Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study

AIMS

Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS.

METHODS AND RESULTS

A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10-8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2-SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26-1.35; P = 2.7 × 10-51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08-1.37; P = 1.4 × 10-3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90-5.12; P = 2.1 × 10-20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17-1.23; P = 4.8 × 10-73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05-1.9; P = 1.9 × 10-12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS.

CONCLUSION

Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

Brain age prediction using deep learning uncovers associated sequence variants

Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual’s predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here, we present a new deep learning approach to predict brain age from a T1-weighted MRI. The method was trained on a dataset of healthy Icelanders and tested on two datasets, IXI and UK Biobank, utilizing transfer learning to improve accuracy on new sites. A genome-wide association study (GWAS) of PAD in the UK Biobank data (discovery set: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=12378$$\end{document}N=12378, replication set: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=4456$$\end{document}N=4456) yielded two sequence variants, rs1452628-T (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta =-0.08$$\end{document}β=−0.08, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P=1.15\times{10}^{-9}$$\end{document}P=1.15×10−9) and rs2435204-G (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta =0.102$$\end{document}β=0.102, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P=9.73\times 1{0}^{-12}$$\end{document}P=9.73×10−12). The former is near KCNK2 and correlates with reduced sulcal width, whereas the latter correlates with reduced white matter surface area and tags a well-known inversion at 17q21.31 (H2).

Machine learning algorithms can be trained to estimate age from brain structural MRI. Here, the authors introduce a new deep-learning-based age prediction approach, and then carry out a GWAS of the difference between predicted and chronological age, revealing two associated variants.

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44-77%) was associated with increased risk of nicotine dependence at P=3.7 × 10-8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04-1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10-4, OR=1.05, and 95% CI=1.02-1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01-1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10-26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10-6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.

Rare and Common Variants Conferring Risk of Tooth Agenesis

We present association results from a large genome-wide association study of tooth agenesis (TA) as well as selective TA, including 1,944 subjects with congenitally missing teeth, excluding third molars, and 338,554 controls, all of European ancestry. We also tested the association of previously identified risk variants, for timing of tooth eruption and orofacial clefts, with TA. We report associations between TA and 9 novel risk variants. Five of these variants associate with selective TA, including a variant conferring risk of orofacial clefts. These results contribute to a deeper understanding of the genetic architecture of tooth development and disease. The few variants previously associated with TA were uncovered through candidate gene studies guided by mouse knockouts. Knowing the etiology and clinical features of TA is important for planning oral rehabilitation that often involves an interdisciplinary approach.

15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia

Several copy number variants have been associated with neuropsychiatric disorders and these variants have been shown to also influence cognitive abilities in carriers unaffected by psychiatric disorders. Previously, we associated the 15q11.2(BP1-BP2) deletion with specific learning disabilities and a larger corpus callosum. Here we investigate, in a much larger sample, the effect of the 15q11.2(BP1-BP2) deletion on cognitive, structural and functional correlates of dyslexia and dyscalculia. We report that the deletion confers greatest risk of the combined phenotype of dyslexia and dyscalculia. We also show that the deletion associates with a smaller left fusiform gyrus. Moreover, tailored functional magnetic resonance imaging experiments using phonological lexical decision and multiplication verification tasks demonstrate altered activation in the left fusiform and the left angular gyri in carriers. Thus, by using convergent evidence from neuropsychological testing, and structural and functional neuroimaging, we show that the 15q11.2(BP1-BP2) deletion affects cognitive, structural and functional correlates of both dyslexia and dyscalculia.

A rare missense mutation in CHRNA4 associates with smoking behavior and its consequences

Using Icelandic whole-genome sequence data and an imputation approach we searched for rare sequence variants in CHRNA4 and tested them for association with nicotine dependence. We show that carriers of a rare missense variant (allele frequency=0.24%) within CHRNA4, encoding an R336C substitution, have greater risk of nicotine addiction than non-carriers as assessed by the Fagerstrom Test for Nicotine Dependence (P=1.2 × 10(-4)). The variant also confers risk of several serious smoking-related diseases previously shown to be associated with the D398N substitution in CHRNA5. We observed odds ratios (ORs) of 1.7-2.3 for lung cancer (LC; P=4.0 × 10(-4)), chronic obstructive pulmonary disease (COPD; P=9.3 × 10(-4)), peripheral artery disease (PAD; P=0.090) and abdominal aortic aneurysms (AAAs; P=0.12), and the variant associates strongly with the early-onset forms of LC (OR=4.49, P=2.2 × 10(-4)), COPD (OR=3.22, P=2.9 × 10(-4)), PAD (OR=3.47, P=9.2 × 10(-3)) and AAA (OR=6.44, P=6.3 × 10(-3)). Joint analysis of the four smoking-related diseases reveals significant association (P=6.8 × 10(-5)), particularly for early-onset cases (P=2.1 × 10(-7)). Our results are in agreement with functional studies showing that the human α4β2 isoform of the channel containing R336C has less sensitivity for its agonists than the wild-type form following nicotine incubation.

Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence

We conducted a 1000 Genomes-imputed genome-wide association study (GWAS) meta-analysis for nicotine dependence, defined by the Fagerström Test for Nicotine Dependence in 17 074 ever smokers from five European-ancestry samples. We followed up novel variants in 7469 ever smokers from five independent European-ancestry samples. We identified genome-wide significant association in the alpha-4 nicotinic receptor subunit (CHRNA4) gene on chromosome 20q13: lowest P=8.0 × 10(-9) across all the samples for rs2273500-C (frequency=0.15; odds ratio=1.12 and 95% confidence interval=1.08-1.17 for severe vs mild dependence). rs2273500-C, a splice site acceptor variant resulting in an alternate CHRNA4 transcript predicted to be targeted for nonsense-mediated decay, was associated with decreased CHRNA4 expression in physiologically normal human brains (lowest P=7.3 × 10(-4)). Importantly, rs2273500-C was associated with increased lung cancer risk (N=28 998, odds ratio=1.06 and 95% confidence interval=1.00-1.12), likely through its effect on smoking, as rs2273500-C was no longer associated with lung cancer after adjustment for smoking. Using criteria for smoking behavior that encompass more than the single 'cigarettes per day' item, we identified a common CHRNA4 variant with important regulatory properties that contributes to nicotine dependence and smoking-related consequences.

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.

A common biological basis of obesity and nicotine addiction

Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM

Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10(-11) and 2.7 × 10(-11)), which were also in strong linkage disequilibrium (r(2)=0.7) with each other, lie in the 23-kb long commonly shared 5' flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10(-09)) near NRCAM-a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10(-09))-an SNP associated with blood pressure-in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10(-05)) and Parkinson's disease pathways (P-value=3.6 × 10(-05)).

An algorithm for detecting high frequency copy number polymorphisms using SNP arrays

We present a general algorithm for the detection of genomic variants using the Illumina iSelect platform. The Illumina iSelect platform is designed to detect SNPs, but our algorithm allows for the detections of more general forms of variations, including copy number polymorphisms and microsatellites. The algorithm does not rely on a priori information of the type of polymorphism being studied and is designed to genotype call a large number of individuals simultaneously. The algorithm proceeds by initially normalizing intensity and correcting for batch effects. Then each marker is clustered using a modified Gaussian mixture model where we account for variances in the expression of an individuals and the variance measured in bead level intensities of a probe/marker pair. Finally, these clusters are used to determine genotypes. The algorithm was then run on a dataset of 35,000 Icelandic individuals.

An association between the kinship and fertility of human couples

Previous studies have reported that related human couples tend to produce more children than unrelated couples but have been unable to determine whether this difference is biological or stems from socioeconomic variables. Our results, drawn from all known couples of the Icelandic population born between 1800 and 1965, show a significant positive association between kinship and fertility, with the greatest reproductive success observed for couples related at the level of third and fourth cousins. Owing to the relative socioeconomic homogeneity of Icelanders, and the observation of highly significant differences in the fertility of couples separated by very fine intervals of kinship, we conclude that this association is likely to have a biological basis.

The inheritance of rheumatoid arthritis in Iceland

OBJECTIVE

Rheumatoid arthritis (RA) is the most common form of inflammatory arthritis. Although there is a large body of evidence suggesting that RA is immune mediated, the etiology remains unresolved. Twin studies have shown disease concordance rates of approximately 15% in monozygotic twins and 4% in dizygotic twins, while the estimated risk ratio for siblings of RA patients ranges from 5 to 8. Our goal was to use genealogic data from Iceland to further investigate the genetic component of RA.

METHODS

Data were obtained from a population-based, computerized genealogy database that was developed to examine multigenerational relationships among individuals in the relatively homogeneous population of Iceland. Using an algorithm, the minimum founder test, we calculated the least number of founders required to account for a list of RA patients, and compared it with 1,000 sets of same-sized matched control groups. In addition, we estimated the kinship coefficient and risk ratios for relatives of the RA patients.

RESULTS

Several familial clustering tests demonstrated that the RA patients were more related to each other than were the average control set of Icelanders. A significantly fewer number of founders was necessary to account for our patient list than for the random sets of matched controls (P < 0.001), and the average pairwise identity-by-descent sharing was greater among the patients than among the control sets (P < 0.001). In addition, there was an increased risk of RA in first- and second-degree relatives of the patients; e.g., for siblings, the risk ratio was 4.38 (95% confidence interval 3.26-5.67), and for uncles/aunts, the risk ratio was 1.95 (95% confidence interval 1.52-2.43).

CONCLUSION

The familial component of RA is shown to extend beyond the nuclear family, thus providing stronger evidence for a significant genetic component to RA.

Inheritance of human longevity in Iceland

The idea that human longevity is influenced by genetic factors has recently received strong support from work on other species. On the basis of partial population studies and selected kinships, significant correlations between the ages of parents and offspring have been reported, and some but not all twin studies have confirmed that human longevity is moderately inherited. However, studies based upon a relatively small proportion of a population are susceptible to sampling error and selection bias. Here we report the use of a comprehensive population-based computerised genealogy database to examine multigenerational relationships among those who live to the 95th percentile in Iceland. We have developed a clustering tool which can generate large extended pedigrees connecting individuals from any list using the genealogy database. First degree relatives of those living to the 95th percentile are almost twice as likely to live to the 95th percentile compared with controls. Furthermore, we have developed an algorithm which we have named the Minimum Founder Test (MFT) to examine the degree of relatedness of any population-based list of individuals to estimate whether a trait has a familial component. The data indicate that there is a significant genetic component to longevity. In addition, age-specific death rates are significantly lower in the offspring of long-lived parents compared with controls, especially after age 70.