Emanuele de Rinaldis

RNA Editing of DEGS1 Links Genetic Risk to Ceramide Dysregulation and Astrocyte Toxicity in ALS

Single-cell multi-ancestry regulatory map of systemic lupus erythematosus

The paper constructs a multi-ancestry single-cell eQTL map for SLE, identifying colocalized eQTLs with GWAS loci and highlighting cell-type-specific regulatory mechanisms.

Genetic liability to psoriasis predicts severe disease outcomes

This study identifies genetic risk factors associated with severe psoriasis and shows that polygenic risk scores can predict severe disease outcomes better than traditional risk factors.

Single-cell neural network classifiers reveal that PM21 NK cell expansion is dependent on B cell signaling

The paper uses single-cell transcriptomics and neural network classifiers to identify B cell signaling as critical for NK cell expansion in allogenic therapy.

Multi-omic triangulation identifies molecular candidates of atopic dermatitis severity

This study identifies 440 genes/proteins associated with atopic dermatitis severity through multi-omics analyses and highlights four with significant cross-evidence, including CEP85, which may contribute to severity via impaired phagocytosis.

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

This study uses deep learning to predict YAP1/TEAD activity from histology slides, linking histological patterns to disease aggressiveness in cancer patients.

Immune disease dialogue of chemokine-based cell communications as revealed by single-cell RNA sequencing meta-analysis

The paper performs a meta-analysis of scRNA-seq data to identify disease-specific and shared chemokine-based cell communication patterns in immune diseases.

Genetic analyses of inflammatory polyneuropathy and chronic inflammatory demyelinating polyradiculoneuropathy identified candidate genes.

This study identifies genetic risk loci and candidate genes for inflammatory polyneuropathy and CIDP through GWAS and functional analyses.

Estimating the impact of single-cell RNA sequencing of human tissues on drug target validation.

This study investigates how scRNA-seq data can predict the clinical success of drug targets by analyzing cell type and disease-specific expression patterns.

Genome-wide association study analysis of disease severity in acne reveals novel biological insights.

This study conducts a GWAS to analyze acne severity, identifying two new loci and six novel genes associated with severity, while showing limited overlap with known acne risk loci.

Leveraging large-scale multi-omics to identify therapeutic targets from genome-wide association studies

This study identifies therapeutic targets by integrating GWAS with multi-omics data, finding enriched causal genes and novel associations like IL6ST in polymyalgia rheumatica.

Comparative Analysis of Association Networks Using Single-Cell RNA Sequencing Data Reveals Perturbation-Relevant Gene Signatures

The paper introduces GENIX, a platform for identifying perturbation-relevant genes using gene association networks, applied to influenza vaccine responses in COVID-19 recovered patients.

The Lupus Epigenome Relates to Genetics, Transcription and Serological Profiles with Dependency on Molecular Subtypes and Informs Drug Discovery

This study identifies epigenetic differences in SLE linked to genetics, transcription, and serology, revealing novel drug targets and pathways.

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

This study integrates public transcriptomic data with network analysis to identify molecular features of psoriasis, revealing key genes and networks involved in the disease.

De Novo Mutations Implicate Novel Genes With Burden Of Rare Variants In Systemic Lupus Erythematosus

This study identifies de novo mutations and rare variant burdens in SLE candidate genes, supporting their role in disease pathogenesis.