Estimation of hereditary fructose intolerance prevalence in Chinese population

Estimation of hereditary fructose intolerance prevalence in Chinese population | 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 Estimation of hereditary fructose intolerance prevalence in Chinese population Meiling Tang, Xiang Chen, Qi Ni, Yulan Lu, Bingbing Wu, Huijun Wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1588804/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Hereditary fructose intolerance (HFI) caused by aldolase B (ALDOB) reduction or deficiency is a rare inherited autosomal recessive (AR) disease that results in fructose metabolism disorder. The disease prevalence in the Chinese population is unknown, which leads to the lack of basis for the formulation of HFI screening and diagnosis strategy. Materials & Methods: From searching local cohort (Chinese Children’s Rare Disease Genetic Testing Clinical Collaboration System, CCGT), public databases (ClinVar and HGMD) and reviewing HFI-related literature (PubMed and Web of Science), we manually curated ALDOB pathogenic or likely-pathogenic (P/LP) variants according to ACMG guidelines. Allele frequency (AF) information from local CCGT, HuaBiao, and gnomAD database for ALDOB P/LP variants were used to estimate and the HFI prevalence in Chinese and other populations by the Bayesian framework. We collected the genotype and clinical characteristics of HFI patients from the CCGT database and published literature to study genotype-phenotype relationships. Result: In total 81 variants from ALDOB were curated as P/LP. The estimated Chinses HFI prevalence is approximately 1/504,678, which is similar to gnomAD-AFR (1/412,335) and SAS (1/465,278) population and much lower than NFE (1/23,147), FlN (1/55,539), AMR (1/132,801) and ASJ (1/263,150) populations. By analyzing the genetic characteristics of ALDOB in Chinese population, two variants (A338V, A338G) had significantly higher AF in Chinese population by comparing to NFE populations from gnomAD (all P-value<0.05). Five variants (A150P, A175D, N335K, R60*, R304Q) had significantly lower AF (all P-value<0.1). The results of genotype-phenotype association showed that patient carrying homozygous variant sites (especially A150P) were more likely to present nausea, and patient carrying two missense variant sites were more likely to present aversion to sweets and fruit (all P-value<0.05). Our research reveals that some gastrointestinal symptoms seem to be associated with genotypes. Conclusion: Chinese population had extremely low prevalence of HFI, with no need to add in current newborn screening project if consider medical costs. Genetic test strategy was suggested for early diagnoses. Hereditary fructose intolerance prevalence estimation curation for pathogenic variants newborn screening allele frequency comparison Figures Figure 1 Figure 2 Figure 3 Introduction Hereditary fructose intolerance (HFI) is a rare inherited autosomal recessive (AR) disease that caused by pathogenic variants in the aldolase enzyme, B isoform gene ( ALDOB ), which led to the fructose-1,6-bisphosphate aldolase B (aldolase B) reduction or deficiency that resulting in fructose metabolism disorder[ 1 ]. Fructose is a monosaccharide like glucose that was the dominant composition of candy, fruits and honey. It is also a metabolic intermediate of sucrose and sorbitol. Therefore, patients with HFI develop symptoms when they are exposed to fructose, sucrose or sorbitol[ 2 ]. The predominance of liver, kidney, and small intestine in fructose metabolism is based on the presence of the three enzymes (fructokinase, aldolase B and triokinase), which convert fructose into intermediates of the glycolytic–gluconeogenic pathway (fructose pathway)[ 3 ]. The fructokinase (ketohexokinase, KHK) could splits fructose to fructose-1-phosphate (F-1-P), and aldolase B which splits F-1-P into dihydroxyacetone phosphate and glyceraldehyde in the liver, small intestine and proximal renal tubule[ 4 , 5 ]. The deficiency of aldolase B could lead to the toxic accumulation of F-1-P and causes multiple clinical manifestation, including nausea, vomiting, hypoglycemia, metabolic acidosis, liver dysfunction, and abnormal renal function[ 6 ]. As special diet (withdrawal of all sources of fructose, like food, drugs, parenteral infusions and so on) could help to avoid severe complications, early diagnosis can help a lot to improve the prognoses of patients, and serious complications can be avoided. The preference of HFI is approximately 1:23,000 in British and 1:20,000 in Switzerland[ 7 ], 1:26,100 in Germany[ 8 ], 1:31,000 in Polish[ 9 ], 1:34,483 in Northwest Russia and so on[ 10 ]. In general, the prevalence in European population is about 1:31,000 to 1:18,000[ 11 ]. The HFI prevalence of Chinese population is remain elusive. Therefore, it is essential to estimate the prevalence of HFI and to evaluate whether HFI screening in newborn babies is necessary. Nowadays, neonatal screening includes congenital adrenal hyperplasia (CAH, 1:20,000–1:10,000), phenylketonuria (PKU, 1:11,800), glucose-6-phosphate dehydrogenase deficiency (G-6-PD deficiency, 1:434) and congenital hypothyroidism (CH, 1:1,059) in China[ 11 , 12 ]. Among them, CAH and PKU are rare diseases in China, and their average prevalence is about 1:12,520. China has released 121 kinds of rare diseases, most of which (98.3%) are not included in neonatal screening[ 11 ]. Among these rare diseases, if many diseases can be diagnosed early, like HFI, the prognosis of patients will be particularly excellent. We hope to analyze the data in real-world and provide suggestions in newborn screening strategies and carrier screening of HFI parents. Newborn screening for HFI may lead to benefit to early diagnosis and treatment. Until now, the relationship between genotype and phenotype of HFI is unknown. Davit-Spraul et al. studied 162 patients from 92 families with HFI and found 16 mutations in the ALDOB gene. They collected the clinical symptoms of the 10 probands, conventional tests (Fructose load, Hepatic aldolase B activity detection), variant sites, age, family history and so on. There was no significant genotype/phenotype correlation to the 10 families[ 13 ]. Mehmet Gunduz et al. retrospectively analyzed a cohort with 26 HFI patients[ 6 ]. They collected the patient's age, clinical symptoms, metabolic crisis history and variant sites. They also found no clear correlation between genotype and phenotype. Previous studies generally believe that no genotype-phenotype correlations have been identified for HFI; clinical severity and extent of organ damage appear to depend on an individual's nutritional environment[ 14 ]. So, in this study, we tried to expand the sample size, and study the relationship between variant site, mutation type, zygosity and phenotype at the same time. HFI diagnosis is based on genetic test. As there are no readily available biochemical markers that are not exposed to fructose[ 1 ]. Therefore, molecular screening for the most common mutations can be a cost-effective way to identify screen out individuals highly suspected as HFI. After literature review, we found the different population had different pathogenic hotspots in ALDOB . Missense mutations A150P and A175D are the two most common alleles in the United States of America, Germany, Italy, United Kingdom, France, Poland et al; A175D and R60* in Poland, A150P and N120Kfs*32 in Spain, N335K and A150P in Australia. Indian population is much complex and had several variants with high allele frequency (AF) including c.112 + 1delG, c.324 + 1G > A, c.380-1 G > A et al[ 15 ]. The AF characteristics of pathogenic or likely-pathogenic (P/LP) ALDOB variants in Chinese population are still intriguing. We tried to estimate the prevalence of HFI in Chinese population, summarize the genotype-phenotype correlation, analyzed the genetic characteristics of ALDOB and evaluate the necessity of newborn screening in Chinese population. We hope our research can be conducive to genetic counseling and provide useful information for neonatal genetic screening and carrier screening strategies. Results Curation of pathogenic variants in ALDOB gene and allele frequency analysis After pathogenicity assessment of ALDOB variants which recruited from public database including ClinVar, HGMD, and PubMed (no additional findings in Web of Science), 81 P/LP variants were identified ( Additional file 1: Table S1 ), containing missense (26%, 21/81), frameshift (22%, 18/81), splicing (21%, 17/81), nonsense (15%, 12/81), inframe indel (6%, 5/81), indel (2%, 2/81), CNV (2%, 2/81), stop lost (1%, 1/81), start lost (1%, 1/81), synonymous (1%, 1/81) and 3’-UTR variants (1%, 1/81). Among 81 P/LP variants, 24 variants had reported allele frequency (AF) in general populations from public databases (Fig. 2 , Additional file 1: Table S2 ). So, we analyzed the AF of these variants in different population to detect the genetic characteristics of ALDOB in Chinese population. In total, two variants (A338V, A338G) had significantly higher AF in Chinese population by comparing to NFE population (all P-value < 0.05), and five P/LP variants (A150P, A175D, N335K, R60*, R304Q) had significantly lower AF (all P-value < 0.01) in Chinses population. The most frequent P/LP site in the gnomAD-TOTAL (all populations in gnomAD) is A150P (1:323), and it is also the most frequent site in admixed American (AMR, 1:714), Finnish in Finland (FIN, 1:244) and non-Finland European (NFE, 1:189). The hotspot detected in this study is consistent with previous study[ 15 ]. However, the frequency is low in the Chinese Children's Rare Disease Genetic Testing Clinical Collaboration System (CCGT) Children Cohort (1:20,833). In addition, A150P was not recorded in the CCGT Parent’s Cohort and HuaBiao database. A338V is the most common variant site in Chinses population (HuaBiao is 1:1,408, CCGT Children is 1:1,887 and Parent is 1:1,538), it is also the most frequent site in African American (AFR, 1:3,226), South Asian (SAS, 1:1,010) and East Asian (EAS, 1:1,563). This variant was not reported in Ashkenazi Jewish (ASJ), FIN and AMR. A338G is the second high-frequency pathogenic site in Chinese population (HuaBiao is 1:1,408, CCGT Children is 1:8,333 and Parent is 1:6,667). N120Kfs*32 is the third high-frequency variant in Chinese population (CCGT Children is 1:3,226 and Parent is 1:6,667). The AF of N120Kfs*32 in Chinese population was slightly higher than AFR (1:8,333), AMR (1:13,699) and NFE population (1:21,739) (all P-value > 0.05). These results showed that Chinese population has special characteristics in ALDOB variants, especially different from Caucasians (NFE). Estimation of HFI prevalence in Chinese population We estimated the HFI prevalence based on 20,919 pediatric patients as CCGT Children Cohort (12,783 males and 8,136 females) and 10,031 parental samples as CCGT Parent’s Cohort (5,006 males and 5,024 females). The total number of individuals carrying P/LP ALDOB variants in Children Cohort is 61 people (36 males and 25 females) and 27 people (11 males and 16 females) in Parent’s Cohort. Based on those results, the estimated HFI prevalence in Chinese population is between 1/470,416 to 1/462,233 in Children Cohort and 1/571,594 to 1/532,412 in Parent’s Cohort by three strategies. Specially, the estimated prevalence of HFI by Bayesian framework was 1/462,839 (95% confidence interval 1/803,692 ~ 1/293,567) in Children Cohort and 1/532,412 (95% confidence interval 1/1,270,634 ~ 1/277,464) in Parent’s Cohort. Totally, the estimated prevalence of the Chinese population is 1/504,678 by averaging all the above results (Table 1 ). The prevalence in HuaBiao (1/410,068) and EAS (1/818,758) were similar ( Additional file 4: Table S7 ). For the result of HFI prevalence estimation by Bayesian framework in other gnomAD populations, the prevalence is 1/23,147 (95% confidence interval 1/28,182 to 1/19,278) in NFE population, 1/55,539 (95% confidence interval 1/107,444 to 1/32,816) in FIN population, 1/132,801 (95% confidence interval 1/274,861 to 1/75,230) in AMR population, 1/263,150 (95% confidence interval 1/2,275,631 to 1/81,267) in ASJ population, 1/412,335 (95% confidence interval 1/702,621 to 1/264,931) in AFR population and 1/465,278 (95% confidence interval 1/7,821,624 to 1/121,173) in SAS population (Fig. 3 , Additional file 4: Table S7 ). Based on these results, we found the prevalence in Chinese population is much lower than other populations, especially lower than Caucasians (NFE). Table 1 HFI prevalence estimation in Children cohort and Parent’s cohort with estimated affected frequency by three methods CCGT Children Cohort CCGT Parent’s Cohort Total number 20919 10031 Gender (Male/Female) 12783/8136 5006/5024 Carrier with P/LP variants (Male/Female) 61 (36/25) 27(11/16) Carrier frequency 1/342 1/371 Couple’s carrier risk 1/117604 1/138026 Method 1: carrier frequency 1/470416 1/552104 Method2: permutation & combination 1/462233 1/571594 Method 3: Bayesian framework (95% CI) 1/462839 (1/803692 ~ 1/293567) 1/532412 (1/1270634 ~ 1/277464) Average 1/465133 1/551573 Estimated HFI frequency 1/504678 Diagnosed children in CCGT database We diagnosed three HFI patients in CCGT database. Patient 1 presented vomiting immediately after feeding with infant formulas. Hunger and poor complexion occurred after eating sweets. Since her parents stop feeding sugary food at three years old, she did not present surgery related gastrointestinal phenotypes. She could speak at seven months old, and walk at two years old. She is now 174.6cm, and BMI is 18.4. The diagnosis was confirmed by genetic testing at the age of 30. She had compound heterozygous variants in the ALDOB gene: one pathogenic missense (c.1013C > T, p.A338V) from father and one frameshift (c.360_363delCAAA, p.N120Kfs*32) variant from mother[ 16 ]. Patient 2 was a one-year-old girl. She has been breastfeeding soon after birth. At 8 months old, she began mixed feeding of infant diet and breastfeeding. Vomiting occurred immediately after eating infant diet. Since her mother stop feeding infant diet, the vomiting can be relieved. The genetic diagnosis was confirmed by genetic testing at the age of 8 months. Gene analysis revealed pathogenic nonsense (c.888G > A, p.W296*) from father and missense (c.1013C > T, p.A338V) variant from mother. After early dietary guidance, her abnormal liver function tests and hepatomegaly disappeared when she was 10 months old. Patient 3 was a three-year-old little girl. After a week of breastfeeding, she presented jaundice, lethargy, metabolic acidosis, anemia, thrombocytopenia, and acute liver failure were found. Her symptoms began to improve after the fructose free diet, with normalization of liver function tests within one week. Genetic testing showed compound heterozygous variants for pathogenic frameshift (c.673_674delinsA, p.E225Rfs*5) and splice acceptor (c.325-1G > A) variant in ALDOB . She remains well with normal growth and development at the time of interview (3 years old). The genotype-phenotype relationship in 68 HFI patients Totally, we collected 68 HFI patients including the three patients mentioned above and additionally searching ClinVar, HGMD and published papers ( Additional file 2: Table S3) . We analyzed the relationship between phenotype and variant site, mutation type, zygosity respectively. Most symptoms were onset in infancy after weaning (94%, 15/16) and symptoms can be prevented by strict dietary restriction (100%, 21/21). Gastroenteric and liver phenotype were the dominant phenotype in HFI patients. We found that 34 patients hate sweets and fruit (87%, 34/39), 31 patients presented vomiting (78%, 31/40), 19 patients presented nausea (54%, 19/35), and 22 patients presented hepatomegaly (59%, 22/37). For each variant-phenotype analysis, we found that patients carrying A150P (homozygote) were more likely to present nausea than combination of other variant sites (P-value < 0.05, Additional file 3: Table S4) . No other variants-phenotype relationship was detected. The mutation types of 68 HFI patients were classified into missense, frameshift, nonsense, splicing and inframe indel in our study ( Additional file 3: Table S5 ). For mutation type-phenotype analyses, we found that patient carrying two missense variant sites were more likely to present aversion to sweets and fruit (P-value < 0.05). For zygosity-phenotype analyses, patients carrying homozygous variant sites were more likely to present nausea (P-value < 0.05) by Chi-square test ( Additional file 3: Table S6 ). The other mutation type-phenotype and zygosity-phenotype relationship were not detected. Discussion In this study, we estimated the prevalence in Chinese population based on public databases and internal database. We found the HFI prevalence in Chinese population and some other East Asia populations is extremely low. The prevalence is especially much lower than Caucasian populations. HFI has not been included in newborn screening plan in any country. Based on the low prevalence, we still recommended not to put it into newborn screening in Chinese population. PKU is a disease that has been included in China's Neonatal Screening Plan. PKU and HFI are both metabolic AR diseases. And the prevalence of PKU varies worldwide, with an average of 1:10,000 newborns[ 25 ]. It is significantly higher than HFI (1/10,000 vs. 1/504,678, P-value < 0.05). However, HFI has good prognoses with diet control, we highly recommended early genetic diagnoses for those patients with suspension. To provide a more precise strategy for HFI early diagnoses, we summarized the phenotype spectrum of 68 HFI patients. We found digestive phenotype were the dominant feature. So, we suggested four typical symptoms in work-flow of HFI diagnoses: 1) vomiting and nausea after eating food or medicine contains fructose; 2) aversion to sweets and fruit; 3) abnormal liver function tests; 4) symptoms can be prevented by withdrawal of all sources of fructose. As fructose malabsorption (FM) and fructose-1,6-bisphosphatase deficiency (FBPase deficiency) had similar phenotype with HFI that gastrointestinal symptoms are onset in infancy after weaning and can be prevented by strict dietary restriction. The differential diagnoses could be very difficult according to clinical phenotype. FBPase deficiency is an inherited disease caused by FBP1 gene mutation[ 2 ]. It is in autosomal recessive manner. WES can help to identify which kind of fructose diseases and exclude other metabolic diseases. However, WES is not cheap enough to be used as first-line diagnostic method. In addition, the symptoms of these three diseases can be easily controlled by fructose avoidance. So, we tried to establish a cost-effective variants panel for HFI diagnosis. The rapid high-frequency site screening panel contains ten high-frequency sites including A338V, N120Kfs*32, A338G, W296*, E225Rfs*5, R304W, A150P, c.325-1G > C, L289Ffs*10 and Q111*. These variants were identified as top 10 variants with high AF in CCGT pediatric cohort and cover about 90% of Chinese pediatric patients. By applying this panel test, time and expenditure could be reduced in a large degree. The specificity and sensitivity need to be verified in large healthy children’s cohorts. HFI is a genetic metabolic disease, and digestive system symptoms are the dominant phenotype recognized by most researchers[ 17 ]. We diagnosed three patients, with gastrointestinal phenotypes. By integrating the information from 68 patients, we found that gastroenteric and liver phenotype were the dominant phenotype. A150P was identified to related to nausea. The function of A150P in unclear. ALDOB sequence is generally highly conserved, but A150 is located in non-conserved area. So, the detected relationship of A150P with nausea by due to that this is a common variant[ 8 ]. The functional study is needed to confirm the relationship. We also found two missense variant sites were related to aversion to sweets and fruit and homozygous variant sites were related to nausea. Two missenses pattern (44/68, 65%) and homozygous pattern (35/68, 51%) are the main mutation type in 68 HFI patients. So, we thought these relationships may indicate the characteristics of ALDOB variants. Fructose metabolism in liver, kidney and intestine requires the synergistic action of two enzymes. In physiological states, fructokinase phosphorylates fructose into F-1-P, and aldolase B decomposes F-1-P into dihydroxyacetone phosphate and glyceraldehyde. The mutation of ALDOB could reduce the aldolase B activity and the accumulation of F-1-P. This leads to deficiency of phosphate and adenosine triphosphate (ATP) and increase of uric acid[ 17 , 21 ]. The renal manifestation of HFI have been reported[ 6 , 18 – 20 ]. This may indicate that kidney could be damaged in HFI. One patient with proximal tubular acidosis was also reported[ 22 ]. However, the characteristics of renal phenotypes of HFI have not been summarized. CCGT is not a healthy people cohort and genotype frequency of CCGT does not correspond with the Hardy-Weinberg equilibration[ 24 ]. So, we applied HuaBiao and gnomAD-EAS database to mimic the healthy and natural gathered population. The estimated prevalence is similar and indicate that CCGT could be used to present the genotype and phenotype characteristics of HFI. With more detailed information, we hope to update the HFI diagnose strategy in the further. Conclusions Chinese population had extremely low prevalence of HFI, with no need to add in current newborn screening project if consider medical costs. Genetic test strategy was suggested for early diagnoses, especially for patients with typical symptoms. The curated variant panel can assist the choice for quick and cheap diagnosis in China. Materials And Methods Data acquisition for Chinese population data This study was approved by the ethics committees of Children's Hospital of Fudan University (2021 − 464). The local CCGT cohort was the same as in our previously study and the detailed processing steps can be found in the study[ 24 ]. Briefly, counselling and informed consents were obtained from the parents of patients. Each individual received whole exome sequencing (WES) or clinical exome sequencing (CES), both covered the exon region and exon-intron splicing junction region (deep intron to 15 bp) of ALDOB genes. Both tests were sequenced on the Illumina HiSeq X10 with 150 bp pair-end. The genetic diagnosis of HFI was performed according to ACMG guideline by experience clinicians and genetic counselors. One parent was diagnosed with special requirement. For the HFI prevalence estimation, Children and parents with genetic diagnosis of HFI, together with their family members, were excluded. Literature search of HFI-related studies PubMed and Web of Science were searched using the terms “Hereditary fructose intolerance”, “Hereditary fructose intolerance and case report”, “ ALDOB mutation”, “ ALDOB variant” between 1988 (first described pathogenic variant) and October 2021[ 15 ]. We applied strict literature inclusion criteria to make a more accurate conclusion. Our literature inclusion criteria: 1) literature about case report and the nomenclature of mutation sites meets the requirements of HGVS[ 31 ]; 2) the sites of case report were evaluated as P/LP according to ACMG guidelines; 3) the literature included in SCI (represents high-quality literature). Exclusion criteria: 1) lack of information of mutation sites or the nomenclature of mutation sites; 2) lack of clinical information; 3) repeated cases. According to those criteria, a total of 711 articles were found, of which 17 were included in this study[ 1 , 6 , 13 , 20 , 26 , 32 – 43 ]. Curation of P/LP variants in ALDOB gene We included reported pathogenic variants of ALDOB gene from ClinVar (level P or LP), HGMD (level DM or DM?) and HFI-related literatures mentioned above. No new variants were reported in CCGT database. These variants were curated by two clinical geneticists back-to-back and after manually check, 81 out of 86 variants were curated as P/LP level ( Additional file 1: Table S1 ). Collection of the other populations data The AF of ALDOB gene in other populations were available from the gnomAD database. AFR, AMR, ASJ, FIN, NFE, SAS and EAS population in gnomAD were included ( Additional file 1: Table S1 ). Gene annotation was from GENCODE, with ID (ENSG00000136872, ENST00000374855). Estimation of HFI prevalence in Chinese population We estimate the HFI prevalence by three strategies as described in our previous studies[ 24 ]. Method 1 was based on the carrier frequency of the two cohorts individuals calculated by Hardy Weinberg principle[ 15 ]. Method 2 was based on permutation & combination[ 24 ]. In this strategy, the hypothesis is to calculate the probability of affected child by random choosing a male individual who carrying P/LP variant in ALDOB gene and a female individual who also carrying P/LP variant in ALDOB gene. Method 3 was based on Bayesian framework with gnomAD allele count dataset, where 95% confidence interval could be estimated[ 44 ]. The third strategy was also adopted to estimate HFI prevalence in other populations with only allele count ( Additional file 4: Table S3 ). Data acquisition and processing for the study of genotype-phenotype relations We collected the genotype and clinical characteristics of HFI patients from CCGT and HFI-related literatures mentioned above to study genotype-phenotype relationships. After manually check, 68 HFI patients were included ( Additional file 2: Table S3 ). Here, the 24 common clinical manifestations are inferred from OMIM database. The variants were further grouped by their mutation type, zygosity. Fisher’s Exact Test and Chi-square test were applied to testify whether one phenotype was over-represented in one type of mutations compared with the others. Statistical analyses All statistical analysis was performed by R version 3.6.1. Chi-square test (λ2.test) was used for AF comparison. Multiple-test was adjusted by “bonferroni” strategy. Abbreviation HFI: hereditary fructose intolerance; ALDOB: aldolase enzyme, B isoform; AR: autosomal recessive; CCGT: Chinese Children's Rare Disease Genetic Testing Clinical Collaboration System; AF: allele frequency; AFR: African American; ASJ: Ashkenazi Jewish; NFE: non-Finland European; FIN: Finnish in Finland; AMR: admixed American; SAS: South Asian; EAS: East Asian; CES: clinical exome sequencing; P/LP: pathogenic/likely pathogenic; VUS: variant of unknown significance; ATP: adenosine triphosphate; PKU: Phenylketonuria; CAH: congenital adrenal hyperplasia; G-6-PD: glucose-6-phosphate dehydrogenase; CH: congenital hypothyroidism; TAT: turnaround time; WES: whole exome sequencing; KHK: ketohexokinase. Declarations Availability of data and materials statements The data that support the findings of this study are either included in the article (or in its supplementary files) or available from the corresponding author on reasonable request. The data are not publicly available due to privacy or ethical restrictions. Acknowledgements We are very grateful to the patients and their families for their trust in our laboratory. Thank the bioinformatics team members of our laboratory for their data analysis. Ethics approval and consent to participate This study was approved by the ethics committee of Children's Hospital of Fudan University. Informed consent was signed by the patient's parents in the clinic or ward. The study was conducted in accordance with the guidelines of the Helsinki declaration. Consent for publication All the patients included signed the consent for publication. Competing interests The authors declare that they do not have a conflict of interest. Funding This work was supported by grants from National Key Research and Development Program (2020YFC2006402), Clinical Research Plan of Shanghai Hospital Development Center (SHDC2020CR6028-002) and Shanghai Municipal Science and Technology Major Project (Grant No. 20Z11900600). Contributions Xinran Dong and Wenhao Zhou designed the study. Xinran Dong, Qi Ni and Yulan Lu interpreted medical exome/genome results and conducted analysis on the aggregated large cohort data. Meiling Tang, Xiang Chen, Bingbing Wu, Huijun Wang and Zhaoqing Yin collected, supervised, and reviewed the clinical data. Meiling Tang and Xiang Chen wrote the original manuscript draft. Xinran Dong and Wenhao Zhou supervised the study, critically reviewed, and revised the manuscript for important intellectual content. All authors reviewed the draft and approved the decision to submit for publication. References Li H, et al. Acute liver failure in neonates with undiagnosed hereditary fructose intolerance due to exposure from widely available infant formulas. Mol Genet Metab. 2018;123(4):428–32. Mayatepek E, Hoffmann B, Meissner T. Inborn errors of carbohydrate metabolism. Best Pract Res Clin Gastroenterol. 2010;24(5):607–18. Tran, et al. Inborn Errors of Fructose Metabolism. What Can We Learn from Them? Nutrients, 2017. 9(4). Kim MS, et al. Hereditary Fructose Intolerance Diagnosed in Adulthood. Gut Liver. 2021;15(1):142–5. Cano A, et al. Transferrin Isoforms, Old but New Biomarkers in Hereditary Fructose Intolerance . J Clin Med, 2021. 10(13). Gunduz M, et al. Molecular and clinical findings of Turkish patients with hereditary fructose intolerance. J Pediatr Endocrinol Metab. 2021;34(8):1017–22. James CL, et al. Neonatal screening for hereditary fructose intolerance: Frequency of the most common mutant aldolase B allele (A149P) in the British population. J Med Genet. 1996;33(10):837–41. Santer R, et al. The spectrum of aldolase B (ALDOB) mutations and the prevalence of hereditary fructose intolerance in Central Europe. Hum Mutat. 2005;25(6):594. Gruchota J, et al. Aldolase B mutations and prevalence of hereditary fructose intolerance in a Polish population. Mol Genet Metab. 2006;87(4):376–8. Barbitoff YA, et al. Whole-exome sequencing provides insights into monogenic disease prevalence in Northwest Russia. Mol Genet Genomic Med. 2019;7(11):e964. Guidelines for diagnosis and treatment of rare diseases . Family medicine, 2019. 3(5): p. 1–780. Li Xueqin YZ. Discussion on the clinical application of four screening items of neonatal diseases in three regions of Sichuan Province. J Prev Med Inform. 2019;35(11):1286–93. Davit-Spraul A, et al. Hereditary fructose intolerance: Frequency and spectrum mutations of the aldolase B gene in a large patients cohort from France—Identification of eight new mutations. Mol Genet Metab. 2008;94(4):443–7. Gaughan S, Baker AL. PR II. Hereditary Fructose Intolerance.2015 Dec 17 [updated 2021 Feb 18]. In: Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Gripp KW, Mirzaa GM, Amemiya A, editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993–2022. PMID: 26677512. . Pinheiro FC, Sperb-Ludwig F, Schwartz IVD. Epidemiological aspects of hereditary fructose intolerance: A database study. Hum Mutat; 2021. Qin Qian CX, et al. Hereditary fructose intolerance caused by complex heterozygous variation of ALDOB gene diet control for 30 years: a case report and literature review. Chin J Evid Based Pediatr. 2018;13(4):269–74. Buziau AM, et al. Recent advances in the pathogenesis of hereditary fructose intolerance: implications for its treatment and the understanding of fructose-induced non-alcoholic fatty liver disease. Cell Mol Life Sci. 2020;77(9):1709–19. Caciottia A, Andrea MAD. Adami. Different genotypes in a large Italian family with recurrent hereditary fructose intolerance. Eur J Gastroenterol Hepatol. 2008;20(2):118–20. Rita, Santamaria, et al. Novel six-nucleotide deletion in the hepatic fructose-1,6-bisphosphate aldolase gene in a patient with hereditary fructose intolerance and enzyme structure-function implications. Eur J Hum Genet. 1999;7:409–14. Coffee EM, Tolan DR. Mutations in the promoter region of the aldolase B gene that cause hereditary fructose intolerance. J Inherit Metab Dis. 2010;33(6):715–25. KOGUT MAURICED, et al. Fructose-induced Hyperuricemia: Observations in Normal Children and in Patients with Hereditary Fructose Intolerance and Galactosemia. Res: Pediat; 1975. pp. 774–8. Lameire, et al. Hereditary fructose intolerance: a difficult diagnosis in the adult. Am J Med. 1978;65::416–23. Hao M, et al. The HuaBiao project: whole-exome sequencing of 5000 Han Chinese individuals. J Genet Genomics. 2021;48(11):1032–5. Qi Ni XC, et al. Systematic estimation of cystic fibrosis prevalence in Chinese and genetic spectrum comparison to Caucasians. Orphanet J Rare Dis. https://doi.org/10.1186/s13023-022-02279-9 , 2022: 1–11. van Spronsen FJ, et al. Phenylketonuria Nat Rev Dis Primers. 2021;7(1):36. Chi ZN, et al. Clinical and genetic analysis for a Chinese family with hereditary fructose intolerance. Endocrine. 2007;32(1):122–6. Richards S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–24. Choi HS. C.Q, et al. Molecular diagnosis of hereditary spherocytosis by multi-gene target sequencing in Korea: matching with osmotic fragility test and presence of spherocyte. Orphanet J Rare Dis. 2019;14(1):114. Retterer K. J.J, et al. Clinical application of whole-exome sequencing across clinical indications. Am Coll Med Genet Genomics. 2016;18(7):696–704. Esposito G, et al. Hereditary fructose intolerance: functional study of two novel ALDOB natural variants and characterization of a partial gene deletion. Hum Mutat. 2010;31(12):1294–303. den Dunnen JT, et al. HGVS Recommendations for the Description of Sequence Variants: 2016 Update. Hum Mutat. 2016;37(6):564–9. Coffee EM, et al. Increased prevalence of mutant null alleles that cause hereditary fructose intolerance in the American population. J Inherit Metab Dis. 2010;33(1):33–42. Caciottia A, et al. Different genotypes in a large Italian family with recurrent hereditary fructose intolerance. Eur J Gastroenterol Hepatol. 2008;20:118–21. Kim AY, et al. Pitfalls in the Diagnosis of Hereditary Fructose Intolerance . Pediatrics, 2020. 146(2). Esposito G, et al. Six novel alleles identified in Italian hereditary fructose intolerance patients enlarge the mutation spectrum of the aldolase B gene. Hum Mutat. 2004;24(6):534. Nicholas CP, Cross DRT, Cox TM. Catalytic deficiency of human aldolase B in hereditary fructose intolerance caused by a common missense mutation. Cell. 1988;53:881–5. Santamaria R, et al. Molecular basis of hereditary fructose intolerance in Italy-identification of two novel mutations in the aldolase B gene. JMed Genet. 1996;33:786–8. M.AIi, GS.a.T.M.C. Identification of a novel mutation (Leu 256—Pro) in the human aidolase B gene associated with hereditary fructose intolerance. Hum Mol Genet. 1994;3:203–4. Tolan CD. a.D.R, Molecular evidence for compound heterozygosity in hereditary fructose intolerance . Am J Hum Genet. 1990;46:1194–9. Ferreira CR, et al. Hereditary fructose intolerance mimicking a biochemical phenotype of mucolipidosis: A review of the literature of secondary causes of lysosomal enzyme activity elevation in serum. Am J Med Genet A. 2017;173(2):501–9. Valadares ER, et al. Hereditary fructose intolerance in Brazilian patients. Mol Genet Metab Rep. 2015;4:35–8. Bijarnia-Mahay S, et al. Molecular Diagnosis of Hereditary Fructose Intolerance: Founder Mutation in a Community from India , in JIMD Reports, Volume 19 . 2014. p. 85–93. Choi HW, et al. A Novel Frameshift Mutation of the ALDOB Gene in a Korean Girl Presenting with Recurrent Hepatitis Diagnosed as Hereditary Fructose Intolerance. Gut Liver. 2012;6(1):126–8. Schrodi SJ, et al. Prevalence estimation for monogenic autosomal recessive diseases using population-based genetic data. Hum Genet. 2015;134(6):659–69. Supplementary Files Additionalfile1.xlsx Additional file 1: Table S1. Manually curated ALDOB variants’ pathogenicity.Additional file 1: Table S2. Allele frequency for top 24 pathogenic variants to different populations. Additionalfile2.xlsx Additional file 2: Table S3. Summary of genotype-phenotype information of 68 patients with HFI. Additionalfile3.xlsx Additional file 3: Table S4. Relationship between variant site and phenotype.Additional file 3: Table S5. Relationship between mutation type and phenotype.Additional file 3: Table S6. Relationship between zygosity and phenotype. Additionalfile4.docx Additional file 4: Table S7. Different populations from HuaBiao and gnomAD database of HFI prevalence calculated based on the Bayesian framework.Additional file 4: Figure S1. Ratio of predicted incidence. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 17 May, 2022 Reviews received at journal 05 May, 2022 Reviewers invited by journal 02 May, 2022 Editor assigned by journal 26 Apr, 2022 First submitted to journal 23 Apr, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-1588804","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":102922530,"identity":"4ce5c5a8-42ab-404a-88b2-4425c8a28dc0","order_by":0,"name":"Meiling Tang","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Meiling","middleName":"","lastName":"Tang","suffix":""},{"id":102922531,"identity":"c9d23505-13ed-4244-a644-6dca14bbf997","order_by":1,"name":"Xiang Chen","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Chen","suffix":""},{"id":102922532,"identity":"c3c7abab-09f0-4358-a0ec-8b976dbd1d38","order_by":2,"name":"Qi Ni","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Ni","suffix":""},{"id":102922533,"identity":"93c91496-6c50-4b91-850b-a38687b8fe14","order_by":3,"name":"Yulan Lu","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yulan","middleName":"","lastName":"Lu","suffix":""},{"id":102922534,"identity":"932e4b88-dde6-4e2a-b058-a04cb40e661c","order_by":4,"name":"Bingbing Wu","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bingbing","middleName":"","lastName":"Wu","suffix":""},{"id":102922535,"identity":"e76315a5-474d-4541-9522-84c3f722c690","order_by":5,"name":"Huijun Wang","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Huijun","middleName":"","lastName":"Wang","suffix":""},{"id":102922536,"identity":"6559057e-030d-447a-9559-a5b41cd6df3e","order_by":6,"name":"Zhaoqing Yin","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhaoqing","middleName":"","lastName":"Yin","suffix":""},{"id":102922537,"identity":"deaf18f4-3b55-42c3-840e-b68611435636","order_by":7,"name":"Wenhao Zhou","email":"","orcid":"","institution":"Children's Hospital of Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wenhao","middleName":"","lastName":"Zhou","suffix":""},{"id":102922538,"identity":"5a2f16d2-439e-477f-87a6-4deea51755d2","order_by":8,"name":"Xinran Dong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYHACAyC24WdgSABxmInWkibZQKqWwyRoMbh9eOPjgl/nJQyOJz97wFBhndjAfvYAXi2SfWnFxjP7bksYnHlmbsBwJj2xgScvAa8Wfh4eM2nentt1BjcSzCQY2w4nNkjwGODVwgbRck7C4Eb6NwnGf0RoAdvC8+MAUEsO0JYGIrRI9rAVG/M2JEtInnlTJpFwLN24jScHvxaDM8wbH/P8sZPgO56+TeJDjbVsP/sZ/FrAgLENykgA+Y6wehD4Q5yyUTAKRsEoGKEAAMjjQM/yZo7uAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-9868-8795","institution":"Children's Hospital of Fudan University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xinran","middleName":"","lastName":"Dong","suffix":""}],"badges":[],"createdAt":"2022-04-24 04:11:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1588804/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1588804/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":21120036,"identity":"7da003ed-fe59-4b09-abaf-9bf63e963050","added_by":"auto","created_at":"2022-05-05 16:14:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":473782,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe workflow for estimation of HFI prevalence in Chinese population.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study consisted of two parts were performed: (1) \u003cem\u003eALDOB\u003c/em\u003e variant pathogenicity curation. (2) Estimation of HFI prevalence.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/6a76e9dc79f42d81b6fa4d19.jpg"},{"id":21120039,"identity":"42d13d45-6066-4fae-a099-6ce964541fa4","added_by":"auto","created_at":"2022-05-05 16:14:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":524679,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAllele frequency comparison for 24 pathogenic variants to\u003c/strong\u003e \u003cstrong\u003edifferent populations.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe value in each box shows the AF for each variant (row) in each population (column). The blank box means the variant has not been detected in the population. All variants will be show if there are less than 10 variants in the mutation type. In total 13 P/LP variants had AF higher than 1e-5 in local CCGT database, and the A338V were significantly higher compared with the other populations (all P-value\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/fba7d98fc963d318f9dd09f0.jpg"},{"id":21120037,"identity":"2b10c268-a0b2-4ed2-9c71-226497fc6278","added_by":"auto","created_at":"2022-05-05 16:14:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":118478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstimated HFI affected frequency to\u003c/strong\u003e \u003cstrong\u003edifferent populations\u003c/strong\u003e \u003cstrong\u003eby Bayesian framework.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eEstimated affected frequency on 81 P/LP screening panel by Bayesian framework. Each population has a bar with each showing the estimated affected frequency if only use the pathogenic variants in the panel, and the P-value above shows the significance for difference. The vertical line shows the 95% confidence interval.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/b9c6a306a595ce867a820f27.jpg"},{"id":21120635,"identity":"e89f5c55-1a76-49df-84ff-deb6646b9f58","added_by":"auto","created_at":"2022-05-05 16:20:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":802184,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/fbb24022-77ba-4c80-9bdd-9d14759aedcf.pdf"},{"id":21120634,"identity":"dc3ff58b-b07f-4869-8e20-3227ef8e1574","added_by":"auto","created_at":"2022-05-05 16:19:57","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34733,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1: Table S1. Manually curated \u003cem\u003eALDOB\u003c/em\u003e variants’ pathogenicity.\u003c/p\u003e\u003cp\u003eAdditional file 1: Table S2. Allele frequency for top 24 pathogenic variants to different populations.\u003c/p\u003e","description":"","filename":"Additionalfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/1d677df3daabf2f0501edcae.xlsx"},{"id":21120633,"identity":"2fe51420-dcb7-4171-adb6-72544d2e3082","added_by":"auto","created_at":"2022-05-05 16:19:57","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":23166,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2: Table S3. Summary of genotype-phenotype information of 68 patients with HFI.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Additionalfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/722c53b1cb85d643c57d063a.xlsx"},{"id":21120040,"identity":"85247f14-de79-4660-9960-eb37c7c78894","added_by":"auto","created_at":"2022-05-05 16:14:57","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":17968,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 3: Table S4. Relationship between variant site and phenotype.\u003c/p\u003e\u003cp\u003eAdditional file 3: Table S5. Relationship between mutation type and phenotype.\u003c/p\u003e\u003cp\u003eAdditional file 3: Table S6. Relationship between zygosity and phenotype. \u003c/p\u003e","description":"","filename":"Additionalfile3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/c28fd57ee633e0246baeabd8.xlsx"},{"id":21120042,"identity":"03bf68d5-dc89-4c5e-83a8-6842eb25ae71","added_by":"auto","created_at":"2022-05-05 16:14:57","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":67674,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 4: Table S7. Different populations from HuaBiao and gnomAD database of HFI prevalence calculated based on the Bayesian framework.\u003c/p\u003e\u003cp\u003eAdditional file 4: Figure S1. Ratio of predicted incidence.\u003c/p\u003e","description":"","filename":"Additionalfile4.docx","url":"https://assets-eu.researchsquare.com/files/rs-1588804/v1/7f8a850139b182af7c0e3f6e.docx"}],"financialInterests":"","formattedTitle":"Estimation of hereditary fructose intolerance prevalence in Chinese population","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHereditary fructose intolerance (HFI) is a rare inherited autosomal recessive (AR) disease that caused by pathogenic variants in the aldolase enzyme, B isoform gene (\u003cem\u003eALDOB\u003c/em\u003e), which led to the fructose-1,6-bisphosphate aldolase B (aldolase B) reduction or deficiency that resulting in fructose metabolism disorder[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Fructose is a monosaccharide like glucose that was the dominant composition of candy, fruits and honey. It is also a metabolic intermediate of sucrose and sorbitol. Therefore, patients with HFI develop symptoms when they are exposed to fructose, sucrose or sorbitol[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The predominance of liver, kidney, and small intestine in fructose metabolism is based on the presence of the three enzymes (fructokinase, aldolase B and triokinase), which convert fructose into intermediates of the glycolytic\u0026ndash;gluconeogenic pathway (fructose pathway)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The fructokinase (ketohexokinase, KHK) could splits fructose to fructose-1-phosphate (F-1-P), and aldolase B which splits F-1-P into dihydroxyacetone phosphate and glyceraldehyde in the liver, small intestine and proximal renal tubule[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The deficiency of aldolase B could lead to the toxic accumulation of F-1-P and causes multiple clinical manifestation, including nausea, vomiting, hypoglycemia, metabolic acidosis, liver dysfunction, and abnormal renal function[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As special diet (withdrawal of all sources of fructose, like food, drugs, parenteral infusions and so on) could help to avoid severe complications, early diagnosis can help a lot to improve the prognoses of patients, and serious complications can be avoided. The preference of HFI is approximately 1:23,000 in British and 1:20,000 in Switzerland[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], 1:26,100 in Germany[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], 1:31,000 in Polish[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], 1:34,483 in Northwest Russia and so on[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In general, the prevalence in European population is about 1:31,000 to 1:18,000[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The HFI prevalence of Chinese population is remain elusive. Therefore, it is essential to estimate the prevalence of HFI and to evaluate whether HFI screening in newborn babies is necessary. Nowadays, neonatal screening includes congenital adrenal hyperplasia (CAH, 1:20,000\u0026ndash;1:10,000), phenylketonuria (PKU, 1:11,800), glucose-6-phosphate dehydrogenase deficiency (G-6-PD deficiency, 1:434) and congenital hypothyroidism (CH, 1:1,059) in China[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Among them, CAH and PKU are rare diseases in China, and their average prevalence is about 1:12,520. China has released 121 kinds of rare diseases, most of which (98.3%) are not included in neonatal screening[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Among these rare diseases, if many diseases can be diagnosed early, like HFI, the prognosis of patients will be particularly excellent. We hope to analyze the data in real-world and provide suggestions in newborn screening strategies and carrier screening of HFI parents. Newborn screening for HFI may lead to benefit to early diagnosis and treatment.\u003c/p\u003e \u003cp\u003eUntil now, the relationship between genotype and phenotype of HFI is unknown. Davit-Spraul et al. studied 162 patients from 92 families with HFI and found 16 mutations in the \u003cem\u003eALDOB\u003c/em\u003e gene. They collected the clinical symptoms of the 10 probands, conventional tests (Fructose load, Hepatic aldolase B activity detection), variant sites, age, family history and so on. There was no significant genotype/phenotype correlation to the 10 families[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Mehmet Gunduz et al. retrospectively analyzed a cohort with 26 HFI patients[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. They collected the patient's age, clinical symptoms, metabolic crisis history and variant sites. They also found no clear correlation between genotype and phenotype. Previous studies generally believe that no genotype-phenotype correlations have been identified for HFI; clinical severity and extent of organ damage appear to depend on an individual's nutritional environment[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. So, in this study, we tried to expand the sample size, and study the relationship between variant site, mutation type, zygosity and phenotype at the same time.\u003c/p\u003e \u003cp\u003eHFI diagnosis is based on genetic test. As there are no readily available biochemical markers that are not exposed to fructose[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Therefore, molecular screening for the most common mutations can be a cost-effective way to identify screen out individuals highly suspected as HFI. After literature review, we found the different population had different pathogenic hotspots in \u003cem\u003eALDOB\u003c/em\u003e. Missense mutations A150P and A175D are the two most common alleles in the United States of America, Germany, Italy, United Kingdom, France, Poland et al; A175D and R60* in Poland, A150P and N120Kfs*32 in Spain, N335K and A150P in Australia. Indian population is much complex and had several variants with high allele frequency (AF) including c.112\u0026thinsp;+\u0026thinsp;1delG, c.324\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A, c.380-1 G\u0026thinsp;\u0026gt;\u0026thinsp;A et al[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The AF characteristics of pathogenic or likely-pathogenic (P/LP) \u003cem\u003eALDOB\u003c/em\u003e variants in Chinese population are still intriguing. We tried to estimate the prevalence of HFI in Chinese population, summarize the genotype-phenotype correlation, analyzed the genetic characteristics of \u003cem\u003eALDOB\u003c/em\u003e and evaluate the necessity of newborn screening in Chinese population. We hope our research can be conducive to genetic counseling and provide useful information for neonatal genetic screening and carrier screening strategies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCuration of pathogenic variants in\u003c/strong\u003e \u003cspan class=\"BoldItalic\"\u003eALDOB\u003c/span\u003e \u003cstrong\u003egene and allele frequency analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter pathogenicity assessment of \u003cem\u003eALDOB\u003c/em\u003e variants which recruited from public database including ClinVar, HGMD, and PubMed (no additional findings in Web of Science), 81 P/LP variants were identified (\u003cstrong\u003eAdditional file 1: Table S1\u003c/strong\u003e), containing missense (26%, 21/81), frameshift (22%, 18/81), splicing (21%, 17/81), nonsense (15%, 12/81), inframe indel (6%, 5/81), indel (2%, 2/81), CNV (2%, 2/81), stop lost (1%, 1/81), start lost (1%, 1/81), synonymous (1%, 1/81) and 3\u0026rsquo;-UTR variants (1%, 1/81). Among 81 P/LP variants, 24 variants had reported allele frequency (AF) in general populations from public databases (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eAdditional file 1: Table S2\u003c/strong\u003e). So, we analyzed the AF of these variants in different population to detect the genetic characteristics of \u003cem\u003eALDOB\u003c/em\u003e in Chinese population. In total, two variants (A338V, A338G) had significantly higher AF in Chinese population by comparing to NFE population (all P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and five P/LP variants (A150P, A175D, N335K, R60*, R304Q) had significantly lower AF (all P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in Chinses population. The most frequent P/LP site in the gnomAD-TOTAL (all populations in gnomAD) is A150P (1:323), and it is also the most frequent site in admixed American (AMR, 1:714), Finnish in Finland (FIN, 1:244) and non-Finland European (NFE, 1:189). The hotspot detected in this study is consistent with previous study[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the frequency is low in the Chinese Children\u0026apos;s Rare Disease Genetic Testing Clinical Collaboration System (CCGT) Children Cohort (1:20,833). In addition, A150P was not recorded in the CCGT Parent\u0026rsquo;s Cohort and HuaBiao database. A338V is the most common variant site in Chinses population (HuaBiao is 1:1,408, CCGT Children is 1:1,887 and Parent is 1:1,538), it is also the most frequent site in African American (AFR, 1:3,226), South Asian (SAS, 1:1,010) and East Asian (EAS, 1:1,563). This variant was not reported in Ashkenazi Jewish (ASJ), FIN and AMR. A338G is the second high-frequency pathogenic site in Chinese population (HuaBiao is 1:1,408, CCGT Children is 1:8,333 and Parent is 1:6,667). N120Kfs*32 is the third high-frequency variant in Chinese population (CCGT Children is 1:3,226 and Parent is 1:6,667). The AF of N120Kfs*32 in Chinese population was slightly higher than AFR (1:8,333), AMR (1:13,699) and NFE population (1:21,739) (all P-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These results showed that Chinese population has special characteristics in \u003cem\u003eALDOB\u003c/em\u003e variants, especially different from Caucasians (NFE).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of HFI prevalence in Chinese population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe estimated the HFI prevalence based on 20,919 pediatric patients as CCGT Children Cohort (12,783 males and 8,136 females) and 10,031 parental samples as CCGT Parent\u0026rsquo;s Cohort (5,006 males and 5,024 females). The total number of individuals carrying P/LP \u003cem\u003eALDOB\u003c/em\u003e variants in Children Cohort is 61 people (36 males and 25 females) and 27 people (11 males and 16 females) in Parent\u0026rsquo;s Cohort. Based on those results, the estimated HFI prevalence in Chinese population is between 1/470,416 to 1/462,233 in Children Cohort and 1/571,594 to 1/532,412 in Parent\u0026rsquo;s Cohort by three strategies. Specially, the estimated prevalence of HFI by Bayesian framework was 1/462,839 (95% confidence interval 1/803,692\u0026thinsp;~\u0026thinsp;1/293,567) in Children Cohort and 1/532,412 (95% confidence interval 1/1,270,634\u0026thinsp;~\u0026thinsp;1/277,464) in Parent\u0026rsquo;s Cohort. Totally, the estimated prevalence of the Chinese population is 1/504,678 by averaging all the above results (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The prevalence in HuaBiao (1/410,068) and EAS (1/818,758) were similar (\u003cstrong\u003eAdditional file 4: Table S7\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eFor the result of HFI prevalence estimation by Bayesian framework in other gnomAD populations, the prevalence is 1/23,147 (95% confidence interval 1/28,182 to 1/19,278) in NFE population, 1/55,539 (95% confidence interval 1/107,444 to 1/32,816) in FIN population, 1/132,801 (95% confidence interval 1/274,861 to 1/75,230) in AMR population, 1/263,150 (95% confidence interval 1/2,275,631 to 1/81,267) in ASJ population, 1/412,335 (95% confidence interval 1/702,621 to 1/264,931) in AFR population and 1/465,278 (95% confidence interval 1/7,821,624 to 1/121,173) in SAS population (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cstrong\u003eAdditional file 4: Table S7\u003c/strong\u003e). Based on these results, we found the prevalence in Chinese population is much lower than other populations, especially lower than Caucasians (NFE).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHFI prevalence estimation in Children cohort and Parent\u0026rsquo;s cohort with estimated affected frequency by three methods\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCCGT Children\u003c/p\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCCGT Parent\u0026rsquo;s\u003c/p\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (Male/Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12783/8136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5006/5024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarrier with P/LP variants (Male/Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (36/25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27(11/16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarrier frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCouple\u0026rsquo;s carrier risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/117604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/138026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethod 1: carrier frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/470416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/552104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethod2: permutation \u0026amp; combination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/462233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/571594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethod 3: Bayesian framework (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/462839\u003c/p\u003e\n \u003cp\u003e(1/803692\u0026thinsp;~\u0026thinsp;1/293567)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/532412\u003c/p\u003e\n \u003cp\u003e(1/1270634\u0026thinsp;~\u0026thinsp;1/277464)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/465133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/551573\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEstimated HFI frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1/504678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosed children in CCGT database\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eWe diagnosed three HFI patients in CCGT database. Patient 1 presented vomiting immediately after feeding with infant formulas. Hunger and poor complexion occurred after eating sweets. Since her parents stop feeding sugary food at three years old, she did not present surgery related gastrointestinal phenotypes. She could speak at seven months old, and walk at two years old. She is now 174.6cm, and BMI is 18.4. The diagnosis was confirmed by genetic testing at the age of 30. She had compound heterozygous variants in the \u003cem\u003eALDOB\u003c/em\u003e gene: one pathogenic missense (c.1013C\u0026thinsp;\u0026gt;\u0026thinsp;T, p.A338V) from father and one frameshift (c.360_363delCAAA, p.N120Kfs*32) variant from mother[\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. Patient 2 was a one-year-old girl. She has been breastfeeding soon after birth. At 8 months old, she began mixed feeding of infant diet and breastfeeding. Vomiting occurred immediately after eating infant diet. Since her mother stop feeding infant diet, the vomiting can be relieved. The genetic diagnosis was confirmed by genetic testing at the age of 8 months. Gene analysis revealed pathogenic nonsense (c.888G\u0026thinsp;\u0026gt;\u0026thinsp;A, p.W296*) from father and missense (c.1013C\u0026thinsp;\u0026gt;\u0026thinsp;T, p.A338V) variant from mother. After early dietary guidance, her abnormal liver function tests and hepatomegaly disappeared when she was 10 months old. Patient 3 was a three-year-old little girl. After a week of breastfeeding, she presented jaundice, lethargy, metabolic acidosis, anemia, thrombocytopenia, and acute liver failure were found. Her symptoms began to improve after the fructose free diet, with normalization of liver function tests within one week. Genetic testing showed compound heterozygous variants for pathogenic frameshift (c.673_674delinsA, p.E225Rfs*5) and splice acceptor (c.325-1G\u0026thinsp;\u0026gt;\u0026thinsp;A) variant in \u003cem\u003eALDOB\u003c/em\u003e. She remains well with normal growth and development at the time of interview (3 years old).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe genotype-phenotype relationship in 68 HFI patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotally, we collected 68 HFI patients including the three patients mentioned above and additionally searching ClinVar, HGMD and published papers (\u003cstrong\u003eAdditional file 2: Table S3)\u003c/strong\u003e. We analyzed the relationship between phenotype and variant site, mutation type, zygosity respectively. Most symptoms were onset in infancy after weaning (94%, 15/16) and symptoms can be prevented by strict dietary restriction (100%, 21/21). Gastroenteric and liver phenotype were the dominant phenotype in HFI patients. We found that 34 patients hate sweets and fruit (87%, 34/39), 31 patients presented vomiting (78%, 31/40), 19 patients presented nausea (54%, 19/35), and 22 patients presented hepatomegaly (59%, 22/37). For each variant-phenotype analysis, we found that patients carrying A150P (homozygote) were more likely to present nausea than combination of other variant sites (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003cstrong\u003eAdditional file 3: Table S4)\u003c/strong\u003e. No other variants-phenotype relationship was detected. The mutation types of 68 HFI patients were classified into missense, frameshift, nonsense, splicing and inframe indel in our study (\u003cstrong\u003eAdditional file 3: Table S5\u003c/strong\u003e). For mutation type-phenotype analyses, we found that patient carrying two missense variant sites were more likely to present aversion to sweets and fruit (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For zygosity-phenotype analyses, patients carrying homozygous variant sites were more likely to present nausea (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) by Chi-square test (\u003cstrong\u003eAdditional file 3: Table S6\u003c/strong\u003e). The other mutation type-phenotype and zygosity-phenotype relationship were not detected.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we estimated the prevalence in Chinese population based on public databases and internal database. We found the HFI prevalence in Chinese population and some other East Asia populations is extremely low. The prevalence is especially much lower than Caucasian populations. HFI has not been included in newborn screening plan in any country. Based on the low prevalence, we still recommended not to put it into newborn screening in Chinese population. PKU is a disease that has been included in China's Neonatal Screening Plan. PKU and HFI are both metabolic AR diseases. And the prevalence of PKU varies worldwide, with an average of 1:10,000 newborns[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. It is significantly higher than HFI (1/10,000 vs. 1/504,678, P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, HFI has good prognoses with diet control, we highly recommended early genetic diagnoses for those patients with suspension.\u003c/p\u003e \u003cp\u003eTo provide a more precise strategy for HFI early diagnoses, we summarized the phenotype spectrum of 68 HFI patients. We found digestive phenotype were the dominant feature. So, we suggested four typical symptoms in work-flow of HFI diagnoses: 1) vomiting and nausea after eating food or medicine contains fructose; 2) aversion to sweets and fruit; 3) abnormal liver function tests; 4) symptoms can be prevented by withdrawal of all sources of fructose. As fructose malabsorption (FM) and fructose-1,6-bisphosphatase deficiency (FBPase deficiency) had similar phenotype with HFI that gastrointestinal symptoms are onset in infancy after weaning and can be prevented by strict dietary restriction. The differential diagnoses could be very difficult according to clinical phenotype. FBPase deficiency is an inherited disease caused by \u003cem\u003eFBP1\u003c/em\u003e gene mutation[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is in autosomal recessive manner. WES can help to identify which kind of fructose diseases and exclude other metabolic diseases. However, WES is not cheap enough to be used as first-line diagnostic method. In addition, the symptoms of these three diseases can be easily controlled by fructose avoidance. So, we tried to establish a cost-effective variants panel for HFI diagnosis. The rapid high-frequency site screening panel contains ten high-frequency sites including A338V, N120Kfs*32, A338G, W296*, E225Rfs*5, R304W, A150P, c.325-1G\u0026thinsp;\u0026gt;\u0026thinsp;C, L289Ffs*10 and Q111*. These variants were identified as top 10 variants with high AF in CCGT pediatric cohort and cover about 90% of Chinese pediatric patients. By applying this panel test, time and expenditure could be reduced in a large degree. The specificity and sensitivity need to be verified in large healthy children\u0026rsquo;s cohorts.\u003c/p\u003e \u003cp\u003eHFI is a genetic metabolic disease, and digestive system symptoms are the dominant phenotype recognized by most researchers[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. We diagnosed three patients, with gastrointestinal phenotypes. By integrating the information from 68 patients, we found that gastroenteric and liver phenotype were the dominant phenotype. A150P was identified to related to nausea. The function of A150P in unclear. \u003cem\u003eALDOB\u003c/em\u003e sequence is generally highly conserved, but A150 is located in non-conserved area. So, the detected relationship of A150P with nausea by due to that this is a common variant[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The functional study is needed to confirm the relationship. We also found two missense variant sites were related to aversion to sweets and fruit and homozygous variant sites were related to nausea. Two missenses pattern (44/68, 65%) and homozygous pattern (35/68, 51%) are the main mutation type in 68 HFI patients. So, we thought these relationships may indicate the characteristics of \u003cem\u003eALDOB\u003c/em\u003e variants.\u003c/p\u003e \u003cp\u003eFructose metabolism in liver, kidney and intestine requires the synergistic action of two enzymes. In physiological states, fructokinase phosphorylates fructose into F-1-P, and aldolase B decomposes F-1-P into dihydroxyacetone phosphate and glyceraldehyde. The mutation of \u003cem\u003eALDOB\u003c/em\u003e could reduce the aldolase B activity and the accumulation of F-1-P. This leads to deficiency of phosphate and adenosine triphosphate (ATP) and increase of uric acid[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The renal manifestation of HFI have been reported[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This may indicate that kidney could be damaged in HFI. One patient with proximal tubular acidosis was also reported[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, the characteristics of renal phenotypes of HFI have not been summarized.\u003c/p\u003e \u003cp\u003eCCGT is not a healthy people cohort and genotype frequency of CCGT does not correspond with the Hardy-Weinberg equilibration[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. So, we applied HuaBiao and gnomAD-EAS database to mimic the healthy and natural gathered population. The estimated prevalence is similar and indicate that CCGT could be used to present the genotype and phenotype characteristics of HFI. With more detailed information, we hope to update the HFI diagnose strategy in the further.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eChinese population had extremely low prevalence of HFI, with no need to add in current newborn screening project if consider medical costs. Genetic test strategy was suggested for early diagnoses, especially for patients with typical symptoms. The curated variant panel can assist the choice for quick and cheap diagnosis in China.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003cp\u003e\u003cstrong\u003eData acquisition for Chinese population data\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis study was approved by the ethics committees of Children\u0026apos;s Hospital of Fudan University (2021\u0026thinsp;\u0026minus;\u0026thinsp;464). The local CCGT cohort was the same as in our previously study and the detailed processing steps can be found in the study[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Briefly, counselling and informed consents were obtained from the parents of patients. Each individual received whole exome sequencing (WES) or clinical exome sequencing (CES), both covered the exon region and exon-intron splicing junction region (deep intron to 15 bp) of \u003cem\u003eALDOB\u003c/em\u003e genes. Both tests were sequenced on the Illumina HiSeq X10 with 150 bp pair-end. The genetic diagnosis of HFI was performed according to ACMG guideline by experience clinicians and genetic counselors. One parent was diagnosed with special requirement. For the HFI prevalence estimation, Children and parents with genetic diagnosis of HFI, together with their family members, were excluded.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLiterature search of HFI-related studies\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePubMed and Web of Science were searched using the terms \u0026ldquo;Hereditary fructose intolerance\u0026rdquo;, \u0026ldquo;Hereditary fructose intolerance and case report\u0026rdquo;, \u0026ldquo;\u003cem\u003eALDOB\u003c/em\u003e mutation\u0026rdquo;, \u0026ldquo;\u003cem\u003eALDOB\u003c/em\u003e variant\u0026rdquo; between 1988 (first described pathogenic variant) and October 2021[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. We applied strict literature inclusion criteria to make a more accurate conclusion. Our literature inclusion criteria: 1) literature about case report and the nomenclature of mutation sites meets the requirements of HGVS[\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]; 2) the sites of case report were evaluated as P/LP according to ACMG guidelines; 3) the literature included in SCI (represents high-quality literature). Exclusion criteria: 1) lack of information of mutation sites or the nomenclature of mutation sites; 2) lack of clinical information; 3) repeated cases. According to those criteria, a total of 711 articles were found, of which 17 were included in this study[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCuration of P/LP variants in\u003c/strong\u003e \u003cspan class=\"BoldItalic\"\u003eALDOB\u003c/span\u003e \u003cstrong\u003egene\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eWe included reported pathogenic variants of \u003cem\u003eALDOB\u003c/em\u003e gene from ClinVar (level P or LP), HGMD (level DM or DM?) and HFI-related literatures mentioned above. No new variants were reported in CCGT database. These variants were curated by two clinical geneticists back-to-back and after manually check, 81 out of 86 variants were curated as P/LP level (\u003cstrong\u003eAdditional file 1: Table S1\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eCollection of the other populations data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe AF of \u003cem\u003eALDOB\u003c/em\u003e gene in other populations were available from the gnomAD database. AFR, AMR, ASJ, FIN, NFE, SAS and EAS population in gnomAD were included (\u003cstrong\u003eAdditional file 1: Table S1\u003c/strong\u003e). Gene annotation was from GENCODE, with ID (ENSG00000136872, ENST00000374855).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of HFI prevalence in Chinese population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe estimate the HFI prevalence by three strategies as described in our previous studies[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Method 1 was based on the carrier frequency of the two cohorts individuals calculated by Hardy Weinberg principle[\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Method 2 was based on permutation \u0026amp; combination[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this strategy, the hypothesis is to calculate the probability of affected child by random choosing a male individual who carrying P/LP variant in \u003cem\u003eALDOB\u003c/em\u003e gene and a female individual who also carrying P/LP variant in \u003cem\u003eALDOB\u003c/em\u003e gene. Method 3 was based on Bayesian framework with gnomAD allele count dataset, where 95% confidence interval could be estimated[\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]. The third strategy was also adopted to estimate HFI prevalence in other populations with only allele count (\u003cstrong\u003eAdditional file 4: Table S3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData acquisition and processing for the study of genotype-phenotype relations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe collected the genotype and clinical characteristics of HFI patients from CCGT and HFI-related literatures mentioned above to study genotype-phenotype relationships. After manually check, 68 HFI patients were included (\u003cstrong\u003eAdditional file 2: Table S3\u003c/strong\u003e). Here, the 24 common clinical manifestations are inferred from OMIM database. The variants were further grouped by their mutation type, zygosity. Fisher\u0026rsquo;s Exact Test and Chi-square test were applied to testify whether one phenotype was over-represented in one type of mutations compared with the others.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analysis was performed by R version 3.6.1. Chi-square test (\u0026lambda;2.test) was used for AF comparison. Multiple-test was adjusted by \u0026ldquo;bonferroni\u0026rdquo; strategy.\u003c/p\u003e"},{"header":"Abbreviation","content":"\u003cp\u003eHFI: hereditary fructose intolerance; ALDOB: aldolase enzyme, B isoform; AR: autosomal recessive; CCGT: Chinese Children\u0026apos;s Rare Disease Genetic Testing Clinical Collaboration System; AF: allele frequency; AFR: African American; ASJ: Ashkenazi Jewish; NFE: non-Finland European; FIN: Finnish in Finland; AMR: admixed American; SAS: South Asian; EAS: East Asian; CES: clinical exome sequencing; P/LP: pathogenic/likely pathogenic; VUS: variant of unknown significance; ATP: adenosine triphosphate; PKU: Phenylketonuria; CAH: congenital adrenal hyperplasia; G-6-PD: glucose-6-phosphate dehydrogenase; CH: congenital hypothyroidism; TAT: turnaround time; WES: whole exome sequencing; KHK: ketohexokinase.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are either included in the article (or in its supplementary files) or available from the corresponding author on reasonable request. The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are very grateful to the patients and their families for their trust in our laboratory. Thank the bioinformatics team members of our laboratory for their data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committee of Children\u0026apos;s Hospital of Fudan University. Informed consent was signed by the patient\u0026apos;s parents in the clinic or ward. The study was conducted in accordance with the guidelines of the Helsinki declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the patients included signed the consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they do not have a conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from National Key Research and Development Program (2020YFC2006402), Clinical Research Plan of Shanghai Hospital Development Center (SHDC2020CR6028-002) and Shanghai Municipal Science and Technology Major Project (Grant No. 20Z11900600).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXinran Dong and Wenhao Zhou designed the study. Xinran Dong, Qi Ni and Yulan Lu interpreted medical exome/genome results and conducted analysis on the aggregated large cohort data. Meiling Tang, Xiang Chen, Bingbing Wu, Huijun Wang and Zhaoqing Yin collected, supervised, and reviewed the clinical data. Meiling Tang and Xiang Chen wrote the original manuscript draft. Xinran Dong and Wenhao Zhou supervised the study, critically reviewed, and revised the manuscript for important intellectual content. All authors reviewed the draft and approved the decision to submit for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi H, et al. Acute liver failure in neonates with undiagnosed hereditary fructose intolerance due to exposure from widely available infant formulas. Mol Genet Metab. 2018;123(4):428\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMayatepek E, Hoffmann B, Meissner T. Inborn errors of carbohydrate metabolism. Best Pract Res Clin Gastroenterol. 2010;24(5):607\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTran, et al. \u003cem\u003eInborn Errors of Fructose Metabolism. What Can We Learn from Them?\u003c/em\u003e Nutrients, 2017. 9(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim MS, et al. Hereditary Fructose Intolerance Diagnosed in Adulthood. Gut Liver. 2021;15(1):142\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCano A, et al. \u003cem\u003eTransferrin Isoforms, Old but New Biomarkers in Hereditary Fructose Intolerance\u003c/em\u003e. J Clin Med, 2021. 10(13).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGunduz M, et al. Molecular and clinical findings of Turkish patients with hereditary fructose intolerance. J Pediatr Endocrinol Metab. 2021;34(8):1017\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJames CL, et al. Neonatal screening for hereditary fructose intolerance: Frequency of the most common mutant aldolase B allele (A149P) in the British population. J Med Genet. 1996;33(10):837\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanter R, et al. The spectrum of aldolase B (ALDOB) mutations and the prevalence of hereditary fructose intolerance in Central Europe. Hum Mutat. 2005;25(6):594.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGruchota J, et al. Aldolase B mutations and prevalence of hereditary fructose intolerance in a Polish population. Mol Genet Metab. 2006;87(4):376\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbitoff YA, et al. Whole-exome sequencing provides insights into monogenic disease prevalence in Northwest Russia. Mol Genet Genomic Med. 2019;7(11):e964.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eGuidelines for diagnosis and treatment of rare diseases\u003c/em\u003e. Family medicine, 2019. 3(5): p.\u0026nbsp;1\u0026ndash;780.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Xueqin YZ. Discussion on the clinical application of four screening items of neonatal diseases in three regions of Sichuan Province. J Prev Med Inform. 2019;35(11):1286\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavit-Spraul A, et al. Hereditary fructose intolerance: Frequency and spectrum mutations of the aldolase B gene in a large patients cohort from France\u0026mdash;Identification of eight new mutations. Mol Genet Metab. 2008;94(4):443\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaughan S, Baker AL. PR II. \u003cem\u003eHereditary Fructose Intolerance.2015 Dec 17 [updated 2021 Feb 18]. In: Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Gripp KW, Mirzaa GM, Amemiya A, editors. GeneReviews\u0026reg; [Internet]. Seattle (WA): University of Washington, Seattle; 1993\u0026ndash;2022. PMID: 26677512.\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinheiro FC, Sperb-Ludwig F, Schwartz IVD. Epidemiological aspects of hereditary fructose intolerance: A database study. Hum Mutat; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQin Qian CX, et al. Hereditary fructose intolerance caused by complex heterozygous variation of ALDOB gene diet control for 30 years: a case report and literature review. Chin J Evid Based Pediatr. 2018;13(4):269\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuziau AM, et al. Recent advances in the pathogenesis of hereditary fructose intolerance: implications for its treatment and the understanding of fructose-induced non-alcoholic fatty liver disease. Cell Mol Life Sci. 2020;77(9):1709\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaciottia A, Andrea MAD. Adami. Different genotypes in a large Italian family with recurrent hereditary fructose intolerance. Eur J Gastroenterol Hepatol. 2008;20(2):118\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRita, Santamaria, et al. Novel six-nucleotide deletion in the hepatic fructose-1,6-bisphosphate aldolase gene in a patient with hereditary fructose intolerance and enzyme structure-function implications. Eur J Hum Genet. 1999;7:409\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoffee EM, Tolan DR. Mutations in the promoter region of the aldolase B gene that cause hereditary fructose intolerance. J Inherit Metab Dis. 2010;33(6):715\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKOGUT MAURICED, et al. Fructose-induced Hyperuricemia: Observations in Normal Children and in Patients with Hereditary Fructose Intolerance and Galactosemia. Res: Pediat; 1975. pp.\u0026nbsp;774\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLameire, et al. Hereditary fructose intolerance: a difficult diagnosis in the adult. Am J Med. 1978;65::416\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao M, et al. The HuaBiao project: whole-exome sequencing of 5000 Han Chinese individuals. J Genet Genomics. 2021;48(11):1032\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi Ni XC, et al. Systematic estimation of cystic fibrosis prevalence in Chinese and genetic spectrum comparison to Caucasians. Orphanet J Rare Dis. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13023-022-02279-9\u003c/span\u003e\u003cspan address=\"10.1186/s13023-022-02279-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2022: 1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Spronsen FJ, et al. Phenylketonuria Nat Rev Dis Primers. 2021;7(1):36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChi ZN, et al. Clinical and genetic analysis for a Chinese family with hereditary fructose intolerance. Endocrine. 2007;32(1):122\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRichards S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi HS. C.Q, et al. Molecular diagnosis of hereditary spherocytosis by multi-gene target sequencing in Korea: matching with osmotic fragility test and presence of spherocyte. Orphanet J Rare Dis. 2019;14(1):114.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRetterer K. J.J, et al. Clinical application of whole-exome sequencing across clinical indications. Am Coll Med Genet Genomics. 2016;18(7):696\u0026ndash;704.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEsposito G, et al. Hereditary fructose intolerance: functional study of two novel ALDOB natural variants and characterization of a partial gene deletion. Hum Mutat. 2010;31(12):1294\u0026ndash;303.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eden Dunnen JT, et al. HGVS Recommendations for the Description of Sequence Variants: 2016 Update. Hum Mutat. 2016;37(6):564\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoffee EM, et al. Increased prevalence of mutant null alleles that cause hereditary fructose intolerance in the American population. J Inherit Metab Dis. 2010;33(1):33\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaciottia A, et al. Different genotypes in a large Italian family with recurrent hereditary fructose intolerance. Eur J Gastroenterol Hepatol. 2008;20:118\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim AY, et al. \u003cem\u003ePitfalls in the Diagnosis of Hereditary Fructose Intolerance\u003c/em\u003e. Pediatrics, 2020. 146(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEsposito G, et al. Six novel alleles identified in Italian hereditary fructose intolerance patients enlarge the mutation spectrum of the aldolase B gene. Hum Mutat. 2004;24(6):534.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNicholas CP, Cross DRT, Cox TM. Catalytic deficiency of human aldolase B in hereditary fructose intolerance caused by a common missense mutation. Cell. 1988;53:881\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantamaria R, et al. Molecular basis of hereditary fructose intolerance in Italy-identification of two novel mutations in the aldolase B gene. JMed Genet. 1996;33:786\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM.AIi, GS.a.T.M.C. Identification of a novel mutation (Leu 256\u0026mdash;Pro) in the human aidolase B gene associated with hereditary fructose intolerance. Hum Mol Genet. 1994;3:203\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolan CD. a.D.R, \u003cem\u003eMolecular evidence for compound heterozygosity in hereditary fructose intolerance\u003c/em\u003e. Am J Hum Genet. 1990;46:1194\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira CR, et al. Hereditary fructose intolerance mimicking a biochemical phenotype of mucolipidosis: A review of the literature of secondary causes of lysosomal enzyme activity elevation in serum. Am J Med Genet A. 2017;173(2):501\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValadares ER, et al. Hereditary fructose intolerance in Brazilian patients. Mol Genet Metab Rep. 2015;4:35\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBijarnia-Mahay S, et al. \u003cem\u003eMolecular Diagnosis of Hereditary Fructose Intolerance: Founder Mutation in a Community from India\u003c/em\u003e, in \u003cem\u003eJIMD Reports, Volume 19\u003c/em\u003e. 2014. p.\u0026nbsp;85\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi HW, et al. A Novel Frameshift Mutation of the ALDOB Gene in a Korean Girl Presenting with Recurrent Hepatitis Diagnosed as Hereditary Fructose Intolerance. Gut Liver. 2012;6(1):126\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchrodi SJ, et al. Prevalence estimation for monogenic autosomal recessive diseases using population-based genetic data. Hum Genet. 2015;134(6):659\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hereditary fructose intolerance, prevalence estimation, curation for pathogenic variants, newborn screening, allele frequency comparison","lastPublishedDoi":"10.21203/rs.3.rs-1588804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1588804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHereditary fructose intolerance (HFI) caused by aldolase B (ALDOB) reduction or deficiency is a rare inherited autosomal recessive (AR) disease that results in fructose metabolism disorder. The disease prevalence in the Chinese population is unknown, which leads to the lack of basis for the formulation of HFI screening and diagnosis strategy. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMaterials \u0026amp; Methods: \u003c/strong\u003eFrom searching local cohort (Chinese Children’s Rare Disease Genetic Testing Clinical Collaboration System, CCGT), public databases (ClinVar and HGMD) and reviewing HFI-related literature (PubMed and Web of Science), we manually curated \u003cem\u003eALDOB\u003c/em\u003e pathogenic or likely-pathogenic (P/LP) variants according to ACMG guidelines. Allele frequency (AF) information from local CCGT, HuaBiao, and gnomAD database for \u003cem\u003eALDOB\u003c/em\u003e P/LP variants were used to estimate and the HFI prevalence in Chinese and other populations by the Bayesian framework. We collected the genotype and clinical characteristics of HFI patients from the CCGT database and published literature to study genotype-phenotype relationships. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResult:\u003c/strong\u003e In total 81 variants from \u003cem\u003eALDOB\u003c/em\u003e were curated as P/LP. The estimated Chinses HFI prevalence is approximately 1/504,678, which is similar to gnomAD-AFR (1/412,335) and SAS (1/465,278) population and much lower than NFE (1/23,147), FlN (1/55,539), AMR (1/132,801) and ASJ (1/263,150) populations. By analyzing the genetic characteristics of \u003cem\u003eALDOB\u003c/em\u003e in Chinese population, two variants (A338V, A338G) had significantly higher AF in Chinese population by comparing to NFE populations from gnomAD (all P-value\u0026lt;0.05). Five variants (A150P, A175D, N335K, R60*, R304Q) had significantly lower AF (all P-value\u0026lt;0.1). The results of genotype-phenotype association showed that patient carrying homozygous variant sites (especially A150P) were more likely to present nausea, and patient carrying two missense variant sites were more likely to present aversion to sweets and fruit (all P-value\u0026lt;0.05). Our research reveals that some gastrointestinal symptoms seem to be associated with genotypes.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Chinese population had extremely low prevalence of HFI, with no need to add in current newborn screening project if consider medical costs. Genetic test strategy was suggested for early diagnoses.\u003c/p\u003e","manuscriptTitle":"Estimation of hereditary fructose intolerance prevalence in Chinese population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-05-05 16:14:55","doi":"10.21203/rs.3.rs-1588804/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-05-17T11:15:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-05-05T09:58:45+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-05-02T12:37:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-26T19:21:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2022-04-24T00:10:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0434fa33-11cc-4fbb-a63b-02a6e8f3d085","owner":[],"postedDate":"May 5th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-08-02T11:43:56+00:00","versionOfRecord":[],"versionCreatedAt":"2022-05-05 16:14:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1588804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1588804","identity":"rs-1588804","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}