GUANIN: an all-in-one GUi-driven analyzer for NanoString interactive normalization.

SUMMARY: Most tools for normalizing NanoString gene expression data, apart from the default NanoString nCounter software, are R packages that focus on technical normalization and lack configurable parameters. However, content normalization is the most sensitive, experiment-specific, and relevant step to preprocess NanoString data. Currently this step requires the use of multiple tools and a deep understanding of data management by the researcher. We present GUANIN, a comprehensive normalization tool that integrates both new and well-established methods, offering a wide variety of options to introduce, filter, choose, and evaluate reference genes for content normalization. GUANIN allows the introduction of genes from an endogenous subset as reference genes, addressing housekeeping-related selection problems. It performs a specific and straightforward normalization approach for each experiment, using a wide variety of parameters with suggested default values. GUANIN provides a large number of informative output files that enable the iterative refinement of the normalization process. In terms of normalization, GUANIN matches or outperforms other available methods. Importantly, it allows researchers to interact comprehensively with the data preprocessing step without programming knowledge, thanks to its easy-to-use Graphical User Interface (GUI). AVAILABILITY AND IMPLEMENTATION: GUANIN can be installed with pip install GUANIN and it is available at https://pypi.org/project/guanin/. Source code, documentation, and case studies are available at https://github.com/julimontoto/guanin under the GPLv3 license.

Whole Exome Sequencing Identifies Epithelial and Immune Dysfunction-Related Biomarkers in Food Protein-Induced Enterocolitis Syndrome.

BACKGROUND: Food protein-induced enterocolitis syndrome (FPIES) is a food allergy primarily affecting infants, often leading to vomiting and shock. Due to its poorly understood pathophysiology and lack of specific biomarkers, diagnosis is frequently delayed. Understanding FPIES genetics can shed light on disease susceptibility and pathophysiology-key to developing diagnostic, prognostic, preventive and therapeutic strategies. Using a well-characterised cohort of patients we explored the potential genome-wide susceptibility factors underlying FPIES. METHODS: Blood samples from 41 patients with oral food challenge-proven FPIES were collected for a comprehensive whole exome sequencing association study. RESULTS: Notable genetic variants, including rs872786 (RBM8A), rs2241880 (ATG16L1) and rs2289477 (ATG16L1), were identified as significant findings in FPIES. A weighted SKAT model identified six other associated genes including DGKZ and SIRPA. DGKZ induces TGF-ß signalling, crucial for epithelial barrier integrity and IgA production; RBM8A is associated with thrombocytopenia absent radius syndrome, frequently associated with cow's milk allergy; SIRPA is associated with increased neutrophils/monocytes in inflamed tissues as often observed in FPIES; ATG16L1 is associated with inflammatory bowel disease. Coexpression correlation analysis revealed a functional correlation between RBM8A and filaggrin gene (FLG) in stomach and intestine tissue, with filaggrin being a known key pathogenic and risk factor for IgE-mediated food allergy. A transcriptome-wide association study suggested genetic variability in patients impacted gene expression of RBM8A (stomach and pancreas) and ATG16L1 (transverse colon). CONCLUSIONS: This study represents the first case-control exome association study of FPIES patients and marks a crucial step towards unravelling genetic susceptibility factors underpinning the syndrome. Our findings highlight potential factors and pathways contributing to FPIES, including epithelial barrier dysfunction and immune dysregulation. While these results are novel, they are preliminary and need further validation in a second cohort of patients.

Sensogenomics of music and Alzheimer's disease: An interdisciplinary view from neuroscience, transcriptomics, and epigenomics.

Introduction: The relationship between music and Alzheimer's disease (AD) has been approached by different disciplines, but most of our outstanding comes from neuroscience. Methods: First, we systematically reviewed the state-of-the-art of neuroscience and cognitive sciences research on music and AD (>100 studies), and the progress made on the therapeutic impact of music stimuli in memory. Next, we meta-analyzed transcriptomic and epigenomic data of AD patients to search for commonalities with genes and pathways previously connected to music in genome association, epigenetic, and gene expression studies. Results: Our findings indicate that >93% of the neuroscience/ cognitive sciences studies indicate at least one beneficial effect of music on patients with neurodegenerative diseases, being improvements on memory and cognition the most frequent outcomes; other common benefits were on social behavior, mood and emotion, anxiety and agitation, quality of life, and depression. Out of the 334 music-related genes, 127 (38%) were found to be linked to epigenome/transcriptome analysis in AD (vs. healthy controls); some of them (SNCA, SLC6A4, ASCC2, FTH1, PLAUR and ARHGAP26) have been reported to be associated e.g. with musical aptitude and music effect on the transcriptome. Other music-related genes (GMPR, SELENBP1 and ADIPOR1) associated to neuropsychiatric, neurodegenerative diseases and music performance, emerged as hub genes in consensus co-expression modules detected between AD and music estimulated transcriptomes. In addition, we found connections between music, AD and dopamine related genes, with SCNA being the most remarkable - a gene previously associated with learning and memory, and neurodegenerative disorders (e.g., Parkinson's disease and AD). Discussion: The present study indicate that the vast majority of neuroscientific studies unambiguously show that music has a beneficial effect on health, being the most common benefits relevant to Alzheimer's disease. These findings illuminate a new roadmap for genetic research in neurosciences, and musical interventions in AD and other neurodegenerative conditions.

Music compensates for altered gene expression in age-related cognitive disorders.

Extensive literature has explored the beneficial effects of music in age-related cognitive disorders (ACD), but limited knowledge exists regarding its impact on gene expression. We analyzed transcriptomes of ACD patients and healthy controls, pre-post a music session (n = 60), and main genes/pathways were compared to those dysregulated in mild cognitive impairment (MCI) and Alzheimer's disease (AD) as revealed by a multi-cohort study (n = 1269 MCI/AD and controls). Music was associated with 2.3 times more whole-genome gene expression, particularly on neurodegeneration-related genes, in ACD than in controls. Co-expressed gene-modules and pathways analysis demonstrated that music impacted autophagy, vesicle and endosome organization, biological processes commonly dysregulated in MCI/AD. Notably, the data indicated a strong negative correlation between musically-modified genes/pathways in ACD and those dysregulated in MCI/AD. These findings highlight the compensatory effect of music on genes/biological processes affected in MCI/AD, providing insights into the molecular mechanisms underlying the benefits of music on these disorders.