Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

M. Bauer; T. Glenn; M. Alda; O. A. Andreassen; E. Angelopoulos; R. Ardau; C. Baethge; R. Bauer; F. Bellivier; R. H. Belmaker; M. Berk; T. D. Bjella; L. Bossini; Y. Bersudsky; E. Y.W. Cheung; J. Conell; M. Del Zompo; S. Dodd; B. Etain; A. Fagiolini; M. A. Frye; K. N. Fountoulakis; J. Garneau-Fournier; A. Gonzalez-Pinto; H. Harima; S. Hassel; C. Henry; A. Iacovides; E. T. Isometsä; F. Kapczinski; S. Kliwicki; B. König; R. Krogh; M. Kunz; B. Lafer; E. R. Larsen; U. Lewitzka; C. Lopez-Jaramillo; G. MacQueen; M. Manchia; W. Marsh; M. Martinez-Cengotitabengoa; I. Melle; S. Monteith; G. Morken; R. Munoz; F. G. Nery; C. O'Donovan; Y. Osher; A. Pfennig; D. Quiroz; R. Ramesar; N. Rasgon; A. Reif; P. Ritter; J. K. Rybakowski; K. Sagduyu; A. M. Scippa; E. Severus; C. Simhandl; D. J. Stein; S. Strejilevich; A. Hatim Sulaiman; K. Suominen; H. Tagata; Y. Tatebayashi; C. Torrent; E. Vieta; B. Viswanath; M. J. Wanchoo; M. Zetin; P. C. Whybrow

doi:10.1016/j.eurpsy.2014.10.005

Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

M. Bauer, T. Glenn, M. Alda, O. A. Andreassen, E. Angelopoulos, R. Ardau, C. Baethge, R. Bauer, F. Bellivier, R. H. Belmaker, M. Berk, T. D. Bjella, L. Bossini, Y. Bersudsky, E. Y.W. Cheung, J. Conell, M. Del Zompo, S. Dodd, B. Etain, A. FagioliniM. A. Frye, K. N. Fountoulakis, J. Garneau-Fournier, A. Gonzalez-Pinto, H. Harima, S. Hassel, C. Henry, A. Iacovides, E. T. Isometsä, F. Kapczinski, S. Kliwicki, B. König, R. Krogh, M. Kunz, B. Lafer, E. R. Larsen, U. Lewitzka, C. Lopez-Jaramillo, G. MacQueen, M. Manchia, W. Marsh, M. Martinez-Cengotitabengoa, I. Melle, S. Monteith, G. Morken, R. Munoz, F. G. Nery, C. O'Donovan, Y. Osher, A. Pfennig, D. Quiroz, R. Ramesar, N. Rasgon, A. Reif, P. Ritter, J. K. Rybakowski, K. Sagduyu, A. M. Scippa, E. Severus, C. Simhandl, D. J. Stein, S. Strejilevich, A. Hatim Sulaiman, K. Suominen, H. Tagata, Y. Tatebayashi, C. Torrent, E. Vieta, B. Viswanath, M. J. Wanchoo, M. Zetin, P. C. Whybrow

Medicine

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29 Citas (Scopus)

Resumen

Purpose: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. Methods: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. Results: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. Conclusion: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

Idioma original	English
Páginas (desde-hasta)	99-105
Número de páginas	7
Publicación	European Psychiatry
Volumen	30
N.º	1
DOI	https://doi.org/10.1016/j.eurpsy.2014.10.005
Estado	Published - ene. 1 2015

Nota bibliográfica

Funding Information:
We thank the European College of Neuropsychopharmacology (ECNP) Network Initiative for supporting the European Network of Bipolar Research Expert Centres (ENBREC). This work was also funded in part by the following: Canadian Institutes of Health Research (MA, Grant number 64410 ); the Research Council of Norway (OAA Grant numbers 213837; 223273; 217776 ); South-East Norway Health Authority (OAA, Grant number 2013-123 ); a NHMRC Senior Principal Research Fellowship ( M Berk, Grant number 1059660; INSERM (BE, Grant number C0829) and APHP (BE, Grant number AOR11096 ); the Spanish Government ( AGP, Grant numbers PS09/02002 CIBER Network; EC10-333, PI10/01430, PI10/01746, PI11/01977, PI11/02708, 2011/1064, 11-BI-01, 1677-DJ-030, EC10-220 ); European Regional Development Funds (Grant numbers UE/2012/FI-STAR, UE/2013/TENDERMH, UE/2013/MASTERMIND ), grants from Spanish Government (Grant numbers PI10/01430, PI10/01746, EC10-220, EC10-333, PI11/01977, 20111064, PI11/02708, PI12/02077, PI13/02252, PI13/00451 ), local grants from the Basque Government (Grant numbers 200911147, 2010111170, 2010112009, 2011111110, 2011111113 ); the Basque Foundation for Health Innovation and Research (Grant number BIO12/AL/002 ); the Spanish Clinical Research Network (Grant numbers CAIBER;1392-D-079 ) and the University of the Basque Country (Grant number IT679-13 ); Stanley Research Foundation (Grant number 03-RC-003 ); the Research Council of Norway (IM, Grant numbers ES488722, ES421716 ); the Regional Health Authority of South Eastern Norway (IM, Grants number 2011085, 2013088 ); DFG (AR, Grant numbers SFB TRR 58, B06, Z02 ); the DFG and Länder funds (AR, Grant number RTG1252/2 ); Medical Research Council of South Africa (DJS); Spanish Ministry of Economy and Competitiveness (EV, Grants number PI12/00912, PN 2008-2011 ); the I nstituto de Salud Carlos III- Subdirección General de Evaluación y Fomento de la Investigación (EV); Fondo Europeo de Desarrollo Regional Unión Europea. Una manera de hacer Europa (EV); CIBERSAM (EV); the Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya to the Bipolar Disorders Group (EV, Grant number 2009 SGR 1022 ), and the Department of Science and Technology INSPIRE scheme, Government of India (BV).

Publisher Copyright:
© 2014 Elsevier Masson SAS.

ASJC Scopus Subject Areas

Psychiatry and Mental health

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10.1016/j.eurpsy.2014.10.005

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Bauer, M., Glenn, T., Alda, M., Andreassen, O. A., Angelopoulos, E., Ardau, R., Baethge, C., Bauer, R., Bellivier, F., Belmaker, R. H., Berk, M., Bjella, T. D., Bossini, L., Bersudsky, Y., Cheung, E. Y. W., Conell, J., Del Zompo, M., Dodd, S., Etain, B., ... Whybrow, P. C. (2015). Influence of birth cohort on age of onset cluster analysis in bipolar I disorder. European Psychiatry, 30(1), 99-105. https://doi.org/10.1016/j.eurpsy.2014.10.005

Bauer, M, Glenn, T, Alda, M, Andreassen, OA, Angelopoulos, E, Ardau, R, Baethge, C, Bauer, R, Bellivier, F, Belmaker, RH, Berk, M, Bjella, TD, Bossini, L, Bersudsky, Y, Cheung, EYW, Conell, J, Del Zompo, M, Dodd, S, Etain, B, Fagiolini, A, Frye, MA, Fountoulakis, KN, Garneau-Fournier, J, Gonzalez-Pinto, A, Harima, H, Hassel, S, Henry, C, Iacovides, A, Isometsä, ET, Kapczinski, F, Kliwicki, S, König, B, Krogh, R, Kunz, M, Lafer, B, Larsen, ER, Lewitzka, U, Lopez-Jaramillo, C, MacQueen, G, Manchia, M, Marsh, W, Martinez-Cengotitabengoa, M, Melle, I, Monteith, S, Morken, G, Munoz, R, Nery, FG, O'Donovan, C, Osher, Y, Pfennig, A, Quiroz, D, Ramesar, R, Rasgon, N, Reif, A, Ritter, P, Rybakowski, JK, Sagduyu, K, Scippa, AM, Severus, E, Simhandl, C, Stein, DJ, Strejilevich, S, Hatim Sulaiman, A, Suominen, K, Tagata, H, Tatebayashi, Y, Torrent, C, Vieta, E, Viswanath, B, Wanchoo, MJ, Zetin, M & Whybrow, PC 2015, 'Influence of birth cohort on age of onset cluster analysis in bipolar I disorder', European Psychiatry, vol. 30, n.º 1, pp. 99-105. https://doi.org/10.1016/j.eurpsy.2014.10.005

@article{517d186b064748fcae013e45dac45ae0,

title = "Influence of birth cohort on age of onset cluster analysis in bipolar I disorder",

abstract = "Purpose: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. Methods: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. Results: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. Conclusion: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.",

author = "M. Bauer and T. Glenn and M. Alda and Andreassen, {O. A.} and E. Angelopoulos and R. Ardau and C. Baethge and R. Bauer and F. Bellivier and Belmaker, {R. H.} and M. Berk and Bjella, {T. D.} and L. Bossini and Y. Bersudsky and Cheung, {E. Y.W.} and J. Conell and {Del Zompo}, M. and S. Dodd and B. Etain and A. Fagiolini and Frye, {M. A.} and Fountoulakis, {K. N.} and J. Garneau-Fournier and A. Gonzalez-Pinto and H. Harima and S. Hassel and C. Henry and A. Iacovides and Isomets{\"a}, {E. T.} and F. Kapczinski and S. Kliwicki and B. K{\"o}nig and R. Krogh and M. Kunz and B. Lafer and Larsen, {E. R.} and U. Lewitzka and C. Lopez-Jaramillo and G. MacQueen and M. Manchia and W. Marsh and M. Martinez-Cengotitabengoa and I. Melle and S. Monteith and G. Morken and R. Munoz and Nery, {F. G.} and C. O'Donovan and Y. Osher and A. Pfennig and D. Quiroz and R. Ramesar and N. Rasgon and A. Reif and P. Ritter and Rybakowski, {J. K.} and K. Sagduyu and Scippa, {A. M.} and E. Severus and C. Simhandl and Stein, {D. J.} and S. Strejilevich and {Hatim Sulaiman}, A. and K. Suominen and H. Tagata and Y. Tatebayashi and C. Torrent and E. Vieta and B. Viswanath and Wanchoo, {M. J.} and M. Zetin and Whybrow, {P. C.}",

note = "Funding Information: We thank the European College of Neuropsychopharmacology (ECNP) Network Initiative for supporting the European Network of Bipolar Research Expert Centres (ENBREC). This work was also funded in part by the following: Canadian Institutes of Health Research (MA, Grant number 64410 ); the Research Council of Norway (OAA Grant numbers 213837; 223273; 217776 ); South-East Norway Health Authority (OAA, Grant number 2013-123 ); a NHMRC Senior Principal Research Fellowship ( M Berk, Grant number 1059660; INSERM (BE, Grant number C0829) and APHP (BE, Grant number AOR11096 ); the Spanish Government ( AGP, Grant numbers PS09/02002 CIBER Network; EC10-333, PI10/01430, PI10/01746, PI11/01977, PI11/02708, 2011/1064, 11-BI-01, 1677-DJ-030, EC10-220 ); European Regional Development Funds (Grant numbers UE/2012/FI-STAR, UE/2013/TENDERMH, UE/2013/MASTERMIND ), grants from Spanish Government (Grant numbers PI10/01430, PI10/01746, EC10-220, EC10-333, PI11/01977, 20111064, PI11/02708, PI12/02077, PI13/02252, PI13/00451 ), local grants from the Basque Government (Grant numbers 200911147, 2010111170, 2010112009, 2011111110, 2011111113 ); the Basque Foundation for Health Innovation and Research (Grant number BIO12/AL/002 ); the Spanish Clinical Research Network (Grant numbers CAIBER;1392-D-079 ) and the University of the Basque Country (Grant number IT679-13 ); Stanley Research Foundation (Grant number 03-RC-003 ); the Research Council of Norway (IM, Grant numbers ES488722, ES421716 ); the Regional Health Authority of South Eastern Norway (IM, Grants number 2011085, 2013088 ); DFG (AR, Grant numbers SFB TRR 58, B06, Z02 ); the DFG and L{\"a}nder funds (AR, Grant number RTG1252/2 ); Medical Research Council of South Africa (DJS); Spanish Ministry of Economy and Competitiveness (EV, Grants number PI12/00912, PN 2008-2011 ); the I nstituto de Salud Carlos III- Subdirecci{\'o}n General de Evaluaci{\'o}n y Fomento de la Investigaci{\'o}n (EV); Fondo Europeo de Desarrollo Regional Uni{\'o}n Europea. Una manera de hacer Europa (EV); CIBERSAM (EV); the Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya to the Bipolar Disorders Group (EV, Grant number 2009 SGR 1022 ), and the Department of Science and Technology INSPIRE scheme, Government of India (BV). Publisher Copyright: {\textcopyright} 2014 Elsevier Masson SAS.",

year = "2015",

month = jan,

day = "1",

doi = "10.1016/j.eurpsy.2014.10.005",

language = "English",

volume = "30",

pages = "99--105",

journal = "European Psychiatry",

issn = "0924-9338",

publisher = "Elsevier Masson",

number = "1",

}

TY - JOUR

T1 - Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

AU - Bauer, M.

AU - Glenn, T.

AU - Alda, M.

AU - Andreassen, O. A.

AU - Angelopoulos, E.

AU - Ardau, R.

AU - Baethge, C.

AU - Bauer, R.

AU - Bellivier, F.

AU - Belmaker, R. H.

AU - Berk, M.

AU - Bjella, T. D.

AU - Bossini, L.

AU - Bersudsky, Y.

AU - Cheung, E. Y.W.

AU - Conell, J.

AU - Del Zompo, M.

AU - Dodd, S.

AU - Etain, B.

AU - Fagiolini, A.

AU - Frye, M. A.

AU - Fountoulakis, K. N.

AU - Garneau-Fournier, J.

AU - Gonzalez-Pinto, A.

AU - Harima, H.

AU - Hassel, S.

AU - Henry, C.

AU - Iacovides, A.

AU - Isometsä, E. T.

AU - Kapczinski, F.

AU - Kliwicki, S.

AU - König, B.

AU - Krogh, R.

AU - Kunz, M.

AU - Lafer, B.

AU - Larsen, E. R.

AU - Lewitzka, U.

AU - Lopez-Jaramillo, C.

AU - MacQueen, G.

AU - Manchia, M.

AU - Marsh, W.

AU - Martinez-Cengotitabengoa, M.

AU - Melle, I.

AU - Monteith, S.

AU - Morken, G.

AU - Munoz, R.

AU - Nery, F. G.

AU - O'Donovan, C.

AU - Osher, Y.

AU - Pfennig, A.

AU - Quiroz, D.

AU - Ramesar, R.

AU - Rasgon, N.

AU - Reif, A.

AU - Ritter, P.

AU - Rybakowski, J. K.

AU - Sagduyu, K.

AU - Scippa, A. M.

AU - Severus, E.

AU - Simhandl, C.

AU - Stein, D. J.

AU - Strejilevich, S.

AU - Hatim Sulaiman, A.

AU - Suominen, K.

AU - Tagata, H.

AU - Tatebayashi, Y.

AU - Torrent, C.

AU - Vieta, E.

AU - Viswanath, B.

AU - Wanchoo, M. J.

AU - Zetin, M.

AU - Whybrow, P. C.

N1 - Funding Information: We thank the European College of Neuropsychopharmacology (ECNP) Network Initiative for supporting the European Network of Bipolar Research Expert Centres (ENBREC). This work was also funded in part by the following: Canadian Institutes of Health Research (MA, Grant number 64410 ); the Research Council of Norway (OAA Grant numbers 213837; 223273; 217776 ); South-East Norway Health Authority (OAA, Grant number 2013-123 ); a NHMRC Senior Principal Research Fellowship ( M Berk, Grant number 1059660; INSERM (BE, Grant number C0829) and APHP (BE, Grant number AOR11096 ); the Spanish Government ( AGP, Grant numbers PS09/02002 CIBER Network; EC10-333, PI10/01430, PI10/01746, PI11/01977, PI11/02708, 2011/1064, 11-BI-01, 1677-DJ-030, EC10-220 ); European Regional Development Funds (Grant numbers UE/2012/FI-STAR, UE/2013/TENDERMH, UE/2013/MASTERMIND ), grants from Spanish Government (Grant numbers PI10/01430, PI10/01746, EC10-220, EC10-333, PI11/01977, 20111064, PI11/02708, PI12/02077, PI13/02252, PI13/00451 ), local grants from the Basque Government (Grant numbers 200911147, 2010111170, 2010112009, 2011111110, 2011111113 ); the Basque Foundation for Health Innovation and Research (Grant number BIO12/AL/002 ); the Spanish Clinical Research Network (Grant numbers CAIBER;1392-D-079 ) and the University of the Basque Country (Grant number IT679-13 ); Stanley Research Foundation (Grant number 03-RC-003 ); the Research Council of Norway (IM, Grant numbers ES488722, ES421716 ); the Regional Health Authority of South Eastern Norway (IM, Grants number 2011085, 2013088 ); DFG (AR, Grant numbers SFB TRR 58, B06, Z02 ); the DFG and Länder funds (AR, Grant number RTG1252/2 ); Medical Research Council of South Africa (DJS); Spanish Ministry of Economy and Competitiveness (EV, Grants number PI12/00912, PN 2008-2011 ); the I nstituto de Salud Carlos III- Subdirección General de Evaluación y Fomento de la Investigación (EV); Fondo Europeo de Desarrollo Regional Unión Europea. Una manera de hacer Europa (EV); CIBERSAM (EV); the Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya to the Bipolar Disorders Group (EV, Grant number 2009 SGR 1022 ), and the Department of Science and Technology INSPIRE scheme, Government of India (BV). Publisher Copyright: © 2014 Elsevier Masson SAS.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Purpose: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. Methods: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. Results: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. Conclusion: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

AB - Purpose: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. Methods: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. Results: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. Conclusion: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

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U2 - 10.1016/j.eurpsy.2014.10.005

DO - 10.1016/j.eurpsy.2014.10.005

M3 - Article

C2 - 25498240

AN - SCOPUS:84921025736

SN - 0924-9338

VL - 30

SP - 99

EP - 105

JO - European Psychiatry

JF - European Psychiatry

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ER -

Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

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