A novel FAM111A frameshift variant associated with osteoclast necroptosis and KCS2-like syndrome

A novel FAM111A frameshift variant associated with osteoclast necroptosis and KCS2-like syndrome | 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 A novel FAM111A frameshift variant associated with osteoclast necroptosis and KCS2-like syndrome Ping Wu, Xue Li, Li Peng, Yanlan Zhong, Kexin Chen, Suyun Cheng, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7188681/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Kenny-Caffey syndrome type II (KCS2) is a rare genetic disorder characterized by skeletal abnormalities, impaired growth, and developmental delay. This study investigates a novel heterozygous FAM111A variant’s role in a patient presenting with KCS2-like features. Methods : An 11-year-old patient with clinical features consistent with KCS2-like syndrome underwent whole exome sequencing, which identified a novel heterozygous variant in FAM111A gene. In vitro experiments and protein structure analysis were performed to elucidate the contribution of this mutation to KCS2-like syndrome. Results : To confirm the diagnosis, whole exome sequencing revealed a novel heterozygous variant (c.405delA/p.E136Sfs*3) in FAM111A gene in an 11-year-oldpatient. Additionally, we found the clinical features of this patient were consistent with KCS2-like syndrome. Our in vitro studies revealed that the variant led to a significant increase in necroptosis of osteoclasts. Furthermore, variant osteoclasts displayed a significant down-regulation of autophagy, which may contribute to the onset of KCS2-like syndrome. Consequently, the augmented necroptosis may result in the up-regulation of inflammatory cytokines such as IL-1β, IL-17, IL-12p70, MCP-1, IFN-γ and TNF-α. Protein structure analysis suggests that the truncated FAM111A (p.E136Sfs*3) retains a ubiquitin-like domain, which might explain the up-regulated ubiquitination in variant osteoclasts. Therefore, the enhanced ubiquitination in variant osteoclasts may lead to the excessive degradation of intracellular proteins, resulting in irreversible necroptosis. Conclusions : Our findings suggest that the novel variant FAM111A (c.405delA) may be a pathogenic factor in KCS2-like syndrome, likely through mechanisms involving increased necroptosis and inflammation. This expands understanding of FAM111A variant’s role in skeletal and immune dysregulation. FAM111A Kenny-Caffey syndrome type II Osteoclast Necroptosis Autophagy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Kenny-Caffey syndrome (KCS) is a rare genetic disorder characterized by features such as short stature, hypoparathyroidism, skeletal defects, and ocular abnormalities [1] The syndrome was first described in 1966 by Kenny et al. , who reported a case involving a mother and her son presenting with hypocalcemia, hyperphosphatemia, cortical thickening of tubular bones, and medullary cavity stenosis [2]. Subsequently, in 1967, Caffey et al . provided a detailed description of these features in the same family, leading to the syndrome being named Kenny-Caffey syndrome [3]. The underlying molecular causes of KCS have been attributed to pathogenic variants in either the tubulin-specific chaperone E gene (TBCE) [KCS type I/ KCS1, Online Mendelian Inheritance in Man (OMIM) #244460] or the family with sequence similarity 111 member A gene (FAM111A, HGNC: 24725) (KCS type II/ KCS2, OMIM #127000) [4-5]. TBCE is involved in microtubule dynamics [6-8], whereas FAM111A plays a role in DNA replication and viral defense [9-13]. KCS1 is associated with mental retardation, microcephaly, and mental hypoplasia, and is inherited in an autosomal recessive manner. In contrast, KCS2 is characterized by the absence of mental retardation and mental hypoplasia, and the variant is inherited in an autosomal dominant or sporadic manner [14]. Compared with KCS1, KCS2 is rarer, with only a dozen cases reported worldwide. In 2013, through the exome sequencing of 5 KCS patients, FAM111A was identified as the pathogenic gene of KCS2 [5]. FAM111A is located in chromosomal 11q12.1 and encodes a protein consisting of 611 amino acids [14]. Current studies have shown that amino acid residues 336-661 of FAM111A encompass a trypopalinase-like serine peptidase domain, including a catalytic triad composed of histidine, aspartate and serine residues [13]. Here, we present a case of child patient with clinical features consistent with KCS2-like syndrome, which was confirmed through exome sequencing, revealing a novel heterozygous variant in the FAM111A gene (c.405delA). The variant c.405delA (p.E136Sfs*3) of FAM111A gene in this child is de novo , while both his parents have normal genotypes. So far, this variant has not been reported in and outside of Chinese population in the reference gene database (Genome Aggregation Database) (https://gnomad.broadinstitute.org/ gene/ENSG00000110719?dataset=gnomad_r2_1). The absence of variant in gnomAD (v2.1.1), the Human Gene Mutation Database, the Online Mendelian Inheritance in Man (OMIM), the Genetic and Rare Diseases Information Center (GARD) and several other rare disease databases reveals its rarity. Although the disease's genetic basis has been linked to variants in the FAM111A gene, the specific pathways through which these genetic alterations contribute to the observed clinical phenotype remain incompletely understood. This study aims to discover the complex relations between clinical features of the child patient with KCS2-like syndrome and FAM111A (c.405delA; p.E136Sfs*3) novel variant through cellular and molecular mechanisms. We hypothesize that decreased autophagy and increased necrosis of osteoclasts induced by FAM111A gene variant may be related to the short stature and increased inflammatory response in patients. These findings highlight the potential physiological effects of the FAM111A variant and provide insight into the underlying mechanisms that may be contributing to the patient's condition. Further research into the specific pathways affected by the variant could help in developing targeted treatments for individuals with similar genetic variants. Materials and Methods Plasmids and transfection Human FAM111A cDNA was amplified by reverse transcription PCR and cloned into pcDNA3.1 plasmid. The FAM111A c.405delA variant was generated by site-directed deletion of adenine at position 405 and verified by Sanger sequencing. For expression of FAM111A c.405delA with a N-terminal Flag tag, the FAM111A c.405delA open reading frame sequence was cloned into pLVX3-3×Flag-blast for lentiviral expression in mouse Raw264.7 cells. The small-guide RNA (sgRNA) was designed using the CRISPR Design Tool (http://chopchop.cbu.uib.no/) to minimize potential off-target effects. The sgRNA sequences were cloned into a lentiCRISPR-V2 vector (Addgene) to knockout the mouse FAM111A gene (FAM111A KO ). The pLVX3-3×Flag-FAM111A c.405delA -blast and lentiCRISPR-V2-FAM111A KO -sgRNA plasmids were introduced by liposomal transfection reagent (#40802ES03, Yeasen), respectively, according to manufacturer’s recommendation. The knockout and variant efficiency of FAM111A was confirmed by immunoblotting. The sgRNA sequences targeting FAM111A was purchased from Sangon (Shanghai, China) as follows: FAM111A sgRNA: 5’-CCCGTCTGCTGTATACCAGA-3’. Cell culture Murine calvarial cell line MC3T3-E1, murine monocyte macrophage leukemia cell line Raw264.7 and Human embryonic kidney cell line (HEK) 293T were obtained from American Type Culture Collection (ATCC), and cultured in Dulbecco's Modified Eagle Medium (DMEM, #10-013-CVR, Corning) supplemented with 10% fetal bovine serum (FBS, #1099-141, Gibco). The lentivirus of FAM111A c.405delA and FAM111A KO were packaged in 293T cells, and purified and concentrated after 2 days. Then, the viruses were harvested to infect Raw264.7 cells, which were selected by blasticidin (#ST018, Beyotime) and puromycin (#P9620, Sigma-Aldrich), respectively, to obtain stable expressing cell lines. After culturing with 100 ng/ml Phorbol-12-myristate-13-acetate (PMA, #P1585, Sigma-Aldrich) for 3 days, the cells were induced to differentiate into macrophages, followed by the addition with 100 ng/ml receptor activator of nuclear factor Kappa-Β ligand (RANKL, #95625ES25, Yeasen) for 5 days to induce the differentiation into osteoclasts. The osteoclast was confirmed by tartrate-resistant acid phosphatase (Trap, #G1050, Lifescience) assay. The autophagy activity of osteoclast was activated by Torin 1 (#T6045, TargetMol Chemicals Inc.), and inhibited by chloroquine phosphate (CQ, #PHR1258, Sigma-Aldrich). The osteoid was confirmed by 0.1% Alizarin Red (#A600144, Sangon Biotech) staining. The bone slides were purchased from (#2-0001-10, Guangzhou Zhuanyan Biotechnology Co., Ltd.). The released Ca 2+ in the supernatant of osteoclast incubated with bone slide was detected by Calcium Colorimetric Assay Kit (#S1063S, Beyotime). Flow cytometry For analysis of cell apoptosis, the osteoclasts were stained with cell apoptosis reagent (propidium iodide and allophycocyanin conjugated Annexin V) following the reagent instruction (#A6030M, UELandy). Flow cytometry analysis was performed on the CytoFLEX Flow Cytometer (Beckman Coulter) using FlowJo software (v10, Tree Star software, Inc.). Representative dotplots were shown from three independent experiments. Lysosome fluorescence qualification The number of intracellular lysosomes was quantitated using Lyso-Tracker reagent (#DND99, Yeasen) through fluorescence qualification. Fluorescence images were acquired by Leica microscopy and analyzed by Leica Application Suite Advanced Fluorescence software (LAS AF, Version 4.2). Representative fluorescence images were shown from three independent experiments. Multiplex Inflammatory cytokines assay Inflammatory cytokines including G-CSF, IFN-γ, IL-10, IL-12p70, IL-17, IL-1β, IL-2, IL-23p19, IL-4, IL-6, KC, MCP-1 and TNF-α were detected using RayPlex ® Mouse Inflammation Array Kit 1 (#FAM-INF-1-48, Ray Biotech). The supernatant of osteoclast from each group was collected to measure the secreted inflammatory cytokines by the CytoFLEX Flow Cytometer (Beckman Coulter) according to the kit instruction. The supernatants were measured from three independent repeats. Immunoblotting analysis Cells were lysed in NP-40 lysis buffer (50 mM Tris-HCl pH 7.4, 150 mM NaCl, 0.1% Nonidet P-40, 5mM EDTA, 50mM NaF, 1mM Na 3 VO 4 , 10% Glycerol) supplemented with protease inhibitor mix (#BL630B, Biosharp). For Western blotting, lysates containing 30 μg of protein were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), transferred to polyvinylidene fluoride membranes, and probed with specific antibodies. First antibodies used for Western blotting: rabbit anti-FAM111A (Abcam, ab184572, 1:1000); mouse anti-GAPDH-Horseradish peroxidase (HRP) (1:5000) (#HRP-60004, Proteintech Group); mouse anti-Flag (1:1000) (K200001M, Solarbio); mouse anti-phospho (p)-MLKL (1:1000) (#ab196436, Abcam) and MLKL (1:1000) (#ab243142, Abcam); rabbit anti-p-JNK1/2/3 (Thr183+Tyr185) (1:1000) (#AF3318, Affinity Biosciences) and anti-JNK1/2/3 (1:1000) (#AF6318, Affinity Biosciences); anti-ubiquitin (#10201-2-AP, Proteintech Group); Anti-SQSTM1/p62 (#5114S, Cell signaling); anti-LC3BII (#14600-1-AP, Proteintech Group). After incubation with the above antibodies, following by the incubation with HRP-conjugated secondary antibodies (1:5000) (#K1223, #K1221, APExBIO). Blots were imaged using ChemiDoc MP (Bio-Rad) and analyzed using the Image Lab software (v5.2, Bio-Rad). Protein structure analysis The predicted protein structure of human FAM111A (AlphaFold Protein Structure Database: AF-Q96PZ2-F1) and mouse FAM111A (AF-Q9D2L9-F1), FAM111A c.405delA and ubiquitin (PDB code: 1Q5W) was determined by the PyMOL Molecular Graphics System software (v2.5.2, Schrodinger, Inc.). The conservation of FAM111A protein between human and mouse was also studied, and alignment results were displayed using ESPript (https://espript.ibcp.fr/ESPript/cgi-bin/ESPript.cgi). Statistical analysis Data are expressed as mean ± standard deviation (SD). Analysis was done using Graphpad Prism v8 (San Diego, CA, USA). For statistical analysis of three groups, the assumption of equal variances was tested using the Brown-Forsythe test and normality was tested using the Shapiro-Wilk test. For two groups, the assumption of equal variances was tested using an F test. If assumptions were not met, data was first logarithmically transformed to achieve equal normality. Then, for three groups one-way ANOVA was used to test for differences in the data, followed by a Tukey’s multiple comparison test in case the null hypothesis was rejected. In the case of two groups, an unpaired Student’s-test was used. Differences with a p value of < 0.05 were considered statistically significant (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001). Results Case presentation and discovery of the FAM111A variant The patient, an 11-year-old male child with KCS2-like syndrome, presented at the outpatient department of Guangzhou Women and Children's Medical Center, with a history of recurrent hyperspasmia lasting over 10 years. The first episode of hyperspasmia occurred in 2014. These hyperspasmia are typically associated with fever, and to date, the patient has experienced a total of 9 such episodes (Figure. 1A-D). Additionally, multiple instances of abnormal electroencephalogram (EEG) readings prompted a diagnosis of epilepsy in 2016 (Figure 1E). At the same time, the child's height and body weight are either below or at the lower limit of the standard development curve (Figure 1F). And so far, he is still short in stature. His sitting height (SH=79 cm), leg length (LL=74 cm), and SH/LL ratio (1.06) are fallen below the 50th percentiles of body proportions for Chinese boys minus 1SD [15]. Meanwhile, a hand X-ray taken at age 13 showed significant abnormalities in bone mass (Figure 1G), such as tubular cortical thickening and medullary cavity stenosis, which may closely relate to the abnormalities in bone metabolism indicators like alkaline phosphatase in supplemental table 1 (Table S1). The other clinical characteristics of this patient including blood diagnostics, biochemical detection index, immune-related index and cytokines were shown in Table S2-4. At the age of 10, a comprehensive exome sequencing was performed on the patient’s family including his parents and younger sister. The results indicated that both parents and younger sister showed no variations (Figure 2B). In contrast, a de novo variant in the FAM111A gene, specifically c.405delA (p.E136Sfs*3), was identified in the child (Figure 2A). This variant involves the deletion of an adenine nucleotide (A) at position 405 of the FAM111A gene verified by Sanger sequencing, resulting in premature termination of gene translation of the third amino acid after the variant site (Figure 2C). When compared the variant genes between the patient and his sister, there are 18 shared genes (Figure 2D). However, the FAM111A gene is out of these. To further find the association between the FAM111A gene variant c.405delA (p.E136Sfs*3) and KCS2-like syndrome, several explorations were conducted in vitro . Unaffected differentiation function of osteoblast and osteoclast but impeded osteolytic ability Different from previous reports [14], we found that the function of osteoblasts were completely normal in KCS2-like syndrome patients. In the in vitro study, we also did not observe any impaired osteoblast (MC3T3-E1) differentiation and observed normal induced osteoid (Figure 3A-B). Interestingly, the differentiation functions of osteoclasts induced from Raw264.7 cells (FAM111A c.405delA and FAM111A KO ) were not affected (Figure 3C-D). Although the differentiation functions of osteoblasts and osteoclasts were unaffected, the etiology of the patient's clinical features remained uncertain. But the Ca 2+ in the supernatant of variant osteoclasts and knockout FAM111A (FAM111A KO ) osteoclasts incubated with bone slides were reduced significantly (Figure 3E). It is implied that the ostolystic ability of osteoclasts may impede. Increased necroptosis of variant osteoclasts may contribute to KCS2-like syndrome To further investigate the etiology, we found an increased percentage of necroptosis (Figure 4A-C) and upregulated necrotic pathway signals like p-MLKL and p-JNK (Figure 4D-E), which may contribute to the short stature phenotype of the patient, leading to the enhanced inflammatory responses and manifesting as recurrent fever and hyperspasmia. Therefore, we have detected the levels of inflammatory cytokines secreted from osteoclasts of each group. The results of multiplex cytokines assay suggest that the up-regulation of cytokines such as MCP-1, TNF-α, IL-1β, IFN-γ, IL-17 and IL-12p70 in the variant osteoclasts (FAM111A c.405delA ) exhibited a higher degree of inflammation compared to the wild type (WT) controls (Figure 4F). This elevated inflammatory state might influence bone remodeling and resorption processes. However, what factors lead to the enhanced necroptosis of osteoclasts (FAM111A c.405delA )? Decreased autophagy activity of variant osteoclasts may lead to the enhanced necroptosis Due to the function of osteoclasts is related to the lysosome, we have stained the intracellular lysosome across different osteoclasts. Obviously, a decreased number of lysosomes in variant osteoclasts (FAM111A c.405delA ) were found, when compared to the WT and FAM111A KO groups (Figure 5A-B). More importantly, the lysosomes often fused with autophagosomes to become autolysosomes to degenerate proteins. Since the LC3BII and p62 are two canonical markers of autophagy pathway, the relative expression patterns of these proteins provide insights into the autophagy activity in osteoclasts. The results of immunoblotting showed that the expression levels of LC3BII and p62 underwent significant changes across different treated groups (Figure 5C-E). The expression level of LC3BII appears to be lower in variant osteoclasts (FAM111A c.405delA ), rather than FAM111A KO osteoclasts (Figure 5D). Oppositely, the expression level of p62 appears to be higher (Figure 5E). The alterations in LC3BII and p62 expression may indicate reduced autophagy activity in variant osteoclasts (FAM111A c.405delA ), potentially disrupting protein degradation and ultimately leading to increased necroptosis. A possible insight for the protein variant In the Figure 6, it appears to contain information about the gene domain and three dimensions (3D) structure, and evolutionary conservation patterns of its coded proteins including human FAM111A and FAM111A (p.E136Sfs*3) as well as mouse FAM111A. Comparing on the gene domain features of FAM111A and FAM111A c.405delA , FAM111A c.405delA represents a variant of FAM111A with a deletion of adenine at position 405 (c.405delA) leading to a frameshift and premature termination at position 138 (p.E136Sfs*3) (Figure 6A). This variant likely resulted in a truncated FAM111A protein. Through protein structure analysis, the predicted 3D structures of the FAM111A protein and truncated FAM111A (p.E136Sfs*3) protein could provide insights into the potential functional and structural changes. The incomplete protein structure possibly affected its function. Notably, the truncated FAM111A (p.E136Sfs*3) protein exhibits structural homology with ubiquitin [root mean square deviation (RMSD) = 3.066, represented a structural deviation between ubiquitin and the truncated FAM111A (p.E136Sfs*3) protein], suggesting that the FAM111A c.405delA variant can lead to a compensative function of ubiquitination (Figure 6B), thereby enhancing necroptosis. The functional domain truncation in the FAM111A c.405delA variant likely disrupts native protein interactions while potentially acquiring novel ubiquitin-like functions that drive pathological mechanisms. In line with these structural and functional insights, cross-species conservation analysis reveals 57.36% sequence identity in functional domains between human and mouse FAM111A (Figure 6C), further underscoring the importance of these conserved regions in maintaining structural integrity and biological function. Discussion This case study offers a unique insight into the clinical and molecular features of KCS2-like syndrome, especially regarding a novel de novo heterozygous variant in the FAM111A gene (c.405delA; p.E136Sfs*3) identifiedin the patient. This is a notable finding considering that the variant has not been reported in the Genome Aggregation Database or observed outside the Chinese population, thereby emphasizing its significance as a potential pathogenic factor in KCS2-like syndrome [16]. The presentation of recurrent hyperspasmia in the patient, along with a familial history of this condition, accentuates the complexity of the clinical manifestations associated with KCS2 and the significance of exploring its genetic underpinnings. Additionally, the detection of abnormal EEG readings prompts an epilepsy diagnosis highlighting the neurological implications linked to KCS2-like syndrome [17-18]. However, the detail mechanism on the correlation between recurrent hyperspasmia and this novel variant in FAM111A gene still needs further investigation. While our study identifies a novel FAM111A variant in a single patient, larger cohorts are needed to confirm its pathogenicity. Collaborative efforts to collect additional KCS2-like cases are underway. Furthermore, the patient's short stature and aberrant bone mass, as evidenced by hand X-ray imaging, underscore further osteodysplasia associated with the syndrome [19-20]. Using in vitro investigations, we observed unaffected osteoblastic and osteoclastic differentiation, suggesting that the bone development and osteoblastic functions were seemingly normal [21-22]. Therefore, the imbalance of bone metabolism may be caused by abnormal function of osteoclasts. The graphical abstract of the possible mechanism model is illustrated in Figure 7. However, this assumption needs further investigation. As we known, autophagy and necroptosis are two important cellular processes that play a crucial role in maintaining cellular homeostasis [23-24]. Autophagy is a catabolic process that involves the degradation of damaged organelles, misfolded proteins, and other cellular components in lysosomes [25]. This process helps to maintain cellular homeostasis by removing potentially harmful cellular components and providing energy and nutrients during periods of cellular stress [26-27]. Necroptosis, on the other hand, is a programmed form of necrosis that is triggered by various cellular stressors, such as infection, inflammation, and DNA damage [28]. It is characterized by the release of cellular contents, inflammation, and cell death [28-29]. While autophagy and necroptosis are distinct cellular processes, they are closely interconnected. Autophagy can inhibit necroptosis by removing damaged organelles and cellular components that can trigger necroptosis [23, 30]. Delving deeper, we uncovered a notable increase in necroptosis and an associated up-regulation of necrotic pathway signals in the variant osteoclasts. These findings provide a potential mechanistic link between the patient's short stature and the elevated inflammatory responses, underscoring the potential possibility of physiological ramifications by the FAM111A variant [31-32]. Moreover, our studies revealed a downregulated autophagy activity in the variant osteoclasts, potentially triggering a disruption in protein degradation, which may culminate in enhanced necroptosis. These molecular insights offer a plausible explanation for the observed clinical manifestations, which may contribute to the development of KCS2-like syndrome. Besides, autophagy is critical for maintaining osteoclast function by regulating lysosomal activity and protein degradation. Reduced autophagy in variant osteoclasts may impair their ability to resorb bone matrix efficiently, leading to abnormal bone remodeling. This dysfunction could exacerbate skeletal defects, such as cortical thickening and medullary stenosis, observed in KCS2-like syndrome. Furthermore, accumulated cellular debris due to impaired autophagy may trigger inflammatory responses, contributing to the patient’s recurrent fever and elevated cytokines (TNF-α, IL-1β, IL-17 and IL-12p70). These findings align with prior studies linking autophagy defects to skeletal dysplasia [25-26]. This suggests that the balance between autophagy and necroptosis is critical for maintaining cellular homeostasis and preventing the development of diseases. Further studies are needed to elucidate the molecular mechanisms underlying the interplay between autophagy and necroptosis and their role in the development of diseases. Upon structural characterization revealed that the FAM111A variant generates a truncated protein exhibiting structural homology with ubiquitin [33-34], suggesting acquired compensatory ubiquitination functionality. This ubiquitin-like property potentially enhances necroptosis through aberrant modification of death signaling complexes, providing mechanistic insight into the observed clinical phenotype. The truncated FAM111A may disrupt endogenous protease activity, leading to accumulated DNA replication stress and subsequent NLRP3 inflammasome activation. These molecular perturbations collectively explain the dual pathology of elevated necroptosis and cytokine production (IL-1β and TNF-α) [13, 28]. From a therapeutic perspective, modulating autophagy through mTOR inhibitors to alleviate proteostasis imbalance or RIPK1 inhibitors to target necroptosis pathways could potentially rescue osteoclast dysfunction and mitigate bone resorption defects in KCS2-like syndromes. While preclinical validation in murine models remains essential, therapeutic development should ultimately prioritize human-relevant systems. Our findings further highlight the precise roles of FAM111A in bone development and Inflammation modulation via inflammasome crosstalk [14]. Notably, current mechanistic evidence from mouse-derived osteoclasts requires confirmation in patient-derived osteoclasts or even using induced pluripotent stem cells-differentiated osteoclasts. In summary, our present comprehensive assessment has shed light on the pathogenic potential of the novel FAM111A variant, offering valuable insights into the molecular pathways and cellular mechanisms contributing to KCS2-like syndrome. Genetic testing is conducive to identifying the etiologics. Early intervention based on early diagnosis can improve prognosis. These findings may open new avenues for further research and hold promise for personalized treatment approaches for rare skeletal dysplasia. Specifically, pharmacological modulation of autophagy-necroptosis crosstalk, like targeting necroptosis regulators MLKL or inflammasome components emerges as a novel potential therapeutic strategy to ameliorate bone pathology and inflammatory manifestations in KCS2-like syndrome. Translational studies using patient-derived cell models or animal systems carrying the FAM111A variant are critical next steps to evaluate these interventions. Declarations Acknowledgments We would like to acknowledge and thank the parents of patient for their kindly cooperation and understood with the clinical data collection. We would like to acknowledge Li Peng and Yanlan Zhong for their help with the clinical data collection. We thank all authors who help in the implementation of the experiment: Zhe Cai, Kexin Chen and Suyun Cheng. In addition, we would like to acknowledge and thank Professor Yu Feng, Chun Kwok Wong and Qiming Liu for their reviewing and revising the article. Funding This work was supported by the Western Medicine-General Guide Item of Guangzhou Municipal Health Commission (No. 20241A011039), the Guangzhou Municipal Science and Technology Bureau Foundation (No. 202201020637), the Research Capacity Improvement Project of Guangzhou Medical University (No. cw02-410-2302143XM and No. cw02-410-2302161XM), the Excellent Young Scholars Project of Ningxia Hui Autonomous Region Natural Science Foundation (No. 2021AAC05021), and the Guangdong Medical Science and Technology Research Fund Project (No. A2025077). Author contributions Conceptualization: Ping Wu, Zhe Cai and Chun Kwok Wong. Investigation: Xue Li, Li Peng, Kexin Chen, Yanlan Zhong, Suyun Cheng, Song Zhang, Wenbo Zhang, Qiming Liu. Validation: Juan Zhou, Chun Kwok Wong and Xue Li. Data curation: Ping Wu, Zhe Cai and Li Peng. Writing original draft: Ping Wu and Zhe Cai. Writing review and editing: Zhe Cai, Yu Feng, Qiming Liu, Chun Kwok Wong. Supervision: Chun Kwok Wong and Zhe Cai. Conflicts of interest statement The authors have no conflicts of interest relevant to this article. Ethics statement This study does not involve human or animal samples and does not require ethical approval. This research also does not involve the need to disclose the privacy information of patients and their family. All experiments and samples were performed in accordance with the ethical and biosafety protocols approved by the institutional guidelines. The usage of clinical information in this research has been approved by the child's parents, who have signed the informed consent. Data availability Restrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality. The datasets generated during and analyzed in this study are available from the corresponding author upon reasonable request. Consent for Publication Informed consent was obtained from all participants. Abbreviations KCS, Kenny-Caffey syndrome; FAM111A, Family with sequence similarity 111 member A; TBCE, Tubulin-specific chaperone E; OMIM, Online Mendelian Inheritance in Man; HGNC, HUGO Gene Nomenclature Committee; EEG, Electroencephalogram; cDNA, complementary DNA; PCR, Polymerase chain reaction; sgRNA, small-guide RNA; CRISPR, Clustered regularly interspaced short palindromic repeats; MC3T3-E1, Murine calvaria 3T3-E1 subclone; HEK, Human embryonic kidney cell line; ATCC, American Type Culture 97 Collection; DMEM, Dulbecco's Modified Eagle Medium; FBS, Fetal bovine serum; PMA, Phorbol-12-myristate-13-acetate; RANKL, Receptor activator of nuclear factor kappa-Β Ligand; TRAP, Tartrate-resistant acid phosphatase; G-CSF, Granulocyte colony-stimulating factor; IFNγ, Interferon gamma; IL-10, Interleukin-10; IL-12p70, Interleukin-12p70; IL-17, Interleukin-17; IL-1β, Interleukin-1 beta; IL-2, Interleukin-2; IL-23p19, Interleukin-23p19; IL-4: Interleukin-4; IL-6, Interleukin-6; KC, Keratinocyte-derived cytokine; MCP-1, Monocyte chemoattractant protein-1; TNF-α, Tumor necrosis factor alpha; SDS-PAGE, Sodium dodecyl sulfate polyacrylamide gel electrophoresis; CCL-2, C-C motif chemokine ligand 2; GAPDH, Glyceraldehyde-3-phosphate dehydrogenase; HRP, Horseradish peroxidase; p-MLKL, phosphorylated mixed lineage kinase domain-like; p-JNK, phosphorylated c-Jun N-terminal kinase; LC3BII, Microtubule-associated proteins 1A/1B light chain 3B II; BF, Bright field; FL, Fluorescent field; NC, Negative control; CQ, Chloroquine phosphate; PIP, PCNA-interacting peptide box; UBL1, Ubiquitin-like domain 1. 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Triad of human cellular proteins, IRF2, FAM111A, and RFC3, restrict replication of orthopoxvirus SPI-1 host-range mutants. Proc Natl Acad Sci U S A . 114 , 3720-3725 (2017). Isojima, T. et al. A recurrent de novo FAM111A mutation causes Kenny-Caffey syndrome type 2. J Bone Miner Res, 29 , 992-998 (2014). Zhang YQ, Li H. Reference charts of sitting height, leg length and body proportions for Chinese children aged 0-18 years. Ann Hum Biol . 42 , 223-30 (2015). Nie, M. et al. FAM111A induces nuclear dysfunction in disease and viral restriction. EMBO Rep . 22 , e50803 (2020). Carvill, G. L. et al. Targeted resequencing in epileptic encephalopathies identifies de novo mutations in CHD2 and SYNGAP1. Nat Genet. 45 , 825-830 (2013). Linkermann, A. et al. Regulated cell death and inflammation: an auto-amplification loop causes organ failure. Nat Rev Immunol 14 , 759-767 (2014). Kamil, G. et al. Clinical relevance of targeted exome sequencing in patients with rare syndromic short stature. 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Tables Table 1. Clinical characteristics of blood diagnostics (n = 12), median (IQR). Parameters Measured values Normal range Absolute number of white blood cells, 10 9 /L 7.58(4.02-14.29) 4.30-11.30 Absolute number of neutrophils, 10 9 /L 3.85(0-6.34) 1.60-7.80 Absolute number of monocytes, 10 9 /L 0.73(0.01-1.37) 0.13-0.76 Absolute number of lymphocytes, 10 9 /L 2.08(0.43-3.79) 1.50-4.60 Absolute number of eosinophils, 10 9 /L 0.10(0.03-0.28) 0.00-0.68 Absolute number of basophils, 10 9 /L 0.02(0.01-0.03) 0.00-0.07 Absolute number of red blood cell, 10 12 /L 4.16(3.46-4.63) * 4.20-5.70 Haemoglobin, g/l 121.41(101.00-136.00) 118-156 Hematocrit, (%) 35.39(29.10-38.90) * 36.00-46.00 Mean corpuscular volume, fL 84.36(80.40-91.30) 77-92 Mean hemoglobin amount, pg 28.90(27.80-30.30) 25-34 Mean hemoglobin concentration, g/l 343.41(311.00-361.00) 310-355 Erythrocyte distribution width -SD, (%) 38.39(35.00-41.60) 35-56 Erythrocyte distribution width -CV, (%) 12.40(11.90-13.10) 11.50-14.50 Absolute number of platelet, 10 9 /L 234.50(167.00-325.00) 167-453 Platelet distribution width, (%) 10.88(8.40-15.40) * 14.80-17.20 Mean platelet volume, fL 8.93(8.30-9.50) 7.60-13.20 Large platelet ratio, (%) 15.62(12.20-19.70) 13-43 Thrombocytic, (%) 0.20(0.15-0.27) 0.10-0.50 Percentage of neutrophils, (%) 57.94(9.60-83.10) 31-70 Percentage of monocyte, (%) 11.65(5.00-17.90) * 2-11 Percentage of lymphocytes, (%) 28.87(6.30-50.00) 23-59 Percentage of eosinophils, (%) 1.23(0-3.30) 0-9 Percentage of basophils, (%) 0.21(0-0.50) 0-1 Infantile granulocyte absolute value, 10 9 /L 0.03(0.02-0.05) 0-0.06 Percentage of naive granulocyte, (%) 0.52(0.30-0.80) 0-0.60 Reticulocyte absolute value, 10 9 /L 81.73(66.00-97.40) 36.30-195.70 Reticulocyte percentage, (%) 1.98(1.50-2.40) 0.82-2.25 Low fluorescence intensity reticulocyte ratio, (%) 92.06(85.00-98.00) 87-98.50 Immature reticulocyte ratio, fL 7.93(2.00-15.00) 3.10-13.40 Medium fluorescent intensity reticulocyte ratio, (%) 7.26(1.80-14.00) 2.80-11.80 High fluorescence intensity reticulocyte ratio, (%) 0.66(0.20-1.00) 0.10-1.50 Reticulocyte hemoglobin content, pg 26.66(25.50-27.60) * 30.30-36 The table shows the statistically significant differences between measurement results and normal range (* p<0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range. Table 2. Clinical characteristics of biochemical detection index (n = 12), median (IQR). Parameters Measured values Normal range Alanine aminotransferase (ALT), U/L 17.88(11.50-23.40) 14-44 Aspartate amino transferase (AST), U/L 29.34(23.80-62.10) 7-30 r-glutamyltransferase (r-GGT), U/L 14.86(12.00-18.00) 8-58 Alkaline phosphatase (ALP), U/L 167.86(128.00-246.00) * 42-140 Cholinesterase (CHE), U/L 7403.50(6183.00-8529.00) 5000-12000 Creatine kinase (CK), U/L 237.63(76.00-628.00) * 15-130 Creatine kinase isoenzyme (CK-MB), U/L 24.80(16.00-49.20) 0-25 Lactate dehydrogenase (LDH), U/L 227.75(167.00-325.00) 109-245 Adenosine dehydrogenase (ADA), U/L 11.58(7.30-15.60) 0-20 Glutathione reductase (GR), U/L 59.00(49.00-69.00) 34-73 A-amylase (a-AMY), U/L 64.14(43.00-88.50) 40-132 A-fucosidase (AFU), U/L 28.40(24.90-34.80) 0-40 A-hydroxybutyrate dehydrogenase (a-HBDH), U/L 183.40(155.00-249.00) * 72-162 Homocysteine (HCY), μmol/L 5.95(4.80-7.10) 4-16 Cystatin c (CYSC), mg/L 0.41(0.34-0.55) 0-1.03 Total protein (TP), g/L 63.85(55.40-72.60) * 66-87 Albumin (ALB), g/L 42.29(37.10-46.40) 35-55 Globulin (GLO), g/L 21.56(17.90-26.20) 20-45 Ig A/G, g/L 1.99(1.61-2.37) 1.25-2.50 Proalbumin (PA), mg/L 202.14(179.00-223.90) 200-400 Total bilirubin (TBIL), μmol/L 8.17(5.50-10.20) 5.10-19 Direct bilirubin (DBIL), μmol/L 2.49(1.10-3.50) 1.70-6.80 Indirect bilirubin (IBIL), μmol/L 5.68(3.60-7.40) 0-17 Total bile acid (TBA), μmol/L 3.46(1.70-6.80) 0-15 Urea (UREA), mmol/L 3.23(2.11-4.50) 2.80-7.60 Uric acid (UA), μmol/L 287.50(309.00-243.00) 208-428 Creatinine (CRE), μmol/L 35.56(27.00-63.00) * 44-133 Calcium (Ca), mmol/L 2.27(2.02-2.38) 2.25-2.80 Phosphorus (P), mmol/L 1.29(1.15-1.55) 1.29-2.26 Potassium (K), mmol/L 3.65(3.14-4.09) 3.50-5.10 Sodium (Na), mmol/L 135.59(130.00-143.00) * 136-146 Chlorine (CL), mmol/L 104.87(96.80-111.00) 98-106 Magnesium (Mg), mmol/L 0.94(0.74-1.20) 0.73-1.06 Serum total carbon dioxide (CO2), mmol/L 21.06(17.00-23.90) * 25-35 Glucose (GLU), mmol/L 5.42(3.75-7.23) 3.89-6.11 Total cholesterol (CHOL), mmol/L 4.33(3.94-4.63) 3-5.70 Triglyceride (TG), mmol/L 0.63(0.36-1.19) 0.40-1.70 High density cholesterol (HDL-C), mmol/L 1.34(1.26-1.38) 0.83-1.96 Low density cholesterol (LDL-C), mmol/L 2.39(2.07-2.79) 0-3.36 Lipoprotein a (LP a), mg/L 110.26(73.00-158.10) 0-300 Apolipoprotein-A1(APOA1), g/L 1.19(1.11-1.26) 1-1.60 C-reactive protein (CRP), mg/L 2.44(0.10-3.30) 0-6 Procalcitonin (PCT), ng/ml 0.12(0.03-0.21) * ＜0.10 The table shows the statistically significant differences between measurement results and normal range (* p<0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range. Table 3. Clinical characteristics of immune-related index (n = 10), median (IQR). Parameters Measured values Normal range IgG, g/L 8.87(7.00-12.30) 3.82-10.58 IgA, g/L 0.65(0.27-0.92) 0.14-1.14 IgM, g/L 1.15(0.90-1.41) 0.40-1.28 IgE, IU/ML 76.53(59.00-88.60) * 0-60 C3, g/L 0.94(0.74-1.23) 0.80-1.50 C4, g/L 0.10(0.06-0.17) * 0.13-0.43 B lymphocytes (CD19 + ), (%) 14.6 (10.90-18.30) 5-18 CD15 + B1 lymphocytes (CD15 + CD19 + ), (%) 46.75 (39.90-53.60) 14.98-53.79 Myeloperoxidase antibody, RU/mL 0.15 (0-0.30) ＜20 Protease 3 antibody (PR3), RU/mL 0.25 (0.10-0.40) ＜20 The table shows the statistically significant differences between measurement results and normal range (* p<0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range. Table 4. Clinical characteristics of cytokines (n = 3), median (IQR). Parameters Measured values Normal range IL-5, pg/mL 1.50 (0.04-2.96) 0-8.70 IL-17, pg/mL 6.22 (5.29-7.16) 0-19.00 IL-1β, pg/mL 5.30 (2.99-7.62) 0-12.30 IL-2, pg/mL 1.59 (0.39-2.79) 0-8.20 IL-4, pg/mL 2.90 (1.11-4.70) 0-11.90 IL-6, pg/mL 3.62 (3.28-3.97) 0-7.00 IL-8, pg/mL 6.17 (3.61-8.74) 0-62.00 IL-10, pg/mL 2.91 (1.74-4.09) 0-9.10 IL-12p70, pg/mL 2.27 (1.63-2.91) 0-8.40 TNF-α, pg/mL 1.77 (0.4-3.15) 0-8.00 IFN-γ, pg/mL 1.61 (0.38-2.85) 0-16.20 IFN-α, pg/mL 2.18 (0.65-3.72) 0-13.20 The table shows the statistically results of measured values and normal range. Supplementary Files Supplementaryinformationfullimage.pdf Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-7188681","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":511538952,"identity":"3c26f937-9d89-4a2b-bb5f-d399ee0123c7","order_by":0,"name":"Ping Wu","email":"","orcid":"","institution":"First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Wu","suffix":""},{"id":511538953,"identity":"3dc6037d-bcbb-4c4e-becd-dd35a2ff53ee","order_by":1,"name":"Xue Li","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical 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15:33:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7188681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7188681/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91306930,"identity":"70cbfb7d-5900-45e1-adb4-5bd911475320","added_by":"auto","created_at":"2025-09-15 06:35:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5675343,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe main important clinical features of the patient. \u003c/strong\u003e(A-C) The patient’s clinical features of hyperspasmia and fever. (D) The linear correlation of concurrent times between hyperspasmia and fever. (E) The ratio of electroencephalogram and fever. (F) The diagram of patient’s body weight and height curve. (G) The X-ray imaging of the left hand of the patient.\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/a88ab238181e270a49d43a49.jpg"},{"id":91305684,"identity":"f4031062-f09b-45a4-83bf-5eacceb3530a","added_by":"auto","created_at":"2025-09-15 06:27:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10816173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe genetic and Venn analysis of gene variants in the patient’s family. \u003c/strong\u003e(A) The high-precision whole exome sequencing report of the patient's family. (B) The genetic diagram of the patient’s family. (C) The Sanger sequencing verified the FAM111A gene variant c.405delA in the patient. (D) The Venn analysis revealed the shared variant genes between the patient and his younger sister, identified through whole exome sequencing.\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/e2a938d429401f9a9ddecb29.jpg"},{"id":91305682,"identity":"d72636a9-eec0-414a-aa21-6c9952277004","added_by":"auto","created_at":"2025-09-15 06:27:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":8798973,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlizarin Red and Trap staining analysis to determine the proportion of induced osteoid and osteoclasts in different group, respectively.\u003c/strong\u003e (A) The Alizarin Red staining of osteoid induced from MC3T3-E1 cells in different groups, scale bar = 100 μm. (B) The statistical analysis of the percentages of osteoid area in different groups, scale bar = 100 μm. (C) The Trap staining of osteoclasts induced from Raw264.7 cells in different groups. (D) The statistical analysis of the percentage of Trap\u003csup\u003e+\u003c/sup\u003e osteoclasts in different groups. (E) The concentrations of Ca\u003csup\u003e2+\u003c/sup\u003e in supernatants of different groups. Statistical significance was assessed by one-way ANOVA followed by Tukey’s post-hoc test (****p\u0026lt;0.0001 vs. WT).\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/42878b6217900586da0497d4.jpg"},{"id":91305689,"identity":"eea0f3d6-d398-4e10-8bf3-d4a4f48541b2","added_by":"auto","created_at":"2025-09-15 06:27:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8440237,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe analysis of osteoclast cell programming death and the expression levels of their secreted inflammatory cytokines in various groups.\u003c/strong\u003e (A-C) The flow cytometric analysis and statistical analysis of osteoclast apoptosis in various groups. Data represent mean ± SD; *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001 and ****p\u0026lt;0.0001 (Student’s t-test). (D) The expression levels of FAM111A and necrotic related proteins, such as p-MLKL, MLKL, p-JNK and JNK in different groups. (E) The relative expression levels of p-MLKL, MLKL, p-JNK and JNK to GAPDH across different osteoclasts. Data represent mean ± SD; *p\u0026lt;0.05, ***p\u0026lt;0.001 (Student’s t-test). (F) The inflammatory cytokines released by osteoclasts in different groups. The redder the color, the higher the expression. Statistical significance was assessed by one-way ANOVA (*p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001 and ****p\u0026lt;0.0001).\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/66aea7320a5e3e9e8c95952f.jpg"},{"id":91305693,"identity":"aa4c1d9b-1ece-459c-9f9f-9ddd2486ecb0","added_by":"auto","created_at":"2025-09-15 06:27:31","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":10681838,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe changes of autophagy and lysosome in different osteoclasts.\u003c/strong\u003e(A) The red fluorescent particles characterized the lysosomes in osteoclasts. BF: Bright field, FL: Fluorescent field, scale bar = 5 μm. (B) The statistical analysis of the number of lysosomes in different groups. (C) The expression levels of LC3BII and p62 across different groups and general ubiquitination. NC: Negative control, CQ: Chloroquine phosphate. (D-E) The statistical analysis of the relative expression levels of LC3BII and p62 to GAPDH across different groups. Statistical significance was assessed by one-way ANOVA (*p\u0026lt;0.05 and ****p\u0026lt;0.0001).\u003c/p\u003e","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/bef0f062c6189ca5753a355d.jpg"},{"id":91305691,"identity":"aacaeba0-e7ca-4217-ae90-4aadbd848c4c","added_by":"auto","created_at":"2025-09-15 06:27:30","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12187794,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic diagram of gene and protein structure.\u003c/strong\u003e (A) The domain features of FAM111A and variant FAM111A\u003csup\u003ec.405delA (p.E136Sfs*3)\u003c/sup\u003e genes. PIP: PCNA-interacting peptide box, UBL1: Ubiquitin-like domain 1. (B) The 3D cartoon structure of protein FAM111A, FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e and Ubiquitin. The α-helix is labeled in red color, β-sheet labeled in yellow color, loop labeled in green, and the truncated FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e labeled in blue. RMSD: Root Mean Square Deviation. (C) The 3D cartoon structure of human and mouse FAM111A proteins were presented. The conserved functional domains of FAM111A protein was aligned between human (AF-Q96PZ2-F1) and mouse (AF-Q9D2L9-F1). The conserved amino acid consensus rate was up to 57.36%.\u003c/p\u003e","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/6d563a0a09f34530a8a69d64.jpg"},{"id":91305694,"identity":"4d575621-44b2-4644-b250-27fe9e189fb3","added_by":"auto","created_at":"2025-09-15 06:27:31","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":13169755,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe possible mechanism of this study presented in a graphical abstract.\u003c/strong\u003e This figure illustrates the potential relation between the FAM111A\u003csup\u003ec.405delA \u003c/sup\u003evariant and the pathogenesis of KCS2 syndrome. Specifically, it shows that a single-nucleotide deletion in FAM111A results in a truncated protein in osteoclasts derived from macrophages (Raw264.7 cells). This alteration is accompanied by impaired bone-resorbing capacity and suppressed autophagy, leading to increased necrotic protein expression and elevated cell death. These cellular events trigger a pronounced rise in pro-inflammatory cytokines including IL-17, TNF-α, IL-1β, IL-12P70, and IFN-γ, thereby exacerbating inflammatory responses. Notably, while osteoclast function is disrupted, osteoblast activity remains intact, ultimately resulting in excessive bone mass accumulation, cortical bone thickening, and narrowing of the medullary cavity. Overall, these findings ultimately reveal the FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e variant leads to bone metabolism imbalance and driving the onset of KCS2 syndrome.\u003c/p\u003e","description":"","filename":"fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/9aaaadbf76ec2fe6df6cc6b4.jpg"},{"id":109759659,"identity":"d877cfdc-1b34-4fad-8a9d-b097c3ed40ef","added_by":"auto","created_at":"2026-05-22 07:27:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":70156982,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/24091cec-5864-44bd-9ad5-ed6c6a7e75a7.pdf"},{"id":91305699,"identity":"28d00bdb-4049-461e-a72c-0af44607d40e","added_by":"auto","created_at":"2025-09-15 06:27:31","extension":"pdf","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":723543,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformationfullimage.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7188681/v1/8a378ae9cb8d5ac46fa46198.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA novel FAM111A frameshift variant associated with osteoclast necroptosis and KCS2-like syndrome\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eKenny-Caffey syndrome (KCS) is a rare genetic disorder characterized by features such as short stature, hypoparathyroidism, skeletal defects, and ocular abnormalities [1] The syndrome was first described in 1966 by Kenny \u003cem\u003eet al.\u003c/em\u003e, who reported a case involving a mother and her son presenting with hypocalcemia, hyperphosphatemia, cortical thickening of tubular bones, and medullary cavity stenosis [2]. Subsequently, in 1967, Caffey\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. provided a detailed description of these features in the same family, leading to the syndrome being named Kenny-Caffey syndrome [3]. The underlying molecular causes of KCS have been attributed to pathogenic variants in either the tubulin-specific chaperone E gene (TBCE) [KCS type I/ KCS1, Online Mendelian Inheritance in Man (OMIM) #244460] or the family with sequence similarity 111 member A gene (FAM111A, HGNC: 24725) (KCS type II/ KCS2, OMIM #127000) [4-5]. TBCE is involved in microtubule dynamics [6-8], whereas FAM111A plays a role in DNA replication and viral defense [9-13]. KCS1 is associated with mental retardation, microcephaly, and mental hypoplasia, and is inherited in an autosomal recessive manner. In contrast, KCS2 is characterized by the absence of mental retardation and mental hypoplasia, and the variant is inherited in an autosomal dominant or sporadic manner [14]. Compared with KCS1, KCS2 is rarer, with only a dozen cases reported worldwide. In 2013, through the exome sequencing of 5 KCS patients, FAM111A was identified as the pathogenic gene of KCS2 [5]. FAM111A is located in chromosomal 11q12.1 and encodes a protein consisting of 611 amino acids [14]. Current studies have shown that amino acid residues 336-661 of FAM111A encompass a trypopalinase-like serine peptidase domain, including a catalytic triad composed of histidine, aspartate and serine residues [13].\u003c/p\u003e\n\u003cp\u003eHere, we present a case of child patient with clinical features consistent with KCS2-like syndrome, which was confirmed through exome sequencing, revealing a novel heterozygous variant in the FAM111A gene (c.405delA). The variant c.405delA (p.E136Sfs*3) of FAM111A gene in this child is\u0026nbsp;\u003cem\u003ede novo\u003c/em\u003e, while both his parents have normal genotypes. So far, this variant has not been reported in and outside of Chinese population in the reference gene database (Genome Aggregation Database) (https://gnomad.broadinstitute.org/ gene/ENSG00000110719?dataset=gnomad_r2_1). The absence of variant in gnomAD (v2.1.1), the Human Gene Mutation Database, the Online Mendelian Inheritance in Man (OMIM), the Genetic and Rare Diseases Information Center (GARD) and several other rare disease databases reveals its rarity. Although the disease's genetic basis has been linked to variants in the FAM111A gene, the specific pathways through which these genetic alterations contribute to the observed clinical phenotype remain incompletely understood. This study aims to discover the complex relations between clinical features of the child patient with KCS2-like syndrome and FAM111A (c.405delA; p.E136Sfs*3) novel variant through cellular and molecular mechanisms. We hypothesize that decreased autophagy and increased necrosis of osteoclasts induced by FAM111A gene variant may be related to the short stature and increased inflammatory response in patients. These findings highlight the potential physiological effects of the FAM111A variant and provide insight into the underlying mechanisms that may be contributing to the patient's condition. Further research into the specific pathways affected by the variant could help in developing targeted treatments for individuals with similar genetic variants.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003ePlasmids and transfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman FAM111A cDNA was amplified by reverse transcription PCR and cloned into pcDNA3.1 plasmid. The FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e variant was generated by site-directed deletion of adenine at position 405 and verified by Sanger sequencing. For expression of FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e with a N-terminal Flag tag, the FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e open reading frame sequence was cloned into pLVX3-3×Flag-blast for lentiviral expression in mouse Raw264.7 cells. The small-guide RNA (sgRNA) was designed using the CRISPR Design Tool (http://chopchop.cbu.uib.no/) to minimize potential off-target effects. The sgRNA sequences were cloned into a lentiCRISPR-V2 vector (Addgene) to knockout the mouse FAM111A gene (FAM111A\u003csup\u003eKO\u003c/sup\u003e). The pLVX3-3×Flag-FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e-blast and lentiCRISPR-V2-FAM111A\u003csup\u003eKO\u003c/sup\u003e-sgRNA plasmids were introduced by liposomal transfection reagent (#40802ES03, Yeasen), respectively, according to manufacturer’s recommendation. The knockout and variant efficiency of FAM111A was confirmed by immunoblotting. The sgRNA sequences targeting FAM111A was purchased from Sangon (Shanghai, China) as follows: FAM111A sgRNA: 5’-CCCGTCTGCTGTATACCAGA-3’.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMurine calvarial cell line MC3T3-E1, murine monocyte macrophage leukemia cell line Raw264.7 and Human embryonic kidney cell line (HEK) 293T were obtained from American Type Culture Collection (ATCC), and cultured in Dulbecco's Modified Eagle Medium (DMEM, #10-013-CVR, Corning) supplemented with 10% fetal bovine serum (FBS, #1099-141, Gibco). The lentivirus of FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e and FAM111A\u003csup\u003eKO\u003c/sup\u003e were packaged in 293T cells, and purified and concentrated after 2 days. Then, the viruses were harvested to infect Raw264.7 cells, which were selected by blasticidin (#ST018, Beyotime) and puromycin (#P9620, Sigma-Aldrich), respectively, to obtain stable expressing cell lines. After culturing with 100 ng/ml Phorbol-12-myristate-13-acetate (PMA, #P1585, Sigma-Aldrich) for 3 days, the cells were induced to differentiate into macrophages, followed by the addition with 100 ng/ml receptor activator of nuclear factor Kappa-Β ligand (RANKL, #95625ES25, Yeasen) for 5 days to induce the differentiation into osteoclasts. The osteoclast was confirmed by tartrate-resistant acid phosphatase (Trap, #G1050, Lifescience) assay. The autophagy activity of osteoclast was activated by Torin 1 (#T6045, TargetMol Chemicals Inc.), and inhibited by chloroquine phosphate (CQ, #PHR1258, Sigma-Aldrich). The osteoid was confirmed by 0.1% Alizarin Red (#A600144, Sangon Biotech) staining. The bone slides were purchased from (#2-0001-10, Guangzhou Zhuanyan Biotechnology Co., Ltd.). The released Ca\u003csup\u003e2+\u0026nbsp;\u003c/sup\u003ein the supernatant of osteoclast incubated with bone slide was detected by Calcium Colorimetric Assay Kit (#S1063S, Beyotime).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor analysis of cell apoptosis, the osteoclasts were stained with cell apoptosis reagent (propidium iodide and allophycocyanin conjugated Annexin V) following the reagent instruction (#A6030M, UELandy). Flow cytometry analysis was performed on the CytoFLEX Flow Cytometer (Beckman Coulter) using FlowJo software (v10, Tree Star software, Inc.). Representative dotplots were shown from three independent experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLysosome\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;fluorescence qualification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of intracellular lysosomes was quantitated using Lyso-Tracker reagent (#DND99, Yeasen) through fluorescence qualification. Fluorescence images were acquired by Leica microscopy and analyzed by Leica Application Suite Advanced Fluorescence software (LAS AF, Version 4.2). Representative fluorescence images were shown from three independent experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiplex Inflammatory cytokines assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInflammatory cytokines including G-CSF, IFN-γ, IL-10, IL-12p70, IL-17, IL-1β, IL-2, IL-23p19, IL-4, IL-6, KC, MCP-1 and TNF-α were detected using RayPlex\u003csup\u003e®\u003c/sup\u003e Mouse Inflammation Array Kit 1 (#FAM-INF-1-48, Ray Biotech). The supernatant of osteoclast from each group was collected to measure the secreted inflammatory cytokines by the CytoFLEX Flow Cytometer (Beckman Coulter) according to the kit instruction. The supernatants were measured from three independent repeats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoblotting analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were lysed in NP-40 lysis buffer (50 mM Tris-HCl pH 7.4, 150 mM NaCl, 0.1% Nonidet P-40, 5mM EDTA, 50mM NaF, 1mM Na\u003csub\u003e3\u003c/sub\u003eVO\u003csub\u003e4\u003c/sub\u003e, 10% Glycerol) supplemented with protease inhibitor mix (#BL630B, Biosharp). For Western blotting, lysates containing 30 μg of protein were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), transferred to polyvinylidene fluoride membranes, and probed with specific antibodies. First antibodies used for Western blotting: rabbit anti-FAM111A (Abcam, ab184572, 1:1000); mouse anti-GAPDH-Horseradish peroxidase (HRP) (1:5000) (#HRP-60004, Proteintech Group); mouse anti-Flag (1:1000) (K200001M, Solarbio); mouse anti-phospho (p)-MLKL (1:1000) (#ab196436, Abcam) and MLKL (1:1000) (#ab243142, Abcam); rabbit anti-p-JNK1/2/3 (Thr183+Tyr185) (1:1000) (#AF3318, Affinity Biosciences) and anti-JNK1/2/3 (1:1000) (#AF6318, Affinity Biosciences); anti-ubiquitin (#10201-2-AP,\u0026nbsp;Proteintech Group); Anti-SQSTM1/p62 (#5114S, Cell signaling); anti-LC3BII (#14600-1-AP,\u0026nbsp;Proteintech Group). After incubation with the above antibodies, following by the incubation with HRP-conjugated secondary antibodies (1:5000) (#K1223, #K1221, APExBIO). Blots were imaged using ChemiDoc MP (Bio-Rad) and analyzed using the Image Lab software (v5.2, Bio-Rad).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein structure analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe predicted protein structure of human FAM111A (AlphaFold Protein Structure Database: AF-Q96PZ2-F1) and mouse FAM111A (AF-Q9D2L9-F1), FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e and ubiquitin (PDB code: 1Q5W) was determined by the PyMOL Molecular Graphics System software (v2.5.2, Schrodinger, Inc.). The conservation of FAM111A protein between human and mouse was also studied, and alignment results were displayed using ESPript (https://espript.ibcp.fr/ESPript/cgi-bin/ESPript.cgi).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are expressed as mean ± standard deviation (SD). Analysis was done using Graphpad Prism v8 (San Diego, CA, USA). For statistical analysis of three groups, the assumption of equal variances was tested using the Brown-Forsythe test and normality was tested using the Shapiro-Wilk test. For two groups, the assumption of equal variances was tested using an F test. If assumptions were not met, data was first logarithmically transformed to achieve equal normality. Then, for three groups one-way ANOVA was used to test for differences in the data, followed by a Tukey’s multiple comparison test in case the null hypothesis was rejected. In the case of two groups, an unpaired Student’s-test was used. Differences with a p value of \u0026lt; 0.05 were considered statistically significant (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCase presentation and discovery of the FAM111A variant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patient, an 11-year-old male child with KCS2-like syndrome, presented at the outpatient department of Guangzhou Women and Children's Medical Center, with a history of recurrent hyperspasmia lasting over 10 years. The first episode of hyperspasmia occurred in 2014. These hyperspasmia are typically associated with fever, and to date, the patient has experienced a total of 9 such episodes (Figure. 1A-D). Additionally, multiple instances of abnormal electroencephalogram (EEG) readings prompted a diagnosis of epilepsy in 2016 (Figure 1E). At the same time, the child's height and body weight are either below or at the lower limit of the standard development curve (Figure 1F). And so far, he is still short in stature. His sitting height (SH=79 cm), leg length (LL=74 cm), and SH/LL\u0026nbsp;ratio\u0026nbsp;(1.06) are fallen below the 50th percentiles of body proportions for Chinese boys minus 1SD [15]. Meanwhile, a hand X-ray taken at age 13 showed significant abnormalities in bone mass (Figure 1G), such as tubular cortical thickening and medullary cavity stenosis, which may closely relate to the abnormalities in bone metabolism indicators like alkaline phosphatase in supplemental table 1 (Table S1). The other clinical characteristics of this patient including blood diagnostics, biochemical detection index, immune-related index and cytokines were shown in Table S2-4. At the age of 10, a comprehensive exome sequencing was performed on the patient’s family including his parents and younger sister. The results indicated that both parents and younger sister showed no variations (Figure 2B). In contrast, a\u0026nbsp;\u003cem\u003ede novo\u003c/em\u003e variant in the FAM111A gene, specifically c.405delA (p.E136Sfs*3), was identified in the child (Figure 2A). This variant involves the deletion of an adenine nucleotide (A) at position 405 of the FAM111A gene verified by Sanger sequencing, resulting in premature termination of gene translation of the third amino acid after the variant site (Figure 2C). When compared the variant genes between the patient and his sister, there are 18 shared genes (Figure 2D). However, the FAM111A gene is out of these. To further find the association between the FAM111A gene variant c.405delA (p.E136Sfs*3) and\u0026nbsp;KCS2-like syndrome, several explorations were conducted\u0026nbsp;\u003cem\u003ein vitro\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnaffected differentiation function of osteoblast and osteoclast but impeded osteolytic ability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferent from previous reports [14], we found that the function of osteoblasts were completely normal in KCS2-like syndrome patients. In the\u0026nbsp;\u003cem\u003ein vitro\u003c/em\u003e study, we also did not observe any impaired osteoblast (MC3T3-E1) differentiation and observed normal induced osteoid (Figure 3A-B). Interestingly, the differentiation functions of osteoclasts induced from Raw264.7 cells (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e and FAM111A\u003csup\u003eKO\u003c/sup\u003e) were not affected (Figure 3C-D). Although the differentiation functions of osteoblasts and osteoclasts were unaffected, the etiology of the patient's clinical features remained uncertain. But the Ca\u003csup\u003e2+\u003c/sup\u003e in the supernatant of variant osteoclasts and knockout FAM111A (FAM111A\u003csup\u003eKO\u003c/sup\u003e) osteoclasts incubated with bone slides were reduced significantly (Figure 3E). It is implied that the ostolystic ability of osteoclasts may impede.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncreased necroptosis of variant osteoclasts may contribute to\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eKCS2-like syndrome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further investigate the etiology, we found an increased percentage of necroptosis (Figure 4A-C) and upregulated necrotic pathway signals like p-MLKL and p-JNK (Figure 4D-E), which may contribute to the short stature phenotype of the patient, leading to the enhanced inflammatory responses and manifesting as recurrent fever and hyperspasmia. Therefore, we have detected the levels of inflammatory cytokines secreted from osteoclasts of each group. The results of multiplex cytokines assay suggest that the up-regulation of cytokines such as MCP-1, TNF-α, IL-1β, IFN-γ, IL-17 and IL-12p70 in the variant osteoclasts (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e) exhibited a higher degree of inflammation compared to the wild type (WT) controls (Figure 4F). This elevated inflammatory state might influence bone remodeling and resorption processes. However, what factors lead to the enhanced necroptosis of osteoclasts (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e)?\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecreased autophagy activity of variant osteoclasts may lead to the enhanced necroptosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the function of osteoclasts is related to the lysosome, we have stained the intracellular lysosome across different osteoclasts. Obviously, a decreased number of lysosomes in variant osteoclasts (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e)\u0026nbsp;were found, when compared to the WT and FAM111A\u003csup\u003eKO\u003c/sup\u003e groups (Figure 5A-B). More importantly, the lysosomes often fused with\u0026nbsp;autophagosomes to become autolysosomes to degenerate proteins. Since the LC3BII and p62 are two canonical markers of autophagy pathway, the relative expression patterns of these proteins provide insights into the autophagy activity in osteoclasts. The results of immunoblotting showed that the expression levels of LC3BII and p62 underwent significant changes across different treated groups (Figure 5C-E). The expression level of LC3BII appears to be lower in variant osteoclasts (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e), rather than FAM111A\u003csup\u003eKO\u003c/sup\u003e osteoclasts (Figure 5D). Oppositely, the expression level of p62 appears to be higher (Figure 5E). The alterations in LC3BII and p62 expression may indicate reduced autophagy activity in variant osteoclasts (FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e), potentially disrupting protein degradation and ultimately leading to increased necroptosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA possible insight for the protein variant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the Figure 6, it appears to contain information about the gene domain and three dimensions (3D) structure, and evolutionary conservation patterns of its coded proteins including human FAM111A and FAM111A (p.E136Sfs*3) as well as mouse FAM111A. Comparing on the gene domain features of FAM111A and FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e, FAM111A\u003csup\u003ec.405delA\u0026nbsp;\u003c/sup\u003erepresents a variant of FAM111A with a deletion of adenine at position 405 (c.405delA) leading to a frameshift and premature termination at position 138 (p.E136Sfs*3) (Figure 6A). This variant likely resulted in a truncated FAM111A protein. Through protein structure analysis, the predicted 3D structures of the FAM111A protein and truncated FAM111A (p.E136Sfs*3) protein could provide insights into the potential functional and structural changes. The incomplete protein structure possibly affected its function. Notably, the truncated FAM111A (p.E136Sfs*3) protein exhibits structural homology with ubiquitin [root mean square deviation (RMSD) = 3.066, represented a structural deviation between ubiquitin and the truncated FAM111A (p.E136Sfs*3) protein], suggesting that the FAM111A\u003csup\u003ec.405delA\u0026nbsp;\u003c/sup\u003evariant can lead to a compensative function of ubiquitination (Figure 6B), thereby enhancing necroptosis. The functional domain truncation in the\u0026nbsp;FAM111A\u003csup\u003ec.405delA\u003c/sup\u003e variant likely disrupts native protein interactions while potentially acquiring novel ubiquitin-like functions that drive pathological mechanisms. In line with these structural and functional insights, cross-species conservation analysis reveals 57.36% sequence identity in functional domains between human and mouse FAM111A (Figure 6C), further underscoring the importance of these conserved regions in maintaining structural integrity and biological function.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis case study offers a unique insight into the clinical and molecular features of KCS2-like syndrome, especially regarding a novel \u003cem\u003ede novo\u003c/em\u003e heterozygous variant in the FAM111A gene (c.405delA; p.E136Sfs*3) identifiedin the patient. This is a notable finding considering that the variant has not been reported in the Genome Aggregation Database or observed outside the Chinese population, thereby emphasizing its significance as a potential pathogenic factor in KCS2-like syndrome [16]. The presentation of recurrent hyperspasmia in the patient, along with a familial history of this condition, accentuates the complexity of the clinical manifestations associated with KCS2 and the significance of exploring its genetic underpinnings. Additionally, the detection of abnormal EEG readings prompts an epilepsy diagnosis highlighting the neurological implications linked to KCS2-like syndrome [17-18]. However, the detail mechanism on the correlation between recurrent hyperspasmia and this novel variant in FAM111A gene still needs further investigation. While our study identifies a novel FAM111A variant in a single patient, larger cohorts are needed to confirm its pathogenicity. Collaborative efforts to collect additional KCS2-like cases are underway.\u003c/p\u003e\n\u003cp\u003eFurthermore, the patient's short stature and aberrant bone mass, as evidenced by hand X-ray imaging, underscore further osteodysplasia associated with the syndrome [19-20]. Using\u0026nbsp;\u003cem\u003ein vitro\u003c/em\u003e investigations, we observed unaffected osteoblastic and osteoclastic differentiation, suggesting that the bone development and osteoblastic functions were seemingly normal [21-22]. Therefore, the imbalance of bone metabolism may be caused by abnormal function of osteoclasts. The graphical abstract of the possible mechanism model is illustrated in Figure 7. However, this assumption needs further investigation.\u003c/p\u003e\n\u003cp\u003eAs we known, autophagy and necroptosis are two important cellular processes that play a crucial role in maintaining cellular homeostasis [23-24]. Autophagy is a catabolic process that involves the degradation of damaged organelles, misfolded proteins, and other cellular components in lysosomes [25]. This process helps to maintain cellular homeostasis by removing potentially harmful cellular components and providing energy and nutrients during periods of cellular stress [26-27]. Necroptosis, on the other hand, is a programmed form of necrosis that is triggered by various cellular stressors, such as infection, inflammation, and DNA damage [28]. It is characterized by the release of cellular contents, inflammation, and cell death [28-29]. While autophagy and necroptosis are distinct cellular processes, they are closely interconnected. Autophagy can inhibit necroptosis by removing damaged organelles and cellular components that can trigger necroptosis [23, 30]. Delving deeper, we uncovered a notable increase in necroptosis and an associated up-regulation of necrotic pathway signals in the variant osteoclasts. These findings provide a potential mechanistic link between the patient's short stature and the elevated inflammatory responses, underscoring the potential possibility of physiological ramifications by the FAM111A variant [31-32]. Moreover, our studies revealed a downregulated autophagy activity in the variant osteoclasts, potentially triggering a disruption in protein degradation, which may culminate in enhanced necroptosis. These molecular insights offer a plausible explanation for the observed clinical manifestations, which may contribute to the development of KCS2-like syndrome. Besides, autophagy is critical for maintaining osteoclast function by regulating lysosomal activity and protein degradation. Reduced autophagy in variant osteoclasts may impair their ability to resorb bone matrix efficiently, leading to abnormal bone remodeling. This dysfunction could exacerbate skeletal defects, such as cortical thickening and medullary stenosis, observed in KCS2-like syndrome. Furthermore, accumulated cellular debris due to impaired autophagy may trigger inflammatory responses, contributing to the patient’s recurrent fever and elevated cytokines (TNF-α, IL-1β, IL-17 and IL-12p70). These findings align with prior studies linking autophagy defects to skeletal dysplasia [25-26]. This suggests that the balance between autophagy and necroptosis is critical for maintaining cellular homeostasis and preventing the development of diseases. Further studies are needed to elucidate the molecular mechanisms underlying the interplay between autophagy and necroptosis and their role in the development of diseases.\u003c/p\u003e\n\u003cp\u003eUpon structural characterization revealed that the FAM111A variant generates a truncated protein exhibiting structural homology with ubiquitin [33-34], suggesting acquired compensatory ubiquitination functionality. This ubiquitin-like property potentially enhances necroptosis through aberrant modification of death signaling complexes, providing mechanistic insight into the observed clinical phenotype. The truncated FAM111A may disrupt endogenous protease activity, leading to accumulated DNA replication stress and subsequent NLRP3 inflammasome activation. These molecular perturbations collectively explain the dual pathology of elevated necroptosis and cytokine production (IL-1β and TNF-α) [13, 28]. From a therapeutic perspective, modulating autophagy\u0026nbsp;through mTOR inhibitors to alleviate proteostasis imbalance or RIPK1 inhibitors to target necroptosis pathways could potentially rescue osteoclast dysfunction and mitigate bone resorption defects in KCS2-like syndromes.\u0026nbsp;While preclinical validation in murine models remains essential, therapeutic development should ultimately prioritize human-relevant systems. Our findings further highlight the precise roles of FAM111A in bone development and Inflammation modulation via inflammasome crosstalk [14]. Notably, current mechanistic evidence from mouse-derived osteoclasts requires confirmation in patient-derived osteoclasts or even using induced pluripotent stem cells-differentiated osteoclasts.\u003c/p\u003e\n\u003cp\u003eIn summary, our present comprehensive assessment has shed light on the pathogenic potential of the novel FAM111A variant, offering valuable insights into the molecular pathways and cellular mechanisms contributing to KCS2-like syndrome. Genetic testing is conducive to identifying the etiologics. Early intervention based on early diagnosis can improve prognosis. These findings may open new avenues for further research and hold promise for personalized treatment approaches for rare skeletal dysplasia. Specifically, pharmacological modulation of autophagy-necroptosis crosstalk, like targeting necroptosis regulators MLKL or inflammasome components emerges as a novel potential therapeutic strategy to ameliorate bone pathology and inflammatory manifestations in KCS2-like syndrome. Translational studies using patient-derived cell models or animal systems carrying the FAM111A variant are critical next steps to evaluate these interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge and thank the parents of patient for their kindly cooperation and understood with the clinical data collection. We would like to acknowledge Li Peng and Yanlan Zhong for their help with the clinical data collection. We thank all authors who help in the implementation of the experiment: Zhe Cai, Kexin Chen and Suyun Cheng. In addition, we would like to acknowledge and thank Professor Yu Feng, Chun Kwok Wong and \u0026nbsp; Qiming Liu for their reviewing and revising the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Western Medicine-General Guide Item of Guangzhou Municipal Health Commission (No. 20241A011039), the Guangzhou Municipal Science and Technology Bureau Foundation (No. 202201020637), the Research Capacity Improvement Project of Guangzhou Medical University (No. cw02-410-2302143XM and No. cw02-410-2302161XM),\u0026nbsp;the Excellent Young Scholars Project of Ningxia Hui Autonomous Region Natural Science Foundation\u0026nbsp;(No.\u0026nbsp;2021AAC05021), and the Guangdong Medical Science and Technology Research Fund Project (No. A2025077).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Ping Wu, Zhe Cai and Chun Kwok Wong. Investigation: Xue Li, Li Peng, Kexin Chen, Yanlan Zhong, Suyun Cheng, Song Zhang, Wenbo Zhang, Qiming Liu. Validation: Juan Zhou, Chun Kwok Wong and Xue Li. Data curation: Ping Wu, Zhe Cai and Li Peng. Writing original draft: Ping Wu and Zhe Cai. Writing review and editing: Zhe Cai, Yu Feng, Qiming Liu, Chun Kwok Wong. Supervision: Chun Kwok Wong and Zhe Cai.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest relevant to this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study does not involve human or animal samples and does not require ethical approval. This research also does not involve the need to disclose the privacy information of patients and their family.\u0026nbsp;All experiments and samples were performed in accordance with the ethical and biosafety protocols approved by the institutional guidelines. The usage of clinical information in this research has been approved by the child\u0026apos;s parents, who have signed the informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRestrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality. The datasets generated during and analyzed in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eKCS, Kenny-Caffey syndrome; FAM111A, Family with sequence similarity 111 member A; TBCE, Tubulin-specific chaperone E; OMIM, Online Mendelian Inheritance in Man; HGNC, HUGO Gene Nomenclature Committee; EEG, Electroencephalogram; cDNA, complementary DNA; PCR, Polymerase chain reaction; sgRNA, small-guide RNA; CRISPR, Clustered regularly interspaced short palindromic repeats; MC3T3-E1, Murine calvaria 3T3-E1 subclone; HEK, Human embryonic kidney cell line; ATCC, American Type Culture 97 Collection; DMEM, Dulbecco\u0026apos;s Modified Eagle Medium; FBS, Fetal bovine serum; PMA, Phorbol-12-myristate-13-acetate; RANKL, Receptor activator of nuclear factor kappa-\u0026Beta; Ligand; TRAP, Tartrate-resistant acid phosphatase; G-CSF, Granulocyte colony-stimulating factor; IFN\u0026gamma;, Interferon gamma; IL-10, Interleukin-10; IL-12p70, Interleukin-12p70; IL-17, Interleukin-17; IL-1\u0026beta;, Interleukin-1 beta; IL-2, Interleukin-2; IL-23p19, Interleukin-23p19; IL-4: Interleukin-4; IL-6, Interleukin-6; KC, Keratinocyte-derived cytokine; MCP-1, Monocyte chemoattractant protein-1; TNF-\u0026alpha;, Tumor necrosis factor alpha; SDS-PAGE, Sodium dodecyl sulfate polyacrylamide gel electrophoresis; CCL-2, C-C motif chemokine ligand 2; GAPDH, Glyceraldehyde-3-phosphate dehydrogenase; HRP, Horseradish peroxidase; p-MLKL, phosphorylated mixed lineage kinase domain-like; p-JNK, phosphorylated c-Jun N-terminal kinase; LC3BII, Microtubule-associated proteins 1A/1B light chain 3B II; BF, Bright field; FL, Fluorescent field; NC, Negative control; CQ, Chloroquine phosphate; PIP, PCNA-interacting peptide box; UBL1, Ubiquitin-like domain 1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchigt, H. et al. 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Ubiquitin modifications. \u003cem\u003eCell Res.\u003c/em\u003e\u003cstrong\u003e26\u003c/strong\u003e, 399-422 (2016). \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Clinical characteristics of blood diagnostics (n = 12), median (IQR).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasured values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of white blood cells, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e7.58(4.02-14.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4.30-11.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of neutrophils, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e3.85(0-6.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e1.60-7.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of monocytes, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.73(0.01-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.13-0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of lymphocytes, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e2.08(0.43-3.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e1.50-4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of eosinophils, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.10(0.03-0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.00-0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of basophils, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.02(0.01-0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.00-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of red blood cell, 10\u003csup\u003e12\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e4.16(3.46-4.63)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4.20-5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eHaemoglobin, g/l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e121.41(101.00-136.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e118-156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eHematocrit, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e35.39(29.10-38.90)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e36.00-46.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003eMean corpuscular volume, fL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e84.36(80.40-91.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e77-92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eMean hemoglobin amount, pg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e28.90(27.80-30.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eMean hemoglobin concentration, g/l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e343.41(311.00-361.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e310-355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eErythrocyte distribution width -SD, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e38.39(35.00-41.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e35-56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eErythrocyte distribution width -CV,\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e12.40(11.90-13.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e11.50-14.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003eAbsolute number of platelet, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e234.50(167.00-325.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e167-453\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003ePlatelet distribution width, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e10.88(8.40-15.40)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e14.80-17.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eMean platelet volume, fL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e8.93(8.30-9.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e7.60-13.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eLarge platelet ratio, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e15.62(12.20-19.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e13-43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eThrombocytic, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.20(0.15-0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.10-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of neutrophils, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e57.94(9.60-83.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e31-70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of monocyte, (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e11.65(5.00-17.90)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e2-11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of lymphocytes, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e28.87(6.30-50.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e23-59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of eosinophils, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e1.23(0-3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0-9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of basophils, (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.21(0-0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eInfantile granulocyte absolute value, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.03(0.02-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003ePercentage of naive granulocyte, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.52(0.30-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0-0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eReticulocyte absolute value, 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e81.73(66.00-97.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e36.30-195.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eReticulocyte percentage, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e1.98(1.50-2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.82-2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eLow fluorescence intensity reticulocyte ratio, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e92.06(85.00-98.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e87-98.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eImmature reticulocyte ratio, fL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e7.93(2.00-15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e3.10-13.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eMedium fluorescent intensity reticulocyte ratio, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e7.26(1.80-14.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.80-11.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eHigh fluorescence intensity reticulocyte ratio, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e0.66(0.20-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.10-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 323px;\"\u003e\n \u003cp\u003eReticulocyte hemoglobin content, pg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e26.66(25.50-27.60)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e30.30-36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe table shows the statistically significant differences between measurement results and normal range (* p\u0026lt;0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Clinical characteristics of biochemical detection index (n = 12), median (IQR).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"640\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasured values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eAlanine aminotransferase (ALT), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e17.88(11.50-23.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e14-44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eAspartate amino transferase (AST), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e29.34(23.80-62.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e7-30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003er-glutamyltransferase (r-GGT), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e14.86(12.00-18.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e8-58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eAlkaline phosphatase (ALP), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e167.86(128.00-246.00)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e42-140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCholinesterase (CHE), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e7403.50(6183.00-8529.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e5000-12000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCreatine kinase (CK), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e237.63(76.00-628.00)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e15-130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCreatine kinase isoenzyme (CK-MB), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e24.80(16.00-49.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eLactate dehydrogenase (LDH), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e227.75(167.00-325.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e109-245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eAdenosine dehydrogenase (ADA), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e11.58(7.30-15.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eGlutathione reductase (GR), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e59.00(49.00-69.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e34-73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eA-amylase (a-AMY), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e64.14(43.00-88.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e40-132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eA-fucosidase (AFU), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e28.40(24.90-34.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eA-hydroxybutyrate dehydrogenase (a-HBDH), U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e183.40(155.00-249.00)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e72-162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eHomocysteine (HCY), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e5.95(4.80-7.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4-16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCystatin c (CYSC), mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e0.41(0.34-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eTotal protein (TP), g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e63.85(55.40-72.60)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e66-87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eAlbumin (ALB), g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e42.29(37.10-46.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e35-55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eGlobulin (GLO), g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e21.56(17.90-26.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e20-45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eIg A/G, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e1.99(1.61-2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.25-2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eProalbumin (PA), mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e202.14(179.00-223.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e200-400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eTotal bilirubin (TBIL), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e8.17(5.50-10.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e5.10-19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eDirect bilirubin (DBIL), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e2.49(1.10-3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.70-6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eIndirect bilirubin (IBIL), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e5.68(3.60-7.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eTotal bile acid (TBA), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e3.46(1.70-6.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eUrea (UREA), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e3.23(2.11-4.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e2.80-7.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eUric acid (UA), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e287.50(309.00-243.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e208-428\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCreatinine (CRE), \u0026mu;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e35.56(27.00-63.00)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e44-133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eCalcium (Ca), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e2.27(2.02-2.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e2.25-2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003ePhosphorus (P), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e1.29(1.15-1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1.29-2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003ePotassium (K), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e3.65(3.14-4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e3.50-5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eSodium (Na), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e135.59(130.00-143.00)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e136-146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eChlorine (CL), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e104.87(96.80-111.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e98-106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eMagnesium (Mg), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e0.94(0.74-1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.73-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eSerum total carbon dioxide (CO2), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e21.06(17.00-23.90)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e25-35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eGlucose (GLU), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e5.42(3.75-7.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e3.89-6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eTotal cholesterol (CHOL), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e4.33(3.94-4.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e3-5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eTriglyceride (TG), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e0.63(0.36-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.40-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eHigh density cholesterol (HDL-C), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e1.34(1.26-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.83-1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eLow density cholesterol (LDL-C), mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e2.39(2.07-2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eLipoprotein a (LP a), mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e110.26(73.00-158.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eApolipoprotein-A1(APOA1), g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e1.19(1.11-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e1-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eC-reactive protein (CRP), mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e2.44(0.10-3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0-6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 309px;\"\u003e\n \u003cp\u003eProcalcitonin (PCT), ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e0.12(0.03-0.21) \u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e＜0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe table shows the statistically significant differences between measurement results and normal range (* p\u0026lt;0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Clinical characteristics of immune-related index (n = 10), median (IQR).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"573\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 303px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasured values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eIgG, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e8.87(7.00-12.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.82-10.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eIgA, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.65(0.27-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.14-1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eIgM, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e1.15(0.90-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.40-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eIgE, IU/ML\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e76.53(59.00-88.60)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0-60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eC3, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.94(0.74-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.80-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eC4, g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.10(0.06-0.17)\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.13-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eB lymphocytes (CD19\u003csup\u003e+\u003c/sup\u003e), (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e14.6 (10.90-18.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5-18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCD15\u003csup\u003e+\u003c/sup\u003e B1 lymphocytes (CD15\u003csup\u003e+\u003c/sup\u003eCD19\u003csup\u003e+\u003c/sup\u003e), (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e46.75 (39.90-53.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e14.98-53.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eMyeloperoxidase antibody, RU/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.15 (0-0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e＜20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 340px;\"\u003e\n \u003cp\u003eProtease 3 antibody (PR3), RU/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e0.25 (0.10-0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e＜20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe table shows the statistically significant differences between measurement results and normal range (* p\u0026lt;0.05). The measurement results with red color are the values higher than normal range. The blue ones are lower than normal range. The black ones are in the normal range.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Clinical characteristics of cytokines (n = 3), median (IQR).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"569\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasured values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-5, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e1.50 (0.04-2.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0-8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-17, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e6.22 (5.29-7.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0-19.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-1\u0026beta;, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e5.30 (2.99-7.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-12.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-2, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e1.59 (0.39-2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-8.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-4, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e2.90 (1.11-4.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-11.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-6, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e3.62 (3.28-3.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-7.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-8, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e6.17 (3.61-8.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-62.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-10, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e2.91 (1.74-4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-9.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIL-12p70, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e2.27 (1.63-2.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-8.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eTNF-\u0026alpha;, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e1.77 (0.4-3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-8.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIFN-\u0026gamma;, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e1.61 (0.38-2.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-16.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 232px;\"\u003e\n \u003cp\u003eIFN-\u0026alpha;, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e2.18 (0.65-3.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e0-13.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe table shows the statistically results of measured values and normal range.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"FAM111A, Kenny-Caffey syndrome type II, Osteoclast, Necroptosis, Autophagy","lastPublishedDoi":"10.21203/rs.3.rs-7188681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7188681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eKenny-Caffey syndrome type II (KCS2) is a rare genetic disorder characterized by skeletal abnormalities, impaired growth, and developmental delay. This study investigates a novel heterozygous FAM111A variant’s role in a patient presenting with KCS2-like features.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e An 11-year-old patient with clinical features consistent with KCS2-like syndrome underwent whole exome sequencing, which identified a novel heterozygous variant in FAM111A gene. \u003cem\u003eIn vitro\u003c/em\u003eexperiments and protein structure analysis were performed to elucidate the contribution of this mutation to KCS2-like syndrome.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e To confirm the diagnosis, whole exome sequencing revealed a novel heterozygous variant (c.405delA/p.E136Sfs*3) in FAM111A gene in an 11-year-oldpatient. Additionally, we found the clinical features of this patient were consistent with KCS2-like syndrome. Our \u003cem\u003ein vitro\u003c/em\u003e studies revealed that the variant led to a significant increase in necroptosis of osteoclasts. Furthermore, variant osteoclasts displayed a significant down-regulation of autophagy, which may contribute to the onset of KCS2-like syndrome. Consequently, the augmented necroptosis may result in the up-regulation of inflammatory cytokines such as IL-1β, IL-17, IL-12p70, MCP-1, IFN-γ and TNF-α. Protein structure analysis suggests that the truncated FAM111A (p.E136Sfs*3) retains a ubiquitin-like domain, which might explain the up-regulated ubiquitination in variant osteoclasts. Therefore, the enhanced ubiquitination in variant osteoclasts may lead to the excessive degradation of intracellular proteins, resulting in irreversible necroptosis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e Our findings suggest that the novel variant FAM111A (c.405delA) may be a pathogenic factor in KCS2-like syndrome, likely through mechanisms involving increased necroptosis and inflammation. This expands understanding of FAM111A variant’s role in skeletal and immune dysregulation.\u003c/p\u003e","manuscriptTitle":"A novel FAM111A frameshift variant associated with osteoclast necroptosis and KCS2-like syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 06:27:25","doi":"10.21203/rs.3.rs-7188681/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ae8980b0-2620-410c-bbba-bb3ac2dd51c2","owner":[],"postedDate":"September 15th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject Without Review","date":"2026-05-19T02:58:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T07:37:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-15 06:27:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7188681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7188681","identity":"rs-7188681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}