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.

HLA-B*58: 01 carrier status of Hmong in Minnesota: first in Hmong genotyping for prevalence of this biomarker of risk for severe cutaneous adverse reactions caused by allopurinol.

Allopurinol, a common medication to treat gout, is associated with severe cutaneous adverse reactions, and the occurrence is highly predicted by an individual's HLA-B*58:01 carrier status. Guidelines endorse preemptive testing in select Asian populations before initiating allopurinol. The Hmong, an Asian subpopulation originally from China who now live dispersed around the world, have a 2.5-fold higher risk of gout when compared to non-Hmong in Minnesota. Given the concern for severe cutaneous adverse reactions when prescribing allopurinol, we quantified the carrier status of HLA-B*58:01 in Hmong from two independent cohorts in Minnesota. Using a community-based participatory research approach, HLA-B*58:01 carrier status was determined in 49 US-born Hmong without a history of gout or allopurinol use. Further, 47 Hmong patients undergoing clinical evaluation to receive gout pharmacotherapy were also tested. The frequency of HLA-B*58:01 positive carrier status in these two cohorts were compared to published data from a Han Chinese (n = 2910) and a Korean cohort (n = 485) using a Fisher's exact test with a Bonferroni-corrected P-value <0.025 for significance. With one uninterpretable result, we identified two out of 95 people (2.1%) who carried HLA-B*58:01. This 2.1% incidence in these Hmong adults is notably lower than Han Chinese (19.6%, P < 0.0001) and Korean (12.2%, P = 0.0016) populations. Though commonly understood to be of Chinese descent, the lower prevalence within the Hmong underscores the risk of generalizing genotypic findings from Chinese to Asian subpopulations. We suggest no change to the current guidelines recommending which populations should be tested for HLA-B*58:01 before allopurinol use until further validation.

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.

An exome-wide sequencing study of lipid response to high-fat meal and fenofibrate in Caucasians from the GOLDN cohort.

Our understanding of genetic influences on the response of lipids to specific interventions is limited. In this study, we sought to elucidate effects of rare genetic variants on lipid response to a high-fat meal challenge and fenofibrate (FFB) therapy in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) cohort using an exome-wide sequencing-based association study. Our results showed that the rare coding variants in ITGA7, SIPA1L2, and CEP72 are significantly associated with fasting LDL cholesterol response to FFB (P = 1.24E-07), triglyceride postprandial area under the increase (AUI) (P = 2.31E-06), and triglyceride postprandial AUI response to FFB (P = 1.88E-06), respectively. We sought to replicate the association for SIPA1L2 in the Heredity and Phenotype Intervention (HAPI) Heart Study, which included a high-fat meal challenge but not FFB treatment. The associated rare variants in GOLDN were not observed in the HAPI Heart study, and thus the gene-based result was not replicated. For functional validation, we found that gene transcript level of SIPA1L2 is associated with triglyceride postprandial AUI (P < 0.05) in GOLDN. Our study suggests unique genetic mechanisms contributing to the lipid response to the high-fat meal challenge and FFB therapy.

Potential Clinical and Economic Impact of Switching Branded Medications to Generics.

Switching branded to generic medications has become a common cost-containment measure. Although this is an important objective for health care systems worldwide, the impact of this practice on patient outcomes needs to be carefully considered. We reviewed the literature summarizing the potential clinical and economic consequences of switching from branded to generic medications on patient outcomes. A literature search of peer-reviewed articles published 2003-2013 using key words of "generic switching" or "substitution" was conducted using PubMed, OvidSP, and ScienceDirect. Of 30 articles identified and reviewed, most were related to the diseases of the central nervous system, especially epilepsy. Based on our review, potential impacts of switching fell into 3 broad categories: patient attitudes and adherence, clinical and safety outcomes, and cost and resource utilization. Although in many cases generics may represent an appropriate alternative to branded products, this may not always be the case. Specifically, several studies suggested that switching may negatively impact medication adherence, whereas other studies found that generic switching was associated with poorer clinical outcomes and more adverse events. In some instances, switching accomplished cost savings but did so at increased total cost of care because of increased physician visits or hospitalizations. Although in many cases generics may represent an appropriate alternative, mandatory generic switching may lead to unintended consequences, especially in certain therapeutic areas. Although further study is warranted, based on our review, it may be medically justifiable for physicians and patients to retain the right to request the branded product in certain cases.

A genome-wide study of lipid response to fenofibrate in Caucasians: a combined analysis of the GOLDN and ACCORD studies.

BACKGROUND: Fibrates are commonly prescribed for hypertriglyceridemia, but they also lower LDL cholesterol and increase HDL cholesterol. Large interindividual variations in lipid response suggest that some patients may benefit more than others and genetic studies could help identify such patients. METHODS: We carried out the first genome-wide association study of lipid response to fenofibrate using data from two well-characterized clinical trials: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Study. Genome-wide association study data from both studies were imputed to the 1000 Genomes CEU reference panel (phase 1). Lipid response was modeled as the log ratio of the post-treatment lipid level to the pretreatment level. Linear mixed models (GOLDN, N=813 from 173 families) and linear regression models (ACCORD, N=781) adjusted for pretreatment lipid level, demographic variables, clinical covariates, and ancestry were used to evaluate the association of genetic markers with lipid response. Among Caucasians, the results were combined using inverse-variance weighted fixed-effects meta-analyses. The main findings from the meta-analyses were examined in other ethnic groups from the HyperTG study (N=267 Hispanics) and ACCORD (N=83 Hispanics, 138 African Americans). RESULTS: A known lipid locus harboring the pre-B-cell leukemia homeobox 4 (PBX4) gene on chromosome 19 is important for LDL cholesterol response to fenofibrate (smallest P=1.5×10). The main results replicated with nominal statistical significance in Hispanics from ACCORD (P<0.05). CONCLUSION: Future research should evaluate the usefulness of this locus to refine clinical strategies for lipid-lowering treatments.

A family-specific linkage analysis of blood lipid response to fenofibrate in the Genetics of Lipid Lowering Drug and Diet Network.

Cost-effective identification of novel pharmacogenetic variants remains a pressing need in the field. Using data from the Genetics of Lipid Lowering Drugs and Diet Network, we identified genomic regions of relevance to fenofibrate response in a sample of 173 families. Our approach included a multipoint linkage scan, followed by selection of the families showing evidence of linkage. We identified a strong signal for changes in LDL-cholesterol (LDL-C) on chromosome 7 (peak logarithm of odds score = 4.76) in the full sample (n = 821). The signal for LDL-C response remained even after adjusting for baseline LDL-C. Restricting analyses only to the families contributing to the linkage signal for LDL-C (N = 19), we observed a peak logarithm of odds score of 5.17 for chromosome 7. Two genes under this peak (ABCB4 and CD36) were of biological interest. These results suggest that linked family analyses might be a useful approach to gene discovery in the presence of a complex (e.g. multigenic) phenotype.

Genome-wide association studies identified novel loci for non-high-density lipoprotein cholesterol and its postprandial lipemic response.

Non-high-density lipoprotein cholesterol(NHDL) is an independent and superior predictor of CVD risk as compared to low-density lipoprotein alone. It represents a spectrum of atherogenic lipid fractions with possibly a distinct genomic signature. We performed genome-wide association studies (GWAS) to identify loci influencing baseline NHDL and its postprandial lipemic (PPL) response. We carried out GWAS in 4,241 participants of European descent. Our discovery cohort included 928 subjects from the Genetics of Lipid-Lowering Drugs and Diet Network Study. Our replication cohorts included 3,313 subjects from the Heredity and Phenotype Intervention Heart Study and Family Heart Study. A linear mixed model using the kinship matrix was used for association tests. The best association signal was found in a tri-genic region at RHOQ-PIGF-CRIPT for baseline NHDL (lead SNP rs6544903, discovery p = 7e-7, MAF = 2 %; validation p = 6e-4 at 0.1 kb upstream neighboring SNP rs3768725, and 5e-4 at 0.7 kb downstream neighboring SNP rs6733143, MAF = 10 %). The lead and neighboring SNPs were not perfect surrogate proxies to each other (D' = 1, r (2) = 0.003) but they seemed to be partially dependent (likelihood ration test p = 0.04). Other suggestive loci (discovery p < 1e-6) included LOC100419812 and LOC100288337 for baseline NHDL, and LOC100420502 and CDH13 for NHDL PPL response that were not replicated (p > 0.01). The current and first GWAS of NHDL yielded an interesting common variant in RHOQ-PIGF-CRIPT influencing baseline NHDL levels. Another common variant in CDH13 for NHDL response to dietary high-fat intake challenge was also suggested. Further validations for both loci from large independent studies, especially interventional studies, are warranted.

A 16-month community-based intervention to increase aspirin use for primary prevention of cardiovascular disease.

INTRODUCTION: Cardiovascular diseases are the leading causes of disability and death in the United States. Primary prevention of these events may be achieved through aspirin use. The ability of a community-based intervention to increase aspirin use has not been evaluated. The objective of this study was to evaluate an educational intervention implemented to increase aspirin use for primary prevention of cardiovascular disease in a small city in Minnesota. METHODS: A community-based intervention was implemented during 16 months in a medium-sized community in Minnesota. Messages for aspirin use were disseminated to individuals, health care professionals, and the general population. Independent cross-sectional samples of residents (men aged 45-79, women aged 55-79) were surveyed by telephone to identify candidates for primary prevention aspirin use, examine their characteristics, and determine regular aspirin use at baseline and after the campaign at 4 months and 16 months. RESULTS: In primary prevention candidates, regular aspirin use rates increased from 36% at baseline to 54% at 4 months (odds ratio = 2.05; 95% confidence interval, 1.09-3.88); the increase was sustained at 52% at 16 months (odds ratio = 1.89; 95% confidence interval, 1.02-3.49). The difference in aspirin use rates at 4 months and 16 months was not significant (P = .77). CONCLUSION: Aspirin use rates for primary prevention remain low. A combined public health and primary care approach can increase and sustain primary prevention aspirin use in a community setting.

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.

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.

Genetic variants associated with VLDL, LDL and HDL particle size differ with race/ethnicity.

Specific constellations of lipoprotein particle features, reflected as differences in mean lipoprotein particle diameters, are associated with risk of insulin resistance (IR) and cardiovascular disease (CVD). The associations of lipid profiles with disease risk differ by race/ethnicity, the reason for this is not clear. We aimed to examine whether there were additional genetic differences between racial/ethnic groups on lipoprotein profile. Genotypes were assessed using the Affymetrix 6.0 array in 817 related Caucasian participants of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Association analysis was conducted on fasting mean particle diameters using linear models, adjusted for age, sex and study center as fixed effects, and pedigree as a random effect. Replication of associations reaching P < 1.97 × 10(-05) (the level at which we achieved at least 80% power to replicate SNP-phenotype associations) was conducted in the Caucasian population of the Multi-Ethnic Study of Atherosclerosis (MESA; N = 2,430). Variants which replicated across both Caucasian populations were subsequently tested for association in the African-American (N = 1,594), Chinese (N = 758), and Hispanic (N = 1,422) populations of MESA. Variants in the APOB gene region were significantly associated with mean VLDL diameter in GOLDN, and in the Caucasian and Hispanic populations of MESA, while variation in the hepatic lipase (LIPC) gene was associated with mean HDL diameter in both Caucasians populations only. Our findings suggest that the genetic underpinnings of mean lipoprotein diameter differ by race/ethnicity. As lipoprotein diameters are modifiable, this may lead new strategies to modify lipoprotein profiles during the reduction of IR that are sensitive to race/ethnicity.

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.

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.

A genome-wide association study of inflammatory biomarker changes in response to fenofibrate treatment in the Genetics of Lipid Lowering Drug and Diet Network.

OBJECTIVE: Despite the evidence in support of the anti-inflammatory and triglyceride-lowering effects of fenofibrate, little is known about genetic determinants of the observed heterogeneity in treatment response. This study provides the first genome-wide examination of fenofibrate effects on systemic inflammation. METHODS: Biomarkers of inflammation were measured in participants of the Genetics of Lipid Lowering Drugs and Diet Network (n=1092) before and after a 3-week daily treatment with 160 mg of fenofibrate. Two inflammatory patterns [high-sensitivity C-reactive protein-interleukin-6 and monocyte chemoattractant protein-1-tumor necrosis factor (MCP1-TNF-α)] were derived using principal component analysis. Associations between single nucleotide polymorphisms on the Affymetrix 6.0 chip and phenotypes were assessed using mixed linear models, adjusted for age, sex, study center, and ancestry as fixed effects and pedigree as a random effect. RESULTS: Before fenofibrate treatment, the strongest evidence for association was observed for polymorphisms near or within the IL2RA gene with the high-sensitivity C-reactive protein-interleukin-6 (IL6) pattern (rs7911500, P=5×10 and rs12722605, P=5×10). Associations of the MCP1-TNF-α pattern with loci in several biologically plausible genes [CYP4F8 (rs3764563), APBB1IP (rs1775246), COL13A1 (rs2683572), and COMMD10 (rs1396485)] approached genome-wide significance (P=3×10, 5×10, 6×10, and 7×10, respectively) before fenofibrate treatment. After fenofibrate treatment, the rs12722605 locus in IL2RA was also associated with the MCP1-TNF-α pattern (P=3×10). The analyses of individual biomarker response to fenofibrate did not yield genome-wide significant results, but the rs6517147 locus near the immunologically relevant IFNAR2 gene was suggestively associated with IL6 (P=7×10). CONCLUSION: We have identified several novel biologically relevant loci associated with systemic inflammation before and after fenofibrate treatment.

Rare PPARA variants and extreme response to fenofibrate in the Genetics of Lipid-Lowering Drugs and Diet Network Study.

OBJECTIVE: Fenofibrate, a peroxisome proliferator-activated receptor-α (PPARα) agonist, reduces triglyceride (TG) concentrations by 25-60%. Given significant interindividual variations in the TG response, we investigated the association of PPARA rare variants with treatment response in the Genetics of Lipid-Lowering Drugs and Diet Network study. METHODS: We calculated the change in the TG concentration (ΔTG) among 861 GOLDN participants treated with fenofibrate (160 mg/day) for 3 weeks. From the distribution of ΔTG adjusted for age and sex, the 150 highest and 150 lowest fenofibrate responders were selected from the tails of the distribution for PPARA resequencing. The resequencing strategy was based on VariantSEQr technology for the amplification of exons and regulatory regions. RESULTS: We identified 73 variants with an average minor allele frequency of 4.8% (range: 0.2-16%). We tested the association of rare variants located in a coding or a regulatory region (minor allele frequency<1%, 13 variants) with treatment response group by an indicator variable (presence/absence of ≥1 rare variant) using general linear mixed models to allow for adjustment for family relationship. After adjusting for baseline, fasting TG concentration carrying at least one rare variant was associated with a low fenofibrate response (odds ratio=6.46; 95% confidence interval: 1.4-30.8). Carrier status was also associated with a relative change in the total cholesterol concentration (P=0.02), but not high-density lipoprotein or low-density lipoprotein concentration. CONCLUSION: Rare, potentially functional variants in PPARA may play a role in the TG response to fenofibrate, but future experimental studies will be necessary to replicate the findings and confirm functional effects.

Genome-wide association study indicates variants associated with insulin signaling and inflammation mediate lipoprotein responses to fenofibrate.

OBJECTIVE: A shift towards overall larger very low-density lipoprotein (VLDL), and smaller low-density lipoprotein and high-density lipoprotein (HDL) diameters occurs in insulin resistance (IR), which reflects shifts in the distribution of the subfraction concentrations. Fenofibrate, indicated for hypertriglyceridemia, simultaneously reduces IR and shifts in lipoprotein diameter. Individual responses to fenofibrate vary, and we conducted a genome-wide association study to identify genetic differences that could contribute to such differences. METHODS: Association analysis was conducted between single nucleotide polymorphisms (SNPs) on the Affymetrix 6.0 array and fasting particle diameter responses to a 12-week fenofibrate trial, in 817 related Caucasian participants of the Genetics of Lipid Lowering Drugs and Diet Network. Linear models were conducted, which adjusted for age, sex and study center as fixed effects, and pedigree as a random effect. The top three SNPs associated with each fraction were examined subsequently for associations with changes in subfraction concentrations. RESULTS: SNPs in AHCYL2 and CD36 genes reached, or closely approached, genome-wide levels of significance with VLDL and HDL diameter responses to fenofibrate, respectively (P=4×10(-9) and 8×10(-8)). SNPs in AHCYL2 were associated with a decrease in the concentration of the large VLDL subfraction only (P=0.002). SNPs associated with HDL diameter change were not associated with a single subfraction concentration change (P>0.05) indicating small shifts across all subfractions. CONCLUSION: We report novel associations between lipoprotein diameter responses to fenofibrate and the AHCYL2 and CD36 genes. Previous associations of these genes with IR emphasize the role of IR in mediating lipoprotein response to fenofibrate.