Acrylamide and Health Outcomes

January 25, 2024 updated by: Federica Laguzzi, Karolinska Institutet

Does Acrylamide Increase the Risk of Neurodegenerative and Cardiovascular Disease?

Acrylamide, a widespread food-processing contaminant, poses a major public health concern due to its high exposure level in the general population and its toxicity. While animal evidence shows that acrylamide causes neurological alterations and may play a role in cardiovascular disease, evidence in humans is lacking. Our project aims to investigate whether dietary acrylamide exposure, measured in blood, increases the risk of dementia, Alzheimer's and Parkinson's diseases and myocardial infarction. In addition, the aim is to improve the understanding of the biological mechanisms underlying these associations integrating small compounds in blood (i.e., OMICS).

In two population-based cohorts, the Cohort of 60-Year-Olds and the Swedish Mammography Cohort, acrylamide will be assessed in blood samples using a case-cohort design (around 2145 individuals, 20-year follow-up). The results will be presented in four scientific publications using adequate data analysis. The project will run from 2024-2028.

The project´s findings will help improve public health through safer food and better nutrition. If findings indicate that acrylamide increases the risk of these diseases, this will urge interventions to decrease acrylamide exposure via food production and consumption. In turn, this will help to reduce the burden of these diseases. Even findings showing null association will be equally relevant to avoid unnecessary and costly preventive measures.

Study Overview

Detailed Description

Background

Acrylamide forms in foods rich in starch when cooked/processed at temperature >120°C (e.g., roasting, frying, grilling) in absence of moisture. Acrylamide may also form in foods from acrolein during the degradation of amino acids, carbohydrates, lipids, and organic acids. Of note, the content of acrylamide in diet may vary strongly depending on the food matrix and processing methods (home and restaurants cooking and/or industrial processing). Acrylamide is prevalent in a wide-range of commonly consumed foods (e.g. coffee, biscuits, breakfast cereals, bread especially crispy bread, potato products and vegetables crisps) - some of these are also part of a healthy diet. Acrylamide is also produced in heated tobacco.

Acrylamide-induced neurotoxic adverse effects have been well-documented in animal and occupational studies. From its inception, acrylamide is a chemical compound used in the industry to produce plastics (polyacrylamides). However, its occupational exposure is considered of low concern due to successful intervention and preventive measures. Cumulative exposure to acrylamide in workers via inhalation and/or dermal absorption have been observed to give rise central and peripheral neurotoxicity, supporting the concern related to cumulative dietary acrylamide exposure in the development of neurodegenerative disorders in the general population. Yet, to date, no epidemiological studies have investigated whether dietary acrylamide exposure associates to neurodegenerative diseases including dementia, Alzheimer´s, and Parkinson´s diseases.

Growing body of evidence also indicate that acrylamide´s mode of action might lead to cardiometabolic alteration which in turn, play a critical role in atherosclerosis and CVD development. Still, epidemiological evidence investigating dietary acrylamide and incidence of CVD including myocardial infarction are lacking.

In theory, acrylamide can exert toxicity in all the human organs. In vivo and vitro studies show that acrylamide-induced toxicity may be evident at low doses. However, it is proposed that the detrimental effects will exacerbate at high doses or most likely at prolonged/cumulative exposure such the dietary exposure resulting in the clinical manifestation of the diseases here investigated. There is substantial evidence showing that toxicity of acrylamide is mediated by glycidamide, a highly reactive compound and the main metabolite of acrylamide, via the formation of DNA adducts. Also, production of oxidative stress and formation of adducts with protein (especially alkylation) are considered plausible molecular initiating events to trigger cumulative neurotoxicity. For the acrylamide-induced neurotoxicity, acrylamide is suspected to promote neuroinflammation, induce neurite degeneration, inhibit axonal transport, alter the level and turnover of neurotransmitters (e.g., enhanced activity of acetylcholinesterase and dopamine depletion) and directly inhibit neurotransmission which ultimately may result in learning and memory impairment, anxiogenic responses, and disturbed motor coordination. Consequently, this can give rise to neurodegenerative disease.

The importance of using objective measures of dietary intake in epidemiological studies to improve accuracy and limit biases and acknowledged difficulties related to the estimation of dietary exposures from self-reported questionnaire and food databases has been stressed. Biomarkers of acrylamide exposure have been identified and validated in blood and in urines. The blood biomarkers i.e., blood hemoglobin adducts are considered more suitable biomarkers of exposure, as they may reflect long term of exposure (previous four months) and are not influenced by daily fluctuations.

Finally, screening for potential acrylamide-related metabolomics and proteomics may contribute, in epidemiological studies, to strengthen the possible exposure-health outcome association and understand its mode of action. To our knowledge, little effort has been made in this direction in this field. In unpublished data based on the EUROMIX (n=120 healthy subject), an association was found between hemoglobin adducts and 4 proteins (JAM-B, CNTN5, CLEC10A and EPHB6) related to neurological alteration.

Specific aims:

To assess the relationship between dietary acrylamide exposure, measured through validated biomarkers (i.e., acrylamide and glycidamide hemoglobin adducts) and the risk of dementia including Alzheimer´s disease (n=700 cases) - Aim 1; Parkinson´s disease (n =190 cases) - Aim 2 and myocardial infarction (n= 390 cases) - Aim 3 in two population-based Swedish cohorts, The Cohort of 60-year-olds (60YO) and The Swedish Mammography Cohort (SMC) employing a case-cohort design.

In addition, exposure-affected OMICS' signatures (mainly proteins and metabolomics) will be used to explore molecular pathways potentially underlying diseases development and to support biological plausibility. Acrylamide-related metabolic and proteins biomarkers will be assessed in relation to risk of the diseases under investigation (only SMC) - Aim 4

Study design: The project will be based on two relatively large population-based cohorts, The Cohort of 60-year-olds (60YO) and the Swedish Mammography Cohort (SMC). Both cohorts are well-established in Sweden. Due to the high cost of acrylamide biomarkers measurements, a case-cohort design will be employed. The total estimated case-cohort sample will consist of approximately 1,740 participants. Two sub-cohorts will be randomly selected from the full cohorts (n = 442 around 5 % of the baseline population in 1997-1999, for 60YO, and 2003-2009, for SMC). All the cases of each of the diseases under investigation (i.e., dementia including Alzheimer´s, Parkinson´s disease and myocardial infarction) occurring outside the sub-cohorts will be included. The cases will include participants free of any diagnosis of each of the diseases investigated at the time of sampling. Incident cases of the diseases under investigation will be identified through linkage to the National Patient Register and Cause of Death Register till the end of follow-up (2022 for both cohorts). The incident cases of dementia and Alzheimer´s disease will also be retrieved through the linkage to the Swedish registry for cognitive/dementia disorders (SveDem). The integration of this quality register will improve the sensitivity of dementia diagnosis which has been shown to be low when detected only from the National Patient Register and the Cause of Death Register. The statistical power calculation (%) based on the expected incident cases (n) for each of the diseases under investigation and assumed Hazard Ratios (HR) as follows:

cases expected: Myocardial infarction: n=390; Dementia (including Alzheimer´s disease) n=710 and Parkinson´s disease n= 192

Power calculation:

HR 1.25: MI: 50%,Dementia: 60% and Parkinson: 34% HR 1.50: MI 90%, Dementia:95%, Parkinson: 70% HR: 1.75: MI 99%, Dementia: 100% and Parkinson 91%

Detailed information on the 60YO and SMC are provided here:

https://ki-se.proxy.kib.ki.se/en/imm/the-cohort-of-60-year-olds; https://www.simpler4health.se/.

Exposures: Acrylamide biomarkers measured in blood, i.e., acrylamide and glycidamide hemoglobin adducts. Whole blood samples (approximately n = 1,740) will be collected (0.5 ml) from samples stored in freezer at -80°C at Uppsala University biobank, for the SMC, and at Karolinska Institutet (KI) biobank, for the 60YO, and sent to a certified laboratory in Stockholm. The assessment will be carried out with a validated method in Törnqvist's laboratory. Briefly, the acrylamide and glycidamide hemoglobin adducts to N-terminal valine (AA-val and Gly-val, respectively) will be measured in blood by LC-MS based methods, representing the exposure during the lifespan of the erythrocyte. The case/control status of the samples will be unknown during the analysis. Laboratory batch will be adjusted for in all analyses. Each of two acrylamide biomarkers will be modeled as continuous (per 10 pmol/g increment) and in categories (tertiles or quartiles) to assess potential nonlinear dose-response.

Outcome definition: Incident cases of dementia (including Alzheimer´s disease), Parkinson´s disease and myocardial infarction. Based on the International Classification of disease version 10 (ICD10), the diagnoses included are the following:

Neurodegenerative disorders:

  • Dementia (in Alzheimer´s disease, vascular, related to other disease, unspecified) including Alzheimer´s disease, other specified (including Lewis bodies) and unspecified neurodegenerative diseases: F00-F03, G30, G31.8, G31.9
  • Parkinson´s disease:G20

Cardiovascular disease:

- Myocardial infarction:I21

Metabolomic and Proteomic data: Metabolites and proteins markers are already available in the SMC sample. Large scale untargeted liquid chromatography-mass spectrometry and OLINK panels (Proseek Multiplex CVD II, CVD III and Metabolism) were employed to obtain these data from blood sample collected at baseline. For detailed information on the methodology and analytical process, please refer to previously published research26,27. A total of approximately 10,000 metabolites and 250 proteins will be available for all the individuals selected for the case-cohort sample (approximately n=900).

Time plan and implementation:

The project will last four years (Jan 2024-Dec 2026).

Data analysis and statistics:

Project I: acrylamide and glycidamide hemoglobin adducts in relation to risk of neurodegenerative and cardiovascular diseases.

Cox proportional hazards weighted regression models will be employed to estimate hazard ratios and 95% confidence intervals (CI) for each of the health outcomes under investigation in relation to acrylamide and glycidamide biomarkers, respectively, with follow-up from the date of acrylamide biomarker measurement till December, 31rst, 2022. Weighted likelihood approach using Borgan II weights will be applied28. The weighted method will allow to make inference on the full cohort28. Models will be adjusted considering several covariates such as sex (only for 60YO), age (only for SMC), education, physical activity, smoking, alcohol consumption, body mass index, dietary factors and other important confounders retrieved a priori from the literature. Analysis will be performed separately in the two cohorts. Then, results will be combined considering the possible heterogeneity between cohorts using random effect models. The main analysis will be repeated separately in smokers and non-smokers. Smokers have three to four times higher levels of acrylamide compared to the non-smokers. Conducting this analysis separately is important to better distinguish the risks associated with different sources of acrylamide exposure, specifically from the diet versus smoking. Since acrylamide may disrupt hormonal levels, menopausal status will be also considered in the analysis. To investigate the shape of the possible relationship between acrylamide biomarkers and the diseases considered, each of the associations with multivariate restricted cubic splines will be also modelled. Assuming that the true hazard ratio (HR) is 1.5 and with a significance level α =0.05, by using 5% of the total cohort, ≥90% of statistical power for analysis involving dementia and myocardial infarction and 70% for Parkinson disease are expected. If the true HR will be ≤1.25, the statistical power will decrease and analysis related to Parkinson´s disease may be underpowered if not combined with dementia including Alzheimer's disease. Multivariable adjustments as well as the employment of exposures in categories may somewhat reduce the power.

Additionally, the association between dietary factors and acrylamide levels (Sub-project), taking advantage of the longitudinal dietary information present in SMC, will be investigated. Multi-adjusted quantile regression models will be employed to model changes in the diet during 1989-1990, 1997, 2009 in relation to blood acrylamide levels. Foods that may have high content of acrylamide have been investigated, however it will be important to clarify which dietary determinants/dietary pattern may be relevant in the association with acrylamide levels.

Project II: associations between acrylamide hemoglobin adducts and OMICS data (Phase I) and related metabolites/proteins and incidence of neurodegenerative and myocardial infarction (Phase II).

The proposed analysis will be performed in SMC only. The expected sample size for this analysis will be around n=900 of which n=236 for the subsample and n=420 cases for neurodegenerative disease and n=160 cases for myocardial infarction.

Phase I: Partial Least Squares analysis adapted for large-scale OMICS data to minimize false positive associations, followed by partial Spearman rank correlation analysis adjusted for covariates will be used to investigate the association between OMICS' data and acrylamide and glycidamide biomarkers29. Phase II: Each of those proteins and metabolites identified in Phase I will be then modeled as independent variables in relation to the risk of each of the diseases under investigation, using multi-adjusted Cox proportional hazards weighted regression models accounting for multiple testing corrections. To facilitate interpretation, significant proteins and metabolites will then be plotted with their correlation with each of the blood biomarkers of acrylamide and the diseases under investigation.

Study Type

Observational

Enrollment (Estimated)

1700

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

      • Stockholm, Sweden, 17177
        • Recruiting
        • Karolinska Institutet
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Probability Sample

Study Population

The project will be based on two relatively large Swedish population-based cohorts, The Cohort of 60-year-olds (60YO) and the Swedish Mammography Cohort (SMC). We will employ a case-cohort design.

The 60YO includes 2,039 men and 2,193 women who during the period from July 1st, 1997, to June 30th, 1998, reached the age of 60 and resided in Stockholm County at the time of recruitment. Every third man and woman who fulfilled the inclusion criteria were invited to participate (https://ki-se.proxy.kib.ki.se/en/imm/the-cohort-of-60-year-olds).

The SMC was initiated in 1987-1990, when all women residing in two counties in central Sweden (Uppsala or adjacent Västmanland county), born 1914-1948, were invited to the study (n = 90,303) by receiving a diet and lifestyle questionnaire (74% response rate). (https://www.simpler4health.se/).

Description

Inclusion Criteria:

  • adults (18 years old)
  • blood measured at the recruitment

Exclusion Criteria:

  • prevalent cases of the diseases investigated

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
The Cohort of 60-year-olds (60YO): case-cohort study design

The project is an observational study and will employ a case-cohort design using two cohorts Swedish cohorts- The Cohort of 60-year-olds (60YO) and the Swedish Mammography Cohort (SMC).

A sub-cohorts will be randomly selected from the full cohorts (aprox n = 450 around 5 %-of the baseline population in 1997-1999, for 60YO, and 2003-2009, for SMC). All the cases of each of the diseases under investigation occurring outside the sub-cohorts will be included. The cases will include participants free of any diagnosis of each of the diseases investigated at the time of sampling. Incident cases of the diseases under investigation will be identified through linkage to the Swedish National Cancer Register, National Patient Register, Cause of Death Register and Swedish registry for cognitive/dementia disorders till the end of follow-up (2022 for both cohorts).

Each of two acrylamide biomarkers will be modeled as continuous (per 10 pmol/g increment) and in categories (tertiles or quartiles) to assess potential nonlinear dose-response.
The Swedish Mammography Cohort (SMC)
A case-cohort design will be employed as for 60YO cohort (see cohort label "60YO")
Each of two acrylamide biomarkers will be modeled as continuous (per 10 pmol/g increment) and in categories (tertiles or quartiles) to assess potential nonlinear dose-response.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Dementia (yes/no)
Time Frame: 20 years

Incident cases of dementia dementia (in Alzheimer´s disease, vascular, related to other disease, unspecified) including Alzheimer´s disease, other specified (including Lewis bodies) and unspecified neurodegenerative diseases using ICD codes version 10 as follows: F00-F03, G30, G31.8, G31.9.

The cases will include participants free of any diagnosis of dementia investigated at the time of blood sampling (2004-2009 for SMC and 1997-1998 for 60YO). Incident cases of dementia will be identified through linkage to the Swedish National Cancer Register, National Patient Register, Swedish registry for cognitive/dementia disorders (SveDem) and Cause of Death Register till the end of follow-up (2022 for both cohorts).

20 years
Parkinson disease (yes/no)
Time Frame: 20 years

Parkinson´s disease, ICD codes version 10th: G20

The cases will include participants free of any diagnosis of Parkinson disease investigated at the time of blood sampling (2004-2009 for SMC and 1997-1998 for 60YO). Incident cases of Parkinson disease will be identified through linkage to the Swedish National Cancer Register, National Patient Register and Cause of Death Register till the end of follow-up (2022 for both cohorts).

20 years
Myocardial infarction (yes/no)
Time Frame: 20 years
Myocardial infarction, ICD code version 10th: I21. The cases will include participants free of any diagnosis of myocardial infarction investigated at the time of blood sampling (2004-2009 for SMC and 1997-1998 for 60YO). Incident cases of Parkinson disease will be identified through linkage to the Swedish National Cancer Register, National Patient Register and Cause of Death Register till the end of follow-up (2022 for both cohorts).
20 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Federica Laguzzi, Karolinska Instittutet

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2024

Primary Completion (Estimated)

December 31, 2024

Study Completion (Estimated)

December 31, 2026

Study Registration Dates

First Submitted

January 16, 2024

First Submitted That Met QC Criteria

January 16, 2024

First Posted (Actual)

January 25, 2024

Study Record Updates

Last Update Posted (Estimated)

January 26, 2024

Last Update Submitted That Met QC Criteria

January 25, 2024

Last Verified

January 1, 2024

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

The individual participant data that support the findings of this study are available from the corresponding author upon reasonable request.

IPD Sharing Time Frame

Proposals may be submitted up to 36 months following article publication. After 36 months the data will be available in our University's data warehouse but without investigator support other than deposited metadata. Information regarding submitting proposals may be found at Clinical Trials. gov

IPD Sharing Access Criteria

Upon reasonable request

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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