98% of 'Junk DNA' Is No Longer Silent: Nature Neuroscience Study Reveals New Therapeutic Targets for Alzheimer’s Disease

Although scientists have identified thousands ofwith Alzheimer’s disease (AD)risk-associated genetic variants, but unraveling the mechanisms by which these variants lead to disease remains a significant challenge. According toWorld Health Organizationdata, there are approximately55 million peopleDementia, with Alzheimer's disease being the most common form.

However, the vast majority of disease-associated genetic variants are not located within protein-coding genes, but rather hidden in regions that occupyThe 98% non-coding region of the human genome,namely, in the so-called "junk DNA."

December 18, 2025Irina Voineagu of the University of New South WalesProfessor Team in*Nature Neuroscience*published an important study.

Figure: Irina Voineagu

(Source: UNSW Sydney)

The research team utilizedCRISPRi Technology and Single-Cell Sequencing, functionally tested nearly 1,000 candidate enhancers in human astrocytes, ultimately identifying approximately 150 genuine “switches” that affect gene activity, many of which are associated with Alzheimer’s disease risk genesDirectRelevant.

This discovery provides insight into understandingThe Role of the Non-Coding Genome in Brain DiseasesProvides a critical "roadmap."

Of the 3 billion base pairs in the human genome, only about2%The sequences responsible for encoding proteins are what we commonly refer to as genes. The remaining 98% of the sequence has long been termed “junk DNA,” as it appeared to have no function.

However, with theENCODE ProjectAs large-scale genomics research advances, scientists have gradually come to realize that this vast non-coding region is not a useless “wasteland,” but rather contains complex regulatory instructions, particularlyEnhancersEnhancers act as remote switches for genes, determining when, where, and to what extent a gene is activated.

This regulatory mechanism is particularly critical in complex diseases, becauseGenome-Wide Association Study (GWAS)Studies have shown that many disease-associated genetic variants are located in these non-coding regions, rather than within the genes themselves. This is akin to a malfunctioning light in a room: the problem may not lie with the light bulb (the gene), but rather with a hidden switch deep within the walls.(Enhancer)and its connecting circuits malfunctioned.

Among the many types of brain cells,Astrocytesare the most abundant glial cells in the human brain. They are not merelyThe “Logistical Support” of Neurons, inModulating synaptic function, maintaining the blood-brain barrier, regulating cerebral blood flow, and participating in neuroinflammatory responsesplay a central role. Changes in the state of astrocytes, such as the generation of reactive astrocytes,with Alzheimer's disease (AD)、Neurodegenerative Diseases Such as Parkinson's Diseaseclosely related to the progress of.

In the brains of patients with Alzheimer’s disease (AD), the gene expression profiles of astrocytes undergo significant alterations, with many disease-risk-associated genes being specifically expressed in these cells. Therefore, elucidating the gene regulatory networks within astrocytes is crucial for understanding the pathological mechanisms of AD.

However, precisely locating and characterizing those distant and cryptic enhancers in astrocytes is no easy task. This is mainly attributed to the genome'sThree-dimensional folded structure——Topologically Associating Domains (TADs). Enhancers are typically not located near the genes they regulate; instead, they physically interact with the promoters of target genes over long distances spanning tens to hundreds of thousands of base pairs via chromatin loops. This"Action at a Distance"making it extremely difficult to infer specific target genes based solely on linear distance.

Figure: Regulatory circuits of astrocyte gene expression

(Source: Nature Neuroscience)

For example, an enhancer located near gene A may in fact regulate the expression of a distal gene B, bypassing gene A. Traditional prediction methods often rely on correlation analyses and lack direct functional validation, leaving our understanding of gene regulatory networks in astrocytes unclear.

To overcome this bottleneck, researchers must go beyond mere sequence analysis and instead seek a method that can directly test theseDNA Switch Functionmethods. Only by individually “flipping” these switches in a genuine cellular environment and observing the resulting changes in gene expression can we truly map out precise regulatory landscapes. This endeavor aims not only to fill gaps in fundamental biology but also to identify potential drug-targetable elements within the vast non-coding genome.Novel Site, thereby opening new avenues for the treatment of neurodegenerative diseases such as Alzheimer's disease.

To systematically decode enhancer function in astrocytes, Professor Irina Voineagu’s team designed aLarge-Scale Combinatorial Screening Experiments.

They first identified 979 candidate enhancer regions active in astrocytes based on open chromatin data. To validate the function of these candidate regions, the researchers employed a method calledCRISPR Interference (CRISPRi)cutting-edge technologies. Unlike traditional CRISPR gene editing, CRISPRi does not cleave DNA; instead, it guides an inactiveCas9 Protein (dCas9) and Transcriptional Repression Domain (KRAB)fusion, binding to specific DNA sequences, thereby physically blocking the binding of transcription factors and precisely “turning off” the target enhancer.

To simultaneously assess the functions of nearly 1,000 enhancers, the research teamCRISPRi Technology and Single-Cell RNA Sequencing (scRNA-seq)combined, analyzed over47,000High-quality single cells, with precise measurement of genome-wide gene expression changes in each individual cell after enhancer inhibition.

The experimental results are remarkable, and the research team has successfully identified158a defined regulatory interaction involving145a functional enhancer and116 itemsTarget genes. Data show that up to84.1%Suppression of the enhancers led to a significant downregulation of target gene expression, confirming their core role as positive regulators.

More importantly, this study reveals a key feature of enhancer regulation: although most enhancers tend to regulate the nearest genes, there are still29%Functional enhancers skip over neighboring highly expressed genes to regulate more distant target genes. This complex jumping regulatory pattern explains why inferring the target genes of pathogenic loci based solely on linear distance often leads to errors.

Regarding specific disease associations, the research team found that many of the identified enhancers directly regulate genes closely associated with Alzheimer's disease pathology.

A striking example is theLGALS3 Generegulation. LGALS3-encodedGalectin-3 Protein in Neurodegenerative Diseasesmodulates microglial activation. Studies have found that LGALS3 expression is controlled by three specific astrocytic enhancers. Notably, LGALS3 is not only a key mediator of astrocyte-microglia interactions but also associated with the strongest ADGenetic Risk Factor APOE4There is an interaction—in carriersAPOE4in the brains of female AD patients with alleles,LGALS3expression was significantly downregulated. This suggests that by manipulating these specific enhancers, LGALS3 levels could be precisely modulated, thereby intervening in the disease process.

Furthermore, the researchers also discovered that the enhancer Enh427 remotely regulatesCCL2 Geneexpression. CCL2 encodes a chemokine that recruits immune cells to aggregate around amyloid plaques, thereby exacerbating neuroinflammation. The Enh427 region contains multiple genetic variants associated with AD, further confirming the central role of these non-coding regions in disease pathogenesis.

In addition to experimental validation, this study also utilized the generated high-quality dataset to train a model namedRandom Forest for EGFRMachine learning models. By integratingChromatin State (H3K27ac, H3K4me3, ATAC-seq), gene stability index, and enhancer-gene distance, the EGrf model demonstrated superior performance in predicting astrocyte-specific gene regulatory relationships, with accuracy significantly outperforming existing ABC models trained on cancer cell lines (such as K562) andTAP-seq RFModel.

Figure: Predicting Enhancer-Gene Regulatory Interactions in Astrocytes Using EGrf

(Source: Nature Neuroscience)

Using this new model, the research team further predicted more than 1,300 potential candidates on a genome-wide scale.Enhancer-Gene Interactionsfunction, greatly expanding our understanding of the gene regulatory landscape of astrocytes. To validate the reliability of the model, researchers selected five enhancers predicted to be associated with Alzheimer’s disease risk genes for individual validation, and four of them (80%) were successfully confirmed, including one that regulates late-onset Alzheimer’s diseaseEnhancer of the Major Risk Gene CLU。

The significance of this study lies not only in its technical triumph but also in the novel perspectives and tools it provides for understanding and treating brain diseases.

First, it has constructed the largest functional enhancer atlas of human astrocytes to date. This atlas serves as a detailed circuit diagram, clearly identifying which “hidden switches” control key “light bulbs” (disease genes).

For Alzheimer’s disease research, this means we will no longer be confined to studying the 2% of protein-coding genes, but can instead delve into the vast and largely uncharted 98% non-coding region.

These data fill the gap"Genome-Wide Association Studies (GWAS)" and "Pathogenic Mechanisms"provides a critical bridge across the gap.Google DeepMind TeamThey have already leveraged this unique dataset to benchmark their latest deep learning model, AlphaGenome, further underscoring the core value of these data in advancing computational biology and AI predictive models. High-quality experimental data serve as the cornerstone for training next-generation AI models, whileEGFR Model’s success also demonstrates that data from specific cell types is crucial for improving prediction accuracy.

Second, this finding represents a substantial breakthrough for precision medicine. Traditional drug development has largely targeted proteins; however, in certain scenarios, directly modulating gene expression may prove more effective. This is particularly relevant for genes that are expressed across multiple cell types yet perform distinct functions, where systemic interventions could lead to severe adverse effects.

The cell-type-specific enhancers identified in the study offer an ideal solution. Because many enhancers are active only in specific cell types (such as astrocytes), targeting these enhancers enables precise regulation of particular cell populations without affecting other types of brain cells (such as neurons).

This is akin to having a remote control that can turn off the lights in specific rooms without plunging the entire building into darkness. For example, targetingLGALS3Genetic intervention, if carried out in astrocytes via specific enhancers, could effectivelyAlleviate Neuroinflammation。

Looking ahead, this study opens a new chapter in the functional exploration of the non-coding genome. Although clinical application remains some distance away, just asStudy Lead VoineaguAs the professor pointed out, the first approved gene-editing therapy for sickle cell anemia specifically targets a cell-specific enhancer (the BCL11A enhancer), providing a strong precedent for enhancer-based therapies.

Furthermore, this study has certain limitations; for instance, although CRISPRi technology avoids the damage caused by DNA cleavage, it may not fully recapitulate the effects of gene deletion. Future studies need to integrateGene Editing(such as CRISPR-Cas9) and base editing technologies to further validate the functional consequences of specific single-nucleotide variants (SNVs). As such functional maps continue to be refined, we have reason to believe that innovative therapies capable of precisely repairing or modulating damaged gene circuits will emerge, thereby correcting at their root the molecular abnormalities underlying complex neurological disorders such as Alzheimer’s disease.

This study byLed by the University of New South WalesThrough large-scale functional screening, this research has successfully transformed the so-called “junk DNA” hidden in non-coding regions into valuable clues for understanding the pathogenesis of Alzheimer’s disease. It not only reveals the complex gene regulatory networks in astrocytes but also provides potential targets for future precision medicine. As our understanding of the brain’s “wiring diagram” continues to deepen, the key to unlocking the mysteries of neurodegenerative diseases may well lie within these once-overlooked DNA fragments.