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171 results on '"Herazo-Maya, Jose D."'

2. Single-Cell Profiling Reveals Immune Aberrations in Progressive Idiopathic Pulmonary Fibrosis

Author

Unterman, Avraham, primary, Zhao, Amy Y, additional, Neumark, Nir, additional, Schupp, Jonas C., additional, Ahangari, Farida, additional, Cosme, Carlos, additional, Sharma, Prapti, additional, Flint, Jasper, additional, Stein, Yan, additional, Ryu, Changwan, additional, Ishikawa, Genta, additional, Sumida, Tomokazu S., additional, Gomez, Jose L, additional, Herazo-Maya, Jose D, additional, Dela Cruz, Charles S., additional, Herzog, Erica L., additional, and Kaminski, Naftali, additional

Published
2024
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4. Mast-cell expressed membrane protein-1 is expressed in classical monocytes and alveolar macrophages in idiopathic pulmonary fibrosis and regulates cell chemotaxis, adhesion, and migration in a TGFβ-dependent manner

Author

Perrot, Carole Y., primary, Karampitsakos, Theodoros, additional, Unterman, Avraham, additional, Adams, Taylor, additional, Marlin, Krystin, additional, Arsenault, Alyssa, additional, Zhao, Amy, additional, Kaminski, Naftali, additional, Katlaps, Gundars, additional, Patel, Kapilkumar, additional, Bandyopadhyay, Debabrata, additional, and Herazo-Maya, Jose D., additional

Published
2024
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5. Joint Models for Time-to-Event Data and Longitudinal Biomarkers of High Dimension

Author

Liu, Molei, Sun, Jiehuan, Herazo-Maya, Jose D., Kaminski, Naftali, and Zhao, Hongyu

Subjects
Statistics - Methodology, 62N01
Abstract

Joint models for longitudinal biomarkers and time-to-event data are widely used in longitudinal studies. Many joint modeling approaches have been proposed to deal with different types of longitudinal biomarkers and survival outcomes. However, most existing joint modeling methods cannot deal with a large number of longitudinal biomarkers simultaneously, such as the longitudinally collected gene expression profiles. In this article, we propose a new joint modeling method under the Bayesian framework, which is able to deal with longitudinal biomarkers of high dimension. Specifically, we assume that only a few unobserved latent variables are related to the survival outcome and the latent variables are inferred using a factor analysis model, which greatly reduces the dimensionality of the biomarkers and also accounts for the high correlations among the biomarkers. Through extensive simulation studies, we show that our proposed method has improved prediction accuracy over other joint modeling methods. We illustrate the usefulness of our method on a dataset of idiopathic pulmonary fibrosis patients in which we are interested in predicting the patients' time-to-death using their gene expression profiles., Comment: This paper has been withdrawn by the author because it was submitted without consents of all authors

Published
2016

6. Distance-Correlation based Gene Set Analysis in Longitudinal Studies

Author

Sun, Jiehuan, Herazo-Maya, Jose D., Huang, Xiu, Kaminski, Naftali, and Zhao, Hongyu

Subjects
Statistics - Methodology, 62H20
Abstract

Longitudinal gene expression profiles of patients are collected in some clinical studies to monitor disease progression and understand disease etiology. The identification of gene sets that have coordinated changes with relevant clinical outcomes over time from these data could provide significant insights into the molecular basis of disease progression and hence may lead to better treatments. In this article, we propose a Distance-Correlation based Gene Set Analysis (dcGSA) method for longitudinal gene expression data. dcGSA is a non-parametric approach, statistically robust, and can capture both linear and nonlinear relationships between gene sets and clinical outcomes. In addition, dcGSA is able to identify related gene sets in cases where the effects of gene sets on clinical outcomes differ across patients due to the patient heterogeneity, alleviate the confounding effects of some unobserved covariates, and allow the assessment of associations between gene sets and multiple related outcomes simultaneously. Through extensive simulation studies, we demonstrate that dcGSA is more powerful of detecting relevant genes than other commonly used gene set analysis methods. When dcGSA is applied to multiple real datasets of different characteristics, we are able to identify more disease related gene sets than other methods., Comment: This paper has been withdrawn by the author because it was submitted without consents of all authors

Published
2016

7. A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data

Author

Sun, Jiehuan, Herazo-Maya, Jose D., Kaminski, Naftali, Zhao, Hongyu, and Warren, Joshua L.

Subjects
Statistics - Methodology, 62G05
Abstract

Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expression profiles might provide additional information on disease progression than what is captured by baseline profiles alone. Moreover, the longitudinal gene expression data allows for intra-individual variability to be accounted for when grouping patients. Therefore, subgroup identification could be more accurate and effective with the aid of longitudinal gene expression data. However, existing statistical methods are unable to fully utilize these data for patient clustering. In this article, we introduce a novel subgroup identification method in the Bayesian setting based on longitudinal gene expression profiles. This method, called BClustLonG, adopts a linear mixed-effects framework to model the trajectory of genes over time while clustering is jointly conducted based on the regression coefficients obtained from all genes. In order to account for the correlations among genes and alleviate the high dimensionality challenges, we adopt a factor analysis model for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. Through extensive simulation studies, we show that BClustLonG has improved performance over other clustering methods. When applied to a dataset of severely injured (burn or trauma) patients, our model is able to distinguish burn patients from trauma patients and identify interesting subgroups in trauma patients., Comment: This paper has been withdrawn by the author because it was submitted without consents of all authors

Published
2016

9. Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data

Author

Vaeli Zadeh, Ali, primary, Dinparastisaleh, Roshan, additional, Vaezi, Atefeh, additional, Bandyopadhyay, Debabrata, additional, Rubinstein, Israel, additional, Baig, Hassan Z, additional, Calderon-Candelario, Rafael, additional, Hashemi Shahraki, Abdolrazagh, additional, Kawasaki, Takeshi, additional, Magnusson, Jesper M., additional, Larsson, Lars-Olof, additional, Sharafkhaneh, Amir, additional, Herazo-Maya, Jose D, additional, Lee, Augustine S, additional, and Mirsaeidi, Mehdi, additional

Published
2023
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10. Expression of PD-1/PD-L1 axis in mediastinal lymph nodes and lung tissue of human and experimental lung fibrosis indicates a potential therapeutic target for idiopathic pulmonary fibrosis

Author

Karampitsakos, Theodoros, primary, Galaris, Apostolos, additional, Chrysikos, Serafeim, additional, Papaioannou, Ourania, additional, Vamvakaris, Ioannis, additional, Barbayianni, Ilianna, additional, Kanellopoulou, Paraskevi, additional, Grammenoudi, Sofia, additional, Anagnostopoulos, Nektarios, additional, Stratakos, Grigoris, additional, Katsaras, Matthaios, additional, Sampsonas, Fotios, additional, Dimakou, Katerina, additional, Manali, Effrosyni D., additional, Papiris, Spyridon, additional, Tourki, Bochra, additional, Juan-Guardela, Brenda M, additional, Bakakos, Petros, additional, Bouros, Demosthenes, additional, Herazo-Maya, Jose D, additional, Aidinis, Vassilis, additional, and Tzouvelekis, Argyris, additional

Published
2023
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11. Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data.

Author

Vaeli Zadeh, Ali, Dinparastisaleh, Roshan, Vaezi, Atefeh, Bandyopadhyay, Debabrata, Rubinstein, Israel, Baig, Hassan Z., Calderon-Candelario, Rafael, Hashemi Shahraki, Abdolrazagh, Kawasaki, Takeshi, Magnusson, Jesper M., Larsson, Lars-Olof, Sharafkhaneh, Amir, Herazo-Maya, Jose D., Lee, Augustine S., and Mirsaeidi, Mehdi

Subjects
COVID-19, INTERSTITIAL lung diseases, LUNGS, MEDICAL personnel, PATIENT readmissions, IDIOPATHIC pulmonary fibrosis
Abstract

Rationale: Hospital readmission within 30 days poses challenges for healthcare providers, policymakers, and patients because of its impact on care quality, costs, and outcomes. Patients with interstitial lung disease (ILD) are particularly affected by readmission, which is associated with increased morbidity and mortality and reduced quality of life. Because small sample sizes have hindered previous studies, this study seeks to address this gap in knowledge by examining a large-scale dataset. Objective: To determine the rate and probability of 30-day all-cause readmission and secondary outcomes in patients with coronavirus disease (COVID-19) or ILD admitted to the hospital. Methods: This study is a nested cohort study that used the PearlDiver patient records database. Adult patients (age ⩾18 yr) who were admitted to hospitals in 28 states in the United States with COVID-19 or ILD diagnoses were included. We defined and analyzed two separate cohorts in this study. The first cohort consisted of patients with COVID-19 and was later divided into two groups with or without a history of ILD. The second cohort consisted of patients with ILD and was later divided into groups with COVID-19 or with a non–COVID-19 pneumonia diagnosis at admission. We also studied two other subcohorts of patients with and without idiopathic pulmonary fibrosis within the second cohort. Propensity score matching was employed to match confounders between groups. The Kaplan-Meier log rank test was applied to compare the probabilities of outcomes. Results: We assessed the data of 2,286,775 patients with COVID-19 and 118,892 patients with ILD. We found that patients with COVID-19 with preexisting ILD had an odds ratio of 1.6 for 30-day all-cause readmission. Similarly, an odds ratio of 2.42 in readmission rates was observed among hospitalized individuals with ILD who contracted COVID-19 compared with those who were hospitalized for non–COVID-19 pneumonia. Our study also found a significantly higher probability of intensive care admission among patients in both cohorts. Conclusions: Patients with ILD face heightened rates of hospital readmissions, particularly when ILD is combined with COVID-19, resulting in adverse outcomes such as decreased quality of life and increased healthcare expenses. It is imperative to prioritize preventive measures against COVID-19 and establish effective postdischarge care strategies for patients with ILD. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Evolving Genomics of Pulmonary Fibrosis

Author

Ibarra, Gabriel, Herazo-Maya, Jose D., Kaminski, Naftali, Rounds, Sharon I.S., Series Editor, Dixon, Anne, Series Editor, Schnapp, Lynn M., Series Editor, Meyer, Keith C., editor, and Nathan, Steven D., editor

Published
2019
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13. Mast-Cell Expressed Membrane Protein-1 (MCEMP1) is expressed in classical monocytes and alveolar macrophages in Idiopathic Pulmonary Fibrosis and regulates cell chemotaxis, adhesion, and migration in a TGFβ dependent manner.

Author

Perrot, Carole Y, primary, Karampitsakos, Theodoros, additional, Unterman, Avraham, additional, Adams, Taylor, additional, Marlin, Krystin, additional, Arsenault, Alyssa, additional, Zhao, Amy, additional, Kaminski, Naftali, additional, Katlaps, Gundars, additional, Patel, Kapilkumar, additional, Bandyopadhyay, Debabrata, additional, and Herazo-Maya, Jose D, additional

Published
2023
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16. Increased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study

Author

Scott, Madeleine K D, Quinn, Katie, Li, Qin, Carroll, Robert, Warsinske, Hayley, Vallania, Francesco, Chen, Shirley, Carns, Mary A, Aren, Kathleen, Sun, Jiehuan, Koloms, Kimberly, Lee, Jungwha, Baral, Jessika, Kropski, Jonathan, Zhao, Hongyu, Herzog, Erica, Martinez, Fernando J, Moore, Bethany B, Hinchcliff, Monique, Denny, Joshua, Kaminski, Naftali, Herazo-Maya, Jose D, Shah, Nigam H, and Khatri, Purvesh

Published
2019
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17. Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study

Author

Herazo-Maya, Jose D, Sun, Jiehuan, Molyneaux, Philip L, Li, Qin, Villalba, Julian A, Tzouvelekis, Argyrios, Lynn, Heather, Juan-Guardela, Brenda M, Risquez, Cristobal, Osorio, Juan C, Yan, Xiting, Michel, George, Aurelien, Nachelle, Lindell, Kathleen O, Klesen, Melinda J, Moffatt, Miriam F, Cookson, William O, Zhang, Yingze, Garcia, Joe G N, Noth, Imre, Prasse, Antje, Bar-Joseph, Ziv, Gibson, Kevin F, Zhao, Hongyu, Herzog, Erica L, Rosas, Ivan O, Maher, Toby M, and Kaminski, Naftali

Published
2017
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18. SH2 Domain-Containing Phosphatase-SHP2 Attenuates Fibrotic Responses through Negative Regulation of Mitochondrial Metabolism in Lung Fibroblasts

Author

Karampitsakos, Theodoros, primary, Galaris, Apostolos, additional, Barbayianni, Ilianna, additional, DeIuliis, Giuseppe, additional, Ahangari, Farida, additional, Sampsonas, Fotis, additional, Sotiropoulou, Vasilina, additional, Aidinis, Vassilis, additional, Bennett, Anton M., additional, Herazo-Maya, Jose D., additional, Xylourgidis, Nikolaos, additional, Bakakos, Petros, additional, Bouros, Demosthenes, additional, Kaminski, Naftali, additional, and Tzouvelekis, Argyrios, additional

Published
2023
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20. Thyroid hormone inhibits lung fibrosis in mice by improving epithelial mitochondrial function

Author

Yu, Guoying, Tzouvelekis, Argyris, Wang, Rong, Herazo-Maya, Jose D, Ibarra, Gabriel H, Srivastava, Anup, de Castro, Joao Pedro Werneck, DeIuliis, Giuseppe, Ahangari, Farida, Woolard, Tony, Aurelien, Nachelle, Arrojo e Drigo, Rafael, Gan, Ye, Graham, Morven, Liu, Xinran, Homer, Robert J, Scanlan, Thomas S, Mannam, Praveen, Lee, Patty J, Herzog, Erica L, Bianco, Antonio C, and Kaminski, Naftali

Subjects
Mitochondrial biogenesis -- Physiological aspects -- Analysis, Pulmonary fibrosis -- Prevention -- Models -- Analysis, Thyroid hormones -- Physiological aspects -- Analysis, House mouse -- Research, Biological sciences, Health
Abstract

Thyroid hormone (TH) is critical for the maintenance of cellular homeostasis during stress responses, but its role in lung fibrosis is unknown. Here we found that the activity and expression of iodothyronine deiodinase 2 (DIO2), an enzyme that activates TH, were higher in lungs from patients with idiopathic pulmonary fibrosis than in control individuals and were correlated with disease severity. We also found that Dio2-knockout mice exhibited enhanced bleomycin-induced lung fibrosis. Aerosolized TH delivery increased survival and resolved fibrosis in two models of pulmonary fibrosis in mice (intratracheal bleomycin and inducible TGF-[beta]1). Sobetirome, a TH mimetic, also blunted bleomycin-induced lung fibrosis. After bleomycin-induced injury, TH promoted mitochondrial biogenesis, improved mitochondrial bioenergetics and attenuated mitochondria-regulated apoptosis in alveolar epithelial cells both in vivo and in vitro. TH did not blunt fibrosis in Ppargc1a- or Pink1-knockout mice, suggesting dependence on these pathways. We conclude that the antifibrotic properties of TH are associated with protection of alveolar epithelial cells and restoration of mitochondrial function and that TH may thus represent a potential therapy for pulmonary fibrosis., Author(s): Guoying Yu [1]; Argyris Tzouvelekis [1, 2]; Rong Wang [1]; Jose D Herazo-Maya [1]; Gabriel H Ibarra [1]; Anup Srivastava [1]; Joao Pedro Werneck de Castro [3, 4]; Giuseppe [...]

Published
2018
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23. Extracellular Mitochondrial DNA Is Generated by Fibroblasts and Predicts Death in Idiopathic Pulmonary Fibrosis

Author

Ryu, Changwan, Sun, Huanxing, Gulati, Mridu, Herazo-Maya, Jose D., Chen, Yonglin, Osafo-Addo, Awo, Brandsdorfer, Caitlin, Winkler, Julia, Blaul, Christina, Faunce, Jaden, Pan, Hongyi, Woolard, Tony, Tzouvelekis, Argyrios, Antin-Ozerkis, Danielle E., Puchalski, Jonathan T., Slade, Martin, Gonzalez, Anjelica L., Bogenhagen, Daniel F., Kirillov, Varvara, Feghali-Bostwick, Carol, Gibson, Kevin, Lindell, Kathleen, Herzog, Raimund I., Dela Cruz, Charles S., Mehal, Wajahat, Kaminski, Naftali, Herzog, Erica L., and Trujillo, Glenda

Published
2017
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25. PINK1 deficiency impairs mitochondrial homeostasis and promotes lung fibrosis

Author

Bueno, Marta, Lai, Yen-Chun, Romero, Yair, Brands, Judith, St. Croix, Claudette, Kamga, Christelle, Corey, Catherine, Herazo-Maya, Jose D., Sembrat, John, Lee, Janet S., Duncan, Steve R., Rojas, Mauricio, Shiva, Sruti, Chu, Charleen T., and Mora, Ana L.

Subjects
Mitochondrial membranes -- Physiological aspects, Pulmonary fibrosis -- Development and progression -- Physiological aspects, Extracellular signal-regulated kinases -- Properties -- Physiological aspects, Health care industry
Abstract

Although aging is a known risk factor for idiopathic pulmonary fibrosis (IPF), the pathogenic mechanisms that underlie the effects of advancing age remain largely unexplained. Some age-related neurodegenerative diseases have an etiology that is related to mitochondrial dysfunction. Here, we found that alveolar type II cells (AECIIs) in the lungs of IPF patients exhibit marked accumulation of dysmorphic and dysfunctional mitochondria. These mitochondrial abnormalities in AECIIs of IPF lungs were associated with upregulation of ER stress markers and were recapitulated in normal mice with advancing age in response to stimulation of ER stress. We found that impaired mitochondria in IPF and aging lungs were associated with low expression of PTEN-induced putative kinase 1 (PINK1). Knockdown of PINK1 expression in lung epithelial cells resulted in mitochondria depolarization and expression of profibrotic factors. Moreover, young PINK1- deficient mice developed similarly dysmorphic, dysfunctional mitochondria in the AECIIs and were vulnerable to apoptosis and development of lung fibrosis. Our data indicate that PINK1 deficiency results in swollen, dysfunctional mitochondria and defective mitophagy, and promotes fibrosis in the aging lung., Introduction Age is a significant risk factor for the development of idiopathic pulmonary fibrosis (IPF): people older than 75 years have 50 times higher prevalence than people 35 years old [...]

Published
2015
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27. Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells

Author

Huang, Yong, primary, Oldham, Justin M., additional, Ma, Shwu-Fan, additional, Unterman, Avraham, additional, Liao, Shu-Yi, additional, Barros, Andrew J., additional, Bonham, Catherine A., additional, Kim, John S., additional, Vij, Rekha, additional, Adegunsoye, Ayodeji, additional, Strek, Mary E., additional, Molyneaux, Philip L., additional, Maher, Toby M., additional, Herazo-Maya, Jose D., additional, Kaminski, Naftali, additional, Moore, Bethany B., additional, Martinez, Fernando J., additional, and Noth, Imre, additional

Published
2021
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28. 50-gene risk profiles in peripheral blood predict COVID-19 outcomes: A retrospective, multicenter cohort study

Author

Juan Guardela, Brenda M., primary, Sun, Jiehuan, additional, Zhang, Tong, additional, Xu, Bing, additional, Balnis, Joseph, additional, Huang, Yong, additional, Ma, Shwu-Fan, additional, Molyneaux, Philip L., additional, Maher, Toby M., additional, Noth, Imre, additional, Michaud, Gaetane, additional, Jaitovich, Ariel, additional, and Herazo-Maya, Jose D., additional

Published
2021
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35. Role of dual-specificity protein phosphatase DUSP10/MKP-5 in pulmonary fibrosis

Author

Xylourgidis, Nikos, primary, Min, Kisuk, additional, Ahangari, Farida, additional, Yu, Guoying, additional, Herazo-Maya, Jose D., additional, Karampitsakos, Theodoros, additional, Aidinis, Vassilis, additional, Binzenhöfer, Leonhard, additional, Bouros, Demosthenes, additional, Bennett, Anton M., additional, Kaminski, Naftali, additional, and Tzouvelekis, Argyrios, additional

Published
2019
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36. Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells.

Author

Yong Huang, Oldham, Justin M., Shwu-Fan Ma, Unterman, Avraham, Shu-Yi Liao, Barros, Andrew J., Bonham, Catherine A., Kim, John S., Vij, Rekha, Adegunsoye, Ayodeji, Strek, Mary E., Molyneaux, Philip L., Maher, Toby M., Herazo-Maya, Jose D., Kaminski, Naftali, Moore, Bethany B., Martinez, Fernando J., Noth, Imre, Huang, Yong, and Ma, Shwu-Fan

Subjects
PULMONARY fibrosis, LUNG disease diagnosis, LUNG disease treatment, GENE expression, KILLER cells, DISEASE progression, RESEARCH, PREDICTIVE tests, IDIOPATHIC pulmonary fibrosis, CROSS-sectional method, RESEARCH methodology, MEDICAL cooperation, EVALUATION research, COMPARATIVE studies, GENE expression profiling, RESEARCH funding, LONGITUDINAL method
Abstract

Rationale: Disease activity in idiopathic pulmonary fibrosis (IPF) remains highly variable, poorly understood, and difficult to predict. Objectives: To identify a predictor using short-term longitudinal changes in gene expression that forecasts future FVC decline and to characterize involved pathways and cell types. Methods: Seventy-four patients from COMET (Correlating Outcomes with Biochemical Markers to Estimate Time-Progression in IPF) cohort were dichotomized as progressors (≥10% FVC decline) or stable. Blood gene-expression changes within individuals were calculated between baseline and 4 months and regressed with future FVC status, allowing determination of expression variations, sample size, and statistical power. Pathway analyses were conducted to predict downstream effects and identify new targets. An FVC predictor for progression was constructed in COMET and validated using independent cohorts. Peripheral blood mononuclear single-cell RNA-sequencing data from healthy control subjects were used as references to characterize cell type compositions from bulk peripheral blood mononuclear RNA-sequencing data that were associated with FVC decline. Measurements and Main Results: The longitudinal model reduced gene-expression variations within stable and progressor groups, resulting in increased statistical power when compared with a cross-sectional model. The FVC predictor for progression anticipated patients with future FVC decline with 78% sensitivity and 86% specificity across independent IPF cohorts. Pattern recognition receptor pathways and mTOR pathways were downregulated and upregulated, respectively. Cellular deconvolution using single-cell RNA-sequencing data identified natural killer cells as significantly correlated with progression. Conclusions: Serial transcriptomic change predicts future FVC decline. An analysis of cell types involved in the progressor signature supports the novel involvement of natural killer cells in IPF progression. [ABSTRACT FROM AUTHOR]

Published
2021
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37. BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis

Author

Prasse, Antje, primary, Binder, Harald, additional, Schupp, Jonas C., additional, Kayser, Gian, additional, Bargagli, Elena, additional, Jaeger, Benedikt, additional, Hess, Moritz, additional, Rittinghausen, Susanne, additional, Vuga, Louis, additional, Lynn, Heather, additional, Violette, Shelia, additional, Jung, Birgit, additional, Quast, Karsten, additional, Vanaudenaerde, Bart, additional, Xu, Yan, additional, Hohlfeld, Jens M., additional, Krug, Norbert, additional, Herazo-Maya, Jose D., additional, Rottoli, Paola, additional, Wuyts, Wim A., additional, and Kaminski, Naftali, additional

Published
2019
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39. BPIFA1 regulates lung neutrophil recruitment and interferon signaling during acute inflammation

Author

Britto, Clemente J., primary, Niu, Naiqian, additional, Khanal, Sara, additional, Huleihel, Luai, additional, Herazo-Maya, Jose D., additional, Thompson, Alison, additional, Sauler, Maor, additional, Slade, Martin D., additional, Sharma, Lokesh, additional, Dela Cruz, Charles S., additional, Kaminski, Naftali, additional, and Cohn, Lauren E., additional

Published
2019
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41. PD-1 up-regulation on CD4 + T cells promotes pulmonary fibrosis through STAT3-mediated IL-17A and TGF-β1 production

Author

Celada, Lindsay J., primary, Kropski, Jonathan A., additional, Herazo-Maya, Jose D., additional, Luo, Weifeng, additional, Creecy, Amy, additional, Abad, Andrew T., additional, Chioma, Ozioma S., additional, Lee, Grace, additional, Hassell, Natalie E., additional, Shaginurova, Guzel I., additional, Wang, Yufen, additional, Johnson, Joyce E., additional, Kerrigan, Amy, additional, Mason, Wendi R., additional, Baughman, Robert P., additional, Ayers, Gregory D., additional, Bernard, Gordon R., additional, Culver, Daniel A., additional, Montgomery, Courtney G., additional, Maher, Toby M., additional, Molyneaux, Philip L., additional, Noth, Imre, additional, Mutsaers, Steven E., additional, Prele, Cecilia M., additional, Stokes Peebles, R., additional, Newcomb, Dawn C., additional, Kaminski, Naftali, additional, Blackwell, Timothy S., additional, Van Kaer, Luc, additional, and Drake, Wonder P., additional

Published
2018
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42. The DNA repair transcriptome in severe COPD

Author

Sauler, Maor, primary, Lamontagne, Maxime, additional, Finnemore, Eric, additional, Herazo-Maya, Jose D., additional, Tedrow, John, additional, Zhang, Xuchen, additional, Morneau, Julia E., additional, Sciurba, Frank, additional, Timens, Wim, additional, Paré, Peter D., additional, Lee, Patty J., additional, Kaminski, Naftali, additional, Bossé, Yohan, additional, and Gomez, Jose L., additional

Published
2018
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43. A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data

Author

Sun, Jiehuan, Herazo-Maya, Jose D., Kaminski, Naftali, Zhao, Hongyu, and Warren, Joshua L.

Subjects
FOS: Computer and information sciences, Models, Genetic, Gene Expression Profiling, Gene Expression, Bayes Theorem, Article, Markov Chains, Statistics, Nonparametric, Methodology (stat.ME), Cluster Analysis, Humans, Regression Analysis, 62G05, Computer Simulation, Burns, Factor Analysis, Statistical, Monte Carlo Method, Statistics - Methodology
Abstract

Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expression profiles might provide additional information on disease progression than what is captured by baseline profiles alone. Moreover, the longitudinal gene expression data allows for intra-individual variability to be accounted for when grouping patients. Therefore, subgroup identification could be more accurate and effective with the aid of longitudinal gene expression data. However, existing statistical methods are unable to fully utilize these data for patient clustering. In this article, we introduce a novel subgroup identification method in the Bayesian setting based on longitudinal gene expression profiles. This method, called BClustLonG, adopts a linear mixed-effects framework to model the trajectory of genes over time while clustering is jointly conducted based on the regression coefficients obtained from all genes. In order to account for the correlations among genes and alleviate the high dimensionality challenges, we adopt a factor analysis model for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. Through extensive simulation studies, we show that BClustLonG has improved performance over other clustering methods. When applied to a dataset of severely injured (burn or trauma) patients, our model is able to distinguish burn patients from trauma patients and identify interesting subgroups in trauma patients., Comment: This paper has been withdrawn by the author because it was submitted without consents of all authors

Published
2017

44. S100A12 as a marker of worse cardiac output and mortality in pulmonary hypertension

Author

Tzouvelekis, Argyrios, primary, Herazo-Maya, Jose D., additional, Ryu, Changwan, additional, Chu, Jen-Hwa, additional, Zhang, Yingze, additional, Gibson, Kevin F., additional, Adonteng-Boateng, Percy K., additional, Li, Qin, additional, Pan, Hongyi, additional, Cherry, Benjamin, additional, Ahmad, Ferhaan, additional, Ford, Hubert J., additional, Herzog, Erica L., additional, Kaminski, Naftali, additional, and Fares, Wassim H., additional

Published
2018
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46. Thyroid hormone inhibits lung fibrosis in mice by improving epithelial mitochondrial function

Author

Yu, Guoying, primary, Tzouvelekis, Argyris, additional, Wang, Rong, additional, Herazo-Maya, Jose D, additional, Ibarra, Gabriel H, additional, Srivastava, Anup, additional, de Castro, Joao Pedro Werneck, additional, DeIuliis, Giuseppe, additional, Ahangari, Farida, additional, Woolard, Tony, additional, Aurelien, Nachelle, additional, Arrojo e Drigo, Rafael, additional, Gan, Ye, additional, Graham, Morven, additional, Liu, Xinran, additional, Homer, Robert J, additional, Scanlan, Thomas S, additional, Mannam, Praveen, additional, Lee, Patty J, additional, Herzog, Erica L, additional, Bianco, Antonio C, additional, and Kaminski, Naftali, additional

Published
2017
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47. Microbiota control immune regulation in humanized mice

Author

Gülden, Elke, primary, Vudattu, Nalini K., additional, Deng, Songyan, additional, Preston-Hurlburt, Paula, additional, Mamula, Mark, additional, Reed, James C., additional, Mohandas, Sindhu, additional, Herold, Betsy C., additional, Torres, Richard, additional, Vieira, Silvio M., additional, Lim, Bentley, additional, Herazo-Maya, Jose D., additional, Kriegel, Martin, additional, Goodman, Andrew L., additional, Cotsapas, Chris, additional, and Herold, Kevan C., additional

Published
2017
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48. Antifibrotic role of vascular endothelial growth factor in pulmonary fibrosis

Author

Murray, Lynne A., primary, Habiel, David M., additional, Hohmann, Miriam, additional, Camelo, Ana, additional, Shang, Huilan, additional, Zhou, Yang, additional, Coelho, Ana Lucia, additional, Peng, Xueyan, additional, Gulati, Mridu, additional, Crestani, Bruno, additional, Sleeman, Matthew A., additional, Mustelin, Tomas, additional, Moore, Meagan W., additional, Ryu, Changwan, additional, Osafo-Addo, Awo D., additional, Elias, Jack A., additional, Lee, Chun G., additional, Hu, Buqu, additional, Herazo-Maya, Jose D., additional, Knight, Darryl A., additional, Hogaboam, Cory M., additional, and Herzog, Erica L., additional

Published
2017
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50. Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis

Author

Vukmirovic, Milica, primary, Herazo-Maya, Jose D., additional, Blackmon, John, additional, Skodric-Trifunovic, Vesna, additional, Jovanovic, Dragana, additional, Pavlovic, Sonja, additional, Stojsic, Jelena, additional, Zeljkovic, Vesna, additional, Yan, Xiting, additional, Homer, Robert, additional, Stefanovic, Branko, additional, and Kaminski, Naftali, additional

Published
2017
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