@article {7786, title = {Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer{\textquoteright}s Disease Sequencing Project.}, journal = {Dement Geriatr Cogn Disord}, volume = {45}, year = {2018}, month = {2018}, pages = {1-17}, abstract = {

BACKGROUND/AIMS: The Alzheimer{\textquoteright}s Disease Sequencing Project (ADSP) aims to identify novel genes influencing Alzheimer{\textquoteright}s disease (AD). Variants within genes known to cause dementias other than AD have previously been associated with AD risk. We describe evidence of co-segregation and associations between variants in dementia genes and clinically diagnosed AD within the ADSP.

METHODS: We summarize the properties of known pathogenic variants within dementia genes, describe the co-segregation of variants annotated as "pathogenic" in ClinVar and new candidates observed in ADSP families, and test for associations between rare variants in dementia genes in the ADSP case-control study. The participants were clinically evaluated for AD, and they represent European, Caribbean Hispanic, and isolate Dutch populations.

RESULTS/CONCLUSIONS: Pathogenic variants in dementia genes were predominantly rare and conserved coding changes. Pathogenic variants within ARSA, CSF1R, and GRN were observed, and candidate variants in GRN and CHMP2B were nominated in ADSP families. An independent case-control study provided evidence of an association between variants in TREM2, APOE, ARSA, CSF1R, PSEN1, and MAPT and risk of AD. Variants in genes which cause dementing disorders may influence the clinical diagnosis of AD in a small proportion of cases within the ADSP.

}, issn = {1421-9824}, doi = {10.1159/000485503}, author = {Blue, Elizabeth E and Bis, Joshua C and Dorschner, Michael O and Tsuang, Debby W and Barral, Sandra M and Beecham, Gary and Below, Jennifer E and Bush, William S and Butkiewicz, Mariusz and Cruchaga, Carlos and DeStefano, Anita and Farrer, Lindsay A and Goate, Alison and Haines, Jonathan and Jaworski, Jim and Jun, Gyungah and Kunkle, Brian and Kuzma, Amanda and Lee, Jenny J and Lunetta, Kathryn L and Ma, Yiyi and Martin, Eden and Naj, Adam and Nato, Alejandro Q and Navas, Patrick and Nguyen, Hiep and Reitz, Christiane and Reyes, Dolly and Salerno, William and Schellenberg, Gerard D and Seshadri, Sudha and Sohi, Harkirat and Thornton, Timothy A and Valadares, Otto and van Duijn, Cornelia and Vardarajan, Badri N and Wang, Li-San and Boerwinkle, Eric and Dupuis, Jos{\'e}e and Pericak-Vance, Margaret A and Mayeux, Richard and Wijsman, Ellen M} } @article {7661, title = {Whole genome sequencing of Caribbean Hispanic families with late-onset Alzheimer{\textquoteright}s disease.}, journal = {Ann Clin Transl Neurol}, volume = {5}, year = {2018}, month = {2018 Apr}, pages = {406-417}, abstract = {

Objective: To identify rare causal variants underlying known loci that segregate with late-onset Alzheimer{\textquoteright}s disease (LOAD) in multiplex families.

Methods: We analyzed whole genome sequences (WGS) from 351 members of 67 Caribbean Hispanic (CH) families from Dominican Republic and New York multiply affected by LOAD. Members of 67 CH and additional 47 Caucasian families underwent WGS as a part of the Alzheimer{\textquoteright}s Disease Sequencing Project (ADSP). All members of 67 CH families, an additional 48 CH families and an independent CH case-control cohort were subsequently genotyped for validation. Patients met criteria for LOAD, and controls were determined to be dementia free. We investigated rare variants segregating within families and gene-based associations with disease within LOAD GWAS loci.

Results: A variant in p.R434W, segregated significantly with LOAD in two large families (OR = 5.77, 95\% CI: 1.07-30.9, = 0.041). In addition, missense mutations in and under previously reported linkage peaks at 7q14.3 and 11q12.3 segregated completely in one family and in follow-up genotyping both were nominally significant ( < 0.05). We also identified rare variants in a number of genes associated with LOAD in prior genome wide association studies, including ( = 0.049), ( = 0.0098) and ( = 0.040).

Conclusions and Relevance: Rare variants in multiple genes influence the risk of LOAD disease in multiplex families. These results suggest that rare variants may underlie loci identified in genome wide association studies.

}, issn = {2328-9503}, doi = {10.1002/acn3.537}, author = {Vardarajan, Badri N and Barral, Sandra and Jaworski, James and Beecham, Gary W and Blue, Elizabeth and Tosto, Giuseppe and Reyes-Dumeyer, Dolly and Medrano, Martin and Lantigua, Rafael and Naj, Adam and Thornton, Timothy and DeStefano, Anita and Martin, Eden and Wang, Li-San and Brown, Lisa and Bush, William and van Duijn, Cornelia and Goate, Allison and Farrer, Lindsay and Haines, Jonathan L and Boerwinkle, Eric and Schellenberg, Gerard and Wijsman, Ellen and Pericak-Vance, Margaret A and Mayeux, Richard and Wang, Li-San} } @article {9577, title = {Human whole-exome genotype data for Alzheimer{\textquoteright}s disease.}, journal = {Nat Commun}, volume = {15}, year = {2024}, month = {2024 Jan 23}, pages = {684}, abstract = {

The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer{\textquoteright}s Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82\% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41\% of the variants are intronic and 1.8\% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

}, keywords = {Alzheimer Disease, Computational Biology, Data Accuracy, Exome, Genotype, Humans}, issn = {2041-1723}, doi = {10.1038/s41467-024-44781-7}, author = {Leung, Yuk Yee and Naj, Adam C and Chou, Yi-Fan and Valladares, Otto and Schmidt, Michael and Hamilton-Nelson, Kara and Wheeler, Nicholas and Lin, Honghuang and Gangadharan, Prabhakaran and Qu, Liming and Clark, Kaylyn and Kuzma, Amanda B and Lee, Wan-Ping and Cantwell, Laura and Nicaretta, Heather and Haines, Jonathan and Farrer, Lindsay and Seshadri, Sudha and Brkanac, Zoran and Cruchaga, Carlos and Pericak-Vance, Margaret and Mayeux, Richard P and Bush, William S and DeStefano, Anita and Martin, Eden and Schellenberg, Gerard D and Wang, Li-San} }