Tag Archives: mild cognitive impairment

What is the difference between dementia and Alzheimer’s disease?

This is probably the most common question I’m asked by my readers, so I decided to devote an entire article to clearing up the confusion. Doctors and scientists often throw around words like “dementia,” “Alzheimer’s,” and “mild cognitive impairment” without making it clear what the difference is between them. Understanding what each of these terms mean is important for being able to interpret articles and recognize how scientific findings may apply to you.

Let’s start with dementia. Dementia itself is actually not a disease, but a set of symptoms. The most well-known dementia symptom is memory loss, but it also includes other things such as difficulty communicating, impaired attention, poor judgement, and a decline in visual perception.

Dementia symptoms can be caused by many different diseases. The most common cause of dementia is Alzheimer’s disease, which makes up around 60% of all dementias. However, many other diseases can cause dementia, including Parkinson’s disease, vascular dementia, frontotemporal dementia, and Lewy body disease. Dementia is often referred to as an “umbrella term” for a range of symptoms than can be caused by multiple diseases.

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Dementia is an “umbrella term” for a set of symptoms that can be caused by several different diseases. Image Source

I like to use an analogy to make this distinction a bit clearer. Think of Alzheimer’s disease like the flu. These are both diseases with a particular cause. Now think of some of the symptoms of having the flu: congestion, chills, nausea, and so on. There are many different diseases that can cause these symptoms, like a cold or sinus infection. In the same way, there are multiple diseases that can cause dementia symptoms.

To put it another way: everyone with Alzheimer’s disease has dementia, but not everyone with dementia has Alzheimer’s disease.

Now, there’s a third term you may have also heard thrown around: mild cognitive impairment, or MCI. It’s characterized by memory problems that are noticeable but not severe enough to interfere with daily life, such as forgetting appointments, losing your train of thought, and having trouble with planning or organization. Some people with MCI later progress to Alzheimer’s disease or other dementias, while others do not. Around 20% of adults over age 65 have MCI.

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Mild cognitive impairment sometimes progresses to Alzheimer’s disease or other dementia-causing diseases. Image Source

So there you have it! To summarize:

  • Dementia is a set of symptoms that include memory loss, impaired attention, and and poor judgement.
  • Alzheimer’s is one of several diseases that can lead to dementia symptoms.
  • Mild cognitive impairment is a less serious memory problem than can, but does not always, progress to dementia.

Hopefully that helps to clear up some of the confusion surrounding these three terms! As always, feel free to comment or send me a message if there are any other topics you’d like me to explain.

 

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Dementia Patients’ Awareness of their Own Illness May Predict Cognitive Decline

According to new research, anosognosia (“lack of self awareness”) may be used to predict whether patients with mild cognitive impairment will progress to Alzheimer’s disease.

Anosognosia describes the inability to recognize that one is experiencing a mental illness. It is most well-known in schizophrenia, where patients frequently cannot acknowledge that their delusions are the result of a mental condition and not based in reality. However, anosognosia can also occur with dementias, such as Alzheimer’s disease. In later stages of the disease, people with Alzheimer’s may lose their ability to recognize their own cognitive deficits.

In a paper published this week in Neurology, researchers from McGill University wanted to assess whether anosognosia could be used to predict whether patients with mild cognitive impairment would later progress to Alzheimer’s disease. Mild cognitive impairment (MCI) is a condition that affects nearly 20% of adults over 65. It is characterized by memory problems that are noticeable but not severe enough to interfere with daily life. Some people with MCI later progress to Alzheimer’s disease, while others do not, and we currently do not have a reliable method to predict whether a person with MCI will develop Alzheimer’s.

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Mild cognitive impairment sometimes progresses to Alzheimer’s disease or other types of dementia. Image Source

The study included a total of 468 MCI patients recruited through the Alzheimer’s Disease Neuroimaging Initiative, a large consortium of researchers searching for reliable ways to predict and diagnose Alzheimer’s. The researchers looked at the subjects’ cognitive self-assessment and compared it to their spouse or caregiver’s assessment of the patient’s cognition. Individuals who rated their own cognition substantially higher than what their caregiver rated them were categorized as anosognosic.

The researchers then administered spinal taps on each subject. They found that the anosognosic patients had higher levels of the toxic tau protein in their cerebrospinal fluid. These patients also had higher levels of amyloid-beta in their brains. Additionally, PET scans revealed that the patients lacking self-awareness had reduced levels of activity in a part of their brains called the default mode network. The default mode network is a group of brain structures that become less active when you’re focusing on a particular task, and more active when you’re daydreaming. Studies have found that the default mode network is among the first parts of the brain to degenerate in Alzheimer’s disease, but its specific role in the disease still remains unclear.

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This fMRI image shows the brain structures that make up the default mode network. Image Source

The final phase of the study involved a follow-up examination two years after the initial assessment. The researchers found that 28% the subjects with anosognosia progressed to Alzheimer’s disease, compared to only 12% of those with intact self-awareness. This shows that assessing MCI patients’ awareness to their own cognition could be a useful tool for predicting whether they will later develop Alzheimer’s disease. The study also suggests that the default mode network might be important for our ability to recognize our own mental status.

 

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Artificial Intelligence Could Help Us Predict Alzheimer’s Disease

Many experts agree that preventing the progression of Alzheimer’s disease is much more effective than trying to reverse it once the damage is done. This makes early diagnosis critical. Unfortunately, most Alzheimer’s patients are not diagnosed until relatively late in disease progression, when toxic amyloid plaques have already accumulated in their brains to potentially irreversable levels. However, this might soon be changing with the recent surge in artificial intelligence technology.

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This diagram shows the stages of Alzheimer’s disease, which can begin up to 20 years before diagnosis. Most patients are not diagnosed until the mild or moderate stage, since this is when cognitive impairments become more noticeable. Image Source

This research was described in a paper published in Neurobiology of Aging by scientists from McGill University in Canada. Their goal was to create an algorithm to predict whether people with mild cognitive impairment would progress to dementia. They utilized a noninvasive technology called positron emission tomography (PET). PET involves the patient lying inside a donut-shaped machine, similar to a CAT scanner. The machine can measure which areas of the brain have higher or lower activity levels based on how much glucose each brain region is consuming.

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A patient lying inside of a PET machine. Image Source

The researchers used PET scans from 273 patients with mild cognitive impairment. 43 of these patients were diagnosed with probable Alzheimer’s disease at a follow-up appointment two years later. Then the scientists trained an artificial intelligence algorithm to predict which patients would develop Alzheimer’s based on their PET scans.

They used the data to generate the map of the brain that’s shown below. The red-colored areas indicate a higher odds ratio (OR). This means that unusual activity levels in those brain areas are associated with an increased risk of Alzheimer’s disease. For example, an odds ratio of 3 means that a person with unusual activity levels in that brain area is 3 times as likely to develop Alzheimer’s compared to someone with normal activity levels.

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Figure 2 of the paper shows which brain regions are the most important for predicting the risk of Alzheimer’s disease.

The algorithm was able to predict which patients would progress to Alzheimer’s disease with an accuracy of 84%. This is better than any previously-developed PET algorithms, and comparable to more invasive diagnostic techniques such as spinal taps. This is exciting news because it suggests that a painless, noninvasive technology can be used to predict Alzheimer’s disease with a fairly high degree of accuracy.

As always, we have to point out a few problems with this study. For one thing, it’s impossible to know for sure whether the patients’ Alzheimer’s disease diagnoses performed by doctors at the follow-up appointment were actually correct. This is because many forms of dementia have similar cognitive symptoms, and can be easily confused during diagnosis. Parkinson’s disease, vascular dementia, or even a urinary tract infection can be misdiagnosed as Alzheimer’s disease. (For more info see Is it really Alzheimer’s? 10 common misdiagnoses you should know about). Only a postmortem brain analysis can reveal for sure whether the patients truly had Alzheimer’s. This muddles our ability to judge how accurate the algorithm really was.

Another problem is that PET scans can be quite expensive, costing upwards of $7,000. If a patient is incorrectly diagnosed with Alzheimer’s, this could lead to futher costs for medication to treat a disease they don’t actually have. Finally, while the mild cognitive impairment stage is earlier than most Alzheimer’s patients are diagnosed, it can still be up to ten years after the true beginning of the disease. We still have no reliable way to make diagnoses that early. Nonetheless, this study is at least a step in the right direction. With future advances in artificial intelligence, we might be able to improve our diagnostic accuracy at earlier stages of the disease.

 

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