A biosocial return to race? A cautionary view for the postgenomic era

Associations of Serum Perfluoroalkyl Substances and Placental Human Chorionic Gonadotropin in Early Pregnancy, Measured in the UPSIDE Study in Rochester, New York

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are widely detected in pregnant women and associated with adverse outcomes related to impaired placental function. Human chorionic gonadotropin (hCG) is a dimeric glycoprotein hormone that can indicate placental toxicity.

OBJECTIVES

Our aim was to quantify the association of serum PFAS with placental hCG, measured as an intact molecule (hCG), as free alpha-(hCG α ) and beta-subunits (hCG β ), and as a hyperglycosylated form (h-hCG), and evaluate effect measure modification by social determinants and by fetal sex.

METHODS

Data were collected from 326 pregnant women enrolled from 2015 to 2019 in the UPSIDE study in Rochester, New York. hCG forms were normalized for gestational age at the time of blood draw in the first trimester [multiple of the median (MoM)]. Seven PFAS were measured in second-trimester maternal serum. Multivariate imputation by chained equations and inverse probability weighting were used to evaluate robustness of linear associations. PFAS mixture effects were estimated by Bayesian kernel machine regression.

RESULTS

Perfluorohexane sulfonic acid (PFHxS) [hCG β : 0.29 log MoM units per log PFHxS; 95% confidence interval (CI): 0.08, 0.51] and perfluorodecanoic acid (PFDA) (hCG: - 0.09 ; 95% CI: - 0.16 , - 0.02 ) were associated with hCG in the single chemical and mixture analyses. The PFAS mixture was negatively associated with hCG α and positively with hCG β . Subgroup analyses revealed that PFAS associations with hCG differed by maternal race/ethnicity and education. Perfluoropentanoic acid (PFPeA) was associated with hCG β only in Black participants (- 0.23 ; 95% CI: - 0.37 , - 0.09 ) and in participants with high school education or less (- 0.14 ; 95% CI: - 0.26 , - 0.02 ); conversely, perfluorononanoic acid (PFNA) was negatively associated with hCG α only in White participants (- 0.15 ; 95% CI: - 0.27 , - 0.03 ) and with hCG β only in participants with a college education or greater (- 0.19 ; 95% CI: - 0.36 , - 0.01 ). These findings were robust to testing for selection bias, confounding bias, and left truncation bias where PFAS detection frequency was < 100 % . Two associations were negative in male (and null in female) pregnancies: Perfluoroundecanoic acid (PFUnDA) with hCG α , and PFNA with h-hCG.

CONCLUSIONS

Evidence was strongest for the association between PFHxS and PFDA with hCG in all participants and for PFPeA and PFNA within subgroups defined by social determinants and fetal sex. PFAS mixture associations with hCG α and hCG β differed, suggesting subunit-specific types of toxicity and/or regulation. Future studies will evaluate the biological, clinical and public health significance of these findings. https://doi.org/10.1289/EHP12950.

The Impact of Health Care Algorithms on Racial and Ethnic Disparities : A Systematic Review

BACKGROUND

There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities.

PURPOSE

To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities.

DATA SOURCES

Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023.

STUDY SELECTION

Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms.

DATA EXTRACTION

Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension.

DATA SYNTHESIS

Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques.

LIMITATION

Results are mostly based on modeling studies and may be highly context-specific.

CONCLUSION

Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes.

PRIMARY FUNDING SOURCE

Agency for Healthcare Quality and Research.

Follow the citations: Tracing pathways of "race as biology" assumptions in medical algorithms in eGFR and spirometry

Despite overwhelming evidence to the contrary, the concept of 'race' as a biological unit continues to persist in various scientific disciplines, notably in the field of medicine. This paper explores the persistence of 'race as biology' in medical research via examining select citational practices that have perpetuated this problematic concept. Citations serve as a cornerstone in scientific literature, signifying reliability and expert affirmation. By analyzing citation threads and historical patterns, we aim to shed light on the creation and perpetuation of false scientific truths and their impact on medical research, training, and practice. We focus on two prominent examples, eGFR and Spirometry, and trace key articles' citational histories, highlighting the flawed evidence in support of racial corrections in medical assessments. The eGFR equation incorporates 'race' as a factor based on the erroneous belief that Black individuals have higher muscle mass than white individuals. Our analysis reveals that key cited sources for this belief lack robust and well-developed datasets. Similarly, Spirometry measurements incorporate racial correction factors, relying on questionable evidence dating back to the Civil War era. Citations serve as a cornerstone in scientific literature, signifying reliability and expert affirmation. They play a crucial role in shaping theoretical positions and validating data and assumed knowledge. Evaluating citation threads and key articles consistently referenced over time can reveal how falsehoods and erroneous assertions are constructed and maintained in scientific fields. This study underscores the need for critical examination of citational practices in medical research and urges a shift toward a more cautious approach when citing sources that support 'race as biology.' The paper calls for a reevaluation of pedagogical approaches and assigned readings in medical education to prioritize an anti-racist perspective in future research endeavors.

Embedded racism: Inequitable niche construction as a neglected evolutionary process affecting health

Racial health disparities are a pervasive feature of modern experience and structural racism is increasingly recognized as a public health crisis. Yet evolutionary medicine has not adequately addressed the racialization of health and disease, particularly the systematic embedding of social biases in biological processes leading to disparate health outcomes delineated by socially defined race. In contrast to the sheer dominance of medical publications which still assume genetic 'race' and omit mention of its social construction, we present an alternative biological framework of racialized health. We explore the unifying evolutionary-ecological principle of niche construction as it offers critical insights on internal and external biological and behavioral feedback processes environments at every level of the organization. We Integrate insights of niche construction theory in the context of human evolutionary and social history and phenotype-genotype modification, exposing the extent to which racism is an evolutionary mismatch underlying inequitable disparities in disease. We then apply ecological models of niche exclusion and exploitation to institutional and interpersonal racial constructions of population and individual health and demonstrate how discriminatory processes of health and harm apply to evolutionarily relevant disease classes and life-history processes in which socially defined race is poorly understood and evaluated. Ultimately, we call for evolutionary and biomedical scholars to recognize the salience of racism as a pathogenic process biasing health outcomes studied across disciplines and to redress the neglect of focus on research and application related to this crucial issue.

An integrative framework and recommendations for the study of DNA methylation in the context of race and ethnicity

Human social epigenomics research is critical to elucidate the intersection of social and genetic influences underlying racial and ethnic differences in health and development. However, this field faces major challenges in both methodology and interpretation with regard to disentangling confounded social and biological aspects of race and ethnicity. To address these challenges, we discuss how these constructs have been approached in the past and how to move forward in studying DNA methylation (DNAm), one of the best-characterized epigenetic marks in humans, in a responsible and appropriately nuanced manner. We highlight self-reported racial and ethnic identity as the primary measure in this field, and discuss its implications in DNAm research. Racial and ethnic identity reflects the biological embedding of an individual's sociocultural experience and environmental exposures in combination with the underlying genetic architecture of the human population (i.e., genetic ancestry). Our integrative framework demonstrates how to examine DNAm in the context of race and ethnicity, while considering both intrinsic factors-including genetic ancestry-and extrinsic factors-including structural and sociocultural environment and developmental niches-when focusing on early-life experience. We reviewed DNAm research in relation to health disparities given its relevance to race and ethnicity as social constructs. Here, we provide recommendations for the study of DNAm addressing racial and ethnic differences, such as explicitly acknowledging the self-reported nature of racial and ethnic identity, empirically examining the effects of genetic variants and accounting for genetic ancestry, and investigating race-related and culturally regulated environmental exposures and experiences.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44155-023-00039-z.

An epigenome-wide association study of insulin resistance in African Americans

Background

African Americans have a high risk for type 2 diabetes (T2D) and insulin resistance. Studies among other population groups have identified DNA methylation loci associated with insulin resistance, but data in African Americans are lacking. Using DNA methylation profiles of blood samples obtained from the Illumina Infinium® HumanMethylation450 BeadChip, we performed an epigenome-wide association study to identify DNA methylation loci associated with insulin resistance among 136 non-diabetic, unrelated African American men (mean age 41.6 years) from the Howard University Family Study.

Results

We identified three differentially methylated positions (DMPs) for homeostatic model assessment of insulin resistance (HOMA-IR) at 5% FDR. One DMP (cg14013695, HOXA5) is a known locus among Mexican Americans, while the other two DMPs are novel—cg00456326 (OSR1; beta = 0.027) and cg20259981 (ST18; beta = 0.010). Although the cg00456326 DMP is novel, the OSR1 gene has previously been found associated with both insulin resistance and T2D in Europeans. The genes HOXA5 and ST18 have been implicated in biological processes relevant to insulin resistance. Differential methylation at the significant HOXA5 and OSR1 DMPs is associated with differences in gene expression in the iMETHYL database. Analysis of differentially methylated regions (DMRs) did not identify any epigenome-wide DMRs for HOMA-IR. We tested transferability of HOMA-IR associated DMPs from five previous EWAS in Mexican Americans, Indian Asians, Europeans, and European ancestry Americans. Out of the 730 previously reported HOMA-IR DMPs, 47 (6.4%) were associated with HOMA-IR in this cohort of African Americans.

Conclusions

The findings from our study suggest substantial differences in DNA methylation patterns associated with insulin resistance across populations. Two of the DMPs we identified in African Americans have not been reported in other populations, and we found low transferability of HOMA-IR DMPs reported in other populations in African Americans. More work in African-ancestry populations is needed to confirm our findings as well as functional analyses to understand how such DNA methylation alterations contribute to T2D pathology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01309-4.