Familial confounding in the associations between maternal health and autism
Kodesh, A. et al. Maternal health around pregnancy and autism risk: a population-based study. Psychol. Med. 52, 4076–4084 (2022).
Google Scholar
Viktorin, A., Uher, R., Reichenberg, A., Levine, S. Z. & Sandin, S. Autism risk following antidepressant medication during pregnancy. Psychol. Med. 47, 2787–2796 (2017).
Google Scholar
Xiang, A. H. et al. Association of maternal diabetes with autism in offspring. JAMA 313, 1425–1434 (2015).
Google Scholar
Croen, L. A., Grether, J. K., Yoshida, C. K., Odouli, R. & Van de Water, J. Maternal autoimmune diseases, asthma and allergies, and childhood autism spectrum disorders: a case–control study. Arch. Pediatr. Adolesc. Med. 159, 151–157 (2005).
Google Scholar
Atladóttir, H. O. et al. Maternal infection requiring hospitalization during pregnancy and autism spectrum disorders. J. Autism Dev. Disord. 40, 1423–1430 (2010).
Google Scholar
Khachadourian, V. et al. Maternal psychiatric diagnosis and comorbidities around pregnancy. Eur. Psychiatry 66, e15 (2023).
Google Scholar
Zaks, N. et al. Association between mental health and reproductive system disorders in women: a systematic review and meta-analysis. JAMA Netw. Open. 6, e238685 (2023).
Google Scholar
Chucri, T. M. et al. A review of immune transfer by the placenta. J. Reprod. Immunol. 87, 14–20 (2010).
Google Scholar
Engelhardt, B. Development of the blood–brain barrier. Cell Tissue Res. 314, 119–129 (2003).
Google Scholar
Grove, J. et al. Identification of common genetic risk variants for autism spectrum disorder. Nat. Genet. 51, 431–444 (2019).
Google Scholar
Ejlskov, L. et al. Prediction of autism risk from family medical history data using machine learning: a national cohort study from Denmark. Biol. Psychiatry Glob. Open Sci. 1, 156–164 (2021).
Google Scholar
Svensson, A. C. et al. Maternal effects for preterm birth: a genetic epidemiologic study of 630,000 families. Am. J. Epidemiol. 170, 1365–1372 (2009).
Google Scholar
Susser, E., Eide, M. G. & Begg, M. Invited commentary: the use of sibship studies to detect familial confounding. Am. J. Epidemiol. 172, 537–539 (2010).
Google Scholar
Lipsitch, M., Tchetgen Tchetgen, E. & Cohen, T. Negative controls: a tool for detecting confounding and bias in observational studies. Epidemiology 21, 383–388 (2010).
Google Scholar
Shattuck, P. T. et al. Timing of identification among children with an autism spectrum disorder: findings from a population-based surveillance study. J. Am. Acad. Child Adolesc. Psychiatry 48, 474–483 (2009).
Google Scholar
Parner, E. T., Schendel, D. E. & Thorsen, P. Autism prevalence trends over time in Denmark: changes in prevalence and age at diagnosis. Arch. Pediatr. Adolesc. Med. 162, 1150–1156 (2008).
Google Scholar
Maenner, M. J. et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2020. MMWR Surveill. Summ. 72, 1–14 (2023).
Google Scholar
Leonard, H. et al. Unpacking the complex nature of the autism epidemic. Res. Autism Spectr. Disord. 4, 548–554 (2010).
Google Scholar
Mandell, D. S., Novak, M. M. & Zubritsky, C. D. Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics 116, 1480–1486 (2005).
Google Scholar
Thomas, T. R. et al. Clinical autism subscales have common genetic liabilities that are heritable, pleiotropic, and generalizable to the general population. Transl. Psychiatry 12, 247 (2022).
Google Scholar
Lee, P. H., Feng, Y.-C. A. & Smoller, J. W. Pleiotropy and cross-disorder genetics among psychiatric disorders. Biol. Psychiatry 89, 20–31 (2021).
Google Scholar
Nudel, R. et al. Maternal pregnancy-related infections and autism spectrum disorder—the genetic perspective. Transl. Psychiatry 12, 334 (2022).
Google Scholar
Karadag, N. et al. Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders. Brain 146, 3392–3403 (2023).
Google Scholar
Smeland, O. B. et al. The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis. Preprint at medRxiv (2023).
Plummer, J. T., Gordon, A. J. & Levitt, P. The genetic intersection of neurodevelopmental disorders and shared medical comorbidities—relations that translate from bench to bedside. Front. Psychiatry 7, 142 (2016).
Google Scholar
Gong, T. et al. Understanding the relationship between asthma and autism spectrum disorder: a population-based family and twin study. Psychol. Med. 53, 3096–3104 (2023).
Google Scholar
Atladóttir, H. O. et al. Association of family history of autoimmune diseases and autism spectrum disorders. Pediatrics 124, 687–694 (2009).
Google Scholar
Koeppen-Schomerus, G., Spinath, F. M. & Plomin, R. Twins and non-twin siblings: different estimates of shared environmental influence in early childhood. Twin Res. 6, 97–105 (2003).
Google Scholar
Kendler, K. S., Ohlsson, H., Lichtenstein, P., Sundquist, J. & Sundquist, K. The nature of the shared environment. Behav. Genet. 49, 1–10 (2019).
Google Scholar
Frisell, T. Invited commentary: sibling-comparison designs, are they worth the effort? Am. J. Epidemiol. 190, 738–741 (2021).
Google Scholar
Sunde, H. F. et al. Genetic similarity between relatives provides evidence on the presence and history of assortative mating. Nat. Commun. 15, 2641 (2024).
Google Scholar
Nordsletten, A. E. et al. Patterns of nonrandom mating within and across 11 major psychiatric disorders. JAMA Psychiatry 73, 354–361 (2016).
Google Scholar
Greenland, S. The effect of misclassification in the presence of covariates. Am. J. Epidemiol. 112, 564–569 (1980).
Google Scholar
Ogburn, E. L. & Vanderweele, T. J. Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders. Biometrika 100, 241–248 (2013).
Google Scholar
Brew, B. K. & Gong, T. Modelling paternal exposure as a negative control. Int. J. Epidemiol. 49, 1053–1054 (2020).
Google Scholar
Taylor, K. et al. Effect of maternal prepregnancy/early-pregnancy body mass index and pregnancy smoking and alcohol on congenital heart diseases: a parental negative control study. J. Am. Heart Assoc. 10, e020051 (2021).
Google Scholar
Keyes, K. M., Davey Smith, G. & Susser, E. Commentary: smoking in pregnancy and offspring health: early insights into family-based and ‘negative control’ studies? Int. J. Epidemiol. 43, 1381–1388 (2014).
Google Scholar
Siklenka, K. et al. Disruption of histone methylation in developing sperm impairs offspring health transgenerationally. Science 350, aab2006 (2015).
Google Scholar
Rodgers, A. B., Morgan, C. P., Bronson, S. L., Revello, S. & Bale, T. L. Paternal stress exposure alters sperm microRNA content and reprograms offspring HPA stress axis regulation. J. Neurosci. 33, 9003–9012 (2013).
Google Scholar
Chen, X. et al. Whole genome bisulfite sequencing of human spermatozoa reveals differentially methylated patterns from type 2 diabetic patients. J. Diabetes Investig. 11, 856–864 (2020).
Google Scholar
Soubry, A. et al. Obesity-related DNA methylation at imprinted genes in human sperm: results from the TIEGER study. Clin. Epigenetics 8, 51 (2016).
Google Scholar
Sasaki, H. & Matsui, Y. Epigenetic events in mammalian germ-cell development: reprogramming and beyond. Nat. Rev. Genet. 9, 129–140 (2008).
Google Scholar
Wolf, J. B. & Wade, M. J. What are maternal effects (and what are they not)? Philos. Trans. R. Soc. B Biol. Sci. 364, 1107–1115 (2009).
Google Scholar
Huang, Q. Q. et al. Examining the role of common variants in rare neurodevelopment disorders. Nature 636, 404–411 (2024).
Google Scholar
Gardener, H., Spiegelman, D. & Buka, S. L. Prenatal risk factors for autism: comprehensive meta-analysis. Br. J. Psychiatry 195, 7–14 (2009).
Google Scholar
Larsson, H. J. et al. Risk factors for autism: perinatal factors, parental psychiatric history, and socioeconomic status. Am. J. Epidemiol. 161, 916–925 (2005).
Google Scholar
Yin, W. et al. Association between parental psychiatric disorders and risk of offspring autism spectrum disorder: a Swedish and Finnish population-based cohort study. Lancet Reg. Health Eur. 40, 100902 (2024).
Google Scholar
Hagberg, K. W., Robijn, A. L. & Jick, S. Maternal depression and antidepressant use during pregnancy and the risk of autism spectrum disorder in offspring. Clin. Epidemiol. 10, 1599–1612 (2018).
Google Scholar
Rai, D. et al. Parental depression, maternal antidepressant use during pregnancy, and risk of autism spectrum disorders: population based case–control study. BMJ 346, f2059 (2013).
Google Scholar
Li, Y.-M. et al. Association between maternal obesity and autism spectrum disorder in offspring: a meta-analysis. J. Autism Dev. Disord. 46, 95–102 (2016).
Google Scholar
Sanchez, C. E. et al. Maternal pre-pregnancy obesity and child neurodevelopmental outcomes: a meta-analysis. Obes. Rev. 19, 464–484 (2018).
Google Scholar
Guo, D., Ju, R., Dai, J. & Zhang, H. Autism spectrum disorders in offspring exposed to maternal gestational diabetes: a meta-analysis and systematic review. Rev. J. Autism Dev. Disord. (2023).
Google Scholar
Chen, S., Zhao, S., Dalman, C., Karlsson, H. & Gardner, R. Association of maternal diabetes with neurodevelopmental disorders: autism spectrum disorders, attention-deficit/hyperactivity disorder and intellectual disability. Int. J. Epidemiol. 50, 459–474 (2021).
Google Scholar
Janecka, M. et al. Association of autism spectrum disorder with prenatal exposure to medication affecting neurotransmitter systems. JAMA Psychiatry 75, 1217–1224 (2018).
Google Scholar
Weisskopf, M. G., Tchetgen Tchetgen, E. J. & Raz, R. Commentary: on the use of imperfect negative control exposures in epidemiologic studies. Epidemiology 27, 365–367 (2016).
Google Scholar
Gjerde, L. C. et al. Maternal perinatal and concurrent depressive symptoms and child behavior problems: a sibling comparison study. J. Child Psychol. Psychiatry 58, 779–786 (2017).
Google Scholar
Gjerde, L. C. et al. Maternal perinatal and concurrent anxiety and mental health problems in early childhood: a sibling-comparison study. Child Dev. 91, 456–470 (2020).
Google Scholar
Bekkhus, M., Lee, Y., Brandlistuen, R. E., Samuelsen, S. O. & Magnus, P. Maternal anxiety and infants birthweight and length of gestation. A sibling design. BMC Psychiatry 21, 609 (2021).
Google Scholar
Petersen, A. H. & Lange, T. What is the causal interpretation of sibling comparison designs? Epidemiology 31, 75–81 (2020).
Google Scholar
Lynge, E., Sandegaard, J. L. & Rebolj, M. The Danish National Patient Register. Scand. J. Public Health 39, 30–33 (2011).
Google Scholar
Mors, O., Perto, G. P. & Mortensen, P. B. The Danish Psychiatric Central Research Register. Scand. J. Public Health 39, 54–57 (2011).
Google Scholar
Pedersen, C. B. The Danish Civil Registration System. Scand. J. Public Health 39, 22–25 (2011).
Google Scholar
Lauritsen, M. B. et al. Validity of childhood autism in the Danish Psychiatric Central Register: findings from a cohort sample born 1990–1999. J. Autism Dev. Disord. 40, 139–148 (2010).
Google Scholar
Sundbøll, J. et al. Positive predictive value of cardiovascular diagnoses in the Danish National Patient Registry: a validation study. BMJ Open 6, e012832 (2016).
Google Scholar
Albaek Jacobsen, H., Jess, T. & Larsen, L. Validity of inflammatory bowel disease diagnoses in the Danish National Patient Registry: a population-based study from the north Denmark region. Clin. Epidemiol. 14, 1099–1109 (2022).
Google Scholar
Thygesen, S. K., Christiansen, C. F., Christensen, S., Lash, T. L. & Sørensen, H. T. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of Patients. BMC Med. Res. Methodol. 11, 83 (2011).
Google Scholar
Chronic Condition Indicator (CCI) for ICD-10-CM (Beta Version) (Agency for Healthcare Research and Quality, 2018).
Greenland, S., Mansournia, M. A. & Altman, D. G. Sparse data bias: a problem hiding in plain sight. BMJ 352, i1981 (2016).
Google Scholar
Schendel, D. E. & Thorsteinsson, E. Cumulative incidence of autism into adulthood for birth cohorts in Denmark, 1980–2012. JAMA 320, 1811–1813 (2018).
Google Scholar
Sandin, S. et al. Advancing maternal age is associated with increasing risk for autism: a review and meta-analysis. J. Am. Acad. Child Adolesc. Psychiatry 51, 477–486 (2012).
Google Scholar
Janecka, M. et al. Parental age and differential estimates of risk for neuropsychiatric disorders: findings from the Danish Birth Cohort. J. Am. Acad. Child Adolesc. Psychiatry 58, 618–627 (2019).
Google Scholar
Biro, M. A., Davey, M.-A., Carolan, M. & Kealy, M. Advanced maternal age and obstetric morbidity for women giving birth in Victoria, Australia: a population-based study. Aust. N. Z. J. Obstet. Gynaecol. 52, 229–234 (2012).
Google Scholar
Daalderop, L. A., Lagendijk, J., Steegers, E. A. P., El Marroun, H. & Posthumus, A. G. Psychological distress during pregnancy and adverse maternal and perinatal health outcomes: the role of socioeconomic status. Int. J. Gynecol. Obstet. 163, 920–930 (2023).
Google Scholar
Delobel-Ayoub, M. et al. Socioeconomic disparities and prevalence of autism spectrum disorders and intellectual disability. PLoS ONE 10, e0141964 (2015).
Google Scholar
Therneau, T. M. & Li, H. Computing the Cox model for case cohort designs. Lifetime Data Anal. (1999).
Google Scholar
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. (1995).
Google Scholar
Palmer, N. et al. Association of sex with recurrence of autism spectrum disorder among siblings. JAMA Pediatr. 171, 1107–1112 (2017).
Google Scholar
Madley-Dowd, P., Rai, D., Zammit, S. & Heron, J. Simulations and directed acyclic graphs explained why assortative mating biases the prenatal negative control design. J. Clin. Epidemiol. 118, 9–17 (2020).
Google Scholar
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016).
link
:max_bytes(150000):strip_icc()/7-Day-No-Sugar-Mediterranean-Diet-Meal-Plan-for-More-Energy-f82d446efc254592899b9927cfd4ac80.jpg "7-Day No-Sugar Mediterranean Diet Meal Plan for More Energy")
