A role for the ubiquitin-proteasome system in activity-dependent presynaptic silencing

Chronic changes in electrical excitability profoundly affect synaptic transmission throughout the lifetime of a neuron. We have previously explored persistent presynaptic silencing, a form of synaptic depression at glutamate synapses produced by ongoing neuronal activity and by strong depolarization. Here we investigate the involvement of the ubiquitin-proteasome system (UPS) in the modulation of presynaptic function. We found that proteasome inhibition prevented the induction of persistent presynaptic silencing. Specifically, application of the proteasome inhibitor, MG-132, prevented decreases in the size of the readily releasable pool of vesicles and in the percentage of active synapses. Presynaptic silencing was accompanied by decreases in levels of the priming proteins, Munc13-1 and Rim1. Importantly, overexpression of Rim1α prevented the induction of persistent presynaptic silencing. Furthermore, strong depolarization itself increased proteasome enzymatic activity measured in cell lysates. These results suggest that modulation of the UPS by electrical activity contributes to persistent presynaptic silencing by promoting the degradation of key presynaptic proteins

A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program

Background Height has been associated with many clinical traits but whether such associations are causal versus secondary to confounding remains unclear in many cases. To systematically examine this question, we performed a Mendelian Randomization-Phenome-wide association study (MR-PheWAS) using clinical and genetic data from a national healthcare system biobank. Methods and findings Analyses were performed using data from the US Veterans Affairs (VA) Million Veteran Program in non-Hispanic White (EA, n = 222,300) and non-Hispanic Black (AA, n = 58,151) adults in the US. We estimated height genetic risk based on 3290 height-associated variants from a recent European-ancestry genome-wide meta-analysis. We compared associations of measured and genetically-predicted height with phenome-wide traits derived from the VA electronic health record, adjusting for age, sex, and genetic principal components. We found 345 clinical traits associated with measured height in EA and an additional 17 in AA. Of these, 127 were associated with genetically-predicted height at phenome-wide significance in EA and 2 in AA. These associations were largely independent from body mass index. We confirmed several previously described MR associations between height and cardiovascular disease traits such as hypertension, hyperlipidemia, coronary heart disease (CHD), and atrial fibrillation, and further uncovered MR associations with venous circulatory disorders and peripheral neuropathy in the presence and absence of diabetes. As a number of traits associated with genetically-predicted height frequently co-occur with CHD, we evaluated effect modification by CHD status of genetically-predicted height associations with risk factors for and complications of CHD. We found modification of effects of MR associations by CHD status for atrial fibrillation/flutter but not for hypertension, hyperlipidemia, or venous circulatory disorders. Conclusions We conclude that height may be an unrecognized but biologically plausible risk factor for several common conditions in adults. However, more studies are needed to reliably exclude horizontal pleiotropy as a driving force behind at least some of the MR associations observed in this study

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Off-Farm Income a Major Component of Total Income for Most Farm Households in 2019

Off-farm income—such as pensions, investment income, or wages and salary from an off-farm job—is an important source of total income for U.S. farm households. In 2019, 96 percent of farm households derived some income from off-farm sources. On average, off-farm income contributed 82 percent of total income, or $101,638, for all family farms in 2019. Smaller farms tend to rely more on off-farm income than larger farms. On average, small family farms, those with an annual gross cash farm income (GCFI) under$350,000, derived more than half of their total household income from off-farm income in 2019. By comparison, on average, very large farms, those with a GCFI of $5 million or more, earned 7 percent of their total income from off-farm sources that year. However, those are averages, and some households operating small farms rely primarily on farm income, while some households operating larger farms rely on income from off-farm sources

Agricultural Income and Finance Situation and Outlook: 2021 Edition

The U.S. agricultural economy experienced pronounced volatility over the 2009–19 decade, including strong periods of expansion in the first part of the decade followed by several years of contraction. Although many financial indicators of well-being—including farm sector and household income—were at or near their long-term average in 2019, shifts in the distribution of Government payments from farm programs occurred. In addition, bankruptcy rates were elevated in some key agricultural States. This report describes major trends in the agricultural economy over the most recent decade for which survey data are available (2009–19) and explores drivers underlying the trends. The analysis is based on USDA’s Farm Income and Wealth Statistics data product, data collected from farm operators and farm households through the Agricultural Resource Management Survey (ARMS), and data from U.S. Bankruptcy Courts. The charts and analyses provide a historical perspective to evaluate current economic conditions

Agricultural Income and Finance Situation and Outlook: 2021 Edition

The agricultural economy experienced pronounced volatility over 2009–19, including strong periods of expansions in the first part of the decade followed by several years of contraction. This report presents and assesses recent trends in three major areas of farm finance: farm income, Government payment programs, and Chapter 12 bankruptcy eligibility and rates

Loops and Self-Reference in the Construction of Dictionaries

Dictionaries link a given word to a set of alternative words (the definition) which in turn point to further descendants. Iterating through definitions in this way, one typically finds that definitions loop back upon themselves. We demonstrate that such definitional loops are created in order to introduce new concepts into a language. In contrast to the expectations for a random lexical network, in graphs of the dictionary, meaningful loops are quite short, although they are often linked to form larger, strongly connected components. These components are found to represent distinct semantic ideas. This observation can be quantified by a singular value decomposition, which uncovers a set of conceptual relationships arising in the global structure of the dictionary. Finally, we use etymological data to show that elements of loops tend to be added to the English lexicon simultaneously and incorporate our results into a simple model for language evolution that falls within the "rich-get-richer" class of network growth

Large scale proteomic studies create novel privacy considerations

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90–95% of proteomes to their correct genome and for 95–99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable