Risk factors affecting polygenic score performance across diverse cohorts.

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Polygenic Risk for Type 2 Diabetes in African Americans.

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Here, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA-focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method. We further tested the score in three independent studies with a total of 7,275 AAs and compared the PRSAA with other published scores. Results show that a 1-SD increase in the PRSAA was associated with 40-60% increase in the odds of T2D (odds ratio [OR] 1.60, 95% CI 1.37-1.88; OR 1.40, 95% CI 1.16-1.70; and OR 1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values for three calculated score thresholds (the top 2%, 5%, and 10%) ranged from 14 to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. The need remains for larger data sets to continue to evaluate the utility of within-ancestry scores in the AA population.

Pharmacogenetic actionability and medication prescribing in people with cystic fibrosis.

Although major advancements have been made in the therapeutics for people with cystic fibrosis (PwCF), many still require the use of multiple medications to manage acute exacerbations of disease and maintain health. Iterative trial and error processes of pharmacotherapeutic management can be optimized by assessing and incorporating pharmacogenetics. For 82 PwCF, we reviewed 2 years of medication use and response history and interrogated metabolizer status for common pharmacogenes, revealing 3336 medication exposure events (MEEs) to 286 unique medications. As expected, the more frequent MEEs were those commonly used to treat cystic fibrosis (CF), such as antibiotics and respiratory medications. Antibiotics also comprised 56.7% of the undesirable drug responses. The impact of gene variants on drug responses was assessed using Pharmacogenomics Knowledgebase (PharmGKB) and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Thirty-three (11.5%) medications have strong evidence of genetic influence on response as evidenced by gene-based dosing guidelines. 110 (38.5%) unique medications had at least one association with a very important pharmacogene, whereas 143 (50%) were associated with at least one clinical or variant annotation. Over 97% of participants had at least one actionable genotype. Eleven (13.4%) patients with an actionable genotype, taking the impacted medication, had an undesirable drug response described in the CPIC guidelines that could potentially have been mitigated with a priori knowledge of the genotype. PwCF take many medications for disease management, with frequent dose changes to elicit a desired clinical effect. As CF care evolves, implementing pharmacogenetics testing can improve efficiency and safety of prescribing practices using precision selection and dosing at medication initiation.

Personalizing Direct Oral Anticoagulant Therapy for a Diverse Population: Role of Race, Kidney Function, Drug Interactions, and Pharmacogenetics.

Oral anticoagulants (OACs) are commonly used to reduce the risk of venous thromboembolism and the risk of stroke in patients with atrial fibrillation. Endorsed by the American Heart Association, American College of Cardiology, and the European Society of Cardiology, direct oral anticoagulants (DOACs) have displaced warfarin as the OAC of choice for both conditions, due to improved safety profiles, fewer drug-drug and drug-diet interactions, and lack of monitoring requirements. Despite their widespread use and improved safety over warfarin, DOAC-related bleeding remains a major concern for patients. DOACs have stable pharmacokinetics and pharmacodynamics; however, variability in DOAC response is common and may be attributed to numerous factors, including patient-specific factors, concomitant medications, comorbid conditions, and genetics. Although DOAC randomized controlled trials included patients of varying ages and levels of kidney function, they failed to include patients of diverse ancestries. Additionally, current evidence to support DOAC pharmacogenetic associations have primarily been derived from European and Asian individuals. Given differences in genotype frequencies and disease burden among patients of different biogeographic groups, future research must engage diverse populations to assess and quantify the impact of predictors on DOAC response. Current under-representation of patients from diverse racial groups does not allow for proper generalization of the influence of clinical and genetic factors in relation to DOAC variability. Herein, we discuss factors affecting DOAC response, such as age, sex, weight, kidney function, drug interactions, and pharmacogenetics, while offering a new perspective on the need for further research including frequently excluded groups.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations.

BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Pharmacogenetic Predictors of Cannabidiol Response and Tolerability in Treatment-Resistant Epilepsy.

In patients with treatment-resistant epilepsy (TRE), cannabidiol (CBD) produces variable improvement in seizure control. Patients in the University of Alabama at Birmingham CBD Expanded Access Program (EAP) were enrolled in the genomic study and genotyped using the Affymetrix Drug Metabolizing Enzymes and Transporters plus array. Associations between variants and CBD response (≥50% seizure reduction) and tolerability (diarrhea, sedation, and abnormal liver function) was evaluated under dominant and recessive models. Expression quantitative trait loci (eQTL) influencing potential CBD targets was evaluated in the UK Brain Expression Consortium data set (Braineac), and genetic co-expression examined. Of 169 EAP patients, 112 (54.5% pediatric and 50.0% female) were included in the genetic analyses. Patients with AOX1 rs6729738 CC (aldehyde oxidase; odds ratio (OR) 6.69, 95% confidence interval (CI) 2.19-20.41, P = 0.001) or ABP1 rs12539 (diamine oxidase; OR 3.96, 95% CI 1.62-9.73, P = 0.002) were more likely to respond. Conversely, patients with SLC15A1 rs1339067 TT had lower odds of response (OR 0.06, 95% CI 0.01-0.56, P = 0.001). ABCC5 rs3749442 was associated with lower likelihood of response and abnormal liver function tests, and higher likelihood of sedation. The eQTL revealed that rs1339067 decreased GPR18 expression (endocannabinoid receptor) in white matter (P = 5.6 × 10-3 ), and rs3749442 decreased hippocampal HTR3E expression (serotonin 5-HT3E ; P = 8.5 × 10-5 ). Furthermore, 75% of genes associated with lower likelihood of response were co-expressed. Pharmacogenetic variation is associated with CBD response and influences expression of CBD targets in TRE. Implicated pathways, including cholesterol metabolism and glutathione conjugation, demonstrate potential interactions between CBD and common medications (e.g., statins and acetaminophen) that may require closer monitoring. These results highlight the role of pharmacogenes in fundamental biologic processes and potential genetic underpinnings of treatment-resistance.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine.

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Evaluation of population-level pharmacogenetic actionability in Alabama.

The evolution of evidence and availability of Clinical Pharmacogenetic Implementation Consortium (CPIC) guidelines have enabled assessment of pharmacogenetic (PGx) actionability and clinical implementation. However, population-level actionability is not well-characterized. We leveraged the Alabama Genomic Health Initiative (AGHI) to evaluate population-level PGx actionability. Participants (>18 years), representing all 67 Alabama counties, were genotyped using the Illumina Global Screening array. Using CPIC guidelines, actionability was evaluated using (1) genotype data and genetic ancestry, (2) prescribing data, and (3) combined genotype and medication data. Of 6,331 participants, 4230 had genotype data and 3386 had genotype and prescription data (76% women; 76% White/18% Black [self-reported]). Genetic ancestry was concordant with self-reported race. For CPIC level A genes, 98.6% had an actionable genotype (99.4% Blacks/African; 98.5% White/European). With the exception of DPYD and CYP2C19, the prevalence of actionable genotypes by gene differed significantly by race. Based on prescribing, actionability was highest for CYP2D6 (70.9%), G6PD (54.1%), CYP2C19 (53.5%), and CYP2C9 (47.5%). Among participants prescribed atenolol, carvedilol, or metoprolol, ~ 50% had an actionable ADRB1 genotype, associated with decreased therapeutic response, with higher actionability among Blacks compared to Whites (62.5% vs. 47.4%; p < 0.0001). Based on both genotype and prescribing frequencies, no significant differences in actionability were observed between men and women. This statewide effort highlights PGx population-level impact to help optimize pharmacotherapy. Almost all Alabamians harbor an actionable genotype, and a significant proportion are prescribed affected medications. Statewide efforts, such as AGHI, lay the foundation for translational research and evaluate "real-world" outcomes of PGx.

Global Burden of Violence.

This article documents the increasing numbers of children impacted annually by 1 or more types of violence against children and describes the range of types of injuries and their immediate and long-term impacts on child outcomes. The article describes the growing number of international collaborations to decrease the numbers of children impacted by violence and to mitigate the consequences thereof, with a particular emphasis on children living in war zones.

Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems.

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.

Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients.

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures: Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Validation of the Spartan RXCYP2C19 Genotyping Assay Utilizing Blood Samples.

The antiplatelet agent clopidogrel, a prodrug that requires bioactivation through the cytochrome P450 2C19 (CYP2C19) enzyme, is commonly prescribed post-percutaneous coronary intervention (PCI). Genetic variation in CYP2C19 contributes to individual variability in clopidogrel response, and can lead to adverse cardiovascular events. Incorporating CYP2C19 testing during routine clinical care helps identify high-risk patients, and provides the opportunity for pharmacotherapeutic interventions in the early post-PCI period. The Spartan RX CYP2C19 System has emerged as an optimal genotyping assay for use in clinical care due to ease of use, utilization of buccal swabs, and rapid turnaround time. However, workflow constraints related to sample collection and processing, storage, time, and personnel were encountered when integrating testing into clinical care. To improve clinical workflow and successfully implement CYP2C19 genotyping at our institution, we validated the Spartan RX System to return genotype utilizing blood samples. Our Molecular Diagnostic Laboratory tested 26 known reference materials and both blood and buccal swab samples from 23 patients and volunteers using the Spartan RX Assay. Genotype results were 100% concordant between DNA from blood and buccal swabs for all patients or volunteers, and consistent with expected results for the 26 reference materials. For reproducibility, three samples were tested in at least four separate runs, with all resulting genotypes in agreement between runs. Post-validation, the laboratory began offering CYP2C19 testing during clinical care. DNA extracted from blood can serve as a genomic DNA source for the Spartan RX Assay. Alteration of the methodology allowed for clinical implementation to support genotype-guided therapy.

Improvement in Kidney Function After Ventricular Assist Device Implantation and Its Influence on Thromboembolism, Hemorrhage, and Mortality.

Although heart transplantation remains the gold standard for management of heart failure, ventricular assist devices (VAD) have emerged as viable alternatives. VAD implantation improves kidney function. However, whether the improvement is sustained or associated with improved outcomes is unclear. Herein we assess kidney function improvement, predictors of improvement, and associations with thromboembolism, hemorrhage, and mortality in VAD patients. Kidney function was defined using chronic kidney disease (CKD) stages: stage 1 (glomerular filtration rate [eGFR] ≥ 90 ml/min/1.73 m), stage 2 (eGFR 60-90 ml/min/1.73 m), stage 3a (eGFR 45-59 ml/min/1.73 m), stage 3b (eGFR 30-44 ml/min/1.73 m), stage 4 (eGFR 15-30 ml/min/1.73 m), and stage 5 (eGFR < 15 ml/min/1.73 m). Improvement in kidney function was defined as an improvement in eGFR that resulted in a CKD stage change to one of lesser severity. Kidney function improved post implant, and was maintained over 1 year for all patients, except those with baseline stage 5 CKD. Younger age at implantation (OR 0.93, 95% CI: 0.90-0.96, P < 0.0001) was associated with sustained improvement in kidney function. Poor kidney function was associated increased mortality but not with thromboembolism or hemorrhage. Compared to patients with baseline eGFR > 45 ml/min/1.73 m; patients with eGFR < 45 ml/min/1.73 m had a higher mortality risk (HR 3.32, 95% CI: 1.10-9.98, p = 0.03 for stage 3b; HR 4.07, 95% CI: 1.27-13.1, p = 0.02 for stage 4; and HR 4.01, 95% CI: 1.17-13.7, p = 0.03 for stage 5 CKD). Kidney function was not associated with thromboembolism or hemorrhage, and sustained improvement was not associated with lower risk of death. However, poor kidney function at implantation was associated with an increased risk of mortality.

Between a rock and a hard place: a high-risk patient with resistance to multiple P2Y12 antagonists.

Impaired response to P2Y12 receptor antagonists, such as clopidogrel and prasugrel, can have devastating consequences for patients that require prolonged or indefinite therapy with these agents, including those with a left ventricular assist device (LVAD). While loss-of-function (LOF) alleles in CYP2C19 have been elucidated as contributing to high on treatment platelet reactivity (HTPR) during clopidogrel therapy, genetic variations in the metabolic pathway of prasugrel have not been shown to elicit this same effect. Moreover, limited studies have assessed the effect of coexisting genetic variations in pharmacokinetic and pharmacodynamic pathways. Herein, we report a left ventricular assist device patient exhibiting high on treatment platelet reactivity during clopidogrel and prasugrel therapy. Genotyping revealed variants in pharmacokinetic (CYP2B6), and pharmacodynamic pathways, with multiple variants in P2Y12, the target receptor.

Prostate cancer-derived cathelicidin-related antimicrobial peptide facilitates macrophage differentiation and polarization of immature myeloid progenitors to protumorigenic macrophages.

BACKGROUND: A growing body of evidence indicates a positive correlation between expression of human antimicrobial peptide leucin leucin 37 (LL-37) and progression of epithelial cancers, including prostate cancer (PCa). Although the molecular mechanisms for this correlation has not yet been elucidated, the primary function of LL-37 as a chemotactic molecule for innate immune effector cells suggests its possible association in coordinating protumorigenic mechanisms, mediated by tumor-infiltrating immune cells. METHODS: To investigate protumorigenic role(s) of cathelicidin-related antimicrobial peptide (CRAMP), a murine orthologue of LL-37, the present study compared tumor growth kinetics between mouse PCa cell lines with and without CRAMP expression (TRAMP-C1 and TRAMP-C1(CRAMP-sh) , respectively) in immunocompetent mice. CRAMP-mediated chemotaxis of different innate immune cell types to the tumor microenvironment (TME) was observed in vivo and confirmed by in vitro chemotaxis assay. The role of CRAMP in differentiation and polarization of immature myeloid progenitors (IMPs) to protumorigenic type 2 macrophages (M2) in TME was determined by adoptive transfer of IMPs into mice bearing CRAMP(+) and CRAMP(-) tumors. To differentiate protumorigenic events mediated by tumor-derived CRAMP from host immune cell-derived CRAMP, tumor challenge study was performed in CRAMP-deficient mice. To identify mechanisms of CRAMP function, macrophage colony stimulating factor (M-CSF) and monocyte chemoattractant protein 1 (MCP-1) gene expression was analyzed by QRT-PCR and STAT3 signaling was determined by immunoblotting. RESULTS: Significantly delayed tumor growth was observed in wild-type (WT) mice implanted with TRAMP-C1(CRAMP-sh) cells compared to mice implanted with TRAMP-C1 cells. CRAMP(+) TME induced increased number of IMP differentiation into protumorigenic M2 macrophages compared to CRAMP(-) TME, indicating tumor-derived CRAMP facilitates differentiation and polarization of IMPs toward M2. Tumor challenge study in CRAMP deficient mice showed comparable tumor growth kinetics with WT mice, suggesting tumor-derived CRAMP plays a crucial role in PCa progression. In vitro study demonstrated that overexpressed M-CSF and MCP-1 in TRAMP-C1 cells through CRAMP-mediated autocrine signaling, involving p65, regulates IMP-to-M2 differentiation/polarization through STAT3 activation. CONCLUSION: Altogether, the present study suggests that overexpressed CRAMP in prostate tumor initially chemoattracts IMPs to TME and mediates differentiation and polarization of early myeloid progenitors into protumorigenic M2 macrophages during PCa progression. Thus, selective downregulation of CRAMP in tumor cells in situ may benefit overcoming immunosuppressive mechanisms in PCa.