Deep phenotyping of dementia in a multi-ethnic cardiovascular cohort: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Our understanding of the specific aspects of vascular contributions to dementia remains unclear. OBJECTIVES: We aim to identify the correlates of incident dementia in a multi-ethnic cardiovascular cohort. METHODS: A total of 6806 participants with follow-up data for incident dementia were included. Probable dementia diagnoses were identified using hospitalization discharge diagnoses according to the International Classification of Diseases Codes (ICD). We used Random Forest analyses to identify the correlates of incident dementia and cognitive function from among 198 variables collected at the baseline MESA exam entailing demographic risk factors, medical history, anthropometry, lab biomarkers, electrocardiograms, cardiovascular magnetic resonance imaging, carotid ultrasonography, coronary artery calcium and liver fat content. Death and stroke were considered competing events. RESULTS: Over 14 years of follow-up, 326 dementia events were identified. Beyond age, the top correlates of dementia included coronary artery calcification, high sensitivity troponin, common carotid artery intima to media thickness, NT-proBNP, physical activity, pulse pressure, tumor necrosis factor-α, history of cancer, and liver to spleen attenuation ratio from computed tomography. Correlates of cognitive function included income and physical activity, body size, serum glucose, glomerular filtration rate, measures of carotid artery stiffness, alcohol use, and inflammation indexed as IL-2 and TNF soluble receptors and plasmin-antiplasmin complex. CONCLUSION: In a deeply phenotyped cardiovascular cohort we identified the key correlates of dementia beyond age as subclinical atherosclerosis and myocyte damage, vascular function, inflammation, physical activity, hepatic steatosis, and history of cancer.

Investigating peripheral blood monocyte and T-cell subsets as non-invasive biomarkers for asymptomatic hepatic steatosis: results from the Multi-Ethnic Study of Atherosclerosis.

Background: Circulating immune cells have gained interest as biomarkers of hepatic steatosis. Data on the relationships between immune cell subsets and early-stage steatosis in population-based cohorts are limited. Methods: This study included 1,944 asymptomatic participants of the Multi-Ethnic Study of Atherosclerosis (MESA) with immune cell phenotyping and computed tomography measures of liver fat. Participants with heavy alcohol use were excluded. A liver-to-spleen ratio Hounsfield units (HU) <1.0 and liver attenuation <40 HU were used to diagnose liver fat presence and >30% liver fat content, respectively. Logistic regression estimated cross-sectional associations of immune cell subsets with liver fat parameters adjusted for risk factors. We hypothesized that higher proportions of non-classical monocytes, Th1, Th17, and memory CD4+ T cells, and lower proportions of classical monocytes and naive CD4+ T cells, were associated with liver fat. Exploratory analyses evaluated additional immune cell phenotypes (n = 19). Results: None of the hypothesized cells were associated with presence of liver fat. Higher memory CD4+ T cells were associated with >30% liver fat content, but this was not significant after correction for multiple hypothesis testing (odds ratio (OR): 1.31, 95% confidence interval (CI): 1.03, 1.66). In exploratory analyses unadjusted for multiple testing, higher proportions of CD8+CD57+ T cells were associated with liver fat presence (OR: 1.21, 95% CI: 1.02, 1.44) and >30% liver fat content (OR: 1.34, 95% CI: 1.07, 1.69). Conclusions: Higher circulating memory CD4+ T cells may reflect liver fat severity. CD8+CD57+ cells were associated with liver fat presence and severity, but replication of findings is required.

Plasma proteomic signature of human longevity.

The identification of protein targets that exhibit anti-aging clinical potential could inform interventions to lengthen the human health span. Most previous proteomics research has been focused on chronological age instead of longevity. We leveraged two large population-based prospective cohorts with long follow-ups to evaluate the proteomic signature of longevity defined by survival to 90 years of age. Plasma proteomics was measured using a SOMAscan assay in 3067 participants from the Cardiovascular Health Study (discovery cohort) and 4690 participants from the Age Gene/Environment Susceptibility-Reykjavik Study (replication cohort). Logistic regression identified 211 significant proteins in the CHS cohort using a Bonferroni-adjusted threshold, of which 168 were available in the replication cohort and 105 were replicated (corrected p value <0.05). The most significant proteins were GDF-15 and N-terminal pro-BNP in both cohorts. A parsimonious protein-based prediction model was built using 33 proteins selected by LASSO with 10-fold cross-validation and validated using 27 available proteins in the validation cohort. This protein model outperformed a basic model using traditional factors (demographics, height, weight, and smoking) by improving the AUC from 0.658 to 0.748 in the discovery cohort and from 0.755 to 0.802 in the validation cohort. We also found that the associations of 169 out of 211 proteins were partially mediated by physical and/or cognitive function. These findings could contribute to the identification of biomarkers and pathways of aging and potential therapeutic targets to delay aging and age-related diseases.

Clonal hematopoiesis of indeterminate potential is associated with acute kidney injury.

Age is a predominant risk factor for acute kidney injury (AKI), yet the biological mechanisms underlying this risk are largely unknown. Clonal hematopoiesis of indeterminate potential (CHIP) confers increased risk for several chronic diseases associated with aging. Here we sought to test whether CHIP increases the risk of AKI. In three population-based epidemiology cohorts, we found that CHIP was associated with a greater risk of incident AKI, which was more pronounced in patients with AKI requiring dialysis and in individuals with somatic mutations in genes other than DNMT3A, including mutations in TET2 and JAK2. Mendelian randomization analyses supported a causal role for CHIP in promoting AKI. Non-DNMT3A-CHIP was also associated with a nonresolving pattern of injury in patients with AKI. To gain mechanistic insight, we evaluated the role of Tet2-CHIP and Jak2V617F-CHIP in two mouse models of AKI. In both models, CHIP was associated with more severe AKI, greater renal proinflammatory macrophage infiltration and greater post-AKI kidney fibrosis. In summary, this work establishes CHIP as a genetic mechanism conferring impaired kidney function recovery after AKI via an aberrant inflammatory response mediated by renal macrophages.

Cytokines, C-Reactive Protein, and Risk of Incident Hypertension in the REGARDS Study.

BACKGROUND: Hypertension is a highly prevalent cardiovascular disease risk factor that may be related to inflammation. Whether adverse levels of specific inflammatory cytokines relate to hypertension is unknown. The present study sought to determine whether higher levels of IL (interleukin)-1ß, IL-6, TNF (tumor necrosis factor)-α, IFN (interferon)-γ, IL-17A, and CRP (C-reactive protein) are associated with a greater risk of incident hypertension. METHODS: The REGARDS study (Reasons for Geographic and Racial Difference in Stroke) is a prospective cohort study that recruited 30 239 community-dwelling Black and White adults from the contiguous United States in 2003 to 2007 (visit 1), with follow-up 9 years later in 2013 to 2016 (visit 2). We included participants without prevalent hypertension who attended follow-up 9 years later and had available laboratory measures and covariates of interest. Poisson regression estimated the risk ratio of incident hypertension by level of inflammatory biomarkers. RESULTS: Among 1866 included participants (mean [SD] aged of 62 [8] years, 25% Black participants, 55% women), 36% developed hypertension. In fully adjusted models comparing the third to first tertile of each biomarker, there was a greater risk of incident hypertension for higher IL-1ß among White (1.24 [95% CI, 1.01-1.53]) but not Black participants (1.01 [95% CI, 0.83-1.23]) and higher TNF-α (1.20 [95% CI, 1.02-1.41]) and IFN-γ (1.22 [95% CI, 1.04-1.42]) among all participants. There was no increased risk with IL-6, IL-17A, or CRP. CONCLUSIONS: Higher levels of IL-1ß, TNF-α, and IFN-γ, representing distinct inflammatory pathways, are elevated in advance of hypertension development. Whether modifying these cytokines will reduce incident hypertension is unknown.

Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease Study.

Rationale Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. Molecular mechanisms underlying these changes are poorly understood in patients due, in part, to the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMC) interact with the pulmonary endothelium. Objective To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with 10 or more pack-years. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume (PMBV), and mean transit time were assessed on contrast-enhanced MRI, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with PMBV measures on contrast-enhanced, dual-energy CT. Differential expression analyses were adjusted for age, gender, race-ethnicity, educational attainment, height, weight, smoking status, and pack-years. Results The 79 participants in the discovery sample had mean age of 69±6 years, 44% were female, 25% were non-white, 34% were current smokers and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with MRI (n=47) or dual-energy CT scan (n=157) measures. Many of the identified genes are involved in inflammatory processes, including NF-κB and chemokine signaling pathways. Conclusions PBMC gene expression in NF-κB, inflammatory and chemokine signaling pathways was associated pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.

Demographic and Clinical Factors Associated With SARS-CoV-2 Spike 1 Antibody Response Among Vaccinated US Adults: the C4R Study.

This study investigates correlates of anti-S1 antibody response following COVID-19 vaccination in a U.S. population-based meta-cohort of adults participating in longstanding NIH-funded cohort studies. Anti-S1 antibodies were measured from dried blood spots collected between February 2021-August 2022 using Luminex-based microsphere immunoassays. Of 6245 participants, mean age was 73 years (range, 21-100), 58% were female, and 76% were non-Hispanic White. Nearly 52% of participants received the BNT162b2 vaccine and 48% received the mRNA-1273 vaccine. Lower anti-S1 antibody levels are associated with age of 65 years or older, male sex, higher body mass index, smoking, diabetes, COPD and receipt of BNT16b2 vaccine (vs mRNA-1273). Participants with a prior infection, particularly those with a history of hospitalized illness, have higher anti-S1 antibody levels. These results suggest that adults with certain socio-demographic and clinical characteristics may have less robust antibody responses to COVID-19 vaccination and could be prioritized for more frequent re-vaccination.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects.

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.

Associations of plasma NfL, GFAP, and t-tau with cerebral small vessel disease and incident dementia: longitudinal data of the AGES-Reykjavik Study.

We investigated the associations of plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and total tau (t-tau) with markers of cerebral small vessel disease (SVD) and with incident dementia. We also investigated whether associations of NfL, GFAP, and t-tau with incident dementia were explained by SVD. Data are from a random subsample (n = 1069) of the population-based AGES-Reykjavik Study who underwent brain MRI and in whom plasma NfL, GFAP, and t-tau were measured at baseline (76.1 ± 5.4 years/55.9% women/baseline 2002-2006/follow-up until 2015). A composite SVD burden score was calculated using white matter hyperintensity volume (WMHV), subcortical infarcts, cerebral microbleeds, and large perivascular spaces. Dementia was assessed in a 3-step process and adjudicated by specialists. Higher NfL was associated with a higher SVD burden score. Dementia occurred in 225 (21.0%) individuals. The SVD burden score significantly explained part of the association between NfL and incident dementia. WMHV mostly strongly contributed to the explained effect. GFAP was not associated with the SVD burden score, but was associated with WMHV, and WMHV significantly explained part of the association between GFAP and incident dementia. T-tau was associated with WMHV, but not with incident dementia. In conclusion, the marker most strongly related to SVD is plasma NfL, for which the association with WMHV appeared to explain part of its association with incident dementia. This study suggests that plasma NfL may reflect the contribution of co-morbid vascular disease to dementia. However, the magnitude of the explained effect was relatively small, and further research is required to investigate the clinical implications of this finding.

Circulating Growth Differentiation Factors 11 and 8, Their Antagonists Follistatin and Follistatin-Like-3, and Risk of Heart Failure in Elders.

BACKGROUND: Heterochronic parabiosis has identified growth differentiation factor (GDF)-11 as a potential means of cardiac rejuvenation, but findings have been inconsistent. A major barrier has been lack of assay specificity for GDF-11 and its homolog GDF-8. METHODS: We tested the hypothesis that GDF-11 and GDF-8, and their major antagonists follistatin and follistatin-like (FSTL)-3, are associated with incident heart failure (HF) and its subtypes in elders. Based on validation experiments, we used liquid chromatography-tandem mass spectrometry to measure total serum GDF-11 and GDF-8, along with follistatin and FSTL-3 by immunoassay, in 2 longitudinal cohorts of older adults. RESULTS: In 2 599 participants (age 75.2 ±â€…4.3) followed for 10.8 ±â€…5.6 years, 721 HF events occurred. After adjustment, neither GDF-11 (HR per doubling: 0.93 [0.67, 1.30]) nor GDF-8 (HR: 1.02 per doubling [0.83, 1.27]) was associated with incident HF or its subtypes. Positive associations with HF were detected for follistatin (HR: 1.15 [1.00, 1.32]) and FLST-3 (HR: 1.38 [1.03, 1.85]), and with HF with preserved ejection fraction for FSTL-3 (HR: 1.77 [1.03, 3.02]). (All HRs per doubling of biomarker.) FSTL-3 associations with HF appeared stronger at higher follistatin levels and vice versa, and also for men, Blacks, and lower kidney function. CONCLUSIONS: Among older adults, serum follistatin and FSTL-3, but not GDF-11 or GDF-8, were associated with incident HF. These findings do not support the concept that low serum levels of total GDF-11 or GDF-8 contribute to HF late in life, but do implicate transforming growth factor-ß superfamily pathways as potential therapeutic targets.

The functional impact of rare variation across the regulatory cascade.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA.

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Demographic and Clinical Characteristics Associated With Serum GFAP Levels in an Ethnically Diverse Cohort.

BACKGROUND AND OBJECTIVES: Elevations in circulating glial fibrillary acidic protein (GFAP), a putative marker of reactive astrocytosis, have been found to associate with cognitive decline and dementia status. Further validation in diverse cohorts and evaluation of potential health disparities are necessary for broader generalization. The goal of this study was to examine the associations between demographics, cardiovascular risk factors, and APOE ε4 status with serum GFAP levels among Mexican American and non-Hispanic White older adults across the continuum from cognitively unimpaired to Alzheimer disease dementia. METHODS: Serum GFAP levels were assayed using a Simoa HD-1 analyzer in older adults enrolled in the observational Texas Alzheimer Research and Care Consortium. Associations between demographic and clinical characteristics with serum GFAP levels were evaluated using linear regression. The diagnostic accuracy of serum GFAP was further examined using area under the receiver operating characteristic curves (AUROC) in univariate and adjusted models, and optimal cut points were derived using the maximum Kolmogorov-Smirnov metric. All models were also stratified by ethnicity and disease stage. RESULTS: A total of 1,156 Mexican American and 587 non-Hispanic White participants were included (mean age = 68 years, standard deviation = 10; 65% female). Older age (ß = 0.562 (95% CI 0.515-0.609), p < 0.001), apolipoprotein ε4 status (ß = 0.139 (95% CI 0.092-0.186), p < 0.001), and cognitive impairment (ß = 0.150 (95% CI 0.103-0.197), p < 0.001) were positively associated with serum GFAP. By contrast, higher body mass index (ß = -0.181 (95% CI -0.228 to -0.134), p < 0.001), diabetes (ß = -0.065 (95% CI -0.112 to -0.018), p < 0.001), and tobacco use (ß = -0.059 (95% CI -0.106 to -0.012), p < 0.001) were inversely associated with serum GFAP. AUROC values were generally comparable across ethnicities and model fit improved with inclusion of additional covariates. However, optimal cut-off values were consistently lower in Mexican Americans relative to non-Hispanic White participants. DISCUSSION: The study results highlight the importance of understanding the role of broader demographic and clinical factors on circulating GFAP levels within diverse cohorts to enhance precision across clinical, research, and community settings.

Associations between eGFR and albuminuria with right ventricular measures: the MESA-Right Ventricle study.

Background: Chronic kidney disease (CKD) is associated with an increased risk of pulmonary hypertension, which may lead to right ventricular (RV) pressure overload and RV dysfunction. However, the presence of subclinical changes in RV structure or function in early CKD and the influence of these changes on mortality are not well studied. We hypothesized that early CKD, as indicated by elevated albuminuria or mild reductions in estimated glomerular filtration rate (eGFR), is associated with greater RV dilation and RV mass. Methods: We included 4063 participants (age 45-84 years) without baseline clinical cardiovascular disease from the Multi-Ethnic Study of Atherosclerosis. The associations of baseline creatinine-cystatin C-based eGFR and albuminuria with cardiac magnetic resonance-derived RV measures (2000-02) were examined cross-sectionally with linear regression models. Cox regression models were used to examine whether RV parameters modified the associations of eGFR and albuminuria with all-cause mortality. Results: Participants with reductions in eGFR primarily within the 60-89 mL/min/1.73 m2 category had smaller RV end-diastolic and end-systolic volumes and stroke volume (all adjusted P-trends <.001) than those with eGFR ≥90 mL/min/1.73 m2, an association that was predominantly seen in participants with albuminuria below 30 mg/g creatinine. Albuminuria was more strongly associated with death among those with lower RV volumes (P-values for interaction <.03). Conclusions: Among community-dwelling adults, reductions in eGFR primarily within the normal range were associated with smaller RV volumes and the association of albuminuria with worse survival was stronger among those with smaller RV volumes. Further studies are needed to elucidate the underlying mechanistic pathways that link kidney measures and RV morphology.

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies.

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWAS) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWAS) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWAS and TWAS can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p-values across all the genes, which suggests a high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma.

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

Multiset correlation and factor analysis enables exploration of multi-omics data.

Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.

Association of Immune Cell Subsets with Incident Hip Fracture: The Cardiovascular Health Study.

In this study, we aimed to evaluate the association of innate and adaptive immune cell subsets in peripheral blood mononuclear cells (PBMCs) with hip fracture. To conduct this study, we used data from the Cardiovascular Health Study (CHS), a U.S. multicenter observational cohort of community-dwelling men and women aged ≥ 65 years. Twenty-five immune cell phenotypes were measured by flow cytometry from cryopreserved PBMCs of CHS participants collected in 1998-1999. The natural killer (NK), γδ T, T helper 17 (Th17), and differentiated/senescent CD4+CD28- T cell subsets were pre-specified as primary subsets of interest. Hip fracture incidence was assessed prospectively by review of hospitalization records. Multivariable Cox hazard models evaluated associations of immune cell phenotypes with incident hip fracture in sex-stratified and combined analyses. Among 1928 persons, 259 hip fractures occurred over a median 9.7 years of follow-up. In women, NK cells were inversely associated with hip fracture [hazard ratio (HR) 0.77, 95% confidence interval (CI) 0.60-0.99 per one standard deviation higher value] and Th17 cells were positively associated with hip fracture [HR 1.18, 95% CI 1.01-1.39]. In men, γδ T cells were inversely associated with hip fracture [HR 0.60, 95% CI 0.37-0.98]. None of the measured immune cell phenotypes were significantly associated with hip fracture incidence in combined analyses. In this large prospective cohort of older adults, potentially important sex differences in the associations of immune cell phenotypes and hip fracture were identified. However, immune cell phenotypes had no association with hip fracture in analyses combining men and women.

Associations between Metabolomic Biomarkers of Avocado Intake and Glycemia in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes. OBJECTIVES: To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia. METHODS: Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined. RESULTS: Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (ß = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (ß = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (ß = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI. CONCLUSIONS: Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.