In a recent study published in Scientific reports, researchers in China used Mendelian randomization (MR) to guage the genetic association between body mass index (BMI) and plenty of neurological diseases.
They found that BMI showed a genetic cause-and-effect association with multiple sclerosis (MS) and ischemic stroke (IS), but not with Parkinson’s disease (PD), Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS) and epilepsy (EP). .
Test: Genetic causal role of body mass index in multiple neurological diseases. Photo credit: Recent Africa/Shutterstock.com
Background
BMI is widely utilized in the assessment of obesity attributable to its simplicity and sensitivity. Economic and lifestyle changes have increased the danger of obesity worldwide. Elevated BMI is related to quite a lot of diseases and better mortality, including type 2 diabetes, hypertension, coronary heart disease, musculoskeletal diseases and the event of cancer.
Neurological diseases cover a broad spectrum of disorders of the nervous system, including neurodegenerative, cerebrovascular, infectious, oncological and hereditary diseases.
While PD is characterised by changes in dopamine concentrations and the presence of Lewy bodies, AD is related to β-amyloid deposition and tau phosphorylation. ALS affects motor neurons, while multiple sclerosis is an immune-mediated demyelinating disease.
IS is related to various risk aspects similar to hypertension and diabetes, and EP arises from synchronized neuronal firing attributable to genetic or structural abnormalities.
MR is a technique for assessing the causal relationship between exposures and effects using genetic instrumental variables, including single nucleotide polymorphisms (SNPs). The strategy is strong to the consequences of confounding aspects and reverse causality.
Subsequently, researchers in the current study investigated the genetic associations between BMI and neurological diseases using MR evaluation, with the aim of developing disease treatment strategies.
Concerning the study
The current study used SNPs from a genome-wide association study (GWAS) dataset as instrumental variables to look at genetic causality between exposure aspects and consequence aspects.
The study used stringent criteria utilized in MR studies, ensuring robust correlations between instrumental variables and exposure aspects while controlling for potential confounding aspects.
BMI data were obtained from the Integrative Epidemiology Unit (IEU) database of nearly a million participants of European descent, with measurements for over seven million SNPs.
Data on various neurological diseases were obtained from the IEU database, including cases of PD, AD, multiple sclerosis, ALS, IS, EP and relevant controls.
Participants were primarily of European descent, aside from ALS and EP, which included people of various races and regions.
Quality control procedures have been implemented for all disease data. SNPs significantly related to BMI were subjected to cluster evaluation to exclude redundant effects. SNPs causally related to PD, AD, multiple sclerosis, ALS, IS, EP and people related to disease confounders were excluded.
Two-sample MR evaluation was used, with inverse variance weighting (IVW) because the fundamental analytical approach, supported by weighted median, Egger MR, easy mode, and weighted mode. Moreover, sensitivity evaluation used the MR-Egger method, the Cochran Q test, and the leave-one-out method to evaluate horizontal pleiotropy, heterogeneity, and the strength of causality between BMI and neurological diseases.
Results and discussion
Based on the study, significant genome-wide associations were found between BMI and SNPs in PD (42), AD (42), multiple sclerosis (39), ALS (42), IS (42), and EP (31). IVW evaluation showed no genetic causal relationship between BMI and PD, AD, ALS and epilepsy (P > 0.05).
Nevertheless, there was a positive genetic causality between BMI and MS (P = 0.035) and IS (P = 0.000). The outcomes suggest that higher BMI is related to an increased risk of MS and IS.
Furthermore, the weighted median evaluation showed a causal association between BMI and multiple sclerosis, IS, while the easy mode suggested an association with IS itself. Interestingly, Egger’s MR and weighted method analyzes didn’t show a causal relationship between BMI and the diseases studied.
The outcomes of the sensitivity evaluation were confirmed by the fundamental findings. No significant heterogeneity or pleiotropy was found, and the outcomes were confirmed as stable and reliable.
The findings were strengthened by means of robust instrumental SNPs from probably the most comprehensive GWAS database to this point.
Nevertheless, limitations of the study include its give attention to patients of European descent, potential incomplete control for all risk aspects for neurological disorders, and reliance solely on BMI without considering other body composition measures.
Future studies including waist circumference, waist-to-hip ratio, body fat percentage, and bioelectrical impedance could potentially reduce bias in the outcomes.
Application
In summary, the study demonstrates the utility of MR evaluation in investigating genetic causal associations between BMI and neurological diseases.
Although no causal association with PD, AD, ALS, or EP has been identified, a genetic causal association of BMI with MS and IS has been identified, suggesting that increased BMI may increase the danger of MS and IS.
These findings highlight the potential role of obesity as a risk factor for neurological diseases, paving the best way for prevention and treatment strategies to enhance health outcomes.