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Cleft lip with or without cleft palate (CL/P) is a common birth defect with a complex, heterogeneous etiology. It is well established that common and rare sequence variants contribute to the formation of CL/P, but the contribution of copy-number variants (CNVs) to cleft formation remains relatively understudied. To fill this knowledge gap, we conducted a large-scale comparative analysis of genome-wide CNV profiles of 869 individuals from the Philippines and 233 individuals of European ancestry with CL/P with three primary goals: first, to evaluate whether differences in CNV number, amount of genomic content, or amount of coding genomic content existed within clefting subtypes; second, to assess whether CNVs in our cohort overlapped with known Mendelian clefting loci; and third, to identify unestablished Mendelian clefting genes. Significant differences in CNVs across cleft types or in individuals with non-syndromic versus syndromic clefts were not observed; however, several CNVs in our cohort overlapped with known syndromic and non-syndromic Mendelian clefting loci. Moreover, employing a filtering strategy relying on population genetics data that rare variants are on the whole more deleterious than common variants, we identify several CNV-associated gene losses likely driving non-syndromic clefting phenotypes. By prioritizing genes deleted at a rare frequency across multiple individuals with clefts yet enriched in our cohort of individuals with clefts compared to control subjects, we identify COBLL1, RIC1, and ARHGEF38 as clefting genes. CRISPR-Cas9 mutagenesis of these genes in Xenopus laevis and Danio rerio yielded craniofacial dysmorphologies, including clefts analogous to those seen in human clefting disorders.
Assuntos
Fenda Labial , Fissura Palatina , Variações do Número de Cópias de DNA , Humanos , Fenda Labial/genética , Fissura Palatina/genética , Estudo de Associação Genômica Ampla , Fatores de Troca do Nucleotídeo Guanina/genética , Fenótipo , Fatores de Transcrição/genéticaRESUMO
Osteoarthritis is the most common chronic joint disease, characterized by the abnormal remodeling of joint tissues including articular cartilage and subchondral bone. However, there are currently no therapeutic drug targets to slow the progression of disease because disease pathogenesis is largely unknown. Thus, the goals of this study were to identify metabolic differences between articular cartilage and subchondral bone, compare the metabolic shifts in osteoarthritic grade III and IV tissues, and spatially map metabolic shifts across regions of osteoarthritic hip joints. Articular cartilage and subchondral bone from 9 human femoral heads were obtained after total joint arthroplasty, homogenized and metabolites were extracted for liquid chromatography-mass spectrometry analysis. Metabolomic profiling revealed that distinct metabolic endotypes exist between osteoarthritic tissues, late-stage grades, and regions of the diseased joint. The pathways that contributed the most to these differences between tissues were associated with lipid and amino acid metabolism. Differences between grades were associated with nucleotide, lipid, and sugar metabolism. Specific metabolic pathways such as glycosaminoglycan degradation and amino acid metabolism, were spatially constrained to more superior regions of the femoral head. These results suggest that radiography-confirmed grades III and IV osteoarthritis are associated with distinct global metabolic and that metabolic shifts are not uniform across the joint. The results of this study enhance our understanding of osteoarthritis pathogenesis and may lead to potential drug targets to slow, halt, or reverse tissue damage in late stages of osteoarthritis.
Assuntos
Cartilagem Articular , Osteoartrite , Humanos , Osteoartrite/patologia , Cartilagem Articular/metabolismo , Cabeça do Fêmur/diagnóstico por imagem , Cabeça do Fêmur/metabolismo , Radiografia , Aminoácidos/metabolismo , LipídeosRESUMO
Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (n = 48 study participants) and age- and sex-matched normal controls (n = 47) and analyzed by liquid chromatography-mass spectrometry. Orthogonal partial least squares-discriminant analysis was used to generate a global metabolomic profile of early ADPKD for the identification of metabolic pathway alterations and discriminatory metabolites as candidates of diagnostic and prognostic biomarkers. The global metabolomic profile exhibited alterations in steroid hormone biosynthesis and metabolism, fatty acid metabolism, pyruvate metabolism, amino acid metabolism, and the urea cycle. A panel of 46 metabolite features was identified as candidate diagnostic biomarkers. Notable putative identities of candidate diagnostic biomarkers for early detection include creatinine, cAMP, deoxycytidine monophosphate, various androgens (testosterone; 5-α-androstane-3,17,dione; trans-dehydroandrosterone), betaine aldehyde, phosphoric acid, choline, 18-hydroxycorticosterone, and cortisol. Metabolic pathways associated with variable rates of disease progression included steroid hormone biosynthesis and metabolism, vitamin D3 metabolism, fatty acid metabolism, the pentose phosphate pathway, tricarboxylic acid cycle, amino acid metabolism, sialic acid metabolism, and chondroitin sulfate and heparin sulfate degradation. A panel of 41 metabolite features was identified as candidate prognostic biomarkers. Notable putative identities of candidate prognostic biomarkers include ethanolamine, C20:4 anandamide phosphate, progesterone, various androgens (5-α-dihydrotestosterone, androsterone, etiocholanolone, and epiandrosterone), betaine aldehyde, inflammatory lipids (eicosapentaenoic acid, linoleic acid, and stearolic acid), and choline. Our exploratory data support metabolic reprogramming in early ADPKD and demonstrate the ability of liquid chromatography-mass spectrometry-based global metabolomic profiling to detect metabolic pathway alterations as new therapeutic targets and biomarkers for early diagnosis and tracking disease progression of ADPKD.NEW & NOTEWORTHY To our knowledge, this study is the first to generate urinary global metabolomic profiles from individuals with early-stage ADPKD with preserved renal function for biomarker discovery. The exploratory dataset reveals metabolic pathway alterations that may be responsible for early cystogenesis and rapid disease progression and may be potential therapeutic targets and pathway sources for candidate biomarkers. From these results, we generated a panel of candidate diagnostic and prognostic biomarkers of early-stage ADPKD for future validation.
Assuntos
Rim Policístico Autossômico Dominante , Humanos , Rim Policístico Autossômico Dominante/diagnóstico , Androgênios , Biomarcadores/urina , Metabolômica/métodos , Progressão da Doença , Redes e Vias Metabólicas , Colina , Aminoácidos , Ácidos Graxos , EsteroidesRESUMO
Osteoarthritis (OA) is a chronic joint disease with heterogenous metabolic pathology. To gain insight into OA-related metabolism, metabolite extracts from healthy (n = 11) and end-stage osteoarthritic cartilage (n = 35) were analyzed using liquid chromatography-mass spectrometry metabolomic profiling. Specific metabolites and metabolic pathways, including lipid and amino acid pathways, were differentially regulated in osteoarthritis-derived and healthy cartilage. The detected alterations in amino acids and lipids highlighted key differences in bioenergetic resources, matrix homeostasis, and mitochondrial alterations in OA-derived cartilage compared to healthy cartilage. Moreover, the metabolomic profiles of osteoarthritic cartilage separated into four distinct endotypes, highlighting the heterogenous nature of OA metabolism and the diverse landscape within the joint in patients. The results of this study demonstrate that human cartilage has distinct metabolomic profiles in healthy and end-stage OA patients. By taking a comprehensive approach to assess metabolic differences between healthy and osteoarthritic cartilage and within osteoarthritic cartilage alone, several metabolic pathways with distinct regulation patterns were detected. Additional investigation may lead to the identification of metabolites that may serve as valuable indicators of disease status or potential therapeutic targets.
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Objective: Osteoarthritis (OA) is a chronic joint disease with heterogenous metabolic pathology. To gain insight into OA-related metabolism, healthy and end-stage osteoarthritic cartilage were compared metabolically to uncover disease-associated profiles, classify OA-specific metabolic endotypes, and identify targets for intervention for the diverse populations of individuals affected by OA. Design: Femoral head cartilage (n=35) from osteoarthritis patients were collected post-total joint arthroplasty. Healthy cartilage (n=11) was obtained from a tissue bank. Metabolites from all cartilage samples were extracted and analyzed using liquid chromatography-mass spectrometry metabolomic profiling. Additionally, cartilage extracts were pooled and underwent fragmentation analysis for biochemical identification of metabolites. Results: Specific metabolites and metabolic pathways, including lipid- and amino acid pathways, were differentially regulated between osteoarthritis-derived and healthy cartilage. The detected alterations of amino acids and lipids highlight key differences in bioenergetic resources, matrix homeostasis, and mitochondrial alterations in osteoarthritis-derived cartilage compared to healthy. Moreover, metabolomic profiles of osteoarthritic cartilage separated into four distinct endotypes highlighting the heterogenous nature of OA metabolism and diverse landscape within the joint between patients. Conclusions: The results of this study demonstrate that human cartilage has distinct metabolomic profiles between healthy and end-stage osteoarthritis patients. By taking a comprehensive approach to assess metabolic differences between healthy and osteoarthritic cartilage, and within osteoarthritic cartilage alone, several metabolic pathways with distinct regulation patterns were detected. Additional investigation may lead to the identification of metabolites that may serve as valuable indicators of disease status or potential therapeutic targets.
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The mechanism by which chondrocytes respond to reduced mechanical loading environments and the subsequent risk of developing osteoarthritis remains unclear. This is of particular concern for astronauts. In space the reduced joint loading forces during prolonged microgravity (10-6 g) exposure could lead to osteoarthritis (OA), compromising quality of life post-spaceflight. In this study, we encapsulated human chondrocytes in an agarose gel of similar stiffness to the pericellular matrix to mimic the cartilage microenvironment. We then exposed agarose-chondrocyte constructs to simulated microgravity (SM) using a rotating wall vessel (RWV) bioreactor to better assess the cartilage health risks associated with spaceflight. Global metabolomic profiling detected a total of 1205 metabolite features across all samples, with 497 significant metabolite features identified by ANOVA (FDR-corrected p-value < 0.05). Specific metabolic shifts detected in response to SM exposure resulted in clusters of co-regulated metabolites, as well as key metabolites identified by variable importance in projection scores. Microgravity-induced metabolic shifts in gel constructs and media were indicative of protein synthesis, energy metabolism, nucleotide metabolism, and oxidative catabolism. The microgravity associated-metabolic shifts were consistent with early osteoarthritic metabolomic profiles in human synovial fluid, which suggests that even short-term exposure to microgravity (or other reduced mechanical loading environments) may lead to the development of OA.
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Objective: Exercise is known to induce beneficial effects in synovial joints. However, the mechanisms underlying these are unclear. Synovial joints experience repeated mechanical loading during exercise. These mechanical stimuli are transduced into biological responses through cellular mechanotransduction. Mechanotransduction in synovial joints is typically studied in tissues. However, synovial fluid directly contacts all components of the joint, and thus may produce a whole-joint picture of the mechanotransduction response to loading. The objective of this study was to determine if metabolic phenotypes are present in the synovial fluid after acute exercise as a first step to understanding the beneficial effects of exercise on the joint. Material and methods: Mice underwent a single night of voluntary wheel running or standard housing and synovial fluid was harvested for global metabolomic profiling by LC-MS. Hierarchical unsupervised clustering, partial least squares discriminant, and pathway analysis provided insight into exercise-induced mechanotransduction. Results: Acute exercise produced a distinct metabolic phenotype in synovial fluid. Mechanosensitive metabolites included coenzyme A derivatives, prostaglandin derivatives, phospholipid species, tryptophan, methionine, vitamin D3, fatty acids, and thiocholesterol. Enrichment analysis identified several pathways previously linked to exercise including amino acid metabolism, inflammatory pathways, citrulline-nitric oxide cycle, catecholamine biosynthesis, ubiquinol biosynthesis, and phospholipid metabolism. Conclusion: To our knowledge, this is the first study to investigate metabolomic profiles of synovial fluid during in vivo mechanotransduction. These profiles indicate that exercise induced stress-response processes including both pro- and anti-inflammatory pathways. Further research will expand these results and define the relationship between the synovial fluid and the serum.
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Osteoarthritis occurs frequently after joint injury. Currently, osteoarthritis is diagnosed by radiographic changes that are typically found after the disease has progressed to multiple tissues. The primary objective was to compare potential metabolomic biomarkers of joint injury between synovial fluid and serum in a mouse model of posttraumatic osteoarthritis. The secondary objective was to gain insight into the pathophysiology of osteoarthritis by examining metabolomic profiles after joint injury. Twelve-week-old adult female C57BL/6 mice (n = 12) were randomly assigned to control, Day 1, or Day 8 postinjury groups. Randomly selected stifle joints were subjected to a single rapid compression. At Days 1 and 8 postinjury, serum was extracted before mice were euthanized for synovial fluid collection. Metabolomic profiling detected ~2500 metabolites across serum and synovial fluid. Of these, 179 were positively correlated and 51 were negatively correlated between synovial fluid and serum, indicating the potential for the development of metabolomic biomarkers. Synovial fluid captured injury-induced differences in metabolomic profiles at both Days 1 and 8 after injury whereas serum did not. However, synovial fluid and serum were distinct at both time points after injury. In synovial fluid, pathways of interest mapped to amino acid synthesis and degradation, bupropion degradation, and transfer RNA (tRNA) charging. In serum, pathways were amino acid synthesis and degradation, the phospholipase pathway, and nicotine degradation. These results provide a rich picture of the injury response at early time points after joint injury. Furthermore, the correlations between synovial fluid and serum metabolites suggest the potential to gain insight into intra-articular pathophysiology through analysis of serum metabolites.