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375 results on '"Ossenkoppele, R."'

1. The behavioral variant of Alzheimer’s disease does not show a selective loss of Von Economo and phylogenetically related neurons in the anterior cingulate cortex

Author

Singleton, EH, Pijnenburg, YAL, Gami-Patel, P, Boon, BDC, Bouwman, F, Papma, JM, Seelaar, H, Scheltens, P, Grinberg, LT, Spina, S, Nana, AL, Rabinovici, GD, Seeley, WW, Ossenkoppele, R, and Dijkstra, AA

Subjects
Biomedical and Clinical Sciences, Acquired Cognitive Impairment, Brain Disorders, Dementia, Neurosciences, Neurodegenerative, Frontotemporal Dementia (FTD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Aetiology, Neurological, Alzheimer Disease, Frontotemporal Dementia, Frontotemporal Lobar Degeneration, Gyrus Cinguli, Humans, Neurons, Alzheimer's disease, Behavior, Frontotemporal dementia, Pathology, Von Economo Neurons, Alzheimer’s disease, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundThe neurobiological origins of the early and predominant behavioral changes seen in the behavioral variant of Alzheimer's disease (bvAD) remain unclear. A selective loss of Von Economo neurons (VENs) and phylogenetically related neurons have been observed in behavioral variant frontotemporal dementia (bvFTD) and several psychiatric diseases. Here, we assessed whether these specific neuronal populations show a selective loss in bvAD.MethodsVENs and GABA receptor subunit theta (GABRQ)-immunoreactive pyramidal neurons of the anterior cingulate cortex (ACC) were quantified in post-mortem tissue of patients with bvAD (n = 9) and compared to typical AD (tAD, n = 6), bvFTD due to frontotemporal lobar degeneration based on TDP-43 pathology (FTLD, n = 18) and controls (n = 13) using ANCOVAs adjusted for age and Bonferroni corrected. In addition, ratios of VENs and GABRQ-immunoreactive (GABRQ-ir) pyramidal neurons over all Layer 5 neurons were compared between groups to correct for overall Layer 5 neuronal loss.ResultsThe number of VENs or GABRQ-ir neurons did not differ significantly between bvAD (VENs: 26.0 ± 15.3, GABRQ-ir pyramidal: 260.4 ± 87.1) and tAD (VENs: 32.0 ± 18.1, p = 1.00, GABRQ-ir pyramidal: 349.8 ± 109.6, p = 0.38) and controls (VENs: 33.5 ± 20.3, p = 1.00, GABRQ-ir pyramidal: 339.4 ± 95.9, p = 0.37). Compared to bvFTD, patients with bvAD showed significantly more GABRQ-ir pyramidal neurons (bvFTD: 140.5 ± 82.658, p = 0.01) and no significant differences in number of VENs (bvFTD: 10.9 ± 13.8, p = 0.13). Results were similar when assessing the number of VENs and GABRQ-ir relative to all neurons of Layer 5.DiscussionVENs and phylogenetically related neurons did not show a selective loss in the ACC in patients with bvAD. Our results suggest that, unlike in bvFTD, the clinical presentation in bvAD may not be related to the loss of VENs and related neurons in the ACC.

Published
2022

2. Brain charts for the human lifespan

Author

Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., Astle, D. E., Auyeung, B., Ayub, M., Bae, J., Ball, G., Baron-Cohen, S., Beare, R., Bedford, S. A., Benegal, V., Beyer, F., Blangero, J., Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, A., Costantino, M., Courchesne, E., Crivello, F., Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, S., Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, G., Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galan-Garcia, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, D. C., Goodyer, I. M., Grant, P. E., Groenewold, N. A., Gunning, F. M., Gur, R. E., Gur, R. C., Hammill, C. F., Hansson, O., Hedden, T., Heinz, A., Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, A. J., Holt, R., Huang, H., Im, K., Ipser, J., Jack, Jr, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, D. T., Kahn, R. S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, S., Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, M. V., Lv, J., Lynch, C., Mallard, T. T., Marcelis, M., Markello, R. D., Mathias, S. R., Mazoyer, B., McGuire, P., Meaney, M. J., Mechelli, A., Medic, N., Misic, B., Morgan, S. E., Mothersill, D., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, R., Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, C., Park, M. M., Paus, T., Pausova, Z., Paz-Linares, D., Pichet Binette, A., Pierce, K., Qian, X., Qiu, J., Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero-Garcia, R., Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, T. D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, G., Schöll, M., Sharp, D., Shinohara, R. T., Skoog, I., Smyser, C. D., Sperling, R. A., Stein, D. J., Stolicyn, A., Suckling, J., Sullivan, G., Taki, Y., Thyreau, B., Toro, R., Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, S. L., van Amelsvoort, T., Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, A., Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, E., Westwater, M. L., Whalley, H. C., Witte, A. V., Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, A., Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.

Published
2022
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7. Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model.

Author

Leuzy, A, Raket, LL, Villemagne, VL, Klein, G, Tonietto, M, Olafson, E, Baker, S, Saad, ZS, Bullich, S, Lopresti, B, Bohorquez, SS, Boada, M, Betthauser, TJ, Charil, A, Collins, EC, Collins, JA, Cullen, N, Gunn, RN, Higuchi, M, Hostetler, E, Hutchison, RM, Iaccarino, L, Insel, PS, Irizarry, MC, Jack, CR, Jagust, WJ, Johnson, KA, Johnson, SC, Karten, Y, Marquié, M, Mathotaarachchi, S, Mintun, MA, Ossenkoppele, R, Pappas, I, Petersen, RC, Rabinovici, GD, Rosa-Neto, P, Schwarz, CG, Smith, R, Stephens, AW, Whittington, A, Carrillo, MC, Pontecorvo, MJ, Haeberlein, SB, Dunn, B, Kolb, HC, Sivakumaran, S, Rowe, CC, Hansson, O, Doré, V, Leuzy, A, Raket, LL, Villemagne, VL, Klein, G, Tonietto, M, Olafson, E, Baker, S, Saad, ZS, Bullich, S, Lopresti, B, Bohorquez, SS, Boada, M, Betthauser, TJ, Charil, A, Collins, EC, Collins, JA, Cullen, N, Gunn, RN, Higuchi, M, Hostetler, E, Hutchison, RM, Iaccarino, L, Insel, PS, Irizarry, MC, Jack, CR, Jagust, WJ, Johnson, KA, Johnson, SC, Karten, Y, Marquié, M, Mathotaarachchi, S, Mintun, MA, Ossenkoppele, R, Pappas, I, Petersen, RC, Rabinovici, GD, Rosa-Neto, P, Schwarz, CG, Smith, R, Stephens, AW, Whittington, A, Carrillo, MC, Pontecorvo, MJ, Haeberlein, SB, Dunn, B, Kolb, HC, Sivakumaran, S, Rowe, CC, Hansson, O, and Doré, V

Abstract

INTRODUCTION: Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS: Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS: A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION: Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification. HIGHLIGHTS: Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

Published
2024

9. Publisher Correction: Brain charts for the human lifespan

Author

Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., Astle, D. E., Auyeung, B., Ayub, M., Bae, J., Ball, G., Baron-Cohen, S., Beare, R., Bedford, S. A., Benegal, V., Beyer, F., Blangero, J., Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, A., Costantino, M., Courchesne, E., Crivello, F., Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, S., Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, G., Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galan-Garcia, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, D. C., Goodyer, I. M., Grant, P. E., Groenewold, N. A., Gunning, F. M., Gur, R. E., Gur, R. C., Hammill, C. F., Hansson, O., Hedden, T., Heinz, A., Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, A. J., Holt, R., Huang, H., Im, K., Ipser, J., Jack, Jr, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, D. T., Kahn, R. S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, S., Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, M. V., Lv, J., Lynch, C., Mallard, T. T., Marcelis, M., Markello, R. D., Mathias, S. R., Mazoyer, B., McGuire, P., Meaney, M. J., Mechelli, A., Medic, N., Misic, B., Morgan, S. E., Mothersill, D., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, R., Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, C., Park, M. M., Paus, T., Pausova, Z., Paz-Linares, D., Pichet Binette, A., Pierce, K., Qian, X., Qiu, J., Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero-Garcia, R., Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, T. D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, G., Schöll, M., Sharp, D., Shinohara, R. T., Skoog, I., Smyser, C. D., Sperling, R. A., Stein, D. J., Stolicyn, A., Suckling, J., Sullivan, G., Taki, Y., Thyreau, B., Toro, R., Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, S. L., van Amelsvoort, T., Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, A., Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, E., Westwater, M. L., Whalley, H. C., Witte, A. V., Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, A., Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.

Published
2022
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10. Tau, amyloid, and hypometabolism in a patient with posterior cortical atrophy

Author

Ossenkoppele, R, Schonhaut, DR, Baker, SL, O'Neil, JP, Janabi, M, Ghosh, PM, Santos, M, Miller, ZA, Bettcher, BM, Gorno-Tempini, ML, Miller, BL, Jagust, WJ, and Rabinovici, GD

Subjects
Neurology & Neurosurgery, Clinical Sciences, Neurosciences
Abstract

Determining the relative contribution of amyloid plaques and neurofibrillary tangles to brain dysfunction in Alzheimer disease is critical for therapeutic approaches, but until recently could only be assessed at autopsy. We report a patient with posterior cortical atrophy (visual variant of Alzheimer disease) who was studied using the novel tau tracer [18F]AV-1451 in conjunction with [11C]Pittsburgh compound B (PIB; amyloid) and [18F]fluorodeoxyglucose (FDG) positron emission tomography. Whereas [11C]PIB bound throughout association neocortex, [18F]AV-1451 was selectively retained in posterior brain regions that were affected clinically and showed markedly reduced [18F]FDG uptake. This provides preliminary in vivo evidence that tau is more closely linked to hypometabolism and symptomatology than amyloid.

Published
2015

12. Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

Author

Jansen, W.J., Janssen, O., Tijms, B.M., Vos, S.J.B., Ossenkoppele, R., Visser, P.J., Group, A.B.S., Aarsland, D., Alcolea, D., Altomare, D., Arnim, C. von, Baiardi, S., Baldeiras, I., Barthel, H., Bateman, R.J., Berckel, B. Van, Binette, A.P., Blennow, K., Boada, M., Boecker, H., Bottlaender, M., Braber, A., Brooks, D.J., Buchem, M.A. van, Camus, V., Carill, J.M., Cerman, J., Chen, K., Chételat, G., Chipi, E., Cohen, A.D., Daniels, A., Delarue, M., Didic, M., Drzezga, A., Dubois, B., Eckerström, M., Ekblad, L.L., Engelborghs, S., Epelbaum, S., Fagan, A.M., Fan, Y., Fladby, T., Fleisher, A.S., Flier, W.M. van der, Förster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Frings, L., Frisoni, G.B., Fröhlich, L., Gabryelewicz, T., Gertz, H.J., Gill, K.D., Gkatzima, O., Gómez-Tortosa, E., Grimmer, T., Guedj, E., Habeck, C.G., Hampel, H., Handels, R., Hansson, O., Hausner, L., Hellwig, S., Heneka, M.T., Herukka, S.K., Hildebrandt, H., Hodges, J., Hort, J., Huang, C.C., Iriondo, A.J., Itoh, Y., Ivanoiu, A., Jagust, W.J., Jessen, F., Johannsen, P., Johnson, K.A., Kandimalla, R., Kapaki, E.N., Kern, S., Kilander, L., Klimkowicz-Mrowiec, A., Klunk, W.E., Koglin, N., Kornhuber, J., Kramberger, M.G., Kuo, H.C., Laere, K. Van, Landau, S.M., Landeau, B., Lee, Dyantha I. van der, Leon, M., Leyton, C.E., Lin, K.J., Lleó, A., Löwenmark, M., Madsen, K., Maier, W., Marcusson, J., Olde Rikkert, M.G.M., Verbeek, M.M., Zboch, M., Zetterberg, H., Jansen, W.J., Janssen, O., Tijms, B.M., Vos, S.J.B., Ossenkoppele, R., Visser, P.J., Group, A.B.S., Aarsland, D., Alcolea, D., Altomare, D., Arnim, C. von, Baiardi, S., Baldeiras, I., Barthel, H., Bateman, R.J., Berckel, B. Van, Binette, A.P., Blennow, K., Boada, M., Boecker, H., Bottlaender, M., Braber, A., Brooks, D.J., Buchem, M.A. van, Camus, V., Carill, J.M., Cerman, J., Chen, K., Chételat, G., Chipi, E., Cohen, A.D., Daniels, A., Delarue, M., Didic, M., Drzezga, A., Dubois, B., Eckerström, M., Ekblad, L.L., Engelborghs, S., Epelbaum, S., Fagan, A.M., Fan, Y., Fladby, T., Fleisher, A.S., Flier, W.M. van der, Förster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Frings, L., Frisoni, G.B., Fröhlich, L., Gabryelewicz, T., Gertz, H.J., Gill, K.D., Gkatzima, O., Gómez-Tortosa, E., Grimmer, T., Guedj, E., Habeck, C.G., Hampel, H., Handels, R., Hansson, O., Hausner, L., Hellwig, S., Heneka, M.T., Herukka, S.K., Hildebrandt, H., Hodges, J., Hort, J., Huang, C.C., Iriondo, A.J., Itoh, Y., Ivanoiu, A., Jagust, W.J., Jessen, F., Johannsen, P., Johnson, K.A., Kandimalla, R., Kapaki, E.N., Kern, S., Kilander, L., Klimkowicz-Mrowiec, A., Klunk, W.E., Koglin, N., Kornhuber, J., Kramberger, M.G., Kuo, H.C., Laere, K. Van, Landau, S.M., Landeau, B., Lee, Dyantha I. van der, Leon, M., Leyton, C.E., Lin, K.J., Lleó, A., Löwenmark, M., Madsen, K., Maier, W., Marcusson, J., Olde Rikkert, M.G.M., Verbeek, M.M., Zboch, M., and Zetterberg, H.

Abstract

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Published
2022

13. Brain charts for the human lifespan

Author

Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, Paus, T, Pausova, Z, Paz-Linares, D, Pichet Binette, A, Pierce, K, Qian, X, Qiu, J, Qiu, A, Raznahan, A, Rittman, T, Rodrigue, A, Rollins, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, Alexander-Bloch, AF, Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, Paus, T, Pausova, Z, Paz-Linares, D, Pichet Binette, A, Pierce, K, Qian, X, Qiu, J, Qiu, A, Raznahan, A, Rittman, T, Rodrigue, A, Rollins, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, and Alexander-Bloch, AF

Abstract

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Published
2022

14. Risk of respiratory tract infections and serious infections in psoriasis patients treated with biologics: Results from the BioCAPTURE registry

Author

Schoot, L.S. van der, Groenewoud, H., Gelder, M.M.H.J. van, Otero, M.E., Peter Arnold, W., Berends, M.A.M., Bruin-Weller, M.S. de, Dodemont, S.R.P., Kleinpenning, M.M., Koetsier, M.I.A., Kop, E.N., Korver, J.E.M., Kuijpers, A.L.A., Lümig, P.P.M. van, Mommers, J.M., Njoo, M.D., Ossenkoppele, R., Tupker, R.A., Visch, M.B., Weppner-Parren, L., Jong, E.M.G.J. de, Reek, J.M.P.A. van den, Schoot, L.S. van der, Groenewoud, H., Gelder, M.M.H.J. van, Otero, M.E., Peter Arnold, W., Berends, M.A.M., Bruin-Weller, M.S. de, Dodemont, S.R.P., Kleinpenning, M.M., Koetsier, M.I.A., Kop, E.N., Korver, J.E.M., Kuijpers, A.L.A., Lümig, P.P.M. van, Mommers, J.M., Njoo, M.D., Ossenkoppele, R., Tupker, R.A., Visch, M.B., Weppner-Parren, L., Jong, E.M.G.J. de, and Reek, J.M.P.A. van den

Abstract

Item does not contain fulltext

Published
2022

15. Brain charts for the human lifespan (vol 604, pg 525, 2022)

Author

Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, Paus, T, Pausova, Z, Paz-Linares, D, Pichet Binette, A, Pierce, K, Qian, X, Qiu, J, Qiu, A, Raznahan, A, Rittman, T, Rodrigue, A, Rollins, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, Alexander-Bloch, AF, Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cabez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, Landeau, B, Lee, S, Lerch, J, Lewis, JD, Li, J, Liao, W, Liston, C, Lombardo, MV, Lv, J, Lynch, C, Mallard, TT, Marcelis, M, Markello, RD, Mathias, SR, Mazoyer, B, McGuire, P, Meaney, MJ, Mechelli, A, Medic, N, Misic, B, Morgan, SE, Mothersill, D, Nigg, J, Ong, MQW, Ortinau, C, Ossenkoppele, R, Ouyang, M, Palaniyappan, L, Paly, L, Pan, PM, Pantelis, C, Park, MM, Paus, T, Pausova, Z, Paz-Linares, D, Pichet Binette, A, Pierce, K, Qian, X, Qiu, J, Qiu, A, Raznahan, A, Rittman, T, Rodrigue, A, Rollins, CK, Romero-Garcia, R, Ronan, L, Rosenberg, MD, Rowitch, DH, Salum, GA, Satterthwaite, TD, Schaare, HL, Schachar, RJ, Schultz, AP, Schumann, G, Scholl, M, Sharp, D, Shinohara, RT, Skoog, I, Smyser, CD, Sperling, RA, Stein, DJ, Stolicyn, A, Suckling, J, Sullivan, G, Taki, Y, Thyreau, B, Toro, R, Traut, N, Tsvetanov, KA, Turk-Browne, NB, Tuulari, JJ, Tzourio, C, Vachon-Presseau, E, Valdes-Sosa, MJ, Valdes-Sosa, PA, Valk, SL, van Amelsvoort, T, Vandekar, SN, Vasung, L, Victoria, LW, Villeneuve, S, Villringer, A, Vertes, PE, Wagstyl, K, Wang, YS, Warfield, SK, Warrier, V, Westman, E, Westwater, ML, Whalley, HC, Witte, AV, Yang, N, Yeo, B, Yun, H, Zalesky, A, Zar, HJ, Zettergren, A, Zhou, JH, Ziauddeen, H, Zugman, A, Zuo, XN, Bullmore, ET, and Alexander-Bloch, AF

Published
2022

16. The behavioral variant of Alzheimer’s disease does not show a selective loss of Von Economo and phylogenetically related neurons in the anterior cingulate cortex

Author

Singleton, E. H., Pijnenburg, Y. A.L., Gami-Patel, P., Boon, B.D.C., Bouwman, F., Papma, J. M., Seelaar, H., Scheltens, P., Grinberg, L. T., Spina, S., Nana, A. L., Rabinovici, G. D., Seeley, W. W., Ossenkoppele, R., Dijkstra, A. A., Singleton, E. H., Pijnenburg, Y. A.L., Gami-Patel, P., Boon, B.D.C., Bouwman, F., Papma, J. M., Seelaar, H., Scheltens, P., Grinberg, L. T., Spina, S., Nana, A. L., Rabinovici, G. D., Seeley, W. W., Ossenkoppele, R., and Dijkstra, A. A.

Abstract

Background: The neurobiological origins of the early and predominant behavioral changes seen in the behavioral variant of Alzheimer’s disease (bvAD) remain unclear. A selective loss of Von Economo neurons (VENs) and phylogenetically related neurons have been observed in behavioral variant frontotemporal dementia (bvFTD) and several psychiatric diseases. Here, we assessed whether these specific neuronal populations show a selective loss in bvAD. Methods: VENs and GABA receptor subunit theta (GABRQ)-immunoreactive pyramidal neurons of the anterior cingulate cortex (ACC) were quantified in post-mortem tissue of patients with bvAD (n = 9) and compared to typical AD (tAD, n = 6), bvFTD due to frontotemporal lobar degeneration based on TDP-43 pathology (FTLD, n = 18) and controls (n = 13) using ANCOVAs adjusted for age and Bonferroni corrected. In addition, ratios of VENs and GABRQ-immunoreactive (GABRQ-ir) pyramidal neurons over all Layer 5 neurons were compared between groups to correct for overall Layer 5 neuronal loss. Results: The number of VENs or GABRQ-ir neurons did not differ significantly between bvAD (VENs: 26.0 ± 15.3, GABRQ-ir pyramidal: 260.4 ± 87.1) and tAD (VENs: 32.0 ± 18.1, p = 1.00, GABRQ-ir pyramidal: 349.8 ± 109.6, p = 0.38) and controls (VENs: 33.5 ± 20.3, p = 1.00, GABRQ-ir pyramidal: 339.4 ± 95.9, p = 0.37). Compared to bvFTD, patients with bvAD showed significantly more GABRQ-ir pyramidal neurons (bvFTD: 140.5 ± 82.658, p = 0.01) and no significant differences in number of VENs (bvFTD: 10.9 ± 13.8, p = 0.13). Results were similar when assessing the number of VENs and GABRQ-ir relative to all neurons of Layer 5. Discussion: VENs and phylogenetically related neurons did not show a selective loss in the ACC in patients with bvAD. Our results suggest that, unlike in bvFTD, the clinical presentation in bvAD may not be related to the loss of VENs and related neurons in the ACC.

Published
2022

17. Additional file 1 of The behavioral variant of Alzheimer���s disease does not show a selective loss of Von Economo and phylogenetically related neurons in the anterior cingulate cortex

Author

Singleton, E. H., Pijnenburg, Y. A. L., Gami-Patel, P., Boon, B. D. C., Bouwman, F., Papma, J. M., Seelaar, H., Scheltens, P., Grinberg, L. T., Spina, S., Nana, A. L., Rabinovici, G. D., Seeley, W. W., Ossenkoppele, R., and Dijkstra, A. A.

Subjects
Data_FILES
Abstract

Additional file 1.

Published
2022
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18. Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

Author

Jansen, WJ, Janssen, O, Tijms, BM, Vos, SJB, Ossenkoppele, R, Visser, PJ, Alcolea D., and Amyloid Biomarker Study Grp

Abstract

IMPORTANCE One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. OBJECTIVE To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. EXPOSURES Alzheimer disease biomarkers detected on PET or in CSF. MAIN OUTCOMES AND MEASURES Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. RESULTS Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PETand CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for dinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18). CONCLUSIONS AND RELEVANCE This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Published
2022

20. The behavioral variant of Alzheimer’s disease does not show a selective loss of Von Economo and phylogenetically related neurons in the anterior cingulate cortex

Author

Singleton, E.H., primary, Pijnenburg, Y.A.L, additional, Gami-Patel, P., additional, Boon, B.D.C., additional, Bouwman, F., additional, Papma, J., additional, Seelaar, H., additional, Scheltens, P., additional, Grinberg, L.T., additional, Spina, S., additional, Nana, A.L., additional, Rabinovici, G.D., additional, Seeley, W.W., additional, Ossenkoppele, R., additional, and Dijkstra, A.A., additional

Published
2021
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21. Provisional research criteria for the behavioral variant of Alzheimer’s disease A systematic review and meta-analysis

Author

Ossenkoppele, R., primary, Singleton, E.H., additional, Groot, C., additional, Dijkstra, Anke A., additional, Eikelboom, Willem S., additional, Seeley, William W., additional, Miller, Bruce, additional, Laforce, R., additional, Scheltens, P., additional, Papma, J.M., additional, Rabinovici, G.D., additional, and Pijnenburg, Y.A.L., additional

Published
2021
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22. Clinical validity of increased cortical uptake of [F-18]flortaucipir on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase biomarker development framework

Author

Wolters, E. E., Dodich, A., Boccardi, M., Corre, J., Drzezga, A., Hansson, O., Nordberg, A., Frisoni, G. B., Garibotto, V, Ossenkoppele, R., Wolters, E. E., Dodich, A., Boccardi, M., Corre, J., Drzezga, A., Hansson, O., Nordberg, A., Frisoni, G. B., Garibotto, V, and Ossenkoppele, R.

Abstract

Purpose In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [F-18]flortaucipir PET and define its research priorities. Methods The level of maturity of [F-18]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5). Results The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [F-18]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [F-18]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved. Conclusion Current literature provides partial evidence for clinical utility of [F-18]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.

Published
2021

24. Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance

Author

Stern, Y. Arenaza-Urquijo, E.M. Bartrés-Faz, D. Belleville, S. Cantilon, M. Chetelat, G. Ewers, M. Franzmeier, N. Kempermann, G. Kremen, W.S. Okonkwo, O. Scarmeas, N. Soldan, A. Udeh-Momoh, C. Valenzuela, M. Vemuri, P. Vuoksimaa, E. Urquiljo, E.M.A. Cantillon, M. Clouston, A.A.P. Estanga, A. Gold, B. Habeck, C. Jones, R. Kochhann, R. Lim, Y.Y. Martínez-Lage, P. Morbelli, S. Okonkwo, O. Ossenkoppele, R. Pettigrew, C. Rosen, A.C. Song, X. Van Loenhoud, A.C. and the Reserve, Resilience Protective Factors PIA Empirical Definitions Conceptual Frameworks Workgroup

Abstract

Several concepts, which in the aggregate get might be used to account for “resilience” against age- and disease-related changes, have been the subject of much research. These include brain reserve, cognitive reserve, and brain maintenance. However, different investigators have use these terms in different ways, and there has never been an attempt to arrive at consensus on the definition of these concepts. Furthermore, there has been confusion regarding the measurement of these constructs and the appropriate ways to apply them to research. Therefore the reserve, resilience, and protective factors professional interest area, established under the auspices of the Alzheimer's Association, established a whitepaper workgroup to develop consensus definitions for cognitive reserve, brain reserve, and brain maintenance. The workgroup also evaluated measures that have been used to implement these concepts in research settings and developed guidelines for research that explores or utilizes these concepts. The workgroup hopes that this whitepaper will form a reference point for researchers in this area and facilitate research by supplying a common language. © 2019 the Alzheimer's Association

Published
2020

25. Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance

Author

Stern, Y., Arenaza-Urquijo, E. M., Bartres-Faz, D., Belleville, S., Cantilon, M., Chetelat, G., Ewers, M., Franzmeier, N., Kempermann, G., Kremen, W. S., Okonkwo, O., Scarmeas, N., Soldan, A., Udeh-Momoh, C., Valenzuela, M., Vemuri, P., Vuoksimaa, E., Arenaza Urquiljo, E. M., Cantillon, M., Clouston, S. A. P., Estanga, A., Gold, B., Habeck, C., Jones, R., Kochhann, R., Kremen, W., Lim, Y. Y., Martinez-Lage, P., Morbelli, S., Ossenkoppele, R., Pettigrew, C., Rosen, A. C., Song, X., and Van Loenhoud, A. C.

Subjects
Aging, Knowledge management, Epidemiology, media_common.quotation_subject, Structural imaging, Guidelines as Topic, 050105 experimental psychology, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, physiology [Brain], Cognition, Developmental Neuroscience, Cognitive Reserve, Alzheimer Disease, medicine, Humans, 0501 psychology and cognitive sciences, ddc:610, Alzheimer's disease, Functional imaging, Workgroup, media_common, Cognitive reserve, Confusion, business.industry, Health Policy, 05 social sciences, Brain, standards [Guidelines as Topic], physiology [Aging], Psychiatry and Mental health, Research Design, Neurology (clinical), Psychological resilience, Geriatrics and Gerontology, medicine.symptom, business, Psychology, 030217 neurology & neurosurgery
Abstract

Several concepts, which in the aggregate get might be used to account for "resilience" against age- and disease-related changes, have been the subject of much research. These include brain reserve, cognitive reserve, and brain maintenance. However, different investigators have use these terms in different ways, and there has never been an attempt to arrive at consensus on the definition of these concepts. Furthermore, there has been confusion regarding the measurement of these constructs and the appropriate ways to apply them to research. Therefore the reserve, resilience, and protective factors professional interest area, established under the auspices of the Alzheimer's Association, established a whitepaper workgroup to develop consensus definitions for cognitive reserve, brain reserve, and brain maintenance. The workgroup also evaluated measures that have been used to implement these concepts in research settings and developed guidelines for research that explores or utilizes these concepts. The workgroup hopes that this whitepaper will form a reference point for researchers in this area and facilitate research by supplying a common language.

Published
2020
Full Text
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26. Amyloid-PET and (18)F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias

Author

Chetelat, G., Arbizu, J., Barthel, H., Garibotto, V., Law, I., Morbelli, S., Giessen, E. van de, Agosta, F., Barkhof, F., Brooks, D.J., Carrillo, M.C., Dubois, B., Fjell, A.M., Frisoni, G.B., Hansson, O., Herholz, K., Hutton, B.F., Jack, C.R., Jr., Lammertsma, A.A., Landau, S.M., Minoshima, S., Nobili, F., Nordberg, A., Ossenkoppele, R., Oyen, W.J.G., Perani, D., Rabinovici, G.D., Scheltens, P., Villemagne, V.L., Zetterberg, H., Drzezga, A., Chetelat, G., Arbizu, J., Barthel, H., Garibotto, V., Law, I., Morbelli, S., Giessen, E. van de, Agosta, F., Barkhof, F., Brooks, D.J., Carrillo, M.C., Dubois, B., Fjell, A.M., Frisoni, G.B., Hansson, O., Herholz, K., Hutton, B.F., Jack, C.R., Jr., Lammertsma, A.A., Landau, S.M., Minoshima, S., Nobili, F., Nordberg, A., Ossenkoppele, R., Oyen, W.J.G., Perani, D., Rabinovici, G.D., Scheltens, P., Villemagne, V.L., Zetterberg, H., and Drzezga, A.

Abstract

Contains fulltext : 229556.pdf (Publisher’s version ) (Closed access), Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and (18)F-fluorodeoxyglucose ((18)F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and (18)F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.

Published
2020

27. Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

Author

Singleton, E.H., Pijnenburg, YA, Sudre, C.H., de Groot, C., Kochova, E., Barkhof, F. (Frederik), La Joie, R., Rosen, H.J., Seeley, WW, Miller, B., Cardoso, MJ, Papma, J., Scheltens, P. (Philip), Rabinovici, G.D., Ossenkoppele, R. (Rik), Singleton, E.H., Pijnenburg, YA, Sudre, C.H., de Groot, C., Kochova, E., Barkhof, F. (Frederik), La Joie, R., Rosen, H.J., Seeley, WW, Miller, B., Cardoso, MJ, Papma, J., Scheltens, P. (Philip), Rabinovici, G.D., and Ossenkoppele, R. (Rik)

Abstract

Background: We previously found temporoparietal-predominant atrophy patterns in the behavioral variant of Alzheimer’s disease (bvAD), with relative sparing of frontal regions. Here, we aimed to understand the clinicoanatomical dissociation in bvAD based on alternative neuroimaging markers. Methods: We retrospectively included 150 participants, including 29 bvAD, 28 “typical” amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other diagnostic groups on glucose metabolism and metabolic connectivity measured by [18F]FDG-PET, and on subcortical gray matter and white matt

Published
2020
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28. Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

Author

Singleton, EH, Pijnenburg, YA, Sudre, CH, Groot, C, Kochova, E, Barkhof, F, La Joie, R, Rosen, HJ, Seeley, WW, Miller, B, Cardoso, MJ, Papma, Janne, Scheltens, P, Rabinovici, GD, Ossenkoppele, R, Singleton, EH, Pijnenburg, YA, Sudre, CH, Groot, C, Kochova, E, Barkhof, F, La Joie, R, Rosen, HJ, Seeley, WW, Miller, B, Cardoso, MJ, Papma, Janne, Scheltens, P, Rabinovici, GD, and Ossenkoppele, R

Published
2020

29. Tau PET and relative cerebral blood flow in dementia with Lewy bodies: A PET study

Author

Wolters, E.E., primary, van de Beek, M., additional, Ossenkoppele, R., additional, Golla, S.S.V., additional, Verfaillie, S.C.J., additional, Coomans, E.M., additional, Timmers, T, additional, Visser, D., additional, Tuncel, H., additional, Barkhof, F., additional, Boellaard, R., additional, Windhorst, A.D., additional, van der Flier, W.M., additional, Scheltens, Ph., additional, Lemstra, A.W., additional, and van Berckel, B.N.M., additional

Published
2020
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30. Amyloid and tau PET relate to memory loss in cognitively normal individuals: the SCIENCe project

Author

Wolters, E., Timmers, T., Ossenkoppele, R., Verfaillie, S. C. J., Visser, D., Scheltens, P., Schmidt, M. E., van den Bosch, K., Boellaard, R., Golla, S. S. V., van der Flier, W. M., van Berckel, B. N. M., Neurology, Radiology and nuclear medicine, Amsterdam Neuroscience - Neurodegeneration, Ethics, Law & Medical humanities, Amsterdam Neuroscience - Brain Imaging, APH - Personalized Medicine, APH - Methodology, Epidemiology and Data Science, and ACS - Heart failure & arrhythmias

Published
2019

31. Mechanisms underlying resilience in ageing

Author

Stern, Y. Chételat, G. Habeck, C. Arenaza-Urquijo, E.M. Vemuri, P. Estanga, A. Bartrés-Faz, D. Cantillon, M. Clouston, S.A.P. Elman, J.A. Gold, B.T. Jones, R. Kempermann, G. Lim, Y.Y. van Loenhoud, A. Martínez-Lage, P. Morbelli, S. Okonkwo, O. Ossenkoppele, R. Pettigrew, C. Rosen, A.C. Scarmeas, N. Soldan, A. Udeh-Momoh, C. Valenzuela, M. Vuoksimaa, E.

Published
2019

32. Early recognition and treatment of neuropsychiatric symptoms to improve quality of life in early Alzheimer's disease

Author

Eikelboom, W.S. (Willem), Singleton, E. (Ellen), Berg, E. (Esther) van den, Coesmans, M.P.H. (Michiel), Mattace Raso, F.U.S. (Francesco), Van Bruchem, R.L. (Rozemarijn), Goudzwaard, J.A. (Jeannette), De Jong, F.J. (Frank J.), Koopmanschap, M.A. (Marc), Heijer, T. (Tom) den, Driesen, J.J.M. (Jan), Vroegindeweij, L.J.H.M. (Lilian), Thomeer, E.C. (Elsbeth), Hoogers, S.E. (Susanne), Dijkstra, A.A. (Anke), Zuidema, S.U. (Sytse), Pijnenburg, Y.A.L. (Yolande), Scheltens, P. (Philip), Swieten, J.C. (John) van, Ossenkoppele, R. (Rik), Papma, J.M. (Janne), Eikelboom, W.S. (Willem), Singleton, E. (Ellen), Berg, E. (Esther) van den, Coesmans, M.P.H. (Michiel), Mattace Raso, F.U.S. (Francesco), Van Bruchem, R.L. (Rozemarijn), Goudzwaard, J.A. (Jeannette), De Jong, F.J. (Frank J.), Koopmanschap, M.A. (Marc), Heijer, T. (Tom) den, Driesen, J.J.M. (Jan), Vroegindeweij, L.J.H.M. (Lilian), Thomeer, E.C. (Elsbeth), Hoogers, S.E. (Susanne), Dijkstra, A.A. (Anke), Zuidema, S.U. (Sytse), Pijnenburg, Y.A.L. (Yolande), Scheltens, P. (Philip), Swieten, J.C. (John) van, Ossenkoppele, R. (Rik), and Papma, J.M. (Janne)

Abstract

__Background:__ Neuropsychiatric symptoms (NPS) are very common in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and are associated with various disadvantageous clinical outcomes including a negative impact on quality of life, caregiver burden, and accelerated disease progression. Despite growing evidence of the efficacy of (non)pharmacological interventions to reduce these symptoms, NPS remain underrecognized and undertreated in memory clinics. The BEhavioural symptoms in Alzheimer's disease Towards early Identification and Treatment (BEAT-IT) study is developed to (1) investigate the neurobiological etiology of NPS in AD and (2) study the effectiveness of the Describe, Investigate, Create, Evaluate (DICE) approach to structure and standardize the current care of NPS in AD. By means of the DICE method, we aim to improve the quality of life of AD patients with NPS and their caregivers who visit the memory clinic. This paper describes the protocol for the intervention study that incorporates the latter aim. __Methods:__ We aim to enroll a total of 150 community-dwelling patients with MCI or AD and their caregivers in two waves. First, we will recruit a control group who will receive care as usual. Next, the second wave of participants will undergo the DICE method. This approach consists of the following steps: (1) describe the context in which NPS occur, (2) investigate the possible causes, (3) create and implement a treatment pla

Published
2019
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33. Early recognition and treatment of neuropsychiatric symptoms to improve quality of life in early Alzheimer's disease: protocol of the BEAT-IT study

Author

Eikelboom, Willem, Singleton, E, van den Berg, Esther, Coesmans, Michiel, Mattace Raso, F.U.S., Van Bruchem - Visser, Rozemarijn, Goudzwaard, Jeannette, de Jong, Frank jan, Koopmanschap, Marc, den Heijer, T, Driesen, JJM, Vroegindeweij, L, Thomeer, EC, Hoogers, SE, Dijkstra, AA, Zuidema, SU, Pijnenburg, YAL, Scheltens, P, van Swieten, J.C., Ossenkoppele, R, Papma, Janne, Eikelboom, Willem, Singleton, E, van den Berg, Esther, Coesmans, Michiel, Mattace Raso, F.U.S., Van Bruchem - Visser, Rozemarijn, Goudzwaard, Jeannette, de Jong, Frank jan, Koopmanschap, Marc, den Heijer, T, Driesen, JJM, Vroegindeweij, L, Thomeer, EC, Hoogers, SE, Dijkstra, AA, Zuidema, SU, Pijnenburg, YAL, Scheltens, P, van Swieten, J.C., Ossenkoppele, R, and Papma, Janne

Published
2019

34. Association of cerebral amyloid-β Aggregation with cognitive functioning in persons without dementia

Author

Jansen, WJ, Ossenkoppele, R, Tijms, BM, Fagan, AM, Hansson, O, Klunk, WE, Van Der Flier, WM, Villemagne, VL, Frisoni, GB, Fleisher, AS, Lleó, A, Mintun, MA, Wallin, A, Engelborghs, S, Na, DL, Chételat, G, Molinuevo, JL, Landau, SM, Mattsson, N, Kornhuber, J, Sabri, O, Rowe, CC, Parnetti, L, Popp, J, Fladby, T, Jagust, WJ, Aalten, P, Lee, DY, Vandenberghe, R, De Oliveira, CR, Kapaki, E, Froelich, L, Ivanoiu, A, Gabryelewicz, T, Verbeek, MM, Sanchez-Juan, P, Hildebrandt, H, Camus, V, Zboch, M, Brooks, DJ, Drzezga, A, Rinne, JO, Newberg, A, De Mendonça, A, Sarazin, M, Rabinovici, GD, Madsen, K, Kramberger, MG, Nordberg, A, Mok, V, Mroczko, B, Wolk, DA, Meyer, PT, Tsolaki, M, Scheltens, P, Verhey, FRJ, Visser, PJ, Aarsland, D, Alcolea, D, Alexander, M, Almdahl, IS, Arnold, SE, Baldeiras, I, Barthel, H, Van Berckel, BNM, Blennow, K, Van Buchem, MA, Cavedo, E, Chen, K, Chipi, E, Cohen, AD, Förster, S, Fortea, J, Frederiksen, KS, Freund-Levi, Y, Gkatzima, O, Gordon, MF, Grimmer, T, Hampel, H, Hausner, L, Hellwig, S, Herukka, SK, Johannsen, P, Klimkowicz-Mrowiec, A, Köhler, S, and Koglin, N

Subjects
mental disorders
Abstract

IMPORTANCE Cerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. OBJECTIVE To investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. MAIN OUTCOMES AND MEASURES Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype. RESULTS Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4%[95%CI, 0%-7%] at 72 years and 21% [95%CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3%[95%CI, -1%to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16%[95%CI, 12%-20%], P < .001) and low MMSE (mean difference, 14%[95%CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years. CONCLUSIONS AND RELEVANCE Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited.

Published
2018
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35. Association of Cerebral Amyloid-beta Aggregation With Cognitive Functioning in Persons Without Dementia

Author

Jansen, WJ, Ossenkoppele, R, Tijms, BM, Fagan, AM, Hansson, O, Klunk, WE, van der Flier, WM, Villemagne, VL, Frisoni, GB, Fleisher, AS, Lleo, A, Mintun, MA, Wallin, A, Engelborghs, S, Na, DL, Chetelat, G, Molinuevo, JL, Landau, SM, Mattsson, N, Kornhuber, J, Sabri, O, Rowe, CC, Parnetti, L, Popp, J, Fladby, T, Jagust, WJ, Aalten, P, Lee, DY, Vandenberghe, R, de Oliveira, CR, Kapaki, E, Froelich, L, Ivanoiu, A, Gabryelewicz, T, Verbeek, MM, Sanchez-Juan, P, Hildebrandt, H, Camus, V, Zboch, M, Brooks, DJ, Drzezga, A, Rinne, JO, Newberg, A, de Mendonca, A, Sarazin, M, Rabinovici, GD, Madsen, K, Kramberger, MG, Nordberg, A, Mok, V, Mroczko, B, Wolk, DA, Meyer, PT, Tsolaki, M, Scheltens, P, Verhey, FRJ, Visser, PJ, and Amyloid Biomarker Study Grp

Subjects
mental disorders
Abstract

IMPORTANCE Cerebral amyloid-beta aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. OBJECTIVE To investigate whether amyloid-beta aggregation is associated with cognitive functioning in persons without dementia. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. MAIN OUTCOMES AND MEASURES Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score

Published
2018

36. Association of cerebral amyloid-β Aggregation with cognitive functioning in persons without dementia

Author

Jansen, W.J. Ossenkoppele, R. Tijms, B.M. Fagan, A.M. Hansson, O. Klunk, W.E. Van Der Flier, W.M. Villemagne, V.L. Frisoni, G.B. Fleisher, A.S. Lleó, A. Mintun, M.A. Wallin, A. Engelborghs, S. Na, D.L. Chételat, G. Molinuevo, J.L. Landau, S.M. Mattsson, N. Kornhuber, J. Sabri, O. Rowe, C.C. Parnetti, L. Popp, J. Fladby, T. Jagust, W.J. Aalten, P. Lee, D.Y. Vandenberghe, R. De Oliveira, C.R. Kapaki, E. Froelich, L. Ivanoiu, A. Gabryelewicz, T. Verbeek, M.M. Sanchez-Juan, P. Hildebrandt, H. Camus, V. Zboch, M. Brooks, D.J. Drzezga, A. Rinne, J.O. Newberg, A. De Mendonça, A. Sarazin, M. Rabinovici, G.D. Madsen, K. Kramberger, M.G. Nordberg, A. Mok, V. Mroczko, B. Wolk, D.A. Meyer, P.T. Tsolaki, M. Scheltens, P. Verhey, F.R.J. Visser, P.J. Aarsland, D. Alcolea, D. Alexander, M. Almdahl, I.S. Arnold, S.E. Baldeiras, I. Barthel, H. Van Berckel, B.N.M. Blennow, K. Van Buchem, M.A. Cavedo, E. Chen, K. Chipi, E. Cohen, A.D. Förster, S. Fortea, J. Frederiksen, K.S. Freund-Levi, Y. Gkatzima, O. Gordon, M.F. Grimmer, T. Hampel, H. Hausner, L. Hellwig, S. Herukka, S.-K. Johannsen, P. Klimkowicz-Mrowiec, A. Köhler, S. Koglin, N. Van Laere, K. De Leon, M. Lisetti, V. Maier, W. Marcusson, J. Meulenbroek, O. Møllergård, H.M. Morris, J.C. Nordlund, A. Novak, G.P. Paraskevas, G.P. Perera, G. Peters, O. Ramakers, I.H.G.B. Rami, L. Rodríguez-Rodríguez, E. Roe, C.M. Rot, U. Rüther, E. Santana, I. Schröder, J. Seo, S.W. Sorininen, H. Spiru, L. Stomrud, E. Struyfs, H. Teunissen, C.E. Vos, S.J.B. Van Waalwijk Van Doorn, L.J.C. Waldemar, G. Wallin, Å.K. Wiltfang, J. Zetterberg, H. Amyloid Biomarker Study Group

Subjects
mental disorders
Abstract

IMPORTANCE Cerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. OBJECTIVE To investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. MAIN OUTCOMES AND MEASURES Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype. RESULTS Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4%[95%CI, 0%-7%] at 72 years and 21% [95%CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3%[95%CI, -1%to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16%[95%CI, 12%-20%], P < .001) and low MMSE (mean difference, 14%[95%CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years. CONCLUSIONS AND RELEVANCE Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited.

Published
2018

40. Prevalence of the apolipoprotein E epsilon4 allele in amyloid beta positive subjects across the spectrum of Alzheimer's disease

Author

Mattsson, N., Groot, C. de, Jansen, W.J., Landau, S.M., Villemagne, V.L., Engelborghs, S., Mintun, M.M., Lleo, A., Molinuevo, J.L., Jagust, W.J., Frisoni, G.B., Ivanoiu, A., Chetelat, G., Oliveira, C. de, Rodrigue, K.M., Kornhuber, J., Wallin, A., Klimkowicz-Mrowiec, A., Kandimalla, R., Popp, J., Aalten, P.P., Aarsland, D., Alcolea, D., Almdahl, I.S., Baldeiras, I., Buchem, M.A. van, Cavedo, E., Chen, K., Cohen, A.D., Forster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Gill, K.D., Gkatzima, O., Grimmer, T., Hampel, H., Herukka, S.K., Johannsen, P., Laere, K. Van, Leon, M.J. de, Maier, W., Marcusson, J., Meulenbroek, O.V., Mollergard, H.M., Morris, J.C., Mroczko, B., Nordlund, A., Prabhakar, S., Peters, O., Rami, L., Rodriguez-Rodriguez, E., Roe, C.M., Ruther, E., Santana, I., Schroder, J., Seo, S.W., Soininen, H., Spiru, L., Stomrud, E., Struyfs, H., Teunissen, C.E., Verhey, F.R.J., Vos, S.J.B., Waalwijk van Doorn, L.L.C. van, Waldemar, G., Wallin, A.K., Wiltfang, J., Vandenberghe, R., Brooks, D.J., Fladby, T., Rowe, C.C., Drzezga, A., Verbeek, M.M., Sarazin, M., Wolk, D.A., Fleisher, A.S., Klunk, W.E., Na, D.L., Sanchez-Juan, P., Lee, D.Y., Nordberg, A., Tsolaki, M., Camus, V., Rinne, J.O., Fagan, A.M., Zetterberg, H., Blennow, K., Rabinovici, G.D., Hansson, O., Berckel, B.N. van, Flier, W.M. van der, Scheltens, P., Visser, P.J., Ossenkoppele, R., Mattsson, N., Groot, C. de, Jansen, W.J., Landau, S.M., Villemagne, V.L., Engelborghs, S., Mintun, M.M., Lleo, A., Molinuevo, J.L., Jagust, W.J., Frisoni, G.B., Ivanoiu, A., Chetelat, G., Oliveira, C. de, Rodrigue, K.M., Kornhuber, J., Wallin, A., Klimkowicz-Mrowiec, A., Kandimalla, R., Popp, J., Aalten, P.P., Aarsland, D., Alcolea, D., Almdahl, I.S., Baldeiras, I., Buchem, M.A. van, Cavedo, E., Chen, K., Cohen, A.D., Forster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Gill, K.D., Gkatzima, O., Grimmer, T., Hampel, H., Herukka, S.K., Johannsen, P., Laere, K. Van, Leon, M.J. de, Maier, W., Marcusson, J., Meulenbroek, O.V., Mollergard, H.M., Morris, J.C., Mroczko, B., Nordlund, A., Prabhakar, S., Peters, O., Rami, L., Rodriguez-Rodriguez, E., Roe, C.M., Ruther, E., Santana, I., Schroder, J., Seo, S.W., Soininen, H., Spiru, L., Stomrud, E., Struyfs, H., Teunissen, C.E., Verhey, F.R.J., Vos, S.J.B., Waalwijk van Doorn, L.L.C. van, Waldemar, G., Wallin, A.K., Wiltfang, J., Vandenberghe, R., Brooks, D.J., Fladby, T., Rowe, C.C., Drzezga, A., Verbeek, M.M., Sarazin, M., Wolk, D.A., Fleisher, A.S., Klunk, W.E., Na, D.L., Sanchez-Juan, P., Lee, D.Y., Nordberg, A., Tsolaki, M., Camus, V., Rinne, J.O., Fagan, A.M., Zetterberg, H., Blennow, K., Rabinovici, G.D., Hansson, O., Berckel, B.N. van, Flier, W.M. van der, Scheltens, P., Visser, P.J., and Ossenkoppele, R.

Abstract

Item does not contain fulltext, INTRODUCTION: Apolipoprotein E (APOE) epsilon4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta (Abeta) pathology. METHODS: We included 3451 Abeta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon4 prevalence in relation to age, sex, education, and geographical location. RESULTS: The APOE epsilon4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Abeta+ cognitively normal and Abeta+ mild cognitive impairment (P < .05) but not in Abeta+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education. DISCUSSION: The APOE epsilon4 prevalence in AD was higher than that in previous studies, which did not require presence of Abeta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.

Published
2018

41. Association of Cerebral Amyloid-beta Aggregation With Cognitive Functioning in Persons Without Dementia

Author

Jansen, W.J., Ossenkoppele, R., Tijms, B.M., Fagan, A.M., Hansson, O., Klunk, W.E., Flier, W.M. van der, Villemagne, V.L., Frisoni, G.B., Fleisher, A.S., Lleo, A., Mintun, M.A., Wallin, A., Engelborghs, S., Na, D.L., Chetelat, G., Molinuevo, J.L., Landau, S.M., Mattsson, N., Kornhuber, J., Sabri, O., Rowe, C.C., Parnetti, L., Popp, J., Fladby, T., Jagust, W.J., Aalten, P., Lee, D.Y., Vandenberghe, R., Oliveira, C. de, Kapaki, E., Froelich, L., Ivanoiu, A., Gabryelewicz, T., Verbeek, M.M., Sanchez-Juan, P., Hildebrandt, H., Camus, V., Zboch, M., Brooks, D.J., Drzezga, A., Rinne, J.O., Newberg, A., Mendonca, A. de, Sarazin, M., Rabinovici, G.D., Madsen, K., Kramberger, M.G., Nordberg, A., Mok, V., Mroczko, B., Wolk, D.A., Meyer, P.T., Tsolaki, M., Scheltens, P., Verhey, F.R.J., Visser, P.J., Aarsland, D., Alcolea, D., Alexander, M., Almdahl, I.S., Arnold, S.E., Baldeiras, I., Barthel, H., Berckel, B.N. van, Blennow, K., Buchem, M.A. van, Cavedo, E., Chen, K., Chipi, E., Cohen, A.D., Forster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Gkatzima, O., Gordon, M.F., Grimmer, T., Hampel, H., Hausner, L., Hellwig, S., Herukka, S.K., Johannsen, P., Klimkowicz-Mrowiec, A., Kohler, S., Koglin, N., Laere, K. Van, Leon, M., Lisetti, V., Maier, W., Marcusson, J., Meulenbroek, O., Mollergard, H.M., Morris, J.C., Nordlund, A., Novak, G.P., Paraskevas, G.P., Perera, G., Peters, O., Ramakers, I., et al., Jansen, W.J., Ossenkoppele, R., Tijms, B.M., Fagan, A.M., Hansson, O., Klunk, W.E., Flier, W.M. van der, Villemagne, V.L., Frisoni, G.B., Fleisher, A.S., Lleo, A., Mintun, M.A., Wallin, A., Engelborghs, S., Na, D.L., Chetelat, G., Molinuevo, J.L., Landau, S.M., Mattsson, N., Kornhuber, J., Sabri, O., Rowe, C.C., Parnetti, L., Popp, J., Fladby, T., Jagust, W.J., Aalten, P., Lee, D.Y., Vandenberghe, R., Oliveira, C. de, Kapaki, E., Froelich, L., Ivanoiu, A., Gabryelewicz, T., Verbeek, M.M., Sanchez-Juan, P., Hildebrandt, H., Camus, V., Zboch, M., Brooks, D.J., Drzezga, A., Rinne, J.O., Newberg, A., Mendonca, A. de, Sarazin, M., Rabinovici, G.D., Madsen, K., Kramberger, M.G., Nordberg, A., Mok, V., Mroczko, B., Wolk, D.A., Meyer, P.T., Tsolaki, M., Scheltens, P., Verhey, F.R.J., Visser, P.J., Aarsland, D., Alcolea, D., Alexander, M., Almdahl, I.S., Arnold, S.E., Baldeiras, I., Barthel, H., Berckel, B.N. van, Blennow, K., Buchem, M.A. van, Cavedo, E., Chen, K., Chipi, E., Cohen, A.D., Forster, S., Fortea, J., Frederiksen, K.S., Freund-Levi, Y., Gkatzima, O., Gordon, M.F., Grimmer, T., Hampel, H., Hausner, L., Hellwig, S., Herukka, S.K., Johannsen, P., Klimkowicz-Mrowiec, A., Kohler, S., Koglin, N., Laere, K. Van, Leon, M., Lisetti, V., Maier, W., Marcusson, J., Meulenbroek, O., Mollergard, H.M., Morris, J.C., Nordlund, A., Novak, G.P., Paraskevas, G.P., Perera, G., Peters, O., and Ramakers, I., et al.

Abstract

Contains fulltext : 190311.pdf (Publisher’s version ) (Closed access), Importance: Cerebral amyloid-beta aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. Objective: To investigate whether amyloid-beta aggregation is associated with cognitive functioning in persons without dementia. Design, Setting, and Participants: This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. Main Outcomes and Measures: Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score

Published
2018

42. Parametric imaging of tau load in Alzheimer's patients and controls using Flortaucipir

Author

Golla, S. S. V., Wolters, E., Timmers, T., Ossenkoppele, R., Groot, C., Verfaillie, S., Scheltens, P., van der Flier, W. M., Schwarte, L., Mintun, M. A., Devous, M., Schuit, R. C., Windhorst, A. D., Lammertsma, A. A., Boellaard, R., van Berckel, B. N. M., Yaqub, M., Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Neurology, Amsterdam Neuroscience - Neurodegeneration, CCA - Imaging and biomarkers, NCA - neurodegeneration, APH - Personalized Medicine, APH - Methodology, Anesthesiology, ACS - Microcirculation, CCA - Cancer biology and immunology, CCA - Cancer Treatment and quality of life, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and ACS - Heart failure & arrhythmias

Published
2017

43. Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting

Author

Perani, D, Della Rosa, P, Cerami, C, Gallivanone, F, Fallanca, F, Vanoli, E, Panzacchi, A, Nobili, F, Pappatà, S, Marcone, A, Garibotto, V, Castiglioni, I, Magnani, G, Cappa, S, Gianolli, L, Drzezga, A, Perneczky, R, Didic, M, Guedj, E, Van Berckel, B, Ossenkoppele, R, Morbelli, S, Frisoni, G, Caroli, A, Perani D, Della Rosa PA, Cerami C, Gallivanone F, Fallanca F, Vanoli EG, Panzacchi A, Nobili F, Pappatà S, Marcone A, Garibotto V, CASTIGLIONI I, Magnani G, Cappa SF, Gianolli L, Drzezga A, Perneczky R, Didic M, Guedj E, Van Berckel BN, Ossenkoppele R, Morbelli S, Frisoni G, Caroli A, Perani, D, Della Rosa, P, Cerami, C, Gallivanone, F, Fallanca, F, Vanoli, E, Panzacchi, A, Nobili, F, Pappatà, S, Marcone, A, Garibotto, V, Castiglioni, I, Magnani, G, Cappa, S, Gianolli, L, Drzezga, A, Perneczky, R, Didic, M, Guedj, E, Van Berckel, B, Ossenkoppele, R, Morbelli, S, Frisoni, G, Caroli, A, Perani D, Della Rosa PA, Cerami C, Gallivanone F, Fallanca F, Vanoli EG, Panzacchi A, Nobili F, Pappatà S, Marcone A, Garibotto V, CASTIGLIONI I, Magnani G, Cappa SF, Gianolli L, Drzezga A, Perneczky R, Didic M, Guedj E, Van Berckel BN, Ossenkoppele R, Morbelli S, Frisoni G, and Caroli A

Abstract

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease-AD, Frontotemporal Lobar Degeneration-FTLD, Dementia with Lewy bodies-DLB and Mild Cognitive Impairment-MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions

Published
2014

44. Atrophy patterns in early clinical stages across distinct phenotypes of Alzheimer's disease

Author

Ossenkoppele, R., Cohn-Sheehy, B.I., La Joie, R., Vogel, J.W., Moller, C., Lehmann, M., van Berckel, B.N.M., Seeley, W.W., Pijnenburg, Y.A., Gorno-Tempini, M.L., Kramer, J.H., Barkhof, F., Rosen, H.J., van der Flier, W.M., Jagust, W.J., Miller, B.L., Scheltens, P., Rabinovici, G.D., Neurology, Radiology and nuclear medicine, and NCA - neurodegeneration

Subjects
Male, Aging, vision, Primary Progressive, posterior cortical atrophy, Neurodegenerative, early-onset dementia, memory, default mode network, atrophy, Clinical Research, Alzheimer Disease, Acquired Cognitive Impairment, Aphasia, 2.1 Biological and endogenous factors, Animals, Humans, magnetic resonance imaging, voxel-based morphometry, Aetiology, Age of Onset, Eye Disease and Disorders of Vision, Aged, Cerebral Cortex, language, logopenic variant primary progressive aphasia, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Experimental Psychology, Syndrome, Middle Aged, Alzheimer's disease, Brain Disorders, Phenotype, Neurological, Biomedical Imaging, Dementia, Female, Cognitive Sciences, Nerve Net
Abstract

© 2015 Wiley Periodicals, Inc. Alzheimer's disease (AD) can present with distinct clinical variants. Identifying the earliest neurodegenerative changes associated with each variant has implications for early diagnosis, and for understanding the mechanisms that underlie regional vulnerability and disease progression in AD. We performed voxel-based morphometry to detect atrophy patterns in early clinical stages of four AD phenotypes: Posterior cortical atrophy (PCA, "visual variant," n = 93), logopenic variant primary progressive aphasia (lvPPA, "language variant," n = 74), and memory-predominant AD categorized as early age-of-onset (EOAD, 65 years, n = 114). Patients with each syndrome were stratified based on: (1) degree of functional impairment, as measured by the clinical dementia rating (CDR) scale, and (2) overall extent of brain atrophy, as measured by a neuroimaging approach that sums the number of brain voxels showing significantly lower gray matter volume than cognitively normal controls (n = 80). Even at the earliest clinical stage (CDR=0.5 or bottom quartile of overall atrophy), patients with each syndrome showed both common and variant-specific atrophy. Common atrophy across variants was found in temporoparietal regions that comprise the posterior default mode network (DMN). Early syndrome-specific atrophy mirrored functional brain networks underlying functions that are uniquely affected in each variant: Language network in lvPPA, posterior cingulate cortex-hippocampal circuit in amnestic EOAD and LOAD, and visual networks in PCA. At more advanced stages, atrophy patterns largely converged across AD variants. These findings support a model in which neurodegeneration selectively targets both the DMN and syndrome-specific vulnerable networks at the earliest clinical stages of AD.

Published
2015
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45. Prevalence of cerebral amyloid pathology in persons without dementia: A meta-analysis

Author

Jansen, WJ, Ossenkoppele, R, Knol, DL, Tijms, BM, Scheltens, P, Verhey, FRJ, Visser, PJ, Aalten, P, Aarsland, D, Alcolea, D, Alexander, M, Almdahl, IS, Arnold, SE, Baldeiras, I, Barthel, H, Van Berckel, BNM, Bibeau, K, Blennow, K, Brooks, DJ, Van Buchem, MA, Camus, V, Cavedo, E, Chen, K, Chetelat, G, Cohen, AD, Drzezga, A, Engelborghs, S, Fagan, AM, Fladby, T, Fleisher, AS, Van Der Flier, WM, Ford, L, Forster, S, Fortea, J, Foskett, N, Frederiksen, KS, Freund-Levi, Y, Frisoni, GB, Froelich, L, Gabryelewicz, T, Gill, KD, Gkatzima, O, Gomez-Tortosa, E, Gordon, MF, Grimmer, T, Hampel, H, Hausner, L, Hellwig, S, Herukka, SK, Hildebrandt, H, Ishihara, L, Ivanoiu, A, Jagust, WJ, Johannsen, P, Kandimalla, R, Kapaki, E, Klimkowicz-Mrowiec, A, Klunk, WE, Kohler, S, Koglin, N, Kornhuber, J, Kramberger, MG, Van Laere, K, Landau, SM, Lee, DY, De Leon, M, Lisetti, V, Lleo, A, Madsen, K, Maier, W, Marcusson, J, Mattsson, N, De Mendonca, A, Meulenbroek, O, Meyer, PT, Mintun, MA, Mok, V, Molinuevo, JL, Mollergard, HM, Morris, JC, Mroczko, B, Van Der Mussele, S, Na, DL, Newberg, A, Nordberg, A, Nordlund, A, Novak, GP, Paraskevas, GP, and Parnetti, L

Subjects
mental disorders
Abstract

Copyright 2015 American Medical Association. All rights reserved. IMPORTANCE: Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies. OBJECTIVE To use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI). DATA SOURCES: Relevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE andWeb of Science databases and through personal communication with investigators. STUDY SELECTION: Studies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity. DATA EXTRACTION: AND SYNTHESIS: Individual recordswere provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies. MAIN OUTCOMES AND MEASURES: Prevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E [APOE] genotype, sex, and education) estimated by generalized estimating equations. RESULTS The prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95%CI, 8%-13%) to 44%(95%CI, 37%-51%) among participants with normal cognition; from 12%(95%CI, 8%-18%) to 43%(95%CI, 32%-55%) among patients with SCI; and from 27%(95%CI, 23%-32%) to 71%(95%CI, 66%-76%) among patients with MCI. APOE-ϵ4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOE ϵ4ϵ4 carriers, 50 years for ϵ2ϵ4 carriers, 55 years for ϵ3ϵ4 carriers, 65 years for ϵ3ϵ3 carriers, and 95 years for ϵ2ϵ3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality. CONCLUSIONS AND RELEVANCE: Among persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOE genotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia.

Published
2015
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46. Hersenen en veroudering

Author

Ossenkoppele, R., van Berckel, B.N.M., Neurology, Radiology and nuclear medicine, and NCA - neurodegeneration

Published
2015

47. Prevalence of cerebral amyloid pathology in persons without dementia: A meta-analysis

Author

Jansen, W.J. Ossenkoppele, R. Knol, D.L. Tijms, B.M. Scheltens, P. Verhey, F.R.J. Visser, P.J. Aalten, P. Aarsland, D. Alcolea, D. Alexander, M. Almdahl, I.S. Arnold, S.E. Baldeiras, I. Barthel, H. Van Berckel, B.N.M. Bibeau, K. Blennow, K. Brooks, D.J. Van Buchem, M.A. Camus, V. Cavedo, E. Chen, K. Chetelat, G. Cohen, A.D. Drzezga, A. Engelborghs, S. Fagan, A.M. Fladby, T. Fleisher, A.S. Van Der Flier, W.M. Ford, L. Forster, S. Fortea, J. Foskett, N. Frederiksen, K.S. Freund-Levi, Y. Frisoni, G.B. Froelich, L. Gabryelewicz, T. Gill, K.D. Gkatzima, O. Gomez-Tortosa, E. Gordon, M.F. Grimmer, T. Hampel, H. Hausner, L. Hellwig, S. Herukka, S.-K. Hildebrandt, H. Ishihara, L. Ivanoiu, A. Jagust, W.J. Johannsen, P. Kandimalla, R. Kapaki, E. Klimkowicz-Mrowiec, A. Klunk, W.E. Kohler, S. Koglin, N. Kornhuber, J. Kramberger, M.G. Van Laere, K. Landau, S.M. Lee, D.Y. De Leon, M. Lisetti, V. Lleo, A. Madsen, K. Maier, W. Marcusson, J. Mattsson, N. De Mendonca, A. Meulenbroek, O. Meyer, P.T. Mintun, M.A. Mok, V. Molinuevo, J.L. Mollergard, H.M. Morris, J.C. Mroczko, B. Van Der Mussele, S. Na, D.L. Newberg, A. Nordberg, A. Nordlund, A. Novak, G.P. Paraskevas, G.P. Parnetti, L. Perera, G. Peters, O. Popp, J. Prabhakar, S. Rabinovici, G.D. Ramakers, I.H.G.B. Rami, L. De Oliveira, C.R. Rinne, J.O. Rodrigue, K.M. Rodriguez-Rodriguez, E. Roe, C.M. Rot, U. Rowe, C.C. Ruther, E. Sabri, O. Sanchez-Juan, P. Santana, I. Sarazin, M. Schroder, J. Schutte, C. Seo, S.W. Soetewey, F. Soininen, H. Spiru, L. Struyfs, H. Teunissen, C.E. Tsolaki, M. Vandenberghe, R. Verbeek, M.M. Villemagne, V.L. Vos, S.J.B. Van Waalwijk Van Doorn, L.J.C. Waldemar, G. Wallin, A. Wallin, A.K. Wiltfang, J. Wolk, D.A. Zboch, M. Zetterberg, H. the Amyloid Biomarker Study Group

Subjects
mental disorders
Abstract

IMPORTANCE: Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies. OBJECTIVE To use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI). DATA SOURCES: Relevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE andWeb of Science databases and through personal communication with investigators. STUDY SELECTION: Studies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity. DATA EXTRACTION: AND SYNTHESIS: Individual recordswere provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies. MAIN OUTCOMES AND MEASURES: Prevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E [APOE] genotype, sex, and education) estimated by generalized estimating equations. RESULTS The prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95%CI, 8%-13%) to 44%(95%CI, 37%-51%) among participants with normal cognition; from 12%(95%CI, 8%-18%) to 43%(95%CI, 32%-55%) among patients with SCI; and from 27%(95%CI, 23%-32%) to 71%(95%CI, 66%-76%) among patients with MCI. APOE-ϵ4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOE ϵ4ϵ4 carriers, 50 years for ϵ2ϵ4 carriers, 55 years for ϵ3ϵ4 carriers, 65 years for ϵ3ϵ3 carriers, and 95 years for ϵ2ϵ3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality. CONCLUSIONS AND RELEVANCE: Among persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOE genotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia. Copyright 2015 American Medical Association. All rights reserved.

Published
2015

48. Brain FDG-PET analysis in patients suspected with Alzheimer's disease: comparison between computer-aided reading using SPM and BRASS.

Author

Trombella, S., Antelmi, L., Bosco, P., Redolfi, A., Tabouret-Viaud, C., Rager, O., Gold, G., Giannakopoulos, P., Ratib, O., Morbelli, S., Nobili, F. M., Perneczky, R., Didic, M., Guedj, E., Drzezga, A., Ossenkoppele, R., van Berckel, B., Frisoni, G. B., Garibotto, V., Trombella, S., Antelmi, L., Bosco, P., Redolfi, A., Tabouret-Viaud, C., Rager, O., Gold, G., Giannakopoulos, P., Ratib, O., Morbelli, S., Nobili, F. M., Perneczky, R., Didic, M., Guedj, E., Drzezga, A., Ossenkoppele, R., van Berckel, B., Frisoni, G. B., and Garibotto, V.

Published
2016

49. Interaction between education and clinical expression of Alzheimer's disease across European countries: an 18F-FDG PET study of the European Alzheimer's Disease Consortium (EADC)

Author

Buschiazzo, A., Frisoni, G., Galluzzi, S., Perneczky, R., Drzezga, A., van Berckel, B., Ossenkoppele, R., Guedj, E., Didic, M., Mecocci, P., Dottorini, M., Bauckneht, M., Sambuceti, G., Nobili, F., Morbelli, S., Buschiazzo, A., Frisoni, G., Galluzzi, S., Perneczky, R., Drzezga, A., van Berckel, B., Ossenkoppele, R., Guedj, E., Didic, M., Mecocci, P., Dottorini, M., Bauckneht, M., Sambuceti, G., Nobili, F., and Morbelli, S.

Published
2016

50. Amyloid and its association with default network integrity in Alzheimer's disease

Author

Adriaanse, S.M., Sanz-Arigita, E.J., Binnewijzend, M.A.A., Ossenkoppele, R., Tolboom, N., Assema, D.M.E. van, Wink, A.M., Boellaard, R., Yaqub, M., Windhorst, A.D., Flier, W.M. van der, Scheltens, P., Lammertsma, A.A., Rombouts, S.A.R.B., Barkhof, F., Berckel, B.N.M. van, Radiology and nuclear medicine, Neurology, and NCA - neurodegeneration

Subjects
default mode network, positron emission tomography, mild cognitive impairment, magnetic resonance imaging, amyloid, Alzheimer disease, resting-state fMRI
Published
2014
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