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1. Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia.

Author: Witt, SH, Streit, F, Jungkunz, M, Frank, J, Awasthi, S, Reinbold, CS, Treutlein, J, Degenhardt, F, Forstner, AJ, Heilmann-Heimbach, S, Dietl, L, Schwarze, CE, Schendel, D, Strohmaier, J, Abdellaoui, A, Adolfsson, R, Air, TM, Akil, H, Alda, M, Alliey-Rodriguez, N, Andreassen, OA, Babadjanova, G, Bass, NJ, Bauer, M, Baune, BT, Bellivier, F, Bergen, S, Bethell, A, Biernacka, JM, Blackwood, DHR, Boks, MP, Boomsma, DI, Børglum, AD, Borrmann-Hassenbach, M, Brennan, P, Budde, M, Buttenschøn, HN, Byrne, EM, Cervantes, P, Clarke, T-K, Craddock, N, Cruceanu, C, Curtis, D, Czerski, PM, Dannlowski, U, Davis, T, de Geus, EJC, Di Florio, A, Djurovic, S, Domenici, E, Edenberg, HJ, Etain, B, Fischer, SB, Forty, L, Fraser, C, Frye, MA, Fullerton, JM, Gade, K, Gershon, ES, Giegling, I, Gordon, SD, Gordon-Smith, K, Grabe, HJ, Green, EK, Greenwood, TA, Grigoroiu-Serbanescu, M, Guzman-Parra, J, Hall, LS, Hamshere, M, Hauser, J, Hautzinger, M, Heilbronner, U, Herms, S, Hitturlingappa, S, Hoffmann, P, Holmans, P, Hottenga, J-J, Jamain, S, Jones, I, Jones, LA, Juréus, A, Kahn, RS, Kammerer-Ciernioch, J, Kirov, G, Kittel-Schneider, S, Kloiber, S, Knott, SV, Kogevinas, M, Landén, M, Leber, M, Leboyer, M, Li, QS, Lissowska, J, Lucae, S, Martin, NG, Mayoral-Cleries, F, McElroy, SL, McIntosh, AM, McKay, JD, and McQuillin, A
Subjects: Bipolar Disorders Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Humans, Genetic Predisposition to Disease, Case-Control Studies, Bipolar Disorder, Depressive Disorder, Major, Borderline Personality Disorder, Schizophrenia, Genotype, Multifactorial Inheritance, Adolescent, Adult, Aged, Middle Aged, Female, Male, Genome-Wide Association Study, Young Adult, Depressive Disorder, Major, Clinical Sciences, Public Health and Health Services, Psychology
Abstract: Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10-7) and PKP4 (P=8.67 × 10-7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10-3]), SCZ (rg=0.34 [P=4.37 × 10-5]) and MDD (rg=0.57 [P=1.04 × 10-3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.
Published: 2017

2. Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.

Author: Li, D, Pain, O, Chiara, F, Wong, WLE, Lo, CWH, Ripke, S, Cattaneo, A, Souery, D, Dernovsek, MZ, Henigsberg, N, Hauser, J, Lewis, G, Mors, O, Perroud, N, Rietschel, M, Uher, R, Maier, W, Baune, BT, Biernacka, JM, Bondolfi, G, Domschke, K, Kato, M, Liu, Y-L, Serretti, A, Tsai, S-J, Weinshilboum, R, GSRD Consortium, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, McIntosh, AM, Lewis, CM, Li, D, Pain, O, Chiara, F, Wong, WLE, Lo, CWH, Ripke, S, Cattaneo, A, Souery, D, Dernovsek, MZ, Henigsberg, N, Hauser, J, Lewis, G, Mors, O, Perroud, N, Rietschel, M, Uher, R, Maier, W, Baune, BT, Biernacka, JM, Bondolfi, G, Domschke, K, Kato, M, Liu, Y-L, Serretti, A, Tsai, S-J, Weinshilboum, R, GSRD Consortium, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, McIntosh, AM, and Lewis, CM
Abstract: Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression me
Published: 2024

3. Predictors of Functional Impairment in Bipolar Disorder: Results from 13 Cohorts from Seven Countries by The Global Bipolar Cohort Collaborative

Author: Burdick, KE, Millett, CE, Yocum, AK, Altimus, CM, Andreassen, OA, Aubin, V, Belzeaux, R, Berk, Michael, Biernacka, JM, Blumberg, HP, Cleare, AJ, Diaz‐Byrd, C, Dubertret, C, Etain, B, Eyler, L, Forester, BP, Fullerton, JM, Frye, MA, Gard, S, Godin, O, Haffen, E, Klaus, F, Lagerberg, TV, Leboyer, M, Martinez‐Aran, A, McElroy, S, Mitchell, PB, Olie, E, Olorunfemi, P, Passerieux, C, Peters, A, Pham, DL, Polosan, M, Potter, JR, Sajatovic, M, Samalin, L, Schwan, R, Shanahan, M, Solé, B, Strawbridge, R, Stuart, Amanda, Torres, I, Ueland, T, Vieta, E, Williams, Lana, Wrobel, Anna, Yatham, LN, Young, AH, Nierenberg, A, McInnis, MG, Burdick, KE, Millett, CE, Yocum, AK, Altimus, CM, Andreassen, OA, Aubin, V, Belzeaux, R, Berk, Michael, Biernacka, JM, Blumberg, HP, Cleare, AJ, Diaz‐Byrd, C, Dubertret, C, Etain, B, Eyler, L, Forester, BP, Fullerton, JM, Frye, MA, Gard, S, Godin, O, Haffen, E, Klaus, F, Lagerberg, TV, Leboyer, M, Martinez‐Aran, A, McElroy, S, Mitchell, PB, Olie, E, Olorunfemi, P, Passerieux, C, Peters, A, Pham, DL, Polosan, M, Potter, JR, Sajatovic, M, Samalin, L, Schwan, R, Shanahan, M, Solé, B, Strawbridge, R, Stuart, Amanda, Torres, I, Ueland, T, Vieta, E, Williams, Lana, Wrobel, Anna, Yatham, LN, Young, AH, Nierenberg, A, and McInnis, MG
Published: 2022

4. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Mullins, N, Kang, J, Campos, A, Coleman, JR, Edwards, AC, Galfalvy, H, Levey, DF, Lori, A, Shabalin, A, Starnawska, A, Su, M-H, Watson, HJ, Adams, M, Awasthi, S, Ganda, M, Hafferty, JD, Hishimoto, A, Kim, M, Okazaki, S, Otsuka, I, Ripke, S, Ware, EB, Bergen, AW, Berrettini, WH, Bohus, M, Brandt, H, Chang, X, Chen, WJ, Chen, H-C, Crawford, S, Crow, S, DiBlasi, E, Duriez, P, Fernandez-Aranda, F, Fichter, MM, Gallinger, S, Glatt, SJ, Gorwood, P, Guo, Y, Hakonarson, H, Halmi, KA, Hwu, H-G, Jain, S, Jamain, S, Jimenez-Murcia, S, Johnson, C, Kaplan, AS, Kaye, WH, Keel, PK, Kennedy, JL, Klump, KL, Li, D, Liao, S-C, Lieb, K, Lilenfeld, L, Liu, C-M, Magistretti, PJ, Marshall, CR, Mitchell, JE, Monson, ET, Myers, RM, Pinto, D, Powers, A, Ramoz, N, Roepke, S, Rozanov, V, Scherer, SW, Schmahl, C, Sokolowski, M, Strober, M, Thornton, LM, Treasure, J, Tsuang, MT, Witt, SH, Woodside, DB, Yilmaz, Z, Zillich, L, Adolfsson, R, Agartz, I, Air, TM, Alda, M, Alfredsson, L, Andreassen, OA, Anjorin, A, Appadurai, V, Artigas, MS, Van der Auwera, S, Azevedo, MH, Bass, N, Bau, CHD, Baune, BT, Bellivier, F, Berger, K, Biernacka, JM, Bigdeli, TB, Binder, EB, Boehnke, M, Boks, MP, Bosch, R, Braff, DL, Bryant, R, Budde, M, Byrne, EM, Cahn, W, Casas, M, Castelao, E, Cervilla, JA, Chaumette, B, Cichon, S, Corvin, A, Craddock, N, Craig, D, Degenhardt, F, Djurovic, S, Edenberg, HJ, Fanous, AH, Foo, JC, Forstner, AJ, Frye, M, Fullerton, JM, Gatt, JM, Gejman, P, Giegling, I, Grabe, HJ, Green, MJ, Grevet, EH, Grigoroiu-Serbanescu, M, Gutierrez, B, Guzman-Parra, J, Hamilton, SP, Hamshere, ML, Hartmann, A, Hauser, J, Heilmann-Heimbach, S, Hoffmann, P, Ising, M, Jones, I, Jones, LA, Jonsson, L, Kahn, RS, Kelsoe, JR, Kendler, KS, Kloiber, S, Koenen, KC, Kogevinas, M, Konte, B, Krebs, M-O, Lander, M, Lawrence, J, Leboyer, M, Lee, PH, Levinson, DF, Liao, C, Lissowska, J, Lucae, S, Mayoral, F, McElroy, SL, McGrath, P, McGuffin, P, McQuillin, A, Medland, SE, Mehta, D, Melle, I, Milaneschi, Y, Mitchell, PB, Molina, E, Morken, G, Mortensen, PB, Mueller-Myhsok, B, Nievergelt, C, Nimgaonkar, V, Noethen, MM, O'Donovan, MC, Ophoff, RA, Owen, MJ, Pato, C, Pato, MT, Penninx, BWJH, Pimm, J, Pistis, G, Potash, JB, Power, RA, Preisig, M, Quested, D, Ramos-Quiroga, JA, Reif, A, Ribases, M, Richarte, V, Rietschel, M, Rivera, M, Roberts, A, Roberts, G, Rouleau, GA, Rovaris, DL, Rujescu, D, Sanchez-Mora, C, Sanders, AR, Schofield, PR, Schulze, TG, Scott, LJ, Serretti, A, Shi, J, Shyn, S, Sirignano, L, Sklar, P, Smeland, OB, Smoller, JW, Sonuga-Barke, EJS, Spalletta, G, Strauss, JS, Swiatkowska, B, Trzaskowski, M, Turecki, G, Vilar-Ribo, L, Vincent, JB, Voelzke, H, Walters, JTR, Weickert, CS, Weickert, TW, Weissman, MM, Williams, LM, Wray, NR, Zai, CC, Ashley-Koch, AE, Beckham, JC, Hauser, ER, Hauser, MA, Kimbrel, NA, Lindquist, JH, McMahon, B, Oslin, DW, Qin, X, Agerbo, E, Borglum, AD, Breen, G, Erlangsen, A, Esko, T, Gelernter, J, Hougaard, DM, Kessler, RC, Kranzler, HR, Li, QS, Martin, NG, McIntosh, AM, Mors, O, Nordentoft, M, Olsen, CM, Porteous, D, Ursano, RJ, Wasserman, D, Werge, T, Whiteman, DC, Bulik, CM, Coon, H, Demontis, D, Docherty, AR, Kuo, P-H, Lewis, CM, Mann, JJ, Renteria, ME, Smith, DJ, Stahl, EA, Stein, MB, Streit, F, Willour, V, Ruderfer, DM, Mullins, N, Kang, J, Campos, A, Coleman, JR, Edwards, AC, Galfalvy, H, Levey, DF, Lori, A, Shabalin, A, Starnawska, A, Su, M-H, Watson, HJ, Adams, M, Awasthi, S, Ganda, M, Hafferty, JD, Hishimoto, A, Kim, M, Okazaki, S, Otsuka, I, Ripke, S, Ware, EB, Bergen, AW, Berrettini, WH, Bohus, M, Brandt, H, Chang, X, Chen, WJ, Chen, H-C, Crawford, S, Crow, S, DiBlasi, E, Duriez, P, Fernandez-Aranda, F, Fichter, MM, Gallinger, S, Glatt, SJ, Gorwood, P, Guo, Y, Hakonarson, H, Halmi, KA, Hwu, H-G, Jain, S, Jamain, S, Jimenez-Murcia, S, Johnson, C, Kaplan, AS, Kaye, WH, Keel, PK, Kennedy, JL, Klump, KL, Li, D, Liao, S-C, Lieb, K, Lilenfeld, L, Liu, C-M, Magistretti, PJ, Marshall, CR, Mitchell, JE, Monson, ET, Myers, RM, Pinto, D, Powers, A, Ramoz, N, Roepke, S, Rozanov, V, Scherer, SW, Schmahl, C, Sokolowski, M, Strober, M, Thornton, LM, Treasure, J, Tsuang, MT, Witt, SH, Woodside, DB, Yilmaz, Z, Zillich, L, Adolfsson, R, Agartz, I, Air, TM, Alda, M, Alfredsson, L, Andreassen, OA, Anjorin, A, Appadurai, V, Artigas, MS, Van der Auwera, S, Azevedo, MH, Bass, N, Bau, CHD, Baune, BT, Bellivier, F, Berger, K, Biernacka, JM, Bigdeli, TB, Binder, EB, Boehnke, M, Boks, MP, Bosch, R, Braff, DL, Bryant, R, Budde, M, Byrne, EM, Cahn, W, Casas, M, Castelao, E, Cervilla, JA, Chaumette, B, Cichon, S, Corvin, A, Craddock, N, Craig, D, Degenhardt, F, Djurovic, S, Edenberg, HJ, Fanous, AH, Foo, JC, Forstner, AJ, Frye, M, Fullerton, JM, Gatt, JM, Gejman, P, Giegling, I, Grabe, HJ, Green, MJ, Grevet, EH, Grigoroiu-Serbanescu, M, Gutierrez, B, Guzman-Parra, J, Hamilton, SP, Hamshere, ML, Hartmann, A, Hauser, J, Heilmann-Heimbach, S, Hoffmann, P, Ising, M, Jones, I, Jones, LA, Jonsson, L, Kahn, RS, Kelsoe, JR, Kendler, KS, Kloiber, S, Koenen, KC, Kogevinas, M, Konte, B, Krebs, M-O, Lander, M, Lawrence, J, Leboyer, M, Lee, PH, Levinson, DF, Liao, C, Lissowska, J, Lucae, S, Mayoral, F, McElroy, SL, McGrath, P, McGuffin, P, McQuillin, A, Medland, SE, Mehta, D, Melle, I, Milaneschi, Y, Mitchell, PB, Molina, E, Morken, G, Mortensen, PB, Mueller-Myhsok, B, Nievergelt, C, Nimgaonkar, V, Noethen, MM, O'Donovan, MC, Ophoff, RA, Owen, MJ, Pato, C, Pato, MT, Penninx, BWJH, Pimm, J, Pistis, G, Potash, JB, Power, RA, Preisig, M, Quested, D, Ramos-Quiroga, JA, Reif, A, Ribases, M, Richarte, V, Rietschel, M, Rivera, M, Roberts, A, Roberts, G, Rouleau, GA, Rovaris, DL, Rujescu, D, Sanchez-Mora, C, Sanders, AR, Schofield, PR, Schulze, TG, Scott, LJ, Serretti, A, Shi, J, Shyn, S, Sirignano, L, Sklar, P, Smeland, OB, Smoller, JW, Sonuga-Barke, EJS, Spalletta, G, Strauss, JS, Swiatkowska, B, Trzaskowski, M, Turecki, G, Vilar-Ribo, L, Vincent, JB, Voelzke, H, Walters, JTR, Weickert, CS, Weickert, TW, Weissman, MM, Williams, LM, Wray, NR, Zai, CC, Ashley-Koch, AE, Beckham, JC, Hauser, ER, Hauser, MA, Kimbrel, NA, Lindquist, JH, McMahon, B, Oslin, DW, Qin, X, Agerbo, E, Borglum, AD, Breen, G, Erlangsen, A, Esko, T, Gelernter, J, Hougaard, DM, Kessler, RC, Kranzler, HR, Li, QS, Martin, NG, McIntosh, AM, Mors, O, Nordentoft, M, Olsen, CM, Porteous, D, Ursano, RJ, Wasserman, D, Werge, T, Whiteman, DC, Bulik, CM, Coon, H, Demontis, D, Docherty, AR, Kuo, P-H, Lewis, CM, Mann, JJ, Renteria, ME, Smith, DJ, Stahl, EA, Stein, MB, Streit, F, Willour, V, and Ruderfer, DM
Abstract: BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.
Published: 2022

5. Identifying the Common Genetic Basis of Antidepressant Response.

Author: Pain, O, Hodgson, K, Trubetskoy, V, Ripke, S, Marshe, VS, Adams, MJ, Byrne, EM, Campos, AI, Carrillo-Roa, T, Cattaneo, A, Als, TD, Souery, D, Dernovsek, MZ, Fabbri, C, Hayward, C, Henigsberg, N, Hauser, J, Kennedy, JL, Lenze, EJ, Lewis, G, Müller, DJ, Martin, NG, Mulsant, BH, Mors, O, Perroud, N, Porteous, DJ, Rentería, ME, Reynolds, CF, Rietschel, M, Uher, R, Wigmore, EM, Maier, W, Wray, NR, Aitchison, KJ, Arolt, V, Baune, BT, Biernacka, JM, Bondolfi, G, Domschke, K, Kato, M, Li, QS, Liu, Y-L, Serretti, A, Tsai, S-J, Turecki, G, Weinshilboum, R, GSRD Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, McIntosh, AM, Lewis, CM, Pain, O, Hodgson, K, Trubetskoy, V, Ripke, S, Marshe, VS, Adams, MJ, Byrne, EM, Campos, AI, Carrillo-Roa, T, Cattaneo, A, Als, TD, Souery, D, Dernovsek, MZ, Fabbri, C, Hayward, C, Henigsberg, N, Hauser, J, Kennedy, JL, Lenze, EJ, Lewis, G, Müller, DJ, Martin, NG, Mulsant, BH, Mors, O, Perroud, N, Porteous, DJ, Rentería, ME, Reynolds, CF, Rietschel, M, Uher, R, Wigmore, EM, Maier, W, Wray, NR, Aitchison, KJ, Arolt, V, Baune, BT, Biernacka, JM, Bondolfi, G, Domschke, K, Kato, M, Li, QS, Liu, Y-L, Serretti, A, Tsai, S-J, Turecki, G, Weinshilboum, R, GSRD Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, McIntosh, AM, and Lewis, CM
Abstract: BACKGROUND: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. METHODS: Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. RESULTS: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. CONCLUSIONS: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap sc
Published: 2022

6. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients (vol 12, 278, 2022)

Author: Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Konig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nothen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, Baune, BT, Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Konig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nothen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, and Baune, BT
Published: 2022

7. HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders

Author: Le Clerc, S, Lombardi, L, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Millischer, V, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O’Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Pisanu, C, Squassina, A, Le Clerc, S, Lombardi, L, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Millischer, V, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O’Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Pisanu, C, and Squassina, A
Abstract: Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10−3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
Published: 2021

8. Gearing up for the future: Exploring facilitators and barriers to inform clinical trial design in frontotemporal lobar degeneration

Author: Banga, YB, Banga, YB, Lai, Y, Kim, P, Boeve, BF, Boxer, AL, Rosen, HJ, Forsberg, LK, Heuer, HW, Brushaber, D, Appleby, B, Biernacka, JM, Bordelon, YM, Botha, H, Bozoki, AC, Brannelly, P, Dickerson, BC, Dickinson, S, Dickson, DW, Domoto-Reilly, K, Faber, K, Fagan, AM, Fields, JA, Fishman, A, Foroud, TM, Galasko, DR, Gavrilova, RH, Gendron, TF, Geschwind, DH, Ghoshal, N, Goldman, J, Graff-Radford, J, Graff-Radford, NR, Grant, I, Grossman, M, Hsiung, GYR, Huang, EJ, Huey, ED, Irwin, DJ, Jones, DT, Kantarci, K, Karydas, AM, Kaufer, D, Knopman, DS, Kramer, JH, Kremers, WK, Kornak, J, Kukull, WA, Lagone, E, Leger, GC, Litvan, I, Ljubenkov, PA, Lucente, DE, Mackenzie, IR, Manoochehri, M, Masdeu, JC, McGinnis, S, Mendez, MF, Miller, BL, Miyagawa, T, Nelson, KM, Onyike, CU, Pantelyat, A, Pascual, B, Pearlman, R, Petrucelli, L, Pottier, CP, Rademakers, R, Ramos, EM, Rankin, KP, Rascovsky, K, Rexach, JE, Ritter, A, Roberson, ED, Rojas, JC, Sabbagh, MN, Salmon, DP, Savica, R, Seeley, WW, Staffaroni, AM, Syrjanen, JA, Tartaglia, MC, Tatton, N, Taylor, JC, Toga, AW, Weintraub, S, Wheaton, D, Wong, B, Wszolek, Z, Banga, YB, Banga, YB, Lai, Y, Kim, P, Boeve, BF, Boxer, AL, Rosen, HJ, Forsberg, LK, Heuer, HW, Brushaber, D, Appleby, B, Biernacka, JM, Bordelon, YM, Botha, H, Bozoki, AC, Brannelly, P, Dickerson, BC, Dickinson, S, Dickson, DW, Domoto-Reilly, K, Faber, K, Fagan, AM, Fields, JA, Fishman, A, Foroud, TM, Galasko, DR, Gavrilova, RH, Gendron, TF, Geschwind, DH, Ghoshal, N, Goldman, J, Graff-Radford, J, Graff-Radford, NR, Grant, I, Grossman, M, Hsiung, GYR, Huang, EJ, Huey, ED, Irwin, DJ, Jones, DT, Kantarci, K, Karydas, AM, Kaufer, D, Knopman, DS, Kramer, JH, Kremers, WK, Kornak, J, Kukull, WA, Lagone, E, Leger, GC, Litvan, I, Ljubenkov, PA, Lucente, DE, Mackenzie, IR, Manoochehri, M, Masdeu, JC, McGinnis, S, Mendez, MF, Miller, BL, Miyagawa, T, Nelson, KM, Onyike, CU, Pantelyat, A, Pascual, B, Pearlman, R, Petrucelli, L, Pottier, CP, Rademakers, R, Ramos, EM, Rankin, KP, Rascovsky, K, Rexach, JE, Ritter, A, Roberson, ED, Rojas, JC, Sabbagh, MN, Salmon, DP, Savica, R, Seeley, WW, Staffaroni, AM, Syrjanen, JA, Tartaglia, MC, Tatton, N, Taylor, JC, Toga, AW, Weintraub, S, Wheaton, D, Wong, B, and Wszolek, Z
Abstract: BACKGROUND: Frontotemporal lobar degeneration (FTLD) refers to a group of neurodegenerative conditions, affecting the frontal and/or temporal lobes. Ongoing research has provided insight into developing clinical trials for FTLD and key clinical measures such as structural MRI. To inform clinical trial design and optimize participation, it is imperative to explore facilitators and barriers for potential candidates. OBJECTIVE: The objective of this study is to explore facilitators and barriers to participating in future clinical trials for FTLD. METHODS: Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) are observational studies focused on characterizing FTLD syndromes in preparation for clinical trials. The 584 participants enrolled across 18 research sites in the United States and Canada completed a survey assessing interest in clinical trial participation. RESULTS: 29% of respondents self-reported as patients (63±10 years), 26% self-reported as caregivers answering on behalf of patients (65±10 years), and 45% self-reported as healthy but at risk for FTLD (48±14 years). Travel reimbursement was the most common factor reported to positively influence participation (≧66%), with the healthy but at risk group showing the strongest endorsement (83%). Cost and time involved in travel were possible barriers for about half of the patients (48%) and healthy but at risk respondents (53%). The respondents value receiving feedback on the study findings (≧80%) and being informed of their individual disease progression (≧75%). Particularly, keeping participation confidential was very important for the healthy but at risk group (62%). In regard to research assessments, most participants demonstrated a high interest in physical and neurological exams at a research center (≧87%) whereas only half were interested in doing more invasive procedures such as the lumbar puncture
Published: 2021

9. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author: Mullins, N, Forstner, AJ, O'Connell, KS, Coombes, B, Coleman, JR, Qiao, Z, Als, TD, Bigdeli, TB, Borte, S, Bryois, J, Charney, AW, Drange, OK, Gandal, MJ, Hagenaars, SP, Ikeda, M, Kamitaki, N, Kim, M, Krebs, K, Panagiotaropoulou, G, Schilder, BM, Sloofman, LG, Steinberg, S, Trubetskoy, V, Winsvold, BS, Won, H-H, Abramova, L, Adorjan, K, Agerbo, E, Al Eissa, M, Albani, D, Alliey-Rodriguez, N, Anjorin, A, Antilla, V, Antoniou, A, Awasthi, S, Baek, JH, Baekvad-Hansen, M, Bass, N, Bauer, M, Beins, EC, Bergen, SE, Birner, A, Pedersen, CB, Boen, E, Boks, MP, Bosch, R, Brum, M, Brumpton, BM, Brunkhorst-Kanaan, N, Budde, M, Bybjerg-Grauholm, J, Byerley, W, Cairns, M, Casas, M, Cervantes, P, Clarke, T-K, Cruceanu, C, Cuellar-Barboza, A, Cunningham, J, Curtis, D, Czerski, PM, Dale, AM, Dalkner, N, David, FS, Degenhardt, F, Djurovic, S, Dobbyn, AL, Douzenis, A, Elvsashagen, T, Escott-Price, V, Ferrier, IN, Fiorentino, A, Foroud, TM, Forty, L, Frank, J, Frei, O, Freimer, NB, Frisen, L, Gade, K, Garnham, J, Gelernter, J, Pedersen, MG, Gizer, IR, Gordon, SD, Gordon-Smith, K, Greenwood, TA, Grove, J, Guzman-Parra, J, Ha, K, Haraldsson, M, Hautzinger, M, Heilbronner, U, Hellgren, D, Herms, S, Hoffmann, P, Holmans, PA, Huckins, L, Jamain, S, Johnson, JS, Kalman, JL, Kamatani, Y, Kennedy, JL, Kittel-Schneider, S, Knowles, JA, Kogevinas, M, Koromina, M, Kranz, TM, Kranzler, HR, Kubo, M, Kupka, R, Kushner, SA, Lavebratt, C, Lawrence, J, Leber, M, Lee, H-J, Lee, PH, Levy, SE, Lewis, C, Liao, C, Lucae, S, Lundberg, M, MacIntyre, DJ, Maier, W, Maihofer, A, Malaspina, D, Maratou, E, Martinsson, L, Mattheisen, M, McCarroll, SA, McGregor, NW, McGuffin, P, McKay, JD, Medeiros, H, Medland, SE, Millischer, V, Montgomery, GW, Moran, JL, Morris, DW, Muhleisen, TW, O'Brien, N, O'Donovan, C, Loohuis, LMO, Oruc, L, Papiol, S, Pardinas, AF, Perry, A, Pfennig, A, Porichi, E, Potash, JB, Quested, D, Raj, T, Rapaport, MH, DePaulo, JR, Regeer, EJ, Rice, JP, Rivas, F, Rivera, M, Roth, J, Roussos, P, Ruderfer, DM, Sanchez-Mora, C, Schulte, EC, Senner, F, Sharp, S, Shilling, PD, Sigurdsson, E, Sirignano, L, Slaney, C, Smeland, OB, Sobell, JL, Hansen, CS, Artigas, MS, Spijker, AT, Stein, DJ, Strauss, JS, Swiatkowska, B, Terao, C, Thorgeirsson, TE, Toma, C, Tooney, P, Tsermpini, E-E, Vawter, MP, Vedder, H, Walters, JTR, Witt, SH, Xi, S, Xu, W, Yang, JMK, Young, AH, Young, H, Zandi, PP, Zhou, H, Zillich, L, Adolfsson, R, Agartz, I, Alda, M, Alfredsson, L, Babadjanova, G, Backlund, L, Baune, BT, Bellivier, F, Bengesser, S, Berrettini, WH, Blackwood, DHR, Boehnke, M, Borglum, AD, Breen, G, Carr, VJ, Catts, S, Corvin, A, Craddock, N, Dannlowski, U, Dikeos, D, Esko, T, Etain, B, Ferentinos, P, Frye, M, Fullerton, JM, Gawlik, M, Gershon, ES, Goes, F, Green, MJ, Grigoroiu-Serbanescu, M, Hauser, J, Henskens, F, Hillert, J, Hong, KS, Hougaard, DM, Hultman, CM, Hveem, K, Iwata, N, Jablensky, A, Jones, I, Jones, LA, Kahn, RS, Kelsoe, JR, Kirov, G, Landen, M, Leboyer, M, Lewis, CM, Li, QS, Lissowska, J, Lochner, C, Loughland, C, Martin, NG, Mathews, CA, Mayoral, F, McElroy, SL, McIntosh, AM, McMahon, FJ, Melle, I, Michie, P, Milani, L, Mitchell, PB, Morken, G, Mors, O, Mortensen, PB, Mowry, B, Muller-Myhsok, B, Myers, RM, Neale, BM, Nievergelt, CM, Nordentoft, M, Nothen, MM, ODonovan, MC, Oedegaard, KJ, Olsson, T, Owen, MJ, Paciga, SA, Pantelis, C, Pato, C, Pato, MT, Patrinos, GP, Perlis, RH, Posthuma, D, Ramos-Quiroga, JA, Reif, A, Reininghaus, EZ, Ribases, M, Rietschel, M, Ripke, S, Rouleau, GA, Saito, T, Schall, U, Schalling, M, Schofield, PR, Schulze, TG, Scott, LJ, Scott, RJ, Serretti, A, Weickert, CS, Smoller, JW, Stefansson, H, Stefansson, K, Stordal, E, Streit, F, Sullivan, PF, Turecki, G, Vaaler, AE, Vieta, E, Vincent, JB, Waldman, ID, Weickert, TW, Werge, T, Wray, NR, Zwart, J, Biernacka, JM, Nurnberger, J, Cichon, S, Edenberg, HJ, Stahl, EA, McQuillin, A, Di Florio, A, Ophoff, RA, Andreassen, OA, Mullins, N, Forstner, AJ, O'Connell, KS, Coombes, B, Coleman, JR, Qiao, Z, Als, TD, Bigdeli, TB, Borte, S, Bryois, J, Charney, AW, Drange, OK, Gandal, MJ, Hagenaars, SP, Ikeda, M, Kamitaki, N, Kim, M, Krebs, K, Panagiotaropoulou, G, Schilder, BM, Sloofman, LG, Steinberg, S, Trubetskoy, V, Winsvold, BS, Won, H-H, Abramova, L, Adorjan, K, Agerbo, E, Al Eissa, M, Albani, D, Alliey-Rodriguez, N, Anjorin, A, Antilla, V, Antoniou, A, Awasthi, S, Baek, JH, Baekvad-Hansen, M, Bass, N, Bauer, M, Beins, EC, Bergen, SE, Birner, A, Pedersen, CB, Boen, E, Boks, MP, Bosch, R, Brum, M, Brumpton, BM, Brunkhorst-Kanaan, N, Budde, M, Bybjerg-Grauholm, J, Byerley, W, Cairns, M, Casas, M, Cervantes, P, Clarke, T-K, Cruceanu, C, Cuellar-Barboza, A, Cunningham, J, Curtis, D, Czerski, PM, Dale, AM, Dalkner, N, David, FS, Degenhardt, F, Djurovic, S, Dobbyn, AL, Douzenis, A, Elvsashagen, T, Escott-Price, V, Ferrier, IN, Fiorentino, A, Foroud, TM, Forty, L, Frank, J, Frei, O, Freimer, NB, Frisen, L, Gade, K, Garnham, J, Gelernter, J, Pedersen, MG, Gizer, IR, Gordon, SD, Gordon-Smith, K, Greenwood, TA, Grove, J, Guzman-Parra, J, Ha, K, Haraldsson, M, Hautzinger, M, Heilbronner, U, Hellgren, D, Herms, S, Hoffmann, P, Holmans, PA, Huckins, L, Jamain, S, Johnson, JS, Kalman, JL, Kamatani, Y, Kennedy, JL, Kittel-Schneider, S, Knowles, JA, Kogevinas, M, Koromina, M, Kranz, TM, Kranzler, HR, Kubo, M, Kupka, R, Kushner, SA, Lavebratt, C, Lawrence, J, Leber, M, Lee, H-J, Lee, PH, Levy, SE, Lewis, C, Liao, C, Lucae, S, Lundberg, M, MacIntyre, DJ, Maier, W, Maihofer, A, Malaspina, D, Maratou, E, Martinsson, L, Mattheisen, M, McCarroll, SA, McGregor, NW, McGuffin, P, McKay, JD, Medeiros, H, Medland, SE, Millischer, V, Montgomery, GW, Moran, JL, Morris, DW, Muhleisen, TW, O'Brien, N, O'Donovan, C, Loohuis, LMO, Oruc, L, Papiol, S, Pardinas, AF, Perry, A, Pfennig, A, Porichi, E, Potash, JB, Quested, D, Raj, T, Rapaport, MH, DePaulo, JR, Regeer, EJ, Rice, JP, Rivas, F, Rivera, M, Roth, J, Roussos, P, Ruderfer, DM, Sanchez-Mora, C, Schulte, EC, Senner, F, Sharp, S, Shilling, PD, Sigurdsson, E, Sirignano, L, Slaney, C, Smeland, OB, Sobell, JL, Hansen, CS, Artigas, MS, Spijker, AT, Stein, DJ, Strauss, JS, Swiatkowska, B, Terao, C, Thorgeirsson, TE, Toma, C, Tooney, P, Tsermpini, E-E, Vawter, MP, Vedder, H, Walters, JTR, Witt, SH, Xi, S, Xu, W, Yang, JMK, Young, AH, Young, H, Zandi, PP, Zhou, H, Zillich, L, Adolfsson, R, Agartz, I, Alda, M, Alfredsson, L, Babadjanova, G, Backlund, L, Baune, BT, Bellivier, F, Bengesser, S, Berrettini, WH, Blackwood, DHR, Boehnke, M, Borglum, AD, Breen, G, Carr, VJ, Catts, S, Corvin, A, Craddock, N, Dannlowski, U, Dikeos, D, Esko, T, Etain, B, Ferentinos, P, Frye, M, Fullerton, JM, Gawlik, M, Gershon, ES, Goes, F, Green, MJ, Grigoroiu-Serbanescu, M, Hauser, J, Henskens, F, Hillert, J, Hong, KS, Hougaard, DM, Hultman, CM, Hveem, K, Iwata, N, Jablensky, A, Jones, I, Jones, LA, Kahn, RS, Kelsoe, JR, Kirov, G, Landen, M, Leboyer, M, Lewis, CM, Li, QS, Lissowska, J, Lochner, C, Loughland, C, Martin, NG, Mathews, CA, Mayoral, F, McElroy, SL, McIntosh, AM, McMahon, FJ, Melle, I, Michie, P, Milani, L, Mitchell, PB, Morken, G, Mors, O, Mortensen, PB, Mowry, B, Muller-Myhsok, B, Myers, RM, Neale, BM, Nievergelt, CM, Nordentoft, M, Nothen, MM, ODonovan, MC, Oedegaard, KJ, Olsson, T, Owen, MJ, Paciga, SA, Pantelis, C, Pato, C, Pato, MT, Patrinos, GP, Perlis, RH, Posthuma, D, Ramos-Quiroga, JA, Reif, A, Reininghaus, EZ, Ribases, M, Rietschel, M, Ripke, S, Rouleau, GA, Saito, T, Schall, U, Schalling, M, Schofield, PR, Schulze, TG, Scott, LJ, Scott, RJ, Serretti, A, Weickert, CS, Smoller, JW, Stefansson, H, Stefansson, K, Stordal, E, Streit, F, Sullivan, PF, Turecki, G, Vaaler, AE, Vieta, E, Vincent, JB, Waldman, ID, Weickert, TW, Werge, T, Wray, NR, Zwart, J, Biernacka, JM, Nurnberger, J, Cichon, S, Edenberg, HJ, Stahl, EA, McQuillin, A, Di Florio, A, Ophoff, RA, and Andreassen, OA
Abstract: Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
Published: 2021

10. Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Author: Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, Y-H, Shekhtman, T, AdIi, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, K, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Etain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Vieta, E, Veeh, J, Witt, SH, Wright, A, Zandi, PP, Mitchell, PB, Bauer, M, Alda, M, Rietschel, M, McMahon, FJ, Schulze, TG, Baune, BT, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Cearns, M, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, Y-H, Shekhtman, T, AdIi, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, K, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Etain, B, Jamain, S, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Osby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Vieta, E, Veeh, J, Witt, SH, Wright, A, Zandi, PP, Mitchell, PB, Bauer, M, Alda, M, Rietschel, M, McMahon, FJ, Schulze, TG, and Baune, BT
Abstract: Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findin
Published: 2021

11. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author: Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Oesby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, Baune, BT, Schubert, KO, Thalamuthu, A, Amare, AT, Frank, J, Streit, F, Adl, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, J-M, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Marie-Claire, C, Cearns, M, Cervantes, P, Chen, H-C, Chillotti, C, Cichon, S, Clark, SR, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Etain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Heilbronner, U, Herms, S, Hoffmann, P, Hou, L, Hsu, Y-H, Jamain, S, Jimenez, E, Kahn, J-P, Kassem, L, Kuo, P-H, Kato, T, Kelsoe, J, Kittel-Schneider, S, Ferensztajn-Rochowiak, E, Koenig, B, Kusumi, I, Laje, G, Landen, M, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Noethen, MM, Novak, T, O'Donovan, C, Ozaki, N, Oesby, U, Papiol, S, Pfennig, A, Pisanu, C, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Tekola-Ayele, F, Tortorella, A, Turecki, G, Veeh, J, Vieta, E, Witt, SH, Roberts, G, Zandi, PP, Alda, M, Bauer, M, McMahon, FJ, Mitchell, PB, Schulze, TG, Rietschel, M, and Baune, BT
Abstract: Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
Published: 2021

12. Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies

Author: Munn-Chernoff, MA, Johnson, EC, Chou, YL, Coleman, JRI, Thornton, LM, Walters, RK, Yilmaz, Z, Baker, JH, Hübel, C, Gordon, S, Medland, SE, Watson, HJ, Gaspar, HA, Bryois, J, Hinney, A, Leppä, VM, Mattheisen, M, Ripke, S, Yao, S, Giusti-Rodríguez, P, Hanscombe, KB, Adan, RAH, Alfredsson, L, Ando, T, Andreassen, OA, Berrettini, WH, Boehm, I, Boni, C, Boraska Perica, V, Buehren, K, Burghardt, R, Cassina, M, Cichon, S, Clementi, M, Cone, RD, Courtet, P, Crow, S, Crowley, JJ, Danner, UN, Davis, OS, Zwaan, M, Dedoussis, G, Degortes, D, DeSocio, JE, Dick, DM, Dikeos, D, Dina, C, Dmitrzak-Weglarz, M, Docampo, E, Duncan, LE, Egberts, K, Ehrlich, S, Escaramís, G, Esko, T, Estivill, X, Farmer, A, Favaro, A, Fernández-Aranda, F, Fichter, MM, Fischer, K, Föcker, M, Foretova, L, Forstner, AJ, Forzan, M, Franklin, CS, Gallinger, S, Giegling, I, Giuranna, J, Gonidakis, F, Gorwood, P, Gratacos Mayora, M, Guillaume, S, Guo, Y, Hakonarson, H, Hatzikotoulas, K, Hauser, J, Hebebrand, J, Helder, SG, Herms, S, Herpertz-Dahlmann, B, Herzog, W, Huckins, LM, Hudson, JI, Imgart, H, Inoko, H, Janout, V, Jiménez-Murcia, S, Julià, A, Kalsi, G, Kaminská, D, Karhunen, L, Karwautz, A, Kas, MJH, Kennedy, JL, Keski-Rahkonen, A, Kiezebrink, K, Kim, YR, Klump, KL, Knudsen, GP, La Via, MC, Le Hellard, S, Levitan, RD, Li, D, Lilenfeld, L, Lin, BD, Lissowska, J, Luykx, J, Magistretti, PJ, Maj, M, Mannik, K, Marsal, S, Marshall, CR, Mattingsdal, M, McDevitt, S, McGuffin, P, Metspalu, A, Meulenbelt, I, Micali, N, Mitchell, K, Monteleone, A M, Monteleone, P, Nacmias, B, Navratilova, M, Ntalla, I, O'Toole, JK, Ophoff, Roel, Padyukov, L, Palotie, A, Pantel, J, Papezova, H, Pinto, D, Rabionet, R, Raevuori, A, Ramoz, N, Reichborn-Kjennerud, T, Ricca, V, Ripatti, S, Ritschel, F, Roberts, M, Rotondo, A, Rujescu, D, Rybakowski, F, Santonastaso, P, Scherag, A, Scherer, SW, Schmidt, U, Schork, NJ, Schosser, A, Seitz, J, Slachtova, L, Slagboom, PE, Slof-Op't Landt, MCT, Slopien, A, Sorbi, S, ?wi?tkowska, B, Szatkiewicz, JP, Tachmazidou, I, Tenconi, E, Tortorella, A, Tozzi, F, Treasure, J, Tsitsika, A, Tyszkiewicz-Nwafor, M, Tziouvas, K, van Elburg, AA, van Furth, EF, Wagner, G, Walton, E, Widen, E, Zeggini, E, Zerwas, S, Zipfel, S, Bergen, AW, Boden, JM, Brandt, H, Crawford, S, Halmi, KA, Horwood, LJ, Johnson, C, Kaplan, AS, Kaye, WH, Mitchell, J E, Olsen, CM, Pearson, JF, Pedersen, NL, Strober, M, Werge, T, Whiteman, DC, Woodside, DB, Grove, J, Henders, AK, Larsen, J T, Parker, R, Petersen, LV, Jordan, J, Kennedy, MA, Birgegård, A, Lichtenstein, P, Norring, C, Landén, M, Mortensen, PB, Polimanti, R, McClintick, JN, Adkins, AE, Aliev, F, Bacanu, SA, Batzler, A, Bertelsen, S, Biernacka, JM, Bigdeli, TB, Chen, L S, Clarke, TK, Degenhardt, F, Docherty, AR, Edwards, AC, Foo, JC, Fox, L, Frank, J, Hack, LM, Hartmann, AM, Hartz, SM, Heilmann-Heimbach, S, Hodgkinson, C, Hoffmann, P, Hottenga, JJ, Konte, B, Lahti, J, Lahti-Pulkkinen, M, Lai, D, Ligthart, L, Loukola, A, Maher, BS, Mbarek, H, McIntosh, AM, McQueen, MB, Meyers, JL, Milaneschi, Y, Palviainen, T, Peterson, RE, Ryu, E, Saccone, N L, Salvatore, JE, Sanchez-Roige, S, Schwandt, M, Sherva, R, Streit, F, Strohmaier, J, Thomas, N, Wang, JCY, Webb, BT, Wedow, R, Wetherill, L, Wills, AG, Zhou, H, Boardman, JD, Chen, D, Choi, D S, Copeland, WE, Culverhouse, RC, Dahmen, N, Degenhardt, L, Domingue, BW, Frye, MA, Gäebel, W, Hayward, C, Ising, M, Keyes, M, Kiefer, F, Koller, G, Kramer, J (John), Kuperman, S, Lucae, S, Lynskey, MT, Maier, W, Mann, K, Männistö, S, Müller-Myhsok, B, Murray, AD, Nurnberger, JI, Preuss, U, Räikkönen, K, Reynolds, MD, Ridinger, M, Scherbaum, N, Schuckit, MA, Soyka, M, Treutlein, J, Witt, SH, Wodarz, N, Zill, P, Adkins, DE, Boomsma, DI, Bierut, LJ, Brown, S, Bucholz, KK, Costello, EJ, Wit, HJ, Diazgranados, N, Eriksson, JG, Farrer, LA, Foroud, TM, Gillespie, NA, Goate, AM, Goldman, D, Grucza, RA, Hancock, DB, Harris, KM, Hesselbrock, V, Hewitt, JK, Hopfer, CJ, Iacono, WG, Johnson, E O, Karpyak, VM, Kendler, KS, Kranzler, HR, Krauter, K, Lind, PA, McGue, M, MacKillop, J, Madden, PA, Maes, HH, Magnusson, PKE, Nelson, EC, Nöthen, MM, Palmer, AA, Penninx, BWJH, Porjesz, B, Rice, JP, Rietschel, M, Riley, BP, Rose, RJ, Shen, PH, Silberg, J, Stallings, MC, Tarter, RE, Vanyukov, MM, Vrieze, S, Wall, TL, Whitfield, JB, Zhao, H, Neale, BM, Wade, TD, Heath, AC, Montgomery, GW, Martin, NG, Sullivan, PF, Kaprio, J, Breen, G, Gelernter, J, Edenberg, HJ, Bulik, CM, Agrawal, A, Munn-Chernoff, MA, Johnson, EC, Chou, YL, Coleman, JRI, Thornton, LM, Walters, RK, Yilmaz, Z, Baker, JH, Hübel, C, Gordon, S, Medland, SE, Watson, HJ, Gaspar, HA, Bryois, J, Hinney, A, Leppä, VM, Mattheisen, M, Ripke, S, Yao, S, Giusti-Rodríguez, P, Hanscombe, KB, Adan, RAH, Alfredsson, L, Ando, T, Andreassen, OA, Berrettini, WH, Boehm, I, Boni, C, Boraska Perica, V, Buehren, K, Burghardt, R, Cassina, M, Cichon, S, Clementi, M, Cone, RD, Courtet, P, Crow, S, Crowley, JJ, Danner, UN, Davis, OS, Zwaan, M, Dedoussis, G, Degortes, D, DeSocio, JE, Dick, DM, Dikeos, D, Dina, C, Dmitrzak-Weglarz, M, Docampo, E, Duncan, LE, Egberts, K, Ehrlich, S, Escaramís, G, Esko, T, Estivill, X, Farmer, A, Favaro, A, Fernández-Aranda, F, Fichter, MM, Fischer, K, Föcker, M, Foretova, L, Forstner, AJ, Forzan, M, Franklin, CS, Gallinger, S, Giegling, I, Giuranna, J, Gonidakis, F, Gorwood, P, Gratacos Mayora, M, Guillaume, S, Guo, Y, Hakonarson, H, Hatzikotoulas, K, Hauser, J, Hebebrand, J, Helder, SG, Herms, S, Herpertz-Dahlmann, B, Herzog, W, Huckins, LM, Hudson, JI, Imgart, H, Inoko, H, Janout, V, Jiménez-Murcia, S, Julià, A, Kalsi, G, Kaminská, D, Karhunen, L, Karwautz, A, Kas, MJH, Kennedy, JL, Keski-Rahkonen, A, Kiezebrink, K, Kim, YR, Klump, KL, Knudsen, GP, La Via, MC, Le Hellard, S, Levitan, RD, Li, D, Lilenfeld, L, Lin, BD, Lissowska, J, Luykx, J, Magistretti, PJ, Maj, M, Mannik, K, Marsal, S, Marshall, CR, Mattingsdal, M, McDevitt, S, McGuffin, P, Metspalu, A, Meulenbelt, I, Micali, N, Mitchell, K, Monteleone, A M, Monteleone, P, Nacmias, B, Navratilova, M, Ntalla, I, O'Toole, JK, Ophoff, Roel, Padyukov, L, Palotie, A, Pantel, J, Papezova, H, Pinto, D, Rabionet, R, Raevuori, A, Ramoz, N, Reichborn-Kjennerud, T, Ricca, V, Ripatti, S, Ritschel, F, Roberts, M, Rotondo, A, Rujescu, D, Rybakowski, F, Santonastaso, P, Scherag, A, Scherer, SW, Schmidt, U, Schork, NJ, Schosser, A, Seitz, J, Slachtova, L, Slagboom, PE, Slof-Op't Landt, MCT, Slopien, A, Sorbi, S, ?wi?tkowska, B, Szatkiewicz, JP, Tachmazidou, I, Tenconi, E, Tortorella, A, Tozzi, F, Treasure, J, Tsitsika, A, Tyszkiewicz-Nwafor, M, Tziouvas, K, van Elburg, AA, van Furth, EF, Wagner, G, Walton, E, Widen, E, Zeggini, E, Zerwas, S, Zipfel, S, Bergen, AW, Boden, JM, Brandt, H, Crawford, S, Halmi, KA, Horwood, LJ, Johnson, C, Kaplan, AS, Kaye, WH, Mitchell, J E, Olsen, CM, Pearson, JF, Pedersen, NL, Strober, M, Werge, T, Whiteman, DC, Woodside, DB, Grove, J, Henders, AK, Larsen, J T, Parker, R, Petersen, LV, Jordan, J, Kennedy, MA, Birgegård, A, Lichtenstein, P, Norring, C, Landén, M, Mortensen, PB, Polimanti, R, McClintick, JN, Adkins, AE, Aliev, F, Bacanu, SA, Batzler, A, Bertelsen, S, Biernacka, JM, Bigdeli, TB, Chen, L S, Clarke, TK, Degenhardt, F, Docherty, AR, Edwards, AC, Foo, JC, Fox, L, Frank, J, Hack, LM, Hartmann, AM, Hartz, SM, Heilmann-Heimbach, S, Hodgkinson, C, Hoffmann, P, Hottenga, JJ, Konte, B, Lahti, J, Lahti-Pulkkinen, M, Lai, D, Ligthart, L, Loukola, A, Maher, BS, Mbarek, H, McIntosh, AM, McQueen, MB, Meyers, JL, Milaneschi, Y, Palviainen, T, Peterson, RE, Ryu, E, Saccone, N L, Salvatore, JE, Sanchez-Roige, S, Schwandt, M, Sherva, R, Streit, F, Strohmaier, J, Thomas, N, Wang, JCY, Webb, BT, Wedow, R, Wetherill, L, Wills, AG, Zhou, H, Boardman, JD, Chen, D, Choi, D S, Copeland, WE, Culverhouse, RC, Dahmen, N, Degenhardt, L, Domingue, BW, Frye, MA, Gäebel, W, Hayward, C, Ising, M, Keyes, M, Kiefer, F, Koller, G, Kramer, J (John), Kuperman, S, Lucae, S, Lynskey, MT, Maier, W, Mann, K, Männistö, S, Müller-Myhsok, B, Murray, AD, Nurnberger, JI, Preuss, U, Räikkönen, K, Reynolds, MD, Ridinger, M, Scherbaum, N, Schuckit, MA, Soyka, M, Treutlein, J, Witt, SH, Wodarz, N, Zill, P, Adkins, DE, Boomsma, DI, Bierut, LJ, Brown, S, Bucholz, KK, Costello, EJ, Wit, HJ, Diazgranados, N, Eriksson, JG, Farrer, LA, Foroud, TM, Gillespie, NA, Goate, AM, Goldman, D, Grucza, RA, Hancock, DB, Harris, KM, Hesselbrock, V, Hewitt, JK, Hopfer, CJ, Iacono, WG, Johnson, E O, Karpyak, VM, Kendler, KS, Kranzler, HR, Krauter, K, Lind, PA, McGue, M, MacKillop, J, Madden, PA, Maes, HH, Magnusson, PKE, Nelson, EC, Nöthen, MM, Palmer, AA, Penninx, BWJH, Porjesz, B, Rice, JP, Rietschel, M, Riley, BP, Rose, RJ, Shen, PH, Silberg, J, Stallings, MC, Tarter, RE, Vanyukov, MM, Vrieze, S, Wall, TL, Whitfield, JB, Zhao, H, Neale, BM, Wade, TD, Heath, AC, Montgomery, GW, Martin, NG, Sullivan, PF, Kaprio, J, Breen, G, Gelernter, J, Edenberg, HJ, Bulik, CM, and Agrawal, A
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotyp
Published: 2021

13. Investigating polygenic burden in age at disease onset in bipolar disorder: Findings from an international multicentric study

Author: Kalman, JL, Papiol, S, Forstner, AJ, Heilbronner, U, Degenhardt, F, Strohmaier, J, Adli, M, Adorjan, K, Akula, N, Alda, M, Anderson-Schmidt, H, Andlauer, TFM, Anghelescu, IG, Ardau, R, Arias, B, Arolt, V, Aubry, JM, Backlund, L, Bartholdi, K, Bauer, M, Baune, BT, Becker, T, Bellivier, F, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Budde, M, Cervantes, P, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Comes, AL, Cruceanu, C, Czerski, PM, Dannlowski, U, Dayer, A, Del Zompo, M, DePaulo, JR, Dietrich, DE, Étain, B, Ethofer, T, Falkai, P, Fallgatter, A, Figge, C, Flatau, L, Folkerts, H, Frisen, L, Frye, MA, Fullerton, JM, Gade, K, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Gryaznova, A, Hake, M, Hauser, J, Herms, S, Hoffmann, P, Hou, L, Jäger, M, Jamain, S, Jiménez, E, Juckel, G, Kahn, JP, Kassem, L, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, Klohn-Sagatholislam, F, Koller, M, König, B, Konrad, C, Lackner, N, Laje, G, Landén, M, Lang, FU, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McMahon, FJ, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Nieratschker, V, Nievergelt, CM, Novák, T, Ösby, U, Pfennig, A, Potash, JB, Kalman, JL, Papiol, S, Forstner, AJ, Heilbronner, U, Degenhardt, F, Strohmaier, J, Adli, M, Adorjan, K, Akula, N, Alda, M, Anderson-Schmidt, H, Andlauer, TFM, Anghelescu, IG, Ardau, R, Arias, B, Arolt, V, Aubry, JM, Backlund, L, Bartholdi, K, Bauer, M, Baune, BT, Becker, T, Bellivier, F, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Budde, M, Cervantes, P, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Comes, AL, Cruceanu, C, Czerski, PM, Dannlowski, U, Dayer, A, Del Zompo, M, DePaulo, JR, Dietrich, DE, Étain, B, Ethofer, T, Falkai, P, Fallgatter, A, Figge, C, Flatau, L, Folkerts, H, Frisen, L, Frye, MA, Fullerton, JM, Gade, K, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Gryaznova, A, Hake, M, Hauser, J, Herms, S, Hoffmann, P, Hou, L, Jäger, M, Jamain, S, Jiménez, E, Juckel, G, Kahn, JP, Kassem, L, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, Klohn-Sagatholislam, F, Koller, M, König, B, Konrad, C, Lackner, N, Laje, G, Landén, M, Lang, FU, Lavebratt, C, Leboyer, M, Leckband, SG, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McMahon, FJ, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Nieratschker, V, Nievergelt, CM, Novák, T, Ösby, U, Pfennig, A, and Potash, JB
Abstract: Objectives: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. Methods: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. Results: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. Conclusions: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.
Published: 2019

14. Analysis of the influence of microRNAs in lithium response in bipolar disorder

Author: Reinbold, CS, Forstner, AJ, Hecker, J, Fullerton, JM, Hoffmann, P, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Marie-Claire, C, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dayer, A, Étain, B, Falkai, P, Frisén, L, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, MacQueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, TJ, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, SH, Wright, AJ, Trevor Young, L, Zandi, PP, Potash, JB, DePaulo, JR, Bauer, M, Reininghaus, E, Novák, T, Aubry, JM, Reinbold, CS, Forstner, AJ, Hecker, J, Fullerton, JM, Hoffmann, P, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Marie-Claire, C, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dayer, A, Étain, B, Falkai, P, Frisén, L, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, MacQueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, TJ, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, SH, Wright, AJ, Trevor Young, L, Zandi, PP, Potash, JB, DePaulo, JR, Bauer, M, Reininghaus, E, Novák, T, and Aubry, JM
Abstract: Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs
Published: 2018

15. Association of polygenic score for schizophrenia and HLA antigen and inflammation genes with response to lithium in bipolar affective disorder: A genome-wide association study

Author: Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O'Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, Turecki, G, Amare, AT, Schubert, KO, Hou, L, Clark, SR, Papiol, S, Heilbronner, U, Degenhardt, F, Tekola-Ayele, F, Hsu, YH, Shekhtman, T, Adli, M, Akula, N, Akiyama, K, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Bhattacharjee, AK, Bellivier, F, Benabarre, A, Bengesser, S, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Cervantes, P, Chen, HC, Chillotti, C, Cichon, S, Cruceanu, C, Czerski, PM, Dalkner, N, Dayer, A, Del Zompo, M, DePaulo, JR, Étain, B, Falkai, P, Forstner, AJ, Frisen, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grigoroiu-Serbanescu, M, Grof, P, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kuo, PH, Kato, T, Kelsoe, J, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Tortorella, A, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, S, Colom, F, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Novák, T, O'Donovan, C, Ozaki, N, Ösby, U, Pfennig, A, Potash, JB, Reif, A, Reininghaus, E, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schweizer, BW, Severino, G, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Squassina, A, Stamm, T, Stopkova, P, Maj, M, and Turecki, G
Abstract: IMPORTANCE Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). OBJECTIVES To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. DESIGN, SETTING, AND PARTICIPANTS A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013.Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. MAIN OUTCOMES AND MEASURES Treatment response to lithiumwas defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. RESULTS Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 ? 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95%
Published: 2018

16. Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Author: Ruderfer, DM, Ripke, S, McQuillin, A, Boocock, J, Stahl, EA, Pavlides, JMW, Mullins, N, Charney, AW, Ori, APS, Loohuis, LMO, Domenici, E, Di Florio, A, Papiol, S, Kalman, JL, Trubetskoy, V, Adolfsson, R, Agartz, I, Agerbo, E, Akil, H, Albani, D, Albus, M, Alda, M, Alexander, M, Alliey-Rodriguez, N, Als, TD, Amin, F, Anjorin, A, Arranz, MJ, Awasthi, S, Bacanu, SA, Badner, JA, Baekvad-Hansen, M, Bakker, S, Band, G, Barchas, JD, Barroso, I, Bass, N, Bauer, M, Baune, BT, Begemann, M, Bellenguez, C, Belliveau, RA, Bellivier, F, Bender, S, Bene, J, Bergen, SE, Berrettini, WH, Bevilacqua, E, Biernacka, JM, Bigdeli, TB, Black, DW, Blackburn, H, Blackwell, JM, Blackwood, DHR, Pedersen, CB, Boehnke, M, Boks, M, Borglum, AD, Bramon, E, Breen, G, Brown, MA, Bruggeman, R, Buccola, NG, Buckner, RL, Budde, M, Bulik-Sullivan, B, Bumpstead, SJ, Bunney, W, Burmeister, M, Buxbaum, JD, Bybjerg-Grauholm, J, Byerley, W, Cahn, W, Cai, G, Cairns, MJ, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Casas, JP, Casas, M, Catts, SV, Cervantes, P, Chambert, KD, Chan, RCK, Chen, EYH, Chen, RYL, Cheng, W, Cheung, EFC, Chong, SA, Clarke, TK, Cloninger, CR, Cohen, D, Cohen, N, Coleman, JRI, Collier, DA, Cormican, P, Coryell, W, Craddock, N, Craig, DW, Ruderfer, DM, Ripke, S, McQuillin, A, Boocock, J, Stahl, EA, Pavlides, JMW, Mullins, N, Charney, AW, Ori, APS, Loohuis, LMO, Domenici, E, Di Florio, A, Papiol, S, Kalman, JL, Trubetskoy, V, Adolfsson, R, Agartz, I, Agerbo, E, Akil, H, Albani, D, Albus, M, Alda, M, Alexander, M, Alliey-Rodriguez, N, Als, TD, Amin, F, Anjorin, A, Arranz, MJ, Awasthi, S, Bacanu, SA, Badner, JA, Baekvad-Hansen, M, Bakker, S, Band, G, Barchas, JD, Barroso, I, Bass, N, Bauer, M, Baune, BT, Begemann, M, Bellenguez, C, Belliveau, RA, Bellivier, F, Bender, S, Bene, J, Bergen, SE, Berrettini, WH, Bevilacqua, E, Biernacka, JM, Bigdeli, TB, Black, DW, Blackburn, H, Blackwell, JM, Blackwood, DHR, Pedersen, CB, Boehnke, M, Boks, M, Borglum, AD, Bramon, E, Breen, G, Brown, MA, Bruggeman, R, Buccola, NG, Buckner, RL, Budde, M, Bulik-Sullivan, B, Bumpstead, SJ, Bunney, W, Burmeister, M, Buxbaum, JD, Bybjerg-Grauholm, J, Byerley, W, Cahn, W, Cai, G, Cairns, MJ, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Casas, JP, Casas, M, Catts, SV, Cervantes, P, Chambert, KD, Chan, RCK, Chen, EYH, Chen, RYL, Cheng, W, Cheung, EFC, Chong, SA, Clarke, TK, Cloninger, CR, Cohen, D, Cohen, N, Coleman, JRI, Collier, DA, Cormican, P, Coryell, W, Craddock, N, and Craig, DW
Abstract: Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment. Genetic analysis of multiple bipolar disorder and schizophrenia cohorts reveals loci and polygenic risk scores that differentiate the clinical symptoms of these two highly correlated disorders.
Published: 2018

17. Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

Author: Amare, AT, Schubert, KO, Tekola-Ayele, F, Hsu, Y-H, Sangkuhl, K, Jenkins, G, Whaley, RM, Barman, P, Batzler, A, Altman, RB, Arolt, V, Brockmoeller, J, Chen, C-H, Domschke, K, Hall-Flavin, DK, Hong, C-J, Illi, A, Ji, Y, Kampman, O, Kinoshita, T, Leinonen, E, Liou, Y-J, Mushiroda, T, Nonen, S, Skime, MK, Wang, L, Kato, M, Liu, Y-L, Praphanphoj, V, Stingl, JC, Bobo, WV, Tsai, S-J, Kubo, M, Klein, TE, Weinshilboum, RM, Biernacka, JM, Baune, BT, Amare, AT, Schubert, KO, Tekola-Ayele, F, Hsu, Y-H, Sangkuhl, K, Jenkins, G, Whaley, RM, Barman, P, Batzler, A, Altman, RB, Arolt, V, Brockmoeller, J, Chen, C-H, Domschke, K, Hall-Flavin, DK, Hong, C-J, Illi, A, Ji, Y, Kampman, O, Kinoshita, T, Leinonen, E, Liou, Y-J, Mushiroda, T, Nonen, S, Skime, MK, Wang, L, Kato, M, Liu, Y-L, Praphanphoj, V, Stingl, JC, Bobo, WV, Tsai, S-J, Kubo, M, Klein, TE, Weinshilboum, RM, Biernacka, JM, and Baune, BT
Abstract: Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.
Published: 2018

18. Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Author: de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, Shi, J, de Jong, S, Abdalla Diniz, MJ, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Curtis, C, Newhouse, SJ, Patel, H, Hall, LS, O'Reilly, PF, Belangero, S, Bressan, RA, Breen, G, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, Krogh, J, Kutalik, Z, Li, Y, Lind, PA, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, Mcgrath, P, Mcguffin, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milaneschi, Y, Milani, L, Mondimore, FM, Montgomery, GW, Mostafavi, S, Mullins, N, Nauck, M, Ng, B, Nivard, MG, Nyholt, DR, Oskarsson, H, Owen, MJ, Painter, JN, Pedersen, CB, Pedersen, MG, Peterson, RE, Pettersson, E, Peyrot, WJ, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shyn, S, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Streit, F, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, Treutlein, J, Trubetskoy, V, Uitterlinden, AG, Umbricht, D, Van der Auwera, S, van Hemert, AM, Viktorin, A, Visscher, PM, Wang, Y, Webb, BT, Weinsheimer, SM, Wellmann, J, Willemsen, G, Witt, SH, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Baune, BT, Berger, K, Boomsma, D, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Grabe, HJ, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, McIntosh, AM, Metspalu, A, Mors, O, Mortensen, PB, Mueller-Myhsok, B, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Rietschel, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Borglum, AD, Sullivan, PF, Meier, S, Strauss, J, Xu, W, Vincent, JB, Matthews, K, Ferreira, M, O'Dushlaine, C, Purcell, S, Raychaudhuri, S, Ruderfer, DM, Sklar, P, Scott, LJ, Flickinger, M, Burmeister, M, Li, J, Guan, W, Absher, D, Thompson, RC, Meng, FG, Schatzberg, AF, Bunney, WE, Barchas, JD, Watson, SJ, Myers, RM, Akil, H, Boehnke, M, Chambert, K, Moran, J, Scolnick, E, Djurovic, S, Melle, I, Morken, G, Corvin, A, Anjorin, A, Kandaswamy, R, Lawrence, J, McLean, AW, Pickard, BS, Bergen, SE, Nimgaonkar, V, Landen, M, Schalling, M, Osby, U, Backlund, L, Frisen, L, Langstrom, N, Stahl, E, Dobbyn, A, Jamain, S, Etain, B, Bellivier, F, Leber, M, Maaser, A, Fischer, SB, Reinbold, CS, Kittel-Schneider, S, Fullerton, JM, Oruc, L, Para, JG, Mayoral, F, Rivas, F, Czerski, PM, Kammerer-Ciernioch, J, Vedder, H, Borrmann-Hassenbach, M, Pfennig, A, Brennan, P, McKay, JD, Kogevinas, M, Schwarz, M, Schofield, PR, Muehleisen, TW, Schumacher, J, Bauer, M, Wright, A, Mitchell, PB, Hautzinger, M, Kelsoe, JR, Greenwood, TA, Nievergelt, CM, Shilling, PD, Smith, EN, Bloss, CS, Edenberg, HJ, Koller, DL, Gershon, ES, Liu, C, Badner, JA, Scheftner, WA, Lawson, WB, Nwulia, EA, Hipolito, M, Coryell, W, Rice, J, Byerley, W, McMahon, FJ, Lohoff, FW, Zandi, PP, Mahon, PB, McInnis, MG, Zollner, S, Zhang, P, Szelinger, S, St Clair, D, Caesar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Kirov, G, Nikolov, I, Collier, DA, Elkin, A, Williamson, R, Young, AH, Ferrier, IN, Milanova, V, Alda, M, Cervantes, P, Cruceanu, C, Rouleau, GA, Turecki, G, Paciga, S, Winslow, AR, Grigoroiu-Serbanescu, M, Ophoff, R, Adolfsson, R, Adolfsson, AN, Del-Favero, J, Pato, C, Biernacka, JM, Frye, MA, Morris, D, Schork, NJ, Reif, A, Lissowska, J, Hauser, J, Szeszenia-Dabrowska, N, McGhee, K, Quinn, E, Moskvina, V, Holmans, PA, Farmer, A, Kennedy, JL, Andreassen, OA, Mattingsdal, M, Bass, NJ, Gurling, H, McQuillin, A, Breuer, R, Hultman, C, Lichtenstein, P, Huckins, LM, Leboyer, M, Lathrop, M, Nurnberger, J, Steffens, M, Foroud, TM, Berrettini, WH, Craig, DW, and Shi, J
Abstract: Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.
Published: 2018

19. Genetic variants associated with response to lithium treatment in bipolar disorder: A genome-wide association study

Author: Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Banzato, CEM, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Bui, ET, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dantas, CR, Dayer, A, Étain, B, Falkai, P, Forstner, AJ, Frisén, L, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, Macqueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, T, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, S, Wright, A, Young, LT, Zandi, PP, Potash, JB, Depaulo, JR, Hou, L, Heilbronner, U, Degenhardt, F, Adli, M, Akiyama, K, Akula, N, Ardau, R, Arias, B, Backlund, L, Banzato, CEM, Benabarre, A, Bengesser, S, Bhattacharjee, AK, Biernacka, JM, Birner, A, Brichant-Petitjean, C, Bui, ET, Cervantes, P, Chen, GB, Chen, HC, Chillotti, C, Cichon, S, Clark, SR, Colom, F, Cousins, DA, Cruceanu, C, Czerski, PM, Dantas, CR, Dayer, A, Étain, B, Falkai, P, Forstner, AJ, Frisén, L, Fullerton, JM, Gard, S, Garnham, JS, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Herms, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kittel-Schneider, S, Kliwicki, S, König, B, Kusumi, I, Lackner, N, Laje, G, Landén, M, Lavebratt, C, Leboyer, M, Leckband, SG, Jaramillo, CAL, Macqueen, G, Manchia, M, Martinsson, L, Mattheisen, M, McCarthy, MJ, McElroy, SL, Mitjans, M, Mondimore, FM, Monteleone, P, Nievergelt, CM, Nöthen, MM, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Reich-Erkelenz, D, Rouleau, GA, Schofield, PR, Schubert, KO, Schweizer, BW, Seemüller, F, Severino, G, Shekhtman, T, Shilling, PD, Shimoda, K, Simhandl, C, Slaney, CM, Smoller, JW, Squassina, A, Stamm, T, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Volkert, J, Witt, S, Wright, A, Young, LT, Zandi, PP, Potash, JB, and Depaulo, JR
Abstract: Background Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified. Methods Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis. Findings A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37×10-8; rs78015114, p=1·31×10-8; rs74795342, p=3·31×10-9; and rs75222709, p=3·50×10-9). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0). Interpretation The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings. Funding Deutsche Forschungsgemeinschaft, National Institute of Mental Hea
Published: 2016

20. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder

Author: Hou, L, Bergen, SE, Akula, N, Song, J, Hultman, CM, Landén, M, Adli, M, Alda, M, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Badner, JA, Barrett, TB, Bauer, M, Baune, BT, Bellivier, F, Benabarre, A, Bengesser, S, Berrettini, WH, Bhattacharjee, AK, Biernacka, JM, Birner, A, Bloss, CS, Brichant-Petitjean, C, Bui, ET, Byerley, W, Cervantes, P, Chillotti, C, Cichon, S, Colom, F, Coryell, W, Craig, DW, Cruceanu, C, Czerski, PM, Davis, T, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Edenberg, HJ, Étain, B, Falkai, P, Foroud, T, Forstner, AJ, Frisén, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Gershon, ES, Goes, FS, Greenwood, TA, Grigoroiu-Serbanescu, M, Hauser, J, Heilbronner, U, Heilmann-Heimbach, S, Herms, S, Hipolito, M, Hitturlingappa, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koller, DL, König, B, Lackner, N, Laje, G, Lang, M, Lavebratt, C, Lawson, WB, Leboyer, M, Leckband, SG, Liu, C, Maaser, A, Mahon, PB, Maier, W, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McInnis, MG, McKinney, R, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Mühleisen, TW, Nievergelt, CM, Nöthen, MM, Novák, T, Nurnberger, JI, Nwulia, EA, Ösby, U, Hou, L, Bergen, SE, Akula, N, Song, J, Hultman, CM, Landén, M, Adli, M, Alda, M, Ardau, R, Arias, B, Aubry, JM, Backlund, L, Badner, JA, Barrett, TB, Bauer, M, Baune, BT, Bellivier, F, Benabarre, A, Bengesser, S, Berrettini, WH, Bhattacharjee, AK, Biernacka, JM, Birner, A, Bloss, CS, Brichant-Petitjean, C, Bui, ET, Byerley, W, Cervantes, P, Chillotti, C, Cichon, S, Colom, F, Coryell, W, Craig, DW, Cruceanu, C, Czerski, PM, Davis, T, Dayer, A, Degenhardt, F, Del Zompo, M, DePaulo, JR, Edenberg, HJ, Étain, B, Falkai, P, Foroud, T, Forstner, AJ, Frisén, L, Frye, MA, Fullerton, JM, Gard, S, Garnham, JS, Gershon, ES, Goes, FS, Greenwood, TA, Grigoroiu-Serbanescu, M, Hauser, J, Heilbronner, U, Heilmann-Heimbach, S, Herms, S, Hipolito, M, Hitturlingappa, S, Hoffmann, P, Hofmann, A, Jamain, S, Jiménez, E, Kahn, JP, Kassem, L, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koller, DL, König, B, Lackner, N, Laje, G, Lang, M, Lavebratt, C, Lawson, WB, Leboyer, M, Leckband, SG, Liu, C, Maaser, A, Mahon, PB, Maier, W, Maj, M, Manchia, M, Martinsson, L, McCarthy, MJ, McElroy, SL, McInnis, MG, McKinney, R, Mitchell, PB, Mitjans, M, Mondimore, FM, Monteleone, P, Mühleisen, TW, Nievergelt, CM, Nöthen, MM, Novák, T, Nurnberger, JI, Nwulia, EA, and Ösby, U
Abstract: Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of > 9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P= 5.87×10-9; odds ratio (OR)=1.12) and markers within ERBB2 (rs2517959, P= 4.53×10-9; OR=1.13). No significant X-chromosome associations were detected and Xlinked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
Published: 2016

21. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response

Author: Biernacka, JM, Sangkuhl, K, Jenkins, G, Whaley, RM, Barman, P, Batzler, A, Altman, RB, Arolt, V, Brockmoeller, J, Chen, CH, Domschke, K, Hall-Flavin, DK, Hong, CJ, Illi, A, Ji, Y, Kampman, O, Kinoshita, T, Leinonen, E, Liou, YJ, Mushiroda, T, Nonen, S, Skime, MK, Wang, L, Baune, BT, Kato, M, Liu, YL, Praphanphoj, V, Stingl, JC, Tsai, SJ, Kubo, M, Klein, TE, Weinshilboum, R, Biernacka, JM, Sangkuhl, K, Jenkins, G, Whaley, RM, Barman, P, Batzler, A, Altman, RB, Arolt, V, Brockmoeller, J, Chen, CH, Domschke, K, Hall-Flavin, DK, Hong, CJ, Illi, A, Ji, Y, Kampman, O, Kinoshita, T, Leinonen, E, Liou, YJ, Mushiroda, T, Nonen, S, Skime, MK, Wang, L, Baune, BT, Kato, M, Liu, YL, Praphanphoj, V, Stingl, JC, Tsai, SJ, Kubo, M, Klein, TE, and Weinshilboum, R
Abstract: Response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably between patients. The International SSRI Pharmacogenomics Consortium (ISPC) was formed with the primary goal of identifying genetic variation that may contribute to response to SSRI treatment of major depressive disorder. A genome-wide association study of 4-week treatment outcomes, measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17), was performed using data from 865 subjects from seven sites. The primary outcomes were percent change in HRSD-17 score and response, defined as at least 50% reduction in HRSD-17. Data from two prior studies, the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study (PGRN-AMPS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, were used for replication, and a meta-analysis of the three studies was performed (N=2394). Although many top association signals in the ISPC analysis map to interesting candidate genes, none were significant at the genome-wide level and the associations were not replicated using PGRN-AMPS and STAR*D data. The top association result in the meta-analysis of response represents SNPs 5′ upstream of the neuregulin-1 gene, NRG1 (P = 1.20E - 06). NRG1 is involved in many aspects of brain development, including neuronal maturation and variations in this gene have been shown to be associated with increased risk for mental disorders, particularly schizophrenia. Replication and functional studies of these findings are warranted.
Published: 2015

22. Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Author: Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Banzato, CEM, Baune, BT, Bellivier, F, Bengesser, S, Biernacka, JM, Brichant-Petitjean, C, Bui, E, Calkin, CV, Cheng, ATA, Chillotti, C, Cichon, S, Clark, S, Czerski, PM, Dantas, C, Del Zompo, M, DePaulo, JR, Detera-Wadleigh, SD, Etain, B, Falkai, P, Frisén, L, Frye, MA, Fullerton, J, Gard, S, Garnham, J, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, JP, Kassem, L, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Kuo, PH, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, SG, López Jaramillo, CA, Maj, M, Malafosse, A, Martinsson, L, Masui, T, Mitchell, PB, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Potash, JB, Reich-Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schubert, OK, Schweizer, B, Seemüller, F, Grigoroiu-Serbanescu, M, Severino, G, Seymour, LR, Slaney, C, Smoller, JW, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Wray, NR, Wright, A, Zandi, PP, Zilles, D, Bauer, M, Rietschel, M, McMahon, FJ, Schulze, TG, Alda, M, Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, JM, Backlund, L, Banzato, CEM, Baune, BT, Bellivier, F, Bengesser, S, Biernacka, JM, Brichant-Petitjean, C, Bui, E, Calkin, CV, Cheng, ATA, Chillotti, C, Cichon, S, Clark, S, Czerski, PM, Dantas, C, Del Zompo, M, DePaulo, JR, Detera-Wadleigh, SD, Etain, B, Falkai, P, Frisén, L, Frye, MA, Fullerton, J, Gard, S, Garnham, J, Goes, FS, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, JP, Kassem, L, Kato, T, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Kuo, PH, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, SG, López Jaramillo, CA, Maj, M, Malafosse, A, Martinsson, L, Masui, T, Mitchell, PB, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Ösby, U, Ozaki, N, Perlis, RH, Pfennig, A, Potash, JB, Reich-Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, GA, Rybakowski, JK, Schalling, M, Schofield, PR, Schubert, OK, Schweizer, B, Seemüller, F, Grigoroiu-Serbanescu, M, Severino, G, Seymour, LR, Slaney, C, Smoller, JW, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, SK, Tortorella, A, Turecki, G, Wray, NR, Wright, A, Zandi, PP, Zilles, D, Bauer, M, Rietschel, M, McMahon, FJ, Schulze, TG, and Alda, M
Abstract: Objective:The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study.Materials and Methods:Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (κ)] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling.Results:Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (κ = 0.66 and κ = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (ICC1 = 0.71 and ICC2 = 0.75, respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders).Conclusions:We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.
Published: 2013

23. Do interactions between SNCA, MAPT, and LRRK2 genes contribute to Parkinson's disease susceptibility?

Author: Biernacka JM, Armasu SM, Cunningham JM, Eric Ahlskog J, Chung SJ, Maraganore DM, Biernacka, Joanna M, Armasu, Sebastian M, Cunningham, Julie M, Ahlskog, J Eric, Chung, Sun Ju, and Maraganore, Demetrius M
Abstract: Background: Polymorphisms in SNCA, MAPT and LRRK2 genes have recently been confirmed as risk factors for Parkinson's disease (PD), although with small individual attributable risk. Here we investigated the association of PD with interactions between variants of these genes.Methods: As part of a previous study of PD susceptibility genes 119 SNCA, MAPT, and LRRK2 haplotype tagging single nucleotide polymorphisms (SNPs) and two variable number tandem repeats (VNTRs) were genotyped in 1098 PD cases from the upper Midwest, USA and 1098 matched controls. Twenty-six of these SNPs were selected for SNP-SNP (or SNP-VNTR or VNTR-VNTR) interaction analysis (256 interaction pairs). Case-control analyses were performed to study association of pairwise SNP interactions with PD susceptibility.Results: Out of the 256 interaction pairs investigated, 10 had uncorrected p-values <0.05. These represented six SNCA-LRRK2 pairs, three SNCA-MAPT pairs, and one MAPT-LRRK2 pair. However, none of these pairwise interactions were significant after correction for multiple testing. Secondary analyses in strata defined by type of control (sibling or unrelated), sex, or age at onset of the case also did not reveal any significant interactions after accounting for multiple testing.Conclusions: This study provides no statistically significant evidence of gene-gene interaction effects for the three confirmed genetic susceptibility loci for PD. However, this does not exclude the possibility that other genomic loci or environmental risk factors interact with these genes. [ABSTRACT FROM AUTHOR]
Published: 2011
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24. Genomic determinants of motor and cognitive outcomes in Parkinson's disease.

Author: Chung SJ, Armasu SM, Biernacka JM, Anderson KJ, Lesnick TG, Rider DN, Cunningham JM, Eric Ahlskog J, Frigerio R, Maraganore DM, Chung, Sun Ju, Armasu, Sebastian M, Biernacka, Joanna M, Anderson, Kari J, Lesnick, Timothy G, Rider, David N, Cunningham, Julie M, Eric Ahlskog, J, Frigerio, Roberta, and Maraganore, Demetrius M
Abstract: Background: Little is known regarding genetic factors associated with motor or cognitive outcomes in Parkinson's disease (PD).Objective: To identify common genetic variants associated with motor and cognitive outcomes in PD.Methods: The sample consisted of 443 PD cases included in the first genome-wide association study (GWAS) of PD. Methods included telephone interview assessments of motor and cognitive outcomes, a median 9 years following the initial clinical assessments. Analyses included Cox proportional hazard models to study the association of 198,345 single nucleotide polymorphisms (SNPs) with survival free of Hoehn and Yahr stage ≥ 4 (motor outcome), and either TICS-M ≤ 27 or AD-8 ≥ 2 (cognitive outcomes).Results: The SNP rs10958605 in the C8orf4 gene had the smallest p value in analyses of the motor outcome (HR = 1.81; 95% CI = 1.42-2.31; p = 1.51 × 10(-6)). The SNP rs6482992 in the CLRN3 gene had the smallest p value in analyses of the cognitive outcome (HR = 2.03, 95% CI 1.47-2.79, p = 4.08 × 10(-6)). However, no SNP associations were significant after Bonferroni correction. The C8orf4 gene had small p values for both motor and cognitive outcomes, highlighting inflammation as a possible pathogenesis mechanism for progression in PD.Conclusions: This study suggests that common variants in several genes may be associated with motor and cognitive outcomes in PD, with biological plausibility. [ABSTRACT FROM AUTHOR]
Published: 2012
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25. Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Author: J. Raymond DePaulo, Martin Alda, Alfonso Tortorella, Susan G. Leckband, Jean-Michel Aubry, James B. Potash, Clara Brichant-Petitjean, Layla Kassem, Joanna Hauser, Tomas Novak, David Zilles, Claire O'Donovan, Rebecca Hoban, Sarah Kittel-Schneider, Claire Slaney, Lena Backlund, Peter Falkai, Andrew T. A. Cheng, John R. Kelsoe, Andrea Pfennig, Janice M. Fullerton, Marcella Rietschel, Caterina Chillotti, Stéphane Jamain, Elise Bui, Po-Hsiu Kuo, Alessio Squassina, Claudio E. M. Banzato, Joanna M. Biernacka, Lisa R. Seymour, Naomi R. Wray, Ichiro Kusumi, Thomas Stamm, Fernando S. Goes, Audrey Nallet, Sarah K. Tighe, Giovanni Severino, Jean-Pierre Kahn, Maria Neuner, Nirmala Akula, Norio Ozaki, Francis J. McMahon, Frank Bellivier, Andreas Reif, Ryota Hashimoto, Barbara W. Schweizer, Palmiero Monteleone, Florian Seemüller, Urs Heilbronner, Sevilla D. Detera-Wadleigh, Pavla Stopkova, Martin Schalling, Julie Garnham, Sébastien Gard, Mark A. Frye, Eva Z. Reininghaus, Lina Martinsson, Urban Ösby, Maria Grigoroiu-Serbanescu, Sara Richardson, Tadafumi Kato, Marion Leboyer, Catharina Lavebratt, Piotr M. Czerski, Scott R. Clark, Daniela Reich-Erkelenz, Sebastian Kliwicki, Guy A. Rouleau, Oliver Gruber, Gonzalo Laje, Adam Wright, Gustavo Turecki, Roy H. Perlis, Takuya Masui, Mirko Manchia, Bernhard T. Baune, Mazda Adli, Michael Bauer, Sven Cichon, Frank Mondimore, Bruno Etain, Philip B. Mitchell, Thomas G. Schulze, Peter P. Zandi, Raffaella Ardau, Peter R. Schofield, Susanne Bengesser, Liping Hou, Janusz K. Rybakowski, Mario Maj, Clarissa de Rosalmeida Dantas, Louise Frisén, O. Schubert, Carlos Jaramillo, Maria Del Zompo, Paul Grof, Cynthia V. Calkin, Jo Steele, Jordan W. Smoller, Alain Malafosse, Manchia, M, Adli, M, Akula, N, Ardau, R, Aubry, Jm, Backlund, L, Banzato, Ce, Baune, Bt, Bellivier, F, Bengesser, S, Biernacka, Jm, Brichant Petitjean, C, Bui, E, Calkin, Cv, Cheng, At, Chillotti, C, Cichon, S, Clark, S, Czerski, Pm, Dantas, C, Zompo, Md, Depaulo, Jr, Detera Wadleigh, Sd, Etain, B, Falkai, P, Frisén, L, Frye, Ma, Fullerton, J, Gard, S, Garnham, J, Goes, F, Grof, P, Gruber, O, Hashimoto, R, Hauser, J, Heilbronner, U, Hoban, R, Hou, L, Jamain, S, Kahn, Jp, Kassem, L, Kato, T, Kelsoe, Jr, Kittel Schneider, S, Kliwicki, S, Kuo, Ph, Kusumi, I, Laje, G, Lavebratt, C, Leboyer, M, Leckband, Sg, López Jaramillo, Ca, Maj, Mario, Malafosse, A, Martinsson, L, Masui, T, Mitchell, Pb, Mondimore, F, Monteleone, P, Nallet, A, Neuner, M, Novák, T, O'Donovan, C, Osby, U, Ozaki, N, Perlis, Rh, Pfennig, A, Potash, Jb, Reich Erkelenz, D, Reif, A, Reininghaus, E, Richardson, S, Rouleau, Ga, Rybakowski, Jk, Schalling, M, Schofield, Pr, Schubert, Ok, Schweizer, B, Seemüller, F, Grigoroiu Serbanescu, M, Severino, G, Seymour, Lr, Slaney, C, Smoller, Jw, Squassina, A, Stamm, T, Steele, J, Stopkova, P, Tighe, Sk, Tortorella, Alfonso Antonio Vincenzo, Turecki, G, Wray, Nr, Wright, A, Zandi, Pp, Zilles, D, Bauer, M, Rietschel, M, Mcmahon, Fj, Schulze, Tg, Alda, M., Department of Psychiatry, Dalhousie University [Halifax], Department of Psychiatry and Psychotherapy, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Unit of Clinical Pharmacology, University-Hospital of Cagliari, Department of Mental Health and Psychiatry, University Hospital of Geneva, Trinity College Dublin-St. James's Hospital, University of Campinas [Campinas] (UNICAMP), University of Adelaide, Pôle de Psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Medical University Graz, Mayo Clinic, Division of Epidemiology and Genetics, Academia Sinica-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo (USP)-Universidade de São Paulo (USP), Department of Genomics, Life and Brain Center, University of Bonn, Psychiatric Genetic Unit, Poznan University of Medical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, University of Homburg, Genetics of Mental Illness and Brain Function, Neuroscience Research Australia, Service de psychiatrie adulte, Université Bordeaux Segalen - Bordeaux 2-Hôpital Charles Perrens-Centre Expert Trouble Bipolaire, Mood Disorders Center of Ottawa (MDCO), University of Ottawa [Ottawa], University of Toronto, Georg-August-University [Göttingen], Osaka University Graduate School of Medicine, University of California [San Diego] (UC San Diego), University of California-University of California, Service de Psychiatrie et Psychologie Clinique, Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Hôpital Jeanne-d'Arc, Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Mental Health Sciences Unit, University College of London [London] (UCL), Department of Adult Psychiatry, Institute of Epidemiology and Preventive Medicine, National Taiwan University [Taiwan] (NTU), Hokkaido University Graduate School of Medicine, Molecular Medicine and Surgery department, Karolinska Institutet [Stockholm], Center for Molecular Medicine, Karolinska University Hospital [Stockholm], Department of Pharmacy, Veterans Affairs San Diego Healthcare System, Skaggs School of Pharmacy and Pharmaceutical Sciences [San Diego], University of Antioquia, University of Napoli, School of Psychiatry, University of New South Wales [Sydney] (UNSW)-Black Dog Institute, Prague Psychiatric Center, University of Prague, Fujita Health University School of Medicine, Nagoya University Graduate School of Medicine, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Technische Universität Dresden = Dresden University of Technology (TU Dresden), University of Iowa [Iowa City], Center of Excellence in Neuroscience, CHU de Montréal, Department of Medicine, Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CR CHUM), Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM)-Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM), Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Psychiatric Hospital, McGill Group for Suicide Studies, Douglas Mental Health University Institute, Queensland Brain Institute, University of Queensland [Brisbane], Department of Mental Health, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU)-Johns Hopkins University (JHU), Department of Genetic Epidemiology in Psychiatry [Mannhein], Universität Heidelberg [Heidelberg]-Central Institute of Mental Health Mannheim, The work on assessment of lithium response has been supported by a grant from Canadian Institutes of Health Research #64410 to MA. MG-S was supported by Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii (UEFISCDI), Bucharest, Romania (grant no. 89/2012). JMA and AN were supported by a grant from the Swiss National Foundation (#32003B_125469/1 to JM Aubry). ConLiGen is in part supported by funds from the Intramural Research Program of the National Institute of Mental Health (NIMH) at the National Institutes of Health (NIH), Department of Health and Human Services, United States Government, Aubry, Jean-Michel, Universidade Estadual de Campinas = University of Campinas (UNICAMP), Universidade de São Paulo = University of São Paulo (USP)-Universidade de São Paulo = University of São Paulo (USP), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Georg-August-University = Georg-August-Universität Göttingen, University of California (UC)-University of California (UC), Guellaen, Georges, Université Bordeaux Segalen - Bordeaux 2-Centre hospitalier Charles Perrens [Bordeaux]-Centre Expert Trouble Bipolaire, and Ikeda, Kazutaka
Subjects: Male, Bipolar Disorder, Lithium (medication), Psychometrics, Psychopharmacology, Epidemiology, International Cooperation, lcsh:Medicine, Lithium, Maintenance Treatment, ConLiGen, ddc:616.89, 0302 clinical medicine, Antimanic Agents, Psychology, lcsh:Science, Reliability (statistics), Psychiatry, Genetics, 0303 health sciences, Multidisciplinary, ASSOCIATION, Genomics, Pharmacoepidemiology, 3. Good health, Mental Health, Phenotype, Treatment Outcome, MAPPING SUSCEPTIBILITY GENES, Behavioral Pharmacology, RELIABILITY, Lithium Compounds, Medicine, Female, Research Article, medicine.drug, Drugs and Devices, MAPPING SUSCEPTIBILITY GENES, PROPHYLACTIC LITHIUM, OBSERVER AGREEMENT, MOOD DISORDERS, ONSET, ASSOCIATION, RELIABILITY, MORTALITY, ILLNESS, AGE, ILLNESS, PROPHYLACTIC LITHIUM, 03 medical and health sciences, AGE, Neuropharmacology, Genomic Medicine, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology, Genome-Wide Association Studies, medicine, Humans, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Bipolar disorder, ddc:610, Biology, 030304 developmental biology, Mood Disorders, business.industry, MORTALITY, lcsh:R, Computational Biology, Reproducibility of Results, Models, Theoretical, medicine.disease, OBSERVER AGREEMENT, Mood disorders, Pharmacogenetics, Therapies, ONSET, lcsh:Q, Pharmacogenomics, business, 030217 neurology & neurosurgery, Kappa
Abstract: Objective: The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. Materials and Methods: Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (\(\kappa\))] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. Results: Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (\(\kappa\) = 0.66 and \(\kappa\) = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (\(ICC_1 = 0.71\) and \(ICC_2 = 0.75\), respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). Conclusions: We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.
Published: 2013

26. Correction: Social connectedness as a determinant of mental health: A scoping review.

Author: Wickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksberg BS, Talati A, Adekkanattu P, Ryu E, Biernacka JM, Charney A, Mann JJ, Pathak J, Olfson M, and Weissman MM
Abstract: [This corrects the article DOI: 10.1371/journal.pone.0275004.]., (Copyright: © 2024 Wickramaratne et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2024
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27. Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model.

Author: Patra BG, Lepow LA, Kasi Reddy Jagadeesh Kumar P, Vekaria V, Sharma MM, Adekkanattu P, Fennessy B, Hynes G, Landi I, Sanchez-Ruiz JA, Ryu E, Biernacka JM, Nadkarni GN, Talati A, Weissman M, Olfson M, Mann JJ, Zhang Y, Charney AW, and Pathak J
Abstract: Objectives: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented in narrative clinical notes rather than as structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labor-intensive process of extraction of such information., Materials and Methods: Psychiatric encounter notes from Mount Sinai Health System (MSHS, n = 300) and Weill Cornell Medicine (WCM, n = 225) were annotated to create a gold-standard corpus. A rule-based system (RBS) involving lexicons and a large language model (LLM) using FLAN-T5-XL were developed to identify mentions of SS and SI and their subcategories (eg, social network, instrumental support, and loneliness)., Results: For extracting SS/SI, the RBS obtained higher macroaveraged F1-scores than the LLM at both MSHS (0.89 versus 0.65) and WCM (0.85 versus 0.82). For extracting the subcategories, the RBS also outperformed the LLM at both MSHS (0.90 versus 0.62) and WCM (0.82 versus 0.81)., Discussion and Conclusion: Unexpectedly, the RBS outperformed the LLMs across all metrics. An intensive review demonstrates that this finding is due to the divergent approach taken by the RBS and LLM. The RBS was designed and refined to follow the same specific rules as the gold-standard annotations. Conversely, the LLM was more inclusive with categorization and conformed to common English-language understanding. Both approaches offer advantages, although additional replication studies are warranted., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2024
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28. Clinical associations with treatment resistance in depression: An electronic health record study.

Author: Coombes BJ, Sanchez-Ruiz JA, Fennessy B, Pazdernik VK, Adekkanattu P, Nuñez NA, Lepow L, Melhuish Beaupre LM, Ryu E, Talati A, Mann JJ, Weissman MM, Olfson M, Pathak J, Charney AW, and Biernacka JM
Abstract: Treatment resistance is common in major depressive disorder (MDD), yet clinical risk factors are not well understood. Using a discovery-replication design, we conducted phenome-wide association studies (PheWASs) of MDD treatment resistance in two electronic health record (EHR)-linked biobanks. The PheWAS included participants with an MDD diagnosis in the EHR and at least one antidepressant (AD) prescription. Participant lifetime diagnoses were mapped to phecodes. PheWASs were conducted for three treatment resistance outcomes based on AD prescription data: number of unique ADs prescribed, ≥1 and ≥2 CE switches. Of the 180 phecodes significantly associated with these outcomes in the discovery cohort (n = 12,558), 71 replicated (n = 8,206). In addition to identifying known clinical factors for treatment resistance in MDD, the total unique AD prescriptions was associated with additional clinical variables including irritable bowel syndrome, gastroesophageal reflux disease, symptomatic menopause, and spondylosis. We calculated polygenic risk of specific-associated conditions and tested their association with AD outcomes revealing that genetic risk for many of these conditions is also associated with the total unique AD prescriptions. The number of unique ADs prescribed, which is easily assessed in EHRs, provides a more nuanced measure of treatment resistance, and may facilitate future research and clinical application in this area., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Mann receives royalties for commercial use of the C-SSRS from the Research Foundation for Mental Hygiene and from Columbia University from sales of the Columbia Pathways app. Dr. Weissman has received funding from NIMH and Columbia University Institute for Developmental Sciences and receives book royalties from Perseus Press and Oxford Press. None of these represent a conflict of interest. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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29. The Wnt signaling pathway in major depressive disorder: A systematic review of human studies.

Author: Sanchez-Ruiz JA, Treviño-Alvarez AM, Zambrano-Lucio M, Lozano Díaz ST, Wang N, Biernacka JM, Tye SJ, and Cuellar-Barboza AB
Subjects: Humans, Depressive Disorder, Major metabolism, Wnt Signaling Pathway physiology
Abstract: Despite uncertainty about the specific molecular mechanisms driving major depressive disorder (MDD), the Wnt signaling pathway stands out as a potentially influential factor in the pathogenesis of MDD. Known for its role in intercellular communication, cell proliferation, and fate, Wnt signaling has been implicated in diverse biological phenomena associated with MDD, spanning neurodevelopmental to neurodegenerative processes. In this systematic review, we summarize the functional differences in protein and gene expression of the Wnt signaling pathway, and targeted genetic association studies, to provide an integrated synthesis of available human data examining Wnt signaling in MDD. Thirty-three studies evaluating protein expression (n = 15), gene expression (n = 9), or genetic associations (n = 9) were included. Only fifteen demonstrated a consistently low overall risk of bias in selection, comparability, and exposure. We found conflicting observations of limited and distinct Wnt signaling components across diverse tissue sources. These data do not demonstrate involvement of Wnt signaling dysregulation in MDD. Given the well-established role of Wnt signaling in antidepressant response, we propose that a more targeted and functional assessment of Wnt signaling is needed to understand its role in depression pathophysiology. Future studies should include more components, assess multiple tissues concurrently, and follow a standardized approach., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Alfredo B. Cuellar-Barboza reports financial support was provided by National Council on Science and Technology. Alfredo B. Cuellar-Barboza reports a relationship with Asofarma De Mexico that includes: consulting or advisory and speaking and lecture fees. Alfredo B. Cuellar-Barboza reports a relationship with Exeltis Mexico that includes: consulting or advisory and speaking and lecture fees. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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30. Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data.

Author: Sanchez-Ruiz JA, Coombes BJ, Pazdernik VM, Melhuish Beaupre LM, Jenkins GD, Pendegraft RS, Batzler A, Ozerdem A, McElroy SL, Gardea-Resendez MA, Cuellar-Barboza AB, Prieto ML, Frye MA, and Biernacka JM
Subjects: Humans, Female, Male, Middle Aged, Aged, Genome-Wide Association Study methods, Genetic Predisposition to Disease genetics, Adult, Aged, 80 and over, Risk Factors, Phenomics methods, Bipolar Disorder genetics, Bipolar Disorder epidemiology, Electronic Health Records, Comorbidity, Biological Specimen Banks, Multifactorial Inheritance genetics, Phenotype
Abstract: Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2024
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31. Differential serum levels of CACNA1C, circadian rhythm and stress response molecules in subjects with bipolar disorder: Associations with genetic and clinical factors.

Author: Allen O 4th, Coombes BJ, Pazdernik V, Gisabella B, Hartley J, Biernacka JM, Frye MA, Markota M, and Pantazopoulos H
Subjects: Humans, Female, Male, Adult, Middle Aged, Genotype, Corticotropin-Releasing Hormone blood, Corticotropin-Releasing Hormone genetics, ARNTL Transcription Factors genetics, ARNTL Transcription Factors blood, Biomarkers blood, Case-Control Studies, Somatostatin blood, Alleles, Bipolar Disorder blood, Bipolar Disorder genetics, Calcium Channels, L-Type genetics, Polymorphism, Single Nucleotide, Circadian Rhythm physiology
Abstract: Background: Many patients with bipolar disorder (BD) do not respond to or have difficulties tolerating lithium and/or other mood stabilizing agents. There is a need for personalized treatments based on biomarkers in guiding treatment options. The calcium voltage-gated channel CACNA1C is a promising candidate for developing personalized treatments. CACNA1C is implicated in BD by genome-wide association studies and several lines of evidence suggest that targeting L-type calcium channels could be an effective treatment strategy. However, before such individualized treatments can be pursued, biomarkers predicting treatment response need to be developed., Methods: As a first step in testing the hypothesis that CACNA1C genotype is associated with serum levels of CACNA1C, we conducted ELISA measures on serum samples from 100 subjects with BD and 100 control subjects., Results: We observed significantly higher CACNA1C (p < 0.01) protein levels in subjects with BD. The risk single nucleotide polymorpshism (SNP) (rs11062170) showed functional significance as subjects homozygous for the risk allele (CC) had significantly greater CACNA1C protein levels compared to subjects with one (p = 0.013) or no copies (p = 0.009). We observed higher somatostatin (SST) (p < 0.003) protein levels and lower levels of the clock protein aryl hydrocarbon receptor nuclear translocator-like (ARTNL) (p < 0.03) and stress signaling factor corticotrophin releasing hormone (CRH) (p < 0.001) in BD. SST and period 2 (PER2) protein levels were associated with both alcohol dependence and lithium response., Conclusions: Our findings represent the first evidence for increased serum levels of CACNA1C in BD. Along with altered levels of SST, ARNTL, and CRH our findings suggest CACNA1C is associated with circadian rhythm and stress response disturbances in BD., Competing Interests: Declaration of competing interest The authors have no competing financial interests to disclose., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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32. Correction: Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.

Author: Li D, Pain O, Fabbri C, Wong WLE, Lo CWH, Ripke S, Cattaneo A, Souery D, Dernovsek MZ, Henigsberg N, Hauser J, Lewis G, Mors O, Perroud N, Rietschel M, Uher R, Maier W, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Liu YL, Serretti A, Tsai SJ, Weinshilboum R, McIntosh AM, and Lewis CM
Published: 2024
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33. Measuring the exposome in bipolar disorder.

Author: Ercis M, Ozerdem A, Veldic M, Singh B, Coombes BJ, Biernacka JM, Lazaridis KN, and Frye MA
Subjects: Humans, Environmental Exposure adverse effects, Bipolar Disorder diagnosis, Exposome
Published: 2024
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34. Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.

Author: Li D, Pain O, Fabbri C, Wong WLE, Lo CWH, Ripke S, Cattaneo A, Souery D, Dernovsek MZ, Henigsberg N, Hauser J, Lewis G, Mors O, Perroud N, Rietschel M, Uher R, Maier W, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Liu YL, Serretti A, Tsai SJ, Weinshilboum R, McIntosh AM, and Lewis CM
Subjects: Female, Humans, Male, Asian People genetics, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics, Depressive Disorder, Major metabolism, Genotype, Phenotype, Treatment Outcome, White People genetics, Antidepressive Agents therapeutic use, Cytochrome P-450 CYP2C19 genetics, Cytochrome P-450 CYP2D6 genetics, Cytochrome P-450 CYP2D6 metabolism
Abstract: Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I 2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes., (© 2024. The Author(s).)
Published: 2024
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35. Deciphering Distinct Genetic Risk Factors for FTLD-TDP Pathological Subtypes via Whole-Genome Sequencing.

Author: Pottier C, Küçükali F, Baker M, Batzler A, Jenkins GD, van Blitterswijk M, Vicente CT, De Coster W, Wynants S, Van de Walle P, Ross OA, Murray ME, Faura J, Haggarty SJ, van Rooij JG, Mol MO, Hsiung GR, Graff C, Öijerstedt L, Neumann M, Asmann Y, McDonnell SK, Baheti S, Josephs KA, Whitwell JL, Bieniek KF, Forsberg L, Heuer H, Lago AL, Geier EG, Yokoyama JS, Oddi AP, Flanagan M, Mao Q, Hodges JR, Kwok JB, Domoto-Reilly K, Synofzik M, Wilke C, Onyike C, Dickerson BC, Evers BM, Dugger BN, Munoz DG, Keith J, Zinman L, Rogaeva E, Suh E, Gefen T, Geula C, Weintraub S, Diehl-Schmid J, Farlow MR, Edbauer D, Woodruff BK, Caselli RJ, Donker Kaat LL, Huey ED, Reiman EM, Mead S, King A, Roeber S, Nana AL, Ertekin-Taner N, Knopman DS, Petersen RC, Petrucelli L, Uitti RJ, Wszolek ZK, Ramos EM, Grinberg LT, Gorno Tempini ML, Rosen HJ, Spina S, Piguet O, Grossman M, Trojanowski JQ, Keene DC, Lee-Way J, Prudlo J, Geschwind DH, Rissman RA, Cruchaga C, Ghetti B, Halliday GM, Beach TG, Serrano GE, Arzberger T, Herms J, Boxer AL, Honig LS, Vonsattel JP, Lopez OL, Kofler J, White CL, Gearing M, Glass J, Rohrer JD, Irwin DJ, Lee EB, Van Deerlin V, Castellani R, Mesulam MM, Tartaglia MC, Finger EC, Troakes C, Al-Sarraj S, Miller BL, Seelaar H, Graff-Radford NR, Boeve BF, Mackenzie IR, van Swieten JC, Seeley WW, Sleegers K, Dickson DW, Biernacka JM, and Rademakers R
Abstract: Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) is a fatal neurodegenerative disorder with only a limited number of risk loci identified. We report our comprehensive genome-wide association study as part of the International FTLD-TDP Whole-Genome Sequencing Consortium, including 985 cases and 3,153 controls, and meta-analysis with the Dementia-seq cohort, compiled from 26 institutions/brain banks in the United States, Europe and Australia. We confirm UNC13A as the strongest overall FTLD-TDP risk factor and identify TNIP1 as a novel FTLD-TDP risk factor. In subgroup analyses, we further identify for the first time genome-wide significant loci specific to each of the three main FTLD-TDP pathological subtypes (A, B and C), as well as enrichment of risk loci in distinct tissues, brain regions, and neuronal subtypes, suggesting distinct disease aetiologies in each of the subtypes. Rare variant analysis confirmed TBK1 and identified VIPR1 , RBPJL , and L3MBTL1 as novel subtype specific FTLD-TDP risk genes, further highlighting the role of innate and adaptive immunity and notch signalling pathway in FTLD-TDP, with potential diagnostic and novel therapeutic implications.
Published: 2024
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36. Exploring the genetics of lithium response in bipolar disorders.

Author: Herrera-Rivero M, Adli M, Akiyama K, Akula N, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, Biernacka JM, Birner A, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark SR, Colom F, Cruceanu C, Czerski PM, Dalkner N, Degenhardt F, Del Zompo M, DePaulo JR, Etain B, Falkai P, Ferensztajn-Rochowiak E, Forstner AJ, Frank J, Frisén L, Frye MA, Fullerton JM, Gallo C, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hasler R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu YH, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kelsoe J, Kittel-Schneider S, Kuo PH, Kusumi I, König B, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Maj M, Manchia M, Marie-Claire C, Martinsson L, McCarthy MJ, McElroy SL, Millischer V, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Novák T, Nöthen MM, O'Donovan C, Ozaki N, Papiol S, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Richard-Lepouriel H, Roberts G, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schulte EC, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Streit F, Tekola-Ayele F, Thalamuthu A, Tortorella A, Turecki G, Veeh J, Vieta E, Viswanath B, Witt SH, Zandi PP, Alda M, Bauer M, McMahon FJ, Mitchell PB, Rietschel M, Schulze TG, and Baune BT
Abstract: Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II., Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism., Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II., (© 2024. The Author(s).)
Published: 2024
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37. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Author: Toikumo S, Jennings MV, Pham BK, Lee H, Mallard TT, Bianchi SB, Meredith JJ, Vilar-Ribó L, Xu H, Hatoum AS, Johnson EC, Pazdernik VK, Jinwala Z, Pakala SR, Leger BS, Niarchou M, Ehinmowo M, Jenkins GD, Batzler A, Pendegraft R, Palmer AA, Zhou H, Biernacka JM, Coombes BJ, Gelernter J, Xu K, Hancock DB, Cox NJ, Smoller JW, Davis LK, Justice AC, Kranzler HR, Kember RL, and Sanchez-Roige S
Subjects: Humans, Genetic Predisposition to Disease genetics, Genome-Wide Association Study, United States epidemiology, Male, Female, Electronic Health Records, Tobacco Use Disorder genetics
Abstract: Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (n combined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2024
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38. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Author: Nievergelt CM, Maihofer AX, Atkinson EG, Chen CY, Choi KW, Coleman JRI, Daskalakis NP, Duncan LE, Polimanti R, Aaronson C, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegoviç E, Babić D, Bacanu SA, Baker DG, Batzler A, Beckham JC, Belangero S, Benjet C, Bergner C, Bierer LM, Biernacka JM, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Brandolino A, Breen G, Bressan RA, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Bækvad-Hansen M, Børglum AD, Børte S, Cahn L, Calabrese JR, Caldas-de-Almeida JM, Chatzinakos C, Cheema S, Clouston SAP, Colodro-Conde L, Coombes BJ, Cruz-Fuentes CS, Dale AM, Dalvie S, Davis LK, Deckert J, Delahanty DL, Dennis MF, Desarnaud F, DiPietro CP, Disner SG, Docherty AR, Domschke K, Dyb G, Kulenović AD, Edenberg HJ, Evans A, Fabbri C, Fani N, Farrer LA, Feder A, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gelaye B, Gelernter J, Geuze E, Gillespie CF, Goleva SB, Gordon SD, Goçi A, Grasser LR, Guindalini C, Haas M, Hagenaars S, Hauser MA, Heath AC, Hemmings SMJ, Hesselbrock V, Hickie IB, Hogan K, Hougaard DM, Huang H, Huckins LM, Hveem K, Jakovljević M, Javanbakht A, Jenkins GD, Johnson J, Jones I, Jovanovic T, Karstoft KI, Kaufman ML, Kennedy JL, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kotov R, Kranzler HR, Krebs K, Kremen WS, Kuan PF, Lawford BR, Lebois LAM, Lehto K, Levey DF, Lewis C, Liberzon I, Linnstaedt SD, Logue MW, Lori A, Lu Y, Luft BJ, Lupton MK, Luykx JJ, Makotkine I, Maples-Keller JL, Marchese S, Marmar C, Martin NG, Martínez-Levy GA, McAloney K, McFarlane A, McLaughlin KA, McLean SA, Medland SE, Mehta D, Meyers J, Michopoulos V, Mikita EA, Milani L, Milberg W, Miller MW, Morey RA, Morris CP, Mors O, Mortensen PB, Mufford MS, Nelson EC, Nordentoft M, Norman SB, Nugent NR, O'Donnell M, Orcutt HK, Pan PM, Panizzon MS, Pathak GA, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Porjesz B, Powers A, Qin XJ, Ratanatharathorn A, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero KJ, Rung A, Runz H, Rutten BPF, de Viteri SS, Salum GA, Sampson L, Sanchez SE, Santoro M, Seah C, Seedat S, Seng JS, Shabalin A, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stensland S, Stevens JS, Sumner JA, Teicher MH, Thompson WK, Tiwari AK, Trapido E, Uddin M, Ursano RJ, Valdimarsdóttir U, Van Hooff M, Vermetten E, Vinkers CH, Voisey J, Wang Y, Wang Z, Waszczuk M, Weber H, Wendt FR, Werge T, Williams MA, Williamson DE, Winsvold BS, Winternitz S, Wolf C, Wolf EJ, Xia Y, Xiong Y, Yehuda R, Young KA, Young RM, Zai CC, Zai GC, Zervas M, Zhao H, Zoellner LA, Zwart JA, deRoon-Cassini T, van Rooij SJH, van den Heuvel LL, Stein MB, Ressler KJ, and Koenen KC
Subjects: Humans, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Neurobiology, Polymorphism, Single Nucleotide, White People genetics, White, Black or African American, American Indian or Alaska Native, Stress Disorders, Post-Traumatic genetics
Abstract: Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Published: 2024
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39. DNA methylation at DLGAP2 and risk for relapse in alcohol dependence during acamprosate treatment.

Author: Özel F, Di Criscio M, Lupu DI, Sarkisyan D, Hlady RA, Robertson KD, Bakalkin G, Liu Y, Biernacka JM, Karpyak VM, Ekström TJ, and Rüegg J
Subjects: Humans, Acamprosate, DNA Methylation, Chronic Disease, Recurrence, Nerve Tissue Proteins, Alcoholism drug therapy, Alcoholism genetics
Abstract: Background: Alcohol use disorders are prevalent mental disorders with significant health implications. Epigenetic alterations may play a role in their pathogenesis, as DNA methylation at several genes has been associated with these disorders. We have previously shown that methylation in the DLGAP2 gene, coding for a synaptic density protein, is associated with alcohol dependence. In this study, we aimed to examine the association between DLGAP2 methylation and treatment response among patients undergoing acamprosate treatment., Methods: 102 patients under acamprosate treatment were included. DNA methylation analysis at DLGAP2 was performed by bisulfite pyrosequencing at the start and after 3-month treatment. Treatment outcomes were having a relapse during the treatment and severity of craving at the end of three months. Cox proportional hazard and linear regression models were performed., Results: Patients whose methylation levels were decreased during the treatment showed an increased risk for relapse within three months in comparison to the ones without methylation change (hazard ratio [HR]=2.44; 95% confidence interval [CI]=1.04, 5.73; p=0.04). For the same group, a positive association for the severity of craving was observed, yet statistical significance was not reached (β=2.97; 95% CI=-0.41, 6.34; p=0.08)., Conclusion: We demonstrate that patients whose DLGAP2 methylation levels decrease during acamprosate treatment are more likely to relapse compared to the ones without changes. This is in line with our previous findings showing that DLGAP2 methylation is lower in alcohol dependent subjects compared to controls, and might suggest a role for changes in DLGAP2 methylation in treatment response., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2024
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40. Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Author: Ou AH, Rosenthal SB, Adli M, Akiyama K, Akula N, Alda M, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bauer M, Baune BT, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, Biernacka JM, Cervantes P, Chen GB, Chen HC, Chillotti C, Cichon S, Clark SR, Colom F, Cousins DA, Cruceanu C, Czerski PM, Dantas CR, Dayer A, Del Zompo M, Degenhardt F, DePaulo JR, Étain B, Falkai P, Fellendorf FT, Ferensztajn-Rochowiak E, Forstner AJ, Frisén L, Frye MA, Fullerton JM, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Gruber O, Hashimoto R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hofmann A, Hou L, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kittel-Schneider S, König B, Kuo PH, Kusumi I, Lackner N, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Jaramillo CAL, MacQueen G, Maj M, Manchia M, Marie-Claire C, Martinsson L, Mattheisen M, McCarthy MJ, McElroy SL, McMahon FJ, Mitchell PB, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Nöthen MM, Novák T, Ösby U, Ozaki N, Papiol S, Perlis RH, Pisanu C, Potash JB, Pfennig A, Reich-Erkelenz D, Reif A, Reininghaus EZ, Rietschel M, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schulze TG, Schweizer BW, Seemüller F, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Tighe SK, Tortorella A, Turecki G, Vieta E, Volkert J, Witt S, Wray NR, Wright A, Young LT, Zandi PP, and Kelsoe JR
Subjects: Humans, Proto-Oncogene Proteins c-akt genetics, Phosphatidylinositol 3-Kinases genetics, Genome-Wide Association Study, Multiomics, Focal Adhesions, Lithium pharmacology, Lithium therapeutic use, Bipolar Disorder drug therapy, Bipolar Disorder genetics
Abstract: Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD., (© 2024. The Author(s).)
Published: 2024
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41. Pharmacogenomic overlap between antidepressant treatment response in major depression & antidepressant associated treatment emergent mania in bipolar disorder.

Author: Nuñez NA, Coombes BJ, Beaupre LM, Ozerdem A, Resendez MG, Romo-Nava F, Bond DJ, Veldic M, Singh B, Moore KM, Betcher HK, Kung S, Prieto ML, Fuentes M, Ercis M, Miola A, Sanchez Ruiz JA, Jenkins G, Batzler A, Leung JG, Cuellar-Barboza A, Tye SJ, McElroy SL, Biernacka JM, and Frye MA
Subjects: Humans, Mania chemically induced, Mania drug therapy, Depression, Pharmacogenetics, Genome-Wide Association Study, Antidepressive Agents therapeutic use, Bipolar Disorder drug therapy, Bipolar Disorder genetics, Bipolar Disorder chemically induced, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics
Abstract: There is increasing interest in individualizing treatment selection for more than 25 regulatory approved treatments for major depressive disorder (MDD). Despite an inconclusive efficacy evidence base, antidepressants (ADs) are prescribed for the depressive phase of bipolar disorder (BD) with oftentimes, an inadequate treatment response and or clinical concern for mood destabilization. This study explored the relationship between antidepressant response in MDD and antidepressant-associated treatment emergent mania (TEM) in BD. We conducted a genome-wide association study (GWAS) and polygenic score analysis of TEM and tested its association in a subset of BD-type I patients treated with SSRIs or SNRIs. Our results did not identify any genome-wide significant variants although, we found that a higher polygenic score (PGS) for antidepressant response in MDD was associated with higher odds of TEM in BD. Future studies with larger transdiagnostic depressed cohorts treated with antidepressants are encouraged to identify a neurobiological mechanism associated with a spectrum of depression improvement from response to emergent mania., (© 2024. The Author(s).)
Published: 2024
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42. Patterns of pharmacotherapy for bipolar disorder: A GBC survey.

Author: Singh B, Yocum AK, Strawbridge R, Burdick KE, Millett CE, Peters AT, Sperry SH, Fico G, Vieta E, Verdolini N, Godin O, Leboyer M, Etain B, Tso IF, Coombes BJ, McInnis MG, Nierenberg AA, Young AH, Ashton MM, Berk M, Williams LJ, Keramatian K, Yatham LN, Overs BJ, Fullerton JM, Roberts G, Mitchell PB, Andreassen OA, Andreazza AC, Zandi PP, Pham D, Biernacka JM, and Frye MA
Subjects: Humans, Female, Male, Lithium therapeutic use, Anticonvulsants therapeutic use, Australia epidemiology, Antidepressive Agents therapeutic use, Bipolar Disorder drug therapy, Bipolar Disorder epidemiology, Bipolar Disorder diagnosis, Antipsychotic Agents therapeutic use
Abstract: Objectives: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia., Methods: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns., Results: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort., Conclusions: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD., (© 2023 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd.)
Published: 2024
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43. Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Author: Panagiotaropoulou G, Hellberg KG, Coleman JRI, Seok D, Kalman J, Mitchell PB, Schofield PR, Forstner AJ, Bauer M, Scott LJ, Pato CN, Pato MT, Li QS, Kirov G, Landén M, Jonsson L, Müller-Myhsok B, Smoller JW, Binder EB, Brückl TM, Czamara D, der Auwera SV, Grabe HJ, Homuth G, Schmidt CO, Potash JB, DePaulo RJ, Goes FS, MacKinnon DF, Mondimore FM, Weissman MM, Shi J, Frye MA, Biernacka JM, Reif A, Witt SH, Kahn RR, Boks MM, Owen MJ, Gordon-Smith K, Mitchell BL, Martin NG, Medland SE, Jones L, Knowles JA, Levinson DF, O'Donovan MC, Lewis CM, Breen G, Werge T, Schork AJ, Ophoff R, Ripke S, and Loohuis LO
Abstract: Background: Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD)., Aims: Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis., Methods: Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses., Results: While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD., Conclusions: We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.
Published: 2024
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44. A genome-wide association study of antidepressant-induced mania.

Author: Zai CC, Squassina A, Tiwari AK, Pisanu C, Pinna M, Pinna F, Meloni A, Paribello P, Carpiniello B, Tondo L, Frye MA, Biernacka JM, Coombes BJ, Kennedy JL, and Manchia M
Subjects: Humans, Hypothalamo-Hypophyseal System, Pituitary-Adrenal System, Antidepressive Agents therapeutic use, Mania drug therapy, Genome-Wide Association Study
Abstract: Antidepressant-induced mania (AIM) is a side effect of antidepressant treatment that is characterized by mania or hypomania after the start of medication. It is likely polygenic, but its genetic component remains largely unexplored. We aim to conduct the first genome-wide association study of AIM in 814 bipolar disorder patients of European ancestry. We report no significant findings from our single-marker or gene-based analyses. Our polygenic risk score analyses also did not yield significant results with bipolar disorder, antidepressant response, or lithium response. Our suggestive findings on the hypothalamic-pituitary-adrenal axis and the opioid system in AIM require independent replications., Competing Interests: Declaration of Competing Interest CCZ, AKT, and JLK hold patents for genetic markers related to psychotropic medication outcomes. JLK is a member of the Scientific Advisory Board of Myriad Neuroscience. The other authors reported no conflicts of interest related to this study., (Copyright © 2023. Published by Elsevier Inc.)
Published: 2023
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45. Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation.

Author: Li D, Pain O, Fabbri C, Wong WLE, Lo CWH, Ripke S, Cattaneo A, Souery D, Dernovsek MZ, Henigsberg N, Hauser J, Lewis G, Mors O, Perroud N, Rietschel M, Uher R, Maier W, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Liu YL, Serretti A, Tsai SJ, Weinshilboum R, McIntosh AM, and Lewis CM
Abstract: Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I 2 =0%, subgroup difference p=0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes., Competing Interests: Conflict of Interest CML has served on the scientific advisory board for Myriad Neuroscience, and is a consultant for UCB. AS is or has been consultant/speaker for: Abbott, AbbVie, Angelini, AstraZeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, InnovaPharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi, and Servier. AMM has received research support from the Sackler Trust and speakers fees from Janssen and Illumina. MK has received grant funding from the Japanese Ministry of Health, Labor and Welfare, the Japan Society for the Promotion of Science, SENSHIN Medical Research Foundation, the Japan Research Foundation for Clinical Pharmacology and the Japanese Society of Clinical Neuropsychopharmacology and speaker’s honoraria from Sumitomo Pharma, Otsuka, Meiji-Seika Pharma, Eli Lilly, MSD K.K., Pfizer, Janssen Pharmaceutical, Shionogi, Mitsubishi Tanabe Pharma, Takeda Pharmaceutical, Lundbeck Viatris Inc, Eisai Co., Ltd. and Ono Pharmaceutical and participated in an advisory/review board for Otsuka, Sumitomo Pharma, Shionogi and Boehringer Ingelheim. DS has received grant/research support from GlaxoSmithKline and Lundbeck; and served as a consultant or on advisory boards for AstraZeneca, Bristol Myers Squibb, Eli Lilly, Janssen, and Lundbeck. CF was a speaker for Janssen. NP is or has been consultant/speaker for: Takeda, Janssen and Lundbeck All other authors report no biomedical financial interests or potential conflicts of interest.
Published: 2023
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46. Exploring the genetics of lithium response in bipolar disorders.

Author: Herrera-Rivero M, Adli M, Akiyama K, Akula N, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, Biernacka JM, Birner A, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark SR, Colom F, Cruceanu C, Czerski PM, Dalkner N, Degenhardt F, Del Zompo M, DePaulo JR, Etain B, Falkai P, Ferensztajn-Rochowiak E, Forstner AJ, Frank J, Frisén L, Frye MA, Fullerton JM, Gallo C, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hasler R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu YH, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kelsoe J, Kittel-Schneider S, Kuo PH, Kusumi I, König B, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Maj M, Manchia M, Marie-Claire C, Martinsson L, McCarthy MJ, McElroy SL, Millischer V, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Novák T, Nöthen MM, O'Donovan C, Ozaki N, Papiol S, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Richard-Lepouriel H, Roberts G, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schulte EC, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Streit F, Tekola-Ayele F, Thalamuthu A, Tortorella A, Turecki G, Veeh J, Vieta E, Viswanath B, Witt SH, Zandi PP, Alda M, Bauer M, McMahon FJ, Mitchell PB, Rietschel M, Schulze TG, and Baune BT
Abstract: Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II., Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism., Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II., Competing Interests: Competing interests Eduard Vieta has received grants and served as consultant, advisor or CME speaker for the following entities: AB-Biotics, Abbvie, Almirall, Allergan, Angelini, AstraZeneca, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Farmindustria, Ferrer, Forest Research Institute, Gedeon Richter, GH Research, Glaxo-Smith-Kline, Janssen, Lundbeck, Orion, Otsuka, Pfizer, Roche, Rovi, Sanofi-Aventis, Servier, Shire, Sunovion, Takeda, the Brain and Behaviour Foundation, the Spanish Ministry of Science and Innovation (CIBERSAM), the Stanley Medical Research Institute and Viatris. Michael Bauer has received grants from the Deutsche Forschungsgemeinschaft (DFG), and Bundesministeriums für Bildung und Forschung (BMBF), and served as consultant, advisor or CME speaker for the following entities: Allergan, Aristo, Janssen, Lilly, Lundbeck, neuraxpharm, Otsuka, Sandoz, Servier and Sunovion outside the submitted work. Sarah Kittel-Schneider has received grants and served as consultant, advisor or speaker for the following entities: Medice Arzneimittel Pütter GmbH and Takeda. Bernhard Baune has received grants and served as consultant, advisor or CME speaker for the following entities: AstraZeneca, Bristol-Myers Squibb, Janssen, Lundbeck, Otsuka, Servier, the National Health and Medical Research Council, the Fay Fuller Foundation, the James and Diana Ramsay Foundation. Tadafumi Kato received honoraria for lectures, manuscripts, and/or consultancy, from Kyowa Hakko Kirin Co, Ltd, Eli Lilly Japan K.K., Otsuka Pharmaceutical Co, Ltd, GlaxoSmithKline K.K., Taisho Toyama Pharmaceutical Co, Ltd, Dainippon Sumitomo Pharma Co, Ltd, Meiji Seika Pharma Co, Ltd, Pfizer Japan Inc., Mochida Pharmaceutical Co, Ltd, Shionogi & Co, Ltd, Janssen Pharmaceutical K.K., Janssen Asia Pacific, Yoshitomiyakuhin, Astellas Pharma Inc, Wako Pure Chemical Industries, Ltd, Wiley Publishing Japan, Nippon Boehringer Ingelheim Co Ltd, Kanae Foundation for the Promotion of Medical Science, MSD K.K., Kyowa Pharmaceutical Industry Co, Ltd and Takeda Pharmaceutical Co, Ltd. Tadafumi Kato also received a research grant from Takeda Pharmaceutical Co, Ltd. Peter Falkai has received grants and served as consultant, advisor or CME speaker for the following entities Abbott, GlaxoSmithKline, Janssen, Essex, Lundbeck, Otsuka, Gedeon Richter, Servier and Takeda as well as the German Ministry of Science and the German Ministry of Health. Eva Reininghaus has received grants and served as consultant, advisor or CME speaker for the following entities: Janssen and Institut Allergosan. Mikael Landén has received lecture honoraria from Lundbeck. Kazufumi Akiyama has received consulting honoraria from Taisho Toyama Pharmaceutical Co, Ltd. Scott Clark has received grants, or data and served as consultant, advisor or CME speaker for the following entities: Otsuka Austalia, Lundbeck Australia, Janssen-Cilag Australia, Servier Australia,Viatris. Bruno Etain received honoraria from Sanofi Aventis. The rest of authors have no conflicts of interest to disclose.
Published: 2023
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47. Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Author: Amare AT, Thalamuthu A, Schubert KO, Fullerton JM, Ahmed M, Hartmann S, Papiol S, Heilbronner U, Degenhardt F, Tekola-Ayele F, Hou L, Hsu YH, Shekhtman T, Adli M, Akula N, Akiyama K, Ardau R, Arias B, Aubry JM, Hasler R, Richard-Lepouriel H, Perroud N, Backlund L, Bhattacharjee AK, Bellivier F, Benabarre A, Bengesser S, Biernacka JM, Birner A, Marie-Claire C, Cervantes P, Chen HC, Chillotti C, Cichon S, Cruceanu C, Czerski PM, Dalkner N, Del Zompo M, DePaulo JR, Étain B, Jamain S, Falkai P, Forstner AJ, Frisen L, Frye MA, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Fallgatter AJ, Stegmaier S, Ethofer T, Biere S, Petrova K, Schuster C, Adorjan K, Budde M, Heilbronner M, Kalman JL, Kohshour MO, Reich-Erkelenz D, Schaupp SK, Schulte EC, Senner F, Vogl T, Anghelescu IG, Arolt V, Dannlowski U, Dietrich D, Figge C, Jäger M, Lang FU, Juckel G, Konrad C, Reimer J, Schmauß M, Schmitt A, Spitzer C, von Hagen M, Wiltfang J, Zimmermann J, Andlauer TFM, Fischer A, Bermpohl F, Ritter P, Matura S, Gryaznova A, Falkenberg I, Yildiz C, Kircher T, Schmidt J, Koch M, Gade K, Trost S, Haussleiter IS, Lambert M, Rohenkohl AC, Kraft V, Grof P, Hashimoto R, Hauser J, Herms S, Hoffmann P, Jiménez E, Kahn JP, Kassem L, Kuo PH, Kato T, Kelsoe J, Kittel-Schneider S, Ferensztajn-Rochowiak E, König B, Kusumi I, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Tortorella A, Manchia M, Martinsson L, McCarthy MJ, McElroy S, Colom F, Millischer V, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Nöthen MM, Novák T, O'Donovan C, Ozaki N, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schweizer BW, Severino G, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Maj M, Turecki G, Vieta E, Veeh J, Witt SH, Wright A, Zandi PP, Mitchell PB, Bauer M, Alda M, Rietschel M, McMahon FJ, Schulze TG, Clark SR, and Baune BT
Subjects: Humans, Female, Male, Adult, Middle Aged, Treatment Outcome, Bayes Theorem, Genome-Wide Association Study methods, Glutamic Acid metabolism, Cohort Studies, Lithium Compounds therapeutic use, Lithium Compounds pharmacology, Acetylcholine metabolism, Polymorphism, Single Nucleotide genetics, Antimanic Agents therapeutic use, Antimanic Agents pharmacology, Bipolar Disorder drug therapy, Bipolar Disorder genetics, Multifactorial Inheritance genetics, Lithium therapeutic use, Lithium pharmacology
Abstract: Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS ) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li + PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical (P = 9.8 × 10 - 12 , R 2 = 1.9%) and continuous (P = 6.4 × 10 - 9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, individuals in the 10 th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10 - 4 , R 2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment., (© 2023. The Author(s).)
Published: 2023
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48. Age-Dependent Sex Differences in the Prevalence of Selective Serotonin Reuptake Inhibitor Treatment: A Retrospective Cohort Analysis.

Author: Sanchez-Ruiz JA, Leibman NI, Larson NB, Jenkins GD, Ahmed AT, Nunez NA, Biernacka JM, Winham SJ, Weinshilboum RM, Wang L, Frye MA, and Ozerdem A
Subjects: Adult, Humans, Female, Male, United States epidemiology, Middle Aged, Retrospective Studies, Prevalence, Antidepressive Agents therapeutic use, Cohort Studies, Selective Serotonin Reuptake Inhibitors therapeutic use, Sex Characteristics
Abstract: Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.
Published: 2023
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49. The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people.

Author: Coombes BJ, Landi I, Choi KW, Singh K, Fennessy B, Jenkins GD, Batzler A, Pendegraft R, Nunez NA, Gao YN, Ryu E, Wickramaratne P, Weissman MM, Pathak J, Mann JJ, Smoller JW, Davis LK, Olfson M, Charney AW, and Biernacka JM
Subjects: Humans, Anxiety epidemiology, Anxiety genetics, Anxiety Disorders epidemiology, Anxiety Disorders genetics, Comorbidity, Multifactorial Inheritance, Risk Factors, Depression epidemiology, Depression genetics, Electronic Health Records
Abstract: Background: Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation., Methods: Diagnostic codes were extracted from electronic health records for four biobanks [ N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry., Results: In total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18-1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05-1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06-1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11-1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02-1.09), showing a genetic risk gradient across the conditions and the comorbidity., Conclusions: This study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.
Published: 2023
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50. Predictors of Functional Impairment in Bipolar Disorder: Results From 13 Cohorts From Seven Countries by the Global Bipolar Cohort Collaborative.

Author: Burdick KE, Millett CE, Yocum AK, Altimus CM, Andreassen OA, Aubin V, Belzeaux R, Berk M, Biernacka JM, Blumberg HP, Cleare AJ, Diaz-Byrd C, Dubertret C, Etain B, Eyler LT, Forester BP, Fullerton JM, Frye MA, Gard S, Godin O, Haffen E, Klaus F, Lagerberg TV, Leboyer M, Martinez-Aran A, McElroy S, Mitchell PB, Olie E, Olorunfemi P, Passerieux C, Peters AT, Pham DL, Polosan M, Potter JR, Sajatovic M, Samalin L, Schwan R, Shanahan M, Solé B, Strawbridge R, Stuart AL, Torres I, Ueland T, Vieta E, Williams LJ, Wrobel AL, Yatham LN, Young AH, Nierenberg AA, and McInnis MG
Abstract: Objectives: Persistent functional impairment is common in bipolar disorder (BD) and is influenced by a number of demographic, clinical, and cognitive features. The goal of this project was to estimate and compare the influence of key factors on community function in multiple cohorts of well-characterized samples of individuals with BD., Methods: Thirteen cohorts from 7 countries included n = 5882 individuals with BD across multiple sites. The statistical approach consisted of a systematic uniform application of analyses across sites. Each site performed a logistic regression analysis with empirically derived "higher versus lower function" as the dependent variable and selected clinical and demographic variables as predictors., Results: We found high rates of functional impairment, ranging from 41 to 75%. Lower community functioning was associated with depressive symptoms in 10 of 12 of the cohorts that included this variable in the analysis. Lower levels of education, a greater number of prior mood episodes, the presence of a comorbid substance use disorder, and a greater total number of psychotropic medications were also associated with low functioning., Conclusions: The bipolar clinical research community is poised to work together to characterize the multi-dimensional contributors to impairment and address the barriers that impede patients' complete recovery. We must also identify the core features which enable many to thrive and live successfully with BD. A large-scale, worldwide, prospective longitudinal study focused squarely on BD and its heterogeneous presentations will serve as a platform for discovery and promote major advances toward optimizing outcomes for every individual with this illness.Reprinted from Bipolar Disord 2022; 24:709-719 , with permission from John Wiley and Sons. Copyright © 2022., (Copyright © 2023 by the American Psychiatric Association.)
Published: 2023
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