Self-reported oral health among a community sample of people experiencing social and health inequities: Cross-sectional findings from a study to enhance equity in primary healthcare settings

Objective: To describe the self-reported oral health issues among a community sample of primary care clients experiencing socioeconomic disadvantages. Methods: As part of a larger mixed-methods, multiple case study evaluating an equity-oriented primary healthcare intervention, we examined the oral health of a sample of 567 people receiving care at four clinics that serve marginalised populations in two Canadian provinces. Data collected included self-rated oral health and experiences accessing and receiving healthcare, standard self-report measures of health and quality of life, and sociodemographic information. Results: The prevalence of self-rated poor oral health was high, with almost half (46.3%) of the participants reporting poor or fair oral health. Significant relationships were observed between poor oral health and vulnerabilities related to mental health, trauma and housing instability. Our findings suggest that the oral health of some Canadian populations may be dramatically worse than what is reported in existing population health surveys. Conclusions: Our findings reinforce the importance of addressing oral health as part of health equity strategies. The health and oral health issues experienced by this client cohort highlight the need for interdisciplinary, team-based care that can address the intersections among people\u27s health status, oral health and social issues

Income inequality, gene expression, and brain maturation during adolescence

Income inequality is associated with poor health and social outcomes. Negative social comparisons and competition may involve the hypothalamic-pituitary-adrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes in underlying some of these complex inter-relationships. Here we investigate brain maturation, indexed by age-related decreases in cortical thickness, in adolescents living in neighborhoods with differing levels of income inequality and household income. We examine whether inter-regional variations relate to those in glucocorticoid receptor (HPA) and androgen receptor (HPG) gene expression. For each sex, we used a median split of income inequality and household income (income-to-needs ratio) to create four subgroups. In female adolescents, the high-inequality low-income group displayed the greatest age-related decreases in cortical thickness. In this group, expression of glucocorticoid and androgen receptor genes explained the most variance in these age-related decreases in thickness across the cortex. We speculate that female adolescents living in high-inequality neighborhoods and low-income households may experience greater HPA and HPG activity, leading to steeper decreases in cortical thickness with age

Establishing an ethics and governance framework for access to and linkage of electronic health data for research projects.

Objectives To develop an ethics and governance framework for the National Centre for Healthy Ageing (NCHA) data platform that supports: streamlined access to data for research; transfer of data into secure data environments; linkage with a range of external data sources and incorporation of a variety of data types. Approach The NCHA data platform is bringing together Electronic Health Data across an entire region for health service and clinical research. Methods used to establish the framework include: review of existing national (Australian Institute of Health and Welfare’s data governance framework) and international (Guiding principles from ISO/IEC 385051:2017) frameworks, stakeholder engagement and early piloting through use cases. End-users and executive staff (clinical, research and legal) were consulted to ensure compliance and streamlining with existing processes. A data access governance committee was formed with expertise in data access, linkage of large health data sets, ethics, health data privacy and legal policy. Results Data governance frameworks and policies from established state registries, large clinical trials and health data sharing and linkage centres (n=7) were reviewed and a summary was presented to the committee.  An existing data access and sharing agreement and principles was chosen as a template based on existing stakeholder collaborations and relevance to the two NCHA institutes (Monash University and Peninsula Health). The draft agreement and principles were modified and piloted for data access use cases (n=6). Feedback from researchers (n=3) was used to refine the framework. The committee identified that additional frameworks, such as those outlined by the Centre for Victorian Data Linkages, will be required to accommodate future data sharing and linkage activities with industry and government. Conclusion Our work highlighted the importance of developing a robust governance framework with the ability to incorporate a range of data, that was acceptable to end-users and had sufficient flexibility to incorporate future yet to be identified data types. Ongoing work will expand the framework to include additional data linkage activities

Developing a linked electronic health record derived data platform to support research into healthy ageing

Introduction Digitalisation of Electronic Health Record (EHR) data has created unique opportunities for research. However, these data are routinely collected for operational purposes and so are not curated to the standard required for research. Harnessing such routine data at large scale allows efficient and long-term epidemiological and health services research. Objectives To describe the establishment a linked EHR derived data platform in the National Centre for Healthy Ageing, Melbourne, Australia, aimed at enabling research targeting national health priority areas in ageing. Methods Our approach incorporated: data validation, curation and warehousing to ensure quality and completeness; end-user engagement and consensus on the platform content; implementation of an artificial intelligence (AI) pipeline for extraction of text-based data items; early consumer involvement; and implementation of routine collection of patient reported outcome measures, in a multisite public health service. Results Data for a cohort of >800,000 patients collected over a 10-year period have been curated within the platform's research data warehouse. So far 117 items have been identified as suitable for inclusion, from 11 research relevant datasets held within the health service EHR systems. Data access, extraction and release processes, guided by the Five Safes Framework, are being tested through project use-cases. A natural language processing (NLP) pipeline has been implemented and a framework for the routine collection and incorporation of patient reported outcome measures developed. Conclusions We highlight the importance of establishing comprehensive processes for the foundations of a data platform utilising routine data not collected for research purposes. These robust foundations will facilitate future expansion through linkages to other datasets for the efficient and cost-effective study of health related to ageing at a large scale

The National Centre for Healthy Ageing data platform: establishing an Electronic Health Record derived linked geographic cohort.

Objectives Electronic Health Record (EHR) data have created unique opportunities for research. However, these data are: not curated, siloed and poorly integrated. We describe linkage of EHR data from an entire health service with government datasets to establish a linked geographic cohort within the Australian National Centre for Healthy Ageing (NCHA). Approach Research suitable EHR items were identified from Peninsula Health (NCHA partner) data systems based on: published research, availability and quality. Items underwent end-user Delphi processes to identify core research items (consensus=70%). Approvals were obtained from the Australian Institute of Health and Welfare (AIHW) for linkage with: Medicare, medication dispensings, Aged Care and death registry data through the AIHW spine, created using identifiers from the Medicare Consumer Directory (MCD); and from the Centre for Victorian Data Linkage for linkage to state-wide hospital data. Identifiers for local residents aged ≥60 years who attended Peninsula Health were submitted for probabilistic data linkage. Results Delphi participants included 10 researchers from 8 fields/departments and 13 clinicians from 11 clinical areas. To date 7 of the 11 datasets have been reviewed. N=107 potentially suitable data items were identified and 96 gained consensus for inclusion in the core dataset. Of the 49,767 Health Service users (episodes: Jan 2010-Dec May 2021) submitted for linkage, 98.4% were successfully linked to the MCD (Median age 72.2 years, 52.2% female, 1.8% regional residence). An additional 172,290 individuals living within the geographic region but not contained within the EHR dataset were identified in the MCD for linkage to the government datasets. Linkage accuracy was impacted by inaccurate/incomplete address fields (~30%) and lack of adherence to naming conventions within the EHR data. Conclusion Linking with EHR data is complex. Having an established EHR research dataset will improve the feasibility of data linkage and potential for future expansion of linkages within the NCHA. Once merged, the data will be used to underpin a range of research activities related to ageing and dementia

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.publishedVersio

Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis

Background: Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. Methods: Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. Results: IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different. Conclusions: We found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions.publishedVersio

Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa

Anorexia nervosa (AN) is a heritable eating disorder (50–60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the “signal by MST1” pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.publishedVersio