Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T12:41:28.148Z Has data issue: false hasContentIssue false

Exploring shared genetic bases and causal relationships of schizophrenia and bipolar disorder with 28 cardiovascular and metabolic traits

Published online by Cambridge University Press:  26 July 2018

Hon-Cheong So*
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong, Shatin, Hong Kong
Kwan-Long Chau
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
Fu-Kiu Ao
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
Cheuk-Hei Mo
Affiliation:
Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
Pak-Chung Sham
Affiliation:
Department of Psychiatry, University of Hong Kong, Pokfulam, Hong Kong Centre for Genomic Sciences, University of Hong Kong, Pokfulam, Hong Kong State Key Laboratory for Cognitive and Brain Sciences, University of Hong Kong, Pokfulam, Hong Kong Centre for Reproduction, Development and Growth, University of Hong Kong, Pokfulam, Hong Kong
*
Author for correspondence: Hon-Cheong So, E-mail: hcso@cuhk.edu.hk

Abstract

Background

Cardiovascular diseases represent a major health issue in patients with schizophrenia (SCZ) and bipolar disorder (BD), but the exact nature of cardiometabolic (CM) abnormalities involved and the underlying mechanisms remain unclear. Psychiatric medications are known risk factors, but it is unclear whether there is a connection between the disorders (SCZ/BD) themselves and CM abnormalities.

Methods

Using polygenic risk scores and linkage disequilibrium score regression, we investigated the shared genetic bases of SCZ and BD with 28 CM traits. We performed Mendelian randomization (MR) to elucidate causal relationships between the two groups of disorders. The analysis was based on large-scale meta-analyses of genome-wide association studies. We also identified the potential shared genetic variants and inferred the pathways involved.

Results

We found tentative polygenic associations of SCZ with glucose metabolism abnormalities, adverse adipokine profiles, increased waist-to-hip ratio and visceral adiposity (false discovery rate or FDR<0.05). However, there was an inverse association with body mass index. For BD, we observed several polygenic associations with favorable CM profiles at FDR<0.05. MR analysis showed that SCZ may be causally linked to raised triglyceride and that lower fasting glucose may be linked to BD. We also identified numerous single nucleotide polymorphisms and pathways shared between SCZ/BD with CM traits, some of which are related to inflammation or the immune system.

Conclusions

Our findings suggest that SCZ patients may be genetically predisposed to several CM abnormalities independent of medication side effects. On the other hand, CM abnormalities in BD may be more likely to be secondary. However, the findings require further validation.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andreassen, OA, Djurovic, S, Thompson, WK, Schork, AJ, Kendler, KS, O'Donovan, MC, Rujescu, D, Werge, T, van de Bunt, M, Morris, AP, McCarthy, MI, International Consortium for Blood Pressure, G., Diabetes Genetics, R., Meta-analysis, C., Psychiatric Genomics Consortium Schizophrenia Working, G., Roddey, JC, McEvoy, LK, Desikan, RS and Dale, AM (2013) Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. American Journal of Human Genetics 92, 197209.Google Scholar
Bartoli, F, Lax, A, Crocamo, C, Clerici, M and Carra, G (2015) Plasma adiponectin levels in schizophrenia and role of second-generation antipsychotics: a meta-analysis. Psychoneuroendocrinology 56, 179189.Google Scholar
Bowden, J, Davey Smith, G and Burgess, S (2015) Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal Epidemiology 44, 512525.Google Scholar
Bowden, J, Davey Smith, G, Haycock, PC and Burgess, S (2016) Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genetic Epidemiology 40, 304314.Google Scholar
Brown, BC, Asian Genetic Epidemiology Network Type 2 Diabetes, C., Ye, CJ, Price, AL and Zaitlen, N (2016) Transethnic genetic-correlation estimates from summary statistics. American Journal Human Genetics 99, 7688.Google Scholar
Bulik-Sullivan, B, Finucane, HK, Anttila, V, Gusev, A, Day, FR, Loh, PR, ReproGen, C, Psychiatric Genomics, C., Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control, C., Duncan, L, Perry, JR, Patterson, N, Robinson, EB, Daly, MJ, Price, AL and Neale, BM (2015) An atlas of genetic correlations across human diseases and traits. Nature Genetics 47, 12361241.Google Scholar
Burgess, S, Butterworth, A and Thompson, SG (2013) Mendelian randomization analysis with multiple genetic variants using summarized data. Genetic Epidemiology 37, 658665.Google Scholar
Burgess, S, Davies, NM and Thompson, SG (2016) Bias due to participant overlap in two-sample Mendelian randomization. Genetic Epidemiology 40, 597608.Google Scholar
Cardno, AG and Owen, MJ (2014) Genetic relationships between schizophrenia, bipolar disorder, and schizoaffective disorder. Schizophrenia Bulletin 40, 504515.Google Scholar
Chadda, RK, Ramshankar, P, Deb, KS and Sood, M (2013) Metabolic syndrome in schizophrenia: differences between antipsychotic-naive and treated patients. Journal of Pharmacology and Pharmacotherapeutics 4, 176186.Google Scholar
Chen, W and Ten Dijke, P (2016) Immunoregulation by members of the TGFbeta superfamily. Nature Reviews Immunology 16, 723740.Google Scholar
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421427.Google Scholar
Dastani, Z, Hivert, MF, Timpson, N, Perry, JR, Yuan, X, Scott, RA, Henneman, P, Heid, IM, Kizer, JR, Lyytikainen, LP, Fuchsberger, C, Tanaka, T, Morris, AP, Small, K, Isaacs, A, Beekman, M, Coassin, S, Lohman, K, Qi, L, Kanoni, S, Pankow, JS, Uh, HW, Wu, Y, Bidulescu, A, Rasmussen-Torvik, LJ, Greenwood, CM, Ladouceur, M, Grimsby, J, Manning, AK, Liu, CT, Kooner, J, Mooser, VE, Vollenweider, P, Kapur, KA, Chambers, J, Wareham, NJ, Langenberg, C, Frants, R, Willems-Vandijk, K, Oostra, BA, Willems, SM, Lamina, C, Winkler, TW, Psaty, BM, Tracy, RP, Brody, J, Chen, I, Viikari, J, Kahonen, M, Pramstaller, PP, Evans, DM, St Pourcain, B, Sattar, N, Wood, AR, Bandinelli, S, Carlson, OD, Egan, JM, Bohringer, S, van Heemst, D, Kedenko, L, Kristiansson, K, Nuotio, ML, Loo, BM, Harris, T, Garcia, M, Kanaya, A, Haun, M, Klopp, N, Wichmann, HE, Deloukas, P, Katsareli, E, Couper, DJ, Duncan, BB, Kloppenburg, M, Adair, LS, Borja, JB, Wilson, JG, Musani, S, Guo, X, Johnson, T, Semple, R, Teslovich, TM, Allison, MA, Redline, S, Buxbaum, SG, Mohlke, KL, Meulenbelt, I, Ballantyne, CM, Dedoussis, GV, Hu, FB, Liu, Y, Paulweber, B, Spector, TD, Slagboom, PE, Ferrucci, L, Jula, A, Perola, M, Raitakari, O, Florez, JC, Salomaa, V, Eriksson, JG, Frayling, TM, Hicks, AA, Lehtimaki, T, Smith, GD, Siscovick, DS, Kronenberg, F, van Duijn, C, Loos, RJ, Waterworth, DM, Meigs, JB, Dupuis, J, Richards, JB, Voight, BF, Scott, LJ, Steinthorsdottir, V, Dina, C, Welch, RP, Zeggini, E, Huth, C, Aulchenko, YS, Thorleifsson, G, McCulloch, LJ, Ferreira, T, Grallert, H, Amin, N, Wu, G, Willer, CJ, Raychaudhuri, S, McCarroll, SA, Hofmann, OM, Segre, AV, van Hoek, M, Navarro, P, Ardlie, K, Balkau, B, Benediktsson, R, Bennett, AJ, Blagieva, R, Boerwinkle, E, Bonnycastle, LL, Bostrom, KB, Bravenboer, B, Bumpstead, S, Burtt, NP, Charpentier, G, Chines, PS, Cornelis, M, Crawford, G, Doney, AS, Elliott, KS, Elliott, AL, Erdos, MR, Fox, CS, Franklin, CS, Ganser, M, Gieger, C, Grarup, N, Green, T, Griffin, S, Groves, CJ, Guiducci, C, Hadjadj, S, Hassanali, N, Herder, C, Isomaa, B, Jackson, AU, Johnson, PR, Jorgensen, T, Kao, WH, Kong, A, Kraft, P, Kuusisto, J, Lauritzen, T, Li, M, Lieverse, A, Lindgren, CM, Lyssenko, V, Marre, M, Meitinger, T, Midthjell, K, Morken, MA, Narisu, N, Nilsson, P, Owen, KR, Payne, F, Petersen, AK, Platou, C, Proenca, C, Prokopenko, I, Rathmann, W, Rayner, NW, Robertson, NR, Rocheleau, G, Roden, M, Sampson, MJ, Saxena, R, Shields, BM, Shrader, P, Sigurdsson, G, Sparso, T, Strassburger, K, Stringham, HM, Sun, Q, Swift, AJ, Thorand, B, Tichet, J, Tuomi, T, van Dam, RM, van Haeften, TW, van Herpt, T, van Vliet-Ostaptchouk, JV, Walters, GB, Weedon, MN, Wijmenga, C, Witteman, J, Bergman, RN, Cauchi, S, Collins, FS, Gloyn, AL, Gyllensten, U, Hansen, T, Hide, WA, Hitman, GA, Hofman, A, Hunter, DJ, Hveem, K, Laakso, M, Morris, AD, Palmer, CN, Rudan, I, Sijbrands, E, Stein, LD, Tuomilehto, J, Uitterlinden, A, Walker, M, Watanabe, RM, Abecasis, GR, Boehm, BO, Campbell, H, Daly, MJ, Hattersley, AT, Pedersen, O, Barroso, I, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, JF, Illig, T, Froguel, P, van Duijn, CM, Stefansson, K, Altshuler, D, Boehnke, M, McCarthy, MI, Soranzo, N, Wheeler, E, Glazer, NL, Bouatia-Naji, N, Magi, R, Randall, J, Elliott, P, Rybin, D, Dehghan, A, Hottenga, JJ, Song, K, Goel, A, Lajunen, T, Doney, A, Cavalcanti-Proenca, C, Kumari, M, Timpson, NJ, Zabena, C, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, Roccasecca, RM, Pattou, F, Sethupathy, P, Ariyurek, Y, Barter, P, Beilby, JP, Ben-Shlomo, Y, Bergmann, S, Bochud, M, Bonnefond, A, Borch-Johnsen, K, Bottcher, Y, Brunner, E, Bumpstead, SJ, Chen, YD, Chines, P, Clarke, R, Coin, LJ, Cooper, MN, Crisponi, L, Day, IN, de Geus, EJ, Delplanque, J, Fedson, AC, Fischer-Rosinsky, A, Forouhi, NG, Franzosi, MG, Galan, P, Goodarzi, MO, Graessler, J, Grundy, S, Gwilliam, R, Hallmans, G, Hammond, N, Han, X, Hartikainen, AL, Hayward, C, Heath, SC, Hercberg, S, Hillman, DR, Hingorani, AD, Hui, J, Hung, J, Kaakinen, M, Kaprio, J, Kesaniemi, YA, Kivimaki, M, Knight, B, Koskinen, S, Kovacs, P, Kyvik, KO, Lathrop, GM, Lawlor, DA, Le Bacquer, O, Lecoeur, C, Li, Y, Mahley, R, Mangino, M, Martinez-Larrad, MT, McAteer, JB, McPherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, BD, Mukherjee, S, Naitza, S, Neville, MJ, Orru, M, Pakyz, R, Paolisso, G, Pattaro, C, Pearson, D, Peden, JF, Pedersen, NL, Pfeiffer, AF, Pichler, I, Polasek, O, Posthuma, D, Potter, SC, Pouta, A, Province, MA, Rice, K, Ripatti, S, Rivadeneira, F, Rolandsson, O, Sandbaek, A, Sandhu, M, Sanna, S, Sayer, AA, Scheet, P, Seedorf, U, Sharp, SJ, Shields, B, Sigurethsson, G, Sijbrands, EJ, Silveira, A, Simpson, L, Singleton, A, Smith, NL, Sovio, U, Swift, A, Syddall, H, Syvanen, AC, Tonjes, A, Uitterlinden, AG, van Dijk, KW, Varma, D, Visvikis-Siest, S, Vitart, V, Vogelzangs, N, Waeber, G, Wagner, PJ, Walley, A, Ward, KL, Watkins, H, Wild, SH, Willemsen, G, Witteman, JC, Yarnell, JW, Zelenika, D, Zethelius, B, Zhai, G, Zhao, JH, Zillikens, MC, Borecki, IB, Meneton, P, Magnusson, PK, Nathan, DM, Williams, GH, Silander, K, Bornstein, SR, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, AR, Cooper, C, Serrano-Rios, M, Lind, L, Palmer, LJ, Hu, FBs, Franks, PW, Ebrahim, S, Marmot, M, Wright, AF, Stumvoll, M, Hamsten, A, Buchanan, TA, Valle, TT, Rotter, JI, Penninx, BW, Boomsma, DI, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, MR, Peltonen, L, Mooser, V, Musunuru, K, Smith, AV, Edmondson, AC, Stylianou, IM, Koseki, M, Pirruccello, JP, Chasman, DI, Johansen, CT, Fouchier, SW, Peloso, GM, Barbalic, M, Ricketts, SL, Bis, JC, Feitosa, MF, Orho-Melander, M, Melander, O, Li, X, Cho, YS, Go, MJ, Kim, YJ, Lee, JY, Park, T, Kim, K, Sim, X, Ong, RT, Croteau-Chonka, DC, Lange, LA, Smith, JD, Ziegler, A, Zhang, W, Zee, RY, Whitfield, JB, Thompson, JR, Surakka, I, Smit, JH, Sinisalo, J, Scott, J, Saharinen, J, Sabatti, C, Rose, LM, Roberts, R, Rieder, M, Parker, AN, Pare, G, O'Donnell, CJ, Nieminen, MS, Nickerson, DA, Montgomery, GW, McArdle, W, Masson, D, Martin, NG, Marroni, F, Lucas, G, Luben, R, Lokki, ML, Lettre, G, Launer, LJ, Lakatta, EG, Laaksonen, R, Konig, IR, Khaw, KT, Kaplan, LM, Johansson, A, Janssens, AC, Igl, W, Hovingh, GK, Hengstenberg, C, Havulinna, AS, Hastie, ND, Harris, TB, Haritunians, T, Hall, AS, Groop, LC, Gonzalez, E, Freimer, NB, Erdmann, J, Ejebe, KG, Doring, A, Dominiczak, AF, Demissie, S, de Faire, U, Caulfield, MJ, Boekholdt, SM, Assimes, TL, Quertermous, T, Seielstad, M, Wong, TY, Tai, ES, Feranil, AB, Kuzawa, CW, Taylor, HA Jr., Gabriel, SB, Holm, H, Gudnason, V, Krauss, RM, Ordovas, JM, Munroe, PB, Kooner, JS, Tall, AR, Hegele, RA, Kastelein, JJ, Schadt, EE, Strachan, DP, Reilly, MP, Samani, NJ, Schunkert, H, Cupples, LA, Sandhu, MS, Ridker, PM, Rader, DJ and Kathiresan, S (2012). Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45891 individuals. PLoS Genetics 8, e1002607.Google Scholar
Ehret, GB, Munroe, PB, Rice, KM, Bochud, M, Johnson, AD, Chasman, DI, Smith, AV, Tobin, MD, Verwoert, GC, Hwang, SJ, Pihur, V, Vollenweider, P, O'Reilly, PF, Amin, N, Bragg-Gresham, JL, Teumer, A, Glazer, NL, Launer, L, Zhao, JH, Aulchenko, Y, Heath, S, Sober, S, Parsa, A, Luan, J, Arora, P, Dehghan, A, Zhang, F, Lucas, G, Hicks, AA, Jackson, AU, Peden, JF, Tanaka, T, Wild, SH, Rudan, I, Igl, W, Milaneschi, Y, Parker, AN, Fava, C, Chambers, JC, Fox, ER, Kumari, M, Go, MJ, van der Harst, P, Kao, WH, Sjogren, M, Vinay, DG, Alexander, M, Tabara, Y, Shaw-Hawkins, S, Whincup, PH, Liu, Y, Shi, G, Kuusisto, J, Tayo, B, Seielstad, M, Sim, X, Nguyen, KD, Lehtimaki, T, Matullo, G, Wu, Y, Gaunt, TR, Onland-Moret, NC, Cooper, MN, Platou, CG, Org, E, Hardy, R, Dahgam, S, Palmen, J, Vitart, V, Braund, PS, Kuznetsova, T, Uiterwaal, CS, Adeyemo, A, Palmas, W, Campbell, H, Ludwig, B, Tomaszewski, M, Tzoulaki, I, Palmer, ND, Aspelund, T, Garcia, M, Chang, YP, O'Connell, JR, Steinle, NI, Grobbee, DE, Arking, DE, Kardia, SL, Morrison, AC, Hernandez, D, Najjar, S, McArdle, WL, Hadley, D, Brown, MJ, Connell, JM, Hingorani, AD, Day, IN, Lawlor, DA, Beilby, JP, Lawrence, RW, Clarke, R, Hopewell, JC, Ongen, H, Dreisbach, AW, Li, Y, Young, JH, Bis, JC, Kahonen, M, Viikari, J, Adair, LS, Lee, NR, Chen, MH, Olden, M, Pattaro, C, Bolton, JA, Kottgen, A, Bergmann, S, Mooser, V, Chaturvedi, N, Frayling, TM, Islam, M, Jafar, TH, Erdmann, J, Kulkarni, SR, Bornstein, SR, Grassler, J, Groop, L, Voight, BF, Kettunen, J, Howard, P, Taylor, A, Guarrera, S, Ricceri, F, Emilsson, V, Plump, A, Barroso, I, Khaw, KT, Weder, AB, Hunt, SC, Sun, YV, Bergman, RN, Collins, FS, Bonnycastle, LL, Scott, LJ, Stringham, HM, Peltonen, L, Perola, M, Vartiainen, E, Brand, SM, Staessen, JA, Wang, TJ, Burton, PR, Soler Artigas, M, Dong, Y, Snieder, H, Wang, X, Zhu, H, Lohman, KK, Rudock, ME, Heckbert, SR, Smith, NL, Wiggins, KL, Doumatey, A, Shriner, D, Veldre, G, Viigimaa, M, Kinra, S, Prabhakaran, D, Tripathy, V, Langefeld, CD, Rosengren, A, Thelle, DS, Corsi, AM, Singleton, A, Forrester, T, Hilton, G, McKenzie, CA, Salako, T, Iwai, N, Kita, Y, Ogihara, T, Ohkubo, T, Okamura, T, Ueshima, H, Umemura, S, Eyheramendy, S, Meitinger, T, Wichmann, HE, Cho, YS, Kim, HL, Lee, JY, Scott, J, Sehmi, JS, Zhang, W, Hedblad, B, Nilsson, P, Smith, GD, Wong, A, Narisu, N, Stancakova, A, Raffel, LJ, Yao, J, Kathiresan, S, O'Donnell, CJ, Schwartz, SM, Ikram, MA, Longstreth, WT Jr., Mosley, TH, Seshadri, S, Shrine, NR, Wain, LV, Morken, MA, Swift, AJ, Laitinen, J, Prokopenko, I, Zitting, P, Cooper, JA, Humphries, SE, Danesh, J, Rasheed, A, Goel, A, Hamsten, A, Watkins, H, Bakker, SJ, van Gilst, WH, Janipalli, CS, Mani, KR, Yajnik, CS, Hofman, A, Mattace-Raso, FU, Oostra, BA, Demirkan, A, Isaacs, A, Rivadeneira, F, Lakatta, EG, Orru, M, Scuteri, A, Ala-Korpela, M, Kangas, AJ, Lyytikainen, LP, Soininen, P, Tukiainen, T, Wurtz, P, Ong, RT, Dorr, M, Kroemer, HK, Volker, U, Volzke, H, Galan, P, Hercberg, S, Lathrop, M, Zelenika, D, Deloukas, P, Mangino, M, Spector, TD, Zhai, G, Meschia, JF, Nalls, MA, Sharma, P, Terzic, J, Kumar, MV, Denniff, M, Zukowska-Szczechowska, E, Wagenknecht, LE, Fowkes, FG, Charchar, FJ, Schwarz, PE, Hayward, C, Guo, X, Rotimi, C, Bots, ML, Brand, E, Samani, NJ, Polasek, O, Talmud, PJ, Nyberg, F, Kuh, D, Laan, M, Hveem, K, Palmer, LJ, van der Schouw, YT, Casas, JP, Mohlke, KL, Vineis, P, Raitakari, O, Ganesh, SK, Wong, TY, Tai, ES, Cooper, RS, Laakso, M, Rao, DC, Harris, TB, Morris, RW, Dominiczak, AF, Kivimaki, M, Marmot, MG, Miki, T, Saleheen, D, Chandak, GR, Coresh, J, Navis, G, Salomaa, V, Han, BG, Zhu, X, Kooner, JS, Melander, O, Ridker, PM, Bandinelli, S, Gyllensten, UB, Wright, AF, Wilson, JF, Ferrucci, L, Farrall, M, Tuomilehto, J, Pramstaller, PP, Elosua, R, Soranzo, N, Sijbrands, EJ, Altshuler, D, Loos, RJ, Shuldiner, AR, Gieger, C, Meneton, P, Uitterlinden, AG, Wareham, NJ, Gudnason, V, Rotter, JI, Rettig, R, Uda, M, Strachan, DP, Witteman, JC, Hartikainen, AL, Beckmann, JS, Boerwinkle, E, Vasan, RS, Boehnke, M, Larson, MG, Jarvelin, MR, Psaty, BM, Abecasis, GR, Chakravarti, A, Elliott, P, van Duijn, CM, Newton-Cheh, C, Levy, D, Caulfield, MJ and Johnson, T (2011). Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478, 103109.Google Scholar
Euesden, J, Lewis, CM and O'Reilly, PF (2015) PRSice: polygenic risk score software. Bioinformatics (Oxford, England) 31, 14661468.Google Scholar
Evans, DM, Brion, MJ, Paternoster, L, Kemp, JP, McMahon, G, Munafo, M, Whitfield, JB, Medland, SE, Montgomery, GW, Consortium, G, Consortium, CRP, Consortium, TAG, Timpson, NJ, St Pourcain, B, Lawlor, DA, Martin, NG, Dehghan, A, Hirschhorn, J and Smith, GD (2013) Mining the human phenome using allelic scores that index biological intermediates. PLoS Genetics 9, e1003919.Google Scholar
Fernandez-Ruiz, I (2016) Immune system and cardiovascular disease. Nature Reviews: Cardiology 13, 503.Google Scholar
Gabriel, A (2007) Changes in plasma cholesterol in mood disorder patients: does treatment make a difference? Journal of Affective Disorders 99, 273278.Google Scholar
Greenhalgh, AM, Gonzalez-Blanco, L, Garcia-Rizo, C, Fernandez-Egea, E, Miller, B, Arroyo, MB and Kirkpatrick, B (2017) Meta-analysis of glucose tolerance, insulin, and insulin resistance in antipsychotic-naive patients with nonaffective psychosis. Schizophrenia Research 179, 5763.Google Scholar
Guha, P, Bhowmick, K, Mazumder, P, Ghosal, M, Chakraborty, I and Burman, P (2014) Assessment of insulin resistance and metabolic syndrome in drug naive patients of bipolar disorder. Indian Journal of Clinical Biochemistry 29, 5156.Google Scholar
Gupta, S, Anderson, R and Holt, RI (2016) Greater variation in affect is associated with lower fasting plasma glucose. Heliyon 2, e00160.Google Scholar
Han, SH, Quon, MJ, Kim, JA and Koh, KK (2007) Adiponectin and cardiovascular disease: response to therapeutic interventions. Journal of American College of Cardiology 49, 531538.Google Scholar
Hartwig, FP, Bowden, J, Loret de Mola, C, Tovo-Rodrigues, L, Davey Smith, G and Horta, BL (2016) Body mass index and psychiatric disorders: a Mendelian randomization study. Scientific Reports 6, 32730.Google Scholar
Hartwig, FP, Davey Smith, G and Bowden, J (2017) Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. International Journal of Epidemiology 46, 19851998.Google Scholar
Hemani, G, Zheng, J, Elsworth, B, Wade, KH, Haberland, V, Baird, D, Laurin, C, Burgess, S, Bowden, J, Langdon, R, Tan, VY, Yarmolinsky, J, Shihab, HA, Timpson, NJ, Evans, DM, Relton, C, Martin, RM, Davey Smith, G, Gaunt, TR and Haycock, PC (2018) The MR-Base platform supports systematic causal inference across the human phenome. Elife 7, e34408.Google Scholar
Henderson, DC, Vincenzi, B, Andrea, NV, Ulloa, M and Copeland, PM (2015) Pathophysiological mechanisms of increased cardiometabolic risk in people with schizophrenia and other severe mental illnesses. The Lancet Psychiatry 2, 452464.Google Scholar
Hou, L, Bergen, SE, Akula, N, Song, J, Hultman, CM, Landen, 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, Etain, B, Falkai, P, Foroud, T, Forstner, AJ, Frisen, 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, Jimenez, E, Kahn, JP, Kassem, L, Kelsoe, JR, Kittel-Schneider, S, Kliwicki, S, Koller, DL, Konig, 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, Muhleisen, TW, Nievergelt, CM, Nothen, MM, Novak, T, Nurnberger, JI Jr., Nwulia, EA, Osby, 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 (2016). Genome-wide association study of 40000 individuals identifies two novel loci associated with bipolar disorder. Human Molecular Genetics 25, 33833394.Google Scholar
Iwakura, Y and Nawa, H (2013) ErbB1-4-dependent EGF/neuregulin signals and their cross talk in the central nervous system: pathological implications in schizophrenia and Parkinson's disease. Frontiers in Cellular Neuroscience 7, 4.Google Scholar
Johnson, T (2012) Efficient calculation for multi-SNP genetic risk scores. Available at https://cran.r-project.org/web/packages/gtx/vignettes/ashg2012.pdf.Google Scholar
Kaur, J (2014) A comprehensive review on metabolic syndrome. Cardiology Research and Practice 2014, 943162.Google Scholar
Koh, KK, Park, SM and Quon, MJ (2008) Leptin and cardiovascular disease: response to therapeutic interventions. Circulation 117, 32383249.Google Scholar
Laursen, TM (2011) Life expectancy among persons with schizophrenia or bipolar affective disorder. Schizophrenia Research 131, 101104.Google Scholar
Lester, D (2002) Serum cholesterol levels and suicide: a meta-analysis. Suicide and Life-Threatening Behavior 32, 333346.Google Scholar
Maina, G, Salvi, V, Vitalucci, A, D'Ambrosio, V and Bogetto, F (2008) Prevalence and correlates of overweight in drug-naive patients with bipolar disorder. Journal of Affective Disorders 110, 149155.Google Scholar
Makki, N, Thiel, KW and Miller, FJ Jr. (2013). The epidermal growth factor receptor and its ligands in cardiovascular disease. International Journal of Molecular Sciences 14, 2059720613.Google Scholar
McEvoy, JP, Meyer, JM, Goff, DC, Nasrallah, HA, Davis, SM, Sullivan, L, Meltzer, HY, Hsiao, J, Scott Stroup, T and Lieberman, JA (2005) Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophrenia Research 80, 1932.Google Scholar
Mondelli, V, Dazzan, P and Pariante, CM (2015) Immune abnormalities across psychiatric disorders: clinical relevance. BJPsych Advances 21, 150156.Google Scholar
Murray, RM, Sham, P, Van Os, J, Zanelli, J, Cannon, M and McDonald, C (2004) A developmental model for similarities and dissimilarities between schizophrenia and bipolar disorder. Schizophrenia Research 71, 405416.Google Scholar
Newcomer, JW (2006). Medical risk in patients with bipolar disorder and schizophrenia. Journal of Clinical Psychiatry 67(Suppl. 9), 2530; discussion 36–42.Google Scholar
Padmavati, R, McCreadie, RG and Tirupati, S (2010) Low prevalence of obesity and metabolic syndrome in never-treated chronic schizophrenia. Schizophrenia Research 121, 199202.Google Scholar
Palla, L and Dudbridge, F (2015) A fast method that uses polygenic scores to estimate the variance explained by genome-wide marker panels and the proportion of variants affecting a trait. American Journal of Human Genetics 97, 250259.Google Scholar
Perry, BI, McIntosh, G, Weich, S, Singh, S and Rees, K (2016) The association between first-episode psychosis and abnormal glycaemic control: systematic review and meta-analysis. The Lancet. Psychiatry 3, 10491058.Google Scholar
Pillinger, T, Beck, K, Gobjila, C, Donocik, JG, Jauhar, S and Howes, OD (2017 a) Impaired glucose homeostasis in first-episode schizophrenia: a systematic review and meta-analysis. JAMA Psychiatry 74, 261269.Google Scholar
Pillinger, T, Beck, K, Stubbs, B and Howes, OD (2017 b) Cholesterol and triglyceride levels in first-episode psychosis: systematic review and meta-analysis. The British Journal of Psychiatry 211, 339349.Google Scholar
Pramyothin, P and Khaodhiar, L (2010) Metabolic syndrome with the atypical antipsychotics. Current Opinion in Endocrinology, Diabetes, and Obesity 17, 460466.Google Scholar
Price, AL, Patterson, NJ, Plenge, RM, Weinblatt, ME, Shadick, NA and Reich, D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38, 904909.Google Scholar
Psychiatric GWAS Consortium Bipolar Disorder Working Group (2011) Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nature Genetics 43, 977983.Google Scholar
Ringen, PA, Engh, JA, Birkenaes, AB, Dieset, I and Andreassen, OA (2014) Increased mortality in schizophrenia due to cardiovascular disease – a non-systematic review of epidemiology, possible causes, and interventions. Frontiers in Psychiatry 5, 137.Google Scholar
Ryan, MC, Collins, P and Thakore, JH (2003) Impaired fasting glucose tolerance in first-episode, drug-naive patients with schizophrenia. American Journal of Psychiatry 160, 284289.Google Scholar
Ryan, MC, Flanagan, S, Kinsella, U, Keeling, F and Thakore, JH (2004) The effects of atypical antipsychotics on visceral fat distribution in first episode, drug-naive patients with schizophrenia. Life Sciences 74, 19992008.Google Scholar
Sabatti, C, Service, SK, Hartikainen, AL, Pouta, A, Ripatti, S, Brodsky, J, Jones, CG, Zaitlen, NA, Varilo, T, Kaakinen, M, Sovio, U, Ruokonen, A, Laitinen, J, Jakkula, E, Coin, L, Hoggart, C, Collins, A, Turunen, H, Gabriel, S, Elliot, P, McCarthy, MI, Daly, MJ, Jarvelin, MR, Freimer, NB and Peltonen, L (2009) Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nature Genetics 41, 3546.Google Scholar
Sagud, M, Mihaljevic-Peles, A, Pivac, N, Jakovljevic, M and Muck-Seler, D (2007) Platelet serotonin and serum lipids in psychotic mania. Journal of Affective Disorders 97, 247251.Google Scholar
Sengupta, S, Parrilla-Escobar, MA, Klink, R, Fathalli, F, Ying Kin, N, Stip, E, Baptista, T, Malla, A and Joober, R (2008) Are metabolic indices different between drug-naive first-episode psychosis patients and healthy controls? Schizophrenia Research 102, 329336.Google Scholar
Smith, GD, Timpson, N and Ebrahim, S (2008) Strengthening causal inference in cardiovascular epidemiology through Mendelian randomization. Annals of Medicine 40, 524541.Google Scholar
Sorensen, HJ, Mortensen, EL, Reinisch, JM and Mednick, SA (2006) Height, weight and body mass index in early adulthood and risk of schizophrenia. Acta Psychiatrica Scandinavica 114, 4954.Google Scholar
Spelman, LM, Walsh, PI, Sharifi, N, Collins, P and Thakore, JH (2007) Impaired glucose tolerance in first-episode drug-naive patients with schizophrenia. Diabetic Medicine 24, 481485.Google Scholar
Stubbs, B, Wang, AK, Vancampfort, D and Miller, BJ (2016) Are leptin levels increased among people with schizophrenia versus controls? A systematic review and comparative meta-analysis. Psychoneuroendocrinology 63, 144154.Google Scholar
Taylor, F, Huffman, MD, Macedo, AF, Moore, TH, Burke, M, Davey Smith, G, Ward, K and Ebrahim, S (2013) Statins for the primary prevention of cardiovascular disease. The Cochrane Database of Systematic Reviews, CD004816.Google Scholar
Vancampfort, D, Vansteelandt, K, Correll, CU, Mitchell, AJ, De Herdt, A, Sienaert, P, Probst, M and De Hert, M (2013) Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. American Journal of Psychiatry 170, 265274.Google Scholar
Venkatasubramanian, G, Chittiprol, S, Neelakantachar, N, Naveen, MN, Thirthall, J, Gangadhar, BN and Shetty, KT (2007) Insulin and insulin-like growth factor-1 abnormalities in antipsychotic-naive schizophrenia. American Journal of Psychiatry 164, 15571560.Google Scholar
Vincenzi, B, Stock, S, Borba, CP, Cleary, SM, Oppenheim, CE, Petruzzi, LJ, Fan, X, Copeland, PM, Freudenreich, O, Cather, C and Henderson, DC (2014) A randomized placebo-controlled pilot study of pravastatin as an adjunctive therapy in schizophrenia patients: effect on inflammation, psychopathology, cognition and lipid metabolism. Schizophrenia Research 159, 395403.Google Scholar
Wehby, GL, Ohsfeldt, RL and Murray, JC (2008) ‘Mendelian randomization’ equals instrumental variable analysis with genetic instruments. Statistics in Medicine 27, 27452749.Google Scholar
Weiner, M, Warren, L and Fiedorowicz, JG (2011) Cardiovascular morbidity and mortality in bipolar disorder. Annals of Clinical Psychiatry 23, 4047.Google Scholar
Yusuf, S, Hawken, S, Ounpuu, S, Bautista, L, Franzosi, MG, Commerford, P, Lang, CC, Rumboldt, Z, Onen, CL, Lisheng, L, Tanomsup, S, Wangai, P Jr., Razak, F, Sharma, AM and Anand, SS (2005). Obesity and the risk of myocardial infarction in 27000 participants from 52 countries: a case-control study. Lancet 366, 16401649.Google Scholar
Zammit, S, Rasmussen, F, Farahmand, B, Gunnell, D, Lewis, G, Tynelius, P and Brobert, GP (2007) Height and body mass index in young adulthood and risk of schizophrenia: a longitudinal study of 1 347 520 Swedish men. Acta Psychiatrica Scandinavica 116, 378385.Google Scholar
Supplementary material: File

So et al. supplementary material

So et al. supplementary material 1

Download So et al. supplementary material(File)
File 14.9 MB