![\"This](\"https:\/\/www.newsbeep.com\/ie\/wp-content\/uploads\/2025\/10\/AI-genetics-Alzheimers-neuroscinec.jpg\")
The researchers tested the algorithm and found that it performed better than existing tools, identifying important disease-relevant cellular signals more clearly. Credit: Neuroscience News<\/p>\nSummary: A new computational tool developed by researchers has uncovered genetic evidence directly linking Alzheimer\u2019s disease to the loss of memory-making neurons, helping to resolve a decades-long mystery in dementia research. The algorithm, called seismic, matches genetic data to individual cell types, outperforming previous methods and highlighting how specific brain cells\u2014not just immune cells\u2014are implicated in Alzheimer\u2019s.<\/p>\n
By merging large-scale genetic and cellular data, the tool provides a clearer view of how genetic risk translates into cellular vulnerability. Researchers say the technique could reshape how scientists identify disease-relevant cells across a wide range of neurological and metabolic disorders.<\/p>\n
Key Facts:<\/p>\n
Novel Algorithm: The seismic tool integrates genetic and cellular data to map which cell types drive disease.Revealed Link: Found genetic evidence tying Alzheimer\u2019s risk to memory-related neurons rather than immune cells.Broad Utility: The method can be applied to other complex diseases like Parkinson\u2019s, aiding in early detection and drug targeting.<\/p>\n
Source: Rice University<\/p>\n
The number of people living with dementia worldwide was\u00a0estimated at 57 million\u00a0in 2021 with nearly 10 million new cases recorded each year. In the U.S., dementia impacts more than 6 million lives, and the number of new cases is expected to double over the next few decades, according to a\u00a02025 study. <\/p>\n
Despite\u00a0advancements in the field, a full understanding of disease-causing mechanisms is still lacking.<\/p>\n
The researchers tested the algorithm and found that it performed better than existing tools, identifying important disease-relevant cellular signals more clearly. Credit: Neuroscience News<\/p>\n
To address this gap, Rice University researchers and collaborators at Boston University have developed a computational tool that can help identify which specific types of cells in the body are genetically linked to complex human traits and diseases, including in forms of dementia such as Alzheimer\u2019s and Parkinson\u2019s.<\/p>\n
Known as \u201cSingle-cell Expression Integration System for Mapping genetically implicated Cell types,\u201d or seismic, the tool helped the team hone in on genetic vulnerabilities in memory-making brain cells that link them to Alzheimer\u2019s \u23af the first to establish an association based on a genetic link between the disease and these specific neurons. The algorithm outperforms existing tools for identifying cell types that are potentially relevant in complex diseases and is applicable in disease contexts beyond dementia.<\/p>\n
The research,\u00a0published in\u00a0Nature Communications, helps unravel a long-standing contradiction in Alzheimer\u2019s research: While genetic clues in patients\u2019 DNA point to infection-fighting cells in the brain, i.e. microglia, as the cell type most robustly implicated in the disease pathology, patients\u2019 brains actually tell a different story.<\/p>\n
\u201cAs we age, some brain cells naturally slow down, but in dementia \u23af a memory-loss disease \u23af specific brain cells actually die and can\u2019t be replaced,\u201d said Qiliang Lai, a Rice doctoral student who is the first author on the study.<\/p>\n
\u201cThe fact that it is memory-making brain cells dying and not infection-fighting brain cells raises this confusing puzzle where DNA evidence and brain evidence don\u2019t match up.\u201d<\/p>\n
The team\u2019s investigation used computational methods to analyze existing genetic data in a new way. Their method integrates two types of large-scale biological data \u23af genome-wide association studies (GWAS) and single-cell RNA sequencing (scRNA-seq), where GWAS analyze the human genome to find small differences in DNA that are shared among people with a certain disease or trait, while scRNA-seq measures which genes are active in tens of thousands to millions of individual cells, creating a detailed map of how cells differ at the molecular level.<\/p>\n
Previous attempts to draw correlated insights from these types of data were difficult to scale and interpret and yielded less robust associations due to two main weaknesses:<\/p>\n
First, in terms of scRNA-seq, cell type resolution can be too broad and overgeneralize, missing critical detail such as brain region where the cells are located; second, in terms of GWAS, the genetic signal in large studies based on clinical diagnoses tends to overemphasize cell types that are more consistently affected, i.e. immune-related cells, drowning out other aspects of the disease.<\/p>\n
\u201cWe built our seismic algorithm to analyze genetic information and match it precisely to specific types of brain cells,\u201d Lai said. \u201cThis enables us to create a more detailed picture of which cell types are affected by which genetic programs.\u201d<\/p>\n
The researchers tested the algorithm and found that it performed better than existing tools, identifying important disease-relevant cellular signals more clearly.<\/p>\n
\u201cWe think this work could help reconcile some contradicting patterns in the data pertaining to Alzheimer\u2019s research,\u201d said\u00a0Vicky Yao, assistant professor of computer science and a member of the\u00a0Ken Kennedy Institute\u00a0at Rice.<\/p>\n
\u201cBeyond that, the method will likely be broadly valuable to help us better understand which cell types are relevant in different complex diseases.\u201d<\/p>\n
The research arrives amid renewed statewide momentum to advance brain health and dementia prevention through new public investment initiatives. Earlier this year, the Texas Legislature established the Dementia Prevention and Research Institute of Texas (DPRIT) through Senate Bill 5, a bipartisan measure designed to accelerate innovation in dementia prevention, treatment and care.<\/p>\n
This November, Proposition 14 will appear on the statewide ballot to fund DPRIT with $3 billion over the next decade, creating the largest state-funded dementia research program in the nation. Modeled after the successful Cancer Prevention and Research Institute of Texas (CPRIT), DPRIT aims to make Texas a global leader in brain health and neurodegenerative disease research.<\/p>\n
\u201cWe are at a point where advances in computing and data science are increasingly transforming how we study human disease,\u201d said Yao, who is a CPRIT Scholar. \u201cNow we have to maintain that momentum.\u201d<\/p>\n
Funding: The research was supported by National Institutes of Health (RF1AG054564, R21AG085464), CPRIT (RR190065), the Cure Alzheimer\u2019s Fund and the Karen Toffler Charitable Trust. The content in this press release is solely the responsibility of the authors and does not necessarily represent the official views of funding organizations and institutions.<\/p>\n
Key Questions Answered:Q: What\u2019s the breakthrough in this study about AI, genetics, and Alzheimer\u2019s disease?<\/p>\n
A: Scientists developed a new computational tool, called seismic, that pinpoints which specific brain cell types are genetically linked to complex diseases like Alzheimer\u2019s.<\/p>\n
Q: What mystery about Alzheimer\u2019s and genetics does it help solve?<\/p>\n
A: The tool reconciles a long-standing contradiction in Alzheimer\u2019s research by linking genetic evidence to the actual memory-making neurons that die in the disease, rather than to immune cells previously thought to be the main culprits.<\/p>\n
Q: How does the AI technology work?<\/p>\n
A: Seismic integrates genetic data (GWAS) with single-cell RNA sequencing to reveal how disease-related genetic changes affect individual cell types across different brain regions.<\/p>\n
Q: Why does it matter?<\/p>\n
A: The approach could transform how researchers identify disease-relevant cells in conditions like Alzheimer\u2019s and Parkinson\u2019s, paving the way for targeted prevention and treatment strategies.<\/p>\n
About this AI, genetics, and Alzheimer\u2019s disease research news<\/p>\n
Author: Silvia Cernea Clark<\/a>
Source: Rice University<\/a>
Contact: Silvia Cernea Clark \u2013 Rice University
Image: The image is credited to Neuroscience News<\/p>\n