Myocarditis is an inflammatory disease of the cardiac muscle and is mainly caused by viral infections. Viral myocarditis has been proposed to be divided into 3 phases: the acute viral phase, the subacute immune phase, and the chronic cardiac remodeling phase. Although individualized therapy should be applied depending on the phase, no clinical or experimental studies have found biomarkers that distinguish between the 3 phases. Theiler’s murine encephalomyelitis virus belongs to the genus Cardiovirus and can cause myocarditis in susceptible mouse strains.
Methods and Results
Using this novel model for viral myocarditis induced with Theiler’s murine encephalomyelitis virus, we conducted multivariate analysis including echocardiography, serum troponin and viral RNA titration, and microarray to identify the biomarker candidates that can discriminate the 3 phases. Using C3H mice infected with Theiler’s murine encephalomyelitis virus on 4, 7, and 60 days post infection, we conducted bioinformatics analyses, including principal component analysis and k-means clustering of microarray data, because our traditional cardiac and serum assays, including 2-way comparison of microarray data, did not lead to the identification of a single biomarker. Principal component analysis separated heart samples clearly between the groups of 4, 7, and 60 days post infection. Representative genes contributing to the separation were as follows: 4 and 7 days post infection, innate immunity–related genes, such as Irf7 and Cxcl9; 7 and 60 days post infection, acquired immunity–related genes, such as Cd3g and H2-Aa; and cardiac remodeling–related genes, such as Mmp12 and Gpnmb.
Sets of molecules, not single molecules, identified by unsupervised principal component analysis, were found to be useful as phase-specific biomarkers.
computational biology; immunology; interferons; Picornaviridae infections; systems biology; T lymphocytes; transcriptome
Vascular Ehlers-Danlos syndrome; type III collagen; COL3A1; vascular inflammation; C-reactive protein
Blood pressure (BP) responses to dietary sodium and potassium intervention and cold pressor test (CPT) vary considerably among individuals. We aimed to identify novel genetic variants influencing individuals’ BP responses to dietary intervention and CPT.
Methods and Results
We conducted a genome-wide association study of BP responses in 1,881 Han Chinese and de novo genotyped top findings in 698 Han Chinese. Diet-feeding study included a 7-day low-sodium (51.3 mmol/day), a 7-day high-sodium (307.8 mmol/day), and a 7-day high-sodium plus potassium-supplementation (60 mmol/day). Nine BP measurements were obtained during baseline observation and each intervention period. The meta-analyses identified eight novel loci for BP phenotypes, which physically mapped in or near PRMT6 (P=7.29×10−9), CDCA7 (P=3.57×10−8), PIBF1 (P=1.78×10−9), ARL4C (P=1.86×10−8), IRAK1BP1 (P=1.44×10−10), SALL1 (P=7.01×10−13), TRPM8 (P=2.68×10−8), and FBXL13 (P=3.74×10−9). There was a strong dose-response relationship between the number of risk alleles of these independent SNPs and the risk of developing hypertension over 7.5-year follow-up in the study participants. Compared to those in the lowest quartile of risk alleles, odds ratios (95% confidence intervals) for those in the second, third and fourth quartiles were 1.39 (0.97, 1.99), 1.72 (1.19, 2.47), and 1.84 (1.29, 2.62), respectively (P=0.0003 for trend).
Our study identified 8 novel loci for BP responses to dietary sodium and potassium intervention and CPT. The effect size of these novel loci on BP phenotypes are much larger than those reported by the previously published studies. Furthermore, these variants predict the risk of developing hypertension among individuals with normal BP at baseline.
blood pressure; genomics; sodium; potassium
cerebral infarction; genetics; molecular epidemiology
Cardiac development is a complex process resulting in an integrated, multi-lineage tissue with developmental corruption in early embryogenesis leading to congenital heart disease. Interrogation of individual genes has provided the backbone for cardiac developmental biology, yet a comprehensive transcriptome derived from natural cardiogenesis is required to gauge innate developmental milestones.
Methods and Results
Stage-specific cardiac structures were dissected from eight distinctive mouse embryonic time points to produce genome-wide expressome analysis across cardiogenesis. In reference to this native cardiogenic expression roadmap, divergent iPSC-derived cardiac expression profiles were mapped from pro-cardiogenic 3-factor (SOX2, OCT4, KLF4) and less-cardiogenic 4-factor (plus c-MYC) reprogrammed cells. Expression of cardiac-related genes from 3F-iPSC differentiated in vitro at days 5 and 11 recapitulated expression profiles of natural embryos at days E7.5–E8.5 and E14.5–E18.5, respectively. In contrast, 4F-iPSC demonstrated incomplete cardiogenic gene expression profiles beginning at day 5 of differentiation. Differential gene expression within the pluripotent state revealed 23 distinguishing candidate genes among pluripotent cell lines with divergent cardiogenic potentials. A confirmed panel of 12 genes, differentially expressed between high and low cardiogenic lines, was transformed into a predictive score sufficient to discriminate individual iPSC lines according to relative cardiogenic potential.
Transcriptome analysis attuned to natural embryonic cardiogenesis provides a robust platform to probe coordinated cardiac specification and maturation from bioengineered stem cell-based model systems. A panel of developmental-related genes allowed differential prognosis of cardiogenic competency, thus prioritizing cell lines according to natural blueprint to streamline functional applications.
cardiac development; differentiation; embryonic development; transcriptome; embryonic stem cell
Human genomes harbor copy number variants (CNVs), regions of DNA gains or losses. While pathogenic CNVs are associated with congenital heart disease (CHD), their impact on clinical outcomes is unknown. This study sought to determine whether pathogenic CNVs among infants with single ventricle (SV) physiology were associated with inferior neurocognitive and somatic growth outcomes.
Methods and Results
Genomic DNAs from 223 subjects of two National Heart, Lung, and Blood Institute-sponsored randomized clinical trials with infants with SV CHD and 270 controls from The Cancer Genome Atlas project were analyzed for rare CNVs >300 kb using array comparative genomic hybridization. Neurocognitive and growth outcomes at 14 months from the CHD trials were compared among subjects with and without pathogenic CNVs. Putatively pathogenic CNVs, comprising 25 duplications and 6 deletions, had a prevalence of 13.9%, significantly greater than the 4.4% rate of such CNVs among controls. CNVs associated with genomic disorders were found in 13 cases but no control. Several CNVs likely to be causative of SV CHD were observed, including aberrations altering the dosage of GATA4, MYH11, and GJA5. Subjects with pathogenic CNVs had worse linear growth, and those with CNVs associated with known genomic disorders had the poorest neurocognitive and growth outcomes. A minority of children with pathogenic CNVs were noted to be dysmorphic on clinical genetics examination.
Pathogenic CNVs appear to contribute to the etiology of SV forms of CHD in at least 10% of cases, are clinically subtle but adversely affect outcomes in children harboring them.
copy number variant; congenital cardiac defect; outcome; hypoplastic left heart syndrome
The cardiac sodium channel SCN5A regulates atrioventricular
and ventricular conduction. Genetic variants in this gene are associated with PR and QRS
intervals. We sought to further characterize the contribution of rare and common coding
variation in SCN5A to cardiac conduction.
Methods and Results
In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted
Sequencing Study (CHARGE), we performed targeted exonic sequencing of
SCN5A (n=3699, European-ancestry individuals) and identified 4 common
(minor allele frequency >1%) and 157 rare variants. Common and rare
SCN5A coding variants were examined for association with PR and QRS intervals through
meta-analysis of European ancestry participants from CHARGE, NHLBI’s Exome
Sequencing Project (ESP, n=607) and the UK10K (n=1275) and by examining ESP
African-ancestry participants (N=972). Rare coding SCN5A variants in
aggregate were associated with PR interval in European and African-ancestry participants
(P=1.3×10−3). Three common variants were associated with PR
and/or QRS interval duration among European-ancestry participants and one among
African-ancestry participants. These included two well-known missense variants;
rs1805124 (H558R) was associated with PR and QRS shortening in European-ancestry
participants (P=6.25×10−4 and
P=5.2×10−3 respectively) and rs7626962 (S1102Y) was
associated with PR shortening in those of African ancestry
(P=2.82×10−3). Among European-ancestry participants, two
novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac
conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening
(P=3.35×10−7 and P=2.69×10−4
respectively), and rs6599230 was associated with PR shortening
By sequencing SCN5A, we identified novel common and rare
coding variants associated with cardiac conduction.
PR interval; QRS interval; genetics; sequencing; cohort
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3 and SPI1, has been associated in genome-wide association studies with fasting glucose (FG) and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced five gene regions at 11p11.2 to identify rare, potentially functional variants influencing FG or FI levels.
Method & Results
Sequencing (mean depth 38×) across 16.1kb in 3,566 non-diabetic individuals identified 653 variants, 79.9% of which were rare (MAF <1%) and novel. We analyzed rare variants in five gene regions with FI or FG using the Sequence Kernel Association Test (SKAT). At NR1H3, 53 rare variants were jointly associated with FI (p=2.73 × 10−3); of these, seven were predicted to have regulatory function and showed association with FI (p=1.28 × 10−3). Conditioning on two previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are more than two independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; MAF 0.00068), contributed 20.6% to the overall SKAT score at NR1H3, lies in intron 2 of NR1H3 and is a predicted binding site for FOXA1, a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.
Sequencing at 11p11.2- NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, appears to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.
fasting glucose; fasting insulin; chr11p11.2; target sequencing; next-generation sequencing
Histones are proteins that wrap DNA around in small spherical structures called nucleosomes. Histone modifications (HMs) refer to the post-translational modifications to the histone tails. At a particular genomic locus, each of these HMs can either be present or absent, and the combinatory patterns of the presence or absence of multiple HMs, or the ‘histone codes,’ are believed to co-regulate important biological processes. We aim to use raw data on HM markers at different genomic loci to (1) decode the complex biological network of HMs in a single region and (2) demonstrate how the HM networks differ in different regulatory regions. We suggest that these differences in network attributes form a significant link between histones and genomic functions.
Methods and Results
We develop a powerful graphical model under Bayesian paradigm. Posterior inference is fully probabilistic, allowing us to compute the probabilities of distinct dependence patterns of the HMs using graphs. Furthermore, our model-based framework allows for easy but important extensions for inference on differential networks under various conditions, such as the different annotations of the genomic locations (e.g., promoters versus insulators). We applied these models to ChIP-Seq data based on CD4+ T lymphocytes. The results confirmed many existing findings and provided a unified tool to generate various promising hypotheses. Differential network analyses revealed new insights on co-regulation of HMs of transcriptional activities in different genomic regions.
The use of Bayesian graphical models and borrowing strength across different conditions provide high power to infer histone networks and their differences.
gene expression/regulation; gene regulation; epigenetics; statistics; statistical model; graph; network; nucleosome
Variants at the 9p21 locus associate with the risk of coronary artery disease (CAD) or myocardial infarction (MI). However, atherosclerotic plaque deposition is distinct from MI (plaque rupture and thrombosis) and recent studies showed no association between these variants and MI in patients with preexisting CAD. We performed haplotype analysis at the 9p21 locus to test whether haplotypes at distinct linkage disequilibrium (LD) blocks predict these phenotypes.
Methods and Results
Using 24 single-nucleotide polymorphisms genotyped in Caucasians without diabetes, we reconstructed haplotypes at the 9p21 locus. Angiographic CAD/MI patients had at least 1 epicardial stenosis > 50% (n=2352) whereas controls were asymptomatic and over age 60 (n=2116). For CAD patients, regression models examined association of haplotypes with initial age of symptomatic CAD, number of diseased vessels, and history of MI. In the case-control study, only haplotypes at one block tagged by rs1333049 associated with CAD more so than MI. These haplotypes also associated with early onset of CAD (β=−0.13 p=1.37*10−4) and disease severity (β=0.1823, p=0.006), but not with prevalent MI among CAD patients. In contrast, haplotypes at another block tagged by rs518394 associated with prevalent MI (β=0.239, p= 2.05*10−4), but remarkably these are inversely associated with disease severity (β=−0.196, p=0.003). This MI association was replicated in the Cleveland Clinic GeneBank premature CAD cohort (n=1385, β=0.207, p= 0.019).
Variants/haplotypes at two blocks are distinguished at 9p21, those at one block predispose to atherosclerosis whereas those at the other predispose to MI among individuals with preexisting CAD.
coronary angiography; haplotype; myocardial infarction; atherosclerosis; chromosome 9p21
editorials; long-QT syndrome; ion channels; genetics
Long-QT Syndrome (LQTS) is characterized by such striking clinical heterogeneity, that even among family members carrying the same mutation, clinical outcome can range between sudden death to no symptoms. We investigated the role of genetic variants as modifiers of risk for cardiac events in LQTS patients.
Methods and Results
In a matched case-control study including 112 LQTS patient duos from France, Italy and Japan, 25 polymorphisms were genotyped based on either their association with QTc duration in healthy populations or on their role in adrenergic responses. The duos were composed of two relatives harboring the same heterozygous KCNQ1 or KCNH2 mutation; one with cardiac events and one asymptomatic and untreated. The findings were then validated in two independent founder populations totaling 174 symptomatic and 162 asymptomatic LQTS patients, and a meta-analysis was performed. The KCNQ1 rs2074238 T-allele was significantly associated with a decreased risk of symptoms 0.34 [0.19 – 0.61] (p<0.0002) and with shorter QTc (p<0.0001) in the combined discovery and replication cohorts.
We provide evidence that the KCNQ1 rs2074238 polymorphism is an independent risk modifier with the minor T-allele conferring protection against cardiac events in LQTS patients. This finding is a step toward a novel approach for risk stratification in LQTS patients.
genetics; association studies; long QT syndrome; risk factor; polymorphism; ion channel
Massively parallel sequencing to identify rare variants is widely practiced in medical research and in the clinic. Genome and exome sequencing can identify the genetic cause of a disease (primary results), but can also identify pathogenic variants underlying diseases that are not being sought (secondary or incidental results). A major controversy has developed surrounding the return of secondary results to research participants. We have piloted a method to analyze exomes to identify participants at-risk for cardiac arrhythmias, cardiomyopathies or sudden death.
Methods and Results
Exome sequencing was performed on 870 participants not selected for arrhythmia, cardiomyopathy, or a family history of sudden death. Exome data from 22 cardiac arrhythmia and 41 cardiomyopathy-associated genes were analyzed using an algorithm that filtered results on genotype quality, frequency, and database information. We identified 1367 variants in the cardiomyopathy genes and 360 variants in the arrhythmia genes. Six participants had pathogenic variants associated with dilated cardiomyopathy (n=1), hypertrophic cardiomyopathy (n=2), left ventricular noncompaction (n=1) or long QT syndrome (n=2). Two of these participants had evidence of cardiomyopathy and one had left ventricular noncompaction on ECHO. Three participants with likely pathogenic variants had prolonged QTc. Family history included unexplained sudden death among relatives.
Approximately 0.5% of participants in this study had pathogenic variants in known cardiomyopathy or arrhythmia genes. This high frequency may be due to self-selection, false positives, or underestimation of the prevalence of these conditions. We conclude that clinically important cardiomyopathy and dysrhythmia secondary variants can be identified in unselected exomes.
arrhythmia (heart rhythm disorders); cardiomyopathy; cardiovascular genomics; genetic heart disease; genetic variation; arrhythmia; genetics; human; genomic medicine
Whole exome sequencing (WES) is a powerful technique for Mendelian disease gene discovery. However, variant prioritization remains a challenge. We applied WES to identify the causal variant in a large family with familial dilated cardiomyopathy (DMC) of unknown etiology.
Methods and Results
A large family with autosomal dominant, familial DCM was identified. Exome capture and sequencing was performed in 3 remotely related, affected subjects predicted to share <0.1% of their genomes by descent. Shared variants were filtered for rarity, evolutionary conservation, and predicted functional significance, and remaining variants were filtered against 71 locally generated exomes. Variants were also prioritized using the Variant Annotation Analysis and Search Tool (VAAST). Final candidates were validated by Sanger sequencing and tested for segregation. There were 664 shared heterozygous nonsense, missense, or splice site variants, of which 26 were rare (minor allele frequency ≤ 0.001 or not reported) in two public databases. Filtering against internal exomes reduced the number of candidates to 2, and of these, a single variant (c.1907 G>A) in RBM20, segregated with disease status and was absent in unaffected internal reference exomes. Bioinformatic prioritization with VAAST supported this result.
WES of remotely related DCM subjects from a large, multiplex family, followed by systematic filtering, identified a causal RBM20 mutation without the need for linkage analysis.
genetic heart disease; exome; congestive heart failure
A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients.
Methods and Results
In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for gender, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T>C (p < 0.001) and ABCG2 c.421C>A (p < 0.01) were important to rosuvastatin concentration (adjusted R2 = 0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A>G (p < 0.01) and c.521T>C (p < 0.05), and 4β-hydroxycholesterol, a CYP3A activity marker (adjusted R2 = 0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient's risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile.
Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine if this approach reduces incidence of statin-myopathy.
statin therapy; pharmacogenetics; pharmacokinetics; drug transporters
The genetic mechanisms of atrial fibrillation (AF) remain incompletely understood. Previous differential expression studies in AF were limited by small sample size and provided limited understanding of global gene networks, prompting the need for larger-scale, network-based analyses.
Methods and Results
Left atrial tissues from Cleveland Clinic cardiac surgery patients were assayed using Illumina Human HT-12 mRNA microarrays. The dataset included three groups based on cardiovascular co-morbidities: mitral valve (MV) disease without coronary artery disease (CAD) (n=64); CAD without MV disease (n=57); and lone AF (LAF) (n=35). Weighted gene co-expression network analysis was conducted in the MV group to detect modules of correlated genes. Module preservation was assessed in the other two groups. Module eigengenes were regressed on AF severity or atrial rhythm at surgery. Modules whose eigengenes correlated with either AF phenotype were analyzed for gene content. 14 modules were detected in the MV group; all were preserved in the other two groups. One module (124 genes) was associated with AF severity and atrial rhythm across all groups. Its top hub gene, RCAN1, is implicated in calcineurin-dependent signaling and cardiac hypertrophy. Another module (679 genes) was associated with atrial rhythm in the MV and CAD groups. It was enriched with cell signaling genes and contained cardiovascular developmental genes including TBX5.
Our network-based approach found two modules strongly associated with AF. Further analysis of these modules may yield insight into AF pathogenesis by providing novel targets for functional studies.
atrial fibrillation; genetics, bioinformatics; genetics, microarrays; arrhythmias; gene network; gene co-expression
next-gen sequencing; titin; dilated cardiomyopathy; exome; cardiomyopathy; genetics; human
High-density lipoprotein cholesterol (HDL-C) and triglycerides are cardiovascular risk factors susceptible to lifestyle behavior modification and genetics. We hypothesized that genetic variants identified by genome-wide association studies (GWASs) as associated with HDL-C or triglyceride levels will modify 1-year treatment response to an intensive lifestyle intervention (ILI), relative to a usual care of diabetes support and education (DSE).
Methods and Results
We evaluated 82 SNPs, representing 31 loci demonstrated by GWAS to be associated with HDL-C and/or triglycerides, in 3,561 participants who consented for genetic studies and met eligibility criteria. Variants associated with higher baseline HDL-C levels, cholesterol ester transfer protein (CETP) rs3764261 and hepatic lipase (LIPC) rs8034802, were found to be associated with HDL-C increases with ILI (p=0.0038 and 0.013, respectively) and had nominally significant treatment interactions (p=0.047 and 0.046, respectively). The fatty acid desaturase-2 (FADS-2) rs1535 variant, associated with low baseline HDL-C (p=0.017), was associated with HDL-C increases with ILI (0.0037) and had a nominal treatment interaction (p= 0.035). ApoB (rs693) and LIPC (rs8034802) SNPs showed nominally significant associations with HDL-C and triglyceride changes with ILI and a treatment interaction (p<0.05). A PGS1 SNP (rs4082919) showed the most significant triglyceride treatment interaction in the full cohort (p=0.0009).
This is the first study to identify genetic variants modifying lipid responses to a randomized lifestyle behavior intervention in overweight/obese diabetic individuals. The effect of genetic factors on lipid changes may differ from the effects on baseline lipids and are modifiable by behavioral intervention.
genomics; physiological; cholesterylester transfer protein genetics; triglycerides; behavior modification; lipoprotein
Common variation at chromosome 9p21 (marked by rs10757278 or rs1333049) is associated with coronary artery disease (CAD) and peripheral vascular disease. A decreasing effect at older age was suggested, and effects on long-term mortality are unclear. We estimated 9p21 associations with CAD and all-cause mortality in a CAD diagnosis–free older population. We also estimated classification gains on adding the variant to the Framingham Risk Score (FRS) for CAD.
Methods and Results
DNA was from an Established Populations for Epidemiological Study of the Elderly–Iowa cohort from 1988 (participants >71 years), with death certificates obtained to 2008 for 92% of participants. Cox regression models were adjusted for confounders and CAD risk factors. Of 1095 CAD diagnosis–free participants, 52% were heterozygous (CG) and 22% were homozygous (CC) for the risk C allele rs1333049. Unadjusted CAD-attributed death rates in the CC group were 30 vs 22 per 1000 person-years for the GG group. The C allele was associated with all-cause (hazard ratio, 1.19; 95% CI, 1.08–1.30) and CAD (hazard ratio, 1.29; 95% CI, 1.08–1.56) mortality, independent of CAD risk factors. There was no association with stroke deaths. Variant associations with CAD mortality were attenuated after the age of 80 years (age-interaction term P=0.05). In age group 71 to 80 years, FRS classified as high risk 21% of respondents who died of CAD within 10 years; adding 9p21 identified 27% of respondents.
In 71- to 80-year-old subjects free of CAD diagnoses, 9p21 is associated with excess mortality, mainly attributed to CAD mortality. Adding 9p21 to the FRS may improve the targeting of CAD prevention in older people, but validation in independent samples is needed for confirmation.
coronary artery disease; genetic variation; myocardial infarction; survival; Framingham Risk Score
Long QT syndrome (LQTS) is the most common cardiac channelopathy with 15 elucidated LQTS-susceptibility genes. Approximately 20% of LQTS cases remain genetically elusive.
Methods and Results
We combined whole exome sequencing (WES) and bioinformatic/systems biology to identify the pathogenic substrate responsible for non-syndromic, genotype-negative, autosomal dominant LQTS in a multigenerational pedigree and established the spectrum and prevalence of variants in the elucidated gene among a cohort of 102 unrelated patients with “genotype-negative/phenotype-positive” LQTS. WES was utilized on three members within a genotype-negative/phenotype-positive family. Genomic triangulation combined with bioinformatic tools and ranking algorithms led to the identification of a CACNA1C mutation. This mutation, Pro857Arg-CACNA1C, co-segregated with the disease within the pedigree, was ranked by three disease-network algorithms as the most probable LQTS-susceptibility gene, and involves a conserved residue localizing to the PEST domain in the II–III linker. Functional studies reveal that Pro857Arg-CACNA1C leads to a gain-of-function with increased ICa,L and increased surface membrane expression of the channel compared to wildtype. Subsequent mutational analysis identified 3 additional variants within CACNA1C in our cohort of 102 unrelated cases of genotype-negative/phenotype-positive LQTS. Two of these variants also involve conserved residues within Cav1.2’s PEST domain.
This study provides evidence that coupling WES and bioinformatic/systems biology is an effective strategy for the identification of potential disease causing genes/mutations. The identification of a functional CACNA1C mutation co-segregating with disease in a single pedigree suggests that CACNA1C perturbations may underlie autosomal dominant LQTS in the absence of Timothy syndrome.
arrhythmia; calcium; genetics; ion channel; long QT syndrome
The transcription factor NKX2-5 is crucial for heart development and mutations in this gene have been implicated in diverse congenital heart diseases (CHD) and conduction defects (CD) in mouse models and humans. Whether NKX2-5 mutations have a role in adult-onset heart disease is unknown.
Methods and Results
Mutation screening was performed in 220 probands with adult-onset dilated cardiomypathy (DCM). Six NKX2-5 coding sequence variants were identified, including 3 non-synonymous variants. A novel heterozygous mutation, I184M, located within the NKX2-5 homeodomain (HD), was identified in one family. A subset of family members had CHD, but there was an unexpectedly high prevalence of DCM. Functional analysis of I184M in vitro demonstrated a striking increase in protein expression when transfected into COS-7 cells or HL-1 cardiomyocytes, due to reduced degradation by the ubiquitin-proteasome system (UPS). In functional assays, DNA binding activity of I184M was reduced, resulting in impaired activation of target genes, despite increased expression levels of mutant protein.
Certain NKX2-5 HD mutations show abnormal protein degradation via the UPS and partially impaired transcriptional activity. We propose that this class of mutation can impair heart development and mature heart function, and contribute to NKX2-5-related cardiomyopathies with graded severity.
dilated cardiomyopathy; transcription factors; gene mutations; ubiquitin-proteasome system; NKX2-5
Natural selection shapes many human genes, including some related to complex diseases. Understanding how selection affects genes, especially pleiotropic ones, may be important in evaluating disease associations and the role played by environmental variation. This may be of particular interest for genes with antagonistic roles that cause divergent patterns of selection. The lectin like low-density lipoprotein 1 receptor (LOX-1), encoded by OLR1, is exemplary. It has antagonistic functions in the cardiovascular and immune systems as the same protein domain binds oxidized LDL and bacterial cell wall proteins - the former contributing to atherosclerosis, the latter presumably protecting from infection. We studied patterns of selection in this gene, in humans and non-human primates, to determine whether variable selection can lead to conflicting results in CVD association studies.
Methods and Results
We analyzed sequences from 11 non-human primate species as well as SNP and sequence data from multiple human populations. Results indicate that the derived allele is favored across primate lineages (probably due to recent positive selection). However, both the derived and ancestral alleles were maintained in human populations, especially European ones (possibly due to balancing selection derived from LOX-1's dual roles). Balancing selection likely reflects response to diverse environmental pressures among humans.
These data indicate that differential selection patterns, within and between species, in OLR1 render association studies difficult to replicate even if the gene is etiologically connected to CVD. Selection analyses can identify genes exhibiting gene-environment interactions critical for unraveling disease association.
lipoproteins; immune system; genetics; LOX-1 receptor; evolution
Left ventricular hypertrophy (LVH) typically manifests during or after adolescence in sarcomere mutation carriers at risk for developing hypertrophic cardiomyopathy. Guidelines recommend serial imaging of mutation carriers without LVH (G+/LVH−) to monitor for phenotypic evolution, but the optimal strategy is undefined. Compared with echocardiography (echo), cardiac MRI (CMR) offers improved endocardial visualization and potential to assess scar. However, the incremental advantage offered by CMR for early diagnosis of hypertrophic cardiomyopathy is unclear. Therefore, we systematically compared echo and CMR in G+/LVH− subjects.
Methods and Results
A total of 40 sarcomere mutation carriers with normal echo wall thickness (<12 mm or z score <2.5 in children) underwent concurrent CMR. Mean age was 21.7±11.1 years, 55% were female. If left ventricular wall thickness seemed nonuniform, the size and location of relatively thickened segments were noted. Late gadolinium enhancement was assessed with CMR. Diagnostic agreement between echo and CMR was good (90%), although CMR measurements of left ventricular wall thickness were ≈19% lower than echo. Four subjects had mild hypertrophy (12.6–14 mm; ≤2 segments) appreciated by CMR but not echo. No subjects had late gadolinium enhancement. During median 35-month follow-up, 2 subjects developed overt hypertrophic cardiomyopathy, including 1 with mild LVH by CMR at baseline.
Echo is unlikely to miss substantial LVH; however, CMR identified mild hypertrophy in ≈10% of mutation carriers with normal echo wall thickness. CMR may be a useful adjunct in hypertrophic cardiomyopathy family screening, particularly in higher risk situations, or if echocardiographic images are suboptimal or suggest borderline LVH.
cardiac MRI; cardiomyopathy, hypertrophic; echocardiography; genetics; humans