Valentina Escott‐Price

The paper uses polygenic risk scores to analyze genetic contributions to neurodegenerative diseases across brain cell types, finding shared and disease-specific genetic risks.

drugMR uses multi-omics data to identify potential drug targets and adverse effects by integrating GWAS and pQTL statistics with various statistical methods.

This study examines how cortical thickness and surface area contribute to cognitive ageing using longitudinal data from multiple cohorts, finding thickness declines more steeply and is more strongly linked to cognitive change.

The paper introduces an adversarial neural network to identify genetic resilience markers in Alzheimer's disease, finding five SNPs associated with resilience independent of polygenic risk scores.

The paper uses plasma proteomics to identify differentially abundant proteins and co-expression modules across Alzheimer's disease stages, highlighting potential biomarkers for early detection.

This study uses human iPSC-derived microglia with high polygenic AD risk to identify functional impairments in immune response, mitochondrial function, and amyloid-beta uptake.

The paper introduces co-expression-based models to improve eQTL predictions and identifies novel schizophrenia-associated genes using brain RNA-seq data.

This study conducts a GWAS on Pick's disease and identifies two SNPs associated with risk, though not at genome-wide significance, suggesting potential genetic factors beyond MAPT mutations.

The paper compares inflammatory markers in sporadic and LRRK2-associated Parkinson's using transcriptomics and proteomics to identify molecular differences and a protein cluster linked to tau pathology.

The paper identifies latent factors underlying white matter metrics using MRI data from a cohort of healthy adults and links these factors to cardiovascular health and cognitive performance.

This study identifies genetic risk loci and factors underlying clinical subtypes of bipolar disorder using GWAS and meta-analysis.

This study performs APOE-stratified GWAS to uncover genetic mechanisms underlying Alzheimer's disease risk and response to therapies.

The paper estimates the frequency of repeat expansion mutations across populations using whole genome sequencing data and finds higher expected prevalence than current reports.

The paper identifies genetically distinct patient subgroups across diseases by analyzing polygenic risk and pathway convergence.

This study shows that DKK3, a Wnt antagonist elevated in Alzheimer's disease, causes synaptic loss and memory impairment, but its knockdown restores synapse integrity and memory in a mouse model.

The paper compares transcriptomic changes in LRRK2 protein interactors between sporadic and LRRK2 Parkinson's Disease to identify molecular differences.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

This paper estimates SNP-based heritability of Alzheimer's disease across five cohorts, showing it ranges from 38-66%, with microglia genes explaining most of the heritability.

The paper uses brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia and identifies enriched networks and genes associated with the disease.

This study examines how genetic risk for Alzheimer's disease affects structural brain networks in young adults using MRI and genotype data.

This paper performs a large meta-analysis of GWAS in dementia with Lewy bodies, identifying sex-specific genetic risk signals and highlighting the need for larger cohorts.

This study identifies genetic resilience factors for Alzheimer's disease by constructing polygenic resilience scores that reduce genetic risk penetrance and correlate with polygenic risk scores in unaffected individuals.

The paper analyzes Alzheimer's disease polygenic risk scores using RNA-sequencing to identify novel biological pathways and common mechanisms between case/control classification and PRS associations.

The paper constructs tissue-specific LRRK2 interactomes and identifies a functional cluster within the striatum, highlighting distinct expression patterns and interactions in brain regions.

This study identifies sex-dependent genetic risk loci shared and specific to mood and psychotic disorders using genome-wide interaction analysis.

Meta-analysis of 41,917 European-ancestry bipolar disorder cases versus 371,549 controls yields 64 risk loci (33 novel), neuronal and synaptic gene enrichment, and 15 eQTL-prioritized genes.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

The paper identifies human-lineage-specific genomic elements, called CNCRs, and shows their enrichment in neurological disease genes and APOE intron-3 retention transcripts in Alzheimer's disease.

This study shows Abi3 is essential for microglial morphology, distribution, and tissue surveillance in vivo, linking it to Alzheimer's disease risk.

The paper identifies a genetic variant in OAS1 linked to increased Alzheimer's disease risk and severe COVID-19 outcomes, showing its role in microglial inflammation.