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. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT integration, with pilot studies and trials revealing each field's potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex datasets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs.

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. The D4Z4 testing revealed that 60 families reported a DRA compatible with FSHD1 (1-10 RU). The DRA co-segregated with the disease in most cases. Five families with truly de novo cases were identified, suggesting that this condition may be slightly lower (8%) than previously reported. In addition, D4Z4 characterization in the investigated families showed 4% of mosaic cases and 2% with translocations. This study further highlighted the importance of performing family studies for clarifying apparently sporadic FSHD cases, with significant implications for genetic counseling, diagnosis, clinical management, and procreative choices for patients and 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 EFEMP1 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. Case Presentation: Three DHRD patients (case 1, male and cases 2 and 3, two sister females, age range 41-46) with EFEMP1 pathogenic variant (c.1033C>T; p.R345W) and drusenoid deposits at the posterior pole were examined at baseline and after 2RT treatment, at regular intervals (every 2-4 months) up to 30 months. All 3 patients underwent one or two treatment sessions in one or both eyes during the follow-up period. Case 3 was treated with only the left eye (LE). Each patient underwent a full ophthalmologic examination, spectral domain optical coherence tomography (OCT), central perimetry with frequency doubling technology, and mesopic and photopic Ganzfeld electroretinograms. Compared to baseline findings, during follow-up, visual acuity improved in both eyes in case 1 and LE in case 2, while it decreased in the right eye in case 2 and LE in case 3; perimetric sensitivity was stable in case 1 and improved in both eyes in cases 2 and 3; and electroretinogram amplitude improved in cases 1 and 2 and was stable in case 3 (both eyes). OCT central macular thickness and retinal structure were stable in all cases. None of the patients had treatment-related side effects. Conclusion: This is the first report showing that in a long-term follow-up, 2RT treatment in DHRD may improve or stabilize some retinal function parameters without significant structural changes.

Whole exome sequencing highlights rare variants in CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1 as associated with FSHD.

Introduction: Despite the progress made in the study of Facioscapulohumeral Dystrophy (FSHD), the wide heterogeneity of disease complicates its diagnosis and the genotype-phenotype correlation among patients and within families. In this context, the present work employed Whole Exome Sequencing (WES) to investigate known and unknown genetic contributors that may be involved in FSHD and may represent potential disease modifiers, even in presence of a D4Z4 Reduced Allele (DRA). Methods: A cohort of 126 patients with clinical signs of FSHD were included in the study, which were characterized by D4Z4 sizing, methylation analysis and WES. Specific protocols were employed for D4Z4 sizing and methylation analysis, whereas the Illumina® Next-Seq 550 system was utilized for WES. The study included both patients with a DRA compatible with FSHD diagnosis and patients with longer D4Z4 alleles. In case of patients harboring relevant variants from WES, the molecular analysis was extended to the family members. Results: The WES data analysis highlighted 20 relevant variants, among which 14 were located in known genetic modifiers (SMCHD1, DNMT3B and LRIF1) and 6 in candidate genes (CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1). Most of them were found together with a permissive short (4-7 RU) or borderline/long DRA (8-20 RU), supporting the possibility that different genes can contribute to disease heterogeneity in presence of a FSHD permissive background. The segregation and methylation analysis among family members, together with clinical findings, provided a more comprehensive picture of patients. Discussion: Our results support FSHD pathomechanism being complex with a multigenic contribution by several known (SMCHD1, DNMT3B, LRIF1) and possibly other candidate genes (CTCF, DNMT1, DNMT3A, EZH2, SUV39H1) to disease penetrance and expressivity. Our results further emphasize the importance of extending the analysis of molecular findings within the proband's family, with the purpose of providing a broader framework for understanding single cases and allowing finer genotype-phenotype correlations in FSHD-affected families.

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 RDH8 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 RDH8 is detected. The disease phenotype is consistent with the expected phenotype hypothesized in previous studies on murine models. The application of the combined approach to genetic data and the multilevel validation allowed the identification of a splicing mutation in a gene that has never been reported before in human disorders.

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. In the present study, methylation levels of 29 CpG sites of the DR1 region (within each repeat unit of the D4Z4 macrosatellite) were assessed on 335 subjects by employing primers designed for enhancing the performance of the assay. First, the DR1 original primers were optimized by adding M13 oligonucleotide tails. Moreover, the DR1 reverse primer was replaced with a degenerate one. As a result, the protocol optimization allowed a better sequencing resolution and a more accurate evaluation of DR1 methylation levels. Moreover, the assessment of the repeatability of measurements proved the reliability and robustness of the assay. The optimized protocol emerges as an excellent method to detect methylation levels compatible with FSHD.

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). Here, we present a non-invasive prenatal paternity test (NIPAT) analyzing 861 Single Nucleotide Variants (SNV) from cffDNA through NGS technology. The test, validated on more than 900 meiosis samples, generated log(CPI)(Combined Paternity Index) values for designated fathers ranging from +34 to +85, whereas log(CPI) values calculated for unrelated individuals were below -150. This study suggests that NIPAT can be used with high accuracy in real cases.

Longitudinal Structure-Function Evaluation in a Patient with CDHR1-Associated Retinal Dystrophy: Progressive Visual Function Loss with Retinal Remodeling.

BACKGROUND: Retinal dystrophies related to damaging variants in the cadherin-related family member 1 (CDHR1) gene are rare and phenotypically heterogeneous. Here, we report a longitudinal (three-year) structure-function evaluation of a patient with a CDHR1-related retinal dystrophy. METHODS: A 14-year-old girl was evaluated between 2019 and 2022. An ophthalmological assessment, including color vision, perimetry, electroretinography, and multimodal imaging of the retina, was performed periodically every six months. Next-generation sequencing disclosed two likely pathogenic/pathogenic variants in the CDHR1 gene, in compound heterozygosity, confirmed by segregation analysis. RESULTS: At first examination, the patient showed a cone-rod pattern retinal dystrophy. Over follow-up, there was a decline of visual acuity and perimetric sensitivity (by ≥0.3 and 0.6 log units, respectively). Visual loss was associated with a progressive increase in inner retinal thickness (by 30%). Outer retina showed no detectable changes over the follow-up. CONCLUSIONS: The results indicate that, in this patient with a CDHR1-related cone-rod dystrophy, the progression to severe visual loss was paralleled by a progressive inner retinal thickening, likely a reflection of remodeling. Inner retinal changes over time may be functionally relevant in view of the therapeutic attempts based on gene therapy or stem cells to mitigate photoreceptor loss.

D4Z4 Methylation Levels Combined with a Machine Learning Pipeline Highlight Single CpG Sites as Discriminating Biomarkers for FSHD Patients.

The study describes a protocol for methylation analysis integrated with Machine Learning (ML) algorithms developed to classify Facio-Scapulo-Humeral Dystrophy (FSHD) subjects. The DNA methylation levels of two D4Z4 regions (DR1 and DUX4-PAS) were assessed by an in-house protocol based on bisulfite sequencing and capillary electrophoresis, followed by statistical and ML analyses. The study involved two independent cohorts, namely a training group of 133 patients with clinical signs of FSHD and 150 healthy controls (CTRL) and a testing set of 27 FSHD patients and 25 CTRL. As expected, FSHD patients showed significantly reduced methylation levels compared to CTRL. We utilized single CpG sites to develop a ML pipeline able to discriminate FSHD subjects. The model identified four CpGs sites as the most relevant for the discrimination of FSHD subjects and showed high metrics values (accuracy: 0.94, sensitivity: 0.93, specificity: 0.96). Two additional models were developed to differentiate patients with lower D4Z4 size and patients who might carry pathogenic variants in FSHD genes, respectively. Overall, the present model enables an accurate classification of FSHD patients, providing additional evidence for DNA methylation as a powerful disease biomarker that could be employed for prioritizing subjects to be tested for FSHD.

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. The present study explored their genetic distribution among different populations (AFR, EAS, EUR and SAS). As a result, the obtained data support the existence of a genetic basis for the observed variability among populations, in terms of SARS-CoV-2 infection and disease outcomes. The comparison of ORs distribution for genetic risk of infection as well as for disease outcome shows that each population presents its own characteristics. These data suggest that each country could benefit from a population-wide risk assessment, aimed to personalize the national vaccine programs and the preventative measures as well as the allocation of resources and the access to proper therapeutic interventions. Moreover, the host genetics should be further investigated in order to realize personalized medicine protocols tailored to improve the management of patients suffering from COVID-19.

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 D4Z4 repeated units and FSHD-associated genes), epigenetic elements (D4Z4 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. In conclusion, the present review highlights how FSHD should be regarded as a disease characterized by a molecular spectrum of genetic and epigenetic factors, whose alteration plays a differential role in DUX4 repression and, subsequently, contributes to determining the FSHD phenotype.

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.

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. WARE is characterized by a user-friendly web page interface that is intended to assist clinicians in reporting risk assessment upon patient evaluation. When using the tool, plots of population risk distribution highlight a "low-risk zone" and a "high-risk zone" into which subjects can fall depending on their risk-assessment result. WARE represents a reliable population-specific computational system for wet AMD risk evaluation that can be exploited to promote preventive actions and personalized medicine approach for affected patients or at-risk individuals. This tool can be suitable to compute the disease risk adjusted to different populations considering their specific genetic factors and related frequencies, non-genetic factors, and the disease prevalence.

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. As a result, 21 SNPs were associated with aMCI and 13 SNPs with sporadic AD. Interestingly, a set of variants shared between aMCI and AD displayed slightly higher Odd Ratios in AD with respect to aMCI, highlighting a specific risk trajectory linking aMCI to AD. Some of the associated genes and miRNAs were shown to interact within the signaling pathways of APP (Amyloid Precursor Protein), ACE2 (Angiotensin Converting Enzyme 2), miR-155 and PPARG (Peroxisome Proliferator Activated Receptor Gamma), which are known to contribute to neuroinflammation and neurodegeneration. Overall, results of this study increase insights concerning the genetic factors contributing to the neuroinflammatory and neurodegenerative mechanisms underlying aMCI and sporadic AD. They have to be exploited to develop personalized approaches based on the individual genetic make-up and multi-target treatments.

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. Two hundred and ten post mortem brain RNA-Seq samples from PD (n = 115) and normal controls (NCs, n = 95) were obtained with systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p < 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/ß-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.

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. These samples were subjected to RT-PCR using the TaqPath COVID-19 RT PCR CE IVD kit. Nonparametric testing and polynomial models fitting were used to compare the spreading of Alpha, Delta and Omicron variants. The samples of interest were correctly amplified and displayed the presence of S gene-target failure, suggesting that these patients carry the Omicron variant. The trend of diffusion was found to be significantly different and more rapid compared with that of the Alpha and Delta variants in our cohorts. Overall, these results highlight that the S gene target failure was a very useful tool for the immediate and inexpensive tracking of Omicron variant in the three weeks from the first detection. Thus, our approach could be used as a first-line screening to reduce the time and costs of monitoring strategies, facilitating the management of preventive and counteracting measures against COVID-19.

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.

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. The etiopathogenesis is characterized by an interplay among multiple genetic and non-genetic factors, which have been extensively studied. Nevertheless, a deeper dissection of molecular machinery associated with risk, onset, progression and effectiveness of therapies is still missing. In this regard, epigenetic signals may be further explored to disentangle disease etiopathogenesis, the possible therapeutic avenues and the differential response to AMD treatment. This review will discuss the epigenomic signatures mostly investigated in AMD, which could be applied to improve the knowledge of disease mechanisms and to set-up novel or modified treatment options.

Pharmacogenomics: An Update on Biologics and Small-Molecule Drugs in the Treatment of Psoriasis.

Pharmacogenomic studies allowed the reasons behind the different responses to treatments to be understood. Its clinical utility, in fact, is demonstrated by the reduction in adverse drug reaction incidence and the improvement of drug efficacy. Pharmacogenomics is an important tool that is able to improve the drug therapy of different disorders. In particular, this review will highlight the current pharmacogenomics knowledge about biologics and small-molecule treatments for psoriasis. To date, studies performed on genes involved in the metabolism of biological drugs (tumor necrosis factor inhibitors and cytokines inhibitors) and small molecules (apremilast, dimethyl fumarate, and tofacitinib) have provided conflicting results, and further investigations are necessary in order to establish a set of biomarkers to be introduced into clinical practice.

Precision Medicine into Clinical Practice: A Web-Based Tool Enables Real-Time Pharmacogenetic Assessment of Tailored Treatments in Psychiatric Disorders.

The management of neuropsychiatric disorders involves different pharmacological treatments. In order to perform efficacious drug treatments, the metabolism of CYP genes can help to foresee potential drug-drug interactions. The NeuroPGx software is an open-source web-based tool for genotype/diplotype/phenotype interpretation for neuropharmacogenomic purposes. The software provides information about: (i) the genotypes of evaluated SNPs (single nucleotide polymorphisms); (ii) the main diplotypes in CYP genes and corresponding metabolization phenotypes; (iii) the list of neuropsychiatric drugs with recommended dosage adjustment (according to CPIC and DPWG guidelines); (iv) the list of possible (rare) diplotypes and corresponding metabolization phenotypes. The combined application of NeuroPGx software to the OpenArray technology results in an easy, quick, and highly automated device ready to be used in routine clinical practice.