Layer myocardial strain is the most heritable echocardiographic trait.

AIMS: Myocardial deformation assessed by strain analysis represents a significant advancement in our assessment of cardiac mechanics. However, whether this variable is genetically heritable or whether all/most of its variability is related to environmental factors is currently unknown. We sought to determine the heritability of echocardiographically determined cardiac mechanics indices in a population setting. METHODS AND RESULTS: A total of 1357 initially healthy subjects (women 51.6%; 48.2 ± 14.1 years) were included in this study from 20-year follow-up after the fourth visit of the longitudinal familial STANISLAS cohort (Lorraine, France). Data were acquired using state-of-the-art cardiac ultrasound equipment, using acquisition and measurement protocols recommended by the EACVI (European Association of Cardiovascular Imaging)/ASE (American Society of Echocardiography)/Industry Task Force. Layer-specific global longitudinal strain (GLS) and global circumferential strain (full-wall, subendocardial, and subepicardial) and conventional structural and functional cardiac parameters and their potential heritability were assessed using restricted maximum likelihood analysis, with genetic relatedness matrix calculated from genome-wide association data. Indices of longitudinal/circumferential myocardial function and left ventricular (LV) ejection fraction had low heritability (ranging from 10% to 20%). Diastolic and standard LV function parameters had moderate heritability (ranging from 20% to 30%) except for end-systolic and end-diastolic volumes (30% and 45%, respectively). In contrast, global longitudinal subendocardial strain (GLSEndo)/global longitudinal subepicardial strain (GLSEpi) ratio had a high level of heritability (65%). Except for GLSEndo/GLSEpi ratio, a large percentage of variance remained unexplained (>50%). CONCLUSIONS: In our population cohort, GLSEndo/GLSEpi ratio had a high level of heritability, whereas other classical and mechanical LV function parameters did not. Given the increasing recognition of GLSEndo/GLSEpi ratio as an early/sensitive imaging biomarker of systolic dysfunction, our results suggest the possible existence of individual genetic predispositions to myocardial decline.

Shared Heritability of Blood Pressure and Pulse Wave Velocity: Insights From the STANISLAS Cohort.

BACKGROUND: Pulse wave velocity (PWV) is a marker of arterial stiffness, which is intrinsically highly correlated with blood pressure (BP). However, the interplay of PWV and BP heritability has not been extensively studied. This study aimed to estimate the heritability of PWV and BP and determine the genetic correlation between PWV and BP. METHODS: The heritability of PWV and BP was estimated in 1080 subjects from the STANISLAS (Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux) cohort with at least one relative using a linear mixed model within one frequentist and one Bayesian framework implemented, respectively, in the Gaston and MCMCglmm R packages. Then their genetic correlations were also estimated. RESULTS: The heritability estimations for PWV were within the same range of the heritability of systolic BP and diastolic BP (23%, 19%, and 27%, respectively). Daytime heritability of BP was higher than nighttime BP. In addition, phenotypic correlations between PWV and systolic BP/diastolic BP were, respectively, 0.34 and 0.23, whereas nonsignificant genetic correlations were 0.08 and 0.22 respectively, indicating that PWV and diastolic BP shared more polygenic codeterminants than PWV and systolic BP. CONCLUSIONS: Our results suggest that the heritability of PWV is >20% and within the same range as BP heritability. It also suggests that the link between PWV and BP goes beyond phenotypic association: PWV and BP (in particular diastolic BP) share common genetic determinants. This genetic interdependence of PWV and BP appears largely polygenic.

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease.

BACKGROUND: Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors. OBJECTIVE: To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study. RESULTS: All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS313 in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively). CONCLUSION: Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.

Fatty acid desaturase genetic variations and dietary omega-3 fatty acid intake associate with arterial stiffness.

Aims: Long-chain polyunsaturated fatty acids (PUFAs) generate diverse bioactive lipid mediators, which tightly regulate vascular inflammation. The effects of omega-3 PUFA supplementation in cardiovascular prevention however remain controversial. In addition to direct dietary intake, fatty acid desaturases (FADS) determine PUFA levels. Increased arterial stiffness represents an independent predictor of mortality and cardiovascular events. The aim of the present study was to determine the association of PUFA intake, FADS1 genotype, and FADS expression with arterial stiffness. Methods and results: A cross-sectional population-based cohort study of 1464 participants without overt cardiovascular disease was conducted. Dietary intake was assessed using a food frequency questionnaire. Arterial stiffness was assessed by carotid-femoral pulse wave velocity (cfPWV), and the FADS1 locus variant was determined. Blood cell transcriptomics was performed in a subset of 410 individuals. Pulse wave velocity was significantly associated with the FADS1 locus variant. Differential associations between PWV and omega-3 PUFA intake were observed depending on the FADS1 genotype. High omega-3 PUFA intake attenuated the FADS1 genotype-dependent associations. Carriers of the minor FADS1 locus variant exhibited increased expression of FADS2, which is associated with PWV. Conclusion: Taken together, these findings point to FADS1 genotype-dependent associations of omega-3 PUFA intake on subclinical cardiovascular disease. These findings may have implications for identifying responders and non-responders to omega-3 PUFA supplementation and open up for personalized dietary counselling in cardiovascular prevention.

Weak Association Between Genetic Markers of Hyperuricemia and Cardiorenal Outcomes: Insights From the STANISLAS Study Cohort With a 20-Year Follow-Up.

Background Hyperuricemia is associated with poor cardiovascular outcomes, although it is uncertain whether this relationship is causal in nature. This study aimed to: (1) assess the heritability of serum uric acid (SUA) levels, (2) conduct a genome-wide association study on SUA levels, and (3) investigate the association between certain single-nucleotide polymorphisms and target organ damage. Methods and Results The STANISLAS (Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux) study cohort is a single-center longitudinal cohort recruited between 1993 and 1995 (visit 1), with a last visit (visit 4 [V4]) performed ≈20 years apart. Serum lipid profile, SUA, urinary albumin/creatinine ratio, estimated glomerular filtration rate, 24-hour ambulatory blood pressure monitoring, transthoracic echocardiography, pulse wave velocity, and genotyping for each participant were assessed at V4. A total of 1573 participants were included at V4, among whom 1417 had available SUA data at visit 1. Genome-wide association study results highlighted multiple single-nucleotide polymorphisms on the SLC2A9 gene linked to SUA levels. Carriers of the most associated mutated SLC2A9 allele (rs16890979) had significantly lower SUA levels. Although SUA level at V4 was highly associated with diabetes, prediabetes, higher body mass index, CRP (C-reactive protein) levels, estimated glomerular filtration rate variation (visit 1-V4), carotid intima-media thickness, and pulse wave velocity, rs16890979 was only associated with higher carotid intima-media thickness. Conclusions Our findings demonstrate that rs16890979, a genetic determinant of SUA levels located on the SLC2A9 gene, is associated with carotid intima-media thickness despite significant associations between SUA levels and several clinical outcomes, thereby lending support to the hypothesis of a link between SUA and cardiovascular disease.

Impact of natriuretic peptide polymorphisms on diastolic and metabolic function in a populational cohort: insights from the STANISLAS cohort.

AIMS: Elevated brain natriuretic peptide (BNP) and the N-terminal fragment of its pro-hormone (NT-proBNP) have become established biomarkers for heart failure and are associated with cardiovascular morbidity and mortality. Investigating sources of inter-individual heterogeneity, particularly genetic factors, could help better identify patients at risk of future cardiovascular disease. The aim of this study was to estimate the heritability of circulating NT-proBNP levels, to perform a genome-wide association study (GWAS) and gene-candidate analysis focused on NPPB-NPPA genes on these levels, and to examine their association with cardiovascular or metabolic outcomes. METHODS AND RESULTS: A total of 1555 individuals from the STANISLAS study were included. The heritability of circulating NT-proBNP levels was estimated at 15%, with seven single nucleotide polymorphisms (SNPs) reaching the significant threshold in the GWAS. All above SNPs were located on the same gene cluster constituted of MTHFR, CLCN6, NPPA, NPPB, and C1orf167. NPPA gene expression was also associated with NT-proBNP levels. Moreover, six other SNPs from NPPA-NPPB genes were associated with diastolic function (lateral e' on echocardiography) and metabolic features (glycated haemoglobin). CONCLUSIONS: The heritability of natriuretic peptides appears relatively low (15%) and mainly based on the same gene cluster constituted of MTHFR, CLCN6, NPPA, NPPB, and C1orf167. Natriuretic peptide polymorphisms are associated with natriuretic peptide levels and diastolic function. These results suggest that natriuretic peptide polymorphisms may have an impact in the early stages of cardiovascular and metabolic disease.

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.

Mutations and variants of ONECUT1 in diabetes.

Genes involved in distinct diabetes types suggest shared disease mechanisms. Here we show that One Cut Homeobox 1 (ONECUT1) mutations cause monogenic recessive syndromic diabetes in two unrelated patients, characterized by intrauterine growth retardation, pancreas hypoplasia and gallbladder agenesis/hypoplasia, and early-onset diabetes in heterozygous relatives. Heterozygous carriers of rare coding variants of ONECUT1 define a distinctive subgroup of diabetic patients with early-onset, nonautoimmune diabetes, who respond well to diabetes treatment. In addition, common regulatory ONECUT1 variants are associated with multifactorial type 2 diabetes. Directed differentiation of human pluripotent stem cells revealed that loss of ONECUT1 impairs pancreatic progenitor formation and a subsequent endocrine program. Loss of ONECUT1 altered transcription factor binding and enhancer activity and NKX2.2/NKX6.1 expression in pancreatic progenitor cells. Collectively, we demonstrate that ONECUT1 controls a transcriptional and epigenetic machinery regulating endocrine development, involved in a spectrum of diabetes, encompassing monogenic (recessive and dominant) as well as multifactorial inheritance. Our findings highlight the broad contribution of ONECUT1 in diabetes pathogenesis, marking an important step toward precision diabetes medicine.

Genome-wide haplotype association study in imaging genetics using whole-brain sulcal openings of 16,304 UK Biobank subjects.

Neuroimaging-genetics cohorts gather two types of data: brain imaging and genetic data. They allow the discovery of associations between genetic variants and brain imaging features. They are invaluable resources to study the influence of genetics and environment in the brain features variance observed in normal and pathological populations. This study presents a genome-wide haplotype analysis for 123 brain sulcus opening value (a measure of sulcal width) across the whole brain that include 16,304 subjects from UK Biobank. Using genetic maps, we defined 119,548 blocks of low recombination rate distributed along the 22 autosomal chromosomes and analyzed 1,051,316 haplotypes. To test associations between haplotypes and complex traits, we designed three statistical approaches. Two of them use a model that includes all the haplotypes for a single block, while the last approach considers each haplotype independently. All the statistics produced were assessed as rigorously as possible. Thanks to the rich imaging dataset at hand, we used resampling techniques to assess False Positive Rate for each statistical approach in a genome-wide and brain-wide context. The results on real data show that genome-wide haplotype analyses are more sensitive than single-SNP approach and account for local complex Linkage Disequilibrium (LD) structure, which makes genome-wide haplotype analysis an interesting and statistically sound alternative to the single-SNP counterpart.

Exploring the Link Between Additive Heritability and Prediction Accuracy From a Ridge Regression Perspective.

Genome-Wide Association Studies (GWAS) explain only a small fraction of heritability for most complex human phenotypes. Genomic heritability estimates the variance explained by the SNPs on the whole genome using mixed models and accounts for the many small contributions of SNPs in the explanation of a phenotype. This paper approaches heritability from a machine learning perspective, and examines the close link between mixed models and ridge regression. Our contribution is two-fold. First, we propose estimating genomic heritability using a predictive approach via ridge regression and Generalized Cross Validation (GCV). We show that this is consistent with classical mixed model based estimation. Second, we derive simple formulae that express prediction accuracy as a function of the ratio n p , where n is the population size and p the total number of SNPs. These formulae clearly show that a high heritability does not imply an accurate prediction when p > n. Both the estimation of heritability via GCV and the prediction accuracy formulae are validated using simulated data and real data from UK Biobank.

PCSK9 Protein and rs562556 Polymorphism Are Associated With Arterial Plaques in Healthy Middle-Aged Population: The STANISLAS Cohort.

Background PCSK9 (Proprotein convertase subtilisin/kexin type 9) binds low-density lipoprotein receptor, preventing its recycling. PCSK9 is a risk predictor and a biotarget in atherosclerosis. The PCSK9-rs562556 variant has been reported as a gain-of-function mutation. The aim of this study was to determine whether the PCSK9-low-density lipoprotein receptor-rs562556 axis is associated with carotid artery plaques between 2 visits separated by almost 20 years in a longitudinal population cohort. Methods and Results The STANISLAS (Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux) cohort is a longitudinal familial cohort from the Lorraine region of France. Participants attending 2 visits (visit 1 and visit 4) separated by 18.5 years (mean) were included (n=997). Carotid artery plaques were determined with standardized vascular echography. The mean age of the adult population at visit 1 was 42±5 years. At visit 4, 203 (20.4%) participants had arterial plaques. Participants who developed arterial plaques were older (42.7±5.4 versus 41.7±4.7 years), more often male (60% versus 49%), smokers (29% versus 18%), with diabetes mellitus (6% versus 3%), and higher cholesterol levels (low-density lipoprotein cholesterol, 1.6±0.4 versus 1.5±0.3 g/L) (all P<0.05). The independent factors associated with arterial plaques were age, smoking, and low-density lipoprotein cholesterol. Higher PCSK9 levels were associated with arterial plaques on top of the clinical model (odds ratio, 2.14; 95% CI,= 1.28-3.58); the missense mutation coding the single-nucleotide polymorphism rs562556 was associated with both higher PCSK9 concentration and incident carotid arterial plaques. Conclusions Higher PCSK9 concentration was associated with the development of arterial plaques almost 20 years in advance in a healthy middle-aged population. Mutations of the single-nucleotide polymorphism rs562556 associated with both PCSK9 levels and arterial plaques reinforce the potential causality of our findings. PCSK9 inhibitors could be useful for primary cardiovascular prevention.

Genomic evidence for MHC disassortative mating in humans.

Although pervasive in many animal species, the evidence for major histocompatibility complex (MHC) disassortative mating in humans remains inconsistent across studies. Here, to revisit this issue, we analyse dense genotype data for 883 European and Middle Eastern couples. To distinguish MHC-specific effects from socio-cultural confounders, the pattern of relatedness between spouses in the MHC region is compared to the rest of the genome. Couples from Israel exhibit no significant pattern of relatedness across the MHC region, whereas across the genome, they are more similar than random pairs of individuals, which may reflect social homogamy and/or cousin marriages. On the other hand, couples from The Netherlands and more generally from Northern Europe are significantly more MHC-dissimilar than random pairs of individuals, and this pattern of dissimilarity is extreme when compared with the rest of the genome. Our findings support the hypothesis that the MHC influences mate choice in humans in a context-dependent way: MHC-driven preferences may exist in all populations but, in some populations, social constraints over mate choice may reduce the ability of individuals to rely on such biological cues when choosing their mates.

Accuracy of heritability estimations in presence of hidden population stratification.

The heritability of a trait is the proportion of its variance explained by genetic factors; it has historically been estimated using familial data. However, new methods have appeared for estimating heritabilities using genomewide data from unrelated individuals. A drawback of this strategy is that population stratification can bias the estimates. Indeed, an environmental factor associated with the phenotype may differ among population subgroups. This factor being associated both with the phenotype and the genetic variation in the population would be a confounder. A common solution consists in adjusting on the first Principal Components (PCs) of the genomic data. We study this procedure on simulated data and on 6000 individuals from the Three-City Study. We analyse the geographical coordinates of the birth cities, which are not genetically determined, but the heritability of which should be overestimated due to population stratification. We also analyse various anthropometric traits. The procedure fails to correct the bias in geographical coordinates heritability estimates. The heritability estimates of the anthropometric traits are affected by the inclusion of the first PC, but not by the following PCs, contrarily to geographical coordinates. We recommend to be cautious with heritability estimates obtained from a large population.

Where is the causal variant? On the advantage of the family design over the case-control design in genetic association studies.

Many associated single-nucleotide polymorphisms (SNPs) have been identified by association studies for numerous diseases. However, the association between a SNP and a disease can result from a causal variant in linkage disequilibrium (LD) with the considered SNP. Assuming that the true causal variant is among the genotyped SNPs, other authors demonstrated that the power to discriminate between it and other SNPs in LD is low. Here, we propose to take advantage of the information provided by family data to improve the inference on the causal variant: we exploit the linkage information provided by affected sib pairs to discriminate the causal variant from the associated SNPs. The family-based approach improves discrimination power requiring up to five times less individuals than its case-control equivalent. However, the main advantage of family design is the possibility to carry out the procedure one step further: the linkage information allows inference on causal variants, which are not genotyped but in LD with tag-SNPs displaying association, which is impossible with case-control design. By means of Bayesian methods, we estimate the LD between the observed SNPs and an unobserved causal variant, as well as the allelic odds ratio at the unobserved causal variant. The proposed procedure is illustrated on a multiple sclerosis (MS) family data set including genotypes of SNPs in IL2RA, confirming the advantage of using a family design to identify causal variants. The results of our method on this data suggest the existence of two distinct causal variants in this gene for the MS.

The Use of the Linear Mixed Model in Human Genetics.

We give a short but detailed review of the methods used to deal with linear mixed models (restricted likelihood, AIREML algorithm, best linear unbiased predictors, etc.), with a few original points. Then we describe three common applications of the linear mixed model in contemporary human genetics: association testing (pathways analysis or rare variants association tests), genomic heritability estimates, and correction for population stratification in genome-wide association studies. We also consider the performance of best linear unbiased predictors for prediction in this context, through a simulation study for rare variants in a short genomic region, and through a short theoretical development for genome-wide data. For each of these applications, we discuss the relevance and the impact of modeling genetic effects as random effects.

Environmental influences on daily emergency admissions in sickle-cell disease patients.

Previous reports have suggested a role for weather conditions and air pollution on the variability of sickle cell disease (SCD) severity, but large-scale comprehensive epidemiological studies are lacking. In order to evaluate the influence of air pollution and climatic factors on emergency hospital admissions (EHA) in SCD patients, we conducted an 8-year observational retrospective study in 22 French university hospitals in Paris conurbation, using distributed lag non-linear models, a methodology able to flexibly describe simultaneously non-linear and delayed associations, with a multivariable approach. During the 2922 days of the study, there were 17,710 EHA, with a mean daily number of 6.1 ± 2.8. Most environmental factors were significantly correlated to each other. The risk of EHA was significantly associated with higher values of nitrogen dioxide, atmospheric particulate matters, and daily mean wind speed; and with lower values of carbon monoxide, ozone, sulfur dioxide, daily temperature (minimal, maximal, mean, and range), day-to-day mean temperature change, daily bright sunshine, and occurrence of storm. There was a lag effect for 12 of 15 environmental factors influencing hospitalization rate. Multivariate analysis identified carbon monoxide, day-to-day temperature change, and mean wind speed, along with calendar factors (weekend, summer season, and year) as independent factors associated with EHA. In conclusion, most weather conditions and air pollutants assessed were correlated to each other and influenced the rate of EHA in SCD patients. In multivariate analysis, lower carbon monoxide concentrations, day-to-day mean temperature drop and higher wind speed were associated with increased risk of EHA.