Publications by authors named "Yaomin Xu"

Importance: Nicotinamide metabolites have recently been implicated in increased risk of major cardiovascular events (MACE). Supportive data about clinical risk of MACE for nicotinamide users is lacking.

Objective: To determine whether nicotinamide use results in an increase of MACE.

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Background: Many patients will develop more than one skin cancer; however, most research to date has examined only case status.

Objective: Describe the frequency and timing of the treatment of multiple skin cancers in individual patients over time.

Methods: We conducted a longitudinal claims and electronic health record-based cohort study to examine the frequency of skin cancer multiplicity.

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Recent advancements of large language models (LLMs) like generative pre-trained transformer 4 (GPT-4) have generated significant interest among the scientific community. Yet, the potential of these models to be utilized in clinical settings remains largely unexplored. In this study, we investigated the abilities of multiple LLMs and traditional machine learning models to analyze emergency department (ED) reports and determine if the corresponding visits were due to symptomatic kidney stones.

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Cases for a disease can be defined broadly using diagnostic codes, or narrowly using gold-standard confirmation that often is not available in large administrative datasets. These different definitions can have significant impacts on the results and conclusions of studies. We conducted this study to assess how using melanoma phecodes versus histologic confirmation for invasive or in situ melanoma impacts the results of a genome-wide association study (GWAS) using the Million Veteran Program.

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Importance: Nicotinamide metabolites have recently been implicated in increased risk of major cardiovascular events (MACE). Supportive data about clinical risk of MACE for nicotinamide users is lacking.

Objective: To determine whether nicotinamide use results in an increase of MACE.

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Background: Recent advancements of large language models (LLMs) like Generative Pre-trained Transformer 4 (GPT-4) have generated significant interest among the scientific community. Yet, the potential of these models to be utilized in clinical settings remains largely unexplored. This study investigated the abilities of multiple LLMs and traditional machine learning models to analyze emergency department (ED) reports and determine if the corresponding visits were caused by symptomatic kidney stones.

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Article Synopsis
  • This study investigates the genetic factors contributing to kidney stone disease using a large-scale analysis of electronic health records from over 5,000 cases and 83,000 controls.
  • The research identified ten significant genetic loci related to kidney stones, with the most notable one being rs28544423, which influences urinary excretion and is linked to calcium oxalate stones.
  • While important genetic associations were found, the study noted some limitations including potential biases and concluded that genetic variants influence stone composition but not the severity of the disease.
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Article Synopsis
  • PheMIME is an interactive visualization tool developed to analyze and characterize multimorbidity patterns across different populations using data from large-scale electronic health record (EHR) systems.
  • It integrates data from institutions like Vanderbilt University and Mass General Brigham, allowing users to explore complex disease relationships through dynamic, multi-faceted visualizations and analyses.
  • The tool enhances our understanding of patient health by making it easier to identify disease associations, ultimately contributing to more personalized healthcare strategies.
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Importance: Many patients will develop more than one skin cancer, however most research to date has examined only case status.

Objective: Describe the frequency and timing of the treatment of multiple skin cancers in individual patients over time.

Design: Longitudinal claims and electronic health record-based cohort study.

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Article Synopsis
  • - PheWAS (Phenome-wide association studies) analyze the link between genetic factors and various diseases using data from DNA biobanks and electronic medical records, typically applying Phecodes as outcome measures and logistic regression for analysis.
  • - Due to inaccuracies in clinical diagnoses within electronic medical records, creating accurate lists of cases and controls becomes challenging, leading to biased odds ratio estimates and requiring a costly curation process.
  • - The proposed solution is to estimate relative risks (RR) instead, which is shown to be unbiased without needing exclusion criteria lists, allowing for more efficient and larger-scale analyses using structured phenotypic information from ICD codes rather than Phecodes.
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Background: Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations.

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Background: Adrenal steroids play important roles in early-life development. However, our understanding of the effects of perinatal adrenal steroids on the development of childhood asthma is incomplete.

Objective: To evaluate the associations between early-life adrenal steroid levels and childhood asthma.

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Clonal hematopoiesis (CH) is an age-associated phenomenon leading to an increased risk of both hematologic malignancy and nonmalignant organ dysfunction. Increasingly available genetic testing has made the incidental discovery of CH clinically common yet evidence-based guidelines and effective management strategies to prevent adverse CH health outcomes are lacking. To address this gap, the prospective CHIVE (clonal hematopoiesis and inflammation in the vasculature) registry and biorepository was created to identify and monitor individuals at risk, support multidisciplinary CH clinics, and refine taxonomy and standards of practice for CH risk mitigation.

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Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a common complication of obesity and, in severe cases, progresses to metabolic dysfunction-associated steatohepatitis (MASH). Small heterodimer partner (SHP) is an orphan member of the nuclear receptor superfamily and regulates metabolism and inflammation in the liver via a variety of pathways. In this study, we investigate the molecular foundation of MASH progression in mice with hepatic SHP deletion and explore possible therapeutic means to reduce MASH.

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Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related phenomenon in which hematopoietic stem cells acquire mutations in a select set of genes commonly mutated in myeloid neoplasia which then expand clonally. Current sequencing assays to detect CHIP mutations are not optimized for the detection of these variants and can be cost-prohibitive when applied to large cohorts or to serial sequencing. In this study, an affordable (approximately US $8 per sample), accurate, and scalable sequencing assay for CHIP is introduced and validated.

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Background: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administrative purposes raise questions about the consistency and reproducibility of EHR-based multimorbidity research.

Methods: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph.

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Purpose: Solid organ transplant recipients comprise a unique population of immunosuppressed patients with increased risk of malignancy, including hematologic neoplasms. Clonal hematopoiesis of indeterminate potential (CHIP) represents a known risk factor for hematologic malignancy and this study describes the prevalence and patterns of CHIP mutations across several types of solid organ transplants.

Experimental Design: We use two national biobank cohorts comprised of >650,000 participants with linked genomic and longitudinal phenotypic data to describe the features of CHIP across 2,610 individuals who received kidney, liver, heart, or lung allografts.

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Immune checkpoint inhibitor-mediated colitis (IMC) is a common adverse event of treatment with immune checkpoint inhibitors (ICI). We hypothesize that genetic susceptibility to Crohn's disease (CD) and ulcerative colitis (UC) predisposes to IMC. In this study, we first develop a polygenic risk scores for CD (PRS) and UC (PRS) in cancer-free individuals and then test these PRSs on IMC in a cohort of 1316 patients with ICI-treated non-small cell lung cancer and perform a replication in 873 ICI-treated pan-cancer patients.

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Background: Atrial Fibrillation (AF) is a common and clinically heterogeneous arrythmia. Machine learning (ML) algorithms can define data-driven disease subtypes in an unbiased fashion, but whether the AF subgroups defined in this way align with underlying mechanisms, such as high polygenic liability to AF or inflammation, and associate with clinical outcomes is unclear.

Methods: We identified individuals with AF in a large biobank linked to electronic health records (EHR) and genome-wide genotyping.

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Introduction And Objective: We sought to replicate and discover genetic associations of kidney stone disease within a large-scale electronic health record (EHR) system.

Methods: We performed genome-wide association studies (GWASs) for nephrolithiasis from genotyped samples of 5,571 cases and 83,692 controls. Among the significant risk variants, we performed association analyses of stone composition and first-time 24-hour urine parameters.

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Background: Despite the remarkable success of immunotherapy in treating melanoma, understanding of the underlying mechanisms of resistance remains limited. Emerging evidence suggests that upregulation of tumor-specific major histocompatibility complex-II (tsMHC-II) serves as a predictive marker for the response to anti-programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) therapy in various cancer types. The genetic and epigenetic pathways modulating tsMHC-II expression remain incompletely characterized.

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Clonal hematopoiesis (CH) can be caused by either single gene mutations (eg point mutations in JAK2 causing CHIP) or mosaic chromosomal alterations (e.g., loss of heterozygosity at chromosome 9p).

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Many researchers in genetics and social science incorporate information about race in their work. However, migrations (historical and forced) and social mobility have brought formerly separated populations of humans together, creating younger generations of individuals who have more complex and diverse ancestry and race profiles than older age groups. Here, we sought to better understand how temporal changes in genetic admixture influence levels of heterozygosity and impact health outcomes.

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Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related phenomenon that occurs when hematopoietic stem cells acquire mutations in a select set of genes commonly mutated in myeloid neoplasia which then expand clonally. Current sequencing assays to detect CHIP are not optimized for the detection of these variants and can be cost-prohibitive when applied to large cohorts or serial sequencing. Here, we present and validate a CHIP targeted sequencing assay that is affordable (∼$8/sample), accurate and highly scalable.

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