Prospective Validation Study of a Novel Integrated Pathway Based on Clinical Features, Magnetic Resonance Imaging Biomarkers, and MicroRNAs for Early Detection of Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is the most diagnosed cancer in men, with an increasing need to integrate noninvasive imaging and circulating microRNAs beyond prostate-specific antigen for screening and early detection. OBJECTIVE: To validate magnetic resonance imaging (MRI) biomarkers and circulating microRNAs as triage tests for patients directed to prostate biopsy, and to test different diagnostic pathways to compare their performance on patients' outcome, in terms of unnecessary biopsy avoidance. DESIGN, SETTING, AND PARTICIPANTS: A prospective single-center cohort study, enrolling patients with PCa suspicion who underwent MRI, MRI-directed fusion biopsy (MRDB), and circulating microRNAs, was conducted. A network-based analysis was used to identify MRI biomarkers and microRNA drivers of clinically significant PCa. INTERVENTION: MRI, MRDB, and blood sampling. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The decision curve analysis was exploited to assess the performance of the proposed diagnostic pathways and to quantify their benefit in terms of biopsy avoidance. RESULTS AND LIMITATIONS: Overall, 261 men were enrolled and underwent MRDB for PCa detection. A total of 178 patients represented the entire cohort: 55 (30.9%) were negative for PCa, 39 (21.9%) had grade group (GG) 1 PCa, and 84 (47.2%) had GG >1 PCa. The proposed integrated pathway, including clinical data, MRI biomarkers, and microRNAs, provided the best net benefit with a biopsy avoidance rate of about 20% at a low disease probability. The main limitation is the monocentric design in a referral center. CONCLUSIONS: The integrated pathway represents a validated model that sees MRI biomarkers and microRNAs as a prebiopsy triage of patients at a risk for clinically significant PCa. The proposed pathway showed the highest net benefit in terms of unnecessary biopsy avoidance. PATIENT SUMMARY: The proposed integrated pathway for early detection of prostate cancer (PCa) allows accurate patient allocation to biopsy and patients' stratification into risk group categories, reducing overdiagnosis and overtreatment of clinically insignificant PCa.

Network analysis identifies circulating miR-155 as predictive biomarker of type 2 diabetes mellitus development in obese patients: a pilot study.

Obesity is the main risk factor for many non-communicable diseases. In clinical practice, unspecific markers are used for the determination of metabolic alterations and inflammation, without allowing the characterization of subjects at higher risk of complications. Circulating microRNAs represent an attractive approach for early screening to identify subjects affected by obesity more at risk of developing connected pathologies. The aim of this study was the identification of circulating free and extracellular vesicles (EVs)-embedded microRNAs able to identify obese patients at higher risk of type 2 diabetes (DM2). The expression data of circulating microRNAs derived from obese patients (OB), with DM2 (OBDM) and healthy donors were combined with clinical data, through network-based methodology implemented by weighted gene co-expression network analysis. The six circulating microRNAs overexpressed in OBDM patients were evaluated in a second group of patients, confirming the overexpression of miR-155-5p in OBDM patients. Interestingly, the combination of miR-155-5p with serum levels of IL-8, Leptin and RAGE was useful to identify OB patients most at risk of developing DM2. These results suggest that miR-155-5p is a potential circulating biomarker for DM2 and that the combination of this microRNA with other inflammatory markers in OB patients can predict the risk of developing DM2.

An ontology-based approach for modelling and querying Alzheimer's disease data.

BACKGROUND: The recent advances in biotechnology and computer science have led to an ever-increasing availability of public biomedical data distributed in large databases worldwide. However, these data collections are far from being "standardized" so to be harmonized or even integrated, making it impossible to fully exploit the latest machine learning technologies for the analysis of data themselves. Hence, facing this huge flow of biomedical data is a challenging task for researchers and clinicians due to their complexity and high heterogeneity. This is the case of neurodegenerative diseases and the Alzheimer's Disease (AD) in whose context specialized data collections such as the one by the Alzheimer's Disease Neuroimaging Initiative (ADNI) are maintained. METHODS: Ontologies are controlled vocabularies that allow the semantics of data and their relationships in a given domain to be represented. They are often exploited to aid knowledge and data management in healthcare research. Computational Ontologies are the result of the combination of data management systems and traditional ontologies. Our approach is i) to define a computational ontology representing a logic-based formal conceptual model of the ADNI data collection and ii) to provide a means for populating the ontology with the actual data in the Alzheimer Disease Neuroimaging Initiative (ADNI). These two components make it possible to semantically query the ADNI database in order to support data extraction in a more intuitive manner. RESULTS: We developed: i) a detailed computational ontology for clinical multimodal datasets from the ADNI repository in order to simplify the access to these data; ii) a means for populating this ontology with the actual ADNI data. Such computational ontology immediately makes it possible to facilitate complex queries to the ADNI files, obtaining new diagnostic knowledge about Alzheimer's disease. CONCLUSIONS: The proposed ontology will improve the access to the ADNI dataset, allowing queries to extract multivariate datasets to perform multidimensional and longitudinal statistical analyses. Moreover, the proposed ontology can be a candidate for supporting the design and implementation of new information systems for the collection and management of AD data and metadata, and for being a reference point for harmonizing or integrating data residing in different sources.

Cognitive Reserve Potential: Capturing Cognitive Resilience Capability in Adolescence.

Cognitive reserve (CR) represents the adaptive response of the cognitive system responsible for preserving normal functioning in the face of brain damage. Experiential factors such as education, occupation, and leisure activities influence the development of CR. Theoretically, such factors build up from childhood and across adulthood. Thus, appropriate tools to define and measure CR as early as adolescence are essential to understand its developmental processes. To this aim, we introduce the construct of "Cognitive Reserve Potential" (CRP) and its corresponding index of experiential factors tailored to youth. We investigated prototypical youth exposures potentially associated with the lifelong development of CR (e.g., sport practice, musical experiences, cultural activities, and relationships with peers and family). Principal component analysis and confirmatory factor analysis identified and replicated the CRP factor structure on two independent samples of Italian students: N = 585 (295 F) and N = 351 (201 F), ages 11 to 20. CRP was associated mainly with family socio-cultural status (i.e., socioeconomic status [SES], Home Possessions, and Books at Home). Results confirmed the strength of the factorial model and warranted the proposal of the CRP-questionnaire as an innovative tool for understanding CR evolutionary dynamics.

Isotopic Tracing of Nucleotide Sugar Metabolism in Human Pluripotent Stem Cells.

Metabolism not only produces energy necessary for the cell but is also a key regulator of several cellular functions, including pluripotency and self-renewal. Nucleotide sugars (NSs) are activated sugars that link glucose metabolism with cellular functions via protein N-glycosylation and O-GlcNAcylation. Thus, understanding how different metabolic pathways converge in the synthesis of NSs is critical to explore new opportunities for metabolic interference and modulation of stem cell functions. Tracer-based metabolomics is suited for this challenge, however chemically-defined, customizable media for stem cell culture in which nutrients can be replaced with isotopically labeled analogs are scarcely available. Here, we established a customizable flux-conditioned E8 (FC-E8) medium that enables stem cell culture with stable isotopes for metabolic tracing, and a dedicated liquid chromatography mass-spectrometry (LC-MS/MS) method targeting metabolic pathways converging in NS biosynthesis. By 13C6-glucose feeding, we successfully traced the time-course of carbon incorporation into NSs directly via glucose, and indirectly via other pathways, such as glycolysis and pentose phosphate pathways, in induced pluripotent stem cells (hiPSCs) and embryonic stem cells. Then, we applied these tools to investigate the NS biosynthesis in hiPSC lines from a patient affected by deficiency of phosphoglucomutase 1 (PGM1), an enzyme regulating the synthesis of the two most abundant NSs, UDP-glucose and UDP-galactose.

The Up-Side of the COVID-19 Pandemic: Are Core Belief Violation and Meaning Making Associated with Post-Traumatic Growth?

The negative impact of the COVID-19 pandemic on mental health has been extensively documented, while its possible positive impact on the individual, defined as Post-Traumatic Growth (PTG), has been much less investigated. The present study examines the association between PTG and socio-demographic aspects, pre-pandemic psychological adjustment, stressors directly linked to COVID-19 and four psychological factors theoretically implicated in the change processes (core belief violation, meaning-making, vulnerability and mortality perception). During the second wave of the pandemic 680 medical patients completed an online survey on direct and indirect COVID-19 stressors, health and demographic information, post-traumatic growth, core belief violation, meaning-making capacity, feelings of vulnerability and perceptions of personal mortality. Violation of core beliefs, feelings of vulnerability and mortality, and pre-pandemic mental illness positively correlated with post-traumatic growth. Moreover, the diagnosis of COVID-19, stronger violation of core beliefs, greater meaning-making ability, and lower pre-existing mental illness predicted greater PTG. Finally, a moderating effect of meaning-making ability was found. The clinical implications were discussed.

Metabolic Cardiomyopathies and Cardiac Defects in Inherited Disorders of Carbohydrate Metabolism: A Systematic Review.

Heart failure (HF) is a progressive chronic disease that remains a primary cause of death worldwide, affecting over 64 million patients. HF can be caused by cardiomyopathies and congenital cardiac defects with monogenic etiology. The number of genes and monogenic disorders linked to development of cardiac defects is constantly growing and includes inherited metabolic disorders (IMDs). Several IMDs affecting various metabolic pathways have been reported presenting cardiomyopathies and cardiac defects. Considering the pivotal role of sugar metabolism in cardiac tissue, including energy production, nucleic acid synthesis and glycosylation, it is not surprising that an increasing number of IMDs linked to carbohydrate metabolism are described with cardiac manifestations. In this systematic review, we offer a comprehensive overview of IMDs linked to carbohydrate metabolism presenting that present with cardiomyopathies, arrhythmogenic disorders and/or structural cardiac defects. We identified 58 IMDs presenting with cardiac complications: 3 defects of sugar/sugar-linked transporters (GLUT3, GLUT10, THTR1); 2 disorders of the pentose phosphate pathway (G6PDH, TALDO); 9 diseases of glycogen metabolism (GAA, GBE1, GDE, GYG1, GYS1, LAMP2, RBCK1, PRKAG2, G6PT1); 29 congenital disorders of glycosylation (ALG3, ALG6, ALG9, ALG12, ATP6V1A, ATP6V1E1, B3GALTL, B3GAT3, COG1, COG7, DOLK, DPM3, FKRP, FKTN, GMPPB, MPDU1, NPL, PGM1, PIGA, PIGL, PIGN, PIGO, PIGT, PIGV, PMM2, POMT1, POMT2, SRD5A3, XYLT2); 15 carbohydrate-linked lysosomal storage diseases (CTSA, GBA1, GLA, GLB1, HEXB, IDUA, IDS, SGSH, NAGLU, HGSNAT, GNS, GALNS, ARSB, GUSB, ARSK). With this systematic review we aim to raise awareness about the cardiac presentations in carbohydrate-linked IMDs and draw attention to carbohydrate-linked pathogenic mechanisms that may underlie cardiac complications.

In Vitro Skeletal Muscle Model of PGM1 Deficiency Reveals Altered Energy Homeostasis.

Phosphoglucomutase 1 (PGM1) is a key enzyme for the regulation of energy metabolism from glycogen and glycolysis, as it catalyzes the interconversion of glucose 1-phosphate and glucose 6-phosphate. PGM1 deficiency is an autosomal recessive disorder characterized by a highly heterogenous clinical spectrum, including hypoglycemia, cleft palate, liver dysfunction, growth delay, exercise intolerance, and dilated cardiomyopathy. Abnormal protein glycosylation has been observed in this disease. Oral supplementation with D-galactose efficiently restores protein glycosylation by replenishing the lacking pool of UDP-galactose, and rescues some symptoms, such as hypoglycemia, hepatopathy, and growth delay. However, D-galactose effects on skeletal muscle and heart symptoms remain unclear. In this study, we established an in vitro muscle model for PGM1 deficiency to investigate the role of PGM1 and the effect of D-galactose on nucleotide sugars and energy metabolism. Genome-editing of C2C12 myoblasts via CRISPR/Cas9 resulted in Pgm1 (mouse homologue of human PGM1, according to updated nomenclature) knockout clones, which showed impaired maturation to myotubes. No difference was found for steady-state levels of nucleotide sugars, while dynamic flux analysis based on 13C6-galactose suggested a block in the use of galactose for energy production in knockout myoblasts. Subsequent analyses revealed a lower basal respiration and mitochondrial ATP production capacity in the knockout myoblasts and myotubes, which were not restored by D-galactose. In conclusion, an in vitro mouse muscle cell model has been established to study the muscle-specific metabolic mechanisms in PGM1 deficiency, which suggested that galactose was unable to restore the reduced energy production capacity.

Neighbourhood deprivation across eight decades and late-life cognitive function in the Lothian Birth Cohort 1936: a life-course study.

INTRODUCTION: although neighbourhood may predict late-life cognitive function, studies mostly rely on measurements at a single time point, with few investigations applying a life-course approach. Furthermore, it is unclear whether the associations between neighbourhood and cognitive test scores relate to specific cognitive domains or general ability. This study explored how neighbourhood deprivation across eight decades contributed to late-life cognitive function. METHODS: data were drawn from the Lothian Birth Cohort 1936 (n = 1,091) with cognitive function measured through 10 tests at ages 70, 73, 76, 79 and 82. Participants' residential history was gathered with 'lifegrid' questionnaires and linked to neighbourhood deprivation in childhood, young adulthood and mid-to-late adulthood. Associations were tested with latent growth curve models for levels and slopes of general (g) and domain-specific abilities (visuospatial ability, memory and processing speed), and life-course associations were explored with path analysis. RESULTS: higher mid-to-late adulthood neighbourhood deprivation was associated with lower age 70 levels (ß = -0.113, 95% confidence intervals [CI]: -0.205, -0.021) and faster decline of g over 12 years (ß = -0.160, 95%CI: -0.290, -0.031). Initially apparent findings with domain-specific cognitive functions (e.g. processing speed) were due to their shared variance with g. Path analyses suggested that childhood neighbourhood disadvantage is indirectly linked to late-life cognitive function through lower education and selective residential mobility. CONCLUSIONS: to our knowledge, we provide the most comprehensive assessment of the life-course neighbourhood deprivation and cognitive ageing relationship. Living in advantaged areas in mid-to-late adulthood may directly contribute to better cognitive function and slower decline, whereas an advantaged childhood neighbourhood likely affects functioning through cognitive reserves.

Linoleic acid potentiates CD8+ T cell metabolic fitness and antitumor immunity.

The metabolic state represents a major hurdle for an effective adoptive T cell therapy (ACT). Indeed, specific lipids can harm CD8+ T cell (CTL) mitochondrial integrity, leading to defective antitumor responses. However, the extent to which lipids can affect the CTL functions and fate remains unexplored. Here, we show that linoleic acid (LA) is a major positive regulator of CTL activity by improving metabolic fitness, preventing exhaustion, and stimulating a memory-like phenotype with superior effector functions. We report that LA treatment enhances the formation of ER-mitochondria contacts (MERC), which in turn promotes calcium (Ca2+) signaling, mitochondrial energetics, and CTL effector functions. As a direct consequence, the antitumor potency of LA-instructed CD8 T cells is superior in vitro and in vivo. We thus propose LA treatment as an ACT potentiator in tumor therapy.

Third dose of SARS-CoV2 mRNA vaccination produces robust persistent cellular and humoral immune responses in liver transplant recipients.

Weaker responses have been described after two doses of anti-SARS-CoV2 vaccination in liver transplant recipients (LTRs). At the Italian National Institute for Infectious Diseases, 122 LTRs (84% males, median age 64 years) were tested for humoral and cell-mediated immune response after a third doses of anti-SARS-CoV2 mRNA vaccines. Humoral response was measured by quantifying anti-receptor binding domain and neutralizing antibodies; cell-mediated response was measured by quantifying IFN-γ after stimulation of T cells with SARS-CoV-2-specific peptides. Humoral and cellular responses improved significantly compared to the second vaccine dose; 86.4% of previous non-responders to the first 2 vaccine doses (N = 22) became responders. Mycophenolate mofetil-containing regimens were not associated with lower response rates to a third vaccine; shorter time since transplantation (<6 years) was associated with lower humoral and cellular responses to third vaccine. Protective antibodies against Omicron variant were detected in 60% of patients 12 weeks after third vaccine dose.

A Network of MicroRNAs and mRNAs Involved in Melanosome Maturation and Trafficking Defines the Lower Response of Pigmentable Melanoma Cells to Targeted Therapy.

BACKGROUND: The ability to increase their degree of pigmentation is an adaptive response that confers pigmentable melanoma cells higher resistance to BRAF inhibitors (BRAFi) compared to non-pigmentable melanoma cells. METHODS: Here, we compared the miRNome and the transcriptome profile of pigmentable 501Mel and SK-Mel-5 melanoma cells vs. non-pigmentable A375 melanoma cells, following treatment with the BRAFi vemurafenib (vem). In depth bioinformatic analyses (clusterProfiler, WGCNA and SWIMmeR) allowed us to identify the miRNAs, mRNAs and biological processes (BPs) that specifically characterize the response of pigmentable melanoma cells to the drug. Such BPs were studied using appropriate assays in vitro and in vivo (xenograft in zebrafish embryos). RESULTS: Upon vem treatment, miR-192-5p, miR-211-5p, miR-374a-5p, miR-486-5p, miR-582-5p, miR-1260a and miR-7977, as well as GPR143, OCA2, RAB27A, RAB32 and TYRP1 mRNAs, are differentially expressed only in pigmentable cells. These miRNAs and mRNAs belong to BPs related to pigmentation, specifically melanosome maturation and trafficking. In fact, an increase in the number of intracellular melanosomes-due to increased maturation and/or trafficking-confers resistance to vem. CONCLUSION: We demonstrated that the ability of pigmentable cells to increase the number of intracellular melanosomes fully accounts for their higher resistance to vem compared to non-pigmentable cells. In addition, we identified a network of miRNAs and mRNAs that are involved in melanosome maturation and/or trafficking. Finally, we provide the rationale for testing BRAFi in combination with inhibitors of these biological processes, so that pigmentable melanoma cells can be turned into more sensitive non-pigmentable cells.

Psychological Factors Explaining the COVID-19 Pandemic Impact on Mental Health: The Role of Meaning, Beliefs, and Perceptions of Vulnerability and Mortality.

This study tested an expanded version of the explanatory model of the negative impact of the COVID-19 pandemic on mental health proposed by Milman and colleagues. Participants (N = 680) completed an online survey on demographic variables associated with poor pandemic mental health, COVID-19 stressors, mental health symptoms, and pandemic-related psychological processes we hypothesized as mediating mechanisms explaining the negative mental health effects of the COVID-19 stressors. Results indicated that these psychological processes (core belief violation, meaning made of the pandemic, vulnerability, and mortality perception) explained the severity of mental health symptoms to a far greater extent than COVID-19 stressors and demographics combined. In addition, these psychological processes mediated the impact of COVID-19 stressors on all mental health outcomes. Specifically, COVID-19 stressors were associated with increased core belief violation, decreased meaning making, and more intense perceived vulnerability and mortality. In turn, those whose core beliefs were more violated by the pandemic, who made less meaning of the pandemic, and who perceived a more pronounced vulnerability and mortality experienced a worse mental health condition. This study's results suggest some possible ways of intervention in pandemic-like events useful for limiting such impact at the individual, group, social and political levels.

Adolescence in lockdown: The protective role of mentalizing and epistemic trust.

OBJECTIVE: Mentalizing is the ability to interpret one's own and others' behavior as driven by intentional mental states. Epistemic trust (openness to interpersonally transmitted information) has been associated with mentalizing. Balanced mentalizing abilities allow people to cope with external and internal stressors. Studies show that social isolation imposed by the COVID-19 pandemic was highly stressful for most people, especially for adolescents. Here we examine whether mentalizing and epistemic trust were protective factors in relation to emotional distress during the lockdown. METHOD: A total of 131 nonclinical adolescents, aged between 12 and 18 years, were evaluated during the lockdown using the Reflective Functioning Questionnaire for Youth, Inventory of Parent and Peer Attachment, Perceived Stress Scale, and Difficulties in Emotion Regulation Scale. RESULTS: Results from network analysis showed that epistemic trust and mentalizing were negatively associated with perceived stress and emotion dysregulation. Epistemic trust in fathers was associated with level of perceived stress, and epistemic trust in mothers with emotion dysregulation. CONCLUSION: These findings suggest that epistemic trust and the capacity to mentalize were low in adolescents during lockdown, and this was associated with high levels of stress. However, robust levels of epistemic trust and mentalizing may have acted as protective factors that buffered individuals from the risk of emotional dysregulation during the lockdown.

Predictors of longitudinal cognitive ageing from age 70 to 82 including APOE e4 status, early-life and lifestyle factors: the Lothian Birth Cohort 1936.

Discovering why some people's cognitive abilities decline more than others is a key challenge for cognitive ageing research. The most effective strategy may be to address multiple risk factors from across the life-course simultaneously in relation to robust longitudinal cognitive data. We conducted a 12-year follow-up of 1091 (at age 70) men and women from the longitudinal Lothian Birth Cohort 1936 study. Comprehensive repeated cognitive measures of visuospatial ability, processing speed, memory, verbal ability, and a general cognitive factor were collected over five assessments (age 70, 73, 76, 79, and 82 years) and analysed using multivariate latent growth curve modelling. Fifteen life-course variables were used to predict variation in cognitive ability levels at age 70 and cognitive slopes from age 70 to 82. Only APOE e4 carrier status was found to be reliably informative of general- and domain-specific cognitive decline, despite there being many life-course correlates of cognitive level at age 70. APOE e4 carriers had significantly steeper slopes across all three fluid cognitive domains compared with non-carriers, especially for memory (ß = -0.234, p < 0.001) and general cognitive function (ß = -0.246, p < 0.001), denoting a widening gap in cognitive functioning with increasing age. Our findings suggest that when many other candidate predictors of cognitive ageing slope are entered en masse, their unique contributions account for relatively small proportions of variance, beyond variation in APOE e4 status. We conclude that APOE e4 status is important for identifying those at greater risk for accelerated cognitive ageing, even among ostensibly healthy individuals.

Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors.

Background: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata. Methods: Fecal samples collected from children with ASD and neurotypical children were analyzed by gas-chromatography mass spectrometry coupled with solid phase microextraction (GC-MS/SPME) to determine volatile organic compounds (VOCs) associated with the metataxonomic approach by 16S rRNA gene sequencing. Multivariate and univariate statistical analyses assessed differential VOC profiles and relationships with ASD anamnestic and clinical features for biomarker discovery. Multiple web-based and machine learning (ML) models identified metabolic predictors of disease and network analyses correlated GM ecological and metabolic patterns. Results: The GM core volatilome for all ASD patients was characterized by a high concentration of 1-pentanol, 1-butanol, phenyl ethyl alcohol; benzeneacetaldehyde, octadecanal, tetradecanal; methyl isobutyl ketone, 2-hexanone, acetone; acetic, propanoic, 3-methyl-butanoic and 2-methyl-propanoic acids; indole and skatole; and o-cymene. Patients were stratified based on age, GI symptoms, and ASD severity symptoms. Disease risk prediction allowed us to associate butanoic acid with subjects older than 5 years, indole with the absence of GI symptoms and low disease severity, propanoic acid with the ASD risk group, and p-cymene with ASD symptoms, all based on the predictive CBCL-EXT scale. The HistGradientBoostingClassifier model classified ASD patients vs. CTRLs by an accuracy of 89%, based on methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, ethanol, butanoic acid, octadecane, acetic acid, skatole, and tetradecanal features. LogisticRegression models corroborated methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, skatole, and acetic acid as ASD predictors. Conclusion: Our results will aid the development of advanced clinical decision support systems (CDSSs), assisted by ML models, for advanced ASD-personalized medicine, based on omics data integrated into electronic health/medical records. Furthermore, new ASD screening strategies based on GM-related predictors could be used to improve ASD risk assessment by uncovering novel ASD onset and risk predictors.

Alzheimer's disease: insights from a network medicine perspective.

Alzheimer's disease (AD) is the most common neurodegenerative disease that currently lacks available effective therapy. Thus, identifying novel molecular biomarkers for diagnosis and treatment of AD is urgently demanded. In this study, we exploited tools and concepts of the emerging research area of Network Medicine to unveil a novel putative disease gene signature associated with AD. We proposed a new pipeline, which combines the strengths of two consolidated algorithms of the Network Medicine: DIseAse MOdule Detection (DIAMOnD), designed to predict new disease-associated genes within the human interactome network; and SWItch Miner (SWIM), designed to predict important (switch) genes within the co-expression network. Our integrated computational analysis allowed us to enlarge the set of the known disease genes associated to AD with additional 14 genes that may be proposed as new potential diagnostic biomarkers and therapeutic targets for AD phenotype.

Identification of Potential Repurposable Drugs in Alzheimer's Disease Exploiting a Bioinformatics Analysis.

Alzheimer's disease (AD) is a neurologic disorder causing brain atrophy and the death of brain cells. It is a progressive condition marked by cognitive and behavioral impairment that significantly interferes with daily activities. AD symptoms develop gradually over many years and eventually become more severe, and no cure has been found yet to arrest this process. The present study is directed towards suggesting putative novel solutions and paradigms for fighting AD pathogenesis by exploiting new insights from network medicine and drug repurposing strategies. To identify new drug-AD associations, we exploited SAveRUNNER, a recently developed network-based algorithm for drug repurposing, which quantifies the vicinity of disease-associated genes to drug targets in the human interactome. We complemented the analysis with an in silico validation of the candidate compounds through a gene set enrichment analysis, aiming to determine if the modulation of the gene expression induced by the predicted drugs could be counteracted by the modulation elicited by the disease. We identified some interesting compounds belonging to the beta-blocker family, originally approved for treating hypertension, such as betaxolol, bisoprolol, and metoprolol, whose connection with a lower risk to develop Alzheimer's disease has already been observed. Moreover, our algorithm predicted multi-kinase inhibitors such as regorafenib, whose beneficial effects were recently investigated for neuroinflammation and AD pathology, and mTOR inhibitors such as sirolimus, whose modulation has been associated with AD.

Cognitive Change Before Old Age (11 to 70) Predicts Cognitive Change During Old Age (70 to 82).

Identifying predictors of cognitive decline in old age helps us understand its mechanisms and identify those at greater risk. Here, we examined how cognitive change from ages 11 to 70 is associated with cognitive change at older ages (70 to 82 years) in the Lothian Birth Cohort 1936 longitudinal study (N = 1,091 at recruitment). Using latent-growth-curve models, we estimated rates of change from ages 70 to 82 in general cognitive ability (g) and in three cognitive domains: visuospatial, memory, and processing speed. We found that g accounted for 71.3% of interindividual change variance. Greater cognitive gain from ages 11 to 70 predicted slower decline in g over 12 subsequent years (ß = 0.163, p = .001), independently of cognitive level in childhood and at age 70, and domain-specific change beyond g. These results contribute to the goal of identifying people at higher risk of age-related cognitive decline.

Characterization of Extracellular Vesicles in Osteoporotic Patients Compared to Osteopenic and Healthy Controls.

Extracellular vesicles (EVs) are mediators of a range of pathological conditions. However, their role in bone loss disease has not been well understood. In this study we characterized plasma EVs of 54 osteoporotic (OP) postmenopausal women compared to 48 osteopenic (OPN) and 44 healthy controls (CN), and we investigated their effects on osteoclasts and osteoblasts. We found no differences between the three groups in terms of anthropometric measurements and biochemical evaluation of serum calcium, phosphate, creatinine, PTH, 25-hydroxy vitamin D and bone biomarkers, except for an increase of CTX level in OP group. FACS analysis revealed that OP patients presented a significantly increased number of EVs and RANKL+ EVs compared with both CN and OPN subjects. Total EVs are negatively associated with the lumbar spine T-score and femoral neck T-score. Only in the OPN patients we observed a positive association between the total number of EVs and RANKL+ EVs with the serum RANKL. In vitro studies revealed that OP EVs supported osteoclastogenesis of healthy donor peripheral blood mononuclear cells at the same level observed following RANKL and M-CSF treatment, reduced the ability of mesenchymal stem cells to differentiate into osteoblasts, while inducing an increase of OSTERIX and RANKL expression in mature osteoblasts. The analysis of miRNome revealed that miR-1246 and miR-1224-5p were the most upregulated and downregulated in OP EVs; the modulated EV-miRNAs in OP and OPN compared to CN are related to osteoclast differentiation, interleukin-13 production and regulation of canonical WNT pathway. A proteomic comparison between OPN and CN EVs evidenced a decrease in fibrinogen, vitronectin, and clusterin and an increase in coagulation factors and apolipoprotein, which was also upregulated in OP EVs. Interestingly, an increase in RANKL+ EVs and exosomal miR-1246 was also observed in samples from patients affected by Gorham-Stout disease, suggesting that EVs could be good candidate as bone loss disease biomarkers. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).