Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment.

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement.

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

Perspectives of peripartum people on opportunities for personal and collective action to reduce exposure to everyday chemicals: Focus groups to inform exposure report-back.

Participants in biomonitoring studies who receive personal exposure reports seek information to reduce exposures. Many chemical exposures are driven by systems-level policies rather than individual actions; therefore, change requires engagement in collective action. Participants' perceptions of collective action and use of report-back to support engagement remain unclear. We conducted virtual focus groups during summer 2020 in a diverse group of peripartum people from cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program (N = 18). We assessed baseline exposure and collective action experience, and report-back preferences. Participants were motivated to protect the health of their families and communities despite significant time and cognitive burdens. They requested time-conscious tactics and accessible information to enable action to reduce individual and collective exposures. Participant input informed the design of digital report-back in the cohorts. This study highlights opportunities to shift responsibility from individuals to policymakers to reduce chemical exposures at the systems level.

Heritability of quantitative autism spectrum traits in adults: A family-based study.

Autism spectrum disorder (ASD) comprises a multi-dimensional set of quantitative behavioral traits expressed along a continuum in autistic and neurotypical individuals. ASD diagnosis-a dichotomous trait-is known to be highly heritable and has been used as the phenotype for most ASD genetic studies. But less is known about the heritability of autism spectrum quantitative traits, especially in adults, an important prerequisite for gene discovery. We sought to measure the heritability of many autism-relevant quantitative traits in adults high in autism spectrum traits and their extended family members. Among adults high in autism spectrum traits (n = 158) and their extended family members (n = 245), we calculated univariate and bivariate heritability estimates for 19 autism spectrum traits across several behavioral domains. We found nearly all tested autism spectrum quantitative traits to be significantly heritable (h2  = 0.24-0.79), including overall ASD traits, restricted repetitive behaviors, broader autism phenotype traits, social anxiety, and executive functioning. The degree of shared heritability varied based on method and specificity of the assessment measure. We found high shared heritability for the self-report measures and for most of the informant-report measures, with little shared heritability among performance-based cognition tasks. These findings suggest that many autism spectrum quantitative traits would be good, feasible candidates for future genetics studies, allowing for an increase in the power of autism gene discovery. Our findings suggest that the degree of shared heritability between traits depends on the assessment method (self-report vs. informant-report vs. performance-based tasks), as well as trait-specificity. LAY SUMMARY: We found that the scores from questionnaires and tasks measuring different types of behaviors and abilities related to autism spectrum disorder (ASD) were heritable (strongly influenced by gene variants passed down through a family) among autistic adults and their family members. These findings mean that these scores can be used in future studies interested in identifying specific genes and gene variants that are associated with different behaviors and abilities related with ASD.