scholarly journals Corrigendum to: Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank

Biostatistics ◽  
2021 ◽  
Author(s):  
Ruilin Li ◽  
Christopher Chang ◽  
Johanne M Justesen ◽  
Yosuke Tanigawa ◽  
Junyang Qian ◽  
...  
Keyword(s):  
Large Scale ◽  
Cox Model ◽  
Uk Biobank ◽  
Lasso Method

scholarly journals Fast Lasso method for Large-scale and Ultrahigh-dimensional Cox Model with applications to UK Biobank

2020 ◽  
Author(s):  
Ruilin Li ◽  
Christopher Chang ◽  
Johanne Marie Justesen ◽  
Yosuke Tanigawa ◽  
Junyang Qian ◽  
...  
Keyword(s):  
Large Scale ◽  
Likelihood Function ◽  
Cox Model ◽  
Partial Likelihood ◽  
Parameter Estimates ◽  
Proportional Hazard ◽  
Uk Biobank ◽  
Cox Proportional Hazard ◽  
The Uk ◽  
Lasso Method

AbstractWe develop a scalable and highly efficient algorithm to fit a Cox proportional hazard model by maximizing the L1-regularized (Lasso) partial likelihood function, based on the Batch Screening Iterative Lasso (BASIL) method developed in (Qian et al. 2019). The output of our algorithm is the full Lasso path, the parameter estimates at all predefined regularization parameters, as well as their validation accuracy measured using the concordance index (C-index) or the validation deviance. To demonstrate the effectiveness of our algorithm, we analyze a large genotype-survival time dataset across 306 disease outcomes from the UK Biobank (Sudlow et al. 2015). Our approach, which we refer to as snpnet-Cox, is implemented in a publicly available package.

scholarly journals Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank

Biostatistics ◽  
2020 ◽  
Author(s):  
Ruilin Li ◽  
Christopher Chang ◽  
Johanne M Justesen ◽  
Yosuke Tanigawa ◽  
Junyang Qiang ◽  
...  
Keyword(s):  
Large Scale ◽  
Likelihood Function ◽  
Cox Model ◽  
Partial Likelihood ◽  
Parameter Estimates ◽  
Proportional Hazard ◽  
Uk Biobank ◽  
Cox Proportional Hazard ◽  
The Uk ◽  
Lasso Method

Summary We develop a scalable and highly efficient algorithm to fit a Cox proportional hazard model by maximizing the $L^1$-regularized (Lasso) partial likelihood function, based on the Batch Screening Iterative Lasso (BASIL) method developed in Qian and others (2019). Our algorithm is particularly suitable for large-scale and high-dimensional data that do not fit in the memory. The output of our algorithm is the full Lasso path, the parameter estimates at all predefined regularization parameters, as well as their validation accuracy measured using the concordance index (C-index) or the validation deviance. To demonstrate the effectiveness of our algorithm, we analyze a large genotype-survival time dataset across 306 disease outcomes from the UK Biobank (Sudlow and others, 2015). We provide a publicly available implementation of the proposed approach for genetics data on top of the PLINK2 package and name it snpnet-Cox.

S23MACHINE LEARNING METHODS TO PREDICT UNMEASURED PHENOTYPES IN LARGE-SCALE BIOBANK STUDIES: PROOF OF PRINCIPLE USING AUDIT IN THE UK BIOBANK

2019 ◽  
Vol 29 ◽  
pp. S125-S126
Author(s):  
Amanda Gentry ◽  
Roseann Peterson ◽  
Alexis Edwards ◽  
Brien Riley ◽  
B. Todd Webb
Keyword(s):  
Large Scale ◽  
Uk Biobank ◽  
Learning Methods ◽  
The Uk ◽  
Proof Of Principle

scholarly journals Genetic variation in the SIM1 locus is associated with erectile dysfunction

2018 ◽  
Vol 115 (43) ◽  
pp. 11018-11023 ◽  
Author(s):  
Eric Jorgenson ◽  
Navneet Matharu ◽  
Melody R. Palmer ◽  
Jie Yin ◽  
Jun Shan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Erectile Dysfunction ◽  
Sexual Function ◽  
Odds Ratio ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Adult Health ◽  
Uk Biobank ◽  
Melanocortin System ◽  
The Uk

Erectile dysfunction affects millions of men worldwide. Twin studies support the role of genetic risk factors underlying erectile dysfunction, but no specific genetic variants have been identified. We conducted a large-scale genome-wide association study of erectile dysfunction in 36,649 men in the multiethnic Kaiser Permanente Northern California Genetic Epidemiology Research in Adult Health and Aging cohort. We also undertook replication analyses in 222,358 men from the UK Biobank. In the discovery cohort, we identified a single locus (rs17185536-T) on chromosome 6 near the single-minded family basic helix-loop-helix transcription factor 1 (SIM1) gene that was significantly associated with the risk of erectile dysfunction (odds ratio = 1.26, P = 3.4 × 10−25). The association replicated in the UK Biobank sample (odds ratio = 1.25, P = 6.8 × 10−14), and the effect is independent of known erectile dysfunction risk factors, including body mass index (BMI). The risk locus resides on the same topologically associating domain as SIM1 and interacts with the SIM1 promoter, and the rs17185536-T risk allele showed differential enhancer activity. SIM1 is part of the leptin–melanocortin system, which has an established role in body weight homeostasis and sexual function. Because the variants associated with erectile dysfunction are not associated with differences in BMI, our findings suggest a mechanism that is specific to sexual function.

scholarly journals Large-scale analysis of iliopsoas muscle volumes in the UK Biobank

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Julie A. Fitzpatrick ◽  
Nicolas Basty ◽  
Madeleine Cule ◽  
Yi Liu ◽  
Jimmy D. Bell ◽  
...  
Keyword(s):  
Large Scale ◽  
Large Population ◽  
Psoas Muscle ◽  
Magnetic Resonance Images ◽  
Muscle Volume ◽  
Iliopsoas Muscle ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Automated Method ◽  
The Uk

AbstractPsoas muscle measurements are frequently used as markers of sarcopenia and predictors of health. Manually measured cross-sectional areas are most commonly used, but there is a lack of consistency regarding the position of the measurement and manual annotations are not practical for large population studies. We have developed a fully automated method to measure iliopsoas muscle volume (comprised of the psoas and iliacus muscles) using a convolutional neural network. Magnetic resonance images were obtained from the UK Biobank for 5000 participants, balanced for age, gender and BMI. Ninety manual annotations were available for model training and validation. The model showed excellent performance against out-of-sample data (average dice score coefficient of 0.9046 ± 0.0058 for six-fold cross-validation). Iliopsoas muscle volumes were successfully measured in all 5000 participants. Iliopsoas volume was greater in male compared with female subjects. There was a small but significant asymmetry between left and right iliopsoas muscle volumes. We also found that iliopsoas volume was significantly related to height, BMI and age, and that there was an acceleration in muscle volume decrease in men with age. Our method provides a robust technique for measuring iliopsoas muscle volume that can be applied to large cohorts.

scholarly journals Mendelian randomization to evaluate the effect of plasma vitamin C levels on the risk of Alzheimer’s disease

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Haijie Liu ◽  
Yan Zhang ◽  
Yang Hu ◽  
Haihua Zhang ◽  
Tao Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vitamin C ◽  
Cognitive Performance ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Plasma Vitamin ◽  
Causal Association ◽  
Uk Biobank ◽  
Gwas Dataset

Abstract Objective Until now, observational studies have explored the impact of vitamin C intake on Alzheimer’s disease (AD) risk, however, reported ambiguous findings. To develop effective therapies or prevention, the causal link between vitamin C levels and AD should be established. Methods Here, we selected 11 plasma vitamin C genetic variants from a large-scale plasma vitamin C GWAS dataset (N = 52,018) as the potential instrumental variables. We extracted their corresponding summary statistics from large-scale IGAP clinically diagnosed AD GWAS dataset (N = 63,926) and UK Biobank AD proxy phenotype GWAS dataset (N = 314,278), as well as two UK Biobank subgroups including the maternal AD group (27,696 cases of maternal AD and 260,980 controls) and paternal AD group (14,338 cases of paternal AD and 245,941 controls). We then performed a Mendelian randomization (MR) study to evaluate the causal association between plasma vitamin C levels and the risk of AD and AD proxy phenotype. Meanwhile, we further verified these findings using a large-scale cognitive performance GWAS dataset (N = 257,841). Results In IGAP, we found no significant causal association between plasma vitamin C levels and the risk of AD. In UK Biobank, we found that per 1 SD increase in plasma vitamin C levels (about 20.2 μmol/l) was significantly associated with the reduced risk of AD proxy phenotype (OR = 0.93, 95% CI 0.88–0.98, P = 7.00E−03). A subgroup MR analysis in UK Biobank indicated that per 1 SD increase in plasma vitamin C levels could significantly reduce the risk of AD proxy phenotype in the maternal AD group (OR = 0.89, 95% CI 0.84–0.94, P = 7.29E−05), but not in the paternal AD group (OR = 1.02, 95% CI 0.92–1.12, P = 7.59E−01). The leave-one-out permutation further showed that the SLC23A1 rs33972313 variant largely changed the precision of the overall MR estimates in all these four GWAS datasets. Meanwhile, we did not observe any significant causal effect of plasma vitamin C levels on the cognitive performance. Conclusion We demonstrated that there may be no causal association between plasma vitamin C levels and the risk of AD in people of European descent. The insistent findings in clinically diagnosed AD and AD proxy phenotype may be caused by the phenotypic heterogeneity.

scholarly journals Lack of evidence for interactions between APOE and Klotho genotypes on cognitive, dementia and brain imaging metrics in UK Biobank

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Daniel J. Smith ◽  
Kristin E. Flegal ◽  
Donald M. Lyall
Keyword(s):  
Cognitive Impairment ◽  
Brain Imaging ◽  
Brain Structure ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Cognitive Test ◽  
Uk Biobank ◽  
Type 1 Error ◽  
Structural Brain

AbstractImportanceRecent research has suggested that genetic variation in the Klotho (KL) locus may modify the association between apolipoprotein e (APOE) e4 genotype and cognitive impairment.ObjectiveLarge-scale testing for associations and interactions between KL and APOE genotypes vs. risk of dementia (n=1,570 cases), cognitive abilities (n=174,513) and brain structure (n = 13,158) in older (60+ years) participants.Design, setting and participantsCross-sectional and prospective data (UK Biobank).Main outcomes and measuresKL status was indexed with heterozygosity of the rs9536314 polymorphism (vs. not), in unrelated people with vs. without APOE e4 genotype, using regression and interaction tests. We assessed non-demented cognitive scores (processing speed; reasoning; memory; executive function), multiple structural brain imaging, and clinical dementia outcomes. All tests were corrected for age, sex, assessment centre, eight principal components for population stratification, genotypic array, smoking history, deprivation, and self-reported medication history.ResultsAPOE e4 presence (vs. not) was associated with increased risk of dementia, worse cognitive abilities and brain structure differences. KL heterozygosity was associated with less frontal lobe grey matter. There were no significant APOE/KL interactions for cognitive, dementia or brain imaging measures (all P>0.05).Conclusions and relevanceWe found no evidence of APOE/KL interactions on cognitive, dementia or brain imaging outcomes. This could be due to some degree of cognitive test imprecision, generally preserved participant health potentially due to relatively young age, type-1 error in prior studies, or indicative of a significant age-dependent KL effect only in the context of marked AD pathology.Key pointsQuestion: Klotho genotype has been previously shown to ‘offset’ a substantial amount of the APOE e4/cognitive impairment association. Is this modification effect apparent in large-scale independent data, in terms of non-demented cognitive abilities, brain structure and dementia prevalence?Findings: In aged 60 years and above participants from UK Biobank, we found significant associations of APOE and Klotho genotypes on cognitive, structural brain and dementia outcomes, but no significant interactions.Meaning: This could reflect somewhat healthy participants, prior type 1 error or cognitive/dementia ascertainment imprecision, and/or that Klotho genotypic effects are age and neuropathology dependent.

scholarly journals Polynomial Mendelian Randomization reveals widespread non-linear causal effects in the UK Biobank

2021 ◽  
Author(s):  
Jonathan Sulc ◽  
Jenny Sjaarda ◽  
Zoltan Kutalik
Keyword(s):  
Causal Inference ◽  
Large Scale ◽  
Causal Effect ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Individual Level ◽  
Glucose Levels ◽  
Causal Function ◽  
The Uk

Causal inference is a critical step in improving our understanding of biological processes and Mendelian randomisation (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here we propose PolyMR, an MR-based method which provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes and found most of these (84%) to have causal effects which deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g. a 1 kg/m2 change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g. the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.

scholarly journals A high number of diseases and consultations: a warning signal for GPs when following up a multimorbid patient

2019 ◽  
Author(s):  
Paul Aujoulat ◽  
Patrice NABBE ◽  
Sophie LALANDE ◽  
Delphine LE GOFF ◽  
Jeremy DERRIENIC ◽  
...  
Keyword(s):  
Risk Factors ◽  
Primary Care ◽  
Large Scale ◽  
Cox Model ◽  
Warning Signal ◽  
Research Network ◽  
P Value ◽  
Patients At Risk ◽  
Definition Of

Abstract Background: the European General Practitioners Research Network (EGPRN) designed and validated a comprehensive definition of multimorbidity using a systematic literature review and qualitative research throughout Europe. Detecting risk factors for decompensation would be an interesting challenge for family physicians (FPs) in the management of multimorbid patients. The purpose of the survey was to assess which items belonging to the EGPRN multimorbidity definition could help to identify patients at risk of decompensation in a cohort pilot study over a 24-month follow-up among primary care outpatients. Method : 131 patients meeting the multimorbidity definition were included using two inclusion periods between 2014 and 2015. Over a 24-month follow-up, the « decompensation » or « nothing to report » status was collected. A logistic regression, following a Cox model, was then performed to identify risk factors for decompensation. Results : After 24 months of follow-up, 120 patients were analyzed. 3 clusters were identified. 44 patients, representing 36.6 % of the population, were still alive and had not been hospitalized for a period exceeding 6 days. Two variables were significantly linked to decompensation: the number of visits to the FP per year (HR 1.06, IC 95 %, 1,03-1,10, p-value <0,001) and the total number of diseases (HR 1,12, IC 95 %, 1,013-1,33, p-value = 0,039). Conclusion: FPs should be aware that a high number of consultations and a high total number of diseases are linked to severe outcomes such as death or unplanned hospitalization. A large-scale cohort in primary care seems feasible to confirm these results.

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