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1.
Australas J Ageing ; 41(4): 522-529, 2022 Dec.
Article in English | MEDLINE | ID: mdl-35129267

ABSTRACT

OBJECTIVES: COVID-19-related restrictions for residential aged care (RAC) have been significant. However, the mental health impacts for residents already living with mental illness remain poorly understood. In this study, we examined change in mental health symptom burden for this group and potential associations with clinical and contextual factors. METHODS: We retrospectively reviewed medical records of patients of a specialist aged mental health clinical service for RAC. Change in symptoms (measured by the Neuropsychiatric Inventory, Nursing Home version [NPI-NH]) between pre-pandemic and two pandemic timepoints were analysed using Wilcoxon signed-rank tests. Potential associations with baseline diagnosis or severity of 'lockdown' restrictions in RAC were assessed using linear regression. RESULTS: Data from 91 patient files were included. The median NPI-NH score slightly increased during wave one (baseline median NPI-NH score = 17.0 [interquartile range, IQR: 10.0-27.0]; wave one median = 19.0, IQR: 8.0-30.0) and fell during wave two (Median: 15.5, IQR: 7.0-28.0), but changes were not statistically significant (all p-values >0.05). Adjusting for age and gender, an association between neurocognitive disorder diagnosis and NPI-NH score during wave one was statistically but not clinically significant (p = 0.046). No other significant associations were identified. CONCLUSIONS: Accounting for pre-pandemic symptoms, we found no clinically relevant evidence of worsening mental health during COVID-19 for a group of older people living with mental illness in RAC. This adds to evidence of relatively stable mental health in older people during the pandemic. Research and policy should consider underpinning mechanisms and emphasise patient- and carer-centred interventions.


Subject(s)
COVID-19 , Dementia , Humans , Aged , Dementia/diagnosis , Dementia/epidemiology , Dementia/therapy , Mental Health , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/therapy , Retrospective Studies , Nursing Homes
2.
Biomark Cancer ; 7: 1-6, 2015.
Article in English | MEDLINE | ID: mdl-25674022

ABSTRACT

Trisomy 8 acute myeloid leukemia (AML) is the commonest numerical aberration in AML. Here we present a global analysis of trisomy 8 AML using methylated DNA immunoprecipitation-sequencing (MeDIP-seq). The study is based on three diagnostic trisomy 8 AML and their parallel relapse status in addition to nine non-trisomic AML and four normal bone marrows (NBMs). In contrast to non-trisomic DNA samples, trisomy 8 AML showed a characteristic DNA methylation distribution pattern because an increase in the frequency of the hypermethylation signals in chromosome 8 was associated with an increase in the hypomethylation signals in the rest of the chromosomes. Chromosome 8 hypermethylation signals were found mainly in the CpG island (CGI) shores and interspersed repeats. Validating the most significant differentially methylated CGI (P = 7.88 × 10(-11)) identified in trisomy 8 AML demonstrated a specific core region within the gene body of HHEX, which was significantly correlated with HHEX expression in both diagnostic and relapse trisomy 8 AMLs. Overall, the existence of extra chromosome 8 was associated with a global impact on the DNA methylation distribution with identification of HHEX gene methylation as a potential diagnostic marker for trisomy 8 AML.

3.
PLoS One ; 7(3): e33213, 2012.
Article in English | MEDLINE | ID: mdl-22479372

ABSTRACT

Methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq) has the potential to identify changes in DNA methylation important in cancer development. In order to understand the role of epigenetic modulation in the development of acute myeloid leukemia (AML) we have applied MeDIP-seq to the DNA of 12 AML patients and 4 normal bone marrows. This analysis revealed leukemia-associated differentially methylated regions that included gene promoters, gene bodies, CpG islands and CpG island shores. Two genes (SPHKAP and DPP6) with significantly methylated promoters were of interest and further analysis of their expression showed them to be repressed in AML. We also demonstrated considerable cytogenetic subtype specificity in the methylomes affecting different genomic features. Significantly distinct patterns of hypomethylation of certain interspersed repeat elements were associated with cytogenetic subtypes. The methylation patterns of members of the SINE family tightly clustered all leukemic patients with an enrichment of Alu repeats with a high CpG density (P<0.0001). We were able to demonstrate significant inverse correlation between intragenic interspersed repeat sequence methylation and gene expression with SINEs showing the strongest inverse correlation (R(2) = 0.7). We conclude that the alterations in DNA methylation that accompany the development of AML affect not only the promoters, but also the non-promoter genomic features, with significant demethylation of certain interspersed repeat DNA elements being associated with AML cytogenetic subtypes. MeDIP-seq data were validated using bisulfite pyrosequencing and the Infinium array.


Subject(s)
DNA Methylation , Genome, Human/genetics , Leukemia, Myeloid/genetics , Short Interspersed Nucleotide Elements/genetics , Acute Disease , Adaptor Proteins, Signal Transducing/genetics , Cell Line, Tumor , Cluster Analysis , CpG Islands/genetics , Dipeptidyl-Peptidases and Tripeptidyl-Peptidases/genetics , Gene Expression Profiling , Gene Expression Regulation, Leukemic , Genome-Wide Association Study/methods , HL-60 Cells , Humans , Inhibitor of Differentiation Proteins/genetics , Nerve Tissue Proteins/genetics , Oligonucleotide Array Sequence Analysis , Potassium Channels/genetics , Promoter Regions, Genetic/genetics , Reverse Transcriptase Polymerase Chain Reaction , Sequence Analysis, DNA/methods
4.
In Silico Biol ; 8(3-4): 363-76, 2008.
Article in English | MEDLINE | ID: mdl-19032168

ABSTRACT

Microarray gene expression datasets are continually being placed in public repositories. As a result, one of the most important emerging challenges is that which enables researchers to take full advantage of such previously accumulated data to discover or validate common genes in similar biological systems. In light of this we have designed the MaXlab software to not only cross-compare available array data from different laboratories but also extract further knowledge from gene expression patterns embedded within published data. More importantly MaXlab offers a flexible and automated solution applicable for microarray technologies including cDNA and Affymetrix gene chips generating expression profiles for common genes with biological significance. We have identified several sets of genes previously unknown to be commonly expressed across studies investigating related biological questions. Among them is the identification of 17 genes involved in the dysregulation of immune tolerance including the crucial transcription factor Egr2. In addition, we have identified 175 genes commonly expressed in basal and luminal breast tumours in response to the chemotherapeutic drug doxorubicin. The universal expression and characterisation of these encouraging genes identified through MaXlab suggests that they may play a common role in the mechanism of disease and hence act as an incentive for further investigation for identifying potential therapeutic targets. Overall, MaXlab is an attractive application for molecular biologists extracting the intersection between microarray datasets together with the gene expression profiles, from which biologists are able to infer further biological insights. The software together with file formats and additional material is freely available at http://www.immuno-software.org.


Subject(s)
Gene Expression Profiling , Oligonucleotide Array Sequence Analysis , Software , Algorithms , Artificial Intelligence , Autoimmune Diseases/genetics , Breast Neoplasms/genetics , Dermatomyositis/genetics , Humans , Immune Tolerance/genetics
5.
Eur J Immunol ; 36(6): 1374-85, 2006 Jun.
Article in English | MEDLINE | ID: mdl-16708405

ABSTRACT

Repetitive antigen stimulation induces peripheral T cell tolerance in vivo. It is not known, however, whether multiple stimulations merely suppress T cell activation or, alternatively, change the transcriptional program to a distinct, tolerant state. In this study, we have discovered that STAT3 and STAT5 were activated in response to antigen stimulation in vivo, in marked contrast to the suppression of AP-1, NF-kappaB and NFAT. In addition, a number of transcription factors were induced in tolerant T cells following antigen challenge in vivo, including T-bet, Irf-1 and Egr-2. The altered transcription program in tolerant cells associates closely with the suppression of cell cycle progression and IL-2 production, as well as with the induction of IL-10. Studies of T-bet and Egr-2 show that the function of T-bet in peptide treatment-induced regulatory T cells is not associated with Th1 differentiation, but correlates with the suppression of IL-2, whereas expression of Egr-2 led to an up-regulation of the cell cycle inhibitors p21(cip1) and p27(kip). Our results demonstrate a balanced transcription program regulated by different transcription factors for T cell activation and/or tolerance during antigen-induced T cell responses. Persistent antigen stimulation can induce T cell tolerance by changing the balance of transcription factors.


Subject(s)
Epitopes, T-Lymphocyte/immunology , T-Lymphocytes, Regulatory/immunology , Transcription, Genetic/immunology , Animals , Cell Cycle/immunology , Cell Nucleus/immunology , Cell Nucleus/metabolism , Cyclin-Dependent Kinase Inhibitor p21/biosynthesis , Cyclin-Dependent Kinase Inhibitor p21/genetics , Cyclin-Dependent Kinase Inhibitor p21/immunology , Cyclin-Dependent Kinase Inhibitor p27/biosynthesis , Cyclin-Dependent Kinase Inhibitor p27/genetics , Cyclin-Dependent Kinase Inhibitor p27/immunology , Early Growth Response Protein 2/biosynthesis , Early Growth Response Protein 2/genetics , Early Growth Response Protein 2/immunology , Gene Expression Profiling , Gene Expression Regulation/immunology , Immune Tolerance/immunology , Interleukin-2/biosynthesis , Interleukin-2/immunology , Lymphocyte Activation/immunology , Mice , Mice, Transgenic , Oligonucleotide Array Sequence Analysis , RNA/chemistry , RNA/genetics , Reverse Transcriptase Polymerase Chain Reaction , Signal Transduction/immunology , T-Box Domain Proteins , Transcription Factors/genetics , Transcription Factors/immunology , Transcription Factors/metabolism , Transfection
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