Genetic GIScience: Toward a Place-Based Synthesis of the Genome, Exposome, and Behavome

Changing Neighborhood Income Deprivation Over Time, Moving in Childhood, and Adult Risk of Depression

Importance

Complex biological, socioeconomic, and psychological variables combine to cause mental illnesses, with mounting evidence that early-life experiences are associated with adulthood mental health.

Objective

To evaluate whether changing neighborhood income deprivation and residential moves during childhood are associated with the risk of receiving a diagnosis of depression in adulthood.

Design, Setting, and Participants

This cohort study included the whole population of 1 096 916 people born in Denmark from January 1, 1982, to December 31, 2003, who resided in the country during their first 15 years of life. Individuals were followed up from 15 years of age until either death, emigration, depression diagnosis, or December 31, 2018. Longitudinal data on residential location was obtained by linking all individuals to the Danish longitudinal population register. Statistical analysis was performed from June 2022 to January 2024.

Exposures

Exposures included a neighborhood income deprivation index at place of residence for each year from birth to 15 years of age and a mean income deprivation index for the entire childhood (aged ≤15 years). Residential moves were considered by defining "stayers" as individuals who lived in the same data zone during their entire childhood and "movers" as those who did not.

Main Outcomes and Measures

Multilevel survival analysis determined associations between neighborhood-level income deprivation and depression incidence rates after adjustment for individual factors. Results were reported as incidence rate ratios (IRRs) with 95% credible intervals (95% CrIs). The hypotheses were formulated before data collection.

Results

A total of 1 096 916 individuals (563 864 male participants [51.4%]) were followed up from 15 years of age. During follow-up, 35 098 individuals (23 728 female participants [67.6%]) received a diagnosis of depression. People living in deprived areas during childhood had an increased risk of depression (IRR, 1.10 [95% CrI, 1.08-1.12]). After full individual-level adjustment, the risk was attenuated (IRR, 1.02 [95% CrI, 1.01-1.04]), indicating an increase of 2% in depression incidence for each 1-SD increase in income deprivation. Moving during childhood, independent of neighborhood deprivation status, was associated with significantly higher rates of depression in adulthood compared with not moving (IRR, 1.61 [95% CrI, 1.52-1.70] for 2 or more moves after full adjustment).

Conclusions and Relevance

This study suggests that, rather than just high or changing neighborhood income deprivation trajectories in childhood being associated with adulthood depression, a settled home environment in childhood may have a protective association against depression. Policies that enable and support settled childhoods should be promoted.

Pathomechanistic Networks of Motor System Injury in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is the most common, adult-onset, progressive motor neurodegenerative disorder that results in death within 3 years of the clinical diagnosis. Due to the clinicopathological heterogeneity, any reliable biomarkers for diagnosis or prognosis of ALS have not been identified till date. Moreover, the only three clinically approved treatments are not uniformly effective in slowing the disease progression. Over the last 15 years, there has been a rapid advancement in research on the complex pathomechanistic landscape of ALS that has opened up new avenues for successful clinical translation of targeted therapeutics. Multiple studies suggest that the age-dependent interaction of risk-associated genes with environmental factors and endogenous modifiers is critical to the multi-step process of ALS pathogenesis. In this review, we provide an updated discussion on the dysregulated cross-talk between intracellular homeostasis processes, the unique molecular networks across selectively vulnerable cell types, and the multisystemic nature of ALS pathomechanisms. Importantly, this work highlights the alteration in epigenetic and epitranscriptomic landscape due to gene-environment interactions, which have been largely overlooked in the context of ALS pathology. Finally, we suggest that precision medicine research in ALS will be largely benefitted from the stratification of patient groups based on the clinical phenotype, onset and progression, genome, exposome, and metabolic identities.

Building effective intervention models utilizing big data to prevent the obesity epidemic

INTRODUCTION

The exposome consists of factors an individual is exposed to across the life course. The exposome is dynamic, meaning the factors are constantly changing, affecting each other and individuals in different ways. Our exposome dataset includes social determinants of health as well as policy, climate, environment, and economic factors that could impact obesity development. The objective was to translate spatial exposure to these factors with the presence of obesity into actionable population-based constructs that could be further explored.

METHODS

Our dataset was constructed from a combination of public-use datasets and the Center of Disease Control's Compressed Mortality File. Spatial Statistics using Queens First Order Analysis was performed to identify hot- and cold-spots of obesity prevalence; followed by Graph Analysis, Relational Analysis, and Exploratory Factor Analysis to model the multifactorial spatial connections.

RESULTS

Areas of high and low presence of obesity had different factors associated with obesity. Factors associated with obesity in areas of high obesity propensity were: poverty / unemployment; workload, comorbid conditions (diabetes, CVD) and physical activity. Conversely, factors associated in areas where obesity was rare were: smoking, lower education, poorer mental health, lower elevations, and heat.

DISCUSSION

The spatial methods described within the paper are scalable to large numbers of variables without issues of multiple comparisons lowering resolution. These types of spatial structural methods provide insights into novel variable associations or factor interactions that can then be studied further at the population or policy levels.

Allostatic Load and Exposure Histories of Disadvantage

The stress pathway posits that those in disadvantaged circumstances are exposed to a higher degree of stressful experiences over time resulting in an accumulated biological burden which subsequently relates to poorer health. Trajectories of disadvantage, in the form of neighbourhood deprivation and structural social capital, are evaluated in their relation to allostatic load representing the cumulative “wear and tear” of chronic stress. This paper uses data from the British Household Panel Survey and Understanding Society in a latent class growth analysis. We identify groups of exposure trajectories over time using these classes to predict allostatic load at the final wave. The results show that persistent exposure to higher deprivation is related to worse allostatic load. High structural social capital over time relates to lower allostatic load, in line with a stress buffering effect, though this relationship is not robust to controlling for individual sociodemographic characteristics. By demonstrating a gradient in allostatic load by histories of deprivation, this analysis supports a biological embedding of disadvantage through chronic exposure to stressful environments as an explanation for social health inequalities.

The latitude gradient for multiple sclerosis prevalence is established in the early lifecourse

The strongest epidemiological clue that the environment at the population level has a significant impact on the risk of developing multiple sclerosis (MS) is the well-established, and in many instances, increasing latitudinal gradient of prevalence, incidence and mortality globally, with prevalence increasing by up to 10-fold between the equator and 60 degrees North and South. The drivers of this gradient are thought to be environmental with latitude seen as a proxy for ultraviolet radiation and thus vitamin D production, however other factors may also play a role. However several important questions remain unanswered, particularly when in the life course is the gradient established, does lifetime migration mitigate or exacerbate previously reported latitude gradients at location of diagnosis, and do factors such as sex or MS disease phenotype influence the timing or significance of the gradient? Utilising life time residence calendars collected as part of the New Zealand national MS prevalence study, we constructed lifetime latitudinal gradients for MS from birth to prevalence day 2006 taking into account migration internally and externally and then analysed by sex and MS clinical course phenotype. 2127 of 2917 people living in NZ on prevalence day 7 March 2006 with MS completed the life course questionnaire and of these 1587 were born in NZ. All cohorts and sub cohorts were representative of the overall MS population in NZ on prevalence day. We found that the prevalence gradient was present at birth and was in fact stronger than at census day, and the slope of the gradient persisted until the age of 12 before gradually declining. We found that internal and external migration into NZ had little if any effect on the gradient except to decrease the significance of the gradient somewhat. Finally, we found as we had reported previously that the lifetime prevalence gradients were largely driven by females with relapse onset MS. These findings confirm for the first time the importance of early life environmental exposures in the risk of MS indicating strongly that exposures as early as in utero and at birth drive the latitudinal gradient. Consequently, prevention studies should be focussed on high risk individuals and populations from the earliest possible time points especially, when appropriate, on females.

Emerging concepts and challenges in implementing the exposome paradigm in allergic diseases and asthma: a Practall document

Exposome research can improve the understanding of the mechanistic connections between exposures and health to help mitigate adverse health outcomes across the life span. The exposomic approach provides a risk profile instead of single predictors and thus is particularly applicable to allergic diseases and asthma. Under the PRACTALL collaboration between the European Academy of Allergy and Clinical Immunology (EAACI) and the American Academy of Allergy, Asthma, and Immunology (AAAAI), we evaluated the current concepts and the unmet needs on the role of the exposome in allergic diseases and asthma.

Gene-Environment-Time Interactions in Neurodegenerative Diseases: Hypotheses and Research Approaches

Background

Amyotrophic lateral sclerosis (ALS), Alzheimer's, and Parkinson's diseases are age-related neurodegenerative diseases. ALS is not a single entity but a syndrome with many different causes. In all 3 diseases, gene mutations account for only 10-15% of cases. Many environmental and lifestyle factors have been implicated as risk factors for ALS, though none have been proven to cause the disease. It is generally believed that ALS results from interactions between environmental risk factors and genetic predisposing factors. The advent of next-generation sequencing and recent advances in research into environmental risk factors offer the opportunity to investigate these interactions.

Summary

We propose a hypothesis to explain the syndrome of ALS based on the interaction of many individual environmental risk factors with many individual genetic predisposing factors. We hypothesize that there are many such combinations of individual, specific, genetic, and environmental factors, and that each combination can lead to the development of the syndrome of ALS. We also propose a hypothesis that explains the overlap between the age-related neurodegenerations and their genetic underpinnings. Age and duration of exposure are crucial factors in these age-related neurodegenerative diseases, and we consider how these may relate to gene-environment interactions.

Key Messages

To date, genetic studies and environmental studies have investigated the causes of ALS separately. We argue that this univariate approach will not lead to discoveries of important gene-environment interactions. We propose new research approaches to investigating gene-environment interactions based on these hypotheses.

Geographic Information Science and the Analysis of Place and Health

The representation of place is a key theoretical advancement that Geographic Information Science can offer to improve the understanding of environmental determinants of health, but developing robust computational representations of place requires a substantial departure from conventional notions of geographic representation in Geographic Information Systems (GIS). Unlike conventional GIS representations based on either objects or locations, we suggest place representation should incorporate dynamic subjective, experiential, and relational aspects of place, as the influence of place on health behavior concerns not only the features that can be objectively observed at a particular location but also the environmental perceptions of the individual, as molded by biological, social, and experiential characteristics. In addition, assessments of environmental exposures on health outcomes should focus on individuals' time-activity patterns and microenvironment profiles, which form a potentially unique personalized exposure environment for each individual. Addressing these representational challenges via collaborative research has the potential to advance both Geographic Information Science and health research.

Residential mobility: Towards progress in mobility health research

Research into health disparities has long recognized the importance of residential mobility as a crucial factor in determining health outcomes. However, a lack of connectivity between the health and mobility literatures has led to a stagnation of theory and application on the health side, which lacks the detail and temporal perspectives now seen as critical to understanding residential mobility decisions. Through a critical re-think of mobility processes with respect to health outcomes and an exploitation of longitudinal analytical techniques, we argue that health geographers have the potential to better understand and identify the relationship that residential mobility has with health.

Assessing Cyanobacterial Harmful Algal Blooms as Risk Factors for Amyotrophic Lateral Sclerosis

Reoccurring seasonal cyanobacterial harmful algal blooms (CHABs) persist in many waters, and recent work has shown links between CHAB and elevated risk of amyotrophic lateral sclerosis (ALS). Quantifying the exposure levels of CHAB as a potential risk factor for ALS is complicated by human mobility, potential pathways, and data availability. In this work, we develop phycocyanin concentration (i.e., CHAB exposure) maps using satellite remote sensing across northern New England to assess relationships with ALS cases using a spatial epidemiological approach. Strategic semi-analytical regression models integrated Landsat and in situ observations to map phycocyanin concentration (PC) for all lakes greater than 8 ha (n = 4117) across the region. Then, systematic versions of a Bayesian Poisson Log-linear model were fit to assess the mapped PC as a risk factor for ALS while accounting for model uncertainty and modifiable area unit problems. The satellite remote sensing of PC had strong overall ability to map conditions (adj. R2, 0.86; RMSE, 11.92) and spatial variability across the region. PC tended to be positively associated with ALS risk with the level of significance depending on fixed model components. Meta-analysis shows that when average PC exposure is 100 μg/L, an all model average odds ratio is 1.48, meaning there is about a 48% increase in average ALS risk. This research generated the first regionally comprehensive map of PC for thousands of lakes and integrated robust spatial uncertainty. The outcomes support the hypothesis that cyanotoxins increase the risk of ALS, which helps our understanding of the etiology of ALS.

How Sensors Might Help Define the External Exposome

The advent of the exposome concept, the advancement of mobile technology, sensors, and the “internet of things” bring exciting opportunities to exposure science. Smartphone apps, wireless devices, the downsizing of monitoring technologies, along with lower costs for such equipment makes it possible for various aspects of exposure to be measured more easily and frequently. We discuss possibilities and lay out several criteria for using smart technologies for external exposome studies. Smart technologies are evolving quickly, and while they provide great promise for advancing exposure science, many are still in developmental stages and their use in epidemiology and risk studies must be carefully considered. The most useable technologies for exposure studies at this time relate to gathering exposure-factor data, such as location and activities. Development of some environmental sensors (e.g., for some air pollutants, noise, UV) is moving towards making the use of these more reliable and accessible to research studies. The possibility of accessing such an unprecedented amount of personal data also comes with various limitations and challenges, which are discussed. The advantage of improving the collection of long term exposure factor data is that this can be combined with more “traditional” measurement data to model exposures to numerous environmental factors.

The Social Determinants of Health Core: Taking a Place-Based Approach

INTRODUCTION

There is growing recognition that health disparities research needs to incorporate social determinants in the local environment into explanatory models. In the transdisciplinary setting of the Mid-South Transdisciplinary Collaborative Center (TCC), the Social Determinants of Health (SDH) Core developed an approach to incorporating SDH across a variety of studies. This place-based approach, which is geographically based, transdisciplinary, and inherently multilevel, is discussed.

METHODS

From 2014 through 2016, the SDH Core consulted on a variety of Mid-South TCC research studies with the goal of incorporating social determinants into their research designs. The approach used geospatial methods (e.g., geocoding) to link individual data files with measures of the physical and social environment in the SDH Core database. Once linked, the method permitted various types of analysis (e.g., multilevel analysis) to determine if racial disparities could be explained in terms of social determinants in the local environment.

RESULTS

The SDH Core consulted on five Mid-South TCC research projects. In resulting analyses for all the studies, a significant portion of the variance in one or more outcomes was partially explained by a social determinant from the SDH Core database.

CONCLUSIONS

The SDH Core approach to addressing health disparities by linking neighborhood social and physical environment measures to an individual-level data file proved to be a successful approach across Mid-South TCC research projects.

The skin aging exposome

The term "exposome" describes the totality of exposures to which an individual is subjected from conception to death. It includes both external and internal factors as well as the human body's response to these factors. Current exposome research aims to understand the effects all factors have on specific organs, yet today, the exposome of human skin has not received major attention and a corresponding definition is lacking. This review was compiled with the collaboration of European scientists, specialized in either environmental medicine or skin biology. A comprehensive review of the existing literature was performed using PubMed. The search was restricted to exposome factors and skin aging. Key review papers and all relevant, epidemiological, in vitro, ex vivo and clinical studies were analyzed to determine the key elements of the exposome influencing skin aging. Here we propose a definition of the skin aging exposome. It is based on a summary of the existing scientific evidence for the role of exposome factors in skin aging. We also identify future research needs which concern knowledge about the interaction of distinct exposomal factors with each other and the resulting net effects on skin aging and suggest some protective measures.

THE LONG-TERM DYNAMICS OF RACIAL/ETHNIC INEQUALITY IN NEIGHBORHOOD AIR POLLUTION EXPOSURE, 1990-2009

Research examining racial/ethnic disparities in pollution exposure often relies on cross-sectional data. These analyses are largely insensitive to exposure trends and rarely account for broader contextual dynamics. To provide a more comprehensive assessment of racial-environmental inequality over time, we combine the 1990 to 2009 waves of the Panel Study of Income Dynamics (PSID) with spatially- and temporally-resolved measures of nitrogen dioxide (NO₂) and particulate matter (PM_2.5 and PM₁₀) in respondents' neighborhoods, as well as census data on the characteristics of respondents' metropolitan areas. Results based on multilevel repeated measures models indicate that Blacks and Latinos are, on average, more likely to be exposed to higher levels of NO₂, PM_2.5, and PM₁₀ than Whites. Despite nationwide declines in levels of pollution over time, racial and ethnic disparities persist and cannot be fully explained by individual-, household-, or metropolitan-level factors.