scholarly journals The Association of Serum Lipid and Lipoprotein Levels with Total and Differential Leukocyte Counts: Results of a Cross-sectional and Longitudinal Analysis of the UK Biobank

2020 ◽  
Author(s):  
Bradley Tucker ◽  
Sonia Sawant ◽  
Hannah McDonald ◽  
Kerry-Anne Rye ◽  
Sanjay Patel ◽  
...  
Keyword(s):  
Longitudinal Analysis ◽  
Positive Association ◽  
Hdl Cholesterol ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Lipoprotein A ◽  
Valid Data ◽  
Leukocyte Counts ◽  
The Uk ◽  
Relationship Of

Background and aims: There is some evidence of a cross-sectional, and possibly causal, relationship of lipid levels with leukocyte counts in mice and humans. This study investigates the cross-sectional and longitudinal relationship of blood lipid and lipoprotein levels with leukocyte counts in the UK Biobank cohort. Methods: The primary cross-sectional analysis included 417,132 participants with valid data on lipid measures and leukocyte counts. A subgroup analysis was performed in 333,668 participants with valid data on lipoprotein(a). The longitudinal analysis included 9,058 participants with valid baseline and follow-up data on lipid and lipoprotein levels and leukocyte counts. The association of lipid and lipoprotein levels with leukocyte counts was analysed by multivariable linear regression. Results: Several relationships were significant in both cross-sectional and longitudinal analysis. After adjustment for demographic, socioeconomic and other confounding factors a higher eosinophil count was associated with lower HDL cholesterol and apolipoproteinA-I concentration (p<0.001). Higher triglycerides levels were associated with higher total leukocyte, basophil, eosinophil, monocyte and neutrophil counts (all p<0.01). A higher lymphocyte count was associated with a higher apolipoprotein B level (p<0.001). In the longitudinal analysis lipoprotein(a) was inversely associated with basophil count in men but not women (p<0.001). Conclusion: Triglyceride levels demonstrate a robust positive association with total and differential leukocyte counts suggesting they may be directly involved in leuokogenesis. However, unlike in murine models, the remainder of these relationships are modest which suggests that cholesterol and lipoproteins are minimally involved in leukogenesis in humans.

scholarly journals Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 991
Author(s):  
Erik Widen ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D. H. Hsu
Keyword(s):  
Disease Risk ◽  
Smoking Status ◽  
Glycated Haemoglobin ◽  
European Ancestry ◽  
Risk Scores ◽  
Common Disease ◽  
Atherosclerotic Cardiovascular Disease ◽  
Uk Biobank ◽  
Lipoprotein A ◽  
The Uk

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

scholarly journals Is Environmental and Occupational Particulate Air Pollution Exposure Related to Type-2 Diabetes and Dementia? A Cross-Sectional Analysis of the UK Biobank

2020 ◽  
Vol 17 (24) ◽  
pp. 9581
Author(s):  
Eirini Dimakakou ◽  
Helinor J. Johnston ◽  
George Streftaris ◽  
John W. Cherrie
Keyword(s):  
Air Pollution ◽  
Occupational Exposure ◽  
Environmental Exposure ◽  
Uk Biobank ◽  
Job Exposure Matrix ◽  
Cross Sectional ◽  
Particulate Air Pollution ◽  
The Uk ◽  
Sectional Analysis

Human exposure to particulate air pollution (e.g., PM2.5) can lead to adverse health effects, with compelling evidence that it can increase morbidity and mortality from respiratory and cardiovascular disease. More recently, there has also been evidence that long-term environmental exposure to particulate air pollution is associated with type-2 diabetes mellitus (T2DM) and dementia. There are many occupations that may expose workers to airborne particles and that some exposures in the workplace are very similar to environmental particulate pollution. We conducted a cross-sectional analysis of the UK Biobank cohort to verify the association between environmental particulate air pollution (PM2.5) exposure and T2DM and dementia, and to investigate if occupational exposure to particulates that are similar to those found in environmental air pollution could increase the odds of developing these diseases. The UK Biobank dataset comprises of over 500,000 participants from all over the UK. Environmental exposure variables were used from the UK Biobank. To estimate occupational exposure both the UK Biobank’s data and information from a job exposure matrix, specifically developed for UK Biobank (Airborne Chemical Exposure–Job Exposure Matrix (ACE JEM)), were used. The outcome measures were participants with T2DM and dementia. In appropriately adjusted models, environmental exposure to PM2.5 was associated with an odds ratio (OR) of 1.02 (95% CI 1.00 to 1.03) per unit exposure for developing T2DM, while PM2.5 was associated with an odds ratio of 1.06 (95% CI 0.96 to 1.16) per unit exposure for developing dementia. These environmental results align with existing findings in the published literature. Five occupational exposures (dust, fumes, diesel, mineral, and biological dust in the most recent job estimated with the ACE JEM) were investigated and the risks for most exposures for T2DM and for all the exposures for dementia were not significantly increased in the adjusted models. This was confirmed in a subgroup of participants where a full occupational history was available allowed an estimate of workplace exposures. However, when not adjusting for gender, some of the associations become significant, which suggests that there might be a bias between the occupational assessments for men and women. The results of the present study do not provide clear evidence of an association between occupational exposure to particulate matter and T2DM or dementia.

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

scholarly journals Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257836
Author(s):  
Roomasa Channa ◽  
Kyungmoo Lee ◽  
Kristen A. Staggers ◽  
Nitish Mehta ◽  
Sidra Zafar ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Glycated Hemoglobin ◽  
Retinal Thickness ◽  
Self Report ◽  
Inner Plexiform Layer ◽  
Uk Biobank ◽  
Fiber Layer ◽  
Cross Sectional ◽  
Retinal Neurodegeneration ◽  
The Uk

Importance Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN). Objective We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort. Design/setting/participants Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM. Exposure Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%. Main outcomes and measures Total retinal, mRNFL and GC-IPL thickness. Results 74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p<0.001), GC-IPL thickness (-1.73 μm, 95% CI: -1.86, -1.59; p<0.001) and mRNFL thickness (-0.68 μm, 95% CI: -0.81, -0.54; p<0.001) compared to those without DM. After adjusting for co-variates, in the GLMM, total retinal thickness was 1.99 um lower (95% CI: -2.47, -1.50; p<0.001) and GC-IPL was 1.02 μm lower (95% CI: -1.18, -0.87; p<0.001) among those with DM compared to without. mRNFL was no longer significantly different (p = 0.369). GC-IPL remained significantly lower, after adjusting for co-variates, among those with DM compared to those without DM when including only participants with no/mild DR (-0.80 μm, 95% CI: -0.98, -0.62; p<0.001). Total retinal thickness decreased 0.40 μm (95% CI: -0.61, -0.20; p<0.001), mRNFL thickness increased 0.20 μm (95% CI: 0.14, 0.27; p<0.001) and GC-IPL decreased 0.26 μm (95% CI: -0.33, -0.20; p<0.001) per unit increase in A1c after adjusting for co-variates. Among participants with diabetes, age, DR grade, ethnicity, body mass index, glaucoma, spherical equivalent, and visual acuity were significantly associated with GC-IPL thickness. Conclusion GC-IPL was thinner among participants with DM, compared to without DM. This difference persisted after adjusting for confounding variables and when considering only those with no/mild DR. This confirms that GC-IPL thinning occurs early in DM and can serve as a useful marker of DRN.

Exploring the relationship of human–nature interaction and mindfulness: a cross-sectional study

2021 ◽  
Author(s):  
Pooja Sahni ◽  
Jyoti Kumar
Keyword(s):  
Mental Health Problems ◽  
Positive Association ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Significant Positive Association ◽  
Cross Sectional ◽  
Nature Relatedness ◽  
Relationship Of ◽  
The Relationship ◽  
Nature Experience

History is replete with examples where humans have sought refuge in nature for psychological restoration. In this cross-sectional study we explore the relationship of nature experience and mindfulness. Nature experience is assessed through “nature in the neighbourhood”, “frequency of visit” to nature-rich spaces, as well as one's inherent connection with nature described as “nature relatedness”. The study sample consisted of 334 Indian adults. The findings from this study show that frequency of visit to nature-rich spaces has a significant positive association with mindfulness. The hierarchical regression analysis suggests an interaction effect of “nature relatedness” in the association of the presence of nature rich spaces in the neighbourhood, frequency of visit as well as mindfulness. Interestingly, when childhood experiences were explored they had a significant association with “nature relatedness” and mindfulness. The evidence from this research suggests that nature experience may find its application as one of the mindfulness techniques prescribed for self-management of mental health problems.

scholarly journals Engagement, not personal characteristics, was associated with the seriousness of regulatory adjudication decisions about physicians: a cross-sectional study

BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Javier A. Caballero ◽  
Steve P. Brown
Keyword(s):  
Personal Characteristics ◽  
Statistical Modelling ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Legal Representation ◽  
Apparent Relationship ◽  
The Uk ◽  
Relationship Of ◽  
To Receive

Abstract Background Outcomes of processes questioning a physician’s ability to practise —e.g. disciplinary or regulatory— may strongly impact their career and provided care. However, it is unclear what factors relate systematically to such outcomes. Methods In this cross-sectional study, we investigate this via multivariate, step-wise, statistical modelling of all 1049 physicians referred for regulatory adjudication at the UK medical tribunal, from June 2012 to May 2017, within a population of 310,659. In order of increasing seriousness, outcomes were: no impairment (of ability to practise), impairment, suspension (of right to practise), or erasure (its loss). This gave adjusted odds ratios (OR) for: age, race, sex, whether physicians first qualified domestically or internationally, area of practice (e.g. GP, specialist), source of initial referral, allegation type, whether physicians attended their outcome hearing, and whether they were legally represented for it. Results There was no systematic association between the seriousness of outcomes and the age, race, sex, domestic/international qualification, or the area of practice of physicians (ORs p≥0.05), except for specialists who tended to receive outcomes milder than suspension or erasure. Crucially, an apparent relationship of outcomes to age (Kruskal-Wallis, p=0.009) or domestic/international qualification (χ2,p=0.014) disappeared once controlling for hearing attendance (ORs p≥0.05). Both non-attendance and lack of legal representation were consistently related to more serious outcomes (ORs [95% confidence intervals], 5.28 [3.89, 7.18] and 1.87 [1.34, 2.60], respectively, p<0.001). Conclusions All else equal, personal characteristics or first qualification place were unrelated to the seriousness of regulatory outcomes in the UK. Instead, engagement (attendance and legal representation), allegation type, and referral source were importantly associated to outcomes. All this may generalize to other countries and professions.

Sign in / Sign up

Export Citation Format

Share Document