Association of body mass index, metabolic health status and clinical outcomes in acute myocardial infarction patients: a national registry-based study

INTRODUCTION: Obesity is an important risk factor for acute myocardial infarction (AMI), but the interplay between metabolic health and obesity on AMI mortality has been controversial. In this study, we aimed to elucidate the risk of short- and long-term all-cause mortality by obesity and metabolic health in AMI patients using data from a multi-ethnic national AMI registry. METHODS: A total of 73,382 AMI patients from the national Singapore Myocardial Infarction Registry (SMIR) were included. These patients were classified into four groups based on the presence or absence of metabolic diseases, diabetes mellitus, hyperlipidaemia, and hypertension, and obesity: (1) metabolically-healthy-normal-weight (MHN); (2) metabolically-healthy-obese (MHO); (3) metabolically-unhealthy-normal-weight (MUN); and (4) metabolically-unhealthy-obese (MUO). RESULTS: MHO patients had reduced unadjusted risk of all-cause in-hospital, 30-day, 1-year, 2-year, and 5-year mortality following the initial MI event. However, after adjusting for potential confounders, the protective effect from MHO on post-AMI mortality was lost. Furthermore, there was no reduced risk of recurrent MI or stroke within 1-year from onset of AMI by the MHO status. However, the risk of 1-year mortality was higher in female and Malay AMI patients with MHO compared to MHN even after adjusting for confounders. CONCLUSION: In AMI patients with or without metabolic diseases, the presence of obesity did not affect mortality. The exception to this finding were female and Malay MHO who had worse long-term AMI mortality outcomes when compared to MHN suggesting that the presence of obesity in female and Malay patients may confer worsened outcomes

Association of anthropometric measures across the life-course with refractive error and ocular biometry at age 15 years

YesBackground A recent Genome-wide association meta-analysis (GWAS) of refractive error reported shared genetics with anthropometric traits such as height, BMI and obesity. To explore a potential relationship with refractive error and ocular structure we performed a life-course analysis including both maternal and child characteristics using data from the Avon Longitudinal Study of Parents and Children cohort. Methods Measures collected across the life-course were analysed to explore the association of height, weight, and BMI with refractive error and ocular biometric measures at age 15 years from 1613children. The outcome measures were the mean spherical equivalent (MSE) of refractive error (dioptres), axial length (AXL; mm), and radius of corneal curvature (RCC; mm). Potential confounding variables; maternal age at conception, maternal education level, parental socio-economic status, gestational age, breast-feeding, and gender were adjusted for within each multi-variable model. Results Maternal height was positively associated with teenage AXL (0.010 mm; 95% CI: 0.003, 0.017) and RCC (0.005 mm; 95% CI: 0.003, 0.007), increased maternal weight was positively associated with AXL (0.004 mm; 95% CI: 0.0001, 0.008). Birth length was associated with an increase in teenage AXL (0.067 mm; 95% CI: 0.032, 0.10) and flatter RCC (0.023 mm; 95% CI: 0.013, 0.034) and increasing birth weight was associated with flatter RCC (0.005 mm; 95% CI: 0.0003, 0.009). An increase in teenage height was associated with a lower MSE (− 0.007 D; 95% CI: − 0.013, − 0.001), an increase in AXL (0.021 mm; 95% CI: 0.015, 0.028) and flatter RCC (0.008 mm; 95% CI: 0.006, 0.010). Weight at 15 years was associated with an increase in AXL (0.005 mm; 95% CI: 0.001, 0.009). Conclusions At each life stage (pre-natal, birth, and teenage) height and weight, but not BMI, demonstrate an association with AXL and RCC measured at age 15 years. However, the negative association between refractive error and an increase in height was only present at the teenage life stage. Further research into the growth pattern of ocular structures and the development of refractive error over the life-course is required, particularly at the time of puberty

Genetic studies of hypertrophic cardiomyopathy in Singaporeans identify variants in TNNI3 and TNNT2 that are common in Chinese patients

Background - To assess the genetic architecture of hypertrophic cardiomyopathy (HCM) in patients of predominantly Chinese ancestry. Methods - We sequenced HCM disease genes in Singaporean patients (n=224) and Singaporean controls (n=3,634), compared findings with additional populations and Caucasian HCM cohorts (n=6,179) and performed in vitro functional studies. Results - Singaporean HCM patients had significantly fewer confidently interpreted HCM disease variants (Pathogenic (P)/Likely Pathogenic (LP):18%, p<0.0001) but an excess of variants of unknown significance (exVUS: 24%, p<0.0001), as compared to Caucasians (P/LP: 31%, exVUS: 7%). Two missense variants in thin filament encoding genes were commonly seen in Singaporean HCM (TNNI3:p.R79C, disease allele frequency (AF)=0.018; TNNT2:p.R286H, disease AF=0.022) and are enriched in Singaporean HCM when compared with Asian controls (TNNI3:p.R79C, Singaporean controls AF=0.0055, p=0.0057, gnomAD-East Asian (gnomAD-EA) AF=0.0062, p=0.0086; TNNT2:p.R286H, Singaporean controls AF=0.0017, p<0.0001, gnomAD-EA AF=0.0009, p<0.0001). Both these variants have conflicting annotations in ClinVar and are of low penetrance (TNNI3:p.R79C, 0.7%; TNNT2:p.R286H, 2.7%) but are predicted to be deleterious by computational tools. In population controls, TNNI3:p.R79C carriers had significantly thicker left ventricular walls compared to non-carriers while its etiological fraction is limited (0.70, 95% CI: 0.35-0.86) and thus TNNI3:p.R79C is considered a VUS. Mutant TNNT2:p.R286H iPSC-CMs show hypercontractility, increased metabolic requirements and cellular hypertrophy and the etiological fraction (0.93, 95% CI: 0.83-0.97) support the likely pathogenicity of TNNT2:p.R286H. Conclusions - As compared to Caucasians, Chinese HCM patients commonly have low penetrance risk alleles in TNNT2 or TNNI3 but exhibit few clinically actionable HCM variants overall. This highlights the need for greater study of HCM genetics in non-Caucasian populations

IMI - Myopia Genetics Report

The knowledge on the genetic background of refractive error and myopia has expanded dramatically in the past few years. This white paper aims to provide a concise summary of current genetic findings and defines the direction where development is needed.We performed an extensive literature search and conducted informal discussions with key stakeholders. Specific topics reviewed included common refractive error, any and high myopia, and myopia related to syndromes.To date, almost 200 genetic loci have been identified for refractive error and myopia, and risk variants mostly carry low risk but are highly prevalent in the general population. Several genes for secondary syndromic myopia overlap with those for common myopia. Polygenic risk scores show overrepresentation of high myopia in the higher deciles of risk. Annotated genes have a wide variety of functions, and all retinal layers appear to be sites of expression.The current genetic findings offer a world of new molecules involved in myopiagenesis. As the missing heritability is still large, further genetic advances are needed. This Committee recommends expanding large-scale, in-depth genetic studies using complementary big data analytics, consideration of gene-environment effects by thorough measurement of environmental exposures, and focus on subgroups with extreme phenotypes and high familial occurrence. Functional characterization of associated variants is simultaneously needed to bridge the knowledge gap between sequence variance and consequence for eye growth

IMI - Myopia Genetics Report

The knowledge on the genetic background of refractive error and myopia has expanded dramatically in the past few years. This white paper aims to provide a concise summary of current genetic findings and defines the direction where development is needed. We performed an extensive literature search and conducted informal discussions with key stakeholders. Specific topics reviewed included common refractive error, any and high myopia, and myopia related to syndromes. To date, almost 200 genetic loci have been identified for refractive error and myopia, and risk variants mostly carry low risk but are highly prevalent in the general population. Several genes for secondary syndromic myopia overlap with those for common myopia. Polygenic risk scores show overrepresentation of high myopia in the higher deciles of risk. Annotated genes have a wide variety of functions, and all retinal layers appear to be sites of expression. The current genetic findings offer a world of new molecules involved in myopiagenesis. As the missing heritability is still large, further genetic advances are needed. This Committee recommends expanding large-scale, in-depth genetic studies using complementary big data analytics, consideration of gene-environment effects by thorough measurement of environmental exposures, and focus on subgroups with extreme phenotypes and high familial occurrence. Functional characterization of associated variants is simultaneously needed to bridge the knowledge gap between sequence variance and consequence for eye growth

Semi-automated pulmonary nodule interval segmentation using the NLST data.

PurposeTo study the variability in volume change estimates of pulmonary nodules due to segmentation approaches used across several algorithms and to evaluate these effects on the ability to predict nodule malignancy.MethodsWe obtained 100 patient image datasets from the National Lung Screening Trial (NLST) that had a nodule detected on each of two consecutive low dose computed tomography (LDCT) scans, with an equal proportion of malignant and benign cases (50 malignant, 50 benign). Information about the nodule location for the cases was provided by a screen capture with a bounding box and its axial location was indicated. Five participating quantitative imaging network (QIN) institutions performed nodule segmentation using their preferred semi-automated algorithms with no manual correction; teams were allowed to provide additional manually corrected segmentations (analyzed separately). The teams were asked to provide segmentation masks for each nodule at both time points. From these masks, the volume was estimated for the nodule at each time point; the change in volume (absolute and percent change) across time points was estimated as well. We used the concordance correlation coefficient (CCC) to compare the similarity of computed nodule volumes (absolute and percent change) across algorithms. We used Logistic regression model on the change in volume (absolute change and percent change) of the nodules to predict the malignancy status, the area under the receiver operating characteristic curve (AUROC) and confidence intervals were reported. Because the size of nodules was expected to have a substantial effect on segmentation variability, analysis of change in volumes was stratified by lesion size, where lesions were grouped into those with a longest diameter of &lt;8&nbsp;mm and those with longest diameter ≥&nbsp;8&nbsp;mm.ResultsWe find that segmentation of the nodules shows substantial variability across algorithms, with the CCC ranging from 0.56 to 0.95 for change in volume (percent change in volume range was [0.15 to 0.86]) across the nodules. When examining nodules based on their longest diameter, we find the CCC had higher values for large nodules with a range of [0.54 to 0.93] among the algorithms, while percent change in volume was [0.3 to 0.95]. Compared to that of smaller nodules which had a range of [-0.0038 to 0.69] and percent change in volume was [-0.039 to 0.92]. The malignancy prediction results showed fairly consistent results across the institutions, the AUC using change in volume ranged from 0.65 to 0.89 (Percent change in volume was 0.64 to 0.86) for entire nodule range. Prediction improves for large nodule range (≥&nbsp;8&nbsp;mm) with AUC range 0.75 to 0.90 (percent change in volume was 0.74 to 0.92). Compared to smaller nodule range (&lt;8&nbsp;mm) with AUC range 0.57 to 0.78 (percent change in volume was 0.59 to 0.77).ConclusionsWe find there is a fairly high concordance in the size measurements for larger nodules (≥8&nbsp;mm) than the lower sizes (&lt;8&nbsp;mm) across algorithms. We find the change in nodule volume (absolute and percent change) were consistent predictors of malignancy across institutions, despite using different segmentation algorithms. Using volume change estimates without corrections shows slightly lower predictability (for two teams)

Remote intensive management to improve antiplatelet adherence in acute myocardial infarction: a secondary analysis of the randomized controlled IMMACULATE trial

This study aim to investigate if remote intensive coaching for the first 6 months post-AMI will improve adherence to the twice-a-day antiplatelet medication, ticagrelor. Between July 8, 2015, to March 29, 2019, AMI patients were randomly assigned to remote intensive management (RIM) or standard care (SC). RIM participants underwent 6 months of weekly then two-weekly consultations to review medication side effects and medication adherence coaching by a centralized nurse practitioner team, whereas SC participants received usual cardiologist face-to-face consultations. Adherence to ticagrelor were determined using pill counting and serial platelet reactivity measurements for 12 months. A total of 149 (49.5%) of participants were randomized to RIM and 152 (50.5%) to SC. Adherence to ticagrelor was similar between RIM and SC group at 1 month (94.4 ± 0.7% vs. 93.6±14.7%, p = 0.537), 6 months (91.0±14.6% vs. 90.6±14.8%, p = 0.832) and 12 months (87.4±17.0% vs. 89.8±12.5%, p = 0.688). There was also no significant difference in platelet reactivity between the RIM and SC groups at 1 month (251AU*min [212–328] vs. 267AU*min [208–351], p = 0.399), 6 months (239AU*min [165–308] vs. 235AU*min [171–346], p = 0.610) and 12 months (249AU*min [177–432] vs. 259AU*min [182–360], p = 0.678). Sensitivity analysis did not demonstrate any association of ticagrelor adherence with bleeding events and major adverse cardiovascular events. RIM, comprising 6 months of intensive coaching by nurse practitioners, did not improve adherence to the twice-a-day medication ticagrelor compared with SC among patients with AMI. A gradual decline in ticagrelor adherence over 12 months was observed despite 6 months of intensive coaching