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Background: Genome-wide association studies have reported 23 gene loci related to abdominal aortic aneurysm (AAA)—a potentially lethal condition characterized by a weakened dilated vessel wall. This study aimed to identify proteomic signatures and pathways related to these risk loci to better characterize AAA genetic susceptibility. Methods: Plasma concentrations of 4870 proteins were determined using a DNA aptamer-based array. Linear regression analysis estimated the associations between the 23 risk alleles and plasma protein levels with adjustments for potential confounders in a race-stratified analysis of 1671 Black and 7241 White participants. Significant proteins were then evaluated for their prediction of clinical AAA (454 AAA events in 11 064 individuals), and those significantly associated with AAA were further interrogated using Mendelian randomization analysis. Results: Risk variants proximal to PSRC1-CELSR2-SORT1 , PCIF1-ZNF335-MMP9, RP11-136O12.2/TRIB1 , ZNF259/APOA5, IL6R , PCSK9 , LPA , and APOE were associated with 118 plasma proteins in Whites and 59 were replicated in Black participants. Novel associations with clinical AAA incidence were observed for kit ligand (HR, 0.59 [95% CI, 0.42–0.82] for top versus first quintiles) and neogenin (HR, 0.64 [95% CI, 0.46–0.88]) over a median 21.2-year follow-up; neogenin was also associated with ultrasound-detected asymptomatic AAA (N=4295; 57 asymptomatic AAA cases). Mendelian randomization inverse variance weighted estimates suggested that AAA risk is promoted by lower levels of kit ligand (OR per SD=0.67; P =1.4×10 −5 ) and neogenin (OR per SD=0.50; P =0.03). Conclusions: Low levels of neogenin and kit ligand may be novel risk factors for AAA development in potentially causal pathways. These findings provide insights and potential targets to reduce AAA susceptibility.

Background There is an incompletely understood increased risk for cardiovascular disease (CVD) among people with HIV (PWH). We investigated if a collection of biomarkers were associated with CVD among PWH. Mendelian randomization (MR) was used to identify potentially causal associations. Methods Data from follow-up in 4 large trials among PWH were used to identify 131 incident CVD cases and they were matched to 259 participants without incident CVD (controls). Tests of associations between 460 baseline protein levels and case status were conducted. Results Univariate analysis found CLEC6A, HGF, IL-6, IL-10RB, and IGFBP7 as being associated with case status and a multivariate model identified 3 of these: CLEC6A (odds ratio [OR] = 1.48, P = .037), HGF (OR = 1.83, P = .012), and IL-6 (OR = 1.45, P = .016). MR methods identified 5 significantly associated proteins: AXL, CHI3L1, GAS6, IL-6RA, and SCGB3A2. Conclusions These results implicate inflammatory and fibrotic processes as contributing to CVD. While some of these biomarkers are well established in the general population and in PWH (IL-6 and its receptor), some are novel to PWH (HGF, AXL, and GAS6) and some are novel overall (CLEC6A). Further investigation into the uniqueness of these biomarkers in PWH and the role of these biomarkers as targets among PWH is warranted.

Background: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. Methods: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. Results: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. Conclusions: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Background Genome-wide association studies have identified six genetic variants associated with severe COVID-19, yet the mechanisms through which they may affect disease remains unclear. We investigated proteomic signatures related to COVID-19 risk variants rs657152 (ABO), rs10735079 (OAS1/OAS2/OAS3), rs2109069 (DPP9), rs74956615 (TYK2), rs2236757 (IFNAR2) and rs11385942 (SLC6A20/LZTFL1/CCR9/FYCO1/CXCR6/XCR1) as well as their corresponding downstream pathways that may promote severe COVID-19 in risk allele carriers and their potential relevancies to other infection outcomes. Methods A DNA aptamer-based array measured 4870 plasma proteins among 11 471 participants. Linear regression estimated associations between the COVID-19 risk variants and proteins with correction for multiple comparisons, and canonical pathway analysis was conducted. Cox regression assessed associations between proteins identified in the main analysis and risk of incident hospitalized respiratory infections (2570 events) over a 20.7-year follow-up. Results The ABO variant rs657152 was associated with 84 proteins in 7241 white participants with 24 replicated in 1671 Black participants. The TYK2 variant rs74956615 was associated with ICAM-1 and -5 in white participants with ICAM-5 replicated in Black participants. Of the 84 proteins identified in the main analysis, seven were significantly associated with incident hospitalized respiratory infections including Ephrin type-A receptor 4 (hazard ratio (HR): 0.87; P = 2.3 × 10−11) and von Willebrand factor type A (HR: 1.17; P = 1.6x10−13). Conclusions Novel proteomics signatures and pathways for COVID-19-related risk variants TYK2 and ABO were identified. A subset of these proteins predicted greater risk of incident hospitalized pneumonia and respiratory infections. Further studies to examine these proteins in COVID-19 patients are warranted.

OBJECTIVE The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis. RESEARCH DESIGN AND METHODS In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47–70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments. RESULTS There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10−5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk. CONCLUSIONS We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.

Aims/hypothesis: Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study. Methods: We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci. Results: Four novel associations were identified (p < 5 × 10−9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis. Conclusions/interpretation: Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations. Data availability: Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics).

Plasma proteomic profiling may aid in the discovery of novel biomarkers upstream of the development of atrial fibrillation (AF). We used data from the Atherosclerosis Risk in Communities study to examine the relation between large-scale proteomics and incident AF in a cohort of older-aged adults in the United States. We quantified 4,877 plasma proteins in Atherosclerosis Risk in Communities participants at visit 5 (2011–2013) using an aptamer-based proteomic profiling platform. We used Cox proportional hazards models to assess the association between protein levels and incident AF, and explored relation of selected protein biomarkers using annotated pathway analysis. Our study included 4,668 AF-free participants (mean age 75 ± 5 years; 59% female; 20% Black race) with proteomic measures. A total of 585 participants developed AF over a mean follow-up of 5.7 ± 1.7 years. After adjustment for clinical factors associated with AF, N-terminal pro-B-type natriuretic peptide (NT-proBNP) was associated with the risk of incident AF (hazard ratio, 1.82; 95% CI, 1.68 to 1.98; p, 2.91 × 10−45 per doubling of NT-proBNP). In addition, 36 other proteins were also significantly associated with incident AF after Bonferroni correction. We further adjusted for medication use and estimated glomerular filtration rate and found 17 proteins, including angiopoietin-2 and transgelin, that remained significantly associated with incident AF. Pathway analyses implicated the inhibition of matrix metalloproteases as the top canonical pathway in AF pathogenesis. In conclusion, using a large-scale proteomic platform, we identified both novel and established proteins associated with incident AF and explored mechanistic pathways of AF development.

Background The cellular adhesion pathway has been suggested as playing an important role in the pathogenesis of atrial fibrillation (AF). However, prior studies that have investigated the role of adhesion pathway proteins in risk of AF have been limited in the number of proteins that were studied and in the ethnic and racial diversity of the study population. Therefore we aimed to study the associations of fifteen adhesion pathway proteins with incident AF in a large, diverse population. Methods Multi-Ethnic Study of Atherosclerosis participants from four races/ethnicities (n = 2504) with protein levels measured were followed for incident AF (n = 253). HGF protein was measured on Exam 1 samples (N = 6669; AF n = 851). Cox proportional hazards regression was used to assess the association of AF with 15 adhesion pathway proteins. Bonferroni correction was applied to account for multiple comparisons. Results After adjusting for potential confounding variables (age, sex, race/ethnicity, height, body mass index, systolic blood pressure, antihypertension therapy, diabetes status, current smoker, current alcohol use, and total and HDL cholesterol), and accounting for multiple testing (P Conclusions Circulating levels of MMP-2, TIMP-2, VCAM-1, and SLPI were positively associated with an increased risk of incident AF in a diverse population. Our findings suggest that adhesion pathway proteins may be important risk predictors of AF.

Aims/hypothesis The aim of this work was to assess the association between diabetes and risk for infection-related hospitalisation and mortality. Methods We conducted a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study. Diabetes was defined as a fasting glucose ≥7 mmol/l or non-fasting glucose ≥11.1 mmol/l, self-report of a diagnosis of diabetes by a physician, or current diabetes medication use. Hospitalisation for infection was ascertained from hospital discharge records. Participants were followed from 1987–1989 to 2019. Results We included 12,379 participants (mean age 54.5 years; 24.7% Black race; 54.3% female sex). During a median follow-up of 23.8 years, there were 4229 new hospitalisations for infection. After adjusting for potential confounders, people with (vs without) diabetes at baseline had a higher risk for hospitalisation for infection (HR 1.67 [95% CI 1.52, 1.83]). Results were generally consistent across infection type but the association was especially pronounced for foot infection (HR 5.99 [95% CI 4.38, 8.19]). Diabetes was more strongly associated with hospitalisation for infection in younger participants and Black people. Overall infection mortality was low (362 deaths due to infection) but the adjusted risk was increased for people with diabetes (HR 1.72 [95% CI 1.28, 2.31]). Conclusions/interpretation Diabetes confers significant risk for infection-related hospitalisation. Enhancing prevention and early treatment of infection in those with diabetes is needed to reduce infection-related morbidity and mortality. Graphical abstract Supplementary Information The online version of this article (10.1007/s00125-021-05522-3) contains peer-reviewed but unedited supplementary material.

Objectives This study assessed the association of diabetes duration with incident heart failure (HF). Background Diabetes increases HF risk. However, the independent effect of diabetes duration on incident HF is unknown. Methods We included 9,734 participants (mean age 63 years, 58% women, 22% Black) at ARIC (Atherosclerosis Risk In Communities) Visit 4 (1996-1998) without HF or coronary heart disease. We calculated diabetes duration at Visit 4 (baseline), utilizing diabetes status at the first 4 ARIC visits spaced 3 years apart, and self-reported diagnosis date for those with diabetes diagnosed before Visit 1. We used Cox regression to estimate associations of diabetes duration with incident HF, accounting for intercurrent coronary heart disease and other risk factors. We performed analyses stratified by age ( Results Over 22.5 years of follow-up, there were 1,968 HF events. Compared to those without diabetes, HF risk rose with longer diabetes duration, with the highest risk among those with ≥15 y diabetes duration (HR: 2.82; 95% CI: 2.25-3.63). Each 5-year increase in diabetes duration was associated with a 17% (95% CI: 11-22) relative increase in HF risk. Similar results were observed across HF subtypes. The HF and diabetes duration associations were stronger among those aged Conclusions Delaying diabetes onset may augment HF prevention efforts, and therapies to improve HF outcomes might target those with long diabetes duration.

Objective: Leukocytes contribute to the development of abdominal aortic aneurysm (AAA). We evaluated whether associations of differential leukocyte counts with AAA persist after accounting for traditional risk factors of AAA. Approach and Results: Among 11 217 adults from the Atherosclerosis Risk in Communities Study, we evaluated associations of differential leukocyte counts at baseline (1987–1989) with incident AAAs over a median follow-up of 22.5 years, using Cox proportional hazards regression. Each differential leukocyte count was categorized into 5 groups—below normal, tertiles within the normal range, and above normal, with the first tertile serving as the referent. We identified 377 incident AAAs through 2011, using hospital discharge diagnoses, linked Medicare records, or death certificates. At baseline, higher neutrophil, monocyte, and eosinophil counts were associated with higher risk of AAA, independent of smoking, other differential leukocyte counts, and other traditional risk factors. The association with incident AAA was the strongest for above normal neutrophil count, with an adjusted hazard ratio (95% CI) of 2.17 (1.29–3.64). Below normal neutrophil, lymphocyte, eosinophil and basophil counts were associated with higher risk of AAA with adjusted hazard ratio (95% CI) between 1.86 (1.04–3.35) and 1.62 (1.10–2.39). Conclusions: Higher neutrophil, monocyte, and eosinophil counts in midlife are associated with higher risk of AAA, even after accounting for traditional risk factors such as smoking, obesity, and atherosclerosis. This suggests the need to identify nontraditional risk factors and treatment strategies to mitigate the residual risk of AAA conferred by midlife inflammation. Whether immunosuppression is associated with higher risk of AAA needs further investigation.

Background Inflammation is key in the pathogenesis of Nonalcoholic Fatty Liver Disease (NAFLD) – a common progressive liver disease. The soluble receptor for advanced glycation end products (sRAGE) attenuates inflammatory signaling; low levels of sRAGE are correlated with increased inflammation. Aim We sought to describe associations between sRAGE and NAFLD. Methods We conducted a cross-sectional analysis of 1088 Atherosclerosis Risk in Communities (ARIC) Study participants and used logistic regression to investigate the associations between sRAGE and NAFLD defined by elevated liver enzymes and fibrosis score. Results In this community-based sample (n = 1,088, mean age 56 years, 61% female, 78% Caucasian), persons in the lowest vs. highest quartile of sRAGE had significantly higher odds of elevated ALT (OR 2.82, 95% CI 1.18-6.76) but not elevated AST (OR 1.16, 95% CI 0.45-2.99); persons in the lowest vs. highest quartile had significantly lower odds of elevated FIB-4 index (OR 0.56, 95% CI 0.37-0.84). Conclusions We found an inverse cross-sectional association between sRAGE and liver inflammation; this is consistent with prior studies linking low sRAGE to inflammatory states. However, we observed a direct association between sRAGE and fibrosis. Our findings suggest that sRAGE is dynamic in NAFLD and patterns may vary with different stages of disease.

BackgroundSeveral hemostatic factors and inflammatory markers are associated with the risk of incident venous thromboembolism (VTE), however, most existing data are from case-control studies in Caucasian populations.ObjectivesWe aimed to prospectively confirm previous findings and explore less studied biomarkers in relation to VTE risk in a multi-racial/multi-ethnic cohort.MethodsCirculating levels of factor VIII, fibrinogen, D-dimer, plasmin-antiplasmin complex (PAP), C-reactive protein (CRP), and interleukin-6 (IL-6) were measured at baseline (2000-2002) in 6706 participants of the Multi-Ethnic Study of Atherosclerosis. Incident VTE was identified using hospitalization discharge codes from baseline to December 31, 2015. Hazard ratios (HRs) of VTE were estimated in Cox regression models.ResultsThere were 227 events during a median of 14years of follow-up. Compared with participants in the lowest quartile, the HRs for those above the 95th percentile and p for trend across categories were 3.50 (95% confidence interval [CI] 1.98-6.19; p&nbsp

BackgroundHeterogeneity in the long-term metabolic response to dietary macronutrient composition can be partially explained by genetic factors. However, few studies have demonstrated reproducible gene-diet interactions (GDIs), likely due in part to measurement error in dietary intake estimation as well as insufficient capture of rare genetic variation. Discovery analyses in ancestry-diverse cohorts that include rare genetic variants from whole-genome sequencing (WGS) could help identify genetic variants modifying the effects of dietary macronutrient composition on glycemic phenotypes.ObjectiveWe aimed to identify macronutrient GDIs across the genetic frequency spectrum associated with continuous glycemic traits in genetically and culturally diverse cohorts.MethodsWe analyzed N=33,187 diabetes-free participants from 10 cohorts in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program with WGS, self-reported diet, and glycemic traits (fasting glucose [FG], insulin [FI], and hemoglobin A1c [HbA1c]). We fit multivariable-adjusted linear mixed models for the main effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and for its interactions with genetic variants genome-wide. Tests were performed for both common variants and gene-based rare variant sets in each cohort followed by a combined cohort meta-analysis.ResultsIn main effect models, participants consuming more calories from carbohydrate at the expense of fat had modestly lower glycemic trait values (β per 250 kcal substitution for FG: −0.030 mmol/L, p=2.7×10−6; lnFI: −0.008 log(pmol/L), p=0.17; HbA1c: −0.013 %, p=0.025). In GDI analyses, a common African ancestry-enriched variant (rs79762542; 78 kb upstream of the FRAS1 gene) reached study-wide significance (p = 1.14×10−8) indicating a higher HbA1c with greater proportion of calories from carbohydrate vs. fat among minor allele carriers only. This interaction was replicated in the UK Biobank cohort. Simulations revealed that there is (1) a substantial impact of measurement error on statistical power for GDI discovery at these sample sizes, especially for rare genetic variants, and (2) over 150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error.ConclusionsOur analysis identified a potential genetic interaction modifying the dietary macronutrient-HbA1c association while highlighting the importance of precise exposure measurement and significantly increased sample size to identify additional similar effects.

Background: Despite improvements in population health, marked racial and ethnic disparities in longevity and cardiovascular disease (CVD) mortality persist. This study aimed to describe risks for all-cause and CVD mortality by race and ethnicity, before and after accounting for socioeconomic status (SES) and other factors, in the MESA study (Multi-Ethnic Study of Atherosclerosis). Methods: MESA recruited 6814 US adults, 45 to 84 years of age, free of clinical CVD at baseline, including Black, White, Hispanic, and Chinese individuals (2000–2002). Using Cox proportional hazards modeling with time-updated covariates, we evaluated the association of self-reported race and ethnicity with all-cause and adjudicated CVD mortality, with progressive adjustments for age and sex, SES (neighborhood SES, income, education, and health insurance), lifestyle and psychosocial risk factors, clinical risk factors, and immigration history. Results: During a median of 15.8 years of follow-up, 22.8% of participants (n=1552) died, of which 5.3% (n=364) died of CVD. After adjusting for age and sex, Black participants had a 34% higher mortality hazard (hazard ratio [HR], 1.34 [95% CI, 1.19–1.51]), Chinese participants had a 21% lower mortality hazard (HR, 0.79 [95% CI, 0.66–0.95]), and there was no mortality difference in Hispanic participants (HR, 0.99 [95% CI, 0.86–1.14]) compared with White participants. After adjusting for SES, the mortality HR for Black participants compared with White participants was reduced (HR, 1.16 [95% CI, 1.01–1.34]) but still statistically significant. With adjustment for SES, the mortality hazards for Chinese and Hispanic participants also decreased in comparison with White participants. After further adjustment for additional risk factors and immigration history, Hispanic participants (HR, 0.77 [95% CI, 0.63–0.94]) had a lower mortality risk than White participants, and hazard ratios for Black participants (HR, 1.08 [95% CI, 0.92–1.26]) and Chinese participants (HR, 0.81 [95% CI, 0.60–1.08]) were not significantly different from those of White participants. Similar trends were seen for CVD mortality, although the age- and sex-adjusted HR for CVD mortality for Black participants compared with White participants was greater than all-cause mortality (HR, 1.72 [95% CI, 1.34–2.21] compared with HR, 1.34 [95% CI, 1.19–1.51]). Conclusions: These results highlight persistent racial and ethnic differences in overall and CVD mortality, largely attributable to social determinants of health, and support the need to identify and act on systemic factors that shape differences in health across racial and ethnic groups.

Introduction: Proteomics could improve our understanding of the etiology of diabetes. We sought to identify proteomic signatures associated with incident diabetes. Method: We used data from the Atherosclerosis Risk in Communities (ARIC) Study (visit 2, 1990-92) in midlife (ages 47-70y) . We examined associations of 4955 plasma proteins measured using an aptamer-based platform in 11341 participants (∼50% women, ∼25% Black) without prevalent diabetes. We divided the data into discovery (2/3) and validation (1/3) sets. We used multivariable Cox regression to examine protein associations with incident diabetes (diagnosis or medication) . Statistical tests were based on Bonferroni corrected p-values. Results: In the discovery set (n=7907) , 1443 diabetes events accrued over a median (IQR 12, 21) years. We identified 568 proteins associated (p Conclusions: We identified multiple established and novel proteins associated with incident diabetes in midlife. Disclosure M.R. Rooney: None. J. Chen: None. O. Tang: None. C.M. Ballantyne: Consultant; Abbott Diagnostics, Althera Pharmaceuticals, Amarin Corporation, Amgen Inc., Arrowhead Pharmaceuticals, Inc., AstraZeneca, Corvidia Therapeutics, Denka Seiken, ESPERION Therapeutics, Inc., Genentech, Inc., Gilead Sciences, Inc., Illumina, Matinas BioPharma Inc, Merck & Co., Inc., New Amsterdam, Novartis Pharmaceuticals Corporation, Novo Nordisk, Pfizer Inc., Regeneron Pharmaceuticals Inc., Roche Diagnostics, Sanofi. Research Support; Abbott Diagnostics, Akcea Therapeutics, Amgen Inc., Arrowhead Pharmaceuticals, Inc., ESPERION Therapeutics, Inc., Ionis Pharmaceuticals, Novartis Pharmaceuticals Corporation, Regeneron Pharmaceuticals Inc., Roche Diagnostics. E. Boerwinkle: None. J. Echouffo Tcheugui: None. C.E. Ndumele: None. J.S. Pankow: None. P. Lutsey: None. L.E. Wagenknecht: None. M. Grams: None. E. Selvin: Other Relationship; Wolters Kluwer. J. Coresh: Consultant; Healthy.io Ltd. Research Support; National Institutes of Health.

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Introduction: There is a paucity of large-scale data from multiethnic populations on proteomic alterations related to type 2 diabetes, which could help identify prognostic mediators. Method: We analyzed 4,955 plasma proteins using SomaLogic v4.0 on 10,478 ARIC Study participants (Visit 2, 1990-92, mean age: 57±6 years, 56% women, 22% Black adults, 14% with diabetes) . We used logistic regression to quantify proteins associations with prevalent diabetes in a 2/3 discovery and 1/3 validation subset, with Bonferroni correction of P-values. Results: After adjustment for demographics, clinical, and lifestyle risk factors (Figure) , 642 proteins were significantly associated with diabetes in the discovery sample (p Conclusions: A large-scale proteomics approach identified numerous diabetes-related alterations. Pathway analysis and comparison to proteomic risk factors for diabetes incidence and complications will shed light on plasma proteomic consequences of diabetes and their relation to future risk. Disclosure J.B.Echouffo tcheugui: None. P.Lutsey: None. M.Grams: None. E.Selvin: Other Relationship; Wolters Kluwer. J.Coresh: Consultant; Healthy.io Ltd, Research Support; National Institutes of Health. J.Chen: None. M.R.Rooney: None. O.Tang: None. C.M.Ballantyne: Consultant; Abbott Diagnostics, Althera Pharmaceuticals, Amarin Corporation, Amgen Inc., Arrowhead Pharmaceuticals, Inc., AstraZeneca, Corvidia Therapeutics, Denka Seiken, ESPERION Therapeutics, Inc., Genentech, Inc., Gilead Sciences, Inc., Illumina, Matinas BioPharma Inc, Merck & Co., Inc., New Amsterdam, Novartis Pharmaceuticals Corporation, Novo Nordisk, Pfizer Inc., Regeneron Pharmaceuticals Inc., Roche Diagnostics, Sanofi, Research Support; Abbott Diagnostics, Akcea Therapeutics, Amgen Inc., Arrowhead Pharmaceuticals, Inc., ESPERION Therapeutics, Inc., Ionis Pharmaceuticals, Novartis Pharmaceuticals Corporation, Regeneron Pharmaceuticals Inc., Roche Diagnostics. E.Boerwinkle: None. C.E.Ndumele: None. J.S.Pankow: None. R.Demmer: None. Funding National Institutes of Health (K23 HL153774)

Background Hearing loss is highly prevalent in older ages and has several health consequences. Some cardiovascular risk factors are associated with worse hearing at older ages. Still, the role of midlife leisure-time physical activity (PA) as a risk factor for hearing loss is yet to be investigated. Methods Among 3 198 participants of the Atherosclerosis Risk in Communities study, we investigated the associations of midlife and change from mid- to late-life PA (assessed via modified Baecke questionnaire) with hearing loss (audiometric battery [worse-ear pure-tone average, and speech-in-noise test]) at older ages. We used regression analyses, adjusted for demographics, medical conditions, and noise exposure, to estimate differences in hearing between those who met and did not meet PA recommendations at midlife and at late life. Results A total of 1 386 (43.3%) participants met PA recommendations at midlife. These participants, compared to those who did not meet recommendations, had lower (better) pure-tone average by 1.51 (0.46, 2.55) decibels, identified 0.37 (0.01, 0.74) more words (better score) in the speech-in-noise test, and had a lower relative risk of having hearing loss at older ages (eg, relative risk ratio for severe hearing loss vs normal hearing = 0.70 [0.52, 0.95]). Similarly, those who persistently met PA recommendations from mid- to late life had, compared with those who did not, a better hearing at older ages. Conclusions Meeting PA public health recommendations in midlife and mid- to late life was associated with better hearing at older ages and reduced risk of hearing loss. Promoting adequate levels of PA may be an essential component of hearing care.

OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.