Genetics of the Framingham Heart Study population

Epidrugs in the clinical management of atherosclerosis: Mechanisms, challenges and promises

Atherosclerosis is a complex and multigenic pathology associated with significant epigenetic reprogramming. Traditional factors (age, sex, obesity, hyperglycaemia, dyslipidaemia, hypertension) and non-traditional factors (foetal indices, microbiome alteration, clonal hematopoiesis, air pollution, sleep disorders) induce endothelial dysfunction, resulting in reduced vascular tone and increased vascular permeability, inflammation and shear stress. These factors induce paracrine and autocrine interactions between several cell types, including vascular smooth muscle cells, endothelial cells, monocytes/macrophages, dendritic cells and T cells. Such cellular interactions lead to tissue-specific epigenetic reprogramming regulated by DNA methylation, histone modifications and microRNAs, which manifests in atherosclerosis. Our review outlines epigenetic signatures during atherosclerosis, which are viewed as potential clinical biomarkers that may be adopted as new therapeutic targets. Additionally, we emphasize epigenetic modifiers referred to as 'epidrugs' as potential therapeutic molecules to correct gene expression patterns and restore vascular homeostasis during atherosclerosis. Further, we suggest nanomedicine-based strategies involving the use of epidrugs, which may selectively target cells in the atherosclerotic microenvironment and reduce off-target effects.

Bioinformatic platforms for clinical stratification of natural history of atherosclerotic cardiovascular diseases

Although bioinformatic methods gained a lot of attention in the latest years, their use in real-world studies for primary and secondary prevention of atherosclerotic cardiovascular diseases (ASCVD) is still lacking. Bioinformatic resources have been applied to thousands of individuals from the Framingham Heart Study as well as health care-associated biobanks such as the UK Biobank, the Million Veteran Program, and the CARDIoGRAMplusC4D Consortium and randomized controlled trials (i.e. ODYSSEY, FOURIER, ASPREE, and PREDIMED). These studies contributed to the development of polygenic risk scores (PRS), which emerged as novel potent genetic-oriented tools, able to calculate the individual risk of ASCVD and to predict the individual response to therapies such as statins and proprotein convertase subtilisin/kexin type 9 inhibitor. ASCVD are the first cause of death around the world including coronary heart disease (CHD), peripheral artery disease, and stroke. To achieve the goal of precision medicine and personalized therapy, advanced bioinformatic platforms are set to link clinically useful indices to heterogeneous molecular data, mainly epigenomics, transcriptomics, metabolomics, and proteomics. The DIANA study found that differential methylation of ABCA1, TCF7, PDGFA, and PRKCZ significantly discriminated patients with acute coronary syndrome from healthy subjects and their expression levels positively associated with CK-MB serum concentrations. The ARIC Study revealed several plasma proteins, acting or not in lipid metabolism, with a potential role in determining the different pleiotropic effects of statins in each subject. The implementation of molecular high-throughput studies and bioinformatic techniques into traditional cardiovascular risk prediction scores is emerging as a more accurate practice to stratify patients earlier in life and to favour timely and tailored risk reduction strategies. Of note, radiogenomics aims to combine imaging features extracted for instance by coronary computed tomography angiography and molecular biomarkers to create CHD diagnostic algorithms useful to characterize atherosclerotic lesions and myocardial abnormalities. The current view is that such platforms could be of clinical value for prevention, risk stratification, and treatment of ASCVD.

Assessment of the Genetic Characteristics of a Generation Born during a Long-Term Socioeconomic Crisis

BACKGROUND

A socioeconomic crisis in Russia lasted from 1991 to 1998 and was accompanied by a sharp drop in the birth rate. The main factor that influenced the refusal to have children during this period is thought to be prolonged social stress.

METHODS

comparing frequencies of common gene variants associated with stress-induced diseases among generations born before, after, and during this crisis may show which genes may be preferred under the pressure of natural selection during periods of increased social stress in urban populations.

RESULTS

In the "crisis" group, a statistically significant difference from the other two groups was found in rs6557168 frequency (p = 0.001); rs4522666 was not in the Hardy-Weinberg equilibrium in this group, although its frequency did not show a significant difference from the other groups (p = 0.118). Frequencies of VNTRs in SLC6A3 and MAOA as well as common variants rs17689918 in CRHR1, rs1360780 in FKBP5, rs53576 in OXTR, rs12720071 and rs806377 in CNR1, rs4311 in ACE, rs1800497 in ANKK1, and rs7412 and rs429358 in APOE did not differ among the groups.

CONCLUSIONS

a generation born during a period of prolonged destructive events may differ from the rest of the gene pool of the population in some variants associated with personality traits or stress-related disorders.

Dairy Food Intake Is Not Associated With Frailty in Adults From the Framingham Heart Study

BACKGROUND

Nutrients, including protein, calcium, and fat may be associated with risk of frailty, yet specific contributions from whole dairy foods rich in these nutrients remain understudied.

OBJECTIVE

To determine associations between dairy intake (milk, yogurt, cheese, total (milk + yogurt + cheese), low-fat and high-fat dairy, and servings per week) and frailty onset and frailty phenotype components.

DESIGN

Prospective cohort study. All dairy intake exposures (servings per week) were assessed via a food frequency questionnaire.

PARTICIPANTS AND SETTING

Participants (aged 33 to 86 years) from the Framingham Offspring Study who were not frail at baseline (1998-2001) completed a food frequency questionnaire and had 1 or 2 follow-up frailty assessments (2005-2008 and 2011-2014) were included.

MAIN OUTCOME MEASURES

Frailty was defined as the presence of ≥3 Fried frailty phenotype components: unintentional weight-loss, exhaustion, slowness (gait speed), weakness (grip strength), and low physical activity. Individuals with zero to two components were considered nonfrail.

STATISTICAL ANALYSES PERFORMED

Repeated measures logistic regression estimated odds ratios and 95% CIs for frailty onset. Logistic (exhaustion and weight loss) and linear regression (gait speed, grip strength, and physical activity) estimated the association between baseline dairy intake and each frailty component at follow-up, adjusting for baseline values for age, sex, energy intake (residual analysis), current smoking, and multivitamin use. Models were further adjusted for health status in a secondary analysis.

RESULTS

Mean baseline age ± SD was 61 ± 9 years (range = 33 to 87 years), and 54% were women. Of 2,550 nonfrail individuals at baseline, 8.8% (2005-2008) and 13.5% (2011-2014) became frail. Higher yogurt intake was associated with decreased odds of frailty (odds ratio 0.96, 95% CI 0.93 to 0.99; P = 0.02). Each additional serving of yogurt (β ± SE) .004 ± .001; P < 0.01) and low-fat dairy (β ± SE) .001 ± .0006; P = 0.04) was associated with significantly faster follow-up gait speed. Dietary intakes of high-fat dairy were associated with increased odds of frailty (odds ratio 1.02, 95% CI 1.00 to 1.04; P = 0.05), but the P value was of borderline significance. No associations were observed for other dairy foods. After adjusting for health status, the associations of high-fat dairy and yogurt with frailty became nonsignificant, although the magnitudes of the associations did not change. The association between yogurt and gait speed decreased in magnitude after adjusting for health status (β ± SE) .002 ± .001; P = 0.01).

CONCLUSIONS

Dietary intakes of yogurt were modestly associated with reduced frailty onset and dietary intakes of high-fat dairy had a borderline association with increased odds of frailty, but other dairy food intakes showed no association in this study of healthy adults. Some dairy food intakes were modestly associated with follow-up gait speed. However, effect sizes were small, and the clinical importance of these associations remains undetermined.

Adaptive and Compensatory Mechanisms of the Cardiovascular System and Disease Risk Factors in Young Males and Females

Background:

Cardiovascular disease (CVD) is increasing dramatically in young people and is the leading cause of death worldwide.

Aims:

This study aimed to evaluate differences in the adaptive and compensatory mechanisms of the cardiovascular system (CVS) in young men and women to determine the most significant risk factors and assess the stability of the non-invasive method used in the early detection of CVD risk factors in young people.

Objectives:

Currently, early evaluation of CVD risk factors is possible only through invasive methods, such as the Framingham risk score and the SCORE chart. Therefore, the development of a more flexible and non-invasive method is crucial in large populations.

Methods:

A cohort cross-sectional investigation examined 173 volunteers, divided into two groups according to gender (n1 female=83, n2 male=90), and their heart rate, blood pressure (SBP/DBP), height, weight, and waist and hip circumference were non-invasively measured. Then, the potential adaptation value (R.M. Baevsky et al., 1987), Martinet test (MT), body mass index (BMI), and waist/hip ratio were calculated. Moreover, we collected information on lifestyle risk factors, including tobacco smoking, alcohol consumption, factors related to unhealthy diet, lack of physical activity, sleep deprivation, and anxiety, through special in-person interviews using paper/online questionnaires. The T-test and the x2 tests were applied for statistical analysis.

Results:

Impaired/pathological cardiovascular adaptation was observed in 11.54% of the female group and 46.07% of the male group. In the female group, cardiovascular recovery abnormalities were observed in the SBP, DBP, and HR MT in 20.59%, 16.18%, and 44.12%, respectively, whereas in the male group, 32.50%, 21.25% and 36.25%, respectively. Despite gender, these deviations were accompanied by the prevalence of sympathetic influences in the regulation of CVS functions in 72.73% of the first group and 69.66% of the second group. BMI was violated in 47.19% of males and 29.49% of females. The test results were identical to that in the invasive methods of assessment of CVD risk factors.

Conclusion:

Abnormalities in cardiovascular adaptation mechanisms in young women are less pronounced. Gender-dependent risk factors have high yields, such as obesity, low physical activity, and hypertension, which are more pronounced in men. The usability of the test requires further investigation on a larger sample.

Heritability of a resting heart rate in a 20-year follow-up family cohort with GWAS data: Insights from the STANISLAS cohort

BACKGROUND

The association between resting heart rate (HR) and cardiovascular outcomes, especially heart failure, is now well established. However, whether HR is mainly an integrated marker of risk associated with other features, or rather a genetic origin risk marker, is still a matter for debate. Previous studies reported a heritability ranging from 14% to 65%.

DESIGN

We assessed HR heritability in the STANISLAS family-study, based on the data of four visits performed over a 20-year period, and adjusted for most known confounding effects.

METHODS

These analyses were conducted using a linear mixed model, adjusted on age, sex, tea or coffee consumption, beta-blocker use, physical activity, tobacco use, and alcohol consumption to estimate the variance captured by additive genetic effects, via average information restricted maximum likelihood analysis, with both self-reported pedigree and genetic relatedness matrix (GRM) calculated from genome-wide association study data.

RESULTS

Based on the data of all visits, the HR heritability (h2) estimate was 23.2% with GRM and 24.5% with pedigree. However, we found a large heterogeneity of HR heritability estimations when restricting the analysis to each of the four visits (h2 from 19% to 39% using pedigree, and from 14% to 32% using GRM). Moreover, only a little part of variance was explained by the common household effect (<5%), and half of the variance remained unexplained.

CONCLUSION

Using a comprehensive analysis based on a family cohort, including the data of multiple visits and GRM, we found that HR variability is about 25% from genetic origin, 25% from repeated measures and 50% remains unexplained.

Multimodal Recruitment to Study Ovulation and Menstruation Health: Internet-Based Survey Pilot Study

BACKGROUND

Multimodal recruitment strategies are a novel way to increase diversity in research populations. However, these methods have not been previously applied to understanding the prevalence of menstrual disorders such as polycystic ovary syndrome.

OBJECTIVE

The purpose of this study was to test the feasibility of recruiting a diverse cohort to complete a web-based survey on ovulation and menstruation health.

METHODS

We conducted the Ovulation and Menstruation Health Pilot Study using a REDCap web-based survey platform. We recruited 200 women from a clinical population, a community fair, and the internet.

RESULTS

We recruited 438 women over 29 weeks between September 2017 and March 2018. After consent and eligibility determination, 345 enrolled, 278 started (clinic: n=43; community fair: n=61; internet: n=174), and 247 completed (clinic: n=28; community fair: n=60; internet: n=159) the survey. Among all participants, the median age was 25.0 (SD 6.0) years, mean BMI was 26.1 kg/m² (SD 6.6), 79.7% (216/271) had a college degree or higher, and 14.6% (37/254) reported a physician diagnosis of polycystic ovary syndrome. Race and ethnicity distributions were 64.7% (176/272) White, 11.8% (32/272) Black/African American, 7.7% (21/272) Latina/Hispanic, and 5.9% (16/272) Asian individuals; 9.9% (27/272) reported more than one race or ethnicity. The highest enrollment of Black/African American individuals was in clinic (17/42, 40.5%) compared to 1.6% (1/61) in the community fair and 8.3% (14/169) using the internet. Survey completion rates were highest among those who were recruited from the internet (159/174, 91.4%) and community fairs (60/61, 98.4%) compared to those recruited in clinic (28/43, 65.1%).

CONCLUSIONS

Multimodal recruitment achieved target recruitment in a short time period and established a racially diverse cohort to study ovulation and menstruation health. There were greater enrollment and completion rates among those recruited via the internet and community fair.

Quantitative and Qualitative Role of Antagonistic Heterogeneity in Genetics of Blood Lipids

Prevailing strategies in genome-wide association studies (GWAS) mostly rely on principles of medical genetics emphasizing one gene, one function, one phenotype concept. Here, we performed GWAS of blood lipids leveraging a new systemic concept emphasizing complexity of genetic predisposition to such phenotypes. We focused on total cholesterol, low- and high-density lipoprotein cholesterols, and triglycerides available for 29,902 individuals of European ancestry from seven independent studies, men and women combined. To implement the new concept, we leveraged the inherent heterogeneity in genetic predisposition to such complex phenotypes and emphasized a new counter intuitive phenomenon of antagonistic genetic heterogeneity, which is characterized by misalignment of the directions of genetic effects and the phenotype correlation. This analysis identified 37 loci associated with blood lipids but only one locus, FBXO33, was not reported in previous top GWAS. We, however, found strong effect of antagonistic heterogeneity that leaded to profound (quantitative and qualitative) changes in the associations with blood lipids in most, 25 of 37 or 68%, loci. These changes suggested new roles for some genes, which functions were considered as well established such as GCKR, SIK3 (APOA1 locus), LIPC, LIPG, among the others. The antagonistic heterogeneity highlighted a new class of genetic associations emphasizing beneficial and adverse trade-offs in predisposition to lipids. Our results argue that rigorous analyses dissecting heterogeneity in genetic predisposition to complex traits such as lipids beyond those implemented in current GWAS are required to facilitate translation of genetic discoveries into health care.

Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases

Epidemiological data support the view that both obesity and cardiovascular diseases (CVD) account for a high proportion of total morbidity and mortality in adults throughout the world. Obesity and CVD have complex interplay mechanisms of genetic and environmental factors, including diet. Nutrition is an environmental factor and it has a predominant and recognizable role in health management and in the prevention of obesity and obesity-related diseases, including CVD. However, there is a marked variation in CVD in patients with obesity and the same dietary pattern. The different genetic polymorphisms could explain this variation, which leads to the emergence of the concept of nutrigenetics. Nutritional genomics or nutrigenetics is the science that studies and characterizes gene variants associated with differential response to specific nutrients and relating this variation to various diseases, such as CVD related to obesity. Thus, the personalized nutrition recommendations, based on the knowledge of an individual's genetic background, might improve the outcomes of a specific dietary intervention and represent a new dietary approach to improve health, reducing obesity and CVD. Given these premises, it is intuitive to suppose that the elucidation of diet and gene interactions could support more specific and effective dietary interventions in both obesity and CVD prevention through personalized nutrition based on nutrigenetics. This review aims to briefly summarize the role of the most important genes associated with obesity and CVD and to clarify the knowledge about the relation between nutrition and gene expression and the role of the main nutrition-related genes in obesity and CVD.

Polygenic risk scores: pleiotropy and the effect of environment

Polygenic risk scores (PRSs) discriminate trait risks better than single genetic markers because they aggregate the effects of risk alleles from multiple genetic loci. Constructing pleiotropic PRSs and understanding heterogeneity, and the replication of PRS-trait associations can strengthen its applications. By using variational Bayesian multivariate high-dimensional regression, we constructed pleiotropic PRSs jointly associated with body mass index, systolic and diastolic blood pressure, total and high-density lipoprotein cholesterol in a sample of 18,108 Caucasians from three independent cohorts. We found that dissecting heterogeneity associated with birth year, which is a proxy of exogenous exposures, improved the replication of significant PRS-trait associations from 37.5% (6 of 16) in the entire sample to 90% (18 of 20) in the more homogeneous sample of individuals born before the year 1925. Our findings suggest that secular changes in exogenous exposures may substantially modify pleiotropic risk profiles affecting translation of genetic discoveries into health care.

Extended methods for gene-environment-wide interaction scans in studies of admixed individuals with varying degrees of relationships

The etiology of many complex diseases involves both environmental exposures and inherited genetic predisposition as well as interactions between them. Gene-environment-wide interaction studies (GEWIS) provide a means to identify the interactions between genetic variation and environmental exposures that underlie disease risk. However, current GEWIS methods lack the capability to adjust for the potentially complex correlations in studies with varying degrees of relationships (both known and unknown) among individuals in admixed populations. We developed novel generalized estimating equation (GEE) based methods-GEE-adaptive and GEE-joint-to account for phenotypic correlations due to kinship while accounting for covariates, including, measures of genome-wide ancestry. In simulation studies of admixed individuals, both methods controlled family-wise error rates, an advantage over the case-only approach. They demonstrated higher power than traditional case-control methods across a wide range of underlying alternative hypotheses, especially where both marginal and interaction effects were present. We applied the proposed method to conduct a GEWIS of a known sarcoidosis risk factor (insecticide exposure) and risk of sarcoidosis in African Americans and identified two novel loci with suggestive evidence of G × E interaction.

Causal effects of cardiovascular risk factors on onset of major age-related diseases: A time-to-event Mendelian randomization study

BACKGROUNDS

Elucidating the causal effects of common intermediate risk factors on the onset of age-related diseases is indispensable for developing prevention and intervention procedures.

METHODS

We conducted two-stage time-to-event Mendelian randomization meta-analyses combining five large-scale longitudinal cohorts to investigate dynamic causal effects of cardiovascular disease risk factors including body mass index (BMI), systolic blood pressure (SBP), and lipids on the age-at-onset of age-related diseases. We constructed weighted polygenic scores based on genetic markers from previously reported genome-wide association studies as instrumental variables to estimate the causal effects. To avoid false positive due to potential pleiotropic effects of the genetic markers, we performed a leave-one-out sensitivity analysis and an MR-Egger sensitivity analysis that we expanded in the survival context.

RESULTS

Our results show that elevated BMI increases the absolute risk of type 2 diabetes (T2D) (p=7.68e-04), heart failure (p=9.03e-03), and cardiovascular diseases (CVD) (p=1.69e-03) and the causal effects start at different ages. A significant association between BMI and the risk of stroke is observed; however, the sensitivity analyses suggest that the association is attributed to the potential pleiotropic effects of rs2867125 and rs1558902. Raised SBP levels are significantly associated with the development of atrial fibrillation (p=6.42e-03). Low-density lipoprotein cholesterol (LDL-C) levels are inversely associated with the age-at-onset of T2D (p=1.05e-02). In addition, LDL-C and triglycerides are inversely associated with the risks of cancer and T2D, respectively. Nevertheless, the sensitivity analyses suggest that these associations are probably due to pleiotropic effects of several single-nucleotide polymorphisms including rs4970834 and rs1260326.

CONCLUSIONS

Our results highlight the involvement of BMI in the development of multiple age-related diseases. Some observed causal associations can attribute to pleiotropic effects of some genetic variations. These findings have important implications in unraveling causal effects of common risk factors on age-related diseases and guiding effective intervention strategies to reduce the incidence of these diseases.

A genome-wide association study of red-blood cell fatty acids and ratios incorporating dietary covariates: Framingham Heart Study Offspring Cohort

Recent analyses have suggested a strong heritable component to circulating fatty acid (FA) levels; however, only a limited number of genes have been identified which associate with FA levels. In order to expand upon a previous genome wide association study done on participants in the Framingham Heart Study Offspring Cohort and FA levels, we used data from 2,400 of these individuals for whom red blood cell FA profiles, dietary information and genotypes are available, and then conducted a genome-wide evaluation of potential genetic variants associated with 22 FAs and 15 FA ratios, after adjusting for relevant dietary covariates. Our analysis found nine previously identified loci associated with FA levels (FADS, ELOVL2, PCOLCE2, LPCAT3, AGPAT4, NTAN1/PDXDC1, PKD2L1, HBS1L/MYB and RAB3GAP1/MCM6), while identifying four novel loci. The latter include an association between variants in CALN1 (Chromosome 7) and eicosapentaenoic acid (EPA), DHRS4L2 (Chromosome 14) and a FA ratio measuring delta-9-desaturase activity, as well as two loci associated with less well understood proteins. Thus, the inclusion of dietary covariates had a modest impact, helping to uncover four additional loci. While genome-wide association studies continue to uncover additional genes associated with circulating FA levels, much of the heritable risk is yet to be explained, suggesting the potential role of rare genetic variation, epistasis and gene-environment interactions on FA levels as well. Further studies are needed to continue to understand the complex genetic picture of FA metabolism and synthesis.

Strong impact of natural-selection-free heterogeneity in genetics of age-related phenotypes

A conceptual difficulty in genetics of age-related phenotypes that make individuals vulnerable to disease in post-reproductive life is genetic heterogeneity attributed to an undefined role of evolution in establishing their molecular mechanisms. Here, we performed univariate and pleiotropic genome-wide meta-analyses of 20 age-related phenotypes leveraging longitudinal information in a sample of 33,431 individuals and dealing with the natural-selection-free genetic heterogeneity. We identified 142 non-proxy single nucleotide polymorphisms (SNPs) with phenotype-specific (18 SNPs) and pleiotropic (124 SNPs) associations at genome-wide level. Univariate meta-analysis identified two novel (11.1%) and replicated 16 SNPs whereas pleiotropic meta-analysis identified 115 novel (92.7%) and nine replicated SNPs. Pleiotropic associations for most novel (93.9%) and all replicated SNPs were strongly impacted by the natural-selection-free genetic heterogeneity in its unconventional form of antagonistic heterogeneity, implying antagonistic directions of genetic effects for directly correlated phenotypes. Our results show that the common genome-wide approach is well adapted to handle homogeneous univariate associations within Mendelian framework whereas most associations with age-related phenotypes are more complex and well beyond that framework. Dissecting the natural-selection-free genetic heterogeneity is critical for gaining insights into genetics of age-related phenotypes and has substantial and unexplored yet potential for improving efficiency of genome-wide analysis.

Analyzing metabolomics data for association with genotypes using two-component Gaussian mixture distributions

Standard approaches to evaluate the impact of single nucleotide polymorphisms (SNP) on quantitative phenotypes use linear models. However, these normal-based approaches may not optimally model phenotypes which are better represented by Gaussian mixture distributions (e.g., some metabolomics data). We develop a likelihood ratio test on the mixing proportions of two-component Gaussian mixture distributions and consider more restrictive models to increase power in light of a priori biological knowledge. Data were simulated to validate the improved power of the likelihood ratio test and the restricted likelihood ratio test over a linear model and a log transformed linear model. Then, using real data from the Framingham Heart Study, we analyzed 20,315 SNPs on chromosome 11, demonstrating that the proposed likelihood ratio test identifies SNPs well known to participate in the desaturation of certain fatty acids. Our study both validates the approach of increasing power by using the likelihood ratio test that leverages Gaussian mixture models, and creates a model with improved sensitivity and interpretability.

Identification of polymorphisms in cancer patients that differentially affect survival with age

The World Health Organization predicts that the proportion of the world's population over 60 will almost double from 12% to 22% between 2015 and 2050. Ageing is the biggest risk factor for cancer, which is a leading cause of deaths worldwide. Unfortunately, research describing how genetic variants affect cancer progression commonly neglects to account for the ageing process. Herein is the first systematic analysis that combines a large longitudinal data set with a targeted candidate gene approach to examine the effect of genetic variation on survival as a function of age in cancer patients. Survival was significantly decreased in individuals with heterozygote or rare homozygote (i.e. variant) genotypes compared to those with a common homozygote genotype (i.e. wild type) for two single nucleotide polymorphisms (rs11574358 and rs4147918), one gene (SIRT3) and one pathway (FoxO signalling) in an age-dependent manner. All identified genes and pathways have previously been associated with ageing and cancer. These observations demonstrate that there are ageing-related genetic elements that differentially affect mortality in cancer patients in an age-dependent manner. Understanding the genetic determinants affecting prognosis differently with age will be invaluable to develop age-specific prognostic biomarkers and personalized therapies that may improve clinical outcomes for older individuals.

Genome-Wide Interaction Study of Omega-3 PUFAs and Other Fatty Acids on Inflammatory Biomarkers of Cardiovascular Health in the Framingham Heart Study

Numerous genetic loci have been identified as being associated with circulating fatty acid (FA) levels and/or inflammatory biomarkers of cardiovascular health (e.g., C-reactive protein). Recently, using red blood cell (RBC) FA data from the Framingham Offspring Study, we conducted a genome-wide association study of over 2.5 million single nucleotide polymorphisms (SNPs) and 22 RBC FAs (and associated ratios), including the four Omega-3 FAs (ALA, DHA, DPA, and EPA). Our analyses identified numerous causal loci. In this manuscript, we investigate the extent to which polyunsaturated fatty acid (PUFA) levels moderate the relationship of genetics to cardiovascular health biomarkers using a genome-wide interaction study approach. In particular, we test for possible gene–FA interactions on 9 inflammatory biomarkers, with 2.5 million SNPs and 12 FAs, including all Omega-3 PUFAs. We identified eighteen novel loci, including loci which demonstrate strong evidence of modifying the impact of heritable genetics on biomarker levels, and subsequently cardiovascular health. The identified genes provide increased clarity on the biological functioning and role of Omega-3 PUFAs, as well as other common fatty acids, in cardiovascular health, and suggest numerous candidate loci for future replication and biological characterization.

Invited Commentary: The Framingham Offspring Study-A Pioneering Investigation Into Familial Aggregation of Cardiovascular Risk

Launched in 1948, the Framingham Heart Study was a seminal prospective cohort study of 5,209 adult residents of Framingham, Massachusetts, that was designed to uncover the determinants and natural history of coronary heart disease. Data from this original cohort established the cardiac threat posed by high blood pressure, high cholesterol, smoking, obesity, physical inactivity, diabetes, and other factors. In the late 1960s, investigators conceived the innovative idea of assembling a second cohort that comprised the adult children of the original study population (and these children's spouses). From 1971 to 1975, a total of 5,124 individuals were recruited to form the Offspring Cohort. Studying successive generations in this fashion provided an efficient method for examining secular trends in cardiovascular disease and its risk factors, as well as an opportunity to assess familial aggregation of risk without the threat of recall bias. In a paper published in the September 1979 issue of the Journal, then study director William Kannel et al. (Am J Epidemiol. 1979;110(3):281-290) described the sampling design of the Offspring Study and presented selected baseline characteristics of the cohort. The scientific questions addressed by this research provided the impetus for a decades-long effort-still in full force today both within the Framingham Study itself and in the broader cardiovascular epidemiologic community-to quantify the independent and synergistic effects of genetic, lifestyle, and other environmental factors on cardiovascular outcomes.

Body mass index change in gastrointestinal cancer and chronic obstructive pulmonary disease is associated with Dedicator of Cytokinesis 1

BACKGROUND

There have been a number of candidate gene association studies of cancer cachexia-related traits, but no genome-wide association study (GWAS) has been published to date. Cachexia presents in patients with a number of complex traits, including both cancer and COPD. The objective of the current investigation was to search for a shared genetic aetiology for change in body mass index (ΔBMI) among cancer and COPD by using GWAS data in the Framingham Heart Study.

METHODS

A linear mixed effects model accounting for age, sex, and change in smoking status was used to calculate ΔBMI in participants over 40 years of age with three consecutive BMI time points (n = 4162). Four GWAS of ΔBMI using generalized estimating equations were performed among 1085 participants with a cancer diagnosis, 204 with gastrointestinal (GI) cancer, 112 with lung cancer, and 237 with COPD to test for association with 418 365 single-nucleotide polymorphisms (SNPs).

RESULTS

Two SNPs reached a level of genome-wide significance (P < 5 × 10^-8 ) with ΔBMI: (i) rs41526344 within the CNTN4 gene, among COPD cases (β = 0.13, P = 4.3 × 10^-8 ); and (ii) rs4751240 in the gene Dedicator of Cytokinesis 1 (DOCK1) among GI cancer cases (β = 0.10, P = 1.9 × 10^-8 ). The DOCK1 SNP association replicated in the ΔBMI GWAS among COPD cases (β_meta-analyis  = 0.10, P_meta-analyis  = 9.3 × 10^-10 ). The DOCK1 gene codes for the dedicator of cytokinesis 1 protein, which has a role in myoblast fusion.

CONCLUSIONS

In sum, one statistically significant common variant in the DOCK1 gene was associated with ΔBMI in GI cancer and COPD cases providing support for at least partially shared aetiology of ΔBMI in complex diseases.

Structured mating: Patterns and implications

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10^-22) and also for PC2 (r = 0.80, P = 7x10^-29). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10^-28) and for PC2 (r = 0.45, P = 2x10^-39). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account.

We analyzed three generations of whites from the Framingham Heart Study (FHS) using genome-wide genotype data to characterize their genetic ancestry. By examination of spouse-pairs, we observed that individuals of Northern/Western European, Southern European and Ashkenazi ancestry preferentially chose spouses of the same ancestry, however, the degree of endogamy decreased in each successive generation, especially between Northern/Western and Southern Europeans. We then showed that the mating pattern results in Hardy-Weinberg disequilibrium (HWD) at ancestrally-informative SNPs, and also results in linkage disequilibrium (LD) between unlinked loci. The HWD and LD decrease as theoretically expected with the decrease in endogamy noted in each generation. In the FHS sample, spouse genetic similarity can be explained by ancestry-related assortative mating.

Pleiotropic Associations of Allelic Variants in a 2q22 Region with Risks of Major Human Diseases and Mortality

Gaining insights into genetic predisposition to age-related diseases and lifespan is a challenging task complicated by the elusive role of evolution in these phenotypes. To gain more insights, we combined methods of genome-wide and candidate-gene studies. Genome-wide scan in the Atherosclerosis Risk in Communities (ARIC) Study (N = 9,573) was used to pre-select promising loci. Candidate-gene methods were used to comprehensively analyze associations of novel uncommon variants in Caucasians (minor allele frequency~2.5%) located in band 2q22.3 with risks of coronary heart disease (CHD), heart failure (HF), stroke, diabetes, cancer, neurodegenerative diseases (ND), and mortality in the ARIC study, the Framingham Heart Study (N = 4,434), and the Health and Retirement Study (N = 9,676). We leveraged the analyses of pleiotropy, age-related heterogeneity, and causal inferences. Meta-analysis of the results from these comprehensive analyses shows that the minor allele increases risks of death by about 50% (p = 4.6×10⁻⁹), CHD by 35% (p = 8.9×10⁻⁶), HF by 55% (p = 9.7×10⁻⁵), stroke by 25% (p = 4.0×10⁻²), and ND by 100% (p = 1.3×10⁻³). This allele also significantly influences each of two diseases, diabetes and cancer, in antagonistic fashion in different populations. Combined significance of the pleiotropic effects was p = 6.6×10⁻²¹. Causal mediation analyses show that endophenotypes explained only small fractions of these effects. This locus harbors an evolutionary conserved gene-desert region with non-coding intergenic sequences likely involved in regulation of protein-coding flanking genes ZEB2 and ACVR2A. This region is intensively studied for mutations causing severe developmental/genetic disorders. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Biomedical research and medical care are traditionally focused on individual health conditions in order to postpone, ameliorate, or prevent the accumulation of morbidities in late life. An attractive idea is to find factors, which could reduce burden of not just one disease but a major subset of them to efficiently extend healthy lifespan. Here we focus on the analyses of genetic predisposition to risks of major human age-related diseases and mortality. The analyses highlight a locus in band 2q22.3 associated with risks of coronary heart disease, heart failure, stroke, diabetes, cancer, neurodegenerative diseases, and death. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Pleiotropic Meta-Analyses of Longitudinal Studies Discover Novel Genetic Variants Associated with Age-Related Diseases

Age-related diseases may result from shared biological mechanisms in intrinsic processes of aging. Genetic effects on age-related diseases are often modulated by environmental factors due to their little contribution to fitness or are mediated through certain endophenotypes. Identification of genetic variants with pleiotropic effects on both common complex diseases and endophenotypes may reveal potential conflicting evolutionary pressures and deliver new insights into shared genetic contribution to healthspan and lifespan. Here, we performed pleiotropic meta-analyses of genetic variants using five NIH-funded datasets by integrating univariate summary statistics for age-related diseases and endophenotypes. We investigated three groups of traits: (1) endophenotypes such as blood glucose, blood pressure, lipids, hematocrit, and body mass index, (2) time-to-event outcomes such as the age-at-onset of diabetes mellitus (DM), cancer, cardiovascular diseases (CVDs) and neurodegenerative diseases (NDs), and (3) both combined. In addition to replicating previous findings, we identify seven novel genome-wide significant loci (< 5e-08), out of which five are low-frequency variants. Specifically, from Group 2, we find rs7632505 on 3q21.1 in SEMA5B, rs460976 on 21q22.3 (1 kb from TMPRSS2) and rs12420422 on 11q24.1 predominantly associated with a variety of CVDs, rs4905014 in ITPK1 associated with stroke and heart failure, rs7081476 on 10p12.1 in ANKRD26 associated with multiple diseases including DM, CVDs, and NDs. From Group 3, we find rs8082812 on 18p11.22 and rs1869717 on 4q31.3 associated with both endophenotypes and CVDs. Our follow-up analyses show that rs7632505, rs4905014, and rs8082812 have age-dependent effects on coronary heart disease or stroke. Functional annotation suggests that most of these SNPs are within regulatory regions or DNase clusters and in linkage disequilibrium with expression quantitative trait loci, implying their potential regulatory influence on the expression of nearby genes. Our mediation analyses suggest that the effects of some SNPs are mediated by specific endophenotypes. In conclusion, these findings indicate that loci with pleiotropic effects on age-related disorders tend to be enriched in genes involved in underlying mechanisms potentially related to nervous, cardiovascular and immune system functions, stress resistance, inflammation, ion channels and hematopoiesis, supporting the hypothesis of shared pathological role of infection, and inflammation in chronic age-related diseases.

Coordinated Action of Biological Processes during Embryogenesis Can Cause Genome-Wide Linkage Disequilibrium in the Human Genome and Influence Age-Related Phenotypes

A role of non-Mendelian inheritance in genetics of complex, age-related traits is becoming increasingly recognized. Recently, we reported on two inheritable clusters of SNPs in extensive genome-wide linkage disequilibrium (LD) in the Framingham Heart Study (FHS), which were associated with the phenotype of premature death. Here we address biologically-related properties of these two clusters. These clusters have been unlikely selected randomly because they are functionally and structurally different from matched sets of randomly selected SNPs. For example, SNPs in LD from each cluster are highly significantly enriched in genes (p=7.1×10-22 and p=5.8×10-18), in general, and in short genes (p=1.4×10-47 and p=4.6×10-7), in particular. Mapping of SNPs in LD to genes resulted in two, partly overlapping, networks of 1764 and 4806 genes. Both these networks were gene enriched in developmental processes and in biological processes tightly linked with development including biological adhesion, cellular component organization, locomotion, localization, signaling, (p<10-4, q<10-4 for each category). Thorough analysis suggests connections of these genetic networks with different stages of embryogenesis and highlights biological interlink of specific processes enriched for genes from these networks. The results suggest that coordinated action of biological processes during embryogenesis may generate genome-wide networks of genetic variants, which may influence complex age-related phenotypes characterizing health span and lifespan.

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG)

Association studies have shown and continue to show a substantial amount of success in identifying links between multiple single nucleotide polymorphisms (SNPs) and phenotypes. These studies are also believed to provide insights toward identification of new drug targets and therapies. Albeit of all the success, challenges still remain for applying and prioritizing these associations based on available biological knowledge. Along with single variant association analysis, genetic interactions also play an important role in uncovering the etiology and progression of complex traits. For gene-gene interaction analysis, selection of the variants to test for associations still poses a challenge in identifying epistatic interactions among the large list of variants available in high-throughput, genome-wide datasets. Therefore in this study, we propose a pipeline to identify interactions among genetic variants that are associated with multiple phenotypes by prioritizing previously published results from main effect association analysis (genome-wide and phenome-wide association analysis) based on a-priori biological knowledge in AIDS Clinical Trials Group (ACTG) data. We approached the prioritization and filtration of variants by using the results of a previously published single variant PheWAS and then utilizing biological information from the Roadmap Epigenome project. We removed variants in low functional activity regions based on chromatin states annotation and then conducted an exhaustive pairwise interaction search using linear regression analysis. We performed this analysis in two independent pre-treatment clinical trial datasets from ACTG to allow for both discovery and replication. Using a regression framework, we observed 50,798 associations that replicate at p-value 0.01 for 26 phenotypes, among which 2,176 associations for 212 unique SNPs for fasting blood glucose phenotype reach Bonferroni significance and an additional 9,970 interactions for high-density lipoprotein (HDL) phenotype and fasting blood glucose (total of 12,146 associations) reach FDR significance. We conclude that this method of prioritizing variants to look for epistatic interactions can be used extensively for generating hypotheses for genomewide and phenome-wide interaction analyses. This original Phenome-wide Interaction study (PheWIS) can be applied further to patients enrolled in randomized clinical trials to establish the relationship between patient's response to a particular drug therapy and non-linear combination of variants that might be affecting the outcome.

Limitations of GCTA as a solution to the missing heritability problem

Genome-wide association studies (GWASs) seek to understand the relationship between complex phenotype(s) (e.g., height) and up to millions of single-nucleotide polymorphisms (SNPs). Early analyses of GWASs are commonly believed to have "missed" much of the additive genetic variance estimated from correlations between relatives. A more recent method, genome-wide complex trait analysis (GCTA), obtains much higher estimates of heritability using a model of random SNP effects correlated between genotypically similar individuals. GCTA has now been applied to many phenotypes from schizophrenia to scholastic achievement. However, recent studies question GCTA's estimates of heritability. Here, we show that GCTA applied to current SNP data cannot produce reliable or stable estimates of heritability. We show first that GCTA depends sensitively on all singular values of a high-dimensional genetic relatedness matrix (GRM). When the assumptions in GCTA are satisfied exactly, we show that the heritability estimates produced by GCTA will be biased and the standard errors will likely be inaccurate. When the population is stratified, we find that GRMs typically have highly skewed singular values, and we prove that the many small singular values cannot be estimated reliably. Hence, GWAS data are necessarily overfit by GCTA which, as a result, produces high estimates of heritability. We also show that GCTA's heritability estimates are sensitive to the chosen sample and to measurement errors in the phenotype. We illustrate our results using the Framingham dataset. Our analysis suggests that results obtained using GCTA, and the results' qualitative interpretations, should be interpreted with great caution.

Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care.

Assessment of whole-genome regression for type II diabetes

Lifestyle and genetic factors play a large role in the development of Type 2 Diabetes (T2D). Despite the important role of genetic factors, genetic information is not incorporated into the clinical assessment of T2D risk. We assessed and compared Whole Genome Regression methods to predict the T2D status of 5,245 subjects from the Framingham Heart Study. For evaluating each method we constructed the following set of regression models: A clinical baseline model (CBM) which included non-genetic covariates only. CBM was extended by adding the first two marker-derived principal components and 65 SNPs identified by a recent GWAS consortium for T2D (M-65SNPs). Subsequently, it was further extended by adding 249,798 genome-wide SNPs from a high-density array. The Bayesian models used to incorporate genome-wide marker information as predictors were: Bayes A, Bayes Cπ, Bayesian LASSO (BL), and the Genomic Best Linear Unbiased Prediction (G-BLUP). Results included estimates of the genetic variance and heritability, genetic scores for T2D, and predictive ability evaluated in a 10-fold cross-validation. The predictive AUC estimates for CBM and M-65SNPs were: 0.668 and 0.684, respectively. We found evidence of contribution of genetic effects in T2D, as reflected in the genomic heritability estimates (0.492±0.066). The highest predictive AUC among the genome-wide marker Bayesian models was 0.681 for the Bayesian LASSO. Overall, the improvement in predictive ability was moderate and did not differ greatly among models that included genetic information. Approximately 58% of the total number of genetic variants was found to contribute to the overall genetic variation, indicating a complex genetic architecture for T2D. Our results suggest that the Bayes Cπ and the G-BLUP models with a large set of genome-wide markers could be used for predicting risk to T2D, as an alternative to using high-density arrays when selected markers from large consortiums for a given complex trait or disease are unavailable.

A genome-wide association study of saturated, mono- and polyunsaturated red blood cell fatty acids in the Framingham Heart Offspring Study

Most genome-wide association studies have explored relationships between genetic variants and plasma phospholipid fatty acid proportions, but few have examined apparent genetic influences on the membrane fatty acid profile of red blood cells (RBC). Using RBC fatty acid data from the Framingham Offspring Study, we analyzed over 2.5 million single nucleotide polymorphisms (SNPs) for association with 14 RBC fatty acids identifying 191 different SNPs associated with at least 1 fatty acid. Significant associations (p<1×10(-8)) were located within five distinct 1MB regions. Of particular interest were novel associations between (1) arachidonic acid and PCOLCE2 (regulates apoA-I maturation and modulates apoA-I levels), and (2) oleic and linoleic acid and LPCAT3 (mediates the transfer of fatty acids between glycerolipids). We also replicated previously identified strong associations between SNPs in the FADS (chromosome 11) and ELOVL (chromosome 6) regions. Multiple SNPs explained 8-14% of the variation in 3 high abundance (>11%) fatty acids, but only 1-3% in 4 low abundance (<3%) fatty acids, with the notable exception of dihomo-gamma linolenic acid with 53% of variance explained by SNPs. Further studies are needed to determine the extent to which variations in these genes influence tissue fatty acid content and pathways modulated by fatty acids.

Integrated allelic, transcriptional, and phenomic dissection of the cardiac effects of titin truncations in health and disease

The recent discovery of heterozygous human mutations that truncate full-length titin (TTN, an abundant structural, sensory, and signaling filament in muscle) as a common cause of end-stage dilated cardiomyopathy (DCM) promises new prospects for improving heart failure management. However, realization of this opportunity has been hindered by the burden of TTN-truncating variants (TTNtv) in the general population and uncertainty about their consequences in health or disease. To elucidate the effects of TTNtv, we coupled TTN gene sequencing with cardiac phenotyping in 5267 individuals across the spectrum of cardiac physiology and integrated these data with RNA and protein analyses of human heart tissues. We report diversity of TTN isoform expression in the heart, define the relative inclusion of TTN exons in different isoforms (using the TTN transcript annotations available at http://cardiodb.org/titin), and demonstrate that these data, coupled with the position of the TTNtv, provide a robust strategy to discriminate pathogenic from benign TTNtv. We show that TTNtv is the most common genetic cause of DCM in ambulant patients in the community, identify clinically important manifestations of TTNtv-positive DCM, and define the penetrance and outcomes of TTNtv in the general population. By integrating genetic, transcriptome, and protein analyses, we provide evidence for a length-dependent mechanism of disease. These data inform diagnostic criteria and management strategies for TTNtv-positive DCM patients and for TTNtv that are identified as incidental findings.

Evidence for cost-effectiveness of lifestyle primary preventions for cardiovascular disease in the Asia-Pacific Region: a systematic review

Background

Countries of the Asia Pacific region account for a major share of the global burden of disease due to cardiovascular disease (CVD) and this burden is rising over time. Modifiable behavioural risk factors for CVD are considered a key target for reduction in incidence but their effectiveness and cost-effectiveness tend to depend on country context. However, no systematic assessment of cost-effectiveness of interventions addressing behavioural risk factors in the region exists.

Methods

A systematic review of the published literature on cost-effectiveness of interventions targeting modifiable behavioural risk factors for CVD was undertaken. Inclusion criteria were (a) countries in Asia and the Pacific, (b) studies that had conducted economic evaluations of interventions (c) published papers in major economic and public health databases and (d) a comprehensive list of search words to identify appropriate articles. All authors independently examined the final list of articles relating to methodology and findings.

Results

Under our inclusion criteria a total of 28 studies, with baseline years ranging from 1990 to 2012, were included in the review, 19 conducted in high-income countries of the region. Reviewed studies assessed cost-effectiveness of interventions for tobacco control, alcohol reduction, salt intake control, physical activity and dietary interventions. The majority of cost-effectiveness analyses were simulation analyses mostly relying on developed country data, and only 6 studies used effectiveness data from RCTs in the region. Other than for Australia, no direct conclusions could be drawn about cost-effectiveness of interventions targeting behavioural risk factors due to the small number of studies, interventions that varied widely in design, and varied methods for measurement of costs associated with interventions.

Conclusions

Good quality cost-effectiveness information on interventions targeting behavioural interventions for the Asia-Pacific region remains a major gap in the literature.

Electronic supplementary material

The online version of this article (doi:10.1186/s12992-014-0079-3) contains supplementary material, which is available to authorized users.

SeqSIMLA2: simulating correlated quantitative traits accounting for shared environmental effects in user-specified pedigree structure

Simulation tools that simulate sequence data in unrelated cases and controls or in families with quantitative traits or disease status are important for genetic studies. The simulation tools can be used to evaluate the statistical power for detecting the causal variants when planning a genetic epidemiology study, or to evaluate the statistical properties for new methods. We previously developed SeqSIMLA version 1 (SeqSIMLA1), which simulates family or case-control data with a disease or quantitative trait model. SeqSIMLA1, and several other tools that simulate quantitative traits, do not specifically model the shared environmental effects among relatives on a trait. However, shared environmental effects are commonly observed for some traits in families, such as body mass index. SeqSIMLA1 simulates a fixed three-generation family structure. However, it would be ideal to simulate prespecified pedigree structures for studies involving large pedigrees. Thus, we extended SeqSIMLA1 to create SeqSIMLA2, which can simulate correlated traits and considers the shared environmental effects. SeqSIMLA2 can also simulate prespecified large pedigree structures. There are no restrictions on the number of individuals that can be simulated in a pedigree. We used a blood pressure example to demonstrate that SeqSIMLA2 can simulate realistic correlation structures between the systolic and diastolic blood pressure among relatives. We also showed that SeqSIMLA2 can simulate large pedigrees with large chromosomal regions in a reasonable time frame.

Large scale analysis of phenotype-pathway relationships based on GWAS results

The widely used pathway-based approach for interpreting Genome Wide Association Studies (GWAS), assumes that since function is executed through the interactions of multiple genes, different perturbations of the same pathway would result in a similar phenotype. This assumption, however, was not systemically assessed on a large scale. To determine whether SNPs associated with a given complex phenotype affect the same pathways more than expected by chance, we analyzed 368 phenotypes that were studied in >5000 GWAS. We found 216 significant phenotype-pathway associations between 70 of the phenotypes we analyzed and known pathways. We also report 391 strong phenotype-phenotype associations between phenotypes that are affected by the same pathways. While some of these associations confirm previously reported connections, others are new and could shed light on the molecular basis of these diseases. Our findings confirm that phenotype-associated SNPs cluster into pathways much more than expected by chance. However, this is true for <20% (70/368) of the phenotypes. Different types of phenotypes show markedly different tendencies: Virtually all autoimmune phenotypes show strong clustering of SNPs into pathways, while most cancers and metabolic conditions, and all electrophysiological phenotypes, could not be significantly associated with any pathway despite being significantly associated with a large number of SNPs. While this may be due to missing data, it may also suggest that these phenotypes could result only from perturbations of specific genes and not from other perturbations of the same pathway. Further analysis of pathway-associated versus gene-associated phenotypes is, therefore, needed in order to understand disease etiology and in order to promote better drug target selection.

Screening strategies for cardiovascular disease in asymptomatic adults

The purpose of this article is to update the primary care community on the evidence and guidelines for cardiovascular disease screening in a general-risk adult population, with the goal of assisting clinicians in developing an evidence-based approach toward screening. This article discusses global risk assessment and screening strategies, including blood pressure, lipids, C-reactive protein, homocysteine, coronary artery calcium score, carotid intima-media thickness, ultrasound of the abdominal aorta, and electrocardiography.

Efficient generalized least squares method for mixed population and family-based samples in genome-wide association studies

Genome-wide association studies (GWAS) that draw samples from multiple studies with a mixture of relationship structures are becoming more common. Analytical methods exist for using mixed-sample data, but few methods have been proposed for the analysis of genotype-by-environment (G×E) interactions. Using GWAS data from a study of sarcoidosis susceptibility genes in related and unrelated African Americans, we explored the current analytic options for genotype association testing in studies using both unrelated and family-based designs. We propose a novel method-generalized least squares (GLX)-to estimate both SNP and G×E interaction effects for categorical environmental covariates and compared this method to generalized estimating equations (GEE), logistic regression, the Cochran-Armitage trend test, and the WQLS and MQLS methods. We used simulation to demonstrate that the GLX method reduces type I error under a variety of pedigree structures. We also demonstrate its superior power to detect SNP effects while offering computational advantages and comparable power to detect G×E interactions versus GEE. Using this method, we found two novel SNPs that demonstrate a significant genome-wide interaction with insecticide exposure-rs10499003 and rs7745248, located in the intronic and 3' UTR regions of the FUT9 gene on chromosome 6q16.1.

Age, gender, and cancer but not neurodegenerative and cardiovascular diseases strongly modulate systemic effect of the Apolipoprotein E4 allele on lifespan

Enduring interest in the Apolipoprotein E (ApoE) polymorphism is ensured by its evolutionary-driven uniqueness in humans and its prominent role in geriatrics and gerontology. We use large samples of longitudinally followed populations from the Framingham Heart Study (FHS) original and offspring cohorts and the Long Life Family Study (LLFS) to investigate gender-specific effects of the ApoE4 allele on human survival in a wide range of ages from midlife to extreme old ages, and the sensitivity of these effects to cardiovascular disease (CVD), cancer, and neurodegenerative disorders (ND). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in all these populations. A highly significant adverse effect of the e4 allele is limited to women with moderate lifespan of about 70 to 95 years in two FHS cohorts and the LLFS with relative risk of death RR = 1.48 (p = 3.6×10⁻⁶) in the FHS cohorts. Major human diseases including CVD, ND, and cancer, whose risks can be sensitive to the e4 allele, do not mediate the association of this allele with lifespan in large FHS samples. Non-skin cancer non-additively increases mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers with cancer two-fold compared to the non-e4 carriers, i.e., RR = 2.07 (p = 5.0×10⁻⁷). The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample that increases the risk of death of the ApoE4 carriers by 150% (p = 5.3×10⁻⁸) compared to the non-carriers. This risk explains the 4.2 year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample. The analyses suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms.

Discovering genetic origins of healthspan and lifespan could lead to breakthroughs in increasing the years of healthy and long life. In this paper we characterize the association of the e4 allele of the well-studied ApoE gene with lifespan in two generations of participants of large longitudinal studies, the Framingham Heart Study and the Long Life Family Study, and investigate the role of major human diseases such as cardiovascular disease, cancer, and neurodegenerative disorders in this association. This wide range of systemic analyses is possible given the large sample with directly genotyped ApoE polymorphism available from these studies (N = 9841, with 2557 deaths). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in these populations. However, the strongly adverse effect of the e4 allele is not observed for all women, but only for those 70 to 95 years old. Cardiovascular disease, cancer, and neurodegenerative disorders do not mediate the association of the e4 allele with lifespan. However, cancer, but not cardiovascular and neurodegenerative diseases, non-additively enhances this effect resulting in 4.2 years of difference in mean lifespan for the e4 allele carriers compared to the non-carriers.

A systems analysis of age-related changes in some cardiac aging traits

Aging process or senescence affects the expression of a wide range of phenotypic traits throughout the life span of organisms. These traits often show modular, synergistic, and even antagonistic relationships, and are also influenced by genomic, developmental, physiological and environmental factors. The cardiovascular system (CVS) in humans represents a major modular system in which the relationships among physiological, anatomical and morphological traits undergo continuous remodeling throughout the life span of an individual. Here we extend the concept of developmental plasticity in order to study the relationships among 14 traits measured on 3,412 individuals from the Framingham Heart Study cohort, relative to age and gender, using exploratory structural equation modeling-a form of systems analysis. Our results reveal differing patterns of association among cardiac traits in younger and older persons in both sexes, indicating that physiological and developmental factors may be channeled differentially in relation to age and gender during the remodeling process. We suggest that systems approaches are necessary in order to understand the coordinated functional relationships among traits of the CVS over the life course of individuals.

Trade-off in the effect of the APOE gene on the ages at onset of cardiocascular disease and cancer across ages, gender, and human generations

Decades of studies of candidate genes show their complex role in aging-related traits. We focus on apolipoprotein E e2/3/4 polymorphism and ages at onset of cardiovascular diseases (CVD) and cancer in the parental and offspring generations of the Framingham Heart Study participants to gain insights on the role of age and gender across generations in genetic trade-offs. The analyses show that the apolipoprotein E e4 allele carriers live longer lives without cancer than the non-e4 allele carriers in each generation. The role of the e4 allele in onset of CVD is age- and generation-specific, constituting two modes of sexually dimorphic genetic trade-offs. In offspring, the e4 allele confers risk of CVD primarily in women and can protect against cancer primarily in men of the same age. In the parental generation, genetic trade-off is seen in different age groups, with a protective role of the e4 allele against cancer in older men and its detrimental role in CVD in younger women. The puzzling complexity of genetic mechanisms working in different genders, ages, and environments calls for more detail and systemic analyses beyond those adapted in current large-scale genetic association studies.

Inter-chromosomal level of genome organization and longevity-related phenotypes in humans

Studies focusing on unraveling the genetic origin of health span in humans assume that polygenic, aging-related phenotypes are inherited through Mendelian mechanisms of inheritance of individual genes. We use the Framingham Heart Study (FHS) data to examine whether non-Mendelian mechanisms of inheritance can drive linkage of loci on non-homologous chromosomes and whether such mechanisms can be relevant to longevity-related phenotypes. We report on genome-wide inter-chromosomal linkage disequilibrium (LD) and on chromosome-wide intra-chromosomal LD and show that these are real phenomena in the FHS data. Genetic analysis of inheritance in families based on Mendelian segregation reveals that the alleles of single nucleotide polymorphisms (SNPs) in LD at loci on non-homologous chromosomes are inherited as a complex resembling haplotypes of a genetic unit. This result implies that the inter-chromosomal LD is likely caused by non-random assortment of non-homologous chromosomes during meiosis. The risk allele haplotypes can be subject to dominant-negative selection primary through the mechanisms of non-Mendelian inheritance. They can go to extinction within two human generations. The set of SNPs in inter-chromosomal LD (N=68) is nearly threefold enriched, with high significance (p=1.6 × 10(-9)), on non-synonymous coding variants (N=28) compared to the entire qualified set of the studied SNPs. Genes for the tightly linked SNPs are involved in fundamental biological processes in an organism. Survival analyses show that the revealed non-genetic linkage is associated with heritable complex phenotype of premature death. Our results suggest the presence of inter-chromosomal level of functional organization in the human genome and highlight a challenging problem of genomics of human health and aging.

Genomics of human health and aging

Despite notable progress of the candidate-gene and genome-wide association studies (GWAS), understanding the role of genes contributing to human health and lifespan is still very limited. We use the Framingham Heart Study to elucidate if recognizing the role of evolution and systemic processes in an aging organism could advance such studies. We combine throughput methods of GWAS with more detail methods typical for candidate-gene analyses and show that both lifespan and ages at onset of CVD and cancer can be controlled by the same allelic variants. The risk allele carriers are at highly significant risk of premature death (e.g., RR=2.9, p=5.0 × 10(-66)), onset of CVD (e.g., RR=1.6, p=4.6 × 10(-17)), and onset of cancer (e.g., RR=1.6, p=1.5 × 10(-6)). The mechanism mediating the revealed genetic associations is likely associated with biological aging. These aging-related phenotypes are associated with a complex network which includes, in this study, 62 correlated SNPs even so these SNPs can be on non-homologous chromosomes. A striking result is three-fold, highly significant (p=3.6 × 10(-10)) enrichment of non-synonymous SNPs (N=27) in this network compared to the entire qualified set of the studied SNPs. Functional significance of this network is strengthened by involvement of genes for these SNPs in fundamental biological processes related to aging (e.g., response to stimuli, protein degradation, apoptosis) and by connections of these genes with neurological (20 genes) and cardio-vascular (nine genes) processes and tumorigenesis (10 genes). These results document challenging role of gene networks in regulating human health and aging and call for broadening focus on genomics of such phenotypes.

The role of lipid-related genes, aging-related processes, and environment in healthspan

The inherent complexity of aging-related traits can temper progress in unraveling the genetic origins of healthspan. We focus on two generations in the Framingham Heart Study, the original (FHS) and offspring (FHSO) cohorts, to determine whether aging-related processes in changing environments can substantially impact the role of lipid-related genes discovered in candidate gene (the apolipoprotein E (APOE) e2/3/4 polymorphism) and genome-wide (the APOB rs1042034 (C/T)) studies, in regulation of total cholesterol (TC) and onset of cardiovascular disease (CVD). We demonstrate that the APOE e4 allele and APOB CC genotype can play detrimental, neutral, and protective sex-specific roles in the etiology of CVD at different ages and in different environments. We document antagonistic roles for the e4 allele in the onset of CVD characterized by detrimental effects at younger ages (RR≤ 75 years = 1.49, P = 7.5 × 10(-4) ) and protective effects at older ages (RR76+years = 0.77, P = 0.044) for FHS participants. We found that disregarding the role of aging erroneously nullifies the significant effects of the e4 allele in this sample (RR = 0.92, P = 0.387). The leading biogenetic pathways mediating genetic effects on CVD may be more relevant to lipid metabolism for APOB than APOE. Aging-related processes can modulate the strength of genetic associations with TC in the same individuals at different chronological ages. We found substantial differences in the effects of the same APOE and APOB alleles on CVD and TC across generations. The results suggest that aging-related processes in changing environments may play key roles in the genetics of healthspan. Detailed systemic integrative analyses may substantially advance the progress.

Burden of rare sarcomere gene variants in the Framingham and Jackson Heart Study cohorts

Rare sarcomere protein variants cause dominant hypertrophic and dilated cardiomyopathies. To evaluate whether allelic variants in eight sarcomere genes are associated with cardiac morphology and function in the community, we sequenced 3,600 individuals from the Framingham Heart Study (FHS) and Jackson Heart Study (JHS) cohorts. Out of the total, 11.2% of individuals had one or more rare nonsynonymous sarcomere variants. The prevalence of likely pathogenic sarcomere variants was 0.6%, twice the previous estimates; however, only four of the 22 individuals had clinical manifestations of hypertrophic cardiomyopathy. Rare sarcomere variants were associated with an increased risk for adverse cardiovascular events (hazard ratio: 2.3) in the FHS cohort, suggesting that cardiovascular risk assessment in the general population can benefit from rare variant analysis.

The multi-faceted outcomes of conjunct diabetes and cardiovascular familial history in type 2 diabetes

BACKGROUND

Familial history of early-onset CHD (EOCHD) is a major risk factor for CHD. Familial diabetes history (FDH) impacts β-cell function. Some transmissible, accretional gradient of CHD risk may exist when diabetes and EOCHD familial histories combine. We investigated whether the impact of such combination is neutral, additive, or potentiating in T2DM descendants, as regards cardiometabolic phenotype, glucose homeostasis and micro-/macroangiopathies.

METHODS

Cross-sectional retrospective cohort study of 796 T2DM divided according to presence (Diab[+]) or absence (Diab[-]) of 1st-degree diabetes familial history and/or EOCHD (CVD(+) and (-)). Four subgroups: (i) [Diab(-)CVD(-)] (n=355); (ii) [Diab(+)CVD(-)] (n=338); (iii) [Diab(-)CVD(+)] (n=47); and (iv) [Diab(+)CVD(+)] (n=56).

RESULTS

No interaction on subgroup distribution between presence of both familial histories, the combination of which translated into additive detrimental outcomes and higher rates of fat mass, sarcopenia, (hs)CRP and retinopathy. FDH(+) had lower insulinemia, insulin secretion, hyperbolic product, and accelerated hyperbolic product loss. An EOCHD family history affected neither insulin secretion nor sensitivity. There were significant differences regarding macroangiopathy/CAD, more prevalent in [Diab(-)CVD(+)] and [Diab(+)CVD(+)]. Among CVD(+), the highest macroangiopathy prevalence was observed in [Diab(-)CVD(+)], who had 66% macroangiopathy, and 57% CAD, rates higher (absolute-relative) by 23%-53% (overall) and 21%-58% (CAD) than [Diab(+)CVD(+)], who inherited the direst cardiometabolic familial history (p 0.0288 and 0.0310).

CONCLUSIONS

A parental history for diabetes markedly affects residual insulin secretion and secretory loss rate in T2DM offspring without worsening insulin resistance. It paradoxically translated into lower macroangiopathy with concurrent familial EOCHD. Conjunct diabetes and CV familial histories generate multi-faceted vascular outcomes in offspring, including lesser macroangiopathy/CAD.

Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits

We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h²) and heritability explained by the common SNPs (h_g²) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insulin (INS), fasting trigylcerides (TG), and fasting high-density lipoprotein (HDL). We found the percentage of h² accounted for by common SNPs to be 58% of h² for height, 41% for BMI, 46% for WHR, 30% for GLU, 39% for INS, 34% for TG, 25% for HDL, and 80% for SBP. We confirmed prior reports for height and BMI using the ARIC population and independently in the Framingham Heart Study (FHS) population. We demonstrated that the multivariate model supported large genetic correlations between BMI and WHR and between TG and HDL. We also showed that the genetic correlations between the MetS traits are directly proportional to the phenotypic correlations.

The narrow-sense heritability of a trait such as body-mass index is a measure of the variability of the trait between people that is accounted for by their additive genetic differences. Knowledge of these genetic differences provides insight into biological mechanisms and hence treatments for diseases. Genome-wide association studies (GWAS) survey a large set of genetic markers common to the population. They have identified several single markers that are associated with traits and diseases. However, these markers do not seem to account for all of the known narrow-sense heritability. Here we used a recently developed model to quantify the genetic information contained in GWAS for single traits and shared between traits. We specifically investigated metabolic syndrome traits that are associated with type 2 diabetes and heart disease, and we found that for the majority of these traits much of the previously unaccounted for heritability is contained within common markers surveyed in GWAS. We also computed the genetic correlation between traits, which is a measure of the genetic components shared by traits. We found that the genetic correlation between these traits could be predicted from their phenotypic correlation.

Nutrient and food intakes of middle-aged adults at low risk of cardiovascular disease: the international study of macro-/micronutrients and blood pressure (INTERMAP)

PURPOSE

Individuals with favorable levels of readily measured cardiovascular disease (CVD) risk factors (low risk, LR) experience low long-term rates of CVD mortality and greater longevity. The purpose of the current study was to compare nutrient/food intakes of LR participants with participants not LR in the INTERMAP study.

METHODS

Men and women (40-59 years) from 17 population samples in four countries (China, Japan, UK, US) provided four 24-h dietary recalls and two timed 24-h urine collections. LR was defined as meeting all of the following CVD risk criteria: systolic/diastolic blood pressure (BP) ≤ 120/ ≤ 80 mmHg; no drug treatment for high BP, hyperlipidemia, or CVD; non-smoking; BMI <25.0 kg/m(2) (US, UK) or <23.0 kg/m(2) (China, Japan); alcohol consumption <26.0 g/day (men)/<13.0 g/day (women); and no history of diabetes or CVD. Multivariate logistic regression was used to examine associations of nutrient/food intakes with LR.

RESULTS

LR individuals reported higher intake of vegetable protein, fiber, magnesium, non-heme iron, potassium; lower energy intake; lower intake of cholesterol, saturated fatty acids, animal protein; and lower 24-h urinary sodium compared with individuals not LR. With regard to foods, LR individuals reported higher intake of fruits, vegetables, grains, pasta/rice, fish; lower intakes of meats, processed meats, high-fat dairy, and sugar-sweetened beverages than individuals not LR.

CONCLUSIONS

Lower energy intake and differential intake of multiple specific nutrients and foods are characteristic of individuals at low risk for developing CVD. Identification of dietary habits associated with LR is important for further development of public health efforts aimed at reduction/prevention of CVD.

Complex phenotypes and phenomenon of genome-wide inter-chromosomal linkage disequilibrium in the human genome

Studies of non-human species show that loci on non-homologous chromosomes can be in linkage disequilibrium (LD). I focus on the Framingham Heart Study (FHS) participants to explore whether the phenomenon of inter-chromosomal LD can be caused by non-stochastic bio-genetic mechanisms in the human genome and be associated with complex, polygenic phenotypes. This paper documents remarkably strong and extensive LD among SNPs at loci on multiple non-homologous chromosomes genotyped using two independent (Affymetrix 50K and 500K) arrays. The analyses provided compelling evidences that the observed inter-chromosomal LD was unlikely generated by stochasticity, population or family structure, or mis-genotyping. The analyses show that this LD is associated with complex heritable phenotypes characterizing poor health. The inter-chromosomal LD was observed in parental and offspring generations of the FHS participants. These findings suggest that inter-chromosomal LD can be caused by bio-genetic mechanisms possibly associated with favorable or unfavorable epistatic evolution. This phenomenon can challenge our understanding of the role of genes and gene networks in regulating complex, polygenic phenotypes in humans.

Trade-off in the effects of the apolipoprotein E polymorphism on the ages at onset of CVD and cancer influences human lifespan

Progress in unraveling the genetic origins of healthy aging is tempered, in part, by a lack of replication of effects, which is often considered a signature of false-positive findings. We convincingly demonstrate that the lack of genetic effects on an aging-related trait can be because of trade-offs in the gene action. We focus on the well-studied apolipoprotein E (APOE) e2/3/4 polymorphism and on lifespan and ages at onset of cardiovascular diseases (CVD) and cancer, using data on 3924 participants of the Framingham Heart Study Offspring cohort. Kaplan-Meier estimates show that the e4 allele carriers live shorter lives than the non-e4 allele carriers (log rank = 0.016). The adverse effect was attributed to the poor survival of the e4 homozygotes, whereas the effect of the common e3/4 genotype was insignificant. The e3/4 genotype, however, was antagonistically associated with onsets of those diseases predisposing to an earlier onset of CVD and a later onset of cancer compared to the non-e4 allele genotypes. This trade-off explains the lack of a significant effect of the e3/4 genotype on survival; adjustment for it in the Cox regression model makes the detrimental effect of the e4 allele highly significant (P = 0.002). This trade-off is likely caused by the lipid-metabolism-related (for CVD) and nonrelated (for cancer) mechanisms. An evolutionary rationale suggests that genetic trade-offs should not be an exception in studies of aging-related traits. Deeper insights into biological mechanisms mediating gene action are critical for understanding the genetic regulation of a healthy lifespan and for personalizing medical care.

The MYH9/APOL1 region and chronic kidney disease in European-Americans

Polymorphisms in the MYH9 and adjacent APOL1 gene region demonstrate a strong association with non-diabetic kidney disease in African-Americans. However, it is not known to what extent these polymorphisms are present in other ethnic groups. To examine the association of genetic polymorphisms in this region with chronic kidney disease (CKD; estimated glomerular filtration rate <60 ml/min/1.73 m(2)) in individuals of European ancestry, we examined rs4821480, an MYH9 single-nucleotide polymorphism (SNP) recently identified as associated with kidney disease in African-Americans, in 13 133 participants from the Framingham Heart Study (FHS) and Atherosclerosis Risk in Communities (ARIC) Study. In addition, we further interrogated the MYH9/APOL1 gene region using 282 SNPs for association with CKD using age-, sex- and center-adjusted models and performed a meta-analysis of the results from both studies. Because of prior data linking rs4821480 and kidney disease, we used a P-value of <0.05 to test the association with CKD. In the meta-analysis, rs4821480 (minor allele frequency 4.45 and 3.96% in FHS and ARIC, respectively) was associated with higher CKD prevalence in participants free of diabetes (odds ratio 1.44; 95% confidence interval 1.15-1.80; P = 0.001). No other SNPs achieved significance after adjusting for multiple testing. Results utilizing directly genotyped data confirmed the results of the primary analysis. Recently identified APOL1 risk variants were also directly genotyped, but did not account for the observed MYH9 signal. These data suggest that the MYH9 polymorphism rs4821480 is associated with an increased risk of non-diabetic CKD in individuals of European ancestry.