Article
Biochemical Research Methods
Peifeng Ruan, Shuang Wang
Summary: Biological network-based strategies are useful in prioritizing genes associated with diseases, but general networks may not accurately reflect gene interactions for a specific disease. By proposing the DiSNEP framework, which enhances disease-specific gene networks, more true disease-associated genes can be identified compared to other methods.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Xinyi Yu, Jiashun Xiao, Mingxuan Cai, Yuling Jiao, Xiang Wan, Jin Liu, Can Yang
Summary: The findings from genome-wide association studies have greatly helped us understand the genetic basis of human complex traits and diseases. However, several major challenges still need to be addressed, including the unknown biological functions of most GWAS hits and the identification of genetic risk variants with weak effects. To overcome these challenges, we propose a powerful and adaptive latent model (PALM) that integrates functional annotations with GWAS summary statistics.
Article
Genetics & Heredity
Johann Kaspar Lieberwirth, Benjamin Buettner, Chiara Kloeckner, Konrad Platzer, Bernt Popp, Rami Abou Jamra
Summary: This study developed an automated evaluation method named AutoCaSc based on a candidate scoring scheme, which showed high accuracy and reliability in unsolved NDD cases. The method can quickly screen and identify candidate genes in NDD, helping to determine potential new NDD genes.
Article
Biochemical Research Methods
Ekta Shah, Pradipta Maji
Summary: In the past few decades, research has extensively studied gene expression data and protein-protein interaction networks for their ability to depict important characteristics of disease-associated genes. This paper introduces a new gene prioritization algorithm that integrates information from both data sources to identify and prioritize cancer-causing genes. The proposed algorithm aims to maximize the importance of selected genes and their functional similarity, combining differential expression patterns and network connectivity as key features for potential biomarker discovery. Additionally, a scalable non-linear graph fusion technique, ScaNGraF, is proposed to learn disease-dependent functional similarity networks efficiently and with lower computational cost.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Katherine A. Kentistou, Jian'an Luan, Laura B. L. Wittemans, Catherine Hambly, Lucija Klaric, Zoltan Kutalik, John R. Speakman, Nicholas J. Wareham, Timothy J. Kendall, Claudia Langenberg, James F. Wilson, Peter K. Joshi, Nicholas M. Morton
Summary: Our understanding of the genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. In this study, the authors used whole-body imaging adiposity phenotypes in large biobanks to enhance their ability to discover genes driving human adiposity, and investigated one such gene using a mouse model.
NATURE COMMUNICATIONS
(2023)
Article
Clinical Neurology
Amy R. Hicks, Regina H. Reynolds, Benjamin O'Callaghan, Sonia Garcia-Ruiz, Ana Luisa Gil-Martinez, Juan Botia, Helene Plun-Favreau, Mina Ryten
Summary: Genes encoding the non-specific lethal complex are highly correlated with and regulate genes associated with Parkinson's disease. The complex plays a potential role in the regulation of genes and pathways implicated in Parkinson's disease. KANSL1 and KAT8 may serve as useful drug targets for Parkinson's disease.
Article
Multidisciplinary Sciences
Vasili Pankratov, Milyausha Yunusbaeva, Sergei Ryakhovsky, Maksym Zarodniuk, Andres Metspalu, Mari Nelis, Lili Milani, Reedik Magi, Tonu Esko, Bayazit Yunusbayev
Summary: Adaptive disease variants in immune genes play an important role in survival and modern inflammatory conditions. The authors used a local-tree-based approach to identify footprints of weak and moderate selection in 28% of risk loci for 21 inflammatory disorders, some of which are population specific. They also predicted the function of selected SNPs and highlighted examples of antagonistic pleiotropy.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Chun-Jing Si, Si-Min Deng, Yuan Quan, Hong-Yu Zhang
Summary: This study prioritized functional genes for complex phenotypes using PPI network-based systems genetics methods, proposing a hybrid model which significantly improved the efficiency of functional gene enrichment. The research is of great importance for functional genomics in plants.
CURRENT BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Noah R. Johnson, Peng Yuan, Erika Castillo, T. Peter Lopez, Weizhou Yue, Annalise Bond, Brianna M. Rivera, Miranda C. Sullivan, Masakazu Hirouchi, Kurt Giles, Atsushi Aoyagi, Carlo Condello
Summary: Microglia play a crucial role in the pathogenesis of various neurological diseases. The effectiveness of drugs targeting CSF1R to inhibit microglial proliferation in preclinical disease models remains unclear. In this study, CSF1R inhibitors were found to reduce pathogenic tau and normalize non-microglial gene expression in the Tg2541 tauopathy mouse model, regardless of sex. However, only female mice showed functional rescue and extended survival, while male mice exhibited excitotoxicity and gene expression patterns consistent with increased neuroinflammatory signaling. These findings emphasize the need to consider sex-dependent effects when developing therapeutics targeting microglia.
NATURE COMMUNICATIONS
(2023)
Article
Immunology
Di Wang, Bingnan Chen, Shuang Bai, Li Zhao
Summary: This study identified three immune cells significantly associated with emphysema phenotype clinical features, including increased proportion of neutrophils and decreased proportions of M2 macrophages and resting mast cells. Through WGCNA and clinical tissue validation, immune-related genes closely related to clinical features were further screened.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Multidisciplinary Sciences
Thomas Bourquard, Kwanghyuk Lee, Ismael Al-Ramahi, Minh Pham, Dillon Shapiro, Yashwanth Lagisetty, Shirin Soleimani, Samantha Mota, Kevin Wilhelm, Maryam Samieinasab, Young Won Kim, Eunna Huh, Jennifer Asmussen, Panagiotis Katsonis, Juan Botas, Olivier Lichtarge
Summary: The incidence of Alzheimer's Disease is higher in females compared to males. By using a machine learning approach focused on functionally impactful coding variants, researchers identified potential sex-specific modulators of neurodegeneration. Genes enriched for immune response pathways were found in a mixed sexes cohort, while stress-response pathways were enriched in males and cell-cycle pathways in females. These genes improved disease risk prediction and affected neurodegeneration in Drosophila, highlighting their potential as diagnostic biomarkers and therapeutic targets.
NATURE COMMUNICATIONS
(2023)
Article
Agriculture, Dairy & Animal Science
Xiangchun Pan, Jiali Cai, Yifei Wang, Dantong Xu, Yao Jiang, Wentao Gong, Yuhan Tian, Qingpeng Shen, Zhe Zhang, Xiaolong Yuan, Jiaqi Li
Summary: This study provides a comprehensive analysis of gene expression in pigs and reveals the presence of housekeeping genes, tissue-specific genes, and co-expressed genes. The results offer a fresh perspective on the transcriptional regulation of pig tissues.
Article
Cell Biology
Lin-kun Zhong, Chang-lian Xie, Shan Jiang, Xing-yan Deng, Xiao-xiong Gan, Jian-hua Feng, Wen-song Cai, Chi-zhuai Liu, Fei Shen, Jian-hang Miao, Bo Xu
Summary: Thyroid cancer ranks second in the incidence rate of endocrine malignant cancer, often asymptomatic at the initial stage, leading patients to easily miss the optimal treatment window. The combination of genetic testing and imaging can significantly improve the diagnostic efficiency of thyroid cancer.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Genetics & Heredity
Lili Yu, Hao Zhang, Rongxia Guan, Yinghui Li, Yong Guo, Lijuan Qiu
Summary: Promoters are crucial for controlling gene expression in higher plant growth and development. Tissue-specific promoters are a solution to the limitations of constitutive promoters in plant genetic engineering. This study identified 10 tissue-specific genes and their corresponding promoters through transcriptome analysis and real-time quantitative PCR. The findings demonstrate the effectiveness of high-throughput transcriptional data in tissue-specific promoter discovery.
Article
Clinical Neurology
Xiao-Lan Wang, Lianjian Li
Summary: Through the integration and analysis of 4,441 differentially expressed genes (DEGs) identified from single-nucleus RNA sequencing (snRNA-seq) of 263,370 cells in cortex samples from 42 AD pathology subjects and 39 normal controls, this study revealed common dysregulated pathways, including up-regulated LINGO1 in oligodendrocytes and excitatory neurons, and enrichment of genes in the mitochondrial module across all cell types, indicating mitochondrial dysfunction in the AD brain. The estrogen signaling pathway was identified as a disrupted pathway in AD.
Article
Urology & Nephrology
Catherine R. Butler, Paul S. Appelbaum, Heather Ascani, Mark Aulisio, Catherine E. Campbell, Ian H. de Boer, Ashveena L. Dighe, Daniel E. Hall, Jonathan Himmelfarb, Richard Knight, Karla Mehl, Raghavan Murugan, Sylvia E. Rosas, John R. Sedor, John F. O'Toole, Katherine R. Tuttle, Sushrut S. Waikar, Michael Freeman
Summary: This article emphasizes the importance of critically examining the ethical basis of human subjects research involving some risks without anticipated clinical benefits. It provides a comprehensive conceptualization of the types of benefits that may be important to research participants and proposes a model to better respect and support participants in future research.
AMERICAN JOURNAL OF KIDNEY DISEASES
(2022)
Correction
Biochemical Research Methods
Jian Zhou, Olga G. Troyanskaya
Article
Oncology
Abhinav Jaiswal, Akanksha Verma, Ruth Dannenfelser, Marit Melssen, Itay Tirosh, Benjamin Izar, Tae-Gyun Kim, Christopher J. Nirschl, K. Sanjana P. Devi, Walter C. Olson, Craig L. Slingluff, Victor H. Engelhard, Levi Garraway, Aviv Regev, Kira Minkis, Charles H. Yoon, Olga Troyanskaya, Olivier Elemento, Mayte Suarez-Farinas, Niroshana Anandasabapathy
Summary: Better classification and understanding of tumor-infiltrating lymphocytes (TILs) is needed. This study found enrichment of T memory/resident memory programs in solid tumors compared to other T cell states. Single-cell analysis of melanoma CD8(+) TILs revealed a high proportion of memory/resident memory-scoring TILs in responders to anti-PD-1 therapy. TILs scoring highly for early T cell activation, but not exhaustion, were associated with non-response. Late/persistent activation signatures were predictive of melanoma survival and co-expressed with dendritic cell and IFN-gamma response programs.
Article
Urology & Nephrology
Rachel Sealfon, Laura Mariani, Carmen Avila-Casado, Viji Nair, Rajasree Menon, Julien Funk, Aaron Wong, Gabriel Lerner, Norifumi Hayashi, Olga Troyanskaya, Matthias Kretzler, Laurence H. Beck
Summary: Using gene expression data from the kidney tissue, MN patients can be accurately distinguished from other kidney disease patients. By analyzing the gene expression differences between MN patients and other glomerulonephropathy patients, specific gene modules related to MN can be identified in a kidney-specific functional network, indicating upregulation of podocyte-expressed genes in MN.
JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
(2022)
Article
Urology & Nephrology
Rajasree Menon, Andrew S. Bomback, Blue B. Lake, Christy Stutzke, Stephanie M. Grewenow, Steven Menez, Vivette D. D'Agati, Sanjay Jain
KIDNEY INTERNATIONAL
(2022)
Article
Cell Biology
Zidong Zhang, Michel Zamojski, Gregory R. Smith, Thea L. Willis, Val Yianni, Natalia Mendelev, Hanna Pincas, Nitish Seenarine, Mary Anne S. Amper, Mital Vasoya, Wan Sze Cheng, Elena Zaslavsky, Venugopalan D. Nair, Judith L. Turgeon, Daniel J. Bernard, Olga G. Troyanskaya, Cynthia L. Andoniadou, Stuart C. Sealfon, Frederique Ruf-Zamojski
Summary: This study characterizes the gene expression and chromatin accessibility of human pituitary stem cells (PSCs) using single nucleus RNA-seq and ATAC-seq. The researchers identified uncommitted PSCs, committing progenitor cells, and sex differences, as well as distinct mechanisms contributing to heterogeneous marker expression within PSCs.
Article
Immunology
Alessandra Soares-Schanoski, Natalie Sauerwald, Carl W. Goforth, Sivakumar Periasamy, Dawn L. Weir, Stephen Lizewski, Rhonda Lizewski, Yongchao Ge, Natalia A. Kuzmina, Venugopalan D. Nair, Sindhu Vangeti, Nada Marjanovic, Antonio Cappuccio, Wan Sze Cheng, Sagie Mofsowitz, Clare M. Miller, Xuechen B. Yu, Mary-Catherine George, Elena Zaslavsky, Alexander Bukreyev, Olga G. Troyanskaya, Stuart C. Sealfon, Andrew G. Letizia, Irene Ramos
Summary: Research has shown that asymptomatic and mild symptomatic COVID-19 infections in young adults have similar viral loads and specific antibody responses, but there are differences in inflammatory protein profiles. Some analytes in asymptomatic infections are associated with tissue repair and may contribute to symptom control.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Health Care Sciences & Services
Jitao Wang, Yu Fang, Elena Frank, Maureen A. Walton, Margit Burmeister, Ambuj Tewari, Walter Dempsey, Timothy NeCamp, Srijan Sen, Zhenke Wu
Summary: The gamified team competition delivered via mobile app significantly increases daily step count for medical interns, but does not significantly affect sleep duration. The effects of competition on step count and sleep duration decrease over time. The results suggest that team competition can serve as a mobile health intervention tool to increase short-term physical activity levels for medical interns.
NPJ DIGITAL MEDICINE
(2023)
Review
Biochemical Research Methods
Jiashu Liu, Cui-Xiang Lin, Xiaoqi Zhang, Zongxuan Li, Wenkui Huang, Jin Liu, Yuanfang Guan, Hong-Dong Li
Summary: Alternative splicing (AS), a key pathway for transcriptional regulation, has been shown to be associated with complex diseases. Computational approaches for detecting disease-associated AS events have been developed. This review discusses the metrics used for characterizing AS events quantitatively. It also reviews and discusses three types of methods for detecting disease-associated splicing events: differential splicing analysis, aberrant splicing detection, and splicing-related network analysis. Additionally, methods for detecting genetic variants that potentially regulate splicing are described. Experimental comparisons are conducted to illustrate the performance of each method. The limitations of these methods are discussed, as well as potential ways to address them. This review aims to provide a systematic understanding of computational approaches for analyzing disease-associated splicing.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Weiguang Mao, Clare M. Miller, Venugopalan D. Nair, Yongchao Ge, Mary Anne S. Amper, Antonio Cappuccio, Mary-Catherine George, Carl W. Goforth, Kristy Guevara, Nada Marjanovic, German Nudelman, Hanna Pincas, Irene Ramos, Rachel S. G. Sealfon, Alessandra Soares-Schanoski, Sindhu Vangeti, Mital Vasoya, Dawn L. Weir, Elena Zaslavsky, Seunghee Biobank Team, Seunghee Kim-Schulze, Sacha Gnjatic, Miriam Merad, Andrew G. Letizia, Olga G. Troyanskaya, Stuart C. Sealfon, Maria Chikina
Summary: DNA methylation is a cumulative record of lifetime exposures and genetic markers. This study investigated the dynamics of blood epigenetic remodeling following asymptomatic and mildly symptomatic SARS-CoV-2 infection. Differential methylation persisted for months after infection and resembled autoimmune or inflammatory disease. Machine learning models based on methylation accurately distinguished different infection time periods and predicted time since infection. The clinical trajectory of young adults and a diverse cohort with severe outcomes was predicted based on the similarity of methylation before or early after SARS-CoV-2 infection to the postinfection state defined by the model. The postacute SARS-CoV-2 epigenetic landscape identified in this study is antiprotective.
MOLECULAR SYSTEMS BIOLOGY
(2023)
Article
Cell Biology
Camille Brewer, Tobias Lanz, Caryn R. Hale, Gregory D. Sepich-Poore, Cameron Martino, Austin D. Swafford, Thomas S. Carroll, Sarah Kongpachith, Lisa K. Blum, Serra E. Elliott, Nathalie E. Blachere, Salina Parveen, John Fak, Vicky Yao, Olga Troyanskaya, Mayu O. Frank, Michelle S. Bloom, Shaghayegh Jahanbani, Alejandro M. Gomez, Radhika Iyer, Nitya S. Ramadoss, Orr Sharpe, Sangeetha Chandrasekaran, Lindsay B. Kelmenson, Qian Wang, Heidi Wong, Holly L. Torres, Mark Wiesen, Dana T. Graves, Kevin D. Deane, V. Michael Holers, Rob Knight, Robert B. Darnell, William H. Robinson, Dana E. Orange
Summary: This study found that periodontal disease is more common in individuals with rheumatoid arthritis (RA) who have detectable anticitrullinated protein antibodies (ACPAs), suggesting a link between oral mucosal inflammation and RA pathogenesis. The researchers also discovered that RA patients with periodontal disease experienced repeated oral bacteremias associated with transcriptional signatures of specific monocyte subsets observed in inflamed RA synovia and blood during RA flares. The bacteremia was caused by citrullinated oral bacteria and resulted in activation of ACPA B cells, promoting affinity maturation and epitope spreading to citrullinated human antigens.
SCIENCE TRANSLATIONAL MEDICINE
(2023)
Article
Biology
Hanrui Zhang, Ziyan Wang, Yiyang Nan, Bulat Zagidullin, Daiyao Yi, Jing Tang, Yuanfang Guan
Summary: Researchers evaluated the transferability issue of single-study-derived models on new datasets and proposed a method to reduce the impact of experimental variability. The method improved the prediction performance of machine learning models by 184% and 1367% compared to baseline models in intra-study and inter-study predictions, respectively, and showed consistent improvement in multiple cross-validation settings. This study addresses the crucial question of transferability in drug combination predictions and is important for extrapolating these models to new drug combination discovery and clinical applications that involve different datasets.
COMMUNICATIONS BIOLOGY
(2023)
Article
Biochemical Research Methods
Zijun Zhang, Natalie Sauerwald, Antonio Cappuccio, Irene Ramos, Venugopalan D. Nair, German Nudelman, Elena Zaslavsky, Yongchao Ge, Angelo Gaitas, Hui Ren, Joel Brockman, Jennifer Geis, Naveen Ramalingam, David King, Micah T. McClain, Christopher W. Woods, Ricardo Henao, Thomas W. Burke, Ephraim L. Tsalik, Carl W. Goforth, Rhonda A. Lizewski, Stephen E. Lizewski, Dawn L. Weir, Andrew G. Letizia, Stuart C. Sealfon, Olga G. Troyanskaya
Summary: Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events have the potential to be better diagnostic biomarkers compared to gene expression. This study presents a computational framework for developing AS diagnostic biomarkers using SARS-CoV-2 infection data and identifies a major functional AS program switch upon viral infection. AS-based biomarkers are more accurate for SARS-CoV-2 diagnosis compared to transcriptome signatures, and microfluidic PCR diagnostic assays achieve nearly perfect test accuracy.
CELL REPORTS METHODS
(2023)
Article
Automation & Control Systems
Weilin Meng, Xinyuan Zhang, Boshu Ru, Yuanfang Guan
Summary: A methodology for predicting real-world time to treatment discontinuation (rwTTD) has been developed, which shows robust performance across different populations and diseases. This study establishes a generic pipeline for real-world time on treatment prediction that can be applied to various machine learning algorithms and drugs.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Article
Medicine, Research & Experimental
Brendon Lutnick, David Manthey, Jan U. Becker, Brandon Ginley, Katharina Moos, Jonathan E. Zuckerman, Luis Rodrigues, Alexander J. Gallan, Laura Barisoni, Charles E. Alpers, Xiaoxin X. Wang, Komuraiah Myakala, Bryce A. Jones, Moshe Levi, Jeffrey B. Kopp, Teruhiko Yoshida, Jarcy Zee, Seung Seok Han, Sanjay Jain, Avi Z. Rosenberg, Kuang Yu. Jen, Pinaki Sarder
Summary: Artificial intelligence is useful in pathology for analyzing microscopic images of tissues. The study has developed a cloud-based tool for pathology image segmentation, which is easy to use and accurate. It can estimate the presence of certain structures as reliably as human experts.
COMMUNICATIONS MEDICINE
(2022)