Reassessing Established Assumptions of Dietary Habits in the USA in the Context of Migration and Acculturation: a Qualitative Study of Latino Immigrants.

INTRODUCTION: The growing prevalence of obesity in the USA disproportionately affects Latinos compared to non-Latino Whites. Immigration and acculturation have been associated with unhealthy dietary shifts among Latino immigrants, a phenomenon known as dietary acculturation. Emerging evidence points to a more nuanced relationship between dietary habits, immigration, and acculturation, highlighting the need for a more current comprehension of dietary acculturation. OBJECTIVE: We explored how Latino immigrants' experiences in migrating to the USA have affected their perceived dietary habits and their experiences of how supportive the USA is in establishing healthy practices compared to their native country. METHODS: Employing a descriptive qualitative study design, we conducted semi-structured interviews with 19 Latinos who had participated in a lifestyle change program between 2016 and 2019. We used thematic analysis to analyze the data and report emerging themes. RESULTS: Participants expressed divergent perceptions of their dietary habits post-immigration. Some affirmed prevailing assumptions of dietary acculturation, citing deteriorating diet quality in the USA in the context of a faster pace of life, healthier options in the native country, and shifts in the food environment that prevented access to healthy foods. Conversely, others held opposing views, attributing their perceived improved diet to unhealthy dietary habits in Latin America, coupled with increased access to and affordability of healthy foods in the USA. CONCLUSION: Our study contributes to the evolving understanding of dietary acculturation among Latino immigrants and provides a more nuanced and updated understanding of this process that reflects their current experiences in acculturating to the USA.

Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations.

SUMMARY: Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION: Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations.

Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations.

Variant-specific Mendelian Risk Prediction Model.

Many pathogenic sequence variants (PSVs) have been associated with increased risk of cancers. Mendelian risk prediction models use Mendelian laws of inheritance to predict the probability of having a PSV based on family history, as well as specified PSV frequency and penetrance (agespecific probability of developing cancer given genotype). Most existing models assume penetrance is the same for any PSVs in a certain gene. However, for some genes (for example, BRCA1/2), cancer risk does vary by PSV. We propose an extension of Mendelian risk prediction models to relax the assumption that risk is the same for any PSVs in a certain gene by incorporating variant-specific penetrances and illustrating these extensions on two existing Mendelian risk prediction models, BRCAPRO and PanelPRO. Our proposed BRCAPRO-variant and PanelPRO-variant models incorporate variant-specific BRCA1/2 PSVs through the region classifications. Due to the sparsity of the variant information we classify BRCA1/2 PSVs into three regions; the breast cancer clustering region (BCCR), the ovarian cancer clustering region (OCCR), and an other region. Simulations were conducted to evaluate the performance of the proposed BRCAPRO-variant model compared to the existing BRCAPRO model which assumes the penetrance is the same for any PSVs in BRCA1 (and respectively BRCA2). Simulation results showed that the BRCAPRO-variant model was well calibrated to predict region-specific BRCA1/2 carrier status with high discrimination and accuracy on the region-specific level. In addition, we showed that the BRCAPRO-variant model achieved performance gains over the existing risk prediction models in terms of calibration without loss in discrimination and accuracy. We also evaluated the performance of the two proposed models, BRCAPRO-variant and PanelPRO-variant, on a cohort of 1,961 families from the Cancer Genetics Network (CGN). We showed that our proposed models provide region-specific PSV carrier probabilities with high accuracy, while the calibration, discrimination and accuracy of gene-specific PSV carrier probabilities were comparable to the existing gene-specific models. As more variant-specific PSV penetrances become available, we have shown that Mendelian risk prediction models can be extended to integrate the additional information, providing precise variant or region-specific PSV carrier probabilities and improving future cancer risk predictions.

Muscle wasting assessment tools for prostate cancer.

Prostate cancer and its treatment may induce muscle wasting. Body composition and muscle functionality are rarely assessed in patients with prostate cancer from developing countries due to the limited availability of high-quality equipment for routine diagnosis. This cross-sectional study evaluated the association between several simplistic techniques for assessing muscle mass and function with a more complex standard of reference for muscle wasting among Mexican men with prostate cancer. Muscle wasting was highly prevalent, yet it was presumably associated with aging rather than cancer and its treatment itself. The restricted availability of specific equipment in clinical settings with technological limitations supports using unsophisticated techniques as surrogate measurements for muscle wasting. The left-arm handgrip dynamometry displayed the highest correlation with the standard of reference and exhibited an acceptable predicted probability for muscle estimation. Combining several simplistic techniques may be preferable. We also developed and internally validated a manageable model that helps to identify elderly patients with prostate cancer at risk of muscle depletion and impairment. These findings promote the early recognition and treatment of muscle wasting alterations occurring among older adults with prostate cancer.

Genomic diversity and meiotic recombination among isolates of the biotech yeast Komagataella phaffii (Pichia pastoris).

BACKGROUND: Komagataella phaffii is a yeast widely used in the pharmaceutical and biotechnology industries, and is one of the two species that were previously called Pichia pastoris. However, almost all laboratory work on K. phaffii has utilized strains derived from a single natural isolate, CBS7435. There is little information about the sequence diversity of K. phaffii or the genetic properties of this species. RESULTS: We sequenced the genomes of all the known isolates of K. phaffii. We made a genetic cross between derivatives of two isolates that differ at 44,000 single nucleotide polymorphism sites, and used this cross to analyze the rate and landscape of meiotic recombination. We conducted tetrad analysis by making use of the property that K. phaffii haploids do not mate in rich media, which enabled us to isolate and sequence the four types of haploid cell that are present in the colony that forms when a tetra-type ascus germinates. CONCLUSIONS: We found that only four distinct natural isolates of K. phaffii exist in public yeast culture collections. The meiotic recombination rate in K. phaffii is approximately 3.5 times lower than in Saccharomyces cerevisiae, with an average of 25 crossovers per meiosis. Recombination is suppressed, and genetic diversity among natural isolates is low, in a region around centromeres that is much larger than the centromeres themselves. Our work lays a foundation for future quantitative trait locus analysis in K. phaffii.