China
Africa
Explore chapters and articles related to this topic
Polypoidal Choroidal Vasculopathy
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Cross-sectional case–control studies have clarified an association but not a causality. Recently, however, emerging genetic data have contributed to our understanding of causal risk factors for PCV and typical nAMD. To reveal a causal relationship, genetic variants that influence modifiable risk factors can be used as their proxies in Mendelian randomization. In short, in Mendelian randomization, naturally occurring random allocation of parental alleles at meiosis, which results in genetic variants independently distributed from potential confounders, is used as instrumental variables. Such genetic variants are immune to the influences of environmental factors and reverse causation. For example, it clarifies whether genetic variants that influence plasma lipid levels affect the risk of PCV, assuming that the genetic variants are independent of PCV, and clarifies whether long-term lipid levels lead to an increased risk of PCV. Studies conducted by two independent groups suggest that plasma HDL-c is causally associated with an increased risk for AMD.51,69 In particular, Fan et al.69 found that a high level of plasma HDL-c is a causal risk factor for advanced AMD in European and Asian populations and a similar trend for the association of PCV with HDL-c level. Another study reported that higher serum CRP levels lead to an increased risk factor for AMD.70 Additionally, refractive error seems to have minimal influence on AMD risk.71
The Meta-Analysis of Genetic Studies
Published in Christopher H. Schmid, Theo Stijnen, Ian R. White, Handbook of Meta-Analysis, 2020
Cosetta Minelli, John Thompson
Mendelian randomization is a method for estimating the causal effect of a risk factor on a disease or trait using genetic variants as instrumental variables (IVs) (Smith and Ebrahim, 2003). This approach has increasingly been used in epidemiology to distinguish causality from correlation.
Etiological explanations
Published in Olaf Dammann, Etiological Explanations, 2020
Mendelian randomization is a more recently developed technique in which investigators identify a genetic variant that is strongly biologically associated with the exposure under investigation. Study participants are then divided into groups defined by the presence or absence of that same genetic variant. Since genetic traits are inherited in a random fashion, the groups are now effectively randomized; confounders are distributed equally between groups, and results turn out to be very close to those from a randomized trial (Yarmolinsky et al. 2018).
Renal function and neurodegenerative diseases : a two-sample Mendelian randomization study
Published in Neurological Research, 2023
Xue Liu, Ya-Nan Ou, Ya-Hui Ma, Liang-Yu Huang, Wei Zhang, Lan Tan
Previous studies have confirmed a correlation between renal function and cognition [5]. Cognitive decline occurred in approximately 10–40% of patients with chronic kidney disease (CKD) and it was more prevalent in patients with end-stage CKD (OR, 2.0, 95% CI 1.1 to 3.9) [6,7]. A study reported a higher risk of PD in patients with uremia [8]. Similarly, CKD patients are more likely to develop Lewy body dementia (LBD) [9]. Interestingly, Calabresi et al. found that eGFR was significantly reduced in 25 patients with progressive multiple sclerosis [10]. Although these observational studies showed associations of kidney function with cognitive decline, PD and MS [5,8–10], it remains unclear whether the observed associations were causal, since observational studies are inevitably limited by reverse causality and confounding bias. Therefore, we urgently need a method to detect whether there is a causal relationship between them. In the absence of randomized controlled trials (RCT), Mendelian randomization (MR) is a unique and convenient technique that uses genetic variation to examine the causal relationship between exposure factors and outcomes.
Association of Body Mass Index and the Risk of Gastro-Esophageal Cancer: A Mendelian Randomization Study in a Japanese Population
Published in Nutrition and Cancer, 2023
Zhaoping Zang, Yi Shao, Rena Nakyeyune, Yi Shen, Chen Niu, Lingyan Zhu, Xiaoli Ruan, Tong Wei, Ping Wei, Fen Liu
Although traditional observational studies can confirm the effect of BMI on upper GI cancer risk, the mechanisms underlying the contribution of BMI to cancer risk remain poorly understood. Therefore, the existence of a causal relationship is disputable. Evidence that probes the causality between BMI and cancer is urgently needed to establish preventive measures. Mendelian randomization (MR) studies could potentially improve causal inference. MR is a method used to estimate the association between a risk factor and a disease using genetic variants, such as single nucleotide polymorphisms (SNPs) associated with risk factors as instrumental variables (IVs) (9, 10). In previous MR studies, BMI was found to be positively associated with esophageal adenocarcinoma (11) and pancreatic (12), small cell lung (13), and colorectal cancers (14) and to be negatively associated with breast cancer (15) in European populations. In another MR study of BMI and cancer in European populations, no causal association was found between BMI and stomach or esophageal cancers (16). However, there is a lack of MR studies for upper GI cancers in Asian populations. Therefore, relevant studies are needed to investigate the causal relationship between BMI and upper GI cancers.
Leveraging “big data” in respiratory medicine – data science, causal inference, and precision medicine
Published in Expert Review of Respiratory Medicine, 2021
Yoshihiko Raita, Carlos A. Camargo, Liming Liang, Kohei Hasegawa
Second, with the rise of publicly available GWAS datasets from large consortiums and biobanks, Mendelian randomization has become a powerful tool in answering various queries. Mendelian randomization builds on the random assignment of genotypes transferred from parents to offspring at conception and uses the genetic variants as instruments. This method allows scientists to relate the genetic variants for modifiable exposures with health outcomes [12], thereby investigating the causal role of phenotypic risk factors (e.g. obesity) and molecular intermediates (e.g. epigenetic factors, proteins) in respiratory diseases [2]. The advent of Mendelian randomization approaches – in conjunction with the increased availability of expanded data sources (e.g. epigenetic and protein quantitative trait loci studies [13]) – has informed the search for new therapeutic targets.