Multiple Human Tissues Research Articles

Global Analysis of the Mammalian MHC Class I Immunopeptidome at the Organism-Wide Scale

Understanding the molecular principles that govern the composition of the mammalian MHC-I immunopeptidome (MHC-Ii) across different primary tissues is fundamentally important to predict how T cell respond in different contexts in vivo. Here, we performed a global analysis of the mammalian MHC-Ii from 29 and 19 primary human and mouse tissues, respectively. First, we observed that different HLA-A, -B and -C allotypes do not contribute evenly to the global composition of the MHC-Ii across multiple human tissues. Second, w e found that peptides that are presented in a tissue-dependent and -independent manner share very distinct properties. Third, we discovered that proteins that were evolutionarily hyperconserved represent the primary source of the MHC-Ii at the organism-wide scale. Finally, we uncovered a remarkable antigen processing and presentation network that may drive the high level of heterogeneity of the MHC-Ii across different tissues in mammals. This study opens up new avenues toward a system-wide understanding of antigen presentation in vivo and may serve as ground work to understand tissue-dependent T cell responses in autoimmunity, infectious diseases and cancer.

Structure of the Receptor Binding Domain of EnvP(b)1, an Endogenous Retroviral Envelope Protein Expressed in Human Tissues.

EnvP(b)1 is an endogenous retroviral envelope gene found in human and other primate genomes. We report EnvP(b)1 sequences in primate genomes consistent with an integration event between 40 and 71 million years ago. Using a highly specific polyclonal antiserum raised against the putative receptor binding domain (RBD) of human EnvP(b)1, we detected expression in human placenta, ovaries, and thymus. We found that EnvP(b)1 is proteolytically processed, and using cell-cell fusion assays in multiple primate cell lines, we demonstrated that extant EnvP(b)1 proteins from a variety of primate genomes are fusogenic. This work supports the idea that EnvP(b)1 is under purifying selection and its fusogenic activity has been maintained for over 40 million years. We determined the structure of the RBD of human EnvP(b)1, which defines structural similarities with extant leukemia viruses, despite little sequence conservation. This structure highlights a common scaffold from which novel receptor binding specificities likely evolved. The evolutionary plasticity of this domain may underlie the diversity of related Envs in circulating viruses.IMPORTANCE Organisms can access genetic and functional novelty by capturing viral elements within their genomes, where they can evolve to drive new cellular or organismal processes. We demonstrate that a retroviral envelope gene, EnvP(b)1, has been maintained and its fusion activity preserved for 40 to 71 million years. It is expressed as a protein in multiple healthy human tissues. We determined the structure of its inferred receptor binding domain and compared it with the same domain in modern viruses. We found a common conserved architecture that underlies the varied receptor binding activity of divergent Env genes. The modularity and versatility of this domain may underpin the evolutionary success of this clade of fusogens.

SARS-CoV-2 Receptor Angiotensin I-Converting Enzyme Type 2 (ACE2) Is Expressed in Human Pancreatic β-Cells and in the Human Pancreas Microvasculature.

Increasing evidence demonstrated that the expression of Angiotensin I-Converting Enzyme type 2 (ACE2) is a necessary step for SARS-CoV-2 infection permissiveness. In light of the recent data highlighting an association between COVID-19 and diabetes, a detailed analysis aimed at evaluating ACE2 expression pattern distribution in human pancreas is still lacking. Here, we took advantage of INNODIA network EUnPOD biobank collection to thoroughly analyze ACE2, both at mRNA and protein level, in multiple human pancreatic tissues and using several methodologies. Using multiple reagents and antibodies, we showed that ACE2 is expressed in human pancreatic islets, where it is preferentially expressed in subsets of insulin producing β-cells. ACE2 is also highly expressed in pancreas microvasculature pericytes and moderately expressed in rare scattered ductal cells. By using different ACE2 antibodies we showed that a recently described short-ACE2 isoform is also prevalently expressed in human β-cells. Finally, using RT-qPCR, RNA-seq and High-Content imaging screening analysis, we demonstrated that pro-inflammatory cytokines, but not palmitate, increase ACE2 expression in the β-cell line EndoC-βH1 and in primary human pancreatic islets. Taken together, our data indicate a potential link between SARS-CoV-2 and diabetes through putative infection of pancreatic microvasculature and/or ductal cells and/or through direct β-cell virus tropism.

Automatic Force-Based Probe Positioning for Precise Robotic Ultrasound Acquisition

The correct orientation of an ultrasound (US) probe is one of the main parameters governing the US image quality. With the rise of robotic ultrasound systems (RUSS), methods that can automatically compute the orientation promise repeatable, automatic acquisition from predefined angles resulting in high-quality US imaging. In this article, we propose a method to automatically position a US probe orthogonally to the tissue surface, thereby improving sound propagation and enabling RUSS to reach predefined orientations relatively to the surface normal at the contact point. The method relies on the derivation of the underlying mechanical model. Two rotations around orthogonal axes are carried out, while the contact force is being recorded. Then, the force data are fed into the model to estimate the normal direction. Accordingly, the probe orientation can be computed without requiring visual features. The method is applicable to the convex and linear probes. It has been evaluated on a phantom with varying tilt angles and on multiple human tissues (forearm, upper arm, lower back, and leg). As a result, it has outperformed existing methods in terms of accuracy. The mean (±SD) absolute angular difference on the in-vivo tissues averaged over all anatomies and probe types is 2.9±1.6° and 2.2±1.5° on the phantom.

The tissue renin-angiotensin system (tRAS) and the impact of its inhibition on inflammation and bone loss in the periodontal tissue.

Recently, the existence of the tissue renin-angiotensin system (tRAS) has been described for multiple tissues in humans, suggesting its fundamental role in the progression of inflammation and fibrosis. Evidence arises that tRAS might have an impact on the progression of periodontitis and bone loss. However, neither the role of tRAS nor its impact as a therapeutic target have been systematically evaluated for periodontal tissue. The present study sought to characterise tRAS in the periodontal tissue and the effect of its inhibition on periodontal inflammation and bone loss. This systematic review was performed according to the preferred reporting items for systematic reviews and meta analyses (PRISMA) statement. Literature was searched using Web of Science core collection (Web of Science), Medline (Ovid), Cochrane central register of controlled trials (Ovid), Cochrane database of systematic reviews (Ovid), Google Scholar databases and the references of the retrieved studies in March 2020. Information on study design, sample size, population, procedure, type of intervention, observation time, as well as information on sources of bias, was extracted and evaluated. From 455 identified articles, 17 were included in the qualitative synthesis and 11 were included in the quantitative synthesis. Outcomes of studies indicated that the inhibition of tRAS components led to a reduction of periodontal bone loss and inflammation, dependent on the inhibitor used. The findings suggested an important role of tRAS in the periodontal tissue and indicate a potential therapeutic approach for periodontal diseases.

Exons as units of phenotypic impact for truncating mutations in autism.

Autism spectrum disorders (ASD) are a group of related neurodevelopmental diseases displaying significant genetic and phenotypic heterogeneity. Despite recent progress in understanding ASD genetics, the nature of phenotypic heterogeneity across probands remains unclear. Notably, likely gene-disrupting (LGD) de novo mutations affecting the same gene often result in substantially different ASD phenotypes. Nevertheless, we find that truncating mutations affecting the same exon frequently lead to strikingly similar intellectual phenotypes in unrelated ASD probands. Analogous patterns are observed for two independent proband cohorts and several other important ASD-associated phenotypes. We find that exons biased toward prenatal and postnatal expression preferentially contribute to ASD cases with lower and higher IQ phenotypes, respectively. These results suggest that exons, rather than genes, often represent a unit of effective phenotypic impact for truncating mutations in autism. The observed phenotypic patterns are likely mediated by nonsense-mediated decay (NMD) of splicing isoforms, with autism phenotypes usually triggered by relatively mild (15-30%) decreases in overall gene dosage. We find that each ASDgene with recurrent mutations can be characterized by a parameter, phenotype dosage sensitivity (PDS), which quantifies the relationship between changes in a gene's dosage and changes in a given disease phenotype. We further demonstrate analogous relationships between exonLGDs and gene expressionchanges in multiplehuman tissues. Therefore, similar phenotypic patterns may be also observed in other human genetic disorders.

Advantage of fat-derived CD73 positive cells from multiple human tissues, prospective isolated mesenchymal stromal cells

Somatic stem cells have been isolated from multiple human tissues for their potential usefulness in cell therapy. Currently, mesenchymal stromal cells (MSCs) are prepared after several passages requiring a few months of cell culture. In this study, we used a prospective isolation method of somatic stem cells from gestational or fat tissues, which were identified using CD73 antibody. CD73-positive population from various tissues existed individually in flowcytometric pattern, especially subcutaneous fat- and amniotic-derived cells showed the highest enrichment of CD73-positive cells. Moreover, the cell populations isolated with the prospective method showed higher proliferative capacity and stem cell marker expression, compared to the cell populations which isolated through several passages of culturing whole living cells: which we named “conventional method” in this paper. Furthermore, the therapeutic potential of CD73-positive cells was evaluated in vivo using a mouse model of pulmonary fibrosis. After intranasal administration, murine CD73-positive cells reduced macrophage infiltration and inhibited fibrosis development. These results suggest that further testing using CD73-positive cells may be beneficial to help establish the place in regenerative medicine use.

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease.

Parkinson’s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

COVID-19 and androgen-targeted therapy for prostate cancer patients.

The current pandemic (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global health challenge with active development of antiviral drugs and vaccines seeking to reduce its significant disease burden. Early reports have confirmed that transmembrane serine protease 2 (TMPRSS2) and angiotensin converting enzyme 2 (ACE2) are critical targets of SARS-CoV-2 that facilitate viral entry into host cells. TMPRSS2 and ACE2 are expressed in multiple human tissues beyond the lung including the testes where predisposition to SARS-CoV-2 infection may exist. TMPRSS2 is an androgen-responsive gene and its fusion represents one of the most frequent alterations in prostate cancer. Androgen suppression by androgen deprivation therapy and androgen receptor signaling inhibitors form the foundation of prostate cancer treatment. In this review, we highlight the growing evidence in support of androgen regulation of TMPRSS2 and ACE2 and the potential clinical implications of using androgen suppression to downregulate TMPRSS2 to target SARS-CoV-2. We also discuss the future directions and controversies that need to be addressed in order to establish the viability of targeting TMPRSS2 and/or ACE2 through androgen signaling regulation for COVID-19 treatment, particularly its relevance in the context of prostate cancer management.

Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing

Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases.

SERPINA1 gene expression in whole blood links the rs6647 variant G allele to an increased risk of large artery atherosclerotic stroke.

The rs6647 variant G allele in SERPINA1 gene was reported to be associated with the risk of large artery atherosclerotic stroke (LAS), however, the mechanism remains unclear. Here, we performed a functional annotation of the rs6647 variant by using the software HaploReg version 4.1 (HaploReg v4.1). Next, the expression quantitative trait loci (eQTLs) analysis of multiple datasets was conducted for determining the association between the rs6647 and SERPINA1 expression in various tissues. Then, a case-control gene expression analysis was done using two independent ischemic stroke (IS) gene expression datasets. Finally, SERPINA1 expression in whole blood samples from 8 LAS patients and 14 healthy persons were compared. The functional annotation suggested that the rs6647 regulates gene expression in multiple human tissues especially in brain and blood. The eQTLs analysis revealed a significant association of the rs6647 G allele with increased expression of SERPINA1 gene only in whole blood. Compared with the controls, there was an increased expression of SERPINA1 gene in whole blood in both IS patients and LAS patients. SERPINA1 gene expression in whole blood bridges the rs6647 variant G allele with increased LAS risk, providing new insights into the mechanisms underlying role of the rs6647 in determining LAS risk.

Common variants in LTBP3 gene contributed to the risk of hip osteoarthritis in Han Chinese population.

Osteoarthritis (OA) is a common chronic joint disease affected by environmental and genetic factors. The LTBP3 gene may be involved in the occurrence and development of OA by regulating TGF-β activity and the TGF-β signaling pathway. A total of 2780 study subjects, including 884 hip OA cases and 1896 controls, were recruited. Nine tag single-nucleotide polymorphisms (SNPs) located within the LTBP3 gene region were selected for genotyping. Genetic association analyses were performed at both the genotypic and allelic levels. GTEx data were extracted to investigate the functional consequence of significant SNPs. SNP rs10896015 was significantly associated with the risk of hip OA at both the genotypic (P=0.0019) and allelic levels (P=0.0009). The A allele of this SNP was significantly associated with a decreased risk of HOA (OR [95%CI] = 0.79 [0.69–0.91]). This SNP was also significantly associated with the clinical severity of hip OA. SNP rs10896015 could affect the gene expression of 11 genes, including LTBP3, in multiple human tissues based on GTEx data. We obtained evidence for a genetic association between the LTBP3 gene and hip OA susceptibility and clinical severity based on Chinese Han populations. Our findings replicated the association signals reported by a recent genome-wide association study and deepen the basic understanding of osteoarthritis pathology.

Genetic Determinants of Reduced Arsenic Metabolism Efficiency in the 10q24.32 Region Are Associated With Reduced AS3MT Expression in Multiple Human Tissue Types.

Approximately 140 million people worldwide are exposed to inorganic arsenic through contaminated drinking water. Chronic exposure increases risk for cancers as well as cardiovascular, respiratory, and neurologic diseases. Arsenic metabolism involves the AS3MT (arsenic methyltransferase) gene, and arsenic metabolism efficiency (AME, measured as relative concentrations of arsenic metabolites in urine) varies among individuals. Inherited genetic variation in the 10q24.32 region, containing AS3MT, influences AME, but the mechanisms remain unclear. To better understand these mechanisms, we use tissue-specific expression data from GTEx (Genotype-tissue Expression project) to identify cis-eQTLs (expression quantitative trait loci) for AS3MT and other nearby genes. We combined these data with results from a genome-wide association study of AME using "colocalization analysis," to determine if 10q24.32 SNPs (single nucleotide polymorphisms) that affect AME also affect expression of AS3MT or nearby genes. These analyses identified cis-eQTLs for AS3MT in 38 tissue types. Colocalization results suggest that the casual variant represented by AME lead SNP rs4919690 impacts expression of AS3MT in 13 tissue types (> 80% probability). Our results suggest this causal SNP also regulates/coregulates expression of nearby genes: BORCS7 (43 tissues), NT5C2 (2 tissues), CYP17A1-AS1 (1 tissue), and RP11-724N1.1 (1 tissue). The rs4919690 allele associated with decreased AME is associated with decreased expression of AS3MT (and other coregulated genes). Our study provides a potential biological mechanism for the association between 10q24.32 variation and AME and suggests that the causal variant, represented by rs4919690, may impact AME (as measured in urine) through its effects on arsenic metabolism occurring in multiple tissue types.

Mammalian Alternative Translation Initiation Is Mostly Nonadaptive.

Alternative translation initiation (ATLI) refers to the existence of multiple translation initiation sites per gene and is a widespread phenomenon in eukaryotes. ATLI is commonly assumed to be advantageous through creating proteome diversity or regulating protein synthesis. We here propose an alternative hypothesis that ATLI arises primarily from nonadaptive initiation errors presumably due to the limited ability of ribosomes to distinguish sequence motifs truly signaling translation initiation from similar sequences. Our hypothesis, but not the adaptive hypothesis, predicts a series of global patterns of ATLI, all of which are confirmed at the genomic scale by quantitative translation initiation sequencing in multiple human and mouse cell lines and tissues. Similarly, although many codons differing from AUG by one nucleotide can serve as start codons, our analysis suggests that using non-AUG start codons is mostly disadvantageous. These and other findings strongly suggest that ATLI predominantly results from molecular error, requiring a major revision of our understanding of the precision and regulation of translation initiation.

Effects of Fever on 18F-FDG Distribution In Vivo: a Preliminary Study.

Elevated body temperature might change glucose metabolism in human organs. The purpose of this study is to explore 18F-FDG distribution in febrile patients on the day of 18F-FDG PET/CT scanning and compare it with patients with a normal temperature. 18F-FDG PET/CT was performed on 69 febrile patients and 82 patients with a normal temperature. Patient sociodemographic data, blood glucose levels before PET/CT, body temperature on the day of the exam, and laboratory test results were collected. Maximal standard uptake values (SUVmax) in the brain, mediastinal blood pool, liver, spleen, and the bone marrow were compared. Compared with the controls, SUVmax of the febrile patients was significantly lower in the brain, mediastinal blood pool, and the liver (p < 0.01), and higher in the spleen and bone marrow (p < 0.01). In the febrile group, SUVmax was not significantly different between the FDG burden and non-FDG burden patients (p > 0.05). Body temperature was found negatively correlated with SUVmax in the brain (r = - 0.646), mediastinal blood pool (r = - 0.530), and the liver (r = - 0.384), and positively correlated with the SUVmax in the spleen (r = 0.592) and bone marrow (r = 0.651). Multivariate linear regression established body temperature on the day of PET/CT as an independent affecting factor (p < 0.01) for the SUVmax in the brain, mediastinal blood pool, liver, spleen, and bone marrow. The SUV in the brain, liver, and mediastinal blood pool remained different (p < 0.05) after corrected with the SUVmax in the blood pool or liver. Fever influences 18F-FDG distribution in multiple human tissues and organs. Altered 18F-FDG distribution in vivo might affect results of disease lesion detection and tumor therapy response assessment. Correction with blood pool or liver SUV fails to cancel the effects of fever. The day of fever should be avoided for PET/CT scan, especially in assessing tumor therapy response.

OTUD4: A Potential Prognosis Biomarker for Multiple Human Cancers.

BackgroundDeubiquitinase OTU domain containing 4 (OTUD4) is initially identified as a K48-specific deubiquitinase and plays an important role in DNA damage repair signaling transduction. However, the expression level, prognostic role, biological function and mechanism of OTUD4 in multiple human cancers are unclear.MethodsGEPIA online (http://gepia.cancer-pku.cn/; The Cancer Genome Atlas (TCGA) database) was used to analyze the mRNA expression of OTUD4 in multiple human cancers. Kaplan-Meier plotter (KM plotter) database and TCGA database were used to evaluate the prognostic value of OTUD4 expression in multiple human cancers. MTT, Transwell and 3D culture assays were used to detect the role of OTUD4 in breast, liver and lung cancer cells. The correlation between OTUD4 and apoptosis signaling pathway and AKT signaling pathway was analyzed by Gene set enrichment analysis (GSEA).ResultsOTUD4 mRNA expression is significantly downregulated in multiple human cancer tissues. Survival analysis establishes that the downregulation of OTUD4 predicts poor prognosis in many solid tumors, including breast invasive carcinoma (BRCA), esophageal carcinoma (ESCA), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), and ovarian serous cystadenocarcinoma (OV). Furthermore, overexpression of OTUD4 could inhibit tumor cell proliferation, migration and invasion of breast, liver and lung cancer cells through inhibiting the AKT signaling pathway.ConclusionThis study found that OTUD4 may be a potential predictive factor for several human cancers and a tumor suppressor for breast, liver and lung cancer. The overexpression of OTUD4 restrained proliferation, migration and invasion of human breast, liver and lung cancer cells through promoting cancer cells apoptosis and inhibiting AKT signaling pathway. Notably, our results indicated that OTUD4 could be a useful biomarker for the prognosis of human cancers and a potential molecular target for diagnosis and treatment of breast, liver and lung cancer.

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

Differential network analysis of multiple human tissue interactomes highlights tissue-selective processes and genetic disorder genes.

Differential network analysis, designed to highlight network changes between conditions, is an important paradigm in network biology. However, differential network analysis methods have been typically designed to compare between two conditions and were rarely applied to multiple protein interaction networks (interactomes). Importantly, large-scale benchmarks for their evaluation have been lacking. Here, we present a framework for assessing the ability of differential network analysis of multiple human tissue interactomes to highlight tissue-selective processes and disorders. For this, we created a benchmark of 6499 curated tissue-specific Gene Ontology biological processes. We applied five methods, including four differential network analysis methods, to construct weighted interactomes for 34 tissues. Rigorous assessment of this benchmark revealed that differential analysis methods perform well in revealing tissue-selective processes (AUCs of 0.82-0.9). Next, we applied differential network analysis to illuminate the genes underlying tissue-selective hereditary disorders. For this, we curated a dataset of 1305 tissue-specific hereditary disorders and their manifesting tissues. Focusing on subnetworks containing the top 1% differential interactions in disease-relevant tissue interactomes revealed significant enrichment for disorder-causing genes in 18.6% of the cases, with a significantly high success rate for blood, nerve, muscle and heart diseases. Altogether, we offer a framework that includes expansive manually curated datasets of tissue-selective processes and disorders to be used as benchmarks or to illuminate tissue-selective processes and genes. Our results demonstrate that differential analysis of multiple human tissue interactomes is a powerful tool for highlighting processes and genes with tissue-selective functionality and clinical impact. Datasets are available as part of the Supplementary data. Supplementary data are available at Bioinformatics online.

Evaluation of the relationships of the WBP1L gene with schizophrenia and the general psychopathology scale based on a case-control study.

WBP1L is a target of microRNA 137 (miR-137) and has been considered a candidate gene for schizophrenia (SCZ). To investigate the relationships between WBP1L and SCZ and its related symptom scales, a total of 5,993 Chinese Han subjects, including 2,128 SCZ patients and 3,865 controls, were enrolled. In addition, an independent sample set for replication study including 1,052 SCZ patients and 2,124 controls were also recruited. Thirty-two tag single nucleotide polymorphisms (SNPs) located within gene region of WBP1L were selected for genotyping and analyzing. The expression quantitative trait loci (eQTL) effects for the targeted SNPs were investigated with gene expression data from multiple human tissues. Rs4147157 (OR = 0.84, p = 1.51 × 10-5 ) and rs284854 (OR = 1.14, p = 7.00 × 10-4 ) were significantly associated with SCZ disease status and these association signals were replicated in our replication sample. A significant association was identified between rs4147157 and the general (β = -.66, p = .001) and total (β = -.8, p = .0042) scores of positive and negative syndrome scale scores in SCZ patients. Both SNPs were significant eQTL for genes around WBP1L in human brain tissues including ARL3 and AS3MT. To conclude, SNPs rs4147157 and rs284854 were associated with SCZ in the Chinese Han population. Additionally, rs4147157 was significantly associated with specific symptom features of SCZ.

Brain clusterin protein isoforms and mitochondrial localization.

Clusterin (CLU), or apolipoprotein J (ApoJ), is the third most predominant genetic risk factor associated with late-onset Alzheimer's disease (LOAD). In this study, we use multiple rodent and human brain tissue and neural cell models to demonstrate that CLU is expressed as multiple isoforms that have distinct cellular or subcellular localizations in the brain. Of particular significance, we identify a non-glycosylated 45 kDa CLU isoform (mitoCLU) that is localized to the mitochondrial matrix and expressed in both rodent and human neurons and astrocytes. In addition, we show that rodent mitoCLU is translated from a non-canonical CUG (Leu) start site in Exon 3, a site that coincides with an AUG (Met) in human CLU. Last, we reveal that mitoCLU is present at the gene and protein level in the currently available CLU-/- mouse model. Collectively, these data provide foundational knowledge that is integral in elucidating the relationship between CLU and the development of LOAD.