Maternal and fetal origins of offspring blood pressure: statistical analysis using genetic correlation and genetic risk score-based Mendelian randomization

Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Evaluating causal influence of maternal educational attainment on offspring birthweight via observational study and Mendelian randomization analyses

Background

Although extensive discussions on the influence of maternal educational attainment on offspring birthweight, the conclusion remains controversial, and it is challenging to comprehensively assess the causal association between them.

Methods

To estimate effect of maternal educational attainment on the birthweight of first child, we first conducted an individual-level analysis with UK Biobank participants of white ancestry (n = 208,162). We then implemented Mendelian randomization (MR) methods including inverse variance weighted (IVW) MR and multivariable MR to assess the causal relation between maternal education and maternal-specific birthweight. Finally, using the UK Biobank parent-offspring trio data (n = 618), we performed a polygenic score based MR to simultaneously adjust for confounding effects of fetal-specific birthweight and paternal educational attainment. We also conducted simulations for power evaluation and sensitivity analyses for horizontal pleiotropy of instruments.

Results

We observed that birthweight of first child was positively influenced by maternal education, with 7 years of maternal education as the reference, adjusted effect = 44.8 (95%CIs 38.0-51.6, P = 6.15 × 10-38), 54.9 (95%CIs 47.6-62.2, P = 4.21 × 10-128), and 89.4 (95%CIs 82.1-96.7, P = 4.28 × 10-34) for 10, 15 and 20 years of maternal educational attainment, respectively. A causal relation between maternal education and offspring birthweight was revealed by IVW MR (estimated effect = 0.074 for one standard deviation increase in maternal education years, 95%CIs 0.054-0.093, P = 2.56 × 10-13) and by complementary MR methods. This connection was not substantially affected by paternal education or horizontal pleiotropy. Further, we found a positive but insignificant causal association (adjusted effect = 24.0, 95%CIs -150.1-198.1, P = 0.787) between maternal education and offspring birthweight after simultaneously controlling for fetal genome and paternal education; this null causality was largely due to limited power of small sample sizes of parent-offspring trios.

Conclusion

This study offers supportive evidence for a causal association between maternal education and offspring birthweight, highlighting the significance of enhancing maternal education to prevent low birthweight.

Causal relationship between gut microbiota and gastrointestinal diseases: a mendelian randomization study

BACKGROUND

Recent research increasingly highlights a strong correlation between gut microbiota and the risk of gastrointestinal diseases. However, whether this relationship is causal or merely coincidental remains uncertain. To address this, a Mendelian randomization (MR) analysis was undertaken to explore the connections between gut microbiota and prevalent gastrointestinal diseases.

METHODS

Genome-wide association study (GWAS) summary statistics for gut microbiota, encompassing a diverse range of 211 taxa (131 genera, 35 families, 20 orders, 16 classes, and 9 phyla), were sourced from the comprehensive MiBioGen study. Genetic associations with 22 gastrointestinal diseases were gathered from the UK Biobank, FinnGen study, and various extensive GWAS studies. MR analysis was meticulously conducted to assess the causal relationship between genetically predicted gut microbiota and these gastrointestinal diseases. To validate the reliability of our findings, sensitivity analyses and tests for heterogeneity were systematically performed.

RESULTS

The MR analysis yielded significant evidence for 251 causal relationships between genetically predicted gut microbiota and the risk of gastrointestinal diseases. This included 98 associations with upper gastrointestinal diseases, 81 with lower gastrointestinal diseases, 54 with hepatobiliary diseases, and 18 with pancreatic diseases. Notably, these associations were particularly evident in taxa belonging to the genera Ruminococcus and Eubacterium. Further sensitivity analyses reinforced the robustness of these results.

CONCLUSIONS

The findings of this study indicate a potential genetic predisposition linking gut microbiota to gastrointestinal diseases. These insights pave the way for designing future clinical trials focusing on microbiome-related interventions, including the use of microbiome-dependent metabolites, to potentially treat or manage gastrointestinal diseases and their associated risk factors.