Pleiotropy assessment is critical for the validity of Mendelian randomization (MR) analyses, and its management remains a challenging task for researchers. This review examines how the authors of MR ...studies address bias due to pleiotropy in practice. We reviewed Pubmed, Medline, Embase and Web of Science for MR studies published before 21 May 2020 that used at least one single
nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene as instrumental variable (IV) for body mass index, irrespective of the outcome. We reviewed: 1) the approaches used to prevent pleiotropy, 2) the methods cited to detect or control the independence or the exclusion restriction assumption highlighting whether pleiotropy assessment was explicitly stated to justify the use of these methods, and 3) the discussion of findings related to pleiotropy. We included 128 studies, of which thirty-three reported one approach to prevent pleiotropy, such as the use of multiple (independent) SNPs combined in a genetic risk score as IVs. One hundred and twenty studies cited at least one method to detect or account for pleiotropy, including robust and other IV estimation methods (
= 70), methods for detection of heterogeneity between estimated causal effects across IVs (
= 72), methods to detect or account associations between IV and outcome outside thought the exposure (
= 85), and other methods (
= 5). Twenty-one studies suspected IV invalidity, of which 16 explicitly referred to pleiotropy, and six incriminating
SNPs. Most reviewed MR studies have cited methods to prevent or to detect or control bias due to pleiotropy. These methods are heterogeneous, their triangulation should increase the reliability of causal inference.
Genetic sex and psychosocial factors relating to sex and gender influence a person's risk of developing neurocognitive impairment (NCI). Yet their role in mechanisms underlying APOE-ɛ4 ...pathophysiology of NCI remains unclear. We explore whether sex and gender independently modify the association between APOE-ɛ4 and NCI.
We conducted effect modification analyses in N=364,793 participants from the UK Biobank pan-ancestry dataset (return #2442) without prevalent cardiovascular disease or NCI. APOE-ɛ4 carrier status was inferred based on diplotypes derived from phased genotypes. NCI cases were identified in hospitalization, mortality, and self-report questionnaire datasets. Gender was measured using a previously constructed literature-based femininity score (FS) that leverages six psychosocial factors. We estimated adjusted generalized linear models (GLM) for NCI, as random effects for ancestry groups were not informative. To evaluate APOE-ɛ4 effect modification by gender, we stratified models by sex and introduced interaction terms for APOE-ɛ4 and FS. We estimated conditional effects corrected for multiplicity to illustrate modification across FS. To evaluate APOE-ɛ4 effect modification by sex, we introduced interaction terms for APOE-ɛ4 and sex and conditioned on FS. Sensitivity analyses were conducted with NCI cases identified from primary care data (N=169,125).
We identified N=6,123 participants with incident NCI in the sex-combined sample (1.7%), of which 2,990 were female. APOE-ɛ4 was associated with increased risk of NCI in females (p
Both sex and gender influence the effect of APOE-ɛ4 on NCI in diverse ancestries. More analyses are needed to clarify mechanisms by which gender influences risk conferred by APOE-ɛ4 in both sexes.
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