Biology subjects

Oh, I. Y.

Publications and source records attributed to Oh, I. Y..

3 recordsLinked to original sources

bioRxiv2023

Leveraging GPT-4 for Identifying Clinical Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo and spaCy's Rule-based & Machine Learning-based methods

ObjectiveAccurately identifying clinical phenotypes from Electronic Health Records (EHRs) provides additional insights into patients health, especially when such information is unavailable in structured data. This study evaluates the application of OpenAIs Generative Pre-trained Transformer (GPT)-4 model to identify clinical phenotypes from EHR text in non-small cell lung cancer (NSCLC) patients. The goal was to identify disease stages, treatments and progression utilizing GPT-4, and compare its performance against GPT-3.5-turbo, Flan-T5-xl, Flan-T5-xxl, and two rule-based and machine learning-based methods, namely, scispaCy and medspaCy. Materials and MethodsPhenotypes such as initial cancer stage, initial treatment, evidence of cancer recurrence, and affected organs during recurrence were identified from 13,646 records for 63 NSCLC patients from Washington University in St. Louis, Missouri. The performance of the GPT-4 model is evaluated against GPT-3.5-turbo, Flan-T5-xxl, Flan-T5-xl, medspaCy and scispaCy by comparing precision, recall, and micro-F1 scores. ResultsGPT-4 achieved higher F1 score, precision, and recall compared to Flan-T5-xl, Flan-T5-xxl, medspaCy and scispaCys models. GPT-3.5-turbo performed similarly to that of GPT-4. GPT and Flan-T5 models were not constrained by explicit rule requirements for contextual pattern recognition. SpaCy models relied on predefined patterns, leading to their suboptimal performance. Discussion and ConclusionGPT-4 improves clinical phenotype identification due to its robust pre-training and remarkable pattern recognition capability on the embedded tokens. It demonstrates data-driven effectiveness even with limited context in the input. While rule-based models remain useful for some tasks, GPT models offer improved contextual understanding of the text, and robust clinical phenotype extraction.

bioinformatics↗

bioRxiv2023

Pathogenic variants in CRX have distinct cis-regulatory effects on enhancers and silencers in photoreceptors

Dozens of variants in the photoreceptor-specific transcription factor (TF) CRX are linked with human blinding diseases that vary in their severity and age of onset. It is unclear how different variants in this single TF alter its function in ways that lead to a range of phenotypes. We examined the effects of human disease-causing variants on CRX cis-regulatory function by deploying massively parallel reporter assays (MPRAs) in live mouse retinas carrying knock-ins of two variants, one in the DNA binding domain (p.R90W) and the other in the transcriptional effector domain (p.E168d2). The degree of reporter gene dysregulation caused by the variants corresponds with their phenotypic severity. The two variants affect similar sets of enhancers, while p.E168d2 has stronger effects on silencers. Cis-regulatory elements (CREs) near cone photoreceptor genes are enriched for silencers that are de-repressed in the presence of p.E168d2. Chromatin environments of CRX-bound loci were partially predictive of episomal MPRA activity, and silencers were notably enriched among distal elements whose accessibility increases later in retinal development. We identified a set of potentially pleiotropic regulatory elements that convert from silencers to enhancers in retinas that lack a functional CRX effector domain. Our findings show that phenotypically distinct variants in different domains of CRX have partially overlapping effects on its cis-regulatory function, leading to misregulation of similar sets of enhancers, while having a qualitatively different impact on silencers.

genomics↗

bioRxiv2019

An enhancer:involucrin regulatory module impacts human skin barrier adaptation out-of-Africa and modifies atopic dermatitis risk

The genetic modules that contribute to human evolution are poorly understood. We identified positive selection for two independent involucrin (IVL) haplotypes in European (CEU) and Asian (JPT/CHB) populations for skin epidermis. CEU IVL associated with increased IVL and a known epidermal-specific enhancer underwent a recent selective sweep out-of-Africa correlating with increased northern latitude. CRISPR/Cas9 deletion of the mouse enhancer revealed enhancer-mediated cis regulation for Ivl expression with human population-specific enhancer reporter assays confirming the additive effect. Furthermore, IVL enhancer eQTLs associated with decreased IVL together with filaggrin loss-of-function variants are enriched in atopic dermatitis cases vs. controls. Together, our enhancer-IVL cis regulatory module findings reveal an emerging paradigm for recently evolved traits to impact skin disease risk in contemporary populations.

genetics↗