Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells.

While animal model studies have extensively defined the mechanisms controlling cell diversity in the developing mammalian lung, there exists a significant knowledge gap with regards to late-stage human lung development. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. Transcriptomic profiling at the single-cell level created a cellular atlas of newborn human lungs. Frozen single-cell isolates obtained from two newborn human lungs from the LungMAP Human Tissue Core Biorepository, were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Transcriptional interrogation of 5500 newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, immune cells and their gene signatures. Computational integration of data from newborn human cells and with 32,000 cells from postnatal days 1 through 10 mouse lungs generated by the LungMAP Cincinnati Research Center facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the newborn human and mouse cellular transcriptomes also demonstrated cell type-specific differences in maturation states of newborn human lung cells. Specifically, newborn human lung matrix fibroblasts could be separated into those representative of younger cells (n = 393), or older cells (n = 158). Cells with each molecular profile were spatially resolved within newborn human lung tissue. This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of maturity.

Neonatal Hyperoxia Activates Activating Transcription Factor 4 to Stimulate Folate Metabolism and Alveolar Epithelial Type 2 Cell Proliferation.

Oxygen supplementation in preterm infants disrupts alveolar epithelial type 2 (AT2) cell proliferation through poorly understood mechanisms. Here, newborn mice are used to understand how hyperoxia stimulates an early aberrant wave of AT2 cell proliferation that occurs between Postnatal Days (PNDs) 0 and 4. RNA-sequencing analysis of AT2 cells isolated from PND4 mice revealed hyperoxia stimulates expression of mitochondrial-specific methylenetetrahydrofolate dehydrogenase 2 and other genes involved in mitochondrial one-carbon coupled folate metabolism and serine synthesis. The same genes are induced when AT2 cells normally proliferate on PND7 and when they proliferate in response to the mitogen fibroblast growth factor 7. However, hyperoxia selectively stimulated their expression via the stress-responsive activating transcription factor 4 (ATF4). Administration of the mitochondrial superoxide scavenger mitoTEMPO during hyperoxia suppressed ATF4 and thus early AT2 cell proliferation, but it had no effect on normative AT2 cell proliferation seen on PND7. Because ATF4 and methylenetetrahydrofolate dehydrogenase are detected in hyperplastic AT2 cells of preterm infant humans and baboons with bronchopulmonary dysplasia, dampening mitochondrial oxidative stress and ATF4 activation may provide new opportunities for controlling excess AT2 cell proliferation in neonatal lung disease.

Neonatal hyperoxia inhibits proliferation and survival of atrial cardiomyocytes by suppressing fatty acid synthesis.

Preterm birth increases the risk for pulmonary hypertension and heart failure in adulthood. Oxygen therapy can damage the immature cardiopulmonary system and may be partially responsible for the cardiovascular disease in adults born preterm. We previously showed that exposing newborn mice to hyperoxia causes pulmonary hypertension by 1 year of age that is preceded by a poorly understood loss of pulmonary vein cardiomyocyte proliferation. We now show that hyperoxia also reduces cardiomyocyte proliferation and survival in the left atrium and causes diastolic heart failure by disrupting its filling of the left ventricle. Transcriptomic profiling showed that neonatal hyperoxia permanently suppressed fatty acid synthase (Fasn), stearoyl-CoA desaturase 1 (Scd1), and other fatty acid synthesis genes in the atria of mice, the HL-1 line of mouse atrial cardiomyocytes, and left atrial tissue explanted from human infants. Suppressing Fasn or Scd1 reduced HL-1 cell proliferation and increased cell death, while overexpressing these genes maintained their expansion in hyperoxia, suggesting that oxygen directly inhibits atrial cardiomyocyte proliferation and survival by repressing Fasn and Scd1. Pharmacologic interventions that restore Fasn, Scd1, and other fatty acid synthesis genes in atrial cardiomyocytes may, thus, provide a way of ameliorating the adverse effects of supplemental oxygen on preterm infants.

Intrinsic mitotic activity supports the human salivary gland acinar cell population.

To develop treatments for salivary gland dysfunction, it is important to understand how human salivary glands are maintained under normal homeostasis. Previous data from our lab demonstrated that murine salivary acinar cells maintain the acinar cell population through self-duplication under conditions of homeostasis, as well as after injury. Early studies suggested that human acinar cells are mitotically active, but the identity of the resultant daughter cells was not clear. Using markers of cell cycle activity and mitosis, as well as an ex vivo 5-Ethynyl-2´-deoxyuridine assay, we show that human salivary gland acinar cells divide to generate daughter acinar cells. As in mouse, our data indicate that human salivary gland homeostasis is supported by the intrinsic mitotic capacity of acinar cells.

T Cell-Dependent Affinity Maturation and Innate Immune Pathways Differentially Drive Autoreactive B Cell Responses in Rheumatoid Arthritis.

OBJECTIVE: Rheumatoid arthritis (RA) is characterized by the activation of B cells that produce anti-citrullinated protein antibodies (ACPAs) and rheumatoid factors (RFs), but the mechanisms by which tolerance is broken in these B cells remain incompletely understood. We undertook this study to investigate whether ACPA+ and RF+ B cells break tolerance through distinct molecular mechanisms. METHODS: We developed antigen-tetramers to isolate ACPA+ and RF+ B cells and performed single-cell RNA sequencing on 2,349 B cells from 6 RA patients and 1 healthy donor to analyze their immunoglobulin repertoires and transcriptional programs. Prominent immunoglobulins were expressed as monoclonal antibodies and tested for autoantigen reactivity. RESULTS: ACPA+ and RF+ B cells were enriched in the peripheral blood of RA patients relative to healthy controls. Characterization of patient-derived monoclonal antibodies confirmed ACPA and RF targeting of tetramer-specific B cells at both antigen-inexperienced and affinity-matured B cell stages. ACPA+ B cells used more class-switched isotypes and exhibited more somatic hypermutations relative to RF+ B cells, and these differences were accompanied by down-regulation of CD72 and up-regulation of genes that promote class-switching and T cell-dependent responses. In contrast, RF+ B cells expressed transcriptional programs that stimulate rapid memory reactivation through multiple innate immune pathways. Coexpression analysis revealed that ACPA+ and RF+ B cell-enriched genes belong to distinct transcriptional regulatory networks. CONCLUSION: Our findings suggest that ACPA+ and RF+ B cells are imprinted with distinct transcriptional programs, which suggests that these autoantibodies associated with increased inflammation in RA arise from 2 different molecular mechanisms.

Neonatal hyperoxia depletes pulmonary vein cardiomyocytes in adult mice via mitochondrial oxidation.

Supplemental oxygen given to preterm infants has been associated with permanently altering postnatal lung development. Now that these individuals are reaching adulthood, there is growing concern that early life oxygen exposure may also promote cardiovascular disease through poorly understood mechanisms. We previously reported that adult mice exposed to 100% oxygen between postnatal days 0 and 4 develop pulmonary hypertension, defined pathologically by capillary rarefaction, dilation of arterioles and veins, cardiac failure, and a reduced lifespan. Here, Affymetrix Gene Arrays are used to identify early transcriptional changes that take place in the lung before pulmonary capillary rarefaction. We discovered neonatal hyperoxia reduced expression of cardiac muscle genes, including those involved in contraction, calcium signaling, mitochondrial respiration, and vasodilation. Quantitative RT-PCR, immunohistochemistry, and genetic lineage mapping using Myh6CreER; Rosa26RmT/mG mice revealed this reflected loss of pulmonary vein cardiomyocytes. The greatest loss of cadiomyocytes was seen within the lung followed by a graded loss beginning at the hilum and extending into the left atrium. Loss of these cells was seen by 2 wk of age in mice exposed to ≥80% oxygen and was attributed, in part, to reduced proliferation. Administering mitoTEMPO, a scavenger of mitochondrial superoxide during neonatal hyperoxia prevented loss of these cells. Since pulmonary vein cardiomyocytes help pump oxygen-rich blood out of the lung, their early loss following neonatal hyperoxia may contribute to cardiovascular disease seen in these mice, and perhaps in people who were born preterm.

Efficient identification of rare variants in large populations: deep re-sequencing the CRP locus in the CARDIA study.

Effect sizes of many common single nucleotide polymorphisms identified in genome-wide association studies generally explain only a modest fraction of the total estimated heritability in a variety of traits. One hypothesis is that rare variants with larger effects might account for the missing heritability. Despite advances in sequencing technology, discovering rare variants in a large population is still economically challenging. Sequencing pooled samples can reduce the cost, but detecting rare variants and identifying individual carriers is difficult and requires additional experiments. To address these issues, we have developed a rare variant-detection algorithm V-Sieve to screen for rare alleles in pooled DNA samples which, in combination with a unique pooling strategy, is able to efficiently screen a candidate gene for idiosyncratic variants in thousands of samples. We applied this method to 2283 individuals, and identified >100 polymorphisms in the C-reactive protein locus at an allele frequency as low as 0.02%, with a positive predictive rate of 93%. We believe this algorithm will be useful in both screening for rare variants in genomic regions known to associate with particular phenotypes and in replicating rare variant associations identified in large-scale studies, such as exome re-sequencing projects.

Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality.

Genome-wide association studies (GWAS) are a useful approach in the study of the genetic components of complex phenotypes. Aside from large cohorts, GWAS have generally been limited to the study of one or a few diseases or traits. The emergence of biobanks linked to electronic medical records (EMRs) allows the efficient reuse of genetic data to yield meaningful genotype-phenotype associations for multiple phenotypes or traits. Phase I of the electronic MEdical Records and GEnomics (eMERGE-I) Network is a National Human Genome Research Institute-supported consortium composed of five sites to perform various genetic association studies using DNA repositories and EMR systems. Each eMERGE site has developed EMR-based algorithms to comprise a core set of 14 phenotypes for extraction of study samples from each site's DNA repository. Each eMERGE site selected samples for a specific phenotype, and these samples were genotyped at either the Broad Institute or at the Center for Inherited Disease Research using the Illumina Infinium BeadChip technology. In all, approximately 17,000 samples from across the five sites were genotyped. A unified quality control (QC) pipeline was developed by the eMERGE Genomics Working Group and used to ensure thorough cleaning of the data. This process includes examination of sample and marker quality and various batch effects. Upon completion of the genotyping and QC analyses for each site's primary study, eMERGE Coordinating Center merged the datasets from all five sites. This larger merged dataset reentered the established eMERGE QC pipeline. Based on lessons learned during the process, additional analyses and QC checkpoints were added to the pipeline to ensure proper merging. Here, we explore the challenges associated with combining datasets from different genotyping centers and describe the expansion to eMERGE QC pipeline for merged datasets. These additional steps will be useful as the eMERGE project expands to include additional sites in eMERGE-II, and also serve as a starting point for investigators merging multiple genotype datasets accessible through the National Center for Biotechnology Information in the database of Genotypes and Phenotypes. Our experience demonstrates that merging multiple datasets after additional QC can be an efficient use of genotype data despite new challenges that appear in the process.

Quality control procedures for genome-wide association studies.

Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of complex disease. Regardless of context, the practical utility of this information will ultimately depend upon the quality of the original data. Quality control (QC) procedures for GWAS are computationally intensive, operationally challenging, and constantly evolving. Here we enumerate some of the challenges in QC of GWAS data and describe the approaches that the electronic MEdical Records and Genomics (eMERGE) network is using for quality assurance in GWAS data, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of GWAS data, including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We propose best practices and discuss areas of ongoing and future research.