From Compressed-Sensing to Deep Learning MR: Comparative Biventricular Cardiac Function Analysis in a Patient Cohort.

BACKGROUND: Conventional segmented, retrospectively gated cine (Conv-cine) is challenged in patients with breath-hold difficulties. Compressed sensing (CS) has shown values in cine imaging but generally requires long reconstruction time. Recent artificial intelligence (AI) has demonstrated potential in fast cine imaging. PURPOSE: To compare CS-cine and AI-cine with Conv-cine in quantitative biventricular functions, image quality, and reconstruction time. STUDY TYPE: Prospective human studies. SUBJECTS: 70 patients (age, 39 ± 15 years, 54.3% male). FIELD STRENGTH/SEQUENCE: 3T; balanced steady state free precession gradient echo sequences. ASSESSMENT: Biventricular functional parameters of CS-, AI-, and Conv-cine were measured by two radiologists independently and compared. The scan and reconstruction time were recorded. Subjective scores of image quality were compared by three radiologists. STATISTICAL TESTS: Paired t-test and two related-samples Wilcoxon sign test were used to compare biventricular functional parameters between CS-, AI-, and Conv-cine. Intraclass correlation coefficient (ICC), Bland-Altman analysis, and Kendall's W method were applied to evaluate agreement of biventricular functional parameters and image quality of these three sequences. A P-value <0.05 was considered statistically significant, and standardized mean difference (SMD) < 0. 100 was considered no significant difference. RESULTS: Compared to Conv-cine, no statistically significant differences were identified in CS- and AI-cine function results (all P > 0.05), except for very small differences in left ventricle end-diastole volumes of 2.5 mL (SMD = 0.082) and 4.1 mL (SMD = 0.096), respectively. Bland-Altman scatter plots revealed that biventricular function results were mostly distributed within the 95% confidence interval. All parameters had acceptable to excellent interobserver agreements (ICC: 0.748-0.989). Compared with Conv-cine (84 ± 13 sec), both CS (14 ± 2 sec) and AI (15 ± 2 sec) techniques reduced scan time. Compared with CS-cine (304 ± 17 sec), AI-cine (24 ± 4 sec) reduced reconstruction time. CS-cine demonstrated significantly lower quality scores than Conv-cine, while AI-cine demonstrated similar scores (P = 0.634). CONCLUSION: CS- and AI-cine can achieve whole-heart cardiac cine imaging in a single breath-hold. Both CS- and AI-cine have the potential to supplement the gold standard Conv-cine in studying biventricular functions and benefit patients having difficulties with breath-holds. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

A two-part mixed-effects model for analyzing longitudinal microbiome compositional data.

MOTIVATION: The human microbial communities are associated with many human diseases such as obesity, diabetes and inflammatory bowel disease. High-throughput sequencing technology has been widely used to quantify the microbial composition in order to understand its impacts on human health. Longitudinal measurements of microbial communities are commonly obtained in many microbiome studies. A key question in such microbiome studies is to identify the microbes that are associated with clinical outcomes or environmental factors. However, microbiome compositional data are highly skewed, bounded in [0,1), and often sparse with many zeros. In addition, the observations from repeated measures in longitudinal studies are correlated. A method that takes into account these features is needed for association analysis in longitudinal microbiome data. RESULTS: In this paper, we propose a two-part zero-inflated Beta regression model with random effects (ZIBR) for testing the association between microbial abundance and clinical covariates for longitudinal microbiome data. The model includes a logistic regression component to model presence/absence of a microbe in the samples and a Beta regression component to model non-zero microbial abundance, where each component includes a random effect to account for the correlations among the repeated measurements on the same subject. Both simulation studies and the application to real microbiome data have shown that ZIBR model outperformed the previously used methods. The method provides a useful tool for identifying the relevant taxa based on longitudinal or repeated measures in microbiome research. AVAILABILITY AND IMPLEMENTATION: https://github.com/chvlyl/ZIBR CONTACT: hongzhe@upenn.edu.

Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production.

OBJECTIVE: The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. DESIGN AND RESULTS: Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. CONCLUSIONS: Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites.

EUS-guided liver biopsy provides diagnostic samples comparable with those via the percutaneous or transjugular route.

BACKGROUND AND AIMS: Liver biopsy (LB) traditionally has been performed via a percutaneous (PC), transjugular (TJ), or surgical approach. EUS-guided LB (EUS-LB) is an emerging method that has shown promise in terms of tissue yield and procedural safety. Comparison of histologic yield of EUS-LB with other methods of LB has not been done. This study aimed to compare tissue yield of different LB methods. METHODS: EUS-LB, TJ-LB, and PC-LB were identified retrospectively. EUS-LB was obtained via transgastric and transduodenal biopsy, or via transgastric (left lobe) biopsy alone using a 19-gauge FNA needle (non-Trucut). TJ-LB specimens were obtained with an 18- or 19-gauge needle, and PC-LB specimens with an 18- or 20-gauge needle. Stained slides were digitized on a whole slide scanner, and the total specimen length (TSL) and the count of complete portal triads (CPTs) were determined. Comparisons of TSL and CPT among the 3 groups were done with Wilcoxon rank sum tests. RESULTS: Wilcoxon rank sum tests indicated that EUS-LB of both liver regions produced significantly more tissue in terms of both TSL and CPTs compared with a PC-LB (P = .0000 and .0006). EUS-LB produced significantly longer TSL than TJ-LB (P = .01) and similar CPTs (P = .22). Those EUS-LB cases in which the left lobe only was sampled were not statistically different compared with PC-LB and TJ-LB. CONCLUSION: EUS-guided-LB produces specimens at least comparable to, and in some cases better than, PC-LB or TJ-LB. Widely separated liver regions can be easily sampled, which may have some benefit. The role of EUS-LB is likely to increase in the future.

Nonhematopoietically derived DNA is shorter than hematopoietically derived DNA in plasma: a transplantation model.

BACKGROUND: Plasma DNA is predominantly hematopoietic in origin. The size difference between maternal- and fetal-derived DNA in maternal plasma prompted us to investigate whether there was any discrepancy in molecular size between hematopoietically and nonhematopoietically derived DNA in plasma. METHODS: Plasma DNA samples from 6 hematopoietic stem cell transplant recipients and 1 liver transplant recipient were analyzed by massively parallel paired-end sequencing. The size of each fragment was deduced from the alignment positions of the paired reads. In sex-mismatched transplant recipients, the reads from chromosome Y were used as markers for the male donor/recipient. For other transplant recipients, the reads of the donor- and recipient-specific alleles were identified from the single-nucleotide polymorphism genotypes. RESULTS: In male patients receiving female hematopoietic stem cells, more chromosome Y-derived DNA molecules (nonhematopoietically derived) were ≤150 bp than the autosome-derived ones (mainly hematopoietically derived) (median difference, 9.9%). In other hematopoietic stem cell transplant recipients, more recipient-specific DNA molecules (nonhematopoietically derived) were ≤150 bp than the donor-specific ones (hematopoietically derived) (median difference, 14.8%). In the liver transplant recipient, more donor-derived DNA molecules (liver derived) were ≤150 bp than the recipient-derived ones (mainly hematopoietically derived) (difference, 13.4%). The nonhematopoietically derived DNA exhibited a reduction in a 166-bp peak compared with the hematopoietically derived DNA. A 10-bp periodicity in size distribution below approximately 143 bp was observed in both DNA populations. CONCLUSIONS: Massively parallel sequencing is a powerful tool for studying posttransplantation chimerism. Plasma DNA molecules exhibit a distinct fragmentation pattern, with the nonhematopoietically derived molecules being shorter than the hematopoietically derived ones.

Pyramid Convolutional RNN for MRI Image Reconstruction.

Fast and accurate MRI image reconstruction from undersampled data is crucial in clinical practice. Deep learning based reconstruction methods have shown promising advances in recent years. However, recovering fine details from undersampled data is still challenging. In this paper, we introduce a novel deep learning based method, Pyramid Convolutional RNN (PC-RNN), to reconstruct images from multiple scales. Based on the formulation of MRI reconstruction as an inverse problem, we design the PC-RNN model with three convolutional RNN (ConvRNN) modules to iteratively learn the features in multiple scales. Each ConvRNN module reconstructs images at different scales and the reconstructed images are combined by a final CNN module in a pyramid fashion. The multi-scale ConvRNN modules learn a coarse-to-fine image reconstruction. Unlike other common reconstruction methods for parallel imaging, PC-RNN does not employ coil sensitive maps for multi-coil data and directly model the multiple coils as multi-channel inputs. The coil compression technique is applied to standardize data with various coil numbers, leading to more efficient training. We evaluate our model on the fastMRI knee and brain datasets and the results show that the proposed model outperforms other methods and can recover more details. The proposed method is one of the winner solutions in the 2019 fastMRI competition.

Mitochondrial dysfunction in inflammatory bowel disease alters intestinal epithelial metabolism of hepatic acylcarnitines.

As the interface between the gut microbiota and the mucosal immune system, there has been great interest in the maintenance of colonic epithelial integrity through mitochondrial oxidation of butyrate, a short-chain fatty acid produced by the gut microbiota. Herein, we showed that the intestinal epithelium could also oxidize long-chain fatty acids, and that luminally delivered acylcarnitines in bile could be consumed via apical absorption by the intestinal epithelium, resulting in mitochondrial oxidation. Finally, intestinal inflammation led to mitochondrial dysfunction in the apical domain of the surface epithelium that may reduce the consumption of fatty acids, contributing to higher concentrations of fecal acylcarnitines in murine Citrobacter rodentium-induced colitis and human inflammatory bowel disease. These results emphasized the importance of both the gut microbiota and the liver in the delivery of energy substrates for mitochondrial metabolism by the intestinal epithelium.

From Deep Learning Towards Finding Skin Lesion Biomarkers.

Melanoma is a type of skin cancer with the most rapidly increasing incidence. Early detection of melanoma using dermoscopy images significantly increases patients' survival rate. However, accurately classifying skin lesions by eye, especially in the early stage of melanoma, is extremely challenging for the dermatologists. Hence, the discovery of reliable biomarkers will be meaningful for melanoma diagnosis. In recent years, the value of deep learning empowered computer-assisted diagnose has been shown in biomedical imaging-based decision making. However, much deep learning research focuses on improving disease detection accuracy but not understanding the features deep learning use to determine the evidence of pathology. We aim to make sure the features used by deep learning methods are the reasonable clinical features for skin lesions diagnosis, rather than artifacts. Further, we aim to discover new biomarkers, which may not have been included in clinical criteria but do make sense to the dermatologists. Our proposed pipeline can find biomarkers for identifying different lesions. The patterns are agreed with dermatologists. Surprisingly, we find surround skins also can be used as evidence for skin lesion diagnosis, which has not been included in traditional diagnosis rules. The biomarkers discovered from deep learning classifier can be significant and useful to guide clinical diagnosis.

Skin Lesion Segmentation with C-UNet.

Malignant melanoma is one of the leading cancers around the world. It is critical to timely diagnose and treat melanoma to improve patient survival. This paper proposes a deep learning model C-UNet for skin lesion segmentation. The C-UNet incorporates the Inception-like convolutional block, the recurrent convolutional block and dilated convolutional layers. We also apply a finetune technique using Dice loss after training the model with commonly used cross-entropy loss. The conditional random field was used to further smooth predicted label maps. Experiment results show that the proposed method achieves better accuracy and more robust segmentation results than UNet.

A Model-Based Approach For Species Abundance Quantification Based On Shotgun Metagenomic Data.

The human microbiome, which includes the collective microbes residing in or on the human body, has a profound influence on the human health. DNA sequencing technology has made the large-scale human microbiome studies possible by using shotgun metagenomic sequencing. One important aspect of data analysis of such metagenomic data is to quantify the bacterial abundances based on the metagenomic sequencing data. Existing methods almost always quantify such abundances one sample at a time, which ignore certain systematic differences in read coverage along the genomes due to GC contents, copy number variation and the bacterial origin of replication. In order to account for such differences in read counts, we propose a multi-sample Poisson model to quantify microbial abundances based on read counts that are assigned to species-specific taxonomic markers. Our model takes into account the marker-specific effects when normalizing the sequencing count data in order to obtain more accurate quantification of the species abundances. Compared to currently available methods on simulated data and real data sets, our method has demonstrated an improved accuracy in bacterial abundance quantification, which leads to more biologically interesting results from downstream data analysis.

A role for bacterial urease in gut dysbiosis and Crohn's disease.

Gut dysbiosis during inflammatory bowel disease involves alterations in the gut microbiota associated with inflammation of the host gut. We used a combination of shotgun metagenomic sequencing and metabolomics to analyze fecal samples from pediatric patients with Crohn's disease and found an association between disease severity, gut dysbiosis, and bacterial production of free amino acids. Nitrogen flux studies using 15N in mice showed that activity of bacterial urease, an enzyme that releases ammonia by hydrolysis of host urea, led to the transfer of murine host-derived nitrogen to the gut microbiota where it was used for amino acid synthesis. Inoculation of a conventional murine host (pretreated with antibiotics and polyethylene glycol) with commensal Escherichia coli engineered to express urease led to dysbiosis of the gut microbiota, resulting in a predominance of Proteobacteria species. This was associated with a worsening of immune-mediated colitis in these animals. A potential role for altered urease expression and nitrogen flux in the development of gut dysbiosis suggests that bacterial urease may be a potential therapeutic target for inflammatory bowel diseases.

Genome wide nucleosome mapping for HSV-1 shows nucleosomes are deposited at preferred positions during lytic infection.

HSV is a large double stranded DNA virus, capable of causing a variety of diseases from the common cold sore to devastating encephalitis. Although DNA within the HSV virion does not contain any histone protein, within 1 h of infecting a cell and entering its nucleus the viral genome acquires some histone protein (nucleosomes). During lytic infection, partial micrococcal nuclease (MNase) digestion does not give the classic ladder band pattern, seen on digestion of cell DNA or latent viral DNA. However, complete digestion does give a mono-nucleosome band, strongly suggesting that there are some nucleosomes present on the viral genome during the lytic infection, but that they are not evenly positioned, with a 200 bp repeat pattern, like cell DNA. Where then are the nucleosomes positioned? Here we perform HSV-1 genome wide nucleosome mapping, at a time when viral replication is in full swing (6 hr PI), using a microarray consisting of 50mer oligonucleotides, covering the whole viral genome (152 kb). Arrays were probed with MNase-protected fragments of DNA from infected cells. Cells were not treated with crosslinking agents, thus we are only mapping tightly bound nucleosomes. The data show that nucleosome deposition is not random. The distribution of signal on the arrays suggest that nucleosomes are located at preferred positions on the genome, and that there are some positions that are not occupied (nucleosome free regions -NFR or Nucleosome depleted regions -NDR), or occupied at frequency below our limit of detection in the population of genomes. Occupancy of only a fraction of the possible sites may explain the lack of a typical MNase partial digestion band ladder pattern for HSV DNA during lytic infection. On average, DNA encoding Immediate Early (IE), Early (E) and Late (L) genes appear to have a similar density of nucleosomes.

Comparative Effectiveness of Nutritional and Biological Therapy in North American Children with Active Crohn's Disease.

BACKGROUND: Therapeutic targets in pediatric Crohn's disease include symptoms, quality of life (QOL), and mucosal healing. Although partial enteral nutrition (PEN), exclusive enteral nutritional (EEN), and anti-tumor necrosis factor alpha (anti-TNF) therapy all improve symptoms, the comparative effectiveness of these approaches to improve QOL and achieve mucosal healing has not been assessed prospectively. METHODS: In a prospective study of children initiating PEN, EEN, or anti-TNF therapy for Crohn's disease, we compared clinical outcomes using the Pediatric Crohn's Disease Activity Index (PCDAI), QOL (IMPACT score), and mucosal healing as estimated by fecal calprotectin (FCP). PCDAI, IMPACT, FCP, and diet (prompted 24-h recall) were measured at baseline and after 8 weeks of therapy. RESULTS: We enrolled 90 children with active Crohn's disease (PCDAI, 33.7 ± 13.7; and FCP, 976 ± 754), of whom 52 were treated with anti-TNF, 22 with EEN, and 16 with PEN plus ad lib diet. Clinical response (PCDAI reduction ≥15 or final PCDAI ≤10) was achieved by 64% on PEN, 88% EEN, and 84% anti-TNF (test for trend P = 0.08). FCP ≤250 µg/g was achieved with PEN in 14%, EEN 45%, and anti-TNF 62% (test for trend P = 0.001). Improvement in overall QOL was not statistically significantly different between the 3 groups (P = 0.86). However, QOL improvement was the greatest with EEN in the body image (P = 0.03) domain and with anti-TNF in the emotional domain (P = 0.04). CONCLUSIONS: Although PEN improved clinical symptoms, EEN and anti-TNF were more effective for decreasing mucosal inflammation and improving specific aspects of QOL.

Endoscopic ultrasound-guided liver biopsy: a multicenter experience.

BACKGROUND AND AIMS: Endoscopic ultrasound-guided (EUS) liver biopsy (LB) is proposed as a newer method that offers several advantages over existing techniques for sampling liver tissue. This study evaluated the diagnostic yield of EUS-LB as the primary outcome measure. In addition, the safety of the technique in a large patient cohort was assessed. PATIENTS AND METHODS: Patients undergoing EUS for evaluation of elevated liver enzymes or hepatic disease were included in this prospective, non-randomized, multicenter study. EUS-LB was performed with EUS-fine needle aspiration (FNA; 19-gauge needle). Tissue was formalin-fixed and stained with hematoxylin and eosin, and trichrome. Using a microscope micrometer, specimen length was measured and the number of complete portal triads (CPTs) were counted. The main outcome measure was to assess the diagnostic yield of EUS-LB, and to monitor for any procedure-related complications. RESULTS: Patients (110; median age, 53 years; 62 women) underwent EUS-LB at eight centers. The indication was abnormal liver enzymes in 96 patients. LB specimens sufficient for pathological diagnosis were obtained in 108 of 110 patients (98 %). The overall tissue yield from 110 patients was a median aggregate length of 38 mm (range, 0 - 203), with median of 14 CPTs (range, 0 - 68). There was no statistical difference in the yield between bilobar, left lobe only, or right lobe only biopsies. There was one complication (0.9 %) where self-limited bleeding occurred in a coagulopathic and thrombocytopenic patient. This complication was managed conservatively. CONCLUSIONS: EUS-guided LB was a safe technique that yields tissue adequate for diagnosis among 98 % of patients evaluated.

Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn's Disease.

Abnormal composition of intestinal bacteria--"dysbiosis"-is characteristic of Crohn's disease. Disease treatments include dietary changes and immunosuppressive anti-TNFα antibodies as well as ancillary antibiotic therapy, but their effects on microbiota composition are undetermined. Using shotgun metagenomic sequencing, we analyzed fecal samples from a prospective cohort of pediatric Crohn's disease patients starting therapy with enteral nutrition or anti-TNFα antibodies and reveal the full complement and dynamics of bacteria, fungi, archaea, and viruses during treatment. Bacterial community membership was associated independently with intestinal inflammation, antibiotic use, and therapy. Antibiotic exposure was associated with increased dysbiosis, whereas dysbiosis decreased with reduced intestinal inflammation. Fungal proportions increased with disease and antibiotic use. Dietary therapy had independent and rapid effects on microbiota composition distinct from other stressor-induced changes and effectively reduced inflammation. These findings reveal that dysbiosis results from independent effects of inflammation, diet, and antibiotics and shed light on Crohn disease treatments.

A Novel YY1-miR-1 regulatory circuit in skeletal myogenesis revealed by genome-wide prediction of YY1-miRNA network.

microRNAs (miRNAs) are non-coding RNAs that regulate gene expression post-transcriptionally, and mounting evidence supports the prevalence and functional significance of their interplay with transcription factors (TFs). Here we describe the identification of a regulatory circuit between muscle miRNAs (miR-1, miR-133 and miR-206) and Yin Yang 1 (YY1), an epigenetic repressor of skeletal myogenesis in mouse. Genome-wide identification of potential down-stream targets of YY1 by combining computational prediction with expression profiling data reveals a large number of putative miRNA targets of YY1 during skeletal myoblasts differentiation into myotubes with muscle miRs ranking on top of the list. The subsequent experimental results demonstrate that YY1 indeed represses muscle miRs expression in myoblasts and the repression is mediated through multiple enhancers and recruitment of Polycomb complex to several YY1 binding sites. YY1 regulating miR-1 is functionally important for both C2C12 myogenic differentiation and injury-induced muscle regeneration. Furthermore, we demonstrate that miR-1 in turn targets YY1, thus forming a negative feedback loop. Together, these results identify a novel regulatory circuit required for skeletal myogenesis and reinforce the idea that regulatory circuitries involving miRNAs and TFs are prevalent mechanisms.

SFRS7-mediated splicing of tau exon 10 is directly regulated by STOX1A in glial cells.

BACKGROUND: In this study, we performed a genome-wide search for effector genes bound by STOX1A, a winged helix transcription factor recently demonstrated to be involved in late onset Alzheimer's disease and affecting the amyloid processing pathway. METHODOLOGY/PRINCIPAL FINDINGS: Our results show that out of 218 genes bound by STOX1A as identified by chromatin-immunoprecipitation followed by sequencing (ChIP-Seq), the serine/arginine-rich splicing factor 7 (SFRS7) was found to be induced, both at the mRNA and protein levels, by STOX1A after stable transfection in glial cells. The increase in SFRS7 was followed by an increase in the 4R/3R ratios of the microtubule-associated protein tau (MAPT) by differential exon 10 splicing. Secondly, STOX1A also induced expression of total tau both at the mRNA and protein levels. Upregulation of total tau expression (SFRS7-independent) and tau exon 10 splicing (SFRS7-dependent), as shown in this study to be both affected by STOX1A, is known to have implications in neurodegeneration. CONCLUSIONS: Our data further supports the functional importance and central role of STOX1A in neurodegeneration.

Noninvasive prenatal diagnosis of fetal trisomy 18 and trisomy 13 by maternal plasma DNA sequencing.

Massively parallel sequencing of DNA molecules in the plasma of pregnant women has been shown to allow accurate and noninvasive prenatal detection of fetal trisomy 21. However, whether the sequencing approach is as accurate for the noninvasive prenatal diagnosis of trisomy 13 and 18 is unclear due to the lack of data from a large sample set. We studied 392 pregnancies, among which 25 involved a trisomy 13 fetus and 37 involved a trisomy 18 fetus, by massively parallel sequencing. By using our previously reported standard z-score approach, we demonstrated that this approach could identify 36.0% and 73.0% of trisomy 13 and 18 at specificities of 92.4% and 97.2%, respectively. We aimed to improve the detection of trisomy 13 and 18 by using a non-repeat-masked reference human genome instead of a repeat-masked one to increase the number of aligned sequence reads for each sample. We then applied a bioinformatics approach to correct GC content bias in the sequencing data. With these measures, we detected all (25 out of 25) trisomy 13 fetuses at a specificity of 98.9% (261 out of 264 non-trisomy 13 cases), and 91.9% (34 out of 37) of the trisomy 18 fetuses at 98.0% specificity (247 out of 252 non-trisomy 18 cases). These data indicate that with appropriate bioinformatics analysis, noninvasive prenatal diagnosis of trisomy 13 and trisomy 18 by maternal plasma DNA sequencing is achievable.

Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus.

Cell-free fetal DNA is present in the plasma of pregnant women. It consists of short DNA fragments among primarily maternally derived DNA fragments. We sequenced a maternal plasma DNA sample at up to 65-fold genomic coverage. We showed that the entire fetal and maternal genomes were represented in maternal plasma at a constant relative proportion. Plasma DNA molecules showed a predictable fragmentation pattern reminiscent of nuclease-cleaved nucleosomes, with the fetal DNA showing a reduction in a 166-base pair (bp) peak relative to a 143-bp peak, when compared with maternal DNA. We constructed a genome-wide genetic map and determined the mutational status of the fetus from the maternal plasma DNA sequences and from information about the paternal genotype and maternal haplotype. Our study suggests the feasibility of using genome-wide scanning to diagnose fetal genetic disorders prenatally in a noninvasive way.