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Race and racism in public health
Published in Sridhar Venkatapuram, Alex Broadbent, The Routledge Handbook of Philosophy of Public Health, 2023
Borrell et al. (2021), in line with Burchard et al. (2003), argue for the use of race in biomedical research that supports public health aims. In their approach, Borrell et al. take it that “it may seem reasonable to assume that all racial/ethnic differences in disease incidence and outcomes derive from socioeconomic differences. However, race is also directly associated with genetic ancestry and therefore indirectly related to genetic variants that may affect disease and health outcomes” (2021: 475).
The Genetic Risk of a Couple Aiming to Conceive
Published in Carlos Simón, Carmen Rubio, Handbook of Genetic Diagnostic Technologies in Reproductive Medicine, 2022
Joe Leigh Simpson, Svetlana Rechitsky, Anver Kuliev
For over 50 years, ethnicity-based screening has identified asymptomatic individuals who are heterozygous for selected disorders. Tay-Sachs disease and hemoglobinopathies were the initial targets of screening, meeting the requisite requirement for a protein-based gene product in which it was possible to distinguish between heterozygous and homozygous asymptomatic individuals. In recent years, it has become clear that the clinical usefulness of ethnicity-based screening was less than predicted, in part because not all individuals of a given ethnic group are aware of their own ancestry. Pan-ethnic screening of carriers, based on DNA sequencing, is now pursued, increasing the number of at-risk couples identified. The genetic basis for at least 5,000 rare Mendelian traits has been determined, so the potential benefit is enormous (1). Moreover, at least 100,000 robust associations have been identified between genomic regions and common genetic diseases (1). Although not yet practicable, aspirational goals include DNA sequencing of every embryo or every fetus in every pregnancy. Chromosomal abnormalities associated with advanced maternal age can be detected non-invasively during pregnancy. Advanced paternal age is not associated with chromosomal abnormalities but is correlated with increased frequency of de novo mutations causing single-gene disorders.
The traffic of cells and ideas
Published in Joanna Ziarkowska, Indigenous Bodies, Cells, and Genes, 2020
As a poetic counterpart and predecessor of Native American DNA by Kim TallBear, Cell Traffic addresses the complex problem of attributing to DNA testing the power to determine and authenticate tribal belonging. Chapter five presents Kim TallBear’s analysis of the coproduction of genetic ancestry tests, from which she concludes that they provide easy biological answers to complex social, legal, and cultural questions. Despite the presence of such claims in many genetic companies’ marketing materials, there is no marker for a tribe that would unequivocally prove an individual’s biological connection to the tribe and, thus, facilitate the enrollment process. Ancestry markers, most commonly used in such tests, are not restricted to single populations. Rather, they are found at higher frequencies in some populations and at lower frequencies in others. Moreover, genetic tests entirely ignore the fact that the tribe is not a genetic population but a dynamic social, legal, and cultural organism which does not rely solely on biological connections.
Disparities in Inherited Retinal Degenerations
Published in Seminars in Ophthalmology, 2023
Sarah Chorfi, Emily M. Place, Rachel M. Huckfeldt
Finally, in addition to the challenges related to equitable representation of populations in our genomic dataset, labelling of the different ethnic backgrounds is also a challenge. The curation of GWAS publications showed “inconsistent” and “ambiguous” reporting of ethnic origin.38 In the absence of established guidelines for representation of ancestry data, Morales et al. described a framework for standardized description of sample ethnic background.38 The development of increasingly sophisticated bioinformatics programs that can infer genetic ancestry based on DNA rather than self-reported genealogic ancestry labels will help with labeling in the future. Populations that have traditionally been grouped together such as African Americans and Africans may be separated if bioinformatics programs are used to infer ancestry.
Radium dial workers: back to the future
Published in International Journal of Radiation Biology, 2022
Nicole E. Martinez, Derek W. Jokisch, Lawrence T. Dauer, Keith F. Eckerman, Ronald E. Goans, John D. Brockman, Sergey Y. Tolmachev, Maia Avtandilashvili, Michael T. Mumma, John D. Boice, Richard W. Leggett
Vital status, date and cause of death as of 31 December 2019 (aka vital status tracing) are being sought from linkages with the National Death Index (NDI); state mortality files; the Social Security Administration (SSA) Death Master File; the SSA Service to Epidemiological Researchers (which confirms alive status); and credit reporting agencies using the methods outlined in Mumma et al. (2018). The Centers for Disease Control and Prevention LinkPlus program, which incorporates a probabilistic scoring system that does not require exact matches on all variables, was used for in-house matches (Campbell 2008). Online ancestry providers (Ancestry.com) and credit record providers (Transunion) are important sources to help complete and correct key demographic and linking data, such as Social Security Number, last names (which often changed since employment), and dates of birth and death. Vital status (VS) tracing (Figure 3) continues, and preliminary results are presented in Table 1. End-of-follow-up (EOFU) in Table 1 refers to the date a person is no longer considered at-risk for analytic purposes. It is their date of death, 95th birthday or December 31 of the calendar year. We anticipate that most of the study participants still being traced will be deceased as of December 2019.
Unraveling racial disparities in asthma emergency department visits using electronic healthcare records and machine learning
Published in Journal of Asthma, 2022
Adeboye A. Adejare, Yadu Gautam, Juliana Madzia, Tesfaye B. Mersha
It is important to note that our analyses, and hence interpretations, are subject to several limitations. Firstly, the patients’ race in EHRs is self-reported, which ignore the possibility that individuals have mixed racial ancestry and group individual in a single racial category (43). Access and collection of biological data such as genetic information can produce a better classification of a patient’s racial ancestry and overcome this limitation (44–46). Secondly, users request for a daily number of ED visits with a primary diagnosis of asthma and ICD-9/ICD-10 codes. However, defining asthma on the basis of primary diagnosis and ICD-9/ICD-10 codes could potentially lead to misclassification, although previous studies showed that such misclassification could not affect the overall interpretation of big data like ours (42,357 records) (47). Third, our analysis assume an accurate FEV1% measurement in the EHR which is dependent on an accurate manual measurement of EHR staff. Inadvertently measurement error by EHR staff due to the ED structure could affect the results. Although we do not have skin test sensitivity between AA and EA specific to this study, multiple studies showed that Black individuals are more likely to have at least one positive skin prick test compared with white individuals (48). Finally, this study relied solely on structured data captured in the EHR. Study findings are therefore subject to the accuracy and completeness of electronic documentation by the EHR team.