SARS-CoV-2 Antiviral Prescribing Gaps Among Nonhospitalized High-Risk Adults.

Within a multistate clinical cohort, SARS-CoV-2 antiviral prescribing patterns were evaluated from April 2022-June 2023 among nonhospitalized patients with SARS-CoV-2 with risk factors for severe COVID-19. Among 3247 adults, only 31.9% were prescribed an antiviral agent (87.6% nirmatrelvir/ritonavir, 11.9% molnupiravir, 0.5% remdesivir), highlighting the need to identify and address treatment barriers.

Competitive exclusion by autologous antibodies can prevent broad HIV-1 antibodies from arising.

The past decade has seen the discovery of numerous broad and potent monoclonal antibodies against HIV type 1 (HIV-1). Eliciting these antibodies via vaccination appears to be remarkably difficult, not least because they arise late in infection and are highly mutated relative to germline antibody sequences. Here, using a computational model, we show that broad antibodies could in fact emerge earlier and be less mutated, but that they may be prevented from doing so as a result of competitive exclusion by the autologous antibody response. We further find that this competitive exclusion is weaker in infections founded by multiple distinct strains, with broadly neutralizing antibodies emerging earlier than in infections founded by a single strain. Our computational model simulates coevolving multitype virus and antibody populations. Broadly neutralizing antibodies may therefore be easier for the adaptive immune system to generate than previously thought. If less mutated broad antibodies exist, it may be possible to elicit them with a vaccine containing a mixture of diverse virus strains.

Estimating Copy Number and Allelic Variation at the Immunoglobulin Heavy Chain Locus Using Short Reads.

The study of genomic regions that contain gene copies and structural variation is a major challenge in modern genomics. Unlike variation involving single nucleotide changes, data on the variation of copy number is difficult to collect and few tools exist for analyzing the variation between individuals. The immunoglobulin heavy variable (IGHV) locus, which plays an integral role in the adaptive immune response, is an example of a complex genomic region that varies in gene copy number. Lack of standard methods to genotype this region prevents it from being included in association studies and is holding back the growing field of antibody repertoire analysis. Here we develop a method that takes short reads from high-throughput sequencing and outputs a genetic profile of the IGHV locus with the read coverage depth and a putative nucleotide sequence for each operationally defined gene cluster. Our operationally defined gene clusters aim to address a major challenge in studying the IGHV locus: the high sequence similarity between gene segments in different genomic locations. Tests on simulated data demonstrate that our approach can accurately determine the presence or absence of a gene cluster from reads as short as 70 bp. More detailed resolution on the copy number of gene clusters can be obtained from read coverage depth using longer reads (e.g., ≥ 100 bp). Detail at the nucleotide resolution of single copy genes (genes present in one copy per haplotype) can be determined with 250 bp reads. For IGHV genes with more than one copy, accurate nucleotide-resolution reconstruction is currently beyond the means of our approach. When applied to a family of European ancestry, our pipeline outputs genotypes that are consistent with the family pedigree, confirms existing multigene variants and suggests new copy number variants. This study paves the way for analyzing population-level patterns of variation in IGHV gene clusters in larger diverse datasets and for quantitatively handling regions of copy number variation in other structurally varying and complex loci.

SCALING LIMITS OF A MODEL FOR SELECTION AT TWO SCALES.

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval [0, 1] with dependence on a single parameter, λ. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on λ and the behavior of the initial data around 1. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

A unifying framework reveals key properties of multilevel selection.

Natural selection can act at multiple biological levels, often in opposing directions. Viral evolution is an important example, with selection occurring both within infected hosts and between hosts via transmission. A fast-replicating virus may outcompete a slower strain within the same host, however, if rapid viral replication incapacitates the host, this fast-replicating virus may not be transmitted as frequently as its slower counterpart. Such examples of antagonistic multilevel selection arise across biological taxa and scales, from microbial public goods production to male mating strategies. A general formalism for describing and analyzing these diverse systems can identify their common underlying properties. Here I introduce such a unifying framework, which can be intuitively visualized as a stochastic ball-and-urn process. This ball-and-urn process illustrates the dynamics of antagonistic selective forces and allows the systematic derivation of properties with little or no dependence on model parameterization. These properties are consistent with previous studies, both theoretical and empirical, of multilevel selection. In particular I show that selection at the group level is favored when group-level events occur frequently relative to individual-level events, when there is little or no mutation, and when there are many groups relative to the number of individuals in each group. This approach demonstrates how multilevel selection can be understood as a general biological phenomenon, and identifies recurring characteristics that may be independent of specific biological contexts.

A simple model of group selection that cannot be analyzed with inclusive fitness.

A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models, we show two distinct limitations that prevent recasting in terms of inclusive fitness. The first is a limitation across models. We show that if inclusive fitness is to always give the correct prediction, the definition of relatedness needs to change, continuously, along with changes in the parameters of the model. This results in infinitely many different definitions of relatedness - one for every parameter value - which strips relatedness of its meaning. The second limitation is across time. We show that one can find the trajectory for the group selection model by solving a partial differential equation, and that it is mathematically impossible to do this using inclusive fitness.

A case report of Extra-neurologic metastasis of ventricular meningioma with literature review.

Ventricular meningiomas are neoplastic cells originating from the ependymal lining of the central canal of the spinal cord and the ventricles of the brain. These tumorigenic cells predominantly manifest in the fourth ventricle, followed by the spinal cord. Most intraparenchymal ventricular meningiomas are located within the brain tissue, exhibiting a higher degree of malignancy compared to their intracerebroventricular counterparts. While intracranial dissemination and metastasis to the spinal cord can occur, extra-neurologic metastasis is an exceedingly rare phenomenon that lacks a clear elucidation regarding its underlying mechanism. The authors presented a case of supratentorial brain parenchymal type ventricular meningioma surgical treatment in a young female patient, occurring two years after the development of multiple metastases in both lungs, pleura, and mediastinum. This may be attributed to the high malignancy degree and strong invasiveness of this lesion, as well as its proximity to the dura mater and venous sinus. The craniotomy provided an opportunity for tumor cells to invade the adjacent venous sinus, leading to dissemination through the blood system. Additionally, postoperative radiation and chemotherapy were administered to inhibit tumor angiogenesis; however, these treatments also increased the likelihood of tumor cell invasion into neighboring brain tissues and distant metastasis.

Knowledge, attitude, and practice toward total neoadjuvant therapy for rectal cancer among oncologists in China: A survey study.

This cross-sectional survey study aimed to explore the knowledge, attitude, and practice (KAP) toward total neoadjuvant therapy (TNT) for rectal cancer (RC) among specialists in Hainan Province, China. RC specialists working in Hainan Province (China) were enrolled in this cross-sectional study between March and June 2023. A self-designed questionnaire was used to collect the participants' characteristics and KAP toward TNT for RC. A total of 279 valid questionnaires were collected. The KAP scores were 15.91 ± 6.02 (possible range: 0-24), 34.16 ± 5.11 (possible range: 10-50), and 12.42 ± 1.83 (possible range: 3-15), respectively. The KAP scores of specialists who had applied TNT in clinical practice or research and had evaluated RC patients treated with TNT were significantly higher than those who had not (all P < 0.05). The structural equation model showed that knowledge of TNT directly affected attitude (ß = 0.292, P = 0.007) and practice (ß = 0.912, P = 0.007), and attitude toward TNT also had a direct effect on practice (ß = 1.047, P = 0.008). In conclusion, RC specialists in Hainan (China) had inadequate knowledge, negative attitudes, and sufficient practice toward TNT in Hainan Province, China. It is necessary to enhance education for RC specialists to improve their knowledge and attitude toward TNT.

Hepatic artery diameter predicts bleeding risk after gastroesophageal varices treatment: a contrast-enhanced CT study.

OBJECTIVE: Portal hypertension leads to hepatic artery dilatation and a higher risk of bleeding. We tried to identify the bleeding risk after gastroesophageal varices (GOV) treatment using hepatic artery diameter of contrast-enhanced CT. METHODS: Retrospective retrieval of 258 patients with cirrhosis who underwent contrast-enhanced CT from January 2022 to May 2023 and endoscopy within one month thereafter at Hainan Affiliated Hospital of Hainan Medical University. Cirrhotic patients before GOV treatment were used as the test cohort (n = 199), and cirrhotic patients after GOV treatment were used as the validation cohort (n = 59). The grading and bleeding risk was classified according to the endoscopic findings. Arterial-phase images of contrast-enhanced CT were used for coronal reconstruction, and the midpoint diameter of the hepatic artery was measured on coronal images. The optimal cutoff value for identifying bleeding risk was analyzed and calculated in the test cohort, and its diagnostic performance was evaluated in the validation cohort. RESULTS: In the test cohort, hepatic artery diameters were significantly higher in high-risk GOV than in low-risk GOV [4.69 (4.31, 5.56) vs. 3.10 (2.59, 3.77), P < 0.001]. With a hepatic artery diameter cutoff value of 4.06 mm, the optimal area under the operating characteristic curve was 0.940 (95% confidence interval: 0.908-0.972), with a sensitivity of 0.887, a specificity of 0.892, a positive predictive value of 0.904, and a negative predictive value of 0.874 for identifying bleeding risk in the test cohort, while in the validation cohort, the sensitivity was 0.885, specificity was 0.939, positive predictive value was 0.920, and negative predictive value was 0.912. CONCLUSION: Hepatic artery diameter has high diagnostic performance in identifying bleeding risk after GOV treatment.

Integrated microbiome and metabolome analysis reveals that new insight into Radix pseudostellariae polysaccharide enhances PRRSV inactivated vaccine.

In this study, we investigated how Radix pseudostellariae polysaccharide (RPP) enhances the immune response of the inactivated porcine reproductive and respiratory syndrome virus (PRRSV) vaccine through interactions with the microbiome and metabolome. We pretreated sows with 10 mg/kg body weight of RPP via drinking water for 7 days prior to intramuscular injection of the PRRSV vaccine. This significantly increased the concentrations of PRRSV GP5 protein antibody, interleukin (IL)-2, IL-4, IL-10, and interferon (IFN)-γ. Oral administration of RPP also significantly improved the abundance of beneficial bacteria in the stool, such as Parabacteroides distasonis, Prevotella_copri, Eubacterium_sp., and Clostridium_sp._CAG:226, and decreased the levels of potentially pathogenic bacteria, such as Paraeggerthella and [Clostridium] innocuum, compared to the vaccine alone. These bacterial changes were confirmed using quantitative real-time polymerase chain reaction (Q-PCR). Moreover, RPP treatment significantly increased the blood concentrations of L-theanine, taurodeoxycholic acid (TDCA), and N-arachidonoyl proline, and decreased the levels of L-glutamine, oclacitinib, lipoxin C4, and leukotriene C5 in sows after immunization (p< 0.05). The concentrations of various blood metabolites were validated using sandwich enzyme-linked immunosorbent assay (ELISA), confirming the accuracy of the metabolomics data. Intriguingly, the integration of microbiome and metabolome analyses highlighted the significance of Prevotella_copri and TDCA. We consequently developed a mouse immunity model using GP5 protein and discovered that oral administration of RPP significantly enhanced the levels of GP5 protein antibodies, IL-2, IL-4, IL-10, and IFN-γ in mouse serum. It also increased the number of CD3+ and CD3+CD4+ cells in the spleen. Additionally, Prevotella_copri was administered into the large intestine via the anus for 7 days prior to the intramuscular injection of the PRRSV GP5 protein. The results demonstrated a significant increase in TDCA and GP5 antibody concentration in the mouse serum, indicating that RPP modulates Prevotella_copri to elevate its metabolite TDCA, thereby enhancing the GP5 antibody level. In conclusion, oral administration of 10 mg/kg RPP optimizes gut flora diversity and blood metabolites, particularly Prevotella_copri and TDCA, thereby improving the immune response to the inactivated PRRSV vaccine.

Viral SARS-CoV-2 Rebound Rates in Linked Commercial Pharmacy-Based Testing and Health Care Claims.

Background: Viral SARS-CoV-2 rebound (viral RNA rebound) is challenging to characterize in large cohorts due to the logistics of collecting frequent and regular diagnostic test results. Pharmacy-based testing data provide an opportunity to study the phenomenon in a large population, also enabling subgroup analyses. The current real-world evidence approach complements approaches focused on smaller, prospective study designs. Methods: We linked real-time reverse transcription quantitative polymerase chain reaction test data from national pharmacy-based testing to health care claims data via tokenization to calculate the cumulative incidence of viral RNA rebound within 28 days following positive test results in nirmatrelvir/ritonavir (NMV-r)-treated and untreated individuals during the Omicron era (December 2021-November 2022) and prior to the Omicron era (October 2020-November 2021). Results: Among 30 646 patients, the rate of viral RNA rebound was 3.5% (95% CI, 2.0%-5.7%) in NMV-r-treated infections as compared with 1.5% (95% CI, 1.3%-1.7%) in untreated infections during the Omicron era and 1.9% (95% CI, 1.7%-2.1%) prior to the Omicron era. Viral RNA rebound in patients who were vaccinated (n = 8151), high risk (n = 4411), or older (≥65 years, n = 4411) occurred at comparable rates to the overall cohort (range, 1.1%-4.8%). Viral rebounds to high RNA levels in NMV-r-treated infections occurred in 8% of viral rebounds as compared with 5% to 11% in untreated infections. Rates of hospitalization were comparable between patients with NMV-r-treated infections with viral RNA rebound (0%) and untreated patients with viral RNA rebound (0%-1.2%). Conclusions: Our findings suggest viral RNA rebound is rare (< 5%), with rates that were consistent with those from the EPIC-HR trial (Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients). Most occurrences of viral RNA rebound were associated with low viral RNA levels, and viral RNA rebound progression to severe disease was not observed.

Navigating the devious course of evolution: the importance of mechanistic models for identifying eco-evolutionary dynamics in nature.

In proposing his genetic feedback mechanism, David Pimentel was one of the first biologists to argue that the reciprocal interplay of ecological and evolutionary dynamics is an important process regulating population dynamics and ultimately affecting community composition. Although the past decade has seen an increase in research activity on these so-called eco-evolutionary dynamics, there remains a conspicuous lack of compelling natural examples of such feedback. Here we argue that this lack may be due to an inherent difficulty in detecting eco-evolutionary dynamics in nature. By examining models of virulence evolution, host resistance evolution, and antigenic evolution, we show that the influence of evolution on ecological dynamics can often be obscured by other ecological processes that yield similar dynamics. We then show, however, that mechanistic models can be used to navigate this, in Pimentel's words, "devious" course of evolution when effectively combined with empirical data. We argue that these models, improving upon Pimentel's original mathematical models, will therefore play an increasingly important role in identifying more subtle, but possibly ubiquitous, eco-evolutionary dynamics in nature. To highlight the importance of identifying these potentially subtle dynamics in nature, we end by considering our ability to anticipate the effect of population control strategies in the presence of these eco-evolutionary feedbacks.

Post-translational modification and mitochondrial function in Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease with currently no cure. Most PD cases are sporadic, and about 5-10% of PD cases present a monogenic inheritance pattern. Mutations in more than 20 genes are associated with genetic forms of PD. Mitochondrial dysfunction is considered a prominent player in PD pathogenesis. Post-translational modifications (PTMs) allow rapid switching of protein functions and therefore impact various cellular functions including those related to mitochondria. Among the PD-associated genes, Parkin, PINK1, and LRRK2 encode enzymes that directly involved in catalyzing PTM modifications of target proteins, while others like α-synuclein, FBXO7, HTRA2, VPS35, CHCHD2, and DJ-1, undergo substantial PTM modification, subsequently altering mitochondrial functions. Here, we summarize recent findings on major PTMs associated with PD-related proteins, as enzymes or substrates, that are shown to regulate important mitochondrial functions and discuss their involvement in PD pathogenesis. We will further highlight the significance of PTM-regulated mitochondrial functions in understanding PD etiology. Furthermore, we emphasize the potential for developing important biomarkers for PD through extensive research into PTMs.

Drosophila Amus and Bin3 methylases functionally replace mammalian MePCE for capping and the stabilization of U6 and 7SK snRNAs.

U6 and 7SK snRNAs have a 5' cap, believed to be essential for their stability and maintained by mammalian MePCE or Drosophila Bin3 enzymes. Although both proteins are required for 7SK stability, loss of neither destabilizes U6, casting doubts on the function of capping U6. Here, we show that the Drosophila Amus protein, homologous to both proteins, is essential for U6 but not 7SK stability. The loss of U6 is rescued by the expression of an Amus-MePCE hybrid protein harboring the methyltransferase domain from MePCE, highlighting the conserved function of the two proteins as the U6 capping enzyme. Our investigations in human cells establish a dependence of both U6 and 7SK stability on MePCE, resolving a long-standing uncertainty. While uncovering a division of labor of Bin3/MePCE/Amus proteins, we found a "Bin3-Box" domain present only in enzymes associated with 7SK regulation. Targeted mutagenesis confirms its importance for Bin3 function, revealing a possible conserved element in 7SK but not U6 biology.

The biochemistry of acetaminophen hepatotoxicity and rescue: a mathematical model.

BACKGROUND: Acetaminophen (N-acetyl-para-aminophenol) is the most widely used over-the-counter or prescription painkiller in the world. Acetaminophen is metabolized in the liver where a toxic byproduct is produced that can be removed by conjugation with glutathione. Acetaminophen overdoses, either accidental or intentional, are the leading cause of acute liver failure in the United States, accounting for 56,000 emergency room visits per year. The standard treatment for overdose is N-acetyl-cysteine (NAC), which is given to stimulate the production of glutathione. METHODS: We have created a mathematical model for acetaminophen transport and metabolism including the following compartments: gut, plasma, liver, tissue, urine. In the liver compartment the metabolism of acetaminophen includes sulfation, glucoronidation, conjugation with glutathione, production of the toxic metabolite, and liver damage, taking biochemical parameters from the literature whenever possible. This model is then connected to a previously constructed model of glutathione metabolism. RESULTS: We show that our model accurately reproduces published clinical and experimental data on the dose-dependent time course of acetaminophen in the plasma, the accumulation of acetaminophen and its metabolites in the urine, and the depletion of glutathione caused by conjugation with the toxic product. We use the model to study the extent of liver damage caused by overdoses or by chronic use of therapeutic doses, and the effects of polymorphisms in glucoronidation enzymes. We use the model to study the depletion of glutathione and the effect of the size and timing of N-acetyl-cysteine doses given as an antidote. Our model accurately predicts patient death or recovery depending on size of APAP overdose and time of treatment. CONCLUSIONS: The mathematical model provides a new tool for studying the effects of various doses of acetaminophen on the liver metabolism of acetaminophen and glutathione. It can be used to study how the metabolism of acetaminophen depends on the expression level of liver enzymes. Finally, it can be used to predict patient metabolic and physiological responses to APAP doses and different NAC dosing strategies.

Factors Influencing the Progression of Patellofemoral Articular Cartilage Damage After Anterior Cruciate Ligament Reconstruction.

Background: Although anterior cruciate ligament reconstruction (ACLR) can restore the stability and function of the knee joint, patellofemoral joint cartilage damage still progresses. Currently, the clinically important factors that lead to the progression of patellofemoral articular cartilage damage are not fully understood. Purpose: To investigate the factors that affect the progression of patellofemoral articular cartilage damage after ACLR. Study Design: Cohort study; Level of evidence, 2. Methods: Among 160 patients who underwent ACLR between January 2015 and December 2019, the authors evaluated 129 patients for at least 1 year after surgery. Within 1 week before ACLR and at the last follow-up, patients underwent subjective functional assessment and magnetic resonance imaging evaluations of articular cartilage damage (modified Outerbridge assessment). At the last follow-up, the side-to-side difference on KT-2000 arthrometer and bilateral quadriceps muscle strength were measured. Univariate and multivariate logistic regression analyses were performed. Results: The mean follow-up was 24.69 ± 10.74 months. Progression of patellar cartilage damage from preoperatively to final follow-up was seen in 45 patients (P < .001). Logistic regression analysis revealed that the follow-up period (P = .047; odds radio (OR) = 0.953) (improvement of patellar cartilage damage with longer follow-up), partial lateral meniscal resection (P = .004; OR = 6.929), partial medial meniscal resection (P = .004; OR = 6.032), and quadriceps muscle strength <80% of the contralateral side (P = .001; OR = 4.745) were risk factors for the progression of patellar cartilage damage. Conclusion: Cartilage damage at the patellofemoral joint, especially the patellar cartilage, still progresses after ACLR. At a mean follow-up of 24.69 months after ACLR, partial meniscal resection and quadriceps femoris muscle strength were found to be the main risk factors for the progression of patellofemoral articular cartilage damage after ACLR.

A machine-learning approach using pubic CT based on radiomics to estimate adult ages.

PURPOSE: Adult skeletal age estimation is an active research field. To evaluate the performance of a pubic CT radiomics-based machine learning model for estimating age, we established a multiple linear regression model based on radiomics and machine learning methods. METHODS: A total of 355 subjects were enrolled in this retrospective study from August 2016 to August 2021, and divided into a training cohort (N = 325) and a testing cohort (N = 30). Computerized texture analysis of the semi-automatically segmentation was performed and 107 texture features were extracted from the regions. Then we used univariate linear regression and multivariate stepwise regression to assess correlations of texture parameters with age. The most vital features were used to make the best predictive model. Eventually, the established radiomics model was tested with an additional 30 patients. RESULTS: Clinical characteristics include age, sex, height, weight and BMI were not statistically significant different between training and testing cohort (p = 0.098-0.888). Through a multivariate regression analysis using stepwise regression, six texture parameters were found to have significant correlations with age. The regression formula estimating the age was constructed. CONCLUSIONS: The radiomics model using machine learning is considered as a new approach forage estimation frompubic symphysis CT features.Digital osteology is obtained in a non-invasive way so that it can be an ideal collection for anthropological studies.

SARS-CoV-2 variant Delta rapidly displaced variant Alpha in the United States and led to higher viral loads.

We report on the sequencing of 74,348 SARS-CoV-2 positive samples collected across the United States and show that the Delta variant, first detected in the United States in March 2021, made up the majority of SARS-CoV-2 infections by July 1, 2021 and accounted for >99.9% of the infections by September 2021. Not only did Delta displace variant Alpha, which was the dominant variant at the time, it also displaced the Gamma, Iota, and Mu variants. Through an analysis of quantification cycle (Cq) values, we demonstrate that Delta infections tend to have a 1.7× higher viral load compared to Alpha infections (a decrease of 0.8 Cq) on average. Our results are consistent with the hypothesis that the increased transmissibility of the Delta variant could be due to the ability of the Delta variant to establish a higher viral load earlier in the infection as compared to the Alpha variant.

Evidence for SARS-CoV-2 Delta and Omicron co-infections and recombination.

BACKGROUND: Between November 2021 and February 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants co-circulated in the United States, allowing for co-infections and possible recombination events. METHODS: We sequenced 29,719 positive samples during this period and analyzed the presence and fraction of reads supporting mutations specific to either the Delta or Omicron variant. FINDINGS: We identified 18 co-infections, one of which displayed evidence of a low Delta-Omicron recombinant viral population. We also identified two independent cases of infection by a Delta-Omicron recombinant virus, where 100% of the viral RNA came from one clonal recombinant. In the three cases, the 5' end of the viral genome was from the Delta genome and the 3' end from Omicron, including the majority of the spike protein gene, though the breakpoints were different. CONCLUSIONS: Delta-Omicron recombinant viruses were rare, and there is currently no evidence that Delta-Omicron recombinant viruses are more transmissible between hosts compared with the circulating Omicron lineages. FUNDING: This research was supported by the NIH RADx initiative and by the Centers for Disease Control Contract 75D30121C12730 (Helix).

Comprehensive Allele Genotyping in Critical Pharmacogenes Reduces Residual Clinical Risk in Diverse Populations.

Genomic-guided pharmaceutical prescribing is increasingly recognized as an important clinical application of genetics. Accurate genotyping of pharmacogenomic (PGx) genes can be difficult, owing to their complex genetic architecture involving combinations of single-nucleotide polymorphisms and structural variation. Here, we introduce the Helix PGx database, an open-source star allele, genotype, and resulting metabolic phenotype frequency database for CYP2C9, CYP2C19, CYP2D6, and CYP4F2, based on short-read sequencing of >86,000 unrelated individuals enrolled in the Helix DNA Discovery Project. The database is annotated using a pipeline that is clinically validated against a broad range of alleles and designed to call CYP2D6 structural variants with high (98%) accuracy. We find that CYP2D6 has greater allelic diversity than the other genes, manifest in both a long tail of low-frequency star alleles, as well as a disproportionate fraction (36%) of all novel predicted loss-of-function variants identified. Across genes, we observe that many rare alleles (<0.1% frequency) in the overall cohort have 10 times higher frequency in one or more subgroups with non-European genetic ancestry. Extending these PGx genotypes to predicted metabolic phenotypes, we demonstrate that >90% of the cohort harbors a high-risk variant in one of the four pharmacogenes. Based on the recorded prescriptions for >30,000 individuals in the Healthy Nevada Project, combined with predicted PGx metabolic phenotypes, we anticipate that standard-of-care screening of these 4 pharmacogenes could impact nearly half of the general population.