Publications by authors named "Jonggeol Jeff Kim"
Article Synopsis
- The study investigates how interactions between different genetic factors (gene-gene interactions, or G×G) may influence the risk of developing Parkinson's disease (PD), potentially uncovering reasons for previously unexplained heritability in the condition.
- Using extensive genetic data from nearly 19,000 PD patients, researchers identified 116 significant interactions between specific SNPs (single nucleotide polymorphisms), suggesting that these genetic pairings could play a crucial role in PD risk.
- Notably, the study highlighted important interactions between the LRRK2 gene and the SYT10 gene, showing that variations in these genes are not only linked to PD risk but also impact how early the disease
Author Correction: The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data.
NPJ Parkinsons Dis
May 2023
Article Synopsis
- * A virtual 3-day hackathon brought together 49 early-career scientists from 12 countries, focusing on building tools and pipelines specifically for PD research, with each team working on one of nine distinct projects.
- * The hackathon not only generated resources to enhance research but also provided training and networking opportunities, ultimately fostering creative problem-solving and collaboration essential for emerging researchers in data science.
Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort.
View Article and Find Full Text PDFA substantial proportion of risk for Parkinson's disease (PD) is driven by genetics. Progress in understanding the genetic basis of PD has been significant. So far, highly-penetrant rare genetic alterations in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1 and GBA have been linked with typical familial PD and common genetic variability at 90 loci have been linked to risk for PD.
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