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Despite major advancements in genomic medicine, research to optimize the design and communication of genetically informed interventions in behavioral health has lagged. The goal of this study was to engage potential end users in participatory codesign of a personalized genetically informed risk tool to intervene on high-risk health behaviors. We used structured interviews to examine end-user attitudes and interest in personalized genetics, qualitative interviews to guide iterative design of a genetically informed tool, and questionnaires to assess acceptability and potential utility of the tool. Participants expressed strong demand for using personal genetics to inform smoking and alcohol-related disease risk and guide treatment (78%-95% agreed). Via iterative design feedback, we cocreated a genetically informed risk profile featuring (i) explanation of genetic and phenotypic markers used to construct a risk algorithm, (ii) personalized risks and benefits of healthy behavior change, and (iii) recommended actions with referral to freely available resources. Participants demonstrated sufficient understanding and cited motivating behavior change as the most useful purpose of the tool. In three phases, we confirmed strong desire for personalized genetics on high-risk health behaviors; codesigned a genetically informed profile with potential end users; and found high acceptability, comprehensibility, and perceived usefulness of the profile. As scientific discovery of genomic medicine advances in behavioral health, we must develop the tools to communicate these discoveries to consumers who stand to benefit. The potential of genomic medicine to engage populations and personalize behavioral health treatment depends, in part, on preparatory studies to design for the future implementation of genetically informed interventions.
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http://dx.doi.org/10.1158/1940-6207.CAPR-20-0029 | DOI Listing |
Bioinformatics
December 2024
Max-Planck-Institute for Biology Tübingen, Department of Molecular Biology, Tübingen, Germany.
Motivation: As genome graphs are powerful data structures for representing the genetic diversity within populations, they can help identify genomic variations that traditional linear references miss, but their complexity and size makes the analysis of genome graphs challenging. We sought to develop a genome graph analysis tool that helps these analyses to become more accessible by addressing the limitations of existing tools. Specifically, we improve scalability and user-friendliness, and we provide many new statistics tailored to variation graphs for graph evaluation, including sample-specific features.
View Article and Find Full Text PDFG3 (Bethesda)
December 2024
Department of Plant Sciences, University of California Davis, Davis, CA 95616, USA.
Mate selection plays an important role in breeding programs. The Usefulness Criterion was proposed to improve mate selection, combining information on both the mean and standard deviation of the potential offspring of a cross, particularly in clonally propagated species where large family sizes are possible. Predicting the mean value of a cross is generally easier than predicting the standard deviation, especially in outbred species when the linkage of alleles is unknown and phasing is required.
View Article and Find Full Text PDFBioinformatics
December 2024
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States.
Motivation: The Variant Call Format (VCF) is widely used in genome sequencing but scales poorly. For instance, we estimate a 150,000 genome VCF would occupy 900 TiB, making it costly and complicated to produce, analyze, and store. The issue stems from VCF's requirement to densely represent both reference-genotypes and allele-indexed arrays.
View Article and Find Full Text PDFAmino Acids
December 2024
Department of Nephrology and Rheumatology, Kanazawa University, 13-1 Takara-Machi, Kanazawa, 920-8641, Japan.
The relationship between D-AA metabolic enzymes and cancer development remains unclear. We aimed to investigate this relationship using mice deficient in D-AA-related metabolic enzymes. We examined mice lacking these enzymes for approximately 900 days and the effects of altered D-AA metabolism on cancer development based on lifespan, pathological findings, and gene expression.
View Article and Find Full Text PDFMol Biol Rep
December 2024
Foodborne and Waterborne Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Blastocystis is a prevalent intestinal parasitic protist that infects both birds and animals. There are at least 44 subtypes (ST) of Blastocystis, with ST1-ST9 being found in humans. The correlation between specific subtypes and pathogenicity has not been definitively established.
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