Sarah E. Bergen

This study identifies a schizophrenia-associated radial glia cell state that disrupts early human brain development through single-cell transcriptomic and epigenomic analyses of organoids.

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

The paper identifies pQTLs for 91 plasma proteins, finds novel associations, and uses MR to uncover causal roles in immune-mediated diseases, suggesting new therapeutic targets.

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

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.

A genome-wide association study of 69,369 schizophrenia cases and 236,642 controls identifies 270 risk loci, prioritizes 130 genes, and links common and rare risk variants to neuronal synaptic biology.

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.

This paper introduces a principal component approach to improve association testing with polygenic risk scores by reducing type I error and improving power compared to permutation tests and a priori parameter selection.

The paper identifies pQTLs for cardiovascular proteins and uses them to evaluate drug targets and suggest new candidates for precision medicine.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study identifies 73 genome-wide significant loci for mood disorders, revealing shared and distinct genetic factors between major depressive disorder and bipolar disorder.

The paper investigates the role of single-gene copy number variants in schizophrenia risk using exome-sequencing data from a Swedish cohort, identifying significant deletions in voltage-gated calcium channels.

This study identifies 30 genome-wide significant loci associated with bipolar disorder, including novel genes involved in ion channels, neurotransmitters, and synaptic components.

The study finds that rare copy number variants (CNVs) contribute to bipolar disorder risk primarily in schizoaffective disorder bipolar type cases, with differences in CNV burden and schizophrenia polygenic risk scores between subtypes.

The paper finds a genetic association between schizophrenia risk and age at first birth in women, with different genetic correlations in younger and older age groups.

This study identifies 114 genome-wide significant loci for schizophrenia and bipolar disorder, with specific subphenotype associations and four genes distinguishing the disorders.

This study compares LDSC and GREML methods for estimating genetic correlation, showing GREML provides higher accuracy, especially in the presence of genetic heterogeneity.