Longitudinal Trends in Childhood Insulin Levels and Body Mass Index and Associations With Risks of Psychosis and Depression in Young Adults

. 2021 Apr 01 ; 78 (4) : 416-425.

Jazyk angličtina Země Spojené státy americké Médium print

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid33439216

Grantová podpora
08426812/Z/07/Z Wellcome Trust - United Kingdom
201486/Z/16/Z Wellcome Trust - United Kingdom
MC_UU_12015/1 Medical Research Council - United Kingdom
MR/T010576/1 Medical Research Council - United Kingdom
MC_PC_17213 Medical Research Council - United Kingdom
MC_UU_00006/1 Medical Research Council - United Kingdom
MR/L010305/1 Medical Research Council - United Kingdom
102215/2/13/2 Wellcome Trust - United Kingdom
G9815508 Medical Research Council - United Kingdom
217065/Z/19/Z Wellcome Trust - United Kingdom
MR/S037675/1 Medical Research Council - United Kingdom
MC_PC_19009 Medical Research Council - United Kingdom
MR/M006727/1 Medical Research Council - United Kingdom
MC_PC_15018 Medical Research Council - United Kingdom
DRF-2018-11-ST2-018 Department of Health - United Kingdom
MC_UU_00006/5 Medical Research Council - United Kingdom

IMPORTANCE: Cardiometabolic disorders often occur concomitantly with psychosis and depression, contribute to high mortality rates, and are detectable from the onset of the psychiatric disorders. However, it is unclear whether longitudinal trends in cardiometabolic traits from childhood are associated with risks for adult psychosis and depression. OBJECTIVE: To examine whether specific developmental trajectories of fasting insulin (FI) levels and body mass index (BMI) from early childhood were longitudinally associated with psychosis and depression in young adults. DESIGN, SETTING, AND PARTICIPANTS: A cohort study from the Avon Longitudinal Study of Parents and Children, a prospective study including a population-representative British cohort of 14 975 individuals, was conducted using data from participants aged 1 to 24 years. Body mass index and FI level data were used for growth mixture modeling to delineate developmental trajectories, and associations with psychosis and depression were assessed. The study was conducted between July 15, 2019, and March 24, 2020. EXPOSURES: Fasting insulin levels were measured at 9, 15, 18, and 24 years, and BMI was measured at 1, 2, 3, 4, 7, 9, 10, 11, 12, 15, 18, and 24 years. Data on sex, race/ethnicity, paternal social class, childhood emotional and behavioral problems, and cumulative scores of sleep problems, average calorie intake, physical activity, smoking, and alcohol and substance use in childhood and adolescence were examined as potential confounders. MAIN OUTCOMES AND MEASURES: Psychosis risk (definite psychotic experiences, psychotic disorder, at-risk mental state status, and negative symptom score) depression risk (measured using the computerized Clinical Interview Schedule-Revised) were assessed at 24 years. RESULTS: From data available on 5790 participants (3132 [54.1%] female) for FI levels and data available on 10 463 participants (5336 [51.0%] female) for BMI, 3 distinct trajectories for FI levels and 5 distinct trajectories for BMI were noted, all of which were differentiated by mid-childhood. The persistently high FI level trajectory was associated with a psychosis at-risk mental state (adjusted odds ratio [aOR], 5.01; 95% CI, 1.76-13.19) and psychotic disorder (aOR, 3.22; 95% CI, 1.29-8.02) but not depression (aOR, 1.38; 95% CI, 0.75-2.54). A puberty-onset major increase in BMI was associated with depression (aOR, 4.46; 95% CI, 2.38-9.87) but not psychosis (aOR, 1.98; 95% CI, 0.56-7.79). CONCLUSIONS AND RELEVANCE: The cardiometabolic comorbidity of psychosis and depression may have distinct, disorder-specific early-life origins. Disrupted insulin sensitivity could be a shared risk factor for comorbid cardiometabolic disorders and psychosis. A puberty-onset major increase in BMI could be a risk factor or risk indicator for adult depression. These markers may represent targets for prevention and treatment of cardiometabolic disorders in individuals with psychosis and depression.

Erratum v

PubMed

Zobrazit více v PubMed

Firth J, Siddiqi N, Koyanagi A, et al. . The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness. Lancet Psychiatry. 2019;6(8):675-712. doi:10.1016/S2215-0366(19)30132-4 PubMed DOI

Naylor C, Parsonage M, McDaid D, Knapp M, Fossey M, Galea A. Long-term Conditions and Mental Health: the Cost of Co-morbidities. The King’s Fund; 2012.

Laursen TM, Plana-Ripoll O, Andersen PK, et al. . Cause-specific life years lost among persons diagnosed with schizophrenia: is it getting better or worse? Schizophr Res. 2019;206:284-290. doi:10.1016/j.schres.2018.11.003 PubMed DOI

Plana-Ripoll O, Pedersen CB, Agerbo E, et al. . A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study. Lancet. 2019;394(10211):1827-1835. doi:10.1016/S0140-6736(19)32316-5 PubMed DOI

Leucht S, Cipriani A, Spineli L, et al. . Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet. 2013;382(9896):951-962. doi:10.1016/S0140-6736(13)60733-3 PubMed DOI

Perry BI, McIntosh G, Weich S, Singh S, Rees K. The association between first-episode psychosis and abnormal glycaemic control: systematic review and meta-analysis. Lancet Psychiatry. 2016;3(11):1049-1058. doi:10.1016/S2215-0366(16)30262-0 PubMed DOI

Pillinger T, Beck K, Gobjila C, Donocik JG, Jauhar S, Howes OD. Impaired glucose homeostasis in first-episode schizophrenia: a systematic review and meta-analysis. JAMA Psychiatry. 2017;74(3):261-269. doi:10.1001/jamapsychiatry.2016.3803 PubMed DOI PMC

Penninx BW, Beekman AT, Honig A, et al. . Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry. 2001;58(3):221-227. doi:10.1001/archpsyc.58.3.221 PubMed DOI

van Melle JP, de Jonge P, Spijkerman TA, et al. . Prognostic association of depression following myocardial infarction with mortality and cardiovascular events: a meta-analysis. Psychosom Med. 2004;66(6):814-822. doi:10.1097/01.psy.0000146294.82810.9c PubMed DOI

Kucukgoncu S, Kosir U, Zhou E, Sullivan E, Srihari VH, Tek C. Glucose metabolism dysregulation at the onset of mental illness is not limited to first episode psychosis: A systematic review and meta-analysis. Early Interv Psychiatry. 2019;13(5):1021-1031. doi:10.1111/eip.12749 PubMed DOI PMC

Perry BI, Upthegrove R, Thompson A, et al. . Dysglycaemia, inflammation and psychosis: findings from the UK ALSPAC Birth Cohort. Schizophr Bull. 2019;45(2):330-338. doi:10.1093/schbul/sby040 PubMed DOI PMC

Mannan M, Mamun A, Doi S, Clavarino A. Prospective associations between depression and obesity for adolescent males and females—a systematic review and meta-analysis of longitudinal studies. PLoS One. 2016;11(6):e0157240. doi:10.1371/journal.pone.0157240 PubMed DOI PMC

Buscot MJ, Thomson RJ, Juonala M, et al. . Distinct child-to-adult body mass index trajectories are associated with different levels of adult cardiometabolic risk. Eur Heart J. 2018;39(24):2263-2270. doi:10.1093/eurheartj/ehy161 PubMed DOI

Tyrrell J, Mulugeta A, Wood AR, et al. . Using genetics to understand the causal influence of higher BMI on depression. Int J Epidemiol. 2019;48(3):834-848. doi:10.1093/ije/dyy223 PubMed DOI PMC

Li Z, Chen P, Chen J, et al. . Glucose and insulin-related traits, type 2 diabetes and risk of schizophrenia: a mendelian randomization study. EBioMedicine. 2018;34:182-188. doi:10.1016/j.ebiom.2018.07.037 PubMed DOI PMC

Boyd A, Golding J, Macleod J, et al. . Cohort profile: the “children of the 90s”—the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol. 2013;42(1):111-127. doi:10.1093/ije/dys064 PubMed DOI PMC

Fraser A, Macdonald-Wallis C, Tilling K, et al. . Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int J Epidemiol. 2013;42(1):97-110. doi:10.1093/ije/dys066 PubMed DOI PMC

Northstone K, Lewcock M, Groom A, et al. . The Avon Longitudinal Study of Parents and Children (ALSPAC): an update on the enrolled sample of index children in 2019. Wellcome Open Res. 2019;4:51. doi:10.12688/wellcomeopenres.15132.1 PubMed DOI PMC

Harris PA, Taylor R, Minor BL, et al. ; REDCap Consortium . The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208. doi:10.1016/j.jbi.2019.103208 PubMed DOI PMC

Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. doi:10.1016/j.jbi.2008.08.010 PubMed DOI PMC

Sullivan SA, Kounali D, Cannon M, et al. . A Population-based cohort study examining the incidence and impact of psychotic experiences from childhood to adulthood, and prediction of psychotic disorder. Am J Psychiatry. 2020;177(4):308-317. doi:10.1176/appi.ajp.2019.19060654 PubMed DOI

World Health Organization . Division of Mental Health. Schedules for clinical assessment in neuropsychiatry: version 2. World Health Organization. Published 1994. Accessed December 7, 2020. https://apps.who.int/iris/handle/10665/40356

Yung AR, Yuen HP, McGorry PD, et al. . Mapping the onset of psychosis: the Comprehensive Assessment of At-Risk Mental States. Aust N Z J Psychiatry. 2005;39(11-12):964-971. doi:10.1080/j.1440-1614.2005.01714.x PubMed DOI

Konings M, Bak M, Hanssen M, van Os J, Krabbendam L. Validity and reliability of the CAPE: a self-report instrument for the measurement of psychotic experiences in the general population. Acta Psychiatr Scand. 2006;114(1):55-61. doi:10.1111/j.1600-0447.2005.00741.x PubMed DOI

Lewis G, Pelosi AJ, Araya R, Dunn G. Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol Med. 1992;22(2):465-486. doi:10.1017/S0033291700030415 PubMed DOI

Goodman R. Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry. 2001;40(11):1337-1345. doi:10.1097/00004583-200111000-00015 PubMed DOI

Ram N, Grimm KJ. Growth mixture modeling: a method for identifying differences in longitudinal change among unobserved groups. Int J Behav Dev. 2009;33(6):565-576. doi:10.1177/0165025409343765 PubMed DOI PMC

Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6(2):65-70.

Asparouhov T, Muthén B.. Auxiliary variables in mixture modeling: three-step approaches using Mplus. Struct Equ Modeling. 2014;21(3):329-341. doi:10.1080/10705511.2014.915181 DOI

Hackinger S, Prins B, Mamakou V, et al. . Evidence for genetic contribution to the increased risk of type 2 diabetes in schizophrenia. Transl Psychiatry. 2018;8(1):252. doi:10.1038/s41398-018-0304-6 PubMed DOI PMC

Tomasik J, Lago SG, Vázquez-Bourgon J, et al. . Association of insulin resistance with schizophrenia polygenic risk score and response to antipsychotic treatment. JAMA Psychiatry. 2019;76(8):864-867. doi:10.1001/jamapsychiatry.2019.0304 PubMed DOI PMC

Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993;341(8850):938-941. doi:10.1016/0140-6736(93)91224-A PubMed DOI

Gariepy G, Nitka D, Schmitz N. The association between obesity and anxiety disorders in the population: a systematic review and meta-analysis. Int J Obes (Lond). 2010;34(3):407-419. doi:10.1038/ijo.2009.252 PubMed DOI

Luppino FS, de Wit LM, Bouvy PF, et al. . Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010;67(3):220-229. doi:10.1001/archgenpsychiatry.2010.2 PubMed DOI

Zhang T, Xu J, Li S, et al. . Trajectories of childhood BMI and adult diabetes: the Bogalusa Heart Study. Diabetologia. 2019;62(1):70-77. doi:10.1007/s00125-018-4753-5 PubMed DOI PMC

Rolland-Cachera MF, Péneau S. Growth trajectories associated with adult obesity. World Rev Nutr Diet. 2013;106:127-134. PubMed

Barker DJ, Osmond C, Forsén TJ, Kajantie E, Eriksson JG. Trajectories of growth among children who have coronary events as adults. N Engl J Med. 2005;353(17):1802-1809. doi:10.1056/NEJMoa044160 PubMed DOI

Mattsson M, Maher GM, Boland F, Fitzgerald AP, Murray DM, Biesma R. Group-based trajectory modelling for BMI trajectories in childhood: a systematic review. Obes Rev. 2019;20(7):998-1015. doi:10.1111/obr.12842 PubMed DOI

Lee KS, Vaillancourt T. Longitudinal associations among bullying by peers, disordered eating behavior, and symptoms of depression during adolescence. JAMA Psychiatry. 2018;75(6):605-612. doi:10.1001/jamapsychiatry.2018.0284 PubMed DOI PMC

Yilmaz Z, Gottfredson NC, Zerwas SC, Bulik CM, Micali N. Developmental premorbid body mass index trajectories of adolescents with eating disorders in a longitudinal population cohort. J Am Acad Child Adolesc Psychiatry. 2019;58(2):191-199. doi:10.1016/j.jaac.2018.11.008 PubMed DOI PMC

Welch E, Jangmo A, Thornton LM, et al. . Treatment-seeking patients with binge-eating disorder in the Swedish national registers: clinical course and psychiatric comorbidity. BMC Psychiatry. 2016;16:163. doi:10.1186/s12888-016-0840-7 PubMed DOI PMC

Schiller CE, Meltzer-Brody S, Rubinow DR. The role of reproductive hormones in postpartum depression. CNS Spectr. 2015;20(1):48-59. doi:10.1017/S1092852914000480 PubMed DOI PMC

Dalal PK, Agarwal M. Postmenopausal syndrome. Indian J Psychiatry. 2015;57(suppl 2):S222-S232. doi:10.4103/0019-5545.161483 PubMed DOI PMC

Soares CN, Zitek B. Reproductive hormone sensitivity and risk for depression across the female life cycle: a continuum of vulnerability? J Psychiatry Neurosci. 2008;33(4):331-343. PubMed PMC

Li W, Liu Q, Deng X, Chen Y, Liu S, Story M. Association between obesity and puberty timing: a systematic review and meta-analysis. Int J Environ Res Public Health. 2017;14(10):E1266. doi:10.3390/ijerph14101266 PubMed DOI PMC

Bell JA, Carslake D, Wade KH, et al. . Influence of puberty timing on adiposity and cardiometabolic traits: a mendelian randomisation study. PLoS Med. 2018;15(8):e1002641. doi:10.1371/journal.pmed.1002641 PubMed DOI PMC

Lewis G, Ioannidis K, van Harmelen AL, et al. . The association between pubertal status and depressive symptoms and diagnoses in adolescent females: a population-based cohort study. PLoS One. 2018;13(6):e0198804. doi:10.1371/journal.pone.0198804 PubMed DOI PMC

Timonen M, Rajala U, Jokelainen J, Keinänen-Kiukaanniemi S, Meyer-Rochow VB, Räsänen P. Depressive symptoms and insulin resistance in young adult males: results from the Northern Finland 1966 birth cohort. Mol Psychiatry. 2006;11(10):929-933. doi:10.1038/sj.mp.4001838 PubMed DOI

Perry BI, Khandaker GM, Marwaha S, et al. . Insulin resistance and obesity, and their association with depression in relatively young people: findings from a large UK birth cohort. Psychol Med. 2020;50(4):556-565. doi:10.1017/S0033291719000308 PubMed DOI PMC

Cham H, Reshetnyak E, Rosenfeld B, Breitbart W. Full information maximum likelihood estimation for latent variable interactions with incomplete indicators. Multivariate Behav Res. 2017;52(1):12-30. doi:10.1080/00273171.2016.1245600 PubMed DOI PMC

Little TD, Jorgensen TD, Lang KM, Moore EW. On the joys of missing data. J Pediatr Psychol. 2014;39(2):151-162. doi:10.1093/jpepsy/jst048 PubMed DOI

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...