Neurogenetics is an interdisciplinary field that examines the genetic factors influencing the development, function, and disorders of the nervous system, integrating principles from genetics, neuroscience, and molecular biology to uncover how genes shape neural characteristics and behaviors.[1] It focuses on both inherited and de novo genetic variations that contribute to neurological conditions, ranging from monogenic disorders like Huntington's disease to complex polygenic traits such as Alzheimer's and Parkinson's.[2]The field originated in the mid-20th century, pioneered by researchers like Seymour Benzer and Sydney Brenner, who adapted microbial genetics techniques to study neural processes in model organisms such as Drosophila melanogaster and Caenorhabditis elegans.[3] Early breakthroughs in the 1960s and 1970s, including the identification of the period gene in 1971 (involved in circadian rhythms), along with molecular cloning of genes like Notch in 1983 (critical for neural development), laid the foundation for understanding gene-neuron relationships.[4][5] By the 1980s, advancements in molecular tools enabled forward genetics approaches, such as mutagenesis, allowing scientists to link specific gene variants to phenotypes like behavior and neurodegeneration.[1]Contemporary neurogenetics leverages cutting-edge technologies, including next-generation sequencing (NGS), CRISPR-Cas9 gene editing, RNA interference (RNAi), and single-cell transcriptomics, to diagnose and model neurological diseases with unprecedented precision.[3][6] For instance, whole exome sequencing has improved diagnostic yields for hereditary neuropathies and ataxias, identifying causative mutations in 20-45% of undiagnosed cases.[2] These methods have facilitated applications in personalized medicine, such as gene therapies like onasemnogene abeparvovec for spinal muscular atrophy (SMA), and have expanded research into behavioral neurogenetics, exploring how genes like fruitless influence courtship in flies.[1][2]Despite these advances, challenges persist, including the interpretation of variants of uncertain significance (VUS), ethical concerns around genetic privacy, and disparities in access to genomic testing in low-resource settings.[2] Looking ahead, neurogenetics aims to integrate multi-omics data with computational modeling to bridge genes, circuits, and behavior, while promoting diverse model organisms and global collaborations to address genetic heterogeneity across populations.[3] This evolving field holds promise for transformative therapies targeting the genetic roots of neurological disorders.[2]
Introduction and History
Definition and Scope
Neurogenetics is defined as the scientific study of the role of genetic factors in the development, structure, function, and disorders of the nervous system.[1] This field examines how genes influence neural characteristics, treating them as phenotypes shaped by inheritance, and integrates genetic analysis to understand both normal and pathological processes in the brain and peripheral nervous system.[3] Early conceptual foundations for aspects of neurogenetics, such as behavioral genetics, were laid by figures like Francis Galton, who explored hereditary influences on human traits in the late 19th century.[7]The scope of neurogenetics is broad, encompassing monogenic disorders caused by mutations in a single gene, such as Huntington's disease, as well as polygenic traits involving multiple genetic variants that contribute to complex conditions like schizophrenia risk.[8] It also includes behavioral genetics, which investigates the heritability of cognitive and psychological traits, and developmental processes that govern neural formation and plasticity from embryogenesis onward.[9] This range allows neurogenetics to address both rare, Mendelian-inherited neurological diseases and common, multifactorial disorders influenced by gene-environment interactions.[2]Neurogenetics is inherently interdisciplinary, drawing from neurology to study nervous system disorders, genetics and genomics for molecular mechanisms, and neuroscience for broader functional insights.[2] Researchers in this field employ tools from these domains to map genetic contributions to neural phenotypes, fostering collaborations that advance both clinical diagnostics and basic research.[10]Neurogenetics focuses on the genetic basis of nervous system traits, distinguishing it from broader neurobiology, which encompasses physiological, cellular, and molecular processes beyond genetics.[11]
Historical Milestones
The foundations of neurogenetics trace back to the late 19th and early 20th centuries, when principles of inheritance began to intersect with studies of neurological and behavioral traits. Francis Galton's pioneering work on twin studies in the 1870s provided early evidence for the genetic basis of human characteristics, including those related to cognition and behavior, by comparing identical and fraternal twins to disentangle hereditary and environmental influences.[7] The rediscovery of Gregor Mendel's laws of inheritance in 1900 further enabled the application of genetic principles to complex human traits, including neurological disorders, through pedigree analyses that revealed patterns of familial transmission.[12]The mid-20th century marked a pivotal shift with the elucidation of DNA's molecular structure, which laid the groundwork for understanding genetic mechanisms underlying neural function. In 1953, James Watson and Francis Crick proposed the double-helix model of DNA, revealing how genetic information is stored and replicated, a discovery that revolutionized the study of hereditary neurological diseases by enabling molecular-level investigations.[13] Building on this, the 1960s saw the emergence of experimental neurogenetics through Seymour Benzer's innovative use of Drosophila melanogaster as a model organism; Benzer's forward genetics approach identified single-gene mutations affecting behavior, such as phototaxis and learning, demonstrating that complex neural traits could be dissected at the genetic level.[14]Advancements in the 1980s accelerated gene discovery in neurological disorders via linkage analysis and positional cloning. Early pedigree studies of Huntington's disease, dating to the late 19th century, evolved into molecular linkage mapping, culminating in 1983 when James Gusella and colleagues identified a DNA marker on chromosome 4 tightly linked to the Huntington's gene, marking the first use of restriction fragment length polymorphisms for localizing a neurological disease locus.[15] This technique paralleled positional cloning successes in other fields, such as the 1989 identification of the CFTR gene in cystic fibrosis, which informed similar strategies in neurology; for instance, in 1986, Anthony Monaco and team isolated candidate cDNAs for the Duchenne muscular dystrophy (DMD) gene, leading to the discovery of dystrophin as its protein product in 1987, the first large-scale gene cloned positionally in a neuromuscular disorder.[16][17]The 1990s consolidated these methods, with refinements in positional cloning yielding genes for additional monogenic neurological conditions, such as those involved in Charcot-Marie-Tooth disease, and the 1993 identification of the HTT gene for Huntington's disease, revealing a CAG repeat expansion as the causative mutation.[18] The completion of the Human Genome Project in 2003 provided a comprehensive reference sequence, dramatically facilitating genome-wide association studies and accelerating the identification of genetic variants contributing to neurological traits and disorders.[19]
Fundamental Concepts
Genetic Mechanisms in Neural Development and Function
Gene expression in neurons is tightly regulated by transcription factors that respond to synaptic activity and environmental cues, enabling adaptive changes in neural structure and function. The cAMP response element-binding (CREB) protein family serves as a key mediator in this process, where phosphorylation at serine-133 allows CREB to recruit co-activators like CBP/p300, thereby initiating transcription of target genes such as BDNF and c-fos that support neuronal survival and plasticity.[20] In the context of synaptogenesis, CREB activation promotes axonal growth and dendritic arborization, as evidenced by studies in CREB-null mice showing impaired synaptic connectivity and reduced spine density.[20] This activity-dependent regulation ensures that gene expression aligns with synaptic strengthening during learning and memory formation.[20]Neural development relies on orchestrated genetic programs that guide the formation of the nervous system through distinct stages of neurogenesis. Hox genes, a family of homeodomain transcription factors, play a pivotal role by establishing anterior-posterior identity and coordinating cellular processes. During proliferation, Hox genes like Abdominal-A in Drosophila regulate progenitor cell cycle exit via apoptosis induction, controlling neuronal numbers.[21] In differentiation, combinatorial Hox expression specifies neuronal subtypes; for instance, Hoxc9 directs thoracic motor neuron columnar identity by activating downstream effectors like Foxp1.[21] Hox genes also influence migration, as seen with Hoxa2 directing pontine neurons via Robo2-mediated repulsion cues, ensuring proper positioning in the hindbrain.[21] For axon guidance, Hox factors such as Hoxb1 modulate guidance receptor expression (e.g., EphA4), facilitating topographic projections and circuit specificity.[21]Beyond development, genetic mechanisms underpin ongoing neural function through the expression of proteins critical for signaling. Ion channel genes, including SCN1A, encode the alpha subunit of voltage-gated sodium channels (NaV1.1) that are predominantly expressed in inhibitory interneurons, where they control sodium influx to generate action potentials and regulate neurotransmitter release timing.[22] Similarly, genes involved in neurotransmitter synthesis, such as tyrosine hydroxylase (TH), catalyze the rate-limiting step in dopamine production by hydroxylating tyrosine to L-DOPA using tetrahydrobiopterin as a cofactor, thereby modulating dopaminergic signaling in reward and motor pathways.[23] TH activity is fine-tuned by phosphorylation at sites like Ser40, which reduces feedback inhibition by catecholamines and enhances enzymatic efficiency in response to neuronal demand.[23]Polygenic interactions manifest through interconnected gene regulatory networks that collectively shape neural circuit formation, providing robustness and flexibility to developmental outcomes. These networks integrate multiple transcription factors and signaling pathways to coordinate synaptogenesis and connectivity, as seen in the combinatorial action of Hox genes with cofactors like Pbx and Meis to refine motor neuron circuits.[21] High-throughput analyses reveal that such polygenic modules, involving hundreds of loci, influence circuit assembly by modulating proliferation and guidance cues across cell types, ensuring precise wiring without reliance on single genes.[24] Epigenetic modifications, such as DNA methylation, can briefly intersect these networks to stabilize gene expression patterns during circuit maturation.[25]
Key Genes and Pathways in the Nervous System
Neurodevelopmental genes such as FOXG1 and MECP2 are fundamental to the establishment of cortical architecture and neuronal maturation in the nervous system. FOXG1, a forkhead box transcription factor expressed in pyramidal neurons, orchestrates inside-out cortical layering by regulating the identity and migration of deep-layer (Tbr1+ and Ctip2+) and upper-layer (Cux1+ and Satb2+) neurons. Mechanistically, FOXG1 forms a repressive complex with the transcriptional regulator Rp58 to suppress axon guidance genes like Robo1 and Slit3, as well as migration-related genes such as Reelin, ensuring proper radial migration and cortico-cortical connectivity, including corpus callosum formation.[26] Similarly, MECP2 encodes methyl-CpG-binding protein 2, an epigenetic regulator that binds methylated DNA to modulate gene expression during postnatal neuronal maturation. In the cortex, MECP2 promotes dendritic arborization, synaptogenesis, and the excitatory-inhibitory balance by influencing chromatin architecture and transcription of maturation-related genes, with its expression increasing from deeper to superficial layers during development.Synaptic plasticity pathways, exemplified by BDNF-TrkB signaling, underpin activity-dependent strengthening of neural connections essential for learning and memory. Brain-derived neurotrophic factor (BDNF) binds to its high-affinity receptor TrkB on postsynaptic neurons, activating intracellular cascades including Ras-ERK and PI3K-AKT pathways that drive local dendritic protein synthesis and enhance AMPA receptor trafficking. This signaling induces a persistent potentiation of synaptic efficacy at hippocampal CA1 synapses, comparable to electrically induced long-term potentiation (LTP), by facilitating presynaptic vesicle release and postsynaptic consolidation. The core mechanism of LTP aligns with Hebbian principles, where coincident pre- and postsynaptic activity strengthens synapses; a basic formulation of this update rule is:\Delta w = \eta \cdot x \cdot yHere, \Delta w represents the change in synaptic weight, \eta is the learning rate, x denotes presynaptic spike activity, and y indicates postsynaptic depolarization, capturing the correlative detection that BDNF-TrkB amplifies for sustained plasticity.Neurotransmitter pathways rely on genes like SLC6A4 to regulate synaptic signaling termination and homeostasis. The SLC6A4 gene encodes the serotonin transporter (SERT), a sodium- and chloride-dependent symporter embedded in the presynaptic plasma membrane of serotonergic neurons. SERT actively reuptakes serotonin (5-HT) from the synaptic cleft into the presynaptic terminal, limiting extracellular serotonin availability, recycling the neurotransmitter for repackaging into vesicles, and preventing overstimulation of postsynaptic receptors. This process maintains precise temporal control of serotonergic transmission across neural circuits.[27]Glial genes, such as GFAP, support neuronal function through astrocyte-mediated maintenance of the neural microenvironment. GFAP (glial fibrillary acidic protein) is a type-III intermediate filament protein that forms cytoskeletal networks in astrocytes, providing structural integrity for process extension and enabling metabolic coupling with neurons. Astrocytes expressing GFAP facilitate neuronal support by clearing excess glutamate via uptake transporters, releasing trophic factors like BDNF, and maintaining ion homeostasis at synapses, thereby preserving synaptic fidelity and energy supply during neural activity.
Neurological Disorders
Monogenic Neurological Diseases
Monogenic neurological diseases are a class of disorders arising from mutations in a single gene, typically exhibiting high penetrance and following Mendelian inheritance patterns, which distinguish them from polygenic conditions influenced by multiple genetic and environmental factors.[28] These mutations disrupt critical neural processes, such as neuronal survival, synaptic function, or protein homeostasis, leading to progressive neurodegeneration or developmental deficits.[29] Common inheritance modes include autosomal dominant, autosomal recessive, and X-linked patterns, each with distinct genetic mechanisms and clinical implications.[30]Autosomal dominant monogenic diseases often result from gain-of-function mutations, where the altered protein acquires toxic properties, or dominant-negative effects that interfere with the wild-type protein.[29] A prototypical example is Huntington's disease, caused by an expansion of CAG trinucleotide repeats in the HTT gene on chromosome 4, where more than 36 repeats lead to a polyglutamine tract in the huntingtin protein, promoting misfolding and aggregation that exerts neurotoxicity, particularly in striatal neurons.[31] This expansion confers autosomal dominant inheritance with anticipation, where repeat length increases across generations, correlating with earlier disease onset.[32]In contrast, autosomal recessive diseases typically involve loss-of-function mutations, requiring biallelic disruption to manifest, as one functional allele suffices for normal protein production.[29] Spinal muscular atrophy exemplifies this, resulting from homozygous deletions or mutations in the SMN1 gene on chromosome 5q13, which encodes the survival motor neuron (SMN) protein essential for motor neuron maintenance; deficiency leads to selective degeneration of spinal cord alpha motor neurons and progressive muscle weakness. Approximately 95% of cases involve exon 7 deletions in both SMN1 alleles, with severity modulated by copy number of the related SMN2 gene.[33]X-linked monogenic diseases disproportionately affect males due to hemizygosity, often through loss-of-function mechanisms that silence gene expression.[29] Fragile X syndrome, the most common inherited intellectual disability, arises from expansion of CGG trinucleotide repeats in the 5' untranslated region of the FMR1 gene on the X chromosome; repeats exceeding 200 trigger hypermethylation and transcriptional silencing, abolishing expression of the fragile X mental retardation protein (FMRP), which regulates mRNA translation at synapses and results in dendritic spine dysmorphology and synaptic deficits.[34] Female carriers may show milder symptoms due to X-inactivation mosaicism.[34]The pathophysiology of many monogenic neurological diseases hinges on whether mutations cause loss-of-function (e.g., haploinsufficiency or null alleles in recessive disorders like spinal muscular atrophy) or gain-of-function (e.g., toxic protein conformers in dominant disorders like Huntington's disease), influencing therapeutic strategies such as gene supplementation versus suppression.[29] Trinucleotide repeat expansions, a recurrent mechanism in disorders like Huntington's and fragile X syndrome, involve slipped-strand mispairing during DNA replication or repair, leading to intergenerational instability and somatic mosaicism that exacerbates neuronal vulnerability over time.[32][28] These expansions often occur in coding or regulatory regions, amplifying polyglutamine tracts or silencing genes via epigenetic modifications, thereby linking genetic instability to progressive neural dysfunction.[32]
Polygenic and Multifactorial Disorders
Polygenic and multifactorial disorders in neurogenetics refer to neurological conditions where risk arises from the combined effects of multiple genetic variants, each contributing small increments, alongside environmental influences, contrasting with monogenic diseases driven by single mutations. These disorders often exhibit complex inheritance patterns, with heritability estimates typically ranging from 40% to 80%, reflecting the interplay of numerous loci across the genome. Genome-wide association studies (GWAS) have identified thousands of such variants, enabling the construction of polygenic risk scores (PRS) that quantify an individual's cumulative genetic liability. As of 2025, recent GWAS have expanded these findings, for example identifying over 250 loci for schizophrenia.In Alzheimer's disease, a prominent example, the APOE ε4 allele serves as a major genetic risk factor, increasing susceptibility by 3- to 15-fold depending on dosage (one or two copies), primarily through interactions with amyloid-beta pathways that accelerate plaque formation and neurodegeneration. This variant explains about 25% of the genetic variance, underscoring the polygenic nature where hundreds of other loci, including those in immune response and lipid metabolism genes, contribute modestly to risk. Environmental factors, such as vascular health and lifestyle, further modulate these genetic effects, highlighting the multifactorial etiology.[35]Schizophrenia exemplifies polygenic risk, with GWAS implicating over 200 loci, many in synaptic plasticity and dopamine signaling pathways, aggregating to account for approximately 80% heritability through PRS that predict case-control status with modest accuracy (area under the curve ~0.7). These scores capture common variants of small effect, distributed across neuronal development genes like those encoding glutamate receptors. Disease onset and severity are influenced by environmental stressors, such as prenatal infections or urbanicity, which interact with genetic load to precipitate symptoms.Certain epilepsy subtypes, including idiopathic generalized epilepsies, demonstrate polygenic architecture involving clusters of variants in ion channel genes, such as those encoding voltage-gated sodium and potassium channels identified in GWAS, which regulate neuronal excitability and contribute to seizure thresholds through additive effects.[36] Unlike rare monogenic epilepsies, these common forms rely on numerous low-penetrance alleles, with PRS derived from GWAS showing associations with seizure frequency and treatment response. Gene-environment interactions, including sleep deprivation or head trauma, can exacerbate risk in genetically predisposed individuals.Gene-environment interactions are central to multifactorial disorders, as illustrated by epistasis—whereby one gene variant modifies another's effect—and specific examples like the COMT Val158Met polymorphism, which alters dopamine degradation and influences cognitive performance under stress. In carriers of the Val allele (higher enzyme activity, lower dopamine), acute stress impairs executive function more severely than in Met carriers, linking genetic variation in catecholamine pathways to vulnerability in disorders like anxiety-related epilepsies or schizophrenia. Such interactions emphasize the need for integrative models beyond genetics alone.
Research Methods
Molecular and Genetic Techniques
Molecular and genetic techniques form the cornerstone of neurogenetic research, enabling the identification, manipulation, and functional analysis of genes implicated in neural development, function, and disorders. These methods allow scientists to isolate specific genetic elements, detect mutations, and disrupt gene expression to study their roles in the nervous system. Key approaches include recombinant DNA technology for gene cloning and amplification, CRISPR-Cas9 for precise editing, linkage analysis for mapping disease loci, and RNA interference for targeted gene knockdown.Recombinant DNA technology, pioneered in the early 1970s, involves the insertion of foreign DNA into host genomes using cloning vectors such as plasmids, which facilitate the propagation and study of neural genes. This technique has been instrumental in neurogenetics for constructing libraries of DNA fragments from neurological disease tissues, enabling the isolation of candidate genes associated with conditions like Huntington's disease. For mutation detection, polymerase chain reaction (PCR) amplification, developed by Kary Mullis in 1983, exponentially copies specific DNA segments to identify variants in genes linked to neurological disorders, such as those causing spinal muscular atrophy. PCR's sensitivity has revolutionized diagnostics by allowing the amplification of low-abundance mutant alleles from patient samples, with specialized methods like digital PCR achieving detection limits as low as 1% allele frequency.[37]CRISPR-Cas9, adapted from bacterial immune systems in 2012, utilizes a single guide RNA (gRNA) designed to hybridize with target DNA sequences adjacent to a protospacer adjacent motif (PAM), directing the Cas9nuclease to induce double-strand breaks for gene editing in neurogenetic models. Guide RNA design involves selecting 20-nucleotide sequences with minimal off-target potential, using algorithms that prioritize unique genomic matches and GC content between 40-60% to enhance specificity in neural cell studies. To mitigate off-target effects—unintended cuts at similar sequences—high-fidelity Cas9 variants, such as those engineered with mutations in the REC3 domain, reduce non-specific binding by up to 100-fold while maintaining on-target efficiency above 80% in applications like modeling Parkinson's disease mutations. These variants have been widely adopted in neurogenetics to edit genes such as SNCA without collateral genomic damage.Linkage analysis maps genes by assessing co-inheritance patterns in families affected by neurological diseases, using logarithm of odds (LOD) scores to quantify evidence for linkage, where LOD is calculated as the base-10 logarithm of the likelihood ratio of linkage versus no linkage. A LOD score greater than 3 is conventionally accepted as significant evidence of linkage, as demonstrated in the 1991 mapping of the amyotrophic lateral sclerosis (ALS) locus to chromosome 21q, later identified as SOD1. This parametric method assumes a known inheritance model and has been pivotal in localizing monogenic neurological disorders, such as Charcot-Marie-Tooth disease type 1A to chromosome 17p, by analyzing multipoint LOD scores across pedigrees.RNA interference (RNAi), discovered in 1998, employs small interfering RNAs (siRNAs) of 21-23 nucleotides to trigger the degradation of homologous mRNA, effectively knocking down target gene expression in neurogenetic studies. In Drosophila, transgenic RNAi lines deliver siRNAs via the Gal4-UAS system to silence neural genes, revealing their roles in behavior; for instance, knockdown of rutabaga disrupts learning and memory circuits. This approach has facilitated various large-scale screens in fruit flies, identifying dozens of genes essential for nervous system development and axon guidance, with broader neural screens revealing hundreds involved in related processes, providing insights conserved across species.
Statistical and Computational Approaches
Statistical and computational approaches in neurogenetics enable the analysis of large-scale genetic data to uncover associations between genetic variants and neurological traits or disorders. These methods address the complexity of the genome and the polygenic nature of many neurological conditions by applying rigorous statistical tests and computational algorithms to identify patterns, estimate genetic contributions, and interpret biological relevance. Key techniques include genome-wide association studies (GWAS), heritability estimation via twin models, polygenic risk scoring, and bioinformatics tools for pathway analysis, which collectively bridge raw genetic data to mechanistic insights.Genome-wide association studies (GWAS) scan the genomes of large cohorts to detect single nucleotide polymorphisms (SNPs) associated with neurological phenotypes, such as Alzheimer's disease or schizophrenia, by comparing allele frequencies between cases and controls. To account for the millions of SNPs tested, GWAS employ stringent multiple testing corrections, such as the Bonferroni method, which sets a genome-wide significance threshold of p < 5 \times 10^{-8} to minimize false positives. Results are often visualized using Manhattan plots, which plot -\log_{10}(p)-values against genomic positions to highlight significant loci as peaks above the threshold line. In neurogenetics, GWAS have identified hundreds of risk loci for disorders like Parkinson's disease, revealing shared genetic architectures across neurological conditions.[38][39]00795-0)Heritability estimation quantifies the proportion of phenotypic variance attributable to genetic factors in neurological traits, often using twin studies that compare monozygotic and dizygotic pairs to disentangle genetic and environmental influences. The classical ACE model, analyzed through structural equation modeling, decomposes variance into additive genetic effects (A), shared environmental effects (C), and unique environmental effects (E), with narrow-sense heritability defined as h^2 = A / (A + C + E). In neurogenetics, twin studies have estimated moderate to high heritabilities for brain morphology and function, such as 40-80% for cortical thickness and gray matter volume, underscoring genetic influences on neural development. For specific disorders like amyotrophic lateral sclerosis, twin data yield heritability estimates around 0.61, supporting a substantial genetic component.[40][41][42][43]Polygenic risk scores (PRS) aggregate the effects of numerous common variants to predict an individual's genetic liability to neurological disorders, calculated as a weighted sum: PRS = \sum \beta_i G_i, where \beta_i is the effect size of the i-th SNP from a discovery GWAS and G_i is the genotype dosage (0, 1, or 2). Seminal work in schizophrenia demonstrated that PRS derived from thousands of subthreshold SNPs explain up to 3-7% of liability variance, highlighting the polygenic basis of the disorder. In neurogenetics, PRS have been applied to neurodegenerative diseases like Alzheimer's, where scores incorporating APOE and other loci predict onset risk with area under the curve values around 0.70-0.80 in validation cohorts, aiding in risk stratification.[44][45]Bioinformatics approaches, such as pathway enrichment analysis, interpret lists of candidate genes from GWAS or other studies by assessing overrepresentation in biological pathways or functional categories. The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool integrates gene ontology (GO) terms, KEGG pathways, and other annotations to compute enrichment statistics, typically using hypergeometric tests with false discovery rate adjustments. In neurogenetics, DAVID has revealed enriched pathways like synaptic transmission and axon guidance in genes associated with Williams syndrome, a neurodevelopmental disorder, linking genetic hits to disrupted neural connectivity. Similarly, analyses in Parkinson's disease using DAVID highlight dopaminergic synapse pathways, providing functional context for identified variants.[46][47][48]
Experimental Models
Animal and Cellular Models
Animal models have been instrumental in elucidating neurogenetic mechanisms, allowing precise genetic manipulations to study neural development, function, and disease pathology in controlled settings.[49] Invertebrate and vertebrate organisms provide complementary insights, with their conserved genetic pathways enabling the modeling of human neurological conditions. These models facilitate the identification of gene functions through targeted mutations and enable real-time observation of neural processes, bridging molecular genetics with behavioral and pathological outcomes.[50]The fruit fly Drosophila melanogaster serves as a foundational model in neurogenetics due to its simple nervous system, short generation time, and powerful genetic tools. Pioneering work by Seymour Benzer in the 1960s and 1970s demonstrated that mutations could disrupt learning and memory, establishing behavioral genetics in this organism.[51] A key example is the dunce mutant, which impairs learning by disrupting the cyclic AMP (cAMP) signaling pathway through elevated phosphodiesterase activity, leading to reduced cAMP levels essential for synaptic plasticity. This mutation highlights the role of second-messenger systems in neural information processing, with dunce flies exhibiting defective olfactory learning in classical conditioning assays.[52]Mouse models offer mammalian relevance for studying complex neurogenetic disorders, particularly through targeted genetic engineering. Knockout mice lacking or overexpressing specific genes recapitulate aspects of human diseases; for instance, transgenic mice overexpressing human α-synuclein, especially the A53T mutant, develop progressive dopaminergic neuron loss, Lewy body-like inclusions, and motor deficits mimicking Parkinson's disease.[53] These models reveal how α-synuclein aggregation impairs mitochondrial function and proteostasis, contributing to neurodegeneration.[54] To address lethality or developmental confounds in global knockouts, conditional alleles using the Cre-loxP recombination system enable tissue- or cell-type-specific gene inactivation. In neurogenetics, Cre-loxP-driven deletion of genes like PINK1 in dopaminergic neurons exacerbates α-synuclein toxicity, underscoring pathways in Parkinson's pathogenesis.[55]Zebrafish (Danio rerio) provide a vertebrate model suited for visualizing dynamic neural processes owing to their optically transparent embryos. This transparency allows real-time imaging of neural migration and axon guidance during development.[56] Genes such as sonic hedgehog (shh) are critical for these processes; mutations or morpholino knockdowns of shh disrupt midline neural progenitor patterning and cranial neural crest cell migration, leading to defects in ventral brain structures and craniofacial development.[57] Such models have illuminated shh signaling's role in establishing neural gradients, with live imaging revealing impaired cell movements in mutants.[58]Cellular models, particularly induced pluripotent stem cell (iPSC)-derived neurons, complement animal systems by enabling patient-specific studies without ethical concerns of human experimentation. iPSCs from patients harboring neurogenetic mutations can be differentiated into neurons, recapitulating disease phenotypes in vitro.[59] For example, iPSC-derived dopaminergic neurons from Parkinson's patients with LRRK2 mutations exhibit α-synuclein accumulation and altered autophagy, mirroring in vivo pathology.[60] The scalability of iPSC cultures supports high-throughput drug screening and gene editing, allowing correction of mutations via CRISPR to validate causality.[61]
Human-Based Studies and Cohorts
Human-based studies in neurogenetics play a crucial role in elucidating the genetic underpinnings of neurological disorders by leveraging real-world human populations, providing insights that complement experimental models. These studies encompass family-based analyses, large-scale population cohorts, and longitudinal observations, all conducted under stringent ethical frameworks to ensure participant protection and data integrity. By focusing on human participants, researchers can identify genetic variants associated with disease susceptibility, progression, and traits in diverse populations, informing precision medicine approaches for conditions such as amyotrophic lateral sclerosis (ALS), migraine, and dementia.[62]Family-based studies, particularly pedigree analyses, have been instrumental in mapping genetic linkages for rare monogenic neurological diseases. In ALS, early linkage studies analyzed multigenerational pedigrees to localize causative genes; for instance, a 1991 study of 23 familial ALS (fALS) pedigrees identified linkage to chromosome 21q, with a maximum lod score of 5.03, establishing genetic locus heterogeneity.[63] Subsequent work confirmed mutations in the SOD1 gene within these pedigrees, where over 230 variants have been identified (as of 2025), accounting for approximately 20% of fALS cases and enabling targeted genetic counseling.[64][65] These analyses rely on parametric linkage methods to trace inheritance patterns, offering high resolution for dominant or recessive traits but requiring large, well-documented families to achieve statistical power.[66]Population-based cohorts have revolutionized neurogenetics by enabling genome-wide association studies (GWAS) on common neurological traits through massive sample sizes. The UK Biobank, comprising genetic, phenotypic, and health data from approximately 500,000 participants aged 40-69 recruited between 2006 and 2010, has facilitated large-scale GWAS; for example, a 2022 meta-analysis using UK Biobank data alongside other cohorts identified 123 independent genetic loci associated with migraine risk, with SNP heritability estimated at 11.2% (95% CI: 10.8–11.6%) on the liability scale.[67][62] Such cohorts support polygenic risk score development and reveal pleiotropic effects across neurological phenotypes, though challenges include population stratification and ascertainment bias.[68]Ethical considerations are paramount in human neurogenetic research, given the sensitive nature of genetic data that can reveal familial risks and personal health predispositions. Informed consent processes must detail potential uses of genetic information, including secondary analyses and data sharing, as outlined by the National Human Genome Research Institute (NHGRI), ensuring participants understand risks like re-identification.[69] Institutional Review Board (IRB) protocols, governed by the Common Rule (45 CFR 46), mandate oversight to minimize harm, while privacy protections under HIPAA in the US classify genetic data as protected health information, prohibiting unauthorized disclosure without explicit authorization.[70] In the European Union, the General Data Protection Regulation (GDPR) imposes strict requirements for processing genetic data, treating it as "special category" information that necessitates explicit consent and data minimization to prevent discrimination or stigmatization.[71] These frameworks address incidental findings and long-term data storage, balancing scientific advancement with autonomy and confidentiality.[72]Longitudinal studies extend these efforts by tracking genetic influences over time, capturing dynamic interactions with environmental factors in neurological decline. The Framingham Heart Study (FHS), initiated in 1948 with over 5,000 original participants and expanded to multigenerational cohorts, has incorporated genetic analyses since 2002, genotyping more than 8,000 individuals for dementia-related variants.[73] Extensions to neurology, including brain MRI and cognitive assessments, have shown a decline in dementia incidence over decades (20% per decade).[74] Favorable cardiovascular health is associated with lower dementia risk independently of genetic risk factors (no significant interaction, p=0.99), highlighting modifiable factors in longitudinal designs.[75]
Behavioral Neurogenetics
Genetic Influences on Complex Behaviors
Complex behaviors, such as aggression, cognition, addiction, and psychiatric traits, are influenced by genetic factors that interact with environmental elements to shape individual differences. Twin and family studies consistently demonstrate moderate to high heritability for these behaviors, indicating that genetic variation contributes substantially to their variance. For instance, genome-wide association studies (GWAS) and candidate gene approaches have identified specific loci and pathways involved, though polygenic effects often predominate, explaining a portion of the phenotypic variation while leaving room for gene-environment interactions. These genetic influences are particularly evident in psychiatric conditions, where endophenotypes—intermediate traits bridging genes and overt behaviors—aid in dissecting underlying mechanisms.[76]In aggression genetics, the monoamine oxidase A (MAOA) gene, often termed the "warrior gene," plays a prominent role through its low-activity variants, which reduce enzyme function and impair neurotransmitter degradation. A seminal study of maltreated children found that individuals with low-activity MAOA genotypes were significantly more likely to develop antisocial and violent behaviors when exposed to childhood maltreatment, highlighting a gene-environment interaction effect. This interaction moderates the cycle of violence, with low-MAOA carriers showing up to a threefold increased risk under adverse conditions. Heritability estimates for aggression range from approximately 40% to 50%, underscoring the genetic contribution alongside environmental triggers.[77][78]Genetic influences on intelligence and cognition are predominantly polygenic, involving numerous variants across the genome that collectively impact traits like educational attainment. Large-scale GWAS have identified hits on genes such as FOXO3, which is implicated in insulin signaling pathways relevant to neurodevelopment and cognitive function. For educational attainment, a proxy for cognitive ability, polygenic scores derived from these GWAS explain about 10-20% of the variance, reflecting the distributed genetic architecture. These findings emphasize that no single gene dominates, but cumulative small effects from loci like FOXO3 contribute to individual differences in learning and intellectual outcomes.[79][80]Addiction vulnerability, particularly for substance use disorders, involves genetic variants in reward pathways, with the dopamine D2 receptor gene (DRD2) being a key example. The TaqI A1 allele of DRD2, which reduces receptor density, has been associated with heightened risk for alcoholism and polysubstance abuse by altering dopamine signaling and reward sensitivity. Meta-analyses confirm this link, showing that DRD2 variants increase susceptibility to addictive behaviors, independent of environmental factors in some cases. These genetic factors contribute to the ~40-60% heritability of substance dependence, influencing the transition from use to disorder.[81][82]Endophenotypes provide a bridge between genetics and complex psychiatric behaviors, with eye-tracking abnormalities serving as a well-studied example in schizophrenia. Smooth pursuit eye movements, which track moving targets, exhibit deficits in patients and their unaffected relatives, indicating heritability and familial aggregation. These eye-tracking endophenotypes, such as reduced gain during pursuit tasks, are more genetically tractable than the full disorder phenotype, with twin studies estimating 30-50% heritability and GWAS identifying associated loci in neural circuitry genes. By focusing on such intermediate traits, researchers can better isolate genetic contributions to schizophrenia-related behaviors like attention and executive function.[83][84]
Cross-Species Gene Conservation and Evolution
Neurogenetics reveals extensive conservation of genes across species, particularly those involved in neural function and neurodegeneration. For instance, the amyloid precursor protein (APP) and its orthologs play a conserved role in maintaining proteostasis and mitigating age-related neurodegeneration from invertebrates to humans. In Drosophila melanogaster, the APP ortholog Appl regulates autophagy and TGFβ signaling to reduce ubiquitin-positive aggregates and neuronal vacuolization during aging, with loss-of-function mutations exacerbating caspase activation and neurodegeneration.[85] Similar mechanisms are observed in human neurons, where APP knockout leads to increased ubiquitin and autophagy markers alongside reduced TGFβ signaling, underscoring the evolutionary preservation of these pathways in Alzheimer's disease pathology.[85] This cross-species homology facilitates the use of model organisms to dissect conserved molecular cascades underlying human neurological disorders.Neural genes, especially those encoding synaptic proteins, exhibit slower evolutionary rates compared to non-neural counterparts, reflecting strong purifying selection to preserve function. Large neuronal genes, enriched in synaptic roles such as neuron recognition and signaling, display low dN/dS ratios (typically <1), indicating minimal tolerance for nonsynonymous mutations that could disrupt protein stability or interactions.[86] These ancient genes, dating back over 950 million years in some cases, have expanded in size and isoform complexity in vertebrates and cephalopods while maintaining relative conservation across species, suggesting that purifying selection acts to safeguard intricate neural networks against deleterious changes.[86] Such evolutionary constraints highlight why disruptions in these genes often manifest as conserved vulnerabilities in neurodevelopmental and degenerative conditions.Comparative genomics has identified human accelerated regions (HARs) as key sites of primate-specific genomic changes driving brain evolution, including structural variants like duplications that influence neurodevelopmental gene regulation. HARs, which are ultraconserved sequences exhibiting accelerated substitutions in humans relative to other primates, are enriched near human-specific structural variants (hsSVs) that rewire three-dimensional genome architecture in neural progenitors.[87] Approximately 30% of high-confidence HARs overlap domains altered by hsSVs, such as duplications, leading to enhancer hijacking and modified chromatin interactions with genes implicated in cortical expansion and brain size differences.[87] These primate-specific adaptations underscore HARs' role in fine-tuning neural enhancer activity, contributing to the unique scaling of human brain structures.The translation of conserved genes to model organisms exemplifies their utility in neurogenetics, as seen with the FOXP2 transcription factor in vocal learning circuits. FOXP2 orthologs are highly conserved across vertebrates, with elevated expression in the songbird brain's Area X—a basal ganglia analog—correlating with vocal plasticity and learning in species like zebra finches.[88] In contrast, non-vocal-learning birds show lower FOXP2 levels in comparable regions, linking the gene's dosage to learned communication behaviors.[88] This conservation positions songbirds as pivotal models for probing FOXP2's network in speech-related neurogenetics, bridging evolutionary insights from simpler vocal systems to human language faculties.
Developmental Neurogenetics
Genetic Regulation of Brain Development
The genetic regulation of brain development encompasses a series of orchestrated transcriptional programs that guide the formation of neural structures from embryonic stages through postnatal refinement. Key genes establish spatial patterns, control progenitor proliferation, direct neuronal positioning, and enable activity-driven circuit maturation, ensuring the precise architecture of the central nervous system.[89] Disruptions in these programs lead to neurodevelopmental disorders, highlighting their critical roles.[90]Segmentation genes, such as Sonic hedgehog (SHH), play a pivotal role in early ventral patterning of the neural tube during embryogenesis. Secreted from the notochord and floor plate, SHH forms a concentration gradient that induces distinct neuronal fates in a dose-dependent manner, with high concentrations specifying ventral identities like floor plate cells and progressively lower levels directing motor neurons and interneurons.[91] This morphogen action relies on canonical signaling through the Gli family of transcription factors, which interpret gradient thresholds to activate specific target genes, thereby dividing the dorsoventral axis into functional domains.[92]Neuronal migration is tightly regulated by the Reelin pathway, encoded by the RELN gene, which ensures proper layering of the cerebral cortex. Reelin, an extracellular glycoprotein secreted by Cajal-Retzius cells, binds to integrin and ApoER2 receptors on migrating neurons, activating downstream signaling via Disabled-1 (Dab1) to detach neurons from radial glia and position them in an inside-out manner.[93] Mutations in RELN disrupt this process, causing lissencephaly—a smooth brain malformation characterized by defective cortical layering and severe intellectual disability—demonstrating Reelin's essential function in gyral formation.[94]Proliferation of neural progenitors is controlled by cyclin-dependent kinases, notably CDK5, which modulates the cell cycle to balance expansion and differentiation in the ventricular zone. Unlike classical cell cycle CDKs, CDK5 is activated by non-cyclin partners p35 and p39 in post-mitotic neurons but influences progenitors by phosphorylating substrates that arrest the cycle, preventing re-entry and promoting exit toward neurogenesis.[95] CDK5 deficiency results in uncontrolled proliferation and failed neuronal differentiation, underscoring its role in maintaining progenitor pools during early brain development.[90]In postnatal stages, activity-dependent genes like Arc (Activity-regulated cytoskeleton-associated protein) drive synaptic refinement and circuit pruning. Induced rapidly by neuronal activity via NMDA receptor signaling, Arc localizes to postsynaptic sites where it promotes endocytosis of AMPA receptors, facilitating the elimination of weak synapses and strengthening active ones in regions such as the cerebellum.[96] This mechanism refines excess connections formed prenatally, optimizing neural circuits for sensory processing and learning.[97]
Epigenetic Modifications in Neural Development
Epigenetic modifications encompass a suite of reversible chemical changes to DNA and associated proteins that regulate gene expression without altering the underlying genetic sequence, playing a pivotal role in orchestrating neural development from progenitor proliferation to neuronal maturation. These processes enable precise spatiotemporal control of neurogenic genes, integrating genetic instructions with environmental signals to shape brain architecture. Key mechanisms include DNA methylation, which typically represses transcription by adding methyl groups to cytosine residues in promoter regions; histone modifications, such as acetylation that loosens chromatin structure to facilitate access by transcriptional machinery; and non-coding RNAs, which post-transcriptionally modulate target mRNAs. Dysregulation of these modifications during critical developmental windows can lead to neurodevelopmental disorders, underscoring their importance in establishing neural circuits.[98]DNA methylation is a fundamental epigenetic mechanism in neural development, often silencing genes involved in progenitor maintenance to favor differentiation. For example, hypermethylation of the BDNF promoter region has been linked to stress-induced disruptions in neurodevelopment, where prenatal stress in rodent models elevates DNA methyltransferase activity, resulting in increased methylation at the Bdnf exon IV promoter and subsequent reduction in BDNF protein levels in the adult hippocampus. This leads to impaired neurogenesis and synaptic plasticity, contributing to behavioral deficits reminiscent of neurodevelopmental delays observed in stress-exposed offspring. Such changes highlight how methylation patterns established early in development can persist, influencing long-term neural function.[99]Histone modifications provide another layer of dynamic regulation, with acetylation promoting an open chromatin state conducive to neurogenic transcription. Specifically, acetylation at lysine 9 on histone H3 (H3K9ac) marks active promoters in neural progenitors, enhancing the expression of genes critical for neuronal lineage commitment. During the differentiation of embryonic stem cells into neural progenitors, elevated H3K9ac levels at neurogenic loci, such as those regulating cell cycle exit, correlate with increased transcriptional activity and reduced repressive marks like H3K9 methylation, facilitating the transition to a neurogenic fate. This acetylation is mediated by histone acetyltransferases and opposed by deacetylases, allowing fine-tuned responses to developmental cues.[100]Non-coding RNAs, particularly microRNAs, exert precise control over neural differentiation by targeting repressors of neuronal genes. The microRNA miR-124, abundantly expressed in maturing neurons, directly targets the REST (RE1-silencing transcription factor), a potent repressor of neuronal differentiation programs. By binding to the 3' untranslated region of REST mRNA, miR-124 promotes its degradation, thereby derepressing neuronal-specific genes like those involved in synaptogenesis. This mechanism operates within a double-negative feedback loop: REST initially suppresses miR-124 expression in progenitors, but rising miR-124 levels during differentiation amplify REST downregulation, accelerating the shift to a post-mitotic neuronal state. Studies in reprogramming models confirm that disrupting this loop impairs neuronal conversion efficiency.[101]Environmental exposures during gestation can profoundly alter these epigenetic landscapes, inducing persistent changes in neural development. Fetal alcohol exposure, a major environmental risk factor, disrupts histone deacetylase (HDAC) activity, leading to aberrant histone acetylation and lasting neurodevelopmental impairments characteristic of fetal alcohol spectrum disorders. In rodent models mimicking third-trimester human exposure, alcohol elevates HDAC expression and reduces global histone acetylation in the hippocampus, particularly affecting genes tied to neurogenesis and neuronal survival. These modifications persist into adulthood, correlating with reduced progenitor proliferation and synaptic deficits, and can be partially reversed by HDAC inhibitors, suggesting therapeutic potential. Such environmental-epigenetic interactions exemplify how external insults reprogram neural gene expression trajectories.[102]
Current Advances
Genomic Sequencing and Precision Medicine
Next-generation sequencing (NGS) technologies have revolutionized neurogenetics by enabling high-throughput analysis of genetic variations associated with neurological disorders, building on historical milestones such as the transition from Sanger sequencing in the 1970s—which sequenced the human genome over a decade for billions of dollars—to the parallelized NGS platforms introduced in the mid-2000s that drastically increased speed and reduced costs.[103] Whole exome sequencing (WES), a key NGS application, targets the protein-coding regions of the genome, covering approximately 95% of exons while comprising only about 1-2% of the total genome, making it efficient for identifying rare variants in neurodevelopmental and neurodegenerative diseases.[104] By 2025, ongoing advancements in NGS have further lowered the cost of whole genome sequencing to around $1000 per genome, enhancing accessibility for large-scale neurogenetic studies and clinical diagnostics.[105]Single-cell RNA sequencing (scRNA-seq), often utilizing protocols from 10x Genomics, has emerged as a powerful tool in neurogenetics for resolving cell-type-specific gene expression patterns in heterogeneous brain tissues, particularly in disorders like autism spectrum disorder and Alzheimer's disease.[106] This approach captures transcriptomic profiles from individual neurons and glia, revealing disease-associated changes such as altered excitatory neuron expression in autism or microglial dysregulation in neurodegeneration, which bulk sequencing overlooks due to averaging across cell populations.[107] For instance, scRNA-seq studies of postmortem brain samples have identified subtype-specific vulnerabilities in Huntington's disease, facilitating targeted research into cellular mechanisms of pathogenesis.[107]In precision medicine, variant interpretation in neurogenetics relies on standardized guidelines from the American College of Medical Genetics and Genomics (ACMG), which classify sequence variants as pathogenic, likely pathogenic, or benign based on weighted criteria.[108] The PVS1 criterion, designated as very strong evidence of pathogenicity, applies to null variants (e.g., nonsense, frameshift, or canonical splice site disruptions) in genes where loss-of-function is a known disease mechanism, such as in epileptic encephalopathies or hereditary ataxias.[109] These guidelines ensure reliable diagnostics by integrating functional, population, and computational evidence, reducing uncertainty in counseling patients with neurogenetic conditions like Rett syndrome caused by MECP2 null variants.[108]Recent advances in long-read sequencing, particularly Pacific Biosciences (PacBio) HiFi technology, address limitations of short-read NGS by accurately resolving repetitive genomic elements, such as trinucleotide repeat expansions in ataxia genes like ATXN1 (spinocerebellar ataxia type 1) or FMR1 (fragile X-associated tremor/ataxia syndrome).[110] Unlike short-read methods that struggle with homopolymer runs and interruptions, PacBio's long reads (up to 20 kb with >99% accuracy) enable precise sizing and phasing of expansions exceeding 100 repeats, improving diagnostic yield in undiagnosed ataxia cases.[111] This has led to novel discoveries in cerebellar ataxias, where repeat interruptions modulate disease severity, guiding personalized risk assessment and family screening.[112]
Gene Therapies and Emerging Interventions
Gene therapies in neurogenetics have advanced significantly, targeting monogenic neurological disorders by directly addressing underlying genetic defects. Adeno-associated virus (AAV)-based delivery systems represent a cornerstone of these interventions, particularly for spinal muscular atrophy (SMA), a neurodegenerative disorder caused by mutations in the SMN1gene. Zolgensma (onasemnogene abeparvovec), approved by the FDA in May 2019 for pediatric patients under two years of age, utilizes an AAV9 vector to deliver a functional copy of the SMN1gene via a single intravenous infusion, thereby restoring survival motor neuron (SMN) protein expression in motor neurons.[113][114] Clinical data from the STR1VE trial demonstrated that treated infants achieved motor milestones, with 11 of 12 patients able to sit independently for at least 30 seconds by 14 months post-treatment, highlighting the therapy's impact on disease progression.[115]Antisense oligonucleotides (ASOs) offer another targeted approach, modulating gene expression at the RNA level without altering the genome. Nusinersen (Spinraza), approved by the FDA in 2016 for SMA, is administered intrathecally and functions by binding to a silencer motif in the SMN2 pre-mRNA, promoting inclusion of exon 7 during splicing to produce full-length SMN protein.[116][117] In the ENDEAR phase 3 trial, nusinersen-treated infants showed a mean improvement of 2.9 points on the total Hammersmith Infant Neurological Examination (HINE) score compared to a -1.4-point decline in controls, underscoring its efficacy in enhancing motor function.[118] These ASO strategies exemplify precision interventions that leverage intrathecal delivery to achieve high central nervous systembioavailability.As of 2025, CRISPR-based editing for Huntington's disease (HD), a polyglutamine expansion disorder driven by CAG repeats in the HTT gene, remains in advanced preclinical development. Preclinical and early-phase studies using AAV-delivered CRISPR systems have demonstrated allele-selective editing, achieving 20-50% reduction in mutant HTT alleles in non-human primate models, with corresponding decreases in toxic protein aggregates.[119] For instance, a 2025 study reported broad central nervous system biodistribution and up to 40% mutant allele silencing via AAV5-CRISPR, paving the way for future clinical trials focused on safety and tolerability in HD patients.[120] In September 2025, a pivotal phase I/II trial of uniQure's non-CRISPR AAV gene therapy AMT-130 reported evidence of slowed disease progression in HD patients, marking a significant advance in huntingtin-lowering therapies.[121]Emerging interventions extend to base editing for precise correction of point mutations in epilepsy-associated genes. In developmental and epileptic encephalopathies, such as those involving SCN8A gain-of-function variants, cytosine base editors have rescued seizure phenotypes in mouse models by converting disease-causing nucleotides without double-strand breaks, achieving over 50% editing efficiency in neuronal populations.[122] Similarly, adenine base editing strategies are under development for Dravet syndrome linked to SCN1A loss-of-function mutations, aiming to restore sodium channel function in patient-derived neurons to reduce hyperexcitability.[123] These tools offer promise for monogenic epilepsies by enabling single-base corrections tailored to specific variants.Therapies targeting non-coding RNAs are also gaining traction for neurodevelopmental disorders (NDDs). Biallelic mutations in the small nuclear RNA gene RNU2-2, identified in 2025 as a cause of severe NDDs with epilepsy and intellectual disability, disrupt spliceosomal function, accounting for approximately 7-10% of diagnosed recessive NDD families.[124] Emerging ASO-based approaches aim to modulate aberrant snRNA activity, with preclinical models showing restoration of splicing fidelity and neurodevelopmental phenotypes upon targeting RNU2-2 variants, highlighting potential for RNA-focused interventions in spliceosomopathies.[125]