Gene Tech (China)

Monogenic Forms of Diabetes (MFD) account for about 3% of all diabetes, and their accurate diagnosis often results in life-changing therapeutic reassignment for the patients. Like other Mendelian diseases, reduced penetrance and variable expressivity are often seen in several different types of MFD, where symptoms develop only in a portion of the persons who carry the pathogenic variant or vary widely in symptom severity and age of onset. This complicates diagnosis and disease management in MFD. In addition to its clinical importance, knowledge of genetic modifiers that confer penetrance and expressivity variability opens possibilities to identify protective genetic variants which may help probe the mechanisms of more common forms of diabetes and shed light in new therapeutic strategies. In this review, we will mainly address penetrance and expressivity variation in different types of MFD, factors that confer such variations and opportunities that come with such knowledge. Related literature was searched in PubMed, Medline and Embase. Papers with publication year from 1974 to 2023 are included. Data are either sourced from literatures or from OMIM, Clinvar and 1000 genome browser.

Killer-cell immunoglobulin-like receptors 2DL4 (KIR2DL4) and the human leukocyte antigen class I-G (HLA-G) display vital parts in immune responses against hepatitis C virus(HCV) infection. We select four potentially functional single nucleotide polymorphisms(SNPs) of KIR/HLA to explore the associations between KIR2DL4/HLA-G genetic variants and HCV infection results.In the present case-control study, a total of 2225 HCV-infected high-risk subjects, including 1778 paid blood donors (PBD) and 447 drug users were consecutively recruited before treatment from 2011 to 2018. KIR2DL4-rs660773, KIR2DL4-rs660437, HLA-G-rs9380142, and HLA-G-rs1707 SNPs were sorted as genotypes in the subdivided groups, involving 1095 uninfected controls subjects, 432 spontaneous HCV clearance subjects and 698 HCV persistent infection subjects. After genotyping experiments using the TaqMan-MGBassay, modified logistic regression was used to calculate the correlation among the SNPs and HCV infection. The SNPs were functionally annotated using bioinformatics analysis.Following adjusting by age, sex, alanine aminotransferase, aspartate aminotransferase, IFNL3-rs12979860, IFNL3-rs8099917, and the infection route, the logistic regression analysisdiscovered that KIR2DL4-rs660773 and HLA-G-rs9380142 were correlated with vulnerability to HCV infection (all p < 0.05). In a locus-dosage way, compared with subjects carrying the rs9380142-AA or rs660773-AA genotypes, subjects with rs9380142-AG or rs660773-AG/GG (all p < 0.05) were more vulnerable to HCV infection; the overall impact of their risk genotypes (rs9380142-AGrs660773-AG/GG) was correlated with an elevated incidence of HCV infection (ptrend < 0.001). In the Haplotype analysis, patients with haplotype AG were more likely to contract HCV compared to those with the highest common AA haplotype (p = 0.002) were higher in susceptibility to infect HCV. The SNPinfo web server estimated that rs660773 is a transcription factor binding site, whereas rs9380142 is a potential microRNA-binding site.In two Chinese high-risk population (PBD and drug uesrs), KIR2DL4 rs660773-G and HLA-G rs9380142-G alleles polymorphisms are related to HCV susceptibility. KIR2DL4/HLA-G pathway genes might affect the innate immune responses by regulating KIR2DL4/HLA-G transcription and translation play a potential role in HCV infection.

Hemorrhagic fever with renal syndrome (HFRS), caused by hantavirus, is a serious public health problem in China. Despite intensive countermeasures including Patriotic Health Campaign, rodent control and vaccination in affected areas, HFRS is still a potential public health threat in China, with more than 10,000 new cases per year. Previous epidemiological evidence suggested that meteorological factors could influence HFRS incidence, but the studies were mainly limited to a specific city or region in China. This study aims to evaluate the association between monthly HFRS cases and meteorological change at the country level using a multivariate distributed lag nonlinear model (DLNM) from 2004 to 2018. The results from both univariate and multivariate models showed a non-linear cumulative relative risk relationship between meteorological factors (with a lag of 0–6 months) such as mean temperature (Tmean), precipitation, relative humidity (RH), sunshine hour (SH), wind speed (WS) and HFRS incidence. The risk for HFRS cases increased steeply as the Tmean between − 23 and 14.79 °C, SH between 179.4 and 278.4 h and RH remaining above 69% with 50–95 mm precipitation and 1.70–2.00 m/s WS. In conclusion, meteorological factors such as Tmean and RH showed delayed-effects on the increased risk of HFRS in the study and the lag varies across climate factors. Temperature with a lag of 6 months (RR = 3.05) and precipitation with a lag of 0 months (RR = 2.08) had the greatest impact on the incidence of HFRS.

Abstract Background: This work investigates the use of methylation driven biomarkers for diagnosis and prognosis in colorectal cancer (CRC) by mining DNA methylation and gene expression data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx), and the Gene Expression Omnibus (GEO). Methods: The differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were screened using mRNA expression and DNA methylation data from TCGA, respectively. The methylation driven genes (MDGs) of CRC were further identified using the MethylMix R package. Subsequently, the MDGs were analyzed with Random Forest (RF), support vector machine (SVM), and logistic regression (LR) algorithms to establish diagnosis prediction models as independent indicators using mRNA expression data from TCGA and GTEx. The RF algorithm was determined to be the most suitable and used to construct the diagnostic model with the combined MDGs, which was then validated by GSE39582 from GEO. Prognostic biomarkers were used to establish the risk score model, which was generated by univariate and multivariate Cox regression analyses. Moreover, we constructed and validated a nomogram that integrated the risk score and clinical information, including age, gender, and tumor stage. Results: 9 out of 10 MDGs performed well as independent diagnostic predictors, and STK33 and EPHX4 were also found to be associated with overall survival (OS). The results of the nomogram suggest that it is a better predictive model for prognosis than the risk score model. Conclusion: Our findings suggest that the identified MDGs could be biomarkers for diagnosis and prognosis of CRC.

The present study aimed to construct a novel methylation-related prognostic model based on microsatellite status that may enhance the prognosis of colorectal cancer (CRC) from methylation and microsatellite status perspective. DNA methylation and mRNA expression data with clinical information were downloaded from The Cancer Genome Atlas (TCGA) data set. The samples were divided into microsatellite stability and microsatellite instability group, and CIBERSORT was used to assess the immune cell infiltration characteristics. After identifying the differentially methylated genes and differentially expression genes using R packages, the methylation-driven genes were further identified. Prognostic genes that were used to establish the methylation-related risk score model were generated by the univariate and multivariate Cox regression model. Finally, we established and evaluated the methylation-related prognostic model for CRC patients. A total of 69 MDGs were obtained and three of these genes (MIOX, TH, DKFZP434K028) were selected to construct the prognostic model. Patients in the low-risk score group had a conspicuously better overall survival than those in the high-risk score group (p < .0001). The area under the receiver operating characteristic curve for this model was 0.689 at 3 years, 0.674 at 4 years, and 0.658 at 5 years. The Wilcoxon test showed that higher risk score was associated with higher T stage (p = .01), N stages (p = .0028), metastasis (p = .013), and advanced pathological stage (p = .0013). However, the more instability of microsatellite status, the lower risk score of CRC patients (p = .0048). Our constructed methylation-related prognostic model based on microsatellite status presents potential significance in assessing recurrence risk stratification, tumor staging, and immunotherapy for CRC patients.

The accurate interpretation of BRCA1/2 variants becomes increasingly important in breast cancer and other related cancers including ovarian cancer, prostate cancer, pancreatic cancer and so forth. In the past decades, especially before year 2015, limitations of techniques and lack of databases and guidelines have led to possible misinterpretation of the clinical significance of sequence variants of BRCA1/2. A published study reported reclassification of some BRCA1/2 variants previously classified as variants of uncertain significance (VUS) to likely pathogenic in breast or ovarian cancer patients from Korea. However, little is known about the situation in Chinese population. We retrospectively retrieved 109 publications studying about BRCA1/2 variants of Chinese population from the year 1999 to year 2019 (March). After excluding publications of meta-analysis and publications with missing data, 72 publications were eventually retained for subsequent analysis. In total, 1,351 BRCA variants (673 BRCA1 variants and 678 BRCA2 variants) derived from 42,430 Chinese cancer patients were standardized and reinterpreted using ACMG/AMP 2015 guidelines and China Expert Consensus on BRCA variant interpretation by genetic counselors. Among the 1,351 BRCA variants, the majority of interpretation (91.7%, 1,239/1,351) remained the same as previously published. However, there were 112 (8.3%, 112/1,351) variants (64 BRCA1, 48 BRCA2) reclassified with different categories. Our results demonstrated that clinical significance of not only VUS, but also pathogenic/likely pathogenic variants varied from time to time in the Chinese population. Precise reinterpretation of BRCA1/2 variants is of crucial importance to genetic counseling or clinical decision-making for risk individuals or patients.

It is estimated that ∼1% of European ancestry patients clinically diagnosed with type 1 diabetes (T1D) actually have monogenic forms of the disease. Because of the much lower incidence of true T1D in East Asians, we hypothesized that the percentage would be much higher. To test this, we sequenced the exome of 82 Chinese Han patients clinically diagnosed with T1D but negative for three autoantibodies. Analysis focused on established or proposed monogenic diabetes genes. We found credible mutations in 18 of the 82 autoantibody-negative patients (22%). All mutations had consensus pathogenicity support by five algorithms. As in Europeans, the most common gene was HNF1A (MODY3), in 6 of 18 cases. Surprisingly, almost as frequent were diallelic mutations in WFS1, known to cause Wolfram syndrome but also described in nonsyndromic cases. Fasting C-peptide varied widely and was not predictive. Given the 27.4% autoantibody negativity in Chinese and 22% mutation rate, we estimate that ∼6% of Chinese with a clinical T1D diagnosis have monogenic diabetes. Our findings support universal sequencing of autoantibody-negative cases as standard of care in East Asian patients with a clinical T1D diagnosis. Nonsyndromic diabetes with WSF1 mutations is not rare in Chinese. Its response to alternative treatments should be investigated.