Preferences for genetic testing among populations underrepresented in genomic research: a systematic review
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Commentary: Why is genetic testing underutilized worldwide? The case for hereditary breast cancer
It is thirty years since the BRCA1 and BRCA2 genes were discovered and genetic testing for BRCA1 and BRCA2 was introduced. Despite increasing awareness of the genetic basis of cancer and our evolving knowledge of effective means of prevention, screening, and treatment for hereditary breast and ovarian cancers, genetic testing is underutilized, and most mutation carriers remain unidentified. In this commentary, we explore possible reasons for why this might be so. Our focus is on factors that may influence or deter a patient from pursuing testing, rather than discussing the implications of receiving a positive test result. Issues of concern include an inadequate number of genetic counselors, restrictive (and conflicting) eligibility criteria for testing, the cost of the test, health insurance coverage, fear of future insurance discrimination, privacy issues, lack of familiarity with the testing process in primary care and gaps in both patient and provider knowledge about the impact and the value of testing. We discuss how these factors may lead to the underutilization of genetic testing in North America and throughout the world and discuss alternative models of genetic healthcare delivery. We have invited leaders in cancer genetic from around the world to tell us what they think are the barriers to testing in their host countries.
Multi-population GWAS detects robust marker associations in a newly established six-rowed winter barley breeding program
Genome-wide association study (GWAS) is a powerful tool for identifying marker-trait associations that can accelerate breeding progress. Yet, its power is typically constrained in newly established breeding programs where large phenotypic and genotypic datasets have not yet accumulated. Expanding the dataset by inclusion of data from well-established breeding programs with many years of phenotyping and genotyping can potentially address this problem. In this study we performed single- and multi-population GWAS on heading date and lodging in four barley breeding populations with varying combinations of row-type and growth habit. Focusing on a recently established 6-rowed winter (6RW) barley population, single-population GWAS hardly resulted in any significant associations. Nevertheless, the combination of the 6RW target population with other populations in multi-population GWAS detected four and five robust candidate quantitative trait loci for heading date and lodging, respectively. Of these, three remained undetected when analysing the combined populations individually. Further, multi-population GWAS detected markers capturing a larger proportion of genetic variance in 6RW. For multi-population GWAS, we compared the findings of a univariate model (MP1) with a multivariate model (MP2). While both models surpassed single-population GWAS in power, MP2 offered a significant advantage by having more realistic assumptions while pointing towards robust marker-trait associations across populations. Additionally, comparisons of GWAS findings for MP2 and single-population GWAS allowed identification of population-specific loci. In conclusion, our study presents a promising approach to kick-start genomics-based breeding in newly established breeding populations.
Too big to purge: persistence of deleterious Mutations in Island populations of the European Barn Owl (Tyto alba)
A key aspect of assessing the risk of extinction/extirpation for a particular wild species or population is the status of inbreeding, but the origin of inbreeding and the current mutational load are also two crucial factors to consider when determining survival probability of a population. In this study, we used samples from 502 barn owls from continental and island populations across Europe, with the aim of quantifying and comparing the level of inbreeding between populations with differing demographic histories. In addition to comparing inbreeding status, we determined whether inbreeding is due to non-random mating or high co-ancestry within the population. We show that islands have higher levels of inbreeding than continental populations, and that this is mainly due to small effective population sizes rather than recent consanguineous mating. We assess the probability that a region is autozygous along the genome and show that this probability decreased as the number of genes present in that region increased. Finally, we looked for evidence of reduced selection efficiency and purging in island populations. Among island populations, we found an increase in numbers of both neutral and deleterious minor alleles, possibly as a result of drift and decreased selection efficiency but we found no evidence of purging.
Genome-wide analysis identifies novel shared loci between depression and white matter microstructure
Depression, a complex and heritable psychiatric disorder, is associated with alterations in white matter microstructure, yet their shared genetic basis remains largely unclear. Utilizing the largest available genome-wide association study (GWAS) datasets for depression (N = 674,452) and white matter microstructure (N = 33,224), assessed through diffusion tensor imaging metrics such as fractional anisotropy (FA) and mean diffusivity (MD), we employed linkage disequilibrium score regression method to estimate global genetic correlations, local analysis of [co]variant association approach to pinpoint genomic regions with local genetic correlations, and conjunctional false discovery rate analysis to identify shared variants. Our findings revealed that depression showed significant local genetic correlations with FA in 37 genomic regions and with MD in 59 regions, while global genetic correlations were weak. Variant-level analysis identified 78 distinct loci jointly associated with depression (25 novel loci) and FA (35 novel loci), and 41 distinct loci associated with depression (17 novel loci) and MD (25 novel loci). Further analyses showed that these shared loci exhibited both concordant and discordant effect directions between depression and white matter traits, as well as distinct yet overlapping hemispheric patterns in their genetic architecture. Enrichment analysis of these shared loci implicated biological processes related to metabolism and regulation. This study provides evidence of a mixed-direction shared genetic architecture between depression and white matter microstructure. The identification of specific loci and pathways offers potential insights for developing targeted interventions to improve white matter integrity and alleviate depressive symptoms.
Using twin-pairs to assess potential bias in polygenic prediction of externalising behaviours across development
Prediction from polygenic scores may be confounded by sources of passive gene-environment correlation (rGE; e.g. population stratification, assortative mating, and environmentally mediated effects of parental genotype on child phenotype). Using genomic data from 10 000 twin pairs, we asked whether polygenic scores from the most recent externalising genome-wide association study predict conduct problems, ADHD symptomology and callous-unemotional traits, and whether these predictions are biased by rGE. We ran regression models including within-family and between-family polygenic scores, to separate the direct genetic influence on a trait from environmental influences that correlate with genes (indirect genetic effects). Findings suggested that this externalising polygenic score is a good index of direct genetic influence on conduct and ADHD-related symptoms across development, with minimal bias from rGE, although the polygenic score predicted less variance in CU traits. Post-hoc analyses showed some indirect genetic effects acting on a common factor indexing stability of conduct problems across time and contexts.
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