The Effects of Aspirin Intervention on Inflammation-Associated Lingual Bacteria: A Pilot Study from a Randomized Clinical Trial.

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50-75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches.

Effect of ginger supplementation on the fecal microbiome in subjects with prior colorectal adenoma.

Ginger has been associated with a decreased incidence of colorectal cancer (CRC) through reduction in inflammatory pathways and inhibition of tumor growth. Recent pre-clinical models have implicated changes in the gut microbiome as a possible mediator of the ginger effect on CRC. We hypothesized that, in adults previously diagnosed with a colorectal adenoma, ginger supplementation would alter the fecal microbiome in the direction consistent with its CRC-inhibitory effect. Sixty-eight adults were randomized to take either ginger or placebo daily for 6 weeks, with a 6-week washout and longitudinal stool collection throughout. We performed 16S rRNA sequencing and evaluated changes in overall microbial diversity and the relative abundances of pre-specified CRC-associated taxa using mixed-effects logistic regression. Ginger supplementation showed no significant effect on microbial community structure through alpha or beta diversity. Of 10 pre-specified CRC-associated taxa, there were significant decreases in the relative abundances of the genera Akkermansia (p < 0.001), Bacteroides (p = 0.018), and Ruminococcus (p = 0.013) after 6-week treatment with ginger compared to placebo. Ginger supplementation led to decreased abundances of Akkermansia and Bacteroides, which suggests that ginger may have an inhibitory effect on CRC-associated taxa. Overall, ginger supplementation appears to have a limited effect on gut microbiome in patients with colorectal adenomas.

Development and Validation of the Pharmacological Statin-Associated Muscle Symptoms Risk Stratification Score Using Electronic Health Record Data.

Statin-associated muscle symptoms (SAMS) can lead to statin nonadherence. This paper aims to develop a pharmacological SAMS risk stratification (PSAMS-RS) score using a previously developed PSAMS phenotyping algorithm that distinguishes objective vs. nocebo SAMS using electronic health record (EHR) data. Using our PSAMS phenotyping algorithm, SAMS cases and controls were identified from Minnesota Fairview EHR, with the statin user cohort divided into derivation (January 1, 2010, to December 31, 2018) and validation (January 1, 2019, to December 31, 2020) cohorts. A Least Absolute Shrinkage and Selection Operator regression model was applied to identify significant features for PSAMS. PSAMS-RS scores were calculated and the clinical utility of stratifying PSAMS risk was assessed by comparing hazard ratios (HRs) between fourth vs. first score quartiles. PSAMS cases were identified in 1.9% (310/16,128) of the derivation and 1.5% (64/4,182) of the validation cohorts. Sixteen out of 38 clinical features were determined to be significant predictors for PSAMS risk. Patients within the fourth quartile of the PSAMS scores had an over sevenfold (HR: 7.1, 95% confidence interval (CI): 4.03-12.45, derivation cohort) or sixfold (HR: 6.1, 95% CI: 2.15-17.45, validation cohort) higher hazard of developing PSAMS vs. those in their respective first quartile. The PSAMS-RS score is a simple tool to stratify patients' risk of developing PSAMS after statin initiation which could inform clinician-guided pre-emptive measures to prevent PSAMS-related statin nonadherence.

Development and application of pharmacological statin-associated muscle symptoms phenotyping algorithms using structured and unstructured electronic health records data.

Importance: Statins are widely prescribed cholesterol-lowering medications in the United States, but their clinical benefits can be diminished by statin-associated muscle symptoms (SAMS), leading to discontinuation. Objectives: In this study, we aimed to develop and validate a pharmacological SAMS clinical phenotyping algorithm using electronic health records (EHRs) data from Minnesota Fairview. Materials and Methods: We retrieved structured and unstructured EHR data of statin users and manually ascertained a gold standard set of SAMS cases and controls using the published SAMS-Clinical Index tool from clinical notes in 200 patients. We developed machine learning algorithms and rule-based algorithms that incorporated various criteria, including ICD codes, statin allergy, creatine kinase elevation, and keyword mentions in clinical notes. We applied the best-performing algorithm to the statin cohort to identify SAMS. Results: We identified 16 889 patients who started statins in the Fairview EHR system from 2010 to 2020. The combined rule-based (CRB) algorithm, which utilized both clinical notes and structured data criteria, achieved similar performance compared to machine learning algorithms with a precision of 0.85, recall of 0.71, and F1 score of 0.77 against the gold standard set. Applying the CRB algorithm to the statin cohort, we identified the pharmacological SAMS prevalence to be 1.9% and selective risk factors which included female gender, coronary artery disease, hypothyroidism, and use of immunosuppressants or fibrates. Discussion and Conclusion: Our study developed and validated a simple pharmacological SAMS phenotyping algorithm that can be used to create SAMS case/control cohort to enable further analysis which can lead to the development of a SAMS risk prediction model.

Development and validation of the pharmacological statin-associated muscle symptoms risk stratification (PSAMS-RS) score using real-world electronic health record data.

Introduction: Statin-associated muscle symptoms (SAMS) contribute to the nonadherence to statin therapy. In a previous study, we successfully developed a pharmacological SAMS (PSAMS) phenotyping algorithm that distinguishes objective versus nocebo SAMS using structured and unstructured electronic health records (EHRs) data. Our aim in this paper was to develop a pharmacological SAMS risk stratification (PSAMS-RS) score using these same EHR data. Method: Using our PSAMS phenotyping algorithm, SAMS cases and controls were identified using University of Minnesota (UMN) Fairview EHR data. The statin user cohort was temporally divided into derivation (1/1/2010 to 12/31/2018) and validation (1/1/2019 to 12/31/2020) cohorts. First, from a feature set of 38 variables, a Least Absolute Shrinkage and Selection Operator (LASSO) regression model was fitted to identify important features for PSAMS cases and their coefficients. A PSAMS-RS score was calculated by multiplying these coefficients by 100 and then adding together for individual integer scores. The clinical utility of PSAMS-RS in stratifying PSAMS risk was assessed by comparing the hazard ratio (HR) between 4th vs 1st score quartile. Results: PSAMS cases were identified in 1.9% (310/16128) of the derivation and 1.5% (64/4182) of the validation cohort. After fitting LASSO regression, 16 out of 38 clinical features were determined to be significant predictors for PSAMS risk. These factors are male gender, chronic pulmonary disease, neurological disease, tobacco use, renal disease, alcohol use, ACE inhibitors, polypharmacy, cerebrovascular disease, hypothyroidism, lymphoma, peripheral vascular disease, coronary artery disease and concurrent uses of fibrates, beta blockers or ezetimibe. After adjusting for statin intensity, patients in the PSAMS score 4th quartile had an over seven-fold (derivation) (HR, 7.1; 95% CI, 4.03-12.45) and six-fold (validation) (HR, 6.1; 95% CI, 2.15-17.45) higher hazard of developing PSAMS versus those in 1st score quartile. Conclusion: The PSAMS-RS score can be a simple tool to stratify patients' risk of developing PSAMS after statin initiation which can facilitate clinician-guided preemptive measures that may prevent potential PSAMS-related statin non-adherence.

Development and Application of Pharmacological Statin-Associated Muscle Symptoms Phenotyping Algorithms Using Structured and Unstructured Electronic Health Records Data.

Background: Statins are widely prescribed cholesterol-lowering medications in the US, but their clinical benefits can be diminished by statin-associated muscle symptoms (SAMS), leading to discontinuation. In this study, we aimed to develop and validate a pharmacological SAMS clinical phenotyping algorithm using electronic health records (EHRs) data from Minnesota Fairview. Methods: We retrieved structured and unstructured EHR data of statin users and manually ascertained a gold standard set of SAMS cases and controls using the SAMS-CI tool from clinical notes in 200 patients. We developed machine learning algorithms and rule-based algorithms that incorporated various criteria, including ICD codes, statin allergy, creatine kinase elevation, and keyword mentions in clinical notes. We applied the best performing algorithm to the statin cohort to identify SAMS. Results: We identified 16,889 patients who started statins in the Fairview EHR system from 2010-2020. The combined rule-based (CRB) algorithm, which utilized both clinical notes and structured data criteria, achieved similar performance compared to machine learning algorithms with a precision of 0.85, recall of 0.71, and F1 score of 0.77 against the gold standard set. Applying the CRB algorithm to the statin cohort, we identified the pharmacological SAMS prevalence to be 1.9% and selective risk factors which included female gender, coronary artery disease, hypothyroidism, use of immunosuppressants or fibrates. Conclusion: Our study developed and validated a simple pharmacological SAMS phenotyping algorithm that can be used to create SAMS case/control cohort for further analysis such as developing SAMS risk prediction model.

Population pharmacokinetics, pharmacodynamics and pharmacogenetics modelling of oxypurinol in Hmong adults with gout and/or hyperuricemia.

AIMS: The aim of this study was to quantify identifiable sources of variability, including key pharmacogenetic variants in oxypurinol pharmacokinetics and their pharmacodynamic effect on serum urate (SU). METHODS: Hmong participants (n = 34) received 100 mg allopurinol twice daily for 7 days followed by 150 mg allopurinol twice daily for 7 days. A sequential population pharmacokinetic pharmacodynamics (PKPD) analysis with non-linear mixed effects modelling was performed. Allopurinol maintenance dose to achieve target SU was simulated based on the final PKPD model. RESULTS: A one-compartment model with first-order absorption and elimination best described the oxypurinol concentration-time data. Inhibition of SU by oxypurinol was described with a direct inhibitory Emax model using steady-state oxypurinol concentrations. Fat-free body mass, estimated creatinine clearance and SLC22A12 rs505802 genotype (0.32 per T allele, 95% CI 0.13, 0.55) were found to predict differences in oxypurinol clearance. Oxypurinol concentration required to inhibit 50% of xanthine dehydrogenase activity was affected by PDZK1 rs12129861 genotype (-0.27 per A allele, 95% CI -0.38, -0.13). Most individuals with both PDZK1 rs12129861 AA and SLC22A12 rs505802 CC genotypes achieve target SU (with at least 75% success rate) with allopurinol below the maximum dose, regardless of renal function and body mass. In contrast, individuals with both PDZK1 rs12129861 GG and SLC22A12 rs505802 TT genotypes would require more than the maximum dose, thus requiring selection of alternative medications. CONCLUSIONS: The proposed allopurinol dosing guide uses individuals' fat-free mass, renal function and SLC22A12 rs505802 and PDZK1 rs12129861 genotypes to achieve target SU.

Hmong microbiome ANd Gout, Obesity, Vitamin C (HMANGO-C): A phase II clinical study protocol.

BACKGROUND: Hmong men in Minnesota exhibit a high prevalence of gout and hyperuricemia. Although evidence of vitamin C's effectiveness as a treatment for gout is mixed, analysis of therapeutic benefit based on an individual's multiomic signature may identify predictive markers of treatment success. OBJECTIVES: The primary objective of the Hmong Microbiome ANd Gout, Obesity, Vitamin C (HMANGO-C) study was to assess the effectiveness of vitamin C on serum urate in Hmong adults with and without gout/hyperuricemia. The secondary objectives were to assess if 1) vitamin C impacts the taxonomic and functional patterns of microbiota; 2) taxonomic and functional patterns of microbiota impact vitamin C's urate-lowering effects; 3) genetic variations impact vitamin C's urate-lowering effects; 4) differential microbial biomarkers exist for patients with or without gout; and 5) there is an association between obesity, gut microbiota and gout/hyperuricemia. METHODS: This prospective open-labelled clinical trial was guided by community-based participatory research principles and conducted under research safety restrictions for SARS-CoV-2. We aimed to enroll a convenient sample of 180 Hmong adults (120 with gout/hyperuricemia and 60 without gout/hyperuricemia) who provided medical, demographic, dietary and anthropometric information. Participants took vitamin C 500mg twice daily for 8 weeks and provided pre-and post- samples of blood and urine for urate measurements as well as stool samples for gut microbiome. Salivary DNA was also collected for genetic markers relevant to uric acid disposition. EXPECTED RESULTS: We expected to quantify the impact of vitamin C on serum urate in Hmong adults with and without gout/hyperuricemia. The outcome will enhance our understanding of how gut microbiome and genomic variants impact the urate-lowering of vitamin C and associations between obesity, gut microbiota and gout/hyperuricemia. Ultimately, findings may improve our understanding of the causes and potential interventions that could be used to address health disparities in the prevalence and management of gout in this underserved population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04938024 (first posted: 06/24/2021).

PharmVar GeneFocus: SLCO1B1.

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Comparison of the Warfarin Dosing and Outcomes in Hmong Versus East Asians Patients: Real-World Data From an Integrated Healthcare System.

Background Previous research predicted that Hmong, an understudied East Asian subpopulation, might require significantly lower warfarin doses than East Asian patients partially due to their unique genetic and clinical factors. However, such findings have not been corroborated using real-world data. Methods This was a retrospective cohort study of Hmong and East Asian patients receiving warfarin. Warfarin stable doses (WSD) and time to the composite outcome, including international normalized ratio (INR) greater than four incidences or major bleeding within six months of warfarin initiation, were compared. Results This cohort study included 55 Hmong and 100 East Asian patients. Compared to East Asian patients, Hmong had a lower mean WSD (14.5 vs. 20.4 mg/week, p<0.05). In addition, Hmong had a 3.1-fold (95% CI: 1.1-9.3, p<0.05) higher hazard of the composite outcome. Conclusion Using real-world data, significant differences in warfarin dosing and hazard for the composite outcome of INR>4 and major bleeding were observed between Hmong and East Asian patients. These observations further underscore the importance of recognizing subpopulation-based differences in warfarin dosing and outcomes.

The Identification of Novel CYP2D6 Variants in US Hmong: Results From Genome Sequencing and Clinical Genotyping.

Objective: Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic CYP2D6 gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms. Methods: DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms. Results: A total of 13 CYP2D6 alleles were identified. The most common alleles were CYP2D6*10 and its structural arrangements (37.5%, 36/96) and the *5 gene deletion (13.5%, 13/96). Three novel suballeles (*10.007, *36.004, and *75.002) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively. Conclusion: Our study to explore CYP2D6 genotypes in the Hmong population suggests that this subpopulation is unique regarding CYP2D6 allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient's CYP2D6 metabolizer status.

The Clinical Pharmacogenetics Implementation Consortium Guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and Statin-Associated Musculoskeletal Symptoms.

Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

Pharmacogenomic variabilities in geo-ancestral subpopulations and their clinical implications: Results of collaborations with Hmong in the United States.

Underrepresentation of subpopulations within geo-ancestral groups engaged in research can exacerbate health disparities and impair progress toward personalized medicine. This is particularly important when implementing pharmacogenomics which uses genomic-based sources of variability to guide medication selection and dosing. This mini-review focuses on pharmacogenomic findings with Hmong in the United States and their potential clinical implications. By actively engaging Hmong community in pharmacogenomic-based research, several clinically relevant differences in allele frequencies were observed within key pharmacogenes such as CYP2C9 and CYP2C19 in Hmong compared to those in either East Asians or Europeans. Additionally, using state-of-the-art genome sequencing approaches, Hmong appear to possess novel genetic variants within CYP2D6, a critical pharmacogene affecting pharmacokinetics of a broad range of medications. The allele frequency differences and novel alleles in Hmong have translational impact and real-world clinical consequences. For example, Hmong patients exhibited a lower warfarin stable dose requirement compared to East Asian patients. This was predicted based on Hmong's unique genetic and non-genetic factors and confirmed using real-world data from clinical practice settings. By presenting evidence of the genetic uniqueness and its translational impact within subpopulations, such as the Hmong, we hope to inspire greater inclusion of other geo-ancestrally underrepresented subpopulations in pharmacogenomic-based research.

Pharmacogenomics education, research and clinical implementation in the state of Minnesota.

Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.

Gout prevalence in the Hmong: a prime example of health disparity and the role of community-based genetic research.

Individuals of distinct Asian backgrounds are commonly aggregated as Asian, which could mask the differences in the etiology and prevalence of health conditions in the different Asian subgroups. The Hmong are a growing Asian subgroup in the United States with a higher prevalence of gout and gout-related comorbidities than non-Hmong. Genetic explorations in the Hmong suggest a higher prevalence of genetic polymorphisms associated with an increased risk of hyperuricemia and gout. History of immigration, acculturation, lifestyle factors, including dietary and social behavioral patterns, and the use of traditional medicines in the Hmong community may also increase the risk of developing gout and lead to poor gout management outcomes. Engaging minorities such as the Hmong population in biomedical research is a needed step to reduce the burden of health disparities within their respective communities, increase diversity in genomic studies, and accelerate the adoption of precision medicine to clinical practice.

People of different Asian heritage are commonly grouped as Asian, which could mask the differences in the causes and rates of specific health conditions in the different Asian subgroups. The Hmong are a growing Asian group in the United States with higher gout rates and gout-related conditions than non-Hmong. Genetic research in the Hmong suggests higher rates of genetic changes associated with higher urate levels and increased gout risk. The immigration to the United States and adaptation to the Western lifestyle could also affect the Hmong's risk for developing elevated urate levels and gout. Some lifestyle factors, including dietary and social behavioral patterns, and the use of traditional medicines in the Hmong, may also increase their risk of developing gout and lead to poor gout management. Engaging minorities such as the Hmong population in clinical research is a needed step to reduce the burden of health disparities within their respective communities, increase diversity in genetic studies, and widen the application of precision medicine to clinical practice.

Differences in Predicted Warfarin Dosing Requirements Between Hmong and East Asians Using Genotype-Based Dosing Algorithms.

INTRODUCTION: Warfarin's narrow therapeutic index and high variability in dosage requirements make dosage selection critical. Genetic factors are known to impact warfarin dosage selection. The Hmong are a unique Asian subpopulation numbering over 278,000 in the United States whose participation in genetics-based research is virtually nonexistent. The translational significance of early reports of warfarin pharmacogene differences in Hmong has not been evaluated. OBJECTIVES: (i) To validate previously identified allele frequency differences relevant to warfarin dosing in Hmong versus East Asians and (ii) to compare predicted warfarin sensitivity and maintenance doses between a Hmong population and an East Asian cohort. METHOD: DNA collected from two independent cohorts (n=236 and n=198) of Hmong adults were genotyped for CYP2C9 (*2, *3), VKORC1 (G-1639A), and CYP4F2 (*3). Allele frequencies between the combined Hmong cohort (n=433) and East Asians (n=1165) from the 2009 International Warfarin Pharmacogenetics Consortium (IWPC) study were compared using a χ2 test. Percentages of Hmong and East Asian participants predicted to be very sensitive to warfarin were compared using a χ2 test, and the predicted mean warfarin maintenance dose was compared with a t test. RESULTS: The allele frequencies of CYP2C9*3 in the combined Hmong cohort and CYP4F2*3 in the VIP-Hmong cohort are significantly different from those in East Asians (18.9% vs 3.0%, p<0.001 and 9.8% vs 22.1%, p<0.001, respectively). Comparing the combined Hmong cohort to the East Asian cohort, the percentage of participants predicted to be very sensitive to warfarin was significantly higher (28% vs 5%, p<0.01) and the mean predicted warfarin maintenance dose was significantly lower (19.8 vs 21.3 mg/week, p<0.001), respectively. CONCLUSION: The unique allele frequencies related to warfarin when combined with nongenetic factors observed in the Hmong translate into clinically relevant differences in predicted maintenance dose requirements for Hmong versus East Asians.

Randomised clinical study: oral aspirin 325 mg daily vs placebo alters gut microbial composition and bacterial taxa associated with colorectal cancer risk.

BACKGROUND: Aspirin is associated with decreased risk of colorectal cancer (CRC), potentially by modulating the gut microbiome. AIMS: To evaluate the effect of aspirin on the gut microbiome in a double-blinded, randomised placebo-controlled pilot trial. METHODS: Healthy volunteers aged 50-75 received a standard dose of aspirin (325 mg, N = 30) or placebo (N = 20) once daily for 6 weeks and provided stool samples every 3 weeks for 12 weeks. Serial measurements of gut microbial community composition and bacterial abundance were derived from 16S rRNA sequences. Linear discriminant analysis of effect size (LEfSe) was tested for between-arm differences in bacterial abundance. Mixed-effect regression with binomial distribution estimated the effect of aspirin use on changes in the relative abundance of individual bacterial taxa via an interaction term (treatment × time). RESULTS: Over the study period, there were differences in microbial composition in the aspirin vs placebo arm. After treatment, four taxa were differentially abundant across arms: Prevotella, Veillonella, Clostridium XlVa and Clostridium XVIII clusters. Of pre-specified bacteria associated with CRC (n = 8) or aspirin intake (n = 4) in published studies, interactions were significant for four taxa, suggesting relative increases in Akkermansia, Prevotella and Ruminococcaceae and relative decreases in Parabacteroides, Bacteroides and Dorea in the aspirin vs placebo arm. CONCLUSION: Compared to placebo, aspirin intake influenced several microbial taxa (Ruminococcaceae, Clostridium XlVa, Parabacteroides and Dorea) in a direction consistent with a priori hypothesis based on their association with CRC. This suggests that aspirin may influence CRC development through an effect on the gut microbiome. The findings need replication in a larger trial.

Salivary AMY1 Copy Number Variation Modifies Age-Related Type 2 Diabetes Risk.

BACKGROUND: Copy number variation (CNV) in the salivary amylase gene (AMY1) modulates salivary α-amylase levels and is associated with postprandial glycemic traits. Whether AMY1-CNV plays a role in age-mediated change in insulin resistance (IR) is uncertain. METHODS: We measured AMY1-CNV using duplex quantitative real-time polymerase chain reaction in two studies, the Boston Puerto Rican Health Study (BPRHS, n = 749) and the Genetics of Lipid-Lowering Drug and Diet Network study (GOLDN, n = 980), and plasma metabolomic profiles in the BPRHS. We examined the interaction between AMY1-CNV and age by assessing the relationship between age with glycemic traits and type 2 diabetes (T2D) according to high or low copy numbers of the AMY1 gene. Furthermore, we investigated associations between metabolites and interacting effects of AMY1-CNV and age on T2D risk. RESULTS: We found positive associations of IR with age among subjects with low AMY1-copy-numbers in both studies. T2D was marginally correlated with age in participants with low AMY1-copy-numbers but not with high AMY1-copy-numbers in the BPRHS. Metabolic pathway enrichment analysis identified the pentose metabolic pathway based on metabolites that were associated with both IR and the interactions between AMY1-CNV and age. Moreover, in older participants, high AMY1-copy-numbers tended to be associated with lower levels of ribonic acid, erythronic acid, and arabinonic acid, all of which were positively associated with IR. CONCLUSIONS: We found evidence supporting a role of AMY1-CNV in modifying the relationship between age and IR. Individuals with low AMY1-copy-numbers tend to have increased IR with advancing age.