Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease.

BACKGROUND AND AIMS: It is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2. METHODS: A PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 × PRS-factor' was tested by risk reclassification. RESULTS: In subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 × PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC. CONCLUSIONS: This study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD.

Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes.

BACKGROUND: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. METHODS: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. RESULTS: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. CONCLUSIONS: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

Genetic and modifiable risk factors combine multiplicatively in common disease.

BACKGROUND: The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized. OBJECTIVES: We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors. METHODS: We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions. RESULTS: In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer. CONCLUSIONS: Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

Phenome-wide association studies on cardiovascular health and fatty acids considering phenotype quality control practices for epidemiological data.

Phenome-wide association studies (PheWAS) allow agnostic investigation of common genetic variants in relation to a variety of phenotypes but preserving the power of PheWAS requires careful phenotypic quality control (QC) procedures. While QC of genetic data is well-defined, no established QC practices exist for multi-phenotypic data. Manually imposing sample size restrictions, identifying variable types/distributions, and locating problems such as missing data or outliers is arduous in large, multivariate datasets. In this paper, we perform two PheWAS on epidemiological data and, utilizing the novel software CLARITE (CLeaning to Analysis: Reproducibility-based Interface for Traits and Exposures), showcase a transparent and replicable phenome QC pipeline which we believe is a necessity for the field. Using data from the Ludwigshafen Risk and Cardiovascular (LURIC) Health Study we ran two PheWAS, one on cardiac-related diseases and the other on polyunsaturated fatty acids levels. These phenotypes underwent a stringent quality control screen and were regressed on a genome-wide sample of single nucleotide polymorphisms (SNPs). Seven SNPs were significant in association with dihomo-γ-linolenic acid, of which five were within fatty acid desaturases FADS1 and FADS2. PheWAS is a useful tool to elucidate the genetic architecture of complex disease phenotypes within a single experimental framework. However, to reduce computational and multiple-comparisons burden, careful assessment of phenotype quality and removal of low-quality data is prudent. Herein we perform two PheWAS while applying a detailed phenotype QC process, for which we provide a replicable pipeline that is modifiable for application to other large datasets with heterogenous phenotypes. As investigation of complex traits continues beyond traditional genome wide association studies (GWAS), such QC considerations and tools such as CLARITE are crucial to the in the analysis of non-genetic big data such as clinical measurements, lifestyle habits, and polygenic traits.

Iron Metabolism, Hepcidin, and Mortality (the Ludwigshafen Risk and Cardiovascular Health Study).

BACKGROUND: Anemia has been shown to be a risk factor for coronary artery disease (CAD) and mortality, whereas the role of iron metabolism remains controversial. METHODS: We analyzed iron metabolism and its associations with cardiovascular death and total mortality in patients undergoing coronary angiography with a median follow-up of 9.9 years. Hemoglobin and iron status were determined in 1480 patients with stable CAD and in 682 individuals in whom significant CAD had been excluded by angiography. RESULTS: Multivariate-adjusted hazard ratios (HRs) for total mortality in the lowest quartiles of iron, transferrin saturation, ferritin, soluble transferrin receptor (sTfR), and hemoglobin were 1.22 (95% CI, 0.96-1.60), 1.23 (95% CI, 0.97-1.56), 1.27 (95% CI, 1.02-1.58), 1.26 (95% CI, 0.97-1.65), and 0.99 (95% CI, 0.79-1.24), respectively, compared to the second or third quartile, which served as reference (1.00) because of a J-shaped association. The corresponding HRs for total mortality in the highest quartiles were 1.44 (95% CI, 1.10-1.87), 1.37 (95% CI, 1.05-1.77), 1.17 (95% CI, 0.92-1.50), 1.76 (95% CI, 1.39-2.22), and 0.83 (95% CI, 0.63-1.09). HRs for cardiovascular death were similar. For hepcidin, the adjusted HRs for total mortality and cardiovascular deaths were 0.62 (95% CI, 0.49-0.78) and 0.70 (95% CI, 0.52-0.90) in the highest quartile compared to the lowest one. CONCLUSIONS: In stable patients undergoing angiography, serum iron, transferrin saturation, sTfR, and ferritin had J-shaped associations and hemoglobin only a marginal association with cardiovascular and total mortality. Hepcidin was continuously and inversely related to mortality.

From Epigenetic Associations to Biological and Psychosocial Explanations in Mental Health.

The development of mental disorders constitutes a complex phenomenon driven by unique social, psychological and biological factors such as genetics and epigenetics, throughout an individual's life course. Both environmental and genetic factors have an impact on mental health phenotypes and act simultaneously to induce changes in brain and behavior. Here, we describe and critically evaluate the current literature on gene-environment interactions and epigenetics on mental health by highlighting recent human and animal studies. We furthermore review some of the main ethical and social implications concerning gene-environment interactions and epigenetics and provide explanations and suggestions on how to move from statistical and epigenetic associations to biological and psychological explanations within a multi-disciplinary and integrative approach of understanding mental health.

Association of a Met88Val diazepam binding inhibitor (DBI) gene polymorphism and anxiety disorders with panic attacks.

Several lines of evidence suggest that anxiety disorders have a strong genetic component, but so far only few susceptibility genes have been identified. There is preclinical and clinical evidence for a dysregulation of the central gamma-aminobutyric acid (GABA)-ergic tone in the pathophysiology of anxiety disorders. Diazepam binding inhibitor (DBI) has been suggested to play a pivotal role in anxiety disorders through direct and indirect, i.e. via synthesis of neuroactive steroids, modulation of GABA(A) receptor function. These findings suggest that the DBI gene can be postulated as a candidate for a genetic association study in this disorder. Thus, single nucleotide polymorphisms (SNPs) of the DBI gene were investigated for putative disease associations in a German sample of anxiety disorder patients suffering from panic attacks and matched controls. We were able to detect a significant association between a non-synonymous coding variant of DBI with anxiety disorders with panic attacks. The rare allele of this polymorphism was more frequent in controls than in patients (OR=0.43; 95% CI: 0.19-0.95). In conclusion, these results suggest a central role of DBI genetic variants in the susceptibility for the development of anxiety disorders that are characterized by the occurrence of panic attacks.

The variant Arg110Gln of human IL-13 is associated with an immunologically hyper-reactive form of onchocerciasis (sowda).

Onchocerca volvulus infection usually results in a predominantly immunopermissive reaction called generalized onchocerciasis and characterized by high microfilarial burden and immunological tolerance to the worms. Rarely, however, infection leads to the sowda form of the disease displaying low microfilarial numbers, i.e. microfilarial control, and a T helper 2 (Th2)-type immune response including high immunoglobulin (Ig)E levels, and interleukin (IL)-13 being one of the key cytokines. The aim of this study was to investigate a possible association of a variant of the IL-13 gene, which confers an IgE-independent risk for asthma and atopy, with the immunologically hyper-reactive sowda form of onchocerciasis. Genotyping for the IL-13 variant Arg110Gln revealed a highly significant association of Arg110Gln with the sowda form (relative risk of 2.98, n = 19 patients), whereas the frequency of the variant was significantly lower in patients with generalized onchocerciasis (n = 92 individuals). Sowda patients had higher IgE levels than those with generalized onchocerciasis. Logistic regression analysis revealed that IgE and IL-13 are independent variables, each increasing the relative risk for sowda. Arg110Gln has been suggested to lead to enhanced IL-13 signaling and thus may be involved in shifting the immune reaction towards the hyper-reactivity characteristic for the sowda form, thereby promoting defense mechanisms.