It’s estimated that 47 million people worldwide suffer from dementia, with this number projected to triple by 2050. In order to manage the significant burden that neurodegenerative diseases pose for society and national healthcare systems, there is a demand for effective diagnostic techniques to facilitate early detection, accurate risk prediction and the development of therapeutic interventions.
To bring about preventative care for dementia, it’s essential that we unravel the pathophysiology causes of neurodegenerative diseases. Few studies have examined the role metabolites play in regulating cognitive ability, despite previous evidence linking metabolic dysregulation to impaired cognition. Pronounced decline in cognitive performance is a key feature characterizing all neurodegenerative diseases, with clinical and epidemiological evidence suggesting a relationship between cognitive function and a number of metabolic aberrations. Dyslipidemia for example, has been linked to impaired cognitive performance, including: high levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and lowered levels of high-density lipoprotein cholesterol (HDL-C).
In a recent study, van der Lee and colleagues analyzed 299 circulating metabolites related to general cognitive ability in two Dutch-based discovery cohorts, the Rotterdam Study (RS) and the Erasmus Rucphen Family (ERF) study (N=5658). Nightingale’s platform was used to measure 220 metabolic biomarkers, including: amino acids, glycolysis measures, ketone bodies and fatty acids, as well as the lipid concentrations and compositions of 14 lipoprotein subclasses. Additional metabolic measures were obtained using mass spectrometry techniques.
Overall, 17 metabolites were found to significantly associate with improved or reduced cognitive ability, independently of known vascular and metabolic risk factors. Two metabolites were then excluded (as they were not found to be significant in replication). In the study’s first main finding, the remaining 15 metabolites were replicated in 4 population cohorts (Netherlands Twin Register, Whitehall II study, the Framingham Heart study and the Study of Health in Pomerania-Trend).
Among these 15 metabolites, 12 strongly associated with higher general cognitive ability, along with 3 metabolites (glycoprotein acetyls, glutamine and ornithine) linked to impaired cognition. Of the 12 metabolites with positive associations, HDL subtractions and (omega-3 fatty acid) docosahexaenoic acid (DHA) displayed the strongest significance.
Investigators further explored the biology of the 15 metabolites by examining their associations with lifestyle factors (e.g. smoking, dietary intake and physical activity), providing an insight into potential lifestyle interventions. A number of lifestyle factor metabolite associations were identified, with dietary intake of fish (oil) found to increase DHA levels. Physical activity was found to associate with increased levels of the metabolites linked to higher cognitive function (e.g. medium and large HDL subtractions), along with decreased levels of the metabolites associated with impaired cognition. Smokers displayed associations in the opposite direction, with increased levels of metabolites associated with impaired cognition and decreased HDL subtractions linked to improved cognitive ability. Whilst these results give us some indication of the complex metabolic effects of lifestyle factors, the molecular mechanisms underpinning these measured associations are poorly understood. It’s clear that more studies are required to fully investigate the impact of metabolism on both the generally healthy and elderly suffering from “mild cognitive impairment.”
To further investigate the 15 metabolites, the researchers tested them for associations with Alzheimer’s disease (AD) and dementia in a total of 10 cohorts. Out of these, 6 metabolites were found to significantly associated with AD and/or all-cause dementia – the study’s second main finding. In the all-cause dementia and AD cases, free cholesterol in small HDLs and DHA displayed the strongest associations with lowered disease risk, and higher glutamine levels were found to significantly associate with increased risk of AD and dementia.
Overall, these findings suggest several novel metabolic indicators of brain health. Further studies investigating these metabolites could lead to more effective assessment of neurodegenerative disease risk. The increasing number of studies investigating vascular disease (along with other common chronic diseases), present an ideal opportunity for a better understanding of the links between seemingly disparate diseases. Nightingale’s high-throughput metabolomics assay also offers the potential for dynamic readouts of the molecular effects resulting from preventative lifestyle changes or therapeutic interventions, facilitating targeted treatment of the molecular mechanisms that underpin dementia.
This study is an example of Nightingale's NMR metabolomics platform being applied in neurodegenerative disease research, as part of the 4th Rainbow Project of the BioBanking for Medical Research Infrastructure of the Netherlands (BBMRI-NL). Our blood analysis service can be utilized to investigate the molecular mechanisms underpinning dementia, using metabolic profiling to identify circulating biomarkers associated with cognitive function and neurodegenerative diseases.
In this study, our assay was used to quantify metabolic measures (including detailed lipid and lipoprotein particle profiles), for 5658 participants across two discovery cohorts, with results being further replicated in four independent cohorts (N total= 56,652). This is one of the largest studies to date utilizing Nightingale’s technology and is currently the biggest investigation into blood-based metabolites associated with general cognitive ability. Nightingale's assay has been successfully used in a wide range of research applications and has featured in over 100 peer-reviewed studies.
Access the full paper here and learn more about how Nightingale’s assay has been used in BBMRI-NL research here.