All Publications


  • Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy. Nature communications Parikh, V. N., Ioannidis, A. G., Jimenez-Morales, D., Gorzynski, J. E., De Jong, H. N., Liu, X., Roque, J., Cepeda-Espinoza, V. P., Osoegawa, K., Hughes, C., Sutton, S. C., Youlton, N., Joshi, R., Amar, D., Tanigawa, Y., Russo, D., Wong, J., Lauzon, J. T., Edelson, J., Mas Montserrat, D., Kwon, Y., Rubinacci, S., Delaneau, O., Cappello, L., Kim, J., Shoura, M. J., Raja, A. N., Watson, N., Hammond, N., Spiteri, E., Mallempati, K. C., Montero-Martín, G., Christle, J., Kim, J., Kirillova, A., Seo, K., Huang, Y., Zhao, C., Moreno-Grau, S., Hershman, S. G., Dalton, K. P., Zhen, J., Kamm, J., Bhatt, K. D., Isakova, A., Morri, M., Ranganath, T., Blish, C. A., Rogers, A. J., Nadeau, K., Yang, S., Blomkalns, A., O'Hara, R., Neff, N. F., DeBoever, C., Szalma, S., Wheeler, M. T., Gates, C. M., Farh, K., Schroth, G. P., Febbo, P., deSouza, F., Cornejo, O. E., Fernandez-Vina, M., Kistler, A., Palacios, J. A., Pinsky, B. A., Bustamante, C. D., Rivas, M. A., Ashley, E. A. 2022; 13 (1): 5107

    Abstract

    The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

    View details for DOI 10.1038/s41467-022-32397-8

    View details for PubMedID 36042219

  • The Genetic Etiology of Periodic Leg Movement in Sleep. Sleep Edelson, J. L., Schneider, L. D., Amar, D., Brink-Kjaer, A., Cederberg, K. L., Kutalik, Z., Hagen, E. W., Peppard, P. E., Tempaku, P. F., Tufik, S., Evans, D. S., Stone, K., Tranah, G., Cade, B., Redline, S., Haba-Rubio, J., Heinzer, R., Marques-Vidal, P., Vollenweider, P., Winkelmann, J., Zou, J., Mignot, E. 2022

    Abstract

    STUDY OBJECTIVES: Periodic Limb Movement in Sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a Genome-Wide Association Study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of 4 cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6,843 total subjects..METHODS: The MrOS study and Wisconsin Sleep Cohort Study (N=1,745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1,002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using mendelian randomization.RESULTS: We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 x 10 -12, beta=0.486), a SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 x10 -22, beta=0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS.CONCLUSIONS: Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.

    View details for DOI 10.1093/sleep/zsac121

    View details for PubMedID 35670608

  • The shared genetic architectures between lung cancer and multiple polygenic phenotypes in genome-wide association studies. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Byun, J., Han, Y., Ostrom, Q. T., Edelson, J., Walsh, K. M., Pettit, R. W., Bondy, M. L., Hung, R. J., McKay, J. D., Amos, C. I. 2021

    Abstract

    BACKGROUND: Prior genome-wide association studies have identified numerous lung cancer risk loci and reveal substantial etiologic heterogeneity across histological subtypes. Analyzing the shared genetic architecture underlying variation in complex traits can elucidate common genetic etiologies across phenotypes. Exploring pairwise genetic correlations between lung cancer and other polygenic traits can reveal the common genetic etiology of correlated phenotypes.METHODS: Using cross-trait linkage disequilibrium score regression, we estimated the pairwise genetic correlation and heritability between lung cancer and multiple traits using publicly available summary statistics. Identified genetic relationships were also examined after excluding genomic regions known to be associated with smoking behaviors, a major risk factor for lung cancer.RESULTS: We observed several traits showing moderate SNP-based heritability and significant genetic correlations with lung cancer. We observed highly significant correlations between the genetic architectures of lung cancer and emphysema/chronic bronchitis across all histological subtypes, as well as among lung cancer occurring among smokers. Our analyses revealed highly significant positive correlations between lung cancer and paternal history of lung cancer. We also observed a strong negative correlation with parental longevity. We observed consistent directions in genetic patterns after excluding genomic regions associated with smoking behaviors.CONCLUSIONS: This study identifies numerous phenotypic traits that share genomic architecture with lung carcinogenesis and are not fully accounted for by known smoking-associated genomic loci.IMPACT: These findings provide new insights into the etiology of lung cancer by identifying traits that are genetically correlated with increased risk of lung cancer.

    View details for DOI 10.1158/1055-9965.EPI-20-1635

    View details for PubMedID 33771847

  • Partitioned glioma heritability shows subtype-specific enrichment in immune cells. Neuro-oncology Ostrom, Q. T., Edelson, J., Byun, J., Han, Y., Kinnersley, B., Melin, B., Houlston, R. S., Monje, M., Walsh, K. M., Amos, C. I., Bondy, M. L. 2021

    Abstract

    BACKGROUND: Epidemiological studies of adult glioma have identified genetic syndromes and 25 heritable risk loci that modify individual risk for glioma, as well increased risk in association with exposure to ionizing radiation and decreased risk in association with allergies. In this analysis we assess whether there is shared genome-wide genetic architecture between glioma and atopic/autoimmune diseases.METHODS: Using summary statistics from a glioma genome-wide association studies (GWAS) meta-analysis, we identified significant enrichment for risk variants associated with gene expression changes in immune cell populations. We also estimated genetic correlations between glioma and autoimmune, atopic, and hematologic traits using LDscore regression, which leverages genome-wide single nucleotide polymorphism (SNP) associations and patterns of linkage disequilibrium.RESULTS: Nominally significant negative correlations were observed for glioblastoma and primary biliary cirrhosis (rg=-0.26, p=0.0228), and for non-glioblastoma gliomas and celiac disease (rg=-0.32, p=0.0109). Our analyses implicate dendritic cells (GB pHM= 0.0306 and non-GB pHM=0.0186) in mediating both glioblastoma and non-glioblastoma genetic predisposition, with glioblastoma-specific associations identified in natural killer (NK) (pHM=0.0201) and stem cells (pHM=0.0265).CONCLUSIONS: This analysis identifies putative new associations between glioma and autoimmune conditions with genomic architecture that is inversely correlated with that of glioma and that T cells, NK cells, and myeloid cells are involved in mediating glioma predisposition. This provides further evidence that increased activation of the acquired immune system may modify individual susceptibility to glioma.

    View details for DOI 10.1093/neuonc/noab072

    View details for PubMedID 33743008

  • Genetic correlation analysis identifies glioma heritability enrichment in immune cell types and novel protective associations with auto-immune conditions Ostrom, Q. T., Edelson, J., Byun, J., Han, Y., Walsh, K., Amos, C., Bondy, M., GLIOGENE Consortium AMER ASSOC CANCER RESEARCH. 2020
  • Genetic correlation between lung cancer and environmental exposures Pettit, R., Byun, J., Han, Y., Edelson, J., Ostrom, Q., Walsh, K., Bondy, M., McKay, J., Amos, C., INTEGRAL Consortium AMER ASSOC CANCER RESEARCH. 2020
  • Genetic Architecture of Lung Cancer Using Machine-Learning Approaches in Genome-Wide Association Studies Byun, J., Han, Y., Edelson, J., Ostrom, Q., Amos, C. ELSEVIER SCIENCE INC. 2019: S516–S517