A novel method for predicting Lp(a) levels from routine outpatient genomic testing identifies those at risk of cardiovascular disease across a diverse cohort DOI Creative Commons
Natalie Telis, Hang Dai,

Ashley Waring

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 4, 2024

Abstract Background Lipoprotein(a) (Lp(a)) levels are a largely genetically determined and often an unmeasured predictor of future Atherosclerotic Cardiovascular Disease (ASCVD). With the increased use exome sequencing in clinical setting, there is opportunity to identify patients who have high chance having elevated Lp(a) therefore at risk ASCVD. However, accurate genetic predictors challenging design. In addition single nucleotide variants (SNVs), which summarized as combined score, significantly impacted by copy number variation repeats kringle IV subtype 2 domain (KIV-2), quantify. KIV-2 numbers highly variable across populations, understanding their impact on important creating equitable reliable Lp(a)-driven cardiovascular for all individuals. Methods We develop novel method quantify individuals’ total from data, validate this quantification against measured levels, then method, with SNV-based genotype entire all-comers cohort individuals health systems United States (Helix Research Network; N = 76,147) estimated level. Results Our genotyping strategy improved prediction those clinically-elevated measurements diverse cohort, especially not similar European reference where GRS-based estimates fall short (r 0.04 GRS, r 0.34 KIV2+GRS non-European). Importantly, genotypes associated earlier onset incidence ASCVD, compared average low retrospective analysis atherosclerotic diagnoses derived electronic records (EHRs). This holds large (CAD HRs=1.29, 1.58), subcohort (HRs=1.30,1.61) well trending significance Europeans (HRs=1.22,1.31). addition, least 2-fold enriched amongst ASCVD diagnosis despite lack EHR-based evidence traditional factors disease. Conclusions study demonstrates that predicted incorporating both SNV our repeat estimate, may be practical predict clinically Lp(a). Supporting this, evidenced data seven US-based systems.

Язык: Английский

A DNA language model based on multispecies alignment predicts the effects of genome-wide variants DOI
Gonzalo Benegas,

Carlos Albors,

Alan J. Aw

и другие.

Nature Biotechnology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Язык: Английский

Процитировано

4
An integrative genomic toolkit for studying the genetic, evolutionary, and molecular underpinnings of eusociality in insects DOI Creative Commons

Dova Brenman-Suttner,

Amro Zayed

Current Opinion in Insect Science, Год журнала: 2024, Номер 65, С. 101231 - 101231

Опубликована: Июль 6, 2024

While genomic resources for social insects have vastly increased over the past two decades, we are still far from understanding genetic and molecular basis of eusociality. Here, briefly review three scientific advancements that, when integrated, can be highly synergistic advancing our knowledge genetics evolution eusocial traits. Population genomics provides a natural way to quantify strength selection on coding regulatory sequences, highlighting genes that undergone adaptive during or maintenance Genome-wide association studies (GWAS) used characterize complex architecture underlying traits identify candidate causal variants. Concurrently, CRISPR/Cas9 enables precise manipulation gene function both validate genotype–phenotype associations study biology interesting each approach has its own advantages disadvantages, which discuss herein, argue their combination will ultimately help us better understand behavior. Specifically, by triangulating across these different approaches, researchers directly loci with key phenotypes evidence positive relevant timescales associated eusociality in insects.

Язык: Английский

Процитировано

1
Polygenic modifiers of expressivity in telomere biology disorders DOI Creative Commons
Michael Poeschla, Uma P. Arora, Amanda J. Walne

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 21, 2024

Abstract Variable expressivity, where individuals carrying identical genetic variants display diverse phenotypes, presents an important challenge in clinical genetics. This is exemplified by the telomere biology disorders (TBDs), which exhibit tremendous heterogeneity despite their presumed monogenic nature, even among harboring same pathogenic variant. Here, we studied cohorts of patients with TBDs and population biobanks to demonstrate that common genome-wide polymorphisms associated variation length general combine large-effect causal significantly impact TBD expressivity. We go on show polygenic can contribute expressivity within a single family shared variant, rare converge set genes implicated maintenance. By elucidating role disease TBDs, these results provide framework for understanding phenotypic variability other disorders.

Язык: Английский

Процитировано

0
A novel method for predicting Lp(a) levels from routine outpatient genomic testing identifies those at risk of cardiovascular disease across a diverse cohort DOI Creative Commons
Natalie Telis, Hang Dai,

Ashley Waring

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 4, 2024

Abstract Background Lipoprotein(a) (Lp(a)) levels are a largely genetically determined and often an unmeasured predictor of future Atherosclerotic Cardiovascular Disease (ASCVD). With the increased use exome sequencing in clinical setting, there is opportunity to identify patients who have high chance having elevated Lp(a) therefore at risk ASCVD. However, accurate genetic predictors challenging design. In addition single nucleotide variants (SNVs), which summarized as combined score, significantly impacted by copy number variation repeats kringle IV subtype 2 domain (KIV-2), quantify. KIV-2 numbers highly variable across populations, understanding their impact on important creating equitable reliable Lp(a)-driven cardiovascular for all individuals. Methods We develop novel method quantify individuals’ total from data, validate this quantification against measured levels, then method, with SNV-based genotype entire all-comers cohort individuals health systems United States (Helix Research Network; N = 76,147) estimated level. Results Our genotyping strategy improved prediction those clinically-elevated measurements diverse cohort, especially not similar European reference where GRS-based estimates fall short (r 0.04 GRS, r 0.34 KIV2+GRS non-European). Importantly, genotypes associated earlier onset incidence ASCVD, compared average low retrospective analysis atherosclerotic diagnoses derived electronic records (EHRs). This holds large (CAD HRs=1.29, 1.58), subcohort (HRs=1.30,1.61) well trending significance Europeans (HRs=1.22,1.31). addition, least 2-fold enriched amongst ASCVD diagnosis despite lack EHR-based evidence traditional factors disease. Conclusions study demonstrates that predicted incorporating both SNV our repeat estimate, may be practical predict clinically Lp(a). Supporting this, evidenced data seven US-based systems.

Язык: Английский

Процитировано

0