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35 results on '"Schellenberg, GD"'

1. Common Variants Near ZIC1 and ZIC4 in Autopsy-Confirmed Multiple System Atrophy.

Author: Hopfner, F, Tietz, AK, Ruf, VC, Ross, OA, Koga, S, Dickson, D, Aguzzi, A, Attems, J, Beach, T, Beller, A, Cheshire, WP, van Deerlin, V, Desplats, P, Deuschl, G, Duyckaerts, C, Ellinghaus, D, Evsyukov, V, Flanagan, ME, Franke, A, Frosch, MP, Gearing, M, Gelpi, E, van Gerpen, JA, Ghetti, B, Glass, JD, Grinberg, LT, Halliday, G, Helbig, I, Höllerhage, M, Huitinga, I, Irwin, DJ, Keene, DC, Kovacs, GG, Lee, EB, Levin, J, Martí, MJ, Mackenzie, I, McKeith, I, Mclean, C, Mollenhauer, B, Neumann, M, Newell, KL, Pantelyat, A, Pendziwiat, M, Peters, A, Molina Porcel, L, Rabano, A, Matěj, R, Rajput, A, Reimann, R, Scott, WK, Seeley, W, Selvackadunco, S, Simuni, T, Stadelmann, C, Svenningsson, P, Thomas, A, Trenkwalder, C, Troakes, C, Trojanowski, JQ, Uitti, RJ, White, CL, Wszolek, ZK, Xie, T, Ximelis, T, Yebenes, J, Alzheimer's Disease Genetics Consortium, Müller, U, Schellenberg, GD, Herms, J, Kuhlenbäumer, G, Höglinger, G, Hopfner, F, Tietz, AK, Ruf, VC, Ross, OA, Koga, S, Dickson, D, Aguzzi, A, Attems, J, Beach, T, Beller, A, Cheshire, WP, van Deerlin, V, Desplats, P, Deuschl, G, Duyckaerts, C, Ellinghaus, D, Evsyukov, V, Flanagan, ME, Franke, A, Frosch, MP, Gearing, M, Gelpi, E, van Gerpen, JA, Ghetti, B, Glass, JD, Grinberg, LT, Halliday, G, Helbig, I, Höllerhage, M, Huitinga, I, Irwin, DJ, Keene, DC, Kovacs, GG, Lee, EB, Levin, J, Martí, MJ, Mackenzie, I, McKeith, I, Mclean, C, Mollenhauer, B, Neumann, M, Newell, KL, Pantelyat, A, Pendziwiat, M, Peters, A, Molina Porcel, L, Rabano, A, Matěj, R, Rajput, A, Reimann, R, Scott, WK, Seeley, W, Selvackadunco, S, Simuni, T, Stadelmann, C, Svenningsson, P, Thomas, A, Trenkwalder, C, Troakes, C, Trojanowski, JQ, Uitti, RJ, White, CL, Wszolek, ZK, Xie, T, Ximelis, T, Yebenes, J, Alzheimer's Disease Genetics Consortium, Müller, U, Schellenberg, GD, Herms, J, Kuhlenbäumer, G, and Höglinger, G
Published: 2022

2. Sex differences in the genetic architecture underlying resilience in AD

Author: Eissman, JM, Dumitrescu, L, Mahoney, ER, Mukherjee, S, Lee, ML, Bush, WS, Engelman, CD, Lu, Q, Fardo, DW, Trittschuh, EH, Mez, J, Kaczorowski, CC, Saucedo, HH, Widaman, KF, Buckley, RF, Properzi, MJ, Mormino, EC, Yang, H, Harrison, TM, Hedden, T, Nho, K, Andrews, SJ, Tommet, D, Hadad, N, Sanders, RE, Ruderfer, DM, Gifford, KA, Zhong, X, Raghavan, NS, Vardarajan, BN, Initiative, ADN, Consortium, ADG, Team, AS, Pericak‐Vance, MA, Farrer, LA, Wang, L, Cruchaga, C, Schellenberg, GD, Cox, NJ, Haines, JL, Keene, CD, Saykin, AJ, Larson, EB, Sperling, RA, Mayeux, R, Cuccaro, ML, Bennett, DA, Schneider, JA, Crane, PK, Jefferson, AL, Hohman, TJ, Eissman, JM, Dumitrescu, L, Mahoney, ER, Mukherjee, S, Lee, ML, Bush, WS, Engelman, CD, Lu, Q, Fardo, DW, Trittschuh, EH, Mez, J, Kaczorowski, CC, Saucedo, HH, Widaman, KF, Buckley, RF, Properzi, MJ, Mormino, EC, Yang, H, Harrison, TM, Hedden, T, Nho, K, Andrews, SJ, Tommet, D, Hadad, N, Sanders, RE, Ruderfer, DM, Gifford, KA, Zhong, X, Raghavan, NS, Vardarajan, BN, Initiative, ADN, Consortium, ADG, Team, AS, Pericak‐Vance, MA, Farrer, LA, Wang, L, Cruchaga, C, Schellenberg, GD, Cox, NJ, Haines, JL, Keene, CD, Saykin, AJ, Larson, EB, Sperling, RA, Mayeux, R, Cuccaro, ML, Bennett, DA, Schneider, JA, Crane, PK, Jefferson, AL, and Hohman, TJ
Abstract: Background Approximately 30% of older adults are cognitively normal at death despite presence of Alzheimer’s disease (AD) neuropathology at autopsy. Studying these “resilient” individuals may lead to the discovery of novel therapeutic targets. In addition, growing evidence suggests sex differences in downstream neurodegenerative consequences of AD neuropathology, with recent studies highlighting notable sex-specific genetic drivers of AD pathogenesis. We sought to extend this work by elucidating sex-specific genetic factors underlying resilience to AD. Method We used our published genetic resilience pipeline to assess sex-specific genetic predictors (Dumitrescu et al., 2020). Briefly, we used modern psychometric approaches to harmonize cognitive measures across four cohorts of cognitive aging (N=5054), in-vivo amyloid PET across two studies, and leveraged autopsy measures of amyloidosis (CERAD staging) across two studies. A continuous measure of resilience was quantified using a latent variable framework whereby higher scores reflected better-than-predicted cognitive performance given amyloidosis level and lower scores reflected worse-than-predicted performance. We then performed sex-stratified GWASs and sex-interaction GWASs, covarying for age and the first three principal components and meta-analyzed across cohorts. Finally, we performed sex-stratified genetic correlation analyses (GNOVA) between our meta-analysis results and summary statistics from 63 complex traits. Result Among individuals with normal cognition, we identified a female-specific locus on chromosome 10 (rs827389, [p(females)=7.4E-09, p(males)=0.64, p(interaction)=8.3E-05, MAF=0.46]). This variant is a modest eQTL for KIN (p=0.003), a gene encoding a DNA/RNA binding protein (http://www.braineac.org). In our genetic correlation analyses, we observed male-specific correlations between resilience and two heart rate-related traits, whereby higher resilience was associated with lower genetic risk for po
Published: 2021

3. Sex‐specific genetic predictors of memory performance

Author: Smith, AN, Dumitrescu, L, Mukherjee, S, Lee, ML, Choi, S, Trittschuh, EH, Mez, J, Mahoney, ER, Bush, WS, Engelman, CD, Lu, Q, Fardo, DW, Widaman, KF, Buckley, RF, Mormino, EC, Harrison, TM, Sanders, RE, Clark, LR, Gifford, KA, Vardarajan, BN, Initiative, ADN, Consortium, ADG, Team, AS, Project, TADS, Cuccaro, ML, Pericak‐Vance, MA, Farrer, LA, Wang, L, Schellenberg, GD, Haines, JL, Jefferson, AL, Johnson, SC, Kukull, WA, Albert, MS, Keene, CD, Saykin, AJ, Larson, EB, Sperling, RA, Mayeux, R, Bennett, DA, Schneider, JA, Crane, PK, Hohman, TJ, Smith, AN, Dumitrescu, L, Mukherjee, S, Lee, ML, Choi, S, Trittschuh, EH, Mez, J, Mahoney, ER, Bush, WS, Engelman, CD, Lu, Q, Fardo, DW, Widaman, KF, Buckley, RF, Mormino, EC, Harrison, TM, Sanders, RE, Clark, LR, Gifford, KA, Vardarajan, BN, Initiative, ADN, Consortium, ADG, Team, AS, Project, TADS, Cuccaro, ML, Pericak‐Vance, MA, Farrer, LA, Wang, L, Schellenberg, GD, Haines, JL, Jefferson, AL, Johnson, SC, Kukull, WA, Albert, MS, Keene, CD, Saykin, AJ, Larson, EB, Sperling, RA, Mayeux, R, Bennett, DA, Schneider, JA, Crane, PK, and Hohman, TJ
Abstract: Background There are notable sex differences in the clinical manifestation of Alzheimer’s disease (AD), including differences in baseline and longitudinal changes in memory performance. However, sex-stratified models have not been routinely incorporated into genetic studies of cognitive performance or decline. We sought to identify sex-specific genetic predictors of memory performance in aging adults. Method We obtained harmonized memory scores from 11,601 females and 8,885 males from 7 cohorts of cognitive aging. We calculated scores using latent variable modeling techniques anchored on overlapping neuropsychological test items across datasets to perform both sex-stratified and sex-interaction genome-wide association studies in each cohort using mixed-effects regression models to assess genetic associations with baseline memory score and rate of memory decline. Covariates included age at baseline and population principal components. We then combined results in a fixed-effect meta-analysis. Results As expected, we observed robust associations at the APOE locus in males and females in both baseline and longitudinal models. Additionally, we identified a sex-specific locus for longitudinal memory performance (interaction-p=2.54e-6) on chromosome 7 within LINC-PINT that was genome-wide significant in males (index SNP= rs66754621; p=1.62e-8; MAF=0.20), but not females (p=0.65). This variant is in an enhancer region within several brain regions, as well as within a promoter-anchored chromatin interaction loop and a methylation eQTL in the prefrontal cortex. No female-specific loci were identified. Interestingly, we did observe nominal associations in baseline memory at some known AD loci, including male-specific effects at MS4A6A, FERMT2, and KAT8 (interaction ps=0.0026, 0.027, and 0.0058, respectively) and opposing effects between males and females at INPP5D (interaction p=0.0021). Conclusion These results highlight a novel male-specific locus of memory performance on ch
Published: 2021

4. Correction: Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.

Author: Bis, JC, Jian, X, Kunkle, BW, Chen, Y, Hamilton-Nelson, KL, Bush, WS, Salerno, WJ, Lancour, D, Ma, Y, Renton, AE, Marcora, E, Farrell, JJ, Zhao, Y, Qu, L, Ahmad, S, Amin, N, Amouyel, P, Beecham, GW, Below, JE, Campion, D, Cantwell, L, Charbonnier, C, Chung, J, Crane, PK, Cruchaga, C, Cupples, LA, Dartigues, J-F, Debette, S, Deleuze, J-F, Fulton, L, Gabriel, SB, Genin, E, Gibbs, RA, Goate, A, Grenier-Boley, B, Gupta, N, Haines, JL, Havulinna, AS, Helisalmi, S, Hiltunen, M, Howrigan, DP, Ikram, MA, Kaprio, J, Konrad, J, Kuzma, A, Lander, ES, Lathrop, M, Lehtimäki, T, Lin, H, Mattila, K, Mayeux, R, Muzny, DM, Nasser, W, Neale, B, Nho, K, Nicolas, G, Patel, D, Pericak-Vance, MA, Perola, M, Psaty, BM, Quenez, O, Rajabli, F, Redon, R, Reitz, C, Remes, AM, Salomaa, V, Sarnowski, C, Schmidt, H, Schmidt, M, Schmidt, R, Soininen, H, Thornton, TA, Tosto, G, Tzourio, C, van der Lee, SJ, van Duijn, CM, Valladares, O, Vardarajan, B, Wang, L-S, Wang, W, Wijsman, E, Wilson, RK, Witten, D, Worley, KC, Zhang, X, Alzheimer’s Disease Sequencing Project, Bellenguez, C, Lambert, J-C, Kurki, MI, Palotie, A, Daly, M, Boerwinkle, E, Lunetta, KL, Destefano, AL, Dupuis, J, Martin, ER, Schellenberg, GD, Seshadri, S, Naj, AC, Fornage, M, Farrer, LA, Bis, JC, Jian, X, Kunkle, BW, Chen, Y, Hamilton-Nelson, KL, Bush, WS, Salerno, WJ, Lancour, D, Ma, Y, Renton, AE, Marcora, E, Farrell, JJ, Zhao, Y, Qu, L, Ahmad, S, Amin, N, Amouyel, P, Beecham, GW, Below, JE, Campion, D, Cantwell, L, Charbonnier, C, Chung, J, Crane, PK, Cruchaga, C, Cupples, LA, Dartigues, J-F, Debette, S, Deleuze, J-F, Fulton, L, Gabriel, SB, Genin, E, Gibbs, RA, Goate, A, Grenier-Boley, B, Gupta, N, Haines, JL, Havulinna, AS, Helisalmi, S, Hiltunen, M, Howrigan, DP, Ikram, MA, Kaprio, J, Konrad, J, Kuzma, A, Lander, ES, Lathrop, M, Lehtimäki, T, Lin, H, Mattila, K, Mayeux, R, Muzny, DM, Nasser, W, Neale, B, Nho, K, Nicolas, G, Patel, D, Pericak-Vance, MA, Perola, M, Psaty, BM, Quenez, O, Rajabli, F, Redon, R, Reitz, C, Remes, AM, Salomaa, V, Sarnowski, C, Schmidt, H, Schmidt, M, Schmidt, R, Soininen, H, Thornton, TA, Tosto, G, Tzourio, C, van der Lee, SJ, van Duijn, CM, Valladares, O, Vardarajan, B, Wang, L-S, Wang, W, Wijsman, E, Wilson, RK, Witten, D, Worley, KC, Zhang, X, Alzheimer’s Disease Sequencing Project, Bellenguez, C, Lambert, J-C, Kurki, MI, Palotie, A, Daly, M, Boerwinkle, E, Lunetta, KL, Destefano, AL, Dupuis, J, Martin, ER, Schellenberg, GD, Seshadri, S, Naj, AC, Fornage, M, and Farrer, LA
Abstract: A correction to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020

5. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author: Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, YC, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Guðnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, CY, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, Destefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, Decarli, C, Wardlaw, JM, Del C. Valdés Hernández, M, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, HW, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Völker, U, Levi, C, Jimenez-Conde, J, Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, YC, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Guðnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, CY, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, Destefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, Decarli, C, Wardlaw, JM, Del C. Valdés Hernández, M, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, HW, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Völker, U, Levi, C, and Jimenez-Conde, J
Abstract: Objective To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n=20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p[BI]= 4.4 × 10-10; p [SSBI] = 1.2 × 10 -4), diabetes (p[BI] = 1.7 × 10 -8; p [SSBI] = 2.8 × 10 -3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10 -24), and MRI-defined white matter hyperintensity burden (p [BI]=1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significan
Published: 2019

6. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author: Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, YC, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Guðnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, CY, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, Destefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, Decarli, C, Wardlaw, JM, Del C. Valdés Hernández, M, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, HW, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Völker, U, Levi, C, Jimenez-Conde, J, McWhirter, Rebekah, Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, YC, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Guðnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, CY, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, Destefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, Decarli, C, Wardlaw, JM, Del C. Valdés Hernández, M, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, HW, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Völker, U, Levi, C, Jimenez-Conde, J, and McWhirter, Rebekah
Published: 2019

7. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author: Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, Y-C, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Gudnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, C-Y, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, DeStefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, DeCarli, C, Wardlaw, JM, Hernandez, MDCV, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, H-W, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Voelker, U, Levi, C, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rosand, J, Woo, D, Cole, JW, Meschia, JF, Slowik, A, Thijs, V, Lindgren, A, Melander, O, Grewal, RP, Rundek, T, Rexrode, K, Rothwell, PM, Arnett, DK, Jern, C, Johnson, JA, Benavente, OR, Wasssertheil-Smoller, S, Lee, J-M, Wong, Q, Mitchell, BD, Rich, SS, McArdle, PF, Geerlings, MI, van der Graaf, Y, de Bakker, PIW, Asselbergs, FW, Srikanth, V, Thomson, R, McWhirter, R, Moran, C, Callisaya, M, Thanh, P, Rutten-Jacobs, LCA, Bevan, S, Tzourio, C, Mather, KA, Sachdev, PS, van Duijn, CM, Worrall, BB, Dichgans, M, Kittner, SJ, Markus, HS, Ikram, MA, Fornage, M, Launer, LJ, Seshadri, S, Longstreth, WT, Debette, S, Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, Y-C, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Gudnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, C-Y, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, DeStefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, DeCarli, C, Wardlaw, JM, Hernandez, MDCV, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, H-W, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Voelker, U, Levi, C, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rosand, J, Woo, D, Cole, JW, Meschia, JF, Slowik, A, Thijs, V, Lindgren, A, Melander, O, Grewal, RP, Rundek, T, Rexrode, K, Rothwell, PM, Arnett, DK, Jern, C, Johnson, JA, Benavente, OR, Wasssertheil-Smoller, S, Lee, J-M, Wong, Q, Mitchell, BD, Rich, SS, McArdle, PF, Geerlings, MI, van der Graaf, Y, de Bakker, PIW, Asselbergs, FW, Srikanth, V, Thomson, R, McWhirter, R, Moran, C, Callisaya, M, Thanh, P, Rutten-Jacobs, LCA, Bevan, S, Tzourio, C, Mather, KA, Sachdev, PS, van Duijn, CM, Worrall, BB, Dichgans, M, Kittner, SJ, Markus, HS, Ikram, MA, Fornage, M, Launer, LJ, Seshadri, S, Longstreth, WT, and Debette, S
Abstract: OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most si
Published: 2019

8. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author: Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, Y-C, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Gudnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, C-Y, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, DeStefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, DeCarli, C, Wardlaw, JM, Hernandez, MDCV, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, H-W, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Voelker, U, Levi, C, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rosand, J, Woo, D, Cole, JW, Meschia, JF, Slowik, A, Thijs, V, Lindgren, A, Melander, O, Grewal, RP, Rundek, T, Rexrode, K, Rothwell, PM, Arnett, DK, Jern, C, Johnson, JA, Benavente, OR, Wasssertheil-Smoller, S, Lee, J-M, Wong, Q, Mitchell, BD, Rich, SS, McArdle, PF, Geerlings, MI, van der Graaf, Y, de Bakker, PIW, Asselbergs, FW, Srikanth, V, Thomson, R, McWhirter, R, Moran, C, Callisaya, M, Thanh, P, Rutten-Jacobs, LCA, Bevan, S, Tzourio, C, Mather, KA, Sachdev, PS, van Duijn, CM, Worrall, BB, Dichgans, M, Kittner, SJ, Markus, HS, Ikram, MA, Fornage, M, Launer, LJ, Seshadri, S, Longstreth, WT, Debette, S, Chauhan, G, Adams, HHH, Satizabal, CL, Bis, JC, Teumer, A, Sargurupremraj, M, Hofer, E, Trompet, S, Hilal, S, Smith, AV, Jian, X, Malik, R, Traylor, M, Pulit, SL, Amouyel, P, Mazoyer, B, Zhu, Y-C, Kaffashian, S, Schilling, S, Beecham, GW, Montine, TJ, Schellenberg, GD, Kjartansson, O, Gudnason, V, Knopman, DS, Griswold, ME, Windham, BG, Gottesman, RF, Mosley, TH, Schmidt, R, Saba, Y, Schmidt, H, Takeuchi, F, Yamaguchi, S, Nabika, T, Kato, N, Rajan, KB, Aggarwal, NT, De Jager, PL, Evans, DA, Psaty, BM, Rotter, JI, Rice, K, Lopez, OL, Liao, J, Chen, C, Cheng, C-Y, Wong, TY, Ikram, MK, van der Lee, SJ, Amin, N, Chouraki, V, DeStefano, AL, Aparicio, HJ, Romero, JR, Maillard, P, DeCarli, C, Wardlaw, JM, Hernandez, MDCV, Luciano, M, Liewald, D, Deary, IJ, Starr, JM, Bastin, ME, Maniega, SM, Slagboom, PE, Beekman, M, Deelen, J, Uh, H-W, Lemmens, R, Brodaty, H, Wright, MJ, Ames, D, Boncoraglio, GB, Hopewell, JC, Beecham, AH, Blanton, SH, Wright, CB, Sacco, RL, Wen, W, Thalamuthu, A, Armstrong, NJ, Chong, E, Schofield, PR, Kwok, JB, van der Grond, J, Stott, DJ, Ford, I, Jukema, JW, Vernooij, MW, Hofman, A, Uitterlinden, AG, van der Lugt, A, Wittfeld, K, Grabe, HJ, Hosten, N, von Sarnowski, B, Voelker, U, Levi, C, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rosand, J, Woo, D, Cole, JW, Meschia, JF, Slowik, A, Thijs, V, Lindgren, A, Melander, O, Grewal, RP, Rundek, T, Rexrode, K, Rothwell, PM, Arnett, DK, Jern, C, Johnson, JA, Benavente, OR, Wasssertheil-Smoller, S, Lee, J-M, Wong, Q, Mitchell, BD, Rich, SS, McArdle, PF, Geerlings, MI, van der Graaf, Y, de Bakker, PIW, Asselbergs, FW, Srikanth, V, Thomson, R, McWhirter, R, Moran, C, Callisaya, M, Thanh, P, Rutten-Jacobs, LCA, Bevan, S, Tzourio, C, Mather, KA, Sachdev, PS, van Duijn, CM, Worrall, BB, Dichgans, M, Kittner, SJ, Markus, HS, Ikram, MA, Fornage, M, Launer, LJ, Seshadri, S, Longstreth, WT, and Debette, S
Published: 2019

9. Immune-related genetic enrichment in frontotemporal dementia: An analysis of genome-wide association studies

Author: Broce, I, Karch, CM, Wen, N, Fan, CC, Wang, Y, Hong Tan, C, Kouri, N, Ross, OA, Höglinger, GU, Muller, U, Hardy, J, Momeni, P, Hess, CP, Dillon, WP, Miller, ZA, Bonham, LW, Rabinovici, GD, Rosen, HJ, Schellenberg, GD, Franke, A, Karlsen, TH, Veldink, JH, Ferrari, R, Yokoyama, JS, Miller, BL, Andreassen, OA, Dale, AM, Desikan, RS, Sugrue, LP, Hernandez, DG, Nalls, MA, Rohrer, JD, Ramasamy, A, Kwok, JBJ, Dobson-Stone, C, Brooks, WS, Schofield, PR, Halliday, GM, Hodges, JR, Piguet, O, Bartley, L, Thompson, E, Haan, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, NJ, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Landqvist Waldö, M, Nilsson, K, Nilsson, C, Mackenzie, IRA, Hsiung, GYR, Mann, DMA, Grafman, J, Morris, CM, Attems, J, Griffiths, TD, G McKeith, I, Thomas, AJ, Pietrini, P, Huey, ED, Wassermann, EM, Baborie, A, Jaros, E, Tierney, MC, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, St George-Hyslop, P, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, JB, Schlachetzki, JCM, Uphill, J, Broce, I, Karch, CM, Wen, N, Fan, CC, Wang, Y, Hong Tan, C, Kouri, N, Ross, OA, Höglinger, GU, Muller, U, Hardy, J, Momeni, P, Hess, CP, Dillon, WP, Miller, ZA, Bonham, LW, Rabinovici, GD, Rosen, HJ, Schellenberg, GD, Franke, A, Karlsen, TH, Veldink, JH, Ferrari, R, Yokoyama, JS, Miller, BL, Andreassen, OA, Dale, AM, Desikan, RS, Sugrue, LP, Hernandez, DG, Nalls, MA, Rohrer, JD, Ramasamy, A, Kwok, JBJ, Dobson-Stone, C, Brooks, WS, Schofield, PR, Halliday, GM, Hodges, JR, Piguet, O, Bartley, L, Thompson, E, Haan, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, NJ, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Landqvist Waldö, M, Nilsson, K, Nilsson, C, Mackenzie, IRA, Hsiung, GYR, Mann, DMA, Grafman, J, Morris, CM, Attems, J, Griffiths, TD, G McKeith, I, Thomas, AJ, Pietrini, P, Huey, ED, Wassermann, EM, Baborie, A, Jaros, E, Tierney, MC, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, St George-Hyslop, P, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, JB, Schlachetzki, JCM, and Uphill, J
Abstract: Background: Converging evidence suggests that immune-mediated dysfunction plays an important role in the pathogenesis of frontotemporal dementia (FTD). Although genetic studies have shown that immune-associated loci are associated with increased FTD risk, a systematic investigation of genetic overlap between immune-mediated diseases and the spectrum of FTD-related disorders has not been performed. Methods and findings: Using large genome-wide association studies (GWASs) (total n = 192,886 cases and controls) and recently developed tools to quantify genetic overlap/pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with FTD-related disorders—namely, FTD, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), and amyotrophic lateral sclerosis (ALS)—and 1 or more immune-mediated diseases including Crohn disease, ulcerative colitis (UC), rheumatoid arthritis (RA), type 1 diabetes (T1D), celiac disease (CeD), and psoriasis. We found up to 270-fold genetic enrichment between FTD and RA, up to 160-fold genetic enrichment between FTD and UC, up to 180-fold genetic enrichment between FTD and T1D, and up to 175-fold genetic enrichment between FTD and CeD. In contrast, for CBD and PSP, only 1 of the 6 immune-mediated diseases produced genetic enrichment comparable to that seen for FTD, with up to 150-fold genetic enrichment between CBD and CeD and up to 180-fold enrichment between PSP and RA. Further, we found minimal enrichment between ALS and the immune-mediated diseases tested, with the highest levels of enrichment between ALS and RA (up to 20-fold). For FTD, at a conjunction false discovery rate < 0.05 and after excluding SNPs in linkage disequilibrium, we found that 8 of the 15 identified loci mapped to the human leukocyte antigen (HLA) region on Chromosome (Chr) 6. We also found novel candidate FTD susceptibility loci within LRRK2 (leucine rich repeat kinase 2), TBKBP1 (TBK1 binding protein 1), and PGBD5 (pi
Published: 2018

10. CXCR4 involvement in neurodegenerative diseases

Author: Bonham, LW, Karch, CM, Fan, CC, Tan, C, Geier, EG, Wang, Y, Wen, N, Broce, IJ, Li, Y, Barkovich, MJ, Ferrari, R, Hardy, J, Momeni, P, Höglinger, G, Müller, U, Hess, CP, Sugrue, LP, Dillon, WP, Schellenberg, GD, Miller, BL, Andreassen, OA, Dale, AM, Barkovich, AJ, Yokoyama, JS, Desikan, RS, Hernandez, DG, Nalls, MA, Rohrer, JD, Ramasamy, A, Kwok, JBJ, Dobson-Stone, C, Schofield, PR, Halliday, GM, Hodges, JR, Piguet, O, Bartley, L, Thompson, E, Haan, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, NJ, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Waldö, ML, Nilsson, K, Nilsson, C, MacKenzie, IRA, Hsiung, GYR, Mann, DMA, Grafman, J, Morris, CM, Attems, J, Griffiths, TD, McKeith, IG, Thomas, AJ, Pietrini, P, Huey, ED, Wassermann, EM, Baborie, A, Jaros, E, Tierney, MC, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, George-Hyslop, PS, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, JB, Schlachetzki, JCM, Uphill, J, Collinge, J, Mead, S, Danek, A, Van Deerlin, VM, Grossman, M, Trojanowski, JQ, Bonham, LW, Karch, CM, Fan, CC, Tan, C, Geier, EG, Wang, Y, Wen, N, Broce, IJ, Li, Y, Barkovich, MJ, Ferrari, R, Hardy, J, Momeni, P, Höglinger, G, Müller, U, Hess, CP, Sugrue, LP, Dillon, WP, Schellenberg, GD, Miller, BL, Andreassen, OA, Dale, AM, Barkovich, AJ, Yokoyama, JS, Desikan, RS, Hernandez, DG, Nalls, MA, Rohrer, JD, Ramasamy, A, Kwok, JBJ, Dobson-Stone, C, Schofield, PR, Halliday, GM, Hodges, JR, Piguet, O, Bartley, L, Thompson, E, Haan, E, Hernández, I, Ruiz, A, Boada, M, Borroni, B, Padovani, A, Cruchaga, C, Cairns, NJ, Benussi, L, Binetti, G, Ghidoni, R, Forloni, G, Albani, D, Galimberti, D, Fenoglio, C, Serpente, M, Scarpini, E, Clarimón, J, Lleó, A, Blesa, R, Waldö, ML, Nilsson, K, Nilsson, C, MacKenzie, IRA, Hsiung, GYR, Mann, DMA, Grafman, J, Morris, CM, Attems, J, Griffiths, TD, McKeith, IG, Thomas, AJ, Pietrini, P, Huey, ED, Wassermann, EM, Baborie, A, Jaros, E, Tierney, MC, Pastor, P, Razquin, C, Ortega-Cubero, S, Alonso, E, Perneczky, R, Diehl-Schmid, J, Alexopoulos, P, Kurz, A, Rainero, I, Rubino, E, Pinessi, L, Rogaeva, E, George-Hyslop, PS, Rossi, G, Tagliavini, F, Giaccone, G, Rowe, JB, Schlachetzki, JCM, Uphill, J, Collinge, J, Mead, S, Danek, A, Van Deerlin, VM, Grossman, M, and Trojanowski, JQ
Abstract: Neurodegenerative diseases likely share common underlying pathobiology. Although prior work has identified susceptibility loci associated with various dementias, few, if any, studies have systematically evaluated shared genetic risk across several neurodegenerative diseases. Using genome-wide association data from large studies (total n = 82,337 cases and controls), we utilized a previously validated approach to identify genetic overlap and reveal common pathways between progressive supranuclear palsy (PSP), frontotemporal dementia (FTD), Parkinson's disease (PD) and Alzheimer's disease (AD). In addition to the MAPT H1 haplotype, we identified a variant near the chemokine receptor CXCR4 that was jointly associated with increased risk for PSP and PD. Using bioinformatics tools, we found strong physical interactions between CXCR4 and four microglia related genes, namely CXCL12, TLR2, RALB, and CCR5. Evaluating gene expression from post-mortem brain tissue, we found that expression of CXCR4 and microglial genes functionally related to CXCR4 was dysregulated across a number of neurodegenerative diseases. Furthermore, in a mouse model of tauopathy, expression of CXCR4 and functionally associated genes was significantly altered in regions of the mouse brain that accumulate neurofibrillary tangles most robustly. Beyond MAPT, we show dysregulation of CXCR4 expression in PSP, PD, and FTD brains, and mouse models of tau pathology. Our multi-modal findings suggest that abnormal signaling across a 'network' of microglial genes may contribute to neurodegeneration and may have potential implications for clinical trials targeting immune dysfunction in patients with neurodegenerative diseases.
Published: 2018

11. Rare Functional Variant in TM2D3 is Associated with Late-Onset Alzheimer's Disease

Author: Jakobsdottir, J, van der Lee, Sven, Bis, JC, Chouraki, V, Li-Kroeger, D, Yamamoto, S, Grove, ML, Naj, A, Vronskaya, M, Salazar, JL, DeStefano, AL, Brody, JA, Smith, AV, Amin, Najaf, Sims, R, Verbaas, Carla, Choi, SH, Satizabal, CL, Lopez, OL, Beiser, A, Ikram, Arfan, Garcia, ME, Hayward, C, Varga, TV, Ripatti, S, Franks, PW, Hallmans, G, Rolandsson, O, Jansson, JH, Porteous, DJ, Salomaa, V, Eiriksdottir, G, Rice, KM, Bellen, HJ, Levy, D, Uitterlinden, André, Emilsson, V, Rotter, JI, Aspelund, T, O'Donnell, CJ, Fitzpatrick, AL, Launer, LJ, Hofman, Bert, Wang, LS (Li-San), Williams, J, Schellenberg, GD, Boerwinkle, E, Psaty, BM, Seshadri, S, Shulman, JM, Gudnason, V, Duijn, Cornelia, Jakobsdottir, J, van der Lee, Sven, Bis, JC, Chouraki, V, Li-Kroeger, D, Yamamoto, S, Grove, ML, Naj, A, Vronskaya, M, Salazar, JL, DeStefano, AL, Brody, JA, Smith, AV, Amin, Najaf, Sims, R, Verbaas, Carla, Choi, SH, Satizabal, CL, Lopez, OL, Beiser, A, Ikram, Arfan, Garcia, ME, Hayward, C, Varga, TV, Ripatti, S, Franks, PW, Hallmans, G, Rolandsson, O, Jansson, JH, Porteous, DJ, Salomaa, V, Eiriksdottir, G, Rice, KM, Bellen, HJ, Levy, D, Uitterlinden, André, Emilsson, V, Rotter, JI, Aspelund, T, O'Donnell, CJ, Fitzpatrick, AL, Launer, LJ, Hofman, Bert, Wang, LS (Li-San), Williams, J, Schellenberg, GD, Boerwinkle, E, Psaty, BM, Seshadri, S, Shulman, JM, Gudnason, V, and Duijn, Cornelia
Abstract: We performed an exome-wide association analysis in 1393 late-onset Alzheimer's disease (LOAD) cases and 8141 controls from the CHARGE consortium. We found that a rare variant (P155L) in TM2D3 was enriched in Icelanders (similar to 0.5% versus < 0.05% in other European populations). In 433 LOAD cases and 3903 controls from the Icelandic AGES substudy, P155L was associated with increased risk and earlier onset of LOAD [odds ratio (95% CI) = 7.5 (3.5-15.9), p = 6.6x10(-9)]. Mutation in the Drosophila TM2D3 homolog, almondex, causes a phenotype similar to loss of Notch/Presenilin signaling. Human TM2D3 is capable of rescuing these phenotypes, but this activity is abolished by P155L, establishing it as a functionally damaging allele. Our results establish a rare TM2D3 variant in association with LOAD susceptibility, and together with prior work suggests possible links to the beta-amyloid cascade.
Published: 2016

12. Evidence for genetic linkage of autism to chromosomes 7 and 4

Author: Schellenberg, GD, Schellenberg, GD, Dawson, G, Sung, YJ, Estes, A, Munson, J, Rosenthal, E, Rothstein, J, Flodman, P, Smith, M, Coon, H, Leong, L, Yu, CE, Stodgell, C, Rodier, PM, Spence, MA, Minshew, N, McMahon, WM, Wijsman, EM, Schellenberg, GD, Schellenberg, GD, Dawson, G, Sung, YJ, Estes, A, Munson, J, Rosenthal, E, Rothstein, J, Flodman, P, Smith, M, Coon, H, Leong, L, Yu, CE, Stodgell, C, Rodier, PM, Spence, MA, Minshew, N, McMahon, WM, and Wijsman, EM
Published: 2006

13. Evidence for genetic linkage of autism to chromosomes 7 and 4

Author: Schellenberg, GD, Schellenberg, GD, Dawson, G, Sung, YJ, Estes, A, Munson, J, Rosenthal, E, Rothstein, J, Flodman, P, Smith, M, Coon, H, Leong, L, Yu, CE, Stodgell, C, Rodier, PM, Spence, MA, Minshew, N, McMahon, WM, Wijsman, EM, Schellenberg, GD, Schellenberg, GD, Dawson, G, Sung, YJ, Estes, A, Munson, J, Rosenthal, E, Rothstein, J, Flodman, P, Smith, M, Coon, H, Leong, L, Yu, CE, Stodgell, C, Rodier, PM, Spence, MA, Minshew, N, McMahon, WM, and Wijsman, EM
Published: 2006

14. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

Author: Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, C-H, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, DeStefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, ADNI, ADGC, GERAD, CHARGE and IPDGC Investigators, Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, C-H, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, DeStefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, and ADNI, ADGC, GERAD, CHARGE and IPDGC Investigators
Abstract: We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
Published: 2015

15. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus

Author: Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, CH, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, Destefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, Van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, CH, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, Destefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, Van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, and Dale, AM
Abstract: We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10 -7). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
Published: 2015

16. Genome-wide association study of corticobasal degeneration identifies risk variants shared with progressive supranuclear palsy

Author: Kouri, N, Ross, OA, Dombroski, B, Younkin, CS, Serie, DJ, Soto-Ortolaza, A, Baker, M, Finch, NCA, Yoon, H, Kim, J, Fujioka, S, McLean, CA, Ghetti, B, Spina, S, Cantwell, LB, Farlow, MR, Grafman, J, Huey, ED, Han, MR, Beecher, S, Geller, ET, Kretzschmar, HA, Roeber, S, Gearing, M, Juncos, JL, Vonsattel, JPG, Van Deerlin, VM, Grossman, M, Hurtig, HI, Gross, RG, Arnold, SE, Trojanowski, JQ, Lee, VM, Wenning, GK, White, CL, Hoeglinger, GU, Mueller, U, Devlin, B, Golbe, LI, Crook, J, Parisi, JE, Boeve, BF, Josephs, KA, Wszolek, ZK, Uitti, RJ, Graff-Radford, NR, Litvan, I, Younkin, SG, Wang, L-S, Ertekin-Taner, N, Rademakers, R, Hakonarsen, H, Schellenberg, GD, Dickson, DW, Kouri, N, Ross, OA, Dombroski, B, Younkin, CS, Serie, DJ, Soto-Ortolaza, A, Baker, M, Finch, NCA, Yoon, H, Kim, J, Fujioka, S, McLean, CA, Ghetti, B, Spina, S, Cantwell, LB, Farlow, MR, Grafman, J, Huey, ED, Han, MR, Beecher, S, Geller, ET, Kretzschmar, HA, Roeber, S, Gearing, M, Juncos, JL, Vonsattel, JPG, Van Deerlin, VM, Grossman, M, Hurtig, HI, Gross, RG, Arnold, SE, Trojanowski, JQ, Lee, VM, Wenning, GK, White, CL, Hoeglinger, GU, Mueller, U, Devlin, B, Golbe, LI, Crook, J, Parisi, JE, Boeve, BF, Josephs, KA, Wszolek, ZK, Uitti, RJ, Graff-Radford, NR, Litvan, I, Younkin, SG, Wang, L-S, Ertekin-Taner, N, Rademakers, R, Hakonarsen, H, Schellenberg, GD, and Dickson, DW
Abstract: Corticobasal degeneration (CBD) is a neurodegenerative disorder affecting movement and cognition, definitively diagnosed only at autopsy. Here, we conduct a genome-wide association study (GWAS) in CBD cases (n=152) and 3,311 controls, and 67 CBD cases and 439 controls in a replication stage. Associations with meta-analysis were 17q21 at MAPT (P=1.42 × 10(-12)), 8p12 at lnc-KIF13B-1, a long non-coding RNA (rs643472; P=3.41 × 10(-8)), and 2p22 at SOS1 (rs963731; P=1.76 × 10(-7)). Testing for association of CBD with top progressive supranuclear palsy (PSP) GWAS single-nucleotide polymorphisms (SNPs) identified associations at MOBP (3p22; rs1768208; P=2.07 × 10(-7)) and MAPT H1c (17q21; rs242557; P=7.91 × 10(-6)). We previously reported SNP/transcript level associations with rs8070723/MAPT, rs242557/MAPT, and rs1768208/MOBP and herein identified association with rs963731/SOS1. We identify new CBD susceptibility loci and show that CBD and PSP share a genetic risk factor other than MAPT at 3p22 MOBP (myelin-associated oligodendrocyte basic protein).
Published: 2015

17. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus

Author: Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, CH, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, Destefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, Van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, CH, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, Destefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, Van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, and Dale, AM
Abstract: We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10 -7). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
Published: 2015

18. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

Author: Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, C-H, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, DeStefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, ADNI, ADGC, GERAD, CHARGE and IPDGC Investigators, Desikan, RS, Desikan, RS, Schork, AJ, Wang, Y, Witoelar, A, Sharma, M, McEvoy, LK, Holland, D, Brewer, JB, Chen, C-H, Thompson, WK, Harold, D, Williams, J, Owen, MJ, O'Donovan, MC, Pericak-Vance, MA, Mayeux, R, Haines, JL, Farrer, LA, Schellenberg, GD, Heutink, P, Singleton, AB, Brice, A, Wood, NW, Hardy, J, Martinez, M, Choi, SH, DeStefano, A, Ikram, MA, Bis, JC, Smith, A, Fitzpatrick, AL, Launer, L, van Duijn, C, Seshadri, S, Ulstein, ID, Aarsland, D, Fladby, T, Djurovic, S, Hyman, BT, Snaedal, J, Stefansson, H, Stefansson, K, Gasser, T, Andreassen, OA, Dale, AM, and ADNI, ADGC, GERAD, CHARGE and IPDGC Investigators
Abstract: We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
Published: 2015

19. Synaptic, transcriptional and chromatin genes disrupted in autism.

Author: De Rubeis, S, He, X, Goldberg, AP, Poultney, CS, Samocha, K, Cicek, AE, Kou, Y, Liu, L, Fromer, M, Walker, S, Singh, T, Klei, L, Kosmicki, J, Shih-Chen, F, Aleksic, B, Biscaldi, M, Bolton, PF, Brownfeld, JM, Cai, J, Campbell, NG, Carracedo, A, Chahrour, MH, Chiocchetti, AG, Coon, H, Crawford, EL, Curran, SR, Dawson, G, Duketis, E, Fernandez, BA, Gallagher, L, Geller, E, Guter, SJ, Hill, RS, Ionita-Laza, J, Jimenz Gonzalez, P, Kilpinen, H, Klauck, SM, Kolevzon, A, Lee, I, Lei, I, Lei, J, Lehtimäki, T, Lin, C-F, Ma'ayan, A, Marshall, CR, McInnes, AL, Neale, B, Owen, MJ, Ozaki, N, Parellada, M, Parr, JR, Purcell, S, Puura, K, Rajagopalan, D, Rehnström, K, Reichenberg, A, Sabo, A, Sachse, M, Sanders, SJ, Schafer, C, Schulte-Rüther, M, Skuse, D, Stevens, C, Szatmari, P, Tammimies, K, Valladares, O, Voran, A, Li-San, W, Weiss, LA, Willsey, AJ, Yu, TW, Yuen, RKC, DDD Study, Homozygosity Mapping Collaborative for Autism, UK10K Consortium, Cook, EH, Freitag, CM, Gill, M, Hultman, CM, Lehner, T, Palotie, A, Schellenberg, GD, Sklar, P, State, MW, Sutcliffe, JS, Walsh, CA, Scherer, SW, Zwick, ME, Barett, JC, Cutler, DJ, Roeder, K, Devlin, B, Daly, MJ, Buxbaum, JD, De Rubeis, S, He, X, Goldberg, AP, Poultney, CS, Samocha, K, Cicek, AE, Kou, Y, Liu, L, Fromer, M, Walker, S, Singh, T, Klei, L, Kosmicki, J, Shih-Chen, F, Aleksic, B, Biscaldi, M, Bolton, PF, Brownfeld, JM, Cai, J, Campbell, NG, Carracedo, A, Chahrour, MH, Chiocchetti, AG, Coon, H, Crawford, EL, Curran, SR, Dawson, G, Duketis, E, Fernandez, BA, Gallagher, L, Geller, E, Guter, SJ, Hill, RS, Ionita-Laza, J, Jimenz Gonzalez, P, Kilpinen, H, Klauck, SM, Kolevzon, A, Lee, I, Lei, I, Lei, J, Lehtimäki, T, Lin, C-F, Ma'ayan, A, Marshall, CR, McInnes, AL, Neale, B, Owen, MJ, Ozaki, N, Parellada, M, Parr, JR, Purcell, S, Puura, K, Rajagopalan, D, Rehnström, K, Reichenberg, A, Sabo, A, Sachse, M, Sanders, SJ, Schafer, C, Schulte-Rüther, M, Skuse, D, Stevens, C, Szatmari, P, Tammimies, K, Valladares, O, Voran, A, Li-San, W, Weiss, LA, Willsey, AJ, Yu, TW, Yuen, RKC, DDD Study, Homozygosity Mapping Collaborative for Autism, UK10K Consortium, Cook, EH, Freitag, CM, Gill, M, Hultman, CM, Lehner, T, Palotie, A, Schellenberg, GD, Sklar, P, State, MW, Sutcliffe, JS, Walsh, CA, Scherer, SW, Zwick, ME, Barett, JC, Cutler, DJ, Roeder, K, Devlin, B, Daly, MJ, and Buxbaum, JD
Abstract: The genetic architecture of autism spectrum disorder involves the interplay of common and rare variants and their impact on hundreds of genes. Using exome sequencing, here we show that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, plus a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic formation, transcriptional regulation and chromatin-remodelling pathways. These include voltage-gated ion channels regulating the propagation of action potentials, pacemaking and excitability-transcription coupling, as well as histone-modifying enzymes and chromatin remodellers-most prominently those that mediate post-translational lysine methylation/demethylation modifications of histones.
Published: 2014

20. Genome-Wide Association Meta-analysis of Neuropathologic Features of Alzheimer's Disease and Related Dementias

Author: Beecham, GW, Hamilton, K, Naj, AC, Martin, ER, Huentelman, M, Myers, AJ, Corneveaux, JJ, Hardy, J, Vonsattel, JP, Younkin, SG, Bennett, DA, De Jager, PL, Larson, EB, Crane, PK, Kamboh, MI, Kofler, JK, Mash, DC, Duque, L, Gilbert, JR, Gwirtsman, H, Buxbaum, JD, Kramer, P, Dickson, DW, Farrer, LA, Frosch, MP, Ghetti, B, Haines, JL, Hyman, BT, Kukull, WA, Mayeux, RP, Pericak-Vance, MA, Schneider, JA, Trojanowski, JQ, Reiman, EM, Schellenberg, GD, Montine, TJ, Beecham, GW, Hamilton, K, Naj, AC, Martin, ER, Huentelman, M, Myers, AJ, Corneveaux, JJ, Hardy, J, Vonsattel, JP, Younkin, SG, Bennett, DA, De Jager, PL, Larson, EB, Crane, PK, Kamboh, MI, Kofler, JK, Mash, DC, Duque, L, Gilbert, JR, Gwirtsman, H, Buxbaum, JD, Kramer, P, Dickson, DW, Farrer, LA, Frosch, MP, Ghetti, B, Haines, JL, Hyman, BT, Kukull, WA, Mayeux, RP, Pericak-Vance, MA, Schneider, JA, Trojanowski, JQ, Reiman, EM, Schellenberg, GD, and Montine, TJ
Abstract: Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.
Published: 2014

21. Genome-Wide Association Meta-analysis of Neuropathologic Features of Alzheimer's Disease and Related Dementias

Author: Beecham, GW, Hamilton, K, Naj, AC, Martin, ER, Huentelman, M, Myers, AJ, Corneveaux, JJ, Hardy, J, Vonsattel, JP, Younkin, SG, Bennett, DA, De Jager, PL, Larson, EB, Crane, PK, Kamboh, MI, Kofler, JK, Mash, DC, Duque, L, Gilbert, JR, Gwirtsman, H, Buxbaum, JD, Kramer, P, Dickson, DW, Farrer, LA, Frosch, MP, Ghetti, B, Haines, JL, Hyman, BT, Kukull, WA, Mayeux, RP, Pericak-Vance, MA, Schneider, JA, Trojanowski, JQ, Reiman, EM, Schellenberg, GD, Montine, TJ, Beecham, GW, Hamilton, K, Naj, AC, Martin, ER, Huentelman, M, Myers, AJ, Corneveaux, JJ, Hardy, J, Vonsattel, JP, Younkin, SG, Bennett, DA, De Jager, PL, Larson, EB, Crane, PK, Kamboh, MI, Kofler, JK, Mash, DC, Duque, L, Gilbert, JR, Gwirtsman, H, Buxbaum, JD, Kramer, P, Dickson, DW, Farrer, LA, Frosch, MP, Ghetti, B, Haines, JL, Hyman, BT, Kukull, WA, Mayeux, RP, Pericak-Vance, MA, Schneider, JA, Trojanowski, JQ, Reiman, EM, Schellenberg, GD, and Montine, TJ
Abstract: Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.
Published: 2014

22. Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene

Author: Ruiz, A, Heilmann, S, Becker, T, Hernandez, I, Wagner, H, Thelen, M, Mauleon, A, Rosende-Roca, M, Bellenguez, C, Bis, JC, Harold, D, Gerrish, A, Sims, R, Sotolongo-Grau, O, Espinosa, A, Alegret, M, Arrieta, JL, Lacour, A, Leber, M, Becker, J, Lafuente, A, Ruiz, S, Vargas, L, Rodriguez, O, Ortega, G, Dominguez, MA, Mayeux, R, Haines, JL, Pericak-Vance, MA, Farrer, LA, Schellenberg, GD, Chouraki, V, Launer, LJ (Lenore), Duijn, Cornelia, Seshadri, S, Antunez, C, Breteler, Monique, Serrano-Rios, M, Jessen, F, Tarraga, L, Nothen, MM, Maier, W, Boada, M, Ramirez, A, Ruiz, A, Heilmann, S, Becker, T, Hernandez, I, Wagner, H, Thelen, M, Mauleon, A, Rosende-Roca, M, Bellenguez, C, Bis, JC, Harold, D, Gerrish, A, Sims, R, Sotolongo-Grau, O, Espinosa, A, Alegret, M, Arrieta, JL, Lacour, A, Leber, M, Becker, J, Lafuente, A, Ruiz, S, Vargas, L, Rodriguez, O, Ortega, G, Dominguez, MA, Mayeux, R, Haines, JL, Pericak-Vance, MA, Farrer, LA, Schellenberg, GD, Chouraki, V, Launer, LJ (Lenore), Duijn, Cornelia, Seshadri, S, Antunez, C, Breteler, Monique, Serrano-Rios, M, Jessen, F, Tarraga, L, Nothen, MM, Maier, W, Boada, M, and Ramirez, A
Abstract: To follow-up loci discovered by the International Genomics of Alzheimer's Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (Fundacio ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P = 0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer's disease risk (odds ratio = 1.31; confidence interval 95% (1.19-1.44); P = 9.74 x 10(-9)).
Published: 2014

23. Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease

Author: Escott-Price, V, Bellenguez, C, Wang, LS (Li-San), Choi, SH, Harold, D, Jones, L, Holmans, P, Gerrish, A, Vedernikov, A, Richards, A, DeStefano, AL, Lambert, JC, Verbaas, Carla, Naj, AC, Sims, R, Jun, G, Bis, JC, Beecham, GW, Grenier-Boley, B, Russo, G, Thornton-Wells, TA, Denning, N, Smith, AV, Chouraki, V, Thomas, C, Ikram, Arfan, Zelenika, D, Vardarajan, BN, Kamatani, Y, Lin, CF, Schmidt, Heléna, Kunkle, B, Dunstan, ML, Vronskaya, M, Johnson, AD, Ruiz, A, Bihoreau, MT, Reitz, C, Pasquier, F, Hollingworth, P, Hanon, O, Fitzpatrick, AL, Buxbaum, JD, Campion, D, Crane, PK, Baldwin, C, Becker, T, Gudnason, V, Cruchaga, C, Craig, D, Amin, Najaf, Berr, C, Lopez, OL, De Jager, PL, Deramecourt, V, Johnston, JA, Evans, D, Lovestone, S, Letenneur, L, Hernandez, I, Rubinsztein, DC, Eiriksdottir, G, Sleegers, K (Kristel), Goate, AM, Fievet, N, Huentelman, MJ, Gill, M, Brown, K, Kamboh, MI, Keller, L, Barberger-Gateau, P, McGuinness, B, Larson, EB, Myers, AJ, Dufouil, C, Todd, S, Wallon, D, Love, S, Rogaeva, E, Gallacher, J, St George-Hyslop, P, Clarimon, J, Lleo, A, Bayer, A, Tsuang, DW, Yu, L, Tsolaki, M, Bossu, P, Spalletta, G, Proitsi, P, Collinge, J, Sorbi, S, Garcia, FS, Fox, NC, Hardy, J, Naranjo, MCD, Bosco, P, Clarke, R, Brayne, C, Galimberti, D, Scarpini, E, Bonuccelli, U, Mancuso, M, Siciliano, G, Moebus, S, Mecocci, P, Del Zompo, M, Maier, W, Hampel, H, Pilotto, A, Frank-Garcia, A, Panza, F, Solfrizzi, V, Caffarra, P, Nacmias, B, Perry, W, Mayhaus, M, Lannfelt, L, Hakonarson, H, Pichler, S, Carrasquillo, MM, Ingelsson, M, Beekly, D, Alvarez, V, Zou, FG, Valladares, O, Younkin, SG, Coto, E, Hamilton-Nelson, KL, Gu, W, Razquin, C, Pastor, P, Mateo, I, Owen, MJ, Faber, KM, Jonsson, PV, Combarros, O, O'Donovan, MC, Cantwell, LB, Soininen, H, Blacker, D, Mead, S, Mosley, TH, Bennett, DA, Harris, TB, Fratiglioni, L, Holmes, C, Bruijn, Renee, Passmore, P, Montine, TJ, Bettens, K, Rotter, JI, Brice, A, Morgan, K, Foroud, TM, Kukull, WA, Hannequin, D, Powell, JF, Nalls, MA, Ritchie, K, Lunetta, KL, Kauwe, JSK, Boerwinkle, E, Riemenschneider, M, Boada, M, Hiltunen, M, Martin, ER, Schmidt, R, Rujescu, D, Dartigues, JF, Mayeux, R, Tzourio, C, Hofman, Bert, Nothen, MM, Graff, C, Psaty, BM, Haines, JL, Lathrop, M, Pericak-Vance, MA, Launer, LJ (Lenore), van Broeckhoven, C, Farrer, LA, Duijn, Cornelia, Ramirez, A, Seshadri, S, Schellenberg, GD, Amouyel, P, Williams, J, Escott-Price, V, Bellenguez, C, Wang, LS (Li-San), Choi, SH, Harold, D, Jones, L, Holmans, P, Gerrish, A, Vedernikov, A, Richards, A, DeStefano, AL, Lambert, JC, Verbaas, Carla, Naj, AC, Sims, R, Jun, G, Bis, JC, Beecham, GW, Grenier-Boley, B, Russo, G, Thornton-Wells, TA, Denning, N, Smith, AV, Chouraki, V, Thomas, C, Ikram, Arfan, Zelenika, D, Vardarajan, BN, Kamatani, Y, Lin, CF, Schmidt, Heléna, Kunkle, B, Dunstan, ML, Vronskaya, M, Johnson, AD, Ruiz, A, Bihoreau, MT, Reitz, C, Pasquier, F, Hollingworth, P, Hanon, O, Fitzpatrick, AL, Buxbaum, JD, Campion, D, Crane, PK, Baldwin, C, Becker, T, Gudnason, V, Cruchaga, C, Craig, D, Amin, Najaf, Berr, C, Lopez, OL, De Jager, PL, Deramecourt, V, Johnston, JA, Evans, D, Lovestone, S, Letenneur, L, Hernandez, I, Rubinsztein, DC, Eiriksdottir, G, Sleegers, K (Kristel), Goate, AM, Fievet, N, Huentelman, MJ, Gill, M, Brown, K, Kamboh, MI, Keller, L, Barberger-Gateau, P, McGuinness, B, Larson, EB, Myers, AJ, Dufouil, C, Todd, S, Wallon, D, Love, S, Rogaeva, E, Gallacher, J, St George-Hyslop, P, Clarimon, J, Lleo, A, Bayer, A, Tsuang, DW, Yu, L, Tsolaki, M, Bossu, P, Spalletta, G, Proitsi, P, Collinge, J, Sorbi, S, Garcia, FS, Fox, NC, Hardy, J, Naranjo, MCD, Bosco, P, Clarke, R, Brayne, C, Galimberti, D, Scarpini, E, Bonuccelli, U, Mancuso, M, Siciliano, G, Moebus, S, Mecocci, P, Del Zompo, M, Maier, W, Hampel, H, Pilotto, A, Frank-Garcia, A, Panza, F, Solfrizzi, V, Caffarra, P, Nacmias, B, Perry, W, Mayhaus, M, Lannfelt, L, Hakonarson, H, Pichler, S, Carrasquillo, MM, Ingelsson, M, Beekly, D, Alvarez, V, Zou, FG, Valladares, O, Younkin, SG, Coto, E, Hamilton-Nelson, KL, Gu, W, Razquin, C, Pastor, P, Mateo, I, Owen, MJ, Faber, KM, Jonsson, PV, Combarros, O, O'Donovan, MC, Cantwell, LB, Soininen, H, Blacker, D, Mead, S, Mosley, TH, Bennett, DA, Harris, TB, Fratiglioni, L, Holmes, C, Bruijn, Renee, Passmore, P, Montine, TJ, Bettens, K, Rotter, JI, Brice, A, Morgan, K, Foroud, TM, Kukull, WA, Hannequin, D, Powell, JF, Nalls, MA, Ritchie, K, Lunetta, KL, Kauwe, JSK, Boerwinkle, E, Riemenschneider, M, Boada, M, Hiltunen, M, Martin, ER, Schmidt, R, Rujescu, D, Dartigues, JF, Mayeux, R, Tzourio, C, Hofman, Bert, Nothen, MM, Graff, C, Psaty, BM, Haines, JL, Lathrop, M, Pericak-Vance, MA, Launer, LJ (Lenore), van Broeckhoven, C, Farrer, LA, Duijn, Cornelia, Ramirez, A, Seshadri, S, Schellenberg, GD, Amouyel, P, and Williams, J
Abstract: Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4x10(-6)) and 14 (IGHV1-67 p = 7.9x10(-8)) which indexed novel susceptibility loci. Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Published: 2014

24. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

Author: State, Matthew, State, Matthew, Sanders, Stephan, He, X, Sanders, SJ, Liu, L, De, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, Matthew, State, Matthew, Sanders, Stephan, He, X, Sanders, SJ, Liu, L, De, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, and Buxbaum, JD
Abstract: De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based
Published: 2013

25. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

Author: State, Matthew, State, Matthew, Sanders, Stephan, He, X, Sanders, SJ, Liu, L, De, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, Matthew, State, Matthew, Sanders, Stephan, He, X, Sanders, SJ, Liu, L, De, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, and Buxbaum, JD
Abstract: De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based
Published: 2013

26. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

Author: He, X, Sanders, SJ, Liu, L, De Rubeis, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, MW, Devlin, B, Roeder, K, He, X, Sanders, SJ, Liu, L, De Rubeis, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, MW, Devlin, B, and Roeder, K
Abstract: De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support. © 2013 He et al.
Published: 2013

27. Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

Author: Liu, L, Sabo, A, Neale, BM, Nagaswamy, U, Stevens, C, Lim, E, Bodea, CA, Muzny, D, Reid, JG, Banks, E, Coon, H, DePristo, M, Dinh, H, Fennel, T, Flannick, J, Gabriel, S, Garimella, K, Gross, S, Hawes, A, Lewis, L, Makarov, V, Maguire, J, Newsham, I, Poplin, R, Ripke, S, Shakir, K, Samocha, KE, Wu, Y, Boerwinkle, E, Buxbaum, JD, Cook, EH, Devlin, B, Schellenberg, GD, Sutcliffe, JS, Daly, MJ, Gibbs, RA, Roeder, K, Liu, L, Sabo, A, Neale, BM, Nagaswamy, U, Stevens, C, Lim, E, Bodea, CA, Muzny, D, Reid, JG, Banks, E, Coon, H, DePristo, M, Dinh, H, Fennel, T, Flannick, J, Gabriel, S, Garimella, K, Gross, S, Hawes, A, Lewis, L, Makarov, V, Maguire, J, Newsham, I, Poplin, R, Ripke, S, Shakir, K, Samocha, KE, Wu, Y, Boerwinkle, E, Buxbaum, JD, Cook, EH, Devlin, B, Schellenberg, GD, Sutcliffe, JS, Daly, MJ, Gibbs, RA, and Roeder, K
Abstract: We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al.
Published: 2013

28. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

Author: He, X, Sanders, SJ, Liu, L, De Rubeis, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, MW, Devlin, B, Roeder, K, He, X, Sanders, SJ, Liu, L, De Rubeis, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, Buxbaum, JD, State, MW, Devlin, B, and Roeder, K
Abstract: De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support. © 2013 He et al.
Published: 2013

29. Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

Author: Liu, L, Sabo, A, Neale, BM, Nagaswamy, U, Stevens, C, Lim, E, Bodea, CA, Muzny, D, Reid, JG, Banks, E, Coon, H, DePristo, M, Dinh, H, Fennel, T, Flannick, J, Gabriel, S, Garimella, K, Gross, S, Hawes, A, Lewis, L, Makarov, V, Maguire, J, Newsham, I, Poplin, R, Ripke, S, Shakir, K, Samocha, KE, Wu, Y, Boerwinkle, E, Buxbaum, JD, Cook, EH, Devlin, B, Schellenberg, GD, Sutcliffe, JS, Daly, MJ, Gibbs, RA, Roeder, K, Liu, L, Sabo, A, Neale, BM, Nagaswamy, U, Stevens, C, Lim, E, Bodea, CA, Muzny, D, Reid, JG, Banks, E, Coon, H, DePristo, M, Dinh, H, Fennel, T, Flannick, J, Gabriel, S, Garimella, K, Gross, S, Hawes, A, Lewis, L, Makarov, V, Maguire, J, Newsham, I, Poplin, R, Ripke, S, Shakir, K, Samocha, KE, Wu, Y, Boerwinkle, E, Buxbaum, JD, Cook, EH, Devlin, B, Schellenberg, GD, Sutcliffe, JS, Daly, MJ, Gibbs, RA, and Roeder, K
Abstract: We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al.
Published: 2013

30. Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study

Author: Majounie, E, Renton, AE, Mok, K, Dopper, Elise, Waite, A, Rollinson, S, Chio, A, Restagno, G, Nicolaou, N, Simon-Sanchez, J, van Swieten, J.C., Abramzon, Y, Johnson, JO, Sendtner, M, Pamphlett, R, Orrell, RW, Mead, S, Sidle, KC, Houlden, H, Rohrer, JD, Morrison, KE, Pall, H, Talbot, K, Ansorge, O, Hernandez, DG, Arepalli, S, Sabatelli, M, Mora, G, Corbo, M, Giannini, F, Calvo, A, Englund, E, Borghero, G, Foris, GL, Remes, AM, Laaksovirta, H, McCluskey, L, Trojanowski, JQ, Van Deerlin, VM, Schellenberg, GD, Nalls, MA, Drory, VE, Lu, CS, Yeh, TH, Ishiura, H, Takahashi, Y, Tsuji, S, Le Ber, I, Brice, A, Drepper, C, Williams, N, Kirby, J, Shaw, P, Hardy, J, Tienari, PJ, Heutink, P, Morris, HR, Pickering-Brown, S, Traynor, BJ, Majounie, E, Renton, AE, Mok, K, Dopper, Elise, Waite, A, Rollinson, S, Chio, A, Restagno, G, Nicolaou, N, Simon-Sanchez, J, van Swieten, J.C., Abramzon, Y, Johnson, JO, Sendtner, M, Pamphlett, R, Orrell, RW, Mead, S, Sidle, KC, Houlden, H, Rohrer, JD, Morrison, KE, Pall, H, Talbot, K, Ansorge, O, Hernandez, DG, Arepalli, S, Sabatelli, M, Mora, G, Corbo, M, Giannini, F, Calvo, A, Englund, E, Borghero, G, Foris, GL, Remes, AM, Laaksovirta, H, McCluskey, L, Trojanowski, JQ, Van Deerlin, VM, Schellenberg, GD, Nalls, MA, Drory, VE, Lu, CS, Yeh, TH, Ishiura, H, Takahashi, Y, Tsuji, S, Le Ber, I, Brice, A, Drepper, C, Williams, N, Kirby, J, Shaw, P, Hardy, J, Tienari, PJ, Heutink, P, Morris, HR, Pickering-Brown, S, and Traynor, BJ
Abstract: Background We aimed to accurately estimate the frequency of a hexanucleotide repeat expansion in C9orf72 that has been associated with a large proportion of cases of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Methods We screened 4448 patients diagnosed with ALS (El Escorial criteria) and 1425 patients with FTD (Lund-Manchester criteria) from 17 regions worldwide for the GGGGCC hexanucleotide expansion using a repeat-primed PCR assay. We assessed familial disease status on the basis of self-reported family history of similar neurodegenerative diseases at the time of sample collection. We compared haplotype data for 262 patients carrying the expansion with the known Finnish founder risk haplotype across the chromosomal locus. We calculated age-related penetrance using the Kaplan-Meier method with data for 603 individuals with the expansion. Findings In patients with sporadic ALS, we identified the repeat expansion in 236 (7.0%) of 3377 white individuals from the USA, Europe, and Australia, two (4.1%) of 49 black individuals from the USA, and six (8.3%) of 72 Hispanic individuals from the USA. The mutation was present in 217 (39.3%) of 552 white individuals with familial MS from Europe and the USA. 59 (6.0%) of 981 white Europeans with sporadic FTD had the mutation, as did 99 (24.8%) of 400 white Europeans with familial FTD. Data for other ethnic groups were sparse, but we identified one Asian patient with familial ALS (from 20 assessed) and two with familial FTD (from three assessed) who carried the mutation. The mutation was not carried by the three Native Americans or 360 patients from Asia or the Pacific Islands with sporadic MS who were tested, or by 41 Asian patients with sporadic FTD. All patients with the repeat expansion had (partly or fully) the founder haplotype, suggesting a one-off expansion occurring about 1500 years ago. The pathogenic expansion was non-penetrant in individuals younger than 35 years, 50% penetrant by 58 years
Published: 2012

31. Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study

Author: Majounie, E, Renton, Ae, Mok, K, Dopper, Egp, Waite, A, Rollinson, S, Chiò, A, Restagno, G, Nicolaou, N, Simon Sanchez, J, Van Swieten, Jc, Abramzon, Y, Johnson, Jo, Sendtner, M, Pamphlett, R, Orrell, Rw, Mead, S, Sidle, Kc, Houlden, H, Rohrer, Jd, Morrison, Ke, Pall, H, Talbot, K, Ansorge, O, Hernandez, Dg, Arepalli, S, Sabatelli, Mario, Mora, G, Corbo, Massimo, Giannini, F, Calvo, A, Englund, E, Borghero, G, Floris, Gl, Remes, Am, Laaksovirta, H, Mccluskey, L, Trojanowski, Jq, Van Deerlin, Vm, Schellenberg, Gd, Nalls, Ma, Drory, Ve, Lu, C, Yeh, T, Ishiura, H, Takahashi, Y, Tsuji, S, Le Ber, I, Brice, A, Drepper, C, Williams, N, Kirby, J, Shaw, P, Hardy, J, Tienari, Pj, Heutink, P, Morris, Hr, Pickering Brown, S, Traynor, Bj, Sabatelli, Mario (ORCID:0000-0001-6635-4985), Majounie, E, Renton, Ae, Mok, K, Dopper, Egp, Waite, A, Rollinson, S, Chiò, A, Restagno, G, Nicolaou, N, Simon Sanchez, J, Van Swieten, Jc, Abramzon, Y, Johnson, Jo, Sendtner, M, Pamphlett, R, Orrell, Rw, Mead, S, Sidle, Kc, Houlden, H, Rohrer, Jd, Morrison, Ke, Pall, H, Talbot, K, Ansorge, O, Hernandez, Dg, Arepalli, S, Sabatelli, Mario, Mora, G, Corbo, Massimo, Giannini, F, Calvo, A, Englund, E, Borghero, G, Floris, Gl, Remes, Am, Laaksovirta, H, Mccluskey, L, Trojanowski, Jq, Van Deerlin, Vm, Schellenberg, Gd, Nalls, Ma, Drory, Ve, Lu, C, Yeh, T, Ishiura, H, Takahashi, Y, Tsuji, S, Le Ber, I, Brice, A, Drepper, C, Williams, N, Kirby, J, Shaw, P, Hardy, J, Tienari, Pj, Heutink, P, Morris, Hr, Pickering Brown, S, Traynor, Bj, and Sabatelli, Mario (ORCID:0000-0001-6635-4985)
Abstract: We aimed to accurately estimate the frequency of a hexanucleotide repeat expansion in C9orf72 that has been associated with a large proportion of cases of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD).
Published: 2012

32. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes

Author: Bucan, M, Abrahams, BS, Wang, K, Glessner, JT, Herman, EI, Sonnenblick, LI, Alvarez Retuerto, AI, Imielinski, M, Hadley, D, Bradfield, JP, Kim, C, Gidaya, NB, Lindquist, I, Hutman, T, Sigman, M, Kustanovich, V, Lajonchere, CM, Singleton, A, Kim, J, Wassink, TH, McMahon, WM, Owley, T, Sweeney, JA, Coon, H, Nurnberger, JI, Li, M, Cantor, RM, Minshew, NJ, Sutcliffe, JS, Cook, EH, Dawson, G, Buxbaum, JD, Grant, SFA, Schellenberg, GD, Geschwind, DH, Hakonarson, H, Bucan, M, Abrahams, BS, Wang, K, Glessner, JT, Herman, EI, Sonnenblick, LI, Alvarez Retuerto, AI, Imielinski, M, Hadley, D, Bradfield, JP, Kim, C, Gidaya, NB, Lindquist, I, Hutman, T, Sigman, M, Kustanovich, V, Lajonchere, CM, Singleton, A, Kim, J, Wassink, TH, McMahon, WM, Owley, T, Sweeney, JA, Coon, H, Nurnberger, JI, Li, M, Cantor, RM, Minshew, NJ, Sutcliffe, JS, Cook, EH, Dawson, G, Buxbaum, JD, Grant, SFA, Schellenberg, GD, Geschwind, DH, and Hakonarson, H
Abstract: The genetics underlying the autism spectrum disorders (ASDs) is complex and remains poorly understood. Previous work has demonstrated an important role for structural variation in a subset of cases, but has lacked the resolution necessary to move beyond detection of large regions of potential interest to identification of individual genes. To pinpoint genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. Through prioritization of exonic deletions (eDels), exonic duplications (eDups), and whole gene duplication events (gDups), we identified more than 150 loci harboring rare variants in multiple unrelated probands, but no controls. Importantly, 27 of these were confirmed on examination of an independent replication cohort comprised of 859 cases and an additional 1,051 controls. Rare variants at known loci, including exonic deletions at NRXN1 and whole gene duplications encompassing UBE3A and several other genes in the 15q11-q13 region, were observed in the course of these analyses. Strong support was likewise observed for previously unreported genes such as BZRAP1, an adaptor molecule known to regulate synaptic transmission, with eDels or eDups observed in twelve unrelated cases but no controls (p = 2.3×10-5). Less is known about MDGA2, likewise observed to be case-specific (p = 1.3×10-4). But, it is notable that the encoded protein shows an unexpectedly high similarity to Contactin 4 (BLAST E-value = 3×10-39), which has also been linked to disease. That hundreds of distinct rare variants were each seen only once further highlights complexity in the ASDs and points to the continued need for larger cohorts.
Published: 2009

33. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes

Author: Bucan, M, Abrahams, BS, Wang, K, Glessner, JT, Herman, EI, Sonnenblick, LI, Alvarez Retuerto, AI, Imielinski, M, Hadley, D, Bradfield, JP, Kim, C, Gidaya, NB, Lindquist, I, Hutman, T, Sigman, M, Kustanovich, V, Lajonchere, CM, Singleton, A, Kim, J, Wassink, TH, McMahon, WM, Owley, T, Sweeney, JA, Coon, H, Nurnberger, JI, Li, M, Cantor, RM, Minshew, NJ, Sutcliffe, JS, Cook, EH, Dawson, G, Buxbaum, JD, Grant, SFA, Schellenberg, GD, Geschwind, DH, Hakonarson, H, Bucan, M, Abrahams, BS, Wang, K, Glessner, JT, Herman, EI, Sonnenblick, LI, Alvarez Retuerto, AI, Imielinski, M, Hadley, D, Bradfield, JP, Kim, C, Gidaya, NB, Lindquist, I, Hutman, T, Sigman, M, Kustanovich, V, Lajonchere, CM, Singleton, A, Kim, J, Wassink, TH, McMahon, WM, Owley, T, Sweeney, JA, Coon, H, Nurnberger, JI, Li, M, Cantor, RM, Minshew, NJ, Sutcliffe, JS, Cook, EH, Dawson, G, Buxbaum, JD, Grant, SFA, Schellenberg, GD, Geschwind, DH, and Hakonarson, H
Abstract: The genetics underlying the autism spectrum disorders (ASDs) is complex and remains poorly understood. Previous work has demonstrated an important role for structural variation in a subset of cases, but has lacked the resolution necessary to move beyond detection of large regions of potential interest to identification of individual genes. To pinpoint genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. Through prioritization of exonic deletions (eDels), exonic duplications (eDups), and whole gene duplication events (gDups), we identified more than 150 loci harboring rare variants in multiple unrelated probands, but no controls. Importantly, 27 of these were confirmed on examination of an independent replication cohort comprised of 859 cases and an additional 1,051 controls. Rare variants at known loci, including exonic deletions at NRXN1 and whole gene duplications encompassing UBE3A and several other genes in the 15q11-q13 region, were observed in the course of these analyses. Strong support was likewise observed for previously unreported genes such as BZRAP1, an adaptor molecule known to regulate synaptic transmission, with eDels or eDups observed in twelve unrelated cases but no controls (p = 2.3×10-5). Less is known about MDGA2, likewise observed to be case-specific (p = 1.3×10-4). But, it is notable that the encoded protein shows an unexpectedly high similarity to Contactin 4 (BLAST E-value = 3×10-39), which has also been linked to disease. That hundreds of distinct rare variants were each seen only once further highlights complexity in the ASDs and points to the continued need for larger cohorts.
Published: 2009

34. Autism and the serotonin transporter: the long and short of it.

Author: Devlin, B, Devlin, B, Cook, EH, Coon, H, Dawson, G, Grigorenko, EL, McMahon, W, Minshew, N, Pauls, D, Smith, M, Spence, MA, Rodier, PM, Stodgell, C, Schellenberg, GD, CPEA Genetics Network, Devlin, B, Devlin, B, Cook, EH, Coon, H, Dawson, G, Grigorenko, EL, McMahon, W, Minshew, N, Pauls, D, Smith, M, Spence, MA, Rodier, PM, Stodgell, C, Schellenberg, GD, and CPEA Genetics Network
Abstract: Autism is a neurodevelopmental disorder manifesting early in childhood. Some symptoms of autism are alleviated by treatment with selective serotonin reuptake inhibitors, which are known to interact with the serotonin transporter. Moreover, variation in the gene that encodes the transporter (SLC6A4), especially the HTTLPR locus, is known to modulate its expression. It is natural, therefore, to evaluate whether this variation plays a role in liability to autism. We investigated the impact of alleles at HTTLPR and three other loci in SLC6A4 by using a large, independent family-based sample (390 families, 1528 individuals) from the NIH Collaborative Programs of Excellence in Autism (CPEA) network. Allele transmissions to individuals diagnosed with autism were biased only for HTTLPR, both for the narrow diagnosis of autism (P=0.035) and for the broader diagnosis of autism spectrum (P=0.007). The short allele of HTTLPR was significantly overtransmitted. Investigation of haplotype transmissions suggested that, in our data, biased transmission was only due to HTTLPR. With respect to this locus, there are now seven of 12 studies reporting significant transmission bias of HTTLPR alleles, a noteworthy result in itself. However, the studies with significant findings are almost equally divided between overtransmission of short and overtransmission of long alleles. We place our results within this extremely heterogeneous field of studies. Determining the factors influencing the relationship between autism phenotypes and HTTLPR variation, as well as other loci in SLC6A4, could be an important advance in our understanding of this complex disorder.
Published: 2005

35. Autism and the serotonin transporter: the long and short of it.

Author: Devlin, B, Devlin, B, Cook, EH, Coon, H, Dawson, G, Grigorenko, EL, McMahon, W, Minshew, N, Pauls, D, Smith, M, Spence, MA, Rodier, PM, Stodgell, C, Schellenberg, GD, CPEA Genetics Network, Devlin, B, Devlin, B, Cook, EH, Coon, H, Dawson, G, Grigorenko, EL, McMahon, W, Minshew, N, Pauls, D, Smith, M, Spence, MA, Rodier, PM, Stodgell, C, Schellenberg, GD, and CPEA Genetics Network
Abstract: Autism is a neurodevelopmental disorder manifesting early in childhood. Some symptoms of autism are alleviated by treatment with selective serotonin reuptake inhibitors, which are known to interact with the serotonin transporter. Moreover, variation in the gene that encodes the transporter (SLC6A4), especially the HTTLPR locus, is known to modulate its expression. It is natural, therefore, to evaluate whether this variation plays a role in liability to autism. We investigated the impact of alleles at HTTLPR and three other loci in SLC6A4 by using a large, independent family-based sample (390 families, 1528 individuals) from the NIH Collaborative Programs of Excellence in Autism (CPEA) network. Allele transmissions to individuals diagnosed with autism were biased only for HTTLPR, both for the narrow diagnosis of autism (P=0.035) and for the broader diagnosis of autism spectrum (P=0.007). The short allele of HTTLPR was significantly overtransmitted. Investigation of haplotype transmissions suggested that, in our data, biased transmission was only due to HTTLPR. With respect to this locus, there are now seven of 12 studies reporting significant transmission bias of HTTLPR alleles, a noteworthy result in itself. However, the studies with significant findings are almost equally divided between overtransmission of short and overtransmission of long alleles. We place our results within this extremely heterogeneous field of studies. Determining the factors influencing the relationship between autism phenotypes and HTTLPR variation, as well as other loci in SLC6A4, could be an important advance in our understanding of this complex disorder.
Published: 2005

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35 results on '"Schellenberg, GD"'

1. Common Variants Near ZIC1 and ZIC4 in Autopsy-Confirmed Multiple System Atrophy.

2. Sex differences in the genetic architecture underlying resilience in AD

3. Sex‐specific genetic predictors of memory performance

4. Correction: Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.

5. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

6. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

7. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

8. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

9. Immune-related genetic enrichment in frontotemporal dementia: An analysis of genome-wide association studies

10. CXCR4 involvement in neurodegenerative diseases

11. Rare Functional Variant in TM2D3 is Associated with Late-Onset Alzheimer's Disease

12. Evidence for genetic linkage of autism to chromosomes 7 and 4

13. Evidence for genetic linkage of autism to chromosomes 7 and 4

14. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

15. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus

16. Genome-wide association study of corticobasal degeneration identifies risk variants shared with progressive supranuclear palsy

17. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus

18. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

19. Synaptic, transcriptional and chromatin genes disrupted in autism.

20. Genome-Wide Association Meta-analysis of Neuropathologic Features of Alzheimer's Disease and Related Dementias

21. Genome-Wide Association Meta-analysis of Neuropathologic Features of Alzheimer's Disease and Related Dementias

22. Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene

23. Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease

24. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

25. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

26. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

27. Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

28. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

29. Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

30. Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study

31. Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study

32. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes

33. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes

34. Autism and the serotonin transporter: the long and short of it.

35. Autism and the serotonin transporter: the long and short of it.

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