Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

Joanna Martin; Ekaterina A. Khramtsova; Slavina B. Goleva; Gabriella A. M. Blokland; Michela Traglia; Raymond K. Walters; Christopher Hubel; Jonathan R. Coleman; Gerome Breen; Anders D. Borglum; Ditte Demontis; Jakob Grove; Thomas Werge; Janita Bralten; Cynthia M. Bulik; Phil H. Lee; Carol A. Mathews; Roseann E. Peterson; Stacey J. Winham; Naomi Wray; Howard J. Edenberg; Wei Guo; Yin Yao; Benjamin M. Neale; Stephen Faraone; Tracey L. Petryshen; Lauren A. Weiss; Laramie E. Duncan; Jill M. Goldstein; Jordan W. Smoller; Barbara E. Stranger; Lea K. Davis; Schizophrenia Working Group of the Psychiatric Genomics Consortium

doi:10.1016/j.biopsych.2020.12.024

Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

Joanna Martin^*, Ekaterina A. Khramtsova, Slavina B. Goleva, Gabriella A. M. Blokland, Michela Traglia, Raymond K. Walters, Christopher Hubel, Jonathan R. Coleman, Gerome Breen, Anders D. Borglum, Ditte Demontis, Jakob Grove, Thomas Werge, Janita Bralten, Cynthia M. Bulik, Phil H. Lee, Carol A. Mathews, Roseann E. Peterson, Stacey J. Winham, Naomi WrayHoward J. Edenberg, Wei Guo, Yin Yao, Benjamin M. Neale, Stephen Faraone, Tracey L. Petryshen, Lauren A. Weiss, Laramie E. Duncan, Jill M. Goldstein, Jordan W. Smoller, Barbara E. Stranger, Lea K. Davis^*, Schizophrenia Working Group of the Psychiatric Genomics Consortium

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.

METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (r(g) < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.

RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although

CONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.

Original language	English
Pages (from-to)	1127-1137
Number of pages	11
Journal	Biological Psychiatry
Volume	89
Issue number	12
DOIs	https://doi.org/10.1016/j.biopsych.2020.12.024
Publication status	Published - 15 Jun 2021

Keywords

GENOME-WIDE ASSOCIATION
BIOBANK
RISK
MECHANISMS
JACKKNIFE
DISORDER
DISEASES
OVERLAP

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Martin, J., Khramtsova, E. A., Goleva, S. B., Blokland, G. A. M., Traglia, M., Walters, R. K., Hubel, C., Coleman, J. R., Breen, G., Borglum, A. D., Demontis, D., Grove, J., Werge, T., Bralten, J., Bulik, C. M., Lee, P. H., Mathews, C. A., Peterson, R. E., Winham, S. J., ... Schizophrenia Working Group of the Psychiatric Genomics Consortium (2021). Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits. Biological Psychiatry, 89(12), 1127-1137. https://doi.org/10.1016/j.biopsych.2020.12.024

@article{7180d0b3493f4208984faace4d65aee0,

title = "Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits",

abstract = "BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (r(g) < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, althoughCONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.",

keywords = "GENOME-WIDE ASSOCIATION, BIOBANK, RISK, MECHANISMS, JACKKNIFE, DISORDER, DISEASES, OVERLAP",

author = "Joanna Martin and Khramtsova, {Ekaterina A.} and Goleva, {Slavina B.} and Blokland, {Gabriella A. M.} and Michela Traglia and Walters, {Raymond K.} and Christopher Hubel and Coleman, {Jonathan R.} and Gerome Breen and Borglum, {Anders D.} and Ditte Demontis and Jakob Grove and Thomas Werge and Janita Bralten and Bulik, {Cynthia M.} and Lee, {Phil H.} and Mathews, {Carol A.} and Peterson, {Roseann E.} and Winham, {Stacey J.} and Naomi Wray and Edenberg, {Howard J.} and Wei Guo and Yin Yao and Neale, {Benjamin M.} and Stephen Faraone and Petryshen, {Tracey L.} and Weiss, {Lauren A.} and Duncan, {Laramie E.} and Goldstein, {Jill M.} and Smoller, {Jordan W.} and Stranger, {Barbara E.} and Davis, {Lea K.} and {Schizophrenia Working Group of the Psychiatric Genomics Consortium}",

note = "Funding Information: This work was supported by the Wellcome Trust (Grant No. 106047 [to JM]), S{\^e}r Cymru II COFUND Fellowship from the Welsh Government (to JM), National Institutes of Health (Grant No. 5U01MH109539 [to RKW], Grant Nos. R01NS102371-01A1 , R01MH113362 , U01HG009086 , R01MH118223 , and RM1HG009034 [to LKD], Grant No. R01CA229618 [to BES], Grant Nos. R00MH101367 and R01MH119243 [to PHL], and Grant No. MH109532 [to HJE]), Stanley Center for Psychiatric Research (to RKW), National Institute for Health Research (NIHR) as part of the Maudsley Biomedical Research Centre (to JRIC and GB), European Union Horizon 2020 Programme for research and innovation (H2020/2014-2020) (Grant No. 667302 [CoCA] [to ADB], Grant Nos. 667302 and 728018 [to SVF], and Grant No. 847879 [PRIME] [to JB]), European Union Seventh Framework Programme for research, technological development and demonstration (Grant No. 602805 [to SVF]), National Institute of Mental Health (Grant Nos. 5R01MH101519 and U01 MH109536-01 [to SVF], Grant No. K01MH113848 [to REP], and Grant No. R01MH114924 [to LAW and MT]), Brain & Behavior Research Foundation (Grant No. 28632 P&S Fund [to REP]), and National Institute of Neurological Disorders and Stroke (Grant Nos. R01 NS102371 and R01 NS105746 [to CAM]). Funding Information: The iPSYCH team was supported by the Lundbeck Foundation (Grant Nos. R165-2013-15320, R102-A9118, R155-2014-1724, and R248-2017-2003) and the universities and university hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis at GenomeDK were supported by the National Institute of Mental Health (Grant No. 1U01MH109514-01 [to ADB]). High-performance computer capacity for handling and statistical analysis of iPSYCH data at GenomeDK was provided by the Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). Funding Information: This study represents independent research partly funded by the NIHR Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King{\textquoteright}s College London. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care. Funding Information: High-performance computing facilities were funded with capital equipment grants from the Guy{\textquoteright}s and St. Thomas{\textquoteright} Charity (Grant No. TR130505) and Maudsley Charity (Grant No. 980). Funding Information: The original GWAS data were supported by National Institute of Mental Health Psychiatric Genomics Consortium (PGC) grants (Grant Nos. U01 MH109528, U01 MH109539, U01 MH109536, U01 MH109501, U01 MH109514, U01 MH109499, and U01 MH109532). Funding Information: This work was supported by the Wellcome Trust (Grant No. 106047 [to JM]), S{\^e}r Cymru II COFUND Fellowship from the Welsh Government (to JM), National Institutes of Health (Grant No. 5U01MH109539 [to RKW], Grant Nos. R01NS102371-01A1, R01MH113362, U01HG009086, R01MH118223, and RM1HG009034 [to LKD], Grant No. R01CA229618 [to BES], Grant Nos. R00MH101367 and R01MH119243 [to PHL], and Grant No. MH109532 [to HJE]), Stanley Center for Psychiatric Research (to RKW), National Institute for Health Research (NIHR) as part of the Maudsley Biomedical Research Centre (to JRIC and GB), European Union Horizon 2020 Programme for research and innovation (H2020/2014-2020) (Grant No. 667302 [CoCA] [to ADB], Grant Nos. 667302 and 728018 [to SVF], and Grant No. 847879 [PRIME] [to JB]), European Union Seventh Framework Programme for research, technological development and demonstration (Grant No. 602805 [to SVF]), National Institute of Mental Health (Grant Nos. 5R01MH101519 and U01 MH109536-01 [to SVF], Grant No. K01MH113848 [to REP], and Grant No. R01MH114924 [to LAW and MT]), Brain & Behavior Research Foundation (Grant No. 28632 P&S Fund [to REP]), and National Institute of Neurological Disorders and Stroke (Grant Nos. R01 NS102371 and R01 NS105746 [to CAM]). High-performance computing facilities were funded with capital equipment grants from the Guy's and St. Thomas{\textquoteright} Charity (Grant No. TR130505) and Maudsley Charity (Grant No. 980). The iPSYCH team was supported by the Lundbeck Foundation (Grant Nos. R165-2013-15320, R102-A9118, R155-2014-1724, and R248-2017-2003) and the universities and university hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis at GenomeDK were supported by the National Institute of Mental Health (Grant No. 1U01MH109514-01 [to ADB]). High-performance computer capacity for handling and statistical analysis of iPSYCH data at GenomeDK was provided by the Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). This work utilized the computational resources of the Dutch national e-infrastructure with the support of SURF Cooperative (https://userinfo.surfsara.nl/). The original GWAS data were supported by National Institute of Mental Health Psychiatric Genomics Consortium (PGC) grants (Grant Nos. U01 MH109528, U01 MH109539, U01 MH109536, U01 MH109501, U01 MH109514, U01 MH109499, and U01 MH109532). This study represents independent research partly funded by the NIHR Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care. The other members of the Sex Differences Cross-Disorder Analysis Group of the PGC are Martin Alda, Marco Bortolato, Christie L. Burton, Enda Byrne, Caitlin E. Carey, Lauren Erdman, Laura M. Huckins, Manuel Mattheisen, Elise Robinson, and Eli Stahl. JM and EAK were responsible for study conception, design, analyses, and writing. SBG and GAMB were responsible for analyses and writing. MT, RKW, CH, JRIC, and GB were responsible for analyses and editing. ADB, DD, JG, TW, JB, CMB, PHL, CAM, REP, SJW, NW, HJE, WG, YY, BMN, SVF, TLP, LAW, and LED were responsible for editing. JMG and JWS were responsible for writing. BES and LKD were responsible for writing and analytic supervision. We thank Dr. Helena Gaspar for providing a python script that was used to estimate differences in linkage disequilibrium score regression genetic correlation across sex and Donald Hucks for computing population prevalence by sex for the BioVU (Vanderbilt University Medical Center biobank) population. We also thank the following consortia and groups that contributed data: Attention Deficit Hyperactivity Disorder Working Group of the PGC and iPSYCH, Autism Spectrum Disorder Working Group of the PGC and iPSYCH, Bipolar Disorder Working Group of the PGC, Major Depressive Disorder Working Group of the PGC, Obsessive Compulsive Disorder Working Group of the PGC, Post-traumatic Stress Disorder Working Group of the PGC, Schizophrenia Working Group of the PGC, Substance Use Disorders Working Group of the PGC, and UK Biobank GWAS results generated by the Neale Lab (http://www.nealelab.is/uk-biobank/). CMB has received a grant from and is a Scientific Advisory Board member of Shire, is a consultant for Idorsia Pharmaceuticals, and has received author royalties from Pearson. EAK is employed by Janssen Pharmaceutical Companies of Johnson & Johnson. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: {\textcopyright} 2021 Society of Biological Psychiatry",

year = "2021",

month = jun,

day = "15",

doi = "10.1016/j.biopsych.2020.12.024",

language = "English",

volume = "89",

pages = "1127--1137",

journal = "Biological Psychiatry",

issn = "0006-3223",

publisher = "Elsevier Science",

number = "12",

}

Martin, J, Khramtsova, EA, Goleva, SB, Blokland, GAM, Traglia, M, Walters, RK, Hubel, C, Coleman, JR, Breen, G, Borglum, AD, Demontis, D, Grove, J, Werge, T, Bralten, J, Bulik, CM, Lee, PH, Mathews, CA, Peterson, RE, Winham, SJ, Wray, N, Edenberg, HJ, Guo, W, Yao, Y, Neale, BM, Faraone, S, Petryshen, TL, Weiss, LA, Duncan, LE, Goldstein, JM, Smoller, JW, Stranger, BE, Davis, LK & Schizophrenia Working Group of the Psychiatric Genomics Consortium 2021, 'Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits', Biological Psychiatry, vol. 89, no. 12, pp. 1127-1137. https://doi.org/10.1016/j.biopsych.2020.12.024

TY - JOUR

T1 - Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

AU - Martin, Joanna

AU - Khramtsova, Ekaterina A.

AU - Goleva, Slavina B.

AU - Blokland, Gabriella A. M.

AU - Traglia, Michela

AU - Walters, Raymond K.

AU - Hubel, Christopher

AU - Coleman, Jonathan R.

AU - Breen, Gerome

AU - Borglum, Anders D.

AU - Demontis, Ditte

AU - Grove, Jakob

AU - Werge, Thomas

AU - Bralten, Janita

AU - Bulik, Cynthia M.

AU - Lee, Phil H.

AU - Mathews, Carol A.

AU - Peterson, Roseann E.

AU - Winham, Stacey J.

AU - Wray, Naomi

AU - Edenberg, Howard J.

AU - Guo, Wei

AU - Yao, Yin

AU - Neale, Benjamin M.

AU - Faraone, Stephen

AU - Petryshen, Tracey L.

AU - Weiss, Lauren A.

AU - Duncan, Laramie E.

AU - Goldstein, Jill M.

AU - Smoller, Jordan W.

AU - Stranger, Barbara E.

AU - Davis, Lea K.

AU - Schizophrenia Working Group of the Psychiatric Genomics Consortium

N1 - Funding Information: This work was supported by the Wellcome Trust (Grant No. 106047 [to JM]), Sêr Cymru II COFUND Fellowship from the Welsh Government (to JM), National Institutes of Health (Grant No. 5U01MH109539 [to RKW], Grant Nos. R01NS102371-01A1 , R01MH113362 , U01HG009086 , R01MH118223 , and RM1HG009034 [to LKD], Grant No. R01CA229618 [to BES], Grant Nos. R00MH101367 and R01MH119243 [to PHL], and Grant No. MH109532 [to HJE]), Stanley Center for Psychiatric Research (to RKW), National Institute for Health Research (NIHR) as part of the Maudsley Biomedical Research Centre (to JRIC and GB), European Union Horizon 2020 Programme for research and innovation (H2020/2014-2020) (Grant No. 667302 [CoCA] [to ADB], Grant Nos. 667302 and 728018 [to SVF], and Grant No. 847879 [PRIME] [to JB]), European Union Seventh Framework Programme for research, technological development and demonstration (Grant No. 602805 [to SVF]), National Institute of Mental Health (Grant Nos. 5R01MH101519 and U01 MH109536-01 [to SVF], Grant No. K01MH113848 [to REP], and Grant No. R01MH114924 [to LAW and MT]), Brain & Behavior Research Foundation (Grant No. 28632 P&S Fund [to REP]), and National Institute of Neurological Disorders and Stroke (Grant Nos. R01 NS102371 and R01 NS105746 [to CAM]). Funding Information: The iPSYCH team was supported by the Lundbeck Foundation (Grant Nos. R165-2013-15320, R102-A9118, R155-2014-1724, and R248-2017-2003) and the universities and university hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis at GenomeDK were supported by the National Institute of Mental Health (Grant No. 1U01MH109514-01 [to ADB]). High-performance computer capacity for handling and statistical analysis of iPSYCH data at GenomeDK was provided by the Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). Funding Information: This study represents independent research partly funded by the NIHR Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care. Funding Information: High-performance computing facilities were funded with capital equipment grants from the Guy’s and St. Thomas’ Charity (Grant No. TR130505) and Maudsley Charity (Grant No. 980). Funding Information: The original GWAS data were supported by National Institute of Mental Health Psychiatric Genomics Consortium (PGC) grants (Grant Nos. U01 MH109528, U01 MH109539, U01 MH109536, U01 MH109501, U01 MH109514, U01 MH109499, and U01 MH109532). Funding Information: This work was supported by the Wellcome Trust (Grant No. 106047 [to JM]), Sêr Cymru II COFUND Fellowship from the Welsh Government (to JM), National Institutes of Health (Grant No. 5U01MH109539 [to RKW], Grant Nos. R01NS102371-01A1, R01MH113362, U01HG009086, R01MH118223, and RM1HG009034 [to LKD], Grant No. R01CA229618 [to BES], Grant Nos. R00MH101367 and R01MH119243 [to PHL], and Grant No. MH109532 [to HJE]), Stanley Center for Psychiatric Research (to RKW), National Institute for Health Research (NIHR) as part of the Maudsley Biomedical Research Centre (to JRIC and GB), European Union Horizon 2020 Programme for research and innovation (H2020/2014-2020) (Grant No. 667302 [CoCA] [to ADB], Grant Nos. 667302 and 728018 [to SVF], and Grant No. 847879 [PRIME] [to JB]), European Union Seventh Framework Programme for research, technological development and demonstration (Grant No. 602805 [to SVF]), National Institute of Mental Health (Grant Nos. 5R01MH101519 and U01 MH109536-01 [to SVF], Grant No. K01MH113848 [to REP], and Grant No. R01MH114924 [to LAW and MT]), Brain & Behavior Research Foundation (Grant No. 28632 P&S Fund [to REP]), and National Institute of Neurological Disorders and Stroke (Grant Nos. R01 NS102371 and R01 NS105746 [to CAM]). High-performance computing facilities were funded with capital equipment grants from the Guy's and St. Thomas’ Charity (Grant No. TR130505) and Maudsley Charity (Grant No. 980). The iPSYCH team was supported by the Lundbeck Foundation (Grant Nos. R165-2013-15320, R102-A9118, R155-2014-1724, and R248-2017-2003) and the universities and university hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. Data handling and analysis at GenomeDK were supported by the National Institute of Mental Health (Grant No. 1U01MH109514-01 [to ADB]). High-performance computer capacity for handling and statistical analysis of iPSYCH data at GenomeDK was provided by the Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to ADB). This work utilized the computational resources of the Dutch national e-infrastructure with the support of SURF Cooperative (https://userinfo.surfsara.nl/). The original GWAS data were supported by National Institute of Mental Health Psychiatric Genomics Consortium (PGC) grants (Grant Nos. U01 MH109528, U01 MH109539, U01 MH109536, U01 MH109501, U01 MH109514, U01 MH109499, and U01 MH109532). This study represents independent research partly funded by the NIHR Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care. The other members of the Sex Differences Cross-Disorder Analysis Group of the PGC are Martin Alda, Marco Bortolato, Christie L. Burton, Enda Byrne, Caitlin E. Carey, Lauren Erdman, Laura M. Huckins, Manuel Mattheisen, Elise Robinson, and Eli Stahl. JM and EAK were responsible for study conception, design, analyses, and writing. SBG and GAMB were responsible for analyses and writing. MT, RKW, CH, JRIC, and GB were responsible for analyses and editing. ADB, DD, JG, TW, JB, CMB, PHL, CAM, REP, SJW, NW, HJE, WG, YY, BMN, SVF, TLP, LAW, and LED were responsible for editing. JMG and JWS were responsible for writing. BES and LKD were responsible for writing and analytic supervision. We thank Dr. Helena Gaspar for providing a python script that was used to estimate differences in linkage disequilibrium score regression genetic correlation across sex and Donald Hucks for computing population prevalence by sex for the BioVU (Vanderbilt University Medical Center biobank) population. We also thank the following consortia and groups that contributed data: Attention Deficit Hyperactivity Disorder Working Group of the PGC and iPSYCH, Autism Spectrum Disorder Working Group of the PGC and iPSYCH, Bipolar Disorder Working Group of the PGC, Major Depressive Disorder Working Group of the PGC, Obsessive Compulsive Disorder Working Group of the PGC, Post-traumatic Stress Disorder Working Group of the PGC, Schizophrenia Working Group of the PGC, Substance Use Disorders Working Group of the PGC, and UK Biobank GWAS results generated by the Neale Lab (http://www.nealelab.is/uk-biobank/). CMB has received a grant from and is a Scientific Advisory Board member of Shire, is a consultant for Idorsia Pharmaceuticals, and has received author royalties from Pearson. EAK is employed by Janssen Pharmaceutical Companies of Johnson & Johnson. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological Psychiatry

PY - 2021/6/15

Y1 - 2021/6/15

N2 - BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (r(g) < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, althoughCONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.

AB - BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (r(g) < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, althoughCONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.

KW - GENOME-WIDE ASSOCIATION

KW - BIOBANK

KW - RISK

KW - MECHANISMS

KW - JACKKNIFE

KW - DISORDER

KW - DISEASES

KW - OVERLAP

U2 - 10.1016/j.biopsych.2020.12.024

DO - 10.1016/j.biopsych.2020.12.024

M3 - Article

C2 - 33648717

SN - 0006-3223

VL - 89

SP - 1127

EP - 1137

JO - Biological Psychiatry

JF - Biological Psychiatry

IS - 12

ER -