Kullo, Iftikhar J.

Abstract Objective To describe the development and implementation of an automated platform for genomic risk prediction that integrates multiple data types. Materials and methods Using the REDCap infrastructure, we constructed the R4 (Recruitment, Results, and Risk Reduction) platform to intake data from clinical sites, partner laboratories, participant surveys, and electronic health record (EHR) data across 13 institutions. Results The R4 Portal successfully integrated data to generate genome-informed risk assessments (GIRAs) across 11 conditions for a 23 840 person cohort. Testing phases and quality control led to network-wide protocols ensuring consistency and accuracy. Discussion As the science of estimating disease risk evolves, standardized and high-throughput methods of collecting and manipulating complex data are required. Platforms should be open-source, modular, and reusable, ensuring flexibility, security, and integration across healthcare environments. Conclusion The electronic MEdical Records and GEnomics (eMERGE) network successfully generated and returned comprehensive risk profiles using logic and data specific to 11 conditions in a secure and semi-automated fashion employing a customized REDCap database.

BACKGROUND: Performance and transferability of contemporary polygenic risk scores (PRS) for atherosclerotic cardiovascular disease phenotypes may vary across PRS methods, training data, and trait ascertainment. METHODS: We aimed to investigate the performance and transferability of contemporary PRS for atherosclerotic cardiovascular disease subtypes: coronary heart disease (CHD), abdominal aortic aneurysm (AAA), ischemic stroke (IS), and peripheral artery disease (PAD), using the All of Us Workbench, which consists of a large, diverse cohort with whole-genome sequence data. We also developed and evaluated a multi-trait PRS for each subtype. Performance of PRS for 4 atherosclerotic cardiovascular disease subtypes was compared across genetic similarity groups in 245 388 All of Us participants. Groups genetically similar to European, African, admixed American, and remaining groups (combined as other) were used to assess PRS for CHD, IS, AAA, PAD, and multi-trait. RESULTS: PRS for CHD and AAA performed better than IS and PAD. For CHD, CHD PGS003725 performed the best (hazard ratio per SD increase [95% CI]), across genetic ancestry groups, European, and African (1.72 [1.67–1.78], 1.23 [1.17–1.29]), with CHD PGS004696 being best for admixed American (1.91 [1.70–2.15]), and CHD PGS003356 for other (1.75 [1.58–1.95]). The best performing PRS for AAA was AAA Multi for European, other, and admixed American (1.71 [1.52–1.92], 1.59 [1.07–2.37], 1.50 [0.90–2.52]) and AAA PGS003972 for African (1.39 [1.19–1.63]). For IS, IS Multi performed best for other and European (1.49 [1.17–1.89], 1.33 [1.25–1.42]), and IS PGS000039 performed best in admixed American and African (1.17 [1.07–1.27], 1.09 [1.04–1.15]). For PAD, PAD Multi performed best for all groups (other, 1.51 [1.19–1.92]; European, 1.32 [1.24–1.41]; admixed American, 1.23 [1.05–1.45]; and African, 1.18 [1.04–1.34]). CONCLUSIONS: Multi-trait and multi-ancestry PRS performed better than individual trait and/or single ancestry PRS for each atherosclerotic cardiovascular disease phenotype across ancestrally diverse and admixed individuals, with minimal change including adjustment for conventional risk factors.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal dominant genetic disorder that increases risk for premature coronary artery disease and has accessible and effective interventions. The Dutch lipid clinic network is currently the most used diagnostic criterion; however, genetic sequencing provides a definitive diagnosis of FH. The goals of this study were to determine whether germline genetic screening using exome sequencing could be used to efficiently identify individuals who were genotype positive for FH. METHODS: Participants were recruited from 3 geographically and racially diverse sites in the United States (Rochester, MN; Phoenix, AZ; and Jacksonville, FL). Participants underwent Exome+ sequencing (dba Helix, San Mateo, CA) and return of results for specific genetic findings in APOB , LDLR , or PCSK9 . A chart review was performed to collect demographics, personal, and family cardiovascular history. RESULTS: At the time of the study, 84 413 participants were enrolled in the Tapestry study. Annotation and interpretation of all variants in genes for FH resulted in the identification of 419 likely pathogenic and pathogenic variants (prevalence, 0.50%), which included 116 APOB , 298 LDLR , and 5 PCSK9 . Sixty-six percent were female, the mean body mass index was 27.3, with 12.3% reporting a history of diabetes. Hypertriglyceridemia (≥150 mg/dL) was present in 39.5% and reduced HDL (<50 mg/dL) was present in 56.7% of patients. 27.5% of patients were not on cholesterol-lowering medications, and only 10% of FH carriers were at goal low-density lipoprotein cholesterol levels. A history of coronary artery disease was reported in 22.4% of the cohort. Nearly 90% of these participants were newly diagnosed carriers of FH. Only 30.8% of confirmed genetic diagnoses of FH satisfied clinical (Dutch lipid clinic network) criteria for a diagnosis. CONCLUSIONS: Our results emphasize the need for wider utilization of germline genetic sequencing for enhanced screening and detection of individuals who have familial hypercholesterolemia. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05212428.

Background Admixture mapping can be leveraged to identify genomic loci associated with disease traits in admixed individuals such as Hispanic Americans. Methods and Results We characterized fine‐scale population structure of participants (n=105 108) in the multiethnic eMERGE‐III (electronic Medical Records and Genomics) cohort, using reference panels from the 1000 Genomes Project and a Native American cohort. We defined “genetically admixed Hispanic Americans” as those having ≥10% Native American genetic ancestry (n=5025), in addition to European (specifically, Iberian) and African genetic ancestry. This population descriptor was subsequently applied to 3 other cohorts: the MESA (Multi‐Ethnic Study of Atherosclerosis; n=1176), WHI (Women’s Health Initiative; n=2873), and the HCHS/SOL (Hispanic Community Health Study/Study of Latinos; n=7804). We inferred local ancestry along the genome in genetically admixed Hispanic Americans in each cohort using RFMix2 with phased haplotypes from SHAPEIT2. Local ancestry proportions were used for admixture mapping of lipid traits (low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, total cholesterol, and triglycerides) using extended linear mixed models that incorporated multiple or single ancestries. After accounting for fixed‐effect covariates and random effects, ancestry proportions at the following loci were associated with lipid traits in the HCHS/SOL cohort: 11q12.2 ( P =6.8×10 −7 ) with low‐density lipoprotein cholesterol, 2p23.3 ( P =5.2×10 −7 ) with total cholesterol, and 11q23.3 ( P =7.3×10 −12 ) with triglycerides. The LDL cholesterol and triglyceride loci replicated in at least one independent cohort, whereas the total cholesterol locus showed suggestive evidence for replication in the eMERGE cohort ( P =0.073). Native American (NAMR) ancestry appeared to drive the LDL‐C association, whereas both NAMR and Iberian population in Spain (IBS) ancestries contributed to the triglyceride signal. Conclusions Admixture mapping in genetically admixed Hispanic Americans identified genomic loci influencing lipid traits and the different ancestral origins driving these associations.

Background: Chronic kidney disease (CKD) has been linked to elevated inflammatory biomarkers, yet few studies have evaluated these associations using iothalamate-based measures of kidney function, highlighting the need for further research. Research question: Is CKD associated with elevated inflammatory markers when defined by measured glomerular filtration rate (mGFR) and urinary albumin-to-creatinine ratio (UACR)? Methods: Participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort were included if they had data available for at least one inflammatory marker at visit 2. 17 inflammatory markers were assessed, including C-reactive protein (CRP), interleukin-6 (IL-6), IL-18, tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), serum amyloid A, intercellular and vascular adhesion molecules (ICAM, VCAM), E-selectin, P-selectin, monocyte chemoattractant protein (MCP), myeloperoxidase (MPO), receptor for advanced glycation end products (RAGE), matrix metalloproteinases 2 and 9 (MMP-2, MMP-9), and tissue inhibitors of metalloproteinases 1 and 2 (TIMP-1, TIMP-2). Kindey function was assessed using the urinary clearance of iothalamate. CKD was defined as mGFR < 60 mL/min/1.73 m 2 or UACR ≥ 30 mg/g. To further assess whether associations persisted without albuminuria, we also defined CKD solely by mGFR < 60 mL/min/1.73 m 2 . Generalized estimating equations (GEE) were used to assess associations between CKD status and inflammatory markers, accounting for familial clustering. Exponentiated beta coefficients from GEE models were used to present geometric mean (GM) ratios of each biomarker by CKD status, adjusted for demographics, lifestyle factors, cardiovascular risk factors, and medication use. Results: Among 1,010 participants (mean age 61 ± 10 years; 67% women; 48% Black adults), 207 were classified as having CKD. After adjusting for potential confounders, individuals with CKD had significantly higher levels of hsCRP, VCAM, TNFR1, and TNFR2 compared to those without CKD (GM ratios > 1; p < 0.05), while the remaining inflammatory markers showed no significant differences ( Figure 1 ). Importantly, these elevations remained significant when CKD was defined by mGFR alone ( Figure 2 ). Conclusion: Our findings suggest that CKD, defined by mGFR, is associated with specific inflammatory biomarkers, underscoring the need for mechanistic studies to investigate these associations.

Introduction/Background: CHIP is a risk factor for cardiovascular (CV) disease, cancer, and all-cause mortality. Previous work has shown that CHIP, and particularly larger CHIP clones, are associated with adverse CV outcomes, yet the molecular pathways through which CHIP impacts CV risk are poorly defined. Hypothesis/Research Question: We hypothesize that the integration of whole blood transcriptomics and methylomics will provide novel insights into the pathophysiology of CHIP. Methods/Approach: Whole blood DNA methylation profiling, transcriptomics, and whole exome sequencing with CHIP calling for variant allele frequencies (VAF) of ≥2% (CHIP) and ≥10% (large CHIP) were performed for 507 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. We identified transcriptomic and methylomic differences between participants with CHIP and large CHIP vs no CHIP using DESeq2 and limma, adjusted for age, sex, and race/ethnicity. Gene set enrichment analysis (GSEA) and probe set enrichment analysis (PSEA) were performed to identify pathway-level alterations in transcription and methylation, respectively. Results/Data: Clinical characteristics of study participants are described in Fig 1A . Compared to no CHIP (n=391), transcriptomics identified 6 differentially expressed genes (DEGs) in CHIP (n=116) and 27 DEGs in large CHIP (n=35) (p-adj<0.05; abs(logFC)>0.25) (Fig 1B) . Compared to no CHIP, methylation identified no differentially methylated probes in CHIP and 6 in large CHIP (padj<0.20, abs(logFC)>0.03). GSEA identified 137 pathways significantly different in both CHIP and large CHIP vs. no CHIP (padj<0.05), while PSEA identified 724 and 2356 pathways (padj<0.20), respectively. Given its stronger relationship with methylation and transcription, downstream analyses focused on large CHIP. Integrating these data, we found 58 pathways to be both hypomethylated and transcriptionally upregulated in large CHIP, including azurophil granule-related pathways implicated in neutrophil degranulation (Fig 1C) . Further investigation into the gene-probe pairs driving the azurophil granule pathway enrichment in large CHIP revealed hypomethylation and increased transcription of genes implicated in neutrophil extracellular trap formation, including ELANE, PTRN3, AZU1, and CTSG (Fig 1D) . Conclusions: Integration of the methylome and transcriptome suggests large CHIP is linked to neutrophil-mediated immune pathways in patients with stable coronary artery disease.

Background: Hypertension and systemic inflammation are independently associated with adverse cardiovascular outcomes. While hypertension is a known risk factor for left ventricular (LV) hypertrophy, the role of inflammation in LV structural changes remains unclear. It is also uncertain whether concomitant inflammation and hypertension ("inflammatory hypertension") exacerbate LV hypertrophy. Research Question: Is inflammatory hypertension associated with increased LV mass index (LVMI) compared to hypertension without inflammation? Methods: We analyzed baseline data from Black adults enrolled in the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort in Jackson, Mississippi. Inflammation was defined by high sensitivity C-reactive protein (hsCRP) >3 mg/L, and hypertension as systolic blood pressure (SBP) >130 mmHg. Participants were classified into four groups: noninflammatory-normotensive (reference group), noninflammatory-hypertensive, inflammatory-normotensive, and inflammatory-hypertensive. The primary outcome was LVMI, assessed by echocardiography. Associations between groups and LVMI were evaluated using generalized estimating equations to account for familial clustering and adjusted for covariates including age, sex, education, smoking status, body mass index, number of antihypertensive medications, statin use, cholesterol, and diabetes. Results: Among 1,027 participants (mean age 64 ± 8.5 years; 71% women), baseline LVMI differed by inflammation-hypertension status. Compared with the LVMI in noninflammatory-normotensive cohort (n=108; 74.5 g/m 2 [70.4–78.6]), significantly higher LVMI was observed in noninflammatory-hypertensive (n=343; 83.6 g/m 2 [81.3–85.9], p<0.001) and inflammatory-hypertensive groups (n=497; 84.7 g/m 2 [82.8–86.7], p<0.001). There was no statistically significant difference between inflammatory-hypertensive and noninflammatory-hypertensive groups (84.7 vs 83.6 g/m 2 )(p=0.460). The inflammatory-normotensive cohort also did not differ from the reference group (74.9 g/m 2 [70.2–79.5], p=0.901). Secondary analyses using elevated IL-6 to define inflammation yielded similar findings ( Figure 1 ). Conclusion: In individuals with inflammatory hypertension, hypertension appears to be the primary driver of LV hypertrophy. Further studies in larger, diverse populations are needed to definitively evaluate the potential additive effect of inflammatory hypertension on LV remodeling.

Introduction: Higher mtDNA-CN reflects better mitochondrial function, while lower levels indicate mtDNA release and increased inflammation. Although mtDNA-CN serves as a marker of cardiovascular health, the importance and mechanism of risk associated with mtDNA in high-risk individuals with chronic coronary artery disease (CAD) remains poorly understood. To address this gap, we leveraged the ISCHEMIA Biorepository to: (1) evaluate the association between mtDNA-CN and all-cause death (ACD); and (2) define a transcriptomic profile associated with high mtDNA-CN and ACD risk for high-risk patients with CAD. Hypothesis: Higher mtDNA-CN is associated with reduced ACD risk and inflammation in high-risk patients enrolled in the ISCHEMIA Biorepository. Methods: Low pass whole genome sequencing and whole blood RNA-Seq were performed on 594 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. Data were processed using the NYU deciphEHR pipeline and mtDNA was quantified using mitoAnalyzer. mtDNA-CN was median split, with samples having values ≤ median classified as the 'low' group and those > median as the 'high' group. Unadjusted group differences were assessed using Chi-squared tests. Survival analysis was performed using Cox proportional hazard models, adjusted for age, sex, diabetes, eGFR, dialysis status, ischemia severity, and left ventricular ejection fraction. Adjusted differential gene expression (DGE) and gene set enrichment analysis (GSEA) were performed to explore molecular mechanisms underlying mtDNA-CN. Results: Median age was 67 (IQR: 57–78); 19% were female, 84% white, and 6% Hispanic. Hypertension (84%), diabetes (43%), and obesity (45%) were common; 26% had eGFR <60 mL/min/1.73 m 2 . Median mtDNA-CN was 153 counts per sample. After multivariate adjustment , mtDNA-CN > median was associated with a 48% reduction in ACD (aHR = 0.52, 95% CI: 0.30–0.90; P = 0.020) (Figure 1A) . DGE revealed downregulation of inflammatory genes in the mtDNA-CN group, including S100A9 (FC=-.41, p=3.32e-10) and S100A12 (FC=-.56, p=3.32e-10). Inflammatory pathways such as the inflammasome complex (NES=-2.17, p=9.32e-03) and interleukin-1 production (NES= -2.02, p=6.60e-03) were downregulated among participants in the high mtDNA-CN ( Figure 1B) . Conclusion: Higher mtDNA-CN is associated with lower risk of ACD and reduced inflammasome activity, suggesting that enhanced mitochondrial health may mitigate inflammasome-related pathology linked to ACD in patients with CAD.

Key Points We studied the link between brachial-ankle pulse wave velocity (baPWV) and CKD risk in adults undergoing cardiovascular disease screening. A higher baseline baPWV was predictive of an increased annualized rate of creatinine-based eGFR (eGFR Cr ) decline. Compared with normal baPWV, higher baseline baPWV was associated with increased risk of developing CKD and lower CKD-free survival time. Background CKD affects 35 million adults in the United States and is associated with high morbidity and mortality. We investigated whether brachial-ankle pulse wave velocity (baPWV), a noninvasive measure of arterial stiffness, was associated with kidney function decline in adults undergoing cardiovascular disease (CVD) screening. Methods In 1862 patients referred for an exercise electrocardiogram test between 2007 and 2009, baPWV was measured using an Omron Colin oscillometric device. Creatinine-based GFR was estimated (eGFR Cr ) for participants with available baseline and follow-up creatinine values using the CKD Epidemiology Collaboration formula. We performed multivariable linear regression analyses to assess whether baseline baPWV was associated with annualized change in eGFR Cr , after adjustment for age, sex, body mass index, baseline eGFR Cr , and traditional CVD risk factors, including mean arterial pressure, diabetes and hypertension diagnoses, nephroprotective medication use, smoking status, and total cholesterol. To determine risk of developing CKD and CKD-free survival time by arterial stiffness subgroups, we performed covariable-adjusted Cox proportional hazards modeling and a Kaplan-Meier survival analysis, respectively. Results After exclusion of participants with missing covariable data and adjustment for covariables, one SD increase in baPWV was associated with a 0.18 ml/min per 1.73 m 2 BSA greater yearly decrease in eGFR Cr ( P = 0.023) over a median follow-up time of 13.2 years. Participants with higher baseline baPWV had increased risk of CKD (hazard ratio [95% confidence interval], P value; elevated baPWV: 2.4 [1.1 to 5.4], P = 0.037; borderline-elevated baPWV: 1.8 [1.1 to 3.1], P = 0.028) and had a shorter CKD-free survival time (median CKD-free survival time [years]; normal baPWV: 16.2; borderline-elevated baPWV: 16.0; elevated baPWV: 15.6 [ P < 0.001]). Conclusions Elevated baPWV, a noninvasive measure of arterial stiffness that can be obtained in the office setting, was associated with decline in kidney function, risk of CKD development, and CKD-free survival in individuals undergoing CVD screening.

Abstract Nephrotic syndrome is a rare, heterogeneous kidney disorder characterized by proteinuria, hypoalbuminemia, and edema. To elucidate its genetic architecture, we conducted a large-scale, electronic health record (EHR)-linked, multi-ancestry genome-wide association study comprising 5,214 cases and 1,601,060 controls. We identified 37 distinct loci associated with disease risk, including novel associations at JAML and STPG2 , and confirmed prior signals at PLA2R1 , HMCN1 , and APOL1 . Fine-mapping of the major histocompatibility complex (MHC) revealed the strongest association at DRB103:01:01G in individuals of European ancestry (OR = 2.01, P = 1.4×10⁻²⁰), alongside nominal ancestry-specific associations in African ( DOA01:01:05 ) and Latino ( DPB1*14:01:01G ) populations. Transcriptome-wide association analysis (TWAS) identified 484 significant gene-tissue associations, including C4A in kidney cortex. Expression quantitative trait locus (eQTL) mapping revealed numerous cis-eQTLs in glomerular and tubular renal tissues, largely within the MHC region. We observed significant genetic correlation between adult and pediatric nephrotic syndrome (Rg = 0.63, P = 3.5x10 -11 ), suggesting shared genetic etiology. Pathway analyses implicated estrogen receptor signaling and histone modification. Mendelian randomization implicated APOM expression and apomorphine exposure with increased disease risk (OR = 4.93, P = 1.8x10 -19 ). These results expand the understanding of nephrotic syndrome pathogenesis and highlight ancestry-informed targets for therapeutic development.