Emily Nicole Moya

All Publications

• Schizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations. Nature genetics Liu, D., Meyer, D., Fennessy, B., Feng, C., Cheng, E., Johnson, J. S., Park, Y. J., Rieder, M., Ascolillo, S., de Pins, A., Dobbyn, A., Lebovitch, D., Moya, E., Nguyen, T., Wilkins, L., Hassan, A., Psychiatric Genomics Consortium Phase 3 Targeted Sequencing of Schizophrenia Study Team, Burdick, K. E., Buxbaum, J. D., Domenici, E., Frangou, S., Hartmann, A. M., Laurent-Levinson, C., Malhotra, D., Pato, C. N., Pato, M. T., Ressler, K., Roussos, P., Rujescu, D., Arango, C., Bertolino, A., Blasi, G., Bocchio-Chiavetto, L., Campion, D., Carr, V., Fullerton, J. M., Gennarelli, M., Gonzalez-Penas, J., Levinson, D. F., Mowry, B., Nimgaokar, V. L., Pergola, G., Rampino, A., Cervilla, J. A., Rivera, M., Schwab, S. G., Wildenauer, D. B., Daly, M., Neale, B., Singh, T., O'Donovan, M. C., Owen, M. J., Walters, J. T., Ayub, M., Malhotra, A. K., Lencz, T., Sullivan, P. F., Sklar, P., Stahl, E. A., Huckins, L. M., Charney, A. W., Aghanwa, H. S., Ansari, M., Asif, A., Aslam, R., Ayuso, J. L., Bigdeli, T., Bignotti, S., Bobes, J., Bradley, B., Buckley, P., Cairns, M. J., Catts, S. V., Chaudhry, A. R., Cohen, D., Collins, B. L., Consoli, A., Costas, J., Crespo-Facorro, B., Daskalakis, N. P., Davidson, M., Davis, K. L., Dickerson, F., Dogar, I. A., Drapeau, E., Fananas, L., Fanous, A., Fatima, W., Fatjo, M., Filippich, C., Friedman, J., Fullard, J. F., Georgakopoulos, P., Giannitelli, M., Giegling, I., Green, M. J., Guillin, O., Gutierrez, B., Handoko, H. Y., Hansen, S. K., Haroon, M., Haroutunian, V., Henskens, F. A., Hussain, F., Jablensky, A. V., Junejo, J., Kelly, B. J., Khan, S. A., Khan, M. N., Khan, A., Khawaja, H. R., Khizar, B., Kleopoulos, S. P., Knowles, J., Konte, B., Kusumawardhani, A. A., Leghari, N., Liu, X., Lori, A., Loughland, C. M., Mahmood, K., Mahmood, S., Malaspina, D., Malik, D., McNaughton, A., Michie, P. T., Michopolous, V., Molina, E., Molto, M. D., Munir, A., Muntane, G., Naeem, F., Nancarrow, D. J., Nasar, A., Nasr, T., Ohaeri, J. U., Ott, J., Pantelis, C., Periyasamy, S., Pinto, A. G., Powers, A., Ramos, B., Rana, N. H., Rapaport, M., Reichenberg, A., Saker-Delye, S., Schall, U., Schofield, P. R., Scott, R. J., Shanahan, M., Weickert, C. S., Sjaarda, C., Smith, H. J., Suarez-Rama, J. J., Tariq, M., Thibaut, F., Tooney, P. A., Umar, M., Vilella, E., Weiser, M., Wu, J. Q., Yolken, R. 2023; 55 (3): 369-376

  Abstract

  Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This recent study-and most other large-scale human genetics studies-was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear. To address this gap, we designed a custom sequencing panel of 161 genes selected based on the current knowledge of SCZ genetics and sequenced a new cohort of 11,580 SCZ cases and 10,555 controls of diverse ancestries. Replicating earlier work, we found that cases carried a significantly higher burden of rare protein-truncating variants (PTVs) among evolutionarily constrained genes (odds ratio=1.48; P=5.4*10-6). In meta-analyses with existing datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five ancestral populations. Two genes (SRRM2 and AKAP11) were newly implicated as SCZ risk genes, and one gene (PCLO) was identified as shared by individuals with SCZ and those with autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of SCZ being conserved across diverse human populations.

  View details for DOI 10.1038/s41588-023-01305-1

  View details for PubMedID 36914870

• Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae NATURE MEDICINE Thompson, R. C., Simons, N. W., Wilkins, L., Cheng, E., Del Valle, D., Hoffman, G. E., Cervia, C., Fennessy, B., Mouskas, K., Francoeur, N. J., Johnson, J. S., Lepow, L., Le Berichel, J., Chang, C., Beckmann, A. G., Wang, Y., Nie, K., Zaki, N., Tuballes, K., Barcessat, V., Cedillo, M. A., Yuan, D., Huckins, L., Roussos, P., Marron, T. U., Glicksberg, B. S., Nadkarni, G., Heath, J. R., Gonzalez-Kozlova, E., Boyman, O., Kim-Schulze, S., Sebra, R., Merad, M., Gnjatic, S., Schadt, E. E., Charney, A. W., Beckmann, N. D., Mt Sinai COVID-19 Biobank Team 2022: 236-246

  Abstract

  Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are debilitating, clinically heterogeneous and of unknown molecular etiology. A transcriptome-wide investigation was performed in 165 acutely infected hospitalized individuals who were followed clinically into the post-acute period. Distinct gene expression signatures of post-acute sequelae were already present in whole blood during acute infection, with innate and adaptive immune cells implicated in different symptoms. Two clusters of sequelae exhibited divergent plasma-cell-associated gene expression patterns. In one cluster, sequelae associated with higher expression of immunoglobulin-related genes in an anti-spike antibody titer-dependent manner. In the other, sequelae associated independently of these titers with lower expression of immunoglobulin-related genes, indicating lower non-specific antibody production in individuals with these sequelae. This relationship between lower total immunoglobulins and sequelae was validated in an external cohort. Altogether, multiple etiologies of post-acute sequelae were already detectable during SARS-CoV-2 infection, directly linking these sequelae with the acute host response to the virus and providing early insights into their development.

  View details for DOI 10.1038/s41591-022-02107-4

  View details for Web of Science ID 000928059900001

  View details for PubMedID 36482101

  View details for PubMedCentralID PMC9873574

• The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals CLINICAL PROTEOMICS Butler-Laporte, G., Gonzalez-Kozlova, E., Su, C., Zhou, S., Nakanishi, T., Brunet-Ratnasingham, E., Morrison, D., Laurent, L., Afilalo, J., Afilalo, M., Henry, D., Chen, Y., Carrasco-Zanini, J., Farjoun, Y., Pietzner, M., Kimchi, N., Afrasiabi, Z., Rezk, N., Bouab, M., Petitjean, L., Guzman, C., Xue, X., Tselios, C., Vulesevic, B., Adeleye, O., Abdullah, T., Almamlouk, N., Moussa, Y., DeLuca, C., Duggan, N., Schurr, E., Brassard, N., Durand, M., Del Valle, D., Thompson, R., Cedillo, M. A., Schadt, E., Nie, K., Simons, N. W., Mouskas, K., Zaki, N., Patel, M., Xie, H., Harris, J., Marvin, R., Cheng, E., Tuballes, K., Argueta, K., Scott, I., Greenwood, C. T., Paterson, C., Hinterberg, M., Langenberg, C., Forgetta, V., Mooser, V., Marron, T., Beckmann, N., Kenigsberg, E., Charney, A. W., Kim-Schulze, S., Merad, M., Kaufmann, D. E., Gnjatic, S., Richards, J., Mt Sinai COVID-19 Biobank Team 2022; 19 (1): 34

  Abstract

  Severe COVID-19 leads to important changes in circulating immune-related proteins. To date it has been difficult to understand their temporal relationship and identify cytokines that are drivers of severe COVID-19 outcomes and underlie differences in outcomes between sexes. Here, we measured 147 immune-related proteins during acute COVID-19 to investigate these questions.We measured circulating protein abundances using the SOMAscan nucleic acid aptamer panel in two large independent hospital-based COVID-19 cohorts in Canada and the United States. We fit generalized additive models with cubic splines from the start of symptom onset to identify protein levels over the first 14 days of infection which were different between severe cases and controls, adjusting for age and sex. Severe cases were defined as individuals with COVID-19 requiring invasive or non-invasive mechanical respiratory support.580 individuals were included in the analysis. Mean subject age was 64.3 (sd 18.1), and 47% were male. Of the 147 proteins, 69 showed a significant difference between cases and controls (p < 3.4 × 10-4). Three clusters were formed by 108 highly correlated proteins that replicated in both cohorts, making it difficult to determine which proteins have a true causal effect on severe COVID-19. Six proteins showed sex differences in levels over time, of which 3 were also associated with severe COVID-19: CCL26, IL1RL2, and IL3RA, providing insights to better understand the marked differences in outcomes by sex.Severe COVID-19 is associated with large changes in 69 immune-related proteins. Further, five proteins were associated with sex differences in outcomes. These results provide direct insights into immune-related proteins that are strongly influenced by severe COVID-19 infection.

  View details for DOI 10.1186/s12014-022-09371-z

  View details for Web of Science ID 000861465600001

  View details for PubMedID 36171541

  View details for PubMedCentralID PMC9516500

• Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children NATURE COMMUNICATIONS Beckmann, N. D., Comella, P. H., Cheng, E., Lepow, L., Beckmann, A. G., Tyler, S. R., Mouskas, K., Simons, N. W., Hoffman, G. E., Francoeur, N. J., Del Valle, D., Kang, G., Do, A., Moya, E., Wilkins, L., Le Berichel, J., Chang, C., Marvin, R., Calorossi, S., Lansky, A., Walker, L., Yi, N., Yu, A., Chung, J., Hartnett, M., Eaton, M., Hatem, S., Jamal, H., Akyatan, A., Tabachnikova, A., Liharska, L. E., Cotter, L., Fennessy, B., Vaid, A., Barturen, G., Shah, H., Wang, Y., Sridhar, S., Soto, J., Bose, S., Madrid, K., Ellis, E., Merzier, E., Vlachos, K., Fishman, N., Tin, M., Smith, M., Xie, H., Patel, M., Nie, K., Argueta, K., Harris, J., Karekar, N., Batchelor, C., Lacunza, J., Yishak, M., Tuballes, K., Scott, I., Kumar, A., Jaladanki, S., Agashe, C., Thompson, R., Clark, E., Losic, B., Peters, L., Roussos, P., Zhu, J., Wang, W., Kasarskis, A., Glicksberg, B. S., Nadkarni, G., Bogunovic, D., Elaiho, C., Gangadharan, S., Ofori-Amanfo, G., Alesso-Carra, K., Onel, K., Wilson, K. M., Argmann, C., Bunyavanich, S., Alarcon-Riquelme, M. E., Marron, T. U., Rahman, A., Kim-Schulze, S., Gnjatic, S., Gelb, B. D., Merad, M., Sebra, R., Schadt, E. E., Charney, A. W., Mount Sinai COVID 19 Biobank Team 2021; 12 (1): 4854

  Abstract

  Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and pathology of multiple organs in individuals under 21 years of age in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although an autoimmune pathogenesis has been proposed, the genes, pathways and cell types causal to this new disease remain unknown. Here we perform RNA sequencing of blood from patients with MIS-C and controls to find disease-associated genes clustered in a co-expression module annotated to CD56dimCD57+ natural killer (NK) cells and exhausted CD8+ T cells. A similar transcriptome signature is replicated in an independent cohort of Kawasaki disease (KD), the related condition after which MIS-C was initially named. Probing a probabilistic causal network previously constructed from over 1,000 blood transcriptomes both validates the structure of this module and reveals nine key regulators, including TBX21, a central coordinator of exhausted CD8+ T cell differentiation. Together, this unbiased, transcriptome-wide survey implicates downregulation of NK cells and cytotoxic T cell exhaustion in the pathogenesis of MIS-C.

  View details for DOI 10.1038/s41467-021-24981-1

  View details for Web of Science ID 000684339800026

  View details for PubMedID 34381049

  View details for PubMedCentralID PMC8357784

• Unexpected words or unexpected languages? Two ERP effects of code-switching in naturalistic discourse COGNITION Yacovone, A., Moya, E., Snedeker, J. 2021; 215: 104814

  Abstract

  Bilingual speakers often switch between languages in conversation without any advance notice. Psycholinguistic research has found that these language shifts (or code-switches) can be costly for comprehenders in certain situations. The present study explores the nature of these costs by comparing code-switches to other types of unexpected linguistic material. To do this, we used a novel EEG paradigm, the Storytime task, in which we record readings of natural texts, and then experimentally manipulate their properties by splicing in words. In this study, we manipulated the language of our target words (English, Spanish) and their fit with the preceding context (strong-fit, weak-fit). If code-switching incurs a unique cost beyond that incurred by an unexpected word, then we should see an additive pattern in our ERP indices. If an effect is driven by lexical expectation alone, then there should be a non-additive interaction such that all unexpected forms incur a similar cost. We found three effects: a general prediction effect (a non-additive N400), a post-lexical recognition of the switch in languages (an LPC for code-switched words), and a prolonged integration difficulty associated with weak-fitting words regardless of language (a sustained negativity). We interpret these findings as suggesting that the processing difficulties experienced by bilinguals can largely be understood within more general frameworks for understanding language comprehension. Our findings are consistent with the broader literature demonstrating that bilinguals do not have two wholly separate language systems but rather a single language system capable of using two coding systems.

  View details for DOI 10.1016/j.cognition.2021.104814

  View details for Web of Science ID 000684293800002

  View details for PubMedID 34303181

• Sampling the host response to SARS-CoV-2 in hospitals under siege NATURE MEDICINE Charney, A. W., Simons, N. W., Mouskas, K., Lepow, L., Cheng, E., Le Berichel, J., Chang, C., Marvin, R., Del Valle, D., Calorossi, S., Lansky, A., Walker, L., Patel, M., Xie, H., Yi, N., Yu, A., Kang, G., Liharska, L. E., Moya, E., Hartnett, M., Hatem, S., Wilkins, L., Eaton, M., Jamal, H., Tuballes, K., Chen, S. T., Chung, J., Harris, J., Batchelor, C., Lacunza, J., Yishak, M., Argueta, K., Karekar, N., Lee, B., Kelly, G., Geanon, D., Handler, D., Leech, J., Stefanos, H., Dawson, T., Scott, I., Francoeur, N., Johnson, J. S., Vaid, A., Glicksberg, B. S., Nadkarni, G. N., Schadt, E. E., Gelb, B. D., Rahman, A., Sebra, R., Martin, G., Marron, T., Beckmann, N., Kim-Schulze, S., Gnjatic, S., Merad, M., Mt Sinai COVID-19 Biobank Team 2020; 26 (8): 1157-1158

  View details for DOI 10.1038/s41591-020-1004-3

  View details for Web of Science ID 000552954000002

  View details for PubMedID 32719485