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Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world’s population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N= 142,646) and the Million Veteran Program (MVP-MD; N= 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.

Lipedema is a common disorder characterized by excessive deposition of subcutaneous adipose tissue (SAT) in the legs, hips, and buttocks, mainly occurring in adult women. Although it appears to be heritable, no specific genes have yet been identified. To identify potential genetic risk factors for lipedema, we used bioelectrical impedance analysis and anthropometric data from the UK Biobank to identify women with and without a lipedema phenotype. Specifically, we identified women with both a high percentage of fat in the lower limbs and a relatively small waist, adjusting for hip circumference. We performed a genome-wide association study (GWAS) for this phenotype, and performed multiple sensitivity GWAS. In an independent case/control study of lipedema based on strict clinical criteria, we attempted to replicate our top hits. We identified 18 significant loci (p< 5 × 10−9), several of which have previously been identified in GWAS of waist-to-hip ratio with larger effects in women. Two loci (VEGFAand GRB14-COBLL1) were significantly associated with lipedema in the independent replication study. Follow-up analyses suggest an enrichment of genes expressed in blood vessels and adipose tissue, among other tissues. Our findings provide a starting point towards better understanding the genetic and physiological basis of lipedema.

BackgroundThe biological consequences of stress from the social environment pattern health outcomes. This study investigated whether social stress is prospectively associated with fracture incidence among racially and ethnically diverse, postmenopausal women.MethodsData from 160 709 postmenopausal women in the Women’s Health Initiative was analysed using Cox proportional hazards regression models to examine prospective associations of social stress with time to total and hip fracture incidence. Self-reported questionnaires measuring social strain, social functioning and social support were used to assess social stress.ResultsAge and race/ethnicity modified associations between social stress and total and hip fractures. HRs for the associations between higher social support (indicating lower social stress) and total fractures among those age 50–59 years were 0.92 (95% CI: 0.90 to 0.94); HR=0.94 (95% CI: 0.93 to 0.95) for those age 60–69 years and HR=0.96 (95% CI: 0.95 to 0.98) for those age 70–79 years. Higher social strain was associated with greater hip fracture incidence among Native American women (HR=1.84, 95% CI: 1.10 to 3.10), Asian women (HR=1.37, 95% CI: 1.01 to 1.86) and white women (HR=1.04, 95% CI: 1.01 to 1.08).ConclusionIdentifying population patterns of fracture incidence as biological expressions of social environments reveals how race/ethnic specific social environmental factors influence disparities in fractures.

ABSTRACTEducation intervention effectiveness to improve bed net care and repair knowledge or practices is unclear. To assess intervention effectiveness, we systematically reviewed eight peer-reviewed literature databases and 16 malaria organizations (PROSPERO protocol CRD42019123932) using pre-specified combinations of ‘education intervention’, ‘mosquito net’, and ‘malaria’ search terms. Data were abstracted for 29 of 43 studies meeting inclusion criteria, of which 16 studies included education as amain focus. Of these 16, there was evidence of intervention effectiveness among half of the studies, which reported improvements in knowledge or practices, while four had mixed results, and four had unclear results. Overall there is no clear conclusion regarding the effectiveness of education interventions to improve net care and repair, though some instructional methods suggest more success than others. Interventions used combinations of instructional methods; passive mass education (6), active mass education (12), and interpersonal methods (8). Interventions combining mass and interpersonal methods resulted in positive improvements (four positive, one mixed). We found no evidence that interventions grounded in health behavior theory achieved more positive results than those not grounded in theory, potentially because net care education was typically asecondary objective. Of 289 gray literature results, 286 (99%) were net distribution reports from Against Malaria Foundation describing 136 distributions; eighty of which (58.8%) mentioned no education related to net care and repair. We found lack of involvement of experts in education among included interventions. Involving trained instructors with expertise in education theory and instructional strategies may improve instruction quality to yield more effective interventions.

Various studies have identified single-nucleotide polymorphisms (SNPs) associated with nonalcoholic fatty liver disease (NAFLD) and related traits, including ones located in or near the LYPLAL1, GCKR, PPP1R3B, TM6SF2, MBOAT7, and PNPLA3 genes. However, these SNPs were identified primarily in populations of European ancestry. This study examined the associations of these previously identified SNPs with hepatic steatosis in a sample of Mexican-origin adults living in Southern Arizona.

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Genome-wide Association Studies (GWAS) have resulted in many discovered risk variants for several obesity-related traits. However, before clinical relevance of these discoveries can be achieved, molecular or physiological mechanisms of these risk variants needs to be discovered. One strategy is to perform data mining of phenotypically-rich data sources such as those present in dbGAP (database of Genotypes and Phenotypes) for hypothesis generation. Here we propose a technique that combines the power of existing Bayesian Network (BN) learning algorithms with the statistical rigour of Structural Equation Modelling (SEM) to produce an overall phenotypic network discovery system with optimal properties. We illustrate our method using the analysis of a candidate SNP data set from the AMERICO sample, a multi-ethnic cross-sectional cohort of roughly 300 children with detailed obesity-related phenotypes. We demonstrate our approach by showing genetic mechanisms for three obesity-related SNPs.