Rapid Genome Sequencing Shows Diagnostic Utility In Infants With Congenital Heart Defects.

Congenital heart disease (CHD) is the most common birth defect and a leading cause of infant mortality. CHD often has a genetic etiology and recent studies demonstrate utility in genetic testing. In clinical practice, decisions around genetic testing choices continue to evolve, and the incorporation of rapid genome sequencing (rGS) in CHD has not been well studied. Though smaller studies demonstrate the value of rGS, they also highlight the burden of results interpretation. We analyze genetic testing in CHD at two time-points, in 2018 and 2022-2023, across a change in clinical testing guidelines from chromosome microarray (CMA) to rGS. Analysis of 421 hospitalized infants with CHD demonstrated consistent genetic testing across time. Overall, after incorporation of rGS in 2022-2023, the diagnostic yield was 6.8% higher compared to 2018, and this pattern was consistent across all patient subtypes analyzed. In 2018, CMA was the most common test performed, with diagnostic results for CHD in 14.3%, while in 2022-2023, rGS was the most frequent test performed, with results diagnostic for CHD in 16.9%. Additionally, rGS identified 44% more unique genetic diagnoses than CMA. This is the largest study to highlight the value of rGS in CHD and has important implications for management.

A gene-based association test of interactions for maternal-fetal genotypes identifies genes associated with nonsyndromic congenital heart defects.

The risk of congenital heart defects (CHDs) may be influenced by maternal genes, fetal genes, and their interactions. Existing methods commonly test the effects of maternal and fetal variants one-at-a-time and may have reduced statistical power to detect genetic variants with low minor allele frequencies. In this article, we propose a gene-based association test of interactions for maternal-fetal genotypes (GATI-MFG) using a case-mother and control-mother design. GATI-MFG can integrate the effects of multiple variants within a gene or genomic region and evaluate the joint effect of maternal and fetal genotypes while allowing for their interactions. In simulation studies, GATI-MFG had improved statistical power over alternative methods, such as the single-variant test and functional data analysis (FDA) under various disease scenarios. We further applied GATI-MFG to a two-phase genome-wide association study of CHDs for the testing of both common variants and rare variants using 947 CHD case mother-infant pairs and 1306 control mother-infant pairs from the National Birth Defects Prevention Study (NBDPS). After Bonferroni adjustment for 23,035 genes, two genes on chromosome 17, TMEM107 (p = 1.64e-06) and CTC1 (p = 2.0e-06), were identified for significant association with CHD in common variants analysis. Gene TMEM107 regulates ciliogenesis and ciliary protein composition and was found to be associated with heterotaxy. Gene CTC1 plays an essential role in protecting telomeres from degradation, which was suggested to be associated with cardiogenesis. Overall, GATI-MFG outperformed the single-variant test and FDA in the simulations, and the results of application to NBDPS samples are consistent with existing literature supporting the association of TMEM107 and CTC1 with CHDs.

Genetic Testing Guidelines Impact Care in Newborns with Congenital Heart Defects.

OBJECTIVE: To evaluate genetic evaluation practices in newborns with the most common birth defect, congenital heart defects (CHD), we determined the prevalence and the yield of genetic evaluation across time and across patient subtypes, before and after implementation of institutional genetic testing guidelines. STUDY DESIGN: This was a retrospective, cross-sectional study of 664 hospitalized newborns with CHD using multivariate analyses of genetic evaluation practices across time and patient subtypes. RESULTS: Genetic testing guidelines for hospitalized newborns with CHD were implemented in 2014, and subsequently genetic testing increased (40% in 2013 and 75% in 2018, OR 5.02, 95% CI 2.84-8.88, P < .001) as did medical geneticists' involvement (24% in 2013 and 64% in 2018, P < .001). In 2018, there was an increased use of chromosomal microarray (P < .001), gene panels (P = .016), and exome sequencing (P = .001). The testing yield was high (42%) and consistent across years and patient subtypes analyzed. Increased testing prevalence (P < .001) concomitant with consistent testing yield (P = .139) added an estimated 10 additional genetic diagnoses per year, reflecting a 29% increase. CONCLUSIONS: In patients with CHD, yield of genetic testing was high. After implementing guidelines, genetic testing increased significantly and shifted to newer sequence-based methods. Increased use of genetic testing identified more patients with clinically important results with potential to impact patient care.

Learning to Crawl: Determining the Role of Genetic Abnormalities on Postoperative Outcomes in Congenital Heart Disease.

Background Our cardiac center established a systematic approach for inpatient cardiovascular genetics evaluations of infants with congenital heart disease, including routine chromosomal microarray (CMA) testing. This provides a new opportunity to investigate correlation between genetic abnormalities and postoperative course. Methods and Results Infants who underwent congenital heart disease surgery as neonates (aged ≤28 days) from 2015 to 2020 were identified. Cases with trisomy 21 or 18 were excluded. Diagnostic genetic results or CMA with variant of uncertain significance were considered abnormal. We compared postoperative outcomes following initial congenital heart disease surgery in patients found to have genetic abnormality to those who had negative CMA. Among 355 eligible patients, genetics consultations or CMA were completed in 88%. A genetic abnormality was identified in 73 patients (21%), whereas 221 had negative CMA results. Genetic abnormality was associated with prematurity, extracardiac anomaly, and lower weight at surgery. Operative mortality rate was 9.6% in patients with a genetic abnormality versus 4.1% in patients without an identified genetic abnormality (P=0.080). Mortality was similar when genetic evaluations were diagnostic (9.3%) or identified a variant of uncertain significance on CMA (10.0%). Among 14 patients with 22q11.2 deletion, the 2 mortality cases had additional CMA findings. In patients without extracardiac anomaly, genetic abnormality was independently associated with increased mortality (P=0.019). CMA abnormality was not associated with postoperative length of hospitalization, extracorporeal membrane oxygenation, or >7 days to initial extubation. Conclusions Routine genetic evaluations and CMA may help to stratify mortality risk in severe congenital heart disease with syndromic or nonsyndromic presentations.

Random field modeling of multi-trait multi-locus association for detecting methylation quantitative trait loci.

MOTIVATION: CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another. RESULTS: We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD. AVAILABILITY AND IMPLEMENTATION: https://github.com/chenlyu2656/Multi-MRF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detecting methylation quantitative trait loci using a methylation random field method.

DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease.

BACKGROUND: Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression. RESULTS: We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues. CONCLUSIONS: Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Identifying Susceptibility Loci for Cutaneous Squamous Cell Carcinoma Using a Fast Sequence Kernel Association Test.

Cutaneous squamous cell carcinoma (cSCC) accounts for about 20% of all skin cancers, the most common type of malignancy in the United States. Genome-wide association studies (GWAS) have successfully identified multiple genetic variants associated with the risk of cSCC. Most of these studies were single-locus-based, testing genetic variants one-at-a-time. In this article, we performed gene-based association tests to evaluate the joint effect of multiple variants, especially rare variants, on the risk of cSCC by using a fast sequence kernel association test (fastSKAT). The study included 1,710 cSCC cases and 24,304 cancer-free controls from the Nurses' Health Study, the Nurses' Health Study II and the Health Professionals Follow-up Study. We used UCSC Genome Browser to define gene units as candidate loci, and further evaluated the association between all variants within each gene unit and disease outcome. Four genes HP1BP3, DAG1, SEPT7P2, and SLFN12 were identified using Bonferroni adjusted significance level. Our study is complementary to the existing GWASs, and our findings may provide additional insights into the etiology of cSCC. Further studies are needed to validate these findings.

Microwave-assisted synthesis of porphyrin conjugated microporous polymers for microextraction of volatile organic acids in tobaccos.

Conjugated microporous polymers (CMPs) with permanent microporosity and extended p-conjugated skeletons have recently shown the fascinating application in separation and enrichment. In this report, porphyrin CMP that possessed microporous structure and nitrogen-rich pyrrole building blocks was successfully synthesized by microwave-assisted method. Then, a novel coating based on porphyrin CMP was fabricated on silica fiber for efficient enrichment volatile organic acids (VOAs). The simulation showed the coating exhibited strong interaction with volatile organic acids based on charge transfer interaction, hydrogen bond and size effect. Hence, we proposed a method for determination of volatile organic acids in tobaccos by headspace solid-phase microextraction (HS-SPME) with porphyrin CMP coating by gas chromatography-mass spectrometry. The results showed that the coating provided high enrichment factors for VOAs ranging from 66,657 to 133,970 and low limits of detection from 4.6 to 22 ng/L. A good linearity was observed for propionic acid and crotonic acid ranging from 0.050 to 8.0 µg/L, 2-methylheptanoic acid ranging from 0.063 to 1.5 µg/L, others ranging from 0.025 to 3.0 µg/L with the determination coefficient (R2) between 0.9900 and 0.9980. The strategy for determination of volatile compounds in complex solid samples was successfully applied to the analysis of volatile organic acids in tobacco leaves. The results showed that the method was accurate and reliable.

Preparation of Fe3O4@PPy magnetic nanoparticles as solid-phase extraction sorbents for preconcentration and separation of phthalic acid esters in water by gas chromatography-mass spectrometry.

The purpose of this paper is to introduce a solid-phase extraction method of separating and determining of phthalic acid esters (PAEs) by PPy-coated Fe3O4 magnetic nanoparticles (Fe3O4@PPy MNPs). In the process, nanoparticles were served as sorbents and the optimal conditions of the extraction have been explored. The composite was synthesized through the chemical oxidation method, combining pyrrole monomer with Fe3O4 magnetic ball in the form of aggregation state and the coated nanoparticles possessed core-shell construction. The PPy-coated Fe3O4 magnetic microspheres have been extensively characterized by transmission electron microscopy, Fourier transform infrared spectroscopy and vibrating sample magnetometry. The optimum conditions were investigated by orthogonal experimental design, which was used to testing the influence of main factors and the interactions among them. The orthoplan is famous for the merit that it can study the whole experiments comprehensively through minimal tests. Under the optimal extraction conditions: 20mg of modified magnetite nanoparticles, eluting with acetic ester of 2mL, 40min of MSPE, eluting in 1h and 20mL of sample volume, good linearity (r(2)>0.9912) of all calibration curves was obtained in validation experiments. And the limits of detection (LODs) were from 0.006 to 0.021ng/mL. The recoveries in different sample matrices were in the range from 80.4% to 108.2% with relative standard deviations less than 12.8%. The present work demonstrates the applicability of the developed method for the determination of PAEs in water sample and the results justified that it can be applied successfully to the selective isolation and enrichment of PAEs in real water samples.