Polygenic Risk Scores for Coronary Heart Disease DOI
Sadiya S. Khan,

Michael Pencina

JAMA, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 16, 2024

Sarah A. Abramowitz, BA; Kristin Boulier, MD; Karl Keat, BS; Katie M. Cardone, Manu Shivakumar, John DePaolo, MD, PhD; Renae Judy, MS; Francisca Bermudez, Nour Mimouni, Christopher Neylan, Dokyoon Kim, Daniel J. Rader, Marylyn D. Ritchie, Benjamin F. Voight, Bogdan Pasaniuc, Michael G. Levin, Scott Damrauer, Penn Medicine BioBank; J Rader; D Ritchie; JoEllen Weaver; Nawar Naseer; Giorgio Sirugo; Afiya Poindexter; Yi-An Ko; Kyle P. Nerz; Meghan Livingstone; Fred Vadivieso; Stephanie DerOhannessian; Teo Tran; Julia Stephanowski; Salma Santos; Ned Haubein; Joseph Dunn; Anurag Verma; Colleen Kripke; Marjorie Risman; Judy; Colin Wollack; Shefali S. M Damrauer; Yuki Bradford; Dudek; Theodore Drivas

Язык: Английский

Instability of high polygenic risk classification and mitigation by integrative scoring DOI Creative Commons
Anika Misra, Buu Truong, Sarah Urbut

и другие.

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Фев. 12, 2025

Polygenic risk scores (PRS) continue to improve with novel methods and expanding genome-wide association studies. Healthcare commercial laboratories are increasingly deploying PRS reports patients, but it is unknown how the classification of high polygenic changes across individual PRS. Here, we assess performance cataloged for three complex traits. We chronologically order all trait-related publications (Pubn) identify single Best(Pubn) each Pubn that has strongest target outcome. While demonstrates generally consistent population-level strengths associations, individuals in top 10% distribution varies widely. Using PRSmix framework, which integrates information several prediction, generate corresponding ChronoAdd(Pubn) combine from up including Pubn. When compared Best(Pubn), demonstrate more high-risk amongst themselves. This integrative scoring approach provides stable reliable an adaptable framework into new can be incorporated as they introduced, integrating easily current implementation strategies. Variability exists classifying diseases. Here authors show improves consistency overall toward clinical applications.

Язык: Английский

Процитировано

1

Cardiovascular Risk Predicts White Matter Hyperintensities, Brain Atrophy and Treatment Resistance in Major Depressive Disorder: Role of Genetic Liability DOI Creative Commons
Marco Paolini,

Melania Maccario,

V. Saredi

и другие.

Acta Psychiatrica Scandinavica, Год журнала: 2025, Номер unknown

Опубликована: Фев. 27, 2025

ABSTRACT Introduction Depressive disorders are a leading cause of global disease burden, particularly with the challenge treatment‐resistant depression (TRD). Research points to complex bidirectional relationship between cardiovascular (CV) risk factors and TRD, CV negatively impacting brain structure potentially influencing antidepressant resistance. Moreover, association genetic vulnerability suggests shared pathophysiological process two. This study investigates mediating role structural alterations in cerebrovascular (CeV) treatment resistance depression. Methods We assessed 165 inpatients Major depressive disorder. Each patient's was via QRISK 3 calculator. For subset patients, CeV polygenic scores (PRS) were obtained. All patients underwent T MRI scan, white matter hyperintensities estimates indicators trophic state Results Both PRSs associated status, hyperintensities, atrophy. Mediation analyses suggested that CV‐induced might underlie relation phenotypic Conclusion These results underscore need explore management as part strategies for depression, pointing toward linking heart health

Язык: Английский

Процитировано

0

Human genetics of metabolic dysfunction–associated steatotic liver disease: from variants to cause to precision treatment DOI Creative Commons
Vincent Chen, Annapurna Kuppa, Antonino Oliveri

и другие.

Journal of Clinical Investigation, Год журнала: 2025, Номер 135(7)

Опубликована: Март 31, 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by increased hepatic steatosis with cardiometabolic and a leading cause of advanced disease. We review here the genetic basis MASLD. The variants most consistently associated implicate genes involved in lipoprotein input or output, glucose metabolism, adiposity/fat distribution, insulin resistance, mitochondrial/ER biology. distinct mechanisms which these promote result effects on that may be best suited to precision medicine. Recent work gene-environment interactions has shown risk not fixed exacerbated attenuated modifiable (diet, exercise, alcohol intake) nonmodifiable environmental factors. Some steatosis-associated variants, notably those patatin-like phospholipase domain-containing 3 (PNPLA3) transmembrane 6 superfamily member 2 (TM6SF2), are developing adverse liver-related outcomes provide information beyond clinical stratification tools, especially individuals at intermediate high for Future better characterize heterogeneity combining genetics factors holistically predict develop therapies based required.

Язык: Английский

Процитировано

0

Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores—Reply DOI
Sarah Abramowitz, Michael G. Levin, Scott M. Damrauer

и другие.

JAMA, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

Язык: Английский

Процитировано

0

Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores DOI
Dan Shan

JAMA, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

Язык: Английский

Процитировано

0

Polygenic Risk Scores for Personalized Cardiovascular Pharmacogenomics―A Scoping Review DOI Creative Commons
Aeshita Dwivedi, Jobanjit Phulka,

Peyman Namdarimoghaddam

и другие.

Scientia Pharmaceutica, Год журнала: 2025, Номер 93(2), С. 18 - 18

Опубликована: Апрель 8, 2025

Cardiovascular disease (CVD) is the leading cause of mortality worldwide, often involving a strong genetic background. Polygenic risk scores (PRSs) combine cumulative effects multiple variants to quantify an individual’s susceptibility CVD. Pharmacogenomics (PGx) can further personalize treatment by tailoring medication choices profile. Even with these potential benefits, extent which PRS be integrated into PGx CVD remains unclear. Our review provides overview current evidence on application in CVD, examining clinical utility and limitations providing directions for future research. Following Preferred Reporting Items Systematic Reviews Meta-Analyses extension Scoping protocol, we conducted comprehensive literature search PubMed, EMBASE, Web Science. Studies investigating relationship between predicting efficacy, adverse effects, or cost-effectiveness cardiovascular medications were selected. Of 1894 articles identified, 32 met inclusion criteria. These studies predominantly examined lipid-lowering therapies, antihypertensives, antiplatelets, although other classes (e.g., rate-control drugs, ibuprofen/acetaminophen, diuretics, antiarrhythmics) also included. findings showed that most robustly validated especially statins, where reported individuals higher PRSs derived greatest reduction lipids while statins. analyzing antiarrhythmic demonstrated more variable outcomes, though certain did identify subgroups significantly improved response rates events. Though was tool many cases, found some key its applicability research, such as under-representation non-European-ancestry cohorts lack standardized outcome reporting. In conclusion, offers promise improving efficacy enhancing personalization individual level, several obstacles, need including broader ancestral diversity robust data remain. Future research must (i) prioritize validating ethnically diverse populations, (ii) refine derivation methods tailor them drug phenotypes, (iii) establish clear attainable guidelines standardizing reporting outcomes.

Язык: Английский

Процитировано

0

Using Genomics to Develop Personalized Cardiovascular Treatments DOI
Mihir M. Sanghvi, William J. Young, Hafiz Naderi

и другие.

Arteriosclerosis Thrombosis and Vascular Biology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 17, 2025

Advances in genomic technologies have significantly enhanced our understanding of both monogenic and polygenic etiologies cardiovascular disease. In this review, we explore how the utilization information is bringing personalized medicine approaches to forefront disease management. We discuss data can resolve diagnostic uncertainty, support cascade screening, inform treatment strategies. The role that genome-wide association studies had identifying thousands risk variants for diseases, these insights, harnessed through development scores, could advance prediction beyond traditional clinical algorithms. detail pharmacogenomics leverage genotype guide drug selection mitigate adverse events. Finally, present paradigm-shifting approach gene therapy, which holds promise being a curative intervention conditions.

Язык: Английский

Процитировано

0

Three Open Questions in Polygenic Score Portability DOI Creative Commons
Joyce Y. Wang,

Neeka Lin,

Michael Zietz

и другие.

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

Опубликована: Авг. 21, 2024

A major obstacle hindering the broad adoption of polygenic scores (PGS) is their lack "portability" to people that differ-in genetic ancestry or other characteristics-from GWAS samples in which effects were estimated. Here, we use UK Biobank measure change PGS prediction accuracy as a continuous function individuals' genome-wide dissimilarity sample ("genetic distance"). Our results highlight three gaps our understanding portability. First, extremely noisy at individual level and not well predicted by distance. In fact, variance explained comparably socioeconomic measures. Second, trends portability vary across traits. For several immunity-related traits, drops near zero quickly even intermediate levels This quick drop may reflect associations being more ancestry-specific traits than Third, show qualitative can depend on used. instance, for white blood cell count, (reduction mean squared error) increases with Together, cannot be understood through global groupings alone. There are other, understudied factors influencing portability, such specifics evolution trait its architecture, social context, construction score. Addressing these aid development application inform equitable genomic research.

Язык: Английский

Процитировано

3

Polygenic Risk Scores for Coronary Heart Disease DOI
Sadiya S. Khan,

Michael Pencina

JAMA, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 16, 2024

Sarah A. Abramowitz, BA; Kristin Boulier, MD; Karl Keat, BS; Katie M. Cardone, Manu Shivakumar, John DePaolo, MD, PhD; Renae Judy, MS; Francisca Bermudez, Nour Mimouni, Christopher Neylan, Dokyoon Kim, Daniel J. Rader, Marylyn D. Ritchie, Benjamin F. Voight, Bogdan Pasaniuc, Michael G. Levin, Scott Damrauer, Penn Medicine BioBank; J Rader; D Ritchie; JoEllen Weaver; Nawar Naseer; Giorgio Sirugo; Afiya Poindexter; Yi-An Ko; Kyle P. Nerz; Meghan Livingstone; Fred Vadivieso; Stephanie DerOhannessian; Teo Tran; Julia Stephanowski; Salma Santos; Ned Haubein; Joseph Dunn; Anurag Verma; Colleen Kripke; Marjorie Risman; Judy; Colin Wollack; Shefali S. M Damrauer; Yuki Bradford; Dudek; Theodore Drivas

Язык: Английский

Процитировано

0