An extra year of education does not protect against brain aging, study finds

Posted on 05/11/2024 by Boris Clair

Thanks to a ‘natural experiment’ involving 30,000 people, researchers at Radboud university medical center were able to determine very precisely what an extra year of education does to the brain in the long term. To their surprise, they found no effect on brain structure and no protective benefit of additional education against brain aging.

It is well-known that education has many positive effects. People who spend more time in school are generally healthier, smarter, and have better jobs and higher incomes than those with less education. However, whether prolonged education actually causes changes in brain structure over the long term and protects against brain aging, was still unknown.

It is challenging to study this, because alongside education, many other factors influence brain structure, such as the conditions under which someone grows up, DNA traits, and environmental pollution. Nonetheless, researchers Rogier Kievit (PI of the Lifespan Cognitive Dynamics lab) and Nicholas Judd from Radboudumc and the Donders Institute found a unique opportunity to very precisely examine the effects of an extra year of education.

Aging

In 1972, a change in the law in the United Kingdom raised the number of mandatory school years from fifteen to sixteen, while all other circumstances remained constant. This created an interesting ‘natural experiment’, an event not under the control of researchers which divides people into an exposed and unexposed group. Data from approximately 30,000 people who attended school around that time, including MRI scans taken much later (46 years after), is available. This dataset is the world’s largest collection of brain imaging data.

The researchers examined the MRI scans for the structure of various brain regions, but they found no differences between those who attended school longer and those who did not. ‘This surprised us’, says Judd. ‘We know that education is beneficial, and we had expected education to provide protection against brain aging. Aging shows up in all of our MRI measures, for instance we see a decline in total volume, surface area, cortical thickness, and worse water diffusion in the brain. However, the extra year of education appears to have no effect here.’

Brain structure

It’s possible that the brain looked different immediately after the extra year of education, but that wasn’t measured. ‘Maybe education temporarily increases brain size, but it returns to normal later. After all, it has to fit in your head’, explains Kievit. ‘It could be like sports: if you train hard for a year at sixteen, you’ll see a positive effect on your muscles, but fifty years later, that effect is gone.’ It’s also possible that extra education only produces microscopic changes in the brain, which are not visible with MRI.

Both in this study and in other, smaller studies, links have been found between more education and brain benefits. For example, people who receive more education have stronger cognitive abilities, better health, and a higher likelihood of employment. However, this is not visible in brain structure via MRI. Kievit notes: ‘Our study shows that one should be cautious about assigning causation when only a correlation is observed. Although we also see correlations between education and the brain, we see no evidence of this in brain structure.’

How are the vaping rules changing?

Posted on 05/11/2024 by Boris Clair

Marketing rules will be stricter, nicotine vapes will be taxed and disposable vapes will be banned.

Nigel Farage’s Latest US Trip To Visit Trump Has Got 1 Word Trending Online

Posted on 05/11/2024 by Boris Clair

🚨 NEW: Donald Trump says Nigel Farage, who is in attendance at one of his rallies in Pennsylvania tonight, was the ‘big winner’ in the UK general election pic.twitter.com/zetYUKtS6N

— Politics UK (@PolitlcsUK) November 4, 2024

Nigel Farage’s latest stateside visit has everyone on social media asking the same question: what is he doing there, and not in his constituency?

The Reform party leader and MP for Clacton is in the US, again, supporting Donald Trump as Americans head to the polls today.

The neck and neck race between the Republican nominee and his Democrat rival, vice-president Kamala Harris, is almost over after a long and turbulent campaign from both sides.

However, Farage is not a US citizen nor is he on Trump’s team (even though he briefly considered supporting it in the summer).

In the end, he actually decided to run as the Reform candidate in Clacton-on-Sea – and won.

That was a major victory for both his party, which only had one Tory defector in parliament during the last term, and for Farage personally, considering his seven previous unsuccessful attempts to get a seat in the Commons.

But the Clacton MP – who initially refused to hold face-to-face surgeries in his constituency, claiming he would be targeted – has just made his third trip to the States in four months.

So, naturally, his critics were quick to call him out.

In fact so many people started to comment on Farage’s trip, they soon got the word “Clacton” trending on X…

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It’s just been announced Nigel Farage is once again in the USA on another jolly. The good people of Clacton however are still waiting for their MP to set up a constituency office, to agree times and places for a surgery or even establish an email address or phone number. pic.twitter.com/W7pb4cfjEQ

— RS Archer (@archer_rs) November 4, 2024

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It’s just been announced Nigel Farage is once again in the USA on another jolly. The good people of Clacton however are still waiting for their MP to set up a constituency office, to agree times and places for a surgery or even establish an email address or phone number. pic.twitter.com/W7pb4cfjEQ

— RS Archer (@archer_rs) November 4, 2024

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Nigel, doing his bit for Clacton by hanging out with a group of demented lunatics who from tomorrow will never wield much influence over anything of consequence, ever again. pic.twitter.com/6tY96kPYbu

— Brendan May (@bmay) November 4, 2024

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Nigel, doing his bit for Clacton by hanging out with a group of demented lunatics who from tomorrow will never wield much influence over anything of consequence, ever again. pic.twitter.com/6tY96kPYbu

— Brendan May (@bmay) November 4, 2024

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Farage: apparently too risky to meet constituents but drinking in his local pub and flying to America is completely fine ✅

Anything but actual work

— skye (@skyera1n) November 4, 2024

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Farage: apparently too risky to meet constituents but drinking in his local pub and flying to America is completely fine ✅

Anything but actual work

— skye (@skyera1n) November 4, 2024

University of Wisconsin-Madison researchers are warning that artificial intelligence tools gaining popularity in the fields of genetics and medicine can lead to flawed conclusions about the connection between genes and physical characteristics, including risk factors for diseases like diabetes.

The faulty predictions are linked to researchers’ use of AI to assist genome-wide association studies. Such studies scan through hundreds of thousands of genetic variations across many people to hunt for links between genes and physical traits. Of particular interest are possible connections between genetic variations and certain diseases.

Genetics’ link to disease not always straightforward

Genetics play a role in the development of many health conditions. While changes in some individual genes are directly connected to an increased risk for diseases like cystic fibrosis, the relationship between genetics and physical traits is often more complicated.

Genome-wide association studies have helped to untangle some of these complexities, often using large databases of individuals’ genetic profiles and health characteristics, such as the National Institutes of Health’s All of Us project and the UK Biobank. However, these databases are often missing data about health conditions that researchers are trying to study.

“Some characteristics are either very expensive or labor-intensive to measure, so you simply don’t have enough samples to make meaningful statistical conclusions about their association with genetics,” says Qiongshi Lu, an associate professor in the UW-Madison Department of Biostatistics and Medical Informatics and an expert on genome-wide association studies.

The risks of bridging data gaps with AI

Researchers are increasingly attempting to work around this problem by bridging data gaps with ever more sophisticated AI tools.

“It has become very popular in recent years to leverage advances in machine learning, so we now have these advanced machine-learning AI models that researchers use to predict complex traits and disease risks with even limited data,” Lu says.

Now, Lu and his colleagues have demonstrated the peril of relying on these models without also guarding against biases they may introduce. The team describe the problem in a paper recently published in the journal Nature Genetics. In it, Lu and his colleagues show that a common type of machine learning algorithm employed in genome-wide association studies can mistakenly link several genetic variations with an individual’s risk for developing Type 2 diabetes.

“The problem is if you trust the machine learning-predicted diabetes risk as the actual risk, you would think all those genetic variations are correlated with actual diabetes even though they aren’t,” says Lu.

These “false positives” are not limited to these specific variations and diabetes risk, Lu adds, but are a pervasive bias in AI-assisted studies.

New statistical method can reduce false positives

In addition to identifying the problem with overreliance on AI tools, Lu and his colleagues propose a statistical method that researchers can use to guarantee the reliability of their AI-assisted genome-wide association studies. The method helps removing bias that machine learning algorithms can introduce when they’re making inferences based on incomplete information.

“This new strategy is statistically optimal,” Lu says, noting that the team used it to better pinpoint genetic associations with individuals’ bone mineral density.

AI not the only problem with some genome-wide association studies

While the group’s proposed statistical method could help improve the accuracy of AI-assisted studies, Lu and his colleagues also recently identified problems with similar studies that fill data gaps with proxy information rather than algorithms.

In another recently published paper appearing in Nature Genetics, the researchers ring the alarm about studies that over-rely on proxy information in an attempt to establish connections between genetics and certain diseases.

For instance, large health databases like the UK Biobank have a ton of genetic information about large populations, but they don’t have very much data regarding the incidence of diseases that tend to crop up later in life, like most neurodegenerative diseases.

For Alzheimer’s disease specifically, some researchers have attempted to bridge that gap with proxy data gathered through family health history surveys, where individuals can report a parent’s Alzheimer’s diagnosis.

The UW-Madison team found that such proxy-information studies can produce “highly misleading genetic correlation” between Alzheimer’s risk and higher cognitive abilities.

“These days, genomic scientists routinely work with biobank datasets that have hundreds of thousands of individuals, however, as statistical power goes up, biases and the probability of errors are also amplified in these massive datasets,” says Lu. “Our group’s recent studies provide humbling examples and highlight the importance of statistical rigor in biobank-scale research studies.”

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