About

Wei-Kuo Chen is a professor in the School of Mathematics at the University of Minnesota. He graduated from the University of California at Irvine in 2012 and joined the University of Minnesota in 2015. Prior to his current position, he served as a L. E. Dickson instructor at the University of Chicago from 2012 to 2015. His research interests include probability theory, stochastic dynamics, spin glasses, random matrices, and related applications.

Research topics

• Artificial Intelligence
• Computer Science
• Quantum mechanics
• Algorithm
• Mathematical analysis
• Discrete mathematics
• Mathematics
• Combinatorics

Selected publications

• Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

  Nature · 2024 · 480 citations

  • Biology
  • Genetics
  • Evolutionary biology

  in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

  DOI

• Data from Discriminant Analysis of <sup>18</sup>F-Fluorothymidine Kinetic Parameters to Predict Survival in Patients with Recurrent High-Grade Glioma

  2023

  • Nuclear medicine
  • Medicine
  • Internal medicine

  <div>Abstract<p><b>Purpose:</b> The primary objective of this study was to investigate whether changes in 3′-deoxy-3′-[<sup>18</sup>F]fluorothymidine (<sup>18</sup>F-FLT) kinetic parameters, taken early after the start of therapy, could predict overall survival (OS) and progression-free survival (PFS) in patients with recurrent malignant glioma undergoing treatment with bevacizumab and irinotecan.</p><p><b>Experimental Design:</b> High-grade recurrent brain tumors were investigated in 18 patients (8 male and 10 female), ages 26 to 76 years. Each had 3 dynamic positron emission tomography (PET) studies as follows: at baseline and after 2 and 6 weeks from the start of treatment, <sup>18</sup>F-FLT (2.0 MBq/kg) was injected intravenously, and dynamic PET images were acquired for 1 hour. Factor analysis generated factor images from which blood and tumor uptake curves were derived. A three-compartment, two-tissue model was applied to estimate tumor <sup>18</sup>F-FLT kinetic rate constants using a metabolite- and partial volume–corrected input function. Different combinations of predictor variables were exhaustively searched in a discriminant function to accurately classify patients into their known OS and PFS groups. A leave-one-out cross-validation technique was used to assess the generalizability of the model predictions.</p><p><b>Results:</b> In this study population, changes in single parameters such as standardized uptake value or influx rate constant did not accurately classify patients into their respective OS groups (<1 and ≥1 year; hit ratios ≤78%). However, changes in a set of <sup>18</sup>F-FLT kinetic parameters could perfectly separate these two groups of patients (hit ratio = 100%) and were also able to correctly classify patients into their respective PFS groups (<100 and ≥100 days; hit ratio = 88%).</p><p><b>Conclusions:</b> Discriminant analysis using changes in <sup>18</sup>F-FLT kinetic parameters early during treatment seems to be a powerful method for evaluating the efficacy of therapeutic regimens. <i>Clin Cancer Res; 17(20); 6553–62. ©2011 AACR</i>.</p></div>

  PublisherDOI

• Data from Discriminant Analysis of <sup>18</sup>F-Fluorothymidine Kinetic Parameters to Predict Survival in Patients with Recurrent High-Grade Glioma

  2023

  • Nuclear medicine
  • Medicine
  • Internal medicine

  <div>Abstract<p><b>Purpose:</b> The primary objective of this study was to investigate whether changes in 3′-deoxy-3′-[<sup>18</sup>F]fluorothymidine (<sup>18</sup>F-FLT) kinetic parameters, taken early after the start of therapy, could predict overall survival (OS) and progression-free survival (PFS) in patients with recurrent malignant glioma undergoing treatment with bevacizumab and irinotecan.</p><p><b>Experimental Design:</b> High-grade recurrent brain tumors were investigated in 18 patients (8 male and 10 female), ages 26 to 76 years. Each had 3 dynamic positron emission tomography (PET) studies as follows: at baseline and after 2 and 6 weeks from the start of treatment, <sup>18</sup>F-FLT (2.0 MBq/kg) was injected intravenously, and dynamic PET images were acquired for 1 hour. Factor analysis generated factor images from which blood and tumor uptake curves were derived. A three-compartment, two-tissue model was applied to estimate tumor <sup>18</sup>F-FLT kinetic rate constants using a metabolite- and partial volume–corrected input function. Different combinations of predictor variables were exhaustively searched in a discriminant function to accurately classify patients into their known OS and PFS groups. A leave-one-out cross-validation technique was used to assess the generalizability of the model predictions.</p><p><b>Results:</b> In this study population, changes in single parameters such as standardized uptake value or influx rate constant did not accurately classify patients into their respective OS groups (<1 and ≥1 year; hit ratios ≤78%). However, changes in a set of <sup>18</sup>F-FLT kinetic parameters could perfectly separate these two groups of patients (hit ratio = 100%) and were also able to correctly classify patients into their respective PFS groups (<100 and ≥100 days; hit ratio = 88%).</p><p><b>Conclusions:</b> Discriminant analysis using changes in <sup>18</sup>F-FLT kinetic parameters early during treatment seems to be a powerful method for evaluating the efficacy of therapeutic regimens. <i>Clin Cancer Res; 17(20); 6553–62. ©2011 AACR</i>.</p></div>

  PublisherDOI

• Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data

  Nature Genetics · 2022 · 354 citations

  • Biology
  • Genetics
  DOI

• Multi-tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas

  Lecture notes in computer science · 2022 · 1 citations

  • Artificial Intelligence
  • Computer Science
  • Artificial Intelligence
  PublisherDOI

• Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

  Nature Genetics · 2022 · 724 citations

  • Biology
  • Genetics
  • Evolutionary biology
  DOI

• Whole genome sequence analysis of blood lipid levels in >66,000 individuals

  Nature Communications · 2022 · 73 citations

  • Genetics
  • Biology
  • Computational biology

  Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

  DOI

• Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

  Nature Genetics · 2021 · 293 citations

  • Biology
  • Genetics
  • Computational biology
  DOI

• Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

  Genome Medicine · 2021 · 34 citations

  • Genetics
  • Medicine
  • Biology

  BACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap. RESULTS: ) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways. CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

  DOI

• Recent Progress on Two-Dimensional Materials

  Acta Physico-Chimica Sinica · 2021 · 454 citations

  • Computer Science
  • Computer Science
  DOI

Recent grants

• Some problems on mean-field spin glasses

  NSF · $135k · 2015–2016

• CAREER: Mean Field Spin Glasses and Related Applications

  NSF · $400k · 2018–2024

• Some problems on mean-field spin glasses

  NSF · $105k · 2015–2018

Frequent coauthors

• Antonio Auffinger

  15 shared

• Dmitry Panchenko

  University of Toronto

  5 shared

• Wai‐Kit Lam

  National Taiwan University

  2 shared

• Ting‐Li Chen

  Huadong Sanatorium

  1 shared

• Hung-Chang Hsiao

  National Cheng Kung University

  1 shared

• Arnab Sen

  1 shared

• Zhong-Yi Liang

  National Taiwan University of Science and Technology

  1 shared

• Madeline Handschy

  University of Minnesota

  1 shared

Education

• B.S.

  University of California at Irvine

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• Eamonn Maherh-172
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