AI-Powered Neurogenetics: Supporting Patient's Evaluation with Chatbot.

Background/objectives: Artificial intelligence and large language models like ChatGPT and Google's Gemini are promising tools with remarkable potential to assist healthcare professionals. This study explores ChatGPT and Gemini's potential utility in assisting clinicians during the first evaluation of patients with suspected neurogenetic disorders.

Methods: By analyzing the model's performance in identifying relevant clinical features, suggesting differential diagnoses, and providing insights into possible genetic testing, this research seeks to determine whether these AI tools could serve as a valuable adjunct in neurogenetic assessments.

Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring.

: Centralizing genetic sequencing in specialized facilities is pivotal for reducing the costs associated with diagnostic testing. These centers must be able to verify data quality and ensure sample integrity. This study aims at developing a protocol for tracking NGS-analyzed samples to prevent errors and mix-ups, ensuring proper quality control, accuracy, and reliability in genetic testing procedures.

Federated Learning: Breaking Down Barriers in Global Genomic Research.

Recent advancements in Next-Generation Sequencing (NGS) technologies have revolutionized genomic research, presenting unprecedented opportunities for personalized medicine and population genetics. However, issues such as data silos, privacy concerns, and regulatory challenges hinder large-scale data integration and collaboration. Federated Learning (FL) has emerged as a transformative solution, enabling decentralized data analysis while preserving privacy and complying with regulations such as the General Data Protection Regulation (GDPR).

Deciphering the Complexity of FSHD: A Multimodal Approach as a Model for Rare Disorders.

Rare diseases are heterogeneous diseases characterized by various symptoms and signs. Due to the low prevalence of such conditions (less than 1 in 2000 people), medical expertise is limited, knowledge is poor and patients' care provided by medical centers is inadequate. An accurate diagnosis is frequently challenging and ongoing research is also insufficient, thus complicating the understanding of the natural progression of the rarest disorders.

Variants and Autosomal Dominant Retinitis Pigmentosa: Insights from the Italian Genetic Landscape.

Autosomal dominant retinitis pigmentosa (AD-RP) is caused by several genes, among which is one of the most investigated. This article will be focused on and its role in explaining AD-RP cases in the Italian population, taking advantage of the experience of the Genomic Medicine Laboratory UILDM at the Santa Lucia Foundation IRCCS. The retrospective evaluation of the distribution of variants in the Italian patients with a clinical suspicion of RP pointed out eight variants.

Innovations in Medicine: Exploring ChatGPT's Impact on Rare Disorder Management.

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use, ChatGPT holds a prominent position, using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for generating human-like responses to queries.

Characterization of D4Z4 alleles and assessment of de novo cases in Facioscapulohumeral dystrophy (FSHD) in a cohort of Italian families.

Facioscapulohumeral dystrophy (FSHD) is an autosomal dominant disease, although 10%-30% of cases are sporadic. However, this percentage may include truly de novo patients (carrying a reduced D4Z4 allele that is not present in either of the parents) and patients with apparently sporadic disease resulting from mosaicism, non-penetrance, or complex genetic situations in either patients or parents. In this study, we characterized the D4Z4 Reduced Alleles (DRA) and evaluated the frequency of truly de novo cases in FSHD1 in a cohort of DNA samples received consecutively for FSHD-diagnostic from 100 Italian families.

Long-Term Structural and Functional Assessment of Doyne Honeycomb Retinal Dystrophy following Nanosecond 2RT Laser Treatment: A Case Series.

Introduction: Doyne honeycomb retinal dystrophy (DHRD), or autosomal dominant radial drusen, is a genetic disease caused by pathogenic variants of the epidermal growth factor (EGF)-containing fibulin-like extracellular matrix protein 1 gene and is characterized by the formation of subretinal drusenoid deposits. In a previous study, we reported the short-term beneficial effects of nanosecond laser treatment (2RT) on retinal function in DHRD. The aim of the present report was to describe the findings of a long-term follow-up of retinal structure/function in a small case series of patients with DHRD who underwent 2RT treatment.

A Splicing Variant in RDH8 Is Associated with Autosomal Recessive Stargardt Macular Dystrophy.

Stargardt macular dystrophy is a genetic disorder, but in many cases, the causative gene remains unrevealed. Through a combined approach (whole-exome sequencing and phenotype/family-driven filtering algorithm) and a multilevel validation (international database searching, prediction scores calculation, splicing analysis assay, segregation analyses), a biallelic mutation in the gene was identified to be responsible for Stargardt macular dystrophy in a consanguineous Italian family. This paper is a report on the first family in which a biallelic deleterious mutation in is detected.

Epigenetic profiling of the D4Z4 locus: Optimization of the protocol for studying DNA methylation at single CpG site level.

The alteration of epigenetic modifications, including DNA methylation, can contribute to the etiopathogenesis and progression of many diseases. Among them, facioscapulohumeral dystrophy (FSHD) is a muscular disorder characterized by the loss of repressive epigenetic features affecting the D4Z4 locus (4q35). As a consequence, these alterations are responsible for DNA hypomethylation and a transcriptional-active chromatin conformation change that, in turn, lead to the aberrant expression of DUX4 in muscle cells.

NIPAT as Non-Invasive Prenatal Paternity Testing Using a Panel of 861 SNVs.

In 1997, it was discovered that maternal plasma contains Cell-Free Fetal DNA (cffDNA). cffDNA has been investigated as a source of DNA for non-invasive prenatal testing for fetal pathologies, as well as for non-invasive paternity testing. While the advent of Next Generation Sequencing (NGS) led to the routine use of Non-Invasive Prenatal Screening (NIPT or NIPS), few data are available regarding the reliability and reproducibility of Non-Invasive Prenatal Paternity Testing (NIPPT or NIPAT).

Longitudinal Structure-Function Evaluation in a Patient with -Associated Retinal Dystrophy: Progressive Visual Function Loss with Retinal Remodeling.

Background: Retinal dystrophies related to damaging variants in the cadherin-related family member 1 () gene are rare and phenotypically heterogeneous. Here, we report a longitudinal (three-year) structure-function evaluation of a patient with a -related retinal dystrophy.

Methods: A 14-year-old girl was evaluated between 2019 and 2022.

Analysis of Genetic Variants Associated with COVID-19 Outcome Highlights Different Distributions among Populations.

The clinical spectrum of SARS-CoV-2 infection ranges from asymptomatic status to mild infections, to severe disease and death. In this context, the identification of specific susceptibility factors is crucial to detect people at the higher risk of severe disease and improve the outcome of COVID-19 treatment. Several studies identified genetic variants conferring higher risk of SARS-CoV-2 infection and COVID-19 severity.

Update on the Molecular Aspects and Methods Underlying the Complex Architecture of FSHD.

Despite the knowledge of the main mechanisms involved in facioscapulohumeral muscular dystrophy (FSHD), the high heterogeneity and variable penetrance of the disease complicate the diagnosis, characterization and genotype-phenotype correlation of patients and families, raising the need for further research and data. Thus, the present review provides an update of the main molecular aspects underlying the complex architecture of FSHD, including the genetic factors (related to repeated units and FSHD-associated genes), epigenetic elements ( methylation status, non-coding RNAs and high-order chromatin interactions) and gene expression profiles (FSHD transcriptome signatures both at bulk tissue and single-cell level). In addition, the review will also describe the methods currently available for investigating the above-mentioned features and how the resulting data may be combined with artificial-intelligence-based pipelines, with the purpose of developing a multifunctional tool tailored to enhancing the knowledge of disease pathophysiology and progression and fostering the research for novel treatment strategies, as well as clinically useful biomarkers.

Relationship between Nutrition, Lifestyle, and Neurodegenerative Disease: Lessons from , and .

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.

WARE: Wet AMD Risk-Evaluation Tool as a Clinical Decision-Support System Integrating Genetic and Non-Genetic Factors.

Given the multifactorial features characterizing age-related macular degeneration (AMD), the availability of a tool able to provide the individual risk profile is extremely helpful for personalizing the follow-up and treatment protocols of patients. To this purpose, we developed an open-source computational tool named WARE (Wet AMD Risk Evaluation), able to assess the individual risk profile for wet AMD based on genetic and non-genetic factors. In particular, the tool uses genetic risk measures normalized for their relative frequencies in the general population and disease prevalence.

A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson's Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples.

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson’s disease (PD) heterogeneity among individuals proves the existence of disease subtypes, so subgrouping patients is vital for better understanding disease mechanisms and designing precise treatment. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis.

Identification of Genetic Networks Reveals Complex Associations and Risk Trajectory Linking Mild Cognitive Impairment to Alzheimer's Disease.

Amnestic mild cognitive impairment (aMCI) and sporadic Alzheimer's disease (AD) are multifactorial conditions resulting from a complex crosstalk among multiple molecular and biological processes. The present study investigates the association of variants localized in genes and miRNAs with aMCI and AD, which may represent susceptibility, prognostic biomarkers or multi-target treatment options for such conditions. We included 371 patients (217 aMCI and 154 AD) and 503 healthy controls, which were genotyped for a panel of 120 single nucleotide polymorphisms (SNPs) and, subsequently, analyzed by statistical, bioinformatics and machine-learning approaches.

Tracking the Initial Diffusion of SARS-CoV-2 Omicron Variant in Italy by RT-PCR and Comparison with Alpha and Delta Variants Spreading.

The emergence of the Omicron SARS-CoV-2 variant caused public health concerns worldwide, raising the need for the improvement of rapid monitoring strategies. The present manuscript aimed at providing evidence of the utility of a diagnostic kit for the routine testing of SARS-CoV-2 infection as a cost-effective method for tracking the Omicron variant in Italy. The study was conducted on patients' naso-oropharyngeal-swab-derived RNA samples.

Epigenomic signatures in age-related macular degeneration: Focus on their role as disease modifiers and therapeutic targets.

Epigenetics is characterized by molecular modifications able to shape gene expression profiles in response to inner and external stimuli. Therefore, epigenetic elements are able to provide intriguing and useful information for the comprehension and management of different human conditions, including aging process, and diseases. On this subject, Age-related Macular Degeneration (AMD) represents one of the most frequent age-related disorders, dramatically affecting the quality of life of older adults worldwide.

Age and Sex Modulate SARS-CoV-2 Viral Load Kinetics: A Longitudinal Analysis of 1735 Subjects.

The COVID-19 pandemic caused by SARS-CoV-2 represents a public health emergency, which became even more challenging since the detection of highly transmissible variants and strategies against COVID-19 were indistinctly established. We characterized the temporal viral load kinetics in individuals infected by original and variant strains. Naso-oropharyngeal swabs from 33,000 individuals (admitted to the IRCCS Santa Lucia Foundation Drive-in, healthcare professionals and hospitalized patients who underwent routinary screening) from November 2020 to June 2021 were analyzed.