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Aims Low levels of HDL cholesterol have been associated with increased risk of infectious disease morbidity and mortality. Nuclear magnetic resonance (NMR) spectroscopy permits the measurement of HDL particle count and allows further subclassification according to particle size. We tested the hypothesis that low number of different HDL subfractions is associated with increased infectious disease morbidity and mortality. Methods and results HDL particle counts were measured using NMR spectroscopy in 30 195 individuals aged 22–99 years from the Copenhagen General Population Study. Using multiple-event Cox regression and cause-specific hazard models, we assessed risk of hospitalizations due to infection and infectious disease-related death, from 2003 through 2018. During follow-up, 9303 individuals had one or more infectious disease events, and 1558 experienced infectious disease-related death. In multifactorial adjusted analyses, low number of small and medium HDL particles was associated with increased risk of any infection and infectious disease-related death, whereas low number of large and extra-large HDL particles was not. A very high number of small and medium HDL particles was also associated with increased risk of any infection, but not with infectious disease-related death. For small and medium HDL particles and compared to individuals in the 91–95th percentile, hazard ratios (HRs) in individuals in the lowest percentile were 2.31 (95% confidence interval: 1.75, 3.05) for any infection and 3.23 (2.08, 5.02) for infectious disease-related death. For the highest percentile, corresponding HRs were 1.36 (1.07, 1.74) and 1.06 (0.57, 1.98), respectively. Individuals in the lowest percentile had increased risk of pneumonia (HR: 1.86; 95% confidence interval: 1.30, 2.65), sepsis (2.17; 1.37, 3.35), urinary tract infection (1.76; 1.17, 2.63), skin infection (1.87; 1.24, 2.81), gastroenteritis (1.78; 1.01, 3.16), and other infections (2.57; 1.28, 5.16). Conclusion Low number of the small HDL particles was associated with increased infectious disease morbidity and mortality. [ABSTRACT FROM AUTHOR]

The Mendelian randomization approach is an epidemiological study design incorporating genetic information into traditional epidemiological studies to infer causality of biomarkers, risk factors, or lifestyle factors on disease risk. Mendelian randomization studies often draw on novel information generated in genome-wide association studies on causal associations between genetic variants and a risk factor or lifestyle factor. Such information can then be used in a largely unconfounded study design free of reverse causation to understand if and how risk factors and lifestyle factors cause cardiovascular disease. If causation is demonstrated, an opportunity for prevention of disease is identified; importantly however, before prevention or treatment can be implemented, randomized intervention trials altering risk factor levels or improving deleterious lifestyle factors needs to document reductions in cardiovascular disease in a safe and side-effect sparse manner. Documentation of causality can also inform on potential drug targets, more likely to be successful than prior approaches often relying on animal or cell studies mainly. The present review summarizes the history and background of Mendelian randomization, the study design, assumptions for using the design, and the most common caveats, followed by a discussion on advantages and disadvantages of different types of Mendelian randomization studies using one or more samples and different levels of information on study participants. The review also provides an overview of results on many of the risk factors and lifestyle factors for cardiovascular disease examined to date using the Mendelian randomization study design. [ABSTRACT FROM AUTHOR]