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THE ROLE OF SEX IN POLYGENIC RISK FOR SEX-BIASED BRAIN DISORDERS 性别在性别偏倚性脑部疾病多基因风险中的作用

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.552

Arielle Crestol , Dennis van der Meer , Nadine Parker , Ann-Marie de Lange , Espen Hagen , Hannah Oppenheimer , Stener Nerland , Edith Breton , Christian K Tamnes , Ole A. Andreassen , Ingrid Agartz , Claudia Barth

Sex differences in genetic vulnerability have been implicated in psychiatric and neurodegenerative disorders, yet their specific impact on brain health and clinical risk remains poorly understood. Leveraging data from up to 220,836 women and 187,651 men from the UK Biobank (aged 39–81), we assessed how sex and polygenic risk scores (PRSs) for major depressive disorder (PRSMDD), Alzheimer’s disease (PRSAD), schizophrenia (PRSSCZ), and Parkinson’s disease (PRSPD) relate to case-control status and brain age gap (BAG), a neuroimaging marker of brain health. We tested for sex differences in PRSs and performed regression analyses examining associations between sex, PRSs, and either case-control status or BAG. We then compared models with sex-pooled and sex-specific PRSs to explore whether sex-specific PRSs can improve predictive accuracy. While PRSSCZ was higher in women compared to men, no other sex differences were found between PRSs. Our most striking finding was a significant PRSAD-by-sex interaction, in which PRSAD conferred greater risk for AD diagnosis in women compared to men. Consistently, the women-only PRSAD model outperformed the sex-pooled model, while no differences were observed between sex-pooled and men-only models. By contrast, sex-pooled PRS models outperformed sex-specific PRS models for MDD, SCZ, and PD. No sex-by-PRS interactions were significantly associated with BAG. However, men presented with higher BAG values than women, indicative of an older brain age. Further, higher PRSMDD, higher PRSAD, and lower PRSPD were each associated with higher BAG, irrespective of sex. Finally, BAG model performance did not differ between sex-pooled and sex-specific PRS models. Our findings highlight that sex moderates AD genetic risk for diagnostic status in middle-to-late-life adults, and as such, tailoring PRSs by sex may improve risk assessment for AD. While sex-specific PRSs offered limited value for the other disorders, our findings suggest that the value of sex-specific PRSs will likely grow with increased statistical power.

遗传易感性的性别差异与精神和神经退行性疾病有关，但它们对大脑健康和临床风险的具体影响仍知之甚少。利用来自英国生物银行（UK Biobank）的多达220,836名女性和187,651名男性（39-81岁）的数据，我们评估了重度抑郁症（PRSMDD）、阿尔茨海默病（PRSAD）、精神分裂症（PRSSCZ）和帕金森病（PRSPD）的性别和多基因风险评分（PRSs）与病例对照状态和脑年龄差距（BAG）（脑健康的神经影像学标志物）的关系。我们测试了PRSs的性别差异，并进行了回归分析，检验了性别、PRSs和病例对照状态或BAG之间的关系。然后，我们比较了性别池和性别特异性PRSs模型，以探索性别特异性PRSs是否可以提高预测准确性。虽然女性的PRSSCZ高于男性，但在prsz之间没有发现其他性别差异。我们最引人注目的发现是PRSAD与性别的显著相互作用，其中PRSAD赋予女性比男性更大的AD诊断风险。一致地，仅限女性的PRSAD模型优于性别混合模型，而性别混合模型和仅限男性的模型之间没有差异。相比之下，性别混合的PRS模型在MDD、SCZ和PD方面的表现优于性别特异性的PRS模型。无性别- prs交互作用与BAG显著相关。然而，男性的BAG值高于女性，表明大脑年龄较大。此外，不论性别，较高的PRSMDD、较高的PRSAD和较低的PRSPD均与较高的BAG相关。最后，BAG模型的性能在性别池和性别特定的PRS模型之间没有差异。我们的研究结果强调，在中老年成年人中，性别调节AD诊断状态的遗传风险，因此，按性别定制PRSs可能会改善AD的风险评估。虽然性别特异性PRSs对其他疾病的价值有限，但我们的研究结果表明，性别特异性PRSs的价值可能会随着统计能力的提高而增加。

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引用次数: 0

LONGITUDINAL DATA ANALYSIS REVEALS SEX DIFFERENCES IN GENETIC RISK FACTORS UNDERLYING WORSENING DEPRESSIVE SYMPTOMS AND COGNITIVE DECLINE IN OLDER ADULTS 纵向数据分析揭示了老年人抑郁症状恶化和认知能力下降的遗传风险因素的性别差异

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.520

Jessica Dennis, Karanvir Singh

Neuropsychiatric symptoms such as depression and apathy are among the earliest signs of dementia, are more common in females than in males, and worsen in-step with cognitive impairment. These symptoms are caused by the brain changes associated with dementia, are difficult to treat, and are not just a predictable consequence of the effects of dementia on quality of life. We sought to understand the genetic and non-genetic factors that influence depressive symptom emergence and progression across the cognitive decline spectrum. We analyzed repeated measures of cognitive and depressive symptoms spanning up to 9 years from ∼8,500 adults aged 65+ at baseline participating in the Canadian Longitudinal Study on Aging. We modeled repeated measures using hierarchical (mixed effect) models and latent class growth models, which allow for multiple possible latent growth trajectories within the study population. We found that known dementia genetic risk factors (APOE e4 allele count and a polygenic score for Alzheimer’s disease) associated with faster cognitive decline in both sexes. Using latent class growth models, we identified three different depressive symptom trajectory groups (persistent low, N=7346; persistent high, N=447; and new-onset, N=974), and we found that faster cognitive decline increased the risk of new-onset depressive symptoms to a greater extent in females than in males, in models adjusted for sociodemographic factors. APOE e4 carriers were more likely to experience new-onset depressive symptoms and cognitive decline compared to non-carriers, regardless of sex, but the polygenic score for Alzheimer’s disease predicted new-onset depressive symptoms and cognitive decline uniquely in females. Our results suggest that new-onset depressive symptoms and accelerated cognitive decline capture a dementia prodrome, especially in females. Moreover, our approach demonstrates the value of longitudinal data analysis in genetic studies for understanding unique patient subgroups, which can be leveraged in future GWAS efforts.

Disclosure: Nothing to disclose.

抑郁和冷漠等神经精神症状是痴呆症的早期症状，在女性中比在男性中更常见，并随着认知障碍而恶化。这些症状是由与痴呆症相关的大脑变化引起的，很难治疗，而且不仅仅是痴呆症对生活质量影响的可预测后果。我们试图了解影响认知衰退谱系中抑郁症状出现和进展的遗传和非遗传因素。我们分析了参与加拿大老龄化纵向研究的~ 8,500名65岁以上的成年人长达9年的认知和抑郁症状的重复测量。我们使用分层（混合效应）模型和潜在类别增长模型对重复测量进行建模，这些模型允许在研究人群中存在多种可能的潜在增长轨迹。我们发现，已知的痴呆症遗传风险因素（APOE e4等位基因计数和阿尔茨海默病的多基因评分）与两性认知能力下降更快有关。使用潜在类别增长模型，我们确定了三个不同的抑郁症状轨迹组（持续低，N=7346；持续高，N=447；和新发，N=974），我们发现，在调整了社会人口因素的模型中，更快的认知衰退增加了女性新发抑郁症状的风险，其程度大于男性。与非携带者相比，APOE e4携带者更有可能出现新发抑郁症状和认知能力下降，无论性别如何，但阿尔茨海默病的多基因评分仅在女性中预测新发抑郁症状和认知能力下降。我们的研究结果表明，新发的抑郁症状和加速的认知衰退捕获了痴呆的前驱症状，特别是在女性中。此外，我们的方法证明了纵向数据分析在遗传研究中的价值，以了解独特的患者亚组，这可以在未来的GWAS工作中加以利用。披露：没有什么可披露的。

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引用次数: 0

PUTTING POLYGENIC SCORES IN CONTEXT: HOW INTERSECTIONAL FACTORS AFFECT RELATIVE AND ABSOLUTE GENETIC RISK 把多基因得分放在上下文中：交叉因素如何影响相对和绝对遗传风险

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.546

Mihael Cudic , Justin Tubbs , Tian Ge , Jordan Smoller

Background

The clinical utility of polygenic scores (PGS) is known to vary when training and test samples differ in ancestry. Recent work also suggests that variation in demographic and environmental contexts can affect PGS performance. However, little attention has been given to the ubiquitous phenomenon of intersectionality—where individuals simultaneously belong to multiple demographic and environmental contexts—and its impact on relative and absolute genetic risk.

Methods

We examined how lifetime odds ratios (ORs) and absolute risk (AR) for high-PGS individuals differ across intersectional contexts in the UK Biobank (UKB; n = 375,054, British-European-like ancestry), with a particular focus on major depressive disorder (MDD). Additional phenotypes studied included atrial fibrillation, coronary artery disease, type 2 diabetes, hypercholesterolemia, asthma, and obesity. PGS were computed using PRS-CS and current GWAS summary statistics. We analyzed 106 two-way intersections across sociodemographic factors (sex, age, income, smoking, alcohol intake, and deprivation). Replication was conducted in the All of Us Research Program (AoU; African-like: n = 36,552; European-like: n = 99,477).

Results

Odds ratios for major depression varied substantially across sociodemographic contexts, with even greater variability across intersectional combinations. In two-way intersections, the average maximal OR variation was 56% across all phenotypes. Although absolute risk differences were more moderate after adjusting for baseline prevalence within a context, intersectional effects were still observed. For example, high-PGS individuals with low income had an average 1.0 percentage-point lower AR across phenotypes when using a context-aware versus context-unaware model. For major depression specifically, the AR was 3.1 percentage points lower among those also reporting low alcohol intake in UKB (3.6 points lower in AoU European-like ancestry). Results were broadly consistent across cohorts, with the strongest replication for depression risk observed in the European-like All of Us sample.

Conclusion

We show that intersectional contexts can substantially shape relative genetic risk. Future clinical applications may need to consider incorporating contextual effects to enhance the precision and equity of patient-specific genetic risk assessments.

当训练样本和测试样本的血统不同时，多基因评分（PGS）的临床应用会有所不同。最近的研究还表明，人口和环境背景的变化会影响PGS的表现。然而，很少有人注意到普遍存在的交叉性现象，即个体同时属于多种人口和环境背景，以及它对相对和绝对遗传风险的影响。方法我们研究了英国生物银行（UKB; n = 375,054，英国-欧洲血统）中高pgs个体的终生优势比（ORs）和绝对风险（AR）在交叉背景下的差异，特别关注重度抑郁症（MDD）。研究的其他表型包括房颤、冠状动脉疾病、2型糖尿病、高胆固醇血症、哮喘和肥胖。使用PRS-CS和当前GWAS汇总统计计算PGS。我们分析了106个跨社会人口因素（性别、年龄、收入、吸烟、饮酒和贫困）的双向交叉点。在我们所有人研究计划中进行了重复研究（AoU；非洲人：n = 36,552；欧洲人：n = 99,477）。结果重度抑郁症的患病率在不同的社会人口背景下差异很大，在不同的交叉组合中差异更大。在双向交叉中，所有表型的平均最大OR变异为56%。虽然在背景下调整基线患病率后，绝对风险差异更为温和，但仍然观察到交叉效应。例如，当使用上下文感知与上下文不感知模型时，低收入的高pgs个体在表型上的AR平均低1.0个百分点。特别是对于重度抑郁症，在英国报告酒精摄入量低的人中，AR降低了3.1个百分点（在AoU欧洲血统中降低了3.6个百分点）。结果在各个队列中大致一致，在类似欧洲人的“我们所有人”样本中观察到的抑郁症风险的重复性最强。结论本研究表明，交叉背景可以在很大程度上影响相对遗传风险。未来的临床应用可能需要考虑纳入情境效应，以提高患者特异性遗传风险评估的准确性和公平性。

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引用次数: 0

ELECTRONIC HEALTH RECORDS AND BIOBANKS IN THE ERA OF COMPUTATIONAL AND GENOMIC PSYCHIATRY 计算和基因组精神病学时代的电子健康记录和生物银行

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.486

Franjo Ivankovic Chair , Julia Sealock Co-chair , Carol Mathews Discussant

<div><div>This symposium will explore how the analysis of large-scale electronic health record (EHR) and biobank data is revolutionizing psychiatric research and driving novel discoveries impacting clinical care. Presentations highlight the utility of EHRs to study and identify sociodemographic biases in psychiatric care, leveraging the rich data across collaborative networks of EHRs to describe and validate novel subtypes of psychiatric disorders, using digital phenotyping for precision psychiatry insights, and utilizing the rich genomic data to develop resources to power the next generation of biological insights.</div><div>The symposium will begin with an overview of the PsycheMERGE network, an NIMH-funded collaboration across 11 institutions that leverages the resources and existing infrastructure of biobanks paired with EHRs across the country to provide a translational “sandbox” in which to evaluate the potential clinical impact of psychiatric genetic findings in a low-risk research setting. The talk will discuss how analysis of multimodal data has yielded “real-world” support for the hypothesis of an immune-metabolic subtype of depression with implications for management.</div><div>The following talk will focus on longitudinal modeling in the All of Us (AoU) dataset to replicate the bidirectional association between activity and mood, as measured by the Patient Health Questionnaire (PHQ-9), highlighting the potential of EHR-integrated digital phenotyping to advance precision psychiatry by informing behavior-based prevention and treatment strategies.</div><div>The third talk will present the two-process model of sleep regulation, a well-established model of sleep disruption in depression, and examine how this model directly translates into observable digital health behaviors that are highly associated with EHR-diagnosed depression and represent interpretable mechanistic phenotypes for further genomic and precision psychiatry approaches.</div><div>The final presentation will showcase a novel reference panel built from over 515,000 individuals from AoU and AnVIL data. In addition to being the largest reference panel to date, this panel prioritizes diversity, encompassing over 250,000 samples from non-European ancestries – a representation nearly twice the size of the entire TOPMed reference panel. The panel includes 101,982 of African and 90,553 individuals of admixed American ancestries. This resource will significantly improve the accuracy of genotype imputation, particularly for rare variants and underrepresented populations, empowering novel discoveries in psychiatric genetics. It will be made widely available for phasing and imputing genotype array and low-pass sequencing data through Broad Institute of MIT and Harvard.</div><div>By showcasing these diverse applications of EHRs, we aim to illuminate the power of computational psychiatry and genomics, when combined with rich phenotypic data, to improve diagnosis, treatment, and ultimately

本次研讨会将探讨大规模电子健康记录（EHR）和生物银行数据的分析是如何彻底改变精神病学研究和推动影响临床护理的新发现的。报告强调了电子病历在精神病学护理中研究和识别社会人口统计学偏差的效用，利用电子病历协作网络中的丰富数据来描述和验证精神疾病的新亚型，使用数字表型进行精确的精神病学见解，并利用丰富的基因组数据开发资源以推动下一代生物学见解。研讨会将首先概述PsycheMERGE网络，该网络由nimh资助，由11家机构合作，利用全国各地生物库的资源和现有基础设施与电子病历相结合，提供一个翻译“沙盒”，在低风险研究环境中评估精神病学遗传发现的潜在临床影响。本次讲座将讨论多模态数据分析如何为抑郁症的免疫代谢亚型假说提供了“现实世界”的支持，并对治疗产生了影响。接下来的演讲将重点关注我们所有人（AoU）数据集中的纵向建模，以复制活动和情绪之间的双向关联，由患者健康问卷（PHQ-9）测量，强调ehr集成数字表型通过告知基于行为的预防和治疗策略来推进精确精神病学的潜力。第三个讲座将介绍睡眠调节的双过程模型，一个完善的抑郁症睡眠中断模型，并研究该模型如何直接转化为可观察的数字健康行为，这些行为与ehr诊断的抑郁症高度相关，并为进一步的基因组和精确精神病学方法提供可解释的机制表型。最后的展示将展示一个新颖的参考面板，该面板由来自AoU和AnVIL数据的515,000多人构建而成。除了是迄今为止最大的参考小组外，该小组还优先考虑多样性，包括超过250,000个来自非欧洲血统的样本-这几乎是整个TOPMed参考小组的两倍。该小组包括101,982名非洲人和90,553名美国混血儿。这一资源将显著提高基因型插入的准确性，特别是对于罕见变异和代表性不足的人群，赋予精神病学遗传学的新发现。它将通过麻省理工学院和哈佛大学的Broad研究所广泛用于分相和输入基因型阵列和低通测序数据。通过展示电子病历的这些不同应用，我们的目标是阐明计算精神病学和基因组学的力量，当与丰富的表型数据相结合时，改善诊断、治疗，并最终改善精神疾病患者的生活。

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引用次数: 0

Risk of manic switch and suicidal outcomes in bipolar depression treated with esketamine: A one-year retrospective cohort study of 2126 patients. 艾氯胺酮治疗双相抑郁症躁狂转换和自杀结局的风险：一项为期一年的2126例患者回顾性队列研究

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 Epub Date: 2025-08-06 DOI: 10.1016/j.euroneuro.2025.07.006

Ting-Hui Liu, Jheng-Yan Wu, Po-Yu Huang, Wan-Lin Cheng, Chih-Cheng Lai

Objective: To evaluate the safety of esketamine in bipolar depression, focusing on suicide-related outcomes and manic switch across timeframe and demographic subgroups.

Methods: This retrospective cohort study was conducted in May 2025 using data from the TriNetX global collaborative network. Adults with bipolar depression treated with esketamine plus a mood stabilizer were propensity score-matched 1:1 to patients who received mood stabilizers alone. The primary outcomes were suicide-related events and manic switches across 1-7, 1-30, 1-90, 1-180, and 1-365 day intervals.

Results: After matching, 2126 patients (mean age, 47.0 years; 63 % female) were included. Esketamine use was associated with significantly lower risk of suicide-related outcomes at 1-7 days (hazard ratio [HR] = 0.439; 95 % CI, 0.256-0.753), 1-30 days (HR = 0.485; 95 % CI, 0.324-0.726), 1-90 days (HR = 0.641; 95 % CI, 0.456-0.901), and 1-365 days (HR = 0.754; 95 % CI, 0.577-0.985). Risk of manic switch was not increased and was significantly lower at 1-180 days (HR = 0.643; 95 % CI, 0.442-0.935) and 1-365 days (HR = 0.673; 95 % CI, 0.477-0.950). Subgroup analyses showed consistent suicide risk reduction across age, sex, and race. Female patients exhibited a significantly lower risk of manic switch at longer intervals, an effect not observed in males.

Conclusions: Our real-world study suggests that esketamine, when used alongside mood stabilizers, is a safe and potentially effective treatment for bipolar depression, demonstrating sustained anti-suicidal benefits without an increased risk of manic switch across both short- and long-term follow-up and across different patient subgroups.

目的：评估艾氯胺酮治疗双相抑郁症的安全性，重点关注自杀相关结果和跨时间框架和人口亚组的躁狂转换。方法：这项回顾性队列研究于2025年5月进行，使用TriNetX全球协作网络的数据。接受艾氯胺酮加心境稳定剂治疗的成人双相抑郁症患者与单独接受心境稳定剂治疗的患者倾向评分匹配率为1:1。主要结果是自杀相关事件和躁狂转换在1-7天、1-30天、1-90天、1-180天和1-365天的间隔。结果：经配对后，2126例患者(平均年龄47.0岁；（63%为女性）。使用艾氯胺酮与1-7天自杀相关结局的风险显著降低相关(风险比[HR] = 0.439；95% CI, 0.256-0.753)， 1-30天(HR = 0.485；95% CI, 0.324-0.726)， 1-90天(HR = 0.641；95% CI, 0.456-0.901)， 1-365天(HR = 0.754；95% ci, 0.577-0.985)。1 ~ 180天躁狂转换风险未增加，且显著降低(HR = 0.643；95% CI, 0.442-0.935)和1-365天(HR = 0.673；95% ci, 0.477-0.950)。亚组分析显示，不同年龄、性别和种族的自杀风险都有所降低。女性患者在较长的间隔时间内表现出明显较低的躁狂转换风险，而在男性患者中没有观察到这种效果。结论：我们的真实世界研究表明，当与情绪稳定剂一起使用时，艾氯胺酮是一种安全且潜在有效的双相抑郁症治疗方法，在短期和长期随访以及不同患者亚组中均显示出持续的抗自杀益处，而不会增加躁狂转换的风险。

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引用次数: 0

LIVING HAPPILY EVER AFTER: WHAT INFLUENCES ENDURING MENTAL HEALTH? 幸福生活：什么影响持久的心理健康？

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.485

Christel M. Middeldorp , Lianne De Vries , Meike Bartels

Enduring mental health (EMH) is a stable state of mental health over time. More insight into factors associated with EMH can aid prevention of mental health problems. Previous research on EMH has primarily focused on the absence of mental health problems, neglecting the equally important dimension of presence of wellbeing. In this study, EMH is defined by the absence of mental health problems and/or the presence of higher wellbeing over time.

Data on twins and their family members registered in the large Netherlands Twin Register will be examined. Individuals will be included when mental health and/or wellbeing data are available in four or more surveys, to create the EMH phenotype. For more than 17,000 individuals genotypes are also available.

Classical twin analyses will be performed to calculate the heritability of EMH. Furthermore, associations will be presented with polygenic scores (PGS) and educational attainment, self esteem, stressful life events, neuroticism, optimism, loneliness, social support, exercise and self reported health. Besides PGS for mental disorders and traits, PGS for educational attainment, wellbeing, neuroticism, loneliness, childhood maltreatment and risky behavior will be included.

First, univariate regressions will be performed. The significantly associated variables will then be included in multiple logistic regression analyses, using family as a grouping variable to account for clustering. Variables as assessed during adolescents and polygenic scores that are related to EMH can be seen as potential predictors for EMH, whereas variables assessed in the last survey in adulthood can be seen as potential outcomes of EMH.

This project follows up on a project using childhood data on enduring mental health (Alrouh et al, under revision for the Journal of the American Academy of Child and Adolescent Psychiatry). Using measures between age 3 and age 12, 37% of the sample had EMH. This was associated with parental education (OR (low) =0.77 [0.70-0.86]; OR (middle) = 0.88 [0.82-0.95]), child academic achievement (OR=1.07 [1.03,1.12]), and child wellbeing (OR=1.44 [1.35,1.54]), and was weakly associated with ADHD PGS. The heritability was estimated at 54%. These findings are now extended with findings in adults, over a longer timespan and with a more comprehensive analysis of factors that could be associated with EMH.

持久心理健康（EMH）是一种长期稳定的心理健康状态。更深入地了解与EMH相关的因素有助于预防心理健康问题。先前对有效市场假说的研究主要集中在心理健康问题的缺失上，而忽视了同样重要的幸福感维度。在这项研究中，EMH被定义为没有心理健康问题和/或随着时间的推移存在更高的幸福感。将审查在大型荷兰双胞胎登记册中登记的双胞胎及其家庭成员的数据。当心理健康和/或幸福数据在四次或更多的调查中可用时，个人将被包括在内，以创建EMH表型。对于17000多个个体，基因型也是可用的。将进行经典的双胞胎分析来计算EMH的遗传力。此外，多基因得分（PGS）与受教育程度、自尊、压力生活事件、神经质、乐观、孤独、社会支持、锻炼和自我报告的健康状况之间存在关联。除了精神障碍和特征方面的PGS，还包括教育程度、幸福感、神经质、孤独感、童年虐待和危险行为方面的PGS。首先，将进行单变量回归。然后将显著相关的变量包含在多重逻辑回归分析中，使用家庭作为分组变量来解释聚类。在青少年时期评估的变量和与EMH相关的多基因评分可以被视为EMH的潜在预测因素，而在成年期最后一次调查中评估的变量可以被视为EMH的潜在结果。这个项目是在一个使用儿童持久心理健康数据的项目的基础上进行的（Alrouh等人，正在为《美国儿童和青少年精神病学学会杂志》进行修订）。在3岁到12岁之间进行测量，37%的样本患有EMH。这与父母教育有关(OR (low) =0.77 [0.70-0.86]；OR（中） = 0.88[0.82-0.95])、儿童学业成绩（OR=1.07[1.03,1.12]）和儿童幸福感（OR=1.44[1.35,1.54]），且与ADHD PGS呈弱相关。遗传率估计为54%。这些发现现在扩展到成年人的研究，在更长的时间跨度和更全面的分析可能与EMH相关的因素。

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引用次数: 0

SLEEP MICRO-ARCHITECTURE BIOMARKERS AND GENETIC RISK FOR SCHIZOPHRENIA 睡眠微结构生物标志物与精神分裂症的遗传风险

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.460

Shaun Purcell , Nataliia Kozhemiako , Jennifer Pan , The GRINS consortium

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations, are altered in individuals with schizophrenia (SCZ), with large (>1 SD) effect sizes and collectively offering high predictive power in a case/control diagnostic context (AUC = 0.93). Further, NREM metrics show increased patient-to-patient variability, driven in part by accelerated age-related effects and medication regimen. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, with relevance to both the etiological heterogeneity of SCZ as well as potential iatrogenic effects of antipsychotic medication.

In this presentation, we consider how human genetics may help to unpick the causal pathways between sleep neurophysiology biomarkers and SCZ. Specifically, following a brief review of our previous work identifying and replicating NREM biomarkers associated with SCZ disease status, we will report 1) an application of polygenic risk score (PRS) analysis to the GRINS sample, aiming to test whether genetic risk for disease is partially mediated by these NREM metrics, 2) a simulation study to quantify the prospects for using PRS-based analyses to study disease-biomarker relationships, 3) parallel work in mice characterizing the effects of mutations in SCZ-associated genes on analogous NREM EEG metrics, and 4) a broader review of some of the challenges faced by current genetic approaches to study the role of sleep in psychiatric disease.

睡眠神经生理学的多个方面，包括脑电图（EEG）指标，如非快速眼动（NREM）纺锤波和慢振荡，在精神分裂症（SCZ）患者中发生改变，具有大的（>1 SD）效应量，并且在病例/对照诊断背景下提供了高的预测能力（AUC = 0.93）。此外，NREM指标显示患者之间的差异增加，部分原因是与年龄相关的加速效应和药物治疗方案。总的来说，我们的研究结果表明，SCZ患者的非快速眼动睡眠缺陷可以客观地、大规模地测量，这与SCZ的病因异质性以及抗精神病药物的潜在医源性作用有关。在本报告中，我们考虑人类遗传学如何帮助解开睡眠神经生理学生物标志物和SCZ之间的因果途径。具体来说，在简要回顾我们之前识别和复制与SCZ疾病状态相关的NREM生物标志物的工作之后，我们将报告1)将多基因风险评分（PRS）分析应用于GRINS样本，旨在测试疾病的遗传风险是否部分由这些NREM指标介导；2)模拟研究，量化使用基于PRS的分析来研究疾病-生物标志物关系的前景。3)在小鼠实验中，研究scz相关基因突变对类似NREM脑电图指标的影响；4)对当前研究睡眠在精神疾病中的作用的遗传方法所面临的一些挑战进行更广泛的回顾。

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引用次数: 0

NEW DIRECTIONS FOR PGC-ANX GENOMICS RESEARCH: PANIC DISORDER, EPIGENETICS, BRAIN STRUCTURE, AND GENE-ENVIRONMENT MODERATION pgc-anx基因组学研究的新方向：恐慌症、表观遗传学、脑结构、基因-环境调节

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.461

John Hettema Chair , Nora Strom Co-chair , Jordan Smoller Discussant

Until recently, research in the genetics of anxiety disorders has suffered from the lack of powerful datasets and significant genetic association findings. Without that valid genetic basis, the application of genetics to fuel anxiety research has been limited compared to other psychiatric disorders. The recently published PGC-ANX meta-analysis has provided a major advancement in anxiety genetics. This symposium will cover a variety of follow-up anxiety genomic research directions. Nora Strom from Humboldt-Universität will present preliminary results from a large GWAS of panic disorder. Dr. Shaunna Clark from Texas A&M University will review the results of the largest meta-analysis of epigenome-wide association studies of anxiety disorders. Dr Mary Mufford from University of Cape Town will discuss the genetic connections between anxiety susceptibility and brain structure. Dr. Brad Verhulst from Texas A&M University will examine genome-wide moderation for anxiety and depression as a function of adverse life events. Dr. Jordan Smoller from Harvard University will serve as the Discussant.

直到最近，焦虑障碍的遗传学研究一直缺乏强大的数据集和重要的遗传关联发现。如果没有有效的遗传基础，与其他精神疾病相比，遗传学在促进焦虑研究中的应用受到了限制。最近发表的PGC-ANX荟萃分析为焦虑遗传学提供了重大进展。本次研讨会将涵盖各种后续焦虑基因组研究方向。来自Humboldt-Universität的诺拉·斯特罗姆将呈现惊恐障碍大规模GWAS的初步结果。来自德州农工大学的Shaunna Clark博士将对焦虑症表观基因组关联研究的最大荟萃分析结果进行综述。开普敦大学的玛丽·穆福德博士将讨论焦虑易感性和大脑结构之间的遗传联系。德州农工大学的Brad Verhulst博士将研究焦虑和抑郁的全基因组调节作为不良生活事件的功能。来自哈佛大学的Jordan Smoller博士将担任讨论者。

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引用次数: 0

DISSECTING THE GENETICS OF PANIC DISORDER, AGORAPHOBIA, AND PANIC ATTACKS: THE FIRST DISORDER-SPECIFIC LARGE-SCALE GENOME-WIDE ASSOCIATION STUDY FROM PGC-ANXIETY 剖析惊恐障碍、广场恐怖症和惊恐发作的遗传学：首个针对pgc -焦虑症的大规模全基因组关联研究

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.462

Nora Strom , Brittany Mitchell , John Hettema , Manuel Mattheisen , Iiris Hovatta , Angelika Erhardt

Panic disorder (PD) is a disabling anxiety disorder with a moderate heritability estimated at 30–40%. It often co-occurs with agoraphobia, which is characterized by anxiety in situations perceived as unsafe or difficult to escape, frequently leading to panic attacks. Despite its public health impact, progress in identifying robust genetic risk loci for PD has lagged behind that of other psychiatric conditions. To address this, we will conduct the first large-scale genome-wide association study (GWAS) meta-analysis of PD (with or without agoraphobia) within the Psychiatric Genomics Consortium Anxiety Disorders Working Group (PGC-ANX), leveraging international collaboration to maximize discovery power.

We will aggregate phenotypic and genetic data from over 100K individuals with lifetime PD across multiple international cohorts and consortia. Standardized quality control and imputation protocols will be applied across datasets in accordance with our standard operation procedure. All individual GWASs will consecutively be meta-analyzed. Beyond primary GWAS, secondary analyses will include functional annotation of associated loci, gene-set enrichment, and genetic correlation analyses to explore shared genetic architecture with related psychiatric and somatic phenotypes.

Since panic attacks are also common in other psychiatric disorders - such as anxious depression, OCD, PTSD, and schizophrenia - we will conduct an extended cross-disorder analysis to investigate whether panic attacks represent a transdiagnostic phenotype with distinct genetic features. Additionally, we will examine the genetic relationship between PD and dimensional anxiety phenotypes. Given that genetic liability can aggregate within families, we will include anamnestic information on familial anxiety to test whether individuals with a positive family history show increased genetic risk. Finally, we will explore whether genetic liability is enriched in individuals with an early age of onset.

Preliminary results from Data Freeze 1 will be presented. This meta-analysis aims to significantly advance our understanding of the biological basis of panic disorder and related anxiety dimensions. The findings will highlight the importance of large-scale, collaborative efforts in psychiatric genetics and inform future work toward precision psychiatry in anxiety disorders.

惊恐障碍（PD）是一种致残性焦虑障碍，遗传率中等，估计为30-40%。它通常与广场恐惧症同时发生，广场恐惧症的特征是在被认为不安全或难以逃离的情况下感到焦虑，经常导致惊恐发作。尽管它对公共卫生有影响，但在识别PD的强大遗传风险位点方面的进展落后于其他精神疾病。为了解决这个问题，我们将在精神病学基因组学联盟焦虑障碍工作组（PGC-ANX）内进行PD（有或没有广场恐怖症）的第一次大规模全基因组关联研究（GWAS）荟萃分析，利用国际合作来最大限度地提高发现能力。我们将收集来自多个国际队列和联盟的100,000多名终身PD患者的表型和遗传数据。标准化的质量控制和归算协议将根据我们的标准操作程序在数据集上应用。所有个体GWASs将被连续进行meta分析。除了初级GWAS，二级分析将包括相关位点的功能注释、基因集富集和遗传相关性分析，以探索与相关精神和躯体表型共享的遗传结构。由于惊恐发作在其他精神疾病中也很常见——如焦虑性抑郁症、强迫症、创伤后应激障碍和精神分裂症——我们将进行扩展的跨障碍分析，以调查惊恐发作是否代表具有独特遗传特征的跨诊断表型。此外，我们将检查PD和维度焦虑表型之间的遗传关系。鉴于遗传责任可以在家庭中聚集，我们将包括家族焦虑的记忆信息，以测试具有阳性家族史的个体是否显示遗传风险增加。最后，我们将探讨遗传倾向是否在早期发病的个体中丰富。将介绍数据冻结1的初步结果。本荟萃分析旨在显著提高我们对惊恐障碍的生物学基础和相关焦虑维度的理解。这一发现将突出精神病学遗传学中大规模合作的重要性，并为焦虑症的精确精神病学的未来工作提供信息。

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引用次数: 0

PHARMACOPOLYGENIC PREDICTORS FOR ANTIDEPRESSANT RESPONSE: CURRENT STATUS, FUTURE DIRECTIONS 抗抑郁反应的药物多基因预测因子：现状和未来方向

IF 6.7 2区医学 Q1 CLINICAL NEUROLOGY

European Neuropsychopharmacology

Pub Date : 2025-10-01 DOI: 10.1016/j.euroneuro.2025.08.502

Cathryn Lewis

Antidepressants are one of the most widely prescribed medications worldwide, but only one-third of people respond to the first drug prescribed, and there are few predictors of who will respond to which antidepressant. This trial-and-error strategy of finding an effective drug is harmful to patients and families and imposes a burden to health services and the economy.

Pharmacogenetics offers a promising route to personalised prescribing. This symposium introduction will summarise current progress, describe studies underway, and outline the potential for genetic testing for antidepressant prescribing.

Most antidepressants are metabolised by CYP2C19, CYP2D6 and CYP2C9, but genetic variation in these genes accounts for only a small proportion of response to antidepressants, suggesting broader genetic contributions. The largest genome-wide association study for antidepressant response, conducted by the Psychiatric Genomics Consortium, assessed remission and percentage change in depressive symptoms in 5,000 patients from clinical trials and research studies. The study reported a SNP-based heritability of 13%, with modest polygenic prediction between studies. Notably, antidepressant response was only weakly associated with polygenic scores for depression, indicating a largely distinct genetic architecture between susceptibility to depression and treatment response. New results from a targeted GWAS of selective serotonin reuptake inhibitors (SSRIs) will be reported, providing response predictors by drug class.

As the polygenic basis of antidepressant response becomes clearer, the primary barrier to expanding our understanding of the genetic predictors becomes sample size. Few studies collect the longitudinal information necessary to robustly evaluate response to treatment, and although clinical trials are the gold standard for rigorous assessment of drug response, their scale is limited.

Harnessing real world data from electronic health records, or assessing self-reported response from patients, will allow us to define proxy phenotypes of antidepressant response, and perform sufficiently powerful genetic studies. In this talk, I will assess the potential of these novel sources of treatment response phenotypes, which we are investigating in the AMBER project. I will outline a plan for expanding genetic studies of antidepressant response to build pharmacopolygenic predictors that might be powerful enough to test and implement clinically, with the potential of personalised prescribing for depression.

Disclosure: Myriad Genetics, Advisory Board

抗抑郁药是世界上最广泛使用的药物之一，但只有三分之一的人对第一种药物有反应，而且很少有预测谁会对哪种抗抑郁药有反应。这种寻找有效药物的试错策略对患者和家庭有害，并对卫生服务和经济造成负担。药物遗传学为个性化处方提供了一条有希望的途径。本次研讨会的介绍将总结目前的进展，描述正在进行的研究，并概述抗抑郁药物处方基因检测的潜力。大多数抗抑郁药是由CYP2C19、CYP2D6和CYP2C9代谢的，但这些基因的遗传变异只占抗抑郁药反应的一小部分，这表明遗传作用更广泛。由精神病学基因组学协会（Psychiatric Genomics Consortium）进行的最大的抗抑郁药物反应全基因组关联研究，评估了5000名临床试验和研究中患者抑郁症状的缓解和百分比变化。该研究报告了基于snp的遗传率为13%，研究之间有适度的多基因预测。值得注意的是，抗抑郁反应与抑郁症的多基因评分只有微弱的相关性，这表明抑郁易感性和治疗反应之间存在很大不同的遗传结构。选择性5 -羟色胺再摄取抑制剂（SSRIs）靶向GWAS的新结果将被报道，提供药物类别的反应预测因子。随着抗抑郁反应的多基因基础变得更加清晰，扩大我们对遗传预测因子的理解的主要障碍是样本量。很少有研究收集必要的纵向信息来可靠地评估对治疗的反应，尽管临床试验是严格评估药物反应的金标准，但其规模有限。利用来自电子健康记录的真实世界数据，或评估患者自我报告的反应，将使我们能够定义抗抑郁药反应的代理表型，并进行足够有力的基因研究。在这次演讲中，我将评估这些治疗反应表型的新来源的潜力，这是我们在AMBER项目中正在研究的。我将概述一项计划，扩大抗抑郁药物反应的基因研究，以建立药物多基因预测指标，这些指标可能足够强大，可以在临床上进行测试和实施，并有可能为抑郁症提供个性化处方。披露：Myriad Genetics，顾问委员会

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引用次数: 0