The "Great Village," a cultural adaptation of a psychoeducation intervention the “Savvy Caregiver” for African American caregivers of persons living with dementia (PLwD), aims to develop caregivers’ skills and improve the quality of the lives of both the PLwD and their caregivers. The goal of this study was to determine the effectiveness of the Great Village on depressive symptoms, anxiety, burden, and mastery in African American caregivers (N = 142). A three-arm randomized control trial (Great Village, Great Village + exercise, and attention control) was conducted over a period of 6 months. Caregivers who received either Great Village or Great Village + exercise reported significant reduction in depressive symptoms and improvement in mastery. Caregivers who received only Great Village reported a reduction in anxiety. Receiving no intervention worsened caregiver burden. African American caregivers should receive culturally tailored interventions to support their health and well-being and improve their competence in caregiving.

Background:Norms for the Uniform Data Set Version 3 Neuropsychological Battery are available for cognitively normal individuals based on age, education, and sex; however, these norms do not include race. We provide expanded norms for African Americans and whites.Methods:Data from 32 Alzheimer's Disease Centers (ADCs) and ADC affiliated cohorts with global Clinical Dementia Rating Scale (CDR) Dementia Staging Instrument scores of 0 were included. Descriptive statistics for each test were calculated by age, sex, race, and education. Multiple linear regressions were conducted to estimate the effect of each demographic variable; squared semipartial correlation coefficients measured the relative importance of variables.Results:There were 8313 participants (16% African American) with complete demographic information, ranging from 6600 to 7885 depending on the test. Lower scores were found for older and less educated groups, and African Americans versus whites. Education was the strongest predictor for most tests, followed in order by age, race, and sex. Quadratic terms were significant for age and education, indicating some nonlinearity, but did not substantially increase R2.Conclusions:Although race-based norms represent incomplete proxies for other sociocultural variables, the appropriate application of these norms is important given the potential to improve diagnostic accuracy and to reduce misclassification bias in cognitive disorders of aging such as Alzheimer disease.

INTRODUCTION: Federally funded Alzheimer's Disease Centers in the United States have been using a standardized neuropsychological test battery as part of the National Alzheimer's Coordinating Center Uniform Data Set (UDS) since 2005. Version 3 (V3) of the UDS replaced the previous version (V2) in 2015. We compared V2 and V3 neuropsychological tests with respect to their ability to distinguish among the Clinical Dementia Rating (CDR) global scores of 0, 0.5, and 1. METHODS: First, we matched participants receiving V2 tests (V2 cohort) and V3 tests (V3 cohort) in their cognitive functions using tests common to both versions. Then, we compared receiver-operating characteristic (ROC) area under the curve in differentiating CDRs for the remaining tests. RESULTS: Some V3 tests performed better than V2 tests in differentiating between CDR 0.5 and 0, but the improvement was limited to Caucasian participants. DISCUSSION: Further efforts to improve the ability for early identification of cognitive decline among diverse racial groups are required.

RNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing.

Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies.

Background: Cognitive abilities tend to decline in advanced age. A novel protective factor of cognitive decline in advanced age is purpose-in-life (PiL), a trait-like tendency to derive life meanings and purpose. However, whether PiL protects against cognitive decline in late-middle-age is unclear. Hence, we examined the association between PiL and perceived cognitive decline, one of the earliest detectable cognitive symptoms before the onset of cognitive impairment. Furthermore, we used a machine learning approach to investigate whether PiL is a robust predictor of cognitive decline when considered with the known protective and risk factors for cognition. Methods: PiL was assessed with a 10-item questionnaire and perceived cognitive decline with the Cognitive Function Instrument among 5,441 Emory Healthy Aging Study participants, whose mean age was 63 and 51% were employed. Association between PiL and perceived cognitive decline was examined with linear regression adjusting for relevant confounding factors. Elastic Net was performed to identify the most robust predictors of cognitive decline. Results: Greater PiL was associated with less perceived cognitive decline after adjusting for the relevant factors. Furthermore, Elastic Net modeling suggested that PiL is a robust predictor of cognitive decline when considered simultaneously with known protective (education, exercise, enrichment activities) and risk factors for cognition (depression, anxiety, diagnosed medical, mental health problems, smoking, alcohol use, family history of dementia, and others) Limitation: This is a cross-sectional study. Conclusions: PiL is a robust protective factor of perceived cognitive decline observed as early as middle age. Thus, interventions to enhance PiL merit further investigation.

RNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing.

Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies.

Background: Cognitive abilities tend to decline in advanced age. A novel protective factor of cognitive decline in advanced age is purpose-in-life (PiL), a trait-like tendency to derive life meanings and purpose. However, whether PiL protects against cognitive decline in late-middle-age is unclear. Hence, we examined the association between PiL and perceived cognitive decline, one of the earliest detectable cognitive symptoms before the onset of cognitive impairment. Furthermore, we used a machine learning approach to investigate whether PiL is a robust predictor of cognitive decline when considered with the known protective and risk factors for cognition. Methods: PiL was assessed with a 10-item questionnaire and perceived cognitive decline with the Cognitive Function Instrument among 5,441 Emory Healthy Aging Study participants, whose mean age was 63 and 51% were employed. Association between PiL and perceived cognitive decline was examined with linear regression adjusting for relevant confounding factors. Elastic Net was performed to identify the most robust predictors of cognitive decline. Results: Greater PiL was associated with less perceived cognitive decline after adjusting for the relevant factors. Furthermore, Elastic Net modeling suggested that PiL is a robust predictor of cognitive decline when considered simultaneously with known protective (education, exercise, enrichment activities) and risk factors for cognition (depression, anxiety, diagnosed medical, mental health problems, smoking, alcohol use, family history of dementia, and others) Limitation: This is a cross-sectional study. Conclusions: PiL is a robust protective factor of perceived cognitive decline observed as early as middle age. Thus, interventions to enhance PiL merit further investigation.

RNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing.

Depression is a common condition, but current treatments are only effective in a subset of individuals. To identify new treatment targets, we integrated depression genome-wide association study (GWAS) results (N = 500,199) with human brain proteomes (N = 376) to perform a proteome-wide association study of depression followed by Mendelian randomization. We identified 19 genes that were consistent with being causal in depression, acting via their respective cis-regulated brain protein abundance. We replicated nine of these genes using an independent depression GWAS (N = 307,353) and another human brain proteomic dataset (N = 152). Eleven of the 19 genes also had cis-regulated mRNA levels that were associated with depression, based on integration of the depression GWAS with human brain transcriptomes (N = 888). Meta-analysis of the discovery and replication proteome-wide association study analyses identified 25 brain proteins consistent with being causal in depression, 20 of which were not previously implicated in depression by GWAS. Together, these findings provide promising brain protein targets for further mechanistic and therapeutic studies.

Background: Cognitive abilities tend to decline in advanced age. A novel protective factor of cognitive decline in advanced age is purpose-in-life (PiL), a trait-like tendency to derive life meanings and purpose. However, whether PiL protects against cognitive decline in late-middle-age is unclear. Hence, we examined the association between PiL and perceived cognitive decline, one of the earliest detectable cognitive symptoms before the onset of cognitive impairment. Furthermore, we used a machine learning approach to investigate whether PiL is a robust predictor of cognitive decline when considered with the known protective and risk factors for cognition. Methods: PiL was assessed with a 10-item questionnaire and perceived cognitive decline with the Cognitive Function Instrument among 5,441 Emory Healthy Aging Study participants, whose mean age was 63 and 51% were employed. Association between PiL and perceived cognitive decline was examined with linear regression adjusting for relevant confounding factors. Elastic Net was performed to identify the most robust predictors of cognitive decline. Results: Greater PiL was associated with less perceived cognitive decline after adjusting for the relevant factors. Furthermore, Elastic Net modeling suggested that PiL is a robust predictor of cognitive decline when considered simultaneously with known protective (education, exercise, enrichment activities) and risk factors for cognition (depression, anxiety, diagnosed medical, mental health problems, smoking, alcohol use, family history of dementia, and others) Limitation: This is a cross-sectional study. Conclusions: PiL is a robust protective factor of perceived cognitive decline observed as early as middle age. Thus, interventions to enhance PiL merit further investigation.