Solveig K. Sieberts

The paper identifies population-level variation in enhancer expression in the human brain and links enhancer eQTL to schizophrenia heritability.

This study examines sex differences in schizophrenia gene expression using RNA-seq data from 437 controls and 341 cases, finding small effect sizes and reproducible signatures involving X/Y-linked genes and synaptic pathways.

This paper identifies 8 genes across 6 genomic loci associated with Alzheimer's disease risk using transcriptome-wide association study and validates them with summary Mendelian randomization.

The paper estimates molecular pseudotime for Alzheimer's disease progression using RNA-Seq data from human brain samples, showing strong concordance with pathological markers and cognitive diagnosis.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

The paper functionally annotates rare structural variants in the human brain by integrating SV calling with RNA-seq data to assess their regulatory effects and prioritize pathogenic deletions.

The paper develops a multi-view evidence aggregation method to identify and rank potential driver genes of Alzheimer's Disease using RNA-Seq data and GWAS summary statistics.

Coexpression meta-analysis of 2114 human brain RNA-seq samples across the AMP-AD consortium identifies five consensus Alzheimer's disease transcriptional clusters, including two sex-heterogeneous clusters and a previously unreported proteostasis cluster.

The paper analyzes allelic expression bias in schizophrenia using RNA-seq data to assess imprinted gene expression and its relationship with age, ancestry, and disease.

The paper uses transcriptomic imputation to identify schizophrenia risk genes across multiple brain regions, finding 71 associated genes and 36 enriched pathways.

This study uses transcriptomic imputation to identify 29 novel genes associated with bipolar disorder and its subtypes, revealing biological pathways related to oxidative stress and circadian rhythms.

The paper integrates GWAS and conditional eQTL data to identify schizophrenia risk loci with co-localization, finding 40 loci and six with conditional eQTL co-localization.