Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

【Objective】 To analyze the effect of sample hemolysis on ELISA test results in blood screening laboratory, so as to determine the acceptable tolerance of hemolysis specific to laboratory test items and detection system, and provide reference for the formulation of tolerance standard of sample hemolysis. 【Methods】 Negative and weakly positive (S/CO was about 2) samples with different hemolysis degrees were tested by several commonly used domestic reagents for HBsAg, HIV Ag/Ab, anti-HCV and anti-TP, respectively. The effects of various degrees of hemolysis on the test results of negative and weakly positive samples for each item were analyzed. 【Results】 1) Hemolysis had no effect on the test results (reactive/non-reactive) of negative and weakly positive samples for HBsAg, anti-HCV and anti-TP ELISA items; 2) Hemolysis affected the test results (reactive/non-reactive) of negative and weakly positive samples for HIV Ag/Ab ELISA item. A tolerance of Hb 2 g/L was taken as the acceptable hemolysis degree for HIV Ag/Ab ELISA item. 【Conclusion】 In this study, the acceptable tolerance of hemolytic samples for corresponding test items and detection system in our laboratory were determined. The influence of hemolysis on ELISA test result is related to the reagent, equipment, environment and other factors, therefore the acceptable tolerance of hemolysis should be determined scientifically and reasonably based on the specific evaluation of each laboratory.

Objective:To analyze the genetic mutation characteristics of glucose-6-phosphate dehydrogenase (G6PD) deficiency among infants in Kunming.Methods:A total of 15 533 infants (7 994 males and 7 539 females) born in Kunming from January 1, 2018, to December 31, 2020, with an age range of 2 to 44 days, were selected. G6PD enzyme activity and gene mutation types were detected using fluorescence quantitative analysis, multicolor melting curve analysis (MMCA), and Sanger sequencing. Droplet digital PCR (ddPCR) was used for quantitative analysis of a newly identified variant family to determine the mutant allele proportion in family members. Meanwhile,the protein structure model and pathogenicity prediction of the novel variant were analyzed.Data analysis was conducted using SPSS 26.0. Specifically, chi-square tests were used for the detection rates of G6PD enzyme activity and gene mutations between different genders. One-way analysis of variance (ANOVA) was used for the comparison of enzyme activity among different mutation types.Results:Among 15 533 infants, 143 cases (129 males and 14 females) were tested positive for G6PD activity, with a detection rate of 0.92% (143/15 533). The difference in detection rates between males and females was statistically significant (χ 2=96.76, P<0.001). Out of 89 enzyme activity-positive cases (83 males and 6 females) underwent genetic testing, 77 (72 males and 5 females) were detected by MMCAand other 12 negative samples were underwent further Sanger sequencing, revealing mutations in 6 samples, all of which were males. Among the 83 individuals with gene mutations, 78 had heterozygous mutations, 1 had a homozygous mutation, and 4 had compound heterozygous mutations. A total of 12 mutation types were detected, with G6PD c.487G>A, c.1024C>T, c.1388G>A, and c.1376G>T being the most common, accounting for 74.70% (62/83) of all mutation types. The average G6PD enzyme activity of c.1376G>T was the lowest, and the differences were statistically significant compared to the average enzyme activity of the other three mutations ( P<0.05). One male infant with a newly identified G6PD c.242G>C mutation was detected, predicted to be pathogenic. ddPCR confirmed that the mother of the affected child was a c.242G>C mutant chimera, with a chimera proportion of 6.66%. Conclusions:In the Kunming region, the predominant G6PD deficiency gene mutation is c.487G>A, with the detection of a novel G6PD c.242G>C mutation. The application of ddPCR technology can assist in detecting the proportion of mutation chimeras.

Objective Hypertriglyceridemic waist(HW),hypertriglyceridemic waist-to-height ratio(HWHtR),and waist-to-hip ratio(WHR)have been shown to be indicators of cardiometabolic risk factors.However,it is not clear which indicator is more suitable for children and adolescents.We aimed to investigate the relationship between HW,HWHtR,WHR,and cardiovascular risk factors clustering to determine the best screening tools for cardiometabolic risk in children and adolescents. Methods This was a national cross-sectional study.Anthropometric and biochemical variables were assessed in approximately 70,000 participants aged 6-18 years from seven provinces in China.Demographics,physical activity,dietary intake,and family history of chronic diseases were obtained through questionnaires.ANOVA,x2 and logistic regression analysis was conducted. Results A significant sex difference was observed for HWHtR and WHR,but not for HW phenotype.The risk of cardiometabolic health risk factor clustering with HW phenotype or the HWHtR phenotype was significantly higher than that with the non-HW or non-HWHtR phenotypes among children and adolescents(HW:OR = 12.22,95%CI:9.54-15.67;HWHtR:OR = 9.70,95%CI:6.93-13.58).Compared with the HW and HWHtR phenotypes,the association between risk of cardiometabolic health risk factors(CHRF)clustering and high WHR was much weaker and not significant(WHR:OR = 1.14,95%CI:0.97-1.34). Conclusion Compared with HWHtR and WHR,the HW phenotype is a more convenient indicator with higher applicability to screen children and adolescents for cardiovascular risk factors.

Objective The study aimed to investigate the impact of rare earth elements(REEs)exposure on pregnancy outcomes of in vitro fertilization-embryo transfer(IVF-ET)by analyzing samples from spouses. Methods A total of 141 couples were included.Blood and follicular fluid from the wives and semen plasma from the husbands,were analyzed for REEs using inductively coupled plasma mass spectrometry(ICP-MS).Spearman's correlation coefficients and the Mann-Whitney U test were used to assess correlations and compare REE concentrations among three types of samples,respectively.Logistic models were utilized to estimate the individual REE effect on IVF-ET outcomes,while BKMR and WQS models explored the mixture of REE interaction effects on IVF-ET outcomes. Results Higher La concentration in semen(median 0.089 ng/mL,P=0.03)was associated with a lower fertilization rate.However,this effect was not observed after artificial selection intervention through intracytoplasmic sperm injection(ICSI)(P=0.27).In semen,the REEs mixture did not exhibit any significant association with clinical pregnancy. Conclusion Our study revealed a potential association between high La exposure in semen and a decline in fertilization rate,but not clinical pregnancy rate.This is the first to report REEs concentrations in follicular fluid with La,Ce,Pr,and Nd found at significantly lower concentrations than in serum,suggesting that these four REEs may not accumulate in the female reproductive system.However,at the current exposure levels,mixed REEs exposure did not exhibit reproductive toxicity.

Objective To elucidate the molecular genetic etiology of patients with disorders of sex development(DSD)using whole exome sequencing(WES),thereby enhancing our understanding of the underlying mechanisms of sexual development abnormalities.Methods Retrospective analysis was conducted on clinical data of 60 DSD patients diagnosed in the First People's Hospital of Yunnan Province between March 2008 and August 2021,with an additional family study for one proband.Genomic DNA was extracted from patients for WES analysis.Single nucleotide polymorphism(SNP)and insertions/deletion(InDel)tests were identified using SAMtools software in conjunction with established SNP and InDel databases.Copy number variations(CNVs)at the exon level were detected using ExomeDepth,while the potential pathogenicity of mutations was predicted with PolyPhen-2,Mutation taster and PyMol software,with Sanger sequencing employed for confirmation.Results The study included 22 patients with 46,XX DSD and 38 with 46,XY DSD.Among the 46,XX DSD patients,the SRY gene was detected in 14 patients.In the remaining 8 patients and a proband's families,single nucleotide site variations(SNVs)of NR5A1,PROKR2 and ANOS1 genes were identified in 2 patients,and CNVs in CYP21A2 gene were found in 4 patients.The pathogenicity of CYP21A2 EX1 Dup has been previously reported,while the remaining 3 CNVs were of uncertain significance,and no DSD-related mutations were detected in 2 patients.In the WES analysis of 46,XY DSD patients,10 pathogenic or likely pathogenic SNVs across 5 genes(SRY,AR,SRD5A2,CYP17A1,and NR5A1)were identified in 14 patients.Additionally,5 likely pathogenic CNVs involving the CYP21A2,AKR1C2,CBX2,and NR5A1 genes were detected in 5 patients,comprising 3 deletions and 2 duplications.Novel SNVs in NR5A1(c.722G>T,c.48C>G)and ANOS1 c.564A>T were identified,with no prior reports in relevant databases.The pathogenicity of CYP21A2 EX1 Dup is documented in related databases,while the remaining CNVs have not been previously reported.Conclusion The utilization of WES technology has enhanced the diagnostic potential for DSD,broadened the spectrum of known DSD-related gene mutations,and deepened our comprehension of DSD pathogenesis,offering valuable support for genetic counseling.