Jack O'Sullivan

All Publications

• Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries. The American journal of cardiology Weale, M. E., Riveros-Mckay, F., Selzam, S., Seth, P., Moore, R., Tarran, W. A., Gradovich, E., Giner-Delgado, C., Palmer, D., Wells, D., Saffari, A., Sivley, R. M., Lachapelle, A. S., Wand, H., Clarke, S. L., Knowles, J. W., O'Sullivan, J. W., Ashley, E. A., McVean, G., Plagnol, V., Donnelly, P. 2021

  Abstract

  The American College of Cardiology / American Heart Association pooled cohort equations tool (ASCVD-PCE) is currently recommended to assess 10-year risk for atherosclerotic cardiovascular disease (ASCVD). ASCVD-PCE does not currently include genetic risk factors. Polygenic risk scores (PRSs) have been shown to offer a powerful new approach to measuring genetic risk for common diseases, including ASCVD, and to enhance risk prediction when combined with ASCVD-PCE. Most work to date, including the assessment of tools, has focused on performance in individuals of European ancestries. Here we present evidence for the clinical validation of a new integrated risk tool (IRT), ASCVD-IRT, which combines ASCVD-PCE with PRS to predict 10-year risk of ASCVD across diverse ethnicity and ancestry groups. We demonstrate improved predictive performance of ASCVD-IRT over ASCVD-PCE, not only in individuals of self-reported White ethnicities (net reclassification improvement (NRI) (with 95% confidence interval) = 2.7% (1.1 - 4.2)) but also Black / African American / Black Caribbean / Black African (NRI = 2.5% (0.6 - 4.3)) and South Asian (Indian, Bangladeshi or Pakistani) ethnicities (NRI = 8.7% (3.1 - 14.4)). NRI confidence intervals were wider and included zero for ethnicities with smaller sample sizes, including Hispanic (NRI = 7.5% (-1.4 - 16.5)), but PRS effect sizes in these ethnicities were significant and of comparable size to those seen in individuals of White ethnicities. Comparable results were obtained when individuals were analysed by genetically inferred ancestry. Together, these results validate the performance of ASCVD-IRT in multiple ethnicities and ancestries, and favour their generalisation to all ethnicities and ancestries.

  View details for DOI 10.1016/j.amjcard.2021.02.032

  View details for PubMedID 33675770

• An Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction. Circulation. Genomic and precision medicine Riveros-Mckay, F., Weale, M. E., Moore, R., Selzam, S., Krapohl, E., Sivley, R. M., Tarran, W. A., Sorensen, P., Lachapelle, A. S., Griffiths, J. A., Saffari, A., Deanfield, J., Spencer, C. C., Hippisley-Cox, J., Hunter, D. J., O'Sullivan, J. W., Ashley, E. A., Plagnol, V., Donnelly, P. 2021

  Abstract

  Background - There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. Methods - Using the UK Biobank (UKB) resource, we developed our own polygenic risk score (PRS) for coronary artery disease (CAD). We used an additional 60,000 UKB individuals to develop an integrated risk tool (IRT) that combined our PRS with established risk tools (either the American Heart Association/American College of Cardiology's Pooled Cohort Equations (PCE) or UK's QRISK3), and we tested our IRT in an additional, independent, set of 186,451 UKB individuals. Results - The novel CAD PRS shows superior predictive power for CAD events, compared to other published PRSs and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an integrated risk tool, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared to 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI 4.7-7.0). When individuals were stratified into age-by-sex subgroups the improvement was larger for all subgroups (range 8.3%-15.4%), with best performance in 40-54yo men (15.4%, 95% CI 11.6-19.3). Comparable results were found using a different risk tool (QRISK3), and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12,000 deaths in the USA over a 5-year period. Conclusions - An integrated risk tool that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person's polygenic risk.

  View details for DOI 10.1161/CIRCGEN.120.003304

  View details for PubMedID 33651632

• Improving reporting standards for polygenic scores in risk prediction studies. Nature Wand, H., Lambert, S. A., Tamburro, C., Iacocca, M. A., O'Sullivan, J. W., Sillari, C., Kullo, I. J., Rowley, R., Dron, J. S., Brockman, D., Venner, E., McCarthy, M. I., Antoniou, A. C., Easton, D. F., Hegele, R. A., Khera, A. V., Chatterjee, N., Kooperberg, C., Edwards, K., Vlessis, K., Kinnear, K., Danesh, J. N., Parkinson, H., Ramos, E. M., Roberts, M. C., Ormond, K. E., Khoury, M. J., Janssens, A. C., Goddard, K. A., Kraft, P., MacArthur, J. A., Inouye, M., Wojcik, G. L. 2021; 591 (7849): 211–19

  Abstract

  Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

  View details for DOI 10.1038/s41586-021-03243-6

  View details for PubMedID 33692554

• Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals with Atrial Fibrillation. Circulation. Genomic and precision medicine O'Sullivan, J. W., Shcherbina, A., Justesen, J. M., Turakhia, M., Perez, M., Wand, H., Tcheandjieu, C., Clarke, S. L., Rivas, M. A., Ashley, E. A. 2021

  Abstract

  Background - Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable, however current risk stratification tools (CHA2DS2-VASc) don't include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods - Using data from the largest available GWAS in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results - Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved net reclassification (NRI: 2.3% (95%CI: 1.3% to 3.0%)), and fit (χ2 P =0.002). Using this improved tool, >115,000 people with AF would have improved risk classification in the US. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (Hazard Ratio: 1.13 per 1 SD (95%CI: 1.06 to 1.23)). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson's correlation coefficient: -0.018). Conclusions - In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors, however the prediction of stroke remains challenging.

  View details for DOI 10.1161/CIRCGEN.120.003168

  View details for PubMedID 34029116

• Consider a CT angiogram before invasive coronary angiogram in patients with NSTEMI. BMJ evidence-based medicine O'Sullivan, J. 2020

  View details for DOI 10.1136/bmjebm-2020-111402

  View details for PubMedID 33203622

• Establishing polygenic risk score reporting standards and a polygenic score catalog to improve validation, interpretation and reproducibility Kraft, P., Wand, H., Lambert, S. A., Tamburro, C., MacArthur, J., Iacocca, M. A., Sillari, C., O'Sullivan, J., Brockman, D., Schuele, B., Venner, E., Kullo, I. J., Rowley, R., McCarthy, M., Antoniou, A. C., Easton, D. F., Hegele, R. A., Khera, A., Kooperberg, C., Edwards, K., Ormond, K. E., Khoury, M. J., Janssens, A. W., Goddard, K. B., Inouye, M., Wojcik, G. WILEY. 2020: 496–97

  View details for Web of Science ID 000540090000068

• Multimodality Imaging for Risk Assessment of Inherited Cardiomyopathies CURRENT CARDIOVASCULAR RISK REPORTS O'Sullivan, J. W., Rhee, J., Hsu, D., Wheeler, M. T., Nieman, K. 2020; 14 (5)

  View details for DOI 10.1007/s12170-020-0639-4

  View details for Web of Science ID 000527933200001

• Should blood pressure medications be taken at bedtime? BMJ evidence-based medicine Heneghan, C., O'Sullivan, J., Mahtani, K. R. 2020

  View details for DOI 10.1136/bmjebm-2019-111311

  View details for PubMedID 31992562

• Alcohol and atrial fibrillation: to or not to drink? BMJ evidence-based medicine O'Sullivan, J. W. 2020

  View details for DOI 10.1136/bmjebm-2020-111340

  View details for PubMedID 32493831

• Accuracy of Smartphone Camera Applications for Detecting Atrial Fibrillation: A Systematic Review and Meta-analysis. JAMA network open O'Sullivan, J. W., Grigg, S. n., Crawford, W. n., Turakhia, M. P., Perez, M. n., Ingelsson, E. n., Wheeler, M. T., Ioannidis, J. P., Ashley, E. A. 2020; 3 (4): e202064

  Abstract

  Atrial fibrillation (AF) affects more than 6 million people in the United States; however, much AF remains undiagnosed. Given that more than 265 million people in the United States own smartphones (>80% of the population), smartphone applications have been proposed for detecting AF, but the accuracy of these applications remains unclear.To determine the accuracy of smartphone camera applications that diagnose AF.MEDLINE and Embase were searched until January 2019 for studies that assessed the accuracy of any smartphone applications that use the smartphone's camera to measure the amplitude and frequency of the user's fingertip pulse to diagnose AF.Bivariate random-effects meta-analyses were constructed to synthesize data. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) of Diagnostic Test Accuracy Studies reporting guideline.Sensitivity and specificity were measured with bivariate random-effects meta-analysis. To simulate the use of these applications as a screening tool, the positive predictive value (PPV) and negative predictive value (NPV) for different population groups (ie, age ≥65 years and age ≥65 years with hypertension) were modeled. Lastly, the association of methodological limitations with outcomes were analyzed with sensitivity analyses and metaregressions.A total of 10 primary diagnostic accuracy studies, with 3852 participants and 4 applications, were included. The oldest studies were published in 2016 (2 studies [20.0%]), while most studies (4 [40.0%]) were published in 2018. The applications analyzed the pulsewave signal for a mean (range) of 2 (1-5) minutes. The meta-analyzed sensitivity and specificity for all applications combined were 94.2% (95% CI, 92.2%-95.7%) and 95.8% (95% CI, 92.4%-97.7%), respectively. The PPV for smartphone camera applications detecting AF in an asymptomatic population aged 65 years and older was between 19.3% (95% CI, 19.2%-19.4%) and 37.5% (95% CI, 37.4%-37.6%), and the NPV was between 99.8% (95% CI, 99.83%-99.84%) and 99.9% (95% CI, 99.94%-99.95%). The PPV and NPV increased for individuals aged 65 years and older with hypertension (PPV, 20.5% [95% CI, 20.4%-20.6%] to 39.2% [95% CI, 39.1%-39.3%]; NPV, 99.8% [95% CI, 99.8%-99.8%] to 99.9% [95% CI, 99.9%-99.9%]). There were methodological limitations in a number of studies that did not appear to be associated with diagnostic performance, but this could not be definitively excluded given the sparsity of the data.In this study, all smartphone camera applications had relatively high sensitivity and specificity. The modeled NPV was high for all analyses, but the PPV was modest, suggesting that using these applications in an asymptomatic population may generate a higher number of false-positive than true-positive results. Future research should address the accuracy of these applications when screening other high-risk population groups, their ability to help monitor chronic AF, and, ultimately, their associations with patient-important outcomes.

  View details for DOI 10.1001/jamanetworkopen.2020.2064

  View details for PubMedID 32242908

• Age is the most important clinical feature to help rule out cardiac syncope. BMJ evidence-based medicine O'Sullivan, J. 2019

  View details for DOI 10.1136/bmjebm-2019-111270

  View details for PubMedID 31690577

• The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study LANCET DIGITAL HEALTH Shcherbina, A., Hershman, S. G., Lazzeroni, L., King, A. C., O'Sullivan, J. W., Hekler, E., Moayedi, Y., Pavlovic, A., Waggott, D., Sharma, A., Yeung, A., Christle, J. W., Wheeler, M. T., McConnell, M. V., Harrington, R. A., Ashley, E. A. 2019; 1 (7): E344–E352

  View details for DOI 10.1016/S2589-7500(19)30129-3

  View details for Web of Science ID 000525872200012

• The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study. The Lancet. Digital health Shcherbina, A., Hershman, S. G., Lazzeroni, L., King, A. C., O'Sullivan, J. W., Hekler, E., Moayedi, Y., Pavlovic, A., Waggott, D., Sharma, A., Yeung, A., Christle, J. W., Wheeler, M. T., McConnell, M. V., Harrington, R. A., Ashley, E. A. 2019; 1 (7): e344-e352

  Abstract

  Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study.In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321.Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p<0·0001), 267 steps (74) for participants in the hourly stand prompt group (p=0·0003), 254 steps (74) for participants in the cluster-specific prompts group (p=0·0006), and by 226 steps (75) for participants in the 10 000 daily step prompt group (p=0·0026 vs baseline).Four smartphone-based physical activity coaching interventions significantly increased daily physical activity. These findings suggests that digital interventions delivered via a mobile app have the ability to increase short-term physical activity levels in a free-living cohort.Stanford Data Science Initiative.

  View details for DOI 10.1016/S2589-7500(19)30129-3

  View details for PubMedID 33323209

• Network meta-analysis for diagnostic tests BMJ EVIDENCE-BASED MEDICINE O'Sullivan, J. W. 2019; 24 (5): 192–93

  View details for DOI 10.1136/bmjebm-2019-111179

  View details for Web of Science ID 000599817800018

• Aspirin for the primary prevention of cardiovascular disease in the elderly BMJ EVIDENCE-BASED MEDICINE O'Sullivan, J. W. 2019; 24 (4): 143–44

  View details for DOI 10.1136/bmjebm-2018-111138

  View details for Web of Science ID 000599816400008

• Prevention of cardiovascular disease and renal failure in type 2 diabetes: sodium-glucose cotransporter-2 (SGLT2) inhibitors. BMJ evidence-based medicine O'Sullivan, J. W. 2019

  View details for DOI 10.1136/bmjebm-2019-111231

  View details for PubMedID 31366588

• Introducing the EBM Verdict: research evidence relevant to clinical practice BMJ EVIDENCE-BASED MEDICINE Heneghan, C., Brassey, J., Aronson, J., O'Sullivan, J. 2019; 24 (3): 85–86

  View details for DOI 10.1136/bmjebm-2019-111172

  View details for Web of Science ID 000599815000001

• Network meta-analysis for diagnostic tests. BMJ evidence-based medicine O'Sullivan, J. W. 2019

  View details for PubMedID 30975716

• Aspirin for the primary prevention of cardiovascular disease in the elderly. BMJ evidence-based medicine O'Sullivan, J. W. 2019

  View details for PubMedID 30733220

• Introducing the EBM Verdict: research evidence relevant to clinical practice. BMJ evidence-based medicine Heneghan, C., Brassey, J., Aronson, J., O'Sullivan, J. W. 2019

  View details for PubMedID 30700435

• Temporal trends in use of tests in UK primary care, 2000-15: retrospective analysis of 250 million tests. BMJ (Clinical research ed.) O'Sullivan, J. W., Stevens, S., Hobbs, F. D., Salisbury, C., Little, P., Goldacre, B., Bankhead, C., Aronson, J. K., Perera, R., Heneghan, C. 2018; 363: k4666

  Abstract

  OBJECTIVES: To assess the temporal change in test use in UK primary care and to identify tests with the greatest increase in use.DESIGN: Retrospective cohort study.SETTING: UK primary care.PARTICIPANTS: All patients registered to UK General Practices in the Clinical Practice Research Datalink, 2000/1 to 2015/16.MAIN OUTCOME MEASURES: Temporal trends in test use, and crude and age and sex standardised rates of total test use and of 44 specific tests.RESULTS: 262974099 tests were analysed over 71436331 person years. Age and sex adjusted use increased by 8.5% annually (95% confidence interval 7.6% to 9.4%); from 14869 tests per 10000 person years in 2000/1 to 49267 in 2015/16, a 3.3-fold increase. Patients in 2015/16 had on average five tests per year, compared with 1.5 in 2000/1. Test use also increased statistically significantly across all age groups, in both sexes, across all test types (laboratory, imaging, and miscellaneous), and 40 of the 44 tests that were studied specifically.CONCLUSION: Total test use has increased markedly over time, in both sexes, and across all age groups, test types (laboratory, imaging, and miscellaneous) and for 40 of 44 tests specifically studied. Of the patients who underwent at least one test annually, the proportion who had more than one test increased significantly over time.

  View details for PubMedID 30487169

• Temporal trends in use of tests in UK primary care, 2000-15: retrospective analysis of 250 million tests BMJ-BRITISH MEDICAL JOURNAL O'Sullivan, J. W., Stevens, S., Hobbs, F., Salisbury, C., Little, P., Goldacre, B., Bankhead, C., Aronson, J. K., Perera, R., Heneghan, C. 2018; 363

  View details for DOI 10.1136/bmj.k4666

  View details for Web of Science ID 000452127500001

• Prevalence and outcomes of incidental imaging findings: umbrella review BMJ-BRITISH MEDICAL JOURNAL O'Sullivan, J. W., Muntinga, T., Grigg, S., Ioannidis, J. A. 2018; 361: k2387

  Abstract

  To provide an overview of the evidence on prevalence and outcomes of incidental imaging findings.Umbrella review of systematic reviews.Searches of MEDLINE, EMBASE up to August 2017; screening of references in included papers.Criteria included systematic reviews and meta-analyses of observational studies that gave a prevalence of incidental abnormalities ("incidentalomas"). An incidental imaging finding was defined as an imaging abnormality in a healthy, asymptomatic patient or an imaging abnormality in a symptomatic patient, where the abnormality was not apparently related to the patient's symptoms. Primary studies that measured the prevalence of incidentalomas in patients with a history of malignancy were also considered in sensitivity analyses.20 systematic reviews (240 primary studies) were identified from 7098 references from the database search. Fifteen systematic reviews provided data to quantify the prevalence of incidentalomas, whereas 18 provided data to quantify the outcomes of incidentalomas (13 provided both). The prevalence of incidentalomas varied substantially between imaging tests; it was less than 5% for chest computed tomography for incidental pulmonary embolism in patients with and without cancer and whole body positron emission tomography (PET) or PET/computed tomography (for patients with and without cancer). Conversely, incidentalomas occurred in more than a third of images in cardiac magnetic resonance imaging (MRI), chest computed tomography (for incidentalomas of thorax, abdomen, spine, or heart), and computed tomography colonoscopy (for extra-colonic incidentalomas). Intermediate rates occurred with MRI of the spine (22%) and brain (22%). The rate of malignancy in incidentalomas varied substantially between organs; the prevalence of malignancy was less than 5% in incidentalomas of the brain, parotid, and adrenal gland. Extra-colonic, prostatic, and colonic incidentalomas were malignant between 10% and 20% of the time, whereas renal, thyroid, and ovarian incidentalomas were malignant around a quarter of the time. Breast incidentalomas had the highest percentage of malignancy (42%, 95% confidence interval 31% to 54%). Many assessments had high between-study heterogeneity (15 of 20 meta-analyses with I2 >50%).There is large variability across different imaging techniques both in the prevalence of incidentalomas and in the prevalence of malignancy for specific organs. This umbrella review will aid clinicians and patients weigh up the pros and cons of requesting imaging scans and will help with management decisions after an incidentaloma diagnosis. Our results can underpin the creation of guidelines to assist these decisions.PROSPERO: CRD42017075679.

  View details for PubMedID 29914908