key: cord-0256731-63r18ho4 authors: Kassam, F.; Chen, H.-Y.; Nosheny, R. L.; McGirr, A.; Williams, T.; Ng, N.; Camacho, M.; Mackin, R. S.; Weiner, M. W.; Ismail, Z. title: Cognitive profile of mild behavioral impairment in Brain Health Registry participants date: 2021-07-22 journal: nan DOI: 10.1101/2021.07.19.21260787 sha: 068519115ae81db1ba68d51d1b1fea63c479bd68 doc_id: 256731 cord_uid: 63r18ho4 INTRODUCTION: Dementia assessment includes cognitive and behavioral testing with informant validation. Conventional testing is resource intensive, with uneven access. Online unsupervised assessments could reduce barriers to risk assessment. We interrogated the relationship between informant-rated behavioral changes and neuropsychological test performance in older adults in the Brain Health Registry. METHODS: Participants completed online unsupervised cognitive tests, and informants completed the Mild Behavioral Impairment Checklist via a Study Partner portal. Cognitive performance was evaluated in MBI+/- individuals, as was the association between cognitive scores and MBI symptom severity. RESULTS: Mean age of the 499 participants was 67, 61% of which were female. MBI+ participants had lower working memory and executive function test scores. Lower cognitive test scores associated with greater MBI burden. DISCUSSION: Our findings support the feasibility of remote, informant-reported behavioral assessment and support its validity by demonstrating a relationship to cognitive test performance using online unsupervised assessments for dementia risk assessment. However, informant information is often required to validate the syndrome, and structured 88 assessment tools suitable for widespread dissemination through unsupervised platforms have 89 only recently been developed. The Mild Behavioral Impairment Checklist (MBI-C) incorporates 90 informant information and is the validated case ascertainment instrument developed specifically 91 to capture MBI in accordance with the criteria developed by the International Society to Advance 92 Alzheimer's Research and Treatment-Alzheimer's Association (ISTAART-AA) 27-30 . Translated 93 into over 20 languages, the MBI-C may also allow a broader reach for obtaining online 94 informant reports of behavioral change. 95 The aim of this study was to investigate informant-based MBI in an online unsupervised 97 platform, the Brain Health Registry (BHR), capable of assessing early dementia risk markers 31 . 98 We determined the utility of the BHR for converging assessments of cognitive and behavioral 99 symptoms using neuropsychological testing and informant-reported MBI-C. We hypothesized 100 that participants with MBI+ status would have poorer cognitive performance measured by the 101 Lumos test battery. We further hypothesized that individuals with poorer memory, executive 102 function, processing speed, and inhibitory control would have a higher burden of MBI 103 symptoms. 104 105 2. Methods 106 The BHR 31 is an internet-based public registry and cohort that recruits participants using a 108 variety of methods including a website, social media, brochures, and online advertising. All 109 participants are required to give informed consent with an online consent form. Upon completion 110 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 The assessment of Forward Memory Span is based on the Corsi block-tapping tasks 36 . The 127 participant is asked to recall the sequence of circles in the same order it was presented. The 128 length of the sequence increases by one every two trials. The session comes to an end when the 129 participant records two incorrect answers at the same span level. This task is used as a measure 130 of visual short-term memory and attention. 131 132 2.3.2 Lumosity online Reverse Memory Span 133 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 The Reverse Memory Span task is a slightly altered version of the original Corsi block-tapping 134 tasks. It is identical to the forward visual memory span assessment, with the exception that the 135 participant is asked to recall the sequence of circles in the reverse order. This reverse task is used 136 as a measure of visual working memory and attention. 137 In Trail Making Test (TMT) B, blue circles (numbered 1 to 12) and capital letters (A to L) are 140 arranged in 6 possible layouts with non-overlapping spatial locations. The participant must 141 alternate between numbers and letters for this task, clicking in increasing order. When the blue 142 circle is clicked, it turns orange and a straight line appears to connect the circles. The timer for 143 the task begins when the participants clicks the first circle. If the participant records an incorrect 144 click, an X appears on their screen and they are required to go back to the previous circle. In the Go/No-Go assessment, participants are presented with target pictures and distractor 150 stimuli. The target picture is chosen from a set of photos of fruit. Each stimulus appears after a 151 random delay between 1000 and 3000 ms to discourage anticipatory responding. The participant 152 is instructed to respond as quickly as possible within 1500ms. The assessment ends when a 153 participant responds to ten "Go" trials. If the participant submits three incorrect responses 154 (responding to "no-go" or failing to respond to "go"), the participant will restart the task. The 155 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 participant is given feedback on timing and correctness. This assessment is used to measure 156 response inhibition and speed of information processing. 157 158 2.3.5 Mild Behavioral Impairment Checklist 159 The MBI-C is included in the BHR study partner portal and is therefore completed by an 160 informant. The MBI-C is explicit that symptoms are de novo in later life, represent a change 161 from longstanding patterns of behavior, and are persistent for at least six months. The MBI-C 162 consists of questions in the five MBI domains of apathy, mood and anxiety, agitation and 163 impulsivity, impaired social cognition, and psychosis, with items geared towards capturing NPS 164 in community dwelling, functionally independent, non-demented older adults. The scale takes 165 ~7-8 minutes to complete, consisting of 34 questions; scoring is from 0-3, representing absent, 166 mild, moderate, and severe changes, with a total score range of 0-102 28 . 167 168 2.4 Statistical Analysis 169 Continuous demographic variables (age and years of education) were analyzed using 170 independent sample t-tests to compare MBI+ and MBI-groups; sex distribution between the two 171 groups was analyzed using chi-square tests. MBI-C was dichotomized based on a validation in 172 primary care non-demented older adults in which scores of >7 differentiated MBI+ from MBI-173 with a sensitivity of 0.93, specificity of 0.76 and AUC of 0.93 37 . As exploratory analyses, 174 cutpoints of >5 and >6 were also analyzed. Univariate Analysis of Covariance (ANCOVA) was 175 used to compare performance on Lumosity cognitive tests between MBI+ and MBI-groups, 176 covarying for age, sex, education, and neuropsychological and neurobehavioral assessment 177 interval. Skewed data were log-transformed, however the TMT response time variable was 178 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101/2021.07.19.21260787 doi: medRxiv preprint analyzed with a negative binomial regression due a skewed distribution with an 179 overrepresentation of zeros. For Go/No-Go errors, ordinal logistic regression was performed 180 because the response variable only had three possible values: 0, 1, and 2. 181 Additionally, negative binomial regressions were fitted to assess Lumosity task 182 prediction of MBI-C total scores. Negative binomial regression is preferred when the data are 183 skewed, as in this sample where the mode on the MBI-C is zero indicating no emergent and 184 persistent NPS. Lumosity task measures as continuous scores were the independent variables in 185 these models. The covariates included were age, sex, education, and neuropsychological and 186 neurobehavioral assessment interval. The p values for Lumosity task measures were calculated 187 using likelihood ratio tests. 188 Statistical analyses were performed using SPSS v26 and R 3.6.2. 189 & 2f) . The effect sizes for these differences were modest. Of the tests that 200 significantly differed between groups, the largest effect size (Cohen's f) was for reverse memory 201 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. Negative binomial regressions utilizing Lumosity scores to predict MBI score determined 205 that worse memory span (X 2 (1, N=499)=6.6, p=0.01), worse reverse memory span X 2 (1, 206 N=498)=5.4, (p= 0.02), more TMT errors (X 2 (1, N=499)=5.8, p=0.02) and longer TMT response 207 time (X 2 (1, N=499)=9.6, p=0.002) were all associated with higher MBI-C total scores. Go/No-208 Go errors (X 2 (1, N=497)=0.16, p=0.69) and Go/No-Go response time (X 2 (1, N=497)=0.97, 209 p=0.33) were not associated with MBI-C score (Table 5) . Our data indicate that the BHR is an effective platform to conduct remote assessments of 227 cognitive functioning with convergence of behavioral and cognitive tests. Poorer performance on 228 unsupervised online neuropsychological testing has been associated with self-report MCI and 229 AD 8 . Online participant testing is an efficient and reliable tool for neuropsychological testing, 230 which can identify performance decrements in executive dysfunction and memory 32 . Similarly, 231 online informant reports such as those collected in the BHR study partner portal are valuable and 232 informative. Online study-partner reported cognitive decline is comparable to data collected in 233 clinic, is associated with objectively defined participant cognition 35 , and is associated with 234 amyloid, clinical diagnosis of dementia due to AD, and in-clinic cognitive screening test scores 5 . 235 In our study, online informant-reported behavioral symptoms associated with differences in 236 memory and executive function collected via the participant portal. This harmonized utilization 237 of participant and study partner portals is effective and can allow continuation of research 238 activities even during trying times such as the recent pandemic, where consistent in person visits 239 between clinicians and patients were not feasible. Although the COVID-19 pandemic has 240 highlighted the need for alternative infrastructure to allow continued care, the tools that have 241 been developed may permit the assessment of older adults who for physical, social, or cognitive 242 reasons could not previously access care. This approach also allows outreach to areas less 243 accessible to academic centers. 244 245 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. was determined using polygenic risk scores. AD genetic risk was associated with worse 262 cognition in the informant-reported MBI+ group but not in the MBI-group. The strongest 263 association was in those with more severe MBI, aged ≥65 47 . These convergent findings support 264 leveraging online cognitive and behavioral measures to explore dementia risk. In a recent study 265 of National Alzheimer Coordinating Center data, the combination of informant-reported MBI 266 and subjective cognitive decline (SCD) had a greater risk of incident cognitive and functional 267 decline at three years compared to either MBI or SCD alone 24 . Further, in a subsequent study, 268 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 those with SCD and MBI together had a shorter median time to incident MCI compared to those 269 with SCD in the absence of MBI 48 . Taken together the results suggest that individuals with subtle 270 neuropsychological test score differences and MBI together may be at higher risk for cognitive 271 and functional decline. 272 As the case ascertainment instrument developed to measure MBI in accordance with the 274 ISTAART-AA MBI criteria, the MBI-C was designed to: 1) operationalize the MBI concept; 2) 275 measure a selected list of NPS which may help identify preclinical or prodromal dementia; and 276 3) predict risk of several dementias 28 . This instrument has been validated in an online cohort of 277 cognitively normal older adults 27 , a primary care sample with SCD 29 or MCI 49 , and a cognitive 278 neurology clinic population with SCD and MCI 50 . 279 280 However, limitations in our study may affect interpretation and generalizability. These 281 limitations include high education levels and restriction to participants and study-partners who 282 can successfully complete tasks online 35 . Since the BHR is an online self-report database, the 283 lack of a clinical diagnosis within the sample group is a potential source of error. BHR 284 participants may have undiagnosed and/or unreported neurodegenerative disease or psychiatric 285 disorders, which may be associated with greater MBI score. While online cognitive testing has 286 been validated 8,33 , further research is needed, given the lack of supervision or control for test 287 environment, external factors, distractors, or cues. Further, we were not able to control for 288 important disease related factors such as severity and time since symptom onset. Although MBI 289 was associated with statistically significant differences in Lumosity neuropsychological test 290 scores, effect sizes were small, and the clinical significance of these differences is difficult to 291 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 interpret in the largely cognitively healthy population enrolled in BHR. Our data are promising 292 but not conclusive, and further research is required. Whether these small differences in cognitive 293 test scores represent greater risk for incident cognitive decline and dementia can be addressed in 294 the future using longitudinal data and a cohort that includes participants with cognitive 295 impairment. 296 In summary, in this BHR study combining self-and informant-rated measures, we observed the 298 convergence of behavioral risk markers for dementia and cognitive differences, reflected by 299 neuropsychological tests incorporating memory and executive function. The findings lend 300 additional support to online unsupervised administration of cognitive and neuropsychiatric 301 measures, as a low-cost approach to improve access to neurocognitive assessments, potentially 302 identifying at-risk older adults. Research, and has received consulting fees/honoraria from Otsuka/Lundbeck, outside the 313 submitted work. His institution has received funds from Acadia, Biogen, Roche, and Sunovion, 314 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 also outside the submitted work. RLN is a co-investigator for the BHR. RSM has received grant 315 funding from the National Institute of Mental Health and has received research support from 316 • This approach is useful when in-person assessments are not feasible (physical, social, 328 cognitive or health systems-realted (e.g., the COVID-19 pandemic)) 329 • The relationship between mild behavioral impairment (MBI) and cognition in older 330 adults was explored 331 • MBI was associated with small magnitude, but significantly poorer performance in 332 memory and executive function, and may serve as a complementary measure of risk 333 334 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 Excluded participants whose Lumosity cognitive tests were not collected (n = 113; 802 remained) Excluded participants whose Lumosity cognitive tests and MBI-C were not collected within a year (n = 416; 499 remained) Analysis . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 22, 2021. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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