Page Catherine Goddard

All Publications

• Impact of genome build on RNA-seq interpretation and diagnostics. medRxiv : the preprint server for health sciences Ungar, R. A., Goddard, P. C., Jensen, T. D., Degalez, F., Smith, K. S., Jin, C. A., Bonner, D. E., Bernstein, J. A., Wheeler, M. T., Montgomery, S. B. 2024

  Abstract

  Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.

  View details for DOI 10.1101/2024.01.11.24301165

  View details for PubMedID 38260490

  View details for PubMedCentralID PMC10802764

• Genetic architecture of cardiac dynamic flow volumes. Nature genetics Gomes, B., Singh, A., O'Sullivan, J. W., Schnurr, T. M., Goddard, P. C., Loong, S., Amar, D., Hughes, J. W., Kostur, M., Haddad, F., Salerno, M., Foo, R., Montgomery, S. B., Parikh, V. N., Meder, B., Ashley, E. A. 2023

  Abstract

  Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

  View details for DOI 10.1038/s41588-023-01587-5

  View details for PubMedID 38082205

  View details for PubMedCentralID 7612636

• Transcriptomics and chromatin accessibility in multiple African population samples. bioRxiv : the preprint server for biology DeGorter, M. K., Goddard, P. C., Karakoc, E., Kundu, S., Yan, S. M., Nachun, D., Abell, N., Aguirre, M., Carstensen, T., Chen, Z., Durrant, M., Dwaracherla, V. R., Feng, K., Gloudemans, M. J., Hunter, N., Moorthy, M. P., Pomilla, C., Rodrigues, K. B., Smith, C. J., Smith, K. S., Ungar, R. A., Balliu, B., Fellay, J., Flicek, P., McLaren, P. J., Henn, B., McCoy, R. C., Sugden, L., Kundaje, A., Sandhu, M. S., Gurdasani, D., Montgomery, S. B. 2023

  Abstract

  Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

  View details for DOI 10.1101/2023.11.04.564839

  View details for PubMedID 37986808

  View details for PubMedCentralID PMC10659267

• Genomics Research with Undiagnosed Children: Ethical Challenges at the Boundaries of Research and Clinical Care JOURNAL OF PEDIATRICS Halley, M. C., Young, J. L., Tang, C., Mintz, K. T., Lucas-Griffin, S., Maghiro, A., Ashley, E. A., Tabor, H. K., Undiagnosed Diseases Network 2023; 261

  View details for DOI 10.1018/j.jpeds.2023.113537

  View details for Web of Science ID 001029333600001

• Participation in a national diagnostic research study: assessing the patient experience. Orphanet journal of rare diseases Rosenfeld, L. E., LeBlanc, K., Nagy, A., Ego, B. K., Undiagnosed Diseases Network, McCray, A. T., Acosta, M. T., Adam, M., Adams, D. R., Alvarez, R. L., Alvey, J., Amendola, L., Andrews, A., Ashley, E. A., Bacino, C. A., Bademci, G., Balasubramanyam, A., Baldridge, D., Bale, J., Bamshad, M., Barbouth, D., Bayrak-Toydemir, P., Beck, A., Beggs, A. H., Behrens, E., Bejerano, G., Bellen, H. J., Bennett, J., Berg-Rood, B., Bernstein, J. A., Berry, G. T., Bican, A., Bivona, S., Blue, E., Bohnsack, J., Bonner, D., Botto, L., Boyd, B., Briere, L. C., Brokamp, E., Brown, G., Burke, E. A., Burrage, L. C., Butte, M. J., Byers, P., Byrd, W. E., Carey, J., Carrasquillo, O., Cassini, T., Chang, T. C., Chanprasert, S., Chao, H., Clark, G. D., Coakley, T. R., Cobban, L. A., Cogan, J. D., Coggins, M., Cole, F. S., Colley, H. A., Cooper, C. M., Cope, H., Corona, R., Craigen, W. J., Crouse, A. B., Cunningham, M., D'Souza, P., Dai, H., Dasari, S., Davis, J., Dayal, J. G., Dell'Angelica, E. C., Dipple, K., Doherty, D., Dorrani, N., Doss, A. L., Douine, E. D., Duncan, L., Earl, D., Eckstein, D. J., Emrick, L. T., Eng, C. M., Falk, M., Fieg, E. L., Fisher, P. G., Fogel, B. L., Forghani, I., Gahl, W. A., Glass, I., Gochuico, B., Goddard, P. C., Godfrey, R. A., Golden-Grant, K., Grajewski, A., Hadley, D., Hahn, S., Halley, M. C., Hamid, R., Hassey, K., Hayes, N., High, F., Hing, A., Hisama, F. M., Holm, I. A., Hom, J., Horike-Pyne, M., Huang, A., Hutchison, S., Introne, W., Isasi, R., Izumi, K., Jamal, F., Jarvik, G. P., Jarvik, J., Jayadev, S., Jean-Marie, O., Jobanputra, V., Karaviti, L., Kennedy, J., Ketkar, S., Kiley, D., Kilich, G., Kobren, S. N., Kohane, I. S., Kohler, J. N., Korrick, S., Kozuira, M., Krakow, D., Krasnewich, D. M., Kravets, E., Lalani, S. R., Lam, B., Lam, C., Lanpher, B. C., Lanza, I. R., Lee, B. H., Levitt, R., Lewis, R. A., Liu, P., Liu, X. Z., Longo, N., Loo, S. K., Loscalzo, J., Maas, R. L., Macnamara, E. F., MacRae, C. A., Maduro, V. V., Mahoney, R., Malicdan, M. C., Mamounas, L. A., Manolio, T. A., Mao, R., Maravilla, K., Marom, R., Marth, G., Martin, B. A., Martin, M. G., Martinez-Agosto, J. A., Marwaha, S., McCauley, J., McConkie-Rosell, A., McGee, E., Mefford, H., Merritt, J. L., Might, M., Mirzaa, G., Morava, E., Moretti, P., Mulvihill, J., Nakano-Okuno, M., Nelson, S. F., Newman, J. H., Nicholas, S. K., Nickerson, D., Nieves-Rodriguez, S., Novacic, D., Oglesbee, D., Orengo, J. P., Pace, L., Pak, S., Pallais, J. C., Palmer, C. G., Papp, J. C., Parker, N. H., Phillips, J. A., Posey, J. E., Potocki, L., Swerdzewski, B. N., Quinlan, A., Rao, D. A., Raper, A., Raskind, W., Renteria, G., Reuter, C. M., Rives, L., Robertson, A. K., Rodan, L. H., Rosenfeld, J. A., Rosenwasser, N., Rossignol, F., Ruzhnikov, M., Sacco, R., Sampson, J. B., Saporta, M., Schaechter, J., Schedl, T., Schoch, K., Scott, D. A., Scott, C. R., Shashi, V., Shin, J., Silverman, E. K., Sinsheimer, J. S., Sisco, K., Smith, E. C., Smith, K. S., Solem, E., Solnica-Krezel, L., Solomon, B., Spillmann, R. C., Stoler, J. M., Sullivan, K., Sullivan, J. A., Sun, A., Sutton, S., Sweetser, D. A., Sybert, V., Tabor, H. K., Tan, Q. K., Tan, A. L., Tekin, M., Telischi, F., Thorson, W., Tifft, C. J., Toro, C., Tran, A. A., Ungar, R. A., Urv, T. K., Vanderver, A., Velinder, M., Viskochil, D., Vogel, T. P., Wahl, C. E., Walker, M., Wallace, S., Walley, N. M., Wambach, J., Wan, J., Wang, L., Wangler, M. F., Ward, P. A., Wegner, D., Hubshman, M. W., Wener, M., Wenger, T., Westerfield, M., Wheeler, M. T., Whitlock, J., Wolfe, L. A., Worley, K., Xiao, C., Yamamoto, S., Yang, J., Zhang, Z., Zuchner, S. 2023; 18 (1): 73

  Abstract

  INTRODUCTION: The Undiagnosed Diseases Network (UDN), a clinical research study funded by the National Institutes of Health, aims to provide answers for patients with undiagnosed conditions and generate knowledge about underlying disease mechanisms. UDN evaluations involve collaboration between clinicians and researchers and go beyond what is possible in clinical settings. While medical and research outcomes of UDN evaluations have been explored, this is the first formal assessment of the patient and caregiver experience.METHODS: We invited UDN participants and caregivers to participate in focus groups via email, newsletter, and a private participant Facebook group. We developed focus group questions based on research team expertise, literature focused on patients with rare and undiagnosed conditions, and UDN participant and family member feedback. In March 2021, we conducted, recorded, and transcribed four 60-min focus groups via Zoom. Transcripts were evaluated using a thematic analysis approach.RESULTS: The adult undiagnosed focus group described the UDN evaluation as validating and an avenue for access to medical providers. They also noted that the experience impacted professional choices and helped them rely on others for support. The adult diagnosed focus group described the healthcare system as not set up for rare disease. In the pediatric undiagnosed focus group, caregivers discussed a continued desire for information and gratitude for the UDN evaluation. They also described an ability to rule out information and coming to terms with not having answers. The pediatric diagnosed focus group discussed how the experience helped them focus on management and improved communication. Across focus groups, adults (undiagnosed/diagnosed) noted the comprehensiveness of the evaluation. Undiagnosed focus groups (adult/pediatric) discussed a desire for ongoing communication and care with the UDN. Diagnosed focus groups (adult/pediatric) highlighted the importance of the diagnosis they received in the UDN. The majority of the focus groups noted a positive future orientation after participation.CONCLUSION: Our findings are consistent with prior literature focused on the patient experience of rare and undiagnosed conditions and highlight benefits from comprehensive evaluations, regardless of whether a diagnosis is obtained. Focus group themes also suggest areas for improvement and future research related to the diagnostic odyssey.

  View details for DOI 10.1186/s13023-023-02695-5

  View details for PubMedID 37032333

• Integrative genomic analysis in African American children with asthma finds three novel loci associated with lung function. Genetic epidemiology Goddard, P. C., Keys, K. L., Mak, A. C., Lee, E. Y., Liu, A. K., Samedy-Bates, L. A., Risse-Adams, O. n., Contreras, M. G., Elhawary, J. R., Hu, D. n., Huntsman, S. n., Oh, S. S., Salazar, S. n., Eng, C. n., Himes, B. E., White, M. J., Burchard, E. G. 2020

  Abstract

  Bronchodilator (BD) drugs are commonly prescribed for treatment and management of obstructive lung function present with diseases such as asthma. Administration of BD medication can partially or fully restore lung function as measured by pulmonary function tests. The genetics of baseline lung function measures taken before BD medication have been extensively studied, and the genetics of the BD response itself have received some attention. However, few studies have focused on the genetics of post-BD lung function. To address this gap, we analyzed lung function phenotypes in 1103 subjects from the Study of African Americans, Asthma, Genes, and Environment, a pediatric asthma case-control cohort, using an integrative genomic analysis approach that combined genotype, locus-specific genetic ancestry, and functional annotation information. We integrated genome-wide association study (GWAS) results with an admixture mapping scan of three pulmonary function tests (forced expiratory volume in 1 s [FEV1 ], forced vital capacity [FVC], and FEV1 /FVC) taken before and after albuterol BD administration on the same subjects, yielding six traits. We identified 18 GWAS loci, and five additional loci from admixture mapping, spanning several known and novel lung function candidate genes. Most loci identified via admixture mapping exhibited wide variation in minor allele frequency across genotyped global populations. Functional fine-mapping revealed an enrichment of epigenetic annotations from peripheral blood mononuclear cells, fetal lung tissue, and lung fibroblasts. Our results point to three novel potential genetic drivers of pre- and post-BD lung function: ADAMTS1, RAD54B, and EGLN3.

  View details for DOI 10.1002/gepi.22365

  View details for PubMedID 32989782