Association of Long Runs of Homozygosity With Alzheimer Disease Among African American Individuals

Ghani, Mahdi; Reitz, Christiane; Cheng, Rong; Vardarajan, Badri N.; Jun, Gyungah; Sato, Christine; Naj, Adam C.; Rajbhandary, Ruchita; Wang, Li San; Valladares, Otto; Lin, Chiao Feng; Larson, Eric B.; Graff‐Radford, Neill R.; Evans, Denis A.; Jager, Philip L. De; Crane, Paul K.; Buxbaum, Joseph D.; Murrell, Jill R.; Raj, Towfique; Ertekin-Taner, Nilüfer; Logue, Mark; Baldwin, Clinton T.; Green, Robert C.; Barnes, Lisa L.; Cantwell, Laura B.; Fallin, M. Daniele; Go, Rodney C.P.; Griffith, Patrick; Obisesan, Thomas O.; Manly, Jennifer J.; Lunetta, Kathryn L.; Kamboh, M. Ilyas; López, Oscar L.; Bennett, David A.; Hendrie, Hugh C.; Hall, Kathleen; Goate, Alison; Byrd, Goldie S.; Kukull, Walter A.; Foroud, Tatiana; Haines, Jonathan L.; Farrer, Lindsay A.; Pericak‐Vance, Margaret A.; Lee, Joseph H.; Schellenberg, Gerard D.; George‐Hyslop, Peter St; Mayeux, Richard; Rogaeva, Ekaterina; Albert, Marilyn; Albin, Roger L.; Apostolova, Liana G.; Arnold, Steven E.; Barber, Robert C.; Barmada, M. Michael; Beach, Thomas G.; Beecham, Gary W.; Beekly, Duane; Bigio, Eileen H.; Bird, Thomas D.; Blacker, Deborah; Boeve, Bradley F.; Bowen, James D.; Boxer, Adam L.; Burke, James R.; Cai, Guiqing; Cairns, Nigel J.; Cao, Chuanhai; Carlson, Chris; Carney, Regina M.; Carroll, Steven L.; Chui, Helena C.; Clark, David G.; Cribbs, David H.; Crocco, Elizabeth; Cruchaga, Carlos; DeCarli, Charles; DeKosky, Steven T.; Demirci, Fuat; Dick, Malcolm; Faber, Kelley; Fallon, Kenneth B.; Ferris, Steven H.; Frosch, Matthew P.; Galasko, Douglas; Ganguli, Mary; Gearing, Marla; Geschwind, Daniel H.; Ghetti, Bernardino; Gilbert, John R.; Gilman, Sid; Glass, Jonathan D.; Growdon, John H.; Hákonarson, Hákon; Hamilton, Ronald L.; Hamilton‐Nelson, Kara L.; Haroutunian, Vahram; Harrell, Lindy E.; Honig, Lawrence S.; Hulette, Christine M.; Hyman, Bradley T.; Jarvik, Gail P.; Jicha, Gregory A.; Jin, Lee Way; Karydas, Anna; Kauwe, John; Kaye, Jeffrey; Kim, Ronald; Koo, Edward H.; Kowall, Neil W.; Kramer, Joel H.; Kramer, Patricia L.; LaFerla, Frank M.; Lah, James J.; Lang-Walker, Rosalyn; Leverenz, James B.; Levey, Aĺlan I.; Li, Ge; Lieberman, Andrew P.; Lyketsos, Constantine G.; Mack, Wendy J.; Marson, Daniel C.; Martiniuk, Frank; Mash, Deborah C.; Masliah, Eliezer; McCormick, Wayne C.; McCurry, Susan M.; McDavid, Andrew; McKee, Ann C.; Mesulam, Marsel; Miller, Bruce L.; Miller, Carol A.; Miller, Joshua W.; Montine, Thomas J.; Morris, John C.; Olichney, John; Parisi, Joseph E.; Peskind, Elaine R.; Petersen, Ronald C.; Pierce, Aimee; Poon, Wayne W.; Potter, Huntington; Quinn, Joseph F.; Raj, Ashok; Raskind, Murray A.; Reiman, Eric M.; Reisberg, Barry; Ringman, John M.; Roberson, Erik D.; Sano, Mary; Saykin, Andrew J.; Schneider, Julie A.; Schneider, Lon S.; Seeley, William W.; Smith, Amanda; Sonnen, Joshua A.; Spina, Salvatore; Stern, Robert; Tanzi, Rudolph E.; Trojanowski, John Q.; Troncoso, Juan C.; Tsuang, Debby W.; Deerlin, Vivianna M. Van; Eldik, Linda J. Van; Vinters, Harry V.; Vonsattel, Jean Paul; Weıntraub, Sandra; Welsh‐Bohmer, Kathleen A.; Williamson, Jennifer; Woltjer, Randall L.; Wright, Clinton B.; Younkin, Steven G.; Yu, Chang; Yu, Lei

doi:10.1001/jamaneurol.2015.1700

Cited by 39 publications

(34 citation statements)

References 48 publications

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“…Loss of function of PSEN1 gene has been correlated to early onset Alzheimer's disease (Kelleher and Shen 2017). Both PSEN1 and its TF, PAX5, were reported to be associated with Alzheimer's in African Americans and Caribbean Hispanics (Ghani et al 2015).…”

Section: Tf-twas Hit Genes Associated With Diseasementioning

confidence: 99%

TF-TWAS: Transcription-factor polymorphism associated with tissue-specific gene expression

Tang

Gottlieb

2018

Preprint

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Transcriptional regulation is associated with a broad range of diseases. Methods associating genetic polymorphism with gene transcription levels offer key insights for understanding the transcriptional regulation plan. The majority of gene imputation methods focus on modeling polymorphism in the cis regions of the gene, partially owing to the large genetic search space.We hypothesize that polymorphism within transcription factors (TFs) may help explain transcription levels of their transcribed genes.Here, we test this hypothesis by developing TF-TWAS: imputation models that integrate transcription factor information with transcription-wide association study methodology. By comparing TF-TWAS models to base models that use only gene cis information, we are able to estimate possible mechanisms of the TF polymorphism effect -TF expression or binding affinity within four tissueswhole blood, liver, brain hippocampus and coronary artery.We identified 48 genes where the TF-TWAS models explain significantly better their expression than cis models alone in at least one of the four tissues. Sixteen of these genes are associated with various diseases, including cancer, neurological, psychiatric and rare genetic diseases. Our method is a new expansion to transcriptome-wide association studies and enables the identification of new associations between polymorphism in transcription factor and gene transcription levels.

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Section: Tf-twas Hit Genes Associated With Diseasementioning

confidence: 99%

TF-TWAS: Transcription-factor polymorphism associated with tissue-specific gene expression

Tang

Gottlieb

2018

Preprint

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“…The global burden of large genome-wide ROHs in outbred datasets from North America and Europe did not show a significant association with AD (Nalls, et al, 2009,Sims, et al, 2011). In the Wadi Ara population (an isolated Arab community from northern Israel) the controls studied were found to have more ROHs than the AD cases (Sherva, et al, 2011) and ROHs were found to be significantly associated with AD in a Caribbean Hispanic data set (Ghani, et al, 2013) and in an outbred African American population (Ghani, et al, 2015). …”

Section: Introductionmentioning

confidence: 98%

“…The absence of consanguineous families in the deeply characterized datasets of North America and Europe has made mapping of recessive loci challenging in Alzheimer’s disease (AD) (Ghani, et al, 2015). Nonetheless, a recent study suggested that nearly 90% of early-onset AD (EOAD) cases are likely the result of autosomal recessive inheritance (Wingo, et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Exome sequencing in a consanguineous family clinically diagnosed with early-onset Alzheimer's disease identifies a homozygous CTSF mutation

Brás

Djaldetti

Alves

et al. 2016

Neurobiology of Aging

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We have previously reported the whole genome genotyping analysis of two consanguineous siblings clinically diagnosed with early onset Alzheimer’s disease. In this analysis we identified several large regions of homozygosity shared between both affected siblings, which we suggested could be candidate loci for a recessive genetic lesion underlying the early onset Alzheimer’s disease in these cases. We have now performed exome sequencing in one of these siblings and identified the potential cause of disease: the CTSF c.G1243A:p.Gly415Arg mutation in homozygosity. Bi-allelic mutations in this gene have been shown to cause Type B Kufs disease, an adult-onset neuronal ceroid lipofuscinosis with some cases resembling the impairment seen in Alzheimer’s disease.

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“…Common regions of homozygosity (ROH), the result of autozygosity (i.e., occurrence of two alleles at the same locus originating from a common ancestor as a consequence of nonrandom mating), have been documented to be detectable at high frequency in outbred populations as a consequence of selective pressure (Ku, Naidoo, Teo, & Pawitan, ; Lencz et al., ). Searching for ROH on a genome‐wide basis therefore affords a strategy for discovery of recessively acting disease genes and has been exploited in studies of rheumatoid arthritis (Yang, Chang, Liang, Lin, & Wang, ), Alzheimer's (Ghani et al., ), and early‐onset Parkinson's disease (Simon‐Sanchez et al., ). Findings from these studies support the hypothesis that recessive, disease‐predisposing loci not readily detected using a conventional GWAS approach exist (Yang et al., ).…”

Section: Introductionmentioning

confidence: 99%

Regions of homozygosity as risk factors for multiple myeloma

Went

Sud

et al. 2019

Annals of Human Genetics

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Genomic regions of homozygosity (ROH), detectable in outbred populations, have been implicated as determinants of inherited risk. To examine whether ROH is associated with risk of multiple myeloma (MM), we performed whole‐genome homozygosity analysis using single‐nucleotide polymorphism genotype data from 2,282 MM cases and 5,197 controls, with replication in an additional 878 MM cases and 7,083 controls. Globally, the distribution of ROH between cases and controls was not significantly different. However, one ROH at chromosome 9q21, harboring the B‐cell transcription factor gene KLF9, showed evidence of a consistent association and may therefore warrant further investigation as a candidate risk factor for MM. Overall, our analysis provides little support for a homozygosity signature being a significant factor in MM risk.

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Association of Long Runs of Homozygosity With Alzheimer Disease Among African American Individuals

Cited by 39 publications

References 48 publications

TF-TWAS: Transcription-factor polymorphism associated with tissue-specific gene expression

TF-TWAS: Transcription-factor polymorphism associated with tissue-specific gene expression

Exome sequencing in a consanguineous family clinically diagnosed with early-onset Alzheimer's disease identifies a homozygous CTSF mutation

Regions of homozygosity as risk factors for multiple myeloma

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