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1. Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression

Author

Guintivano, Jerry, Byrne, Enda M, Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E, Aberg, Karolina A, Adams, Mark J, Campbell, Archie, Campbell, Megan L, Choi, Karmel W, Corfield, Elizabeth C, Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L, Mullaert, Jimmy, Peterson, Roseann E, Raffield, Laura M, Sallis, Hannah M, Sealock, Julia M, Walker, Alicia, Watson, Hunna J, Xiong, Ying, Yang, Jessica M K, Anney, Richard J L, Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A, Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F, Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H, Viktorin, Alexander, Andreassen, Ole A, Bigdeli, Tim B, Davis, Lea K, Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A, Frey, Benicio N, Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L, Krohn, Holly, Kunovac Kallak, Theodora, Li, Yun, Martin, Nicholas G, McIntosh, Andrew M, Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M, Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Robertson Blackmore, Emma, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W, Stein, Dan J, Stowe, Zachary N, Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J, van den Oord, Edwin J C G, Vigod, Simone N, Werge, Thomas, Westlye, Lars T, Whiteman, David C, Zar, Heather J, Wray, Naomi, Meltzer-Brody, Samantha, Sullivan, Patrick, Guintivano, Jerry, Byrne, Enda M, Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E, Aberg, Karolina A, Adams, Mark J, Campbell, Archie, Campbell, Megan L, Choi, Karmel W, Corfield, Elizabeth C, Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L, Mullaert, Jimmy, Peterson, Roseann E, Raffield, Laura M, Sallis, Hannah M, Sealock, Julia M, Walker, Alicia, Watson, Hunna J, Xiong, Ying, Yang, Jessica M K, Anney, Richard J L, Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A, Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F, Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H, Viktorin, Alexander, Andreassen, Ole A, Bigdeli, Tim B, Davis, Lea K, Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A, Frey, Benicio N, Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L, Krohn, Holly, Kunovac Kallak, Theodora, Li, Yun, Martin, Nicholas G, McIntosh, Andrew M, Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M, Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Robertson Blackmore, Emma, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W, Stein, Dan J, Stowe, Zachary N, Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J, van den Oord, Edwin J C G, Vigod, Simone N, Werge, Thomas, Westlye, Lars T, Whiteman, David C, Zar, Heather J, Wray, Naomi, Meltzer-Brody, Samantha, and Sullivan, Patrick

Abstract

OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).

Published
2023
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2. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains:[Inkl. Correction]

Author

Demontis, Ditte, Walters, G. Bragi, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine Tollerup, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas D., Duan, Jinjie, Satterstrom, F. Kyle, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur O., Magnusson, Sigurdur H., Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda S., Agerbo, Esben, Hoffman, Gabriel E., Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret I., Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah E., Zayats, Tetyana, Rajagopal, Veera M., Havdahl, Alexandra, Doyle, Alysa, Reif, Andreas, Thapar, Anita, Cormand, Bru, Liao, Calwing, Burton, Christie, Bau, Claiton H.D., Rovaris, Diego Luiz, Sonuga-Barke, Edmund, Corfield, Elizabeth, Grevet, Eugenio Horacio, Larsson, Henrik, Gizer, Ian R., Nordentoft, Merete, Werge, Thomas, Demontis, Ditte, Walters, G. Bragi, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine Tollerup, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas D., Duan, Jinjie, Satterstrom, F. Kyle, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur O., Magnusson, Sigurdur H., Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda S., Agerbo, Esben, Hoffman, Gabriel E., Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret I., Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah E., Zayats, Tetyana, Rajagopal, Veera M., Havdahl, Alexandra, Doyle, Alysa, Reif, Andreas, Thapar, Anita, Cormand, Bru, Liao, Calwing, Burton, Christie, Bau, Claiton H.D., Rovaris, Diego Luiz, Sonuga-Barke, Edmund, Corfield, Elizabeth, Grevet, Eugenio Horacio, Larsson, Henrik, Gizer, Ian R., Nordentoft, Merete, and Werge, Thomas

Abstract

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with a major genetic component. Here, we present a genome-wide association study meta-analysis of ADHD comprising 38,691 individuals with ADHD and 186,843 controls. We identified 27 genome-wide significant loci, highlighting 76 potential risk genes enriched among genes expressed particularly in early brain development. Overall, ADHD genetic risk was associated with several brain-specific neuronal subtypes and midbrain dopaminergic neurons. In exome-sequencing data from 17,896 individuals, we identified an increased load of rare protein-truncating variants in ADHD for a set of risk genes enriched with probable causal common variants, potentially implicating SORCS3 in ADHD by both common and rare variants. Bivariate Gaussian mixture modeling estimated that 84–98% of ADHD-influencing variants are shared with other psychiatric disorders. In addition, common-variant ADHD risk was associated with impaired complex cognition such as verbal reasoning and a range of executive functions, including attention.

Published
2023

3. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains:[Inkl. Correction]

Author

Demontis, Ditte, Walters, G. Bragi, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine Tollerup, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas D., Duan, Jinjie, Satterstrom, F. Kyle, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur O., Magnusson, Sigurdur H., Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda S., Agerbo, Esben, Hoffman, Gabriel E., Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret I., Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah E., Zayats, Tetyana, Rajagopal, Veera M., Havdahl, Alexandra, Doyle, Alysa, Reif, Andreas, Thapar, Anita, Cormand, Bru, Liao, Calwing, Burton, Christie, Bau, Claiton H.D., Rovaris, Diego Luiz, Sonuga-Barke, Edmund, Corfield, Elizabeth, Grevet, Eugenio Horacio, Larsson, Henrik, Gizer, Ian R., Nordentoft, Merete, Werge, Thomas, Demontis, Ditte, Walters, G. Bragi, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine Tollerup, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas D., Duan, Jinjie, Satterstrom, F. Kyle, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur O., Magnusson, Sigurdur H., Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda S., Agerbo, Esben, Hoffman, Gabriel E., Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret I., Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah E., Zayats, Tetyana, Rajagopal, Veera M., Havdahl, Alexandra, Doyle, Alysa, Reif, Andreas, Thapar, Anita, Cormand, Bru, Liao, Calwing, Burton, Christie, Bau, Claiton H.D., Rovaris, Diego Luiz, Sonuga-Barke, Edmund, Corfield, Elizabeth, Grevet, Eugenio Horacio, Larsson, Henrik, Gizer, Ian R., Nordentoft, Merete, and Werge, Thomas

Abstract

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with a major genetic component. Here, we present a genome-wide association study meta-analysis of ADHD comprising 38,691 individuals with ADHD and 186,843 controls. We identified 27 genome-wide significant loci, highlighting 76 potential risk genes enriched among genes expressed particularly in early brain development. Overall, ADHD genetic risk was associated with several brain-specific neuronal subtypes and midbrain dopaminergic neurons. In exome-sequencing data from 17,896 individuals, we identified an increased load of rare protein-truncating variants in ADHD for a set of risk genes enriched with probable causal common variants, potentially implicating SORCS3 in ADHD by both common and rare variants. Bivariate Gaussian mixture modeling estimated that 84–98% of ADHD-influencing variants are shared with other psychiatric disorders. In addition, common-variant ADHD risk was associated with impaired complex cognition such as verbal reasoning and a range of executive functions, including attention.

Published
2023

4. Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression

Author

Guintivano, Jerry, Byrne, Enda M., Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E., Aberg, Karolina A., Adams, Mark J., Campbell, Archie, Campbell, Megan L., Choi, Karmel W., Corfield, Elizabeth C., Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L., Mullaert, Jimmy, Peterson, Roseann E., Raffield, Laura M., Sallis, Hannah M., Sealock, Julia M., Walker, Alicia, Watson, Hunna J., Xiong, Ying, Yang, Jessica M. K., Anney, Richard J. L., Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A., Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F., Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H., Viktorin, Alexander, Andreassen, Ole A., Bigdeli, Tim B., Davis, Lea K., Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A., Frey, Benicio N., Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L., Krohn, Holly, Kallak, Theodora Kunovac, Li, Yun, Martin, Nicholas G., McIntosh, Andrew M., Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M., Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Blackmore, Emma Robertson, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W., Stein, Dan J., Stowe, Zachary N., Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J., van den Oord, Edwin J. C. G., Vigod, Simone N., Werge, Thomas, Westlye, Lars T., Whiteman, David C., Zar, Heather J., Wray, Naomi, Meltzer-Brody, Samantha, Sullivan, Patrick, Guintivano, Jerry, Byrne, Enda M., Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E., Aberg, Karolina A., Adams, Mark J., Campbell, Archie, Campbell, Megan L., Choi, Karmel W., Corfield, Elizabeth C., Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L., Mullaert, Jimmy, Peterson, Roseann E., Raffield, Laura M., Sallis, Hannah M., Sealock, Julia M., Walker, Alicia, Watson, Hunna J., Xiong, Ying, Yang, Jessica M. K., Anney, Richard J. L., Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A., Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F., Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H., Viktorin, Alexander, Andreassen, Ole A., Bigdeli, Tim B., Davis, Lea K., Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A., Frey, Benicio N., Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L., Krohn, Holly, Kallak, Theodora Kunovac, Li, Yun, Martin, Nicholas G., McIntosh, Andrew M., Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M., Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Blackmore, Emma Robertson, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W., Stein, Dan J., Stowe, Zachary N., Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J., van den Oord, Edwin J. C. G., Vigod, Simone N., Werge, Thomas, Westlye, Lars T., Whiteman, David C., Zar, Heather J., Wray, Naomi, Meltzer-Brody, Samantha, and Sullivan, Patrick

Abstract

OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD.METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system.RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD.CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).

Published
2023

5. Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression

Author

Guintivano, Jerry, Byrne, Enda M., Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E., Aberg, Karolina A., Adams, Mark J., Campbell, Archie, Campbell, Megan L., Choi, Karmel W., Corfield, Elizabeth C., Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L., Mullaert, Jimmy, Peterson, Roseann E., Raffield, Laura M., Sallis, Hannah M., Sealock, Julia M., Walker, Alicia, Watson, Hunna J., Xiong, Ying, Yang, Jessica M. K., Anney, Richard J. L., Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A., Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F., Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H., Viktorin, Alexander, Andreassen, Ole A., Bigdeli, Tim B., Davis, Lea K., Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A., Frey, Benicio N., Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L., Krohn, Holly, Kallak, Theodora Kunovac, Li, Yun, Martin, Nicholas G., McIntosh, Andrew M., Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M., Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Blackmore, Emma Robertson, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W., Stein, Dan J., Stowe, Zachary N., Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J., van den Oord, Edwin J. C. G., Vigod, Simone N., Werge, Thomas, Westlye, Lars T., Whiteman, David C., Zar, Heather J., Wray, Naomi, Meltzer-Brody, Samantha, Sullivan, Patrick, Guintivano, Jerry, Byrne, Enda M., Kiewa, Jacqueline, Yao, Shuyang, Bauer, Anna E., Aberg, Karolina A., Adams, Mark J., Campbell, Archie, Campbell, Megan L., Choi, Karmel W., Corfield, Elizabeth C., Havdahl, Alexandra, Hucks, Donald, Koen, Nastassja, Lu, Yi, Mægbæk, Merete L., Mullaert, Jimmy, Peterson, Roseann E., Raffield, Laura M., Sallis, Hannah M., Sealock, Julia M., Walker, Alicia, Watson, Hunna J., Xiong, Ying, Yang, Jessica M. K., Anney, Richard J. L., Gordon-Smith, Katherine, Hubbard, Leon, Jones, Lisa A., Mihaescu, Raluca, Nyegaard, Mette, Pardiñas, Antonio F., Perry, Amy, Saquib, Nazmus, Shadyab, Aladdin H., Viktorin, Alexander, Andreassen, Ole A., Bigdeli, Tim B., Davis, Lea K., Dennis, Cindy-Lee, Di Florio, Arianna, Dubertret, Caroline, Feng, Yen-Chen A., Frey, Benicio N., Grigoriadis, Sophie, Gloaguen, Emilie, Jones, Ian, Kennedy, James L., Krohn, Holly, Kallak, Theodora Kunovac, Li, Yun, Martin, Nicholas G., McIntosh, Andrew M., Milgrom, Jeannette, Munk-Olsen, Trine, Oberlander, Tim, Olsen, Catherine M., Ramoz, Nicolas, Reichborn-Kjennerud, Ted, Blackmore, Emma Robertson, Rubinow, David, Skalkidou, Alkistis, Smoller, Jordan W., Stein, Dan J., Stowe, Zachary N., Taylor, Valerie, Tebeka, Sarah, Tesli, Martin, Van Lieshout, Ryan J., van den Oord, Edwin J. C. G., Vigod, Simone N., Werge, Thomas, Westlye, Lars T., Whiteman, David C., Zar, Heather J., Wray, Naomi, Meltzer-Brody, Samantha, and Sullivan, Patrick

Abstract

OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD.METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system.RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD.CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).

Published
2023

6. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared, Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared, Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
Full Text
View/download PDF

7. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
Full Text
View/download PDF

8. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
Full Text
View/download PDF

9. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
Full Text
View/download PDF

10. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects.

Author

Howe, Laurence J, Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Social Science Genetic Association Consortium, Within Family Consortium, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, Brumpton, Ben, Howe, Laurence J, Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Social Science Genetic Association Consortium, Within Family Consortium, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, and Brumpton, Ben

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Published
2022

11. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
Full Text
View/download PDF

12. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, Davies, Neil M., Howe, Laurence J., Nivard, Michel G., Morris, Tim T., Hansen, Ailin F., Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A., Palviainen, Teemu, van der Zee, Matthijs D., Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M., Bielak, Lawrence F., Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A., Reynolds, Chandra A., Balbona, Jared V., Andreassen, Ole A., Ask, Helga, Baras, Aris, Bauer, Christopher R., Boomsma, Dorret I., Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C., Dokuru, Deepika R., Evans, Luke M., de Geus, Eco J. C., Giddaluru, Sudheer, Gordon, Scott D., Harden, K. Paige, Hill, W. David, Hughes, Amanda, Kerr, Shona M., Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A., Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik K. E., Mallard, Travis T., Martikainen, Pekka, Mills, Melinda C., Njolstad, Pal Rasmus, Overton, John D., Pedersen, Nancy L., Porteous, David J., Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C., Stoltenberg, Camilla, Tucker-Drob, Elliot M., Wright, Margaret J., Hewitt, John K., Keller, Matthew C., Stallings, Michael C., Lee, James J., Christensen, Kaare, Kardia, Sharon L. R., Peyser, Patricia A., Smith, Jennifer A., Wilson, James F., Hopper, John L., Hagg, Sara, Spector, Tim D., Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G., Oskarsson, Sven, Justice, Anne E., Millwood, Iona Y., Hveem, Kristian, Naess, Oyvind, Willer, Cristen J., Asvold, Bjorn Olav, Koellinger, Philipp D., Kaprio, Jaakko, Medland, Sarah E., Walters, Robin G., Benjamin, Daniel J., Turley, Patrick, Evans, David M., Smith, George Davey, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M.

Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects. Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Published
2022
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13. Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

Author

Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, Arnold, P.D., Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, and Arnold, P.D.

Abstract

Contains fulltext : 231401.pdf (publisher's version ) (Open Access)

Published
2021

14. Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

Author

Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, Arnold, P.D., Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, and Arnold, P.D.

Abstract

Contains fulltext : 231401.pdf (publisher's version ) (Open Access)

Published
2021

15. Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

Author

Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, Arnold, P.D., Burton, C., Lemire, M., Xiao, B., Corfield, Elizabeth C., Erdman, Lauren, Bralten, J.B., Poelmans, G.J.V., Crosbie, Jennifer, and Arnold, P.D.

Abstract

Contains fulltext : 231401.pdf (publisher's version ) (Open Access)

Published
2021

16. Characterising the relationship between fatigue and depression

Author

Corfield, Elizabeth C. and Corfield, Elizabeth C.

Abstract

This dissertation focused on increasing our knowledge and understanding of the comorbidity and genetics of fatigue and depression. Statistical computations, including twin modelling and analysis of genome-wide association data, were conducted to characterise the phenotypic and genetic relationship between fatigue and depression. The high levels of comorbidity observed between fatigue and depression is independent of the traits overlapping symptoms and is likely attributable to the non-causal genetic relationship which exists between the traits. Whereby, a significant proportion of the association between fatigue and depression is explained by shared genetic factors.

Published
2017

17. Familiality and heritability of fatigue in an Australian twin sample

Author

Corfield, Elizabeth, Martin, Nicholas, Nyholt, Dale, Corfield, Elizabeth, Martin, Nicholas, and Nyholt, Dale

Abstract

Free to read Familial factors have previously been implicated in the etiology of fatigue, of which a significant proportion is likely attributable to genetic influences. However, family studies have primarily focused on chronic fatigue syndrome, while univariate twin studies have investigated broader fatigue phenotypes. The results for similar fatigue phenotypes vary between studies, particularly with regard to sex-specific contributions to the heritability of the traits. Therefore, the current study aims to investigate the familiality and sex-specific effects of fatigue experienced over the past few weeks in an older Australian population of 660 monozygotic (MZ) twin pairs, 190 MZ singleton twins, 593 dizygotic (DZ) twin pairs, and 365 DZ singleton twins. Higher risks for fatigue were observed in MZ compared to DZ co-twins of probands with fatigue. Univariate heritability analyses indicated fatigue has a significant genetic component, with a heritability (h2) estimate of 40%. Sex-specific effects did not significantly contribute to the heritability of fatigue, with similar estimates for males (h2 = 41%, 95% CI [18, 62]) and females (h2 = 40%, 95% CI [27, 52]). These results indicate that fatigue experienced over the past few weeks has a familial contribution, with additive genetic factors playing an important role in its etiology.

Published
2017

18. A continuum of genetic liability for minor and major depression

Author

Corfield, Elizabeth, Yang, Yuanhao, Martin, Nicholas, Nyholt, Dale, Corfield, Elizabeth, Yang, Yuanhao, Martin, Nicholas, and Nyholt, Dale

Abstract

The recent success of a large genome-wide association (GWA) study—analysing 130 620 major depression cases and 347 620 controls—in identifying the first single-nucleotide polymorphism (SNP) loci robustly associated with major depression in Europeans confirms that immense sample sizes are required to identify risk loci for depression. Given the phenotypic similarity between major depressive disorder (MDD) and the less severe minor depressive disorder (MiDD), we hypothesised that broadening the case definition to include MiDD may be an efficient approach to increase sample sizes in GWA studies of depression. By analysing two large twin pair cohorts, we show that minor depression and major depression lie on a single genetic continuum, with major depression being more severe but not aetiologically distinct from minor depression. Furthermore, we estimate heritabilities of 37% for minor depression, 46% for major depression and 48% for minor or major depression in a cohort of older adults (aged 50–92). However, the heritability of minor or major depression was estimated at 40% in a cohort of younger adults (aged 23–38). Moreover, two robust major depression-risk SNPs nominally associated with major depression in our Australian GWA data set produced more significant evidence for association with minor or major depression. Hence, broadening the case phenotype in GWA studies to include subthreshold definitions, such as MiDD, should facilitate the identification of additional genetic risk loci for depression.

Published
2017

19. GMP Synthase Is Required for Virulence Factor Production and Infection by Cryptococcus neoformans

Author

Chitty, Jessica L., Tatzenko, Tayla L., Williams, Simon, Koh, Y. Q. Andre E., Corfield, Elizabeth C., Butler, Mark S., Robertson, Avril A. B., Cooper, Matthew A., Kappler, Ulrike, Kobe, Bostjan, Fraser, James A., Chitty, Jessica L., Tatzenko, Tayla L., Williams, Simon, Koh, Y. Q. Andre E., Corfield, Elizabeth C., Butler, Mark S., Robertson, Avril A. B., Cooper, Matthew A., Kappler, Ulrike, Kobe, Bostjan, and Fraser, James A.

Abstract

Over the last four decades the HIV pandemic and advances in medical treatments that also cause immunosuppression have produced an ever-growing cohort of individuals susceptible to opportunistic pathogens. Of these, AIDS patients are particularly vulnerable to infection by the encapsulated yeast Cryptococcus neoformans Most commonly found in the environment in purine-rich bird guano, C. neoformans experiences a drastic change in nutrient availability during host infection, ultimately disseminating to colonize the purine-poor central nervous system. Investigating the consequences of this challenge, we have characterized C. neoformans GMP synthase, the second enzyme in the guanylate branch of de novo purine biosynthesis. We show that in the absence of GMP synthase, C. neoformans becomes a guanine auxotroph, the production of key virulence factors is compromised, and the ability to infect nematodes and mice is abolished. Activity assays performed using recombinant protein unveiled differences in substrate binding between the C. neoformans and human enzymes, with structural insights into these kinetic differences acquired via homology modeling. Collectively, these data highlight the potential of GMP synthase to be exploited in the development of new therapeutic agents for the treatment of disseminated, life-threatening fungal infections.

Published
2017

20. Co-occurrence and symptomatology of fatigue and depression

Author

Corfield, Elizabeth, Martin, Nicholas, Nyholt, Dale, Corfield, Elizabeth, Martin, Nicholas, and Nyholt, Dale

Abstract

Objective Fatigue and depression are highly comorbid phenotypes with partially overlapping symptoms. The main aims of the present study are to: - (i) identify the risk of current fatigue and depression; - (ii) determine if the depression symptoms experienced by individuals who are fatigued (N = 766) and non-fatigued (N = 1849) are different, and; - (iii) identify if the fatigue symptoms experienced by depressed (N = 275) and non-depressed (N = 2340) individuals are different, in a community-based sample of Australian twins aged over 50 years. Methods Fatigue and depression symptom profiles and classifications were generated using the Schedule of Fatigue and Anergia (SOFA); the General Health Questionnaire; and the Delusions-Symptoms-States Inventory, States of Anxiety and Depression questionnaires. The association between co-occurring fatigue and depression was assessed using prevalence ratios. Differences in the preponderance of fatigue and depression symptoms were assessed using logistic regression modeling. Results Individuals with either fatigue or depression have an approximately two-fold increased risk for comorbid presentation of both traits, compared to the general population. Logistic regression analysis indicated that fatigued individuals were significantly more likely to report all of the Diagnostic and Statistical Manual of Mental Disorders (DSM) depression symptoms assessed in the study. Similarly, depressed individuals were significantly more likely to report all {SOFA} fatigue symptoms. Conclusions Fatigue and depression are highly correlated traits within the community. Depression symptomatology and prevalence are significantly increased in fatigued individuals. Fatigue and especially the symptoms of insomnia and poor concentration are strong predictors of depression. Notably, the association between fatigue and depression is independent of their overlapping symptomatology. Therefore, presentation with fatigue, and

Published
2016

21. Shared genetic factors in the co-occurrence of depression and fatigue

Author

Corfield, Elizabeth, Martin, Nicholas, Nyholt, Dale, Corfield, Elizabeth, Martin, Nicholas, and Nyholt, Dale

Abstract

Free to read Depression and fatigue have previously been suggested to share an underlying genetic contribution. The present study aims to investigate and characterize the familiality and genetic relationship between depression and fatigue. The familiality of depression and fatigue was assessed by calculating relative risks, measured by the prevalence ratio, within 643 monozygotic (MZ) and 577 dizygotic (DZ) twin pairs. Bivariate twin modeling was utilized to assess the magnitude of shared heritability between depression and fatigue. Finally, the relationship between depression and fatigue was investigated using the co-twin control method, to determine whether the association is explained by causal or non-causal models. We observed an increased risk of fatigue in co-twins of probands with depression and increased risk of depression in co-twins of probands with fatigue. Higher risks were observed in MZ compared to DZ twin pairs, and bivariate heritability analyses indicated significant genetic components for depression and fatigue, with heritability estimates of 48% and 41%, respectively. Importantly, a significant additive genetic correlation of 0.71 [95% CI = 0.51–0.92) and bivariate heritability of 21% [95% CI = 10–35%] was observed between depression and fatigue. Furthermore, results from the co-twin control method indicate a non-causal genetic relationship that likely explains the association between depression and fatigue. Notably, the contribution of shared genetic factors remained significant, independent of the overlapping symptoms, indicating that the relationship between co-occurring depression and fatigue is primarily due to shared genetic factors rather than overlapping symptomatology.

Published
2016

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