AIMC Topic: UK Biobank

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Identification of novel vertebral development factors through UK Biobank candidate gene search and body imaging analysis.

Communications biology
Numerical variations and transitional anatomy in the human vertebral column represent a significant yet understudied aspect of skeletal development with potential effects on multiple physiological systems. Utilising UK Biobank data, we integrated gen...

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PloS one
BACKGROUND: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by tradit...

Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.

Nature communications
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Scientific reports
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...

A plasma metabolome-derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank.

Diabetes, obesity & metabolism
AIMS: Severe liver disease (SLD) in nonalcoholic fatty liver disease (NAFLD) is often diagnosed late due to the long asymptomatic period of progressive fibrosis. We aimed to identify metabolomic profiles associated with SLD and develop a predictive m...

Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort.

eLife
BACKGROUND: Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results have been inconsistent. Here, we present a comprehensive study of MHT use and brain characteristics in females from the UK Biobank.

Dietary and lifestyle determinants of vitamin D status in the UK Biobank Cohort study for predictive modeling.

The Journal of nutritional biochemistry
Vitamin D (VD) is involved in a wide variety of physiological processes. The high prevalence of VD deficiency in the population requires stronger preventive measures. The aim was to characterize the dietary and lifestyle determinants of VD levels in ...

Estimation of Machine Learning-Based Models to Predict Dementia Risk in Patients With Atherosclerotic Cardiovascular Diseases: UK Biobank Study.

JMIR aging
BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However, the risk factors of dementia in patients with ASCVD remain unclear, necessitating the development of accurate prediction models.

UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases.

NeuroImage
In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. Our analysis also includes established met...

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.

Nature communications
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...