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4. The Gene Ontology resource: enriching a GOld mine

Author

Carbon, Seth, Douglass, Eric, Good, Benjamin M, Unni, Deepak R, Harris, Nomi L, Mungall, Christopher J, Basu, Siddartha, Chisholm, Rex L, Dodson, Robert J, Hartline, Eric, Fey, Petra, Thomas, Paul D, Albou, Laurent-Philippe, Ebert, Dustin, Kesling, Michael J, Mi, Huaiyu, Muruganujan, Anushya, Huang, Xiaosong, Mushayahama, Tremayne, LaBonte, Sandra A, Siegele, Deborah A, Antonazzo, Giulia, Attrill, Helen, Brown, Nick H, Garapati, Phani, Marygold, Steven J, Trovisco, Vitor, dos Santos, Gil, Falls, Kathleen, Tabone, Christopher, Zhou, Pinglei, Goodman, Joshua L, Strelets, Victor B, Thurmond, Jim, Garmiri, Penelope, Ishtiaq, Rizwan, Rodríguez-López, Milagros, Acencio, Marcio L, Kuiper, Martin, Lægreid, Astrid, Logie, Colin, Lovering, Ruth C, Kramarz, Barbara, Saverimuttu, Shirin CC, Pinheiro, Sandra M, Gunn, Heather, Su, Renzhi, Thurlow, Katherine E, Chibucos, Marcus, Giglio, Michelle, Nadendla, Suvarna, Munro, James, Jackson, Rebecca, Duesbury, Margaret J, Del-Toro, Noemi, Meldal, Birgit HM, Paneerselvam, Kalpana, Perfetto, Livia, Porras, Pablo, Orchard, Sandra, Shrivastava, Anjali, Chang, Hsin-Yu, Finn, Robert Daniel, Mitchell, Alexander Lawson, Rawlings, Neil David, Richardson, Lorna, Sangrador-Vegas, Amaia, Blake, Judith A, Christie, Karen R, Dolan, Mary E, Drabkin, Harold J, Hill, David P, Ni, Li, Sitnikov, Dmitry M, Harris, Midori A, Oliver, Stephen G, Rutherford, Kim, Wood, Valerie, Hayles, Jaqueline, Bähler, Jürg, Bolton, Elizabeth R, De Pons, Jeffery L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Plasterer, Cody, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Matthews, Lisa, Balhoff, James P, Aleksander, Suzi A, Alexander, Michael J, Cherry, J Michael, Engel, Stacia R, Gondwe, Felix, and Karra, Kalpana

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Genetics, 1.5 Resources and infrastructure (underpinning), 2.6 Resources and infrastructure (aetiology), Animals, Arabidopsis, Caenorhabditis elegans, Dictyostelium, Drosophila melanogaster, Escherichia coli, Gene Ontology, Humans, Internet, Mice, Molecular Sequence Annotation, Rats, Saccharomyces cerevisiae, Schizosaccharomyces, User-Computer Interface, Zebrafish, Gene Ontology Consortium, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

Published
2021

5. Liver Cancer–Specific Serine Protease Inhibitor Kazal Is a Potentially Novel Biomarker for the Early Detection of Hepatocellular Carcinoma

Author

Lu, Felix, Shah, Ahmad, Rao, Abhishek, Gifford-Hollingsworth, Cynthia, Chen, Anne, Trey, Gary, Soryal, Mina, Talat, Arslan, Aslam, Aysha, Nasir, Bilal, Choudhry, Saad, Ishtiaq, Rizwan, Sanoff, Hanna, Conteh, Lanla F, Noonan, Anne, Hu, Ke-Qin, Schmidt, Carl, Fu, Min, Civan, Jesse, Xiao, Gary, Lau, Daryl T-Y, and Lu, Xuanyong

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Hepatitis - B, Clinical Research, Infectious Diseases, Liver Disease, Rare Diseases, Hepatitis, Digestive Diseases, Liver Cancer, Hepatitis - C, HIV/AIDS, Cancer, Emerging Infectious Diseases, Chronic Liver Disease and Cirrhosis, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Infection, Good Health and Well Being, Adult, Biomarkers, Tumor, Biopsy, Carcinoma, Hepatocellular, Case-Control Studies, Early Detection of Cancer, Female, Humans, Liver, Liver Neoplasms, Magnetic Resonance Imaging, Male, Middle Aged, Prospective Studies, Protein Isoforms, ROC Curve, Tomography, X-Ray Computed, Trypsin Inhibitor, Kazal Pancreatic, Clinical sciences
Abstract

IntroductionLiver cancer-secreted serine protease inhibitor Kazal (LC-SPIK) is a protein that is specifically elevated in cases of hepatocellular carcinoma (HCC). We assessed the performance of LC-SPIK in detecting HCC, including its early stages, in patients with cirrhosis, hepatitis B virus (HBV), and hepatitis C virus (HCV).MethodsWe enrolled 488 patients, including 164 HCC patients (81 early HCC) and 324 controls in a blinded, prospective, case-control study. Serum LC-SPIK levels were determined by an enzyme-linked immunosorbent assay-based assay. The performance of serum LC-SPIK and α-fetoprotein (AFP), including area under the curve (AUC), sensitivity, and specificity, are compared. The performance of LC-SPIK was evaluated in an independent validation cohort with 102 patients.ResultsIn distinguishing all HCC patients from those with cirrhosis and chronic HBV/HCV, LC-SPIK had an AUC of 0.87, with 80% sensitivity and 90% specificity using a cutoff of 21.5 ng/mL. This is significantly higher than AFP, which had an AUC of 0.70 and 52% sensitivity and 86% specificity using a standard cutoff value of 20.0 ng/mL. For early-stage HCC (Barcelona Clinic Liver Cancer stage 0 and A), LC-SPIK had an AUC of 0.85, with 72% sensitivity and 90% specificity, compared with AFP, which had an AUC of 0.61, with 42% sensitivity and 86% specificity. In addition, LC-SPIK accurately detected the presence of HCC in more than 70% of HCC patients with false-negative AFP results.DiscussionThe study provided strong evidence that LC-SPIK detects HCC, including early-stage HCC, with high sensitivity and specificity, and might be useful for surveillance in cirrhotic and chronic HBV/HCV patients, who are at an elevated risk of developing HCC.

Published
2020

10. Trends in mortality from gastrointestinal, hepatic, and pancreatic cancers in the United States: A comprehensive analysis (1999–2020)

Author

Ali, Hassam, primary, Ishtiaq, Rizwan, additional, Tedder, Brandon, additional, Zweigle, Joshua, additional, Nomigolzar, Romina, additional, Dahiya, Dushyant S, additional, Moond, Vishali, additional, Humza Sohail, Amir, additional, Patel, Pratik, additional, Basuli, Debargha, additional, and Tillmann, Hans L, additional

Published
2024
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14. S400 Comparing Adenoma Detection Rate (ADR) in Single vs Dual Observer vs Artificial Intelligence-Assisted Colonoscopy: A Network Analysis of Randomized Controlled Trials

Author

Gangwani, Manesh Kumar, primary, Haghbin, Hossein, additional, Ishtiaq, Rizwan, additional, Dahiya, Dushyant Singh., additional, Hayat, Umar, additional, Lee-Smith, Wade M., additional, Rani, Anooja, additional, Nawras, Yusuf, additional, Aziz, Muhammad, additional, Javaid, Toseef, additional, and Hart, Benjamin, additional

Published
2023
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15. The Gene Ontology knowledgebase in 2023

Author

Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Huaiyu, Mi, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Kan Yan Chloe, Li, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin C C, Renzhi, Su, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Li, Ni, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley J F, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
gene annotation, gene function, knowledge graphs, Genetics, gene ontology, Molecular Biology, knowledgebase
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

16. Association of nonalcoholic fatty liver disease with acute cholangitis: a nationwide propensity-matched analysis from the United States

Author

Patel, Pratik, primary, Inayat, Faisal, additional, Ali, Hassam, additional, Afzal, Arslan, additional, Taj, Sobaan, additional, Rehman, Attiq Ur, additional, Hussain, Nadeem, additional, Ishtiaq, Rizwan, additional, Nawaz, Gul, additional, Afzal, Muhammad Sohaib, additional, Fatakhova, Karina, additional, and Satapathy, Sanjaya K., additional

Published
2023
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18. Trends in hospital admissions and mortality among inflammatory bowel disease patients with substance use disorder: a 10-year United States nationwide analysis

Author

Fatakhova, Karina, primary, Patel, Pratik, additional, Inayat, Faisal, additional, Dhillon, Rubaid, additional, Ali, Hassam, additional, Taj, Sobaan, additional, Nawaz, Gul, additional, Afzal, Arslan, additional, Rehman, Attiq Ur, additional, Afzal, Muhammad Sohaib, additional, Khan, Rafeh, additional, Ishtiaq, Rizwan, additional, Jones, Lindsey, additional, and Rajapakse, Ramona, additional

Published
2023
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19. The Gene Ontology knowledgebase in 2023

Author

Consortium, Gene Ontology, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
Ecology,Evolution & Ethology, Cell Cycle & Chromosomes, Cell Biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023
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22. Operator-specific outcomes in endoscopic sleeve gastroplasty: a propensity-matched analysis of the US population using a multicenter database.

Author

Ali, Hassam, Inayat, Faisal, Malik, Talia F., Patel, Pratik, Nawaz, Gul, Taj, Sobaan, Rehman, Attiq Ur, Afzal, Arslan, Ishtiaq, Rizwan, Afzal, Muhammad Sohaib, Advani, Rashmi, and Watson, Rabindra R.

Abstract

Endoscopic sleeve gastroplasty (ESG) has emerged as an effective endoscopic bariatric procedure over the past decade. Data comparing short-term outcomes of ESG based on operator specialty is scarce. We aimed to assess the impact of operator specialization on patient outcomes using a large bariatric-specific database. We identified a retrospective cohort of patients who underwent ESG by gastroenterologists using the Metabolic and Bariatric Surgery Accreditation Quality Improvement Program database (2020–2021). A matched comparison cohort of patients who underwent ESG by surgeons was identified and underwent 1:1 propensity score matching based on age, race, gender, American Society of Anesthesiologists physical status classification, and preoperative body mass index. After matching, 154 patients were included in the final analysis. Of these, 77 patients underwent ESG by surgeons and 77 by gastroenterologists. In the matched cohort, the median operation time was lower in ESG by surgeons compared to gastroenterologists (P < 0.001). The median percent body mass index decrease was higher in the gastroenterologist cohort compared to the surgeon cohort (4.9% vs 3.8%, P = 0.04). The median percent weight loss after ESG was 4.8% in the surgeon cohort and 5.9% in the gastroenterologist cohort (P = 0.09). There was no statistically significant difference in postoperative emergency department visits (P = 0.65), reoperations (P = 0.15), or reinterventions within 30 days (P = 0.87) between the cohorts. There was no difference in major adverse effects between the groups (0% each). Operator choice does not affect ESG-related adverse events or 30-day outcomes in patients undergoing ESG. [ABSTRACT FROM AUTHOR]

Published
2023
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33. sj-pdf-1-hic-10.1177_2324709620987703 – Supplemental material for Jejunal Dieulafoy’s Lesion: A Systematic Review of Evaluation, Diagnosis, and Management

Author

Malik, Adnan, Inayat, Faisal, Goraya, Muhammad Hassan Naeem, Almas, Talal, Ishtiaq, Rizwan, Sohira Malik, and Tarar, Zahid Ijaz

Subjects
FOS: Biological sciences, Medicine, 69999 Biological Sciences not elsewhere classified
Abstract

Supplemental material, sj-pdf-1-hic-10.1177_2324709620987703 for Jejunal Dieulafoy’s Lesion: A Systematic Review of Evaluation, Diagnosis, and Management by Adnan Malik, Faisal Inayat, Muhammad Hassan Naeem Goraya, Talal Almas, Rizwan Ishtiaq, Sohira Malik and Zahid Ijaz Tarar in Journal of Investigative Medicine High Impact Case Reports

Published
2021
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34. Clinical characteristics and outcomes of patients with Corona Virus Disease 2019 (COVID-19) at Mercy Health Hospitals, Toledo, Ohio

Author

Khan, Muhammad Shayan, primary, Dogra, Ratika, additional, Miriyala, Leela K. V., additional, Salman, F. N. U., additional, Ishtiaq, Rizwan, additional, Patti, Dilnoor K., additional, Kumar, Aakash, additional, Sandho, Gaurav, additional, Jacob, Karim, additional, Luthra, Kritika, additional, Sharma, Ravina, additional, Ravikumar, Rekha, additional, Edara, Dharmakaruna, additional, Pittampalli, Shanti, additional, Sood, Divya, additional, Khatri, Vinod, additional, Mahajan, Vijay, additional, Avasthi, Salil, additional, Auoad, Arlette, additional, and Katragadda, Srinivas, additional

Published
2021
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