TITLE: Systematic review and meta-analysis of Mendelian randomisation studies on modifiable risk factors for dementia
AUTHORS: Liam Seungjin Lee, William Whiteley, Rosie Walker

[STEPS]
?. [Data sources and search strategy]
Articles will be selected for consideration through three stages. Uncertainties will resolved by discussion between two  reviewers. In stage 1, article relevance will be assessed from the title and abstract of the articles. Inclusion criteria in stage 1.- Published and pre-print primary MR studies- Outcome of any type of dementia- Risk factors investigating any of systolic blood pressure, diastolic blood pressure, HDL, LDL, triglycerides, total cholesterol, BMI, diabetes, or plasma glucose. If the risk factors were not explicitly mentioned in title or abstract, these studies were tentatively included for Stage 2 assessment. Exclusion criteria in stage 1. - Non-English articles- Duplicates - Unavailable full textsIn stage 2, relevance will be further assessed by reading the full texts. Full texts will be accessed through an institutional libraryInclusion criteria in stage 2.- Risk factors investigating any of systolic blood pressure, diastolic blood pressure, HDL, LDL, triglycerides, total cholesterol, BMI, diabetes, or plasma glucose. - Reported causal estimate value of either odds ratio, hazard ratio, relative risk or beta coefficient using inverse-variance weighted method in either main text or supplementary material.- Reported value of either standard deviation, standard error, or 95% confidence interval in either main text or supplementary material. In stage 3, forward searching will be performed from the selected studies to identify additional studies. Newly added studies will be processed as per stage 1 and 2.
?. [Data sources and search strategy]
Literature search will be performed via OVID and Web of Science. These cover 13 databases: Medline, Embase, AMED, PsycINFO, BIOSIS Citation Index, Web of Science core collection, Current Contents Connect, Data Citation Index, Derwent Innovations Index, KCI-Korean Journal Database, Russian Science Citation Index, SciELO Citation Index, Zoological Record. Following search syntaxes will be employed. OVID:(exp Dementia/ or exp Cognition Disorders/ or dement* or alzheimer* or cognit* or neurocognit* or ((cognit* or memory or cerebr* or mental*) adj3 (declin* or impair* or los* or deteriorat* or degenerat* or deficit* or complain* or disturb* or disorder* or dysfunction* or insufficien* or fail*)))AND(exp Mendelian Randomization Analysis/ or (Mendelian adj1 random*) or (MR not (magnetic or resonance or imag* or receptor)) or (instrumental adj1 variable*) or (genetic adj1 instrument))Web of Science:TS=(dement* OR Alzheimer* OR cognit* OR neurocognit* OR memory OR cerebr* OR mental*) AND TS=(“Mendelian random*” OR “instrumental variable*” OR “genetic instrument*")
?. [Background]
Dementia is a clinical syndrome of progressive cognitive decline and loss of everyday functioning (Chertkow et al., 2013). It is caused by a variety of disease processes, most commonly Alzheimer's disease (Duong, Patel and Chang, 2017). Worldwide prevalence of dementia has nearly doubled since 1990 to 2016 due to population ageing (Nichols et al., 2019). The economic burden of dementia is projected to rise significantly in the next coming decades (Wittenberg et al., 2020). Studies of risk factors have identified education, physical activity, and cardiovascular risk factors (Baumgart et al., 2015). Importantly, approximately a third of Alzheimer's disease cases are thought to develop from modifiable risk factors (Norton et al., 2014). Although observational studies have identified risk factors in general populations, they are limited by residual confounding (for example by education) (Carlson and Morrison, 2009).   Mendelian Randomisation (MR) used genetic variants as proxy for risk factor of interest to generate estimates that are less susceptible to some types of confounding (Smith and Hemani, 2014). However, there are few primary MR studies on modifiable risk factors and dementia with differing estimates. To date, only one descriptive systematic review on dementia from MR studies has been published (Kuźma et al., 2018). Therefore, we aim to perform an updated systematic review and meta-analysis of MR that will provide further insight into the causative factors of dementia. Our protocol has been adapted from PRISMA and MOOSE (Meta-analysis Of Observational Studies in Epidemiology) guidelines (Stroup et al., 2000; Moher et al., 2009). The aim of this planned meta-analysis is to:1) Assess the causal effect of modifiable risk factors associated with dementia; 2) Quantify the effect of modifiable risk factors on the risk of dementia; 3) Provide information to guide intervention in preventing or delaying onset of dementia.
?. [Quality assessment]
Quality assessment questionnaire was developed through synthesizing three published guidelines (Davies, Holmes and Davey Smith, 2018; Grover, Del Greco and König, 2018; Burgess et al., 2020). Primary focus was put on determining authors' considerations for the three main assumptions of Mendelian randomisation studies: 1) Instrumental variable is associated with risk factor of interest; 2) There are no confounders between instrumental variable and outcome; 3) Instrumental variable affects outcome only through the risk factor of interest.
Quality assessment questionnaire1. Are outcome and exposure samples drawn from same ethnic population?2. Are outcome and exposure samples independent?3. Assumption 1 - Is there sufficient evidence that the variants are robustly associated with the risk factor?4. Assumption 2 - Do authors consider confounders of association between genetic variants and outcome?5. Assumption 3 - Do authors consider other biological mechanism of genetic variants other than risk factor of interest?6. Are variants manually picked (e.g. to tackle pleiotropy)?7. Are variants pruned to include independent instruments (linkage disequilibrium)?8. Are the effect and other alleles coded in the same direction for the exposure and outcome (variable harmonization)?9. Is MR estimate compared with conventional observational estimate?10. Is sensitivity analysis performed?11. Is data available in a supplement or by request to allow researchers to reproduce their findings?
?. [Data analysis]
Qualitative data analysis:Selected data will be summarised with baseline study characteristics as described above, exposure cohort and outcome cohort.Quantitative data analysis:Units will be standardised to common units. For studies which presented standard errors, values will be converted to 95% CI. Data will be analysed using the R package 'meta' (Balduzzi, Rücker and Schwarzer, 2019). Odds ratios (OR) from inverse-weighted variance analysis will be pooled to give an overall estimate using fixed effects model for each risk factor. The OR of individual studies, the overall estimates, and 95% CI will be represented on a forest plot.     Heterogeneity analysis:Assess heterogeneity across studies with I2 statistics. Increasing value is an indication of heterogeneity where 0-25% is low heterogeneity, 50-75% is moderate heterogeneity, and >75% is high heterogeneity (Higgins et al., 2003). If a study is outside 95% CI, we will perform "one study removed" method to determine if one result is skewing the overall effect size.  Publication bias will be assessed using Funnel plot and Egger's regression.
?. [Data extraction]
Baseline study characteristics will be extracted - title, year of publication, author, exposure(s) and outcome(s).For the exposure(s) of each study, the following will be extracted:- Exposure source article title and year - Cohort- Cohort inclusion and exclusion criteria- Covariates- Sex- SNP linkage disequilibrium r^2 cut-off- Number of SNPsFor the outcome(s) of each study, the following will be extracted:- Outcome source article title and year- Cohort- Case sample size- Control sample size
?. [Publication]
This paper will be submitted as a conference abstract and a journal submission.
?. [References]
Balduzzi, S., Rücker, G. and Schwarzer, G. (2019) ‘How to perform a meta-analysis with R: A practical tutorial’, Evidence-Based Mental Health. BMJ Publishing Group, 22(4), pp. 153–160. doi: 10.1136/ebmental-2019-300117.Baumgart, M. et al. (2015) ‘Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective’, Alzheimer’s and Dementia. Elsevier Inc., 11(6), pp. 718–726. doi: 10.1016/j.jalz.2015.05.016.Burgess, S. et al. (2020) ‘Guidelines for performing Mendelian randomization investigations’, Wellcome Open Research. F1000 Research Ltd, 4. doi: 10.12688/wellcomeopenres.15555.2.Carlson, M. D. A. and Morrison, R. S. (2009) ‘Study design, precision, and validity in observational studies’, Journal of Palliative Medicine. Mary Ann Liebert, Inc., 12(1), pp. 77–82. doi: 10.1089/jpm.2008.9690.Chertkow, H. et al. (2013) ‘Definitions of dementia and predementia states in Alzheimer’s disease and vascular cognitive impairment: consensus from the Canadian conference on diagnosis of dementia’, Alzheimer’s Research & Therapy. Springer Nature, 5(Suppl 1), p. S2. doi: 10.1186/alzrt198.Davies, N. M., Holmes, M. V. and Davey Smith, G. (2018) ‘Reading Mendelian randomisation studies: A guide, glossary, and checklist for clinicians’, BMJ (Online). BMJ Publishing Group, 362. doi: 10.1136/bmj.k601.Duong, S., Patel, T. and Chang, F. (2017) ‘Dementia: What pharmacists need to know’, Canadian Pharmacists Journal. Canadian Pharmacists Association, 150(2), pp. 118–129. doi: 10.1177/1715163517690745.Grover, S., Del Greco, F. and König, I. R. (2018) ‘Evaluating the current state of Mendelian randomization studies: A protocol for a systematic review on methodological and clinical aspects using neurodegenerative disorders as outcome’, Systematic Reviews. BioMed Central Ltd., 7(1), p. 145. doi: 10.1186/s13643-018-0809-3.Higgins, J. P. T. et al. (2003) ‘Measuring inconsistency in meta-analyses’, British Medical Journal. BMJ Publishing Group, pp. 557–560. doi: 10.1136/bmj.327.7414.557.Kuźma, E. et al. (2018) ‘Which Risk Factors Causally Influence Dementia? A Systematic Review of Mendelian Randomization Studies’, Journal of Alzheimer’s Disease. IOS Press, 64(1), pp. 181–193. doi: 10.3233/JAD-180013.Moher, D. et al. (2009) ‘Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement’, PLoS Medicine. PLoS Med. doi: 10.1371/journal.pmed.1000097.Nichols, E. et al. (2019) ‘Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016’, The Lancet Neurology. Lancet Publishing Group, 18(1), pp. 88–106. doi: 10.1016/S1474-4422(18)30403-4.Norton, S. et al. (2014) ‘Potential for primary prevention of Alzheimer’s disease: An analysis of population-based data’, The Lancet Neurology. Lancet Publishing Group, 13(8), pp. 788–794. doi: 10.1016/S1474-4422(14)70136-X.Smith, G. D. and Hemani, G. (2014) ‘Mendelian randomization: Genetic anchors for causal inference in epidemiological studies’, Human Molecular Genetics. Oxford University Press, 23(R1). doi: 10.1093/hmg/ddu328.Stroup, D. F. et al. (2000) ‘Meta-analysis of observational studies in epidemiology: A proposal for reporting’, Journal of the American Medical Association. American Medical Association, 283(15), pp. 2008–2012. doi: 10.1001/jama.283.15.2008.Wittenberg, R. et al. (2020) ‘Projections of care for older people with dementia in England: 2015 to 2040’, Age and Ageing. Oxford University Press, 49(2), pp. 264–269. doi: 10.1093/ageing/afz154.
?. [Discussion]
Here we provide a protocol for systematic review and meta-analysis of MR studies investigating risk factors for dementia. Our findings will provide a better insight into the modifiable causes of dementia. This will ultimately contribute with suggestions for interventions and guide future clinical trials. Considering the growing burden of dementia in conjunction with the expansion of primary MR studies, this protocol is timely and may even be adapted for meta-analysis of MR studies investigating other outcomes.