Lifepath: how we will use biomarker research

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Quality of life and life expectancy are not the same for all individuals. Dramatic differentials in these traits, as well as in many other health features, represent one of the biggest challenges for our society. Social and economic factors play a major role in determining these differences, as it has been proved that people from higher socio-economic groups are more likely to live longer and in better health conditions. Such an issue may only be faced by developing future health policies and strategies that take into account the close relationship between health and wellbeing on the one hand, and socio-economic conditions on the other. And this is one of the main objectives pursued by Lifepath project.

Biological pathways linking determinants to healthy ageing

What is missing in linking overarching determinants like socio-economic status (SES) to health and poor ageing is an understanding of the intermediate mechanisms and biological pathways that relate low SES with deterioration of organic parameters. For example, research on immune markers in the Whitehall II study has shown that glucocorticoids and inflammation may in part explain how the body mediates the effects of low SES thus leading to disease, and this is partly independent from the most common and well-known risk factors like smoking. More generally, recent studies have shown that SES can influence the global physiological dysregulation across the life-course, measured using a measure of biological multisystem wastage defined as allostatic load.

The approach based on intermediate biomarkers is more powerful than the one based on traditional risk factors alone because (a) it may explain subtle chronic effects acting throughout the life-course (like chronic stress) that are not easily captured by questionnaire-based epidemiology; (b) it allows to trace signals that start in early life down to health effects in later life; (c) it provides an approach to the discovery of new pathways and causes of disease, particularly through the new omic technologies. By analysing intermediate biomarkers potentially involved in various diseases, this approach is likely to reveal some common – and currently unknown – roots of many non-communicable diseases (NCDs) like multi-morbidity, thus improving our ability to implement successful interventions, with a wide range of actions.

Epigenetics and human social genomics

Recently, evidence has accumulated on the key role of epigenetic modifications induced by the experience of psychosocial adversity in initiating physiological dysregulations. More specifically, human and animal studies have shown that SES influences DNA methylation and gene expression, particularly across genomic regions regulating immune function. A pivotal study in macaques detected altered levels of expression and methylation in inflammatory genes (in particular NFATC1, IL8RB – CXCR2 in humans – and PTGS2) in relation to changes in hierarchical status. To date, the few studies that have addressed this issue in humans reported associations between SES in early and adult life and DNA methylation of genes regulating the immune function. However, these studies were usually based on small samples and subject to methodological limitations. In particular, it remains to be established to what extent SES has an impact on DNA methylation independently of unhealthy lifestyles – thus directly altering gene regulation – and which are the features of low SES directly influencing cellular activity and its regulation.

To encompass the overall impact of social adversities on biology, the concept of human social genomics has been put forward. A core element is the modulation of transcription factors by environmental and social circumstances, through the so-called conserved transcription response to adversity (CTRA). The latter is represented by the pattern of responses (largely inflammatory and immunological) that have developed during evolution to cope with stressful environments, and that implicate networks of transcription factors in their mechanisms. Although such patterns were originally developed to respond to microbial and traumatic sources of stress, they have evolved into generalized responses to environmental pressure, including psychological stress or sleep loss. These modulation patterns occur in the leukocytes, i.e. a cell type that is easily accessible in large population-based studies. 

Biological pathways: omics and biomarkers in Lifepath

The research carried out by Lifepath is focused on cohorts that are extremely rich in biomarker measurements, most of which have been measured recently and still have to be analysed statistically. Some biomarkers are already available or will be measured with existing funds: methylome, inflammation markers and metabolomics. Most cohorts have C-Reactive Protein (CRP), and many have cytokines.

We will perform new methylome analyses for 2,500 new subjects and new transcriptomic analyses for about 600 subjects. Peripheral blood is a convenient source for epigenetic testing, but cellular heterogeneity can confound or mask the results, because epigenetic signatures differ from one cell subtype to another. Moreover, the composition of the blood cells can change under a plethora of pathophysiological conditions, and this can also be influenced by SES. The importance of measuring epigenetic patterns across specific cell subtypes also depends on disease status, and subtle differences are likely more important for multifactorial traits. For these reasons, we will perform first the methylome in two specific blood cell types in 500 Whitehall II subjects and then validate the findings in PBMC in cohorts with cell counts available. We will also enrich our biomarker stock by measuring IL6 and other cytokines in 6,600 additional subjects in Whitehall II and in Skipogh and Colaus, in which also the methylome and RNA sequencing will be measured (n=500).

Gene-environment interactions will be part of the project. Genotyping will be performed (or is already available) through other funds for 17,000 subjects from Airwave, 6,600 from Whitehall II, 1,100 from Skipogh and 6,000 from Colaus. The Cardiometabochip will be used in all of them except in Colaus. We will be able to relate genetic susceptibility to SES and to include genetic susceptibility in the life-course trajectories leading from poor SES to unhealthy ageing and to investigate how genetic susceptibility modulates the role of exposures and omic markers.

Paolo Vineis, Imperial College, London

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