Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. / Dahl, Andrew; Thompson, Michael; An, Ulzee; Krebs, Morten; Appadurai, Vivek; Border, Richard; Bacanu, Silviu-Alin; Werge, Thomas; Flint, Jonathan; Schork, Andrew J.; Sankararaman, Sriram; Kendler, Kenneth S.; Cai, Na.

In: Nature Genetics, Vol. 55, No. 12, 2023, p. 2082-2093.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Dahl, A, Thompson, M, An, U, Krebs, M, Appadurai, V, Border, R, Bacanu, S-A, Werge, T, Flint, J, Schork, AJ, Sankararaman, S, Kendler, KS & Cai, N 2023, 'Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder', Nature Genetics, vol. 55, no. 12, pp. 2082-2093. https://doi.org/10.1038/s41588-023-01559-9

APA

Dahl, A., Thompson, M., An, U., Krebs, M., Appadurai, V., Border, R., Bacanu, S-A., Werge, T., Flint, J., Schork, A. J., Sankararaman, S., Kendler, K. S., & Cai, N. (2023). Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nature Genetics, 55(12), 2082-2093. https://doi.org/10.1038/s41588-023-01559-9

Vancouver

Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R et al. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nature Genetics. 2023;55(12):2082-2093. https://doi.org/10.1038/s41588-023-01559-9

Author

Dahl, Andrew ; Thompson, Michael ; An, Ulzee ; Krebs, Morten ; Appadurai, Vivek ; Border, Richard ; Bacanu, Silviu-Alin ; Werge, Thomas ; Flint, Jonathan ; Schork, Andrew J. ; Sankararaman, Sriram ; Kendler, Kenneth S. ; Cai, Na. / Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. In: Nature Genetics. 2023 ; Vol. 55, No. 12. pp. 2082-2093.

Bibtex

@article{9e2eade5683d45cf82878e5bca11d01d,

title = "Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder",

abstract = "Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.",

author = "Andrew Dahl and Michael Thompson and Ulzee An and Morten Krebs and Vivek Appadurai and Richard Border and Silviu-Alin Bacanu and Thomas Werge and Jonathan Flint and Schork, {Andrew J.} and Sriram Sankararaman and Kendler, {Kenneth S.} and Na Cai",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

doi = "10.1038/s41588-023-01559-9",

language = "English",

volume = "55",

pages = "2082--2093",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "nature publishing group",

number = "12",

}

RIS

TY - JOUR

T1 - Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

AU - Dahl, Andrew

AU - Thompson, Michael

AU - An, Ulzee

AU - Krebs, Morten

AU - Appadurai, Vivek

AU - Border, Richard

AU - Bacanu, Silviu-Alin

AU - Werge, Thomas

AU - Flint, Jonathan

AU - Schork, Andrew J.

AU - Sankararaman, Sriram

AU - Kendler, Kenneth S.

AU - Cai, Na

PY - 2023

Y1 - 2023

N2 - Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

AB - Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

U2 - 10.1038/s41588-023-01559-9

DO - 10.1038/s41588-023-01559-9

M3 - Journal article

C2 - 37985818

AN - SCOPUS:85177187428

VL - 55

SP - 2082

EP - 2093

JO - Nature Genetics

JF - Nature Genetics

SN - 1061-4036

IS - 12

ER -

ID: 374455787

Globe Institute