ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans

Longitudinal Analysis of the Relationship Between Social Isolation and Hypertension in Early Middle Adulthood

BACKGROUND

Most studies have used cross-sectional or limited follow-up data to evaluate the relationship between social isolation (SI) and hypertension in older populations. The objective of this analysis was to examine the relationship between longitudinal SI and hypertension in a younger population.

METHODS AND RESULTS

The present analysis used data from waves I to V of the National Longitudinal Study of Adolescent to Adult Health (1994-2018) and logistic regression models to describe the association of timing, duration, and transitional patterns of SI with hypertension in early middle adulthood. Models were adjusted for demographic variables and adolescent socioeconomic and health-related confounders. SI was higher across life stages among individuals with hypertension (adolescence: 38% versus 35%, young adulthood: 52% versus 44%, and early middle adulthood: 61% versus 52%). Individuals who were socially isolated in young adulthood or early middle adulthood had greater odds of hypertension in early middle adulthood than those who were not (odds ratio [OR], 1.30 [95% CI, 1.07-1.56]; OR, 1.42 [95% CI, 1.15-1.76], respectively). Early middle adulthood hypertension was significantly associated with persistent SI across all life stages and for those who moved into persistent SI after adolescence (OR, 1.40 [95% CI, 1.02-1.93]; OR, 1.61 [95% CI, 1.18-2.19], respectively).

CONCLUSIONS

SI in young or early middle adulthood significantly increased the odds of hypertension, as did moving into SI and the accumulation of SI across life stages. Our analysis provides insights regarding timing for effective interventions to reduce hypertension earlier in the life course, which may prevent future adverse cardiovascular-related events.

Associations between dimensions of the social environment and cardiometabolic risk factors: Systematic review and meta-analysis

Aim

The social environment (SE), including social contacts, norms and support, is an understudied element of the living environment which impacts health. We aim to comprehensively summarize the evidence on the association between the SE and risk factors of cardiometabolic disease (CMD).

Methods

We performed a systematic review and meta-analysis based on studies published in PubMed, Scopus and Web of Science Core Collection from inception to 16 February 2021. Studies that used a risk factor of CMD, e.g., HbA1c or blood pressure, as outcome and social environmental factors such as area-level deprivation or social network size as independent variables were included. Titles and abstracts were screened in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale. Data appraisal and extraction were based on the study protocol published in PROSPERO. Data were synthesized through vote counting and meta-analyses.

Results

From the 7521 records screened, 168 studies reported 1050 associations were included in this review. Four meta-analyses based on 24 associations suggested that an unfavorable social environment was associated with increased risk of cardiometabolic risk factors, with three of them being statistically significant. For example, individuals that experienced more economic and social disadvantage had a higher "CVD risk scores" (OR = 1.54, 95%CI: 1.35 to 1.84). Of the 458 associations included in the vote counting, 323 (71%) pointed towards unfavorable social environments being associated with higher CMD risk.

Conclusion

Higher economic and social disadvantage seem to contribute to unfavorable CMD risk factor profiles, while evidence for other dimensions of the social environment is limited.

Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels

The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10^-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r²  ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.

Stressful social environment and financial strain drive depressive symptoms, and reveal the effects of a FKBP5 variant and male sex, in African Americans living in Tallahassee

OBJECTIVES

The World Health Organization estimates that almost 300 million people suffer from depression worldwide. African Americans are understudied for depression-related phenotypes despite widespread racial disparities. In our study of African Americans, we integrated information on psychosocial stressors with genetic variation in order to better understand how these factors associated with depressive symptoms.

METHODS

Our research strategy combined information on financial strain and social networks with genetic data to investigate variation in symptoms of depression (CES-D scores). We collected self-report data on depressive symptoms, financial strain (difficulty paying bills) and personal social networks (a model of an individual's social environment), and we genotyped genetic variants in five genes previously implicated in depressive disorders (HTR1a, BDNF, GNB3, SLC6A4, and FKBP5) in 128 African Americans residing in Tallahassee, Florida. We tested for direct and gene-environment interactive effects of the psychosocial stressors and genetic variants on depressive symptoms.

RESULTS

Significant associations were identified between high CES-D scores and a stressful social environment (i.e., a high percentage of people in participants' social network who were a source of stress) and high financial strain. Only one genetic variant (rs1360780 in FKBP5) was significantly associated with CES-D scores and only when psychosocial stressors were included in the model; the T allele had an additive effect on depressive symptoms. Sex was also significantly associated with CES-D score in the model with psychosocial stressors and genetic variants; males had higher CES-D scores. No significant interactive effects were detected.

CONCLUSIONS

A stressful social environment and material disadvantage increase depressive symptoms in the study population. Additional associations with FKBP5 and male sex were revealed in models that included both psychosocial and genetic data. Our results suggest that incorporating psychosocial stressors may empower future genetic association studies and help clarify the biological consequences of social and financial stress.

Advancing precision public health using human genomics: examples from the field and future research opportunities

Precision public health is a relatively new field that integrates components of precision medicine, such as human genomics research, with public health concepts to help improve population health. Despite interest in advancing precision public health initiatives using human genomics research, current and future opportunities in this emerging field remain largely undescribed. To that end, we provide examples of promising opportunities and current applications of genomics research within precision public health and outline future directions within five major domains of public health: biostatistics, environmental health, epidemiology, health policy and health services, and social and behavioral science. To further extend applications of genomics within precision public health research, three key cross-cutting challenges will need to be addressed: developing policies that implement precision public health initiatives at multiple levels, improving data integration and developing more rigorous methodologies, and incorporating initiatives that address health equity. Realizing the potential to better integrate human genomics within precision public health will require transdisciplinary efforts that leverage the strengths of both precision medicine and public health.

Social and behavioral science at the forefront of genomics: Discovery, translation, and health equity

This special issue highlights the unique role that social and behavioral science has to play at the forefront of genomics. Through the introduction of papers comprising this special issue, we outline priority research areas at the nexus of genomics and the social and behavioral sciences. These include: Discovery science; clinical and community translation, and equity, including engagement and inclusion of diverse populations in genomic science. We advocate for genomic discovery that considers social context, neural, cognitive, and behavioral endophenotypes, and that is grounded in social and behavioral science research and theory. Further, the social and behavioral sciences should play a leadership role in identifying best practices for effective clinical and community translation of genomic discoveries. Finally, inclusive research that engages diverse populations is necessary for genomic discovery and translation to benefit all. We also highlight ways that genomics can be a fruitful testbed for the development and refinement of social and behavioral science theory. Indeed, an expanded ecological lens that runs from genomes to society will be required to fully understand human behavior.

Behavioral and social scientists' reflections on genomics: a systematic evaluation within the Society of Behavioral Medicine

Clinical and public health translation of genomics could be facilitated by expertise from behavioral medicine, yet genomics has not been a significant focus of the Society of Behavioral Medicine (SBM). SBM convened a working group (WG) to lead a systematic exploration of members' views on: (a) whether SBM should give a higher priority to genomic translation and (b) what efforts, if any, should be made to support this increased engagement. The WG used a stepped process over 2 years that began by gaining input from SBM leadership regarding key issues and suggestions for approach, engaging a cross section of membership to expand and record these discussions, followed by systematic qualitative analyses to inform priority action steps. Discussions with SBM leaders and members suggested that genomics was relevant to SBM, particularly for junior members. SBM members' expertise in social and behavioral theory, and implementation study designs, were viewed as highly relevant to genomic translation. Participants expressed that behavioral and social scientists should be engaged in translational genomics work, giving special attention to health disparities. Proposed action steps are aligned with a "push-pull" framework of innovation dissemination. "Push" strategies aim to reach potential adopters and included linking members with genomics expertise to those wanting to become involved and raising awareness of evidence-based genomic applications ready for implementation. "Pull" strategies aim to expand demand and included developing partnerships with genomics societies and advocating for funding, study section modifications, and training programs.

Investigating Relationships Between Hypertension, Sleep, and Cognitive Risk in an Underserved Community

Purpose

The aim of this descriptive correlational pilot study was to investigate the relationship between hypertension, sleep deprivation, and risk of Alzheimer's disease in a rural, older, underserved, and ethnically diverse cohort.

Sample

Residents (n = 52) from three independent subsidized housing units for retired farmer workers, located in a rural Florida area known as the Glades, volunteered for the study.

Methods

A quantitative descriptive approach using Pearson correlations, t-tests, and scatter plot analysis was applied to surveys and Mini-CogTM results.

Findings

About a quarter (23.1%) of the participants were identified as being at risk for cognitive impairment. Hypertension risk correlated moderately with cognitive impairment risk (r = 0.40, p = 0.01). However, in this ethnically, diverse cohort, sleep quality did not significantly influence either blood pressure or cognitive status. This is contrary to other studies that have found an increased risk of Alzheimer's disease among persons with hypertension (Carnevale, Perrotta, Lembo, & Trimarco, 2015) and insufficient sleep (Brzecka et al., 2018).

Implications

These results suggest that further investigation is needed to examine if rural living or culture moderates Alzheimer's disease risk factors of diminished sleep and hypertension. Future findings could impact the design of interventions aimed at reducing AD risk in diverse rural settings.