Breast Cancer Polygenic Risk Score Validation and Effects of Variable Imputation.

Breast cancer (BC) is a complex disease affecting one in eight women in the USA. Advances in population genomics have led to the development of polygenic risk scores (PRSs) with the potential to augment current risk models, but replication is often limited. We evaluated 2 robust PRSs with 313 and 3820 SNPs and the effects of multiple genotype imputation replications in BC cases and control populations. Biological samples from BC cases and cancer-free controls were drawn from three European ancestry cohorts. Genotyping on the Illumina Global Screening Array was followed by stringent quality control measures and 20 genotype imputation replications. A total of 468 unrelated cases and 4337 controls were scored, revealing significant differences in mean PRS percentiles between cases and controls (p < 0.001) for both SNP sets (313-SNP PRS: 52.81 and 48.07; 3820-SNP PRS: 55.45 and 49.81), with receiver operating characteristic curve analysis showing area under the curve values of 0.596 and 0.603 for the 313-SNP and 3820-SNP PRS, respectively. PRS fluctuations (from ~2-3% up to 9%) emerged across imputation iterations. Our study robustly reaffirms the predictive capacity of PRSs for BC by replicating their performance in an independent BC population and showcases the need to average imputed scores for reliable outcomes.

Genome-Wide DNA Methylation Profiles in Whole-Blood and Buccal Samples-Cross-Sectional, Longitudinal, and across Platforms.

The field of DNA methylation research is rapidly evolving, focusing on disease and phenotype changes over time using methylation measurements from diverse tissue sources and multiple array platforms. Consequently, identifying the extent of longitudinal, inter-tissue, and inter-platform variation in DNA methylation is crucial for future advancement. DNA methylation was measured in 375 individuals, with 197 of those having 2 blood sample measurements ~10 years apart. Whole-blood samples were measured on Illumina Infinium 450K and EPIC methylation arrays, and buccal samples from a subset of 58 participants were measured on EPIC array. The data were analyzed with the aims to examine the correlation between methylation levels in longitudinal blood samples in 197 individuals, examine the correlation between methylation levels in the blood and buccal samples in 58 individuals, and examine the correlation between blood methylation profiles assessed on the EPIC and 450K arrays in 83 individuals. We identified 136,833, 7674, and 96,891 CpGs significantly and strongly correlated (>0.50) longitudinally, across blood and buccal samples as well as array platforms, respectively. A total of 3674 of these CpGs were shared across all three sets. Analysis of these shared CpGs identified previously found associations with aging, ancestry, and 7016 mQTLs as well.

More Than Results: The Clinical and Research Relationship in the Evolving Detection and Surveillance of SARS-CoV-2.

INTRODUCTION: During the coronavirus disease 2019 (COVID-19) pandemic, real-time reverse transcription polymerase chain reaction (RT-PCR) became an essential tool for laboratories to provide high-sensitivity qualitative diagnostic testing for patients and real-time data to public health officials. Here we explore the predictive value of quantitative data from RT-PCR cycle threshold (Ct) values in epidemiological measures, symptom presentation, and variant transition. METHODS: To examine the association with hospitalizations and deaths, data from 74,479 patients referred to the Avera Institute for Human Genetics (AIHG) for COVID-19 testing in 2020 were matched by calendar week to epidemiological data reported by the South Dakota Department of Health. We explored the association between symptom data, patient age, and Ct values for 101 patients. We also explored changes in Ct values during variant transition detected by genomic surveillance sequencing of the AIHG testing population during 2021. RESULTS: Measures from AIHG diagnostic testing strongly explain variance in the South Dakota state positivity percentage (R2 = 0.758), a two-week delay in hospitalizations (R2 = 0.856), and a four-week delay in deaths (R2 = 0.854). Based on factor analysis of patient symptoms, three groups could be distinguished which had different presentations of age, Ct value, and time from collection. Additionally, conflicting Ct value results among SARSCoV- 2 variants during variant transition may reflect the community transmission dynamics. CONCLUSIONS: Measures of Ct value in RT-PCR diagnostic assays combined with routine screening have valuable applications in monitoring the dynamics of SARS-CoV-2 within communities.

Implementation and implications for polygenic risk scores in healthcare.

Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.

Chimerism in health and potential implications on behavior: A systematic review.

In this review, we focus on the phenomenon of chimerism and especially microchimerism as one of the currently underexplored explanations for differences in health and behavior. Chimerism is an amalgamation of cells from two or more unique zygotes within a single organism, with microchimerism defined by a minor cell population of <1%. This article first presents an overview of the primary techniques employed to detect and quantify the presence of microchimerism and then reviews empirical studies of chimerism in mammals including primates and humans. In women, male microchimerism, a condition suggested to be the result of fetomaternal exchange in utero, is relatively easily detected by polymerase chain reaction molecular techniques targeting Y-chromosomal markers. Consequently, studies of chimerism in human diseases have largely focused on diseases with a predilection for females including autoimmune diseases, and female cancers. We detail studies of chimerism in human diseases and also discuss some potential implications in behavior. Understanding the prevalence of chimerism and the associated health outcomes will provide invaluable knowledge of human biology and guide novel approaches for treating diseases.