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Abstract: TH-PO127

Multi-Trait Genome-Wide Association Study (GWAS) and Functional Genomics Identifies Novel Genetic Traits and Dynamic Networks for FGF23

Session Information

Category: Bone and Mineral Metabolism

  • 502 Bone and Mineral Metabolism: Clinical


  • Perwad, Farzana, University of California San Francisco, San Francisco, California, United States
  • Vartanian, Nicholas, Vanderbilt University Medical Center, Nashville, Tennessee, United States
  • Akwo, Elvis Abang, Vanderbilt University Medical Center, Nashville, Tennessee, United States
  • Robinson-Cohen, Cassianne, Vanderbilt University Medical Center, Nashville, Tennessee, United States

Multi-trait analysis of Genome-wide association (MTAG) is a novel method to explore overlapping genetic architecture between traits. In this study, we investigated genetic traits common to mineral metabolism (MM) to identify novel genetic associations for fibroblast growth factor 23 (FGF23).


We applied MTAG to genetic variants common to 5 genetically correlated mineral metabolism markers (phosphorus, FGF23, calcium, 25(OH)D and PTH) in European-ancestry subjects from UKBioBank GWAS for phosphate and calcium (n=366,484), and two GWAS from the CHARGE consortium for PTH (n=29,155) and FGF23 (n=16,624). We used a functional genomics approach to model interactive and dynamic networks to identify novel associations between MM and FGF23.


MTAG identified independent genome-wide significant SNPs for all traits, including 47 novel and known loci for FGF23. Using gene ontology and pathway analysis, we identified 9 overlapping networks including canonical pathways associated with cardiac hypertrophy and hematopoiesis. VDR and TGFβR2 signaling pathways were identified as the top regulator effect networks and MAPK signaling molecules were common to the top 5 causal networks (Figure 1 and 2). In addition, Coordinated Lysosomal Expression and Regulation (CLEAR) signaling pathway that regulates lysosomal function, autophagy and cellular response to nutrient sensing had the highest predicted activation z-score.


Novel genetic traits for FGF23 were identified with MTAG. Functional genomics revealed networks that inform unique biologic processes and cellular functions that could be targeted to develop therapeutics for mineral disorders.


  • NIDDK Support