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1. 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

2. 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

3. 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

4. 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

5. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

Author: Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, 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, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, 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 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, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, Borglum, AD, Glanville, KP, Coleman, JR, Hanscombe, KB, Euesden, J, Choi, SW, Purves, KL, Breen, G, Air, TM, Andlauer, TFM, Baune, BT, Binder, EB, Blackwood, DHR, Boomsma, D, Buttenschon, HN, Colodro-Conde, L, Dannlowski, U, Direk, N, Dunn, EC, Forstner, AJ, de Geus, EJC, Grabe, HJ, Hamilton, SP, Jones, I, Jones, LA, Knowles, JA, Kutalik, Z, Levinson, DF, Lewis, G, Lind, PA, Lucae, S, Magnusson, PK, McGuffin, P, McIntosh, AM, Milaneschi, Y, Mors, O, Mostafavi, S, Mueller-Myhsok, B, Pedersen, NL, Penninx, BWJH, Potash, JB, Preisig, M, Ripke, S, Shi, J, Shyn, S, Smoller, JW, Streit, F, Sullivan, PF, Tiemeier, H, Uher, R, Van der Auwera, S, Weissman, MM, O'Reilly, PF, Lewis, CM, Wray, NR, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Bryois, J, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Dolan, C, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jorgenson, E, Kohane, IS, Kraft, J, Kretzschmar, WW, Li, Y, MacIntyre, DJ, MacKinnon, DF, Maier, RM, Maier, W, Marchini, J, Mbarek, H, McGrath, P, Medland, SE, Mehta, D, Middeldorp, CM, Mihailov, E, Milani, L, Mondimore, FM, Montgomery, GW, 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, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, 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 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, Berger, K, Cichon, S, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Li, QS, Madden, PAF, Martin, NG, Metspalu, A, Mortensen, PB, Nordentoft, M, Noethen, MM, O'Donovan, MC, Paciga, SA, Perlis, RH, Porteous, DJ, Rietschel, M, Schaefer, C, Schulze, TG, Stefansson, K, Voelzke, H, Werge, T, and Borglum, AD
Abstract: BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
Published: 2020

6. Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Author: Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, 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, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, 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 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, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, 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, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, Sullivan, PF, Coleman, JRI, Peyrot, WJ, Purves, KL, Davis, KAS, Rayner, C, Choi, SW, Hubel, C, Gaspar, HA, Kan, C, Van der Auwera, S, Adams, MJ, Lyall, DM, Choi, KW, Dunn, EC, Vassos, E, Danese, A, Maughan, B, Grabe, HJ, Lewis, CM, O'Reilly, PF, McIntosh, AM, Smith, DJ, Wray, NR, Hotopf, M, Eley, TC, Breen, G, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Bryois, J, Buttenschon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, T-K, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Howard, DM, Ising, M, Jansen, R, Jones, I, Jones, LA, Jorgenson, E, Knowles, JA, Kohane, IS, Kraft, J, Kretzschmar, WW, 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, Pistis, G, Posthuma, D, Quiroz, JA, Qvist, P, Rice, JP, Riley, BP, Rivera, M, Mirza, SS, Schoevers, R, Schulte, EC, Shen, L, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, 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 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, DI, Cichon, S, Dannlowski, U, de Geus, EJC, DePaulo, JR, Domenici, E, Domschke, K, Esko, T, Hamilton, SP, Hayward, C, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, 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, Volzke, H, Weissman, MM, Werge, T, Levinson, DF, Borglum, AD, and Sullivan, PF
Abstract: Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.
Published: 2020

7. A pilot fMRI study of lithium response in bipolar disorder

Author: Kelly Rootes-Murdy, DePaulo, Fernando S. Goes, Mondimore Fm, Kara Glazer, Peter P. Zandi, Pamela B. Mahon, and Arnold Bakker
Subjects: Lithium (medication), business.industry, Neuroscience (miscellaneous), medicine.disease, Article, Psychiatry and Mental health, Text mining, medicine, Radiology, Nuclear Medicine and imaging, Bipolar disorder, Psychology, business, Neuroscience, medicine.drug
Published: 2019

8. 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

9. Evidence for increased genetic risk load for major depression in patients assigned to electroconvulsive therapy

Author: Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, 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, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, 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, O'Reilly, PF, 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, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, 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, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, 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, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, Sullivan, PF, Foo, JC, Streit, F, Frank, J, Witt, SH, Treutlein, J, Baune, BT, Moebus, S, Joeckel, K-H, Forstner, AJ, Noethen, MM, Rietschel, M, Sartorius, A, Kranaster, L, 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, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, 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, O'Reilly, PF, 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, Shi, J, Shyn, SI, Sigurdsson, E, Sinnamon, GCB, Smit, JH, Smith, DJ, Stefansson, H, Steinberg, S, Strohmaier, J, Tansey, KE, Teismann, H, Teumer, A, Thompson, W, Thomson, PA, Thorgeirsson, TE, Traylor, M, 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, Wu, Y, Xi, HS, Yang, J, Zhang, F, Arolt, V, Berger, K, Boomsma, DI, 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, O'Donovan, MC, Paciga, SA, Pedersen, NL, Penninx, BWJH, Perlis, RH, Porteous, DJ, Potash, JB, Preisig, M, Schaefer, C, Schulze, TG, Smoller, JW, Stefansson, K, Tiemeier, H, Uher, R, Voelzke, H, Weissman, MM, Werge, T, Lewis, CM, Levinson, DF, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment-resistant depression; disorder severity and unfavorable treatment outcomes are shown to be influenced by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment and response/nonresponse are associated with an increased genetic burden for major depression (MD) using polygenic risk score (PRS), which summarize the contribution of disease-related common risk variants. Fifty-one psychiatric inpatients suffering from a major depressive episode underwent ECT. MD-PRS were calculated for these inpatients and a separate population-based sample (n = 3,547 healthy; n = 426 self-reported depression) based on summary statistics from the Psychiatric Genomics Consortium MDD-working group (Cases: n = 59,851; Controls: n = 113,154). MD-PRS explained a significant proportion of disease status between ECT patients and healthy controls (p = .022, R2 = 1.173%); patients showed higher MD-PRS. MD-PRS in population-based depression self-reporters were intermediate between ECT patients and controls (n.s.). Significant associations between MD-PRS and ECT response (50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate that ECT cohorts show an increased genetic burden for MD and are consistent with the hypothesis that treatment-resistant MD patients represent a subgroup with an increased genetic risk for MD. Larger samples are needed to better substantiate these findings.
Published: 2019

10. Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Author: Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, 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, O'Reilly, PF, 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, Shi, J, 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, 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, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, 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, Breen, G, Borglum, ASD, Sullivan, PF, Arnau-Soler, A, Macdonald-Dunlop, E, Adams, MJ, Clarke, T-K, MacIntyre, DJ, Milburn, K, Navrady, L, Hayward, C, McIntosh, AM, Thomson, PA, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, S-A, Baekvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenscon, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Coleman, JR, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Rawford, GEC, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, C, Dunn, EC, Eley, TC, Escott-Price, V, Kiadeh, FFH, Finucane, HK, Foo, JC, Forstner, AJ, Frank, J, Gaspar, HA, Gill, M, Goes, FS, Gordon, SD, Grove, J, Hall, LS, 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, O'Reilly, PF, 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, Shi, J, 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, 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, Heath, AC, Kendler, KS, Kloiber, S, Lewis, G, Li, QS, Lucae, S, Madden, PAF, Magnusson, PK, Martin, NG, 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, Breen, G, Borglum, ASD, and Sullivan, PF
Abstract: Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.
Published: 2019

11. Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Author: Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, 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, 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, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, 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, O'Reilly, PF, 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, Shi, J, 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, Breen, G, Borglum, AD, Sullivan, PF, Czamara, D, Eraslan, G, Page, CM, Lahti, J, Lahti-Pulkkinen, M, Hamalainen, E, Kajantie, E, Laivuori, H, Villa, PM, Reynolds, RM, Nystad, W, Haberg, SE, London, SJ, O'Donnell, KJ, Garg, E, Meaney, MJ, Entringer, S, Wadhwa, PD, Buss, C, Jones, MJ, Lin, DTS, MacIsaac, JL, Kobor, MS, Koen, N, Zar, HJ, Koenen, KC, Dalvie, S, Stein, DJ, Kondofersky, I, Mueller, NS, Theis, FJ, Raikkonen, K, Binder, EB, 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, 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, Hall, LS, Hansen, CS, Hansen, TF, Herms, S, Hickie, IB, Hoffmann, P, Homuth, G, Horn, C, Hottenga, J-J, Hougaard, DM, Ising, M, Jansen, R, 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, O'Reilly, PF, 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, Shi, J, 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, Breen, G, Borglum, AD, and Sullivan, PF
Abstract: Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Published: 2019

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

Author: de Jong, S, Diniz, MJA, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, SA, Bækvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschøn, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, TK, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, 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, JJ, 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, de Jong, S, Diniz, MJA, Saloma, A, Gadelha, A, Santoro, ML, Ota, VK, Noto, C, Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, Adams, MJ, Agerbo, E, Air, TM, Andlauer, TFM, Bacanu, SA, Bækvad-Hansen, M, Beekman, ATF, Bigdeli, TB, Binder, EB, Blackwood, DHR, Bryois, J, Buttenschøn, HN, Bybjerg-Grauholm, J, Cai, N, Castelao, E, Christensen, JH, Clarke, TK, Coleman, JRI, Colodro-Conde, L, Couvy-Duchesne, B, Craddock, N, Crawford, GE, Davies, G, Deary, IJ, Degenhardt, F, Derks, EM, Direk, N, Dolan, CV, 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, JJ, 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, and Painter, JN
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

13. 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

14. 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

15. 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

16. 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

17. Mood-incongruent psychotic features in bipolar disorder: familial aggregation and suggestive linkage to 2p11-q14 and 13q21-33.

Author: Goes FS, Zandi PP, Miao K, McMahon FJ, Steele J, Willour VL, MacKinnon DF, Mondimore FM, Schweizer B, Nurnberger JI Jr., Rice JP, Scheftner W, Coryell W, Berrettini WH, Kelsoe JR, Byerley W, Murphy DL, Gershon ES, DePaulo JR Jr., and McInnis MG
Abstract: Objective: Mood-incongruent psychotic features in bipolar disorder may signify a more severe form of the illness and might represent phenotypic manifestations of susceptibility genes shared with schizophrenia. This study attempts to characterize clinical correlates, familial aggregation, and genetic linkage in subjects with these features.Method: Subjects were drawn from The National Institute of Mental Health (NIMH) Genetics Initiative Bipolar Disorder Collaborative cohort, consisting of 708 families recruited at 10 academic medical centers. Subjects with mood-incongruent and mood-congruent psychotic features were compared on clinical variables. Familial aggregation was tested using a proband-predictive model and generalized estimating equations. A genome-wide linkage scan incorporating a mood-incongruence covariate was performed.Results: Mood-incongruent psychotic features were associated with an increased rate of hospitalization and attempted suicide. A proband with mood-incongruence predicted mood-incongruence in relatives with bipolar I disorder when compared with all other subjects and when compared with subjects with mood-congruent psychosis. The presence of mood-incongruent psychotic features increased evidence for linkage on chromosomes 13q21-33 and 2p11-q14. These logarithm of the odds ratio (LOD) scores and their increase from baseline met empirical genome-wide suggestive criteria for significance.Conclusions: Mood-incongruent psychotic features showed evidence of a more severe course, familial aggregation, and suggestive linkage to two chromosomal regions previously implicated in major mental illness susceptibility. The 13q21-33 finding supports prior evidence of bipolar disorder/schizophrenia overlap in this region, while the 2p11-q14 finding is, to the authors' knowledge, the first to suggest that this schizophrenia linkage region might also harbor a bipolar disorder susceptibility gene. [ABSTRACT FROM AUTHOR]
Published: 2007
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18. Eating and feeding difficulties in patients with intellectual and developmental disabilities: four cases.

Author: Gallucci G, Andersen AE, Hackerman F, and Mondimore FM
Abstract: Eating problems in patients with intellectual or developmental disabilities represent unique challenges for the clinician. We present four cases of eating problems in patients with intellectual and developmental disabilities. The cases illustrate the complexity of these eating problems when associated with cognitive and/or developmental disabilities. [ABSTRACT FROM AUTHOR]
Published: 2003

19. Never-ending winter: chronic depression.

Author: Mondimore FM
Published: 2007

20. 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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21. 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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22. 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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23. 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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24. 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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25. Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach - CORRIGENDUM.

Author: Cearns M, Amare AT, Schubert KO, Thalamuthu A, Frank J, Streit F, Adli M, Akula N, Akiyama K, Ardau R, Arias B, Aubry J, Backlund L, Bhattacharjee AK, Bellivier F, Benabarre A, Bengesser S, Biernacka JM, Birner A, Brichant-Petitjean C, Cervantes P, Chen H, Chillotti C, Cichon S, Cruceanu C, Czerski PM, Dalkner N, Dayer A, Degenhardt F, Zompo MD, 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, Heilbronner U, Herms S, Hoffmann P, Hofmann A, Hou L, Hsu YH, 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, Maj M, 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, Millischer V, 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, TekolaAyele 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, Clark SR, and Baune BT
Published: 2022
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26. Correction: 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 JM, Backlund L, Bhattacharjee AK, Bellivier F, Benabarre A, Bengesser S, Biernacka JM, Birner A, Marie-Claire C, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark SR, Cruceanu C, Czerski PM, Dalkner N, Dayer A, Degenhardt F, 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, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu YH, Jamain S, 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, Maj M, 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, 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
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27. Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study.

Author: Coombes BJ, Millischer V, Batzler A, Larrabee B, Hou L, Papiol S, Heilbronner U, Adli M, Akiyama K, Akula N, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bauer M, Baune BT, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, 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, Étain B, Falkai P, Ferensztajn-Rochowiak E, Forstner AJ, Frisen L, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hauser J, Herms S, Hoffmann P, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kelsoe JR, Kittel-Schneider S, König B, Kuo PH, Kusumi I, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Maj M, Manchia M, Martinsson L, McCarthy MJ, McElroy SL, Mitchell PB, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Nöthen MM, Novák T, O'Donovan C, Osby U, Ozaki N, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Rietschel M, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Tortorella A, Turecki G, Vieta E, Witt SH, Zandi PP, Fullerton JM, Alda M, Frye MA, Schulze TG, McMahon FJ, and Biernacka JM
Abstract: Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients ( N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD., Competing Interests: Eduard Vieta has received grants and served as consultant, advisor, or CME speaker for the following entities: AB-Biotics, Allergan, Angelini, AstraZeneca, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Farmindustria, Ferrer, Forest Research Institute, Gedeon Richter, GlaxoSmithKline, Janssen, Lundbeck, Otsuka, Pfizer, Roche, Sanofi-Aventis, Servier, Shire, Sunovion, Takeda, the Brain and Behaviour Foundation, the Spanish Ministry of Science and Innovation (CIBERSAM), and the Stanley Medical Research Institute. Michael Bauer has received grants from the Deutsche Forschungsgemeinschaft and Bundesministeriums für Bildung und Forschung 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 Shire. 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, and 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. T.K. 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 declares that, over the past 36 months, he has received lecture honoraria from Lundbeck and served as scientific consultant for EPID Research Oy; no other equity ownership, profit-sharing agreements, royalties, or patent. Kazufumi Akiyama has received consulting honoraria from Taisho Toyama Pharmaceutical Co., Ltd. The other authors have no other conflict of interest to disclose., (Copyright © 2021 by S. Karger AG, Basel.)
Published: 2021
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28. 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 JM, Backlund L, Bhattacharjee AK, Bellivier F, Benabarre A, Bengesser S, Biernacka JM, Birner A, Marie-Claire C, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark SR, Cruceanu C, Czerski PM, Dalkner N, Dayer A, Degenhardt F, 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, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu YH, Jamain S, 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, Maj M, 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, 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
Subjects: Depression, Genetic Predisposition to Disease, Humans, Lithium therapeutic use, Multifactorial Inheritance, Risk Factors, Bipolar Disorder drug therapy, Bipolar Disorder genetics, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics, Schizophrenia drug therapy, Schizophrenia genetics
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., (© 2021. The Author(s).)
Published: 2021
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29. 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, 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, Spadoni JL, Boukouaci W, Richard JR, Le Corvoisier P, Barrau C, Zagury JF, Leboyer M, and Tamouza R
Subjects: Adult, Alleles, Bipolar Disorder drug therapy, Female, Gene Frequency, Genetic Variation, Genotype, Haplotypes, Humans, Male, Middle Aged, Pharmacogenetics, Treatment Outcome, Bipolar Disorder genetics, Genetic Predisposition to Disease, HLA-DQ beta-Chains genetics, HLA-DRB1 Chains genetics, Lithium therapeutic use
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., (© 2021. The Author(s).)
Published: 2021
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30. 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 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, Hofmann A, Jiménez E, Kahn JP, Kassem L, Kuo PH, Kato T, Kelsoe JR, 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 SL, 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, 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
Subjects: Depression, Genome-Wide Association Study, Humans, Lithium therapeutic use, Bipolar Disorder drug therapy, Bipolar Disorder genetics, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics
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 findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2021
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31. Comparing sensitivity to change using the 6-item versus the 17-item Hamilton depression rating scale in the GUIDED randomized controlled trial.

Author: Dunlop BW, Parikh SV, Rothschild AJ, Thase ME, DeBattista C, Conway CR, Forester BP, Mondimore FM, Shelton RC, Macaluso M, Logan J, Traxler P, Li J, Johnson H, and Greden JF
Subjects: Double-Blind Method, Humans, Treatment Outcome, Depressive Disorder, Major diagnosis, Pharmacogenetics, Psychiatric Status Rating Scales, Randomized Controlled Trials as Topic
Abstract: Background: Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown., Methods: This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6., Results: At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms., Conclusions: The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms., Trial Registration: Clinicaltrials.gov: NCT02109939. Registered 10 April 2014.
Published: 2019
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32. Impact of Pharmacogenomics on Clinical Outcomes for Patients Taking Medications With Gene-Drug Interactions in a Randomized Controlled Trial.

Author: Thase ME, Parikh SV, Rothschild AJ, Dunlop BW, DeBattista C, Conway CR, Forester BP, Mondimore FM, Shelton RC, Macaluso M, Li J, Brown K, Jablonski MR, and Greden JF
Subjects: Adult, Depressive Disorder, Major genetics, Female, Genotype, Humans, Male, Middle Aged, Phenotype, Treatment Outcome, Antidepressive Agents therapeutic use, Depressive Disorder, Major drug therapy, Pharmacogenetics
Abstract: Objective: The objective of the Genomics Used to Improve DEpression Decisions (GUIDED) trial was to evaluate the utility of pharmacogenomic testing to improve outcomes among patients with major depressive disorder (MDD) who had not responded to at least 1 prior medication trial. The objective of the present analysis was to assess outcomes for the subset of patients expected to benefit from combinatorial pharmacogenomic testing because they were taking medications with predicted gene-drug interactions., Methods: Participants (enrolled from April 14, 2014, to February 10, 2017) had an inadequate response to at least 1 psychotropic medication in the current episode of MDD. Patients were randomized to treatment as usual (TAU) or the guided-care arm, in which clinicians had access to a combinatorial pharmacogenomic test report to inform medication selection. Patients and raters were blinded to study arm through week 8. The following outcomes were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17): symptom improvement (percent change in HDRS-17 score), response (≥ 50% decrease in HDRS-17 score), and remission (HDRS-17 score ≤ 7). In the GUIDED trial, the primary endpoint of symptom improvement did not reach significance in the intent-to-treat cohort (P = .069). Here, a post hoc analysis of patients who were taking medications subject to gene-drug interactions at baseline as predicted by combinatorial pharmacogenomic testing (N = 912) is presented., Results: Among participants taking medications subject to gene-drug interactions at baseline, outcomes at week 8 were significantly improved for those in the guided-care arm compared to TAU (symptom improvement: 27.1% versus 22.1%, P = .029; response: 27.0% versus 19.0%, P = .008; remission: 18.2% versus 10.7%, P = .003). When patients who switched medications were assessed, all outcomes were significantly improved in the guided-care arm compared to TAU (P = .011 for symptom improvement, P = .011 for response, P = .008 for remission)., Conclusions: By identifying and focusing on the patients with predicted gene-drug interactions, use of a combinatorial pharmacogenomic test significantly improved outcomes among patients with MDD who had at least 1 prior medication failure., Trial Registration: ClinicalTrials.gov identifier: NCT02109939., (© Copyright 2019 Physicians Postgraduate Press, Inc.)
Published: 2019
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33. Response to: Goldberg et al. and Severance et al. Letters to the Editor: The clinical significance of improving remission over standard of care - The reality of treatment resistant-based therapies.

Author: Greden JF, Parikh SV, Rothschild AJ, Thase ME, Dunlop BW, DeBattista C, Conway CR, Forester BP, Mondimore FM, Shelton RC, Macaluso M, Li J, Brown K, Gilbert A, Burns L, Jablonski MR, and Dechairo B
Subjects: Humans, Pharmacogenetics, Research Design, Standard of Care, Depressive Disorder, Major
Published: 2019
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34. A pilot fMRI study of lithium response in bipolar disorder.

Author: Rootes-Murdy K, Glazer K, Mondimore FM, Goes FS, Zandi PP, Bakker A, DePaulo JR Jr, and Mahon PB
Published: 2019
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35. Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study.

Author: Greden JF, Parikh SV, Rothschild AJ, Thase ME, Dunlop BW, DeBattista C, Conway CR, Forester BP, Mondimore FM, Shelton RC, Macaluso M, Li J, Brown K, Gilbert A, Burns L, Jablonski MR, and Dechairo B
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Antidepressive Agents administration & dosage, Antidepressive Agents adverse effects, Cohort Studies, Cytochrome P-450 Enzyme System genetics, Double-Blind Method, Female, Humans, Male, Middle Aged, Receptor, Serotonin, 5-HT2A genetics, Remission Induction, Serotonin Plasma Membrane Transport Proteins genetics, Selective Serotonin Reuptake Inhibitors pharmacology, Young Adult, Antidepressive Agents therapeutic use, Depressive Disorder, Major metabolism, Outcome Assessment, Health Care, Pharmacogenomic Testing
Abstract: Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939)., (Copyright © 2019. Published by Elsevier Ltd.)
Published: 2019
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36. 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 TF, 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, Reich-Erkelenz D, Reif A, Reimer J, Reininghaus E, Reitt M, Ripke S, Rouleau GA, Rybakowski JK, Schalling M, Scherk H, Schmauß M, Schofield PR, Schubert KO, Schulte EC, Schulz S, Senner F, Severino G, Shekhtman T, Shilling PD, Simhandl C, Slaney CM, Spitzer C, Squassina A, Stamm T, Stegmaier S, Stierl S, Stopkova P, Thiel A, Tighe SK, Tortorella A, Turecki G, Vieta E, Veeh J, von Hagen M, Wigand ME, Wiltfang J, Witt S, Wright A, Zandi PP, Zimmermann J, Nöthen M, Rietschel M, and Schulze TG
Subjects: Adolescent, Adult, Age Factors, Child, Female, Humans, Male, Middle Aged, Multifactorial Inheritance, Phenotype, Bipolar Disorder genetics, Schizophrenia genetics
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., (© 2018 The Authors. Bipolar Disorders Published by John Wiley & Sons Ltd.)
Published: 2019
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37. 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, López Jaramillo CA, 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, Young LT, Zandi PP, Potash JB, DePaulo JR, Bauer M, Reininghaus E, Novák T, Aubry JM, Maj M, Baune BT, Mitchell PB, Vieta E, Frye MA, Rybakowski JK, Kuo PH, Kato T, Grigoroiu-Serbanescu M, Reif A, Del Zompo M, Bellivier F, Schalling M, Wray NR, Kelsoe JR, Alda M, McMahon FJ, Schulze TG, Rietschel M, Nöthen MM, and Cichon S
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 in larger GWAS samples of BD and lithium response is warranted.
Published: 2018
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38. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.

Author: Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, Adams MJ, Agerbo E, Air TM, Andlauer TMF, Bacanu SA, Bækvad-Hansen M, Beekman AFT, Bigdeli TB, Binder EB, Blackwood DRH, Bryois J, Buttenschøn HN, Bybjerg-Grauholm J, Cai N, Castelao E, Christensen JH, Clarke TK, Coleman JIR, Colodro-Conde L, Couvy-Duchesne B, Craddock N, Crawford GE, Crowley CA, Dashti HS, Davies G, Deary IJ, Degenhardt F, Derks EM, Direk N, Dolan CV, Dunn EC, Eley TC, Eriksson N, Escott-Price V, Kiadeh FHF, Finucane HK, Forstner AJ, Frank J, Gaspar HA, Gill M, Giusti-Rodríguez P, Goes FS, Gordon SD, Grove J, Hall LS, Hannon E, Hansen CS, Hansen TF, Herms S, Hickie IB, Hoffmann P, Homuth G, Horn C, Hottenga JJ, Hougaard DM, Hu M, Hyde CL, Ising M, Jansen R, Jin F, Jorgenson E, Knowles JA, Kohane IS, Kraft J, Kretzschmar WW, Krogh J, Kutalik Z, Lane JM, Li Y, Li Y, Lind PA, Liu X, Lu L, 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, Mill J, Mondimore FM, Montgomery GW, Mostafavi S, Mullins N, Nauck M, Ng B, Nivard MG, Nyholt DR, O'Reilly PF, Oskarsson H, Owen MJ, Painter JN, Pedersen CB, Pedersen MG, Peterson RE, Pettersson E, Peyrot WJ, Pistis G, Posthuma D, Purcell SM, Quiroz JA, Qvist P, Rice JP, Riley BP, Rivera M, Saeed Mirza S, Saxena R, Schoevers R, Schulte EC, Shen L, Shi J, Shyn SI, Sigurdsson E, Sinnamon GBC, Smit JH, Smith DJ, Stefansson H, Steinberg S, Stockmeier CA, Streit F, Strohmaier J, Tansey KE, Teismann H, Teumer A, Thompson W, Thomson PA, Thorgeirsson TE, Tian C, 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 DI, Cichon S, Dannlowski U, de Geus ECJ, DePaulo JR, Domenici E, Domschke K, Esko T, Grabe HJ, Hamilton SP, Hayward C, Heath AC, Hinds DA, Kendler KS, Kloiber S, Lewis G, Li QS, Lucae S, Madden PFA, Magnusson PK, Martin NG, McIntosh AM, Metspalu A, Mors O, Mortensen PB, Müller-Myhsok B, Nordentoft M, Nöthen 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, Völzke H, Weissman MM, Werge T, Winslow AR, Lewis CM, Levinson DF, Breen G, Børglum AD, and Sullivan PF
Subjects: Case-Control Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Humans, Male, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia genetics, Depressive Disorder, Major genetics, Multifactorial Inheritance
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
Published: 2018
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39. Mobile technology for medication adherence in people with mood disorders: A systematic review.

Author: Rootes-Murdy K, Glazer KL, Van Wert MJ, Mondimore FM, and Zandi PP
Subjects: Cell Phone, Cost-Benefit Analysis, Humans, Medication Adherence, Mobile Applications, Mood Disorders drug therapy
Abstract: Background: Medication non-adherence is a critical challenge for many patients diagnosed with mood disorders (Goodwin and Jamison, 1990). There is a need for alternative strategies that improve adherence among patients with mood disorders that are cost-effective, able to reach large patient populations, easy to implement, and that allow for communication with patients outside of in-person visits. Technology-based approaches to promote medication adherence are increasingly being explored to address this need. The aim of this paper is to provide a systematic review of the use of mobile technologies to improve medication adherence in patients with mood disorders., Methods: A total of nine articles were identified as describing mobile technology targeting medication adherence in mood disorder populations., Results: Results showed overall satisfaction and feasibility of mobile technology, and reduction in mood symptoms; however, few examined effectiveness of mobile technology improving medication adherence through randomized control trials., Limitations: Given the limited number of studies, further research is needed to determine long term effectiveness., Conclusions: Mobile technologies has the potential to improve medication adherence and can be further utilized for symptom tracking, side effects tracking, direct links to prescription refills, and provide patients with greater ownership over their treatment progress., (Copyright © 2017 Elsevier B.V. All rights reserved.)
Published: 2018
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40. 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, Vieta E, Volkert J, Witt S, Wright A, Zandi PP, Mitchell PB, Bauer M, Alda M, Rietschel M, McMahon FJ, Schulze TG, and Baune BT
Subjects: Adult, Bipolar Disorder drug therapy, Female, Genetic Load, Genotype, Humans, Male, Middle Aged, Schizophrenia drug therapy, Schizophrenic Psychology, Treatment Outcome, Bipolar Disorder genetics, Genome-Wide Association Study, HLA Antigens genetics, Inflammation genetics, Lithium Carbonate therapeutic use, Multifactorial Inheritance genetics, Schizophrenia genetics
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 lithium was 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% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines., Conclusions and Relevance: This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.
Published: 2018
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41. 2018 American Society of Consultant Pharmacists Annual Meeting & Exhibition.

Author: Bridgeman M, Prete D, Rolston N, Abazia D, Sturgill M, Finn L, Summers D, Marvanova M, Henkel P, Thompson J, Dewey M, Friesner D, Marvanova M, Alessi C, Cuellar L, Yamagishi L, O'Neil C, Erickson O, Mazzei K, Kamal K, Early N, Bainter B, Hanson L, Schmitz E, Loomis A, Norberto M, Hume A, Meyer M, Batra R, Likar D, Enguidanos S, Liu C, Kotansky B, Fisher A, Ruby CM, Pruskowski J, Karim SNA, Yong BSW, Alessi C, Cuellar L, Slattum P, Crouse E, Delafuente J, Donohoe K, Ogbonna K, Peron E, Powers K, Price E, Zimmerman K, Rahim S, Gendron T, Slattum P, Donohoe K, Cho C, Zimmerman K, Crouse E, Peron E, Powers K, Price E, Slattum P, Donohoe K, Elliott L, Minter C, Morin M, Marshall L, Stevens G, Cordaro C, Hill M, Nagy K, Kroustos KR, Sobota KF, Mahan R, Bailey T, Ioannou K, Mansour D, Thompson T, Chatellier K, Schwenk A, Ruby C, Chen TS, Li S, James M, Spilios M, Leschak A, Levine A, Forgette S, Oluigbo N, Szollosi D, Avalime D, Weaver SB, Maneno M, Ettienne E, Yi JY, Hart L, Gray S, Ozalas S, Miller K, Dave R, Bork J, Emmelhainz J, Adams K, Postolski J, Willoughby M, Feldman E, Braham K, Miller C, Barbagallo D, Seabury R, Noviasky J, Alessi C, Cuellar L, Dabhi J, Bartlett D, Le T, Simoni-Wastila L, Kuzucan A, Simoni-Wastila L, Le T, Park S, Simoni-Wastila L, Le T, Park S, Choi M, Simoni-Wastila L, Park S, Le T, Choi M, Simoni-Wastila L, Khokhar B, Choi M, Le T, Simoni-Wastila L, Brody P, Hejna M, Mason J, Graham M, Micceri J, Lypska R, Quinn B, Wilson H, Wahler R, Aloyo M, Tomm V, Hill A, Obringer A, Butterfoss K, Blak J, Balcer R, Boza J, Foster A, Shafique E, Kleven C, Wigle P, Brown B, Alessi C, Cuellar L, Meyer K, Mobley-Bukstein W, Singh H, Perez E, Mira AE, Kuehner W, Czechowski L, Cook H, Brandt N, Parson J, Fornaro R, Brandt N, Claeys K, Zarowitz B, Mansour D, McFadden C, Simpkins S, Ojowa F, Klutts A, Holmes S, Smith E, Cornman JR, Doran K, Resnick B, Brandt N, Umeozulu C, Williams A, Brandt N, Hennawi G, Thomas D, Gerber DK, Meyer K, Sharma K, Cooke C, Howard A, Chater R, Vogler A, Brandt N, Kennett-Hayes K, Elliott L, Engelbert J, Hargrave E, Bambico C, Patel K, Warriner C, Slattum P, Desai NR, Rowan CG, Alvarez P, Fogli J, Toto RD, Desai NR, Alvarez P, Fogli J, Reed P, Owens MK, Greden JF, Rothschild AJ, Zandy S, Thase M, Dunlop BW, DeBattista C, Conway CR, Forester BP, Mondimore FM, Shelton RC, Li J, Gilbert A, Burns L, Jablonski M, Dechairo B, Parikh S, Donohue J, Feldman G, Sethi S, Barnes C, Pendyala S, Bourdet D, Ferguson G, Barnes C, Pendyala S, Crater G, Fogli J, Mayo M, Gross C, Miyawa J, Ono R, Woods S, Garza D, Panov N, Fogli J, Moran E, Sabesan V, Wertman J, and Ngim K
Abstract: Poster abstracts are evaluated based on the following criteria: significance of the problem to healthy aging or medication management; innovativeness of ideas, methods, and/or approach; methodological rigor of methods and approach; presentation of finding; implications identified for future research, practice, and/or policy; and clarity of writing. Submissions are not evaluated through the peer-reviewed process used by The Consultant Pharmacist . Industry support is indicated, where applicable. Presenting author is in italics. The poster abstract presentation is supported by the ASCP Foundation.
Published: 2017

42. 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 Jr, Nwulia EA, Ösby U, Pfennig A, Potash JB, Propping P, Reif A, Reininghaus E, Rice J, Rietschel M, Rouleau GA, Rybakowski JK, Schalling M, Scheftner WA, Schofield PR, Schork NJ, Schulze TG, Schumacher J, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Simhandl C, Slaney CM, Smith EN, Squassina A, Stamm T, Stopkova P, Streit F, Strohmaier J, Szelinger S, Tighe SK, Tortorella A, Turecki G, Vieta E, Volkert J, Witt SH, Wright A, Zandi PP, Zhang P, Zollner S, and McMahon FJ
Subjects: Female, Humans, Male, Bipolar Disorder genetics, Chromosomes, Human, X genetics, Genome-Wide Association Study, Receptor, ErbB-2 genetics
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 X-linked 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 by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the United States.)
Published: 2016
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43. 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, Bauer M, Reininghaus EZ, Novák T, Aubry JM, Maj M, Baune BT, Mitchell PB, Vieta E, Frye MA, Rybakowski JK, Kuo PH, Kato T, Grigoroiu-Serbanescu M, Reif A, Del Zompo M, Bellivier F, Schalling M, Wray NR, Kelsoe JR, Alda M, Rietschel M, McMahon FJ, and Schulze TG
Subjects: Bipolar Disorder drug therapy, Female, Genetic Variation, Genome-Wide Association Study, Genotype, Glial Cell Line-Derived Neurotrophic Factor Receptors genetics, Humans, Male, Middle Aged, Phenotype, Prospective Studies, Treatment Outcome, Bipolar Disorder genetics, Lithium Compounds therapeutic use, Polymorphism, Single Nucleotide genetics
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 Health Intramural Research Program., (Copyright © 2016 Elsevier Ltd. All rights reserved.)
Published: 2016
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44. Distinguishing bipolar from unipolar depression: the importance of clinical symptoms and illness features.

Author: Leonpacher AK, Liebers D, Pirooznia M, Jancic D, MacKinnon DF, Mondimore FM, Schweizer B, Potash JB, Zandi PP, and Goes FS
Subjects: Adult, Diagnosis, Differential, Diagnostic and Statistical Manual of Mental Disorders, Female, Humans, Logistic Models, Male, Middle Aged, Multivariate Analysis, ROC Curve, Affective Symptoms diagnosis, Bipolar Disorder diagnosis, Depressive Disorder, Major diagnosis
Abstract: Background: Distinguishing bipolar disorder (BP) from major depressive disorder (MDD) has important relevance for prognosis and treatment. Prior studies have identified clinical features that differ between these two diseases but have been limited by heterogeneity and lack of replication. We sought to identify depression-related features that distinguish BP from MDD in large samples with replication., Method: Using a large, opportunistically ascertained collection of subjects with BP and MDD we selected 34 depression-related clinical features to test across the diagnostic categories in an initial discovery dataset consisting of 1228 subjects (386 BPI, 158 BPII and 684 MDD). Features significantly associated with BP were tested in an independent sample of 1000 BPI cases and 1000 MDD cases for classifying ability in receiver operating characteristic (ROC) analysis., Results: Seven clinical features showed significant association with BPI compared with MDD: delusions, psychomotor retardation, incapacitation, greater number of mixed symptoms, greater number of episodes, shorter episode length, and a history of experiencing a high after depression treatment. ROC analyses of a model including these seven factors showed significant evidence for discrimination between BPI and MDD in an independent dataset (area under the curve = 0.83). Only two features (number of mixed symptoms, and feeling high after an antidepressant) showed an association with BPII versus MDD., Conclusions: Our study suggests that clinical features distinguishing depression in BPI versus MDD have important classification potential for clinical practice, and should also be incorporated as 'baseline' features in the evaluation of novel diagnostic biomarkers.
Published: 2015
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45. Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing.

Author: Mostafavi S, Battle A, Zhu X, Potash JB, Weissman MM, Shi J, Beckman K, Haudenschild C, McCormick C, Mei R, Gameroff MJ, Gindes H, Adams P, Goes FS, Mondimore FM, MacKinnon DF, Notes L, Schweizer B, Furman D, Montgomery SB, Urban AE, Koller D, and Levinson DF
Subjects: Adult, Depressive Disorder, Major drug therapy, Female, Gene Expression, Genome-Wide Association Study, Humans, Interviews as Topic, Male, Middle Aged, Polymorphism, Single Nucleotide, Recurrence, Self Report, Sequence Analysis, RNA methods, Signal Transduction genetics, White People genetics, Young Adult, Depressive Disorder, Major genetics, Interferon Type I genetics
Abstract: A study of genome-wide gene expression in major depressive disorder (MDD) was undertaken in a large population-based sample to determine whether altered expression levels of genes and pathways could provide insights into biological mechanisms that are relevant to this disorder. Gene expression studies have the potential to detect changes that may be because of differences in common or rare genomic sequence variation, environmental factors or their interaction. We recruited a European ancestry sample of 463 individuals with recurrent MDD and 459 controls, obtained self-report and semi-structured interview data about psychiatric and medical history and other environmental variables, sequenced RNA from whole blood and genotyped a genome-wide panel of common single-nucleotide polymorphisms. We used analytical methods to identify MDD-related genes and pathways using all of these sources of information. In analyses of association between MDD and expression levels of 13 857 single autosomal genes, accounting for multiple technical, physiological and environmental covariates, a significant excess of low P-values was observed, but there was no significant single-gene association after genome-wide correction. Pathway-based analyses of expression data detected significant association of MDD with increased expression of genes in the interferon α/β signaling pathway. This finding could not be explained by potentially confounding diseases and medications (including antidepressants) or by computationally estimated proportions of white blood cell types. Although cause-effect relationships cannot be determined from these data, the results support the hypothesis that altered immune signaling has a role in the pathogenesis, manifestation, and/or the persistence and progression of MDD.
Published: 2014
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46. Posttraumatic stress disorder increases risk for suicide attempt in adults with recurrent major depression.

Author: Stevens D, Wilcox HC, MacKinnon DF, Mondimore FM, Schweizer B, Jancic D, Coryell WH, Weissman MM, Levinson DF, and Potash JB
Subjects: Adult, Age of Onset, Comorbidity, Depressive Disorder, Major psychology, Female, Humans, Logistic Models, Male, Middle Aged, Prevalence, Recurrence, Risk Factors, Stress Disorders, Post-Traumatic diagnosis, Stress Disorders, Post-Traumatic psychology, Suicide, Attempted statistics & numerical data, Depressive Disorder, Major complications, Life Change Events, Stress Disorders, Post-Traumatic complications, Suicide, Attempted psychology, Violence psychology
Abstract: Background: Genetics of Recurrent Early-Onset Depression study (GenRED II) data were used to examine the relationship between posttraumatic stress disorder (PTSD) and attempted suicide in a population of 1,433 individuals with recurrent early-onset major depressive disorder (MDD). We tested the hypothesis that PTSD resulting from assaultive trauma increases risk for attempted suicide among individuals with recurrent MDD., Methods: Data on lifetime trauma exposures and clinical symptoms were collected using the Diagnostic Interview for Genetic Studies version 3.0 and best estimate diagnoses of MDD, PTSD, and other DSM-IV Axis I disorders were reported with best estimated age of onset., Results: The lifetime prevalence of suicide attempt in this sample was 28%. Lifetime PTSD was diagnosed in 205 (14.3%) participants. We used discrete time-survival analyses to take into account timing in the PTSD-suicide attempt relationship while adjusting for demographic variables (gender, race, age, and education level) and comorbid diagnoses prior to trauma exposure. PTSD was an independent predictor of subsequent suicide attempt (HR = 2.5, 95% CI: 1.6, 3.8; P < .0001). Neither assaultive nor nonassaultive trauma without PTSD significantly predicted subsequent suicide attempt after Bonferroni correction. The association between PTSD and subsequent suicide attempt was driven by traumatic events involving assaultive violence (HR = 1.7, 95% CI: 1.3, 2.2; P< .0001)., Conclusions: Among those with recurrent MDD, PTSD appears to be a vulnerability marker of maladaptive responses to traumatic events and an independent risk factor for attempted suicide. Additional studies examining differences between those with and without PTSD on biological measures might shed light on this potential vulnerability., (© 2013 Wiley Periodicals, Inc.)
Published: 2013
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47. Co-morbid anxiety disorders in bipolar disorder and major depression: familial aggregation and clinical characteristics of co-morbid panic disorder, social phobia, specific phobia and obsessive-compulsive disorder.

Author: Goes FS, McCusker MG, Bienvenu OJ, Mackinnon DF, Mondimore FM, Schweizer B, Depaulo JR, and Potash JB
Subjects: Adult, Anxiety Disorders genetics, Bipolar Disorder genetics, Comorbidity, Depressive Disorder, Major genetics, Female, Genetic Predisposition to Disease, Humans, Interview, Psychological, Male, Multivariate Analysis, Severity of Illness Index, Anxiety Disorders epidemiology, Bipolar Disorder epidemiology, Depressive Disorder, Major epidemiology, Models, Statistical, Pedigree
Abstract: Background: Co-morbidity of mood and anxiety disorders is common and often associated with greater illness severity. This study investigates clinical correlates and familiality of four anxiety disorders in a large sample of bipolar disorder (BP) and major depressive disorder (MDD) pedigrees., Method: The sample comprised 566 BP families with 1416 affected subjects and 675 MDD families with 1726 affected subjects. Clinical characteristics and familiality of panic disorder, social phobia, specific phobia and obsessive-compulsive disorder (OCD) were examined in BP and MDD pedigrees with multivariate modeling using generalized estimating equations., Results: Co-morbidity between mood and anxiety disorders was associated with several markers of clinical severity, including earlier age of onset, greater number of depressive episodes and higher prevalence of attempted suicide, when compared with mood disorder without co-morbid anxiety. Familial aggregation was found with co-morbid panic and OCD in both BP and MDD pedigrees. Specific phobia showed familial aggregation in both MDD and BP families, although the findings in BP were just short of statistical significance after adjusting for other anxiety co-morbidities. We found no evidence for familiality of social phobia., Conclusions: Our findings suggest that co-morbidity of MDD and BP with specific anxiety disorders (OCD, panic disorder and specific phobia) is at least partly due to familial factors, which may be of relevance to both phenotypic and genetic studies of co-morbidity.
Published: 2012
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48. A genome-wide association study of attempted suicide.

Author: Willour VL, Seifuddin F, Mahon PB, Jancic D, Pirooznia M, Steele J, Schweizer B, Goes FS, Mondimore FM, Mackinnon DF, Perlis RH, Lee PH, Huang J, Kelsoe JR, Shilling PD, Rietschel M, Nöthen M, Cichon S, Gurling H, Purcell S, Smoller JW, Craddock N, DePaulo JR Jr, Schulze TG, McMahon FJ, Zandi PP, and Potash JB
Subjects: Brain metabolism, Case-Control Studies, Female, Genome-Wide Association Study methods, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Protein Tyrosine Phosphatases metabolism, Proto-Oncogene Proteins metabolism, Bipolar Disorder genetics, Bipolar Disorder psychology, Genetic Predisposition to Disease genetics, Genome-Wide Association Study statistics & numerical data, Protein Tyrosine Phosphatases genetics, Proto-Oncogene Proteins genetics, Suicide, Attempted psychology
Abstract: The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. Although attempted suicide linkage regions have been identified on 2p11-12 and 6q25-26, there are likely many more such loci, the discovery of which will require a much higher resolution approach, such as the genome-wide association study (GWAS). With this in mind, we conducted an attempted suicide GWAS that compared the single-nucleotide polymorphism (SNP) genotypes of 1201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1497 BP subjects without a history of suicide attempts. In all, 2507 SNPs with evidence for association at P<0.001 were identified. These associated SNPs were subsequently tested for association in a large and independent BP sample set. None of these SNPs were significantly associated in the replication sample after correcting for multiple testing, but the combined analysis of the two sample sets produced an association signal on 2p25 (rs300774) at the threshold of genome-wide significance (P=5.07 × 10(-8)). The associated SNPs on 2p25 fall in a large linkage disequilibrium block containing the ACP1 (acid phosphatase 1) gene, a gene whose expression is significantly elevated in BP subjects who have completed suicide. Furthermore, the ACP1 protein is a tyrosine phosphatase that influences Wnt signaling, a pathway regulated by lithium, making ACP1 a functional candidate for involvement in the phenotype. Larger GWAS sample sets will be required to confirm the signal on 2p25 and to identify additional genetic risk factors increasing susceptibility for attempted suicide.
Published: 2012
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49. Association study of serotonin pathway genes in attempted suicide.

Author: Judy JT, Seifuddin F, Mahon PB, Huo Y, Goes FS, Jancic D, Schweizer B, Mondimore FM, Mackinnon DF, Depaulo JR Jr, Gershon ES, McMahon FJ, Cutler DJ, Zandi PP, Potash JB, and Willour VL
Subjects: Humans, Polymorphism, Single Nucleotide genetics, Synaptic Transmission genetics, Genetic Association Studies, Serotonin genetics, Signal Transduction genetics, Suicide, Attempted psychology
Abstract: Epidemiological studies, such as family, twin, and adoption studies, demonstrate the presence of a heritable component to both attempted and completed suicide. Some of this heritability is accounted for by the presence of comorbid psychiatric disorders, but the evidence also indicates that a portion of this heritability is specific to suicidality. The serotonergic system has been studied extensively in this phenotype, but findings have been inconsistent, possibly due to the presence of multiple susceptibility variants and/or gene-gene interactions. In this study, we genotyped 174 tag and coding single nucleotide polymorphisms (SNPs) from 17 genes within the serotonin pathway on 516 subjects with a major mood disorder and a history of a suicide attempt (cases) and 515 healthy controls, with the goal of capturing the common genetic variation across each of these candidate genes. We tested the 174 markers in single-SNP, haplotype, gene-based, and epistasis analyses. While these association analyses identified multiple marginally significant SNPs, haplotypes, genes, and interactions, none of them survived correction for multiple testing. Additional studies, including assessment in larger sample sets and deep resequencing to identify rare causal variants, may be required to fully understand the role that the serotonin pathway plays in suicidal behavior., (Copyright © 2011 Wiley Periodicals, Inc.)
Published: 2012
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50. Sex-specific association of the Reelin gene with bipolar disorder.

Author: Goes FS, Willour VL, Zandi PP, Belmonte PL, MacKinnon DF, Mondimore FM, Schweizer B, DePaulo JR Jr, Gershon ES, McMahon FJ, and Potash JB
Subjects: Alleles, Family Health, Female, Genetic Markers, Genotype, Humans, Male, Models, Genetic, Neurons metabolism, Quality Control, Reelin Protein, Risk Factors, Schizophrenia genetics, Sex Factors, Bipolar Disorder genetics, Cell Adhesion Molecules, Neuronal genetics, Extracellular Matrix Proteins genetics, Nerve Tissue Proteins genetics, Serine Endopeptidases genetics
Abstract: The Reelin gene (RELN) encodes a secretory glycoprotein critical for brain development and synaptic plasticity. Post-mortem studies have shown lower Reelin protein levels in the brains of patients with schizophrenia and bipolar disorder (BP) compared with controls. In a recent genome-wide association study of schizophrenia, the strongest association was found in a marker within RELN, although this association was seen only in women. In this study, we investigated whether genetic variation in RELN is associated with BP in a large family sample. We genotyped 75 tagSNPs and 6 coding SNPs in 1,188 individuals from 318 nuclear families, including 554 affected offspring. Quality control measures, transmission-disequilibrium tests (TDTs), and empirical simulations were performed in PLINK. We found a significant overtransmission of the C allele of rs362719 to BP offspring (OR = 1.47, P = 5.9 x 10(-4)); this withstood empirical correction for testing of multiple markers (empirical P = 0.048). In a hypothesis-driven secondary analysis, we found that the association with rs362719 was almost entirely accounted for by overtransmission of the putative risk allele to affected females (OR(Female) = 1.79, P = 8.9 x 10(-5) vs. OR(Male) = 1.12, P = 0.63). These results provide preliminary evidence that genetic variation in RELN is associated with susceptibility to BP and, in particular, to BP in females. However, our findings should be interpreted with caution until further replication and functional assays provide convergent support., ((c) 2009 Wiley-Liss, Inc.)
Published: 2010
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