https://link.springer.com/content/pdf/10.1007/s10096-021-04264-9.pdf

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Abstract: “It is commonly assumed that cities are detrimental to mental health. However, the evidence remains inconsistent and at most, makes the case for differences between rural and urban environments as a whole. Here, we propose a model of depression driven by an individual’s accumulated experience mediated by social networks. The connection between observed systematic variations in socioeconomic networks and built environments with city size provides a link between urbanization and mental health. Surprisingly, this model predicts lower depression rates in larger cities. We confirm this prediction for US cities using four independent datasets. These results are consistent with other behaviors associated with denser socioeconomic networks and suggest that larger cities provide a buffer against depression. This approach introduces a systematic framework for conceptualizing and modeling mental health in complex physical and social networks, producing testable predictions for environmental and social determinants of mental health also applicable to other psychopathologies.”

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Abstract: Socioeconomic factors have been suggested to influence the effect of education- and intelligence-associated genetic variants. However, results from previous studies on the interaction between socioeconomic status and education or intelligence have been inconsistent. The authors sought to assess these interactions in the UK Biobank cohort of 500,000 participants.
The authors assessed the effect of socioeconomic deprivation on education- and intelligence-associated genetic variants by estimating the single-nucleotide polymorphism (SNP) heritability for fluid intelligence, educational attainment, and years of education in subsets of UK Biobank participants with different degrees of social deprivation, using linkage disequilibrium score regression. They also generated polygenic scores with LDpred and tested for interactions with social deprivation.
SNP heritability increased with socioeconomic deprivation for fluid intelligence, educational attainment, and years of education. Polygenic scores were also found to interact with socioeconomic deprivation, where the effects of the scores increased with increasing deprivation for all traits.
These results indicate that genetics have a larger influence on educational and cognitive outcomes in more socioeconomically deprived U.K. citizens, which has serious implications for equality of opportunity.

Rask-Andersen M et al., Modification of Heritability for Educational Attainment and Fluid Intelligence by Socioeconomic Deprivation in the U.K. Biobank.  Amer J Psychiatry, EPub: https://doi.org/10.1176/appi.ajp.2020.20040462

Hill WD: Environmental Influences on Genetic Contributions to Intelligence and Education. Am J Psychiatry. 2021 Jul;178(7):582-583. doi: 10.1176/appi.ajp.2021.21050545. PMID: 34270340.

https://ajp.psychiatryonline.org/doi/pdf/10.1176/appi.ajp.2021.21050545

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https://www.nature.com/articles/d41586-021-02039-y
Nature. 2021 Jul;595(7869):640-644.


doi: 10.1038/d41586-021-02039-y

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https://www.nature.com/articles/s41582-021-00531-7.pdf

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https://www.pnas.org/content/pnas/118/24/e2013155118.full.pdf

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190281/pdf/41467_2021_Article_23694.pdf

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Abstract: “While many diseases of aging have been linked to the immunological system, immune metrics capable of identifying the most at-risk individuals are lacking. From the blood immunome of 1,001 individuals aged 8–96 years, we developed a deep-learning method based on patterns of systemic age-related inflammation. The resulting inflammatory clock of aging (iAge) tracked with multimorbidity, immunosenescence, frailty and cardiovascular aging, and is also associated with exceptional longevity in centenarians. The strongest contributor to iAge was the chemokine CXCL9, which was involved in cardiac aging, adverse cardiac remodeling and poor vascular function. Furthermore, aging endothelial cells in human and mice show loss of function, cellular senescence and hallmark phenotypes of arterial stiffness, all of which are reversed by silencing CXCL9. In conclusion, we identify a key role of CXCL9 in age-related chronic inflammation and derive a metric for multimorbidity that can be utilized for the early detection of age-related clinical phenotypes.”

Sayed, N., Huang, Y., Nguyen, K. et al. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging. Nat Aging 1, 598–615 (2021). https://doi.org/10.1038/s43587-021-00082-y.

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COVID and the brain: researchers zero in on how damage occurs.

Nature News July 7, 2021.
“Growing evidence suggests that the coronavirus causes ‘brain fog’ and other neurological symptoms through multiple mechanisms….

How COVID-19 damages the brain is becoming clearer. New evidence suggests that the coronavirus’s assault on the brain could be multipronged: it might attack certain brain cells directly, reduce blood flow to brain tissue or trigger production of immune molecules that can harm brain cells.Infection with the coronavirus SARS-CoV-2 can cause memory loss, strokes and other effects on the brain. The question, says Serena Spudich, a neurologist at Yale University in New Haven, Connecticut, is: “Can we intervene early to address these abnormalities so that people don’t have long-term problems?” With so many people affected — neurological symptoms appeared in 80% of the people hospitalized with COVID-19 who were surveyed in one study1 — researchers hope that the growing evidence base will point the way to better treatments….”

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Makhani, N., Tremlett, H. The multiple sclerosis prodrome. Nat Rev Neurol (2021). https://doi.org/10.1038/s41582-021-00519-3

https://www.nature.com/articles/s41582-021-00519-3

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