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Alzheimer's Disease Fact Sheet

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How does Alzheimer's disease affect the brain?

Signs and symptoms of alzheimer's disease, stages of alzheimer's disease, what causes alzheimer’s disease, how is alzheimer’s disease diagnosed, how is alzheimer’s disease treated, support for families and alzheimer's disease caregivers.

Alzheimer’s disease is a brain disorder that slowly destroys memory and thinking skills, and eventually, the ability to carry out the simplest tasks. In most people with Alzheimer’s, symptoms first appear later in life. Estimates vary, but experts suggest that more than 6 million Americans, most of them age 65 or older, may have Alzheimer’s.

Alzheimer’s is currently ranked as the seventh leading cause of death in the United States and is the most common cause of dementia among older adults.

Dementia is the loss of cognitive functioning — thinking, remembering, and reasoning — and behavioral abilities to such an extent that it interferes with a person’s daily life and activities. Dementia ranges in severity from the mildest stage, when it is just beginning to affect a person’s functioning, to the most severe stage, when the person must depend completely on others for help with basic activities of daily living.

The causes of dementia can vary depending on the types of brain changes that may be taking place. Other forms of dementia include Lewy body dementia , frontotemporal disorders , and vascular dementia . It is common for people to have mixed dementia — a combination of two or more types of dementia. For example, some people have both Alzheimer’s and vascular dementia.

Alzheimer’s disease is named after Dr. Alois Alzheimer. In 1906, Dr. Alzheimer noticed changes in the brain tissue of a woman who had died of an unusual mental illness. Her symptoms included memory loss, language problems, and unpredictable behavior. After she died, he examined her brain and found many abnormal clumps (now called amyloid plaques) and tangled bundles of fibers (now called neurofibrillary, or tau, tangles).

These plaques and tangles in the brain are still considered some of the main features of Alzheimer’s. Another feature is the loss of connections between neurons in the brain. Neurons transmit messages between different parts of the brain, and from the brain to muscles and organs in the body.

Participating in Alzheimer's disease clinical trials

Everybody — those with Alzheimer’s or mild cognitive impairment as well as healthy volunteers with or without a family history of Alzheimer’s — may be able to take part in clinical trials and studies. Participants in Alzheimer’s clinical research can help scientists learn how the brain changes in healthy aging and in Alzheimer’s.

Many volunteers are needed to participate in the hundreds of active clinical trials and studies that are testing ways to better understand, diagnose, treat, and prevent Alzheimer’s. Researchers need participants of different ages, sexes, races, and ethnicities to ensure that results are meaningful for many people. To learn more about clinical trials, watch this video from the NIH National Library of Medicine.

NIA leads the federal government’s research efforts on Alzheimer’s. NIA-funded Alzheimer’s Disease Research Centers throughout the United States conduct a wide range of research, including trials and studies of the causes, diagnosis, and management of the disease. NIA also sponsors the Alzheimer’s Clinical Trials Consortium , which is designed to accelerate and expand research and therapies in Alzheimer’s and related dementias.

To learn more about Alzheimer’s clinical trials and studies:

• Talk to your health care provider about local studies that may be right for you.
• Search the Alzheimers.gov Clinical Trials Finder for options near you or sign up for email alerts about new trials and studies.
• Sign up for a registry or matching service to be invited to participate in trials and studies.
• Contact an Alzheimer’s Disease Research Center or a memory or neurology clinic in your community.

Learn more about participating in clinical trials . Watch videos of participants in Alzheimer’s clinical trials talking about their experiences.

The damage initially appears to take place in the hippocampus and the entorhinal cortex, which are parts of the brain that are essential in forming memories. As more neurons die, additional parts of the brain are affected and begin to shrink. By the final stage of Alzheimer’s, damage is widespread and brain tissue has shrunk significantly.

Memory problems are typically one of the first signs of cognitive impairment related to Alzheimer’s. Some people with memory problems have a condition called mild cognitive impairment (MCI). With MCI, people have more memory problems than normal for their age, but their symptoms do not interfere with their everyday lives. Movement difficulties and problems with the sense of smell have also been linked to MCI. Older people with MCI are at greater risk for developing Alzheimer’s, but not all of them do so. Some may even revert to normal cognition.

The first symptoms of Alzheimer’s vary from person to person. For many, decline in nonmemory aspects of cognition, such as word finding, vision/spatial issues, and impaired reasoning or judgment may signal the very early stages of the disease. Researchers are studying biomarkers (biological signs of disease found in brain images, cerebrospinal fluid, and blood) to detect early changes in the brains of people with MCI and in cognitively normal people who may be at greater risk for Alzheimer’s. More research is needed before these techniques can be used broadly and routinely to diagnose Alzheimer’s in a health care provider’s office.

Mild Alzheimer’s disease

As Alzheimer’s worsens, people experience greater memory loss and other cognitive difficulties. Problems can include wandering and getting lost, trouble handling money and paying bills , repeating questions, taking longer to complete normal daily tasks, and personality and behavior changes . People are often diagnosed in this stage.

Moderate Alzheimer’s disease

In this stage, damage occurs in areas of the brain that control language, reasoning, conscious thought, and sensory processing, such as the ability to correctly detect sounds and smells. Memory loss and confusion grow worse, and people begin to have problems recognizing family and friends. They may be unable to learn new things, carry out multistep tasks such as getting dressed, or cope with new situations. In addition, people at this stage may have hallucinations, delusions, and paranoia and may behave impulsively.

Severe Alzheimer’s disease

Ultimately, plaques and tangles spread throughout the brain, and brain tissue shrinks significantly. People with severe Alzheimer’s cannot communicate and are completely dependent on others for their care. Near the end of life , the person may be in bed most or all of the time as the body shuts down.

In recent years, scientists have made tremendous progress in better understanding Alzheimer’s and the momentum continues to grow. Still, scientists don’t yet fully understand what causes Alzheimer’s disease in most people. The causes probably include a combination of age-related changes in the brain, along with genetic, environmental, and lifestyle factors. The importance of any one of these factors in increasing or decreasing the risk of developing Alzheimer’s may differ from person to person.

The basics of Alzheimer’s disease

Scientists are conducting studies to learn more about plaques, tangles, and other biological features of Alzheimer’s. Advances in brain imaging techniques enable researchers to see the development and spread of abnormal amyloid and tau proteins in the living brain, as well as changes in brain structure and function. Scientists are also exploring the very earliest steps in the disease process by studying changes in the brain and body fluids that can be detected years before Alzheimer’s symptoms appear. Findings from these studies will help improve our understanding of the causes of Alzheimer’s and make diagnosis easier.

One of the great mysteries of Alzheimer’s is why it largely affects older adults. Research on normal brain aging is exploring this question. For example, scientists are learning how age-related changes in the brain may harm neurons and affect other types of brain cells to contribute to Alzheimer’s damage. These age-related changes include atrophy (shrinking) of certain parts of the brain, inflammation, blood vessel damage, production of unstable molecules called free radicals, and mitochondrial dysfunction (a breakdown of energy production within a cell).

Alzheimer's disease genetics

In most cases, Alzheimer’s does not have a single genetic cause. Instead, it is likely influenced by multiple genes in combination with lifestyle and environmental factors. Changes in genes, called genetic variations, may increase or decrease a person’s risk of developing the disease.

Scientists currently know of more than 80 genetic regions associated with Alzheimer’s. Of the genetic variants associated with Alzheimer’s so far, only three are known to cause the disease. Although it happens rarely, when someone inherits an altered version of one of these genes — APP, PSEN1, or PSEN2 — they will likely develop Alzheimer’s before age 65 and sometimes much earlier.

People with Down syndrome also have a higher risk of developing Alzheimer’s earlier in life. Down syndrome results from having an extra chromosome 21, which carries the APP gene that produces the amyloid precursor protein. Too much of this protein leads to build-up of beta-amyloid plaques in the brain. Estimates suggest that 50% or more of people living with Down syndrome will develop Alzheimer’s with symptoms appearing in their 50s and 60s.

Another genetic variation, in the APOE gene, which has several forms, is known to influence the risk of Alzheimer’s. Specifically, APOE ε4 increases a person’s risk of developing Alzheimer’s and is also associated with developing Alzheimer’s earlier in life for certain populations. APOE ε2 may provide some protection against Alzheimer’s.

Changes in different genes, along with other biomedical, lifestyle, and environmental factors, play a role in potentially developing Alzheimer’s. Still, it is never known for certain if any individual will or will not develop the disease.

For more about Alzheimer’s genetics research, see NIA’s Alzheimer’s Disease Genetics Fact Sheet .

Health, environmental, and lifestyle factors

Research suggests that a host of factors beyond genetics may play a role in the development and course of Alzheimer’s. There is a great deal of interest, for example, in the relationship between cognitive decline and vascular conditions, such as heart disease , stroke , and high blood pressure , as well as metabolic diseases, such as diabetes and obesity. Ongoing research will help us understand whether and how reducing risk factors for these conditions may also reduce the risk of Alzheimer’s.

A nutritious diet , physical activity , social engagement , and mentally stimulating pursuits have all been associated with helping people stay healthy as they age. These factors might also help reduce the risk of cognitive decline and Alzheimer’s. Researchers are testing some of these possibilities in clinical trials.

Doctors use several methods and tools to help determine whether a person who is having memory problems has Alzheimer’s.

To diagnose Alzheimer’s, doctors may:

• Ask the person and a family member or friend questions about overall health, use of prescription and over-the-counter medicines, diet, past medical problems, ability to carry out daily activities, and changes in behavior and personality.
• Conduct tests of memory, problem solving, attention, counting, and language.
• Order blood, urine, and other standard medical tests to help identify other possible causes of the problem.
• Administer tests to determine if depression or another mental health condition is causing or contributing to a person’s symptoms.
• Collect cerebrospinal fluid via a spinal tap or order blood tests to measure the levels of proteins associated with Alzheimer’s and related dementias.
• Perform brain scans, such as CT, MRI, or PET (positron emission tomography), to support an Alzheimer’s diagnosis or to rule out other possible causes for symptoms.

These tests may be repeated to give doctors information about how the person’s memory and other cognitive functions are changing over time.

People with memory and thinking concerns should talk to their doctor to find out whether their symptoms are due to Alzheimer’s or to another cause, such as stroke , tumor, Parkinson’s disease , sleep disturbances , side effects of medication , an infection, or another type of dementia . Some of these conditions may be treatable and, possibly, reversible.

If the diagnosis is Alzheimer’s , beginning treatment as early as possible in the disease process may help preserve daily functioning for a while. An early diagnosis also helps families plan for the future. They can take care of financial and legal matters , address potential safety issues , learn about living arrangements , and develop support networks.

In addition, an early diagnosis provides people with more opportunities to participate in clinical trials or studies testing possible new treatments for Alzheimer’s.

For more information, visit How Is Alzheimer’s Disease Diagnosed?

Alzheimer’s is complex, and it is therefore unlikely that any one drug or other intervention will successfully treat it in all people living with the disease. In ongoing clinical trials, scientists are developing and testing several possible treatment interventions.

While there is currently no cure for Alzheimer’s, medications are emerging to treat the progression of the disease by targeting its underlying causes. There are also medications that may temporarily improve or stabilize memory and thinking skills in some people and may help manage certain symptoms and behavioral problems.

Additionally, people with Alzheimer’s also may experience sleeplessness , depression, anxiety, agitation , and other behavioral and psychological symptoms. Scientists continue to research why these symptoms occur and are exploring new medications and non-drug strategies to manage them. Research shows that treating these symptoms may make people with Alzheimer’s feel more comfortable and also help their caregivers. Antidepressants, antipsychotics, and anti-anxiety drugs may be helpful for some people with Alzheimer’s, but experts agree that these medicines should be used only after other strategies to promote physical and emotional comfort, such as avoiding stressful situations, have been tried. It’s important to talk with a doctor about what treatment will be most effective in your situation.

For more information, visit How Is Alzheimer's Disease Treated?

Clinical trials on Alzheimer’s disease treatments

Volunteers are needed for clinical trials that are testing ways to treat Alzheimer’s. By joining one of these studies, you may help scientists discover new Alzheimer’s treatments and contribute useful information to help people living with Alzheimer's disease.

Caring for a person with Alzheimer’s can have significant physical, emotional, and financial costs. The demands of day-to-day care, changes in family roles, and decisions about placement in a care facility can be difficult. NIA supports efforts to evaluate programs, strategies, approaches, and other research to improve the quality of care and life for those living with dementia and their caregivers.

Becoming well-informed about the disease is one important long-term strategy. Programs that teach families about the various stages of Alzheimer’s and about ways to deal with difficult behaviors and other caregiving challenges can help.

Good coping skills, a strong support network, and respite care are other things that may help caregivers handle the stress of caring for a loved one with Alzheimer’s. For example, staying physically active provides physical and emotional benefits.

Some caregivers have found that joining a support group is a critical lifeline. These support groups enable caregivers to find respite, express concerns, share experiences, get tips, and receive emotional comfort. Many organizations sponsor in-person and online support groups, including groups for people with early-stage Alzheimer’s and their families.

For more information, see Alzheimer’s Caregiving .

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For more information about Alzheimer’s disease

NIA Alzheimer’s and related Dementias Education and Referral (ADEAR) Center 800-438-4380 [email protected] www.nia.nih.gov/alzheimers The NIA ADEAR Center offers information and free print publications about Alzheimer’s and related dementias for families, caregivers, and health professionals. ADEAR Center staff answer telephone, email, and written requests and make referrals to local and national resources.

Alzheimers.gov www.alzheimers.gov Explore the Alzheimers.gov website for information and resources on Alzheimer’s and related dementias from across the federal government.

Eldercare Locator 800-677-1116 [email protected] https://eldercare.acl.gov

MedlinePlus National Library of Medicine       www.medlineplus.gov

Alzheimer's Association 800-272-3900  866-403-3073 (TTY) [email protected] www.alz.org

Alzheimer’s Foundation of America 866-232-8484 [email protected] www.alzfdn.org

This content is provided by the NIH National Institute on Aging (NIA). NIA scientists and other experts review this content to ensure it is accurate and up to date.

Content reviewed: April 5, 2023

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• Open access
• Published: 20 June 2024

Circulating small extracellular vesicles in Alzheimer’s disease: a case–control study of neuro-inflammation and synaptic dysfunction

• Rishabh Singh 1 ,
• Sanskriti Rai 1 ,
• Prahalad Singh Bharti 1 ,
• Sadaqa Zehra 1 ,
• Priya Kumari Gorai 2 ,
• Gyan Prakash Modi 3 ,
• Neerja Rani 2 ,
• Kapil Dev 4 ,
• Krishna Kishore Inampudi 1 ,
• Vishnu V. Y. 5 ,
• Prasun Chatterjee 6 ,
• Fredrik Nikolajeff 7 &
• Saroj Kumar 1 , 7  

BMC Medicine volume  22 , Article number:  254 ( 2024 ) Cite this article

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Alzheimer’s disease (AD) is a neurodegenerative disease characterized by Aβ plaques and neurofibrillary tangles. Chronic inflammation and synaptic dysfunction lead to disease progression and cognitive decline. Small extracellular vesicles (sEVs) are implicated in AD progression by facilitating the spread of pathological proteins and inflammatory cytokines. This study investigates synaptic dysfunction and neuroinflammation protein markers in plasma-derived sEVs (PsEVs), their association with Amyloid-β and tau pathologies, and their correlation with AD progression.

A total of 90 [AD = 35, mild cognitive impairment (MCI) = 25, and healthy age-matched controls (AMC) = 30] participants were recruited. PsEVs were isolated using a chemical precipitation method, and their morphology was characterized by transmission electron microscopy. Using nanoparticle tracking analysis, the size and concentration of PsEVs were determined. Antibody-based validation of PsEVs was done using CD63, CD81, TSG101, and L1CAM antibodies. Synaptic dysfunction and neuroinflammation were evaluated with synaptophysin, TNF-α, IL-1β, and GFAP antibodies. AD-specific markers, amyloid-β (1–42), and p-Tau were examined within PsEVs using Western blot and ELISA.

Our findings reveal higher concentrations of PsEVs in AD and MCI compared to AMC ( p  < 0.0001). Amyloid-β (1–42) expression within PsEVs is significantly elevated in MCI and AD compared to AMC. We could also differentiate between the amyloid-β (1–42) expression in AD and MCI. Similarly, PsEVs-derived p-Tau exhibited elevated expression in MCI compared with AMC, which is further increased in AD. Synaptophysin exhibited downregulated expression in PsEVs from MCI to AD ( p  = 0.047) compared to AMC, whereas IL-1β, TNF-α, and GFAP showed increased expression in MCI and AD compared to AMC. The correlation between the neuropsychological tests and PsEVs-derived proteins (which included markers for synaptic integrity, neuroinflammation, and disease pathology) was also performed in our study. The increased number of PsEVs correlates with disease pathological markers, synaptic dysfunction, and neuroinflammation.

Conclusions

Elevated PsEVs, upregulated amyloid-β (1–42), and p-Tau expression show high diagnostic accuracy in AD. The downregulated synaptophysin expression and upregulated neuroinflammatory markers in AD and MCI patients suggest potential synaptic degeneration and neuroinflammation. These findings support the potential of PsEV-associated biomarkers for AD diagnosis and highlight synaptic dysfunction and neuroinflammation in disease progression.

Peer Review reports

The progressive neurodegenerative condition known as Alzheimer’s disease (AD) is characterized by cognitive decline as a result of the formation of amyloid-β (Aβ) plaques, neurofibrillary tangles (NFTs), and chronic neuroinflammation that leads to neurodegeneration [ 1 , 2 , 3 ]. Synapse loss is a crucial pathophysiological event in disease progression, and synaptic proteins have been extensively studied due to earlier perturbations [ 4 , 5 ]. The pathological hallmark of AD, amyloid-β plaques, originates from the imprecise cleavage of the amyloid precursor protein (APP) by β-secretase (BACE1) and γ-secretase generating amyloid-β peptide forms [ 6 , 7 , 8 , 9 ]. Primary amyloid-β peptide forms are Aβ40 and Aβ42, where the majority of the amyloid-β plaques in AD brains are composed of Aβ42 [ 10 ]. Many point mutations in APP and γ-secretase cause familial early-onset AD, favoring Aβ42 formation, causing amyloid-β peptides prone to aggregate as fibrils and plaques [ 9 , 11 , 12 , 13 , 14 ]. Hyperphosphorylation of tau causes the formation of NFTs. The combined effect of accumulation of NFTs, amyloid-β fibrils, and plaques leads to neuronal function loss and cell death [ 15 , 16 ]. Aβ plaques activate immune receptors on microglia, thereby releasing pro-inflammatory cytokines and chemokines that mediate neuroinflammation, which, if it reaches a chronic level, causes damage to brain cells, including axonal demyelination and synaptic pruning [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. In addition to these, other proteins, including the neurofilament light (NFL) protein, glial fibrillary acidic protein (GFAP), and synaptic proteins, have also been identified as AD biomarkers [ 24 , 25 , 26 , 27 , 28 ]. Understanding the intricate dynamics of AD in terms of its varied pathophysiological manifestations, such as neuroinflammation, synaptic loss, and proteinopathy, is essential for developing potential therapeutic interventions for AD and biomarker discovery. In clinical practice, cognitive assessment tools such as the Addenbrooke’s Cognitive Examination (ACE-III) and Mini-Mental State Examination (MMSE) are used to diagnose AD. These tools evaluate verbal fluency and temporal orientation, although results may be influenced by subject bias [ 29 , 30 , 31 ].

In recent years, small extracellular vesicles (sEVs) or exosomes have been acknowledged as crucial mediators of communication and signaling within the body, contributing significantly to the transmission of cellular cargo in various health and disease states. They also play a notable role in disseminating protein aggregates associated with neurodegenerative diseases [ 32 ]. sEVs are bi-layered membrane vesicles that have a heterogeneous group of (< 200 nm in diameter) that are found in different human body fluids, including blood, urine, saliva, and ascites, and that are actively released by all cell types [ 33 , 34 , 35 ]. For their functions in various physiological and pathological circumstances, sEVs are the most extensively researched type of EV [ 36 , 37 , 38 ]. sEVs exchange information between cells by transferring bioactive components (nucleic acids and proteins) [ 39 ]. As the sEVs’ composition bears the molecular signature of the secreting cell and bears an intrinsic property of transversing the blood–brain barrier (BBB) in both directions [ 40 , 41 ], they are a target of constant research in neurodegenerative disease. Furthermore, sEVs released by neuronal cells are crucial in transmitting signals to other nerve cells, influencing central nervous system (CNS) development, synaptic activity regulation, and nerve injury regeneration. Moreover, sEVs exhibit a dual function in neurodegenerative processes, as sEVs not only play an essential role in clearing misfolded proteins, thereby exerting detoxifying effects and providing neuroprotection [ 42 ]. On the other hand, they also have the potential to participate in the propagation and aggregation of misfolded proteins, particularly implicated in the pathological spread of Tau aggregates as indicated by both in vitro and in vivo studies [ 43 ]. As a protective mechanism, astrocytes (most abundant glial cells) accumulate at the locations where Aβ peptides are deposited, internalizing and breaking down aggregated peptides [ 44 ]. However, severe endosomal–lysosomal abnormalities arise in astrocytes when a significantly large amount of Aβ accumulates within astrocytes for a prolonged period without degradation [ 45 , 46 ]. Astrocytes then release engulfed amyloid-β (1-42) protofibrils through exosomes, leading to severe neurotoxicity to neighboring neurons [ 44 ]. Additionally, it has been found that the release of amyloid-β by microglia in association with large extracellular vesicles (Aβ-lEVs) damages synaptic plasticity and modifies the architecture of the dendritic spine [ 47 ]. Thus, sEVs can be a compelling subject for the investigation to understand AD’s inflammation and synaptic dysfunction [ 48 , 49 , 50 , 51 , 52 ].

In this study, we reported that protein levels are associated with AD pathology, neuroinflammation, and synaptic dysfunction in plasma-derived small extracellular vesicles (PsEVs). Our objective was to understand the pathophysiological process, neuroinflammation, synaptic dysfunction, and Aβ pathology through sEVs. Our study revealed a significant correlation between the concentration of cargo proteins derived from PsEVs and clinical diagnosis concerning ACE-III and MMSE scores. Furthermore, the levels of these studied proteins within PsEVs could differentiate between patients with MCI and AD. Thus, our study sheds light on the potential of PsEVs in understanding AD dynamics and offers insights into the underlying mechanisms of disease progression.

Subject recruitment

A total of n  = 35 AD patients and n  = 25 subjects with MCI were recruited from the Memory Clinic, Department of Geriatrics, All India Institute of Medical Sciences, New Delhi, India. Additionally, n  = 30 healthy AMC (volunteers) were recruited. The inclusion criteria were as follows: a clinical diagnosis of MCI and AD patients using ACE-III and MMSE tests. The exclusion criteria encompass medical conditions such as cancer, autoimmune disorders, liver disease, hematological disorders, or stroke, as well as psychiatric conditions, substance abuse, or any impediment to participation. Controls were healthy, age-matched adults without neurological symptoms. AMC was 60–71, MCI was 65–79, and AD was 70–80 years of age range (Table  1 ). Neuropsychological scores, viz., ACE-III and MMSE, were recorded before subject selection.

Study ethical approval

The institutional ethics committee of All India Institute of Medical Sciences, New Delhi, India, granted the study ethical permission. The study has been granted the ethical approval number IECPG-670/25.08.2022. Following the acquisition of the written informed consent, all participants were enrolled.

Sample collection

One milliliter of blood was drawn from each participant using venipuncture, and blood collection vials were kept on ice during collection. The blood was centrifuged at 1700 g for 20 min at 4 °C to remove the cells, and the straw-colored plasma was collected. It was further clarified by centrifuging for 30 mi at 4 °C at 10,000 g. Finally, cleared plasma was stored at − 80 °C until further use. The samples were used for the downstream experiment after being thawed on ice and centrifuged at 10,000 g.

Isolation of PsEVs

The PsEVs were extracted by chemical-based precipitation from the plasma samples of AD patients, MCI patients, and AMC, as discussed previously [ 53 , 54 ]. In brief, 180 μL of plasma sample was used and filtered with 0.22 μm filter (SFNY25R, Axiva), followed by overnight incubation with the chemical precipitant (14% polyethylene glycol 6000) (807,491, Sigma). The samples underwent an hour-long, 13,000 g centrifugation at 4 °C the next day. Before being resuspended in 200 μL of 1X PBS (ML116-500ML, HiMedia), the pellet was first cleaned twice with 1X PBS. Before downstream experiments, the sEVs-enriched fraction was further filtered through a 100-kDa filter (UFC5100, Millipore).

Nanoparticle tracking analysis (NTA)

5000-fold dilution in 1X-PBS buffer was used for the NTA of PsEVs. In the ZetaView Twin system (Particle Metrix, Germany) sample chamber, 1 mL of diluted PsEVs sample was introduced. The following parameters were used throughout three cycles of scanning 11 cell locations each, and 60 frames per position were collected (video setting: high, focus: autofocus, shutter: 150, 488 nm internal laser, camera sensitivity: 80, cell temperature: 25 °C. CMOS cameras were used for recording, and the built-in ZetaView Software 8.05.12 (Particle Metrix, Germany) was used to analyze: 10 nm as minimum particle size, 1000 nm as maximum particle size, and 30 minimum particle brightness.

Transmission electron microscopy for morphological characterization

Transmission electron microscopy was employed to investigate PsEVs’ ultrastructural morphology. The resultant PsEVs pellet was diluted with PBS using 0.1 M phosphate buffer (pH 7.4). A carbon-coated copper grid of 300 mesh (01843, Ted Pella) was used to adsorb the separated PsEVs at room temperature for 30 min. After blot-drying, the adsorbed grids were dyed. For 10 s, 2% aqueous uranyl acetate solution (81,405, SRL Chem) as negative staining. After blotting the grids, they were inspected using a Talos S transmission electron microscope (ThermoScientific, USA).

Western blot

Based on the initial volume of biofluid input, all samples were normalized, i.e., 180 μL and the sample loading dye (2 × Laemmle Sample buffer) was mixed with PsEVs sample, and 20 μL equal volume was loaded to run on an 8–12% SDS PAGE [ 53 , 55 ]. After the completion of SDS-PAGE, protein from the gel was subjected to the Wet transfer onto the PVDF membrane of 0.22 μm (1,620,177, BioRad). The membrane-blocking with 3% bovine serum albumin (BSA) (D0024, BioBasic) in Tris (TB0194, BioBasic) base saline containing 0.1% of Tween 20 (65,296, SRL Chem) (TBST) using the BioRad Western blotting apparatus (BioRad, USA). Following this, overnight incubation of primary antibodies of CD63 (10628D, Invitrogen), CD81 (PA5-86,534, Invitrogen), TSG101 (MA1-23,296, Invitrogen), L1CAM (MA1-46,045, Invitrogen), synaptophysin (ADI-VAM-SV011-D, Enzo life sciences), GFAP (A19058, Abclonal), amyloid-β (1–42) oligomer (AHB0052, Invitrogen), phospho-Tau (s396) (35–5300, Invitrogen), interleukin 1β (IL-1β) (PA5-95,455, Invitrogen), tumor necrosis factor α (TNF-α) (E-AB-33121, Elabscience), and β-actin (AM4302, Invitrogen) were done at 4 °C. The membranes were washed with TBST buffer four times before at RT incubating with HRP-conjugated secondary antibodies, anti-rabbit (AB6721, Abcam), anti-mouse (31,430, Invitrogen). The Femto LUCENT™ PLUS-HRP kit (AD0023, GBiosciences) was used to develop the blot for visualizing the protein bands utilizing the method of enhanced chemiluminescence.

Enzyme-linked Immunosorbent Assay (ELISA)

According to the previous protocol, ELISA was carried out. [ 53 ]. PsEV samples were subjected to freeze–thaw cycles; next, PsEVs were ultrasonicated for two minutes, with a 30-s on-and-off cycle, at an amplitude of 25. Following this, they underwent a 10-min centrifugation at 10,000 g, at 4 °C, and the obtained supernatant was used. The samples were kept at 37 °C before loading into the ELISA plates. The bicinchoninic acid (BCA) protein assay kit (23,225, ThermoFisher Scientific) was used to quantify the total protein concentration using BSA (D0024, BioBasic) as a reference. The ELISA kit was used to detect the presence of protein in 100 μL of PsEV sample are as follows: amyloid-β (1–42) (E-EL-H0543, ELabsciences), p-Tau (s-396) (E-EL-H5314, ELabsciences), IL-1β (ITLK01270, GBiosciences), TNF-α (ITLK01190, GBiosciences), GFAP (E-EL-H6093, ELabsciences), and synaptophysin (E-EL-H2014, ELabsciences). The manufacturer’s instructions were followed for every step of the process. A 96-well microplate spectrophotometer (SpectraMax i3x Multi-Mode Microplate Reader, Molecular devices) was used to measure the absorbance at 450 nm.

Data and statistical analysis

The mean age values, ACE-III score, and MMSE score were ascertained using descriptive statistical analysis Table  1 . GraphPad Prism 8.0 was used for statistical data analysis, including NTA concentration, Western blotting densitometric analysis, and ELISA. Unpaired student t -test and ANOVA were used for group analysis, and statistical significance was determined. p  < 0.05 was used to assess significance. The Image J software (NIH, USA) was used for the densitometry analysis. The receiver operating characteristic (ROC) curve was used to analyze the efficiency of distinguishing the case from controls. Correlation analysis was conducted between the concentration of PsEVs and the levels of ELISA proteins, including amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin, and additionally between the PsEVs-derived levels of amyloid-β (1–42) β1-42, p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin with ACE-III and MMSE values. ROC curve is a probability curve utilized to assess the accuracy of a test. The test’s ability to distinguish between groups is indicated by the area under the curve (AUC), which acts as a quantitative measure of separability. An outstanding test typically exhibits an AUC close to 1, signifying a high level of separability. Conversely, a subpar test tends to have an AUC closer to 0, indicating a poor ability to distinguish between the two classes.

Characterization and validation of isolated sEVs

PsEVs were isolated, characterized, and validated following Minimal Information for Studies of Extracellular Vesicles (MISEV) 2018 guidelines, which suggest a protocol for documenting work specifically with extracellular vesicles [ 56 ]. PsEVs from AMC, MCI, and AD subjects were morphologically characterized by transmission electron microscopy, and spherical lipid bi-layered vesicles were observed in the size range of sEVs (Fig.  1 A–C). In Fig.  1 D–F, the size distribution and concentration of PsEVs were observed in the size range of 30–200 nm in diameter by NTA, which is within the sEVs’ size range. The mean concentration of PsEVs in AMC, MCI, and AD patients were 5.12E + 10, 2.6E + 11, and 3.13E + 11 particle/ml, respectively, with higher concentrations of PsEVs in MCI and AD than in AMC ( p  < 0.0001) (Fig.  1 G). To differentiate AD from AMC, ROC and AUC analyses were performed where the AUC = 0.9748, with a sensitivity of 97.14% and specificity of 70.01% (Fig.  1 H), while in AMC versus MCI, AUC = 0.987, sensitivity of 96% and specificity of 86.67% (Fig.  1 I). Furthermore, we could also differentiate between MCI and AD, AUC = 0.629, sensitivity of 60%, and specificity of 56% (Fig.  1 J). Validation of PsEVs was done using immunoblot for sEVs-specific markers (CD63, CD81, and TSG101), which showed a significant increase in expressions in MCI and AD than in AMC (CD63, p  = 0.0489, 0.0478 (Additional File 1 : Fig. S1); CD81, p  = 0.0172, 0.0133 (Additional File 1 : Fig. S2); TSG101 p  = 0.0240, 0.0329 (Additional File 1 : Fig. S3)) for AD and MCI respectively (Fig.  2 A–D). Additionally, higher L1CAM (neuron-associated marker) expression was observed in MCI ( p  = 0.0100) and AD ( p  = 0.0184) (Additional File 1 : Fig. S4) compared to AMC (Fig.  2 E). All densitometric values were normalized against β-actin, which was used as a loading control (Additional File 1 : Fig. S7).

Isolation and analysis of PsEVs. The isolated PsEV morphology characterize by transmission electron microscopy from age-matched healthy controls (AMC) ( A ), mild-cognitive impairment (MCI) patients ( B ), and Alzheimer’s disease (AD) ( C ). The size distribution of PsEVs subpopulation (nm) versus the concentration (particle/ml) in AMC ( D ), individuals with MCI ( E ), and AD ( F ). Comparison of the sEVs concentration of AD, MCI, and AMC patients ( G ). Receiver operating characteristic (ROC) curve of PsEVs concentration in AMC v/s AD ( H ), AMC v/s MCI ( I ), and MCI v/s AD ( J ) (scale bar 100 nm)

Validation of PsEVs expression analysis of different markers in PsEVs in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease patients (AD) ( A ). Densitometric analysis of CD63 ( B ), densitometric analysis of CD81 ( C ), densitometric analysis of TSG101 ( D ), densitometric analysis of L1CAM ( E ), densitometric analysis of synaptophysin ( F ), densitometric analysis of GFAP ( G ), and densitometric analysis of amyloid-β (1–42) oligomer ( H ). All densitometric values were normalized against β-actin

Differential expression of amyloid-β (1–42), p-Tau, synaptophysin, GFAP markers, and levels of IL-1β and TNF-α in PsEVs

Using ELISA, we measured levels of amyloid-β (1–42) and p-Tau in PsEVs from AMC, MCI, and AD patients. The significant increase of amyloid-β (1–42) and p-Tau among the groups (Fig.  3 A–H). Amyloid-β (1–42) levels were higher in MCI compared to AMC ( p  < 0.0001) and more significant in AD than in MCI and AMC ( p  < 0.0001) (Fig.  3 A). Similarly, in comparison to MCI and AMC, p-Tau levels were significantly higher in AD ( p  < 0.0001) (Fig.  3 E). Similar levels of both markers were found in their Western blots (Fig.  2 ). We checked GFAP (astrocytic marker) and proinflammatory cytokines (TNF-α and IL-1β) to evaluate neuroinflammation. For proinflammatory markers, IL-1β and TNF-α levels showed a significant increase among the three groups ( p  < 0.0001 for IL-1β and TNF-α) (Fig.  3 I, M). When comparing AD to MCI and AMC, the GFAP concentration in PsEVs was significantly higher ( p  < 0.0001) (Fig.  3 Q). Similar trends were observed with Western blot analysis (Fig.  2 , Additional File 1 : Fig. S6, S9). Their elevated levels suggest prominent neuroinflammatory conditions contributing to potential neuronal damage. The elevated levels of these neuroinflammatory markers could be due to the activation of astrocytes and microglia and the subsequent increase in the secretion of PsEVs containing proinflammatory proteins, which suggests prominent neuroinflammatory conditions that may contribute to neuronal damage [ 57 ]. While synaptophysin concentration in PsEVs was downregulated in AD and MCI compared to AMC ( p  < 0.0001) in ELISA (Fig.  3 U), it shows synaptic dysfunction. We also checked synaptophysin levels in PsEVs in Western blotting, finding it was downregulated in AD compared to MCI and AMC ( p  = 0.0045, 0.0142), indicating synaptic degeneration in AD (Fig.  2 , Additional File 1 : Fig. S5). In MCI, synaptophysin levels did not significantly differ from AMC (Fig.  2 F). This aligns with synaptic loss in AD, reflected in lower neuropsychological test scores indicating more pronounced cognitive impairment compared to MCI and AMC.

PsEVs derived amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin protein concentration was measured. ELISA results in A shows levels of PsEVs amyloid-β (1–42) in AMC, MCI, and AD and receiver operating characteristic (ROC) curve of PsEVs concentration in AMC v/s MCI ( B ), AMC v/s AD ( C ), and MCI v/s AD ( D ). Similarly, p-Tau concentration in AMC, MCI, and AD ( E ), ROC curve of PsEVs concentration in AMC v/s MCI ( F ), AMC v/s AD ( G ), and MCI v/s AD ( H ). PsEVs derived IL-1β concentration in AMC, MCI and AD ( I ), ROC curve of PsEVs concentration in AMC v/s MCI ( J ), AMC v/s AD ( K ), and MCI v/s AD ( L ). PsEVs derived TNF-α concentration in AMC, MCI and AD ( M ), ROC curve of PsEVs concentration in AMC v/s MCI ( N ), AMC v/s AD ( O ), and MCI v/s AD ( P ). Similarly, GFAP concentration in AMC, MCI, and AD ( Q ), ROC curve of PsEVs concentration in AMC v/s MCI ( R ), AMC v/s AD ( S ), and MCI v/s AD ( T ). For PsEVs-derived synaptophysin concentration in AMC, MCI, and AD ( U ), ROC curve of PsEVs concentration in AMC v/s MCI ( V ), AMC v/s AD ( W ), and MCI v/s AD ( X ). Abbreviations: AMC, age-matched control; MCI, mild-cognitive impairment patients; AD, Alzheimer’s disease patients; TNF-α, tumor necrosis factor-alpha; GFAP, glial fibrillary acidic protein

Determining the diagnostic potential of PsEVs-derived amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP and synaptophysin

We observed the levels of amyloid-β (1–42) and p-Tau in PsEVs, where the increase in amyloid-β (1–42) and p-Tau levels underscores their potential as biomarkers of MCI and AD. The diagnostic efficacy of amyloid-β (1–42) by ROC analysis was observed for AMC vs MCI [AUC = 0.9347, p  < 0.0001, sensitivity (Sn) = 92%, specificity (Sp) = 80%] (Fig.  3 B), AMC vs AD (AUC = 0.9862, p  < 0.0001, Sn = 91.43%, Sp = 96.67%) (Fig.  3 C), and MCI vs AD (AUC of 0.8457, p  < 0.0001, Sn = 80%, and Sp = 72%) (Fig.  3 D). Similarly, diagnostic efficacy of p-Tau by ROC analysis was observed for AMC vs MCI (AUC = 0.8760, p  < 0.0001, Sn = 88%, Sp = 83.33%) (Fig.  3 F), AMC vs AD (AUC = 0.9757, p  < 0.0001, Sn = 94.29%, Sp = 83.33%) (Fig.  3 G), and MCI vs AD (AUC of 0.9074, p  < 0.0001, Sn = 88.57%, and Sp = 92%) (Fig.  3 H). So, we observed that the pathological hallmarks of the disease, viz., amyloid-β (1–42) and p-Tau levels, are increased significantly in PsEVs cargo of AD and MCI groups.

Furthermore, we also checked GFAP, TNF-α, IL-1β, and synaptophysin in PsEVs from MCI and AD groups. The diagnostic efficacy of IL-1β by ROC analysis was observed for AMC vs MCI (AUC = 0.9520, p  < 0.0001, Sn = 96%, Sp = 86.67%) (Fig.  3 J), AMC vs AD (AUC = 0.9857, p  < 0.0001, Sn = 94.29%, Sp = 90%) compared to AMC (Fig.  3 K), MCI vs AD (AUC = 0.9114, p  < 0.0001, Sn = 85.71%, Sp = 92%) (Fig.  3 L). Similarly, diagnostic efficacy of TNF-α by ROC analysis was observed for AMC vs MCI (AUC = 0.8920, p  < 0.0001, Sn = 84%, Sp = 80%) (Fig.  3 N), AMC vs AD (AUC = 0.9848, p  < 0.0001, Sn = 88.57%, Sp = 96.67%), and MCI vs AD (AUC = 0.9280, p  < 0.0001, Sn = 88.57%, Sp = 96%) (Fig.  3 P). So, we observed an elevated expression of neuroinflammatory markers within the PsEVs isolated from the AD and MCI groups.

GFAP is an activation marker of astroglia, and in AD, this activation is associated with synaptic dysfunction [ 58 ]. In PsEVs, the diagnostic efficacy of GFAP by ROC analysis was observed as for AMC vs MCI (AUC = 0.8393, p  < 0.0001, Sn = 88%, Sp = 76.67%) (Fig.  3 R), AMC vs. AD (AUC = 0.8814, p  < 0.0001, Sn = 91.43%, Sp = 76.67%) compared to AMC (Fig.  3 S); MCI vs AD (AUC = 0.7657, p  < 0.0001, Sn = 74.29%, Sp = 72%) (Fig.  3 T). In addition to this, we also checked the level of presynaptic protein, i.e., synaptophysin, within the PsEVs, as the level of synaptophysin correlates with cognitive decline in AD [ 59 ]. The diagnostic efficacy of synaptophysin by ROC analysis was observed as follows for AMC vs MCI (AUC = 0.8507, p  < 0.0001, Sn = 80%, Sp = 86.67%) (Fig.  3 V), AMC vs AD (AUC = 0.9738, p  < 0.0001, Sn = 88.57%, Sp = 96.67%) compared to AMC (Fig.  3 W); MCI vs AD (AUC = 0.8291, p  < 0.0001, Sn = 85.71%, and Sp = 68%) (Fig.  3 X). Table 2 summarizes all the AUC, sensitivity, specificity, and p -value values for all the PsEVs-derived proteins.

Correlations of PsEVs concentration values with protein levels of amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin in PsEVs

As we found an elevated number of PsEVs in the diseased condition, we performed a correlation analysis between PsEVs concentration and the amyloid-β (1–42) level, p-Tau, IL-1β, and TNF-α within PsEV. We found that PsEV concentration was positively correlated with all the protein levels except synaptophysin, which showed a negative correlation (Fig.  4 ). In these correlations, amyloid-β (1–42) was positively correlated ( r  = 0.7196, p  < 0.0001) (Fig.  4 A); p-Tau positively correlates ( r  = 0.7960, p  < 0.0001) (Fig.  4 B); IL-1β also showed positive correlation ( r  = 0.7220, p  < 0.0001) (Fig.  4 C); and TNF-α also showed positive correlation ( r  = 0.6473, p  < 0.0001) (Fig.  4 D). GFAP showed a weak correlation with PsEVs concentration ( r  = 0.5155, p  < 0.0001) (Fig.  4 E), and synaptophysin showed a weak correlation ( r  = 0.5752, p  < 0.0001) (Fig.  4 F).

Correlation analysis between PsEVs concentration and PsEVs derived AD pathology markers. The correlation between PsEVs concentration with the amyloid-β (1–42) ( A ), p-Tau ( B ), IL-1β ( C ), TNF-α ( D ), GFAP ( E ), and synaptophysin ( F ). Abbreviations: p-Tau, Phospho-Tau, TNF-α, tumor necrosis factor-alpha; GFAP, glial fibrillary acidic protein. Spearman correlation was used for correlation analysis

Correlations of ACE-III and MMSE scores with protein levels of amyloid-β (1–42), p-Tau, IL-1β, and TNF-α in PsEVs

We performed a correlation analysis between ACE-III and MMSE values with the level of amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin (Fig.  5 ). We found that ACE-III and MMSE values were negatively correlated with all the protein levels except synaptophysin, which showed a positive value for the correlation coefficient. ACE-III values showed a negative correlation with amyloid-β (1–42) ( r  =  − 0.5107, p  < 0.0001) (Fig.  5 A), p-Tau ( r  =  − 0.5055, p  < 0.0001) (Fig.  5 B), IL-1β ( r  =  − 0.5684, p  < 0.0001) (Fig.  5 C), and TNF-α ( r  =  − 0.6110, p  < 0.0001) (Fig.  5 D). ACE-III values showed a negative correlation with GFAP ( r  =  − 0.5024, p  < 0.0001) (Fig.  5 E), while synaptophysin showed a positive correlation ( r  = 0.5036, p  < 0.0001) (Fig.  5 F). In the case of MMSE, the values were as follows: for amyloid-β (1–42) ( r  =  − 0.5276, p  < 0.0001) (Fig.  5 G), p-Tau ( r  =  − 0.6081, p  < 0.0001) (Fig.  5 H), IL-1β ( r  =  − 0.5743, p  < 0.0001) (Fig.  5 I), TNF-α ( r  =  − 0.5522, p  < 0.0001) (Fig.  5 J), GFAP ( r  =  − 0.4596 p  = 0.0002) (Fig.  5 K), and synaptophysin ( r  = 0.5428, p  < 0.0001) (Fig.  5 L). Table 3 summarizes all the values of Correlation coefficients for all the PsEVs-derived proteins.

Correlation between neuropsychological test (ACE-III and MMSE) and PsEV-derived AD pathology markers. Amyloid-β (1–42) β, p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin protein concentration. A – F Correlation between ACE-III scores and amyloid-β (1–42) ( A ), pTau ( B ), IL-1β ( C ), TNF-α ( D ), GFAP ( E ), and synaptophysin ( F ) protein concentration. G – L A correlation between MMSE Score and amyloid-β (1–42) ( G ), p-Tau (H), IL-1β ( I ), TNF-α ( J ), GFAP ( K ), and synaptophysin ( L ) protein concentration. Abbreviations: ACE-III, Addenbrooke Cognitive Examination; MMSE, Mini-Mental State Examination; p-Tau, Phospho-Tau; TNF-α, tumor necrosis factor-alpha; GFAP, glial fibrillary acidic protein. Spearman correlation was used for correlation analysis

In this study, we aimed to investigate the capacity of PsEVs to mirror pathological processes linked to AD and MCI. sEVs are extensively documented in the propagation of pathological processes associated with neurodegenerative and metabolic disorders [ 60 ]. The increased secretion of sEVs, coupled with the transmission of disease-related pathologies through sEVs-associated cargo, makes sEVs a viable candidate for understanding the physiological state of their originating cells, which is reflected in sEVs cargo [ 61 ]. To isolate the PsEVs, we employed a combined approach involving chemical precipitation followed by ultrafiltration, which effectively eliminates co-precipitants and minute protein contaminants such as albumin and LDL. We employed the neuronal protein L1CAM as a marker to ascertain the neuronal origin, although there is a debate surrounding its specificity for neuronal origin [ 62 ]. Nevertheless, in our study, the L1CAM marker is used to check for protein markers and not to confirm L1CAM affinity-based isolation. A two-step filtration procedure was used to accompany the sEV isolation method in our study to ensure high purity. Spherical lipid bi-layered vesicles within the typical size range of small extracellular vesicles (30–150 nm) were observed across AD, MCI, and AMC subjects (Fig.  1 A–C). NTA was employed to study the size distribution of sEVs in AD, MCI, and AMC. We observed that the isolated PsEVs come within the size range of < 200 nm, and there was a notable increase in the number of particles in diseased conditions compared to the control group. (Fig.  1 D–G).

Validation using sEVs-specific markers (CD63, CD81, and TSG101) demonstrated a noteworthy upregulation in MCI and AD, indicating PsEVs numbers are increased in disease conditions (Fig.  2 A–D). Levels of sEV-specific markers in AD and MCI are elevated because PsEV numbers are increased in the disease condition. As documented by various studies in MCI and AD, there is an increase in cross-talk between different pathophysiological processes, which leads to an increase in sEVs number and sEVs specific marker as a cellular response to heightened cellular stress aggravating neuronal damage and synaptic dysfunction [ 33 , 63 , 64 ]. Neuroinflammation, a characteristic feature of AD and MCI, may lead to the release of sEVs with inflammatory markers. Synaptic dysfunction, evidenced by synaptic degeneration, could contribute to the increased sEV-specific markers, reflecting vesicle release in response to altered synaptic activity [ 9 , 65 ]. Additionally, cells undergoing stress might activate compensatory mechanisms, and the elevated sEV-specific markers could signify communication for potential repair or damage mitigation. Therefore, the increase in sEV-specific markers may be linked to the progression of neurodegenerative processes, indicating ongoing pathological changes in the brain as the disease progresses. Additionally, the elevated expression of L1CAM, a neuron-associated marker, in MCI and AD further strengthens the association between PsEVs and neurodegenerative processes (Fig.  2 E). Furthermore, our observations extend beyond AD and MCI, showing increased concentrations of sEVs in other health conditions where higher levels of these vesicles correlate with elevated levels of disease markers [ 53 , 54 , 55 ]. The results of our research provide valuable insight into the characterization, validation, and functional implications of plasma-derived small extracellular vesicles (PsEVs) in the context of AD and MCI. Our comprehensive analysis encompassed morphological, biochemical, and functional aspects, shedding light on the potential role of PsEVs as biomarkers and contributors to neurodegenerative processes.

For this purpose, we performed the ELISA of amyloid-β (1–42) in PsEVs, where we observed higher protein concentrations of amyloid-β (1–42) in MCI. At the same time, in AD, the concentration also significantly increased (Fig.  3 A). In a similar study by A. Manolopoulos et al. [ 66 ], they studied levels of Aβ42, total Tau, and pro-brain-derived neurotrophic factor (BDNF) in both plasma neuron-derived extracellular vesicles (NDEVs) and plasma. The study reported a lack of correlation between the plasma and NDEVs, substantiating concerns about levels of the Aβ42 and total Tau measured in plasma originating from non-CNS sources. Multiple studies support the involvement of extracellular vesicles (EVs) in AD pathogenesis, where Aβ and Tau are released in association with EVs, influencing neuronal cell death and trans-synaptic spreading of the disease [ 7 , 15 , 54 , 67 ]. A progressive elevation in PsEV levels of p-Tau was observed in MCI, reaching a significantly higher AD concentration (Fig.  3 E). Previous research has revealed that p-tau alone effectively differentiates Frontotemporal Dementia (FTD) from AD with high specificity [ 68 , 69 ]. In our study, the alone analysis of p-Tau and amyloid-β (1–42) proved effective in distinguishing patients with MCI from AMC (Table  2 ). Consequently, studies have reported that the elevation of p-Tau suggests the future likelihood of AD development [ 70 ]. This dual elevation in amyloid-β (1–42) and p-Tau levels highlights their potential utility as concurrent biomarkers associated with MCI and AD diagnosis, as indicated by our ROC analysis. Therefore, the investigation into PsEV content revealed significant alterations in key markers associated with AD pathology, viz., amyloid-β (1–42) and p-Tau, which are a well-established marker of AD and exhibit an elevated level in PsEVs from AD and MCI patients compared to AMC in our study.

Synaptic dysfunction is considered a core feature of AD. It is suggested to precede other pathophysiological events of AD rather than neurodegeneration, which manifests during the later stages of the disease [ 71 ]. Synaptic dysfunction interacts with other core pathophysiology events of AD, such as the amyloid-β cascade, tau pathology, and neuroinflammation, eventually progressing to irreversible neurodegeneration and atrophy [ 72 , 73 ]. In this context, the synchronized exchange of proteins involved in these pathological processes between the CNS and neuronal-derived sEVs highlights the potential of sEVs as reliable carriers of pathophysiological cascade occurring at the pathological site [ 74 ]. In Fig.  3 U, we observed downregulated synaptophysin levels, a synaptic vesicle marker, in AD PsEVs compared to MCI and AMC. This suggests synaptic degeneration, which has also been discussed in several studies [ 59 , 63 , 64 ]. Synaptic damage induced by amyloid-β deposition triggers a response from the glia to eliminate impaired synapses. As amyloid-β accumulates, the severity of synaptic dysfunction intensifies, leading to tau hyperphosphorylation and the formation of tau tangles. Our study’s findings contradict J. Utz et al. (2021), which showed increased synaptophysin levels in microvesicles isolated from cerebrospinal fluid (CSF) in AD [ 28 ]. This discrepancy could be due to different biofluid sources, cellular origins, or clearance mechanisms for synaptophysin in these compartments. Our study also differs from Utz J et al. (2021) as we have studied PsEVs compared to microvesicles; both differ in biogenesis, structure, and functions. Moreover, our study aligns with existing studies that reported lower synaptophysin levels in plasma neuronal-derived EVs. Goetzl et al. [ 75 ] investigated the synaptic protein levels in neuronal-derived exosomes in plasma (NDEs) of patients with FTD and AD, where the authors found significantly lower levels of synaptopodin, neurogranin, synaptophysin, and synaptotagmin-2 in both conditions compared to controls. Furthermore, our results also align with the overall synaptic loss seen in AD patient’s brains, where lower levels of synaptophysin in the hippocampus have been reported to correlate with cognitive decline in AD [ 59 ]. Our study found that no significant difference in synaptophysin levels between MCI and AMC was observed, indicating that synapse dysfunction is more pronounced due to neuronal loss in the advanced disease stage, and its indication is reflected in PsEVs. Since the PsEVs pool also contains neuronal-derived EVs, we interpolate that the reduction in synaptic proteins in brain tissue is reflected in our results.

IL-1β, a potent immunomodulating cytokine, has previously been identified as a trigger for various inflammatory mediators in astrocytes and neurons [ 76 ]. Consistent evidence from post-mortem AD brain studies indicates the prevalent overexpression of IL-1β, with immunohistochemical analyses revealing its localization to microglia around plaques [ 77 ]. Moreover, pro-inflammatory markers (IL-1β and TNF-α) were significantly higher in PsEVs from AD and MCI subjects, as evidenced by ELISA and Western blot findings in our study (Fig. 3 I and M). Table 3 summarizes the correlation between PsEVs and neuroinflammatory markers. IL-1β plays a direct role in the pathophysiological changes associated with AD owing to its specific expression in the vicinity of plaques, and this localization suggests IL-1β as a mediator in the formation of plaques and tangles, thereby contributing to AD pathology [ 65 ]. TNF-α, another pro-inflammatory cytokine primarily secreted by activated macrophages and microglia, is recognized for its dual role in promoting cell survival and death in the central nervous system [ 78 , 79 ].

The cytoskeletal GFAP is found in astrocytic cells [ 80 ]. Increased plasma GFAP levels could result from “reactive astrogliosis,” another term for aberrant astrocytic function brought on by damage to neurons [ 81 ]. According to research on animal and cell models, reactive astrocytes encircle and penetrate amyloid-β plaques, contributing to the amyloid-β pathological process [ 82 , 83 ]. Research has demonstrated a correlation between amyloid-β burden, cognitive decline, and plasma GFAP [ 83 ]. PsEVs of GFAP were elevated in AD [ 27 ] and MCI (Fig.  3 Q). It is well known that sEVs play a pivotal role in the progression of disease pathologies in neurodegenerative and metabolic diseases [ 33 , 84 ]. The high levels of neuro-inflammatory markers (GFAP, TNF-α, and IL-1β) in PsEVs from MCI and AD subjects suggest a potential role of PsEVs in neuroinflammation. This activation of astrocytes and microglia precedes increased secretion of pro-inflammatory PsEVs and may contribute to neuronal damage and progressive cognitive impairment. Diseased conditions involve an increased secretion of sEVs and the cargo they carry, including pathological hallmark proteins or immunomodulatory cytokines [ 33 ].

Correlation analyses unveiled positive associations between PsEVs concentration and the protein levels of amyloid-β (1–42), p-Tau, IL-1β, TNF-α, GFAP, and synaptophysin (Fig.  4 ). Furthermore, our study also analyzed the correlation between cognitive examination scores (ACE-III and MMSE) and PsEV-associated protein levels (Fig.  5 ). The negative correlations observed imply that lower cognitive scores align with elevated levels of amyloid-β (1–42), p-Tau, IL-1β, and TNF-α in PsEVs Table  3 . This implies a strong connection between PsEV biomarkers and cognitive decline, reinforcing that PsEVs could serve as valuable diagnostic and prognostic tools. These findings underscore the potential of PsEVs as reliable disease progression and pathology indicators. The robust correlations further support the hypothesis that PsEVs may actively participate in disseminating neurodegenerative signals.

Our study extensively studied the multiple pathophysiological processes associated with AD by checking the protein levels involved in these processes within PsEVs, including amyloid-β (1–42), p-Tau, neuroinflammatory markers (IL-1β, TNF-α, GFAP), and synaptic protein levels. This comprehensive approach enhances diagnostic accuracy by considering the synergistic effects of these processes, providing valuable insights into disease progression from MCI to AD. We have also performed a systematic comparison with MCI, which was lacking in previous studies. We observed a significant correlation between these investigated protein levels within PsEVs and neuropsychological tests, thus filling a research gap addressing the clinical relevance of these dysregulated pathophysiological processes. The observed downregulated synaptophysin levels in AD PsEVs compared to MCI and control subjects shed light on the combined role of neuroinflammation and proteinopathy in the cognitive decline observed as the disease progresses. This finding suggests that PsEVs may reflect synaptic degeneration, opening avenues for further exploration into the role of PsEVs in synaptic damage and dysfunction in neurodegenerative diseases.

Our study provides a multifaceted examination of PsEVs, offering compelling evidence of their potential as biomarkers and functional contributors in AD. We have comprehensively discussed the synergistic role of synaptic dysfunction and neuroinflammation and their association with amyloid-β and tau pathologies within the PsEVs in AD progression. The pathophysiological conditions in the MCI and AD brain are reflected in PsEVs, as observed by the increased concentration of PsEVs containing disease-associated markers and markers for synaptic dysfunction and neuroinflammation. Therefore, the PsEVs can be exploited to understand the pathophysiological process involved in the progression and severity of MCI and AD.

Availability of data and materials

No datasets were generated or analysed during the current study.

Abbreviations

Addenbrooke Cognitive Examination

• Alzheimer’s disease

Age-matched controls

Glial fibrillary acidic protein

Interleukin-1β

• Mild cognitive impairment

Mini-Mental State Examination

Phospho-Tau

Tumor necrosis factor-alpha

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Acknowledgements

We express our gratitude to the Electron Microscopy Facility, Sophisticated Analytical Instrumentation Facility (SAIF) at AIIMS, New Delhi.

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S.K. conceptualized and designed the study. R.S., S.R., P.S.B., and S.Z. performed the acquisition and analysis of data. R.S., S.R., P.S.B., S.Z., and P.K.G. performed the drafting the text or preparing the figures. R.S., S.R., P.S.B., N.R., K.D., K.K.I., P.C., V.V.Y, G.P.M., F.N., and S.K. performed the initial revision and proofreading of the manuscript. All authors read and approved the final manuscript.

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12916_2024_3475_moesm1_esm.docx.

Additional file 1: Fig S1. [CD63 expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S2. [CD81 expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S3. [TSG101 expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S4. [L1CAM expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S5. [Synaptophysin (SYP) expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S6. [Glial Fibrillary Acidic Protein (GFAP) expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S7. [β-Actin expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S8. [Amyloidβ-42 Oligomer expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S9. [IL1β (A) and TNFα (B) expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis]. Fig S10. [p-Tau expression in age-matched controls (AMC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) and their densitometric analysis].

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Singh, R., Rai, S., Bharti, P.S. et al. Circulating small extracellular vesicles in Alzheimer’s disease: a case–control study of neuro-inflammation and synaptic dysfunction. BMC Med 22 , 254 (2024). https://doi.org/10.1186/s12916-024-03475-z

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Case Report of a 63-Year-Old Patient With Alzheimer Disease and a Novel Presenilin 2 Mutation

Wells, Jennie L. BSc, MSc, MD, FACP, FRCPC, CCRP *,† ; Pasternak, Stephen H. MD, PhD, FRCPC †,‡,§

* Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine and Dentistry, Western University

† St. Joseph’s Health Care London—Parkwood Institute

‡ Molecular Medicine Research Group, Robarts Research Institute

§ Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada

The authors declare no conflicts of interest.

Reprints: Jennie L. Wells, BSc, MSc, MD, FACP, FRCPC, CCRP, Department of Medicine, Division of Geriatric Medicine, St. Joseph’s Health Care London—Parkwood Institute, Room A2-129, P.O. Box 5777 STN B, London, ON, Canada N6A 4V2 (e-mail: [email protected] ).

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/

Early onset Alzheimer disease (EOAD) is a neurodegenerative dementing disorder that is relatively rare (<1% of all Alzheimer cases). Various genetic mutations of the presenilin 1 ( PSEN1 ) and presenilin 2 ( PSEN2 ) as well as the amyloid precursor protein (APP) gene have been implicated. Mutations of PSEN1 and PSEN2 alter γ-secretase enzyme that cleaves APP resulting in increase in the relative amount of the more amyloidogenic Aβ42 that is produced. 1

PSEN2 has been less studied than PSEN1 and fewer mutations are known. Here, we report a case of a 63-year-old woman (at the time of death) with the clinical history consistent with Alzheimer D, an autopsy with brain histopathology supporting Alzheimer disease (AD), congophylic angiopathy, and Lewy Body pathology, and whose medical genetic testing reveals a novel PSEN2 mutation of adenosine replacing cytosine at codon 222, nucleotide position 665 (lysine replacing threonine) that has never been previously reported. This suggests that genetic testing may be useful in older patients with mixed pathology.

CASE REPORT

The patient was referred to our specialty memory clinic at the age of 58 with a 2-year history of repetitiveness, memory loss, and executive function loss. Magnetic resonance imaging scan at age 58 revealed mild generalized cortical atrophy. She is white with 2 years of postsecondary education. Retirement at age 48 from employment as a manager in telecommunications company was because family finances allowed and not because of cognitive challenges with work. Progressive cognitive decline was evident by the report of deficits in instrumental activities of daily living performance over the past 9 months before her initial consultation in the memory clinic. Word finding and literacy skills were noted to have deteriorated in the preceding 6 months according to her spouse. Examples of functional losses were being slower in processing and carrying out instructions, not knowing how to turn off the stove, and becoming unable to assist in boat docking which was the couple’s pastime. She stopped driving a motor vehicle about 6 months before her memory clinic consultation. Her past medical history was relevant for hypercholesterolemia and vitamin D deficiency. She had no surgical history. She had no history of smoking, alcohol, or other drug misuse. Laboratory screening was normal. There was no first-degree family history of presenile dementia. Neurocognitive assessment at the first clinic visit revealed a Mini Mental State Examination (MMSE) score of 14/30; poor verbal fluency (patient was able to produce only 5 animal names and 1 F-word in 1 min) as well as poor visuospatial and executive skills ( Fig. 1 ). She had fluent speech without semantic deficits. Her neurological examination was pertinent for normal muscle tone and power, mild ideomotor apraxia on performing commands for motor tasks with no suggestion of cerebellar dysfunction, normal gait, no frontal release signs. Her speech was fluent with obvious word finding difficulties but with no phonemic or semantic paraphrasic errors. Her general physical examination was unremarkable without evidence of presenile cataracts. She had normal hearing. There was no evidence of depression or psychotic symptoms.

At the time of the initial assessment, her mother was deceased at age 79 after a hip fracture with a history long-term smoking and idiopathic pulmonary fibrosis. Her family believes that there is possible German and Danish descent on her father’s side. Her father was alive and well at age 80 at the time of her presentation with a history coronary artery disease. He is still alive and well with no functional or cognitive concerns at age 87 at the time of writing this report. Her paternal grandfather died at approximately age 33 of appendicitis with her paternal grandmother living with mild memory loss but without known dementia or motor symptoms until age 76, dying after complications of abdominal surgery. Her paternal uncle was diagnosed with Parkinson disease in his 40s and died at age 58. Her maternal grandmother was reported to be functionally intact, but mildly forgetful at the time of her death at age 89. The maternal grandfather had multiple myocardial infarctions and died of congestive heart failure at age 75. She was the eldest of 4 siblings (ages 44 to 56 at the time of presentation); none had cognitive problems. She had no children.

Because of her young age and clinical presentation with no personality changes, language or motor change, nor fluctuations, EOAD was the most likely clinical diagnosis. As visuospatial challenges were marked at her first visit and poor depth perception developing over time, posterior cortical variant of AD was also on the differential as was atypical presentation of frontotemporal dementias. Without fluctuations, Parkinsonism, falls, hallucinations, or altered attention, Lewy Body dementia was deemed unlikely. After treatment with a cholinesterase inhibitor, her MMSE improved to 18/30, tested 15 months later with stability in function. Verbal fluency improved marginally with 7 animals and 3 F-words. After an additional 18 months, function and cognition declined (MMSE=13/30) so memantine was added. The stabilizing response to the cholinesterase inhibitor added some degree of confidence to the EOAD diagnosis. In the subsequent 4 years, she continued to decline in cognition and function such that admission to a care facility was required with associated total dependence for basic activities of daily living. Noted by family before transfer to the long-term care facility were episodic possible hallucinations. It was challenging to know if what was described was misinterpretation of objects in view or a true hallucination. During this time, she developed muscle rigidity, motor apraxias, worsening perceptual, and language skills and became dependent for all activities of daily livings. At the fourth year of treatment, occasional myoclonus was noted. She was a 1 person assist for walking because of increased risk of falls. After 1 year in the care home, she was admitted to the acute care hospital in respiratory distress. CT brain imaging during that admission revealed marked generalized global cortical atrophy and marked hippocampal atrophy ( Fig. 2 ). She died at age 63 of pneumonia. An autopsy was performed confirming the cause of death and her diagnosis of AD, showing numerous plaques and tangles with congophilic amyloid angiopathy. In addition, there was prominent Lewy Body pathology noted in the amygdala.

Three years before her death informed consent was obtained from the patient and family to perform medical genetic testing for EOAD. The standard panel offered by the laboratory was selected and included PSEN1 , PSEN2 , APP, and apoE analysis. Tests related to genes related to frontotemporal dementia were not requested based on clinical presentation and clinical judgement. This was carried out with blood samples and not cerebrospinal fluid because of patient, family, and health provider preference. The results revealed a novel PSEN2 mutation with an adenosine replacing cytosine at nucleotide position 665, codon 222 [amino acid substation of lysine for threonine at position 221 (L221T)]. This PSEN2 variant was noted to be novel to the laboratory’s database, noting that models predicted that this variant is likely pathogenic. The other notable potentially significant genetic finding is the apoliprotein E genotype was Є 3/4 .

β-amyloid (Aβ) is a 38 to 43 amino acid peptide that aggregates in AD forming toxic soluble oligomers and insoluble amyloid fibrils which form plaques. Aβ is produced by the cleavage of the APP first by an α-secretase, which produces a 99 amino acid C-terminal fragment of APP, and then at a variable “gamma” position by the γ-secretase which releases the Aβ peptide itself. It is this second γ-cleavage which determines the length and therefore the pathogenicity of the Aβ peptides, with 42 amino acid form of Aβ having a high propensity to aggregate and being more toxic.

The γ-secretase is composed of at least 4 proteins, mAph1, PEN2, nicastrin, and presenilin . Of these proteins, presenilin has 2 distinct isoforms ( PSEN1 and PSEN2 ), which contain the catalytic site responsible for the γ-cleavage. PSEN mutants are the most common genetic cause of AD with 247 mutations described in PSEN1 and 48 mutations described in PSEN2 (Alzgene database; www.alzforum.org/mutations ). PSEN2 mutations are reported to be associated with AD of both early onset and variable age onset as well as with other neurodegenerative disorders such as Lewy Body dementia, frontotemporal dementia, Parkinson dementia, and posterior cortical atrophy. 2–4 In addition, PSEN2 has associations with breast cancer and dilated cardiomyopathy. 3

PSEN2 mutants are believed to alter the γ-secretase cleavage of APP increasing the relative amount of the more toxic Aβ42. The mean age of onset in PSEN2 mutations, is 55.3 years but the range of onset is surprisingly wide, spanning 39 to 83 years. Over 52% of cases are over 60 years. All cases have extensive amyloid plaque and neurofibrillary tangles, and many have extensive alpha-synuclein pathology as well. 5

In considering the novelty of this reported PSEN2 mutation, a literature search of Medline, the Alzgene genetic database of PSEN2 and the Alzheimer Disease and Frontotemporal Dementia Mutation Databases (AD&FTMD) were completed ( www.molgen.vib-ua.be/ADMutations ). The mutation presented here (L221T) has never been described before.

Although this mutation has not been described, we believe that it is highly likely to be pathogenic. This mutation is not conservative, as it replaces a lysine residue which is positively charged with threonine which is an uncharged polar, hydrophilic amino acid. The mutation itself occurs in a small cytoplasmic loop between transmembrane domain 4 and 5, which is conserved in the PSEN1 gene, and in PSEN2 is highly conserved across vertebrates, including birds and zebrafish all the way to Caenorhabditis elegans , but differs in Drosophila melanogaster (fruit fly) ( Fig. 3 ). We examined this mutation using several computer algorithms which examine the likelihood that a mutation will not be tolerated. Both SIFT ( http://sift.bii.a-star.edu.sg ) and PolyPhen-2.2.2 (HumVar) ( www.bork.embl-heidelberg.de/PolyPhen ) predicts that this variant is pathogenic. Interestingly, it is noted that PSEN1 mutations after amino acid 200 develop amyloid angiopathy. 5,7

This patient also had an additional risk factor for AD, being a heterozygote for the apoЄ4 allele. Among other mechanisms, its presence reduces clearance of Aβ42 from the brain and increases glial activation. 8 Although the apoЄ4 allele is known to lower the age of onset of dementia in late onset AD, it has not been clearly shown to influence age of onset of EOAD in a limited case series. 9 It should be noted that heterozygote state may have contributed to an acceleration of her course given the known metabolism of apoЄ4 and its association with accelerated cerebral amyloid and known reduction in age of onset. 10

Given that there is no definite family history of autosomal dominant early onset dementia, it is likely that her PSEN2 mutation was a new random event. With the unusually wide age of onset it is conceivable that one of her parents could still harbor this PSEN2 mutation. The patient’s father, however, is currently 87 and living independently at the time of writing this manuscript, making him highly unlikely to be an EOAD carrier. Nonpaternity is an alternate explanation for the lack of known first-degree relative with EOAD; however, this is deemed unlikely by the family member who provided the supplemental history. Her mother died at age 79, so she could conceivably carry our mutation but we do not have access to this genetic material. Without extensive testing of many family members it would be impossible to speculate about autosomal recessive form of gene expression. In addition, the genetic testing requested was limited to presenilins , APP, and apoE mutations. Danish heritage may add Familial Danish dementia as a remote consideration; however, Familial Danish dementia has a much different clinical presentation with long tract signs, cerebellar dysfunction, onset in the fourth decade as well as hearing loss and cataracts at a young age. 11 This disease has high autosomal dominant penetration which also makes it less likely in the patient’s context. This specific gene (chromosome 13) was not tested. The autopsy findings do not support this possibility. There are reports of Familial AD pedigrees in Germany, including a Volga pedigree with PSEN141I mutation in exon 5, but this is clearly separate from our mutation which is in exon 7. Our mutation was also not observed in a recent cohort of 23 German individuals with EOAD which underwent whole genome sequencing, but did find 2 carriers of the Volga pedigree. It is also possible that both the PSEN2 mutation and the ApoE genotype contributed to her disease and early onset presentation. This case illustrates the multiple pathology types which occur in individuals bearing PSEN2 mutations, and highlights the later ages in which patients can present with PSEN2 mutations. 12

ACKNOWLEDGMENT

The authors acknowledge Gwyneth Duhn, RN, BNSc, MSc, for her support of this paper.

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• Spring 2024 | VOL. 36, NO. 2 CURRENT ISSUE pp.A4-174
• Winter 2024 | VOL. 36, NO. 1 pp.A5-81

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Case Study 1: A 55-Year-Old Woman With Progressive Cognitive, Perceptual, and Motor Impairments

• Scott M. McGinnis , M.D. ,
• Andrew M. Stern , M.D., Ph.D. ,
• Jared K. Woods , M.D., Ph.D. ,
• Matthew Torre , M.D. ,
• Mel B. Feany , M.D., Ph.D. ,
• Michael B. Miller , M.D., Ph.D. ,
• David A. Silbersweig , M.D. ,
• Seth A. Gale , M.D. ,
• Kirk R. Daffner , M.D.

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CASE PRESENTATION

A 55-year-old right-handed woman presented with a 3-year history of cognitive changes. Early symptoms included mild forgetfulness—for example, forgetting where she left her purse or failing to remember to retrieve a take-out order her family placed—and word-finding difficulties. Problems with depth perception affected her ability to back her car out of the driveway. When descending stairs, she had to locate her feet visually in order to place them correctly, such that when she carried her dog and her view was obscured, she had difficulty managing this activity. She struggled to execute relatively simple tasks, such as inserting a plug into an outlet. She lost the ability to type on a keyboard, despite being able to move her fingers quickly. Her symptoms worsened progressively for 3 years, over which time she developed a sad mood and anxiety. She was laid off from work as a nurse administrator. Her family members assumed responsibility for paying her bills, and she ceased driving.

Her past medical history included high blood pressure, Hashimoto’s thyroiditis with thyroid peroxidase antibodies, remote history of migraine, and anxiety. Medications included mirtazapine, levothyroxine, calcium, and vitamin D. She had no history of smoking, drinking alcohol, or recreational drug use. There was no known family history of neurologic diseases.

What Are Diagnostic Considerations Based on the History? How Might a Clinical Examination Help to Narrow the Differential Diagnosis?

Insidious onset and gradual progression of cognitive symptoms over the course of several years raise concern for a neurodegenerative disorder. It is helpful to consider whether or not the presentation fits with a recognized neurodegenerative clinical syndrome, a judgment based principally on familiarity with syndromes and pattern recognition. Onset of symptoms before age 65 should prompt consideration of syndromes in the spectrum of frontotemporal dementia (FTD) and atypical (nonamnesic) presentations of Alzheimer’s disease (AD) ( 1 , 2 ). This patient’s symptoms reflect relatively prominent early dysfunction in visual-spatial processing and body schema, as might be observed in posterior cortical atrophy (PCA), although the history also includes mention of forgetfulness and word-retrieval difficulties. A chief goal of the cognitive examination would be to survey major domains of cognition—attention, executive functioning, memory, language, visual-spatial functioning, and higher somatosensory and motor functioning—to determine whether any domains stand out as more prominently affected. In addition to screening for evidence of focal signs, a neurological examination in this context should assess for evidence of parkinsonism or motor neuron disease, which can coexist with cognitive changes in neurodegenerative presentations.

The patient’s young age and history of Hashimoto’s thyroiditis might also prompt consideration of Hashimoto’s encephalopathy (HE; also known as steroid-responsive encephalopathy), associated with autoimmune thyroiditis. This syndrome is most likely attributable to an autoimmune or inflammatory process affecting the central nervous system. The time course of HE is usually more subacute and rapidly progressive or relapsing-remitting, as opposed to the gradual progression over months to years observed in the present case ( 3 ).

The patient’s mental status examination included the Montreal Cognitive Assessment (MoCA), a brief global screen of cognition ( 4 ), on which she scored 12/30. There was evidence of dysfunction across multiple cognitive domains ( Figure 1 ). She was fully oriented to location, day, month, year, and exact date. When asked to describe a complex scene from a picture in a magazine, she had great difficulty doing so, focusing on different details but having trouble directing her saccades to pertinent visual information. She likewise had problems directing her gaze to specified objects in the room and problems reaching in front of her to touch target objects in either visual field. In terms of other symptoms of higher order motor and somatosensory functioning, she had difficulty demonstrating previously learned actions—for example, positioning her hand correctly to pantomime holding a brush and combing her hair. She was confused about which side of her body was the left and which was the right. She had difficulty with mental calculations, even relatively simple ones such as “18 minus 12.” In addition, she had problems writing a sentence in terms of both grammar and the appropriate spacing of words and letters on the page.

FIGURE 1. Selected elements of a 55-year-old patient’s cognitive examination at presentation a

a BNT-15=Boston Naming Test (15-Item); MoCA=Montreal Cognitive Assessment.

On elementary neurologic examination she had symmetrically brisk reflexes, with spread. She walked steadily with a narrow base, but when asked to pass through a doorway she had difficulty finding her way through it and bumped into the door jamb. Her elemental neurological examination was otherwise normal, including but not limited to brisk, full-amplitude vertical eye movements, normal visual fields, no evidence of peripheral neuropathy, and no parkinsonian signs such as slowness of movement, tremor, or rigidity.

How Does the Examination Contribute to Our Understanding of Diagnostic Considerations? What Additional Tests or Studies Are Indicated?

The most prominent early symptoms and signs localize predominantly to the parietal association cortex: The patient has impairments in visual construction, ability to judge spatial relationships, ability to synthesize component parts of a visual scene into a coherent whole (simultanagnosia or asimultagnosia), impaired visually guided reaching for objects (optic ataxia), and most likely impaired ability to shift her visual attention so as to direct saccades to targets in her field of view (oculomotor apraxia or ocular apraxia). The last three signs constitute Bálint syndrome, which localizes to disruption of dorsal visual networks (i.e., dorsal stream) with key nodes in the posterior parietal and prefrontal cortices bilaterally ( 5 ). She has additional salient symptoms and signs suggesting left inferior parietal dysfunction, including ideomotor limb apraxia and elements of Gerstmann syndrome, which comprises dysgraphia, acalculia, left-right confusion, and finger agnosia ( 6 ). Information was not included about whether she was explicitly examined for finger agnosia, but elements of her presentation suggested a more generalized disruption of body schema (i.e., her representation of the position and configuration of her body in space). Her less prominent impairment in lexical-semantic retrieval evidenced by impaired confrontation naming and category fluency likely localizes to the language network in the left hemisphere. Her impairments in attention and executive functions have less localizing value but would plausibly arise in the context of frontoparietal network dysfunction. At this point, it is unclear whether her impairment in episodic memory mostly reflects encoding and activation versus a rapid rate of forgetting (storage), as occurs in temporolimbic amnesia. Regardless, it does not appear to be the most salient feature of her presentation.

This localization, presenting with insidious onset and gradual progression, is characteristic of a PCA syndrome. If we apply consensus clinical diagnostic criteria proposed by a working group of experts, we find that our patient has many of the representative features of early disturbance of visual functions plus or minus other cognitive functions mediated by the posterior cerebral cortex ( Table 1 ) ( 7 ). Some functions such as limb apraxia also occur in corticobasal syndrome (CBS), a clinical syndrome defined initially in association with corticobasal degeneration (CBD) neuropathology, a 4-repeat tauopathy characterized by achromatic ballooned neurons, neuropil threads, and astrocytic plaques. However, our patient lacks other suggestive features of CBS, including extrapyramidal motor dysfunction (e.g., limb rigidity, bradykinesia, dystonia), myoclonus, and alien limb phenomenon ( Table 1 ) ( 8 ).

TABLE 1. Clinical features and neuropathological associations of posterior cortical atrophy and corticobasal syndrome

a Consensus diagnostic criteria for posterior cortical atrophy per Crutch et al. ( 7 ) require at least three cognitive features and relative sparing of anterograde memory, speech-nonvisual language functions, executive functions, behavior, and personality. Diagnostic criteria for probable corticobasal syndrome per Armstrong et al. ( 8 ) require asymmetric presentation of at least two motor features and at least two higher cortical features. AD=Alzheimer’s disease; CBD=corticobasal degeneration; FDG-PET=[ 18 ]F-fluorodexoxyglucose positron emission tomography; JCD=Jakob-Creutzfeldt disease; LBD=Lewy body disease; PSP=progressive supranuclear palsy; SPECT=single-photon emission computed tomography; TDP=TDP–43 proteinopathy.

TABLE 1. Clinical features and neuropathological associations of posterior cortical atrophy and corticobasal syndrome a

In addition to a standard laboratory work-up for cognitive impairment, it is important to determine whether imaging of the brain provides evidence of neurodegeneration in a topographical distribution consistent with the clinical presentation. A first step in most cases would be to obtain an MRI of the brain that includes a high-resolution T 1 -weighted MRI sequence to assess potential atrophy, a T 2 /fluid-attenuated inversion recovery (FLAIR) sequence to assess the burden of vascular disease and rule out less likely etiological considerations (e.g., infection, autoimmune-inflammatory, neoplasm), a diffusion-weighted sequence to rule out subacute infarcts and prion disease (more pertinent to subacute or rapidly progressive cases), and a T 2 *-gradient echo or susceptibility weighted sequence to examine for microhemorrhages and superficial siderosis.

A lumbar puncture would serve two purposes. First, it would allow for the assessment of inflammation that might occur in HE, as approximately 80% of cases have some abnormality of CSF (i.e., elevated protein, lymphocytic pleiocytosis, or oligoclonal bands) ( 9 ). Second, in selected circumstances—particularly in cases with atypical nonamnesic clinical presentations or early-onset dementia in which AD is in the neuropathological differential diagnosis—we frequently pursue AD biomarkers of molecular neuropathology ( 10 , 11 ). This is most frequently accomplished with CSF analysis of amyloid-β-42, total tau, and phosphorylated tau levels. Amyloid positron emission tomography (PET) imaging, and most recently tau PET imaging, represent additional options that are approved by the U.S. Food and Drug Administration for clinical use. However, insurance often does not cover amyloid PET and currently does not reimburse tau PET imaging. [ 18 ]-F-fluorodeoxyglucose (FDG) PET and perfusion single-photon emission computed tomography imaging may provide indirect evidence for AD neuropathology via a pattern of hypometabolism or hypoperfusion involving the temporoparietal and posterior cingulate regions, though without molecular specificity. Pertinent to this case, a syndromic diagnosis of PCA is most commonly associated with underlying AD neuropathology—that is, plaques containing amyloid-β and neurofibrillary tangles containing tau ( 12 – 15 ).

The patient underwent MRI, demonstrating a minimal burden of T 2 /FLAIR hyperintensities and some degree of bilateral parietal volume loss with a left greater than right predominance ( Figure 2A ). There was relatively minimal medial temporal volume loss. Her basic laboratory work-up, including thyroid function, vitamin B 12 level, and treponemal antibody, was normal. She underwent a lumbar puncture; CSF studies revealed normal cell counts, protein, and glucose levels and low amyloid-β-42 levels at 165.9 pg/ml [>500 pg/ml] and elevated total and phosphorylated tau levels at 1,553 pg/ml [<350 pg/ml] and 200.4 pg/ml [<61 pg/ml], respectively.

FIGURE 2. MRI brain scan of the patient at presentation and 4 years later a

a Arrows denote regions of significant atrophy.

Considering This Additional Data, What Would Be an Appropriate Diagnostic Formulation?

For optimal clarity, we aim to provide a three-tiered approach to diagnosis comprising neurodegenerative clinical syndrome (e.g., primary amnesic, mixed amnesic and dysexecutive, primary progressive aphasia), level of severity (i.e., mild cognitive impairment; mild, moderate or severe dementia), and predicted underlying neuropathology (e.g., AD, Lewy body disease [LBD], frontotemporal lobar degeneration) ( 16 ). This approach avoids problematic conflations that cause confusion, for example when people equate AD with memory loss or dementia, whereas AD most strictly describes the neuropathology of plaques and tangles, regardless of the patient’s clinical symptoms and severity. This framework is important because there is never an exclusive, one-to-one correspondence between syndromic and neuropathological diagnosis. Syndromes arise from neurodegeneration that starts focally and progresses along the anatomical lines of large-scale brain networks that can be defined on the basis of both structural and functional connectivity, a concept detailed in the network degeneration hypothesis ( 17 ). It is important to note that neuropathologies defined on the basis of specific misfolded protein inclusions can target more than one large-scale network, and any given large-scale network can degenerate in association with more than one neuropathology.

The MRI results in this case support a syndromic diagnosis of PCA, with a posteriorly predominant pattern of atrophy. Given the patient’s loss of independent functioning in instrumental activities of daily living (ADLs), including driving and managing her finances, the patient would be characterized as having a dementia (also known as major neurocognitive disorder). The preservation of basic ADLs would suggest that the dementia was of mild severity. The CSF results provide supportive evidence for AD amyloid plaque and tau neurofibrillary tangle (NFT) neuropathology over other pathologies potentially associated with PCA syndrome (i.e., CBD, LBD, TDP-43 proteinopathy, and Jakob-Creutzfeldt disease) ( 13 , 14 ). The patient’s formulation would thus be best summarized as PCA at a level of mild dementia, likely associated with underlying AD neuropathology.

The patient’s symptoms progressed. One year after initial presentation, she had difficulty locating the buttons on her clothing or the food on her plate. Her word-finding difficulties worsened. Others observed stiffness of her right arm, a new symptom that was not present initially. She also had decreased ability using her right hand to hold everyday objects such as a comb, a brush, or a pen. On exam, she was noted to have rigidity of her right arm, impaired dexterity with her right hand for fine motor tasks, and a symmetrical tremor of the arms, apparent when holding objects or reaching. Her right hand would also intermittently assume a flexed, dystonic posture and would sometime move in complex ways without her having a sense of volitional control.

Four to 5 years after initial presentation, her functional status declined to the point where she was unable to feed, bathe, or dress herself. She was unable to follow simple instructions. She developed neuropsychiatric symptoms, including compulsive behaviors, anxiety, and apathy. Her right-sided motor symptoms progressed; she spent much of the time with her right arm flexed in abnormal postures or moving abnormally. She developed myoclonus of both arms. Her speech became slurred and monosyllabic. Her gait became less steady. She underwent a second MRI of the brain, demonstrating progressive bilateral atrophy involving the frontal and occipital lobes in addition to the parietal lobes and with more left > right asymmetry than was previously apparent ( Figure 2B ). Over time, she exhibited increasing weight loss. She was enrolled in hospice and ultimately passed away 8 years from the onset of symptoms.

Does Information About the Longitudinal Course of Her Illness Alter the Formulation About the Most Likely Underlying Neuropathological Process?

This patient developed clinical features characteristic of corticobasal syndrome over the longitudinal course of her disease. With time, it became apparent that she had lost volitional control over her right arm (characteristic of an alien limb phenomenon), and she developed signs more suggestive of basal ganglionic involvement (i.e., limb rigidity and possible dystonia). This presentation highlights the frequent overlap between neurodegenerative clinical syndromes; any given person may have elements of more than one syndrome, especially later in the course of a disease. In many instances, symptomatic features that are less prominent at presentation but evolve and progress can provide clues regarding the underlying neuropathological diagnosis. For example, a patient with primary progressive apraxia of speech or nonfluent-agrammatic primary progressive aphasia could develop the motor features of a progressive supranuclear palsy (PSP) clinical syndrome (e.g., supranuclear gaze impairment, axial rigidity, postural instability), which would suggest underlying PSP neuropathology (4-repeat tauopathy characterized by globose neurofibrillary tangles, tufted astrocytes, and oligodendroglial coiled bodies).

If CSF biomarker data were not suggestive of AD, the secondary elements of CBS would substantially increase the likelihood of underlying CBD neuropathology presenting with a PCA syndrome and evolving to a mixed PCA-CBS. But the CSF amyloid and tau levels are unambiguously suggestive of AD (i.e., very low amyloid-β-42 and very high p-tau levels), the neuropathology of which accounts for not only a vast majority of PCA presentations but also roughly a quarter of cases presenting with CBS ( 18 , 19 ). Thus, underlying AD appears most likely.

NEUROPATHOLOGY

On gross examination, the brain weighed 1,150 g, slightly less than the lower end of normal at 1,200 g. External examination demonstrated mild cortical atrophy with widening of the sulci, relatively symmetrical and uniform throughout the brain ( Figure 3A ). There was no evidence of atrophy of the brainstem or cerebellum. On cut sections, the hippocampus was mildly atrophic. The substantia nigra in the midbrain was intact, showing appropriate dark pigmentation as would be seen in a relatively normal brain. The remainder of the gross examination was unremarkable.

FIGURE 3. Mild cortical atrophy with posterior predominance and neurofibrillary tangles, granulovacuolar degeneration, and a Hirano body a

a Panel A shows the gross view of the brain, demonstrating mild cortical atrophy with posterior predominance (arrow). Panel B shows the hematoxylin and eosin of the hippocampus at high power, demonstrating neurofibrillary tangles, granulovacuolar degeneration, and a Hirano body.

Histological examination confirmed that the neurons in the substantia nigra were appropriately pigmented, with occasional extraneuronal neuromelanin and moderate neuronal loss. In the nucleus basalis of Meynert, NFTs were apparent on hematoxylin and eosin staining as dense fibrillar eosinophilic structures in the neuronal cytoplasm, confirmed by tau immunohistochemistry (IHC; Figure 4 ). Low-power examination of the hippocampus revealed neuronal loss in the subiculum and in Ammon’s horn, most pronounced in the cornu ammonis 1 (CA1) subfield, with a relatively intact neuronal population in the dentate gyrus. Higher power examination with hematoxylin and eosin demonstrated numerous NFTs, neurons exhibiting granulovacuolar degeneration, and Hirano bodies ( Figure 3B ). Tau IHC confirmed numerous NFTs in the CA1 region and the subiculum. Amyloid-β IHC demonstrated occasional amyloid plaques in this region, less abundant than tau pathology. An α-synuclein stain revealed scattered Lewy bodies in the hippocampus and in the amygdala.

FIGURE 4. Tau immunohistochemistry demonstrating neurofibrillary tangles (staining brown) in the nucleus basalis of Meynert, in the hippocampus, and in the cerebral cortex of the frontal, temporal, parietal, and occipital lobes

In the neocortex, tau IHC highlighted the extent of the NFTs, which were very prominent in all of the lobes from which sections were taken: frontal, temporal, parietal and occipital. Numerous plaques on amyloid-β stain were likewise present in all cortical regions examined. The tau pathology was confined to the gray matter, sparing white matter. There were no ballooned neurons and no astrocytic plaques—two findings one would expect to see in CBD ( Table 2 ).

TABLE 2. Neuropathological features of this case compared with a case of corticobasal degeneration

a AD=Alzheimer’s disease; CBD=corticobasal degeneration; CBS=corticobasal syndrome; PCA=posterior cortical atrophy.

TABLE 2. Neuropathological features of this case compared with a case of corticobasal degeneration a

The case was designated by the neuropathology division as Alzheimer’s-type pathology, Braak stage V–VI (of VI), due to the widespread neocortical tau pathology, with LBD primarily in the limbic areas.

Our patient had AD neuropathology presenting atypically with a young age at onset (52 years old) and a predominantly visual-spatial and corticobasal syndrome as opposed to prominent amnesia. Syndromic diversity is a well-recognized phenomenon in AD. Nonamnesic presentations include not only PCA and CBS but also the logopenic variant of primary progressive aphasia and a behavioral-dysexecutive syndrome ( 20 ). Converging lines of evidence link the topographical distribution of NFTs with syndromic presentations and the pattern of hypometabolism and cortical atrophy. Neuropathological case reports and case series suggest that atypical AD syndromes arise in the setting of higher than normal densities of NFTs in networks subserving the functions compromised, including visual association areas in PCA-AD ( 21 ), the language network in PPA-AD ( 22 ), and frontal regions in behavioral-dysexecutive AD ( 23 ). In a large sample of close to 900 cases of pathologically diagnosed AD employing quantitative assessment of NFT density and distribution in selected neocortical and hippocampal regions, 25% of cases did not conform to a typical distribution of NFTs characterized in the Braak staging scheme ( 24 ). A subset of cases classified as hippocampal sparing with higher density of NFTs in the neocortex and lower density of NFTs in the hippocampus had a younger mean age at onset, higher frequency of atypical (nonamnesic) presentations, and more rapid rate of longitudinal decline than subsets defined as typical or limbic-predominant.

Tau PET, which detects the spatial distribution of fibrillary tau present in NFTs, has corroborated postmortem work in demonstrating distinct patterns of tracer uptake in different subtypes of AD defined by clinical symptoms and topographical distributions of atrophy ( 25 – 28 ). Amyloid PET, which detects the spatial distribution of fibrillar amyloid- β found in amyloid plaques, does not distinguish between typical and atypical AD ( 29 , 30 ). In a longitudinal study of 32 patients at early symptomatic stages of AD, the baseline topography of tau PET signal predicted subsequent atrophy on MRI at the single patient level, independent of baseline cortical thickness ( 31 ). This correlation was strongest in early-onset AD patients, who also tended to have higher tau signal and more rapid progression of atrophy than late-onset AD patients.

Differential vulnerability of selected large-scale brain networks in AD and in neurodegenerative disease more broadly remains poorly understood. There is evidence to support multiple mechanisms that are not mutually exclusive, including metabolic stress to key network nodes, trophic failure, transneuronal spread of pathological proteins (i.e., prion-like mechanisms), and shared vulnerability within network regions based on genetic or developmental factors ( 32 ). In the case of AD, cortical hub regions with high intrinsic functional connectivity to other regions across the brain appear to have high metabolic rates across the lifespan and to be foci of convergence of amyloid-β and tau accumulation ( 33 , 34 ). Tau NFT pathology appears to spread temporally along connected networks within the brain ( 35 ). Patients with primary progressive aphasia are more likely to have a personal or family history of developmental language-based learning disability ( 36 ), and patients with PCA are more likely to have a personal history of mathematical or visuospatial learning disability ( 37 ).

This case highlights the symptomatic heterogeneity in AD and the value of a three-tiered approach to diagnostic formulation in neurodegenerative presentations. It is important to remember that not all AD presents with amnesia and that early-onset AD tends to be more atypical and to progress more rapidly than late-onset AD. Multiple lines of evidence support a relationship between the burden and topographical distribution of tau NFT neuropathology and clinical symptomatology in AD, instantiating network-based neurodegeneration via mechanisms under ongoing investigation.

The authors report no financial relationships with commercial interests.

Supported by NIH grants K08 AG065502 (to Dr. Miller) and T32 HL007627 (to Dr. Miller).

The authors have confirmed that details of the case have been disguised to protect patient privacy.

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• Jeffrey Maneval , M.D. ,
• Kirk R. Daffner , M.D. ,
• Scott M. McGinnis , M.D.
• Seth A. Gale , M.A., M.D. ,
• C. Alan Anderson , M.D. ,
• David B. Arciniegas , M.D.

• Posterior Cortical Atrophy
• Corticobasal Syndrome
• Atypical Alzheimer Disease
• Network Degeneration

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• v.14(4); 2017 Jul

A Case Report of a 37-Year-Old Alzheimer's Disease Patient with Prominent Striatum Amyloid Retention

Yoo hyun um.

1 Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Woo Hee Choi

2 Department of Radiology, Division of Nuclear Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea.

Won Sang Jung

3 Department of Radiology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea.

Young Ha Park

Chang-uk lee.

4 Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Hyun Kook Lim

With recent advancement in amyloid imaging, diagnostic application of this new modality has become a great interest among researchers. New ligands, such as 18F- florbetaben, florbetapir and flutemetamol, have been discovered to overcome limitations of preexisting ligand Pittsburgh compound B. We report here a case of a 37-year-old male patient whose initial complaints comprised of gradual cognitive decline, apraxia, disorientation and sleep disturbances. 18F-Florbetaben amyloid imaging of the patient showed diffuse amyloid retention with prominent striatal uptake. This finding supports the clinical utility of amyloid imaging in diagnostic process of early-onset AD. Moreover, striatal dominant uptake pattern demonstrated in this patient include some meaningful clinical implications that warrant special attention among clinicians.

INTRODUCTION

Amyloid deposition has long been considered one of the pathognomonic markers of Alzheimer's disease (AD). Moreover, disruption in amyloid hypothesis has been frequently discussed as important targets of intervention for many years. 1 To date, most validated research results have been narrowed down to yield a model for biological trajectory of AD, where amyloid deposition far precedes clinical symptoms. 2 Thus, early detection of amyloid deposition has emerged a major target of intervention in AD patients. In this regard, amyloid imaging has emerged as an effective diagnostic tool that could enable early intervention in patients in AD trajectory, and the clinical utility of amyloid imaging has become a main topic of interest among researchers over the recent years. 3 If validated further, clinical usage of amyloid imaging is expected to extend beyond confirming AD pathology in patients with high risk factors, helping to differentiate AD from various types of dementia in those who present with atypical course or symptoms. 4

Pittsburgh compound B has been the first ligand used to detect amyloid deposition in AD patients. 5 However, its short half-life and resultant limitations in applying it to clinical setting have resulted in the development of new ligands for detecting amyloid deposition, such as 18F-florbetaben, florbetapir and flutemetamol. 6 Amyloid deposition usually initiates from temporal and orbitofrontal cortices, which later extends to frontal, parietal, precuneus, anterior and posterior cingulate cortices. 7 However, differential uptake patterns in autosomal dominant gene carriers have been noted that warrant special clinical attention. While typical amyloid deposition occurs from cortical structures, those with autosomal dominant gene carriers demonstrated initial amyloid deposition in striatum. 8 , 9

We report here a case where a case of early-onset AD patient who received a confirmatory diagnosis of AD by beta-amyloid imaging. There is relatively few evidence on the clinical application of beta-amyloid imaging in early-onset AD patients, and therefore, we expect our case can contribute to this line of inquiry. Moreover, validity of utilizing beta-amyloid imaging in differential diagnosis of dementias will be discussed.

A 37-year old male patient visited outpatient clinic, with complaints of gradual cognitive decline which had started 3 years earlier. Working as an industrial researcher, he started to make serious calculation mistakes that made him quit the job and began working as a manager in a company. However, his frequent forgetfulness, along with aggravation in recent memory impairments hampered him from fulfilling his duties, making him change jobs frequently. Apraxia and apathy had started 2 years before his visit to our clinic, and disorientation to time and person was worsened to a degree which it became impossible to commute daily between his workplace and home. At time of his visit to our clinic, not only he was fired from his recent job, but also he needed frequent reminder from his family to maintain hygiene. His sleep disturbance became prominent, frequently waking up middle of the night self-talking.

Before his visit to our clinic, he had visited two hospitals for evaluation and management of his symptoms, but to no avail. For a thorough examination of his symptoms, he was immediately admitted to our psychiatric ward. His laboratory findings did not reveal any abnormalities, and his tests for human immunodeficiency virus, syphilis all turned out to be negative. Upon his psychiatric admission, a neuropsychological test battery was implemented to evaluate the patient's cognitive status. He scored 22 in Mini-mental status examination, 1 in Clinical dementia rating scale (CDR), 10 and 4.5 in Clinical Dementia Rating-Sum of Box score(CDR-SB). 11 In his cognitive tests, in contrast to his relatively preserved language function, he displayed serious impairments in free recall, 20-minute delayed recall and recognition.

Brain magnetic resonance imaging demonstrated global cerebral atrophy of grade 1 by cortical atrophy scale 12 and notable medial temporal lobe atrophy of grade 2 by medial temporal lobe atrophy visual rating scale ( Figure 1A and B ). 13 Atypically early onset of dementia symptoms made the patient an eligible candidate for amyloid positron emission tomography (PET) imaging. 14 18-Florbetaben PET images revealed diffuse amyloid deposition with score 3 in brain beta-amyloid plaque load (BAPL), 15 with predominant amyloid deposition in the striatum ( Figure 1C and D ).

The patient's history, along with neuroimaging results and cognitive test results all satisfied the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association Alzheimer's (NINCDS-ADRDA) criteria16 for probable Alzheimer's disease with high level of evidence. 5 mg of donepezil was prescribed, and the patient was discharged on the 10th day of his admission. To control his persistent cognitive decline even after the discharge, donepezil was increased up to 23 mg with combination of memantine, which was also increased up to 20 mg. His cognitive decline has been relatively plateaued, but we advised the patient and his caregiver to regularly visit the clinic for monitoring of his symptoms.

This is one of the few case reports that demonstrated diagnosis of early-onset AD by 18F-florbetaben PET imaging. The patient demonstrated early onset of cognitive decline with accelerated deterioration. The fact that he meandered along various departments at different hospitals for confirmatory diagnosis reflect major role amyloid imaging played in the diagnostic process of the patient.

Amyloid imaging is usually indicated in patients with progressive MCI with dubious etiology, patients with atypical presentations and clinical course, and patients with early-onset progressive dementias. 14 Considering the patient in the case exhibited dementia symptoms at atypically early age, amyloid imaging was appropriately prescribed to diagnose the etiology of his cognitive decline. Integration of information attained from his history, clinical data indicated his diagnosis to be early-onset AD.

There have been relatively few reports utilizing 18F-labelled amyloid beta PET tracers that include clinical implications related to autosomal dominant AD. One study adopted 18F-florbetaben PET imaging in Down syndrome patients, suggesting potential role of amyloid imaging in identifying population at risk of dementia. 17 Similar study was conducted on patients with Down syndrome, but with 18F-florbetapir tracer. 18 An attempt to differentiate Down Syndrome pathology from AD has also been made with 18F-florbetapir tracer. 19 Future studies on autosomal dominant AD with 18F-labelled amyloid beta PET tracers could increase validity of adopting these new ligands in the diagnostic process.

Most notable test results in the case report arise from uptake patterns of 18F-florbetaben PET imaging. Unlike typical uptake patterns demonstrated by late-onset AD patients, where striatum is usually involved in the later course of illness, there was a dominant striatal uptake pattern in the patient. A previous study conducted on nondemented young adults with Down syndrome compared their results with that of studies conducted on autosomal dominant early-onset AD patients, where two groups of subjects concordantly showed predominant striatal uptake. 8 Indeed, previous studies on autosomal early-onset AD patients consistently showed high striatal amyloid deposition. 20 , 21 The aforementioned finding could explain 18F-florbetaben uptake patterns in the case.

The underlying mechanisms have been discussed in prior studies on the relatively early involvement of the striatum in autosomal dominant early-onset AD patients. Axonal mistrafficking induced by presenillin-1 gene mutation has been suggested as a potential culprit for striatal amyloid deposition in one animal study. 22 Such axonal mistrafficking is considered to stem from disruption in APP processing. 22 Indeed, APP processing patterns differed between autosomal dominant AD patients and sporadic AD patients. 23 Striatal vulnerability to early stages of tau protein accumulation in autosomal dominant AD has also been elucidated, and such phenomenon is considered more toxic to induce significant striatal neuronal injury. 24

The most prominent limitation of our case report is lack of genotype testing in the patient. If the genetic testing had been done, one missing puzzle in the diagnosis of patient would have been complete. Nevertheless, we believe our case report affirms diagnostic usefulness and clinical application of amyloid imaging in the differential diagnosis of early-onset dementia. We expect more prevalent use of amyloid imaging with accumulation of evidences and validation studies over time.

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2015R1C1A1A02036578).

• DOI: 10.1186/s12916-024-03475-z
• Corpus ID: 270618391

Circulating small extracellular vesicles in Alzheimer’s disease: a case–control study of neuro-inflammation and synaptic dysfunction

• Rishabh Singh , Sanskriti Rai , +10 authors Saroj Kumar
• Published in BMC Medicine 20 June 2024
• Medicine, Biology

83 References

Exploratory study on microrna profiles from plasma-derived extracellular vesicles in alzheimer’s disease and dementia with lewy bodies, neuronal-derived ev biomarkers track cognitive decline in alzheimer’s disease, comparative assessment of alzheimer’s disease-related biomarkers in plasma and neuron-derived extracellular vesicles: a nested case-control study, extracellular vesicles and alzheimer’s disease in the novel era of precision medicine: implications for disease progression, diagnosis and treatment, innate immune cell death in neuroinflammation and alzheimer’s disease, inflammation as a central mechanism in alzheimer's disease, the amyloid-β pathway in alzheimer’s disease, blood-brain barrier dysfunction and alzheimer’s disease: associations, pathogenic mechanisms, and therapeutic potential, neuronally derived extracellular vesicles: an emerging tool for understanding alzheimer’s disease, molecular and cellular mechanisms underlying the pathogenesis of alzheimer’s disease, related papers.

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Increased serum levels of dehydroepiandrosterone (DHEA) and interleukin-6 (IL-6) in women with mild to moderate Alzheimer's disease

Affiliation.

• 1 Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University Hospital, Umeå, Sweden. [email protected]
• PMID: 21729423
• DOI: 10.1017/S1041610211000810

Background: It has been suggested that hypercortisolism contributes to the pathophysiology of Alzheimer's disease (AD), based on the fact that excess glucocorticoid exposure has potent adverse effects on the central nervous system. In contrast, dehydroepiandrosterone (DHEA) has been linked to a broad range of beneficial physiological effects including neuronal excitability and neuroprotection and even memory enhancing properties. Of note, proinflammatory cytokines are present in neuritic plaques (a hallmark of AD) and may regulate cortisol/DHEA release. In this exploratory study, we hypothesized that there is a flattened diurnal curve of cortisol and DHEA in mild to moderate AD, linked to increased cytokine levels.

Methods: Diurnal profiles of cortisol, adrenocorticotropic hormone (ACTH), and DHEA were studied in 15 patients with mild to moderate AD (7 men and 8 women, 75.6 ± 5.5 years) and 15 healthy elderly controls (7 men and 8 women, 73.3 ± 5.8 years, respectively). Interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and soluble TNF receptors were analyzed.

Results: Women with AD had significantly increased morning levels of ACTH, DHEA, and IL-6 compared to healthy elderly women. Cortisol levels were significantly increased in men with AD at 0300 h versus healthy elderly men, in spite of slightly decreased ACTH levels.

Conclusions: Our data suggest important sex differences in hypothalamic-pituitary-adrenal (HPA) axis regulation and steroid hormone clearance in patients with AD. Increased secretion of IL-6 may have a contributory role in this difference.

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