COMBINING MENDELIAN RANDOMISATION WITH DEPRESSION TRAJECTORIES TO IDENTIFY DEVELOPMENTALLY SPECIFIC PREDICTORS OF CHANGE IN DEPRESSIVE SYMPTOMS

IF 6.1 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology Pub Date : 2024-10-01 DOI:10.1016/j.euroneuro.2024.08.092

Robyn Wootton , Richard Parker , Michael Lawton , Kate Tilling

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引用次数: 0

Abstract

Prevalence of depression is increasing, especially amongst adolescents and young adults, representing a key risk period where intervention is critical. When using Mendelian randomisation (MR) to identify causal risk factors for depression, estimates are limited to average lifetime effects, rather than being specific to developmental stages.

Methods. We have combined trajectories of depressive symptoms with MR to identify developmentally specific risk factors. We used repeated measures of depressive symptoms (short Moods and Feelings Questionnaire) in the ALSPAC cohort, with 11 repeated assessments covering ages 9 to 27 years. First, we used a repeated measures multi-level model (MLM) to describe the average trajectory of depressive symptoms. Linear splines split by knot points were used to explain the non-linear pattern of growth. Second, we used latent class analysis to explore heterogeneity in depression trajectories. Third, we combined both trajectory models with genetic instruments for depression (positive control) and with modifiable risk factors for depression.

Our models included 44,611 repeated assessments of sMFQ from 6,422 unique individuals. Our best fitting MLM trajectory had three linear splines corresponding to puberty (9-14.5 years), adolescence (14.5-21 years) and early adulthood (21-27 years). Latent classes were stable low, decreasing, transient, increasing and stable high. Positive control genetic instrument for MDD predicted trajectories, most strongly membership into the increasing and stable high class. Genetic instruments for BMI and educational attainment were not associated with change in population average depressive symptoms at any of the different developmental stages nor with class membership. This could suggest no causal effects of these risk factors at these developmental stages, or low power.

We are continuing to develop our methods, test power and incorporate additional risk factors. We believe that combining outcome trajectories with MR analyses has wide ranging application to improve specificity of causal effects and recommendations for intervention development.

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将 "泯灭随机法 "与抑郁轨迹相结合，确定抑郁症状变化的发育特异性预测因素

抑郁症的发病率正在上升，尤其是在青少年和年轻成年人中，这是一个关键的风险期，干预至关重要。当使用孟德尔随机法（MR）来确定抑郁症的因果风险因素时，估计结果仅限于平均终生效应，而不是针对特定的发展阶段。我们将抑郁症状的轨迹与孟德尔随机化相结合，以确定发育阶段的特定风险因素。我们在ALSPAC队列中使用了抑郁症状的重复测量方法（情绪和感觉简易问卷），共进行了11次重复评估，年龄涵盖9至27岁。首先，我们使用重复测量多层次模型（MLM）来描述抑郁症状的平均轨迹。我们使用按结点分割的线性样条来解释非线性增长模式。其次，我们使用潜类分析来探索抑郁轨迹的异质性。第三，我们将两个轨迹模型与抑郁的遗传工具（阳性对照）和可改变的抑郁风险因素结合起来。我们的最佳拟合 MLM 轨迹有三个线性样条，分别对应青春期（9-14.5 岁）、青春期（14.5-21 岁）和成年早期（21-27 岁）。潜伏类别为稳定低、下降、短暂、上升和稳定高。MDD 的正对照基因工具预测了轨迹，其中最强烈的是上升和稳定高类别。体重指数（BMI）和教育程度的遗传工具与不同发育阶段人群平均抑郁症状的变化无关，也与类别成员资格无关。这可能表明这些风险因素在这些发展阶段没有产生因果效应，或者说这些因素的作用力较低。我们正在继续开发我们的方法、测试作用力并纳入更多的风险因素。我们相信，将结果轨迹与 MR 分析相结合，可以提高因果效应的特异性，并为干预措施的制定提供建议，具有广泛的应用前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Neuropsychopharmacology 医学-精神病学

CiteScore

10.30

自引率

5.40%

发文量

730

审稿时长

41 days

期刊介绍： European Neuropsychopharmacology is the official publication of the European College of Neuropsychopharmacology (ECNP). In accordance with the mission of the College, the journal focuses on clinical and basic science contributions that advance our understanding of brain function and human behaviour and enable translation into improved treatments and enhanced public health impact in psychiatry. Recent years have been characterized by exciting advances in basic knowledge and available experimental techniques in neuroscience and genomics. However, clinical translation of these findings has not been as rapid. The journal aims to narrow this gap by promoting findings that are expected to have a major impact on both our understanding of the biological bases of mental disorders and the development and improvement of treatments, ideally paving the way for prevention and recovery.