In view of the consolidating evidence on the causal role of Lp(a) in cardiovascular disease, the Italian Society for the Study of Atherosclerosis (SISA) has assembled a consensus on Lp(a) genetics and epidemiology, together with recommendations for its measurement and current and emerging therapeutic approaches to reduce its plasma levels. Data on the Italian population are also provided.
Lp(a) is constituted by one apo(a) molecule and a lipoprotein closely resembling to a low-density lipoprotein (LDL). Its similarity with an LDL, together with its ability to carry oxidized phospholipids are considered the two main features making Lp(a) harmful for cardiovascular health. Plasma Lp(a) concentrations vary over about 1000 folds in humans and are genetically determined, thus they are quite stable in any individual. Mendelian Randomization studies have suggested a causal role of Lp(a) in atherosclerotic cardiovascular disease (ASCVD) and aortic valve stenosis and observational studies indicate a linear direct correlation between cardiovascular disease and Lp(a) plasma levels. Lp(a) measurement is strongly recommended once in a patient\'s lifetime, particularly in FH subjects, but also as part of the initial lipid screening to assess cardiovascular risk. The apo(a) size polymorphism represents a challenge for Lp(a) measurement in plasma, but new strategies are overcoming these difficulties. A reduction of Lp(a) levels can be currently attained only by plasma apheresis and, moderately, with PCSK9 inhibitor treatment.
Awaiting the approval of selective Lp(a)-lowering drugs, an intensive management of the other risk factors for individuals with elevated Lp(a) levels is strongly recommended.

Genomics-driven drug discovery is indispensable for accelerating the development of novel therapeutic targets. However, the drug discovery framework based on evidence from genome-wide association studies (GWASs) has not been established, especially for cross-population GWAS meta-analysis. Here, we introduce a practical guideline for genomics-driven drug discovery for cross-population meta-analysis, as lessons from the Global Biobank Meta-analysis Initiative (GBMI). Our drug discovery framework encompassed three methodologies and was applied to the 13 common diseases targeted by GBMI (N mean = 1,329,242). Individual methodologies complementarily prioritized drugs and drug targets, which were systematically validated by referring previously known drug-disease relationships. Integration of the three methodologies provided a comprehensive catalog of candidate drugs for repositioning, nominating promising drug candidates targeting the genes involved in the coagulation process for venous thromboembolism and the interleukin-4 and interleukin-13 signaling pathway for gout. Our study highlighted key factors for successful genomics-driven drug discovery using cross-population meta-analyses.

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.

Mendelian randomization (MR) analyses have been increasingly used to seek evidence of causal associations. This systematic review aims at characterizing and evaluating the reporting of MR analyses in oncological studies.
The PubMed database was searched to identify MR cancer studies until December 31, 2017. Two of the authors independently selected and evaluated reporting quality of the studies. Reporting quality in MR studies before 2016 and in 2016/17 was compared.
Cancer studies with MR analyses in 2016 and 2017 accounted for 55.8% of the total number of studies identified. In the 77 eligible articles, 39 (50.6%) did not report subjects\' characteristics, 53 (68.8%) did not conduct power estimation, 40 (51.9%) did not state all of the first three MR assumptions (i.e., genetic instrument is associated with exposure, is not associated with confounders, and acts on outcome only through exposure), and 31 (40.3%) did not exclude SNPs that diverged from Hardy-Weinberg equilibrium. More studies estimated power in 2016/2017 than before 2016 (p = 0.028).
Some MR cancer studies did not sufficiently report essential information, posing obstacles for critical appraisal. This study proposes for MR analysis a guideline/checklist for future publications in cancer and other biomedical research.

UNASSIGNED: To appraise the clinical and genetic evidence that low-density lipoproteins (LDLs) cause atherosclerotic cardiovascular disease (ASCVD).
UNASSIGNED: We assessed whether the association between LDL and ASCVD fulfils the criteria for causality by evaluating the totality of evidence from genetic studies, prospective epidemiologic cohort studies, Mendelian randomization studies, and randomized trials of LDL-lowering therapies. In clinical studies, plasma LDL burden is usually estimated by determination of plasma LDL cholesterol level (LDL-C). Rare genetic mutations that cause reduced LDL receptor function lead to markedly higher LDL-C and a dose-dependent increase in the risk of ASCVD, whereas rare variants leading to lower LDL-C are associated with a correspondingly lower risk of ASCVD. Separate meta-analyses of over 200 prospective cohort studies, Mendelian randomization studies, and randomized trials including more than 2 million participants with over 20 million person-years of follow-up and over 150 000 cardiovascular events demonstrate a remarkably consistent dose-dependent log-linear association between the absolute magnitude of exposure of the vasculature to LDL-C and the risk of ASCVD; and this effect appears to increase with increasing duration of exposure to LDL-C. Both the naturally randomized genetic studies and the randomized intervention trials consistently demonstrate that any mechanism of lowering plasma LDL particle concentration should reduce the risk of ASCVD events proportional to the absolute reduction in LDL-C and the cumulative duration of exposure to lower LDL-C, provided that the achieved reduction in LDL-C is concordant with the reduction in LDL particle number and that there are no competing deleterious off-target effects.
UNASSIGNED: Consistent evidence from numerous and multiple different types of clinical and genetic studies unequivocally establishes that LDL causes ASCVD.