Applications of genetic data to identify cardiovascular disease mechanisms and therapeutic opportunities

Recent years have offered a wealth of genetic association data, with a concurrent explosion in the availability of methods for exploring causal effects through randomly allocated genetic variants that serve as proxies for traits of interest. This thesis investigates the state of this field within the remit of cardiovascular disease. Following an introduction into cardiovascular disease and Mendelian randomization (MR), the research focuses on dietary, social and pharmacological exposures as demonstrative examples for highlighting the breadth of techniques that can be harnessed towards understanding underlying mechanisms and therapeutic opportunities. Both two-sample and one-sample MR analyses are performed, using genetic summary data from large-scale consortia and the UK Biobank. Sample sizes for individual analyses typically exceed tens of thousands of participants. A diverse array of MR methods are employed, appropriate to the setting and objective of each analysis. Considering systemic iron status as a diet-related trait, genetic instruments are identified with consequent MR analyses supporting a protective effect on risk of cardiovascular outcomes related to atherosclerosis but a detrimental effect on outcomes related to thrombosis arising from stasis of blood. Phenome-wide association study further highlights effects of systemic iron status outside the remit of cardiovascular disease. In the investigation of social factors, MR mediation analysis techniques are applied to identify the pathways by which education affects cardiovascular disease risk, with multivariable MR further used to disentangle the direct effects of education and intelligence respectively. In the investigation of pharmacological exposures, genetic instruments for antihypertensive drugs are identified and validated by comparing against corresponding estimates from clinical trials. Phenome-wide association study is used to identify possible side-effects and repurposing opportunities, with a potential detrimental effect of calcium channel blockers identified on risk of diverticulosis. The final section provides an overview of the current state of applied MR, as well as future perspectives.Open Acces

Phenome-wide association study (PheWAS) of colorectal cancer risk SNP effects on health outcomes in UK Biobank

BACKGROUND: Associations between colorectal cancer (CRC) and other health outcomes have been reported, but these may be subject to biases, or due to limitations of observational studies. METHODS: We set out to determine whether genetic predisposition to CRC is also associated with the risk of other phenotypes. Under the phenome-wide association study (PheWAS) and tree-structured phenotypic model (TreeWAS), we studied 334,385 unrelated White British individuals (excluding CRC patients) from the UK Biobank cohort. We generated a polygenic risk score (PRS) from CRC genome-wide association studies as a measure of CRC risk. We performed sensitivity analyses to test the robustness of the results and searched the Danish Disease Trajectory Browser (DTB) to replicate the observed associations. RESULTS: Eight PheWAS phenotypes and 21 TreeWAS nodes were associated with CRC genetic predisposition by PheWAS and TreeWAS, respectively. The PheWAS detected associations were from neoplasms and digestive system disease group (e.g. benign neoplasm of colon, anal and rectal polyp and diverticular disease). The results from the TreeWAS corroborated the results from the PheWAS. These results were replicated in the observational data within the DTB. CONCLUSIONS: We show that benign colorectal neoplasms share genetic aetiology with CRC using PheWAS and TreeWAS methods. Additionally, CRC genetic predisposition is associated with diverticular disease

Investigating genetic determinants of liver disease and its associations with cardiovascular diseases

Background Dramatic modifications in lifestyle have given rise to an epidemic in chronic liver diseases, predominantly driven by non-alcoholic fatty liver disease (NAFLD). The more severe NAFLD phenotypes are associated with elevated liver iron, inflammation (steatohepatitis), scarring and liver failure (fibrosis, cirrhosis), and possibly with cardiovascular diseases (CVDs); genetic and population studies of these phenotypes and their links to CVDs have been limited. Aims 1) Investigate the genetic susceptibility underlying liver MRI phenotypes (iron and corrected T1 (cT1), a steatohepatitis proxy) and explore associations with other cardiometabolic traits. 2) Investigate whether liver fibrosis is an independent risk factor for CVDs. Methods We carried out genome-wide association studies (GWASs) of liver MRI phenotypes (iron (N = 8,289), and corrected T1 (a steatohepatitis proxy, N = 14,440)) in UK Biobank. We used genetics to investigate causality with other traits. We calculated a FIB-4 score (a validated non-invasive scoring system that predicts liver fibrosis) in 44,956 individuals in the UK and investigated its association with the incidence of five CVDs (ischaemic stroke, myocardial infarction, heart failure, peripheral arterial disease, atrial fibrillation (AF)). Results Three genetic variants known to influence hepcidin regulation (rs1800562 (C282Y) and rs1799945 (H63D) in HFE, rs855791 (V736A) in TMPRSS6) were associated with liver iron (p < 5 x 10-8). Mendelian randomisation provided evidence that central obesity causes higher liver iron. Four variants (rs75935921 in SLC30A10, rs13107325 in SLC39A8, rs58542926 in TM6SF2, rs738409 in PNPLA3) were associated with elevated cT1 (p < 5 x 10-8). Insulin resistance, type 2 diabetes, fatty liver, and BMI were causally associated with elevated cT1 whilst favourable adiposity was protective. In 44,956 individuals over a median of 5.4 years, adjusted models demonstrated strong associations of “suspected liver fibrosis” (FIB-4 1.3) with cirrhosis (Hazard ratio (HR 13.64 [10.79 – 17.26], p < 2 x 10-16)) and hepatocellular carcinoma (HR 11.64 [5.15 – 26.31], p = 3.5 x 10-9), but no association with the incidence of most CVDs, albeit a modest increase in AF risk (HR 1.18 [1.01 – 1.37]), when compared to individuals with a FIB-4 < 1.3. Conclusions This thesis provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific. The association between two metal ion transporters and cT1 indicates a new mechanism in steatohepatitis. There is little evidence to suggest that liver fibrosis is an independent risk factor for most CVDs, except possibly a small increase risk in incident AF risk. This thesis’ findings can be used to investigate causality, generate hypotheses for drug development and inform health policies

A polygenic and phenotypic risk prediction for polycystic ovary syndrome evaluated by phenomewide association studies

Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated tobe unidentified in clinical practice. Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-widecomorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventivetreatment.Design, Patients, and Methods: Leveraging the electronic health records (EHRs) of 124 852individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores(PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). Weevaluated its predictive capability across different ancestries and perform a PRS-based phenomewide association study (PheWAS) to assess the phenomic expression of the heightened risk ofPCOS.Results: The integrated polygenic prediction improved the average performance (pseudo-R2)for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null modelacross European, African, and multi-ancestry participants respectively. The subsequent PRSpowered PheWAS identified a high level of shared biology between PCOS and a range ofmetabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity","type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension",and "sleep apnea" reaching phenome-wide significance.Conclusions: Our study has expanded the methodological utility of PRS in patient stratificationand risk prediction, especially in a multifactorial condition like PCOS, across different geneticorigins. By utilizing the individual genome-phenome data available from the EHR, our approachalso demonstrates that polygenic prediction by PRS can provide valuable opportunities todiscover the pleiotropic phenomic network associated with PCOS pathogenesis.Abbreviations: AA, African ancestry; ANOVA, analysis of variance; BMI, body mass index; EA,European ancestry; EHR, electronic health records; eMERGE, electronic Medical Records andGenomics Network; GWAS, genome-wide association study; IBD, identity-by-descent; ICDCM, International Classification of Diseases, Clinical Modification; LD, linkage disequilibrium;MA, multi-ancestry; MAF, minor allele frequency; NIH, National Institutes of Health; PCA,principal component analysis; PheWAS, phenome-wide association study; PCOS, polycysticovary syndrome; PPRS, polygenic and phenotypic risk score; PRS, polygenic risk sc

Phenome-wide association study (PheWAS) on the genetic determinants of serum urate level and disease outcomes in UK Biobank

IntroductionElevated serum uric acid (SUA) concentration, known as hyperuricaemia, is a common abnormity in individuals with metabolic disorders. There is increasing evidence supporting the link between high SUA level and the increased risk of a wide range of clinical disorders, including hypertension, cardiovascular diseases (CVD), chronic renal diseases and metabolic syndrome. Although there are considerable research efforts in understanding the pathogenic pathways of high SUA level and the related clinical consequences, their causal relationships have not been established except for gout. Like other complex traits, genetic determinants play a substantial role (an estimated heritability of 40-70%) in the regulation of SUA level. Investigating the role of genetic variants related to SUA in various diseases might provide evidence for the above hypothesis which links uric acid to clinical disorders. Method Umbrella review was carried out first to provide a comprehensive overview on the range of health outcomes in relation to SUA level by incorporating evidence from systematic reviews and meta-analyses of observational studies, meta-analyses of randomised controlled trials (RCTs), and Mendelian randomisation (MR) studies. The umbrella review summarised the range of related health outcomes, the magnitude, direction and significance of identified associations and effects, and classified the evidence into four categories (class I [convincing], II [highly suggestive], III [suggestive], and IV [weak]) with assessment of multiple sources of biases. Then, a MR-PheWAS (Phenome-wide association study incorporated with Mendelian randomisation [MR]) was performed to investigate the associations between the 31 SUA genetic risk variants and a very wide range of disease outcomes by using the interim release data of UK Biobank (n=120,091). The SUA genetic risk loci were employed as instruments individually. The framework of phenome was defined by the PheCODE schema using the International Classification of Diseases (ICD) diagnosis codes documented in the health records of UK Biobank. Phenome-wide association test was performed first to identify any association across the SUA genetic risk loci and the phenome; MR design and HEIDI (heterogeneity in dependent instruments) tests were then applied to distinguish the PheWAS associations that were due to causality, pleiotropy or genetic linkage.To validate the MR-PheWAS findings, an enlarged Phenome-wide Mendelian randomisation (PWMR) analysis were performed by using data from the full UK Biobank cohort (n=339,256). A weighted polygenic risk score (GRS), incorporating effect estimates of multiple genetic risk loci, was employed as a proxy of the SUA level. The framework of phenome was defined by both the PheCODE schema and an alternative Tree-structured phenotypic model (TreeWAS) for analysis. Significant associations from these analyses were taken forward for replication in different populations by analysing data from various GWAS consortia documented in the MR-base database. Sensitivity analyses examining the pleiotropic effects of urate genetic risk loci on a set of metabolic traits were performed to explore any causal effects and pleiotropic associations.ResultsThe umbrella review included 101 articles and comprised 144 meta-analyses of observational studies, 31 meta-analyses of randomised controlled trials and 107 Mendelian randomisation studies. This remarkable assembly of evidence explored 136 unique health outcomes and reported convincing (class I) evidence for the causal role of SUA in gout and nephrolithiasis. Furthermore, highly suggestive (class II) evidence was reported for five health outcomes, in which high SUA level was associated with increased risk of heart failure, hypertension, impaired fasting glucose or diabetes, chronic kidney disease, and coronary heart disease mortality in the general population. The remaining 129 associations were classified as either suggestive or weak. The MR-PheWAS (using the interim release cohort) identified 25 disease groups/ outcomes to be associated with SUA genetic risk loci after multiple testing correction (p<8.6 ×10-5). The MR IVW (inverse variance weighted) 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. The analysis also highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy.The PWMR analysis, using data from the full UK Biobank cohort (n=339,256), examining the association with 1,431 disease outcomes, identified 13 phecodes that were associated with the weighted GRS of SUA level with the p value passing the significance threshold of PheWAS (p<3.4×10-4). These phecodes represent 4 disease groups: inflammatory polyarthropathies (OR=1.28; 95% CI: 1.21 to 1.35; p=4.97×10-19), hypertensive disease (OR=1.08; 95% CI: 1.05 to 1.11; p=6.02×10-7), circulatory disease (OR=1.05; 95% CI: 1.02 to 1.07; p=3.29×10-4) and metabolic disorders (OR=1.07; 95% CI: 1.03 to 1.11; p= 3.33×10-4), and 9 disease outcomes: gout (OR=5.37; 95% CI: 4.67 to 6.18; p= 4.27×10-123), gouty arthropathy (OR=5.11; 95% CI: 2.45 to 10.66; p=1.39×10-5), pyogenic arthritis (OR=2.10; 95% CI: 1.41 to 3.14; p=2.87×10-4), essential hypertension (OR=1.08; 95% CI: 1.05 to 1.11; p=6.62×10-7), coronary atherosclerosis (OR=1.10; 95% CI: 1.05 to 1.15; p=1.17×10-5), ischaemic heart disease (OR=1.10, 95% CI: 1.05 to 1.15; p=1.73×10-5), chronic ischaemic heart disease (OR=1.10, 95% CI: 1.05 to 1.15; p=1.52×10-5), myocardial infarction (OR=1.15, 95% CI=1.07 to 1.23, p=5.23×10-5), and hypercholesterolaemia (OR=1.08, 95% CI: 1.04 to 1.13, p=3.34×10-4). Findings from the TreeWAS analysis were generally consistent with that of PheWAS, with a number of more sub-phenotypes being identified. Results from IVW MR suggested that genetically determined high serum urate level was associated with increased risk of gout (OR=4.53, 95%CI: 3.64-5.64, p=9.66×10-42), CHD (OR=1.10, 95%CI: 1.02 to 1.19, p=0.009), myocardial infarction (OR=1.11, 95%CI:1.02 to 1.20, p=0.011) and decreased level of HDL-c (OR=0.93, 95%CI:0.88 to 0.98, p=0.004), but had no effect on RA (OR=0.92, 95%CI: 0.84 to 1.01, p=0.085) and ischaemic stroke (OR=1.03, 95%CI: 0.93 to 1.14, P= 0.582). Egger MR indicated pleiotropic effects on the causal estimates of DBP (P_pleiotropy=0.014), SBP (P_pleiotropy=0.003), CHD (P_pleiotropy=0.008), myocardial infarction (P_pleiotropy=0.008) and HDL-c (P_pleiotropy=0.016). When balancing out the potential pleiotropic effects in Egger MR, a causal effect can only be verified for gout (OR=4.17, 95%CI: 3.03 to 5.74, P_effect=1.27×〖10〗^(-9); P_pleiotropy=0.485). Sensitivity analyses on the GRSs of different groups of pleiotropic loci support an inference that pleiotropic effects of genetic variants on urate and metabolic traits contribute to the observed associations with cardiovascular/metabolic diseases. ConclusionsThis thesis presents a comprehensive investigation on the health outcomes in relation to SUA level. The causal relationship between high SUA level and gout is robustly verified in this thesis with consistent evidence from the umbrella review, the MR-PheWAS and the PWMR. The association of high SUA level with hypertension and heart diseases is supported by both the evidence from umbrella review and analyses conducted in this thesis, however, given the caveat of pleiotropy in the causal inference, a conclusion of causality on hypertension and heart diseases is not robust enough based on the current findings. Furthermore, the epidemiological evidence from the umbrella review indicated that high SUA level was associated with several components of metabolic disorders, and the analyses of the UK Biobank data identified a significant association with metabolic disorders and a sub-phenotype (hypercholesterolaemia). The causal inference in this study is limited by the common difficulty of pleiotropy caused by the use of multiple genetic instruments. Although we have performed sensitivity analysis by excluding the key pleiotropic locus, unmeasured pleiotropy and biases are still possible. In particular, unbalanced pleiotropy is recognised as an issue for the causal connections on the association between SUA level and hypertension. Other potential causal relevance of SUA level with respiratory diseases and ocular diseases is also worthy of further investigation. Overall, when taken together the findings from umbrella review, MR-PheWAS, PheWAS/TreeWAS analysis, MR replication and sensitivity analysis conducted in this thesis, I conclude that there are robust associations between urate and several disease groups, including gout, hypertensive diseases, heart diseases and metabolic disorders, but the causal role of urate only exists in gout. This study indicates that the observed associations between urate and cardiovascular/metabolic diseases are probably derived from the pleiotropic effects of genetic variants on urate and metabolic traits. Further investigation of therapies targeting the shared biological pathways between urate and metabolic traits may be beneficial for the treatment of gout and the primary prevention of cardiovascular/metabolic diseases

Phenome wide association study of vitamin D genetic variants in the UK Biobank cohort

Introduction Vitamin D status is an important public health issue due to the high prevalence of vitamin D insufficiency and deficiency, especially in high latitude areas. Furthermore, it has been reported to be associated with a number of diseases. In a previous umbrella review of meta-analyses of randomized clinical trials (RCTs) and of observational studies, it was found that plasma/ serum 25-hydroxyvitamin D (25(OH)D) or supplemental vitamin D has been linked to more than 130 unique health outcomes. However, the majority of the studies yielded conflicting results and no association was convincing. Aim and Objectives The aim of my PhD was to comprehensively explore the association between vitamin D and multiple outcomes. The specific objectives were to: 1) update the umbrella review of meta-analysis of observational studies or randomized controlled trials on associations between vitamin D and health outcomes published between 2014 and 2018; 2) conduct a systematic literature review of previous Mendelian Randomization studies on causal associations between vitamin D and all outcomes; 3) conduct a systematic literature review of published phenome wide association studies, summarizing the methods, results and predictors; 4) create a polygenic risk score of vitamin D related genetic variants, weighted by their effect estimates from the most recent genome wide association study; 5) encode phenotype groups based on electronic medical records of participants; 6) study the associations between vitamin D related SNPs and the whole spectrum of health outcomes, defined by electronic medical records utilising the UK Biobank study; 7) explore the causal effect of 25- hydroxyvitamin D level on health outcomes by applying novel instrumental variable methods. Methods First I updated the vitamin D umbrella review published in 2015, by summarizing the evidence from meta-analyses of observational studies and meta-analyses of RCTs published between 2014 and 2018. I also performed a systematic literature review of all previous Mendelian Randomizations studies on the effect of vitamin D on all health outcomes, as well as a systematic review of all published PheWAS studies and the methodology they applied. Then I conducted original data analysis in a large prospective population-based cohort, the UK Biobank, which includes more than 500,000 participants. A 25(OH)D genetic risk score (weighted sum score of 6 serum 25(OH)D-related SNPs: rs3755967, rs12785878, rs10741657, rs17216707, rs10745742 and rs8018720, as identified by the largest genome wide association study of 25(OH)D levels) was constructed to be used as the instrumental variable. I used a phenotyping algorithm to code the electronic medical records (EMR) of UK Biobank participants into 1853 distinct disease categories and I then ran the PheWAS analysis to test the associations between the 25(OH)D genetic risk score and 950 disease outcome groups (i.e. outcomes with more than 200 cases). For phenotypes found to show a statistically significant association with 25(OH)D levels in the PheWAS or phenotypes which were found to be convincing or highly suggestive in previous studies, I developed an extended case definition by incorporating self-reported data collected by UK Biobank baseline questionnaire and interview. The possible causal effect of vitamin D on those outcomes was then explored by the MR two-stage method, inverse variance weighted MR and Egger’s regression, followed by sensitivity analyses. Results In the updated systematic literature review of meta-analyses of observational studies or RCTs, only studies on new outcomes which had not been covered by the previous umbrella review were included. A total of 95 meta-analyses met the inclusion criteria. Among the included studies there were 66 meta-analyses of observational studies, and 29 meta-analyses of RCTs. Eighty-five new outcomes were explored by meta-analyses of observational studies, and 59 new outcomes were covered by meta-analyses of RCTs. In the systematic review of published Mendelian Randomization studies on vitamin D, a total of 29 studies were included. A causal role of 25(OH)D level was supported by MR analysis for the following outcomes: type 2 diabetes, total adiponectin, diastolic blood pressure, risk of hypertension, multiple sclerosis, Alzheimer’s disease, all-cause mortality, cancer mortality, mortality excluding cancer and cardiovascular events, ovarian cancer, HDL-cholesterol, triglycerides and cognitive functions. For the systematic literature review of published PheWAS studies and their methodology, a total of 45 studies were included. The processes for implementing a PheWAS study include the following steps: sample selection, predictor selection, phenotyping, statistical analysis and result interpretation. One of the main challenges is the definitions of the phenotypes (i.e., the method of binning participants into different phenotype groups). In the phenotyping step, an ICD curated phenotyping was widely used by previous PheWAS, which I also used in my own analysis. By applying the ICD curated phenotyping, 1853 phenotype groups were defined in the participants I used. In PheWAS, only phenotype groups with more than 200 cases were analysed (920 phenotypes). In the PheWAS, only associations between rs17216707 (CYP24A1) and “calculus of ureter” (beta = -0.219, se = 0.045, P = 1.14*10-6), “urinary calculus” (beta = -0.129, se = 0.027, P = 1.31*10-6), “alveolar and parietoalveolar pneumonopathy” (beta = 0.418, se = 0.101, P = 3.53*10-5) survived Bonferroni correction. Nine outcomes, including systolic blood pressure, diastolic blood pressure, body mass index, risk of hypertension, type 2 diabetes, ischemic heart disease, depression, non-vertebral fracture and all-cause mortality were explored in MR analyses. The MR analysis had more than 80% power for detecting a true odds ratio of 1.2 or larger for binary outcomes. None of explored outcomes were statistically significant. Results from multiple MR methods and sensitivity analyses were consistent. Discussion Vitamin D and its association with multiple outcomes has been widely studied. More than 230 outcomes have been linked with vitamin D by meta-analyses of observational studies and RCTs. On the contrary, evidence from Mendelian Randomization studies is lacking. In particular I identified only 20 existing MR studies and only 13 outcomes were suggested to be causally related to vitamin D. In the systematic literature review of previous PheWAS studies, I summarized the applied methods, predictors and results. Although phenotyping based on ICD codes provided good performance and was widely applied by previous PheWAS studies, phenotyping can be improved if lab data, imaging data and medical notes can be incorporated. Alternative algorithms, which takes advantage of deep learning and thus enable high precision phenotyping, needs to be developed. From the PheWAS analysis, the score of vitamin D related genetic variants was not statistically significantly associated with any of the 920 phenotypes tested. In the single variant analysis, only rs17216707 (CYP24A1) was shown to be associated with calculus outcomes statistically significantly. Previous studies reported associations between vitamin D and hypercalcemia, hypercalciuria, nephrolithiasis and nephrocalcinosis, may be due to the role of vitamin D in calcium homeostasis. In the MR analysis, I found no evidence of large to moderate (OR>1.2) causal associations of vitamin D on a very wide range of health outcomes. These included SBP, DBP, hypertension, T2D, IHD, BMI, depression, non-vertebral fracture and allcause mortality which have previously been proposed to be influenced by low vitamin D levels. Further, even larger studies, probably involving the joint analysis of data from several large biobanks with future IVs that explain a higher proportion of the trait variance, will be required to exclude smaller causal effects which could have public health importance because of the high population prevalence of low vitamin D levels in some populations

Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.

AIMS: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. METHODS AND RESULTS: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health. CONCLUSION: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare

Association of helicobacter pylori positivity with risk of disease and mortality

BACKGROUND: Helicobacter pylori colonizes the human stomach. Infection causes chronic gastritis and increases the risk for gastroduodenal ulcer and gastric cancer. Its chronic colonization in the stomach triggers aberrant epithelial and inflammatory signals, that are also associated with systemic alterations. METHODS: Using PheWAS analysis in more than 8.000 participants in the community-based UK Biobank we explored the association of H. pylori positivity with gastric and extra gastric disease and mortality in a European country. RESULTS: Along with well-established gastric diseases we dominantly found overrepresented cardiovascular, respiratory, and metabolic disorders. Using multivariate analysis, the overall mortality of H. pylori positive participants was not altered, while the respiratory and COVID-19 associated mortality increased. Lipidomic analysis for H. pylori positive participants revealed a dyslipidemic profile with reduced HDL cholesterol and omega-3 fatty acids, which may represent a causative link between infection, systemic inflammation, and disease. CONCLUSION: Our study of H. pylori positivity demonstrates that it plays an organ- and disease entity-specific role in the development of human disease and highlight the importance of further research into the systemic effects of H. pylori infection

A Genome-First Approach To Investigating The Biological And Clinical Relevance Of Exome-Wide Rare Coding Variation Using Electronic Health Record Phenotypes

Genome-wide association studies (GWAS) have successfully described the roles of common genetic variation on human diseases by analyzing large populations recruited based on a shared phenotype, but the biological and clinical relevance of numerous genes remain incompletely described through these ‘phenotype-first’ methodologies. Much of the unexplained genetic contribution to disease risk and variability in complex traits may belong to the very rare and private spectrum of alleles, a range traditionally ignored by GWAS. Furthermore, the phenotype-first approach is likely to miss unexpected phenotypic consequences of genetic variants, such as those that may not be feasible to study in a phenotype-first approach due to rarity of the condition. The Penn Medicine BioBank, a healthcare system-based database of genotype, whole-exome sequencing, and electronic health record data, allows for an unbiased, ‘genome-first’ approach to describing the relationships between genetic variants and human disease traits captured in the clinical setting. Through ‘gene burden’ tests that interrogate the cumulative effects of multiple rare and private variants in a gene that are predicted to affect gene function, this dissertation aims to characterize the clinical manifestations of diseases and traits caused by rare, predicted loss-of-function and predicted deleterious missense variants on an exome-wide and/or phenome-wide scale. These analyses uncover previously unsuspected medical and biological consequences of loss-of-function variants in multiple genes. In summary, this dissertation will investigate the biological and clinical relevance of disease-associated genes by investigating the association of rare coding variation found in whole-exome sequencing with phenotypes derived from the EHR