Jingwen Yan’s groundbreaking research, with help from $1.9M NIA grant, aims to identify early warning signs and key variations that could revolutionize Alzheimer’s detection and treatment.
The first signs seem so innocent, so common, so normal.
A missed appointment.
A struggle to grasp the name of a lifelong friend.
The inability to backtrack to find a missing set of keys.
Of course, by the time those first symptoms appear, Alzheimer’s disease’s deadly tentacles may have been creeping throughout the brain for years. And even then, the slow, heartbreaking, relentless march for both patient and loved ones could be far, far from over.
For those who have watched a loved one fade into the murky nothingness of Alzheimer’s disease, who have been there as the once intimately familiar becomes distressingly strange, the condition earns its epithet as The Long Goodbye.
Alzheimer’s is a long and merciless unraveling of identity that can take decades to fully manifest. For families, it is a prolonged farewell filled with uncertainty and fresh sadness daily. For researchers, it has proven to be an enduring challenge — a puzzle whose pieces begin to develop years before the first symptoms appear, its shards scattered across vast stretches of time.
$1.9M grant helping Jingwen Yan advance Alzheimer’s detection and treatment.
Associate Professor Jingwen Yan, director of the Bioinformatics Program at Indiana University’s Luddy School of Informatics, Computing, and Engineering, is determined to rewrite the story. With a $1.9 million grant from the National Institute on Aging awarded this September, she is using cutting-edge bioinformatics tools to study the subtle, progressive changes in the brain that occur during the early stages of Alzheimer’s. Her goal is ambitious yet essential: to identify early warning signs that could transform Alzheimer’s from an irreversible slow descent toward emptiness into a condition that can be detected — and possibly mitigated — before it takes hold.
“The disease itself can take up to 30 years to develop, but our research data often spans only a fraction of that time — seven or eight years at most,” Yan says.
The challenge is to connect these fragmented data points and build a clear picture of what’s happening during this long progression.
Jingwen Yan
Yan’s mission, then, is clear: lay the foundation to start turning The Long Goodbye into something more humane, a battle more bearable — and perhaps even winnable.
Big data, big opportunities, big problem
Yan’s research comes at a pivotal moment in Alzheimer’s studies. Just a decade ago, scientists were hampered by a lack of data about the disease, she says. Researchers struggled to develop accurate models for understanding its insidious progression because the sample sizes and available data sets were too small to draw meaningful conclusions.
Now, thanks to enormous investments in genomic research, neuroimaging, and other technologies, the pendulum has swung wide in the opposite direction. Researchers are inundated with data — far more than any one team can analyze effectively.
"We don’t have enough people to look at all the data we’ve collected.” Yan says. “We need to identify the critical biomedical questions and translate them into computational problems so that we can leverage the full power of artificial intelligence and bioinformatics."
Bioinformatics is an interdisciplinary field that combines biology, computer science, mathematics, and statistics to analyze biological data. It involves using computational tools and techniques to manage, visualize, and draw insights from complex datasets, such as genetic sequences, protein structures, and other biological information.
For Yan, this means taking the short-term snapshots of data collected from a disease that develops over decades and integrating them into computational models that illuminate the entire progression of Alzheimer’s, from pre-diagnosis to death. By connecting these often distant dots, her work aims to identify patterns in brain imaging, gene expression, and other biological markers that occur in the earliest, most subtle stages of the disease.
Inside the research project
The stakes of Yan’s work couldn’t be higher.
According to the Alzheimer’s Association, nearly 7 million Americans are living with Alzheimer's. By 2050, this number is projected to rise to nearly 13 million. Health and long-term care costs for people living with Alzheimer’s and related dementia conditions are projected to hit $360 billion this year and nearly $1 trillion in 2050.
Alzheimer’s currently has no cure, and while recent drug approvals have offered some hope by slowing the disease’s progression, these treatments are limited in scope and effective only after symptoms have already emerged, Yan says.
They can, in effect, make The Long Goodbye even longer, even more painful.
Yan’s research could change that by paving the way for earlier detection — and potentially earlier intervention. The $1.9 million grant will support a project focused on using computer tools to discover new genetic clues that explain how Alzheimer’s develops and progresses. The goal is twofold:
- Find genetic markers that show up at specific stages of the disease.
- Understand why people experience different symptoms and rates of progression.
One of the most exciting things about this project is the possibility of finding biomarkers in the early stages.”
Jingwen Yan
Yan says. “If we can model the entire progression of the disease, we can identify changes that happen before symptoms appear, giving us a chance to diagnose it earlier.”
This early detection could be transformative, allowing patients to seek interventions that delay or prevent the disease’s onset. Beyond that, Yan’s work also delves into the concept of subtyping — identifying distinct variations in how Alzheimer’s manifests in different patients. Understanding these subtypes could lead to personalized treatment plans tailored to each patient’s unique disease progression, a key step toward precision medicine.
Once scientists can identify these subtypes, they can start asking if there are genetic markers for different variations and if different subtypes respond differently to treatments, Yan says. This could help transition Alzheimer’s care from a one-size-fits-all approach to treatments that are specific to each patient’s needs.
A collaborative vision
Yan’s journey to this groundbreaking research reflects her ability to bridge disciplines and foster collaboration. Originally trained in computer vision and artificial intelligence, she pivoted to bioinformatics during her PhD studies at Indiana University. The strong partnership between the Luddy School and the IU School of Medicine provided her with an invaluable opportunity to work alongside some of the nation’s top neuroscientists, clinicians, and geneticists.
In the beginning, communication was a challenge, Yan admits. Doctors cared about their medical questions, and she cared about her algorithms. It took years of persistence to understand and meld each other’s priorities into an effective collaboration.
That effort has paid off. Today, Yan is not only a leader in her field but also an advocate for building bridges between computational science and medicine. She credits IU’s collaborative environment, including resources like the Center for Computational Biology and Bioinformatics, for enabling her team to tackle complex problems no single discipline could solve alone.
Molding future researchers
As director of the Luddy School’s Bioinformatics Program in Indianapolis, Yan is also focused on preparing the next generation of researchers to take on these challenges. With just four faculty members and around 70 graduate students in the program, she sees an urgent need to train more specialists who can interpret the mountains of data being generated in fields like Alzheimer’s research.
“We’ve gone from not having enough data to having too much data,” Yan says.
The challenge is making sense of all [the data] and ensuring we have enough people equipped to do that.
Jingwen Yan
Her work with students mirrors her approach to research — bridging gaps, fostering collaboration, and translating complexity into actionable insights. It’s a model that not only advances science but also ensures its impact reaches patients and their families.
Rewriting the narrative
For families facing Alzheimer’s, the disease often feels like a relentless thief, stealing loved ones piece by piece. But Yan’s work offers a glimmer of hope — a hazy vision of a future where The Long Goodbye might be shortened, eased, or perhaps avoided altogether.
By using bioinformatics to unravel the mysteries of Alzheimer’s, Yan is charting a path toward earlier detection, personalized treatments, and better outcomes. The recent $1.9 million grant is more than a recognition of her work, Yan says; it is an investment in a future where the story of Alzheimer’s can be rewritten from one of inevitable loss into one of hope.