Genetic Insights into the Risk of Metabolic Syndrome and Its Components on Dementia: A Mendelian Randomization

INTRODUCTION

Dementia is characterized by a chronic and progressive decline affecting cognitive function in aged adults [1]. Generally, the main types of dementia consist of Alzheimer’s disease (AD), vascular dementia, frontotemporal dementia, dementia with Lewy bodies, and dementia in Parkinson’s disease. It is estimated that there have 50 million patients around the world [2]. More seriously, the number of cases is dramatically increasing due to the increasing life expectancy and risk factors [3], which puts a heavy burden on individuals, families, health care, and society. Therefore, strategies for preventing and alleviating dementia are priorities in healthcare.

Metabolic syndrome (MetS) is a cluster of pathological conditions based on the World Health Organization’s (WHO) definition, including glucose abnormalities, hyperlipidemia, central obesity, and hypertension [4]. At present, the incidence of MetS is increasing rapidly, and approximately 25% adults have MetS [5]. Some studies have shown that MetS has a positive association with the risk of dementia [6, 7], while no association is observed, even the inverse relationship in other studies [8, 9]. In addition, obvious confounding factors such as the study design and retrospective features are inherent shortcomings in these observational studies, which may interfere with the understanding of these conclusions.

Mendelian randomization (MR), as a genetic approach, is a robust statistical analysis using genetic variants to make a causal inference, which can overcome the limitation of observational studies [10]. During gestation, single nucleotide polymorphism (SNP), a genomic variant at a single base position in the deoxyribonucleic acid (DNA), is assorted randomly in forming a zygote [11]. However, no study has been conducted to investigate the causal association of MetS and its five components on dementia. Therefore, we performed this MR analysis to illustrate their causal links.

METHODS

Study design

The overview of our MR study is shown in Fig. 1. In our study, we explored the causal relationship between MetS, waist circumference (WC), hypertension, fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and different dementia types, including AD, vascular dementia, frontotemporal dementia, dementia with Lewy bodies, and dementia due to Parkinson’s disease. No ethical approval is required due to the analysis of the public summary-level datasets.

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Fig. 1

The flow chart of our MR analysis. MetS, metabolic syndrome; MR, Mendelian randomization; SNP, single nucleotide polymorphism; HDL-C, high-density lipoprotein cholesterol.

RESULTS

The casual effects of genetically predicted MetS and its components on dementia

The results of this MR study are presented in Table 2. The demographic characteristics for dementia are displayed in Tables 3–5.

As to any dementia, it can be found that MetS, WC, hypertension, FBG, TG, and HDL-C are not causally associated with the risk of any dementia (all p > 0.0016, Table 2, Fig. 2). The results of Cochran’s Q analysis show a visible heterogeneity between TG and any dementia (Table 2), while a symmetry of MR results in the funnel plot (Fig. 3) is observed. In the MR-Egger and MR-PRESSO analyses, no pleiotropy is identified (MR-Egger: all p > 0.05; MR-PRESSO: all p > 0.05, Table 2). Additionally, no influential SNPs are detected in the leave-one-out analysis when excluding any one of the SNP in turn (Fig. 4). Figure 5 presents the results of the causal estimate of every SNP on any dementia.

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Fig. 2

The scatter plots of the association between genetically predicted MetS and its components on dementia in the MR analysis. MetS, metabolic syndrome; WC, waist circumference; FBG, fasting blood glucose; TG, triglycerides; HDL-C, high-density lipoprotein cholesterol; AD, Alzheimer’s disease; VD, vascular dementia; FD, frontotemporal dementia; DLB, dementia with Lewy bodies; D-PD, dementia due to Parkinson’s disease.

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Fig. 3

The funnel plots of the association between genetically predicted MetS and its components on dementia in the MR analysis. AD, Alzheimer’s disease; VD, vascular dementia; FD, frontotemporal dementia; DLB, dementia with Lewy bodies; HDL-C, high-density lipoprotein cholesterol; MR, Mendelian randomization; D-PD, dementia due to Parkinson’s disease.

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Fig. 4

The leave-one-out analysis of the association between genetically MetS and its components on dementia in the MR analysis. AD, Alzheimer’s disease; VD, vascular dementia; FD, frontotemporal dementia; DLB, dementia with Lewy bodies; HDL-C, high-density lipoprotein cholesterol; MR, Mendelian randomization; D-PD, dementia due to Parkinson’s disease.

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Fig. 5

The frost plots of the association between genetically MetS and its components on dementia in the MR analysis. AD, Alzheimer’s disease; VD, vascular dementia; FD, frontotemporal dementia; DLB, dementia with Lewy bodies; HDL-C, high-density lipoprotein cholesterol; MR, mendelian randomization; D-PD, dementia due to Parkinson’s disease.

For AD, the results of IVW method show that no causal relationship of MetS and its subtypes is identified (all p > 0.0016, Table 2, Fig. 2). No evidence of heterogeneity is detected in Cochran’s Q analysis (all p > 0.05, Table 2) and the funnel plot (Fig. 3). Furthermore, no signs of pleiotropy is found in MR-Egger and MR-PRESSO analyses (Table 2). The leave-one-out analyses indicate the robustness of our MR results (Fig. 4). The causal estimate of each IV on AD is shown in Fig. 5.

In MR analysis for vascular dementia, we do not observe significant causal association between MetS, its subtypes, and vascular dementia (all p > 0.0016, Table 2, Fig. 2). In sensitivity analysis, Cochran’s Q test does not find any heterogeneity (Fig. 3, Table 2). In addition, there is no evidence of pleiotropyin MR-Egger and MR-PRESSO analyses (Table 2). The causal estimates are not driven by single SNP in the leave-one-out analysis (Fig. 4, Table 2). The frost plot manifesting the casual estimate of every SNP on vascular dementia is shown in Fig. 5.

As to frontotemporal dementia, there is no causal association between MetS, WC, hypertension, FBG, TG, HDL-C, and frontotemporal dementia (all p > 0.0016, Table 2, Fig. 2). Although the results in Cochran’s Q test demonstrate a visible heterogeneity between MetS and frontotemporal dementia (Table 2), the funnel plot reveals a symmetry of MR results (Fig. 3). We do not find pleiotropy in MR-Egger and MR-PRESSO analyses (Table 2), and the results of leave-one-out analysis remain robust (Fig. 4, Table 2). The causal estimate of each IV on frontotemporal dementia is displayed in frost plot (Fig. 5).

HDL-C decreases the risk of dementia with Lewy bodies (odd ratios (OR) = 0.81, 95% confidential index (CI) = 0.72–0.92, p = 0.0010), while no causal relationship is observed between MetS, WC, hypertension, FBG, TG, and dementia with Lewy bodies (all p > 0.0016, Table 2, Fig. 2). The funnel plot is symmetrical despite a visible heterogeneity in Cochran’s Q analysis (Table 2, Fig. 3). MR-Egger method and MR-PRESSO do not find potential pleiotropy (Table 2). The results of the leave-one-out analysis are stable (Fig. 4). The causal estimate of each SNP on dementia with Lewy bodies is depicted in Fig. 5.

As shown in Table 2 and Fig. 2, MetS and its five components are not causally related to dementia due to Parkinson’s disease (all p > 0.05). In sensitivity analyses, although there has pleiotropy (MR-Egger: p-Egger intercept <0.05, Table 2), the relationship still does not exist after performing CAUSE analysis (p = 0.94). There is no evidence of heterogeneity according to the findings of Cochran’s Q test and the funnel plot (Fig. 3, Table 2). Additionally, the robustness of the MR estimates is verified by the leave-one-out analysis (Fig. 4). Figure 5 demonstrates the casual estimate of each SNP on dementia due to Parkinson’s disease.

DISCUSSION

In our MR analysis, we find that no significant causal association exists between MetS, its five components, and different dementia types, including any dementia, AD, vascular dementia, frontotemporal dementia, dementia with Lewy bodies, and dementia due to Parkinson’s disease, except for the relationship between HDL-C and dementia with Lewy bodies. HDL-C may play a protective role in dementia with Lewy bodies.

The previous results of the association between MetS, its components, and dementia is summarized in Table 6. The role of MetS on any dementia is not yet concluded. Some studies support the association between MetS and any dementia. For example, a cohort study including 1,519 participants conducted in Singapore finds that the MetS is associated with an increased risk of dementia [6]. The findings in the Whitehall II study also reveal that persistent MetS decline cognitive performance in late midlife [7]. In contrast, other studies do not support the association. In a cross-sectional and prospective study consisting of 2,476 men and women aged 65 years, researchers find that MetS is not associated with the increasing risk of dementia after 4.4 years of follow-up [8]. A recent meta-analysis including 18,313 participants ranging from January 1, 2000 to August 31, 2018 shows that no statistical significance pooled association emerges between MetS and dementia [27]. Some studies even support the protective role of MetS on dementia [9]. In our MR study, we do not identify the causal association between MetS and any dementia.

For the relationship between five components of MetS and any dementia, the association remains inconsistent. As to waist circumference, Abbatecola and his colleagues think that WC can predict the risk of cognitive decline during the 12-year follow-up in older patients with diabetes [28]. However, a study including 2,565 men and women does not find the association [29]. In our MR study, we do not support the causal association. The effect of hypertension on dementia remains unclear. Considering the numerous factors affecting hypertension, such as age and hypertension chronicity, the role of hypertension in dementia is complex [30]. For example, large epidemiological studies have demonstrated a consistent association between high midlife blood pressure and cognitive decline, while a similar association between late-life blood pressure and cognition decline is not consistent [31]. From the perspective of neuroimage, a recent study finds that hypertension may alter brain structure and function, which may result in disruption in cognitive function [32]. However, the causal association between hypertension and dementia does not exist in this study. FBG represents the abnormality of glucose level and is recognized as a well-known risk factor for dementia [33, 34], while we do not identify the causal association. In the association of TG, HDL-C, and dementia, the results also remain inclusive [35 –37]. Our MR analysis does not find a causal relationship.

Inconsistent conclusions are also obtained about the association between MetS, its components, and AD [27, 38]. A meta-analysis, including a total of 18,313 participants aged older than 40 years with mean MetS prevalence of 22.7% and followed on average for 9.41 years, found that no significant pooled association existed between MetS and AD [27]. However, contradictory results also been reported [39], and the inverse association also have been observed [40]. As for MetS components, the effects on AD remain inconsistent. For example, a meta-analysis including 16 cohort studies and 41,781 participants and 4,511 dementia cases, no beneficial impacts of obesity in older age on incident dementia is found [41]. However, a study including a total of 10,308 adults found the detrimental effects on AD incidence [42]. In our MR study, no causal association between MetS, its components and the risk of AD were identified.

The studies related to the role of MetS on vascular dementia support the detrimental effect of MetS and may increase the risk of vascular dementia [43, 44], although these studies are scarce. In the Italian Longitudinal Study on Ageing including a total of 2,097 participants (MetS subjects [n = 918], subjects without MetS [n = 1,179]), studies found that MetS elevated the risk of vascular dementia [44]. So far, potential associations between frontotemporal dementia, and head trauma [45], diabetes [46], and autoimmune conditions may exist [47]. However, the study about the causal association between MetS and frontotemporal dementia is limited [48]. The study related to the association between MetS and dementia with Lewy bodies [49] and dementia due to Parkinson’s disease is also scarce, and no association between MetS, its components and dementia due to Parkinson’s disease was identified [50]. In our MR study, we find no significant casual association between MetS, its components and vascular dementia, frontotemporal dementia, and dementia due to Parkinson’s disease. As for dementia with Lewy bodies, Dou and colleagues thought that reduced levels of HDL-C were associated with the development of dementia with Lewy bodies in a case-control study including 65 patients with Lewy body dementia and 110 older adult controls [51]. Several studies also supported the relationship [52, 53].

Many observational studies may be influenced by many confounding factors such as limited sample size or (and) retrospective study. The strength of our MR study overcomes the possible confounders and clarifies the causal association between MetS and different dementia types. Additionally, it is the first study to illustrate their association. However, this study has several limitations. Firstly, the cases of different dementia are relatively small. Second, there is an ethnic bias because the datasets are all of European ancestry, which may limit the generalization of the conclusion. Third, we do not make stratification based on some factors such as age and gender due to the unavailability of stratification datasets. Future studies are required to verify these association in other ancestries, larger studies, and proper stratification people.