Data Science Commons^™

Statins Are Rarely Prescribed For Incidentally Discovered Covert Cerebrovascular Disease: A Retrospective Cohort In A Large Electronic Health Record (Ehr) Identified Using Natural Language Processing, Lester Y Leung, Eric Puttock, David F Kallmes, Patrick Luetmer, Sunyang Fu, Chengyi X Zheng, Hongfang Liu, Wansu Chen, David M Kent

Faculty, Staff and Student Publications

Introduction: While incidentally discovered covert cerebrovascular diseases (id-CCD) are associated with future stroke, it is not known if patients with id-CCD are prescribed statins.

Methods: Patients age ≥50 with id-CCD on neuroimaging from 2009 to 2019 with no prior ischaemic stroke, transient ischaemic attack or dementia were identified using natural language processing in a large real-world cohort. Robust Poisson multivariable regression was used to assess statin prescription among patients without prior statins.

Results: Among 2 41 050 patients, 74 975 patients (31.1%; 4.7% with covert brain infarcts (CBI); 29.0% with white matter disease (WMD)) had id-CCD. 53.5% (95% CI 53.2 …

The Enact Network Is Acting On Housing Instability And The Unhoused Using The Open Health Natural Language Processing Toolkit, Daniel R Harris, Sunyang Fu, Andrew Wen, Alexandria Corbeau, Darren Henderson, Jordan Hilsman, David Oniani, Yanshan Wang

Faculty, Staff and Student Publications

Housing is an environmental social determinant of health that is linked to mortality and clinical outcomes. We developed a lexicon of housing-related concepts and rule-based natural language processing methods for identifying these housing-related concepts within clinical text. We piloted our methods on several test cohorts: a synthetic cohort generated by ChatGPT for initial infrastructure testing, a cohort with substance use disorders (SUD), and a cohort diagnosed with problems related to housing and economic circumstances (HEC). Our methods successfully identified housing concepts in our ChatGPT notes (recall = 1.0, precision = 1.0), our SUD population (recall = 0.9798, precision = 0.9898), …

Descriptor:Benchmarking Secure Neural Network Evaluation Methods For Protein Sequence Classification (Idash24), Arif Harmanci, Luyao Chen, Miran Kim, Xiaoqian Jiang

Faculty, Staff and Student Publications

To uniformly test and benchmark the secure evaluation of transformer-based models, we designed the iDASH24 homomorphic encryption track dataset. The dataset comprises a protein family classification model with a transformer architecture and an example dataset that is used to build and test the secure evaluation strategies. This dataset was used in the challenge period of iDASH24 Genomic Privacy Competition, where the teams designed secure evaluation of the classification model using a homomorphic encryption scheme. Combined with the benchmarking results and companion methods, iDASH24 dataset is a unique resource that can be used to benchmark secure evaluation of neural network models.

Prioritizing Clinically Significant Lung Cancer Somatic Mutations For Targeted Therapy Through Efficient Ngs Data Filtering System, Jinlian Wang, Hui Li, Hongfang Liu

Faculty, Staff and Student Publications

In the realm of lung cancer treatment, where genetic heterogeneity presents formidable challenges, precision oncology demands an exacting approach to identify and hierarchically sort clinically significant somatic mutations. Current Next-Generation Sequencing (NGS) data filtering pipelines, while utilizing various external databases for mutation screening, often fall short in comprehensive integration and flexibility needed to keep pace with the evolving landscape of clinical data. Our study introduces a sophisticated NGS data filtering system, which not only aggregates but effectively synergizes diverse data sources, encompassing genetic variants, gene functions, clinical evidence, and an extensive body of literature. This system is distinguished by a …

Sequencing Conversational Turns In Peer Interactions: An Integrated Approach For Evidence-Based Conversational Agent For Just-In-Time Nicotine Cravings Intervention, Tavleen Singh, Michael Truong, Kirk Roberts, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Risky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions.

METHODS: In this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior …

Linking Cancer Clinical Trials To Their Result Publications, Evan Pan, Kirk Roberts

Faculty, Staff and Student Publications

The results of clinical trials are a valuable source of evidence for researchers, policy makers, and healthcare professionals. However, online trial registries do not always contain links to the publications that report on their results, instead requiring a time-consuming manual search. Here, we explored the application of pre-trained transformer-based language models to automatically identify result-reporting publications of cancer clinical trials by computing dense vectors and performing semantic search. Models were fine-tuned on text data from trial registry fields and article metadata using a contrastive learning approach. The best performing model was PubMedBERT, which achieved a mean average precision of 0.592 …

Community Scientist Program Provides Bi-Directional Communication And Co-Learning Between Researchers And Community Members, Jessica Alvarado, Larkin L Strong, Birnur Buzcu-Guven, Leonetta B Thompson, Erica Cantu, Chelsea C Carrier, Chiamaka D Chukwu, Cassandra L Harris, Luz K Melendez, Crystal L Roberson, Angela M Ross, Sophia C Russell, Pablo Sanchez, Amirali Tahanan, Blair C Zdenek, Belinda M Reininger, Lorna H Mcneill

Faculty, Staff and Student Publications

Community involvement in research is key to translating science into practice, and new approaches to engaging community members in research design and implementation are needed. The Community Scientist Program, established at the MD Anderson Cancer Center in Houston in 2018 and expanded to two other Texas institutions in 2021, provides researchers with rapid feedback from community members on study feasibility and design, cultural appropriateness, participant recruitment, and research implementation. This paper aims to describe the Community Scientist Program and assess Community Scientists' and researchers' satisfaction with the program. We present the analysis of the data collected from 116 Community Scientists …

Human Equilibrative Nucleoside Transporter 1: Novel Biomarker And Prognostic Indicator For Patients With Gemcitabine-Treated Pancreatic Cancer, Jianchun Xiao, Fangyu Zhao, Wenhao Luo, Gang Yang, Yicheng Wang, Jiangdong Qiu, Yueze Liu, Lei You, Lianfang Zheng, Taiping Zhang

Faculty, Staff and Student Publications

AIM: This article aimed to find appropriate pancreatic cancer (PC) patients to treat with Gemcitabine with better survival outcomes by detecting hENT1 levels.

METHODS: We collected surgical pathological tissues from PC patients who received radical surgery in our hospital from September 2004 to December 2014. A total of 375 PC tissues and paired adjacent nontumor tissues were employed for the construction of 4 tissue microarrays (TMAs). The quality of the 4 TMAs was examined by HE staining. We performed immunohistochemistry analysis to evaluate hENT1 expression in the TMAs. Moreover, we detected hENT1 expression level and proved the role of hENT1 …

Visualsphere: A Web-Based Interactive Visualization System For Clinical Research Data, Shiwei Lin, Shiqiang Tao, Wei-Chun Chou, Guo-Qiang Zhang, Xiaojin Li

Faculty, Staff and Student Publications

Clinical research data visualization is integral to making sense of biomedical research and healthcare data. The complexity and diversity of data, along with the need for solid programming skills, can hinder advances in clinical research data visualization. To overcome these challenges, we introduce VisualSphere, a web-based interactive visualization system that directly interfaces with clinical research data repositories, streamlining and simplifying the visualization workflow. VisualSphere is founded on three primary component modules: Connection, Configuration, and Visualization. An end-user can set up connections to the data repositories, create charts by selecting the desired tables and variables, and render visualization dashboards generated by …

A Real-World Disproportionality Analysis Of Everolimus: Data Mining Of The Public Version Of Fda Adverse Event Reporting System, Bin Zhao, Yumei Fu, Shichao Cui, Xiangning Chen, Shu Liu, Lan Luo

Faculty, Staff and Student Publications

Background: Everolimus is an inhibitor of the mammalian target of rapamycin and is used to treat various tumors. The presented study aimed to evaluate the Everolimus-associated adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS).

Methods: The AE records were selected by searching the FDA Adverse Event Reporting System database from the first quarter of 2009 to the first quarter of 2022. Potential adverse event signals were mined using the disproportionality analysis, including reporting odds ratio the proportional reporting ratio the Bayesian confidence propagation neural network and the empirical Bayes geometric …

Linking Artificial Sweetener Intake With Kidney Function: Insights From Nhanes 2003-2006 And Findings From Mendelian Randomization Research, Zhuoling Ran, Yuxuan Zheng, Lin Yu, Yuxian Zhang, Zhenjiang Zhang, Huijie Li, Xuhan Li, Jing Song, Li Zhang, Ran Zhang, Chang Lu, Yang Gong, Jian Gong

Faculty, Staff and Student Publications

BACKGROUND: The current investigation examines the association between artificial sweetener (AS) consumption and the likelihood of developing chronic kidney disease (CKD), along with its impact on kidney function.

METHODS: We utilized data from the National Health and Nutrition Examination Survey from 2003-2006 to conduct covariance analysis and weighted adjusted logistic regression, aiming to assess the association between artificial sweetener intake and CKD risk, as well as kidney function indicators. Subsequently, we employed Mendelian randomization methods to validate the causal relationship between the intake of artificial sweeteners, CKD risk, and kidney function indicators. Instrumental variable analysis using inverse-variance weighting and Robust …

Siglec15, Negatively Correlated With Pd-L1 In Hcc, Could Induce Cd8+ T Cell Apoptosis To Promote Immune Evasion, Zheng Chen, Mincheng Yu, Bo Zhang, Lei Jin, Qiang Yu, Shuang Liu, Binghai Zhou, Jiuliang Yan, Wentao Zhang, Xiaoqiang Li, Yongfeng Xu, Yongsheng Xiao, Jian Zhou, Jia Fan, Mien-Chie Hung, Qinghai Ye, Hui Li, Lei Guo

Faculty, Staff and Student Publications

Functional roles of SIGLEC15 in hepatocellular carcinoma (HCC) were not clear, which was recently found to be an immune inhibitor with similar structure of inhibitory B7 family members. SIGLEC15 expression in HCC was explored in public databases and further examined by PCR analysis. SIGLEC15 and PD-L1 expression patterns were examined in HCC samples through immunohistochemistry. SIGLEC15 expression was knocked-down or over-expressed in HCC cell lines, and CCK8 tests were used to examine cell proliferative ability in vitro. Influences of SIGLEC15 expression on tumor growth were examined in immune deficient and immunocompetent mice respectively. Co-culture system of HCC cell lines and …

Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches Da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak

Faculty, Staff and Student Publications

Genetically modified (GM) crops that have been engineered to express transgenes have been in commercial use since 1995 and are annually grown on 200 million hectares globally. These crops have provided documented benefits to food security, rural economies, and the environment, with no substantiated case of food, feed, or environmental harm attributable to cultivation or consumption. Despite this extensive history of advantages and safety, the level of regulatory scrutiny has continually increased, placing undue burdens on regulators, developers, and society, while reinforcing consumer distrust of the technology. CropLife International held a workshop at the 16th International Society of Biosafety Research …

Vagus Nerve Stimulation For The Therapy Of Dravet Syndrome: A Systematic Review And Meta-Analysis, Shuang Chen, Man Li, Ming Huang

Faculty, Staff and Student Publications

OBJECTIVE: Dravet syndrome (DS) is a refractory developmental and epileptic encephalopathy characterized by seizures, developmental delay and cognitive impairment with a variety of comorbidities, including autism-like behavior, speech dysfunction, and ataxia. Vagus nerve stimulation (VNS) is one of the common therapies for DS. Here, we aim to perform a meta-analysis and systematic review of the efficacy of VNS in DS patients.

METHODS: We systematically searched four databases (PubMed, Embase, Cochrane and CNKI) to identify potentially eligible studies from their inception to January 2024. These studies provided the effective rate of VNS in treating patients with DS. The proportions of DS …

Leveraging Redundancy As A Link Between Spreading Dynamics On And Of Networks, Felipe Xavier Costa

Electronic Theses & Dissertations (2024 - present)

A constant quest in network science has been in the development of methods to identify the most relevant components in a dynamical system solely via the interaction structure amongst its subsystems. This information allows the development of control and intervention strategies in biochemical signaling and epidemic spreading. We highlight the relevant components in heterogeneous dynamical system by their patterns of redundancy, which can connect how dynamics affect network topology and which pathways are necessary to spreading phenomena on networks. In order to measure the redundancies in a large class of empirical systems, we develop the backbone of directed networks methodology, …

Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas

Theses and Dissertations--Chemical and Materials Engineering

Hydrophobic deep eutectic solvents (DESs) have emerged as excellent extractants. A major challenge is the lack of an efficient tool to discover DES candidates. Currently, the search relies heavily on the researchers’ intuition or a trial-and-error process, which leads to a low success rate or bypassing of promising candidates. DES performance depends on the heterogeneous hydrogen bond environment formed by multiple hydrogen bond donors and acceptors. Understanding this heterogeneous hydrogen bond environment can help develop principles for designing high performance DESs for extraction and other separation applications. This work investigates the structure and dynamics of hydrogen bonds in hydrophobic DESs …

Combination Chemotherapy Optimization With Discrete Dosing, Temitayo Ajayi, Seyedmohammadhossein Hosseinian, Andrew J Schaefer, Clifton D Fuller

Faculty, Staff and Student Publications

Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens; one way to alleviate this burden and better inform future trials is to build reliable models for drug administration. This paper presents a mixed-integer program for combination chemotherapy (utilization of multiple drugs) optimization that incorporates various important operational constraints and, besides dose and concentration limits, controls treatment toxicity based on its effect on the count of white blood cells. To address the uncertainty of tumor heterogeneity, we also propose chance constraints that guarantee reaching an operable tumor size with a high probability in …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Lesion Detection In Women Breast’S Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using Deep Learning, Sudarshan Saikia, Tapas Si, Darpan Deb, Kangkana Bora, Saurav Mallik, Ujjwal Maulik, Zhongming Zhao

Faculty, Staff and Student Publications

Breast cancer is one of the most common cancers in women and the second foremost cause of cancer death in women after lung cancer. Recent technological advances in breast cancer treatment offer hope to millions of women in the world. Segmentation of the breast's Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is one of the necessary tasks in the diagnosis and detection of breast cancer. Currently, a popular deep learning model, U-Net is extensively used in biomedical image segmentation. This article aims to advance the state of the art and conduct a more in-depth analysis with a focus on the use …

Deep Learning For Microbiome-Based Integrative Modeling And Microbial Biomarkers Identification, Sen Yang

Statistical Science Theses and Dissertations

The human microbiome, comprising trillions of microorganisms, plays a pivotal role in modulating host physiology via molecular and metabolite exchanges. One of the major challenges in this field lies in the effective integration of microbiome and metabolomics data, an achievement that holds the promise of substantially enhancing the precision of disease prediction. However, many datasets prioritize microbiome data while neglecting paired metabolome information. Additionally, the prevalent analytical tools face challenges in effectively merging these intricate datasets, leading to possible misinterpretations and reduced prediction accuracies.

To address these challenges, the first part of this research introduces the Microbiome-based Supervised Contrastive Learning …

Mitochondrial Dna Variants At Low-Level Heteroplasmy And Decreased Copy Numbers In Chronic Kidney Disease (Ckd) Tissues With Kidney Cancer, Yuki Kanazashi, Kazuhiro Maejima, Todd A Johnson, Shota Sasagawa, Ryosuke Jikuya, Hisashi Hasumi, Naomichi Matsumoto, Shigekatsu Maekawa, Wataru Obara, Hidewaki Nakagawa

Faculty, Staff and Student Publications

The human mitochondrial genome (mtDNA) is a circular DNA molecule with a length of 16.6 kb, which contains a total of 37 genes. Somatic mtDNA mutations accumulate with age and environmental exposure, and some types of mtDNA variants may play a role in carcinogenesis. Recent studies observed mtDNA variants not only in kidney tumors but also in adjacent kidney tissues, and mtDNA dysfunction results in kidney injury, including chronic kidney disease (CKD). To investigate whether a relationship exists between heteroplasmic mtDNA variants and kidney function, we performed ultra-deep sequencing (30,000×) based on long-range PCR of DNA from 77 non-tumor kidney …

Association Between Viral Infections And Glioma Risk: A Two-Sample Bidirectional Mendelian Randomization Analysis, Sheng Zhong, Wenzhuo Yang, Zhiyun Zhang, Yangyiran Xie, Lin Pan, Jiaxin Ren, Fei Ren, Yifan Li, Haoqun Xie, Hongyu Chen, Davy Deng, Jie Lu, Hui Li, Bo Wu, Youqi Chen, Fei Peng, Vinay K Puduvalli, Ke Sai, Yunqian Li, Ye Cheng, Yonggao Mou

Faculty, Staff and Student Publications

Background: Glioma is one of the leading types of brain tumor, but few etiologic factors of primary glioma have been identified. Previous observational research has shown an association between viral infection and glioma risk. In this study, we used Mendelian randomization (MR) analysis to explore the direction and magnitude of the causal relationship between viral infection and glioma.

Methods: We conducted a two-sample bidirectional MR analysis using genome-wide association study (GWAS) data. Summary statistics data of glioma were collected from the largest meta-analysis GWAS, involving 12,488 cases and 18,169 controls. Single-nucleotide polymorphisms (SNPs) associated with exposures were used as instrumental …

Brain-Wide Correspondence Of Neuronal Epigenomics And Distant Projections, Jingtian Zhou, Zhuzhu Zhang, May Wu, Hanqing Liu, Yan Pang, Anna Bartlett, Zihao Peng, Wubin Ding, Angeline Rivkin, Will N Lagos, Elora Williams, Cheng-Ta Lee, Paula Assakura Miyazaki, Andrew Aldridge, Qiurui Zeng, J L Angelo Salinda, Naomi Claffey, Michelle Liem, Conor Fitzpatrick, Lara Boggeman, Zizhen Yao, Kimberly A Smith, Bosiljka Tasic, Jordan Altshul, Mia A Kenworthy, Cynthia Valadon, Joseph R Nery, Rosa G Castanon, Neelakshi S Patne, Minh Vu, Mohammad Rashid, Matthew Jacobs, Tony Ito, Julia Osteen, Nora Emerson, Jasper Lee, Silvia Cho, Jon Rink, Hsiang-Hsuan Huang, António Pinto-Duartec, Bertha Dominguez, Jared B Smith, Carolyn O'Connor, Hongkui Zeng, Shengbo Chen, Kuo-Fen Lee, Eran A Mukamel, Xin Jin, M Margarita Behrens, Joseph R Ecker, Edward M Callaway

Faculty, Staff and Student Publications

Single-cell analyses parse the brain’s billions of neurons into thousands of ‘cell-type’ clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. …

Selecting Patient-Reported Outcome Measures For A Patient-Facing Technology, Priyank Raj, Youmin Cho, Yun Jiang, Yang Gong

Faculty, Staff and Student Publications

OBJECTIVE: This article provides insight into our process and considerations for selecting patient-reported outcome measures (PROMs) designed for self-reporting symptoms and quality-of-life among breast cancer (BCA) patients undergoing oral anticancer agent treatment via a patient-facing technology (PFT) platform.

METHODS: Following established guidelines, we conducted a thorough assessment of a specific set of PROMs, comparing their content to identify the most suitable options for studying BCA patients.

RESULTS: We recommend utilizing the combination of EORTC QLQ-C30 + EORTC QLQ-BR45 as the preferred instrument, especially when developing a dedicated "breast cancer-only" application.

DISCUSSION: When developing and maintaining a dashboard for a PFT …

Discovery Of Novel 2-Aminopyridine Derivatives As Ros1 And Alk Dual Inhibitors To Combat Drug-Resistant Mutants Including Ros1g2032r And Alkg1202r, Siming Liu, Chuan Huang, Chunhui Huang, Yaqi Huang, Yonghuan Yu, Guowu Wu, Fengqiu Guo, Ying Jiang, Shanhe Wan, Zhengguang Zhu, Yuanxin Tian, Jianghua Zhu, Jiajie Zhang

Faculty, Staff and Student Publications

Clinical treatment by FDA-approved ROS1/ALK inhibitor Crizotinib significantly improved the therapeutic outcomes. However, the emergence of drug resistance, especially driven by acquired mutations, have become an inevitable problem and worsened the clinical effects of Crizotinib. To combat drug resistance, some novel 2-aminopyridine derivatives were designed rationally based on molecular simulation, then synthesised and subjected to biological test. The preferred spiro derivative C01 exhibited remarkable activity against CD74-ROS1G2032R cell with an IC50 value of 42.3 nM, which was about 30-fold more potent than Crizotinib. Moreover, C01 also potently inhibited enzymatic activity against clinically Crizotinib-resistant ALKG1202R, harbouring a 10-fold potency superior to …

Targeted Gene Expression Profiling Predicts Meningioma Outcomes And Radiotherapy Responses, William C Chen, Abrar Choudhury, Mark W Youngblood, Mei-Yin C Polley, Calixto-Hope G Lucas, Kanish Mirchia, Sybren L N Maas, Abigail K Suwala, Minhee Won, James C Bayley, Akdes S Harmanci, Arif O Harmanci, Tiemo J Klisch, Minh P Nguyen, Harish N Vasudevan, Kathleen Mccortney, Theresa J Yu, Varun Bhave, Tai-Chung Lam, Jenny Kan-Suen Pu, Lai-Fung Li, Gilberto Ka-Kit Leung, Jason W Chan, Haley K Perlow, Joshua D Palmer, Christine Haberler, Anna S Berghoff, Matthias Preusser, Theodore P Nicolaides, Christian Mawrin, Sameer Agnihotri, Adam Resnick, Brian R Rood, Jessica Chew, Jacob S Young, Lauren Boreta, Steve E Braunstein, Jessica Schulte, Nicholas Butowski, Sandro Santagata, David Spetzler, Nancy Ann Oberheim Bush, Javier E Villanueva-Meyer, James P Chandler, David A Solomon, C Leland Rogers, Stephanie L Pugh, Minesh P Mehta, Penny K Sneed, Mitchel S Berger, Craig M Horbinski, Michael W Mcdermott, Arie Perry, Wenya Linda Bi, Akash J Patel, Felix Sahm, Stephen T Magill, David R Raleigh

Faculty, Staff and Student Publications

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems …

Fimap A Fast Identity-By-Descent Mapping Test For Biobank-Scale Cohorts, Han Chen, Ardalan Naseri, Degui Zhi

Faculty, Staff and Student Publications

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. …

A Transcriptomic Taxonomy Of Mouse Brain-Wide Spinal Projecting Neurons, Carla C Winter, Anne Jacobi, Junfeng Su, Leeyup Chung, Cindy T J Van Velthoven, Zizhen Yao, Changkyu Lee, Zicong Zhang, Shuguang Yu, Kun Gao, Geraldine Duque Salazar, Evgenii Kegeles, Yu Zhang, Makenzie C Tomihiro, Yiming Zhang, Zhiyun Yang, Junjie Zhu, Jing Tang, Xuan Song, Ryan J Donahue, Qing Wang, Delissa Mcmillen, Michael Kunst, Ning Wang, Kimberly A Smith, Gabriel E Romero, Michelle M Frank, Alexandra Krol, Riki Kawaguchi, Daniel H Geschwind, Guoping Feng, Lisa V Goodrich, Yuanyuan Liu, Bosiljka Tasic, Hongkui Zeng, Zhigang He

Faculty, Staff and Student Publications

The brain controls nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from the brain to the spinal cord. However, a comprehensive molecular characterization of brain-wide SPNs is still lacking. Here we transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain1. This taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) heterogeneous populations in the reticular formation with broad …

Single-Cell Analysis Of Chromatin Accessibility In The Adult Mouse Brain, Songpeng Zu, Yang Eric Li, Kangli Wang, Ethan J Armand, Sainath Mamde, Maria Luisa Amaral, Yuelai Wang, Andre Chu, Yang Xie, Michael Miller, Jie Xu, Zhaoning Wang, Kai Zhang, Bojing Jia, Xiaomeng Hou, Lin Lin, Qian Yang, Seoyeon Lee, Bin Li, Samantha Kuan, Hanqing Liu, Jingtian Zhou, Antonio Pinto-Duarte, Jacinta Lucero, Julia Osteen, Michael Nunn, Kimberly A Smith, Bosiljka Tasic, Zizhen Yao, Hongkui Zeng, Zihan Wang, Jingbo Shang, M Margarita Behrens, Joseph R Ecker, Allen Wang, Sebastian Preissl, Bing Ren

Faculty, Staff and Student Publications

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are …

Molecularly Defined And Spatially Resolved Cell Atlas Of The Whole Mouse Brain, Meng Zhang, Xingjie Pan, Won Jung, Aaron R Halpern, Stephen W Eichhorn, Zhiyun Lei, Limor Cohen, Kimberly A Smith, Bosiljka Tasic, Zizhen Yao, Hongkui Zeng, Xiaowei Zhuang

Faculty, Staff and Student Publications

In mammalian brains, millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells have impeded our understanding of the molecular and cellular basis of brain function. Recent advances in spatially resolved single-cell transcriptomics have enabled systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3, including several brain regions (for example, refs. 1-11). However, a comprehensive cell atlas of the whole brain is still missing. Here we imaged a panel of more than 1,100 genes in approximately 10 million cells across the …