Transcriptomic and Genetic Associations between Alzheimer's Disease, Parkinson's Disease, and Cancer

Monoamine oxidase B inhibits epithelial-mesenchymal transition and trigger apoptosis via targeting ERK1/2 signaling pathway in head and neck squamous cell carcinoma

BACKGROUND

Monoamine oxidase B (MAOB), a flavin monoamine oxidase, regulates biogenic and xenobiotic amine oxidative deaminization. We demonstrate MAOB expression in head and neck epithelium and its biological importance in head and neck squamous cell carcinoma (HNSCC) development.

METHODS

First, we found a possible MAOB downregulation in HNSCC using bioinformatic analysis. Second, we validated MAOB expression changes in vitro and assessed its tumorigenicity in HNSCC. Finally, preclinical xenograft models further confirmed our findings.

RESULTS

Results proved that MAOB was significantly reduced in HNSCC tissues and cell lines. By comparing MAOB localization in patient specimens, we found that epithelial basal cells express MAOB and that it changes throughout HNSCC development. We observed that MAOB overexpression inhibited HNSCC cell malignancy via lentiviral transfection. We additionally discovered that selegiline partly counter-regulated MAOB overexpression-induced phenotypes in HNSCC cells.

CONCLUSIONS

We found that MAOB is a potent biomarker and a unique and essential indication of HNSCC carcinogenesis.

Natural resistance to cancer: A window of hope

As healthcare systems are improving and thereby the life expectancy of human populations is increasing, cancer is representing itself as the second leading cause of death. Although cancer biologists have put enormous effort on cancer research so far, we still have a long way to go before being able to treat cancers efficiently. One interesting approach in cancer biology is to learn from natural resistance and/or predisposition to cancer. Cancer-resistant species and tissues are thought-provoking models whose study shed light on the inherent cancer resistance mechanisms that arose during the course of evolution. On the other hand, there are some syndromes and factors that increase the risk of cancer development, and revealing their underlying mechanisms will increase our knowledge about the process of cancer formation. Here, we review natural resistance and predisposition to cancer and the known mechanisms at play. Further insights from these natural phenomena will help design future cancer research and could ultimately lead to the development of novel cancer therapeutic strategies.

Alzheimer's Disease and Different Types of Cancer Likelihood: Unveiling Disparities and Potential Protective Effects in a Korean Cohort Study

The link between Alzheimer's disease and cancer risk is a concern in public health. However, research has yielded limited and sometimes contrasting results, suggesting the need for more validation. We analyzed a large cohort to examine the long-term association between Alzheimer's disease (AD) and the risk of developing cancer. In total, 24,664 AD patients and 98,656 control participants were selected from the National Health Insurance Cohort database of Korea, spanning from 2002 to 2019. Propensity score matching and overlap-weighted adjustment techniques were used to balance the standardized differences between the AD and control groups. The Cox proportional hazards model was applied to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for various cancers, considering relevant covariates. Results indicated that patients with AD had a significantly lower likelihood of overall malignancy (HR 0.63; 95% CI, 0.59-0.68) and each of the 10 site-specific cancers compared to the control group. Among these, pancreatic cancer (HR, 0.50) exhibited the strongest inverse association, followed by hepatic (HR, 0.60), gastric (HR, 0.63), kidney (HR, 0.63), lung (HR, 0.64), thyroid (HR, 0.65), colorectal (HR, 0.67), gallbladder and biliary duct (HR, 0.73), hematologic malignancy (HR, 0.73), and bladder cancers (HR, 0.76). This protective effect against certain organ-specific cancers persisted over the 16-year follow-up period, except for in kidney cancer and hematologic malignancies. The protective effect against specific cancer types (gastric, colorectal, lung, hepatic, and pancreatic) was more prominent in individuals aged 60 years and older, regardless of their sex. However, there were some variations in the specific types of cancer observed between males and females. In summary, Korean patients with AD had a lower risk of cancer, especially in individuals 60 years and older, during the 16-year follow-up period.

Longitudinal study of the inverse relationship between Parkinson's disease and cancer in Korea

Despite growing epidemiological evidence, the relationship between Parkinson's disease (PD) and cancer has not been conclusively demonstrated, and related studies are scarce in the Asian population. We aimed to determine the association between PD and subsequent development of various cancers from longitudinal data of a representative sample of Korean adults aged ≥40 years. We retrospectively identified 8381 patients diagnosed with PD from 2002 to 2019 using claims data among 514,866 people of random samples from the Korean National Health Insurance database. We sampled 33,524 age-, sex-, income-, and residential area-matched participants without PD from the same database. The longitudinal associations between PD and overall cancer, as well as 10 common types of cancer, were estimated using multivariable Cox proportional-hazards regression analysis. The adjusted hazard ratio (aHR) of all cancer types was 0.63 (95% confidence interval = 0.57-0.69) in patients with PD compared with matched controls. The aHRs of gastric, thyroid, colorectal, lung, hepatic, and pancreatic cancer and hematological malignancy were 0.69 (0.56-0.85), 0.60 (0.39-0.93), 0.56 (0.44-0.70), 0.71 (0.58-0.84), 0.64 (0.48-0.86), 0.37 (0.23-0.60), and 0.56 (0.36-0.87), respectively. The associations of bladder, gallbladder and biliary duct, and kidney cancer with PD were not statistically significant. Our findings show inverse associations between overall cancer and most cancer types in patients with PD. These inverse associations and their pathogeneses merit further investigation.

Apoptosis Genes as a Key to Identification of Inverse Comorbidity of Huntington's Disease and Cancer

Cancer and neurodegenerative disorders present overwhelming challenges for healthcare worldwide. Epidemiological studies showed a decrease in cancer rates in patients with neurodegenerative disorders, including the Huntington disease (HD). Apoptosis is one of the most important processes for both cancer and neurodegeneration. We suggest that genes closely connected with apoptosis and associated with HD may affect carcinogenesis. We applied reconstruction and analysis of gene networks associated with HD and apoptosis and identified potentially important genes for inverse comorbidity of cancer and HD. The top 10 high-priority candidate genes included APOE, PSEN1, INS, IL6, SQSTM1, SP1, HTT, LEP, HSPA4, and BDNF. Functional analysis of these genes was carried out using gene ontology and KEGG pathways. By exploring genome-wide association study results, we identified genes associated with neurodegenerative and oncological disorders, as well as their endophenotypes and risk factors. We used publicly available datasets of HD and breast and prostate cancers to analyze the expression of the identified genes. Functional modules of these genes were characterized according to disease-specific tissues. This integrative approach revealed that these genes predominantly exert similar functions in different tissues. Apoptosis along with lipid metabolism dysregulation and cell homeostasis maintenance in the response to environmental stimulus and drugs are likely key processes in inverse comorbidity of cancer in patients with HD. Overall, the identified genes represent the promising targets for studying molecular relations of cancer and HD.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

BACKGROUND

Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties.

OBJECTIVE

We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors.

METHODS

We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses.

RESULTS

We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31).

CONCLUSIONS

We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Metabolomic analysis of vascular cognitive impairment due to hepatocellular carcinoma

Introduction

Screening for metabolically relevant differentially expressed genes (DEGs) shared by hepatocellular carcinoma (HCC) and vascular cognitive impairment (VCI) to explore the possible mechanisms of HCC-induced VCI.

Methods

Based on metabolomic and gene expression data for HCC and VCI, 14 genes were identified as being associated with changes in HCC metabolites, and 71 genes were associated with changes in VCI metabolites. Multi-omics analysis was used to screen 360 DEGs associated with HCC metabolism and 63 DEGs associated with VCI metabolism.

Results

According to the Cancer Genome Atlas (TCGA) database, 882 HCC-associated DEGs were identified and 343 VCI-associated DEGs were identified. Eight genes were found at the intersection of these two gene sets: NNMT, PHGDH, NR1I2, CYP2J2, PON1, APOC2, CCL2, and SOCS3. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. The HCC metabolomics prognostic model was constructed and proved to have a good prognostic effect. Following principal component analyses (PCA), functional enrichment analyses, immune function analyses, and TMB analyses, these eight DEGs were identified as possibly affecting HCC-induced VCI and the immune microenvironment. As well as gene expression and gene set enrichment analyses (GSEA), a potential drug screen was conducted to investigate the possible mechanisms involved in HCC-induced VCI. The drug screening revealed the potential clinical efficacy of A-443654, A-770041, AP-24534, BI-2536, BMS- 509744, CGP-60474, and CGP-082996.

Conclusion

HCC-associated metabolic DEGs may influence the development of VCI in HCC patients.

Parkinson's Disease, Parkinsonisms, and Mitochondria: the Role of Nuclear and Mitochondrial DNA

PURPOSE OF REVIEW

Overwhelming evidence indicates that mitochondrial dysfunction is a central factor in Parkinson's disease (PD) pathophysiology. This paper aims to review the latest literature published, focusing on genetic defects and expression alterations affecting mitochondria-associated genes, in support of their key role in PD pathogenesis.

RECENT FINDINGS

Thanks to the use of new omics approaches, a growing number of studies are discovering alterations affecting genes with mitochondrial functions in patients with PD and parkinsonisms. These genetic alterations include pathogenic single-nucleotide variants, polymorphisms acting as risk factors, and transcriptome modifications, affecting both nuclear and mitochondrial genes. We will focus on alterations of mitochondria-associated genes described by studies conducted on patients or on animal/cellular models of PD or parkinsonisms. We will comment how these findings can be taken into consideration for improving the diagnostic procedures or for deepening our knowledge on the role of mitochondrial dysfunctions in PD.

Neurotherapeutic Effects of Quercetin and Its Metabolite Compounds on Cognitive Impairment and Parkinson's Disease: An In Silico Study

BACKGROUND AND OBJECTIVE

Little is known about the metabolomic profile of quercetin and its biological effects. This study aimed to determine the biological activities of quercetin and its metabolite products, as well as the molecular mechanisms of quercetin in cognitive impairment (CI) and Parkinson's disease (PD).

METHODS

Key methods used were MetaTox, PASS Online, ADMETlab 2.0, SwissADME, CTD MicroRNA MIENTURNE, AutoDock, and Cytoscape.

RESULTS

A total of 28 quercetin metabolite compounds were identified by phase I reactions (hydroxylation and hydrogenation reactions) and phase II reactions (methylation, O-glucuronidation, and O-sulfation reactions). Quercetin and its metabolites were found to inhibit cytochrome P450 (CYP) 1A, CYP1A1, and CYP1A2. The studied compounds demonstrated significant gastrointestinal absorption and satisfied Lipinsky's criterion. Due to their high blood-brain barrier permeability, P-glycoprotein inhibition, anticancer, anti-inflammatory, and antioxidant capabilities, quercetin and its metabolite products have been proposed as promising molecular targets for the therapy of CI and PD. By regulating the expression of crucial signaling pathways [mitogen-activated protein kinase (MAPK) signaling pathway, and neuroinflammation and glutamatergic signaling], genes [brain derived neurotrophic factor (BDNF), human insulin gene (INS), and dopamine receptor D2 (DRD2), miRNAs (hsa-miR-16-5p, hsa-miR-26b-5p, hsa-miR-30a-5p, hsa-miR-125b-5p, hsa-miR-203a-3p, and hsa-miR-335-5p], and transcription factors [specificity protein 1 (SP1), v-rel avian reticuloendotheliosis viral oncogene homolog A (RELA), and nuclear factor Kappa B subunit 1 (NFKB1)], quercetin exhibited its neurotherapeutic effects in CI and PD. In addition to inhibiting β-N-acetylhexosaminidase, quercetin also showed robust interactions and binding affinities with heme oxygenase 1 (HMOX1), superoxide dismutase 2 (SOD2), tumor necrosis factor (TNF), nitric oxide synthase 2 (NOS2), brain-derived neurotrophic factor (BDNF), INS, DRD2, and γ-aminobutyric acid type A (GABAa).

CONCLUSION

This study identified 28 quercetin metabolite products. The metabolites have similar characteristics to quercetin such as physicochemical properties, absorption, distribution, metabolism, and excretion (ADME), and biological activities. More research, especially clinical trials, is needed to find out how quercetin and its metabolites protect against CI and PD.

Genetic outline of the hermeneutics of the diseases connection phenomenon in human

The structure of diseases in humans is heterogeneous, which is manifested by various combinations of diseases, including comorbidities associated with a common pathogenetic mechanism, as well as diseases that rarely manifest together. Recently, there has been a growing interest in studying the patterns of development of not individual diseases, but entire families associated with common pathogenetic mechanisms and common genes involved in their development. Studies of this problem make it possible to isolate an essential genetic component that controls the formation of disease conglomerates in a complex way through functionally interacting modules of individual genes in gene networks. An analytical review of studies on the problems of various aspects of the combination of diseases is the purpose of this study. The review uses the metaphor of a hermeneutic circle to understand the structure of regular relationships between diseases, and provides a conceptual framework related to the study of multiple diseases in an individual. The existing terminology is considered in relation to them, including multimorbidity, polypathies, comorbidity, conglomerates, families, "second diseases", syntropy and others. Here we summarize the key results that are extremely useful, primarily for describing the genetic architecture of diseases of a multifactorial nature. Summaries of the research problem of the disease connection phenomenon allow us to approach the systematization and natural classification of diseases. From practical healthcare perspective, the description of the disease connection phenomenon is crucial for expanding the clinician's interpretive horizon and moving beyond narrow, disease-specific therapeutic decisions.

Role and Dysregulation of miRNA in Patients with Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative synucleinopathy that has a not yet fully understood molecular pathomechanism behind it. The role of risk genes regulated by small non-coding RNAs, or microRNAs (miRNAs), has also been highlighted in PD, where they may influence disease progression and comorbidities. In this case-control study, we analyzed miRNAs on peripheral blood mononuclear cells by means of RNA-seq in 30 participants, with the aim of identifying miRNAs differentially expressed in PD compared to age-matched healthy controls. Additionally, we investigated the pathways influenced by differentially expressed miRNAs and assessed whether a specific pathway could potentially be associated with PD susceptibility (enrichment analyses performed using the Ingenuity Pathway Analysis tools). Overall, considering that the upregulation of miRNAs might be related with the downregulation of their messenger RNA targets, and vice versa, we found several putative targets of dysregulated miRNAs (i.e., upregulated: hsa-miR-1275, hsa-miR-23a-5p, hsa-miR-432-5p, hsa-miR-4433b-3p, and hsa-miR-4443; downregulated: hsa-miR-142-5p, hsa-miR-143-3p, hsa-miR-374a-3p, hsa-miR-542-3p, and hsa-miR-99a-5p). An inverse connection between cancer and neurodegeneration, called "inverse comorbidity", has also been noted, showing that some genes or miRNAs may be expressed oppositely in neurodegenerative disorders and in some cancers. Therefore, it may be reasonable to consider these miRNAs as potential diagnostic markers and outcome measures.

Autoencoder Networks Decipher the Association between Lung Cancer and Alzheimer’s Disease

Lung cancer is the most common malignancy and is responsible for the largest cancer-related mortality worldwide. Alzheimer’s disease is a degenerative neurological disease that burdens healthcare worldwide. While the two diseases are distinct, several transcriptomic studies have demonstrated they are linked. However, no concordant conclusion on how they are associated has been drawn. Since these studies utilized conventional bioinformatics methods, such as the differentially expressed gene (DEG) analysis, it is naturally expected that the proportion of DEGs having either the same or inverse directions in lung cancer and Alzheimer’s disease is substantial. This raises the inconsistency. Therefore, a novel bioinformatics method capable of determining the direction of association is desirable. In this study, the moderated t-tests were first used to identify DEGs that are shared by the two diseases. For the shared DEGs, separate autoencoder (AE) networks were trained to extract a one-dimensional representation (pseudogene) for each disease. Based on these pseudogenes, the association direction between lung cancer and Alzheimer’s disease was inferred. AE networks based on 266 shared DEGs revealed a comorbidity relationship between Alzheimer’s disease and lung cancer. Specifically, Spearman’s correlation coefficient between the predicted values using the two AE networks for the Alzheimer’s disease test set was 0.825 and for the lung cancer test set was 0.316. Novel bioinformatics methods such as an AE network may help decipher how distinct diseases are associated by providing the refined representations of dysregulated genes.

Deciphering the molecular mechanism and crosstalk between Parkinson's disease and breast cancer through multi-omics and drug repurposing approach

Epidemiological studies indicate a higher occurrence of breast cancer (BRCA) in patients with Parkinson's disease. However, the exact molecular mechanism is still not precise. Herein, we tested the hypothesis that this inverse comorbidity result from shared genetic and molecular processes. We conducted an integrated omics analysis to identify the common gene signatures associated with PD and BRCA. Secondly, several dysregulated biological processes in both indications were analyzed by functional enrichment methods, and significant overlapping processes were identified. To establish common regulatory mechanisms, information about transcription factors and miRNAs associated with both the disorders was extracted. Finally, disease-specific gene expression signatures were compared through LINCS L1000 analysis to identify potential repurposing drugs for PD. The potential repurposed drug candidates were then correlated with PD-specific gene signatures by Cmap analysis. In conclusion, this study highlights the shared genes, biological pathways and regulatory signatures associated with PD and BRCA with an improved understanding of crosstalk involved. Additionally, the role of therapeutics was investigated in context with their comorbid associations. These findings could help to explain the complex molecular patterns of associations between PD and BRCA.

The Crosstalk between HepG2 and HMC-III Cells: In Vitro Modulation of Gene Expression with Conditioned Media

Epidemiological studies have postulated an inverse correlation between developing cancer and neurodegeneration. It is known that the secretome plays a vital role in cell-cell communication in health and disease; the microglia is the resident macrophage of the central nervous system which maintains neuronal integrity by adapting as the microenvironment changes. The present study aimed to identify, in a cell model, biomarkers that link neurodegenerative diseases to cancer or vice versa. Real-time PCR and western blot analysis were used to characterize the effects on gene and protein expression of human hepatoblastoma (HepG2) and human microglia (HMC-III) cells after exchanging part of their conditioned medium. Biomarkers of the endoplasmic reticulum, and mitophagy and inflammatory processes were evaluated. In both cell types, we observed the activation of cytoprotective mechanisms against any potential pro-oxidant or pro-inflammatory signals present in secretomes. In contrast, HepG2 but not HMC-III cells seem to trigger autophagic processes following treatment with conditioned medium of microglia, thus suggesting a cell-specific adaptive response.

Differential Neuropathology, Genetics, and Transcriptomics in Two Kindred Cases with Alzheimer’s Disease and Lewy Body Dementia

Alzheimer’s disease (AD) and Lewy body dementia (LBD) are two different forms of dementia, but their pathology may involve the same cortical areas with overlapping cognitive manifestations. Nonetheless, the clinical phenotype is different due to the topography of the lesions driven by the different underlying molecular processes that arise apart from genetics, causing diverse neurodegeneration. Here, we define the commonalities and differences in the pathological processes of dementia in two kindred cases, a mother and a son, who developed classical AD and an aggressive form of AD/LBD, respectively, through a neuropathological, genetic (next-generation sequencing), and transcriptomic (RNA-seq) comparison of four different brain areas. A genetic analysis did not reveal any pathogenic variants in the principal AD/LBD-causative genes. RNA sequencing highlighted high transcriptional dysregulation within the substantia nigra in the AD/LBD case, while the AD case showed lower transcriptional dysregulation, with the parietal lobe being the most involved brain area. The hippocampus (the most degenerated area) and basal ganglia (lacking specific lesions) expressed the lowest level of dysregulation. Our data suggest that there is a link between transcriptional dysregulation and the amount of tissue damage accumulated across time, assessed through neuropathology. Moreover, we highlight that the molecular bases of AD and LBD follow very different pathways, which underlie their neuropathological signatures. Indeed, the transcriptome profiling through RNA sequencing may be an important tool in flanking the neuropathological analysis for a deeper understanding of AD and LBD pathogenesis.

Examples of Inverse Comorbidity between Cancer and Neurodegenerative Diseases: A Possible Role for Noncoding RNA

Cancer is one of the most common causes of death; in parallel, the incidence and prevalence of central nervous system diseases are equally high. Among neurodegenerative diseases, Alzheimer’s dementia is the most common, while Parkinson’s disease (PD) is the second most frequent neurodegenerative disease. There is a significant amount of evidence on the complex biological connection between cancer and neurodegeneration. Noncoding RNAs (ncRNAs) are defined as transcribed nucleotides that perform a variety of regulatory functions. The mechanisms by which ncRNAs exert their functions are numerous and involve every aspect of cellular life. The same ncRNA can act in multiple ways, leading to different outcomes; in fact, a single ncRNA can participate in the pathogenesis of more than one disease—even if these seem very different, as cancer and neurodegenerative disorders are. The ncRNA activates specific pathways leading to one or the other clinical phenotype, sometimes with obvious mechanisms of inverse comorbidity. We aimed to collect from the existing literature examples of inverse comorbidity in which ncRNAs seem to play a key role. We also investigated the example of mir-519a-3p, and one of its target genes Poly (ADP-ribose) polymerase 1, for the inverse comorbidity mechanism between some cancers and PD. We believe it is very important to study the inverse comorbidity relationship between cancer and neurodegenerative diseases because it will help us to better assess these two major areas of human disease.

Cancer History Is Associated with Slower Speed of Cognitive Decline in Patients with Amnestic Cognitive Impairment

Background: Several epidemiological studies report a negative association between Cancer and Alzheimer’s disease (AD). Objective: To characterize the trajectories of memory loss in individuals with early amnestic cognitive impairment with and without history of previous cancer. Methods: Cognitive deterioration was assessed using the Montreal Cognitive Assessment (MoCA) or MoCA-Memory Index Score (MoCA-MIS) biannually in subjects with early amnestic cognitive impairment followed-up retrospectively from 2007 to 2021. History of Cancer was obtained from clinical records. Simple linear regressions of MoCA-MIS scores were calculated for each subject and analyzed with K-means cluster analysis to identify subgroups with different cognitive decline trajectories. χ 2 and t tests were used for descriptive categorical and continuous variables and mixed multiple linear regressions to determine cognitive decline covariates. Results: Analysis of the trajectory of cognitive decline in 141 subjects with early amnestic cognitive impairment identified two subgroups: Fast (n = 60) and Slow (n = 81) progressors. At baseline Fast progressors had better MoCA-MIS (p <  0.001) and functionality (CDR p = 0.02, AD8 p = 0.05), took less anti-dementia medications (p = 0.005), and had higher depression rates (p = 0.02). Interestingly, Fast progressors slowed their speed of memory decline (from 1.6 to 1.1 MoCA-MIS points/year) and global cognitive decline (from 2.0 to 1.4 total MoCA points/year) when Cancer history was present. Conclusion: Two trajectories of amnestic cognitive decline were identified, possibly derived from different neurophysiopathologies or clinical stages. This study suggests that a history of previous Cancer slows down amnestic cognitive decline, specifically in a subgroup of subjects with depression at baseline and accelerated deterioration at follow-up.

Identification of Novel Molecular Therapeutic Targets and Their Potential Prognostic Biomarkers Based on Cytolytic Activity in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) attracts attention worldwide for its extremely high malignancy. A novel term cytolytic activity (CYT) has been introduced as a potential immunotherapy biomarker associated with counter-regulatory immune responses and enhanced prognosis in tumors. In this study, we extracted all datasets of SKCM patients, namely, RNA sequencing data and clinical information from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database, conducted differential expression analysis to yield 864 differentially expressed genes (DEGs) characteristic of CYT and used non-negative matrix factorization (NMF) method to classify molecular subtypes of SKCM patients. Among all genes, 14 hub genes closely related to prognosis for SKCM were finally screen out. Based on these genes, we constructed a 14-gene prognostic risk model and its robustness and strong predictive performance were further validated. Subsequently, the underlying mechanisms in tumor pathogenesis and prognosis have been defined from a number of perspectives, namely, tumor mutation burden (TMB), copy number variation (CNV), tumor microenvironment (TME), infiltrating immune cells, gene set enrichment analysis (GSEA) and immune checkpoint inhibitors (ICIs). Furthermore, combined with GTEx database and HPA database, the expression of genes in the model was verified at the transcriptional level and protein level, and the relative importance of genes in the model was described by random forest algorithm. In addition, the model was used to predict the difference in sensitivity of SKCM patients to chemotherapy and immunotherapy. Finally, a nomogram was constructed to better aid clinical diagnosis.

Multiomics Topic Modeling for Breast Cancer Classification

The integration of transcriptional data with other layers of information, such as the post-transcriptional regulation mediated by microRNAs, can be crucial to identify the driver genes and the subtypes of complex and heterogeneous diseases such as cancer. This paper presents an approach based on topic modeling to accomplish this integration task. More specifically, we show how an algorithm based on a hierarchical version of stochastic block modeling can be naturally extended to integrate any combination of 'omics data. We test this approach on breast cancer samples from the TCGA database, integrating data on messenger RNA, microRNAs, and copy number variations. We show that the inclusion of the microRNA layer significantly improves the accuracy of subtype classification. Moreover, some of the hidden structures or "topics" that the algorithm extracts actually correspond to genes and microRNAs involved in breast cancer development and are associated to the survival probability.

Associations of ARHGAP26 Polymorphisms with Alzheimer's Disease and Cardiovascular Disease

The Rho GTPase activating protein 26 (ARHGAP26) gene has been reported to be associated with neuropsychiatric diseases and neurodegenerative diseases including Parkinson's disease. We examined whether the ARHGAP26 gene is associated with Alzheimer's disease (AD) and/or cardiovascular disease (CVD). Multivariable logistic regression model was used to examine the associations of 154 single nucleotide polymorphisms (SNPs) within the ARHGAP26 gene with AD and CVD using the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) cohort. Fourteen SNPs were associated with AD (top SNP rs3776362 with p = 3.43 × 10^-3), while 37 SNPs revealed associations with CVD (top SNP rs415235 with p = 2.06 × 10^-4). Interestingly, 13 SNPs were associated with both AD and CVD. SNP rs3776362 was associated with CVD, Functional Activities Questionnaire (FAQ), and Clinical Dementia Rating Sum of Boxes (CDR-SB). A replication study using a Caribbean Hispanics sample showed that 17 SNPs revealed associations with AD, and 12 SNPs were associated with CVD. The third sample using a family-based study design showed that 9 SNPs were associated with AD, and 3 SNPs were associated with CVD. SNP rs6836509 within the ARHGAP10 gene (an important paralogon of ARHGAP26) was associated with AD and cerebrospinal fluid total tau (t-tau) level in the ADNI sample. Several SNPs were functionally important using the RegulomeDB, while a number of SNPs were associated with significant expression quantitative trait loci (eQTLs) using Genotype-Tissue Expression (GTEx) databases. In conclusion, genetic variants within ARHGAP26 were associated with AD and CVD. These findings add important new insights into the potentially shared pathogenesis of AD and CVD.

A Transcriptome Analysis of mRNAs and Long Non-Coding RNAs in Patients with Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder. The number of cases of PD is expected to double by 2030, representing a heavy burden on the healthcare system. Clinical symptoms include the progressive loss of dopaminergic neurons in the substantia nigra of the midbrain, which leads to striatal dopamine deficiency and, subsequently, causes motor dysfunction. Certainly, the study of the transcriptome of the various RNAs plays a crucial role in the study of this neurodegenerative disease. In fact, the aim of this study was to evaluate the transcriptome in a cohort of subjects with PD compared with a control cohort. In particular we focused on mRNAs and long non-coding RNAs (lncRNA), using the Illumina NextSeq 550 DX System. Differential expression analysis revealed 716 transcripts with padj ≤ 0.05; among these, 630 were mRNA (coding protein), lncRNA, and MT_tRNA. Ingenuity pathway analysis (IPA, Qiagen) was used to perform the functional and pathway analysis. The highest statistically significant pathways were: IL-15 signaling, B cell receptor signaling, systemic lupus erythematosus in B cell signaling pathway, communication between innate and adaptive immune cells, and melatonin degradation II. Our findings further reinforce the important roles of mitochondria and lncRNA in PD and, in parallel, further support the concept of inverse comorbidity between PD and some cancers.

A Transcriptome Analysis of mRNAs and Long Non-Coding RNAs in Patients with Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder. The number of cases of PD is expected to double by 2030, representing a heavy burden on the healthcare system. Clinical symptoms include the progressive loss of dopaminergic neurons in the substantia nigra of the midbrain, which leads to striatal dopamine deficiency and, subsequently, causes motor dysfunction. Certainly, the study of the transcriptome of the various RNAs plays a crucial role in the study of this neurodegenerative disease. In fact, the aim of this study was to evaluate the transcriptome in a cohort of subjects with PD compared with a control cohort. In particular we focused on mRNAs and long non-coding RNAs (lncRNA), using the Illumina NextSeq 550 DX System. Differential expression analysis revealed 716 transcripts with padj ≤ 0.05; among these, 630 were mRNA (coding protein), lncRNA, and MT_tRNA. Ingenuity pathway analysis (IPA, Qiagen) was used to perform the functional and pathway analysis. The highest statistically significant pathways were: IL-15 signaling, B cell receptor signaling, systemic lupus erythematosus in B cell signaling pathway, communication between innate and adaptive immune cells, and melatonin degradation II. Our findings further reinforce the important roles of mitochondria and lncRNA in PD and, in parallel, further support the concept of inverse comorbidity between PD and some cancers.

A study of gene expression by RNA-seq in patients with prostate cancer and in patients with Parkinson disease: an example of inverse comorbidity

BACKGROUND

Prostate cancer (PCa) is one of the leading causes of death in Western countries. Environmental and genetic factors play a pivotal role in PCa etiology. Timely identification of the genetic causes is useful for an early diagnosis. Parkinson's disease (PD) is the most frequent neurodegenerative movement disorder; it is associated with the presence of Lewy bodies and genetic factors are involved in its pathogenesis. Several studies have indicated that the expression of target genes in patients with PD is inversely related to cancer development; this phenomenon has been named "inverse comorbidity". The present study was undertaken to evaluate whether a genetic dysregulation occurs in opposite directions in patients with PD or PCa.

METHODS AND RESULTS

In the present study, next-generation sequencing transcriptome analysis was used to assess whether a genetic dysregulation in opposite directions occurs in patients with PD or PCa. The genes SLC30A1, ADO, SRGAP2C, and TBC1D12 resulted up-regulated in patients with PD compared to healthy donors as controls and down-regulated in patients with PCa compared with the same control group.

CONCLUSIONS

These results support the hypothesis of the presence of inverse comorbidity between PD and PCa.