Dmitry Prokopenko

GWAS on short tandem repeats identifies novel genetic mechanisms in Alzheimer's disease

This study conducts GWAS on short tandem repeats (STRs) to identify novel genetic mechanisms in Alzheimer's disease using data from ~330,000 individuals.

Matching Heterogeneous Cohorts by Projected Principal Components Reveals Two Novel Alzheimer's Disease-Associated Genes in the Hispanic Population

Analyzing associations and higher-order effects in multi-omics data with double machine learning

The paper introduces ROMY, a framework for analyzing multi-omics data with robust association testing, variance-covariance effects, and interaction testing using double machine learning.

Context-dependent regulatory variants in Alzheimer's disease

The paper identifies context-dependent regulatory variants in Alzheimer's disease by analyzing their effects across different cellular contexts using MPRAs and machine learning.

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

This study identifies molecular and cellular signatures of cognitive resilience in Alzheimer's disease by integrating multi-omics data from brain tissues.

Identification of 16 novel Alzheimer's disease susceptibility loci using multi-ancestry meta-analyses of clinical Alzheimer's disease and AD-by-proxy cases from four whole genome sequencing datasets

This study identifies 16 new Alzheimer's disease susceptibility loci through multi-ancestry GWAS using whole genome sequencing data from diverse cohorts.

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model

This paper develops polygenic hazard score models using lasso for Cox's proportional hazards to predict Alzheimer's free survival, showing improved accuracy and personalized survival curves.

Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

RITSS identifies gene-environment interactions in quantitative traits using sample splitting and robust statistics, finding significant interactions in lung function and height data.

Fast computation of principal components of genomic similarity matrices

This paper introduces fast algorithms for computing principal components of genomic similarity matrices, including exact methods for specific matrices and an approximate Jaccard matrix with theoretical guarantees.

Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2

This study identifies two novel Alzheimer's disease-associated genes, DTNB and DLG2, by analyzing rare variants in whole-genome sequencing data from AD family datasets.

Unsupervised genome-wide cluster analysis: nucleotide sequences of the omicron variant of SARS-CoV-2 are similar to sequences from early 2020

The paper uses unsupervised cluster analysis to show that omicron variant SARS-CoV-2 sequences are most similar to early 2020 sequences, suggesting long-term circulation.

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

The paper conducts GWAS on CSF Alzheimer's disease biomarkers, identifying genetic associations with NF-L, YKL-40, and Ng levels.

Whole-genome sequencing reveals new Alzheimer's disease-associated rare variants in loci related to synaptic function and neuronal development

Estimating the effective sample size in association studies of quantitative traits

This paper introduces an analytical method to estimate effective sample size in mixed-model GWAS of quantitative traits, showing its performance in unrelated and related individuals.

A smoothed version of the Lassosum penalty for fitting integrated risk models

This paper introduces a smoothed version of the Lassosum penalty to improve integrated risk models, showing increased accuracy in predicting Alzheimer's and COPD risks compared to the original Lassosum and LDpred2.

Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

The paper conducts a genome-wide association study (GWAS) on Alzheimer’s disease CSF biomarkers in the EMIF-AD dataset, identifying novel genetic signals and confirming existing associations.

locStra: Fast analysis of regional/global stratification in whole genome sequencing (WGS) studies

locStra efficiently analyzes regional and global population stratification in WGS studies using sparse matrix algebra and sliding window approaches to improve association testing.

Expanded genetic landscape of chronic obstructive pulmonary disease reveals heterogeneous cell type and phenotype associations

This study expands the genetic landscape of COPD by identifying 82 risk loci, revealing associations with lung function, cell types, and comorbidities.

New genetic signals for lung function highlight pathways and pleiotropy, and chronic obstructive pulmonary disease associations across multiple ancestries

The paper identifies 279 new genetic signals for lung function across multiple ancestries, showing associations with COPD and pleiotropic effects.

Reporting correct p-values in VEGAS analyses

The paper identifies an error in VEGAS2's top-percentage test that leads to deflated p-values and false positives, providing corrected code for accurate p-value computation.

Quantifying polygenic effects in genome-wide association studies using generalized estimating equations

This paper extends LD Score regression using generalized estimating equations to better quantify polygenic effects in GWAS by incorporating external reference panel information.