基因变异可预测抗忧郁剂的反应


  【24drs.com】研究者确认了与重度忧郁患者(major depressive disorder,MDD)对bupropion之反应有关的一种基因变异。
  
  研究者使用基因检测公司23andMe, Inc的客户资料发现,对于有rs1908557基因变异者,使用bupropion治疗无效的机率比较高。
  
  他们也发现几个「基因组」与长期忧郁、昼夜节律和血管内皮生长因子途径有关,这些与bupropion之反应分析有很大的关联。
  
  第一作者、纽泽西Titusville Janssen Research & Development, LLC神经科学综合解决方案暨信息科学主任Qingqin Li博士表示,最有趣的发现是,bupropion有反应者和无反应者,在对重度忧郁症患者很重要的生物过程有关之基因的差异相对较多[相较于其它人类基因组而言]。
  
  Li博士表示,这些生物过程包括睡眠障碍和神经新生,这些与「遗传」[即:可以透过遗传风险因素进行解释之疾病风险比例]在自我报告与协会的临床确认世代报告之间相似,这代表根据自我报告信息的基因组对于确定所选的治疗结果和疾病状态具有可证明之信息,且有助于促进在治疗反应差异之理解。
  
  该研究在线发表于9月13日的转译精神病学。
  
  研究团队指出,大约有30种抗忧郁药可用于MDD,治疗反应因产生效益的起始时间、整体效果、效益持续时间等而异,遗传变异会促成在药物特定性、类别特定性、或抗忧郁剂广泛治疗无反应/阻抗等之差异。
  
  他们分析了238,000名23andMe客户的自我报告信息,包括大约48,000名表示有在治疗忧郁症。他们使用表型和基因型资料,对四组表型进行了全基因组关联研究(GWAS):无治疗阻抗忧郁症vs治疗阻抗忧郁症;选择性血清素再摄取抑制剂有反应者vs无反应者;citalopram/escitalopram有反应者vs无反应者;以及bupropion有反应者vs无反应者。
  
  他们报告指出,进行的12项GWAS分析中,只有bupropion有反应者vs无反应者之分析获得的基因轨迹达到全基因组显著性阈值。每一个rs1908557-C等位基因都与对bupropion无反应之机率较高有关(胜算比1.35)。研究者报告指出,在研究对象中,C等位基因的频率相对比较常见(次要等位基因频率 = 25%)。
  
  他们写道,这项研究发现最终将需要在临床确认的样本中再现,以进一步仔细研究忧郁症患者对于bupropion之治疗反应的基因差异。他们指出,在MDD患者与健康对照组之间,rs1908557除了与已知会呈现容量的两个脑部区域有轻微相关,rs1908557的生物学意义是未知的。
  
  他们进一步承认,单靠遗传变异是不可能实现临床可行的预测诊断测试。最终需要使用各种预测因子的更全面性方法,以预测某特定药物类别的治疗结果,且具有足够的敏感性和特异性,以保证它的临床使用。
  
  Li博士表示,我们在这领域的研究正持续进行著。透过增加研究的样本量,收集更多资料以扩展当前的分析,再现报告的显著结果,或者在样本数更大时研究其它类的抗忧郁药。搜集的其它临床样本也可有助于再现报告的结果。
  
  纽约市西奈山Icahn医学院神经科学副教授Scott Russo博士在访问中指出,我认为这是一篇不错的报告。
  
  未参与该研究的Russo博士解释,使用23andMe的客户资料是有趣的,我认为这将会包括通常不会参加研究的一些人,而这样的数据-有点类似于脸书采集-可以触及一组潜在的参与者,而在传统研究设计则会是人数不足。对于那些在传统研究获得之效益差的患者,在基因组学和遗传学与特定疾病或治疗反应之关联的理解方面,将会带来极大的利益。
  
  Russo博士表示,临床上,我们最需要的是,可以预测哪里些人对哪里种治疗有反应,这是第一步要达到的。Russo博士指出,精神病学的一个主要目标,是整合生物诊断标准且可以用于预测疾病和治疗反应。
  
  资料来源:http://www.24drs.com/
  
  Native link:Gene Variant May Predict Antidepressant Response

Gene Variant May Predict Antidepressant Response

By Megan Brooks
Medscape Medical News

Researchers have identified a genetic variant associated with response to bupropion in patients with major depressive disorder (MDD).

Using data from customers of genetic testing company 23andMe, Inc, they found that for individuals with the genetic variant rs1908557, the odds were higher that treatment with bupropion would be ineffective.

They also identified several "gene sets" associated with long-term depression, circadian rhythm, and the vascular endothelial growth factor pathway that were enriched in the bupropion response analysis.

"The most interesting finding is that there were relatively more genetic differences between bupropion responders and nonresponders in genes implicated in biological processes important for patients with major depressive disorder [than genes elsewhere in the human genome]," first author Qingqin Li, PhD, scientific director, Neuroscience Integrative Solutions and Informatics, Janssen Research & Development, LLC, Titusville, New Jersey, told Medscape Medical News.

"Those biological processes included sleep disturbance and neurogenesis. These together with the 'heritability' [ie, the proportion of disease risk that could be explained by genetic risk factors] similarity between self-report and clinically ascertained cohorts reported by consortium efforts suggest that phenotype based on self-report information may prove informative for ascertaining selected treatment outcome and disease status and help to advance the understanding of difference in treatment response," said Dr Li.

The study was published online September 13 in Translational Psychiatry.

Pinpointing the Right Drug

There are roughly 30 antidepressants available for MDD. Response to treatment varies in time to onset of benefit, overall efficacy, and duration of effect. Genetic variability may contribute to the differences in drug-specific, class-specific, or antidepressant-wide treatment nonresponse/resistance, the study team notes in their article.

They analyzed self-reported information from 238,000 23andMe customers, including roughly 48,000 who reported being treated for depression. Using phenotype and genotype data, they conducted a genome-wide association study (GWAS) on four groups of phenotypes: non-treatment-resistant depression vs treatment-resistant depression; selective serotonin reuptake inhibitor responders vs nonresponders; citalopram/escitalopram responders vs nonresponders; and bupropion responders vs nonresponders.

Of a total of 12 GWAS analyses performed, only the bupropion responders vs nonresponders analysis yielded a locus that reached the genome-wide significance threshold, they report. Each copy of the rs1908557-C allele was associated with higher odds of not responding to bupropion (odds ratio, 1.35). "The frequency of C allele was relatively common (minor allele frequency = 25%) in the study population," the investigators report.

"This finding will ultimately require replication in clinically ascertained samples to further dissect the genetic basis of treatment response to bupropion among depression patients," they write. "The biological significance of rs1908557 is unknown except that rs1908557 is also marginally associated with two brain regions known to exhibit volumetric difference between MDD subjects and healthy controls," they add.

They further acknowledge that "genetic variants alone are unlikely to deliver clinically actionable predictive diagnostic tests. A more comprehensive approach using a composite signature of predictors ultimately may be required to predict treatment outcome to a particular drug class with sufficient sensitivity and specificity to warrant its use in the clinic."

"Our studies in this area are ongoing," Dr Li told Medscape Medical News. "Additional data collected could be used to augment the current analysis by increasing the study sample size, replicate the reported significant finding, or to study additional class of antidepressants when the sample size becomes larger. Other clinical samples being collected could also help to replicate the reported findings."

Unique Dataset

"I think this is a good paper," Scott Russo, PhD, associate professor of neuroscience, Icahn School of Medicine at Mount Sinai in New York City, noted in an interview with Medscape Medical News.

"What's interesting about using 23andMe customers is that I think it will include populations of people that typically wouldn't take part in a research study, and so that data – kind of like Facebook mining – could reach a group of potential participants that are underrepresented in traditional research settings," explained Dr Russo, who was not involved in the study. "For genomics and genetics and understanding linkages to particular diseases or treatment responses, that would be a huge benefit in enriching for patients who you have low power for in your more traditional studies.

"Clinically," Dr Russo said, "what we need the most is to be able to predict who is going to respond to what treatment. This is a first step toward that." One major goal in psychiatry, Dr Russo added, is to incorporate biological diagnostic criteria and be able to use that to predict not just disease but also treatment response.

The genotype-phenotype association analysis was funded by Janssen Research and Development, LLC. Four of the five authors are employees of the company. The other author is an employee of 23andMe. Dr Russo has received funding from Janssen Pharmaceuticals to conduct research in the past but is not currently funded by Janssen.

Transl Psychiatry. Published online September 13, 2016.

    
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