Besga Ariadna, Chyzhyk Darya, González-Ortega Itxaso, Savio Alexandre, Ayerdi Borja, Echeveste Jon, Graña Manuel, González-Pinto Ana
Department of Psychiatry, University Hospital of Alava-Santiago, Vitoria, Spain; Centre for Biomedical Research Network on Mental Health (CIBERSAM), Spain and School of Medicine, University of the Basque Country, Vitoria, Spain.
Curr Alzheimer Res. 2016;13(5):557-65. doi: 10.2174/1567205013666151116125349.
Late Onset Bipolar Disorder (LOBD) is the arousal of Bipolar Disorder (BD) at old age (>60) without any previous history of disorders. LOBD is often difficult to distinguish from degenerative dementias, such as Alzheimer Disease (AD), due to comorbidities and common cognitive symptoms. Moreover, LOBD prevalence is increasing due to population aging. Biomarkers extracted from blood plasma are not discriminant because both pathologies share pathophysiological features related to neuroinflammation, therefore we look for anatomical features highly correlated with blood biomarkers that allow accurate diagnosis prediction. This may shed some light on the basic biological mechanisms leading to one or another disease. Moreover, accurate diagnosis is needed to select the best personalized treatment.
We look for white matter features which are correlated with blood plasma biomarkers (inflammatory and neurotrophic) discriminating LOBD from AD.
A sample of healthy controls (HC) (n=19), AD patients (n=35), and BD patients (n=24) has been recruited at the Alava University Hospital. Plasma biomarkers have been obtained at recruitment time. Diffusion weighted (DWI) magnetic resonance imaging (MRI) are obtained for each subject.
DWI is preprocessed to obtain diffusion tensor imaging (DTI) data, which is reduced to fractional anisotropy (FA) data. In the selection phase, eigenanatomy finds FA eigenvolumes maximally correlated with plasma biomarkers by partial sparse canonical correlation analysis (PSCCAN). In the analysis phase, we take the eigenvolume projection coefficients as the classification features, carrying out cross-validation of support vector machine (SVM) to obtain discrimination power of each biomarker effects. The John Hopkins Universtiy white matter atlas is used to provide anatomical localizations of the detected feature clusters.
Classification results show that one specific biomarker of oxidative stress (malondialdehyde MDA) gives the best classification performance ( accuracy 85%, F-score 86%, sensitivity, and specificity 87%, ) in the discrimination of AD and LOBD. Discriminating features appear to be localized in the posterior limb of the internal capsule and superior corona radiata.
It is feasible to support contrast diagnosis among LOBD and AD by means of predictive classifiers based on eigenanatomy features computed from FA imaging correlated to plasma biomarkers. In addition, white matter eigenanatomy localizations offer some new avenues to assess the differential pathophysiology of LOBD and AD.
迟发性双相情感障碍（LOBD）是指在老年期（>60岁）首次出现双相情感障碍（BD）且既往无任何疾病史。由于合并症和常见的认知症状，LOBD常难以与退行性痴呆，如阿尔茨海默病（AD）相区分。此外，由于人口老龄化，LOBD的患病率正在上升。从血浆中提取的生物标志物缺乏鉴别能力，因为这两种疾病都具有与神经炎症相关的病理生理特征，因此我们寻找与血液生物标志物高度相关的解剖学特征，以实现准确的诊断预测。这可能有助于揭示导致这两种疾病的基本生物学机制。此外，需要准确的诊断来选择最佳的个性化治疗方案。
我们寻找与区分LOBD和AD的血浆生物标志物（炎症和神经营养）相关的白质特征。
在阿拉瓦大学医院招募了健康对照（HC）样本（n = 19）、AD患者样本（n = 35）和BD患者样本（n = 24）。在招募时获取血浆生物标志物。为每个受试者进行扩散加权（DWI）磁共振成像（MRI）检查。
对DWI进行预处理以获得扩散张量成像（DTI）数据，将其简化为分数各向异性（FA）数据。在选择阶段，特征解剖学通过部分稀疏典型相关分析（PSCCAN）找到与血浆生物标志物最大程度相关的FA特征体积。在分析阶段，我们将特征体积投影系数作为分类特征，进行支持向量机（SVM）的交叉验证，以获得每个生物标志物效应的鉴别能力。使用约翰霍普金斯大学白质图谱来提供检测到的特征簇的解剖定位。
分类结果表明，一种特定的氧化应激生物标志物（丙二醛MDA）在区分AD和LOBD时具有最佳的分类性能（准确率85%，F值86%，敏感性和特异性87%）。鉴别特征似乎位于内囊后肢和放射冠上部。
通过基于与血浆生物标志物相关的FA成像计算的特征解剖学特征的预测分类器来支持LOBD和AD之间的对比诊断是可行的。此外，白质特征解剖定位为评估LOBD和AD的不同病理生理学提供了一些新途径。
