Loneliness and perceived social support in pregnancy and early postpartum of mothers living with HIV in Ontario, Canada.

The HIV Mothering Study (n = 72) was a prospective, observational, cohort study exploring psychosocial experiences and needs of WLWHIV in pregnancy and postpartum. We performed quantitative analysis of determinants of loneliness (UCLA Loneliness Scale) and lower perceived social support (SS) (Medical Outcomes Study-Social Support Survey). The hypothesized determinants included: age, years with HIV, racism (Everyday Discrimination Scale), depression (Edinburgh Postnatal Depression Scale [EPDS]), nadir CD4 (<200 cells/µL), tertiary vs. community HIV care, and marital status. The median age was 33 (IQR = 30-37); 65.3% were African/Caribbean/Black. Multivariable analyses revealed associations between marital status and perceived social support (ß = -16.48, p < 0.0001), and this association was also seen with change over time (p = 0.02). Variables associated with SS that did not change over time were: income, EDS racism, EPDS score. Significant associations with loneliness were seen with the same variables associated with SS. Variables associated with loneliness that also changed over time were: EDS Racism (ß = 0.22, p = 0.0005, and over time p = 0.003), and EPDS score (ß = 0.74, p < 0.0001), and over time (p = 0.0211). Variables associated with loneliness but that did not change over time were: marital status and income. This analysis provides clinicians with prenatal risk factors which may be associated with increase loneliness and lower SS during pregnancy and postpartum: marital status, income, racism and depression.

Gain-of-function variants in the melanocortin 4 receptor gene confer susceptibility to binge eating disorder in subjects with obesity: a systematic review and meta-analysis.

The association between coding variants in the melanocortin 4 receptor gene (MC4R) and binge eating disorder (BED) in patients with obesity is controversial. Two independent reviewers systematically searched MEDLINE, Embase, PsycINFO, BIOSIS Previews, Web of Science Core Collection and Google Scholar up to February 2018, using terms describing the MC4R gene and BED. Six of 103 identified references were included. Studies examined associations between at least one coding variant/mutation in MC4R and BED and screened for BED as per the Diagnostic and Statistical Manual of Mental Disorders. Risk of bias was assessed using a modified version of the Q-Genie tool, and overall quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation guidance. Meta-analysis was conducted via logistic regression models. A positive association between gain-of-function (GOF) variants in the MC4R and BED was observed (odds ratio [OR] = 3.05; 95% confidence interval [CI]: 1.82, 5.04; p = 1.7 × 10-5 ), while no association was detected between loss-of-function (LOF) mutations and BED (OR = 1.50; 95% CI: 0.73, 2.96; p = 0.25). Similar results were found after accounting for study quality (GOF variants: OR = 3.15; 95% CI: 1.76, 5.66; p = 1.1 × 10-4 ; LOF mutations: OR = 1.50; 95% CI: 0.73, 2.97; p = 0.25). Our systematic review and meta-analysis provides evidence that GOF variants as opposed to LOF mutations in MC4R are associated with BED in subjects with obesity.

Ethnic and population differences in the genetic predisposition to human obesity.

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

Empirical evaluation of the Q-Genie tool: a protocol for assessment of effectiveness.

INTRODUCTION: Meta-analyses of genetic association studies are affected by biases and quality shortcomings of the individual studies. We previously developed and validated a risk of bias tool for use in systematic reviews of genetic association studies. The present study describes a larger empirical evaluation of the Q-Genie tool. METHODS AND ANALYSIS: MEDLINE, Embase, Global Health and the Human Genome Epidemiology Network will be searched for published meta-analyses of genetic association studies. Twelve reviewers in pairs will apply the Q-Genie tool to all studies in included meta-analyses. The Q-Genie will then be evaluated on its ability to (i) increase precision after exclusion of low quality studies, (ii) decrease heterogeneity after exclusion of low quality studies and (iii) good agreement with experts on quality rating by Q-Genie. A qualitative assessment of the tool will also be conducted using structured questionnaires. DISCUSSION: This systematic review will quantitatively and qualitatively assess the Q-Genie's ability to identify poor quality genetic association studies. This information will inform the selection of studies for inclusion in meta-analyses, conduct sensitivity analyses and perform metaregression. Results of this study will strengthen our confidence in estimates of the effect of a gene on an outcome from meta-analyses, ultimately bringing us closer to deliver on the promise of personalised medicine. ETHICS AND DISSEMINATION: An updated Q-Genie tool will be made available from the Population Genomics Program website and the results will be submitted for a peer-reviewed publication.

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer.

Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin α (PTMA), 14-3-3ζ and 14-3-3σ was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic-pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment.