About

Andrew D. Wells, Ph.D., is a Professor of Pathology and Laboratory Medicine at the Perelman School of Medicine at the University of Pennsylvania and a member of The Children's Hospital of Philadelphia Research Institute. His research addresses the fundamental question of how a healthy immune system is able to tolerate self-tissues and beneficial microbes or antigens, and how this process breaks down in autoimmunity and organ transplant rejection. His laboratory has established that immune tolerance is imprinted epigenetically and has developed advanced methods for mapping the 3D structure of the genome, integrating these with techniques for measuring genome accessibility, transcription factor occupancy, disease-associated genetic variation, and gene expression. These approaches enable the understanding of gene regulation at a genome-wide scale, particularly in the context of immune tolerance and autoimmune diseases. Wells' work includes identifying long-range control mechanisms of key immune genes such as IL-2, elucidating the role of transcription factors Foxp3 and Ikaros in T cell tolerance, and exploring how human genetic variation contributes to autoimmune disease susceptibility. His research has provided mechanistic insights into gene regulatory architectures in human cells, connecting disease variants to their target genes through 3D chromatin maps. His studies on autoimmune diseases like systemic lupus erythematosus (SLE) and the functional validation of novel regulatory elements have advanced the understanding of immune regulation and identified potential therapeutic targets. As co-director of the Center for Spatial and Functional Genomics at The Children’s Hospital of Philadelphia, he collaborates with multidisciplinary teams to generate and analyze multi-omic datasets, contributing significantly to the field of immunogenomics and immune tolerance.

Research topics

• Genetics
• Computer Science
• Biology
• Computational biology
• Medicine
• Internal medicine

Selected publications

• Figure S5 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Figure S5: Characteristics of lncMod analysis and results</p>

  PublisherOA PDFDOI

• Trans-ancestry genome-wide association meta-analysis of gallstone disease

  medRxiv · 2025-03-17

  preprintOpen access

  Gallstone disease is a highly prevalent and costly gastrointestinal disease. Yet, genetic variation in susceptibility to gallstone disease and its implication in metabolic regulatory pathways remain to be explored. We report a trans-ancestry genome-wide association meta-analysis of gallstone disease including 88,063 cases and 1,490,087 controls in the UK Biobank, FinnGen, Biobank Japan, and Million Veteran Program. We identified 91 (37 novel) risk loci across the meta-analysis and found replication in statistically compelling signals in the All of Us Research Program. A polygenic risk score constructed from trans-ancestry lead variants was positively associated with liver chemistry and alpha-1-antitrypsin deficiency and negatively associated with total cholesterol and low-density lipoprotein levels among trans-ancestry and European ancestry groups in the Penn Medicine BioBank. Cross-trait colocalization analysis between risk loci and 44 liver, metabolic, renal, and inflammatory traits yielded 350 significant colocalizations as well as 97 significant colocalizations and 65 prioritized genes from expression quantitative trait loci from eight tissues. These findings broaden our understanding of the genetic architecture of gallstone disease.

  PublisherOA PDFDOI

• Mapping chromatin interactions at melanoma susceptibility loci uncovers distant cis-regulatory gene targets

  The American Journal of Human Genetics · 2025-05-22 · 6 citations

  articleOpen access
  PublisherOA PDFDOI

• Figure S1 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Figure S1: Workflow for RNA-seq gene mapping and quantification</p>

  PublisherOA PDFDOI

• GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density

  Genome biology · 2025-10-03

  articleOpen access

  BACKGROUND: Over 1100 independent signals have been identified with genome-wide association studies (GWAS) for bone mineral density (BMD), a key risk factor for mortality-increasing fragility fractures; however, the effector gene(s) for most remain unknown. RESULTS: We execute a CRISPRi screen in human fetal osteoblasts (hFOBs) with single-cell RNA-seq read-out for 89 non-coding elements predicted to regulate osteoblast gene expression at BMD GWAS loci. The BMD relevance of hFOBs is supported by heritability enrichment from stratified LD-score regression involving 98 cell types grouped into 15 tissues. Twenty-three genes show perturbation in the screen, with four (ARID5B, CC2D1B, EIF4G2, and NCOA3) exhibiting consistent effects upon siRNA knockdown on three measures of osteoblast maturation and mineralization. Lastly, additional heritability enrichments, genetic correlations, and multi-trait fine-mapping unexpectedly reveal that many BMD GWAS signals are pleiotropic and likely mediate their effects via non-bone tissues. CONCLUSIONS: Our results provide a roadmap for how single-cell CRISPRi screens may be applied to the challenging task of resolving effector gene identities at all BMD GWAS loci. Extending our CRISPRi screening approach to other tissues could play a key role in fully elucidating the etiology of BMD.

  PublisherOA PDFDOI

• Tables S1-S3 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Table S1: TARGET clinical sample and RNA-sequencing characteristics, Table S2: Genomic loci for lncRNA and protein coding genes in this study, Table S3: Number and types of genes expressed per cancer</p>

  PublisherDOI

• Tables S10-S12 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Table S10: Statistics for input and output variables of lncMod analysis (xls file), Table S11: Significantly dysregulated lncMod triplets, Table S12: lncRNA TF associations ranked by # target genes</p>

  PublisherDOI

• 3D chromatin-based variant-to-gene maps across 57 human cell types reveal the cellular and genetic architecture of autoimmune disease susceptibility

  Genome biology · 2025-12-08 · 1 citations

  articleOpen accessSenior authorCorresponding

  Abstract Background Insight into the genetic basis for many common autoimmune disorders has been uncovered by genome-wide association studies (GWAS), but this alone does not reveal causal variants, effector genes, or the cell types impacted by disease-associated variation. Results Here, we generate 3D genomic datasets consisting of promoter-focused Capture-C, Hi-C, ATAC-seq, and RNA-seq and integrate this data with GWAS of 16 autoimmune traits to physically map disease-associated variants to the effector genes they likely regulate in 57 human cell types. The majority of variants implicated by these cis-regulatory architectures are trait-specific, but nearly half of the target genes connected to these variants are shared across multiple autoimmune disorders in multiple cell types, leading to enrichment of similar biological networks. While this suggests a high level of genetic diversity and complexity that converges at the level of target gene and cell type, some trait-specific pathways representing potential areas for disease-specific intervention were identified. We pharmacologically validate squalene synthase, a cholesterol biosynthetic enzyme encoded by the FDFT1 gene implicated by our approach and supported by prior eQTL data in multiple sclerosis and systemic lupus erythematosus, as a novel immunomodulatory drug target controlling T cell inflammatory cytokine production and aiding B cell antibody production in a human lymphoid organoid model. Conclusions These data represent a comprehensive resource for basic discovery of gene cis-regulatory mechanisms, and the analyses reported reveal mechanisms by which autoimmune-associated variants act to regulate gene expression, function, and pathology across multiple, distinct tissues and cell types. Graphical Abstract

  PublisherDOI

• Tables S13-S14 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Table S13: lncRNAs associated with CRC of NBL, Table S14: Differentially expressed lncRNAs between major subtypes in NBL</p>

  PublisherDOI

• Tables S15-S17 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

  2025-11-24

  articleOpen access

  <p>Table S15: Data integration using multi-dimensional analysis to prioritize functional lncRNAs in each cancer, Table S16: Prioritized lncRNAs and predicted lncRNA target genes and pathways in NBL, Table S17: GSEA Analysis: MSigDB Hallmarks enriched across genes impacted by siTBX2-AS1 or siTBX2 treatment in NLF</p>

  PublisherDOI

Recent grants

• NIH Grant R21AI110179

  NIH · $462k · 2016

• Cyclin-dependent kinases: Novel switches in anergy and targets for tolerance

  NIH · $5.7M · 2002–2021

• NIH Grant P01AI073489

  NIH · $14.1M · 2014

• NIH Grant R21AI059881

  NIH · $510k · 2006

• NIH Grant R56AI054643

  NIH · $293k · 2015

Frequent coauthors

• Struan F.A. Grant

  345 shared

• Chun Su

  136 shared

• Matthew E. Johnson

  124 shared

• Elisabetta Manduchi

  University of Pennsylvania

  123 shared

• Alessandra Chesi

  Children's Hospital of Philadelphia

  119 shared

• Rajan M. Thomas

  Children's Hospital of Philadelphia

  98 shared

• James A. Pippin

  Children's Hospital of Philadelphia

  94 shared

• Wayne W. Hancock

  University of Pennsylvania

  81 shared