☆ 4.6 Review

Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine

FRONTIERS IN GENETICS (2022)

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Review Biochemical Research Methods

Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine

Sreya Vadapalli et al.

Summary: Precision medicine utilizes genetic, environmental, and lifestyle factors to accurately diagnose and treat diseases in specific patient groups. The integration of genetics into precision medicine is a complex and data-rich aspect. The use of artificial intelligence (AI) and machine learning (ML) methods is crucial for successfully incorporating genetics into precision medicine across diverse populations and diseases. This review compares and analyzes the scientific objectives, methodologies, datasets, data sources, ethics, and gaps of AI/ML approaches in genomics and precision medicine, identifying 32 different AI/ML approaches applied in various genomics studies.

BRIEFINGS IN BIOINFORMATICS (2022)

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Review Cell Biology

RNAstructures in alternative splicing and back-splicing

Bingbing Xu et al.

Summary: Alternative splicing greatly expands transcriptomic and proteomic diversities in higher eukaryotes, with the splicing of long noncoding RNAs and back-/trans- splicing further enhancing the regulatory repertoire. RNA structures play a crucial role in regulating alternative splicing and back-splicing processes, and novel sequencing technologies have allowed for the identification of genome-wide RNA structures and interaction networks, providing new insights into RNA splicing regulation. The emerging transcription-folding-splicing paradigm is revolutionizing our understanding of RNA alternative splicing regulation and its impact on human diseases.

WILEY INTERDISCIPLINARY REVIEWS-RNA (2021)

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Article Pharmacology & Pharmacy

Characterization of Pharmacogenetic Information in Food and Drug Administration Drug Labeling and the Table of Pharmacogenetic Associations

Christine M. Cheng et al.

Summary: This study categorized over 300 drug-gene pairs based on FDA-reviewed pharmacogenetic information, with the majority of them being associated with efficacy or safety outcomes.

ANNALS OF PHARMACOTHERAPY (2021)

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Article Pharmacology & Pharmacy

Potential of whole-genome sequencing-based pharmacogenetic profiling

Sylvan Manuel Caspar et al.

Summary: Pharmacogenetics plays a key role in personalized medicine, with whole-genome sequencing offering a more comprehensive approach to pharmacogenetic profiling. Short-read next-generation sequencing has limitations, and there may be a shift towards long-read sequencing for improved gene diagnostics and pharmacogenetic profiling in the future.

PHARMACOGENOMICS (2021)

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Article Multidisciplinary Sciences

A prenylated dsRNA sensor protects against severe COVID-19

Arthur Wickenhagen et al.

Summary: Inherited genetic factors can influence the severity of COVID-19, with intracellular antiviral defenses, particularly OAS1 through ribonuclease L, playing a significant role in inhibiting SARS-CoV-2. The expression of prenylated OAS1 may be associated with protection from severe COVID-19 in hospitalized patients.

SCIENCE (2021)

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Review Chemistry, Analytical

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Selina A. Bernauer et al.

Summary: This systematic review explores the application of AI in prosthodontics, focusing on the training and use of AI systems. Despite the relatively low number of studies included, the findings demonstrate the potential of AI technology in personalized dental treatment for patients.

SENSORS (2021)

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Article Health Care Sciences & Services

Pharmacogenomic Biomarkers in US FDA-Approved Drug Labels (2000-2020)

Jeeyun A. Kim et al.

Summary: Pharmacogenomics (PGx) is a key component of precision medicine that analyzes genetic variations to tailor drug therapies. This study found that the proportion of new drugs approved by the US FDA with PGx information has been increasing, especially in the field of cancer therapies. Results show that PGx information in cancer drugs is more clinically actionable compared to other therapeutic areas, indicating the need for more evidence to support the clinical adoption of pharmacogenomics in non-cancer treatments.

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Review Health Care Sciences & Services

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Marta Weronika Wronikowska et al.

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Review Pharmacology & Pharmacy

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Poongothai Venkatachalapathy et al.

Summary: Type 2 diabetes mellitus is a common and complex disease with a rising incidence, where multiple gene variants play a role in its pathogenesis. Pharmacogenomics enables personalized drug therapy based on genetic information, and different classes of oral hypoglycemic agents show varying pharmacogenetic variants. Precision medicine holds promise for personalized therapy for various forms of diabetes mellitus.

PHARMACOGENOMICS & PERSONALIZED MEDICINE (2021)

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Health Insurance and Out-Of-Pocket Expenditure on Health and Medicine: Heterogeneities along Income

Mohammed Khaled Al-Hanawi et al.

Summary: The study examined the impact of health insurance on healthcare and medicine expenses and found that the effects varied across different income levels. Additionally, the research highlighted that the influence of health insurance was more pronounced among citizens, particularly those with access to free public healthcare.

FRONTIERS IN PHARMACOLOGY (2021)

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Article Biochemistry & Molecular Biology

AI models and the future of genomic research and medicine: True sons of knowledge? Artificial intelligence needs to be integrated with causal conceptions in biomedicine to harness its societal benefits for the field

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Summary: With the increasing use of artificial intelligence in genomic research and medicine, integrating AI methods with traditional causal concepts will have a significant impact on future scientific understanding and self-conceptions, and will be crucial in developing differentiated policies.

BIOESSAYS (2021)

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Review Biotechnology & Applied Microbiology

Using machine learning approaches for multi-omics data analysis: A review

Parminder S. Reel et al.

Summary: With the advancement of high-throughput omics technologies, it is crucial for biomedical research to adopt integrative approaches to analyze diverse omics data using machine learning algorithms. This can lead to the discovery of novel biomarkers and improve disease prediction and precision medicine delivery.-Methods in machine learning have enabled researchers to gain a deeper insight into biological systems and provide recommendations for interdisciplinary professionals looking to incorporate machine learning skills in multi-omics studies.

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Codon usage and protein length-dependent feedback from translation elongation regulates translation initiation and elongation speed

Xueliang Lyu et al.

Summary: Codon usage bias plays a crucial role in determining gene expression levels and ribosome flux, with an impact on both protein abundance and translation initiation efficiency. Optimal codon usage facilitates production of large proteins, while non-optimal codon usage in long CDS mRNAs inhibits translation initiation by inducing phosphorylation of eIF2 alpha. Additionally, a feedback mechanism from translation elongation, influenced by codon usage and CDS length, regulates translation initiation and elongation kinetics.

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DGLinker: flexible knowledge-graph prediction of disease-gene associations

Jiajing Hu et al.

Summary: The rapid progress in understanding genetics underlying biological processes has led to the development of DGLinker, a webserver that uses machine learning models to predict novel genetic factors associated with human diseases. DGLinker allows users to explore biomedical information, generate knowledge graphs, and predict new disease-associated genes, making it a valuable tool for researchers in the field.

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J. M. McDonnell et al.

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BONE & JOINT JOURNAL (2021)

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Article Biochemistry & Molecular Biology

JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping

Zeeshan Ahmed et al.

Summary: Whole genome and exome sequencing are widely used next-generation sequencing methods for detecting rare and common genetic variants of clinical significance. The newly developed JWES pipeline provides a solution for efficient variant discovery, interpretation, big data modeling, and visualization, with cross-platform and user-friendly features. Through testing and validation, JWES has been successfully applied for processing, managing, and discovering gene variants in WGS and WES data.

FEBS OPEN BIO (2021)

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Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction and genotyping

Zeeshan Ahmed et al.

Summary: Genomics has been advancing towards an audacious future, transforming biomedical research and disease study. Whole genome sequencing and exome sequencing are two popular methods to detect clinically significant genetic variations. Despite the availability of various bioinformatics applications, timely interpretation of genetic variants remains a challenge for diagnostic laboratories and clinicians. This study assesses the current solutions for processing NGS data for variant identification, alleles, and haplotypes, focusing on standalone and networked bioinformatics applications.

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Integrative clinical, genomics and metabolomics data analysis for mainstream precision medicine to investigate COVID-19

Zeeshan Ahmed et al.

Summary: Despite ongoing scientific and medical advancements, understanding the genetics of novel infectious diseases like COVID-19 remains a challenge. Analyzing germline and somatic mutations of patients could lead to the discovery of effective medical treatments and biomarkers. Machine learning and big data analysis may assist in predicting early COVID-19 infections, developing new therapies, and improving personalized healthcare.

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Review Biochemistry & Molecular Biology

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Claudia Caudai et al.

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Jianmin Shen et al.

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PHYSICAL REVIEW E (2021)

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Article Oncology

Impact of combinations of single-nucleotide polymorphisms of anthracycline transporter genes upon the efficacy and toxicity of induction chemotherapy in acute myeloid leukemia

Juan Eduardo Megias-Vericat et al.

Summary: This study reveals the impact of transporter polymorphisms on chemotherapy safety in AML patients, indicating associations with various toxicities and induction death rates. Further prospective studies with larger populations are needed to validate these findings.

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Daniel A. Hashimoto et al.

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BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS (2020)

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Mahendra Bhandari et al.

CURRENT OPINION IN UROLOGY (2020)

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Dean Ho et al.

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Being Precise About Precision Medicine: What Should Value Frameworks Incorporate to Address Precision Medicine? A Report of the Personalized Precision Medicine Special Interest Group

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Yoav Mintz et al.

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