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Identifying biological factors which contribute to the clinical progression of heterogeneous motor and non-motor phenotypes in Parkinson's disease may help to better understand the disease process. Several lipid-related genetic risk factors for Parkinson's disease have been identified, and the serum lipid signature of Parkinson's disease patients is significantly distinguishable from controls. However, the extent to which lipid profiles are associated with clinical outcomes remains unclear. Untargeted high-performance liquid chromatography-tandem mass spectrometry identified >900 serum lipids in Parkinson's disease subjects at baseline (n = 122), and the potential for machine learning models using these lipids to predict motor and non-motor clinical scores after 2 years (n = 67) was assessed. Machine learning models performed best when baseline serum lipids were used to predict the 2-year future Unified Parkinson's disease rating scale part three (UPDRS III) and Geriatric Depression Scale scores (both normalised root mean square error = 0.7). Feature analysis of machine learning models indicated that species of lysophosphatidylethanolamine, phosphatidylcholine, platelet-activating factor, sphingomyelin, diacylglycerol and triacylglycerol were top predictors of both motor and non-motor scores. Serum lipids were overall more important predictors of clinical outcomes than subject sex, age and mutation status of the Parkinson's disease risk gene LRRK2. Furthermore, lipids were found to better predict clinical scales than a panel of 27 serum cytokines previously measured in this cohort (The Michael J. Fox Foundation LRRK2 Clinical Cohort Consortium). These results suggest that lipid changes may be associated with clinical phenotypes in Parkinson's disease.
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BACKGROUND: DNA methylation is a critical molecular mark involved in cellular differentiation and cell-specific processes. Single-cell whole genome DNA methylation profiling methods hold great potential to resolve the DNA methylation profiles of individual cell-types. Here we present a method that couples single-cell combinatorial indexing (sci) with enzymatic conversion (sciEM) of unmethylated cytosines. RESULTS: The sciEM method facilitates DNA methylation profiling of single-cells that is highly correlated with single-cell bisulfite-based workflows (r2 > 0.99) whilst improving sequencing alignment rates, reducing adapter contamination and over-estimation of DNA methylation levels (CpG and non-CpG). As proof-of-concept we perform sciEM analysis of the temporal lobe, motor cortex, hippocampus and cerebellum of the human brain to resolve single-cell DNA methylation of all major cell-types. CONCLUSION: To our knowledge sciEM represents the first non-bisulfite single-cell DNA methylation sequencing approach with single-base resolution.
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Leucine-rich-repeat kinase 2 (LRRK2), a potential therapeutic target for the treatment of Parkinson's disease (PD), is highly expressed in monocytes and macrophages and may play a role in the regulation of inflammatory pathways. To determine how LRRK2 protein levels and/or its activity modulate inflammatory cytokine/chemokine levels in human immune cells, isogenic human induced pluripotent stem cells (iPSC) with the LRRK2-activating G2019S mutation, wild-type LRRK2, and iPSC deficient in LRRK2 were differentiated to monocytes and macrophages and stimulated with inflammatory toll-like receptor (TLR) agonists in the presence and absence of LRRK2 kinase inhibitors. The effect of LRRK2 inhibitors and the effect of increasing LRRK2 levels with interferon gamma on TLR-stimulated cytokines were also assessed in primary peripheral blood-derived monocytes. Monocytes and macrophages with the LRRK2 G2019S mutation had significantly higher levels of cytokines and chemokines in tissue culture media following stimulation with TLR agonists compared to isogenic controls. Knockout of LRRK2 impaired phagocytosis but did not significantly affect TLR-mediated cytokine levels. Interferon gamma significantly increased the levels of LRRK2 and phosphorylation of its downstream Rab10 substrate, and potentiated TLR-mediated cytokine levels. LRRK2 kinase inhibitors did not have a major effect on TLR-stimulated cytokine levels. Results suggest that the LRRK2 G2019S mutation may potentiate inflammation following activation of TLRs. However, this was not dependent on LRRK2 kinase activity. Indeed, LRRK2 kinase inhibitors had little effect on TLR-mediated inflammation under the conditions employed in this study.
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For more than a decade, researchers have sought to uncover the biological function of the enigmatic leucine rich repeat kinase 2 (LRRK2) enzyme, a large multi-domain protein with dual GTPase and kinase activities. Originally identified as a familial Parkinson's disease (PD) risk gene, variations in LRRK2 are also associated with risk of idiopathic PD, inflammatory bowel disease and susceptibility to bacterial infections. LRRK2 is highly expressed in peripheral immune cells and the potential of LRRK2 to regulate immune and inflammatory pathways has emerged as common link across LRRK2-implicated diseases. This review outlines the current genetic and biochemical evidence linking LRRK2 to the regulation of innate immune inflammatory pathways, including the toll-like receptor and inflammasome pathways. Evidence suggests a complex interplay between genetic risk and protective alleles acts to modulate immune outcomes in a manner dependent on the particular pathogen and cell type invaded.
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The heterogeneous nature of Parkinson's disease (PD) symptoms and variability in their progression complicates patient treatment and interpretation of clinical trials. Consequently, there is much interest in developing models that can predict PD progression. In this study we have used serum samples from a clinically well characterized longitudinally followed Michael J Fox Foundation cohort of PD patients with and without the common leucine-rich repeat kinase 2 (LRRK2) G2019S mutation. We have measured 27 inflammatory cytokines and chemokines in serum at baseline and after 1 year to investigate cytokine stability. We then used the baseline measurements in conjunction with machine learning models to predict longitudinal clinical outcomes after 2 years follow up. Using the normalized root mean square error (NRMSE) as a measure of performance, the best prediction models were for the motor symptom severity scales, with NRMSE of 0.1123 for the Hoehn and Yahr scale and 0.1193 for the unified Parkinson's disease rating scale part three (UPDRS III). For each model, the top variables contributing to prediction were identified, with the chemokines macrophage inflammatory protein one alpha (MIP1α), and monocyte chemoattractant protein one (MCP1) making the biggest peripheral contribution to prediction of Hoehn and Yahr and UPDRS III, respectively. These results provide information on the longitudinal assessment of peripheral inflammatory cytokines in PD and give evidence that peripheral cytokines may have utility for aiding prediction of PD progression using machine learning models.
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The human Y chromosome has an inevitable role in male fertility because it contains many genes critical for spermatogenesis and the development of the male gonads. Any genetic variation or epigenetic modification affecting the expression pattern of Y chromosome genes may thus lead to male infertility. In this study, we performed isoform-level gene expression profiling of Y chromosome genes within the azoospermia factor (AZF) regions, their X chromosome counterparts, and few autosomal paralogues in testicular biopsies of 12 men with preserved spermatogenesis and 68 men with nonobstructive azoospermia (NOA) (40 Sertoli-cell-only syndrome (SCOS) and 28 premiotic maturation arrest (MA)). This was undertaken using quantitative real-time PCR (qPCR) at the transcript level and Western blotting (WB) and immunohistochemistry (IHC) at the protein level. We profiled the expression of 41 alternative transcripts encoded by 14 AZFa, AZFb, and AZFc region genes (USP9Y, DDX3Y, XKRY, HSFY1, CYORF15A, CYORF15B, KDM5D, EIF1AY, RPS4Y2, RBMY1A1, PRY, BPY2, DAZ1, and CDY1) as well as their X chromosome homologue transcripts and a few autosomal homologues. Of the 41 transcripts, 18 were significantly down-regulated in men with NOA when compared with those of men with complete spermatogenesis. In contrast, the expression of five transcripts increased significantly in NOA patients. Furthermore, to confirm the qPCR results at the protein level, we performed immunoblotting and IHC experiments (based on 24 commercial and homemade antibodies) that detected 10 AZF-encoded proteins. In addition, their localization in testis cell types and organelles was determined. Interestingly, the two missing proteins, XKRY and CYORF15A, were detected for the first time. Finally, we focused on the expression patterns of the significantly altered genes in 12 MA patients with successful sperm retrieval compared to those of 12 MA patients with failed sperm retrieval to predict the success of sperm retrieval in azoospermic men. We showed that HSFY1-1, HSFY1-3, BPY2-1, KDM5C2, RBMX2, and DAZL1 transcripts could be used as potential molecular markers to predict the presence of spermatozoa in MA patients. In this study, we have identified isoform level signature that can be used to discriminate effectively between MA, SCOS, and normal testicular tissues and suggests the possibility of diagnosing the presence of mature sperm cell in azoospermic men to prevent additional testicular sperm extraction (TESE) surgery.
Assuntos
Azoospermia/genética , Cromossomos Humanos X , Cromossomos Humanos Y , Perfilação da Expressão Gênica , Testículo/patologia , Adulto , Azoospermia/patologia , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
The Chromosome-centric Human Proteome Project (C-HPP) aims to systematically map the entire human proteome with the intent to enhance our understanding of human biology at the cellular level. This project attempts simultaneously to establish a sound basis for the development of diagnostic, prognostic, therapeutic, and preventive medical applications. In Iran, current efforts focus on mapping the proteome of the human Y chromosome. The male-specific region of the Y chromosome (MSY) is unique in many aspects and comprises 95% of the chromosome's length. The MSY continually retains its haploid state and is full of repeated sequences. It is responsible for important biological roles such as sex determination and male fertility. Here, we present the most recent update of MSY protein-encoding genes and their association with various traits and diseases including sex determination and reversal, spermatogenesis and male infertility, cancers such as prostate cancers, sex-specific effects on the brain and behavior, and graft-versus-host disease. We also present information available from RNA sequencing, protein-protein interaction, post-translational modification of MSY protein-coding genes and their implications in biological systems. An overview of Human Y chromosome Proteome Project is presented and a systematic approach is suggested to ensure that at least one of each predicted protein-coding gene's major representative proteins will be characterized in the context of its major anatomical sites of expression, its abundance, and its functional relevance in a biological and/or medical context. There are many technical and biological issues that will need to be overcome in order to accomplish the full scale mapping.