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      Night Shift Work, Genetic Risk, and Type 2 Diabetes in the UK Biobank

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          Abstract

          OBJECTIVE

          To examine the effects of past and current night shift work and genetic type 2 diabetes vulnerability on type 2 diabetes odds.

          RESEARCH DESIGN AND METHODS

          In the UK Biobank, we examined associations of current ( N = 272,214) and lifetime ( N = 70,480) night shift work exposure with type 2 diabetes risk (6,770 and 1,191 prevalent cases, respectively). For 180,704 and 44,141 unrelated participants of European ancestry (4,002 and 726 cases, respectively) with genetic data, we assessed whether shift work exposure modified the relationship between a genetic risk score (comprising 110 single-nucleotide polymorphisms) for type 2 diabetes and prevalent diabetes.

          RESULTS

          Compared with day workers, all current night shift workers were at higher multivariable-adjusted odds for type 2 diabetes (none or rare night shifts: odds ratio [OR] 1.15 [95% CI 1.05–1.26]; some nights: OR 1.18 [95% CI 1.05–1.32]; and usual nights: OR 1.44 [95% CI 1.19–1.73]), except current permanent night shift workers (OR 1.09 [95% CI 0.93–1.27]). Considering a person’s lifetime work schedule and compared with never shift workers, working more night shifts per month was associated with higher type 2 diabetes odds (<3/month: OR 1.24 [95% CI 0.90–1.68]; 3–8/month: OR 1.11 [95% CI 0.90–1.37]; and >8/month: OR 1.36 [95% CI 1.14–1.62]; P trend = 0.001). The association between genetic type 2 diabetes predisposition and type 2 diabetes odds was not modified by shift work exposure.

          CONCLUSIONS

          Our findings show that night shift work, especially rotating shift work including night shifts, is associated with higher type 2 diabetes odds and that the number of night shifts worked per month appears most relevant for type 2 diabetes odds. Also, shift work exposure does not modify genetic risk for type 2 diabetes, a novel finding that warrants replication.

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          An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

          Robert Scott, Laura J. Scott, Reedik Mägi … (2017)
          To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
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            Circadian Misalignment Augments Markers of Insulin Resistance and Inflammation, Independently of Sleep Loss

            Rachel Leproult, Ulf Holmbäck, Eve Van Cauter (2014)
            Shift workers, who are exposed to irregular sleep schedules resulting in sleep deprivation and misalignment of circadian rhythms, have an increased risk of diabetes relative to day workers. In healthy adults, sleep restriction without circadian misalignment promotes insulin resistance. To determine whether the misalignment of circadian rhythms that typically occurs in shift work involves intrinsic adverse metabolic effects independently of sleep loss, a parallel group design was used to study 26 healthy adults. Both interventions involved 3 inpatient days with 10-h bedtimes, followed by 8 inpatient days of sleep restriction to 5 h with fixed nocturnal bedtimes (circadian alignment) or with bedtimes delayed by 8.5 h on 4 of the 8 days (circadian misalignment). Daily total sleep time (SD) during the intervention was nearly identical in the aligned and misaligned conditions (4 h 48 min [5 min] vs. 4 h 45 min [6 min]). In both groups, insulin sensitivity (SI) significantly decreased after sleep restriction, without a compensatory increase in insulin secretion, and inflammation increased. In male participants exposed to circadian misalignment, the reduction in SI and the increase in inflammation both doubled compared with those who maintained regular nocturnal bedtimes. Circadian misalignment that occurs in shift work may increase diabetes risk and inflammation, independently of sleep loss.
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              Sleep disturbances compared to traditional risk factors for diabetes development: Systematic review and meta-analysis.

              Thunyarat Anothaisintawee, Sirimon Reutrakul, Eve Van Cauter … (2015)
              Sleep disturbances [short ( 8 h) sleeping time, insomnia (initiating or maintaining sleep), obstructive sleep apnea (OSA) and abnormal sleep timing] have been associated with increased diabetes risk but the effect size relative to that of traditional risk factors is unknown. We conducted a systematic review and meta-analysis to compare the risk associated with sleep disturbances to traditional risk factors. Studies were identified from Medline and Scopus. Cohort studies measuring the association between sleep disturbances and incident diabetes were eligible. For traditional risk factors (i.e., overweight, family history, and physical inactivity), systematic reviews with or without meta-analysis were included. Thirty-six studies (1,061,555 participants) were included. Pooled relative risks (RRs) of sleep variables were estimated using a random-effect model. Pooled RRs of sleeping ≤5 h, 6 h, and ≥9 h/d were respectively 1.48 (95%CI:1.25,1.76), 1.18 (1.10,1.26) and 1.36 (1.12,1.65). Poor sleep quality, OSA and shift work were associated with diabetes with a pooled RR of 1.40 (1.21,1.63), 2.02 (1.57, 2.61) and 1.40 (1.18,1.66), respectively. The pooled RRs of being overweight, having a family history of diabetes, and being physically inactive were 2.99 (2.42,3.72), 2.33 (1.79,2.79), and 1.20 (1.11,1.32), respectively. In conclusion, the risk of developing diabetes associated with sleep disturbances is comparable to that of traditional risk factors. Sleep disturbances should be considered in clinical guidelines for type 2 diabetes screening.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Diabetes Care
                Journal ID (iso-abbrev): Diabetes Care
                Journal ID (hwp): diacare
                Journal ID (pmc): dcare
                Journal ID (publisher-id): Diabetes Care
                Title: Diabetes Care
                Publisher: American Diabetes Association
                ISSN (Print): 0149-5992
                ISSN (Electronic): 1935-5548
                Publication date (Print): April 2018
                Publication date (Electronic): 12 February 2018
                Volume: 41
                Issue: 4
                Pages: 762-769
                Affiliations
                [1] 1Department of Integrative Physiology, University of Colorado, Boulder, CO
                [2] 2Broad Institute of MIT and Harvard, Cambridge, MA
                [3] 3Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston and Harvard Medical School, Boston, MA
                [4] 4Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
                [5] 5Division of Endocrinology, Diabetes and Gastroenterology, Faculty of Biology, Medicine and Health, School of Medical Sciences, University of Manchester, Manchester, U.K.
                [6] 6Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, U.K.
                [7] 7Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
                [8] 8Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA
                [9] 9Division of Sleep Medicine, Harvard Medical School, Boston, MA
                Author notes
                Corresponding author: Céline Vetter, celine.vetter@ 123456colorado.edu .

                C.V. and H.S.D. contributed equally to this work.

                M.K.R., R.S., and F.A.J.L.S. contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-3752-1067
                http://orcid.org/0000-0002-8896-073X
                Article
                Publisher ID: 1933
                DOI: 10.2337/dc17-1933
                PMC ID: 5860836
                PubMed ID: 29440150
                SO-VID: a76c9028-a0d7-475b-8310-ab6f74f7b91d
                Copyright © © 2018 by the American Diabetes Association.
                License:

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals.org/content/license.

                History
                Date received : 15 September 2017
                Date accepted : 2 January 2018
                Page count
                Figures: 0, Tables: 4, Equations: 0, References: 48, Pages: 8
                Funding
                Funded by: National Institutes of Health, DOI http://dx.doi.org/10.13039/100000062;
                Award ID: R01-DK-105072
                Award ID: R01-DK-102696
                Award ID: R01-HL-118601
                Award ID: R01-DK-099512
                Categories
                Subject: 0406
                Subject: Epidemiology/Health Services Research

                ScienceOpen disciplines: Endocrinology & Diabetes
                Data availability:
                ScienceOpen disciplines: Endocrinology & Diabetes

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