Ralda Nehme

The paper develops a high-throughput all-optical platform to map gene perturbations to electrophysiology using engineered hiPSCs and automated analysis.

The paper introduces a cell village-based fitness screening approach and a Dirichlet regression framework to analyze genetic factors affecting cell proliferation and environmental sensitivity in human neural progenitor cells.

This study analyzes 42 de novo CACNA1A missense variants in neurodevelopmental disorders, finding most alter channel function and correlate with clinical outcomes.

The paper uses village editing to study how genetic backgrounds affect the impact of schizophrenia-associated mutations in human neurons.

The paper identifies chr22q as a regulatory hub where genetic risk for neuropsychiatric conditions is associated with coordinated gene expression downregulation in brain tissue.

The paper identifies genetic variants that influence neuronal responses to interferons by analyzing gene expression and STAT1 binding in iPSC-derived neurons.

This study integrates multi-omics data from Drosophila and human Alzheimer's disease models to identify pathways involved in neurodegeneration.

The paper identifies three neuron-specific schizophrenia protein networks enriched for genetic and transcriptional perturbations and validates their disruption in 22q11.2 deletion carriers.

This study identifies AKAP11's role in regulating lipid metabolism and neuronal support in astrocytes, linking its dysfunction to schizophrenia and bipolar disorder risk.

This paper introduces Perturb-FISH, a method combining spatial transcriptomics and CRISPR screening to study transcriptional circuits, showing intracellular and intercellular effects in immune and neurological contexts.

The paper integrates pathway discovery with pooled genetic perturbation to identify modifiers of Huntington's disease, revealing genes involved in neuronal development and morphology.

The paper shows that astrocyte-supplied cholesterol drives synaptic gene expression in neurons and induces astrocytic transcriptional responses, linking lipid metabolism to neurodevelopmental disorders.

CellMincer is a self-supervised deep learning method for denoising voltage imaging data, achieving significant noise reduction and improved functional phenotype separation.

The paper introduces NeuroPainting, a morphological phenotyping method, and combines it with transcriptomics to identify cell-type-specific effects of the 22q11.2 deletion on mitochondrial structure and gene expression in astrocytes.

This study identifies genetic variants associated with cellular morphology using high-content imaging and genomic data from iPSCs.

The paper introduces a multi-donor brain organoid model called Chimeroids to study individual genetic variation in neurotoxin susceptibility.

The paper identifies a transient hyperactive neuronal state in early Alzheimer's disease using single-nucleus transcriptomics from living patients.

This study develops a rapid, scalable method to generate functional human astrocytes from pluripotent stem cells using NGN2 induction, showing high homogeneity and disease relevance.

The paper shows that astrocyte-neuron interactions enhance synaptic gene expression in neurons and correlate with schizophrenia risk genes.

This study combines Ngn2 overexpression with small molecule patterning to efficiently generate lower induced Motor Neurons (liMoNes) from hPSCs, achieving high yields and functional characteristics.

This study investigates how the 22q11.2 deletion affects gene expression in neural progenitor cells and neurons, linking it to schizophrenia risk through altered presynaptic gene products.

The paper identifies a common genetic variant in IFITM3 that explains most inter-individual variation in neural progenitor cell susceptibility to Zika virus using natural genetic variation and synthetic perturbations.

Census-seq pools cells from >100 human donors into "cell villages" and quantifies donor DNA before and after selection to map genetic effects on cellular traits.