Vinh Philip B, Verhulst Brad, Maes Hermine H M, Dolan Conor V, Neale Michael C
Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, USA.
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Behav Genet. 2025 Jan;55(1):59-70. doi: 10.1007/s10519-024-10207-9. Epub 2024 Nov 26.
Causal inference is inherently complex and relies on key assumptions that can be difficult to validate. One strong assumption is population homogeneity, which assumes that the causal direction remains consistent across individuals. However, there may be variation in causal directions across subpopulations, leading to potential heterogeneity. In psychiatry, for example, the co-occurrence of disorders such as depression and substance use disorder can arise from multiple sources, including shared genetic or environmental factors (common causes) or direct causal pathways between the disorders. A patient diagnosed with two disorders might have one recognized as primary and the other as secondary, suggesting the existence of different types of comorbidity. For example, in some individuals, depression might lead to substance use, while in others, substance use could lead to depression. We account for potential heterogeneity in causal direction by integrating the Direction of Causation (DoC) model for twin data with finite mixture modeling, which allows for the calculation of individual-level likelihoods for alternate causal directions. Through simulations, we demonstrate the effectiveness of using the Direction of Causation Twin Mixture (mixDoC) model to detect and model heterogeneity due to varying causal directions.
因果推断本质上很复杂，且依赖于一些难以验证的关键假设。一个强有力的假设是总体同质性，即假设因果方向在个体间保持一致。然而，亚群体间的因果方向可能存在差异，从而导致潜在的异质性。例如，在精神病学中，抑郁症和物质使用障碍等疾病的共现可能源于多种因素，包括共同的遗传或环境因素（共同原因）或疾病之间的直接因果途径。被诊断患有两种疾病的患者可能有一种被认定为原发性，另一种为继发性，这表明存在不同类型的共病情况。例如，在一些个体中，抑郁症可能导致物质使用，而在另一些个体中，物质使用可能导致抑郁症。我们通过将双胞胎数据的因果方向（DoC）模型与有限混合模型相结合来考虑因果方向上的潜在异质性，这使得我们能够计算不同因果方向的个体水平似然性。通过模拟，我们证明了使用因果方向双胞胎混合（mixDoC）模型来检测和建模因因果方向变化而产生的异质性的有效性。
