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Original Investigation |

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

Mahdi Ghani, MD, PhD1; Christiane Reitz, MD, PhD2,3,4; Rong Cheng, PhD2; Badri Narayan Vardarajan, PhD3; Gyungah Jun, PhD5,6,7; Christine Sato, MSc1; Adam Naj, PhD8; Ruchita Rajbhandary, MPH8; Li-San Wang, PhD9; Otto Valladares, MS9; Chiao-Feng Lin, PhD9; Eric B. Larson, MD, MPH10,11; Neill R. Graff-Radford, MD12,13; Denis Evans, MD14; Philip L. De Jager, MD, PhD15,16,17; Paul K. Crane, MD, MPH10; Joseph D. Buxbaum, PhD18,19,20,21; Jill R. Murrell, PhD22; Towfique Raj, PhD16; Nilufer Ertekin-Taner, MD, PhD12,13; Mark Logue, PhD5; Clinton T. Baldwin, PhD5; Robert C. Green, MD, MPH16,23,24; Lisa L. Barnes, PhD25,26; Laura B. Cantwell, MPH9; M. Daniele Fallin, PhD27; Rodney C. P. Go, PhD28; Patrick A. Griffith, MD29; Thomas O. Obisesan, MD30; Jennifer J. Manly, PhD2,4; Kathryn L. Lunetta, PhD6; M. Ilyas Kamboh, PhD31,32; Oscar L. Lopez, MD32; David A. Bennett, MD25,33; Hugh Hendrie, MB, ChB, DSc34,35,36; Kathleen S. Hall, PhD35; Alison M. Goate, PhD37; Goldie S. Byrd, PhD38; Walter A. Kukull, PhD39; Tatiana M. Foroud, PhD26; Jonathan L. Haines, PhD40; Lindsay A. Farrer, PhD5,6,7,41,42; Margaret A. Pericak-Vance, PhD8; Joseph H. Lee, PhD2,3,43; Gerard D. Schellenberg, PhD9; Peter St. George-Hyslop, MD1; Richard Mayeux, MD2,3,4,32,44; Ekaterina Rogaeva, PhD1 ; for the Alzheimer’s Disease Genetics Consortium
[+] Author Affiliations
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario, Canada
2Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
3Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York
4Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
5Department of Medicine (Biomedical Genetics), Boston University, Boston, Massachusetts
6Department of Biostatistics, Boston University, Boston, Massachusetts
7Department of Ophthalmology, Boston University, Boston, Massachusetts
8The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
9Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
10Department of Medicine, University of Washington, Seattle
11Group Health Research Institute, Group Health, Seattle, Washington
12Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
13Department of Neurology, Mayo Clinic, Jacksonville, Florida
14Rush Institute for Healthy Aging, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
15Program in Translational Neuropsychiatric Genomics, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
16Harvard Medical School, Boston, Massachusetts
17Program in Medical and Population Genetics, The Broad Institute, Cambridge, Massachusetts
18Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
19Department of Genetics and Genomics Sciences, Mount Sinai School of Medicine, New York, New York
20Department of Neuroscience, Mount Sinai School of Medicine, New York, New York
21Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York
22Department of Medical and Molecular Genetics, Indiana University, Indianapolis
23Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
24Partners Center for Personalized Genetic Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
25Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
26Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
27Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, Maryland
28School of Public Health, University of Alabama at Birmingham
29SABA University School of Medicine, SABA, Dutch Caribbean
30Division of Geriatrics, Howard University Hospital, Washington, DC
31Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania
32Alzheimer’s Disease Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania
33Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
34Indiana University Center for Aging Research, Indianapolis
35Department of Psychiatry, Indiana University School of Medicine, Indianapolis
36Regenstrief Institute Inc, Indianapolis, Indiana
37Hope Center Program on Protein Aggregation and Neurodegeneration, Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
38Department of Biology, North Carolina A & T University, Greensboro
39National Alzheimer’s Coordinating Center, Department of Epidemiology, University of Washington, Seattle
40Vanderbilt Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee
41Department of Neurology, Boston University, Boston, Massachusetts
42Department of Epidemiology, Boston University, Boston, Massachusetts
43Department of Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York
44Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, New York
JAMA Neurol. 2015;72(11):1313-1323. doi:10.1001/jamaneurol.2015.1700.
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Importance  Mutations in known causal Alzheimer disease (AD) genes account for only 1% to 3% of patients and almost all are dominantly inherited. Recessive inheritance of complex phenotypes can be linked to long (>1-megabase [Mb]) runs of homozygosity (ROHs) detectable by single-nucleotide polymorphism (SNP) arrays.

Objective  To evaluate the association between ROHs and AD in an African American population known to have a risk for AD up to 3 times higher than white individuals.

Design, Setting, and Participants  Case-control study of a large African American data set previously genotyped on different genome-wide SNP arrays conducted from December 2013 to January 2015. Global and locus-based ROH measurements were analyzed using raw or imputed genotype data. We studied the raw genotypes from 2 case-control subsets grouped based on SNP array: Alzheimer’s Disease Genetics Consortium data set (871 cases and 1620 control individuals) and Chicago Health and Aging Project–Indianapolis Ibadan Dementia Study data set (279 cases and 1367 control individuals). We then examined the entire data set using imputed genotypes from 1917 cases and 3858 control individuals.

Main Outcomes and Measures  The ROHs larger than 1 Mb, 2 Mb, or 3 Mb were investigated separately for global burden evaluation, consensus regions, and gene-based analyses.

Results  The African American cohort had a low degree of inbreeding (F ~ 0.006). In the Alzheimer’s Disease Genetics Consortium data set, we detected a significantly higher proportion of cases with ROHs greater than 2 Mb (P = .004) or greater than 3 Mb (P = .02), as well as a significant 114-kilobase consensus region on chr4q31.3 (empirical P value 2 = .04; ROHs >2 Mb). In the Chicago Health and Aging Project–Indianapolis Ibadan Dementia Study data set, we identified a significant 202-kilobase consensus region on Chr15q24.1 (empirical P value 2 = .02; ROHs >1 Mb) and a cluster of 13 significant genes on Chr3p21.31 (empirical P value 2 = .03; ROHs >3 Mb). A total of 43 of 49 nominally significant genes common for both data sets also mapped to Chr3p21.31. Analyses of imputed SNP data from the entire data set confirmed the association of AD with global ROH measurements (12.38 ROHs >1 Mb in cases vs 12.11 in controls; 2.986 Mb average size of ROHs >2 Mb in cases vs 2.889 Mb in controls; and 22% of cases with ROHs >3 Mb vs 19% of controls) and a gene-cluster on Chr3p21.31 (empirical P value 2 = .006-.04; ROHs >3 Mb). Also, we detected a significant association between AD and CLDN17 (empirical P value 2 = .01; ROHs >1 Mb), encoding a protein from the Claudin family, members of which were previously suggested as AD biomarkers.

Conclusions and Relevance  To our knowledge, we discovered the first evidence of increased burden of ROHs among patients with AD from an outbred African American population, which could reflect either the cumulative effect of multiple ROHs to AD or the contribution of specific loci harboring recessive mutations and risk haplotypes in a subset of patients. Sequencing is required to uncover AD variants in these individuals.

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Figure 1.
Significant Results Obtained by Analyses of Consensus Regions

Consensus regions are indicated by red bars containing white arrowheads. A, The consensus region detected in the Alzheimer’s Disease Genetics Consortium (ADGC) data set contains the SH3D19 and RPS3A genes intersected by runs of homozygosity greater than 2 Mb in 7 cases (samples 10AD24322, 10AD30747, 11AD35799, 11AD35549, 10AD32217, 10AD32219, and 11AD35543) and no control individuals. B, The consensus region detected in the Chicago Health and Aging Project (CHAP)–Indianapolis Ibadan Dementia Study (IIDS) data set contains the STOML1, PML, GOLGA6A, and ISLR2 genes intersected by runs of homozygosity greater than 1 Mb in 5 cases (samples PT-J6K8_796, PT-J6L9_937, PT-28ZI_899514246, PT-9X4V_537994104, and PT-J7BC_5951) and no control individuals.

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Figure 2.
Significant Results Obtained by Gene-Based Analyses of the Chicago Health and Aging Project (CHAP)–Indianapolis Ibadan Dementia Study (IIDS) Data Set

The top section shows the runs of homozygosity (ROHs) greater than 3 Mb on chromosome 3 among cases (n = 279) and control individuals (n = 1367). Owing to an unbalanced distribution of cases and control individuals, fewer ROHs were observed among cases compared with control individuals, except at the Chr3p21.31 locus (section within the dashed lines), which was affected by ROHs greater than 3 Mb significantly more frequently in cases (2.9%, red bars) compared with control individuals (0.4%, blue bars). The middle section shows 2 down-brackets pointing to the significantly overlapped genes. The bottom section shows the linkage disequilibrium structure of the Chr3:46500000-52500000/hg18 region estimated based on control genotypes from the CHAP-IIDS data set. tRNA indicates transfer ribonucleic acid; UCSC, University of California–Santa Cruz.

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Figure 3.
Significant Results Obtained by Gene-Based Analyses of the Entire Data Set

The CLDN17 gene was intersected by runs of homozygosity (ROH) in 11 cases (red bars) but no control individuals (blue bar). CCDS indicates consensus coding sequence; tRNA, transfer ribonucleic acid; UCSC, University of California–Santa Cruz.

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