Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis

Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ware, Erin B. [verfasserIn] Mukherjee, Bhramar Sun, Yan V. Diez-Roux, Ana V. Kardia, Sharon L.R. Smith, Jennifer A.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Depressive symptoms Generalized estimating equations Genome-wide association studies Longitudinal Psychogenetics

Anmerkung:	© Ware et al. 2015

Übergeordnetes Werk:	Enthalten in: BMC genetics - London : BioMed Central, 2000, 16(2015), 1 vom: 12. Okt.
Übergeordnetes Werk:	volume:16 ; year:2015 ; number:1 ; day:12 ; month:10

Links:	Volltext

DOI / URN:	10.1186/s12863-015-0274-0

Katalog-ID:	SPR027014037

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520			\|a Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses.
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allfields	10.1186/s12863-015-0274-0 doi (DE-627)SPR027014037 (SPR)s12863-015-0274-0-e DE-627 ger DE-627 rakwb eng Ware, Erin B. verfasserin aut Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Ware et al. 2015 Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213 Mukherjee, Bhramar aut Sun, Yan V. aut Diez-Roux, Ana V. aut Kardia, Sharon L.R. aut Smith, Jennifer A. aut Enthalten in BMC genetics London : BioMed Central, 2000 16(2015), 1 vom: 12. Okt. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:16 year:2015 number:1 day:12 month:10 https://dx.doi.org/10.1186/s12863-015-0274-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2015 1 12 10
spelling	10.1186/s12863-015-0274-0 doi (DE-627)SPR027014037 (SPR)s12863-015-0274-0-e DE-627 ger DE-627 rakwb eng Ware, Erin B. verfasserin aut Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Ware et al. 2015 Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213 Mukherjee, Bhramar aut Sun, Yan V. aut Diez-Roux, Ana V. aut Kardia, Sharon L.R. aut Smith, Jennifer A. aut Enthalten in BMC genetics London : BioMed Central, 2000 16(2015), 1 vom: 12. Okt. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:16 year:2015 number:1 day:12 month:10 https://dx.doi.org/10.1186/s12863-015-0274-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2015 1 12 10
allfields_unstemmed	10.1186/s12863-015-0274-0 doi (DE-627)SPR027014037 (SPR)s12863-015-0274-0-e DE-627 ger DE-627 rakwb eng Ware, Erin B. verfasserin aut Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Ware et al. 2015 Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213 Mukherjee, Bhramar aut Sun, Yan V. aut Diez-Roux, Ana V. aut Kardia, Sharon L.R. aut Smith, Jennifer A. aut Enthalten in BMC genetics London : BioMed Central, 2000 16(2015), 1 vom: 12. Okt. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:16 year:2015 number:1 day:12 month:10 https://dx.doi.org/10.1186/s12863-015-0274-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2015 1 12 10
allfieldsGer	10.1186/s12863-015-0274-0 doi (DE-627)SPR027014037 (SPR)s12863-015-0274-0-e DE-627 ger DE-627 rakwb eng Ware, Erin B. verfasserin aut Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Ware et al. 2015 Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213 Mukherjee, Bhramar aut Sun, Yan V. aut Diez-Roux, Ana V. aut Kardia, Sharon L.R. aut Smith, Jennifer A. aut Enthalten in BMC genetics London : BioMed Central, 2000 16(2015), 1 vom: 12. Okt. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:16 year:2015 number:1 day:12 month:10 https://dx.doi.org/10.1186/s12863-015-0274-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2015 1 12 10
allfieldsSound	10.1186/s12863-015-0274-0 doi (DE-627)SPR027014037 (SPR)s12863-015-0274-0-e DE-627 ger DE-627 rakwb eng Ware, Erin B. verfasserin aut Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Ware et al. 2015 Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213 Mukherjee, Bhramar aut Sun, Yan V. aut Diez-Roux, Ana V. aut Kardia, Sharon L.R. aut Smith, Jennifer A. aut Enthalten in BMC genetics London : BioMed Central, 2000 16(2015), 1 vom: 12. Okt. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:16 year:2015 number:1 day:12 month:10 https://dx.doi.org/10.1186/s12863-015-0274-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2015 1 12 10
language	English
source	Enthalten in BMC genetics 16(2015), 1 vom: 12. Okt. volume:16 year:2015 number:1 day:12 month:10
sourceStr	Enthalten in BMC genetics 16(2015), 1 vom: 12. Okt. volume:16 year:2015 number:1 day:12 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Depressive symptoms Generalized estimating equations Genome-wide association studies Longitudinal Psychogenetics
isfreeaccess_bool	true
container_title	BMC genetics
authorswithroles_txt_mv	Ware, Erin B. @@aut@@ Mukherjee, Bhramar @@aut@@ Sun, Yan V. @@aut@@ Diez-Roux, Ana V. @@aut@@ Kardia, Sharon L.R. @@aut@@ Smith, Jennifer A. @@aut@@
publishDateDaySort_date	2015-10-12T00:00:00Z
hierarchy_top_id	326644938
id	SPR027014037
language_de	englisch
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This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. 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author	Ware, Erin B.
spellingShingle	Ware, Erin B. misc Depressive symptoms misc Generalized estimating equations misc Genome-wide association studies misc Longitudinal misc Psychogenetics Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
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topic_title	Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis Depressive symptoms (dpeaa)DE-He213 Generalized estimating equations (dpeaa)DE-He213 Genome-wide association studies (dpeaa)DE-He213 Longitudinal (dpeaa)DE-He213 Psychogenetics (dpeaa)DE-He213
topic	misc Depressive symptoms misc Generalized estimating equations misc Genome-wide association studies misc Longitudinal misc Psychogenetics
topic_unstemmed	misc Depressive symptoms misc Generalized estimating equations misc Genome-wide association studies misc Longitudinal misc Psychogenetics
topic_browse	misc Depressive symptoms misc Generalized estimating equations misc Genome-wide association studies misc Longitudinal misc Psychogenetics
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title	Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
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title_full	Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
author_sort	Ware, Erin B.
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author_browse	Ware, Erin B. Mukherjee, Bhramar Sun, Yan V. Diez-Roux, Ana V. Kardia, Sharon L.R. Smith, Jennifer A.
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title_sort	comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
title_auth	Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
abstract	Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. © Ware et al. 2015
abstractGer	Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. © Ware et al. 2015
abstract_unstemmed	Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×$ 10^{−8} $ < p-value ≤ 5×$ 10^{−6} $) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses. © Ware et al. 2015
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title_short	Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
url	https://dx.doi.org/10.1186/s12863-015-0274-0
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Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis

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