Biology subjects

Benchek, P.

Publications and source records attributed to Benchek, P..

3 recordsLinked to original sources

bioRxiv2022

kimma: flexible linear mixed effects modeling with kinship for RNA-seq data

We introduce kimma (Kinship In Mixed Model Analysis), an open-source R package for flexible linear mixed effects modeling of RNA-seq including covariates, weights, random effects, covariance matrices, and fit metrics. In simulated datasets, kimma detects differentially expressed genes (DEGs) with similar specificity, sensitivity, and computational time as limma unpaired and dream paired models. Unlike other software, kimma supports covariance matrices as well as fit metrics like AIC. Utilizing genetic kinship covariance, kimma revealed that kinship impacts model fit and DEG detection in a related cohort. Thus, kimma equals or outcompetes current DEG pipelines in sensitivity, computational time, and model complexity.

bioinformatics↗

bioRxiv2022

A Haptoglobin (HP) Structural Variant Alters the Effect of APOE Alleles on Alzheimer's Disease

BackgroundHaptoglobin (HP) is an antioxidant of apolipoprotein E (APOE), and previous reports have shown HP binds with APOE and amyloid-{beta} (A{beta}) to aid its clearance. A common structural variant of the HP gene distinguishes it into two alleles: HP1 and HP2. MethodsHP genotypes were imputed in 29 cohorts from the Alzheimers Disease (AD) Genetics Consortium (N=22,651). Associations between the HP polymorphism and AD risk and age of onset through APOE interactions were investigated using regression models. ResultsThe HP polymorphism significantly impacts AD risk and age at onset in European-descent individuals (and in meta-analysis with African Americans) by modifying both the protective effect of APOE{varepsilon}2 and the detrimental effect of APOE{varepsilon}4, especially for APOE{varepsilon}4 carriers. DiscussionThe effect modification of APOE by HP suggests adjustment and/or stratification by HP genotype is warranted when APOE risk is considered. Our findings also provided directions for further investigations on potential mechanisms behind this association.

genetics↗

bioRxiv2021

An Association Test of the Spatial Distribution of Rare Missense Variants within Protein Structures Improves Statistical Power of Sequencing Studies

Over 90% of variants are rare, and 50% of them are singletons in the Alzheimers Disease Sequencing Project Whole Exome Sequencing (ADSP WES) data. However, either single variant tests or unit-based tests are limited in the statistical power to detect the association between rare variants and phenotypes. To best utilize rare variants and investigate their biological effect, we exam their association with phenotypes in the context of protein. We developed a protein structure-based approach, POKEMON (Protein Optimized Kernel Evaluation of Missense Nucleotides), which evaluates rare missense variants based on their spatial distribution on the protein rather than allele frequency. The hypothesis behind this is that the three-dimensional spatial distribution of variants within a protein structure provides functional context and improves the power of association tests. POKEMON identified four candidate genes from the ADSP WES data, namely two known Alzheimers disease (AD) genes (TREM2 and SORL) and two novel genes (DUSP18 and CSF1R). For known AD genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low frequency risk variants within these genes. DUSP18 has a cluster of variants primarily shared by case subjects around the ligand-binding domain, and this cluster is further validated in a replication dataset with a larger sample size. POKEMON is an open-source tool available at https://github.com/bushlab-genomics/POKEMON.

bioinformatics↗