A Genetic Variant in FIGN Gene Reduces the Risk of Congenital Heart Disease in Han Chinese Populations

The fidgetin family: Shaking things up among the microtubule-severing enzymes

The microtubule cytoskeleton is required for several crucial cellular processes, including chromosome segregation, cell polarity and orientation, and intracellular transport. These functions rely on microtubule stability and dynamics, which are regulated by microtubule-binding proteins (MTBPs). One such type of regulator is the microtubule-severing enzymes (MSEs), which are ATPases Associated with Diverse Cellular Activities (AAA+ ATPases). The most recently identified family are the fidgetins, which contain three members: fidgetin, fidgetin-like 1 (FL1), and fidgetin-like 2 (FL2). Of the three known MSE families, the fidgetins have the most diverse range of functions in the cell, spanning mitosis/meiosis, development, cell migration, DNA repair, and neuronal function. Furthermore, they offer intriguing novel therapeutic targets for cancer, cardiovascular disease, and wound healing. In the two decades since their first report, there has been great progress in our understanding of the fidgetins; however, there is still much left unknown about this unusual family. This review aims to consolidate the present body of knowledge of the fidgetin family of MSEs and to inspire deeper exploration into the fidgetins and the MSEs as a whole.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Genomic frontiers in congenital heart disease

The application of next-generation sequencing to study congenital heart disease (CHD) is increasingly providing new insights into the causes and mechanisms of this prevalent birth anomaly. Whole-exome sequencing analysis identifies damaging gene variants altering single or contiguous nucleotides that are assigned pathogenicity based on statistical analyses of families and cohorts with CHD, high expression in the developing heart and depletion of damaging protein-coding variants in the general population. Gene classes fulfilling these criteria are enriched in patients with CHD and extracardiac abnormalities, evidencing shared pathways in organogenesis. Developmental single-cell transcriptomic data demonstrate the expression of CHD-associated genes in particular cell lineages, and emerging insights indicate that genetic variants perturb multicellular interactions that are crucial for cardiogenesis. Whole-genome sequencing analyses extend these observations, identifying non-coding variants that influence the expression of genes associated with CHD and contribute to the estimated ~55% of unexplained cases of CHD. These approaches combined with the assessment of common and mosaic genetic variants have provided a more complete knowledge of the causes and mechanisms of CHD. Such advances provide knowledge to inform the clinical care of patients with CHD or other birth defects and deepen our understanding of the complexity of human development. In this Review, we highlight known and candidate CHD-associated human genes and discuss how the integration of advances in developmental biology research can provide new insights into the genetic contributions to CHD.

Associations between IL-6 Variations and Congenital Heart Disease Incidence among Chinese Han People

Background

Our research explored if Interleukin-6 (IL-6) variants held substantial connection to congenital heart disease (CHD) susceptibility among Chinese Han children.

Material/Methods

A total of 102 CHD children were recruited as the case group while 98 healthy persons were recruited as the control group. We used polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) completed genotyping for IL-6 variants rs1800795 and rs1800796. The Hardy-Weinberg equilibrium (HWE) among controls was tested using χ² analysis. Genotype and allele frequencies for variants were compared between groups. Odds ratio (OR) accompanied by 95% confidence interval (CI) reflected the potential link of IL-6 variants to CHD occurrence.

Results

A remarkable increased trend of rs1800795 CC genotype and C allele was detected in the CHD patient group (P<0.05). Individuals carrying rs1800795 CC genotype showed higher risk for CHD (OR=3.763, 95% CI=1.162–12.190). In addition, rs1800795 C allele could increase CHD incidence (OR=1.766, 95% CI=1.101–2.832). No significant differences were detected in IL-6 gene rs1800796 polymorphism in both genotype and allele distributions between the case group and the control group (P>0.05). These associations had no significant alteration after the adjustment of age, gender, maternal smoking history, and maternal history of diabetes.

Conclusions

IL-6 variant rs1800795 exhibited a close relation to CHD susceptibility among Chinese Han people while the mutant C allele promoted CHD incidence. But rs1800796 variant showed no such influence.

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common, complex genetic disorder affecting up to 15% of reproductive-age women worldwide, depending on the diagnostic criteria applied. These diagnostic criteria are based on expert opinion and have been the subject of considerable controversy. The phenotypic variation observed in PCOS is suggestive of an underlying genetic heterogeneity, but a recent meta-analysis of European ancestry PCOS cases found that the genetic architecture of PCOS defined by different diagnostic criteria was generally similar, suggesting that the criteria do not identify biologically distinct disease subtypes. We performed this study to test the hypothesis that there are biologically relevant subtypes of PCOS.

METHODS AND FINDINGS

Using biochemical and genotype data from a previously published PCOS genome-wide association study (GWAS), we investigated whether there were reproducible phenotypic subtypes of PCOS with subtype-specific genetic associations. Unsupervised hierarchical cluster analysis was performed on quantitative anthropometric, reproductive, and metabolic traits in a genotyped cohort of 893 PCOS cases (median and interquartile range [IQR]: age = 28 [25-32], body mass index [BMI] = 35.4 [28.2-41.5]). The clusters were replicated in an independent, ungenotyped cohort of 263 PCOS cases (median and IQR: age = 28 [24-33], BMI = 35.7 [28.4-42.3]). The clustering revealed 2 distinct PCOS subtypes: a "reproductive" group (21%-23%), characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low BMI and insulin levels, and a "metabolic" group (37%-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH levels. We performed a GWAS on the genotyped cohort, limiting the cases to either the reproductive or metabolic subtypes. We identified alleles in 4 loci that were associated with the reproductive subtype at genome-wide significance (PRDM2/KAZN, P = 2.2 × 10-10; IQCA1, P = 2.8 × 10-9; BMPR1B/UNC5C, P = 9.7 × 10-9; CDH10, P = 1.2 × 10-8) and one locus that was significantly associated with the metabolic subtype (KCNH7/FIGN, P = 1.0 × 10-8). We developed a predictive model to classify a separate, family-based cohort of 73 women with PCOS (median and IQR: age = 28 [25-33], BMI = 34.3 [27.8-42.3]) and found that the subtypes tended to cluster in families and that carriers of previously reported rare variants in DENND1A, a gene that regulates androgen biosynthesis, were significantly more likely to have the reproductive subtype of PCOS. Limitations of our study were that only PCOS cases of European ancestry diagnosed by National Institutes of Health (NIH) criteria were included, the sample sizes for the subtype GWAS were small, and the GWAS findings were not replicated.

CONCLUSIONS

In conclusion, we have found reproducible reproductive and metabolic subtypes of PCOS. Furthermore, these subtypes were associated with novel, to our knowledge, susceptibility loci. Our results suggest that these subtypes are biologically relevant because they appear to have distinct genetic architecture. This study demonstrates how phenotypic subtyping can be used to gain additional insights from GWAS data.

Race-specific alterations in DNA methylation among middle-aged African Americans and Whites with metabolic syndrome

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors for all-cause mortality, cardiovascular disease, and cancer. Identifying epigenetic alterations associated with MetS in African Americans (AAs) and Whites may provide insight into genes that influence its differential health outcomes. We examined DNA methylation (DNAm) and performed an epigenome-wide association study (EWAS) of MetS among AAs and Whites with and without MetS. We assessed age, race and poverty status associated DNAm among AAs (n = 225) and White (n = 233) adults using NCEP-ATP III guidelines. Genome-wide DNAm measurement was assessed using Illumina Infinium Methylation EPIC BeadChip. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) were identified using dmpFinder and bumphunter. EWAS was performed using CpGassoc. We found significant DMPs associated with age, poverty status and MetS in each race. GSTT1(Glutathione S-Transferase Theta 1) was one of the top-hypermethylated genes and MIPEP (Mitochondrial Intermediate Peptidase) was one of the most hypomethylated genes when comparing AAs with and without MetS. PPP1R13L (Protein Phosphatase 1 Regulatory Subunit 13 Like) was the top hypermethylated and SCD (stearoyl-CoA desaturase-1) was one of the most hypomethylated genes for Whites with and without MetS. EWAS results showed that DNAm differences might contribute to MetS risk among Whites and AAs since different genes were identified in AAs and Whites. We replicated previously identified MetS associated genes and found that Thioredoxin-interacting protein (TXN1P) was statistically significantly differentially expressed only in Whites. Our results may be useful in further studies of genes underlying differences in MetS among AAs and Whites.