Race/Ethnicity, Spirometry Reference Equations, and Prediction of Incident Clinical Events: The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study.

Rationale: Normal values for FEV1 and FVC are currently calculated using cross-sectional reference equations that include terms for race/ethnicity, an approach that may reinforce disparities and is of unclear clinical benefit. Objectives: To determine whether race/ethnicity-based spirometry reference equations improve the prediction of incident chronic lower respiratory disease (CLRD) events and mortality compared with race/ethnicity-neutral equations. Methods: The MESA Lung Study, a population-based, prospective cohort study of White, Black, Hispanic, and Asian adults, performed standardized spirometry from 2004 to 2006. Predicted values for spirometry were calculated using race/ethnicity-based equations following guidelines and, alternatively, race/ethnicity-neutral equations without terms for race/ethnicity. Participants were followed for events through 2019. Measurements and Main Results: The mean age of 3,344 participants was 65 years, and self-reported race/ethnicity was 36% White, 25% Black, 23% Hispanic, and 17% Asian. There were 181 incident CLRD-related events and 547 deaths over a median of 11.6 years. There was no evidence that percentage predicted FEV1 or FVC calculated using race/ethnicity-based equations improved the prediction of CLRD-related events compared with those calculated using race/ethnicity-neutral equations (difference in C statistics for FEV1, -0.005; 95% confidence interval [CI], -0.013 to 0.003; difference in C statistic for FVC, -0.008; 95% CI, -0.016 to -0.0006). Findings were similar for mortality (difference in C statistics for FEV1, -0.002; 95% CI, -0.008 to 0.003; difference in C statistics for FVC, -0.004; 95% CI, -0.009 to 0.001). Conclusions: There was no evidence that race/ethnicity-based spirometry reference equations improved the prediction of clinical events compared with race/ethnicity-neutral equations. The inclusion of race/ethnicity in spirometry reference equations should be reconsidered.

Moving towards the detection of frailty with biomarkers: A population health study.

Aging adults experience increased health vulnerability and compromised abilities to cope with stressors, which are the clinical manifestations of frailty. Frailty is complex, and efforts to identify biomarkers to detect frailty and pre-frailty in the clinical setting are rarely reproduced across cohorts. We developed a predictive model incorporating biological and clinical frailty measures to identify robust biomarkers across data sets. Data were from two large cohorts of older adults: "Invecchiare in Chianti (Aging in Chianti, InCHIANTI Study") (n = 1453) from two small towns in Tuscany, Italy, and replicated in the Atherosclerosis Risk in Communities Study (ARIC) (n = 6508) from four U.S. communities. A complex systems approach to biomarker selection with a tree-boosting machine learning (ML) technique for supervised learning analysis was used to examine biomarker population differences across both datasets. Our approach compared predictors with robust, pre-frail, and frail participants and examined the ability to detect frailty status by race. Unique biomarker features identified in the InCHIANTI study allowed us to predict frailty with a model accuracy of 0.72 (95% confidence interval (CI) 0.66-0.80). Replication models in ARIC maintained a model accuracy of 0.64 (95% CI 0.66-0.72). Frail and pre-frail Black participant models maintained a lower model accuracy. The predictive panel of biomarkers identified in this study may improve the ability to detect frailty as a complex aging syndrome in the clinical setting. We propose several concrete next steps to keep research moving toward detecting frailty with biomarker-based detection methods.

UNSUPERVISED AIRWAY TREE CLUSTERING WITH DEEP LEARNING: THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA) LUNG STUDY.

High-resolution full lung CT scans now enable the detailed segmentation of airway trees up to the 6th branching generation. The airway binary masks display very complex tree structures that may encode biological information relevant to disease risk and yet remain challenging to exploit via traditional methods such as meshing or skeletonization. Recent clinical studies suggest that some variations in shape patterns and caliber of the human airway tree are highly associated with adverse health outcomes, including all-cause mortality and incident COPD. However, quantitative characterization of variations observed on CT segmented airway tree remain incomplete, as does our understanding of the clinical and developmental implications of such. In this work, we present an unsupervised deep-learning pipeline for feature extraction and clustering of human airway trees, learned directly from projections of 3D airway segmentations. We identify four reproducible and clinically distinct airway sub-types in the MESA Lung CT cohort.

Pulmonary Blood Volume Among Older Adults in the Community: The MESA Lung Study.

BACKGROUND: The pulmonary vasculature is essential for gas exchange and impacts both pulmonary and cardiac function. However, it is difficult to assess and its characteristics in the general population are unknown. We measured pulmonary blood volume (PBV) noninvasively using contrast enhanced, dual-energy computed tomography to evaluate its relationship to age and symptoms among older adults in the community. METHODS: The MESA (Multi-Ethnic Study of Atherosclerosis) is an ongoing community-based, multicenter cohort. All participants attending the most recent MESA exam were selected for contrast enhanced dual-energy computed tomography except those with estimated glomerular filtration rate <60 mL/min per 1.73 m2. PBV was calculated by material decomposition of dual-energy computed tomography images. Multivariable models included age, sex, race/ethnicity, education, height, weight, smoking status, pack-years, and scanner model. RESULTS: The mean age of the 727 participants was 71 (range 59-94) years, and 55% were male. The race/ethnicity distribution was 41% White, 29% Black, 17% Hispanic, and 13% Asian. The mean±SD PBV in the youngest age quintile was 547±180 versus 433±194 mL in the oldest quintile (P<0.001), with an approximately linear decrement of 50 mL per 10 years of age ([95% CI, 32-67]; P<0.001). Findings were similar with multivariable adjustment. Lower PBV was associated independently with a greater dyspnea after a 6-minute walk (P=0.04) and greater composite dyspnea symptom scores (P=0.02). Greater PBV was also associated with greater height, weight, lung volume, Hispanic race/ethnicity, and nonsmoking history. CONCLUSIONS: Pulmonary blood volume was substantially lower with advanced age and was associated independently with greater symptoms scores in the elderly.

Blood DNA methylation sites predict death risk in a longitudinal study of 12, 300 individuals.

DNA methylation has fundamental roles in gene programming and aging that may help predict mortality. However, no large-scale study has investigated whether site-specific DNA methylation predicts all-cause mortality. We used the Illumina-HumanMethylation450-BeadChip to identify blood DNA methylation sites associated with all-cause mortality for 12, 300 participants in 12 Cohorts of the Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium. Over an average 10-year follow-up, there were 2,561 deaths across the cohorts. Nine sites mapping to three intergenic and six gene-specific regions were associated with mortality (P < 9.3x10-7) independently of age and other mortality predictors. Six sites (cg14866069, cg23666362, cg20045320, cg07839457, cg07677157, cg09615688)-mapping respectively to BMPR1B, MIR1973, IFITM3, NLRC5, and two intergenic regions-were associated with reduced mortality risk. The remaining three sites (cg17086398, cg12619262, cg18424841)-mapping respectively to SERINC2, CHST12, and an intergenic region-were associated with increased mortality risk. DNA methylation at each site predicted 5%-15% of all deaths. We also assessed the causal association of those sites to age-related chronic diseases by using Mendelian randomization, identifying weak causal relationship between cg18424841 and cg09615688 with coronary heart disease. Of the nine sites, three (cg20045320, cg07839457, cg07677157) were associated with lower incidence of heart disease risk and two (cg20045320, cg07839457) with smoking and inflammation in prior CHARGE analyses. Methylation of cg20045320, cg07839457, and cg17086398 was associated with decreased expression of nearby genes (IFITM3, IRF, NLRC5, MT1, MT2, MARCKSL1) linked to immune responses and cardiometabolic diseases. These sites may serve as useful clinical tools for mortality risk assessment and preventative care.

Whole Blood DNA Methylation Signatures of Diet Are Associated With Cardiovascular Disease Risk Factors and All-Cause Mortality.

BACKGROUND: DNA methylation patterns associated with habitual diet have not been well studied. METHODS: Diet quality was characterized using a Mediterranean-style diet score and the Alternative Healthy Eating Index score. We conducted ethnicity-specific and trans-ethnic epigenome-wide association analyses for diet quality and leukocyte-derived DNA methylation at over 400 000 CpGs (cytosine-guanine dinucleotides) in 5 population-based cohorts including 6662 European ancestry, 2702 African ancestry, and 360 Hispanic ancestry participants. For diet-associated CpGs identified in epigenome-wide analyses, we conducted Mendelian randomization (MR) analysis to examine their relations to cardiovascular disease risk factors and examined their longitudinal associations with all-cause mortality. RESULTS: We identified 30 CpGs associated with either Mediterranean-style diet score or Alternative Healthy Eating Index, or both, in European ancestry participants. Among these CpGs, 12 CpGs were significantly associated with all-cause mortality (Bonferroni corrected P<1.6×10-3). Hypermethylation of cg18181703 (SOCS3) was associated with higher scores of both Mediterranean-style diet score and Alternative Healthy Eating Index and lower risk for all-cause mortality (P=5.7×10-15). Ten additional diet-associated CpGs were nominally associated with all-cause mortality (P<0.05). MR analysis revealed 8 putatively causal associations for 6 CpGs with 4 cardiovascular disease risk factors (body mass index, triglycerides, high-density lipoprotein cholesterol concentrations, and type 2 diabetes mellitus; Bonferroni corrected MR P<4.5×10-4). For example, hypermethylation of cg11250194 (FADS2) was associated with lower triglyceride concentrations (MR, P=1.5×10-14).and hypermethylation of cg02079413 (SNORA54; NAP1L4) was associated with body mass index (corrected MR, P=1×10-6). CONCLUSIONS: Habitual diet quality was associated with differential peripheral leukocyte DNA methylation levels of 30 CpGs, most of which were also associated with multiple health outcomes, in European ancestry individuals. These findings demonstrate that integrative genomic analysis of dietary information may reveal molecular targets for disease prevention and treatment.

The influence of obesity-related single nucleotide polymorphisms on BMI across the life course: the PAGE study.

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18-100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18-25 years), adulthood (ages 26-49 years), middle-age adulthood (ages 50-69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (ß [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m², respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.

Genome-wide detection of allele specific copy number variation associated with insulin resistance in African Americans from the HyperGEN study.

African Americans have been understudied in genome wide association studies of diabetes and related traits. In the current study, we examined the joint association of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with fasting insulin and an index of insulin resistance (HOMA-IR) in the HyperGEN study, a family based study with proband ascertainment for hypertension. This analysis is restricted to 1,040 African Americans without diabetes. We generated allele specific CNV genotypes at 872,243 autosomal loci using Birdsuite, a freely available multi-stage program. Joint tests of association for SNPs and CNVs were performed using linear mixed models adjusting for covariates and familial relationships. Our results highlight SNPs associated with fasting insulin and HOMA-IR (rs6576507 and rs8026527, 3.7*10(-7)≤P≤1.1*10(-5)) near ATPase, class V, type 10A (ATP10A), and the L Type voltage dependent calcium channel (CACNA1D, rs1401492, P≤5.2*10(-6)). ATP10A belongs to a family of aminophospholipid-transporting ATPases and has been associated with type 2 diabetes in mice. CACNA1D has been linked to pancreatic beta cell generation in mice. The two most significant copy variable markers (rs10277702 and rs361367; P<2.0*10(-4)) were in the beta variable region of the T-cell receptor gene (TCRVB). Human and mouse TCR has been shown to mimic insulin and its receptor and could contribute to insulin resistance. Our findings differ from genome wide association studies of fasting insulin and other diabetes related traits in European populations, highlighting the continued need to investigate unique genetic influences for understudied populations such as African Americans.