@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 {9508,
	title = {Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer{\textquoteright}s Diseases Sequencing Project Subjects},
	journal = {medRxiv},
	year = {2023},
	month = {Sep},
	abstract = {. We also identified 16 SVs associated with AD and 13 SVs associated with AD-related pathological/cognitive endophenotypes. Our findings demonstrate the broad impact of SVs on AD genetics.\ Alzheimer{\textquoteright}s disease, Structural variation, Copy number variation.},
	author = {Wang, H. and Dombroski, B. A. and Cheng, P. L. and Tucci, A. and Si, Y. Q. and Farrell, J. J. and Tzeng, J. Y. and Leung, Y. Y. and Malamon, J. S. and Wang, L. S. and Vardarajan, B. N. and Farrer, L. A. and Schellenberg, G. D. and Lee, W. P.}
}
@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.}
}
@article {9789,
	title = {{Blood-derived mitochondrial DNA copy number is associated with Alzheimer disease, Alzheimer-related biomarkers and serum metabolites},
	journal = {Alzheimers Res Ther},
	volume = {16},
	year = {2024},
	month = {Oct},
	pages = {234},
	abstract = {Blood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear.\ We performed two-sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA-CN and AD to investigate the causal relationship between mtDNA-CN and AD. We estimated mtDNA-CN using whole-genome sequence data from blood and brain samples of 13,799 individuals from the Alzheimer{\textquoteright}s Disease Sequencing Project. Linear and Cox proportional hazards models adjusting for age, sex, and study phase were used to assess the association of mtDNA-CN with AD. The association of AD biomarkers and serum metabolites with mtDNA-CN in blood was evaluated in Alzheimer{\textquoteright}s Disease Neuroimaging Initiative using linear regression. We conducted a causal mediation analysis to test the natural indirect effects of mtDNA-CN change on AD risk through the significantly associated biomarkers and metabolites.\ 0.005).\ Our study indicates that mtDNA-CN measured in blood is predictive of AD and is associated with AD biomarkers including plasma NFL particularly in females. Further, we illustrate that decreased mtDNA-CN possibly increases AD risk through dysregulation of mitochondrial lipid metabolism and inflammation.},
	author = {Tong, T. and Zhu, C. and Farrell, J. J. and Khurshid, Z. and Martin, E. R. and Pericak-Vance, M. A. and Wang, L. S. and Bush, W. S. and Schellenberg, G. D. and Haines, J. L. and Qiu, W. Q. and Lunetta, K. L. and Farrer, L. A. and Zhang, X.}
}
