- Email: [email protected]
SELECTIVE ESTROGEN EFFECTS ON CHOLINERGIC-RELATED COGNITIVE PERFORMANCE AND FMRI IN POSTMENOPAUSAL WOMEN WITH AND WITHOUT SUBJECTIVE COGNITIVE DECLINE
Poster Presentations: Wednesday, July 19, 2017 P4-189
SYMPTOM ONSET IN GENETIC FRONTOTEMPORAL DEMENTIA
Katrina M. Dick1, John C. van Swieten2, Alexander Gerhard3, Isabelle Le Ber4, Giovanni B. Frisoni5, Bradford C. Dickerson6, Caroline Graff7, Nupur Ghoshal8, Barbara Borroni9, Daniela Galimberti10, Ian R. Mackenzie11, Matthis Synofzik12, Raquel Sanchez-Valle13, Isabel Santana14, Fermin Moreno15, Johannes Levin16, James B. Rowe17, Alexandre Mendonca18, Mario Masellis19, Maria Carmela Tartaglia19, Philippe Couratier20, Edward D. Huey21, Sandro Sorbi22, Robert Laforce, Jr.23, Rik Vandenberghe24, Chiadi U. Onyike25, Emily J. Rogalski26, Simon Ducharme27, Sokratis G. Papageorgiou28, Adeline Su Lyn Ng29, Amy Brodtmann30, Florence Pasquier31, Fabrizio Tagliavini32, Christopher R. Butler33, Elizabeth Finger34, Murray Grossman35, Olivier Martinaud36, Markus Otto37, Erik D. Roberson38, Jennifer M. Nicholas39, John R. Hodges40, Adam L. Boxer41, Howard J. Rosen42, Bradley F. Boeve43, Jonathan D. Rohrer44, 1 Institute of Neurology, University College London, London, United Kingdom; 2Erasmus MC - University Medical Center Rotterdam, Rotterdam, Netherlands; 3University of Manchester, Manchester, United Kingdom; 4Sorbonne Universites, UPMC Univ Paris 06, Inserm, CNRS, Institut du Cerveau et la Moelle (ICM), AP-HP - H^ opital Pitie-Salp^etriere, Paris, France; 5Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; 6Massachusetts General Hospital, Boston, MA, USA; 7Karolinska Institutet, Department of Neurobiology, Care Sciences and Society (NVS), Center for Alzheimer Research, Division of Neurogeriatrics, 14157, Huddinge, Sweden; 8Washington University School of Medicine, St. Louis, MO, USA; 9Neurology Unit, University of Brescia, Brescia, Italy; 10University of Milan, Fondazione Ca Granda, IRCCS Ospedale Policlinico, Milan, Italy; 11University of British Columbia, Vancouver, BC, Canada; 12Centre for Neurology and Hertie-Institute for Clinical Brain Research Hoppe-Seyler-Str, Tuebingen, Germany; 13Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Department, Hospital Clınic de Barcelona, IDIBAPS, Barcelona, Spain; 14Dementia Clinic, Centro Hospitalar e Universitario de Coimbra and Faculty of Medicine, Universidade de Coimbra, Coimbra, Portugal; 15 Unidad de Deterioro Cognitivo, Hospital Universitario Donostia, San Sebastian, Spain; 16University of Munich, Munich, Germany; 17University of Cambridge, Cambridge, United Kingdom; 18University of Lisbon, Lisbon, Portugal; 19University of Toronto, Toronto, ON, Canada; 20University Hospital, Limoges, France; 21Gertrude H. Sergievsky Center at Columbia University, New York, NY, USA; 22University of Florence, Florence, Italy; 23 Universite Laval, Faculte de medecine, Quebec, QC, Canada; 24 KU Leuven, Leuven, Belgium; 25Johns Hopkins University, Baltimore, MD, USA; 26Northwestern University, Chicago, IL, USA; 27Institut et H^ opital Neurologiques de Montreal, Montreal, QC, Canada; 28National and Kapodistrian University of Athens, Medical School, Athens, Greece; 29National Neuroscience Institute Singapore, Singapore, Singapore; 30Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; 31 Lille University, Lille, France; 32Fondazione IRCSS Istituto Neurologico Carlo Besta, Milano, Italy; 33University of Oxford, Oxford, United Kingdom; 34University of Western Ontario, London, ON, Canada; 35Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; 36CHU Rouen, Rouen, France; 37University of Ulm, Ulm, Germany; 38University of Alabama at Birmingham, Birmingham, AL, USA; 39London School of Hygiene and Tropical Medicine, London, United Kingdom; 40 University of Sydney, Sydney, Australia; 41University of California, San Francisco, San Francisco, CA, USA; 42University of California San Francisco, San Francisco, CA, USA; 43Mayo
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Clinic, Rochester, MN, USA; 44Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom. Contact e-mail: [email protected] Background: Genetic frontotemporal dementia (FTD) is caused by
mutations in three main genes: C9orf72, progranulin (GRN) and microtubule-associated protein tau (MAPT). Little is currently known about the factors that influence age at symptom onset in FTD. This study aimed to investigate this through data collected from multiple families through the Frontotemporal dementia Prevention Initiative, a group connecting research centres within four large studies: GENFI, ARTFL, LEFFTDS and DINAD. Methods: We collected data on ages at symptom onset (AAO) from 2410 individuals from 988 families: 969 C9orf72 (461 families), 539 MAPT (167 families: 66 different mutations, most commonly P301L), and 902 GRN (360 families: 125 different mutations, most commonly T272fs). We assessed several factors influencing AAO, including parental AAO and AAO by mutation type and family. Results: The mean age at symptom onset was 58.6 (standard deviation 9.8) in C9orf72, 50.6 (9.3) in MAPT, and 61.4 (8.8) in GRN. In preliminary analysis we assessed the correlation of individual AAO with parental AAO and mean AAO within the family. The strongest correlation between individual AAO and both parental AAO (r ¼ 0.55, p<0.001) and mean AAO in the family (r ¼ 0.66, p <0.001) was seen in MAPT. In C9orf72, there was a significant correlation between individual AAO and both parental AAO (r ¼ 0.33, p¼0.001) and mean AAO in the family (r ¼ 0.30, p <0.001) but to a lesser extent than MAPT. The lowest correlation was in the GRN group for both individual AAO and parental AAO (r ¼ 0.15, p¼0.013) and mean family AAO (r¼0.18, p<0.001) although these are nonetheless significant. Conclusions: In a preliminary analysis we show that a significant proportion of the observed variance in age at symptom onset in genetic FTD can be explained by family history but is variable by mutation type. In our final analysis we plan to develop a model for predicting age at symptom onset in different FTD mutations. Such findings will be essential in analysing data in presymptomatic cohorts when estimating time to symptom onset, and will hopefully provide empirical support for the use of such predictive models in clinical trials. P4-190
SELECTIVE ESTROGEN EFFECTS ON CHOLINERGIC-RELATED COGNITIVE PERFORMANCE AND FMRI IN POSTMENOPAUSAL WOMEN WITH AND WITHOUT SUBJECTIVE COGNITIVE DECLINE
Kimberly Albert1, Dumas Julie2, Savannah Boyd1, Andrew J. Saykin3, Brenna C. McDonald3, Warren Taylor1,4, Paul A. Newhouse1,4, 1Vanderbilt University Medical Center, Nashville, TN, USA; 2University of Vermont, Burlington, VT, USA; 3Indiana University School of Medicine, Indianapolis, IN, USA; 4Geriatric Research Education and Clinical Center VA - TVHS, Nashville, TN, USA. Contact e-mail: [email protected] Background: Subjective cognitive decline (SCD) has begun to emerge as an identifiable risk factor for late life cognitive decline and dementia. Women appear at higher risk for late life cognitive impairment than men, which may be linked to the loss of estradiol (E2) at menopause and reduced cholinergic function. Our aim was to examine the effect of E2 on the response to cholinergic blockade in women with and without SCD. Methods: Thirty four (50-60 year old) postmenopausal women (SCD n ¼ 18, non-SCD n ¼ 16) were placed on oral 17-b estradiol (1mg/day) or placebo for three months. Subjects completed pre- and post-treatment fMRI followed by four randomized doubleblinded pharmacological challenges: 2.5 mg/kg scopolamine, 20 mg
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Poster Presentations: Wednesday, July 19, 2017
mecamylamine, a combination of 2.5 mg/kg scopolamine and 10 mg mecamylamine, or placebo. Working memory performance was assessed during fMRI and cholinergic challenge using the N-Back Task (NBT). Results: After E2 treatment women without SCD showed a greater increase in frontal activity during the NBT (3-back > 0-back) than women without SCD (p ¼ 0.01, k ¼ 200, pcorr ¼ 0.05). During mecamylamine challenge there was a significant three-way interaction between SCD status, E2 treatment, and task condition (F(3,480) ¼ 2.71, p < 0.05). Women without SCD who received E2 treatment had better 3-back performance during mecamylamine challenge than women who did not receive estradiol (t (16) ¼ 2.45, p<0.05: E2 d’ mean ¼ 2.41 SD ¼ 0.49; no E2 d’ mean ¼ 1.82, SD ¼ 0.53). Women with SCD who received E2 treatment had worse 3-back performance than women who did not receive E2 treatment (t (16) ¼ -3.68, p<0.05: E2 d’ mean ¼ 2.13, SD ¼ 0.14; no E2 d’ mean ¼ 2.72, SD ¼ 0.14). Conclusions: In women without SCD, E2 ameliorated the effects of cholinergic blockade on memory performance. This was not seen in the SCD group. The imaging results further support E2 salutary effects on cholinergic system functioning in normal postmenopausal women but not in women with SCD. Postmenopausal SCD may be a marker of cholinergic vulnerability or E2 unresponsiveness which reduces the cognitive effect of E2. P4-191
HIGH SOCIAL SUPPORTS RELATE WITH LOW IN VIVO ALZHEIMER’S DISEASE PATHOLOGIES IN COGNITIVELY NORMAL ELDERLY INDIVIDUALS
Kiyoung Sung1, Min Soo Byun2, Dahyun Yi2, Jun Ho Lee1, Kang Ko1, Seung Hoon Lee1, Na Young Han1, Myeong-Il Han3, Dong Young Lee1, 1 Seoul National University Hospital, Seoul, Republic of South Korea; 2 Medical Research Center Seoul National University, Seoul, Republic of South Korea; 3Jeollabukdo Maeumsarang Hospital, Wanju, Republic of South Korea. Contact e-mail: [email protected] Background: Although previous studies indicated that various aspects of social supports (SS) contribute to the prevention of Alzheimer’s disease (AD) dementia, underlying mechanism how SS are related to pathogenesis of AD are still poorly understood. We aimed to investigate whether high SS are related to low AD-specific pathologies such as cerebral beta-amyloid (Ab) deposition and neurodegeneration in cognitively normal (CN) elderly individuals. Methods: Total 255 CN elderly individuals from the Korean Brain Aging Study for Early Diagnosis & Prediction of Alzheimer’s Disease (KBASE), an ongoing prospective cohort study, were included for this analysis. All participants underwent comprehensive clinical and neuropsychological assessment, 11C-labelled Pittsburgh Compound B (PiB) positron emission tomography, magnetic resonance imaging, and apolipoprotein E genotyping. Ab positivity was defined if a subjects had one or more region-of-interests (ROIs: frontal, lateral temporal, lateral parietal and precuneus/posterior cingulate cortices) with mean standardized uptake value ratio > 1.4. AD-signature cortical thickness, a mean cortical thickness of several brain regions known to be sensitive to AD-specific neurodegeneration was obtained after excluding 5 subjects with poor image segmentation. Neurodegeneration positivity was defined if the AD-signature cortical thickness < 2.457 mm. The Medical Outcome Study – Social Support Survey (MOS-SSS), a 19-iem brief, multidimensional, self-report social support survey, were administered to all participants to assess overall SS indices. We divided participants into low vs. high SS by median of overall SS index. Results: In terms of Ab biomarkers, high SS was significantly associated with lower Ab positivity rate after controlling the effect of demographic variables and the presence of APOE4 allele. In addition, high SS was significantly
associated with lower neurodegeneration positivity after controlling the same covariates. Conclusions: Our results suggest that social support may contribute to the prevention or delay of the occurrence of AD by inhibiting both cerebral Ab burden and AD-type neurodegeneration. Further prospective studies are needed to confirm the contribution and reveal the mediating factors.
P4-192
RELATIONSHIPS AND SEX DIFFERENCES BETWEEN COGNITION AND SLEEP PARAMETERS AND MEDIATING EFFECTS OF DEPRESSION
Mal Rye Choi, Hun Jeong Eun, Presbyterian Medical Center-Jesus Hospital, Jeonju, Republic of South Korea. Contact e-mail: mdcmr@ daum.net Background: Sleep variables and depression affect cognition.De-
pression is associated with undiagnosed sleep problems. Depression is one of the most common psychiatric symptoms in Alzheimer’s disease (AD). Methods: Recruited 105 samples. Data Collections(sex, age, Ht, BW, BMI, sleep scoring data includingAHI & RDI, PSQI, ESS, SI, BDI, Overnight PSG), IBM SPSS statistics 23.0 version(t-test, Multiple regression analysis I-IV, Mediation effect test of Baron and Kenny. Results: 105 samples (Men 74, Women 31), Age(Men 50.20615.02,Women 52.58 612.97, Mean 50.90614.43), Height(Men 170.1066.05cm, Women 155.1266.27cm, Mean 165.6869.17cm), Body weight (Men 75.94614.18kg, Women 60.32611.94kg, Mean 71.33 615.28kg), Body mass index(Men 26.2164.09, Women 25.15 65.23, Mean 25.9064.45), Neck circumference(Men 38.2863.18cm, Women 33.6663.95cm, Mean 36.9264.01cm, Waist(Men 92.73611.25cm, Women 83.81615.69cm, Mean 90.10613.28cm),t-test(Sex differences) siginificant results(Height, body weight, WASO, Duration N1 stage, Duration N3 stage, AHI, NREM AHI, RDI, NREM RDI, Supine AHI, Supine RDI, Arousal Index, Snoring Index, Mean SpO2, Neck circumference, Waist), Stepwise multiple regression analysis I : Dependent variable Moca-K, endent variable- Age Age(model 1), Adjusted R2¼0.092, F¼11.494, p¼0.001/ Age & Waist(model 2) Adjusted R2¼0.128(D 0.036), F¼8.629, p¼0.000, Stepwise multiple regression analysis II : Dependent variable Moca-K, Independent variable- % N1 stage(model 1) Adjusted R2¼0.107, F¼13.469, p¼0.000 / % N1 stage & Duration N1(model 2) Adjusted R2¼0.134(D 0,027), F¼9.079, p¼0.000,Stepwise multiple regression analysis III : Dependent variable Moca-K, Independent variable-BDI(model 1) Adjusted R2¼0.057, F¼7.260, p¼ 0,008 / BDI & supine RDI (model 2) Adjusted R2¼0.098, F¼6.571, p¼0.002. Stepwise multiple regression analysis IV : Dependent variable BDI, Independent variable PSQI(model 1) Adjusted R2¼0.162, F¼20.959, p¼0.000 / PSQI & Snoring Index(model 2) Adjusted R2¼0.222, F¼15.732. p¼0.000/PSQI & Snoring index & Moca-K(model 3) Adjusted R2¼0.252. F¼15.572, p¼0.000, Mediation effect test of Baron and Kenny : Dependent Variable Moca-K, Independent variable % N1 stage, Age, BDI, supine RDI-Model 1% N1 stage(model 1) Adjusted R2¼0.107, F¼13.469, p¼0.000/%N1 stage & Age(model 2) Adjusted R2¼0.157, F¼10.716, p¼0.000/%N1 stage & Age & BDI(model 3) Adjusted R2¼0.226, F¼11.101, p¼0.000 Conclusions: Cognitive function were affected by changes in age, waist thickness, NREM sleep stage I, depression, and sleep apnea. Poor sleep quality, increased snoring, and decreased cognitive function will increase
SYMPTOM ONSET IN GENETIC FRONTOTEMPORAL DEMENTIA
Katrina M. Dick1, John C. van Swieten2, Alexander Gerhard3, Isabelle Le Ber4, Giovanni B. Frisoni5, Bradford C. Dickerson6, Caroline Graff7, Nupur Ghoshal8, Barbara Borroni9, Daniela Galimberti10, Ian R. Mackenzie11, Matthis Synofzik12, Raquel Sanchez-Valle13, Isabel Santana14, Fermin Moreno15, Johannes Levin16, James B. Rowe17, Alexandre Mendonca18, Mario Masellis19, Maria Carmela Tartaglia19, Philippe Couratier20, Edward D. Huey21, Sandro Sorbi22, Robert Laforce, Jr.23, Rik Vandenberghe24, Chiadi U. Onyike25, Emily J. Rogalski26, Simon Ducharme27, Sokratis G. Papageorgiou28, Adeline Su Lyn Ng29, Amy Brodtmann30, Florence Pasquier31, Fabrizio Tagliavini32, Christopher R. Butler33, Elizabeth Finger34, Murray Grossman35, Olivier Martinaud36, Markus Otto37, Erik D. Roberson38, Jennifer M. Nicholas39, John R. Hodges40, Adam L. Boxer41, Howard J. Rosen42, Bradley F. Boeve43, Jonathan D. Rohrer44, 1 Institute of Neurology, University College London, London, United Kingdom; 2Erasmus MC - University Medical Center Rotterdam, Rotterdam, Netherlands; 3University of Manchester, Manchester, United Kingdom; 4Sorbonne Universites, UPMC Univ Paris 06, Inserm, CNRS, Institut du Cerveau et la Moelle (ICM), AP-HP - H^ opital Pitie-Salp^etriere, Paris, France; 5Lab Alzheimer’s Neuroimaging & Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy; 6Massachusetts General Hospital, Boston, MA, USA; 7Karolinska Institutet, Department of Neurobiology, Care Sciences and Society (NVS), Center for Alzheimer Research, Division of Neurogeriatrics, 14157, Huddinge, Sweden; 8Washington University School of Medicine, St. Louis, MO, USA; 9Neurology Unit, University of Brescia, Brescia, Italy; 10University of Milan, Fondazione Ca Granda, IRCCS Ospedale Policlinico, Milan, Italy; 11University of British Columbia, Vancouver, BC, Canada; 12Centre for Neurology and Hertie-Institute for Clinical Brain Research Hoppe-Seyler-Str, Tuebingen, Germany; 13Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Department, Hospital Clınic de Barcelona, IDIBAPS, Barcelona, Spain; 14Dementia Clinic, Centro Hospitalar e Universitario de Coimbra and Faculty of Medicine, Universidade de Coimbra, Coimbra, Portugal; 15 Unidad de Deterioro Cognitivo, Hospital Universitario Donostia, San Sebastian, Spain; 16University of Munich, Munich, Germany; 17University of Cambridge, Cambridge, United Kingdom; 18University of Lisbon, Lisbon, Portugal; 19University of Toronto, Toronto, ON, Canada; 20University Hospital, Limoges, France; 21Gertrude H. Sergievsky Center at Columbia University, New York, NY, USA; 22University of Florence, Florence, Italy; 23 Universite Laval, Faculte de medecine, Quebec, QC, Canada; 24 KU Leuven, Leuven, Belgium; 25Johns Hopkins University, Baltimore, MD, USA; 26Northwestern University, Chicago, IL, USA; 27Institut et H^ opital Neurologiques de Montreal, Montreal, QC, Canada; 28National and Kapodistrian University of Athens, Medical School, Athens, Greece; 29National Neuroscience Institute Singapore, Singapore, Singapore; 30Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; 31 Lille University, Lille, France; 32Fondazione IRCSS Istituto Neurologico Carlo Besta, Milano, Italy; 33University of Oxford, Oxford, United Kingdom; 34University of Western Ontario, London, ON, Canada; 35Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; 36CHU Rouen, Rouen, France; 37University of Ulm, Ulm, Germany; 38University of Alabama at Birmingham, Birmingham, AL, USA; 39London School of Hygiene and Tropical Medicine, London, United Kingdom; 40 University of Sydney, Sydney, Australia; 41University of California, San Francisco, San Francisco, CA, USA; 42University of California San Francisco, San Francisco, CA, USA; 43Mayo
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Clinic, Rochester, MN, USA; 44Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom. Contact e-mail: [email protected] Background: Genetic frontotemporal dementia (FTD) is caused by
mutations in three main genes: C9orf72, progranulin (GRN) and microtubule-associated protein tau (MAPT). Little is currently known about the factors that influence age at symptom onset in FTD. This study aimed to investigate this through data collected from multiple families through the Frontotemporal dementia Prevention Initiative, a group connecting research centres within four large studies: GENFI, ARTFL, LEFFTDS and DINAD. Methods: We collected data on ages at symptom onset (AAO) from 2410 individuals from 988 families: 969 C9orf72 (461 families), 539 MAPT (167 families: 66 different mutations, most commonly P301L), and 902 GRN (360 families: 125 different mutations, most commonly T272fs). We assessed several factors influencing AAO, including parental AAO and AAO by mutation type and family. Results: The mean age at symptom onset was 58.6 (standard deviation 9.8) in C9orf72, 50.6 (9.3) in MAPT, and 61.4 (8.8) in GRN. In preliminary analysis we assessed the correlation of individual AAO with parental AAO and mean AAO within the family. The strongest correlation between individual AAO and both parental AAO (r ¼ 0.55, p<0.001) and mean AAO in the family (r ¼ 0.66, p <0.001) was seen in MAPT. In C9orf72, there was a significant correlation between individual AAO and both parental AAO (r ¼ 0.33, p¼0.001) and mean AAO in the family (r ¼ 0.30, p <0.001) but to a lesser extent than MAPT. The lowest correlation was in the GRN group for both individual AAO and parental AAO (r ¼ 0.15, p¼0.013) and mean family AAO (r¼0.18, p<0.001) although these are nonetheless significant. Conclusions: In a preliminary analysis we show that a significant proportion of the observed variance in age at symptom onset in genetic FTD can be explained by family history but is variable by mutation type. In our final analysis we plan to develop a model for predicting age at symptom onset in different FTD mutations. Such findings will be essential in analysing data in presymptomatic cohorts when estimating time to symptom onset, and will hopefully provide empirical support for the use of such predictive models in clinical trials. P4-190
SELECTIVE ESTROGEN EFFECTS ON CHOLINERGIC-RELATED COGNITIVE PERFORMANCE AND FMRI IN POSTMENOPAUSAL WOMEN WITH AND WITHOUT SUBJECTIVE COGNITIVE DECLINE
Kimberly Albert1, Dumas Julie2, Savannah Boyd1, Andrew J. Saykin3, Brenna C. McDonald3, Warren Taylor1,4, Paul A. Newhouse1,4, 1Vanderbilt University Medical Center, Nashville, TN, USA; 2University of Vermont, Burlington, VT, USA; 3Indiana University School of Medicine, Indianapolis, IN, USA; 4Geriatric Research Education and Clinical Center VA - TVHS, Nashville, TN, USA. Contact e-mail: [email protected] Background: Subjective cognitive decline (SCD) has begun to emerge as an identifiable risk factor for late life cognitive decline and dementia. Women appear at higher risk for late life cognitive impairment than men, which may be linked to the loss of estradiol (E2) at menopause and reduced cholinergic function. Our aim was to examine the effect of E2 on the response to cholinergic blockade in women with and without SCD. Methods: Thirty four (50-60 year old) postmenopausal women (SCD n ¼ 18, non-SCD n ¼ 16) were placed on oral 17-b estradiol (1mg/day) or placebo for three months. Subjects completed pre- and post-treatment fMRI followed by four randomized doubleblinded pharmacological challenges: 2.5 mg/kg scopolamine, 20 mg
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Poster Presentations: Wednesday, July 19, 2017
mecamylamine, a combination of 2.5 mg/kg scopolamine and 10 mg mecamylamine, or placebo. Working memory performance was assessed during fMRI and cholinergic challenge using the N-Back Task (NBT). Results: After E2 treatment women without SCD showed a greater increase in frontal activity during the NBT (3-back > 0-back) than women without SCD (p ¼ 0.01, k ¼ 200, pcorr ¼ 0.05). During mecamylamine challenge there was a significant three-way interaction between SCD status, E2 treatment, and task condition (F(3,480) ¼ 2.71, p < 0.05). Women without SCD who received E2 treatment had better 3-back performance during mecamylamine challenge than women who did not receive estradiol (t (16) ¼ 2.45, p<0.05: E2 d’ mean ¼ 2.41 SD ¼ 0.49; no E2 d’ mean ¼ 1.82, SD ¼ 0.53). Women with SCD who received E2 treatment had worse 3-back performance than women who did not receive E2 treatment (t (16) ¼ -3.68, p<0.05: E2 d’ mean ¼ 2.13, SD ¼ 0.14; no E2 d’ mean ¼ 2.72, SD ¼ 0.14). Conclusions: In women without SCD, E2 ameliorated the effects of cholinergic blockade on memory performance. This was not seen in the SCD group. The imaging results further support E2 salutary effects on cholinergic system functioning in normal postmenopausal women but not in women with SCD. Postmenopausal SCD may be a marker of cholinergic vulnerability or E2 unresponsiveness which reduces the cognitive effect of E2. P4-191
HIGH SOCIAL SUPPORTS RELATE WITH LOW IN VIVO ALZHEIMER’S DISEASE PATHOLOGIES IN COGNITIVELY NORMAL ELDERLY INDIVIDUALS
Kiyoung Sung1, Min Soo Byun2, Dahyun Yi2, Jun Ho Lee1, Kang Ko1, Seung Hoon Lee1, Na Young Han1, Myeong-Il Han3, Dong Young Lee1, 1 Seoul National University Hospital, Seoul, Republic of South Korea; 2 Medical Research Center Seoul National University, Seoul, Republic of South Korea; 3Jeollabukdo Maeumsarang Hospital, Wanju, Republic of South Korea. Contact e-mail: [email protected] Background: Although previous studies indicated that various aspects of social supports (SS) contribute to the prevention of Alzheimer’s disease (AD) dementia, underlying mechanism how SS are related to pathogenesis of AD are still poorly understood. We aimed to investigate whether high SS are related to low AD-specific pathologies such as cerebral beta-amyloid (Ab) deposition and neurodegeneration in cognitively normal (CN) elderly individuals. Methods: Total 255 CN elderly individuals from the Korean Brain Aging Study for Early Diagnosis & Prediction of Alzheimer’s Disease (KBASE), an ongoing prospective cohort study, were included for this analysis. All participants underwent comprehensive clinical and neuropsychological assessment, 11C-labelled Pittsburgh Compound B (PiB) positron emission tomography, magnetic resonance imaging, and apolipoprotein E genotyping. Ab positivity was defined if a subjects had one or more region-of-interests (ROIs: frontal, lateral temporal, lateral parietal and precuneus/posterior cingulate cortices) with mean standardized uptake value ratio > 1.4. AD-signature cortical thickness, a mean cortical thickness of several brain regions known to be sensitive to AD-specific neurodegeneration was obtained after excluding 5 subjects with poor image segmentation. Neurodegeneration positivity was defined if the AD-signature cortical thickness < 2.457 mm. The Medical Outcome Study – Social Support Survey (MOS-SSS), a 19-iem brief, multidimensional, self-report social support survey, were administered to all participants to assess overall SS indices. We divided participants into low vs. high SS by median of overall SS index. Results: In terms of Ab biomarkers, high SS was significantly associated with lower Ab positivity rate after controlling the effect of demographic variables and the presence of APOE4 allele. In addition, high SS was significantly
associated with lower neurodegeneration positivity after controlling the same covariates. Conclusions: Our results suggest that social support may contribute to the prevention or delay of the occurrence of AD by inhibiting both cerebral Ab burden and AD-type neurodegeneration. Further prospective studies are needed to confirm the contribution and reveal the mediating factors.
P4-192
RELATIONSHIPS AND SEX DIFFERENCES BETWEEN COGNITION AND SLEEP PARAMETERS AND MEDIATING EFFECTS OF DEPRESSION
Mal Rye Choi, Hun Jeong Eun, Presbyterian Medical Center-Jesus Hospital, Jeonju, Republic of South Korea. Contact e-mail: mdcmr@ daum.net Background: Sleep variables and depression affect cognition.De-
pression is associated with undiagnosed sleep problems. Depression is one of the most common psychiatric symptoms in Alzheimer’s disease (AD). Methods: Recruited 105 samples. Data Collections(sex, age, Ht, BW, BMI, sleep scoring data includingAHI & RDI, PSQI, ESS, SI, BDI, Overnight PSG), IBM SPSS statistics 23.0 version(t-test, Multiple regression analysis I-IV, Mediation effect test of Baron and Kenny. Results: 105 samples (Men 74, Women 31), Age(Men 50.20615.02,Women 52.58 612.97, Mean 50.90614.43), Height(Men 170.1066.05cm, Women 155.1266.27cm, Mean 165.6869.17cm), Body weight (Men 75.94614.18kg, Women 60.32611.94kg, Mean 71.33 615.28kg), Body mass index(Men 26.2164.09, Women 25.15 65.23, Mean 25.9064.45), Neck circumference(Men 38.2863.18cm, Women 33.6663.95cm, Mean 36.9264.01cm, Waist(Men 92.73611.25cm, Women 83.81615.69cm, Mean 90.10613.28cm),t-test(Sex differences) siginificant results(Height, body weight, WASO, Duration N1 stage, Duration N3 stage, AHI, NREM AHI, RDI, NREM RDI, Supine AHI, Supine RDI, Arousal Index, Snoring Index, Mean SpO2, Neck circumference, Waist), Stepwise multiple regression analysis I : Dependent variable Moca-K, endent variable- Age Age(model 1), Adjusted R2¼0.092, F¼11.494, p¼0.001/ Age & Waist(model 2) Adjusted R2¼0.128(D 0.036), F¼8.629, p¼0.000, Stepwise multiple regression analysis II : Dependent variable Moca-K, Independent variable- % N1 stage(model 1) Adjusted R2¼0.107, F¼13.469, p¼0.000 / % N1 stage & Duration N1(model 2) Adjusted R2¼0.134(D 0,027), F¼9.079, p¼0.000,Stepwise multiple regression analysis III : Dependent variable Moca-K, Independent variable-BDI(model 1) Adjusted R2¼0.057, F¼7.260, p¼ 0,008 / BDI & supine RDI (model 2) Adjusted R2¼0.098, F¼6.571, p¼0.002. Stepwise multiple regression analysis IV : Dependent variable BDI, Independent variable PSQI(model 1) Adjusted R2¼0.162, F¼20.959, p¼0.000 / PSQI & Snoring Index(model 2) Adjusted R2¼0.222, F¼15.732. p¼0.000/PSQI & Snoring index & Moca-K(model 3) Adjusted R2¼0.252. F¼15.572, p¼0.000, Mediation effect test of Baron and Kenny : Dependent Variable Moca-K, Independent variable % N1 stage, Age, BDI, supine RDI-Model 1% N1 stage(model 1) Adjusted R2¼0.107, F¼13.469, p¼0.000/%N1 stage & Age(model 2) Adjusted R2¼0.157, F¼10.716, p¼0.000/%N1 stage & Age & BDI(model 3) Adjusted R2¼0.226, F¼11.101, p¼0.000 Conclusions: Cognitive function were affected by changes in age, waist thickness, NREM sleep stage I, depression, and sleep apnea. Poor sleep quality, increased snoring, and decreased cognitive function will increase