Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, 751 24 Uppsala, Sweden.
Int J Mol Sci. 2022 May 23;23(10):5856. doi: 10.3390/ijms23105856.
The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene-environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.
青春期的形成阶段在成年期技能和能力的发展中起着至关重要的作用。受心理健康状况影响的青少年有自杀和社交及学业受损的风险。基因-环境互补对涉及精神疾病的分子机制的贡献强调了需要分析表观遗传标记，如 DNA 甲基化 (DNAm) 和非编码 RNA。然而，大量和多样化的生物信息学和统计方法，涉及统计模型的混杂因素、多重测试调整方法的应用、关于 DNAm 在组织间相关性的问题，以及结果中性别依赖性差异，都对结果的解释提出了挑战。基于广泛性焦虑障碍 (GAD) 和抑郁障碍 (MDD) 的例子，我们阐明了目前在分析表观遗传学方面方法工具的应用和认识。统计稳健性是更好地理解和解释表观遗传修饰的必要前提，并有助于为精神疾病的个性化治疗找到新的靶点。
