R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment

A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.

Association of Thyroid Function Genetic Predictors With Atrial Fibrillation: A Phenome-Wide Association Study and Inverse-Variance Weighted Average Meta-analysis

Importance

Thyroid hormone levels are tightly regulated through feedback inhibition by thyrotropin, produced by the pituitary gland. Hyperthyroidism is overwhelmingly due to thyroid disorders and is well recognized to contribute to a wide spectrum of cardiovascular morbidity, particularly the increasingly common arrhythmia atrial fibrillation (AF).

Objective

To determine the association between genetically determined thyrotropin levels and AF.

Design, Setting, and Participants

This phenome-wide association study scanned 1318 phenotypes associated with a polygenic predictor of thyrotropin levels identified by a previously published genome-wide association study that included participants of European ancestry. North American individuals of European ancestry with longitudinal electronic health records were analyzed from May 2008 to November 2016. Analysis began March 2018.

Main Outcomes and Measures

Clinical diagnoses associated with a polygenic predictor of thyrotropin levels.

Exposures

Genetically determined thyrotropin levels.

Results

Of 37 154 individuals, 19 330 (52%) were men. The thyrotropin polygenic predictor was positively associated with hypothyroidism (odds ratio [OR], 1.10; 95% CI, 1.07-1.14; P = 5 × 10-11) and inversely associated with diagnoses related to hyperthyroidism (OR, 0.64; 95% CI, 0.54-0.74; P = 2 × 10-8 for toxic multinodular goiter). Among nonthyroid associations, the top association was AF/flutter (OR, 0.93; 95% CI, 0.9-0.95; P = 9 × 10-7). When the analyses were repeated excluding 9801 individuals with any diagnoses of a thyroid-related disease, the AF association persisted (OR, 0.91; 95% CI, 0.88-0.95; P = 2.9 × 10-6). To replicate this association, we conducted an inverse-variance weighted average meta-analysis using AF single-nucleotide variant weights from a genome-wide association study of 17 931 AF cases and 115 142 controls. As in the discovery analyses, each SD increase in predicted thyrotropin was associated with a decreased risk of AF (OR, 0.86; 95% CI, 0.79-0.93; P = 4.7 × 10-4). In a set of AF cases (n = 745) and controls (n = 1680) older than 55 years, directly measured thyrotropin levels that fell within the normal range were inversely associated with AF risk (OR, 0.91; 95% CI, 0.83-0.99; P = .04).

Conclusions and Relevance

This study suggests a role for genetically determined variation in thyroid function within a physiologically accepted normal range as a risk factor for AF. The clinical decision to treat subclinical thyroid disease should incorporate the risk for AF as antithyroid medications to treat hyperthyroidism may reduce AF risk and thyroid hormone replacement for hypothyroidism may increase AF risk.

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization

BACKGROUND

The extent to which obesity and genetics determine postoperative complications is incompletely understood.

METHODS

We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components.

RESULTS

Individuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10-20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10-5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10-6) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10-6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures.

CONCLUSIONS

Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.

PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies

Objective

Standard approaches for large scale phenotypic screens using electronic health record (EHR) data apply thresholds, such as ≥2 diagnosis codes, to define subjects as having a phenotype. However, the variation in the accuracy of diagnosis codes can impair the power of such screens. Our objective was to develop and evaluate an approach which converts diagnosis codes into a probability of a phenotype (PheProb). We hypothesized that this alternate approach for defining phenotypes would improve power for genetic association studies.

Methods

The PheProb approach employs unsupervised clustering to separate patients into 2 groups based on diagnosis codes. Subjects are assigned a probability of having the phenotype based on the number of diagnosis codes. This approach was developed using simulated EHR data and tested in a real world EHR cohort. In the latter, we tested the association between low density lipoprotein cholesterol (LDL-C) genetic risk alleles known for association with hyperlipidemia and hyperlipidemia codes (ICD-9 272.x). PheProb and thresholding approaches were compared.

Results

Among n = 1462 subjects in the real world EHR cohort, the threshold-based p-values for association between the genetic risk score (GRS) and hyperlipidemia were 0.126 (≥1 code), 0.123 (≥2 codes), and 0.142 (≥3 codes). The PheProb approach produced the expected significant association between the GRS and hyperlipidemia: p = .001.

Conclusions

PheProb improves statistical power for association studies relative to standard thresholding approaches by leveraging information about the phenotype in the billing code counts. The PheProb approach has direct applications where efficient approaches are required, such as in Phenome-Wide Association Studies.

Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation

BACKGROUND

The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR).

OBJECTIVE

The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes.

METHODS

We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS.

RESULTS

We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]).

CONCLUSIONS

This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Health effects associated with serum calcium concentrations: evidence from MR-PheWAS analysis in UK Biobank

We conducted a phenome-wide Mendelian randomization analysis (MR-PheWAS) to survey health effects associated with high normal serum calcium. We found causal evidence for conditions related to renal function, bone and joint health, and cardiovascular risk. These conditions collectively suggest that tissue calcification may be a key mechanism through which serum calcium influences health.

INTRODUCTION

Calcium is essential for the normal functioning of the cardiovascular system, muscles, and nerves. In this MR-PheWAS study, we sought to capture the totality of health effects associated with high normal serum calcium.

METHODS

We used data from up to 337,535 UK Biobank participants, and tested for associations between calcium genetic score (calcium-GS) and 925 disease outcomes, with follow-up analyses using complementary MR methods.

RESULTS

Calcium-GS was robustly associated with serum calcium concentration (F statistics = 349). After multiple testing correction (P < 1.62E-4), we saw genetic evidence for an association between high serum calcium and urinary calculus (OR per 1 mg/dl 3.5, 95%CI 1.3-9.2), renal colic (9.1, 95%CI 2.5-33.5), and allergy/adverse effect of penicillin (2.2, 95%CI 1.5-3.3). Secondary analyses with independent replication from consortia meta-analyses suggested further effects on myocardial infarction and osteoarthrosis.

CONCLUSION

We found causal evidence for effects of high normal serum calcium with conditions related to renal function, bone and joint health, and cardiovascular risk, which may collectively reflect influences on tissue calcification and immune function.

Phenome-wide Mendelian-randomization study of genetically determined vitamin D on multiple health outcomes using the UK Biobank study

BACKGROUND

Vitamin D deficiency is highly prevalent across the globe. Existing studies suggest that a low vitamin D level is associated with more than 130 outcomes. Exploring the causal role of vitamin D in health outcomes could support or question vitamin D supplementation.

METHODS

We carried out a systematic literature review of previous Mendelian-randomization studies on vitamin D. We then implemented a Mendelian Randomization-Phenome Wide Association Study (MR-PheWAS) analysis on data from 339 256 individuals of White British origin from UK Biobank. We first ran a PheWAS analysis to test the associations between a 25(OH)D polygenic risk score and 920 disease outcomes, and then nine phenotypes (i.e. systolic blood pressure, diastolic blood pressure, risk of hypertension, T2D, ischaemic heart disease, body mass index, depression, non-vertebral fracture and all-cause mortality) that met the pre-defined inclusion criteria for further analysis were examined by multiple MR analytical approaches to explore causality.

RESULTS

The PheWAS analysis did not identify any health outcome associated with the 25(OH)D polygenic risk score. Although a selection of nine outcomes were reported in previous Mendelian-randomization studies or umbrella reviews to be associated with vitamin D, our MR analysis, with substantial study power (>80% power to detect an association with an odds ratio >1.2 for per standard deviation increase of log-transformed 25[OH]D), was unable to support an interpretation of causal association.

CONCLUSIONS

We investigated the putative causal effects of vitamin D on multiple health outcomes in a White population. We did not support a causal effect on any of the disease outcomes tested. However, we cannot exclude small causal effects or effects on outcomes that we did not have enough power to explore due to the small number of cases.

Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems

OBJECTIVE

Individuals at high risk for schizophrenia may benefit from early intervention, but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts. The authors sought to test the utility of this approach in clinical settings and to evaluate the broader health consequences of high genetic risk for schizophrenia.

METHODS

The authors used electronic health records for 106,160 patients from four health care systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1,359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.

RESULTS

PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS, 1.55; 95% CI=1.4, 1.7), and patients in the highest risk decile of the PRS distribution had up to 4.6-fold higher odds of schizophrenia compared with those in the bottom decile (95% CI=2.9, 7.3). PRSs were also positively associated with other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.

CONCLUSIONS

The study demonstrates that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in health care settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. The results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in health care systems.

Evaluating statistical approaches to leverage large clinical datasets for uncovering therapeutic and adverse medication effects

Motivation

Phenome-wide association studies (PheWAS) have been used to discover many genotype-phenotype relationships and have the potential to identify therapeutic and adverse drug outcomes using longitudinal data within electronic health records (EHRs). However, the statistical methods for PheWAS applied to longitudinal EHR medication data have not been established.

Results

In this study, we developed methods to address two challenges faced with reuse of EHR for this purpose: confounding by indication, and low exposure and event rates. We used Monte Carlo simulation to assess propensity score (PS) methods, focusing on two of the most commonly used methods, PS matching and PS adjustment, to address confounding by indication. We also compared two logistic regression approaches (the default of Wald versus Firth's penalized maximum likelihood, PML) to address complete separation due to sparse data with low exposure and event rates. PS adjustment resulted in greater power than PS matching, while controlling Type I error at 0.05. The PML method provided reasonable P-values, even in cases with complete separation, with well controlled Type I error rates. Using PS adjustment and the PML method, we identify novel latent drug effects in pediatric patients exposed to two common antibiotic drugs, ampicillin and gentamicin.

Availability and implementation

R packages PheWAS and EHR are available at https://github.com/PheWAS/PheWAS and at CRAN (https://www.r-project.org/), respectively. The R script for data processing and the main analysis is available at https://github.com/choileena/EHR.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Genetic Approach to the Association Between PCSK9 and Sepsis

IMPORTANCE

Whether the PCSK9 gene is associated with the progress from infection to sepsis is unknown to date.

OBJECTIVE

To test the associations between PCSK9 genetic variants, a PCSK9 genetic risk score (GRS), or genetically estimated PCSK9 expression levels and the risk of sepsis among patients admitted to a hospital with infection.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used deidentified electronic health records to identify patients admitted to Vanderbilt University Medical Center, Nashville, Tennessee, with infection. Patients were white adults, had a code indicating infection from the International Classification of Diseases, Ninth Revision, Clinical Modification, or the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification, and received an antibiotic within 1 day of hospital admission (N = 61 502). Data were collected from January 1, 1993, through December 31, 2017, and analyzed from April 1, 2018, to March 16, 2019.

EXPOSURES

Four known PCSK9 functional variants, a GRS for PCSK9, and genetically estimated PCSK9 expression.

MAIN OUTCOMES AND MEASURES

The primary outcome was sepsis; secondary outcomes included cardiovascular failure and in-hospital death.

RESULTS

Of patients with infection, genotype information was available in 10 922 white patients for PCSK9 functional variants (5628 men [51.5%]; mean [SD] age, 60.1 [15.7] years), including 7624 patients with PCSK9 GRS and 6033 patients with estimated PCSK9 expression. Of these, 3391 developed sepsis, 835 developed cardiovascular failure, and 366 died during hospitalization. None of the 4 functional PCSK9 variants were significantly associated with sepsis, cardiovascular failure, or in-hospital death, with or without adjustment for (1) age and sex or (2) age, sex, and Charlson-Deyo comorbidities (in model adjusted for age, sex, and comorbidities, odds ratios for any loss-of function variant were 0.96 [95% CI, 0.88-1.04] for sepsis, 1.05 [95% CI, 0.90-1.22] for cardiovascular failure, and 0.89 [95% CI, 0.72-1.11] for death). Similarly, neither the PCSK9 GRS nor genetically estimated PCSK9 expression were significantly associated with sepsis, cardiovascular failure, or in-hospital death in any of the analysis models. For GRS, in the full model adjusted for age, sex, and comorbidities, the odds ratios were 1.01 for sepsis (95% CI, 0.96-1.06; P = .70), 1.03 for cardiovascular failure (95% CI, 0.95-1.12; P = .48), and 1.05 for in-hospital death (95% CI, 0.92-1.19; P = .50). For genetically estimated PCSK9 expression, in the full model adjusted for age, sex, and comorbidities, the odds ratios were 1.01 for sepsis (95% CI, 0.95-1.06; P = .86), 0.96 for cardiovascular failure (95% CI, 0.88-1.05; P = .41), and 0.99 for in-hospital death (95% CI, 0.87-1.14; P = .94).

CONCLUSIONS AND RELEVANCE

In this study, PCSK9 genetic variants were not significantly associated with risk of sepsis or the outcomes of sepsis in patients hospitalized with infection.

A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes

PURPOSE

"Genome-first" approaches, in which genetic sequencing is agnostically linked to associated phenotypes, can enhance our understanding of rare variants' contributions to disease. Loss-of-function variants in LMNA cause a range of rare diseases, including cardiomyopathy.

METHODS

We leveraged exome sequencing from 11,451 unselected individuals in the Penn Medicine Biobank to associate rare variants in LMNA with diverse electronic health record (EHR)-derived phenotypes. We used Rare Exome Variant Ensemble Learner (REVEL) to annotate rare missense variants, clustered predicted deleterious and loss-of-function variants into a "gene burden" (N = 72 individuals), and performed a phenome-wide association study (PheWAS). Major findings were replicated in DiscovEHR.

RESULTS

The LMNA gene burden was significantly associated with primary cardiomyopathy (p = 1.78E-11) and cardiac conduction disorders (p = 5.27E-07). Most patients had not been clinically diagnosed with LMNA cardiomyopathy. We also noted an association with chronic kidney disease (p = 1.13E-06). Regression analyses on echocardiography and serum labs revealed that LMNA variant carriers had dilated cardiomyopathy and primary renal disease.

CONCLUSION

Pathogenic LMNA variants are an underdiagnosed cause of cardiomyopathy. We also find that LMNA loss of function may be a primary cause of renal disease. Finally, we show the value of aggregating rare, annotated variants into a gene burden and using PheWAS to identify novel ontologies for pleiotropic human genes.

Operative vs Nonoperative Treatment for Atraumatic Rotator Cuff Tears: A Trial Protocol for the Arthroscopic Rotator Cuff Pragmatic Randomized Clinical Trial

IMPORTANCE

Rotator cuff disorders remain the most common cause of shoulder pain and are among the most common reasons for patients to seek care in primary and specialty settings. Although operative and nonoperative treatments are offered to patients with atraumatic rotator cuff tears, there is a lack of evidence to support operative vs nonoperative treatment. This paucity of evidence has been highlighted by several professional agencies and experts.

OBJECTIVE

To perform a pragmatic randomized clinical trial, the Arthroscopic Rotator Cuff trial, comparing pain and functional outcomes in patients undergoing operative vs nonoperative treatment for atraumatic rotator cuff tears, and assessing heterogeneity of treatment effects by age and tear size.

DESIGN, SETTING, AND PARTICIPANTS

Trial protocol of the Arthroscopic Rotator Cuff trial. This pragmatic randomized clinical trial of an estimated 700 patients is adequately powered to accomplish its aims with 488 patients. Primary analysis will be conducted on an intent-to-treat population in the context of a mixed model. The multicenter trial started recruitment in 2018 with a 1-year follow-up duration. Patients aged 50 years or older to younger than 85 years with magnetic resonance imaging-confirmed atraumatic rotator cuff tears that are suitable for either operative or nonoperative treatment will be enrolled. Block randomization will be performed and stratified by site, age, and tear size.

INTERVENTION

Nonoperative treatment consists of an approximately 3-month standardized physical therapy program, whereas operative treatment consists of rotator cuff surgery followed by approximately 4 months of postoperative rehabilitation.

MAIN OUTCOMES AND MEASURES

The primary outcome is patient-reported Shoulder Pain and Disability Index score, and the secondary outcome is American Shoulder and Elbow Surgeons Standardized Shoulder Form score measured at 1 year of follow-up.

DISCUSSION

The Arthroscopic Rotator Cuff trial is ongoing, and 12 sites with more than 40 physicians are currently recruiting patients. Although there is variation by site, as of May 2, 2019, 13% of all patients screened (787 of 6293) were eligible for the trial, and 9% of eligible patients (74 of 787) were recruited. Results of this study may help patients, clinicians, and policy makers assess the comparative effectiveness of operative vs nonoperative treatment for atraumatic rotator cuff tears.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03295994.

Association of APOL1 Risk Alleles With Cardiovascular Disease in Blacks in the Million Veteran Program

BACKGROUND

Approximately 13% of black individuals carry 2 copies of the apolipoprotein L1 (APOL1) risk alleles G1 or G2, which are associated with 1.5- to 2.5-fold increased risk of chronic kidney disease. There have been conflicting reports as to whether an association exists between APOL1 risk alleles and cardiovascular disease (CVD) that is independent of the effects of APOL1 on kidney disease. We sought to test the association of APOL1 G1/G2 alleles with coronary artery disease, peripheral artery disease, and stroke among black individuals in the Million Veteran Program.

METHODS

We performed a time-to-event analysis of retrospective electronic health record data using Cox proportional hazard and competing-risks Fine and Gray subdistribution hazard models. The primary exposure was APOL1 risk allele status. The primary outcome was incident coronary artery disease among individuals without chronic kidney disease during the 12.5-year follow-up period. We separately analyzed the cross-sectional association of APOL1 risk allele status with lipid traits and 115 cardiovascular diseases using phenome-wide association.

RESULTS

Among 30 903 black Million Veteran Program participants, 3941 (13%) carried the 2 APOL1 risk allele high-risk genotype. Individuals with normal kidney function at baseline with 2 risk alleles had slightly higher risk of developing coronary artery disease compared with those with no risk alleles (hazard ratio, 1.11 [95% CI, 1.01-1.21]; P=0.039). Similarly, modest associations were identified with incident stroke (hazard ratio, 1.20 [95% CI, 1.05-1.36; P=0.007) and peripheral artery disease (hazard ratio, 1.15 [95% CI, 1.01-1.29l; P=0.031). When both cardiovascular and renal outcomes were modeled, APOL1 was strongly associated with incident renal disease, whereas no significant association with the CVD end points could be detected. Cardiovascular phenome-wide association analyses did not identify additional significant associations with CVD subsets.

CONCLUSIONS

APOL1 risk variants display a modest association with CVD, and this association is likely mediated by the known APOL1 association with chronic kidney disease.

GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition.

METHODS

First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI).

RESULTS

Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10- 20). This effect was consistent in both pediatric (p = 9.92 × 10- 6) and adult (p = 9.73 × 10- 15) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10- 8, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10- 4). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10- 8), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10- 11). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses.

CONCLUSIONS

In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings.

Phenome-Wide Association Studies Uncover a Novel Association of Increased Atrial Fibrillation in Male Patients With Systemic Lupus Erythematosus

OBJECTIVE

Phenome-wide association studies (PheWAS) scan across billing codes in the electronic health record (EHR) and re-purpose clinical EHR data for research. In this study, we examined whether PheWAS could function as an EHR-based discovery tool for systemic lupus erythematosus (SLE) and identified novel clinical associations in male versus female patients with SLE.

METHODS

We used a de-identified version of the Vanderbilt University Medical Center EHR, which includes more than 2.8 million subjects. We performed EHR-based PheWAS to compare SLE patients with age-, sex-, and race-matched control subjects and to compare male SLE patients with female SLE patients, controlling for multiple testing using a false discovery rate (FDR) P value of 0.05.

RESULTS

We identified 1,097 patients with SLE and 5,735 matched control subjects. In a comparison of patients with SLE and matched controls, SLE patients were shown to be more likely to have International Classification of Diseases, Ninth Revision codes related to the SLE disease criteria. In the PheWAS of male versus female SLE patients, with adjustment for age and race, male patients were shown to be more likely to have atrial fibrillation (odds ratio 4.50, false discovery rate P = 3.23 × 10^-3 ). Chart review confirmed atrial fibrillation, with the majority of patients developing atrial fibrillation after the SLE diagnosis and having multiple risk factors for atrial fibrillation. After adjustment for age, sex, race, and coronary artery disease, SLE disease status was shown to be significantly associated with atrial fibrillation (P = 0.002).

CONCLUSION

Using PheWAS to compare male and female patients with SLE, we identified a novel association of an increased incidence of atrial fibrillation in male patients. SLE disease status was shown to be independently associated with atrial fibrillation, even after adjustment for age, sex, race, and coronary artery disease. These results demonstrate the utility of PheWAS as an EHR-based discovery tool for SLE.

Genome-wide association study of peripheral artery disease in the Million Veteran Program

Peripheral artery disease (PAD) is a leading cause of cardiovascular morbidity and mortality¹; however, the extent to which genetic factors increase risk for PAD is largely unknown. Using electronic health record data, we performed a genome-wide association study in the Million Veteran Program testing ~32 million DNA sequence variants with PAD (31,307 cases and 211,753 controls) across veterans of European, African, and Hispanic ancestry. The results were replicated in an independent sample of 5,117 PAD cases and 389,291 controls from UK Biobank. We identified 19 PAD loci, 18 of which have not been previously reported. 11 of the 19 loci were associated with disease in three vascular beds (coronary, cerebral, peripheral), including LDLR, LPL, and LPA, suggesting that therapeutic modulation of LDL cholesterol, the LPL pathway or circulating lipoprotein(a) may be efficacious for multiple atherosclerotic disease phenotypes. Conversely, 4 of the variants appeared to be specific for PAD, including F5 p.R506Q, highlighting the pathogenic role of thrombosis in the peripheral vascular bed and providing genetic support for Factor Xa inhibition as a therapeutic strategy for PAD. Our results highlight mechanistic similarities and differences among coronary, cerebral, and peripheral atherosclerosis and provide therapeutic insights.

Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants

BACKGROUND

Truncating variants in the Titin gene (TTNtvs) are common in individuals with idiopathic dilated cardiomyopathy (DCM). However, a comprehensive genomics-first evaluation of the impact of TTNtvs in different clinical contexts, and the evaluation of modifiers such as genetic ancestry, has not been performed.

METHODS

We reviewed whole exome sequence data for >71 000 individuals (61 040 from the Geisinger MyCode Community Health Initiative (2007 to present) and 10 273 from the PennMedicine BioBank (2013 to present) to identify anyone with TTNtvs. We further selected individuals with TTNtvs in exons highly expressed in the heart (proportion spliced in [PSI] >0.9). Using linked electronic health records, we evaluated associations of TTNtvs with diagnoses and quantitative echocardiographic measures, including subanalyses for individuals with and without DCM diagnoses. We also reviewed data from the Jackson Heart Study to validate specific analyses for individuals of African ancestry.

RESULTS

Identified with a TTNtv in a highly expressed exon (hiPSI) were 1.2% individuals in PennMedicine BioBank and 0.6% at Geisinger. The presence of a hiPSI TTNtv was associated with increased odds of DCM in individuals of European ancestry (odds ratio [95% CI]: 18.7 [9.1-39.4] {PennMedicine BioBank} and 10.8 [7.0-16.0] {Geisinger}). hiPSI TTNtvs were not associated with DCM in individuals of African ancestry, despite a high DCM prevalence (odds ratio, 1.8 [0.2-13.7]; P=0.57). Among 244 individuals of European ancestry with DCM in PennMedicine BioBank, hiPSI TTNtv carriers had lower left ventricular ejection fraction (β=-12%, P=3×10-7), and increased left ventricular diameter (β=0.65 cm, P=9×10-3). In the Geisinger cohort, hiPSI TTNtv carriers without a cardiomyopathy diagnosis had more atrial fibrillation (odds ratio, 2.4 [1.6-3.6]) and heart failure (odds ratio, 3.8 [2.4-6.0]), and lower left ventricular ejection fraction (β=-3.4%, P=1×10-7).

CONCLUSIONS

Individuals of European ancestry with hiPSI TTNtv have an abnormal cardiac phenotype characterized by lower left ventricular ejection fraction, irrespective of the clinical manifestation of cardiomyopathy. Associations with arrhythmias, including atrial fibrillation, were observed even when controlling for cardiomyopathy diagnosis. In contrast, no association between hiPSI TTNtvs and DCM was discerned among individuals of African ancestry. Given these findings, clinical identification of hiPSI TTNtv carriers may alter clinical management strategies.

GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort

In this study, we perform a full genome-wide association study (GWAS) to identify statistically significantly associated single nucleotide polymorphisms (SNPs) with three red blood cell (RBC) components and follow it with two independent PheWASs to examine associations between phenotypic data (case-control status of diagnoses or disease), significant SNPs, and RBC component levels. We first identified associations between the three RBC components: mean platelet volume (MPV), mean corpuscular volume (MCV), and platelet counts (PC), and the genotypes of approximately 500,000 SNPs on the Illumina Infimum DNA Human OmniExpress-24 BeadChip using a single cohort of 4,673 Northern Nevadans. Twenty-one SNPs in five major genomic regions were found to be statistically significantly associated with MPV, two regions with MCV, and one region with PC, with p<5x10^-8. Twenty-nine SNPs and nine chromosomal regions were identified in 30 previous GWASs, with effect sizes of similar magnitude and direction as found in our cohort. The two strongest associations were SNP rs1354034 with MPV (p = 2.4x10^-13) and rs855791 with MCV (p = 5.2x10^-12). We then examined possible associations between these significant SNPs and incidence of 1,488 phenotype groups mapped from International Classification of Disease version 9 and 10 (ICD9 and ICD10) codes collected in the extensive electronic health record (EHR) database associated with Healthy Nevada Project consented participants. Further leveraging data collected in the EHR, we performed an additional PheWAS to identify associations between continuous red blood cell (RBC) component measures and incidence of specific diagnoses. The first PheWAS illuminated whether SNPs associated with RBC components in our cohort were linked with other hematologic phenotypic diagnoses or diagnoses of other nature. Although no SNPs from our GWAS were identified as strongly associated to other phenotypic components, a number of associations were identified with p-values ranging between 1x10^-3 and 1x10^-4 with traits such as respiratory failure, sleep disorders, hypoglycemia, hyperglyceridemia, GERD and IBS. The second PheWAS examined possible phenotypic predictors of abnormal RBC component measures: a number of hematologic phenotypes such as thrombocytopenia, anemias, hemoglobinopathies and pancytopenia were found to be strongly associated to RBC component measures; additional phenotypes such as (morbid) obesity, malaise and fatigue, alcoholism, and cirrhosis were also identified to be possible predictors of RBC component measures.

Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods.

Unbiased Phenome-Wide Association Studies of Red Cell Distribution Width Identifies Key Associations with Pulmonary Hypertension

Rationale: Red cell distribution width (RDW) is a prognostic factor in many diseases; however, its clinical utility remains limited because the relative value of RDW as a biomarker across disease states has not been established. Objectives: To establish an unbiased RDW disease hierarchy to guide the clinical use of RDW and to assess its relationship to cardiovascular hemodynamic and structural parameters. Methods: We performed phenome-wide association studies for RDW in discovery and replication cohorts derived from a deidentified electronic health record in nonanemic individuals. RDW values obtained within 30 days of echocardiogram or right heart catheterization were tested for association with structural and hemodynamic variables. Results: RDW was associated with 263 phenotypes in both men and women in the discovery cohort (n = 121,530), 48 of which replicated in an independent cohort (n = 2,039). The strongest associations were observed with pulmonary arterial hypertension (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.9-2.3), chronic pulmonary heart disease (OR, 2.0; 95% CI, 1.9-2.2), and congestive heart failure (OR, 1.9; 95% CI, 1.8-2.0); P < 1 × 10-74 for all. By echocardiography, RDW was higher in the setting of right ventricular dysfunction than left ventricular dysfunction (P < 0.001). Measured invasively, mean pulmonary arterial pressure was associated with RDW (21 vs. 33 mm Hg at 25th vs. 75th percentile RDW; P < 1 × 10-7) and remained strongly significant even when controlling for mean pulmonary capillary wedge pressure (21 vs. 29 mm Hg at 25th vs. 75th percentile RDW; P < 1 × 10-7). Conclusions: Among 1,364 coded medical conditions, increased RDW was strongly associated with pulmonary hypertension and heart failure. Hemodynamic and echocardiographic phenotyping confirmed these associations and underscored that the most clinically relevant phenotype associated with RDW was pulmonary hypertension. These hypothesis-generating findings highlight the potential shared pathophysiology of pulmonary hypertension and elevated RDW. Elevated RDW in the absence of anemia should alert clinicians to the potential for underlying cardiopulmonary disease.

Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations

Alcohol consumption level and alcohol use disorder (AUD) diagnosis are moderately heritable traits. We conduct genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores and AUD diagnoses in a multi-ancestry Million Veteran Program sample (N = 274,424). We identify 18 genome-wide significant loci: 5 associated with both traits, 8 associated with AUDIT-C only, and 5 associated with AUD diagnosis only. Polygenic Risk Scores (PRS) for both traits are associated with alcohol-related disorders in two independent samples. Although a significant genetic correlation reflects the overlap between the traits, genetic correlations for 188 non-alcohol-related traits differ significantly for the two traits, as do the phenotypes associated with the traits' PRS. Cell type group partitioning heritability enrichment analyses also differentiate the two traits. We conclude that, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.

A phenome-wide association study to discover pleiotropic effects of PCSK9, APOB, and LDLR

We conducted an electronic health record (EHR)-based phenome-wide association study (PheWAS) to discover pleiotropic effects of variants in three lipoprotein metabolism genes PCSK9, APOB, and LDLR. Using high-density genotype data, we tested the associations of variants in the three genes with 1232 EHR-derived binary phecodes in 51,700 European-ancestry (EA) individuals and 585 phecodes in 10,276 African-ancestry (AA) individuals; 457 PCSK9, 730 APOB, and 720 LDLR variants were filtered by imputation quality (r 2 > 0.4), minor allele frequency (>1%), linkage disequilibrium (r 2 < 0.3), and association with LDL-C levels, yielding a set of two PCSK9, three APOB, and five LDLR variants in EA but no variants in AA. Cases and controls were defined for each phecode using the PheWAS package in R. Logistic regression assuming an additive genetic model was used with adjustment for age, sex, and the first two principal components. Significant associations were tested in additional cohorts from Vanderbilt University (n = 29,713), the Marshfield Clinic Personalized Medicine Research Project (n = 9562), and UK Biobank (n = 408,455). We identified one PCSK9, two APOB, and two LDLR variants significantly associated with an examined phecode. Only one of the variants was associated with a non-lipid disease phecode, ("myopia") but this association was not significant in the replication cohorts. In this large-scale PheWAS we did not find LDL-C-related variants in PCSK9, APOB, and LDLR to be associated with non-lipid-related phenotypes including diabetes, neurocognitive disorders, or cataracts.

Association Between Low-Density Lipoprotein Cholesterol Levels and Risk for Sepsis Among Patients Admitted to the Hospital With Infection

IMPORTANCE

Whether low levels of low-density lipoprotein cholesterol (LDL-C) are associated with increased risk of sepsis and poorer outcomes is unknown.

OBJECTIVE

To examine the association between LDL-C levels and risk of sepsis among patients admitted to the hospital with infection.

DESIGN, SETTING, AND PARTICIPANTS

Cohort study in which deidentified electronic health records were used to define a cohort of patients admitted to Vanderbilt University Medical Center, Nashville, Tennessee, with infection. Patients were white adults, had a code indicating infection from the International Classification of Diseases, Ninth Revision, Clinical Modification, and received an antibiotic within 1 day of hospital admission (N = 61 502). Data were collected from January 1, 1993, through December 31, 2017, and analyzed from January 24 through October 31, 2018.

INTERVENTIONS

Clinically measured LDL-C levels (excluding measurements <1 year before hospital admission and those associated with acute illness) and a genetic risk score (GRS).

MAIN OUTCOMES AND MEASURES

The primary outcome was sepsis; secondary outcomes included admission to an intensive care unit (ICU) and in-hospital death.

RESULTS

Among the 3961 patients with clinically measured LDL-C levels (57.8% women; mean [SD] age, 64.1 [15.9] years) and the 7804 with a GRS for LDL-C (54.0% men; mean [SD] age, 59.8 [15.2] years), lower measured LDL-C levels were significantly associated with increased risk of sepsis (odds ratio [OR], 0.86; 95% CI, 0.79-0.94; P = .001) and ICU admission (OR, 0.85; 95% CI, 0.76-0.96; P = .008), but not in-hospital mortality (OR, 0.80; 95% CI, 0.63-1.00; P = .06); however, none of these associations were statistically significant after adjustment for age, sex, and comorbidity variables (OR for risk of sepsis, 0.96 [95% CI, 0.88-1.06]; OR for ICU admission, 0.94 [95% CI, 0.83-1.06]; OR for in-hospital death, 0.97 [95% CI, 0.76-1.22]; P > .05 for all). The LDL-C GRS correlated with measured LDL-C levels (r = 0.24; P < 2.2 × 10-16) but was not significantly associated with any of the outcomes.

CONCLUSIONS AND RELEVANCE

Results of this study suggest that lower measured LDL-C levels were significantly associated with increased risk of sepsis and admission to ICU in patients admitted to the hospital with infection; however, this association was due to comorbidities because both clinical models adjusted for confounders, and the genetic model showed no increased risk. Levels of LDL-C do not appear to directly alter the risk of sepsis or poor outcomes in patients hospitalized with infection.

Trans-ethnic association study of blood pressure determinants in over 750,000 individuals

In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.

Phenome-wide association study identifies dsDNA as a driver of major organ involvement in systemic lupus erythematosus

In systemic lupus erythematosus (SLE), dsDNA antibodies are associated with renal disease. Less is known about comorbidities in patients without dsDNA or other autoantibodies. Using an electronic health record (EHR) SLE cohort, we employed a phenome-wide association study (PheWAS) that scans across billing codes to compare comorbidities in SLE patients with and without autoantibodies. We used our validated algorithm to identify SLE subjects. Autoantibody status was defined as ever positive for dsDNA, RNP, Smith, SSA and SSB. PheWAS was performed in antibody positive vs. negative SLE patients adjusting for age and race and using a false discovery rate of 0.05. We identified 1097 SLE subjects. In the PheWAS of dsDNA positive vs. negative subjects, dsDNA positive subjects were more likely to have nephritis ( p = 2.33 × 10^-9) and renal failure ( p = 1.85 × 10^-5). After adjusting for sex, race, age and other autoantibodies, dsDNA was independently associated with nephritis and chronic kidney disease. Those patients negative for dsDNA, RNP, SSA and SSB negative subjects were all more likely to have billing codes for sleep, pain and mood disorders. PheWAS uncovered a hierarchy within SLE-specific autoantibodies with dsDNA having the greatest impact on major organ involvement.

LPA Variants Are Associated With Residual Cardiovascular Risk in Patients Receiving Statins

BACKGROUND

Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.

METHODS

We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.

RESULTS

The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10-10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.

CONCLUSIONS

Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

An Atlas of Genetic Variation Linking Pathogen-Induced Cellular Traits to Human Disease

Pathogens have been a strong driving force for natural selection. Therefore, understanding how human genetic differences impact infection-related cellular traits can mechanistically link genetic variation to disease susceptibility. Here we report the Hi-HOST Phenome Project (H2P2): a catalog of cellular genome-wide association studies (GWAS) comprising 79 infection-related phenotypes in response to 8 pathogens in 528 lymphoblastoid cell lines. Seventeen loci surpass genome-wide significance for infection-associated phenotypes ranging from pathogen replication to cytokine production. We combined H2P2 with clinical association data from patients to identify a SNP near CXCL10 as a risk factor for inflammatory bowel disease. A SNP in the transcriptional repressor ZBTB20 demonstrated pleiotropy, likely through suppression of multiple target genes, and was associated with viral hepatitis. These data are available on a web portal to facilitate interpreting human genome variation through the lens of cell biology and should serve as a rich resource for the research community.

Relationship between very low low-density lipoprotein cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: A US-based cross-sectional observational study using electronic health records

BACKGROUND

Observations from statin clinical trials and from Mendelian randomization studies suggest that low low-density lipoprotein cholesterol (LDL-C) concentrations may be associated with increased risk of type 2 diabetes mellitus (T2DM). Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations in increased risk of T2DM.

METHODS AND FINDINGS

We used de-identified electronic health records (EHRs) at Vanderbilt University Medical Center to compare the risk of T2DM in a cross-sectional study among individuals with very low (≤60 mg/dl, N = 8,943) and normal (90-130 mg/dl, N = 71,343) LDL-C levels calculated using the Friedewald formula. LDL-C levels associated with statin use, hospitalization, or a serum albumin level < 3 g/dl were excluded. We used a 2-phase approach: in 1/3 of the sample (discovery) we used T2DM phenome-wide association study codes (phecodes) to identify cases and controls, and in the remaining 2/3 (validation) we identified T2DM cases and controls using a validated algorithm. The analysis plan for the validation phase was constructed at the time of the design of that component of the study. The prevalence of T2DM in the very low and normal LDL-C groups was compared using logistic regression with adjustment for age, race, sex, body mass index (BMI), high-density lipoprotein cholesterol, triglycerides, and duration of care. Secondary analyses included prespecified stratification by sex, race, BMI, and LDL-C level. In the discovery cohort, phecodes related to T2DM were significantly more frequent in the very low LDL-C group. In the validation cohort (N = 33,039 after applying the T2DM algorithm to identify cases and controls), the risk of T2DM was increased in the very low compared to normal LDL-C group (odds ratio [OR] 2.06, 95% CI 1.80-2.37; P < 2 × 10-16). The findings remained significant in sensitivity analyses. The association between low LDL-C levels and T2DM was significant in males (OR 2.43, 95% CI 2.00-2.95; P < 2 × 10-16) and females (OR 1.74, 95% CI 1.42-2.12; P = 6.88 × 10-8); in normal weight (OR 2.18, 95% CI 1.59-2.98; P = 1.1× 10-6), overweight (OR 2.17, 95% CI 1.65-2.83; P = 1.73× 10-8), and obese (OR 2.00, 95% CI 1.65-2.41; P = 8 × 10-13) categories; and in individuals with LDL-C < 40 mg/dl (OR 2.31, 95% CI 1.71-3.10; P = 3.01× 10-8) and LDL-C 40-60 mg/dl (OR 1.99, 95% CI 1.71-2.32; P < 2.0× 10-16). The association was significant in individuals of European ancestry (OR 2.67, 95% CI 2.25-3.17; P < 2 × 10-16) but not in those of African ancestry (OR 1.09, 95% CI 0.81-1.46; P = 0.56). A limitation was that we only compared groups with very low and normal LDL-C levels; also, since this was not an inception cohort, we cannot exclude the possibility of reverse causation.

CONCLUSIONS

Very low LDL-C concentrations occurring in the absence of statin treatment were significantly associated with T2DM risk in a large EHR population; this increased risk was present in both sexes and all BMI categories, and in individuals of European ancestry but not of African ancestry. Longitudinal cohort studies to assess the relationship between very low LDL-C levels not associated with lipid-lowering therapy and risk of developing T2DM will be important.

MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank

OBJECTIVES

We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank.

METHODS

We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelianrandomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage.

RESULTS

Our PheWAS identified 25 disease groups/outcomes associated with SUA genetic risk loci after multiple testing correction (P<8.57e-05). Our conventional MR analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. Our analysis highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy.

CONCLUSIONS

Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether polygenic risk scores (PRS) for common cancers are associated with multiple phenotypes in a phenome-wide association study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRS exhibited strong association for several cancer traits they were designed for, including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of "exclusion PRS PheWAS" was introduced. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This comprehensive PheWAS used PRS instead of a single variant.

Rare Variants in the Gene ALPL That Cause Hypophosphatasia Are Strongly Associated With Ovarian and Uterine Disorders

Context

Mutations in alkaline phosphatase (AlkP), liver/bone/kidney (ALPL), which encodes tissue-nonspecific isozyme AlkP, cause hypophosphatasia (HPP). HPP is suspected by a low-serum AlkP. We hypothesized that some patients with bone or dental disease have undiagnosed HPP, caused by ALPL variants.

Objective

Our objective was to discover the prevalence of these gene variants in the Vanderbilt University DNA Biobank (BioVU) and to assess phenotypic associations.

Design

We identified subjects in BioVU, a repository of DNA, that had at least one of three known, rare HPP disease-causing variants in ALPL: rs199669988, rs121918007, and/or rs121918002. To evaluate for phenotypic associations, we conducted a sequential phenome-wide association study of ALPL variants and then performed a de-identified manual record review to refine the phenotype.

Results

Out of 25,822 genotyped individuals, we identified 52 women and 53 men with HPP disease-causing variants in ALPL, 7/1000. None had a clinical diagnosis of HPP. For patients with ALPL variants, the average serum AlkP levels were in the lower range of normal or lower. Forty percent of men and 62% of women had documented bone and/or dental disease, compatible with the diagnosis of HPP. Forty percent of the female patients had ovarian pathology or other gynecological abnormalities compared with 15% seen in controls.

Conclusions

Variants in the ALPL gene cause bone and dental disease in patients with and without the standard biomarker, low plasma AlkP. ALPL gene variants are more prevalent than currently reported and underdiagnosed. Gynecologic disease appears to be associated with HPP-causing variants in ALPL.

Phenome-wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus

Background

African Americans with systemic lupus erythematosus (SLE) have increased renal disease compared to Caucasians, but differences in other comorbidities have not been well-described. We used an electronic health record (EHR) technique to test for differences in comorbidities in African Americans compared to Caucasians with SLE.

Methods

We used a de-identified EHR with 2.8 million subjects to identify SLE cases using a validated algorithm. We performed phenome-wide association studies (PheWAS) comparing African American to Caucasian SLE cases and African American SLE cases to matched non-SLE controls. Controls were age, sex, and race matched to SLE cases. For multiple testing, a false discovery rate (FDR) p value of 0.05 was used.

Results

We identified 270 African Americans and 715 Caucasians with SLE and 1425 matched African American controls. Compared to Caucasians with SLE adjusting for age and sex, African Americans with SLE had more comorbidities in every organ system. The most striking included hypertension odds ratio (OR) = 4.25, FDR p = 5.49 × 10^{− 15}; renal dialysis OR = 10.90, FDR p = 8.75 × 10^{− 14}; and pneumonia OR = 3.57, FDR p = 2.32 × 10^{− 8}. Compared to the African American matched controls without SLE, African Americans with SLE were more likely to have comorbidities in every organ system. The most significant codes were renal and cardiac, and included renal failure (OR = 9.55, FDR p = 2.26 × 10^{− 40}) and hypertensive heart and renal disease (OR = 8.08, FDR p = 1.78 × 10^{− 22}). Adjusting for race, age, and sex in a model including both African American and Caucasian SLE cases and controls, SLE was independently associated with renal, cardiovascular, and infectious diseases (all p < 0.01).

Conclusions

African Americans with SLE have an increased comorbidity burden compared to Caucasians with SLE and matched controls. This increase in comorbidities in African Americans with SLE highlights the need to monitor for cardiovascular and infectious complications.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1561-8) contains supplementary material, which is available to authorized users.

Recent Genetics and Epigenetics Approaches to PTSD

PURPOSE OF REVIEW

Following a life-threatening traumatic exposure, about 10% of those exposed are at considerable risk for developing posttraumatic stress disorder (PTSD), a severe and disabling syndrome characterized by uncontrollable intrusive memories, nightmares, avoidance behaviors, and hyperarousal in addition to impaired cognition and negative emotion symptoms. This review will explore recent genetic and epigenetic approaches to PTSD that explain some of the differential risk following trauma exposure.

RECENT FINDINGS

A substantial portion of the variance explaining differential risk responses to trauma exposure may be explained by differential inherited and acquired genetic and epigenetic risk. This biological risk is complemented by alterations in the functional regulation of genes via environmentally induced epigenetic changes, including prior childhood and adult trauma exposure. This review will cover recent findings from large-scale genome-wide association studies as well as newer epigenome-wide studies. We will also discuss future "phenome-wide" studies utilizing electronic medical records as well as targeted genetic studies focusing on mechanistic ways in which specific genetic or epigenetic alterations regulate the biological risk for PTSD.

Current Scope and Challenges in Phenome-Wide Association Studies

PURPOSE OF REVIEW

Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS.

RECENT FINDINGS

PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data.

SUMMARY

The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.

Phenome-Wide Association Study of Rheumatoid Arthritis Subgroups Identifies Association Between Seronegative Disease and Fibromyalgia

OBJECTIVE

The differences between seronegative and seropositive rheumatoid arthritis (RA) have not been widely reported. We performed electronic health record (EHR)-based phenome-wide association studies (PheWAS) to identify disease associations in seropositive and seronegative RA.

METHODS

A validated algorithm identified RA subjects from the de-identified version of the Vanderbilt University Medical Center EHR. Serotypes were determined by rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (ACPA) values. We tested EHR-derived phenotypes using PheWAS comparing seropositive RA and seronegative RA, yielding disease associations. PheWAS was also performed in RF-positive versus RF-negative subjects and ACPA-positive versus ACPA-negative subjects. Following PheWAS, select phenotypes were then manually reviewed, and fibromyalgia was specifically evaluated using a validated algorithm.

RESULTS

A total of 2,199 RA individuals with either RF or ACPA testing were identified. Of these, 1,382 patients (63%) were classified as seropositive. Seronegative RA was associated with myalgia and myositis (odds ratio [OR] 2.1, P = 3.7 × 10^-10 ) and back pain. A manual review of the health record showed that among subjects coded for Myalgia and Myositis, ∼80% had fibromyalgia. Follow-up with a specific EHR algorithm for fibromyalgia confirmed that seronegative RA was associated with fibromyalgia (OR 1.8, P = 4.0 × 10^-6 ). Seropositive RA was associated with chronic airway obstruction (OR 2.2, P = 1.4 × 10^-4 ) and tobacco use (OR 2.2, P = 7.0 × 10^-4 ).

CONCLUSION

This PheWAS of RA patients identifies a strong association between seronegativity and fibromyalgia. It also affirms relationships between seropositivity and chronic airway obstruction and between seropositivity and tobacco use. These findings demonstrate the utility of the PheWAS approach to discover novel phenotype associations within different subgroups of a disease.

Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record

OBJECTIVE

To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.

METHODS AND MATERIALS

We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.

RESULTS

Out of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.

CONCLUSION

Our results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.

A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS

The availability of electronic health record (EHR)-based phenotypes allows for genome-wide association analyses in thousands of traits and has great potential to enable identification of genetic variants associated with clinical phenotypes. We can interpret the phenome-wide association study (PheWAS) result for a single genetic variant by observing its association across a landscape of phenotypes. Because a PheWAS can test thousands of binary phenotypes, and most of them have unbalanced or often extremely unbalanced case-control ratios (1:10 or 1:600, respectively), existing methods cannot provide an accurate and scalable way to test for associations. Here, we propose a computationally fast score-test-based method that estimates the distribution of the test statistic by using the saddlepoint approximation. Our method is much (∼100 times) faster than the state-of-the-art Firth's test. It can also adjust for covariates and control type I error rates even when the case-control ratio is extremely unbalanced. Through application to PheWAS data from the Michigan Genomics Initiative, we show that the proposed method can control type I error rates while replicating previously known association signals even for traits with a very small number of cases and a large number of controls.

Hospitalizations for mitochondrial disease across the lifespan in the U.S

IMPORTANCE

Mitochondrial disease is being diagnosed with increasing frequency. Although children with mitochondrial disease often have severe, life-limiting illnesses, many survive into adulthood. There is, however, limited information about the impact of mitochondrial disease on healthcare utilization in the U.S. across the lifespan.

OBJECTIVES

To describe the characteristics of inpatient hospitalizations related to mitochondrial disease in the U.S., to identify patient-level clinical factors associated with in-hospital mortality, and to estimate the burden of hospitalizations on individual patients.

DESIGN

Cross-sectional and longitudinal observational studies.

SETTING

U.S. hospitals.

PARTICIPANTS

Individuals with hospital discharges included in the triennial Healthcare Cost and Utilization Project (HCUP) Kids Inpatient Database (KID) and the National Inpatient Sample (NIS) in 2012 (cross-sectional analysis); individuals with hospital discharges included in the HCUP California State Inpatient Database from 2007 to 2011, inclusive (longitudinal analysis).

EXPOSURE

Hospital discharge associated with a diagnosis of mitochondrial disease.

MAIN OUTCOME MEASURES

Total number and rate of hospitalizations for individuals with mitochondrial disease (International Classification of Diseases, 9th revision, Clinical Modification code 277.87, disorder of mitochondrial metabolism); in-hospital mortality.

RESULTS

In the 2012, there were approximately 3200 inpatient pediatric hospitalizations (1.9 per 100,000 population) and 2000 inpatient adult hospitalizations (0.8 per 100,000 population) for mitochondrial disease in the U.S., with associated direct medical costs of $113million. In-hospital mortality rates were 2.4% for children and 3.0% for adults, far exceeding population averages. Higher socioeconomic status was associated with both having a diagnosis of mitochondrial disease and with higher in-hospital mortality. From 2007 to 2011 in California, 495 individuals had at least one admission with a diagnosis of mitochondrial disease. Patients had a median of 1.1 hospitalizations (IQI, 0.6-2.2) per calendar year of follow-up; infants under 2y were hospitalized more frequently than other age groups. Over up to five years of follow up, 9.9% of participants with any hospitalization for mitochondrial disease were noted to have an in-hospital death.

CONCLUSIONS AND RELEVANCE

Hospitalizations for pediatric and adult mitochondrial diseases are associated with serious illnesses, substantial costs, and significant patient time. Identification of opportunities to prevent or shorten such hospitalizations should be the focus of future studies.

Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants

Although many phenotypes have been associated with variants in human leukocyte antigen (HLA) genes, the full phenotypic impact of HLA variants across all diseases is unknown. We imputed HLA genomic variation from two populations of 28,839 and 8431 European ancestry individuals and tested association of HLA variation with 1368 phenotypes. A total of 104 four-digit and 92 two-digit HLA allele phenotype associations were significant in both discovery and replication cohorts, the strongest being HLA-DQB1*03:02 and type 1 diabetes. Four previously unidentified associations were identified across the spectrum of disease with two- and four-digit HLA alleles and 10 with nonsynonymous variants. Some conditions associated with multiple HLA variants and stronger associations with more severe disease manifestations were identified. A comprehensive, publicly available catalog of clinical phenotypes associated with HLA variation is provided. Examining HLA variant disease associations in this large data set allows comprehensive definition of disease associations to drive further mechanistic insights.

Defining the complex phenotype of severe systemic loxoscelism using a large electronic health record cohort

Objective

Systemic loxoscelism is a rare illness resulting from the bite of the recluse spider and, in its most severe form, can lead to widespread hemolysis, coagulopathy, and death. We aim to describe the clinical features and outcomes of the largest known cohort of individuals with moderate to severe loxoscelism.

Methods

We performed a retrospective, cross sectional study from January 1, 1995, to December 31, 2015, at a tertiary-care academic medical center, to determine individuals with clinical records consistent with moderate to severe loxoscelism. Age-, sex-, and race-matched controls were compared. Demographics, clinical characteristics, laboratory measures, and outcomes of individuals with loxoscelism are described. Case and control groups were compared with descriptive statistics and phenome-wide association study (PheWAS).

Results

During the time period, 57 individuals were identified as having moderate to severe loxoscelism. Of these, only 33% had an antecedent spider bite documented. Median age of individuals diagnosed with moderate to severe loxoscelism was 14 years old (IQR 9.0–24.0 years). PheWAS confirmed associations of systemic loxoscelism with 29 other phenotypes, e.g., rash, hemolytic anemia, and sepsis. Hemoglobin level dropped an average of 3.1 g/dL over an average of 2.0 days (IQR 2.0–6.0). Lactate dehydrogenase and total bilirubin levels were on average over two times their upper limit of normal values. Eighteen individuals of 32 tested had a positive direct antiglobulin (Coombs’) test. Mortality was 3.5% (2/57 individuals).

Conclusion

Systemic loxoscelism is a rare but devastating process with only a minority of patients recalling the toxic exposure; hemolysis reaches a peak at 2 days after admission, with some cases taking more than a week before recovery. In endemic areas, suspicion for systemic loxoscelism should be high in individuals, especially children and younger adults, presenting with a cutaneous ulcer and hemolysis or coagulopathy, even in the absence of a bite exposure history.

Transcription factor ETV1 is essential for rapid conduction in the heart

Rapid impulse propagation in the heart is a defining property of pectinated atrial myocardium (PAM) and the ventricular conduction system (VCS) and is essential for maintaining normal cardiac rhythm and optimal cardiac output. Conduction defects in these tissues produce a disproportionate burden of arrhythmic disease and are major predictors of mortality in heart failure patients. Despite the clinical importance, little is known about the gene regulatory network that dictates the fast conduction phenotype. Here, we have used signal transduction and transcriptional profiling screens to identify a genetic pathway that converges on the NRG1-responsive transcription factor ETV1 as a critical regulator of fast conduction physiology for PAM and VCS cardiomyocytes. Etv1 was highly expressed in murine PAM and VCS cardiomyocytes, where it regulates expression of Nkx2-5, Gja5, and Scn5a, key cardiac genes required for rapid conduction. Mice deficient in Etv1 exhibited marked cardiac conduction defects coupled with developmental abnormalities of the VCS. Loss of Etv1 resulted in a complete disruption of the normal sodium current heterogeneity that exists between atrial, VCS, and ventricular myocytes. Lastly, a phenome-wide association study identified a link between ETV1 and bundle branch block and heart block in humans. Together, these results identify ETV1 as a critical factor in determining fast conduction physiology in the heart.

Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk

Greater genetic variability in an individual is protective against recessive disease. However, existing quantifications of autozygosity, such as runs of homozygosity (ROH), have proved highly sensitive to genotyping density and have yielded inconclusive results about the relationship of diversity and disease risk. Using genotyping data from three data sets with >43,000 subjects, we demonstrated that an alternative approach to quantifying genetic variability, the heterozygosity ratio, is a robust measure of diversity and is positively associated with the nondisease trait height and several disease phenotypes in subjects of European ancestry. The heterozygosity ratio is the number of heterozygous sites in an individual divided by the number of nonreference homozygous sites and is strongly affected by the degree of genetic admixture of the population and varies across human populations. Unlike quantifications of ROH, the heterozygosity ratio is not sensitive to the density of genotyping performed. Our results establish the heterozygosity ratio as a powerful new statistic for exploring the patterns and phenotypic effects of different levels of genetic variation in populations.

Phenome-Wide Association Studies as a Tool to Advance Precision Medicine

Beginning in the early 2000s, the accumulation of biospecimens linked to electronic health records (EHRs) made possible genome-phenome studies (i.e., comparative analyses of genetic variants and phenotypes) using only data collected as a by-product of typical health care. In addition to disease and trait genetics, EHRs proved a valuable resource for analyzing pharmacogenetic traits and developing reverse genetics approaches such as phenome-wide association studies (PheWASs). PheWASs are designed to survey which of many phenotypes may be associated with a given genetic variant. PheWAS methods have been validated through replication of hundreds of known genotype-phenotype associations, and their use has differentiated between true pleiotropy and clinical comorbidity, added context to genetic discoveries, and helped define disease subtypes, and may also help repurpose medications. PheWAS methods have also proven to be useful with research-collected data. Future efforts that integrate broad, robust collection of phenotype data (e.g., EHR data) with purpose-collected research data in combination with a greater understanding of EHR data will create a rich resource for increasingly more efficient and detailed genome-phenome analysis to usher in new discoveries in precision medicine.

Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods

OBJECTIVE

The combination of phenomic data from electronic health records (EHR) and clinical data repositories with dense biological data has enabled genomic and pharmacogenomic discovery, a first step toward precision medicine. Computational methods for the identification of clinical phenotypes from EHR data will advance our understanding of disease risk and drug response, and support the practice of precision medicine on a national scale.

METHODS

Based on our experience within three national research networks, we summarize the broad approaches to clinical phenotyping and highlight the important role of these networks in the progression of high-throughput phenotyping and precision medicine. We provide supporting literature in the form of a non-systematic review.

RESULTS

The practice of clinical phenotyping is evolving to meet the growing demand for scalable, portable, and data driven methods and tools. The resources required for traditional phenotyping algorithms from expert defined rules are significant. In contrast, machine learning approaches that rely on data patterns will require fewer clinical domain experts and resources.

CONCLUSIONS

Machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, derived from data rather than experts. Research networks and phenotype developers should cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and truly modernize biomedical research and precision medicine.

Phenome-wide association study maps new diseases to the human major histocompatibility complex region

BACKGROUND

Over 160 disease phenotypes have been mapped to the major histocompatibility complex (MHC) region on chromosome 6 by genome-wide association study (GWAS), suggesting that the MHC region as a whole may be involved in the aetiology of many phenotypes, including unstudied diseases. The phenome-wide association study (PheWAS), a powerful and complementary approach to GWAS, has demonstrated its ability to discover and rediscover genetic associations. The objective of this study is to comprehensively investigate the MHC region by PheWAS to identify new phenotypes mapped to this genetically important region.

METHODS

In the current study, we systematically explored the MHC region using PheWAS to associate 2692 MHC-linked variants (minor allele frequency ≥0.01) with 6221 phenotypes in a cohort of 7481 subjects from the Marshfield Clinic Personalized Medicine Research Project.

RESULTS

Findings showed that expected associations previously identified by GWAS could be identified by PheWAS (eg, psoriasis, ankylosing spondylitis, type I diabetes and coeliac disease) with some having strong cross-phenotype associations potentially driven by pleiotropic effects. Importantly, novel associations with eight diseases not previously assessed by GWAS (eg, lichen planus) were also identified and replicated in an independent population. Many of these associated diseases appear to be immune-related disorders. Further assessment of these diseases in 16 484 Marshfield Clinic twins suggests that some of these diseases, including lichen planus, may have genetic aetiologies.

CONCLUSIONS

These results demonstrate that the PheWAS approach is a powerful and novel method to discover SNP-disease associations, and is ideal when characterising cross-phenotype associations, and further emphasise the importance of the MHC region in human health and disease.

The phenotypic legacy of admixture between modern humans and Neandertals

Many modern human genomes retain DNA inherited from interbreeding with archaic hominins, such as Neandertals, yet the influence of this admixture on human traits is largely unknown. We analyzed the contribution of common Neandertal variants to over 1000 electronic health record (EHR)-derived phenotypes in ~28,000 adults of European ancestry. We discovered and replicated associations of Neandertal alleles with neurological, psychiatric, immunological, and dermatological phenotypes. Neandertal alleles together explained a significant fraction of the variation in risk for depression and skin lesions resulting from sun exposure (actinic keratosis), and individual Neandertal alleles were significantly associated with specific human phenotypes, including hypercoagulation and tobacco use. Our results establish that archaic admixture influences disease risk in modern humans, provide hypotheses about the effects of hundreds of Neandertal haplotypes, and demonstrate the utility of EHR data in evolutionary analyses.

Unravelling the human genome-phenome relationship using phenome-wide association studies

Advances in genotyping technology have, over the past decade, enabled the focused search for common genetic variation associated with human diseases and traits. With the recently increased availability of detailed phenotypic data from electronic health records and epidemiological studies, the impact of one or more genetic variants on the phenome is starting to be characterized both in clinical and population-based settings using phenome-wide association studies (PheWAS). These studies reveal a number of challenges that will need to be overcome to unlock the full potential of PheWAS for the characterization of the complex human genome-phenome relationship.