The power of genetic diversity in genome-wide association studies of lipids.

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Characterizing genetic profiles for high triglyceride levels in U.S. patients of African ancestry.

Hypertriglyceridemia (HTG) is a common cardiovascular risk factor characterized by elevated triglyceride (TG) levels. Researchers have assessed the genetic factors that influence HTG in studies focused predominantly on individuals of European ancestry. However, relatively little is known about the contribution of genetic variation of HTG in people of African ancestry (AA), potentially constraining research and treatment opportunities. Our objective was to characterize genetic profiles among individuals of AA with mild-to-moderate HTG and severe HTG versus those with normal TGs by leveraging whole-genome sequencing data and longitudinal electronic health records available in the All of Us program. We compared the enrichment of functional variants within five canonical TG metabolism genes, an AA-specific polygenic risk score for TGs, and frequencies of 145 known potentially causal TG variants between HTG patients and normal TG among a cohort of AA patients (N = 15,373). Those with mild-to-moderate HTG (N = 342) and severe HTG (N ≤ 20) were more likely to carry APOA5 p.S19W (odds ratio = 1.94, 95% confidence interval = [1.48-2.54], P = 1.63 × 10-6 and OR = 3.65, 95% confidence interval: [1.22-10.93], P = 0.02, respectively) than those with normal TG. They were also more likely to have an elevated (top 10%) polygenic risk score, elevated carriage of potentially causal variant alleles, and carry any genetic risk factor. Alternative definitions of HTG yielded comparable results. In conclusion, individuals of AA with HTG were enriched for genetic risk factors compared to individuals with normal TGs.

High-throughput framework for genetic analyses of adverse drug reactions using electronic health records.

Understanding the contribution of genetic variation to drug response can improve the delivery of precision medicine. However, genome-wide association studies (GWAS) for drug response are uncommon and are often hindered by small sample sizes. We present a high-throughput framework to efficiently identify eligible patients for genetic studies of adverse drug reactions (ADRs) using "drug allergy" labels from electronic health records (EHRs). As a proof-of-concept, we conducted GWAS for ADRs to 14 common drug/drug groups with 81,739 individuals from Vanderbilt University Medical Center's BioVU DNA Biobank. We identified 7 genetic loci associated with ADRs at P < 5 × 10-8, including known genetic associations such as CYP2D6 and OPRM1 for CYP2D6-metabolized opioid ADR. Additional expression quantitative trait loci and phenome-wide association analyses added evidence to the observed associations. Our high-throughput framework is both scalable and portable, enabling impactful pharmacogenomic research to improve precision medicine.

Correction: A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease.

[This corrects the article DOI: 10.1371/journal.pgen.1008629.].

Deep learning for virtual orthodontic bracket removal: tool establishment and application.

OBJECTIVE: We aimed to develop a tool for virtual orthodontic bracket removal based on deep learning algorithms for feature extraction from bonded teeth and to demonstrate its application in a bracket position assessment scenario. MATERIALS AND METHODS: Our segmentation network for virtual bracket removal was trained using dataset A, containing 978 bonded teeth, 20 original teeth, and 20 brackets generated by scanners. The accuracy and segmentation time of the network were tested by dataset B, which included an additional 118 bonded teeth without knowing the original tooth morphology. This tool was then applied for bracket position assessment. The clinical crown center, bracket center, and orientations of separated teeth and brackets were extracted for analyzing the linear distribution and angular deviation of bonded brackets. RESULTS: This tool performed virtual bracket removal in 2.9 ms per tooth with accuracies of 98.93% and 97.42% (P < 0.01) in datasets A and B, respectively. The tooth surface and bracket characteristics were extracted and used to evaluate the results of manually bonded brackets by 49 orthodontists. Personal preferences for bracket angulation and bracket distribution were displayed graphically and tabularly. CONCLUSIONS: The tool's efficiency and precision are satisfactory, and it can be operated without original tooth data. It can be used to display the bonding deviation in the bracket position assessment scenario. CLINICAL SIGNIFICANCE: With the aid of this tool, unnecessary bracket removal can be avoided when evaluating bracket positions and modifying treatment plans. It has the potential to produce retainers and orthodontic devices prior to tooth debonding.

Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups.

Because polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from mainly European ancestry (EA) cohorts, their validity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear. We investigated associations of "restricted" and genome-wide PRSs with CHD in three major racial and ethnic groups in the U.S. The eMERGE cohort (mean age 48 ± 14 years, 58% female) included 45,645 EA, 7,597 AA, and 2,493 HE individuals. We assessed two restricted PRSs (PRSTikkanen and PRSTada; 28 and 50 variants, respectively) and two genome-wide PRSs (PRSmetaGRS and PRSLDPred; 1.7 M and 6.6 M variants, respectively) derived from EA cohorts. Over a median follow-up of 11.1 years, 2,652 incident CHD events occurred. Hazard and odds ratios for the association of PRSs with CHD were similar in EA and HE cohorts but lower in AA cohorts. Genome-wide PRSs were more strongly associated with CHD than restricted PRSs were. PRSmetaGRS, the best performing PRS, was associated with CHD in all three cohorts; hazard ratios (95% CI) per 1 SD increase were 1.53 (1.46-1.60), 1.53 (1.23-1.90), and 1.27 (1.13-1.43) for incident CHD in EA, HE, and AA individuals, respectively. The hazard ratios were comparable in the EA and HE cohorts (pinteraction = 0.77) but were significantly attenuated in AA individuals (pinteraction= 2.9 × 10-3). These results highlight the potential clinical utility of PRSs for CHD as well as the need to assemble diverse cohorts to generate ancestry- and ethnicity PRSs.

Race, Genotype, and Azathioprine Discontinuation : A Cohort Study.

BACKGROUND: Thiopurines are an important class of immunosuppressants despite their risk for hematopoietic toxicity and narrow therapeutic indices. Benign neutropenia related to an ACKR1 variant (rs2814778-CC) is common among persons of African ancestries. OBJECTIVE: To test whether rs2814778-CC was associated with azathioprine discontinuation attributed to hematopoietic toxicity and lower thiopurine dosing. DESIGN: Retrospective cohort study. SETTING: Two tertiary care centers. PATIENTS: Thiopurine users with White or Black race. MEASUREMENTS: Azathioprine discontinuation attributed to hematopoietic toxicity. Secondary outcomes included weight-adjusted final dose, leukocyte count, and change in leukocyte count. RESULTS: The rate of azathioprine discontinuation attributed to hematopoietic toxicity was 3.92 per 100 person-years among patients with the CC genotype (n = 101) and 1.34 per 100 person-years among those with the TT or TC genotype (n = 1365) (hazard ratio [HR] from competing-risk model, 2.92 [95% CI, 1.57 to 5.41]). The risk remained significant after adjustment for race (HR, 2.61 [CI, 1.01 to 6.71]). The risk associated with race alone (HR, 2.13 [CI, 1.21 to 3.75]) was abrogated by adjustment for genotype (HR, 1.13 [CI, 0.48 to 2.69]). Lower last leukocyte count and lower dosing were significant among patients with the CC genotype. Lower dosing was validated in an external cohort of 94 children of African ancestries prescribed the thiopurine 6-mercaptopurine (6-MP) for acute lymphoblastic leukemia. The CC genotype was independently associated with lower 6-MP dose intensity relative to the target daily dose of 75 mg/m2 (median, 0.83 [IQR, 0.70 to 0.94] for the CC genotype vs. 0.94 [IQR, 0.72 to 1.13] for the TT or TC genotype; P = 0.013). LIMITATIONS: Unmeasured confounding; data limited to tertiary centers. CONCLUSION: Patients with the CC genotype had higher risk for azathioprine discontinuation attributed to hematopoietic toxicity and lower thiopurine doses. Genotype was associated with those risks, even after adjustment for race. PRIMARY FUNDING SOURCE: National Institutes of Health.

A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease.

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10-11). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10-43), alkaline phosphatase (-0.025 SD, 1.2*10-37), total cholesterol (-0.030 SD, p = 1.9*10-36) and LDL cholesterol (-0.027 SD, p = 5.1*10-30) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis.

Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.

Loci identified by a genome-wide association study of carotid artery stenosis in the eMERGE network.

Carotid artery atherosclerotic disease (CAAD) is a risk factor for stroke. We used a genome-wide association (GWAS) approach to discover genetic variants associated with CAAD in participants in the electronic Medical Records and Genomics (eMERGE) Network. We identified adult CAAD cases with unilateral or bilateral carotid artery stenosis and controls without evidence of stenosis from electronic health records at eight eMERGE sites. We performed GWAS with a model adjusting for age, sex, study site, and genetic principal components of ancestry. In eMERGE we found 1793 CAAD cases and 17,958 controls. Two loci reached genome-wide significance, on chr6 in LPA (rs10455872, odds ratio [OR] (95% confidence interval [CI]) = 1.50 (1.30-1.73), p = 2.1 × 10-8 ) and on chr7, an intergenic single nucleotide variant (SNV; rs6952610, OR (95% CI) = 1.25 (1.16-1.36), p = 4.3 × 10-8 ). The chr7 association remained significant in the presence of the LPA SNV as a covariate. The LPA SNV was also associated with coronary heart disease (CHD; 4199 cases and 11,679 controls) in this study (OR (95% CI) = 1.27 (1.13-1.43), p = 5 × 10-5 ) but the chr7 SNV was not (OR (95% CI) = 1.03 (0.97-1.09), p = .37). Both variants replicated in UK Biobank. Elevated lipoprotein(a) concentrations ([Lp(a)]) and LPA variants associated with elevated [Lp(a)] have previously been associated with CAAD and CHD, including rs10455872. With electronic health record phenotypes in eMERGE and UKB, we replicated a previously known association and identified a novel locus associated with CAAD.

Genome-wide association analyses of common infections in a large practice-based biobank.

INTRODUCTION: Infectious diseases are common causes of morbidity and mortality worldwide. Susceptibility to infection is highly heritable; however, little has been done to identify the genetic determinants underlying common infectious diseases. One GWAS was performed using 23andMe information about self-reported infections; we set out to confirm previous loci and identify new ones using medically diagnosed infections. METHODS: We used the electronic health record (EHR)-based biobank at Vanderbilt and diagnosis codes to identify cases of 12 infectious diseases in white patients: urinary tract infection, pneumonia, chronic sinus infections, otitis media, candidiasis, streptococcal pharyngitis, herpes zoster, herpes labialis, hepatitis B, infectious mononucleosis, tuberculosis (TB) or a positive TB test, and hepatitis C. We selected controls from patients with no diagnosis code for the candidate disease and matched by year of birth, sex, and calendar year at first and last EHR visits. We conducted GWAS using SAIGE and transcriptome-wide analysis (TWAS) using S-PrediXcan. We also conducted phenome-wide association study to understand associations between identified genetic variants and clinical phenotypes. RESULTS: We replicated three 23andMe loci (p ≤ 0.05): herpes zoster and rs7047299-A (p = 2.6 × 10-3) and rs2808290-C (p = 9.6 × 10-3;); otitis media and rs114947103-C (p = 0.04). We also identified 2 novel regions (p ≤ 5 × 10-8): rs113235453-G for otitis media (p = 3.04 × 10-8), and rs10422015-T for candidiasis (p = 3.11 × 10-8). In TWAS, four gene-disease associations were significant: SLC30A9 for otitis media (p = 8.06 × 10-7); LRP3 and WDR88 for candidiasis (p = 3.91 × 10-7 and p = 1.95 × 10-6); and AAMDC for hepatitis B (p = 1.51 × 10-6). CONCLUSION: We conducted GWAS and TWAS for 12 infectious diseases and identified novel genetic contributors to the susceptibility of infectious diseases.

Association of Genetic Variation With Cirrhosis: A Multi-Trait Genome-Wide Association and Gene-Environment Interaction Study.

BACKGROUND & AIMS: In contrast to most other common diseases, few genetic variants have been identified that impact risk of cirrhosis. We aimed to identify new genetic variants that predispose to cirrhosis, to test whether such variants, aggregated into a polygenic score, enable genomic risk stratification, and to test whether alcohol intake or body mass index interacts with polygenic predisposition. METHODS: We conducted a multi-trait genome-wide association study combining cirrhosis and alanine aminotransferase levels performed in 5 discovery studies (UK Biobank, Vanderbilt BioVU, Atherosclerosis Risk in Communities study, and 2 case-control studies including 4829 individuals with cirrhosis and 72,705 controls and 362,539 individuals with alanine aminotransferase levels). Identified variants were replicated in 3 studies (Partners HealthCare Biobank, FinnGen, and Biobank Japan including 3554 individuals with cirrhosis and 343,826 controls). A polygenic score was tested in Partners HealthCare Biobank. RESULTS: Five previously reported and 7 newly identified genetic variants were associated with cirrhosis in both the discovery studies multi-trait genome-wide association study (P < 5 × 10-8) and the replication studies (P < .05), including a missense variant in the APOE gene and a noncoding variant near EFN1A. These 12 variants were used to generate a polygenic score. Among Partners HealthCare Biobank individuals, high polygenic score-defined as the top quintile of the distribution-was associated with significantly increased risk of cirrhosis (odds ratio, 2.26; P < .001) and related comorbidities compared with the lowest quintile. Risk was even more pronounced among those with extreme polygenic risk (top 1% of the distribution, odds ratio, 3.16; P < .001). The impact of extreme polygenic risk was substantially more pronounced in those with elevated alcohol consumption or body mass index. Modeled as risk by age 75 years, probability of cirrhosis with extreme polygenic risk was 13.7%, 20.1%, and 48.2% among individuals with no or modest, moderate, and increased alcohol consumption, respectively (Pinteraction < .001). Similarly, probability among those with extreme polygenic risk was 6.5%, 10.3%, and 19.5% among individuals with normal weight, overweight, and obesity, respectively (Pinteraction < .001). CONCLUSIONS: Twelve independent genetic variants, 7 of which are newly identified in this study, conferred risk for cirrhosis. Aggregated into a polygenic score, these variants identified a subset of the population at substantially increased risk who are most susceptible to the hepatotoxic effects of excess alcohol consumption or obesity.

Pleiotropy of systemic lupus erythematosus risk alleles and cardiometabolic disorders: A phenome-wide association study and inverse-variance weighted meta-analysis.

OBJECTIVES: To test the hypothesis that genetic predisposition to systemic lupus erythematosus (SLE) increases the risk of cardiometabolic disorders. METHODS: Using 41 single nucleotide polymorphisms (SNPs) associated with SLE, we calculated a weighted genetic risk score (wGRS) for SLE. In a large biobank we tested the association between this wGRS and 9 cardiometabolic phenotypes previously associated with SLE: atrial fibrillation, ischemic stroke, coronary artery disease, type 1 and type 2 diabetes, obesity, chronic kidney disease, hypertension, and hypercholesterolemia. Additionally, we performed a phenome-wide association analysis (pheWAS) to discover novel clinical associations with a genetic predisposition to SLE. Findings were replicated in the Electronic Medical Records and Genomics (eMERGE) Network. To further define the association between SLE-related risk alleles and the selected cardiometabolic phenotypes, we performed an inverse variance weighted regression (IVWR) meta-analysis. RESULTS: The wGRS for SLE was calculated in 74,759 individuals of European ancestry. Among the pre-selected phenotypes, the wGRS was significantly associated with type 1 diabetes (OR [95%CI] =1.11 [1.06, 1.17], P-value = 1.05x10-5). In the PheWAS, the wGRS was associated with several autoimmune phenotypes, kidney disorders, and skin neoplasm; but only the associations with autoimmune phenotypes were replicated. In the IVWR meta-analysis, SLE-related risk alleles were nominally associated with type 1 diabetes (P = 0.048) but the associations were heterogeneous and did not meet the adjusted significance threshold. CONCLUSION: A weighted GRS for SLE was associated with an increased risk of several autoimmune-related phenotypes including type I diabetes but not with cardiometabolic disorders.

ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes.

OBJECTIVE: Identifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) - that systematically scans a disease's clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic. METHODS: We created a natural language processing pipeline to extract concepts from clinical notes in a local ER corresponding to the PCR testing date for patients who had a COVID-19 test and evaluated these concepts as predictors for developing COVID-19. We identified predictors from Firth's logistic regression adjusted by age, gender, and race. We also performed ConceptWAS using cumulative data every two weeks to identify the timeline for recognition of early COVID-19-specific symptoms. RESULTS: We processed 87,753 notes from 19,692 patients subjected to COVID-19 PCR testing between March 8, 2020, and May 27, 2020 (1,483 COVID-19-positive). We found 68 concepts significantly associated with a positive COVID-19 test. We identified symptoms associated with increasing risk of COVID-19, including "anosmia" (odds ratio [OR] = 4.97, 95% confidence interval [CI] = 3.21-7.50), "fever" (OR = 1.43, 95% CI = 1.28-1.59), "cough with fever" (OR = 2.29, 95% CI = 1.75-2.96), and "ageusia" (OR = 5.18, 95% CI = 3.02-8.58). Using ConceptWAS, we were able to detect loss of smell and loss of taste three weeks prior to their inclusion as symptoms of the disease by the Centers for Disease Control and Prevention (CDC). CONCLUSION: ConceptWAS, a high-throughput approach for exploring specific symptoms and characteristics of a disease like COVID-19, offers a promise for enabling EHR-powered early disease manifestations identification.

A retrospective approach to evaluating potential adverse outcomes associated with delay of procedures for cardiovascular and cancer-related diagnoses in the context of COVID-19.

OBJECTIVE: During the COVID-19 pandemic, health systems postponed non-essential medical procedures to accommodate surge of critically-ill patients. The long-term consequences of delaying procedures in response to COVID-19 remains unknown. We developed a high-throughput approach to understand the impact of delaying procedures on patient health outcomes using electronic health record (EHR) data. MATERIALS AND METHODS: We used EHR data from Vanderbilt University Medical Center's (VUMC) Research and Synthetic Derivatives. Elective procedures and non-urgent visits were suspended at VUMC between March 18, 2020 and April 24, 2020. Surgical procedure data from this period were compared to a similar timeframe in 2019. Potential adverse impact of delay in cardiovascular and cancer-related procedures was evaluated using EHR data collected from January 1, 1993 to March 17, 2020. For surgical procedure delay, outcomes included length of hospitalization (days), mortality during hospitalization, and readmission within six months. For screening procedure delay, outcomes included 5-year survival and cancer stage at diagnosis. RESULTS: We identified 416 surgical procedures that were negatively impacted during the COVID-19 pandemic compared to the same timeframe in 2019. Using retrospective data, we found 27 significant associations between procedure delay and adverse patient outcomes. Clinician review indicated that 88.9% of the significant associations were plausible and potentially clinically significant. Analytic pipelines for this study are available online. CONCLUSION: Our approach enables health systems to identify medical procedures affected by the COVID-19 pandemic and evaluate the effect of delay, enabling them to communicate effectively with patients and prioritize rescheduling to minimize adverse patient outcomes.

Use of Genetic Variants Related to Antihypertensive Drugs to Inform on Efficacy and Side Effects.

BACKGROUND: Drug effects can be investigated through natural variation in the genes for their protein targets. The present study aimed to use this approach to explore the potential side effects and repurposing potential of antihypertensive drugs, which are among the most commonly used medications worldwide. METHODS: Genetic proxies for the effect of antihypertensive drug classes were identified as variants in the genes for the corresponding targets that associated with systolic blood pressure at genome-wide significance. Mendelian randomization estimates for drug effects on coronary heart disease and stroke risk were compared with randomized, controlled trial results. A phenome-wide association study in the UK Biobank was performed to identify potential side effects and repurposing opportunities, with findings investigated in the Vanderbilt University biobank (BioVU) and in observational analysis of the UK Biobank. RESULTS: Suitable genetic proxies for angiotensin-converting enzyme inhibitors, ß-blockers, and calcium channel blockers (CCBs) were identified. Mendelian randomization estimates for their effect on coronary heart disease and stroke risk, respectively, were comparable to results from randomized, controlled trials against placebo. A phenome-wide association study in the UK Biobank identified an association of the CCB standardized genetic risk score with increased risk of diverticulosis (odds ratio, 1.02 per standard deviation increase; 95% CI, 1.01-1.04), with a consistent estimate found in BioVU (odds ratio, 1.01; 95% CI, 1.00-1.02). Cox regression analysis of drug use in the UK Biobank suggested that this association was specific to nondihydropyridine CCBs (hazard ratio 1.49 considering thiazide diuretic agents as a comparator; 95% CI, 1.04-2.14) but not dihydropyridine CCBs (hazard ratio, 1.04; 95% CI, 0.83-1.32). CONCLUSIONS: Genetic variants can be used to explore the efficacy and side effects of antihypertensive medications. The identified potential effect of nondihydropyridine CCBs on diverticulosis risk could have clinical implications and warrants further investigation.

Phenome-wide association analysis suggests the APOL1 linked disease spectrum primarily drives kidney-specific pathways.

The relationship between commonly occurring genetic variants (G1 and G2) in the APOL1 gene in African Americans and different disease traits, such as kidney disease, cardiovascular disease, and pre-eclampsia, remains the subject of controversy. Here we took a genotype-first approach, a phenome-wide association study, to define the spectrum of phenotypes associated with APOL1 high-risk variants in 1,837 African American participants of Penn Medicine Biobank and 4,742 African American participants of Vanderbilt BioVU. In the Penn Medicine Biobank, outpatient creatinine measurement-based estimated glomerular filtration rate and multivariable regression models were used to evaluate the association between high-risk APOL1 status and renal outcomes. In meta-analysis of both cohorts, the strongest phenome-wide association study associations were for the high-risk APOL1 variants and diagnoses codes were highly significant for "kidney dialysis" (odds ratio 3.75) and "end stage kidney disease" (odds ratio 3.42). A number of phenotypes were associated with APOL1 high-risk genotypes in an analysis adjusted only for demographic variables. However, no associations were detected with non-renal phenotypes after controlling for chronic/end stage kidney disease status. Using calculated estimated glomerular filtration rate -based phenotype analysis in the Penn Medicine Biobank, APOL1 high-risk status was associated with prevalent chronic/end stage kidney disease /kidney transplant (odds ratio 2.27, 95% confidence interval 1.67-3.08). In high-risk participants, the estimated glomerular filtration rate was 15.4 mL/min/1.73m2; significantly lower than in low-risk participants. Thus, although APOL1 high-risk variants are associated with a range of phenotypes, the risks for other associated phenotypes appear much lower and in our dataset are driven by a primary effect on renal disease.

Combining clinical and candidate gene data into a risk score for azathioprine-associated leukopenia in routine clinical practice.

Leukopenia is a serious, frequent side effect associated with azathioprine use. Currently, we use thiopurine methyltransferase (TPMT) testing to predict leukopenia in patients taking azathioprine. We hypothesized that a risk score incorporating additional clinical and genetic variables would improve the prediction of azathioprine-associated leukopenia. In the discovery phase, we developed four risk score models: (1) age, sex, and TPMT metabolizer status; (2) model 1 plus additional clinical variables; (3) sixty candidate single nucleotide polymorphisms; and (4) model 2 plus model 3. The area under the receiver-operating-characteristic curve (AUC) of the risk scores was 0.59 (95% CI: 0.54-0.64), 0.75 (0.71-0.80), 0.66 (0.61-0.71), and 0.78 (0.74-0.82) for models 1, 2, 3, and 4, respectively. During the replication phase, models 2 and 4 (AUC = 0.64, 95% CI: 0.59-0.70 and AUC = 0.63, 95% CI: 0.58-0.69, respectively) were significant in an independent group. Compared with TPMT testing alone, additional genetic and clinical variables improve the prediction of azathioprine-associated leukopenia.