Zinan Zhou

The paper identifies a shared TOP1-mediated mutagenic mechanism in ALS, FTD, and AD through single-cell genomic analysis and experimental validation.

This study identifies somatic Ras-MAPK pathway variants in hippocampal tissue from patients with drug-resistant epilepsy, showing their association with clonal competition and worse surgical outcomes.

This study uses snRNA-seq and a new method called GO-TEN to analyze mosaic genetic variants in focal cortical dysplasia, revealing cell-autonomous and non-cell-autonomous transcriptional changes associated with epilepsy.

This study finds that Alzheimer's disease patients have more clonal hematopoiesis mutations than controls, especially those with APOE ε3/ε3 genotype, suggesting a risk factor independent of APOE ε4.

This study investigates whether somatic mutations in PRNP contribute to sporadic Creutzfeldt-Jakob Disease (sCJD) by sequencing PRNP in 205 sCJD cases and 170 controls, finding no evidence of pathogenic somatic variants.

The paper identifies somatic driver mutations in microglia of Alzheimer's disease brains, showing increased clonal expansion and inflammatory signatures.

The paper identifies rare somatic mutations in sporadic ALS and FTD cases, suggesting they contribute to disease and widespread neurodegeneration.

The paper compares somatic mutation rates in neurons and oligodendrocytes across aging human brains, finding faster mutation accumulation in oligodendrocytes and distinct genomic distribution patterns.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper evaluates brain somatic mosaicism in the adult human to identify rules governing cellular distribution during embryogenesis.

The paper introduces PTA for single-cell DNA sequencing and SCAN2 to detect somatic SNVs and indels in single neurons, finding age-related increases in both with indels having greater functional impact.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.