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Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited.
JAMA Psychiatry ( IF 25.8 ) Pub Date : 2022-09-01 , DOI: 10.1001/jamapsychiatry.2022.2075
Nikolaos Koutsouleris 1, 2, 3 , Christos Pantelis 4 , Dennis Velakoulis 4 , Philip McGuire 2 , Dominic B Dwyer 1 , Maria-Fernanda Urquijo-Castro 1 , Riya Paul 1 , Sen Dong 1 , David Popovic 1 , Oemer Oeztuerk 1 , Joseph Kambeitz 5 , Raimo K R Salokangas 6 , Jarmo Hietala 6 , Alessandro Bertolino 7 , Paolo Brambilla 8, 9 , Rachel Upthegrove 10, 11 , Stephen J Wood 12, 13, 14 , Rebekka Lencer 15, 16 , Stefan Borgwardt 15, 17 , Carlo Maj 18 , Markus Nöthen 19 , Franziska Degenhardt 19, 20 , Maryna Polyakova 21, 22 , Karsten Mueller 21 , Arno Villringer 21 , Adrian Danek 23 , Klaus Fassbender 24 , Klaus Fliessbach 25, 26 , Holger Jahn 27 , Johannes Kornhuber 28 , Bernhard Landwehrmeyer 29 , Sarah Anderl-Straub 29 , Johannes Prudlo 30 , Matthis Synofzik 26, 31 , Jens Wiltfang 26, 32 , Lina Riedl 33 , Janine Diehl-Schmid 33 , Markus Otto 29 , Eva Meisenzahl 34 , Peter Falkai 1 , Matthias L Schroeter 21, 22 ,
Affiliation  

Importance The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far. Objective To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD). Design, Setting, and Participants This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022. Main Outcomes and Measures Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery. Results Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery. Conclusions and Relevance Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.

中文翻译:

使用多模态机器学习探索精神病与额颞叶痴呆之间的联系:重访早发性痴呆。

重要性 严重精神障碍的行为和认知症状与痴呆症的症状重叠。然而,共享的大脑改变仍然存在争议,迄今为止尚未探索它们与处于高危疾病阶段的患者的相关性。目的 使用机器学习比较行为变异性额颞叶痴呆 (bvFTD)、阿尔茨海默病 (AD) 和精神分裂症的结构磁共振成像 (MRI) 模式的表达;根据社会人口统计学、临床和生物学数据估计 bvFTD 和精神分裂症患者的可预测性;并检查具有临床高危 (CHR) 状态的精神病或新发抑郁症 (ROD) 患者的预后价值、遗传基础和进展。设计、设置和参与者这项研究包括来自 5 个队列的 1870 人,包括 (1) 患有 bvFTD (n = 108)、确诊 AD (n = 44)、轻度认知障碍或早期 AD (n = 96)、精神分裂症 (n = 157) 或重度抑郁症 (n = 102) 的患者推导和比较诊断模式和 (2) CHR (n = 160) 或 ROD (n = 161) 患者以测试模式的预后相关性和进展。健康个体 (n = 1042) 用于年龄相关和队列相关的数据校准。数据收集时间为 1996 年 1 月至 2019 年 7 月,分析时间为 2020 年 4 月至 2022 年 4 月。社会人口统计学、临床和生物学数据;具有高模式表达与低模式表达的 CHR 和 ROD 患者的 2 年功能结果和遗传可分离性;和模式进展从基线到后续 MRI 扫描的患者 nonrecovery 与 preserved recovery。结果 1870 名患者中,902 名 (48.2%) 为女性,平均 (SD) 年龄为 38.0 (19.3) 岁。包括前额叶、岛叶和边缘体积减少的 bvFTD 模式在精神分裂症患者(157 人中的 65 人 [41.2%])和重度抑郁症患者(102 人中的 22 人 [21.6%])中比颞叶边缘 AD 模式(28 人中的 28 人)表现得更多157 [17.8%] 和 102 个中的 3 个 [2.9%])。bvFTD 表达由高体重指数、精神运动迟缓、情感去抑制和偏执观念预测 (R2 = 0.11)。精神分裂症模式在 108 名 bvFTD 患者中的 92 名 (85.5%) 中表达,并且与 C9orf72 变异、脑脊液中的寡克隆带、认知障碍和较年轻有关 (R2 = 0.29)。bvFTD 和精神分裂症模式表达预测了 CHR 患者 2 年的心理社会障碍,并通过额颞叶痴呆、AD 和精神分裂症的多基因风险评分进行了预测。结果与 AD 或大脑加速老化无关。最后,1 年 bvFTD/精神分裂症模式进展将未恢复的患者与恢复正常的患者区分开来。结论和相关性 bvFTD 和精神病之间可能存在神经生物学联系,侧重于前额叶和显着系统的改变。需要进一步的跨诊断研究来确定 2 种疾病谱之间神经解剖学界面的共同病理生理过程。
更新日期:2022-08-03
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