Results from a Virginia Tech-led study provide the first direct geochemical evidence of the slushy planet — otherwise known as the “plumeworld ocean” era — when sky-high carbon dioxide levels forced the frozen Earth into a massive, rapid melting period.

“Our results have important implications for understanding how Earth’s climate and ocean chemistry changed after the extreme conditions of the last global ice age,” said lead author Tian Gan, a former Virginia Tech postdoctoral researcher. Gan worked with geologist Shuhai Xiao on the study, which was released Nov. 5 in the Proceedings of the National Academy of Sciences journal.

Deep-frozen Earth

The last global ice age took place about 635 million to 650 million years ago, when scientists believe global temperatures dropped and the polar ice caps began to creep around the hemispheres. The growing ice reflected more sunlight away from the Earth, setting off a spiral of plunging temperatures.

“A quarter of the ocean was frozen due to extremely low carbon-dioxide levels,” said Xiao, who recently was inducted into the National Academy of Sciences.

When the surface ocean sealed, a chain of reactions stuttered to a stop:

• The water cycle locked up. No evaporation and very little rain or snow.
• Without water, there was a massive slowdown in a carbon-dioxide consuming process called chemical weathering, where rocks erode and disintegrate.
• Without weathering and erosion, carbon dioxide began to amass in the atmosphere and trap heat.

“It was just a matter of time until the carbon-dioxide levels were high enough to break the pattern of ice,” Xiao said. “When it ended, it probably ended catastrophically.”

Plume world

Suddenly, heat started to build. The ice caps began to recede, and Earth’s climate backpedaled furiously toward the drippy and soupy. Over a mere 10 million years, average global temperatures swung from minus 50 to 120 degrees Fahrenheit (minus 45 to 48 degrees Celsius).

But the ice didn’t melt and remix with seawater at the same time. The research findings paint a very different world than what we can imagine: vast rivers of glacial water rushing like a reverse tsunami from the land into the sea, then pooling on top of extra salty, extra dense ocean water.

The researchers tested this version of the prehistoric world by looking at a set of carbonate rocks that formed as the global ice age was ending.

They analyzed a certain geochemical signature, the relative abundance of lithium isotopes, recorded within the carbonate rocks. According to plumeworld ocean theory, the geochemical signatures of freshwater would be stronger in rocks formed under nearshore meltwater than in the rocks formed offshore, beneath the deep, salty sea — and that’s exactly what the researchers observed.

The findings bring the limit of environmental change into better focus, said Xiao, but they also give researchers additional insight into the frontiers of biology and the resiliency of life under extreme conditions — hot, cold, and slushy.

Study collaborators include:

• Ben Gill, Virginia Tech associate professor of sedimentary geochemistry
• Morrison Nolan, former graduate student, now at Denison University
• Collaborators from the Chinese Academy of Sciences, University of Maryland at College Park, University of Munich in Germany, University of North Carolina at Chapel Hill, and University of Nevada at Las Vegas

In a pair of recent papers, scientists in the lab of molecular biologist John Petrini, PhD, showed that innate immune signaling plays a key role in maintaining genome stability during DNA replication. Furthermore, the researchers showed that chronic activation of these immune pathways can contribute to tumor development in a mouse model of breast cancer.

Not only do the findings add vital insights to our understanding of fundamental human biology, says Dr. Petrini, they may also shed new light on tumor initiation and present potential opportunities for new therapies.

“Living organisms have evolved complex pathways to sense, signal, and repair damaged DNA,” he says. “Here we’re learning new things about the role of the innate immune system in responding to that damage — both in the context of cancer and also in human health more generally.”

How Chronic Activation of the Innate Immune System Can Lead to Cancer

The newest paper, led by first author Hexiao Wang, PhD, a postdoctoral fellow in the Petrini Lab, and published in Genes & Development, reveals a connection between innate immune signaling and tumor development in breast tissue. And, Dr. Petrini says, the data suggest that when instability arises in the genome, chronic activation of the innate immune system can greatly increase the chances of developing cancer.

The study focused on a protein complex called the Mre11 complex, which plays a pivotal role in maintaining the stability of the genome by sensing and repairing double-strand breaks in DNA.

To study how problems with the Mre11 complex can lead to cancer, the team manipulated copies of the protein in mammary tissue organoids (miniature lab-grown model organs) and then implanted them into laboratory animals.

When oncogenes (genes known to drive cancer) were activated in these mice, tumors arose about 40% of the time, compared with about 5% in their normal counterparts. And the tumors in the mice with mutant Mre11 organoids were highly aggressive.

The research further showed that the mutant Mre11 led to higher activation of interferon-stimulated genes (ISGs). Interferons are signaling molecules that are released by cells in response to viral infections, immune responses, and other cellular stressors.

They also found that the normally tightly controlled packaging of DNA was improperly accessible in these organoids — making it more likely that genes will get expressed, when they otherwise would be inaccessible for transcription.

“We actually saw differences in the expression of more than 5,600 genes between the two different groups of mice,” Dr. Petrini says.

And strikingly, these profound effects depended on an immune sensor called IFI205.

When the organoids were further manipulated so they would lack IFI205, the packaging of DNA returned almost to normal, and the mice developed cancer at essentially the same rate as normal mice.

“So what we learned is that problems with Mre11 — which can be inherited or develop during life like other mutations — can create an environment where the activation of an oncogene is much more likely to lead to cancer,” Dr. Petrini says. “And that the real lynch pin of this cascade is this innate immune sensor, IFI205, which detects that there’s a problem and starts sending out alarm signals. In other words, when problems with Mre11 occur, chronic activation of this innate immune signaling can significantly contribute to the development of cancer.”

New Understandings Could Pave the Way for Future Treatments

The work builds on a previous study, led by Christopher Wardlaw, PhD, a former senior scientist in the Petrini Lab, that appeared in Nature Communications.

That study focused on the role of the Mre11 complex in maintaining genomic integrity. It found that when the Mre11 complex is inactive or deficient, it results in the accumulation of DNA in the cytoplasm of cells and in the activation of innate immune signaling. This research primarily looked at the involvement of ISG15, a protein made by an interferon-stimulating gene, in protecting against replication stress and promoting genomic stability.

“Together, these studies shed new light on how the Mre11 complex works to protect the genome when cells replicate, and how, when it’s not working properly, it can trigger the innate immune system in ways that can promote cancer,” Dr. Petrini says.

By shedding light on the interrelationships between these complex systems and processes, the researchers hope to identify new strategies to prevent or treat cancer, he adds, such as finding ways to short-circuit the increased DNA accessibility when Mre11 isn’t working properly.

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.’

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.”