20 results on '"Boehme, Kevin L."'
Search Results
2. Fine-mapping of the human leukocyte antigen locus as a risk factor for Alzheimer disease: A case-control study.
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Steele, Natasha ZR, Carr, Jessie S, Bonham, Luke W, Geier, Ethan G, Damotte, Vincent, Miller, Zachary A, Desikan, Rahul S, Boehme, Kevin L, Mukherjee, Shubhabrata, Crane, Paul K, Kauwe, John SK, Kramer, Joel H, Miller, Bruce L, Coppola, Giovanni, Hollenbach, Jill A, Huang, Yadong, and Yokoyama, Jennifer S
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Humans ,Alzheimer Disease ,HLA Antigens ,Risk Factors ,Case-Control Studies ,Chromosome Mapping ,Haplotypes ,Aged ,Aged ,80 and over ,Middle Aged ,United States ,San Francisco ,Female ,Male ,General & Internal Medicine ,Medical and Health Sciences - Abstract
BackgroundAlzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations.Methods and findingsBuilding on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08-1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01-1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01-1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = -0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes.ConclusionsWe provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.
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- 2017
3. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease
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Allen, Genevera I, Amoroso, Nicola, Anghel, Catalina, Balagurusamy, Venkat, Bare, Christopher J, Beaton, Derek, Bellotti, Roberto, Bennett, David A, Boehme, Kevin L, Boutros, Paul C, Caberlotto, Laura, Caloian, Cristian, Campbell, Frederick, Neto, Elias Chaibub, Chang, Yu‐Chuan, Chen, Beibei, Chen, Chien‐Yu, Chien, Ting‐Ying, Clark, Tim, Das, Sudeshna, Davatzikos, Christos, Deng, Jieyao, Dillenberger, Donna, Dobson, Richard JB, Dong, Qilin, Doshi, Jimit, Duma, Denise, Errico, Rosangela, Erus, Guray, Everett, Evan, Fardo, David W, Friend, Stephen H, Fröhlich, Holger, Gan, Jessica, St George‐Hyslop, Peter, Ghosh, Satrajit S, Glaab, Enrico, Green, Robert C, Guan, Yuanfang, Hong, Ming‐Yi, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph, Inglese, Paolo, Iyappan, Anandhi, Jiang, Qijia, Katsumata, Yuriko, Kauwe, John SK, Klein, Arno, Kong, Dehan, Krause, Roland, Lalonde, Emilie, Lauria, Mario, Lee, Eunjee, Lin, Xihui, Liu, Zhandong, Livingstone, Julie, Logsdon, Benjamin A, Lovestone, Simon, Ma, Tsung‐wei, Malhotra, Ashutosh, Mangravite, Lara M, Maxwell, Taylor J, Merrill, Emily, Nagorski, John, Namasivayam, Aishwarya, Narayan, Manjari, Naz, Mufassra, Newhouse, Stephen J, Norman, Thea C, Nurtdinov, Ramil N, Oyang, Yen‐Jen, Pawitan, Yudi, Peng, Shengwen, Peters, Mette A, Piccolo, Stephen R, Praveen, Paurush, Priami, Corrado, Sabelnykova, Veronica Y, Senger, Philipp, Shen, Xia, Simmons, Andrew, Sotiras, Aristeidis, Stolovitzky, Gustavo, Tangaro, Sabina, Tateo, Andrea, Tung, Yi‐An, Tustison, Nicholas J, Varol, Erdem, Vradenburg, George, Weiner, Michael W, Xiao, Guanghua, Xie, Lei, Xie, Yang, Xu, Jia, Yang, Hojin, Zhan, Xiaowei, Zhou, Yunyun, Zhu, Fan, and Zhu, Hongtu
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Acquired Cognitive Impairment ,Prevention ,Neurodegenerative ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,Alzheimer's Disease ,Aging ,Brain Disorders ,Neurological ,Alzheimer Disease ,Apolipoproteins E ,Biomarkers ,Cognition Disorders ,Computational Biology ,Databases ,Bibliographic ,Humans ,Predictive Value of Tests ,Azheimer's disease ,Crowdsource ,Big data ,Bioinformatics ,Cognitive decline ,Imaging ,Genetics ,Alzheimer's Disease Neuroimaging Initiative ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
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- 2016
4. Distinct clinicopathologic clusters of persons with TDP-43 proteinopathy
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Katsumata, Yuriko, Abner, Erin L., Karanth, Shama, Teylan, Merilee A., Mock, Charles N., Cykowski, Matthew D., Lee, Edward B., Boehme, Kevin L., Mukherjee, Shubhabrata, Kauwe, John S. K., Kryscio, Richard J., Schmitt, Frederick A., Fardo, David W., and Nelson, Peter T.
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- 2020
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5. Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study.
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Østergaard, Søren D, Mukherjee, Shubhabrata, Sharp, Stephen J, Proitsi, Petroula, Lotta, Luca A, Day, Felix, Perry, John RB, Boehme, Kevin L, Walter, Stefan, Kauwe, John S, Gibbons, Laura E, Alzheimer’s Disease Genetics Consortium, GERAD1 Consortium, EPIC-InterAct Consortium, Larson, Eric B, Powell, John F, Langenberg, Claudia, Crane, Paul K, Wareham, Nicholas J, and Scott, Robert A
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Alzheimer’s Disease Genetics Consortium ,GERAD1 Consortium ,EPIC-InterAct Consortium ,Humans ,Alzheimer Disease ,Genetic Predisposition to Disease ,Risk Factors ,Polymorphism ,Single Nucleotide ,Female ,Male ,Mendelian Randomization Analysis ,Obesity ,Cardiovascular ,Diabetes ,Acquired Cognitive Impairment ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,Tobacco Smoke and Health ,Brain Disorders ,Human Genome ,Aging ,Clinical Research ,Genetics ,Tobacco ,Prevention ,Neurodegenerative ,Alzheimer's Disease ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,General & Internal Medicine ,Medical and Health Sciences - Abstract
BackgroundPotentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR).Methods and findingsWe used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses.ConclusionsInherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.
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- 2015
6. Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments
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Mukherjee, Shubhabrata, Russell, Joshua C., Carr, Daniel T., Burgess, Jeremy D., Allen, Mariet, Serie, Daniel J., Boehme, Kevin L., Kauwe, John S.K., Naj, Adam C., Fardo, David W., Dickson, Dennis W., Montine, Thomas J., Ertekin-Taner, Nilufer, Kaeberlein, Matt R., and Crane, Paul K.
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- 2017
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7. Genome-wide association study of brain arteriolosclerosis.
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Shade, Lincoln MP, Katsumata, Yuriko, Hohman, Timothy J, Nho, Kwangsik, Saykin, Andrew J, Mukherjee, Shubhabrata, Boehme, Kevin L, Kauwe, John SK, Farrer, Lindsay A, Schellenberg, Gerard D, Haines, Jonathan L, Mayeux, Richard P, Schneider, Julie A, Nelson, Peter T, and Fardo, David W
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Brain arteriolosclerosis (B-ASC) is characterized by pathologically altered brain parenchymal arterioles. B-ASC is associated with cognitive impairment and increased likelihood of clinical dementia. To date, no study has been conducted on genome-wide genetic risk of autopsy-proven B-ASC. We performed a genome-wide association study (GWAS) of the B-ASC phenotype using multiple independent aged neuropathologic cohorts. Included in the study were participants with B-ASC autopsy and genotype data available from the NACC, ROSMAP, ADNI, and ACT data sets. Initial Stage 1 GWAS (n = 3382) and Stage 2 mega-analysis (n = 4569) were performed using data from the two largest cohorts (NACC and ROSMAP). Replication of top variants and additional Stage 3 mega-analysis were performed incorporating two smaller cohorts (ADNI and ACT). Lead variants in the top two loci in the Stage 2 mega-analysis (rs7902929, p = 1.8 × 10 − 7 ; rs2603462, p = 4 × 10 − 7 ) were significant in the ADNI cohort (rs7902929, p = 0.012 ; rs2603462, p = 0.012). The rs2603462 lead variant colocalized with ELOVL4 expression in the cerebellum (posterior probability = 90.1%). Suggestive associations were also found near SORCS1 and SORCS3. We thus identified putative loci associated with B-ASC risk, but additional replication is needed. [ABSTRACT FROM AUTHOR]
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- 2022
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8. Analysis of genes (TMEM106B, GRN, ABCC9, KCNMB2, and APOE) implicated in risk for LATE-NC and hippocampal sclerosis provides pathogenetic insights: a retrospective genetic association study.
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Dugan, Adam J., Nelson, Peter T., Katsumata, Yuriko, Shade, Lincoln M. P., Boehme, Kevin L., Teylan, Merilee A., Cykowski, Matthew D., Mukherjee, Shubhabrata, Kauwe, John S. K., Hohman, Timothy J., Schneider, Julie A., and Fardo, David W.
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SINGLE nucleotide polymorphisms ,GENETIC variation ,GENOME-wide association studies ,HIPPOCAMPAL sclerosis ,GENES ,EXOMES ,PHENOTYPES - Abstract
Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is the most prevalent subtype of TDP-43 proteinopathy, affecting up to 1/3rd of aged persons. LATE-NC often co-occurs with hippocampal sclerosis (HS) pathology. It is currently unknown why some individuals with LATE-NC develop HS while others do not, but genetics may play a role. Previous studies found associations between LATE-NC phenotypes and specific genes: TMEM106B, GRN, ABCC9, KCNMB2, and APOE. Data from research participants with genomic and autopsy measures from the National Alzheimer's Coordinating Center (NACC; n = 631 subjects included) and the Religious Orders Study and Memory and the Rush Aging Project (ROSMAP; n = 780 included) were analyzed in the current study. Our goals were to reevaluate disease-associated genetic variants using newly collected data and to query whether the specific genotype/phenotype associations could provide new insights into disease-driving pathways. Research subjects included in prior LATE/HS genome-wide association studies (GWAS) were excluded. Single nucleotide variants (SNVs) within 10 kb of TMEM106B, GRN, ABCC9, KCNMB2, and APOE were tested for association with HS and LATE-NC, and separately for Alzheimer's pathologies, i.e. amyloid plaques and neurofibrillary tangles. Significantly associated SNVs were identified. When results were meta-analyzed, TMEM106B, GRN, and APOE had significant gene-based associations with both LATE and HS, whereas ABCC9 had significant associations with HS only. In a sensitivity analysis limited to LATE-NC + cases, ABCC9 variants were again associated with HS. By contrast, the associations of TMEM106B, GRN, and APOE with HS were attenuated when adjusting for TDP-43 proteinopathy, indicating that these genes may be associated primarily with TDP-43 proteinopathy. None of these genes except APOE appeared to be associated with Alzheimer's-type pathology. In summary, using data not included in prior studies of LATE or HS genomics, we replicated several previously reported gene-based associations and found novel evidence that specific risk alleles can differentially affect LATE-NC and HS. [ABSTRACT FROM AUTHOR]
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- 2021
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9. CHR17Q21 H2 HAPLOTYPE STRATIFIED GWAS REVEALS DIFFERENTIAL ASSOCIATION FOR AD RISK VARIANTS
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Strickland, Samantha L., Reddy, Joseph S., Allen, Mariet, N'Songo, Aurelie, Burgess, Jeremy D., Corda, Morgane M., Ballard, Travis, Mukherjee, Shubhabrata, Boehme, Kevin L., Crane, Paul K., Kauwe, John, and Ertekin-Taner, Nilufer
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- 2018
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10. FINE-MAPPING OF THE HUMAN LEUKOCYTE ANTIGEN (HLA) LOCUS AS A RISK FACTOR FOR ALZHEIMER'S DISEASE
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Carr, Jessie S., Steele, Natasha ZR., Bonham, Luke W., Geier, Ethan G., Damotte, Vincent, Miller, Zachary A., Desikan, Rahul S., Boehme, Kevin L., Mukherjee, Shubhabrata, Crane, Paul K., Kauwe, John, Kramer, Joel H., Miller, Bruce L., Coppola, Giovanni, Hollenbach, Jill A., Huang, Yadong, and Yokoyama, Jennifer S.
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- 2017
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11. SECONDARY ANALYSES OF INTERNATIONAL GENOMICS OF ALZHEIMER'S PROJECT STAGE I GWAS SUMMARY DATA IDENTIFIES ADDITIONAL VARIANTS ASSOCIATED WITH LATE-ONSET ALZHEIMER'S DISEASE
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Mukherjee, Shubhabrata, Boehme, Kevin L., Fardo, David W., Kunkle, Brian W., Kauwe, John, Lambert, Jean-Charles, Amouyel, Philippe, Pericak-Vance, Margaret A., Schellenberg, Gerard D., and Crane, Paul K.
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- 2016
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12. ASSESSMENT OF THE GENETIC VARIANCE OF LATE-ONSET ALZHEIMER’S DISEASE
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Ridge, Perry G., Ebbert, Mark, Hoyt, Kaitlyn, Boehme, Kevin L., Mukherjee, Shubhabrata, Crane, Paul K., Haines, Jonathan L., Mayeux, Richard, Farrer, Lindsay A., Pericak-Vance, Margaret A., Schellenberg, Gerard D., and Kauwe, John
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- 2016
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13. Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk.
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Ebbert, Mark T.W., Boehme, Kevin L., Wadsworth, Mark E., Staley, Lyndsay A., Mukherjee, Shubhabrata, Crane, Paul K., Ridge, Perry G., and Kauwe, John S.K.
- Abstract
Introduction Ebbert et al. reported gene-gene interactions between rs11136000-rs670139 ( CLU - MS4A4E ) and rs3865444-rs670139 ( CD33 - MS4A4E ). We evaluate these interactions in the largest data set for an epistasis study. Methods We tested interactions using 3837 cases and 4145 controls from Alzheimer's Disease Genetics Consortium using meta-analyses and permutation analyses. We repeated meta-analyses stratified by apolipoprotein E ( APOE ) ε4 status, estimated combined odds ratio (OR) and population attributable fraction (cPAF), and explored causal variants. Results Results support the CLU - MS4A4E interaction and a dominant effect. An association between CLU - MS4A4E and APOE ε4 negative status exists. The estimated synergy factor, OR, and cPAF for rs11136000-rs670139 are 2.23, 2.45, and 8.0, respectively. We identified potential causal variants. Discussion We replicated the CLU - MS4A4E interaction in a large case-control series and observed APOE ε4 and possible dominant effect. The CLU - MS4A4E OR is higher than any Alzheimer's disease locus except APOE ε4, APP , and TREM2 . We estimated an 8% decrease in Alzheimer's disease incidence without CLU - MS4A4E risk alleles and identified potential causal variants. [ABSTRACT FROM AUTHOR]
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- 2016
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14. Variant Tool Chest: an improved tool to analyze and manipulate variant call format (VCF) files.
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Ebbert, Mark T. W., Wadsworth, Mark E., Boehme, Kevin L., Hoyt, Kaitlyn L., Sharp, Aaron R., O'Fallon, Brendan D., Kauwe, John S. K., and Ridge, Perry G.
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MEDICAL equipment ,GENOMICS ,NEXT generation networks ,REMOTE access networks ,MEDICAL records - Abstract
Background: Since the advent of next-generation sequencing many previously untestable hypotheses have been realized. Next-generation sequencing has been used for a wide range of studies in diverse fields such as population and medical genetics, phylogenetics, microbiology, and others. However, this novel technology has created unanticipated challenges such as the large numbers of genetic variants. Each caucasian genome has more than four million single nucleotide variants, insertions and deletions, copy number variants, and structural variants. Several formats have been suggested for storing these variants; however, the variant call format (VCF) has become the community standard. Results: We developed new software called the Variant Tool Chest (VTC) to provide much needed tools to work with VCF files. VTC provides a variety of tools for manipulating, comparing, and analyzing VCF files beyond the functionality of existing tools. In addition, VTC was written to be easily extended with new tools. Conclusions: Variant Tool Chest brings new and important functionality that complements and integrates well with existing software. VTC is available at https://github.com/mebbert/VariantToolChest. [ABSTRACT FROM AUTHOR]
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- 2014
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15. Population substructure in Cache County, Utah: the Cache County study.
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Sharp, Aaron R., Ridge, Perry G., Bailey, Matthew H., Boehme, Kevin L., Norton, Maria C., Tschanz, JoAnn T., Munger, Ronald G., Corcoran, Christopher D., and Kauwe, John S. K.
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POPULATION genetics ,GENETIC load ,CELLULAR automata ,POPULATION transfers ,ECOLOGICAL research - Abstract
Background: Population stratification is a key concern for genetic association analyses. In addition, extreme homogeneity of ethnic origins of a population can make it difficult to interpret how genetic associations in that population may translate into other populations. Here we have evaluated the genetic substructure of samples from the Cache County study relative to the HapMap Reference populations and data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Results: Our findings show that the Cache County study is similar in ethnic diversity to the self-reported "Whites" in the ADNI sample and less homogenous than the HapMap CEU population. Conclusions: We conclude that the Cache County study is genetically representative of the general European American population in the USA and is an appropriate population for conducting broadly applicable genetic studies. [ABSTRACT FROM AUTHOR]
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- 2014
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16. P2‐136: ANALYZING THE SNP‐BASED HERITABILITY IN ALZHEIMER'S DISEASE.
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Black, Gage S., Boehme, Kevin L., Mukherjee, Shubhabrata, Crane, Paul K., Ridge, Perry G., and Kauwe, John
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- 2019
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17. P2‐141: CHR17Q21 H2 HAPLOTYPE STRATIFIED GWAS REVEALS DIFFERENTIAL ASSOCIATION FOR AD RISK VARIANTS.
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Strickland, Samantha L., Reddy, Joseph S., Allen, Mariet, N'Songo, Aurelie, Burgess, Jeremy D., Corda, Morgane M., Ballard, Travis, Mukherjee, Shubhabrata, Boehme, Kevin L., Crane, Paul K., Kauwe, John, and Ertekin-Taner, Nilufer
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- 2018
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18. Integrating human protein-protein interaction network with results from gwas in whites and african-americans identifies common genes underlying late-onset Alzheimer’s disease.
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Mukherjee, Shubhabrata, Boehme, Kevin L., Naj, Adam C., Fardo, David W., Kauwe, John, Manly, Jennifer J., Montine, Thomas J., and Crane, Paul K.
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- 2015
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19. Genome-Wide Sensitivity Analysis of the Microsymbiont Sinorhizobium meliloti to Symbiotically Important, Defensin-Like Host Peptides.
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Arnold MFF, Shabab M, Penterman J, Boehme KL, Griffitts JS, and Walker GC
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- Bacterial Proteins genetics, Cysteine metabolism, Defensins pharmacology, High-Throughput Nucleotide Sequencing, Medicago truncatula chemistry, Membrane Transport Proteins metabolism, Mutagenesis, Nitrogen Fixation, Sinorhizobium meliloti drug effects, Defensins metabolism, Medicago truncatula microbiology, Sinorhizobium meliloti genetics, Sinorhizobium meliloti metabolism, Symbiosis
- Abstract
The model legume species Medicago truncatula expresses more than 700 nodule-specific cysteine-rich (NCR) signaling peptides that mediate the differentiation of Sinorhizobium meliloti bacteria into nitrogen-fixing bacteroids. NCR peptides are essential for a successful symbiosis in legume plants of the inverted-repeat-lacking clade (IRLC) and show similarity to mammalian defensins. In addition to signaling functions, many NCR peptides exhibit antimicrobial activity in vitro and in vivo Bacterial resistance to these antimicrobial activities is likely to be important for symbiosis. However, the mechanisms used by S. meliloti to resist antimicrobial activity of plant peptides are poorly understood. To address this, we applied a global genetic approach using transposon mutagenesis followed by high-throughput sequencing (Tn-seq) to identify S. meliloti genes and pathways that increase or decrease bacterial competitiveness during exposure to the well-studied cationic NCR247 peptide and also to the unrelated model antimicrobial peptide polymyxin B. We identified 78 genes and several diverse pathways whose interruption alters S. meliloti resistance to NCR247. These genes encode the following: (i) cell envelope polysaccharide biosynthesis and modification proteins, (ii) inner and outer membrane proteins, (iii) peptidoglycan (PG) effector proteins, and (iv) non-membrane-associated factors such as transcriptional regulators and ribosome-associated factors. We describe a previously uncharacterized yet highly conserved peptidase, which protects S. meliloti from NCR247 and increases competitiveness during symbiosis. Additionally, we highlight a considerable number of uncharacterized genes that provide the basis for future studies to investigate the molecular basis of symbiotic development as well as chronic pathogenic interactions. IMPORTANCE Soil rhizobial bacteria enter into an ecologically and economically important symbiotic interaction with legumes, in which they differentiate into physiologically distinct bacteroids that provide essential ammonia to the plant in return for carbon sources. Plant signal peptides are essential and specific to achieve these physiological changes. These peptides show similarity to mammalian defensin peptides which are part of the first line of defense to control invading bacterial populations. A number of these legume peptides are indeed known to possess antimicrobial activity, and so far, only the bacterial BacA protein is known to protect rhizobial bacteria against their antimicrobial action. This study identified numerous additional bacterial factors that mediate protection and belong to diverse biological pathways. Our results significantly contribute to our understanding of the molecular roles of bacterial factors during legume symbioses and, second, provide insights into the mechanisms that pathogenic bacteria may use to resist the antimicrobial effects of defensins during infections., (Copyright © 2017 Arnold et al.)
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- 2017
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20. Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk.
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Ebbert MTW, Boehme KL, Wadsworth ME, Staley LA, Mukherjee S, Crane PK, Ridge PG, and Kauwe JSK
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- Alleles, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study methods, Humans, Male, Risk Factors, Alzheimer Disease genetics, Apolipoprotein E4 genetics, Clusterin genetics, Epistasis, Genetic, Membrane Proteins genetics, Sialic Acid Binding Ig-like Lectin 3 genetics
- Abstract
Introduction: Ebbert et al. reported gene-gene interactions between rs11136000-rs670139 (CLU-MS4A4E) and rs3865444-rs670139 (CD33-MS4A4E). We evaluate these interactions in the largest data set for an epistasis study., Methods: We tested interactions using 3837 cases and 4145 controls from Alzheimer's Disease Genetics Consortium using meta-analyses and permutation analyses. We repeated meta-analyses stratified by apolipoprotein E (APOE) ε4 status, estimated combined odds ratio (OR) and population attributable fraction (cPAF), and explored causal variants., Results: Results support the CLU-MS4A4E interaction and a dominant effect. An association between CLU-MS4A4E and APOE ε4 negative status exists. The estimated synergy factor, OR, and cPAF for rs11136000-rs670139 are 2.23, 2.45, and 8.0, respectively. We identified potential causal variants., Discussion: We replicated the CLU-MS4A4E interaction in a large case-control series and observed APOE ε4 and possible dominant effect. The CLU-MS4A4E OR is higher than any Alzheimer's disease locus except APOE ε4, APP, and TREM2. We estimated an 8% decrease in Alzheimer's disease incidence without CLU-MS4A4E risk alleles and identified potential causal variants., (Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)
- Published
- 2016
- Full Text
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