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Application of a deep learning algorithm in the detection of hip fractures

ISCIENCE 2023年第8期26卷 107350页

作者： Gao, Yan Soh, Nicholas Yock Teck Liu, Nan Lim, Gilbert Ting, Daniel Cheng, Lionel Tim-Ee Min, Kang Liew, Charlene Oh, Hong Choon Tan, Jin Rong Venkataraman, Narayan Goh, Siang Hiong Yan, Yet Yen Singapore Hlth Serv SingHlth Changi Gen Hosp Hlth Serv Res Singapore Singapore Singapore Hlth Serv SingHlth Changi Gen Hosp Dept Diagnost Radiol Singapore Singapore Duke NUS Med Sch Ctr Quantitat Med Singapore Singapore Singapore Hlth Serv SingHlth Duke NUS Med Sch Singapore Singapore Singapore Gen Hosp Dept Diagnost Radiol Singapore Singapore Duke NUS Med Sch Radiol Sci ACP Singapore Singapore Singapore Hlth Serv SingHlth Changi Gen Hosp Dept Med Informat Singapore Singapore Singapore Hlth Serv SingHlth Changi Gen Hosp Dept Emergency Med Singapore Singapore

This paper describes the development of a deep learning model for prediction of hip fractures on pelvic radiographs (X-rays). Developed using over 40,000 pelvic radiographs from a single institution, the model demonstrated high sensitivity and specificity when applied to a test set of emergency department radiographs. This study approximates the real-world application of a deep learning fracture detection model by including radiographs with sub-optimal image quality, other non-hip fractures, and metallic implants, which were excluded from prior published work. The study also explores the effect of ethnicity on model performance, as well as the accuracy of visualization algorithm for fracture localization.

关键词： computational bioinformatics Imaging anatomy Musculoskeletal anatomy

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Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results

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ISCIENCE 2023年第12期26卷 108473页

作者： Baron, Cantin Cherkaoui, Sarah Therrien-Laperriere, Sandra Ilboudo, Yann Poujol, Raphael Mehanna, Pamela Garrett, Melanie E. Telen, Marilyn J. Ashley-Koch, Allison E. Bartolucci, Pablo Rioux, John D. Lettre, Guillaume Rosiers, Christine Des Ruiz, Matthieu Hussin, Julie G. Univ Montreal Dept Biochim & Med Mol Montreal PQ Canada Montreal Heart Inst Montreal PQ Canada Univ Childrens Hosp Zurich Univ Zurich Childrens Res Ctr Div Oncol Zurich Switzerland Univ Paris Saclay Gustave Roussy Canc Ctr Dept Pediat & Adolescent Oncol Villejuif France Duke Mol Inst Duke Med Ctr Durham NC USA Duke Univ Med Ctr Dept Med Div Hematol Durham NC USA Univ Paris Est Creteil Hop Univ Henri Mondor Sickle Cell Referral Ctr AP HPUMGGR Creteil France Univ Paris Est Creteil Lab Excellence LABEX IMRB Creteil France Univ Montreal Dept Med Montreal PQ Canada Univ Montreal Dept Nutr Montreal PQ Canada

Metabolite genome-wide association studies (mGWAS) have advanced our understanding of the genetic control of metabolite levels. However, interpreting these associations remains challenging due to a lack of tools to annotate gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we introduce the shortest reactional distance (SRD) metric, drawing from the comprehen-sive KEGG database, to enhance the biological interpretation of mGWAS results. We applied this approach to three independent mGWAS, including a case study on sickle cell disease patients. Our analysis reveals an enrichment of small SRD values in reported mGWAS pairs, with SRD values significantly correlating with mGWAS p values, even beyond the standard conservative thresholds. We demonstrate the utility of SRD annotation in identifying potential false negatives and inaccuracies within current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs, suitable to integrate statistical evidence to biological networks.

关键词： Association analysis computational bioinformatics Quantitative genetics

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Prediction of postpartum prediabetes by machine learning methods in women with gestational diabetes mellitus

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ISCIENCE 2023年第10期26卷 107846页

作者： Parkhi, Durga Periyathambi, Nishanthi Ghebremichael-Weldeselassie, Yonas Patel, Vinod Sukumar, Nithya Siddharthan, Rahul Narlikar, Leelavati Saravanan, Ponnusamy Univ Warwick Div Hlth Sci Populat Evidence & Technol Coventry England George Eliot Hosp Dept Diabet Endocrinol & Metab Nuneaton England Open Univ Sch Math & Stat Milton Keynes England Inst Math Sci Dept Computat Biol Chennai India Indian Inst Sci Educ & Res Dept Data Sci Pune India

Early onset of type 2 diabetes and cardiovascular disease are common complications for women diagnosed with gestational diabetes. Prediabetes refers to a condition in which blood glucose levels are higher than normal, but not yet high enough to be diagnosed as type 2 diabetes. Currently, there is no accurate way of knowing which women with gestational diabetes are likely to develop postpartum prediabetes. This study aims to predict the risk of postpartum prediabetes in women diagnosed with gestational diabetes. Our sparse logistic regression approach selects only two variables - antenatal fasting glucose at OGTT and HbA1c soon after the diagnosis of GDM - as relevant, but gives an area under the receiver operating characteristic curve of 0.72, outperforming all other methods. We envision this to be a practical solution, which coupled with a targeted follow-up of high-risk women, could yield better cardiometabolic outcomes in women with a history of GDM.

关键词： Endocrinology Reproductive medicine Female reproductive endocrinology computational bioinformatics

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A multi-center performance assessment for automated histopathological classification and grading of glioma using whole slide images

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ISCIENCE 2023年第11期26卷 108041页

作者： Jin, Lei Sun, Tianyang Liu, Xi Cao, Zehong Liu, Yan Chen, Hong Ma, Yixin Zhang, Jun Zou, Yaping Liu, Yingchao Shi, Feng Shen, Dinggang Wu, Jinsong Fudan Univ Huashan Hosp Neurol Surg Dept Glioma Surg Div Shanghai 200040 Peoples R China Fudan Univ Huashan Hosp Natl Ctr Neurol Disorders Shanghai 200040 Peoples R China Shanghai United Imaging Intelligence Co Ltd Dept Res & Dev Shanghai 200030 Peoples R China Fudan Univ Huashan Hosp Dept Pathol Shanghai 200040 Peoples R China Wuhan Zhongji Biotechnol Co Ltd Wuhan 430206 Peoples R China Shandong First Med Univ Prov Hosp Dept Neurosurg Jinan 250021 Shandong Peoples R China ShanghaiTech Univ Sch Biomed Engn Shanghai 201210 Peoples R China Shanghai Clin Res & Trial Ctr Shanghai 201210 Peoples R China

Accurate pathological classification and grading of gliomas is crucial in clinical diagnosis and treatment. The application of deep learning techniques holds promise for automated histological pathology diagnosis. In this study, we collected 733 whole slide images from four medical centers, of which 456 were used for model training, 150 for internal validation, and 127 for multi-center testing. The study includes 5 types of common gliomas. A subtask-guided multi-instance learning image-to-label training pipeline was employed. The pipeline leveraged "patch prompting"for the model to converge with reasonable computational cost. Experiments showed that an overall accuracy of 0.79 in the internal validation dataset. The performance on the multi-center testing dataset showed an overall accuracy to 0.73. The findings suggest a minor yet acceptable performance decrease in multi-center data, demonstrating the model's strong generalizability and establishing a robust foundation for future clinical applications.

关键词： Cancer computational bioinformatics Health informatics Pathology

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Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis

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ISCIENCE 2023年第8期26卷 107394页

作者： N'Guessan, Arnaud Kailasam, Senthilkumar Mostefai, Fatima Poujol, Raphael Grenier, Jean-Christophe Ismailova, Nailya Contini, Paola De Palma, Raffaele Haber, Carsten Stadler, Volker Bourque, Guillaume Hussin, Julie G. Shapiro, B. Jesse Fritz, Jorg H. Piccirillo, Ciriaco A. McGill Univ Dept Microbiol & Immunol Montreal PQ Canada McGill Univ McGill Genome Ctr Montreal PQ Canada Canadian Ctr Computat Genom Montreal PQ Canada McGill Univ Dept Human Genet Montreal PQ Canada Montreal Heart Inst Res Ctr Montreal PQ Canada Univ Montreal Dept Biochim & Med Mol Montreal PQ Canada Univ Genoa Dept Internal Med Genoa Italy PEPperPRINT GmbH Heidelberg Germany Univ Montreal Dept Med Montreal PQ Canada McGill Univ McGill Univ Res Ctr Complex Traits MRCCT Montreal PQ Canada McGill Infect Dis & Immun Global Hlth Program Res Inst Hlth Ctr Montreal PQ Canada McGill Univ Dahdaleh Inst Med DIgM Montreal PQ Canada

Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

关键词： Immunology Virology Structural biology computational bioinformatics

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Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study

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ISCIENCE 2023年第11期26卷 108150页

作者： Liu, Zeye Xu, Jing Tan, Jiangshan Li, Xiaofei Zhang, Fengwen Ouyang, Wenbin Wang, Shouzheng Huang, Yuan Li, Shoujun Pan, Xiangbin Natl Ctr Cardiovasc Dis Dept Struct Heart Dis Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Beijing 100037 Peoples R China Natl Hlth Commiss Key Lab Cardiovasc Regenerat Med Beijing 100037 Peoples R China Chinese Acad Med Sci Key Lab Innovat Cardiovasc Devices Beijing 100037 Peoples R China Chinese Acad Med Sci Fuwai Hosp Natl Clin Res Ctr Cardiovasc Dis Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Natl Ctr Cardiovasc Dis Fuwai Hosp State Key Lab Cardiovasc Dis Beijing Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Key Lab Pulm Vasc Med Natl Clin Res Ctr Cardiovasc Dis State Key Lab Cardiovasc DisFuwai HospNatl Ctr C Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Dept Cardiol Beijing Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Pediat Cardiac Surg Ctr State Key Lab Cardiovasc DisNatl Ctr Cardiovasc D Beijing Peoples R China

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

关键词： Cardiovascular medicine Human Genetics Quantitative genetics computational bioinformatics Association analysis

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Modeling breast cancer proliferation, drug synergies, and alternating therapies

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ISCIENCE 2023年第5期26卷 106714页

作者： He, Wei Demas, Diane M. Shajahan-Haq, Ayesha N. Baumann, William T. Virginia Tech Program Genet Bioinformat & Computat Biol VT BIOTRANS Blacksburg VA 24061 USA Georgetown Univ Med Ctr Lombardi Comprehens Canc Ctr Dept Oncol Washington DC 20057 USA Virginia Tech Dept Elect & Comp Engn Blacksburg VA 24061 USA

Estrogen receptor positive (ER+) breast cancer is responsive to a number of tar-geted therapies used clinically. Unfortunately, the continuous application of tar-geted therapy often results in resistance, driving the consideration of combina-tion and alternating therapies. Toward this end, we developed a mathematical model that can simulate various mono, combination, and alternating therapies for ER + breast cancer cells at different doses over long time scales. The model is used to look for optimal drug combinations and predicts a significant synergism between Cdk4/6 inhibitors in combination with the anti-estrogen fulvestrant, which may help explain the clinical success of adding Cdk4/6 inhibitors to anti -es-trogen therapy. Furthermore, the model is used to optimize an alternating treatment protocol so it works as well as monotherapy while using less total drug dose.

关键词： Mathematical biosciences computational bioinformatics Pharmacoinformatics Cancer systems biology Cancer

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Intragenomic diversity of the V9 hypervariable domain in eukaryotes has little effect on metabarcoding

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ISCIENCE 2023年第8期26卷 107291页

作者： Flegontova, Olga Lukes, Julius Horak, Ales Czech Acad Sci Inst Parasitol Biol Ctr Ceske Budejovice Czech Republic Univ Ostrava Fac Sci Dept Biol & Ecol Ostrava Czech Republic Univ South Bohemia Fac Sci Dept Mol Biol Ceske Budejovice Czech Republic

Metabarcoding revolutionized our understanding of diversity and ecology of microorganisms in different habitats. However, it is also associated with several inherent biases, one of which is associated with intragenomic diversity of a molecular barcode. Here, we compare intragenomic variability of the V9 region of the 18S rRNA gene in 19 eukaryotic phyla abundant in marine plankton. The level of intragenomic variability is comparable across all the phyla, and in most genomes and transcriptomes one V9 sequence and one OTU is predominant. However, most of the variability observed at the barcode level is probably caused by sequencing errors and is mitigated by using a denoising tool, DADA2. The SWARM algorithm commonly used in metabarcoding studies is not optimal for collapsing genuine and erroneous sequences into a single OTU, leading to an overestimation of diversity in metabarcoding data. For an unknown reason, SWARM inflates diversity of eupelagonemids more than that of other eukaryotes.

关键词： Genetics Genomics computational bioinformatics

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A Kmer-based paired-end read de novo assembler and genotyper for canine MHC class I genotyping

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ISCIENCE 2023年第2期26卷 105996页

作者： Feng, Yuan Hess, Paul R. Tompkins, Stephen M. Hildebrand, William H. Zhao, Shaying Univ Georgia Inst Bioinformat Dept Biochem & Mol Biol Athens GA 30602 USA North Carolina State Univ Coll Vet Med Dept Clin Sci Raleigh NC 27607 USA Univ Georgia Ctr Vaccines & Immunol UGA Athens GA 30602 USA Univ Oklahoma Hlth Sci Ctr Dept Microbiol & Immunol Oklahoma City OK 73104 USA

The major histocompatibility complex class I (MHC-I) genes are highly polymorphic. MHC-I genotyping is required for determining the peptide epitopes available to an individual's T-cell repertoire. Current genotyping software tools do not work for the dog, due to very limited known canine alleles. To address this, we developed a Kmer-based paired-end read (KPR) de novo assembler and genotyper, which assemble paired-end RNA-seq reads from MHC-I regions into contigs, and then ge-notype each contig and estimate its expression level. KPR tools outperform other popular software examined in typing new alleles. We used KPR tools to success-fully genotype152 dogs from a published dataset. The study discovers 33 putative new alleles, finds dominant alleles in 4 dog breeds, and builds allele diversity and expression landscapes among the 152 dogs. Our software meets a significant need in biomedical research.

关键词： Biocomputational method computational bioinformatics Genomic analysis

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Epitranscriptome analysis of NAD-capped RNA by spike-in-based normalization and prediction of chronological age

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ISCIENCE 2023年第12期26卷 108558页

作者： Li, Dean Ge, Shuwe Liu, Yandong Pan, Miaomia Wang, Xueting Han, Guojing Zou, Sili Liu, Rui Niu, Kongyan Zhao, Chao Liu, Nan Qu, Lefeng Chinese Acad Sci Interdisciplinary Res Ctr Biol & Chem Shanghai Inst Organ Chem 100 Haike Ke Rd Shanghai 201210 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Naval Med Univ Chang Zheng Hosp Dept Vasc & Endovasc Surg Shanghai 200003 Peoples R China Fudan Univ Huashan Hosp Shanghai Med Coll Natl Clin Res Ctr Aging & MedSch Basic Med Sci 131 Dong An Rd Shanghai 200032 Peoples R China Metalife Biotechnol 1000 Zhen Chen Rd Shanghai 200444 Peoples R China Singlera Genom 500 Fu Rong Hua Rd Shanghai 201204 Peoples R China Shanghai Key Lab Aging Studies 100 Hai Ke Rd Shanghai 201210 Peoples R China

Nicotinamide adenine dinucleotide (NAD) can be used as an initiating nucleotide in RNA transcription to produce NAD-capped RNA (NAD-RNA). RNA modification by NAD that links metabolite with expressed transcript is a poorly studied epitranscriptomic modification. Current NAD-RNA profiling methods involve multi-steps of chemo-enzymatic labeling and affinity-based enrichment, thus presenting a critical analytical challenge to remove unwanted variations, particularly batch effects. Here, we propose a computational framework, enONE, to remove unwanted variations. We demonstrate that designed spike-in RNA, together with modular normalization procedures and evaluation metrics, can mitigate technical noise, empowering quantitative and comparative assessment of NAD-RNA across different datasets. Using enONE and a human aging cohort, we reveal age-associated features of NAD-capping and further develop an accurate RNA-based aging clock that combines signatures from both transcriptome and NAD-modified epitranscriptome. enONE facilitates the discovery of NAD-RNA responsive to physiological changes, laying an important foundation for functional investigations into this modification.

关键词： computational bioinformatics Sequence analysis Transcriptomics Methodology in biological sciences

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