- Email: [email protected]
OBJECT AND SCENE MEMORY ARE DIFFERENTIALLY ASSOCIATED WITH CSF MARKERS OF ALZHEIMER’S DISEASE AND MRI VOLUMETRY
Poster Presentations: Wednesday, July 19, 2017
approximately 5 years between SUVR¼1.17 and SUVR¼1.35 (mean value for AD Ab+ participants). Regional analysis demonstrated spatially non-uniform tau accumulation, with a flat trajectory for the medial temporal region and sequentially increasing trajectories for lateral temporal, parietal and then frontal regions. Conclusions: Average long-term trajectories combining 139 longitudinal sequences of 18F-Flortaucipir images, obtained over a short 18-month interval, suggests an accelerated tau accumulation as Alzheimer’s Disease advances. This preliminary observation requires additional validation using independent datasets and further optimization of the applied methodology is warranted. Individual variability in trajectories is acknowledged; the average trajectories found in the present analysis may inform the construction of more individualized models.
P4-531
TDP-43 DRIVES FASTER RATES OF HIPPOCAMPAL ATROPHY IN ALZHEIMER’S DISEASE STARTING AT LEAST 10 YEARS PRIOR TO DEATH
Keith A. Josephs1, Dennis W. Dickson2, Nirubol Tosakulwong1, Melissa E. Murray2, Stephen D. Weigand1, Leonard Petrucelli2, Amanda Liesinger2, Matthew L. Senjem1, Anthony J. Spychalla1, David S. Knopman1, Joseph E. Parisi1, Ronald C. Petersen3, Clifford R. Jack Jr.3, Jennifer L. Whitwell1, 1Mayo Clinic, Rochester, MN, USA; 2Mayo Clinic, Jacksonville, FL, USA; 3Mayo Clinic College of Medicine, Rochester, MN, USA. Contact e-mail: [email protected] Background: Autopsy studies have not found an association between
beta-amyloid or tau and rates of hippocampal atrophy in Alzheimer’s disease. TAR DNA binding protein of 43kDa (TDP-43) has been linked to Alzheimer’s disease yet no studies have assessed for an association between TDP-43 and rates of hippocampal atrophy. Methods: Two-hundred ninety-eight autopsied cases with Alzheimer’s spectrum disease that had antemortem head MRI scans were analysed for this study. TDP-43 immunohistochemistry and staging was performed and cases classified as follows: no TDP-43; TDP-43 restricted to amygdala; and TDP-43 spreading into hippocampus. Eight-hundred seventeen MRI scans, spanning 1.0-11.2 years prior to death, were available for analysis. We utilized two independent neuroimaging techniques to calculate hippocampal volume on all serial MRI available for each case (longitudinal FreeSurfer and tensor-based morphometry with symmetric normalization (TBM-SyN)) and performed linear mixed-effects regression models to estimate the association between TDP-43 and rate of hippocampal atrophy, accounting for NIA-Alzheimer’s Association neurofibrillary tangle stage, and determine the trajectory of TDP-43 associated atrophy. In addition we determined whether higher NIAAlzheimer’s Association neurofibrillary tangle stage was associated with faster rates of hippocampal atrophy accounting for TDP-43. Re-
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sults: One-hundred forty-one cases showed no TDP-43, 33 had TDP-
43 restricted to the amygdala and 124 had TDP-43 in hippocampus. Cases with hippocampal TDP-43 had faster rates of hippocampal atrophy compared to cases with amygdala-only TDP-43 and those without any TDP-43 in cases with an intermediate-high likelihood of having Alzheimer’s disease. The trajectory analysis suggested that increased rates of TDP-43 associated hippocampal atrophy could be detected at least 10-years before death (Figure). Results were similar for FreeSurfer and TBM-SyN. Higher NIA-Alzheimer’s Association neurofibrillary tangle stage was only associated with faster rates when TDP-43 was absent. Conclusions: In Alzheimer’s disease, TDP-43 is one of, if not the main driver of faster rates of hippocampal atrophy, at least in the last 10 years prior to death. The findings also suggest that the effect of tau on rates of hippocampal atrophy may be an early phenomenon in typical Alzheimer’s disease, or may play a more important role in atypical clinical and pathological variants of Alzheimer’s disease. P4-532
OBJECT AND SCENE MEMORY ARE DIFFERENTIALLY ASSOCIATED WITH CSF MARKERS OF ALZHEIMER’S DISEASE AND MRI VOLUMETRY
David Berron1,2, Hartmut Sch€utze1, Arturo Cardenas-Blanco3,4, Klaus Fliessbach5,6, Michael Wagner6,7, Annika Spottke6, Martin Reuter8,9,10, Stefan J. Teipel11,12, Katharina Buerger13,14, Anja Schneider6,15, Oliver Peters16,17, Peter Nestor3, Josef Priller17,18, Jens Wiltfang19,20, Christoph Laske21,22, Frank Jessen23,24, Emrah D€uzel3,4,25, the DELCODE consortium, 1Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany; 2German Center for Neurodegnerative Diseases (DZNE), Magdeburg, Germany; 3German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; 4Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany; 5University Hospital Bonn, Bonn, Germany; 6 German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; 7 Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany; 8German Center for Neurodegnerative Diseases (DZNE), Bonn, Germany; 9Harvard Medical School, Boston, MA, USA; 10Massachusetts Institute of Technology, Cambridge, MA, USA; 11German Center for Neurodegenerative Disease (DZNE), Rostock, Germany; 12Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany; 13 Institute for Stroke and Dementia Research (ISD), Klinikum der Universit€at M€unchen, Munich, Germany; 14German Center for Neurodegenerative Diseases, Munich, Germany; 15Department of Psychiatry and Psychotherapy, University Medical Center, Bonn, Germany;
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Poster Presentations: Wednesday, July 19, 2017
16 Department of Psychiatry, Charite – Universit€atsmedizin Berlin, Berlin, Germany; 17German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; 18Department of Psychiatry, Charite Universit€ atsmedizin Berlin, Berlin, Germany; 19German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany; 20Department of Psychiatry and Psychotherapy, University Medical Center G€ottingen, G€ ottingen, Germany; 21Department of Psychiatry and Psychotherapy, Eberhard Karls University, T€ubingen, Germany; 22German Center for Neurodegenerative Diseases (DZNE), T€ubingen, Germany; 23German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany; 24 Department of Psychiatry, University of Cologne, Cologne, Germany; 25 University College London, London, United Kingdom. Contact e-mail: [email protected]
Background: Alzheimer’s Disease (AD) is characterized by progressive tau-pathology in perirhinal and entorhinal cortices (ErC), hippocampus, parahippocampal cortex and the retrosplenial/posterior cingulate region (RsC/PCC). The latter also shows early amyloid plaque accumulation. While these regions form a network for complex objectsin-scene memories, there is a segregation of object memory into a perirhinal-entorhinal and scene-layout memory into a RsC/PCC-parahippocampal-entorhinal pathway. Here we investigated whether complex objects-in-scene memory, as opposed to isolated object or scene-layout memory is correlated with CSF levels of Aß42 and phospho-tau and MR volume and thickness measures. Methods: 204 participants (cognitively healthy, subjective memory complaints, mild cognitive impairment or early AD) of the DELCODE study of the DZNE performed a complex scene recognition memory task. CSF samples were available from 80 participants. 78 participants also performed a second task on mnemonic discrimination of objects (in the absence of scenes) and scenes (in the absence of objects). Of these 28 CSF samples were available. MR thickness measures were obtained from T1 and T2-weighted images using Freesurfer 6. Results: Objectsin-scene recognition memory correlated with right and left PCC volume (p¼0.005; p¼0.047), right and left hippocampal volume (p¼0.002; p¼0.001), Aß42, phospho-tau and their ratio (p¼0.002; p¼0.002; p¼0.000). Isolated object and scene discrimination correlated with left and right hippocampal volume (Scene: p¼0.039; p¼0.006; Object: p¼0.011; p¼0.001); scene memory correlated with right and object memory with both left and right ErC thickness (Scene: p¼0.027; Object: p¼0.024; p¼0.031). A scene-minus-object difference score correlated with Aß42 levels indicating that decreasing levels of Aß42 were associated with selective decline of scene discrimination (p¼0.034). When considering only healthy older adults, object discrimination relatively selectively correlated with right and left hippocampal volume (N¼57; rp¼0.022; p¼0.005), left entorhinal thickness (p¼0.042) and with phospho-tau levels (N¼19; p¼0.052). Conclusions: These data suggest that complex object-in-scene recognition captures variance caused by both tau and amyloid pathology. A domain-specific breakdown, however, indicates that tau-related variance tends to be captured by object discrimination whereas amyloid pathology is captured by scene discrimination performance. The findings are compatible with the possibility that object and scene discrimination track different stages of disease progression in AD. P4-533
GENOTYPE-DEPENDENT LONGITUDINAL TRAJECTORIES OF COGNITIVE DECLINE IN AUTOSOMAL DOMINANT ALZHEIMER’S DISEASE
Ove Almkvist1,2,3, Elena Rodriguez-Vieitez1, Steinunn Thordardottir1, Anne Kinhult St ahlbom1, Matti Viitanen1,2,4,5, Lars Lannfelt6, Caroline Graff1,2, 1Karolinska Institutet, Stockholm, Sweden; 2Karolinska University Hospital Huddinge, Stockholm, Sweden; 3Stockholm University,
Stockholm, Sweden; 4Turku City Hospital, Turku, Finland; 5University of Turku, Turku, Finland; 6Uppsala University, Uppsala, Sweden. Contact e-mail: [email protected] Background: Phenotypic heterogeneity is evident in Alzheimer’s disease (AD) due to multifactorial genetic and environmental causes. In familial autosomal dominant AD (ADAD), characterized by a family-specific age of clinical onset, cognitive decline begins in mutation carriers at the preclinical stage. However, possible genotype-specific differences in cognition are unknown. In this study, we compared the longitudinal trajectories of cognitive decline in APP and PSEN1 mutation carriers from a Swedish ADAD cohort, encompassing forty years of preclinical and clinical progression. Methods: l:/ELSEVIER/JALZ/ 35 carriers and 43 non-carriers from five families harboring a mutation in an ADAD gene (APP or PSEN1) were followed with repeated comprehensive clinical examinations (average follow-up time: 7.2 6 5.4 years). The time measure, years to estimated clinical onset (YECO), was defined as the individual’s age minus the family-specific estimated clinical onset, and applied to both mutation carriers and noncarriers. Mixed-effects models were used to predict cognitive performance vs. predictors including YECO, YECO2, years of education, age, mutation status (carrier or non-carrier), and genotype (APP or PSEN1), including a random intercept at the subject level, and investigating interaction terms of mutation status-by-YECO and genotype-byYECO. Results: APP and PSEN1 carriers were comparable in premorbid global cognition and demographic characteristics. Pooling all mutation carriers and non-carriers, a significant mutation status-by-YECO interaction was observed in all ten cognitive tests investigated. YECO, YECO2 and education were significant predictors in mutation carriers showing curvilinear cognitive decline, whereas education and age were significant predictors in non-carriers showing minor age-related deterioration. In mutation carriers, significant genotype-by-YECO interaction was found in selected tests of episodic memory, executive and visuospatial functions, and working memory. APP carriers showed earlier longitudinal decline than PSEN1 carriers, most prominently in episodic memory and executive function. APP carriers began to diverge from non-carriers nearly 15 years prior to the estimated clinical onset, while PSEN1 carriers began to decline close to the estimated clinical onset. Conclusions: The longitudinal trajectories of cognitive decline in APP and PSEN1 may be differentiated, which motivates further research on the underlying molecular bases of this finding and may be important for clinical practice and to design therapeutic strategies.
P4-534
LINKING MEASURES OF SUBJECTIVE COGNITION ACROSS INTERNATIONAL AGING STUDIES USING ITEM RESPONSE THEORY
Laura Rabin1, Richard N. Jones2, Douglas Tommet3, Paul K. Crane4, Shannon L. Risacher5, Andrew J. Saykin6, Beth E. Snitz7, Rebecca Amariglio8,9,10,11, Dorene M. Rentz9,11,12, Reisa A. Sperling8,9,11,13,14, Sietske A. M. Sikkes15,16,17,18, ADNI, 1 Brooklyn College of The City University of New York, Brooklyn, NY, USA; 2 Alpert Medical School of Brown University, Providence, RI, USA; 3Warren Alpert Medical School, Brown University, Providence, RI, USA; 4University of Washington, Seattle, WA, USA; 5Indiana Alzheimer Disease Center, Indianapolis, IN, USA; 6Indiana University Network Science Institute, Bloomington, IN, USA; 7Alzheimer’s Disease Research Center, Pittsburgh, PA, USA; 8Center for Alzheimer Research and Treatment, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA; 9Brigham and Women’s Hospital, Boston, MA, USA; 10Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; 11Harvard Medical School, Boston, MA, USA; 12Massachusetts General Hospital,
approximately 5 years between SUVR¼1.17 and SUVR¼1.35 (mean value for AD Ab+ participants). Regional analysis demonstrated spatially non-uniform tau accumulation, with a flat trajectory for the medial temporal region and sequentially increasing trajectories for lateral temporal, parietal and then frontal regions. Conclusions: Average long-term trajectories combining 139 longitudinal sequences of 18F-Flortaucipir images, obtained over a short 18-month interval, suggests an accelerated tau accumulation as Alzheimer’s Disease advances. This preliminary observation requires additional validation using independent datasets and further optimization of the applied methodology is warranted. Individual variability in trajectories is acknowledged; the average trajectories found in the present analysis may inform the construction of more individualized models.
P4-531
TDP-43 DRIVES FASTER RATES OF HIPPOCAMPAL ATROPHY IN ALZHEIMER’S DISEASE STARTING AT LEAST 10 YEARS PRIOR TO DEATH
Keith A. Josephs1, Dennis W. Dickson2, Nirubol Tosakulwong1, Melissa E. Murray2, Stephen D. Weigand1, Leonard Petrucelli2, Amanda Liesinger2, Matthew L. Senjem1, Anthony J. Spychalla1, David S. Knopman1, Joseph E. Parisi1, Ronald C. Petersen3, Clifford R. Jack Jr.3, Jennifer L. Whitwell1, 1Mayo Clinic, Rochester, MN, USA; 2Mayo Clinic, Jacksonville, FL, USA; 3Mayo Clinic College of Medicine, Rochester, MN, USA. Contact e-mail: [email protected] Background: Autopsy studies have not found an association between
beta-amyloid or tau and rates of hippocampal atrophy in Alzheimer’s disease. TAR DNA binding protein of 43kDa (TDP-43) has been linked to Alzheimer’s disease yet no studies have assessed for an association between TDP-43 and rates of hippocampal atrophy. Methods: Two-hundred ninety-eight autopsied cases with Alzheimer’s spectrum disease that had antemortem head MRI scans were analysed for this study. TDP-43 immunohistochemistry and staging was performed and cases classified as follows: no TDP-43; TDP-43 restricted to amygdala; and TDP-43 spreading into hippocampus. Eight-hundred seventeen MRI scans, spanning 1.0-11.2 years prior to death, were available for analysis. We utilized two independent neuroimaging techniques to calculate hippocampal volume on all serial MRI available for each case (longitudinal FreeSurfer and tensor-based morphometry with symmetric normalization (TBM-SyN)) and performed linear mixed-effects regression models to estimate the association between TDP-43 and rate of hippocampal atrophy, accounting for NIA-Alzheimer’s Association neurofibrillary tangle stage, and determine the trajectory of TDP-43 associated atrophy. In addition we determined whether higher NIAAlzheimer’s Association neurofibrillary tangle stage was associated with faster rates of hippocampal atrophy accounting for TDP-43. Re-
P1553
sults: One-hundred forty-one cases showed no TDP-43, 33 had TDP-
43 restricted to the amygdala and 124 had TDP-43 in hippocampus. Cases with hippocampal TDP-43 had faster rates of hippocampal atrophy compared to cases with amygdala-only TDP-43 and those without any TDP-43 in cases with an intermediate-high likelihood of having Alzheimer’s disease. The trajectory analysis suggested that increased rates of TDP-43 associated hippocampal atrophy could be detected at least 10-years before death (Figure). Results were similar for FreeSurfer and TBM-SyN. Higher NIA-Alzheimer’s Association neurofibrillary tangle stage was only associated with faster rates when TDP-43 was absent. Conclusions: In Alzheimer’s disease, TDP-43 is one of, if not the main driver of faster rates of hippocampal atrophy, at least in the last 10 years prior to death. The findings also suggest that the effect of tau on rates of hippocampal atrophy may be an early phenomenon in typical Alzheimer’s disease, or may play a more important role in atypical clinical and pathological variants of Alzheimer’s disease. P4-532
OBJECT AND SCENE MEMORY ARE DIFFERENTIALLY ASSOCIATED WITH CSF MARKERS OF ALZHEIMER’S DISEASE AND MRI VOLUMETRY
David Berron1,2, Hartmut Sch€utze1, Arturo Cardenas-Blanco3,4, Klaus Fliessbach5,6, Michael Wagner6,7, Annika Spottke6, Martin Reuter8,9,10, Stefan J. Teipel11,12, Katharina Buerger13,14, Anja Schneider6,15, Oliver Peters16,17, Peter Nestor3, Josef Priller17,18, Jens Wiltfang19,20, Christoph Laske21,22, Frank Jessen23,24, Emrah D€uzel3,4,25, the DELCODE consortium, 1Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany; 2German Center for Neurodegnerative Diseases (DZNE), Magdeburg, Germany; 3German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; 4Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany; 5University Hospital Bonn, Bonn, Germany; 6 German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; 7 Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany; 8German Center for Neurodegnerative Diseases (DZNE), Bonn, Germany; 9Harvard Medical School, Boston, MA, USA; 10Massachusetts Institute of Technology, Cambridge, MA, USA; 11German Center for Neurodegenerative Disease (DZNE), Rostock, Germany; 12Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany; 13 Institute for Stroke and Dementia Research (ISD), Klinikum der Universit€at M€unchen, Munich, Germany; 14German Center for Neurodegenerative Diseases, Munich, Germany; 15Department of Psychiatry and Psychotherapy, University Medical Center, Bonn, Germany;
P1554
Poster Presentations: Wednesday, July 19, 2017
16 Department of Psychiatry, Charite – Universit€atsmedizin Berlin, Berlin, Germany; 17German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; 18Department of Psychiatry, Charite Universit€ atsmedizin Berlin, Berlin, Germany; 19German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany; 20Department of Psychiatry and Psychotherapy, University Medical Center G€ottingen, G€ ottingen, Germany; 21Department of Psychiatry and Psychotherapy, Eberhard Karls University, T€ubingen, Germany; 22German Center for Neurodegenerative Diseases (DZNE), T€ubingen, Germany; 23German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany; 24 Department of Psychiatry, University of Cologne, Cologne, Germany; 25 University College London, London, United Kingdom. Contact e-mail: [email protected]
Background: Alzheimer’s Disease (AD) is characterized by progressive tau-pathology in perirhinal and entorhinal cortices (ErC), hippocampus, parahippocampal cortex and the retrosplenial/posterior cingulate region (RsC/PCC). The latter also shows early amyloid plaque accumulation. While these regions form a network for complex objectsin-scene memories, there is a segregation of object memory into a perirhinal-entorhinal and scene-layout memory into a RsC/PCC-parahippocampal-entorhinal pathway. Here we investigated whether complex objects-in-scene memory, as opposed to isolated object or scene-layout memory is correlated with CSF levels of Aß42 and phospho-tau and MR volume and thickness measures. Methods: 204 participants (cognitively healthy, subjective memory complaints, mild cognitive impairment or early AD) of the DELCODE study of the DZNE performed a complex scene recognition memory task. CSF samples were available from 80 participants. 78 participants also performed a second task on mnemonic discrimination of objects (in the absence of scenes) and scenes (in the absence of objects). Of these 28 CSF samples were available. MR thickness measures were obtained from T1 and T2-weighted images using Freesurfer 6. Results: Objectsin-scene recognition memory correlated with right and left PCC volume (p¼0.005; p¼0.047), right and left hippocampal volume (p¼0.002; p¼0.001), Aß42, phospho-tau and their ratio (p¼0.002; p¼0.002; p¼0.000). Isolated object and scene discrimination correlated with left and right hippocampal volume (Scene: p¼0.039; p¼0.006; Object: p¼0.011; p¼0.001); scene memory correlated with right and object memory with both left and right ErC thickness (Scene: p¼0.027; Object: p¼0.024; p¼0.031). A scene-minus-object difference score correlated with Aß42 levels indicating that decreasing levels of Aß42 were associated with selective decline of scene discrimination (p¼0.034). When considering only healthy older adults, object discrimination relatively selectively correlated with right and left hippocampal volume (N¼57; rp¼0.022; p¼0.005), left entorhinal thickness (p¼0.042) and with phospho-tau levels (N¼19; p¼0.052). Conclusions: These data suggest that complex object-in-scene recognition captures variance caused by both tau and amyloid pathology. A domain-specific breakdown, however, indicates that tau-related variance tends to be captured by object discrimination whereas amyloid pathology is captured by scene discrimination performance. The findings are compatible with the possibility that object and scene discrimination track different stages of disease progression in AD. P4-533
GENOTYPE-DEPENDENT LONGITUDINAL TRAJECTORIES OF COGNITIVE DECLINE IN AUTOSOMAL DOMINANT ALZHEIMER’S DISEASE
Ove Almkvist1,2,3, Elena Rodriguez-Vieitez1, Steinunn Thordardottir1, Anne Kinhult St ahlbom1, Matti Viitanen1,2,4,5, Lars Lannfelt6, Caroline Graff1,2, 1Karolinska Institutet, Stockholm, Sweden; 2Karolinska University Hospital Huddinge, Stockholm, Sweden; 3Stockholm University,
Stockholm, Sweden; 4Turku City Hospital, Turku, Finland; 5University of Turku, Turku, Finland; 6Uppsala University, Uppsala, Sweden. Contact e-mail: [email protected] Background: Phenotypic heterogeneity is evident in Alzheimer’s disease (AD) due to multifactorial genetic and environmental causes. In familial autosomal dominant AD (ADAD), characterized by a family-specific age of clinical onset, cognitive decline begins in mutation carriers at the preclinical stage. However, possible genotype-specific differences in cognition are unknown. In this study, we compared the longitudinal trajectories of cognitive decline in APP and PSEN1 mutation carriers from a Swedish ADAD cohort, encompassing forty years of preclinical and clinical progression. Methods: l:/ELSEVIER/JALZ/ 35 carriers and 43 non-carriers from five families harboring a mutation in an ADAD gene (APP or PSEN1) were followed with repeated comprehensive clinical examinations (average follow-up time: 7.2 6 5.4 years). The time measure, years to estimated clinical onset (YECO), was defined as the individual’s age minus the family-specific estimated clinical onset, and applied to both mutation carriers and noncarriers. Mixed-effects models were used to predict cognitive performance vs. predictors including YECO, YECO2, years of education, age, mutation status (carrier or non-carrier), and genotype (APP or PSEN1), including a random intercept at the subject level, and investigating interaction terms of mutation status-by-YECO and genotype-byYECO. Results: APP and PSEN1 carriers were comparable in premorbid global cognition and demographic characteristics. Pooling all mutation carriers and non-carriers, a significant mutation status-by-YECO interaction was observed in all ten cognitive tests investigated. YECO, YECO2 and education were significant predictors in mutation carriers showing curvilinear cognitive decline, whereas education and age were significant predictors in non-carriers showing minor age-related deterioration. In mutation carriers, significant genotype-by-YECO interaction was found in selected tests of episodic memory, executive and visuospatial functions, and working memory. APP carriers showed earlier longitudinal decline than PSEN1 carriers, most prominently in episodic memory and executive function. APP carriers began to diverge from non-carriers nearly 15 years prior to the estimated clinical onset, while PSEN1 carriers began to decline close to the estimated clinical onset. Conclusions: The longitudinal trajectories of cognitive decline in APP and PSEN1 may be differentiated, which motivates further research on the underlying molecular bases of this finding and may be important for clinical practice and to design therapeutic strategies.
P4-534
LINKING MEASURES OF SUBJECTIVE COGNITION ACROSS INTERNATIONAL AGING STUDIES USING ITEM RESPONSE THEORY
Laura Rabin1, Richard N. Jones2, Douglas Tommet3, Paul K. Crane4, Shannon L. Risacher5, Andrew J. Saykin6, Beth E. Snitz7, Rebecca Amariglio8,9,10,11, Dorene M. Rentz9,11,12, Reisa A. Sperling8,9,11,13,14, Sietske A. M. Sikkes15,16,17,18, ADNI, 1 Brooklyn College of The City University of New York, Brooklyn, NY, USA; 2 Alpert Medical School of Brown University, Providence, RI, USA; 3Warren Alpert Medical School, Brown University, Providence, RI, USA; 4University of Washington, Seattle, WA, USA; 5Indiana Alzheimer Disease Center, Indianapolis, IN, USA; 6Indiana University Network Science Institute, Bloomington, IN, USA; 7Alzheimer’s Disease Research Center, Pittsburgh, PA, USA; 8Center for Alzheimer Research and Treatment, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA; 9Brigham and Women’s Hospital, Boston, MA, USA; 10Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; 11Harvard Medical School, Boston, MA, USA; 12Massachusetts General Hospital,