scholarly journals Generalisability of Results from UK Biobank: Comparison With a Pooling of 18 Cohort Studies

2019 ◽  
Author(s):  
G. David Batty ◽  
Catharine R. Gale ◽  
Mika Kivimäki ◽  
Ian J. Deary ◽  
Steven Bell
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Health Surveys ◽  
Response Rate ◽  
P Value ◽  
Uk Biobank ◽  
Individual Level ◽  
Hazard Ratios ◽  
Nationally Representative ◽  
The Uk

AbstractBackgroundThe UK Biobank cohort study has become a much-utilised and influential scientific resource. With a primary goal of understanding disease aetiology, the low response to the original survey of 5.5% has, however, led to debate as to the generalisability of these findings. We therefore compared risk factor–disease estimations in UK Biobank with those from 18 nationally representative studies with conventional response rates.MethodsWe used individual-level baseline data from UK Biobank (N=502,655) and a pooling of data from the Health Surveys for England (HSE) and the Scottish Health Surveys (SHS), comprising 18 studies and 89,895 individuals (mean response rate 68%). Both study populations were aged 40-69 years at study induction and linked to national cause-specific mortality registries.FindingsDespite a typically more favourable risk factor profile and lower mortality rates in UK Biobank participants relative to the HSE-SHS consortium, risk factors–endpoints associations were directionally consistent between studies, albeit with some heterogeneity in magnitude. For instance, for cardiovascular disease mortality, the age- and sex-adjusted hazard ratio (95% confidence interval) for ever having smoked cigarettes (versus never) was 2.04 (1.87, 2.24) in UK Biobank and 1.99 (1.78, 2.23) in HSE-SHS, yielding a ratio of hazard ratios close to unity (1.02, 0.88, 1.19; p-value 0.76). For hypertension (versus none), corresponding results were again in same direction but with a lower effect size in UK Biobank (1.89; 1.69, 2.11) than in HSE-SHS (2.56; 2.20, 2.98), producing a ratio of hazard ratios below unity (0.74; 0.62, 0.89; p-value 0.001). A similar pattern of observations were made for risk factors (smoking, obesity, educational attainment, and physical stature) in relation to different cancer presentations and suicide whereby the ratios of hazard ratios ranged from 0.57 (0.40, 0.81) and 1.07 (0.42, 2.74).InterpretationDespite a low response rate, aetiological findings from UK Biobank appear to be generalisable to England and Scotland.

scholarly journals Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

BMJ ◽  
2020 ◽  
pp. m131 ◽  
Author(s):  
G David Batty ◽  
Catharine R Gale ◽  
Mika Kivimäki ◽  
Ian J Deary ◽  
Steven Bell
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Cohort Study ◽  
Health Surveys ◽  
Response Rate ◽  
Meta Analysis ◽  
Uk Biobank ◽  
Hazard Ratios ◽  
Individual Participant

AbstractObjectiveTo compare established associations between risk factors and mortality in UK Biobank, a study with an exceptionally low rate of response to its baseline survey, against those from representative studies that have conventional response rates.DesignProspective cohort study alongside individual participant meta-analysis of other cohort studies.SettingUnited Kingdom.ParticipantsAnalytical sample of 499 701 people (response rate 5.5%) in analyses in UK Biobank; pooled data from the Health Surveys for England (HSE) and the Scottish Health Surveys (SHS), including 18 studies and 89 895 people (mean response rate 68%). Both study populations were linked to the same nationwide mortality registries, and the baseline age range was aligned at 40-69 years.Main outcome measureDeath from cardiovascular disease, selected malignancies, and suicide. To quantify the difference between hazard ratios in the two studies, a ratio of the hazard ratios was used with HSE-SHS as the referent.ResultsRisk factor levels and mortality rates were typically more favourable in UK Biobank participants relative to the HSE-SHS consortium. For the associations between risk factors and mortality endpoints, however, close agreement was seen between studies. Based on 14 288 deaths during an average of 7.0 years of follow-up in UK Biobank and 7861 deaths over 10 years of mortality surveillance in HSE-SHS, for cardiovascular disease mortality, for instance, the age and sex adjusted hazard ratio for ever having smoked cigarettes (versus never) was 2.04 (95% confidence interval 1.87 to 2.24) in UK Biobank and 1.99 (1.78 to 2.23) in HSE-SHS, yielding a ratio of hazard ratios close to unity (1.02, 0.88 to 1.19). The overall pattern of agreement between studies was essentially unchanged when results were compared separately by sex and when baseline years and censoring dates were aligned.ConclusionDespite a very low response rate, risk factor associations in the UK Biobank seem to be generalisable.

scholarly journals Age- and sex-specific modifiable risk factor profiles of dementia: evidence from the UK Biobank

2021 ◽  
Author(s):  
Hui Chen ◽  
Yaying Cao ◽  
Yuan Ma ◽  
Geng Zong ◽  
Changzheng Yuan
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Alcohol Intake ◽  
Health Condition ◽  
Modifiable Risk Factors ◽  
Uk Biobank ◽  
Younger Adults ◽  
Moderate Alcohol Intake ◽  
The Uk ◽  
Age And Sex

Abstract Background: To inform targeted preventive strategies of dementia, systematic investigation in its age- and sex-specific modifiable risk factor profiles in the general adult population is warranted.Methods: We used data of 372,867 adults free from dementia at baseline (2006-2010) in the UK Biobank, and followed them up until March 2021. We assigned participants into five groups according to their age and into two groups according to their sex. We estimated the age- and sex-specific hazard ratios (HRs) using Cox proportional hazard models and calculated the corresponding population attributable fractions (PAFs) for dementia attributable to three major categories of modifiable risk factors, including socioeconomic (low education level, high Townsend deprivation index), lifestyle (non-moderate alcohol intake, current smoking, suboptimal diet, non-regular physical exercise, and sleep duration <=6 or >=8 hrs/d), and health condition (hypertension, diabetes, cardiovascular diseases, and depressive symptom) risk factors.Findings: During 4,338,030 person-years of follow-up, 113, 146, 360, 1,087, and 2,002 of participants across five increasing age groups (40-<50, 50-<55, 55-<60, 60-<65, or >=65 y), respectively, were newly diagnosed with dementia. Five out of eleven modifiable risk factors showed significantly stronger associations with dementia among younger adults than in relatively older adults (P-interactions < 0.05), including non-moderate alcohol intake (HR [95% confidence interval, CI]=1.90 [1.35, 2.68] for participants 50-<55 y vs. 1.22 [1.11, 1.35] for participants > 65 y), suboptimal diet (1.86 [1.26, 2.74] for participants 40-< 50 y vs. 0.96 [0.86, 1.06] for participants > 65 y), hypertension (1.52 [0.96, 2.42] vs. 1.08 [0.99, 1.19]), CVD (4.20 [2.15, 8.22] vs. 1.64 [1.45, 1.85]), and diabetes (3.09 [1.60, 6.00] vs. 1.73 [1.51, 2.00]). We observed no significant difference in dementia risk factor profiles between women and men. Dementia cases attributable to three categories of risk factors all decreased with age, with the PAFs (95% CI) for sociodemographic, lifestyle, and health condition risk factors being 52.56% (22.98%, 82.15%), 46.57% (8.08%, 85.06%), and 35.42% (24.09%, 46.75%) for participants aged 40-<50 y, and 12.29% (3.82%, 20.75%), 13.01% (2.53%, 23.49%), and 15.85% (11.81%, 19.90%) for those over 65 y.Interpretation: This study identified stronger association and greater attributable risk of several modifiable risk factors for dementia among younger adults, underscoring the importance of preventive strategies from an earlier age across adult life course to reduce the risk of dementia.

scholarly journals What Proportion of Cancers in the UK and Its Constituent Countries Could Be Prevented? An Updated Analysis

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 25s-25s
Author(s):  
K. Brown ◽  
H. Rumgay ◽  
C. Dunlop ◽  
M. Ryan ◽  
F. Quartly ◽  
...  
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Risk Factor ◽  
Health Policy ◽  
Cancer Risk ◽  
Public Health Policy ◽  
Cancer Risk Factors ◽  
Cancer Types ◽  
Nationally Representative ◽  
The Uk

Background: Understanding population-level exposure to cancer risk factors is vital when devising risk-reduction policies. By reducing exposure to cancer risk factors, many cancers could be prevented. But what impact on cancer incidence do these risk factors have? And what proportion of cancers could be prevented if these risk factors are avoided? Aim: The aim of this analysis was to update the estimates of the number and proportion of theoretically preventable cancers in the UK to reflect the changing behavior as assessed in representative national surveys, and new epidemiologic evidence. Separate estimates were also calculated for England, Wales, Scotland, and Northern Ireland because prevalence of risk factor exposure varies between them. Methods: Population attributable fractions (PAFs) were calculated for combinations of risk factor and cancer type with sufficient/convincing evidence of a causal association. Relative risks (RRs) were drawn from meta-analyses of cohort studies where possible. Prevalence of exposure to risk factors was obtained from nationally representative population surveys. Cancer incidence data for 2015 were sourced from national data releases and, where needed, personal communications. Results: Around four in ten (38%) cancer cases in 2015 in the UK were attributable to known risk factors. The proportion was around two percentage points higher in UK males (39%) than UK females (37%). Comparing UK countries, the attributable proportion for persons was highest in Scotland (41%) and lowest in England (37%). Tobacco smoking contributed by far the largest proportion of attributable cancer cases, followed by overweight and obesity, accounting for 15% and 6%, respectively, of all cases in the UK in 2015. Conclusion: Around four in ten (38%) cancer cases in the UK could be prevented. Tobacco and obesity remain the top contributors of attributable cancer cases. Tobacco smoking has the highest PAF because it greatly increases cancer risk and has a large number of cancer types associated with it. Obesity has the second-highest PAF because it affects a high proportion of the UK population and is also linked with many cancer types. Public health policy may seek to reduce the level of harm associated with exposure or reduce exposure levels - both approaches may be effective in preventing cancer. The variation in PAFs between UK countries is affected by sociodemographic differences which drive differences in exposure to theoretically avoidable 'lifestyle' factors. PAFs at UK country level have not been available previously and they should be used by policymakers in the devolved nations to develop more targeted public health measures. This analysis demonstrates the importance of nationally representative exposure prevalence data and cancer registration in informing evidence-based public health policy.

scholarly journals Calcification of abdominal aorta is an underappreciated cardiovascular disease risk factor

2020 ◽  
Author(s):  
Anurag Sethi ◽  
Leland Taylor ◽  
J Graham Ruby ◽  
Jagadish Venkataraman ◽  
Madeleine Cule ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Disease Risk ◽  
Cardiovascular Outcomes ◽  
Whole Body ◽  
Uk Biobank ◽  
Clinical Biomarkers ◽  
Wide Range ◽  
The Uk

AbstractBackgroundCalcification of the abdominal artery is an important contributor to cardiovascular disease in diabetic and chronic kidney disease (CKD) populations. However, prevalence of the pathology, risk factors, and long term disease outcomes in a general population have not been systematically analyzed.MethodWe developed machine learning models to quantify levels of abdominal aortic calcification (AAC) in 29,957 whole body dual-energy X-ray absorptiometry (DEXA) scans from the UK Biobank cohort. Using regression techniques we associated severity of calcification across a wide range of physiological parameters, clinical biomarkers, and environmental risk factors (406 in total). We performed a common variant genetic association study spanning 9,572,557 single-nucleotide polymorphisms to identify genetic loci relevant to AAC. We evaluated the prognostic value of AAC across 151 disease classes using Cox proportional hazard models. We further examined an epidemiological model of calcification on cardiovascular morbidity with and without LDL interactions.FindingsWe find evidence for AAC in >10.4% of the cohort despite low prevalence of diabetes (2.5%) and CKD (0.5%). Increased level of AAC is a strong prognostic indicator of cardiovascular outcomes for stenosis of precerebral arteries (HR~1.5), Myocardial Infarction (HR~1.5), & Ischemic Heart Disease (HR~1.33). We find that AAC is genetically correlated with cardiovascular-related traits and that the genetic signals are enriched in vascular and adipose tissue. We report three loci associated with AAC, with the strongest association occuring at the TWIST1/HDAC9 locus (beta=0.078, p-value=1.4e-11) in a region also associated with coronary artery disease. Surprisingly, we find that elevated but still within clinically normal levels of serum phosphate and glycated hemoglobin are linked to increased vascular calcification. Furthermore, we show AAC arises in the absence of hypercholesterolemia. By our estimate, AAC is an LDL-independent risk factor for cardiovascular outcomes, with risk similar to elevated LDL.DataThis research has been conducted using the UK Biobank Resource.

scholarly journals 699 Sleep Health Traits and COVID-19: Mortality Risk from the UK Biobank

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A273-A273
Author(s):  
Xi Zheng ◽  
Ma Cherrysse Ulsa ◽  
Peng Li ◽  
Lei Gao ◽  
Kun Hu
Keyword(s):  
Risk Factors ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Sex Education ◽  
Mortality Risk ◽  
Self Report ◽  
Severe Illness ◽  
Uk Biobank ◽  
Sleep Health ◽  
The Uk

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (&gt;9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

scholarly journals Sex differences in the association between major cardiovascular risk factors in midlife and dementia: a cohort study using data from the UK Biobank

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jessica Gong ◽  
Katie Harris ◽  
Sanne A. E. Peters ◽  
Mark Woodward
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Sex Differences ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Sex Difference ◽  
Incidence Rates ◽  
Cox Proportional Hazards ◽  
Uk Biobank ◽  
The Uk

Abstract Background Sex differences in major cardiovascular risk factors for incident (fatal or non-fatal) all-cause dementia were assessed in the UK Biobank. The effects of these risk factors on all-cause dementia were explored by age and socioeconomic status (SES). Methods Cox proportional hazards models were used to estimate hazard ratios (HRs) and women-to-men ratio of HRs (RHR) with 95% confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP), smoking, diabetes, adiposity, stroke, SES and lipids with dementia. Poisson regression was used to estimate the sex-specific incidence rate of dementia for these risk factors. Results 502,226 individuals in midlife (54.4% women, mean age 56.5 years) with no prevalent dementia were included in the analyses. Over 11.8 years (median), 4068 participants (45.9% women) developed dementia. The crude incidence rates were 5.88 [95% CI 5.62–6.16] for women and 8.42 [8.07–8.78] for men, per 10,000 person-years. Sex was associated with the risk of dementia, where the risk was lower in women than men (HR = 0.83 [0.77–0.89]). Current smoking, diabetes, high adiposity, prior stroke and low SES were associated with a greater risk of dementia, similarly in women and men. The relationship between blood pressure (BP) and dementia was U-shaped in men but had a dose-response relationship in women: the HR for SBP per 20 mmHg was 1.08 [1.02–1.13] in women and 0.98 [0.93–1.03] in men. This sex difference was not affected by the use of antihypertensive medication at baseline. The sex difference in the effect of raised BP was consistent for dementia subtypes (vascular dementia and Alzheimer’s disease). Conclusions Several mid-life cardiovascular risk factors were associated with dementia similarly in women and men, but not raised BP. Future bespoke BP-lowering trials are necessary to understand its role in restricting cognitive decline and to clarify any sex difference.

Variation of cardiac magnetic resonance radiomics features by age and sex in healthy participants from the UK Biobank

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
Z Raisi-Estabragh ◽  
A Jaggi ◽  
N Aung ◽  
S Neubauer ◽  
S Piechnik ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiac Magnetic Resonance ◽  
Age Groups ◽  
Texture Features ◽  
Funding Source ◽  
Uk Biobank ◽  
Men And Women ◽  
The Uk ◽  
Age And Sex ◽  
Apparently Healthy

Abstract Introduction Cardiac magnetic resonance (CMR) radiomics use voxel-level data to derive quantitative indices of myocardial tissue texture, which may provide complementary risk information to traditional CMR measures. Purpose In this first stage of our work, establishing the performance characteristics of CMR radiomics in relation to disease outcomes, we aimed to elucidate differences in radiomic features by sex and age in apparently healthy adults. Methods We defined a healthy cohort from the first 5,065 individuals completing the UK Biobank Imaging Enhancement, limiting to white Caucasian ethnicity, and excluding those with major co-morbidities, or cardiovascular risk factors/symptoms. We created evenly distributed age groups: 45–54 years, 55–64 years, 65–74 years. Radiomics features were extracted from left ventricle segmentations, with normalisation to body surface area. We compared mean values of individual features between the sexes, stratified by age and separately between the oldest and youngest age groups for each sex. Results We studied 657 (309 men, 358 women) healthy individuals. There were significant differences between radiomics features of men and women. Different features appeared more important at different age groups. For instance, in the youngest age group “end-systolic coarseness” showed greatest difference between men and women, whilst “end-diastolic run percentage” and “end-diastolic high grey level emphasis” showed most variation in the oldest and middle age groups. In the oldest age groups, differences between men and women were most predominant in the texture features, whilst in the younger groups a mixture of shape and texture differences were observed. We demonstrate significant variation between radiomics features by age, these differences are exclusively in texture features with different features implicated in men and women (“end-diastolic mean intensity” in women, “end-systolic sum entropy in men”). Conclusions There are significant age and sex differences in CMR radiomics features of apparently healthy adults, demonstrating alterations in myocardial architecture not appreciated by conventional indices. In younger ages, shape and texture differences are observed, whilst in older ages texture differences dominate. Furthermore, texture features are the most different features between the youngest and oldest hearts. We provide proof-of-concept data indicating CMR radiomics has discriminatory value with regard to two characteristics strongly linked to cardiovascular outcomes. We will next elucidate relationships between CMR radiomics, cardiac risk factors, and clinical outcomes, establishing predictive value incremental to existing measures. Funding Acknowledgement Type of funding source: Other. Main funding source(s): European Union's Horizon 2020 research and innovation programme (825903),British Heart Foundation Clinical Research Training Fellowship (FS/17/81/33318)

scholarly journals Sex differences in risk factors for myocardial infarction: cohort study of UK Biobank participants

BMJ ◽  
2018 ◽  
pp. k4247 ◽  
Author(s):  
Elizabeth R C Millett ◽  
Sanne A E Peters ◽  
Mark Woodward
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Blood Pressure ◽  
Type 1 Diabetes ◽  
Sex Differences ◽  
Confidence Interval ◽  
Systolic Blood Pressure ◽  
Uk Biobank ◽  
Hazard Ratios

AbstractObjectivesTo investigate sex differences in risk factors for incident myocardial infarction (MI) and whether they vary with age.DesignProspective population based study.SettingUK Biobank.Participants471 998 participants (56% women; mean age 56.2) with no history of cardiovascular disease.Main outcome measureIncident (fatal and non-fatal) MI.Results5081 participants (1463 (28.8%) of whom were women) had MI over seven years’ mean follow-up, resulting in an incidence per 10 000 person years of 7.76 (95% confidence interval 7.37 to 8.16) for women and 24.35 (23.57 to 25.16) for men. Higher blood pressure indices, smoking intensity, body mass index, and the presence of diabetes were associated with an increased risk of MI in men and women, but associations were attenuated with age. In women, systolic blood pressure and hypertension, smoking status and intensity, and diabetes were associated with higher hazard ratios for MI compared with men: ratio of hazard ratios 1.09 (95% confidence interval 1.02 to 1.16) for systolic blood pressure, 1.55 (1.32 to 1.83) for current smoking, 2.91 (1.56 to 5.45) for type 1 diabetes, and 1.47 (1.16 to 1.87) for type 2 diabetes. There was no evidence that any of these ratios of hazard ratios decreased with age (P>0.2). With the exception of type 1 diabetes, the incidence of MI was higher in men than in women for all risk factors.ConclusionsAlthough the incidence of MI was higher in men than in women, several risk factors were more strongly associated with MI in women compared with men. Sex specific associations between risk factors and MI declined with age, but, where it occurred, the higher relative risk in women remained. As the population ages and the prevalence of lifestyle associated risk factors increase, the incidence of MI in women will likely become more similar to that in men.

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

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