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Creswell JD, Tumminia MJ, Price S, Sefidgar Y, Cohen S, Ren Y, Brown J, Dey AK, Dutcher JM, Villalba D, Mankoff J, Xu X, Creswell K, Doryab A, Mattingly S, Striegel A, Hachen D, Martinez G, Lovett MC. Nightly sleep duration predicts grade point average in the first year of college. Proc Natl Acad Sci U S A 2023; 120:e2209123120. [PMID: 36780521 PMCID: PMC9974458 DOI: 10.1073/pnas.2209123120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 01/09/2023] [Indexed: 02/15/2023] Open
Abstract
Academic achievement in the first year of college is critical for setting students on a pathway toward long-term academic and life success, yet little is known about the factors that shape early college academic achievement. Given the important role sleep plays in learning and memory, here we extend this work to evaluate whether nightly sleep duration predicts change in end-of-semester grade point average (GPA). First-year college students from three independent universities provided sleep actigraphy for a month early in their winter/spring academic term across five studies. Findings showed that greater early-term total nightly sleep duration predicted higher end-of-term GPA, an effect that persisted even after controlling for previous-term GPA and daytime sleep. Specifically, every additional hour of average nightly sleep duration early in the semester was associated with an 0.07 increase in end-of-term GPA. Sensitivity analyses using sleep thresholds also indicated that sleeping less than 6 h each night was a period where sleep shifted from helpful to harmful for end-of-term GPA, relative to previous-term GPA. Notably, predictive relationships with GPA were specific to total nightly sleep duration, and not other markers of sleep, such as the midpoint of a student's nightly sleep window or bedtime timing variability. These findings across five studies establish nightly sleep duration as an important factor in academic success and highlight the potential value of testing early academic term total sleep time interventions during the formative first year of college.
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Affiliation(s)
- J. David Creswell
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | | | - Stephen Price
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | - Yasaman Sefidgar
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA98195
| | - Sheldon Cohen
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | - Yiyi Ren
- The Information School, University of Washington, Seattle, WA98105
| | - Jennifer Brown
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA98195
| | - Anind K. Dey
- The Information School, University of Washington, Seattle, WA98105
| | - Janine M. Dutcher
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | - Daniella Villalba
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | - Jennifer Mankoff
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA98195
| | - Xuhai Xu
- The Information School, University of Washington, Seattle, WA98105
| | - Kasey Creswell
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
| | - Afsaneh Doryab
- School of Engineering and Applied Science, University of Virginia, Charlottesville, VA22904
| | - Stephen Mattingly
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN46556
| | - Aaron Striegel
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN46556
| | - David Hachen
- Department of Sociology, University of Notre Dame, Notre Dame, IN46556
| | - Gonzalo Martinez
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN46556
| | - Marsha C. Lovett
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA15213
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Taylor HJ, Hung YH, Narisu N, Erdos MR, Kanke M, Yan T, Grenko CM, Swift AJ, Bonnycastle LL, Sethupathy P, Collins FS, Taylor DL. Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis. Proc Natl Acad Sci U S A 2023; 120:e2206797120. [PMID: 36757889 PMCID: PMC9963967 DOI: 10.1073/pnas.2206797120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 01/11/2023] [Indexed: 02/10/2023] Open
Abstract
Genetic studies have identified ≥240 loci associated with the risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterized the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression [miRNA-expression quantitative trait loci (eQTLs)]. We found i) 84 heritable miRNAs, primarily regulated by trans-acting genetic effects, and ii) 5 miRNA-eQTLs. We also used several different strategies to identify T2D-associated miRNAs. First, we colocalized miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersected miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and found 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we performed differential expression analysis and identified 14 miRNAs associated with T2D status-including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p-and 4 miRNAs associated with a polygenic score for HbA1c levels-miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.
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Affiliation(s)
- Henry J. Taylor
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, CambridgeCB2 0BB, UK
- Heart and Lung Research Institute, University of Cambridge, CambridgeCB2 0BB, UK
| | - Yu-Han Hung
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY14853
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Michael R. Erdos
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Matthew Kanke
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY14853
| | - Tingfen Yan
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Caleb M. Grenko
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Amy J. Swift
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Lori L. Bonnycastle
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - Praveen Sethupathy
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY14853
| | - Francis S. Collins
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
| | - D. Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD20892
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