Case study of a 47-year-old long COVID patient diagnosed with Alzheimer’s disease

Introduction

Coronavirus disease 2019 (COVID-19) increases the risk of developing Alzheimer’s disease (AD) in the future. However, the emergence of AD-like symptoms associated with COVID-19 (1) has not been extensively reported nor studied.

Case presentation

A female patient, born in 1974, began exhibiting repetitive behavior, memory loss, and executive dysfunction since 2021, after the peak of COVID-19 pandemic. By the end of 2023, she received a diagnosis of AD, primarily based on positive results of both amyloid positron emission tomography/computed tomography (Amyloid-PET/CT) and Tau-PET/CT imaging, as well as negative results of mGluR5-PET/magnetic resonance imaging (mGluR5-PET/MRI). However, early onset AD (EOAD) is a neurodegenerative dementing disorder that is relatively rare (<1% of all AD cases) (2). Furthermore, this patient did not exhibit characteristics typically associated with EOAD, such as AD-related gene mutations or increased sulcal widths in the temporoparietal cortex. Notably, based on a comparison of results between magnetic resonance spectroscopy (MRS) and Amyloid-PET/CT imaging, our analysis suggested that no direct correlation can be established between neuronal injury or degeneration and the presence of amyloid plaques in the hippocampus. We concluded that this AD case is different from typical EOAD cases.

All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee(s) and the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the patient for publication of this article and accompanying images. A copy of the written consent is available for review by the editorial office of this journal.

Our conclusion was preliminarily validated by subsequent clinical observations and diagnostic tests. Over the past 10 months since her AD diagnosis, no significant progressive cognitive decline was observed; instead, her health exhibited slight improvement. Notably, her Mini Mental State Examination (MMSE) score improved from 23 to 27, with a maximum possible score of 30. However, her plasma biomarkers remained positive. Specifically, the levels of Aβ42/Aβ40, pTau181, and pTau217 were 0.055, 4.885, and 5.474 respectively, compared to the thresholds of ≥0.06, ≤4 and ≤3.3. In the present study, we presented this case, along with our comprehensive analysis and all available data, to contribute to future research and guide clinical practice. Our research did not address AD diagnostic conclusion per se, but focused on the scientific questions that the diagnostic data bring to light.

Results

Previous diagnosis, positron emission tomography (PET) imaging results, and our analysis

The patient received diagnoses of mild cognitive impairment (MCI) from one hospital and AD from another, based primarily on positive results of both Amyloid-PET/CT and Tau-PET/CT imaging. Her Amyloid-PET/CT and Tau-PET/CT imaging were conducted using 18F-AV45 (florbetapir) and 18F-MK6240, respectively. Images were taken over a 10-min period, 50 min after injection of PET tracers. The images were subsequently evaluated by two individuals who are not aware of any clinical information about the patient. In addition to visual assessment, the images were also evaluated quantitatively using the standard uptake value ratio (SUVr) in the specific regions of interest, relative to the cerebellum defined as the reference region. Both Amyloid-PET/CT and Tau-PET/CT scans (Date: 20231227 and 20240113) provided clear visualization across various brain regions, showing radioactivity uptake notably increased and diffusely distributed in the cerebral cortex, involving the bilateral temporal lobes (including the hippocampus and entorhinal cortex), frontal lobes, parietal lobes, occipital lobes, the posterior cingulate cortex, among others. The quantitation of Amyloid-PET/CT images yielded an average SUVr of 1.9 for the parietal, 2.1 for the frontal lobe, 1.9 for the temporal lobes, and 1.8 for the posterior cingulate gyrus. However, the pattern of these values (1.9, 2.1, 1.9 and 1.8) was notably different from that observed in a previous study (3,4), which reported values of 1.24, 1.28, 1.42, and 1.44 for the respective regions in AD patients. In addition, the PET/MRI results using 18F-PSS232 showed no significant reduction in the distribution of mGluR5 in the patient’s brain (Date: 20240515).

Neuronal injury or degeneration was identified through the decreased N-acetylaspartate (NAA) levels detected using MRS, which accounts for the patient’s clinical symptoms. Given that more severe neuronal injury or degeneration was detected in the left hippocampus compared to the right one (Figure 1A,1B), it was expected that a significantly higher abundance of amyloid plaques would be detected in the left hippocampus via Amyloid-PET/CT imaging. However, Amyloid-PET/CT images showed a significantly higher abundance of amyloid plaques in the right hippocampus (Figure 1C,1D). These results suggested that no direct correlation can be established between neuronal injury or degeneration and the presence of amyloid plaques in the hippocampus. Therefore, the aggregated amyloid proteins in the plaques may primarily originate from alternative sources, rather than from injured or degenerated neurons.

Figure 1 Comparison of results between MRS and Amyloid-PET/CT imaging. MRS results (Date: 20240515) of the right hippocampus (A) were compared with those of the left one (B). Specifically, the peak for NAA on the right side (chemical shifts of 2.0 ppm) is higher than that on the left side. Conversely, the peaks for creatine (Cr) and choline (Cho) on the right side (chemical shifts of 3.03 ppm and 3.2 ppm, respectively) are lower than their counterparts on the left side. X-axis represents the chemical shift in parts per million (ppm), while y-axis represents the signal intensity or amplitude of the metabolite peaks. (C) Amyloid plaques (in red color) in the right hippocampus (indicated by black arrow) were compared with that in the left hippocampus. (C) and (D) depict the same image in pseudocolor and grayscale styles, respectively. Amyloid-PET/CT report date is 20231227. Amyloid-PET/CT, amyloid-positron emission tomography computed tomography; MRS, magnetic resonance spectroscopy; NAA, N-acetylaspartate.

Genetic testing results and circular RNA (circRNA) biomarker

As EOAD or autosomal dominantly inherited AD is frequently associated with genetic causes and is often substantially or even entirely genetically determined (5), we performed genetic testing for the patient using whole exome sequencing (WES). The WES was performed by Innovo Biotechnology Co. Ltd, using 2×150 paired-end sequencing strategy on an Illumina sequencer, producing 32,769,278 pairs of reads. After data quality control, the cleaned reads (SRA: SRR31604084) were aligned to the reference human genome GRCh38. A total of 19,441 protein-coding genes and ORFs in the panel (VAHTS Target Capture Core Exome Panel) were covered with the average depth 148.17. As a result (Date: 20241026), no known deleterious mutations were detected in her AD-associated genes, particularly APP, PSEN1, PSEN2, MAPT, APOE, and CLU (6). Her APOE genotype is ε3/ε3. Additionally, no known deleterious mutations had been detected in her son’s genetic profile using WES, and there is no family history of AD among her parents. Based on the analysis of WES data, a genetic origin for this AD case was excluded. As a novel diagnostic method, a circRNA named circDENND1B-1, discovered as a potential biomarker for AD in a previous study (7), was tested separately using her plasma and blood cells. Positive detection of circDENND1B-1 (qPCR Ct <40) typically indicates abnormal RNA splicing in cells, a critical factor implicated in the pathogenesis of neurodegenerative diseases. However, the negative results observed in this patient confirmed the atypical nature of this AD case.

Further exploration of potential etiologies

The patient had undergone a comprehensive physical examination utilizing a range of diagnostic modalities to assess all bodily systems. Fortunately, numerous potential etiologies were systematically excluded. The prime suspect was the prolonged presence of inflammatory cytokines, as evidenced by the detection of high levels of IL-6 and IL-10 in the patient’s blood following the peak of the COVID-19 pandemic. The only suspected cause is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or its vaccination. Notably, the patient’s symptoms emerged after the peak of the COVID-19 pandemic, when she was 47 years old, which is close to the median age of 44 identified in a study investigating 32 cases of central nervous system (CNS) demyelination following COVID-19 vaccination (8). Additionally, the timing of symptom emergence is consistent with an earlier finding that people with COVID-19 were at significantly increased risk for new diagnosis of AD within 360 days after the initial COVID-19 diagnosis, especially in people age ≥85 years and in women (9). Demyelination was identified in the patient’s cerebral white matter by at least seven separate MRI scans (Data: 20231216, 20231221, 20240414, 20240427, 20240515, 20240701 and 20240826). Given this, the potential association between SARS-CoV-2 infection or its vaccination and the observed demyelination merits further investigation.

Potential alternative sources of the aggregated amyloid and Tau proteins

To pinpoint the alternative source of aggregated amyloid proteins in the patient’s brain, a single-cell RNA sequencing (scRNA-seq) dataset was utilized to compare the expression levels of APP, MAPT, and ACE2 (Figure 2) across 13 major cell types (10). Unexpectedly, the expression levels of APP and MAPT in oligodendrocytes were exceptionally higher than those in the other 12 cell types, exceeding twofold the levels in neurons. Remarkably, the expression level of ACE2 in pericytes was substantially higher, exceeding 13 times the combined levels across all other cells. Given that ACE2 encodes the specific receptor for SARS-CoV-2, it is plausible that the demyelination could initiate with the infection of pericytes in blood-brain barrier (BBB) by SARS-CoV-2 or its vaccine through ACE2. This demyelinating process likely involves oligodendrocytes (11), potentially due to similar interactions observed between pericytes and oligodendrocyte precursor cells (OPCs) in the perivascular regions of cerebral white matter (9). As a result, amyloid and Tau proteins could be secreted from living oligodendrocytes or released from dying ones, serving as the alternative source for plaque formation. Thus, the formation of amyloid plaques in the patient’s brain can be elucidated by a potential alternative pathway that extends from virus infection to amyloid plaque formation. The mechanisms underlying this pathway can also explain a previous finding that oligodendrocytes produce amyloid proteins and contribute to plaque formation (12).

Figure 2 Cell-specific expression of APP, MAPT and ACE2. The expression levels of APP (top), MAPT (middle) and ACE2 (bottom) in 13 major cell types (CMC, neuron, microglia, Mono/Maph, neutrophil, T/NK, fibroblast, endothelial, pericyte, OPC, oligodendrocyte, astrocyte, and ependymal) were showed using a scRNA-seq dataset (GEO: GSE236293). Although this dataset was derived by sequencing cells from mouse spinal cords, the gene expression profile of these cell types in spinal cords is similar to that in brains. MAPT encodes the Tau protein, and ACE2 encodes the specific receptor for SARS-CoV-2. CMC, cycling myeloid cell; Mono, monocyte; Maph, macrophage; NK, natural killer cell; OPC, oligodendrocyte precursor cell; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; T, T cell.

Discussion

CNS demyelination (8,13-15) and “COVID fog” (16) following SARS-CoV-2 infection or its vaccination have been reported in various studies. However, the emergence of AD-like symptoms associated with COVID-19 has not been extensively reported nor studied. The previous studies (8,9) suggested that a considerable number of AD cases analogous to the case in the present study may have emerged after the peak of the COVID-19 pandemic. For future research on CNS demyelination, “COVID fog” and AD-like symptoms associated with COVID-19, we suggest that the analogous AD cases be categorized under a distinct subset within the long COVID syndromes, termed AD-like COVID syndromes. In addition, we propose a potential alternative pathway to elucidate amyloid plaque formation in the patient’s brain: virus infection → blood-brain barrier (pericytes and oligodendrocytes) → demyelination → amyloid plaques that can be detected using Amyloid-PET/CT imaging. However, no direct correlation can be established between the presence of amyloid plaques and neuronal injury or degeneration in the hippocampus, which can be detected using MRS. Therefore, the causes of neuronal injury or degeneration in the hippocampus, which remain unknown, were not studied in our study. To aid in future research on AD-like COVID syndromes, we characterized this unusual AD case by integrating data from various diagnostic methods, including PET, MRI imaging, genetic testing, plasma biomarker testing, among others. Although plasma biomarker testing results align with those from Amyloid-PET/CT and Tau-PET/CT imaging, neither of these diagnostic methods can be used to distinguish AD-like COVID syndromes from typical EOAD. Based on our findings (Figure 1), we suggest integrating MRS detection of neuronal injury or degeneration with Amyloid-PET/CT imaging to confirm the correlation between neuronal injury or degeneration and the presence of amyloid plaques in the hippocampus, leading to the final determination of AD origins.

Conclusions

For the first time, our study has characterized AD-like COVID syndromes from multiple perspectives, facilitating future diagnosis of these diseases. Our discovery of the inconsistency between the presence of amyloid plaques and neuronal injury or degeneration in the hippocampus not only paves the way for research into the mechanisms underlying AD, but also provides a valuable direction for elucidating AD-like COVID syndromes.

Acknowledgments

We appreciate the special help from Assistant Professor Zhi Cheng from College of Life Sciences, Tianjin Normal University. This manuscript was online as a preprint on Nov. 29th, 2024 at Research Square (https://www.researchsquare.com/article/rs-5549836/v1).

Footnote

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-125/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee(s) and the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from the patient for publication of this article and accompanying images. A copy of the written consent is available for review by the editorial office of this journal.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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