Multi-ancestry GWAS of major depression aids locus discovery, fine-mapping, gene prioritisation, and causal inference

Meng, X.; Navoly, G.; Giannakopoulou, O.; DL, D.; Koller, D.; Pathak, G.; Koen, N.; Lin, K.; Renteria, M.; Feng, Y.; Gaziano, J. M.; Stein, D.; Zar, H.; Campbell, M.; van Heel, D.; Trivedi, B.; Finer, S.; McQuillin, A.; Bass, N.; Chundru, V. K.; Martin, H.; Huang, Q. Q.; Valkovskaya, M.; Kuo, P.-H.; Chen, H.-C.; Tsai, S.-J.; Liu, Y.-L.; Kendler, K.; Peterson, R.; Cai, N.; Fang, Y.; Sen, S.; Scott, L.; Burmeister, M.; Loos, R.; Preuss, M.; Actkins, K.; Davis, L.; Uddin, M.; Wani, A.; Wildman, D.; Ursano, R.; Kessler, R.; Kanai, M.; Okada, Y.; Sakaue, S.; Rabinowitz, J.; Maher, B.; Uhl, G.; Eato

doi:10.1101/2022.07.20.500802

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bioRxiv · 10.1101/2022.07.20.500802

Multi-ancestry GWAS of major depression aids locus discovery, fine-mapping, gene prioritisation, and causal inference

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Abstract

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 studies with 88,316 MD cases and 902,757 controls to previously reported data from individuals of European ancestry. This includes samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latinx participants (32%). The multi-ancestry GWAS identified 190 significantly associated loci, 53 of them novel. For previously reported loci from GWAS in European ancestry the power-adjusted transferability ratio was 0.6 in the Hispanic/Latinx group and 0.3 in each of the other groups. Fine-mapping benefited from additional sample diversity: the number of credible sets with [≤]5 variants increased from 3 to 12. A transcriptome-wide association study identified 354 significantly associated genes, 205 of them novel. Mendelian Randomisation showed a bidirectional relationship with BMI exclusively in samples of European ancestry. This first multi-ancestry GWAS of MD demonstrates the importance of large diverse samples for the identification of target genes and putative mechanisms.

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Meng, X., Navoly, G., Giannakopoulou, O., DL, D., Koller, D., Pathak, G., Koen, N., Lin, K., Renteria, M., Feng, Y., Gaziano, J. M., Stein, D., Zar, H., Campbell, M., van Heel, D., Trivedi, B., Finer, S., McQuillin, A., Bass, N., Chundru, V. K., Martin, H., Huang, Q. Q., Valkovskaya, M., Kuo, P.-H., Chen, H.-C., Tsai, S.-J., Liu, Y.-L., Kendler, K., Peterson, R., Cai, N., Fang, Y., Sen, S., Scott, L., Burmeister, M., Loos, R., Preuss, M., Actkins, K., Davis, L., Uddin, M., Wani, A., Wildman, D., Ursano, R., Kessler, R., Kanai, M., Okada, Y., Sakaue, S., Rabinowitz, J., Maher, B., Uhl, G., Eato. 2022-07-21. Multi-ancestry GWAS of major depression aids locus discovery, fine-mapping, gene prioritisation, and causal inference. https://doi.org/10.1101/2022.07.20.500802

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