Author: "Chiba-Falek, O." - Searchworks@Jio Institute Digital Library Search Results

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140 results on '"Chiba-Falek, O."'

1. Amplifying Efficiency and Accuracy in Dementia Drug Development

Author: Lerch, O., Levine, S. Z., Sivakumaran, S., Lutz, M. W., Chiba-Falek, O., Mazer, N., Bairu, M., Haraldsen, I. R. J. Hebold, Rossini, P. M., Snyder, P. J., Bouteiller, J., Khachaturian, Z. S., and Khachaturian, Ara S.
Published: 2024
Full Text: View/download PDF

2. Erratum: GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

Author: Trampush, JW, Yang, MLZ, Yu, J, Knowles, E, Davies, G, Liewald, DC, Starr, JM, Djurovic, S, Melle, I, Sundet, K, Christoforou, A, Reinvang, I, DeRosse, P, Lundervold, AJ, Steen, VM, Espeseth, T, Räikkönen, K, Widen, E, Palotie, A, Eriksson, JG, Giegling, I, Konte, B, Roussos, P, Giakoumaki, S, Burdick, KE, Payton, A, Ollier, W, Horan, M, Chiba-Falek, O, Attix, DK, Need, AC, Cirulli, ET, Voineskos, AN, Stefanis, NC, Avramopoulos, D, Hatzimanolis, A, Arking, DE, Smyrnis, N, Bilder, RM, Freimer, NA, Cannon, TD, London, E, Poldrack, RA, Sabb, FW, Congdon, E, Conley, ED, Scult, MA, Dickinson, D, Straub, RE, Donohoe, G, Morris, D, Corvin, A, Gill, M, Hariri, AR, Weinberger, DR, Pendleton, N, Bitsios, P, Rujescu, D, Lahti, J, Le Hellard, S, Keller, MC, Andreassen, OA, Deary, IJ, Glahn, DC, Malhotra, AK, and Lencz, T
Subjects: Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Genetics, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract: This corrects the article DOI: 10.1038/mp.2016.244.
Published: 2017

3. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

Author: Trampush, JW, Yang, MLZ, Yu, J, Knowles, E, Davies, G, Liewald, DC, Starr, JM, Djurovic, S, Melle, I, Sundet, K, Christoforou, A, Reinvang, I, DeRosse, P, Lundervold, AJ, Steen, VM, Espeseth, T, Räikkönen, K, Widen, E, Palotie, A, Eriksson, JG, Giegling, I, Konte, B, Roussos, P, Giakoumaki, S, Burdick, KE, Payton, A, Ollier, W, Horan, M, Chiba-Falek, O, Attix, DK, Need, AC, Cirulli, ET, Voineskos, AN, Stefanis, NC, Avramopoulos, D, Hatzimanolis, A, Arking, DE, Smyrnis, N, Bilder, RM, Freimer, NA, Cannon, TD, London, E, Poldrack, RA, Sabb, FW, Congdon, E, Conley, ED, Scult, MA, Dickinson, D, Straub, RE, Donohoe, G, Morris, D, Corvin, A, Gill, M, Hariri, AR, Weinberger, DR, Pendleton, N, Bitsios, P, Rujescu, D, Lahti, J, Le Hellard, S, Keller, MC, Andreassen, OA, Deary, IJ, Glahn, DC, Malhotra, AK, and Lencz, T
Subjects: Psychiatry, Medical and Health Sciences, Biological Sciences, Psychology and Cognitive Sciences
Abstract: This corrects the article DOI: 10.1038/mp.2016.244.
Published: 2017

4. Toward deciphering the mechanistic role of variations in the Rep1 repeat site in the transcription regulation of SNCA gene

Author: Afek, A., Tagliafierro, L., Glenn, O.C., Lukatsky, D.B., Gordan, R., and Chiba-Falek, O.
Published: 2018
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5. Up-regulation of SNCA gene expression: implications to synucleinopathies

Author: Tagliafierro, L. and Chiba-Falek, O.
Published: 2016
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6. A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing

Author: Davies, G, Harris, S E, Reynolds, C A, Payton, A, Knight, H M, Liewald, D C, Lopez, L M, Luciano, M, Gow, A J, Corley, J, Henderson, R, Murray, C, Pattie, A, Fox, H C, Redmond, P, Lutz, M W, Chiba-Falek, O, Linnertz, C, Saith, S, Haggarty, P, McNeill, G, Ke, X, Ollier, W, Horan, M, Roses, A D, Ponting, C P, Porteous, D J, Tenesa, A, Pickles, A, Starr, J M, Whalley, L J, Pedersen, N L, Pendleton, N, Visscher, P M, and Deary, I J
Published: 2014
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7. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Author: Lam, M. Chen, C.-Y. Ge, T. Xia, Y. Hill, D.W. Trampush, J.W. Yu, J. Knowles, E. Davies, G. Stahl, E.A. Huckins, L. Liewald, D.C. Djurovic, S. Melle, I. Christoforou, A. Reinvang, I. DeRosse, P. Lundervold, A.J. Steen, V.M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J.G. Giegling, I. Konte, B. Hartmann, A.M. Roussos, P. Giakoumaki, S. Burdick, K.E. Payton, A. Ollier, W. Chiba-Falek, O. Koltai, D.C. Need, A.C. Cirulli, E.T. Voineskos, A.N. Stefanis, N.C. Avramopoulos, D. Hatzimanolis, A. Smyrnis, N. Bilder, R.M. Freimer, N.B. Cannon, T.D. London, E. Poldrack, R.A. Sabb, F.W. Congdon, E. Conley, E.D. Scult, M.A. Dickinson, D. Straub, R.E. Donohoe, G. Morris, D. Corvin, A. Gill, M. Hariri, A.R. Weinberger, D.R. Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Le Hellard, S. Keller, M.C. Andreassen, O.A. Deary, I.J. Glahn, D.C. Huang, H. Liu, C. Malhotra, A.K. Lencz, T.
Abstract: Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify “druggable” targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing. © 2021, The Author(s).
Published: 2021

8. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Author: Lam, M, Chen, CY, Ge, T, Xia, Y, Hill, DW, Trampush, JW, Yu, J, Knowles, E, Davies, G, Stahl, EA, Huckins, L, Liewald, DC, Djurovic, S, Melle, I, Christoforou, A, Reinvang, I, DeRosse, P, Lundervold, AJ, Steen, VM, Espeseth, T, Räikkönen, K, Widen, E, Palotie, A, Eriksson, JG, Giegling, I, Konte, B, Hartmann, AM, Roussos, P, Giakoumaki, S, Burdick, KE, Payton, A, Ollier, W, Chiba-Falek, O, Koltai, DC, Need, AC, Cirulli, ET, Voineskos, AN, Stefanis, NC, Avramopoulos, D, Hatzimanolis, A, Smyrnis, N, Bilder, RM, Freimer, NB, Cannon, TD, London, E, Poldrack, RA, Sabb, FW, Congdon, E, Conley, ED, Scult, MA, Dickinson, D, Straub, RE, Donohoe, G, Morris, D, Corvin, A, Gill, M, Hariri, AR, Weinberger, DR, Pendleton, N, Bitsios, P, Rujescu, D, Lahti, J, Le Hellard, S, Keller, MC, Andreassen, OA, Deary, IJ, Glahn, DC, Huang, H, Liu, C, Malhotra, AK, Lencz, T, Lam, M, Chen, CY, Ge, T, Xia, Y, Hill, DW, Trampush, JW, Yu, J, Knowles, E, Davies, G, Stahl, EA, Huckins, L, Liewald, DC, Djurovic, S, Melle, I, Christoforou, A, Reinvang, I, DeRosse, P, Lundervold, AJ, Steen, VM, Espeseth, T, Räikkönen, K, Widen, E, Palotie, A, Eriksson, JG, Giegling, I, Konte, B, Hartmann, AM, Roussos, P, Giakoumaki, S, Burdick, KE, Payton, A, Ollier, W, Chiba-Falek, O, Koltai, DC, Need, AC, Cirulli, ET, Voineskos, AN, Stefanis, NC, Avramopoulos, D, Hatzimanolis, A, Smyrnis, N, Bilder, RM, Freimer, NB, Cannon, TD, London, E, Poldrack, RA, Sabb, FW, Congdon, E, Conley, ED, Scult, MA, Dickinson, D, Straub, RE, Donohoe, G, Morris, D, Corvin, A, Gill, M, Hariri, AR, Weinberger, DR, Pendleton, N, Bitsios, P, Rujescu, D, Lahti, J, Le Hellard, S, Keller, MC, Andreassen, OA, Deary, IJ, Glahn, DC, Huang, H, Liu, C, Malhotra, AK, and Lencz, T
Abstract: Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify “druggable” targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.
Published: 2021

9. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function (vol 9, 2098, 2018)

Author: Davies, G., Lam, M., Harris, S.E., Trampush, J.W., Luciano, M., Hill, W.D., Hagenaars, S.P., Ritchie, S.J., Marioni, R.E., Fawns-Ritchie, C., Liewald, D.C.M., Okely, J.A., Ahola-Olli, A.V., Barnes, C.L.K., Bertram, L., Bis, J.C., Burdick, K.E., Christoforou, A., DeRosse, P., Djurovic, S., Espeseth, T., Giakoumaki, S., Giddaluru, S., Gustavson, D.E., Hayward, C., Hofer, E., Ikram, M.A., Karlsson, R., Knowles, E., Lahti, J., Leber, M., Li, S., Mather, K.A., Melle, I., Morris, D., Oldmeadow, C., Palviainen, T., Payton, A., Pazoki, R., Petrovic, K., Reynolds, C.A., Sargurupremraj, M., Scholz, M., Smith, J.A., Smith, A.V., Terzikhan, N., Thalamuthu, A., Trompet, S., Lee, S.J. van der, Ware, E.B., Windham, B.G., Wright, M.J., Yang, J.Y., Yu, J., Ames, D., Amin, N., Amouyel, P., Andreassen, O.A., Armstrong, N.J., Assareh, A.A., Attia, J.R., Attix, D., Avramopoulos, D., Bennett, D.A., Bohmer, A.C., Boyle, P.A., Brodaty, H., Campbell, H., Cannon, T.D., Cirulli, E.T., Congdon, E., Conley, E.D., Corley, J., Cox, S.R., Dale, A.M., Dehghan, A., Dick, D., Dickinson, D., Eriksson, J.G., Evangelou, E., Faul, J.D., Ford, I., Freimer, N.A., Gao, H., Giegling, I., Gillespie, N.A., Gordon, S.D., Gottesman, R.F., Griswold, M.E., Gudnason, V., Harris, T.B., Hartmann, A.M., Hatzimanolis, A., Heiss, G., Holliday, E.G., Joshi, P.K., Kahonen, M., Kardia, S.L.R., Karlsson, I., Kleineidam, L., Knopman, D.S., Kochan, N.A., Konte, B., Kwok, J.B., Hellard, S. le, Lee, T., Lehtimaki, T., Li, S.C., Lill, C.M., Liu, T., Koini, M., London, E., Longstreth, W.T., Lopez, O.L., Loukola, A., Luck, T., Lundervold, A.J., Lundquist, A., Lyytikainen, L.P., Martin, N.G., Montgomery, G.W., Murray, A.D., Need, A.C., Noordam, R., Nyberg, L., Ollier, W., Papenberg, G., Pattie, A., Polasek, O., Poldrack, R.A., Psaty, B.M., Reppermund, S., Riedel-Heller, S.G., Rose, R.J., Rotter, J.I., Roussos, P., Rovio, S.P., Saba, Y., Sabb, F.W., Sachdev, P.S., Satizabal, C.L., Schmid, M., Scott, R.J., Scult, M.A., Simino, J., Slagboom, P.E., Smyrnis, N., Soumare, A., Stefanis, N.C., Stott, D.J., Straub, R.E., Sundet, K., Taylor, A.M., Taylor, K.D., Tzoulaki, I., Tzourio, C., Uitterlinden, A., Vitart, V., Voineskos, A.N., Kaprio, J., Wagner, M., Wagner, H., Weinhold, L., Wen, K.H., Widen, E., Yang, Q., Zhao, W., Adams, H.H.H., Arking, D.E., Bilder, R.M., Bitsios, P., Boerwinkle, E., Chiba-Falek, O., Corvin, A., Jager, P.L. de, Debette, S., Donohoe, G., Elliott, P., Fitzpatrick, A.L., Gill, M., Glahn, D.C., Hagg, S., Hansell, N.K., Hariri, A.R., Ikram, M.K., Jukema, J.W., Vuoksimaa, E., Keller, M.C., Kremen, W.S., Launer, L., Lindenberger, U., Palotie, A., Pedersen, N.L., Pendleton, N., Porteous, D.J., Raikkonen, K., Raitakari, O.T., Ramirez, A., Reinvang, I., Rudan, I., Rujescu, D., Schmidt, R., Schmidt, H., Schofield, P.W., Schofield, P.R., Starr, J.M., Steen, V.M., Trollor, J.N., Turner, S.T., Duijn, C.M. van, Villringer, A., Weinberger, D.R., Weir, D.R., Wilson, J.F., Malhotra, A., McIntosh, A.M., Gale, C.R., Seshadri, S., Mosley, T.H., Bressler, J., Lencz, T., and Deary, I.J.
Published: 2019

10. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Davies, G., Lam, M., Harris, S. E., TRAMPUSH, J. W., LUCIANO, M., HILL, W. D., HAGENAARS, S. P., RITCHIE, S. J., MARIONI, R. E., FAWNS-RITCHIE, C., LIEWALD, D. C. M., OKELY, J. A., AHOLA-OLLI, A. V., BARNES, C. L. K., Bertram, L., BIS, J. C., BURDICK, K. E., CHRISTOFOROU, A., DEROSSE, P., Djurovic, S., ESPESETH, T., GIAKOUMAKI, S., GIDDALURU, S., GUSTAVSON, D. E., Hayward, C., Hofer, E., KARLSSON, R., KNOWLES, E., Lahti, J., Leber, M., MATHER, K. A., Melle, I., Morris, D., OLDMEADOW, C., PALVIAINEN, T., PAYTON, A., PAZOKI, R., PETROVIC, K., Reynolds, C. A., SARGURUPREMRAJ, M., Scholz, M., Smith, J. A., SMITH, A. V., TERZIKHAN, N., THALAMUTHU, A., TROMPET, S., VAN DER LEE, S. J., WARE, E. B., WINDHAM, B. G., WRIGHT, M. J., Yang, J., Yu, J., Ames, D., Amin, N., Amouyel, P., ANDREASSEN, O. A., ARMSTRONG, N. J., ASSAREH, A. A., ATTIA, J. R., ATTIX, D., AVRAMOPOULOS, D., BENNETT, D. A., BOHMER, A. C., BOYLE, P. A., BRODATY, H., Campbell, H., CANNON, T. D., CIRULLI, E. T., CONGDON, E., CONLEY, E. D., CORLEY, J., COX, S. R., DALE, A. M., DEHGHAN, A., Dick, D., Dickinson, D., ERIKSSON, J. G., EVANGELOU, E., FAUL, J. D., Ford, I., FREIMER, N. A., Gao, H., Giegling, I., GILLESPIE, N. A., GORDON, S. D., GOTTESMAN, R. F., GRISWOLD, M. E., GUDNASON, V., HARRIS, T. B., HARTMANN, A. M., Hatzimanolis, A., Heiss, G., HOLLIDAY, E. G., Joshi, P. K., KAHONEN, M., KARDIA, S. L. R., KARLSSON, I., KLEINEIDAM, L., KNOPMAN, D. S., KOCHAN, N. A., Konte, B., KWOK, J. B., LE HELLARD, S., Lee, T., LEHTIMAKI, T., Li, S. C., Lill, C. M., Liu, T., KOINI, M., London, E., LONGSTRETH, W. T., Jr., LOPEZ, O. L., LOUKOLA, A., LUCK, T., LUNDERVOLD, A. J., LUNDQUIST, A., LYYTIKAINEN, L. P., Martin, N. G., MONTGOMERY, G. W., MURRAY, A. D., NEED, A. C., NOORDAM, R., Nyberg, L., OLLIER, W., PAPENBERG, G., PATTIE, A., POLASEK, O., POLDRACK, R. A., PSATY, B. M., REPPERMUND, S., RIEDEL-HELLER, S. G., ROSE, R. J., ROTTER, J. I., ROUSSOS, P., ROVIO, S. P., SABA, Y., SABB, F. W., SACHDEV, P. S., SATIZABAL, C. L., Schmid, M., Scott, R. J., SCULT, M. A., SIMINO, J., SLAGBOOM, P. E., SMYRNIS, N., Soumare, A., Stefanis, N. C., STOTT, D. J., STRAUB, R. E., SUNDET, K., Taylor, A. M., TAYLOR, K. D., TZOULAKI, I., Tzourio, C., Uitterlinden, A., Vitart, V., VOINESKOS, A. N., Kaprio, J., Wagner, M., Wagner, H., WEINHOLD, L., WEN, K. H., WIDEN, E., Yang, Q., Zhao, W., ADAMS, H. H. H., ARKING, D. E., Bilder, R. M., BITSIOS, P., BOERWINKLE, E., CHIBA-FALEK, O., Corvin, A., DE JAGER, P. L., Debette, S., Donohoe, G., Elliott, P., FITZPATRICK, A. L., Gill, M., GLAHN, D. C., HAGG, S., HANSELL, N. K., HARIRI, A. R., Ikram, M. A., JUKEMA, J. W., VUOKSIMAA, E., KELLER, M. C., KREMEN, W. S., LAUNER, L., LINDENBERGER, U., Palotie, A., PEDERSEN, N. L., PENDLETON, N., PORTEOUS, D. J., RAIKKONEN, K., RAITAKARI, O. T., Ramirez, A., REINVANG, I., RUDAN, I., DAN, Rujescu, Schmidt, R., Schmidt, H., SCHOFIELD, P. W., STARR, J. M., STEEN, V. M., TROLLOR, J. N., TURNER, S. T., VAN DUIJN, C. M., VILLRINGER, A., WEINBERGER, D. R., WEIR, D. R., WILSON, J. F., Malhotra, A., MCINTOSH, A. M., GALE, C. R., SESHADRI, S., MOSLEY, T. H., Jr., BRESSLER, J., Lencz, T., DEARY, I. J., Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: VINTAGE, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, HEALTHY, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
Abstract: Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
Published: 2019

11. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function (Nature Communications, (2018), 9, 1, (2098), 10.1038/s41467-018-04362-x)

Author: Davies, G. Lam, M. Harris, S.E. Trampush, J.W. Luciano, M. Hill, W.D. Hagenaars, S.P. Ritchie, S.J. Marioni, R.E. Fawns-Ritchie, C. Liewald, D.C.M. Okely, J.A. Ahola-Olli, A.V. Barnes, C.L.K. Bertram, L. Bis, J.C. Burdick, K.E. Christoforou, A. DeRosse, P. Djurovic, S. Espeseth, T. Giakoumaki, S. Giddaluru, S. Gustavson, D.E. Hayward, C. Hofer, E. Ikram, M.A. Karlsson, R. Knowles, E. Lahti, J. Leber, M. Li, S. Mather, K.A. Melle, I. Morris, D. Oldmeadow, C. Palviainen, T. Payton, A. Pazoki, R. Petrovic, K. Reynolds, C.A. Sargurupremraj, M. Scholz, M. Smith, J.A. Smith, A.V. Terzikhan, N. Thalamuthu, A. Trompet, S. van der Lee, S.J. Ware, E.B. Windham, B.G. Wright, M.J. Yang, J. Yu, J. Ames, D. Amin, N. Amouyel, P. Andreassen, O.A. Armstrong, N.J. Assareh, A.A. Attia, J.R. Attix, D. Avramopoulos, D. Bennett, D.A. Böhmer, A.C. Boyle, P.A. Brodaty, H. Campbell, H. Cannon, T.D. Cirulli, E.T. Congdon, E. Conley, E.D. Corley, J. Cox, S.R. Dale, A.M. Dehghan, A. Dick, D. Dickinson, D. Eriksson, J.G. Evangelou, E. Faul, J.D. Ford, I. Freimer, N.A. Gao, H. Giegling, I. Gillespie, N.A. Gordon, S.D. Gottesman, R.F. Griswold, M.E. Gudnason, V. Harris, T.B. Hartmann, A.M. Hatzimanolis, A. Heiss, G. Holliday, E.G. Joshi, P.K. Kähönen, M. Kardia, S.L.R. Karlsson, I. Kleineidam, L. Knopman, D.S. Kochan, N.A. Konte, B. Kwok, J.B. Le Hellard, S. Lee, T. Lehtimäki, T. Li, S.-C. Lill, C.M. Liu, T. Koini, M. London, E. Longstreth, W.T., Jr. Lopez, O.L. Loukola, A. Luck, T. Lundervold, A.J. Lundquist, A. Lyytikäinen, L.-P. Martin, N.G. Montgomery, G.W. Murray, A.D. Need, A.C. Noordam, R. Nyberg, L. Ollier, W. Papenberg, G. Pattie, A. Polasek, O. Poldrack, R.A. Psaty, B.M. Reppermund, S. Riedel-Heller, S.G. Rose, R.J. Rotter, J.I. Roussos, P. Rovio, S.P. Saba, Y. Sabb, F.W. Sachdev, P.S. Satizabal, C.L. Schmid, M. Scott, R.J. Scult, M.A. Simino, J. Slagboom, P.E. Smyrnis, N. Soumaré, A. Stefanis, N.C. Stott, D.J. Straub, R.E. Sundet, K. Taylor, A.M. Taylor, K.D. Tzoulaki, I. Tzourio, C. Uitterlinden, A. Vitart, V. Voineskos, A.N. Kaprio, J. Wagner, M. Wagner, H. Weinhold, L. Wen, K.H. Widen, E. Yang, Q. Zhao, W. Adams, H.H.H. Arking, D.E. Bilder, R.M. Bitsios, P. Boerwinkle, E. Chiba-Falek, O. Corvin, A. De Jager, P.L. Debette, S. Donohoe, G. Elliott, P. Fitzpatrick, A.L. Gill, M. Glahn, D.C. Hägg, S. Hansell, N.K. Hariri, A.R. Ikram, M.K. Jukema, J.W. Vuoksimaa, E. Keller, M.C. Kremen, W.S. Launer, L. Lindenberger, U. Palotie, A. Pedersen, N.L. Pendleton, N. Porteous, D.J. Räikkönen, K. Raitakari, O.T. Ramirez, A. Reinvang, I. Rudan, I. Dan Rujescu Schmidt, R. Schmidt, H. Schofield, P.W. Schofield, P.R. Starr, J.M. Steen, V.M. Trollor, J.N. Turner, S.T. Van Duijn, C.M. Villringer, A. Weinberger, D.R. Weir, D.R. Wilson, J.F. Malhotra, A. McIntosh, A.M. Gale, C.R. Seshadri, S. Mosley, T.H., Jr. Bressler, J. Lencz, T. Deary, I.J.
Subjects: ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
Abstract: Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article. © 2019, The Author(s).
Published: 2019

12. Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

Author: Lam, M. Hill, W.D. Trampush, J.W. Yu, J. Knowles, E. Davies, G. Stahl, E. Huckins, L. Liewald, D.C. Djurovic, S. Melle, I. Sundet, K. Christoforou, A. Reinvang, I. DeRosse, P. Lundervold, A.J. Steen, V.M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J.G. Giegling, I. Konte, B. Hartmann, A.M. Roussos, P. Giakoumaki, S. Burdick, K.E. Payton, A. Ollier, W. Chiba-Falek, O. Attix, D.K. Need, A.C. Cirulli, E.T. Voineskos, A.N. Stefanis, N.C. Avramopoulos, D. Hatzimanolis, A. Arking, D.E. Smyrnis, N. Bilder, R.M. Freimer, N.A. Cannon, T.D. London, E. Poldrack, R.A. Sabb, F.W. Congdon, E. Conley, E.D. Scult, M.A. Dickinson, D. Straub, R.E. Donohoe, G. Morris, D. Corvin, A. Gill, M. Hariri, A.R. Weinberger, D.R. Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Le Hellard, S. Keller, M.C. Andreassen, O.A. Deary, I.J. Glahn, D.C. Malhotra, A.K. Lencz, T.
Subjects: mental disorders
Abstract: Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected (“concordant”) direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive (“discordant”) relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10−8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms—early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways—that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness. © 2019
Published: 2019

13. Multi-Trait analysis of gwas and biological insights into cognition: A response to hill (2018)

Author: Lam, M. Trampush, J.W. Yu, J. Knowles, E. Djurovic, S. Melle, I. Sundet, K. Christoforou, A. Reinvang, I. Derosse, P. Lundervold, A.J. Steen, V.M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J.G. Giegling, I. Konte, B. Roussos, P. Giakoumaki, S. Burdick, K.E. Payton, A. Ollier, W. Chiba-Falek, O. Attix, D.K. Need, A.C. Cirulli, E.T. Voineskos, A.N. Stefanis, N.C. Avramopoulos, D. Hatzimanolis, A. Arking, D.E. Smyrnis, N. Bilder, R.M. Freimer, N.A. Cannon, T.D. London, E. Poldrack, R.A. Sabb, F.W. Congdon, E. Conley, E.D. Scult, M.A. Dickinson, D. Straub, R.E. Donohoe, G. Morris, D. Corvin, A. Gill, M. Hariri, A.R. Weinberger, D.R. Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Hellard, S.L. Keller, M.C. Andreassen, O.A. Glahn, D.C. Malhotra, A.K. Lencz, T.
Abstract: Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'. © The Author(s) 2018Â.
Published: 2018

14. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Author: Savage, J.E. Jansen, P.R. Stringer, S. Watanabe, K. Bryois, J. De Leeuw, C.A. Nagel, M. Awasthi, S. Barr, P.B. Coleman, J.R.I. Grasby, K.L. Hammerschlag, A.R. Kaminski, J.A. Karlsson, R. Krapohl, E. Lam, M. Nygaard, M. Reynolds, C.A. Trampush, J.W. Young, H. Zabaneh, D. Hägg, S. Hansell, N.K. Karlsson, I.K. Linnarsson, S. Montgomery, G.W. Muñoz-Manchado, A.B. Quinlan, E.B. Schumann, G. Skene, N.G. Webb, B.T. White, T. Arking, D.E. Avramopoulos, D. Bilder, R.M. Bitsios, P. Burdick, K.E. Cannon, T.D. Chiba-Falek, O. Christoforou, A. Cirulli, E.T. Congdon, E. Corvin, A. Davies, G. Deary, I.J. Derosse, P. Dickinson, D. Djurovic, S. Donohoe, G. Conley, E.D. Eriksson, J.G. Espeseth, T. Freimer, N.A. Giakoumaki, S. Giegling, I. Gill, M. Glahn, D.C. Hariri, A.R. Hatzimanolis, A. Keller, M.C. Knowles, E. Koltai, D. Konte, B. Lahti, J. Le Hellard, S. Lencz, T. Liewald, D.C. London, E. Lundervold, A.J. Malhotra, A.K. Melle, I. Morris, D. Need, A.C. Ollier, W. Palotie, A. Payton, A. Pendleton, N. Poldrack, R.A. Räikkönen, K. Reinvang, I. Roussos, P. Rujescu, D. Sabb, F.W. Scult, M.A. Smeland, O.B. Smyrnis, N. Starr, J.M. Steen, V.M. Stefanis, N.C. Straub, R.E. Sundet, K. Tiemeier, H. Voineskos, A.N. Weinberger, D.R. Widen, E. Yu, J. Abecasis, G. Andreassen, O.A. Breen, G. Christiansen, L. Debrabant, B. Dick, D.M. Heinz, A. Hjerling-Leffler, J. Ikram, M.A. Kendler, K.S. Martin, N.G. Medland, S.E. Pedersen, N.L. Plomin, R. Polderman, T.J.C. Ripke, S. Van Der Sluis, S. Sullivan, P.F. Vrieze, S.I. Wright, M.J. Posthuma, D.
Abstract: Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders. © 2018 The Author(s).
Published: 2018

15. A cystic fibrosis transmembrane conductance regulator splice variant with partial penetrance associated with variable cystic fibrosis presentations.

Author: Kerem, E, Rave-Harel, N, Augarten, A, Madgar, I, Nissim-Rafinia, M, Yahav, Y, Goshen, R, Bentur, L, Rivlin, J, Aviram, M, Genem, A, Chiba-Falek, O, Kraemer, M R, Simon, A, Branski, D, and Kerem, B
Published: 1997
Full Text: View/download PDF

16. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Davies, G. (Gail), Lam, M. (Max), Harris, S.E. (Sarah), Trampush, J.W. (Joey W.), Luciano, M. (Michelle), Hill, W.D. (W. David), Hagenaars, S. (Saskia), Ritchie, S.J. (Stuart J.), Marioni, R.E. (Riccardo), Fawns-Ritchie, C., Liewald, D.C.M. (David C. M.), Okely, J.A. (Judith A.), Ahola-Olli, A.V. (Ari V.), Barnes, C.L.K. (Catriona L. K.), Bertram, L. (Lars), Bis, J.C. (Joshua), Burdick, K.E. (Katherine E.), Christoforou, A. (Andrea), Derosse, P. (Pamela), Djurovic, S. (Srdjan), Espeseth, T. (Thomas), Giakoumaki, S. (Stella), Giddaluru, S. (Sudheer), Gustavson, D.E. (Daniel E.), Hayward, C. (Caroline), Hofer, E. (Edith), Ikram, M.A. (Arfan), Karlsson, R. (Robert), Knowles, E. (Emma), Lahti, J. (Jari), Leber, I. (Isabelle), Li, S. (Shuo), Mather, R., Melle, I. (Ingrid), Morris, D. (Derek), Oldmeadow, C. (Christopher), Palviainen, T. (Teemu), Payton, A. (Antony), Pazoki, R. (Raha), Petrovic, K. (Katja), Reynolds, C.A. (C.), Sargurupremraj, M. (Muralidharan), Scholz, M. (Markus), Smith, J.A. (Jennifer A), Smith, A.V. (Albert), Terzikhan, N. (Natalie), Thalamuthu, A. (Anbupalam), Trompet, S. (Stella), Lee, S.J. (Sven) van der, Ware, E.B. (Erin B.), Windham, B.G. (Gwen), Wright, M.J. (Margaret J.), Yang, J. (Jingyun), Yu, J. (Jin), Ames, D.J. (David), Amin, N. (Najaf), Amouyel, P. (Philippe), Andreassen, O.A. (Ole), Armstrong, N.J. (Nicola J.), Assareh, A.A., Attia, J. (John), Attix, D. (Deborah), Avramopoulos, D. (Dimitrios), Bennett, D.A. (David), Böhmer, M.R. (Marcel), Boyle, P.A. (Patricia A.), Brodaty, H. (Henry), Campbell, H. (Harry), Cannon, T.D. (Tyrone D.), Cirulli, E.T. (Elizabeth T.), Congdon, E. (Eliza), Conley, E.D. (Emily Drabant), Corley, J. (Janie), Cox, S.R. (Simon R.), Dale, A.M. (Anders), Dehghan, A. (Abbas), Dick, D. (Danielle), Dickinson, D. (Dwight), Hagen, K. (Knut), Evangelou, E. (Evangelos), Faul, J.D. (Jessica D.), Ford, I. (Ian), Freimer, N.A. (Nelson A.), Gao, H. (He), Giegling, I. (Ina), Gillespie, N.A. (Nathan A.), Gordon, S.D. (Scott D.), Gottesman, R.F. (Rebecca), Griswold, M.D. (Michael), Gudnason, V. (Vilmundur), Harris, T.B. (Tamara), Hartmann, A.M. (Annette M), Hatzimanolis, A. (Alex), Heiss, G. (Gerardo), Holliday, E.G. (Elizabeth), Joshi, P.K. (Peter), Kähönen, M. (Mika), Kardia, S.L.R. (Sharon L. R.), Karlsson, I. (Ida), Kleineidam, L. (Luca), Knopman, D.S. (David), Kochan, N.A. (Nicole A.), Konte, B. (Bettina), Kwok, J.B.J. (John), Le Hellard, S. (Stephanie), Lee, T. (Teresa), Lehtimäki, T. (Terho), Li, S.-C. (Shu-Chen), Liu, T. (Tian), Koini, M. (Marisa), London, E. (Edythe), Longstreth Jr, W.T., Lopez, O.L. (Oscar), Loukola, A. (Anu), Luck, T. (Tobias), Lundervold, A.J. (Astri), Lundquist, A. (Anders), Lyytikäinen, L.-P. (Leo-Pekka), Martin, N.G. (Nicholas), Montgomery, G.W. (Grant W.), Murray, A.D. (Alison D.), Need, A.C. (Anna C.), Noordam, R. (Raymond), Nyberg, L. (Lisa), Ollier, W.E.R. (William), Papenberg, G., Pattie, A. (Alison), Polasek, O. (Ozren), Poldrack, R.A. (Russell A.), Psaty, B.M. (Bruce M.), Reppermund, S., Riedel-Heller, S. (Steffi), Rose, R.J. (Richard), Rotter, J.I. (Jerome I.), Roussos, A. (Alexandra), Rovio, S.P. (Suvi P.), Saba, Y. (Yasaman), Sabb, F.W. (Fred W.), Sachdev, P.S. (Perminder), Satizabal, C.L. (Claudia), Schmid, M. (Matthias), Scott, R.J. (Rodney J.), Scult, M.A. (Matthew A.), Simino, J. (Jeannette), Slagboom, P.E. (Eline), Smyrnis, N. (Nikolaos), Soumaré, A. (Aicha), Stefanis, N.C. (Nikos C.), Stott, D.J. (David. J.), Straub, R.E. (Richard), Sundet, K. (Kjetil), Taylor, A.M. (Adele M.), Taylor, K.D. (Kent), Tzoulaki, I., Tzourio, C. (Christophe), Uitterlinden, A.G. (André), Vitart, V. (Veronique), Voineskos, A.N. (Aristotle N.), Kaprio, J. (Jaakko), Wagner, M. (Michael), Wagner, H. (Hermann), Weinhold, L. (Leonie), Wen, K.H. (K. Hoyan), Widen, E., Yang, Q. (Qiong Fang), Zhao, W. (Wei), Adams, H.H.H. (Hieab), Arking, D.E. (Dan), Bilder, R.M. (Robert M.), Bitsios, P. (Panos), Boerwinkle, E. (Eric), Chiba-Falek, O. (Ornit), Corvin, A. (Aiden), Jager, P.L. (Philip) de, Debette, S. (Stéphanie), Donohoe, D.J. (Dennis), Elliott, P. (Paul), Fitzpatrick, A.L. (Annette), Gill, M. (Michael), Glahn, D.C. (David), Hägg, S. (Sara), Hansell, N.K. (Narelle), Hariri, A.R. (Ahmad), Ikram, M.K. (Kamran), Jukema, J.W. (Jan Wouter), Vuoksimaa, E. (Eero), Keller, M.C. (Matthew C), Kremen, W.S. (William S.), Launer, L.J. (Lenore), Lindenberger, U. (Ulman), Palotie, A. (Aarno), Pedersen, N.L. (Nancy), Pendleton, N. (Neil), Porteous, D.J. (David J.), Räikkönen, K. (Katri), Raitakari, O.T. (Olli T.), Ramirez, A. (Alfredo), Reinvang, I. (Ivar), Rudan, I. (Igor), Rujescu, D. (Dan), Schmidt, R. (Reinhold), Schmidt, H. (Helena), Schofield, P.W. (Peter W.), Schofield, C.J. (Christopher), Starr, J.M. (John), Steen, V.M. (Vidar), Trollor, J., Turner, S.T. (Steven T.), Duijn, C.M. (Cornelia) van, Villringer, A. (Arno), Weinberger, D.R. (Daniel), Weir, D.R. (David R.), Wilson, J.F. (James F.), Malhotra, A.K. (Anil K), McIntosh, A.M. (Andrew), Gale, C.R. (Catharine R.), Seshadri, S. (Sudha), Mosley, T.H. (Thomas H.), Bressler, J. (Jan), Lencz, T. (Todd), Deary, I.J. (Ian), Davies, G. (Gail), Lam, M. (Max), Harris, S.E. (Sarah), Trampush, J.W. (Joey W.), Luciano, M. (Michelle), Hill, W.D. (W. David), Hagenaars, S. (Saskia), Ritchie, S.J. (Stuart J.), Marioni, R.E. (Riccardo), Fawns-Ritchie, C., Liewald, D.C.M. (David C. M.), Okely, J.A. (Judith A.), Ahola-Olli, A.V. (Ari V.), Barnes, C.L.K. (Catriona L. K.), Bertram, L. (Lars), Bis, J.C. (Joshua), Burdick, K.E. (Katherine E.), Christoforou, A. (Andrea), Derosse, P. (Pamela), Djurovic, S. (Srdjan), Espeseth, T. (Thomas), Giakoumaki, S. (Stella), Giddaluru, S. (Sudheer), Gustavson, D.E. (Daniel E.), Hayward, C. (Caroline), Hofer, E. (Edith), Ikram, M.A. (Arfan), Karlsson, R. (Robert), Knowles, E. (Emma), Lahti, J. (Jari), Leber, I. (Isabelle), Li, S. (Shuo), Mather, R., Melle, I. (Ingrid), Morris, D. (Derek), Oldmeadow, C. (Christopher), Palviainen, T. (Teemu), Payton, A. (Antony), Pazoki, R. (Raha), Petrovic, K. (Katja), Reynolds, C.A. (C.), Sargurupremraj, M. (Muralidharan), Scholz, M. (Markus), Smith, J.A. (Jennifer A), Smith, A.V. (Albert), Terzikhan, N. (Natalie), Thalamuthu, A. (Anbupalam), Trompet, S. (Stella), Lee, S.J. (Sven) van der, Ware, E.B. (Erin B.), Windham, B.G. (Gwen), Wright, M.J. (Margaret J.), Yang, J. (Jingyun), Yu, J. (Jin), Ames, D.J. (David), Amin, N. (Najaf), Amouyel, P. (Philippe), Andreassen, O.A. (Ole), Armstrong, N.J. (Nicola J.), Assareh, A.A., Attia, J. (John), Attix, D. (Deborah), Avramopoulos, D. (Dimitrios), Bennett, D.A. (David), Böhmer, M.R. (Marcel), Boyle, P.A. (Patricia A.), Brodaty, H. (Henry), Campbell, H. (Harry), Cannon, T.D. (Tyrone D.), Cirulli, E.T. (Elizabeth T.), Congdon, E. (Eliza), Conley, E.D. (Emily Drabant), Corley, J. (Janie), Cox, S.R. (Simon R.), Dale, A.M. (Anders), Dehghan, A. (Abbas), Dick, D. (Danielle), Dickinson, D. (Dwight), Hagen, K. (Knut), Evangelou, E. (Evangelos), Faul, J.D. (Jessica D.), Ford, I. (Ian), Freimer, N.A. (Nelson A.), Gao, H. (He), Giegling, I. (Ina), Gillespie, N.A. (Nathan A.), Gordon, S.D. (Scott D.), Gottesman, R.F. (Rebecca), Griswold, M.D. (Michael), Gudnason, V. (Vilmundur), Harris, T.B. (Tamara), Hartmann, A.M. (Annette M), Hatzimanolis, A. (Alex), Heiss, G. (Gerardo), Holliday, E.G. (Elizabeth), Joshi, P.K. (Peter), Kähönen, M. (Mika), Kardia, S.L.R. (Sharon L. R.), Karlsson, I. (Ida), Kleineidam, L. (Luca), Knopman, D.S. (David), Kochan, N.A. (Nicole A.), Konte, B. (Bettina), Kwok, J.B.J. (John), Le Hellard, S. (Stephanie), Lee, T. (Teresa), Lehtimäki, T. (Terho), Li, S.-C. (Shu-Chen), Liu, T. (Tian), Koini, M. (Marisa), London, E. (Edythe), Longstreth Jr, W.T., Lopez, O.L. (Oscar), Loukola, A. (Anu), Luck, T. (Tobias), Lundervold, A.J. (Astri), Lundquist, A. (Anders), Lyytikäinen, L.-P. (Leo-Pekka), Martin, N.G. (Nicholas), Montgomery, G.W. (Grant W.), Murray, A.D. (Alison D.), Need, A.C. (Anna C.), Noordam, R. (Raymond), Nyberg, L. (Lisa), Ollier, W.E.R. (William), Papenberg, G., Pattie, A. (Alison), Polasek, O. (Ozren), Poldrack, R.A. (Russell A.), Psaty, B.M. (Bruce M.), Reppermund, S., Riedel-Heller, S. (Steffi), Rose, R.J. (Richard), Rotter, J.I. (Jerome I.), Roussos, A. (Alexandra), Rovio, S.P. (Suvi P.), Saba, Y. (Yasaman), Sabb, F.W. (Fred W.), Sachdev, P.S. (Perminder), Satizabal, C.L. (Claudia), Schmid, M. (Matthias), Scott, R.J. (Rodney J.), Scult, M.A. (Matthew A.), Simino, J. (Jeannette), Slagboom, P.E. (Eline), Smyrnis, N. (Nikolaos), Soumaré, A. (Aicha), Stefanis, N.C. (Nikos C.), Stott, D.J. (David. J.), Straub, R.E. (Richard), Sundet, K. (Kjetil), Taylor, A.M. (Adele M.), Taylor, K.D. (Kent), Tzoulaki, I., Tzourio, C. (Christophe), Uitterlinden, A.G. (André), Vitart, V. (Veronique), Voineskos, A.N. (Aristotle N.), Kaprio, J. (Jaakko), Wagner, M. (Michael), Wagner, H. (Hermann), Weinhold, L. (Leonie), Wen, K.H. (K. Hoyan), Widen, E., Yang, Q. (Qiong Fang), Zhao, W. (Wei), Adams, H.H.H. (Hieab), Arking, D.E. (Dan), Bilder, R.M. (Robert M.), Bitsios, P. (Panos), Boerwinkle, E. (Eric), Chiba-Falek, O. (Ornit), Corvin, A. (Aiden), Jager, P.L. (Philip) de, Debette, S. (Stéphanie), Donohoe, D.J. (Dennis), Elliott, P. (Paul), Fitzpatrick, A.L. (Annette), Gill, M. (Michael), Glahn, D.C. (David), Hägg, S. (Sara), Hansell, N.K. (Narelle), Hariri, A.R. (Ahmad), Ikram, M.K. (Kamran), Jukema, J.W. (Jan Wouter), Vuoksimaa, E. (Eero), Keller, M.C. (Matthew C), Kremen, W.S. (William S.), Launer, L.J. (Lenore), Lindenberger, U. (Ulman), Palotie, A. (Aarno), Pedersen, N.L. (Nancy), Pendleton, N. (Neil), Porteous, D.J. (David J.), Räikkönen, K. (Katri), Raitakari, O.T. (Olli T.), Ramirez, A. (Alfredo), Reinvang, I. (Ivar), Rudan, I. (Igor), Rujescu, D. (Dan), Schmidt, R. (Reinhold), Schmidt, H. (Helena), Schofield, P.W. (Peter W.), Schofield, C.J. (Christopher), Starr, J.M. (John), Steen, V.M. (Vidar), Trollor, J., Turner, S.T. (Steven T.), Duijn, C.M. (Cornelia) van, Villringer, A. (Arno), Weinberger, D.R. (Daniel), Weir, D.R. (David R.), Wilson, J.F. (James F.), Malhotra, A.K. (Anil K), McIntosh, A.M. (Andrew), Gale, C.R. (Catharine R.), Seshadri, S. (Sudha), Mosley, T.H. (Thomas H.), Bressler, J. (Jan), Lencz, T. (Todd), and Deary, I.J. (Ian)
Abstract: General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the c
Published: 2018
Full Text: View/download PDF

17. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Davies, G., Lam, M., Harris, S.E., Trampush, J.W., Luciano, M., Hill, W.D., Hagenaars, S.P., Ritchie, S.J., Marioni, R.E., Fawns-Ritchie, C., Liewald, D.C.M., Okely, J.A., Ahola-Olli, A.V., Barnes, C.L.K., Bertram, L., Bis, J.C., Burdick, K.E., Christoforou, A., DeRosse, P., Djurovic, S., Espeseth, T., Giakoumaki, S., Giddaluru, S., Gustavson, D.E., Hayward, C., Hofer, E., Ikram, M.A., Karlsson, R., Knowles, E., Lahti, J., Leber, M., Li, S., Mather, K.A., Melle, I., Morris, D., Oldmeadow, C., Palviainen, T., Payton, A., Pazoki, R., Petrovic, K., Reynolds, C.A., Sargurupremraj, M., Scholz, M., Smith, J.A., Smith, A.V., Terzikhan, N., Thalamuthu, A., Trompet, S., van der Lee, S.J., Ware, E.B., Windham, B.G., Wright, M.J., Yang, J., Yu, J., Ames, D., Amin, N., Amouyel, P., Andreassen, O.A., Armstrong, N.J., Assareh, A.A., Attia, J.R., Attix, D., Avramopoulos, D., Bennett, D.A., Böhmer, A.C., Boyle, P.A., Brodaty, H., Campbell, H., Cannon, T.D., Cirulli, E.T., Congdon, E., Conley, E.D., Corley, J., Cox, S.R., Dale, A.M., Dehghan, A., Dick, D., Dickinson, D., Eriksson, J.G., Evangelou, E., Faul, J.D., Ford, I., Freimer, N.A., Gao, H., Giegling, I., Gillespie, N.A., Gordon, S.D., Gottesman, R.F., Griswold, M.E., Gudnason, V., Harris, T.B., Hartmann, A.M., Hatzimanolis, A., Heiss, G., Holliday, E.G., Joshi, P.K., Kähönen, M., Kardia, S.L.R., Karlsson, I., Kleineidam, L., Knopman, D.S., Kochan, N.A., Konte, B., Kwok, J.B., Le Hellard, S., Lee, T., Lehtimäki, T., Li, S-C, Liu, T., Koini, M., London, E., Longstreth, W.T., Lopez, O.L., Loukola, A., Luck, T., Lundervold, A.J., Lundquist, A., Lyytikäinen, L-P, Martin, N.G., Montgomery, G.W., Murray, A.D., Need, A.C., Noordam, R., Nyberg, L., Ollier, W., Papenberg, G., Pattie, A., Polasek, O., Poldrack, R.A., Psaty, B.M., Reppermund, S., Riedel-Heller, S.G., Rose, R.J., Rotter, J.I., Roussos, P., Rovio, S.P., Saba, Y., Sabb, F.W., Sachdev, P.S., Satizabal, C.L., Schmid, M., Scott, R.J., Scult, M.A., Simino, J., Slagboom, P.E., Smyrnis, N., Soumaré, A., Stefanis, N.C., Stott, D.J., Straub, R.E., Sundet, K., Taylor, A.M., Taylor, K.D., Tzoulaki, I., Tzourio, C., Uitterlinden, A., Vitart, V., Voineskos, A.N., Kaprio, J., Wagner, M., Wagner, H., Weinhold, L., Wen, K.H., Widen, E., Yang, Q., Zhao, W., Adams, H.H.H., Arking, D.E., Bilder, R.M., Bitsios, P., Boerwinkle, E., Chiba-Falek, O., Corvin, A., De Jager, P.L., Debette, S., Donohoe, G., Elliott, P., Fitzpatrick, A.L., Gill, M., Glahn, D.C., Hägg, S., Hansell, N.K., Hariri, A.R., Ikram, M.K., Jukema, J.W., Vuoksimaa, E., Keller, M.C., Kremen, W.S., Launer, L., Lindenberger, U., Palotie, A., Pedersen, N.L., Pendleton, N., Porteous, D.J., Räikkönen, K., Raitakari, O.T., Ramirez, A., Reinvang, I., Rudan, I., Rujescu, D., Schmidt, R., Schmidt, H., Schofield, P.W., Schofield, P.R., Starr, J.M., Steen, V.M., Trollor, J.N., Turner, S.T., van Duijn, C.M., Villringer, Arno, Weinberger, D.R., Weir, D.R., Wilson, J.F., Malhotra, A., McIntosh, A.M., Gale, C.R., Seshadri, S., Mosley, T.H., Bressler, J., Lencz, T., Deary, I.J., Davies, G., Lam, M., Harris, S.E., Trampush, J.W., Luciano, M., Hill, W.D., Hagenaars, S.P., Ritchie, S.J., Marioni, R.E., Fawns-Ritchie, C., Liewald, D.C.M., Okely, J.A., Ahola-Olli, A.V., Barnes, C.L.K., Bertram, L., Bis, J.C., Burdick, K.E., Christoforou, A., DeRosse, P., Djurovic, S., Espeseth, T., Giakoumaki, S., Giddaluru, S., Gustavson, D.E., Hayward, C., Hofer, E., Ikram, M.A., Karlsson, R., Knowles, E., Lahti, J., Leber, M., Li, S., Mather, K.A., Melle, I., Morris, D., Oldmeadow, C., Palviainen, T., Payton, A., Pazoki, R., Petrovic, K., Reynolds, C.A., Sargurupremraj, M., Scholz, M., Smith, J.A., Smith, A.V., Terzikhan, N., Thalamuthu, A., Trompet, S., van der Lee, S.J., Ware, E.B., Windham, B.G., Wright, M.J., Yang, J., Yu, J., Ames, D., Amin, N., Amouyel, P., Andreassen, O.A., Armstrong, N.J., Assareh, A.A., Attia, J.R., Attix, D., Avramopoulos, D., Bennett, D.A., Böhmer, A.C., Boyle, P.A., Brodaty, H., Campbell, H., Cannon, T.D., Cirulli, E.T., Congdon, E., Conley, E.D., Corley, J., Cox, S.R., Dale, A.M., Dehghan, A., Dick, D., Dickinson, D., Eriksson, J.G., Evangelou, E., Faul, J.D., Ford, I., Freimer, N.A., Gao, H., Giegling, I., Gillespie, N.A., Gordon, S.D., Gottesman, R.F., Griswold, M.E., Gudnason, V., Harris, T.B., Hartmann, A.M., Hatzimanolis, A., Heiss, G., Holliday, E.G., Joshi, P.K., Kähönen, M., Kardia, S.L.R., Karlsson, I., Kleineidam, L., Knopman, D.S., Kochan, N.A., Konte, B., Kwok, J.B., Le Hellard, S., Lee, T., Lehtimäki, T., Li, S-C, Liu, T., Koini, M., London, E., Longstreth, W.T., Lopez, O.L., Loukola, A., Luck, T., Lundervold, A.J., Lundquist, A., Lyytikäinen, L-P, Martin, N.G., Montgomery, G.W., Murray, A.D., Need, A.C., Noordam, R., Nyberg, L., Ollier, W., Papenberg, G., Pattie, A., Polasek, O., Poldrack, R.A., Psaty, B.M., Reppermund, S., Riedel-Heller, S.G., Rose, R.J., Rotter, J.I., Roussos, P., Rovio, S.P., Saba, Y., Sabb, F.W., Sachdev, P.S., Satizabal, C.L., Schmid, M., Scott, R.J., Scult, M.A., Simino, J., Slagboom, P.E., Smyrnis, N., Soumaré, A., Stefanis, N.C., Stott, D.J., Straub, R.E., Sundet, K., Taylor, A.M., Taylor, K.D., Tzoulaki, I., Tzourio, C., Uitterlinden, A., Vitart, V., Voineskos, A.N., Kaprio, J., Wagner, M., Wagner, H., Weinhold, L., Wen, K.H., Widen, E., Yang, Q., Zhao, W., Adams, H.H.H., Arking, D.E., Bilder, R.M., Bitsios, P., Boerwinkle, E., Chiba-Falek, O., Corvin, A., De Jager, P.L., Debette, S., Donohoe, G., Elliott, P., Fitzpatrick, A.L., Gill, M., Glahn, D.C., Hägg, S., Hansell, N.K., Hariri, A.R., Ikram, M.K., Jukema, J.W., Vuoksimaa, E., Keller, M.C., Kremen, W.S., Launer, L., Lindenberger, U., Palotie, A., Pedersen, N.L., Pendleton, N., Porteous, D.J., Räikkönen, K., Raitakari, O.T., Ramirez, A., Reinvang, I., Rudan, I., Rujescu, D., Schmidt, R., Schmidt, H., Schofield, P.W., Schofield, P.R., Starr, J.M., Steen, V.M., Trollor, J.N., Turner, S.T., van Duijn, C.M., Villringer, Arno, Weinberger, D.R., Weir, D.R., Wilson, J.F., Malhotra, A., McIntosh, A.M., Gale, C.R., Seshadri, S., Mosley, T.H., Bressler, J., Lencz, T., and Deary, I.J.
Abstract: General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16–102) and find 148 genome-wide significant independent loci (P < 5 × 10−8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.
Published: 2018

18. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Author: Davies, G, Lam, M, Harris, SE, Trampush, JW, Luciano, M, Hill, WD, Hagenaars, SP, Ritchie, SJ, Marioni, RE, Fawns-Ritchie, C, Liewald, DCM, Okely, JA, Ahola-Olli, AV, Barnes, CLK, Bertram, L, Bis, JC, Burdick, KE, Christoforou, A, DeRosse, P, Djurovic, S, Espeseth, T, Giakoumaki, S, Giddaluru, S, Gustavson, DE, Hayward, C, Hofer, E, Ikram, MA, Karlsson, R, Knowles, E, Lahti, J, Leber, M, Li, S, Mather, KA, Melle, I, Morris, D, Oldmeadow, C, Palviainen, T, Payton, A, Pazoki, R, Petrovic, K, Reynolds, CA, Sargurupremraj, M, Scholz, M, Smith, JA, Smith, AV, Terzikhan, N, Thalamuthu, A, Trompet, S, van der Lee, SJ, Ware, EB, Windham, BG, Wright, MJ, Yang, J, Yu, J, Ames, D, Amin, N, Amouyel, P, Andreassen, OA, Armstrong, NJ, Assareh, AA, Attia, JR, Attix, D, Avramopoulos, D, Bennett, DA, Boehmer, AC, Boyle, PA, Brodaty, H, Campbell, H, Cannon, TD, Cirulli, ET, Congdon, E, Conley, ED, Corley, J, Cox, SR, Dale, AM, Dehghan, A, Dick, D, Dickinson, D, Eriksson, JG, Evangelou, E, Faul, JD, Ford, I, Freimer, NA, Gao, H, Giegling, I, Gillespie, NA, Gordon, SD, Gottesman, RF, Griswold, ME, Gudnason, V, Harris, TB, Hartmann, AM, Hatzimanolis, A, Heiss, G, Holliday, EG, Joshi, PK, Kahonen, M, Kardia, SLR, Karlsson, I, Kleineidam, L, Knopman, DS, Kochan, NA, Konte, B, Kwok, JB, Le Hellard, S, Lee, T, Lehtimaki, T, Li, S-C, Liu, T, Koini, M, London, E, Longstreth, WT, Lopez, OL, Loukola, A, Luck, T, Lundervold, AJ, Lundquist, A, Lyytikainen, L-P, Martin, NG, Montgomery, GW, Murray, AD, Need, AC, Noordam, R, Nyberg, L, Ollier, W, Papenberg, G, Pattie, A, Polasek, O, Poldrack, RA, Psaty, BM, Reppermund, S, Riedel-Heller, SG, Rose, RJ, Rotter, JI, Roussos, P, Rovio, SP, Saba, Y, Sabb, FW, Sachdev, PS, Satizabal, CL, Schmid, M, Scott, RJ, Scult, MA, Simino, J, Slagboom, PE, Smyrnis, N, Soumare, A, Stefanis, NC, Stott, DJ, Straub, RE, Sundet, K, Taylor, AM, Taylor, KD, Tzoulaki, I, Tzourio, C, Uitterlinden, A, Vitart, V, Voineskos, AN, Kaprio, J, Wagner, M, Wagner, H, Weinhold, L, Wen, KH, Widen, E, Yang, Q, Zhao, W, Adams, HHH, Arking, DE, Bilder, RM, Bitsios, P, Boerwinkle, E, Chiba-Falek, O, Corvin, A, De Jager, PL, Debette, S, Donohoe, G, Elliott, P, Fitzpatrick, AL, Gill, M, Glahn, DC, Hagg, S, Hansell, NK, Hariri, AR, Ikram, MK, Jukema, JW, Vuoksimaa, E, Keller, MC, Kremen, WS, Launer, L, Lindenberger, U, Palotie, A, Pedersen, NL, Pendleton, N, Porteous, DJ, Raikkonen, K, Raitakari, OT, Ramirez, A, Reinvang, I, Rudan, I, Rujescu, D, Schmidt, R, Schmidt, H, Schofield, PW, Schofield, PR, Starr, JM, Steen, VM, Trollor, JN, Turner, ST, Van Duijn, CM, Villringer, A, Weinberger, DR, Weir, DR, Wilson, JF, Malhotra, A, McIntosh, AM, Gale, CR, Seshadri, S, Mosley, TH, Bressler, J, Lencz, T, Deary, IJ, Davies, G, Lam, M, Harris, SE, Trampush, JW, Luciano, M, Hill, WD, Hagenaars, SP, Ritchie, SJ, Marioni, RE, Fawns-Ritchie, C, Liewald, DCM, Okely, JA, Ahola-Olli, AV, Barnes, CLK, Bertram, L, Bis, JC, Burdick, KE, Christoforou, A, DeRosse, P, Djurovic, S, Espeseth, T, Giakoumaki, S, Giddaluru, S, Gustavson, DE, Hayward, C, Hofer, E, Ikram, MA, Karlsson, R, Knowles, E, Lahti, J, Leber, M, Li, S, Mather, KA, Melle, I, Morris, D, Oldmeadow, C, Palviainen, T, Payton, A, Pazoki, R, Petrovic, K, Reynolds, CA, Sargurupremraj, M, Scholz, M, Smith, JA, Smith, AV, Terzikhan, N, Thalamuthu, A, Trompet, S, van der Lee, SJ, Ware, EB, Windham, BG, Wright, MJ, Yang, J, Yu, J, Ames, D, Amin, N, Amouyel, P, Andreassen, OA, Armstrong, NJ, Assareh, AA, Attia, JR, Attix, D, Avramopoulos, D, Bennett, DA, Boehmer, AC, Boyle, PA, Brodaty, H, Campbell, H, Cannon, TD, Cirulli, ET, Congdon, E, Conley, ED, Corley, J, Cox, SR, Dale, AM, Dehghan, A, Dick, D, Dickinson, D, Eriksson, JG, Evangelou, E, Faul, JD, Ford, I, Freimer, NA, Gao, H, Giegling, I, Gillespie, NA, Gordon, SD, Gottesman, RF, Griswold, ME, Gudnason, V, Harris, TB, Hartmann, AM, Hatzimanolis, A, Heiss, G, Holliday, EG, Joshi, PK, Kahonen, M, Kardia, SLR, Karlsson, I, Kleineidam, L, Knopman, DS, Kochan, NA, Konte, B, Kwok, JB, Le Hellard, S, Lee, T, Lehtimaki, T, Li, S-C, Liu, T, Koini, M, London, E, Longstreth, WT, Lopez, OL, Loukola, A, Luck, T, Lundervold, AJ, Lundquist, A, Lyytikainen, L-P, Martin, NG, Montgomery, GW, Murray, AD, Need, AC, Noordam, R, Nyberg, L, Ollier, W, Papenberg, G, Pattie, A, Polasek, O, Poldrack, RA, Psaty, BM, Reppermund, S, Riedel-Heller, SG, Rose, RJ, Rotter, JI, Roussos, P, Rovio, SP, Saba, Y, Sabb, FW, Sachdev, PS, Satizabal, CL, Schmid, M, Scott, RJ, Scult, MA, Simino, J, Slagboom, PE, Smyrnis, N, Soumare, A, Stefanis, NC, Stott, DJ, Straub, RE, Sundet, K, Taylor, AM, Taylor, KD, Tzoulaki, I, Tzourio, C, Uitterlinden, A, Vitart, V, Voineskos, AN, Kaprio, J, Wagner, M, Wagner, H, Weinhold, L, Wen, KH, Widen, E, Yang, Q, Zhao, W, Adams, HHH, Arking, DE, Bilder, RM, Bitsios, P, Boerwinkle, E, Chiba-Falek, O, Corvin, A, De Jager, PL, Debette, S, Donohoe, G, Elliott, P, Fitzpatrick, AL, Gill, M, Glahn, DC, Hagg, S, Hansell, NK, Hariri, AR, Ikram, MK, Jukema, JW, Vuoksimaa, E, Keller, MC, Kremen, WS, Launer, L, Lindenberger, U, Palotie, A, Pedersen, NL, Pendleton, N, Porteous, DJ, Raikkonen, K, Raitakari, OT, Ramirez, A, Reinvang, I, Rudan, I, Rujescu, D, Schmidt, R, Schmidt, H, Schofield, PW, Schofield, PR, Starr, JM, Steen, VM, Trollor, JN, Turner, ST, Van Duijn, CM, Villringer, A, Weinberger, DR, Weir, DR, Wilson, JF, Malhotra, A, McIntosh, AM, Gale, CR, Seshadri, S, Mosley, TH, Bressler, J, Lencz, T, and Deary, IJ
Abstract: General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.
Published: 2018

19. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Author: Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., Grasby, K. L., Hammerschlag, A. R., Kaminski, J. A., Karlsson, R., Krapohl, E., Lam, M., Nygaard, M., Reynolds, C. A., Trampush, J. W., Young, H., Zabaneh, D., Hägg, S., Hansell, N. K., Karlsson, Ida K., Linnarsson, S., Montgomery, G. W., Muñoz-Manchado, A. B., Quinlan, E. B., Schumann, G., Skene, N. G., Webb, B. T., White, T., Arking, D. E., Avramopoulos, D., Bilder, R. M., Bitsios, P., Burdick, K. E., Cannon, T. D., Chiba-Falek, O., Christoforou, A., Cirulli, E. T., Congdon, E., Corvin, A., Davies, G., Deary, I. J., Derosse, P., Dickinson, D., Djurovic, S., Donohoe, G., Conley, E. D., Eriksson, J. G., Espeseth, T., Freimer, N. A., Giakoumaki, S., Giegling, I., Gill, M., Glahn, D. C., Hariri, A. R., Hatzimanolis, A., Keller, M. C., Knowles, E., Koltai, D., Konte, B., Lahti, J., Le Hellard, S., Lencz, T., Liewald, D. C., London, E., Lundervold, A. J., Malhotra, A. K., Melle, I., Morris, D., Need, A. C., Ollier, W., Palotie, A., Payton, A., Pendleton, N., Poldrack, R. A., Räikkönen, K., Reinvang, I., Roussos, P., Rujescu, D., Sabb, F. W., Scult, M. A., Smeland, O. B., Smyrnis, N., Starr, J. M., Steen, V. M., Stefanis, N. C., Straub, R. E., Sundet, K., Tiemeier, H., Voineskos, A. N., Weinberger, D. R., Widen, E., Yu, J., Abecasis, G., Andreassen, O. A., Breen, G., Christiansen, L., Debrabant, B., Dick, D. M., Heinz, A., Hjerling-Leffler, J., Ikram, M. A., Kendler, K. S., Martin, N. G., Medland, S. E., Pedersen, N. L., Plomin, R., Polderman, T. J. C., Ripke, S., Van Der Sluis, S., Sullivan, P. F., Vrieze, S. I., Wright, M. J., Posthuma, D., Savage, J. E., Jansen, P. R., Stringer, S., Watanabe, K., Bryois, J., De Leeuw, C. A., Nagel, M., Awasthi, S., Barr, P. B., Coleman, J. R. I., Grasby, K. L., Hammerschlag, A. R., Kaminski, J. A., Karlsson, R., Krapohl, E., Lam, M., Nygaard, M., Reynolds, C. A., Trampush, J. W., Young, H., Zabaneh, D., Hägg, S., Hansell, N. K., Karlsson, Ida K., Linnarsson, S., Montgomery, G. W., Muñoz-Manchado, A. B., Quinlan, E. B., Schumann, G., Skene, N. G., Webb, B. T., White, T., Arking, D. E., Avramopoulos, D., Bilder, R. M., Bitsios, P., Burdick, K. E., Cannon, T. D., Chiba-Falek, O., Christoforou, A., Cirulli, E. T., Congdon, E., Corvin, A., Davies, G., Deary, I. J., Derosse, P., Dickinson, D., Djurovic, S., Donohoe, G., Conley, E. D., Eriksson, J. G., Espeseth, T., Freimer, N. A., Giakoumaki, S., Giegling, I., Gill, M., Glahn, D. C., Hariri, A. R., Hatzimanolis, A., Keller, M. C., Knowles, E., Koltai, D., Konte, B., Lahti, J., Le Hellard, S., Lencz, T., Liewald, D. C., London, E., Lundervold, A. J., Malhotra, A. K., Melle, I., Morris, D., Need, A. C., Ollier, W., Palotie, A., Payton, A., Pendleton, N., Poldrack, R. A., Räikkönen, K., Reinvang, I., Roussos, P., Rujescu, D., Sabb, F. W., Scult, M. A., Smeland, O. B., Smyrnis, N., Starr, J. M., Steen, V. M., Stefanis, N. C., Straub, R. E., Sundet, K., Tiemeier, H., Voineskos, A. N., Weinberger, D. R., Widen, E., Yu, J., Abecasis, G., Andreassen, O. A., Breen, G., Christiansen, L., Debrabant, B., Dick, D. M., Heinz, A., Hjerling-Leffler, J., Ikram, M. A., Kendler, K. S., Martin, N. G., Medland, S. E., Pedersen, N. L., Plomin, R., Polderman, T. J. C., Ripke, S., Van Der Sluis, S., Sullivan, P. F., Vrieze, S. I., Wright, M. J., and Posthuma, D.
Abstract: Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
Published: 2018
Full Text: View/download PDF

20. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium (vol 22, pg 336, 2017)

Author: Trampush, JW, Yang, MLZ, Yu, J, Knowles, E, Davies, G, Liewald, DC, Starr, JM, Djurovic, S, Melle, I, Sundet, K, Christoforou, A, Reinvang, I, DeRosse, P, Lundervold, AJ, Steen, VM, Espeseth, T, Raikkonen, K, Widen, E, Palotie, A, Eriksson, JG, Giegling, I, Konte, B, Roussos, P, Giakoumaki, S, Burdick, KE, Payton, A, Ollier, W, Horan, M, Chiba-Falek, O, Attix, DK, Need, AC, Cirulli, ET, Voineskos, AN, Stefanis, NC, Avramopoulos, D, Hatzimanolis, A, Arking, DE, Smyrnis, N, Bilder, RM, Freimer, NA, Cannon, TD, London, E, Poldrack, RA, Sabb, FW, Congdon, E, Conley, ED, Scult, MA, Dickinson, D, Straub, RE, Donohoe, G, Morris, D, Corvin, A, Gill, M, Hariri, AR, Weinberger, DR, Pendleton, N, Bitsios, P, Rujescu, D, Lahti, J, Le Hellard, S, Keller, MC, Andreassen, OA, Deary, IJ, Glahn, DC, Malhotra, AK, and Lencz, T
Subjects: Psychiatry, 17 Psychology And Cognitive Sciences, Biochemistry & Molecular Biology, Science & Technology, Neurosciences, Neurosciences & Neurology, 11 Medical And Health Sciences, 06 Biological Sciences, Life Sciences & Biomedicine
Published: 2017

21. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

Author: Trampush, J. W. Yang, M. L. Z. Yu, J. Knowles, E. and Davies, G. Liewald, D. C. Starr, J. M. Djurovic, S. and Melle, I. Sundet, K. Christoforou, A. Reinvang, I. and DeRosse, P. Lundervold, A. J. Steen, V. M. Espeseth, T. and Raikkonen, K. Widen, E. Palotie, A. Eriksson, J. G. and Giegling, I. Konte, B. Roussos, P. Giakoumaki, S. and Burdick, K. E. Payton, A. Ollier, W. Horan, M. and Chiba-Falek, O. Attix, D. K. Need, A. C. Cirulli, E. T. and Voineskos, A. N. Stefanis, N. C. Avramopoulos, D. and Hatzimanolis, A. Arking, D. E. Smyrnis, N. Bilder, R. M. and Freimer, N. A. Cannon, T. D. London, E. Poldrack, R. A. and Sabb, F. W. Congdon, E. Conley, E. D. Scult, M. A. and Dickinson, D. Straub, R. E. Donohoe, G. Morris, D. and Corvin, A. Gill, M. Hariri, A. R. Weinberger, D. R. and Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Le Hellard, S. Keller, M. C. Andreassen, O. A. Deary, I. J. and Glahn, D. C. Malhotra, A. K. Lencz, T.
Abstract: The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (similar to 8M single-nucleotide polymorphisms (SNP) with minor allele frequency >= 1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P
Published: 2017

22. Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

Author: Lam, M. Trampush, J.W. Yu, J. Knowles, E. Davies, G. Liewald, D.C. Starr, J.M. Djurovic, S. Melle, I. Sundet, K. Christoforou, A. Reinvang, I. DeRosse, P. Lundervold, A.J. Steen, V.M. Espeseth, T. Räikkönen, K. Widen, E. Palotie, A. Eriksson, J.G. Giegling, I. Konte, B. Roussos, P. Giakoumaki, S. Burdick, K.E. Payton, A. Ollier, W. Chiba-Falek, O. Attix, D.K. Need, A.C. Cirulli, E.T. Voineskos, A.N. Stefanis, N.C. Avramopoulos, D. Hatzimanolis, A. Arking, D.E. Smyrnis, N. Bilder, R.M. Freimer, N.A. Cannon, T.D. London, E. Poldrack, R.A. Sabb, F.W. Congdon, E. Conley, E.D. Scult, M.A. Dickinson, D. Straub, R.E. Donohoe, G. Morris, D. Corvin, A. Gill, M. Hariri, A.R. Weinberger, D.R. Pendleton, N. Bitsios, P. Rujescu, D. Lahti, J. Le Hellard, S. Keller, M.C. Andreassen, O.A. Deary, I.J. Glahn, D.C. Malhotra, A.K. Lencz, T.
Abstract: Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability (“g”), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth. Lam et al. conduct a large-scale genome-wide association study of cognitive ability, identifying 70 associated loci. Results provide biological insights into the molecular basis of individual differences in cognitive ability, as well as their relationship to psychiatric and other health-relevant phenotypes. © 2017 The Author(s)
Published: 2017

23. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function

Author: University of Helsinki, Medicum, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, University of Helsinki, Helsinki Collegium for Advanced Studies, Trampush, J. W., Yang, M. L. Z., Yu, J., Knowles, E., Davies, G., Liewald, D. C., Starr, J. M., Djurovic, S., Melle, I., Sundet, K., Christoforou, A., Reinvang, I., DeRosse, P., Lundervold, A. J., Steen, V. M., Espeseth, T., Räikkönen, Katri, Widen, E., Palotie, A., Eriksson, J. G., Giegling, I., Konte, B., Roussos, P., Giakoumaki, S., Burdick, K. E., Payton, A., Ollier, W., Horan, M., Chiba-Falek, O., Attix, D. K., Need, A. C., Cirulli, E. T., Voineskos, A. N., Stefanis, N. C., Avramopoulos, D., Hatzimanolis, A., Arking, D. E., Smyrnis, N., Bilder, R. M., Freimer, N. A., Cannon, T. D., London, E., Poldrack, R. A., Sabb, F. W., Congdon, E., Conley, E. D., Scult, M. A., Dickinson, D., Straub, R. E., Donohoe, G., Morris, D., Corvin, A., Gill, M., Hariri, A. R., Weinberger, D. R., Pendleton, N., Bitsios, P., Rujescu, D., Lahti, J., Le Hellard, S., Keller, M. C., Andreassen, O. A., Deary, I. J., Glahn, D. C., Malhotra, A. K., Lencz, T., University of Helsinki, Medicum, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, University of Helsinki, Helsinki Collegium for Advanced Studies, Trampush, J. W., Yang, M. L. Z., Yu, J., Knowles, E., Davies, G., Liewald, D. C., Starr, J. M., Djurovic, S., Melle, I., Sundet, K., Christoforou, A., Reinvang, I., DeRosse, P., Lundervold, A. J., Steen, V. M., Espeseth, T., Räikkönen, Katri, Widen, E., Palotie, A., Eriksson, J. G., Giegling, I., Konte, B., Roussos, P., Giakoumaki, S., Burdick, K. E., Payton, A., Ollier, W., Horan, M., Chiba-Falek, O., Attix, D. K., Need, A. C., Cirulli, E. T., Voineskos, A. N., Stefanis, N. C., Avramopoulos, D., Hatzimanolis, A., Arking, D. E., Smyrnis, N., Bilder, R. M., Freimer, N. A., Cannon, T. D., London, E., Poldrack, R. A., Sabb, F. W., Congdon, E., Conley, E. D., Scult, M. A., Dickinson, D., Straub, R. E., Donohoe, G., Morris, D., Corvin, A., Gill, M., Hariri, A. R., Weinberger, D. R., Pendleton, N., Bitsios, P., Rujescu, D., Lahti, J., Le Hellard, S., Keller, M. C., Andreassen, O. A., Deary, I. J., Glahn, D. C., Malhotra, A. K., and Lencz, T.
Abstract: The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (similar to 8M single-nucleotide polymorphisms (SNP) with minor allele frequency >= 1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P
Published: 2017

24. A Genome-wide association study of non-pathological cognitive ageing

Author: Davies, G, Harris, S, Reynolds, C, Payton, A, Liewald, D, Lopez, L, Luciano, M, Gow, A, Corley, J, Henderson, R, Murray, C, Pattie, A, Fox, H, Redmond, P, Lutz, M, Chiba-Falek, O, Linnertz, C, Saith, S, Knight, H, Haggarty, P, McNeill, G, Ollier, W, Horan, M, Roses, A, and Ponting, C
Published: 2016

25. Analysis of the human alpha-synuclein promoter

Author: Chiba-Falek, O., Orrison, B.M., Touchman, J.W., Dehejia, A., Polymeropoulos, M.H., and Nussbaum, R.L.
Subjects: Genetic research -- Analysis, Human genetics -- Research, Biological sciences
Published: 2000

26. Modification of the CFTR splicing pattern by cellular and viral splicing factors in CFTR expressing cells

Author: Nissim-Rafinia, M., Chiba-Falek, O., and Kerem, B.
Subjects: Cystic fibrosis -- Genetic aspects, RNA splicing -- Genetic aspects, Biological sciences
Published: 2000

27. African-American TOMM40'523-APOE haplotypes are admixture of West African and Caucasian alleles

Author: Roses, A., Lutz, M., Saunders, A., Goldgaber, D., Saul, R., Sundseth, S., Akkari, Patrick, Roses, S., Gottschalk, W., Whitfield, K., Vostrov, A., Hauser, M., Allingham, R., Burns, D., Chiba-Falek, O., Welsh-Bohmer, K., Roses, A., Lutz, M., Saunders, A., Goldgaber, D., Saul, R., Sundseth, S., Akkari, Patrick, Roses, S., Gottschalk, W., Whitfield, K., Vostrov, A., Hauser, M., Allingham, R., Burns, D., Chiba-Falek, O., and Welsh-Bohmer, K.
Abstract: Background: Several studies have demonstrated a lower apolipoprotein E4 (APOE e4) allele frequency in African-Americans, but yet an increased age-related prevalence of AD. An algorithm for prevention clinical trials incorporating TOMM40'523 (Translocase of Outer Mitochondria Membrane) and APOE depends on accurate TOMM40'523-APOE haplotypes. Methods: We have compared the APOE and TOMM40'523 phased haplotype frequencies of a 9.5 kb TOMM40/APOE genomic region in West African, Caucasian, and African-American cohorts. Results: African-American haplotype frequency scans of poly-T lengths connected in phase with either APOE e4 or APOE e3 differ from both West Africans and Caucasians and represent admixture of several distinct West African and Caucasian haplotypes. A new West African TOMM40'523 haplotype, with APOE e4 connected to a short TOMM40'523 allele, is observed in African-Americans but not Caucasians. Conclusion: These data have therapeutic implications for the age of onset risk algorithm estimates and the design of a prevention trial for African-Americans or other mixed ethnic populations.
Published: 2014

28. The genetic contributions of SNCA and LRRK2 genes to Lewy Body pathology in Alzheimer's disease

Author: Linnertz, C., primary, Lutz, M. W., additional, Ervin, J. F., additional, Allen, J., additional, Miller, N. R., additional, Welsh-Bohmer, K. A., additional, Roses, A. D., additional, and Chiba-Falek, O., additional
Published: 2014
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29. A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing

Author: Davies, G, primary, Harris, S E, additional, Reynolds, C A, additional, Payton, A, additional, Knight, H M, additional, Liewald, D C, additional, Lopez, L M, additional, Luciano, M, additional, Gow, A J, additional, Corley, J, additional, Henderson, R, additional, Murray, C, additional, Pattie, A, additional, Fox, H C, additional, Redmond, P, additional, Lutz, M W, additional, Chiba-Falek, O, additional, Linnertz, C, additional, Saith, S, additional, Haggarty, P, additional, McNeill, G, additional, Ke, X, additional, Ollier, W, additional, Horan, M, additional, Roses, A D, additional, Ponting, C P, additional, Porteous, D J, additional, Tenesa, A, additional, Pickles, A, additional, Starr, J M, additional, Whalley, L J, additional, Pedersen, N L, additional, Pendleton, N, additional, Visscher, P M, additional, and Deary, I J, additional
Published: 2012
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30. Regulation of -Synuclein Expression: Implications for Parkinson's Disease

Author: CHIBA-FALEK, O., primary and NUSSBAUM, R.L., additional
Published: 2003
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31. Effect of allelic variation at the NACP-Rep1 repeat upstream of the alpha-synuclein gene (SNCA) on transcription in a cell culture luciferase reporter system

Author: Chiba-Falek, O., primary
Published: 2001
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32. Regulation of α-Synuclein Expression: Implications for Parkinson's Disease.

Author: Chiba-Falek, O. and Nussbaum, R. L.
Subjects: *PARKINSON'S disease, *GENE expression, *ETIOLOGY of diseases, *BIOLOGICAL variation, *HUMAN genetics, *GENETIC disorders
Abstract: Focuses on the implications of α-synuclein expression on Parkinson's disease (PD). Etiology of Parkinson's disease; Potential role of variation of α-synuclein expression in predisposing to PD; Environmental and cellular trans-acting factors that contribute to the modulation of α-synuclein expression.
Published: 2003
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33. Human and mouse alpha-synuclein genes: comparative genomic sequence analysis and identification of a novel gene regulatory element.

Author: Touchman, J W, Dehejia, A, Chiba-Falek, O, Cabin, D E, Schwartz, J R, Orrison, B M, Polymeropoulos, M H, and Nussbaum, R L
Abstract: The human alpha-synuclein gene (SNCA) encodes a presynaptic nerve terminal protein that was originally identified as a precursor of the non-beta-amyloid component of Alzheimer's disease plaques. More recently, mutations in SNCA have been identified in some cases of familial Parkinson's disease, presenting numerous new areas of investigation for this important disease. Molecular studies would benefit from detailed information about the long-range sequence context of SNCA. To that end, we have established the complete genomic sequence of the chromosomal regions containing the human and mouse alpha-synuclein genes, with the objective of using the resulting sequence information to identify conserved regions of biological importance through comparative sequence analysis. These efforts have yielded approximately 146 and approximately 119 kb of high-accuracy human and mouse genomic sequence, respectively, revealing the precise genetic architecture of the alpha-synuclein gene in both species. A simple repeat element upstream of SNCA/Snca has been identified and shown to be necessary for normal expression in transient transfection assays using a luciferase reporter construct. Together, these studies provide valuable data that should facilitate more detailed analysis of this medically important gene.
Published: 2001

34. Advancements in APOE and dementia research: Highlights from the 2023 AAIC Advancements: APOE conference.

Author: Kloske CM, Belloy ME, Blue EE, Bowman GR, Carrillo MC, Chen X, Chiba-Falek O, Davis AA, Paolo GD, Garretti F, Gate D, Golden LR, Heinecke JW, Herz J, Huang Y, Iadecola C, Johnson LA, Kanekiyo T, Karch CM, Khvorova A, Koppes-den Hertog SJ, Lamb BT, Lawler PE, Guen YL, Litvinchuk A, Liu CC, Mahinrad S, Marcora E, Marino C, Michaelson DM, Miller JJ, Morganti JM, Narayan PS, Naslavsky MS, Oosthoek M, Ramachandran KV, Ramakrishnan A, Raulin AC, Robert A, Saleh RNM, Sexton C, Shah N, Shue F, Sible IJ, Soranno A, Strickland MR, Tcw J, Thierry M, Tsai LH, Tuckey RA, Ulrich JD, van der Kant R, Wang N, Wellington CL, Weninger SC, Yassine HN, Zhao N, Bu G, Goate AM, and Holtzman DM
Subjects: Humans, Congresses as Topic, Animals, Amyloid beta-Peptides metabolism, Dementia genetics, Dementia metabolism, Biomedical Research, Apolipoproteins E genetics, Apolipoproteins E metabolism, Alzheimer Disease genetics, Alzheimer Disease metabolism
Abstract: Introduction: The apolipoprotein E gene (APOE) is an established central player in the pathogenesis of Alzheimer's disease (AD), with distinct apoE isoforms exerting diverse effects. apoE influences not only amyloid-beta and tau pathologies but also lipid and energy metabolism, neuroinflammation, cerebral vascular health, and sex-dependent disease manifestations. Furthermore, ancestral background may significantly impact the link between APOE and AD, underscoring the need for more inclusive research., Methods: In 2023, the Alzheimer's Association convened multidisciplinary researchers at the "AAIC Advancements: APOE" conference to discuss various topics, including apoE isoforms and their roles in AD pathogenesis, progress in apoE-targeted therapeutic strategies, updates on disease models and interventions that modulate apoE expression and function., Results: This manuscript presents highlights from the conference and provides an overview of opportunities for further research in the field., Discussion: Understanding apoE's multifaceted roles in AD pathogenesis will help develop targeted interventions for AD and advance the field of AD precision medicine., Highlights: APOE is a central player in the pathogenesis of Alzheimer's disease. APOE exerts a numerous effects throughout the brain on amyloid-beta, tau, and other pathways. The AAIC Advancements: APOE conference encouraged discussions and collaborations on understanding the role of APOE., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
Published: 2024
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35. The therapeutic implications of all-in-one AAV-delivered epigenome-editing platform in neurodegenerative disorders.

Author: Kantor B, O'Donovan B, Rittiner J, Hodgson D, Lindner N, Guerrero S, Dong W, Zhang A, and Chiba-Falek O
Subjects: Humans, Animals, Mice, Neurodegenerative Diseases genetics, Neurodegenerative Diseases therapy, Genetic Therapy methods, Epigenome, HEK293 Cells, Methyl-CpG-Binding Protein 2 genetics, Methyl-CpG-Binding Protein 2 metabolism, Epigenesis, Genetic, Alzheimer Disease genetics, Alzheimer Disease therapy, Apolipoproteins E genetics, Staphylococcus aureus genetics, Gene Editing methods, Dependovirus genetics, CRISPR-Cas Systems genetics, Genetic Vectors genetics
Abstract: Safely and efficiently controlling gene expression is a long-standing goal of biomedical research, and CRISPR/Cas system can be harnessed to create powerful tools for epigenetic editing. Adeno-associated-viruses (AAVs) represent the delivery vehicle of choice for therapeutic platform. However, their small packaging capacity isn't suitable for large constructs including most CRISPR/dCas9-effector vectors. Thus, AAV-based CRISPR/Cas systems have been delivered via two separate viral vectors. Here we develop a compact CRISPR/dCas9-based repressor system packaged in AAV as a single optimized vector. The system comprises the small Staphylococcus aureus (Sa)dCas9 and an engineered repressor molecule, a fusion of MeCP2's transcription repression domain (TRD) and KRAB. The dSaCas9-KRAB-MeCP2(TRD) vector platform repressed robustly and sustainably the expression of multiple genes-of-interest, in vitro and in vivo, including ApoE, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD). Our platform broadens the CRISPR/dCas9 toolset available for transcriptional manipulation of gene expression in research and therapeutic settings., (© 2024. The Author(s).)
Published: 2024
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36. Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks.

Author: Shwab EK, Gingerich DC, Man Z, Gamache J, Garrett ME, Crawford GE, Ashley-Koch AE, Serrano GE, Beach TG, Lutz MW, and Chiba-Falek O
Subjects: Humans, Male, Female, alpha-Synuclein genetics, alpha-Synuclein metabolism, Aged, YY1 Transcription Factor genetics, YY1 Transcription Factor metabolism, Genome-Wide Association Study, Transcriptome, Single-Cell Analysis, Temporal Lobe metabolism, Temporal Lobe pathology, Middle Aged, Gene Expression Regulation genetics, Multiomics, Parkinson Disease genetics, Parkinson Disease metabolism, Parkinson Disease pathology, Neurons metabolism, Neurons pathology, Gene Regulatory Networks
Abstract: The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis., (© 2024. The Author(s).)
Published: 2024
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37. All-in-one AAV-delivered epigenome-editing platform: proof-of-concept and therapeutic implications for neurodegenerative disorders.

Author: Kantor B, Odonovan B, Rittiner J, Hodgson D, Lindner N, Guerrero S, Dong W, Zhang A, and Chiba-Falek O
Abstract: Safely and efficiently controlling gene expression is a long-standing goal of biomedical research, and the recently discovered bacterial CRISPR/Cas system can be harnessed to create powerful tools for epigenetic editing. Current state-of-the-art systems consist of a deactivated-Cas9 nuclease (dCas9) fused to one of several epigenetic effector motifs/domains, along with a guide RNA (gRNA) which defines the genomic target. Such systems have been used to safely and effectively silence or activate a specific gene target under a variety of circumstances. Adeno-associated vectors (AAVs) are the therapeutic platform of choice for the delivery of genetic cargo; however, their small packaging capacity is not suitable for delivery of large constructs, which includes most CRISPR/dCas9-effector systems. To circumvent this, many AAV-based CRISPR/Cas tools are delivered in two pieces, from two separate viral cassettes. However, this approach requires higher viral payloads and usually is less efficient. Here we develop a compact dCas9-based repressor system packaged within a single, optimized AAV vector. The system uses a smaller dCas9 variant derived from Staphylococcus aureus ( Sa ). A novel repressor was engineered by fusing the small transcription repression domain (TRD) from MeCP2 with the KRAB repression domain. The final d Sa Cas9-KRAB-MeCP2(TRD) construct can be efficiently packaged, along with its associated gRNA, into AAV particles. Using reporter assays, we demonstrate that the platform is capable of robustly and sustainably repressing the expression of multiple genes-of-interest, both in vitro and in vivo . Moreover, we successfully reduced the expression of ApoE, the stronger genetic risk factor for late onset Alzheimer's disease (LOAD). This new platform will broaden the CRISPR/dCas9 toolset available for transcriptional manipulation of gene expression in research and therapeutic settings.
Published: 2024
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38. Editorial: Amplifying Efficiency and Accuracy in Dementia Drug Development.

Author: Lerch O, Levine SZ, Sivakumaran S, Lutz MW, Chiba-Falek O, Mazer N, Bairu M, Hebold Haraldsen IRJ, Rossini PM, Snyder PJ, Bouteiller J, Khachaturian ZS, and Khachaturian AS
Subjects: Humans, Alzheimer Disease drug therapy, Drug Development, Dementia drug therapy
Abstract: Competing Interests: The authors are all members of the INDRC Scientific Advisory Board and have no relevant financial conflicts of interest to report.
Published: 2024
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39. Neuronal-type-specific epigenome editing to decrease SNCA expression: Implications for precision medicine in synucleinopathies.

Author: Sun Z, Kantor B, and Chiba-Falek O
Abstract: Overexpression of SNCA has been implicated in the pathogenesis of synucleinopathies, particularly Parkinson's disease (PD) and dementia with Lewy bodies (DLB). While PD and DLB share some clinical and pathological similarities, each disease presents distinct characteristics, including the primary affected brain region and neuronal type. We aimed to develop neuronal-type-specific SNCA -targeted epigenome therapies for synucleinopathies. The system is based on an all-in-one lentiviral vector comprised of CRISPR-d Sa Cas9 and guide RNA (gRNA) targeted at SNCA intron 1 fused with a synthetic repressor molecule of Krüppel-associated box (KRAB)/ methyl CpG binding protein 2 (MeCp2) transcription repression domain (TRD). To achieve neuronal-type specificity for dopaminergic and cholinergic neurons, the system was driven by tyrosine hydroxylase (TH) and choline acetyltransferase (ChAT) promoters, respectively. Delivering the system into human induced pluripotent stem cell (hiPSC)-derived dopaminergic and cholinergic neurons from a patient with the SNCA triplication resulted in efficient and neuronal-type-specific downregulation of SNCA -mRNA and protein. Furthermore, the reduction in SNCA levels by the gRNA-d Sa Cas9-repressor system rescued disease-related cellular phenotypes including Ser129-phophorylated α-synuclein, neuronal viability, and mitochondrial dysfunction. We established a novel neuronal-type-specific SNCA -targeted epigenome therapy and provided in vitro proof of concept using human-based disease models. Our results support the therapeutic potential of our system for PD and DLB and provide the foundation for further preclinical studies in animal models toward investigational new drug (IND) enablement and clinical trials., Competing Interests: Drs. Chiba-Falek and Kantor are inventors of intellectual property related to this research, and Duke University filed a patent application for the technology developed in this study. CLAIRIgene has an exclusive, worldwide option agreement from Duke for the related patent portfolio for all fields of use. Dr. Sun is a scientist at CLAIRIgene. Drs. Kantor and Chiba-Falek are co-founders at CLAIRIgene, LLC., (© 2023 The Authors.)
Published: 2023
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40. Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains.

Author: Gamache J, Gingerich D, Shwab EK, Barrera J, Garrett ME, Hume C, Crawford GE, Ashley-Koch AE, and Chiba-Falek O
Abstract: Background: The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD., Methods: Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs)., Results: Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes., Conclusions: To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD., (© 2023. Society of Chinese Bioscientists in America (SCBA).)
Published: 2023
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41. Bioinformatics pipeline to guide post-GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants.

Author: Lutz MW and Chiba-Falek O
Subjects: Humans, Genetic Predisposition to Disease genetics, Computational Biology, Genomics, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Alzheimer Disease genetics
Abstract: Background: Short structural variants (SSVs), including insertions/deletions (indels), are common in the human genome and impact disease risk. The role of SSVs in late-onset Alzheimer's disease (LOAD) has been understudied. In this study, we developed a bioinformatics pipeline of SSVs within LOAD-genome-wide association study (GWAS) regions to prioritize regulatory SSVs based on the strength of their predicted effect on transcription factor (TF) binding sites., Methods: The pipeline utilized publicly available functional genomics data sources including candidate cis-regulatory elements (cCREs) from ENCODE and single-nucleus (sn)RNA-seq data from LOAD patient samples., Results: We catalogued 1581 SSVs in candidate cCREs in LOAD GWAS regions that disrupted 737 TF sites. That included SSVs that disrupted the binding of RUNX3, SPI1, and SMAD3, within the APOE-TOMM40, SPI1, and MS4A6A LOAD regions., Conclusions: The pipeline developed here prioritized non-coding SSVs in cCREs and characterized their putative effects on TF binding. The approach integrates multiomics datasets for validation experiments using disease models., (© 2023 the Alzheimer's Association.)
Published: 2023
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42. The APOE-TOMM40 Humanized Mouse Model: Characterization of Age, Sex, and PolyT Variant Effects on Gene Expression.

Author: Gottschalk WK, Mahon S, Hodgson D, Barrera J, Hill D, Wei A, Kumar M, Dai K, Anderson L, Mihovilovic M, Lutz MW, and Chiba-Falek O
Subjects: Humans, Animals, Mice, Genotype, Phenotype, Introns, Gene Expression, Genetic Predisposition to Disease, Mitochondrial Precursor Protein Import Complex Proteins, Apolipoproteins E genetics, Alzheimer Disease genetics, Alzheimer Disease metabolism
Abstract: Background: The human chromosome 19q13.32 is a gene rich region and has been associated with multiple phenotypes, including late onset Alzheimer's disease (LOAD) and other age-related conditions., Objective: Here we developed the first humanized mouse model that contains the entire TOMM40 and APOE genes with all intronic and intergenic sequences including the upstream and downstream regions. Thus, the mouse model carries the human TOMM40 and APOE genes and their intact regulatory sequences., Methods: We generated the APOE-TOMM40 humanized mouse model in which the entire mouse region was replaced with the human (h)APOE-TOMM40 loci including their upstream and downstream flanking regulatory sequences using recombineering technologies. We then measured the expression of the human TOMM40 and APOE genes in the mice brain, liver, and spleen tissues using TaqMan based mRNA expression assays., Results: We investigated the effects of the '523' polyT genotype (S/S or VL/VL), sex, and age on the human TOMM40- and APOE-mRNAs expression levels using our new humanized mouse model. The analysis revealed tissue specific and shared effects of the '523' polyT genotype, sex, and age on the regulation of the human TOMM40 and APOE genes. Noteworthy, the regulatory effect of the '523' polyT genotype was observed for all studied organs., Conclusion: The model offers new opportunities for basic science, translational, and preclinical drug discovery studies focused on the APOE genomic region in relation to LOAD and other conditions in adulthood.
Published: 2023
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43. Differential Gene Expression and DNA Methylation in the Risk of Depression in LOAD Patients.

Author: Upadhya S, Gingerich D, Lutz MW, and Chiba-Falek O
Subjects: Female, Humans, Male, Chitinases genetics, Epigenesis, Genetic, Transcriptome, Alzheimer Disease complications, Alzheimer Disease genetics, Depression etiology, Depression genetics, DNA Methylation
Abstract: Depression is common among late-onset Alzheimer's Disease (LOAD) patients. Only a few studies investigated the genetic variability underlying the comorbidity of depression in LOAD. Moreover, the epigenetic and transcriptomic factors that may contribute to comorbid depression in LOAD have yet to be studied. Using transcriptomic and DNA-methylomic datasets from the ROSMAP cohorts, we investigated differential gene expression and DNA-methylation in LOAD patients with and without comorbid depression. Differential expression analysis did not reveal significant association between differences in gene expression and the risk of depression in LOAD. Upon sex-stratification, we identified 25 differential expressed genes (DEG) in males, of which CHI3L2 showed the strongest upregulation, and only 3 DEGs in females. Additionally, testing differences in DNA-methylation found significant hypomethylation of CpG (cg20442550) on chromosome 17 (log 2 FC = -0.500, p = 0.004). Sex-stratified differential DNA-methylation analysis did not identify any significant CpG probes. Integrating the transcriptomic and DNA-methylomic datasets did not discover relationships underlying the comorbidity of depression and LOAD. Overall, our study is the first multi-omics genome-wide exploration of the role of gene expression and epigenome alterations in the risk of comorbid depression in LOAD patients. Furthermore, we discovered sex-specific differences in gene expression underlying the risk of depression symptoms in LOAD.
Published: 2022
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44. Polygenic Risk Score Effectively Predicts Depression Onset in Alzheimer's Disease Based on Major Depressive Disorder Risk Variants.

Author: Upadhya S, Liu H, Luo S, Lutz MW, and Chiba-Falek O
Abstract: Introduction: Depression is a common, though heterogenous, comorbidity in late-onset Alzheimer's Disease (LOAD) patients. In addition, individuals with depression are at greater risk to develop LOAD. In previous work, we demonstrated shared genetic etiology between depression and LOAD. Collectively, these previous studies suggested interactions between depression and LOAD. However, the underpinning genetic heterogeneity of depression co-occurrence with LOAD, and the various genetic etiologies predisposing depression in LOAD, are largely unknown., Methods: Major Depressive Disorder (MDD) genome-wide association study (GWAS) summary statistics were used to create polygenic risk scores (PRS). The Religious Orders Society and Rush Memory and Aging Project (ROSMAP, n = 1,708) and National Alzheimer's Coordinating Center (NACC, n = 10,256) datasets served as discovery and validation cohorts, respectively, to assess the PRS performance in predicting depression onset in LOAD patients., Results: The PRS showed marginal results in standalone models for predicting depression onset in both ROSMAP (AUC = 0.540) and NACC (AUC = 0.527). Full models, with baseline age, sex, education, and APOEε4 allele count, showed improved prediction of depression onset (ROSMAP AUC: 0.606, NACC AUC: 0.581). In time-to-event analysis, standalone PRS models showed significant effects in ROSMAP ( P = 0.0051), but not in NACC cohort. Full models showed significant performance in predicting depression in LOAD for both datasets ( P < 0.001 for all)., Conclusion: This study provided new insights into the genetic factors contributing to depression onset in LOAD and advanced our knowledge of the genetics underlying the heterogeneity of depression in LOAD. The developed PRS accurately predicted LOAD patients with depressive symptoms, thus, has clinical implications including, diagnosis of LOAD patients at high-risk to develop depression for early anti-depressant treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Upadhya, Liu, Luo, Lutz and Chiba-Falek.)
Published: 2022
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45. Bioinformatics pipeline to guide late-onset Alzheimer's disease (LOAD) post-GWAS studies: Prioritizing transcription regulatory variants within LOAD-associated regions.

Author: Lutz MW and Chiba-Falek O
Abstract: Introduction: As new late-onset Alzheimer's disease (LOAD) genetic risk loci are identified and brain cell-type specific omics data becomes available, there is an unmet need for a bioinformatics framework to prioritize genes and variants for testing in single-cell molecular profiling experiments and validation using disease models and gene editing technologies. Prior work has characterized and prioritized active enhancers located in LOAD-genome-wide association study (GWAS) regions and their potential interactions with candidate genes. The current study extends this work by focusing on single nucleotide polymorphisms (SNPs) within these LOAD enhancers and their impact on altering transcription factor (TF) binding. The proposed bioinformatics pipeline progresses from SNPs located in LOAD-GWAS regions to a filtered set of candidate regulatory SNPs that have a predicted strong effect on TF binding., Methods: Active enhancers within LOAD-associated regions were identified and SNPs located in the enhancers were catalogued. SNPs that disrupt TF binding sites were prioritized and the respective TFs were filtered to include only those that were expressed in brain tissues relevant to LOAD. The TFs binding to the corresponding sequence was further confirmed by ChIP-seq signals. Finally, the high-priority candidate SNPs were evaluated as expression quantitative trait loci (eQTLs) in disease-relevant tissues., Results: We catalogued 61 strong enhancers in LOAD-GWAS regions encompassing 326 SNPs and 104 TF binding sites. Seventy-seven and 78 of the TFs were expressed in brain and monocytes, respectively, out of which 19 TF-binding sites showed ChIP-seq signals. Eleven SNPs were found to interrupt with TF binding out of which three SNPs were also significant eQTL., Discussion: This study provides a framework to catalogue noncoding variations in enhancers located in LOAD-GWAS loci and characterize their likelihood to perturb TF binding. The approach integrates multiple data types to characterize and prioritize SNPs for putative regulatory function using single-cell multi-omics assays and gene editing., Competing Interests: Grant funding for the past 36 months. Ornit Chiba‐Falek: 1. SRA 2020 Chiba‐Falek, Kantor (MPI) 08/26/2020 ‐ 02/25/2022 Seelos Therapeutics, 2. Kahn Neurodegeneration Award (Duke) Chiba‐Falek (PI), 3. 1RF1‐NS113548‐01A1 Chiba‐Falek (PI) National Institutes of Health, 4. R56‐AG062344 Chiba‐Falek (subaward PI) Wang, 5. 1R56‐AG062302 Lutz, Chiba‐Falek, Luo, Williamson National Institutes of Health/NIA, 6. 1R01‐AG057522 Chiba‐Falek, Lutz (MPI) National Institutes of Health/NIH. Michael W. Lutz: 1. R01AG057522 Chiba‐Falek (PI) National Institutes of Health, 2. RF1‐AG057895 Lutz (co‐PI) National Institutes of Health, 3. R01‐AG066184 Badea (PI) National Institutes of Health, 4. R01‐AG064803‐02 Luo (PI) National Institutes of Health, 5. P01‐AG031719 Vaupel (PI) National Institutes of Health, 6. R01‐ES024288 Plassman (PI) National Institutes of Health, 7. R56‐AG062302 Lutz (PI) National Institutes of Health. Dr. Chiba‐Falek is a consultant to Seelos Therapeutics. Dr. Lutz received consulting fees and travel expenses to attend scientific conferences from Zinfandel Pharmaceuticals. Dr. Chiba‐Falek reports filing a patent application: PCT/US2019/028786 entitled “Downregulation of SNCA Expression by Targeted Editing of DNA‐Methylation.”, (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)
Published: 2022
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46. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Author: Lam M, Chen CY, Ge T, Xia Y, Hill DW, Trampush JW, Yu J, Knowles E, Davies G, Stahl EA, Huckins L, Liewald DC, Djurovic S, Melle I, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Hartmann AM, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Chiba-Falek O, Koltai DC, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Smyrnis N, Bilder RM, Freimer NB, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Huang H, Liu C, Malhotra AK, and Lencz T
Subjects: Cognition, Genome-Wide Association Study, Humans, Transcriptome, Nootropic Agents, Schizophrenia drug therapy, Schizophrenia genetics
Abstract: Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing., (© 2021. The Author(s).)
Published: 2021
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47. Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer's disease brains.

Author: Barrera J, Song L, Gamache JE, Garrett ME, Safi A, Yun Y, Premasinghe I, Sprague D, Chipman D, Li J, Fradin H, Soldano K, Gordân R, Ashley-Koch AE, Crawford GE, and Chiba-Falek O
Subjects: Aged, Aged, 80 and over, Base Sequence, Binding Sites, Cell Fractionation methods, Cell Nucleus ultrastructure, Chromatin genetics, Datasets as Topic, Female, Flow Cytometry, Gene Expression, Gene Library, Genome-Wide Association Study, Humans, Male, Middle Aged, Neurons ultrastructure, Single-Cell Analysis, Temporal Lobe ultrastructure, Transcription Factors metabolism, Alzheimer Disease genetics, Chromatin ultrastructure, Neuroglia ultrastructure, Sex Characteristics
Abstract: Background: In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer's disease (LOAD) and translate the associations to causation., Methods: We conducted ATAC-seq profiling using NeuN sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner., Results: We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100 kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets., Conclusions: Using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci., (© 2021. The Author(s).)
Published: 2021
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48. Cell-Type Specific Changes in DNA Methylation of SNCA Intron 1 in Synucleinopathy Brains.

Author: Gu J, Barrera J, Yun Y, Murphy SK, Beach TG, Woltjer RL, Serrano GE, Kantor B, and Chiba-Falek O
Abstract: Parkinson's disease (PD) and dementia with Lewy body (DLB) are the most common synucleinopathies. SNCA gene is a major genetic risk factor for these diseases group, and dysregulation of its expression has been implicated in the genetic etiologies of several synucleinopathies. DNA methylation at CpG island (CGI) within SNCA intron 1 has been suggested as a regulatory mechanism of SNCA expression, and changes in methylation levels at this region were associated with PD and DLB. However, the role of DNA methylation in the regulation of SNCA expression in a cell-type specific manner and its contribution to the pathogenesis of PD and DLB remain poorly understood, and the data are conflicting. Here, we employed a bisulfite pyrosequencing technique to profile the DNA methylation across SNCA intron 1 CGI in PD and DLB compared to age- and sex-matched normal control subjects. We analyzed homogenates of bulk post-mortem frozen frontal cortex samples and a subset of neuronal and glia nuclei sorted by the fluorescence-activated nuclei sorting (FANS) method. Bulk brain tissues showed no significant difference in the overall DNA methylation across SNCA intron 1 CGI region between the neuropathological groups. Sorted neuronal nuclei from PD frontal cortex showed significant lower levels of DNA methylation at this region compared to normal controls, but no differences between DLB and control, while sorted glia nuclei exhibited trends of decreased overall DNA methylation in DLB only. In conclusion, our data suggested disease-dependent cell-type specific differential DNA methylation within SNCA intron 1 CGI. These changes may affect SNCA dysregulation that presumably mediates disease-specific risk. Our results can be translated into the development of the SNCA intron 1 CGI region as an attractive therapeutics target for gene therapy in patients who suffer from synucleinopathies due to SNCA dysregulation., Competing Interests: OC-F and BK are inventors of intellectual property PCT/US2019/028786 which is related to this research and is licensed to Seelos Therapeutics, Inc., Duke, the inventors, and Seelos Therapeutics, Inc., could potentially benefit from the outcome of this research if commercially successful. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Gu, Barrera, Yun, Murphy, Beach, Woltjer, Serrano, Kantor and Chiba-Falek.)
Published: 2021
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49. The Path to Progress Preclinical Studies of Age-Related Neurodegenerative Diseases: A Perspective on Rodent and hiPSC-Derived Models.

Author: MacDougall G, Brown LY, Kantor B, and Chiba-Falek O
Subjects: Animals, Humans, Rodentia, Alzheimer Disease therapy, Disease Models, Animal, Induced Pluripotent Stem Cells cytology, Parkinson Disease therapy, Stem Cell Transplantation methods
Abstract: Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most prevalent age-related neurodegenerative diseases, and currently no effective clinical treatments exist for either, despite decades of clinical trials. The failure to translate preclinical findings into effective treatments is indicative of a problem in the current evaluation pipeline for potential therapeutics. At present, there are no useful animal models for AD and PD research that reflect the entire biology of the diseases, specifically, the more common non-Mendelian forms. Whereas the field continues to seek suitable rodent models for investigating potential therapeutics for these diseases, rodent models have still been used primarily for preclinical studies. Here, we advocate for a paradigm shift toward the application of human-induced pluripotent stem cell (hiPSC)-derived systems for PD and AD modeling and the development of improved human-based models in a dish for drug discovery and preclinical assessment of therapeutic targets., Competing Interests: Declaration of Interests The authors have no competing interests., (Copyright © 2021 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)
Published: 2021
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50. APOE : The New Frontier in the Development of a Therapeutic Target towards Precision Medicine in Late-Onset Alzheimer's.

Author: Yang A, Kantor B, and Chiba-Falek O
Subjects: Age of Onset, Amyloid beta-Peptides genetics, Brain metabolism, Brain pathology, Humans, Molecular Targeted Therapy, Precision Medicine, Alzheimer Disease genetics, Alzheimer Disease therapy, Apolipoproteins E genetics, Genetic Predisposition to Disease
Abstract: Alzheimer's disease (AD) has a critical unmet medical need. The consensus around the amyloid cascade hypothesis has been guiding pre-clinical and clinical research to focus mainly on targeting beta-amyloid for treating AD. Nevertheless, the vast majority of the clinical trials have repeatedly failed, prompting the urgent need to refocus on other targets and shifting the paradigm of AD drug development towards precision medicine. One such emerging target is apolipoprotein E ( APOE ), identified nearly 30 years ago as one of the strongest and most reproduceable genetic risk factor for late-onset Alzheimer's disease (LOAD). An exploration of APOE as a new therapeutic culprit has produced some very encouraging results, proving that the protein holds promise in the context of LOAD therapies. Here, we review the strategies to target APOE based on state-of-the-art technologies such as antisense oligonucleotides, monoclonal antibodies, and gene/base editing. We discuss the potential of these initiatives in advancing the development of novel precision medicine therapies to LOAD.
Published: 2021
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