzysztof; Neale, Benjamin; Ionita-Laza, Iuliana; Engels, Eric; Brown, Derek W.; Smoller, Jordan; Green, Robert; Karlson, Elizabeth; Lebo, Matthew; Ellinor, Patrick; Weiss, Scott; Daly, Mark; Terao, Chikashi; Zhao, Hongyu; Ebert, Benjamin; Reilly, Muredach; Ganna, Andrea; Machiela, Mitchell; Genovese, Giulio; Natarajan, Pradeep
    The burden of mosaic chromosomal alterations in blood-derived DNA, a type of clonal hematopoiesis, is associated with an increased risk for diverse types of infections, including sepsis and pneumonia. Age is the dominant risk factor for infectious diseases, but the mechanisms linking age to infectious disease risk are incompletely understood. Age-related mosaic chromosomal alterations (mCAs) detected from genotyping of blood-derived DNA, are structural somatic variants indicative of clonal hematopoiesis, and are associated with aberrant leukocyte cell counts, hematological malignancy, and mortality. Here, we show that mCAs predispose to diverse types of infections. We analyzed mCAs from 768,762 individuals without hematological cancer at the time of DNA acquisition across five biobanks. Expanded autosomal mCAs were associated with diverse incident infections (hazard ratio (HR) 1.25; 95% confidence interval (CI) = 1.15-1.36; P = 1.8 x 10(-7)), including sepsis (HR 2.68; 95% CI = 2.25-3.19; P = 3.1 x 10(-28)), pneumonia (HR 1.76; 95% CI = 1.53-2.03; P = 2.3 x 10(-15)), digestive system infections (HR 1.51; 95% CI = 1.32-1.73; P = 2.2 x 10(-9)) and genitourinary infections (HR 1.25; 95% CI = 1.11-1.41; P = 3.7 x 10(-4)). A genome-wide association study of expanded mCAs identified 63 loci, which were enriched at transcriptional regulatory sites for immune cells. These results suggest that mCAs are a marker of impaired immunity and confer increased predisposition to infections.
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    A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data
    (Nature Publishing Group UK, 2018) Pandey, Gaurav; Pandey, Om P.; Rogers, Angela J.; Ahsen, Mehmet E.; Hoffman, Gabriel E.; Raby, Benjamin; Weiss, Scott; Schadt, Eric E.; Bunyavanich, Supinda
    Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.
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    Multiancestry association study identifies new asthma risk loci that colocalize with immune cell enhancer marks
    (2018) Demenais, Florence; Margaritte-Jeannin, Patricia; Barnes, Kathleen C; Cookson, William OC; Altmüller, Janine; Ang, Wei; Barr, R Graham; Beaty, Terri H; Becker, Allan B; Beilby, John; Bisgaard, Hans; Bjornsdottir, Unnur Steina; Bleecker, Eugene; Bønnelykke, Klaus; Boomsma, Dorret I; Bouzigon, Emmanuelle; Brightling, Christopher E; Brossard, Myriam; Brusselle, Guy G; Burchard, Esteban; Burkart, Kristin M; Bush, Andrew; Chan-Yeung, Moira; Chung, Kian Fan; Alves, Alexessander Couto; Curtin, John A; Custovic, Adnan; Daley, Denise; de Jongste, Johan C; Del-Rio-Navarro, Blanca E; Donohue, Kathleen M; Duijts, Liesbeth; Eng, Celeste; Eriksson, Johan G; Farrall, Martin; Fedorova, Yuliya; Feenstra, Bjarke; Ferreira, Manuel A; Freidin, Maxim B; Gajdos, Zofia; Gauderman, Jim; Gehring, Ulrike; Geller, Frank; Genuneit, Jon; Gharib, Sina A; Gilliland, Frank; Granell, Raquel; Graves, Penelope E; Gudbjartsson, Daniel F; Haahtela, Tari; Heckbert, Susan R; Heederik, Dick; Heinrich, Joachim; Heliövaara, Markku; Henderson, John; Himes, Blanca E; Hirose, Hiroshi; Hirschhorn, Joel; Hofman, Albert; Holt, Patrick; Hottenga, Jouke Jan; Hudson, Thomas J; Hui, Jennie; Imboden, Medea; Ivanov, Vladimir; Jaddoe, Vincent WV; James, Alan; Janson, Christer; Jarvelin, Marjo-Riitta; Jarvis, Deborah; Jones, Graham; Jonsdottir, Ingileif; Jousilahti, Pekka; Kabesch, Michael; Kähönen, Mika; Kantor, David; Karunas, Alexandra S; Khusnutdinova, Elza; Koppelman, Gerard H; Kozyrskyj, Anita L; Kreiner, Eskil; Kubo, Michiaki; Kumar, Rajesh; Kumar, Ashish; Kuokkanen, Mikko; Lahousse, Lies; Laitinen, Tarja; Laprise, Catherine; Lathrop, Mark; Lau, Susanne; Lee, Young-Ae; Lehtimäki, Terho; Letort, Sébastien; Levin, Albert M; Li, Guo; Liang, Liming; Loehr, Laura R; London, Stephanie J; Loth, Daan W; Manichaikul, Ani; Marenholz, Ingo; Martinez, Fernando J; Matheson, Melanie C; Mathias, Rasika A; Matsumoto, Kenji; Mbarek, Hamdi; McArdle, Wendy L; Melbye, Mads; Melén, Erik; Meyers, Deborah; Michel, Sven; Mohamdi, Hamida; Musk, Arthur W; Myers, Rachel A; Nieuwenhuis, Maartje AE; Noguchi, Emiko; O'Connor, George T; Ogorodova, Ludmila M; Palmer, Cameron D; Palotie, Aarno; Park, Julie E; Pennell, Craig E; Pershagen, Göran; Polonikov, Alexey; Postma, Dirkje S; Probst-Hensch, Nicole; Puzyrev, Valery P; Raby, Benjamin; Raitakari, Olli T; Ramasamy, Adaikalavan; Rich, Stephen S; Robertson, Colin F; Romieu, Isabelle; Salam, Muhammad T; Salomaa, Veikko; Schlünssen, Vivi; Scott, Robert; Selivanova, Polina A; Sigsgaard, Torben; Simpson, Angela; Siroux, Valérie; Smith, Lewis J; Solodilova, Maria; Standl, Marie; Stefansson, Kari; Strachan, David P; Stricker, Bruno H; Takahashi, Atsushi; Thompson, Philip J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tiesler, Carla MT; Torgerson, Dara G; Tsunoda, Tatsuhiko; Uitterlinden, André G; van der Valk, Ralf JP; Vaysse, Amaury; Vedantam, Sailaja; Von Berg, Andrea; Von Mutius, Erika; Vonk, Judith M; Waage, Johannes; Wareham, Nick J; Weiss, Scott; White, Wendy B; Wickman, Magnus; Widén, Elisabeth; Willemsen, Gonneke; Williams, L Keoki; Wouters, Inge M; Yang, James J; Zhao, Jing Hua; Moffatt, Miriam F; Ober, Carole; Nicolae, Dan L
    We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 cases, 118,538 controls) from ethnically-diverse populations. We identified five new asthma loci, uncovered two additional novel associations at two known asthma loci, established asthma associations at two loci implicated previously in comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. Enrichment of asthma risk loci in enhancer marks, especially in immune cells, suggests a major role of these loci in the regulation of immune-related mechanisms.
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    A high-throughput chemical screen identifies novel inhibitors and enhancers of anti-inflammatory functions of the glucocorticoid receptor
    (Nature Publishing Group UK, 2017) Jiang, Xiaofeng; Dahlin, Amber; Weiss, Scott; Tantisira, Kelan; Lu, Quan
    Glucocorticoids (GCs)—ligands of the glucocorticoid receptor (GR)—are widely used to treat inflammatory diseases, but suffer from significant side effects and poor responsiveness in certain patient populations. Identification of chemical GR modulators may provide insights into the regulatory mechanisms of anti-inflammatory functions of GR and help improve GC-based therapy. Here we report the development and application of a high-throughput screening to identify compounds that either enhance or suppress the anti-inflammatory effect of GR function. Using a cell-based GR activity assay that measures Dexamethasone (Dex)-mediated NF-κB repression, we have screened ~8,000 compounds and identified several compounds that suppressed GR activity, including multiple GSK3β inhibitors and anti-cancer agent camptothecin. Notably, we also identified two kinase IKK2 inhibitors, including TPCA-1, as GR enhancers that improve the anti-inflammatory effect of GR. In particular, TPCA-1 augmented the activity of Dex in NF-κB repression by attenuating GR down-regulation. Consistent with the observation, siRNA-mediated IKK2 knockdown decreased GR down-regulation and increased GR expression. Together, our results identified chemical compounds as novel modulators of GR and revealed an unexpected role for IKK2 in GR down-regulation. Furthermore, we have established a high-throughput screening platform for discovering GR-modulating compounds that may be repurposed to improve current GC-based therapies.
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    Circulating microRNAs and association with methacholine PC20 in the Childhood Asthma Management Program (CAMP) cohort
    (Public Library of Science, 2017) Davis, Joshua S.; Sun, Maoyun; Kho, Alvin; Moore, Kip G.; Sylvia, Jody M.; Weiss, Scott; Lu, Quan; Tantisira, Kelan
    Introduction: Circulating microRNAs (miRNA) are promising biomarkers for human diseases. Our study hypothesizes that circulating miRNA would reveal candidate biomarkers related to airway hyperresponsiveness (AHR) and provide biologic insights into asthma epigenetic influences. Methods: Serum samples obtained at randomization for 160 children in the Childhood Asthma Management Program were profiled using a TaqMan miRNA array set. The association of the isolated miRNA with methacholine PC20 was assessed. Network and pathway analyses were performed. Functional validation of two significant miRNAs was performed in human airway smooth muscle cells (HASMs). Results: Of 155 well-detected circulating miRNAs, eight were significantly associated with PC20 with the strongest association with miR-296-5p. Pathway analysis revealed miR-16-5p as a network hub, and involvement of multiple miRNAs interacting with genes in the FoxO and Hippo signaling pathways by KEGG analysis. Functional validation of two miRNA in HASM showed effects on cell growth and diameter. Conclusion: Reduced circulatory miRNA expression at baseline is associated with an increase in PC20. These miRNA provide biologic insights into, and may serve as biomarkers of, asthma severity. miR-16-5p and -30d-5p regulate airway smooth muscle phenotypes critically involved in asthma pathogenesis, supporting a mechanistic link to these findings. Functional ASM phenotypes may be directly relevant to AHR.
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    Association Between Cigarette Smoking and Acute Respiratory Tract Illness in Young Adults
    (American Medical Association (AMA), 1982-07-09) Aronson, Mark; Weiss, Scott; Ben, Ricca L.; Komaroff, Anthony
    The association of cigarette smoking with the occurrence and severity of an acute respiratory tract illness (ARTI) was studied. Clinical data were obtained prospectively on 867 men and women with an ARTI and on a control group of 289 women. Three hundred seven (57%) of the 534 women in the ARTI group were smokers, compared with 97 (34%) of the 289 women in the control group, a highly significant difference. Of the 867 men and women with ARTIs, 506 were smokers. Smokers had a statistically significant greater likelihood of having a lower respiratory tract illness (57% v 45%), a longer duration of cough (8.9 v 6.8 days), and a greater frequency of abnormal auscultatory findings (31% v 20%) than did the 361 nonsmokers. Cigarette smoking may thus contribute to the substantial morbidity and lost productivity resulting from ARTI.
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    CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data
    (Public Library of Science, 2014) McGeachie, Michael; Chang, Hsun-Hsien; Weiss, Scott
    Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
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    RNA-Seq Transcriptome Profiling Identifies CRISPLD2 as a Glucocorticoid Responsive Gene that Modulates Cytokine Function in Airway Smooth Muscle Cells
    (Public Library of Science, 2014) Himes, Blanca; Jiang, Xiaofeng; Wagner, Peter; Hu, Ruoxi; Wang, Qiyu; Klanderman, Barbara; Whitaker, Reid M.; Duan, Q; Lasky-Su, Jessica; Nikolos, Christina; Jester, William; Johnson, Martin; Panettieri, Reynold A.; Tantisira, Kelan; Weiss, Scott; Lu, Quan
    Asthma is a chronic inflammatory respiratory disease that affects over 300 million people worldwide. Glucocorticoids are a mainstay therapy for asthma because they exert anti-inflammatory effects in multiple lung tissues, including the airway smooth muscle (ASM). However, the mechanism by which glucocorticoids suppress inflammation in ASM remains poorly understood. Using RNA-Seq, a high-throughput sequencing method, we characterized transcriptomic changes in four primary human ASM cell lines that were treated with dexamethasone—a potent synthetic glucocorticoid (1 µM for 18 hours). Based on a Benjamini-Hochberg corrected p-value <0.05, we identified 316 differentially expressed genes, including both well known (DUSP1, KLF15, PER1, TSC22D3) and less investigated (C7, CCDC69, CRISPLD2) glucocorticoid-responsive genes. CRISPLD2, which encodes a secreted protein previously implicated in lung development and endotoxin regulation, was found to have SNPs that were moderately associated with inhaled corticosteroid resistance and bronchodilator response among asthma patients in two previously conducted genome-wide association studies. Quantitative RT-PCR and Western blotting showed that dexamethasone treatment significantly increased CRISPLD2 mRNA and protein expression in ASM cells. CRISPLD2 expression was also induced by the inflammatory cytokine IL1β, and small interfering RNA-mediated knockdown of CRISPLD2 further increased IL1β-induced expression of IL6 and IL8. Our findings offer a comprehensive view of the effect of a glucocorticoid on the ASM transcriptome and identify CRISPLD2 as an asthma pharmacogenetics candidate gene that regulates anti-inflammatory effects of glucocorticoids in the ASM.
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    Prenatal Tobacco Smoke Exposure Is Associated with Childhood DNA CpG Methylation
    (Public Library of Science, 2014) Breton, Carrie V.; Siegmund, Kimberly D.; Joubert, Bonnie R.; Wang, Xinhui; Qui, Weiliang; Carey, Vincent; Nystad, Wenche; Håberg, Siri E.; Ober, Carole; Nicolae, Dan; Barnes, Kathleen C.; Martinez, Fernando; Liu, Andy; Lemanske, Robert; Strunk, Robert; Weiss, Scott; London, Stephanie; Gilliland, Frank
    Background: Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail. Objectives: To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children. Methods: Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR. Results: Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group. Conclusions: These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown.
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    ITGB5 and AGFG1 variants are associated with severity of airway responsiveness
    (BioMed Central, 2013) Himes, Blanca; Qiu, Weiliang; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Szefler, Stanley J; Lemanske, Jr, Robert F; Zeiger, Robert S; Strunk, Robert C; Martinez, Fernando D; Boushey, Homer; Chinchilli, Vernon M; Israel, Elliot; Mauger, David; Koppelman, Gerard H; Nieuwenhuis, Maartje AE; Postma, Dirkje S; Vonk, Judith M; Rafaels, Nicholas; Hansel, Nadia N; Barnes, Kathleen; Raby, Benjamin; Tantisira, Kelan; Weiss, Scott
    Background: Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity. Methods: A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects. Results: The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1. Conclusions: Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings.