Transcriptomic analysis reveals sex-specific patterns in the hippocampus in Alzheimer's disease.

Background: The hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer's Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility. Methods: We conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1. Results: The hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44. Conclusion: These findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

The influence of environmental risk factors in the development of ALS in the Mediterranean Island of Cyprus.

Introduction: Amyotrophic lateral sclerosis (ALS) is a devastating, uniformly lethal degenerative disease of motor neurons, presenting with relentlessly progressive muscle atrophy and weakness. The etiology of ALS remains unexplained for over 85% of all cases, suggesting that besides the genetic basis of the disease, various environmental factors are implicated in the pathogenesis of ALS. This study aimed to investigate the contribution of known environmental risk factors of ALS in the Cypriot population. Methods: We conducted a case-control study with a total of 56 ALS cases and 56 healthy gender/age-matched controls of Cypriot nationality. Demographic, lifestyle characteristics, medical conditions, and environmental exposures were collected through the use of a detailed questionnaire. Statistical analyses using the R programming language examined the association between the above environmental factors and ALS. Results: A chi-square test analysis revealed a statistically significant (p = 0.000461) difference in smoking status between the two groups. In addition, univariate logistic regression analysis showed a statistically significant association between ALS cases for head trauma/injury (p = 0.0398) and exposure to chemicals (p = 0.00128), compared to controls. Conclusion: This case-control investigation has shed some light on the epidemiological data of ALS in Cyprus, by identifying environmental determinants of ALS, such as smoking, head trauma, and chemical exposure, in the Cypriot population.

Unraveling the transcriptomic signatures of Parkinson's disease and major depression using single-cell and bulk data.

Background: Motor symptoms are well-characterized in Parkinson's disease (PD). However, non-motor symptoms, such as depression, are commonly observed and can appear up to 10 years before motor features, resulting in one-third of individuals being misdiagnosed with a neuropsychiatric disorder. Thus, identifying diagnostic biomarkers is crucial for accurate PD diagnosis during its prodromal or early stages. Methods: We employed an integrative approach, combining single nucleus RNA and bulk mRNA transcriptomics to perform comparative molecular signatures analysis between PD and major depressive disorder (MDD). We examined 39,834 nuclei from PD (GSE202210) and 32,707 nuclei from MDD (GSE144136) in the dorsolateral prefrontal cortex (dlPFC) of Brodmann area 9. Additionally, we analyzed bulk mRNA peripheral blood samples from PD compared to controls (GSE49126, GSE72267), as well as MDD compared to controls (GSE39653). Results: Our findings show a higher proportion of astrocytes, and oligodendrocyte cells in the dlPFC of individuals with PD vs. MDD. The excitatory to inhibitory neurons (E/I) ratio analysis indicates that MDD has a ratio close to normal 80/20, while PD has a ratio of 62/38, indicating increased inhibition in the dlPFC. Microglia displayed the most pronounced differences in gene expression profiles between the two conditions. In PD, microglia display a pro-inflammatory phenotype, while in MDD, they regulate synaptic transmission through oligodendrocyte-microglia crosstalk. Analysis of bulk mRNA blood samples revealed that the COL5A, MID1, ZNF148, and CD22 genes were highly expressed in PD, whereas the DENR and RNU1G2 genes were highly expressed in MDD. CD22 is involved in B-cell activation and the negative regulation of B-cell receptor signaling. Additionally, CD86, which provides co-stimulatory signals for T-cell activation and survival, was found to be a commonly differentially expressed gene in both conditions. Pathway analysis revealed several immune-related pathways common in both conditions, including the complement and coagulation cascade, and B-cell receptor signaling. Discussion: This study demonstrates that bulk peripheral immune cells play a role in both conditions, but neuroinflammation in the dlPFC specifically manifests in PD as evidenced by the analysis of single nucleus dlPFC datasets. Integrating these two omics levels offers a better understanding of the shared and distinct molecular pathophysiology of PD and MDD in both the periphery and the brain. These findings could lead to potential diagnostic biomarkers, improving accuracy and guiding pharmacological treatments.

Investigating the Dietary Intake Using the CyFFQ Semi-Quantitative Food Frequency Questionnaire in Cypriot Huntington's Disease Patients.

Huntington's disease (HD) is a rare progressive neurodegenerative disease characterised by autosomal dominant inheritance. The past decade saw a growing interest in the associations between the Mediterranean Diet (MD) and HD risk and outcomes. The aim of this case-control study was to assess the dietary intake and habits of Cypriot HD patients, comparing them to gender and age-matched controls, using the Cyprus Food Frequency Questionnaire (CyFFQ) and to assess adherence to the MD by disease outcomes. The method relied on the validated CyFFQ semi-quantitative questionnaire to assess energy, macro- and micronutrient intake over the past year in n = 36 cases and n = 37 controls. The MedDiet Score and the MEDAS score were used to assess adherence to the MD. Patients were grouped based on symptomatology such as movement and cognitive and behavioral impairment. The two-sample Wilcoxon rank-sum (Mann-Whitney) test was used to compare cases vs. controls. Statistically significant results were obtained for energy intake (kcal/day) (median (IQR): 4592 (3376) vs. 2488 (1917); p = 0.002) from cases and controls. Energy intake (kcal/day) (median (IQR): 3751 (1894) vs. 2488 (1917); p = 0.044) was also found to be significantly different between asymptomatic HD patients and controls. Symptomatic patients were also different from controls in terms of energy intake (kcal/day) (median (IQR): 5571 (2907) vs. 2488 (1917); p = 0.001); % energy monounsaturated fatty acids (median (IQR): 13.4 (5.2) vs. 15.5 (5.7); p = 0.0261) and several micronutrients. A significant difference between asymptomatic and symptomatic HD patients was seen in the MedDiet score (median (IQR): 31.1 (6.1) vs. 33.1 (8.1); p = 0.024) and a significant difference was observed between asymptomatic HD patient and controls (median (IQR): 5.5 (3.0) vs. 8.2 (2.0); p = 0.014) in the MEDAS score. This study confirmed previous findings that HD cases have a significantly higher energy intake than controls, revealing differences in macro and micronutrients and adherence to the MD by both patients and controls and by HD symptom severity. These findings are important as they are an effort to guide nutritional education within this population group and further understand diet-disease associations.

Integrated Bioinformatics Analysis of Shared Genes, miRNA, Biological Pathways and Their Potential Role as Therapeutic Targets in Huntington's Disease Stages.

Huntington's Disease (HD) is a progressive neurodegenerative disease caused by CAG repeat expansion in the huntingtin gene (HTT). The HTT gene was the first disease-associated gene mapped to a chromosome, but the pathophysiological mechanisms, genes, proteins or miRNAs involved in HD remain poorly understood. Systems bioinformatics approaches can divulge the synergistic relationships of multiple omics data and their integration, and thus provide a holistic approach to understanding diseases. The purpose of this study was to identify the differentially expressed genes (DEGs), HD-related gene targets, pathways and miRNAs in HD and, more specifically, between the pre-symptomatic and symptomatic HD stages. Three publicly available HD datasets were analysed to obtain DEGs for each HD stage from each dataset. In addition, three databases were used to obtain HD-related gene targets. The shared gene targets between the three public databases were compared, and clustering analysis was performed on the common shared genes. Enrichment analysis was performed on (i) DEGs identified for each HD stage in each dataset, (ii) gene targets from the public databases and (iii) the clustering analysis results. Furthermore, the hub genes shared between the public databases and the HD DEGs were identified, and topological network parameters were applied. Identification of HD-related miRNAs and their gene targets was obtained, and a miRNA-gene network was constructed. Enriched pathways identified for the 128 common genes revealed pathways linked to multiple neurodegeneration diseases (HD, Parkinson's disease, Spinocerebellar ataxia), MAPK and HIF-1 signalling pathways. Eighteen HD-related hub genes were identified based on network topological analysis of MCC, degree and closeness. The highest-ranked genes were FoxO3 and CASP3, CASP3 and MAP2 were found for betweenness and eccentricity and CREBBP and PPARGC1A were identified for the clustering coefficient. The miRNA-gene network identified eleven miRNAs (mir-19a-3p, mir-34b-3p, mir-128-5p, mir-196a-5p, mir-34a-5p, mir-338-3p, mir-23a-3p and mir-214-3p) and eight genes (ITPR1, CASP3, GRIN2A, FoxO3, TGM2, CREBBP, MTHFR and PPARGC1A). Our work revealed that various biological pathways seem to be involved in HD either during the pre-symptomatic or symptomatic stages of HD. This may offer some clues for the molecular mechanisms, pathways and cellular components underlying HD and how these may act as potential therapeutic targets for HD.

Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts' curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease.

Investigating the Transition of Pre-Symptomatic to Symptomatic Huntington's Disease Status Based on Omics Data.

Huntington's disease is a rare neurodegenerative disease caused by a cytosine-adenine-guanine (CAG) trinucleotide expansion in the Huntingtin (HTT) gene. Although Huntington's disease (HD) is well studied, the pathophysiological mechanisms, genes and metabolites involved in HD remain poorly understood. Systems bioinformatics can reveal synergistic relationships among different omics levels and enables the integration of biological data. It allows for the overall understanding of biological mechanisms, pathways, genes and metabolites involved in HD. The purpose of this study was to identify the differentially expressed genes (DEGs), pathways and metabolites as well as observe how these biological terms differ between the pre-symptomatic and symptomatic HD stages. A publicly available dataset from the Gene Expression Omnibus (GEO) was analyzed to obtain the DEGs for each HD stage, and gene co-expression networks were obtained for each HD stage. Network rewiring, highlights the nodes that change most their connectivity with their neighbors and infers their possible implication in the transition between different states. The CACNA1I gene was the mostly highly rewired node among pre-symptomatic and symptomatic HD network. Furthermore, we identified AF198444 to be common between the rewired genes and DEGs of symptomatic HD. CNTN6, DEK, LTN1, MST4, ZFYVE16, CEP135, DCAKD, MAP4K3, NUPL1 and RBM15 between the DEGs of pre-symptomatic and DEGs of symptomatic HD and CACNA1I, DNAJB14, EPS8L3, HSDL2, SNRPD3, SOX12, ACLY, ATF2, BAG5, ERBB4, FOCAD, GRAMD1C, LIN7C, MIR22, MTHFR, NABP1, NRG2, OTC, PRAMEF12, SLC30A10, STAG2 and Y16709 between the rewired genes and DEGs of pre-symptomatic HD. The proteins encoded by these genes are involved in various biological pathways such as phosphatidylinositol-4,5-bisphosphate 3-kinase activity, cAMP response element-binding protein binding, protein tyrosine kinase activity, voltage-gated calcium channel activity, ubiquitin protein ligase activity, adenosine triphosphate (ATP) binding, and protein serine/threonine kinase. Additionally, prominent molecular pathways for each HD stage were then obtained, and metabolites related to each pathway for both disease stages were identified. The transforming growth factor beta (TGF-ß) signaling (pre-symptomatic and symptomatic stages of the disease), calcium (Ca2+) signaling (pre-symptomatic), dopaminergic synapse pathway (symptomatic HD patients) and Hippo signaling (pre-symptomatic) pathways were identified. The in silico metabolites we identified include Ca2+, inositol 1,4,5-trisphosphate, sphingosine 1-phosphate, dopamine, homovanillate and L-tyrosine. The genes, pathways and metabolites identified for each HD stage can provide a better understanding of the mechanisms that become altered in each disease stage. Our results can guide the development of therapies that may target the altered genes and metabolites of the perturbed pathways, leading to an improvement in clinical symptoms and hopefully a delay in the age of onset.

Dietary Intake, Mediterranean Diet Adherence and Caloric Intake in Huntington's Disease: A Review.

Decades of research and experimental studies have investigated Huntington's disease (HD), a rare neurodegenerative disease. Similarly, several studies have investigated whether high/moderate adherence to the Mediterranean Diet and specific macro and micronutrients can decrease cognitive loss and provide a neuroprotective function to neurons. This review systematically identifies and examines studies that have investigated Mediterranean Diet adherence, micro- and macronutrients, supplementation and caloric intake in people with HD, in order to identify if dietary exposures resulted in improvement of disease symptoms, a delay in age of onset or if they contributed to an earlier age of onset in people with HD. A systematic search of PubMed, Directory of open access journal and HubMed was performed independently by two reviewers using specific search terms criteria for studies. The identified abstracts were screened and the studies were included in the review if they satisfied predetermined inclusion criteria. Reference screening of included studies was also performed. A total of 18 studies were included in the review. A few studies found that patients who had high/moderate adherence to Mediterranean Diet showed a slight improvement in their Unified Huntington's Disease Rating Scale and Total Functional Capacity. In addition, people with HD who had high Mediterranean Diet adherence showed an improvement in both cognitive and motor scores and had a better quality of life compared to patients who had low Mediterranean Diet adherence. Furthermore, a few studies showed that supplementation with specific nutrients, such as triheaptanoin, L-acetyl-carnitine and creatine, had no beneficial effect on the patients' Unified Huntington's Disease Rating Scale score. A few studies suggest that the Mediterranean Diet may confer a motor and cognitive benefit to people with HD. Unfortunately, there was little consistency among study findings. It is important for more research to be conducted to have a better understanding of which dietary exposures are beneficial and may result delaying age of onset or disease progression in people with HD.

Revealing Clusters of Connected Pathways Through Multisource Data Integration in Huntington's Disease and Spastic Ataxia.

The advancement of scientific and medical research over the past years has generated a wealth of experimental data from multiple technologies, including genomics, transcriptomics, proteomics, and other forms of -omics data, which are available for a number of diseases. The integration of such multisource data is a key component toward the success of precision medicine. In this paper, we are investigating a multisource data integration method developed by our group, regarding its ability to drive to clusters of connected pathways under two different approaches: first, a disease-centric approach, where we integrate data around a disease, and second, a gene-centric approach, where we integrate data around a gene. We have used as a paradigm for the first approach Huntington's disease (HD), a disease with a plethora of available data, whereas for the second approach the GBA2, a gene that is related to spastic ataxia (SA), a phenotype with sparse availability of data. Our paper shows that valuable information at the level of disease-related pathway clusters can be obtained for both HD and SA. New pathways that classical pathway analysis methods were unable to reveal, emerged as necessary "connectors" to build connected pathway stories formed as pathway clusters. The capability to integrate multisource molecular data, concluding to something more than the sum of the existing information, empowers precision and personalized medicine approaches.