publications

2026+

1. Preprint

   Knockoff-augmented meta-analysis identifies shared and ancestry-specific risk loci in multi-ancestry genome-wide association studies

   J. Yin and Y. Yang^*

   2026+

   Code

2026

1. Genome Biol.

   

   KNOT: A knockoff-augmented neural network for identifying risk variants and epistatic interactions in family-based association studies

   Y. Fu and Y. Yang^*

   Genome Biology, 2026

   Abs Code

   While deep learning has recently been used for identifying risk variants in genome-wide association studies, its stochastic nature and the complex correlation within genetic data have posed significant challenges for deep-learning-based methods to pinpoint risk variants. We introduce KNOT, a knockoff-augmented neural network for stabilized variable selection with false discovery rate control. KNOT employs contrastive learning and attention mechanisms to model sample relatedness and linkage disequilibrium, alongside a permutation test to detect epistatic interactions. In applications to two autism spectrum disorder family cohorts, KNOT outperforms conventional methods by identifying more known and putative risk loci and epistatic interactions for autism.

2025

1. npj Digit. Med.

   

   Knockoff-ML: A knockoff machine learning framework for controlled variable selection and risk stratification in electronic health record data

   Q. Wang, L. Li, and Y. Yang^*

   npj Digital Medicine, 2025

   Abs DOI HTML Code

   Effective risk stratification is essential in clinical practice, enabling better resource allocation and improved patient outcomes. Although machine learning models have been widely used for risk prediction and stratification in electronic health record (EHR) data, conventional interpretability metrics for machine learning models typically lack decision rules for clinicians to determine which patient features significantly influence outcomes. We proposed Knockoff-ML, a model-free machine learning framework that simultaneously accomplishes outcome prediction and identification of risk features through integrating a knockoff framework with various predictive machine learning algorithms. Specifically, Knockoff-ML augments traditional machine learning models with the knockoff framework that enables machine learning models to perform variable selection with false discovery rate (FDR) control in the presence of complex, nonlinear associations between features and outcomes in EHR data. We extensively evaluated Knockoff-ML in both simulations and real-data applications. Our simulation results demonstrated that Knockoff-ML consistently achieved high statistical power to identify risk features while rigorously controlling the FDR, whereas conventional feature selection methods exhibited inflated FDR in most scenarios. In applications to a cohort of 50,591 intensive care unit (ICU) patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database, Knockoff-ML identified risk features significantly associated with short- and long-term mortality. Prediction models with identified risk features in Knockoff-ML also achieved comparable prediction accuracy with full models using all available features. Furthermore, Knockoff-ML exhibited substantially higher predictive power and clinical utility compared to conventional ICU scoring systems such as SOFA and SAPS II. The robust performance and interpretability of Knockoff-ML make it a useful tool for enhancing clinical decision-making, with the potential to significantly improve patient outcomes and optimize healthcare delivery.

2024

1. AJHG

   

   KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies

   Y. Yang^*, Q. Wang, C. Wang, J. Buxbaum, and I. Ionita-Laza

   American Journal of Human Genetics, 2024

   Abs DOI HTML Code

   Both trio and population designs are popular study designs for identifying risk genetic variants in genome-wide association studies (GWASs). The trio design, as a family-based design, is robust to confounding due to population structure, whereas the population design is often more powerful due to larger sample sizes. Here, we propose KnockoffHybrid, a knockoff-based statistical method for hybrid analysis of both the trio and population designs. KnockoffHybrid provides a unified framework that brings together the advantages of both designs and produces powerful hybrid analysis while controlling the false discovery rate (FDR) in the presence of linkage disequilibrium and population structure. Furthermore, KnockoffHybrid has the flexibility to leverage different types of summary statistics for hybrid analyses, including expression quantitative trait loci (eQTL) and GWAS summary statistics. We demonstrate in simulations that KnockoffHybrid offers power gains over non-hybrid methods for the trio and population designs with the same number of cases while controlling the FDR with complex correlation among variants and population structure among subjects. In hybrid analyses of three trio cohorts for autism spectrum disorders (ASDs) from the Autism Speaks MSSNG, Autism Sequencing Consortium, and Autism Genome Project with GWAS summary statistics from the iPSYCH project and eQTL summary statistics from the MetaBrain project, KnockoffHybrid outperforms conventional methods by replicating several known risk genes for ASDs and identifying additional associations with variants in other genes, including the PRAME family genes involved in axon guidance and which may act as common targets for human speech/language evolution and related disorders.

2022

1. AJHG

   

   KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design

   Y. Yang, C. Wang, L. Liu, J. Buxbaum, Z. He, and I. Ionita-Laza

   American Journal of Human Genetics, 2022

   Abs DOI HTML Code

   Family-based designs can eliminate confounding due to population substructure and can distinguish direct from indirect genetic effects, but these designs are underpowered due to limited sample sizes. Here, we propose KnockoffTrio, a statistical method to identify putative causal genetic variants for father-mother-child trio design built upon a recently developed knockoff framework in statistics. KnockoffTrio controls the false discovery rate (FDR) in the presence of arbitrary correlations among tests and is less conservative and thus more powerful than the conventional methods that control the family-wise error rate via Bonferroni correction. Furthermore, KnockoffTrio is not restricted to family-based association tests and can be used in conjunction with more powerful, potentially nonlinear models to improve the power of standard family-based tests. We show, using empirical simulations, that KnockoffTrio can prioritize causal variants over associations due to linkage disequilibrium and can provide protection against confounding due to population stratification. In applications to 14,200 trios from three study cohorts for autism spectrum disorders (ASDs), including AGP, SPARK, and SSC, we show that KnockoffTrio can identify multiple significant associations that are missed by conventional tests applied to the same data. In particular, we replicate known ASD association signals with variants in several genes such as MACROD2, NRXN1, PRKAR1B, CADM2, PCDH9, and DOCK4 and identify additional associations with variants in other genes including ARHGEF10, SLC28A1, ZNF589, and HINT1 at FDR 10%.

2. Genet. Epidemiol.

   

   A Bayesian hierarchically structured prior for gene-based association test with multiple traits in genome-wide association studies

   Y. Yang^*, S. Basu, and L. Zhang

   Genetic Epidemiology, 2022

   Abs DOI HTML Code

   Although genome-wide association studies (GWAS) often collect data on multiple correlated traits for complex diseases, conventional gene-based analysis is usually univariate, and therefore, treating traits as uncorrelated. Multivariate analysis of multiple correlated traits can potentially increase the power to detect genes that affect some or all of these traits. In this study, we propose the multivariate hierarchically structured variable selection (HSVS-M) model, a flexible Bayesian model that tests the association of a gene with multiple correlated traits. With only summary statistics, HSVS-M can account for the correlations among genetic variants and among traits simultaneously and can also estimate the various directions and magnitudes of associations between a gene and multiple traits. Simulation studies show that HSVS-M substantially outperforms competing methods in various scenarios, particularly when variants in a gene are associated with a trait in similar directions and magnitudes. We applied HSVS-M to the summary statistics of a meta-analysis GWAS on four lipid traits from the Global Lipids Genetics Consortium and identified 15 genes that have also been confirmed as risk factors in previous studies.

2021

1. Genet. Epidemiol.

   

   A Bayesian hierarchically structured prior for rare-variant association testing

   Y. Yang^*, S. Basu, and L. Zhang

   Genetic Epidemiology, 2021

   Abs DOI HTML Code

   Although genome-wide association studies have been widely used to identify associations between complex diseases and genetic variants, standard single-variant analyses often have limited power when applied to rare variants. To overcome this problem, set-based methods have been developed with the aim of boosting power by borrowing strength from multiple rare variants. We propose the adaptive hierarchically structured variable selection (HSVS-A) before test for association of rare variants in a set with continuous or dichotomous phenotypes and to estimate the effect of individual rare variants simultaneously. HSVS-A has the flexibility to integrate a pairwise weighting scheme, which adaptively induces desirable correlations among variants of similar significance such that we can borrow information from potentially causal and noncausal rare variants to boost power. Simulation studies show that for both continuous and dichotomous phenotypes, HSVS-A is powerful when there are multiple causal rare variants, either in the same or opposite direction of effect, with the presence of a large number of noncausal variants. We also apply HSVS-A to the Wellcome Trust Case Control Consortium Crohn’s disease data for testing the association of Crohn’s disease with rare variants in pathways. HSVS-A identifies two pathways harboring novel protective rare variants for Crohn’s disease.

2. JCEM

   

   Body composition is associated with islet function after pancreatectomy and islet autotransplantation for pancreatitis

   T. Harindhanavudhi, Y. Yang, J. Hodges, T. Pruett, V. Kirchner, G. Beilman, and M. Bellin

   Journal of Clinical Endocrinology & Metabolism, 2021

   Abs DOI HTML

   Context Body composition in total pancreatectomy with islet autotransplantation (TPIAT) has never been studied. Objective Determine whether presurgical body composition is associated with islet function and insulin sensitivity after TPIAT. Methods In 88 adults undergoing TPIAT (median age 41.0 years, IQR 32.8-48.0), beta-cell function and insulin sensitivity were assessed using mixed meal tolerance test and frequent sample intravenous glucose tolerance test before surgery and 12 and 18 months afterward. Body composition was measured by dual x-ray absorptiometry. Analyses used linear and logistic regression. Results Before surgery, 8 individuals (9.1%) were underweight, 40 (45.5%) normal weight, 20 (22.7%) overweight, and 20 (22.7%) obese. Overweight/obese patients had higher area under the curve C-peptide and lower insulin sensitivity index. Baseline body weight was positively associated with first-phase insulin secretion (AIRg) at 12 months (average 38.5 [SE 17.1] mU/L/min higher per extra kg; P = 0.03) and 18 months (38.3 [18.5]; P = 0.04), while baseline lean mass was inversely associated with AIRg at 12 months (−0.05 [0.02] per extra kg; P = 0.01) and 18 months (−0.05 [0.02]; P = 0.03). Percent gynoid fat was inversely associated with disposition index at 18 months (−206.0 [97.2] per extra percent; P = 0.04). Percent body fat and percent gynoid fat were associated with glucose effectiveness index at 18 months (1.9 × 10-3 [0.9 × 10-3] per extra percent; P = 0.04 and −1.96 × 10-3 [0.8 × 10-3]; P = 0.02, respectively). Insulin independence was not significantly associated with body weight or composition. Conclusions Half of these chronic pancreatitis patients were overweight/obese; underweight was uncommon. Preoperative body weight and composition were associated with islet function but not insulin independence after TPIAT.

3. Pancreatology

   

   Surgical approach and short-term outcomes in adults and children undergoing total pancreatectomy with islet autotransplantation: A report from the Prospective Observational Study of TPIAT

   J. Nathan, Y. Yang, P. Witkowski, J. Hodges, M. Bellin, and others

   Pancreatology, 2021

   Abs DOI HTML

   Background Total pancreatectomy with islet autotransplantation (TPIAT) is a viable option for treating debilitating recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) in adults and children. No data is currently available regarding variation in approach to operation. Methods We evaluated surgical techniques, islet isolation and infusion approaches, and outcomes and complications, comparing children (n = 84) with adults (n = 195) enrolled between January 2017 and April 2020 by 11 centers in the United States in the Prospective Observational Study of TPIAT (POST), which was launched in 2017 to collect standard history and outcomes data from patients undergoing TPIAT for RAP or CP. Results Children more commonly underwent splenectomy (100% versus 91%, p = 0.002), pylorus preservation (93% versus 67%; p < 0.0001), Roux-en-Y duodenojejunostomy reconstruction (92% versus 35%; p < 0.0001), and enteral feeding tube placement (93% versus 63%; p < 0.0001). Median islet equivalents/kg transplanted was higher in children (4577; IQR 2816-6517) than adults (2909; IQR 1555-4479; p < 0.0001), with COBE purification less common in children (4% versus 15%; p = 0.0068). Median length of hospital stay was higher in children (15 days; IQR 14-22 versus 11 days; IQR 8-14; p < 0.0001), but 30-day readmissions were lower in children (13% versus 26%, p = 0.018). Rate of portal vein thrombosis was significantly lower in children than in adults (2% versus 10%, p = 0.028). There were no mortalities in the first 90 days post-TPIAT. Conclusions Pancreatectomy techniques differ between children and adults, with islet yields higher in children. The rates of portal vein thrombosis and early readmission are lower in children.

4. Transpl. Int.

   

   Performance of modified IGLS criteria to evaluate islet autograft function after total pancreatectomy with islet autotransplantation

   K. McEachron, Y. Yang, J. Hodges, G. Beilman, V. Kirchner, T. Pruett, S. Chinnakotla, B. Hering, and M. Bellin

   Transplant International, 2021

   Abs DOI HTML

   The Igls criteria assess islet function after islet allotransplant, based on C-peptide, insulin use, hemoglobin A1c, and severe hypoglycemia. However, these criteria as currently defined cannot be applied to total pancreatectomy islet autotransplant (TPIAT) patients. We tested modified criteria for assessing islet function in a large cohort of TPIAT patients (n = 379). Metabolic outcomes were assessed. We assigned Auto-Igls class to each patient as able and evaluated the utility, validity, and perioperative risk factors of Auto-Igls at 1-year post-IAT. We tested the association of Auto-Igls with independent measures of islet graft function, specifically continuous glucose monitoring (CGM) data or acute C-peptide response to glucose (ACRglu) from intravenous glucose tolerance tests. An Auto-Igls class was assigned to 264 patients (69%). Among patients who could not be classified, most were missing exact insulin dose. Seventy-three percent of TPIAT recipients were classified as optimal or good at 1 year. The only significant predictor of Auto-Igls class was islet mass transplanted (P < 0.0001). Auto-Igls class was associated with percent time in range (70-140 mg/dl) on CGM (P = 0.02) and ACRglu (P < 0.0001). Modified Igls classification for IAT permits simple, comprehensive assessment of metabolic outcomes after TPIAT and is associated with other islet functional measures.

5. Pancreatology

   

   Preoperative ERCP has no impact on islet yield following total pancreatectomy and islet autotransplantation (TPIAT): Results from the Prospective Observational Study of TPIAT (POST) cohort

   G. Trikudanathan, B. Elmunzer, Y. Yang, M. Abu-El-Haija, D. Adams, S. Ahmad, M. Bellin, and others

   Pancreatology, 2021

   Abs DOI HTML

   Background and aims Many patients undergoing total pancreatectomy with islet autotransplant (TPIAT) for severe, refractory chronic pancreatitis or recurrent acute pancreatitis have a history of endoscopic retrograde cholangiopancreatography (ERCP). Using data from the multicenter POST (Prospective Observational Study of TPIAT) cohort, we aimed to determine clinical characteristics associated with ERCP and the effect of ERCP on islet yield. Methods Using data from 230 participants (11 centers), demographics, pancreatitis history, and imaging features were tested for association with ERCP procedures. Logistic and linear regression were used to assess association of islet yield measures with having any pre-operative ERCPs and with the number of ERCPs, adjusting for confounders. Results 175 (76%) underwent ERCPs [median number of ERCPs (IQR) 2 (1-4). ERCP was more common in those with obstructed pancreatic duct (p = 0.0009), pancreas divisum (p = 0.0009), prior pancreatic surgery (p = 0.005), and longer disease duration (p = 0.004). A greater number of ERCPs was associated with disease duration (p < 0.0001), obstructed pancreatic duct (p = 0.006), and prior pancreatic surgery (p = 0.006) and increased risk for positive islet culture (p < 0.0001). Mean total IEQ/kg with vs. without prior ERCP were 4145 (95% CI 3621-4669) vs. 3476 (95% CI 2521-4431) respectively (p = 0.23). Adjusting for confounders, islet yield was not significantly associated with prior ERCP, number of ERCPs, biliary or pancreatic sphincterotomy or stent placement. Conclusions ERCP did not appear to adversely impact islet yield. When indicated, ERCP need not be withheld to optimize islet yield but the risk-benefit ratio of ERCP should be considered given its potential harms, including risk for excessive delay in TPIAT.

6. Head & Neck

   

   Epidemiologic factors in patients with advanced head and neck cancer treated with radiation therapy

   M. Brennan, N. Treister, T. Sollecito, B. Schmidt, L. Patton, Y. Yang, A. Lin, L. Elting, J. Hodges, and R. Lalla

   Head & Neck, 2021

   Abs DOI HTML

   Background Approximately 50% of patients with head and neck cancer (HNC) initially were seen with advanced disease. We aimed to evaluate the association of epidemiologic factors with advanced HNC at diagnosis. Methods The OraRad multicenter prospective cohort study enrolled HNC patients receiving curative‐intent radiation therapy. Factors assessed for association with advanced HNC presentation at diagnosis included demographics, social and medical history, cancer characteristics, human papilloma virus (HPV) status, and dental disease measures. Results We enrolled 572 participants; 77% male and mean (SD) age of 61.7 (11.2) years. Oropharyngeal squamous cell carcinomas (88% HPV‐related) were seen with smaller tumors, but more frequent nodal involvement. Private medical insurance and no Medicaid were associated with smaller tumors. A higher dental disease burden was associated with larger tumors. Conclusions Insurance status, cancer type/location, and dental disease are associated with advanced HNC and may represent potentially modifiable factors or factors to be considered in the screening process of new lesions.

2020

1. Stat. Med.

   

   A Bayesian hierarchical variable selection prior for pathway-based GWAS using summary statistics

   Y. Yang, S. Basu, and L. Zhang

   Statistics in Medicine, 2020

   Abs DOI HTML

   While genome‐wide association studies (GWASs) have been widely used to uncover associations between diseases and genetic variants, standard SNP‐level GWASs often lack the power to identify SNPs that individually have a moderate effect size but jointly contribute to the disease. To overcome this problem, pathway‐based GWASs methods have been developed as an alternative strategy that complements SNP‐level approaches. We propose a Bayesian method that uses the generalized fused hierarchical structured variable selection prior to identify pathways associated with the disease using SNP‐level summary statistics. Our prior has the flexibility to take in pathway structural information so that it can model the gene‐level correlation based on prior biological knowledge, an important feature that makes it appealing compared to existing pathway‐based methods. Using simulations, we show that our method outperforms competing methods in various scenarios, particularly when we have pathway structural information that involves complex gene‐gene interactions. We apply our method to the Wellcome Trust Case Control Consortium Crohn’s disease GWAS data, demonstrating its practical application to real data.

2. Pancreas

   

   Alterations in enteroendocrine hormones after total pancreatectomy with islet autotransplantation

   K. McEachron, Y. Yang, J. Hodges, G. Beilman, T. Pruett, V. Kirchner, M. Freeman, G. Trikudanathan, K. Mulier, P. Ptacek, and M. Bellin

   Pancreas, 2020

   Abs DOI HTML

   Objective When total pancreatectomy with islet autotransplantation (TPIAT) is performed for chronic pancreatitis, the pancreas and most of the duodenum are removed, with Roux-en-Y reconstruction of the gastrointestinal tract. Enteroendocrine cells in the intestines and pancreas secrete hormones coordinating digestion and motility, but anatomic reconstruction alters transit of nutrients to these cells. We hypothesized that TPIAT leads to changes in enteroendocrine hormones. Methods Glucagon-like peptide 1 (GLP-1), peptide YY (PYY), and pancreatic polypeptide (PP) were measured from mixed-meal tolerance tests of 34 clinical trial participants before and 18 months after TPIAT. Area under the curve of GLP-1 and PYY-stimulated responses were calculated by trapezoidal method, and the PP response was measured as the stimulated max minus baseline (ΔPP). Results Area under the curve of GLP-1 and PYY increased significantly after TPIAT (GLP-1 average +553.1 pg/mL per minute, P = 0.004; PYY average +4647.9 pg/mL per minute, P = 0.02). ΔPP trended toward lower after TPIAT (average, −52.2 pg/mL, P = 0.06). Conclusions In this novel study of enteroendocrine hormones in TPIAT patients, stimulated levels of GLP-1 and PYY were significantly higher after versus before TPIAT. ΔPP was lower after TPIAT, but not significantly. These hormone changes have potential clinical implications that warrant further research.

2019

1. Pancreas

   

   Risk factors associated with progression towards endocrine insufficiency in chronic pancreatitis

   B. Gutama, Y. Yang, G. Beilman, M. Freeman, V. Kirchner, T. Pruett, S. Chinnakotla, E. Downs, G. Trikudanathan, S. Schwarzenberg, J. Hodges, and M. Bellin

   Pancreas, 2019

   Abs DOI HTML

   Objective Little data exist describing the change over time in islet function and glycemic control in patients with chronic pancreatitis (CP). Methods In 325 CP patients who underwent 2 mixed meal tolerance tests and/or glycated hemoglobin (HbA1c) levels, we estimated the rate of change in metabolic measures per 6 months and assessed the association between potential risk factors for diabetes and rate of change using multivariate regression models. Results Per 6-month time, HbA1c increased by 0.062% with a standard error of 0.029% (P = 0.037) and the ratio (area under the curve (AUC) C-peptide to AUC glucose from mixed meal tolerance testing) decreased by 0.0028 with a standard error of 0.0011 (P = 0.014). We observed more rapid decline in smokers (AUC C-peptide, P = 0.043) and patients with surgical drainage (AUC glucose, P = 0.001; ratio, P = 0.03) or with calcific pancreatitis (HbA1c, P = 0.003). In multivariate models, AUC C-peptide and ratio declined at a greater rate in smokers and HbA1c in those with pancreatic calcifications (both P < 0.05). Conclusions We observed a measurable decline in β-cell function and glycemic control in patients with CP. Patients with a history of tobacco smoking, surgical drainage, or pancreatic calcification may be at highest risk.

2. Clin. Transplant.

   

   Utility of arginine stimulation testing in preoperative assessment of children undergoing total pancreatectomy with islet autotransplantation

   K. McEachron, M. Skube, Y. Yang, J. Hodges, J. Wilhelm, G. Beilman, S. Chinnakotla, S. Schwarzenberg, and M. Bellin

   Clinical Transplantation, 2019

   Abs DOI HTML

   Metabolic outcomes after total pancreatectomy with islet autotransplantation (TPIAT) are influenced by the islet mass transplanted. Preclinical and clinical studies indicate that insulin and C‐peptide levels measured after intravenous administration of the beta cell secretagogue arginine can be used to estimate the available islet mass. We sought to determine if preoperative arginine stimulation test (AST) results predicted transplanted islet mass and metabolic outcomes in pediatric patients undergoing TPIAT. We evaluated the association of preoperative C‐peptide and insulin responses to AST with islet isolation metrics using linear regression, and with postoperative insulin independence using logistic regression. Twenty‐six TPIAT patients underwent preoperative AST from 2015 to 2018. The acute C‐peptide response to arginine (ACRarg) was correlated with isolated islet equivalents (IEQ; r = 0.59, P = 0.002) and islet number (IPN; r = 0.48, P = 0.013). The acute insulin response to arginine (AIRarg) was not significantly correlated with IEQ (r = 0.38, P = 0.095) or IPN (r = 0.41, P = 0.071). Neither ACRarg nor AIRarg was associated with insulin use at 6 months postoperatively. Preoperative C‐peptide response to arginine correlates with islet mass available for transplant in pediatric TPIAT patients. AST represents an additional tool before autotransplant to provide counseling on likely islet mass and to inform quality improvements of islet isolation techniques.

2018

1. Cancer Inform.

   

   A Bayesian gene-based genome-wide association study analysis of osteosarcoma trio data using a hierarchically structured prior

   Y. Yang, S. Basu, L. Mirabello, L. Spector, and L. Zhang

   Cancer Informatics, 2018

   Abs DOI HTML

   Osteosarcoma is considered to be the most common primary malignant bone cancer among children and young adults. Previous studies suggest growth spurts and height to be risk factors for osteosarcoma. However, studies on the genetic cause are still limited given the rare occurrence of the disease. In this study, we investigated in a family trio data set that is composed of 209 patients and their unaffected parents and conducted a genome-wide association study (GWAS) to identify genetic risk factors for osteosarcoma. We performed a Bayesian gene-based GWAS based on the single-nucleotide polymorphism (SNP)-level summary statistics obtained from a likelihood ratio test of the trio data, which uses a hierarchically structured prior that incorporates the SNP-gene hierarchical structure. The Bayesian approach has higher power than SNP-level GWAS analysis due to the reduced number of tests and is robust by accounting for the correlations between SNPs so that it borrows information across SNPs within a gene. We identified 217 genes that achieved genome-wide significance. Ingenuity pathway analysis of the gene set indicated that osteosarcoma is potentially related to TP53, estrogen receptor signaling, xenobiotic metabolism signaling, and RANK signaling in osteoclasts.

2017

1. J. Am. Coll. Surg.

   

   Outcomes and risk factors for graft loss: Lessons learned from 1,056 pediatric kidney transplants at the University of Minnesota

   S. Chinnakotla, P. Verghese, B. Chavers, M. Rheault, V. Kirchner, T. Dunn, C. Kashtan, T. Nevins, M. Mauer, T. Pruett, Y. Kim, L. Najera, C. Hanna, S. Kizilbash, M. Cook, L. Cisek, K. Gillingham, Y. Yang, A. Matas, and J. Najarian

   Journal of the American College of Surgeons, 2017

   Abs DOI HTML

   Background Advances in immunosuppression, surgical techniques, and management of infections in children receiving kidney transplants have affected outcomes. Study design We analyzed a prospectively maintained database of pediatric kidney transplantations. Results From June 1963 through October 2016, we performed 1,056 pediatric kidney transplantations. Of these, 129 were in children less than 2 years old. The most common indications for transplant were congenital anomalies (dysplastic kidneys), obstructive uropathy, and congenital nephrotic syndrome. Living donors constituted 721 (68%) of all donors. The graft and patient survival rates remarkably improved for both deceased and living donor recipients (p = 0.001). Currently, graft survival rates for deceased donor recipients are 92% at 1 year, 76% at 5 years, and 57% at 10 years post-transplant; for living donor recipients, 96% at 1 year, 85% at 5 years, and 78% at 10 years. The graft half-life was 19 years in deceased donor recipients, compared with 25 years in living donor recipients (p ≤ 0.001). Acute rejection was the most common cause of graft loss in the first year post-transplant. The following risk factors were associated with an increased risk of graft loss: deceased donor grafts (p = 0.0001), retransplant (p = 0.02), ages 11 to 18 years (p = 0.001) and pre-transplant urologic issues (p = 0.04). Living donor grafts (p ≤ 0.0001) and pre-emptive transplants (p = 0.02) were associated with decreased risks of graft loss. Conclusions The success rates of pediatric kidney transplants have significantly improved. Pre-emptive kidney transplantation with a living donor graft continues to be superior and should be the choice in children with end-stage renal disease.

2014

1. Enterp. Inf. Syst.

   

   The effect of human image in B2C website design: An eye-tracking study

   Q. Wang, Y. Yang, Q. Wang, and Q. Ma

   Enterprise Information Systems, 2014

   Abs DOI HTML

   On B2C shopping websites, effective visual designs can bring about consumers’ positive emotional experience. From this perspective, this article developed a research model to explore the impact of human image as a visual element on consumers’ online shopping emotions and subsequent attitudes towards websites. This study conducted an eye-tracking experiment to collect both eye movement data and questionnaire data to test the research model. Questionnaire data analysis showed that product pictures combined with human image induced positive emotions among participants, thus promoting their attitudes towards online shopping websites. Specifically, product pictures with human image first produced higher levels of image appeal and perceived social presence, thus stimulating higher levels of enjoyment and subsequent positive attitudes towards the websites. Moreover, a moderating effect of product type was demonstrated on the relationship between the presence of human image and the level of image appeal. Specifically, human image significantly increased the level of image appeal when integrated in entertainment product pictures while this relationship was not significant in terms of utilitarian products. Eye-tracking data analysis further supported these results and provided plausible explanations. The presence of human image significantly increased the pupil size of participants regardless of product types. For entertainment products, participants paid more attention to product pictures integrated with human image whereas for utilitarian products more attention was paid to functional information of products than to product pictures no matter whether or not integrated with human image.