Associations between a Polymorphism in the Pleiotropic GCKR and Age-Related Phenotypes: The HALCyon Programme

Background

The glucokinase regulatory protein encoded by GCKR plays an important role in glucose metabolism and a single nucleotide polymorphism (SNP) rs1260326 (P446L) in the gene has been associated with several age-related biomarkers, including triglycerides, glucose, insulin and apolipoproteins. However, associations between SNPs in the gene and other ageing phenotypes such as cognitive and physical capability have not been reported.

Methods

As part of the Healthy Ageing across the Life Course (HALCyon) collaborative research programme, men and women from five UK cohorts aged between 44 and 90+ years were genotyped for rs1260326. Meta-analysis was used to pool within-study genotypic associations between the SNP and several age-related phenotypes, including body mass index (BMI), blood lipid levels, lung function, and cognitive and physical capability.

Results

We confirm the associations between the minor allele of the SNP and higher triglycerides and lower glucose levels. We also observed a triglyceride-independent association between the minor allele and lower BMI (pooled beta on z-score = −0.04, p-value = 0.0001, n = 16,251). Furthermore, there was some evidence for gene-environment interactions, including physical activity attenuating the effects on triglycerides. However, no associations were observed with measures of cognitive and physical capability.

Conclusion

Findings from middle-aged to older adults confirm associations between rs1260326 GCKR and triglycerides and glucose, suggest possible gene-environment interactions, but do not provide evidence that its relevance extends to cognitive and physical capability.     

Gene-gene and gene-environment interactions involving HLA-DRB1, PTPN22, and smoking in two subsets of rheumatoid arthritis

Gene-gene and gene-environment interactions are key features in the development of rheumatoid arthritis (RA) and other complex diseases. The aim of this study was to use and compare three different definitions of interaction between the two major genetic risk factors of RA--the HLA-DRB1 shared epitope (SE) alleles and the PTPN22 R620W allele--in three large case-control studies: the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, the North American RA Consortium (NARAC) study, and the Dutch Leiden Early Arthritis Clinic study (in total, 1,977 cases and 2,405 controls). The EIRA study was also used to analyze interactions between smoking and the two genes. "Interaction" was defined either as a departure from additivity, as interaction in a multiplicative model, or in terms of linkage disequilibrium--for example, deviation from independence of penetrance of two unlinked loci. Consistent interaction, defined as departure from additivity, between HLA-DRB1 SE alleles and the A allele of PTPN22 R620W was seen in all three studies regarding anti-CCP-positive RA. Testing for multiplicative interactions demonstrated an interaction between the two genes only when the three studies were pooled. The linkage disequilibrium approach indicated a gene-gene interaction in EIRA and NARAC, as well as in the pooled analysis. No interaction was seen between smoking and PTPN22 R620W. A new pattern of interactions is described between the two major known genetic risk factors and the major environmental risk factor concerning the risk of developing anti-CCP-positive RA. The data extend the basis for a pathogenetic hypothesis for RA involving genetic and environmental factors. The study also raises and illustrates principal questions concerning ways to define interactions in complex diseases.     

Risk Factors for Asthma-Related Healthcare Use: Longitudinal Analysis Using the NHI Claims Database in a Korean Asthma Cohort

Background

Though insurance claims data are useful for researching asthma, they have important limitations, such as a diagnostic inaccuracy and a lack of clinical information. To overcome these drawbacks, we used the novel method by merging the clinical data from our asthma cohort with the National Health Insurance (NHI) claims data.

Methods and Results

Longitudinal analysis of asthma-related healthcare use from the NHI claims database, merged with data of 736 patients registered in a Korean asthma cohort, was conducted for three consecutive years from registration of the cohort. Asthma-related asthma healthcare referred to outpatient and emergency department visits, hospitalizations, and the use of systemic corticosteroids. Univariate and multivariate logistic regression analysis was used to evaluate risk factors for asthma-related healthcare. Over three years after enrollment, many patients changed from tertiary to primary/secondary hospitals with a lack of maintenance of inhaled corticosteroid-based controllers. An independent risk factor for emergency visits was a previous history of asthma exacerbation. In hospitalizations, old age and Asthma Control Test (ACT) score variability were independent risk factors. An independent risk factor for per person cumulative duration of systemic corticosteroids was the FEV₁ (Forced expiratory volume in one second)%. The use of systemic corticosteroids was independently associated with being female, the FEV₁%, and ACT score variability.

Conclusion

We found that old age, being female, long-standing asthma, a low FEV₁%, asthma brittleness, asthma drug compliance, and a history of asthma exacerbation were independent risk factors for increased asthma-related healthcare use in Korea.     

Adjudicated Morbidity and Mortality Outcomes by Age among Individuals with HIV Infection on Suppressive Antiretroviral Therapy

Background

Non-AIDS conditions such as cardiovascular disease and non-AIDS defining cancers dominate causes of morbidity and mortality among persons with HIV on suppressive combination antiretroviral therapy. Accurate estimates of disease incidence and of risk factors for these conditions are important in planning preventative efforts.

Methods

With use of medical records, serious non-AIDS events, AIDS events, and causes of death were adjudicated using pre-specified criteria by an Endpoint Review Committee in two large international trials. Rates of serious non-AIDS which include cardiovascular disease, end-stage renal disease, decompensated liver disease, and non-AIDS cancer, and other serious (grade 4) adverse events were determined, overall and by age, over a median follow-up of 4.3 years for 3,570 participants with CD4⁺ cell count ≥300 cells/mm³ who were taking antiretroviral therapy and had an HIV RNA level ≤500 copies/mL. Cox models were used to examine the effect of age and other baseline factors on risk of a composite outcome of all-cause mortality, AIDS, or serious non-AIDS.

Results

Five-year Kaplan-Meier estimates of the composite outcome, overall and by age were 8.3% (overall), 3.6% (<40), 8.7% (40–49) and 16.1% (≥50), respectively (p<0.001). In addition to age, smoking and higher levels of interleukin-6 and D-dimer were significant predictors of the composite outcome. The composite outcome was dominated by serious non-AIDS events (overall 65% of 277 participants with a composite event). Most serious non-AIDS events were due to cardiovascular disease and non-AIDS cancers.

Conclusions

To date, few large studies have carefully collected data on serious non-AIDS outcomes. Thus, reliable estimates of event rates are scarce. Data cited here, from a geographically diverse cohort, will be useful for planning studies of interventions aimed at reducing rates of serious non-AIDS events among people with HIV.     

Safety evaluation of the single-dose Ad26.COV2.S vaccine among healthcare workers in the Sisonke study in South Africa: A phase 3b implementation trial

BackgroundReal-world evaluation of the safety profile of vaccines after licensure is crucial to accurately characterise safety beyond clinical trials, support continued use, and thereby improve public confidence. The Sisonke study aimed to assess the safety and effectiveness of the Janssen Ad26.COV2.S vaccine among healthcare workers (HCWs) in South Africa. Here, we present the safety data.Methods and findingsIn this open-label phase 3b implementation study among all eligible HCWs in South Africa registered in the national Electronic Vaccination Data System (EVDS), we monitored adverse events (AEs) at vaccination sites through self-reporting triggered by text messages after vaccination, healthcare provider reports, and active case finding. The frequency and incidence rate of non-serious and serious AEs were evaluated from the day of first vaccination (17 February 2021) until 28 days after the final vaccination in the study (15 June 2021). COVID-19 breakthrough infections, hospitalisations, and deaths were ascertained via linkage of the electronic vaccination register with existing national databases. Among 477,234 participants, 10,279 AEs were reported, of which 138 (1.3%) were serious AEs (SAEs) or AEs of special interest. Women reported more AEs than men (2.3% versus 1.6%). AE reports decreased with increasing age (3.2% for age 18–30 years, 2.1% for age 31–45 years, 1.8% for age 46–55 years, and 1.5% for age > 55 years). Participants with previous COVID-19 infection reported slightly more AEs (2.6% versus 2.1%). The most common reactogenicity events were headache (n = 4,923) and body aches (n = 4,483), followed by injection site pain (n = 2,767) and fever (n = 2,731), and most occurred within 48 hours of vaccination. Two cases of thrombosis with thrombocytopenia syndrome and 4 cases of Guillain-Barré Syndrome were reported post-vaccination. Most SAEs and AEs of special interest (n = 138) occurred at lower than the expected population rates. Vascular (n = 37; 39.1/100,000 person-years) and nervous system disorders (n = 31; 31.7/100,000 person-years), immune system disorders (n = 24; 24.3/100,000 person-years), and infections and infestations (n = 19; 20.1/100,000 person-years) were the most common reported SAE categories. A limitation of the study was the single-arm design, with limited routinely collected morbidity comparator data in the study setting.ConclusionsWe observed similar patterns of AEs as in phase 3 trials. AEs were mostly expected reactogenicity signs and symptoms. Furthermore, most SAEs occurred below expected rates. The single-dose Ad26.COV2.S vaccine demonstrated an acceptable safety profile, supporting the continued use of this vaccine in this setting.Trial registrationClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT04838795","term_id":"NCT04838795"}}NCT04838795; Pan African Clinical Trials Registry PACTR202102855526180.

Saimbarashe Takuva, Azwi Takalani, and colleagues investigate the frequency and incidence of adverse events reported after receipt of a single dose of the Ad26.COV2.S COVID-19 vaccine among health care workers in South Africa.     

Adherence at 2 years with distribution of essential medicines at no charge: The CLEAN Meds randomized clinical trial

BackgroundAdherence to medicines is low for a variety of reasons, including the cost borne by patients. Some jurisdictions publicly fund medicines for the general population, but many jurisdictions do not, and such policies are contentious. To our knowledge, no trials studying free access to a wide range of medicines have been conducted.Methods and findingsWe randomly assigned 786 primary care patients who reported not taking medicines due to cost between June 1, 2016 and April 28, 2017 to either free distribution of essential medicines (n = 395) or to usual medicine access (n = 391). The trial was conducted in Ontario, Canada, where hospital care and physician services are publicly funded for the general population but medicines are not. The trial population was mostly female (56%), younger than 65 years (83%), white (66%), and had a low income from wages as the primary source (56%). The primary outcome was medicine adherence after 2 years. Secondary outcomes included control of diabetes, blood pressure, and low-density lipoprotein (LDL) cholesterol in patients taking relevant treatments and healthcare costs over 2 years. Adherence to all appropriate prescribed medicines was 38.7% in the free distribution group and 28.6% in the usual access group after 2 years (absolute difference 10.1%; 95% confidence interval (CI) 3.3 to 16.9, p = 0.004). There were no statistically significant differences in control of diabetes (hemoglobin A1c 0.27; 95% CI −0.25 to 0.79, p = 0.302), systolic blood pressure (−3.9; 95% CI −9.9 to 2.2, p = 0.210), or LDL cholesterol (0.26; 95% CI −0.08 to 0.60, p = 0.130) based on available data. Total healthcare costs over 2 years were lower with free distribution (difference in median CAN$1,117; 95% CI CAN$445 to CAN$1,778, p = 0.006). In the free distribution group, 51 participants experienced a serious adverse event, while 68 participants in the usual access group experienced a serious adverse event (p = 0.091). Participants were not blinded, and some outcomes depended on participant reports.ConclusionsIn this study, we observed that free distribution of essential medicines to patients with cost-related nonadherence substantially increased adherence, did not affect surrogate health outcomes, and reduced total healthcare costs over 2 years.Trial registrationClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT02744963","term_id":"NCT02744963"}}NCT02744963.     

Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer

Genome-wide association studies (GWAS) explore the genetic causes of complex diseases. However, classical approaches ignore the biological context of the genetic variants and genes under study. To address this shortcoming, one can use biological networks, which model functional relationships, to search for functionally related susceptibility loci. Many such network methods exist, each arising from different mathematical frameworks, pre-processing steps, and assumptions about the network properties of the susceptibility mechanism. Unsurprisingly, this results in disparate solutions. To explore how to exploit these heterogeneous approaches, we selected six network methods and applied them to GENESIS, a nationwide French study on familial breast cancer. First, we verified that network methods recovered more interpretable results than a standard GWAS. We addressed the heterogeneity of their solutions by studying their overlap, computing what we called the consensus. The key gene in this consensus solution was COPS5, a gene related to multiple cancer hallmarks. Another issue we observed was that network methods were unstable, selecting very different genes on different subsamples of GENESIS. Therefore, we proposed a stable consensus solution formed by the 68 genes most consistently selected across multiple subsamples. This solution was also enriched in genes known to be associated with breast cancer susceptibility (BLM, CASP8, CASP10, DNAJC1, FGFR2, MRPS30, and SLC4A7, P-value = 3 × 10⁻⁴). The most connected gene was CUL3, a regulator of several genes linked to cancer progression. Lastly, we evaluated the biases of each method and the impact of their parameters on the outcome. In general, network methods preferred highly connected genes, even after random rewirings that stripped the connections of any biological meaning. In conclusion, we present the advantages of network-guided GWAS, characterize their shortcomings, and provide strategies to address them. To compute the consensus networks, implementations of all six methods are available at https://github.com/hclimente/gwas-tools.