Constructing identities: the implications of DTC ancestry testing for tribal communities.
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ABSTRACT:
SUBMITTER: Walajahi H
PROVIDER: S-EPMC6642857 | biostudies-literature | 2019 Aug
REPOSITORIES: biostudies-literature
Publications
Constructing identities: the implications of DTC ancestry testing for tribal communities.
Walajahi Hina H Wilson David R DR Hull Sara Chandros SC
Genetics in medicine : official journal of the American College of Medical Genetics 20190121 8
<h4>Purpose</h4>Direct-to-consumer (DTC) genetic ancestry companies have rapidly increased in popularity, with top testing services maintaining genetic databases of several million consumers. While genetic ancestry tests are often characterized as recreational, companies invoke deeply personal concepts of individual identity, group membership, and kinship when marketing their services. In particular, many companies claim to be able to determine Native American heritage, claims that are not suppo ...[more]
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Project description:PurposeDiscussions about direct-to-consumer (DTC) DNA ancestry tests have to date been based primarily on conjectures, speculation, and anecdotes, despite the industry being more than a decade old. Representative, empirical data on consumer characteristics; motivations and expectations for testing; intended uses for the information; understanding of results; and behavioral and psychological reactions to the tests are absent. Although the 2010 American Society of Human Genetics white paper clarifies the number and some general characteristics of companies marketing and selling DNA ancestry tests, additional data about the industry's practices have been unavailable.MethodsTo promote a data-driven discussion of the DNA ancestry testing industry, we conducted a systematic investigation to identify companies selling DNA ancestry tests and conducted an empirical study of the industry's practices using data collected from each company's website.ResultsHere, we present a wealth of data, including an updated directory of companies, marketing slogans, product types and names, range of prices, diversity of reporting and representing results, noted benefits and limitations of testing, and a host of website practices.ConclusionThe tremendous diversity of tests, information, and practices of companies in the DNA ancestry sector should be considered when policies for best practice guidelines or regulatory oversight are being developed.
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Project description:When conducting research with American Indian tribes, informed consent beyond conventional institutional review board (IRB) review is needed because of the potential for adverse consequences at a community or governmental level that are unrecognized by academic researchers.In this article, we review sovereignty, research ethics, and data-sharing considerations when doing community-based participatory health-related or natural-resource-related research with American Indian nations and present a model material and data-sharing agreement that meets tribal and university requirements.Only tribal nations themselves can identify potential adverse outcomes, and they can do this only if they understand the assumptions and methods of the proposed research. Tribes must be truly equal partners in study design, data collection, interpretation, and publication. Advances in protection of intellectual property rights (IPR) are also applicable to IRB reviews, as are principles of sovereignty and indigenous rights, all of which affect data ownership and control.Academic researchers engaged in tribal projects should become familiar with all three areas: sovereignty, ethics and informed consent, and IPR. We recommend developing an agreement with tribal partners that reflects both health-related IRB and natural-resource-related IPR considerations.
| S-EPMC3261947 | biostudies-literature
Project description:PURPOSE:The majority of poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) are thought to dedifferentiated from differentiated thyroid cancer (DTC). PDTC is regarded as an intermediate form, through which DTC dedifferentiates into ATC. Although accumulation of gene mutations has been observed in PDTC and ATC, evidence of a direct link between DTC, PDTC, and ATC is still lacking. This work aims to illustrate if PDTC is the intermediate state between DTC and ATC. PATIENTS AND METHODS:Whole-exome sequencing was performed in a single patient presenting with primary papillary thyroid cancer (PTC) with simultaneous PTC, PDTC, and ATC in metastatic lymph nodes. RESULTS:167 nonsynonymous mutations were identified, and 24 of them were exclusive to metastatic loci. Comparison of mutational spectra revealed following results: 1) PDTC and ATC were associated with PTC-LN2 but not PTC-LN1; 2) the majority (5/6) of non-ubiquitous mutations in ATC were also present in PDTC; and 3) despite one mutation observed simultaneously in PTC-LN2, PDTC and ATC, no other associations were found between the ATC and PTC samples (primary or metastatic). Additionally, we identified five mutations (four mutations present in both PDTC and ATC, and one exclusive to ATC), including TP53 p.N107_S108delinsX, possibly related with DTC dedifferentiation. CONCLUSIONS:We observed an apparent potential, stepwise dedifferentiation process linking DTC, PDTC, and ATC, with PDTC serving as an intermediate state between DTC and ATC in one certain patient. One key mutation, combined with several low-frequency mutations, appears to underlie this dedifferentiation pathway.
| S-EPMC6944019 | biostudies-literature
Project description:Consumer uptake of direct-to-consumer (DTC) DNA ancestry testing is accelerating, yet few empirical studies have examined test impacts on recipients despite the DTC ancestry industry being two decades old. Participants in a longitudinal cohort study of response to health-related DTC genomic testing also received personal DNA ancestry testing at no additional cost. Baseline survey data from the primary study were analyzed together with responses to an additional follow-up survey focused on the response to ancestry results. Ancestry results were generated for 3466 individuals. Of those, 1317 accessed their results, and 322 individuals completed an ancestry response survey, in other words, approximately one in ten who received ancestry testing responded to the survey. Self-reported race/ethnicity was predictive of those most likely to view their results. While 46% of survey responders (N = 147) reported their ancestry results as surprising or unexpected, less than 1% (N = 3) were distressed by them. Importantly, however, 21% (N = 67) reported that their results reshaped their personal identity. Most (81%; N = 260) planned to share results with family, and 12% (N = 39) intended to share results with a healthcare provider. Many (61%; N = 196) reported test benefits (e.g., health insights), while 12% (N = 38) reported negative aspects (e.g., lack of utility). Over half (N = 162) reported being more likely to have other genetic tests in the future. DNA ancestry testing affected individuals with respect to personal identity, intentions to share genetic information with family and healthcare providers, and the likelihood to engage with other genetic tests in the future. These findings have implications for medical care and research, specifically, provider readiness to engage with genetic ancestry information.
| S-EPMC7846620 | biostudies-literature
Project description:Microarrays are useful tools for detecting and quantifying specific functional and phylogenetic genes in natural microbial communities. In order to track uncultivated microbial genotypes and their close relatives in an environmental context, we designed and implemented a “genome proxy” microarray that targets microbial genome fragments recovered directly from the environment. Fragments consisted of sequenced clones from large-insert genomic libraries from microbial communities in Monterey Bay, the Hawaii Ocean Time-series station ALOHA, and Antarctic coastal waters. In a prototype array, we designed probe sets to thirteen of the sequenced genome fragments and to genomic regions of the cultivated cyanobacterium Prochlorococcus MED4. Each probe set consisted of multiple 70-mers, each targeting an individual ORF, and distributed along each ~40-160kbp contiguous genomic region. The targeted organisms or clones, and close relatives, were hybridized to the array both as pure DNA mixtures and as additions of cells to a background of coastal seawater. This prototype array correctly identified the presence or absence of the target organisms and their relatives in laboratory mixes, with negligible cross-hybridization to organisms having ≤~75% genomic identity. In addition, the array correctly identified target cells added to a background of environmental DNA, with a limit of detection of ~0.1% of the community, corresponding to ~10^3 cells/ml in these samples. Signal correlated to cell concentration with an R2 of 1.0 across six orders of magnitude. In addition the array could track a related strain (at 86% genomic identity to that targeted) with a linearity of R2=0.9999 and a limit of detection of ~1% of the community. Closely related genotypes were distinguishable by differing hybridization patterns across each probe set. This array’s multiple-probe, “genome-proxy” approach and consequent ability to track both target genotypes and their close relatives is important for the array’s environmental application given the recent discoveries of considerable intra-population diversity within marine microbial communities. Keywords: target addition experiment, proof-of-concept for GPL6012
2007-10-31 | GSE9384 | GEO
Project description:Microarrays are useful tools for detecting and quantifying specific functional and phylogenetic genes in natural microbial communities. In order to track uncultivated microbial genotypes and their close relatives in an environmental context, we designed and implemented a âgenome proxyâ microarray that targets microbial genome fragments recovered directly from the environment. Fragments consisted of sequenced clones from large-insert genomic libraries from microbial communities in Monterey Bay, the Hawaii Ocean Time-series station ALOHA, and Antarctic coastal waters. In a prototype array, we designed probe sets to thirteen of the sequenced genome fragments and to genomic regions of the cultivated cyanobacterium Prochlorococcus MED4. Each probe set consisted of multiple 70-mers, each targeting an individual ORF, and distributed along each ~40-160kbp contiguous genomic region. The targeted organisms or clones, and close relatives, were hybridized to the array both as pure DNA mixtures and as additions of cells to a background of coastal seawater. This prototype array correctly identified the presence or absence of the target organisms and their relatives in laboratory mixes, with negligible cross-hybridization to organisms having â¤~75% genomic identity. In addition, the array correctly identified target cells added to a background of environmental DNA, with a limit of detection of ~0.1% of the community, corresponding to ~10^3 cells/ml in these samples. Signal correlated to cell concentration with an R2 of 1.0 across six orders of magnitude. In addition the array could track a related strain (at 86% genomic identity to that targeted) with a linearity of R2=0.9999 and a limit of detection of ~1% of the community. Closely related genotypes were distinguishable by differing hybridization patterns across each probe set. This arrayâs multiple-probe, âgenome-proxyâ approach and consequent ability to track both target genotypes and their close relatives is important for the arrayâs environmental application given the recent discoveries of considerable intra-population diversity within marine microbial communities. Keywords: target addition experiment, proof-of-concept for GPL6012 ***Overall Array design*** The prototype microarray targeted thirteen BAC or fosmid genome fragments (20-160kb) from both bacteria and archaea, recovered from a variety of marine habitats, as well as the cyanobacterium Prochlorococcus MED4. These clones were originally sequenced because of the presence of taxonomic marker or specific functional genes. This array consisted of sets of 70-bp oligonucleotides targeting each genome or genome fragment (Fig. 1), dispersed along the target sequences with no more than one probe per gene, and excluding rRNA genes as targets. The probes were selected solely based on theoretical thermodynamic properties and GC content (~40%); that is, probe selection did not focus on specific genes or regions, but simply produced the âoptimalâ probes for each genome proxy based on the probesâ predicted hybridization properties. rRNA genes were excluded, because this probe design approach, which avoids sequence alignments and considerations of RNA secondary structure, would be unlikely to result in useful rRNA probes. Furthermore, rRNA probes of traditional design could not be included on the array because their appropriate hybridization conditions would be very different from those of this arrayâs probes. ***Microarray probe design*** Microarray 70-mer probes were designed using the program ArrayOligoSelector (Zhu et al., 2003) with the following settings: target %GC = 40%, 1 probe/gene, with the ORFs for each genome fragment as both the input and the database file. The output candidate 70mers were then sorted based on their %GC and those closest to 40% were chosen. In the case of more than the target number of probes having 40%GC, the subset with the lowest free energy of hybridization were selected as probes. Generally, 20 probes were selected per organism. Prochlorococcus MED4 was represented by 60 probes total, 20 each for three different 80kb âgenome-proxyâ regions: 0-80kb, 1.29-1.37Mbp, and 1.58 to 1.66Mbp. Using the same method, a set (n=20) of positive control probes were designed to the genome of the halophillic archaeon Halobacterium salinarum NRC-1. Negative control probes (n=28) were designed to a set of 49 random 1000-base sequences (Stothard, 2000). ***Microarray construction and hybridization*** Oligonucleotides were synthesized (Illumina, San Diego, California), suspended in 3XSSC to a concentration of 40pmol/μl, and spotted on homemade poly-L-lysine-coated glass slides using a QArray 2 microarraying robot (Genetix, Hampshire, England). Six replicates of each probe were spotted. ***Microarray data analysis*** Hybridized arrays were scanned using an Axon Instruments 4000B scanner (Foster City, CA) and the data was normalized and filtered using perl scripts written for the purpose, by the following steps. (1) Signal intensities for each spot were calculated by subtracting the local background (mean F532 â median B532, as calculated by GenePix Pro 5.1 software, Axon Instruments). (2) The median value across replicates was calculated for each probe. (3) For each probe set, the number of probes greater than twice the mean negative control signal was calculated, before further processing. (4) Filter I: Arrays with less than half their positive control probes exceeding twice the mean negative control signal were considered poor quality, low dynamic range, arrays and were excluded from further analysis. (5) Each probe signal was corrected for non-specific binding by subtracting the mean negative control spot signal. (6) The data was then normalized for array-to-array variations in brightness by dividing each probe signal by the mean positive control signal. This positive control signal was the mean signal across the Halobacterium salinarum probes in each hybridization, with identical amounts of H. salinarum DNA having been added to each reaction prior to amplification and labeling. (7) Filter II: In order for a genotype to be considered âpresentâ, at least 45% of its probes had to exceed twice the mean negative control signal. (8) Finally, each genotype signal was calculated as either the MEAN or TUKEY BIWEIGHT across its probe set. ***Experimental Design*** The array was hybridized to laboratory mixtures of cloned environmental genomic DNA targeted by the array, in varying ratios. The use of multiple probes to target many genes from each organism helped to normalize probe-to-probe heterogeneity, by averaging across all probes in a set (as described below). The evenness of probe response across each genotypeâs set was also used to evaluate the relatedness of hybridizing DNA. To more precisely define the arrayâs phylogenetic range and specificity, it was tested against DNA from Prochlorococcus MED4 and related strains, spanning the known range of Prochlorococcus phylogenetic diversity. To test the effects of hybridization stringency on the specificity and signal of the MED4 probes, Prochlorococcus strains were hybridized at a range of conditions. To test whether the specificity results for Prochlorococcus were comparable for other targeted clades, two genome fragments recovered from closely related phylotypes within the SAR86 clade of the gamma-proteobacteria were represented on the array, and were tested for specificity. To understand the equivalence of probe sets targeting different regions of the same organismâs genome, we targeted three 80kb âgenome proxyâ regions of the Prochlorococcus MED4 genome. One of the regions fell in a genomic âislandâ where inter-strain variability is concentrated (âISL5â in Coleman et al., 2006). To test the array in a complex environmental context, we collected coastal seawater (lacking detectable Prochlorococcus cells by flow cytometry) and added Prochlorococcus cells from strains MED4, MIT9515, MIT9312 and MIT9313 over a range of concentrations from ~101 â 106 cells/ml (Fig. 3). The seawater was then filtered and the DNA extracted, amplified, labeled, and hybridized to the array.
2010-05-25 | E-GEOD-9384 | biostudies-arrayexpress
Project description:Pharmaceuticals, personal care products, hormones, and other chemicals lacking water quality standards are frequently found in surface water. While evidence is growing that these contaminants of emerging concern (CECs) - those previously unknown, unrecognized, or unregulated - can affect the behavior and reproduction of fish and wildlife, little is known about the distribution of these chemicals in rural, tribal areas. Therefore, we surveyed the presence of CECs in water, sediment, and subsistence fish species across various waterbodies, categorized as undeveloped (i.e., no human development along shorelines), developed (i.e., human development along shorelines), and wastewater effluent-impacted (i.e., contain effluence from wastewater treatment plants), within the Grand Portage Indian Reservation and 1854 Ceded Territory in northeastern Minnesota, U.S.A. Overall, in 28 sites across three years (2016-2018), 117 of the 158 compounds tested were detected in at least one form of medium (i.e., water, sediment, or fish). CECs were detected most frequently at wastewater effluent-impacted sites, with up to 83 chemicals detected in one such lake, while as many as 17 were detected in an undeveloped lake. Although there was no statistically significant difference between the number of CECs present in developed versus undeveloped lakes, a range of 3-17 CECs were detected across these locations. Twenty-two CECs were detected in developed and undeveloped sites that were not detected in wastewater effluent-impacted sites. The detection of CECs in remote, undeveloped locations, where subsistence fish are harvested, raises scientific questions about the safety and security of subsistence foods for indigenous communities. Further investigation is warranted so that science-based solutions to reduce chemical risks to aquatic life and people can be developed locally and be informative for indigenous communities elsewhere.
| S-EPMC8208820 | biostudies-literature
Project description:Increasing public interest in direct-to-consumer (DTC) genetic ancestry testing has been accompanied by growing concern about issues ranging from the personal and societal implications of the testing to the scientific validity of ancestry inference. The very concept of "ancestry" is subject to misunderstanding in both the general and scientific communities. What do we mean by ancestry? How exactly is ancestry measured? How far back can such ancestry be defined and by which genetic tools? How do we validate inferences about ancestry in genetic research? What are the data that demonstrate our ability to do this correctly? What can we say and what can we not say from our research findings and the test results that we generate? This white paper from the American Society of Human Genetics (ASHG) Ancestry and Ancestry Testing Task Force builds upon the 2008 ASHG Ancestry Testing Summary Statement in providing a more in-depth analysis of key scientific and non-scientific aspects of genetic ancestry inference in academia and industry. It culminates with recommendations for advancing the current debate and facilitating the development of scientifically based, ethically sound, and socially attentive guidelines concerning the use of these continually evolving technologies.
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Project description:For samples of admixed individuals, it is possible to test for both ancestry effects via admixture mapping and genotype effects via association mapping. Here, we describe a joint test called BMIX that combines admixture and association statistics at single markers. We first perform high-density admixture mapping using local ancestry. We then perform association mapping using stratified regression, wherein for each marker genotypes are stratified by local ancestry. In both stages, we use generalized linear models, providing the advantage that the joint test can be used with any phenotype distribution with an appropriate link function. To define the alternative densities for admixture mapping and association mapping, we describe a method based on autocorrelation to empirically estimate the testing burdens of admixture mapping and association mapping. We then describe a joint test that uses the posterior probabilities from admixture mapping as prior probabilities for association mapping, capitalizing on the reduced testing burden of admixture mapping relative to association mapping. By simulation, we show that BMIX is potentially orders-of-magnitude more powerful than the MIX score, which is currently the most powerful frequentist joint test. We illustrate the gain in power through analysis of fasting plasma glucose among 922 unrelated, non-diabetic, admixed African Americans from the Howard University Family Study. We detected loci at 1q24 and 6q26 as genome-wide significant via admixture mapping; both loci have been independently reported from linkage analysis. Using the association data, we resolved the 1q24 signal into two regions. One region, upstream of the gene FAM78B, contains three binding sites for the transcription factor PPARG and two binding sites for HNF1A, both previously implicated in the pathology of type 2 diabetes. The fact that both loci showed ancestry effects may provide novel insight into the genetic architecture of fasting plasma glucose in individuals of African ancestry.
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