Early puberty and early childbirth may come with a cost

Reproductive timing can accelerate aging and disease

Buck Institute for Research on Aging

LinkedInWeChatBlueskyMessageWhatsAppEmail

Reproductive timing matters when it comes to aging and age-related disease.  In a study now online at eLife¸ Buck researchers determine that girls who go through puberty (the onset of menstruation) before the age of 11 or women who give birth before the age of 21 have double the risk of developing type 2 diabetes, heart failure and obesity and quadruple the risk of developing severe metabolic disorders. The study also reveals that later puberty and childbirth are genetically associated with longer lifespan, lower frailty, slower epigenetic aging and reduced risk of age-related diseases, including type 2 diabetes and Alzheimer’s.

Buck professor Pankaj Kapahi, PhD, senior author of the study says the public health implications of the research are significant.  “Even though women are routinely asked about their menstrual and childbirth history when they receive medical care, this information has rarely factored into the care they receive outside of OB/GYN,” he says. “These risk factors, whether positive or negative, clearly have significant influence on a variety of age-related diseases and should be considered in the larger context of overall health.”

The research was based on one of the most comprehensive analyses to date, using regression analysis on nearly 200,000 women in the UK Biobank to confirm genetic associations. “We identified 126 genetic markers that mediate the effects of early puberty and childbirth on aging,” said postdoctoral fellow Yifan Xiang, MD, who led the research. “Many of these markers are involved in well-known longevity pathways, such as IGF-1, growth hormone, AMPK and mTOR signaling, key regulators of metabolism and aging.” 

Genetic associations for antagonistic pleiotropy in humans

Evolution is based on natural selection acting on traits early in life to encourage reproduction and survival of the species. The antagonistic pleiotropy theory of aging suggests that traits beneficial in the young can have negative effects later in life.  “Our study provides some of the strongest human evidence for this theory,” Kapahi says. “We show that genetic factors favoring early reproduction come with the significant cost later in life including accelerated aging and disease. It makes sense that the very factors that help enhance survival of the offspring may lead to detrimental consequences for the mother.”

The role of BMI in aging and disease risk

Kapahi says the study highlights the role of Body Mass Index (BMI) as a critical mediator of this process, finding that early reproductive events contribute to a higher BMI, which in turn increases the risk of metabolic disease.  "One can envisage that enhancing the ability to absorb nutrients would benefit the offspring but if nutrients are plentiful then it can enhance the risk of obesity and diabetes.”                                                                                                       

Implications for public health and basic science

Kapahi says understanding the long-term impact of reproductive timing allows for the development of personalized healthcare strategies that could help mitigate the risks associated with early puberty and early childbirth, adding that lifestyle modifications, metabolic screenings and tailored dietary recommendations could improve long-term health in women.  He says taking reproductive timing into account is currently relevant based on research that shows the age at which girls in the US begin menstruating has dropped by about three months per decade since the 1970s. No specific causes for the phenomena have been identified, but research suggests obesity may play a role.

While updated research guidelines call for the use of both sexes in preclinical research in mice, Kapahi says this current study still challenges traditional experimental design, noting that most disease models use virgin female mice, which may not accurately represent real-world aging patterns.

“If evolution has shaped us to prioritize early reproduction at the cost of aging, how can we leverage this knowledge to extend healthspan in modern society? Kapahi asks.  “While we cannot change our genetic inheritance, understanding these genetic tradeoffs empowers us to make informed choices about health, lifestyle and medical care.” The study also identifies several genetic pathways that can be manipulated to optimize health for mothers as well as her offspring Kapahi says.

CITATION: Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

DOI:   https://doi.org/10.7554/eLife.102447.4

Other Buck researchers involved in the study include: Vineeta Tanwar, Parminder Singh, and Lizellen La Follette, 

Acknowledgements: This research was supported by Hevolution Foundation (PK), National Institute of Health grant R01AG068288 and R01AG045835 (PK), Larry L. Hillblom Foundation (PK), and Larry L. Hillblom Foundation (PS). 

About the Buck Institute for Research on Aging

At the Buck, we aim to end the threat of age-related diseases for this and future generations. We bring together the most capable and passionate scientists from a broad range of disciplines to study mechanisms of aging and to identify therapeutics that slow down aging. Our goal is to increase human health span, or the healthy years of life. Located just north of San Francisco, we are globally recognized as the pioneer and leader in efforts to target aging, the number one risk factor for serious diseases including Alzheimer’s, Parkinson’s, cancer, macular degeneration, heart disease, and diabetes. The Buck wants to help people live better longer. Our success will ultimately change healthcare. Learn more at: https://buckinstitute.org

 

 

---

Journal

eLife

DOI

10.7554/eLife.102447.4 

Method of Research

Data/statistical analysis

Subject of Research

People

Article Title

Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

Article Publication Date

19-Aug-2025

 

New method advances reliability of AI with applications in medical diagnostics

Johns Hopkins Medicine

LinkedInWeChatEmail

 

image: 

MIGHT algorithm for AI-informed medical decisions and MIGHT-informed liquid biopsies for distinguishing cancer from inflammatory diseases

view more 

Credit: Elizabeth Cooke

Two studies led by Johns Hopkins Kimmel Cancer Center, Ludwig Center, and Johns Hopkins Whiting School of Engineering researchers report on a powerful new method that significantly improves the reliability and accuracy of artificial intelligence (AI) for many applications. As an example, they apply the new method to early cancer detection from blood samples, known as liquid biopsy.

One study reports on the development of MIGHT (Multidimensional Informed Generalized Hypothesis Testing), an AI  method that the researchers created to meet the high level of confidence needed for AI tools used in clinical decision making.  To illustrate the benefits of MIGHT, they used it to develop a test for early cancer detection using circulating cell-free DNA (ccfDNA)—fragments of DNA circulating in the blood. A companion study found that ccfDNA fragmentation patterns used to detect cancer also appear in patients with autoimmune and vascular diseases. To develop a test with high sensitivity for cancer but reduced false-positive results, MIGHT was expanded to incorporate data from autoimmune and vascular diseases obtained from colleagues at Johns Hopkins and other institutions who treat and study these diseases.

The studies, supported in part by the National Institutes of Health, are to be published on Aug. 18 in the Proceedings of the National Academy of Sciences. 

A related article, authored by three researchers from Johns Hopkins, Pixar co-founder Ed Catmull, Ph.D., and Microsoft chief data scientist of the AI for Good Lab Juan Lavista Ferres, was published concurrently in Cancer Discovery, a publication of the American Association for Cancer Research.  It discusses the challenges of incorporating AI into clinical practice, including challenges addressed by MIGHT.

MIGHT fine-tunes itself using real data and checks its accuracy on different subsets of the data, using tens of thousands of decision-trees, and can be applied to any field employing big data, ranging from astronomy to zoology. It is particularly effective for the analysis of biomedical datasets with many variables but relatively few patient samples, a common situation in which traditional AI models often falter. 

In tests using patient data, MIGHT consistently outperformed other AI methods in both sensitivity and consistency. It was applied to the blood of 1,000 individuals—352 patients with advanced cancers and 648 individuals without cancer. For each sample, the researchers evaluated 44 different variable sets, each consisting of a set of biological features, such as DNA fragment lengths or chromosomal abnormalities, and found that aneuploidy-based features (an abnormal number of chromosomes) delivered the best cancer detection performance with a sensitivity of 72% (ability to detect cancer) at 98% specificity (correctly identified those who were cancer free). This balance is critical in real-world medical applications where minimizing false positives is necessary to avoid unneeded procedures.

“MIGHT gives us a powerful way to measure uncertainty and increase reliability, especially in situations where sample sizes are limited but data complexity is high,” says Joshua Vogelstein, Ph.D., associate professor of biomedical engineering and a lead investigator.

MIGHT was also extended to a companion algorithm, called CoMIGHT, to determine whether combining multiple variable sets could improve cancer detection. 

The researchers applied CoMIGHT to blood samples from 125 patients with early stage breast cancers and 125 patients with early-stage pancreatic cancer, which were analyzed along with 500 controls (participants without cancer). While pancreatic cancers were more often detected than breast cancers, CoMIGHT analysis suggested that early-stage breast cancer might benefit from combining multiple biological signals, highlighting the tool’s potential for tailoring detection strategies by cancer type. 

In the companion study, researchers Christopher Douville, Ph.D., assistant professor of oncology, Samuel Curtis, Ph.D., postdoctoral fellow in the Ludwig Center, and their teams serendipitously discovered that ccfDNA fragmentation signatures previously believed to be specific to individuals with cancer also occur in patients with other diseases, including  autoimmune conditions such as lupus, systemic sclerosis and dermatomyositis, and vascular diseases like venous thromboembolism. 

Among individuals with abnormal fragmentation signatures, they found an increase in inflammatory biomarkers in all patients, whether they had autoimmune diseases, vascular disease or cancer. Their results suggest that inflammation—rather than cancer per se— is responsible for fragmentation signals, complicating efforts to use ccfDNA fragmentation as a biomarker specific for cancer. 

To address the challenge of misconstruing inflammation for cancer, the team added information characteristic of inflammation in its training data for MIGHT. The enhanced version reduced, but did not completely eliminate, the false-positive results from non-cancerous diseases. “Our main goal was to further investigate the biological mechanisms responsible for fragmentation signatures that have previously been thought to be specific for cancer,” says Curtis. “As the field moves to more complex biomarkers, understanding the underlying biological mechanisms leading to the results are critical to their interpretation, particularly to avoid false positive results. Our new data indicate that patients with diseases other than cancer can be mistakenly believed to have cancer unless appropriate safeguards are incorporated into the tests.” 

Adds Douville, “A silver lining of this study is that reworking of MIGHT could result in a separate diagnostic test for inflammatory diseases.” 

Together, the studies demonstrate the promise as well as the complexities of developing trustworthy clinical technologies using AI. In a related editorial, researchers noted several critical challenges that need to be addressed so that tools like MIGHT can be fully integrated into clinical practice. 

They identified eight key barriers to bringing AI into routine clinical care. In simple terms, these include the false expectation that AI tools need to be flawless before they’re considered useful; the need to present results as probabilities rather than simple yes-or-no answers; making sure AI predictions match real-world probabilities; ensuring results are reproducible; training models on diverse populations; explaining how AI makes decisions; recognizing how test accuracy can change when diseases are rare; and avoiding over-reliance on computer-generated recommendations. 

“MIGHT could be applied to any field where measuring uncertainty and having confidence in the reliability and reproducibility of findings is key. This could be in the natural sciences, social sciences, or medical sciences. Research across all fields of science requires confidence that what the algorithm is spitting out is real, reproducible, and reliable,” says Joshua Vogelstein.

The researchers say results obtained using AI technologies should be viewed as AI-informed data that can complement but not replace clinical judgment. Although MIGHT and CoMIGHT offer powerful new tools in cancer detection, and potentially inflammatory and vascular disease detection, they say that further clinical trials and validation are necessary before such tests can be extended to clinical use. 

“Trust in the result is essential, and now that there is a reliable, quantitative tool in MIGHT, we and other researchers can use it and focus our efforts on studying more patients and adding statistically meaningful features to our tests for earlier cancer detection,” says Bert Vogelstein, M.D., Clayton Professor of Oncology, co-director of the Ludwig Center, Howard Hughes Medical Institute investigator, and study co-leader. 

MIGHT and its companion algorithm, CoMIGHT, are now publicly available at treeple.ai.

The study  is a collaborative effort with researchers in Vietnam, led by Lan Ho-Pham and Tuan Nguyen, who provided critical clinical data, samples, and interpretation to the study.

In addition, to Joshua Vogelstein, Douville, Curtis, and Bert Vogelstein, researchers from Johns Hopkins were Tingshan Liu, Sambit Panda, Adam Li, Haoyin Xu, Yuxin Bai, Admin Li, Lisa Dobbyn, Maria Popoli, Janine Ptak, Natalie Stillman, Chris Thoburn, Maximillian Konig, Michelle Petri, Antony Rosen, Christopher Mecoli, Ami Shah, Itsuki Ogihara, Eliza O’Reilly, Yuxuan Wang, Michael Goggins, Tian-Li Wang, Ie-Ming Shih, Amanda Fader, Anne Marie Lennon, Ralph Hruban, Chetan Bettegowda, Kenneth Kinzler, and Nickolas Papadopoulos. The research team also included investigators from the University of Pittsburgh, the University of Texas MD Anderson Cancer Center and NYU Langone in the U.S., and the University of Melbourne in Australia, Saigon Precision Medicine Research Center, Pham Ngoc Thach University, and Tam Anh Research Institute in Ho Chi Minh City, Vietnam; the University of New South Wales; McGill University Health Centre in Montreal; and Amsterdam University Medical Centers. In addition to Catmull and Ferres, the editorial was authored by Elliot Fishman, Bert Vogelstein, and Joshua Vogelstein. 

These studies were supported by National Institutes of Health grants R21NS113016, RA37CA230400 U01CA230691, U01CA230691, 5P50CA062924-22, T32GM119998, Oncology Core CA 06973, Ovarian Cancer SPORE, DRP 80057309 and 1R21A1766764-01; the Virginia and D.K. Ludwig Fund for Cancer Research; the Lustgarten Foundation, the Commonwealth Fund; the Thomas M. Hohman Memorial Cancer Research Fund; the Sol Goldman Sequencing Facility at Johns Hopkins; the Conrad R. Hilton Foundation; the Benjamin Baker Endowment 80049589; Swim Across America/Baltimore; JHTV Innovation Grant, the Burroughs Wellcome Career Award for Medical Scientists; the Thomas M. Hohman Memorial Cancer Research Fund; the National Health and Medical Research Council Investigator Grant APP1194970; the National Science Foundation NSF Computing Innovation Fellowship 2127309 and award DMS-1921310; the Rheumatology Research Foundation Investigator Award; the Harrington Discovery Institute Scholar-Innovator Awardl the Jerome L. Greene Foundation; the Cupid Foundation; and the Stephen & Renee Bisciotti Foundation. 

Bert Vogelstein, Kenneth Kinzler, and Nickolas Papadopoulos are founders of Thrive Earlier Detection, an Exact Sciences Company. Kinzler, Papadopoulos, and Christopher Douville are consultants to Thrive Earlier Detection. B. Vogelstein, Kinzler, Papadopoulos, and Douville hold equity in Exact Sciences. B. Vogelstein, Kinzler, and Papadopoulos are founders of and own equity in Haystack Oncology and ManaT Bio. Kinzler and Papadopoulos are consultants to Neophore. Kinzler, B. Vogelstein, and Papadopoulos hold equity in and are consultants to CAGE Pharma. B. Vogelstein is a consultant to and holds equity in Catalio Capital Management. Chetan Bettegowda is a consultant to Depuy-Synthes, Bionaut Labs, Haystack Oncology and Galectin Therapeutics and is a co-founder of OrisDx. Bettegowda and Douville are co-founders of Diagnostics. The companies named above, as well as other companies, have licensed previously described technologies related to the work described in this paper from The Johns Hopkins University. B.Vogelstein, Kinzler, Papadopoulos, Bettegowda, and Douville, are inventors on some of these technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to The Johns Hopkins University. Patent applications on the work described in this paper may be filed by The Johns Hopkins University. The terms of all these arrangements are being managed by The Johns Hopkins University in accordance with its conflict-of-interest policies.

---

Journal

Proceedings of the National Academy of Sciences

 

An alphabet for hand actions in the human brain

Analogous to how all of the words in a language can be created by recombining the letters of its alphabet, the full repertoire of human hand actions can be built out of a small number of basic building block movements.

Carnegie Mellon University

WeChat
WhatsAppEmail

Using a corkscrew, writing a letter with a pen or unlocking a door by turning a key are actions that seem simple but actually require a complex orchestration of precise movements. So, how does the brain do it?

According to a new study by researchers from Carnegie Mellon University and the University of Coimbra, the human brain has a specialized system that builds these actions in a surprisingly systematic way.

Analogous to how all of the words in a language can be created by recombining the letters of its alphabet, the full repertoire of human hand actions can be built out of a small number of basic building block movements.

The researchers used computational modeling of functional MRI data to demonstrate that a brain region called the supramarginal gyrus (SMG) — located in the left inferior parietal lobe and already known for its role in planning object-directed actions — builds representations of complex actions by recombining a limited set of coordinated movement patterns of the fingers, hands, wrists, and arms. Scientists call these movement patterns “kinematic synergies”.

For instance, the posture of the hand while using a pair of scissors is similar to that when using a pair of pliers — even though scissors and pliers have very different functions. By contrast, even though a pair of scissors and an X-ACTO knife might be used for the same function or purpose, the postures of the hand when using the two types of objects would be very different. The researchers found that activity in the SMG portion of the brain had very similar representations for objects that also had very similar hand postures. 

“Just as brain regions supporting language function combine sounds, or phonemes, to form words, the brain also combines kinematic synergies to form complex, object-directed actions,” said Leyla Caglar, lead author of the study, which will be published in Proceedings of the National Academy of Sciences on August 18, 2025. “From this closed set of basic building blocks, the brain constructs the full repertoire of actions that can be performed with the human hand.”

Caglar is currently a postdoctoral fellow at Mount Sinai Medical Center. She led this research effort while she was a postdoctoral fellow, jointly at Carnegie Mellon University and the University of Coimbra, Portugal. This research was jointly funded by grants from the National Institute of Health, the Pennsylvania Department of Health and The European Research Council.

“These findings support the idea that the supramarginal gyrus functions as an assembly hub, combining basic elements of actions into more complex, functional sequences,” explained Caglar.

Implications for Robotics, Brain-Machine Interfaces and Action Deficits Caused by Brain Injury

While the idea that the brain uses a combinatorial structure of motor synergies is not new to this study, the new evidence provided by this study has far-reaching implications for robotics and the development of effective brain-computer interfaces.

“If we can map these synergies directly from neural activity, we could build more efficient brain-machine interfaces that allow users to control prosthetics with greater naturalness, precision and flexibility,” says study author Dr. Jorge Almeida. “This also moves us closer to creating artificial systems capable of acting with agility, efficiency and intelligence comparable to that of humans,” said Almeida.

The discovery might also offer new perspectives on disorders such as apraxia — a neurological condition in which patients can lose the ability to use objects correctly, despite being able to recognize the objects they cannot use. “Just as a deficit to the ability to properly assemble the sounds of language into words impairs language function, damage to this brain area can make it difficult for people to plan and carry out complex actions with objects.”

Integration of Cognition, Perception and Action

Of course, when we use our hands to grasp objects we don’t have to ‘think’ about building up actions out of their elemental parts — just like native speakers of a language don’t have to think about how to say the words they want to use. The processes supported by the supramarginal gyrus are always running automatically in the background, behind what we are thinking about in any given moment.

A key aspect of the system that supports complex hand actions is that its location – about one inch above and behind the left ear – is strategically located in the brain to receive and integrate many different types of information. These include visual, tactile, motor and conceptual information about the world and the status of the body.

The structure and organization of the brain reflects the integration of each individual’s lived experience with evolutionarily constrained structures. We are not born knowing how to manipulate, for instance, a key, or a pen — the specific way to use objects must be learned, and is a type of cultural knowledge. Despite the very different kinds of interactions with objects that different people have, and despite differences in manual dexterity across individuals, all humans have a common neural system that supports complex object directed interactions. 

Similarly, by analogy, while human infants are not born speaking any particular language, human infants are able to become a native speaker of any language in the world — and all humans have a common neural system that supports language.

“This study moves us one step closer to understanding the fundamental principles of brain organization that make human tool use possible,” said Caglar.  

---

Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2421032122 

Method of Research

Computational simulation/modeling

Subject of Research

People

Article Title

Object-directed action representations are componentially built in the parietal cortex

Article Publication Date

18-Aug-2025

COI Statement

BZM holds intellectual property (PCT/US2019/064015, US2022/0039732) associated with predictive analytics in neuromedicine, and is co-founder and CSO of MindTrace Technologies, Inc., which licenses some of that intellectual property from Carnegie Mellon University.

Marxists.orgwww.marxists.org/archive/marx/works/1876/part-played-labour/

The Part Played by Labour in the Transition from Ape to Man

On the other hand, the development of labour necessarily helped to bring the members of society closer together by increasing cases of mutual support and joint ...

Catching a 'eureka' before it strikes: New research spots the signs

University of California - Merced

Facebook

XLinkedInWeChatBluesky
Email

They feel like lightning — sudden, brilliant and seemingly impossible to predict. But according to new research, those mind-flashing “aha” moments of insight may leave detectable traces before they strike.

Scientists have developed a way to identify subtle behavioral changes that happen minutes before a breakthrough, offering a new window into the elusive mechanics of human creativity.

The study was published in the Proceedings of the National Academy of Sciences. Shadab Tabatabaeian, who earned her Ph.D. in Cognitive and Information Sciences from the University of California, Merced, is lead author, and Tyler Marghetis, UC Merced assistant professor of Cognitive and Information Sciences, is senior author. Co-authors are Artemisia O’bi (Indiana University) and David Landy (Netflix and Indiana University).

Their work builds on theories from statistical physics and ecology to answer an old question with a modern twist: Can we spot the approach of a eureka moment in real time?

The team video-recorded six Ph.D.-level mathematicians as they wrestled with notoriously tough problems from the William Lowell Putnam Mathematical Competition. Filming took place in the mathematicians’ offices and in seminar rooms, chalk in hand. The researchers documented more than 4,600 moment-to-moment interactions with blackboard “inscriptions” — writing, pointing, erasing and shifting attention.

They found a striking pattern. In the minutes before a mathematician suddenly exclaimed “aha!” or “I see it!” their behavior became measurably less predictable. Familiar patterns of moving between ideas gave way to novel, unprecedented connections.

Using a measure from information theory, the researchers quantified this unpredictability and found it reliably ramped up before verbalized insights.

“This is one of those discoveries that was possible only because we made connections between very different scientific disciplines,” Marghetis said. “We took ideas from ecology and physics, added tools from information theory, and combined them with a century of work on the psychology of creativity.

“The resulting discovery belongs to all of those disciplines but also to none of them. It's its own thing.”

Though the experiment focused on expert mathematics, the researchers said the method could work in any field where thinking unfolds in observable steps, such as a chemist sketching molecular bonds, a designer shifting between prototypes, or an artist exploring new forms. The authors suggest their approach could help scientists better understand the micro-dynamics of creativity and, perhaps, even predict breakthroughs before they happen.

---

Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2502791122 

Method of Research

Observational study

Subject of Research

People

Article Title

An information-theoretic foreshadowing of mathematicians’ sudden insights

Article Publication Date

18-Aug-2025

SERPENTOLOGY

When rattlesnakes marry their cousins

Inbreeding is hurting Michigan’s only rattlesnake. A long-term study shows how

Michigan State University

Facebook\

XLinkedInWhatsAppEmail

 

image: 

Researcher team members used snake tongs to catch Eastern Massasauga rattlesnakes for their 15-year study.

view more 

Credit: Sarah Fitzpatrick

Roads, buildings and farms are preventing Michigan’s only rattlesnake from finding mates outside of their population. A 15-year study shows that fragmentation into smaller, more isolated patches is likely reducing the threatened snake’s chances of survival. 

Michigan State University conservation biologists traced the family histories of more than 1,000 Eastern Massasauga rattlesnakes caught and released in a U.S. Fish and Wildlife Service-funded project. The new findings, published in the Proceedings of the National Academy of Sciences, surprised even the researchers – the most inbred snakes were 13% less likely to have surviving offspring and had a nearly 12% lower annual survival rate. 

These results paint a striking picture of the need for rattlesnake habitat connectivity to be restored, MSU Professor Sarah Fitzpatrick said. 

“These are fairly large and stable populations of Eastern Massasaugas,” said Fitzpatrick, a senior author on the study. “The fact that we’re detecting problems from inbreeding in these populations is concerning, given that many other populations throughout the Midwest are much smaller and even more fragmented.” 

While Eastern Massasauga rattlesnakes aren’t the most popular animal, they’re keystone species of wetland food webs throughout the Midwest. They hunt prey like mice and rats that otherwise might run rampant in nearby homes and barns. If rattlesnakes disappeared, the entire balance of the ecosystem would be disrupted, said Meaghan Clark, lead author and former MSU graduate student in Fitzpatrick’s lab. 

These rattlesnakes are homebodies who typically don’t like to venture beyond the wetland where they were born. They only wander to explore a nearby habitat and find a mate before returning home. 

But an increasing human presence – and developments such as roads, farms and houses – are likely keeping Eastern Massasaugas even more homebound. That means when it’s time to choose a mate, they are more likely to end up with a relative instead of an out-of-towner. 

“They’re very vulnerable to even minor disturbances to their habitat,” Fitzpatrick said. “Even a single road can isolate populations.” 

When animals have offspring with their relatives, there’s usually a negative impact to their babies’ fitness. In the evolutionary sense, an animal’s fitness doesn’t mean how many pushups they can do or how much they can bench press. Researchers use “fitness” to describe how successful an animal is at surviving, producing babies and continuing the species.  

A decrease in fitness resulting from inbreeding is known to conservationists as “inbreeding depression.” But that’s difficult to prove in wild populations, especially snakes with a venomous bite. 

Fitzpatrick’s lab joined forces with long-term monitoring projects in Cass and Barry counties, partnering with Jennifer Moore at Grand Valley State University, Eric Hileman at West Virginia University, and Lisa Faust from the Association of Zoos and Aquariums. Each summer since 2009 and 2011, respectively, their research teams have donned tall rubber boots and armed themselves with snake tongs to trek through wetlands and capture the elusive reptile.  

The teams checked each captured snake’s length, weight and pregnancy status and drew blood, which they used to extract DNA and sequence their genomes. These details were enough for researchers to reconstruct pedigrees and determine how closely any two individual snakes were related. Each snake was marked with a PIT tag, similar to a microchip for a pet, before being released back into the wild. 

By returning to the same wetlands year after year, researchers could track snakes’ survival based on whether they were eventually recaptured. Genomic sequencing made it possible to generate a family tree for each population, track how many snake babies were born and survived to adulthood, and determine who their parents were. 

“This long-term field monitoring is the backbone of the study,” Clark said. “Having people out each season catching these snakes made all of this possible.” 

Fitzpatrick hopes the study informs conservation efforts that help Eastern Massasaugas find mates outside their families, especially in declining populations beyond Michigan. Small changes, like habitat restoration or building road underpasses, could promote more connectivity that would boost the gene pool and give the snakes a better shot at survival. Conservationists could also explore moving imperiled rattlesnakes to new habitats with more options for finding mates. 

They may be feared and misunderstood, but the Eastern Massasauga is a silent ally. Ensuring their survival could keep Michigan’s wetlands balanced and thriving for generations.  

Researchers catch Eastern Massasauga rattlesnakes every summer as part of a 15-year study.

Credit
Sarah Fitzpatrick



Eastern Massasauga rattlesnakes live in Michigan as well as other Midwestern states.



Eastern Massasauga rattlesnakes live in Michigan and other Midwestern states.


Credit
Eric Hileman

Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2501745122 

Subject of Research

Animals

Article Title

Inbreeding reduces fitness in spatially structured populations of a threatened rattlesnake

Article Publication Date

18-Aug-2025