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Influence of Artificial Intelligence in Clinical and Genomic Diagnostics
Published in P. Kaliraj, T. Devi, Artificial Intelligence Theory, Models, and Applications, 2021
E. Kiruba Nesamalar, J. Satheeshkumar, T. Amudha
Genomics is a multidisciplinary scientific domain that centers around the study of genome structure, function, mapping, modification, etc. A genome is a collection of DNA in an organism that includes all genes. It divides into several subsets such as regulatory and structural genomic. Regulatory genomics is a study of genomic features and ways of implementing an expression, whereas structural genomics is a study in exploring the characteristics of genome structures. Functional genomics is a study describing gene functions and interactions and a genome analysis involves a set of phases such as sequencing, assembly, gene prediction, gene annotation, and genome alignment. Three main phases provide a better understanding of genetic analysis, such as DNA sequencing and assembly of DNA that represent original chromosomes, and analysis must be done to represent data.
Pharmacogenomics: Ethical, Social, and Public Policy Issues
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2020
Privacy protection is an ethical and legal issue often associated with genomic research. It is a particularly important issue for pharmacogenomics as there will be not only genomic information included in a participants’ research file but also medical information and other types of personal data (e.g., lifestyle, familial health data). On the one hand, some industry researchers have argued that pharmacogenomic information is not particularly sensitive health information [88]. Scholars, on the other hand, counter that pharmacogenomic research, like other types of genetic research, can produce incidental findings (some of those related to susceptibility to disease, paternity, etc.) and that databases used in pharmacogenomics are vulnerable to third-party misuse (i.e., potential misuse by governmental law enforcement agencies, insurers, employers, and drug companies) [27, 72]. In pharmacogenomics, the privacy concerns are complex because private pharmaceutical companies often control sample collections. This raises concerns regarding the long-term governance of the samples. For example, what will happen to the samples if a private company becomes bankrupt or is sold [33, 100]? Another scenario to consider is the case where law enforcement officials, in the context of a criminal investigation, request access to the database.
Pharmacogenomics: Ethical, Social, and Public Policy Issues
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2019
Privacy protection is an ethical and legal issue often associated with genomic research. It is a particularly important issue for pharmacogenomics as there will be not only genomic information included in a participants’ research file but also medical information and other types of personal data (e.g., lifestyle, familial health data). On the one hand, some industry researchers have argued that pharmacogenomic information is not particularly sensitive health information [88]. Scholars, on the other hand, counter that pharmacogenomic research, like other types of genetic research, can produce incidental findings (some of those related to susceptibility to disease, paternity, etc.) and that databases used in pharmacogenomics are vulnerable to third-party misuse (i.e., potential misuse by governmental law enforcement agencies, insurers, employers, and drug companies) [27, 72]. In pharmacogenomics, the privacy concerns are complex because private pharmaceutical companies often control sample collections. This raises concerns regarding the long-term governance of the samples. For example, what will happen to the samples if a private company becomes bankrupt or is sold [33, 100]? Another scenario to consider is the case where law enforcement officials, in the context of a criminal investigation, request access to the database.
The Environmental Exposures in Lebanese Infants (EELI) birth cohort: an investigation into the Developmental Origins of Health and Diseases (DOHaD)
Published in International Journal of Environmental Health Research, 2023
Emile Whaibeh, Myriam Mrad-Nakhlé, Norma Aouad, Isabella Annesi-Maesano, Nivine Abbas, Clara Chaiban, Jowy Abi Hanna, Georges Abi Tayeh
The human genome has brought significant advancements in understanding of the genetic causes of various diseases (Schmutz et al. 2004). However, the role of environmental exposures in interacting with biological systems is equally crucial role, which gave rise the complementary concept of “exposome”, proposed by molecular epidemiologist Christopher P. Wild (2005). It is defined as the totality of exposures that one encounters through their life course, including the food they ingest, the air they breathe, the objects they touch, the psychological stress they endure, and the behaviors they engage in (Miller 2013). The Developmental Origins of Health and Disease (DOHaD) hypothesis suggests that the first 1000 days of life after conception, including the pregnancy and the first 2 years after birth, determine the susceptibility of individuals to non-communicable diseases (Gluckman et al. 2016). During the early stages of development, infants are at risk as environmental exposures pose can alter developmental pathways due to rapid organ growth, immature metabolism, and low body weight relative to dose of exposure (Robinson and Vrijheid 2015; Subbarao et al. 2015). As a result, many diseases that develop in adulthood may have originated in utero origin due to suboptimal intrauterine conditions, which induce adaptive fetal responses that predispose individuals to neonatal and/or chronic diseases (Gluckman et al. 2010; Fleming et al. 2018).
Epigenotoxicity: a danger to the future life
Published in Journal of Environmental Science and Health, Part A, 2023
Farzaneh Kefayati, Atoosa Karimi Babaahmadi, Taraneh Mousavi, Mahshid Hodjat, Mohammad Abdollahi
Since completing the Human Genome Project about twenty years ago, there has been a great deal of help from geneticists and physicians regarding having access to the human genome map and better diagnosing diseases. Today, epigenetics has enabled us to understand the complexities of the human biological system and the body’s processes of growth and regulation. Epigenetics indicates that the sequence of nucleotides and their bonds with different functional groups is crucial in DNA function [88] Mistakes in epigenetic mechanisms alter the expression of genes causing a range of disorders. Amongst, developmental and mental disorders, immunodeficiency, Chronic obstructive pulmonary disease (COPD), asthma, and organ defects, are the most common; each will be discussed separately below as well as in Table 2.[88,89]
A pilot study of exome sequencing in a diverse New Zealand cohort with undiagnosed disorders and cancer
Published in Journal of the Royal Society of New Zealand, 2018
Colina McKeown, Samantha Connors, Rachel Stapleton, Tim Morgan, Ian Hayes, Katherine Neas, Joanne Dixon, Kate Gibson, David M. Markie, Peter Tsai, Cherie Blenkiron, Sandra Fitzgerald, Paula Shields, Patrick Yap, Ben Lawrence, Cristin Print, Stephen P. Robertson
The search space within which to find a specific genetic explanation for monogenic disorders is becoming well-refined. There are approximately 19,000 protein-coding genes in the human genome, covering approximately 50 Mb of DNA sequence, and it is in this portion of the genome—the exome—that an estimated 85% of Mendelian molecular diagnoses will be found (Blackburn et al. 2015; Chong et al. 2015; Valencia et al. 2015). Whole exome sequencing (WES) is increasingly being used worldwide with studies of its utility demonstrating diagnostic rates of 16%–57% (de Ligt et al. 2012; Soden et al. 2014; Yang et al. 2014; Chong et al. 2015; Valencia et al. 2015; Wright et al. 2015; Monroe et al. 2016; Stark et al. 2016). Currently, mutations in 3849 genes have been proven to be responsible for 6121 Mendelian phenotypes (OMIM Gene Map Statistics 2017).