Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation.

BACKGROUND: Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank. METHODS: The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score. RESULTS: Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm). CONCLUSIONS: We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.

Lipoprotein (a) is associated with increased risk of Abdominal Aortic Aneurysm.

Introduction: Lipoprotein(a) (Lp(a)) is a circulating apolipoprotein B (ApoB) containing particle that has been observationally linked to atherosclerotic cardiovascular disease and is the target of emerging therapeutics. Recent work has highlighted the role of circulating lipoproteins in abdominal aortic aneurysm (AAA). We sought to triangulate human observational and genetic evidence to evaluate the role of Lp(a) in AAA. Methods: We tested the association between circulating levels of Lp(a) and clinically diagnosed abdominal aortic aneurysms while controlling for traditional AAA risk factors and levels of ApoB using logistic regression among 795 individuals with and 374,772 individuals without AAA in the UK Biobank (UKB). Multivariable Mendelian randomization (MVMR) was used to test for putatively causal associations between Lp(a) and AAA controlling for ApoB. Genetic instruments for Lp(a) and ApoB were created from genome-wide association studies (GWAS) of Lp(a) and ApoB comprising 335,796 and 418,505 UKB participants, respectively. The instruments were tested for association with AAA using data from a GWAS of 39,221 individuals with and 1,086,107 without AAA. Results: Elevated Lp(a) levels were observationally associated with an increased risk of AAA (OR 1.04 per 10 nmol/L Lp(a); 95%CI 1.02-1.05; P<0.01). Clinically elevated Lp(a) levels (>150nmol/L) were likewise associated with an increased risk of AAA (OR 1.47; 95% CI 1.15-1.88; P < 0.01) when compared to individuals with Lp(a) levels <150nmol/L. MVMR confirmed a significant, ApoB-independent association between increased Lp(a) and increased risk of AAA (OR 1.13 per SD increase in Lp(a); 95%CI 1.02-1.24; P<0.02). Conclusion: Both observational and genetic analyses support an association between increased Lp(a) and AAA risk that is independent of ApoB. These findings suggest that Lp(a) may be a therapeutic target for AAA and drive the inclusion of AAA as an outcome in clinical trials of Lp(a) antagonists.

Population Performance and Individual Agreement of Coronary Artery Disease Polygenic Risk Scores.

Importance: Polygenic risk scores (PRSs) for coronary artery disease (CAD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease liability is a critical consideration for clinical implementation that remains uncharacterized. Objective: Characterize the reliability of CAD PRSs that perform equivalently at the population level at predicting individual-level risk. Design: Cross-sectional Study. Setting: All of Us Research Program (AOU), Penn Medicine Biobank (PMBB), and UCLA ATLAS Precision Health Biobank. Participants: Volunteers of diverse genetic backgrounds enrolled in AOU, PMBB, and UCLA with available electronic health record and genotyping data. Exposures: Polygenic risk for CAD from previously published PRSs and new PRSs developed separately from the testing cohorts. Main Outcomes and Measures: Sets of CAD PRSs that perform population prediction equivalently were identified by comparing calibration and discrimination (Brier score and AUROC) of generalized linear models of prevalent CAD using Bayesian analysis of variance. Among equivalently performing scores, individual-level agreement between risk estimates was tested with intraclass correlation (ICC) and Light's Kappa, measures of inter-rater reliability. Results: 50 PRSs were calculated for 171,095 AOU participants. When included in a model of prevalent CAD, 48 scores had practically equivalent Brier scores and AUROCs (region of practical equivalence = 0.02). Across these scores, 84% of participants had at least one score in both the top and bottom risk quintile. Continuous agreement of individual risk predictions from the 48 scores was poor, with an ICC of 0.351 (95% CI; 0.349, 0.352). Agreement between two statistically equivalent scores was moderate, with an ICC of 0.649 (95% CI; 0.646, 0.652). Light's Kappa, used to evaluate consistency of assignment to high-risk thresholds, did not exceed 0.56 (interpreted as 'fair') across statistically and practically equivalent scores. Repeating the analysis among 41,193 PMBB and 50,748 UCLA participants yielded different sets of statistically and practically equivalent scores which also lacked strong individual agreement. Conclusions and Relevance: Across three diverse biobanks, CAD PRSs that performed equivalently at the population level produced unreliable individual risk estimates. Approaches to clinical implementation of CAD PRSs must consider the potential for discordant individual risk estimates from otherwise indistinguishable scores.

Genome-Wide Association Study Identifies Genes for Hair Growth and Patterning are Associated With Pilonidal Disease.

BACKGROUND: Pilonidal sinus disease is a highly morbid condition characterized by the formation of chronic sinus tracts throughout the sacrococcygeal region. Despite its commonality and strong association with family history, no prior investigation of genetic risk factors for pilonidal sinus disease exists. OBJECTIVE: To identify genetic risk factors for pilonidal sinus disease. DESIGN: A genome-wide association study. SETTINGS: The United Kingdom Biobank, FinnGen Biobank, and Penn Medicine BioBank. PATIENTS: There were 772,072 participants. MAIN OUTCOME MEASURE: Genome-wide significant variants ( p < 5 × 10 -8 ) were mapped to genes using physical distance and gene expression in skin. Genetic correlation between pilonidal sinus disease and morphometric, androgen-driven, and hair phenotypes was estimated with linkage disequilibrium score regression. Finally, a genome-first approach to rare predicted deleterious variants in hair shaft genes TCHH , PADI3 , and TGM3 was conducted for association with pilonidal sinus disease via the Penn Medicine BioBank. RESULTS: A genome-wide association study comprising 2835 individuals with pilonidal sinus disease identified 5 genome-wide significant loci, prioritizing HDAC9, TBX15, WARS2, RP11-293M10.1 , PRKAR1B , TWIST1, GPATCH2L, NEK9 , and EIF2B2 , as putative causal genes; several of these genes have known roles in balding and hair patterning. There was a significant correlation between the genetic background of pilonidal sinus disease and the androgen-driven hair traits of male pattern baldness and young age at first facial hair. In a candidate analysis of genes associated with syndromic hair disorders, rare coding variants in TCHH , a monogenic cause of uncombable hair syndrome, were associated with increased prevalence of pilonidal sinus disease (OR 4.81 [95% CI, 2.06-11.2]). LIMITATIONS: This study is limited to European ancestry. However, because there is a higher incidence of pilonidal sinus disease in men of European ancestry, this analysis is focused on the at-risk population. CONCLUSIONS: Genetic analysis of pilonidal sinus disease identified shared genetic architecture with hair biology and androgen-driven traits. As the first study investigating the genetic basis of pilonidal sinus disease, this provides biological insight into the long-appreciated connection between the disease state, male sex, and hair. See Video abstract. UN ESTUDIO DE ASOCIACIN DEL GENOMA COMPLETO IDENTIFICA GENES DEL CRECIMIENTO Y EL PATRN DEL PELO ASOCIADOS A LA ENFERMEDAD PILONIDAL: ANTECEDENTES:La enfermedad del seno pilonidal es una condición muy mórbida caracterizada por la formación de tractos sinusales crónicos en toda la región sacrococcígea. A pesar de su frecuencia y su fuerte asociación con los antecedentes familiares, no se han investigado previamente los factores de riesgo genéticos de la enfermedad sinusal pilonidal.OBJETIVO:Identificar factores genéticos de riesgo para la enfermedad del seno pilonidal.DISEÑO:Estudio de asociación de genoma completo.CONJUNTOS:Biobanco del Reino Unido, Biobanco FinnGen y Biobanco PennMedicine.PACIENTES:772.072 participantes.MEDIDA DE RESULTADO PRINCIPAL:Las variantes significativas en todo el genoma (p < 5x10-8) se asignaron a genes utilizando la distancia física y la expresión génica en la piel. La correlación genética entre la enfermedad del seno pilonidal y los fenotipos morfométricos, androgénicos y de cabello se estimó con regresión de puntuación LD. Por último, se realizó una aproximación genómica a variantes deletéreas raras predichas en los genes del tallo piloso TCHH, PADI3 y TGM3 para su asociación con la enfermedad del seno pilonidal a través del Biobanco PennMedicine.RESULTADOS:El estudio de asociación de todo el genoma, que incluyó a 2.835 individuos con enfermedad del seno pilonidal, identificó 5 loci significativos en todo el genoma, dando prioridad a HDAC9, TBX15, WARS2, RP11-293M10.1, PRKAR1B, TWIST1, GPATCH2L, NEK9 y EIF2B2, como genes causales putativos; varios de estos genes tienen funciones conocidas en la calvicie y el patrón del cabello. Se observó una correlación significativa entre los antecedentes genéticos de la enfermedad del seno pilonidal y los de los rasgos calvicie de patrón masculino y edad temprana del primer vello facial impulsados por andrógenos. En un análisis de genes candidatos asociados a trastornos capilares sindrómicos, las variantes raras de codificación en TCHH, una causa monogénica del síndrome capilar incombustible, se asociaron a una mayor prevalencia de la enfermedad del seno pilonidal (OR 4,81 [IC del 5%, 2,06-11,2]).LIMITACIONES:Este estudio se limita a la ascendencia europea. Sin embargo, debido a que hay una mayor incidencia de la enfermedad sinusal pilonidal en los hombres de ascendencia europea, este análisis se centra en la población de riesgo.CONCLUSIÓN:El análisis genético de la enfermedad del seno pilonidal identificó una arquitectura genética compartida con la biología del cabello y los rasgos impulsados por andrógenos. Siendo el primer estudio que investiga las bases genéticas de la enfermedad del seno pilonidal, esto proporciona una visión biológica de la conexión, apreciada desde hace tiempo, entre el estado de la enfermedad, el sexo masculino y el cabello. (Traducción-Dr. Aurian Garcia Gonzalez ).

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

BACKGROUND: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). METHODS: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. RESULTS: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. CONCLUSIONS: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People With Type 2 Diabetes.

OBJECTIVE: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD. RESULTS: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648, hazard ratio [HR] 1.23, P = 3.6 × 10-9), rs77142250 (near HS3ST1, HR 1.89, P = 9.9 × 10-9), and rs335407 (near TFB1M/NOX3, HR 1.25, P = 1.5 × 10-8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison-adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10-16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Titin-Truncating variants Predispose to Dilated Cardiomyopathy in Diverse Populations.

Importance: The effect of high percentage spliced in (hiPSI) TTN truncating variants (TTNtvs) on risk of dilated cardiomyopathy (DCM) has historically been studied among population subgroups defined by genetic similarity to European reference populations. This has raised questions about the effect of TTNtvs in diverse populations, especially among individuals genetically similar to African reference populations. Objective: To determine the effect of TTNtvs on risk of DCM in diverse population as measured by genetic distance (GD) in principal component (PC) space. Design: Cohort study. Setting: Penn Medicine Biobank (PMBB) is a large, diverse biobank. Participants: Participants were recruited from across the Penn Medicine healthcare system and volunteered to have their electronic health records linked to biospecimen data including DNA which has undergone whole exome sequencing. Main Outcomes and Measures: Risk of DCM among individuals carrying a hiPSI TTNtv. Results: Carrying a hiPSI TTNtv was associated with DCM among PMBB participants across a range of GD deciles from the 1000G European centroid; the effect estimates ranged from odds ratio (OR) = 3.29 (95% confidence interval [CI] 1.26 to 8.56) to OR = 9.39 (95% CI 3.82 to 23.13). When individuals were assigned to population subgroups based on genetic similarity to the 1000G reference populations, hiPSI TTNtvs conferred significant risk of DCM among those genetically similar to the 1000G European reference population (OR = 7.55, 95% CI 4.99 to 11.42, P<0.001) and individuals genetically similar to the 1000G African reference population (OR 3.50, 95% CI 1.48 to 8.24, P=0.004). Conclusions and Relevance: TTNtvs are associated with increased risk of DCM among a diverse cohort. There is no significant difference in effect of TTNtvs on DCM risk across deciles of GD from the 1000G European centroid, suggesting genetic background should not be considered when screening individuals for titin-related DCM.

Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine.

Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.

Genome-wide association meta-analysis identifies risk loci for abdominal aortic aneurysm and highlights PCSK9 as a therapeutic target.

Abdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in AAA pathogenesis. These genes also indicate overlap between the development of AAA and other monogenic aortopathies, particularly via transforming growth factor ß signaling. Motivated by the strong evidence for the role of lipid metabolism in AAA, we used Mendelian randomization to establish the central role of nonhigh-density lipoprotein cholesterol in AAA and identified the opportunity for repurposing of proprotein convertase, subtilisin/kexin-type 9 (PCSK9) inhibitors. This was supported by a study demonstrating that PCSK9 loss of function prevented the development of AAA in a preclinical mouse model.

Relationships between body fat distribution and metabolic syndrome traits and outcomes: A mendelian randomization study.

BACKGROUND: Obesity is a complex, multifactorial disease associated with substantial morbidity and mortality worldwide. Although it is frequently assessed using BMI, many epidemiological studies have shown links between body fat distribution and obesity-related outcomes. This study examined the relationships between body fat distribution and metabolic syndrome traits using Mendelian Randomization (MR). METHODS/FINDINGS: Genetic variants associated with visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and gluteofemoral adipose tissue (GFAT), as well as their relative ratios, were identified from a genome wide association study (GWAS) performed with the United Kingdom BioBank. GWAS summary statistics for traits and outcomes related to metabolic syndrome were obtained from the IEU Open GWAS Project. Two-sample MR and BMI-controlled multivariable MR (MVMR) were performed to examine relationships between each body fat measure and ratio with the outcomes. Increases in absolute GFAT were associated with a protective cardiometabolic profile, including lower low density lipoprotein cholesterol (ß: -0.19, [95% CI: -0.28, -0.10], p < 0.001), higher high density lipoprotein cholesterol (ß: 0.23, [95% CI: 0.03, 0.43], p = 0.025), lower triglycerides (ß: -0.28, [95% CI: -0.45, -0.10], p = 0.0021), and decreased systolic (ß: -1.65, [95% CI: -2.69, -0.61], p = 0.0019) and diastolic blood pressures (ß: -0.95, [95% CI: -1.65, -0.25], p = 0.0075). These relationships were largely maintained in BMI-controlled MVMR analyses. Decreases in relative GFAT were linked with a worse cardiometabolic profile, with higher levels of detrimental lipids and increases in systolic and diastolic blood pressures. CONCLUSION: A MR analysis of ASAT, GFAT, and VAT depots and their relative ratios with metabolic syndrome related traits and outcomes revealed that increased absolute and relative GFAT were associated with a favorable cardiometabolic profile independently of BMI. These associations highlight the importance of body fat distribution in obesity and more precise means to categorize obesity beyond BMI.

Using a polygenic score to account for genomic risk factors in a model to detect individuals with dilated ascending thoracic aortas.

Background: Ascending thoracic aortic dilation is a complex trait that involves modifiable and non-modifiable risk factors and can lead to thoracic aortic aneurysm and dissection. Clinical risk factors have been shown to predict ascending thoracic aortic diameter. Polygenic scores (PGS) are increasingly used to assess clinical risk for multifactorial diseases. The degree to which a PGS can improve aortic diameter prediction is not known. In this study we tested the extent to which the addition of a PGS to clinical prediction algorithms improves the prediction of aortic diameter. Methods: The patient cohort comprised 6,790 Penn Medicine Biobank (PMBB) participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a large genome wide association study of thoracic aortic diameter in the UK biobank and were compared to the performance of the standard and a reweighted variation of the recently published AORTA Score. Results: Cohort participants were 56% male, had a median age of 61 years (IQR 52-70) with a mean ascending aortic diameter of 3.4 cm (SD 0.5). Compared to the AORTA Score which explained 28.4% (95% CI 28.1% to 29.2%) of the variance in aortic diameter, AORTA Score + PGS explained 28.8%, (95% CI 28.1% to 29.6%), the reweighted AORTA score explained 30.4% (95% CI 29.6% to 31.2%), and the reweighted AORTA Score + PGS explained 31.0% (95% CI 30.2% to 31.8%). The addition of a PGS to either the AORTA Score or the reweighted AORTA Score improved model sensitivity for the identifying individuals with a thoracic aortic diameter ≥ 4 cm. The respective areas under the receiver operator characteristic curve for the AORTA Score + PGS (0.771, 95% CI 0.756 to 0.787) and reweighted AORTA Score + PGS (0.785, 95% CI 0.770 to 0.800) were greater than the standard AORTA Score (0.767, 95% CI 0.751 to 0.783) and reweighted AORTA Score (0.780 95% CI 0.765 to 0.795). Conclusions: We demonstrated that inclusion of a PGS to the AORTA Score results in a small but clinically meaningful performance enhancement. Further investigation is necessary to determine if combining genetic and clinical risk prediction improves outcomes for thoracic aortic disease.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD. METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D. RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance (P<5.0×10-8): rs147138607 (intergenic variant between CACNA1E and ZNF648) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, P=3.6×10-9, rs11444867 (intergenic variant near HS3ST1) with HR 1.89, 95% CI 1.52 - 2.35, P=9.9×10-9, and rs335407 (intergenic variant between TFB1M and NOX3) HR 1.25, 95% CI 1.16 - 1.35, P=1.5×10-8. Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P<0.05, and 5 were significant after Bonferroni correction (P<0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase (P=1.0×10-16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Carriers of rare damaging CCR2 genetic variants are at lower risk of atherosclerotic disease.

Background: The CCL2/CCR2 axis governs monocyte trafficking and recruitment to atherosclerotic lesions. Human genetic analyses and population-based studies support an association between circulating CCL2 levels and atherosclerosis. Still, it remains unknown whether pharmacological targeting of CCR2, the main CCL2 receptor, would provide protection against human atherosclerotic disease. Methods: In whole-exome sequencing data from 454,775 UK Biobank participants (40-69 years), we identified predicted loss-of-function (LoF) or damaging missense (REVEL score >0.5) variants within the CCR2 gene. We prioritized variants associated with lower monocyte count (p<0.05) and tested associations with vascular risk factors and risk of atherosclerotic disease over a mean follow-up of 14 years. The results were replicated in a pooled cohort of three independent datasets (TOPMed, deCODE and Penn Medicine BioBank; total n=441,445) and the effect of the most frequent damaging variant was experimentally validated. Results: A total of 45 predicted LoF or damaging missense variants were identified in the CCR2 gene, 4 of which were also significantly associated with lower monocyte count, but not with other white blood cell counts. Heterozygous carriers of these variants were at a lower risk of a combined atherosclerosis outcome, showed a lower burden of atherosclerosis across four vascular beds, and were at a lower lifetime risk of coronary artery disease and myocardial infarction. There was no evidence of association with vascular risk factors including LDL-cholesterol, blood pressure, glycemic status, or C-reactive protein. Using a cAMP assay, we found that cells transfected with the most frequent CCR2 damaging variant (3:46358273:T:A, M249K, 547 carriers, frequency: 0.14%) show a decrease in signaling in response to CCL2. The associations of the M249K variant with myocardial infarction were consistent across cohorts (ORUKB: 0.62 95%CI: 0.39-0.96; ORexternal: 0.64 95%CI: 0.34-1.19; ORpooled: 0.64 95%CI: 0.450.90). In a phenome-wide association study, we found no evidence for higher risk of common infections or mortality among carriers of damaging CCR2 variants. Conclusions: Heterozygous carriers of damaging CCR2 variants have a lower burden of atherosclerosis and lower lifetime risk of myocardial infarction. In conjunction with previous evidence from experimental and epidemiological studies, our findings highlight the translational potential of CCR2-targeting as an atheroprotective approach.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

Genome-wide association study of thoracic aortic aneurysm and dissection in the Million Veteran Program.

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Evaluation of the Performance of the RECODe Equation with the Addition of Polygenic Risk Scores for Adverse Cardiovascular Outcomes in Individuals with Type II Diabetes.

Aims/Hypothesis: Individuals with T2D are at an increased risk of developing cardiovascular complications; early identification of individuals can lead to an alteration of the natural history of the disease. Current approaches to risk prediction tailored to individuals with T2D are exemplified by the RECODe algorithms which predict CVD outcomes among individuals with T2D. Recent efforts to improve CVD risk prediction among the general population have included the incorporation of polygenic risk scores (PRS). This paper aims to investigate the utility of the addition of a coronary artery disease (CAD), stroke and heart failure risk score to the current RECODe model for disease stratification. Methods: We derived PRS using summary statistics for ischemic stroke (IS) from the coronary artery disease (CAD) and heart failure (HF) and tested prediction accuracy in the Penn Medicine Biobank (PMBB). A Cox proportional hazards model was used for time-to-event analyses within our cohort, and we compared model discrimination for the RECODe model with and without a PRS using AUC. Results: The RECODe model alone demonstrated an AUC [95% CI] of 0.67 [0.62-0.72] for ASCVD; the addition of the three PRS to the model demonstrated an AUC [95% CI] of 0.66 [0.63-0.70]. A z-test to compare the AUCs of the two models did not demonstrate a detectable difference between the two models (p=0.97). Conclusions/Interpretation: In the present study, we demonstrate that although PRS associate with CVD outcomes independent of traditional risk factors among individuals with T2D, the addition of PRS to contemporary clinical risk models does not specifically improve the predictive performance as compared to the baseline model.

Session Introduction: SALUD: Scalable Applications of cLinical risk Utility and preDiction.

This PSB 2023 session discusses challenges in clinical implication and application of risk prediction models, which includes but is not limited to: implementation of risk models, responsible use of polygenic risk scores (PGS), and other risk prediction strategies. We focus on the development and use of new, scalable methods for harmonizing and refining risk prediction models by incorporating genetic and non-genetic risk factors, applying new phenotyping strategies, and integrating clinical factors and biomarkers. Lastly, we will discuss innovation in expanding the utility of these prediction models to underrepresented populations. This session focuses on the overarching theme of enabling early diagnosis, and treatment and preventive measures related to complex diseases and comorbidities.

Metabolite patterns associated with individual response to supervised exercise therapy in patients with intermittent claudication.

Objective: Supervised exercise therapy (SET) is the first line treatment for intermittent claudication owing to peripheral arterial disease. Despite multiple randomized controlled trials proving the efficacy of SET, there are large differences in individual patient's responses. We used plasma metabolomics to identify potential metabolic influences on the individual response to SET. Methods: Primary metabolites, complex lipids, and lipid mediators were measured on plasma samples taken at before and after Gardner graded treadmill walking tests that were administered before and after 12 weeks of SET. We used an ensemble modeling approach to identify metabolites or changes in metabolites at specific time points that associated with interindividual variability in the functional response to SET. Specific time points analyzed included baseline metabolite levels before SET, dynamic metabolomics changes before SET, the difference in pre- and post-SET baseline metabolomics, and the difference (pre- and post-SET) of the dynamic (pre- and post-treadmill). Results: High levels of baseline anandamide levels pre- and post-SET were associated with a worse response to SET. Increased arachidonic acid (AA) and decreased levels of the AA precursor dihomo-γ-linolenic acid across SET were associated with a worse response to SET. Participants who were able to tolerate large increases in AA during acute exercise had longer, or better, walking times both before and after SET. Conclusions: We identified two pathways of relevance to individual response to SET that warrant further study: anandamide synthesis may activate endocannabinoid receptors, resulting in worse treadmill test performance. SET may train patients to withstand higher levels of AA, and inflammatory signaling, resulting in longer walking times. Clinical Relevance: This manuscript describes the use of metabolomic techniques to measure the interindividual effects of SET in patients with peripheral artery disease (PAD). We identified high levels of AEA are linked to CB1 signaling and activation of inflammatory pathways. This alters energy expenditure in myoblasts by decreasing glucose uptake and may induce an acquired skeletal muscle myopathy. SET may also help participants tolerate increased levels of AA and inflammation produced during exercise, resulting in longer walking times. This data will enhance understanding of the pathophysiology of PAD and the mechanism by which SET improves walking intolerance.

The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population.

The Penn Medicine BioBank (PMBB) is an electronic health record (EHR)-linked biobank at the University of Pennsylvania (Penn Medicine). A large variety of health-related information, ranging from diagnosis codes to laboratory measurements, imaging data and lifestyle information, is integrated with genomic and biomarker data in the PMBB to facilitate discoveries and translational science. To date, 174,712 participants have been enrolled into the PMBB, including approximately 30% of participants of non-European ancestry, making it one of the most diverse medical biobanks. There is a median of seven years of longitudinal data in the EHR available on participants, who also consent to permission to recontact. Herein, we describe the operations and infrastructure of the PMBB, summarize the phenotypic architecture of the enrolled participants, and use body mass index (BMI) as a proof-of-concept quantitative phenotype for PheWAS, LabWAS, and GWAS. The major representation of African-American participants in the PMBB addresses the essential need to expand the diversity in genetic and translational research. There is a critical need for a "medical biobank consortium" to facilitate replication, increase power for rare phenotypes and variants, and promote harmonized collaboration to optimize the potential for biological discovery and precision medicine.

Exome-wide association analysis of CT imaging-derived hepatic fat in a medical biobank.

Nonalcoholic fatty liver disease is common and highly heritable. Genetic studies of hepatic fat have not sufficiently addressed non-European and rare variants. In a medical biobank, we quantitate hepatic fat from clinical computed tomography (CT) scans via deep learning in 10,283 participants with whole-exome sequences available. We conduct exome-wide associations of single variants and rare predicted loss-of-function (pLOF) variants with CT-based hepatic fat and perform cross-modality replication in the UK Biobank (UKB) by linking whole-exome sequences to MRI-based hepatic fat. We confirm single variants previously associated with hepatic fat and identify several additional variants, including two (FGD5 H600Y and CITED2 S198_G199del) that replicated in UKB. A burden of rare pLOF variants in LMF2 is associated with increased hepatic fat and replicates in UKB. Quantitative phenotypes generated from clinical imaging studies and intersected with genomic data in medical biobanks have the potential to identify molecular pathways associated with human traits and disease.