Application of Precision Medicine in Neurodegenerative Diseases

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Clinical dimensions along the non-fluent variant primary progressive aphasia spectrum

It is debated whether primary progressive apraxia of speech (PPAOS) and progressive agrammatic aphasia (PAA) belong to the same clinical spectrum, traditionally termed non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), or exist as two completely distinct syndromic entities with specific pathologic/prognostic correlates. We analysed speech, language and disease severity features in a comprehensive cohort of patients with progressive motor speech impairment and/or agrammatism to ascertain evidence of naturally occurring, clinically meaningful non-overlapping syndromic entities (e.g. PPAOS and PAA) in our data. We also assessed if data-driven latent clinical dimensions with aetiologic/prognostic value could be identified. We included 98 participants, 43 of whom had an autopsy-confirmed neuropathological diagnosis. Speech pathologists assessed motor speech features indicative of dysarthria and apraxia of speech (AOS). Quantitative expressive/receptive agrammatism measures were obtained and compared with healthy controls. Baseline and longitudinal disease severity was evaluated using the Clinical Dementia Rating Sum of Boxes (CDR-SB). We investigated the data's clustering tendency and cluster stability to form robust symptom clusters and employed principal component analysis to extract data-driven latent clinical dimensions (LCD). The longitudinal CDR-SB change was estimated using linear mixed-effects models. Of the participants included in this study, 93 conformed to previously reported clinical profiles (75 with AOS and agrammatism, 12 PPAOS and six PAA). The remaining five participants were characterized by non-fluent speech, executive dysfunction and dysarthria without apraxia of speech or frank agrammatism. No baseline clinical features differentiated between frontotemporal lobar degeneration neuropathological subgroups. The Hopkins statistic demonstrated a low cluster tendency in the entire sample (0.45 with values near 0.5 indicating random data). Cluster stability analyses showed that only two robust subgroups (differing in agrammatism, executive dysfunction and overall disease severity) could be identified. Three data-driven components accounted for 71% of the variance [(i) severity-agrammatism; (ii) prominent AOS; and (iii) prominent dysarthria]. None of these data-driven LCDs allowed an accurate prediction of neuropathology. The severity-agrammatism component was an independent predictor of a faster CDR-SB increase in all the participants. Higher dysarthria severity, reduced words per minute and expressive and receptive agrammatism severity at baseline independently predicted accelerated disease progression. Our findings indicate that PPAOS and PAA, rather than exist as completely distinct syndromic entities, constitute a clinical continuum. In our cohort, splitting the nfvPPA spectrum into separate clinical phenotypes did not improve clinical-pathological correlations, stressing the need for new biological markers and consensus regarding updated terminology and clinical classification.

Neurocognitive Effects of an Online Brain Health Program and Weekly Telehealth Support Group in Older Adults with Subjective Memory Loss: A Pilot Study

INTRODUCTION

Adopting healthy lifestyle behaviors has the potential to slow cognitive decline in older adults by reducing risks associated with dementia. Curriculum-based group health coaching may aid in establishing behavior change centered for dementia risk factors.

METHODS

In this pilot clinical care patient group study (n = 6), we examined the effects of a six-month online Cognitive Health Program combined with a weekly telehealth support group led by the course creator, and personalized health optimization by a collaborating physician, in older adults with subjective cognitive decline. Cognition was assessed at baseline and post-intervention using a computerized battery.

RESULTS

Cognitive changes were estimated with nonparametric tests and effect sizes (Cohen's d). Results showed significant improvements in global cognition (p < 0.03, d = 1.6), spatial planning (p < 0.01, d = 2.3), and visuospatial processing (p < 0.05, d = 1.1) compared to baseline. Participants reported high levels of satisfaction with the virtual group format and online curriculum.

CONCLUSIONS

This small pilot study suggests that a virtual six-month personalized health coaching group with self-paced online health education is feasible and potentially efficacious for improving cognition in participants with subjective cognitive complaints. This format may facilitate behavior change to slow cognitive decline. Future studies should include a control group, a larger, more diverse sample as well as assessing mood and other subjective measures.

Alzheimer's Disease: A Suitable Case for Treatment with Precision Medicine?

Alzheimer's disease (AD) is the most common cause of neurodegenerative impairment in elderly people. Clinical characteristics include short-term memory loss, confusion, hallucination, agitation, and behavioural disturbance. Owing to evolving research in biomarkers AD can be discovered at early onset, but the disease is currently considered a continuum, which suggests that pharmacotherapy is most efficacious in the preclinical phase, possibly 15 - 20 years before discernible onset. Present developments in AD therapy aim to respond to this understanding and go beyond the drug families that relieve clinical symptoms. Another important factor in this development is the emergence of precision medicine that aims to tailor treatment to specific patients or patient subgroups. This relatively new platform would categorize AD patients on the basis of parameters like clinical aspects, brain imaging, genetic profiling, clinical genetics and epidemiological factors. This review enlarges on recent progress in the design and clinical use of antisense molecules, antibodies, antioxidants, small molecules and gene editing to stop AD progress and possibly reverse the disease on the basis of relevant biomarkers.

An Evolutionary Concept Analysis of Precision Medicine, and Its Contribution to a Precision Health Model for Nursing Practice

Precision medicine is a new concept that has been routinely encountered in the literature for little more than a decade. With increasing use, it becomes crucial to understand the meaning of this concept as it is applied in various settings. An evolutionary concept analysis was conducted to develop an understanding of the essential features of precision medicine and its use. The analysis led to a comprehensive list of the antecedents, attributes, and consequences of precision medicine in multiple settings. With this understanding, precision medicine becomes part of the broader practice of precision health, an important process proposed by nursing scholars to provide complete, holistic care to our patients. A model for precision health is presented as a framework for care.

A Review of the Common Neurodegenerative Disorders: Current Therapeutic Approaches and the Potential Role of Bioactive Peptides

Neurodegenerative disorders, which include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS), represent a significant and growing global health challenge. Current therapies predominantly focus on symptom management rather than altering disease progression. In this review, we discuss the major therapeutic strategies in practice for these disorders, highlighting their limitations. For AD, the mainstay treatments are cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists. For PD, dopamine replacement therapies, including levodopa, are commonly used. HD is managed primarily with symptomatic treatments, and reusable extends survival in ALS. However, none of these therapies halts or substantially slows the neurodegenerative process. In contrast, this review highlights emerging research into bioactive peptides as potential therapeutic agents. These naturally occurring or synthetically designed molecules can interact with specific cellular targets, potentially modulating disease processes. Preclinical studies suggest that bioactive peptides may mitigate oxidative stress, inflammation, and protein misfolding, which are common pathological features in neurodegenerative diseases. Clinical trials using bioactive peptides for neurodegeneration are limited but show promising initial results. For instance, hemiacetal, a γ-secretase inhibitor peptide, has shown potential in AD by reducing amyloid-beta production, though its development was discontinued due to side effects. Despite these advancements, many challenges remain, including identifying optimal peptides, confirming their mechanisms of action, and overcoming obstacles related to their delivery to the brain. Future research should prioritize the discovery and development of novel bioactive peptides and improve our understanding of their pharmacokinetics and pharmacodynamics. Ultimately, this approach may lead to more effective therapies for neurodegenerative disorders, moving beyond symptom management to potentially modify the course of these devastating diseases.

The impact of toxic metal bioaccumulation on colorectal cancer: Unravelling the unexplored connection

Colorectal cancer is a major public health concern, with increasing incidence and mortality rates worldwide. Environmental factors, including exposure to toxic metals, such as lead, chromium, cadmium, aluminium, copper, arsenic and mercury, have been suggested to play a significant role in the development and progression of this neoplasia. In particular, the bioaccumulation of toxic metals can play a significant role in colorectal cancer by regulating biological phenomenon associated to both cancer occurrence and progression, such as cell death and proliferation. Also, frequently these metals can induce DNA mutations in well-known oncogenes. This review provides a critical analysis of the current evidence, highlighting the need for further research to fully grasp the complex interplay between toxic metal bioaccumulation and colorectal cancer. Understanding the contribution of toxic metals to colorectal cancer occurrence and progression is essential for the development of targeted preventive strategies and social interventions, with the ultimate goal of reducing the burden of this disease.

Patient-Derived Cellular Models for Polytarget Precision Medicine in Pantothenate Kinase-Associated Neurodegeneration

The term neurodegeneration with brain iron accumulation (NBIA) brings together a broad set of progressive and disabling neurological genetic disorders in which iron is deposited preferentially in certain areas of the brain. Among NBIA disorders, the most frequent subtype is pantothenate kinase-associated neurodegeneration (PKAN) caused by pathologic variants in the PANK2 gene codifying the enzyme pantothenate kinase 2 (PANK2). To date, there are no effective treatments to stop the progression of these diseases. This review discusses the utility of patient-derived cell models as a valuable tool for the identification of pharmacological or natural compounds for implementing polytarget precision medicine in PKAN. Recently, several studies have described that PKAN patient-derived fibroblasts present the main pathological features associated with the disease including intracellular iron overload. Interestingly, treatment of mutant cell cultures with various supplements such as pantothenate, pantethine, vitamin E, omega 3, α-lipoic acid L-carnitine or thiamine, improved all pathophysiological alterations in PKAN fibroblasts with residual expression of the PANK2 enzyme. The information provided by pharmacological screenings in patient-derived cellular models can help optimize therapeutic strategies in individual PKAN patients.

Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine

Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.

Neurodegenerative and Neurodevelopmental Diseases and the Gut-Brain Axis: The Potential of Therapeutic Targeting of the Microbiome

The human gut microbiome contains the largest number of bacteria in the body and has the potential to greatly influence metabolism, not only locally but also systemically. There is an established link between a healthy, balanced, and diverse microbiome and overall health. When the gut microbiome becomes unbalanced (dysbiosis) through dietary changes, medication use, lifestyle choices, environmental factors, and ageing, this has a profound effect on our health and is linked to many diseases, including lifestyle diseases, metabolic diseases, inflammatory diseases, and neurological diseases. While this link in humans is largely an association of dysbiosis with disease, in animal models, a causative link can be demonstrated. The link between the gut and the brain is particularly important in maintaining brain health, with a strong association between dysbiosis in the gut and neurodegenerative and neurodevelopmental diseases. This link suggests not only that the gut microbiota composition can be used to make an early diagnosis of neurodegenerative and neurodevelopmental diseases but also that modifying the gut microbiome to influence the microbiome-gut-brain axis might present a therapeutic target for diseases that have proved intractable, with the aim of altering the trajectory of neurodegenerative and neurodevelopmental diseases such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, autism spectrum disorder, and attention-deficit hyperactivity disorder, among others. There is also a microbiome-gut-brain link to other potentially reversible neurological diseases, such as migraine, post-operative cognitive dysfunction, and long COVID, which might be considered models of therapy for neurodegenerative disease. The role of traditional methods in altering the microbiome, as well as newer, more novel treatments such as faecal microbiome transplants and photobiomodulation, are discussed.

Sex and gender differences in Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis: a narrative review

Neurodegenerative diseases (NDs), including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS), exhibit high phenotypic variability and they are very common in the general population. These diseases are associated with poor prognosis and a significant burden on patients and their caregivers. Although increasing evidence suggests that biological sex is an important factor for the development and phenotypical expression of some NDs, the role of sex and gender in the diagnosis and prognosis of NDs has been poorly explored. Current knowledge relating to sex- and gender-related differences in the epidemiology, clinical features, biomarkers, and treatment of AD, PD, and ALS will be summarized in this narrative review. The cumulative evidence hitherto collected suggests that sex and gender are factors to be considered in explaining the heterogeneity of these NDs. Clarifying the role of sex and gender in AD, PD, and ALS is a key topic in precision medicine, which will facilitate sex-specific prevention and treatment strategies to be implemented in the near future.

Complementary and integrative medicines for behavioral and psychological symptoms of dementia: Overview of systematic reviews

BACKGROUND

Behavioral and psychological symptoms of dementia (BPSDs) are major contributing factors to disease burden in dementia patients. Complementary and integrative medicine (CIM) has received attention in the management of dementia in patients with BPSDs. This overview aimed to comprehensively and critically review previous systematic reviews (SRs) of CIM modalities for BPSD management.

METHODS

Thirteen databases were searched in November 2021 to identify SRs on CIM for BPSDs. The methodological quality of the included studies was assessed using A MeaSurement Tool to Assess systematic Reviews 2.

RESULTS

Among 38 SRs, aromatherapy was the most commonly studied intervention, followed by herbal medicine (HM), acupuncture/acupressure, mindfulness-based interventions, relaxation, and Taichi. Half of the studies on aromatherapy reported significantly improved BPSDs, especially agitation, while the remainder reported mixed results/insufficient evidence. Most studies (85.71%) on HM supported its significant benefits in BPSDs. Yokukansan, an individual HM, was most frequently studied for BPSDs, with a significant beneficial effect on delusions, hallucinations, and agitation/aggression. Moreover, some meta-analyses supported the benefits of HM as an adjunct to psychotropic drugs in BPSD management. Other CIM interventions had insufficient clinical evidence. The methodological quality of the included studies was poor, and most were rated low or critically low (92.11%).

CONCLUSION

Aromatherapy, the most frequently investigated CIM for BPSD, had mixed results or insufficient evidence. HM, as an adjunct to psychotropic drugs including antipsychotics, exhibited additional benefits regarding the efficacy and safety for BPSDs. This overview emphasizes the requirement for greater quantity and quality of research in this field.

REGISTRATION NUMBER

Open Science Framework registry (g5f3m) (https://osf.io/g5f3m), PROSPERO (CRD42020211009) (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211009).

Calabria as a Genetic Isolate: A Model for the Study of Neurodegenerative Diseases

Although originally multi-ethnic in its structure, nowadays the Calabria region of southern Italy represents an area with low genetic heterogeneity and a high level of consanguinity that allows rare mutations to be maintained due to the founder effect. A complex research methodology—ranging from clinical activity to the genealogical reconstruction of families/populations across the centuries, the creation of databases, and molecular/genetic research—was modelled on the characteristics of the Calabrian population for more than three decades. This methodology allowed the identification of several novel genetic mutations or variants associated with neurodegenerative diseases. In addition, a higher prevalence of several hereditary neurodegenerative diseases has been reported in this population, such as Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease, Niemann–Pick type C disease, spinocerebellar ataxia, Creutzfeldt–Jakob disease, and Gerstmann–Straussler–Scheinker disease. Here, we summarize and discuss the results of research data supporting the view that Calabria could be considered as a genetic isolate and could represent a model, a sort of outdoor laboratory—similar to very few places in the world—useful for the advancement of knowledge on neurodegenerative diseases.

Relationship between Nutrition, Lifestyle, and Neurodegenerative Disease: Lessons from ADH1B, CYP1A2 and MTHFR

In the present review, the main features involved in the susceptibility and progression of neurodegenerative disorders (NDDs) have been discussed, with the purpose of highlighting their potential application for promoting the management and treatment of patients with NDDs. In particular, the impact of genetic and epigenetic factors, nutrients, and lifestyle will be presented, with particular emphasis on Alzheimer’s disease (AD) and Parkinson’s disease (PD). Metabolism, dietary habits, physical exercise and microbiota are part of a complex network that is crucial for brain function and preservation. This complex equilibrium can be disrupted by genetic, epigenetic, and environmental factors causing perturbations in central nervous system homeostasis, contributing thereby to neuroinflammation and neurodegeneration. Diet and physical activity can directly act on epigenetic modifications, which, in turn, alter the expression of specific genes involved in NDDs onset and progression. On this subject, the introduction of nutrigenomics shed light on the main molecular players involved in the modulation of health and disease status. In particular, the review presents data concerning the impact of ADH1B, CYP1A2, and MTHFR on the susceptibility and progression of NDDs (especially AD and PD) and how they may be exploited for developing precision medicine strategies for the disease treatment and management.

Neuroprotective mechanisms of multitarget 7-aminophenanthridin-6(5H)-one derivatives against metal-induced amyloid proteins generation and aggregation

Brain's metals accumulation is associated with toxic proteins, like amyloid-proteins (Aβ), formation, accumulation, and aggregation, leading to neurodegeneration. Metals downregulate the correct folding, disaggregation, or degradation mechanisms of toxic proteins, as heat shock proteins (HSPs) and proteasome. The 7-amino-phenanthridin-6(5H)-one derivatives (APH) showed neuroprotective effects against metal-induced cell death through their antioxidant effect, independently of their chelating activity. However, additional neuroprotective mechanisms seem to be involved. We tested the most promising APH compounds (APH1-5, 10-100 μM) chemical ability to prevent metal-induced Aβ proteins aggregation; the APH1-5 effect on HSP70 and proteasome 20S (P20S) expression, the metals effect on Aβ formation and the involvement of HSP70 and P20S in the process, and the APH1-5 neuroprotective effects against Aβ proteins (1 μM) and metals in SN56 cells. Our results show that APH1-5 compounds chemically avoid metal-induced Aβ proteins aggregation and induce HSP70 and P20S expression. Additionally, iron and cadmium induced Aβ proteins formation through downregulation of HSP70 and P20S. Finally, APH1-5 compounds protected against Aβ proteins-induced neuronal cell death, reversing partially or completely this effect. These data may help to provide a new therapeutic approach against the neurotoxic effect induced by metals and other environmental pollutants, especially when mediated by toxic proteins.

The Advent of Omics Sciences in Clinical Trials of Motor Neuron Diseases

The “omics revolution” has totally changed the scientific research approach and is contributing to the development of personalized therapies. In motor neuron diseases (MNDs), a set of complex, multifactorial, late-onset and chronic neurodegenerative diseases, the use of multi-omics approaches in clinical trials is providing new opportunities to stratify patients and develop target therapies. To show how omics science is gaining momentum in MNDs, in this work, we review the interventional clinical trials for MNDs based on the application of omics sciences. We analyze a total of 62 clinical trials listed in the ClinicalTrials database where different omics approaches have been applied in an initial phase, for diagnosis or patient selection, or in subsequent stages to cluster subjects, identify molecular signatures or evaluate drugs security or efficacy. The rise of omics sciences in clinical experimentation of MNDs is leading to an upheaval in their diagnosis and therapy that will require significant investments and means to ensure the correct and rapid evolution of personalized medicine.

Healthy Food Pyramid as Well as Physical and Mental Activity in the Prevention of Alzheimer’s Disease

The ageing of the population is resulting in neurodegenerative diseases, including Alzheimer’s disease (AD), which are an increasing social, economic and medical problem. Diet and physical activity are now considered as important modifiable factors that help prevent or delay the development of AD and other dementia-related diseases. The pyramid of healthy nutrition and lifestyle is a way of presenting the principles, the implementation of which gives a chance for proper development and a long healthy life. The basis of the pyramid, in the first place, is physical activity. Our review of the literature in the PubMed database supports the hypothesis that complementary factors, such as proper diet, physical exercise and mental activity, have a positive impact on the prevention of neurodegenerative diseases. The nutritional recommendations for healthy adults primarily include the consumption of vegetables, fruits, cereals, legumes, vegetable oils and fishes. Therefore, the introduction of Mediterranean and Asian diets may reduce the risk of the neurodegenerative diseases associated with dementia, whereas dairy products and meat—the main sources of L-carnitine—should be consumed in moderate amounts. The aim of our work is to provide up-to-date knowledge about the appropriate dietary model and healthy lifestyle elements and their impact on good health and the long life of people.

Deregulation of ncRNA in Neurodegenerative Disease: Focus on circRNA, lncRNA and miRNA in Amyotrophic Lateral Sclerosis

Parallel and massive sequencing of total RNA samples derived from different samples are possible thanks to the use of NGS (Next Generation Sequencing) technologies. This allowed characterizing the transcriptomic profile of both cell and tissue populations, increasing the knowledge of the molecular pathological processes of complex diseases, such as neurodegenerative diseases (NDs). Among the NDs, Amyotrophic Lateral Sclerosis (ALS) is caused by the progressive loss of motor neurons (MNs), and, to date, the diagnosis is often made by exclusion because there is no specific symptomatologic picture. For this reason, it is important to search for biomarkers that are clinically useful for carrying out a fast and accurate diagnosis of ALS. Thanks to various studies, it has been possible to propose several molecular mechanisms associated with the disease, some of which include the action of non-coding RNA, including circRNAs, miRNAs, and lncRNAs which will be discussed in the present review. The evidence analyzed in this review highlights the importance of conducting studies to better characterize the different ncRNAs in the disease to use them as possible diagnostic, prognostic, and/or predictive biomarkers of ALS and other NDs.

From psychiatry to neurology: Psychedelics as prospective therapeutics for neurodegenerative disorders

The studies of psychedelics, especially psychedelic tryptamines like psilocybin, are rapidly gaining interest in neuroscience research. Much of this interest stems from recent clinical studies demonstrating that they have a unique ability to improve the debilitating symptoms of major depressive disorder (MDD) long-term after only a single treatment. Indeed, the Food and Drug Administration (FDA) has recently designated two Phase III clinical trials studying the ability of psilocybin to treat forms of MDD with "Breakthrough Therapy" status. If successful, the use of psychedelics to treat psychiatric diseases like depression would be revolutionary. As more evidence appears in the scientific literature to support their use in psychiatry to treat MDD on and substance use disorders (SUD), recent studies with rodents revealed that their therapeutic effects might extend beyond treating MDD and SUD. For example, psychedelics may have efficacy in the treatment and prevention of brain injury and neurodegenerative diseases such as Alzheimer's Disease. Preclinical work has highlighted psychedelics' ability to induce neuroplasticity and synaptogenesis, and neural progenitor cell proliferation. Psychedelics may also act as immunomodulators by reducing levels of proinflammatory biomarkers, including IL-1β, IL-6, and tumor necrosis factor-α (TNF-α). Their exact molecular mechanisms, and induction of cellular interactions, especially between neural and glial cells, leading to therapeutic efficacy, remain to be determined. In this review, we discuss recent findings and information on how psychedelics may act therapeutically on cells within the central nervous system (CNS) during brain injuries and neurodegenerative diseases.

Nuclear and Mitochondrial Genome, Epigenome and Gut Microbiome: Emerging Molecular Biomarkers for Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is currently the second most common neurodegenerative disorder, burdening about 10 million elderly individuals worldwide. The multifactorial nature of PD poses a difficult obstacle for understanding the mechanisms involved in its onset and progression. Currently, diagnosis depends on the appearance of clinical signs, some of which are shared among various neurologic disorders, hindering early diagnosis. There are no effective tools to prevent PD onset, detect the disease in early stages or accurately report the risk of disease progression. Hence, there is an increasing demand for biomarkers that may identify disease onset and progression, as treatment-based medicine may not be the best approach for PD. Over the last few decades, the search for molecular markers to predict susceptibility, aid in accurate diagnosis and evaluate the progress of PD have intensified, but strategies aimed to improve individualized patient care have not yet been established.

CONCLUSIONS

Genomic variation, regulation by epigenomic mechanisms, as well as the influence of the host gut microbiome seem to have a crucial role in the onset and progress of PD, thus are considered potential biomarkers. As such, the human nuclear and mitochondrial genome, epigenome, and the host gut microbiome might be the key elements to the rise of personalized medicine for PD patients.

Technological readiness and implementation of genomic-driven precision medicine for complex diseases

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

Cognitive Effects of the BET Protein Inhibitor Apabetalone: A Prespecified Montreal Cognitive Assessment Analysis Nested in the BETonMACE Randomized Controlled Trial

Background:

Epigenetic changes may contribute importantly to cognitive decline in late life including Alzheimer’s disease (AD) and vascular dementia (VaD). Bromodomain and extra-terminal (BET) proteins are epigenetic “readers” that may distort normal gene expression and contribute to chronic disorders.

Objective:

To assess the effects of apabetalone, a small molecule BET protein inhibitor, on cognitive performance of patients 70 years or older participating in a randomized trial of patients at high risk for major cardiovascular events (MACE).

Methods:

The Montreal Cognitive Assessment (MoCA) was performed on all patients 70 years or older at the time of randomization. 464 participants were randomized to apabetalone or placebo in the cognition sub-study. In a prespecified analysis, participants were assigned to one of three groups: MoCA score≥26 (normal performance), MoCA score 25–22 (mild cognitive impairment), and MoCA score≤21 (dementia). Exposure to apabetalone was equivalent in the treatment groups in each MoCA-defined group.

Results:

Apabetalone was associated with an increased total MoCA score in participants with baseline MoCA score of≤21 (p = 0.02). There was no significant difference in change from baseline in the treatment groups with higher MoCA scores. In the cognition study, more patients randomized to apabetalone discontinued study drug for adverse effects (11.3% versus 7.9%).

Conclusion:

In this randomized controlled study, apabetalone was associated with improved cognition as measured by MoCA scores in those with baseline scores of 21 or less. BET protein inhibitors warrant further investigation for late life cognitive disorders.

Towards realizing the vision of precision medicine: AI based prediction of clinical drug response

Accurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring integrating different data types from the same individual into one prediction model. We used the anti-epileptic drug brivaracetam as a case study and combine a hybrid data/knowledge-driven feature extraction with machine learning to systematically integrate clinical and genetic data from a clinical discovery dataset (n = 235 patients). We constructed a model that successfully predicts clinical drug response [area under the curve (AUC) = 0.76] and show that even with limited sample size, integrating high-dimensional genetics data with clinical data can inform drug response prediction. After further validation on data collected from an independently conducted clinical study (AUC = 0.75), we extensively explore our model to gain insights into the determinants of drug response, and identify various clinical and genetic characteristics predisposing to poor response. Finally, we assess the potential impact of our model on clinical trial design and demonstrate that, by enriching for probable responders, significant reductions in clinical study sizes may be achieved. To our knowledge, our model represents the first retrospectively validated machine learning model linking drug mechanism of action and the genetic, clinical and demographic background in epilepsy patients to clinical drug response. Hence, it provides a blueprint for how machine learning-based multimodal data integration can act as a driver in achieving the goals of precision medicine in fields such as neurology.

Immune System and Neuroinflammation in Idiopathic Parkinson's Disease: Association Analysis of Genetic Variants and miRNAs Interactions

The present study investigated the association of SNPs involved in the regulation of immune response, cellular degenerative and neuroinflammatory pathways with the susceptibility and progression of idiopathic Parkinson's Disease (PD). In particular, 342 PD patients were subjected to a genotyping analysis of a panel of 120 SNPs by Open Array Technology. As control group, 503 samples representative of the European general population were utilized. The genetic analysis identified 26 SNPs associated with PD susceptibility. Of them, 12 SNPs were described as significant expression Quantitative Loci (eQTL) variants in different brain regions associated with motor and non-motor PD phenomenology. Moreover, the study highlighted 11 novel susceptibility genes for PD, which may alter multiple signaling pathways critically involved in peripheral immune response, neuroinflammation, neurodegeneration and dopaminergic neurons wiring. The study of miRNA-target genes highlighted a possible role of miR-499a, miR-196a2, and miR-29a in the modulation of multiple neuroinflammatory and neurodegenerative mechanisms underlying PD physiopathology. The study described a network of interconnected genes (APOE, CLU, IL6, IL7R, IL12B, INPP5D, MAPK1, MEF2C, MIF, and TNFSF14), which may act as upstream regulators in the modulation of biological pathways relevant to PD. Intriguingly, IL6 stands out as a master gene regulator since it may indirectly regulate the network of interconnected genes. The study highlighted different genes and miRNAs interactions potentially involved in PD physiopathology, which are worth to be further explored to improve the knowledge of disease and the research of novel treatments strategies.

Genetic Determinants Highlight the Existence of Shared Etiopathogenetic Mechanisms Characterizing Age-Related Macular Degeneration and Neurodegenerative Disorders

Age-related macular degeneration (AMD) showed several processes and risk factors in common with neurodegenerative disorders (NDDs). The present work explored the existence of genetic determinants associated with AMD, which may provide insightful clues concerning its relationship with NDDs and their possible application into the clinical practice. In this study, 400 AMD patients were subjected to the genotyping analysis of 120 genetic variants by OpenArray technology. As the reference group, 503 samples representative of the European general population were utilized. Statistical analysis revealed the association of 23 single-nucleotide polymorphisms (SNPs) with AMD risk. The analysis of epistatic effects revealed that ARMS2, IL6, APOE, and IL2RA could contribute to AMD and neurodegenerative processes by synergistic modulation of the expression of disease-relevant genes. In addition, the bioinformatic analysis of the associated miRNA variants highlighted miR-196a, miR-6796, miR-6499, miR-6810, miR-499, and miR-7854 as potential candidates for counteracting AMD and neurodegenerative processes. Finally, this work highlighted the existence of shared disease mechanisms (oxidative stress, immune-inflammatory response, mitochondrial dysfunction, axonal guidance pathway, and synaptogenesis) between AMD and NDDs and described the associated SNPs as candidate biomarkers for developing novel strategies for early diagnosis, monitoring, and treatment of such disorders in a progressive aging population.

Genetic Counselling Improves the Molecular Characterisation of Dementing Disorders

Dementing disorders are a complex group of neurodegenerative diseases characterised by different, but often overlapping, pathological pathways. Genetics have been largely associated with the development or the risk to develop dementing diseases. Recent advances in molecular technologies permit analyzing of several genes in a small time, but the interpretation analysis is complicated by several factors: the clinical complexity of neurodegenerative disorders, the frequency of co-morbidities, and the high phenotypic heterogeneity of genetic diseases. Genetic counselling supports the diagnostic path, providing an accurate familial and phenotypic characterisation of patients. In this review, we summarise neurodegenerative dementing disorders and their genetic determinants. Genetic variants and associated phenotypes will be divided into high and low impact, in order to reflect the pathologic continuum between multifactorial and mendelian genetic factors. Moreover, we report a molecular characterisation of genes associated with neurodegenerative disorders with cognitive impairment. In particular, the high frequency of rare coding genetic variants in dementing genes strongly supports the role of geneticists in both, clinical phenotype characterisation and interpretation of genotypic data. The smart application of exome analysis to dementia patients, with a pre-analytical selection on familial, clinical, and instrumental features, improves the diagnostic yield of genetic test, reduces time for diagnosis, and allows a rapid and personalised management of disease.

Multi-Layer Picture of Neurodegenerative Diseases: Lessons from the Use of Big Data through Artificial Intelligence

In the big data era, artificial intelligence techniques have been applied to tackle traditional issues in the study of neurodegenerative diseases. Despite the progress made in understanding the complex (epi)genetics signatures underlying neurodegenerative disorders, performing early diagnosis and developing drug repurposing strategies remain serious challenges for such conditions. In this context, the integration of multi-omics, neuroimaging, and electronic health records data can be exploited using deep learning methods to provide the most accurate representation of patients possible. Deep learning allows researchers to find multi-modal biomarkers to develop more effective and personalized treatments, early diagnosis tools, as well as useful information for drug discovering and repurposing in neurodegenerative pathologies. In this review, we will describe how relevant studies have been able to demonstrate the potential of deep learning to enhance the knowledge of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases through the integration of all sources of biomedical data.

Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort

Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling-associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

Review of nanotheranostics for molecular mechanisms underlying psychiatric disorders and commensurate nanotherapeutics for neuropsychiatry: The mind knockout

Bio-neuronal led psychiatric abnormalities transpired by the loss of neuronal structure and function (neurodegeneration), pro-inflammatory cytokines, microglial dysfunction, altered neurotransmission, toxicants, serotonin deficiency, kynurenine pathway, and excessively produced neurotoxic substances. These uncontrolled happenings in the etiology of psychiatric disorders initiate further changes in neurotransmitter metabolism, pathologic microglial, cell activation, and impaired neuroplasticity. Inflammatory cytokines, the outcome of dysfunctional mitochondria, dysregulation of the immune system, and under stress functions of the brain are leading biochemical factors for depression and anxiety. Nanoscale drug delivery platforms, inexpensive diagnostics using nanomaterials, nano-scale imaging technologies, and ligand-conjugated nanocrystals used for elucidating the molecular mechanisms and foremost cellular communications liable for such disorders are highly capable features to study for efficient diagnosis and therapy of the mental illness. These theranostic tools made up of multifunctional nanomaterials have the potential for effective and accurate diagnosis, imaging of psychiatric disorders, and are at the forefront of leading technologies in nanotheranostics openings field as they can collectively and efficiently target the stimulated territories of the cerebellum (cells and tissues) through molecular-scale interactions with higher bioavailability, and bio-accessibility. Specifically, the nanoplatforms based neurological changes are playing a significant role in the diagnosis of psychiatric disorders and portraying the routes of functional restoration of mental disorders by newer imaging tools at nano-level in all directions. Because of these nanotherapeutic platforms, the molecules of nanomedicine can penetrate the Blood-Brain Barrier with an increased half-life of drug molecules. The discoveries in nanotheranostics and nanotherapeutics inbuilt unique multi-functionalities are providing the best multiplicities of novel nanotherapeutic potentialities with no toxicity concerns at the level of nano range.

Refining in vitro and in silico neurotoxicity approaches by accounting for interspecies and interindividual differences in toxicodynamics

INTRODUCTION

The process of chemical risk assessment traditionally relies on animal experiments and associated default uncertainty factors to account for interspecies and interindividual differences. To work toward a more precise and personalized risk assessment, these uncertainty factors should be refined and replaced by chemical-specific adjustment factors (CSAFs).

AREAS COVERED

This concise review discusses alternative (in vitro/in silico) approaches that can be used to assess interspecies and interindividual differences in toxicodynamics, ranging from targeted to more integrated approaches. Although data are available on interspecies differences, the increasing use of human-induced pluripotent stem cell (hiPSC)-derived neurons may provide opportunities to also assess interindividual variability in neurotoxicity. More integrated approaches, like adverse outcome pathways (AOPs) can provide a more quantitative understanding of the toxicodynamics of a chemical.

EXPERT OPINION

To improve chemical risk assessment, refinement of uncertainty factors is crucial. In vitro and in silico models can facilitate the development of CSAFs, but still these models cannot always capture the complexity of the in vivo situation, thereby potentially hampering regulatory acceptance. The combined use of more integrated approaches, like AOPs and physiologically based kinetic models, can aid in structuring data and increasing suitability of alternative approaches for regulatory purposes.

Investigation of Genetic Variations of IL6 and IL6R as Potential Prognostic and Pharmacogenetics Biomarkers: Implications for COVID-19 and Neuroinflammatory Disorders

In the present study, we investigated the distribution of genetic variations in IL6 and IL6R genes, which may be employed as prognostic and pharmacogenetic biomarkers for COVID-19 and neurodegenerative diseases. The study was performed on 271 samples representative of the Italian general population and identified seven variants (rs140764737, rs142164099, rs2069849, rs142759801, rs190436077, rs148171375, rs13306435) in IL6 and five variants (rs2228144, rs2229237, rs2228145, rs28730735, rs143810642) within IL6R, respectively. These variants have been predicted to affect the expression and binding ability of IL6 and IL6R. Ingenuity Pathway Analysis (IPA) showed that IL6 and IL6R appeared to be implicated in several pathogenetic mechanisms associated with COVID-19 severity and mortality as well as with neurodegenerative diseases mediated by neuroinflammation. Thus, the availability of IL6-IL6R-related biomarkers for COVID-19 may be helpful to counteract harmful complications and prevent multiorgan failure. At the same time, IL6-IL6R-related biomarkers could also be useful for assessing the susceptibility and progression of neuroinflammatory disorders and undertake the most suitable treatment strategies to improve patients' prognosis and quality of life. In conclusion, this study showed how IL6 pleiotropic activity could be exploited to meet different clinical needs and realize personalized medicine protocols for chronic, age-related and modern public health emergencies.

Overview of the molecular determinants contributing to the expression of Psoriasis and Psoriatic Arthritis phenotypes

Psoriasis and psoriatic arthritis are multifactorial chronic disorders whose etiopathogenesis essentially derives from the alteration of several signalling pathways and the co-occurrence of genetic, epigenetic and non-genetic susceptibility factors that altogether affect the functional and structural property of the skin. Although shared and differential susceptibility genes and molecular pathways are known to contribute to the onset of pathological phenotypes, further research is needed to dissect the molecular causes of psoriatic disease and its progression towards Psoriatic Arthritis. This review will therefore be addressed to explore differences and similarities in the etiopathogenesis and progression of both disorders, with a particular focus on genes involved in the maintenance of the skin structure and integrity (keratins and collagens), modulation of patterns of recognition (through Toll-like receptors and dectin-1) and immuno-inflammatory response (by NLRP3-dependent inflammasome) to microbial pathogens. In addition, special emphasis will be given to the contribution of epigenetic elements (methylation pattern, non-coding RNAs, chromatin modifiers and 3D genome organization) to the etiopathogenesis and progression of psoriasis and psoriatic arthritis. The evidence discussed in this review highlights how the knowledge of patients' clinical and (epi)genomic make-up could be helpful for improving the available therapeutic strategies for psoriasis and psoriatic arthritis treatment.

Precision Medicine in Rare Diseases

Rare diseases are those that have a low prevalence in the population (less than 5 individuals per 10,000 inhabitants). However, infrequent pathologies affect a large number of people, since according to the World Health Organization (WHO), there are about 7000 rare diseases that affect 7% of the world’s population. Many patients with rare diseases have suffered the consequences of what is called the diagnostic odyssey, that is, extensive and prolonged serial tests and clinical visits, sometimes for many years, all with the hope of identifying the etiology of their disease. For patients with rare diseases, obtaining the genetic diagnosis can mean the end of the diagnostic odyssey, and the beginning of another, the therapeutic odyssey. This scenario is especially challenging for the scientific community, since more than 90% of rare diseases do not currently have an effective treatment. This therapeutic failure in rare diseases means that new approaches are necessary. Our research group proposes that the use of precision or personalized medicine techniques can be an alternative to find potential therapies in these diseases. To this end, we propose that patients’ own cells can be used to carry out personalized pharmacological screening for the identification of potential treatments.

Pharmacogenetic profile and the development of the dyskinesia induced by levodopa-therapy in Parkinson's disease patients: a population-based cohort study

Levodopa-induced dyskinesia (LID) is an adverse effect that negatively impacts the quality of life of patients with Parkinson's disease (PD). Studies report that genetic variations in the genes of the pharmacogenetic pathway of the levodopa (L-DOPA) might be associated with LID development. The goal of the present study was to investigate a possible influence of functional genetic variants in the DRD1 (rs4532), DRD2 (rs1800497), DAT1 (rs28363170), and COMT (rs4680) genes with LID development. A total of 220 patients with idiopathic PD were enrolled. The genotyping for DRD1 (rs4532), DRD2 (rs1800497), DAT1 (rs28363170), and COMT (rs4680) polymorphisms were performed using Restriction Fragment Length Polymorphism (PCR-RFLP). Univariate and multivariate analyses were performed to assess the association of these polymorphisms and risk factors with LID development. Multivariate Cox regression analysis showed increased risk to LID development for both Levodopa Dose Equivalency (LED) (Hazard ratios (HR) = 1.001; 95% CI 1.00-1.01; p = 0.009) and individuals carrying the COMT L/L genotype (HR = 2.974; 95% CI 1.12-7.83; p = 0.010). Furthermore, when performed a Cox regression analysis adjusted for a total LED, we observed that the genotype COMT L/L had a 3.84-fold increased risk for LID development (HR = 3.841; 95% CI 1.29-11.37; p = 0.012). Our results suggest that before treating LID in PD patients, it is important to take into consideration genetic variant in the COMT gene, since COMT LL genotype may increase the risk for LID development.

Clustering of Alzheimer's and Parkinson's disease based on genetic burden of shared molecular mechanisms

One of the visions of precision medicine has been to re-define disease taxonomies based on molecular characteristics rather than on phenotypic evidence. However, achieving this goal is highly challenging, specifically in neurology. Our contribution is a machine-learning based joint molecular subtyping of Alzheimer's (AD) and Parkinson's Disease (PD), based on the genetic burden of 15 molecular mechanisms comprising 27 proteins (e.g. APOE) that have been described in both diseases. We demonstrate that our joint AD/PD clustering using a combination of sparse autoencoders and sparse non-negative matrix factorization is reproducible and can be associated with significant differences of AD and PD patient subgroups on a clinical, pathophysiological and molecular level. Hence, clusters are disease-associated. To our knowledge this work is the first demonstration of a mechanism based stratification in the field of neurodegenerative diseases. Overall, we thus see this work as an important step towards a molecular mechanism-based taxonomy of neurological disorders, which could help in developing better targeted therapies in the future by going beyond classical phenotype based disease definitions.

Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort

Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling-associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

Characterization of Recessive Parkinson Disease in a Large Multicenter Study

Studies of the phenotype and population distribution of rare genetic forms of parkinsonism are required, now that gene-targeting approaches for Parkinson disease have reached the clinical trial stage. We evaluated the frequencies of PRKN, PINK1, and DJ-1 mutations in a cohort of 1,587 cases. Mutations were found in 14.1% of patients; 27.6% were familial and 8% were isolated. PRKN was the gene most frequently mutated in Caucasians, whereas PINK1 mutations predominated in Arab-Berber individuals. Patients with PRKN mutations had an earlier age at onset, and less asymmetry, levodopa-induced motor complications, dysautonomia, and dementia than those without mutations. ANN NEUROL 2020;88:843-850.

Precision and Personalized Medicine: How Genomic Approach Improves the Management of Cardiovascular and Neurodegenerative Disease

Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represent suitable models for taking full advantage of precision medicine technologies applied to all stages of disease development. The availability of high technology incorporating artificial intelligence and advancement progress made in the field of biomedical research have been substantial to understand how genes, epigenetic modifications, aging, nutrition, drugs, microbiome and other environmental factors can impact health and chronic disorders. The aim of the present review is to address how precision and personalized medicine can bring greater clarity to the clinical and biological complexity of these types of disorders associated with high mortality, involving tremendous health care costs, by describing in detail the methods that can be applied. This might offer precious tools for preventive strategies and possible clues on the evolution of the disease and could help in predicting morbidity, mortality and detecting chronic disease indicators much earlier in the disease course. This, of course, will have a major effect on both improving the quality of care and quality of life of the patients and reducing time efforts and healthcare costs.

Preventive Role of L-Carnitine and Balanced Diet in Alzheimer's Disease

The prevention or alleviation of neurodegenerative diseases, including Alzheimer's disease (AD), is a challenge for contemporary health services. The aim of this study was to review the literature on the prevention or alleviation of AD by introducing an appropriate carnitine-rich diet, dietary carnitine supplements and the MIND (Mediterranean-DASH Intervention for Neurodegenerative Delay) diet, which contains elements of the Mediterranean diet and the Dietary Approaches to Stop Hypertension (DASH) diet. L-carnitine (LC) plays a crucial role in the energetic metabolism of the cell. A properly balanced diet contains a substantial amount of LC as well as essential amino acids and microelements taking part in endogenous carnitine synthesis. In healthy people, carnitine biosynthesis is sufficient to prevent the symptoms of carnitine deficiency. In persons with dysfunction of mitochondria, e.g., with AD connected with extensive degeneration of the brain structures, there are often serious disturbances in the functioning of the whole organism. The Mediterranean diet is characterized by a high consumption of fruits and vegetables, cereals, nuts, olive oil, and seeds as the major source of fats, moderate consumption of fish and poultry, low to moderate consumption of dairy products and alcohol, and low intake of red and processed meat. The introduction of foodstuffs rich in carnitine and the MIND diet or carnitine supplementation of the AD patients may improve their functioning in everyday life.

The variability of SMCHD1 gene in FSHD patients: evidence of new mutations

In this study, we investigated the sequence of (Structural Maintenance of Chromosomes flexible Hinge Domain containing 1) SMCHD1 gene in a cohort of clinically defined FSHD (facioscapulohumeral muscular dystrophy) patients in order to assess the distribution of SMCHD1 variants, considering the D4Z4 fragment size in terms of repeated units (RUs; short fragment: 1–7 RU, borderline: 8-10RU and normal fragment: >11RU). The analysis of SMCHD1 revealed the presence of 82 variants scattered throughout the introns, exons and 3’untranslated region (3′UTR) of the gene. Among them, 64 were classified as benign polymorphisms and 6 as VUS (variants of uncertain significance). Interestingly, seven pathogenic/likely pathogenic variants were identified in patients carrying a borderline or normal D4Z4 fragment size, namely c.182_183dupGT (p.Q62Vfs^*48), c.2129dupC (p.A711Cfs^*11), c.3469G>T (p.G1157^*), c.5150_5151delAA (p.K1717Rfs^*16) and c.1131+2_1131+5delTAAG, c.3010A>T (p.K1004^*), c.853G>C (p.G285R). All of them were predicted to disrupt the structure and conformation of SMCHD1, resulting in the loss of GHKL-ATPase and SMC hinge essential domains. These results are consistent with the FSHD symptomatology and the Clinical Severity Score (CSS) of patients. In addition, five variants (c.^*1376A>C, rs7238459; c.^*1579G>A, rs559994; c.^*1397A>G, rs150573037; c.^*1631C>T, rs193227855; c.^*1889G>C, rs149259359) were identified in the 3′UTR region of SMCHD1, suggesting a possible miRNA-dependent regulatory effect on FSHD-related pathways. The present study highlights the clinical utility of next-generation sequencing (NGS) platforms for the molecular diagnosis of FSHD and the importance of integrating molecular findings and clinical data in order to improve the accuracy of genotype–phenotype correlations.

Shared (epi)genomic background connecting neurodegenerative diseases and type 2 diabetes

The progressive aging of populations has resulted in an increased prevalence of chronic pathologies, especially of metabolic, neurodegenerative and movement disorders. In particular, type 2 diabetes (T2D), Alzheimer’s disease (AD) and Parkinson’s disease (PD) are among the most prevalent age-related, multifactorial pathologies that deserve particular attention, given their dramatic impact on patient quality of life, their economic and social burden as well the etiopathogenetic mechanisms, which may overlap in some cases. Indeed, the existence of common triggering factors reflects the contribution of mutual genetic, epigenetic and environmental features in the etiopathogenetic mechanisms underlying T2D and AD/PD. On this subject, this review will summarize the shared (epi)genomic features that characterize these complex pathologies. In particular, genetic variants and gene expression profiles associated with T2D and AD/PD will be discussed as possible contributors to determine the susceptibility and progression to these disorders. Moreover, potential shared epigenetic modifications and factors among T2D, AD and PD will also be illustrated. Overall, this review shows that findings from genomic studies still deserves further research to evaluate and identify genetic factors that directly contribute to the shared etiopathogenesis. Moreover, a common epigenetic background still needs to be investigated and characterized. The evidences discussed in this review underline the importance of integrating large-scale (epi)genomic data with additional molecular information and clinical and social background in order to finely dissect the complex etiopathogenic networks that build up the “disease interactome” characterizing T2D, AD and PD.

Genetic Counseling and NGS Screening for Recessive LGMD2A Families

Genetic counseling applied to limb–girdle muscular dystrophies (LGMDs) can be very challenging due to their clinical and genetic heterogeneity and the availability of different molecular assays. Genetic counseling should therefore be addressed to select the most suitable approach to increase the diagnostic rate and provide an accurate estimation of recurrence risk. This is particularly true for families with a positive history for recessive LGMD, in which the presence of a known pathogenetic mutation segregating within the family may not be enough to exclude the risk of having affected children without exploring the genetic background of phenotypically unaffected partners. In this work, we presented a family with a positive history for LGMD2A (OMIM #253600, also known as calpainopathy) characterized by compound heterozygosity for two CAPN3 mutations. The genetic specialist suggested the segregation analysis of both mutations within the family as a first-level analysis. Sequentially, next-generation sequencing (NGS) analysis was performed in the partners of healthy carriers to provide an accurate recurrence/reproductive risk estimation considering the genetic background of the couple. Finally, this work highlighted the importance of providing a genetic counseling/testing service even in unaffected individuals with a carrier partner. This approach can support genetic counselors in estimating the reproductive/recurrence risk and eventually, suggesting prenatal testing, early diagnosis or other medical surveillance strategies.

RNAseq-Based Prioritization Revealed COL6A5, COL8A1, COL10A1 and MIR146A as Common and Differential Susceptibility Biomarkers for Psoriasis and Psoriatic Arthritis: Confirmation from Genotyping Analysis of 1417 Italian Subjects

Psoriasis (Ps) and Psoriatic Arthritis (PsA) are characterized by a multifactorial etiology, involving genetic and environmental factors. The present study aimed to investigate polymorphisms (SNPs) within genes involved in extracellular matrix and cell homeostasis and microRNA genes as susceptibility biomarkers for Ps and PsA. Bioinformatic analysis on public RNA-seq data allowed for selection of rs12488457 (A/C, COL6A5), rs13081855 (G/T, COL8A1), rs3812111 (A/T, COL10A1) and rs2910164 (C/G, MIR146A) as candidate biomarkers. These polymorphisms were analyzed by Real-Time PCR in a cohort of 1417 Italian patients (393 Ps, 424 PsA, 600 controls). Statistical and bioinformatic tools were utilized for assessing the genetic association and predicting the effects of the selected SNPs. rs12488457, rs13081855 and rs2910164 were significantly associated with both Ps (p = 1.39 × 10⁻⁸, p = 4.52 × 10⁻⁴, p = 0.04, respectively) and PsA (p = 5.12 × 10⁻⁵, p = 1.19 × 10⁻⁶, p = 0.01, respectively). rs3812111, instead, was associated only with PsA (p = 0.005). Bioinformatic analysis revealed common and differential biological pathways involved in Ps and PsA. COL6A5 and COL8A1 take part in the proliferation and angiogenic pathways which are altered in Ps/PsA and contribute to inflammation together with MIR146A. On the other hand, the exclusive association of COL10A1 with PsA highlighted the specific involvement of bone metabolism in PsA.

The shift of the paradigm between ageing and diseases

In the area of the Medical Sciences, the chronological age has always been, and still is, an indicator by which we try to understand the health status of an individual. However, besides considering people born with an already expressed disease, each human genome has sequence alterations called predisposing mutations; carriers of such genetic alterations have an increased risk of contracting diseases during their life. In addition, the exposome, i.e. the totality of environmental noxae (“hits”) to which our body is exposed throughout life (through ingestion, breathing, body surface hits, and psychosociological stress agents, etc.) contributes to increase gradually but inexorably the frailty of an organism, and this process is usually referred to as “physiological ageing”. This position paper proposes that we invert our visual angle and view the passage-of-time not as the cause of diseases, but consider the genome alterations present at birth and the noxae received during our life as the real major causes of ageing. The Biomedical Sciences are now increasingly unraveling the etiopathogenesis of most chronic degenerative diseases; thus, it will be possible to monitor and treat those that most contribute to the increased frailty of each person, which is now referred to with the misnomer “physiological ageing”. These concepts are not banal; indeed, they imply that we must try to avoid the causes of alterations that result later in chronic degenerative diseases. Thus, we should shift our attention from the cure to the prevention of alterations/diseases also to improve both the length and quality of our life. Moreover, this approach involves real personalized or individualized medicine, thus conferring a more direct benefit to each of us by finalizing either the cure or the monitoring of diseases.

Exploring Alzheimer's Disease Molecular Variability via Calculation of Personalized Transcriptional Signatures

Despite huge investments and major efforts to develop remedies for Alzheimer’s disease (AD) in the past decades, AD remains incurable. While evidence for molecular and phenotypic variability in AD have been accumulating, AD research still heavily relies on the search for AD-specific genetic/protein biomarkers that are expected to exhibit repetitive patterns throughout all patients. Thus, the classification of AD patients to different categories is expected to set the basis for the development of therapies that will be beneficial for subpopulations of patients. Here we explore the molecular heterogeneity among a large cohort of AD and non-demented brain samples, aiming to address the question whether AD-specific molecular biomarkers can progress our understanding of the disease and advance the development of anti-AD therapeutics. We studied 951 brain samples, obtained from up to 17 brain regions of 85 AD patients and 22 non-demented subjects. Utilizing an information-theoretic approach, we deciphered the brain sample-specific structures of altered transcriptional networks. Our in-depth analysis revealed that 7 subnetworks were repetitive in the 737 diseased and 214 non-demented brain samples. Each sample was characterized by a subset consisting of ~1–3 subnetworks out of 7, generating 52 distinct altered transcriptional signatures that characterized the 951 samples. We show that 30 different altered transcriptional signatures characterized solely AD samples and were not found in any of the non-demented samples. In contrast, the rest of the signatures characterized different subsets of sample types, demonstrating the high molecular variability and complexity of gene expression in AD. Importantly, different AD patients exhibiting similar expression levels of AD biomarkers harbored distinct altered transcriptional networks. Our results emphasize the need to expand the biomarker-based stratification to patient-specific transcriptional signature identification for improved AD diagnosis and for the development of subclass-specific future treatment.