Diabetes, hemoglobin A1c, and cognitive performance in older adults: is there any impact of frailty? Evidence from the ELSI-Brazil study

Abstract The aim of this study was to evaluate the association between diabetes and cognitive performance in a nationally representative study in Brazil. We also aimed to investigate the interaction between frailty and diabetes on cognitive performance. A cross-sectional analysis of the Brazilian Longitudinal Study of Aging (ELSI-Brazil) baseline data that included adults aged 50 years and older was conducted. Linear regression models were used to study the association between diabetes and cognitive performance. A total of 8,149 participants were included, and a subgroup analysis was performed in 1,768 with hemoglobin A1c data. Diabetes and hemoglobin A1c levels were not associated with cognitive performance. Interaction of hemoglobin A1c levels with frailty status was found on global cognitive z-score (P-value for interaction=0.038). These results suggested an association between higher hemoglobin A1c levels and lower cognitive performance only in non-frail participants. Additionally, undiagnosed diabetes with higher hemoglobin A1c levels was associated with both poor global cognitive (β=-0.36; 95%CI: -0.62; -0.10, P=0.008) and semantic verbal fluency performance (β=-0.47; 95%CI: -0.73; -0.21, P=0.001). In conclusion, higher hemoglobin A1c levels were associated with lower cognitive performance among non-frail participants. Higher hemoglobin A1c levels without a previous diagnosis of diabetes were also related to poor cognitive performance. Future longitudinal analyses of the ELSI-Brazil study will provide further information on the role of frailty in the association of diabetes and glycemic control with cognitive decline.

Diabetes, hemoglobin A1c, and cognitive performance in older adults: is there any impact of frailty? Evidence from the ELSI-Brazil study.

The aim of this study was to evaluate the association between diabetes and cognitive performance in a nationally representative study in Brazil. We also aimed to investigate the interaction between frailty and diabetes on cognitive performance. A cross-sectional analysis of the Brazilian Longitudinal Study of Aging (ELSI-Brazil) baseline data that included adults aged 50 years and older was conducted. Linear regression models were used to study the association between diabetes and cognitive performance. A total of 8,149 participants were included, and a subgroup analysis was performed in 1,768 with hemoglobin A1c data. Diabetes and hemoglobin A1c levels were not associated with cognitive performance. Interaction of hemoglobin A1c levels with frailty status was found on global cognitive z-score (P-value for interaction=0.038). These results suggested an association between higher hemoglobin A1c levels and lower cognitive performance only in non-frail participants. Additionally, undiagnosed diabetes with higher hemoglobin A1c levels was associated with both poor global cognitive (ß=-0.36; 95%CI: -0.62; -0.10, P=0.008) and semantic verbal fluency performance (ß=-0.47; 95%CI: -0.73; -0.21, P=0.001). In conclusion, higher hemoglobin A1c levels were associated with lower cognitive performance among non-frail participants. Higher hemoglobin A1c levels without a previous diagnosis of diabetes were also related to poor cognitive performance. Future longitudinal analyses of the ELSI-Brazil study will provide further information on the role of frailty in the association of diabetes and glycemic control with cognitive decline.

Data-driven decision making for the screening of cognitive impairment in primary care: a machine learning approach using data from the ELSA-Brasil study.

The systematic assessment of cognitive performance of older people without cognitive complaints is controversial and unfeasible. Identifying individuals at higher risk of cognitive impairment could optimize resource allocation. We aimed to develop and test machine learning models to predict cognitive impairment using variables obtainable in primary care settings. In this cross-sectional study, we included 8,291 participants of the baseline assessment of the ELSA-Brasil study, who were aged between 50 and 74 years and were free of dementia. Cognitive performance was assessed with a neuropsychological battery and cognitive impairment was defined as global cognitive z-score below 2 standard deviations. Variables used as input to the prediction models included demographics, social determinants, clinical conditions, family history, lifestyle, and laboratory tests. We developed machine learning models using logistic regression, neural networks, and gradient boosted trees. Participants' mean age was 58.3±6.2 years, 55% were female. Cognitive impairment was present in 328 individuals (4%). Machine learning algorithms presented fair to good discrimination (areas under the ROC curve between 0.801 and 0.873). Extreme Gradient Boosting presented the highest discrimination, high specificity (97%), and negative predictive value (97%). Seventy-six percent of the individuals with cognitive impairment were included among the highest ranked individuals by this algorithm. In conclusion, we developed and tested a machine learning model to predict cognitive impairment based on primary care data that presented good discrimination and high specificity. These characteristics could support the detection of patients who would not benefit from cognitive assessment, facilitating the allocation of human and economic resources.

Data-driven decision making for the screening of cognitive impairment in primary care: a machine learning approach using data from the ELSA-Brasil study

The systematic assessment of cognitive performance of older people without cognitive complaints is controversial and unfeasible. Identifying individuals at higher risk of cognitive impairment could optimize resource allocation. We aimed to develop and test machine learning models to predict cognitive impairment using variables obtainable in primary care settings. In this cross-sectional study, we included 8,291 participants of the baseline assessment of the ELSA-Brasil study, who were aged between 50 and 74 years and were free of dementia. Cognitive performance was assessed with a neuropsychological battery and cognitive impairment was defined as global cognitive z-score below 2 standard deviations. Variables used as input to the prediction models included demographics, social determinants, clinical conditions, family history, lifestyle, and laboratory tests. We developed machine learning models using logistic regression, neural networks, and gradient boosted trees. Participants' mean age was 58.3±6.2 years, 55% were female. Cognitive impairment was present in 328 individuals (4%). Machine learning algorithms presented fair to good discrimination (areas under the ROC curve between 0.801 and 0.873). Extreme Gradient Boosting presented the highest discrimination, high specificity (97%), and negative predictive value (97%). Seventy-six percent of the individuals with cognitive impairment were included among the highest ranked individuals by this algorithm. In conclusion, we developed and tested a machine learning model to predict cognitive impairment based on primary care data that presented good discrimination and high specificity. These characteristics could support the detection of patients who would not benefit from cognitive assessment, facilitating the allocation of human and economic resources.

Association of Cognitive Performance with Frailty in Older Individuals with Cognitive Complaints.

OBJECTIVES: Frailty is a risk factor for poor cognitive performance in older adults. However, few studies have evaluated the association of cognitive performance with frailty in a low- to middle-income country (LMIC). This study aimed to investigate an association between cognitive performance and frailty in older adults with memory complaints in Brazil. Secondarily, we aim to assess an association of cognitive performance with gait speed and grip strength. DESIGN: Cross-sectional study. SETTING: Outpatient service from a LMIC. PARTICIPANTS: Older adults with memory complaints reported by the participants, their proxies, or their physicians. MEASUREMENTS: Frailty was evaluated using the Cardiovascular Health Study criteria. A neuropsychological battery evaluated memory, attention, language, visuospatial function, executive function. Linear regression analysis with adjustment for age, sex, and education was used. We also evaluated the interaction of education with frailty, grip strength, and gait speed. RESULTS: Prefrailty was associated with poor performance in the memory domain, as well as slower gait speed was associated with worse performance in memory, attention, language, and executive function. Frailty and grip strength were not associated with cognitive performance. Interactions of education with gait speed were significant for global performance, as well as for attention and visuospatial ability. CONCLUSION: In elderly patients with memory complaints, prefrailty was associated with poor memory performance. Slowness was associated with poorer performance in some cognitive domains, mainly in participants with low education.

Association of sleep disturbances with sarcopenia and its defining components: the ELSA-Brasil study.

Sarcopenia and sleep problems share common physiopathology. We aimed to investigate the association of sleep disturbances with sarcopenia and its defining components in Brazilian middle-aged and older adults. In this cross-sectional analysis of the second wave of the ELSA-Brasil study, we included data from 7948 participants aged 50 years and older. Muscle mass was evaluated by bioelectrical impedance analysis and muscle strength by hand-grip strength. Sarcopenia was defined according to the Foundation for the National Institutes of Health criteria. Sleep duration and insomnia complaint were self-reported. Short sleep duration was considered as ≤6 h/night and long sleep duration as >8 h/night. High risk of obstructive sleep apnea (OSA) was assessed using the STOP-Bang questionnaire. Possible confounders included socio-demographic characteristics, lifestyle, clinical comorbidities, and use of sedatives and hypnotics. The frequencies of sarcopenia, low muscle mass, and low muscle strength were 1.6, 21.1, and 4.1%, respectively. After adjustment for possible confounders, high risk of OSA was associated with low muscle mass (OR=2.17, 95%CI: 1.92-2.45). Among obese participants, high risk of OSA was associated with low muscle strength (OR=1.68, 95%CI: 1.07-2.64). However, neither short nor long sleep duration or frequent insomnia complaint were associated with sarcopenia or its defining components. In conclusion, high risk of OSA was associated with low muscle mass in the whole sample and with low muscle strength among obese participants. Future studies are needed to clarify the temporal relationship between both conditions.

Death trends based on autopsy data compared to the beginning of the coronavirus pandemic in Brazil.

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

Ideal vascular health and cognitive performance in the Brazilian Longitudinal Study of Adult Health.

BACKGROUND AND PURPOSE: Most evidence for the association between ideal vascular health (IVH) and cognitive performance comes from high income countries. The aim was to investigate this association in the Brazilian Longitudinal Study of Adult Health. METHODS: Cognition was assessed using the word list, verbal fluency and trail making tests. The IVH score included ideal metrics for body mass index, smoking, physical activity, diet, blood pressure, fasting glucose and total cholesterol. Poor, intermediate and optimal health were characterized in those presenting 0-2, 3-4, 5-7 ideal metrics, respectively. To determine the association between IVH score and cognitive performance, linear regression models adjusted for age, sex, education, race, alcohol use, depression and thyroid function were used. RESULTS: In 12 271 participants, the mean age was 51.3 ± 8.9 years, 54% were women, 57% White and 53% had poor vascular health. Participants with intermediate (ß = 0.064, 95% confidence interval 0.033; 0.096) and optimal health (ß = 0.108, 95% confidence interval 0.052; 0.164) had better global cognitive Z-scores. In addition, interactions of IVH score with age, education and race were found, suggesting a better cognitive performance with higher IVH in older adults, Black/Brown participants and those with lower levels of education. CONCLUSION: Ideal vascular health was associated with better cognitive performance. Older, Black/Brown and low-educated participants had better cognition in the presence of higher IVH scores.

Death trends based on autopsy data compared to the beginning of the coronavirus pandemic in Brazil

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

Association of sleep disturbances with sarcopenia and its defining components: the ELSA-Brasil study

Sarcopenia and sleep problems share common physiopathology. We aimed to investigate the association of sleep disturbances with sarcopenia and its defining components in Brazilian middle-aged and older adults. In this cross-sectional analysis of the second wave of the ELSA-Brasil study, we included data from 7948 participants aged 50 years and older. Muscle mass was evaluated by bioelectrical impedance analysis and muscle strength by hand-grip strength. Sarcopenia was defined according to the Foundation for the National Institutes of Health criteria. Sleep duration and insomnia complaint were self-reported. Short sleep duration was considered as ≤6 h/night and long sleep duration as >8 h/night. High risk of obstructive sleep apnea (OSA) was assessed using the STOP-Bang questionnaire. Possible confounders included socio-demographic characteristics, lifestyle, clinical comorbidities, and use of sedatives and hypnotics. The frequencies of sarcopenia, low muscle mass, and low muscle strength were 1.6, 21.1, and 4.1%, respectively. After adjustment for possible confounders, high risk of OSA was associated with low muscle mass (OR=2.17, 95%CI: 1.92-2.45). Among obese participants, high risk of OSA was associated with low muscle strength (OR=1.68, 95%CI: 1.07-2.64). However, neither short nor long sleep duration or frequent insomnia complaint were associated with sarcopenia or its defining components. In conclusion, high risk of OSA was associated with low muscle mass in the whole sample and with low muscle strength among obese participants. Future studies are needed to clarify the temporal relationship between both conditions.

Association between cognitive performance and self-reported glaucoma in middle-aged and older adults: a cross-sectional analysis of ELSA-Brasil.

Recent evidence suggests that glaucoma and Alzheimer's disease are neurodegenerative diseases sharing common pathophysiological and etiological features, although findings are inconclusive. We sought to investigate whether self-reported glaucoma patients without dementia present poorer cognitive performance, an issue that has been less investigated. We employed cross-sectional data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) and included participants ≥50 years of age without a known diagnosis of dementia and a self-reported glaucoma diagnosis. We excluded those with previous stroke, other eye conditions, and using drugs that could impair cognition. We evaluated cognition using delayed word recall, phonemic verbal fluency, and trail making (version B) tests. We used multinomial linear regression models to investigate associations between self-reported glaucoma with cognition, adjusted by several sociodemographic and clinical variables. Out of 4,331 participants, 139 reported glaucoma. Fully-adjusted models showed that self-reported glaucoma patients presented poorer performance in the verbal fluency test (ß=-0.39, 95%CI=-0.64 to -0.14, P=0.002), but not in the other cognitive assessments. Thus, our results support the hypothesis that self-reported glaucoma is associated with poor cognitive performance; however, longitudinal data are necessary to corroborate our findings.

Association between cognitive performance and self-reported glaucoma in middle-aged and older adults: a cross-sectional analysis of ELSA-Brasil

Recent evidence suggests that glaucoma and Alzheimer's disease are neurodegenerative diseases sharing common pathophysiological and etiological features, although findings are inconclusive. We sought to investigate whether self-reported glaucoma patients without dementia present poorer cognitive performance, an issue that has been less investigated. We employed cross-sectional data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) and included participants ≥50 years of age without a known diagnosis of dementia and a self-reported glaucoma diagnosis. We excluded those with previous stroke, other eye conditions, and using drugs that could impair cognition. We evaluated cognition using delayed word recall, phonemic verbal fluency, and trail making (version B) tests. We used multinomial linear regression models to investigate associations between self-reported glaucoma with cognition, adjusted by several sociodemographic and clinical variables. Out of 4,331 participants, 139 reported glaucoma. Fully-adjusted models showed that self-reported glaucoma patients presented poorer performance in the verbal fluency test (β=-0.39, 95%CI=-0.64 to -0.14, P=0.002), but not in the other cognitive assessments. Thus, our results support the hypothesis that self-reported glaucoma is associated with poor cognitive performance; however, longitudinal data are necessary to corroborate our findings.

Association between ideal cardiovascular health and depression incidence: a longitudinal analysis of ELSA-Brasil.

OBJECTIVE: We investigated whether ideal cardiovascular health (ICH), a metric proposed by the American Heart Association, predicts depression development. METHODS: Cohort analysis from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Adults with no current depression and other common mental disorders, cardiovascular diseases, and antidepressant drug use at baseline had their ICH (composite score of smoking, dietary habits, body mass index, blood pressure, fasting glucose, cholesterol, and physical activity) assessed and classified into poor, intermediate, and optimal. Depression was assessed using the Clinical Interview Schedule-Revised (CIS-R). Poisson regression models, adjusted for sociodemographic factors and alcohol consumption, were employed. Stratified analyses were performed for age and sex. RESULTS: We included 9214 participants (mean age 52 ± 9 years, 48.6% women). Overall depression incidence at 3.8-year follow-up was 1.5%. Intermediate and poor ICH significantly increased the risk rate (RR) of developing depression (2.48 [95%CI 1.06-5.78] and 3 [1.28-7.03], respectively) at a 3.8-year follow-up. Higher ICH scores decreased the rate of depression development (RR = 0.84 [0.73-0.96] per metric). Stratified analyses were significant for women and adults < 55 years old. CONCLUSIONS: Poor cardiovascular health tripled depression risk at follow-up in otherwise healthy adults. Ameliorating cardiovascular health might decrease depression risk development.

A 10-min Targeted Geriatric Assessment Predicts Mortality in Fast-Paced Acute Care Settings: A Prospective Cohort Study.

OBJECTIVES: To estimate whether a 10-minute Targeted Geriatric Assessment (10-TaGA) adds utility to sociodemographic characteristics and comorbidities in predicting one-year mortality in busy acute care settings. We have also compared the performance of 10-TaGA with the Identification of Seniors at Risk (ISAR) scale. DESIGN: Prospective cohort study. SETTING: Geriatric day hospital specializing in acute care in Brazil. PARTICIPANTS: 751 older adults aged 79.4 ± 8.4 years (64% female), presenting non-surgical, medical illness requiring hospital-level care (e.g., intravenous therapy, laboratory test, radiology) for ≤ 12 hours. MEASUREMENTS: The 10-TaGA, an easy-to-administer screening tool based on the comprehensive geriatric assessment (CGA), provided a measure of cumulative deficits ranging from 0 (no deficits) to 1 (highest deficit) on admission. Standard risk factors, including sociodemographics (age, gender, ethnicity, income) and the Charlson comorbidity index, were evaluated. The ISAR, a well-validated screening tool, was used for comparison. RESULTS: During one year of follow-up, 130 (17%) participants died. Compared to the ISAR, 10-TaGA offered better accuracy in identifying older patients at risk of death (area under the receiver operating characteristic curve: [AUC] 0.70 vs 0.65; P = 0.03). In a Cox regression model adjusted for sociodemographics and comorbidities, each 0.1 increment in the 10-TaGA score (range 0-1) was associated with increased mortality (hazard ratio = 1.42, 95% confidence interval 1.27-1.59). The addition of 10-TaGA markedly improved the discrimination of the model, which already incorporated standard risk factors (AUC 0.76 vs 0.71; P = 0.005); adding ISAR (AUC 0.73 vs 0.71; P = 0.09) did not have this marked effect. CONCLUSION: The 10-TaGA is an independent predictor of one-year mortality in acute care patients. This multidimensional screening tool offers better accuracy than ISAR when differentiating between older people at low and high risk of death in healthcare settings where providers have limited time and resources.

Prevalence of transactive response DNA-binding protein 43 (TDP-43) proteinopathy in cognitively normal older adults: systematic review and meta-analysis.

OBJECTIVE: To perform a systematic review and meta-analysis on the prevalence of transactive response DNA-binding protein 43 (TDP-43) proteinopathy in cognitively normal older adults. METHODS: We systematically reviewed and performed a meta-analysis on the prevalence of TDP-43 proteinopathy in older adults with normal cognition, evaluated by the Mini-Mental State Examination or the Clinical Dementia Rating. We estimated the overall prevalence of TDP-43 using random-effect models, and stratified by age, sex, sample size, study quality, antibody used to assess TDP-43 aggregates, analysed brain regions, Braak stage, Consortium to Establish a Registry for Alzheimer's Disease score, hippocampal sclerosis and geographic location. RESULTS: A total of 505 articles were identified in the systematic review, and 7 were included in the meta-analysis with 1196 cognitively normal older adults. We found an overall prevalence of TDP-43 proteinopathy of 24%. Prevalence of TDP-43 proteinopathy varied widely across geographic location (North America: 37%, Asia: 29%, Europe: 14%, and Latin America: 11%). Estimated prevalence of TDP-43 proteinopathy also varied according to study quality (quality score >7: 22% vs. quality score <7: 42%), antibody used to assess TDP-43 proteinopathy (native: 18% vs. hyperphosphorylated: 24%) and presence of hippocampal sclerosis (without 24% vs. with hippocampal sclerosis: 48%). Other stratified analyses by age, sex, analysed brain regions, sample size and severity of AD neuropathology showed similar pooled TDP-43 prevalence. CONCLUSIONS: Different methodology to access TDP-43, and also differences in lifestyle and genetic factors across different populations could explain our results. Standardization of TDP-43 measurement, and future studies about the impact of genetic and lifestyle characteristics on the development of neurodegenerative diseases are needed.

Quantifying the accretion of hyperphosphorylated tau in the locus coeruleus and dorsal raphe nucleus: the pathological building blocks of early Alzheimer's disease.

AIMS: Hyperphosphorylated tau neuronal cytoplasmic inclusions (ht-NCI) are the best protein correlate of clinical decline in Alzheimer's disease (AD). Qualitative evidence identifies ht-NCI accumulating in the isodendritic core before the entorhinal cortex. Here, we used unbiased stereology to quantify ht-NCI burden in the locus coeruleus (LC) and dorsal raphe nucleus (DRN), aiming to characterize the impact of AD pathology in these nuclei with a focus on early stages. METHODS: We utilized unbiased stereology in a sample of 48 well-characterized subjects enriched for controls and early AD stages. ht-NCI counts were estimated in 60-µm-thick sections immunostained for p-tau throughout LC and DRN. Data were integrated with unbiased estimates of LC and DRN neuronal population for a subset of cases. RESULTS: In Braak stage 0, 7.9% and 2.6% of neurons in LC and DRN, respectively, harbour ht-NCIs. Although the number of ht-NCI+ neurons significantly increased by about 1.9× between Braak stages 0 to I in LC (P = 0.02), we failed to detect any significant difference between Braak stage I and II. Also, the number of ht-NCI+ neurons remained stable in DRN between all stages 0 and II. Finally, the differential susceptibility to tau inclusions among nuclear subdivisions was more notable in LC than in DRN. CONCLUSIONS: LC and DRN neurons exhibited ht-NCI during AD precortical stages. The ht-NCI increases along AD progression on both nuclei, but quantitative changes in LC precede DRN changes.

Body mass index and cognitive function: the potential for reverse causation.

OBJECTIVE: Higher late life body mass index (BMI) is unrelated to or even predicts lower risk of dementia in late life, a phenomenon that may be explained by reverse causation due to weight loss during preclinical phases of dementia. We aim to investigate the association of baseline BMI and changes in BMI with dementia in a large prospective cohort, and to examine whether weight loss predicts cognitive function. METHODS: Using a national cohort of adults average age 58 years at baseline in 1994 (n=7029), we investigated the associations between baseline BMI in 1994 and memory scores from 2000 to 2010. We also examined the association of BMI change from 1994 to 1998 with memory scores from 2000 to 2010. Last, to investigate reverse causation, we examined whether memory scores in 1996 predicted BMI trajectories from 2000 to 2010. RESULTS: Baseline overweight predicted better memory scores 6 to 16 years later (ß=0.012, 95% confidence interval (CI)=0.001; 0.023). Decline in BMI predicted lower memory scores over the subsequent 12 years (ß=-0.026, 95% CI= -0.041; -0.011). Lower memory scores at mean age 60 years in 1996 predicted faster annual rate of BMI decline during follow-up (ß=-0.158 kg m(-2) per year, 95% CI= -0.223; -0.094). CONCLUSION: Consistent with reverse causation, greater decline in BMI over the first 4 years of the study was associated with lower memory scores over the next decade and lower memory scores was associated with a decline in BMI. These findings suggest that preclinical dementia predicts weight loss for people as early as their late 50s.

d-serine levels in Alzheimer's disease: implications for novel biomarker development.

Alzheimer's disease (AD) is a severe neurodegenerative disorder still in search of effective methods of diagnosis. Altered levels of the NMDA receptor co-agonist, d-serine, have been associated with neurological disorders, including schizophrenia and epilepsy. However, whether d-serine levels are deregulated in AD remains elusive. Here, we first measured D-serine levels in post-mortem hippocampal and cortical samples from nondemented subjects (n=8) and AD patients (n=14). We next determined d-serine levels in experimental models of AD, including wild-type rats and mice that received intracerebroventricular injections of amyloid-ß oligomers, and APP/PS1 transgenic mice. Finally, we assessed d-serine levels in the cerebrospinal fluid (CSF) of 21 patients with a diagnosis of probable AD, as compared with patients with normal pressure hydrocephalus (n=9), major depression (n=9) and healthy controls (n=10), and results were contrasted with CSF amyloid-ß/tau AD biomarkers. d-serine levels were higher in the hippocampus and parietal cortex of AD patients than in control subjects. Levels of both d-serine and serine racemase, the enzyme responsible for d-serine production, were elevated in experimental models of AD. Significantly, d-serine levels were higher in the CSF of probable AD patients than in non-cognitively impaired subject groups. Combining d-serine levels to the amyloid/tau index remarkably increased the sensitivity and specificity of diagnosis of probable AD in our cohort. Our results show that increased brain and CSF d-serine levels are associated with AD. CSF d-serine levels discriminated between nondemented and AD patients in our cohort and might constitute a novel candidate biomarker for early AD diagnosis.

African ancestry protects against Alzheimer's disease-related neuropathology.

Previous studies in dementia epidemiology have reported higher Alzheimer's disease rates in African-Americans when compared with White Americans. To determine whether genetically determined African ancestry is associated with neuropathological changes commonly associated with dementia, we analyzed a population-based brain bank in the highly admixed city of São Paulo, Brazil. African ancestry was estimated through the use of previously described ancestry-informative markers. Risk of presence of neuritic plaques, neurofibrillary tangles, small vessel disease, brain infarcts and Lewy bodies in subjects with significant African ancestry versus those without was determined. Results were adjusted for multiple environmental risk factors, demographic variables and apolipoprotein E genotype. African ancestry was inversely correlated with neuritic plaques (P=0.03). Subjects with significant African ancestry (n=112, 55.4%) showed lower prevalence of neuritic plaques in the univariate analysis (odds ratio (OR) 0.72, 95% confidence interval (CI) 0.55-0.95, P=0.01) and when adjusted for age, sex, APOE genotype and environmental risk factors (OR 0.43, 95% CI 0.21-0.89, P=0.02). There were no significant differences for the presence of other neuropathological alterations. We show for the first time, using genetically determined ancestry, that African ancestry may be highly protective of Alzheimer's disease neuropathology, functioning through either genetic variants or unknown environmental factors. Epidemiological studies correlating African-American race/ethnicity with increased Alzheimer's disease rates should not be interpreted as surrogates of genetic ancestry or considered to represent African-derived populations from the developing nations such as Brazil.