See Editorial by Aguilar

Coronary artery disease (CAD) is a leading cause of death, yet its genetic determinants are not fully elucidated. We report a multi-ethnic genome-wide association study of CAD involving nearly a quarter of a million cases, incorporating the largest cohorts to date of Whites, Blacks, and Hispanics from the Million Veteran Program with existing studies including CARDIoGRAMplusC4D, UK Biobank, and Biobank Japan. We verify substantial and nearly equivalent heritability of CAD across multiple ancestral groups, discover 107 novel loci including the first nine on the X-chromosome, identify the first eight genome-wide significant loci among Blacks and Hispanics, and demonstrate that two common haplotypes are largely responsible for the risk stratification at the well-known 9p21 locus in most populations except those of African origin where both haplotypes are virtually absent. We identify 15 loci for angiographically derived burden of coronary atherosclerosis, which robustly overlap with the strongest and earliest loci reported to date for clinical CAD. Phenome-wide association analyses of novel loci and externally validated polygenic risk scores (PRS) augment signals from the insulin resistance cluster of risk factors and consequences, extend previously established pleiotropic associations of loci with traditional risk factors to include smoking and family history, and confirm a substantially reduced transferability of existing PRS to Blacks. Downstream integrative genomic analyses reinforce the critical role of endothelial, fibroblast, and smooth muscle cells within the coronary vessel wall in CAD susceptibility. Our study highlights the value of a multi-ethnic design in efficiently characterizing the genetic architecture of CAD across all human populations.

Data on proteomic and metabolomic signatures of healthy dietary patterns are limited. We evaluated the cross-sectional association of serum proteomic and metabolomic markers with three dietary patterns: the Alternative Healthy Eating Index (AHEI), the Dietary Approaches to Stop Hypertension (DASH) diet; and a Mediterranean-style (MDS) diet. We examined participants from the Framingham Offspring Study (mean age; 55 years; 52% women) who had complete proteomic (n = 1713) and metabolomic (n = 2284) data; using food frequency questionnaires to derive dietary pattern indices. Proteins and metabolites were quantified using the SomaScan platform and liquid chromatography/tandem mass spectrometry; respectively. We used multivariable-adjusted linear regression models to relate each dietary pattern index (independent variables) to each proteomic and metabolomic marker (dependent variables). Of the 1373 proteins; 103 were associated with at least one dietary pattern (48 with AHEI; 83 with DASH; and 8 with MDS; all false discovery rate [FDR] ≤ 0.05). We identified unique associations between dietary patterns and proteins (17 with AHEI; 52 with DASH; and 3 with MDS; all FDR ≤ 0.05). Significant proteins enriched biological pathways involved in cellular metabolism/proliferation and immune response/inflammation. Of the 216 metabolites; 65 were associated with at least one dietary pattern (38 with AHEI; 43 with DASH; and 50 with MDS; all FDR ≤ 0.05). All three dietary patterns were associated with a common signature of 24 metabolites (63% lipids). Proteins and metabolites associated with dietary patterns may help characterize intermediate phenotypes that provide insights into the molecular mechanisms mediating diet-related disease. Our findings warrant replication in independent populations

BackgroundLarge databases provide an efficient way to analyze patient data. A challenge with these databases is the inconsistency of ICD codes and a potential for inaccurate ascertainment of cases. The purpose of this study was to develop and validate a reliable protocol to identify cases of acute ischemic stroke (AIS) from a large national database.MethodsUsing the national Veterans Affairs electronic health-record system, Center for Medicare and Medicaid Services, and National Death Index data, we developed an algorithm to identify cases of AIS. Using a combination of inpatient and outpatient ICD9 codes, we selected cases of AIS and controls from 1992 to 2014. Diagnoses determined after medical-chart review were considered the gold standard. We used a machine-learning algorithm and a neural network approach to identify AIS from ICD9 codes and electronic health-record information and compared it with a previous rule-based stroke-classification algorithm.ResultsWe reviewed administrative hospital data, ICD9 codes, and medical records of 268 patients in detail. Compared with the gold standard, this AIS algorithm had a sensitivity of 91%, specificity of 95%, and positive predictive value of 88%. A total of 80,508 highly likely cases of AIS were identified using the algorithm in the Veterans Affairs national cardiovascular disease-risk cohort (n=2,114,458).ConclusionOur algorithm had high specificity for identifying AIS in a nationwide electronic health-record system. This approach may be utilized in other electronic health databases to accurately identify patients with AIS.

Background: Ruptured aortic aneurysm and aortic dissections are potentially preventable disorders associated with high mortality. Screening of individuals at risk may translate into elective surgical interventions and lowered mortality. It is uncertain if the risk of aortic dilation of varying degrees aggregates within families. Methods: We investigated the risk of having thoracic and abdominal aortic sizes in the highest quartile (measured by computed tomography scans and indexed for body size) if at least one parent did so in the Framingham Heart Study (FHS) cohorts, and estimated the incidence rates and hazards ratio of developing aortic aneurysm or dissection among first-degree relatives of those with aortic aneurysm or dissection, as compared with age- and sex-matched controls (1:10 for aortic aneurysm and 1:100 for aortic dissection) using the Danish nationwide administrative registries. Results: In FHS, offspring (n=235) whose parent(s) had a sex- and age-standardized aortic size in the upper quartile had a multivariable-adjusted ~3-fold increased odds ratio of belonging to the upper quartile themselves. In Denmark, a total of 68,939 individuals (mean age 42 years) had a first-degree relative with aortic aneurysm and 7,209 persons (mean age 39 years) had a firstdegree relative with aortic dissection. During an average follow-up of 7 years, first-degree relatives of patients with aortic aneurysm and dissection had a hazards ratio of 6.70 (95% CI 5.96-7.52) for developing aortic aneurysm and 9.24 (95% CI 5.53-15.44) for dissection, compared to matched controls. These estimates remained unchanged upon adjusting for several comorbidities, including prevalent hypertension, bicuspid aortic valve, and the Marfan syndrome. For both aortic aneurysm and dissections, the absolute event rates approached 1 per 1000 person-years for first-degree relatives versus 11-13 (aortic aneurysm) and 2-3 (aortic dissections) per 100,000 person-years among controls. Conclusions: Increased aortic size, a precursor of aortic aneurysm and a risk factor for dissection, clusters in families. The incidence rates of aortic aneurysm and dissections approach that of other common cardiovascular conditions in first-degree relatives, supporting the use of systematic screening for these conditions.