Use of Mendelian Randomization for Identifying Risk Factors for Brain Tumors

Abstract

Gliomas are a group of primary brain tumors, the most common and aggressive subtype of which is glioblastoma. Glioblastoma has a median survival of just 15 months after diagnosis. Only previous exposure to ionizing radiation and particular inherited genetic syndromes are accepted risk factors for glioma; the vast majority of cases are thought to occur spontaneously. Previous observational studies have described associations between several risk factors and glioma, but studies are often conflicting and whether these associations reflect true casual relationships is unclear because observational studies may be susceptible to confounding, measurement error and reverse causation. Mendelian randomization (MR) is a form of instrumental variable analysis that can be used to provide supporting evidence for causal relationships between exposures (e.g., risk factors) and outcomes (e.g., disease onset). MR utilizes genetic variants, such as single nucleotide polymorphisms (SNPs), that are robustly associated with an exposure to determine whether there is a causal effect of the exposure on the outcome. MR is less susceptible to confounding, reverse causation and measurement errors as it is based on the random inheritance during conception of genetic variants that can be relatively accurately measured. In previous studies, MR has implicated a genetically predicted increase in telomere length with an increased risk of glioma, and found little evidence that obesity related factors, vitamin D or atopy are causal in glioma risk. In this review, we describe MR and its potential use to discover and validate novel risk factors, mechanistic factors, and therapeutic targets in glioma.

Serum Uric Acid Level and Multiple Sclerosis: A Mendelian Randomization Study

“…Because of the inherent bias, it is not possible to determine the direction of causality between the serum UA level and risk of MS from the above-mentioned case-control studies. The method of MR can be used to clarify the causality of exposure factors in disease etiology (Smith and Ebrahim, 2003;Mokry et al, 2015a;Harroud and Richards, 2018;Howell et al, 2018). In MR analysis, genetic variations such as SNPs will be used as surrogate measures of genetically determined lifetime exposure of the trait of interest.…”

Epidemiology, genetic epidemiology and Mendelian randomisation: more need than ever to attend to detail

“…Much of the literature on IVs assumes the first case, whereas some applications, in particular Mendelian randomisation, fall into the second category. As the two are not always clearly distinguished in the MR literature (Thanassoulis and O'Donnell 2009;Thompson 2013, 2015;Howell et al 2018), we feel it is important to highlight and discuss the differences here.…”

The Role of Network Science in Glioblastoma

“…In another branch of causal discovery, Mendelian randomization (MR) uses genetic variants, such as single-nucleotide polymorphisms (SNPs), that are robustly associated with an exposure as proxies for the risk factor of interest [ 154 ], therefore eliminating confounding and reverse causation effects between the exposure of interest and outcome. Howell et al (2020) [ 155 ] used MR to assess the causal relationship of associations of 36 reported glioma risk factors obtained from a systematic MEDLINE search on observational epidemiology studies.…”