Prediabetes, intervening diabetes and subsequent risk of dementia: the Atherosclerosis Risk in Communities (ARIC) study.

AIMS/HYPOTHESIS: The aim of this work was to evaluate whether the association of prediabetes with dementia is explained by the intervening onset of diabetes. METHODS: Among participants of the Atherosclerosis Risk in Communities (ARIC) study we defined baseline prediabetes as HbA1c 39-46 mmol/mol (5.7-6.4%) and subsequent incident diabetes as a self-reported physician diagnosis or use of diabetes medication. Incident dementia was ascertained via active surveillance and adjudicated. We quantified the association of prediabetes with dementia risk before and after accounting for the subsequent development of diabetes among ARIC participants without diabetes at baseline (1990-1992; participants aged 46-70 years). We also evaluated whether age at diabetes diagnosis modified the risk of dementia. RESULTS: Among 11,656 participants without diabetes at baseline, 2330 (20.0%) had prediabetes. Before accounting for incident diabetes, prediabetes was significantly associated with the risk of dementia (HR 1.12 [95% CI 1.01, 1.24]). After accounting for incident diabetes, the association was attenuated and non-significant (HR 1.05 [95% CI 0.94, 1.16]). Earlier age of onset of diabetes had the strongest association with dementia: HR 2.92 (95% CI 2.06, 4.14) for onset before 60 years; HR 1.73 (95% CI 1.47, 2.04) for onset at 60-69 years; and HR 1.23 (95% CI 1.08, 1.40) for onset at 70-79 years. CONCLUSIONS/INTERPRETATION: Prediabetes is associated with dementia risk but this risk is explained by the subsequent development of diabetes. Earlier age of onset of diabetes substantially increases dementia risk. Preventing or delaying progression of prediabetes to diabetes will reduce dementia burden.

Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer's disease and myocardial infarction.

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P < 5.30 × 10-7); including a novel signal near TOMM40/APOE. Joint analysis of TOMM40/APOE variants revealed the TOMM40 signal was attributed to APOE rs429358-T; APOE rs7412 was not associated with liver attenuation. Moreover, rs429358-T was associated with higher serum alanine aminotransferase, liver steatosis, cirrhosis, triglycerides and obesity; as well as, lower cholesterol and decreased risk of myocardial infarction and Alzheimer's disease (AD) in phenome-wide association analyses in the Michigan Genomics Initiative, United Kingdom Biobank and/or public datasets. These results implicate APOE in imaging-based identification of NAFLD. This association may or may not translate to nonalcoholic steatohepatitis; however, these results indicate a significant association with advanced liver disease and hepatic cirrhosis. These findings highlight allelic heterogeneity at the APOE locus and demonstrate an inverse link between NAFLD and AD at the exome level in the largest analysis to date.

Associations of Vascular Risk and Amyloid Burden with Subsequent Dementia.

OBJECTIVE: Midlife vascular risk factors (MVRFs) are associated with incident dementia, as are amyloid ß (Aß) deposition and neurodegeneration. Whether vascular and Alzheimer disease-associated factors contribute to dementia independently or interact synergistically to reduce cognition is poorly understood. METHODS: Participants in the Atherosclerosis Risk in Communities-Positron Emission Tomography study were followed from 1987-1989 (45-64 years old) through 2016-2017 (74-94 years old), with repeat cognitive assessment and dementia adjudication. In 2011-2013, dementia-free participants underwent brain magnetic resonance imaging (with white matter hyperintensity [WMH] and brain volume measurement) and florbetapir (Aß) positron emission tomography. The relative contributions of vascular risk and injury (MVRFs, WMH volume), elevated Aß standardized uptake value ratio (SUVR), and neurodegeneration (smaller temporoparietal brain regions) to incident dementia were evaluated with adjusted Cox models. RESULTS: In 298 individuals, 36 developed dementia (median follow-up = 4.9 years). Midlife hypertension and Aß each independently predicted dementia risk (hypertension: hazard ratio [HR] = 2.57, 95% confidence interval [CI] = 1.16-5.67; Aß SUVR [per standard deviation (SD)]: HR = 2.57, 95% CI = 1.72-3.84), but did not interact significantly, whereas late life diabetes (HR = 2.50, 95% CI = 1.18-5.28) and Aß independently predicted dementia risk. WMHs (per SD: HR = 1.51, 95% CI = 1.03-2.20) and Aß SUVR (HR = 2.52, 95% CI = 1.83-3.47) independently contributed to incident dementia, but WMHs lost significance when MVRFs were included. Smaller temporoparietal brain regions were associated with incident dementia, independent of Aß and MVRFs (HR = 2.18, 95% CI = 1.18-4.01). INTERPRETATION: Midlife hypertension and late life Aß are independently associated with dementia risk, without evidence for synergy on a multiplicative scale. Given the independent contributions of vascular and amyloid mechanisms, multiple pathways should be considered when evaluating interventions to reduce the burden of dementia. ANN NEUROL 2022;92:607-619.

Methods for estimating insulin resistance from untargeted metabolomics data.

CONTEXT: Insulin resistance is associated with multiple complex diseases; however, precise measures of insulin resistance are invasive, expensive, and time-consuming. OBJECTIVE: Develop estimation models for measures of insulin resistance, including insulin sensitivity index (SI) and homeostatic model assessment of insulin resistance (HOMA-IR) from metabolomics data. DESIGN: Insulin Resistance Atherosclerosis Family Study (IRASFS). SETTING: Community based. PARTICIPANTS: Mexican Americans (MA) and African Americans (AA). MAIN OUTCOME: Estimation models for measures of insulin resistance, i.e. SI and HOMA-IR. RESULTS: Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net regression were used to build insulin resistance estimation models from 1274 metabolites combined with clinical data, e.g. age, sex, body mass index (BMI). Metabolite data were transformed using three approaches, i.e. inverse normal transformation, standardization, and Box Cox transformation. The analysis was performed in one MA recruitment site (San Luis Valley, Colorado (SLV); N = 450) and tested in another MA recruitment site (San Antonio, Texas (SA); N = 473). In addition, the two MA recruitment sites were combined and estimation models tested in the AA recruitment sample (Los Angeles, California; N = 495). Estimated and empiric SI were correlated in the SA (r2 = 0.77) and AA (r2 = 0.74) testing datasets. Further, estimated and empiric SI were consistently associated with BMI, low-density lipoprotein cholesterol (LDL), and triglycerides. We applied similar approaches to estimate HOMA-IR with similar results. CONCLUSIONS: We have developed a method for estimating insulin resistance with metabolomics data that has the potential for application to a wide range of biomedical studies and conditions.

Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS).

INTRODUCTION: African Americans are at increased risk for type 2 diabetes. OBJECTIVES: This work aimed to examine metabolomic signature of glucose homeostasis in African Americans. METHODS: We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (SI, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and SG, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans. RESULTS: We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans. CONCLUSION: We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.

Metabolomic profiling of the Dietary Approaches to Stop Hypertension diet provides novel insights for the nutritional epidemiology of type 2 diabetes mellitus.

Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is inversely associated with type 2 diabetes mellitus (T2DM) risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. The objective is to determine metabolite clusters associated with adherence to a DASH-like diet in the Insulin Resistance Atherosclerosis Study cohort and explore if the clusters predicted 5-year incidence of T2DM. The current study included 570 non-diabetic multi-ethnic participants aged 40­69 years. Adherence to a DASH-like diet was determined a priori through an eighty-point scale for absolute intakes of the eight DASH food groups. Quantitative measurements of eighty-seven metabolites (acylcarnitines, amino acids, bile acids, sterols and fatty acids) were obtained at baseline. Metabolite clusters related to DASH adherence were determined through partial least squares (PLS) analysis using R. Multivariable-adjusted logistic regression was used to explore the associations between metabolite clusters and incident T2DM. A group of acylcarnitines and fatty acids loaded strongly on the two components retained under PLS. Among strongly loading metabolites, a select group of acylcarnitines had over 50 % of their individual variance explained by the PLS model. Component 2 was inversely associated with incident T2DM (OR: 0·89; (95 % CI 0·80, 0·99), P-value = 0·043) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 1·02; (95 % CI 0·88, 1·19), P-value = 0·74). Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine and fatty acid physiology.

Comparing data-driven and hypothesis-driven MRI-based predictors of cognitive impairment in individuals from the Atherosclerosis Risk in Communities (ARIC) study.

INTRODUCTION: A data-driven index of dementia risk based on magnetic resonance imaging (MRI), the Alzheimer's Disease Pattern Similarity (AD-PS) score, was estimated for participants in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: AD-PS scores were generated for 839 cognitively non-impaired individuals with a mean follow-up of 4.86 years. The scores and a hypothesis-driven volumetric measure based on several brain regions susceptible to AD were compared as predictors of incident cognitive impairment in different settings. RESULTS: Logistic regression analyses suggest the data-driven AD-PS scores to be more predictive of incident cognitive impairment than its counterpart. Both biomarkers were more predictive of incident cognitive impairment in participants who were White, female, and apolipoprotein E gene (APOE) ε4 carriers. Random forest analyses including predictors from different domains ranked the AD-PS scores as the most relevant MRI predictor of cognitive impairment. CONCLUSIONS: Overall, the AD-PS scores were the stronger MRI-derived predictors of incident cognitive impairment in cognitively non-impaired individuals.

Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study.

BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. METHODS: A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children's hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children's Hospital, Cincinnati, OH, Seattle Children's Hospital, Seattle, WA, and Children's Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. RESULTS: Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. CONCLUSIONS: Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth.

Fatty acids in the de novo lipogenesis pathway and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.

BACKGROUND: De novo lipogenesis (DNL) is the primary metabolic pathway synthesizing fatty acids from carbohydrates, protein, or alcohol. Our aim was to examine associations of in vivo levels of selected fatty acids (16:0, 16:1n7, 18:0, 18:1n9) in DNL with incidence of type 2 diabetes (T2D). METHODS AND FINDINGS: Seventeen cohorts from 12 countries (7 from Europe, 7 from the United States, 1 from Australia, 1 from Taiwan; baseline years = 1970-1973 to 2006-2010) conducted harmonized individual-level analyses of associations of DNL-related fatty acids with incident T2D. In total, we evaluated 65,225 participants (mean ages = 52.3-75.5 years; % women = 20.4%-62.3% in 12 cohorts recruiting both sexes) and 15,383 incident cases of T2D over the 9-year follow-up on average. Cohort-specific association of each of 16:0, 16:1n7, 18:0, and 18:1n9 with incident T2D was estimated, adjusted for demographic factors, socioeconomic characteristics, alcohol, smoking, physical activity, dyslipidemia, hypertension, menopausal status, and adiposity. Cohort-specific associations were meta-analyzed with an inverse-variance-weighted approach. Each of the 4 fatty acids positively related to incident T2D. Relative risks (RRs) per cohort-specific range between midpoints of the top and bottom quintiles of fatty acid concentrations were 1.53 (1.41-1.66; p < 0.001) for 16:0, 1.40 (1.33-1.48; p < 0.001) for 16:1n-7, 1.14 (1.05-1.22; p = 0.001) for 18:0, and 1.16 (1.07-1.25; p < 0.001) for 18:1n9. Heterogeneity was seen across cohorts (I2 = 51.1%-73.1% for each fatty acid) but not explained by lipid fractions and global geographical regions. Further adjusted for triglycerides (and 16:0 when appropriate) to evaluate associations independent of overall DNL, the associations remained significant for 16:0, 16:1n7, and 18:0 but were attenuated for 18:1n9 (RR = 1.03, 95% confidence interval (CI) = 0.94-1.13). These findings had limitations in potential reverse causation and residual confounding by imprecisely measured or unmeasured factors. CONCLUSIONS: Concentrations of fatty acids in the DNL were positively associated with T2D incidence. Our findings support further work to investigate a possible role of DNL and individual fatty acids in the development of T2D.

Trends in Incidence of Type 1 and Type 2 Diabetes Among Youths - Selected Counties and Indian Reservations, United States, 2002-2015.

Diabetes is one of the most common chronic diseases among persons aged <20 years (1). Onset of diabetes in childhood and adolescence is associated with numerous complications, including diabetic kidney disease, retinopathy, and peripheral neuropathy, and has a substantial impact on public health resources (2,3). From 2002 to 2012, type 1 and type 2 diabetes incidence increased 1.4% and 7.1%, respectively, among U.S. youths (4). To assess recent trends in incidence of diabetes in youths (defined for this report as persons aged <20 years), researchers analyzed 2002-2015 data from the SEARCH for Diabetes in Youth Study (SEARCH), a U.S. population-based registry study with clinical sites located in five states. The incidence of both type 1 and type 2 diabetes in U.S. youths continued to rise at constant rates throughout this period. Among all youths, the incidence of type 1 diabetes increased from 19.5 per 100,000 in 2002-2003 to 22.3 in 2014-2015 (annual percent change [APC] = 1.9%). Among persons aged 10-19 years, type 2 diabetes incidence increased from 9.0 per 100,000 in 2002-2003 to 13.8 in 2014-2015 (APC = 4.8%). For both type 1 and type 2 diabetes, the rates of increase were generally higher among racial/ethnic minority populations than those among whites. These findings highlight the need for continued surveillance for diabetes among youths to monitor overall and group-specific trends, identify factors driving these trends, and inform health care planning.

Insulin resistance and reduced cardiac autonomic function in older adults: the Atherosclerosis Risk in Communities study.

BACKGROUND: Prior studies have shown insulin resistance is associated with reduced cardiac autonomic function measured at rest, but few studies have determined whether insulin resistance is associated with reduced cardiac autonomic function measured during daily activities. METHODS: We examined older adults without diabetes with 48-h ambulatory electrocardiography (n = 759) in an ancillary study of the Atherosclerosis Risk in Communities Study. Insulin resistance, the exposure, was defined by quartiles for three indexes: 1) the homeostatic model assessment of insulin resistance (HOMA-IR), 2) the triglyceride and glucose index (TyG), and 3) the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C). Low heart rate variability, the outcome, was defined by <25th percentile for four measures: 1) standard deviation of normal-to-normal R-R intervals (SDNN), a measure of total variability; 2) root mean square of successive differences in normal-to-normal R-R intervals (RMSSD), a measure of vagal activity; 3) low frequency spectral component (LF), a measure of sympathetic and vagal activity; and 4) high frequency spectral component (HF), a measure of vagal activity. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals weighted for sampling/non-response, adjusted for age at ancillary visit, sex, and race/study-site. Insulin resistance quartiles 4, 3, and 2 were compared to quartile 1; high indexes refer to quartile 4 versus quartile 1. RESULTS: The average age was 78 years, 66% (n = 497) were women, and 58% (n = 438) were African American. Estimates of association were not robust at all levels of HOMA-IR, TyG, and TG/HDL-C, but suggest that high indexes were associated consistently with indicators of vagal activity. High HOMA-IR, high TyG, and high TG/HDL-C were consistently associated with low RMSSD (OR: 1.68 (1.00, 2.81), OR: 2.03 (1.21, 3.39), and OR: 1.73 (1.01, 2.91), respectively). High HOMA-IR, high TyG, and high TG/HDL-C were consistently associated with low HF (OR: 1.90 (1.14, 3.18), OR: 1.98 (1.21, 3.25), and OR: 1.76 (1.07, 2.90), respectively). CONCLUSIONS: In older adults without diabetes, insulin resistance was associated with reduced cardiac autonomic function - specifically and consistently for indicators of vagal activity - measured during daily activities. Primary prevention of insulin resistance may reduce the related risk of cardiac autonomic dysfunction.

Genome-wide interaction with the insulin secretion locus MTNR1B reveals CMIP as a novel type 2 diabetes susceptibility gene in African Americans.

Although type 2 diabetes (T2D) results from metabolic defects in insulin secretion and insulin sensitivity, most of the genetic risk loci identified to date relates to insulin secretion. We reported that T2D loci influencing insulin sensitivity may be identified through interactions with insulin secretion loci, thereby leading to T2D. Here, we hypothesize that joint testing of variant main effects and interaction effects with an insulin secretion locus increases power to identify genetic interactions leading to T2D. We tested this hypothesis with an intronic MTNR1B SNP, rs10830963, which is associated with acute insulin response to glucose, a dynamic measure of insulin secretion. rs10830963 was tested for interaction and joint (main + interaction) effects with genome-wide data in African Americans (2,452 cases and 3,772 controls) from five cohorts. Genome-wide genotype data (Affymetrix Human Genome 6.0 array) was imputed to a 1000 Genomes Project reference panel. T2D risk was modeled using logistic regression with rs10830963 dosage, age, sex, and principal component as predictors. Joint effects were captured using the Kraft two degrees of freedom test. Genome-wide significant (P < 5 × 10-8 ) interaction with MTNR1B and joint effects were detected for CMIP intronic SNP rs17197883 (Pinteraction  = 1.43 × 10-8 ; Pjoint  = 4.70 × 10-8 ). CMIP variants have been nominally associated with T2D, fasting glucose, and adiponectin in individuals of East Asian ancestry, with high-density lipoprotein, and with waist-to-hip ratio adjusted for body mass index in Europeans. These data support the hypothesis that additional genetic factors contributing to T2D risk, including insulin sensitivity loci, can be identified through interactions with insulin secretion loci.

Associations Between Left Ventricular Structure, Function, and Cerebral Amyloid: The ARIC-PET Study.

Background and Purpose- Cardiovascular disease is a known risk factor for cognitive decline, although the mechanisms remain unclear. We hypothesize that Aß (ß-amyloid), a core pathology of Alzheimer's disease, will be associated with subclinical cardiac structure and function echocardiogram indices. Methods- Three hundred six nondemented participants from the ARIC study (Atherosclerosis Risk in Communities Study) underwent florbetapir positron emission tomography and 2D echocardiography (echo). Cross-sectional associations between echo markers of left ventricular structure and function and global cortical Aß (≥1.2 standardized uptake value ratio were evaluated using multivariable logistic regression with interaction terms when appropriate. Results- Participants ranged in age from 67 to 88 years, were 57% female and 42% black. Per 1 cm increase in end-diastolic left ventricular diameter, the odds of elevated florbetapir standardized uptake value ratio doubled (odds ratio, 2.04 [95% CI, 1.10-3.77]), with similar findings when excluding mild cognitive impairment (odds ratio, 2.61 [95% CI, 1.22-5.59]). Conclusions- We have demonstrated a significant association between a marker of left ventricular structure and elevated florbetapir standardized uptake value ratio, identified using positron emission tomography. Ongoing prospective work will help determine if changes in cardiac structure and function either precede, or occur simultaneously with deposition of amyloid.

The prevalence of atrial fibrillation on 48-hour ambulatory electrocardiography in African Americans compared to Whites: The Atherosclerosis Risk in Communities (ARIC) study.

BACKGROUND: A lower prevalence of atrial fibrillation (AF), but paradoxically higher burden of cardiovascular disease risk factors, has been observed among African Americans compared to Whites in studies of AF identified by mostly 12-lead electrocardiograms (ECGs) and clinically. METHODS: We performed 48-hour ambulatory electrocardiography (aECG) in a biracial sample of 1,193 participants in the Atherosclerosis Risk in Communities (ARIC) (mean age = 78 years, 62% African Americans, 64% female). Atrial fibrillation was identified from aECG, study visit ECGs, and discharge codes from cohort hospitalizations. We used covariate-adjusted logistic regression to estimate prevalence odds ratios (ORs) for AF in African Americans versus Whites, with adjustment for sampling and nonresponse. RESULTS: African Americans were more likely than Whites to have hypertension and diabetes but less likely to have coronary heart disease. The prevalence of AF detected by aECG or ARIC study ECG (adjusted for age and coronary heart disease) was lower in African Americans than Whites (2.7% vs 5.0%). White men had a higher (although not significant) AF prevalence of 7.8% compared to the other race and gender groups at 2.3%-2.8%. The adjusted OR for AF was 0.49 (0.24-0.99) comparing African Americans to Whites. Findings were similar when AF was defined to include prior AF hospitalizations (OR = 0.42, 0.25-0.72). There were no significant differences by race for asymptomatic or paroxysmal AF. CONCLUSIONS: Atrial fibrillation was less prevalent in African American than white older adults, regardless of detection method. Although overall detection of new AF cases with aECG was low, future studies should consider longer-term monitoring to characterize AF by race.

Differences in Cardiovascular Mortality Risk among African Americans in the Minnesota Heart Survey: 1985-2015 vs The Atherosclerosis Risk in Communities Study Cohort: 1987-2015.

Geographic differences in cardiovascular disease (CVD) mortality among African Americans (AAs) are well-established, but not well-characterized. Using the Minnesota Heart Survey (MHS) and Atherosclerosis Risk in Communities (ARIC) Study, we aimed to assess whether CVD risk factors drive geographic disparities in CVD mortality among AAs. ARIC risk factors were measured between1987-1989 from a population-based sample of AAs, aged 45 to 64 years, living in Jackson, MS and Forsyth County, NC. Similar measures were made at MHS baseline, 1985, in AAs from Minneapolis-St. Paul, MN. CVD mortality was identified using ICD codes for underlying cause of death. We compared MHS and ARIC on CVD death rates using Poisson regression, risk factor prevalences, and hazard ratios using Cox regression. After CVD risk factor adjustment, AA men in MHS had 3.4 (95% CI: 2.1, 4.7) CVD deaths per 1000 person-years vs 9.9 (95% CI: 8.7, 11.1) in ARIC. AA women in MHS had 2.7 (95% CI: 1.8, 3.6) CVD deaths per 1000 person-years vs 6.7 (95% CI: 6.0, 7.4) in ARIC. A 2-fold higher CVD mortality rate remained in ARIC vs MHS after additional adjustment for education and income. ARIC had higher total cholesterol, hypertension, diabetes, and BMI, as well as less education and income than MHS. Risk factor hazard ratios of CVD death did not differ. The CVD death rate was lower in AAs in Minnesota (MHS) than AAs in the Southeast (ARIC). While our findings support maintaining low risk for CVD prevention, differences in CVD mortality reflect unidentified geographic variation.

Serum metabolomic profile of incident diabetes.

AIMS/HYPOTHESIS: Metabolomic profiling offers the potential to reveal metabolic pathways relevant to the pathophysiology of diabetes and improve diabetes risk prediction. METHODS: We prospectively analysed known metabolites using an untargeted approach in serum specimens from baseline (1987-1989) and incident diabetes through to 31 December 2015 in a subset of 2939 Atherosclerosis Risk in Communities (ARIC) study participants with metabolomics data and without prevalent diabetes. RESULTS: Among the 245 named compounds identified, seven metabolites were significantly associated with incident diabetes after Bonferroni correction and covariate adjustment; these included a food additive (erythritol) and compounds involved in amino acid metabolism [isoleucine, leucine, valine, asparagine, 3-(4-hydoxyphenyl)lactate] and glucose metabolism (trehalose). Higher levels of metabolites were associated with increased risk of incident diabetes (HR per 1 SD increase in isoleucine 2.96, 95% CI 2.02, 4.35, p = 3.18 × 10-8; HR per 1 SD increase in trehalose 1.16, 95% CI 1.09, 1.25, p = 1.87 × 10-5), with the exception of asparagine, which was associated with a lower risk of diabetes (HR per 1 SD increase in asparagine 0.78, 95% CI 0.71, 0.85, p = 4.19 × 10-8). The seven metabolites modestly improved prediction of incident diabetes beyond fasting glucose and established risk factors (C statistics 0.744 vs 0.735, p = 0.001 for the difference in C statistics). CONCLUSIONS/INTERPRETATION: Branched chain amino acids may play a role in diabetes development. Our study is the first to report asparagine as a protective biomarker of diabetes risk. The serum metabolome reflects known and novel metabolic disturbances that improve prediction of diabetes.

Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.

BACKGROUND: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). METHODS AND FINDINGS: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. CONCLUSIONS: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.

Individual serum saturated fatty acids and markers of chronic subclinical inflammation: the Insulin Resistance Atherosclerosis Study.

Recent evidence has documented distinct effects of individual saturated FAs (SFAs) on cardiometabolic outcomes, with potential protective effects from odd- and very long-chain SFAs (VLSFAs). Cross-sectional and prospective associations of individual serum SFAs (12:0, 14:0, 15:0, 16:0, 18:0, 20:0, 22:0, and total SFA) with proinflammatory biomarkers and adiponectin were investigated in 555 adults from the IRAS. Principal component analysis (PCA) of proinflammatory markers yielded three clusters: principal component (PC) 1: fibrinogen, white cell count, C-reactive protein; PC 2: plasminogen activator inhibitor-1 (PAI-1), TNF-α, IL-18; PC 3: IL-6 and IL-8. Cross-sectional analyses on proinflammatory PCs and adiponectin, and prospective analyses on 5 year PAI-1 and fibrinogen concentrations were conducted with multiple regression. Total SFA and 16:0 were positively associated with PC 1 and PC 2, and negatively associated with adiponectin. The 14:0 was positively associated with PC 1 and negatively associated with adiponectin. In contrast, 15:0, 20:0, and 22:0 were negatively associated with PC 2, and 20:0 and 22:0 were positively associated with adiponectin. The 18:0 was negatively associated with PC 3. Prospectively, 15:0, 18:0, 20:0, and 22:0 were negatively associated with 5 year PAI-1 concentrations. The results demonstrate that individual SFAs have distinct roles in subclinical inflammation, highlighting the unique metabolic impacts of individual SFAs.

Analysis of Whole Exome Sequencing with Cardiometabolic Traits Using Family-Based Linkage and Association in the IRAS Family Study.

Family-based methods are a potentially powerful tool to identify trait-defining genetic variants in extended families, particularly when used to complement conventional association analysis. We utilized two-point linkage analysis and single variant association analysis to evaluate whole exome sequencing (WES) data from 1205 Hispanic Americans (78 families) from the Insulin Resistance Atherosclerosis Family Study. WES identified 211,612 variants above the minor allele frequency threshold of ≥0.005. These variants were tested for linkage and/or association with 50 cardiometabolic traits after quality control checks. Two-point linkage analysis yielded 10,580,600 logarithm of the odds (LOD) scores with 1148 LOD scores ≥3, 183 LOD scores ≥4, and 29 LOD scores ≥5. The maximal novel LOD score was 5.50 for rs2289043:T>C, in UNC5C with subcutaneous adipose tissue volume. Association analysis identified 13 variants attaining genome-wide significance (P < 5 × 10-08 ), with the strongest association between rs651821:C>T in APOA5 and triglyceride levels (P = 3.67 × 10-10 ). Overall, there was a 5.2-fold increase in the number of informative variants detected by WES compared to exome chip analysis in this population, nearly 30% of which were novel variants relative to the Database of Single Nucleotide Polymorphisms (dbSNP) build 138. Thus, integration of results from two-point linkage and single-variant association analysis from WES data enabled identification of novel signals potentially contributing to cardiometabolic traits.

Genome-wide linkage and association analysis of cardiometabolic phenotypes in Hispanic Americans.

Linkage studies of complex genetic diseases have been largely replaced by genome-wide association studies, due in part to limited success in complex trait discovery. However, recent interest in rare and low-frequency variants motivates re-examination of family-based methods. In this study, we investigated the performance of two-point linkage analysis for over 1.6 million single-nucleotide polymorphisms (SNPs) combined with single variant association analysis to identify high impact variants, which are both strongly linked and associated with cardiometabolic traits in up to 1414 Hispanics from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Evaluation of all 50 phenotypes yielded 83 557 000 LOD (logarithm of the odds) scores, with 9214 LOD scores ⩾3.0, 845 ⩾4.0 and 89 ⩾5.0, with a maximal LOD score of 6.49 (rs12956744 in the LAMA1 gene for tumor necrosis factor-α (TNFα) receptor 2). Twenty-seven variants were associated with P<0.005 as well as having an LOD score >4, including variants in the NFIB gene under a linkage peak with TNFα receptor 2 levels on chromosome 9. Linkage regions of interest included a broad peak (31 Mb) on chromosome 1q with acute insulin response (max LOD=5.37). This region was previously documented with type 2 diabetes in family-based studies, providing support for the validity of these results. Overall, we have demonstrated the utility of two-point linkage and association in comprehensive genome-wide array-based SNP genotypes.