Genomic Mismatch at LIMS1 Locus and Kidney Allograft Rejection.

BACKGROUND: In the context of kidney transplantation, genomic incompatibilities between donor and recipient may lead to allosensitization against new antigens. We hypothesized that recessive inheritance of gene-disrupting variants may represent a risk factor for allograft rejection. METHODS: We performed a two-stage genetic association study of kidney allograft rejection. In the first stage, we performed a recessive association screen of 50 common gene-intersecting deletion polymorphisms in a cohort of kidney transplant recipients. In the second stage, we replicated our findings in three independent cohorts of donor-recipient pairs. We defined genomic collision as a specific donor-recipient genotype combination in which a recipient who was homozygous for a gene-intersecting deletion received a transplant from a nonhomozygous donor. Identification of alloantibodies was performed with the use of protein arrays, enzyme-linked immunosorbent assays, and Western blot analyses. RESULTS: In the discovery cohort, which included 705 recipients, we found a significant association with allograft rejection at the LIMS1 locus represented by rs893403 (hazard ratio with the risk genotype vs. nonrisk genotypes, 1.84; 95% confidence interval [CI], 1.35 to 2.50; P = 9.8×10-5). This effect was replicated under the genomic-collision model in three independent cohorts involving a total of 2004 donor-recipient pairs (hazard ratio, 1.55; 95% CI, 1.25 to 1.93; P = 6.5×10-5). In the combined analysis (discovery cohort plus replication cohorts), the risk genotype was associated with a higher risk of rejection than the nonrisk genotype (hazard ratio, 1.63; 95% CI, 1.37 to 1.95; P = 4.7×10-8). We identified a specific antibody response against LIMS1, a kidney-expressed protein encoded within the collision locus. The response involved predominantly IgG2 and IgG3 antibody subclasses. CONCLUSIONS: We found that the LIMS1 locus appeared to encode a minor histocompatibility antigen. Genomic collision at this locus was associated with rejection of the kidney allograft and with production of anti-LIMS1 IgG2 and IgG3. (Funded by the Columbia University Transplant Center and others.).

Author Correction: The copy number variation landscape of congenital anomalies of the kidney and urinary tract.

In the version of this article initially published, affiliation 38 incorrectly read "ICNU-Nephrology and Urology Department, Barcelona, Spain"; "Renal Division, Hospital Clinic, IDIBAPS, University of Barcelona, Barcelona, Spain" is the correct affiliation. The error has been corrected in the HTML and PDF versions of the article.

The copy number variation landscape of congenital anomalies of the kidney and urinary tract.

Congenital anomalies of the kidney and urinary tract (CAKUT) are a major cause of pediatric kidney failure. We performed a genome-wide analysis of copy number variants (CNVs) in 2,824 cases and 21,498 controls. Affected individuals carried a significant burden of rare exonic (that is, affecting coding regions) CNVs and were enriched for known genomic disorders (GD). Kidney anomaly (KA) cases were most enriched for exonic CNVs, encompassing GD-CNVs and novel deletions; obstructive uropathy (OU) had a lower CNV burden and an intermediate prevalence of GD-CNVs; and vesicoureteral reflux (VUR) had the fewest GD-CNVs but was enriched for novel exonic CNVs, particularly duplications. Six loci (1q21, 4p16.1-p16.3, 16p11.2, 16p13.11, 17q12 and 22q11.2) accounted for 65% of patients with GD-CNVs. Deletions at 17q12, 4p16.1-p16.3 and 22q11.2 were specific for KA; the 16p11.2 locus showed extensive pleiotropy. Using a multidisciplinary approach, we identified TBX6 as a driver for the CAKUT subphenotypes in the 16p11.2 microdeletion syndrome.

miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer.

Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of n = 27 mice and a user-blinded validation set of n = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy.Significance: These findings present a panel of extracellular vesicle miRNA blood-based biomarkers that can detect pancreatic cancer at a precancerous stage in a transgenic mouse model. Cancer Res; 78(13); 3688-97. ©2018 AACR.

Pervasive within-Mitochondrion Single-Nucleotide Variant Heteroplasmy as Revealed by Single-Mitochondrion Sequencing.

A number of mitochondrial diseases arise from single-nucleotide variant (SNV) accumulation in multiple mitochondria. Here, we present a method for identification of variants present at the single-mitochondrion level in individual mouse and human neuronal cells, allowing for extremely high-resolution study of mitochondrial mutation dynamics. We identified extensive heteroplasmy between individual mitochondrion, along with three high-confidence variants in mouse and one in human that were present in multiple mitochondria across cells. The pattern of variation revealed by single-mitochondrion data shows surprisingly pervasive levels of heteroplasmy in inbred mice. Distribution of SNV loci suggests inheritance of variants across generations, resulting in Poisson jackpot lines with large SNV load. Comparison of human and mouse variants suggests that the two species might employ distinct modes of somatic segregation. Single-mitochondrion resolution revealed mitochondria mutational dynamics that we hypothesize to affect risk probabilities for mutations reaching disease thresholds.

Exome-wide Association Study Identifies GREB1L Mutations in Congenital Kidney Malformations.

Renal agenesis and hypodysplasia (RHD) are major causes of pediatric chronic kidney disease and are highly genetically heterogeneous. We conducted whole-exome sequencing in 202 case subjects with RHD and identified diagnostic mutations in genes known to be associated with RHD in 7/202 case subjects. In an additional affected individual with RHD and a congenital heart defect, we found a homozygous loss-of-function (LOF) variant in SLIT3, recapitulating phenotypes reported with Slit3 inactivation in the mouse. To identify genes associated with RHD, we performed an exome-wide association study with 195 unresolved case subjects and 6,905 control subjects. The top signal resided in GREB1L, a gene implicated previously in Hoxb1 and Shha signaling in zebrafish. The significance of the association, which was p = 2.0 × 10-5 for novel LOF, increased to p = 4.1 × 10-6 for LOF and deleterious missense variants combined, and augmented further after accounting for segregation and de novo inheritance of rare variants (joint p = 2.3 × 10-7). Finally, CRISPR/Cas9 disruption or knockdown of greb1l in zebrafish caused specific pronephric defects, which were rescued by wild-type human GREB1L mRNA, but not mRNA containing alleles identified in case subjects. Together, our study provides insight into the genetic landscape of kidney malformations in humans, presents multiple candidates, and identifies SLIT3 and GREB1L as genes implicated in the pathogenesis of RHD.

Primary Cell Culture of Live Neurosurgically Resected Aged Adult Human Brain Cells and Single Cell Transcriptomics.

Investigation of human CNS disease and drug effects has been hampered by the lack of a system that enables single-cell analysis of live adult patient brain cells. We developed a culturing system, based on a papain-aided procedure, for resected adult human brain tissue removed during neurosurgery. We performed single-cell transcriptomics on over 300 cells, permitting identification of oligodendrocytes, microglia, neurons, endothelial cells, and astrocytes after 3 weeks in culture. Using deep sequencing, we detected over 12,000 expressed genes, including hundreds of cell-type-enriched mRNAs, lncRNAs and pri-miRNAs. We describe cell-type- and patient-specific transcriptional hierarchies. Single-cell transcriptomics on cultured live adult patient derived cells is a prime example of the promise of personalized precision medicine. Because these cells derive from subjects ranging in age into their sixties, this system permits human aging studies previously possible only in rodent systems.

High-resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury.

Microglial cells, the resident immune cells of the spinal cord, become activated in response to peripheral nerve injury. Microglia activation contributes to the development of neuropathic pain. Here we employed microarray analysis of individually collected pools of 10 spinal microglia cells to identify changes of levels and cell-to-cell expression variance of microglial genes during their activation after peripheral nerve injury. The analysis of microglia on postoperative day 1 (POD1) identified miR-29c as a critical factor for microglial activation and the development of neuropathic pain. Early POD1 microglia exhibited a very distinct expression profile compared to late POD7 microglia, possibly leading to the transition from initiation to maintenance of neuropathic pain. We found sample variance patterns that were consistent with the hypothesis that microglia were highly heterogeneous at the level of individual cells, and variation analysis identified 56 microglial genes potentially linked to the maintenance of neuropathic pain which included Gria1. This study provides insights into spinal microglial biology and reveals novel microglial targets for the treatment of neuropathic pain.

Interpretation of personal genome sequencing data in terms of disease ranks based on mutual information.

BACKGROUND: The rapid advances in genome sequencing technologies have resulted in an unprecedented number of genome variations being discovered in humans. However, there has been very limited coverage of interpretation of the personal genome sequencing data in terms of diseases. METHODS: In this paper we present the first computational analysis scheme for interpreting personal genome data by simultaneously considering the functional impact of damaging variants and curated disease-gene association data. This method is based on mutual information as a measure of the relative closeness between the personal genome and diseases. We hypothesize that a higher mutual information score implies that the personal genome is more susceptible to a particular disease than other diseases. RESULTS: The method was applied to the sequencing data of 50 acute myeloid leukemia (AML) patients in The Cancer Genome Atlas. The utility of associations between a disease and the personal genome was explored using data of healthy (control) people obtained from the 1000 Genomes Project. The ranks of the disease terms in the AML patient group were compared with those in the healthy control group using "Leukemia, Myeloid, Acute" (C04.557.337.539.550) as the corresponding MeSH disease term. CONCLUSIONS: Overall, the area under the receiver operating characteristics curve was significantly larger for the AML patient data than for the healthy controls. This methodology could contribute to consequential discoveries and explanations for mining personal genome sequencing data in terms of diseases, and have versatility with respect to genomic-based knowledge such as drug-gene and environmental-factor-gene interactions.

Targeted exon sequencing fails to identify rare coding variants with large effect in rheumatoid arthritis.

INTRODUCTION: Although it has been suggested that rare coding variants could explain the substantial missing heritability, very few sequencing studies have been performed in rheumatoid arthritis (RA). We aimed to identify novel functional variants with rare to low frequency using targeted exon sequencing of RA in Korea. METHODS: We analyzed targeted exon sequencing data of 398 genes selected from a multifaceted approach in Korean RA patients (n = 1,217) and controls (n = 717). We conducted a single-marker association test and a gene-based analysis of rare variants. For meta-analysis or enrichment tests, we also used ethnically matched independent samples of Korean genome-wide association studies (GWAS) (n = 4,799) or immunochip data (n = 4,722). RESULTS: After stringent quality control, we analyzed 10,588 variants of 398 genes from 1,934 Korean RA case controls. We identified 13 nonsynonymous variants with nominal association in single-variant association tests. In a meta-analysis, we did not find any novel variant with genome-wide significance for RA risk. Using a gene-based approach, we identified 17 genes with nominal burden signals. Among them, VSTM1 showed the greatest association with RA (P = 7.80 × 10-4). In the enrichment test using Korean GWAS, although the significant signal appeared to be driven by total genic variants, we found no evidence for enriched association of coding variants only with RA. CONCLUSIONS: We were unable to identify rare coding variants with large effect to explain the missing heritability for RA in the current targeted resequencing study. Our study raises skepticism about exon sequencing of targeted genes for complex diseases like RA.

Ethnic specificity of lupus-associated loci identified in a genome-wide association study in Korean women.

OBJECTIVES: To identify novel genetic candidates for systemic lupus erythematosus (SLE) in the Korean population, and to validate the risk loci for SLE identified in previous genome-wide association studies (GWAS). METHODS: We performed a GWAS in 400 Korean female SLE patients and 445 controls. Selected single-nucleotide polymorphisms (SNP) were then replicated in an independent cohort of 385 SLE patients and 583 controls (replication cohort 1), and in a further 811 SLE patients and 1502 controls (replication cohort 2). RESULTS: In the GWAS phase, rs9275428 located near HLA-DQB1 showed the strongest association with SLE (OR 0.50, false discovery rate (FDR) p=3.07×10(-6)). Although no loci reached genome-wide significance outside major histocompatibility complex (MHC), C8orf13-BLK, STAT4, CSMD1, DIAPH3, GLDC and TNFSF4 showed FDR p < 0.05. Our results suggest that STAT4, BLK, IRF5, PTTG1-miR-146a, UBE2L3 and TNFAIP3 are shared susceptibility loci among Caucasians and Asians, while ETS1, IKZF1, SLC15A4 are likely to be Asian-specific loci. In a combined analysis of 1596 SLE patients and 2540 controls for selected 22 candidate SNP, STAT4 and BLK as positive controls showed a strong association with SLE (FDR p=9.85×10(-13) and 2.28×10(-8), respectively). Of these, 16 candidates (PEX5L, TRAJ50, MYO18B, SOS1, ARHGAP26, SMURF1, CADPS, HAND1, FAM78B, DIAPH3, TBL1XR1, CSMD1, ZBTB20, C3orf21, HIPK1 and AP001042.1) showed only nominal significance (7.05×10(-4)≤FDR p≤4.38×10(-2)). CONCLUSIONS: There are similarities and differences in genetic susceptibility for SLE between Caucasian and Asian ethnic groups. Although 16 putative novel loci for SLE have been suggested in the Korean population, further research on a larger sample is required to discriminate truth from error.

AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes.

OBJECTIVES: Next-generation sequencing (NGS) data in the identification of disease-causing genes provides a promising opportunity in the diagnosis of disease. Beyond the previous efforts for NGS data alignment, variant detection, and visualization, developing a comprehensive annotation system supported by multiple layers of disease phenotype-related databases is essential for deciphering the human genome. To satisfy the impending need to decipher the human genome, it is essential to develop a comprehensive annotation system supported by multiple layers of disease phenotype-related databases. METHODS: AnsNGS (Annotation system of sequence variations for next-generation sequencing data) is a tool for contextualizing variants related to diseases and examining their functional consequences. The AnsNGS integrates a variety of annotation databases to attain multiple levels of annotation. RESULTS: The AnsNGS assigns biological functions to variants, and provides gene (or disease)-centric queries for finding disease-causing variants. The AnsNGS also connects those genes harbouring variants and the corresponding expression probes for downstream analysis using expression microarrays. Here, we demonstrate its ability to identify disease-related variants in the human genome. CONCLUSIONS: The AnsNGS can give a key insight into which of these variants is already known to be involved in a disease-related phenotype or located in or near a known regulatory site. The AnsNGS is available free of charge to academic users and can be obtained from http://snubi.org/software/AnsNGS/.

Understanding cooperativity of microRNAs via microRNA association networks.

BACKGROUND: MicroRNAs (miRNAs) are key components in post-transcriptional gene regulation in multicellular organisms. As they control cooperatively a large number of their target genes, they affect the complexity of gene regulation. One of the challenges to understand miRNA-mediated regulation is to identify co-regulating miRNAs that simultaneously regulate their target genes in a network perspective. RESULTS: We created miRNA association network by using miRNAs sharing target genes based on sequence complementarity and co-expression patterns of miRNA-target pairs. The degree of association between miRNAs can be assessed by the level of concordance between targets of miRNAs. Cooperatively regulating miRNAs have been identified by network topology-based approach. Cooperativity of miRNAs is evaluated by their shared transcription factors and functional coherence of target genes. Pathway enrichment analysis of target genes in the cooperatively regulating miRNAs revealed the mutually exclusive functional landscape of miRNA cooperativity. In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner. Sequence and structural similarity analysis within miRNA association network showed that pre-miRNA secondary structure may be involved in the expression of mature miRNA's function. CONCLUSIONS: On the system level, we identified cooperatively regulating miRNAs in the miRNA association network. We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar. This study demonstrates the potential importance of the secondary structures of pre-miRNAs in both cooperativity and specificity of target genes.

Comprehensive analysis of microRNA-mRNA co-expression in circadian rhythm.

To investigate the potential role of microRNA (miRNA) in the regulation of circadian rhythm, we performed microarray-based expression profiling study of both miRNA and mRNA in mouse liver for 48 h at 4-hour intervals. Circadian miRNA-mRNA target pair is defined as the pair both elements of which show circadian expression patterns and the sequence-based target relationship of which can be predicted. Circadian initiators, Clock and Bmal1, showed inversely correlated circadian expression patterns against their corresponding miRNAs, miR-181d and miR-191, targeting them. In contrast, circadian suppressors, Per, Cry, CKIe and Rev-erba, exhibited positively correlated circadian expression patterns to their corresponding miRNAs. Genomic location analysis revealed that intronic region showed higher abundance of cyclic than non-cyclic miRNAs targeting circadian genes while other (i.e., 3-UTR, exon and intergenic) regions showed no difference. It is suggested that miRNAs are involved in the regulation of peripheral circadian rhythm in mouse liver by modulating Clock:Bmal1 complex. Identifying specific miRNAs and their targets that are critically involved in circadian rhythm will provide a better understanding of the regulation of circadian- clock system.

Comprehensive analysis of time- and dose-dependent patterns of gene expression in a human mesenchymal stem cell line exposed to low-dose ionizing radiation.

We focused on the transcriptional responses induced by low and very low doses of ionizing radiation with time effect. Regardless of their importance only a few limited studies have been done. Here we applied a large-scale gene transcript profile to elucidate the genes and biological pathways. Immortalized human mesenchymal stem cells were irradiated with 0.01, 0.05, 0.2 and 1 Gy of gamma radiation and total RNA was extracted from each cell line at 1, 4, 12 and 48 h after exposure. The essential transcriptional responses were identified according to dose and time. A total of 6,016 genes showed altered expression patterns at more than one time point or dose level among the investigated 10,800 genes. Genes that showed dose-dependent expression responses were involved in signal transduction, regulation of transcription, proteolysis, peptidolysis and metabolism. Those that showed time-dependent responses were divided into two distinct groups: the up-and-down group was associated with 'cellular defense mechanisms' such as apoptosis, cell adhesion, stress response and immune response and the down-and-up group with 'fundamental cellular processes' such as DNA replication, mitosis, RNA splicing, DNA repair and translation initiation. Genes showing both dose-and time-dependent responses exhibited a mixture of both features. A highly non-linear relationship between the IR dose and the transcriptional relative response was obtained from the dose-dependent group. The time-dependent group also exhibited a non-linear relationship as the complex effect group did. Some of the early-reactive-phase (1-4 h) genes showed a differential expression response to 0.01, 0.05 and 0.2 Gy but were unresponsive to 1 Gy. Some of the late-recovery-phase (12-48 h) genes showed a differential expression to 1 Gy but were relatively unresponsive to other doses. We further characterized the gene expression patterns that could be implicated in the molecular mechanism of the cellular responses to low and very low-dose irradiation.