The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Random-Effects Model Aimed at Discovering Associations in Meta-Analysis of Genome-wide Association Studies
Open accessAbstract
Meta-analysis is an increasingly popular tool for combining multiple different genome-wide association studies (GWASs) in a single aggregate analysis in order to identify associations with very small effect sizes. Because the data of a meta-analysis can be heterogeneous, referring to the differences in effect sizes between the collected studies, what is often done in the literature is to apply both the fixed-effects model (FE) under an assumption of the same effect size between studies and the random-effects model (RE) under an assumption of varying effect size between studies. However, surprisingly, RE gives less significant p values than FE at variants that actually show varying effect sizes between studies. This is ironic because RE is designed specifically for the case in which there is heterogeneity. As a result, usually, RE does not discover any associations that FE did not discover. In this paper, we show that the underlying reason for this phenomenon is that RE implicitly assumes a markedly conservative null-hypothesis model, and we present a new random-effects model that relaxes the conservative assumption. Unlike the traditional RE, the new method is shown to achieve higher statistical power than FE when there is heterogeneity, indicating that the new method has practical utility for discovering associations in the meta-analysis of GWASs.
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“Compared to the conventional random-effects model, the RE2 model offers greater power under heterogeneity.”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [17]
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Cites
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Statistical Aspects of the Analysis of Data From Retrospective Studies of Disease
(1959) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/22.4.719 · Cited by 14,689
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
The combination of estimates from different experiments
Cochran, W. G. (1954) · Biometrics · doi:10.2307/3001666 · Cited by 5,380
A second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162
Genome-wide association studies for complex traits: consensus, uncertainty and challenges
McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., & Hirschhorn, J. N. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2344 · Cited by 2,891
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Items 601–692 of 692
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018029
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018023
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018032
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018035
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018026
Heterogeneity Measure in Meta-analysis without Study-specific Variance Information
Sangnawakij, P., & Sittimongkol, R. (2024) · Lobachevskii Journal of Mathematics · doi:10.1134/s1995080224600262
Trans-ancestry genome-wide association meta-analyses of hippocampal and subfield volumesPreprint
Liu, N., Zhang, L. J., Tian, T., Cheng, J., Zhang, B., Qiu, S., Geng, Z., Cui, G., Zhang, Q., Liao, W., et al. (2024) · Research Square · doi:10.21203/rs.3.pex-2067/v1
Jiang, D., Ma, Y., Su, J., Li, J., Zheng, G., Deng, Y. J., Gou, X., Gao, S., Cheng, C., Deng, C., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4514542/v1
Identifying pleiotropic genes via the composite test amidst the complexity of polygenic traits
Lai, E., & Huang, Y. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae327 · Cited by 1
Addressing overlapping sample challenges in genome-wide association studies: Meta-reductive approach
Rajabli, F., & Emekci, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296207
Moazed, K. T. (2024) · Springer eBooks · doi:10.1007/978-3-031-64322-4_4
Lee, D., Baek, J. H., Kim, Y., Lee, B. D., Cho, E.-Y., Joo, E.-J., Ahn, Y.-M., Kim, S. H., Chung, Y., Rami, F. Z., et al. (2024) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2024.104203
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Mugo, J. W., Day, C., Choudhury, A., Deetlefs, M., Freercks, R., Geraty, S., Panieri, A., Cotchbos, C., Ribeiro, M., Engelbrecht, A., et al. (2024) · medRxiv · doi:10.1101/2024.09.13.24313664
Empirically adjusted fixed-effects meta-analysis methods in genomic studies
Jayanetti, W. T., & Sikdar, S. (2024) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/sagmb-2023-0041
Li, R., Li, M., & Zhao, N. (2024) · Genetic Epidemiology · doi:10.1002/gepi.22596
Large-scale collaborative studies in medical imaging through meta-analyses
Altmann, A., Dockès, J., Thompson, P. M., & Jahanshad, N. (2025) · Elsevier eBooks · doi:10.1016/b978-0-44-323761-4.00035-3
Muriuki, J., Mentzer, A. J., Band, G., Chong, A., Macharia, A., Mogire, R., Abuga, K. M., Mitchell, R., Gilchrist, J., Webb, E. L., et al. (2025) · Nature Communications · doi:10.1038/s41467-026-71567-w · Cited by 1
Defo, J., & Ramesar, R. (2025) · Acta Neuropsychiatrica · doi:10.1017/neu.2025.12
Feng, Y., Ji, X., Huang, P., & Yang, S. (2025) · Research Square · doi:10.21203/rs.3.rs-6316036/v1
Mogire, R. M., Muriuki, J. M., Bayimenye, R. F., Mentzer, A. J., Chong, A., Gouveia, M. H., Bentley, A. R., Band, G., King’ori, P., Mitchell, R. E., et al. (2025) · medRxiv · doi:10.1101/2025.05.27.25328359
Liu, S. K., Cao, H., Yang, X., Zhou, X., Chen, Y., Fu, W., Chan, S. Y., Ip, F. C. F., Mok, K. Y., Mok, V., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251350722
Sun, F., Hui, S., Gong, B., Gu, J., & Huang, P. (2025) · PLoS ONE · doi:10.1371/journal.pone.0336109
Adewuyi, E. O., Auta, A., Ossai, C. I., Anyaegbu, C. C., Nguyen, T. T., Rahman, M. R., Stephan, B. C. M., Tessema, G. A., Nyholt, D. R., & Pereira, G. F. (2025) · Research Square · doi:10.21203/rs.3.rs-8080408/v1
Durante, G. L., Tyler, A. L., Scott, R. C., Hernan, A. E., & Mahoney, J. M. (2025) · Epilepsia · doi:10.1111/epi.70035
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Kaka, M. O., Topaloudi, A., Chen, G., Gupta, P., Levey, D. F., Gao, B., & Paschou, P. (2025) · medRxiv · doi:10.64898/2025.12.12.25342160
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588466
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588424
Cavazos, T. B., Kachuri, L., Graff, R. E., Nierenberg, J. L., Thai, K. K., Alexeeff, S., Eeden, S. K. V. D., Corley, D. A., Kushi, L. H., Hoffmann, T. J., et al. (2022) · Figshare · doi:10.6084/m9.figshare.21282414
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588409
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588448
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588454
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588430
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588460
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588433
Akinyemi, R. O., Tiwari, H. K., Srinivasasainagendra, V., Akpa, O., Sarfo, F. S., Akpalu, A., Wahab, K., Obiako, R., Komolafe, M., Owolabi, L. F., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26677133
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588406
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588475
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588469
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588481
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Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588442
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588463
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018020
Pérez-García, J., Pino-Yanes, M., Plender, E. G., Everman, J. L., Eng, C. S., Jackson, N. D., Moore, C. M., Beckman, K. B., Medina, V., Sharma, S., et al. (2023) · Figshare · doi:10.6084/m9.figshare.24234233
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588436
Fatumo, S., Sathan, D., Samtal, C., Isewon, I., Tamuhla, T., Soremekun, C., Jafali, J., Panji, S., Tiffin, N., & Fakim, Y. J. (2024) · Figshare · doi:10.6084/m9.figshare.26633919
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588403
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588457
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588445
Akinyemi, R. O., Tiwari, H. K., Srinivasasainagendra, V., Akpa, O., Sarfo, F. S., Akpalu, A., Wahab, K., Obiako, R., Komolafe, M., Owolabi, L. F., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26677142
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588415
Castellani, C. A., Longchamps, R. J., Sumpter, J. A., Newcomb, C. E., Lane, J., Grove, M. L., Bressler, J., Brody, J. A., Floyd, J. S., Bartz, T. M., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13018017
Akinyemi, R. O., Tiwari, H. K., Srinivasasainagendra, V., Akpa, O., Sarfo, F. S., Akpalu, A., Wahab, K., Obiako, R., Komolafe, M., Owolabi, L. F., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26677139
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588451
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588412
Akinyemi, R. O., Tiwari, H. K., Srinivasasainagendra, V., Akpa, O., Sarfo, F. S., Akpalu, A., Wahab, K., Obiako, R., Komolafe, M., Owolabi, L. F., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26677136
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588421
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588418
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588478
Cai, W., Zhang, Y., Chang, T., Wang, Z., Zhu, B., Chen, Y., Gao, X., Xu, L., Zhang, L., Gao, H., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26588427
Feng, Y., Li, Y., Zhang, H., Xia, H., Lü, Y., Zhou, H., & Huang, P. (2026) · BMC Psychiatry · doi:10.1186/s12888-026-07816-5
Asanomi, Y., Mitsumori, R., Yamakawa, A., Morizono, T., Shigemizu, D., Niida, S., Sakurai, T., & Ozaki, K. (2026) · Journal of Human Genetics · doi:10.1038/s10038-026-01454-1
Cao, H., Zheng, Z., Zhou, X., Kikuchi, M., Wong, H. Y., Cheng, E. Y. L., Wong, B. W. Y., Lo, R. M. N., Shoai, M., Chong, J. R., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71219
Montalvo‐Ortiz, J. L., Martínez‐Magaña, J. J., Brito, D. E. A., Trichia, E., Rivera-Hernández, M., Porras, L. M., Sullivan, K. A., Jacobson, D., Kember, R. L., Núñez, D., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-8789707/v1
Lorenz, K., Yoon, S., Coz, C. L., Zur, K. B., Wells, A. D., Romberg, N. D., & Voight, B. F. (2026) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2026.08.004
Khurshid, Z., Tong, T., Olayinka, O. A., Farrell, J. J., Zhu, C., Alzheimer's Disease Sequencing Project, Martin, E. R., Bush, W. S., Pericak‐Vance, M. A., Wang, L.-S., et al. (2026) · Alzheimer s Research & Therapy · doi:10.1186/s13195-026-02005-8 · Cited by 1
Combining Association and Haplotype Studies Towards the Improvement of Fruit Quality in Tomato
Zhao, J. (2019) · theses.fr (ABES) · doi:10.70675/998b4925z8633z4ddcz9bc0z4fb6ad557530
Early-life factors and epigenetic precursors of childhood leukemia
Novoloaca, A. (2020) · theses.fr (ABES) · doi:10.70675/4286201fz357fz4b0ez8dbfzdc0b44a46cae
Guibon, J. (2021) · theses.fr (ABES) · doi:10.70675/7d747e55z1443z4206za935zaa05542869e3
Ramı́rez, A., Bustos, C., Arboleda, G., Pardo, R., Ortega-Rojas, J., Mahecha, M. F., Mera, A. G. C., Caicedo, J., Bonilla-Vargas, K., Andrade, V., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-8996305/v1
Walsche, A. D. (2025) · theses.fr (ABES) · doi:10.70675/0df76955z9a01z470dzbd40z8105df32d440
Zvereva, A., Kemp, H., Gillespie, A., Tomczyk, K., Cardoso, S. R., Sevgi, S., Mackie, K., Fedele, V., Alexander, J., Goulding, I., et al. (2026) · medRxiv · doi:10.64898/2026.04.09.26350488
Multi-Ancestry Survival GWAS of Substance Use Initiation in the ABCD StudyPreprint
Wei, M., & Peng, Q. (2026) · medRxiv · doi:10.64898/2026.04.08.26350431
Dai, H., Chu, X., Du, H., Yang, S., Yao, Y., Yu, X., Zhao, Y., Dong, P., Lyu, Z., Wang, W., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71785-2
Piga, N.-N., Portelli, M. A., Shrine, N., Chen, J., Packer, R., Coley, K., Williams, A. T., Batini, C., John, C., Lutz, S. M., et al. (2026) · ERJ Open Research · doi:10.1183/23120541.00327-2026
Adewuyi, E. O., Auta, A., Ossai, C. I., Anyaegbu, C. C., Nguyen, T. T. H., Rahman, M. R., Stephan, B. C. M., Tessema, G. A., Nyholt, D. R., & Pereira, G. F. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27114792
Maimaiti, A., Jia, N., Feng, Y., Ji, X., He, C., Turhon, M., Maimaitili, A., Shen, J., Yang, S., Wang, Y., et al. (2026) · Stroke · doi:10.1161/strokeaha.126.055253
Ishibashi, N., Furutani, M., Nakashima, M., Ishida, S., Maeda, J., Sakai, T., Oguri, N., Miyamoto, S., Miyauchi, S., Okamura, S., et al. (2026) · Journal of the American Heart Association · doi:10.1161/jaha.125.047046
traceCB: Trans-ancestry cell-type-specific eQTLs mapping by integrating scRNA-seq and bulk dataPreprint
Jiang, W., Xiao, J., & Cai, M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.20.733502
Yan, P., Wang, H., Shu, Y., Xie, R., Reyidan, A., & Fu, S. (2026) · Brain and Behavior · doi:10.1002/brb3.71594
Common genetic determinants of dynamic human in vivo immune response to Mycobacterium tuberculosisPreprint
Zhang, P., Turner, C. T., Chandran, A., Parks, T., Rosenheim, J., Jiang, J., Bell, L. C. K., Rose-Key, R., Berkeley, M. I. K., Capocci, S., et al. (2026) · medRxiv · doi:10.64898/2026.07.06.26357408
Ayoufu, A., Abulimiti, A., Aierken, W., Wei, Z., Wang, X., Wang, H., & Zhao, L. (2026) · Genes Brain & Behavior · doi:10.1111/gbb.70062
Kazemi, H., Drake, J. E., Bacanu, S., McMahon, B. H., Agarwal, K., Zuniga, A., Choudhury, S., Abbaszadegan, H., Dhaubhadel, S., Johnson, K. A., et al. (2026) · medRxiv · doi:10.64898/2026.07.20.26358275
Zhan, Q., Xie, H., Han, H., Zhang, Z., Wei, R., 李海侠, Zhao, W., Feng, B., Hou, X., Wang, J., et al. (2026) · Animal Genetics · doi:10.1002/age.70179
Shared genetic architecture and therapeutic targets across paediatric immune-mediated diseases
Li, J., Qu, H., March, M., Glessner, J., Fu, Y., Chen, J., Xu, Y., Chen, H., Li, Y. R., Xia, Q., et al. (2026) · Annals of the Rheumatic Diseases · doi:10.1016/j.ard.2026.07.007
Anthropometric and cardio-metabolic trait variation and genetic associations in sub-Saharan Africa
Hansen, M. E. B., Hazra, U., Kim, M., Raj, S. M., Fan, S., Beggs, W. R., Mpoloka, S. W., Mokone, G. G., Nyambo, T., Meskel, D. W., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.07.006 · Cited by 1
Alzheimer’s disease genetics converges on microglial and neuronal dysregulation
Uffelmann, E., Wightman, D. P., Bahrami, S., Shadrin, A. A., Fominykh, V., Ojima, T., Jiang, C., Benner, C., Moreno, E., Campos, A. I., et al. (2026) · Nature · doi:10.1038/s41586-026-11206-y
Metadata
- Authors
- Han, B., & Eskin, E.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Eskin, Eleazar
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 88
- Issue
- 5
- Pages
- 586-598
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC3146723
- OpenAlex
- W2042421957
- Cited by
- 680
- References
- 55
- Citations by year
- 2026: 39 · 2025: 53 · 2024: 86 · 2023: 57 · 2022: 68 · 2021: 54 · 2020: 44 · 2019: 52 · 2018: 48 · 2017: 32 · 2016: 40 · 2015: 27 · 2014: 37 · 2013: 21 · 2012: 17
- FWCI
- 2.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Institutes of Health (5u01da024417-02)
- National Heart, Lung, and Blood Institute (K25HL080079)
- National Institute on Drug Abuse (U01-DA024417)
- National Institute of Environmental Health Sciences (N01 ES045530)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- random effects models, genome-wide association study, meta-analysis, heterogeneity, fixed effects model, statistical power, null hypothesis, association discovery
- MeSH terms
- Crohn Disease, Diabetes Mellitus, Type 2, Humans, Models, Genetic, Models, Statistical, Likelihood Functions, Quantitative Trait Loci, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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