Higher Body Mass Index in Adolescence Predicts Cardiomyopathy Risk in Midlife

Robertson, Josefina; Schaufelberger, Maria; Lindgren, Martin; Adiels, Martin; Schiöler, Linus; Torén, Kjell; McMurray, John J.V.; Sattar, Naveed; Åberg, Maria; Rosengren, Annika

doi:10.1161/circulationaha.118.039132

Cited by 67 publications

(31 citation statements)

References 33 publications

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“…The BMI and DBP levels of CVD patients were significantly higher than those of the healthy volunteers. This result was consistent with previous reports, as BMI and DBP are high risk factors for CVD (2,12,13). The training set included 358 participants from Hebei and Shaanxi (96 HI, 74 stroke, 73 CHD, 65 diabetes, and 50 HBP volunteers).…”

Section: Participant Characteristicssupporting

confidence: 89%

A Novel Dried Blood Spot Detection Strategy for Characterizing Cardiovascular Diseases

Liu

Jin

et al. 2020

Front. Cardiovasc. Med.

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Cardiovascular diseases (CVDs) are the leading cause of death in China. Conventional diagnostic methods are dependent on advanced instruments, which are expensive, inaccessible, and inconvenient in underdeveloped areas. To build a novel dried blood spot (DBS) detection strategy for imaging CVDs, in this study, a total of 12 compounds, including seven amino acids [homocysteine (Hcy), isoleucine (Ile), leucine (Leu), valine (Val), phenylalanine (Phe), tyrosine (Tyr), and tryptophan (Trp)], three amino acid derivatives [choline, betaine, and trimethylamine N-oxide (TMAO)], L-carnitine, and creatinine, were screened for their ability to identify CVD. A rapid and reliable method was established for the quantitative analysis of the 12 compounds in DBS. A total of 526 CVD patients and 200 healthy volunteers in five provinces of China were recruited and divided into the following groups: stroke, coronary heart disease, diabetes, and high blood pressure. The orthogonal projection to latent structures-discriminant analysis (OPLSDA) model was used to characterize the difference between each CVD group. Marked differences between the groups based on the OPLSDA model were observed. Based on the model, the patients in the three training sets were mostly accurately categorized into the appropriate group. In addition, the receiver operating characteristic (ROC) curves and logistic regression of each metabolite chosen by the OPLSDA model had an excellent predictive value in both the test and validation groups. DBS detection of 12 biomarkers was sensitive and powerful for characterizing different types of CVD. Such differentiation may reduce unnecessary invasive coronary angiography, enhance predictive value, and complement current diagnostic methods.

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Section: Participant Characteristicssupporting

confidence: 89%

A Novel Dried Blood Spot Detection Strategy for Characterizing Cardiovascular Diseases

Liu

Jin

et al. 2020

Front. Cardiovasc. Med.

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“…We and others have demonstrated strong links between body weight in young people and HF and cardiomyopathy later in life [7‐10], where obesity continues to be a strong risk factor for HF also amongst the middle‐aged [11]. In contrast, whilst body weight amongst the young is a strong predictor also for CHD and ischaemic stroke (IS), obesity amongst the middle‐aged, whether expressed as body mass index (BMI) or as abdominal obesity, seems to be less important as predictors over and above blood pressure, diabetes and lipids [12].…”

Section: Introductionmentioning

confidence: 99%

Diverging trends for onset of acute myocardial infarction, heart failure, stroke and mortality in young males: role of changes in obesity and fitness

et al. 2021

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“…HCM-related outcomes) [12]. Moreover, a prospective study in adolescent men demonstrated that even mildly elevated body weight in late adolescence significantly increased the risk to develop dilated cardiomyopathy in adulthood [13]. At the heart level, a recent proteomics study in human HCM tissue samples showed reduced levels of energy metabolism proteins [14].…”

Section: Altered Metabolism As Key Driver Of Disease In Cardiomyopathiesmentioning

confidence: 99%

Strength of patient cohorts and biobanks for cardiomyopathy research

et al. 2020

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In 2011 the Netherlands Heart Foundation allocated funding (CVON, Cardiovasculair Onderzoek Nederland) to stimulate collaboration between clinical and preclinical researchers on specific areas of research. One of those areas involves genetic heart diseases, which are frequently caused by pathogenic variants in genes that encode sarcomere proteins. In 2014, the DOSIS (Determinants of susceptibility in inherited cardiomyopathy: towards novel therapeutic approaches) consortium was initiated, focusing their research on secondary disease hits involved in the onset and progression of cardiomyopathies. Here we highlight several recent observations from our consortium and collaborators which may ultimately be relevant for clinical practice.

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Higher Body Mass Index in Adolescence Predicts Cardiomyopathy Risk in Midlife

Abstract: Supplemental Digital Content is available in the text.

Cited by 67 publications

References 33 publications

A Novel Dried Blood Spot Detection Strategy for Characterizing Cardiovascular Diseases

A Novel Dried Blood Spot Detection Strategy for Characterizing Cardiovascular Diseases

Diverging trends for onset of acute myocardial infarction, heart failure, stroke and mortality in young males: role of changes in obesity and fitness

Strength of patient cohorts and biobanks for cardiomyopathy research

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