Na Cai

ATTICUS improves gene expression prediction and association testing by incorporating uncertainty awareness and personalized training, enhancing accuracy and cell-type specificity in disease studies.

This paper introduces SpaceDX, a method that jointly identifies differentially expressed genes and their spatial localization in multi-subject spatial transcriptomics data, improving detection compared to traditional approaches.

This study examines how genetic and lifestyle factors together influence the risk of developing type 2 diabetes in the UK Biobank population.

This paper introduces EDGAR, a deep learning framework that removes genetic confounding in EHR-based GWAS by learning lifetime disease liability and isolating systemic biases in EHR codes.

The paper shows genotype- and phenotype-based genetic instruments explain largely independent components of liability to psychiatric disorders, supported by theoretical analysis and simulations.

REECAP uses contrastive learning to link retinal aging patterns with genetic loci associated with eye diseases, identifying 178 loci including 27 linked to age-related eye diseases.

This study identifies synergistic sets of genetic risk variants in psychiatric disorders, suggesting subtypes and reinterpreting shared genetic effects.

LEOPARD completes missing views in multi-timepoint omics data by disentangling content and temporal representations, outperforming existing methods on benchmark datasets.

The paper identifies five genomic factors explaining most genetic variance across 14 psychiatric disorders and finds shared and disorder-specific genetic signals with distinct biological functions.

BayesRVAT improves rare variant association testing by integrating multiple annotations, increasing power and detecting novel gene-disease associations in real data.

The paper maps tissue-specific mtDNA heteroplasmy and its associations with age and mtDNA gene expression using bulk RNAseq data from GTEx.

The paper investigates the role of mitochondrial DNA in gene regulation across 48 tissues and 684 individuals, identifying eQTLs and associations with nuclear DNA genes.

This study quantifies the heritability of drug response to statins, metformin, warfarin, and methotrexate in UK Biobank participants and identifies genetic modifiers of drug effects and side effects.

This paper introduces MrDAG, a Bayesian Mendelian randomization method that models complex dependencies among multiple exposures and outcomes to improve causal effect estimation, highlighting education and smoking as key interventions for mental health.

The paper identifies neural ensembles in the extended amygdala of mice that encode diverse behaviours across contexts and links these ensembles to gene expression profiles associated with psychiatric and neurodegenerative disorders.

The paper shows that PHQ9 and CIDI-SF MDD symptoms have low to moderate genetic correlations, with distinct associations to dysphoria and symptom heterogeneity.

AutoComplete improves phenotype imputation in biobank data, enhancing GWAS power and genetic discovery.

The paper reports genotyping and population structure findings from the China Kadoorie Biobank, revealing relatedness, consanguinity, and population movement patterns.

The paper introduces PA-FGRS, a method to estimate genetic liability from family records, and shows it improves MDD classification and GWAS power when combined with genotypes.

This paper shows that cross-trait assortative mating explains genetic correlations between traits, suggesting many reported genetic similarities may be overestimated.

This paper improves genetic studies of MDD by integrating shallow and deep phenotypes, enhancing GWAS power and PRS accuracy while preserving specificity.

This paper conducts a multi-ancestry GWAS of major depression, identifying 190 loci and 354 genes, with findings showing increased fine-mapping power and bidirectional BMI relationship in European ancestry samples.

The paper identifies a novel tripartite CRH circuit connecting extended amygdala and basal ganglia that drives arousal and avoidance behaviour through CRH receptor 1 in the substantia nigra.

The paper combines data from two independent mouse studies to identify genetic loci for traits, finds poor replication rates, and proposes a method to assess confidence in associations.

This paper introduces a statistical method to identify tissue-specific genetic contributions to complex traits at the individual level using eQTLs and applies it to BMI and WHRadjBMI in the UK Biobank.

The paper maps regulatory effects of human disease variants in pluripotent cells, identifying cis- and trans-QTL across 18,556 genes and linking them to GWAS traits.

The paper introduces JEPEGMIX2-P, a TWAS pathway method that improves computational efficiency and performance for psychiatric disorder GWAS, showing increased power over existing methods like MAGMA.

This study identifies 308 genetic loci associated with mood disorder and schizophrenia across East Asian and European populations, revealing shared and distinct genetic mechanisms.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

The paper examines how structural variants and short tandem repeats affect gene expression and complex traits, identifying high-impact variants associated with multiple genes and GWAS traits.