Vahid Gazestani

The paper investigates the phenotypic and transcriptional effects of glycoengineering in CHO cells, identifying distinct clusters and molecular mechanisms associated with different glycosyltransferase modifications.

This study identifies the murine dura mater as a transient niche for early-postnatal B lymphopoiesis, highlighting the role of CXCL12-expressing fibroblasts in supporting B cell development.

This paper develops a platform to model and manipulate human microglial states in vitro using single-cell RNA sequencing and genetic tools, identifying disease-associated transcriptional signatures.

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

Whole-brain snRNA-seq paired with Slide-seq assigns cell types to each mouse neuroanatomical structure; most clusters need at least three markers to be defined uniquely.

This study identifies brain region-specific changes and dopamine dysregulation in Grin2a mutant mice, supporting schizophrenia hypotheses and highlighting their utility as a genetic model.

The paper identifies atypical genomic cortical patterning in autistic toddlers with poor early language outcome, linking it to prenatal developmental processes and later functional specialization.

This paper introduces BalanceIT, a method using genetic algorithms to balance clinical factors in RNA-Seq studies, improving differential gene expression and pathway analysis in autism research.

The paper identifies ten distinct midbrain dopaminergic neuron populations in Parkinson's disease, highlighting an AGTR1-expressing subtype vulnerable to degeneration and associated with PD risk genes.

This study quantifies how repeated freeze-thaw cycles affect RNA-Seq reliability, showing that poly(A)-enriched samples lose reproducibility after three cycles.

This study identifies two groups of ASD risk genes—broadly-expressed and brain-specific—that disrupt sequential stages of neurodevelopment through distinct regulatory networks.

The paper identifies a perturbed gene network in leukocytes linked to ASD genetics and symptom severity through analysis of transcriptomics data from toddlers.

The paper reports exome sequencing of 457 ASD families, identifying 10.4% with known ASD genes and 3.4% with possibly associated variants, and provides statistical support for 34 ASD risk genes using the TADA framework.