The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits.

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Distribution, Determinants and Normal Reference Values of Aortic Arch Width: Thoracic Aortic Geometry in the Framingham Heart Study.

Study Objective: Aortic arch geometry changes with age, including an increase in aortic arch width (AAW). High AAW is a predictor of incident adverse cardiovascular disease (CVD) events, but its distribution and determinants are unknown. We hypothesized that traditional CVD risk factors, in addition to age, are associated with increased AAW in community-dwelling adults. Study Design: Framingham Offspring and Third Generation cohort participants (N=3026, 52% Men) underwent thoracic multidetector computed tomography (MDCT). A referent group (733M, 738W) free of clinical CVD, hypertension, dyslipidemia, smoking, and diabetes was used to generate sex and 10-year age-group specific upper 90th percentile (P90) cut-points for AAW. AAW was measured as the distance between the cross-sectional centroids of the ascending and descending thoracic aorta. Multivariable logistic regression models were used to identify clinical correlates of high AAW (≥referent P90) in the overall study group. Results: Among referent participants, AAW increased with greater age-group, p for trend <0.0001 in each sex. Overall and within each age group, AAW was greater in men than women, p<0.0001 all comparisons. Across all participants, high AAW was associated with greater age (odds ratio, OR=1.34/10y; 95% confidence interval 1.20 - 1.50), body surface area (OR=1.97/SD; 1.62 - 2.40), diastolic blood pressure (OR=1.59/10mmHg; 1.40 - 1.81), pack-years smoked (OR=1.07; 1.02 - 1.13), and prevalent CVD (OR=1.64; 1.08 - 2.49). Conclusion: AAW increases with greater age, body size, diastolic blood pressure and burden of smoking. High AAW (≥referent P90) is also associated with prevalent (clinically apparent) CVD. AAW is often seen on and easily measured from tomographic thoracic images and has prognostic value.

An Exploratory Study Using Electronic Medical Records to Assess the Feasibility of Establishing Cohorts of Patients with Genetic Causes of Parkinson's Disease.

BACKGROUND: More efficient screening methods are needed to improve the ability to identify and follow genetic cohorts in Parkinson's disease (PD). OBJECTIVE: To explore the use of the electronic medical records (EMRs) to identify participants with PD. METHODS: Using an algorithm previously developed in collaboration with Maccabi Healthcare Services (MHS), approximately 5,200 participants with PD were identified, more than 3,200 were screened, and 837 participants were enrolled and genotyped for leucine-rich repeat kinase 2 (LRRK2) and beta-glucocerebrosidase (GBA) variants. Questionnaires were completed to ascertain Ashkenazi Jewish (AJ) ancestry and family history of PD. RESULTS: Among 837 participants with PD, 82% were 65 years and older and 72% had a family history of AJ ancestry. Among those with AJ ancestry, 15.6% reported having relatives with PD. The frequency of observed mutations for LRRK2 and GBA genes combined was approximately 15.4%. The frequency of observed LRRK2 mutation was 6.1% overall and 7.2% from those with AJ ancestry; and for GBA mutation was 9.3% overall and 11.2% from those with AJ ancestry. CONCLUSION: Although the frequency of observed mutations in this study was lower than anticipated, mutation carriers were enriched among those with a family history of AJ ancestry increasing nearly 2-3-fold, from 3% -7% (LRRK2) and 4% -11% (GBA). The identification (and selection) of PD patients through EMRs prior to genotyping is a viable approach, to establish a genetically defined cohort of patients with PD for clinical research.

Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design.

BACKGROUND: New electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates. OBJECTIVE: The objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study. METHODS: We coenrolled participants from the Framingham Heart Study (FHS) into the FHS-Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months. RESULTS: Compared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms. CONCLUSIONS: Our pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups.

Using Human Genetics to Drive Drug Discovery: A Perspective.

The probability of success of developing medicines to treat human disease can be improved by leveraging human genetics. Different types of genetic data and techniques, including genome-wide association, whole-exome sequencing, and whole-genome sequencing, can be used to gain insight into human disease. Layering different types of genetic evidence from Mendelian disease, coding variants, and common variation can bolster support for a genetic target. Human knockouts offer the potential to perform reverse genetic screens in humans to identify physiologically relevant targets. Other components of a good genetic target include protective loss-of-function mutations, some degree of known biology, tractability, and a clean on-target safety profile. In addition to using human genetics to inspire new drug programs, phenome-wide association studies can be used to identify alternative indications or repurposing opportunities. This information can be combined into a 5-step approach for selecting a genetic target for validation, which is presented in detail in this review. Finally, current challenges in leveraging human genetics are highlighted, including the difficulties translating certain types of genetic data, relatively small number of bona fide disease-associated coding rare variants, and current sample sizes of large well-curated biobanks linked to comprehensive genetic information.

Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies.

BACKGROUND: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. METHODS: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. FINDINGS: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-PC, which included 693 816 individuals (557 583 [80%] with diabetes). Data for 675 904 individuals and 7461 end-stage kidney disease events were available for our primary outcome analysis. Change in ACR was consistently associated with subsequent risk of end-stage kidney disease. The adjusted hazard ratio (HR) for end-stage kidney disease after a 30% decrease in ACR during a baseline period of 2 years was 0·83 (95% CI 0·74-0·94), decreasing to 0·78 (0·66-0·92) after further adjustment for regression dilution. Adjusted HRs were fairly consistent across cohorts and subgroups (ie, estimated glomerular filtration rate, diabetes, and sex), but the association was somewhat stronger among participants with higher baseline ACR than among those with lower baseline ACR (pinteraction<0·0001). In individuals with baseline ACR of 300 mg/g or higher, a 30% decrease in ACR over 2 years was estimated to confer a more than 1% absolute reduction in 10-year risk of end-stage kidney disease, even at early stages of chronic kidney disease. Results were generally similar when we used change in PCR and when study populations from clinical trials were assessed. INTERPRETATION: Change in albuminuria was consistently associated with subsequent risk of end-stage kidney disease across a range of cohorts, lending support to the use of change in albuminuria as a surrogate endpoint for end-stage kidney disease in clinical trials of progression of chronic kidney disease in the setting of increased albuminuria. FUNDING: US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.

Integrating genetic, transcriptional, and biological information provides insights into obesity.

OBJECTIVE: Indices of body fat distribution are heritable, but few genetic signals have been reported from genome-wide association studies (GWAS) of computed tomography (CT) imaging measurements of body fat distribution. We aimed to identify genes associated with adiposity traits and the key drivers that are central to adipose regulatory networks. SUBJECTS: We analyzed gene transcript expression data in blood from participants in the Framingham Heart Study, a large community-based cohort (n up to 4303), as well as implemented an integrative analysis of these data and existing biological information. RESULTS: Our association analyses identified unique and common gene expression signatures across several adiposity traits, including body mass index, waist-hip ratio, waist circumference, and CT-measured indices, including volume and quality of visceral and subcutaneous adipose tissues. We identified six enriched KEGG pathways and two co-expression modules for further exploration of adipose regulatory networks. The integrative analysis revealed four gene sets (Apoptosis, p53 signaling pathway, Proteasome, Ubiquitin-mediated proteolysis) and two co-expression modules with significant genetic variants and 94 key drivers/genes whose local networks were enriched with adiposity-associated genes, suggesting that these enriched pathways or modules have genetic effects on adiposity. Most identified key driver genes are involved in essential biological processes such as controlling cell cycle, DNA repair, and degradation of regulatory proteins are cancer related. CONCLUSIONS: Our integrative analysis of genetic, transcriptional, and biological information provides a list of compelling candidates for further follow-up functional studies to uncover the biological mechanisms underlying obesity. These candidates highlight the value of examining CT-derived and central adiposity traits.

Phenome-wide association studies across large population cohorts support drug target validation.

Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P < 0.05) and identify nine study-wide significant novel associations (of 71 with FDR < 0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.

Large-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels.

Elevated serum urate levels can cause gout, an excruciating disease with suboptimal treatment. Previous GWAS identified common variants with modest effects on serum urate. Here we report large-scale whole-exome sequencing association studies of serum urate and kidney function among ≤19,517 European ancestry and African-American individuals. We identify aggregate associations of low-frequency damaging variants in the urate transporters SLC22A12 (URAT1; p = 1.3 × 10-56) and SLC2A9 (p = 4.5 × 10-7). Gout risk in rare SLC22A12 variant carriers is halved (OR = 0.5, p = 4.9 × 10-3). Selected rare variants in SLC22A12 are validated in transport studies, confirming three as loss-of-function (R325W, R405C, and T467M) and illustrating the therapeutic potential of the new URAT1-blocker lesinurad. In SLC2A9, mapping of rare variants of large effects onto the predicted protein structure reveals new residues that may affect urate binding. These findings provide new insights into the genetic architecture of serum urate, and highlight molecular targets in SLC22A12 and SLC2A9 for lowering serum urate and preventing gout.

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.

Genomic atlas of the human plasma proteome.

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

Aortic Arch Width and Cardiovascular Disease in Men and Women in the Community.

BACKGROUND: We sought to determine whether increased aortic arch width (AAW) adds to standard Framingham risk factors and coronary artery calcium (CAC) for prediction of incident adverse cardiovascular disease (CVD) events in community-dwelling adults. METHODS AND RESULTS: A total of 3026 Framingham Heart Study Offspring and Third Generation cohort participants underwent noncontrast multidetector computed tomography from 2002 to 2005 to quantify CAC. We measured AAW as the distance between the centroids of the ascending and descending thoracic aorta, at the level of main pulmonary artery bifurcation or the right pulmonary artery. We determined sex, age group, and body size specific cut points for high (≥90th percentile) AAW from a healthy referent group (N=1471) and dichotomized AAW as high or not high across all study participants. Clinical covariates were obtained at Offspring cycle 7 (1998-2001) or Third Generation cycle 1 (2002-2005) examinations. The primary CVD outcome was a composite of myocardial infarction, coronary insufficiency, cerebrovascular accident, first hospitalization for heart failure, or CVD death. Cox proportional hazards models were used to estimate hazard ratio of high AAW on time-to-incident CVD after adjustment for Framingham risk factors and CAC. Net reclassification improvement was used to assess the effect of adding AAW to the baseline Framingham risk factor+CAC model. A total of 2826 participants (aged 51±11 years, 48% women) had complete covariates and were free of CVD at multidetector computed tomography. Over a median 8.9 years of follow-up, there were 135 incident CVD events. High AAW was independently predictive of CVD events (hazard ratio, 1.55; P=0.032) and appropriately reclassified participants at risk: net reclassification improvement, 0.31 (95% confidence interval, 0.15-0.48). CONCLUSION: AAW augments traditional CVD risk factors and CAC for prediction of incident adverse CVD events among community-dwelling adults.

Observational and Genetic Associations of Resting Heart Rate With Aortic Valve Calcium.

It is unknown if lifelong exposure to increased hemodynamic stress from an elevated resting heart rate (HR) may contribute to aortic valve calcium (AVC). We performed multivariate regression analyses using data from 1,266 Framingham Heart Study (FHS) Offspring cohort participants and 6,764 Multi-Ethnic Study of Atherosclerosis (MESA) participants. We constructed a genetic risk score (GRS) for HR using summary-level data in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) AVC Consortium to investigate if there was evidence in favor of a causal relation. AVC was present in 39% of FHS Offspring cohort participants and in 13% of MESA cohort participants. In multivariate adjusted models, participants in the highest resting HR quartiles had significantly greater prevalence of AVC, with a prevalence ratio of 1.19 (95% confidence interval [CI] 0.99 to 1.44) for the FHS Offspring cohort and 1.32 (95% CI 1.12 to 1.63) for the MESA cohort, compared with those in the lowest quartile. There was a similar increase in the prevalence of AVC per standard deviation increase in resting HR in both FHS Offspring (prevalence ratio 1.08, 95% CI 1.01 to 1.15) and MESA (1.10, 95% CI 1.03 to 1.17). In contrast with these observational findings, a HR associated GRS was not significantly associated with AVC. Although our observational analysis indicates that a higher resting HR is associated with AVC, our genetic results do not support a causal relation. Unmeasured environmental and/or lifestyle factors associated with both increased resting HR and AVC that are not fully explained by covariates in our observational models may account for the association between resting HR and AVC.

Association of Cardiovascular Biomarkers With Incident Heart Failure With Preserved and Reduced Ejection Fraction.

Importance: Nearly half of all patients with heart failure have preserved ejection fraction (HFpEF) as opposed to reduced ejection fraction (HFrEF), yet associations of biomarkers with future heart failure subtype are incompletely understood. Objective: To evaluate the associations of 12 cardiovascular biomarkers with incident HFpEF vs HFrEF among adults from the general population. Design, Setting, and Participants: This study included 4 longitudinal community-based cohorts: the Cardiovascular Health Study (1989-1990; 1992-1993 for supplemental African-American cohort), the Framingham Heart Study (1995-1998), the Multi-Ethnic Study of Atherosclerosis (2000-2002), and the Prevention of Renal and Vascular End-stage Disease study (1997-1998). Each cohort had prospective ascertainment of incident HFpEF and HFrEF. Data analysis was performed from June 25, 2015, to November 9, 2017. Exposures: The following biomarkers were examined: N-terminal pro B-type natriuretic peptide or brain natriuretic peptide, high-sensitivity troponin T or I, C-reactive protein (CRP), urinary albumin to creatinine ratio (UACR), renin to aldosterone ratio, D-dimer, fibrinogen, soluble suppressor of tumorigenicity, galectin-3, cystatin C, plasminogen activator inhibitor 1, and interleukin 6. Main Outcomes and Measures: Development of incident HFpEF and incident HFrEF. Results: Among the 22 756 participants in these 4 cohorts (12 087 women and 10 669 men; mean [SD] age, 60 [13] years) in the study, during a median follow-up of 12 years, 633 participants developed incident HFpEF, and 841 developed HFrEF. In models adjusted for clinical risk factors of heart failure, 2 biomarkers were significantly associated with incident HFpEF: UACR (hazard ratio [HR], 1.33; 95% CI, 1.20-1.48; P < .001) and natriuretic peptides (HR, 1.27; 95% CI, 1.16-1.40; P < .001), with suggestive associations for high-sensitivity troponin (HR, 1.11; 95% CI, 1.03-1.19; P = .008), plasminogen activator inhibitor 1 (HR, 1.22; 95% CI, 1.03-1.45; P = .02), and fibrinogen (HR, 1.12; 95% CI, 1.03-1.22; P = .01). By contrast, 6 biomarkers were associated with incident HFrEF: natriuretic peptides (HR, 1.54; 95% CI, 1.41-1.68; P < .001), UACR (HR, 1.21; 95% CI, 1.11-1.32; P < .001), high-sensitivity troponin (HR, 1.37; 95% CI, 1.29-1.46; P < .001), cystatin C (HR, 1.19; 95% CI, 1.11-1.27; P < .001), D-dimer (HR, 1.22; 95% CI, 1.11-1.35; P < .001), and CRP (HR, 1.19; 95% CI, 1.11-1.28; P < .001). When directly compared, natriuretic peptides, high-sensitivity troponin, and CRP were more strongly associated with HFrEF compared with HFpEF. Conclusions and Relevance: Biomarkers of renal dysfunction, endothelial dysfunction, and inflammation were associated with incident HFrEF. By contrast, only natriuretic peptides and UACR were associated with HFpEF. These findings highlight the need for future studies focused on identifying novel biomarkers of the risk of HFpEF.

Maintenance of Ideal Cardiovascular Health and Coronary Artery Calcium Progression in Low-Risk Men and Women in the Framingham Heart Study.

BACKGROUND: Ideal cardiovascular health (CVH) is associated with a lower risk of cardiovascular disease and freedom from coronary artery calcium (CAC). Prospective data on the association between maintenance of optimal CVH and the progression of subclinical coronary atherosclerosis are limited. We assessed the influence of unfavorable versus favorable CVH on the incidence of CAC progression. METHODS AND RESULTS: The study population consisted of 1119 FHS (Framingham Heart Study) participants who attended the serial FHS MDCT I and MDCT II study (Multi-Detector Computed Tomography) and had a zero Agatston CAC score at baseline. CVH status was defined using 6 CVH metrics from the American Heart Association definition. CAC progression was defined by an increase in Agatston CAC score to ≥3.4. Generalized estimating equations were applied to identify significant associations of CAC progression with both the baseline measurement of CVH and the longitudinal maintenance of CVH. After follow-up (mean, 6.1 years), we observed CAC progression in 191 participants (17.1%). Participants with unfavorable CVH at baseline had a greater risk of CAC progression (odds ratio, 2.43; 95% confidence interval, 1.40-4.23; P=0.0017). In addition, each unit decrease in ideal CVH metric was associated with an increase in CAC progression (odds ratio, 1.15; 95% confidence interval, 0.99-1.34; P=0.067), after adjustment for baseline ideal CVH metrics. CONCLUSIONS: Significant associations between an unfavorable CVH profile and CAC progression support public health measures that seek to prevent cardiovascular disease by promoting favorable CVH profiles in persons free of clinical and subclinical cardiovascular disease.

Ambient air pollution, adipokines, and glucose homeostasis: The Framingham Heart Study.

OBJECTIVE: To examine associations of proximity to major roadways, sustained exposure to fine particulate matter (PM2.5), and acute exposure to ambient air pollutants with adipokines and measures of glucose homeostasis among participants living in the northeastern United States. METHODS: We included 5958 participants from the Framingham Offspring cohort examination cycle 7 (1998-2001) and 8 (2005-2008) and Third Generation cohort examination cycle 1 (2002-2005) and 2 (2008-2011), who did not have type 2 diabetes at the time of examination visit. We calculated 2003 annual average PM2.5 at participants' home address, residential distance to the nearest major roadway, and daily PM2.5, black carbon (BC), sulfate, nitrogen oxides (NOx), and ozone concentrations. We used linear mixed effects models for fasting glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) which were measured up to twice, and used linear regression models for adiponectin, resistin, leptin, and hemoglobin A1c (HbA1c) which were measured only once, adjusting for demographics, socioeconomic position, lifestyle, time, and seasonality. RESULTS: The mean age was 51years and 55% were women. Participants who lived 64m (25th percentile) from a major roadway had 0.28% (95% CI: 0.05%, 0.51%) higher fasting plasma glucose than participants who lived 413m (75th percentile) away, and the association appeared to be driven by participants who lived within 50m from a major roadway. Higher exposures to 3- to 7-day moving averages of BC and NOx were associated with higher glucose whereas the associations for ozone were negative. The associations otherwise were generally null and did not differ by median age, sex, educational attainment, obesity status, or prediabetes status. CONCLUSIONS: Living closer to a major roadway or acute exposure to traffic-related air pollutants were associated with dysregulated glucose homeostasis but not with adipokines among participants from the Framingham Offspring and Third Generation cohorts.

Barriers to medication adherence and links to cardiovascular disease risk factor control: the Framingham Heart Study.

BACKGROUND: In the elderly, impaired cognition may weaken medication adherence and compromise treatment for cardiovascular disease (CVD). AIM: We examined risk factors for medication adherence and the relationship between adherence and levels of CVD risk factors among older participants with hypertension, dyslipidaemia and diabetes in the Framingham Heart Study. METHODS: The four-item Morisky Medication Adherence Scale was administered to 1559 participants, median age 70 years, 53% women. We created an adherence score, ranging from 0 to 4, with low adherence defined as a score ≥2. CVD risk factors were assessed using standard protocols. Cognition was measured using the Mini-Mental State Examination (MMSE) and depressive symptoms were measured using the Center for Epidemiologic Studies of Depression (CES-D) scale. RESULTS: Among participants who self-reported taking antihypertensive, lipid-lowering and/or hyperglycaemic medication(s), 12% (n = 191) had low medication adherence. The risk of low adherence increased by 45% (95% confidence interval (CI): 25-68%, P < 0.001) per five-unit increase in CES-D score. In participants taking antihypertensive medication (n = 1017), low adherence was associated with higher mean diastolic blood pressure (73 mmHg, 95% CI: 71-75 vs 71 mmHg, 95% CI: 70-71; P = 0.04) after adjusting for covariates. Among participants taking lipid-lowering medication (n = 937), low adherence was associated with higher mean low-density lipoprotein cholesterol (92 mg/dL, 95% CI: 87-96 vs 86 mg/dL, 95% CI: 84-88; P = 0.03). Low adherence was not associated with fasting plasma glucose (P = 0.10) or haemoglobin A1c (P = 0.68) in the subgroup of participants (n = 192) taking hypoglycaemic medication. CONCLUSIONS: Depressive symptoms might act as a barrier for medication adherence, which exacerbates CVD risk factors in older-aged adults.

Predictors and outcomes of heart failure with mid-range ejection fraction.

AIMS: While heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid-range ejection fraction (HFmrEF) remain unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community. METHODS AND RESULTS: We pooled data from four community-based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF [ejection fraction (EF) 41-49%], HFpEF (EF ≥50%), and HFrEF (EF ≤40%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P ≤ 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin-C, and high-sensitivity troponin (P ≤ 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF [hazard ratio (HR) 2.00 per 1 standard deviation increase, 95% confidence interval (CI) 1.81-2.20] than of HFmrEF (HR 1.51, 95% CI 1.20-1.90, P = 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95% CI 1.41-1.73, P = 0.68 for difference). All-cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person-years, P = 0.02), but comparable to that of HFrEF (46 events per 1000 person-years, P = 0.78). CONCLUSIONS: We found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.

Epigenome-wide association studies identify DNA methylation associated with kidney function.

Chronic kidney disease (CKD) is defined by reduced estimated glomerular filtration rate (eGFR). Previous genetic studies have implicated regulatory mechanisms contributing to CKD. Here we present epigenome-wide association studies of eGFR and CKD using whole-blood DNA methylation of 2264 ARIC Study and 2595 Framingham Heart Study participants to identify epigenetic signatures of kidney function. Of 19 CpG sites significantly associated (P < 1e-07) with eGFR/CKD and replicated, five also associate with renal fibrosis in biopsies from CKD patients and show concordant DNA methylation changes in kidney cortex. Lead CpGs at PTPN6/PHB2, ANKRD11, and TNRC18 map to active enhancers in kidney cortex. At PTPN6/PHB2 cg19942083, methylation in kidney cortex associates with lower renal PTPN6 expression, higher eGFR, and less renal fibrosis. The regions containing the 243 eGFR-associated (P < 1e-05) CpGs are significantly enriched for transcription factor binding sites of EBF1, EP300, and CEBPB (P < 5e-6). Our findings highlight kidney function associated epigenetic variation.