bluuebunny/crossref_metadata_2025 huggingface dataset:
Lithium protects against ApoE4 mediated calcium dysregulation and mitochondrial dysfunction and cell damage in iPSCs from a sporadic Alzheimer’s disease patient
Authors: Liang Ge , Anchipolovsky Samuel , Zhang Roland , Das Ipsita , Ayala Benjamin , Xu Xandro , Tsai Li‐Huei , Wei Huafeng
Published: December 2023

Background

We hypothesized that lithium inhibits critical upper stream Ca2+ dysregulation via inhibition of methyl‐D‐aspartate (NMDARs) and/or InsP3 (InsP3Rs) receptors and downstream mitochondria dysfunction and cell death in a cell model of sporadic Alzheimer’s Disease (SAD).

Method

Induced pluripotent stem cells (iPSCs) were derived from the skin fibroblasts of a SAD patient with parental ApoE4/E4, and then gene‐edited to isogenic ApoE3/E3 cells as control. Cells were cultured with mTeSR1 plus medium on Matrigel‐coated plates, differentiated to NPC by Dual‐SMAD inhibition. Mitochondrial function and cell viability of both ApoE4/E4 vs. ApoE3/E3 iPSCs were determined using MTT reduction assay. Cells were pretreated with lithium and then challenged with glutamate for 24 hrs. Calcium concentration in cytosol space ([Ca2+]c) was measured using jellyfish‐specific photo protein aequorin‐based probes or microscopy Fura‐2 dye. Mitochondria oxygen consumption rate (OCR) and ATP production were measured using the Seahorse ® Mito Stress Assay.

Result

Compared to ApoE3/E3 cells, ApoE4/E4 cells have significantly decreased cell viability, which could be inhibited by lithium at clinically low concentrations. ApoE4/E4 iPSCs had significantly increased baseline levels of [Ca2+]c and a significantly higher elevation of [Ca2+]c after glutamate treatment than its isogenic ApoE3/E3 iPSCs. Lithium at a clinical concentration (1mM) significantly inhibited the pathological elevation of baseline [Ca2+]c in ApoE4/E4 iPSCs. Lithium‐inhibited mitochondria proton leak as an indicator of cell damage induced by glutamate (15mM) in ApoE4/E4 iPSCs. Glutamate induced mitochondrial and cell damage dose‐dependently. Lithium at a clinically low concentration (0.25mM) significantly inhibited glutamate (15mM)‐induced mitochondria and cell damage in ApoE4/E4 iPSCs. Glutamate treatment for 24 hours significantly inhibited the proliferation of NPCs derived from SAD iPSCs with parental ApoE4/E4 and isogenic E3/E3. Lithium (1mM) significantly inhibited the glutamate‐mediated impairment of ApoE3/E3 NPCs proliferation.

Conclusion

Our results suggest that ApoE4 plays an important role in critical upstream Ca2+ dysregulation and downstream mitochondrial dysfunction and cell damage, particularly under the stress of glutamate excitotoxicity. Lithium at clinically low concentrations ameliorated critical Ca2+ dysregulation and AD pathologies, warranting further studies to repurpose lithium as future effective drug for AD treatment.
The Intra‐ and Inter‐regional Relationship Between Alzheimer’s Disease Neuropathologic Change (ADNC) and Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC)
Authors: Oh Jae Won , Yu Lei , Sperling Reisa A. , Bennett David A. A , Schneider Julie A , Yang Hyun‐Sik
Published: December 2023

Background

Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) is found in over half of pathologically confirmed Alzheimer’s disease (AD) dementia cases. However, the region‐specific relationship between AD neuropathologic change (ADNC) and LATE‐NC remains unclear. Here, we investigated the intraregional and interregional associations between ADNC and LATE‐NC.

Methods

We analyzed multi‐regional postmortem neuropathology data from the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP). Quantitative ADNC burden was assessed with amyloid‐β (Aβ) and tau immunohistochemistry in 8 brain regions. The Aβ burden was averaged across all regions, given strong inter‐regional correlations. Semi‐quantitative LATE‐NC burden was assessed with TDP‐43 immunohistochemistry in 7 brain regions, scored in 6 grades. Hippocampal sclerosis (HS) was defined as a severe neuronal loss in a mid‐hippocampal coronal section, irrespective of ADNC or LATE‐NC burden. We assessed the association between regional LATE‐NC and global Aβ burden, adjusting for APOE ε4, age at death, and sex. Then, we tested the intra‐ and inter‐regional associations between LATE‐NC and tau, adjusting for Aβ, APOE ε4, age at death, and sex. We performed a post‐hoc subgroup analysis in participants without HS.

Results

We analyzed the data from n = 1264 deceased ROSMAP participants (Table 1). Global Aβ was positively associated with LATE‐NC in most regions (Fig.1A). Interestingly, even after accounting for Aβ and APOE ε4, tau and LATE‐NC were positively associated within the entorhinal (t = 7.29, p = 5.4×10−13) and midfrontal cortex (t = 4.33, p = 1.6×10−5) but not within the hippocampus (Fig.1B, bold boxes). Tau and LATE‐NC were positively correlated across most interregional pairs (Fig.1B) except for negative associations between hippocampal tau (CA1/subiculum) and frontal LATE‐NC. There was no association between hippocampal tau and frontal LATE‐NC in the HS(‐) subgroup (n = 1143; inferior frontal, p = 0.67; midfrontal, p = 0.15), suggesting that extensive hippocampal neuronal loss in HS(+) cases could have artifactually driven the negative association between hippocampal tau and frontal LATE‐NC.

Conclusions

Aβ was positively associated with LATE‐NC in most regions. Even after adjusting for Aβ and APOE ε4, tau was positively associated with LATE‐NC across most regions, except for hippocampal tau and frontal LATE‐NC. Further studies are required to determine the underlying mechanisms linking ADNC and LATE‐NC.
NINDS funding opportunities for Alzheimer’s Disease‐Related Dementia therapy development
Authors: Roof Rebecca , Mcgavern Linda , Boshoff Chris , Lavaute Timothy , Cywin Charles , Thomas Shruthi , McCartney Amber J , Corriveau Roderick A
Published: December 2023

Background

Goal 1 of the National Plan to Address Alzheimer’s Disease (AD) is to prevent and effectively treat AD and AD‐related dementias (ADRD) by 2025. Toward this goal, NINDS plans 14 ADRD funding opportunities for 2024 to support training, basic mechanisms, translational, and clinical research for ADRD. Here, we describe ADRD translational therapy development initiatives, which include 1) multi‐target validation, 2) early‐stage therapy development, 3) genome editing and 4) animal model development and validation. Note, ADRD specific funding opportunities are not required. ADRD researchers can also take advantage of NINDS existing programs such as the NIH Blueprint for Neurotherapeutics (BPN) for Small Molecule or Biologic therapy development. These programs support optimization, manufacture, IND‐enabling studies and first in human clinical trials through a combination of grants and complementary access to NIH‐provided CROs and consultants.

Method

All concepts discussed here are approved, however NIH cannot guarantee future funding opportunities, award mechanisms, or funding allocation. A funding opportunity is only official when published in the NIH Guide.

Result

Multi‐Target Validation for ADRD concept has the goal to support research that would validate multiple targets for future therapy development that better reflect the complexity of disease.

Early‐Stage Therapy Development concept would support the development of small molecule or biologic therapeutics and would be a reissue of RFA‐NS‐22‐059, which supported assay development, therapeutic screening, optimization, and in vivo efficacy work in preparation for later‐stage programs.

Genome Editing for ADRD concept would support early translational research focused on somatic cell gene editing with the expectation that studies will address feasibility of the gene editing approach and would be a reissue of RFA‐NS‐23‐017.

PAR‐23‐154 “Development and Validation of Models for Alzheimer’s Disease‐Related Dementias (ADRD)” supports the development and validation of clinically‐ and pathophysiologically‐relevant models of ADRD that can be used for future therapy development. Models should reflect multiple aspects of the human condition and include internal, face, construct, and predictive validation to the extent possible.

Conclusion

Through these initiatives, NINDS hopes to provide a comprehensive pipeline for ADRD therapy development from target validation to the clinic.
Within‐network Functional Connectivity of Intrinsic Networks in SuperAgers
Authors: Diamond Bram Ryder , Martersteck Adam , Sridhar Jaiashre , Wood Jessica , Gill Nathan Pruneau , Weintraub Sandra , Mesulam Marsel , Rogalski Emily J
Published: December 2023

Background

Memory decline in late life is a hallmark of aging, yet SuperAgers are individuals age 80 or older with episodic memory performance at least as good as cognitively average 50‐to‐60‐year‐olds. Neuroimaging analyses have found SuperAgers to have thicker cortices and slower atrophy rates compared to similarly aged controls (Controls). This project extended the anatomical findings by examining the functional integrity of seven intrinsic networks spanning the entire cortex and two memory‐specific systems identified from task‐based and resting state studies.

Methods

Within‐network functional connectivity (FC) of seven large‐scale networks and two memory systems were compared between 25 SuperAgers and 16 Controls using resting state functional MRI (rs‐fMRI) and T1‐weighted structural imaging from a single visit. Classification of SuperAgers/Controls was determined based on measures of episodic memory, executive functioning, verbal fluency, and picture naming (Harrison et al., 2012). Inclusion criteria required stable cognitive status across two visits. In the first analysis, we included all seven networks from a common resting‐state atlas (Schaefer et al., 2018). Within‐network FCs for all networks were defined as the average FCs between all within‐network regions (Figure 1A). In the second analysis, we investigated two memory‐specific networks: the anterior temporal (AT) and posterior medial (PM) systems. AT and PM cortical maps (Figure 1B) were identified from prior research (de Flores et al., 2022). Within‐network FC of the AT and PM systems were defined as the FC between AT‐to‐anterior‐hippocampus and PM‐to‐posterior‐hippocampus, respectively. For both analyses, FCs were compared across groups using two‐sample independent t‐tests and corrected for multiple comparisons (Benjamini‐Hochberg false discovery rate).

Results

We found no significant between‐group differences in demographic characteristics including age, sex, and education. Performance on neuropsychological measures was significantly different for episodic memory, verbal fluency, and picture naming. Group differences in within‐network FCs for large‐scale networks and memory systems were nonsignificant.

Conclusion

At the group‐level, within‐network FC of large‐scale networks and memory‐specific systems were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Person‐specific functional connectome approaches may be important for understanding network organizational features of SuperAgers.
Selective vulnerability of subcortical nuclei in atypical Alzheimer’s Disease
Authors: Craig Miranda C , Grinberg Lea T. , Ehrenberg Alexander J. , Li Song Hua , Seeley William W. , Satpati Abhijit ,   Memory and Aging Center
Published: December 2023

Background

Recent evidence suggests that sleep‐wake dysregulation in Alzheimer’s disease (AD) is an early event and parallels the tau accumulation in the arousal system spefically noted in the locus coeruleus (LC) as well as other subcortical nuclei as the Pedunculopontine Tegmental Nucleus (PPTg), Laterodorsal Tegmental Nucleus (LDTg), and the Dorsal Raphe (DR). We have previously demonstrated that the pattern of sleep‐wake dysfunction is different among AD clinical variants. This existence of specific sleep‐wake profiles suggest differential degeneration patterns of the arousal system within differing AD presentations. This study continues this investigation at the cellular/molecular level to uncover the selective vulnerability of subcortical structures to AD specific tau accumulation. That remains elusive to‐date.

Method

Human postmortem brainstem samples were sourced from the Neurodegenerative Disease Brain Bank (NDBB) at UCSF. 24 subjects were selected based on primary diagnosis, including 6 amnestic AD, 17 non‐amnestic AD (5 EOAD, 3 PCA, 5 lvPPA, 4 CBS) and 1 control. Paraffin blocks containing the areas of interest were cut into 8‐lm‐thick sections that underwent double‐labeled immunohistochemistry (IHC) and brightfield imaging. The images were then overlayed to created mutlidimentaional maps and neurons were classified in 4 subgroups: (1) positive for the neurotransmitter of interest (NEU‐positive), (2) bearing hyperphosphorylated tau neuronal cytoplasmic inclusions (tau‐positive), (3) positive for the neurotransmitter of interest and bearing tau‐positive (NEU‐positive/tau‐positive colocalized neurons), and (4) negative for NEU and tau.

Result

In the LC, lvPPA had the highest had the highest percentage of tau postive neurons (40%), followed by amnestic AD (31.1%), PCA (29.3%), EOAD (27.1%), and finally CBS (24.3%). EOAD had the highest percentage of colocalized neurons (34.7%) as well as LOAD (31%) compared to PCA (0.02%), lvPPA (0.18%), CBS (0.09%).

Conclusion

Multidimensional quantitative analysis suggests differences in vulnerabliblity of sleep‐wake subcortical nuclei to AD, EOAD, PCA, lvPPA, and CBS. For instance the neuronal loss in EOAD was so extreme in the LC that few neurons remained to develop aggregates whereas in PCA, CBS, and lvPPA the high percentage of tau accumulation presents a neuropathological framework underlying atypical clinical manifestations and possible insight into therapeutic targets.
Reorganization of functional brain networks in healthy aging and mild cognitive impairment during the visual motion discrimination task
Authors: Požar Rok , Giordani Bruno , Kavcic Voyko
Published: December 2023

Background

Previously, we reported that there was significant decrease in spectral power for eyes‐closed resting state EEG (rsEEG) immediately following a visual motion discrimination task as compared to before task engagement in older adults – the so‐called Task Aftereffect (TA). Further, we have also shown that rsEEG TA differentiated between older adults with mild cognitive impairment (MCI) and healthy controls (HC), with the MCI participants showing more integrated topology in post‐ as compared to pre‐cognitive task rsEEG. We now report EEG topological changes during task performance with regards to: changes in functional network organization from the beginning to the end of the task and evidence for significant differences in topology between MCI patients and HC.

Method

We studied a sample of community dwelling African American older participants over age 60 years, with consensus‐based diagnosis for 51 HC and 39 MCI. EEG epochs extracted for analysis were two‐second epochs before the motion onset of each stimulus at the beginning, middle, and end of the full task. Functional connectivity between channels was assessed by the phase lag index. Minimum spanning tree (MST) was used to characterize network topology.

Result

Time effect was confirmed, as network organization in all participants significantly improved with task progression. On average, brain topology became more integrated with higher leaf fraction and smaller average eccentricity. Moreover, our results show differences between groups in MST parameters over the whole task. Most differences were observed at the earliest timepoint at lower frequency range (theta and lower alpha) where average eccentricity was significantly decreased. Leaf fraction and maximal betweenness centrality were significantly increased in the MCI group as compared to HC.

Conclusion

The change in network organization suggests that MCI require greater network integration across brain areas before repeated motion onset presentations. This could reflect compensatory brain mechanisms, especially as both groups did not show significant differences in task performance. These findings enhance our understanding of the functional brain network organization immediately prior to repeated responses in a visual perceptual task in MCI compared to HC. This emphasizes the potential for using graph‐theoretic measures as a valid tool for the early detection of cognitive impairment.
Mood disturbance and tau pathology in older women at risk for Alzheimer’s disease
Authors: Dratva Melanie A , Wang Xin , Lui Kitty K , Heyworth Nadine , Sundermann Erin E. , Banks Sarah J
Published: December 2023

Background

Neuropsychiatric symptoms, particularly depression, have been associated with Alzheimer’s disease (AD) biomarkers in individuals on the AD continuum. Although mood changes are a clinical manifestation of AD, research examining how the spectrum of common mood symptoms relates to AD biomarkers is limited. We examined the association between mood disturbance and tau pathology measured with positron emission tomography (PET) in older women at risk for AD and particular mood domains driving any associations.

Method

Participants included 18 women (Mage = 71.5, SDage = 3.3 years) with higher AD genetic risk (polygenetic hazard score ≥50th percentile) and mild impairment on the Montreal Cognitive Assessment who had completed the Profile of Mood States (POMS) questionnaire and a PET Scan as part of a larger research study. Those with formal psychiatric or neurodegenerative diagnoses were excluded. The POMS assessed six mood subcategories. The Total Mood Disturbance (TMD) was calculated as the sum of Tension, Depression, Anger, Fatigue, and Confusion subscores, minus the Vigor subscore. Tau standardized uptake value ratio (SUVR) were calculated for each Braak region of interest (ROI) (i.e., Braak 1‐2: transentorhinal stage, Braak 3‐4: limbic stage, and Braak 5‐6: isocortical stage). Linear regression models were conducted with TMD as the predictor and each Braak‐derived ROI as the outcome while controlling for age. Significant relationships were further probed by repeating analyses with each POMS subcategory as the predictor.

Result

Higher POMS TMD scores significantly predicted higher tau‐PET SUVRs in Braak 1‐2 (β = 0.73, p<0.01), Braak 3‐4 (β = 0.88, p<0.001), and Braak 5‐6 (β = 0.72, p<0.01) (Figure 1). Further analysis showed that the Tension subscore significantly predicted tau‐PET in all three regions (Figure 2) and Confusion significantly predicted tau‐PET in Braak 1‐2 and Braak 5‐6 (Figure 3).

Conclusion

Mood disturbance was consistently associated with higher tau across all Braak regions in older women with higher AD risk. These relationships were strongest when reflecting the combination of mood symptoms, but tension may have a stronger influence than other subcategories. Longitudinal research should be done to assess the directionality of this relationship and to explore whether treatments for mood symptoms may have protective effects on Alzheimer’s pathogenesis before diagnosis.
Exploring brain‐derived exosomal miRNA as a novel blood‐based biomarker for Alzheimer’s disease
Authors: Jiang Yanfeng , Li Jincheng , Sun Jian , Wang Yingzhe , Li Jialin , Cui Mei
Published: December 2023

Background

Biomarkers of Alzheimer’s disease (AD) currently rely on invasive and time‐consuming methods such as cerebrospinal fluid analysis and neuroimaging. Non‐invasive blood‐based biomarkers are needed for early diagnosis and risk prediction. Brain‐derived exosomes are promising candidates for blood biomarkers, as they can cross the blood‐brain barrier and enter the bloodstream, and exosomal miRNAs could serve as potential biomarkers for identifying patients with AD and screening individuals at high risk. Here, we conducted a hospital‐based case‐control study to investigate exosomal miRNAs as biomarkers for AD.

Method

Exosomes were isolated from plasma samples of AD patients (n = 18) and healthy controls (HC; n = 18), and exosomal miRNAs were analyzed using high‐throughput sequencing. AD‐differentially expressed miRNAs were identified and their associations with Mini‐Mental State Examination (MMSE) and amyloid positron emission tomography with standardized uptake value ratio (PET‐SUVR) were evaluated by Spearman’s correlation analyses. Logistic regression was used to select miRNA biomarkers and construct a classifier to discriminate AD from HC.

Result

We identified 65 miRNAs (47 downregulated and 18 upregulated) that were differentially expressed in AD, and 20 of which were significantly associated with both MMSE and PET‐SUVR (all false discovery rate adjusted P <0.05) (Figure 1). We selected hsa‐miR‐33a‐5p and hsa‐miR‐342‐3p as potential biomarkers to identify AD from HC, with an area under the curve (AUC) reaching 100% in the internal validation, whereas a model consisting of gender, age, and apolipoprotein E ε4 only had an AUC of 0.63. Both miRNAs were significantly correlated with MMSE and PET‐SUVR after adjusting age and sex. The miRNA target analysis revealed that the target genes of hsa‐miR‐33a‐5p and hsa‐miR‐342‐3p were involved in multiple processes related to the nervous system, including axon guidance, neurotransmitter receptors and postsynaptic signal transmission, and dopaminergic synapse, among others (Figure 2).

Conclusion

Our results suggest that differentially expressed miRNAs are significantly correlated with the pathological process of AD and cognitive function, and that blood exosomal miRNAs have the potential to detect AD with high sensitivity and specificity. These findings may provide a basis for the development of non‐invasive blood‐based biomarkers for AD diagnosis and risk prediction.
Higher pupillary dilation during phasic transcutaneous vagus nerve stimulation (taVNS) and its relevance to the noradrenergic system of the locus coeruleus (LC‐NE)
Authors: Ludwig Mareike , Düzel Emrah , Betts Matthew , Hämmerer Dorothea
Published: December 2023

Background

Transcutaneous auricular vagus nerve stimulation (taVNS) may affect the locus coeruleus‐norepinephrine system (LC‐NE system) via modulation of the vagus nerve. The LC is our main source of NE in the brainstem and declines with age and is a potential epicentre of tau pathology in Alzheimer´s diseases (AD). Besides the excessive NE release leading to the formation of amyloid plaques, the severity and duration of AD are also related to LC cell death, decreased cortical NE levels, and accelerated tau spread. An increase in NE release in the LC accompanied by reduced inflammatory markers was achieved in animal models using phasic invasive (i)VNS. In humans, phasic taVNS leads to an increase in pupil dilation, which can serve as a proxy for LC activation. Therefore, taVNS may have the potential to increase NE release and thereby impact LC function and related links to tau pathology.

Method

Twenty‐four subjects (50% women; 22.96 +/‐ 2.24 years) received time‐synchronous phasic taVNS during a fixation task (∼ 18min) while recording pupillary dilation changes, which allowed systematic testing of phasic taVNS (3 sec) with low (3 mA) and high (5 mA) intensities and low (10 Hz) and high (25 Hz) frequencies at constant pulse width (250 µs).

Result

During on stimulation pupil dilation was higher during real (0.18±0.03) as compared to sham (0.09±0.03) stimulation (χ2 = 10.29, p = 0.001) (see Fig. 1). Likewise higher (0.21±0.03) compared to lower (0.06±0.03) intensity (χ2 = 23.02, p < 0.001) led to higher pupil dilation, while there was no significant difference between higher (0.13±0.03) and lower (0.14±0.03) frequencies (χ2 = 0.11, p = 0.74).

Conclusion

Systematic testing of different frequencies and intensities, while keeping the pulse width constant, showed that phasic real taVNS and higher intensity lead to higher pupillary dilation, which is consistent with animal and human studies. Furthermore, the results suggest that the influence of intensity on pupil dilation might be stronger than that of frequency. The increased pupillary dilation during phasic taVNS could be an indication of LC involvement, however, more detailed studies e.g., functional magnetic resonance imaging (fMRI) during taVNS are needed to confirm this association.
Bridging the Gap: The Global CEOi Collaborative Workgroup for Adoption of Alzheimer’s disease Blood‐Based Biomarkers in Clinical Practice
Authors: Udeh‐Momoh Chi T. , Mielke Michelle M. , Schindler Suzanne E. , Hansson Oskar , Khachaturian Ara S , Weiss Joan
Published: December 2023

Background

The United States healthcare system is not prepared for disease modifying therapies (DMTs) of Alzheimer’s disease (AD). Eligibility for DMTs will be contingent on confirmation of AD pathology using biomarkers. Major difficulties are expected in providing PET and CSF testing in the population. Blood‐based biomarkers (BBMs) could greatly reduce the burden of biomarker testing by triaging patients for subsequent confirmation of AD brain pathology in specialty and primary care. The Global CEO Initiative on Alzheimer’s Disease (CEOi) has convened a Workgroup (WG) to develop guidelines and recommendations for the widespread adoption of BBMs in clinical practice to support feasible, timely, and accurate AD dementia diagnosis among symptomatic patients.

Method

Over 80 stakeholders spanning academia, healthcare, advocacy, industry, non‐profit, and venture capital have joined the Workgroup, ensuring a wide range of expertise. The Workgroup consists of three active workstreams. Workstream A has defined use cases for symptomatic patients and minimum viable test specifications; Workstream B will provide recommendations on implementing BBMs in clinical practice; and Workstream C serves to educate practicing clinicians on outputs garnered from Workstreams A and B. Jointly led by 2 CEOi‐nominated experts, each Workstream has a core team, consisting of 6‐8 experts, and meet on a weekly basis to drive the WG objectives. General Workstream meetings are held periodically for the core team to present plans and outputs for full group input and feedback.

Result

Workgroup members have conceptualized the clinical care pathway for operationalizing BBM across specialty and primary care settings; and will present a feasible framework for real‐world implementation of BBMs. We have defined appropriate‐use criteria for BBMs in clinical settings, including test specifications, and will provide actionable recommendations to accelerate adoption in clinical care, while critically considering implementation challenges such as test result interpretation, and value to existing diagnostic pathway. Strategies to facilitate optimal implementation including novel educational tools will be disseminated.

Conclusion

The Workgroup seeks rapid, efficient and effective utility of BBMs in clinical practice that is scientifically valid, and patient focused. Successful adoption will facilitate effectual triaging of patients for comprehensive diagnostic evaluations, streamlining patient access to appropriate and integrated care.
Employing transfer learning to optimize deep learning models for Alzheimer’s disease classification using two tau PET tracers
Authors: Bauer‐Negrini Guilherme , Povala Guilherme , Lucchese Luisa Vieira , Lussier Firoza Z , Bellaver Bruna , Ferreira Pamela C.L. , Aguzzoli Cristiano Schaffer , Soares Carolina , Zalzale Hussein , Rohden Francieli , Abbas Sarah , Ferrari‐Souza João Pedro , Leffa Douglas Teixeira , Lemaire Peter Charles , Cabrera Arlec , Tissot Cécile , Therriault Joseph , Bezgin Gleb , Servaes Stijn , Stevenson Jenna , Rahmouni Nesrine , Gauthier Serge , Karikari Thomas K , Zatt Bruno , Rosa‐Neto Pedro , Pascoal Tharick A.
Published: December 2023

Background

Deep learning models, particularly convolutional neural networks (CNNs), have shown promise in Alzheimer’s disease (AD) classification using tau PET data. However, limited sample sizes and unharmonized tau tracers present challenges to developing an agnostic tau tracer tool to predict AD using machine learning. Transfer learning, which leverages pre‐trained models for related tasks, may address these issues. Here we evaluate the effectiveness of transfer learning in optimizing 3D CNNs for AD classification with distinct cohorts and tau tracers.

Method

We used tau PET images from ADNI ([18F]Flortaucipir, n = 437) and TRIAD ([18F]MK‐6240, n = 423) cohorts, categorizing patients into CU (cognitively unimpaired) and CI (cognitively impaired). Standardized uptake value ratios (SUVR) were used for tau PET data. Separate 3D CNNs were trained for each tracer, with SUVR volumes as input and diagnosis as output. For transfer learning, we trained a model on [18F]Flortaucipir data with a reduced learning rate, using a pre‐trained model from [18F]MK‐6240. Models underwent 5‐fold cross‐validation, and metrics were computed as the average of validation metrics across folds. To avoid data leakage, images from the same subject were assigned to the same fold.

Result

The model trained on [18F]MK‐6240 tracer demonstrated higher classification performance than [18F]Flortaucipir (AUC = 0.84 vs 0.67; Figure 1. F1‐score = 79.77% vs 64.66%; Table 1). To enhance the classification performance of [18F]Flortaucipir model, we employed a transfer learning approach by leveraging the model pre‐trained with [18F]MK‐6240. With this approach, we observed a slight improvement in all classification metrics compared to the model trained solely on [18F]Flortaucipir data (AUC = 0.71 vs 0.67; Figure 1. Accuracy = 71.39% vs 67.72, F1‐score = 67.97% vs 64.66%; Table 1).

Conclusion

This finding highlights the value of transfer learning in optimizing deep learning models for Alzheimer’s disease classification, particularly when handling tau tracers with varying performance levels. Our results are consistent with previous on transfer learning’s effectiveness in this context. These preliminary findings indicate that applying this technique to larger datasets of tau tracers may further enhance model performance, potentially leading to the development of a tau tracer‐agnostic tool that overcomes the need of tracer harmonization for predicting dementia.
Gene‐level Association Study of Alzheimer’s Disease on CHS and FRAM cohorts
Authors: Zhbannikov Ilya , Ukraintseva Svetlana , Wu Deqing , Bagley Olivia , Duan Hongzhe , Holmes Rachel , Yashin Anatoliy I
Published: December 2023

Background

Experimental, clinical, and genetic epidemiological studies continue clarifying important aspects of Alzheimer’s disease (AD) pathological development. Despite this progress the genetic mechanisms of AD regulation remain unclear. One problem that may contribute to slowing further progress in better understanding of these mechanisms deals with difficulties in replication of the results of genetic association studies. To overcome this problem the idea of using a gene‐based analysis in which all common variation within a candidate gene is considered jointly has been suggested. In this paper we investigate to what extent the use of gene‐based analyses resolves the non‐replication problem.

Method

We performed gene‐level and meta‐analysis association studies for two cohorts: Cardiovascular Heart Study (CHS) and Framingham (FRAM) using Alzheimer’s disease as a primary outcome. To support our findings, we also performed meta‐analysis following gene‐enrichment study for both cohorts. Analysis was performed separately for males and females and for both sexes. Additional covariates were age, smoking. Gene‐level analysis was performed with fastBAT and enrichment analysis with ClusterProfiler on KEGG database.

Result

Our analysis identified a list of highly significant genes, such as TOMM40, APOC1 (all with FDR‐adjusted p‐value < 0.05) and pathways, such as Cholesterol metabolism, Fluid shear stress and atherosclerosis, Proteoglycans in cancer, Lipid and atherosclerosis showed statistically significant associations (FDR‐adjusted p‐value < 0.05) in both datasets and sexes.

Meta‐analysis revealed TOMM40 (p‐value = 2.35E‐16), APOC1 (p‐value 4.46E‐13), ENSG00000259648 (p‐value = 8.88E‐06), PEX7 (p‐value = 4.40E‐05), ENSG00000287274 (p‐value = 5.38E‐05) genes for men and women combined; men exclusively revealed ENSG00000259648, TOMM40, and APOC1 (p‐value<1.75E‐05) and women TOMM40 and APOC1 (p‐value<6E‐08).

Gene‐enrichment meta‐analysis revealed NOD‐like receptor signaling pathway (adjusted p‐value 3.23E‐07), Lipid and atherosclerosis (p‐value = 5.93E‐05), Yersinia (p‐value = 1.17E‐04) for men and women combined; for men only the pathways are Lipid and atherosclerosis (p‐value = 3.61E‐03), TGF‐beta signaling pathway (p‐value = 3.61E‐03), AGE‐RAGE signaling pathway in diabetic complications (p‐value = 5.18E‐03); and for women Cholesterol metabolism (p‐value = 3.49E‐07), Fatty acid degradation (p‐value = 1.04E‐06), PPAR signaling pathway (p‐value = 1.23E‐05).

Conclusion

In this work we were able to identify statistically significant genes and pathways showed replication across the studies and are potentially useful for uncovering genetic mechanisms of AD. However, other things such as genetic heterogeneity may influence disease developing and needed further exploration.
A Machine Learning Approach to Identify Individualized Baseline MRI, Plasma, Cardiovascular and Lifestyle Predictors of a 5‐Year Cognitive Decline
Authors: Gebre Robel K , Ramanan Vijay K , Raghavan Sheelakumari , Hofrenning Ekaterina I. , Przybelski Scott A. , Lesnick Timothy G. , Knopman David S. , Machulda Mary M. , Vassilaki Maria , Petersen Ronald C. , Jack Clifford R. , Graff‐Radford Jonathan , Vemuri Prashanthi
Published: December 2023

Background

The mapping between risk factors and biomarkers with cognitive performance and decline in the older adults is complex and varies significantly across different age and sex groups. Our goals were to (i) develop a machine learning (ML) model to predict baseline cognition and cognitive decline over a 5‐year follow‐up using only baseline assessments, and (ii) identify important modifiable and non‐modifiable predictors of cognitive decline across different age strata.

Method

We utilized longitudinal data from 2219 participants (mean age (SD): 70 (12) years, 49% male) from Mayo Clinic Study of Aging who had 43 features belonging to cardiovascular health, plasma, MRI (diffusion and structural), and lifestyle measures. Cognition was measured using a global cognition z‐score. We built ML models to predict baseline cognition and rate of cognitive decline over 5‐years (linear regression slopes over all individual followup measurements for each participant) using baseline assessments as inputs. We then built a model for each category separately and as a pooled model with all measures included, incorporating education and sex as demographic features in all models (Fig. 1). We applied a multi‐layer stack ensemble ML technique that utilized repeated k‐fold bagging to maximize accuracy. Importance of the top predictors were assessed in three age strata (55‐65 years (31%), 65‐80 years (46%), 80‐95 years (23%)).

Result

The pooled model explained the largest variance for prediction of baseline cognition and cognitive decline (Fig. 2). In individuals ≤80 years, lower NfL was most predictive of higher baseline cognition. A combination of imaging and plasma features predicted the 5‐year cognitive decline. Additionally, in individuals ≤65 years, diabetes and hypertension were important predictors of faster cognitive decline and in those >80, lower BMI and midlife physical/cognitive activity was an important predictor of faster cognitive decline (Fig. 3).

Conclusion

The plasma model was best for baseline cognition prediction and imaging model was best for cognitive decline prediction. There was significant heterogeneity in important features across the age strata. In individuals >65 years, plasma GFAP was the most important predictor of cognitive decline. Our model allowed identification of key risk factors that predicted cognitive decline.
24‐hour Activity Rhythms, Sleep, and Amyloid Pathology in the population‐based Rotterdam Study
Authors: Ho Phuong Thuy Nguyen , Hoepel Sanne J.W. , Luik Annemarie I. , Vernooij Meike W , Neitzel Julia
Published: December 2023

Background

Previous research found associations between activity rhythms, sleep, and amyloid pathology (Winer et.al, JAMA Neurology, 2021; Leng et.al, Lancet Neurology, 2019). Shorter self‐reported sleep duration and more napping were robust predictors in the amyloid prediction model we recently developed (A4 Study, n = 4,119) and validated (Rotterdam Study, n = 500). Studies with more population‐representative samples, longer follow‐up time and objective activity/sleep measures are needed to understand whether disturbances of the activity rhythm and sleep increase the risk of developing amyloid pathology.

Method

Nondemented participants (n = 319) from the prospective, population‐based Rotterdam Study (mean age 69.2±5.3, 47.0% women) were asked to wear an actigraph watch for 7 days before undergoing amyloid 18F‐florbetaben PET on average 7.8 years [range 4‐16] later (Fig.1). 24‐hour activity rhythms (intradaily stability and variability, L5 start time) and sleep (sleep efficiency, sleep onset latency, total sleep time, and wake after sleep onset) were associated with continuous PET readouts (log‐transformed SUVr values) using linear regression models, adjusted for age, sex, education, APOE4 risk allele count, time between actigraphy and PET assessment, difference in type of actigraphy watches, employment status, depressive symptoms, and vascular risk factors (BMI, diabetes, hypertension, physical activity, smoking).

Result

Higher intradaily variability, i.e. a more fragmented activity rhythm, was associated with higher amyloid‐PET SUVr (b(SE) = 0.149(0.055), pFDR = 0.049). This association was significantly stronger in APOE4 carriers than non‐carriers (interaction: pFDR = 0.014, Fig.2). Our results remained after excluding participants who probably were already on the AD pathway (excluded lowest 10% of hippocampal volume and highest 10% atrophy on two consecutive MRIs) at the time of measuring activity rhythms. This may suggest that a fragmented activity rhythm is a risk factor rather than a result of amyloid pathology. There were no significant associations of other 24‐hour activity rhythm and sleep variables with amyloid.

Conclusion

Higher fragmentation of the 24‐hour activity rhythm was associated with more cerebral amyloid pathology eight years later, even after accounting for potential reverse causality. Since activity disturbances are potentially modifiable, early risk factors of AD, further research should be conducted to examine the preventative effect on the development of AD neuropathology.
Targeted metabolomics reveals progression of early Alzheimer’s disease in TgF344 transgenic rats
Authors: Yin Chunyuan
Published: December 2023

Background

Alzheimer’s disease (AD) is an aging‐related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Current AD diagnosis methods can only identify patients in the advanced stage of the disease, that means when the dementia is already present. This highlights the need for new approaches for the diagnosis of AD at earlier stages, especially before the symptoms appear. In addition, AD is reported to be closely linked with abnormal lipid metabolism. The objective of this study is to identify blood‐based lipid biomarkers to gain a more comprehensive understanding of what causes AD and its subsequent development.

Method

A longitudinal study with 4 different ages (12 weeks, 25 weeks, 50 weeks, and 85 weeks) was conducted in TgF344 transgenic (AD) and wild‐type (WT) rats. Metabolomics profiling of EDTA plasma yielded 811 metabolites after quality control. Metabolites profiled included medium and apolar lipids covering 27 lipid classes, signaling lipids including oxylipins, isoprostanes, eicosanoids, bile acids, endocannabinoids. All data was log2 transformed. All statistical analysis and visualizations were performed in R.

Result

The sphingomyelins (SM) were decreased at 25 weeks with AD having more SM expressed than the WT group, while this was reversed at 50 weeks. In 12 weeks, the volcano plot of AD/WT showed more significant lipids on female (p<0.05:15) than male (p<0.05:2). Whereas, in 25 weeks, male (p<0.05:56) showed more significant lipids than female (p<0.05:7). The ratios of an eicosanoid to its seven products were first decreased, then increased over time in both WT and AD group. However, the WT group reached its minimum at 50 weeks, while the AD group reached its minimum at 25 weeks. Sex differences were found in AD/WT among all ages.

Conclusion

Lipidomics data on longitudinal course of potential lipid biomarkers in plasma of WT and AD rats show some effects of AD and/or aging. It is anticipated that this information will contribute to developing lipid biomarker fingerprints for diagnosis and monitoring AD progression distinct from normal aging.
mTOR signaling regulates microglia metabolism and survival via 4E‐BP‐controlled mRNA translation
Authors: Bermudez Sara L , Choi Junghyun , Kim Sunghoon , Mahmood Niaz , Healy Luke M , Sonenberg Nahum
Published: December 2023

Background

Rare loss‐of‐function variants in TREM2 (Triggering Receptor Expressed in Myeloid cells 2) are associated with an increased risk of AD. There are ongoing efforts to therapeutically boost microglial neuroprotective functions by targeting TREM2. However, the intracellular mechanisms underlying these functions in AD are not fully understood. TREM2 signaling maintains metabolic fitness through activation of the mechanistic target of rapamycin (mTOR) allowing microglia to sustain their metabolism during amyloidosis (Ulland et al., 2017). Detrimental decreases in microglial mTOR signalling during amyloidosis independent of TREM2 loss‐of‐function has also been reported (Baik et al., 2019).

The mTOR pathway acts upstream of the eukaryotic mRNA translation by suppressing the translation repressor, eukaryotic translation initiation factor 4E (eIF4E)‐binding proteins (4E‐BPs). mTOR inhibits the 4E‐BPs via phosphorylation, thereby releasing eIF4E and allowing mRNA translation to initiate (Hay and Sonenberg, 2004). Work from our group demonstrated that mTOR boosts mitochondrial metabolism through 4E‐BP‐controlled mRNA translation (Morita et al., 2013). Therefore, we aimed to understand the dysregulated mechanisms at the intersection of mTOR‐controlled mRNA translation and metabolism in microglia response to Amyloid‐β (Aß).

Method

We used immunoblotting to investigate the effect on 4E‐BP phosphorylation following chronic exposure to Aß aggregates and TREM2 signaling inhibition in a microglia cell line. We manipulated the mTOR pathway by knocking out the downstream effectors, 4E‐BPs, to promote the translation of 4E‐BP‐controlled mRNAs in microglia in vitro and in vivo. We crossed the microglia‐specific 4E‐BPs knock out mouse with a RiboTag mouse to pull‐down ribosome‐bound mRNAs, providing a genome‐wide pool of actively translating mRNAs (the translatome) in the absence of 4E‐BPs in microglia.

Result

We showed that 4E‐BP‐controlled mRNA translation is inhibited upon chronic exposure to Aß or TREM2 signaling inhibition. The deletion of 4E‐BPs in microglia in‐vitro leads to a decrease in expression of pro‐inflammatory mediators and microglia cell death, and an increase in reliance on oxidative phosphorylation upon exposure to Aß. We also observed that 4E‐BP deletion changes the microglia translatome and decreases expression of inflammatory mediators in vivo after an intracranial Aß infusion.

Conclusion

We conclude that mTOR signaling exerts key effects on microglia function and metabolism through 4E‐BP‐controlled mRNA translation.
Head‐to‐head comparison of CSF AD biomarker assays: fully‐automated high‐throughput platforms (ECLIA and CLEIA) vs ELISA
Authors: Günzel Désirée , Güngör Cansu , Goldhardt Oliver , Sommer Patrick , Förstl Hans , Hedderich Dennis , Yakushev Igor , Bruegger Dirk , Grimmer Timo
Published: December 2023

Background

Biomarkers in cerebrospinal fluid (CSF) can help to diagnose Alzheimer’s disease (AD) and classify patients according to the amyloid/tau/neurodegeneration (ATN) research framework.

Method

We directly compared the performance of three different testing systems, i..e. traditional solid‐phase sandwich ELISA assays (Innotest®, Fujirebio Europe N.V., Gent, Belgium, and IBL, Minneapolis, USA), a fully automated electrochemiluminescence immunoassays (ECLIA) platform (Elecsys® CSF assays measured on the cobas e 411 analyzer, Roche Diagnostics International Ltd, Rotkreuz, Switzerland), and a fully automated chemiluminescent enzyme immunoassays (CLEIA) platform (Lumipulse® G600II, Fujirebio Europe N.V., Gent, Belgium), in 50 early AD patients (64±8.1y) and 25 cognitively unimpaired (CU) controls (65±9.4y)] from the same cohort. Individual CSF biomarkers Aβ42, Aβ40, pTau181 and tTau were measured using all systems. Ratios for pTau181/Aβ42, tTau/Aβ42, Aβ42/Aβ40, pTau181/Aβ42/Aβ40, tTau/Aβ42/Aβ40, pTau181/Aβ40, and tTau/Aβ40 were calculated.

Result

Across all systems, biomarkers and their ratios accurately distinguished AD patients from CU in a comparable manner: ROC: AUCs >0.96 (upper bound of CI:1.0)], except for ELISA Aβ42/Aβ40 [AUC = 0.948 (CI: 0.901‐0.995)]; according to Youden Index (YI)‐derived optimal cut‐offs, sensitivity and specificity were comparably high. YI cut‐offs and manufacturer (MA) cut‐offs were highly consistent. However, for the ECLIA platform (Elecsys®), the YI cut‐off led to significantly higher sensitivity for tTau (97.8% [0.88‐1.00%]/ 80.9%) and pTau181 (97.8% [0.88‐1.00%]/ 83.0%), and higher specificity for Aβ42 (96.0% [79‐100%]/ 76.0%), than MA cut‐off, maybe due to high prevalence of AD. The two fully automated platforms showed markedly reduced maximal coefficients of variation (CV) than ELISA.

Conclusion

In addition to increased time efficiency, fully automated platforms showed more consistent results than ELISA assays which favor single analyte measurements. Improved accuracy using YI cut‐offs suggests that in‐house cut‐offs might be important for optimal performance. The two fully automated platforms had comparable accuracy. Thus, the platform of choice might depend on the user’s needs; for instance, the pTau181/Aβ42 ratio (Elecsys®; (AUC: 1.0 [1.0‐1.0], sensitivity 100%, specificity 100%)) combines the two AD hallmarks (A and T) in one test. For ATN classification, the Aβ42/Aβ40 ratio (Lumipulse®, AUC: 1.0 [1.0‐1.0], sensitivity 100%, specificity 100%) might be a more accurate marker for amyloid positivity (A+) than Aβ42 alone.