Researchers from MIT and the MIT-Watson AI Lab have developed a new, unified framework that can simultaneously predict molecular properties and generate new molecules much more efficiently than these popular deep-learning approaches.

To teach a machine-learning model to predict a molecule’s biological or mechanical properties, researchers must show it millions of labeled molecular structures — a process known as training. Due to the expense of discovering molecules and the challenges of hand-labeling millions of structures, large training datasets are often hard to come by, which limits the effectiveness of machine-learning approaches.

By contrast, the system created by the MIT researchers can effectively predict molecular properties using only a small amount of data. Their system has an underlying understanding of the rules that dictate how building blocks combine to produce valid molecules. These rules capture the similarities between molecular structures, which helps the system generate new molecules and predict their properties in a data-efficient manner.

This method outperformed other machine-learning approaches on both small and large datasets, and was able to accurately predict molecular properties and generate viable molecules when given a dataset with fewer than 100 samples.

“Our goal with this project is to use some data-driven methods to speed up the discovery of new molecules, so you can train a model to do the prediction without all of these cost-heavy experiments,” says lead author Minghao Guo, a computer science and electrical engineering (EECS) graduate student.

Guo’s co-authors include MIT-IBM Watson AI Lab research staff members Veronika Thost, Payel Das, and Jie Chen; recent MIT graduates Samuel Song ’23 and Adithya Balachandran ’23; and senior author Wojciech Matusik, a professor of electrical engineering and computer science and a member of the MIT-IBM Watson AI Lab, who leads the Computational Design and Fabrication Group within the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). The research will be presented at the International Conference for Machine Learning.

Learning the language of molecules

To achieve the best results with machine-learning models, scientists need training datasets with millions of molecules that have similar properties to those they hope to discover. In reality, these domain-specific datasets are usually very small. So, researchers use models that have been pretrained on large datasets of general molecules, which they apply to a much smaller, targeted dataset. However, because these models haven’t acquired much domain-specific knowledge, they tend to perform poorly.

The MIT team took a different approach. They created a machine-learning system that automatically learns the “language” of molecules — what is known as a molecular grammar — using only a small, domain-specific dataset. It uses this grammar to construct viable molecules and predict their properties.

In language theory, one generates words, sentences, or paragraphs based on a set of grammar rules. You can think of a molecular grammar the same way. It is a set of production rules that dictate how to generate molecules or polymers by combining atoms and substructures.

Just like a language grammar, which can generate a plethora of sentences using the same rules, one molecular grammar can represent a vast number of molecules. Molecules with similar structures use the same grammar production rules, and the system learns to understand these similarities.

Since structurally similar molecules often have similar properties, the system uses its underlying knowledge of molecular similarity to predict properties of new molecules more efficiently.

“Once we have this grammar as a representation for all the different molecules, we can use it to boost the process of property prediction,” Guo says.

The system learns the production rules for a molecular grammar using reinforcement learning — a trial-and-error process where the model is rewarded for behavior that gets it closer to achieving a goal.

But because there could be billions of ways to combine atoms and substructures, the process to learn grammar production rules would be too computationally expensive for anything but the tiniest dataset.

The researchers decoupled the molecular grammar into two parts. The first part, called a metagrammar, is a general, widely applicable grammar they design manually and give the system at the outset. Then it only needs to learn a much smaller, molecule-specific grammar from the domain dataset. This hierarchical approach speeds up the learning process.

Big results, small datasets

In experiments, the researchers’ new system simultaneously generated viable molecules and polymers, and predicted their properties more accurately than several popular machine-learning approaches, even when the domain-specific datasets had only a few hundred samples. Some other methods also required a costly pretraining step that the new system avoids.

The technique was especially effective at predicting physical properties of polymers, such as the glass transition temperature, which is the temperature required for a material to transition from solid to liquid. Obtaining this information manually is often extremely costly because the experiments require extremely high temperatures and pressures.

To push their approach further, the researchers cut one training set down by more than half — to just 94 samples. Their model still achieved results that were on par with methods trained using the entire dataset.

“This grammar-based representation is very powerful. And because the grammar itself is a very general representation, it can be deployed to different kinds of graph-form data. We are trying to identify other applications beyond chemistry or material science,” Guo says.

In the future, they also want to extend their current molecular grammar to include the 3D geometry of molecules and polymers, which is key to understanding the interactions between polymer chains. They are also developing an interface that would show a user the learned grammar production rules and solicit feedback to correct rules that may be wrong, boosting the accuracy of the system.

This work is funded, in part, by the MIT-IBM Watson AI Lab and its member company, Evonik. Paper: “Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction”

CWD is caused by a pathogenic agent called a prion, which can pass from deer-to-deer through contact with things like prion-contaminated soil and infected bodily fluids such as urine, saliva, blood and feces. Prions, which cause disease in animals and in humans, prompt certain proteins to fold abnormally, particularly in the brain, and prevent these proteins from carrying out their normal functions. Over time, the CWD prion can cause severe brain damage and eventually death in deer.

A lot of CWD studies focus on the role soil plays in spreading the fatal neurological disease among deer. But Heather Inzalaco, a researcher in the Wisconsin Cooperative Wildlife Research Unit, housed in the UW-Madison Department of Forest and Wildlife Ecology, was curious about other potential environmental and behavioral means of transmission.

“Deer live these secret lives; we don’t see everything that they do,” Inzalaco says.

She started to consider what sort of things pester deer that could be connected to CWD: Ticks were the perfect parasitic potential culprit to investigate.

Ticks have a goal, of course, to feed on their host’s blood. Inzalaco began to wonder if ticks that acquire blood from CWD-infected deer could also host the prions and if so, could they contain enough prions to spread the disease.

The question became even more intriguing when she discovered that the most common non-aggressive social behavior that deer engage in is allogrooming.

“Deer will groom one another to get places that they can’t reach on their own through self-grooming,” Inzalaco says. “If they’re grooming each other and they’re doing that to remove ectoparasites [such as ticks], that might be problematic because they’re probably eating the ectoparasites.”

First, she needed to show that ticks can take up and harbor these prions when they feed on CWD-infected blood. She designed an experiment to do just that.

“You’d think that it’d be easy to get ticks to take a blood meal, but they are surprisingly fussy in the lab,” Inzalaco says.

She was able to determine that ticks can not only carry the prions in their blood meal, they can also carry enough of the agent to potentially infect another animal with CWD. After seeing that the phenomenon was possible in the lab, it was time to see what was happening in the wild.

Inzalaco partnered with the Department of Natural Resources to study ticks collected from deer that hunters harvested and submitted for CWD testing. Of the 176 deer with ticks she studied, 15 of the deer were also positive for CWD. Inzalaco took the ticks from the infected deer and tested the blood they contained to quantify the amount of prion the ticks harbored.

She determined that these engorged, wild ticks did carry transmissible levels of prions — just like those in the lab — making them potential mechanical vectors for the disease.

“They’re just like a little CWD tic-tac that are possibly being eaten by the deer,” Inzalaco says.

The study did not test whether prion-carrying ticks did cause transmission to other deer.

Understanding more about how CWD can spread can help improve the management of the disease. While it isn’t practical to treat all wild deer with tick preventatives, Inzalaco believes better land stewardship could help manage tick populations.

For instance, having contiguous habitat of native plant communities and properly managing areas to continue a natural fire regime has been shown to limit tick populations, she says, while more fragmented, unbalanced ecosystems riddled with invasive plants may allow ticks to proliferate more readily.

Inzalaco says it might be possible to use ticks as a way to screen for CWD in both wild and farmed deer. Current methods of diagnosis or screening involve invasive sample collection from animals or tissue sampling after their death. While testing the ticks from deer may not lead to the same level of accuracy as testing tissue samples, it could still be a useful tool to better understanding where the disease is affecting deer population in the state.

Inzalaco also believes her research can help improve the ecosystems that everyone relies on, especially the state’s hunters.

“We are all inextricably linked to ecosystem function and the biodiversity of those ecosystems,” she says. “That is really what drives my desire to learn and do good science on a daily basis. We need to make an effort to preserve our natural heritage so that we can continue living on this planet and not be overtaken by disease and have healthy animals and healthy functioning ecosystems.”

Christofer Skurka, Jessica Myrick and graduate student Yin Yang found that seeing bad news about climate change can make people more afraid over time, but it also may encourage audiences to think about what society can do to address the problem. They published the results of two separate studies in an article titled “Fanning the flames or burning out? Testing competing hypotheses about repeated exposure to threatening climate change messages,” which appeared in the journal Climatic Change.

“The public is surrounded by media coverage about climate change, and this messaging tends to be negative in tone, focusing on the threats that climate change poses to human prosperity and ecological health,” said Skurka, the paper’s lead author and an assistant professor of media studies in the Donald P. Bellisario College of Communications. “We know from years of research in the field of communication that media messaging can impact our emotions, our beliefs and, in turn, sometimes our behavior.”

The first study involved exposing participants to three days of negative news stories about climate change. A follow-up study consisted of participants reading negative news headlines about climate change in the form of Twitter posts for seven consecutive days.

“We found that three days in a row of reading doom-and-gloom news stories about climate change was linked to greater fear and less hope, which can potentially hurt an audience’s attitude that they can do anything to tackle the problem,” said Myrick, the Donald P. Bellisario Professor of Health Communication and co-funded faculty member of the Institutes of Energy and the Environment. “However, our follow-up study had people look only at headlines and not full news stories for a longer period of seven days in a row. In that study, we found that fear peaked after a few days and then held steady.”

The researchers reported that over time, people who repeatedly saw climate change headlines started to feel like they could do more to affect change and that the topic of climate change was important.

“You would think that as people are repeatedly exposed to threatening climate news devoid of solutions content that their efficacy beliefs will decrease over time,” Skurka said. “We saw the opposite pattern in our second study. People’s efficacy beliefs increased over time. In other words, the more exposure people had to these threatening news stories each day, they were increasingly likely to think that they can make a difference in addressing climate change.”

Skurka said one possibility is that as the public copes with unpleasant feelings about the enormous threat climate change presents, they may convince themselves that they have control over the situation, which translates into greater efficacy beliefs that their actions will make a difference.

“Our findings suggest that people have gotten used to doom-and-gloom reporting around climate change and what may be more important for motivating them to take action is that they see coverage of it on a daily basis,” Myrick said. “This is called an agenda-setting effect, where a topic that is covered more often in the news is then viewed as more important by people who consume the news.”

According to Skurka, decades of research in communication and psychology show that under certain circumstances, fear can be motivating.

“We found that people exposed to the high-threat headlines, which tended to evoke more fear, generally expressed greater intentions to share the information than people exposed to the low-threat headlines, which means there may be an advantage to evoking fear,” Skurka said. “However, people’s responses over time were essentially the same regardless of whether they were shown the high-threat or low-threat news headlines. That tells us that when it comes to over-time responses to repeated media exposure, simply mentioning climate change in the news activates pre-existing emotions and thoughts associated with climate change.”

Myrick added that this does not mean that fear-appeals should be used for all climate change communication. Instead, the more important factor may be communicating hope and solutions.

“For communication to be most impactful, people need to feel like there is still something we can do about it to make a difference,” Myrick said. “That should hopefully motivate reporters and strategic communicators to include information about solutions to climate change in their messaging.”

The study is the first to exhaustively observe the natural evolution of the earliest stages of human cancers, starting with cells that have a single cancer-priming mutation and culminating with a panel of descendants harboring a galaxy of genetic abnormalities.

Identifying the first steps associated with future cancer development could not only facilitate earlier-than-ever diagnosis — when a deadly outcome is but a twinkle in a rogue cell’s eye — but may also highlight novel interventions that could stop the disease in its tracks, the researchers say.

“Ideally, we would find ways to intercept this progression before the cells become truly cancerous,” said Christina Curtis, PhD, professor of medicine, of genetics and of biomedical data science. “Can we identify a minimal constellation of genetic alterations that imply the cell will progress? And, if so, can we intervene? The striking reproducibility in the genetic changes we observed from multiple donors suggests it’s possible.”

Curtis is the senior author of the research, which was published on May 31 in Nature. The lead authors of the study are former postdoctoral scholar Kasper Karlsson, PhD, and visiting graduate student Moritz Przybilla.

Cells of nefarious beginnings

The research builds on previous work in Curtis’s laboratory indicating that some colon cancer cells are seemingly born to be bad — they acquire the ability to metastasize long before the disease is detectable.

“Our studies of established tumors showed us that early genomic alterations seem to dictate what happens later, and that many of these changes seem to happen before tumor formation,” Curtis said. “We wanted to know what happens at the very earliest stages. How does a cancer cell evolve, and is this evolutionary path repeatable? If we start with a given set of conditions, will we get the same result in every case?”

The researchers studied tiny, three-dimensional clumps of human stomach cells called gastric organoids. The cells were obtained from patients undergoing gastric bypass surgery to treat obesity. At the beginning of the study, the researchers nudged the cells toward cancers by disabling the production of a key cancer-associated protein called p53 that regulates when and how often a cell divides. Mutations in p53 are known to be an early event in many human cancers, and they trigger the accumulation of additional genetic changes including mutations and copy number alterations — in which repetitive regions of the genome are lost or gained during cell division.

Then they waited.

Every two weeks, for two years, Karlsson cataloged the genetic changes occurring in the dividing cells. When Karlsson and Przybilla analyzed the data they found that, although changes occurred randomly, those that conferred greater fitness gave their host cells an evolutionary advantage over other cells in the organoid. As the cells continued to divide and the cycle of mutation and competition repeated over many iterations, the researchers saw some common themes.

Predictable pathways

“There are reproducible patterns,” Curtis said. “Certain regions of the genome are consistently lost very early after the initial inactivation of p53. This was repeatedly seen in cells from independent experiments with the same donor and across donors. This indicates that these changes are cell-intrinsic, that they are hardwired into tumor evolution. At the same time, these cells and organoids appear mostly normal under the microscope. They have not yet progressed to a cancer.”

The researchers found that these early changes usually occur in biological pathways that control when and how often a cell divides, that interfere with a cell’s intricate internal signaling network coordinating the thousands of steps necessary to keep it running smoothly, or that control cell structure and polarity — its ability to know what is “up” and “down” and to situate itself with respect to neighboring cells to form a functioning tissue.

The researchers saw similar patterns occur again and again in cells from different donors. Like water flowing downhill into dry creek beds, the cells traced tried-and-true paths, gaining momentum with each new genetic change. Several of these changes mirror mutations previously observed in stomach cancer and in Barrett’s esophagus, a pre-cancerous condition arising from cells that line the colon and stomach.

“These changes occur in a stereotyped manner that suggest constraints in the system,” Curtis said. “There’s a degree of predictability at the genomic level and even more so at the transcriptomic level — in the biological pathways that are affected — that gives insights into how these cancers arise.”

Curtis and her colleagues plan to repeat the study in different cell types and initiating events other than p53 mutation.

“We’re trying to understand exactly what malignant transformation is,” Curtis said. “What does it mean to catch these cells in the act, about to topple over the edge? We’d like to repeat this study with other tissue types and initiating mutations so we can understand the early genetic events that occur in different organs. And we’d like to study the interplay between the host and the environment. Do inflammatory factors play a role in promoting progression? We know that it matters that the cells in these organoids are communicating with each other, and that is important to understanding progression and treatment response.”

Researchers from Karolinska Institutet, the University College London and the Chan Zuckerberg Biohub also contributed to the study.

The research was supported by the National Institutes of Health (grants DP1-CA238296 and U01-CA217851) and the Swedish Research Council.

The findings suggest grasslands that now cover much of the enormous island off the eastern coast of southern Africa were a relatively recent change facilitated by people rather than a natural habitat sustained in part by these famously large vegetarians.

The study was published in the journal Plants, People, Planet.

When Madagascar broke away from Africa’s mainland 150 million years ago, its plants and animals evolved in geographic isolation in the Indian Ocean. Madagascar had no elephants, giraffes, rhinos or other big mammals like those found on the mainland today.

But it did have hippos.

About the size of a cow, the dwarf or Malagasy hippo was far smaller than its four-ton cousin, the common hippopotamus. Even so, the Malagasy hippopotamus was among the largest land animals on the island along with Nile crocodiles and the flightless and enormous elephant bird.

These hippos likely resembled today’s secretive and endangered pygmy hippos found in the forests and swamps of West Africa’s Liberia and Guinea, said Brooke Crowley, a UC professor of geosciences and anthropology and lead author of the study.

“Ecologically, we think the Malagasy dwarf hippos were pretty close to the pygmy hippos that live in forests in West Africa,” Crowley said.

Crowley and her research colleagues conducted an isotopic analysis of stable carbon and nitrogen found in the bones of extinct Malagasy dwarf hippos that roamed the island more than 1,000 years ago. These isotopes, found in the bones of animals, leave behind a fingerprint of the foods they ate. And this provides clues about their preferred habitats.

Researchers took samples from the bones of dwarf hippos at museums along with those the team collected on the island. They found that dwarf hippos did not regularly graze on grass in dry, open habitats, even in regions dominated by grassland today. Instead, they preferred plants found in the wetter, more forested landscapes. This suggests forest was more abundant before people began changing the landscape to grow cultivated plants, graze domesticated cows and goats and obtain firewood and building materials.

Common hippos on the mainland love grass. Their name derives from the Greek words for “river horse.” Each night they leave the safety of rivers and waterholes to find fresh pasture, cropping grass like a horse, before returning in the morning.

But the researchers’ analysis found that grass represented only a small part of the diet of Malagasy dwarf hippos. Instead, they behaved more like browsers, feeding on sedges and leaves. As a result, hippos likely had little influence on maintaining or expanding grasslands on the island.

“For years we’ve seen evidence that these animals were not grazers,” said Laurie Godfrey, a study co-author and professor emerita at the University of Massachusetts Amherst.

Godfrey said there is evidence to suggest that people caused the extinction of hippos on the island when they created permanent communities and moved from hunting and gathering to raising domestic animals and crops. She calls her idea the “Subsistence Shift Hypothesis,” which she said is an elaboration on a similar idea first proposed by noted archaeologist Robert Dewar.

“There is pretty compelling convergent evidence showing that many of the extinct animals disappeared in a short window of time coinciding with the transition of people from hunting and gathering to pastoralism,” UC’s Crowley said.

Crowley thinks restoring native forests is key to helping conserve wildlife on the island. Based on their study, expansive grasslands were not a critical habitat, at least for the island’s hippos.

“Some colleagues argue that grasslands are ancient and that we need to protect and manage them like we do forest,” Crowley said. “I would argue that forests are far more important. We are not contending that grasses did not exist in the past, but pointing out that there is no evidence for large grasslands devoid of trees prior to about 1,000 years ago.”

It’s a point the researchers make in the study as well.

“It is clear that Madagascar faces a biodiversity crisis much greater than that which it has already endured. Preventing this crisis will demand new conservation actions,” the study concluded.

The study was supported by grants from the National Science Foundation, the African Regional Research Program Fulbright and the National Geographic Society.

But a new study from University of Wisconsin-Madison researcher Nan Li shows that intentionally integrating art with data visualizations can help non-expert audiences more meaningfully engage with climate change while also bridging political divides in ways that data alone cannot. In fact, data graphs on their own can exacerbate political division on climate change.

As an assistant professor in the Department of Life Sciences Communication, Li studies how innovative visual representations of science can shape people’s understanding and opinions about various scientific issues. Li teamed up with Isabel Villanueva, Thomas Jilk and Dominique Brossard from UW-Madison and Brianna Rae Van Matre from EcoAgriculture Partners to survey the responses of people across the political spectrum to a painting by Diane Burko entitled “Summer Heat, 2020.”

The painting depicts red, orange and blue motifs of wildfires and melting glaciers that overlap with maps that appear to drip over a graph of global atmospheric carbon dioxide levels. It’s not just art and science side-by-side or pretty colors added to a graph; the two are combined to tell a larger story that makes people stop and think about climate change.

Li thinks this intentional integration of the data into the piece of art is part of its success.

“In order for art to maximize its potential as a tool for public engagement, you really need to use it as a catalyst for triggering self-reflection,” Li says. “People use this piece of art as a starting point to think about what this all means to themselves.”

For the study, published in Communications Earth & Environment, 671 survey participants from across the U.S. were divided into groups and shown four different presentations of the painting and data it contains: the original painting, a detailed version of the graph it includes, a simplified version of that same graph and an edited version of the painting with a detailed graph.

In the first iteration of the survey, participants were instructed ahead of time to reflect on the meaning of and emotions evoked by the visuals. Survey participants who saw the paintings reported stronger positive emotions — like happiness, awe, inspiration and hope — than participants who were shown just the graphs.

The researchers then used a digital editing tool to represent what it would look like if “Summer Heat, 2020” and other visuals were posted to an Instagram feed. The caption contained more details about the painting and facts about climate change.

Participants felt the artwork post was as credible a source of information as the data graphs post. Li says this finding supports the idea that galleries aren’t the only way these kinds of artwork can be successful, but that bringing them to a larger audience through social media is beneficial as well.

In general, when people see graphs about climate change, whether they identify as liberal or conservative influences how they perceive the relevance of the issue. But in the new study, Li’s team saw that the gap between political affiliations was reduced when survey participants saw the painting in a social media format. In other words, when liberals and conservatives both see artistic representations of climate data rather than data alone, they are more likely to share the perception that climate change is relevant to them.

Another iteration of the survey did not instruct participants to reflect on the meaning and emotions the visuals inspired before seeing them. Participants viewed the simulated Instagram posts and then later reported their perceived relevance of climate change. This time, participants’ perceived relevance of climate change was equally polarized along their political ideology despite the different visuals they were shown. To Li, this suggests that priming people for introspection is important for breaking down political barriers.

While the findings are exciting, Li also recognizes this case study is very specific. The study is limited to the use of one painting in one style from one artist.

Moving forward, she and her team hope to complete additional studies that tease out what element of a piece makes communicating the scientific information more successful. They want to expand the study to consider reactions to other styles by artists from other backgrounds and survey reactions of people in other countries. Li and her team also highlight that it’s important for scientists and artists to be aware of their audience’s interest level in art and recognize that not everyone will react emotionally or cognitively to a piece in the same way.

Even though communicating these polarizing concepts can be challenging, Li believes in the ability of art to bridge the gap between a lay audience and scientific data.

“When you show art, I think it sort of makes people think, ‘Hey, wait a minute. What is this all about?'” Li says. “It fills in people’s imaginative deficit of what data means without taking a lecturing approach. It actually engages people to explore the meaning themselves.”

The study was published in the European Heart Journal.

“The gene ACTA2 codes a specific protein that has nothing to do with cholesterol,” said Dianna Milewicz, MD, PhD, senior author of the study and professor and director of the Division of Medical Genetics at McGovern Medical School at UTHealth Houston. “It was a surprise to find that people with the gene mutation had too much atherosclerosis at a young age and with no risk factors.”

A 2009 study led by Milewicz found that a number of mutations in ACTA2 predispose humans to develop early onset (30s or younger) coronary artery disease.

Atherosclerosis is a buildup of fats, cholesterol, and other substances in and on the artery walls. It can develop over time and most people don’t know they have it until they suffer a heart attack or stroke. Traditional risk factors for developing atherosclerosis include high cholesterol, high blood pressure, diabetes, smoking, obesity, lack of exercise, and consuming a high-fat diet.

ACTA2 is typically found in the smooth muscle cells, which line the arteries and allow the arteries to contract to control blood pressure and flow. Milewicz and her team found that protein coded by this gene is not folded correctly because of the mutation, and it triggers stress in the smooth muscle cell, which then forces the cell to make more cholesterol internally, regardless of the levels of cholesterol in the blood, driving atherosclerotic plaque formation.

“This finding is unique in that we found a completely new pathway to atherosclerosis. It explains why for years we have known statins protect people from heart attacks, even those people whose blood cholesterol levels are normal. In the people with ACTA2 mutations, the statins block the cholesterol made by the stressed smooth muscle cells,” said Milewicz, the President George Bush Chair in Cardiovascular Medicine with McGovern Medical School. “In our study, the mutant protein made by the ACTA2 mutation caused the cells in the artery wall to be stressed, but there are many other factors that can stress cells. We are now working on the risk factors for coronary artery disease, like hypertension, that would also stress the cells and activate this novel pathway for coronary artery disease.”

One of the results of stress in smooth muscle cells associated with atherosclerosis is the deposition of calcium in the arteries.

“Cardiac calcium imaging in individuals with ACTA2 mutations could be a useful early diagnostic tool to monitor the development of the early atherosclerosis in these people. This would allow physicians to decide at what age to start these patients on statins,” Milewicz said.

Using a genetically engineered mouse that contains a particular ACTA2 mutation and feeding the mice a diet rich in cholesterol, the researchers induced atherosclerosis and found that these mice have much more atherosclerosis than similarly treated mice normal mice. The study also found that the increased atherosclerosis could be reversed by treating the mice with pravastatin, a member of the statin group of drugs commonly prescribed to lower blood cholesterol. The researchers confirmed that same molecular pathway is activated in smooth muscles cells isolated from a human patient with an ACTA2 mutation.

Statins prevent coronary artery disease by lowering the levels of cholesterol in the blood. At the same time, more than half of heart attacks occur in apparently healthy men and women with average or low levels of plasma LDL-cholesterol. Statins also reduce heart attack events in people with normal cholesterol levels.

This work was supported by the National Heart, Lung, and Blood Institute (RO1 HL146583); an America Heart Association Merit Award, NIH T32GM120011; Marfan Foundation McKusick Fellowship Award; and American Heart Association Grant 20CDA35310689. Lipid profile analysis was performed at the Mouse Metabolism and Phenotypic Core at Baylor College of Medicine, funded by NIH RO1DK114356 and UM1HG006348. Single cell RNA sequencing was performed at the Single Cell Genomics Core at Baylor College of Medicine, funded by National Institutes of Health shared instrument grants S10OD023469, S10OD025240 and P30EY002520.

Additional UTHealth Houston authors include Kaveeta Kaw, MD, PhD; Abhijnan Chattopadhyay, PhD; Pujun Guan, MM; Jiyuan Chen, PhD; Suravi Majumder, PhD; Xue-yan Duan, PhD, and Callie S. Kwartler, PhD. Other authors include Shuangtao Ma, MD, MSc, with Michigan State University College of Human Medicine (a former postdoctoral fellow at UTHealth Houston) and Chen Zhang, MD, with Baylor College of Medicine.

The paper published in the journal PAIN is providing new insights — through its novel combination of individual- and macro-level measures — into geographic differences in pain and their causes.

“The risk of joint pain is over three times higher in some states compared to others, with states in the South, especially the lower Mississippi Valley and southern Appalachia, having particularly high prevalence of joint pain,” says Rui Huang, a sociology PhD student in the UB College of Arts and Sciences, and the paper’s first author. “We also observed educational disparities in joint pain in all states that vary substantially in magnitude, even after adjusting for demographic characteristics.”

The percentage point difference in pain prevalence between people who did not complete high school versus those who obtained at least a bachelor’s degree is much larger in West Virginia (31.1), Arkansas (29.7), and Alabama (28.3) than in California (8.8), Nevada (9.8) and Utah (10.1).

“Education can function as a ‘personal firewall’ that protects more highly educated people from undesirable state-level contexts, while increasing the vulnerability of less educated individuals,” says Huang.

Nearly 59 million people in the U.S. have arthritis, and at least 15 million of them experience severe joint pain because of that condition. Severe joint pain is associated with diminished range of motion, disability and mortality.

While existing research on the social determinants of pain has relied primarily on individual-level data, individuals are embedded in social contexts, such as a specific U.S. state.

Different states can have dramatically different policies that affect many aspects of life including opportunities, resources and social relationships, which can in turn influence individuals’ pain, a potential influence that has gone largely unexplored in previous research.

“Very little research has examined the geography of chronic pain, and virtually none has examined the role of state-level policies in shaping pain prevalence,” says Hanna Grol-Prokopczyk, PhD, UB associate professor of sociology, and a co-author of the study. “We were excited to identify state characteristics that reduce residents’ risk of pain.”

The current study does so by combining data on nearly 408,000 adults (ages 25-80) from the 2017 Behavioral Risk Factor Surveillance System with state-level data about SNAP programs (formerly known as food stamps), Earned Income Tax Credits, income inequality, social cohesion (relationship strength among community members), Medicaid Generosity Scores, and tobacco taxes.

Although SNAP programs exist in all 50 states, some states offer more expansive benefits to qualifying residents than others. States with more generous SNAP benefits had a lower prevalence of pain. The same was true for states with greater social cohesion, indicating that both material resources and social functioning play critical roles in shaping pain risk.

“The increase in the generosity of SNAP benefits could potentially alleviate pain by promoting healthier eating habits and alleviating the life stress associated with food insecurity,” says Huang. “Social factors such as conflict, isolation and devaluation are also among the ‘social threats’ that can lead to physical reactions such as inflammation and immune system changes.”

In addition to providing new information on pain disparities across states, the paper might also fuel a reorientation of pain research that puts equal emphasis on macro- and individual-level factors, according to Huang.

“Chronic pain can — and should — be addressed through macro-level policies, as well as through individual-level interventions,” says Huang. “This study also implies that pain research in general should move towards a greater understanding of the macro contextual factors that shape pain and pain inequalities.”