bluuebunny/crossref_metadata_2025 huggingface dataset:
CAIDE dementia risk score and cognitive correlates among Filipinos with mild cognitive impairment
Authors: Cano Jemellee , Guzman Ma Fe P , Phung Thien Kieu Thi , Dominguez Jacqueline C
Published: December 2020

Background

The Cardiovascular Risk Factors, Aging and Dementia (CAIDE) dementia risk score is a validated tool predicting the risk of dementia.1,2 It includes age, sex, education, blood pressure, cholesterol, body mass index (BMI), and physical inactivity, with higher scores indicating increased risk of subsequent dementia.1,2 Mild Cognitive Impairment (MCI) is a The objective is to compare the cognitive profiles of Mild Cognitive Impairment (MCI) participants with significant modifiable risk factors (CAIDE > 6) in a Filipino cohort.

Method

A total of 60 participants with MCI from the Filipino Multicomponent Intervention to Maintain Cognitive Performance among High Risks Population (FINOMAIN) study were included. Data on age, sex, educational level, blood pressure, cholesterol, body mass index (BMI), and physical activity were obtained. Mini Mental Status Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were obtained. Participants were administered the Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Alzheimer’s Disease Assessment Scale Cognitive Subscale (ADAS‐Cog).

Result

Forty‐four participants (73%) have significant modifiable risk factors (CAIDE > 6). Compared to participants without significant risk factors, participants with significant modifiable risk factors (CAIDE > 6) have more impaired cognition with lower MoCA scores (16 + 4 vs 19 + 3, p=0.02). MMSE was noted to be lower (25 + 3 vs 27 + 2, p=0.06); and ADAS‐Cog scores higher (13.6 + 6 vs 11.8 + 5, p=0.2), however, it was not significant.

Conclusion

This study shows that MCI participants with significant modifiable risk factors (CAIDE > 6) have more cognitive impairment suggesting the utility of CAIDE in the community to screen individuals at risk for dementia. Findings support the need to address modifiable risk factors to prevent cognitive deterioration. Further trials that investigate the effects of multi‐domain intervention and treatment for risk factors in improving cognition, delaying cognitive deterioration and dementia conversion.
Subjective memory decline and neuropsychological performance
Authors: Xu Ying , Peters Ruth , Eramudugolla Ranmalee , Anstey Kaarin J
Published: December 2020

Background

The association between subjective memory decline (SMD) and different domains of cognition is not well understood.

Method

Four waves (4‐year intervals between waves) of data from 2,551 participants (aged 62.5 ±1.5 years, 52% male) of the Personality and Total Health (PATH) study were used. SMD was defined as a response of ‘no’ to one question: ‘Do you feel you can remember things as well as you used to?’ (w1 and w2), and categorized as ‘consistent’ (SMD both waves), ‘fluctuate’ (either wave) and ‘neither’. The more comprehensive Memory Assessment Clinic‐Q (MAC‐Q) was also available at w4, and includes remembering names, phone numbers, postcodes, where objects are, newspaper reports and shopping‐list items. Neuropsychological tests (w2 to w4) included immediate and delayed recall, digit span backwards, spot the word, symbol digit modalities (SMDT), Trails A and B and Purdue pegboard. We used random‐effect linear mixed models (LMMs) to examine temporal and prospective associations between SMD categories and neuropsychological performance, and linear regression models to investigate cross‐sectional associations between SMD and neuropsychological performance at w4.

Result

Fifty‐one percent, 27% and 22% of participants had ‘neither’, ‘fluctuate’ and ‘consistent’ SMD. SMD categories were not associated with steeper decline in any neuropsychological performance, but were associated with lower z transformed SDMT and purdue pegboard (both hands and dominant hand) scores at w2 in all LMMs (adjusted for age, sex, education [model 1], plus anxiety, depression [model 2], smoking, hypertension, diabetes and high cholesterol [model 3], and effect sizes were ‐0.07 (‐0.13, ‐0.01), ‐0.20 (‐0.32, ‐0.08) and ‐0.13 (‐0.24, ‐0.02) in model 3 (all P ≤ 0.03). In sensitivity analyses, similar results were found when using SMD at w1 or w2, separately, as the ‘exposure’. Nineteen percent of participants had MAC‐Q assessed SMD, which was cross‐sectionally associated with all neuropsychological tests except for digit span backwards (all P<0.02).

Conclusion

Presence of MAC‐Q assessed SMD was cross‐sectionally associated with verbal memory, executive function, processing speed, manual dexterity and bimanual coordination. To be useful in healthcare settings, while ensuring simplicity, SMD measurement may need to contain specific memory items, and its value in predicting cognitive decline needs confirmation.
Collaborative co‐design of an active and healthy ageing program using mobile technology to reduce dementia risk in older Aboriginal Australians
Authors: Radford Kylie , Nichols Madeleine , Timbery Alison , Wettasinghe Pam , Allan Wendy , Daylight Gail , Lavrencic Louise , Broe Gerald A , Garvey Gail , Delbaere Kim
Published: December 2020

Background

High rates of dementia have been observed in Aboriginal Australians and dementia risk reduction is a priority in this population. The Koori Active and Healthy Ageing Project aimed to develop new, effective, culturally appropriate healthy brain ageing approaches in collaboration with older Aboriginal people and partner communities in regional and urban Australia.

Method

Initially, 34 semi‐structured interviews and 2 yarning (focus) groups were conducted with older Aboriginal participants to understand perceptions regarding community health priorities, preferences for healthy ageing programs and acceptability of technology as a platform for program delivery. Following consultation and development, a pilot randomised control trial (RCT) was conducted over 16 weeks, to evaluate the feasibility of a new program versus a health education control condition in 30 Aboriginal people aged 45+ years. The primary outcome included dual‐task walking. Trial registration ID: ACTRN12619001130156.

Result

Qualitative interviews identified key health concerns including memory loss, mobility, depression, and access to healthcare services. Using self‐directed technology for healthy ageing was widely supported, however, the importance of maintaining social group connections was emphasised. StandingTall is an unsupervised balance exercise program delivered using mobile technology for older people and was the preferred option selected in yarning groups. With further consultation, this program was redeveloped to provide a culturally inclusive interface, and incorporate cognitive‐motor (dual‐task) activities to boost potential benefits for healthy brain ageing and maintaining functional independence. Eighteen participants were enrolled and completed the RCT (8 intervention, 10 control). Users rated the StandingTall program as easy and enjoyable to use. There was no significant effect of intervention observed on dual‐task walking in intention to treat analysis (F(1,16)=0.14, p=0.71). However, adherence was highly variable and likely affected outcomes; three participants did not engage with the program and five reached a median of 33.4 minutes per week (max=130.7).

Conclusion

By implementing a technological platform, this program has strong potential to improve access to dementia prevention strategies, enable low‐cost individualised program tailoring and facilitate transferability across diverse community settings. Understanding the factors related to program adherence is critical and a larger trial is needed to examine the effectiveness of the program in this population.
Comparing conventional wet EEG vs dry‐sensor wireless EEG to probe sensory processing and neuronal function in the aging brain
Authors: Nolan Hugh , Barbey Florentine , Buick Alison R , Dyer John , Murphy Brian
Published: December 2020

Background

Neurodegenerative conditions such as AD, PD and MS can develop slowly, making early detection and on‐going characterisation a challenge. Current methods rely primarily on clinical opinion/self‐reports, or on burdensome and expensive clinic‐based methods. Visual and other sensory evoked potential tasks, particularly with steady‐state stimulation, have been used to probe neuronal function in healthy aging (Sridhar & Manian 2019), and neurodegeneration (Jacob et al 2002, Viallate et al 2010), in pre‐clinical and symptomatic stages (Shahmiri et al 2017) – but using conventional lab/clinic based wired wet EEG systems. In this proof‐of‐concept study, we evaluate wireless dry EEG as a less burdensome alternative. If feasible this could provide an easy‐to‐use, scalable and objective measure of neuronal function, for use in larger longitudinal studies of these conditions.

Methods

We compare signals recorded from a wireless dry‐EEG headset (BrainWaveBank Ltd – Murphy 2018, 2019), and state‐of‐the‐art conventional wet‐EEG hardware (Biosemi ActiveTwo). Informed consent was obtained from 8 healthy adult males for this methodological study. Each attended 2 separate in‐lab sessions, one week apart, in which both dry and wet recordings were made. Static and flickering steady state (14Hz) visual stimulus conditions were presented. Grand average VEPs were calculated for each recording and stimulus condition. Signal stability was quantified using a Monte Carlo process to estimate 95% confidence intervals. From the steady state VEP, scalp topographies of spectral power were also computed.

Results

After band‐pass and notch filtering, a grand average of a simple visual‐evoked potential (Figure 1) recorded at posterior recording sites with the wireless dry‐EEG headset has similar waveform morphology and noise levels to that from conventional wet‐EEG equipment – as does the steady state VEP (Figure 2). Topographies of spectral power at 14 and 28Hz (Figure 3) show a similar central/posterior scalp distribution.

Conclusions

In controlled environments, a wireless dry‐sensor EEG headset can yield aggregate data of comparable quality to a state‐of‐the‐art wet‐EEG, making much larger scale studies of sensory processing and broader neuronal function possible for the first time.
Perception of fragmented letters differentiates pathologically confirmed dementia with Lewy bodies from Alzheimer’s disease
Authors: Salmon David P. , Smirnov Denis S. , Hamilton Joanne M. , Hansen Lawrence A. , Galasko Doug R.
Published: December 2020

Background

There is evidence that disproportionate impairment of visuoperceptual abilities can help distinguish Dementia with Lewy Bodies (DLB) from Alzheimer’s Disease (AD), but the reliability of this effect has not been established in patients with autopsy confirmed disease, and the impact of co‐occurring Lewy body and Alzheimer pathology has not been examined.

Method

A relatively pure test of visuoperceptual ability, the Fragmented Letters Task of the Visual Object and Space Perception (VSOP) battery was administered to 19 patients with pathologically confirmed DLB (17 Neocortical, 2 Limbic) with various levels of concomitant AD and 23 patients with pathologically confirmed AD only. Groups were matched for a mild level of dementia (MMSE >15, AD mean=24.7+3.6 and DLB mean=25.7+3.4) and were compared to 45 healthy elderly controls. In the Fragmented Letters Task individuals must identify 20 letters that are visually degraded by 70%. Performances on more complex visuospatial (Block Design) and memory (California Verbal Learning Test; CVLT) tests were also compared.

Result

DLB patients performed worse than AD patients (B=‐2.29±0.64, p = 6x10‐4) and controls (B=‐2.73±0.62, p=3.8x10‐5) on the Fragmented Letters Task even after adjustment for demographics, MMSE, and ability to identify intact letters. AD patients did not differ from controls (B=‐0.53±0.62, p=0.34). Results were similar when DLB with (n=8, B=‐2.31±0.81, p = 0.006) or without (n=11, B=‐2.15±0.77, p = 0.006) concomitant AD pathology (Braak stage < 4 vs. 5‐6) were separately compared to pure AD. ROC analyses to distinguish DLB from AD showed that the Fragmented Letter Test (AUC 0.86) outperformed Block Design (AUC 0.71) and CVLT Immediate Recall (AUC 0.48).

Conclusion

In contrast to complex visuospatial and memory tasks, a relatively pure test of visuoperceptual ability, the Fragmented Letters Task, was uniquely impaired in DLB (vis a vis AD) and effective at distinguishing DLB from AD. Because impairment was not associated with concomitant AD pathology in DLB patients, and patients with AD were unimpaired, the deficit appears to be driven primarily by Lewy body pathology. Results suggest the quick and easily administered Fragmented Letters Task has excellent clinical utility for differentiating DLB from AD in mild to moderate stages of dementia.
Role of white matter hyperintensities, hemoglobin and vitamin B‐12 on cognitive decline: Two‐year follow‐up data from the Tata Longitudinal Study of Ageing (TLSA)
Authors: Balakrishnan Aditi , Tiwari Vivek , Abhishek M.L. , Rao Naren P. , Ravindranath Vijayalakshmi ,   TLSA Investigators
Published: December 2020

Background

The presence of white matter hyperintensities is commonly seen in elderly individuals and many studies have identified its relation to cognitive decline, however the effect size of this relationship has been seen to be relatively small. Evidence also suggests that among older individuals, low levels of hemoglobin and Vitamin B‐12 are indicators of cognitive decline. This study seeks to identify the role of white matter hyperintensities, hemoglobin and Vitamin B‐12 on cognitive change among an urban elderly population in Bangalore, India.

Method

A subset of 87 individuals (49 Males and 38 Females, mean age=65.9 years) from TLSA Cohort above the age of 45 participated in the TATA longitudinal Study of Ageing, conducted in Bangalore, India. All participants underwent the Addenbrooke’s Cognitive Examination III (ACE‐III), blood investigations and Magnetic Resonance Imaging (MRI) scans as per the Alzheimer's Disease Neuroimaging Initiative (ADNI‐II) protocol at baseline. Brain images were acquired with a 3T Siemens Skyra MR Scanner. MRI scans were then visually rated on Fazeka’s scale for white matter lesions. Cognitive assessments were repeated two years later, on all participants. Change in cognition was calculated by subtracting followup scores from baseline scores. Regression analysis was conducted in order to examine the relation between White matter hyperintensities, vitamin b‐12 and hemoglobin at baseline with change in cognitive scores over time.

Result

The results indicate that Fazeka’s deep white matter scores, hemoglobin and vitamin B‐12 are significant predictors of changes in ACE‐III Memory scores at a 2 year follow up. A significant regression equation was found (F(3,38)=6.73, p<0.001), with an R2 of 0.347.

Conclusion

The findings of the study suggest that an individual’s deep white matter hyperintensity, along with hemoglobin levels and Vitamin B12 at baseline are potential indicator of cognitive change during follow up. Future longitudinal studies with larger sample size are required to examine whether this model is a significant predictor of cognitive decline and dementia.
Cognitive decline and conversion to MCI and dementia in heart failure: A 12‐year follow‐up study
Authors: Jung Miyeon J , Apostolova Liana G. , Gao Sujuan , Burney Heather , Saykin Andrew J. , Pressler Susan J
Published: December 2020

Background

Cognitive decline and development of mild cognitive impairment (MCI) and dementia over time in heart failure (HF) have not been fully examined. The purpose of this study was to compare (1) cognitive decline and (2) time to convert to MCI or dementia between people with and without HF.

Method

Data were retrieved from the National Alzheimer’s Coordinating Center database in September 2017. People with baseline dementia were excluded. Cognitive decline was assessed using changes in age, education, and gender‐adjusted z‐scores of verbal memory (Logical Memory Test delayed recall), attention (Digit Span Forward, Trail Making Test A), executive function (Trail Making B, Digit Symbol Test), and language (Category Fluency, Boston Naming Test) over 12 years. Time to convert was assessed using diagnosis of cognitive status by neurologists at each visit. Statistical analyses were conducted using multivariable Cox Proportional Hazards Models after adjusting for covariates (e.g., comorbidity, APOE carrier status).

Result

Among 4,149 participants, 87 had HF (66 with normal cognition, 21 with MCI) at baseline Median years of follow‐up was 6 (SD=2; range = 1‐12). At baseline, compared with non‐HF participants, HF participants were significantly older, had less education and more comorbidities, and were more likely to have MCI. Compared with non‐HF participants, HF participants had faster decline in attention (time by group interaction b=‐0.059, p=.0007), executive function (b=‐0.095, p=.0006) and language (b=‐0.051, p=.0137) but not memory (b=‐0.055, p=.0595) over 12 years after controlling for covariates and baseline cognitive status. Time to convert from normal cognition to MCI was not significantly different between participants with and without HF. Similarly, time to convert from MCI to dementia did not differ between the groups. The small number of HF participants may have limited the ability to detect 50% survival probability.

Conclusion

Participants with HF had accelerated cognitive decline, especially in the domains of attention, executive function, and language compared with people without HF. The effect of HF on time to convert needs to be tested in larger samples.
Combining MRI and genetic data in the Tohoku Medical Megabank Organization cohort study for innovative Alzheimer’s disease research
Authors: Taira Makiko , Fuse Nobuo , Mugikura Shunji , Kinoshita Kengo , Yamamoto Masayuki
Published: December 2020

Background

The Tohoku Medical Megabank Organization (ToMMo) is a prospective genome cohort study and biobank established in 2012 in Northern Japan’s Miyagi Prefecture following the Great East Japan Earthquake and Tsunami. ToMMo has enrolled 120,000 healthy male and female adults aged over 20, plus 30,000 children in a longitudinal study designed to identify diverse biological, psychological, and lifestyle characteristics associated with mainly common diseases and support additional innovative research. Baseline information includes brain MRI, genetic data, physiological measurements, several cognitive and psychological screening tests, and health/lifestyle assessments. Alzheimer’s disease (AD) is a key research focus; goals include using MRI, genomic and other data in combination to identify predictive biomarkers. This communication reports initial progress.

Method

MRI: MP‐RAGE, PCASL, FLAIR and DTI sequences were performed. Following quality checks and pre‐processing, Freesurfer (2.1.0) was used with the Destrieux or Desikan‐Killiany atlas to parcellate multiple anatomical brain regions and derive cortical thickness data. The digitized data were archived; raw data was preserved. Genetics: whole genome sequencing (WGS) and/or DNA array data were obtained for participants; apolipoprotein E (APOE) genotype was identified. Blood, urine, stool, saliva and dental plaque samples were collected and stored for biomarker identification and other studies.

Result

Usable MRI data exist for >12,000 participants (4,000 for FLAIR); approximately half the scans are of participants aged ≥50 (see Table). The quality exclusion rate was <5%. WGS and DNA array data have so far been prepared for 800 participants who had MRI scans; APOE genotype information exists for all participants with MRI scans. The MRI and genetic data, plus demographic, cognitive screening and relevant health data are currently being readied for use in combination to identify valuable biomarkers, e.g., those predicting incipient cognitive impairment in preclinical AD. The frequency of major known AD risk alleles in the ToMMo sample will also be determined and compared to that in external GWAS studies.

Conclusion

ToMMo’s MRI, WGS/DNA array, biospecimen repository and other data represent a powerful resource for AD research. Specifically, the combination of MRI and genetic data will support unique disease progression analyses and investigations to elucidate AD pathophysiology.
Quantitative accuracy remains after shortening of dynamic [18F]flortaucipir PET protocol
Authors: Tuncel Hayel , Visser Denise , Yaqub Maqsood , Timmers Tessa , Wolters Emma E. , Ossenkoppele Rik , Van Berckel Bart N.M. , Boellaard Ronald , Golla Sandeep S.V.
Published: December 2020

Background

Tau pathology can be assessed by [18F]flortaucipir positron emission tomography (PET). Dynamic PET protocols allow for accurate quantification of [18F]flortaucipir specific binding. However, dynamic acquisitions can be challenging or burdensome to patients given the long required scan duration of 130 min, especially in persons with cognitive impairment due to Alzheimer’s disease (AD). Therefore, the current study assessed the effect of shorter scan protocols for [18F]flortaucipir PET on its quantitative accuracy.

Method

For this study, two study samples were used: 10 Alzheimer disease (AD) patients and 10 healthy controls (HC) with arterial blood sampling, and 8 AD patients and 6 HCs with a test‐retest scan protocol but without arterial sampling. All subjects underwent a 130‐minute dynamic [18F]flortaucipir PET scan with a 20 min break after 60 minutes. First, the second part of the scan was shortened to 80‐120, 80‐110 and 80‐100 minutes p.i.. Second, the first part of the scan was shortened to 0‐50, 0‐40, and 0‐30 min p.i.. To fill the gap of missing time frames in the reference region (i.e. grey matter cerebellum) time activity curves, four different interpolation methods were tested: 2T4k_VB model using population‐based input‐function (2T4k_POP‐IP), cubic, linear and exponential interpolations. Regional BPND values estimated using SRTM and/or RPM and different scan protocols were compared to the respective values estimated using the original scan acquisition. In addition, test‐retest repeatability (TRT) of the RPM BPND values estimated using the optimal shortest scan duration was assessed.

Result

RPM BPND values obtained using a shortened second part of the PET scan had negligible effect on the accuracy of parameter estimates (Table 1). The RPM BPND values using 0‐30/80‐100 min with 2T4k_POP‐IP interpolation had the best correlation with original DVR‐1, SRTM and RPM BPND (r2=0.95, slope=0.91; r2=0.97, slope=0.88; r2=0.99, slope=0.96). The TRT remained similar using the shortest scan duration (Figure 1).

Conclusion

The current study demonstrated that accurate [18F]flortaucipir quantification can be obtained using a scan protocol of 0‐30/80‐100 min p.i.. With this reduction in total scan duration the scan will be less burdensome while remaining quantitatively accurate.
Complex morphometric effects of sex and aging on subcortical brain structures (N = 9,872)
Authors: Ching Christopher , Abaryan Zvart , Zhu Alyssa , Bright Joanna , Jahanshad Neda , Thompson Paul M
Published: December 2020

Background

Much remains to be understood about subcortical brain alterations across the lifespan and how such changes are related to sex and genetic risk for dementia. Here we analyze the effect of sex, age and APOE genotype on subcortical volume and high‐resolution morphometry in a large population‐based sample. We hypothesized that shape analysis would reveal complex age and sex effects not revealed by gross volumetric analysis and that each copy of the APOE 4 alele would be associated with smaller hippocampal volume.

Method

T1‐weighted brain MRI data (N=9,872) from the UK Biobank were processed using FreeSurfer v5.3 to derive bilateral hippocampus, thalamus, putamen, pallidum, amygdala, caudate, nucleus accumbens, lateral ventricle and intracranial volumes (ICV). The ENIGMA Shape Analysis Pipeline was used to compute local thickness and surface area (SA) metrics for up to 2,502 vertices along each structure’s surface (Figure 1). Linear regression was used to model age (44‐79 yrs), sex, age‐by‐sex interactions, and APOE genotype (Table 1) associations with gross volumes and shape metrics while adjusting for age2, ICV, years of education and body mass index, and adjusting for multiple comparisons.

Result

Older individuals had generally lower gross volumes and larger lateral ventricles (Table 2). Males tended to have larger volumes compared to females (Table 2), though shape analysis revealed subregions that were larger in females (Figure 2). In the full cohort, a significant age‐by‐sex interaction showed males had lower volumes with increasing age. However, in individuals over 60, this interaction was significantly attenuated (Table 2). Shape analysis revealed age‐by‐sex interactions to be more complex, with females displaying subregions of lower thickness and SA with increasing age. No effect of APOE genotype nor interaction between age, sex and genotype were observed, possibly due to small samples of APOE e2/2 and e4/4 genotypes.

Conclusion

Here we show that age and sex effects on subcortical structures may be more complex when modeled using local shape morphometric features. While males tended to lose volume faster than females over the full age span, these effects were weaker at more advanced ages (>60), indicating potentially complex and differential brain aging patterns in men and women.
Comparison of fasting blood sugar, HbA1c, vitamin B12, homocysteine and vitamin D in two parallel, aging study cohorts from rural and urban India: SANSCOG study and TLSA
Authors: Sundarakumar Jonas , Karunakaran Smitha , ME Sumathi , R Kalyani , Sivakumar Palanimuthu T. , Rao Naren P. , Ravindranath Vijayalakshmi ,   SANSCOG and TLSA Investigators
Published: December 2020

Background

Research on identification of risk factors and biomarkers for dementia to facilitate early intervention and prevention has emerged as an important research priority, globally. Previously known risk factors of dementia, mostly from research on the western population could potentially differ vastly in occurrence in the Indian population.

Method

Srinivaspura Aging, Neuro Senescence and COGnition (SANSCOG) study and Tata Longitudinal Study on Aging (TLSA) are parallel, prospective, community‐based, cohort studies in India – rural and urban, respectively – for comprehensive evaluation of risk and protective factors associated with cognitive changes due to normal ageing, dementia and other related disorders. Both the study cohorts comprise of cognitively healthy individuals aged ≥ 45 years. However, they have distinct population characteristics. Participants in the SANSCOG study are recruited from the villages of Srinivaspur Taluk in Kolar District in southern India, through an area sampling strategy, whereas, those in TLSA are recruited through convenience sampling, from urban Bangalore, India. In addition to the detailed clinical and neurocognitive evaluations, fasting peripheral blood is collected in serum, EDTA and fluoride vacutainers and sent to a laboratory for biochemical measurements. Preliminary analysis was been done on biochemical parameters such as fasting blood sugar (FBS), HbA1c, vitamin B12, homocysteine and vitamin D.

Result

Significantly higher percentage of the urban cohort had fasting blood glucose in the diabetic and prediabetic ranges. HbA1c values were also substantially higher in the urban cohort, which also had a much higher percentage of persons with abnormal total cholesterol (≥ 200 mg/dL). However, Vitamin B12 deficiency (< 200 pg/mL) was significantly more in the rural than in the urban cohort. Conversely, Vitamin D deficiency (< 20 ng/mL) was less in the rural than in the urban cohort. The urban cohort had a significantly higher percentage of persons with abnormally high serum homocysteine levels (≥ 15 µmol/L).

Conclusion

The two study cohorts differed significantly in their biochemical measurements – the urban cohort having a higher proportion of participants with abnormal values of FBS and HbA1c, total cholesterol and serum homocysteine. Vitamin B12 deficiency was seen more in the rural cohort and vitamin D deficiency more in the urban cohort.
Longitudinal hippocampal atrophy is associated with an amyloid‐independent entorhinal tauopathy and an amyloid‐dependent neocortical tauopathy
Authors: Hanseeuw Bernard , Jacobs Heidi I.L. , Schultz Aaron P. , Buckley Rachel F. , Properzi Michael J. , Becker Alex , Farrell Michelle E. , Scott Matthew R. , Hampton Olivia L. , Sanchez Justin S. , Quiroz Yakeel T. , Chhatwal Jasmeer P. , Price Julie C. , Sperling Reisa A. , Johnson Keith A.
Published: December 2020

Background

Hippocampal atrophy is observed in Alzheimer’s disease (AD), but also in older adults with no evidence of amyloid‐β (Aβ) plaques. To understand the pathophysiology of hippocampal volume (HV) loss, we investigated the associations between longitudinal HV, age, genotype, Aβ, and tau in clinically normal (CN) participants from the Harvard Aging Brain Study.

Method

Serial MRI (HV [1.3‐7.0y], PiB‐PET (Aβ, [1.9‐8.5y]), and Flortaucipir‐PET (tau, [0.8‐6.0y]) measures were obtained from 128CN participants (72 [56%] females, 38 [30%] e4 carriers, median age at baseline: 71.3, follow‐up duration: 5.1y). Participants had a median of 3MRIs [2‐5], 3PiB‐PET [2‐5], and 2Flortaucipir‐PET [2‐4]. Longitudinal HVs were processed using Freesurfer v.6 and adjusted for intracranial volume. PiB was measured in a neocortical aggregate, Flortaucipir in inferior temporal (IT) and entorhinal cortex (EC). PET data were expressed as PVC‐SUVr scaled to subcortical white matter. We predicted imaging data over time with random intercept and slope in linear mixed‐models and extracted PiB, FTP, and HV slopes for each subject. Baseline PET and slope data were entered in age‐adjusted linear regressions to evaluate their associations with HV slope.

Result

Faster HV loss was observed at older ages (Figure 1), and marginally in e4 carriers (Table, #1‐2). It was also associated with higher baseline PiB levels (#3). The PiB association was stronger than the one of e4 status (#3). HV slope did not correlate with PiB slope (#4). HV loss was associated with baseline EC‐FTP (#5) and baseline IT‐FTP (#6). The association between HV loss and EC‐FTP was also observed in the low‐PiB only (#7), but not the one with IT‐FTP (#8). IT‐FTP, but not EC‐FTP, interacted with baseline PiB to predict HV slope (Figure 2‐3). FTP slopes measures were associated with HV slope, above and beyond the baseline association (#9‐10). Altogether PET data explained 40% of the variance in HV slope; but faster HV loss was still associated with age after taking PET measures into account.

Conclusion

In preclinical AD, hippocampal atrophy is associated with an Aβ‐independent entorhinal tau accumulation and an Aβ‐dependent neocortical tau accumulation. It is also likely associated with pathological processes that our biomarkers did not measure.
Dextromethorphan for the treatment of agitation in dementia: A pilot study
Authors: Hwang Tzung‐Jeng , Chen Jiahn‐Jyh , Lin Yi‐Ting , Chan Hung‐Yu
Published: December 2020

Background

Agitation is highly prevalent in patients with dementia and off‐label use of antipsychotic agents for agitation is common. But antipsychotic agents are clearly associated with increased adverse effects. A recent study found dextromethorphan (DXM) and low dose quinidine may be effective for the management of agitation in patients with Alzheimer disease (AD).

Methods

This is an open‐label, 10‐week study. Eligible dementia patients (AD or VaD) were enrolled. These patients received DXM 60 mg/day from Day 1 through Day 7. If the symptoms of agitation were not reduced, the dose might be gradually increased to 240 mg/day. The primary endpoint was score change in agitation domain of the Neuropsychiatric Inventory (NPI), and secondary endpoints include change on NPI total score and subscores, CGI, and MMSE.

Results

A total of 16 patients were recruited. The mean (SD) of age was 79.3 (9.9) years, with male to female ratio 1:1. The mean (SD) of MMSE was 9.7 (9.7). At baseline, CGI‐Severity for agitation was 4 to 6 (mean=4.9), The mean and SD of behavioral disturbances were: 8.4 (3.5) for NPI agitation score, 8.1 (4.3) for NPI irritability score, 7.6 (4.8) for NPI aberrant motor behavior, and 58.8 (33.7) for NPI total score. At the endpoint, the mean dose of DXM was 150 mg/day. There was a significant decrease of the score of behavioral disturbance: 3.8 (3.0) for NPI agitation score (p<0.001), 4.2 (3.9) for NPI irritability score (p<0.001), 2.3 (3.9) for NPI aberrant motor behavior (p<0.036), and 24.4 (19.6) for NPI total score (p<0.001). The CGI‐I on agitation revealed 69% (n=11) with much/very much improved, 25% (n=4) minimal improved, and 6% (n=1) minimally worse. There were some mild to moderate adverse effects reported, including malaise, anemia, drowsiness, skin itching, and increased appetite. No severe adverse effects were found.

Conclusions

The results of this preliminary study suggest DXM 60‐240 mg/day seem quite efficacious for the treatment of agitation in dementia and without severe adverse reactions. It may be suitable for short‐term use for control of agitation in elderly dementia patients.
Multimodal modelling of the heterogeneity of Alzheimer’s disease
Authors: Garcia Mar Estarellas , Young Alexandra L. , Schott Jonathan M. , Alexander Daniel C. ,   Centre for Medical Image Computing
Published: December 2020

Background

Data‐driven modelling techniques, such as Subtype and Stage Inference (SuStaIn) (Young, et al., 2018), have been developed to disentangle the temporal and phenotypic heterogeneity of neurodegenerative diseases such as Alzheimer’s disease (AD) from widely available cross‐sectional datasets such as ADNI. This study builds on early work with SuStaIn by using multimodal data and missing‐data modelling to give a more detailed picture of the landscape of sporadic AD subtypes.

Method

SuStaIn was applied to cross‐sectional cerebrospinal fluid (CSF), magnetic resonance imaging (MRI) and positron emission tomography (PET) metrics, and cognitive scores from ADNI to identify multimodal disease subtypes with distinct progression patterns. The dataset consists of 789 subjects that passed quality control (182 cognitively normal (CN), 86 subjective memory concern (SMC), 241 early mild cognitive impairment (MCI), 163 late MCI and 117 AD). Amyloid‐negative (CSF Abeta < 192pg/ml) subjects were chosen as control subjects. A K‐Nearest Neighbour (KNN) algorithm was used to impute missing values (3% of the data), allowing for subtyping and staging of the full dataset.

Result

Figure 1 visualises the subtype progression patterns, with the precise model output being shown in Figure 2. Four different subtypes can be inferred from the data: 1) Typical AD with late tau: First changes are seen in CSF and PET measures of b‐amyloid, followed by cognitive scores impairment and finally, brain atrophy. 2) Typical AD: Changes in b‐amyloid closely followed by an increase in tau, both using CSF and PET based biomarkers. Cognitive scores and subcortical areas are affected next. 3) Cortical AD: Cortical atrophy is followed by subcortical atrophy and then increase in CSF and PET amyloid. 4) Cognitive decline with hippocampal atrophy: Mainly defined by a decrease in cognitive tests performance, followed by atrophy of the hippocampus and the amygdala.

Conclusion

This study provides a deeper insight into the heterogeneity of AD, revealing four subtypes with differing trajectories of biomarker abnormalities. Unravelling this heterogeneity will be a critical step in developing personalised medicine, allowing for improved power for clinical trials and better information for patients.
CT‐based brain segmentation and volumetry using deep learning methods
Authors: Srikrishna Meera , Pereira Joana B , Heckemann Rolf A , Volpe Giovanni , Zettergren Anna , Kern Silke , Westman Eric , Skoog Ingmar , Schöll Michael
Published: December 2020

Background

Computed tomography (CT) is the most commonly used brain examination tool for the initial assessment of neurodegenerative diseases such as dementia disorders. It is widely available, affordable and provides short scan times, however, it is mainly used for visual assessment of brain integrity and exclusion of co‐pathologies while magnetic resonance imaging (MRI) is the preferred modality for the extraction of regional brain volumetric measures, obtained by brain segmentation into tissue classes and anatomical regions. We developed an automated, deep learning‐based approach to segment CT scans into intracranial volume (ICV), grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF).

Method

139 CT and T1‐weighted MRI scans acquired on the same day in participants of the Gothenburg H70 Birth Cohort Study (70% female) were included in this study. SPM12 was used to extract GM, WM and CSF tissue class labels and Pincram for creating ICV masks from the MRIs. These labels were used as training input and as the reference criteria for subsequent volumetric and similarity comparisons. In a training subcohort (n=120), CT scans were co‐registered to their corresponding MRI. A U‐Net deep learning model was developed using the Keras software package which underwent two training sessions: 1. Predict ICVs in CT and extract brain; 2. Predict GM, WM and CSF volumes with extracted CT images as input, preserving the predictions in individual space. MRI labels were incorporated during the training sessions including 120 datasets.

Result

Nineteen validation datasets which were not included in the training were used for the prediction process without MRI intervention. Continuous Dice scores between ICV, GM, WM and CSF predictions from the model in the validation datasets and independently MRI‐derived labels were 0.97, 0.79, 0.81 and 0.72 with a volumetric Pearson correlation coefficient, r of 0.93, 0.84, 0.73 and 0.71, respectively.

Conclusion

Our pilot study developed a deep learning model that enables the automated segmentation and volumetric measure extraction from cranial CT. With further optimization, training on larger and more diverse datasets, we aim at improving the model to execute predictions comparable to MRI‐based approaches, thus, developing a diagnostic support tool based on routinely acquired CT scans.
Abnormalities of cortical neural synchronization mechanisms in subjects with mild cognitive impairment due to Alzheimer's disease and epileptiform‐like signatures
Authors: Percio Claudio Del , Noce Giuseppe , Bonaventura Carlo Di , Lizio Roberta , Soricelli Andrea , Ferri Raffaele , Nobili Flavio Mariano , Famà Francesco , Palma Eleonora , Cifelli Pierangelo , Marizzoni Moira , Frisoni Giovanni B , Babiloni Claudio
Published: December 2020

Background

Previous evidence has shown that Alzheimer’s disease (AD) patients exhibited an increased risk of overt epileptic seizures or subclinical, non‐convulsive, epileptiform‐like electroencephalographic (EEG) signatures (i.e., spike‐sharp wave discharges, giant spikes, etc.) due to temporal and frontal lobe dysfunctions and aberrant cortical neural synchronization. In the present study, cortical sources of resting state eyes‐closed EEG (rsEEG) rhythms were estimated in patients with amnesic mild cognitive impairment due to AD (ADMCI), using normal elderly (Nold) and AD patients with dementia (ADD) as controls. The hypothesis was that rsEEG sources may be more abnormal in ADMCI with than without epileptiform‐like EEG signatures.

Method

Clinical and rsEEG data in 35 ADD, 50 ADMCI, and 35 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini Mental State Evaluation (MMSE) score was matched between the ADMCI with and without epileptiform‐like EEG signatures (i.e., spike‐sharp wave discharges, giant spikes, etc.). No subject had received a clinical diagnosis of epilepsy. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources.

Result

Frontal and temporal delta source activities were more abnormal in the ADMCI patients with epileptiform‐like EEG signatures (N = 13; 26%; ADMCI‐ELES) and ADD than the control ADMCI patients (N= 37; ADMCI‐noELES; Figure 1). This effect may not depend on sleep onset or epileptiform‐like EEG signatures as “biological artifacts” in the EEG signal, because of the present source analysis was performed from rsEEG epochs free from those signatures.

Conclusion

The present findings suggest that in MCI patients, AD neuropathology may derange neurophysiological low‐frequency (i.e. delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance, and such derangement may be more pronounced in frontal and temporal cortical regions in ADMCI patients characterized by epileptiform EEG signatures. Future investigations should cross‐validate the present findings by a longitudinal prospective study testing. We predict that ADMCI patients with those delta source and epileptiform‐like EEG signatures may develop a fast disease progression.
Impact of age, gender, and education on the performance of Addenbrooke’s Cognitive Examination (ACE‐ III) in urban and rural Indians
Authors: Kahali Bratati , Dutt Siddharth , Rao Naren P , Ravindranath Vijayalakshmi ,   SANSCOG and TLSA Investigators
Published: December 2020

Background

Addenbrooke’s Cognitive Examination (ACE‐III) is a well‐validated cognitive screening test, designed to detect Dementia. This work intends to investigate the influence of age, gender, and education in Indian population.

Method

Srinivaspura Aging, Neuro Senescence and COGnition (SANSCOG) study and Tata Longitudinal Study on Aging (TLSA) are parallel, prospective, community‐based, cohort studies in India – rural and urban respectively – for comprehensive evaluation of risk and protective factors associated with cognitive changes due to normal ageing, Alzheimer’s disease and other related disorders. 444 and 1344 volunteers were enrolled in TLSA and SANSCOG respectively. ACE‐III was administered on them by trained psychologists. They were classified in four age groups (45– 55, 56–65, 66‐75, and >75 years of age) and six levels for years of education (0‐4, 5‐8, 9‐12, 13‐15, 16‐18, >18). Univariate analysis was performed to study the effect of age, gender, or education, on the ACE‐III total scores. Multivariate analysis was done to study the effects of age, gender, and education on the different cognitive domains of ACE‐III.

Result

No significant differences were observed for ACE‐III among different age groups or gender for individuals enrolled in TLSA, as well as those in SANSCOG. The level of education had a significant effect on ACE‐III as well as all the sub‐domains for SANSCOG participants, but not for TLSA participants. However, age or gender do not show such trends. When the effect of age, gender, and level of education was jointly assessed on these indices, they were found to have significant effects only for visuospatial domain for TLSA participants; and attention and visuospatial domain for SANSCOG participants. Additionally, memory, fluency, language, visuospatial indices of ACE‐III are significantly affected by the age of the participant in SANSCOG.

Conclusion

These results show that age, gender and education of participants can have important effects on performance of ACE‐III and its cognitive sub‐domains. Nevertheless, this is an ongoing work, and currently more participants are being assessed in both the studies who would be followed up longitudinally, which can yield precise conclusive results in future.
Sensitivity and specificity of EEG biomarkers of AD at the preclinical stage
Authors: Noce Giuseppe , Babiloni Claudio , Lopez Susanna , Percio Claudio Del , Pascarelli Maria Teresa , Lizio Roberta , Teipel Stefan J. , González‐Escamilla Gabriel , Bakardjian Hovagim , George Nathalie , Cavedo Enrica , Lista Simone , Chiesa Patrizia Andrea , Vergallo Andrea , Lemercier Pablo , Spinelli Giuseppe , Grothe Michel , Potier Marie‐Claude , Stocchi Fabrizio , Ferri Raffaele , Habert Marie‐Odile , Fraga Francisco J. , Dubois Bruno , Hampel Harald ,   INSIGHT‐preAD study group
Published: December 2020

Background

Cognitive reserve (CR) is present in Alzheimer’s disease (AD) seniors with high education attainment making them clinically resilient to extended brain neuropathology and neurodegeneration. Here we tested whether subjective memory complaint (SMC) seniors with AD neuropathology and high education attainment may present abnormal eyes‐closed resting state posterior electroencephalographic (rsEEG) rhythms around individual alpha frequency peak (IAFp), typically altered in AD patients with mild cognitive impairment and dementia.

Method

We selected all individual baseline data of the prospective INSIGHT‐preAD cohort (Paris) including mini mental state examination score ≥ 28, artifact‐free markers of 18F‐florbetapir positron emission tomography (amyPET), structural magnetic resonance imaging, and rsEEG rhythms (e.g., 172 SMC seniors). Delta, theta, alpha1, alpha2, and alpha3 bands were determined on individual basis based on IAFp, while beta1 (14‐20 Hz), beta2 (20‐30 Hz), and gamma (30‐40 Hz) were standard fixed bands.

Result

The SMC participants negative to amyPET AD markers (SMCneg) with high (over low‐moderate) education level showed higher posterior alpha 2 power density (possibly “neuroprotective”). Furthermore, amyPET‐positive SMC (SMCpos) participants with high (over low‐moderate) education level showed higher temporal alpha 3 power density (possibly “neuroprotective”) and lower posterior alpha 2 power density (possibly “compensatory”; Figure 1). This effect may reflect CR as no differences in brain gray‐white matter and cognitive functions were observed between these SMCpos/SMCneg sub‐groups.

Conclusion

Preclinical Alzheimer’s neuropathology may interact with education attainment and neurophysiological mechanisms generating cortical alpha rhythms around IAFp (i.e., alpha 2 and 3) in quiet wakefulness.