Maternal cell-free DNA-based screening for fetal microdeletion and the importance of careful diagnostic follow-up.

BackgroundNoninvasive prenatal screening (NIPS) by next-generation sequencing of cell-free DNA (cfDNA) in maternal plasma is used to screen for common aneuploidies such as trisomy 21 in high risk pregnancies. NIPS can identify fetal genomic microdeletions; however, sensitivity and specificity have not been systematically evaluated. Commercial companies have begun to offer expanded panels including screening for common microdeletion syndromes such as 22q11.2 deletion (DiGeorge syndrome) without reporting the genomic coordinates or whether the deletion is maternal or fetal. Here we describe a phenotypically normal mother and fetus who tested positive for atypical 22q deletion via maternal plasma cfDNA testing.MethodsWe performed cfDNA sequencing on saved maternal plasma obtained at 11 weeks of gestation from a phenotypically normal woman with a singleton pregnancy whose earlier screening at a commercial laboratory was reported to be positive for a 22q11.2 microdeletion. Fluorescence in situ hybridization and chromosomal microarray diagnostic genetic tests were done postnatally.ConclusionNIPS detected a 22q microdeletion that, upon diagnostic workup, did not include the DiGeorge critical region. Diagnostic prenatal or postnatal testing with chromosomal microarray and appropriate parental studies to determine precise genomic coordinates and inheritance should follow a positive microdeletion NIPS result

Structural and Regulatory Characterization of the Placental Epigenome at Its Maternal Interface

Epigenetics can be loosely defined as the study of cellular “traits” that influence biological phenotype in a fashion that is not dependent on the underlying primary DNA sequence. One setting in which epigenetics is likely to have a profound influence on biological phenotype is during intrauterine development. In this context there is a defined and critical window during which balanced homeostasis is essential for normal fetal growth and development. We have carried out a detailed structural and functional analysis of the placental epigenome at its maternal interface. Specifically, we performed genome wide analysis of DNA methylation in samples of chorionic villus (CVS) and maternal blood cells (MBC) using both commercially available and custom designed microarrays. We then compared these data with genome wide transcription data for the same tissues. In addition to the discovery that CVS genomes are significantly more hypomethylated than their MBC counterparts, we identified numerous tissue-specific differentially methylated regions (T-DMRs). We further discovered that these T-DMRs are clustered spatially along the genome and are enriched for genes with tissue-specific biological functions. We identified unique patterns of DNA methylation associated with distinct genomic structures such as gene bodies, promoters and CpG islands and identified both direct and inverse relationships between DNA methylation levels and gene expression levels in gene bodies and promoters respectively. Furthermore, we found that these relationships were significantly associated with CpG content. We conclude that the early gestational placental DNA methylome is highly organized and is significantly and globally associated with transcription. These data provide a unique insight into the structural and regulatory characteristics of the placental epigenome at its maternal interface and will drive future analyses of the role of placental dysfunction in gestational disease

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

The advent of large pre-trained models has brought about a paradigm shift in both visual representation learning and natural language processing. However, clustering unlabeled images, as a fundamental and classic machine learning problem, still lacks effective solution, particularly for large-scale datasets. In this paper, we propose a novel image clustering pipeline that leverages the powerful feature representation of large pre-trained models such as CLIP and cluster images effectively and efficiently at scale. We show that the pre-trained features are significantly more structured by further optimizing the rate reduction objective. The resulting features may significantly improve the clustering accuracy, e.g., from 57\% to 66\% on ImageNet-1k. Furthermore, by leveraging CLIP's image-text binding, we show how the new clustering method leads to a simple yet effective self-labeling algorithm that successfully works on unlabeled large datasets such as MS-COCO and LAION-Aesthetics. We will release the code in https://github.com/LeslieTrue/CPP.Comment: 21 pages, 13 figure

Selective hypermethylation is evident in small intestine samples from infants with necrotizing enterocolitis

OBJECTIVE: Necrotizing enterocolitis (NEC) is the most common and lethal gastrointestinal disease affecting preterm infants. NEC develops suddenly and is characterized by gut barrier destruction, an inflammatory response, intestinal necrosis and multi-system organ failure. There is currently no method for early NEC detection, and the pathogenesis of NEC remains unclear. DESIGN: To further understand the molecular mechanisms that support NEC, we used solution phase hybridization and next-generation DNA sequencing of bisulfite converted DNA to perform targeted genome-wide analysis of DNA methylation at high read depth. RESULTS: We found that ileal samples from surgical NEC infants (n = 5) exist in a broadly hypermethylated state relative to their non-NEC counterparts (n = 9). These trends were not uniform, with hypermethylation being most consistently observed outside CpG islands and promoters. We further identified several biologically interesting gene promoters that displayed differential methylation in NEC and a number of biological pathways that appear dysregulated in NEC. We also found that DNA methylation patterns identified in ileal NEC tissue were correlated with those found and published previously in stool samples from NEC-affected infants. CONCLUSION: We confirmed that surgical NEC is associated with broad DNA hypermethylation in the ileum, and this may be detectable in stool samples of affected individuals. Thus, an epigenomic liquid biopsy of stool may have significant potential as a biomarker with respect to the diagnostic/predictive detection of NEC. Our findings, along with recent similar observations in colon, suggest that epigenomic dysregulation is a significant feature of surgical NEC. These findings motivate future studies which will involve the longitudinal screening of samples obtained prior to the onset of NEC. Our long-term goal is the development of novel screening, diagnostic and phenotyping methods for NEC