Pathways for advancing good work in food systems: reflecting on the good work for good food international forum

The crucial roles that workers, especially seasonal and migrant workers, play in our food systems have come under renewed attention in recent years. The coronavirus pandemic resulted in food work­ers being recognized as critical or essential workers in many countries. In 2021, this coincided with the UN International Year of Fruits and Vegetables (IYFV), highlighting the importance of horticul­tural crops to healthy lives globally. Yet, workers’ quality of life in this most labor-intensive form of food production is often disregarded, or in the case of the UN IYFV, misconstrued. The agriculture-migration nexus—on which food systems depend—remains recognized as a challenge, yet there is limited debate about how it could be ameliorated and a lack of articulation of desirable alternatives. While alternative food and peasant movements propose food system transformation and alternative labor futures based on agroecology, labor lawyers and other advocates propose regula­tion and formalization of workplace regimes to ensure fair working conditions. Most recently, a third pos­sibility has emerged from agri-tech innovators: a techno-centric future with far fewer agricultural work­ers. These three archetypes of agricultural labor futures (agroecological, formally regulated, and techno-centric) have the potential to leave food scholars and activists without a unified, coherent vision to advance. Addressing this gap, this paper reports and builds on insights harvested from the international Good Work for Good Food Forum, organized by the authors with the aim of shaping consensus on positive visions for work in food systems. About 40 scholar-activists across three continents discussed the current challenges facing food workers and crafted a collective vision for good food work. This vision is documented in the form of nine principles supported by a framework of seven enabling pathways. We conclude by em­pha­sizing the need for a people-centered incor­poration of technology and a re-valuation of food workers’ contributions to global food systems. We offer the vision as a collective platform for action to advocate for and organize with workers in food systems

The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation

While initiation of cannabis use is around 40% heritable, not much is known about the underlying genetic aetiology. Here, we meta-analysed two genome-wide association studies of initiation of cannabis use with >10000 individuals. None of the genetic variants reached genome-wide significance. We also performed a gene-based association test, which also revealed no significant effects of individual genes. Finally, we estimated that only approximately 6% of the variation in cannabis initiation is due to common genetic variants. Future genetic studies using larger sample sizes and different methodologies (including sequencing) might provide more insight in the complex genetic aetiology of cannabis use

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases