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Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes., Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders., Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10 -7 ). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10 -3 ) and prevalent type 2 diabetes (OR Val&#95;PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10 -27 ). Furthermore, Val&#95;PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HR Val&#95;PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10 -15 ), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose)., Conclusions/interpretation: In this study we have shown that the Val&#95;PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.

Background and Aim: Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use., Methods: Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation., Results: Polygenic risk scores for schizophrenia were significantly (α<0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of r g =0.22 (SE=0.07, p=0.003) between schizophrenia and lifetime cannabis use., Conclusions: Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development., Competing Interests: Dr. BM Psaty serves on the DSMB for a clinical trial of a device funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Steno Diabetes Center and Synlab Holding Deutschland GmbH provided support in the form of salaries for authors T.S.A. and W.M. respectively, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Human aggression encompasses a wide range of behaviors and is related to many psychiatric disorders. We introduce the different classification systems of aggression and related disorders as a basis for discussing biochemical biomarkers and then present an overview of studies in humans (published between 1990 and 2015) that reported statistically significant associations of biochemical biomarkers with aggression, DSM-IV disorders involving aggression, and their subtypes. The markers are of different types, including inflammation markers, neurotransmitters, lipoproteins, and hormones from various classes. Most studies focused on only a limited portfolio of biomarkers, frequently a specific class only. When integrating the data, it is clear that compounds from several biological pathways have been found to be associated with aggressive behavior, indicating complexity and the need for a broad approach. In the second part of the paper, using examples from the aggression literature and psychiatric metabolomics studies, we argue that a better understanding of aggression would benefit from a more holistic approach such as provided by metabolomics. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.

Objective: Metformin is used as a first-line oral treatment for type 2 diabetes (T2D). However, the underlying mechanism is not fully understood. Here, we aimed to comprehensively investigate the pleiotropic effects of metformin., Research Design and Methods: We analyzed both metabolomic and genomic data of the population-based KORA cohort. To evaluate the effect of metformin treatment on metabolite concentrations, we quantified 131 metabolites in fasting serum samples and used multivariable linear regression models in three independent cross-sectional studies (n = 151 patients with T2D treated with metformin [mt-T2D]). Additionally, we used linear mixed-effect models to study the longitudinal KORA samples (n = 912) and performed mediation analyses to investigate the effects of metformin intake on blood lipid profiles. We combined genotyping data with the identified metformin-associated metabolites in KORA individuals (n = 1,809) and explored the underlying pathways., Results: We found significantly lower (P < 5.0E-06) concentrations of three metabolites (acyl-alkyl phosphatidylcholines [PCs]) when comparing mt-T2D with four control groups who were not using glucose-lowering oral medication. These findings were controlled for conventional risk factors of T2D and replicated in two independent studies. Furthermore, we observed that the levels of these metabolites decreased significantly in patients after they started metformin treatment during 7 years' follow-up. The reduction of these metabolites was also associated with a lowered blood level of LDL cholesterol (LDL-C). Variations of these three metabolites were significantly associated with 17 genes (including FADS1 and FADS2) and controlled by AMPK, a metformin target., Conclusions: Our results indicate that metformin intake activates AMPK and consequently suppresses FADS, which leads to reduced levels of the three acyl-alkyl PCs and LDL-C. Our findings suggest potential beneficial effects of metformin in the prevention of cardiovascular disease., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Background: Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods., Methods: The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22,193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes., Results: There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9.10(-7)), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9.10(-19)) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3.10(-107)). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD., Conclusions: Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke., (© The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Metabolomics is the comprehensive study of metabolites, which are the substrates, intermediate, and end products of cellular metabolism. The heritability of the concentrations of circulating metabolites bears relevance for evaluating their suitability as biomarkers for disease. We report aspects of familial resemblance for the concentrations in human serum of more than 100 metabolites, measured using a targeted metabolomics platform. Age- and sex-corrected monozygotic twin correlations, midparent-offspring regression coefficients, and spouse correlations in subjects from two independent cohorts (Netherlands Twin Register and Leiden Longevity Study) were estimated for each metabolite. In the Netherlands Twin Register subjects, who were largely fasting, we found significant monozygotic twin correlations for 121 out of 123 metabolites. Heritability was confirmed by midparent-offspring regression. For most detected metabolites, the correlations between spouses were considerably lower than those between twins, indicating a contribution of genetic effects to familial resemblance. Remarkably high heritability was observed for free carnitine (monozygotic twin correlation 0.66), for the amino acids serine (monozygotic twin correlation 0.77) and threonine (monozygotic twin correlation 0.64), and for phosphatidylcholine acyl-alkyl C40:3 (monozygotic twin correlation 0.77). For octenoylcarnitine, a consistent point estimate of approximately 0.50 was found for the spouse correlations in the two cohorts as well as for the monozygotic twin correlation, suggesting that familiality for this metabolite is explained by shared environment. We conclude that for the majority of metabolites targeted by the used metabolomics platform, the familial resemblance of serum concentrations is largely genetic. Our results contribute to the knowledge of the heritability of fasting serum metabolite concentrations, which is relevant for biomarker research.

Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

Over the past 25 years, the Adult Netherlands Twin Register (ANTR) has collected a wealth of information on physical and mental health, lifestyle, and personality in adolescents and adults. This article provides an overview of the sources of information available, the main research findings, and an outlook for the future. Between 1991 and 2012, longitudinal surveys were completed by twins, their parents, siblings, spouses, and offspring. Data are available for 33,957 participants, with most individuals having completed two or more surveys. Smaller projects provided in-depth phenotyping, including measurements of the autonomic nervous system, neurocognitive function, and brain imaging. For 46% of the ANTR participants, DNA samples are available and whole genome scans have been obtained in more than 11,000 individuals. These data have resulted in numerous studies on heritability, gene x environment interactions, and causality, as well as gene finding studies. In the future, these studies will continue with collection of additional phenotypes, such as metabolomic and telomere length data, and detailed genetic information provided by DNA and RNA sequencing. Record linkage to national registers will allow the study of morbidity and mortality, thus providing insight into the development of health, lifestyle, and behavior across the lifespan.

Twin and family studies are typically used to elucidate the relative contribution of genetic and environmental variation to phenotypic variation. Here, we apply a quantitative genetic method based on hierarchical clustering, to blood plasma lipidomics data obtained in a healthy cohort consisting of 37 monozygotic and 28 dizygotic twin pairs, and 52 of their biological nontwin siblings. Such data are informative of the concentrations of a wide range of lipids in the studied blood samples. An important advantage of hierarchical clustering is that it can be applied to a high-dimensional 'omics' type data, whereas the use of many other quantitative genetic methods for analysis of such data is hampered by the large number of correlated variables. For this study we combined two lipidomics data sets, originating from two different measurement blocks, which we corrected for block effects by 'quantile equating'. In the analysis of the combined data, average similarities of lipidomics profiles were highest between monozygotic (MZ) cotwins, and became progressively lower between dizygotic (DZ) cotwins, among sex-matched nontwin siblings and among sex-matched unrelated participants, respectively. Our results suggest that (1) shared genetic background, shared environment, and similar age contribute to similarities in blood plasma lipidomics profiles among individuals; and (2) that the power of quantitative genetic analyses is enhanced by quantile equating and combination of data sets obtained in different measurement blocks.

The classical twin study has been a powerful heuristic in biomedical, psychiatric and behavioural research for decades. Twin registries worldwide have collected biological material and longitudinal phenotypic data on tens of thousands of twins, providing a valuable resource for studying complex phenotypes and their underlying biology. In this Review, we consider the continuing value of twin studies in the current era of molecular genetic studies. We conclude that classical twin methods combined with novel technologies represent a powerful approach towards identifying and understanding the molecular pathways that underlie complex traits.

Combination of data sets from different objects (for example, from two groups of healthy volunteers from the same population) that were measured on a common set of variables (for example, metabolites or peptides) is desirable for statistical analysis in "omics" studies because it increases power. However, this type of combination is not directly possible if nonbiological systematic differences exist among the individual data sets, or "blocks". Such differences can, for example, be due to small analytical changes that are likely to accumulate over large time intervals between blocks of measurements. In this article we present a data transformation method, that we will refer to as "quantile equating", which per variable corrects for linear and nonlinear differences in distribution among blocks of semiquantitative data obtained with the same analytical method. We demonstrate the successful application of the quantile equating method to data obtained on two typical metabolomics platforms, i.e., liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy. We suggest uni- and multivariate methods to evaluate similarities and differences among data blocks before and after quantile equating. In conclusion, we have developed a method to correct for nonbiological systematic differences among semiquantitative data blocks and have demonstrated its successful application to metabolomics data sets.

Background and Purpose: Normal limits of the spatial QRS-T angle and spatial ventricular gradient (SVG) are only available from Frank vectorcardiograms (VCGs) of male subjects. We determined normal limits for these variables derived from standard 12-lead electrocardiograms (ECGs) of 660 male and female students aged 18 to 29 years., Methods: A computer algorithm was used that constructed approximated VCG leads by inverse Dower matrix transformation of the 12-lead ECG and subsequently calculated the spatial QRS-T angle, SVG magnitude, and orientation., Results: In female subjects, the QRS-T angle was more acute (females, 66 degrees +/- 23 degrees; normal, 20 degrees-116 degrees; males, 80 degrees +/- 24 degrees; normal, 30 degrees-130 degrees; P < .001), and the SVG magnitude was smaller (females, 81 +/- 23 mV x ms; normal, 39-143 mV x ms; males, 110 +/- 29 mV x ms; normal, 59-187 mV x ms; P < .001) than in male subjects. The male SVG magnitude in our study was larger than that computed in Frank VCGs (79 +/- 28 mV.ms; P < .001)., Conclusions: The spatial QRS-T angle and SVG depend strongly on sex. Furthermore, normal limits of SVG derived from Frank VCGs differ markedly from those derived from VCGs synthesized from the standard ECG. As nowadays, VCGs are usually synthesized from the 12-lead ECG; normal limits derived from the standard ECG should preferably be used.

Electrocardiograms (ECGs) made with Mason-Likar electrode configuration (ML-ECGs) show well-known differences from standard 12-lead ECGs (Std-ECGs). We recorded, simultaneously, Std-ECGs and ML-ECGs in 180 subjects. Using these ECGs, 8 x 8 individual and general conversion matrices were created by linear regression, and standard ECGs were reconstructed from ML-ECGs using these matrices. The performance of the matrices was assessed by the root mean square differences between the original Std-ECGs and the reconstructed standard ECGs, by the differences in major ECG parameters, and by comparison of computer-generated diagnostic statements. As a result, we conclude that, based on the root mean square differences, reconstructions with 8 x 8 individual matrices perform significantly better than reconstructions with the group matrix and perform equally well with respect to the calculation of major electrocardiographic parameters, which gives an improved reliability of the QRS frontal axis and the maximal QRS and T amplitudes. Both types of matrices were able to reverse the underdiagnosis of inferior myocardial infarctions and the erroneous statements about the QRS frontal axis that arose in the ECGs that were made by using the Mason-Likar electrode positions.

Objective: To assess the effect of pulmonary valve replacement (PVR) on the repolarization of patients with tetralogy of Fallot., Background: Pulmonary valve regurgitation may cause right ventricular failure in adult patients with Fallot's tetralogy. In these patients, prolonged depolarization and disturbed repolarization are associated with ventricular arrhythmias and sudden cardiac death., Methods: Thirty Fallot patients (age 32+/-9 years, 19 male) eligible for PVR were studied with cardiac magnetic resonance imaging (CMR) before and 6 months after PVR. Electrocardiograms obtained during initial and follow-up CMR were analyzed and occurrence of ventricular arrhythmias was studied., Results: Right ventricular end-diastolic volume (RV EDV) decreased from 322+/-87 to 215+/-57 ml after PVR (P<0.0001). The spatial QRS-T angle normalized from 117+/-34 to 100+/-35 degrees , P=0.0004 (normal angle <105 degrees). QT dispersion and T-wave complexity did not change significantly. T-wave amplitude decreased from 376+/-121 to 329+/-100 microV (P=0.01). T-wave area decreased from 43+/-15 to 38+/-13 microV s (P=0.02). Decreases in T-wave amplitude and area were most prominent in the right precordial leads overlying the RV. Three patients had sustained ventricular arrhythmias and one patient died suddenly. These patients had a QRS duration >160 ms. No severe ventricular arrhythmias were found in patients with a RV EDV <220 ml, QRS-T angle <100 degrees , QT dispersion <60 ms or T-wave complexity <0.30., Conclusion: Normal repolarization indices may be associated with the absence of severe ventricular arrhythmias. PVR in Fallot patients with dilated right ventricles has a beneficial effect on electrocardiographic indices of repolarization heterogeneity.

Differences in genetic background and/or environmental exposure among individuals are expected to give rise to differences in measurable characteristics, or phenotypes. Consequently, genetic resemblance and similarities in environment should manifest as similarities in phenotypes. The metabolome reflects many of the system properties, and is therefore an important part of the phenotype. Nevertheless, it has not yet been examined to what extent individuals sharing part of their genome and/or environment indeed have similar metabolomes. Here we present the results of hierarchical clustering of blood plasma lipid profile data obtained by liquid chromatography-mass spectrometry from 23 healthy, 18-year-old twin pairs, of which 21 pairs were monozygotic, and 8 of their siblings. For 13 monozygotic twin pairs, within-pair similarities in relative concentrations of the detected lipids were indeed larger than the similarities with any other study participant. We demonstrate such high coclustering to be unexpected on basis of chance. The similarities between dizygotic twins and between nontwin siblings, as well as between nonfamilial participants, were less pronounced. In a number of twin pairs, within-pair dissimilarity of lipid profiles positively correlated with increased blood plasma concentrations of C-reactive protein in one twin. In conclusion, this study demonstrates that in healthy individuals, the individual genetic background contributes to the blood plasma lipid profile. Furthermore, lipid profiling may prove useful in monitoring health status, for example, in the context of personalized medicine.

The study aim was to assess three-dimensional electrocardiogram (ECG) changes during development of pulmonary arterial hypertension (PAH). PAH was induced in male Wistar rats (n = 23) using monocrotaline (MCT; 40 mg/kg sc). Untreated healthy rats served as controls (n = 5). ECGs were recorded with an orthogonal three-lead system on days 0, 14, and 25 and analyzed with dedicated computer software. In addition, left ventricular (LV)-to-right ventricular (RV) fractional shortening ratio was determined using echocardiography. Invasively measured RV systolic pressure was 49 (SD 10) mmHg on day 14 and 64 (SD 10) mmHg on day 25 vs. 25 (SD 2) mmHg in controls (both P < 0.001). Baseline ECGs of controls and MCT rats were similar, and ECGs of controls did not change over time. In MCT rats, ECG changes were already present on day 14 but more explicit on day 25: increased RV electromotive forces decreased mean QRS-vector magnitude and changed QRS-axis orientation. Important changes in action potential duration distribution and repolarization sequence were reflected by a decreased spatial ventricular gradient magnitude and increased QRS-T spatial angle. On day 25, LV-to-RV fractional shortening ratio was increased, and RV hypertrophy was found, but not on day 14. In conclusion, developing PAH is characterized by early ECG changes preceding RV hypertrophy, whereas severe PAH is marked by profound ECG changes associated with anatomical and functional changes in the RV. Three-dimensional ECG analysis appears to be very sensitive to early changes in RV afterload.

The ventricular gradient, a notion conceived by Wilson et al during the 1930s, has contributed considerably to a better understanding of the ECG manifestations of the cardiac repolarization process. The power of the ventricular gradient is its ability to assess the primary factors that contribute to the T wave (i.e., heterogeneity of action potential morphology throughout the ventricles) in the presence of secondary factors contributing to the T wave (i.e., heterogeneity in ventricular depolarization instants). Where T-wave morphology is an ECG expression of heterogeneity of the repolarization, the ventricular gradient discriminates between primary or secondary causes of such heterogeneity. Besides the spatial ventricular gradient (Burger's three-dimensional elaboration of Wilson's two-dimensional concept), body surface mapping of local components of the ventricular gradient has emerged as a technique for assessing local ventricular action potential duration heterogeneity. The latter is believed to contribute to localization of arrhythmogenic areas in the heart. The spatial ventricular gradient, which can be computed on the basis of a regular routine ECG and does not require body surface mapping, aims to assess the overall heterogeneity of ventricular action potential morphology. This review addresses the nature and diagnostic potential of the spatial ventricular gradient. The main focus is the role of the spatial ventricular gradient in ECG assessment of dispersion of repolarization, a key factor in arrhythmogeneity.

Background: Proarrhythmic effects of cardiac resynchronization therapy (CRT) as a result of increased transmural dispersion of repolarization (TDR) induced by left ventricular (LV) epicardial pacing in a subset of vulnerable patients have been reported. The possibility of identifying these patients by ECG repolarization indices has been suggested., Objectives: The purpose of this study was to test whether repolarization indices on the ECG can be used to measure dispersion of repolarization during pacing., Methods: CRT devices of 28 heart failure patients were switched among biventricular, LV, and right ventricular (RV) pacing. ECG indices proposed to measure dispersion of repolarization were calculated. The effects of CRT on repolarization were simulated in ECGSIM, a mathematical model of electrocardiogram genesis. TDR was calculated as the difference in repolarization time between the epicardial and endocardial nodes of the heart model., Patients: The interval from the apex to the end of the T wave was shorter during biventricular pacing (102 +/- 18 ms) and LV pacing (106 +/- 21 ms) than during RV pacing (117 +/- 22 ms, P < or =.005). T-wave amplitude and area were low during biventricular pacing (287 +/- 125 microV and 56 +/- 22 microV.s, respectively, P = .0006 vs RV pacing). T-wave complexity was high during biventricular pacing (0.42 +/- 0.26, P = .004 vs RV pacing). Simulations: Repolarization patterns were highly similar to the preceding depolarization patterns. The repolarization patterns of different pacing modes explained the observed magnitudes of the ECG repolarization indices. Average and local TDR were not different between pacing modes., Conclusion: In patients treated with CRT, ECG repolarization indices are related to pacing-induced activation sequences rather than transmural dispersion. TDR during biventricular and LV pacing is not larger than TDR during conventional RV endocardial pacing.

Introduction: Repolarization heterogeneity (RH) is functionally linked to dispersion in refractoriness and to arrhythmogenicity. In the current study, we validate several proposed electrocardiogram (ECG) indices for RH: T-wave amplitude, -area, -complexity, and -symmetry ratio, QT dispersion, and the Tapex-end interval (the latter being an index of transmural dispersion of the repolarization (TDR))., Methods and Results: We used ECGSIM, a mathematical simulation model of ECG genesis in a human thorax, and varied global RH by increasing the standard deviation (SD) of the repolarization instants from 20 (default) to 70 msec in steps of 10 msec. T-wave amplitude, -area, -symmetry, and Tapex-end depended linearly on SD. T-wave amplitude increased from 275 +/- 173 to 881 +/- 456 muV, T-wave area from 34 x 10(3)+/- 21 x 10(3) to 141 x 10(3)+/- 58 x 10(3)muV msec, T-wave symmetry decreased from 1.55 +/- 0.11 to 1.06 +/- 0.23, and Tapex-end increased from 84 +/- 17 to 171 +/- 52 msec. T-wave complexity increased initially but saturated at SD = 50 msec. QT dispersion increased modestly until SD = 40 msec and more rapidly for higher values of SD. TDR increased linearly with SD. Tapex-end increased linearly with TDR, but overestimated it., Conclusion: T-wave complexity did not discriminate between differences in larger RH values. QT dispersion had low sensitivity in the transitional zone between normal and abnormal RH. In conclusion, T-wave amplitude, -area, -symmetry, and, with some limitations, Tapex-end and T-wave complexity reliably reflect changes in RH.