Polygenic score accuracy in ancient samples: Quantifying the effects of allelic turnover.

Polygenic scores link the genotypes of ancient individuals to their phenotypes, which are often unobservable, offering a tantalizing opportunity to reconstruct complex trait evolution. In practice, however, interpretation of ancient polygenic scores is subject to numerous assumptions. For one, the genome-wide association (GWA) studies from which polygenic scores are derived, can only estimate effect sizes for loci segregating in contemporary populations. Therefore, a GWA study may not correctly identify all loci relevant to trait variation in the ancient population. In addition, the frequencies of trait-associated loci may have changed in the intervening years. Here, we devise a theoretical framework to quantify the effect of this allelic turnover on the statistical properties of polygenic scores as functions of population genetic dynamics, trait architecture, power to detect significant loci, and the age of the ancient sample. We model the allele frequencies of loci underlying trait variation using the Wright-Fisher diffusion, and employ the spectral representation of its transition density to find analytical expressions for several error metrics, including the expected sample correlation between the polygenic scores of ancient individuals and their true phenotypes, referred to as polygenic score accuracy. Our theory also applies to a two-population scenario and demonstrates that allelic turnover alone may explain a substantial percentage of the reduced accuracy observed in cross-population predictions, akin to those performed in human genetics. Finally, we use simulations to explore the effects of recent directional selection, a bias-inducing process, on the statistics of interest. We find that even in the presence of bias, weak selection induces minimal deviations from our neutral expectations for the decay of polygenic score accuracy. By quantifying the limitations of polygenic scores in an explicit evolutionary context, our work lays the foundation for the development of more sophisticated statistical procedures to analyze both temporally and geographically resolved polygenic scores.

Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis.

Background Digital breast tomosynthesis (DBT) is often inadequate for screening women with a personal history of breast cancer (PHBC). The ongoing prospective Tomosynthesis or Contrast-Enhanced Mammography, or TOCEM, trial includes three annual screenings with both DBT and contrast-enhanced mammography (CEM). Purpose To perform interim assessment of cancer yield, stage, and recall rate when CEM is added to DBT in women with PHBC. Materials and Methods From October 2019 to December 2022, two radiologists interpreted both examinations: Observer 1 reviewed DBT first and then CEM, and observer 2 reviewed CEM first and then DBT. Effects of adding CEM to DBT on incremental cancer detection rate (ICDR), cancer type and node status, recall rate, and other performance characteristics of the primary radiologist decisions were assessed. Results Among the participants (mean age at entry, 63.6 years ± 9.6 [SD]), 1273, 819, and 227 women with PHBC completed year 1, 2, and 3 screening, respectively. For observer 1, year 1 cancer yield was 20 of 1273 (15.7 per 1000 screenings) for DBT and 29 of 1273 (22.8 per 1000 screenings; ICDR, 7.1 per 1000 screenings [95% CI: 3.2, 13.4]) for DBT plus CEM (P < .001). Year 2 plus 3 cancer yield was four of 1046 (3.8 per 1000 screenings) for DBT and eight of 1046 (7.6 per 1000 screenings; ICDR, 3.8 per 1000 screenings [95% CI: 1.0, 7.6]) for DBT plus CEM (P = .001). Year 1 recall rate for observer 1 was 103 of 1273 (8.1%) for (incidence) DBT alone and 187 of 1273 (14.7%) for DBT plus CEM (difference = 84 of 1273, 6.6% [95% CI: 5.3, 8.1]; P < .001). Year 2 plus 3 recall rate was 40 of 1046 (3.8%) for DBT and 92 of 1046 (8.8%) for DBT plus CEM (difference = 52 of 1046, 5.0% [95% CI: 3.7, 6.3]; P < .001). In 18 breasts with cancer detected only at CEM after integration of both observers, 13 (72%) cancers were invasive (median tumor size, 0.6 cm) and eight of nine (88%) with staging were N0. Among 1883 screenings with adequate reference standard, there were three interval cancers (one at the scar, two in axillae). Conclusion CEM added to DBT increased early breast cancer detection each year in women with PHBC, with an accompanying approximately 5.0%-6.6% recall rate increase. Clinical trial registration no. NCT04085510 © RSNA, 2024 Supplemental material is available for this article.

Cancer Yield Exceeds 2% for BI-RADS 3 Probably Benign Findings in Women Older Than 60 Years in the National Mammography Database.

Background Breast Imaging Reporting and Data System (BI-RADS) category 3 (BR3) (probably benign) mammographic assessments are reserved for imaging findings known to have likelihood of malignancy of 2% or less. Purpose To determine the effect of age, finding type, and prior mammography on cancer yield for BR3 findings in the National Mammography Database (NMD). Materials and Methods This HIPAA-compliant retrospective cohort institutional review board-exempt study evaluated women recalled from screening mammography followed by BR3 assessment at diagnostic evaluation from January 2009 to March 2018 and from 471 NMD facilities. Only the first BR3 occurrence was included for women with biopsy or imaging follow-up of at least 2 years. Women with a history of breast cancer or who underwent biopsy at time of initial BR3 assessment were excluded. Women were stratified by age in 10-year intervals. Cancer yield was calculated for each age group, with (for presumed new findings) and without prior mammographic comparison, and by lesion type, where available. Linear regression with weighted-age binning was performed to assess for differences between groups; P < .05 was indicative of a significant difference. Results A total of 1 380 652 (18.2%) women were recalled after screening mammography, of whom 157 130 (11.4%) were given a BR3 assessment within 90 days after screening. Of these, 43 628 women (median age, 55 years; age range, 25-90 years) had adequate follow-up for analysis. Cancer yield increased with increasing age decile, ranging from 0.51% (six of 1167) in women aged 30-39 years to 4.63% (41 of 885) in women aged 80-90 years; cancer yield exceeded 2% at and after age 59.7 years for baseline findings and at and after age 53.6 years for presumed new findings, although there was no effect on stage distribution. Cancer yield for baseline BR3 masses was 10 of 2111 (0.47% [95% CI: 0.24, 0.90]) versus 47 of 3003 (1.57% [95% CI: 1.16, 2.09]) with prior comparisons (P < .001); cancer yield for baseline calcifications was eight of 929 (0.86% [95% CI: 0.40, 1.76]) versus 84 of 2999 (2.80% [95% CI: 2.23, 3.47]) with prior comparisons (P < .001). Difference in cancer yield was 0.51% (95% CI: 0.16, 0.86) between women with and women without prior comparison at the same age (P = .006). Conclusion Cancer yield exceeded the 2% threshold for women aged 60 years or older and reached 4.6% for women aged 80-89 years. Breast Imaging Reporting and Data System 3 findings in women with a prior comparison had higher cancer yield than in those without a prior comparison at the same age. © RSNA, 2021 Online supplemental material is available for this article.

Parallel altitudinal clines reveal trends in adaptive evolution of genome size in Zea mays.

While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.

Cancer Yield and Patterns of Follow-up for BI-RADS Category 3 after Screening Mammography Recall in the National Mammography Database.

Background The literature supports the use of short-interval follow-up as an alternative to biopsy for lesions assessed as probably benign, Breast Imaging Reporting and Data System (BI-RADS) category 3, with an expected malignancy rate of less than 2%. Purpose To assess outcomes from 6-, 12-, and 24-month follow-up of probably benign findings first identified at recall from screening mammography in the National Mammography Database (NMD). Materials and Methods This retrospective study included women recalled from screening mammography with BI-RADS category 3 assessment at additional evaluation from January 2009 through March 2018 from 471 NMD facilities. Only the first BI-RADS category 3 occurrence for women aged 25 years or older with no personal history of breast cancer was analyzed, with biopsy or 2-year imaging follow-up. Cancer yield and positive predictive value of biopsies performed (PPV3) were determined at each follow-up. Results Among 45 202 women (median age, 55 years; range, 25-90 years) with a BI-RADS category 3 lesion, 1574 (3.5%) underwent biopsy at the time of lesion detection, yielding 72 cancers (cancer yield, 4.6%; 72 of 1574 women). For the remaining 43 628 women who accepted surveillance, 922 were seen within 90 days (with 78 lesions biopsied and 12 [15%] classified as malignant). The women still in surveillance (31 465 of 43 381 women [72.5%]) underwent follow-up mammography at 6 months. Of 3001 (9.5%) lesions biopsied, 456 (15.2%) were malignant (cancer yield, 1.5%; 456 of 31 465 women; 95% confidence interval [CI]: 1.3%, 1.6%). Among 18 748 of 25 997 women (72.1%) in surveillance who underwent follow-up at 12 months, 1219 (6.5%) underwent biopsy with 230 (18.9%) malignant lesions found (cancer yield, 1.2%; 230 of 18 748 women; 95% CI: 1.1%, 1.4%). Through 2-year follow-up, the biopsy rate was 11.2% (4894 of 43 628 women) with a cancer yield of 1.86% (810 malignancies found among 43 628 women; 95% CI: 1.73%, 1.98%) and a PPV3 of 16.6% (810 malignancies found among 4894 women). Conclusion In the National Mammography Database, Breast Imaging Reporting and Data System (BI-RADS) category 3 use is appropriate, with 1.86% cumulative cancer yield through 2-year follow-up. Of 810 malignancies, 468 (57.8%) were diagnosed at or before 6 months, validating necessity of short-interval follow-up of mammographic BI-RADS category 3 findings. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Moy in this issue.

Toward a sustainable biomedical research enterprise: Finding consensus and implementing recommendations.

The US research enterprise is under significant strain due to stagnant funding, an expanding workforce, and complex regulations that increase costs and slow the pace of research. In response, a number of groups have analyzed the problems and offered recommendations for resolving these issues. However, many of these recommendations lacked follow-up implementation, allowing the damage of stagnant funding and outdated policies to persist. Here, we analyze nine reports published since the beginning of 2012 and consolidate over 250 suggestions into eight consensus recommendations made by the majority of the reports. We then propose how to implement these consensus recommendations, and we identify critical issues, such as improving workforce diversity and stakeholder interactions, on which the community has yet to achieve consensus.

A population genetic signal of polygenic adaptation.

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of [Q(ST)/F(ST)] comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results.

Brain Tuberculoma: A Case Report and Literature Review.

We are reporting on a rare case of central nervous system tuberculosis (TB) in the state of South Dakota. Our case features one of the most infrequent forms of TB in the brain: multiple tuberculomas. A 44-year-old immunocompetent man was admitted complaining of a headache and fever for a week. His physical exam was unremarkable. A magnetic resonance imaging scan of his brain showed two ring-enhancing lesions. The largest lesion was excised surgically and the histopathology exam was consistent with tuberculoma. We will discuss in this report various aspects of this rare disease in term of epidemiology, diagnosis, and treatment.

Lubert Stryer (1938-2024).

Trailblazing biochemist and author.

Precise spatio-temporal regulation of the anthocyanin biosynthetic pathway leads to petal spot formation in Clarkia gracilis (Onagraceae).

Petal spots are widespread in angiosperms and are often implicated in pollinator attraction. Clarkia gracilis petals each have a single red-purple spot that contrasts against a pink background. The position and presence of spots in C. gracilis are determined by the epistatic interaction of alleles at two as yet unidentified loci. We used HPLC to identify the different pigments produced in the petals, and qualitative and quantitative RT-PCR to assay for spatio-temporal patterns of expression of different anthocyanin pathway genes. We found that spots contain different pigments from the remainder of the petal, being composed of cyanidin/peonidin-based, instead of malvidin-based anthocyanins. Expression assays of anthocyanin pathway genes showed that the dihydroflavonol-4-reductase 2 (Dfr2) gene has a spot-specific expression pattern and acts as a switch for spot production. Co-segregation analyses implicated the gene products of the P and I loci as trans-regulators of this switch. Spot pigments appear earlier in development as a result of early expression of Dfr2 and the flavonoid 3' hydroxylase 1 (F3'h1) gene. Pigments in the background appear later, as a result of later expression of Dfr1 and the flavonoid 3'-5' hydroxylase 1 (F3'5'h1) genes. The evolution of this spot production mechanism appears to have been facilitated by duplication of the Dfr gene and to have required substantial reworking of the anthocyanin pathway regulatory network.

High priority preparedness research and its support.

The US Federal Government has considerable interest in supporting research into preparedness. Because of the diverse nature of possible threats and the responsibilities of different agencies, a number of different programs have been developed. Perspectives from representatives from 3 of the leading agencies; the Department of Homeland Security, the Centers from Disease Control and Prevention, and the National Institutes of Health, are described herein.

Testing for differences in polygenic scores in the presence of confounding.

Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Finally, we use the understanding gained from this analysis to develop a method that uses patterns of genetic similarity between the two panels to guard against these biases, and show that this method can provide better protection against confounding than the standard PCA-based approach.

Prospective Multicenter Diagnostic Performance of Technologist-Performed Screening Breast Ultrasound After Tomosynthesis in Women With Dense Breasts (the DBTUST).

PURPOSE: To assess diagnostic performance of digital breast tomosynthesis (DBT) alone or combined with technologist-performed handheld screening ultrasound (US) in women with dense breasts. METHODS: In an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant multicenter protocol in western Pennsylvania, 6,179 women consented to three rounds of annual screening, interpreted by two radiologist observers, and had appropriate follow-up. Primary analysis was based on first observer results. RESULTS: Mean participant age was 54.8 years (range, 40-75 years). Across 17,552 screens, there were 126 cancer events in 125 women (7.2/1,000; 95% CI, 5.9 to 8.4). In year 1, DBT-alone cancer yield was 5.0/1,000, and of DBT+US, 6.3/1,000, difference 1.3/1,000 (95% CI, 0.3 to 2.1; P = .005). In years 2 + 3, DBT cancer yield was 4.9/1,000, and of DBT+US, 5.9/1,000, difference 1.0/1,000 (95% CI, 0.4 to 1.5; P < .001). False-positive rate increased from 7.0% for DBT in year 1 to 11.5% for DBT+US and from 5.9% for DBT in year 2 + 3 to 9.7% for DBT+US (P < .001 for both). Nine cancers were seen only by double reading DBT and one by double reading US. Ten interval cancers (0.6/1,000 [95% CI, 0.2 to 0.9]) were identified. Despite reduction in specificity, addition of US improved receiver operating characteristic curves, with area under receiver operating characteristic curve increasing from 0.83 for DBT alone to 0.92 for DBT+US in year 1 (P = .01), with smaller improvements in subsequent years. Of 6,179 women, across all 3 years, 172/6,179 (2.8%) unique women had a false-positive biopsy because of DBT as did another 230/6,179 (3.7%) women because of US (P < .001). CONCLUSION: Overall added cancer detection rate of US screening after DBT was modest at 19/17,552 (1.1/1,000; CI, 0.5- to 1.6) screens but potentially overcomes substantial increases in false-positive recalls and benign biopsies.

Exploring the use of cobalt(II) dipolar shifts in refining the structure of a zinc finger peptide.

The uses of dipolar shifts due to cobalt(II) substituted for zinc(II) in a consensus zinc finger peptide for refining the NMR-determined structure were examined. Substantial differences between the calculated and observed chemical shift differences between the cobalt(II) and zinc(II) complexes were observed when these dipolar shifts were not used as constraints in the structure refinement. However, inclusion of these constraints resulted in excellent agreement with minor adjustments in the structure and a slight improvement in the precision of the structure determination. Other calculations revealed that the dipolar shifts were not adequate to determine the overall folded structure by themselves, but were useful in increasing the accuracy and precision of a structure determined based only on nuclear Overhauser effects constraints involving only backbone atoms.

Identification of nucleic acid binding residues in the FCS domain of the polycomb group protein polyhomeotic.

Polycomb group (PcG) proteins maintain the silent state of developmentally important genes. Recent evidence indicates that noncoding RNAs also play an important role in targeting PcG proteins to chromatin and PcG-mediated chromatin organization, although the molecular basis for how PcG and RNA function in concert remains unclear. The Phe-Cys-Ser (FCS) domain, named for three consecutive residues conserved in this domain, is a 30-40-residue Zn(2+) binding motif found in a number of PcG proteins. The FCS domain has been shown to bind RNA in a non-sequence specific manner, but how it does so is not known. Here, we present the three-dimensional structure of the FCS domain from human Polyhomeotic homologue 1 (HPH1, also known as PHC1) determined using multidimensional nuclear magnetic resonance methods. Chemical shift perturbations upon addition of RNA and DNA resulted in the identification of Lys 816 as a potentially important residue required for nucleic acid binding. The role played by this residue in Polyhomeotic function was demonstrated in a transcription assay conducted in Drosophila S2 cells. Mutation of the Arg residue to Ala in the Drosophila Polyhomeotic (Ph) protein, which is equivalent to Lys 816 in HPH1, was unable to repress transcription of a reporter gene to the level of wild-type Ph. These results suggest that direct interaction between the Ph FCS domain and nucleic acids is required for Ph-mediated repression.