Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

Reliability and validity of the modified child and adolescent physical activity and nutrition survey (CAPANS-C) questionnaire examining potential correlates of physical activity participation among Chinese-Australian youth

BACKGROUND: To date, few questionnaires examining psychosocial influences of physical activity (PA) participation have been psychometrically tested among Culturally and Linguistically Diverse (CALD) youth. An understanding of these influences may help explain the observed differences in PA among CALD youth. Therefore, this study examined the reliability and predictive validity of a brief self-report questionnaire examining potential psychological and social correlates of physical activity among a sample of Chinese-Australian youth. METHODS: Two Chinese-weekend cultural schools from eastern metropolitan Melbourne consented to participate in this study. In total, 505 students aged 11 to 16 years were eligible for inclusion in the present study, and of these, 106 students agreed to participate (21% response rate). Participants completed at 37-item self-report questionnaire examining perceived psychological and social influences on physical activity participation twice, with a test–retest interval of 7 days. Predictive validity, internal consistency and test–retest reliability were evaluated using exploratory factor analyses, Cronbach’s α coefficient, and the intraclass correlation coefficient (ICC) respectively. Predictive validity was assessed by correlating responses against duration spent in self-reported moderate-to-vigorous physical activity (MVPA). RESULTS: The exploratory factor analysis revealed a nine factor structure, with the majority of factors exhibiting high internal consistency (α ≥ 0.6). In addition, four of the nine factors had an ICC ≥ 0.6. Spearman rank-order correlations coefficients between the nine factors and self-reported minutes spent in MVPA ranged from -0.5 to 0.3 for all participants. CONCLUSION: This is the first study to examine the psychometric properties of a potential psychological and social correlates questionnaire among Chinese-Australian youth. The questionnaire was found to provide reliable estimates on a range of psychological and social influences on physical activity and evidence of predictive validity on a limited number of factors. More research is required to improve the reliability and validity of the questionnaire

The effect of intravenous ferric carboxymaltose on health-related quality of life in iron-deficient patients with acute heart failure: the results of the AFFIRM-AHF study

Aims: Patients with heart failure (HF) and iron deficiency experience poor health-related quality of life (HRQoL). We evaluated the impact of intravenous (IV) ferric carboxymaltose (FCM) vs. placebo on HRQoL for the AFFIRM-AHF population. Methods and results: The baseline 12-item Kansas City Cardiomyopathy Questionnaire (KCCQ-12), which was completed for 1058 (535 and 523) patients in the FCM and placebo groups, respectively, was administered prior to randomization and at Weeks 2, 4, 6, 12, 24, 36, and 52. The baseline KCCQ-12 overall summary score (OSS) mean ± standard error was 38.7 ± 0.9 (FCM group) and 37.1 ± 0.8 (placebo group); corresponding values for the clinical summary score (CSS) were 40.9 ± 0.9 and 40.1 ± 0.9. At Week 2, changes in OSS and CSS were similar for FCM and placebo. From Week 4 to Week 24, patients assigned to FCM had significantly greater improvements in OSS and CSS scores vs. placebo [adjusted mean difference (95% confidence interval, CI) at Week 4: 2.9 (0.5-5.3, P = 0.018) for OSS and 2.8 (0.3-5.3, P = 0.029) for CSS; adjusted mean difference (95% CI) at Week 24: 3.0 (0.3-5.6, P = 0.028) for OSS and 2.9 (0.2-5.6, P = 0.035) for CSS]. At Week 52, the treatment effect had attenuated but remained in favour of FCM. Conclusion: In iron-deficient patients with HF and left ventricular ejection fraction ≤50% who had stabilized after an episode of acute HF, treatment with IV FCM, compared with placebo, results in clinically meaningful beneficial effects on HRQoL as early as 4 weeks after treatment initiation, lasting up to Week 24

Ferric carboxymaltose for iron deficiency at discharge after acute heart failure:a multicentre, double-blind, randomised, controlled trial

Background Intravenous ferric carboxymaltose has been shown to improve symptoms and quality of life in patients with chronic heart failure and iron deficiency. We aimed to evaluate the effect of ferric carboxymaltose, compared with placebo, on outcomes in patients who were stabilised after an episode of acute heart failure. Methods AFFIRM-AHF was a multicentre, double-blind, randomised trial done at 121 sites in Europe, South America, and Singapore. Eligible patients were aged 18 years or older, were hospitalised for acute heart failure with concomitant iron deficiency (defined as ferritin Findings Between March 21, 2017, and July 30, 2019, 1525 patients were screened, of whom 1132 patients were randomly assigned to study groups. Study treatment was started in 1110 patients, and 1108 (558 in the carboxymaltose group and 550 in the placebo group) had at least one post-randomisation value. 293 primary events (57.2 per 100 patient-years) occurred in the ferric carboxymaltose group and 372 (72.5 per 100 patient-years) occurred in the placebo group (rate ratio [RR] 0.79, 95% CI 0.62-1.01, p=0.059). 370 total cardiovascular hospitalisations and cardiovascular deaths occurred in the ferric carboxymaltose group and 451 occurred in the placebo group (RR 0.80, 95% CI 0.64-1.00, p=0.050). There was no difference in cardiovascular death between the two groups (77 [14%] of 558 in the ferric carboxymaltose group vs 78 [14%] in the placebo group; hazard ratio [HR] 0.96, 95% CI 0.70-1.32, p=0.81). 217 total heart failure hospitalisations occurred in the ferric carboxymaltose group and 294 occurred in the placebo group (RR 0.74; 95% CI 0.58-0.94, p=0.013). The composite of first heart failure hospitalisation or cardiovascular death occurred in 181 (32%) patients in the ferric carboxymaltose group and 209 (38%) in the placebo group (HR 0.80, 95% CI 0.66-0.98, p=0.030). Fewer days were lost due to heart failure hospitalisations and cardiovascular death for patients assigned to ferric carboxymaltose compared with placebo (369 days per 100 patient-years vs 548 days per 100 patient-years; RR 0.67, 95% CI 0.47-0.97, p=0.035). Serious adverse events occurred in 250 (45%) of 559 patients in the ferric carboxymaltose group and 282 (51%) of 551 patients in the placebo group. Interpretation In patients with iron deficiency, a left ventricular ejection fraction of less than 50%, and who were stabilised after an episode of acute heart failure, treatment with ferric carboxymaltose was safe and reduced the risk of heart failure hospitalisations, with no apparent effect on the risk of cardiovascular death

Genetic loci for retinal arteriolar microcirculation.

Narrow arterioles in the retina have been shown to predict hypertension as well as other vascular diseases, likely through an increase in the peripheral resistance of the microcirculatory flow. In this study, we performed a genome-wide association study in 18,722 unrelated individuals of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium and the Blue Mountain Eye Study, to identify genetic determinants associated with variations in retinal arteriolar caliber. Retinal vascular calibers were measured on digitized retinal photographs using a standardized protocol. One variant (rs2194025 on chromosome 5q14 near the myocyte enhancer factor 2C MEF2C gene) was associated with retinal arteriolar caliber in the meta-analysis of the discovery cohorts at genome-wide significance of P-value <5×10(-8). This variant was replicated in an additional 3,939 individuals of European ancestry from the Australian Twins Study and Multi-Ethnic Study of Atherosclerosis (rs2194025, P-value = 2.11×10(-12) in combined meta-analysis of discovery and replication cohorts). In independent studies of modest sample sizes, no significant association was found between this variant and clinical outcomes including coronary artery disease, stroke, myocardial infarction or hypertension. In conclusion, we found one novel loci which underlie genetic variation in microvasculature which may be relevant to vascular disease. The relevance of these findings to clinical outcomes remains to be determined

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis

Multi-Site Benchmark Classification of Major Depressive Disorder Using Machine Learning on Cortical and Subcortical Measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

A genomic database of all Earth’s eukaryotic species could contribute to many scientific discoveries; however, only a tiny fraction of species have genomic information available. In 2018, scientists across the world united under the Earth BioGenome Project (EBP), aiming to produce a database of high-quality reference genomes containing all ~1.5 million recognized eukaryotic species. As the European node of the EBP, the European Reference Genome Atlas (ERGA) sought to implement a new decentralised, equitable and inclusive model for producing reference genomes. For this, ERGA launched a Pilot Project establishing the first distributed reference genome production infrastructure and testing it on 98 eukaryotic species from 33 European countries. Here we outline the infrastructure and explore its effectiveness for scaling high-quality reference genome production, whilst considering equity and inclusion. The outcomes and lessons learned provide a solid foundation for ERGA while offering key learnings to other transnational, national genomic resource projects and the EBP.info:eu-repo/semantics/publishedVersio