Biology subjects

Biernacka, J. M.

Publications and source records attributed to Biernacka, J. M..

4 recordsLinked to original sources

bioRxiv2025

Alcohol Use Disorder Associated Gene FNDC4 Alters Glutamatergic and GABAergic Neurogenesis

Large-cohort genome-wide association studies (GWAS) for alcohol use disorder (AUD) and AUD-related phenotypes have identified more than one hundred genetic loci. Functional study of those GWAS-identified loci might represent an important step toward understanding AUD pathophysiology. We found that genetic loci which are splicing quantitative trait loci (sQTLs) for the fibronectin III domain containing 4 (FNDC4) gene in the brain were identified by GWAS for both AUD drug treatment outcomes and AUD risk. However, FNDC4 function in the brain and how it might contribute to AUD pathophysiology remain unknown. In the present study, we characterized GWAS locus-associated FNDC4 splice isoforms, studies which suggested that FNDC4 alternative splicing results in loss-of-function for FNDC4. We also investigated FNDC4 function using CRISPR/cas9 gene editing, and the creation of human induced pluripotent stem cell (iPSC)-derived neural organoids joined with single-nucleus RNA sequencing. We observed that knock-out (KO) of FNDC4 resulted in a striking shift in the relative proportions of glutamatergic and GABAergic neurons in iPSC-derived neural organoids, suggesting a possible important role for FNDC4 in neurogenesis. We also explored potential mechanism(s) of FNDC4-dependent neurogenesis with results that suggested a role for FNDC4 in mediating neural cell-cell interaction. In summary, this series of experiments indicates that FNDC4 plays a role in regulating cerebral cortical neurogenesis in the brain. This regulation may contribute to the response to AUD pharmacotherapy as well as the effects of alcohol on the brain.

genomics↗

bioRxiv2020

Identification of novel Alzheimer's disease genes co-expressed with TREM2

By analyzing whole-exome data from the Alzheimers disease sequencing project (ADSP), we identify a set of 4 genes that show highly significant association with Alzheimers disease (AD). These genes were identified within a human TREM2 co-expression network using a novel approach wherein prioritized polygenic score analyses were performed sequentially to identify significant polygenic components. Two of the 4 genes (TREM2, RIN3) have previously been linked to AD and two (ATP8B4, IL17RA) are novel. Like TREM2, the 2 novel AD genes are selectively expressed in human microglial cells. The most significant variants in ATP8B4 and IL17RA are non-synonymous variants with strong effects comparable to the APOE {varepsilon}4 and {varepsilon}2 alleles. These protein-altering variants will provide unique opportunities to further explore the biological role of microglial cells in AD and help inform future immune modulatory therapeutic development for AD.

genetics↗

bioRxiv2019

A principal component approach to improve association testing with polygenic risk scores

Polygenic risk scores (PRSs) have become an increasingly popular approach for demonstrating polygenic influences on complex traits and for establishing common polygenic signals between different traits. PRSs are typically constructed using pruning and thresholding (P+T), but the best choice of parameters is uncertain; thus multiple settings are used and the best is chosen. This optimization can lead to inflated type I error. To correct this, permutation procedures can be used but they can be computationally intensive. Alternatively, a single parameter setting can be chosen a priori for the PRS, but choosing suboptimal settings result in loss of power. We propose computing PRSs under a range of parameter settings, performing principal component analysis (PCA) on the resulting set of PRSs, and using the first PRS-PC in association tests. The first PC reweights the variants included in the PRS with new weights to achieve maximum variation over all PRS settings used. Using simulations, we compare the performance of the proposed PRS-PCA approach with a permutation test and a priori selection of p-value threshold. We then apply the approach to the Mayo Clinic Bipolar Disorder Biobank study to test for PRS association with psychosis using a variety of PRSs constructed from summary statistics from the largest studies of psychiatric disorders and related traits. The PRS-PCA approach is simple to implement, outperforms the other strategies in most scenarios, and provides an unbiased estimate of prediction performance. We therefore recommend it to be used PRS association studies where multiple phenotypes and/or PRSs are being investigated.

genetics↗

bioRxiv2018

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: meta-analysis of data from genome-wide association studies

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects.\n\nCYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2-4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group.\n\nAnalysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19-0.66) and higher remission rates (OR=1.55, CI=1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08-1.47), neurological (OR=1.28, CI=1.07-1.53) and sexual side effects (OR=1.52, CI=1.23-1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups.\n\nCYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).

genetics↗