Skip to main content
Download PDF
Download ePub

A mediation analysis of the role of total free fatty acids on pertinence of gut microbiota composition and cognitive function in late life depression

Lipids in Health and Disease volume 23, Article number: 64 (2024) Cite this article

Abstract

Background

Extensive evidence demonstrates correlations among gut microbiota, lipid metabolism and cognitive function. However, there is still a lack of researches in the field of late-life depression (LLD). This research targeted at investigating the relationship among gut microbiota, lipid metabolism indexes, such as total free fatty acids (FFAs), and cognitive functions in LLD.

Methods

Twenty-nine LLD patients from the Cognitive Outcome Cohort Study of Depression in Elderly were included. Cognitive functions were estimated through the Chinese version of Montreal Cognitive Assessment (MoCA). Blood samples were collected to evaluate serum lipid metabolism parameters. Fecal samples were evaluated for gut microbiota determination via 16S rRNA sequencing. Spearman correlation, linear regression and mediation analysis were utilized to explore relationship among gut microbiota, lipid metabolism and cognitive function in LLD patients.

Results

Spearman correlation analysis revealed significant correlations among Akkermansia abundance, total Free Fatty Acids (FFAs) and MoCA scores (P < 0.05). Multiple regression indicated Akkermansia and total FFAs significantly predicted MoCA scores (P < 0.05). Mediation analysis demonstrated that the correlation between decreased Akkermansia relative abundance and cognitive decline in LLD patients was partially mediated by total FFAs (Bootstrap 95%CI: 0.023–0.557), accounting for 43.0% of the relative effect.

Conclusion

These findings suggested a significant relationship between cognitive functions in LLD and Akkermansia, as well as total FFAs. Total FFAs partially mediated the relationship between Akkermansia and cognitive functions. These results contributed to understanding the gut microbial-host lipid metabolism axis in the cognitive function of LLD.

Background

Late-life depression (LLD) refers to depression that occurs over 60 years of age, and primary depression first occurring in old age is one of the special forms, which is the object of this study. Cognitive decline is a prominent symptom in LLD patients, thereby increasing the risk of dementias [1]. Authoritative findings indicated that in association with late-onset LLD (onset after age 70), the morbidity risk of Alzheimer's disease (AD) nearly doubles [2]. Current medications for the cognitive impairment of LLD often exhibited poor efficacy, which leads to the persistence of symptoms [3]. Therefore, exploring the mechanism underlying cognitive impairment in LLD and identifying new therapeutic targets is of paramount importance.

Recently, the microbiome-gut-brain axis emerged to be a concept closely associated with brain function [4] and the pathogenesis of various neuropsychiatric diseases. This axis bi-directionally regulated the intestinal microbiome and brain function through neuroanatomical pathways, neuroimmune and neuroendocrine pathways, intestinal mucosal barrier, microbial metabolites, and blood–brain barrier. Studies demonstrated gut microbiota strongly relates to cognitive function. For instance, Zhou [5] discovered that Sphingomonas exhibited a negative association with overall cognitive function in AD patients, whereas Anaerobacterium and Papillibacter were positively related to cognitive function. Mice transplanted with feces from patients with Schizophrenia showed impairments in learning ability, which was similar to their donors [6]. Lactobacillus rhamnosus could regulate cognitive function in anxious–depressed mice [7]. Numerous researches reported the abnormalities in serotonin signaling pathway could be mediated by probiotics, further confirming vital roles of gut microbiota in cognitive symptoms of depression in the elderly [8,9,10]. However, to date, the roles of the gut microbiome in cognitive deficits among LLD patients remain unexplored.

Most research concentrated on the impact on gut microbial metabolites on neurotransmitters and neuroinflammation, with a focus on the proximal part of the nervous system [11]. A variety of researchers claimed the nonnegligible pertinence among the intestinal flora, endocrine and metabolic pathology [12, 13], such as obesity and diabetes [4]. Additionally, studies also found that the gut microbiota played an important role in lipid metabolism [14]. The increase of specific depression-related microbiota, such as Firmicutes and Streptococcus could up-regulate the levels of cholesterol substances [15]. Academic circles emphasized the correlation between lipid metabolism and cognitive function. For example, the apolipoprotein E (ApoE) gene [16], apolipoprotein C1 (ApoC1) gene [17] and Clusterin (CLU) gene [18], which strongly related to AD pathogenesis, were involved in the regulation of lipid transport. Excessive cholesterol levels in the brain can produce more Aβ deposits, thereby increasing the risk of dementia [19]. However, few studies emphasized the impact of gut microbiota on cognitive functions in LLD through its influence on lipid metabolism.

Hence, our research targeted at exploring cognitive functions in LLD patients and their relationships with the gut microbiota composition and lipid metabolism through mediation analysis. The study hypothesized that lipid metabolism mediated the pertinence between gut microbiota and cognitive function in LLD patients.

Methods

Participants

All the participants or their caregivers signed informed consent forms and completed questionnaires to collect demographic information, which involved age, sex, body mass index (BMI), education years, self-reported history of hypertension and diabetes, smoking status, alcohol use history, neuropsychological assessment and gastrointestinal conditions. This research adhered the Declaration of Helsinki and obtained approval from the Ethics Committee of Zhejiang Provincial People's Hospital (2019KY184).

Untreated LLD patients were recruited from the Department of Psychiatry in Zhejiang Provincial People's Hospital from Jan. 2020 to Dec. 2021. The inclusion criteria for the LLD group were: (1) patients ranging in age from 60 to 85 years and (2) patients with first onset and met the Major Depressive Disorder(MDD) criteria in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria after the age of 60 years [20].

The following patients were excluded from the study [20]: had (1) depression caused by other neuropsychiatric diseases (neurodegenerative diseases, dementia, schizophrenia, bipolar disorder, etc.); (2) serious cardiovascular, kidney, gastrointestinal, nervous system, blood system, tumor or other related physical diseases; and (3) a history of psychoactive substance abuse. In addition, on the basis of previous work, this study adopted a series of exclusion criteria to exclude other factors that may affect the gut microbiota [21, 22]: (1) had undergone gastrointestinal surgery within 5 years; (2) had current gastrointestinal diseases such as gastrointestinal bleeding, ulcers, Crohn's disease, irritable bowel syndrome, untreated Helicobacter pylori infection, long-term diarrhea, cancer, etc.; and (3) had used probiotics, prebiotics, antibiotics or other drugs within three months before sampling.

Neuropsychological assessment

All patients underwent medical history assessment and psychiatric examination by two highly trained psychiatrists. On the day of enrollment, the cognitive function of LLD patients was evaluated via Montreal Cognitive Assessment (MoCA) and disease severity was evaluated via Geriatric Depression Scale 30 item (GDS-30). MoCA was designed by Professor Nasreddine in 2004 [23]. It can be used to assess cognitive domains, including attention, language, memory, executive ability, visuospatial ability, orientation, calculation and abstract thinking. The total score is 30 points, with a normal value considered to be ≥ 26 points. The GDS-30, developed by Brink et al. in 1982, serves as a depression screening scale specifically designed for the elderly [24]. The scale consists of 30 items representing the core performance of depression in the elderly, with rating categories including moderate to severe depression (above 21), mild depression (11–20), and no risk (0–10).

Blood collection and lipid metabolism indicators measurements

After the patients were enrolled, 5 mL of peripheral venous blood was obtained on an empty stomach, and the serum was collected. Low density lipoprotein (LDL), high density lipoprotein (HDL), ApoE, apolipoprotein B (ApoB), apolipoprotein A1 (ApoA1), Triglyceride (TG), total cholesterol (TC), total FFAs, and lipoprotein A (LPPA) were assayed by AU400 automatic biochemical analyzer (Olympus Corporation, Japan).

Gut microbiota characteristic processing

First, 5.0 g of fresh midcourse stool sample was collected 1 day before treatment and stored in a sterile container without urine. After adding a deoxyribonucleic acid stabilizer, the sample was reserved at -80℃ for examination. Next, deoxyribonucleic acid extraction was performed via nucleic acid extraction kit (Hangzhou Guhe: GHFDE100), with concentration and quality assessed using a NanoDrop luminance meter (Thermo Fisher Scientific, USA). All samples were verified through agarose gel electrophoresis. Then, the bacterial V4 fragment of 16 S rRNA was amplified utilizing the 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 806R (5'-GGACTACHVGGGTWTCTAAT-3') primers via PCR. The amplified fragments were subsequently purified with AMPure XP Beads (Beckman, USA) and assessed using Qubit dsDNA HS Kit. Later, high-throughput sequencing was conducted using the Illumina Novaseq 6000 platform with paired-END 2 × 150 bp. The data was read and filtered using intestinal flora RNA software. Similar overlapping relationships among the flora data were read and then spliced into tags. Operational taxonomic unit (OTU) analysis was conducted using VSEARCH software v2.4.4, covering de-repeating sequences (–derep_fulllength), clustering (–cluster_fast,–id 0.97), and de-chimerism (–uchime_ref) [25]. Sequences were clustered into OTUs with 97% similarity, and typical sequences of OTUs were chosen with default parameters and annotated with species via VSEARCH software with the SILVA ribosomal RNA database version 128 [26]. The OTU list was further generated, and the community composition at each taxonomic level, including species, genus, family, order, class, phylum and kingdom, was classified. OTUs below 0.001% of the total sequence in all samples were removed.

In this study, the abundance of 183 bacteria species was detected at the genus level. After reviewing the previous literature, 8 species of bacteria most likely related to cognition and emotion, Bacteroides [27,28,29], Prevotella [30,31,32], Megamonas [33,34,35], Parabacteroides [29, 36, 37], Ruminococcus [37,38,39], Faecalibacterium [33, 40, 41], Bifidobacterium [36, 42, 43], and Akkermansia [40, 44, 45], were included for further analysis.

Covariates

Factors known to be associated with cognitive function, gut microbiota and lipid profiles were considered as covariates, including gender, age, BMI and years of education. Self-reported and hospital episode statistics and clinical data were used to determine predepression diagnoses of hypertension and diabetes. Current smoking status (Yes/No) in self-reported data were used to classify participants into smokers and nonsmokers. Current alcohol consumption status (Yes/No) in self-reported data were used to classify participants into drinkers and nondrinkers.

Data statistics

The continuous variables were displayed as the mean ± standard deviation (SD) or median (25th, 75th) according to whether they fit a normal distribution. Categorical variables are described by counts (%). Spearman correlation analysis was utilized for determining the relationships among MoCA score, lipid metabolism index level and intestinal microbial abundance. Since the relative abundance of Akkermansia did not conform to the normal distribution through Shapiro‒Wilk test (P < 0.001), the relative abundance of Akkermansia was transformed by taking the logarithm (log-transformed) [46]. The relationships among Log Akkermansia, FFAs and MoCA scores were analyzed by linear regression. In addition, potential confounding factors were adjusted. Finally, SPSS PROCESS Macro v3.4 (Model 4) [47] was used to present the mediation effect of FFAs in the relationship between Log Akkermansia and cognitive function in LLD patients. A bootstrapping of 1000 was used to estimate 95% confidence interval (CI) of the mediating effect, and to determine whether FFAs mediated the associations between Log Akkermansia and cognitive impairment in LLD. P < 0.05 (two-tailed) was considered statistically significant.

Results

Patient characteristics

Thirty-five LLD patients were initially enrolled. Due to the presence of diarrhea in the stool of six subjects on the day of collection, their samples were subsequently excluded from the study. Data from 29 LLD patients were obtained, with an average age of 68.83 ± 6.56. The ratio of females to males was 21:8. The score of GDS-30 was 19.86 ± 5.84, while that of MoCA was 21.55 ± 3.75 (Table 1).

Table 1 Demographic and clinical characteristics of patients with LLD (N = 29)
Full size table

In this study, the abundance of 183 species of bacteria was sequenced at genus level (Fig. 1). The relative abundance of the selected eight microbial genera was as follows: Bacteroides, 0.198 (0.113, 0.289); Prevotella, 0.092 (0.069, 0.119); Megamonas, 0.073 (0.026, 0.095); Parabacteroides, 0.028 (0.023, 0.041); Ruminococcus, 0.018 (0.005, 0.033); Faecalibacterium, 0.017 (0.014, 0.021); Bifidobacterium, 0.012 (0.006, 0.013); and Akkermansia, 0.005 (0.002, 0.006) (Table 1).

Fig. 1
figure 1

Relative abundance of gut microbiome composition in patients with LLD. Note: Relative abundance of genus-level for LLD. Abbreviation: LLD, Late-Life Depression

Full size image

The results for the lipid metabolism parameters were as follows: cholesterol, 5.51 ± 0.88; triglycerides, 1.61 ± 0.67; HDL, 1.31 ± 0.28; LDL, 3.28 ± 0.81; ApoA1, 1.47 ± 0.27; ApoB, 1.04 ± 0.27; ApoE, 4.06 ± 1.01; LPPA, 416.28 ± 469.87; and FFAs, 535.76 ± 198.93 (Table 1, Fig. 1).

Correlations among the gut microbiota, lipid metabolism parameters and cognitive function in LLD patients

The pertinence among gut microbiota, lipid metabolism, and cognitive function in LLD was explored by Spearman analysis. As shown in Table 2 and Fig. 2, cognitive functions were related to gut microbiota in LLD patients, as follows: MoCA total score was positively correlated with Akkermansia (r = 0.760, P < 0.001) and Parabacteroides (r = -0.441, P = 0.017). Visuospatial/executive ability positively correlated with Akkermansia (r = 0.412, P = 0.026) and Parabacteroides (r = 0.438, P = 0.018). Naming ability exhibited a positive correlation with Akkermansia (r = 0.373, P = 0.047), while orientation positively related to Akkermansia (r = 0.498, P = 0.006) and Parabacteroides (r = 0.438, P = 0.018). Attention showed a positive correlation with Prevotella (r = -0.441, P = 0.017). Secondly, total FFAs were negatively related to MoCA total scores (r = -0.752, P < 0.001) and visuospatial/executive ability (r = -0.492, P = 0.007). Thirdly, total FFAs were found to be negatively related to Akkermansia (r = -0.543, P = 0.002) and Bifidobacterium (r = -0.473, P = 0.010). ApoE showed a negative correlation with Bacteroides (r = -0.451, P = 0.014) and a positive correlation with Ruminococcus (r = 0.452, P = 0.014).

Table 2 Correlations among gut microbes, cognition assessment and lipid profile indexes
Full size table
Fig. 2
figure 2

Correlations among gut microbiota, lipid metabolites and cognitive function scores. Note: Heat map revealing the relationships among gut microbes, lipid metabolites and MoCA scores in LLD. Red circle indicates positive associations, blue circle represents negative associations. The level of correlation is indicated by the degree of color. All correlations with significant differences are highlighted with asterisk (*P < 0.05). Abbreviation: MoCA, Montreal Cognitive Assessment; FFAs, free fatty acids; LLD, Late-Life Depression; ApoE, apolipoprotein E

Full size image

Multiple regression models for Akkermansia, total FFAs and the MoCA score

Uncorrected regression models revealed that both Log Akkermansia and total FFAs scores had significant predictive effects on MoCA scores (P < 0.05). Taking gender, age, years of education, hypertension, diabetes, drinking and smoking as covariates, regression analysis indicated that Log Akkermansia negatively predicted total FFAs content (β = -0.553, P < 0.004). When Log Akkermansia and total FFAs were separately used as predictor, Log Akkermansia positively predicted MoCA (β = 0.604, P < 0.001), total FFAs negatively predicted MoCA (β = -0.652, P < 0.001). When both Log Akkermansia and total FFAs were predictors, the effect on MoCA total score displayed remarkable significance (β = 0.343, P = 0.039 and β = -0.470, P = 0.006) (Table 3).

Table 3 Regression analysis between variables with LLD
Full size table

FFAs as a mediator between Akkermansia and cognitive functions in the LLD

As presented in Table 4, the direct effect of Log Akkermansia on MoCA was 0.343 (95%CI: 0.190–0.669). The indirect influence of Log Akkermansia on MoCA via total FFAs was 0.261 (95%CI: 0.023–0.557). Overall, the model demonstrated that 43.0% of the influence of Log Akkermansia on cognitive functions in LLD patients was mediated by total FFAs. In summary, a mediation model based on data was illustrated in Fig. 3.

Table 4 The mediating effect of total FFAs between Akkermansia and cognition in LLD
Full size table
Fig. 3
figure 3

Mediation model for the role of total FFAs in the relationship between Akkermansia and cognitive functions. Note: Mediating models described total FFAs as a Mediator in the Relevance Between Akkermansia and Cognitive Function in LLD. Path A: the effect of Akkermansia on total FFAs; Path B: the effect of total FFAs on cognitive function; Path C: the total effect of Akkermansia on Cognitive Function; Path C’: the direct effect of Akkermansia on Cognitive Function. Abbreviation: MoCA, Montreal Cognitive Assessment; FFAs, free fatty acids; LLD, Late-Life Depression

Full size image

Discussion

In this research, cognitive functions and their correlations with gut microbiota and lipid metabolism in patients with LLD were analyzed. Correlation analysis showed that the cognitive function was positively correlated with Akkermansia and negatively correlated with total FFAs. Both LogAkkermansia and total FFAs scores exhibited significant predictive effects on MoCA scores. Moreover, total FFAs partially mediated the relationship between Akkermansia abundance and cognitive functions in LLD. To our best knowledge, this is the first report evaluating the relationships among cognitive function, gut microbiota and lipid metabolism in LLD patients.

This research revealed cognitive functions in patients with LLD was positively correlated with Akkermansia, particularly in terms of visuospatial/executive function, naming and orientation. Regression analysis indicated that Akkermansia served as a positive predictor of cognitive function. Previous studies found that the relative abundance of Akkermansia was decreased in patients suffering from Mild Cognitive Impairment (MCI) and was positively related to MoCA scores [48]. Another research assessed cognitive function in depressed mice using Morris Water Maze test and found a decrease in the relative abundance of Akkermansia was associated with cognitive decline [49]. Current results aligned with these findings, suggesting a decline in Akkermansia related to cognitive impairment in LLD. It should be noted that cognitive functions were negatively associated with total FFAs in LLD, especially in visuospatial/executive function. Regression analysis indicated that total FFAs negatively predicted cognitive functions. FFAs, as non-esterified fatty acids, are products of the breakdown of triglycerides, known to be lipotoxic [50] and able to permeate the brain through passive transportation or protein-mediated endocytosis, thereby affecting vascular endothelial function [51]. They were believed to forewarn the incidence of AD in patients suffering from type 2 diabetes mellitus (T2DM) [52]. Zhu [53] reported that FFAs are negatively related to cognitive function, especially attention and executive ability, in T2DM patients suffering from MCI. Holloway [54] reported that higher FFA levels were related to worse cognitive functions among healthy people. These findings revealed the effects of FFAs on cognitive functions in patients suffering from LLD. However, there were some inconsistent results. For example, studies showed that the levels of certain FFAs, such as monounsaturated fatty acids, had protective effects on cognitive function and were decreased in patients suffering from AD [55]. One probable interpretation for above contradictions was that different types of FFAs had diverse influences on cognition, the positive effects of some fatty acids may be offset by the negative effects of others. Current study measured total FFAs content.

As for gut microbiota and lipid metabolism, current results revealed that Akkermansia was negatively related to total FFAs. Many previous studies confirmed the correlation between Akkermansia and lipid metabolism [56, 57]. Zou [56] reported a correlation between Akkermansia and FFAs in an obese mouse model. Rodríguez-Carrio [57] reported that, in the normal population, Akkermansia could predict the level of FFAs in peripheral blood and was negatively correlated with this parameter, which is consistent with this study. The Akkermansia-host relationship was manifested in energy expenditure related to glycolipid metabolism, which affected obesity [58]. Research had shown a close inverse relationship between Akkermansia enrichment and obesity development [59] and T2DM [60]. This research also supplemented the literature about the correlation between Akkermansia and lipid metabolism in individuals with geriatric mental disorders.

Most importantly, mediation analysis, for the first time, revealed that the impact of Akkermansia on cognitive function in LLD was mediated by FFAs. Previous research displayed lipid metabolism level is an important factor affecting the prognosis of patients with cognitive impairment [61, 62]. Wang [61] found that cognitive decline related to altered gut microbiota among peritoneal dialysis patients, and functional analyses showed this relationship was related to fatty acid metabolism. Ou [62] found that in AD model mice transplanted with Akkermansia, FFAs levels decreased and cognitive function improved accordingly. Akkermansia existed inside the mucous intestinal layer, thereby contributing to the reinforcement of the intestinal wall [63]. Furthermore, FFAs may induce neuroinflammatory response and insulin resistance through G protein-coupled receptors overactivation, therefore causing neurotoxicity and affecting cognitive function [57]. This study was consistent with these findings and provided new explanation for the relationship between FFAs, gut microbes and cognitive function in LLD. The mediation relationship also had noteworthy implications for clinical practice. Firstly, in LLD patients, we should pay more attention to those who have dysregulation of lipid metabolism, especially elevated FFAs, as they may have a higher potential risk of cognitive deficits. Besides, regulating lipid metabolism in patients while treating depression may lead to cognitive benefits. Finally, due to the metabolic disorders caused by some antidepressants and antipsychotics, cognitive symptoms of LLD should also be concerned.

Study strengths and limitations

This study is so far the first to investigate the relationship between cognitive function, gut microbiota and lipid metabolism in LLD patients, and emphasizes the mediating role of total FFAs in microbiome-gut-brain axis. Current study also made extensive adjustments for potential confounding factors. However, a few unignorable limitations should be taken into consideration. Firstly, the limited sample size should not be overlooked, necessitating further expansion to deepen the understanding of the pertinence of gut microbiota, lipid metabolism and cognitive functions among LLD patients. Secondly, it is a cross-sectional study that reflects the causal relation of gut microbiota, and lipid metabolism upon cognitive function in patients with LLD in a limited way.

Conclusion

In conclusion, this study demonstrated that cognitive function was correlated with the levels of total FFAs and the relative abundance of Akkermansia in LLD. Furthermore, this study emphasizes the significant mediating role of total FFAs between Akkermansia and cognitive function, which offers new perspective into the role of gut microbial-lipid metabolism axis in the cognitive function of LLD, and could guide individualized therapeutic interventions. Clinically, the results highlight the importance of fluctuation of serum lipid metabolism markers, especially total FFAs, which may imply the gut microbiota dysregulation and further potential cognitive impairment in LLD. Furthermore, lipid metabolism management may have clinical benefits for cognitive function in LLD. For the future perspectives, further revealing the precise interactions between gut microbiota and lipid metabolism may provide mechanistic insights and help to develop new therapeutic approaches for cognitive impairment in LLD.

Availability of data and materials

The data supporting the results of our study are stored in the OMIX repository: https://download.cncb.ac.cn/OMIX/OMIX004832/.

Abbreviations

LLD:

Late-life depression

MoCA:

Montreal Cognitive Assessment

FFAs:

Free Fatty Acids

AD:

Alzheimer’s disease

ApoE:

Apolipoprotein E(ApoE)

ApoC1:

Apolipoprotein C1

CLU:

Clusterin

BMI:

Body-mass index

MDD:

Major Depressive Disorder

DSM-V:

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

GDS-30:

30-Item Geriatric Depression Scale

HDL:

High density lipoprotein

LDL:

Low density lipoprotein

ApoA1:

Apolipoprotein A1(ApoA1)

ApoB:

Apolipoprotein B(ApoB)

TC:

Total cholesterol

TG:

Triglyceride

LPPA:

Lipoprotein A

OTU:

Operational taxonomic unit

SD:

Standard deviation

CI:

Confidence interval

MCI:

Mild Cognitive Impairment

T2DM:

Type 2 diabetes mellitus

References

  1. Mindikoglu AL, Abdulsada MM, Jain A, Choi JM, Jalal PK, Devaraj S, Mezzari MP, Petrosino JF, Opekun AR, Jung SY. Intermittent fasting from dawn to sunset for 30 consecutive days is associated with anticancer proteomic signature and upregulates key regulatory proteins of glucose and lipid metabolism, circadian clock, DNA repair, cytoskeleton remodeling, immune system and cognitive function in healthy subjects. J Proteomics. 2020;217:103645.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Gracia-Garcia P, de-la-Camara C, Santabarbara J, Lopez-Anton R, Quintanilla MA, Ventura T, Marcos G, Campayo A, Saz P, Lyketsos C, Lobo A. Depression and incident Alzheimer disease: the impact of disease severity. Am J Geriatr Psychiatry. 2015;23:119–29.

    Article  PubMed  Google Scholar 

  3. Diniz BS, Butters MA, Albert SM, Dew MA, Reynolds CF 3rd. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202:329–35.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Afzaal M, Saeed F, Shah YA, Hussain M, Rabail R, Socol CT, Hassoun A, Pateiro M, Lorenzo JM, Rusu AV, Aadil RM. Human gut microbiota in health and disease: unveiling the relationship. Front Microbiol. 2022;13.

  5. Zhou Y, Wang Y, Quan M, Zhao H, Jia J. Gut microbiota changes and their correlation with cognitive and neuropsychiatric symptoms in Alzheimer’s disease. J Alzheimers Dis. 2021;81:583–95.

    Article  CAS  PubMed  Google Scholar 

  6. Zhu F, Guo R, Wang W, Ju Y, Wang Q, Ma Q, Sun Q, Fan Y, Xie Y, Yang Z, et al. Transplantation of microbiota from drug-free patients with schizophrenia causes schizophrenia-like abnormal behaviors and dysregulated kynurenine metabolism in mice. Mol Psychiatry. 2020;25:2905–18.

    Article  CAS  PubMed  Google Scholar 

  7. Xu H, Wang Z, Zhu L, Sui Z, Bi W, Liu R, Bi K, Li Q. Targeted Neurotransmitters Profiling Identifies Metabolic Signatures in Rat Brain by LC-MS/MS: application in insomnia, depression and Alzheimer's disease. Molecules. 2018;23.

  8. Akram N, Faisal Z, Irfan R, Shah YA, Batool SA, Zahid T, Zulfiqar A, Fatima A, Jahan Q, Tariq H, et al. Exploring the serotonin-probiotics-gut health axis: a review of current evidence and potential mechanisms. 2023.

    Google Scholar 

  9. Engevik M, Ruan W, Visuthranukul C, Shi Z, Engevik KA, Engevik AC, Fultz R, Schady DA, Spinler JK, Versalovic J. Limosilactobacillus reuteri ATCC 6475 metabolites upregulate the serotonin transporter in the intestinal epithelium. Benef Microbes. 2021;12:583–99.

    Article  CAS  PubMed  Google Scholar 

  10. Wang YM, Ge XZ, Wang WQ, Wang T, Cao HL, Wang BL, Wang BM. Lactobacillus rhamnosus GG supernatant upregulates serotonin transporter expression in intestinal epithelial cells and mice intestinal tissues. Neurogastroenterol Motil. 2015;27:1239–48.

    Article  CAS  PubMed  Google Scholar 

  11. Shabbir U, Arshad MS, Sameen A, Oh DH. Crosstalk between gut and brain in Alzheimer's disease: the role of gut microbiota modulation strategies. Nutrients. 2021;13.

  12. Biagioli V, Volpedo G, Riva A, Mainardi P, Striano P. From birth to weaning: a window of opportunity for microbiota. Nutrients. 2024;26.

  13. Clemente-Suárez VJ, Redondo-Flórez L, Rubio-Zarapuz A, Martín-Rodríguez A, Tornero-Aguilera JF. Microbiota implications in endocrine-related diseases: from development to novel therapeutic approaches. Biomedicines. 2024;12.

  14. Jiang W, Gong L, Liu F, Ren Y, Mu J. Alteration of gut microbiome and correlated lipid metabolism in post-stroke depression. Front Cell Infect Microbiol. 2021;11:663967.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Yu Y, Raka F, Adeli K. The Role of the Gut Microbiota in Lipid and Lipoprotein Metabolism. J Clin Med. 2019;8.

  16. Raulin AC, Doss SV, Trottier ZA, Ikezu TC, Bu G, Liu CC. ApoE in Alzheimer’s disease: pathophysiology and therapeutic strategies. Mol Neurodegener. 2022;17:72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kulminski AM, Philipp I, Shu L, Culminskaya I. Definitive roles of TOMM40-APOE-APOC1 variants in the Alzheimer’s risk. Neurobiol Aging. 2022;110:122–31.

    Article  CAS  PubMed  Google Scholar 

  18. Harold D, Abraham R, Hollingworth P, Sims R, Gerrish A, Hamshere ML, Pahwa JS, Moskvina V, Dowzell K, Williams A, et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat Genet. 2009;41:1088–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sun JH, Yu JT, Tan L. The role of cholesterol metabolism in Alzheimer’s disease. Mol Neurobiol. 2015;51:947–65.

    Article  CAS  PubMed  Google Scholar 

  20. Jean-Charles R, Thomas D, Sébastien D, Iris M-G, Louise W, Elise B, Laurent B, Dominique D, Jean-Marie B, Renaud D, et al. Connectivity patterns of the core resting-state networks associated with apathy in late-life depression. J Psychiatry Neurosci. 2023;48:E404–13.

    Article  Google Scholar 

  21. Shen Y, Yang X, Li G, Gao J, Liang Y. The change of gut microbiota in MDD patients under SSRIs treatment. Sci Rep. 2021;11:14918.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  22. Deng D, Su H, Song Y, Chen T, Sun Q, Jiang H, Zhao M. Altered fecal microbiota correlated with systemic inflammation in male subjects with methamphetamine use disorder. Front Cell Infect Microbiol. 2021;11.

  23. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–9.

    Article  PubMed  Google Scholar 

  24. Benedetti A, Wu Y, Levis B, Wilchesky M, Boruff J, Ioannidis JPA, Patten SB, Cuijpers P, Shrier I, Gilbody S, et al. Diagnostic accuracy of the geriatric depression scale-30, geriatric depression scale-15, geriatric depression scale-5 and geriatric depression scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis. BMJ Open. 2018;8:e026598.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Rognes T, Flouri T, Nichols B, Quince C, Mahe F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016;4:e2584.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590-596.

    Article  CAS  PubMed  Google Scholar 

  27. Chang CH, Lin CH, Lane HY. d-glutamate and gut microbiota in Alzheimer's disease. Int J Mol Sci. 2020;21.

  28. Liang X, Fu Y, Cao WT, Wang Z, Zhang K, Jiang Z, Jia X, Liu CY, Lin HR, Zhong H, et al. Gut microbiome, cognitive function and brain structure: a multi-omics integration analysis. Transl Neurodegener. 2022;11:49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhang S, Qian Y, Li Q, Xu X, Li X, Wang C, Cai H, Zhu J, Yu Y. Metabolic and neural mechanisms underlying the associations between gut bacteroides and cognition: a large-scale functional network connectivity study. Front Neurosci. 2021;15:750704.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Aljumaah MR, Bhatia U, Roach J, Gunstad J, Azcarate Peril MA. The gut microbiome, mild cognitive impairment, and probiotics: a randomized clinical trial in middle-aged and older adults. Clin Nutr. 2022;41:2565–76.

    Article  PubMed  Google Scholar 

  31. Khedr EM, Omeran N, Karam-Allah Ramadan H, Ahmed GK, Abdelwarith AM. Alteration of gut microbiota in Alzheimer’s disease and their relation to the cognitive impairment. J Alzheimers Dis. 2022;88:1103–14.

    Article  CAS  PubMed  Google Scholar 

  32. Qu L, Dong Z, Ma S, Liu Y, Zhou W, Wang Z, Wu C, Ma R, Jiang X, Zu T, et al. Gut microbiome signatures are predictive of cognitive impairment in hypertension patients-a cohort study. Front Microbiol. 2022;13:841614.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Du Y, Li L, Gong C, Li T, Xia Y. The diversity of the intestinal microbiota in patients with alcohol use disorder and its relationship to alcohol consumption and cognition. Front Psychiatry. 2022;13:1054685.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Renson A, Kasselman LJ, Dowd JB, Waldron L, Jones HE, Herd P. Gut bacterial taxonomic abundances vary with cognition, personality, and mood in the Wisconsin Longitudinal Study. Brain Behav Immun Health. 2020;9:100155.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Guo X, Lin F, Yang F, Chen J, Cai W, Zou T. Gut microbiome characteristics of comorbid generalized anxiety disorder and functional gastrointestinal disease: correlation with alexithymia and personality traits. Front Psychiatry. 2022;13:946808.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Shi S, Zhang Q, Sang Y, Ge S, Wang Q, Wang R, He J. Probiotic bifidobacterium longum BB68S improves cognitive functions in healthy older adults: a randomized, double-blind, placebo-controlled trial. Nutrients. 2022;15.

  37. Khine WWT, Voong ML, Ng TKS, Feng L, Rane GA, Kumar AP, Kua EH, Mahendran R, Mahendran R, Lee YK. Mental awareness improved mild cognitive impairment and modulated gut microbiome. Aging (Albany NY). 2020;12:24371–93.

    Article  CAS  PubMed  Google Scholar 

  38. Bajaj JS, Fagan A, White MB, Wade JB, Hylemon PB, Heuman DM, Fuchs M, John BV, Acharya C, Sikaroodi M, Gillevet PM. Specific gut and salivary microbiota patterns are linked with different cognitive testing strategies in minimal hepatic encephalopathy. Am J Gastroenterol. 2019;114:1080–90.

    Article  PubMed  PubMed Central  Google Scholar 

  39. van Soest APM, Hermes GDA, Berendsen AAM, van de Rest O, Zoetendal EG, Fuentes S, Santoro A, Franceschi C, de Groot L, de Vos WM. Associations between pro- and anti-inflammatory gastro-intestinal microbiota, diet, and cognitive functioning in Dutch healthy older adults: the NU-AGE study. Nutrients. 2020;12.

  40. Badal VD, Vaccariello ED, Murray ER, Yu KE, Knight R, Jeste DV, Nguyen TT. The gut microbiome, aging, and longevity: a systematic review. Nutrients. 2020;12.

  41. Strasser B, Ticinesi A. Intestinal microbiome in normal ageing, frailty and cognition decline. Curr Opin Clin Nutr Metab Care. 2023;26:8–16.

    Article  CAS  PubMed  Google Scholar 

  42. Asaoka D, Xiao J, Takeda T, Yanagisawa N, Yamazaki T, Matsubara Y, Sugiyama H, Endo N, Higa M, Kasanuki K, et al. Effect of probiotic bifidobacterium breve in improving cognitive function and preventing brain atrophy in older patients with suspected mild cognitive impairment: results of a 24-Week randomized, double-blind, Placebo-Controlled Trial. J Alzheimers Dis. 2022;88:75–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Cho S, Samuel TM, Li T, Howell BR, Baluyot K, Hazlett HC, Elison JT, Zhu H, Hauser J, Sprenger N, Lin W. Interactions between Bifidobacterium and Bacteroides and human milk oligosaccharides and their associations with infant cognition. Front Nutr. 2023;10:1216327.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Li Z, Lai J, Zhang P, Ding J, Jiang J, Liu C, Huang H, Zhen H, Xi C, Sun Y, et al. Multi-omics analyses of serum metabolome, gut microbiome and brain function reveal dysregulated microbiota-gut-brain axis in bipolar depression. Mol Psychiatry. 2022;27:4123–35.

    Article  CAS  PubMed  Google Scholar 

  45. Higarza SG, Arboleya S, Arias JL, Gueimonde M, Arias N. Akkermansia muciniphila and environmental enrichment reverse cognitive impairment associated with high-fat high-cholesterol consumption in rats. Gut Microbes. 2021;13:1–20.

    Article  PubMed  Google Scholar 

  46. Wang Y, Li Q, Yuan Z, Ma S, Shao S, Wu Y, Wang Z, Li Q, Gao L, Zhao M, Zhao J. Statin use and benefits of thyroid function: a retrospective cohort study. Front Endocrinol. 2021;12.

  47. Hayes AF. PROCESS: A Versatile Computational Tool for Observed Variable Mediation, Moderation, and Conditional Process Modeling 1. 2012.

    Google Scholar 

  48. McLeod A, Penalver Bernabe B, Xia Y, Sanchez-Flack J, Lamar M, Schiffer L, Castellanos K, Fantuzzi G, Maki P, Fitzgibbon M, Tussing-Humphreys L. Comparing the gut microbiome of obese, African American, older adults with and without mild cognitive impairment. PLoS ONE. 2023;18:e0280211.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Szala-Rycaj J, Szewczyk A, Zagaja M, Kaczmarczyk-Ziemba A, Maj M, Andres-Mach M. The Influence of topinambur and inulin preventive supplementation on microbiota, anxious behavior, cognitive functions and neurogenesis in mice exposed to the chronic unpredictable mild stress. Nutrients. 2023;15.

  50. Sekizkardes H, Chung ST, Chacko S, Haymond MW, Startzell M, Walter M, Walter PJ, Lightbourne M, Brown RJ. Free fatty acid processing diverges in human pathologic insulin resistance conditions. J Clin Invest. 2020;130:3592–602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Yang WC, Cao HL, Wang YZ, Li TT, Hu HY, Wan Q, Li WZ. Inhibition of nitric oxide synthase aggravates brain injury in diabetic rats with traumatic brain injury. Neural Regen Res. 2021;16:1574–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Fonteh AN, Cipolla M, Chiang J, Arakaki X, Harrington MG. Human cerebrospinal fluid fatty acid levels differ between supernatant fluid and brain-derived nanoparticle fractions, and are altered in Alzheimer’s disease. PLoS ONE. 2014;9:e100519.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  53. Zhu W, Xu L, Zhang H, Tian S, An K, Cao W, Shi J, Tang W, Wang S. Elevated plasma free fatty acid susceptible to early cognitive impairment in type 2 diabetes mellitus. J Alzheimers Dis. 2021;82:1345–56.

    Article  CAS  PubMed  Google Scholar 

  54. Holloway CJ, Cochlin LE, Emmanuel Y, Murray A, Codreanu I, Edwards LM, Szmigielski C, Tyler DJ, Knight NS, Saxby BK, et al. A high-fat diet impairs cardiac high-energy phosphate metabolism and cognitive function in healthy human subjects. Am J Clin Nutr. 2011;93:748–55.

    Article  CAS  PubMed  Google Scholar 

  55. Innis SM. Fatty acids and early human development. Early Hum Dev. 2007;83:761–6.

    Article  CAS  PubMed  Google Scholar 

  56. Zou H, Zhang M, Zhu X, Zhu L, Chen S, Luo M, Xie Q, Chen Y, Zhang K, Bu Q, et al. Ginsenoside Rb1 improves metabolic disorder in high-fat diet-induced obese mice associated with modulation of gut microbiota. Front Microbiol. 2022;13:826487.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Rodriguez-Carrio J, Salazar N, Margolles A, Gonzalez S, Gueimonde M, de Los Reyes-Gavilan CG, Suarez A. Free fatty acids profiles are related to gut microbiota signatures and short-chain fatty acids. Front Immunol. 2017;8:823.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zhang T, Li Q, Cheng L, Buch H, Zhang F. Akkermansia muciniphila is a promising probiotic. Microb Biotechnol. 2019;12:1109–25.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Parks BW, Nam E, Org E, Kostem E, Norheim F, Hui ST, Pan C, Civelek M, Rau CD, Bennett BJ, et al. Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice. Cell Metab. 2013;17:141–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Pascale A, Marchesi N, Govoni S, Coppola A, Gazzaruso C. The role of gut microbiota in obesity, diabetes mellitus, and effect of metformin: new insights into old diseases. Curr Opin Pharmacol. 2019;49:1–5.

    Article  CAS  PubMed  Google Scholar 

  61. Wang J, Wu S, Zhang J, Li Y, Wu Y, Qi X. Correlation between gut microbiome and cognitive impairment in patients undergoing peritoneal dialysis. BMC Nephrol. 2023;24:360.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Ou Z, Deng L, Lu Z, Wu F, Liu W, Huang D, Peng Y. Protective effects of Akkermansia muciniphila on cognitive deficits and amyloid pathology in a mouse model of Alzheimer’s disease. Nutr Diabetes. 2020;10:12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Derrien M, Belzer C, de Vos WM. Akkermansia muciniphila and its role in regulating host functions. Microb Pathog. 2017;106:171–81.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We have no acknowledgments.

Disclosure

The authors state that there are no conflicts of interest related to this paper.

Funding

This paper obtained support from the Science Foundation of the Health Commission of Zhejiang Province (2024KY731).

Author information

Authors and Affiliations

  1. Center for Rehabilitation Medicine, Department of Psychiatry, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, 158 Shangtang Rd, Hangzhou, 310014, Zhejiang, People’s Republic of China

    Yan Chen, Dansheng Le & Zhengluan Liao

  2. Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, 1 Weigang, Nanjing, 210095, Jiangsu Province, China

    Jiarong Li

  3. The Second Clinical College of Zhejiang, Chinese Medical University, Hangzhou, 310053, Zhejiang, China

    Yuhan Zhang

Authors
  1. Yan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiarong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dansheng Le
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuhan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhengluan Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Y.C. and Z.L.L led the study. Y.C performed the data analysis and implemented the methodology. J.R.L, D.S.L and Y.H.Z collected the data. Y.C prepared the original draft. Z.L.L and J.R.L reviewed and edited the final manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Zhengluan Liao.

Ethics declarations

Ethics approval and consent to participate

This research obtained approval from the Ethics Committee of Zhejiang Provincial People’s Hospital (2019KY184). Informed consent was obtained from and signed by all the participants or their caregivers.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Li, J., Le, D. et al. A mediation analysis of the role of total free fatty acids on pertinence of gut microbiota composition and cognitive function in late life depression. Lipids Health Dis 23, 64 (2024). https://doi.org/10.1186/s12944-024-02056-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12944-024-02056-6

Keywords

Lipids in Health and Disease

ISSN: 1476-511X