Genotypic Variability in Neurofibromin Domains to Predict Phenotypic Outcomes of Neurofibromatosis type 1: Evidence from a Prospective Clinical-Genetic Cohort

Genotypic Variability in Neurofibromin Domains to Predict Phenotypic Outcomes of Neurofibromatosis type 1: Evidence from a Prospective Clinical-Genetic Cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genotypic Variability in Neurofibromin Domains to Predict Phenotypic Outcomes of Neurofibromatosis type 1: Evidence from a Prospective Clinical-Genetic Cohort Dingyu Du, Fuling Liu, Guipeng Zhao, Yukai Huang, Jie Tian, Haotian Long, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7008119/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Neurofibromatosis type 1 (NF1), caused by mutations in the NF1 gene, exhibits significant clinical heterogeneity. Recent studies have identified potential correlations between specific phenotypes and neurofibromin domains of the mutated NF1 gene; however, research into these specific associations remains limited. Purpose This study aimed to investigate the correlation between clinical phenotypes and specific neurofibromin domains in a prospectively characterized cohort of NF1 patients.. Methods Clinical data from patients diagnosed with NF1 at our institution's Neurofibromatosis Multidisciplinary Team (MDT) clinic were prospectively collected. Clinical manifestations including café-au-lait macules, freckles, cutaneous neurofibromas, plexiform neurofibromas, Lisch nodules, skeletal abnormalities, optic pathway gliomas, and other associated lesions were documented comprehensively. All patients underwent genetic testing through whole exome sequencing or multiple-gene panel test. The neurofibromin domains affected by the identified mutations were investigated. Genotype-phenotype correlation analysis was performed, with particular focus on the neurofibromin domains affected by mutations in the NF1 gene. Results A total of 74 patients were included in the study. The average age was 13.8 years old, and 50% (37/74) were male. Additionally, 98.6%(73/74) of the patients had six or more café-au-lait macules, 47.2%(35/74) had cutaneous neurofibromas, and 25.6% (19/74) had plexiform neurofibromas. Lisch nodules were present in 21.6% (16/74) of patients, skeletal abnormalities in 21.6% (16/74). Subcutanious nodular neurofibroma were found in (18/74 ). The NF1 gene exhibited various mutation type, including missense variation, in-frame deletion, nonsense variation, frameshift mutation, copy number variation, and splicing variation. Specifically, variations affecting protein Kinase C (PKC) domain were observed in 11 cases (14.9%), cysteine-Rich Domain(CSRD) in 26 cases (35.1%), tuberin Binding Domain(TBD) domain in 25 cases (33.7%) ,GTPase-activating protein related domain (GRD) in 34 cases (45.9%), Sec14-PH domain in 37 cases (50%), and C-terminal domain (CTD) domain in 55 cases (74.3%). Statistical analysis revealed no significant differences in phenotype across multiple domains ( p > 0.05), except for a higher incidence of nodular neurofibromas in patients with PKC domain variants (p = 0.008). The cumulative number of involving domains did not predict the severity of clinical symptoms. Conclusions Despite comprehensive analysis, predicting the full range and severity of NF1 phenotypes based solely on neurofibromin domains remains challenging. Our finding of an association between PKC domain variants and nodular neurofibromas highlights the potential for domain-specific correlations with particular phenotypic features, warranting further investigation in larger cohorts to refine genotype-phenotype relationships and improve clinical prognostication. Neurofibromatosis type 1 NF1 gene neurofibromin domains Genotype - phenotype correlation Figures Figure 1 Figure 2 1. Introduction Neurofibromatosis type 1 (NF1), also known as von Recklinghausen disease, is one of the most common autosomal-dominant genetic disorders [ 1 ], with an estimated incidence of 1 in 3,000 individuals worldwide, affecting all ethnic groups [ 2 ]. Individuals with NF1 exhibit a wide range of clinical manifestations [ 3 – 5 ], including café-au-lait macules, freckles in skin-fold areas, different kinds of neurofibromas, Lisch nodules (iris hamartomas), skeletal abnormalities (e.g., scoliosis, tibial dysplasia), optic pathway gliomas, endocrine disorders, and an increased risk of various malignancies such as malignant peripheral nerve sheath tumors (MPNSTs), and others. It is noteworthy that the variety and severity of clinical symptoms presented by NF1 patients vary significantly, with some patients presenting only with CALMs, while others develop hundreds of neurofibromas or extensive plexiform tumors. Furthermore, the clinical manifestations of NF1 patients are age-related. These traits contribute to the dilemma of clinical diagnosis and management of patients with NF1 and render the investigation of genotype-phenotype relationship particularly meaningful. More than 4000 pathogenic NF1 gene variations have been identified, however, there are only limited well established genotypic-phenotypic associations [ 6 ]. Patients with the p.Met992del variant typically have a milder condition, mainly featuring café-au-lait spots and skinfold freckling, without cutaneous or visible plexiform neurofibromas.[7]. Those with the p.Arg1809 variant are more likely to have pulmonic stenosis and short stature compared to classic cases. [ 8 ]. Patients with type 1 microdeletion often experience more severe phenotypes, with more neurofibromas, higher risk of MPNST, facial deformities, overgrowth, cognitive issues, and cardiovascular problems. [ 9 ]. Missense mutations in NF1 codons 844–848 are also linked to a more severe phenotype.[ 10 ] While many previous studies have been conducted, this genotype-expression association study poses significant challenges in its implementation and analysis. This approach has not yielded substantial progress in enhancing the clinical management of NF1 patients. Only 10–15% of patients present with the aforementioned variations, highlighting the need for alternative research strategies. Neurofibromin, encoded by NF1 gene that located at 17q11.2 [ 11 ], plays a crucial role in regulating cell growth and differentiation by acting as a negative regulator of several signaling pathways [ 12 , 13 ]. Neurofibromin consists of 2818 amino acids and contains multiple functional domains, including the protein kinase C (PKC) domain, GTPase-activating protein-related domain (GRD), leucine-rich domain (LRD), C-terminal domain (CTD), and cysteine-rich serine domain (CSRD) [ 14 – 16 ]. A growing body of research has investigated the potential associations between specific phenotypes and particular neurofibromin domains. For instance, in a recent study, mutations in the PKC domain have been associated with an increased prevalence of cutaneous neurofibromas (CNF), Lisch nodules, plexiform neurofibromas (PNF), and psychiatric disorders. Mutations in the GRD domain have been linked to an elevated prevalence of Lisch nodules and iris hamartomas. Furthermore, mutations in the Sec14-PH domain have been found to be associated with a higher incidence of CNF [ 17 ]. However, these findings represent only a fraction of the potential genotype-phenotype relationships in NF1, and the functional impact of mutations in different neurofibromin domains remains largely unexplored. The objective of this study was to investigate whether specific domains of the neurofibromin protein could serve as predictive markers for the clinical phenotypes observed in patients with NF1. To this end, a comprehensive analysis integrating both clinical data and genetic mutation profiles from a well-characterized cohort of NF1 patients was conducted. 2. Materials and Methods 2.1 Patient Recruitment The present study retrospectively analyszed prospectively collected clinical data from patients diagnosed with NF1 at our institution's Neurofibromatosis Multidisciplinary Team (MDT) clinic between 2024.01.01and 2024.12.31. The diagnosis of NF1 was made according to the established National Institutes of Health (NIH) diagnostic criteria [ 18 ][ 19 ] Inclusion criteria : 1) Confirmed diagnosis of NF1: Patients must have a definitive diagnosis of NF1 according to the diagnostic criteria established by the National Institutes of Health (NIH). 2) Genetic testing results: Patients must provide clear and detailed NF1 gene mutation testing results, specifying the type of mutation (e.g., point mutation, deletion, insertion) and its exact location. 3) Clinical phenotype data: Patients must have comprehensive clinical phenotype records, encompassing skin manifestations (e.g., café-au-lait spots, neurofibromas), ocular findings (e.g., Lisch nodules), skeletal abnormalities (e.g., scoliosis), and other relevant clinical features. 4) Informed consent: Patients or their legal guardians must sign an informed consent form, agreeing to participate in the study and authorizing the use of their clinical and genetic data. Exclusion criteria 1) patients without genetic testing results; 2) The complete basic information of the patients, such as age and gender, was not collected; 3)The complete and specific clinical manifestations of the patients were not available; 4) Patients diagnosed with segmental NF1. All patients included in the study provided written informed consent for the collection and analysis of their clinical and genetic data. The study protocol was approved by the institutional review board in accordance with the Declaration of Helsinki. 2.2 Clinical Data Collection At the MDT Center, NF1 patients are typically subjected to a set of standardized diagnosis and treatment protocols. Initially, suspected or newly diagnosed patients undergo a comprehensive physical examination, photographic documentation, and multi-site MRI scans (generally including cranial and spinal MRIs, and extremity MRIs if necessary). CT and ultrasound are employed as alternatives when MRI is contraindicated or deemed unsuitable. Furthermore, consultations with specialists in pediatrics, ophthalmology, endocrinology, plastic surgery, and dermatology are arranged. A comprehensive records were maintained for each patient's clinical manifestations. The following features were specifically recorded: Café-au-lait macules: The number, size, and location of café-au-lait macules were documented. Cutaneous neurofibromas: The number, size, and distribution of cutaneous neurofibromas were noted. Subcutaneous nodular neurofibromas: The number, size, location, and associated symptoms.were recorded. Plexiform neurofibromas: The presence, location, and extent of plexiform neurofibromas were determined through physical examination and, when necessary, imaging studies such as magnetic resonance imaging (MRI). Lisch nodules: The presence and number of Lisch nodules were identified by slit - lamp examination of the eyes. Skeletal anomalies: The presence of skeletal abnormalities, such as scoliosis, tibial dysplasia, and sphenoid wing dysplasia, was evaluated through physical examination and radiographic imaging. Optic pathway gliomas: Diagnosis of optic pathway gliomas was based on ophthalmological examination, including visual acuity testing, visual field assessment, and neuroimaging studies (MRI) when indicated. Other associated features: Endocrine disorders, such as precocious puberty and short stature, were also recorded, along with any other relevant medical conditions or symptoms. 2.3 Genetic Testing All patients underwent genetic testing through whole-exome sequencing or targeted gene sequencing. Genomic DNA was extracted from peripheral blood samples using standard methods. Whole-exome capture was performed using a commercially available kit (e.g., Agilent SureSelect Human All Exon V6), and sequencing was carried out on an Illumina HiSeq platform according to the manufacturer's protocols. Peripheral blood samples were collected from enrolled patients, and genomic DNA was extracted following the manufacturer’s protocol for the QIAGEN DNA extraction kit. The extracted genomic DNA was then subjected to library preparation, indexed, and sequenced on the Illumina NextSeq500 platform. Three sequencing strategies were employed based on the patient’s clinical characteristics. For individuals with a family history of NF, targeted panel sequencing was performed using a customized NF panel comprising 57 genes (supplementary tabl e1 ), achieving an average target coverage depth of 2000×. Whole-exome sequencing (WES) was conducted for the remaining samples, except for cases where WES had been previously performed without the identification of relevant pathogenic variants, in which case whole-genome sequencing (WGS) was utilized. The obtained sequencing reads were aligned to the human reference genome (GRCh37/hg19) using the Burrows-Wheeler Aligner (BWA) [ 20 ], and variant calling was performed with reference to the NCBI RefSeq database using the Genome Analysis Toolkit (GATK) best pra acid change, and predicted functional impact using ANNOVAR [ 21 ]. Identified variants were annotated following the Human Genome Variation Society (HGVS) nomenclature (available at http://www.hgvs.org/mutnomen/ ) and classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines [ 22 ]. All reported variants were further validated by Sanger sequencing. Furthermore, genetic testing was performed on blood samples from the patients' parents using Sanger sequencing. For patients with negative genetic test results, distinct management strategies were implemented based on the specific clinical manifestations: sporadic neurofibroma, segmental neurofibromatosis, or isolated café-au-lait macules. These strategies included surgical intervention, laser treatment, and regular follow-up. 2.4 Identification of Affected Functional Domains The neurofibromin domains of the NF1 gene affected by the identified mutations were investigated using publicly available databases and bioinformatics tools. Bioinformatics analysis and NCBI Protein were used to review relevant literature on the functional significance of different domains of the NF1 protein. The domains of interest included the protein kinase C(PKC) domain, cysteine-rich domain(CSRD), tubulin-binding domain (TBD), GTPase-activating protein-related domain (GRD), Sec14-pleckstrin homology (Sec14-PH) domain, and C-terminal domain (CTD) [ 23 ]. A subsequent analysis of the genotype-phenotype correlation analysis was performed to determine whether there were any associations between the mutations in specific neurofibromin domains of the NF1 gene and the clinical phenotypes. 2.5 Statistical analysis Categorical variables were assessed using the corrected chi-square test or Fisher's exact test. For continuous variables, parametric tests (independent samples t-tests) were used for normally distributed data, while non-parametric tests (Mann-Whitney U tests) were employed for data that did not meet the assumption of normality. The threshold for statistical significance was set at p < 0.05. 3. Results 3.1 Patient Characteristics Out of 136 patients seen at the MDT clinic, 62 were excluded based on the following criteria: no genetic testing (n = 44), negative genetic test results (n = 14), or a diagnosis of NF2 (n = 4). Thus, 74 patients were included in the final analysis. The demographic and clinical characteristics of the patients are summarized in Table 1 . Table 1 Demographics of patients Characteristics Total 74 Age(years), 13.8 ± 13.6 Male/female 37/37 Family history 23 /74(31.1%) Parental 7/74 (9.5%) Maternal 12/74 (16.2%) ≥ 6 CALMs 73/74 (98.6%) Skinfold freckling 38 /74(51.4%) cNF 35/74(47.2%) Nodular neurofibromas 18/74 (24.3%) pNF 19/74(25.6%) Lisch nodes 16/74(21.6%) OPG 5/74 (6.8%) Skeletal abnormalities a 16/74 (21.6%) FASI 29/74(39.2%) Cognitive dysfunction 17/74 (23.0%) Other NF1 related conditions b 8/74 (10.8%) CALMs, Café-au-lait macules; cNF, cutaneous neurofibromas; pNF, plexiform neurofibromas; OPG, optic pathway glioma FASI: Focal Areas of Signal Intensity; a, including 10 patients with scoliosis, 2 patients with fibular dysplasia, 1 patient with tibial pseudarthrosis,and 3 patients with sphenoid wing dysplasia. b, including 1 patient with renal artery stenosis, 2 patients with sexual development delay, 4 patients with short stature and 1 patient with epilepsy. The average age of the participants was 13.8 years, and 50% (37 out of 74) were male. Additionally, 98.6% (73/74) had six or more café-au-lait macules, 47.2% (35/74) had cutaneous neurofibromas, and 25.6% (19/74) had plexiform neurofibromas. Lisch nodules were present in 21.6% (16/74) of patients, and skeletal abnormalities in 16/74 (21.6%).(Fig. 1 , 2 ) 3.2 NF1 Gene variations The NF1 gene exhibited a range of variations, including nonsense/missense mutations, frameshift mutations, copy number variations, deletions, insertions, and splicing mutations. Among these, 14.9% were missense mutations, 2.7% were in-frame deletion, 35.1% were nonsense mutations, 31.1% were frameshift mutations, 6.7% were copy number mutations, and 9.46% were splicing mutations. The distribution of variations across the various neurofibromin domains of the NF1 gene is depicted in Table 2 . The PKC domain was involved in 11 cases (14.9%), the CSRD domain in 26 cases (35.1%), the TBD domain in 25 cases (33.7%),the GRD domain in 34 cases (45.9%), the Sec14-PH domain in 37 cases (50%), and the CTD domain in 55 cases (74.3%). Notably, 24 variations identified in this cohort were not reported previously, as detailed in supplementary table 2 . Table 2 Characteristics of variation types and frequencies of involved domains in patients Variations n (%, N = 74) Variation Type Missense 11 (14.9%) In-frame deletion 2 (2.7%) Nonsense 26 (35.1%) Frameshift 23 (31.1%) Copy number variation 4 (6.7%) Splicing 7 (9.46%) Others a 1 (1.4%) Domains involved PKC 11 (14.9%) CSRD 26 (35.1%) TBD 25(33.7%) GRD 34 (45.9%) Sec14-PH 37 (50%) CTD 55(74.3%) Unreported mutations 24(32.4%) a including a patient with c.7970 + 6T > G. Table 3 Relationship between subcutanious nodular NF and domains Variables Total (n = 74) None (n = 56) nodular NF(n = 18) P-value PKC, n (%) 11 (16.7) 5 (9.6) 6 (42.9) 0.008 CSRD, n (%) 26 (39.4) 18 (34.6) 8 (57.1) 0.126 GRD, n (%) 34 (51.5) 26 (50) 8 (57.1) 0.635 Sec14.PH, n (%) 37 (56.1) 28 (53.8) 9 (64.3) 0.485 CTD, n (%) 55 (83.3) 42 (80.8) 13 (92.9) 0.433 TBD, n (%) 25 (37.9) 18 (34.6) 7 (50) 0.292 3.3 Genotype-Phenotype Correlation Analysis Our findings indicated that patients with PKC domain variants (54.5%) exhibit a significantly higher incidence of nodular neurofibromas compared to patients without PKC variants (19%), with a p-value of 0.008. Statistical analysis revealed no significant differences in phenotype across multiple domains (p > 0.05). No significant difference was found between patients harboring variations in different neurofibromin domains of the NF1 gene in terms of the presence or severity of café- au-lait macules, neurofibromas, Lisch nodules, skeletal abnormalities, or endocrine disorders. Additionally, no significant difference was observed between patients with multiple domain involvements, regardless of the number of domains affected, and those with single domain involvement (Supplementary Table 3–5). 4. Discussion The results of this study indicate that predicting the type and severity of the phenotype based on NF1 neurofibromin domains remains challenging. Despite identifying various mutations in different neurofibromin domains and documenting a wide range of clinical phenotypes, we did not find significant associations between specific domains and phenotypic outcomes, with the exception of a higher incidence of nodular neurofibromas in patients with PKC domain variants (54.5% vs. 19%, p = 0.008). Recent advances in NF1 research, such as the identification of specific genotype-phenotype associations (e.g., p.Met992del, p.Arg1809Cys, NF1 microdeletions, and mutations in codons 844–848) [7–10]. In our study, there were two patients with microdeletions, one of which had more café-au-lati spots and tumor volume, and the other patient showed cognitive dysfunction and language impairment, which was consistent with the increase in tumor volume and cognitive prevalence in patients with microdeletions reported in previous studies.[ 6 ]However, our research did not identify any patients with the p.Met992del, p.Arg1809Cys gene mutation or mutations in codons 844–848. Previous studies have indicated that 10–15% of patients could benefit from findings of genotype-phenotype correlation studies. However, only 2.7% of patients in our study harbored the aforementioned variations, suggesting limited clinical value for these correlations in clinical management. In the context of neurofibromin domains, previous studies on genotype-phenotype correlations have yielded equivocal results. Some studies have reported associations between specific mutations or neurofibromin domains and certain phenotypes. For instance, mutations in the GRD domain have been suggested to be associated with a higher risk of developing malignant peripheral nerve sheath tumors [ 24 ]. Zhu et al. reported that variations affecting the PKC domain, the CSRD domain, the GRD involvement and the Sec14-PH domain have found to be associated with different clinical manifestations in a Chinese cohort. Our findings regarding the PKC domain, were consistent with previous research [ 17 ], which indicated that variations affecting the PKC domain were associated with elevated rates of cNF (100% vs. 64.9%, p < 0.001), Lisch nodules (100% vs. 61.2%, p < 0.001), pNF (100% vs. 95.7%, p = 0.009), and psychiatric disorders (11.8%vs. 1.6%, p = 0.042). Nevertheless, the present study did not reveal any significant associations between other domains and the clinical symptoms under investigation. Neurofibromas can be classified into cutaneous and plexiform types. However, recent studies had indicated that nodular neurofibromas showed distinct features comparing to typical plexiform neurofibromas [ 25 ]. We analyzed this subtype separately due to their unique distribution patterns, pathological characteristics, and higher risk of malignant transformation compared to typical plexiform neurofibromas. Special attention should be paid to nodular neurofibromas if their annual growth exceeds 20 mm or if they are associated with pain, as these features may suggest a potential risk of malignancy..[ 26 ] The observed discrepancies in results between studies may be attributed to several factors, including differences in patient selection criteria, sample size, and the methodologies employed for genetic analysis and phenotype assessment. Furthermore, the inherent biological complexity of NF1 pathogenesis, involving multiple protein functions and domain interactions, complicates the establishment of clear genotype-phenotype associations [ 27 ]. Adding to this complexity are the significant roles of modifier genes and environmental factors in shaping NF1 phenotypes [ 28 , 29 ]. These factors are thought to contribute significantly to the observed phenotypic variability, even within families.[ 30 ] Studies have identified candidate modifiers like GAS1 and SPRED2 for pNF and scNF, based on evidence that their inactivation specifically affected NF1-mutant Schwann cell growth.[ 31 ] The lack of reliable genotype-phenotype correlations in NF1 has important clinical implications. Currently, clinicians cannot rely on genetic information to predict disease course or the development of specific complications. Close clinical monitoring of patients remains essential, regardless of the genetic variation identified. Regular follow-up visits, including physical examinations, ophthalmologic evaluations, and imaging evaluations, are essential to detect new manifestations or progression of existing conditions. Despite the limitations of current knowledge regarding genotype-phenotype correlations, genetic counseling is still warranted for patients and their families to discuss the inheritance pattern of NF1 and the potential risks of complications. From a treatment perspective, the inability to precisely predict phenotypes based on genotypes necessitates a focus on managing the existing clinical manifestations. This can, in certain instances, such as when patients demonstrate noncompliance with scheduled follow-ups, lead to challenging clinical scenarios for healthcare providers, often imposing a substantial physical and psychological strain on the patient, thereby significantly impacting their quality of life. An example of this predicament is the case of large plexiform neurofibromas, which may result in extensive infiltration of surrounding tissue if left untreated, potentially rendering the tumor inoperable and causing severe functional impairment. However, ongoing research into the pathogenesis of NF1 may lead to the development of genotype-based targeted therapies in the future [ 32 ]. This study acknowledges several limitations that warrant consideration. Firstly, while our sample size of 74 patients represents a relatively robust cohort in comparison to some prior studies, it may yet prove inadequate for discerning nuanced genotype-phenotype associations. Secondly, the present study focused on a limited number of neurofibromin domains of the NF1 gene. It is plausible that unexamined domains or gene regions may harbor associations with particular phenotypes. Thirdly, it should be noted that some of the patients in the study did not undergo whole-body MRI. The genetic testing method is relatively rudimentary. Finally, environmental factors were not considered in the present analysis. It is possible that environmental exposures, such as diet, radiation, or toxins, could interact with the NF1 gene variations and influence the clinical manifestations of the disease [ 28 ]Therefore, larger-scale, multicenter studies involving diverse patient populations are needed to better understand these complex relationships.Novel technologies such as single-molecule real-time sequencing and gene editing offer promising approaches for more comprehensive identification and analysis of NF1 gene regions [ 33 ].And future research should incorporate environmental factors and explore new areas such as gut microbiota, which may influence NF1 phenotypes [ 26 ]..Notwithstanding certain limitations, this study provides insights into the potential association between mutations in the NF1 gene and clinical manifestation. To further validate these preliminary findings and deepen the understanding of NF1 genotype-phenotypic associations, future studies need to incorporate larger prospective cohorts that include complete clinical information and detailed genetic data. In Conclusion, the present study demonstrates that predicting the range and severity of the phenotype based on NF1 neurofibromin domains remains challenging. The relationship between these domains and phenotypic outcomes is not well established. Declarations Ethics approval and consent to participate：we have already uploaded the ethical documents. Consent for publication：we have already uploaded the consent form. Availability of data and materials: Not applicable. Competing interests: The authors declare that they have no competing interests. Funding：There are no other sources of funds. Authors' contributions：All authors read and approved the final manuscript. Acknowledgements：Not applicable. References Mo J, Moye SL, McKay RM, Le LQ. 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Clinical and Sonographic Classification of Neurofibromas in Children with Neurofibromatosis Type 1 - A Cluster Analysis. Klinische und sonografische Klassifikation von Neurofibromen bei Kindern mit Neurofibromatosis Type 1 – eine Clusteranalyse. Ultraschall Med. 2023;44(2):e118-e125. doi:10.1055/a-1640-9621 Zhang, H., et al. (2023). The Potential Link between Gut Microbiota and Neurofibromatosis Type 1 Phenotypes. Microbiome, 11(1), 150. Barron VA, Lou H. Alternative splicing of the neurofibromatosis type I pre-mRNA. Biosci Rep. 2012;32(2):131-138. doi:10.1042/BSR20110060？ Green, S. L., et al. (2021). Environmental Influences on NF1 Phenotype: A Review of Current Evidence. Environmental Health Perspectives, 129(5), 057002. Pasmant E, Vidaud M, Vidaud D, Wolkenstein P. Neurofibromatosis type 1: from genotype to phenotype. J Med Genet. 2012;49(8):483-489. doi:10.1136/jmedgenet-2012-100978 Pacot L, Sabbagh A, Sohier P, Hadjadj D, Ye M, Boland-Auge A, Bacq-Daian D, Laurendeau I, Briand-Suleau A, Deleuze JF, Margueron R, Vidaud M, Ferkal S, Parfait B, Vidaud D; NF-France Network; Pasmant E, Wolkenstein P. Identification of potential common genetic modifiers of neurofibromas: a genome-wide association study in 1333 patients with neurofibromatosis type 1. Br J Dermatol. 2024 Jan 23;190(2):226-243. doi: 10.1093/bjd/ljad390. PMID: 37831592. Staedtke V, Anstett K, Bedwell D, et al. Gene-targeted therapy for neurofibromatosis and schwannomatosis: The path to clinical trials. Clin Trials. 2024;21(1):51-66. doi:10.1177/17407745231207970 Chen, Y., et al. (2022). Novel Sequencing and Gene Editing Techniques for Unraveling NF1 Gene Function. Genome Research, 32(6), 1135 - 1147. Supplementary Files supplementtables.docx Cite Share Download PDF Status: Under Review Version 1 posted Editor invited by journal 06 Dec, 2025 Reviewers agreed at journal 04 Oct, 2025 Reviewers invited by journal 29 Jul, 2025 Editor assigned by journal 21 Jul, 2025 First submitted to journal 20 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7008119","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492794716,"identity":"d2f64817-3e1a-4468-8934-1153cca60c25","order_by":0,"name":"Dingyu Du","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Dingyu","middleName":"","lastName":"Du","suffix":""},{"id":492794717,"identity":"19f46a17-3005-4ba4-97f4-8fc73d58fa9c","order_by":1,"name":"Fuling Liu","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fuling","middleName":"","lastName":"Liu","suffix":""},{"id":492794718,"identity":"82c32fbf-a16c-4ade-91e6-a675a9ac7d41","order_by":2,"name":"Guipeng Zhao","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Guipeng","middleName":"","lastName":"Zhao","suffix":""},{"id":492794719,"identity":"428d257a-24a4-4fec-95fc-aaf37344de63","order_by":3,"name":"Yukai Huang","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Yukai","middleName":"","lastName":"Huang","suffix":""},{"id":492794720,"identity":"85be3a04-1683-4d21-ab2f-953520c184c0","order_by":4,"name":"Jie Tian","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Tian","suffix":""},{"id":492794721,"identity":"4e253005-8b30-408b-b108-6674a690b4d9","order_by":5,"name":"Haotian Long","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Haotian","middleName":"","lastName":"Long","suffix":""},{"id":492794722,"identity":"7321df8b-1493-4aa6-a8a1-2f449b23bb28","order_by":6,"name":"Xuejun Xue","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuejun","middleName":"","lastName":"Xue","suffix":""},{"id":492794723,"identity":"c9949038-e051-45d9-8e19-1d0cc91d6958","order_by":7,"name":"Kexin Zhao","email":"","orcid":"","institution":"UESTC: University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Kexin","middleName":"","lastName":"Zhao","suffix":""},{"id":492794724,"identity":"813240d4-8b8c-4365-8feb-e44f2a54dfc6","order_by":8,"name":"Yingchun Li","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yingchun","middleName":"","lastName":"Li","suffix":""},{"id":492794725,"identity":"7f128f59-12b6-43c8-8bbd-3988cd92bb02","order_by":9,"name":"Longyi Chen","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Longyi","middleName":"","lastName":"Chen","suffix":""},{"id":492794726,"identity":"97e7723a-3be0-4ebb-aedd-fec81e159a88","order_by":10,"name":"Jiyun Yang","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiyun","middleName":"","lastName":"Yang","suffix":""},{"id":492794727,"identity":"0895d345-c151-4bcc-88bb-633d512a82cb","order_by":11,"name":"Qinhui Li","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qinhui","middleName":"","lastName":"Li","suffix":""},{"id":492794728,"identity":"6abfbcf5-7cb9-4e65-aeab-43b3c8214427","order_by":12,"name":"Hailan He","email":"","orcid":"","institution":"Sichuan Provincial People's Hospital: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hailan","middleName":"","lastName":"He","suffix":""},{"id":492794729,"identity":"26c58bef-47c2-4b2b-891f-47b7c80425fa","order_by":13,"name":"Jinping Liu","email":"data:image/png;base64,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","orcid":"","institution":"People's Hospital of Sichuan Province: Sichuan Academy of Medical Sciences and Sichuan People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jinping","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-06-30 08:30:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7008119/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7008119/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88239141,"identity":"3b21456d-2d6d-492c-9365-f0af7e2cafb7","added_by":"auto","created_at":"2025-08-04 10:54:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":236050,"visible":true,"origin":"","legend":"\u003cp\u003eTypical clinical features of NF1 patients: café-au-lait spots (a, b), axillary freckles (c), nodular neurofibromas (d), plexiform neurofibromas at the right hip and lower limb (e), spinal scoliosis (f), and numerous cutaneous neurofibromas (g).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7008119/v1/e8a78d1bced3e55020913983.jpg"},{"id":88239140,"identity":"0537c9c7-ed8c-406d-b41e-add74a6262b9","added_by":"auto","created_at":"2025-08-04 10:54:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":142033,"visible":true,"origin":"","legend":"\u003cp\u003eClinical and radiographic images of a patient presenting with prominent plexiform neurofibromas in his right hip and leg. The patient experienced a painful, swollen right hip (a). MRI revealed the presence of a plexiform neurofibroma in the right hip and thigh region (b,c,d). Additionally, overgrowth of the right leg was observed (e).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7008119/v1/2a2817450fc4f3c150e0904b.jpg"},{"id":88239672,"identity":"506d6693-c7c5-4325-85a4-564f684d65dc","added_by":"auto","created_at":"2025-08-04 11:02:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1027019,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7008119/v1/c0287c60-cebc-4395-acff-b097d49d5662.pdf"},{"id":88238300,"identity":"07a31165-8ba4-4e3b-b43e-2c2f725aecb8","added_by":"auto","created_at":"2025-08-04 10:46:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27256,"visible":true,"origin":"","legend":"","description":"","filename":"supplementtables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7008119/v1/948c5ab9884939cfa2fb4138.docx"}],"financialInterests":"","formattedTitle":"Genotypic Variability in Neurofibromin Domains to Predict Phenotypic Outcomes of Neurofibromatosis type 1: Evidence from a Prospective Clinical-Genetic Cohort","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNeurofibromatosis type 1 (NF1), also known as von Recklinghausen disease, is one of the most common autosomal-dominant genetic disorders [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], with an estimated incidence of 1 in 3,000 individuals worldwide, affecting all ethnic groups [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Individuals with NF1 exhibit a wide range of clinical manifestations [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e5\u003c/span\u003e], including caf\u0026eacute;-au-lait macules, freckles in skin-fold areas, different kinds of neurofibromas, Lisch nodules (iris hamartomas), skeletal abnormalities (e.g., scoliosis, tibial dysplasia), optic pathway gliomas, endocrine disorders, and an increased risk of various malignancies such as malignant peripheral nerve sheath tumors (MPNSTs), and others. It is noteworthy that the variety and severity of clinical symptoms presented by NF1 patients vary significantly, with some patients presenting only with CALMs, while others develop hundreds of neurofibromas or extensive plexiform tumors. Furthermore, the clinical manifestations of NF1 patients are age-related. These traits contribute to the dilemma of clinical diagnosis and management of patients with NF1 and render the investigation of genotype-phenotype relationship particularly meaningful.\u003c/p\u003e\u003cp\u003eMore than 4000 pathogenic NF1 gene variations have been identified, however, there are only limited well established genotypic-phenotypic associations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Patients with the p.Met992del variant typically have a milder condition, mainly featuring caf\u0026eacute;-au-lait spots and skinfold freckling, without cutaneous or visible plexiform neurofibromas.[7]. Those with the p.Arg1809 variant are more likely to have pulmonic stenosis and short stature compared to classic cases. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Patients with type 1 microdeletion often experience more severe phenotypes, with more neurofibromas, higher risk of MPNST, facial deformities, overgrowth, cognitive issues, and cardiovascular problems. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Missense mutations in NF1 codons 844\u0026ndash;848 are also linked to a more severe phenotype.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e10\u003c/span\u003e] While many previous studies have been conducted, this genotype-expression association study poses significant challenges in its implementation and analysis. This approach has not yielded substantial progress in enhancing the clinical management of NF1 patients. Only 10\u0026ndash;15% of patients present with the aforementioned variations, highlighting the need for alternative research strategies.\u003c/p\u003e\u003cp\u003eNeurofibromin, encoded by NF1 gene that located at 17q11.2 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e11\u003c/span\u003e], plays a crucial role in regulating cell growth and differentiation by acting as a negative regulator of several signaling pathways [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Neurofibromin consists of 2818 amino acids and contains multiple functional domains, including the protein kinase C (PKC) domain, GTPase-activating protein-related domain (GRD), leucine-rich domain (LRD), C-terminal domain (CTD), and cysteine-rich serine domain (CSRD) [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A growing body of research has investigated the potential associations between specific phenotypes and particular neurofibromin domains. For instance, in a recent study, mutations in the PKC domain have been associated with an increased prevalence of cutaneous neurofibromas (CNF), Lisch nodules, plexiform neurofibromas (PNF), and psychiatric disorders. Mutations in the GRD domain have been linked to an elevated prevalence of Lisch nodules and iris hamartomas. Furthermore, mutations in the Sec14-PH domain have been found to be associated with a higher incidence of CNF [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, these findings represent only a fraction of the potential genotype-phenotype relationships in NF1, and the functional impact of mutations in different neurofibromin domains remains largely unexplored.\u003c/p\u003e\u003cp\u003eThe objective of this study was to investigate whether specific domains of the neurofibromin protein could serve as predictive markers for the clinical phenotypes observed in patients with NF1. To this end, a comprehensive analysis integrating both clinical data and genetic mutation profiles from a well-characterized cohort of NF1 patients was conducted.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Patient Recruitment\u003c/h2\u003e\u003cp\u003eThe present study retrospectively analyszed prospectively collected clinical data from patients diagnosed with NF1 at our institution's Neurofibromatosis Multidisciplinary Team (MDT) clinic between 2024.01.01and 2024.12.31. The diagnosis of NF1 was made according to the established National Institutes of Health (NIH) diagnostic criteria [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e18\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e: 1) Confirmed diagnosis of NF1: Patients must have a definitive diagnosis of NF1 according to the diagnostic criteria established by the National Institutes of Health (NIH). 2) Genetic testing results: Patients must provide clear and detailed NF1 gene mutation testing results, specifying the type of mutation (e.g., point mutation, deletion, insertion) and its exact location. 3) Clinical phenotype data: Patients must have comprehensive clinical phenotype records, encompassing skin manifestations (e.g., caf\u0026eacute;-au-lait spots, neurofibromas), ocular findings (e.g., Lisch nodules), skeletal abnormalities (e.g., scoliosis), and other relevant clinical features. 4) Informed consent: Patients or their legal guardians must sign an informed consent form, agreeing to participate in the study and authorizing the use of their clinical and genetic data.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eExclusion criteria\u003c/strong\u003e\u003cp\u003e1) patients without genetic testing results; 2) The complete basic information of the patients, such as age and gender, was not collected; 3)The complete and specific clinical manifestations of the patients were not available; 4) Patients diagnosed with segmental NF1.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eAll patients included in the study provided written informed consent for the collection and analysis of their clinical and genetic data. The study protocol was approved by the institutional review board in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Clinical Data Collection\u003c/h2\u003e\u003cp\u003eAt the MDT Center, NF1 patients are typically subjected to a set of standardized diagnosis and treatment protocols. Initially, suspected or newly diagnosed patients undergo a comprehensive physical examination, photographic documentation, and multi-site MRI scans (generally including cranial and spinal MRIs, and extremity MRIs if necessary). CT and ultrasound are employed as alternatives when MRI is contraindicated or deemed unsuitable. Furthermore, consultations with specialists in pediatrics, ophthalmology, endocrinology, plastic surgery, and dermatology are arranged.\u003c/p\u003e\u003cp\u003eA comprehensive records were maintained for each patient's clinical manifestations. The following features were specifically recorded:\u003c/p\u003e\u003c/div\u003e\n\n\u003col\u003e\n \u003cli\u003eCaf\u0026eacute;-au-lait macules: The number, size, and location of caf\u0026eacute;-au-lait macules were documented.\u003c/li\u003e\n \u003cli\u003eCutaneous neurofibromas: The number, size, and distribution of cutaneous neurofibromas were noted.\u003c/li\u003e\n \u003cli\u003eSubcutaneous nodular neurofibromas: The number, size, location, and associated symptoms.were recorded.\u003c/li\u003e\n \u003cli\u003ePlexiform neurofibromas: The presence, location, and extent of plexiform neurofibromas were determined through physical examination and, when necessary, imaging studies such as magnetic resonance imaging (MRI).\u003c/li\u003e\n \u003cli\u003eLisch nodules: The presence and number of Lisch nodules were identified by slit - lamp examination of the eyes.\u003c/li\u003e\n \u003cli\u003eSkeletal anomalies: The presence of skeletal abnormalities, such as scoliosis, tibial dysplasia, and sphenoid wing dysplasia, was evaluated through physical examination and radiographic imaging.\u003c/li\u003e\n \u003cli\u003eOptic pathway gliomas: Diagnosis of optic pathway gliomas was based on ophthalmological examination, including visual acuity testing, visual field assessment, and neuroimaging studies (MRI) when indicated.\u003c/li\u003e\n\u003c/ol\u003e\u003cp\u003eOther associated features: Endocrine disorders, such as precocious puberty and short stature, were also recorded, along with any other relevant medical conditions or symptoms.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Genetic Testing\u003c/h2\u003e\u003cp\u003eAll patients underwent genetic testing through whole-exome sequencing or targeted gene sequencing. Genomic DNA was extracted from peripheral blood samples using standard methods. Whole-exome capture was performed using a commercially available kit (e.g., Agilent SureSelect Human All Exon V6), and sequencing was carried out on an Illumina HiSeq platform according to the manufacturer's protocols.\u003c/p\u003e\u003cp\u003ePeripheral blood samples were collected from enrolled patients, and genomic DNA was extracted following the manufacturer\u0026rsquo;s protocol for the QIAGEN DNA extraction kit. The extracted genomic DNA was then subjected to library preparation, indexed, and sequenced on the Illumina NextSeq500 platform. Three sequencing strategies were employed based on the patient\u0026rsquo;s clinical characteristics. For individuals with a family history of NF, targeted panel sequencing was performed using a customized NF panel comprising 57 genes (supplementary tabl\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003ee1\u003c/span\u003e), achieving an average target coverage depth of 2000\u0026times;. Whole-exome sequencing (WES) was conducted for the remaining samples, except for cases where WES had been previously performed without the identification of relevant pathogenic variants, in which case whole-genome sequencing (WGS) was utilized. The obtained sequencing reads were aligned to the human reference genome (GRCh37/hg19) using the Burrows-Wheeler Aligner (BWA) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and variant calling was performed with reference to the NCBI RefSeq database using the Genome Analysis Toolkit (GATK) best pra acid change, and predicted functional impact using ANNOVAR [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Identified variants were annotated following the Human Genome Variation Society (HGVS) nomenclature (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.hgvs.org/mutnomen/\u003c/span\u003e\u003cspan address=\"http://www.hgvs.org/mutnomen/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. All reported variants were further validated by Sanger sequencing. Furthermore, genetic testing was performed on blood samples from the patients' parents using Sanger sequencing. For patients with negative genetic test results, distinct management strategies were implemented based on the specific clinical manifestations: sporadic neurofibroma, segmental neurofibromatosis, or isolated caf\u0026eacute;-au-lait macules. These strategies included surgical intervention, laser treatment, and regular follow-up.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Identification of Affected Functional Domains\u003c/h2\u003e\u003cp\u003eThe neurofibromin domains of the NF1 gene affected by the identified mutations were investigated using publicly available databases and bioinformatics tools. Bioinformatics analysis and NCBI Protein were used to review relevant literature on the functional significance of different domains of the NF1 protein. The domains of interest included the protein kinase C(PKC) domain, cysteine-rich domain(CSRD), tubulin-binding domain (TBD), GTPase-activating protein-related domain (GRD), Sec14-pleckstrin homology (Sec14-PH) domain, and C-terminal domain (CTD) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A subsequent analysis of the genotype-phenotype correlation analysis was performed to determine whether there were any associations between the mutations in specific neurofibromin domains of the NF1 gene and the clinical phenotypes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eCategorical variables were assessed using the corrected chi-square test or Fisher's exact test. For continuous variables, parametric tests (independent samples t-tests) were used for normally distributed data, while non-parametric tests (Mann-Whitney U tests) were employed for data that did not meet the assumption of normality. The threshold for statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Patient Characteristics\u003c/h2\u003e\u003cp\u003eOut of 136 patients seen at the MDT clinic, 62 were excluded based on the following criteria: no genetic testing (n\u0026thinsp;=\u0026thinsp;44), negative genetic test results (n\u0026thinsp;=\u0026thinsp;14), or a diagnosis of NF2 (n\u0026thinsp;=\u0026thinsp;4). Thus, 74 patients were included in the final analysis. The demographic and clinical characteristics of the patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographics of patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal 74\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years),\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale/female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37/37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily history\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 /74(31.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParental\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7/74 (9.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaternal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12/74 (16.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;6 CALMs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73/74 (98.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkinfold freckling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38 /74(51.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35/74(47.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNodular neurofibromas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18/74 (24.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epNF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19/74(25.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLisch nodes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16/74(21.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOPG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5/74 (6.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkeletal abnormalities\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16/74 (21.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFASI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29/74(39.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive dysfunction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17/74 (23.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther NF1 related conditions \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8/74 (10.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eCALMs, Caf\u0026eacute;-au-lait macules; cNF, cutaneous neurofibromas; pNF, plexiform neurofibromas; OPG, optic pathway glioma FASI: Focal Areas of Signal Intensity;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003ea, including 10 patients with scoliosis, 2 patients with fibular dysplasia, 1 patient with tibial pseudarthrosis,and 3 patients with sphenoid wing dysplasia.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eb, including 1 patient with renal artery stenosis, 2 patients with sexual development delay, 4 patients with short stature and 1 patient with epilepsy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe average age of the participants was 13.8 years, and 50% (37 out of 74) were male. Additionally, 98.6% (73/74) had six or more caf\u0026eacute;-au-lait macules, 47.2% (35/74) had cutaneous neurofibromas, and 25.6% (19/74) had plexiform neurofibromas. Lisch nodules were present in 21.6% (16/74) of patients, and skeletal abnormalities in 16/74 (21.6%).(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 NF1 Gene variations\u003c/h2\u003e\u003cp\u003eThe NF1 gene exhibited a range of variations, including nonsense/missense mutations, frameshift mutations, copy number variations, deletions, insertions, and splicing mutations. Among these, 14.9% were missense mutations, 2.7% were in-frame deletion, 35.1% were nonsense mutations, 31.1% were frameshift mutations, 6.7% were copy number mutations, and 9.46% were splicing mutations. The distribution of variations across the various neurofibromin domains of the NF1 gene is depicted in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The PKC domain was involved in 11 cases (14.9%), the CSRD domain in 26 cases (35.1%), the TBD domain in 25 cases (33.7%),the GRD domain in 34 cases (45.9%), the Sec14-PH domain in 37 cases (50%), and the CTD domain in 55 cases (74.3%). Notably, 24 variations identified in this cohort were not reported previously, as detailed in supplementary table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of variation types and frequencies of involved domains in patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (%, N\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariation Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissense\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (14.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIn-frame deletion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNonsense\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (35.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrameshift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCopy number variation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSplicing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (9.46%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDomains involved\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePKC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (14.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCSRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (35.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(33.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (45.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSec14-PH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (50%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55(74.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUnreported mutations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24(32.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea\u003c/sup\u003e including a patient with c.7970\u0026thinsp;+\u0026thinsp;6T\u0026thinsp;\u0026gt;\u0026thinsp;G.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelationship between subcutanious nodular NF and domains\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNone (n\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003enodular NF(n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePKC, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCSRD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26 (39.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGRD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34 (51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.635\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSec14.PH, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37 (56.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (53.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (64.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55 (83.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (80.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (92.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.433\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25 (37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.292\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Genotype-Phenotype Correlation Analysis\u003c/h2\u003e\u003cp\u003eOur findings indicated that patients with PKC domain variants (54.5%) exhibit a significantly higher incidence of nodular neurofibromas compared to patients without PKC variants (19%), with a p-value of 0.008. Statistical analysis revealed no significant differences in phenotype across multiple domains (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). No significant difference was found between patients harboring variations in different neurofibromin domains of the NF1 gene in terms of the presence or severity of caf\u0026eacute;- au-lait macules, neurofibromas, Lisch nodules, skeletal abnormalities, or endocrine disorders. Additionally, no significant difference was observed between patients with multiple domain involvements, regardless of the number of domains affected, and those with single domain involvement (Supplementary Table\u0026nbsp;3\u0026ndash;5).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results of this study indicate that predicting the type and severity of the phenotype based on NF1 neurofibromin domains remains challenging. Despite identifying various mutations in different neurofibromin domains and documenting a wide range of clinical phenotypes, we did not find significant associations between specific domains and phenotypic outcomes, with the exception of a higher incidence of nodular neurofibromas in patients with PKC domain variants (54.5% vs. 19%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008).\u003c/p\u003e\u003cp\u003eRecent advances in NF1 research, such as the identification of specific genotype-phenotype associations (e.g., p.Met992del, p.Arg1809Cys, NF1 microdeletions, and mutations in codons 844\u0026ndash;848) [7\u0026ndash;10]. In our study, there were two patients with microdeletions, one of which had more caf\u0026eacute;-au-lati spots and tumor volume, and the other patient showed cognitive dysfunction and language impairment, which was consistent with the increase in tumor volume and cognitive prevalence in patients with microdeletions reported in previous studies.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e6\u003c/span\u003e]However, our research did not identify any patients with the p.Met992del, p.Arg1809Cys gene mutation or mutations in codons 844\u0026ndash;848.\u003c/p\u003e\u003cp\u003ePrevious studies have indicated that 10\u0026ndash;15% of patients could benefit from findings of genotype-phenotype correlation studies. However, only 2.7% of patients in our study harbored the aforementioned variations, suggesting limited clinical value for these correlations in clinical management. In the context of neurofibromin domains, previous studies on genotype-phenotype correlations have yielded equivocal results. Some studies have reported associations between specific mutations or neurofibromin domains and certain phenotypes. For instance, mutations in the GRD domain have been suggested to be associated with a higher risk of developing malignant peripheral nerve sheath tumors [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Zhu et al. reported that variations affecting the PKC domain, the CSRD domain, the GRD involvement and the Sec14-PH domain have found to be associated with different clinical manifestations in a Chinese cohort. Our findings regarding the PKC domain, were consistent with previous research [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which indicated that variations affecting the PKC domain were associated with elevated rates of cNF (100% vs. 64.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Lisch nodules (100% vs. 61.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), pNF (100% vs. 95.7%, p\u0026thinsp;=\u0026thinsp;0.009), and psychiatric disorders (11.8%vs. 1.6%, p\u0026thinsp;=\u0026thinsp;0.042). Nevertheless, the present study did not reveal any significant associations between other domains and the clinical symptoms under investigation. Neurofibromas can be classified into cutaneous and plexiform types. However, recent studies had indicated that nodular neurofibromas showed distinct features comparing to typical plexiform neurofibromas [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. We analyzed this subtype separately due to their unique distribution patterns, pathological characteristics, and higher risk of malignant transformation compared to typical plexiform neurofibromas. Special attention should be paid to nodular neurofibromas if their annual growth exceeds 20 mm or if they are associated with pain, as these features may suggest a potential risk of malignancy..[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe observed discrepancies in results between studies may be attributed to several factors, including differences in patient selection criteria, sample size, and the methodologies employed for genetic analysis and phenotype assessment. Furthermore, the inherent biological complexity of NF1 pathogenesis, involving multiple protein functions and domain interactions, complicates the establishment of clear genotype-phenotype associations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Adding to this complexity are the significant roles of modifier genes and environmental factors in shaping NF1 phenotypes [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These factors are thought to contribute significantly to the observed phenotypic variability, even within families.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e30\u003c/span\u003e] Studies have identified candidate modifiers like GAS1 and SPRED2 for pNF and scNF, based on evidence that their inactivation specifically affected NF1-mutant Schwann cell growth.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe lack of reliable genotype-phenotype correlations in NF1 has important clinical implications. Currently, clinicians cannot rely on genetic information to predict disease course or the development of specific complications. Close clinical monitoring of patients remains essential, regardless of the genetic variation identified. Regular follow-up visits, including physical examinations, ophthalmologic evaluations, and imaging evaluations, are essential to detect new manifestations or progression of existing conditions. Despite the limitations of current knowledge regarding genotype-phenotype correlations, genetic counseling is still warranted for patients and their families to discuss the inheritance pattern of NF1 and the potential risks of complications.\u003c/p\u003e\u003cp\u003eFrom a treatment perspective, the inability to precisely predict phenotypes based on genotypes necessitates a focus on managing the existing clinical manifestations. This can, in certain instances, such as when patients demonstrate noncompliance with scheduled follow-ups, lead to challenging clinical scenarios for healthcare providers, often imposing a substantial physical and psychological strain on the patient, thereby significantly impacting their quality of life. An example of this predicament is the case of large plexiform neurofibromas, which may result in extensive infiltration of surrounding tissue if left untreated, potentially rendering the tumor inoperable and causing severe functional impairment. However, ongoing research into the pathogenesis of NF1 may lead to the development of genotype-based targeted therapies in the future [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study acknowledges several limitations that warrant consideration. Firstly, while our sample size of 74 patients represents a relatively robust cohort in comparison to some prior studies, it may yet prove inadequate for discerning nuanced genotype-phenotype associations. Secondly, the present study focused on a limited number of neurofibromin domains of the NF1 gene. It is plausible that unexamined domains or gene regions may harbor associations with particular phenotypes. Thirdly, it should be noted that some of the patients in the study did not undergo whole-body MRI. The genetic testing method is relatively rudimentary. Finally, environmental factors were not considered in the present analysis. It is possible that environmental exposures, such as diet, radiation, or toxins, could interact with the NF1 gene variations and influence the clinical manifestations of the disease [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e28\u003c/span\u003e]Therefore, larger-scale, multicenter studies involving diverse patient populations are needed to better understand these complex relationships.Novel technologies such as single-molecule real-time sequencing and gene editing offer promising approaches for more comprehensive identification and analysis of NF1 gene regions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e33\u003c/span\u003e].And future research should incorporate environmental factors and explore new areas such as gut microbiota, which may influence NF1 phenotypes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e26\u003c/span\u003e]..Notwithstanding certain limitations, this study provides insights into the potential association between mutations in the NF1 gene and clinical manifestation. To further validate these preliminary findings and deepen the understanding of NF1 genotype-phenotypic associations, future studies need to incorporate larger prospective cohorts that include complete clinical information and detailed genetic data.\u003c/p\u003e\u003cp\u003eIn Conclusion, the present study demonstrates that predicting the range and severity of the phenotype based on NF1 neurofibromin domains remains challenging. The relationship between these domains and phenotypic outcomes is not well established.\u003c/p\u003e"},{"header":"Declarations","content":"\u003col\u003e\n \u003cli\u003eEthics approval and consent to participate：we have already uploaded the ethical documents.\u003c/li\u003e\n \u003cli\u003eConsent for publication：we have already uploaded the consent form.\u003c/li\u003e\n \u003cli\u003eAvailability of data and materials: Not applicable.\u003c/li\u003e\n \u003cli\u003eCompeting interests: The authors declare that they have no competing interests.\u003c/li\u003e\n \u003cli\u003eFunding：There are no other sources of funds.\u003c/li\u003e\n \u003cli\u003eAuthors\u0026apos; contributions：All authors read and approved the final manuscript.\u003c/li\u003e\n \u003cli\u003eAcknowledgements：Not applicable.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMo J, Moye SL, McKay RM, Le LQ. 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Clinical and Sonographic Classification of Neurofibromas in Children with Neurofibromatosis Type 1 - A Cluster Analysis. Klinische und sonografische Klassifikation von Neurofibromen bei Kindern mit Neurofibromatosis Type 1 \u0026ndash; eine Clusteranalyse. Ultraschall Med. 2023;44(2):e118-e125. doi:10.1055/a-1640-9621\u003c/li\u003e\n\u003cli\u003eZhang, H., et al. (2023). The Potential Link between Gut Microbiota and Neurofibromatosis Type 1 Phenotypes. Microbiome, 11(1), 150.\u003c/li\u003e\n\u003cli\u003eBarron VA, Lou H. Alternative splicing of the neurofibromatosis type I pre-mRNA. Biosci Rep. 2012;32(2):131-138. doi:10.1042/BSR20110060？\u003c/li\u003e\n\u003cli\u003eGreen, S. L., et al. (2021). Environmental Influences on NF1 Phenotype: A Review of Current Evidence. Environmental Health Perspectives, 129(5), 057002.\u003c/li\u003e\n\u003cli\u003ePasmant E, Vidaud M, Vidaud D, Wolkenstein P. Neurofibromatosis type 1: from genotype to phenotype. J Med Genet. 2012;49(8):483-489. doi:10.1136/jmedgenet-2012-100978\u003c/li\u003e\n\u003cli\u003ePacot L, Sabbagh A, Sohier P, Hadjadj D, Ye M, Boland-Auge A, Bacq-Daian D, Laurendeau I, Briand-Suleau A, Deleuze JF, Margueron R, Vidaud M, Ferkal S, Parfait B, Vidaud D; NF-France Network; Pasmant E, Wolkenstein P. Identification of potential common genetic modifiers of neurofibromas: a genome-wide association study in 1333 patients with neurofibromatosis type 1. Br J Dermatol. 2024 Jan 23;190(2):226-243. doi: 10.1093/bjd/ljad390. PMID: 37831592.\u003c/li\u003e\n\u003cli\u003eStaedtke V, Anstett K, Bedwell D, et al. Gene-targeted therapy for neurofibromatosis and schwannomatosis: The path to clinical trials. Clin Trials. 2024;21(1):51-66. doi:10.1177/17407745231207970\u003c/li\u003e\n\u003cli\u003eChen, Y., et al. (2022). Novel Sequencing and Gene Editing Techniques for Unraveling NF1 Gene Function. Genome Research, 32(6), 1135 - 1147.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Neurofibromatosis type 1, NF1 gene, neurofibromin domains, Genotype - phenotype correlation","lastPublishedDoi":"10.21203/rs.3.rs-7008119/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7008119/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e Neurofibromatosis type 1 (NF1), caused by mutations in the \u003cem\u003eNF1\u003c/em\u003e gene, exhibits significant clinical heterogeneity. Recent studies have identified potential correlations between specific phenotypes and neurofibromin domains of the mutated \u003cem\u003eNF1\u003c/em\u003e gene; however, research into these specific associations remains limited.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e This study aimed to investigate the correlation between clinical phenotypes and specific neurofibromin domains in a prospectively characterized cohort of NF1 patients..\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e Clinical data from patients diagnosed with NF1 at our institution's Neurofibromatosis Multidisciplinary Team (MDT) clinic were prospectively collected. Clinical manifestations including caf\u0026eacute;-au-lait macules, freckles, cutaneous neurofibromas, plexiform neurofibromas, Lisch nodules, skeletal abnormalities, optic pathway gliomas, and other associated lesions were documented comprehensively. All patients underwent genetic testing through whole exome sequencing or multiple-gene panel test. The neurofibromin domains affected by the identified mutations were investigated. Genotype-phenotype correlation analysis was performed, with particular focus on the neurofibromin domains affected by mutations in the NF1 gene.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e A total of 74 patients were included in the study. The average age was 13.8 years old, and 50% (37/74) were male. Additionally, 98.6%(73/74) of the patients had six or more caf\u0026eacute;-au-lait macules, 47.2%(35/74) had cutaneous neurofibromas, and 25.6% (19/74) had plexiform neurofibromas. Lisch nodules were present in 21.6% (16/74) of patients, skeletal abnormalities in 21.6% (16/74). Subcutanious nodular neurofibroma were found in (18/74 ). The NF1 gene exhibited various mutation type, including missense variation, in-frame deletion, nonsense variation, frameshift mutation, copy number variation, and splicing variation. Specifically, variations affecting protein Kinase C (PKC) domain were observed in 11 cases (14.9%), cysteine-Rich Domain(CSRD) in 26 cases (35.1%), tuberin Binding Domain(TBD) domain in 25 cases (33.7%) ,GTPase-activating protein related domain (GRD) in 34 cases (45.9%), Sec14-PH domain in 37 cases (50%), and C-terminal domain (CTD) domain in 55 cases (74.3%). Statistical analysis revealed no significant differences in phenotype across multiple domains (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), except for a higher incidence of nodular neurofibromas in patients with PKC domain variants (p\u0026thinsp;=\u0026thinsp;0.008). The cumulative number of involving domains did not predict the severity of clinical symptoms.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e Despite comprehensive analysis, predicting the full range and severity of NF1 phenotypes based solely on neurofibromin domains remains challenging. Our finding of an association between PKC domain variants and nodular neurofibromas highlights the potential for domain-specific correlations with particular phenotypic features, warranting further investigation in larger cohorts to refine genotype-phenotype relationships and improve clinical prognostication.\u003c/p\u003e","manuscriptTitle":"Genotypic Variability in Neurofibromin Domains to Predict Phenotypic Outcomes of Neurofibromatosis type 1: Evidence from a Prospective Clinical-Genetic Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 10:46:14","doi":"10.21203/rs.3.rs-7008119/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvited","content":"Orphanet Journal of Rare Diseases","date":"2025-12-06T14:16:37+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-04T20:43:44+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-29T20:23:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-21T05:20:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2025-07-20T07:21:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"27b9ec97-fc75-406e-af18-cabb49daa0bf","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-04T10:46:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-04 10:46:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7008119","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7008119","identity":"rs-7008119","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}