Genomic and molecular characterization of preterm birth.

Preterm birth (PTB) complications are the leading cause of long-term morbidity and mortality in children. By using whole blood samples, we integrated whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and DNA methylation data for 270 PTB and 521 control families. We analyzed this combined dataset to identify genomic variants associated with PTB and secondary analyses to identify variants associated with very early PTB (VEPTB) as well as other subcategories of disease that may contribute to PTB. We identified differentially expressed genes (DEGs) and methylated genomic loci and performed expression and methylation quantitative trait loci analyses to link genomic variants to these expression and methylation changes. We performed enrichment tests to identify overlaps between new and known PTB candidate gene systems. We identified 160 significant genomic variants associated with PTB-related phenotypes. The most significant variants, DEGs, and differentially methylated loci were associated with VEPTB. Integration of all data types identified a set of 72 candidate biomarker genes for VEPTB, encompassing genes and those previously associated with PTB. Notably, PTB-associated genes RAB31 and RBPJ were identified by all three data types (WGS, RNA-seq, and methylation). Pathways associated with VEPTB include EGFR and prolactin signaling pathways, inflammation- and immunity-related pathways, chemokine signaling, IFN-γ signaling, and Notch1 signaling. Progress in identifying molecular components of a complex disease is aided by integrated analyses of multiple molecular data types and clinical data. With these data, and by stratifying PTB by subphenotype, we have identified associations between VEPTB and the underlying biology.

Measurement of Organ-Specific and Acute-Phase Blood Protein Levels in Early Lyme Disease.

Lyme disease results from infection of humans with the spirochete Borrelia burgdorferi. The first and most common clinical manifestation is the circular, inflamed skin lesion referred to as erythema migrans; later manifestations result from infections of other body sites. Laboratory diagnosis of Lyme disease can be challenging in patients with erythema migrans because of the time delay in the development of specific diagnostic antibodies against Borrelia. Reliable blood biomarkers for the early diagnosis of Lyme disease in patients with erythema migrans are needed. Here, we performed selected reaction monitoring, a targeted mass spectrometry-based approach, to measure selected proteins that (1) are known to be predominantly expressed in one organ (i.e., organ-specific blood proteins) and whose blood concentrations may change as a result of Lyme disease, or (2) are involved in acute immune responses. In a longitudinal cohort of 40 Lyme disease patients and 20 healthy controls, we identified 10 proteins with significantly altered serum levels in patients at the time of diagnosis, and we also developed a 10-protein panel identified through multivariate analysis. In an independent cohort of patients with erythema migrans, six of these proteins, APOA4, C9, CRP, CST6, PGLYRP2, and S100A9, were confirmed to show significantly altered serum levels in patients at time of presentation. Nine of the 10 proteins from the multivariate panel were also verified in the second cohort. These proteins, primarily innate immune response proteins or proteins specific to liver, skin, or white blood cells, may serve as candidate blood biomarkers requiring further validation to aid in the laboratory diagnosis of early Lyme disease.

Taking Systems Medicine to Heart.

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine.

Evolutionary history of Tibetans inferred from whole-genome sequencing.

The indigenous people of the Tibetan Plateau have been the subject of much recent interest because of their unique genetic adaptations to high altitude. Recent studies have demonstrated that the Tibetan EPAS1 haplotype is involved in high altitude-adaptation and originated in an archaic Denisovan-related population. We sequenced the whole-genomes of 27 Tibetans and conducted analyses to infer a detailed history of demography and natural selection of this population. We detected evidence of population structure between the ancestral Han and Tibetan subpopulations as early as 44 to 58 thousand years ago, but with high rates of gene flow until approximately 9 thousand years ago. The CMS test ranked EPAS1 and EGLN1 as the top two positive selection candidates, and in addition identified PTGIS, VDR, and KCTD12 as new candidate genes. The advantageous Tibetan EPAS1 haplotype shared many variants with the Denisovan genome, with an ancient gene tree divergence between the Tibetan and Denisovan haplotypes of about 1 million years ago. With the exception of EPAS1, we observed no evidence of positive selection on Denisovan-like haplotypes.

Sex, obesity, diabetes, and exposure to particulate matter among patients with severe asthma: Scientific insights from a comparative analysis of open clinical data sources during a five-day hackathon.

This special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator program ('Translator'). Specifically, Translator team members self-organized and worked together to conceptualize and execute, over a five-day period, a multi-institutional clinical research study that aimed to examine, using open clinical data sources, relationships between sex, obesity, diabetes, and exposure to airborne fine particulate matter among patients with severe asthma. The goal was to develop a proof of concept that this new model of collaboration and data sharing could effectively produce meaningful scientific results and generate new scientific hypotheses. Three Translator Clinical Knowledge Sources, each of which provides open access (via Application Programming Interfaces) to data derived from the electronic health record systems of major academic institutions, served as the source of study data. Jupyter Python notebooks, shared in GitHub repositories, were used to call the knowledge sources and analyze and integrate the results. The results replicated established or suspected relationships between sex, obesity, diabetes, exposure to airborne fine particulate matter, and severe asthma. In addition, the results demonstrated specific differences across the three Translator Clinical Knowledge Sources, suggesting cohort- and/or environment-specific factors related to the services themselves or the catchment area from which each service derives patient data. Collectively, this special communication demonstrates the power and utility of intense, team-oriented hackathons and offers general technical, organizational, and scientific lessons learned.

Novel metrics for quantifying bacterial genome composition skews.

BACKGROUND: Bacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints, particularly for energy efficiency. Analysis of compositional skews in a diverse set of bacteria provides a comparative context in which mutational and selective environmental constraints can be studied. These analyses typically require finished and well-annotated genomic sequences. RESULTS: We present three novel metrics for examining genome composition skews; all three metrics can be computed for unfinished or partially-annotated genomes. The first two metrics, (dot-skew and cross-skew) depend on sequence and gene annotation of a single genome, while the third metric (residual skew) highlights unusual genomes by subtracting a GC content-based model of a library of genome sequences. We applied these metrics to 7738 available bacterial genomes, including partial drafts, and identified outlier species. A phylogenetically diverse set of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns but share lifestyle characteristics, such as intracellularity and biosynthetic dependence on their hosts. CONCLUSIONS: Our novel metrics appear to reflect the effects of biosynthetic constraints and adaptations to life within one or more hosts on genome composition. We provide results for each analyzed genome, software and interactive visualizations at http://db.systemsbiology.net/gestalt/ skew_metrics .

Heterozygous Loss-of-Function Mutations in DLL4 Cause Adams-Oliver Syndrome.

Adams-Oliver syndrome (AOS) is a rare developmental disorder characterized by the presence of aplasia cutis congenita (ACC) of the scalp vertex and terminal limb-reduction defects. Cardiovascular anomalies are also frequently observed. Mutations in five genes have been identified as a cause for AOS prior to this report. Mutations in EOGT and DOCK6 cause autosomal-recessive AOS, whereas mutations in ARHGAP31, RBPJ, and NOTCH1 lead to autosomal-dominant AOS. Because RBPJ, NOTCH1, and EOGT are involved in NOTCH signaling, we hypothesized that mutations in other genes involved in this pathway might also be implicated in AOS pathogenesis. Using a candidate-gene-based approach, we prioritized DLL4, a critical NOTCH ligand, due to its essential role in vascular development in the context of cardiovascular features in AOS-affected individuals. Targeted resequencing of the DLL4 gene with a custom enrichment panel in 89 independent families resulted in the identification of seven mutations. A defect in DLL4 was also detected in two families via whole-exome or genome sequencing. In total, nine heterozygous mutations in DLL4 were identified, including two nonsense and seven missense variants, the latter encompassing four mutations that replace or create cysteine residues, which are most likely critical for maintaining structural integrity of the protein. Affected individuals with DLL4 mutations present with variable clinical expression with no emerging genotype-phenotype correlations. Our findings demonstrate that DLL4 mutations are an additional cause of autosomal-dominant AOS or isolated ACC and provide further evidence for a key role of NOTCH signaling in the etiology of this disorder.

Rare variants in neuronal excitability genes influence risk for bipolar disorder.

We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5' and 3' UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

Mutations in NOTCH1 cause Adams-Oliver syndrome.

Notch signaling determines and reinforces cell fate in bilaterally symmetric multicellular eukaryotes. Despite the involvement of Notch in many key developmental systems, human mutations in Notch signaling components have mainly been described in disorders with vascular and bone effects. Here, we report five heterozygous NOTCH1 variants in unrelated individuals with Adams-Oliver syndrome (AOS), a rare disease with major features of aplasia cutis of the scalp and terminal transverse limb defects. Using whole-genome sequencing in a cohort of 11 families lacking mutations in the four genes with known roles in AOS pathology (ARHGAP31, RBPJ, DOCK6, and EOGT), we found a heterozygous de novo 85 kb deletion spanning the NOTCH1 5' region and three coding variants (c.1285T>C [p.Cys429Arg], c.4487G>A [p.Cys1496Tyr], and c.5965G>A [p.Asp1989Asn]), two of which are de novo, in four unrelated probands. In a fifth family, we identified a heterozygous canonical splice-site variant (c.743-1 G>T) in an affected father and daughter. These variants were not present in 5,077 in-house control genomes or in public databases. In keeping with the prominent developmental role described for Notch1 in mouse vasculature, we observed cardiac and multiple vascular defects in four of the five families. We propose that the limb and scalp defects might also be due to a vasculopathy in NOTCH1-related AOS. Our results suggest that mutations in NOTCH1 are the most common cause of AOS and add to a growing list of human diseases that have a vascular and/or bony component and are caused by alterations in the Notch signaling pathway.

Relationship estimation from whole-genome sequence data.

The determination of the relationship between a pair of individuals is a fundamental application of genetics. Previously, we and others have demonstrated that identity-by-descent (IBD) information generated from high-density single-nucleotide polymorphism (SNP) data can greatly improve the power and accuracy of genetic relationship detection. Whole-genome sequencing (WGS) marks the final step in increasing genetic marker density by assaying all single-nucleotide variants (SNVs), and thus has the potential to further improve relationship detection by enabling more accurate detection of IBD segments and more precise resolution of IBD segment boundaries. However, WGS introduces new complexities that must be addressed in order to achieve these improvements in relationship detection. To evaluate these complexities, we estimated genetic relationships from WGS data for 1490 known pairwise relationships among 258 individuals in 30 families along with 46 population samples as controls. We identified several genomic regions with excess pairwise IBD in both the pedigree and control datasets using three established IBD methods: GERMLINE, fastIBD, and ISCA. These spurious IBD segments produced a 10-fold increase in the rate of detected false-positive relationships among controls compared to high-density microarray datasets. To address this issue, we developed a new method to identify and mask genomic regions with excess IBD. This method, implemented in ERSA 2.0, fully resolved the inflated cryptic relationship detection rates while improving relationship estimation accuracy. ERSA 2.0 detected all 1(st) through 6(th) degree relationships, and 55% of 9(th) through 11(th) degree relationships in the 30 families. We estimate that WGS data provides a 5% to 15% increase in relationship detection power relative to high-density microarray data for distant relationships. Our results identify regions of the genome that are highly problematic for IBD mapping and introduce new software to accurately detect 1(st) through 9(th) degree relationships from whole-genome sequence data.

Identification of Organ-Enriched Protein Biomarkers of Acute Liver Injury by Targeted Quantitative Proteomics of Blood in Acetaminophen- and Carbon-Tetrachloride-Treated Mouse Models and Acetaminophen Overdose Patients.

Organ-enriched blood proteins, those produced primarily in one organ and secreted or exported to the blood, potentially afford a powerful and specific approach to assessing diseases in their cognate organs. We demonstrate that quantification of organ-enriched proteins in the blood offers a new strategy to find biomarkers for diagnosis and assessment of drug-induced liver injury (and presumably the assessment of other liver diseases). We used selected reaction monitoring (SRM) mass spectrometry to quantify 81 liver-enriched proteins plus three aminotransferases (ALT1, AST1, and AST2) in plasma of C57BL/6J and NOD/ShiLtJ mice exposed to acetaminophen or carbon tetrachloride. Plasma concentrations of 49 liver-enriched proteins were perturbed significantly in response to liver injury induced by one or both toxins. We validated four of these toxin-responsive proteins (ALDOB, ASS1, BHMT, and GLUD1) by Western blotting. By both assays, these four proteins constitute liver injury markers superior to currently employed markers such as ALT and AST. A similar approach was also successful in human serum where we had analyzed 66 liver-enriched proteins in acetaminophen overdose patients. Of these, 23 proteins were elevated in patients; 15 of 23 overlapped with the concentration-increased proteins in the mouse study. A combination of 5 human proteins, AGXT, ALDOB, CRP, FBP1, and MMP9, provides the best diagnostic performance to distinguish acetaminophen overdose patients from controls (sensitivity: 0.85, specificity: 0.84, accuracy: 85%). These five blood proteins are candidates for detecting acetaminophen-induced liver injury using next-generation diagnostic devices (e.g, microfluidic ELISA assays).

Realistic artificial DNA sequences as negative controls for computational genomics.

A common practice in computational genomic analysis is to use a set of 'background' sequences as negative controls for evaluating the false-positive rates of prediction tools, such as gene identification programs and algorithms for detection of cis-regulatory elements. Such 'background' sequences are generally taken from regions of the genome presumed to be intergenic, or generated synthetically by 'shuffling' real sequences. This last method can lead to underestimation of false-positive rates. We developed a new method for generating artificial sequences that are modeled after real intergenic sequences in terms of composition, complexity and interspersed repeat content. These artificial sequences can serve as an inexhaustible source of high-quality negative controls. We used artificial sequences to evaluate the false-positive rates of a set of programs for detecting interspersed repeats, ab initio prediction of coding genes, transcribed regions and non-coding genes. We found that RepeatMasker is more accurate than PClouds, Augustus has the lowest false-positive rate of the coding gene prediction programs tested, and Infernal has a low false-positive rate for non-coding gene detection. A web service, source code and the models for human and many other species are freely available at http://repeatmasker.org/garlic/.

Crowdsourced direct-to-consumer genomic analysis of a family quartet.

BACKGROUND: We describe the pioneering experience of a Spanish family pursuing the goal of understanding their own personal genetic data to the fullest possible extent using Direct to Consumer (DTC) tests. With full informed consent from the Corpas family, all genotype, exome and metagenome data from members of this family, are publicly available under a public domain Creative Commons 0 (CC0) license waiver. All scientists or companies analysing these data ("the Corpasome") were invited to return results to the family. METHODS: We released 5 genotypes, 4 exomes, 1 metagenome from the Corpas family via a blog and figshare under a public domain license, inviting scientists to join the crowdsourcing efforts to analyse the genomes in return for coauthorship or acknowldgement in derived papers. Resulting analysis data were compiled via social media and direct email. RESULTS: Here we present the results of our investigations, combining the crowdsourced contributions and our own efforts. Four companies offering annotations for genomic variants were applied to four family exomes: BIOBASE, Ingenuity, Diploid, and GeneTalk. Starting from a common VCF file and after selecting for significant results from company reports, we find no overlap among described annotations. We additionally report on a gut microbiome analysis of a member of the Corpas family. CONCLUSIONS: This study presents an analysis of a diverse set of tools and methods offered by four DTC companies. The striking discordance of the results mirrors previous findings with respect to DTC analysis of SNP chip data, and highlights the difficulties of using DTC data for preventive medical care. To our knowledge, the data and analysis results from our crowdsourced study represent the most comprehensive exome and analysis for a family quartet using solely DTC data generation to date.

Systems genomics evaluation of the SH-SY5Y neuroblastoma cell line as a model for Parkinson's disease.

BACKGROUND: The human neuroblastoma cell line, SH-SY5Y, is a commonly used cell line in studies related to neurotoxicity, oxidative stress, and neurodegenerative diseases. Although this cell line is often used as a cellular model for Parkinson's disease, the relevance of this cellular model in the context of Parkinson's disease (PD) and other neurodegenerative diseases has not yet been systematically evaluated. RESULTS: We have used a systems genomics approach to characterize the SH-SY5Y cell line using whole-genome sequencing to determine the genetic content of the cell line and used transcriptomics and proteomics data to determine molecular correlations. Further, we integrated genomic variants using a network analysis approach to evaluate the suitability of the SH-SY5Y cell line for perturbation experiments in the context of neurodegenerative diseases, including PD. CONCLUSIONS: The systems genomics approach showed consistency across different biological levels (DNA, RNA and protein concentrations). Most of the genes belonging to the major Parkinson's disease pathways and modules were intact in the SH-SY5Y genome. Specifically, each analysed gene related to PD has at least one intact copy in SH-SY5Y. The disease-specific network analysis approach ranked the genetic integrity of SH-SY5Y as higher for PD than for Alzheimer's disease but lower than for Huntington's disease and Amyotrophic Lateral Sclerosis for loss of function perturbation experiments.

Chromosomal haplotypes by genetic phasing of human families.

Assignment of alleles to haplotypes for nearly all the variants on all chromosomes can be performed by genetic analysis of a nuclear family with three or more children. Whole-genome sequence data enable deterministic phasing of nearly all sequenced alleles by permitting assignment of recombinations to precise chromosomal positions and specific meioses. We demonstrate this process of genetic phasing on two families each with four children. We generate haplotypes for all of the children and their parents; these haplotypes span all genotyped positions, including rare variants. Misassignments of phase between variants (switch errors) are nearly absent. Our algorithm can also produce multimegabase haplotypes for nuclear families with just two children and can handle families with missing individuals. We implement our algorithm in a suite of software scripts (Haploscribe). Haplotypes and family genome sequences will become increasingly important for personalized medicine and for fundamental biology.

Diffuse angiopathy in Adams-Oliver syndrome associated with truncating DOCK6 mutations.

Adams-Oliver syndrome (AOS) is a rare malformation syndrome characterized by the presence of two anomalies: aplasia cutis congenita of the scalp and transverse terminal limb defects. Many affected individuals also have additional malformations, including a variety of intracranial anomalies such as periventricular calcification in keeping with cerebrovascular microbleeds, impaired neuronal migration, epilepsy, and microcephaly. Cardiac malformations can be present, as can vascular dysfunction in the forms of cutis marmorata telangiectasia congenita, pulmonary vein stenoses, and abnormal hepatic microvasculature. Elucidated genetic causes include four genes in different pathways, leading to a model of AOS as a multi-pathway disorder. We identified an infant with mild aplasia cutis congenita and terminal transverse limb defects, developmental delay and a severe, diffuse angiopathy with incomplete microvascularization. Whole-genome sequencing documented two rare truncating variants in DOCK6, a gene associated with a type of autosomal recessive AOS that recurrently features periventricular calcification and impaired neurodevelopment. We highlight an unexpectedly high frequency of likely deleterious mutations in this gene in the general population, relative to the rarity of the disease, and discuss possible explanations for this discrepancy.

Origin of the PSEN1 E280A mutation causing early-onset Alzheimer's disease.

BACKGROUND: A mutation in presenilin 1 (E280A) causes early-onset Alzheimer's disease. Understanding the origin of this mutation will inform medical genetics. METHODS: We sequenced the genomes of 102 individuals from Antioquia, Colombia. We applied identity-by-descent analysis to identify regions of common ancestry. We estimated the age of the E280A mutation and the local ancestry of the haplotype harboring this mutation. RESULTS: All affected individuals share a minimal haplotype of 1.8 Mb containing E280A. We estimate a time to most recent common ancestor of E280A of 10 (95% credible interval, 7.2-12.6) generations. We date the de novo mutation event to 15 (95% credible interval, 11-25) generations ago. We infer a western European geographic origin of the shared haplotype. CONCLUSIONS: The age and geographic origin of E280A are consistent with a single founder dating from the time of the Spanish Conquistadors who began colonizing Colombia during the early 16th century.

Correction: Reproducible big data science: A case study in continuous FAIRness.

[This corrects the article DOI: 10.1371/journal.pone.0213013.].

Kaviar: an accessible system for testing SNV novelty.

SUMMARY: With the rapidly expanding availability of data from personal genomes, exomes and transcriptomes, medical researchers will frequently need to test whether observed genomic variants are novel or known. This task requires downloading and handling large and diverse datasets from a variety of sources, and processing them with bioinformatics tools and pipelines. Alternatively, researchers can upload data to online tools, which may conflict with privacy requirements. We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys; and (ii) software for querying the database efficiently.

Quality control of large genome datasets.

The 1000 Genomes Project (TGP) is a foundational resource that serves the biomedical community as a standard reference cohort for human genetic variation. There are now seven public versions of these genomes. The TGP Consortium produced the first by mapping its final data release against human reference sequence GRCh37, then "lifted over" these genomes to the improved reference sequence (GRCh38) when it was released, and remapped the original data to GRCh38 with two similar pipelines. As best-practice quality validation, the pipelines that generated these versions were benchmarked against the Genome In A Bottle Consortium's "platinum quality" genome (NA12878). The New York Genome Center recently released the results of independently resequencing the cohort at greater depth (30×), a phased version informed by the inclusion of related individuals, and independently remapped the original variant calls to GRCh38. We performed a cross-comparison evaluation of all seven versions using genome fingerprinting, which supports ultrafast genome comparison even across reference versions. We noted multiple issues, including discrepancies in cohort membership, disagreement on the overall level of variation, evidence of substandard pipeline performance on specific genomes and in specific regions of the genome, cryptic relationships between individuals, inconsistent phasing, and annotation distortions caused by the history of the reference genome itself. We therefore recommend global quality assessment by rapid genome comparisons, alongside benchmarking as part of best-practice quality assessment of large genome datasets. Our observations also help inform the decision of which version to use, to support analyses by individual researchers.