33 research outputs found

    A glossary for social-to-biological research

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    Research has shown that our socially structured experiences elicit a biological response, leading to the observation that numerous biomarkers (objective biological measures that are representative of various biological processes) are socially patterned. This ‘social-to-biological’ research is of interest to researchers across multiple disciplines and topics and especially to those with an interest in understanding the biological embodiment of the ‘social environment’. Combining social and biomarker data is also of relevance to those examining the biological determinants of social behaviours (for example, the relationship between genetics and certain behaviours like smoking). However, as much of the research involving biomarkers and social data are multidisciplinary, researchers need to understand why and how to optimally use and combine such data. This article provides a resource for researchers by introducing a range of commonly available biomarkers across studies and countries. Because of the breadth of possible analyses, we do not aim to provide an exhaustive and detailed review of each. Instead, we have structured the glossary to include: an easy-to-understand definition; a description of how it is measured; key considerations when using; and an example of its use in a relevant social-to-biological study. We have limited this glossary to biomarkers that are available in large health and social surveys or population-based cohort studies and focused on biomarkers in adults. We have structured the glossary around the main physiological systems studied in research on social to biological transition and those that go across systems and highlight some basic terms and key theoretical concepts

    Life-course socioeconomic status and DNA methylation of genes regulating inflammation

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    Background: In humans, low socioeconomic status (SES) across the life course is associated with greater diurnal cortisol production, increased inflammatory activity and higher circulating antibodies for several pathogens, all suggesting a dampened immune response. Recent evidence suggests that DNA methylation of pro-inflammatory genes may be implicated in the biological embedding of the social environment. Methods: The present study examines the association between life-course SES and DNA methylation of candidate genes, selected on the basis of their involvement in SES-related inflammation, in the context of a genome-wide methylation study. Participants were 857 healthy individuals sampled from the EPIC Italy prospective cohort study. Results: Indicators of SES were associated with DNA methylation of genes involved in inflammation. NFATC1, in particular, was consistently found to be less methylated in individuals with low vs high SES, in a dose-dependent manner. IL1A, GPR132 and genes belonging to the MAPK family were also less methylated among individuals with low SES. In addition, associations were found between SES and CXCL2 and PTGS2, but these genes were consistently more methylated among low SES individuals. Conclusions: Our findings support the hypothesis that the social environment leaves an epigenetic signature in cells. Although the functional significance of SES-related DNA methylation is still unclear, we hypothesize that it may link SES to chronic disease ris

    A glossary for social-to-biological research

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    Research has shown that our socially structured experiences elicit a biological response, leading to the observation that numerous biomarkers (objective biological measures that are representative of various biological processes) are socially patterned. This ‘social-to-biological’ research is of interest to researchers across multiple disciplines and topics and especially to those with an interest in understanding the biological embodiment of the ‘social environment’. Combining social and biomarker data is also of relevance to those examining the biological determinants of social behaviours (for example, the relationship between genetics and certain behaviours like smoking). However, as much of the research involving biomarkers and social data are multidisciplinary, researchers need to understand why and how to optimally use and combine such data. This article provides a resource for researchers by introducing a range of commonly available biomarkers across studies and countries. Because of the breadth of possible analyses, we do not aim to provide an exhaustive and detailed review of each. Instead, we have structured the glossary to include: an easy-to-understand definition; a description of how it is measured; key considerations when using; and an example of its use in a relevant social-to-biological study. We have limited this glossary to biomarkers that are available in large health and social surveys or population-based cohort studies and focused on biomarkers in adults. We have structured the glossary around the main physiological systems studied in research on social to biological transition and those that go across systems and highlight some basic terms and key theoretical concepts

    Biological marks of early-life socioeconomic experience is detected in the adult inflammatory transcriptome.

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    Consistent evidence is accumulating to link lower socioeconomic position (SEP) and poorer health, and the inflammatory system stands out as a potential pathway through which socioeconomic environment is biologically embedded. Using bloodderived genome-wide transcriptional profiles from 268 Italian participants of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we evaluated the association between early life, young and later adulthood SEP and the expression of 845 genes involved in human inflammatory responses. These were examined individually and jointly using several inflammatory scores. Our results consistently show that participants whose father had a manual (as compared to nonmanual) occupation exhibit, later in life, a higher inflammatory score, hence indicating an overall increased level of expression for the selected inflammatory-related genes. Adopting a life course approach, these associations remained statistically significant upon adjustment for later-in-life socioeconomic experiences. Sensitivity analyses indicated that our findings were not affected by the way the inflammatory score was calculated, and were replicated in an independent study. Our study provides additional evidence that childhood SEP is associated with a sustainable upregulation of the inflammatory transcriptome, independently of subsequent socioeconomic experiences. Our results support the hypothesis that early social inequalities impacts adult physiology

    The Choice of the Filtering Method in Microarrays Affects the Inference Regarding Dosage Compensation of the Active X-Chromosome

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    The hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays.To investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels than autosomes. We compared the ratio of expression levels of X-linked to autosomal transcripts (X∶AA) using two different filtering methods: 1. gene expressions were filtered out using a detection threshold irrespective of gene chromosomal location (the standard method in microarrays); 2. equal proportions of genes were filtered out separately on the X and on autosomes. For a wide range of filtering proportions, the X∶AA ratio estimated with the first method was not significantly different from 1, the value expected if dosage compensation was achieved, whereas it was significantly lower than 1 with the second method, leading to the rejection of the hypothesis of dosage compensation. We further showed in simulated data that the choice of the most appropriate method was dependent on biological assumptions regarding the proportion of actively expressed genes on the X chromosome comparative to the autosomes and the extent of dosage compensation.This study shows that the method used for filtering out lowly expressed genes in microarrays may have a major impact according to the hypothesis investigated. The hypothesis of dosage compensation of X-linked genes cannot be firmly accepted or rejected using microarray-based data

    Patterning of educational attainment across inflammatory markers: Findings from a multi-cohort study

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    Background: Evidence suggests that the inflammatory reaction, an adaptive response triggered by a variety of harmful stimuli and conditions involved in the risk and development of many chronic diseases, is a potential pathway through which the socioeconomic environment is biologically embedded. Difficulty in interpreting the role of the inflammatory system in the embodiment dynamic arises because of heterogeneity across studies that use a limited but varied number of inflammatory markers. There is no consensus in the literature as to which inflammatory markers beyond the C-reactive protein and to a lesser extent interleukin 6 are related to the social environment. Accordingly, we aimed to investigate the association between educational attainment, and several markers of inflammation - C-reactive protein, fibrinogen, interleukin 6, interleukin 1 beta and tumor necrosis factor alpha- in 6 European cohort studies.Methods: Up to 17,470 participants from six European cohort studies with data on educational attainment, health behaviors and lifestyle factors, and at least two different inflammatory markers. Four sub-datasets were drawn with varying numbers of participants to allow pairwise comparison of the social patterning of C-reactive protein and any other inflammatory markers. To evaluate within each sub-dataset the importance of the context and cohort specificities, linear regression-based analyses were performed separately for each cohort and combined in a random effect meta-analysis to determine the relationship between educational attainment and inflammation.Results: We found that the magnitude of the relationship between educational attainment and five inflammatory biomarkers (C-reactive protein, fibrinogen, interleukin 6 and 1 beta and tumor necrosis factor alpha) was variable. By far the most socially patterned biomarker was C-reactive protein, followed by fibrinogen and to lesser extent interleukin 6, where a low educational attainment was associated with higher inflammation even after adjusting for health behaviours and body mass index. No association was found with interleukin 1 beta and tumor necrosis factor alpha.Conclusions: Our study suggests different educational patterning of inflammatory biomarkers. Further large-scale research is needed to explore social differences in the inflammatory cascade in greater detail and the extent to which these differences contribute to social inequalities in health.</div

    Large scale international replication and meta-analysis study confirms association of the 15q14 locus with myopia. The CREAM consortium

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    Myopia is a complex genetic disorder and a common cause of visual impairment among working age adults. Genome-wide association studies have identified susceptibility loci on chromosomes 15q14 and 15q25 in Caucasian populations of European ancestry. Here, we present a confirmation and meta-analysis study in which we assessed whether these two loci are also associated with myopia in other populations. The study population comprised 31 cohorts from the Consortium of Refractive Error and Myopia (CREAM) representing 4 different continents with 55,177 individuals; 42,845 Caucasians and 12,332 Asians. We performed a meta-analysis of 14 single nucleotide polymorphisms (SNPs) on 15q14 and 5 SNPs on 15q25 using linear regression analysis with spherical equivalent as a quantitative outcome, adjusted for age and sex. We calculated the odds ratio (OR) of myopia versus hyperopia for carriers of the top-SNP alleles using a fixed effects meta-analysis. At locus 15q14, all SNPs were significantly replicated, with the lowest P value 3.87 × 10 -12 for SNP rs634990 in Caucasians, and 9.65 × 10 -4 for rs8032019 in Asians. The overall meta-analysis provided P value 9.20 × 10 -23 for the top SNP rs634990. The risk of myopia versus hyperopia was OR 1.88 (95 % CI 1.64, 2.16, P < 0.001) for homozygous carriers of the risk allele at the top SNP rs634990, and OR 1.33 (95 % CI 1.19, 1.49, P < 0.001) for heterozygous carriers. SNPs at locus 15q25 did not replicate significantly (P value 5.81 × 10 -2 for top SNP rs939661). We conclude that common variants at chromosome 15q14 influence susceptibility for myopia in Caucasian and Asian populations world-wide. © The Author(s) 2012

    Associations of adverse childhood experiences with smoking initiation in adolescence and persistence in adulthood, and the role of the childhood environment: Findings from the 1958 British birth cohort

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    International audienceAdverse childhood experiences (ACEs) have been identified as a strong determinant of smoking. We aimed to examine the association between ACEs and early smoking initiation and subsequent persistence and the contribution of five pathways including family factors, parental involvement, material living conditions, social activities and conscientiousness.Data are from 7414 individuals born in 1958 in Great Britain included in the National Child Development Study. ACEs were measured at ages 7, 11, and 16. Smoking initiation was derived from smoking variables from ages 16 to 42 and persistent smoking was derived from smoking variables from ages 23 to 42. We modelled the relationship between ACEs and smoking, and further assessed the contribution of each pathway using multinomial logistic regressions.During childhood, 20.9% of respondents experienced one ACE and 6.4% two or more. Those who experienced ACEs had a higher risk of initiating smoking by age 16 and of persistent smoking (RRR initiation by 16y = 1.89 [1.62; 2.20] for one ACE; RRR initiation by 16y = 2.36 [1.81; 3.08] for two or more ACEs, and RRR persistent smoking = 2.07 [1.73; 2.47] for one ACE, RRR persistent smoking = 2.59 [1.92; 3.49] for two or more ACEs). The factors that contributed most to explaining these associations were parental smoking, sibling order and conscientiousness. ACEs remained associated with persistent smoking after further adjusting for young adulthood variables.Smoking prevention measures may need to be tailored when considering adolescents from communities where ACEs are more prevalent to curtail initiation, intensity and persistence
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