The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

Xu, Lin; Borges, Maria Carolina; Hemani, Gibran; Lawlor, Debbie A

doi:10.1007/s00125-017-4396-y

Cited by 88 publications

(73 citation statements)

References 48 publications

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“…In summary, the exact mechanisms remain elusive and are probably multifactorial, stemming from mechanical alterations of the airways and lung parenchyma, to systemic and airway inflammatory and metabolic dysfunction that adversely influences pulmonary function and/or response to therapy. In addition to the detrimental effects on lung function, obesity is a confirmed cause of diabetes and cardiovascular disease, leading to higher overall mortality (32)(33)(34). In our study, patients with a BMI $28 kg/m 2 were at increased odds of developing a severe case of COVID-19, which remained significant in the multivariable analysis after adjustment for reported comorbidities.…”

Section: Discussionmentioning

confidence: 51%

“…Moreover, men had a higher prevalence of obesity than women (17.5% versus 4.5%). Obese patients also tended to have cough (P 5 0.03) and fever (P 5 0.06) as initial symptoms, compared with nonobese patients, but they were comparable in terms of other symptoms (P 5 0.09-0.81), epidemiological characteristics (P 5 0.10), personal disease history (P 5 0.15-0.82), and disease progression or treatment (P 5 0.14-0.88) ( [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41] days). Three deaths occurred in the severe group, and no deaths occurred in the nonsevere group (Table 2).…”

Section: Resultsmentioning

confidence: 99%

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Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China

et al. 2020

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OBJECTIVE Patients with obesity are at increased risk of exacerbations from viral respiratory infections. However, the association of obesity with the severity of coronavirus disease 2019 (COVID-19) is unclear. We examined this association using data from the only referral hospital in Shenzhen, China. RESEARCH DESIGN AND METHODS A total of 383 consecutively hospitalized patients with COVID-19 admitted from 11 January 2020 to 16 February 2020 and followed until 26 March 2020 at the Third People’s Hospital of Shenzhen were included. Underweight was defined as a BMI <18.5 kg/m2, normal weight as 18.5–23.9 kg/m2, overweight as 24.0–27.9 kg/m2, and obesity as ≥28 kg/m2. RESULTS Of the 383 patients, 53.1% were normal weight, 4.2% were underweight, 32.0% were overweight, and 10.7% were obese at admission. Obese patients tended to have symptoms of cough (P = 0.03) and fever (P = 0.06) compared with patients who were not obese. Compared with normal weight patients, those who were overweight had 1.84-fold odds of developing severe COVID-19 (odds ratio [OR] 1.84, 95% CI 0.99–3.43, P = 0.05), while those who were obese were at 3.40-fold odds of developing severe disease (OR 3.40, 95% CI 1.40–2.86, P = 0.007), after adjusting for age, sex, epidemiological characteristics, days from disease onset to hospitalization, presence of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease, liver disease, and cancer, and drug used for treatment. Additionally, after similar adjustment, men who were obese versus those who were normal weight were at increased odds of developing severe COVID-19 (OR 5.66, 95% CI 1.80–17.75, P = 0.003). CONCLUSIONS In this study, obese patients had increased odds of progressing to severe COVID-19. As the severe acute respiratory syndrome coronavirus 2 may continue to spread worldwide, clinicians should pay close attention to obese patients, who should be carefully managed with prompt and aggressive treatment.

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Section: Discussionmentioning

confidence: 51%

Section: Resultsmentioning

confidence: 99%

Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China

et al. 2020

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“…There are a number of mechanisms by which this is proposed to be mediated, including the stimulatory effect of insulin on fatty acid storage and cell growth and a reduction in glycosuria (75-77). Furthermore, Mendelian randomisation analyses have supported a positive relationship between insulin and weight gain (78,79). Given the nature of the clinical presentation of anorexia, the effect of insulin on hunger and satiety is particularly pertinent.…”

Section: Discussionmentioning

confidence: 99%

Investigating the effect of glycaemic traits on the risk of psychiatric illness using Mendelian randomisation

Adams

Geaghan

Cairns

2020

Preprint

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Data from observational studies have suggested an involvement of abnormal glycaemic regulation in the pathophysiology of psychiatric illness. This may be an attractive target for clinical intervention as glycaemia can be modulated by both lifestyle factors and pharmacological agents. However, observational studies are inherently confounded, and therefore causal relationships cannot be reliably established. We employed genetic variants rigorously associated with three glycaemic traits (fasting glucose, fasting insulin, and glycated haemoglobin) as instrumental variables in a two-sample Mendelian randomisation analysis to investigate the causal effect of these measures on the risk for eight psychiatric disorders. A significant protective effect of a unit increase in fasting insulin levels was observed for anorexia nervosa after the application of multiple testing correction (OR = 0.48 [95% CI: 0.33-0.71] -inverse-variance weighted estimate. The relationship between fasting insulin and anorexia nervosa was supported by a suite of sensitivity analyses, with no statistical evidence of instrument heterogeneity or horizontal pleiotropy. Further investigation is required to explore the relationship between insulin levels and anorexia.

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“…This study, as some other previous studies [23][24][25][26] , did not exclude those with pre-existing disease and smoking 9 , which might mask the BMI-mortality risk association. Moreover, inappropriate adjustment for mediating factors for the associations between BMI and major health endpoints (i.e., CVD), such as glycaemia, triglycerides and low-density lipoprotein cholesterol will attenuate the result towards the null 9,27 . One recent study in China also showed no association between greater BMI groups (i.e., BMI > 26, 28 or 30 kg/m 2 ) and all-cause mortality, in subgroups by glycaemic status or in the whole sample 15 .…”

Section: Discussionmentioning

confidence: 99%

Adiposity and mortality in older Chinese: an 11-year follow-up of the Guangzhou Biobank Cohort Study

Jiang

Zhang

et al. 2020

Sci Rep

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Previous studies on Chinese showed mixed results describing the relationship between obesity and mortality. The optimum levels of body mass index (BMI) and waist circumference (WC) are inconsistent. In the Guangzhou Biobank Cohort Study, after excluding ever smokers and those with poor health, 19,405 Chinese (50+ years) recruited from 2003 to 2008 were followed-up until 2017. During an average follow-up of 11.5 (standard deviation = 2.3) years, 1,757 deaths were recorded. All-cause mortality showed a J-shaped association with BMI, with the lowest mortality risks at 22.5 kg/m 2 for both men and women. In those with BMI ≥ 22.5 kg/m 2 , an increase of 5 kg/m 2 was associated with 29% higher allcause mortality (hazard ratio (HR) = 1.29, 95% confidence interval (CI) 1.15-1.46), 30% higher cancer mortality (1.30, 95% CI 1.08-1.57), and 37% higher cardiovascular disease (CVD) mortality (1.37, 95% CI 1.13-1.67) after adjustment for potential confounders. In this first cohort study in one of the most economically developed cities in China, the lowest all-cause mortality was observed for a BMI of 22.5 kg/ m 2 in all participants, and a WC of 78 cm in men and 72 cm in women. The global emergence of the obesity epidemic has serious adverse health effects. WHO Global Health Observation data shows that at least 2.8 million deaths and 35.8 million of Disability Adjusted Life Years are attributable to adiposity each year globally 1. Most of the estimates above are based on studies in high-income countries several decades ago. As developing countries have only recently experienced a short period of obesity, the adverse population effects on morbidity or mortality have not been evident and tend to be underestimated. The effect in the low-to-middle income and high-income countries needs to be examined separately and the disease burden updated urgently. China is now in the first stage of the obesity epidemic 2 , as indicated by a relatively low prevalence of obesity 3,4 and obesity attributable mortality risk 4-6. Although the prevalence is increasing rapidly 7 , its effect on mortality has yet to be elucidated. Moreover, previous studies of obesity and mortality did not comprehensively account for pre-existing illnesses, which, if ignored, may result in reverse causality. For example, unmeasured underlying disease reduces body weight and leads to an observation that lower body weight was detrimental and obesity was protective 8-11. Additionally, the obesity-mortality association is often confounded by smoking, and simply adjusting for smoking status does not eliminate such confounding 12. Studies failing to account for reverse causality and smoking might underestimate the excess risk due to overweight and obesity especially in never smokers 13. Note that previous studies of Chinese populations did not show an adverse effect of overweight or obesity (i.e., BMI ≥ 24 or 28 kg/m 2 , respectively) on all-cause and cause-specific mortality 9-11,14,15. Although useful on a population level, for individuals BMI has some limitations due to ...

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The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

Cited by 88 publications

References 48 publications

Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China

Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China

Investigating the effect of glycaemic traits on the risk of psychiatric illness using Mendelian randomisation

Adiposity and mortality in older Chinese: an 11-year follow-up of the Guangzhou Biobank Cohort Study

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