bluuebunny/crossref_metadata_2025 huggingface dataset:
Alzheimer's Disease Genotype Frequencies Differ in Top Risk Alleles Between Mexican Americans and Non‐Hispanic Whites in HABLE Cohort
Authors: Housini Mohammad , Rao Sumedha R , Phillips Nicole , O'Bryant Sid E. , Barber Robert
Published: December 2022

Background

Alzheimer’s Disease (AD) and/or other related dementias remain a significant burden on our aging population. Here we evaluate the top 10 AD risk alleles previously reported by Kunkle et al. (2018) in Mexican Americans and non‐Hispanic whites enrolled in the Healthy Aging Brain in Latino Elders Study (HABLE) cohort to see if allele frequencies vary based on ethnicity.

Method

DNA was extracted from buffy coat samples (n = 1635) on the Hamilton robotic system with the Mag‐Bind Blood & Tissue DNA HDQ 96 Kit. Genotyping was performed per manufacturer’s protocol using the Illumina Infinium Global Screening Array (GSA) and analyzed with Genome Studio 2.0. Samples with call rates less than 98% were repeated or excluded.

Allele and genotype frequencies were calculated using standard statistics by compiling the top ten AD risk alleles from Kunkle et al. (2018) and measuring their frequencies in the HABLE cohort.

Result

Our data suggest varying degrees of allele and genotype frequencies among the top 10 risk conferring SNPs between Mexican Americans and Non‐Hispanic Whites. In particular, we show some instances (BIN1, PTK2B) where the heterozygotes are in higher frequency than homozygotes. 8 of our evaluated SNPs show a difference greater than 5% between the two ethnicities

Conclusion

It may be beneficial to further study the top AD risk alleles among different ethnicities to determine if there are variable frequencies in those populations. We plan to expand and continue this work in other ethnicities and further elaborate on these differences to promote ethnicity targeted diagnostics and help reduce health disparities in medicine and science.
Longitudinal trajectory of microglial activation and astrocyte activation
Authors: Edison Paul
Published: December 2022

Background

Neuroinflammation plays a significant role in the pathogenesis of AD. Here, we evaluate neuroinflammation, the interrelationship between neuroinflammation, amyloid and tau pathologies, and the impact of neuroinflammation in disease trajectory. We specifically focus on microglia as a major player in neuroinflammation and spatial and temporal variation of microglial phenotypes and novel methods of evaluation of astroglial activation.

Hypothesis

Microglial activation is the driver of neuronal dysfunction and tau aggregation in neurodegenerative diseases, and that levels of microglial activation will correlate with tau aggregation.

Astrocyte activation could be detected by novel astrocyte marker [11C]BU99008 PET

Methods

We evaluated AD, MCI and cognitively normal subjects using amyloid ([18F]Flutemetamol), tau ([18F]AV1451 and neuroinflammation using [11C]PBR28 PET scans. A separate group of AD, MCI and control subjects were evaluated using novel astrocyte marker [11C]BU99008 PET along with [18F]FDG PET and amyloid PET. [11C]PBR28 and [11C]BU99008 PET scans were analysed using two tissue compartmental model, while [18F]Flutemetamol was analysed using target to cerebellar ratio. [18F]FDG PET was analysed using pons as a reference region. We performed regional and voxel wise analysis for all the tracers.

Results

Microglial activation was elevated in different cortical regions in both AD and MCI subjects. There were areas of increased astrocyte activation in both AD and MCI. Higher microglial activation was associated with increased tau formation and neuronal damage in later stages of the disease. Interestingly, there was increased astrocyte activation in the early stages of the disease.

Conclusion

While microglial activation in the late phase of the disease is associated with neuronal damage, activation of the astrocytes is prominent in the early stage of the disease and may be associated with neuroprotection. This suggests that in targeting glial activation as a therapeutic strategy, we must target astrocyte and microglia separately and in different stages of the disease.
Cholinergic drug downregulates annexin A3 in platelets of Alzheimer’s Disease patients
Authors: Park Lucas Yongsoo , Gattaz Wagner Farid , Joaquim Helena Passarelli Giroud , Talib Leda Leme
Published: December 2022

Background

Investigation of the expression of annexin A3 (ANXA3) platelets of Alzheimer´s Disease patients pre and post three‐month treatment with cholinesterase inhibitors and compared to healthy controls.

Method

The sample consisted of healthy controls (n=24) and AD drug‐naïve patients (n=34), diagnosed according to DSM‐IV and specificized according to NINCDS‐ADRDA diagnostic criteria. After three months of treatment with cholinesterase inhibitors, platelets were extracted from blood samples of the same AD patients (n=34). The Cambridge cognitive test (CAMCOG) was used as a measure of global cognitive performance, however, scores on both tests were not used to establish the patients' diagnosis. The method of Western Blotting sample analysis was performed through primary antibodies against ANXA3 and secondary antibody, anti‐rabbit IgG‐HRP peroxidase. Student's t‐test or Mann‐Whitney, Pearson's Chi‐square tests were used for numerical variables, Kolmogorov‐Smirnov test were used to analyze a normal distribution and Wilcoxon test to longitudinal variables. Spearman’s rank correlation coefficient was performed for association between ANXA3 levels and clinical parameters.

Result

There was no difference in ANXA3 expression between AD patients before treatment and healthy controls (p=0.926). However, after three months with anticholinergic treatment the AD patients present a decrease in ANXA3 expressions (p=0.012).

Conclusion

ANXA3 levels on platelets samples of patients diagnosed with AD decrease before an evident improvement of the clinical manifestation of the disease.
Hyperacusis in Frontal Variant Alzheimer’s Dementia ‐ an unrecognized symptom?
Authors: Taiwo Tolulola O
Published: December 2022

Background

Disruptive behaviors are common in individuals living with Alzheimer’s dementia. The identification of the factors that contribute and exacerbate these behaviors is important.

Method

Retrospective Chart Review of Patients with Frontal Variant Alzheimer’s dementia seen by the Specialized Geriatric Services in Red Deer between 2019 and 2022. Demographic and clinical data, cognitive assessments and behavioral assesssment tools were used in assessing patients.

Result

Hyperacusis was reported in 8 of the 42 patients with frontal variant AD. The hypersensitivity to sound was associated with restlessness and agitation. Patients with hyperacusis had poor functional status and had prominent language disturbances.

Conclusion

Hyperacusis may be an underrecognized condition in patients living with Alzheimer’s dementia. It may also be indication of disease severity in patients with frontal variant Alzheimer’s dementia.
Smart Home Tech: an interface to provide feedback to caregivers of persons living with cognitive impairment
Authors: Thomas Neil W. , Bhati Divya K , Ault Laura , Lariviere‐Chartier Julien , Petriu Mihaela D , Wallace Bruce , Knoefel Frank , Kaye Jeffrey A , Goubran Rafik
Published: December 2022

Background

Home‐based sensor technologies can detect information on daily activities, such as sleep, activity level, and time spent together. This is relevant information for care partners of individuals with cognitive impairment as it can detect early changes in daily activities and cognition. The challenge is how to present thousands of data points to care partners in real‐time, allowing them to make adjustments in their daily routine to help reduce burden.

Method

The Collaborative Aging Research using Technology (CART) sensor platform was installed in 4 Ottawa homes of persons with cognitive impairment and their care partner. This system includes contact and motion sensors to assess home activity, a smart watch to record steps and sleep patterns, a bed sensor, and medication tracking pillboxes. Questions regarding areas of stress, the types of information that caregivers would like to receive, and how to receive their data were posed in focus group discussions involving caregivers with and without the sensor platform. An interface was designed based on participant input.

Result

Eight care partners (75% female) aged 30 to 81 participated in focus groups that obtained their opinions on the usefulness of a feedback system, its content, layout, and frequency in which care partners would like to receive their sensor information. The majority of participants wished to be sent their sensor information on a weekly basis in easy to interpret graphical formats that summarized information for them. An algorithm that collects sensor data, parses appropriate measures; steps, sleep, time together in a room, and displays it in graphical representation, was developed. The user interface displays the daily summary compared to the weekly average, with the ability to navigate between day and weekly views.

Conclusion

Sensor‐based data needs to be displayed in an efficient and convenient manner if it is going to be used by care partners to help guide changes in behavior to reduce stress. This project designed an interface, based on user feedback. This system also has the potential to be used by clinicians to evaluate longitudinal cognitive decline. Next, we will provide participants with the CART system with sample visual reports and gather their feedback.
Smartphone Application Usability Test for Dementia Patients' Primary Caregivers: Pilot Study
Authors: Park Jeong Min , Kim Seong Min , Seo Jihye
Published: December 2022

Background

The increase in the prevalence of dementia is emerging as a serious social problem by increasing the physical, mental, and social burdens of family caregivers taking care of dementia patients We would like to conduct a preliminary study to evaluate the application design, development, and usability test before conducting a study on the effectiveness of the smartphone application developed for the main caregiver of dementia patients.

Method

After approval of N university IRB, usability test will be carried out in 2 cycles. We will use the application developed for 10 family caregivers (5 people in 1 cycle) in South Korea aged 18 to 80 years old. We will then collect usability testing surveys on content, interface design, technology etc. either via online (web‐based) or telephone surveys.

Result

The application to be developed in this study will enable key caregivers caring for dementia patients at home to obtain information on dementia knowledge and coping strategies, set physical and mental goals, and monitor their physical and mental status. In addition, through communication within the app, they share information about diseases and care, maintain and improve mental and physical health through emotional support and empathy, and increase coping strategies and care effectiveness.

Conclusion

This study is a usability study of a smartphone application developed for caregivers of dementia patients. The results of this study will encourage the use of applications to improve the mental and physical health of caregivers caring for dementia patients, and to improve coping strategies and caring efficacy.
Profiles of 24‐hour Activity Cycle in Older Adults with Mild Cognitive Impairment: Does it Matter for Cognition?
Authors: Balbim Guilherme Moraes
Published: December 2022

Background

Mild cognitive impairment (MCI) is associated with increased risk for dementia and is characterized by poorer cognitive performance. Physical activity, sedentary behaviour, and sleep constitute the 24‐hour activity cycle (24‐HAC). Each of these share an inter‐dependent relationship with each other and are associated with cognitive health in older adults. It is unclear whether differences in the 24‐HAC profiles in older adults with MCI are associated with cognitive performance. Therefore, we examined whether older adults with MCI showed differences in cognitive performance based on profiles of 24‐HAC.

Method

A cross‐sectional analysis of 247 community‐dwelling older adults (aged 55+ years) with MCI (Montreal Cognitive Assessment <26). MotionWatch8© assessed 24‐HAC (5‐7 days) of physical activity, sedentary behaviour, and sleep duration and quality. We measured cognitive performance with composite z‐scores of executive function (verbal fluency test, digit span forward and backward), processing speed (trail making tests A and B), and memory (word recognition, word recall, and delayed recall). Latent profile analysis identified common profiles of the 24‐HAC. ANCOVAs compared cognitive performance between profiles, adjusted for age, biological sex, body mass index, and educational attainment.

Result

We identified four distinct profiles with acceptable fit (Table 2). Profile 1 (n = 84) showed balanced levels in the 24‐HAC and longer sleep duration. Profile 2 (n = 44) had below‐average physical activity, sleep duration and quality, and above‐average sedentary behaviour. Profile 3 (n = 37) showed the lowest physical activity levels, the highest sedentary behaviour, above‐average sleep duration and quality. Profile 4 (n = 71) had the highest physical activity, the lowest sedentary behaviour, and below‐average sleep duration and quality. ANCOVAs revealed a main effect of profile (p = 0.046) on processing speed (Table 3). Post‐hoc analysis (Estimated mean difference = 0.39, p = 0.036) showed that participants in Profile 1 demonstrated better performance (0.08 [95%CI ‐0.23; 0.39]) compared with participants in Profile 3 (‐0.31 [95%CI ‐0.68; 0.06]) (Table 3). No other statistically significant differences were noted.

Conclusion

Older adults with MCI appear to have four distinct 24‐HAC profiles. Balanced levels of 24‐HAC are associated with better processing speed compared with a less physically active, more sedentary, and lower sleep quality profile.
Lower in‐vivo locus coeruleus integrity is associated with lower cortical thickness in older individuals with elevated Alzheimer’s pathology
Authors: Engels Nina , Hsieh Stephanie , Schneider Christoph , Prokopiou Prokopis C. , Schultz Aaron P. , Riphagen Joost M. , Koops Elouise A. , Hanseeuw Bernard , Rentz Dorene M. , Sperling Reisa A. , Johnson Keith A. , Jacobs Heidi I.L.
Published: December 2022

Background

Cortical neurodegeneration is, along with Alzheimer’s Disease (AD) pathology, an important feature of AD, which correlates highly with tauopathy and cognitive decline. Post‐mortem data show that the locus coeruleus (LC) loses approximately 8.4% volume per cortical Braak stage. This work investigates whether LC integrity, as indexed by LC MRI signal intensity, is associated with cortical thickness, and whether this is exacerbated by the presence of AD pathology.

Method

Cross‐sectional data from 165 Harvard Aging Brain Study participants (age range=50‐94 years; female=∼60%; cognitively unimpaired: n=149, cognitively impaired: n=16; Table 1) who underwent 3T‐MRI, PiB‐PET (cut‐off=1.324 DVR) and T807‐PET scanning was selected. LC MRI signal intensity was assessed by normalizing the LC to the pontine tegmentum (reference region) for each individual and averaging clusters of 5 voxels with the highest intensities. Unilateral cortical thickness (CT) values were extracted utilizing the Desikan‐Killiany atlas (FreeSurfer 6) and averaged across hemispheres to obtain regional bilateral values. PET measures were corrected for partial‐volume effects. Associations between CT and i) LC intensity, or ii) LC intensity interacted with pathology (i.e., inferior temporal (IT) tau, entorhinal (EC) tau and global amyloid), were examined with bootstrapped linear regressions, while controlling for age, sex, and education, and applying FDR‐correction.

Result

We found a positive association between LC intensity and CT for medial and lateral temporal regions (p‐FDR<0.05; Figure 1). Models interacting LC intensity with IT or EC tau revealed that lower LC intensity was associated with lower CT especially in temporal regions. This effect was greater in individuals with elevated tau (p‐FDR<0.05; Figure 2‐3). Results still held after controlling for amyloid (p‐FDR<0.05). Similarly, interacting LC intensity with amyloid showed a relation between lower LC intensity and lower CT in temporal and some occipital regions, which was stronger in individuals with elevated amyloid (p‐FDR<0.05; Figure 4).

Conclusion

This work demonstrates that lower LC integrity is associated with bilateral cortical thinning in regions aligning with the expected topographical distribution of tau in preclinical AD. Additionally, these spatial patterns are more widespread in individuals with elevated AD pathology. These results suggest that LC integrity is closely related to the downstream neurodegenerative sequela of AD pathology.
Comparison of plasma amyloid, tau, and astrocyte biomarkers to identify AD pathophysiology
Authors: Ferreira Pamela C.L. , Tissot Cécile , Ferrari‐Souza João Pedro , Bellaver Bruna , Brum Wagner S. , Leffa Douglas Teixeira , Therriault Joseph , Benedet Andréa Lessa , Servaes Stijn , Lussier Firoza Z , Chamoun Mira , Stevenson Jenna , Rahmouni Nesrine , Tudorascu Dana L , Klunk William E , Villemagne Victor L , Cohen Ann D , Zimmer Eduardo R. , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Karikari Thomas K , Rosa‐Neto Pedro , Pascoal Tharick A
Published: December 2022

Background

Although it has been already demonstrated that plasma amyloid‐β (Aβ), phosphorylated tau (p‐tau), and glial fibrillar protein (GFAP) can predict with high accuracy Alzheimer's disease (AD) pathophysiology, no previous study has compared their performance in the same set of individuals. Here, we compare the performance of plasma Aβ42/40, p‐tau, GFAP, and NfL against Aβ and tau PET across the AD spectrum.

Method

We used the ROC curve to test the predictive performance of Simoa plasma Aβ42/40, p‐tau (at threonine 181 and 231), NfL, and GFAP to identify Aβ and Pau PET positivity in 138 cognitive unimpaired (CU) and 87 cognitive impaired (CI) from the McGill TRIAD cohort. Pearson correlation and linear regression tested the association between markers.

Result

We showed that plasma p‐tau231, p‐tau181, GFAP, and NfL correlated with each other (Figure 1), while Aβ42/40 did not. In CU, voxel‐wise linear regressions (Figure 2A) showed that p‐tau231, p‐tau181, and GFAP concentrations were significantly associated with Aβ‐PET (Figure 2A). While for Tau‐PET (Figure 2B), there was a significant association only with p‐tau231 and p‐tau181 (Figure 2B). P‐tau231 outperformed the other plasma biomarkers to identify both Aβ‐ and Tau‐PET positivity (AUC 0.877 and 0.796, respectively) in CU individuals. In CI, Aβ‐ and Tau‐PET were significantly associated with p‐tau231, p‐tau181, and GFAP, whereas NfL was only associated with Tau‐PET. The discriminative accuracy of GFAP in identifying both Aβ‐PET and Tau positivity (AUC 0.936 and 0.944, respectively) outperformed the other plasma biomarkers in CI individuals (Figure 3, Table 1).

Conclusion

We showed that plasma p‐tau231, a novel biomarker of early AD, best depicted AD pathophysiology in CU individuals. Interestingly, GFAP, an astrocyte reactivity marker, was better associated with brain Aβ and tau pathologies than plasma p‐tau and Aβ markers in CI individuals. Our results highlight that the performance of the novel plasma biomarkers of amyloid, tau and neuroinflammation to detect brain AD pathophysiology is disease stage specific.
Unique contributions of brain amyloid load and APOE4 Status to Regional Brain Volume
Authors: Boyle Christina P , Ching Christopher RK , Thomopoulos Sophia I , Thompson Paul M
Published: December 2022

Background

Brain amyloid and tau, and volumetric atrophy on MRI, are defining features of AD (Jack et al., 2018). Despite growing interest in these component processes, their relationship is still poorly understood.

We evaluated the unique contributions of APOE4 allele (E4+/E4−) and brain amyloid (Aβ) status (Amy+/Amy−) to brain volume in the elderly to identify associations with neurodegeneration in regions vulnerable to Alzheimer’s disease (AD).

Method

Accelerated 3T T1‐weighted brain MRI scans (N=1,353) obtained at screening for three distinct phases of ADNI with available information on APOE status and/or Amyloid positive/negative status were identified for the following subjects: 561 healthy controls (CN) (age: 71.8±6.3 y, 330F/231M), 599 MCI (mild cognitive impairment; age: 71.9 ± 7.5 y, 264 F/335 M), and 193 AD (age: 74.4±8.2 y, 79 F/114 M). Amyloid status was based on standardized cut‐off values in amyloid sensitive PET scans (Royse et al., 2021).

We applied unbiased tensor‐based morphometry (TBM; Leow et al., 2009; Hua et al., 2011) to each scan to measure relative volume differences between each subject and a common minimal deformation template (MDT), resulting in 3D Jacobian maps to represent relative expansion or contraction at each brain voxel.

At each voxel, a linear regression model was fit to relate regional brain volumes to amyloid status, and APOE4, after adjusting for covariates. P‐value maps were generated to visualize the pattern of voxel‐wise model contributions and statistical significance while enforcing a standard 5% false discovery rate (FDR) correction for multiple statistical comparisons across the brain (Benjamini et al., 1995).

Result

Amyloid positive status was associated with significantly lower regional volume in the temporal lobes and higher volume in the ventricles, i.e., ventricular expansion. APOE4 positive status was associated with lower volume in the temporal lobes (see Fig. 1).

Conclusion

The highly localized effects of APOE4 status and amyloid load on brain volumes are consistent with greatest effects of AD pathologic processes in the temporal lobes and similar associations found for Amy+ and E4+ status with cortical thinning (Li et al. (2017).

Continued analysis of longitudinal ADNI data will offer further insight into effects of amyloid and APOE4 allele status on atrophy estimates.
Distinctive age‐related longitudinal dementia progression patterns using a machine‐learning‐based MRI biomarker
Authors: Ma Da , Popuri Karteek , Wang Lei , Lockhart Samuel N. , Craft Suzanne , Gurcan Metin Nafi , Beg Mirza Faisal
Published: December 2022

Background

Dementia of Alzheimer’s type (DAT) is an age‐related neurodegenerative syndrome caused by Alzheimer’s disease. The risk of developing dementia increases with age, but also depends on disease trajectory. In this study, we aim to evaluate the effect of normal aging on the MRI‐derived dementia risk score and investigate the distinctive age‐related longitudinal dementia progression patterns among individuals with different dementia trajectories.

Methods

A total of 1609 participants with multi‐timepoint neuroimaging tests and diagnoses were recruited from the ADNI. Based on their dementia trajectories, the subjects were stratified into four groups: stable normal cognition (sNC=423), stable/progressive mild cognitive impairment (sMCI=535/pMCI=321), and stable dementia of Alzheimer’s type (sDAT=330). Brain structures were automatically segmented and harmonized to control the confounding effect of sex and scanner, and feed into an extensively‐validated kernel‐based ensemble classifier to derive the score, which we termed longitudinal MR‐DAT‐Score (MRDATS). The CSF‐based biomarker was derived as the ratio between the total tau and the amyloid beta (t‐tau/Aβ1‐42). We analyzed the effect of aging on the biomarkers’ distribution of each stratified group in terms of their empirical cumulative distribution function (ECDF). We also evaluated the difference in longitudinal MRDATS progression patterns among different groups.

Results

Compared to the CSF biomarker, the MRDATS revealed a more distinctive age‐related risk increase among all stratified groups (Figure 1). In addition, the effect of aging persisted across both the non‐progression groups (sNC and sMCI) and the progression groups (pMCI) except for the DAT group, where the age‐related effect is only observable for the 80‐90 year old group. Distinctive longitudinal dementia risk progression patterns (in terms of MRDATS) were also observed for each stratified group (Figure 2). Specifically, for patients with mild cognitive impairment (MCI), distinctive patterns were observed between sMCI and pMCI across subjects from different aged populations.

Conclusion

Our study demonstrated differential aging effect patterns as well as distinctive longitudinal patterns between AD‐progressive and non‐progressive subjects across different age groups. The results of this study emphasize the importance of disentangling the effect of aging with disease‐driven brain atrophy patterns.
Genetic and Structural Network Contributions to The Regional Vulnerability of Tauopathy
Authors: Wen Qiuting , Yu Meichen , Shahid Syed Salman , Zhao Yi , Risacher Shannon L. , Saykin Andrew J. , Wu Yu‐Chien
Published: December 2022

Background

Tau propagates in a highly stereotyped pattern in both normally aged and cognitively impaired individuals, with the medial temporal lobe (MTL) being first affected. Although substantial progress has been made in revealing its spreading pattern with the aid of network analysis, it remains unclear why tau first seeds in this specific region. We hypothesize that regional white‐matter connections exacerbate MTL’s vulnerability to tauopathy. Further, we speculate that tau candidate genes have higher expression levels in MTL. This study tested the two hypotheses in cognitively normal older brains using two independent imaging datasets, i.e., ADNI and Indiana ADRC (IADRC), along with gene expression data derived from the Allen Human Brain Atlas (AHBA).

Method

We identified 159 cognitively normal participants (72±7 y/o) in ADNI and 57 (70±7 y/o) in IADRC that have both diffusion MRI and tau‐PET (AV1451) data. We estimated network metrics and tau SUVR in 68 cortical regions of interest (ROIs) for each participant. All participants' data were then averaged (after controlling for age and sex) to produce ROI‐wise measurements. Gene expression data were extracted from the same 68 ROIs. We preselected eight tau risk genes, including MAPT, LRP1, PTK2B, MADD, CASS4, BIN1, EPHA1, and APOE. Spearman correlation was applied to examine their spatial correlations.

Result

ADNI and IADRC reveal a similar spatial pattern for structural connectivity and tau deposition, with MTL demonstrating lower connectivity and higher gene expression levels (Figure 1A‐B). This trend is also evident when summarized in Braak stages (Figure 1C‐D), with Braak I ROI (entorhinal) showing the most elevated tau deposition, lowest structural connectivity, and highest gene expression level. Figure 2 summarizes the Spearman’s Rho across the 68 ROIs. Consistently, higher tau deposition is associated with lower connectivity and higher the expression levels of BIN1 and APOE.

Conclusion

The two independent datasets produced consistent results, supporting our hypotheses that both weaker structural connectivity and higher tau candidate gene expression contribute to the regional vulnerability in the MTL. These preliminary results encourage future studies to systemically examine the interaction between tau, gene expression, and axonal changes in healthy aging and across the AD spectrum.
Rural‐urban and gender differences in the prevalence of metabolic syndrome among older Indians
Authors: Sundarakumar Jonas S. , Stezin Albert , Lingegodwa Abhishek Mensegere , Ravindranath Vijayalakshmi
Published: December 2022

Background

The clinical significance of metabolic syndrome (MetS) as a risk factor for cardiovascular disease, cerebrovascular disease, and dementia is becoming increasingly prominent. However, there is a dearth of studies from India on the prevalence of MetS, especially in the aging population. We aimed to estimate MetS prevalence and associated comorbidities in two prospective, aging cohorts from rural and urban India.

Method

Our study sample includes aging (≥ 45 years) individuals – 2171 from the rural (SANSCOG) cohort and 332 from the urban (TLSA) cohort. These older Indian adults have contrasting population characteristics, which echo the stark rural‐urban divide in the country. Data from baseline clinical and biochemical assessments were used to calculate the prevalence of MetS in both the above cohorts using two well‐established criteria, namely consensus criteria and NCEP‐ATP III criteria. Further, we compare rural‐urban, gender‐ and age‐wise differences in the prevalence of MetS as per the consensus criteria.

Result

Prevalence of MetS was 46.2% and 54.8% as per consensus criteria in rural and urban subjects, respectively; corresponding numbers using NCEP‐ATP III criteria were 40.3% and 45.1%. Rural‐dwelling older adults had a significantly lesser prevalence of all individual MetS parameters except impaired triglycerides and high‐density lipoprotein levels. Rural women had a significantly higher prevalence than rural men, whereas there was no significant difference among urban subjects. We did not observe any consistent age‐wise trend when comparing both these cohorts. There was a high burden of comorbidities among both groups, mostly undiagnosed in rural subjects.

Conclusion

Roughly 1 in 2 older Indians have MetS, urban significantly more than rural, reaching an alarming 63.1% among urban subjects aged 65‐74 years. The very high prevalence of undiagnosed co‐morbidities in rural Indians is extremely concerning, calling for urgent public health measures including ramping up the primary health care system in this marginalized and health disparate population.
Cardiorespiratory Fitness, BMI, and Dementia risk: Findings from The Cooper Center Longitudinal Study
Authors: Gafni Tal , Weinstein Galit , David Leonard , Carolyn Barlow E. , DeFina Laura F. , Gabriel Kelley Pettee , Berry Jarett D , Shuval Kerem
Published: December 2022

Background

Cardiorespiratory fitness (CRF) and body mass index (BMI) are each independently related to premature mortality. Previous research indicates that high fitness is protective against premature mortality even among those who are overweight or obese. We aimed to explore the independent and joint associations of CRF and BMI with incident dementia among middle‐aged adults.

Method

Data on CRF, BMI and covariates were derived from the Cooper Center Longitudinal Study (CCLS). The sample included 6,458 middle‐aged adults (mean age 50.9±7.6 years; 85% men; mean CRF 11.6±2.3 METs and BMI 25.3±3.2 kg/m2), who attended the Cooper Clinic (Dallas, TX) for preventive medical exams twice between 1970‐1999 (mean time between exams 2.5±2.1 years), and had fee‐for‐service Medicare coverage after age 65 at any time between 1999 and 2009. Maximal metabolic equivalents (MET) levels of CRF were computed based on the final speed and grade on treadmills. BMI was calculated based on measurements of weight and height (kg/m2). The primary independent variables consisted of average CRF and BMI from the two exams and the change between exams. The chronic condition warehouse definition of Alzheimer’s disease and related dementias was based on the International Classification of Diseases, 9th Revision. Proportional hazards models were applied to investigate the independent and joint associations of midlife CRF and BMI and their change over time with dementia diagnosis adjusted for age, sex, education, systolic blood pressure and fasting glucose and cholesterol levels.

Result

Over 40,975 person‐years of Medicare surveillance (average 6.3±3.6), 637 cases of dementia were identified. Average CRF and BMI were each related to incident dementia (HR = 0.95 per MET 95% CI 0.91‐0.99 and HR = 1.03 per kg/m2 95% CI 1.00‐1.06, respectively), but not the interaction. Change in CRF or BMI between exams did not predict incident dementia.

Conclusion

In line with studies exploring the link of CRF and BMI with mortality, our findings suggest that baseline fitness is related to dementia incidence independently of body mass and that significant joint effects were not observed.
“Hablemos de Alzheimer”: Words Mexican Americans use to talk about Alzheimer’s disease genetic testing. Implications for precision medicine education.
Authors: Fong Jamie C , Chavez Fatima , Silos Karla , Castro Gabriela Castro , Arroyo‐Miranda Mirna L , Kunik Mark E , Shulman Joshua M , Medina Luis D
Published: December 2022

Background

Effective Alzheimer’s disease (AD) diagnosis and therapy will require a tailored approach to each person’s unique AD manifestation, known as AD precision medicine (PM). PM‐associated comprehensive genetic testing is currently restricted to the research domain and not readily available to minoritized Hispanics/Latinos (H/L). Successful AD precision medicine programs benefitting everyone require culturally appropriate patient outreach/education materials. We investigated the words H/L use to talk about AD genetic testing.

Method

We conducted freelisting interviews with 14 Spanish‐preferring Mexican American adults (female, 85.7%; mean age, 49.3±16.8 years, range = 19‐73; completed less than or at most a high school education, 35.7%). Participants were presented with vignettes about a H/L father of varied ages (5th‐7th decade) and degrees of cognitive impairment (no memory deficits to severe memory loss) who received genome sequencing results. During freelisting, participants were given prompts about the vignettes, and were asked to list all words that came to mind when they thought about the prompts. Responses were reviewed for semantically related words. Discrepancies were resolved by consensus agreement. Among sociodemographic data collected, familism and perceived social status were measured by the Pan‐Hispanic Familism Scale and scored (1‐strongly disagree to 5‐strongly agree, max score 25), and the MacArthur Scale of Subjective Social Status (SSS; each item: 1‐lowest to 10‐highest), respectively.

Results

Highest frequency unique word/word clusters (n = 151) for one vignette (father: age 70 with cognitive slowing, prompt: father’s reaction to his own moderate risk result) included worry (17.2%), age/aging/older (15.9%), family (12.6%), high/medium/low chance (12.6%), Alzheimer’s (10.6%), and normal/well/healthy (7.9%). High frequency of family‐related worry aligned with high familism scores (M = 23.2±2.6, range = 15‐25). Moderate frequency words of participants, 78.6% of whom perceived they held social standing in the top half of the community (SSS>5), reflected action orientation: do (6.6%), seek (1.7%), inform (1.5%), and manage (1.1%).

Conclusion

Spanish‐preferring Mexican Americans respond robustly to information about family. Family‐centered educational materials about AD precision medicine, including information about healthy aging versus neurodegeneration, risk magnitude categories, and action words, could have high impact. Additional research to learn words used by diverse Spanish‐preferring H/L is needed.
Alzheimer’s disease status can be predicted using a novel fractal‐based metric computed from resting‐state EEG
Authors: Brookshire Geoffrey , Wu Yunan "Charles" , Quirk Colin , Gerrol Spencer , Merrill David A. , Caselli Richard J. , Lucero Ché
Published: December 2022

Background

Alzheimer’s disease (AD) lacks a fast, easy, reliable, and inexpensive method of diagnosis. Currently, diagnosis is based on time‐consuming behavioral tests and the exclusion of other potential causes of impairment. Several biomarkers show good or promising diagnostic performance (e.g. CSF, tau PET, MRI, blood), but are either expensive, invasive, or still in development and while some can detect preclinical disease stages, all appear slow to change relative to the rate of cognitive decline. Here we develop a prototype diagnostic classifier based on novel metrics of brain activity in resting state electroencephalography (EEG) that correlates well with mental status.

Method

Archival resting‐state EEG recordings of older adults (N=248) came from a memory clinic and university‐based clinic with a range of clinical diagnoses including subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and dementia, representing AD, vascular dementia, and Lewy body dementia, TBI, and depression. We developed XGBoost classifiers to detect AD using EEG, age, and sex under increasingly challenging conditions. We computed metrics of periodic and aperiodic brain activity using the FOOOF algorithm. Furthermore, we developed a novel technique called [Banded Fractal Variability], which yields a set of features based on fluctuations in the fractal dimension within canonical frequency bands. We trained classifiers using cross‐validation to avoid overfitting during hyperparameter selection.

Result

Along with ROCAUC, we report an optimal sensitivity, specificity, and accuracy for the point on the ROC curve that maximizes Youden’s j. The classification tasks were healthy vs. probable AD (ROCAUC = 98%, sensitivity = 90%, specificity = 99%, accuracy = 96%), SCI vs. mild AD (ROCAUC = 89%, sensitivity = 76%, specificity = 87%, accuracy = 84%), and AD vs. other pathologies (no AD diagnosis) in MCI and dementia patients (ROCAUC = 82%, sensitivity = 72%, specificity = 87%, accuracy = 80%). All ROCAUC values were stronger than would be expected by chance (ps < 0.001).

Conclusion

These preliminary results suggest that AD could be diagnosed in the clinic on the basis of machine‐learning classifiers and resting‐state EEG. Furthermore, they demonstrate that [Banded Fractal Variability] carries clinically‐relevant information about AD.
LANGaware: Robust Multimodal Machine Learning Methods for the Early Detection of Neurodegenerative and Psychiatric Diseases
Authors: Rentoumi Vassiliki , Vassiliou Evangelos , Pittaras Nikiforos , Demiraj Admir , Alexandridou Martha , Danezi Maria , Hatzopoulou Maria , Kamtsadeli Vassiliki , Papatriantafyllou John D , Paliouras George
Published: December 2022

Background

Multiple neurodegenerative and psychiatric diseases can affect speech, manifesting as subtle changes in spoken language. We perform a rigorous evaluation of a Machine Learning (ML) pipeline on a large‐scale multiaxial experimental setting, to investigate its capacity for detecting early signs of cognitive decline as manifested in speech. Using a diverse dataset of speech samples spanning different languages, patient cohorts and cognitive status diagnoses, we propose that the developed pipeline showcases robust performance, facilitating efficient decision support for early cognitive decline detection.

Method

We build upon previous research efforts on data‐driven cognitive decline prediction. Random forest models are constructed from a dataset of more than 3000 audio recordings and ASR‐generated transcripts, constituting cognitive assessment test tasks (e.g. picture description, everyday activity recounting, etc.). A multimodal NLP and audio analysis procedure derives sophisticated predictive biomarkers, using three methods for feature selection, feature decorrelation preprocessing and rigorous, grid search‐based hyperparameter optimization. We introduce novel experimental axes of investigation, including the spoken language (English and Greek), single and multi‐task verbal task settings, and different neurodegenerative diseases for the pathological cohorts (Alzheimer’s Disease or Dementia, along with age and education‐matched healthy cohorts). Four different NLP analysis tools for tokenization, syntax and dependency extraction are considered, using both ML and Deep Learning (DL) techniques. Model stability and generalization is supported via 5‐fold cross‐validation and the use of a separate test set.

Result

Results are validated against medical expert diagnosis. Αverage performance across all investigative axes reaches high scores for accuracy (0.73), sensitivity (0.72), specificity (0.74), precision (0.77), F1 (0.74), and AUC (0.78). Additional findings suggest that single‐task models outperform multitask ones (e.g. reaching AUC scores of 0.85). Moreover, cognitive decline detection is more efficient for pathological cohorts of Alzheimer's, versus patients with Dementias.

Conclusion

The broad empirical evaluation verifies the effectiveness of the deployed ML system, adding evidence in favor of multimodal AI solutions for predicting early cognitive decline and showcasing their robustness in diverse evaluation settings. Future work includes leveraging DL methods for classification and evaluation on differential diagnosis discrimination tasks.
Amyloid independent pathways have an impact on longitudinal tau deposition
Authors: Vemuri Prashanthi , Lesnick Timothy G. , Przybelski Scott A. , Graff‐Radford Jonathan , Ramanan Vijay K , Lowe Val J. , Machulda Mary M. , Mielke Michelle M. , Petersen Ronald C. , Knopman David S. , Jack Clifford R.
Published: December 2022

Background

Amyloidosis‐driven tau deposition has been a significant focus of imaging research in Alzheimer’s disease (AD). However, the 3R/4R tau seen in AD can be observed in the transentorhinal/entorhinal regions (Braak I/II) in the absence of amyloidosis. The underlying drivers of this phenomenon are not well understood. Our goal was to examine amyloid‐independent pathways of longitudinal Tau‐PET SUVR progression in the entorhinal cortex (ERC) using a broad range of risk and protective factors.

Method

We identified 449 participants from the population‐based sample of Mayo Clinic Study of Aging >50 years old with baseline amyloid PET and at least two serial tau PET scans (mean number of scans=2.3; mean follow‐up time=3.2 years). Using an amyloid SUVR cut‐point of 1.48, we categorized participants into A+ (n=167; mean age=77.5 years; 56% male; baseline ERC tau=1.20; 83% cognitively unimpaired) and A‐ (n=282; mean age=67.5; 56% male; baseline ERC tau=1.07; 92% cognitively unimpaired). We used an ERC tau SUVR cut‐point of 1.21 to determine T+. We fit mixed effects and growth curve models with age, sex, baseline amyloid, risk factors (midlife activities, sleep, stress, education/occupation, cardiovascular metabolic conditions) as predictors and longitudinal ERC tau as the outcome. We fit separate models in A‐, A+, and all participants.

Results

For models of all participants and A+ participants, the only predictors of higher rates of ERC tau deposition were increasing age and amyloid SUVR (p<0.05). In the A‐ models (figure below), amyloid SUVR and age were predictors of baseline, but not longitudinal ERC tau. However, a greater number of cardiovascular metabolic conditions predicted a higher rate of ERC tau accumulation (0.007 (0.002), p<0.05). Only 13% of the 23 A‐T+ participants were APOE4 carriers (compared to 31% in the overall sample), suggesting the role of non‐APOE4 pathways to tau deposition.

Conclusion

Our results support previous evidence that significant amyloidosis is causal to higher rates of tau deposition. However, in those without significant amyloidosis, cardiovascular metabolic conditions predicted higher rates of ERC tau accumulation. Further work is warranted to investigate the mechanisms through which genetics, comorbidities, and lifestyle may play a role in early tau deposition.
Association of mitochondrial haplogroups and cognitive impairment in the Amish
Authors: Dorfsman Daniel A. , Prough Michael B. , Caywood Laura J. , Clouse Jason E. , Herington Sharlene D. , Slifer Susan H. , Adams Larry D. , Laux Renee A. , Song Yeunjoo E. , Lynn Audrey , Fuzzell M. Denise , Fuzzell Sarada L. , Hochstetler Sherri D. , Miskimen Kristy L. , Main Leighanne R. , Osterman Michael D. , Ogrocki Paula K. , Lerner Alan J. , Vance Jeffery M. , Cuccaro Michael L. , Haines Jonathan L. , Pericak‐Vance Margaret A. , Scott William K.
Published: December 2022

Background

Mitochondrial dysfunction is an important feature of Alzheimer’s Disease (AD) pathogenesis. Reduced glucose utilization and increased oxidative stress are intermediates through which impaired mitochondria may promote AD‐associated brain changes. Association between groups of variants (“haplogroups”) in the mitochondrial genome and AD have been reported for haplogroups U, J, and K. To test these effects in the Amish, we looked for evidence of association between AD‐associated haplogroups and cognitive impairment in a sample of aged Amish individuals.

Method

Cognitive status in adult Amish participants (n=670) with whole‐genome sequence (WGS) data was determined based on modified mini‐mental status exam results (3MS). An outcome of cognitively impaired (CI) was assigned to individuals with an education‐adjusted 3MS < 87 at any age. A status of cognitively unimpaired (CU) was assigned to those aged ≥ 75 scoring ≥ 87 on the 3MS. Mitochondrial variants detected by WGS were used to derive broad haplogroups for each sample using Haplogrep2. Mixed model association testing was performed in GENESIS with CI as the outcome, and haplogroup (U, J, or K), APOE ε4 carrier status (ε4 vs no ε4), sex, and age as predictors. Based on reports of sex‐specific haplogroup U effects on AD, a sex‐stratified analysis was conducted. A random‐effect kinship matrix was used to account for relationships.

Result

Association between mitochondrial haplogroups U, J, or K and CI was not observed at a 5% significance level. The sex‐stratified analysis showed the strongest association of CI with haplogroup U (OR 1.8, 95% CI 0.92‐3.5) among women. Among men, the estimated effect was 0.77 (95% CI 0.37‐1.62). The overall direction of association was opposite in men and women, though neither was statistically significant at 5%.

Conclusion

Although significant evidence of a haplogroup effect on cognitive status was not observed, the moderate sex‐dependent effect of haplogroup U on impairment warrants further examination in an expanded dataset.Previously, haplogroup U was proposed as an AD risk factor among men, whereas it appears as a risk factor for CI in women in the present study.