Publications by authors named "Slave Petrovski"

Epstein-Barr Virus (EBV) is an endemic herpesvirus implicated in autoimmunity, cancer, and neurological disorders. Though primary infection typically resolves with subclinical symptoms, long-term complications can arise due to immune dysregulation or viral latency, in which EBV DNA is detectable in blood for decades. Despite the ubiquity of this virus, we have an incomplete understanding of the highly variable responses to EBV that range from asymptomatic infection to a trigger for severe disease.

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Somatic DNMT3A-R882 codon mutations drive the most common form of clonal haematopoiesis (CH) and are associated with increased acute myeloid leukaemia (AML) risk. Preventing expansion of DNMT3A-R882-mutant haematopoietic stem/progenitor cells (HSPCs) may therefore avert progression to AML. To identify DNMT3A-R882-mutant-specific vulnerabilities, we conducted a genome-wide CRISPR screen on primary mouse Dnmt3a HSPCs.

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The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation-regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E).

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Despite its significant heritability, the genetic basis of Parkinson's disease (PD) remains incompletely understood. Here, in analyzing whole-genome sequence data from 3,809 PD cases and 247,101 controls in the UK Biobank, we discover that protein-truncating variants in ITSN1 confer a substantially increased risk of PD (p = 6.1 × 10; odds ratio [95% confidence interval] = 10.

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The biological mechanisms through which most nonprotein-coding genetic variants affect disease risk are unknown. To investigate gene-regulatory mechanisms, we mapped blood gene expression and splicing quantitative trait loci (QTLs) through bulk RNA sequencing in 4,732 participants and integrated protein, metabolite and lipid data from the same individuals. We identified cis-QTLs for the expression of 17,233 genes and 29,514 splicing events (in 6,853 genes).

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Genomics can provide insight into the etiology of type 2 diabetes and its comorbidities, but assigning functionality to non-coding variants remains challenging. Polygenic scores, which aggregate variant effects, can uncover mechanisms when paired with molecular data. Here, we test polygenic scores for type 2 diabetes and cardiometabolic comorbidities for associations with 2,922 circulating proteins in the UK Biobank.

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Despite great progress, thousands of neurodevelopmental disorder (NDD) risk genes remain to be discovered. We present a computational approach that accelerates NDD risk gene identification using machine learning. First, we demonstrate that models trained solely on single-cell RNA sequencing data can robustly predict genes implicated in autism spectrum disorder (ASD), developmental and epileptic encephalopathy (DEE), and developmental delay (DD).

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To assess the contribution of rare coding germline genetic variants to prostate cancer risk and severity, we perform here a meta-analysis of 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline whole exome or genome sequencing data, and one cohort with imputed array data. At the gene level, our case-control collapsing analysis confirms associations between rare damaging variants in four genes and increased prostate cancer risk: SAMHD1, BRCA2 and ATM at the study-wide significance level (P < 1×10), and CHEK2 at the suggestive threshold (P < 2.6×10).

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The impact of genetic ancestry on the development of clonal hematopoiesis (CH) remains largely unexplored. Here, we compared CH in 136,401 participants from the Mexico City Prospective Study (MCPS) to 416,118 individuals from the UK Biobank (UKB) and observed CH to be significantly less common in MCPS compared to UKB (adjusted odds ratio = 0.59, 95% confidence interval (CI) = [0.

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Key Points: We conducted a clinical, genetic, and pathological analysis on 64 cases from 39 families with TRPC6-associated podocytopathy (TRPC6-AP). Analysis of 37,542 individuals excluded a major contribution of loss-of-function variants to TRPC6-AP, legitimating current drug discovery approaches. This study identifies key features of disease that can help intervention studies design and suggests similarities between TRPC6-AP and primary FSGS.

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The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank's longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores.

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Article Synopsis
  • Telomeres are protective caps on chromosomes, and their length is related to aging and diseases, prompting a study on telomere length in over 462,000 UK Biobank participants.
  • Researchers created a new metric for measuring telomere length that improved understanding of its genetic control and identified 64 genetic variants and 30 genes linked to telomere length.
  • Notably, many of these genes are involved in clonal hematopoiesis, which is linked to certain cancers, indicating a complex relationship between rare genetic variants and telomere length.
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Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors.

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The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants.

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The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome.

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Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R.

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Article Synopsis
  • * The study focuses on 48 de novo missense variants in GRIN1, GRIN2A, and GRIN2B that affect the M3 transmembrane helix, identified in children with conditions like epilepsy and developmental delays.
  • * Most of these variants lead to a gain-of-function effect, promoting NMDAR channel activity, reinforcing the importance of the M3 region in receptor function, and providing insights into how certain drugs may affect these variant receptors.
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African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers.

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Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes.

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  • The Mexico City Prospective Study is a large-scale research initiative involving over 150,000 adults from urban areas in Mexico City, aimed at understanding genetic diversity and ancestry.
  • The study reveals a mix of Indigenous American, European, and African ancestries among participants, highlighting significant genetic differences and a unique genetic landscape within the Indigenous Mexican population.
  • Researchers created a valuable reference panel for genetic research, improving the accuracy of studying genetic variants in populations with high Indigenous ancestry, and providing essential resources for future genetic studies in both Mexico and the US.
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  • The Pharma Proteomics Project is a large-scale research initiative analyzing blood protein profiles from over 54,000 UK Biobank participants to understand links between genetics and health.
  • The project identifies significant genetic associations with proteins, revealing many novel interactions and highlighting ancestry-specific variations, along with insights into disease mechanisms and potential drug targets.
  • By making their findings publicly accessible, the consortium aims to advance research in biomarker development and therapeutic strategies, enhancing our understanding of how genetic factors influence health outcomes.
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Article Synopsis
  • Integrating human genomics and proteomics can uncover disease mechanisms and identify potential biomarkers and drug targets.
  • Our study highlights the importance of rare protein-coding variants, finding 5,433 associations with plasma protein levels that were largely missed in previous studies.
  • We also demonstrate practical applications of our findings, including potential biomarkers for diseases and insights into the effects of clonal hematopoiesis on protein levels.
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Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic.

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