6th Mendelian Randomization Conference
19 to 21 June 2024
Humanities, 11 Woodland Road, Clifton, Bristol, BS8 1TB
The use of appropriate methods is key to robust estimation in all applications of Mendelian Randomization. Methodological developments can make novel applications possible or help to improve the reliability of existing areas of research. There is a wide range of ongoing topics and challenges for methodological research in MR which cut across the full range of applied areas of research to which MR is applied.
MR in multi-ancestry and non-European populations
To date, the majority of MR studies have been conducted in European populations with non-European populations often under-represented or excluded from these studies due to challenges such as data availability and technical challenges such as confounding, differences in LD structure and weak instrument bias. However, inclusion of these demographic groups is valuable and important to consider as exposure to causal risk factors and the effects of those causal risk factors in disease outcomes may be different across populations.
Focusing on contexts where there is a tendency for few or even single genetic instruments, the “Molecular traits” theme will explore the complexities of applying Mendelian randomization (MR) methodologies to seemingly simple molecular or more complex cellular and ‘omic traits, the caution is required in the interpretation of these analyses and novel methodology developed to appraise violations of MR assumptions.
Drug target MR
Drug target Mendelian Randomization uses human genetics to evaluate the on-target efficacy, safety and repurposing potential of pharmaceutical targets. Genetically supported targets are more likely to succeed in clinical trials, reducing the associated economic and social costs. Challenges include limited availability of genetic instruments and difficulties interpreting and translating results to trial design and clinical practice.
The Mental Health theme will focus on recent advances in the application of Mendelian randomisation approaches for the investigation of the causes and consequences of psychiatric, neurodevelopmental, and neurodegenerative conditions. Specifically, MR approaches have contributed towards identifying potential intervention targets and biomarkers for mental health conditions, disentangling intergenerational contributions to risk, and understanding links to cardiometabolic and other physical health conditions. This session will also consider methodological challenges regarding the application of MR and related methods for mental health research particularly genetic and phenotypic heterogeneity.
Disease progression refers to outcomes occurring after disease diagnosis, including treatment response, mortality and relapse. Mendelian randomization (MR) studies of disease progression are directly relevant to the design of pharmaceutical interventions, which typically aim to treat rather than prevent disease. However, they suffer from the same issues as conventional MR as well as smaller sample sizes and collider bias.
Infection remains a major problem in both the developed and developing worlds. Although genetic susceptibility to infection and infection-related mortality is established for certain pathogens (e.g. malaria, COVID-19), there is a relative death of MR studies in infection relative to non-communicable disease. This is despite the success of the COVID-19 Host Genetics Initiative using MR to identify and corroborate drug targets for COVID-19. In fact, the approval of baricitinib for severe COVID-19 was driven in great part by genetic data. This theme will focus on the unique challenges and opportunities of instrumentation, methods, and data in the field of infection.
New for the Conference in 2024 will be a session aimed at a wider audience. An early evening roundtable event will bring together conference delegates with a non-research audience, including older school students, undergraduates, and health professionals. Attendees will be able to take part in a series of discussions about Mendelian Randomization in some areas of research.