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146 results on '"Mortensen, Preben B"'

1. Potential causal association between gut microbiome and posttraumatic stress disorder

Author: Cardiologie, Onderzoeksgroep 2, Brain, MGGZ, Hersenen-Medisch 1, Neurogenetica, Diagnostiek & Vroege Psychose Medisch, He, Qiang, Wang, Wenjing, Xu, Dingkang, Xiong, Yang, Tao, Chuanyuan, You, Chao, Ma, Lu, Ma, Junpeng, Nievergelt, Caroline M., Maihofer, Adam X., Klengel, Torsten, Atkinson, Elizabeth G., Chen, Chia Yen, Choi, Karmel W., Coleman, Jonathan R.I., Dalvie, Shareefa, Duncan, Laramie E., Logue, Mark W., Provost, Allison C., Ratanatharathorn, Andrew, Stein, Murray B., Torres, Katy, Aiello, Allison E., Almli, Lynn M., Amstadter, Ananda B., Andersen, Søren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegovic, Esmina, Babić, Dragan, Bækvad-Hansen, Marie, Baker, Dewleen G., Beckham, Jean C., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Børglum, Anders D., Bradley, Bekh, Brashear, Megan, Breen, Gerome, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Calabrese, Joseph R., Caldas-de-Almeida, José M., Dale, Anders M., Daly, Mark J., Daskalakis, Nikolaos P., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Disner, Seth G., Domschke, Katharina, Dzubur-Kulenovic, Alma, Erbes, Christopher R., Evans, Alexandra, Farrer, Lindsay A., Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles, Uka, Aferdita Goci, Gordon, Scott D., Guffanti, Guia, Hammamieh, Rasha, Harnal, Supriya, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hougaard, David Michael, Jakovljevic, Miro, Jett, Marti, Johnson, Eric Otto, Jones, Ian, Jovanovic, Tanja, Qin, Xue Jun, Junglen, Angela G., Karstoft, Karen Inge, Kaufman, Milissa L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kranzler, Henry R., Kremen, William S., Lawford, Bruce R., Lebois, Lauren A.M., Lewis, Catrin E., Linnstaedt, Sarah D., Lori, Adriana, Lugonja, Bozo, Luykx, Jurjen J., Lyons, Michael J., Maples-Keller, Jessica, Marmar, Charles, Martin, Alicia R., Martin, Nicholas G., Maurer, Douglas, Mavissakalian, Matig R., McFarlane, Alexander, McGlinchey, Regina E., McLaughlin, Katie A., McLean, Samuel A., McLeay, Sarah, Mehta, Divya, Milberg, William P., Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben B., Neale, Benjamin M., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., O’Donnell, Meaghan, Orcutt, Holly K., Panizzon, Matthew S., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Rice, John P., Ripke, Stephan, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Ken, Rung, Ariane, Rutten, Bart P.F., Saccone, Nancy L., Sanchez, Sixto E., Schijven, Dick, Seedat, Soraya, Seligowski, Antonia V., Seng, Julia S., Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Solovieff, Nadia, Sponheim, Scott R., Stein, Dan J., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., van den Heuvel, Leigh Luella, van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Wolff, Jonathan D., Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zhao, Hongyu, Zoellner, Lori A., Liberzon, Israel, Ressler, Kerry J., Haas, Magali, Koenen, Karestan C., Cardiologie, Onderzoeksgroep 2, Brain, MGGZ, Hersenen-Medisch 1, Neurogenetica, Diagnostiek & Vroege Psychose Medisch, He, Qiang, Wang, Wenjing, Xu, Dingkang, Xiong, Yang, Tao, Chuanyuan, You, Chao, Ma, Lu, Ma, Junpeng, Nievergelt, Caroline M., Maihofer, Adam X., Klengel, Torsten, Atkinson, Elizabeth G., Chen, Chia Yen, Choi, Karmel W., Coleman, Jonathan R.I., Dalvie, Shareefa, Duncan, Laramie E., Logue, Mark W., Provost, Allison C., Ratanatharathorn, Andrew, Stein, Murray B., Torres, Katy, Aiello, Allison E., Almli, Lynn M., Amstadter, Ananda B., Andersen, Søren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegovic, Esmina, Babić, Dragan, Bækvad-Hansen, Marie, Baker, Dewleen G., Beckham, Jean C., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Børglum, Anders D., Bradley, Bekh, Brashear, Megan, Breen, Gerome, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Calabrese, Joseph R., Caldas-de-Almeida, José M., Dale, Anders M., Daly, Mark J., Daskalakis, Nikolaos P., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Disner, Seth G., Domschke, Katharina, Dzubur-Kulenovic, Alma, Erbes, Christopher R., Evans, Alexandra, Farrer, Lindsay A., Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles, Uka, Aferdita Goci, Gordon, Scott D., Guffanti, Guia, Hammamieh, Rasha, Harnal, Supriya, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hougaard, David Michael, Jakovljevic, Miro, Jett, Marti, Johnson, Eric Otto, Jones, Ian, Jovanovic, Tanja, Qin, Xue Jun, Junglen, Angela G., Karstoft, Karen Inge, Kaufman, Milissa L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kranzler, Henry R., Kremen, William S., Lawford, Bruce R., Lebois, Lauren A.M., Lewis, Catrin E., Linnstaedt, Sarah D., Lori, Adriana, Lugonja, Bozo, Luykx, Jurjen J., Lyons, Michael J., Maples-Keller, Jessica, Marmar, Charles, Martin, Alicia R., Martin, Nicholas G., Maurer, Douglas, Mavissakalian, Matig R., McFarlane, Alexander, McGlinchey, Regina E., McLaughlin, Katie A., McLean, Samuel A., McLeay, Sarah, Mehta, Divya, Milberg, William P., Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben B., Neale, Benjamin M., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., O’Donnell, Meaghan, Orcutt, Holly K., Panizzon, Matthew S., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Rice, John P., Ripke, Stephan, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Ken, Rung, Ariane, Rutten, Bart P.F., Saccone, Nancy L., Sanchez, Sixto E., Schijven, Dick, Seedat, Soraya, Seligowski, Antonia V., Seng, Julia S., Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Solovieff, Nadia, Sponheim, Scott R., Stein, Dan J., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., van den Heuvel, Leigh Luella, van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Wolff, Jonathan D., Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zhao, Hongyu, Zoellner, Lori A., Liberzon, Israel, Ressler, Kerry J., Haas, Magali, and Koenen, Karestan C.
Published: 2024

2. ADuLT:An efficient and robust time-to-event GWAS

Author: Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Steinbach, Jette, Krebs, Morten D., Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Børglum, Anders D., Musliner, Katherine L., Ganna, Andrea, Schork, Andrew J., Mortensen, Preben B., McGrath, John J., Privé, Florian, Vilhjálmsson, Bjarni J., Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Steinbach, Jette, Krebs, Morten D., Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Børglum, Anders D., Musliner, Katherine L., Ganna, Andrea, Schork, Andrew J., Mortensen, Preben B., McGrath, John J., Privé, Florian, and Vilhjálmsson, Bjarni J.
Abstract: Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.
Published: 2023

3. Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks

Author: Appadurai, Vivek, Bybjerg-Grauholm, Jonas, Krebs, Morten Dybdahl, Rosengren, Anders, Buil, Alfonso, Ingason, Andrés, Mors, Ole, Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Delaneau, Olivier, Werge, Thomas, Schork, Andrew J., Appadurai, Vivek, Bybjerg-Grauholm, Jonas, Krebs, Morten Dybdahl, Rosengren, Anders, Buil, Alfonso, Ingason, Andrés, Mors, Ole, Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Delaneau, Olivier, Werge, Thomas, and Schork, Andrew J.
Abstract: Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.
Published: 2023

4. Associations of psychiatric disorders with sex chromosome aneuploidies in the Danish iPSYCH2015 dataset:a case-cohort study

Author: Sánchez, Xabier Calle, Montalbano, Simone, Vaez, Morteza, Krebs, Morten Dybdahl, Byberg-Grauholm, Jonas, Mortensen, Preben B., Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Geschwind, Daniel H., Buil, Alfonso, Schork, Andrew J., Thompson, Wesley K., Raznahan, Armin, Helenius, Dorte, Werge, Thomas, Ingason, Andrés, Sánchez, Xabier Calle, Montalbano, Simone, Vaez, Morteza, Krebs, Morten Dybdahl, Byberg-Grauholm, Jonas, Mortensen, Preben B., Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Geschwind, Daniel H., Buil, Alfonso, Schork, Andrew J., Thompson, Wesley K., Raznahan, Armin, Helenius, Dorte, Werge, Thomas, and Ingason, Andrés
Abstract: Background: Increased prevalence of mental illness has been reported in clinical studies of sex chromosome aneuploidies, but accurate population-based estimates of the prevalence and clinical detection rate of sex chromosome aneuploidies and the associated risks of psychiatric disorders are needed. In this study, we provide such estimates, valid for children and young adults of the contemporary Danish population. Methods: We used the iPSYCH2015 case-cohort dataset, which is based on a source population of single-born individuals born in Denmark between May 1, 1981, and Dec 31, 2008. The case sample comprises all individuals from the source population with a diagnosis of any index psychiatric disorder (schizophrenia spectrum disorder, bipolar disorder, major depressive disorder, autism spectrum disorder, or ADHD) by the end of follow-up (Dec 31, 2015), registered in the hospital-based Danish Psychiatric Central Research Register. The cohort consists of individuals randomly selected from the source population, and overlaps with the case sample. Biobanked blood samples for individuals in the case and cohort samples underwent genotyping and quality-control filtering, after which we analysed microarray data to detect sex chromosome aneuploidy karyotypes (45,X, 47,XXX, 47,XXY, and 47,XYY). We estimated the population-valid prevalence of these karyotypes from the cohort sample. Weighted Cox proportional hazards models were used to estimate the risks of each index psychiatric disorder associated with each sex chromosome aneuploidy karyotype, by use of date of first hospitalisation with the index disorder in the respective case group and the cohort as outcome. The clinical detection rate was determined by comparing records of clinical diagnoses of genetic conditions from the Danish National Patient Register with sex chromosome aneuploidy karyotype determined by our study. Findings: The assessed sample comprised 119 481 individuals (78 726 in the case sample and 43 326 in
Published: 2023

5. School performance and genetic propensities for educational attainment and depression in the etiology of self-harm:a Danish population-based study

Author: Sørensen, Holger J, Antonsen, Sussie, Benros, Michael E, Erlangsen, Annette, Albiñana, Clara, Nordentoft, Merete, Børglum, Anders D, Mors, Ole, Werge, Thomas, Mortensen, Preben B, Hougaard, David, Webb, Roger T, Agerbo, Esben, Sørensen, Holger J, Antonsen, Sussie, Benros, Michael E, Erlangsen, Annette, Albiñana, Clara, Nordentoft, Merete, Børglum, Anders D, Mors, Ole, Werge, Thomas, Mortensen, Preben B, Hougaard, David, Webb, Roger T, and Agerbo, Esben
Abstract: BACKGROUND: Poor school performance is linked to higher risks of self-harm. The association might be explained through genetic liabilities for depression or educational attainment. We investigated the association between school performance and self-harm in a population-based sample while assessing the potential influence of polygenic risk scores (PRSs) for depression (PRSMDD) and for educational attainment (PRSEDU).METHOD: We conducted a follow-up study of individuals born 1987-98 and followed from age 18 until 2016. The total sample consisted of a case group (23,779 diagnosed with mental disorders; schizophrenia, bipolar disorder, depression, autism, and attention deficit hyperactivity disorder (ADHD) and a randomly sampled comparison group (n = 10,925). Genome-wide data were obtained from the Neonatal Screening Biobank and information on school performance, family psychiatric history, and socioeconomic status from national administrative registers.RESULTS: Individuals in the top PRSMDD decile were at higher self-harm risk in the case group (IRR: 1.30; 95% CI 1.15-1.46), whereas individuals in the top PRSEDU decile were at lower self-harm risk (IRR: 0.63; 95% CI: 0.55-0.74). Poorer school performance was associated with higher self-harm risk in persons diagnosed with any mental disorder (IRR: 1.69; 95% CI: 1.44-1.99) and among the comparison group (IRR: 7.93; 95% CI: 4.47-15.18). Observed effects of PRSMDD and PRSEDU on self-harm risk were strongest for individuals with poor school performance.CONCLUSION: Associations between PRSMDD and self-harm risk and between PRSEDU and self-harm risk were found. Nevertheless, these polygenic scores seem currently of limited clinical utility for identifying individuals at high self-harm risk.
Published: 2023

6. Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks

Author: Appadurai, Vivek, Bybjerg-Grauholm, Jonas, Krebs, Morten Dybdahl, Rosengren, Anders, Buil, Alfonso, Ingason, Andrés, Mors, Ole, Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Delaneau, Olivier, Werge, Thomas, Schork, Andrew J., Appadurai, Vivek, Bybjerg-Grauholm, Jonas, Krebs, Morten Dybdahl, Rosengren, Anders, Buil, Alfonso, Ingason, Andrés, Mors, Ole, Børglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Delaneau, Olivier, Werge, Thomas, and Schork, Andrew J.
Abstract: Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.
Published: 2023

7. Genome-wide by Environment Interaction Study of Stressful Life Events and Hospital-Treated Depression in the iPSYCH2012 Sample

Author: Suppli, Nis P., Andersen, Klaus K., Agerbo, Esben, Rajagopal, Veera M., Appadurai, Vivek, Coleman, Jonathan R.i., Breen, Gerome, Bybjerg-grauholm, Jonas, Bækvad-hansen, Marie, Pedersen, Carsten B., Pedersen, Marianne G., Thompson, Wesley K., Munk-Olsen, Trine, Benros, Michael E., Als, Thomas D., Grove, Jakob, Werge, Thomas, Børglum, Anders D., Hougaard, David M., Mors, Ole, Nordentoft, Merete, Mortensen, Preben B., Musliner, Katherine L., Suppli, Nis P., Andersen, Klaus K., Agerbo, Esben, Rajagopal, Veera M., Appadurai, Vivek, Coleman, Jonathan R.i., Breen, Gerome, Bybjerg-grauholm, Jonas, Bækvad-hansen, Marie, Pedersen, Carsten B., Pedersen, Marianne G., Thompson, Wesley K., Munk-Olsen, Trine, Benros, Michael E., Als, Thomas D., Grove, Jakob, Werge, Thomas, Børglum, Anders D., Hougaard, David M., Mors, Ole, Nordentoft, Merete, Mortensen, Preben B., and Musliner, Katherine L.
Abstract: Background Researchers have long investigated a hypothesized interaction between genetic risk and stressful life events in the etiology of depression, but studies on the topic have yielded inconsistent results. Methods We conducted a genome-wide by environment interaction study (GWEIS) in 18,532 patients with depression from hospital-based settings and 20,184 population controls. All individuals were drawn from the iPSYCH2012 case-cohort study, a nationally representative sample identified from Danish national registers. Information on stressful life events including family disruption, serious medical illness, death of a first-degree relative, parental disability, and child maltreatment was identified from the registers and operationalized as a time-varying count variable. Hazard ratios for main and interaction effects were estimated using Cox regressions weighted to accommodate the case-cohort design. Our replication sample included 22,880 depression cases and 50,378 controls from the UK Biobank. Results The GWEIS in the iPSYCH2012 sample yielded three novel, genome-wide–significant (p < 5 × 10−8) loci located in the ABCC1 gene (rs56076205, p = 3.7 × 10−10), the AKAP6 gene (rs3784187, p = 1.2 × 10−8), and near the MFSD1 gene (rs340315, p = 4.5 × 10−8). No hits replicated in the UK Biobank (rs56076205: p = .87; rs3784187: p = .93; rs340315: p = .71). Conclusions In this large, population-based GWEIS, we did not find any replicable hits for interaction. Future gene-by-stress research in depression should focus on establishing even larger collaborative GWEISs to attain sufficient power.
Published: 2023

8. Risk of Depression in People With Human Immunodeficiency Virus:A Nationwide Population-based Matched Cohort Study

Author: Vollmond, Cecilie V., Tetens, Malte M., Paulsen, Fie W., Gerstoft, Jan, Kronborg, Gitte, Johansen, Isik S., Larsen, Carsten S., Wiese, Lothar, Dalager-Pedersen, Michael, Leth, Steffen, Mortensen, Preben B., Lebech, Anne Mette, Obel, Niels, Omland, Lars H., Vollmond, Cecilie V., Tetens, Malte M., Paulsen, Fie W., Gerstoft, Jan, Kronborg, Gitte, Johansen, Isik S., Larsen, Carsten S., Wiese, Lothar, Dalager-Pedersen, Michael, Leth, Steffen, Mortensen, Preben B., Lebech, Anne Mette, Obel, Niels, and Omland, Lars H.
Abstract: Background Human immunodeficiency virus (HIV) infection is associated with depression. However, previous studies have not addressed familial factors. Methods Nationwide, population-based, matched cohort study of people with HIV (PWH) in Denmark between 1995 and 2021 who were matched on sex and date of birth with a comparison cohort randomly selected from the Danish population. Family-related factors were examined by inclusion of siblings of those in the cohorts. We calculated hazard ratios (HRs) for depression, receipt of antidepressants, electroconvulsive therapy (ECT), and suicide, as well as the yearly proportions of study cohorts with psychiatric hospital contact due to depression and receipt of antidepressants from 10 years before to 10 years after study inclusion. Results We included 5943 PWH and 59 430 comparison cohort members. Median age was 38 years, and 25% were women. We observed an increased risk of depression, receipt of antidepressants, ECT, and suicide among PWH in the 2 first years of observation (HR, 3.3; 95% confidence interval [CI]: 2.5–4.4), HR, 3.0 (95% CI: 2.7–3.4), HR, 2.8 (95% CI: .9–8.6), and HR, 10.7 (95% CI: 5.2–22.2), thereafter the risk subsided but remained increased. The proportions of PWH with psychiatric hospital contact due to depression and receipt of antidepressants were increased prior to and especially after HIV diagnosis. Risk of all outcomes was substantially lower among siblings of PWH than among PWH (HR for receipt of antidepressants, 1.1; 95% CI: 1.0–1.2). Conclusions PWH have an increased risk of depression. Family-related factors are unlikely to explain this risk., Background: Human immunodeficiency virus (HIV) infection is associated with depression. However, previous studies have not addressed familial factors. Methods: Nationwide, population-based, matched cohort study of people with HIV (PWH) in Denmark between 1995 and 2021 who were matched on sex and date of birth with a comparison cohort randomly selected from the Danish population. Family-related factors were examined by inclusion of siblings of those in the cohorts. We calculated hazard ratios (HRs) for depression, receipt of antidepressants, electroconvulsive therapy (ECT), and suicide, as well as the yearly proportions of study cohorts with psychiatric hospital contact due to depression and receipt of antidepressants from 10 years before to 10 years after study inclusion. Results: We included 5943 PWH and 59 430 comparison cohort members. Median age was 38 years, and 25% were women. We observed an increased risk of depression, receipt of antidepressants, ECT, and suicide among PWH in the 2 first years of observation (HR, 3.3; 95% confidence interval [CI]: 2.5-4.4), HR, 3.0 (95% CI: 2.7-3.4), HR, 2.8 (95% CI:. 9-8.6), and HR, 10.7 (95% CI: 5.2-22.2), thereafter the risk subsided but remained increased. The proportions of PWH with psychiatric hospital contact due to depression and receipt of antidepressants were increased prior to and especially after HIV diagnosis. Risk of all outcomes was substantially lower among siblings of PWH than among PWH (HR for receipt of antidepressants, 1.1; 95% CI: 1.0-1.2). Conclusions: PWH have an increased risk of depression. Family-related factors are unlikely to explain this risk.
Published: 2023

9. ADuLT:An efficient and robust time-to-event GWAS

Author: Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Steinbach, Jette, Krebs, Morten D., Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Børglum, Anders D., Musliner, Katherine L., Ganna, Andrea, Schork, Andrew J., Mortensen, Preben B., McGrath, John J., Privé, Florian, Vilhjálmsson, Bjarni J., Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Steinbach, Jette, Krebs, Morten D., Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Børglum, Anders D., Musliner, Katherine L., Ganna, Andrea, Schork, Andrew J., Mortensen, Preben B., McGrath, John J., Privé, Florian, and Vilhjálmsson, Bjarni J.
Abstract: Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.
Published: 2023

10. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses

Author: Als, Thomas D., Kurki, Mitja I., Grove, Jakob, Voloudakis, Georgios, Therrien, Karen, Tasanko, Elisa, Nielsen, Trine Tollerup, Naamanka, Joonas, Veerapen, Kumar, Levey, Daniel F., Bendl, Jaroslav, Bybjerg-Grauholm, Jonas, Zeng, Biao, Demontis, Ditte, Rosengren, Anders, Athanasiadis, Georgios, Bækved-Hansen, Marie, Qvist, Per, Bragi Walters, G., Thorgeirsson, Thorgeir, Stefánsson, Hreinn, Musliner, Katherine L., Rajagopal, Veera M., Farajzadeh, Leila, Thirstrup, Janne, Vilhjálmsson, Bjarni J., McGrath, John J., Mattheisen, Manuel, Meier, Sandra, Agerbo, Esben, Stefánsson, Kári, Nordentoft, Merete, Werge, Thomas, Hougaard, David M., Mortensen, Preben B., Stein, Murray B., Gelernter, Joel, Hovatta, Iiris, Roussos, Panos, Daly, Mark J., Mors, Ole, Palotie, Aarno, Børglum, Anders D., Als, Thomas D., Kurki, Mitja I., Grove, Jakob, Voloudakis, Georgios, Therrien, Karen, Tasanko, Elisa, Nielsen, Trine Tollerup, Naamanka, Joonas, Veerapen, Kumar, Levey, Daniel F., Bendl, Jaroslav, Bybjerg-Grauholm, Jonas, Zeng, Biao, Demontis, Ditte, Rosengren, Anders, Athanasiadis, Georgios, Bækved-Hansen, Marie, Qvist, Per, Bragi Walters, G., Thorgeirsson, Thorgeir, Stefánsson, Hreinn, Musliner, Katherine L., Rajagopal, Veera M., Farajzadeh, Leila, Thirstrup, Janne, Vilhjálmsson, Bjarni J., McGrath, John J., Mattheisen, Manuel, Meier, Sandra, Agerbo, Esben, Stefánsson, Kári, Nordentoft, Merete, Werge, Thomas, Hougaard, David M., Mortensen, Preben B., Stein, Murray B., Gelernter, Joel, Hovatta, Iiris, Roussos, Panos, Daly, Mark J., Mors, Ole, Palotie, Aarno, and Børglum, Anders D.
Abstract: Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment., Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment.
Published: 2023

11. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walters, James T. R., Ripke, Stephan, Neale, Benjamin M., Farh, Kai-How, Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A., Huang, Hailiang, Pers, Tune H., Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A., Begemann, Martin, Homman, Lina, Belliveau, Richard A ., Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walters, James T. R., Ripke, Stephan, Neale, Benjamin M., Farh, Kai-How, Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A., Huang, Hailiang, Pers, Tune H., Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A., Begemann, Martin, Homman, Lina, and Belliveau, Richard A .
Abstract: Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, setting, and participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main outcomes and measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380, Funding/Support: This work was supported by Medical Research Council Centre grant MR/L010305/1, Medical Research Council Program grant MR/P005748/1, and Medical Research Council Project grants MR/L011794/1 and MC_PC_17212 to Cardiff University and by the National Centre for Mental Health, funded by the Welsh Government through Health and Care Research Wales. This work acknowledges the support of the Supercomputing Wales project, which is partially funded by the European Regional Development Fund via the Welsh Government. Dr Pardiñas was supported by an Academy of Medical Sciences Springboard Award (SBF005\1083). Dr Andreassen was supported by the Research Council of Norway (grants 283798, 262656, 248980, 273291, 248828, 248778, and 223273); KG Jebsen Stiftelsen, South-East Norway Health Authority, and the European Union’s Horizon 2020 Research and Innovation Programme (grant 847776). Dr Ajnakina was supported by an National Institute for Health Research postdoctoral fellowship (PDF-2018-11-ST2-020). Dr Joyce was supported by the University College London Hospitals/UCL University College London Biomedical Research Centre. Dr Kowalec received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (793530) from the government of Canada Banting postdoctoral fellowship programme and the University of Manitoba. Dr Sullivan was supported by the Swedish Research Council (Vetenskapsrådet, D0886501), the European Union’s Horizon 2020 programme (COSYN, 610307) and the US National Institute of Mental Health (U01 MH109528 and R01 MH077139). The Psychiatric Genomics Consortium was partly supported by the National Institute Of Mental Health (grants R01MH124873). The Sweden Schizophrenia Study was supported by the National Institute Of Mental Health (grant R01MH077139). The STRATA consortium was supported by a Stratified Medicine Programme grant to Dr MacCabe from the Medical Research Council (grant MR/L0, STRATA
Published: 2022
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12. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Author: Maihofer, Adam X., Choi, Karmel W., Coleman, Jonathan R.I., Daskalakis, Nikolaos P., Denckla, Christy A., Ketema, Elizabeth, Morey, Rajendra A., Polimanti, Renato, Ratanatharathorn, Andrew, Torres, Katy, Wingo, Aliza P., Zai, Clement C., Aiello, Allison E., Almli, Lynn M., Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegović, Esmina, Borglum, Anders D., Babić, Dragan, Bækvad-Hansen, Marie, Baker, Dewleen G., Beckham, Jean C., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Bradley, Bekh, Brashear, Meghan, Breen, Gerome, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Calabrese, Joseph R., Caldas-de-Almeida, José M., Chen, Chia Yen, Dale, Anders M., Dalvie, Shareefa, Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Disner, Seth G., Domschke, Katharina, Duncan, Laramie E., Džubur Kulenović, Alma, Erbes, Christopher R., Evans, Alexandra, Farrer, Lindsay A., Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gautam, Aarti, Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goçi, Aferdita, Gordon, Scott D., Guffanti, Guia, Hammamieh, Rasha, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hougaard, David Michael, Jakovljević, Miro, Jett, Marti, Johnson, Eric Otto, Jones, Ian, Jovanovic, Tanja, Qin, Xue Jun, Karstoft, Karen Inge, Kaufman, Milissa L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kranzler, Henry R., Kremen, William S., Lawford, Bruce R., Lebois, Lauren A.M., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lugonja, Božo, Luykx, Jurjen J., Lyons, Michael J., Maples-Keller, Jessica L., Marmar, Charles, Martin, Nicholas G., Maurer, Douglas, Mavissakalian, Matig R., McFarlane, Alexander, McGlinchey, Regina E., McLaughlin, Katie A., McLean, Samuel A., Mehta, Divya, Mellor, Rebecca, Michopoulos, Vasiliki, Milberg, William, Miller, Mark W., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben B., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., O'Donnell, Meaghan, Orcutt, Holly K., Panizzon, Matthew S., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Rice, John P., Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Rutten, Bart P.F., Saccone, Nancy L., Sanchez, Sixto E., Schijven, Dick, Seedat, Soraya, Seligowski, Antonia V., Seng, Julia S., Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stevens, Jennifer S., Teicher, Martin H., Thompson, Wesley K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., van den Heuvel, Leigh Luella, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan, Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zhao, Hongyu, Zoellner, Lori A., Haas, Magali, Lasseter, Heather, Provost, Allison C., Salem, Rany M., Sebat, Jonathan, Shaffer, Richard A., Wu, Tianying, Ripke, Stephan, Daly, Mark J., Ressler, Kerry J., Koenen, Karestan C., Stein, Murray B., Nievergelt, Caroline M., Maihofer, Adam X., Choi, Karmel W., Coleman, Jonathan R.I., Daskalakis, Nikolaos P., Denckla, Christy A., Ketema, Elizabeth, Morey, Rajendra A., Polimanti, Renato, Ratanatharathorn, Andrew, Torres, Katy, Wingo, Aliza P., Zai, Clement C., Aiello, Allison E., Almli, Lynn M., Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegović, Esmina, Borglum, Anders D., Babić, Dragan, Bækvad-Hansen, Marie, Baker, Dewleen G., Beckham, Jean C., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Bradley, Bekh, Brashear, Meghan, Breen, Gerome, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Calabrese, Joseph R., Caldas-de-Almeida, José M., Chen, Chia Yen, Dale, Anders M., Dalvie, Shareefa, Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Disner, Seth G., Domschke, Katharina, Duncan, Laramie E., Džubur Kulenović, Alma, Erbes, Christopher R., Evans, Alexandra, Farrer, Lindsay A., Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gautam, Aarti, Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goçi, Aferdita, Gordon, Scott D., Guffanti, Guia, Hammamieh, Rasha, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M.J., Hougaard, David Michael, Jakovljević, Miro, Jett, Marti, Johnson, Eric Otto, Jones, Ian, Jovanovic, Tanja, Qin, Xue Jun, Karstoft, Karen Inge, Kaufman, Milissa L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kranzler, Henry R., Kremen, William S., Lawford, Bruce R., Lebois, Lauren A.M., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lugonja, Božo, Luykx, Jurjen J., Lyons, Michael J., Maples-Keller, Jessica L., Marmar, Charles, Martin, Nicholas G., Maurer, Douglas, Mavissakalian, Matig R., McFarlane, Alexander, McGlinchey, Regina E., McLaughlin, Katie A., McLean, Samuel A., Mehta, Divya, Mellor, Rebecca, Michopoulos, Vasiliki, Milberg, William, Miller, Mark W., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben B., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., O'Donnell, Meaghan, Orcutt, Holly K., Panizzon, Matthew S., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Rice, John P., Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Rutten, Bart P.F., Saccone, Nancy L., Sanchez, Sixto E., Schijven, Dick, Seedat, Soraya, Seligowski, Antonia V., Seng, Julia S., Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stevens, Jennifer S., Teicher, Martin H., Thompson, Wesley K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., van den Heuvel, Leigh Luella, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan, Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Yehuda, Rachel, Young, Keith A., Young, Ross Mc D., Zhao, Hongyu, Zoellner, Lori A., Haas, Magali, Lasseter, Heather, Provost, Allison C., Salem, Rany M., Sebat, Jonathan, Shaffer, Richard A., Wu, Tianying, Ripke, Stephan, Daly, Mark J., Ressler, Kerry J., Koenen, Karestan C., Stein, Murray B., and Nievergelt, Caroline M.
Abstract: Background: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.
Published: 2022

13. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., Homman, Lina, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., and Homman, Lina
Abstract: Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380
Published: 2022
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14. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., Homman, Lina, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., and Homman, Lina
Abstract: Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380
Published: 2022
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15. Maternal pregnancy-related infections and autism spectrum disorder-the genetic perspective.

Author: Nudel, Ron, Nudel, Ron, Thompson, Wesley K, Børglum, Anders D, Hougaard, David M, Mortensen, Preben B, Werge, Thomas, Nordentoft, Merete, Benros, Michael E, Nudel, Ron, Nudel, Ron, Thompson, Wesley K, Børglum, Anders D, Hougaard, David M, Mortensen, Preben B, Werge, Thomas, Nordentoft, Merete, and Benros, Michael E
Abstract: Autism spectrum disorder (ASD) refers to a group of neurodevelopmental disorders which include deficits in behavior, social interaction and communication. ASD has a complex genetic architecture, and it is also influenced by certain environmental exposures. Both types of predisposing factors may be related to immunological mechanisms, involving, for example, immune system genes and infections. Past studies have shown an association between infections occurring during the pregnancy in the mother and increased risk of ASD in the child, an observation which has received recent support from experimental animal studies of ASD-like behavior. The aim of this study was to study the genetic contribution to this effect. We employed genetic correlation analyses across potential ASD subtypes stratified on the basis of maternal pregnancy-related infections within the iPSYCH ASD case-cohort sample, as well as a case-case GWAS. We validated the trends of the genetic correlation analyses observed in our sample using GWAS summary statistics from the PGC ASD study (excluding iPSYCH). The genetic correlation between ASD with a history of maternal pregnancy-related infections and ASD without a history of maternal infections in iPSYCH was rg = 0.3811. We obtained a similar estimate between the former and the PGC ASD phenotype (rg = 0.3997). Both estimates are lower compared to the genetic correlation between ASD without a history of maternal infections and the PGC ASD phenotype (rg = 0.6735), and between ASD with a history of maternal infections occurring only more than 2 months following childbirth and the PGC ASD phenotype (rg = 0.6293). Additionally, we observed genetic variance between the two main ASD phenotypes using summary statistics from the case-case GWAS in iPSYCH (h2cc = 0.1059), indicating genome-wide differences between the phenotypes. Our results suggest potentially different etiologies of ASD based on a history of maternal pregnancy-related infections, which may, in part
Published: 2022

16. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author: Blokland, Gabriëlla A. M., Grove, Jakob, Chen, Chia-Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, St Clair, David, Lencz, Todd, Mowry, Bryan J., Periyasamy, Sathish, Cairns, Murray J., Tooney, Paul A., Wu, Jing Qin, Kelly, Brian, Kirov, George, Sullivan, Patrick F., Corvin, Aiden, Riley, Brien P., Esko, Tõnu, Milani, Lili, Jönsson, Erik G., Palotie, Aarno, Ehrenreich, Hannelore, Begemann, Martin, Steixner-Kumar, Agnes, Sham, Pak C., Iwata, Nakao, Weinberger, Daniel R., Gejman, Pablo V., Sanders, Alan R., Buxbaum, Joseph D., Rujescu, Dan, Giegling, Ina, Konte, Bettina, Hartmann, Anette M., Bramon, Elvira, Murray, Robin M., Pato, Michele T., Lee, Jimmy, Melle, Ingrid, Molden, Espen, Ophoff, Roel A., McQuillin, Andrew, Bass, Nicholas J., Adolfsson, Rolf, Malhotra, Anil K., Martin, Nicholas G., Fullerton, Janice M., Mitchell, Philip B., Schofield, Peter R., Forstner, Andreas J., Degenhardt, Franziska, Schaupp, Sabrina, Comes, Ashley L., Kogevinas, Manolis, Guzman-Parra, José, Reif, Andreas, Streit, Fabian, Sirignano, Lea, Cichon, Sven, Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Lissowska, Jolanta, Mayoral, Fermin, Müller-Myhsok, Bertram, Świątkowska, Beata, Schulze, Thomas G., Nöthen, Markus M., Rietschel, Marcella, Kelsoe, John, Leboyer, Marion, Jamain, Stéphane, Etain, Bruno, Bellivier, Frank, Vincent, John B., Alda, Martin, O'Donovan, Claire, Cervantes, Pablo, Biernacka, Joanna M., Frye, Mark, McElroy, Susan L., Scott, Laura J., Stahl, Eli A., Landén, Mikael, Hamshere, Marian L., Smeland, Olav B., Djurovic, Srdjan, Vaaler, Arne E., Andreassen, Ole A., Baune, Bernhard T., Air, Tracy, Preisig, Martin, Uher, Rudolf, Levinson, Douglas F., Weissman, Myrna M., Potash, James B., Shi, Jianxin, Knowles, James A., Perlis, Roy H., Lucae, Susanne, Boomsma, Dorret I, Penninx, Brenda W. J. H., Hottenga, Jouke-Jan, de Geus, Eco J. C., Willemsen, Gonneke, Milaneschi, Yuri, Tiemeier, Henning, Grabe, Hans J., Teumer, Alexander, Van der Auwera, Sandra, Völker, Uwe, Hamilton, Steven P., Magnusson, Patrik K. E., Viktorin, Alexander, Mehta, Divya, Mullins, Niamh, Adams, Mark J., Breen, Gerome, McIntosh, Andrew M., Lewis, Cathryn M., Hougaard, David M., Nordentoft, Merete, Mors, Ole, Mortensen, Preben B., Werge, Thomas, Als, Thomas D., Børglum, Anders D., Petryshen, Tracey L., Smoller, Jordan W., Goldstein, Jill M., Blokland, Gabriëlla A. M., Grove, Jakob, Chen, Chia-Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, St Clair, David, Lencz, Todd, Mowry, Bryan J., Periyasamy, Sathish, Cairns, Murray J., Tooney, Paul A., Wu, Jing Qin, Kelly, Brian, Kirov, George, Sullivan, Patrick F., Corvin, Aiden, Riley, Brien P., Esko, Tõnu, Milani, Lili, Jönsson, Erik G., Palotie, Aarno, Ehrenreich, Hannelore, Begemann, Martin, Steixner-Kumar, Agnes, Sham, Pak C., Iwata, Nakao, Weinberger, Daniel R., Gejman, Pablo V., Sanders, Alan R., Buxbaum, Joseph D., Rujescu, Dan, Giegling, Ina, Konte, Bettina, Hartmann, Anette M., Bramon, Elvira, Murray, Robin M., Pato, Michele T., Lee, Jimmy, Melle, Ingrid, Molden, Espen, Ophoff, Roel A., McQuillin, Andrew, Bass, Nicholas J., Adolfsson, Rolf, Malhotra, Anil K., Martin, Nicholas G., Fullerton, Janice M., Mitchell, Philip B., Schofield, Peter R., Forstner, Andreas J., Degenhardt, Franziska, Schaupp, Sabrina, Comes, Ashley L., Kogevinas, Manolis, Guzman-Parra, José, Reif, Andreas, Streit, Fabian, Sirignano, Lea, Cichon, Sven, Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Lissowska, Jolanta, Mayoral, Fermin, Müller-Myhsok, Bertram, Świątkowska, Beata, Schulze, Thomas G., Nöthen, Markus M., Rietschel, Marcella, Kelsoe, John, Leboyer, Marion, Jamain, Stéphane, Etain, Bruno, Bellivier, Frank, Vincent, John B., Alda, Martin, O'Donovan, Claire, Cervantes, Pablo, Biernacka, Joanna M., Frye, Mark, McElroy, Susan L., Scott, Laura J., Stahl, Eli A., Landén, Mikael, Hamshere, Marian L., Smeland, Olav B., Djurovic, Srdjan, Vaaler, Arne E., Andreassen, Ole A., Baune, Bernhard T., Air, Tracy, Preisig, Martin, Uher, Rudolf, Levinson, Douglas F., Weissman, Myrna M., Potash, James B., Shi, Jianxin, Knowles, James A., Perlis, Roy H., Lucae, Susanne, Boomsma, Dorret I, Penninx, Brenda W. J. H., Hottenga, Jouke-Jan, de Geus, Eco J. C., Willemsen, Gonneke, Milaneschi, Yuri, Tiemeier, Henning, Grabe, Hans J., Teumer, Alexander, Van der Auwera, Sandra, Völker, Uwe, Hamilton, Steven P., Magnusson, Patrik K. E., Viktorin, Alexander, Mehta, Divya, Mullins, Niamh, Adams, Mark J., Breen, Gerome, McIntosh, Andrew M., Lewis, Cathryn M., Hougaard, David M., Nordentoft, Merete, Mors, Ole, Mortensen, Preben B., Werge, Thomas, Als, Thomas D., Børglum, Anders D., Petryshen, Tracey L., Smoller, Jordan W., and Goldstein, Jill M.
Abstract: BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular f
Published: 2022
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17. Genome-wide by Environment Interaction Study of Stressful Life Events and Hospital-Treated Depression in the iPSYCH2012 Sample.

Author: Suppli, Nis P, Suppli, Nis P, Andersen, Klaus K, Agerbo, Esben, Rajagopal, Veera M, Appadurai, Vivek, Coleman, Jonathan RI, Breen, Gerome, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Pedersen, Carsten B, Pedersen, Marianne G, Thompson, Wesley K, Munk-Olsen, Trine, Benros, Michael E, Als, Thomas D, Grove, Jakob, Werge, Thomas, Børglum, Anders D, Hougaard, David M, Mors, Ole, Nordentoft, Merete, Mortensen, Preben B, Musliner, Katherine L, Suppli, Nis P, Suppli, Nis P, Andersen, Klaus K, Agerbo, Esben, Rajagopal, Veera M, Appadurai, Vivek, Coleman, Jonathan RI, Breen, Gerome, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Pedersen, Carsten B, Pedersen, Marianne G, Thompson, Wesley K, Munk-Olsen, Trine, Benros, Michael E, Als, Thomas D, Grove, Jakob, Werge, Thomas, Børglum, Anders D, Hougaard, David M, Mors, Ole, Nordentoft, Merete, Mortensen, Preben B, and Musliner, Katherine L
Abstract: BackgroundResearchers have long investigated a hypothesized interaction between genetic risk and stressful life events in the etiology of depression, but studies on the topic have yielded inconsistent results.MethodsWe conducted a genome-wide by environment interaction study (GWEIS) in 18,532 patients with depression from hospital-based settings and 20,184 population controls. All individuals were drawn from the iPSYCH2012 case-cohort study, a nationally representative sample identified from Danish national registers. Information on stressful life events including family disruption, serious medical illness, death of a first-degree relative, parental disability, and child maltreatment was identified from the registers and operationalized as a time-varying count variable. Hazard ratios for main and interaction effects were estimated using Cox regressions weighted to accommodate the case-cohort design. Our replication sample included 22,880 depression cases and 50,378 controls from the UK Biobank.ResultsThe GWEIS in the iPSYCH2012 sample yielded three novel, genome-wide-significant (p < 5 × 10-8) loci located in the ABCC1 gene (rs56076205, p = 3.7 × 10-10), the AKAP6 gene (rs3784187, p = 1.2 × 10-8), and near the MFSD1 gene (rs340315, p = 4.5 × 10-8). No hits replicated in the UK Biobank (rs56076205: p = .87; rs3784187: p = .93; rs340315: p = .71).ConclusionsIn this large, population-based GWEIS, we did not find any replicable hits for interaction. Future gene-by-stress research in depression should focus on establishing even larger collaborative GWEISs to attain sufficient power.
Published: 2022

18. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., Homman, Lina, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., and Homman, Lina
Abstract: Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380
Published: 2022
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19. Differences in the genetic architecture of common and rare variants in childhood, persistent and late-diagnosed attention-deficit hyperactivity disorder

Author: Rajagopal, Veera M., Duan, Jinjie, Vilar-Ribó, Laura, Grove, Jakob, Zayats, Tetyana, Ramos-Quiroga, J. Antoni, Satterstrom, F. Kyle, Artigas, María Soler, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Als, Thomas D., Rosengren, Anders, Daly, Mark J, Neale, Benjamin M, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Mortensen, Preben B., Ribasés, Marta, Børglum, Anders D., Demontis, Ditte, Rajagopal, Veera M., Duan, Jinjie, Vilar-Ribó, Laura, Grove, Jakob, Zayats, Tetyana, Ramos-Quiroga, J. Antoni, Satterstrom, F. Kyle, Artigas, María Soler, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Als, Thomas D., Rosengren, Anders, Daly, Mark J, Neale, Benjamin M, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Mortensen, Preben B., Ribasés, Marta, Børglum, Anders D., and Demontis, Ditte
Abstract: Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with onset in childhood (childhood ADHD); two-thirds of affected individuals continue to have ADHD in adulthood (persistent ADHD), and sometimes ADHD is diagnosed in adulthood (late-diagnosed ADHD). We evaluated genetic differences among childhood (n = 14,878), persistent (n = 1,473) and late-diagnosed (n = 6,961) ADHD cases alongside 38,303 controls, and rare variant differences in 7,650 ADHD cases and 8,649 controls. We identified four genome-wide significant loci for childhood ADHD and one for late-diagnosed ADHD. We found increased polygenic scores for ADHD in persistent ADHD compared with the other two groups. Childhood ADHD had higher genetic overlap with hyperactivity and autism compared with late-diagnosed ADHD and the highest burden of rare protein-truncating variants in evolutionarily constrained genes. Late-diagnosed ADHD had a larger genetic overlap with depression than childhood ADHD and no increased burden in rare protein-truncating variants. Overall, these results suggest a genetic influence on age at first ADHD diagnosis, persistence of ADHD and the different comorbidity patterns among the groups.
Published: 2022

20. Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups

Author: Mattheisen, Manuel, Grove, Jakob, Als, Thomas D., Martin, Joanna, Voloudakis, Georgios, Meier, Sandra, Demontis, Ditte, Bendl, Jaroslav, Walters, Raymond, Carey, Caitlin E., Rosengren, Anders, Strom, Nora I., Hauberg, Mads Engel, Zeng, Biao, Hoffman, Gabriel, Zhang, Wen, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Agerbo, Esben, Cormand, Bru, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Buxbaum, Joseph D., Faraone, Stephen V., Franke, Barbara, Dalsgaard, Søren, Mortensen, Preben B., Robinson, Elise B., Roussos, Panos, Neale, Benjamin M., Daly, Mark J., Børglum, Anders D., Mattheisen, Manuel, Grove, Jakob, Als, Thomas D., Martin, Joanna, Voloudakis, Georgios, Meier, Sandra, Demontis, Ditte, Bendl, Jaroslav, Walters, Raymond, Carey, Caitlin E., Rosengren, Anders, Strom, Nora I., Hauberg, Mads Engel, Zeng, Biao, Hoffman, Gabriel, Zhang, Wen, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Agerbo, Esben, Cormand, Bru, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Buxbaum, Joseph D., Faraone, Stephen V., Franke, Barbara, Dalsgaard, Søren, Mortensen, Preben B., Robinson, Elise B., Roussos, Panos, Neale, Benjamin M., Daly, Mark J., and Børglum, Anders D.
Abstract: Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable neurodevelopmental conditions, with considerable overlap in their genetic etiology. We dissected their shared and distinct genetic etiology by cross-disorder analyses of large datasets. We identified seven loci shared by the disorders and five loci differentiating them. All five differentiating loci showed opposite allelic directions in the two disorders and significant associations with other traits, including educational attainment, neuroticism and regional brain volume. Integration with brain transcriptome data enabled us to identify and prioritize several significantly associated genes. The shared genomic fraction contributing to both disorders was strongly correlated with other psychiatric phenotypes, whereas the differentiating portion was correlated most strongly with cognitive traits. Additional analyses revealed that individuals diagnosed with both ASD and ADHD were double-loaded with genetic predispositions for both disorders and showed distinctive patterns of genetic association with other traits compared with the ASD-only and ADHD-only subgroups. These results provide insights into the biological foundation of the development of one or both conditions and of the factors driving psychopathology discriminatively toward either ADHD or ASD.
Published: 2022

21. Genome-wide study of early and severe childhood asthma identifies interaction between CDHR3 and GSDMB

Author: Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andreanna, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., Bønnelykke, Klaus, Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andreanna, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., and Bønnelykke, Klaus
Abstract: Background: Asthma with severe exacerbation is one of the most common causes of hospitalization among young children. Exacerbations are typically triggered by respiratory infections, but the host factors causing recurrent infections and exacerbations in some children are poorly understood. As a result, current treatment options and preventive measures are inadequate. Objective: To identify genetic interaction associated with the development of childhood asthma. Methods: We performed an exhaustive search for pairwise interaction between genetic variants, single nucleotide polymorphisms (SNPs), using 1204 cases with a specific phenotype of early childhood asthma with severe exacerbations (age 2-6 years) combined with 5328 non-asthmatic controls. Replication was attempted in 3 independent populations, and potential underlying immune mechanisms were investigated in the COPSAC2010 and COPSAC2000 birth cohorts. Results: We found evidence of interaction, including replication in independent populations, between the known childhood asthma loci, CDHR3 and GSDMB. The effect of CDHR3 was dependent on the GSDMB genotype and this interaction was more pronounced for severe and early onset of disease. Blood immune analyses suggested a mechanism related to increased IL-17A production after viral stimulation. Conclusions: We found evidence of interaction between CDHR3 and GSDMB in development of early childhood asthma, possibly related to increased IL-17A response to viral infections. This study demonstrates the importance of focusing on specific disease subtypes for understanding the genetic mechanisms of asthma.
Published: 2022

22. Early-Life Injuries and the Development of Attention-Deficit/Hyperactivity Disorder

Author: Wimberley, Theresa, Brikell, Isabell, Pedersen, Emil M., Agerbo, Esben, Vilhjálmsson, Bjarni J., Albiñana, Clara, Privé, Florian, Thapar, Anita, Langley, Kate, Riglin, Lucy, Simonsen, Marianne, Nielsen, Helena S., Børglum, Anders D., Nordentoft, Merete, Mortensen, Preben B., Dalsgaard, Søren, Wimberley, Theresa, Brikell, Isabell, Pedersen, Emil M., Agerbo, Esben, Vilhjálmsson, Bjarni J., Albiñana, Clara, Privé, Florian, Thapar, Anita, Langley, Kate, Riglin, Lucy, Simonsen, Marianne, Nielsen, Helena S., Børglum, Anders D., Nordentoft, Merete, Mortensen, Preben B., and Dalsgaard, Søren
Abstract: Objective: To estimate phenotypic and familial association between early-life injuries and attention-deficit/hyperactivity disorder (ADHD) and the genetic contribution to the association using polygenic risk score for ADHD (PRS-ADHD) and genetic correlation analyses. Methods: Children born in Denmark between 1995–2010 (n = 786,543) were followed from age 5 years until a median age of 14 years (interquartile range: 10–18 years). Using ICD-10 diagnoses, we estimated hazard ratios (HRs) and absolute risks of ADHD by number of hospital/emergency ward–treated injuries by age 5. In a subset of ADHD cases and controls born 1995 to 2005 who had genetic data available (n = 16,580), we estimated incidence rate ratios (IRRs) for the association between PRS-ADHD and number of injuries before age 5 and the genetic correlation between ADHD and any injury before age 5. Results: Injuries were associated with ADHD (HR = 1.61; 95% CI, 1.55–1.66) in males (HR = 1.59; 1.53–1.65) and females (HR = 1.65; 1.54–1.77), with a dose-response relationship with number of injuries. The absolute ADHD risk by age 15 was 8.4% (3+ injuries) vs 3.1% (no injuries). ADHD was also associated with injuries in relatives, with a stronger association in first- than second-degree relatives. PRS-ADHD was marginally associated with the number of injuries in the general population (IRR = 1.06; 1.00–1.14), with a genetic correlation of 0.53 (0.21–0.85). Conclusions: Early-life injuries in individuals and their relatives were associated with a diagnosis of ADHD. However, even in children with the most injuries, more than 90% were not diagnosed with ADHD by age 15. Despite a low positive predictive value and that the impact of unmeasured factors such as parental behavior remains unclear, results indicate that the association is partly explained by genetics, suggesting that early-life injuries may represent or herald early behavioral manifestations of ADHD.
Published: 2022

23. Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

Author: Weiner, Daniel J., Ling, Emi, Erdin, Serkan, Tai, Derek J.C., Yadav, Rachita, Grove, Jakob, Fu, Jack M., Nadig, Ajay, Carey, Caitlin, Baya, Nikolas, Bybjerg-Grauholm, Jonas, Mortensen, Preben B., Werge, Thomas, Demontis, Ditte, Mors, Ole, Nordentoft, Merete, Als, Thomas D., Baekvad-Hansen, Marie, Rosengren, Anders, Havdahl, Alexandra, Hedemand, Anne, Palotie, Aarno, Chakravarti, Aravinda, Arking, Dan, Sulovari, Arvis, Starnawska, Anna, Thiruvahindrapuram, Bhooma, de Leeuw, Christiaan, Ladd-Acosta, Christine, van der Merwe, Celia, Devlin, Bernie, Cook, Edwin H., Eichler, Evan, Corfield, Elisabeth, Dieleman, Gwen, Schellenberg, Gerard, Hakonarson, Hakon, Coon, Hilary, Dziobek, Isabel, Vorstman, Jacob, Girault, Jessica, Sutcliffe, James S., Duan, Jinjie, Nurnberger, John, Hallmayer, Joachim, Buxbaum, Joseph, Hinney, Anke, Larsson, Henrik, Dalsgaard, Soren, Weiner, Daniel J., Ling, Emi, Erdin, Serkan, Tai, Derek J.C., Yadav, Rachita, Grove, Jakob, Fu, Jack M., Nadig, Ajay, Carey, Caitlin, Baya, Nikolas, Bybjerg-Grauholm, Jonas, Mortensen, Preben B., Werge, Thomas, Demontis, Ditte, Mors, Ole, Nordentoft, Merete, Als, Thomas D., Baekvad-Hansen, Marie, Rosengren, Anders, Havdahl, Alexandra, Hedemand, Anne, Palotie, Aarno, Chakravarti, Aravinda, Arking, Dan, Sulovari, Arvis, Starnawska, Anna, Thiruvahindrapuram, Bhooma, de Leeuw, Christiaan, Ladd-Acosta, Christine, van der Merwe, Celia, Devlin, Bernie, Cook, Edwin H., Eichler, Evan, Corfield, Elisabeth, Dieleman, Gwen, Schellenberg, Gerard, Hakonarson, Hakon, Coon, Hilary, Dziobek, Isabel, Vorstman, Jacob, Girault, Jessica, Sutcliffe, James S., Duan, Jinjie, Nurnberger, John, Hallmayer, Joachim, Buxbaum, Joseph, Hinney, Anke, Larsson, Henrik, and Dalsgaard, Soren
Abstract: The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.
Published: 2022

24. Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups

Author: Mattheisen, Manuel, Grove, Jakob, Als, Thomas D., Martin, Joanna, Voloudakis, Georgios, Meier, Sandra, Demontis, Ditte, Bendl, Jaroslav, Walters, Raymond, Carey, Caitlin E., Rosengren, Anders, Strom, Nora I., Hauberg, Mads Engel, Zeng, Biao, Hoffman, Gabriel, Zhang, Wen, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Agerbo, Esben, Cormand, Bru, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Buxbaum, Joseph D., Faraone, Stephen V., Franke, Barbara, Dalsgaard, Søren, Mortensen, Preben B., Robinson, Elise B., Roussos, Panos, Neale, Benjamin M., Daly, Mark J., Børglum, Anders D., Mattheisen, Manuel, Grove, Jakob, Als, Thomas D., Martin, Joanna, Voloudakis, Georgios, Meier, Sandra, Demontis, Ditte, Bendl, Jaroslav, Walters, Raymond, Carey, Caitlin E., Rosengren, Anders, Strom, Nora I., Hauberg, Mads Engel, Zeng, Biao, Hoffman, Gabriel, Zhang, Wen, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Agerbo, Esben, Cormand, Bru, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Buxbaum, Joseph D., Faraone, Stephen V., Franke, Barbara, Dalsgaard, Søren, Mortensen, Preben B., Robinson, Elise B., Roussos, Panos, Neale, Benjamin M., Daly, Mark J., and Børglum, Anders D.
Abstract: Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable neurodevelopmental conditions, with considerable overlap in their genetic etiology. We dissected their shared and distinct genetic etiology by cross-disorder analyses of large datasets. We identified seven loci shared by the disorders and five loci differentiating them. All five differentiating loci showed opposite allelic directions in the two disorders and significant associations with other traits, including educational attainment, neuroticism and regional brain volume. Integration with brain transcriptome data enabled us to identify and prioritize several significantly associated genes. The shared genomic fraction contributing to both disorders was strongly correlated with other psychiatric phenotypes, whereas the differentiating portion was correlated most strongly with cognitive traits. Additional analyses revealed that individuals diagnosed with both ASD and ADHD were double-loaded with genetic predispositions for both disorders and showed distinctive patterns of genetic association with other traits compared with the ASD-only and ADHD-only subgroups. These results provide insights into the biological foundation of the development of one or both conditions and of the factors driving psychopathology discriminatively toward either ADHD or ASD.
Published: 2022

25. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Medical Research Council (UK), Cardiff University, Welsh Government, Health and Care Research Wales, European Commission, Academy of Medical Sciences (UK), Research Council of Norway, K. G. Jebsen Centres for Medical Research, National Institute for Health Research (UK), University College London, Government of Canada, University of Manitoba, Swedish Research Council, National Institute of Mental Health (US), Kings College London, Public Health Agency (Northern Ireland), The Psychiatry Research Trust, Maudsley Charity, Swiss National Science Foundation, Fondation Alamaya, Ministry of Health of the Czech Republic, Instituto de Salud Carlos III, Plan Nacional sobre Drogas (España), Fundació Seny, Fundación Marques de Valdecilla, Ministerio de Economía y Competitividad (España), Wellcome Trust, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy, Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O'Donovan, Michael C., Walters, James T. R., Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances (STRATA), Consortium and the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC), Medical Research Council (UK), Cardiff University, Welsh Government, Health and Care Research Wales, European Commission, Academy of Medical Sciences (UK), Research Council of Norway, K. G. Jebsen Centres for Medical Research, National Institute for Health Research (UK), University College London, Government of Canada, University of Manitoba, Swedish Research Council, National Institute of Mental Health (US), Kings College London, Public Health Agency (Northern Ireland), The Psychiatry Research Trust, Maudsley Charity, Swiss National Science Foundation, Fondation Alamaya, Ministry of Health of the Czech Republic, Instituto de Salud Carlos III, Plan Nacional sobre Drogas (España), Fundació Seny, Fundación Marques de Valdecilla, Ministerio de Economía y Competitividad (España), Wellcome Trust, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy, Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O'Donovan, Michael C., Walters, James T. R., Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances (STRATA), and Consortium and the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC)
Abstract: [Importance] About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts., [Objective] To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples., [Design, Setting, and Participants] Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G])., [Main Outcomes and Measures] GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition., [Results] The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04)., [Conclusions and Relevance] In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.
Published: 2022

26. Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

Author: Weiner, Daniel J., Ling, Emi, Erdin, Serkan, Tai, Derek J.C., Yadav, Rachita, Grove, Jakob, Fu, Jack M., Nadig, Ajay, Carey, Caitlin, Baya, Nikolas, Bybjerg-Grauholm, Jonas, Mortensen, Preben B., Werge, Thomas, Demontis, Ditte, Mors, Ole, Nordentoft, Merete, Als, Thomas D., Baekvad-Hansen, Marie, Rosengren, Anders, Havdahl, Alexandra, Hedemand, Anne, Palotie, Aarno, Chakravarti, Aravinda, Arking, Dan, Sulovari, Arvis, Starnawska, Anna, Thiruvahindrapuram, Bhooma, de Leeuw, Christiaan, Ladd-Acosta, Christine, van der Merwe, Celia, Devlin, Bernie, Cook, Edwin H., Eichler, Evan, Corfield, Elisabeth, Dieleman, Gwen, Schellenberg, Gerard, Hakonarson, Hakon, Coon, Hilary, Dziobek, Isabel, Vorstman, Jacob, Girault, Jessica, Sutcliffe, James S., Duan, Jinjie, Nurnberger, John, Hallmayer, Joachim, Buxbaum, Joseph, Hinney, Anke, Larsson, Henrik, Dalsgaard, Soren, Weiner, Daniel J., Ling, Emi, Erdin, Serkan, Tai, Derek J.C., Yadav, Rachita, Grove, Jakob, Fu, Jack M., Nadig, Ajay, Carey, Caitlin, Baya, Nikolas, Bybjerg-Grauholm, Jonas, Mortensen, Preben B., Werge, Thomas, Demontis, Ditte, Mors, Ole, Nordentoft, Merete, Als, Thomas D., Baekvad-Hansen, Marie, Rosengren, Anders, Havdahl, Alexandra, Hedemand, Anne, Palotie, Aarno, Chakravarti, Aravinda, Arking, Dan, Sulovari, Arvis, Starnawska, Anna, Thiruvahindrapuram, Bhooma, de Leeuw, Christiaan, Ladd-Acosta, Christine, van der Merwe, Celia, Devlin, Bernie, Cook, Edwin H., Eichler, Evan, Corfield, Elisabeth, Dieleman, Gwen, Schellenberg, Gerard, Hakonarson, Hakon, Coon, Hilary, Dziobek, Isabel, Vorstman, Jacob, Girault, Jessica, Sutcliffe, James S., Duan, Jinjie, Nurnberger, John, Hallmayer, Joachim, Buxbaum, Joseph, Hinney, Anke, Larsson, Henrik, and Dalsgaard, Soren
Abstract: The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.
Published: 2022

27. Maternal pregnancy-related infections and autism spectrum disorder—the genetic perspective

Author: Nudel, Ron, Thompson, Wesley K., Børglum, Anders D., Hougaard, David M., Mortensen, Preben B., Werge, Thomas, Nordentoft, Merete, Benros, Michael E., Nudel, Ron, Thompson, Wesley K., Børglum, Anders D., Hougaard, David M., Mortensen, Preben B., Werge, Thomas, Nordentoft, Merete, and Benros, Michael E.
Abstract: Autism spectrum disorder (ASD) refers to a group of neurodevelopmental disorders which include deficits in behavior, social interaction and communication. ASD has a complex genetic architecture, and it is also influenced by certain environmental exposures. Both types of predisposing factors may be related to immunological mechanisms, involving, for example, immune system genes and infections. Past studies have shown an association between infections occurring during the pregnancy in the mother and increased risk of ASD in the child, an observation which has received recent support from experimental animal studies of ASD-like behavior. The aim of this study was to study the genetic contribution to this effect. We employed genetic correlation analyses across potential ASD subtypes stratified on the basis of maternal pregnancy-related infections within the iPSYCH ASD case-cohort sample, as well as a case-case GWAS. We validated the trends of the genetic correlation analyses observed in our sample using GWAS summary statistics from the PGC ASD study (excluding iPSYCH). The genetic correlation between ASD with a history of maternal pregnancy-related infections and ASD without a history of maternal infections in iPSYCH was rg = 0.3811. We obtained a similar estimate between the former and the PGC ASD phenotype (rg = 0.3997). Both estimates are lower compared to the genetic correlation between ASD without a history of maternal infections and the PGC ASD phenotype (rg = 0.6735), and between ASD with a history of maternal infections occurring only more than 2 months following childbirth and the PGC ASD phenotype (rg = 0.6293). Additionally, we observed genetic variance between the two main ASD phenotypes using summary statistics from the case-case GWAS in iPSYCH (h2cc = 0.1059), indicating genome-wide differences between the phenotypes. Our results suggest potentially different etiologies of ASD based on a
Published: 2022

28. Differences in the genetic architecture of common and rare variants in childhood, persistent and late-diagnosed attention-deficit hyperactivity disorder

Author: Rajagopal, Veera M., Duan, Jinjie, Vilar-Ribó, Laura, Grove, Jakob, Zayats, Tetyana, Ramos-Quiroga, J. Antoni, Satterstrom, F. Kyle, Artigas, María Soler, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Als, Thomas D., Rosengren, Anders, Daly, Mark J, Neale, Benjamin M, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Mortensen, Preben B., Ribasés, Marta, Børglum, Anders D., Demontis, Ditte, Rajagopal, Veera M., Duan, Jinjie, Vilar-Ribó, Laura, Grove, Jakob, Zayats, Tetyana, Ramos-Quiroga, J. Antoni, Satterstrom, F. Kyle, Artigas, María Soler, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Als, Thomas D., Rosengren, Anders, Daly, Mark J, Neale, Benjamin M, Nordentoft, Merete, Werge, Thomas, Mors, Ole, Hougaard, David M., Mortensen, Preben B., Ribasés, Marta, Børglum, Anders D., and Demontis, Ditte
Abstract: Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with onset in childhood (childhood ADHD); two-thirds of affected individuals continue to have ADHD in adulthood (persistent ADHD), and sometimes ADHD is diagnosed in adulthood (late-diagnosed ADHD). We evaluated genetic differences among childhood (n = 14,878), persistent (n = 1,473) and late-diagnosed (n = 6,961) ADHD cases alongside 38,303 controls, and rare variant differences in 7,650 ADHD cases and 8,649 controls. We identified four genome-wide significant loci for childhood ADHD and one for late-diagnosed ADHD. We found increased polygenic scores for ADHD in persistent ADHD compared with the other two groups. Childhood ADHD had higher genetic overlap with hyperactivity and autism compared with late-diagnosed ADHD and the highest burden of rare protein-truncating variants in evolutionarily constrained genes. Late-diagnosed ADHD had a larger genetic overlap with depression than childhood ADHD and no increased burden in rare protein-truncating variants. Overall, these results suggest a genetic influence on age at first ADHD diagnosis, persistence of ADHD and the different comorbidity patterns among the groups.
Published: 2022

29. Maternal pregnancy-related infections and autism spectrum disorder—the genetic perspective

Author: Nudel, Ron, Thompson, Wesley K., Børglum, Anders D., Hougaard, David M., Mortensen, Preben B., Werge, Thomas, Nordentoft, Merete, Benros, Michael E., Nudel, Ron, Thompson, Wesley K., Børglum, Anders D., Hougaard, David M., Mortensen, Preben B., Werge, Thomas, Nordentoft, Merete, and Benros, Michael E.
Abstract: Autism spectrum disorder (ASD) refers to a group of neurodevelopmental disorders which include deficits in behavior, social interaction and communication. ASD has a complex genetic architecture, and it is also influenced by certain environmental exposures. Both types of predisposing factors may be related to immunological mechanisms, involving, for example, immune system genes and infections. Past studies have shown an association between infections occurring during the pregnancy in the mother and increased risk of ASD in the child, an observation which has received recent support from experimental animal studies of ASD-like behavior. The aim of this study was to study the genetic contribution to this effect. We employed genetic correlation analyses across potential ASD subtypes stratified on the basis of maternal pregnancy-related infections within the iPSYCH ASD case-cohort sample, as well as a case-case GWAS. We validated the trends of the genetic correlation analyses observed in our sample using GWAS summary statistics from the PGC ASD study (excluding iPSYCH). The genetic correlation between ASD with a history of maternal pregnancy-related infections and ASD without a history of maternal infections in iPSYCH was rg = 0.3811. We obtained a similar estimate between the former and the PGC ASD phenotype (rg = 0.3997). Both estimates are lower compared to the genetic correlation between ASD without a history of maternal infections and the PGC ASD phenotype (rg = 0.6735), and between ASD with a history of maternal infections occurring only more than 2 months following childbirth and the PGC ASD phenotype (rg = 0.6293). Additionally, we observed genetic variance between the two main ASD phenotypes using summary statistics from the case-case GWAS in iPSYCH (h2cc = 0.1059), indicating genome-wide differences between the phenotypes. Our results suggest potentially different etiologies of ASD based on a
Published: 2022

30. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., Homman, Lina, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., and Homman, Lina
Abstract: Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380
Published: 2022
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31. Genome-wide study of early and severe childhood asthma identifies interaction between CDHR3 and GSDMB

Author: Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andréanne, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., Bønnelykke, Klaus, Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andréanne, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., and Bønnelykke, Klaus
Abstract: Background: Asthma with severe exacerbation is one of the most common causes of hospitalization among young children. Exacerbations are typically triggered by respiratory infections, but the host factors causing recurrent infections and exacerbations in some children are poorly understood. As a result, current treatment options and preventive measures are inadequate. Objective: We sought to identify genetic interaction associated with the development of childhood asthma. Methods: We performed an exhaustive search for pairwise interaction between genetic single nucleotide polymorphisms using 1204 cases of a specific phenotype of early childhood asthma with severe exacerbations in patients aged 2 to 6 years combined with 5328 nonasthmatic controls. Replication was attempted in 3 independent populations, and potential underlying immune mechanisms were investigated in the COPSAC2010 and COPSAC2000 birth cohorts. Results: We found evidence of interaction, including replication in independent populations, between the known childhood asthma loci CDHR3 and GSDMB. The effect of CDHR3 was dependent on the GSDMB genotype, and this interaction was more pronounced for severe and early onset of disease. Blood immune analyses suggested a mechanism related to increased IL-17A production after viral stimulation. Conclusions: We found evidence of interaction between CDHR3 and GSDMB in development of early childhood asthma, possibly related to increased IL-17A response to viral infections. This study demonstrates the importance of focusing on specific disease subtypes for understanding the genetic mechanisms of asthma.
Published: 2022

32. Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Author: Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., Homman, Lina, Pardiñas, Antonio F., Smart, Sophie E., Willcocks, Isabella R., Holmans, Peter A., Dennison, Charlotte A., Lynham, Amy J., Legge, Sophie E., Baune, Bernhard T., Bigdeli, Tim B., Cairns, Murray J., Corvin, Aiden, Fanous, Ayman H., Frank, Josef, Kelly, Brian, McQuillin, Andrew, Melle, Ingrid, Mortensen, Preben B., Mowry, Bryan J., Pato, Carlos N., Periyasamy, Sathish, Rietschel, Marcella, Rujescu, Dan, Simonsen, Carmen, St Clair, David, Tooney, Paul, Wu, Jing Qin, Andreassen, Ole A., Kowalec, Kaarina, Sullivan, Patrick F., Murray, Robin M., Owen, Michael J., MacCabe, James H., O’Donovan, Michael C., Walter, James, T., and Homman, Lina
Abstract: Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380
Published: 2022
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33. Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Author: Medical Research Council (UK), National Natural Science Foundation of China, Royal Society (UK), Chinese Academy of Sciences, Shanghai Science and Technology Committee, Research Council of Norway, European Commission, Fundação de Amparo à Pesquisa do Estado de São Paulo, Ministerio de Ciencia e Innovación (España), Instituto de Salud Carlos III, Comunidad de Madrid, Fundación Alicia Koplowitz, Fundación Alonso Lozano, Mental Health Research UK, Wellcome Trust, Brain and Behavior Research Foundation, NIHR Biomedical Research Centre (UK), University College London, Generalitat Valenciana, Trubetskoy, Vassily, Pardiñas, Antonio F., Qi, Ting, Panagiotaropoulou, Georgia, Awasthi, Swapnil, Bigdeli, Tim B., Bryois, Julien, Chen, Chia-Yen, Dennison, Charlotte A., Hall, Lynsey S., Lam, Max, Curtis, Charles, Nikitina-Zake, Liene, Davidson, Michael, Joa, Inge, Davis, Kenneth L., Yolken, Robert, Murray, Robin M., de Haan, Lieuwe, Legge, Sophie E., Serretti, Alessandro, van Os, Jim, Smoller, Jordan W., Agartz, Ingrid, Alizadeh, Behrooz Z., Degenhardt, Franziska, DeLisi, Lynn E., Demontis, Ditte, Dickerson, Faith, Zai, Clement C., Dikeos, Dimitris, Dinan, Timothy, Henskens, Frans A., Vaaler, Arne, Noto, Cristiano, Nimgaonkar, Vishwajit, Rautanen, Anna, Lehrer, Douglas S., Djurovic, Srdjan, Duan, Jubao, Julià, Antonio, Stahl, Eli A., Zhou, Wei, Vawter, Marquis P., Toncheva, Draga, Webb, Bradley T., Ducci, Giuseppe, Dudbridge, Frank, Eriksson, Johan G., Fañanas Saura, Lourdes, Goldstein, Jacqueline I., Faraone, Stephen V., Lencer, Rebecca, Moreno, Carmen, Bacanu, Silviu A., Fiorentino, Alessia, Calkins, Monica E., Mitjans, Marina, Forstner, Andreas, Nuechterlein, Keith H., Frank, Josef, Tsuang, Debby W., Freimer, Nelson B., Tooney, Paul A., Belangero, Sintia Iole, Weinberger, Daniel R., Fromer, Menachem, Ge,Tian, Adolfsson, Rolf, Hakonarson, Hakon, Zhu, Feng, Frustaci, Alessandra, Nöthen, Markus M., Gadelha, Ary, Genovese, Giulio, Gershon, Elliot S., Quattrone, Diego, Kähler, Anna K., Kam-Thong, Tony, van Amelsvoort, Therese, Vilella, Elisabet, Molden, Espen, O'Brien, Niamh Louise, Zimprich, Fritz, Kamatani, Yoichiro, Braun, Alice, Melegh, Bela, Pirinen, Matti, Karachanak-Yankova, Sena, Ophoff, Roel A., Kebir, Oussama, Lerer, Bernard, Nordentoft, Merete, Fanous, Ayman H., Reichenberg, Abraham, Li, Miaoxin, Periyasamy, Sathish, Lieberman, Jeffrey, Werge, Thomas, Light, Gregory A., Limborska, Svetlana, Tosato, Sarah, Liu, Chih-Min, Olincy, Ann, Magnusson, Sigurdur, Gareeva, Anna, Bressan, Rodrigo Affonseca, Lönnqvist, Jouko, Roe, Cheryl, Cheng, Wei, Athanasiu, Lavinia, Gutiérrez, Blanca, Harvey, Carol, Loughland, Carmel M., Lubinski, Jan, Luykx, Jurjen J., Lynham, Amy, Gawlik, Micha, Macek, Milan, Mackinnon, Andrew, Buxbaum, Joseph D., Tura, Gian Battista, Bromet, Evelyn J., Atbaşoğlu, Eşref Cem, Roffman, Joshua L., Magnusson, Patrik K. E., Maher, Brion S., Ota, Vanessa Kiyomi, Paciga, Sara A., Gejman, Pablo V., Arango, Celso, Forti, Marta Di, Maier, Wolfgang, Richards, Alexander L., Malaspina, Dolores, Mallet, Jacques, Metspalu, Andres, Marder, Stephen R., Li, Zhiqiang, Takahashi, Atsushi, Marsal, Sara, Kučinskiene, Zita Ausrele, Suvisaari, Jaana, Martin, Alicia R., Turetsky, Bruce I., Martorell, Lourdes, Palotie, Aarno, Mattheisen, Manuel, Baune, Bernhard T., Saka, Meram C., McCarley, Robert W., Giusti-Rodríguez, Paola, Riley, Brien P., Murphy, Kieran C., Gill, Michael, McDonald, Colm, Bruggeman, Richard, McGrath, John J., Sidorenko, Julia, Medeiros, Helena, Pantelis, Christos, Grove, Jakob, Campion, Dominique, Pato, Carlos N., Svrakic, Dragan M., Üçok, Alp, Glatt, Stephen J., Papadimitriou, George N., Khrunin, Andrey, Straub, Richard E., Parellada, Mara, Buckley, Peter F., Paunio, Tiina, Roth, Julian, Morgan, Vera A., Wildenauer, Dieter B., Ayub, Muhammad, Rothermundt, Matthias, Weiser, Mark, Rutten, Bart P. F., Saker-Delye, Safaa, Salomaa, Veikko, Børglum, Anders D., Sanjuán, Julio, van Winkel, Ruud, González Peñas, Javier, Yu, Xin, Kim, Sung-Wan, Santoro, Marcos Leite, Benner, Christian, Ikeda, Masashi, Morley, Christopher P., Zeng, Jian, Savitz, Adam, Schall, Ulrich, Scott, Rodney J., Voloudakis, Georgios, Yue, Weihua, Seidman, Larry J., Sharp, Sally Isabel, Alptekin, Köksal, Klovins, Janis, Amin, Farooq, Bertolino, Alessandro, Shi, Jianxin, Siever, Larry J., Atkinson, Elizabeth G., Buckner, Randy L., Holmans, Peter A., Rivera, Margarita, Sigurdsson, Engilbert, González-Pinto, Ana, Sim, Kang, Skarabis, Nora, Stroup, T Scott, Slominsky, Petr, Guillin, Olivier, Wang, Shi-Heng, So, Hon-Cheong, Quested, Digby, Sobell, Janet L., Braff, David, Zhang, Wen, Bybjerg-Grauholm, Jonas, Söderman, Erik, Rujescu, Dan, Chambert, Kimberley D., Stain, Helen J., Melle, Ingrid, Carr, Vaughan J, Pocklington, Andrew J., Steen, Nils Eiel, Harwood, Janet, Steixner-Kumar, Agnes A., Gopal, Srihari, Stögmann, Elisabeth, Veijola, Juha, Watanabe, Kyoko, Sham, Pak C., Cahn, Wiepke, Bramon, Elvira, Roussos, Panos, Waddington, John, Perkins, Diana O., Pato, Michele T., Walter, Henrik, Kondratiev, Nikolay, Waterreus, Anna, Al Eissa, Mariam, Bobes, Julio, Golimbet, Vera, Black, Donald W., Als, Thomas D., Bray, Nicholas J., Breen, Gerome, Buccola, Nancy G., Sanders, Alan R., Byerley, William F., Cervilla, Jorge A., Michie, Patricia T., Pfuhlmann, Bruno, Chen, Wei J., Hong, Kyung Sue, O'Neill, F Anthony, Terao, Chikashi, Green, Michael F., Cloninger, C. Robert, Crespo-Facorro, Benedicto, Donohoe, Gary, Gülöksüz, Sinan, Freedman, Robert, Albus, Margot, Hayward, Caroline, Pietiläinen, Olli, Herms, Stefan, Hultman, Christina M., Galletly, Cherrie, Gandal, Michael J., Hahn, Eric, Konte, Bettina, Castle, David, Gennarelli, Massimo, Milani, Lili, Hougaard, David M., Hwu, Hai-Gwo, Pulver, Ann E., Jablensky, Assen V., Molina, Esther, Qin, Shengying, McCarroll, Steven A., Moran, Jennifer L., Azevedo, Maria Helena, Gur, Rachel E., Kraft, Julia, Mors, Ole, Catts, Stanley V., Lazzeroni, Laura C., Mortensen, Preben B., Streit, Fabian, Kusumawardhani, Agung, Alexander, Madeline, Godard, Stephanie, Müller-Myhsok, Bertram, Milanova, Vihra, Neil, Amanda L., Cichon, Sven, Giannitelli, Marianna, Cheung, Eric F. C., Kubo, Michiaki, Schwab, Sibylle G., Collier, David A., Williams, Nigel M., Morris, Derek W., Corvin, Aiden, Pimm, Jonathan, Curtis, David, Haroutunian, Vahram, Keller, Matthew C., Vassos, Evangelos, Hyman, Steven E., Iwata, Nakao, Jönsson, Erik G., Kahn, René S., Chan, Raymond C. K., Kennedy, James L., Shi, Yongyong, Adams, Mark, Witt, Stephanie H., Khusnutdinova, Elza, Verhage, Matthijs, Xu, Shuhua, Wu, Yang, Kirov, George, Arolt, Volker, Knowles, James A., Moltó, Maria Dolores, Krebs, Marie-Odile, Hartmann, Annette M., Nestadt, Gerald, Wormley, Brandon K., Bass, Nicholas J., Laurent-Levinson, Claudine, Lee, Jimmy, Muntané, Gerard, Porteous, David, Kuzelova-Ptackova, Hana, Lencz, Todd, Subramaniam, Mythily, Levinson, Douglas F., Li, Qingqin S., Liu, Jianjun, Swerdlow, Neal R., Cairns, Murray J., Malhotra, Anil K., Malhotra, Dheeraj, Iyegbe, Conrad, Mondelli, Valeria, Kim, Minsoo, Arrojo, Manuel, Landi, Stefano, McIntosh, Andrew M., Petryshen, Tracey L., Radant, Allen D., Frei, Oleksandr, Mesholam-Gately, Raquelle I., McQuillin, Andrew, Sugar, Catherine A., Menezes, Paulo Rossi, St Clair, David, Meier, Sandra, Powell, John, Chaumette, Boris, Stefansson, Hreinn, Domenici, Enrico, Bonassi, Stefano, Stefánsson, Kári, Wu, Jing Qin, Tsuang, Ming T., Myin-Germeys, Inez, Pellegrino, Renata, Visscher, Peter M., Yang, Jian, Posthuma, Danielle, Andreassen, Ole A., Koopmans, Frank, Kendler, Kenneth S., Chong, Siow Ann, Gur, Ruben C., Ehrenreich, Hannelore, Owen, Michael J., Rietschel, Marcella, Gratten, Jacob, Wray, Naomi R., Hoffmann, Per, Daly, Mark J., Szatkiewicz, Jin P., Huang, Hailiang, Nenadić, Igor, Torretta, Silvia, Escott-Price, Valentina, Neale, Benjamin M., Begemann, Martin, Thibaut, Florence, Agerbo, Esben, Rampino, Antonio, Sullivan, Patrick F., Schulze, Thomas G., Ripke, Stephan, Walters, James T. R., O'Donovan, Michael C., Kučinskas, Vaidutis, Belliveau, Richard A., Bene, Judit, Oh, Sang-Yun, Ta, Thi Minh Tam, Greenwood, Tiffany A., Howrigan, Daniel P., Rapaport, Mark H., Benyamin, Beben, Mowry, Bryan J., Giegling, Ina, Strengman, Eric, Bergen, Sarah E., Silverman, Jeremy M., Blasi, Giuseppe, Cohen, David, Stone, William S., Xu, Zhida, Lee, Phil H., Consoli, Angèle, Kelly, Brian J.., Cordeiro, Quirino, Esko, Tõnu, Costas, Javier, Medical Research Council (UK), National Natural Science Foundation of China, Royal Society (UK), Chinese Academy of Sciences, Shanghai Science and Technology Committee, Research Council of Norway, European Commission, Fundação de Amparo à Pesquisa do Estado de São Paulo, Ministerio de Ciencia e Innovación (España), Instituto de Salud Carlos III, Comunidad de Madrid, Fundación Alicia Koplowitz, Fundación Alonso Lozano, Mental Health Research UK, Wellcome Trust, Brain and Behavior Research Foundation, NIHR Biomedical Research Centre (UK), University College London, Generalitat Valenciana, Trubetskoy, Vassily, Pardiñas, Antonio F., Qi, Ting, Panagiotaropoulou, Georgia, Awasthi, Swapnil, Bigdeli, Tim B., Bryois, Julien, Chen, Chia-Yen, Dennison, Charlotte A., Hall, Lynsey S., Lam, Max, Curtis, Charles, Nikitina-Zake, Liene, Davidson, Michael, Joa, Inge, Davis, Kenneth L., Yolken, Robert, Murray, Robin M., de Haan, Lieuwe, Legge, Sophie E., Serretti, Alessandro, van Os, Jim, Smoller, Jordan W., Agartz, Ingrid, Alizadeh, Behrooz Z., Degenhardt, Franziska, DeLisi, Lynn E., Demontis, Ditte, Dickerson, Faith, Zai, Clement C., Dikeos, Dimitris, Dinan, Timothy, Henskens, Frans A., Vaaler, Arne, Noto, Cristiano, Nimgaonkar, Vishwajit, Rautanen, Anna, Lehrer, Douglas S., Djurovic, Srdjan, Duan, Jubao, Julià, Antonio, Stahl, Eli A., Zhou, Wei, Vawter, Marquis P., Toncheva, Draga, Webb, Bradley T., Ducci, Giuseppe, Dudbridge, Frank, Eriksson, Johan G., Fañanas Saura, Lourdes, Goldstein, Jacqueline I., Faraone, Stephen V., Lencer, Rebecca, Moreno, Carmen, Bacanu, Silviu A., Fiorentino, Alessia, Calkins, Monica E., Mitjans, Marina, Forstner, Andreas, Nuechterlein, Keith H., Frank, Josef, Tsuang, Debby W., Freimer, Nelson B., Tooney, Paul A., Belangero, Sintia Iole, Weinberger, Daniel R., Fromer, Menachem, Ge,Tian, Adolfsson, Rolf, Hakonarson, Hakon, Zhu, Feng, Frustaci, Alessandra, Nöthen, Markus M., Gadelha, Ary, Genovese, Giulio, Gershon, Elliot S., Quattrone, Diego, Kähler, Anna K., Kam-Thong, Tony, van Amelsvoort, Therese, Vilella, Elisabet, Molden, Espen, O'Brien, Niamh Louise, Zimprich, Fritz, Kamatani, Yoichiro, Braun, Alice, Melegh, Bela, Pirinen, Matti, Karachanak-Yankova, Sena, Ophoff, Roel A., Kebir, Oussama, Lerer, Bernard, Nordentoft, Merete, Fanous, Ayman H., Reichenberg, Abraham, Li, Miaoxin, Periyasamy, Sathish, Lieberman, Jeffrey, Werge, Thomas, Light, Gregory A., Limborska, Svetlana, Tosato, Sarah, Liu, Chih-Min, Olincy, Ann, Magnusson, Sigurdur, Gareeva, Anna, Bressan, Rodrigo Affonseca, Lönnqvist, Jouko, Roe, Cheryl, Cheng, Wei, Athanasiu, Lavinia, Gutiérrez, Blanca, Harvey, Carol, Loughland, Carmel M., Lubinski, Jan, Luykx, Jurjen J., Lynham, Amy, Gawlik, Micha, Macek, Milan, Mackinnon, Andrew, Buxbaum, Joseph D., Tura, Gian Battista, Bromet, Evelyn J., Atbaşoğlu, Eşref Cem, Roffman, Joshua L., Magnusson, Patrik K. E., Maher, Brion S., Ota, Vanessa Kiyomi, Paciga, Sara A., Gejman, Pablo V., Arango, Celso, Forti, Marta Di, Maier, Wolfgang, Richards, Alexander L., Malaspina, Dolores, Mallet, Jacques, Metspalu, Andres, Marder, Stephen R., Li, Zhiqiang, Takahashi, Atsushi, Marsal, Sara, Kučinskiene, Zita Ausrele, Suvisaari, Jaana, Martin, Alicia R., Turetsky, Bruce I., Martorell, Lourdes, Palotie, Aarno, Mattheisen, Manuel, Baune, Bernhard T., Saka, Meram C., McCarley, Robert W., Giusti-Rodríguez, Paola, Riley, Brien P., Murphy, Kieran C., Gill, Michael, McDonald, Colm, Bruggeman, Richard, McGrath, John J., Sidorenko, Julia, Medeiros, Helena, Pantelis, Christos, Grove, Jakob, Campion, Dominique, Pato, Carlos N., Svrakic, Dragan M., Üçok, Alp, Glatt, Stephen J., Papadimitriou, George N., Khrunin, Andrey, Straub, Richard E., Parellada, Mara, Buckley, Peter F., Paunio, Tiina, Roth, Julian, Morgan, Vera A., Wildenauer, Dieter B., Ayub, Muhammad, Rothermundt, Matthias, Weiser, Mark, Rutten, Bart P. F., Saker-Delye, Safaa, Salomaa, Veikko, Børglum, Anders D., Sanjuán, Julio, van Winkel, Ruud, González Peñas, Javier, Yu, Xin, Kim, Sung-Wan, Santoro, Marcos Leite, Benner, Christian, Ikeda, Masashi, Morley, Christopher P., Zeng, Jian, Savitz, Adam, Schall, Ulrich, Scott, Rodney J., Voloudakis, Georgios, Yue, Weihua, Seidman, Larry J., Sharp, Sally Isabel, Alptekin, Köksal, Klovins, Janis, Amin, Farooq, Bertolino, Alessandro, Shi, Jianxin, Siever, Larry J., Atkinson, Elizabeth G., Buckner, Randy L., Holmans, Peter A., Rivera, Margarita, Sigurdsson, Engilbert, González-Pinto, Ana, Sim, Kang, Skarabis, Nora, Stroup, T Scott, Slominsky, Petr, Guillin, Olivier, Wang, Shi-Heng, So, Hon-Cheong, Quested, Digby, Sobell, Janet L., Braff, David, Zhang, Wen, Bybjerg-Grauholm, Jonas, Söderman, Erik, Rujescu, Dan, Chambert, Kimberley D., Stain, Helen J., Melle, Ingrid, Carr, Vaughan J, Pocklington, Andrew J., Steen, Nils Eiel, Harwood, Janet, Steixner-Kumar, Agnes A., Gopal, Srihari, Stögmann, Elisabeth, Veijola, Juha, Watanabe, Kyoko, Sham, Pak C., Cahn, Wiepke, Bramon, Elvira, Roussos, Panos, Waddington, John, Perkins, Diana O., Pato, Michele T., Walter, Henrik, Kondratiev, Nikolay, Waterreus, Anna, Al Eissa, Mariam, Bobes, Julio, Golimbet, Vera, Black, Donald W., Als, Thomas D., Bray, Nicholas J., Breen, Gerome, Buccola, Nancy G., Sanders, Alan R., Byerley, William F., Cervilla, Jorge A., Michie, Patricia T., Pfuhlmann, Bruno, Chen, Wei J., Hong, Kyung Sue, O'Neill, F Anthony, Terao, Chikashi, Green, Michael F., Cloninger, C. Robert, Crespo-Facorro, Benedicto, Donohoe, Gary, Gülöksüz, Sinan, Freedman, Robert, Albus, Margot, Hayward, Caroline, Pietiläinen, Olli, Herms, Stefan, Hultman, Christina M., Galletly, Cherrie, Gandal, Michael J., Hahn, Eric, Konte, Bettina, Castle, David, Gennarelli, Massimo, Milani, Lili, Hougaard, David M., Hwu, Hai-Gwo, Pulver, Ann E., Jablensky, Assen V., Molina, Esther, Qin, Shengying, McCarroll, Steven A., Moran, Jennifer L., Azevedo, Maria Helena, Gur, Rachel E., Kraft, Julia, Mors, Ole, Catts, Stanley V., Lazzeroni, Laura C., Mortensen, Preben B., Streit, Fabian, Kusumawardhani, Agung, Alexander, Madeline, Godard, Stephanie, Müller-Myhsok, Bertram, Milanova, Vihra, Neil, Amanda L., Cichon, Sven, Giannitelli, Marianna, Cheung, Eric F. C., Kubo, Michiaki, Schwab, Sibylle G., Collier, David A., Williams, Nigel M., Morris, Derek W., Corvin, Aiden, Pimm, Jonathan, Curtis, David, Haroutunian, Vahram, Keller, Matthew C., Vassos, Evangelos, Hyman, Steven E., Iwata, Nakao, Jönsson, Erik G., Kahn, René S., Chan, Raymond C. K., Kennedy, James L., Shi, Yongyong, Adams, Mark, Witt, Stephanie H., Khusnutdinova, Elza, Verhage, Matthijs, Xu, Shuhua, Wu, Yang, Kirov, George, Arolt, Volker, Knowles, James A., Moltó, Maria Dolores, Krebs, Marie-Odile, Hartmann, Annette M., Nestadt, Gerald, Wormley, Brandon K., Bass, Nicholas J., Laurent-Levinson, Claudine, Lee, Jimmy, Muntané, Gerard, Porteous, David, Kuzelova-Ptackova, Hana, Lencz, Todd, Subramaniam, Mythily, Levinson, Douglas F., Li, Qingqin S., Liu, Jianjun, Swerdlow, Neal R., Cairns, Murray J., Malhotra, Anil K., Malhotra, Dheeraj, Iyegbe, Conrad, Mondelli, Valeria, Kim, Minsoo, Arrojo, Manuel, Landi, Stefano, McIntosh, Andrew M., Petryshen, Tracey L., Radant, Allen D., Frei, Oleksandr, Mesholam-Gately, Raquelle I., McQuillin, Andrew, Sugar, Catherine A., Menezes, Paulo Rossi, St Clair, David, Meier, Sandra, Powell, John, Chaumette, Boris, Stefansson, Hreinn, Domenici, Enrico, Bonassi, Stefano, Stefánsson, Kári, Wu, Jing Qin, Tsuang, Ming T., Myin-Germeys, Inez, Pellegrino, Renata, Visscher, Peter M., Yang, Jian, Posthuma, Danielle, Andreassen, Ole A., Koopmans, Frank, Kendler, Kenneth S., Chong, Siow Ann, Gur, Ruben C., Ehrenreich, Hannelore, Owen, Michael J., Rietschel, Marcella, Gratten, Jacob, Wray, Naomi R., Hoffmann, Per, Daly, Mark J., Szatkiewicz, Jin P., Huang, Hailiang, Nenadić, Igor, Torretta, Silvia, Escott-Price, Valentina, Neale, Benjamin M., Begemann, Martin, Thibaut, Florence, Agerbo, Esben, Rampino, Antonio, Sullivan, Patrick F., Schulze, Thomas G., Ripke, Stephan, Walters, James T. R., O'Donovan, Michael C., Kučinskas, Vaidutis, Belliveau, Richard A., Bene, Judit, Oh, Sang-Yun, Ta, Thi Minh Tam, Greenwood, Tiffany A., Howrigan, Daniel P., Rapaport, Mark H., Benyamin, Beben, Mowry, Bryan J., Giegling, Ina, Strengman, Eric, Bergen, Sarah E., Silverman, Jeremy M., Blasi, Giuseppe, Cohen, David, Stone, William S., Xu, Zhida, Lee, Phil H., Consoli, Angèle, Kelly, Brian J.., Cordeiro, Quirino, Esko, Tõnu, and Costas, Javier
Abstract: Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.
Published: 2022

34. Accounting for age of onset and family history improves power in genome-wide association studies

Author: Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Grove, Jakob, Dreier, Julie W., Musliner, Katherine L., Bækvad-Hansen, Marie, Athanasiadis, Georgios, Schork, Andrew, Bybjerg-Grauholm, Jonas, Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Mors, Ole, Dalsgaard, Søren, Christensen, Jakob, Børglum, Anders D., Mortensen, Preben B., McGrath, John J., Privé, Florian, Vilhjálmsson, Bjarni J., Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Grove, Jakob, Dreier, Julie W., Musliner, Katherine L., Bækvad-Hansen, Marie, Athanasiadis, Georgios, Schork, Andrew, Bybjerg-Grauholm, Jonas, Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Mors, Ole, Dalsgaard, Søren, Christensen, Jakob, Børglum, Anders D., Mortensen, Preben B., McGrath, John J., Privé, Florian, and Vilhjálmsson, Bjarni J.
Abstract: Genome-wide association studies (GWASs) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age of onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here, we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), which jointly accounts for age of onset and sex as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields statistically significant power gains over LT-FH and large power gains over genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data and to mortality in the UK Biobank and found 20 genome-wide significant associations with LT-FH++, compared to ten for LT-FH and eight for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.
Published: 2022

35. Accounting for age of onset and family history improves power in genome-wide association studies

Author: Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Grove, Jakob, Dreier, Julie W., Musliner, Katherine L., Bækvad-Hansen, Marie, Athanasiadis, Georgios, Schork, Andrew, Bybjerg-Grauholm, Jonas, Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Mors, Ole, Dalsgaard, Søren, Christensen, Jakob, Børglum, Anders D., Mortensen, Preben B., McGrath, John J., Privé, Florian, Vilhjálmsson, Bjarni J., Pedersen, Emil M., Agerbo, Esben, Plana-Ripoll, Oleguer, Grove, Jakob, Dreier, Julie W., Musliner, Katherine L., Bækvad-Hansen, Marie, Athanasiadis, Georgios, Schork, Andrew, Bybjerg-Grauholm, Jonas, Hougaard, David M., Werge, Thomas, Nordentoft, Merete, Mors, Ole, Dalsgaard, Søren, Christensen, Jakob, Børglum, Anders D., Mortensen, Preben B., McGrath, John J., Privé, Florian, and Vilhjálmsson, Bjarni J.
Abstract: Genome-wide association studies (GWASs) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age of onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here, we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), which jointly accounts for age of onset and sex as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields statistically significant power gains over LT-FH and large power gains over genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data and to mortality in the UK Biobank and found 20 genome-wide significant associations with LT-FH++, compared to ten for LT-FH and eight for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.
Published: 2022

36. Comparing Copy Number Variations in a Danish Case Cohort of Individuals with Psychiatric Disorders

Author: Calle Sánchez, Xabier, Helenius, Dorte, Bybjerg-Grauholm, Jonas, Pedersen, Carsten, Hougaard, David M., Børglum, Anders D., Nordentoft, Merete, Mors, Ole, Mortensen, Preben B., Geschwind, Daniel H., Montalbano, Simone, Raznahan, Armin, Thompson, Wesley K., Ingason, Andrés, Werge, Thomas, Calle Sánchez, Xabier, Helenius, Dorte, Bybjerg-Grauholm, Jonas, Pedersen, Carsten, Hougaard, David M., Børglum, Anders D., Nordentoft, Merete, Mors, Ole, Mortensen, Preben B., Geschwind, Daniel H., Montalbano, Simone, Raznahan, Armin, Thompson, Wesley K., Ingason, Andrés, and Werge, Thomas
Abstract: Importance: Although the association between several recurrent genomic copy number variants (CNVs) and mental disorders has been studied for more than a decade, unbiased, population-based estimates of the prevalence, disease risks and trajectories, fertility, and mortality to contrast chromosomal abnormalities and advance precision health care are lacking. Objective: To generate unbiased, population-based estimates of prevalence, disease risks and trajectories, fertility, and mortality of CNVs implicated in neuropsychiatric disorders. Design, Setting, and Participants: In a population-based case-cohort study, using the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) 2012 database, individuals born between May 1, 1981, and December 31, 2005, and followed up until December 31, 2012, were analyzed. All individuals (n = 57377) with attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), schizophrenia (SCZ), autism spectrum disorder (ASD), or bipolar disorder (BPD) were included, as well as 30000 individuals randomly drawn from the database. Data analysis was conducted from July 1, 2017, to September 7, 2021. Exposures: Copy number variants at 6 genomic loci (1q21.1, 15q11.2, 15q13.3, 16p11.2, 17p12, and 17q12). Main Outcomes and Measures: Population-unbiased hazard ratio (HR) and survival estimates of CNV associations with the 5 ascertained psychiatric disorders, epilepsy, intellectual disability, selected somatic disorders, fertility, and mortality. Results: Participants' age ranged from 1 to 32 years (mean, 12.0 [IQR, 6.9] years) during follow-up, and 38 662 were male (52.3%). Copy number variants broadly associated with an increased risk of autism spectrum disorder and ADHD, whereas risk estimates of SCZ for most CNVs were lower than previously reported. Comparison with previous studies suggests that the lower risk estimates are associated with a higher CNV prevalence in the general population than in control
Published: 2022

37. Vagotomy and the risk of mental disorders:A nationwide population-based study

Author: Bunyoz, Artemis H, Christensen, Rune H B, Orlovska-Waast, Sonja, Nordentoft, Merete, Mortensen, Preben B, Petersen, Liselotte V, Benros, Michael E, Bunyoz, Artemis H, Christensen, Rune H B, Orlovska-Waast, Sonja, Nordentoft, Merete, Mortensen, Preben B, Petersen, Liselotte V, and Benros, Michael E
Abstract: OBJECTIVE: To investigate vagotomy, the severance of the vagus nerve, and its association with mental disorders, as gut-brain communication partly mediated by the vagus nerve have been suggested as a risk factor.METHODS: Nationwide population-based Danish register study of all individuals alive and living in Denmark during the study period 1977-2016 and who had a hospital contact for ulcer with or without vagotomy. Follow-up was until any diagnosis of mental disorders requiring hospital contact, emigration, death, or end of follow-up on December 31, 2016, whichever came first. Data were analysed using survival analysis and adjusted for sex, age, calendar year, ulcer type and Charlson comorbidity index score.RESULTS: During the study period, 113,086 individuals had a hospital contact for ulcer. Of these, 5,408 were exposed to vagotomy where 375 (6.9%) subsequently developed a mental disorder. Vagotomy overall was not associated with mental disorders (HR: 1.10; 95%CI: 0.99-1.23), compared to individuals with ulcer not exposed to vagotomy. However, truncal vagotomy was associated with an increased HR of 1.22 (95%CI: 1.06-1.41) for mental disorders, whereas highly selective vagotomy was not associated with mental disorders (HR: 0.98; 95%CI: 0.84-1.15). Truncal vagotomy was also associated with higher risk of mental disorders when compared to highly selective vagotomy (p=0.034).CONCLUSIONS: Overall, vagotomy did not increase the risk of mental disorders; however, truncal vagotomy specifically was associated with a small risk increase in mental disorders, whereas no association was found for highly selective vagotomy. Thus, the vagus nerve does not seem to have a major impact on the development of mental disorders.
Published: 2022

38. Genome-wide study of early and severe childhood asthma identifies interaction between CDHR3 and GSDMB

Author: Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andréanne, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., Bønnelykke, Klaus, Eliasen, Anders U., Pedersen, Casper Emil T., Rasmussen, Morten A., Wang, Ni, Soverini, Matteo, Fritz, Amelie, Stokholm, Jakob, Chawes, Bo L., Morin, Andréanne, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Söderhall, Cilla, Altman, Matthew C., Thysen, Anna H., McKennan, Chris G., Brix, Susanne, Gern, James E., Ober, Carole, Ahluwalia, Tarunveer S., Bisgaard, Hans, Pedersen, Anders G., and Bønnelykke, Klaus
Abstract: Background: Asthma with severe exacerbation is one of the most common causes of hospitalization among young children. Exacerbations are typically triggered by respiratory infections, but the host factors causing recurrent infections and exacerbations in some children are poorly understood. As a result, current treatment options and preventive measures are inadequate. Objective: We sought to identify genetic interaction associated with the development of childhood asthma. Methods: We performed an exhaustive search for pairwise interaction between genetic single nucleotide polymorphisms using 1204 cases of a specific phenotype of early childhood asthma with severe exacerbations in patients aged 2 to 6 years combined with 5328 nonasthmatic controls. Replication was attempted in 3 independent populations, and potential underlying immune mechanisms were investigated in the COPSAC2010 and COPSAC2000 birth cohorts. Results: We found evidence of interaction, including replication in independent populations, between the known childhood asthma loci CDHR3 and GSDMB. The effect of CDHR3 was dependent on the GSDMB genotype, and this interaction was more pronounced for severe and early onset of disease. Blood immune analyses suggested a mechanism related to increased IL-17A production after viral stimulation. Conclusions: We found evidence of interaction between CDHR3 and GSDMB in development of early childhood asthma, possibly related to increased IL-17A response to viral infections. This study demonstrates the importance of focusing on specific disease subtypes for understanding the genetic mechanisms of asthma.
Published: 2022

39. Polygenic Heterogeneity Across Obsessive-Compulsive Disorder Subgroups Defined by a Comorbid Diagnosis

Author: Strom, Nora I., Grove, Jakob, Meier, Sandra M., Bækvad-Hansen, Marie, Becker Nissen, Judith, Damm Als, Thomas, Halvorsen, Matthew, Nordentoft, Merete, Mortensen, Preben B., Hougaard, David M., Werge, Thomas, Mors, Ole, Børglum, Anders D., Crowley, James J., Bybjerg-Grauholm, Jonas, Mattheisen, Manuel, Strom, Nora I., Grove, Jakob, Meier, Sandra M., Bækvad-Hansen, Marie, Becker Nissen, Judith, Damm Als, Thomas, Halvorsen, Matthew, Nordentoft, Merete, Mortensen, Preben B., Hougaard, David M., Werge, Thomas, Mors, Ole, Børglum, Anders D., Crowley, James J., Bybjerg-Grauholm, Jonas, and Mattheisen, Manuel
Abstract: Among patients with obsessive-compulsive disorder (OCD), 65–85% manifest another psychiatric disorder concomitantly or at some other time point during their life. OCD is highly heritable, as are many of its comorbidities. A possible genetic heterogeneity of OCD in relation to its comorbid conditions, however, has not yet been exhaustively explored. We used a framework of different approaches to study the genetic relationship of OCD with three commonly observed comorbidities, namely major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). First, using publicly available summary statistics from large-scale genome-wide association studies, we compared genetic correlation patterns for OCD, MDD, ADHD, and ASD with 861 somatic and mental health phenotypes. Secondly, we examined how polygenic risk scores (PRS) of eight traits that showed heterogeneous correlation patterns with OCD, MDD, ADHD, and ASD partitioned across comorbid subgroups in OCD using independent unpublished data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). The comorbid subgroups comprised of patients with only OCD (N = 366), OCD and MDD (N = 1,052), OCD and ADHD (N = 443), OCD and ASD (N = 388), and OCD with more than 1 comorbidity (N = 429). We found that PRS of all traits but BMI were significantly associated with OCD across all subgroups (neuroticism: p = 1.19 × 10−32, bipolar disorder: p = 7.51 × 10−8, anorexia nervosa: p = 3.52 × 10−20, age at first birth: p = 9.38 × 10−5, educational attainment: p = 1.56 × 10−4, OCD: p = 1.87 × 10−6, insomnia: p = 2.61 × 10−5, BMI: p = 0.15). For age at first birth, educational attainment, and insomnia PRS estimates significantly differed across comorbid subgroups (p = 2.29 × 10−4, p = 1.63 × 10−4, and p = 0.045, respectively). Especially for anorexia nervosa, age a
Published: 2021

40. Pharmacogenetic genotype and phenotype frequencies in a large Danish population-based case-cohort sample

Author: Lunenburg, Carin A.T.C., Thirstrup, Janne P., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Hougaard, David M., Nordentoft, Merete, Werge, Thomas, Børglum, Anders D., Mors, Ole, Mortensen, Preben B., Gasse, Christiane, Lunenburg, Carin A.T.C., Thirstrup, Janne P., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Hougaard, David M., Nordentoft, Merete, Werge, Thomas, Børglum, Anders D., Mors, Ole, Mortensen, Preben B., and Gasse, Christiane
Abstract: Pharmacogenetics aims to improve clinical care by studying the relationship between genetic variation and variable drug response. Large population-based datasets could improve our current understanding of pharmacogenetics from selected study populations. We provide real-world pharmacogenetic frequencies of genotypes and (combined) phenotypes of a large Danish population-based case-cohort sample (iPSYCH2012; data of the Integrative Psychiatric Research consortium). The genotyped sample consists of 77,684 individuals, of which 51,464 individuals had diagnoses of severe mental disorders (SMD case-cohort) and 26,220 were individuals randomly selected from the Danish population (population cohort). Array-based genotype data imputed to 8.4 million genetic variants was searched for a selected pharmacogenetic panel of 42 clinically relevant variants and a CYP2D6 gene deletion and duplication. We identified 19 of 42 variants. Minor allele frequencies (MAFs) were consistent with previously reported MAFs, and did not differ between SMD cases and population cohorts. Almost all individuals carried at least one genetic variant (> 99.9%) and 87% carried three or more genetic variants. When genotypes were translated into phenotypes, also > 99.9% of individuals had at least one divergent phenotype (i.e. divergent from the common phenotypes considered normal, e.g. extensive metabolizer). The high number of identified individuals with at least one pharmacogenetic variant or divergent phenotype indicates the importance of pharmacogenetic panel-based genotyping. Combined CYP2C19-CYP2D6 phenotypes revealed that 72.7% of individuals had divergent phenotypes for one or both enzymes. As CYP2D6 and CYP2C19 have an important role in the metabolism of psychotropic drugs, this indicates the relevance of pharmacogenetic testing specifically in individuals using psychotropic drugs.
Published: 2021

41. Genetic disposition towards educational attainment and intelligence test performance predict voter turnout

Author: Aaroe, Lene, Appadurai, Vivek, Hansen, Kasper Møller, Schork, Andrew J., Werge, Thomas, Mors, Ole, Borglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Thompson, Wesley Kurt, Buil, Alfonso, Agerbo, Esben, Petersen, Michael Bang, Aaroe, Lene, Appadurai, Vivek, Hansen, Kasper Møller, Schork, Andrew J., Werge, Thomas, Mors, Ole, Borglum, Anders D., Hougaard, David M., Nordentoft, Merete, Mortensen, Preben B., Thompson, Wesley Kurt, Buil, Alfonso, Agerbo, Esben, and Petersen, Michael Bang
Abstract: The genetic variance that predicts educational attainment or intelligence test performance predicts individual-level voter turnout in a nationally representative sample and among people with psychiatric conditions, such as depression.Although the genetic influence on voter turnout is substantial (typically 40-50%), the underlying mechanisms remain unclear. Across the social sciences, research suggests that 'resources for politics' (as indexed notably by educational attainment and intelligence test performance) constitute a central cluster of factors that predict electoral participation. Educational attainment and intelligence test performance are heritable. This suggests that the genotypes that enhance these phenotypes could positively predict turnout. To test this, we conduct a genome-wide complex trait analysis of individual-level turnout. We use two samples from the Danish iPSYCH case-cohort study, including a nationally representative sample as well as a sample of individuals who are particularly vulnerable to political alienation due to psychiatric conditions (n = 13,884 and n = 33,062, respectively). Using validated individual-level turnout data from the administrative records at the polling station, genetic correlations and Mendelian randomization, we show that there is a substantial genetic overlap between voter turnout and both educational attainment and intelligence test performance.
Published: 2021

42. Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders - findings from a Danish population-based study:[Incl. Corrigendum]

Author: Liu, Xueping, Nudel, Ron, Thompson, Wesley K, Appadurai, Vivek, Schork, Andrew J, Buil, Alfonso, Rasmussen, Simon, Allesøe, Rosa L, Werge, Thomas, Mors, Ole, Børglum, Anders D, Hougaard, David M, Mortensen, Preben B, Nordentoft, Merete, Benros, Michael E, Liu, Xueping, Nudel, Ron, Thompson, Wesley K, Appadurai, Vivek, Schork, Andrew J, Buil, Alfonso, Rasmussen, Simon, Allesøe, Rosa L, Werge, Thomas, Mors, Ole, Børglum, Anders D, Hougaard, David M, Mortensen, Preben B, Nordentoft, Merete, and Benros, Michael E
Abstract: BACKGROUND: Previous studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders and investigated the genetic basis of overall autoimmune disease.METHODS: We used diagnostic information from patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on autoimmune and mental diseases. Genetic factors were investigated using GWAS and imputed HLA alleles in the iPSYCH cohort.RESULTS: Of 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1,383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two disease classes (P=2.67×10-7, OR=1.38, 95%CI=1.22-1.56), with an overall bidirectional association, wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR=1.13, 95%CI: 1.07-1.21, P=7.95×10-5) and vice versa (HR=1.27, 95%CI=1.16-1.39, P=8.77×10-15). Adding PRSs to these adjustment models did not have an impact on the associations. PRSs for autoimmune diseases were only slightly associated with increased risk of mental disorders (HR=1.01, 95%CI: 1.00-1.02, p=0.038), whereas PRSs for mental disorders were not associated with autoimmune diseases overall. Our GWAS highlighted 12 loci on chromosome 6 (minimum P=2.74 × 10-36, OR=1.80, 95% CI: 1.64-1.96), which were implicated in gene regulation through bioinformatic functional analyses, thereby identifying new candidate genes for overall autoimmune disease. Moreover, we observed 20 human leukocyte antigen (HLA) alleles strongly associated with overall autoimmune disease, but w
Published: 2021

43. Polygenic Heterogeneity Across Obsessive-Compulsive Disorder Subgroups Defined by a Comorbid Diagnosis

Author: Strom, Nora I., Grove, Jakob, Meier, Sandra M., Bækvad-Hansen, Marie, Becker Nissen, Judith, Damm Als, Thomas, Halvorsen, Matthew, Nordentoft, Merete, Mortensen, Preben B., Hougaard, David M., Werge, Thomas, Mors, Ole, Børglum, Anders D., Crowley, James J., Bybjerg-Grauholm, Jonas, Mattheisen, Manuel, Strom, Nora I., Grove, Jakob, Meier, Sandra M., Bækvad-Hansen, Marie, Becker Nissen, Judith, Damm Als, Thomas, Halvorsen, Matthew, Nordentoft, Merete, Mortensen, Preben B., Hougaard, David M., Werge, Thomas, Mors, Ole, Børglum, Anders D., Crowley, James J., Bybjerg-Grauholm, Jonas, and Mattheisen, Manuel
Abstract: Among patients with obsessive-compulsive disorder (OCD), 65–85% manifest another psychiatric disorder concomitantly or at some other time point during their life. OCD is highly heritable, as are many of its comorbidities. A possible genetic heterogeneity of OCD in relation to its comorbid conditions, however, has not yet been exhaustively explored. We used a framework of different approaches to study the genetic relationship of OCD with three commonly observed comorbidities, namely major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). First, using publicly available summary statistics from large-scale genome-wide association studies, we compared genetic correlation patterns for OCD, MDD, ADHD, and ASD with 861 somatic and mental health phenotypes. Secondly, we examined how polygenic risk scores (PRS) of eight traits that showed heterogeneous correlation patterns with OCD, MDD, ADHD, and ASD partitioned across comorbid subgroups in OCD using independent unpublished data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). The comorbid subgroups comprised of patients with only OCD (N = 366), OCD and MDD (N = 1,052), OCD and ADHD (N = 443), OCD and ASD (N = 388), and OCD with more than 1 comorbidity (N = 429). We found that PRS of all traits but BMI were significantly associated with OCD across all subgroups (neuroticism: p = 1.19 × 10−32, bipolar disorder: p = 7.51 × 10−8, anorexia nervosa: p = 3.52 × 10−20, age at first birth: p = 9.38 × 10−5, educational attainment: p = 1.56 × 10−4, OCD: p = 1.87 × 10−6, insomnia: p = 2.61 × 10−5, BMI: p = 0.15). For age at first birth, educational attainment, and insomnia PRS estimates significantly differed across comorbid subgroups (p = 2.29 × 10−4, p = 1.63 × 10−4, and p = 0.045, respectively). Especially for anorexia nervosa, age a
Published: 2021

44. Pharmacogenetic genotype and phenotype frequencies in a large Danish population-based case-cohort sample

Author: Lunenburg, Carin A.T.C., Thirstrup, Janne P., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Hougaard, David M., Nordentoft, Merete, Werge, Thomas, Børglum, Anders D., Mors, Ole, Mortensen, Preben B., Gasse, Christiane, Lunenburg, Carin A.T.C., Thirstrup, Janne P., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Hougaard, David M., Nordentoft, Merete, Werge, Thomas, Børglum, Anders D., Mors, Ole, Mortensen, Preben B., and Gasse, Christiane
Abstract: Pharmacogenetics aims to improve clinical care by studying the relationship between genetic variation and variable drug response. Large population-based datasets could improve our current understanding of pharmacogenetics from selected study populations. We provide real-world pharmacogenetic frequencies of genotypes and (combined) phenotypes of a large Danish population-based case-cohort sample (iPSYCH2012; data of the Integrative Psychiatric Research consortium). The genotyped sample consists of 77,684 individuals, of which 51,464 individuals had diagnoses of severe mental disorders (SMD case-cohort) and 26,220 were individuals randomly selected from the Danish population (population cohort). Array-based genotype data imputed to 8.4 million genetic variants was searched for a selected pharmacogenetic panel of 42 clinically relevant variants and a CYP2D6 gene deletion and duplication. We identified 19 of 42 variants. Minor allele frequencies (MAFs) were consistent with previously reported MAFs, and did not differ between SMD cases and population cohorts. Almost all individuals carried at least one genetic variant (> 99.9%) and 87% carried three or more genetic variants. When genotypes were translated into phenotypes, also > 99.9% of individuals had at least one divergent phenotype (i.e. divergent from the common phenotypes considered normal, e.g. extensive metabolizer). The high number of identified individuals with at least one pharmacogenetic variant or divergent phenotype indicates the importance of pharmacogenetic panel-based genotyping. Combined CYP2C19-CYP2D6 phenotypes revealed that 72.7% of individuals had divergent phenotypes for one or both enzymes. As CYP2D6 and CYP2C19 have an important role in the metabolism of psychotropic drugs, this indicates the relevance of pharmacogenetic testing specifically in individuals using psychotropic drugs.
Published: 2021

45. A large-scale genome-wide association study meta-analysis of cannabis use disorder.

Author: Johnson, Emma C, Johnson, Emma C, Demontis, Ditte, Thorgeirsson, Thorgeir E, Walters, Raymond K, Polimanti, Renato, Hatoum, Alexander S, Sanchez-Roige, Sandra, Paul, Sarah E, Wendt, Frank R, Clarke, Toni-Kim, Lai, Dongbing, Reginsson, Gunnar W, Zhou, Hang, He, June, Baranger, David AA, Gudbjartsson, Daniel F, Wedow, Robbee, Adkins, Daniel E, Adkins, Amy E, Alexander, Jeffry, Bacanu, Silviu-Alin, Bigdeli, Tim B, Boden, Joseph, Brown, Sandra A, Bucholz, Kathleen K, Bybjerg-Grauholm, Jonas, Corley, Robin P, Degenhardt, Louisa, Dick, Danielle M, Domingue, Benjamin W, Fox, Louis, Goate, Alison M, Gordon, Scott D, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Hickie, Ian B, Hougaard, David M, Krauter, Kenneth, Lind, Penelope A, McClintick, Jeanette N, McQueen, Matthew B, Meyers, Jacquelyn L, Montgomery, Grant W, Mors, Ole, Mortensen, Preben B, Nordentoft, Merete, Pearson, John F, Peterson, Roseann E, Reynolds, Maureen D, Rice, John P, Runarsdottir, Valgerdur, Saccone, Nancy L, Sherva, Richard, Silberg, Judy L, Tarter, Ralph E, Tyrfingsson, Thorarinn, Wall, Tamara L, Webb, Bradley T, Werge, Thomas, Wetherill, Leah, Wright, Margaret J, Zellers, Stephanie, Adams, Mark J, Bierut, Laura J, Boardman, Jason D, Copeland, William E, Farrer, Lindsay A, Foroud, Tatiana M, Gillespie, Nathan A, Grucza, Richard A, Harris, Kathleen Mullan, Heath, Andrew C, Hesselbrock, Victor, Hewitt, John K, Hopfer, Christian J, Horwood, John, Iacono, William G, Johnson, Eric O, Kendler, Kenneth S, Kennedy, Martin A, Kranzler, Henry R, Madden, Pamela AF, Maes, Hermine H, Maher, Brion S, Martin, Nicholas G, McGue, Matthew, McIntosh, Andrew M, Medland, Sarah E, Nelson, Elliot C, Porjesz, Bernice, Riley, Brien P, Stallings, Michael C, Vanyukov, Michael M, Vrieze, Scott, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Davis, Lea K, Bogdan, Ryan, Gelernter, Joel, Edenberg, Howard J, Johnson, Emma C, Johnson, Emma C, Demontis, Ditte, Thorgeirsson, Thorgeir E, Walters, Raymond K, Polimanti, Renato, Hatoum, Alexander S, Sanchez-Roige, Sandra, Paul, Sarah E, Wendt, Frank R, Clarke, Toni-Kim, Lai, Dongbing, Reginsson, Gunnar W, Zhou, Hang, He, June, Baranger, David AA, Gudbjartsson, Daniel F, Wedow, Robbee, Adkins, Daniel E, Adkins, Amy E, Alexander, Jeffry, Bacanu, Silviu-Alin, Bigdeli, Tim B, Boden, Joseph, Brown, Sandra A, Bucholz, Kathleen K, Bybjerg-Grauholm, Jonas, Corley, Robin P, Degenhardt, Louisa, Dick, Danielle M, Domingue, Benjamin W, Fox, Louis, Goate, Alison M, Gordon, Scott D, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Hickie, Ian B, Hougaard, David M, Krauter, Kenneth, Lind, Penelope A, McClintick, Jeanette N, McQueen, Matthew B, Meyers, Jacquelyn L, Montgomery, Grant W, Mors, Ole, Mortensen, Preben B, Nordentoft, Merete, Pearson, John F, Peterson, Roseann E, Reynolds, Maureen D, Rice, John P, Runarsdottir, Valgerdur, Saccone, Nancy L, Sherva, Richard, Silberg, Judy L, Tarter, Ralph E, Tyrfingsson, Thorarinn, Wall, Tamara L, Webb, Bradley T, Werge, Thomas, Wetherill, Leah, Wright, Margaret J, Zellers, Stephanie, Adams, Mark J, Bierut, Laura J, Boardman, Jason D, Copeland, William E, Farrer, Lindsay A, Foroud, Tatiana M, Gillespie, Nathan A, Grucza, Richard A, Harris, Kathleen Mullan, Heath, Andrew C, Hesselbrock, Victor, Hewitt, John K, Hopfer, Christian J, Horwood, John, Iacono, William G, Johnson, Eric O, Kendler, Kenneth S, Kennedy, Martin A, Kranzler, Henry R, Madden, Pamela AF, Maes, Hermine H, Maher, Brion S, Martin, Nicholas G, McGue, Matthew, McIntosh, Andrew M, Medland, Sarah E, Nelson, Elliot C, Porjesz, Bernice, Riley, Brien P, Stallings, Michael C, Vanyukov, Michael M, Vrieze, Scott, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Davis, Lea K, Bogdan, Ryan, Gelernter, Joel, and Edenberg, Howard J
Abstract: BackgroundVariation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.MethodsTo conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.FindingsWe identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.InterpretationThese findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between gen
Published: 2020

46. The genetic architecture of sporadic and multiple consecutive miscarriage.

Author: Laisk, Triin, Laisk, Triin, Soares, Ana Luiza G, Ferreira, Teresa, Painter, Jodie N, Censin, Jenny C, Laber, Samantha, Bacelis, Jonas, Chen, Chia-Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y, Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S, Yang, Ling, Becker, Christian M, Børglum, Anders D, Gordon, Scott D, Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M, Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A, Metspalu, Andres, Montgomery, Grant W, Morris, Andrew P, Mors, Ole, Mortensen, Preben B, Njølstad, Pål R, Nordentoft, Merete, Nyholt, Dale R, Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F, Jacobsson, Bo, Li, Liming, Martin, Nicholas G, Neale, Benjamin M, Nielsen, Rasmus, Walters, Robin G, Granne, Ingrid, Medland, Sarah E, Mägi, Reedik, Lawlor, Deborah A, Lindgren, Cecilia M, Laisk, Triin, Laisk, Triin, Soares, Ana Luiza G, Ferreira, Teresa, Painter, Jodie N, Censin, Jenny C, Laber, Samantha, Bacelis, Jonas, Chen, Chia-Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y, Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S, Yang, Ling, Becker, Christian M, Børglum, Anders D, Gordon, Scott D, Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M, Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A, Metspalu, Andres, Montgomery, Grant W, Morris, Andrew P, Mors, Ole, Mortensen, Preben B, Njølstad, Pål R, Nordentoft, Merete, Nyholt, Dale R, Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F, Jacobsson, Bo, Li, Liming, Martin, Nicholas G, Neale, Benjamin M, Nielsen, Rasmus, Walters, Robin G, Granne, Ingrid, Medland, Sarah E, Mägi, Reedik, Lawlor, Deborah A, and Lindgren, Cecilia M
Abstract: Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10-8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10-8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10-9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10-8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
Published: 2020

47. The genetic architecture of sporadic and multiple consecutive miscarriage

Author: Laisk, Triin, Soares, Ana Luiza G., Ferreira, Teresa, Painter, Jodie N., Censin, Jenny C., Laber, Samantha, Bacelis, Jonas, Chen, Chia Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y., Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S., Yang, Ling, Becker, Christian M., Børglum, Anders D., Gordon, Scott D., Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M., Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A., Metspalu, Andres, Montgomery, Grant W., Morris, Andrew P., Mors, Ole, Mortensen, Preben B., Njølstad, Pål R., Nordentoft, Merete, Nyholt, Dale R., Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F., Jacobsson, Bo, Li, Liming, Martin, Nicholas G., Neale, Benjamin M., Nielsen, Rasmus, Walters, Robin G., Granne, Ingrid, Medland, Sarah E., Mägi, Reedik, Lawlor, Deborah A., Lindgren, Cecilia M., Laisk, Triin, Soares, Ana Luiza G., Ferreira, Teresa, Painter, Jodie N., Censin, Jenny C., Laber, Samantha, Bacelis, Jonas, Chen, Chia Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y., Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S., Yang, Ling, Becker, Christian M., Børglum, Anders D., Gordon, Scott D., Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M., Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A., Metspalu, Andres, Montgomery, Grant W., Morris, Andrew P., Mors, Ole, Mortensen, Preben B., Njølstad, Pål R., Nordentoft, Merete, Nyholt, Dale R., Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F., Jacobsson, Bo, Li, Liming, Martin, Nicholas G., Neale, Benjamin M., Nielsen, Rasmus, Walters, Robin G., Granne, Ingrid, Medland, Sarah E., Mägi, Reedik, Lawlor, Deborah A., and Lindgren, Cecilia M.
Abstract: Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10−8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10−8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10−9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10−8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
Published: 2020

48. The genetic architecture of sporadic and multiple consecutive miscarriage.

Author: Laisk, Triin, Laisk, Triin, Soares, Ana Luiza G, Ferreira, Teresa, Painter, Jodie N, Censin, Jenny C, Laber, Samantha, Bacelis, Jonas, Chen, Chia-Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y, Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S, Yang, Ling, Becker, Christian M, Børglum, Anders D, Gordon, Scott D, Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M, Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A, Metspalu, Andres, Montgomery, Grant W, Morris, Andrew P, Mors, Ole, Mortensen, Preben B, Njølstad, Pål R, Nordentoft, Merete, Nyholt, Dale R, Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F, Jacobsson, Bo, Li, Liming, Martin, Nicholas G, Neale, Benjamin M, Nielsen, Rasmus, Walters, Robin G, Granne, Ingrid, Medland, Sarah E, Mägi, Reedik, Lawlor, Deborah A, Lindgren, Cecilia M, Laisk, Triin, Laisk, Triin, Soares, Ana Luiza G, Ferreira, Teresa, Painter, Jodie N, Censin, Jenny C, Laber, Samantha, Bacelis, Jonas, Chen, Chia-Yen, Lepamets, Maarja, Lin, Kuang, Liu, Siyang, Millwood, Iona Y, Ramu, Avinash, Southcombe, Jennifer, Andersen, Marianne S, Yang, Ling, Becker, Christian M, Børglum, Anders D, Gordon, Scott D, Bybjerg-Grauholm, Jonas, Helgeland, Øyvind, Hougaard, David M, Jin, Xin, Johansson, Stefan, Juodakis, Julius, Kartsonaki, Christiana, Kukushkina, Viktorija, Lind, Penelope A, Metspalu, Andres, Montgomery, Grant W, Morris, Andrew P, Mors, Ole, Mortensen, Preben B, Njølstad, Pål R, Nordentoft, Merete, Nyholt, Dale R, Lippincott, Margaret, Seminara, Stephanie, Salumets, Andres, Snieder, Harold, Zondervan, Krina, Werge, Thomas, Chen, Zhengming, Conrad, Donald F, Jacobsson, Bo, Li, Liming, Martin, Nicholas G, Neale, Benjamin M, Nielsen, Rasmus, Walters, Robin G, Granne, Ingrid, Medland, Sarah E, Mägi, Reedik, Lawlor, Deborah A, and Lindgren, Cecilia M
Abstract: Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10-8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10-8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10-9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10-8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
Published: 2020

49. A large-scale genome-wide association study meta-analysis of cannabis use disorder.

Author: Johnson, Emma C, Johnson, Emma C, Demontis, Ditte, Thorgeirsson, Thorgeir E, Walters, Raymond K, Polimanti, Renato, Hatoum, Alexander S, Sanchez-Roige, Sandra, Paul, Sarah E, Wendt, Frank R, Clarke, Toni-Kim, Lai, Dongbing, Reginsson, Gunnar W, Zhou, Hang, He, June, Baranger, David AA, Gudbjartsson, Daniel F, Wedow, Robbee, Adkins, Daniel E, Adkins, Amy E, Alexander, Jeffry, Bacanu, Silviu-Alin, Bigdeli, Tim B, Boden, Joseph, Brown, Sandra A, Bucholz, Kathleen K, Bybjerg-Grauholm, Jonas, Corley, Robin P, Degenhardt, Louisa, Dick, Danielle M, Domingue, Benjamin W, Fox, Louis, Goate, Alison M, Gordon, Scott D, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Hickie, Ian B, Hougaard, David M, Krauter, Kenneth, Lind, Penelope A, McClintick, Jeanette N, McQueen, Matthew B, Meyers, Jacquelyn L, Montgomery, Grant W, Mors, Ole, Mortensen, Preben B, Nordentoft, Merete, Pearson, John F, Peterson, Roseann E, Reynolds, Maureen D, Rice, John P, Runarsdottir, Valgerdur, Saccone, Nancy L, Sherva, Richard, Silberg, Judy L, Tarter, Ralph E, Tyrfingsson, Thorarinn, Wall, Tamara L, Webb, Bradley T, Werge, Thomas, Wetherill, Leah, Wright, Margaret J, Zellers, Stephanie, Adams, Mark J, Bierut, Laura J, Boardman, Jason D, Copeland, William E, Farrer, Lindsay A, Foroud, Tatiana M, Gillespie, Nathan A, Grucza, Richard A, Harris, Kathleen Mullan, Heath, Andrew C, Hesselbrock, Victor, Hewitt, John K, Hopfer, Christian J, Horwood, John, Iacono, William G, Johnson, Eric O, Kendler, Kenneth S, Kennedy, Martin A, Kranzler, Henry R, Madden, Pamela AF, Maes, Hermine H, Maher, Brion S, Martin, Nicholas G, McGue, Matthew, McIntosh, Andrew M, Medland, Sarah E, Nelson, Elliot C, Porjesz, Bernice, Riley, Brien P, Stallings, Michael C, Vanyukov, Michael M, Vrieze, Scott, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Davis, Lea K, Bogdan, Ryan, Gelernter, Joel, Edenberg, Howard J, Johnson, Emma C, Johnson, Emma C, Demontis, Ditte, Thorgeirsson, Thorgeir E, Walters, Raymond K, Polimanti, Renato, Hatoum, Alexander S, Sanchez-Roige, Sandra, Paul, Sarah E, Wendt, Frank R, Clarke, Toni-Kim, Lai, Dongbing, Reginsson, Gunnar W, Zhou, Hang, He, June, Baranger, David AA, Gudbjartsson, Daniel F, Wedow, Robbee, Adkins, Daniel E, Adkins, Amy E, Alexander, Jeffry, Bacanu, Silviu-Alin, Bigdeli, Tim B, Boden, Joseph, Brown, Sandra A, Bucholz, Kathleen K, Bybjerg-Grauholm, Jonas, Corley, Robin P, Degenhardt, Louisa, Dick, Danielle M, Domingue, Benjamin W, Fox, Louis, Goate, Alison M, Gordon, Scott D, Hack, Laura M, Hancock, Dana B, Hartz, Sarah M, Hickie, Ian B, Hougaard, David M, Krauter, Kenneth, Lind, Penelope A, McClintick, Jeanette N, McQueen, Matthew B, Meyers, Jacquelyn L, Montgomery, Grant W, Mors, Ole, Mortensen, Preben B, Nordentoft, Merete, Pearson, John F, Peterson, Roseann E, Reynolds, Maureen D, Rice, John P, Runarsdottir, Valgerdur, Saccone, Nancy L, Sherva, Richard, Silberg, Judy L, Tarter, Ralph E, Tyrfingsson, Thorarinn, Wall, Tamara L, Webb, Bradley T, Werge, Thomas, Wetherill, Leah, Wright, Margaret J, Zellers, Stephanie, Adams, Mark J, Bierut, Laura J, Boardman, Jason D, Copeland, William E, Farrer, Lindsay A, Foroud, Tatiana M, Gillespie, Nathan A, Grucza, Richard A, Harris, Kathleen Mullan, Heath, Andrew C, Hesselbrock, Victor, Hewitt, John K, Hopfer, Christian J, Horwood, John, Iacono, William G, Johnson, Eric O, Kendler, Kenneth S, Kennedy, Martin A, Kranzler, Henry R, Madden, Pamela AF, Maes, Hermine H, Maher, Brion S, Martin, Nicholas G, McGue, Matthew, McIntosh, Andrew M, Medland, Sarah E, Nelson, Elliot C, Porjesz, Bernice, Riley, Brien P, Stallings, Michael C, Vanyukov, Michael M, Vrieze, Scott, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Davis, Lea K, Bogdan, Ryan, Gelernter, Joel, and Edenberg, Howard J
Abstract: BackgroundVariation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.MethodsTo conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.FindingsWe identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.InterpretationThese findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between gen
Published: 2020

50. FUT2–ABO epistasis increases the risk of early childhood asthma and Streptococcus pneumoniae respiratory illnesses

Author: Ahluwalia, Tarunveer S., Eliasen, Anders U., Sevelsted, Astrid, Pedersen, Casper Emil T., Stokholm, Jakob, Chawes, Bo, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Sharma, Amitabh, Weiss, Scott T., Evans, Michael D., Jackson, Daniel J., Morin, Andreanne, Krogfelt, Karen A., Schjørring, Susanne, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Gern, James E., Lemanske, Robert F., Ober, Carole, Pedersen, Anders G., Bisgaard, Hans, Bønnelykke, Klaus, Ahluwalia, Tarunveer S., Eliasen, Anders U., Sevelsted, Astrid, Pedersen, Casper Emil T., Stokholm, Jakob, Chawes, Bo, Bork-Jensen, Jette, Grarup, Niels, Pedersen, Oluf, Hansen, Torben, Linneberg, Allan, Sharma, Amitabh, Weiss, Scott T., Evans, Michael D., Jackson, Daniel J., Morin, Andreanne, Krogfelt, Karen A., Schjørring, Susanne, Mortensen, Preben B., Hougaard, David M., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Mors, Ole, Nordentoft, Merete, Børglum, Anders D., Werge, Thomas, Agerbo, Esben, Gern, James E., Lemanske, Robert F., Ober, Carole, Pedersen, Anders G., Bisgaard, Hans, and Bønnelykke, Klaus
Abstract: Asthma with severe exacerbation is the most common cause of hospitalization among young children. We aim to increase the understanding of this clinically important disease entity through a genome-wide association study. The discovery analysis comprises 2866 children experiencing severe asthma exacerbation between ages 2 and 6 years, and 65,415 non-asthmatic controls, and we replicate findings in 918 children from the Copenhagen Prospective Studies on Asthma in Childhood (COPSAC) birth cohorts. We identify rs281379 near FUT2/MAMSTR on chromosome 19 as a novel risk locus (OR = 1.18 (95% CI = 1.11–1.25), Pdiscovery = 2.6 × 10−9) as well as a biologically plausible interaction between functional variants in FUT2 and ABO. We further discover and replicate a potential causal mechanism behind this interaction related to S. pneumoniae respiratory illnesses. These results suggest a novel mechanism of early childhood asthma and demonstrates the importance of phenotype-specificity for discovery of asthma genes and epistasis.
Published: 2020

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