Atlas of the clinical genetics of human dilated cardiomyopathy.

AIM: Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. METHODS AND RESULTS: In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. CONCLUSION: This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM.

Randomized crossover trial of a modified ketogenic diet in Alzheimer's disease.

BACKGROUND: Brain energy metabolism is impaired in Alzheimer's disease (AD), which may be mitigated by a ketogenic diet. We conducted a randomized crossover trial to determine whether a 12-week modified ketogenic diet improved cognition, daily function, or quality of life in a hospital clinic of AD patients. METHODS: We randomly assigned patients with clinically confirmed diagnoses of AD to a modified ketogenic diet or usual diet supplemented with low-fat healthy-eating guidelines and enrolled them in a single-phase, assessor-blinded, two-period crossover trial (two 12-week treatment periods, separated by a 10-week washout period). Primary outcomes were mean within-individual changes in the Addenbrookes Cognitive Examination - III (ACE-III) scale, AD Cooperative Study - Activities of Daily Living (ADCS-ADL) inventory, and Quality of Life in AD (QOL-AD) questionnaire over 12 weeks. Secondary outcomes considered changes in cardiovascular risk factors and adverse effects. RESULTS: We randomized 26 patients, of whom 21 (81%) completed the ketogenic diet; only one withdrawal was attributed to the ketogenic diet. While on the ketogenic diet, patients achieved sustained physiological ketosis (12-week mean beta-hydroxybutyrate level: 0.95 ± 0.34 mmol/L). Compared with usual diet, patients on the ketogenic diet increased their mean within-individual ADCS-ADL (+ 3.13 ± 5.01 points, P = 0.0067) and QOL-AD (+ 3.37 ± 6.86 points, P = 0.023) scores; the ACE-III also increased, but not significantly (+ 2.12 ± 8.70 points, P = 0.24). Changes in cardiovascular risk factors were mostly favourable, and adverse effects were mild. CONCLUSIONS: This is the first randomized trial to investigate the impact of a ketogenic diet in patients with uniform diagnoses of AD. High rates of retention, adherence, and safety appear to be achievable in applying a 12-week modified ketogenic diet to AD patients. Compared with a usual diet supplemented with low-fat healthy-eating guidelines, patients on the ketogenic diet improved in daily function and quality of life, two factors of great importance to people living with dementia. TRIAL REGISTRATION: This trial is registered on the Australia New Zealand Clinical Trials Registry, number ACTRN12618001450202 . The trial was registered on August 28, 2018.

Cloninger's Temperament dimensions, socio-economic and lifestyle factors and metabolic syndrome markers at age 31 years in the Northern Finland Birth Cohort 1966.

The aim of this study was to assess the association between temperament and metabolic syndrome markers. Cloninger's Temperament and Character Inventory and clinical examination were carried out in 1997 in the Northern Finland Birth Cohort 1966 (N = 4364 respondents). Novelty seeking was positively associated with waist circumference in both genders. Systolic blood pressure was highest in men with high harm avoidance and low persistence scores and lowest in women with high reward dependence and high persistence scores. Childhood socio-economic status did not confound these associations. Smoking and alcohol consumption were associated with higher novelty seeking. Our results suggest that temperament is associated with metabolic syndrome markers and this association may be partly mediated by lifestyle factors and socio-economic status in adulthood.

Variation at the insulin gene VNTR (variable number tandem repeat) polymorphism and early growth: studies in a large Finnish birth cohort.

Variation at the insulin gene (INS-)VNTR (variable number of tandem repeats) minisatellite polymorphism has been reported to be associated with both early growth and adult metabolic phenotypes. However, the samples studied have been small and the relationship between INS-VNTR variation and parameters of early growth inconsistent, with four previous studies producing conflicting results. We have studied the relationship between INS-VNTR class (measured by genotyping the nearby -23HphI variant with which it is in tight linkage disequilibrium) and early growth in 5,646 members of the Northern Finnish Birth Cohort of 1966. Comparing class III homozygotes with other genotypes using multivariate linear regression analysis, we found no significant associations with any early growth measure (birth weight, birth length, ponderal index, and head circumference at 1 year), even after stratifying subjects by growth trajectory during infancy and/or birth order. For example, among infants with limited postnatal growth realignment (n = 2,470), class III/III infants were no heavier at birth (difference [+/-SE] in the means [fully adjusted], 58 +/- 51 g; P = 0.26) than class I/- infants. No significant associations were detected following reanalysis with an additive model (for example, for birth weight, beta = 20 g [95% CI -3 to 44], P = 0.09). Studies of this large population-based cohort have failed to generate convincing evidence that INS-VNTR variation influences early growth.

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart.

BACKGROUND: Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. METHODS AND RESULTS: State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. CONCLUSION: This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation.

Assembling cell context-specific gene sets: a case in cardiomyopathy.

An increasing amount of evidence suggests that canonical pathways and standard molecular signature databases are incomplete and inadequate to model the complex behavior of cell physiology and pathology. Yet, many Gene Set Analysis (GSA) studies still rely on these databases to identify disease biomarkers and molecular mechanisms within a specific cell context. While tremendous effort has been invested in developing GSA tools, there is limited number of studies focusing on de novo assembly of context-specific gene sets as opposed to simply applying GSA using the standard gene set database. In this paper, we propose a pipeline to derive the entire collection of Cell context-Specific Gene Sets (CSGS) from a molecular interaction network, based on the hypothesis that molecular events linked to a specific phenotypic response should cluster within a subnet of interacting genes. Gene sets are assigned using both physical properties of the network and functional annotations of the neighboring nodes. The identified gene sets could provide a precise starting point such that the downstream GSA will cover all functional pathways in this particular cell context and, at the same time, avoid the noise and excessive multiple-hypothesis testing due to inclusion of irrelevant gene sets from the standard database. We applied the pipeline in the context of cardiomyopathy and demonstrated its superiority over MSigDB gene set collection in terms of: (i) reproducibility and robustness in GSA, (ii) effectiveness in uncovering molecular mechanisms associated with cardiomyopathy, and (iii) the performance in distinguishing diseased vs. normal states.

Birthweight and blood pressure in five European birth cohort studies: an investigation of confounding factors.

BACKGROUND: It has been suggested that the association between birthweight and blood pressure has been overstated as a result of publication bias and, within studies, a lack of adjustment for potentially important maternal and socioeconomic confounding factors and 'overadjustment' for current body size. This study investigates the impact of potential confounding variables on the birthweight-blood pressure association in birth cohort studies from different time periods and geographical locations in Europe. METHODS: Data from five European birth cohort studies (from Finland, the UK, and the Faroe Islands) taking part in the European Birth-Lifecourse-Studies (EURO-BLCS) project were analysed. Birthweight was measured at birth in all cohorts and confounding variable information was collected prospectively at subsequent follow-ups in all cohorts. Regression models were used to assess the unadjusted association between birthweight and blood pressure and then to assess the impact of potential maternal and socioeconomic confounding variables and adjustment for later body size. Analyses were carried out in the same way across all five cohorts. RESULTS: Birthweight was consistently negatively associated with systolic blood pressure (SBP) across all cohorts. Gestational age and possibly maternal pre-pregnancy weight, but not socioeconomic status, may be important confounding factors of the relationship between birthweight and SBP. The size of the birthweight-SBP association in adulthood may be larger than in childhood before adjustment for current body size, although a cohort effect cannot be ruled out. CONCLUSION: This study highlights the value of future cross-cohort comparisons in the investigation of the foetal origins of adult disease.

Early life factors and blood pressure at age 31 years in the 1966 northern Finland birth cohort.

Data on the birth weight-blood pressure relationship are inconsistent. Although an inverse association has been suggested in several large studies, interpretation is complicated by publication and other biases. Few data are available on the relationship between other early growth measures and blood pressure. We examined the shape and size of association between determinants of fetal growth, size at birth, growth in infancy, and adult systolic and diastolic blood pressure at 31 years in the prospective northern Finnish 1966 birth cohort of 5960 participants. Birth weight, birth length, gestational age, ponderal index, and birth weight relative to gestational age showed a significant inverse association with blood pressure at age 31. Rapid growth in infancy ("change-up") was positively associated with blood pressure. Adjusted regression coefficients for birth weight indicated systolic/diastolic blood pressure lower by -1.7 (95% confidence interval [CI], -2.5, -1.0)/-0.7 (95% CI, -1.4, -0.02) mm Hg for 1 kg higher birth weight. The significant inverse association between birth weight and systolic blood pressure persisted without adjustment for adult body mass index for males. Among females, gestational age showed a stronger association with blood pressure than birth weight: gestational age higher by 7 weeks (equivalent to an average of 1 kg higher birth weight) among singletons associated with -2.9 (95% CI, -4.7, -1.1) mm Hg lower systolic blood pressure. Our results support the concept that birth weight, other birth measures, and infant growth are important determinants of blood pressure and hence cardiovascular disease risk in later life.