Macrophage Migration Inhibitory Factor as a Potential Plasma Biomarker of Cognitive Impairment in Cerebral Small Vessel Disease.

As the pathogenesis of cerebral small vessel disease with cognitive impairment (CSVD-CI) remains unclear, identifying effective biomarkers can contribute to the clinical management of CSVD-CI. This study recruited 54 healthy controls (HCs), 60 CSVD-CI patients, and 57 CSVD cognitively normal (CSVD-CN) patients. All participants underwent neuropsychological assessments and multimodal magnetic resonance imaging. Macrophage migration inhibitory factors (MIFs) were assessed in plasma. The least absolute shrinkage and selection operator model was used to determine a composite marker. Compared with HCs or CSVD-CN patients, CSVD-CI patients had significantly increased plasma MIF levels. In CSVD-CI patients, plasma MIF levels were significantly correlated with multiple cognitive assessment scores, plasma levels of blood-brain barrier (BBB)-related indices, white matter hyperintensity Fazekas scores, and the mean amplitude of low-frequency fluctuation in the right superior temporal gyrus. Higher plasma MIF levels were significantly associated with worse global cognition and information processing speed in CSVD-CI patients. The composite marker (including plasma MIF) distinguished CSVD-CI patients from CSVD-CN and HCs with >80% accuracy. Meta-analysis indicated that blood MIF levels were significantly increased in CSVD-CI patients. In conclusion, plasma MIF is a potential biomarker for early identification of CSVD-CI. Plasma MIF may play a role in cognitive decline in CSVD through BBB dysfunction and changes in white matter hyperintensity and brain activity.

Plasma circRNA HIPK2 as a putative biomarker for the diagnosis and prediction of therapeutic effects in major depressive disorder.

BACKGROUND: Circular RNAs (circRNAs) are a prevalent type of non-coding RNAs exhibiting extensive expression in mammalian cells. Owing to their involvement in diverse pathophysiological mechanisms of major depressive disorder (MDD) and their inherent stability in peripheral blood, circRNAs have emerged as potential biomarkers of considerable significance. This study aimed to identify and validate circular RNA HIPK2 (circHIPK2) in MDD patients and to investigate its potential as a biomarker for the diagnosis and prognosis of MDD. METHODS: Patients with MDD (n = 81) and healthy controls (HCs) (n = 48) were recruited for our study (October 2022 to June 2023). The expression of circHIPK2 in plasma was assessed using absolute quantitative polymerase chain reaction (qPCR). RESULTS: The expression of circHIPK2 in plasma of patients with MDD exhibited a significant increase compared to HCs. The circHIPK2 levels showed an area under the curve (AUC) of 0.796, corresponding to a specificity of 97.9% and a sensitivity of 60.4% in diagnosing MDD. Additionally, the rate of change in circHIPK2 over a 14-day period exhibited an AUC curve of 0.819, indicating its predictive value for antidepressive effects. CONCLUSIONS: CircHIPK2 could serve as a potential biomarker for diagnosing MDD and predicting therapeutic effects of MDD.

Non-inferiority of intermittent theta burst stimulation over the left V1 vs. classical target for depression: A randomized, double-blind trial.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) targeting the visual cortex (VC) has shown antidepressant effects for major depressive disorder (MDD) in sham-controlled trials, but comparisons with rTMS targeting the left dorsolateral prefrontal cortex (DLPFC) are lacking. We aimed to determine the non-inferiority of intermittent theta-burst stimulation (iTBS) over VC vs DLPFC for MDD. METHODS: Participants randomly received navigated iTBS over the left V1 or the left DLPFC twice daily for 14 days with a 3-month follow-up. The primary outcome was change in Hamilton Depression Rating Scale (HAMD-17) score from baseline to treatment end, with 2.5 points as the non-inferiority margin. Secondary outcomes included: improvement in Montgomery-Asberg Depression Rating Scale (MADRS), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA); response and remission rates; suicidal ideation and adverse events. RESULTS: Of 75 randomized patients, 67 completed full treatment, including 52 first-episode patients and 15 relapsers. The primary outcome indicated the non-inferiority of VC (adjusted difference 1.14, lower 97.5 % CI -1.24; p = .002), confirmed by improvements in objective cognitive task and protein levels, as did most secondary outcomes. Reduced suicidal ideation after treatment, incidence of eye discomfort and pain score were lower in the VC group. CONCLUSIONS: Left VC iTBS has the potential to be non-inferior to DLPFC iTBS in most first-episode MDD in improving depressive symptoms and cognitive function, with less suicidal ideation and adverse events. LIMITATIONS: Given the limited sample size, the lack of a sham control and the use of antidepressants, the findings should be interpreted with caution.

Potential Association of Neutrophil Extracellular Traps With Cognitive Impairment in Cerebral Small Vessel Disease.

No acceptable biomarker can facilitate the early identification of cognitive impairment associated with cerebral small vessel disease (CSVD) in the older persons. The neutrophil extracellular traps (NETs) in the inflammation response of circulatory and central systems are essential in destroying the blood-brain barrier. The present study aims to explore the potential associations of plasma NETs with cognitive performance in CSVD. We recruited 146 CSVD patients and 66 healthy controls (HCs), and comprehensive neuropsychological assessments and multimodal magnetic resonance imaging were conducted. Three NETs markers, namely citrullination of histone H3, neutrophil elastase-DNA, and myeloperoxidase (MPO)-DNA, and 4 oxidative stress-related indexes in plasma samples, were measured. The plasma levels of 3 NETs markers were more significantly elevated in CSVD patients than in HCs. Significant correlations of the 3 NETs markers were observed with multiple cognitive domain scores. Furthermore, higher plasma malondialdehyde and NETs levels were significantly associated with the worse Montreal Cognitive Assessment scores among CSVD patients. Moreover, plasma MPO-DNA levels significantly mediated the effect of the amplitude of low-frequency fluctuation value within the bilateral caudate and the scores of global cognitive function, executive function, and information processing speed. Additionally, a panel of 3 NETs markers had the highest area under the curve value to distinguish the cognitively impaired CSVD patients from HCs and nonimpaired ones. Therefore, plasma NETs may be potential biomarkers for early diagnosis of CSVD-related cognitive impairment. Activated lipid peroxidation in circulation and impaired caudate function support potential associations of plasma NETs in cognitively impaired CSVD patients.

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients. Methods: Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing. Results: Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm. Conclusion: The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.

The impact of iron deposition on the fear circuit of the brain in patients with Parkinson's disease and anxiety.

Objective: Anxiety is one of the most common psychiatric symptoms of Parkinson's disease (PD), and brain iron deposition is considered to be one of the pathological mechanisms of PD. The objective of this study was to explore alterations in brain iron deposition in PD patients with anxiety compared to PD patients without anxiety, especially in the fear circuit. Methods: Sixteen PD patients with anxiety, 23 PD patients without anxiety, and 26 healthy elderly controls were enrolled prospectively. All subjects underwent neuropsychological assessments and brain magnetic resonance imaging (MRI) examinations. Voxel-based morphometry (VBM) was used to study morphological brain differences between the groups. Quantitative susceptibility mapping (QSM), an MRI technique capable of quantifying susceptibility changes in brain tissue, was used to compare susceptibility changes in the whole brain among the three groups. The correlations between brain susceptibility changes and anxiety scores quantified using the Hamilton Anxiety Rating Scale (HAMA) were compared and analyzed. Results: PD patients with anxiety had a longer duration of PD and higher HAMA scores than PD patients without anxiety. No morphological brain differences were observed between the groups. In contrast, voxel-based and ROI-based QSM analyses showed that PD patients with anxiety had significantly increased QSM values in the medial prefrontal cortex, anterior cingulate cortex, hippocampus, precuneus, and angular cortex. Furthermore, the QSM values of some of these brain regions were positively correlated with the HAMA scores (medial prefrontal cortex: r = 0.255, p = 0.04; anterior cingulate cortex: r = 0.381, p < 0.01; hippocampus: r = 0.496, p < 0.01). Conclusion: Our findings support the idea that anxiety in PD is associated with iron burden in the brain fear circuit, providing a possible new approach to explaining the potential neural mechanism of anxiety in PD.

Combination of platelet-to-lymphocyte ratio and D-dimer for the identification of cardiogenic cerebral embolism in non-valvular atrial fibrillation.

Background: Non-valvular atrial fibrillation (NVAF) is the most common cause of cardiogenic cerebral embolism (CCE). However, the underlying mechanism between cerebral embolism and NVAF is indefinite, and there is no effective and convenient biomarker to identify potential risk of CCE in patients with NVAF in clinic. The present study aims to identify risk factors for interpreting the potential association of CCE with NVAF and providing valuable biomarkers to predict the risk of CCE for NVAF patients. Methods: 641 NVAF patients diagnosed with CCE and 284 NVAF patients without any history of stroke were recruited in the present study. Clinical data including demographic characteristics, medical history, and clinical assessments, were recorded. Meanwhile, Blood cell counts, lipid profiles, high-sensitivity C-reactive protein, and coagulation function-related indicators were measured. Least absolute shrinkage and selection operator (LASSO) regression analysis was utilized to build a composite indicator model based on the blood risk factors. Results: (1) CCE patients had significantly increased neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio (PLR), and D-dimer levels as compared with patients in the NVAF group, and these three indicators can distinguish CCE patients from ones in the NVAF group with an area under the curve (AUC) value of over 0.750, respectively. (2) Using the LASSO model, a composite indicator, i.e., the risk score, was determined based on PLR and D-dimer and displayed differential power for distinguishing CCE patients from NVAF patients with an AUC value of over 0.934. (3) The risk score was positively correlated with the National Institutes of Health Stroke Scale and CHADS2 scores in CCE patients. (4) There was a significant association between the change value of the risk score and the recurrence time of stroke in initial CCE patients. Conclusions: The PLR and D-dimer represent an aggravated process of inflammation and thrombosis in the occurrence of CCE after NVAF. The combination of these two risk factors can contribute to identifying the risk of CCE for patients with NVAF with an accuracy of 93.4%, and the greater in change of composite indicator, the shorter in the recurrence of CCE for NVAF patients.

Episodic Memory-Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer's Disease: A Multicenter Study Based on Machine Learning.

BACKGROUND: Individualized and reliable biomarkers are crucial for diagnosing Alzheimer's disease (AD). However, lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD. METHODS: Episodic memory-related magnetic resonance imaging (MRI) features of 143 patients with amnesic mild cognitive impairment (MCI) were identified using a multivariate relevance vector regression algorithm. The support vector machine classification model was constructed using these MRI features and verified in 2 independent datasets (N = 994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid, and positron emission tomography images of amyloid-ß plaques. RESULTS: The combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual patients with amnesic MCI (r = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal control subjects with more than 86% accuracy. Furthermore, most identified episodic memory-related regions showed significantly different amyloid-ß positron emission tomography measurements among the AD, MCI, and normal control groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and cerebrospinal fluid pathological biomarkers' levels in the MCI and AD groups. CONCLUSIONS: Neuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.

Machine learning-based characterization of cuprotosis-related biomarkers and immune infiltration in Parkinson's disease.

Background: Parkinson's disease (PD) is a neurodegenerative disease commonly seen in the elderly. On the other hand, cuprotosis is a new copper-dependent type of cell death that can be observed in various diseases. Methods: This study aimed to identify potential novel biomarkers of Parkinson's disease by biomarker analysis and to explore immune cell infiltration during the onset of cuprotosis. Gene expression profiles were retrieved from the GEO database for the GSE8397, GSE7621, GSE20163, and GSE20186 datasets. Three machine learning algorithms: the least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE) were used to screen for signature genes for Parkinson's disease onset and cuprotosis-related genes (CRG). Immune cell infiltration was estimated by ssGSEA, and cuprotosis-related genes associated with immune cells and immune function were examined using spearman correlation analysis. Nomogram was created to validate the accuracy of these cuprotosis-related genes in predicting PD disease progression. Classification of Parkinson's specimens using consensus clustering methods. Result: Three PD datasets from the Gene Expression Omnibus (GEO) database were combined after eliminating batch effects. By ssGSEA, we identified three cuprotosis-related genes ATP7A, SLC31A1, and DBT associated with immune cells or immune function in PD and more accurate for the diagnosis of Parkinson's disease course. Patients could benefit clinically from a characteristic line graph based on these genes. Consistent clustering analysis identified two subtypes, with the C2 subtype exhibiting higher immune cell infiltration and immune function. Conclusion: In conclusion, our study reveals that several newly identified cuprotosis-related genes intervene in the progression of Parkinson's disease through immune cell infiltration.

Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients.

Background: Reliable and individualized biomarkers are crucial for identifying early cognitive impairment in subcortical small-vessel disease (SSVD) patients. Personalized brain age prediction can effectively reflect cognitive impairment. Thus, the present study aimed to investigate the association of brain age with cognitive function in SSVD patients and assess the potential value of brain age in clinical assessment of SSVD. Materials and methods: A prediction model for brain age using the relevance vector regression algorithm was developed using 35 healthy controls. Subsequently, the prediction model was tested using 51 SSVD patients [24 subjective cognitive impairment (SCI) patients and 27 mild cognitive impairment (MCI) patients] to identify brain age-related imaging features. A support vector machine (SVM)-based classification model was constructed to differentiate MCI from SCI patients. The neurobiological basis of brain age-related imaging features was also investigated based on cognitive assessments and oxidative stress biomarkers. Results: The gray matter volume (GMV) imaging features accurately predicted brain age in individual patients with SSVD (R 2 = 0.535, p < 0.001). The GMV features were primarily distributed across the subcortical system (e.g., thalamus) and dorsal attention network. SSVD patients with age acceleration showed significantly poorer Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores. The classification model based on GMV features could accurately distinguish MCI patients from SCI patients (area under the curve = 0.883). The classification outputs of the classification model exhibited significant associations with MoCA scores, Trail Making Tests A and B scores, Stroop Color and Word Test C scores, information processing speed total scores, and plasma levels of total antioxidant capacity in SSVD patients. Conclusion: Brain age can be accurately quantified using GMV imaging data and shows potential clinical value for identifying early cognitive impairment in SSVD patients.

Circular RNA FUNDC1 for Prediction of Acute Phase Outcome and Long-Term Survival of Acute Ischemic Stroke.

Circular RNAs (CircRNAs) have shown promising potential in the diagnosis and the prediction of outcomes of stroke. This study aimed to explore the potential value of circRNAs for identifying acute neurological deterioration and estimating long-term survival for acute ischemic stroke (AIS). One hundred healthy controls and 200 patients with AIS within 72 h were recruited, 140 of whom were admitted within 24 h after onset. CircRNA levels in peripheral blood were measured by quantitative polymerase chain reaction (qPCR). Compared to the controls, the levels of three circRNAs were significantly increased in three subgroups of patients, including large artery atherosclerosis (LAA) stroke, small artery occlusion (SAO) stroke, and cardioembolism (CE) stroke (all P < 0.001). Among, LAA stroke patients had higher levels of circular RNA FUNDC1 (circFUNDC1) compared to SAO stroke patients (P = 0.015). CircFUNDC1 levels were positively correlated with National Institutes of Health Stroke Scale (NIHSS) scores on the 7th day only in LAA patients (P = 0.048, r = 0.226). It should be noted that the levels of circFUNDC1 in patients with early neurological deterioration (END), admitted within 24 h after onset, were significantly higher than those without END (P = 0.013). In addition, circFUNDC1 levels positively correlated with baseline NIHSS scores (P = 0.016, r = 0.203) or the 7th day NIHSS scores (P = 0.001, r = 0.289) in patients within 24 h after onset. Importantly, after 18 months of follow-up, a significant difference was observed on survival Kaplan-Meier curves (P = 0.042) between AIS patients with low (below cut-off) or high circFUNDC1 levels (above cut-off). Circulating circFUNDC1 could be a potential biomarker for predicting acute-phase outcome and long-term survival in AIS.

Platelet-Derived Amyloid-ß Protein Precursor as a Biomarker of Alzheimer's Disease.

BACKGROUND: Platelet proteins may be associated with Alzheimer's disease (AD) pathology. OBJECTIVE: To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. METHODS: We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-ß (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. RESULTS: Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer's continuum (AD). The platelet amyloid-ß protein precursor (AßPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-ß42 level, which could affect MMSE scores through CSF amyloid-ß42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AßPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. CONCLUSION: Our study was the first to find an association between platelet AßPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.

Selective activation of ABCA1/ApoA1 signaling in the V1 by magnetoelectric stimulation ameliorates depression via regulation of synaptic plasticity.

Emerging evidence suggests that dysfunction of the visual cortex may be involved in major depressive disorder (MDD). However, the underlying mechanisms remain unclear. We previously established that combined magnetic stimulation system treatment (c-MSST) resulted in an antidepressant effect in mice. In the present study, we found that V1-targeted c-MSST induced significant antidepressant effects in chronic unpredictable mild stress (CUMS)- and lipopolysaccharide (LPS)-treated mice. Proteomic screening investigation and repeatable validation revealed that expression of the V1 neuronal ATP-binding cassette transporter A1 (ABCA1) and apolipoprotein A-1 (ApoA1) was downregulated in CUMS mice, an effect that was normalized by c-MSST. Neuron-specific knockdown of ABCA1 in V1 blocked c-MSST's antidepressant effects. Mechanistically, CUMS reduced dendritic spine density and long-term plasticity in V1, and these deficits were reversed by c-MSST. V1-targeted c-MSST was found to induce rapid antidepressant effects that are mediated by alterations in synaptic plasticity via the ABCA1/ApoA1 signaling pathway in V1.

Effects of standard treatments on depressive/anxiety symptoms in patients with inflammatory bowel disease: A systematic review and meta-analysis.

OBJECTIVE: A combination of inflammatory bowel disease (IBD) and psychological comorbidities can influence the natural course of IBD. A systematic review and meta-analysis was performed to examine whether a standard IBD medical therapy without any antipsychotic intervention has beneficial effects on depression/anxiety in IBD patients. METHODS: PubMed and Web of Science databases were systematically searched for related literature from their inception to March 2020. The random-effects model was used to calculate the standardized mean difference (SMD). A total of 16 eligible studies were included in the present meta-analysis. RESULTS: Compared with baseline assessments, IBD patients with standard IBD medication had significantly reduced depression assessment scores (pooled SMD = 0.500; 95% confidence interval: 0.207, 0.793; P = 0.001). These results were obtained without any psychological interventions. Additionally, no significant differences in anxiety-related scores were detected between the baseline assessments and the end of therapy assessments (pooled SMD = 0.083; 95% confidence interval: -0.120, 0.285; P = 0.425). The meta-regression and subgroup analyses revealed that differences in assessment tools and medications might be the main source of heterogeneity. CONCLUSION: Standard IBD treatments can significantly alleviate the depressive symptoms in IBD patients. However, more studies are needed to analyze this association.

Altered task modulation of global signal topography in the default-mode network of unmedicated major depressive disorder.

BACKGROUND: Altered global signal (GS) topography features in the resting-state fMRI of major depressive disorder (MDD), showing abnormally strong global signal representation in the default-mode network (DMN). Whether the abnormal local to global change also shapes activity during task states, and how it relates to psychopathological symptoms, e.g., abnormally slow time speed of motor, cognitive, and affective symptoms, remains unknown. METHODS: We investigated fMRI-based GS with its topographical representation during task states in unmedicated 51 MDD subjects and 28 healthy subjects. Task-related global signal correlation (GSCORR) was probed by a novel paradigm testing the processing of negative/neutral emotions during different time speeds, i.e., slow and fast. RESULTS: We observed a significant interaction between time speed and emotion of GSCORR in various DMN regions in healthy subjects. Next, we showed that MDD exhibits reduced task-related GSCORR in various DMN regions during specifically the fast processing of negative emotions. Finally, we demonstrated that GSCORR in DMN and other brain regions (motor-related regions, inferior frontal cortex) correlated with the degree of psychomotor retardation especially during the fast emotional stimuli. LIMITATIONS: The measurement of interoceptive variables like respiration rate or heart rate were not included in our fMRI acquisition. CONCLUSION: Together, we demonstrated the functional relevance of GS topography by showing reduced GSCORR in DMN during specifically the fast processing of negative emotions in MDD, suggesting the abnormal slowness, i.e., reduced time speed, to be a key feature of both brain and symptoms in MDD.

The effect of Alzheimer's disease risk factors on brain aging in normal Chineses: Cognitive aging and cognitive reserve.

Aging has been recognized as a major driving force of the Alzheimer's disease's (AD) progression, however, the relationship between brain aging and AD is still unclear. There is also a lack of studies investigating the influence of AD risk factors on brain aging in cognitively normal people. Here, the "Brain Age Gap Estimation" (BrainAGE) framework was applied to investigate the effects of AD risk factors on individual brain aging. Across a total of 165 cognitively normal elderly subjects, although no significant difference was observed in the BrainAGE scores among the three groups, AD risk dose (i.e., the number of AD risk factors) is tend to associated with an increased BrainAGE scores (high-risk > middle risk > low risk). Female exhibited more advanced brain aging (P = 0.004), and higher education years were associated with preserved brain aging (P < 0.001). APOE-ɛ4 (P = 0.846) and family history (FH) of dementia (P = 0.209) did not increase BrainAGE scores. When comparing 52 aMCI patients with 38 cognitively normal controls from ADNI dataset, aMCI patients showed significantly increased BrainAGE scores. BrainAGE scores were negatively correlated with CSF Aß42 levels in the aMCI group (r = -0.275, P = 0.048). With an accuracy of 68.9%, BrainAGE outperformed APOE-ɛ4 and hippocampus gray matter volume (GMV) in predicting aMCI. In conclusion, AD is independently associated with structural changes in the brain that reflect advanced aging. Potentially, BrainAGE combined with APOE-ɛ4 and hippocampus GMV could be used as a pre-screening tool in early-stage AD.

Potential of Antithrombin III as a Biomarker of Antidepressive Effect in Major Depressive Disorder.

Background: The evaluation of treatment response to antidepressant therapy commonly depends on neuropsychologic assessments, as there are currently no suitable biomarkers. Previous research has identified a panel of increased proteins in patients with major depressive disorder (MDD), including antithrombin III (ATIII), as potential biomarkers of depression. Methods: A total of 90 MDD patients were recruited. Of these, 74 patients received occipital repetitive transcranial magnetic stimulation (rTMS) as individualized, standard, or sham treatment for 5 days, and underwent the complete procedure, including clinical assessments, blood collection, and protein measurement. Results: After treatment, ATIII was significantly decreased in both the individualized and standard groups (both p < 0.001) relative to the sham group. In the individualized group, reduction in ATIII was associated with improvements in several neuropsychological assessments. Furthermore, ATIII at baseline in the standard group and after individualized rTMS showed good performance for evaluating or predicting the response to five-day treatment (AUC = 0.771, 95% CI, 0.571-0.971; AUC = 0.875, 95% CI, 0.714-1.000, respectively) and remission at follow-up (AUC = 0.736, 95% CI, 0.529-0.943; AUC = 0.828, 95% CI, 0.656-1.000, respectively). Lastly, both baseline ATIII and change in ATIII showed good predictive value for the 24-item Hamilton Depression Rating Scale at follow-up (p = 0.024 and 0.023, respectively). Conclusion: Our study revealed a reduction in ATIII after occipital rTMS in MDD patients and a relationship between change in ATIII and therapeutic response. Taken together, these findings provide evidence for the potential of ATIII as a biomarker for the evaluation and prediction of antidepressive effects.

Non-coding RNAs in depression: Promising diagnostic and therapeutic biomarkers.

Non-coding RNAs (ncRNAs), including microRNAs, circular RNAs, and long non-coding RNAs, are important regulators of normal biological processes and their abnormal expression may be involved in the pathogenesis of human diseases including depression. Multiple studies have demonstrated a significantly increased or reduced ncRNAs expression in depressed patients compared with healthy subjects and that antidepressant therapy can alter the aberrant expression of ncRNAs in depressed patients. Although the existing evidence is important, it is also mixed and a comprehensive review to guide an effective clinical translation is lacking. Focused on human research, this review summarizes clinical findings of ncRNAs in depression, including those in brain tissues and peripheral samples. We outlined the characteristics and functions of ncRNAs and highlighted their performance in the diagnosis and treatment of depression. Although their precise roles in depression remain uncertain, ncRNAs have shown potential value as biomarkers for diagnosis and therapy in depressed patients.

CRISPR-Cas12-Based Rapid Authentication of Halal Food.

The halal food market is globally growing along with the increased risk of adulteration. We proposed an amplification-free and mix-to-read CRISPR-Cas12-based nucleic acid analytical strategy allowing rapid identification and analysis of pork components, thus enriching the toolbox for ensuring halal food authenticity. We designed and optimized guide RNA (gRNA) targeting the pork cytochrome b (Cyt b) gene. gRNA allowed specific identification of the target Cyt b gene from pork components followed by activation of Cas12 protein to abundantly cleave single-stranded DNA probes with terminally labeled fluorophore and quencher groups, thus turning on fluorescence. The presence of the pork Cyt b gene thus can be mix-and-read- and only-one-step-detected, which may indicate the risk of halal food adulteration. The method allowed specific discrimination of pork meat from beef, mutton, and chicken and yielded a detection limit of 2.7 ng/µL of total DNA from pork meat. The reliability of the method was tested using the following processed meat products: halal foods beef luncheon meat and spiced beef and non-halal foods sausage and dried pork slices. The CRISPR-Cas12-based nucleic acid test strategy is promising for rapid food authentication.