Comment on “Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study”

Dear Editor,

We read with great interest the study "Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study" by Hu et al. [1]. which was recently published on Mar 11, 2025, in the Journal of Prevention of Alzheimer's Disease. They identified the different subtypes of Alzheimer's disease (AD) using consensus clustering, extracted key module genes between the two subtypes via weighted correlation network analysis, combined the shared cluster

differentially expressed genes, key module genes, and druggable genes to generate 21 hub genes, which were subsequently filtered using various machine learning techniques, and finally conducted a two-sample Mendelian randomization (MR) analysis incorporating the identified druggable genes to ascertain the causal relationships between druggable gene expression and the risk of AD. Although acknowledging the significant contribution of that study, Hu et al. had misunderstood Fig. 8A-B in the section titled "3.7. MR analysis"—they believed that each of the genes LIMK2, MAPK8, and NDUFV2 might contribute to an enhanced risk of AD by MR in brain tissues and blood samples [1].

Fig. 8.

Identification of hub genes in AD by MR. (A) Forest plot for MR results between brain eQTL and AD. (B) Forest plot for the MR result between blood eQTL and AD. (C) MR results of AD markers and AD outcome in IVW method. (Image source: Hu et al. [1]., Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study).

The odds ratio (OR) is a commonly used metric for measuring the magnitude of an effect, particularly in the fields of epidemiological and medical research. It gauges the strength of the association between exposure factors and outcome events by comparing the ratio of the probabilities of an event occurring in the exposed group versus the non-exposed group [2]. Mendelian randomization is a research approach that utilizes natural genetic variation within observational studies to assess the causal effects of modifiable risk factors [3]. In MR analysis, an OR equal to 1 suggests that there is no statistically significant evidence to support a causal effect of genetically predicted changes in exposure levels on the risk of binary outcomes. An OR greater than 1 implies that an increase in the genetically predicted exposure level is causally associated with an elevated risk of binary outcomes, indicating that the exposure serves as a risk factor for the outcome. Conversely, an OR less than 1 indicates a causal relationship between an increase in the genetically predicted exposure level and a reduced risk of binary outcomes, suggesting that the exposure acts as a protective factor for the outcome [4]. Therefore, the accurate interpretation should be that LIMK2 may elevate the risk of AD attributable to MR, whereas MAPK8 and NDUFV2 may mitigate the risk of AD induced by MR (LIMK2 OR 1.084 (1.019–1.154), MAPK8 OR 0.943 (0.899–0.989), and NDUFV2 OR 0.943 (0.904–0.983)) in brain tissues (Fig. 8A), and (LIMK2 OR 1.097 (1.019–1.181), MAPK8 OR 0.837 (0.731–0.960), and NDUFV2 OR 0.938 (0.891–0.987)) in blood samples (Fig. 8B).

To sum up, readers ought to approach the relevant chapters with caution to guarantee precise understanding.

Funding/Support

The authors declare financial support was received for the research, authorship, and publication of this article. The authors acknowledge funding from the National Natural Science Foundation project (No. 82,072,780).

CRediT authorship contribution statement

Jihao Xue: Conceptualization, Writing – original draft. Yitian Chen: Conceptualization, Writing – original draft. Ligang Chen: Supervision, Writing – review & editing. Qijia Yin: Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Ligang Chen reports article publishing charges was provided by National Natural Science Foundation project. Reports a relationship with that includes:. Has patent pending to. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.