A review of Mendelian randomization in amyotrophic lateral sclerosis

Abstract

Amyotrophic lateral sclerosis (ALS) is a relatively common and rapidly progressive neurodegenerative disease which, in the majority of cases, is thought to be determined by a complex gene-environment interaction. Exponential growth in the number of performed genome-wide association studies (GWAS), combined with the advent of Mendelian randomization (MR) is opening significant new opportunities to identify environmental exposures which increase or decrease the risk of ALS. Each of these discoveries has the potential to shape new therapeutic interventions. However, to do so rigorous methodological standards must be applied in the performance of MR. We have performed a review of MR studies performed in ALS to date. We identified 20 MR studies, including evaluation of physical exercise, adiposity, cognitive performance, immune function, blood lipids, sleep behaviours, educational attainment, alcohol consumption, smoking and type 2 diabetes mellitus. We have evaluated each study using gold standard methodology supported by the MR literature and the STROBE-MR checklist. Where discrepancies exist between MR studies, we suggest the underlying reasons. A number of studies conclude that there is a causal link between blood lipids and risk of ALS; replication across different datasets and even different populations adds confidence. For other putative risk factors, such as smoking and immune function, MR studies have provided cause for doubt. We highlight the use of positive control analyses in choosing exposure SNPs to make up the MR instrument, use of SNP clumping to avoid false positive results due to SNPs in linkage, and the importance of multiple testing correction. We discuss the implications of survival bias for study of late age of onset diseases such as ALS, and make recommendations to mitigate this potentially important confounder. For MR to be useful to the ALS field, high methodological standards must be applied to ensure reproducibility. MR is already an impactful tool but poor quality studies will lead to incorrect interpretations by a field which includes non-statisticians, wasted resources and missed opportunities.

Unraveling the complex interplay between genes, environment, and climate in ALS

“…9,10 Single nucleotide polymorphisms (SNPs) related to a particular exposure are retrieved from the summary statistics of previous GWA studies and then used as a separate outcome GWAS to assess the relationship between the exposure and the outcome. 11 However, Mendelian randomization studies are not free from limitations, and three major assumptions must hold for the results to be valid: (i) genetic variants should be associated with the exposure (relevance assumption); (ii) they must not be associated with confounders (independence assumption); and (iii) they must not influence the outcome through other pathways than the exposure considered (exclusion restriction assumption). 8,9 The first assumption is usually quantified using the F-statistics, while the remaining two are addressed through sensitivity measures such as the MR-PRESSO and Cochran's Q test.…”

“… 9 , 10 Single nucleotide polymorphisms (SNPs) related to a particular exposure are retrieved from the summary statistics of previous GWA studies and then used as a separate outcome GWAS to assess the relationship between the exposure and the outcome. 11 …”

“… 8 , 9 The first assumption is usually quantified using the F-statistics, while the remaining two are addressed through sensitivity measures such as the MR-PRESSO and Cochran's Q test. 11 A practical consideration is that Mendelian randomization requires large datasets to detect meaningful effects, and, ideally, a positive outcome should be replicated in an independent dataset.…”

“…In these cases, GWAS would be performed at a specific time point while the behaviour could change before and after that point in response to many internal and external stimuli. 11 , 12 The confounding effect of time (or aging) is a recurring theme when tackling gene-environment-climate relationships.…”

Unbiased metabolome screen leads to personalized medicine strategy for amyotrophic lateral sclerosis

“…We have previously shown that a conservative threshold can lead to an underpowered test and paradoxical results. 9 , 19 In the current work, the risk of invalid SNPs was mitigated by robust MR measures and sensitivity analyses as described below. Identified SNPs within a 10 kb window were clumped for independence using a stringent cut-off of R 2 ≤0.001 within a European reference panel; where SNPs were in linkage disequilibrium (LD), those with the lowest P -value were retained.…”