探討憂鬱症治療療效變異:憂鬱症治療療效預測之臨床特性、腦波及遺傳特徵研究

Investigation of the treatment variation of major depression and prediction of treatment response of antidepressants effects using clinical characteristics, genetic data, and electroencephalogram tool

黃孝先(Shiau-Shian Huang)

指導教授 ： 郭柏秀

國立臺灣大學/公共衛生學院/流行病學與預防醫學研究所/博士(2022年)

https://doi.org/10.6342/NTU202200365

摘要

憂鬱症是一常見且嚴重的精神疾病，其特性反覆發作容易形成慢性化，影響病人甚鉅，也是所有疾病造成失能負擔排行第二名的疾病，是相當重要的公衛議題。藥物一直在發展進步，然而研究顯示有接受治療的病人當中，超過一半無法達到症狀緩解，持續受到疾病的影響，有許多人進展成難治型憂鬱症。在臨床上患者的治療反應存在相當大的變異性，因此值得探討其背後原因。可能原因之一是憂鬱症群體的異質性，醫師透過診斷症狀學，評估眾多憂鬱症狀來診斷患者，囊括了許多不同特性的患者，患者基因特性也可能有很大的差別。另一方面憂鬱症患者常併有其他精神科診斷或是內外科的共病，也使得病情複雜化影響治療效果。探討這些遺傳特性、臨床共病對於療效的變異有助於了解疾病潛在機轉。探討療效預測因子，找出重要的生物標記，將可協助診斷與制定相關的治療計畫。遺傳訊息屬於靜態資訊，進一步尋找療效的動態預測因子對於臨床治療的指引是很重要的。近年來針對憂鬱症研究，許多學者將心力投注於非侵入性、經濟效應性高的腦部檢查，如腦電波。過往一些小型研究利用腦波功率譜發現具有潛力可以用來預測療效的指標，然而結果重現性並不高。近期許多研究將焦點轉至腦部功能性連結與憂鬱症的關聯性。綜合上述，本研究有幾個研究目標:(1)研究漢氏憂鬱量表分數，執行因素分析探討憂鬱個案分類，降低異質性；(2a)研究憂鬱症治療效果相關基因位點；(2b) 研究憂鬱症藥物治療副作用相關基因位點；(3)利用多基因風險評分探討帶有憂鬱症疾病位點與療效之關聯性；(4)研究難治型憂鬱症臨床早期特性及終身特性；(5)研究共病於難治型憂鬱症風險之影響性；(6)探討腦波功能性連結在健康對照組與憂鬱患者的差異性；(7)探討功能性連結訊號與療效關聯性。本研究期望能了解憂鬱症疾患的異質性，探討治療變異原因，以推論生物機制，結合動態、靜態預測因子，甚至將具有潛力的指標結合，以協助未來在重鬱症診斷、與預估療效的參考。本論文包含三種研究設計:(1)基因研究; (2)世代追蹤研究; (3)臨床腦波觀察性研究。研究最後發現憂鬱症狀分數可以降維區分為五個因子，在五個因子中也發現許多與療效相關的基因位點。多基因風險評分發現五個因子中somatic anxiety有著最顯著的關係。本研究也報告許多抗憂鬱劑副作用相關位點。憂鬱症療效基因進一步的路徑分析發現，與免疫、神經功能相關。世代研究發現難治型憂鬱症，在憂鬱患者占35%。我們發現了許多早期及終生的風險因子，例如初期使用較高的鎮靜安眠藥劑量或是女性有較高的風險變成難治型憂鬱症。患者有較多的精神科共病也有加成風險，接近七成未來變成難治型憂鬱症，值得早期注意。腦波研究則發現患者初期的功能性連結較健康對照組差，在治療一週之後有所提升並且接近健康對照組的表現。而對於治療有反應的患者比起無反應組，在高頻的腦波頻帶顯示有較好的功能性連結訊號，且此現象沒有隨著治療而改變。隨著治療而改變的訊號主要出現在低頻的訊號。患者功能性連結的改善(betweenness centrality)與患者症狀學改善在部分結果呈現正相關，其結果對於未來預測患者療效提供更進一步的研究指引。

關鍵字

憂鬱症 ； 治療效果變異 ； 難治型憂鬱症 ； 基因路徑分析 ； 全基因組 ； 共病症 ； 腦波 ； 腦部功能性網路連結 ； 多基因風險評分 ； 治療模式

並列摘要

Major depressive disorder (MDD) is a severe and common mental disorder. Patients with MDD often suffer from frequent relapse and recurrence. MDD has become one of the important public health issues in the 21st century. Although the development of drugs has been progressing, studies have shown that more than half of the patients are unable to achieve remission. Many people develop into treatment-resistant depression (TRD). There is considerable clinical variability in treatment response, so it is important to explore the reasons behind it. One of the reasons may be the heterogeneity of the etiology. From the perspective of diagnostic system of major depression, the criteria encompass many different characteristics. The genetic characteristics of each patient may be different from each other. On the other hand, patients with depression often have other psychiatric or medical comorbidities, which also complicates the condition and affects the treatment response. It is important to explore the influence of these genetic characteristics and clinical comorbidities on the efficacy. It is also important to explore the predictive factors of treatment response and to identify important biomarkers, which will assist in formulation of related preventive policies. In addition, genetic information is static information, and further searching for dynamic predictors of treatment response is very important. In recent years, many scholars in the study of major depression have focused their efforts on non-invasive, effective brain examinations, such as electroencephalography. Some small studies in the past have found potential indicators by analyzing power spectrum that can be used to predict treatment effects, but the reproducibility of the results is limited. Recent studies have shifted the focus to the relationship between functional connectivity of the brain and depression, which is worthy of further exploration. Based on the above, this research has several research goals (1): To analyze heterogeneity of MDD by perform factors analysis of Hamilton Depression Rating Scale (HAM-D) score and to explore the potential classification of patients with depression; (2a) To study the gene loci related to the treatment effect of depression; (2b) To identify potential genetic loci for adverse effect to antidepressants; (3) Using polygenic risk scores to explore the relationship between depression loci and treatment-responsive effect by different syndromal factors; (4) To study the early clinical characteristics of TRD; (5) To investigate the influence of comorbidities on the risk of TRD using the time-to-event (TRD occurring) method and method of population attributable fraction; (6) To explore the differences of electroencephalography (EEG) functional network connectivity (FNC) between healthy controls and patients; (7) To investigate the correlation between FNC and treatment response. This study hopes to understand the heterogeneity of depression, explore the causes of treatment variation, infer the biological mechanism, and use dynamic and static predictors, to assist in the diagnosis of major depression and the estimated treatment response in the future. Three studies were included in this thesis: (1)a Genetic study; (2)a TRD cohort study; (3)a clinical EEG study. The results found that depressive symptom scores can be divided into five syndromal factors by exploratory factor analysis. Many gene loci related to treatment response were also found in the five factors, and further polygenic risk score analysis found that somatic anxiety was most correlated with treatment response among the five factors. This study also reported loci associated with antidepressant side effects. Further pathway analysis of the treatment responsive gene loci found that these loci were related to immune and neurological functions. The prevalence of TRD in this study was up to 35%. This study found many early and lifetime risk factors, such as initial use of higher dose of sedative-hypnotics or antidepressants and female, with a higher risk of becoming TRD. Patients with more psychiatric comorbidities have a higher risk of TRD and nearly 70% patients become TRD during the ten-year follow-up period, which is worthy of early attention. The EEG study found that the patients’ EEG FNC at baseline was lower compared with the controls. After one week treatment, patient’s FNC improved and it was close to the value of the healthy control. Patients who responded to treatment had higher FNC in the high-frequency band frequency than non-responders both before and after treatment. Among treatment responder, FNC in low-frequency band (delta) improved with receiving antidepressant treatment. The change in the patient's FNC (betweenness centrality) was also positively correlated with the change in the patient's depression scores. The results provide information of future direction to investigate treatment response in MDD.

並列關鍵字

Major depression ； Treatment-resistant depression ； Electroencephalography ； Treatment response variation ； Syndromal factors ； Genome-wide ； Pathway analysis ； Side effects ； Comorbidities ； Prescription pattern ； Functional network connectivity

參考文獻

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