Prader-Willi syndrome: Genetics, clinical symptoms, and model systems

Genetic Subtypes and their Related Phenotypes: Deletions (DEL)

The PWS region is demarcated by three breakpoints (BP1, BP2, and BP3) that define the two major deletion subtypes illustrated in Figure 2. Type I DEL, spanning from BP1 to BP3 (approximately 6.58 Mb), results in the loss of a significant amount of genetic material. It is associated with more pronounced neuropsychiatric deficits, including increased anxiety, behavioral challenges, and cognitive impairments (25). The deletion also encompasses genes within the BP1-BP2 region, such as CYFIP1, which has been linked to disruptions in the excitatory/inhibitory balance of neuronal circuits and increased risk for ASD and SCZ (25, 51, 52). The significance of this region is further highlighted by the co-occurrence of traits from Burnside-Butler syndrome in some patients with PWS (53, 54).

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Conversely, type II DEL (BP2-BP3), which spans approximately 5.33 Mb, is generally associated with less severe phenotypic consequences than type I DEL (16, 55). However, recent research indicates that individuals with type II DEL can still present with distinct cognitive and social impairments that differ in nature from those observed in type I cases (25, 31). This underscores the nuanced influence of genetic deletions on neurodevelopmental outcomes. The critical genes situated between BP2 and BP3 are essential for neurodevelopmental processes, and their loss can contribute to hallmark features of PWS, including hypotonia, hyperphagia, and cognitive impairments (16, 55).

The phenotypic differences between type I and type II DEL in PWS underscore the genetic complexity of the syndrome. Individuals with the more significant type I DEL tend to exhibit increased compulsiveness but also experience more severe behavioral and psychiatric challenges compared to those with the smaller type II DEL (44, 56). Studies have shown that individuals with type I DEL generally have more behavioral and psychological problems, including higher physical depression scores, than those with type II DEL (56). Moreover, although both types of deletions lead to neurodevelopmental impairments, type I DEL appears to be associated with more pronounced psychiatric symptoms, including a higher prevalence of ASD and PSD, whereas type II DEL is associated with a distinct cognitive-behavioral profile (34, 44, 57–59).

While deletions account for the majority of PWS cases and are frequently linked to more pronounced physical and behavioral symptoms, a growing body of research has drawn attention to mUPD, a distinct subtype with a different clinical and psychiatric profile.

Genetic Subtypes and their Related Phenotypes: mUPD

Beyond DEL subtypes, a more extensive genotype-phenotype correlation further distinguishes PWS individuals with DEL and mUPD. Individuals with mUPD tend to exhibit distinct clinical features and implications compared to their DEL counterparts. Notably, research has shown that individuals with mUPD have a higher prevalence of PSDs, including SCZ, as well as increased anxiety and mood disorders. This may arise from the absence of paternal gene expression crucial for neurodevelopment (12, 35, 37). In contrast, individuals with DEL are often more prone to compulsive behaviors, aggression, and self-injury, highlighting the differing behavioral implications associated with these genetic subtypes (12, 56, 61–63).

A significant finding is that postterm deliveries (>42 weeks) are more common in mUPD cases compared to DEL cases, potentially pointing to unique prenatal and postnatal developmental pathways influenced by the absence of paternal alleles (64). Moreover, individuals with DEL characteristically experience frequent feeding difficulties, early-onset hyperphagia, and obesity, with neonatal hypotonia leading to prolonged hospitalization. In contrast, patients with mUPD often demonstrate slightly better verbal skills and notably higher verbal IQ scores than DEL subjects (69.9 vs. 60.8, respectively) despite a significantly higher incidence of co-occurring ASD and social communication difficulties (33, 65, 66).

Furthermore, endocrine differences also emerge between these genotypes, as patients with mUPD exhibit more significant GH deficiencies but often respond better to recombinant human growth hormone (rhGH) therapy. However, this treatment can sometimes be associated with increased anxiety and delusions in PWS individuals (49).

Finally, from a physical perspective, patients with DEL exhibit more pronounced PWS-related features, such as skin hypopigmentation and distinct facial characteristics, whereas individuals with mUPD are less likely to present with these traits (16). Additional complications, such as scoliosis, hypothyroidism, type 2 diabetes, and sleep-disordered breathing, further highlight the complexity of PWS across different genetic subtypes (67–69). Despite these variations, mortality rates have been found to be similar across the various genetic subtypes of PWS, indicating that the underlying genetic mechanisms still converge on core aspects of the disorder (17).

While mUPD diverges from the DEL subtype in its risk for psychiatric features, a third and less common subtype—ICDs—adds further complexity by disrupting epigenetic regulation.

Genetic Subtypes and their Related Phenotypes: ICDs

ICDs often mimic features of both DEL and mUPD but originate from distinct mechanisms that disrupt the regulation of gene expression on the paternal allele of chromosome 15, within the PWS critical region. ICDs such as microdeletions and epimutations (incorrect methylation patterns), which can be either inherited or acquired, may lead to PWS in approximately 1%–4% of patients who exhibit biparental allele inheritance but a maternal-only DNA methylation pattern (16, 70, 71). The imprinting center features a bipartite structure comprising two critical regions: a PWS-imprinting center (PWS-IC), a 4.3-kb sequence that includes the SNRPN promoter/exon 1, and an Angelman syndrome-imprinting center (AS-IC), an 880-bp sequence located 35 kb upstream (72). Both the PWS and the AS-ICs cooperate intricately in regulating the epigenetic status and allele-specific gene expression within the 15q11q13 chromosomal region (73).

The findings (summarized in Tables 1 and 2) underscore the notion that PWS is not a singular genetic disorder but rather a spectrum of neurodevelopmental syndromes influenced by various genetic mechanisms. The precise relationships between genotype and phenotype remain an active research area, with emerging evidence indicating that even within the same genetic subtype, epigenetic modifications and environmental factors may further refine phenotypic outcomes. A comprehensive understanding of these complex relationships is essential for the development of tailored clinical management strategies, which could improve the quality of care and outcomes for individuals diagnosed with PWS (12, 16, 25).

MAGE Family Member L2 (MAGEL2)

MAGEL2 is a maternally imprinted gene involved in cellular processes such as endosomal protein recycling and the production of secretory granules (76, 77). The loss of MAGEL2 leads to a decrease in neuropeptide production and a reduction in the abundance of secretory granules in the hypothalamus, which may contribute to the symptoms of PWS (77). MAGEL2 is vital for normal hypothalamic-pituitary function, and disruptions in its expression can result in metabolic and behavioral abnormalities commonly associated with PWS (78). Evidence also implicates MAGEL2 in neuronal connectivity, regulating circadian rhythms and sleep-wake cycles (76, 78–80). Knockout mouse models lacking functional MAGEL2 exhibit significant deficits in social interaction, impaired synaptic plasticity, and disruptions in oxytocinergic signaling, mirroring findings observed in patients with PWS (81–83). These results imply that the absence of MAGEL2 disrupts neurodevelopmental pathways involved in social cognition, reinforcing its significance in the psychiatric manifestations associated with PWS. In light of these findings, MAGEL2 emerges as a pivotal target for future therapeutic interventions, with efforts underway to restore its function to ameliorate associated behavioral and cognitive impairments (84, 85).

Necdin (NDN)

NDN represents a pivotal paternally expressed gene that plays significant roles in neuronal survival, differentiation, and the regulation of apoptosis (86). It plays a crucial role in maintaining neuronal integrity by inhibiting programmed cell death during neurodevelopment. Evidence from animal models indicates that NDN suppresses E2F1-mediated transcription of proapoptotic genes like CDC2, thereby attenuating neuronal apoptosis (87). Mouse models of PWS reveal that the loss of NDN expression correlates with increased neuronal death in the hypothalamus, aligning with the metabolic and behavioral deficits commonly observed in patients with PWS (13).

Beyond its role in apoptosis, NDN is involved in hypothalamic functions, affecting essential biological processes like feeding behavior, thermoregulation, and respiratory control. It is vital for developing gonadotropin-releasing hormone (GnRH) neurons, as it promotes GnRH transcription and facilitates axonal extension toward the median eminence (88). Animal studies further highlight its role in hypothalamic functionality, showing that NDN-deficient mice exhibit a reduction in oxytocin and luteinizing hormone-releasing hormone (LHRH)-producing neurons, which may contribute to the behavioral and endocrine deficit characteristics of PWS (89). Disruptions in NDN expression have also been associated with cognitive deficits, irregular breathing, severe apneas, abnormal serotonin levels, mirroring respiratory disturbances, and psychiatric symptoms observed in individuals with PWS (90, 91). Moreover, NDN deficiency is associated with reduced firing activity of locus coeruleus noradrenergic neurons, potentially contributing to the symptoms observed in PWS, such as central apnea and pronounced stress responses (92).

Makorin Ring Finger Protein 3 (MKRN3)

The expression of MKRN3 is influenced by the PWS-IC, which is thought to mediate allele-specific interactions, potentially through transcription factors such as nuclear respiratory factors (NRFs) and YY1 (93). Its regulation involves complex mechanisms, including DNA methylation, with a differentially methylated region identified in its 5' untranslated region, as shown in studies involving cattle (94).

The MKRN3 gene plays a crucial role in regulating pubertal onset by inhibiting GnRH secretion. Loss-of-function mutations in MKRN3 are the most common genetic cause of central precocious puberty (95, 96). MKRN3 exhibits a progressive decline in expression as puberty approaches, highlighting its essential role in the reproductive axis (97). The functional role of the MKRN3 protein, while still being elucidated, is believed to relate to the ubiquitin-proteasome system, a key cellular mechanism for degrading unwanted proteins (98). This system operates by tagging proteins with ubiquitin, signaling them for degradation. It is hypothesized that MKRN3 attaches ubiquitin to proteins that could otherwise trigger premature GnRH release (99). By facilitating the destruction of these proteins, MKRN3 plays an essential role in ensuring that puberty commences at the appropriate time (98).

In the context of PWS, evidence suggests that individuals with PWS frequently experience atypical puberty timing, which correlates with hypothalamic abnormalities. Cassidy et al. (16) highlight that inadequate expression of MKRN3 can disrupt the hypothalamic-pituitary-gonadal axis, leading to pubertal disruptions in PWS. Despite MKRN3’s recognized significance, there is a notable scarcity of direct functional studies on its mechanisms in PWS. However, evidence indicates that MKRN3 may serve as a critical regulator, impacting not only reproductive maturation but broader neurodevelopmental aspects associated with PWS (16, 100).

SNURF-SNRPN

The SNURF-SNRPN locus is a complex, imprinted region implicated in PWS (101). It encodes a bicistronic transcript, producing two proteins, SNURF and SmN, from a single mRNA (102). The locus also contains multiple C/D box small nucleolar RNAs (snoRNAs), including HBII-52, which regulates the alternative splicing of the serotonin receptor 2C pre-mRNA (103). The SNRPN 5' region, which colocalizes with the PWS-IC, contains two DNase I hypersensitive sites (DHS1 and DHS2) on the paternal chromosome. These sites interact with regulatory proteins, including NRF-1, which is involved in mitochondrial and metabolic functions. DHS2 is an enhancer for the SNRPN promoter and shows allele-specific interactions with various transcription factors (104). This role is vital for preserving the integrity of neuronal networks, which are crucial for normal brain development and function.

Disruption of this locus, particularly on the paternal allele, can lead to PWS-like phenotypes (16, 101). Investigations involving individuals with PWS have clarified the role of SNURF-SNRPN in neurodevelopmental impairments, with changes in the expression of these genes having been linked to various neurological outcomes, especially those exhibiting features consistent with ASD (105–107). Accordingly, alterations in the expression of the SNURF-SNRPN gene may provide a molecular foundation for the neurodevelopmental impairments observed in PWS, specifically its relationship with ASD-like traits. Subsequent research aimed at understanding the impact of these disruptions on neural networks may yield critical insights into the mechanisms underlying both PWS and the broader spectrum of ASD-related disorders.

snoRNAs

snoRNAs are short, non–protein-coding RNAs that regulate ribosomal and spliceosomal functions. They fulfill this role by directing ribose methylation and pseudouridylation at specific nucleotide residues in ribosomal RNAs and small nuclear RNAs, respectively (108, 109). Paternally expressed snoRNA clusters, particularly SNORD116 (HBII-85), within the PWS critical region were found to be crucial for proper neural differentiation and development in human iPSC models (110) and essential for regulating gene expression through chromatin decondensation and nucleolar maturation in neural tissue (111). Deleting these snoRNA clusters in human Lund human mesencephalic (LUHMES) cells using CRISPR-Cas9 has been linked to significant disruptions in the expression of genes that govern cytoskeletal formation, extracellular matrix integrity, and neuronal arborization (112). These studies, as reviewed by Bratkovic et al. (108), indicate that snoRNAs are vital for posttranscriptional modifications of RNA, a process crucial for normal neuronal function and plasticity.

Although other genes within the PWS region contribute to subtle phenotypic variations and may play a role in the overall phenotypic variability of PWS, SNORD116 deficiency is the primary cause of key PWS characteristics, including infantile hypotonia, early-onset obesity, and hypogonadism (113–115). Mouse models with the DEL of SNORD116 exhibit cognitive impairments in learning and memory, which are essential characteristics of PWS (116). Notably, the epigenetically regulated chromatin decondensation observed at snoRNA clusters is essential for neuronal maturation processes and alterations in nucleolar size, as research indicates that brains affected by PWS exhibit diminished nucleolar size (111). A gene expression study utilizing microarrays and quantitative RT-PCR analysis on RNA extracted from lymphoblastoid cells of male patients with PWS compared to age and cognition-matched nonsyndromic males showed differential expression of 14 neurodevelopmental genes, including serotonin receptor genes and genes involved in eating behaviors and obesity, such as ADIPOR2, MC2R, HCRT, and OXTR (117). These findings underscore the importance of snoRNA clusters within the critical PWS region as a key regulator of gene expression in the brain. They also highlight their potential role in shaping the neural phenotype in PWS.

Cytoplasmic FMRP Interacting Protein 1 (CYFIP1)

CYFIP1 is located in the 15q11.2 BP1-BP2 region, outside the critical locus associated with PWS. This gene encodes a protein that plays a vital role in controlling cytoskeletal dynamics and the process of protein translation. The resulting protein is a WAVE regulatory complex component, aiding actin polymerization. It also interacts with the FMR1 protein, which regulates synaptic function and translation initiation factor 4E, helping to inhibit protein translation (118–120).

CYFIP1 is crucial for synaptic structure and function, with studies showing that it is enriched at inhibitory postsynaptic sites, and its dosage can bidirectionally impact inhibitory synaptic structure and function (51, 121). Specifically, CYFIP1 upregulation increases excitatory synapse number while decreasing inhibitory synapse size, whereas its loss enhances synaptic inhibition (51). This enrichment suggests that CYFIP1 plays a critical role in stabilizing synaptic connections and enhancing synaptic signaling, helping to maintain a healthy balance between excitatory and inhibitory inputs in neural circuits. Recent research underscores that CYFIP1's regulation of this excitatory-inhibitory balance is essential for maintaining synaptic plasticity (51, 121). An imbalance can hinder effective neural communication, leading to disrupted network function and cognitive deficits.

Furthermore, research has shown that missense variants in CYFIP1 disrupt actin polymerization, which is critical for maintaining dendritic spine morphology, synaptic architecture, and neuronal connectivity. These structural impairments have been associated with intellectual disabilities and behavioral deficits and are believed to disrupt large-scale brain connectivity, thereby emphasizing the significance of appropriate CYFIP1 function in neural development (122).

Supporting this, Domínguez-Iturza et al. (123) demonstrated that CYFIP1 haploinsufficiency in mice leads to significantly reduced bilateral functional connectivity, particularly across the corpus callosum. This decline was correlated with atypical interhemispheric coordination and behavioral alterations relevant to ASD and SCZ, thereby underscoring CYFIP1’s critical role in the formation of coherent large-scale neural networks.

In addition to these structural implications, Hsiao et al. (124) have demonstrated that CYFIP1 is vital for regulating presynaptic activity during development. This regulation is critical for the maturation and functionality of synapses, suggesting that disruptions in CYFIP1 expression can lead to neurodevelopmental impairments. The study indicates that when CYFIP1 levels are inadequate, presynaptic dysfunction can adversely affect neurotransmitter release, impacting the efficacy of synaptic transmission and potentially exacerbating the symptoms of neurodevelopmental disorders such as ASD and SCZ. This positions CYFIP1 as a participant in maintaining synaptic structure and as a key regulator of synaptic signaling (124).

Specifically, reduced CYFIP1 levels have been associated with hyperactivity of glutamatergic signaling pathways, exacerbating excitatory activity and contributing to synaptic dysfunction observed in neurodevelopmental disorders (51). CYFIP1-deficient mice exhibit impaired synaptic transmission and behaviors, with parental origin-specific effects observed despite no evidence of parental expression differences (125). Furthermore, investigations utilizing mouse models exhibiting haploinsufficiency of CYFIP1 revealed abnormal frontostriatal connectivity alongside impaired cognitive flexibility (55), linking CYFIP1’s role directly to behavioral outcomes associated with ASD and SCZ.

Emerging evidence indicates that CYFIP1 haploinsufficiency significantly shapes PWS phenotypes by affecting both compulsive behaviors and the regulation of feeding. Mouse models exhibiting DEL of the CYFIP1 gene demonstrate an increase in compulsive-like behaviors alongside alterations in palatable food consumption, indicating a potential involvement in the obsessive eating patterns frequently observed in individuals with PWS (126). Furthermore, CYFIP1 is recognized as a key factor in the neurodevelopmental trajectory of those with PWS, with variations in its expression associated with cognitive impairments, repetitive behaviors, and deficits in social cognition (58).

In conclusion, the balance of excitatory and inhibitory neural activity regulated by CYFIP1 is essential for the normal neurodevelopmental trajectory. Disruptions in this balance may lead to functional impairments in neural circuits that manifest as social and cognitive deficits observed in neurodevelopmental disorders such as ASD and SCZ (51, 55). Investigating specific genetic variants of CYFIP1 that correlate with these behaviors will enhance our understanding of the genotype-phenotype relationships in PWS (55, 126) . Concurrent research suggests that pharmacological interventions targeting downstream pathways related to CYFIP1 might offer promising therapeutic avenues for individuals with PWS and related neurodevelopmental disorders (51, 118).

The molecular roles of MAGEL2, NDN, SNURF-SNRPN, and CYFIP1 converge on common neurodevelopmental and physiological pathways disrupted in PWS. These genes influence hypothalamic function, neuronal survival, synaptic architecture, and gene expression regulation mechanisms essential for appetite regulation, social behavior, and cognitive functioning. For instance, MAGEL2 and NDN contribute to hypothalamic function, including feeding, reproduction, and respiratory control. At the same time, SNURF-SNRPN and CYFIP1 modulate synaptic plasticity and excitatory/inhibitory balance through RNA regulation and translational control. Dysfunctions across these genes result in overlapping outcomes, including hyperphagia, cognitive impairments, and psychiatric comorbidities such as ASD and SCZ. This convergence suggests that diverse genetic alterations within the 15q11-q13 region ultimately disrupt shared neurobiological circuits, providing a mechanistic framework that links genotype to phenotype in PWS (as summarized in Table 3).

Structural MRI and GM Abnormalities

Structural MRI (sMRI) studies have consistently shown widespread GM reductions in PWS, particularly in reward processing and inhibitory control regions (128, 129). Ogura et al. (129) examined the entire brain and found significant reductions in GM and WM volume in the orbitofrontal cortex (OFC), caudate nucleus, and hypothalamus of patients with PWS (N = 12) compared to controls (N = 13). Moreover, in patients with PWS, the mean GM volume was smaller than in controls, as was the case for the mean volume of WM. Using T1-weighted and DTI in 12 children with PWS, 18 obese children, and 18 controls, Xu et al. (128) reported that both the PWS and obese children groups showed similar GM alterations, particularly in prefrontal, cingulate, and temporal regions, possibly reflecting shared mechanisms in the development of eating disorders. However, only the PWS group exhibited distinct WM changes connecting these regions, which may explain hyperphagia and constant hunger in PWS.

Using T1-weighted MRI, a study involving 31 healthy controls and 21 patients with PWS from a Japanese population found reduced pituitary volume in patients with PWS (130). This reduction correlated with hyperphagic and autistic traits, supporting hypothalamic-pituitary dysregulation as a core feature of PWS. Conversely, comparing high-resolution T1-weighted images of 11 age- and gender-matched typically developing siblings and 20 children with genetically confirmed PWS—11 with DEL and 9 with mUPD—revealed increased cortical thickness in the medial prefrontal cortex (PFC) and anterior cingulate cortex in the mUPD group, suggesting a delay in synaptic pruning (131). Moreover, examination of three-dimensional (3D) T1-weighted images in 21 Japanese adolescents and adults with PWS (age range 13–50 years, 14 males, 7 females) and 40 age- and sex-matched healthy controls with normal development revealed that cerebellar abnormalities in PWS, including reduced posterior lobule volume and enlarged dentate nuclei, are linked to motor deficits and autism-like traits. Notably, posterior cerebellar lobule volumes negatively correlated with hyperphagia and autism scores. At the same time, dentate nucleus enlargement was inversely associated with intellectual quotient, highlighting the cerebellum's role in cognitive and behavioral domains (132). These structural changes underscore the role of developmental disruptions in PWS pathophysiology.

More recently, in a study comparing alterations in brain nuclei in 18 obese children without PWS, 12 age- and sex-matched children with PWS, and 18 healthy, Wu et al. (133), using T1-weighted MRI, found significant atrophy in the bilateral thalamus, pallidum, hippocampus, amygdala, nucleus accumbens, right caudate, bilateral hypothalamus, and bilateral deep cerebellar nuclei in the PWS group compared to controls and obese individuals without PWS. Based on these findings, the authors suggest that the structural abnormalities in PWS are distinct from those in obesity and are likely influenced by genetic factors.

In summary, sMRI studies in individuals with PWS reveal widespread gray and WM reductions, especially in regions involved in reward processing, inhibitory control, and hypothalamic-pituitary function. Compared to controls and obese individuals, patients with PWS show unique structural abnormalities, including reduced OFC, caudate, hypothalamus, cerebellar volumes, and distinct WM changes. These abnormalities are linked to hyperphagia, motor deficits, and autism-like traits. Increased cortical thickness in medial prefrontal and cingulate cortices in mUPD-PWS suggests delayed synaptic pruning. Findings highlight neurodevelopmental disruptions as core to PWS pathophysiology.

Diffusion MRI and WM Integrity

Although limited in number, DTI studies have been instrumental in characterizing WM integrity in PWS. A study in 15 PWS (ages 17 to 30) and 15 age- and gender-matched controls reported WM microstructural deficits in PWS, including reduced fractional anisotropy in the corpus callosum, cingulum, and superior longitudinal fasciculus, indicative of impaired axonal myelination (134). Furthermore, a study involving 38 Dutch children and adolescents found that fractional anisotropy correlates with hypotonia, attention deficits, and sensory processing issues. Subtype-specific differences were also observed, such that cases of mUPD exhibited WM abnormalities (e.g., in the cingulate cortex), while those with the DEL subtype displayed milder changes (135). Intriguingly, these findings align with the increased risk of psychosis in mUPD cases and with the substantially lower risk for psychosis in DEL cases, highlighting the significance of WM integrity in the emergence of psychosis in PWS. Collectively, these abnormalities point to disrupted neural connectivity as a key contributor to the behavioral and cognitive phenotype in PWS.

fMRI and Reward Circuit Dysregulation

This section investigates the intricate dysregulation of reward circuits in PWS, as evidenced by fMRI studies. It underscores the association between reward-related networks and appetite regulation, analyzing how these cerebral mechanisms contribute to the characteristic insatiable hunger observed in individuals with PWS. The assessment of functional connectivity through resting-state fMRI further elucidates the neural pathways implicated in this syndrome, providing critical insights into the connectivity patterns that underpin behavioral regulations in PWS.

In one of the earliest fMRI studies on PWS, Holsen et al. (136) compared brain activation in response to food images before and after a meal between age-matched adolescents with PWS (N = 9) and healthy-weight controls (N = 9). In response to food pictures presented post-meal, the PWS group exhibited greater activation in food motivation networks involving the OFC, medial PFC, insula, hippocampus, and Parahippocampal gyrus. Dimitropoulos and Schultz (137) examined food-related neural circuitry in individuals with PWS (N = 9, age range = 8–38 years) and controls (N = 10, age range = 18–29 years) with developmental delay and similar body mass index (BMI). In response to high-versus low-calorie foods, they showed increased activation in the PWS group in the neural circuitry known to mediate hunger and motivation, including the hypothalamus and the OFC. Subsequently, Holsen et al. (138) conducted a functional MRI in 15 age-matched healthy-weight controls, 14 patients with PWS, and 14 BMI age-matched obese patients without PWS before (pre-meal) and after (post-meal) eating while viewing images of food and non-food. In this study, individuals with PWS exhibited heightened post-meal activation in subcortical regions, including the hypothalamus, amygdala, and hippocampus, while showing reduced cortical activation in inhibitory control areas such as the dorsolateral PFC. In contrast, the obese group displayed greater engagement of the inhibitory control regions compared to both the PWS and healthy-weight groups, highlighting a potential neural basis for impaired regulatory control and increased obesity risk in PWS.

Using resting-state fMRI, several studies investigated functional brain network alterations in individuals with PWS. A study involving 21 children with PWS (10 girls, 11 boys) and 18 healthy siblings as controls (10 girls, eight boys) revealed decreased functional connectivity in the default mode network (DMN) and the motor sensory network, as well as increased functional connectivity in the core network (anterior cingulate/insula). The PFC network exhibited both increased (between the ventral PFC with both the dorsolateral and orbital PFCs) and decreased (between dorsolateral and orbital PFCs) connectivity (139). These findings indicate altered functional connectivity among brain regions involved in eating/satiety reward processing (139). In a study comparing 24 with PWS to 29 control adults (140), PWS showed (i) disrupted functional connectivity between the PFC and basal ganglia, as well as within subcortical regions, which was linked to obsessive-compulsive behaviors, (ii) Increased connectivity in the sensorimotor–putamen loop which was strongly associated with self-picking, (iii) abnormal connectivity within basal ganglia circuits and between the striatum, hypothalamus, and amygdala which was related to obsessive eating behavior.

Finally, a study by Huang et al. (141) involving 58 children: 32 Healthy controls (21 males) and 26 with PWS (17 males) found that children with PWS exhibited decreased intranetwork functional connectivity in the dorsal attention, auditory, medial visual, and sensorimotor networks (SMN). These changes were positively correlated with developmental quotients, suggesting that intranetwork functional connectivity alterations could serve as biomarkers for developmental delays in PWS. Additionally, internetwork functional connectivity between the posterior DMN and anterior DMN and between the posterior DMN and SMN was significantly reduced in PWS children, with these changes negatively correlated with developmental scores. These findings highlight the importance of both intra- and inter-network FC in understanding the neurodevelopmental mechanisms underlying PWS.

Functional and resting-state fMRI studies in individuals with PWS consistently revealed hyperactivation in reward-related and hunger-related brain regions, such as the OFC, hypothalamus, and amygdala, following food cues, particularly after meals. Compared to controls, individuals with PWS exhibited reduced activation in inhibitory control regions and showed altered functional connectivity in networks related to eating behavior, satiety, and compulsivity. Resting-state studies further indicated disruptions in both intranetwork and internetwork connectivity, including the default mode, attention, and SMNs, which were associated with obsessive behaviors and developmental delays, suggesting these connectivity patterns may serve as potential biomarkers for PWS.

Structural-Functional Coupling and Network Topology

A recent study by Huang et al. (142) explored the coupling between structural and functional networks using DTI and resting-state fMRI data from 25 children with PWS and 28 age- and sex-matched healthy controls. They found that children with PWS exhibited decreased structural-functional coupling associated with developmental delays. This decoupling is characterized by a higher characteristic path length and lower global efficiency in the structural network, indicating reduced integration and information transfer efficiency.

Nodal analysis further revealed alterations in key brain regions, including the precentral gyrus, prefrontal gyrus, and basal ganglia, which are part of large-scale networks such as the SMN, DMN, salience network (SAN), and basal ganglia network (BGN). Structural network disruptions were more pronounced in the SMN, DMN, and visual network, while functional network disruptions were more evident in the SAN and BGN. These findings suggest that the structural and functional decoupling may be linked to developmental delays in motor and cognitive domains. Moreover, group differences based on nodal analysis revealed that functional networks in PWS children showed less significant disruptions than structural network disruptions, suggesting that structural network abnormalities may play a more critical role in the neurodevelopmental delays observed in PWS.

Neuroimaging Findings in PWS by Their Genetic Subtypes

The genetic heterogeneity of PWS profoundly influences neuroimaging phenotypes, which can be categorized by two primary genetic subtypes: DEL and mUPD. A study involving 15 individuals with PWS due to a typical DEL, 8 with PWS due to mUPD, and 25 age-matched healthy-weight individuals found that the DEL subtype exhibited pronounced GM loss in prefrontal and temporal cortices. In contrast, mUPD was found to be associated with diffuse cortical atrophy, ventriculomegaly, and thickened cortices—features linked to psychiatric symptoms (143). For instance, mUPD individuals showed heightened amygdala reactivity and ACC dysfunction, mirroring SCZ-like phenotypes (35). In contrast, DEL patients with 15q11-q13 Type I DEL display more severe cerebellar hypoplasia and visual processing deficits (13).

Neuroimaging studies utilizing structural sMRI, DTI, and fMRI further revealed how genetic differences influence brain structure, neural connectivity, and associated cognitive, behavioral, and metabolic dysfunctions. Key genes such as SNRPN, SNORD116, and MAGEL2 play crucial roles in brain development and function, contributing to subtype-specific neuroimaging patterns (127, 129, 130, 132). Table 4 summarizes these structural and functional connectivity alterations across key brain regions, emphasizing genetic subtype differences (DEL vs. mUPD) and their implications for neurodevelopment, reward processing, and psychiatric comorbidities.

With respect to structural and functional connectivity abnormalities, the DEL subtype is characterized by greater structural atrophy, particularly in the PFC, hypothalamus, and cerebellum. Functional imaging suggests compensatory hyperactivation in the OFC and amygdala, leading to exaggerated responses to food cues and impaired inhibitory control. Genetic alterations, particularly involving SNRPN and MAGEL2, may disrupt neural pathways that are crucial for reward processing, emotional regulation, and satiety, further contributing to the functional deficits observed in this subgroup.

Conversely, the mUPD subtype displays widespread disruptions in functional connectivity, particularly within the prefrontal-limbic circuit. This subtype is linked to psychiatric symptoms resembling those seen in SCZ, with reduced prefrontal-amygdala and prefrontal-striatal connectivity leading to emotional dysregulation and increased risk of affective disorders. SNORD116 gene expression plays a significant role in modulating neural circuits involved in mood and behavior regulation, and its dysregulation in mUPD individuals contributes to these abnormalities.

DTI studies further support these differences by showing greater WM disconnection in mUPD individuals, particularly in the cingulum and corpus callosum. This structural disconnection correlates with higher rates of compulsivity, emotional lability, and impaired social cognition, reflecting underlying genomic imprinting effects. The close association between genetic subtype, structural abnormalities, and functional connectivity disruptions suggests that targeted interventions should be tailored to the specific neural vulnerabilities of each PWS subtype. In future genetic studies, incorporating genes such as SNRPN, SNORD116, and MAGEL2 could provide deeper insights into how these genes influence neuroanatomy and neural circuits. Additionally, integrating multimodal neuroimaging approaches (such as fMRI, diffusion MRI, and sMRI) with genomic data could further elucidate the relationship between genetic defects and neurodevelopmental outcomes in PWS. Future research combining genomic, transcriptomic, and multimodal neuroimaging approaches could shed light on the molecular mechanisms that drive neurodevelopmental differences, enabling the development of more personalized and effective interventions for individuals with PWS.

Longitudinal and Developmental Insights

Longitudinal MRI studies remain limited but suggest dynamic neurodevelopmental changes in PWS. Children with mUPD exhibit early brain atrophy and progressive WM degeneration, while DEL subtypes show static GM reductions without cortical thinning (131). Cortical gyrification index reductions in the frontal and parietal lobes correlate with cognitive impairment, highlighting disrupted intracortical organization (135). Early-life hypothalamic volume loss predicts later hyperphagia severity, emphasizing the need for developmental biomarkers (128).

Future Directions and Advanced Techniques

Advanced neuroimaging techniques have significantly contributed to characterizing the structural and functional brain abnormalities associated with PWS, offering critical insights into the neural mechanisms underlying its cognitive, behavioral, and developmental features. Structural MRI studies revealed GM reductions and WM lesions, but protocol variability, limited resolution, and motion artifacts affect generalizability and accuracy. DTI is specifically limited by partial volume effects and difficulty resolving crossing fibers. To overcome these limitations, more advanced diffusion imaging techniques have been developed. Diffusion Spectrum Imaging (DSI), High Angular Resolution Diffusion Imaging (HARDI), and Neurite Orientation Dispersion and Density Imaging (NODDI) offer substantial improvements in detecting and characterizing complex fiber structures. DSI, for example, is capable of crossing fibers in regions such as the optic chiasm, centrum semiovale, and brainstem—regions where DTI frequently falls short (144). HARDI offers enhanced resolution in characterizing intricate fiber orientations and crossings within a single voxel (145, 146), and although computationally intensive, it yields more dependable results in fiber tractography. Furthermore, NODDI provides additional insight into axonal density and morphology, capturing tissue microstructure with high precision (146). Moreover, advanced techniques like diffusion kurtosis imaging and arterial spin labeling may better capture WM complexity and perfusion changes (127) and thus enhance our insights into structural-functional coupling characteristics in PWS. Furthermore, the interpretation of fMRI is complicated by syndrome heterogeneity, psychiatric comorbidities, and compliance challenges, especially in children. See Table 4A in the Supplementary Material for more details.

To advance research on PWS, future studies should prioritize large-scale, longitudinal cohorts to track brain maturation trajectories and treatment responses across development. This is especially relevant given the limitations of existing imaging studies, which are often constrained by small sample sizes, broad age ranges, and substantial genetic and clinical heterogeneity, including frequent comorbidities such as ASD and SCZ. High-resolution neuroimaging methods (see above) in younger populations are particularly needed to capture early neural alterations. Innovative methodological approaches can help overcome current challenges in data acquisition. For example, the use of mock scanner training protocols can help individuals with behavioral difficulties acclimate to the MRI environment, thereby enhancing data quality and participant compliance (147). The integration of artificial intelligence (AI) with multimodal MRI data holds promise for identifying predictive biomarkers of ASD or SCZ risk in PWS, paving the way for personalized interventions. Finally, integrating neuroimaging techniques such as MRI with cellular-resolution imaging methods like confocal or electron microscopy in iPSC models may provide critical insights into how specific genetic variants in PWS influence neural circuit development, a concept supported by recent transcriptomic studies using patient-derived neurons to investigate shared and distinct mechanisms in ASD and SCZ.