Author: "Chapman, Sinéad B." - Searchworks@Jio Institute Digital Library Search Results

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43 results on '"Chapman, Sinéad B."'

1. Inter-species geographic signatures for tracing horizontal gene transfer and long-term persistence of carbapenem resistance

Author: Salamzade, Rauf, Manson, Abigail L, Walker, Bruce J, Brennan-Krohn, Thea, Worby, Colin J, Ma, Peijun, He, Lorrie L, Shea, Terrance P, Qu, James, Chapman, Sinéad B, Howe, Whitney, Young, Sarah K, Wurster, Jenna I, Delaney, Mary L, Kanjilal, Sanjat, Onderdonk, Andrew B, Bittencourt, Cassiana E, Gussin, Gabrielle M, Kim, Diane, Peterson, Ellena M, Ferraro, Mary Jane, Hooper, David C, Shenoy, Erica S, Cuomo, Christina A, Cosimi, Lisa A, Huang, Susan S, Kirby, James E, Pierce, Virginia M, Bhattacharyya, Roby P, and Earl, Ashlee M
Subjects: Microbiology, Biological Sciences, Genetics, Infectious Diseases, Prevention, Vaccine Related, Emerging Infectious Diseases, Antimicrobial Resistance, 2.2 Factors relating to the physical environment, Aetiology, Infection, Anti-Bacterial Agents, Carbapenems, Gene Transfer, Horizontal, Humans, Plasmids, Prospective Studies, Clinical Sciences
Abstract: BackgroundCarbapenem-resistant Enterobacterales (CRE) are an urgent global health threat. Inferring the dynamics of local CRE dissemination is currently limited by our inability to confidently trace the spread of resistance determinants to unrelated bacterial hosts. Whole-genome sequence comparison is useful for identifying CRE clonal transmission and outbreaks, but high-frequency horizontal gene transfer (HGT) of carbapenem resistance genes and subsequent genome rearrangement complicate tracing the local persistence and mobilization of these genes across organisms.MethodsTo overcome this limitation, we developed a new approach to identify recent HGT of large, near-identical plasmid segments across species boundaries, which also allowed us to overcome technical challenges with genome assembly. We applied this to complete and near-complete genome assemblies to examine the local spread of CRE in a systematic, prospective collection of all CRE, as well as time- and species-matched carbapenem-susceptible Enterobacterales, isolated from patients from four US hospitals over nearly 5 years.ResultsOur CRE collection comprised a diverse range of species, lineages, and carbapenem resistance mechanisms, many of which were encoded on a variety of promiscuous plasmid types. We found and quantified rearrangement, persistence, and repeated transfer of plasmid segments, including those harboring carbapenemases, between organisms over multiple years. Some plasmid segments were found to be strongly associated with specific locales, thus representing geographic signatures that make it possible to trace recent and localized HGT events. Functional analysis of these signatures revealed genes commonly found in plasmids of nosocomial pathogens, such as functions required for plasmid retention and spread, as well survival against a variety of antibiotic and antiseptics common to the hospital environment.ConclusionsCollectively, the framework we developed provides a clearer, high-resolution picture of the epidemiology of antibiotic resistance importation, spread, and persistence in patients and healthcare networks.
Published: 2022

2. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H, Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B, Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N, Faro, Valeria Lo, Lopera-Maya, Esteban A, Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J, Chapman, Sinéad B, Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M, Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A, Guare, Lindsay A, Gignoux, Christopher R, Graham, Sarah E, Hornsby, Whitney E, Ingold, Nathan, Ismail, Said I, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y, Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H, Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M, Thani, Asma Al, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H, Damrauer, Scott M, Douville, Nicholas J, Finer, Sarah, Fritsche, Lars G, Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J, Guo, Yu, Hunt, Karen A, Ioannidis, Alexander, Jansonius, Nomdo M, Konuma, Takahiro, Lee, Ming Ta Michael, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E, Moatamed, Babak, Nava-Aguilar, Marco A, Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A, Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C, Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K, Franke, Lude, Gamazon, Eric R, Ganna, Andrea, Gaunt, Tom R, Ge, Tian, Huang, Hailiang, and Huffman, Jennifer
Subjects: Human Genome, Genetics, Biotechnology, Generic health relevance, Good Health and Well Being, Biobank of the Americas, Biobank Japan Project, BioMe, BioVU, CanPath - Ontario Health Study, China Kadoorie Biobank Collaborative Group, Colorado Center for Personalized Medicine, deCODE Genetics, Estonian Biobank, FinnGen, Generation Scotland, Genes & Health Research Team, LifeLines, Mass General Brigham Biobank, Michigan Genomics Initiative, National Biobank of Korea, Penn Medicine BioBank, Qatar Biobank, QSkin Sun and Health Study, Taiwan Biobank, HUNT Study, UCLA ATLAS Community Health Initiative, Uganda Genome Resource, UK Biobank, GWAS, ancestry diversity, biobank, genetic association studies, meta-analysis, phenotype harmonization
Abstract: Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
Published: 2022

3. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia

Author: Palmer, Duncan S, Howrigan, Daniel P, Chapman, Sinéad B, Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco PM, Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P, Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B, Goes, Fernando S, Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S, Landén, Mikael, Locke, Adam E, McIntosh, Andrew M, McQuillin, Andrew, Morris, Derek W, O’Donovan, Michael C, Ophoff, Roel A, Owen, Michael J, Pedersen, Nancy L, Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W, Solomonson, Matthew, Clair, David St, Stahl, Eli A, Vreeker, Annabel, Walters, James TR, Wang, Weiqing, Watts, Nicholas A, Yolken, Robert, Zandi, Peter P, and Neale, Benjamin M
Subjects: Biotechnology, Human Genome, Clinical Research, Serious Mental Illness, Schizophrenia, Brain Disorders, Bipolar Disorder, Mental Health, Genetics, 2.1 Biological and endogenous factors, Aetiology, Mental health, A Kinase Anchor Proteins, Exome, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Exome Sequencing, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract: We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10-9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD's polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.
Published: 2022

4. Rare coding variants in ten genes confer substantial risk for schizophrenia.

Author: Singh, Tarjinder, Poterba, Timothy, Curtis, David, Akil, Huda, Al Eissa, Mariam, Barchas, Jack D, Bass, Nicholas, Bigdeli, Tim B, Breen, Gerome, Bromet, Evelyn J, Buckley, Peter F, Bunney, William E, Bybjerg-Grauholm, Jonas, Byerley, William F, Chapman, Sinéad B, Chen, Wei J, Churchhouse, Claire, Craddock, Nicholas, Cusick, Caroline M, DeLisi, Lynn, Dodge, Sheila, Escamilla, Michael A, Eskelinen, Saana, Fanous, Ayman H, Faraone, Stephen V, Fiorentino, Alessia, Francioli, Laurent, Gabriel, Stacey B, Gage, Diane, Gagliano Taliun, Sarah A, Ganna, Andrea, Genovese, Giulio, Glahn, David C, Grove, Jakob, Hall, Mei-Hua, Hämäläinen, Eija, Heyne, Henrike O, Holi, Matti, Hougaard, David M, Howrigan, Daniel P, Huang, Hailiang, Hwu, Hai-Gwo, Kahn, René S, Kang, Hyun Min, Karczewski, Konrad J, Kirov, George, Knowles, James A, Lee, Francis S, Lehrer, Douglas S, Lescai, Francesco, Malaspina, Dolores, Marder, Stephen R, McCarroll, Steven A, McIntosh, Andrew M, Medeiros, Helena, Milani, Lili, Morley, Christopher P, Morris, Derek W, Mortensen, Preben Bo, Myers, Richard M, Nordentoft, Merete, O'Brien, Niamh L, Olivares, Ana Maria, Ongur, Dost, Ouwehand, Willem H, Palmer, Duncan S, Paunio, Tiina, Quested, Digby, Rapaport, Mark H, Rees, Elliott, Rollins, Brandi, Satterstrom, F Kyle, Schatzberg, Alan, Scolnick, Edward, Scott, Laura J, Sharp, Sally I, Sklar, Pamela, Smoller, Jordan W, Sobell, Janet L, Solomonson, Matthew, Stahl, Eli A, Stevens, Christine R, Suvisaari, Jaana, Tiao, Grace, Watson, Stanley J, Watts, Nicholas A, Blackwood, Douglas H, Børglum, Anders D, Cohen, Bruce M, Corvin, Aiden P, Esko, Tõnu, Freimer, Nelson B, Glatt, Stephen J, Hultman, Christina M, McQuillin, Andrew, Palotie, Aarno, Pato, Carlos N, Pato, Michele T, Pulver, Ann E, and St Clair, David
Subjects: Humans, Genetic Predisposition to Disease, Receptors, N-Methyl-D-Aspartate, Case-Control Studies, Schizophrenia, Mutation, Exome, Neurodevelopmental Disorders, Human Genome, Biotechnology, Mental Health, Neurosciences, Brain Disorders, Genetics, Serious Mental Illness, Aetiology, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract: Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P
Published: 2022

5. Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

Author: Bigdeli, Tim B, Genovese, Giulio, Georgakopoulos, Penelope, Meyers, Jacquelyn L, Peterson, Roseann E, Iyegbe, Conrad O, Medeiros, Helena, Valderrama, Jorge, Achtyes, Eric D, Kotov, Roman, Stahl, Eli A, Abbott, Colony, Azevedo, Maria Helena, Belliveau, Richard A, Bevilacqua, Elizabeth, Bromet, Evelyn J, Byerley, William, Carvalho, Celia Barreto, Chapman, Sinéad B, DeLisi, Lynn E, Dumont, Ashley L, O’Dushlaine, Colm, Evgrafov, Oleg V, Fochtmann, Laura J, Gage, Diane, Kennedy, James L, Kinkead, Becky, Macedo, Antonio, Moran, Jennifer L, Morley, Christopher P, Dewan, Mantosh J, Nemesh, James, Perkins, Diana O, Purcell, Shaun M, Rakofsky, Jeffrey J, Scolnick, Edward M, Sklar, Brooke M, Sklar, Pamela, Smoller, Jordan W, Sullivan, Patrick F, Macciardi, Fabio, Marder, Stephen R, Gur, Ruben C, Gur, Raquel E, Braff, David L, Nicolini, Humberto, Escamilla, Michael A, Vawter, Marquis P, Sobell, Janet L, Malaspina, Dolores, Lehrer, Douglas S, Buckley, Peter F, Rapaport, Mark H, Knowles, James A, Fanous, Ayman H, Pato, Michele T, McCarroll, Steven A, and Pato, Carlos N
Subjects: Human Genome, Serious Mental Illness, Clinical Research, Schizophrenia, Brain Disorders, Genetics, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Black People, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Male, Polymorphism, Single Nucleotide, Consortium on the Genetics of Schizophrenia (COGS) Investigators, Genomic Psychiatry Cohort (GPC) Consortium, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke's R2 = 0.032; liability R2 = 0.017; P
Published: 2020

6. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Mutaamba, Maasha, Partanen, Juulia J., Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Palta, Priit, Pandit, Anita, Preuss, Michael H., Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Zawistowski, Matthew, Zhong, Xue, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Konuma, Takahiro, Marioni, Riccardo E., Nomdo, Jansonius, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Trembath, Richard C., Vonk, Judith M., Whiteman, David, Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Cox, Nancy J., Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lin, Yen-Feng, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., Neale, Benjamin M., Lopera, Esteban, Kerminen, Sini, Wu, Kuan-Han, Bhatta, Laxmi, Brumpton, Ben, Deelen, Patrick, Murakami, Yoshinori, Willer, Cristen, and Hirbo, Jibril
Published: 2023
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7. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M., Al Thani, Asma, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Damrauer, Scott M., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Ioannidis, Alexander, Jansonius, Nomdo M., Konuma, Takahiro, Michael Lee, Ming Ta, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E., Moatamed, Babak, Nava-Aguilar, Marco A., Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Katsanis, Nicholas, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Takano, Tomohiro, Trembath, Richard C., Vonk, Judith M., Whiteman, David C., Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Bustamante, Carlos D., Cox, Nancy J., Fatumo, Segun, Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lee, Seunggeun, Lin, Yen-Feng, Mbarek, Hamdi, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Rader, Daniel J., Ritchie, Marylyn D., Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Biobank of the Americas, Biobank Japan Project, BioMe, BioVU, CanPath - Ontario Health Study, China Kadoorie Biobank Collaborative Group, Colorado Center for Personalized Medicine, deCODE Genetics, Estonian Biobank, FinnGen, Generation Scotland, Genes & Health Research Team, LifeLines, Mass General Brigham Biobank, Michigan Genomics Initiative, National Biobank of Korea, Penn Medicine BioBank, Qatar Biobank, The Qskin Sun and Health Study, Taiwan Biobank, The Hunt Study, Ucla Atlas Community Health Initiative, Uganda Genome Resource, Uk Biobank, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., Neale, Benjamin M., and Elzur, Roy
Published: 2022
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8. Increasing diversity in genomics requires investment in equitable partnerships and capacity building

Author: Martin, Alicia R., Stroud, II, Rocky E., Abebe, Tamrat, Akena, Dickens, Alemayehu, Melkam, Atwoli, Lukoye, Chapman, Sinéad B., Flowers, Katelyn, Gelaye, Bizu, Gichuru, Stella, Kariuki, Symon M., Kinyanjui, Sam, Korte, Kristina J., Koen, Nastassja, Koenen, Karestan C., Newton, Charles R. J. C., Olivares, Ana Maria, Pollock, Sam, Post, Kristianna, Singh, Ilina, Stein, Dan J., Teferra, Solomon, Zingela, Zukiswa, and Chibnik, Lori B.
Published: 2022
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9. Longitudinal multi-omics analyses link gut microbiome dysbiosis with recurrent urinary tract infections in women

Author: Worby, Colin J., Schreiber, IV, Henry L., Straub, Timothy J., van Dijk, Lucas R., Bronson, Ryan A., Olson, Benjamin S., Pinkner, Jerome S., Obernuefemann, Chloe L. P., Muñoz, Vanessa L., Paharik, Alexandra E., Azimzadeh, Philippe N., Walker, Bruce J., Desjardins, Christopher A., Chou, Wen-Chi, Bergeron, Karla, Chapman, Sinéad B., Klim, Aleksandra, Manson, Abigail L., Hannan, Thomas J., Hooton, Thomas M., Kau, Andrew L., Lai, H. Henry, Dodson, Karen W., Hultgren, Scott J., and Earl, Ashlee M.
Published: 2022
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10. Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations

Author: Martin, Alicia R., Atkinson, Elizabeth G., Chapman, Sinéad B., Stevenson, Anne, Stroud, Rocky E., Abebe, Tamrat, Akena, Dickens, Alemayehu, Melkam, Ashaba, Fred K., Atwoli, Lukoye, Bowers, Tera, Chibnik, Lori B., Daly, Mark J., DeSmet, Timothy, Dodge, Sheila, Fekadu, Abebaw, Ferriera, Steven, Gelaye, Bizu, Gichuru, Stella, Injera, Wilfred E., James, Roxanne, Kariuki, Symon M., Kigen, Gabriel, Koenen, Karestan C., Kwobah, Edith, Kyebuzibwa, Joseph, Majara, Lerato, Musinguzi, Henry, Mwema, Rehema M., Neale, Benjamin M., Newman, Carter P., Newton, Charles R.J.C., Pickrell, Joseph K., Ramesar, Raj, Shiferaw, Welelta, Stein, Dan J., Teferra, Solomon, van der Merwe, Celia, and Zingela, Zukiswa
Published: 2021
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11. Multi-institute analysis of carbapenem resistance reveals remarkable diversity, unexplained mechanisms, and limited clonal outbreaks

Author: Cerqueira, Gustavo C, Earl, Ashlee M, Ernst, Christoph M, Grad, Yonatan H, Dekker, John P, Feldgarden, Michael, Chapman, Sinéad B, Reis-Cunha, João L, Shea, Terrance P, Young, Sarah, Zeng, Qiandong, Delaney, Mary L, Kim, Diane, Peterson, Ellena M, O’Brien, Thomas F, Ferraro, Mary Jane, Hooper, David C, Huang, Susan S, Kirby, James E, Onderdonk, Andrew B, Birren, Bruce W, Hung, Deborah T, Cosimi, Lisa A, Wortman, Jennifer R, Murphy, Cheryl I, and Hanage, William P
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Microbiology, Clinical Sciences, Medical Microbiology, Antimicrobial Resistance, Infectious Diseases, Lung, Vaccine Related, Infection, Bacterial Proteins, Boston, Carbapenems, Clone Cells, Cross Infection, DNA Transposable Elements, Disease Outbreaks, Enterobacteriaceae, Enterobacteriaceae Infections, Genetic Variation, Genome, Bacterial, Humans, Prospective Studies, R Factors, Sequence Alignment, Transformation, Bacterial, beta-Lactam Resistance, beta-Lactamases, carbapenem resistance, comparative genomics, whole-genome sequencing, molecular evolution
Abstract: Carbapenem-resistant Enterobacteriaceae (CRE) are among the most severe threats to the antibiotic era. Multiple different species can exhibit resistance due to many different mechanisms, and many different mobile elements are capable of transferring resistance between lineages. We prospectively sampled CRE from hospitalized patients from three Boston-area hospitals, together with a collection of CRE from a single California hospital, to define the frequency and characteristics of outbreaks and determine whether there is evidence for transfer of strains within and between hospitals and the frequency with which resistance is transferred between lineages or species. We found eight species exhibiting resistance, with the majority of our sample being the sequence type 258 (ST258) lineage of Klebsiella pneumoniae There was very little evidence of extensive hospital outbreaks, but a great deal of variation in resistance mechanisms and the genomic backgrounds carrying these mechanisms. Local transmission was evident in clear phylogeographic structure between the samples from the two coasts. The most common resistance mechanisms were KPC (K. pneumoniae carbapenemases) beta-lactamases encoded by blaKPC2, blaKPC3, and blaKPC4, which were transferred between strains and species by seven distinct subgroups of the Tn4401 element. We also found evidence for previously unrecognized resistance mechanisms that produced resistance when transformed into a susceptible genomic background. The extensive variation, together with evidence of transmission beyond limited clonal outbreaks, points to multiple unsampled transmission chains throughout the continuum of care, including asymptomatic carriage and transmission of CRE. This finding suggests that to control this threat, we need an aggressive approach to surveillance and isolation.
Published: 2017

12. Limited effects of long-term daily cranberry consumption on the gut microbiome in a placebo-controlled study of women with recurrent urinary tract infections

Author: Straub, Timothy J., Chou, Wen-Chi, Manson, Abigail L., Schreiber, IV, Henry L., Walker, Bruce J., Desjardins, Christopher A., Chapman, Sinéad B., Kaspar, Kerrie L., Kahsai, Orsalem J., Traylor, Elizabeth, Dodson, Karen W., Hullar, Meredith A. J., Hultgren, Scott J., Khoo, Christina, and Earl, Ashlee M.
Published: 2021
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13. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Wang, Ying, Namba, Shinichi, Lopera-Maya, Esteban A., Kerminen, Sini, Tsuo, Kristin, Läll, Kristi, Kanai, Masahiro, Zhou, Wei, Wu, Kuan Han H., Favé, Marie Julie, Bhatta, Laxmi, Awadalla, Philip, Brumpton, Ben M., Deelen, Patrick, Hveem, Kristian, Lo Faro, Valeria, Mägi, Reedik, Murakami, Yoshinori, Sanna, Serena, Smoller, Jordan W., Uzunovic, Jasmina, Wolford, Brooke N., Rasheed, Humaira, Hirbo, Jibril B., Bhattacharya, Arjun, Zhao, Huiling, Surakka, Ida, Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Mutaamba, Maasha, Partanen, Juulia J., Chavan, Sameer, Chen, Tzu Ting, Daya, Michelle, Ding, Yi, Feng, Yen Chen A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Loos, Ruth J.F., Wang, Ying, Namba, Shinichi, Lopera-Maya, Esteban A., Kerminen, Sini, Tsuo, Kristin, Läll, Kristi, Kanai, Masahiro, Zhou, Wei, Wu, Kuan Han H., Favé, Marie Julie, Bhatta, Laxmi, Awadalla, Philip, Brumpton, Ben M., Deelen, Patrick, Hveem, Kristian, Lo Faro, Valeria, Mägi, Reedik, Murakami, Yoshinori, Sanna, Serena, Smoller, Jordan W., Uzunovic, Jasmina, Wolford, Brooke N., Rasheed, Humaira, Hirbo, Jibril B., Bhattacharya, Arjun, Zhao, Huiling, Surakka, Ida, Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Mutaamba, Maasha, Partanen, Juulia J., Chavan, Sameer, Chen, Tzu Ting, Daya, Michelle, Ding, Yi, Feng, Yen Chen A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., and Loos, Ruth J.F.
Abstract: Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.
Published: 2023

14. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Wang, Ying, primary, Namba, Shinichi, additional, Lopera, Esteban, additional, Kerminen, Sini, additional, Tsuo, Kristin, additional, Läll, Kristi, additional, Kanai, Masahiro, additional, Zhou, Wei, additional, Wu, Kuan-Han, additional, Favé, Marie-Julie, additional, Bhatta, Laxmi, additional, Awadalla, Philip, additional, Brumpton, Ben, additional, Deelen, Patrick, additional, Hveem, Kristian, additional, Lo Faro, Valeria, additional, Mägi, Reedik, additional, Murakami, Yoshinori, additional, Sanna, Serena, additional, Smoller, Jordan W., additional, Uzunovic, Jasmina, additional, Wolford, Brooke N., additional, Willer, Cristen, additional, Gamazon, Eric R., additional, Cox, Nancy J., additional, Surakka, Ida, additional, Okada, Yukinori, additional, Martin, Alicia R., additional, Hirbo, Jibril, additional, Wu, Kuan-Han H., additional, Rasheed, Humaira, additional, Hirbo, Jibril B., additional, Wang, Ying, additional, Bhattacharya, Arjun, additional, Zhao, Huiling, additional, Lopera-Maya, Esteban A., additional, Chapman, Sinéad B., additional, Karjalainen, Juha, additional, Kurki, Mitja, additional, Mutaamba, Maasha, additional, Partanen, Juulia J., additional, Brumpton, Ben M., additional, Chavan, Sameer, additional, Chen, Tzu-Ting, additional, Daya, Michelle, additional, Ding, Yi, additional, Feng, Yen-Chen A., additional, Gignoux, Christopher R., additional, Graham, Sarah E., additional, Hornsby, Whitney E., additional, Ingold, Nathan, additional, Johnson, Ruth, additional, Laisk, Triin, additional, Lin, Kuang, additional, Lv, Jun, additional, Millwood, Iona Y., additional, Palta, Priit, additional, Pandit, Anita, additional, Preuss, Michael H., additional, Thorsteinsdottir, Unnur, additional, Zawistowski, Matthew, additional, Zhong, Xue, additional, Campbell, Archie, additional, Crooks, Kristy, additional, de Bock, Geertruida H., additional, Douville, Nicholas J., additional, Finer, Sarah, additional, Fritsche, Lars G., additional, Griffiths, Christopher J., additional, Guo, Yu, additional, Hunt, Karen A., additional, Konuma, Takahiro, additional, Marioni, Riccardo E., additional, Nomdo, Jansonius, additional, Patil, Snehal, additional, Rafaels, Nicholas, additional, Richmond, Anne, additional, Shortt, Jonathan A., additional, Straub, Peter, additional, Tao, Ran, additional, Vanderwerff, Brett, additional, Barnes, Kathleen C., additional, Boezen, Marike, additional, Chen, Zhengming, additional, Chen, Chia-Yen, additional, Cho, Judy, additional, Smith, George Davey, additional, Finucane, Hilary K., additional, Franke, Lude, additional, Ganna, Andrea, additional, Gaunt, Tom R., additional, Ge, Tian, additional, Huang, Hailiang, additional, Huffman, Jennifer, additional, Koskela, Jukka T., additional, Lajonchere, Clara, additional, Law, Matthew H., additional, Li, Liming, additional, Lindgren, Cecilia M., additional, Loos, Ruth J.F., additional, MacGregor, Stuart, additional, Matsuda, Koichi, additional, Olsen, Catherine M., additional, Porteous, David J., additional, Shavit, Jordan A., additional, Snieder, Harold, additional, Trembath, Richard C., additional, Vonk, Judith M., additional, Whiteman, David, additional, Wicks, Stephen J., additional, Wijmenga, Cisca, additional, Wright, John, additional, Zheng, Jie, additional, Zhou, Xiang, additional, Boehnke, Michael, additional, Geschwind, Daniel H., additional, Hayward, Caroline, additional, Kenny, Eimear E., additional, Lin, Yen-Feng, additional, Martin, Hilary C., additional, Medland, Sarah E., additional, Palotie, Aarno V., additional, Pasaniuc, Bogdan, additional, Stefansson, Kari, additional, van Heel, David A., additional, Walters, Robin G., additional, Zöllner, Sebastian, additional, Willer, Cristen J., additional, Daly, Mark J., additional, and Neale, Benjamin M., additional
Published: 2023
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15. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H, Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B, Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N, Lo Faro, Valeria, Lopera-Maya, Esteban A, Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J, Chapman, Sinéad B, Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M, Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A, Guare, Lindsay A, Gignoux, Christopher R, Graham, Sarah E, Hornsby, Whitney E, Ingold, Nathan, Ismail, Said I, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y, Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H, Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M, Al Thani, Asma, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, De Bock, Geertruida H, Damrauer, Scott M, Douville, Nicholas J, Finer, Sarah, Fritsche, Lars G, Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J, Guo, Yu, Hunt, Karen A, Ioannidis, Alexander, Jansonius, Nomdo M, Konuma, Takahiro, Lee, Ming Ta Michael, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E, Moatamed, Babak, Nava-Aguilar, Marco A, Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A, Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C, Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K, Franke, Lude, Gamazon, Eric R, Ganna, Andrea, Gaunt, Tom R, Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Katsanis, Nicholas, Koskela, Jukka T, Lajonchere, Clara, Law, Matthew H, Li, Liming, Lindgren, Cecilia M, Loos, Ruth JF, MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M, Porteous, David J, Shavit, Jordan A, Snieder, Harold, Takano, Tomohiro, Trembath, Richard C, Vonk, Judith M, Whiteman, David C, Wicks, Stephen J, Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Bustamante, Carlos D, Cox, Nancy J, Fatumo, Segun, Geschwind, Daniel H, Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E, Lee, Seunggeun, Lin, Yen-Feng, Mbarek, Hamdi, Mägi, Reedik, Martin, Hilary C, Medland, Sarah E, Okada, Yukinori, Palotie, Aarno V, Pasaniuc, Bogdan, Rader, Daniel J, Ritchie, Marylyn D, Sanna, Serena, Smoller, Jordan W, Stefansson, Kari, Van Heel, David A, Walters, Robin G, Zöllner, Sebastian, Biobank Of The Americas, Biobank Japan Project, BioMe, BioVU, CanPath-Ontario Health Study, China Kadoorie Biobank Collaborative Group, Colorado Center For Personalized Medicine, DeCODE Genetics, Estonian Biobank, FinnGen, Generation Scotland, Genes & Health Research Team, LifeLines, Mass General Brigham Biobank, Michigan Genomics Initiative, National Biobank Of Korea, Penn Medicine BioBank, Qatar Biobank, QSkin Sun And Health Study, Taiwan Biobank, HUNT Study, UCLA ATLAS Community Health Initiative, Uganda Genome Resource, UK Biobank, Martin, Alicia R, Willer, Cristen J, Daly, Mark J, Neale, Benjamin M, Namba, Shinichi [0000-0002-7486-3146], Guare, Lindsay A [0000-0001-6988-5319], Palta, Priit [0000-0001-9320-7008], de Bock, Geertruida H [0000-0003-3104-4471], Finer, Sarah [0000-0002-2684-4653], Jansonius, Nomdo M [0000-0002-6495-6568], Rojas-Muñoz, Agustin [0000-0001-7594-0599], Gamazon, Eric R [0000-0003-4204-8734], Ganna, Andrea [0000-0002-8147-240X], Koskela, Jukka T [0000-0002-0154-7222], MacGregor, Stuart [0000-0001-6731-8142], Palotie, Aarno V [0000-0002-2527-5874], and Apollo - University of Cambridge Repository
Subjects: biobank, meta-analysis, genetic association studies, GWAS, ancestry diversity, phenotype harmonization
Abstract: Funder: Biogen, Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
Published: 2023
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16. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak

Author: Gire, Stephen K., Goba, Augustine, Andersen, Kristian G., Sealfon, Rachel S. G., Park, Daniel J., Kanneh, Lansana, Jalloh, Simbirie, Momoh, Mambu, Fullah, Mohamed, Dudas, Gytis, Wohl, Shirlee, Moses, Lina M., Yozwiak, Nathan L., Winnicki, Sarah, Matranga, Christian B., Malboeuf, Christine M., Qu, James, Gladden, Adrianne D., Schaffner, Stephen F., Yang, Xiao, Jiang, Pan-Pan, Nekoui, Mahan, Colubri, Andres, Coomber, Moinya Ruth, Fonnie, Mbalu, Moigboi, Alex, Gbakie, Michael, Kamara, Fatima K., Tucker, Veronica, Konuwa, Edwin, Saffa, Sidiki, Sellu, Josephine, Jalloh, Abdul Azziz, Kovoma, Alice, Koninga, James, Mustapha, Ibrahim, Kargbo, Kandeh, Foday, Momoh, Yillah, Mohamed, Kanneh, Franklyn, Robert, Willie, Massally, James L. B., Chapman, Sinéad B., Bochicchio, James, Murphy, Cheryl, Nusbaum, Chad, Young, Sarah, Birren, Bruce W., Grant, Donald S., Scheiffelin, John S., Lander, Eric S., Happi, Christian, Gevao, Sahr M., Gnirke, Andreas, Rambaut, Andrew, Garry, Robert F., Khan, S. Humarr, and Sabeti, Pardis C.
Published: 2014

17. Rare coding variants in 10 genes confer substantial risk for schizophrenia

Author: Singh, Tarjinder, Poterba, Timothy, Curtis, David, Akil, Huda, Al Eissa, Mariam, Barchas, Jack D., Bass, Nicholas, Bigdeli, Tim B., Breen, Gerome, Bromet, Evelyn J., Buckley, Peter F., Bunney, William E., Bybjerg-Grauholm, Jonas, Byerley, William F., Chapman, Sinéad B., Chen, Wei J., Churchhouse, Claire, Craddock, Nicholas, Cusick, Caroline M., DeLisi, Lynn, Dodge, Sheila, Escamilla, Michael A., Eskelinen, Saana, Fanous, Ayman H., Faraone, Stephen V., Fiorentino, Alessia, Francioli, Laurent, Gabriel, Stacey B., Gage, Diane, Taliun, Sarah A. Gagliano, Ganna, Andrea, Genovese, Giulio, Glahn, David C., Grove, Jakob, Hall, Mei-Hua, Hämäläinen, Eija, Heyne, Henrike O., Holi, Matti, Hougaard, David M., Howrigan, Daniel P., Huang, Hailiang, Hwu, Hai-Gwo, Kahn, René S., Kang, Hyun Min, Karczewski, Konrad J., Kirov, George, Knowles, James A., Lee, Francis S., Lehrer, Douglas S., Lescai, Francesco, Malaspina, Dolores, Marder, Stephen R., McCarroll, Steven A., McIntosh, Andrew M., Medeiros, Helena, Milani, Lili, Morley, Christopher P., Morris, Derek W., Bo Mortensen, Preben, Myers, Richard M., Nordentoft, Merete, O’Brien, Niamh L., Olivares, Ana Maria, Ongur, Dost, Ouwehand, Willem H., Palmer, Duncan S., Paunio, Tiina, Quested, Digby, Rapaport, Mark H., Rees, Elliott, Rollins, Brandi, Satterstrom, F. Kyle, Schatzberg, Alan, Scolnick, Edward, Scott, Laura J., Sharp, Sally I., Sklar, Pamela, Smoller, Jordan W., Sobell, Janet l., Solomonson, Matthew, Stevens, Christine R., Suvisaari, Jaana, Tiao, Grace, Watson, Stanley J., Watts, Nicholas A., Blackwood, Douglas H., Børglum, Anders D., Cohen, Bruce M., Corvin, Aiden P., Esko, Tõnu, Freimer, Nelson B., Glatt, Stephen J., Hultman, Christina M., McQuillin, Andrew, Palotie, Aarno, Pato, Carlos N., Pato, Michele T., Pulver, Ann E., St. Clair, David, Tsuang, Ming T., Vawter, Marquis P., Walters, James T., Werge, Thomas M., Ophoff, Roel A., Sullivan, Patrick F., Owen, Michael J., Boehnke, Michael, O’Donovan, Michael C., Neale, Benjamin M., and Daly, Mark J.
Subjects: Article
Abstract: Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analyzing the whole-exomes of 24,248 cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in ten genes as conferring substantial risk for schizophrenia (odds ratios 3 – 50, P < 2.14 × 10(−6)), and 32 genes at a FDR < 5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure, and function of the synapse. The associations of NMDA receptor subunit GRIN2A and AMPA receptor subunit GRIA3 provide support for the dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk between schizophrenia, autism spectrum disorders (ASD)(1), epilepsy and severe neurodevelopmental disorders (DD/ID)(2), though in some shared genes different mutation types are implicated. Most genes described here however are not implicated in neurodevelopment and we demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk(3), suggesting that common and rare genetic risk factors at least partially converge on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, implying that more risk genes await discovery using this approach.
Published: 2022

18. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia

Author: Palmer, Duncan S., Howrigan, Daniel P., Chapman, Sinéad B., Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco P. M., Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P., Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B., Goes, Fernando S., Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S., Landén, Mikael, Locke, Adam E., McIntosh, Andrew M., McQuillin, Andrew, Morris, Derek W., O’Donovan, Michael C., Ophoff, Roel A., Owen, Michael J., Pedersen, Nancy L., Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W., Solomonson, Matthew, Clair, David St., Stahl, Eli A., Vreeker, Annabel, Walters, James T. R., Wang, Weiqing, Watts, Nicholas A., Yolken, Robert, Zandi, Peter P., Neale, Benjamin M., Palmer, Duncan S., Howrigan, Daniel P., Chapman, Sinéad B., Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco P. M., Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P., Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B., Goes, Fernando S., Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S., Landén, Mikael, Locke, Adam E., McIntosh, Andrew M., McQuillin, Andrew, Morris, Derek W., O’Donovan, Michael C., Ophoff, Roel A., Owen, Michael J., Pedersen, Nancy L., Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W., Solomonson, Matthew, Clair, David St., Stahl, Eli A., Vreeker, Annabel, Walters, James T. R., Wang, Weiqing, Watts, Nicholas A., Yolken, Robert, Zandi, Peter P., and Neale, Benjamin M.
Abstract: We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10−9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD’s polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.
Published: 2022
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19. Global Biobank Meta-analysis Initiative:Powering genetic discovery across human disease

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu Ting, Daya, Michelle, Ding, Yi, Feng, Yen Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Loos, Ruth J.F., Zhou, Wei, Kanai, Masahiro, Wu, Kuan Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu Ting, Daya, Michelle, Ding, Yi, Feng, Yen Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, and Loos, Ruth J.F.
Abstract: Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
Published: 2022

20. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia

Author: Onderzoeksgroep 2, Brain, Palmer, Duncan S, Howrigan, Daniel P, Chapman, Sinéad B, Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco P M, Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P, Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B, Goes, Fernando S, Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S, Landén, Mikael, Locke, Adam E, McIntosh, Andrew M, McQuillin, Andrew, Morris, Derek W, O'Donovan, Michael C, Ophoff, Roel A, Owen, Michael J, Pedersen, Nancy L, Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W, Solomonson, Matthew, Clair, David St, Stahl, Eli A, Vreeker, Annabel, Walters, James T R, Wang, Weiqing, Watts, Nicholas A, Yolken, Robert, Zandi, Peter P, Neale, Benjamin M, Onderzoeksgroep 2, Brain, Palmer, Duncan S, Howrigan, Daniel P, Chapman, Sinéad B, Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco P M, Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P, Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B, Goes, Fernando S, Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S, Landén, Mikael, Locke, Adam E, McIntosh, Andrew M, McQuillin, Andrew, Morris, Derek W, O'Donovan, Michael C, Ophoff, Roel A, Owen, Michael J, Pedersen, Nancy L, Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W, Solomonson, Matthew, Clair, David St, Stahl, Eli A, Vreeker, Annabel, Walters, James T R, Wang, Weiqing, Watts, Nicholas A, Yolken, Robert, Zandi, Peter P, and Neale, Benjamin M
Published: 2022

21. Additional file 3 of Inter-species geographic signatures for tracing horizontal gene transfer and long-term persistence of carbapenem resistance

Author: Salamzade, Rauf, Manson, Abigail L., Walker, Bruce J., Brennan-Krohn, Thea, Worby, Colin J., Ma, Peijun, He, Lorrie L., Shea, Terrance P., Qu, James, Chapman, Sinéad B., Howe, Whitney, Young, Sarah K., Wurster, Jenna I., Delaney, Mary L., Kanjilal, Sanjat, Onderdonk, Andrew B., Bittencourt, Cassiana E., Gussin, Gabrielle M., Kim, Diane, Peterson, Ellena M., Ferraro, Mary Jane, Hooper, David C., Shenoy, Erica S., Cuomo, Christina A., Cosimi, Lisa A., Huang, Susan S., Kirby, James E., Pierce, Virginia M., Bhattacharyya, Roby P., and Earl, Ashlee M.
Abstract: Additional file 3. Supplementary Results.
Published: 2022
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22. Additional file 2 of Inter-species geographic signatures for tracing horizontal gene transfer and long-term persistence of carbapenem resistance

Author: Salamzade, Rauf, Manson, Abigail L., Walker, Bruce J., Brennan-Krohn, Thea, Worby, Colin J., Ma, Peijun, He, Lorrie L., Shea, Terrance P., Qu, James, Chapman, Sinéad B., Howe, Whitney, Young, Sarah K., Wurster, Jenna I., Delaney, Mary L., Kanjilal, Sanjat, Onderdonk, Andrew B., Bittencourt, Cassiana E., Gussin, Gabrielle M., Kim, Diane, Peterson, Ellena M., Ferraro, Mary Jane, Hooper, David C., Shenoy, Erica S., Cuomo, Christina A., Cosimi, Lisa A., Huang, Susan S., Kirby, James E., Pierce, Virginia M., Bhattacharyya, Roby P., and Earl, Ashlee M.
Abstract: Additional file 2: Fig. S1. Method for the delineation of segments shared between plasmids. Fig. S2. Workflow to identify geographic signatures. Fig. S3. Phylogenetic tree for each of the 15 species in our collection with at least five representatives. Fig. S4. Resistance mechanisms were diverse, with many shared across species. Fig. S5. Carbapenemase-carrying isolates tended to have a higher minimum inhibitory concentration than those with other resistance mechanisms. Fig. S6. High level of diversity and phylogenetic range among predicted plasmids. Fig. S7. Plasmids of diverse groups carried carbapenemases and were found in different species, and hospitals. Fig. S8. Limited tracing of carbapenemase localized spread using Tn4401 isoforms and their immediate flanking sequences. Fig. S9. Signatures were present across diverse sequence types. Fig. S10. Signatures carried genes important for hospital adaptation and signature mobility. Fig. S11. Details of signature content. Fig. S12. Signatures were highly conserved and likely derived from a common ancestral sequence. Fig. S13. Geographic signatures with blaKPC can occur in multiple configurations across several species and plasmid groups. Fig. S14. Geographic signatures with blaKPC occurred in multiple configurations across several species and plasmid groups.
Published: 2022
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23. Sequencing of Culex quinquefasciatus Establishes a Platform for Mosquito Comparative Genomics

Author: Arensburger, Peter, Megy, Karine, Waterhouse, Robert M., Abrudan, Jenica, Amedeo, Paolo, Antelo, Beatriz, Bartholomay, Lyric, Bidwell, Shelby, Caler, Elisabet, Camara, Francisco, Campbell, Corey L., Campbell, Kathryn S., Casola, Claudio, Castro, Marta T., Chandramouliswaran, Ishwar, Chapman, Sinéad B., Christley, Scott, Costas, Javier, Eisenstadt, Eric, Feschotte, Cedric, Fraser-Liggett, Claire, Guigo, Roderic, Haas, Brian, Hammond, Martin, Hansson, Bill S., Hemingway, Janet, Hill, Sharon R., Howarth, Clint, Ignell, Rickard, Kennedy, Ryan C., Kodira, Chinnappa D., Lobo, Neil F., Mao, Chunhong, Mayhew, George, Michel, Kristin, Mori, Akio, Liu, Nannan, Naveira, Horado, Nene, Vishvanath, Nguyen, Nam, Pearson, Matthew D., Pritham, Ellen J., Puiu, Daniela, Qi, Yumin, Ranson, Hilary, Ribeiro, Jose M. C., Roberston, Hugh M., Severson, David W., Shumway, Martin, Stanke, Mario, Strausberg, Robert L., Sun, Cheng, Sutton, Granger, Tubio, Jose Manuel C., Unger, Maria F., Vanlandingham, Dana L., Vilella, Albert J., White, Owen, White, Jared R., Wondji, Charles S., Wortman, Jennifer, Zdobnov, Evgeny M., Birren, Bruce, Christensen, Bruce M., Collins, Frank H., Cornel, Anthony, Dimopoulos, George, Hannick, Linda I., Higgs, Stephen, Lanzaro, Gregory C., Lawson, Daniel, Lee, Norman H., Muskavitch, Marc A. T., Raikhel, Alexander S., and Atkinson, Peter W.
Published: 2010

24. Pathogenomics of Culex quinquefasciatus and Meta-Analysis of Infection Responses to Diverse Pathogens

Author: Bartholomay, Lyric C., Waterhouse, Robert M., Mayhew, George F., Campbell, Corey L., Michel, Kristin, Zou, Zhen, Ramirez, Jose L., Das, Suchismita, Alvarez, Kanwal, Arensburger, Peter, Bryant, Bart, Chapman, Sinead B., Dong, Yuemei, Erickson, Sara M., Karunaratne, S. H. P. Parakrama, Kokoza, Vladimir, Kodira, Chinnappa D., Pignatelli, Patricia, Shin, Sang Woon, Vanlandingham, Dana L., Atkinson, Peter W., Birren, Bruce, Christophides, George K., Clem, Rollie J., Hemingway, Janet, Higgs, Stephen, Megy, Karine, Ranson, Hilary, Zdobnov, Evgeny M., Raikhel, Alexander S., Christensen, Bruce M., Dimopoulos, George, and Muskavitch, Marc A. T.
Published: 2010

25. Inter-species geographic signatures for tracing horizontal gene transfer and long-term persistence of carbapenem resistance

Author: Salamzade, Rauf, primary, Manson, Abigail L., additional, Walker, Bruce J., additional, Brennan-Krohn, Thea, additional, Worby, Colin J., additional, Ma, Peijun, additional, He, Lorrie L., additional, Shea, Terrance P., additional, Qu, James, additional, Chapman, Sinéad B., additional, Howe, Whitney, additional, Young, Sarah K., additional, Wurster, Jenna I., additional, Delaney, Mary L., additional, Kanjilal, Sanjat, additional, Onderdonk, Andrew B., additional, Pironti, Alejandro, additional, Bittencourt, Cassiana E., additional, Gussin, Gabrielle M., additional, Kim, Diane, additional, Peterson, Ellena M., additional, Ferraro, Mary Jane, additional, Hooper, David C., additional, Shenoy, Erica S., additional, Cuomo, Christina A., additional, Hung, Deborah T., additional, Cosimi, Lisa A., additional, Huang, Susan S., additional, Kirby, James E., additional, Pierce, Virginia M., additional, Bhattacharyya, Roby P., additional, and Earl, Ashlee M., additional
Published: 2021
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26. Gut-bladder axis syndrome associated with recurrent UTIs in humans

Author: Worby, Colin J., primary, Schreiber, Henry L., additional, Straub, Timothy J., additional, van Dijk, Lucas R., additional, Bronson, Ryan A., additional, Olson, Benjamin, additional, Pinkner, Jerome S., additional, Obernuefemann, Chloe L. P., additional, Muñoz, Vanessa L., additional, Paharik, Alexandra E., additional, Walker, Bruce J., additional, Desjardins, Christopher A., additional, Chou, Wen-Chi, additional, Bergeron, Karla, additional, Chapman, Sinéad B., additional, Klim, Aleksandra, additional, Manson, Abigail L., additional, Hannan, Thomas J., additional, Hooton, Thomas M., additional, Kau, Andrew L., additional, Lai, H. Henry, additional, Dodson, Karen W., additional, Hultgren, Scott J., additional, and Earl, Ashlee M., additional
Published: 2021
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27. Additional file 8 of Limited effects of long-term daily cranberry consumption on the gut microbiome in a placebo-controlled study of women with recurrent urinary tract infections

Author: Straub, Timothy J., Chou, Wen-Chi, Manson, Abigail L., Schreiber, Henry L., Walker, Bruce J., Desjardins, Christopher A., Chapman, Sinéad B., Kaspar, Kerrie L., Orsalem J. Kahsai, Traylor, Elizabeth, Dodson, Karen W., Hullar, Meredith A. J., Hultgren, Scott J., Khoo, Christina, and Earl, Ashlee M.
Subjects: respiratory system, human activities
Abstract: Additional file 8: Figure S1. Additional analysis of diversity using 16S data. a) Shannon diversity index, a measure of ɑ-diversity, is not significantly different between cranberry and placebo cohort (p > 0.5) b) β-diversity of longitudinal samples from the same subject is significantly lower than that between samples from different subjects (p = 1.6 × 10− 20); c) β-diversity of samples from the placebo cohort versus those from the cranberry cohort do not differ significantly; p = 0.51).
Published: 2021
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28. Additional file 16 of Limited effects of long-term daily cranberry consumption on the gut microbiome in a placebo-controlled study of women with recurrent urinary tract infections

Author: Straub, Timothy J., Chou, Wen-Chi, Manson, Abigail L., Schreiber, Henry L., Walker, Bruce J., Desjardins, Christopher A., Chapman, Sinéad B., Kaspar, Kerrie L., Orsalem J. Kahsai, Traylor, Elizabeth, Dodson, Karen W., Hullar, Meredith A. J., Hultgren, Scott J., Khoo, Christina, and Earl, Ashlee M.
Abstract: Additional file 16: Figure S9. Oligotyping entropy profile for OTU41. X axis is the position in the alignment to OTU41 consensus sequence. Y axis is the Shannon Entropy of each position in the sequences that were clustered into OTU41. Position 183 was the only position in the OTU41 alignment that was above an entropy of 0.4. The background highlights the major oligotypes based on the top 6 most entropic positions, which represent the G and A alleles at position 183.
Published: 2021
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29. Additional file 9 of Limited effects of long-term daily cranberry consumption on the gut microbiome in a placebo-controlled study of women with recurrent urinary tract infections

Author: Straub, Timothy J., Chou, Wen-Chi, Manson, Abigail L., Schreiber, Henry L., Walker, Bruce J., Desjardins, Christopher A., Chapman, Sinéad B., Kaspar, Kerrie L., Orsalem J. Kahsai, Traylor, Elizabeth, Dodson, Karen W., Hullar, Meredith A. J., Hultgren, Scott J., Khoo, Christina, and Earl, Ashlee M.
Abstract: Additional file 9: Figure S2. Analysis of WMS data confirms that cranberry beverage consumption does not change overall gut microbiome composition. a) WMS-based taxonomic profiles displaying the phylum-level composition of the microbial population indicate that the composition did not change over time or due to cranberry consumption. The sample order was sorted by the relative abundance of Firmicutes. b) The species richness, based on WMS data, did not change significantly with cranberry beverage consumption. c) A comparison of all samples at the 16S OTU level, using principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarities, indicated that the samples from the cranberry cohort did not cluster into a specific group, and the trajectories from week 0 to week 24 (shown by arrows) were scattered, indicating no common shift in microbial composition after 24 weeks of cranberry or placebo treatment. The first two principal components (PCo1 and PCo2) accounted for 14.8 and 10.8% of the variability, respectively.
Published: 2021
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30. Gut-bladder axis syndrome associated with recurrent UTIs in humans

Author: Worby, Colin J., Schreiber, Henry L., IV, Straub, Timothy J., van Dijk, Lucas R., Bronson, Ryan A., Olson, Benjamin, Pinkner, Jerome S., Obernuefemann, Chloe L. P., Muñoz, Vanessa L., Paharik, Alexandra E., Walker, Bruce J., Desjardins, Christopher A., Chou, Wen-Chi, Bergeron, Karla, Chapman, Sinéad B., Klim, Aleksandra, Manson, Abigail L., Hannan, Thomas J., Hooton, Thomas M., Kau, Andrew L., Lai, H. Henry, Dodson, Karen W., Hultgren, Scott J., Earl, Ashlee M., Worby, Colin J., Schreiber, Henry L., IV, Straub, Timothy J., van Dijk, Lucas R., Bronson, Ryan A., Olson, Benjamin, Pinkner, Jerome S., Obernuefemann, Chloe L. P., Muñoz, Vanessa L., Paharik, Alexandra E., Walker, Bruce J., Desjardins, Christopher A., Chou, Wen-Chi, Bergeron, Karla, Chapman, Sinéad B., Klim, Aleksandra, Manson, Abigail L., Hannan, Thomas J., Hooton, Thomas M., Kau, Andrew L., Lai, H. Henry, Dodson, Karen W., Hultgren, Scott J., and Earl, Ashlee M.
Abstract: Recurrent urinary tract infections (rUTIs) are a major health burden worldwide, with history of infection being a significant risk factor. While the gut is a known reservoir for uropathogenic bacteria, the role of the microbiota in rUTI remains unclear. We conducted a year-long study of women with and without history of rUTIs, from whom we collected urine, blood and monthly fecal samples for multi-omic interrogation. The rUTI gut microbiome was significantly depleted in microbial richness and butyrate-producing bacteria compared to controls, reminiscent of other inflammatory conditions, though Escherichia coli gut and bladder dynamics were comparable between cohorts. Blood samples revealed signals of differential systemic immunity, leading us to hypothesize that rUTI susceptibility is in part mediated through a syndrome involving the gut-bladder axis, comprising gut dysbiosis and differential immune response to bacterial bladder colonization, manifesting in symptoms. This work highlights the potential for microbiome therapeutics to prevent and treat rUTIs.
Published: 2021

31. The malaria parasite Plasmodium vivax exhibits greater genetic diversity than Plasmodium falciparum

Author: Neafsey, Daniel E, Galinsky, Kevin, Jiang, Rays H Y, Young, Lauren, Sykes, Sean M, Saif, Sakina, Gujja, Sharvari, Goldberg, Jonathan M, Young, Sarah, Zeng, Qiandong, Chapman, Sinéad B, Dash, Aditya P, Anvikar, Anupkumar R, Sutton, Patrick L, Birren, Bruce W, Escalante, Ananias A, Barnwell, John W, and Carlton, Jane M
Published: 2012
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32. VIRAL EVOLUTION: Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak

Author: Gire, Stephen K., Goba, Augustine, Andersen, Kristian G., Sealfon, Rachel S. G., Park, Daniel J., Kanneh, Lansana, Jalloh, Simbirie, Momoh, Mambu, Fullah, Mohamed, Dudas, Gytis, Wohl, Shirlee, Moses, Lina M., Yozwiak, Nathan L., Winnicki, Sarah, Matranga, Christian B., Malboeuf, Christine M., Qu, James, Gladden, Adrianne D., Schaffner, Stephen F., Yang, Xiao, Jiang, Pan-Pan, Nekoui, Mahan, Colubri, Andres, Coomber, Moinya Ruth, Fonnie, Mbalu, Moigboi, Alex, Gbakie, Michael, Kamara, Fatima K., Tucker, Veronica, Konuwa, Edwin, Saffa, Sidiki, Sellu, Josephine, Jalloh, Abdul Azziz, Kovoma, Alice, Koninga, James, Mustapha, Ibrahim, Kargbo, Kandeh, Foday, Momoh, Yillah, Mohamed, Kanneh, Franklyn, Robert, Willie, Massally, James L. B., Chapman, Sinéad B., Bochicchio, James, Murphy, Cheryl, Nusbaum, Chad, Young, Sarah, Birren, Bruce W., Grant, Donald S., Scheiffelin, John S., Lander, Eric S., Happi, Christian, Gevao, Sahr M., Gnirke, Andreas, Rambaut, Andrew, Garry, Robert F., Khan, S. Humarr, and Sabeti, Pardis C.
Published: 2014
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33. Exome sequencing in bipolar disorder reveals shared risk geneAKAP11with schizophrenia

Author: Palmer, Duncan S, primary, Howrigan, Daniel P, additional, Chapman, Sinéad B, additional, Adolfsson, Rolf, additional, Bass, Nick, additional, Blackwood, Douglas, additional, Boks, Marco PM, additional, Chen, Chia-Yen, additional, Churchhouse, Claire, additional, Corvin, Aiden P, additional, Craddock, Nicholas, additional, Curtis, David, additional, Di Florio, Arianna, additional, Dickerson, Faith, additional, Goes, Fernando S, additional, Jia, Xiaoming, additional, Jones, Ian, additional, Jones, Lisa, additional, Jonsson, Lina, additional, Kahn, Rene S, additional, Landén, Mikael, additional, Locke, Adam, additional, McIntosh, Andrew, additional, McQuillin, Andrew, additional, Morris, Derek W, additional, O’Donovan, Michael C, additional, Ophoff, Roel A, additional, Owen, Michael J, additional, Pedersen, Nancy, additional, Posthuma, Danielle, additional, Reif, Andreas, additional, Risch, Neil, additional, Schaefer, Catherine, additional, Scott, Laura, additional, Singh, Tarjinder, additional, Smoller, Jordan W, additional, Solomonson, Matthew, additional, St. Clair, David, additional, Stahl, Eli A, additional, Vreeker, Annabel, additional, Walters, James, additional, Wang, Weiqing, additional, Watts, Nicholas A, additional, Yolken, Robert, additional, Zandi, Peter, additional, and Neale, Benjamin M, additional
Published: 2021
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34. Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events

Author: Lemieux, Jacob E., primary, Siddle, Katherine J., additional, Shaw, Bennett M., additional, Loreth, Christine, additional, Schaffner, Stephen F., additional, Gladden-Young, Adrianne, additional, Adams, Gordon, additional, Fink, Timelia, additional, Tomkins-Tinch, Christopher H., additional, Krasilnikova, Lydia A., additional, DeRuff, Katherine C., additional, Rudy, Melissa, additional, Bauer, Matthew R., additional, Lagerborg, Kim A., additional, Normandin, Erica, additional, Chapman, Sinéad B., additional, Reilly, Steven K., additional, Anahtar, Melis N., additional, Lin, Aaron E., additional, Carter, Amber, additional, Myhrvold, Cameron, additional, Kemball, Molly E., additional, Chaluvadi, Sushma, additional, Cusick, Caroline, additional, Flowers, Katelyn, additional, Neumann, Anna, additional, Cerrato, Felecia, additional, Farhat, Maha, additional, Slater, Damien, additional, Harris, Jason B., additional, Branda, John A., additional, Hooper, David, additional, Gaeta, Jessie M., additional, Baggett, Travis P., additional, O’Connell, James, additional, Gnirke, Andreas, additional, Lieberman, Tami D., additional, Philippakis, Anthony, additional, Burns, Meagan, additional, Brown, Catherine M., additional, Luban, Jeremy, additional, Ryan, Edward T., additional, Turbett, Sarah E., additional, LaRocque, Regina C., additional, Hanage, William P., additional, Gallagher, Glen R., additional, Madoff, Lawrence C., additional, Smole, Sandra, additional, Pierce, Virginia M., additional, Rosenberg, Eric, additional, Sabeti, Pardis C., additional, Park, Daniel J., additional, and MacInnis, Bronwyn L., additional
Published: 2021
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35. Exome sequencing in bipolar disorder identifies AKAP11as a risk gene shared with schizophrenia

Author: Palmer, Duncan S., Howrigan, Daniel P., Chapman, Sinéad B., Adolfsson, Rolf, Bass, Nick, Blackwood, Douglas, Boks, Marco P. M., Chen, Chia-Yen, Churchhouse, Claire, Corvin, Aiden P., Craddock, Nicholas, Curtis, David, Di Florio, Arianna, Dickerson, Faith, Freimer, Nelson B., Goes, Fernando S., Jia, Xiaoming, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S., Landén, Mikael, Locke, Adam E., McIntosh, Andrew M., McQuillin, Andrew, Morris, Derek W., O’Donovan, Michael C., Ophoff, Roel A., Owen, Michael J., Pedersen, Nancy L., Posthuma, Danielle, Reif, Andreas, Risch, Neil, Schaefer, Catherine, Scott, Laura, Singh, Tarjinder, Smoller, Jordan W., Solomonson, Matthew, Clair, David St., Stahl, Eli A., Vreeker, Annabel, Walters, James T. R., Wang, Weiqing, Watts, Nicholas A., Yolken, Robert, Zandi, Peter P., and Neale, Benjamin M.
Abstract: We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11emerges as a definitive risk gene (odds ratio (OR) = 7.06, P= 2.83 × 10−9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD’s polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.
Published: 2022
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36. Phylogenomic Classification and the Evolution of Clonal Complex 5 Methicillin-Resistant Staphylococcus aureus in the Western Hemisphere

Author: Challagundla, Lavanya, primary, Reyes, Jinnethe, additional, Rafiqullah, Iftekhar, additional, Sordelli, Daniel O., additional, Echaniz-Aviles, Gabriela, additional, Velazquez-Meza, Maria E., additional, Castillo-Ramírez, Santiago, additional, Fittipaldi, Nahuel, additional, Feldgarden, Michael, additional, Chapman, Sinéad B., additional, Calderwood, Michael S., additional, Carvajal, Lina P., additional, Rincon, Sandra, additional, Hanson, Blake, additional, Planet, Paul J., additional, Arias, Cesar A., additional, Diaz, Lorena, additional, and Robinson, D. Ashley, additional
Published: 2018
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37. Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance

Author: Manson, Abigail L. (author), Cohen, Keira A (author), Abeel, T.E.P.M.F. (author), Desjardins, Christopher A. (author), Armstrong, Derek T. (author), Barry III, Clifton E. (author), Brand, Jeannette (author), Chapman, Sinéad B. (author), Cho, Sang-Nae (author), Gabrielian, Andrei (author), Salazar, A.N. (author), Manson, Abigail L. (author), Cohen, Keira A (author), Abeel, T.E.P.M.F. (author), Desjardins, Christopher A. (author), Armstrong, Derek T. (author), Barry III, Clifton E. (author), Brand, Jeannette (author), Chapman, Sinéad B. (author), Cho, Sang-Nae (author), Gabrielian, Andrei (author), and Salazar, A.N. (author)
Abstract: Multidrug-resistant tuberculosis (MDR-TB), caused by drug-resistant strains of Mycobacterium tuberculosis, is an increasingly serious problem worldwide. Here we examined a data set of whole-genome sequences from 5,310 M. tuberculosis isolates from five continents. Despite the great diversity of these isolates with respect to geographical point of isolation, genetic background and drug resistance, the patterns for the emergence of drug resistance were conserved globally. We have identified harbinger mutations that often precede multidrug resistance. In particular, the katG mutation encoding p.Ser315Thr, which confers resistance to isoniazid, overwhelmingly arose before mutations that conferred rifampicin resistance across all of the lineages, geographical regions and time periods. Therefore, molecular diagnostics that include markers for rifampicin resistance alone will be insufficient to identify pre-MDR strains. Incorporating knowledge of polymorphisms that occur before the emergence of multidrug resistance, particularly katG p.Ser315Thr, into molecular diagnostics should enable targeted treatment of patients with pre-MDR-TB to prevent further development of MDR-TB., Accepted author manuscript, Pattern Recognition and Bioinformatics
Published: 2017
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38. Draft Genome Sequences of Two Extensively Drug-Resistant Strains of Mycobacterium tuberculosis Belonging to the Euro-American S Lineage

Author: Malinga, Lesibana A., primary, Abeel, Thomas, additional, Desjardins, Christopher A., additional, Dlamini, Talent C., additional, Cassell, Gail, additional, Chapman, Sinéad B., additional, Birren, Bruce W., additional, Earl, Ashlee M., additional, and van der Walt, Martie, additional
Published: 2016
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39. Evolution of Extensively Drug-Resistant Tuberculosis over Four Decades: Whole Genome Sequencing and Dating Analysis of Mycobacterium tuberculosis Isolates from KwaZulu-Natal

Author: Cohen, Keira A., primary, Abeel, Thomas, additional, Manson McGuire, Abigail, additional, Desjardins, Christopher A., additional, Munsamy, Vanisha, additional, Shea, Terrance P., additional, Walker, Bruce J., additional, Bantubani, Nonkqubela, additional, Almeida, Deepak V., additional, Alvarado, Lucia, additional, Chapman, Sinéad B., additional, Mvelase, Nomonde R., additional, Duffy, Eamon Y., additional, Fitzgerald, Michael G., additional, Govender, Pamla, additional, Gujja, Sharvari, additional, Hamilton, Susanna, additional, Howarth, Clinton, additional, Larimer, Jeffrey D., additional, Maharaj, Kashmeel, additional, Pearson, Matthew D., additional, Priest, Margaret E., additional, Zeng, Qiandong, additional, Padayatchi, Nesri, additional, Grosset, Jacques, additional, Young, Sarah K., additional, Wortman, Jennifer, additional, Mlisana, Koleka P., additional, O'Donnell, Max R., additional, Birren, Bruce W., additional, Bishai, William R., additional, Pym, Alexander S., additional, and Earl, Ashlee M., additional
Published: 2015
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40. Genomic analysis of globally diverse Mycobacterium tuberculosis strains provides insights into the emergence and spread of multidrug resistance

Author: Manson, Abigail L, Cohen, Keira A, Abeel, Thomas, Desjardins, Christopher A, Armstrong, Derek T, Barry, Clifton E, Brand, Jeannette, Chapman, Sinéad B, Cho, Sang-Nae, Gabrielian, Andrei, Gomez, James, Jodals, Andreea M, Joloba, Moses, Jureen, Pontus, Lee, Jong Seok, Malinga, Lesibana, Maiga, Mamoudou, Nordenberg, Dale, Noroc, Ecaterina, Romancenco, Elena, Salazar, Alex, Ssengooba, Willy, Velayati, A A, Winglee, Kathryn, Zalutskaya, Aksana, Via, Laura E, Cassell, Gail H, Dorman, Susan E, Ellner, Jerrold, Farnia, Parissa, Galagan, James E, Rosenthal, Alex, Crudu, Valeriu, Homorodean, Daniela, Hsueh, Po-Ren, Narayanan, Sujatha, Pym, Alexander S, Skrahina, Alena, Swaminathan, Soumya, Van der Walt, Martie, Alland, David, Bishai, William R, Cohen, Ted, Hoffner, Sven, Birren, Bruce W, and Earl, Ashlee M
Abstract: Multidrug-resistant tuberculosis (MDR-TB), caused by drug-resistant strains of Mycobacterium tuberculosis, is an increasingly serious problem worldwide. Here we examined a data set of whole-genome sequences from 5,310 M. tuberculosis isolates from five continents. Despite the great diversity of these isolates with respect to geographical point of isolation, genetic background and drug resistance, the patterns for the emergence of drug resistance were conserved globally. We have identified harbinger mutations that often precede multidrug resistance. In particular, the katG mutation encoding p.Ser315Thr, which confers resistance to isoniazid, overwhelmingly arose before mutations that conferred rifampicin resistance across all of the lineages, geographical regions and time periods. Therefore, molecular diagnostics that include markers for rifampicin resistance alone will be insufficient to identify pre-MDR strains. Incorporating knowledge of polymorphisms that occur before the emergence of multidrug resistance, particularly katG p.Ser315Thr, into molecular diagnostics should enable targeted treatment of patients with pre-MDR-TB to prevent further development of MDR-TB.
Published: 2017
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41. Phenotype harmonization and analysis for The Populations Underrepresented in Mental illness Association Studies (the PUMAS Project).

Author: Ramirez-Diaz AM, Diaz-Zuluaga AM, Stroud RE 2nd, Vreeker A, Bitta M, Ivankovic F, Wootton O, Whiteman CA, Mountcastle H, Jha SC, Georgakopoulos P, Kaur I, Mena L, Asaaf S, de Souza Rodrigues AL, Ziebold C, Newton CRJC, Stein DJ, Akena D, Valencia-Echeverry J, Kyebuzibwa J, Palacio-Ortiz JD, McMahon J, Ongeri L, Chibnik LB, Quarantini LC, Atwoli L, Santoro ML, Baker M, Diniz MJA, Castaño-Ramirez M, Alemayehu M, Holanda N, Ayola-Serrano NC, Lorencetti PG, Mwema RM, James R, Albuquerque S, Sharma S, Chapman SB, Belangero SI, Teferra S, Gichuru S, Service SK, Kariuki SM, Freitas TH, Zingela Z, Gadelha A, Bearden CE, Ophoff RA, Neale BM, Martin AR, Koenen KC, Pato CN, Lopez-Jaramillo C, Reus V, Freimer N, Pato MT, Gelaye B, and Loohuis LO
Abstract: Background: The Populations Underrepresented in Mental illness Association Studies (PUMAS) project is attempting to remediate the historical underrepresentation of African and Latin American populations in psychiatric genetics through large-scale genetic association studies of individuals diagnosed with a serious mental illness [SMI, including schizophrenia (SCZ), schizoaffective disorder (SZA) bipolar disorder (BP), and severe major depressive disorder (MDD)] and matched controls. Given growing evidence indicating substantial symptomatic and genetic overlap between these diagnoses, we sought to enable transdiagnostic genetic analyses of PUMAS data by conducting phenotype alignment and harmonization for 89,320 participants (48,165 cases and 41,155 controls) from four cohorts, each of which used different ascertainment and assessment methods: PAISA n=9,105; PUMAS-LATAM n=14,638; NGAP n=42,953 and GPC n=22,624. As we describe here, these efforts have yielded harmonized datasets enabling us to analyze PUMAS genetic variation data at three levels: SMI overall, diagnoses, and individual symptoms., Methods: In aligning item-level phenotypes obtained from 14 different clinical instruments, we incorporated content, branching nature, and time frame for each phenotype; standardized diagnoses; and selected 19 core SMI item-level phenotypes for analyses. The harmonization was evaluated in PUMAS cases using multiple correspondence analysis (MCA), co-occurrence analyses, and item-level endorsement., Outcomes: We mapped >6,895 item-level phenotypes in the aggregated PUMAS data, in which SCZ (44.97%) and severe BP (BP-I, 31.53%) were the most common diagnoses. Twelve of the 19 core item-level phenotypes occurred at frequencies of > 10% across all diagnoses, indicating their potential utility for transdiagnostic genetic analyses. MCA of the 14 phenotypes that were present for all cohorts revealed consistency across cohorts, and placed MDD and SCZ into separate clusters, while other diagnoses showed no significant phenotypic clustering., Interpretation: Our alignment strategy effectively aggregated extensive phenotypic data obtained using diverse assessment tools. The MCA yielded dimensional scores which we will use for genetic analyses along with the item level phenotypes. After successful harmonization, residual phenotypic heterogeneity between cohorts reflects differences in branching structure of diagnostic instruments, recruitment strategies, and symptom interpretation (due to cultural variation).
Published: 2024
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42. A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner.

Author: Boltz TA, Chu BB, Liao C, Sealock JM, Ye R, Majara L, Fu JM, Service S, Zhan L, Medland SE, Chapman SB, Rubinacci S, DeFelice M, Grimsby JL, Abebe T, Alemayehu M, Ashaba FK, Atkinson EG, Bigdeli T, Bradway AB, Brand H, Chibnik LB, Fekadu A, Gatzen M, Gelaye B, Gichuru S, Gildea ML, Hill TC, Huang H, Hubbard KM, Injera WE, James R, Joloba M, Kachulis C, Kalmbach PR, Kamulegeya R, Kigen G, Kim S, Koen N, Kwobah EK, Kyebuzibwa J, Lee S, Lennon NJ, Lind PA, Lopera-Maya EA, Makale J, Mangul S, McMahon J, Mowlem P, Musinguzi H, Mwema RM, Nakasujja N, Newman CP, Nkambule LL, O'Neil CR, Olivares AM, Olsen CM, Ongeri L, Parsa SJ, Pretorius A, Ramesar R, Reagan FL, Sabatti C, Schneider JA, Shiferaw W, Stevenson A, Stricker E, Stroud RE 2nd, Tang J, Whiteman D, Yohannes MT, Yu M, Yuan K, Akena D, Atwoli L, Kariuki SM, Koenen KC, Newton CRJC, Stein DJ, Teferra S, Zingela Z, Pato CN, Pato MT, Lopez-Jaramillo C, Freimer N, Ophoff RA, Olde Loohuis LM, Talkowski ME, Neale BM, Howrigan DP, and Martin AR
Abstract: We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R 2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R 2 for SNPs with MAF<1%. Furthermore, concordance rates among local ancestries within two recently admixed cohorts were consistent among SNPs with MAF≥1%, with only minor deviations in SNPs with MAF<1%. We also benchmarked the discovery capacity of BGE to access protein-coding copy number variants (CNVs) against deep whole genome data, finding that deletions and duplications spanning at least 3 exons had a positive predicted value of ~90%. Our results demonstrate BGE scalability and efficacy in capturing SNPs, indels, and CNVs in the human genome at 28% of the cost of deep whole-genome sequencing. BGE is poised to enhance access to genomic testing and empower genomic discoveries, particularly in underrepresented populations.
Published: 2024
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43. Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays.

Author: DeFelice M, Grimsby JL, Howrigan D, Yuan K, Chapman SB, Stevens C, DeLuca S, Townsend M, Buxbaum J, Pericak-Vance M, Qin S, Stein DJ, Teferra S, Xavier RJ, Huang H, Martin AR, and Neale BM
Abstract: Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r 2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.
Published: 2024
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