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Slowing down as we age could be warning sign for dementia

We grudgingly accept we will lose muscle strength and slow down as we get older, making it more difficult to walk, sit down, and get up.
But new research from Edith Cowan University (ECU) in Western Australia published in the Journal of Cachexia, Sarcopenia and Muscle, indicates this could also be a signal for another sinister age-related health concern: late-life dementia.
To investigate the relationship between muscle function and dementia, the research teams from ECU’s Nutrition and Health Innovation Research Institute and Centre for Precision Health, used data from the 15-year long Perth Longitudinal Study of Ageing in Women to examine more than 1,000 females with an average age of 75.
In collaboration with the University of Western Australia in Perth, the team measured the women’s grip strength and the time it took for them to rise from a chair, walk three metres, turn around and sit back down – known as a timed-up-and-go (TUG) test.
These tests were repeated after five years to monitor any loss of performance.
Over the next 15 years, almost 17% of women involved in the study were found to have had a dementia event, categorised as a dementia-related hospitalisation or death.
The team found lower grip strength and slower TUG were significant risk factors for presenting with dementia, independent of genetic risk and lifestyle factors such as smoking, alcohol intake and physical activity levels.
The women with the weakest grip strength were found to be more than twice as likely to have a late-life dementia event than the strongest individuals.
A similar relationship emerged between TUG performance and dementia, with the slowest in their TUG test more than twice as likely to experience dementia than the quickest.
When researchers looked at the changes in grip strength and TUG test results after five years, a decrease in performance was also linked with greater dementia risk.
Those who had experienced the biggest decline in grip strength and TUG speed were approximately two and 2.5 times more likely, respectively, to have had a dementia event, compared to those in the group who recorded the smallest decline in performance.
Women with the biggest drop in TUG performance were found to be over four times more likely to have a dementia-related death than the fastest.
Senior researcher Dr Marc Sim said grip strength, which can be easily measured using a handheld device known as a dynamometer, may be a measure of brain health due to the overlapping nature of cognitive and motor decline.
“Possibly due to a range of underlying similarities, grip strength may also present as a surrogate measure of cardiovascular disease, inflammation and frailty, which are known risk factors for dementia,” Dr Sim said.
He said the findings from the study could help health professionals to identify dementia risk in patients earlier.
“Both grip strength and TUG tests aren’t commonly performed in clinical practice, but both are inexpensive and simple screening tools,” he explained.
“Incorporating muscle function tests as part of dementia screening could be useful to identify high-risk individuals, who might then benefit from primary prevention programmes aimed at preventing the onset of the condition, such as a healthy diet and a physically active lifestyle.
“The exciting findings were that decline in these measures was associated with substantially higher risk, suggesting that if we can halt this decline, we may be able to prevent late-life dementias. However, further research is needed in this area.”
Centre for Precision Health Director, Professor Simon Laws, said there has been encouraging progress in identifying early warning signs of dementia.
“We are now starting to see a number of simple yet indicative screening assessments that could be combined with other biological and clinical measures to provide a holistic risk-profile for individuals presenting to their GP with, for example, memory concerns.
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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