Environmental triggers as significant as genetics for disease development – upi.com

A Paradigm Shift in Biomedical Research Towards Sustainable Health Outcomes

A significant shift is underway in biomedical research, moving from a primary focus on genetics to a more comprehensive framework known as “exposomics.” This emerging field aims to systematically map the totality of environmental exposures an individual encounters throughout their life. This holistic approach is critical for advancing Sustainable Development Goal 3 (SDG 3), which aims to ensure healthy lives and promote well-being for all at all ages, by addressing the vast majority of disease factors that are non-genetic.

Exposomics: Rationale and Alignment with Global Health Goals

Addressing the Environmental Determinants of Health (SDG 3)

Research indicates that genetic factors account for approximately 10% of common diseases, with the remaining 90% attributed to environmental influences. By investigating this vast environmental component, exposomics directly supports the targets of SDG 3 by seeking to understand and mitigate the root causes of non-communicable diseases and other health issues. The primary objective is to translate comprehensive exposure data into practical, personalized health solutions.

Defining the Exposome for Holistic Health Assessment

The exposome encompasses a wide range of elements that contribute to an individual’s health status over their lifetime. This data is crucial for building a complete picture of health that can inform public policy and clinical practice, contributing to both SDG 3 and SDG 10 (Reduced Inequalities) by highlighting social determinants of health. Key components include:

• Chemical Exposures: Environmental chemicals and pollutants.
• Physical Exposures: Light, temperature, and radiation.
• Social Determinants: Income, education, and community context.
• Biological Elements: Dietary intake, physical activity, and biomarkers in bodily fluids.

Innovation and Infrastructure for Sustainable Development (SDG 9 & SDG 17)

Advanced Technologies Driving Research

The recent momentum in exposomics is propelled by technological advancements capable of managing and analyzing immense datasets, reflecting progress under SDG 9 (Industry, Innovation, and Infrastructure). These tools allow for a “discovery-based” approach that moves beyond targeted hypotheses to a more comprehensive scan of potential health factors. Key technologies include:

• Geospatial Data: Satellite imagery and location-based data are used to measure exposures such as air and water quality, directly supporting the creation of sustainable and healthy communities (SDG 11).
• Mass Spectrometry: Advanced analytical techniques detect thousands of chemical markers in biological samples, providing a detailed molecular snapshot of an individual’s exposures.
• Wearable Devices: Sensors and devices like the “exposometer” enable real-time collection of chemical and biological samples directly from an individual, offering unprecedented data resolution.
• Artificial Intelligence: Computational models and AI are employed to systematically analyze vast and complex datasets to identify patterns between exposures and health outcomes.

Fostering Collaborative Partnerships (SDG 17)

The immense scope of exposomics necessitates interdisciplinary collaboration, a core principle of SDG 17 (Partnerships for the Goals). The field unites experts from genetics, environmental science, and data science. This collaborative spirit is exemplified by the establishment of the Network for Exposomics in the United States (NEXUS), a national coordinating center supported by a $7.7 million grant from the National Institutes of Health (NIH) to foster integrated research efforts.

Future Directions: Integrating Exposomics for Global Goal Attainment

Personalized Medicine and Reduced Health Inequalities (SDG 3 & SDG 10)

The ultimate vision for exposomics is the integration of an individual’s “exposomic profile” into their electronic medical records. This will enable a move beyond generalized diagnostics to highly personalized health interventions. By systematically analyzing social determinants like income and education, this approach can also help identify and address the root causes of health disparities, contributing directly to SDG 10.

An Integrated Health Paradigm

Exposomics does not replace genomics but rather complements it, providing the other half of the health equation. As noted by experts, understanding both the genetic predisposition (“genomics”) and the lifetime environmental influences (“exposomics”) is essential for creating a complete and effective paradigm for health assessment and disease prevention, thereby accelerating progress towards achieving global health and sustainability targets.

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article on exposomics connects to several Sustainable Development Goals (SDGs) by focusing on the intersection of health, environment, technology, and scientific collaboration. The primary SDGs addressed are:

• SDG 3: Good Health and Well-being

  This is the most central SDG to the article. The entire premise of exposomics is to understand and mitigate the environmental causes of disease to improve human health. The article states that 90% of diseases are thought to be caused by environmental factors and the “ultimate goal” of this research is to “turn this big bucket of individual knowledge points into practical, personalized health solutions.”

• SDG 9: Industry, Innovation, and Infrastructure

  The article highlights a significant investment in scientific research and technological innovation. It describes exposomics as an “emerging field” gaining momentum through new technologies like geospatial data analysis, mass spectrometry, and wearable devices. The mention of the National Institutes of Health (NIH) announcing a “$7.7 million grant” for the Network for Exposomics in the United States (NEXUS) directly points to investment in research and innovation infrastructure.

• SDG 11: Sustainable Cities and Communities

  The research methods described in the article have direct relevance to creating healthier and more sustainable urban environments. The use of “Geospatial data: Satellite images and social determinants of health data” to measure “location-specific exposures like air pollution and water quality” is a key tool for monitoring and improving the environmental quality of cities and communities.

• SDG 17: Partnerships for the Goals

  The article emphasizes the collaborative nature of exposomics research. It states that this field “requires researchers from various disciplines — including genetics, environmental science and data science — to work together.” The creation of NEXUS, a “national coordinating center” funded by a public institution (NIH), exemplifies a partnership designed to advance scientific knowledge for the public good.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s focus, several specific SDG targets can be identified:

• Under SDG 3: Good Health and Well-being

  • Target 3.4: By 2030, reduce by one-third premature mortality from non-communicable diseases through prevention and treatment. The article’s core mission is to understand the 90% of diseases caused by environmental factors, which are primarily non-communicable (e.g., Parkinson’s). By creating an “exposomic profile” for individuals, the research aims to enable prevention of these diseases.
  • Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination. The article directly addresses this target by describing technologies used to measure “air pollution and water quality” and “environmental chemicals” in biological samples, which are the first steps toward reducing illnesses caused by them.

• Under SDG 9: Industry, Innovation, and Infrastructure

  • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries… and substantially increase… public and private research and development spending. The article is a case study for this target, detailing a “major shift” in biomedical research, the development of new tools (“exposometer,” advanced mass spectrometry), and significant public R&D spending through the “$7.7 million grant” from the NIH.

• Under SDG 11: Sustainable Cities and Communities

  • Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality. The article’s mention of using “Geospatial data” and “Satellite images” to “measure location-specific exposures like air pollution” directly supports the monitoring component necessary to achieve this target.

• Under SDG 17: Partnerships for the Goals

  • Target 17.17: Encourage and promote effective public, public-private and civil society partnerships. The establishment of NEXUS, a “national coordinating center” funded by the public NIH and involving researchers from multiple universities (Columbia, Harvard, USC), is a clear example of an effective public partnership to advance science and health.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions or implies several specific indicators that can be used to measure progress:

• For Target 3.9 (Reduce illness from pollution)

  • Implied Indicator: Measurement of exposure to pollution. The article describes tools that serve as direct indicators of exposure, such as the use of “Mass spectrometry” to “detect thousands of markers in biological samples like blood and urine” and “Geospatial data” to “measure location-specific exposures like air pollution and water quality.”

• For Target 9.5 (Enhance scientific research)

  • Direct Indicator: Public research and development spending. The article explicitly states the NIH provided a “$7.7 million grant,” which is a quantifiable measure of R&D expenditure.
  • Implied Indicator: Development of new technologies. The mention of new tools like the “exposometer” developed at Stanford and the use of “computational models and artifical intelligence” represent progress in technological capabilities.

• For Target 11.6 (Reduce environmental impact of cities)

  • Implied Indicator: Ambient air pollution levels. The article’s reference to using “Satellite images” to measure “air pollution” points directly to the measurement of this key environmental indicator for cities.

4. Create a table with three columns titled ‘SDGs, Targets and Indicators” to present the findings from analyzing the article.

Source: upi.com