@article {9098,
	title = {An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer{\textquoteright}s disease-related patterns},
	journal = {Genome Res},
	volume = {32},
	year = {2022},
	month = {04},
	pages = {778{\textendash}790},
	abstract = {is a novel AD risk gene that has a cluster of variants primarily shared by case subjects around the Sec6 domain. This cluster is also validated in an independent replication data set and a validation data set with a larger sample size.},
	author = {Jin, B. and Capra, J. A. and Benchek, P. and Wheeler, N. and Naj, A. C. and Hamilton-Nelson, K. L. and Farrell, J. J. and Leung, Y. Y. and Kunkle, B. and Vadarajan, B. and Schellenberg, G. D. and Mayeux, R. and Wang, L. S. and Farrer, L. A. and Pericak-Vance, M. A. and Martin, E. R. and Haines, J. L. and Crawford, D. C. and Bush, W. S.}
}
@article {9859,
	title = {Alzheimer{\textquoteright}s Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset},
	journal = {medRxiv},
	year = {2024},
	month = {Dec},
	abstract = {The Alzheimer{\textquoteright}s Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer{\textquoteright}s Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer{\textquoteright}s Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45\% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.},
	author = {Leung, Y. Y. and Lee, W. P. and Kuzma, A. B. and Nicaretta, H. and Valladares, O. and Gangadharan, P. and Qu, L. and Zhao, Y. and Ren, Y. and Cheng, P. L. and Kuksa, P. P. and Wang, H. and White, H. and Katanic, Z. and Bass, L. and Saravanan, N. and Greenfest-Allen, E. and Kirsch, M. and Cantwell, L. and Iqbal, T. and Wheeler, N. R. and Farrell, J. J. and Zhu, C. and Turner, S. L. and Gunasekaran, T. I. and Mena, P. R. and Jin, J. and Carter, L. and Zhang, X. and Vardarajan, B. N. and Toga, A. and Cuccaro, M. and Hohman, T. J. and Bush, W. S. and Naj, A. C. and Martin, E. and Dalgard, C. and Kunkle, B. W. and Farrer, L. A. and Mayeux, R. P. and Haines, J. L. and Pericak-Vance, M. A. and Schellenberg, G. D. and Wang, L. S.}
}
