At a time when complex diseases affect globally 280 million people and claim 14 million lives every year, there is an urgent need to rapidly increase our knowledge into their underlying etiologies. Though critical in identifying the people at risk, the causal environmental factors (microbiome and/or pollutants) and the affected pathophysiological mechanisms are not well understood. Herein, we consider the variations of autophagy-related (ATG) genes at the heart of mechanisms of increased susceptibility to environmental stress. A comprehensive autophagy genomic resource is presented with 263 single nucleotide polymorphisms (SNPs) for 69 autophagy-related genes associated with 117 autoimmune, inflammatory, infectious, cardiovascular, neurological, respiratory, and endocrine diseases. We thus propose the term ‘autophagopathies’ to group together a class of complex human diseases the etiology of which lies in a genetic defect of the autophagy machinery, whether directly related or not to an abnormal flux in autophagy, LC3-associated phagocytosis, or any associated trafficking. The future of precision medicine for common diseases will lie in our ability to exploit these ATG SNP x environment relationships to develop new polygenetic risk scores, new management guidelines, and optimal therapies for afflicted patients. Abbreviations: ATG, autophagy‐related; ALS-FTD, amyotrophic lateral sclerosis-frontotemporal dementia; ccRCC, clear cell renal cell carcinoma; CD, Crohn disease; COPD, chronic obstructive pulmonary disease; eQTL, expression quantitative trait loci; HCC, hepatocellular carcinoma; HNSCC, head and neck squamous cell carcinoma; GTEx, genotype-tissue expression; GWAS, genome-wide association studies; LAP, LC3-associated phagocytosis; LC3-II, phosphatidylethanolamine conjugated form of LC3; LD, linkage disequilibrium; LUAD, lung adenocarcinoma; MAF, minor allele frequency; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; NSCLC, non-small cell lung cancer; OS, overall survival; PtdIns3K CIII, class III phosphatidylinositol 3 kinase; PtdIns3P, phosphatidylinositol-3-phosphate; SLE, systemic lupus erythematosus; SNPs, single-nucleotide polymorphisms; mQTL, methylation quantitative trait loci; ULK, unc-51 like autophagy activating kinase; UTRs, untranslated regions; WHO, World Health Organization.

Nearly fifty million older people suffer from neurodegenerative diseases, including Alzheimer (AD) and Parkinson (PD) disease, a global burden expected to triple by 2050. Such an imminent "neurological pandemic" urges the identification of environmental risk factors that are hopefully avoided to fight the disease. In 2022, strong evidence in mouse models incriminated defective lysosomal acidification and impairment of the autophagy pathway as modifiable risk factors for dementia. To date, the most prescribed lysosomotropic drugs are proton pump inhibitors (PPIs), chloroquine (CQ), and the related hydroxychloroquine (HCQ), which belong to the group of disease-modifying antirheumatic drugs (DMARDs). This commentary aims to open the discussion on the possible mechanisms connecting the long-term prescribing of these drugs to the elderly and the incidence of neurodegenerative diseases.Abbreviations: AD: Alzheimer disease; APP-βCTF: amyloid beta precursor protein-C-terminal fragment; BACE1: beta-secretase 1; BBB: brain blood barrier; CHX: Ca²⁺/H⁺ exchanger; CMI: cognitive mild impairment; CQ: chloroquine; DMARD: disease-modifying antirheumatic drugs; GBA1: glucosylceramidase beta 1; HCQ: hydroxychloroquine; HPLC: high-performance liquid chromatography; LAMP: lysosomal associated membrane protein; MAPK/JNK: mitogen-activated protein kinase; MAPT: microtubule associated protein tau; MCOLN1/TRPML1: mucolipin TRP cation channel 1; NFE2L2/NRF2: NFE2 like bZIP transcription factor 2; NRBF2: nuclear receptor binding factor 2; PANTHOS: poisonous flower; PD: Parkinson disease; PIK3C3: phosphatIdylinositol 3-kinase catalytic subunit type 3; PPI: proton pump inhibitor; PSEN1: presenilin 1, RUBCN: rubicon autophagy regulator; RUBCNL: rubicon like autophagy enhancer; SQSTM1: sequestosome 1; TMEM175: transmembrane protein 175; TPCN2: two pore segment channel 2; VATPase: vacuolar-type H⁺-translocating ATPase; VPS13C: vacuolar protein sorting ortholog 13 homolog C; VPS35: VPS35 retromer complex component; WDFY3: WD repeat and FYVE domain containing 3; ZFYVE1: zinc finger FYVE-type containing 1.

In less than eleven months, the world was brought to a halt by the COVID-19 outbreak. With hospitals becoming overwhelmed, one of the highest priorities concerned critical care triage to ration the scarce resources of intensive care units. Which patient should be treated first? Based on what clinical and biological criteria? A global joint effort rapidly led to sequencing the genomes of tens of thousands of COVID-19 patients to determine the patients’ genetic signature that causes them to be at risk of suddenly developing severe disease. In this commentary, we would like to consider some points concerning the use of a multifactorial risk score for COVID-19 severity. This score includes macroautophagy (hereafter referred to as autophagy), a critical host process that controls all steps harnessed by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Abbreviation list: ATG5: autophagy related 5; BECN1: beclin 1; COVID-19: coronavirus infectious disease-2019; EGR1: early growth response 1; ER: endoplasmic reticulum; DMVs: double-membrane vesicles; IBV: infectious bronchitis virus; MAP1LC3: microtubule associated protein 1 light chain 3; LC3-I: proteolytically processed, non-lipidated MAP1LC3; LC3-II: lipidated MAP1LC3; MEFs: mouse embryonic fibroblasts; MERS-CoV: Middle East respiratory syndrome-coronavirus; MHV: mouse hepatitis virus; NSP: non-structural protein; PEDV: porcine epidemic diarrhea virus; PLP2-TM: membrane-associated papain-like protease 2; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TGEV: transmissible gastroenteritis virus.

Overactivation of the mitogen-activated protein kinase (MAPK) pathway is a critical driver of many human cancers. However, therapies directly targeting this pathway lead to cancer drug resistance. Resistance has been linked to compensatory RAS overexpression, but the mechanisms underlying this response remain unclear. Here, we find that MEK inhibitors (MEKi) are associated with an increased translation of the KRAS and NRAS oncogenes through a mechanism involving dissolution of processing body (P-body) biocondensates. This effect is seen across different cell types and is extremely dynamic since removal of MEKi and ERK reactivation result in reappearance of P-bodies and reduced RAS-dependent signaling. Moreover, we find that P-body scaffold protein levels negatively impact RAS expression. Overall, we describe a new feedback loop mechanism involving biocondensates such as P-bodies in the translational regulation of RAS proteins and MAPK signaling.

Overactivation of the Mitogen-activated protein kinase (MAPK) pathway is a critical driver of many human cancers. However, therapies targeting this pathway have proven effective in only a few cancers, as cancers inevitably develop resistance. Puzzling observations suggest that MAPK targeting fails in tumors due to early compensatory RAS overexpression, albeit by unexplained mechanisms. We identified a novel mechanism of drug tolerance to MEK inhibitors (MEKi) that involves Processing Bodies (PBs), a membraneless organelle (MLO). MEKi promoted translation of the oncogenes KRAS and NRAS, which in turn triggered BRAF phosphorylation. This overexpression, which occurred in the absence of neotranscription, depended on PB dissolution as the source of the RAS mRNA. Moreover, in response to MEKi removal, the process was dynamic as PBs rapidly reformed and reduced MAPK signaling. These results highlight a dynamic spatiotemporal negative feedback loop of MAPK signaling via RAS mRNA sequestration. Furthermore, we observed a phenotype with a low number of PBs along with strong KRAS and NRAS induction capacities. Overall, we describe a new intricate mechanism involving PBs in the translational regulation of essential cellular signaling pathways like MAPKs, paving the way for future therapies altering MLO and thereby improving targeted cancer therapies.