bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationship of daily, institutional and structural racism with cognition in ethnically/racially diverse middle‐age Americans
Authors: Seblova Dominika , Avila Justina F , Kraal A.Zarina , Starks Tiara M. , Adkins‐Jackson Paris AJ , Brickman Adam M. , Manly Jennifer J
Published: December 2022

Background

Racism is a social determinant of health that operates at multiple levels ‐ interpersonal, institutional, structural ‐ producing stress and limiting access to resources that have dire biopsychosocial effects for historically marginalized communities. Research on older adults suggests interpersonal and structural racism, separately, are associated with worse cognition and may be an underlying reason for racial/ethnic disparities in cognitive aging. An evidence gap remains on how multilevel racism influences cognition throughout the life‐course.

Method

We assessed 942 middle‐aged community‐dwelling adults (mean age = 55, SD = 11; 64% women; 19% non‐Latinx White; 23% non‐Latinx Black; 55% Latinx). Daily interpersonal racism was ascertained by the Everyday Discrimination (ED) scale, institutional racism by the Major Discrimination (MD) Scale, and structural racism in early life was measured by residential segregation of the census block group in which parents of our respondents lived. Our outcomes were derived from a neuropsychological evaluation with the Digit Span assessing attention and working memory, and delayed recall from the Selective Reminding Test capturing episodic memory. Two fluency measures (animal and letter) were also studied. The relationship between multilevel racism indicators and cognition was estimated using age‐adjusted linear regression models. Additional models were stratified by racialized/ethnic group and added education as a covariate.

Result

Exposure to multilevel racism varied across racialized/ethnic group. Non‐Latinx Black respondents scored highest on interpersonal racism, second highest on institutional racism, and were more likely to grow up in segregated residential areas with higher proportion of other Black residents. Exposure to interpersonal (Figure A) and institutional racism (Figure B) was associated with lower memory scores and these associations were driven by non‐Latinx Black respondents. Structural racism was associated with lower episodic memory in the full sample.

Conclusion

Our findings indicate that multilevel racism related to cognition and due to higher exposure among marginalized groups may be a substantial driver of racial/ethnic disparities in cognitive health. In future, additive and multiplicative effects of our exposures will be examined.
Prevalence and clinical associations of atrophy subtypes using clinical routine image analysis software in MCI patients from a memory clinic population
Authors: Schwarz Adam J. , Cavedo Enrica , Gordon Elizabeth , Samper‐González Jorge , dos Santos Clarisse Longo ,   the MEMENTO Study Group
Published: December 2022

Background

Three patterns of brain atrophy have been consistently identified in cases of Alzheimer’s dementia [1]: a limbic‐predominant (LP) phenotype, with atrophy of the hippocampus but relatively spared neocortex; a hippocampal sparing (HS) phenotype, with atrophy in the cortex (especially lateral temporal and parietal lobes) but sparing of the hippocampus; and a typical/diffuse (TD) phenotype that presents with atrophy in both. A recent study extended this concept to a less severely affected memory clinic population (the MEMENTO Study). Here, we assessed atrophy subtypes in that same population using an approach based on the output of QyScore® an FDA‐approved and CE‐marked image analysis software.

Method

1642 MCI participants from the MEMENTO cohort (Age 71±9, MMSE 27.8±2.0, CDR‐SB 0.6±0.7) had 3DT1 MRI scans analyzed with QyScore®. 678 (41%) had amyloid status from CSF or PET, of which 193 (28%) were amyloid‐positive (A+). Neurodegeneration‐positive (N+) atrophy subtypes were defined on individual scans using z‐scores from parietal cortex and hippocampus volumes referenced to 1290 cognitively normal individuals. LP and HS were defined by atrophy (z<‐1.64) of parietal lobe or hippocampus only, and TD by atrophy in both structures (otherwise N‐).

Result

The proportion of single‐domain amnestic (aMCIsd), multi‐domain amnestic (aMCImd), single‐domain non‐amnestic (naMCIsd) and multi‐domain non‐amnestic (naMCImd) individuals was 10%, 50%, 21% and 18% respectively. N+ subtypes were more prevalent in amnestic (aMCIsd 18%, aMCImd 17%) than non‐amnestic (naMCIsd 8%, naMCImd 10%) presentations. N+ subtypes were more common in A+ participants, especially the amnestic presentations (aMCIsd 42%, aMCImd 29%). Overall, the HS subtype was the most common (8% of all cases, 16% of A+ cases), followed by LP (4%/6%) and TD (2%/3%). The LP subtype was more prevalent in amnestic presentations.

Conclusion

The relatively low prevalence of the TD subtype in this cohort is consistent with [2]. The overall prevalence of N+ subtypes in MEMENTO by this method is intermediate between those previously reported using a similar method for ADNI CN A+ and aMCI A+ cohorts [3].

[1] Ferriera et al. (2020) Neurology 94:436 [2] Planche et al. (2021) Alz & Dem 17(4):651 [3] Charil et al. (2018) AAIC
Interplay of the human exposome, metabolome and gut microbiome in dementia and major depression
Authors: van Duijn Cornelia M , Amin Najaf , Liu Jun , Bonnechere Bruno , MahmoudianDehkordi Siamak , Arnold Matthias , Batra Richa , Chiou Yu‐Jie , Fernandes Marco , Ikram M. Arfan , Kraaij Robert , Krumsiek Jan , Newby Danielle , Nho Kwangsik , Radjabzadeh Djawad , Saykin Andrew J. , Shi Liu , Sproviero William , Winchester Laura M , Yang Yang , Nevado‐Holgado Alejo J , Kastenmüller Gabi , Kaddurah‐Daouk Rima
Published: December 2022

Background

The pathogenesis of dementia and depression is complex involving the interplay of genetic and environmental risk factors including diet, life‐style and the gut microbiome. Dementia and depression co‐occur and metabolomics studies may shed light on the interplay of the various risk factors.

Methods

We have studied the metabolome of 118,466 individuals including 8462 cases with a history of major depression (MDD) and 1,364 patients who developed dementia during follow‐up from the UK Biobank (UKB). The human metabolome was profiled using the Nightingale platform.

Result

For both disorders, we find direct evidence that metabolites involved in the tricarboxylic acid (TCA) cycle are altered in patients, albeit that different metabolites emerge as the most significant drivers in the two disorders. Both dementia and MDD dementia patients show a marked change in the HDL/VLDL axis in blood, with similar changes in particular small and extra large HDL subfractions seen in patients with MDD and those who develop depression in the future. The two patients groups further show similar changes in fat metabolism as measured by omega 3, omega 6 and PUFA levels. When comparing metabolic profiles over environmental risk factors for MDD and dementia, we find that MDD clusters with dementia risk factors physical activity, history of previous smoking and social isolation. Integrating the metabolic profiles of major depression and the gut microbiome we find that the gut microbiome may be a key mediator in the relationship between various metabolites involved in the HDL subfractions associated to both MDD and dementia.

Conclusion

Our study shows that energy and fat metabolism is disturbed in patients with MDD as well as patients who develop dementia in the future and that the interplay between the genome, exposome, gut microbiome, human metabolome may play role in the co‐occurrence of major depression and dementia.
A Novel Protective locus significantly reduces the ApoEε4 risk for Alzheimer’s Disease in individuals of African Ancestry.
Authors: Vasquez Marina Lipkin , Rajabli Farid , Beecham Gary W. , Hendrie Hugh C , Baiyewu Olusegun , Ogunniyi Adesola , Gao Sujuan , Kushch Nicholas A. , Hamilton‐Nelson Kara L. , Young Juan J , Dykxhoorn Derek M. , Nuytemans Karen , Kunkle Brian W. , Wang Liyong , Jin Fulai , Liu Xiaoxiao , Feliciano‐Astacio Briseida E. , Dalgard Clifton L. , Griswold Anthony J. , Byrd Goldie S. , Reitz Christiane , Haines Jonathan L. , Pericak‐Vance Margaret A. , Vance Jeffery M. ,   Alzheimer’s Disease Sequencing Project,   Alzheimer’s Disease Genetic Consortium
Published: December 2022

Background

African ancestry populations have a lower risk for developing Alzheimer disease (AD) from ApoEε4 compared to other populations. Understanding this mechanism of protection could lead new therapeutic insights for AD. Our goal is to identify areas of the genome that interact with ApoEε4 in African ancestry that result in the lowered risk for developing AD in this population.

Methods

We performed association analyses using a logistic regression model with ApoEε4 allele as an interaction term and adjusted for genome‐wide ancestry, age, and sex. Discovery analysis included imputed SNP data from 1,850 African American (AA) individuals with AD and 4,331 AA controls. We performed replication analysis on whole‐genome sequenced (WGS) data from 1) 63 Ibadan (Nigerian) AD individuals and 648 Ibadan controls; 2) WGS 273 Puerto Rican (PR) AD individuals and 275 PR controls; and 3) SNPs imputed from 8,463 non‐Hispanic White (NHW) AD individuals and 11,365 NHW controls.

Results

We identified a significant interaction with the ApoE ε4 allele and the SNP rs10423769_A allele, that reduces the odds ratio for AD risk from 7.2 for ApoEε4/ε4 without the A allele to 2.1 for allele ApoEε4/ε4 carriers with at least one A allele. rs10423769 (frequency = 0.11 in AA, NHW= 0.003) is located approximately 2 megabases distal to ApoE, in a large cluster of pregnancy specific beta‐1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. rs10423769 is reported to be a splicing QTL (sQTL) for TMEM145, whose highest brain expression is in the cerebellum. This interaction analysis was identified in the discovery AA dataset (β=‐0.54, SE=0.12,p‐value=7.50x10‐6), and this finding was replicated in both the Ibadan (β = ‐1.32,SE = 0.52,p‐value = 1.15x10‐2) and PR (β=‐1.27,SE=0.64,p‐value=4.91x10‐2) datasets while it trended but was not significant in the NHW dataset.

Conclusion

This study identified a new African‐ancestry specific locus that reduces the risk effect of ApoEε4 for developing AD by approximately 75%. The genes lying near this protective locus suggest potential new protective mechanisms for AD development.
Short Telomeres Associate with Hyperphosphorylated Tau Burden in Primary Age‐Related Tauopathy
Authors: McMillan Corey T , Adhikari Bandita , Farrell Kurt W. , Wolk David A. , Lee Eddie B ,   PART Working Group, Crary John F. , Johnson F Brad
Published: December 2022

Background

Primary age‐related tauopathy (PART) is characterized by neuropathological hyperphosphorylated tau burden (p‐tau) in the absence of significant amyloid pathology. Aging is a major risk factor for p‐tau that is generally defined chronologically in years since birth. Telomeres shorten with age and various sources of DNA damage and thus telomere lengths (TL) provide an alternative measure of biological age. Additionally, DNA methylation (DNAm) changes over time and may contribute to changes in TL. Together, we hypothesize that shorter mean TL will be associated with increased risk of p‐tau burden and that this process may be mediated by DNAm.

Method

We extracted DNA from frontal cortex of 113 individuals (Age=87.3+9.3; 37% Female) that met neuropathological criteria for definite PART. We measured mean TL using qPCR to determine the copy number of telomere repeat DNA in comparison to a single copy gene. The assays were performed in a blinded fashion, and each sample was measured using two different amounts of input DNA to ensure linearity. We also measured bisulfite‐converted DNA methylation using the Illumina MethylationEPIC BeadChip Kit for ∼850K CpGs. P‐tau burden was measured in medial temporal cortex (entorhinal cortex and hippocampus proper) using an Aperio Digital Pathology Slide Scanner. Linear regression related TL to p‐tau burden, adjusting for age. We used eWAS to relate methylation to TL. Lastly, non‐parametric bootstrapping using the mediation package in R was used to evaluate whether TL association with p‐tau burden may be mediated by DNAm.

Result

Shorter TL was significantly associated with increased p‐tau burden (B=‐0.28; p=‐.003), including adjustment for age (B=0.003; p=0.003). eWAS identified six CpG sites significantly associated with TL (all q<0.05). Causal mediation analyses identified that two of these CpGs partially mediate the association between TL length and p‐tau burden: 32.5% proportion mediated by cg08701686 (UNC5D) and 48.6% proportion mediated by cg24533059 (near IFNGR1 and OLIG3).

Conclusion

Shorter TL is associated with increased p‐tau pathological burden in PART and may be mediated in part by DNAm at particular loci. These findings support the concept that biological aging, as measured with TL and DNAm, may contribute to tauopathy beyond chronological age effects.
Choice of Inversion Time for Arterial Spin Labeling MRI in the U.S. POINTER Lifestyle Intervention Trial
Authors: Jung Youngkyoo , Hong Sarah Y. , Kim Donghoon , Vemuri Prashanthi , Borowski Bret J. , Jack Clifford R. , Koeppe Robert A. , Lockhart Samuel N. , Harrison Theresa M. , Gordineer Leslie , Woolard Nancy , Espeland Mark A. , Harvey Danielle J. , Lovato Laura , Toga Arthur W. , Masdeu Joseph C. , Oh Hwamee , Gitelman Darren R. , Aggarwal Neelum T. , Carrillo Maria C. , Snyder Heather M. , Whitmer Rachel A. , Baker Laura D. , DeCarli Charles S. , Landau Susan M.
Published: December 2022

Background

The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in older adults (60‐79 years). The POINTER Imaging ancillary study is collecting Arterial Spin Labeling (ASL) MRI data to map cerebral blood flow (CBF) and evaluate the effect of interventions in the perfusion imaging biomarker. The optimization of timing parameters is essential for robust and efficient acquisition of ASL MRI.

Method

A subset (n=83; F/M=51/32; age=69.0±5.5) of POINTER Imaging participants at two imaging sites underwent two ASL MRI scans during the same baseline session. Two 3D Pulsed ASL were obtained with TI1 of 790ms and TI2 values of 2000ms or 2750ms, which provide the delay times (between labeling and imaging) of 1210ms or 1960ms. ASL images were quantified into a physiological unit of CBF, ml/100g/min, using a single compartment kinetic model. CBF maps from two scans were normalized into a standard space and a voxel‐wise paired t‐test was performed after site variations were harmonized and covariates (age and sex) were adjusted. The age and sex effects in the difference of CBF values between two scans were also examined using linear regression. To control false positives, clusters smaller than 41ml were removed based on a simulation with α=0.05.

Result

The CBF values in ASL MRI rely on the timing of image acquisition: only a fraction of label bolus arrives in the tissue with a short delay while images suffer from low signal due to the magnetization decay with a long delay. Figure 1 shows the regions that require a long delay time (red) or a short delay (blue). The difference in CBF is proportional to arterial transit time (ATT) and the analysis shows females have shorter ATT mainly in the peri‐Sylvian region (Figure 2). No cluster survived correction in the analysis of the aging effect.

Conclusion

The acquisition of two CBF maps not only offers optimization of acquisition timing but provides an additional perfusion parameter, arterial transit time, which may be a potential biomarker of cerebrovascular pathophysiology.
Learning differentially increases the synaptic levels of AMPA receptor subunits (GluA1‐GluA4) in the rodent hippocampus: a single‐synapse approach
Authors: Prieto G. Aleph , Rodriguez‐Ortiz Carlos J. , Kitazawa Masashi , Cotman Carl W.
Published: December 2022

Background

Decades of experimental work support the idea that synapses are the anatomical substrate for experience‐dependent plasticity in the brain. Changes in the synaptic strength underlie learning and memory via the accumulation of glutamate AMPA receptors (AMPAR) at the surface of excitatory synapses. AMPAR are tetrameric receptors constituted by multiple combination of four subunits: GluA1 GluA2, GluA3, and GluA4. However, the relative contribution of each AMPAR subunit on learning and memory is relatively unexplored.

Method

Here, we introduce Fluorescence Analysis of Single‐Synapse Potentiation induced by Learning (FASS‐PiL), a flow cytometry‐based method to quantify surface levels of all four GluA‐AMPAR subunits, in parallel, in isolated synaptosomes after a learning episode in rodents. We evaluated surface levels of all four AMPAR subunits in synaptosomes of mice trained in a learning protocol commonly used for studying episodic memory in the hippocampus (e.g., Object Location Memory (OLM) and Object Recognition Memory (ORM) tasks). Briefly, after exploring novel objects in a novel environment for 10 min, mice were returned to their home cage for 60 min. After hippocampus dissection, synaptosome isolation, and immunostaining, samples were analyzed via flow cytometry.

Result

We first demonstrated that FASS‐PiL is a simple and sensitive method to track all four GluAs at the synaptosome surface (each GluA subunit was paired with the presynaptic marker Neurexin‐1beta to focus on synaptosome particles containing both pre‐ and postsynaptic compartments). Notably, by profiling hundreds of events, our data showed that the OLM training increases the number of hippocampal synaptosomes expressing high levels of GluA1 and GluA2, but not GluA3 and GluA4 (vs control animals).

Conclusion

Our results indicate that plasticity‐related mechanisms underlying learning are AMPA‐subunit‐specific in hippocampal synapses. Our approach could provide the basis for protocols to study behavioral‐relevant mechanisms of plasticity directly at the synapse, with single‐event resolution.
Distinguishing between amyloid‐beta‐directed antibodies: Ability of PMN310 to target toxic oligomers despite competing species
Authors: Gibbs Ebrima , Coutts Juliane , Roman Andrei , Zhao Beibei , Kaplan Johanne , Cashman Neil R
Published: December 2022

Background

A large body of evidence indicates that the most pathogenic species of Abeta in Alzheimer’s disease (AD) consist of soluble toxic oligomers as opposed to insoluble fibrils and monomers. The ability of a therapeutic antibody to target toxic Abeta oligomers without being diverted by binding to competing non‐toxic species is expected to result in greater efficacy. This is supported by clinical results to date showing poor efficacy of non‐selective antibodies but improved success with partially selective antibodies that bind oligomers and plaque. As a next generation antibody, PMN310 is a therapeutic candidate designed to more selectively target toxic oligomers. Avoiding interaction with plaque and vascular deposits has the additional advantage of potentially decreasing the incidence of amyloid‐related imaging abnormalities (ARIA). In this study, PMN310 was compared to other Abeta antibodies for selectivity and ability to maintain interaction with toxic oligomers in the presence of competing monomers.

Methods

The binding of multiple Abeta‐directed antibodies (PMN310 and biosimilars donanemab, aducanumab, lecanemab, crenezumab, solanezumab) to synthetic oligomers, with and without pre‐exposure to competing monomers, was evaluated by surface plasmon resonance (SPR). Binding of the antibodies to a toxic oligomer‐enriched low molecular fraction of brain extract from AD patients was similarly evaluated by SPR, with and without monomer competition. Binding to insoluble Abeta deposits was examined by immunohistochemistry (IHC) of AD brain sections.

Results

PMN310 showed little or no interaction with monomers and was among the least impacted by excess monomer competition in binding to synthetic oligomers or naturally occurring toxic oligomers in AD brain extract. This characteristic was shared by other Abeta antibodies that have shown positive clinical outcomes. Non‐selective antibodies that failed in the clinic were strongly inhibited by monomer competition. In contrast to other Abeta antibodies, PMN310 additionally avoided interaction with plaque and vascular deposits as determined by IHC.

Conclusions

PMN310 distinguishes itself from other Abeta antibodies by its enhanced selectivity for toxic oligomers (negligible binding to monomers and plaque) along with its ability to withstand competition by abundant monomers. Additionally, the avoidance of interaction with plaque and vascular deposits by PMN310 could potentially reduce the risk of ARIA.
Event timelines for atrophy‐defined subtypes of Alzheimer’s disease
Authors: Aksman Leon M.
Published: December 2022

Background

A variety of studies have consistently identified three distinct atrophy subtypes in AD1. However, little is known about the timeline of progression for each subtype. Here, for the first time, we identify these timelines using data‐driven disease progression models.

Method

We used a cross‐sectional subtyping model to identify known atrophy subtypes followed by longitudinal disease progression models to identify subtype‐specific event timelines. We first applied the mixture version of Subtype and Stage Inference (SuStaIn2,3) algorithm to 1133 subjects’ CSF‐based amyloid (ABETA), total and phosphorylated tau (TAU and PTAU), MRI‐based hippocampal and cortical volume and cognition (ADAS13 and MMSE). For each biomarker, we built mixture models using cognitively normal, CSF amyloid negative subjects to define normality and diagnosed AD subjects to define abnormality. We used each subject’s last available MRI visit and built a four‐subtype model. We identified the ‘typical’, ‘cortical’ and ‘subcortical’ subtypes and a fourth subtype with non‐AD related progression, which we excluded from further analysis. We also excluded those at stage zero (controls). This left 828 subjects: 540 typical, 177 cortical and 67 subcortical. We then applied the Temporal Event Based Model (TEBM3) to each subtype separately, using all available longitudinal data for each subject. We used the mixture model version of the TEBM with the same eight biomarkers and the same mixture modeling approach. We bootstrapped each subtype’s TEBM model 30 times to estimate confidence intervals for each event.

Result

The TEBM models strongly agreed with the ordering of events in the SuStaIn model (Figures 1 and 2). The typical subtype’s event timeline has onset of cognitive impairment occurring roughly 15‐20 years after tau abnormality (Figure 2). In the cortical subtype, cognitive impairment occurs several years earlier (roughly 5‐12 years), whereas in the subcortical subtype abnormal MMSE and ADAS13 are the earliest events, with decreased hippocampal volume following.

Conclusion

There are clear differences in both the timing and uncertainty of events across subtypes.

References

1. Ferreira, et al., 2019, Neurology.

2. Young, et al., 2018, Nature Communications.

3. Aksman, Wijeratne, et al., 2021, SoftwareX.

4. Wijeratne and Alexander, 2021, IPMI.
Measures of Voice Quality as Indicators of Mild Cognitive Impairment
Authors: Chen Liu , Dodge Hiroko H , Asgari Meysam
Published: December 2022

Background

Noticeable decline in communication skills of patients with Alzheimer’s disease are often observed in the early stages of the disease, years before the dementia emerges. Prior literature has identified language abnormalities such as decline of linguistic ability or syntactic deficits influenced by the cognitive impairment. While language‐related measures are able to characterize spoken words of speech samples, they are inherently incapable of quantifying the voice‐related properties such as emotion or voice quality. Focusing on automatically derived voice‐based biomarkers that reflect the voicing quality of speakers, our objective is to explore the usefulness of these measures at detecting mild cognitive impairment (MCI) as early indicators of MCI in machine learning models. We hypothesize that cognitive impairment influences the individual’s voice quality resulting in an abnormal periodicity in speech often known as vocal dysperiodicity.

Method

We analyzed acoustic properties of audio‐recordings of Craft Story test administered to 107 subjects (50 MCI and 57 healthy controls, mean age 81 yrs) from a recently completed randomized control trial aimed to enhance cognitive reserve by increasing social interactions using video‐chats (www.I-conect.org). In the Craft Story test, the examiner reads a short story to the participant who is asked to retell the story first immediately after hearing the story and next retell it after a 20‐minute delay. Using cepstral analysis method, we extracted cepstrum from both immediate recall (IR) and delayed recall (DR) tests, and utilized statistical measures to represent their acoustic characteristics. We also used recursive feature elimination to only select informative measures and utilized the support vector machine for building classification models.

Result

Cepstrum‐based Measures derived from the IR test achieved higher predictive ability than those derived from the DR test. Combining the measures derived from both IR and DR tests increased the classification results and achieved ROC AUC of 98.83% and 97.09% on gender‐balanced models trained on males and females, respectively.

Conclusion

Our results indicate that voice‐based measures are capable of detecting MCI from audio samples of the Craft Story capitalizing their potential use in automatic screening and telemonitoring of the disorder in research, clinical trials and ultimately clinical practice.
Late‐life behavioral disorder: when is it FTD?
Authors: de Boer Sterre C.M. , Gossink Flora T , Krudop Welmoed A. , Vijverberg Everard G.B. , Pijnenburg Yolande A.L. , Dols Annemiek
Published: December 2022

Background

Distinguishing the behavioural variant of Frontotemporal Dementia (bvFTD) from late‐onset primary psychiatric diseases (PPD) remains challenging with the lack of robust biomarkers for either disorder. Optimal duration of follow‐up of potential FTD cases remains elusive. Our aim was to determine whether a follow up duration of 5 years has added value compared to 2 years in the late‐onset frontal lobe syndrome. Second, we defined which clinical characteristics are valuable for diagnostic precision.

Method

Clinical outcomes of participants of the Late‐Onset frontal lobe (LOF) study were retrieved from 137 patients at least 5 years after baseline visit (T5). Endpoint diagnosis of bvFTD, PPD or Other Neurological Disorders (OND) were obtained. Baseline demographics and measures were compared between the T5 diagnosis groups. Clinical records of cases that switched diagnosis during follow‐up were assessed.

Result

In the 137 patients that were included in the study, the final diagnoses at T5 were bvFTD in 24.1% (n = 33, n = 29 probable bvFTD and n = 4 definite bvFTD), PPD 39.4% (n = 54), OND 33.6% (n = 46) and unknown 2.9% (n = 4). Between T2 and T5, 8 patients switched diagnosis compared to 29 patients during the first 2 years after inclusion (figure 1). Patients with a T2 diagnosis of probable bvFTD with an abnormal FDG‐PET whilst having normal structural imaging results (MRI) were prone to a diagnostic switch between T2 and T5.

Conclusion

A follow up duration of two years is sufficient for patients with a late‐onset frontal lobe syndrome to distinguish bvFTD from PPD on the condition that in cases with non‐supporting structural imaging results after two years further diagnostic work‐up is done.
Understanding the impact of PET amyloid cutpoints on prognostic modelling for cognitively normal individuals
Authors: Goudey Benjamin , Fedyashov Victor , Fripp Jurgen , Rowe Christopher , Maruff Paul , Masters Colin L
Published: December 2022

Background

Amyloid beta (Aβ), measured using PET imaging, is a key biomarker for Alzheimer’s disease (AD) with the consequences of abnormally high Aβ levels (Aβ+) well‐established from prospective research cohorts. A critical question is whether the prognostic capabilities of Aβ can be improved further, for example by refinement of optimal criteria for abnormality.

To date, existing studies have explored such issues using association analyses, which may not reflect performance in prognostic settings due to potential overfitting. Here, the impact of different Aβ cut‐points is determined in a cross‐validation framework, providing performance estimates on data from individuals that were not used for model construction, which better reflects realworld prognostic application. Using data for cognitively normal individuals (CN) from ADNI and AIBL, we estimate time to i) MCI or AD diagnosis and ii) cognitive deficit, defined as MMSE≤26.

Method

We analyse measurements from 344 and 748 CN from ADNI and AIBL respectively who have available PET Aβ scans. PET Aβ SUVRs were transformed to the centiloid scale (CL). For each task, the Aβ cut‐point is varied from ‐10 to 65CL and Cox models are constructed within 10 repeats of 10‐fold cross‐validation. From the resulting 100 models, performance is quantified as the median concordance index (i.e. Harrell’s C).

Result

Details of the two cohorts are shown in Table 1. Across both AIBL and ADNI, a PET only model shows robust performance for cut‐points within a wide range (5 and 50CL) for predicting either time to diagnosis cognitive deficit (Figure 1), with performance dropping rapidly outside this range. When additional covariates are included 2, we see maximal performance for lower cutpoints (5‐20CL) for diagnosis in ADNI and cognitive deficit in ADNI, while remaining tasks show improved performance with higher cut‐point ranges (20‐50CL). Trends in cut‐point are consistent regardless of covariates. Leaving Aβ as a continuous variable yields near‐optimal performance across all tasks.

Conclusion

Our results suggest that within a range (5 and 50CL), prognostic performance is robust to the choice of cut‐point for Aβ, suggesting further refinement of a single cut‐point within this range may not yield substantial improvements for prognostic tasks for CN individuals.
Comparison of Plasma‐based Biomarkers and Cognitive Assessments in predicting progression of MCI to Dementia
Authors: Nallapu Bhargav Teja , Petersen Kellen K. , Lipton Richard B. , Harvey Danielle J. , Ezzati Ali
Published: December 2022

Background

We evaluated the predictive value of phospho‐tau181 (ptau181) and neurofilament light (NfL) in predicting disease progression from amnestic mild cognitive impairment stage (aMCI) to Dementia in models including demographic data and neuropsychological test results.

Method

Participants were 248 Cognitively Normal (CN), 325 MCI, and 91 individuals with dementia due to AD confirmed with amyloid PET from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who had at least one follow‐up visit, and measures of plasma biomarkers (ptau181 and NfL) were included. We examined the separate and joint predictive value of baseline plasma biomarkers and neuropsychological tests (RAVLT: Rey Auditory Verbal Learning Test; ADAS‐Cog: Alzheimer’s Disease Assessment Scale–Cognitive Subscale; TRA‐B: Trail Making Test – Part B; FAQ: Functional Activity Questionnaire) in estimating disease progression from MCI to Dementia. Random Forests machine learning models were used for the classification. Data from CN and AD participants were used for training the models and trained models were used in MCI group to identify those more likely to progress to Dementia. Predictive performances of these models were assessed using longitudinal outcomes at 2 years.

Result

Participants were on average 71.9 yr. old (SD=6.9) and 49.6% female (Table 1). Addition of plasma biomarkers to the model with demographics and APOE4 (base model) improved predictive performance of models in prediction of conversion from MCI to dementia at 2 years (Sensitivity=53.7%, Specificity=81.5%, AUC=0.68). Models that included cognitive tests in addition to the measures in the base model had higher performance in comparison with that only included biomarkers (Sensitivity=55.6%, Specificity=91.5%, AUC=0.74). Best predictive performance was achieved when cognitive scores and plasma biomarkers were both included in the models (Sensitivity=63.0%, Specificity=91.5%, AUC=0.77, Table 2). In the MCI‐subgroup who were amyloid positive (Aβ+) at baseline, similar pattern of results was observed (Table 3).

Conclusion

In persons with MCI, plasma biomarkers of ptau181and NFL can improve our ability to predict disease progression. Concurrent use of plasma biomarkers and cognitive scores improve this predictive ability. This work needs to be extended to various samples and a broader set of plasma biomarkers and neuropsychological tests.
TAR DNA‐binding protein 43 (TDP‐43) contributes to the mismatch between medial temporal volumes and flortaucipir uptake in elderly patients with Alzheimer’s disease neuropathologic changes
Authors: Carlos Arenn F. , Tosakulwong Nirubol , Weigand Stephen D , Senjem Matthew L. , Schwarz Christopher G. , Knopman David S. , Boeve Bradley F. , Petersen Ronald C. , Nguyen Aivi T. , Reichard Ross R. , Dickson Dennis W. , Jack Clifford R. , Lowe Val J. , Whitwell Jennifer L , Josephs Keith A
Published: December 2022

Background

We previously demonstrated that Alzheimer’s disease (AD) patients ≥70 y/o tend to have smaller medial temporal volumes in the presence of relatively less medial temporal 18F‐flortaucipir‐PET uptake compared to young AD patients. TAR DNA‐binding protein 43 (TDP‐43) is frequently found in the brains of AD patients and is associated with old age and medial temporal atrophy. In this study, we aimed to determine whether TDP‐43 could be contributing to the mismatch between medial temporal volumes and flortaucipir‐PET uptake in older AD patients.

Method

We identified 77 participants (median age at death 79 years [range: 51‐99]) who had been enrolled into the Mayo Clinic Alzheimer’s Disease Research Center or Neurodegenerative Research Group (NRG), had undergone flortaucipir‐PET and volumetric MRI scans close to death, and autopsy confirmed AD neuropathological changes, as well as TDP‐43 assessments. Grey matter volumes and flortaucipir standard uptake value ratios (SUVRs) were calculated for hippocampus, amygdala, entorhinal, inferior temporal, and midfrontal cortices. We used bivariate‐response linear regression modelling, adjusting for Braak neurofibrillary tangle stage, to estimate the effect of TDP‐43 and age on gray matter volume and flortaucipir uptake, and tested whether TDP‐43 effect sizes varied according to age.

Result

After accounting for Braak stage, older individuals tended to have significantly lower flortaucipir uptake across regions and lower hippocampal and entorhinal cortex (ERC) volumes. TDP‐43 was associated with reduced hippocampus and ERC volumes but was unrelated to flortaucipir SUVRs (Figure 1). Notably, the TDP‐43 effect size for the hippocampus and ERC was largely consistent across age, i.e., at any age, TDP‐43‐positive participants had significantly smaller hippocampal (∼12% decrease) and ERC (13% decrease) volumes than TDP‐43‐negative participants. However, at older ages, the mean volumes in the whole cohort and, more evidently, in those with dementia moved closer towards the mean of those with TDP‐43 (Figure 1), likely attributable to the increasing frequency of TDP‐43 with age.

Conclusion

TDP‐43 is a major contributor to the mismatch between flortaucipir uptake and medial temporal lobe volumes in older AD patients where lower medial temporal regional volumes are observed in the presence of less flortaucipir uptake.
Successful Recruitment of Vietnamese Americans into the Asian Cohort for Alzheimer’s Disease (ACAD) Pilot Study at UC San Diego
Authors: Lu Anna T. , Park Van Ta , Peavy Guerry M. , Evans Carol , Vo Nam Khue , Tzuang Marian , Revta Carolyn , Nguyen Diep , Nguyen Luan , Nam Percival , Nguyen Khai H. , Feldman Howard H. ,   ACAD Consortium
Published: December 2022

Background

Vietnamese Americans represent the 4th largest Asian American population in the United States with about 2.3 million people nationwide, yet research and literature on the recruitment of Vietnamese Americans in dementia research is limited. In addition to the cultural/linguistic barriers, the lack of Vietnamese language recruitment materials and cognitive assessments has made it difficult to enroll this underserved population into Alzheimer’s disease (AD) research.

Method

To facilitate the recruitment of Vietnamese Americans aged 60 and older into the Asian Cohort for Alzheimer’s Disease (ACAD) pilot study, recruitment methods were established to address physical, technological, linguistic, experiential (protection of identifiable data), and cultural challenges (war‐related trauma, dementia stigma). Localized data collection forms and outreach materials were developed and appropriately translated into Vietnamese with socio‐cultural/linguistic sensitivity. Trusted community advisors/partners and bilingual/bicultural Vietnamese‐English research staff were central to the successful recruitment of Vietnamese American participants. Remote assessments were conducted using a customized electronic tablet platform (Claris Companion
®
) via Zoom that allowed consent, cognitive interviews, and medical exams. Saliva samples were collected remotely with prepaid envelopes to mail‐in samples.

Result

Remote assessments were well accepted by participants. This was critical in conducting this study given the technological, safety (during COVID‐19 pandemic), and socio‐economic limitations. Although time consuming on the front‐end, our methods resulted in the successful recruitment of the target sample of 25 participants, with no dropouts. ACAD community advisory board members referred 56% of participants, enrolled study participants referred 40%, and other sources, 4%. Mean age of participants was 73 years (median: 76; range: 60‐91), 52% female, and 100% foreign‐born. Most (80%) were interviewed in Vietnamese. Successful recruitment strategies included: (1) development of culturally/linguistically appropriate recruitment materials, (2) community connected bilingual/bicultural (Vietnamese‐English) research staff, (3) responsiveness to identified physical, technological, and language/cultural recruitment challenges, (4) community partnerships and participant referrals, and (5) appropriate technology/device for remote assessments.

Conclusion

To facilitate successful research recruitment and participation in the ACAD pilot study and AD‐related research in the Vietnamese American community, recruitment methods and strategies require a thorough understanding of the specific linguistic, cultural, access, and historical/experiential challenges experienced in this population.
Amyloid burden is not associated with brain atrophy in the oldest‐old
Authors: Woodworth Davis C. , Faramarzi Sina , Greenia Dana E. , Kawas Claudia H. , Sajjadi S. Ahmad
Published: December 2022

Background

Alzheimer’s disease (AD) is an important contributor to brain atrophy in older individuals. However, in the oldest‐old (≥85 years), where multiple pathologies are common and contribute to brain atrophy, the relationship between AD and brain atrophy may be attenuated. Here we examined associations between amyloid burden and brain volumes in oldest‐old participants and compared this to younger‐old.

Method

We used data from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and The 90+ Study who had both MRI and florbetapir amyloid PET scans. We examined the association between volumes of brain structures (from FreeSurfer‐v7) and amyloid standardized uptake value ratios (SUVr) using multiple linear regressions adjusted for age, sex, and education. We performed two different analyses, with and without adjusting for cognitive status. For ADNI we used the summary cortical region SUVr normalized to composite white‐matter/brainstem/cerebellum reference, and for The 90+ Study we used a precuneus/posterior‐cingulate SUVr normalized to eroded white matter. Oldest‐old (≥85 years) data were obtained from The 90+ Study (N=206) and ADNI (N=178) whereas younger‐old (55 to 85 years) data (N=1134) came exclusively from the ADNI cohort. We display semi‐partial correlations (sr) as measures of effect size, thresholded at Puncorrected<0.05.

Result

Table‐1 summarizes participant characteristics for ADNI and The 90+ Study. In younger‐old participants amyloid was related to atrophy of multiple regions (sr∼‐0.1), but in the oldest‐old the opposite was true, where amyloid was weakly associated with increased volume in some regions for both ADNI and The 90+ Study (Figure‐1). In the model without adjusting for cognitive status, the atrophic effect of amyloid on brain volumes was more pronounced in the younger‐old (sr∼‐0.3), while amyloid remained unrelated to brain atrophy in the oldest‐old (Figure‐2). Lastly, we further illustrate this effect by plotting volumes for two regions, the hippocampus and inferior temporal, against SUVrs for the different groups (Figure‐3).

Conclusion

We found that in the oldest‐old amyloid burden was not related to brain atrophy. This finding underscores the importance of non‐AD pathologies and/or general aging processes compared with AD pathology in the oldest‐old.
Qualification of classical biomarkers for Alzheimer’s Disease in a multiplex format in blood using a new technology
Authors: Vanderstichele Hugo Marcel , Yu Heng , Juang Alice , Davis Pepe , Galasko Douglas R. , Carbonell Luis , Verdooner Steven R , Anderson Leyla
Published: December 2022

Background

Protein biomarker profiling in biological fluids will soon become an established procedure in clinical diagnosis of neurodegenerative disease subtypes. Observed differences between technology platforms in performances can be attributed to technology principles and their development status, selection and characterization of antibody combinations, reproducibility of test results, and pre‐analytical factors and processing of samples. Combination of advantages of emerging technologies, together with availability of precision‐qualified assay formats and innovative sample processing procedures, will create additional possibilities for individual patient management using clinically validated protein biomarker panels.

Method

The Giant Magneto Resistance (GMR) technology platform was used to develop multiplex immunoassays for different biomarker proteoforms in blood (e.g., Aß, (phospho)Tau, NF‐L, and GFAP).

Result

We have developed and optimized performance of multiplex assays using a Design of Experiment (DOE) approach to generate reproducible results. The selectivity and specificity of each antibody combination was confirmed with multiplex assay designs. We have used clinical samples instead of calibrators in buffer to shorten the development time. Process optimization through DOE was done with biotinylated peptides. After optimization, reproducibility was improved by approximately 4‐fold to < 5% CV for each analyte. We have included 3D6 as a capture antibody on the printed circuit boards (PCBs), while analyzing Aß1‐42 & Aß1‐40 using 21F12 and 2G3 as capture antibodies, respectively, to identify the presence of Aß oligomers. PCB selection, printing conditions including environmental factors, buffer selections, and conjugation process were optimized in a stepwise manner while frequently checking biomarker levels in clinical samples. Sample processing is part of our roadmap to generate clinically valuable results. The diagnostic potential for each assay format to identify amyloidopathy in an early phase of the disease will be presented using blood samples from cognitively normal, MCI, and AD subjects, characterized by CSF biomarker profiles and/or amyloid PET status.

Conclusion

The GMR technology allows screening of performance of antibodies in multiplex formats, shortening the assay development time. The biomarker panels and novel methods for analysis are uniquely positioned to help the healthcare community. This study was funded by Alzheimer’s Drug Discovery Foundation's Diagnostics Accelerator (DxA) Program.
Differential associations of amyloid and tau (from PET) with brain volumes (from MRI) by cognitive status
Authors: Woodworth Davis C. , Corrada Maria M. , Kawas Claudia H. , Sajjadi S. Ahmad
Published: December 2022

Background

Alzheimer’s disease pathology (AD) is an important cause of neurodegeneration and brain atrophy. Non‐AD mechanisms can also cause neurodegeneration alone or in conjunction with AD. Harboring combination of AD and non‐AD pathologies leads to greater cognitive impairment and dementia. Here, we examined the hypothesis that the association of amyloid and tau burden from positron emission tomography (PET) with brain volumes from magnetic resonance imaging (MRI) is weaker in those with dementia compared to those with mild cognitive impairment (MCI) or normal cognition.

Method

We used data from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who had either florbetapir amyloid PET (N=1320) of flortaucipir tau PET (N=833, 535 of whom had both). We examined the association between volumes of brain structures (FreeSurfer‐v7) and standardized uptake value ratios (SUVr) for amyloid (summary cortical region, normalized to whole cerebellum) and tau (meta‐temporal region, normalized to inferior cerebellar gray matter) separately, using linear regressions adjusting for age, sex, and education. We report results in overall groups and by cognitive status (normal, MCI, dementia). We display semi‐partial correlations (sr, thresholded at Puncorrected<0.05), as measures of effect size.

Result

Table‐1 summarizes participant characteristics. The effect of amyloid on brain volumes was modest in the overall cohort, with associations strongest for inferior/middle temporal, inferior parietal, entorhinal, hippocampus, and amygdala regions (sr∼‐0.2, P<0.001 all). In those with dementia, however, there were no distinct associations between amyloid and brain atrophy (Figure‐1). For tau, associations in the overall cohort were similarly strongest for inferior/middle temporal, inferior parietal, entorhinal, hippocampus, and amygdala regions (sr∼‐0.3, P<0.001 all). In those with dementia, associations remained strong for inferior/middle temporal regions (sr∼‐0.3, P<0.001) but tau was not associated with hippocampus volumes (left, sr=‐0.05, P=0.6; right, sr=‐0.12, P=0.14, Figure‐2); this divergence is further highlighted in select regions (inferior temporal and hippocampus) in Figure‐3.

Conclusion

We found that the relationship between amyloid and tau burden and atrophy was stronger in the overall cohort than in participants with dementia. This was particularly the case for medial temporal lobe structures. The effect of non‐AD pathologies on medial temporal lobe atrophy is a potential explanation for the observed results.