AIMC Topic: Mendelian Randomization Analysis

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Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

Frontiers in public health
BACKGROUND AND OBJECTIVE: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy me...

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Nature communications
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to asse...

Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models.

PLoS computational biology
Multi-task deep learning (DL) models can accurately predict diverse genomic marks from sequence, but whether these models learn the causal relationships between genomic marks is unknown. Here, we describe Deep Mendelian Randomization (DeepMR), a meth...

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature.

Circulation
BACKGROUND: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale com...

Multi-omics identification of circulating protein biomarkers for intervertebral disc degeneration using Mendelian randomization and scRNA-seq.

Clinical rheumatology
BACKGROUND: Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear,...

Genetic and molecular underpinnings of the link between rheumatoid arthritis and myasthenia gravis: Insights from GWAS and transcriptomic analyses.

Clinical rheumatology
BACKGROUND: Although studies have shown that patients with rheumatoid arthritis (RA) are at a higher risk of developing myasthenia gravis (MG), the causal relationship and shared genetic basis between these two diseases have not been fully investigat...

Identification of hub genes involved in the pathogenesis of diabetic nephropathy: A multi-omics study integrating machine learning, mendelian randomization and mediation analysis.

Diabetes, obesity & metabolism
BACKGROUND: Diabetic nephropathy (DN), affecting 30%-40% of diabetic patients, is the leading cause of end-stage renal disease worldwide. This study aims to identify diagnostic biomarkers and explore potential gene-metabolite interactions in DN patho...

The Role of HbA1c in Parkinson's Disease: An Integrative Analysis by Single-Cell, Bulk Transcriptome and Mendelian Randomization.

Molecular neurobiology
Decreased glucose tolerance is recognized as a factor associated with Parkinson's disease (PD) progression, yet the relationship between HbA1c and PD prognosis remains insufficiently explored. Using data from the Integrated Epidemiological Unit (IEU)...

A flexible machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition.

American journal of human genetics
Mendelian randomization (MR) enables the estimation of causal effects while controlling for unmeasured confounding factors. However, traditional MR's reliance on strong parametric assumptions can introduce bias if these are violated. We describe a ma...