Taurine Intake, Plasma Taurine Concentration, and Dementia Risk: Findings From the Malmö Diet and Cancer Study

ABSTRACT

Preclinical studies suggest that taurine may exert neuroprotective effects. However, its relevance to dementia risk in human populations remains unclear. We investigated the associations between mid‐life dietary taurine intake, circulating taurine concentrations, and the risk of late‐life all‐cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD) in a large prospective cohort. This study utilized data from 27 786 participants of the Malmö Diet and Cancer Study with baseline examination from 1991 to 1996. Dietary taurine intake was estimated from a detailed diet history and adjusted for energy intake. Plasma taurine concentration was measured in a subset of 3693 individuals. Dementia diagnoses were ascertained through the Swedish National Patient Register and validated by memory clinic physicians. Cox proportional hazards models assessed associations with dementia risk, adjusting for potential confounders including APOE ε4 status, lifestyle factors, and comorbidities. Over a median 25‐year follow‐up, 3224 participants developed dementia. No significant associations were found between dietary taurine intake or plasma taurine concentrations and the risk of all‐cause dementia, AD, or VaD. Circulating taurine concentrations were only weakly correlated with dietary intake, suggesting a predominant role of endogenous taurine synthesis and metabolism. Our findings fail to support a protective role for taurine intake against dementia in humans. Further studies are warranted to examine potential effects under specific pathological conditions or with high‐dose supplementation.

Using a large prospective population cohort in Sweden, we did not find any important association between dietary taurine consumption, concentrations of taurine in blood, and the risk of developing dementia. These findings are in contrast with those from previously published work on animal models.

Abbreviations

AD

Alzheimer's disease

AIC

Akaike information criterion

APOE

apolipoprotein E

BMI

body mass index

CI

confidence interval

HR

hazard ratio

MDC

Malmö Diet and Cancer

MET

metabolic equivalent of task

RCS

restricted cubic spline

T2D

type 2 diabetes

VaD

vascular dementia

1. Introduction

Dementia represents a group of disorders characterized by cognitive decline that affects daily living, and its prevalence is expected to nearly triple in the next 30 years, likely due to increased longevity and unhealthy lifestyles (GBD Dementia Forecasting GBD ²⁰²²). Obesity and its comorbidities, such as hypertension, cardiovascular disease, metabolic syndrome and type 2 diabetes (T2D), have been proposed to be risk factors for developing dementia (Albanese et al. 2017; Livingston et al. ²⁰²⁰; Qizilbash et al. ²⁰¹⁵). Moreover, these highly prevalent risk factors can accelerate neurodegeneration and might interact with genetic susceptibility to influence the development of neurodegenerative disorders, namely Alzheimer's disease (AD) (Ezkurdia et al. 2023; Guerreiro et al. ²⁰¹²; Patel and Edison ²⁰²⁴).

Animal models of AD show reduced brain taurine concentration (Aytan et al. 2016; Chiquita et al. ²⁰¹⁹; Takado et al. ²⁰¹⁸; Tondo et al. ²⁰²⁰). Interestingly, Takado et al. demonstrated an inverse relationship between cortical taurine concentration and tau protein accumulation measured by positron emission tomography in rTg4510 mice (Takado et al. 2018), and Aytan et al. showed an inverse correlation between taurine and brain levels of the gliosis marker GFAP in the 5xFAD model (Aytan et al. 2016), suggesting that taurine depletion is associated with features of neurodegeneration and gliosis. Furthermore, taurine supplementation was proposed to prevent neurodegeneration in neurons in vitro (Louzada et al. 2004) and in an AD mouse model (Kim et al. 2014). Taurine supplementation has also been suggested to mitigate neuroinflammation (Ahmed et al. 2024), but its benefits against amyloid pathology are controversial (Ahmed et al. 2024; Oh et al. ²⁰²⁰). In animal models of stress, taurine prevents retraction of dendritic arborizations, deficits in neurotransmitter levels, depressive behavior and memory impairment (Wu et al. 2017; Zhu et al. ²⁰²³). Taurine also improved memory in aged mice (El Idrissi ²⁰⁰⁸). These findings raise the possibility that taurine availability may modulate disease progression; however, whether taurine acts only as a marker of ongoing pathology in genetic AD or may influence dementia risk in the context of sporadic AD remains to be clarified.

Diets rich in fat and sugar are commonly employed to experimentally induce obesity with metabolic syndrome, and lead to memory impairment (Garcia‐Serrano and Duarte ²⁰²⁰). Mice fed a high‐fat diet for 6 months show altered concentrations of metabolites measured in vivo with magnetic resonance spectroscopy, including a prominent increase of hippocampal taurine (Lizarbe et al. 2018). While this effect on brain taurine concentrations contrasts with what is observed in AD models (Aytan et al. 2016; Chiquita et al. ²⁰¹⁹; Takado et al. ²⁰¹⁸; Tondo et al. ²⁰²⁰), increased hippocampal taurine concentration has also been observed in insulin‐resistant Goto‐Kakizaki rats (Duarte et al. 2018) and streptozotocin‐induced diabetic rats (Duarte et al. 2009; Zhang et al. ²⁰¹⁵). In a longitudinal study, high‐fat and high‐sucrose diet feeding in mice led to increased taurine in the hippocampus, which could be recovered to control levels by diet normalization (Garcia‐Serrano et al. ²⁰²²). Altogether, these findings suggest that hippocampal taurine accumulation is unlikely to be related to the development of memory impairment in obesity and diabetes models, and it might be a consequence of metabolic syndrome severity. Thus, it is likely that taurine counteracts neurodegeneration in metabolic disease (Rafiee et al. 2022). Indeed, taurine supplementation prevented memory impairment in obese mice (Garcia‐Serrano et al. ²⁰²³).

Taurine is found naturally in meat, fish, shellfish, and dairy products. Since taurine homeostasis is important for several biological processes (Rafiee et al. 2022), we hypothesize that taurine intake is inversely associated with the risk of developing dementia in humans. In this study, we set out to determine whether taurine consumption influences plasma concentration of taurine, and to determine associations between taurine consumption, plasma taurine and the risk of developing dementia.

2. Methods

2.1. Study Population and Data Collection

This study was based on participants from the Malmö Diet and Cancer (MDC) study, a population‐based prospective cohort conducted in southern Sweden. This study invited all women born between 1923 and 1950, as well as all men born between 1923 and 1945 who were residing in Malmö, Sweden, to take part in the study (Manjer et al. 2002). A total of 74 138 individuals constitute the source population. Baseline assessments were carried out between 1991 and 1996, during which 28 233 participants completed the dietary assessment. The participants also answered a questionnaire covering various lifestyle factors, and underwent anthropometric measurements, including weight, height, waist circumference, and body fat percentage, which were recorded by registered nurses. Ethical approval for the MDC study was obtained from the Regional Ethical Review Board in Lund, Sweden (LU/90‐51), and all participants provided written informed consent before enrollment.

The self‐administered questionnaire included questions on multiple aspects, including medication use, medical history, socioeconomic status, and lifestyle behaviors. Leisure‐time physical activity was assessed based on the duration of 17 different activities, and metabolic equivalent of task (MET) hours per week were calculated based on the intensity of the activities (Ainsworth et al. 2011). Smoking status was categorized as never, current, or former smoker, while educational attainment was classified according to Swedish educational levels: < 9 years, 9 years, upper secondary school, and university (with or without a degree). Information on alcohol consumption was derived from both the questionnaire and a 7‐day food diary, where individuals who had not consumed alcohol in the past year were identified as zero‐consumers. The Social Network Index (adapted from the original instrument from Berkman and Syme (Berkman and Syme 1979)) is scored on a continuous 0–5 scale: 0 represents the highest level of social support, whereas 5 indicates the greatest social isolation. Prevalent diabetes were identified through self‐reported diagnosis, medication use and through registers (Zhang et al. 2025), and anti‐hypertensive drugs were self‐reported through the questionnaire and the 7‐day diary. Participants who reported significant dietary changes before the baseline assessments were identified through self‐administered questionnaires (Sonestedt et al. 2005), and potential energy misreporters were detected using the Goldberg method, based on their estimated energy expenditure (Mattisson et al. 2005). Participants missing data on covariates such as education, BMI, smoking, and physical activity were excluded (n = 447), leaving a final sample of 27 786 individuals for the main analysis (Figure 1).

FIGURE 1.

Flow diagram of participant enrollment and selection.

2.2. Dietary Taurine Intake Assessment

Dietary data were collected using a diet history method that included a seven‐day food diary covering cooked meals, cold beverages, and dietary supplements as well as a 168‐item diet history questionnaire covering the frequency and portion size of consumed foods that were not included in the food diary during the preceding 12 months. In addition, a 60‐min (until September 1, 1994) or 45‐min (after September 1, 1994) diet history interview was conducted to collect information about serving sizes and cooking methods of the foods recorded in the food diary (Wirfalt et al. 2002). The collected food intake data were converted into daily nutrient and energy intakes using the Malmö Diet and Cancer Study Food and Nutrient Database, originating from a database by the Swedish National Food Agency. An 18‐day weighted food record was used to validate a similar diet history method and demonstrated a strong correlation for meat (Pearson's correlation coefficients of 0.84 and 0.94 for men and women, respectively), and moderate correlation for fish (0.35 and 0.74 for men and women) (Elmstahl et al. 1996).

Taurine intake was estimated as the mean value derived from measured taurine content in various foods reported in seven publications (Dragnes et al. 2009; Laidlaw et al. ¹⁹⁹⁰; Manzi and Pizzoferrato ²⁰¹³; Pasantesmorales et al. ¹⁹⁸⁹; Purchas et al. ²⁰⁰⁴; Spitze et al. ²⁰⁰³; Wojcik et al. ²⁰¹⁰). The specific taurine content from each source, along with the calculated mean values, is presented in Table S1. As the food items in these sources did not directly correspond to the food variables in our dietary questionnaire, several assumptions were made to align the data: (1) The taurine content in milk was assumed to be consistent across different fat contents and fermentation processes. Similarly, the taurine content of pork, beef, and lamb was considered uniform, regardless of fat content. (2) Shellfish intake in the questionnaire was estimated based on a composition of 25% mussels and 75% shrimp. (3) The taurine content for “Poultry” was calculated as the average value of chicken breasts and chicken thighs. (4) “Game meat” was assumed to have a taurine content equivalent to the average of pork, beef, and lamb. (5) “Sausage” intake was estimated as the average taurine content of ham and salami. (6) The taurine content of nuts was analyzed in only one of the referenced publications and was calculated as the average value of walnuts, hazelnuts, almonds, pistachios, cashews, and pine nuts (Pasantesmorales et al. 1989).

Total taurine intake for each participant was estimated by calculating the product of taurine content in various foods (Table S1) and their corresponding intake levels. To reduce extraneous variation, and reduce the influence of misreporting, taurine intake was adjusted for total energy intake using the residual method in a regression analysis, allowing for the assessment of taurine intake independently of overall energy consumption. This approach is particularly useful for minimizing collinearity, which can occur in multivariable models when nutrient intake is strongly correlated with total energy intake (r = 0.52 for taurine intake and total energy intake in this study). The energy‐adjusted taurine intake derived from this method was subsequently divided into quintiles for further analysis.

2.3. Plasma Taurine Measurement

Citrate plasma was collected from 3799 fasting participants in the MDC‐CC sub‐cohort and stored at −80°C. Extraction was performed by adding 120 μL of 80:20 methanol/water to 20 μL of plasma, before centrifugation and separation of supernatants. Samples were analyzed by hydrophilic‐interaction chromatography (ACQUITY UPLC BEH Amide 1.7 μm, 2.1 × 100 mm) coupled to quadrupole time‐of‐flight mass spectrometry (Agilent Technologies, 6550 QTOF, Santa Clara, CA, USA), using previously described methods (Ottosson et al. 2018). Taurine was identified using an authentic standard and peak areas were integrated using Agilent Profinder B.06.00. To ensure analytical repeatability, quality control (QC) samples were injected after every eight analytical samples. Taurine concentrations in analytical samples were normalized based on measurements in the QC samples. A low‐order nonlinear locally estimated smoothing function was fitted to the Taurine intensities in the QC samples as a function of injection order. This fitted model was then used to interpolate a correction curve for the analytical samples, to which their Taurine measurements were normalized (Yan et al. 2022). After excluding participants with incomplete dietary and lifestyle data, a final sample of 3693 individuals was included in this study.

2.4. Apolipoprotein E Genotyping

The apolipoprotein E (APOE) gene is the most significant genetic factor linked to the risk of developing sporadic AD (van der Lee et al. ²⁰¹⁸). It has three primary alleles: APOE ε2, which is considered protective; APOE ε3, regarded as neutral; and APOE ε4, which is associated with an increased risk of AD. This study included data on APOE ε4 status, categorized as carrier or non‐carrier. Genotyping was performed with the NeuroChip (Illumina), as detailed previously (Samuelsson et al. 2022). Among the study participants, APOE ε4 status was available for 26 775 individuals, comprising 18 683 non‐carriers and 8092 carriers.

2.5. Dementia Outcome Ascertainment

The classification of all‐cause dementia and its subtypes was derived from the Swedish National Patient Register up to 2020, which compiles data from both the Swedish Inpatient Register and the hospital‐based outpatient register. The following ICD codes were used: AD dementia (ICD‐10 and ICD‐9 codes F00, G30, 331A/331.0), VaD (F01, 290E/290.4), Parkinson's disease dementia (F020, G310, 331B/331.1), and unspecified dementia (F03, 290, 294B/294.1, 331C/331.2). Dementia diagnoses up to 31 December 2014, were validated by trained physicians based on a review of medical records incorporating symptom evaluation, cognitive test results, and brain imaging, in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5) criteria (Nägga et al. 2022). Of the dementia cases derived from the patient register, 96% were confirmed through the validation process (Nägga et al. 2022). However, only 40% of the dementia subtypes (e.g., AD or VaD) were revised during the validation process (Nägga et al. 2022). To ensure a comprehensive analysis of all‐cause dementia, we separately examined data from the validated 2014 diagnoses and the full 2020 dataset, which includes both validated cases from 2014 and unvalidated cases from 2015 to 2020. For dementia subtype analyses, only the validated 2014 diagnoses were considered.

2.6. Statistical Analysis

Baseline characteristics across quintiles of energy‐adjusted taurine intakes were presented as means with standard deviations (SD) for continuous variables and percentages for categorical variables. We used proportional Cox regression models to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all‐cause dementia and its subtypes associated with energy‐adjusted taurine intake. Analyses were conducted using two models. Following the 2024 update from the Lancet Commission on dementia prevention, intervention, and care (Mukadam et al. 2024), we accounted for potential confounders assessed at baseline. Model 1 was adjusted for age (continuous), sex (male/female), season of dietary assessment (spring, summer, autumn, or winter), diet method (before and after 1 September 1994), and energy intake (kcal/day, continuous). Model 2 included further adjustments for smoking status (current smokers, former smokers, or never smokers), educational level (< 9 years; 9 years; upper secondary school; university, no degree; university degree), leisure‐time physical activity (< 7.5 MET‐h/week, 7.5–15 MET‐h/week, 15–25 MET‐h/week, 25–50 MET‐h/week, or > 50 MET‐h/week), alcohol consumption (never/alcohol consumer), BMI (continuous), Social Network Index (0–5, continuous) (Berkman and Syme 1979), prevalent diabetes (yes/no), and anti‐hypertensive medication use (yes/no). BMI was introduced as an intermediate step between Model 1 and Model 2 to assess its influence on the associations. Additionally, restricted cubic spline curves were generated based on Model 2 to explore potential non‐linear relationships between energy‐adjusted taurine intake and dementia risk. To identify the optimal curve fit, models with three to seven cutoff points were tested, with the model demonstrating the lowest Akaike information criterion (AIC) selected. Five cutoffs (0.05, 0.275, 0.5, 0.725, and 0.95) were ultimately chosen. To investigate if APOE ε4 status modified the impact of the energy‐adjusted taurine intake on dementia risk, we explored interactions between energy‐adjusted taurine intake and APOE ε4 status (carrier/non‐carrier) in relation to all‐cause dementia, AD, and vascular dementia (VaD) on a multiplicative scale by entering the interaction variables (energy‐adjusted taurine intake × APOE ε4 status) into Cox models.

The correlation between plasma taurine concentrations and food groups were assessed using Pearson correlation analyses. Partial correlations were conducted to examine the relationship between plasma taurine concentrations and lifestyle factors, adjusting for age and sex (additionally adjusted for blood pressure medication use in the analysis of systolic blood pressure). Partial correlations between plasma taurine concentrations and food intake were adjusted for age, sex, and total energy intake. Additionally, stepwise linear regression was performed to evaluate the associations between plasma taurine concentrations and both lifestyle and dietary factors. The results were further stratified by sex to examine potential sex‐specific effects. RCS curves were used to explore potential non‐linear relationships between plasma taurine levels and dementia risk.

Several sensitivity analyses were performed to assess the robustness of the findings and minimize the likelihood of chance associations. To assess the relationship between dietary taurine intake and dementia risk, four sensitivity analyses were performed. In the first sensitivity analysis, we used the crude taurine intake with adjustment of total energy intake in the Cox regression models. In the second sensitivity analysis, participants who were identified as energy misreporters or who had made significant dietary changes before the baseline examination (details have been described previously (Mattisson et al. 2005)) were excluded, resulting in a sample of 17 369 individuals. In the third sensitivity analysis, we excluded individuals with follow‐up time of < 5 years, leaving a total of 26 813 participants. In the fourth sensitivity analysis, participants with prevalent diabetes and cardiovascular disease (CVD) at baseline were excluded, leaving a total of 25 879 individuals for analysis. To examine the robustness of the correlations between plasma taurine concentrations and lifestyle factors or food intake, two additional sensitivity analyses were performed. First, we excluded energy misreporters and individuals with substantial dietary changes before baseline, resulting in a sample of 2329 participants. Second, we excluded participants with prevalent diabetes and CVD, leaving 3425 individuals for analysis. All statistical analyses were performed using R software (version 4.4.1) with the packages “survival” and “plotRCS.”

3. Results

3.1. Baseline Characteristics

Among the 27 786 dementia‐free participants recruited at baseline (1991–1996), 3224 (11.6%) developed dementia during a median follow‐up of 24.9 years, up to 2020. Table 1 presents baseline characteristics of participants by level of energy‐adjusted taurine intake. The average crude taurine intake was 127 mg/day, with a standard deviation of 49 mg. Individuals with higher energy‐adjusted taurine intake were more likely to be male, older, alcohol consumers, and anti‐hypertensive medication users. They also had slightly higher BMI and lower educational attainment. Additionally, higher energy‐adjusted taurine intake was more frequently associated with potential energy misreporting, prior significant dietary changes, a higher prevalence of diabetes, and higher use of anti‐hypertensive medications.

TABLE 1.

Baseline Characteristics of the Study Population by quintiles of energy‐adjusted taurine intake, n = 27 786.

	Energy‐adjusted taurine intake
	Quintile 1 (n = 5558)	Quintile 2 (n = 5557)	Quintile 3 (n = 5557)	Quintile 4 (n = 5557)	Quintile 5 (n = 5557)
	Mean (SD)
Age	56.8 (7.6)	58.1 (7.7)	58.5 (7.8)	58.7 (7.6)	58.5 (7.2)
BMI	24.9 (3.8)	25.5 (3.9)	25.8 (4.0)	26.0 (3.9)	26.5 (4.1)
Total energy intake (kcal/d)	2431 (695)	2212 (622)	2158 (603)	2204 (611)	2374 (685)
	N (%)
Males	2056 (37.0)	1870 (33.7)	1973 (35.5)	2186 (39.3)	2851 (51.3)
Smoking
Current smoker	1625 (29.2)	1553 (27.9)	1482 (26.7)	1576 (28.4)	1603 (28.8)
Former smoker	1737 (31.3)	1787 (32.2)	1905 (34.3)	1893 (34.1)	2094 (37.7)
Never smoker	2196 (39.5)	2217 (39.9)	2170 (39.0)	2088 (37.6)	1860 (33.5)
Alcohol consumers	5106 (91.9)	5190 (93.4)	5204 (93.6)	5242 (94.3)	5297 (95.3)
Education level
< 9 years	2115 (38.1)	2331 (41.9)	2420 (43.5)	2471 (44.5)	2304 (41.5)
9 years	1406 (25.3)	1493 (26.9)	1467 (26.4)	1491 (26.8)	1421 (25.6)
Upper secondary school	551 (9.9)	491 (8.8)	472 (8.5)	454 (8.2)	507 (9.1)
University, no degree	560 (10.1)	462 (8.3)	455 (8.2)	445 (8.0)	509 (9.2)
University degree	926 (16.7)	780 (14.0)	743 (13.4)	696 (12.5)	816 (14.7)
Physical activity, MET‐h/weeks
< 7.5	568 (10.2)	521 (9.4)	554 (10.0)	527 (9.5)	520 (9.4)
7.5–15	815 (14.7)	862 (15.5)	850 (15.3)	806 (14.5)	810 (14.6)
15–25	1215 (21.9)	1311 (23.6)	1314 (23.6)	1271 (22.9)	1286 (23.1)
25–50	2014 (36.2)	1954 (35.2)	2013 (36.2)	2068 (37.2)	2039 (36.7)
> 50	946 (17.0)	909 (16.4)	826 (14.9)	885 (15.9)	902 (16.2)
Social Network Index
0	645 (11.6)	825 (14.8)	866 (15.6)	900 (16.2)	898 (16.2)
1	1558 (28.0)	1677 (30.2)	1795 (32.3)	1853 (33.3)	1734 (31.2)
2	1671 (30.1)	1701 (30.6)	1653 (29.7)	1628 (29.3)	1638 (29.5)
3	1122 (20.2)	935 (16.8)	859 (15.5)	833 (15.0)	890 (16.0)
4	453 (8.2)	339 (6.1)	307 (5.5)	284 (5.1)	324 (5.8)
5	109 (2.0)	80 (1.4)	77 (1.4)	59 (1.1)	73 (1.3)
Prevalent diabetes	140 (2.5)	190 (3.4)	245 (4.4)	279 (5.0)	380 (6.8)
Anti‐hypertensive medication use	741 (13.3)	929 (16.7)	1025 (18.4)	1122 (20.2)	1185 (21.3)
Misreporters of energy intake
Under report	641 (11.5)	883 (15.9)	1013 (18.2)	961 (17.3)	787 (14.2)
Accurate	4620 (83.1)	4523 (81.4)	4442 (79.9)	4482 (80.7)	4590 (82.6)
Over report	297 (5.3)	151 (2.7)	102 (1.8)	114 (2.1)	180 (3.2)
Drastic diet changers	1366 (24.6)	1177 (21.2)	1253 (22.5)	1338 (24.1)	1637 (29.5)

3.2. Dietary Taurine Intake and Dementia Risk

Table 2 and Figure 2 illustrate the associations between quintiles of energy‐adjusted taurine intake and the risk of all‐cause dementia, with follow‐up to 2014 (based on validated dementia diagnoses by trained physicians) and extending follow‐up until 2020 (including unvalidated dementia cases from 2015 to 2020). Across both follow‐up periods, no significant linear or non‐linear associations were observed between taurine intake and dementia risk. In the fully adjusted model, individuals in the highest quintile of taurine intake did not have a significantly different risk of all‐cause dementia compared to those in the lowest quintile (HR for follow‐up till 2014: 0.97; 95% CI, 0.83–1.12; HR for follow‐up till 2020: 0.97; 95% CI, 0.86–1.08). Stratified analysis by sex yielded similar results for men and women (Table S2).

TABLE 2.

Associations between energy‐adjusted taurine intake and risk of all‐cause dementia.

	All‐cause dementia (until follow‐up 2014)			All‐cause dementia (until follow‐up 2020)
	Cases/Person‐years	Model 1	Model 2	Cases/Person‐years	Model 1	Model 2
Quintile 1	352/103093	Ref	Ref	608/124107	Ref	Ref
Quintile 2	373/100926	0.95 (0.82–1.10)	0.94 (0.81–1.09)	641/120448	0.98 (0.87–1.09)	0.97 (0.86–1.08)
Quintile 3	440/101366	1.06 (0.92–1.22)	1.04 (0.90–1.20)	704/120425	1.04 (0.93–1.16)	1.02 (0.91–1.14)
Quintile 4	382/101033	0.92 (0.80–1.07)	0.90 (0.78–1.04)	642/120156	0.94 (0.84–1.05)	0.92 (0.82–1.03)
Quintile 5	381/100317	0.99 (0.86–1.15)	0.97 (0.83–1.12)	629/118445	0.99 (0.89–1.11)	0.97 (0.86–1.08)
Per 1‐SD		0.99 (0.95–1.04)	0.99 (0.94–1.03)		1.00 (0.96–1.03)	0.99 (0.95–1.03)

Abbreviations: Model 1: age, sex, season of dietary assessment, and diet method; Model 2: age, sex, season of dietary assessment, diet method, smoking status, educational level, leisure‐time physical activity, alcohol consumption, body mass index, Social Network Index, prevalent diabetes, and anti‐hypertensive medication use.

FIGURE 2.

Restricted cubic spline analysis of energy‐adjusted taurine intake in relation to the risk of all‐cause dementia (followed up to 2014 and 2020), Alzheimer's disease (followed up to 2014), and vascular dementia (followed up to 2014). Models are adjusted for age, sex, season of dietary assessment, diet method, smoking status, educational level, leisure‐time physical activity, alcohol consumption, body mass index, Social Network Index, prevalent diabetes, and anti‐hypertensive medication use.

Table 3 and Figure 2 display the associations between quintiles of energy‐adjusted taurine intake and the risk of AD and VaD up to 2014, based on validated dementia subtype diagnoses. No evident linear or non‐linear trend was observed between taurine intake and either dementia subtype. In the fully adjusted model, individuals in the highest quintile of taurine intake did not have a significantly different risk of developing AD and VaD compared to those in the lowest quintile (AD: HR, 1.01; 95% CI, 0.83–1.22; VaD: HR, 0.99; 95% CI, 0.72–1.35). Similar findings were observed in sex‐stratified analyses (Table S3). In the restricted cubic spline analysis stratified by APOE ε4 status (Figure S1), no significant association was observed between taurine intake and risk of all‐cause dementia, AD, and VaD in either APOE ε4 carriers or non‐carriers.

TABLE 3.

Associations between energy‐adjusted taurine intake and risk of Alzheimer's disease and vascular dementia until end of follow‐up 31 December 2014.

	Alzheimer's disease			Vascular dementia
	Cases/Person‐years	Model 1	Model 2	Cases/Person‐years	Model 1	Model 2
Quintile 1	208/103530	Ref	Ref	74/104179	Ref	Ref
Quintile 2	209/101428	0.88 (0.72–1.06)	0.86 (0.71–1.05)	93/102013	1.15 (0.85–1.56)	1.12 (0.82–1.52)
Quintile 3	260/101904	1.04 (0.87–1.25)	1.02 (0.85–1.23)	102/102556	1.18 (0.87–1.59)	1.12 (0.83–1.51)
Quintile 4	227/101441	0.92 (0.76–1.11)	0.90 (0.74–1.09)	94/102018	1.08 (0.79–1.46)	1.00 (0.74–1.36)
Quintile 5	225/100793	1.02 (0.84–1.23)	1.01 (0.83–1.22)	92/101312	1.10 (0.81–1.49)	0.99 (0.72–1.35)
Per 1‐SD		1.01 (0.95–1.08)	1.01 (0.95–1.08)		1.00 (0.91–1.11)	0.97 (0.88–1.07)

Abbreviations: Model 1, age, sex, season of dietary assessment, and diet method; Model 2, age, sex, season of dietary assessment, diet method, smoking status, educational level, leisure‐time physical activity, alcohol consumption, body mass index, Social Network Index, prevalent diabetes, and anti‐hypertensive medication use.

3.3. Correlations Between Plasma Taurine Concentrations, Lifestyle Factors, and Food Intake

Table 4 presents the correlation between serum taurine concentrations and various lifestyle factors, food intake, and dietary taurine intake. Among lifestyle factors, serum taurine concentrations showed a weak but significant positive correlation with age (r = 0.12) and sex (r = 0.10), indicating higher taurine concentrations in older individuals and males. No significant associations were observed with alcohol consumption, education, smoking, physical activity, or BMI. Serum taurine concentrations were weakly positively correlated with HDL and LDL cholesterol and systolic blood pressure, while negatively associated with fasting plasma glucose.

TABLE 4.

Correlations between plasma taurine level and lifestyle factors and food intakes.

	Pearson correlation	Partial correlation	Stepwise‐linear regression
Age	0.116 (< 0.001)	—	0.108 (< 0.001)
Sex	0.099 (< 0.001)	—	0.055 (0.002)
Alcohol habits a	−0.015 (0.359)	0.016 (0.327)	—
Education a	−0.012 (0.474)	0.000 (0.982)	—
Smoking a	−0.009 (0.582)	−0.022 (0.175)	—
Physical activity a	0.002 (0.905)	−0.004 (0.818)	—
BMI a	−0.015 (0.365)	−0.004 (0.831)	—
Fasting glucose (plasma) a	−0.046 (0.005)	0.032 (0.055)	−0.045 (0.007)
Triglycerides (mmol/L) a	−0.034 (0.036)	−0.014 (0.395)	—
HDL (mmol/L) a	0.087 (< 0.001)	0.038 (0.021)	0.060 (< 0.001)
LDL (mmol/L) a	0.073 (< 0.001)	0.063 (< 0.001)	0.051 (0.002)
Systolic blood pressure b	0.070 (< 0.001)	0.036 (0.030)	0.052 (0.003)
Ice cream > 6% fat c	0.001 (0.973)	0.011 (0.494)	—
Nuts c	−0.069 (< 0.001)	−0.016 (0.322)	−0.054 (< 0.001)
Vegetables c	−0.001 (0.975)	0.021 (0.195)	—
Fruit and berries c	0.034 (0.038)	0.012 (0.459)	—
Potatoes c	−0.033 (0.045)	0.007 (0.667)	—
Bread (low fiber content) c	−0.067 (< 0.001)	−0.022 (0.173)	—
Bread (high fiber content) c	−0.023 (0.161)	0.013 (0.440)	—
Grains/Cereals < 15% sugar c	−0.037 (0.024)	−0.023 (0.166)	—
Grains/Cereals > 15% sugar c	−0.019 (0.242)	−0.003 (0.848)	—
Rice pasta c	−0.022 (0.188)	0.014 (0.399)	—
Pastries c	0.006 (0.724)	−0.009 (0.594)	—
Eggs c	0.001 (0.928)	0.014 (0.395)	—
Cream c	−0.024 (0.140)	−0.009 (0.578)	−0.038 (0.021)
Cheese c	0.002 (0.902)	0.035 (0.036)	—
Margarine c	−0.065 (< 0.001)	−0.042 (0.010)	−0.044 (0.008)
Butter‐based fat c	−0.012 (0.464)	0.015 (0.352)	—
Oil/Mayonise/Dressing c	−0.027 (0.102)	0.026 (0.120)	—
Candy c	0.039 (0.017)	0.060 (< 0.001)	0.053 (0.001)
Chocolate c	−0.009 (0.570)	−0.001 (0.950)	—
Jam/Sugar	−0.024 (0.140)	−0.020 (0.217)	—
Fruit juice c	0.025 (0.136)	−0.005 (0.751)	—
Sugar‐enriched drinks c	−0.028 (0.085)	−0.009 (0.584)	—
Diet drinks c	0.015 (0.364)	−0.011 (0.491)	—
Coffee c	0.020 (0.217)	0.056 (< 0.001)	0.043 (0.009)
Tea c	−0.038 (0.020)	−0.051 (0.002)	—
Red meat c	−0.044 (0.008)	0.004 (0.807)	—
Milk c	−0.028 (0.091)	−0.032 (0.052)	—
Fish c	0.014 (0.404)	0.004 (0.797)	—
Shellfish c	0.028 (0.093)	0.034 (0.039)	0.037 (0.024)
Chicken c	−0.018 (0.282)	−0.013 (0.438)	—
Total taurine intake d	−0.033 (0.044)	0.011 (0.497)	—

^a Partial correlation between plasma taurine and lifestyle factors. Adjusted for age and sex.

^b Partial correlation between plasma taurine and systolic blood pressure. Controlled for age, sex, and use of blood pressure medication.

^c Partial correlation between plasma taurine and food intake. Adjusted for age, sex, and energy intake.

^d Partial correlation between plasma taurine and estimated daily taurine intake. Adjusted for age, sex, and energy intake.

Serum taurine level was negatively associated with dietary taurine intake (r: −0.033, p = 0.044). For specific food groups, when mutually adjusting for lifestyle factors and the other foods (using stepwise linear regression), serum taurine concentrations exhibited weak inverse correlations (r = −0.04 to 0.05) with consumption of nuts, cream and margarine and positive correlations (r = 0.04–0.05) with consumption of candy, coffee and shellfish. Additional stratified analysis by sex is provided in Table S4. The results indicate that correlations between plasma taurine concentrations and lifestyle factors, as well as food intake, were generally consistent across sexes. However, stronger associations were observed in males for coffee intake and cheese consumption. Chocolate and tea consumption was inversely associated with plasma taurine concentrations in females but not in males, whereas shellfish consumption was positively associated with plasma taurine concentrations in females but not in males.

3.4. Plasma Taurine Concentrations and Dementia Risk

Figure 3 illustrates the association between plasma taurine concentrations and all‐cause dementia (follow‐up to 2014 and to 2020), AD (follow‐up to 2014) and VaD (follow‐up to 2014) risk. This analysis revealed no associations between plasma taurine concentrations and the risk of all‐cause dementia, AD, or VaD.

FIGURE 3.

Restricted cubic spline analysis of plasma taurine level in relation to the risk of all‐cause dementia (followed up to 2014 and 2020), Alzheimer's disease (followed up to 2014), and vascular dementia (followed up to 2014). Models are adjusted for age, sex, season of dietary assessment, diet method, smoking status, educational level, leisure‐time physical activity, alcohol consumption, body mass index, Social Network Index, prevalent diabetes, and anti‐hypertensive medication use.

3.5. Sensitivity Analyses

To assess the robustness of our findings on dietary taurine intake and dementia risk, we performed several sensitivity analyses (Tables S5 and S6). Using crude instead of energy‐adjusted taurine intake, excluding participants classified as potential energy misreporters or those who had significantly altered their diet before baseline, or excluding participants with < 5 years of follow‐up did not alter the results. Similarly restricting the analysis to participants without diabetes or cardiovascular disease at baseline yielded comparable null associations.

For plasma taurine concentrations, excluding energy misreporters and individuals with major dietary changes before baseline (Table S7), or those with diabetes and cardiovascular disease at baseline (Table S8), had minimal impact on observed correlations with lifestyle factors and food intake, confirming the stability of the findings.

4. Discussion

This study aimed to explore the relationship between dietary taurine intake, plasma taurine concentrations, and the risk of dementia in a large, well‐characterized Swedish cohort. Despite compelling preclinical evidence suggesting that taurine may exert neuroprotective effects, our findings do not support a significant association between taurine intake or circulating taurine concentrations and the risk of all‐cause dementia, AD or VaD.

While preclinical studies have consistently demonstrated that taurine supplementation can mitigate the neurodegenerative process in AD mouse models (Ahmed et al. 2024; El Idrissi ²⁰⁰⁸; Garcia‐Serrano et al. ²⁰²³; Kim et al. ²⁰¹⁴; Louzada et al. ²⁰⁰⁴; Oh et al. ²⁰²⁰; Wu et al. ²⁰¹⁷; Zhu et al. ²⁰²³), translating these findings to human populations remains challenging. Our results contrast with previous observations that higher concentrations of taurine are associated with a lower risk of dementia (Chouraki et al. 2017) and rather align with the lack of a protective effect of taurine supplementation against cognitive decline or with limited effects on learning and memory capacity (Chupel et al. 2021; Park et al. ²⁰²²). A clinical study in elderly people suggested that 4‐week taurine supplementation improves some measurements of memory impairment compared to performance at baseline, but lacked control groups to account for placebo and other effects of the intervention (Bae et al. 2022). Another study by the same authors proposed a positive relation between taurine intake and cognitive performance, but included a small number of test subjects (Bae et al. 2017). The lack of association in our study may reflect the complexity of human diets and lifestyles, or the possibility that taurine's neuroprotective effects are only evident under specific pathological conditions or in combination with other lifestyle factors that are not captured in general population studies (Rafiee et al. 2022). Moreover, preclinical studies often use controlled environments, genetically homogeneous animals, and high doses of taurine. These factors are surely not replicating the complexity of human populations or real‐world exposure to dietary taurine, or the multifactorial nature of dementia in humans. Our findings suggest that, within the range of dietary intake and plasma concentrations observed in our cohort, taurine may not exert a measurable protective effect against dementia. Importantly, the doses of taurine administered in animal studies are often substantially higher than those achievable through a typical human diet, and taurine bioavailability may differ between species (e.g., plasma or cortical taurine concentrations are much larger in mice or rats than in humans; Rafiee et al. ²⁰²²). In our cohort, both dietary intake and plasma levels of taurine reflected habitual consumption without taurine supplementation, which may be insufficient for affording the neuroprotection suggested by animal research.

Interestingly, we observed only weak correlations between plasma taurine concentrations and dietary intake, suggesting that endogenous regulation and other metabolic factors may play a more prominent role in determining circulating taurine concentrations than diet alone. Moreover, the inverse correlation between plasma taurine and dietary taurine intake, though modest, raises questions about the reliability of plasma taurine as a biomarker of intake or even its utility in predicting dementia risk. Our findings remained robust across multiple sensitivity analyses and were consistent across sexes and APOE ε4 genotypes. This suggests that neither genetic susceptibility nor sex‐specific metabolic differences significantly modify the relationship between taurine and dementia risk.

A major strength of this study is its large, well‐characterized cohort with an extended follow‐up duration, which enabled robust analyses of taurine intake and dementia risk. Additionally, the use of validated dementia diagnoses by trained physicians strengthens the accuracy of the results. The incorporation of unvalidated dementia diagnoses from 2015 to 2020 is another strength, as prior research has shown that general dementia diagnoses (all‐cause dementia) are valid in 96% of cases. However, unvalidated AD and VaD data from 2015 to 2020 were excluded from analyses, as 40% of specific dementia diagnoses prior to 2014 were altered during the re‐evaluation process (Nägga et al. 2022). Another strength of this study is that we summarized taurine content as the mean value derived from measured taurine levels in various foods reported across seven publications, providing a standardized reference that can be utilized in future studies investigating taurine intake and its potential health effects.

Several limitations should also be acknowledged. First, dietary intake data were self‐reported, making them susceptible to recall bias and misreporting. Nevertheless, the dietary method captured both habitual and recent intakes, and validation studies have shown that the quality of dietary data in the Malmö Diet and Cancer Study is high (Elmstahl et al. 1996; Riboli et al. ¹⁹⁹⁷). Furthermore, previous research has demonstrated acceptable agreement between repeated dietary measures in participants of similar age to those in our study (Jankovic et al. 2014; Nagel et al. ²⁰⁰⁷). Second, despite extensive adjustments for potential confounders and conducting several sensitivity analyses, residual confounding cannot be entirely ruled out. Additionally, dietary data were collected in the 1990s, meaning information on the consumption of energy drinks—known to contain high taurine levels (~4000 mg/L) (Rubio et al. 2022)–was unavailable, which may limit the interpretation of dietary taurine sources. Nevertheless, taurine‐containing energy drinks only reached the Swedish market after 1996 and were unavailable during the baseline assessment and sample collection, and the European Food Safety Authority estimates low consumption rates of energy drinks by the age segment of the MDC population (Zucconi et al. 2013). Lastly, the findings may have limited generalizability to non‐Nordic populations with distinct dietary habits and patterns.

In conclusion, this study provides no evidence to support a protective role of dietary taurine against dementia, AD or VaD, despite the promising findings from experimental models of neurodegeneration and metabolic disease. These findings underscore the importance of validating preclinical results in diverse human populations and highlight the need for further research to clarify the role of taurine in brain aging and cognitive health. Future studies should consider longitudinal changes in taurine levels, the impact of high‐dose supplementation, and interactions with other dietary and metabolic factors to better understand taurine's potential in dementia prevention.

Author Contributions

Naiqi Zhang: writing – original draft, investigation, formal analysis, data curation, visualization. Yan Borné: investigation, formal analysis, writing – review and editing, data curation. Elisabeth Hagberg: writing – review and editing. Sebastian Palmqvist: writing – review and editing. Isabelle Glans: writing – review and editing. Filip Ottosson: writing – review and editing. Jessica Samuelsson: writing – review and editing. Katarina Nägga: writing – review and editing. Oskar Hansson: conceptualization, writing – review and editing. João M. N. Duarte: conceptualization, writing – review and editing, funding acquisition, resources, project administration. Emily Sonestedt: conceptualization, supervision, resources, writing – review and editing, project administration.

Conflicts of Interest

Sebastian Palmqvist has acquired research support (for the institution) from Avid and ki elements through ADDF. In the past 2 years, he has received consultancy/speaker fees from Bioartic, Eisai, Eli Lilly, Novo Nordisk, and Roche. Oskar Hansson is an employee of Lund University and Eli Lilly. João M.N. Duarte is handling editor of the Journal of Neurochemistry.

Supporting information

Data S1: jnc70298‐sup‐0001‐Supinfo.pdf.

Zhang, N. , Borné Y., Hagberg E., et al. 2025. “Taurine Intake, Plasma Taurine Concentration, and Dementia Risk: Findings From the Malmö Diet and Cancer Study.” Journal of Neurochemistry 169, no. 11: e70298. 10.1111/jnc.70298.

Data Availability Statement

All data supporting the findings of this study are available from the MDCS (https://www.malmo‐kohorter.lu.se/malmo‐cohorts).