Simultaneous alcohol and marijuana use among college students in the United States, 2006-2019

OBJECTIVE: Simultaneous alcohol and marijuana (SAM) use exposes college students to a myriad of adverse consequences. However, there is no recent nationally representative study on SAM use among college students in the United States (US). To provide an update to the literature, the present study aimed to examine the trends, prevalence, and correlates of SAM use among US college students between 2006 and 2019, using nationally representative data. METHOD: We used data from the 2006-2019 National Survey on Drug Use and Health (NSDUH) and the analytic sample was limited to the 55,669 full-time college student respondents (ages 18-22). Using logistic regression analysis, we assessed trends in SAM use prevalence and examined sociodemographic and psycho-social-behavioral correlates of SAM use. RESULTS: The proportion of US college students who reported SAM use increased significantly from 8.13% (2006-2010) to 8.44% (2015-2019). However, examination by race/ethnicity revealed that the increasing trend was largely driven by Black college students, whose SAM use prevalence increased significantly from 5.50% (2006-2010) to 9.30% (2015-2019), reflecting a 69.09% increase. SAM use rates did not change significantly among other racial/ethnic groups. CONCLUSIONS: This study uncovered an upward trend and prevalence of SAM use among US college students, calling for more research and public health interventions in this area. At-risk subgroups that warrant more attention include college students who are Black, female, above the legal drinking age, have a lower than $20,000 household income, and reside in small metropolitan areas.Published versio

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Cognitive behavioral therapy for primary care depression and anxiety: a secondary meta-analytic review using robust variance estimation in meta-regression

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153320/1/2019ZhangetalJBM.pd

The effectiveness of four empirically supported psychotherapies for primary care depression and anxiety: A systematic review and meta-analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153296/1/2019ZhangetalJAD.pd

The trans-ancestral genomic architecture of glycemic traits

Abstract Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P &lt; 5 x 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

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Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field