The role of APOE-ɛ4 and beta amyloid in the differential rate of recovery from ECT: a review

Neurobiological Highlights of Cognitive Impairment in Psychiatric Disorders

This review is focused on several psychiatric disorders in which cognitive impairment is a major component of the disease, influencing life quality. There are plenty of data proving that cognitive impairment accompanies and even underlies some psychiatric disorders. In addition, sources provide information on the biological background of cognitive problems associated with mental illness. This scientific review aims to summarize the current knowledge about neurobiological mechanisms of cognitive impairment in people with schizophrenia, depression, mild cognitive impairment and dementia (including Alzheimer's disease).The review provides data about the prevalence of cognitive impairment in people with mental illness and associated biological markers.

Plasma Amyloid-β and Alzheimer's Disease-Related Changes in Late-Life Depression

To elucidate an involvement of amyloid dysmetabolism in the pathophysiology of depression, we investigated associations of plasma amyloid-β (Aβ) levels with Alzheimer's disease-related changes in neuroimaging and cognitive dysfunction in patients with late-life depression. Higher plasma Aβ40, but not Aβ42 nor Aβ40/Aβ42 ratio, was associated with higher degree of parahippocampal atrophy and lower verbal fluency performance. Indeed, high plasma Aβ40 predicted poor cognitive prognosis of depressed patients with mild cognitive impairment. As an anti-depressive treatment, electroconvulsive therapy (ECT) resulted in a marginally significant reduction of plasma Aβ40 compared to pharmacotherapy alone, suggesting protective effects of ECT against amyloid dysmetabolism.

Brain Stimulation in Alzheimer's Disease

Brain stimulation techniques can modulate cognitive functions in many neuropsychiatric diseases. Pilot studies have shown promising effects of brain stimulations on Alzheimer's disease (AD). Brain stimulations can be categorized into non-invasive brain stimulation (NIBS) and invasive brain stimulation (IBS). IBS includes deep brain stimulation (DBS), and invasive vagus nerve stimulation (VNS), whereas NIBS includes transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), electroconvulsive treatment (ECT), magnetic seizure therapy (MST), cranial electrostimulation (CES), and non-invasive VNS. We reviewed the cutting-edge research on these brain stimulation techniques and discussed their therapeutic effects on AD. Both IBS and NIBS may have potential to be developed as novel treatments for AD; however, mixed findings may result from different study designs, patients selection, population, or samples sizes. Therefore, the efficacy of NIBS and IBS in AD remains uncertain, and needs to be further investigated. Moreover, more standardized study designs with larger sample sizes and longitudinal follow-up are warranted for establishing a structural guide for future studies and clinical application.

The potential of predictive analytics to provide clinical decision support in depression treatment planning

PURPOSE OF REVIEW

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD).

RECENT FINDINGS

Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem.

SUMMARY

Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

Biomarkers for Early Diagnostic of Mild Cognitive Impairment in Type-2 Diabetes Patients: A Multicentre, Retrospective, Nested Case-Control Study

Background

Both type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) are common age-associated disorders and T2DM patients show an increased risk to suffer from AD, however, there is currently no marker to identify who in T2DM populations will develop AD. Since glycogen synthase kinase-3β (GSK-3β) activity, ApoE genotypes and olfactory function are involved in both T2DM and AD pathogenesis, we investigate whether alterations of these factors can identify cognitive impairment in T2DM patients.

Methods

The cognitive ability was evaluated using Minimum Mental State Examination (MMSE) and Clinical Dementia Rating (CDR), and the mild cognitive impairment (MCI) was diagnosed by Petersen's criteria. GSK-3β activity in platelet, ApoE genotypes in leucocytes and the olfactory function were detected by Western/dot blotting, the amplification refractory mutation system (ARMS) PCR and the Connecticut Chemosensory Clinical Research Center (CCCRC) test, respectively. The odds ratio (OR) and 95% confidence intervals (95% CI) of the biomarkers for MCI diagnosis were calculated by logistic regression. The diagnostic capability of the biomarkers was evaluated by receiver operating characteristics (ROC) analyses.

Findings

We recruited 694 T2DM patients from Jan. 2012 to May. 2015 in 5 hospitals (Wuhan), and 646 of them met the inclusion criteria and were included in this study. 345 patients in 2 hospitals were assigned to the training set, and 301 patients in another 3 hospitals assigned to the validation set. Patients in each set were randomly divided into two groups: T2DM without MCI (termed T2DM-nMCI) or with MCI (termed T2DM-MCI). There were no significant differences for sex, T2DM years, hypertension, hyperlipidemia, coronary disease, complications, insulin treatment, HbA1c, ApoE ε2, ApoE ε3, tGSK3β and pS9GSK3β between the two groups. Compared with the T2DM-nMCI group, T2DM-MCI group showed lower MMSE score with older age, ApoE ε4 allele, higher olfactory score and higher rGSK-3β (ratio of total GSK-3β to Ser9-phosphorylated GSK-3β) in the training set and the validation set. The OR values of age, ApoE ε4 gene, olfactory score and rGSK-3β were 1.09, 2.09, 1.51, 10.08 in the training set, and 1.06, 2.67, 1.47, 7.19 in the validation set, respectively. The diagnostic accuracy of age, ApoE ε4 gene, olfactory score and rGSK-3β were 0.76, 0.72, 0.66, 0.79 in the training set, and 0.70, 0.68, 0.73, 0.79 in the validation set, respectively. These four combined biomarkers had the area under the curve (AUC) of 82% and 86%, diagnostic accuracy of 83% and 81% in the training set and the validation set, respectively.

Interpretation

Aging, activation of peripheral circulating GSK-3β, expression of ApoE ε4 and increase of olfactory score are diagnostic for the mild cognitive impairment in T2DM patients, and combination of these biomarkers can improve the diagnostic accuracy.

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ApoE ε4 gene, platelet GSK-3β activation, olfactory dysfunction and aging are non-invasive, affordable and accessible biomarkers for diagnosing mild cognitive impairment in type 2 diabetes mellitus patients, and the combination of these non-invasive, affordable and accessible biomarkers can improve the accuracy of the diagnosis.

Epidemiological studies show that type 2 diabetes mellitus is an independent risk factor of Alzheimer disease, and a large proportion of diabetic patients will develop Alzheimer disease, but no early diagnostic tool to identify them. We find that ApoE ε4 gene, platelet GSK-3β activation, olfactory dysfunction and aging are early markers for dementia in type 2 diabetes patients, and combination of these non-invasive markers can improve the diagnostic accuracy. These findings shed light on the early identification in type 2 diabetes population who will develop Alzheimer disease and thus enable early intervention to this currently incurable neurodegenerative disorder.